Non-destructive method for assessing nitrogen fixation status in legume plants

Abstract

Non-destructive methods for assessing nitrogen fixation status in legume plants are disclosed. Also disclosed are methods of determining a nitrogen threshold for a legume plant, reporter plants, systems and methods for rapid, field-deployable monitoring of nitrogen fixation, for optimizing fertilizer use, and for supporting breeding programs aimed at improved symbiotic efficiency.

Description

PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webNON-DESTRUCTIVE METHOD FOR ASSESSING NITROGEN FIXATION STATUS IN LEGUME PLANTSGOVERNMENTAL RIGHTS

[0001] This invention was made with government support under Award #2021 -67034-35144 awarded by U.S. Department of Agriculture - National Institute of Food and Agriculture - Agriculture and Food Research Initiative. The government has certain rights in the invention.CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority from Provisional Application number 63 / 689,341 , filed August 30, 2024, the entire contents of which are hereby incorporated by reference.INCORPORATION OF SEQUENCE LISTING

[0003] The present application contains a Sequence Listing that has been submitted in .XML format via Patentcenter and is hereby incorporated herein by reference in its entirety. Said .XMI was created on 2 September, 2025, is named DDPSC0172-401 -PCT, and is 14 kilobytes in size.FIELD OF THE INVENTION

[0004] The present disclosure relates to methods, compositions, and tools for the evaluation, monitoring, and analysis of nitrogen fixation in legumes.BACKGROUND OF THE INVENTION

[0005] In agricultural systems, legumes play a central role in sustainable nitrogen management by forming symbiotic associations with soil bacteria that fix atmospheric nitrogen into plant- available forms. Soybean (Glycine max), a globally important grain and oilseed crop, derives a significant portion of its nitrogen requirements from symbiotic nitrogen fixation within root nodules. These nodules house nitrogenase-containing bacteroids, which convert N2to ammonia using energy derived from plant-supplied carbohydrates. Because nitrogen fixation isPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web energy intensive, requiring substantial photosynthate allocation to the root system, plants carefully balance nodule activity and symbiotic nitrogen fixation with the uptake of externally supplied nitrogen fertilizer. At low to moderate levels, added nitrogen fertilizer can stimulate plant growth and even support nodule development; however, as external nitrogen levels increase beyond a certain nitrogen threshold, plants preferentially utilize the readily available soil nitrogen, leading to a suppression of nodule activity and biological nitrogen fixation. As a result, a reliable assessment of nitrogen fixation status is essential for optimizing fertilizer inputs, maximizing yield, and preserving soil fertility, yet existing measurement techniques present practical challenges.

[0006] Traditional methods for quantifying nodule nitrogenase activity include the acetylene reduction assay (ARA),15N isotope dilution, and gas-exchange monitoring. Although these approaches are widely used in research settings, they typically require destructive sampling of roots and nodules, specialized equipment (e.g., gas chromatographs, isotope ratio mass spectrometers), and complex sample handling that limits throughput. They often involve incubating entire root systems under controlled atmospheres or injecting tracers into nodules, procedures that are invasive, laborious, time-consuming, and ill-suited to rapid field-scale monitoring. As a result, growers and plant breeders lack a convenient, noninvasive means to gauge symbiotic nitrogen fixation in standing crops, leading to either under- or over-application of synthetic fertilizers with attendant environmental and economic costs.

[0007] Molecular assays have emerged as an alternative for probing symbiotic status by measuring expression levels of nodule-specific genes or reporter constructs. Techniques such as quantitative PCR or reporter enzyme activity can indicate the presence of nodulation or early nodule development. However, these assays generally depend on harvesting root tissue or engineered transgenic lines, and they often require laboratory infrastructure and trained personnel. While efforts to identify leaf-based markers correlated with nodule function have shown promise, no robust field-deployable test has yet been established. Thus, practitioners continue to rely on indirect indicators, such as visual nodule counts or general crop vigor, which do not accurately reflect current nitrogen fixation rates.

[0008] Accordingly, there remains a need for a streamlined, non-destructive method to assess nitrogen fixation status in legumes during the growing season. Such a method would ideallyPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web utilize aboveground samples, leaves or sap, to infer nodule activity, thereby avoiding root excavation.SUMMARY OF THE INVENTION

[0009] One aspect of the instant disclosure encompasses a non-destructive method for assessing nitrogen fixation status in legume plants. The method comprises calculating a gene expression ratio (GER) for at least one polynucleotide pair selected from the polynucleotide pairs identified in Table B, wherein the GER is a ratio of an expression level of a first polynucleotide of the pair to an expression level of a second polynucleotide of the pair, in a leaf tissue sample. The method further comprises comparing the calculated GER for the polynucleotide pair to a corresponding maximum or minimum nitrogen fixation threshold GER (GERNFT) predetermined for said pair of polynucleotides, wherein a maximum GERNFT represents a maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal, and a calculated GER of a polynucleotide pair equal to or below the maximum GERNFT indicates suppressed nitrogen fixation; or a minimum GERNFT represents a minimum GER value above which nitrogen fixation is optimal and below which nitrogen fixation is suppressed, and a calculated GER of a polynucleotide pair equal to or above the minimum GERNFT indicates optimal nitrogen fixation. The maximum or minimum GERNFT of each polynucleotide pair correlates GER values with measured nitrogen fixation activity in plants. The expression level can be the expression level of the polynucleotide, the expression level of a protein encoded by the polynucleotide, the expression level of a reporter under the regulatory control of the polynucleotide, or any combination thereof.

[0010] In some aspects, the calculated GER for the polynucleotide pair is compared to a corresponding maximum GERNFT, wherein a maximum GERNFT represents a maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal.

[0011] In some aspects, the method further comprises predetermining the maximum or minimum GERNFT of a polynucleotide pair by growing legume plants under low external nitrogen conditions that support optimal nitrogen fixation, and under external nitrogenPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web conditions that suppress nitrogen fixation; determining expression levels of each polynucleotide of a polynucleotide pair in leaf samples obtained from the plants after nitrogen fertilizer treatment; measuring nitrogen fixation activity in root samples of the plants; calculating a GER in the leaf tissue samples from plants grown under each growth condition; and identifying the maximum GERNFT for the polynucleotide pair as the maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal, or identifying the minimum GERNFT for the polynucleotide pair as the minimum GER value above which nitrogen fixation is optimal and below which nitrogen fixation is suppressed. In some aspects, the plants are grown under a range of external nitrogen concentrations ranging from concentrations that suppress nitrogen fixation to concentrations that allow optimal nitrogen fixation, and the maximum or minimum GERNFT is determined from the range of GERs corresponding to the transition between suppressed and optimal nitrogen fixation. In some aspects, the external nitrogen conditions comprise the application of nitrogen fertilizer. In some aspects, the low external nitrogen conditions that support optimal nitrogen fixation comprise about 0.5 mM available nitrogen. In some aspects, the external nitrogen conditions that suppress nitrogen fixation comprise about 100 mM available nitrogen.

[0012] In some aspects, nitrogen fixation is assessed at the stage of nodule development when nodules are fully formed and actively fixing nitrogen. The method can be applied to legume plants comprising indeterminate or determinate nodules. In some aspects, the nitrogen fixation status is assessed at the stage of determinate nodule development when nodules are fully formed and actively fixing nitrogen, and GERs are calculated at 4-6 weeks post inoculation (wpi) at 0, 2, and 4 days post treatment (dpt) with nitrogen fertilizer. In some aspects, the maximum and minimum GERNFT for the pairs of polynucleotides is as shown in Table B. Suppressed nitrogen fixation levels can be due to stress conditions selected from high levels of nitrogen, drought, salinity, heat, cold, pathogen infection, or nutrient deficiency. The tissue sample can be a punch biopsy, excised leaflet, or sap extract. The GER can be calculated using expression levels measured by protein abundance, mRNA transcript abundance, or a reporter gene product. The expression level can be determined by quantitative PCR (qPCR), digital PCR, microarray, RNA sequencing, ELISA, a colorimetric, fluorometric, or chemiluminescent assay, or a reporter gene assay. In some aspects, the expression level is anPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webRNAseq-derived metric, such as an average Fragments Per Kilobase of transcript per Million mapped reads (FPKM) value. The method can be applied to legume plants such as soybean, alfalfa, clover, lentil, pea, or vetch, and in some aspects, specifically to soybean. In some aspects, the nitrogen fixation status is assessed during the vegetative growth stage of the soybean plant, coinciding with peak nodule activity and optimal nitrogen fixation efficiency, and at around 5 to 6 weeks post-inoculation. Each polynucleotide of the polynucleotide pairs can comprise a soybean gene identified in Table B, or a variant, allele, fragment, or synthetic form thereof. The GERNFT for the pairs of polynucleotides can be as shown in Table B. One or more of the polynucleotides can comprise an endogenous gene, an exogenous gene, or any combination thereof.

[0013] One aspect of the instant disclosure encompasses a non-destructive method for assessing nitrogen fixation status in legume plants by measuring the expression level in a leaf tissue sample of any combination of one or more polynucleotides identified in Table A, wherein the GR3.4, the bHLH13, the a / b hydrolase, and the SOS3-4 polynucleotides are predetermined to be downregulated and the GdAS1-1 , the GdAS1 -2, the MtN21 , the cP450, and the HIRD11 -like polynucleotides are predetermined to be upregulated in plants grown under conditions that suppress nitrogen fixation. The method further comprises determining that the plant has suppressed nitrogen fixation when the expression level of any one or more of the downregulated polynucleotides is equal to or below a predetermined untreated threshold expression level for the respective polynucleotide, the expression level of any one or more of the upregulated polynucleotides is equal to or above a predetermined untreated threshold expression level for the respective polynucleotide, or any combination of one or more downregulated or upregulated polynucleotide; or determining that the plant has optimal nitrogen fixation when the expression level of any one or more of the downregulated polynucleotides is equal to or above a predetermined treated threshold expression level for the respective polynucleotide, or the expression level of any one or more of the upregulated polynucleotides is equal to or below a predetermined treated threshold expression level for the respective polynucleotide, or any combination of one or more downregulated or upregulated polynucleotide. The untreated threshold expression level is determined based on expression of the polynucleotide in plants grown under conditions supporting optimal nitrogen fixation, andPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web the treated threshold expression level is determined based on expression of the polynucleotide in plants grown under conditions that suppress nitrogen fixation. The expression level can be the expression level of the polynucleotide, the expression level of a protein encoded by the polynucleotide, the expression level of a reporter under the regulatory control of the polynucleotide, or any combination thereof.

[0014] In some aspects, the method further comprises predetermining the threshold expression levels of a polynucleotide by growing legume plants under conditions supporting optimal nitrogen fixation to determine an untreated threshold expression level of a polynucleotide, growing legume plants under conditions that suppress nitrogen fixation to determine a treated threshold expression level of a polynucleotide, or both; determining expression levels of the polynucleotide in leaf samples of the plants; measuring nitrogen fixation activity in root samples of the plants; and setting the untreated threshold expression level for a downregulated polynucleotide as the expression level of the polynucleotide in a plant grown under conditions supporting optimal nitrogen fixation below which nitrogen fixation is suppressed, and for an upregulated polynucleotide as the expression level of the polynucleotide in a plant grown under conditions supporting optimal nitrogen fixation above which nitrogen fixation is suppressed, based on comparison to nitrogen fixation activity in the plants; setting the treated threshold expression level for a downregulated polynucleotide as the expression level measured under conditions that suppress nitrogen fixation above which nitrogen fixation is suppressed, and for an upregulated polynucleotide as the expression level measured under conditions that suppress nitrogen fixation below which nitrogen fixation is suppressed, based on comparison to nitrogen fixation activity in the plants; or both. In some aspects, the untreated and treated threshold expression level for each polynucleotide is as shown in Table A. The legume plant can be soybean, and each polynucleotide can comprise a soybean gene identified in Table A, or a variant, allele, fragment, or synthetic form thereof.

[0015] One aspect of the instant disclosure encompasses a genetically modified reporter plant or a part, plant cell, or seed thereof for reporting nitrogen fixation status in a legume plant. The genetically modified plant can comprise a reporter construct comprising a reporter under the regulatory control of a polynucleotide listed in Table A; a pair of reporter constructs comprising a first reporter construct comprising a first reporter under the regulatory control of a firstPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web polynucleotide and a second reporter construct comprising a second reporter under the regulatory control of a second polynucleotide, wherein the first and second polynucleotides are selected from the polynucleotide pairs identified in Table B; or any combination of the expression constructs of (a) the pair of expression constructs of (b), or both. Differential expression of the reporter construct, the pair of reporter constructs, or a GER calculated from expression levels of the pair of reporter constructs indicates the nitrogen fixation status of the plant. In some aspects, the reporter under the regulatory control of a polynucleotide is the polynucleotide itself, such that the endogenous gene functions as the reporter when introduced into a different organism, or a detectable reporter operably linked to one or more regulatory elements of the polynucleotide, including a promoter, enhancer, 5' or 3' untranslated region, or other cis-regulatory sequence, such that reporter expression reflects the regulatory activity of the polynucleotide. The reporter can be selected from the group consisting of [3-glucuronidase (GUS), green fluorescent protein (GFP), yellow fluorescent protein (YFP), red fluorescent protein (RFP), luciferase (LUC), alkaline phosphatase, and chloramphenicol acetyltransferase (CAT). The reporter gene expression can be detectable by fluorescence microscopy, luminescence imaging, or colorimetric assay, and can be quantifiable in a non-destructive assay.One aspect of the instant disclosure encompasses a method of determining a nitrogen threshold for a legume plant. The method comprises growing legume plants under untreated conditions and under a range of increasing nitrogen fertilizer concentrations; determining expression levels of polynucleotides of Table A or any combination thereof; calculating a GER using expression levels of pairs of polynucleotides of Table B in plants grown under each growth condition; and identifying the nitrogen threshold as the lowest nitrogen fertilizer concentration at which the GER indicates a significant reduction in nitrogen fixation status compared to untreated controls.

[0016]

[0017] One aspect of the instant disclosure encompasses a method for selecting legume plants for breeding, guiding nitrogen fertilizer application, or monitoring field-level nitrogen fixation status. The method comprises determining a nitrogen threshold for a legume plant according to the method of claim 41 ; and selecting plants for breeding that maintain optimal nitrogenPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web fixation status at higher external nitrogen concentrations relative to other plants in the population, as determined by the nitrogen threshold.

[0018] One aspect of the instant disclosure encompasses a kit for assessing nitrogen fixation status in a legume plant. The kit can comprise one or more reagents for detecting the expression level of a polynucleotide of Table A or a pair of polynucleotides of Table B; one or more genetically modified reporter plant or a part, plant cell, or seed thereof for reporting nitrogen fixation status in a legume plant; instructions for calculating a gene expression ratio (GER) and comparing the GER to a predetermined minimum or maximum GERNFT; or any combination of the above.

[0019] BRIEF DESCRIPTION OF THE FIGURES

[0020] The following drawings form part of the present specification and are included to further demonstrate certain embodiments of the present disclosure. Certain embodiments can be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

[0021] FIG. 1 B. Nitrogenase activity is not contingent upon both nodule number and nodule mass. Plot showing nitrogenase activity measured in soybean (Glycine max cv. W82) wholeroot systems.

[0022] FIG. 1C. Nitrogenase activity is not contingent upon both nodule number and nodule mass. Plot showing fresh weight of collected nodules, measured 3-hours post ARA and used in the calculation of nitrogenase activity.

[0023] FIG. 1 D. Nitrogenase activity is not contingent upon both nodule number and nodule mass. Plot showing total number of nodules per plant. Data collected spans 4 to 7 weeks post inoculation with Bradyrhizobium diazoefficiens USDA110. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0024] FIG. 2A. Shoot and root mass was measured prior to Acetylene Reduction Assay (ARA). Fresh weight of shoot of soybean plants used in the ARA. Data collected spans 5 to 7 weeks post inoculation with Bradyrhizobium USDA110. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).

[0025] FIG. 2B. Shoot and root mass was measured prior to Acetylene Reduction Assay (ARA). Fresh weight of root of soybean plants used in the ARA. Data collected spans 5 to 7 weeks post inoculation with Bradyrhizobium USDA110. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).

[0026] FIG. 3A. Comprehensive Primer Design and 5’ Bias in Expression of Bradyrhizobium nifH gene in Soybean Nodules. Diagram illustrating the four primer sets designed to span the Bradyrhizobium nifH transcript from the 5’ to the 3’ end. These primer sets were developed to measure the expression levels of the nifH gene in soybean nodules. The specific regions targeted by each primer set are indicated along the length of the nifH transcript. This design ensures comprehensive coverage for accurate measurement of gene expression levels across different sections of the RNA transcript.

[0027] FIG. 3B. Comprehensive Primer Design and 5’ Bias in Expression of Bradyrhizobium nifH gene in Soybean Nodules. Quantitative PCR (qPCR) results showing the expression levels of the Bradyrhizobium nifH gene in soybean nodules from 2 wpi to 9 wpi. Four primer sets, spanning the nifH transcript from the 5’ to 3’ end, were used to measure transcript levels. The figure displays the relative expression of nifH across different stages of nodule development, capturing the dynamic changes in gene expression from young to mature nodules. Endogenous gene control: Bradyrhizobium 16S

[0028] FIG.4A. Bradyrhizobium nifH gene expression and corresponding NifH protein gradually accumulate in nodules throughout root nodule symbiosis. Expression levels of the Bradyrhizobium nifH gene in soybean nodules aged 2 to 10 wpi. Relative nifH expression is shown on the Y-axis using Bradyrhizobium 16S as an endogenous control gene.

[0029] FIG.4B. Bradyrhizobium nifH gene expression and corresponding NifH protein gradually accumulate in nodules throughout root nodule symbiosis. Corresponding NifH protein levels in nodules collected from the same plants used for nifH expression analysis.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0030] FIG.4C. Bradyrhizobium nifH gene expression and corresponding NifH protein gradually accumulate in nodules throughout root nodule symbiosis. Western blot analysis showing NifH protein accumulation from (top) 2 to 6 wpi and (bottom) 6 to 10 wpi. G.max ACTIN protein was used as an endogenous loading control. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 )

[0031] FIG. 5A. Leghemoglobin (LBA) protein exhibits a low-to-high-to-low accumulation pattern in nodules. LBA protein levels in nodules from 2 to 10 weeks post inoculation (wpi). LBA protein is transcribed by LEGHEMOGLOBIN 3 (Lb3) -Glyma.10G199100)

[0032] FIG. 5B. Leghemoglobin (LBA) protein exhibits a low-to-high-to-low accumulation pattern in nodules. Western blot analysis showing LBA protein accumulation from nodules aged (top) 2 to 6 wpi and (bottom) 6 to 10 wpi with Bradyrhizobium USDA110. ACTIN protein was used as an endogenous loading control. Protein used for both LBA and NifH analyses was from the same nodule samples. Additionally, (See FIGs. 4A and 4B) primary antibodies for both proteins were run on the same gel, using different channels. This was possible because LBA (16 kDa MW) and NifH (32 kDa MW) antibodies have different hosts and molecular weights. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 )

[0033] FIG. 6. Dual RNA Sequencing Captures Soybean and Bradyrhizobium Transcripts. The y-axis shows the mapping percentages of each RNA sequencing library, which are represented on the x-axis. Reads mapping the plant genome are shown in teal, while reads mapping to the Bradyrhizobium genome are shown in purple.

[0034] FIG. 7A. Temporal Distribution of Differentially Expressed Genes in Soybean Nodules during Root Nodule Symbiosis. Utilizing DEseq2, the Gene expression dynamics of soybean and Bradyrhizobium was examined, comparing each week against its preceding one. Tables depict the counts of soybean-specific (top) and Bradyrhizobium (bottom) DE genes, categorized by comparison (nwpi vs. n-1wpi) and further distinguished by up- or downregulation.

[0035] FIG. 7B. Temporal Distribution of Differentially Expressed Genes in Soybean Nodules during Root Nodule Symbiosis. Utilizing DEseq2, the Gene expression dynamics of soybean and Bradyrhizobium was examined, comparing each week against its preceding one. StackedPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web barplots visually represent the distribution of DE genes in soybean (left) and Bradyrhizobium (right), with up-regulated genes in red and down-regulated genes in blue.

[0036] FIG. 8A. Gene Differential Expression in Nodules is Stage-Specific for both Soybean and Bradyrhizobium. Upset plot showing the common and specific genes differentially expressed in each week-to-week comparison, for Soybean.

[0037] FIG. 8B. Gene Differential Expression in Nodules is Stage-Specific for both Soybean and Bradyrhizobium. Bradyrhizobium USDA110. The bottom left shows the size of each set as a horizontal histogram, the bottom right shows the intersection matrix and the upper right shows the size of each combination as a vertical histogram.

[0038] FIG. 9A. Dynamic Gene Expression Patterns in Soybean Nodules Across Eight Weekly Comparisons Revealed by GO Analysis. Differentially expressed (DE) upregulated Glycine max genes associated with Biological Processes pathways using ShinyGO (V0.80), are shown in the figure above, scaled by the Iog2 of their Fold Enrichment. The analysis includes gene expression data collected from soybean nodules at weekly intervals from 2 to 10 weeks post inoculation (wpi). Pathways were identified and categorized using Gene Ontology (GO) analysis, highlighting key processes such as sucrose metabolic processes, asparagine biosynthesis, sulfate transport, and oxidation-reduction processes during symbiotic nitrogen fixation.

[0039] FIG. 9B. Dynamic Gene Expression Patterns in Soybean Nodules Across Eight Weekly Comparisons Revealed by GO Analysis. Differentially expressed (DE) upregulated Glycine max genes associated with Biological Processes pathways using ShinyGO (V0.80), are shown in the figure above, scaled by the Iog2 of their Fold Enrichment. The analysis includes gene expression data collected from soybean nodules at weekly intervals from 2 to 10 weeks post inoculation (wpi). Pathways were identified and categorized using Gene Ontology (GO) analysis, highlighting key processes such as sucrose metabolic processes, asparagine biosynthesis, sulfate transport, and oxidation-reduction processes during symbiotic nitrogen fixation.

[0040] FIG. 10A. Gene expression clusters reveal a tightly regulated transcriptional network involved in each step of nodule development. The WGCNA software is used for the hierarchical clustering of gene expression. Nodule age is represented on the x-axis by weeksPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web post-inoculation (wpi), including three biological replicates. The y-axis displays the clusters, which range from ME1 to ME10. The colors signify the relative gene levels, with high accumulation in red shades and low accumulation in blue shades. The dendrogram on the left side indicates the similarity between clusters.

[0041] FIG. 10B. Gene expression clusters reveal a tightly regulated transcriptional network involved in each step of nodule development. Soybean GO analysis WGCNA SoyBase revealed the presence of genes associated with different biological processes GO categories in each of the WGCNA clusters. Black indicates the GO category is present in the individual ME cluster, while white indicates absence.

[0042] FIG. 11. Key Biomarkers and Regulators of Nitrogen Fixation Dynamics. Heatmap A shows RNAseq-derived FPKM values for all genes with a 2-up-5-down-10 temporal expression pattern (n=315). Heat maps B, C and D are three subsets of heatmap A, and grouped based on average FPKM expression. The three groups contain genes whose average FPKM values is (B-D) (i) 1 to 10 (n=111 genes), (ii) 100 to 1000 (n=152 genes), or (iii) greater than 1000 (n=52 genes). Each heatmap displays average FPKM values of listed genes from 2 to 10 weeks post inoculation (wpi). Expression was sorted by row. To the immediate left of the heat map is a column showing expression density, accompanied by a dendrogram clustering based on FPKM expression levels. Color Key: light yellow indicates low RPM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average RPM values (highest gene expression).

[0043] FIG. 12A. The pattern of host Leghemoglobin gene accumulation is similar in nodules but at different levels. RNAseq-derived FPKM values for the five symbiotic Gmax. Leghemoglobin (Lb) genes (Lb1-Lb5) and non-symbiotic hemoglobin-2 (Hb2) are shown in barplots. Data collected spans 2 to 10 weeks post inoculation with Bradyrhizobium diazoefficiens USDA110.

[0044] FIG. 12 B. The pattern of host Leghemoglobin gene accumulation is similar in nodules but at different levels. A heatmap of average FPKM values. To the immediate left of the heat map is a column showing expression density, accompanied by a dendrogram clustering based on FPKM expression levels. Color Key: light yellow indicates low RPM values (lowest genePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web expression), orange for moderate levels of gene expression, and dark red for high average RPM values (highest gene expression).

[0045] FIG. 13A. Distinct Expression Patterns of Highly Expressed Argonaute Genes throughout Symbiosis. RNAseq-derived FPKM values for the eight highly expressed soybean AGO genes, each with average FPKM values (>100) across the observation period, are displayed in a heat map, sorted by row. To the immediate left of the heat map is a column showing expression density, accompanied by a dendrogram clustering based on FPKM expression levels. Color Key: light yellow indicates low RPM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average RPM values (highest gene expression). The data were collected from soybean nodules 2 to 10 wpi with Bradyrhizobium diazoefficiens USDA110.

[0046] FIG. 13B. Distinct Expression Patterns of Highly Expressed Argonaute Genes throughout Symbiosis. Individual bar plots for FPKM values of AG05 (Glyma.11 G190900) and AG02 (Glyma.20G022900) illustrate their temporal expression patterns. The data were collected from soybean nodules 2 to 10 wpi with Bradyrhizobium diazoefficiens LISDA110.

[0047] FIG. 14A. Progressive Enrichment and Dominance of Dicer-Like-3 (DCL3) and DCL1 Transcripts during Nodule Development. RNAseq-derived FPKM values for the eight highly expressed soybean DCL genes, each with average FPKM values (>50) across the observation period, are displayed in a heat map, sorted by row. To the immediate left of the heat map is a column showing expression density, accompanied by a dendrogram clustering based on FPKM expression levels. Color Key: light yellow indicates low RPM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average RPM values (highest gene expression). The data were collected from soybean nodules 2 to 10 wpi with Bradyrhizobium diazoefficiens USDA110.

[0048] FIG. 14B. Progressive Enrichment and Dominance of Dicer-Like-3 (DCL3) and DCL1 Transcripts during Nodule Development. A bar plot, grouping values of DCL average FPKM by week. The data were collected from soybean nodules 2 to 10 wpi with Bradyrhizobium diazoefficiens USDA110.

[0049] FIG. 15A. Young and Mature Nodules are Enriched with Low to Moderately Expressed Defense-Related Genes. Heat maps displaying RNAseq-derived FPKM values for allPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web expressed soybean defense-related genes (n=265). Lowly expressed defense-related genes with average FPKM values of 1 to 100 (n=233) across the observation period. Genes are sorted by row. The column to the immediate left of the heat maps indicates expression density and includes a dendrogram showing clustering based on FPKM expression levels. Color Key: light yellow indicates low average FPKM values lowest gene expression), orange indicates moderate levels of gene expression, and dark red signifies the high average FPKM values (highest gene expression). Data were collected from soybean nodules 2 to 10 wpi with Bradyrhizobium diazoefficiens USDA110.

[0050] FIG. 15B. Young and Mature Nodules are Enriched with Low to Moderately Expressed Defense-Related Genes. Heat maps displaying RNAseq-derived FPKM values for all expressed soybean defense-related genes (n=265). moderately expressed defense-related genes with average FPKM values greater than 100 (n=32) across the observation period. Genes are sorted by row. The column to the immediate left of the heat maps indicates expression density and includes a dendrogram showing clustering based on FPKM expression levels. Color Key: light yellow indicates low average FPKM values lowest gene expression), orange indicates moderate levels of gene expression, and dark red signifies the high average FPKM values (highest gene expression). Data were collected from soybean nodules 2 to 10 wpi with Bradyrhizobium diazoefficiens USDA110.

[0051] FIG. 16A. Highly Expressed Symbiotic-Related Genes implicated in nitrogen fixation based on expression in nodules throughout Development. Heat maps displaying RNAseq- derived FPKM values for symbiotic-related genes (n=73) in soybean nodules, which were sorted by pattern of expression across the observation period. Expression Patterns from 2 to 10 wpi included: Low to High. Genes were annotated with functional categories indicated by color, included the number of genes in each category in parenthesis, and used shapes to denote AVG FPKM across all samples: triangles indicate genes with high average FPKM value (> 1000), squares indicate genes with moderate average FPKM values (100 to 1000), andcircles represent genes with low average FPKM values (< 100). The column to the immediate left of the heat maps indicates expression density and includes a dendrogram showing clustering based on FPKM expression levels. Color Key: light yellow indicates low FPKM values (lowest gene expression), orange for moderate levels of gene expression, andPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web dark red for high average FPKM values (highest gene expression). Genes are sorted by row. Data collected from soybean nodules 2 to 10 wpi with Bradyrhizobium USDA110.

[0052] FIG. 16B. Highly Expressed Symbiotic-Related Genes implicated in nitrogen fixation based on expression in nodules throughout Development. Heat maps displaying RNAseq- derived FPKM values for symbiotic-related genes (n=73) in soybean nodules, which were sorted by pattern of expression across the observation period. Expression Patterns from 2 to 10 wpi included: Low to High to Low. Genes were annotated with functional categories indicated by color, included the number of genes in each category in parenthesis, and used shapes to denote AVG FPKM across all samples: triangles indicate genes with high average FPKM value (> 1000), squares indicate genes with moderate average FPKM values (100 to 1000), andcircles represent genes with low average FPKM values (< 100). The column to the immediate left of the heat maps indicates expression density and includes a dendrogram showing clustering based on FPKM expression levels. Color Key: light yellow indicates low FPKM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average FPKM values (highest gene expression). Genes are sorted by row. Data collected from soybean nodules 2 to 10 wpi with Bradyrhizobium USDA110.

[0053] FIG. 16C. Highly Expressed Symbiotic-Related Genes implicated in nitrogen fixation based on expression in nodules throughout Development. Heat maps displaying RNAseq- derived FPKM values for symbiotic-related genes (n=73) in soybean nodules, which were sorted by pattern of expression across the observation period. Expression Patterns from 2 to 10 wpi included: Low to High. Genes were annotated with functional categories indicated by color, included the number of genes in each category in parenthesis, and used shapes to denote AVG FPKM across all samples: triangles indicate genes with high average FPKM value (> 1000), squares indicate genes with moderate average FPKM values (100 to 1000), andcircles represent genes with low average FPKM values (< 100). The column to the immediate left of the heat maps indicates expression density and includes a dendrogram showing clustering based on FPKM expression levels. Color Key: light yellow indicates low FPKM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average FPKM values (highest gene expression). Genes are sorted by row. Data collected from soybean nodules 2 to 10 wpi with Bradyrhizobium USDA110.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0054] FIG. 16D. Highly Expressed Symbiotic-Related Genes implicated in nitrogen fixation based on expression in nodules throughout Development. Heat maps displaying RNAseq- derived FPKM values for symbiotic-related genes (n=73) in soybean nodules, which were sorted by pattern of expression across the observation period. Expression Patterns from 2 to 10 wpi included: Low to High to Low. Genes were annotated with functional categories indicated by color, included the number of genes in each category in parenthesis, and used shapes to denote AVG FPKM across all samples: triangles indicate genes with high average FPKM value (> 1000), squares indicate genes with moderate average FPKM values (100 to 1000), andcircles represent genes with low average FPKM values (< 100). The column to the immediate left of the heat maps indicates expression density and includes a dendrogram showing clustering based on FPKM expression levels. Color Key: light yellow indicates low FPKM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average FPKM values (highest gene expression). Genes are sorted by row. Data collected from soybean nodules 2 to 10 wpi with Bradyrhizobium USDA110.

[0055] FIG. 16E. Highly Expressed Symbiotic-Related Genes implicated in nitrogen fixation based on expression in nodules throughout Development. Heat maps displaying RNAseq- derived FPKM values for symbiotic-related genes (n=73) in soybean nodules, which were sorted by pattern of expression across the observation period. Expression Patterns from 2 to 10 wpi included: Fluctuating or Steady. Genes were annotated with functional categories indicated by color, included the number of genes in each category in parenthesis, and used shapes to denote AVG FPKM across all samples: triangles indicate genes with high average FPKM value (> 1000), squares indicate genes with moderate average FPKM values (100 to 1000), andcircles represent genes with low average FPKM values (< 100). The column to the immediate left of the heat maps indicates expression density and includes a dendrogram showing clustering based on FPKM expression levels. Color Key: light yellow indicates low FPKM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average FPKM values (highest gene expression). Genes are sorted by row. Data collected from soybean nodules 2 to 10 wpi with Bradyrhizobium USDA110.

[0056] FIG. 17. Nodules contain small RNAs from soybean and Bradyrhizobium. The y-axis shows the mapping percentages of each small RNA library, which are represented on the x-PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web axis. Reads mapping the plant genome are shown in teal, while reads mapping the Bradyrhizobium genome are shown in purple.

[0057] FIG. 18A. Soybean and Bradyrhizobium small RNAs have distinct size distributions. Small RNA read size distribution of reads mapping the soybean genome Gmax W82 v4.a1 , arranged from 2 wpi to 10 wpi, top to bottom. For each barplot, the x-axis represents the size of the small RNA read, ranging from 10 to 50 nucleotides. The y-axis shows the abundance in reads per million (RPM). Each color in the barplots represents a different biological replicate.

[0058] FIG. 18B. Soybean and Bradyrhizobium small RNAs have distinct size distributions. Small RNA read size distribution of reads mapping the Bradyrhizobium USDA110 genome, arranged from 2 wpi to 10 wpi, top to bottom. For each barplot, the x-axis represents the size of the small RNA read, ranging from 10 to 50 nucleotides. The y-axis shows the abundance in reads per million (RPM). Each color in the barplots represents a different biological replicate.

[0059] FIG. 19. 22-nt small RNAs present at 2 wpi originate from ribosomal RNAs and Transposable Elements. Each barplot represents the abundance of reads mapping to individual features of the Soybean genome. The grey-shaded barplots represent reads mapping to the entire Soybean genome. These reads are categorized by size, including those from 20 to 24 nucleotides. The x-axis of each barplot indicates the weeks post-inoculation, ranging from 2 wpi to 10 wpi. The y-axis shows the abundance of small RNA reads in reads per million (RPM). Each barplot includes data from three biological replicates.

[0060] FIG. 20. Small RNA reads map soybean ribosomal RNAs and Bradyrhizobium coding regions. Genomic origin of small RNA reads based on the categories established in the Glycine max cv. W82 and Bradyrhizobium genomes. The x-axis represents the week post inoculation (wpi), ranging from 2 wpi to 10 wpi. The y-axis represents the cumulative abundance in reads per million (RPM). Each different genome feature is represented in a different color, blue shades for features of the Bradyrhizobium genome, including coding regions (Bdi.cds), ribosomal RNAs (Bdi.rRNAs), and transfer RNAs(Bdi.tRNAs). In brown shades for features of the Soybean genome, including coding regions (Gma.cds), microRNAs (Gma.miRNAs), ribosomal RNAs (Gma.rRNAs), transacting siRNAs genes (Gma.TAS), Transposable elements (Gma.TE), and transfer RNAs (Gma.tRNAs). Each barplot contains three biological replicates.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0061] FIG. 21 A. microRNA differential accumulation highlights three different groups, corresponding to early nodulation, nitrogen fixation, and nodule senescence. Principal component analysis (PCA) of microRNA expression. The x-axis represents the first principal component, driving 39% of the variability, and the y-axis represents the second principal component, driving 14% of the variability. Each week post inoculation (wpi) is represented in a different color and includes three biological replicates. Circles represent samples that cluster together.

[0062] FIG. 21 B. microRNA differential accumulation highlights three different groups, corresponding to early nodulation, nitrogen fixation, and nodule senescence. Differentially accumulated miRNAs in each of the comparisons. The x-axis represents the comparing weeks, and the y-axis represents the number of DA miRNAs. In red are the up-accumulated miRNAs and in blue are the down-accumulated miRNAs.

[0063] FIG. 21C. microRNA differential accumulation highlights three different groups, corresponding to early nodulation, nitrogen fixation, and nodule senescence. Upset plot showing each comparison's common and unique differentially accumulated miRNAs. The bottom left shows the size of each set as a horizontal histogram, the bottom right shows the intersection matrix and the upper right shows the size of each combination as a vertical Histogram.

[0064] FIG. 22. miRNAs play crucial roles in all stages of nodule development.

[0065] FIG. 22A. miRNAs play crucial roles in all stages of nodule development. Relative accumulation of miRNAs with a peak at 5 weeks post inoculation (wpi) indicating roles in nitrogen fixation. The x-axis shows the age of nodules in wpi, where young nodules are represented on the far left and old nodules are shown on the right. The y-axis represents the different miRNAs. Color Key: light yellow indicates low RPM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average RPM values (highest gene expression). The dendrogram on the left side indicates the similarity between clusters.

[0066] FIG. 22B. miRNAs play crucial roles in all stages of nodule development. The WGCNA software is used for the hierarchical clustering of miRNA expression. The x-axis represents the different weeks post-inoculation (wpi), including three biological replicates. The y-axis displaysPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web the clusters, which range from ME1 to ME11 . The colors signify the relative level of accumulation of miRNAs, with high accumulation in red shades and low accumulation in blue shades. The dendrogram on the left side indicates the similarity between clusters.

[0067] FIG. 23A. Different 21 -nt phasiRNAs are present in all stages of nodule development. Relative accumulation of known microRNAs that trigger phasiRNAs. The x-axis shows the different weeks post inoculation (wpi) and the y-axis represents each miRNA. The column to the immediate left of the heat maps indicates expression density and includes a dendrogram showing clustering based on RPM expression levels. Color Key: light yellow indicates low RPM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average RPM values (highest gene expression).

[0068] FIG. 23B. Different 21 -nt phasiRNAs are present in all stages of nodule development. phasiRNA accumulation of each PHAS locus identified. The x-axis represents each PHAS locus, the y-axis represents the relative cumulative abundance (in percentage) for each PHAS locus. The five different colors represent different small RNA sizes, ranging from 20- to 24-nt long.

[0069] FIG. 23C. Different 21 -nt phasiRNAs are present in all stages of nodule development. Heat maps displaying sRNAseq reads per million values for PHAS loci in soybean nodules. The column to the immediate left of the heat maps indicates expression density and includes a dendrogram showing clustering based on RPM expression levels. Color Key: light yellow indicates low RPM values (lowest gene expression), orange for moderate levels of gene expression, and dark red for high average RPM values.

[0070] FIG. 24A. Different tRF sizes accumulate at different nodule development stage. Small RNA read size distribution of reads mapping soybean tRNAs. For each barplot, the x-axis represents the size of the small RNA read, ranging from 10 to 50 nucleotides. The y-axis shows the abundance in reads per million (RPM). Each color in the barplots represents a different biological replicate.

[0071] FIG. 24B. Different tRF sizes accumulate at different nodule development stage. Abundance of tRNA categories defined by llnitas. For each barplot, the x-axis represents the nodule stage in weeks post inoculation. The y-axis represents the abundance in normalizedPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web absolute reads provided by llnitas. Each color in the barplots represents a different biological replicate.

[0072] FIG. 25. tRNA fragments from specific anticodons accumulate during nodule development. In this bar plot, the x-axis represents the different tRNA genes identified in the Soybean genome grouped by their anticodon and amino acid. The y-axis shows the normalized abundance provided by the software llnitas. Each color in the barplots represents a nodule stage in weeks post inoculation (wpi) and includes three biological replicates.

[0073] FIG. 26. Size distribution of Bradyrhizobium tRNA fragments is distinct from plants. Each bar plot contains data from a different nodule stage, from 2 weeks post inoculation (wpi) to 10 wpi. For each bar plot, the x-axis represents the size of the tRNA mapping reads, ranging from 10 to 50 nucleotides. The y-axis shows the abundance in reads per million (RPM). Each color in the barplots represents a different biological replicate.

[0074] FIG. 27. The negative response to excess nitrogen is similar between nitrogenase activity and Bradyrhizobium nifH expression, while the response by soybean Lb1 expression is delayed. Boxplots demonstrate the short-term effect of high nitrogen stress on soybean nodules, including their (A) nitrogenase activity, relative (B) Gm.Lbl and (C) Bd.nifH expression, and (D) relative NifH protein level. Soybeans were treated with 500ml of 50 mM NH4NO3 at 4 wpi, 5 wpi, and 6 wpi and again two days past the first treatment (dpt). RNA and protein were extracted from nodules collected prior to measurement of nitrogenase activity via the acetylene reduction assay (ARA). During the ARA, whole root-systems were incubated with 5% acetylene gas for 30 minutes in a sealed 1 L glass container with a septa cap. Nodule nitrogenase catalyzed the reduction of acetylene to ethylene during this time and a 500 pl aliquot of ethylene produced in the assay was measured using gas chromatography with flame ionization detection (GC-FID), with five technical replicates of each biological sample, taken two minutes apart. Experimental ethylene concentrations were compared with a standard curve of known ethylene concentrations. Nitrogenase activity was then calculated based on the determined ethylene concentration per time incubated per nodule mass. Relative Lb1 and nifH gene expression levels were normalized using Gm.TefSI and Bd.16S as endogenous controls, respectively. Additionally, NifH protein content was measured using a NifH primary antibody, and normalized with soybean ACTIN as an endogenous protein control in nodules. DataPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web collected spans Glycine max cv. Williams-82 root systems and nodules aged 3 wpi to 7 wpi with nitrogen-fixing Bradyrhizobium diazoefficiens USDA110. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).

[0075] FIG. 28. High levels of soil nitrogen slightly inhibit soybean root growth, while having no measurable effect on shoot growth. Prior to measuring whole-root system nitrogenase activity by acetylene reduction assay (ARA), soybean (A) shoots and (B) roots were separated and weighed. Shoots were then stored at 65°C, and after 1 -week of dehydration, (C) shoot dry mass was obtained. Shoot and root samples were collected at various stages of soybean development. All plants were grown with low nitrogen (0.5 mM KNO3) during germination and early growth. Plants collected at 2 days past-treatment (dpt) received one high nitrogen treatment (50 mM NH4NO3), while those collected at 4 dpt received two HN treatments, one at 0 dpt and one at 2 dpt. Data collected spans Glycine max root systems and shoots aged 3 to 7 weeks post inoculation (wpi) with Bradyrhizobium diazoefficiens USDA110.

[0076] FIG. 29. NifH protein levels in soybean nodules are unaffected by high nitrogen treatments. Western blot gel analysis showing NifH protein accumulation in nodule samples collected at various stages of soybean nodule development (3 wpi to 7 wpi) following high nitrogen treatments (50 mM NH4NO3). All plants were grown with low nitrogen (0.5 mM KNO3) during germination and early growth. Plants collected at 2 days past treatment (dpt) received one high nitrogen treatment. Plants collected at 4 dpt received two high nitrogen treatments, one at 0 dpt and one at 2 dpt. The individual protein gels show the presence of Bradyrhizobium USDA110 NifH (32 kDa) and Gm.ACTIN (45 kDa) in samples collected at: (A) 3 wpi, 4 wpi, and 5 wpi (untreated) and 2 dpt and 4 dpt (treated) samples at 4 wpi, (B) 5 wpi, 6 wpi, and 7 wpi (untreated) and 2 dpt and 4 dpt (treated) samples at 5 wpi, and (C) 5 wpi, 6 wpi, and 7 wpi (untreated), and 2 dpt and 4 dpt (treated) samples at 6 wpi. G.max ACTIN protein was used as an endogenous loading and protein control across all samples.

[0077] FIG. 30A. LBA protein levels in soybean nodules are unaffected by high nitrogen treatments despite low Lb3 transcript levels. Nodule samples were collected at various stages of soybean nodule development (3 wpi to 7 wpi) following high nitrogen treatments (50 mM NH4NO3). All plants were grown with low nitrogen (0.5 mM KNO3) during germination and early growth. Plants collected at 2 days post-treatment (dpt) received one high nitrogenPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web treatment, while those collected at 4 dpt received two high nitrogen treatments, one at 0 dpt and one at 2 dpt. Boxplot shows Gm.Lb3 FPKM expression obtained from RNAseq analysis.

[0078] FIG. 30B. LBA protein levels in soybean nodules are unaffected by high nitrogen treatments despite low Lb3 transcript levels. Nodule samples were collected at various stages of soybean nodule development (3 wpi to 7 wpi) following high nitrogen treatments (50 mM NH4NO3). All plants were grown with low nitrogen (0.5 mM KNO3) during germination and early growth. Plants collected at 2 days post-treatment (dpt) received one high nitrogen treatment, while those collected at 4 dpt received two high nitrogen treatments, one at 0 dpt and one at 2 dpt. Boxplot shows Gm. LBA protein levels.

[0079] FIG. 30C. Western blot gel analysis shows the presence of Glycine max LBA protein (16 kDa) and Gm. ACTIN (45 kDa) in samples collected at: 3 wpi, 4 wpi, and 5 wpi (untreated) and 2 dpt and 4 dpt (treated) samples at 4 wpi. G. max ACTIN protein was used as an endogenous loading and protein control across all samples. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).

[0080] FIG. 30D. Western blot gel analysis shows the presence of Glycine max LBA protein (16 kDa) and Gm. ACTIN (45 kDa) in samples collected at: 5 wpi, 6 wpi, and 7 wpi (untreated) and 2 dpt and 4 dpt (treated) samples at 5 wpi. G. max ACTIN protein was used as an endogenous loading and protein control across all samples. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).

[0081] FIG. 30E. Western blot gel analysis shows the presence of Glycine max LBA protein (16 kDa) and Gm. ACTIN (45 kDa) in samples collected at 5 wpi, 6 wpi, and 7 wpi (untreated), and 2 dpt and 4 dpt (treated) samples at 6 wpi. G. max ACTIN protein was used as an endogenous loading and protein control across all samples. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).

[0082] FIG. 31A-C. Emergence of small nodules contributes to increased nodule number after 6 wpi. Following the measurement of root system nitrogenase activity using the acetylene reduction assay, root nodules were removed, cleaned of debris, (A) weighed 3-hours post incubation with acetylene. All plants were grown with low nitrogen (0.5 mM KNO3) during germination and early growth. Plants collected at 2 days past-treatment (dpt) received one high nitrogen treatment (50 mM NH4NO3), while those collected at 4 dpt received two highPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web nitrogen treatments, one at 0 dpt and one at 2 dpt. Data collected spans Glycine max nodules aged 3 to 7 weeks post inoculation (wpi) with Bradyrhizobium diazoefficiens USDA110.Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).

[0083] FIG. 31 B Emergence of small nodules contributes to increased nodule number after 6 wpi. Following the measurement of root system nitrogenase activity using the acetylene reduction assay, root nodules were removed, cleaned of debris, and counted. After observing the emergence of small nodules at 5 wpi and 2 dpt. All plants were grown with low nitrogen (0.5 mM KNO3) during germination and early growth. Plants collected at 2 days past-treatment (dpt) received one high nitrogen treatment (50 mM NH4NO3), while those collected at 4 dpt received two high nitrogen treatments, one at 0 dpt and one at 2 dpt. Data collected spans Glycine max nodules aged 3 to 7 weeks post inoculation (wpi) with Bradyrhizobium diazoefficiens USDA110. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).

[0084] FIG. 31CEmergence of small nodules contributes to increased nodule number after 6 wpi. After observing the emergence of small nodules at 5 wpi and 2 dpt, the nodules were sorted into groups according to size: small (< 2mm) and large (> 2mm). Nodules were collected at various stages of soybean development. All plants were grown with low nitrogen (0.5 mM KNO3) during germination and early growth. Plants collected at 2 days past-treatment (dpt) received one high nitrogen treatment (50 mM NH4NO3), while those collected at 4 dpt received two high nitrogen treatments, one at 0 dpt and one at 2 dpt. Data collected spans Glycine max nodules aged 3 to 7 weeks post inoculation (wpi) with Bradyrhizobium diazoefficiens USDA110. Significant p-values are indicated by asterisks: * (0.01 to 0.05), ** (0.001 to 0.01 ), and *** (< 0.001 ).

[0085] FIG. 32A. The volume and the type of nitrogen used during treatment had no measurable effect across eight measured parameters.

[0086] Boxplots nitrogenase activity, show data measured from soybean plants aged 4 weeks post inoculation (wpi) to 5 wpi. Data measured at 4 wpi and at 5 wpi was acquired from soybeans that received minimal levels of nitrogen (0.5 mM KNO3) throughout their development (indicated by a lighter shade of color). Treated plants, those measured at 4 wpiPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web plus 4 days post treatment (dpt), received minimal nitrogen until 4 wpi, and at 4 wpi they received either 500 mL of high nitrogen (50 mM NH4NO3) (indicated by a darker shade of color) or 500 mL of low nitrogen (0.5 mM NH4NO3). This application was repeated twice, once at 4 wpi and again at 2 dpt. Both sets of treated plants were assayed and measured accordingly.

[0087] FIG. 32B. The volume and the type of nitrogen used during treatment had no measurable effect across eight measured parameters. Boxplots nodule fresh mass, show data measured from soybean plants aged 4 weeks post inoculation (wpi) to 5 wpi. Data measured at 4 wpi and at 5 wpi was acquired from soybeans that received minimal levels of nitrogen (0.5 mM KNO3) throughout their development (indicated by a lighter shade of color). Treated plants, those measured at 4 wpi plus 4 days post treatment (dpt), received minimal nitrogen until 4 wpi, and at 4 wpi they received either 500 mL of high nitrogen (50 mM NH4NO3) (indicated by a darker shade of color) or 500 mL of low nitrogen (0.5 mM NH4NO3). This application was repeated twice, once at 4 wpi and again at 2 dpt. Both sets of treated plants were assayed and measured accordingly.

[0088] FIG. 32C. The volume and the type of nitrogen used during treatment had no measurable effect across eight measured parameters. Boxplots nodule number, show data measured from soybean plants aged 4 weeks post inoculation (wpi) to 5 wpi. Data measured at 4 wpi and at 5 wpi was acquired from soybeans that received minimal levels of nitrogen (0.5 mM KNO3) throughout their development (indicated by a lighter shade of color). Treated plants, those measured at 4 wpi plus 4 days post treatment (dpt), received minimal nitrogen until 4 wpi, and at 4 wpi they received either 500 mL of high nitrogen (50 mM NH4NO3) (indicated by a darker shade of color) or 500 mL of low nitrogen (0.5 mM NH4NO3). This application was repeated twice, once at 4 wpi and again at 2 dpt. Both sets of treated plants were assayed and measured accordingly.

[0089] FIG. 32D. The volume and the type of nitrogen used during treatment had no measurable effect across eight measured parameters. Boxplots root fresh mass, show data measured from soybean plants aged 4 weeks post inoculation (wpi) to 5 wpi. Data measured at 4 wpi and at 5 wpi was acquired from soybeans that received minimal levels of nitrogen (0.5 mM KNO3) throughout their development (indicated by a lighter shade of color). TreatedPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web plants, those measured at 4 wpi plus 4 days post treatment (dpt), received minimal nitrogen until 4 wpi, and at 4 wpi they received either 500 mL of high nitrogen (50 mM NH4NO3) (indicated by a darker shade of color) or 500 mL of low nitrogen (0.5 mM NH4NO3). This application was repeated twice, once at 4 wpi and again at 2 dpt. Both sets of treated plants were assayed and measured accordingly.

[0090] FIG. 32E. The volume and the type of nitrogen used during treatment had no measurable effect across eight measured parameters. Boxplots (E) relative Bradyrhizobium nifH expression, show data measured from soybean plants aged 4 weeks post inoculation (wpi) to 5 wpi. Data measured at 4 wpi and at 5 wpi was acquired from soybeans that received minimal levels of nitrogen (0.5 mM KNO3) throughout their development (indicated by a lighter shade of color). Treated plants, those measured at 4 wpi plus 4 days post treatment (dpt), received minimal nitrogen until 4 wpi, and at 4 wpi they received either 500 mL of high nitrogen (50 mM NH4NO3) (indicated by a darker shade of color) or 500 mL of low nitrogen (0.5 mM NH4NO3). This application was repeated twice, once at 4 wpi and again at 2 dpt. Both sets of treated plants were assayed and measured accordingly.

[0091] FIG. 32F. The volume and the type of nitrogen used during treatment had no measurable effect across eight measured parameters. Boxplots relative soybean Lb1 expression, show data measured from soybean plants aged 4 weeks post inoculation (wpi) to 5 wpi. Data measured at 4 wpi and at 5 wpi was acquired from soybeans that received minimal levels of nitrogen (0.5 mM KNO3) throughout their development (indicated by a lighter shade of color). Treated plants, those measured at 4 wpi plus 4 days post treatment (dpt), received minimal nitrogen until 4 wpi, and at 4 wpi they received either 500 mL of high nitrogen (50 mM NH4NO3) (indicated by a darker shade of color) or 500 mL of low nitrogen (0.5 mM NH4NO3). This application was repeated twice, once at 4 wpi and again at 2 dpt. Both sets of treated plants were assayed and measured accordingly.

[0092] FIG. 32G. The volume and the type of nitrogen used during treatment had no measurable effect across eight measured parameters. Boxplots shoot fresh mass, show data measured from soybean plants aged 4 weeks post inoculation (wpi) to 5 wpi. Data measured at 4 wpi and at 5 wpi was acquired from soybeans that received minimal levels of nitrogen (0.5 mM KNO3) throughout their development (indicated by a lighter shade of color). TreatedPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web plants, those measured at 4 wpi plus 4 days post treatment (dpt), received minimal nitrogen until 4 wpi, and at 4 wpi they received either 500 mL of high nitrogen (50 mM NH4NO3) (indicated by a darker shade of color) or 500 mL of low nitrogen (0.5 mM NH4NO3). This application was repeated twice, once at 4 wpi and again at 2 dpt. Both sets of treated plants were assayed and measured accordingly.

[0093] FIG. 32H. The volume and the type of nitrogen used during treatment had no measurable effect across eight measured parameters. Boxplots shoot dry mass, show data measured from soybean plants aged 4 weeks post inoculation (wpi) to 5 wpi. Data measured at 4 wpi and at 5 wpi was acquired from soybeans that received minimal levels of nitrogen (0.5 mM KNO3) throughout their development (indicated by a lighter shade of color). Treated plants, those measured at 4 wpi plus 4 days post treatment (dpt), received minimal nitrogen until 4 wpi, and at 4 wpi they received either 500 mL of high nitrogen (50 mM NH4NO3) (indicated by a darker shade of color) or 500 mL of low nitrogen (0.5 mM NH4NO3). This application was repeated twice, once at 4 wpi and again at 2 dpt. Both sets of treated plants were assayed and measured accordingly.

[0094] FIG. 33A. Red pigment is present in nodules treated with high nitrogen two days past treatment. A dissecting scope was used to image nodules from treated and untreated soybean plants at three points: 5 wpi + 0 dpt (days past first treatment), + 2 dpt, and + 4 dpt. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth. Untreated nodule controls were collected and imaged at 5 wpi + 0 dpt. The data encompasses nodules from soybean plants aged 5 wpi to 5 wpi + 4 dpt. Soybeans were inoculated with Bradyrhizobium diazoefficiens USDA110 one week after sowing.

[0095] FIG. 33B. Red pigment is present in nodules treated with high nitrogen two days past treatment. A dissecting scope was used to image nodules from treated and untreated soybean plants at three points: 5 wpi + 0 dpt (days past first treatment), + 2 dpt, and + 4 dpt. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth. Nodules collected from plants at 2 dpt received one high nitrogen treatment (50 mM NH4NO3). The data encompasses nodules from soybean plants aged 5 wpi to 5 wpi + 4 dpt. Soybeans were inoculated with Bradyrhizobium diazoefficiens USDA110 one week after sowing.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0096] FIG. 33C. Red pigment is present in nodules treated with high nitrogen two days past treatment. A dissecting scope was used to image nodules from treated and untreated soybean plants at three points: 5 wpi + 0 dpt (days past first treatment), + 2 dpt, and + 4 dpt. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth. Nodules collected at 4 dpt received two HN treatments, one at 5 wpi + 0 dpt and another at + 2 dpt. The data encompasses nodules from soybean plants aged 5 wpi to 5 wpi + 4 dpt. Soybeans were inoculated with Bradyrhizobium diazoefficiens USDA110 one week after sowing.

[0097] FIG. 34. Host-origin dominance in nodule gene expression. RNA was analyzed from treated and untreated nodules, mapping it to both the soybean (Glycine max) and Bradyrhizobium diazoefficiens USDA110 genomes. The y-axis represents the percentage of reads mapped from each biological replicate’s (BR) RNA sequencing library, which are depicted on the x-axis. Reads mapping to the soybean genome (Gmax v4.a1 ) are shown in teal, while reads mapping to the Bradyrhizobium genome are shown in purple. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth. Nodules from plants collected at 2 days past-treatment (dpt) received one high nitrogen treatment (50 mM NH4NO3), while those collected at 4 dpt received two treatments, one at 0 dpt and another at 2 dpt. The data encompasses nodules from soybean plants aged 4 weeks post inoculation (wpi) to 7 wpi.

[0098] FIG. 35A. Gene expression is significantly altered in nodules under high nitrogen conditions. Principal component analysis (PCA) using all soybean gene expression from all nodule samples. The x-axis represents the first principal component, driving 65% of the variability, and the y-axis represents the second principal component, driving 11 % of the variability. The line separates treated from untreated (control) samples. Genes were highlighted that shared by all comparisons (n=2000), all 2 dpt vs. 0 dpt comparisons (n=334), and all 4 dpt vs. 0 dpt comparisons (n=231 ) in orange.

[0099] FIG. 35B. Gene expression is significantly altered in nodules under high nitrogen conditions. Heatmap representing the fold change of all differentially expressed (DE) soybean genes in nodules (n=15,354). The x-axis represent six individual treated vs. untreated comparisons. Color Key: blue indicates a negative fold change and red indicates a positive foldPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web change (Iog2 scale). Genes were highlighted that shared by all comparisons (n=2000), all 2 dpt vs. 0 dpt comparisons (n=334), and all 4 dpt vs. 0 dpt comparisons (n=231 ) in orange.

[0100] FIG. 35C. Gene expression is significantly altered in nodules under high nitrogen conditions. Upset plot showing the common and specific genes differentially expressed in each treated vs. untreated comparison, for soybean. The bottom left shows the size of each set as a horizontal histogram, the bottom right shows the intersection matrix and the upper right shows the size of each combination as a vertical histogram. Genes were highlighted that shared by all comparisons (n=2000), all 2 dpt vs. 0 dpt comparisons (n=334), and all 4 dpt vs. 0 dpt comparisons (n=231 ) in orange.

[0101] FIG. 36A. Diverse biological pathways revealed by GO analysis are modulated in soybean nodules in response to high nitrogen treatments. Gene Ontology (GO) analysis of differentially expressed nodule genes under high nitrogen conditions. The GO analysis was performed of 2,000 differentially expressed (DE) nodule genes shared across all treated vs. untreated comparisons (n=6) using Shiny GO V0.80. This analysis revealed pathways related to biological processes associated with upregulated genes (n=863). The color scale indicates the false discovery rate (FDR) in a -Iog10 scale, with red representing higher confidence pathways (lower FDR) and blue indicating pathways with a higher amount of false positives (higher FDR).

[0102] FIG. 36B. GO pathway network analysis illustrates the relationships between enriched pathways for upregulated genes. In these network diagrams, pathways (nodes) are represented by green circles. Nodes are connected by lines if they share 40% or more of their genes, with thicker lines indicating a higher percentage of shared genes between connected pathways. Darker nodes denote more significantly enriched gene sets, while bigger nodes represent gene sets with a greater number of genes.

[0103] FIG. 36C. Diverse biological pathways revealed by GO analysis are modulated in soybean nodules in response to high nitrogen treatments. Gene Ontology (GO) analysis of differentially expressed nodule genes under high nitrogen conditions. The GO analysis was performed of 2,000 differentially expressed (DE) nodule genes shared across all treated vs. untreated comparisons (n=6) using Shiny GO V0.80. This analysis revealed pathways related to biological processes associated with (C) downregulated genes (n=1 , 137). The color scalePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web indicates the false discovery rate (FDR) in a -Iog10 scale, with red representing higher confidence pathways (lower FDR) and blue indicating pathways with a higher amount of false positives (higher FDR).

[0104] FIG. 36D. GO pathway network analysis illustrates the relationships between enriched pathways for downregulated genes. In these network diagrams, pathways (nodes) are represented by green circles. Nodes are connected by lines if they share 40% or more of their genes, with thicker lines indicating a higher percentage of shared genes between connected pathways. Darker nodes denote more significantly enriched gene sets, while bigger nodes represent gene sets with a greater number of genes.

[0105] FIG. 37 A. Dynamic transcriptional regulation of symbiotic-related genes in nodules under high nitrogen conditions. Heat maps display RNAseq-derived average FPKM values for symbiotic-related genes in soybean nodules that are upregulated in response to high nitrogen treatments applied at 0 days past first treatment (dpt) and 2 dpt at 4 weeks post inoculation (wpi), 5 wpi and 6 wpi. An asterisk (*) indicates a differentially expressed (DE) gene. Light yellow indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row. Genes are classified into one of seven groups based on gene family or related function, with functional categories indicated by color. The number of genes upregulated and downregulated in each category is annotated. In untreated samples, triangles indicate genes with high (H) average FPKM value (> 1000), squares indicate genes with moderate (M) average FPKM values (100 to 1000), and circles represent genes with low (L) average FPKM values (< 100). Average expression density is indicated in column to the left of the heat map and genes are clustered by similar expression levels.

[0106] FIG. 37B. Dynamic transcriptional regulation of symbiotic-related genes in nodules under high nitrogen conditions. Heat maps display RNAseq-derived average FPKM values for symbiotic-related genes in soybean nodules that are downregulated in response to high nitrogen treatments applied at 0 days past first treatment (dpt) and 2 dpt at 4 weeks post inoculation (wpi), 5 wpi and 6 wpi. An asterisk (*) indicates a differentially expressed (DE) gene. Light yellow indicates low average FPKM values (lowest gene expression), orangePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row. Genes are classified into one of seven groups based on gene family or related function, with functional categories indicated by color. The number of genes upregulated and downregulated in each category is annotated. In untreated samples, triangles indicate genes with high (H) average FPKM value (> 1000), squares indicate genes with moderate (M) average FPKM values (100 to 1000), and circles represent genes with low (L) average FPKM values (< 100). Average expression density is indicated in column to the left of the heat map and genes are clustered by similar expression levels.

[0107] FIG. 38A. Differential regulation of soybean Leghemoglobin (Lb) and Hemoglobin (Hb) genes in nodules following high nitrogen treatments. Boxplots of RNAseq-derived FPKM values of (A) symbiotic Leghemoglobin (top, n=5) in soybean nodules that are either upregulated or downregulated in response to high nitrogen treatments applied at 0 days past first treatment (dpt) and 2 dpt at 4 weeks post inoculation (wpi), 5 wpi and 6 wpi. An asterisk (*) indicates a differentially expressed (DE) gene. High nitrogen treatments are indicated in dark green and consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth, indicated in light green.

[0108] FIG. 38B. Differential regulation of soybean Leghemoglobin (Lb) and Hemoglobin (Hb) genes in nodules following high nitrogen treatments. (B) Boxplots of RNAseq-derived FPKM values of Non-symbiotic Hemoglobin genes (bottom, n=2) in soybean nodules that are either upregulated or downregulated in response to high nitrogen treatments applied at 0 days past first treatment (dpt) and 2 dpt at 4 weeks post inoculation (wpi), 5 wpi and 6 wpi. An asterisk (*) indicates a differentially expressed (DE) gene. High nitrogen treatments are indicated in dark green and consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth, indicated in light green.

[0109] FIG. 39A. Argonaute (AGO) genes are downregulated in nodules following high nitrogen treatments. RNAseq-derived average FPKM values of six differentially expressed (DE) Argonaute (AGO) genes in soybean nodules that are either upregulated or downregulated in response to high nitrogen treatments applied at 0 days past first treatmentPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web(dpt) and 2 dpt at 4 weeks post inoculation (wpi), 5 wpi and 6 wpi, as illustrated in heatmap. An asterisk (*) indicates a DE gene. Light yellow indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row. Average expression density is indicated in column to the left of the heat map and genes are clustered by similar expression levels.

[0110] FIG. 39B. Argonaute (AGO) genes are downregulated in nodules following high nitrogen treatments. Boxplots show FPKM expression for three significant DE AGO genes with unique patterns of downregulation in nodules under high nitrogen conditions. High nitrogen treatments are indicated in dark green and consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth, indicated by light green.

[0111] FIG.40A. Differential regulation of DICER-like (DCL) genes in nodules following high nitrogen treatments. Heatmap illustrates average RNAseq-derived FPKM values for eight differentially expressed (DE) DICER-like (DCL) genes in soybean nodules under high nitrogen treatments. An asterisk (*) indicates a DE gene. Light yellow indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row and clustered by similar expression levels, with the average expression density indicated in the column to the left of the heat map.

[0112] FIG.40B. Differential regulation of DICER-like (DCL) genes in nodules following high nitrogen treatments. Boxplots shows FPKM expression for five DE DCL genes with clear patterns of upregulation (top) and downregulation (bottom) in nodules under high nitrogen conditions. High nitrogen treatments, indicated in dark green, consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth, indicated by light green.

[0113] FIG.41A. Differential regulation of RNA-dependent RNA polymerases RDR1 and RDR3 in nodules following high nitrogen treatments. Heatmap illustrates average RNAseq- derived FPKM values for six RNA-dependent RNA polymerase (RDR) genes in soybean nodules under high nitrogen treatments. An asterisk (*) indicates a DE gene. Light yellowPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row and clustered by similar expression levels, with the average expression density indicated in the column to the left of the heat map.

[0114] FIG.41B. Differential regulation of RNA-dependent RNA polymerases RDR1 and RDR3 in nodules following high nitrogen treatments. Boxplots show FPKM expression for two DE RDR genes with a clear pattern of upregulation (left) or downregulation (right) in nodules under high nitrogen conditions. High nitrogen treatments, indicated in dark green, consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth, indicated by light green.

[0115] FIG.42A. Differential regulation of nodule defense-related genes following high nitrogen treatments. Heat maps display average RNAseq-derived FPKM values for differentially expressed (DE) defense-related genes in soybean nodules upregulated (n=54), following high nitrogen treatments. Light yellow indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row and clustered by similar expression levels, with the average expression density indicated in the column to the left of the heat map. High nitrogen treatments consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0116] FIG.42B. (B) Differential regulation of nodule defense-related genes following high nitrogen treatments. Heat maps display average RNAseq-derived FPKM values for differentially expressed (DE) defense-related genes in soybean nodules downregulated (n=49), following high nitrogen treatments. Light yellow indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row and clustered by similar expression levels, with the average expression density indicated in the column to the left of the heat map. High nitrogen treatments consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0117] FIG. 43. Bradyrhizobium gene expression is significantly altered in nodules under high nitrogen conditions. Principal component analysis (PCA) using all Bradyrhizobium gene expression from nodule samples. The x-axis represents the first principal component, driving 48% of the variability, and the y-axis represents the second principal component, driving 32% of the variability. The line separates treated from untreated (control) samples. Nodule samples ranged from 4 weeks post inoculation (wpi) to 7 wpi and from 0 days past first treatment (dpt) to 4 dpt. High nitrogen treatments consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0118] FIG. 44A. Temporal distribution of differentially expressed bacterial genes in soybean nodules following high nitrogen treatments. Utilizing DEseq2, the gene expression dynamics of Bradyrhizobium were examined in nodules under high nitrogen conditions. (A) Stacked bar plot visually represents the distribution of differentially expressed (DE) genes in nodules, with upregulated genes in red and down-regulated in blue. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0119] FIG. 44B. Table depicts the counts of bacterial DE genes, categorized by treated vs. untreated comparison using nodule age in weeks post inoculation (wpi) and days past first treatment (dpt) as sample identifier. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0120] FIG. 44C. Heatmap illustrates the fold change (Iog2 scale) of all Bradyrhizobium genes that are DE in at least one comparison (n=2,887). An asterisk (*) indicates gene is DE. Nodule samples ranged from 4 weeks post inoculation (wpi) to 7 wpi and from 0 days past first treatment (dpt) to 4 dpt. High nitrogen treatments of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0121] FIG. 45A. Dynamic and age-dependent transcriptional response by Bradyrhizobium in nodules in response to high nitrogen treatments. Upset plot showing the common and specific genes differentially expressed (DE) in nodules of each treated vs. untreated comparison, for Bradyrhizobium. The bottom left shows the size of each set as a horizontal histogram, the bottom right shows the intersection matrix and the upper right shows the size of each combination as a vertical histogram. DE genes shared by all comparisons (n=59) and all 4 dpt vs. 0 dpt comparisons (n=22) in orange were highlighted.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0122] FIG. 45B. Dynamic and age-dependent transcriptional response by Bradyrhizobium in nodules in response to high nitrogen treatments. Heatmap illustrates the fold change (Iog2 scale) of 59 genes that are consistently shared by all comparisons. The x- axis represent six individual treated vs. untreated comparisons. Color Key: blue indicates a negative fold change (downregulation) and red indicates a positive fold change (upregulation). Genes are clustered by similar pattern of fold change.

[0123] FIG. 45C. Dynamic and age-dependent transcriptional response by Bradyrhizobium in nodules in response to high nitrogen treatments. Heat maps display average RNAseq-derived FPKM values for all niF genes (n=11 ) in soybean nodules. Light yellow indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression.

[0124] FIG. 46A-46C. Gene expression is significantly altered in leaves under high nitrogen conditions. (A) Principal component analysis (PCA) using all soybean gene expression from leaf samples. The x-axis represents the first principal component, driving 30% of the variability, and the y-axis represents the second principal component, driving 18% of the variability. Samples are labeled by weeks post inoculation and days past first treatment “wpi_dpt”. The line separates treated from untreated (control) samples. Genes shared by all comparisons (n=56 genes), all 2 dpt vs. 0 dpt comparisons (n=7 genes), and all 4 dpt vs. 0 dpt comparisons (n=6) in orange were highlighted.

[0125] FIG. 46B. Gene expression is significantly altered in leaves under high nitrogen conditions. Heatmap representing the fold change (Iog2 scale) of all differentially expressed (DE) soybean genes in leaves (n=4,164). The x-axis represent six individual treated vs. untreated comparisons. Color Key: blue indicates a negative fold change and red indicates a positive fold change (Iog2 scale). Genes shared by all comparisons (n=56 genes), all 2 dpt vs. 0 dpt comparisons (n=7 genes), and all 4 dpt vs. 0 dpt comparisons (n=6) in orange were highlighted.

[0126] FIG. 46C. Gene expression is significantly altered in leaves under high nitrogen conditions. Upset plot showing the common and specific genes differentially expressed in each treated vs. untreated comparison, for soybean. The bottom left shows the size of each set as a horizontal histogram, the bottom right shows the intersection matrix and the upper right showsPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web the size of each combination as a vertical histogram. Genes shared by all comparisons (n=56 genes), all 2 dpt vs. 0 dpt comparisons (n=7 genes), and all 4 dpt vs. 0 dpt comparisons (n=6) in orange were highlighted.

[0127] FIG. 47A. Upregulation of non-symbiotic Hemoglobin 1 and 2 (Hb1 and Hb2) in leaves following high nitrogen treatments. Heatmap displays average RNAseq-derived FPKM values for the 56 differentially expressed (DE) genes shared between all treated vs. untreated comparisons. Genes were either upregulated (n=48) or downregulated (n=8). Light yellow indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row and clustered by similar expression levels, with the average expression density indicated in the column to the left of the heat map. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0128] FIG. 47B. Upregulation of non-symbiotic Hemoglobin 1 and 2 (Hb1 and Hb2) in leaves following high nitrogen treatments. Gene Ontology (GO) analysis of upregulated DE leaf genes under high nitrogen conditions, performed using Shiny GO V0.80, revealed pathways related to biological processes. The color scale indicates the false discovery rate (FDR) in a -Iog10 scale, with red representing higher confidence pathways (lower FDR) and blue indicating pathways with a higher amount of false positives (higher FDR). All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0129] FIG. 47C. Upregulation of non-symbiotic Hemoglobin 1 and 2 (Hb1 and Hb2) in leaves following high nitrogen treatments. GO pathway network analysis illustrates the relationships between enriched pathways for upregulated genes in leaves. In these network diagrams, pathways (nodes) are represented by green circles. Nodes are connected by lines if they share 40% or more of their genes, with thicker lines indicating a higher percentage of shared genes between connected pathways. Darker nodes denote more significantly enriched gene sets, while bigger nodes represent gene sets with a greater number of genes. HighPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web nitrogen treatments consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0130] FIG. 48A. Dynamic transcriptional regulation of symbiotic-related genes in leaves under high nitrogen conditions. Heat maps display RNAseq-derived average FPKM values for symbiotic-related genes in soybean leaves that are either upregulated in response to high nitrogen treatments An asterisk (*) indicates a differentially expressed (DE) gene. Light yellow indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row. Genes are classified into one of seven groups based on gene family or related function, with functional categories indicated by color. The number of genes upregulated and downregulated in each category is annotated. In untreated samples, triangles indicate genes with high (H) average FPKM value (> 1000), squares indicate genes with moderate (M) average FPKM values (100 to 1000), and circles represent genes with low (L) average FPKM values (< 100). Average expression density is indicated in column to the left of the heat map and genes are clustered by similar expression levels.

[0131] FIG. 48B. Dynamic transcriptional regulation of symbiotic-related genes in leaves under high nitrogen conditions. Heat maps display RNAseq-derived average FPKM values for symbiotic-related genes in soybean leaves that are downregulated in response to high nitrogen treatments An asterisk (*) indicates a differentially expressed (DE) gene. Light yellow indicates low average FPKM values (lowest gene expression), orange represents moderate levels of gene expression, and dark red denotes high average FPKM values (highest gene expression). Gene expression values are sorted by row. Genes are classified into one of seven groups based on gene family or related function, with functional categories indicated by color. The number of genes upregulated and downregulated in each category is annotated. In untreated samples, triangles indicate genes with high (H) average FPKM value (> 1000), squares indicate genes with moderate (M) average FPKM values (100 to 1000), and circles represent genes with low (L) average FPKM values (< 100). Average expression density is indicated in column to the left of the heat map and genes are clustered by similar expression levels.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0132] FIG. 49A-C. Age-dependent transcriptional regulation of sRNA biogenesis genes in leaves following high nitrogen treatments. Boxplots of RNAseq-derived FPKM values illustrate the expression levels of genes involved in small RNA biogenesis, including (A) Argonautes (AG05, AG07, AG06) in soybean leaves that are differentially expressed (DE) following high nitrogen treatments. An asterisk (*) indicates a DE gene. High nitrogen treatments are indicated in dark green and consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth, indicated in light green.

[0133] FIG. 49B. Age-dependent transcriptional regulation of sRNA biogenesis genes in leaves following high nitrogen treatments. Boxplots of RNAseq-derived FPKM values illustrate the expression levels of genes involved in small RNA biogenesis, including RNA-dependent RNA polymerases (RDR1 and RDR6) in soybean leaves that are differentially expressed (DE) following high nitrogen treatments. An asterisk (*) indicates a DE gene. High nitrogen treatments are indicated in dark green and consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth, indicated in light green.

[0134] FIG. 49C. Age-dependent transcriptional regulation of sRNA biogenesis genes in leaves following high nitrogen treatments. Boxplots of RNAseq-derived FPKM values illustrate the expression levels of genes involved in small RNA biogenesis, including Dicer-like 1 (DCL1 ) in soybean leaves that are differentially expressed (DE) following high nitrogen treatments. An asterisk (*) indicates a DE gene. High nitrogen treatments are indicated in dark green and consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth, indicated in light green.

[0135] FIG. 50A. Differential expression of symbiotic-related and small RNA biogenesis genes in both nodules and leaves in response to high nitrogen treatments. Heatmaps illustrate the average fold change (Iog2 scale) of differentially expressed (DE) genes in soybean nodules (n=63) and leaves (n=17) following high nitrogen treatments. An asterisk (*) indicates a DE gene. The genes in this figure are: symbiosis-related genes (n=50). Upregulated genes are shown in shades of red, while downregulated genes are shown in shades of blue. Genes that are both bold and underlined are DE in both leaves and nodules following high nitrogenPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web treatments. Symbiotic-related genes are classified into one of seven groups based on gene family or related function, with functional categories indicated by color.Agene identified in the list of DE genes in nodules across all treated vs. untreated comparisons.Bgene identified in the list of DE genes in nodules comparing 2 days past treatment (dpt) vs. 0 dpt.cgene identified in the list of DE genes in nodules comparing 4 dpt vs. 0 dpt.Dgene identified in the list of DE genes in leaves across all treated vs. untreated comparisons.

[0136] FIG. 50B. Differential expression of symbiotic-related and small RNA biogenesis genes in both nodules and leaves in response to high nitrogen treatments. Heatmaps illustrate the average fold change (Iog2 scale) of differentially expressed (DE) genes in soybean nodules (n=63) and leaves (n=17) following high nitrogen treatments. An asterisk (*) indicates a DE gene. The genes in this figure are: small RNA biogenesis genes (n=19). Upregulated genes are shown in shades of red, while downregulated genes are shown in shades of blue. Genes that are both bold and underlined are DE in both leaves and nodules following high nitrogen treatments. Symbiotic-related genes are classified into one of seven groups based on gene family or related function, with functional categories indicated by color.Agene identified in the list of DE genes in nodules across all treated vs. untreated comparisons.Bgene identified in the list of DE genes in nodules comparing 2 days past treatment (dpt) vs. 0 dpt.cgene identified in the list of DE genes in nodules comparing 4 dpt vs. 0 dpt.Dgene identified in the list of DE genes in leaves across all treated vs. untreated comparisons.

[0137] FIG. 50C. The number of genes upregulated and downregulated in each tissue is annotated.Agene identified in the list of DE genes in nodules across all treated vs. untreated comparisons.Bgene identified in the list of DE genes in nodules comparing 2 days past treatment (dpt) vs. 0 dpt.cgene identified in the list of DE genes in nodules comparing 4 dpt vs. 0 dpt.Dgene identified in the list of DE genes in leaves across all treated vs. untreated comparisons.

[0138] FIG. 51. High nitrogen treatments do not affect nodule sRNAs’ genomic origins. sRNA from treated and untreated soybean nodules were analyzed, mapping it to both the soybean host (Glycine max W82) and bacterial symbiont (Bradyrhizobium diazoefficiens USDA1 10) genomes. The y-axis represents the percentages of reads mapped from each biological replicate’s (BR) small RNA (sRNA) library to soybean and Bradyrhizobium, whichPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web are represented on the x-axis. Reads mapping the plant genome Gmax_W82 v4.a1 are shown in teal, while reads mapping the Bradyrhizobium USDA110 genome are shown in purple. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth. Nodules from plants collected at 2 days past first treatment (dpt) received one high nitrogen treatment (50 mM NH4NO3), while those collected at 4 dpt received two treatments, one at 0 dpt and another at 2 dpt. The data encompasses nodules from soybean plants aged 4 weeks post inoculation (wpi) to 7 wpi.

[0139] FIG. 52A. Distinct size distributions of soybean and Bradyrhizobium small RNAs in nodules. The size distribution of small RNA (sRNA) reads mapping to the soybean genome Gmax_W82 v4.a1 . The data is organized vertically from 4 weeks post inoculation (wpi) to 7 wpi, and horizontally from 0 days past first treatment (dpt) to 4 dpt. Each bar plot shows the abundance of sRNA reads, with the x-axis representing sRNA size, ranging from 10- to 50- nucleotides (nt) and the y-axis indicating sRNA abundance in reads per million (RPM). Different colors in the bar plots represent distinct biological replicates.

[0140] FIG. 52B. Distinct size distributions of soybean and Bradyrhizobium small RNAs in nodules. The size distribution of small RNA (sRNA) reads mapping to the Bradyrhizobium genome. The data is organized vertically from 4 weeks post inoculation (wpi) to 7 wpi, and horizontally from 0 days past first treatment (dpt) to 4 dpt. Each bar plot shows the abundance of sRNA reads, with the x-axis representing sRNA size, ranging from 10- to 50-nucleotides (nt) and the y-axis indicating sRNA abundance in reads per million (RPM). Different colors in the bar plots represent distinct biological replicates.

[0141] FIG. 53. Nitrogen treatments do not significantly alter the source of plant or bacterial small RNAs in nodules. This figure depicts the genomic origin of small RNA (sRNA) reads that mapped to the Glycine max (Gma) cv. W82 and Bradyrhizobium diazoefficiens (Bdi) LISDA110 genomes. The x-axis represents the week post inoculation (wpi) ranging from 4 wpi to 7 wpi, and days after first treatment (dpt) ranging from 0 dpt to 4 dpt. The y-axis indicates the cumulative abundance of sRNAs in reads per million (RPM). Each genome feature is represented by a distinct color: blue-green shades for features of the Bradyrhizobium genome, including coding regions (Bdi_cds), ribosomal RNAs (Bdi_rRNAs), and transfer RNAs (Bdi_tRNAs); and brown shades for features of the soybean genome, including coding regionsPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web(Gma_cds), microRNAs (Gma_miRNAs), ribosomal RNAs (Gma_rRNAs), transacting siRNAs genes (Gma_TAS), transposable elements (Gma_TE), and transfer RNAs (Gma_tRNAs). Each bar plot contains three biological replicates.

[0012] FIG. 54. Soybean miRNAs are mostly downregulated in nodules following high nitrogen treatments. Differentially accumulated (DA) miRNAs in nodules following high nitrogen treatments.

[0143] FIG. 54A-B. Soybean miRNAs are mostly downregulated in nodules following high nitrogen treatments. Differentially accumulated (DA) miRNAs in nodules following high nitrogen treatments. Stacked bar plot illustrating the distribution of DA miRNAs, with upregulated miRNAs in red and downregulated miRNAs in blue.

[0144] FIG. 54B. Soybean miRNAs are mostly downregulated in nodules following high nitrogen treatments. Upset plot showing DA miRNAs shared across each treated vs. untreated comparison, with the intersection matrix at the bottom and a vertical histogram at the top displaying the number of miRNAs in each combination. miRNAs shared by all comparisons (n=8) are highlighted orange.

[0145] FIG. 54C. Soybean miRNAs are mostly downregulated in nodules following high nitrogen treatments. Heatmaps display average sRNAseq-derived FPKM values for the 8 DA miRNAs shared between all treated vs. untreated comparisons. Light yellow indicates low average FPKM values (lowest miRNA expression), orange represents moderate levels of miRNA expression, and dark red denotes high average FPKM values (highest miRNA expression). miRNA expression values are sorted by row and clustered by similar expression levels.

[0146] FIG. 54D. Soybean miRNAs are mostly downregulated in nodules following high nitrogen treatments. Heatmaps display average sRNAseq-derived FPKM values for the 5 miRNAs consistently upregulated but not always DA. Light yellow indicates low average FPKM values (lowest miRNA expression), orange represents moderate levels of miRNA expression, and dark red denotes high average FPKM values (highest miRNA expression). miRNA expression values are sorted by row and clustered by similar expression levels.

[0147] FIG. 54E. Soybean miRNAs are mostly downregulated in nodules following high nitrogen treatments. Heatmaps display average sRNAseq-derived FPKM values for the 17PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web miRNAs consistently downregulated but not always DA. Light yellow indicates low average FPKM values (lowest miRNA expression), orange represents moderate levels of miRNA expression, and dark red denotes high average FPKM values (highest miRNA expression). miRNA expression values are sorted by row and clustered by similar expression levels.

[0148] FIG. 55A-55B. Minority of PHAS loci (28%) in soybean nodules respond to high nitrogen treatments. Differentially accumulated (DA) PHAS (phased secondary siRNA “phasiRNA”) loci in nodules following high nitrogen treatments (n=23). (A) Stacked bar plot illustrating the distribution of DA PHAS loci, with upregulated loci in red (n=12) and downregulated loci in blue (n=11 ).

[0149] FIG. 55B. Minority of PHAS loci (28%) in soybean nodules respond to high nitrogen treatments. Table showing counts of PHAS loci across treated vs. untreated comparisons, indicated on the x-axis, with nodule age in weeks post inoculation (wpi) and days past first treatment (dpt) as sample identifiers.

[0150] FIG. 55C. Minority of PHAS loci (28%) in soybean nodules respond to high nitrogen treatments. Heatmap representing the fold change (Iog2 scale) of DA PHAS loci overlapping genomic coding regions (n=7).

[0151] FIG. 55D. Minority of PHAS loci (28%) in soybean nodules respond to high nitrogen treatments. Heatmap representing fold change (Iog2 scale) of DA PHAS loci overlapping non-coding regions (n=16). Blue denotes a negative fold change, while red denotes a positive fold change.

[0152] FIG. 56A. Treated soybean nodules are enriched in Glutamic acid (Glu) tRNAs. Stacked bar plot illustrating the response of soybean tRNA genes in nodules to high nitrogen treatments. Reads mapping tRNAs are grouped by individual tRNA anticodon, represented on the x-axis, and the y-axis shows the normalized abundance of tRNA genes in each sample. Each color in the bar plots represents a different nodule stage in weeks post inoculation (wpi) and days past first treatment (dpt), including three biological replicates.

[0153] FIG. 56B. Treated soybean nodules are enriched in Glutamic acid (Glu) tRNAs. Stacked bar plot of reads mapping tRNAs, separated by treatment and indicated by leaf age in wpi and dpt. The x-axis represents the tRNA genes by their amino acid and anticodon, whilePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web the y-axis shows the abundance in reads per million (RPM). Each color in the bar plots represents a different biological replicate.

[0154] FIG. 57 A. Bacterial tRNA size distribution in nodules. Size distribution of small RNA reads mapping to Bradyrhizobium tRNA genes across specific treated and untreated nodule samples, from 4 weeks post inoculation (wpi) to 7 wpi and from 0 days past first treatment (dpt) to 4 dpt. The x-axis represents the size of the tRNA, ranging from 10 to 50 nucleotides. The y-axis shows the abundance in reads per million (RPM). Each color in the bar plots represents a different biological replicate.

[0155] FIG. 57B. Bacterial tRNA size distribution in nodules. Size distribution of small RNA reads mapping to Bradyrhizobium tRNA genes, focusing on reads ranging from 18 to 24 nucleotides. Each bar plot contains data from the same treated and untreated samples, with the x-axis representing the tRNA fragment size and the y-axis showing the abundance in reads per million (RPM). Each color in the bar plots represents a different biological replicate.

[0156] FIG. 58A. The majority of soybean leaf sRNAs originate from coding regions and ribosomal RNA. Small RNA (sRNA) sequencing data from treated and untreated soybean leaves collected from the same plants as the nodule samples were analyzed. (A) The reads were mapped to the soybean (Glycine max W82 v4.a1 ) genome. The y-axis shows the percentages of reads mapped from each biological replicate’s (BR) sRNA library, represented on the x-axis. Samples for sRNA libraries were obtained from treated and untreated soybean plants spanning 4 weeks post inoculation (wpi) to 7 wpi, and from 0 days past first treatment (dpt) to 4 dpt.

[0157] FIG. 58B. The majority of soybean leaf sRNAs originate from coding regions and ribosomal RNA. The genomic origin of sRNA reads mapping to the soybean genome is depicted. Each genomic feature is represented by a distinct color. Features include: coding regions (Gma_cds), microRNAs (Gma_miRNAs), ribosomal RNAs (Gma_rRNAs), transacting siRNAs genes (Gma_TAS), transposable elements (Gma_TE), and transfer RNAs (Gma_tRNAs). Each bar plot contains three biological replicates.

[0158] FIG. 58C. The majority of soybean leaf sRNAs originate from coding regions and ribosomal RNA. Small RNA (sRNA) sequencing data from treated and untreated soybean leaves collected from the same plants as the nodule samples were analyzed. The sizePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web distribution of sRNA reads mapping to the soybean genome across specific treated and untreated leaf samples is shown. The x-axis represents the size of the sRNA, ranging from 10 to 50 nucleotides. The y-axis shows the abundance in reads per million (RPM). Each color in the bar plots represents a different biological replicate.

[0159] FIG. 59A. Soybean leaves are enriched in 21 nucleotide miRNAs and phasiRNAs. The size distribution of leaf small RNAs (sRNAs) mapping to specific genomic features is shown and it includes micro RNA (miRNA). The x-axis represents the size of the sRNA, ranging from 10 to 50 nucleotides. The y-axis indicates the abundance in reads per million (RPM). Each color in the bar plots represents a different biological replicate, with each bar plot containing data from three biological replicates. Leaf samples ranged from 4 weeks post inoculation (wpi) to 7 wpi and from 0 days past first treatment (dpt) to 4 dpt. High nitrogen treatments consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0160] FIG. 59B. Soybean leaves are enriched in 21 nucleotide miRNAs and phasiRNAs. The size distribution of leaf small RNAs (sRNAs) mapping to specific genomic features is shown and it includes phased secondary, small interfering RNA (phasiRNA). The x- axis represents the size of the sRNA, ranging from 10 to 50 nucleotides. The y-axis indicates the abundance in reads per million (RPM). Each color in the bar plots represents a different biological replicate, with each bar plot containing data from three biological replicates. Leaf samples ranged from 4 weeks post inoculation (wpi) to 7 wpi and from 0 days past first treatment (dpt) to 4 dpt. High nitrogen treatments consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0161] FIG. 59C. Soybean leaves are enriched in 21 nucleotide miRNAs and phasiRNAs. The size distribution of leaf small RNAs (sRNAs) mapping to specific genomic features is shown and it includes ribosomal RNA (rRNA). The x-axis represents the size of the sRNA, ranging from 10 to 50 nucleotides. The y-axis indicates the abundance in reads per million (RPM). Each color in the bar plots represents a different biological replicate, with each bar plot containing data from three biological replicates. Leaf samples ranged from 4 weeks post inoculation (wpi) to 7 wpi and from 0 days past first treatment (dpt) to 4 dpt. High nitrogenPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web treatments consisted of 50 mM NH4NO3. All plants were grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0162] FIG. 60A. Age-dependent regulation of soybean miRNAs in leaves in response to high nitrogen. Differentially accumulated (DA) miRNAs in leaves following high nitrogen treatments. Stacked bar plot illustrating the distribution of DA miRNAs, with upregulated miRNAs in red and downregulated miRNAs in blue.

[0163] FIG. 60B. Age-dependent regulation of soybean miRNAs in leaves in response to high nitrogen. Differentially accumulated (DA) miRNAs in leaves following high nitrogen treatments. Heat map representing fold change (Iog2 scale) of miRNA that were DA at least at one time point (n=46). Blue denotes a negative fold change, while red denotes a positive fold change. An (*) asterisk indicates miRNA is DA.

[0164] FIG. 61 A. Leaves from treated soybeans are enriched in a diversity of tRNAs. Stacked bar plot illustrating the response of soybean tRNA genes in leaves to high nitrogen treatments. Reads mapping tRNAs are grouped by individual tRNA anticodon, represented on the x-axis, and the y-axis shows the normalized abundance of tRNA genes in each sample. Each color in the bar plots represents a different leaf stage in weeks post inoculation (wpi) and days past first treatment (dpt), including three biological replicates.

[0165] FIG. 61 B. Leaves from treated soybeans are enriched in a diversity of tRNAs. Stacked bar plot of reads mapping tRNAs, separated by treatment and indicated by leaf age in wpi and dpt. The x-axis represents the tRNA genes by their amino acid and anticodon, while the y-axis shows the abundance in reads per million (RPM). Each color in the bar plots represents a different biological replicate.

[0166] FIG. 62. Dynamic response of Lysin-motif receptor-like Kinase (LYK) genes during the nitrogen response. A Venn diagram illustrating the involvement of LYK genes implicated in various functions during nodule development and their differential expression during the nitrogen response in soybean (Glycine max cv. Williams-82) nodules under high nitrogen conditions. Arrows indicate upregulation (f) or downregulation (J.) in nodules. High nitrogen treatments consisted of 50 mM NH4NO3, applied at 0 and 2 days post-treatment (dpt) at 4, 5, and 6 weeks post-inoculation (wpi). All plants were initially grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0167] FIG. 63. Nodule Inception (NIN) genes responding to high nitrogen are also implicated in senescence. A Venn diagram illustrating the involvement of NIN genes implicated in various functions during nodule development and their differential expression during the nitrogen response in soybean (Glycine max cv. Williams-82) nodules under high nitrogen conditions. Arrows indicate upregulation (f) or downregulation (|) in nodules. High nitrogen treatments consisted of 50 mM NH4NO3, applied at 0 and 2 days post-treatment (dpt) at 4, 5, and 6 weeks post-inoculation (wpi). All plants were initially grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0168] FIG. 64. Dynamic regulation of NIN-Like Protein (NLP) genes in response to high nitrogen reveals majority's involvement in senescence. A Venn diagram illustrating the involvement of NIN genes implicated in various functions during nodule development and their differential expression during the nitrogen response in soybean (Glycine max cv. Williams-82) nodules and leaves under high nitrogen conditions. Arrows indicate upregulation (f) or downregulation (|) in nodules and leaves, respectively, with a single arrow indicating regulation specific to nodules. High nitrogen treatments consisted of 50 mM NH4NO3, applied at 0 and 2 days post-treatment (dpt) at 4, 5, and 6 weeks post-inoculation (wpi). All plants were initially grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0169] FIG. 65. MiR399 miRNAs dominate the nitrogen response in nodules and leaves. A Venn diagram illustrating the involvement of miRNAs implicated in nitrogen fixation and their differential accumulation during the nitrogen response in soybean (Glycine max cv. Williams- 82) nodules and leaves under high nitrogen conditions. The diagram highlights the significant roles of the miR399 family in this process, along with other miRNAs from families associated with nitrogen fixation. Arrows indicate upregulation (J) or downregulation (J.) in nodules and leaves, respectively, with a single arrow indicating regulation specific to nodules. High nitrogen treatments consisted of 50 mM NH4NO3, applied at 0 and 2 days post-treatment (dpt) at 4, 5, and 6 weeks post-inoculation (wpi). All plants were initially grown under low nitrogen conditions (0.5 mM KNO3) during germination and early growth.

[0170] FIG. 66A. Leaf Expression Ratio for Nitrogen-Fixation Status (LERN-FS). LERN- FS provides a non-destructive and rapid assessment of nitrogenase activity usingPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web aboveground leaf samples from a single plant at a single time point. The LERN-FS method offers a valuable tool for researchers and farmers to monitor nitrogen fixation status, providing insights into plant health and optimizing nitrogen use efficiency. This method involves analyzing the expression of soybean genes BHLH13 (Glyma.03G258100) and HIRD11 -like (Glyma.16G037900). Box plots illustrate RNAseq-derived FPKM values for both genes in treated and untreated leaves. , with light green indicating untreated samples grown under low nitrogen condtions (0.5 mM KNO3) and dark green indicating treated samples grown under high nitrogen contions (50 mM NH4NO3) from 4 weeks post inoculation (wpi) to 6 wpi, measured at 0 days past treatment, 2 dpt, and 4 dpt. The 4 dpt samples received high nitrogen treatment at 0 dpt and 2 dpt.

[0171] FIG. 66B. Leaf Expression Ratio for Nitrogen-Fixation Status (LERN-FS). LERN- FS provides a non-destructive and rapid assessment of nitrogenase activity using aboveground leaf samples from a single plant at a single time point. The LERN-FS method offers a valuable tool for researchers and farmers to monitor nitrogen fixation status, providing insights into plant health and optimizing nitrogen use efficiency. This method involves analyzing the expression of soybean genes BHLH13 (Glyma.03G258100) and HIRD11 -like (Glyma.16G037900). (B) Box plot shows the leaf expression ratio of BHLH13 FPKM to HIRD11 -like FPKM from three individual biological replicates per time point, where values above 0.5 (purple dashed line) suggest opitimal nitrogen fixation levels, and values below 0.5. indicate inhibition of nitrogen fixation due to developmental nodule senescence or high nitrogen levels.

[0172] FIG. 66C. Leaf Expression Ratio for Nitrogen-Fixation Status (LERN-FS). LERN- FS provides a non-destructive and rapid assessment of nitrogenase activity using aboveground leaf samples from a single plant at a single time point. The LERN-FS method offers a valuable tool for researchers and farmers to monitor nitrogen fixation status, providing insights into plant health and optimizing nitrogen use efficiency.This method involves analyzing the expression of soybean genes BHLH13 (Glyma.03G258100) and HIRD11-like (Glyma.16G037900). (C) Box plots display RNAseq-derived FPKM values for BHLH13 and HIRD11 -like genes in nodules during development, from 2 wpi to 10 wpi under low nitrogen conditions.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0173] FIG. 66D. Leaf Expression Ratio for Nitrogen-Fixation Status (LERN-FS). LERN- FS provides a non-destructive and rapid assessment of nitrogenase activity using aboveground leaf samples from a single plant at a single time point. The LERN-FS method offers a valuable tool for researchers and farmers to monitor nitrogen fixation status, providing insights into plant health and optimizing nitrogen use efficiency. This method involves analyzing the expression of soybean genes BHLH13 (Glyma.03G258100) and HIRD11 -like (Glyma.16G037900). Box plots illustrate RNAseq-derived FPKM values for both genes in treated and untreated nodules, with light green indicating untreated samples grown under low nitrogen condtions (0.5 mM KNO3) and dark green indicating treated samples grown under high nitrogen contions (50 mM NH4NO3) from 4 weeks post inoculation (wpi) to 6 wpi, measured at 0 days past treatment, 2 dpt, and 4 dpt. The 4 dpt samples received high nitrogen treatment at 0 dpt and 2 dpt.

[0174] FIG. 67. Schematic overview of the experimental design for non-destructive assessment of nitrogen fixation status in soybean.

[0175] FIG. 68. Schematic overview of the experimental design for generating expression data for the non-destructive assessment of nitrogen fixation status in soybean.

[0176] FIG. 69A. Plots showing the quantification of expression profiles of nine candidate biomarker genes in soybean leaf tissue under varying nitrogen conditions and time points. Each plot displays the RNAseq-derived FPKM values for one gene, with data representing the average expression from three biological replicates per sample. Downregulated genes (GR3.4, bHLH13, a / b hydrolase, SOS3-4) are shown. These expression patterns form the basis for subsequent gene expression ratio (GER) calculations used to assess nitrogen fixation status.

[0177] FIG. 69B. Plots showing the quantification of expression profiles of nine candidate biomarker genes in soybean leaf tissue under varying nitrogen conditions and time points. Each plot displays the RNAseq-derived FPKM values for one gene, with data representing the average expression from three biological replicates per sample. Genes are grouped according to their response to high nitrogen. Upregulated genes (GdAS1-1 , GdAS1 -2, MtN21 , cP450, HIRD11 -like) are shown.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0178] FIG. 70. Gene expression ratios (GERs) calculated for all possible pairs of downregulated and upregulated candidate biomarker genes in soybean leaves. The table displays GER values for each combination, with the numerator representing a downregulated gene (GR3.4, bHLH13, a / b hydrolase, SOS3-4) and the denominator representing an upregulated gene (GdAS1 -1 , GdAS1-2, MtN21 , cP450, HIRD11 -like). These GERs are used to distinguish between optimal and suppressed nitrogen fixation status based on their separation in untreated and treated samples.

[0179] FIG. 71. Plots showing the GERs of the bHLH / HIRD11 -like gene pair and corresponding nitrogen fixation status measured in the plants.DETAILED DESCRIPTION

[0180] The present disclosure is based in part on the surprising discovery that nitrogen fixation activity in the roots of legume plants can be accurately assessed by measuring gene expression in aboveground leaf tissue. The inventors discovered that the expression levels of a remarkably small set of genes in leaves, rather than in nodules or roots, can serve as reliable biomarkers for the nitrogen fixation status occurring belowground. Furthermore, they discovered that specific gene expression ratios (GERs) calculated from some of these leaf- expressed genes provide a highly accurate, non-destructive, and field-deployable method for determining whether nitrogen fixation in the roots is optimal or suppressed.I. Methods

[0181] One aspect of the present disclosure encompasses a non-destructive method for assessing nitrogen fixation status in legume plants. The method employs measurable biomarkers whose expression correlates with nodule function and responds dynamically to changes in soil nitrogen or nodule health. The rapid, sensitive assay of the instant disclosure based on gene expression or other molecular signatures in leaf tissue can provide real-time feedback for crop management decisions, enable precision fertilizer application, and support high-throughput screening in breeding programs aimed at improving symbiotic efficiency.Unlike traditional approaches, which require destructive sampling of roots or nodules and arePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web impractical for routine use by farmers, the methods described herein enable rapid, convenient, and non-invasive assessment of symbiotic nitrogen fixation status in standing crops.

[0182] In one aspect, the method comprises calculating a gene expression ratio (GER) in a leaf tissue sample and comparing the GER to a predetermined nitrogen threshold GER (GERNT), wherein a GER equal to or below the GERNT indicates suppressed nitrogen fixation levels. In some aspects, a GER above the GERNT indicates optimal nitrogen fixation levels.

[0183] In another aspect, the method comprises determining the expression level of a gene in a leaf tissue sample, comparing the expression level of the gene to a predetermined threshold expression level for the gene, and determining that the plant has suppressed nitrogen fixation status when the measured expression level is equal to or below the predetermined threshold. The expression level of a gene is the expression level of the gene, the expression level of a reporter under the regulatory control of the gene, or both.

[0184]

[0185] wherein the tissue sample is a punch biopsy, excised leaflet, or sap extract.(a) Legumes and nitrogen fixation

[0186] A legume is a plant in the family Fabaceae (or Leguminosae), or the fruit or seed of such a plant. When used as a dry grain, the seed is also called a pulse. Farmed legumes can belong to many agricultural classes, including forage, grain, blooms, pharmaceutical / industrial, soil-enhancing fallow / green manure, and timber species. Well- known legumes include beans, locust bean, fenugreek, soybean (Glycine), chickpeas, peanuts, garden beans, cowpea, mungbean, lentils, lupins, mesquite, carob, guar, tamarind, alfalfa, lima bean, fava bean, lentils, chickpea, crown vetch (Vicia sp.), hairy vetch, stylo (stylosanthes), adzuki bean, Leucaena, Albizia, trifolium, common bean (Phaseolus sp.), field bean (Pisum sp.), clover (Melilotus sp.), Lotus, trefoil, lens, and false indigo. Legumes are notable in that most of them have symbiotic nitrogen-fixing bacteria in structures called root nodules. For that reason, they play a key role in crop rotation.

[0187] Legume root nodules are specialized de novo organs that develop in response to infection by nitrogen-fixing soil bacteria, collectively known as rhizobia. These nodules provide a unique microenvironment in which rhizobial nitrogenase enzymes convert atmosphericPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web nitrogen (N2) into ammonia (NH3), a form of nitrogen that is readily assimilated by the plant. The process of nodule formation and function is highly regulated and involves a dynamic exchange of chemical signals, hormones, and transcriptional networks between the host plant and its symbiotic bacteria.

[0188] Nodules can be classified into two main types: determinate and indeterminate. Determinate nodules, such as those found in soybean (Glycine max) and some other legumes, originate from the central cortex and possess a transient meristem that is only active during early nodule development. As a result, determinate nodules are typically spherical in shape, have a relatively short lifespan, and lack distinct developmental zones. In contrast, indeterminate nodules, which are characteristic of species like clover and Medicago, arise from the inner cortex and maintain a persistent meristem at the nodule tip. Indeterminate nodules are elongated and display clear zonation, with regions dedicated to cell division, infection, nitrogen fixation, and senescence.

[0189] The development of nodules proceeds through several distinct stages. In the early phase, host plants secrete flavonoids into the rhizosphere, which are recognized by compatible rhizobia, triggering the production of Nod factors. These signaling molecules initiate a cascade of events in the root, including root hair curling, infection thread formation, and cortical cell division. As rhizobia enter the root and are released into plant cells, they differentiate into bacteroids, the specialized form capable of nitrogen fixation. Within the mature nodule, bacteroids are surrounded by a plant-derived peribacteroid membrane, forming the symbiosome, which facilitates nutrient exchange and maintains the low-oxygen environment required for nitrogenase activity.

[0190] Nitrogen fixation activity within nodules is not constant but varies with nodule age and environmental conditions. In determinate nodules, nitrogenase activity typically peaks during the mid-developmental stage, around 4 to 6 weeks post-inoculation, and then gradually declines as the nodule ages and enters senescence. Indeterminate nodules, due to their persistent meristem, can sustain nitrogen fixation over a longer period, with new cells continuously entering the fixation zone as older cells progress toward senescence. Nodule senescence is characterized by a decline in nitrogenase activity, breakdown of symbiotic structures, and eventual cessation of nitrogen fixation.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0191] The formation, maintenance, and senescence of nodules are tightly regulated by both local and systemic plant signals, including the autoregulation of nodulation (AON) pathway and nitrogen status feedback mechanisms. This regulation ensures that the plant balances the energetic costs of supporting symbiotic nitrogen fixation with its overall growth and nutrient requirements, particularly in response to external nitrogen availability.

[0192] Traditional methods for assaying nitrogen fixation and nitrogenase activity include the acetylene reduction assay (ARA), which measures the conversion of acetylene to ethylene by nitrogenase in excised root systems or nodules, as well as15N isotope dilution or incorporation methods, gas-exchange monitoring, and visual or manual nodule counts. These approaches are often labor-intensive, require specialized equipment, and typically involve destructive sampling of the root system. In addition, traditional molecular assays for assessing nitrogen fixation status have primarily focused on measuring the expression of nodule-specific or root-specific genes, such as those involved in nodulation or encoding components of the nitrogenase enzyme complex. These molecular approaches also generally require destructive sampling of root or nodule tissue and do not provide a convenient means to assess nitrogen fixation status using above-ground plant material.

[0193] Methods of the instant disclosure can comprise assessing or determining the nitrogen fixation status in legume plants. As used herein, “nitrogen fixation status” refers to the level or extent of biological nitrogen fixation occurring in a legume plant as a result of symbiotic activity in root nodules. Nitrogen fixation status can be described as “optimal nitrogen fixation”, meaning the plant is actively and efficiently converting atmospheric nitrogen to ammonia via symbiotic bacteria, or as “suppressed nitrogen fixation”, meaning the rate or extent of nitrogen fixation is reduced or inhibited. Optimal and suppressed methods of nitrogen fixation can and will vary based on the legume species, growth conditions, nodule type (determinate or indeterminate), and developmental stage of the plant and nodules, and can be determined exprimentally.

[0194] Methods of determining nitrogen fixation status in root tissue of a plant are known to individuals of skill in the art. For instance, nitrogen fixation status can be determined by measuring nitrogenase activity (such as by the acetylene reduction assay), the incorporation of labeled nitrogen isotopes (e.g.,15N isotope dilution or15N? incorporation), analysis of totalPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web nitrogen content, measurement of ammonia or ureide accumulation, gas-exchange monitoring (e.g., hydrogen or nitrogen gas flux), gene expression analysis of nitrogen fixation-related genes, protein abundance of nitrogenase or associated proteins, reporter gene assays, or other direct or indirect biochemical, molecular, or physiological indicators of nitrogen fixation in the plant. In some aspects, nitrogen fixation status of a plant is determined by measuring nitrogenase activity. In some aspects, nitrogenase activity is measured using the acetylene reduction assay (ARA), which quantifies the conversion of acetylene to ethylene by nitrogenase in excised root systems or nodules.

[0195] When nitrogen fixation status is measured using the ARA method, optimal nitrogen fixation can be nitrogenase activity below about 8,000 nmol ethylene produced per mg nodule per hour or above, or can be nitrogenase activity ranging from about 8,000 to about 25,000 nmol ethylene produced per mg nodule per hour, as observed in plants grown under low or minimal external nitrogen conditions. In some aspects, when nitrogen fixation status is measured using the ARA method, optimal nitrogen fixation can be nitrogenase activity below about 8,000 nmol ethylene produced per mg nodule per hour or above, as observed in plants grown under low or minimal external nitrogen conditions.

[0196] When nitrogen fixation status is measured using the ARA method, suppressed nitrogen fixation can be about 4,000 nmol ethylene produced per mg nodule per hour or below, or can range from about 2,000 to about 4,000 nmol ethylene produced per mg nodule per hour, as observed in plants grown under external nitrogen conditions that inhibit symbiotic nitrogen fixation. In some aspects, suppressed nitrogen fixation can be nitrogenase activity below approximately 4,000 nmol ethylene produced per mg nodule per hour, as observed in plants grown under external nitrogen conditions that inhibit symbiotic nitrogen fixation.

[0197] Suppressed nitrogen fixation levels can be due to stress conditions selected from high levels of available nitrogen conditions (nitrogen stress), drought, salinity, heat, cold, pathogen infection, or nutrient deficiency. In some aspects, suppressed nitrogen fixation is due to high levels of available nitrogen conditions. As used herein, “available nitrogen” refers to the concentration of nitrogen in the soil or growth medium that is accessible for plant uptake, including forms such as nitrate (NO3") and ammonium (NH4+). High levels of available nitrogen conditions are defined as external nitrogen concentrations sufficient to suppress symbioticPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web nitrogen fixation. External nitrogen concentrations sufficient to suppress symbiotic nitrogen fixation can and will vary based on the legume species, growth conditions, nodule type (determinate or indeterminate), and developmental stage of the plant and nodules. In some aspects, the nodules are determinate nodules. In some aspects, high levels of available nitrogen sufficient to suppress symbiotic nitrogen fixation can range from about 10 mM to about 100 mM total available nitrogen. In some aspects, high levels of available nitrogen sufficient to suppress symbiotic nitrogen fixation can range from about 40 mM to about 60 mM ammonium nitrate (NH4NO3) or higher.

[0198] In some aspects, the legume plant comprises indeterminate nodules. In some aspects, the legume plant comprises determinate nodules. When the legume plant comprises determinate nodules, the nitrogen fixation status can be assessed at the stage of determinate nodule development when nodules are fully formed and actively fixing nitrogen. Nitrogen fixation can be assessed at the stage of nodule development when nodules are fully formed and actively fixing nitrogen. In some aspects, when the legume plant comprises determinate nodules, the GERs are calculated at 4-6 weeks post inoculation (wpi) at 0 days post treatment (dpt), 2 dpt, and 4 dpt.

[0199] The legume plant can be soybean, alfalfa, clover, lentil, pea, or vetch. In some aspects, the plant is a soybean (Glycine sp.). Non-limiting examples of Glycine sp. include Glycine hispida, Glycine max, and Glycine soja. In another aspect, the plant is Glycine hispida. In some aspects, the soybean plant is a domesticated soybean plant. In one aspect, the plant is Glycine max. In some aspects, the GERs are calculated at 4-6 weeks post inoculation (wpi) with nitrogen-fixing bacteria at 0 days post treatment (dpt), 2 dpt, and 4 dpt with nitrogen-containing fertilizer.(b) Expression

[0200] Methods of the instant disclosure can comprise determining the expression of one or more genes in plant tissues, including but not limited to leaf tissue. As used herein, the term “gene” refers to a polynucleotide comprising at least one open reading frame (ORF) encoding a polypeptide, together with any associated sequences that contribute to its expression, regulation, or processing. Such sequences can include promoters, enhancers,PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web introns, untranslated regions (UTRs), terminators, or other regulatory elements, alone or in any combination. The polynucleotide can comprise full-length genes and homologs thereof, allelic variants, splice variants, fragments, and synthetic or recombinant forms of the genes.

[0201] As used herein, the terms “gene expression” or “polynucleotide expression” are used interchangeably and broadly refer to the presence, amount, or activity of a polynucleotide or a product encoded thereby. Polynucleotide expression can thus encompass levels of RNA transcripts, levels of polypeptides translated from the polynucleotide, or the activity of a reporter molecule operably linked to one or more regulatory sequences associated with the polynucleotide. Polynucleotide expression can further encompass any detectable biochemical, molecular, or physiological effect that correlates with the activity of the polynucleotide or its encoded product.

[0202] The methods described herein are not limited to any single detection platform and can be implemented using a wide variety of molecular, biochemical, and cellular assays. In some aspects, expression is determined at the nucleic acid transcription level. Non-limiting examples of methods of polynucleotide expression suitable for methods of the instant disclosure include amplification-based techniques such as quantitative reverse transcription PCR, droplet digital PCR, microfluidic digital PCR, or isothermal amplification systems including loop-mediated isothermal amplification, nucleic acid sequence-based amplification, recombinase polymerase amplification, or transcription-mediated amplification. Other nonlimiting examples include hybridization-based methods such as Northern blotting, dot or slot blotting, or capture-hybridization with probe-based digital counting. Sequencing approaches can also be employed, including bulk RNA sequencing, targeted RNA sequencing panels, long-read sequencing, small RNA sequencing, cap analysis gene expression, and three-prime end counting methods. In situ detection of transcripts can be performed using RNA in situ hybridization, RNAscope®, hybridization chain reaction fluorescence in situ hybridization, or spatial transcriptom ics platforms. Nascent transcription can further be evaluated by metabolic labeling with modified nucleotides such as 4-thiouridine or 5-ethynyl uridine, global run-on sequencing, or transient transcriptome sequencing. Translation-coupled measures such as ribosome profiling, polysome profiling, or translating ribosome affinity purification can also provide useful indicators of polynucleotide expression. In some aspects, an expression level isPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web an RNAseq-derived metric. In some aspects, an expression level is an RNAseq-derived average Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values.

[0203] In other aspects, expression is determined at the protein level by detecting the presence, amount, or activity of a polypeptide encoded by the polynucleotide. Non-limiting examples of protein detection methods include immunoassays such as Western blotting, enzyme-linked immunosorbent assays, electrochemiluminescence immunoassays, lateral-flow assays, proximity ligation assays, and proximity extension assays. Mass spectrometry-based approaches can also be used, including targeted proteomics with selected or parallel reaction monitoring, discovery proteomics using label-free or data-independent acquisition, and immunoprecipitation followed by mass spectrometry. In situ or cell-based detection can be carried out using immunohistochemistry, immunofluorescence in tissue sections, antibody staining of protoplasts, flow cytometry, or imaging cytometry. Expression can also be inferred from polypeptide function, for example, by enzyme activity assays that measure substrate turnover, aptamer-based binding assays, or biosensor platforms.

[0204] In additional aspects, expression is determined using a reporter system under regulatory control of the polynucleotide. As used herein, “under regulatory control” refers to operable linkage of a reporter sequence to a regulatory region such that the activity of the reporter reflects the transcriptional or translational activity of the polynucleotide. Non-limiting examples of reporter architectures include transcriptional fusions, translational fusions, dualreporter systems, destabilized reporters with short half-lives, and split-reporter complementation systems. Reporter modalities can include enzymatic reporters such as [3- glucuronidase, luciferases, alkaline phosphatase, or [3-galactosidase; fluorescent proteins such as green fluorescent protein, yellow fluorescent protein, cyan fluorescent protein, or red fluorescent proteins; chromogenic reporters; and biosensor-based reporters such as Forster resonance energy transfer pairs, riboswitch-controlled constructs, or CRISPR-based recorders. Detection can be achieved by luminometry, fluorimetry, imaging with CCD or CMOS devices, histochemical staining, or by ratiometric analysis against a control reporter.

[0205] Further aspects encompass indirect or surrogate approaches to determining gene expression. Non-limiting examples include phenotypic proxies such as chlorophyll fluorescence parameters or hyperspectral reflectance profiles, which can be correlated withPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web expression through trained computational models. Expression can also be inferred by measuring metabolites whose levels are directly influenced by the encoded polypeptide, including by liquid chromatography (mass spectrometry or gas chromatography) mass spectrometry. Biosensor devices can be configured to provide electrochemical, optical, or impedance-based readouts when bound to nucleic acid or protein targets. Chromatin accessibility assays and transcription factor occupancy assays can be employed as proxies of transcriptional competence. Multi-omics approaches can further integrate two or more detection modalities, such as RNA and protein measurements, reporter and RNA measurements, or metabolite and transcript measurements.

[0206] Accordingly, methods of the present disclosure can use a broad and flexible framework for determining expression of polynucleotides in plant tissues. Methods can be selected based on throughput, sensitivity, or resolution requirements, and can be applied individually or in combination. Non-limiting examples described herein ensure that expression can be evaluated comprehensively, whether at the polynucleotide level, the protein level, through reporters, or through indirect physiological or biochemical proxies.

[0207] In some aspects, an expression level of a polynucleotide is an RNAseq-derived metric. In some aspects, an expression level of a polynucleotide is an RNAseq-derived average Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values.(c) Threshold expression level

[0208] One aspect of the instant disclosure encompasses a non-destructive method for assessing nitrogen fixation status in legume plants using expression levels of polynucleotides identified by the inventors as being markers of nitrogen fixation activity in roots and nodules when the level of expression is measured in leaves. As described herein above, the inventors identified that a surprisingly small number of genes among genes whose differential expression levels in leaves can indicate the nitrogen fixation activity in roots of that plant. The legume plants can be as described in Section l(a) herein above.

[0209] Designations of the polynucleotides of the instant disclosure are as listed in column 1 of Table A and differential expression of the polynucleotides are as listed in column 2 of Table A.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0210] Accordingly, a method of the instant disclosure comprises measuring the expression level in a leaf tissue sample of any combination of one or more polynucleotides identified in Table A to assess the nitrogen fixation status in root tissue of the plant. As shown in Table A, column 2, the GR3.4, the bHLH13, the a / b hydrolase, and the SOS3-4 polynucleotides are predetermined to be downregulated and the GdAS1 -1 , the GdAS1-2, the MtN21 , the cP450, and the HIRD11 -like polynucleotides are predetermined to be upregulated in plants grown under conditions that suppress nitrogen fixation.

[0211] The method further comprises determining that the plant has suppressed nitrogen fixation when the expression level of any one or more of the downregulated polynucleotides is equal to or below a predetermined untreated threshold expression level for the respective polynucleotide, the expression level of any one or more of the upregulated polynucleotides is equal to or above a predetermined untreated threshold expression level for the respective polynucleotide, or any combination of one or more downregulated or upregulated polynucleotide. Alternatively, when the treated threshold expression level is determined based on expression of the polynucleotide in plants grown under conditions that suppress nitrogen fixation, the method further comprises determining that the plant has optimalPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web nitrogen fixation when the expression level of any one or more of the downregulated polynucleotides is equal to or above a predetermined treated threshold expression level for the respective polynucleotide, or the expression level of any one or more of the upregulated polynucleotides is equal to or below a predetermined treated threshold expression level for the respective polynucleotide, or any combination of one or more downregulated or upregulated polynucleotide. In some aspects, the method comprises determining that the plant has suppressed nitrogen fixation when the expression level of any one or more of the downregulated polynucleotides is equal to or below a predetermined untreated threshold expression level for the respective polynucleotide, the expression level of any one or more of the upregulated polynucleotides is equal to or above a predetermined untreated threshold expression level for the respective polynucleotide, or any combination of one or more downregulated or upregulated polynucleotide.

[0212] The untreated threshold expression level is determined based on expression of the polynucleotide in plants grown under conditions supporting optimal nitrogen fixation and the treated threshold expression level is determined based on expression of the polynucleotide in plants grown under conditions that suppress nitrogen fixation. In some aspects, the untreated and treated threshold expression level for each polynucleotide is as shown in columns 3 and 4 of Table A, respectively.

[0213] In some aspects, the method further comprises predetermining the threshold expression levels of a polynucleotide. Predetermining the threshold expression level of a polynucleotide can comprise growing legume plants under conditions supporting optimal nitrogen fixation, under conditions that suppress nitrogen fixation, or both. The method further comprises determining expression levels of the polynucleotide in leaf samples of the grown plants and measuring nitrogen fixation activity in root samples of the plants.

[0214] When the method further comprises predetermining a threshold expression level of a polynucleotide, the method further comprises setting the untreated threshold expression level for a downregulated polynucleotide as the expression level of the polynucleotide in a plant grown under conditions supporting optimal nitrogen fixation below which nitrogen fixation is suppressed, and for an upregulated polynucleotide as the expression level of the polynucleotide in a plant grown under conditions supporting optimal nitrogen fixation abovePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web which nitrogen fixation is suppressed, based on comparison to nitrogen fixation activity in the plants.

[0215] Alternatively, when the method further comprises predetermining the threshold expression level of a polynucleotide, the method further comprises setting the treated threshold expression level for a downregulated polynucleotide as the expression level measured under conditions that suppress nitrogen fixation above which nitrogen fixation is suppressed, and for an upregulated polynucleotide as the expression level measured under conditions that suppress nitrogen fixation below which nitrogen fixation is suppressed, based on comparison to nitrogen fixation activity in the plants.

[0216] According to methods of the instant disclosure, the expression level is the expression level of the polynucleotide, the expression level of a protein encoded by the polynucleotide, the expression level of a reporter under the regulatory control of the polynucleotide, or any combination thereof.

[0217] In some aspects, the threshold expression level for a polynucleotide of the instant disclosure is the untreated threshold expression level. In some aspects, the threshold expression level for a polynucleotide of the instant disclosure is the treated threshold expression level.

[0218] As the method relies on detecting differential expression levels of a polynucleotide in leaf tissue samples from plants grown under conditions that support optimal nitrogen fixation, conditions that suppress nitrogen fixation, or both, the expression of the polynucleotide can be influenced by any mechanism of gene regulation associated with that polynucleotide. Non-limiting examples of such regulatory mechanisms include transcriptional or translational control mediated by promoter or enhancer elements, terminators, 5' or 3' untranslated regions (UTRs), exons, introns, or other sequences within the polynucleotide.

[0219] Legume plants can be as described in Section l(a) herein above. In some aspects, a legume plant of the instant disclosure is a soybean (Glycine max) plant. In some aspects, the legume plant is a Glycine max cv. Williams-82. When the legume plant is soybean, polynucleotide of the instant disclosure comprise a soybean gene identified in Table A, or a variant, allele, fragment, or synthetic form thereof. In some aspects, the untreated andPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web treated threshold expression level of a polynucleotide in a soybean plant is as shown in Table A.

[0220] It will be noted that in addition to the specific polynucleotides described herein, polynucleotides of the instant disclosure include homologs, orthologs, and paralogs of such polynucleotides, as well as allelic variants, splice variants, and synthetic or recombinant derivatives thereof. A polynucleotide or encoded polypeptide can be considered encompassed if it is substantially identical to, or shares a specified degree of sequence identity with, a disclosed sequence. For instance, polynucleotides and polypeptides having at least about 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98%, 99%, or greater sequence identity to the disclosed polynucleotide or encoded polypeptide can be useful for use in methods of the instant disclosure. Homologous sequences identified in other plant species are also contemplated. The disclosure further encompasses functional equivalents of the disclosed polynucleotides, including sequences that retain the ability to serve as markers of the relevant biological state despite sequence variation.

[0221] Unless otherwise specified, “homologous gene” includes any gene that is evolutionarily related and maintains sufficient sequence identity and / or conserved functional domains such that it can be expected to perform a similar role in gene expression profiling. Accordingly, the disclosure is not limited to the exact nucleotide or amino acid sequences explicitly described, but includes variants and homologs within the above ranges of identity, as well as sequences exhibiting conserved motifs, domains, or regulatory elements.

[0222] It is also recognized that although the threshold expression levels described herein were determined experimentally in soybean, threshold expression levels for these polynucleotides could vary among different soybean varieties, as well as among other legume species and varieties, due to genetic background, environmental conditions, or physiological differences. As discovered by the inventors and described in this disclosure, threshold expression levels for these genes in other soybean varieties or in other legumes can be readily determined by experimentally measuring gene expression in leaf tissue and correlating those levels with measured nitrogen fixation activity under conditions supporting optimal or suppressed nitrogen fixation. Thus, the methods of the instant disclosure are broadlyPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web applicable to a range of legume species and varieties, with threshold values determined empirically for each context.

[0223] As used herein, the term “about,” when modifying a numerically defined parameter such as a threshold expression level in Table A, means that the parameter can vary by as much as 10% above or below the stated numerical value for that parameter. For example, a threshold expression level of “about 309” FPKM includes values from 278 to 340 FPKM. The use of “about” is intended to account for experimental variability, differences in measurement platforms, biological variation among samples, and other factors that can affect the precise determination of expression levels. Thus, the specific numbers provided in Table A are not absolute limits, but represent a range of values that are considered functionally equivalent for the purposes of the invention. In some aspects, “about” can encompass a range of ±5%, ±10%, or, where appropriate, a broader or narrower range as would be understood by one of skill in the art, provided that the measured expression level remains predictive of nitrogen fixation status as described herein.(d) Gene expression ratio (GER)

[0224] Another aspect of the instant disclosure encompasses a non-destructive method for assessing nitrogen fixation status in legume plants using polynucleotide expression ratios (GERs) of polynucleotides identified by the inventors as being markers of nitrogen fixation activity in roots and nodules. The legume plants can be as described in Section l(a) herein above. The polynucleotides can be as described in Section l(c) herein above. Methods of measuring polynucleotide expression to calculate GERs can be as described in Section l(b) herein above.

[0225] In addition to discovering differentially expressed genes, the inventors determined that some gene expression ratios using expression levels of specific pairs of polynucleotides can give even better results. Accordingly, a method of the instant disclosure comprises calculating a gene expression ratio (GER) for at least one polynucleotide pair selected from the polynucleotide pairs identified in Table B. The GER is a ratio of an expression level of a first polynucleotide of the pair to an expression level of a secondPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web polynucleotide of the pair, in a leaf tissue sample. The polynucleotide pair can be selected from the polynucleotide pairs identified in Table B.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0226] The method further comprises comparing the calculated GER for the polynucleotide pair to a corresponding maximum or minimum nitrogen fixation threshold GER (GERNFT) predetermined for said pair of polynucleotides. In some aspects, the method further comprises comparing the calculated GER for the polynucleotide pair to a corresponding maximum nitrogen fixation threshold GER (GERNFT) predetermined for said pair of polynucleotides. A maximum GERNFT represents a maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal and a calculated GER of a polynucleotide pair equal to or below the maximum GERNFT indicates suppressed nitrogen fixation. In some aspects, the method further comprises comparing the calculated GER for the polynucleotide pair to a corresponding minimum GERNFT predetermined for said pair of polynucleotides. A minimum GERNFT represents a minimum GER value above which nitrogen fixation is optimal and below which nitrogen fixation is suppressed, and a calculated GER of a polynucleotide pair equal to or above the minimum GERNFT indicates optimal nitrogen fixation.

[0227] The GERNFT of each polynucleotide pair correlates GER values with measured nitrogen fixation activity in plants and the expression level is the expression level of the polynucleotide, the expression level of a protein encoded by the polynucleotide, the expression level of a reporter under the regulatory control of the polynucleotide, or any combination thereof. In some aspects, the maximum and minimum GERNFT for the pairs of polynucleotides is as shown in Table B.

[0228] In some aspects, the method further comprises predetermining the maximum or minimum GERNFT of a polynucleotide pair. Predetermining the GERNFT of a polynucleotide pairPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web comprises the steps of (a) growing legume plants under low external nitrogen conditions that support optimal nitrogen fixation, and under external nitrogen conditions that suppress nitrogen fixation; (b) determining expression levels of each polynucleotide of a polynucleotide pair in leaf samples obtained from the plants after nitrogen fertilizer treatment; (c) measuring nitrogen fixation activity in root samples of the plants; (d) calculating a GER in the leaf tissue samples from plants grown under each growth condition; and (e) identifying the maximum GERNFT for the polynucleotide pair as the maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal; or identifying the minimum GERNFT for the polynucleotide pair as the minimum GER value above which nitrogen fixation is optimal and below which nitrogen fixation is suppressed. In some aspects, the plants are grown under a range of external nitrogen concentrations to determine the GERNFT for the polynucleotide pair.

[0229] In some aspects, the plants are grown under a range of external nitrogen concentrations ranging from external nitrogen concentrations that suppress nitrogen fixation to nitrogen concentrations that allow optimal nitrogen fixation. When the plants are grown under a range of external nitrogen concentrations, the method comprises identifying the maximum GER NFT for the polynucleotide pair as the maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal, or identifying the minimum GERNFT for the polynucleotide pair as the minimum GER value above which nitrogen fixation is optimal and below which nitrogen fixation is suppressed, wherein the maximum or minimum GERNFT is determined from the range of GERs corresponding to the transition between suppressed and optimal nitrogen fixation.

[0230] In some aspects, the external nitrogen conditions comprise the application of nitrogen fertilizer. External nitrogen conditions can be as described in Section l(a). The low external nitrogen conditions that support optimal nitrogen fixation can comprise about 0.5 mM available nitrogen. In some aspects, the external nitrogen conditions that suppress nitrogen fixation comprise about 100 mM available nitrogen.

[0231] Nitrogen fixation can be assessed at the stage of nodule development when nodules are fully formed and actively fixing nitrogen. Accordingly, the stage of nodule development when nodules are fully formed and actively fixing nitrogen can and will varyPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web depending on the type of nodule (determinate or indeterminate), the plant species or variety, the rhizobial strain, environmental conditions such as soil type, temperature, moisture, and nutrient availability, the age or developmental stage of the plant and nodules, the timing and method of inoculation, the presence or absence of abiotic or biotic stresses, and overall crop management practices among other factors.

[0232] In some aspects, the legume plant comprises indeterminate nodules. In other aspects, the legume plant comprises determinate nodules. When the legume plant comprises determinate nodules, the nitrogen fixation status can be assessed at the stage of determinate nodule development when nodules are fully formed and actively fixing nitrogen. In some aspects, the GERs are calculated at 4-6 weeks post inoculation (wpi) at 0 days post treatment (dpt) with nitrogen fertilizer, 2 dpt, and 4 dpt.

[0233] In some aspects, methods of the instant disclosure comprise comparing the calculated GER for the polynucleotide pair to a corresponding maximum nitrogen fixation threshold GER (GERNFT), wherein a calculated GER of a polynucleotide pair equal to or below the maximum GERNFT indicates suppressed nitrogen fixation.

[0234] In some aspects, methods of the instant disclosure comprise comparing the calculated GER for the polynucleotide pair to a corresponding minimum nitrogen fixation threshold GER (GERNFT) predetermined for said pair of polynucleotides, wherein a calculated GER of a polynucleotide pair equal to or above the minimum GERNFT indicates optimal nitrogen fixation.

[0235] Suppressed nitrogen fixation levels can be due to stress conditions selected from high levels of nitrogen conditions, drought, salinity, heat, cold, pathogen infection, or nutrient deficiency. In some aspects, suppressed nitrogen fixation levels are due to high levels of nitrogen conditions.

[0236] In some aspects, the legume plant is soybean. When the legume plant is soybean, the nitrogen fixation status can be assessed during the vegetative growth stage of the soybean plant, coinciding with peak nodule activity and optimal nitrogen fixation efficiency. Further, when the legume plant is soybean, the nitrogen fixation status is assessed at the stage of determinate nodule development when nodules are fully formed and actively fixing nitrogen. In some aspects, when the legume plant is soybean, the nitrogen fixation status isPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web assessed at around 5 to 6 weeks post-inoculation. In some aspects, each polynucleotide of the polynucleotide pairs comprises a soybean gene identified in Table B, or a variant, allele, fragment, or synthetic form thereof and the GERNFT for the pairs of polynucleotides can be as shown in Table B.

[0237] As used herein, the term “about,” when modifying a numerically defined parameter such as a gene expression ratio (GER) threshold in Table B, means that the parameter can vary by as much as 10% above or below the stated numerical value for that parameter. For instance, a GERNFT of “about 26” includes values from 23.4 to 28.6. The use of “about” is intended to account for experimental variability, differences in measurement platforms, biological variation among samples, and other factors that can affect the precise determination of GER values. Thus, the specific numbers provided in Table B are not absolute limits, but represent a range of values that are considered functionally equivalent for the purposes of the invention. In some aspects, “about” can encompass a range of ±5%, ±10%, or, where appropriate, a broader or narrower range as would be understood by one of skill in the art, provided that the measured GER remains predictive of nitrogen fixation status as described herein.(e) Determining nitrogen threshold

[0238] Yet another aspect of the instant disclosure encompasses a method of determining a nitrogen threshold for a legume plant. As used herein, the term “nitrogenthreshold” refers to the point where maximal symbiotic nitrogen fixation activity is achieved with the highest amount of applied nitrogen. This implies that at some level of applied nitrogen, the host plant balances both nitrogen uptake and symbiosis. Beyond this nitrogen-threshold, the plants favor nitrogen uptake over symbiosis, leading to diminished benefits from additional fertilizer. At this point, the profits obtained from higher yield gains are minimized by the high costs associated with nitrogen fertilizer.

[0239] The methods of the instant disclosure greatly simplify and accelerate the determination of the nitrogen threshold compared to traditional approaches, which required destructive sampling and labor-intensive biochemical assays. By enabling rapid, nondestructive assessment of nitrogen fixation status using gene expression measurements fromPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web leaf tissue, the claimed methods provide a practical, high-throughput, and field-deployable framework for identifying the nitrogen threshold specific to each context.

[0240] The methods comprise growing legume plants under untreated conditions and under a range of increasing nitrogen fertilizer concentrations. The methods then comprise determining expression levels of polynucleotides of Table A or any combination thereof and calculating a GER using expression levels of pairs of polynucleotides of Table B in plants grown under each growth condition. Based on these measurements, the methods comprise identifying the nitrogen threshold as the lowest nitrogen fertilizer concentration at which the GER indicates a significant reduction in nitrogen fixation status compared to untreated controls.

[0241] The legume plants can be as described in Section l(a) herein above. The polynucleotides can be as described in Section l(c) herein above. Methods of measuring polynucleotide expression to calculate GERs can be as described in Section l(b) herein above.

[0242] It is recognized that the nitrogen threshold is not a fixed value and can vary substantially among different legume species and even among varieties within a species. The specific nitrogen threshold for a given plant can be influenced by a range of genetic and physiological factors, including a plant’s inherent capacity for symbiotic nitrogen fixation, the efficiency of its association with particular rhizobial strains, and its overall nitrogen use efficiency. Environmental factors such as soil composition, moisture, temperature, and the presence of other nutrients or stressors can also impact the nitrogen threshold. For example, a soybean variety with high nitrogen fixation efficiency can maintain optimal fixation at higher external nitrogen concentrations than a less efficient variety, while other legumes such as alfalfa, clover, or lentil can exhibit different thresholds due to differences in nodule structure, plant metabolism, or rhizobial compatibility.

[0243] Additionally, the developmental stage of the plant, the type of nodule formed (determinate or indeterminate), and crop management practices can further influence the nitrogen threshold. As a result, the nitrogen threshold can be empirically determined for each legume species and variety of interest, under the relevant environmental and agronomic conditions. The methods of the instant disclosure enable such determination by providing aPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web framework for experimentally measuring gene expression and nitrogen fixation status across a range of nitrogen conditions, thereby allowing for the identification of the nitrogen threshold specific to each context. This ensures that the assessment of nitrogen fixation status and the guidance for nitrogen fertilizer application are tailored to the unique requirements and characteristics of each legume species and variety.(f) Methods of breeding

[0244] As described in Section l(e) herein above, one aspect of the instant disclosure encompasses methods of determining a nitrogen threshold for a legume plant. The instant invention greatly simplifies and accelerates the process of determining the nitrogen threshold for legume plants compared to traditional methods. Because the claimed methods make it straightforward to determine the nitrogen threshold for individual plants, it is now practical to breed for improved nitrogen threshold by selecting plants that maintain optimal nitrogen fixation at higher external nitrogen concentrations. Unlike prior approaches, which required labor-intensive, destructive sampling of roots or nodules and complex biochemical assays, the claimed methods enable rapid, non-destructive assessment of nitrogen fixation status using gene expression measurements from easily accessible leaf tissue. This allows for high- throughput screening of large plant populations under varying nitrogen conditions, making it practical and efficient to identify and select plants that maintain optimal nitrogen fixation at higher external nitrogen concentrations. As a result, the invention provides a powerful tool for breeding, crop management, and precision agriculture applications.

[0245] Accordingly, one aspect of the instant disclosure encompasses a method for selecting legume plants for breeding, guiding nitrogen fertilizer application, or monitoring fieldlevel nitrogen fixation status. The method comprises determining a nitrogen threshold for a legume plant and selecting plants for breeding that maintain optimal nitrogen fixation status at higher external nitrogen concentrations relative to other plants in the population, as determined by the nitrogen threshold. Methods of determining a nitrogen threshold for a legume plant can be as described in Section l(e). The legume plants can be as described in Section l(a) herein above.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webII. Genetically modified plant

[0246] One aspect of the present disclosure encompasses a genetically modified reporter legume plant or part thereof, plant cell, or seed thereof for reporting nitrogen fixation status in a legume plant. The methods of the present invention, which enable non-destructive assessment of nitrogen fixation status through gene expression analysis in leaf tissue, have made it possible to identify and validate specific polynucleotides as reliable biomarkers. This, in turn, has provided the opportunity to create genetically modified reporter plants that can visually or quantitatively report nitrogen fixation status in real time.

[0247] The genetically modified reporter plant can comprise a reporter construct comprising a reporter under the regulatory control of a polynucleotide listed in Table A. Alternatively, the genetically modified reporter plant can comprise a pair of reporter constructs comprising a first reporter construct comprising a first reporter under the regulatory control of a first polynucleotide and a second reporter construct comprising a second reporter under the regulatory control of a second polynucleotide. When the plant comprises a pair of reporter constructs, the first and second polynucleotides are selected from the polynucleotide pairs identified in Table B. In some aspects, the genetically modified reporter plant can comprise any combination of the expression constructs, pairs of expression constructs, or both. Differential expression of the reporter construct, the pair of reporter constructs, or a GER calculated from expression levels of the pair of reporter constructs indicates the nitrogen fixation status of the plant.

[0248] As used herein, “under regulatory control” refers to operable linkage of a reporter sequence to a regulatory region such that the activity of the reporter reflects the transcriptional or translational activity of the polynucleotide. Non-limiting examples of reporter architectures include transcriptional fusions, translational fusions, dual-reporter systems, destabilized reporters with short half-lives, and split-reporter complementation systems. Reporter modalities can include enzymatic reporters such as p-glucuronidase, luciferases, alkaline phosphatase, or [3-galactosidase; fluorescent proteins such as green fluorescent protein, yellow fluorescent protein, cyan fluorescent protein, or red fluorescent proteins; chromogenic reporters; and biosensor-based reporters such as Fdrster resonance energy transfer pairs, riboswitch- controlled constructs, or CRISPR-based recorders. Detection can be achieved by luminometry,PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web fluorimetry, imaging with CCD or CMOS devices, histochemical staining, or by ratiometric analysis against a control reporter.

[0249] In some aspects, the reporter under the regulatory control of a polynucleotide is the polynucleotide itself, such that the endogenous gene functions as the reporter when introduced into a different organism. In some aspects, the reporter under the regulatory control of a polynucleotide is a detectable reporter operably linked to one or more regulatory elements of the polynucleotide, including a promoter, enhancer, 5' or 3' untranslated region, or other cis-regulatory sequence, such that reporter expression reflects the regulatory activity of the polynucleotide.

[0250] The legume plants can be as described in Section l(a) herein above. Reporters and reporters under the regulatory control of the polynucleotide can be as described in Section l(b) herein above. The polynucleotides can be as described in Section l(c) herein above. Methods of measuring polynucleotide expression to calculate GERs can be as described in Section l(b) herein above.III. Kits

[0251] A further aspect of the present disclosure provides kits for assessing nitrogen fixation status in a legume plant. The kit comprises a. one or more reagents for detecting the expression level of a polynucleotide of Table A or a pair of nucleotides of Table B; one or more genetically modified reporter plant or a part, plant cell, or seed thereof for reporting nitrogen fixation status in a legume plant; instructions for calculating a gene expression ratio (GER) and comparing the GER to a predetermined minimum or maximum GERNFT; or any combination thereof. The legume plants can be as described in Section l(a) herein above. Genetically modified reporter plants can be as described in Section II herein above. The polynucleotides can be as described in Section l(c) herein above. Methods of measuring polynucleotide expression to calculate GERs can be as described in Section l(b) herein above.

[0252] The kits can further comprise transfection reagents, cell growth media, selection media, in-vitro transcription reagents, nucleic acid purification reagents, protein purification reagents, buffers, and the like. The kits provided herein generally include instructions forPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web carrying out the methods detailed below. Instructions included in the kits can be affixed to packaging material or can be included as a package insert. While the instructions are typically written or printed materials, they are not limited to such. Any medium capable of storing such instructions and communicating them to an end user is contemplated by this disclosure. Such media include, but are not limited to, electronic storage media (e.g., magnetic discs, tapes, cartridges, chips), optical media (e.g., CD ROM), and the like. As used herein, the term “instructions” can include the address of an internet site that provides the instructions.DEFINITIONS

[0253] Unless defined otherwise, all technical and scientific terms used herein have the meaning commonly understood by a person skilled in the art to which this invention belongs. The following references provide one of skill with a general definition of many of the terms used in this invention: Singleton et al., Dictionary of Microbiology and Molecular Biology (2nd ed. 1994); The Cambridge Dictionary of Science and Technology (Walker ed., 1988); The Glossary of Genetics, 5th Ed., R. Rieger et al. (eds.), Springer Verlag (1991 ); and Hale & Marham, The Harper Collins Dictionary of Biology (1991 ). As used herein, the following terms have the meanings ascribed to them unless specified otherwise.

[0254] When introducing elements of the present disclosure or the preferred aspects(s) thereof, the articles "a", "an", "the" and "said" are intended to mean that there are one or more of the elements. The terms "comprising", "including" and "having" are intended to be inclusive and mean that there may be additional elements other than the listed elements.

[0255] A “genetically modified” cell refers to a cell in which the nuclear, organellar or extrachromosomal nucleic acid sequences of a cell has been modified, i.e. , the cell contains at least one nucleic acid sequence that has been engineered to contain an insertion of at least one nucleotide, a deletion of at least one nucleotide, and / or a substitution of at least one nucleotide.

[0256] "Homology" refers to sequence similarity between two polypeptide sequences when they are optimally aligned. When a position in both of the two compared sequences is occupied by the same amino acid monomer subunit, e.g., if a position in a light chain CDR ofPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web two different Abs is occupied by alanine, then the two Abs are homologous at that position. The percent of homology is the number of homologous positions shared by the two sequences divided by the total number of positions compared *100. For example, if 8 of 10 of the positions in two sequences are matched or homologous when the sequences are optimally aligned then the two sequences are 80% homologous. Generally, the comparison is made when two sequences are aligned to give maximum percent homology. For example, the comparison can be performed by a BLAST algorithm wherein the parameters of the algorithm are selected to give the largest match between the respective sequences over the entire length of the respective reference sequences.

[0257] The following references relate to BLAST algorithms often used for sequence analysis: BLAST ALGORITHMS: Altschul, S.F., et al, (1990) J. Mol. Biol. 215:403-410; Gish, W., et al, (1993) Nature Genet. 3:266-272; Madden, T.L., et al, (1996) Meth. Enzymol. 266:131 -141 ; Altschul, S.F., et al, (1997) Nucleic Acids Res. 25:3389-3402; Zhang, J., et al, (1997) Genome Res. 7:649-656; Wootton, J.C., et al, (1993) Comput. Chem. 17:149-163; Hancock, J.M. et al, (1994) Comput. Appl. Biosci. 10:67-70; ALIGNMENT SCORING SYSTEMS: Dayhoff, M.O., et al, "A model of evolutionary change in proteins." in Atlas of Protein Sequence and Structure, (1978) vol. 5, suppl. 3. M.O. Dayhoff (ed.), pp. 345-352, Natl. Biomed. Res. Found., Washington, DC; Schwartz, R.M., et al, "Matrices for detecting distant relationships." in Atlas of Protein Sequence and Structure, (1978) vol. 5, suppl. 3." M.O.Dayhoff (ed.), pp. 353-358, Natl. Biomed. Res. Found., Washington, DC; Altschul, S.F., (1991 ) J. Mol. Biol. 219:555-565; States, D.J., et al, (1991 ) Methods 3:66-70; Henikoff, S., et al, (1992) Proc. Natl. Acad. Sci. USA 89:10915-10919; Altschul, S.F., et al, (1993) J. Mol. Evol. 36:290-300; ALIGNMENT STATISTICS: Karlin, S., et al, (1990) Proc. Natl. Acad, Sci. USA 87:2264-2268; Karlin, S., et al, (1993) Proc. Natl. Acad. Sci. USA 90:5873-5877; Dembo, A., et al, (1994) Ann. Prob. 22:2022-2039; and Altschul, S.F. "Evaluating the statistical significance of multiple distinct local alignments." in Theoretical and Computational Methods in Genome Research (S. Suhai, ed.), (1997) pp. 1 -14, Plenum, New York. "Isolated antibody" and "isolated antibody fragment" refers to the purification status and in such context means the named molecule is substantially free of other biological molecules such as nucleic acids, proteins, lipids, carbohydrates, or other material such as cellular debris and growth media.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webGenerally, the term "isolated" is not intended to refer to a complete absence of such material or to an absence of water, buffers, or salts, unless they are present in amounts that substantially interfere with experimental or therapeutic use of the binding compound as described herein.

[0258] The term “sample” or “biological sample” as used herein, refers to a sample obtained from an organism or from components (e.g., cells) of an organism. The sample may be a sample which is derived from a plant. Such samples include, but are not limited to, a punch biopsy, excised leaflet, or sap extract. Biological samples may also include sections of tissues such as frozen sections taken for histological purposes.

[0259] The terms “nucleic acid” and “polynucleotide” refer to a deoxyribonucleotide or ribonucleotide polymer, in linear or circular conformation. For the purposes of the present disclosure, these terms are not to be construed as limiting with respect to the length of a polymer. The terms may encompass known analogs of natural nucleotides, as well as nucleotides that are modified in the base, sugar and / or phosphate moieties. In general, an analog of a particular nucleotide has the same base-pairing specificity, i.e. , an analog of A will base-pair with T. The nucleotides of a nucleic acid or polynucleotide may be linked by phosphodiester, phosphothioate, phosphoramidite, phosphorodiamidate bonds, or combinations thereof.

[0260] The term "nucleotide" refers to deoxyribonucleotides or ribonucleotides. The nucleotides may be standard nucleotides (i.e., adenosine, guanosine, cytidine, thymidine, and uridine) or nucleotide analogs. A nucleotide analog refers to a nucleotide having a modified purine or pyrimidine base or a modified ribose moiety. A nucleotide analog may be a naturally occurring nucleotide (e.g., inosine) or a non-naturally occurring nucleotide. Non-limiting examples of modifications on the sugar or base moieties of a nucleotide include the addition (or removal) of acetyl groups, amino groups, carboxyl groups, carboxymethyl groups, hydroxyl groups, methyl groups, phosphoryl groups, and thiol groups, as well as the substitution of the carbon and nitrogen atoms of the bases with other atoms (e.g., 7-deaza purines). Nucleotide analogs also include dideoxy nucleotides, 2’-O-methyl nucleotides, locked nucleic acids (LNA), peptide nucleic acids (PNA), and morpholinos.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0261] The terms “polypeptide” and “protein” are used interchangeably to refer to a polymer of amino acid residues.

[0262] As used herein, the terms "target site", "target sequence", or “nucleic acid locus” refer to a nucleic acid sequence that defines a portion of a nucleic acid sequence to be modified or edited and to which a homologous recombination composition is engineered to target.

[0263] The terms "upstream" and "downstream" refer to locations in a nucleic acid sequence relative to a fixed position. Upstream refers to the region that is 5' (i.e. , near the 5' end of the strand) to the position, and downstream refers to the region that is 3' (i.e., near the 3' end of the strand) to the position.

[0264] Techniques for determining nucleic acid and amino acid sequence identity are known in the art. Typically, such techniques include determining the nucleotide sequence of the mRNA for a gene and / or determining the amino acid sequence encoded thereby, and comparing these sequences to a second nucleotide or amino acid sequence. Genomic sequences may also be determined and compared in this fashion. In general, identity refers to an exact nucleotide-to-nucleotide or amino acid-to-amino acid correspondence of two polynucleotides or polypeptide sequences, respectively. Two or more sequences (polynucleotide or amino acid) may be compared by determining their percent identity. The percent identity of two sequences, whether nucleic acid or amino acid sequences, is the number of exact matches between two aligned sequences divided by the length of the shorter sequences and multiplied by 100. An approximate alignment for nucleic acid sequences is provided by the local homology algorithm of Smith and Waterman, Advances in Applied Mathematics 2:482-489 (1981 ). This algorithm may be applied to amino acid sequences by using the scoring matrix developed by Dayhoff, Atlas of Protein Sequences and Structure, M. O. Dayhoff ed., 5 suppl. 3:353-358, National Biomedical Research Foundation, Washington, D.C., USA, and normalized by Gribskov, Nucl. Acids Res. 14(6):6745-6763 (1986). An exemplary implementation of this algorithm to determine percent identity of a sequence is provided by the Genetics Computer Group (Madison, Wis.) in the "BestFit" utility application. Other suitable programs for calculating the percent identity or similarity between sequences are generally known in the art, for example, another alignment program is BLAST, used withPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web default parameters. For example, BLASTN and BLASTP may be used using the following default parameters: genetic code=standard; filter=none; strand=both; cutoff =60; expect=10; Matrix=BLOSUM62; Descriptions=50 sequences; sort by=HIGH SCORE; Databases=non- redundant, GenBank+EMBL+DDBJ+PDB+GenBank CDS translations+Swiss protein+Spupdate+PIR. Details of these programs may be found on the GenBank website. With respect to sequences described herein, the range of desired degrees of sequence identity is approximately 80% to 100% and any integer value therebetween. Typically the percent identities between sequences are at least 70-75%, preferably 80-82%, more preferably 85- 90%, even more preferably 92%, still more preferably 95%, and most preferably 98% sequence identity.

[0265] As various changes could be made in the above-described cells and methods without departing from the scope of the invention, it is intended that all matter contained in the above description and in the examples given below, shall be interpreted as illustrative and not in a limiting sense.EXAMPLES

[0266] All patents and publications mentioned in the specification are indicative of the levels of those skilled in the art to which the present disclosure pertains. All patents and publications are herein incorporated by reference to the same extent as if each individual publication was specifically and individually indicated to be incorporated by reference.

[0267] The publications discussed throughout are provided solely for their disclosure before the filing date of the present application. Nothing herein is to be construed as an admission that the invention is not entitled to antedate such disclosure by virtue of prior invention.

[0268] The following examples are included to demonstrate the disclosure. It should be appreciated by those of skill in the art that the techniques disclosed in the following examples represent techniques discovered by the inventors to function well in the practice of the disclosure. Those of skill in the art should, however, in light of the present disclosure, appreciate that many changes could be made in the disclosure and still obtain a like or similarPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web result without departing from the spirit and scope of the disclosure, therefore all matter set forth is to be interpreted as illustrative and not in a limiting sense.Example 1. Unraveling the Temporal Transcriptom ic Dynamics in Soybean Bradyrhizobium Nodules

[0269] The soybean-Rhizobium symbiosis is an agriculturally relevant model system for studying plant-microbe interactions due to its ability to fix atmospheric nitrogen, enhancing global nitrogen use efficiency by reducing reliance on environmentally and economically costly synthetic nitrogen fertilizers and improving agricultural sustainability. This study aimed to identify regulatory genes and small RNAs (sRNAs) involved in nitrogen fixation by characterizing the metatranscriptome of soybean nodules from both the plant (Glycine max cv. Williams-82) and the bacterium (Bradyrhizobium diazoefficiens USDA110) during nodule development, spanning from 2 weeks post inoculation (wpi) to 10 wpi. Using RNA sequencing, sRNA sequencing, nitrogenase activity assays, and analysis of key symbioticrelated proteins (LBA and NifH), the regulatory dynamics of nodule symbiosis during early nodule development, nitrogen fixation, and age-related nodule senescence were elucidated. The results showed that nitrogenase activity peaked at 5 wpi but did not correlate with nodule number, mass, or nifH expression, suggesting nifH is not a reliable indicator of nitrogen fixation. Interestingly, nifH expression and protein levels (NifH) continued to rise even as nitrogenase activity declined. Distinct expression patterns of Leghemoglobin and small RNA genes were observed, highlighting their specialized roles at different stages of nodule development. This study underscores the complexity of regulatory mechanisms in soybean nodules and identifies potential biomarkers for nitrogen fixation and developmental senescence. These insights contribute to a deeper understanding of transcriptional regulation in soybean nodules, offering potential strategies for optimizing nitrogen use efficiency in legume cultivation, thereby supporting sustainable agricultural practices.

[0270] Improving agricultural productivity through increasing nitrogen use efficiency, while minimizing environmental impact, is imperative to meet the challenge of feeding a growing population. One promising avenue lies in legumes, such as soybean, which acquirePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web nitrogen from nitrogen-fixing soil bacteria known as rhizobia through a process called symbiotic nitrogen fixation. Within the soybean-Rhizobium symbiosis, nitrogen fixation occurs within specialized de novo root organs, called nodules. In these nodules, rhizobial nitrogenases utilize host-derived photosynthetic sugars to convert atmospheric nitrogen (N2) into bioavailable nitrogen in the form of ammonia (NH3). This intricate process involves a dynamic exchange of chemical signals, hormone flux, and precise transcriptional regulation between the host and rhizobia (Ferguson et al. 2019).

[0271] Rhizobia enter into their host’s roots primarily through infection threads, leading to differentiation into symbiotic nitrogen-fixing bacteroids within host -derived symbiosome membranes (Udvardi and Poole 2013). Bacteroids, enveloped in peribacteroid membranes (PBM), exchange nutrients with the host (Udvardi et al. 1988). Within mature nodules, nitrogen fixation is facilitated by host-supplied sugars, particularly malate, and N2 is converted by rhizobial nitrogenases into ammonia (Schwember et al. 2019). The catalytic activity of rhizobial nitrogenase involves two partners, an iron (Fe) protein and a molybdenum-iron (MoFe) protein, encoded by several NIF genes, with nifH, the ironcontaining protein, being the most highly expressed NIF gene during nitrogen fixation (Franck et al. 2018; Jimenez-Vicente et al. 2018).

[0272] To support this process, the host plant maintains an ideal environment within the nodules, particularly by regulating oxygen content. Oxygen in nodules acts as a double-edged sword - too much oxygen inhibits nitrogenase activity, while too little oxygen limits bacterial respiration and ATP synthesis. To balance these conflicting needs, legume nodules contain leghemoglobin, specialized protein pigments that modulate nodule oxygen levels, facilitating an anaerobic environment crucial for nitrogen fixation (Du et al. 2020). This ensures a low oxygen environment necessary for the oxygen-sensitive rhizobial nitrogenase to function effectively during nitrogen fixation while supporting bacteroid respiration.

[0273] Age-related, developmental nodule senescence typically occurs when the host plant reaches a specific developmental stage, often transitioning from vegetative growth to reproductive stages, which alters the host's nitrogen demand. Senescence can also be induced by external factors such as high levels of soil nitrogen and other environmental stressors. Nodule senescence is characterized by declining nitrogenase activity andPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web leghemoglobin content, leading to reduced nitrogen fixation efficiency (Dupont et al. 2012; Kazmierczak et al. 2020).

[0274] The process of symbiotic nitrogen fixation demands substantial energy, with approximately 25% of net photosynthetic products allocated to nodules throughout their development (Li et al. 2022b). Due to this high-energy requirement, the host plant must carefully balance the formation of new nodules with its overall energy budget and developmental stage. This balance ensures that the host efficiently manages its energy and resources, coordinating the need for nitrogen fixation with its growth and development. Consequently, nodulation and the internal process of nitrogen fixation are tightly regulated by the host organism. The Autoregulation of Nodulation (AON) pathway plays a crucial role, systemically regulating nodulation by controlling the formation of new nodules in response to rhizobial infection. Additionally, the Nitrogen Regulation of Nodulation Pathway plays a pivotal role in regulating new nodulation in response to an ample supply of external nitrogen (Oldroyd et al. 2011 ; Ferguson et al. 2019; Li et al. 2022b). However, less is known about the specific regulatory pathways controlling nitrogen fixation activity.

[0275] Recent research has identified host-derived small RNAs (sRNAs), particularly microRNAs (miRNAs) (Hossain et al. 2019; Xu et al. 2021 ; Zhang et al. 2021 ) as critical regulators, influencing the development of nodules and their function. miRNAs are small, noncoding RNA molecules that regulate gene expression post-transcriptionally and play significant roles in various plant biological processes. Understanding the dynamic changes in miRNA accumulation and their regulatory mechanisms during the different stages of nodule development is essential for optimizing symbiotic nitrogen fixation across diverse environmental conditions.

[0276] The model soybean, Glycine max cv. Williams-82, was inoculated with highly specialized nitrogen-fixing bacteria known as Bradyrhizobium diazoefficiens USDA110. Weekly nodule samples were collected for nine weeks, from 2 weeks post inoculation (wpi) to 10 wpi, and their RNA and protein content were analyzed. Leveraging RNA sequencing and small RNA sequencing together with protein content analysis and nitrogenase activity assays, important genes and regulatory miRNAs were identified that are involved in early nodule development, nitrogen fixation, and the transition from nitrogen fixation to senescence, as wellPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web as those present in the AON and Nitrogen Regulation of Nodulation pathways. This example characterizes the transcriptional regulation occurring during soybean nodule development, with specific emphasis on the stages of nitrogen fixation and the transition to senescence.RESULTSNitrogenase activity peaks at 5 weeks post inoculation in soybean nodules

[0277] Measuring nitrogenase activity levels during nodule development is essential for understanding when nodules are in the initiation phase, the highly active fixation phase, and the senescence phase. To identify the peak of nitrogen fixation activity during root nodule symbiosis (RNS) between soybean and Bradyrhizobium, the enzymatic activity of the rhizobial nitrogenase enzyme in nodules was measured using the acetylene reduction assay (ARA) (Vessey 2004; Montes-Luz et al. 2023). To evaluate nitrogenase activity in soybean nodules, G. max cv. Williams-82 was cultivated in a greenhouse under low soil-nitrogen conditions (0.5 mM KNO3). The entire root systems were harvested weekly, from 4 wpi to 7 wpi, and analyzed them using the ARA (Figure 1 ). Nitrogenase activity was quantified as the amount of ethylene produced from acetylene (nmols) per nodule (mg) per hour (Figure 1A - bottom). Before performing the ARA, the weight of separated shoots and roots (Figure 2). Post-ARA, the nodules were harvested, measured, weighed (Figure 1C), and counted (Figure 1 D).

[0278] Soybean nitrogenase activity peaked at 5 wpi, showing a 2.1 -fold increase from 4 wpi to 5 wpi, followed by a gradual decrease, with a 0.83-fold reduction from 5 wpi to 7 wpi (Figure 1 B). In parallel with shoot and root growth (Figure 2), nodule mass increased significantly each week from 4 wpi to 7 wpi (Figure 1 C). The number of nodules also increased significantly from 5 wpi to 6 wpi, rising from an average of 180 to 439 nodules per plant (2.4- fold increase), respectively (Figure 1 D). However, this increase in nodule number did not correlate with a rise in nodule nitrogenase activity from 5 wpi to 6 wpi, which decreased 0.82- fold (Figure 1 B). This may indicate that new nodules created after 5 wpi are not as competent at nitrogen fixation as the older more established nodules and therefore do not contribute greatly to overall nitrogen fixation levels.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webBradyrhizobium nifH transcript and corresponding NifH protein levels do not correlate with nitrogen fixation activity

[0279] To characterize the transcriptional regulation of symbiotic nitrogen fixation and nodule developmental senescence in soybeans, G. max cv. Williams-82 plants were grown in a greenhouse under low nitrogen conditions (0.5 mM KNO3) to mimic nitrogen levels found in unfertilized soils. Nodules were harvested weekly from 2 wpi to 10 wpi to capture a wide range of developmental stages, from young nodules to mature nodules, encompassing the full spectrum from active nitrogen fixation to age-related nodule senescence. To assess the role of rhizobial nitrogenase in regulating nitrogen fixation activity, four primer sets (Table 1) were designed and tested to measure the expression of the Bradyrhizobium nifH gene, the most highly expressed component of the rhizobial nitrogenase enzyme (Franck et al. 2018). Primer sets spanning the nifH transcript from 5’ to 3’ (Figure 3A) were used, and transcript levels in soybean nodules were measured using reverse transcription quantitative PCR (RT-qPCR) (Figure 3B).PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0280] The nifH primer sets located closer to the 5’ region of the transcript exhibited higher relative expression levels compared to primer sets targeting the 3’ end of the transcript. Based on this observation, primer set 1 was selected for subsequent experiments.Using nifH primer set 1 , nifH expression was measured in nodules aged 2 wpi to 10 wpi (Figure 4A). Transcript levels increased 1 .5-fold from 2 wpi to 3 wpi, followed by a gradual additional 1.5-fold increase through 10 wpi.

[0281] The nodules used were harvested from the same plants utilized for gene expression analysis for protein extraction and quantification of NifH protein content from 2 wpi to 10 wpi (Figure 4B). Employing a primary NifH antibody, western blot analysis was conducted, with the objective of exploring its potential correlation with nifH transcriptional levels. A strong signal corresponding to the NifH MW (32kD) (Figure 4C) was detected. NifH protein levels showed a similar trend to nifH gene expression. A 1 .4-fold increase from 2 wpi to 4 wpi was observed and a gradual 1 .2-fold increase from 4 wpi to 10 wpi, with its highest peak observed at 8 wpi. While NifH protein levels correlated with expression levels of nifH, neither the protein nor the expression levels correlated with nitrogen fixation activity.Peak levels of LEGHEMOGLOBIN-3 (LBA) proteins coincide with a decline in nitrogenase activity

[0282] Next, the relationship between host leghemoglobin levels and nitrogen fixation activity was assessed. LEGHEMOGLOBIN-3 (Lb3), the most highly expressed soybean leghemoglobin gene in nodules, exhibits expression levels that closely track nitrogen fixation activity (Du et al. 2020).A primary LBA antibody was employed to evaluate the levels of LBA protein (product of Glyma.10g199100 Lb3 expression) within nodules aged 2 wpi to 10 wpi (Figure 5A). An exponential increase was observed in LBA protein levels from 2 wpi to 6 wpi, peaking with a 2.2-fold rise from 5 wpi to 6 wpi. Subsequently, LBA protein levels remained relatively stable from 6 wpi to 8 wpi, and gradually declined by 0.52-fold from 8 wpi to 10 wpi. ItPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web is important to note that a weak signal corresponding to the LBA molecular weight (16 kD) was observed, accompanied by high non-specific signals (Figure 5B). These results indicate that while LBA protein levels peaked between 6 wpi and 8 wpi, they do not correlate with nitrogen fixation, which peaked at 5 wpi and gradually declined. This suggests that although LBA is crucial for optimal nitrogen fixation during early nodule development, its abundance does not sustain high nitrogenase activity in mature nodules, possibly due to senescence-related changes or feedback inhibition mechanisms.Dual RNA sequencing captures soybean and Bradyrhizobium transcripts

[0283] In order to elucidate the dynamic gene expression during symbiotic nitrogen fixation, RNA libraries from 2 wpi to 10 wpi were generated to analyze gene expression of both host plant and rhizobial symbiont during symbiosis. A sequential ribosomal RNA (rRNA) depletion was performed from total nodule RNA to reduce rRNA content, thereby increasing sensitivity for capturing mRNA and non-coding RNAs from both plant and bacteria. The remaining ribo-depleted RNA was used for RNA library construction and sequencing. On average, 36.9 million reads per sample were obtained. These were mapped to the soybean genome (G / ??ax_W82 v4.a1 , from SoyBase) and the BradyrhizobiumUSDA1 10_ASM 164267v 1 genome (from NCBI). Most of the reads, -75%, mapped to the plant genome. This percentage varied across samples, ranging from 59 to 84%. In addition to this, it was found that reads, ranging from 2 to 17.5%, mapped to the bacterial genome (Figure 6).

[0284] The HISAT2 Stringtie pipeline was used to analyze gene expression from both species (Pertea et al. 2016). Out of the 52,872 annotated genes in the soybean genome, transcripts for 44,901 were identified, which corresponds to 84.9% of the annotated genes. Similarly, the Bradyrhizobium genome contains 8,641 annotated genes, and transcripts for 8,581 , were identified which is 99.3% of the total. It was hypothesized that the genes that were not capture are either too low to be detected, are tissue-specific and are not expressed in nodule samples under the experimental conditions, or could not be captured for technical reasons.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webGene differential expression in nodules is stage-specific for both soybean and Bradyrhizobium

[0285] To comprehend the transcriptional changes in each step of the RNS, the DESeq2 pipeline was utilized for sample comparison, each against its immediate previous week (Figure 7). It was noted that most of the differentially expressed (DE) genes in soybean nodules are significant in the late stages of RNS, particularly in the comparison between 8 wpi and 9 wpi (29% of DE genes, mainly downregulated) and 9 wpi to 10 wpi (23% of DE genes, mainly upregulated). Conversely, for Bradyrhizobium, most DE genes are significant in the early stages of RNS, primarily in the 2 wpi to 3 wpi comparison, with 36% of DE genes, most of them downregulated.

[0286] To ascertain if these genes were differentially expressed only in one comparison (hence stage-specific) or if the same genes were involved in different stages, these groups of DE genes were compared at each stage using an Upset plot (Figure 8). It was observed that for the late stages of soybean, 1011 out of 2179 genes (-46%) are unique to the 8 wpi vs 9 wpi comparison, 703 out of 1744 genes (-40%) are unique to the 9 wpi vs 10 wpi comparison, and an additional 576 genes are shared by both comparisons (representing -26% and

[0287] -33%, respectively). In the early stages, 570 out of 1025 DE genes (-55%) were unique to the 2 wpi to 3 wpi comparison. For Bradyrhizobium, a similar scenario was observed. In the early stages, 951 out of 1551 DE genes in 2 wpi vs 3 wpi (-61 %), and 441 out of 708 DE genes in 3 wpi vs 4 wpi (-62%) are unique to each comparison. It was concluded that most DE genes are stage-specific and differentially expressed in only one or perhaps two of the stages.Gene Ontology (GO) analysis reveals dynamic regulatory mechanisms in soybean nodules during nitrogen fixation and senescence

[0288] To understand the functional implications of these DE genes, all significant (p- value < 0.05) DE soybean genes were analyzed across eight weekly comparisons, which included 4050 upregulated and 3460 downregulated genes, using Gene Ontology (GO) categories in ShinyGO V0.80 (Ge et al. 2020). the resulting pathways were sorted first by False Discovery Rate (FDR) with a cutoff at 0.01 , and then by Fold Enrichment, which is defined as the ratio of the percentage of identified genes in a particular pathway to the percentage of genes inPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web the background set associated with the same pathway. For these analyses, genes that were upregulated and downregulated in each comparison were separated.

[0289] The GO analysis identified 1127 genes, or 15% of the total DE genes (n=7510), associated with 43 pathways within the GO category of Biological Processes (Figure 9). Among these pathways, 14 were shared between both upregulated and downregulated DE genes, while 11 were unique to upregulated and 18 to downregulated genes. The distribution of DE genes across GO Biological Processes pathways included 539 upregulated (Figure 9A) and 588 downregulated genes (Figure 9B) across the weekly comparisons. Notably, three comparisons (2 wpi to 3 wpi, 8 wpi to 9 wpi, and 9 wpi to 10 wpi) collectively, including both upregulated and downregulated genes, accounted for 64% (n=718) of the identified genes, with downregulated genes from 8 wpi to 9 wpi comprising 20% (n=231 ) of the total. This indicates a high level of transcriptional regulation in younger (2 wpi to 3 wpi) and older nodules (8 wpi to 10 wpi), likely relating to nodule development, where younger nodules are in the process of establishing symbiotic nitrogen fixation pathways and older nodules are transitioning to senescence. These results suggest that mid-stage nodules, from 3 wpi to 8 wpi contain more stable regulomes compared to younger and older nodules.

[0290] Important biological process pathways associated with DE genes in young nodules (2 wpi to 4 wpi) contained upregulated genes involved in asparagine biosynthetic process, photosynthetic electron transport in photosystem II, photosynthesis-light reaction, polysaccharide catabolic process, and inositol catabolic process pathways, and downregulated genes involved in asparagine and methionine biosynthetic processes, mannose metabolic process, and response to biotic stimulus, among others. Other relevant pathways include those associated with downregulated genes from 6 wpi to 8 wpi, including heme oxidation, autophagosome assembly, methionine biosynthentic process, and cellular amino acid biosynthetic process pathways. Notably, genes linked to the sucrose metabolic process exhibited a pattern mirroring nitrogen fixation activity, being upregulated from 3 wpi to 5 wpi and downregulated from 5 wpi to 6 wpi. Additionally, genes associated with response to stress pathways exhibited contrasting trends, where some of the genes were downregulated from 6 wpi to 7 wpi, and some were upregulated 7 wpi to 9 wpi. Genes with the highest fold enrichment scores were of particular interest, especially those involved in sulfatePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web transmembrane transport. These genes exhibited a distinctive pattern, being downregulated from 5 wpi to 6 wpi, similar to N-fixation activity, and then upregulated from 6 wpi to 7 wpi. These findings suggest dynamic regulatory mechanisms underlying nodule photosynthesis, asparagine biosynthesis, sucrose and sulfate metabolisms, and stress response, during critical transitions in nodule development and function, particularly during SNF and the transition to senescence.Contrasting gene expression patterns suggest functional specializations in nodule development

[0291] It was hypothesized that certain genes might serve as excellent markers for SNF but are often overlooked in DE analysis, due to their gradual changes in expression levels. To identify these genes, two approaches were employed: (i) hierarchical clustering and (ii) DE analysis focused on genes whose expression significantly increased from 2 wpi to 5 wpi and decreases from 5 wpi to 10 wpi (2-up-5-down-10).

[0292] Hierarchical clustering analysis was used to group RNA transcripts according to their expression patterns (Figure 10A). Using WGCNA software (Langfelder and Horvath 2008), 10 different clusters were identified, encompassing a total of 5703 genes. Notably, the two largest clusters, ME2 and ME3, accounted for 86% of all reported genes and displayed contrasting expression trends. ME2 exhibited higher expression (represented by red- orange shades) later in nodule development, beginning at 5 wpi and peaking at 9 wpi, suggesting a role in senescence. In contrast, ME3 showed higher expression earlier in development peaking at 2 wpi, indicating a role in early nodule development. Additionally, genes in clusters ME6 / 8 / 10 and ME1 / 3 / 5 demonstrated low expression (represented by blue shades) at 8 wpi and 9 wpi, respectively. At 3 wpi, ME4 had high expression, flanked by low expression at 2 wpi and 4 wpi, indicating a tight regulatory control of ME4 genes in young nodules.

[0293] To elucidate the functions of the clustered genes, the GO categories present in each of the 10 ME clusters were analyzed using the SoyBase GO Term Enrichment Tool (Figure 10B) (Morales et al. 2013). The GO analysis identified 28 Biological Processes pathways. The ME3 cluster contained genes involved in all pathways, whereas those involved in the response to abiotic and biotic stimuli were notably absent in the ME2 cluster. ThisPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web absence in the ME2 cluster suggests that these genes primarily function in young nodules and not during senescence. Interestingly, despite its relatively high number of identified genes, ME1 had no annotated genes linked to any GO Biological Processes pathways. Notably, genes involved in carbohydrate metabolic process were present in all clusters, except ME1 . This distribution underscores the distinct functional specializations among the different ME clusters, revealing a tightly regulated transcriptional network involved in each step of RNS.Transcriptomic analysis reveals key biomarkers and regulators of nitrogen fixation dynamics in soybean nodules

[0294] To uncover key biomarkers and regulators of nitrogen fixation in soybean nodules, a comprehensive transcriptomic analysis was conducted. Understanding these biomarkers is crucial for enhancing nitrogen fixation, which can reduce reliance on synthetic fertilizers and improve sustainable agricultural practices. Additionally, identifying these biomarkers can provide deeper insights into the underlying biological processes, offering potential targets for genetic and biotechnological interventions to optimize nitrogen fixation and improve crop yields.

[0295] Using DESeq2, expression data from 2 wpi to 5 wpi and from 5 wpi to 10 wpi were compared, and identified genes that exhibited the 2-up-5-down-10 temporal expression pattern that were significantly upregulated in the first comparison and significantly downregulated in the second comparison. To ensure these genes could serve as effective biomarkers, those with an average FPKM (Fragments Per Kilobase of transcript per Million mapped reads) of < 1 across all time points were filtered out, resulting in a final list of 315 genes (Figure 11 A). These genes were further categorized based on their average FPKM expression into three groups: (i) average FPKM 1 to 10 (n = 111 genes) (Figure 11 B), (ii) average FPKM 100 to 1000 (n = 152 genes) (Figure 11C), (iii) average FPKM >1000 (n = 52 genes) (Figure 11D).

[0296] The focus was placed on the third group of genes, which includes highly expressed genes (average FPKM >1000) exhibiting the 2-up-5-down-10 expression pattern. These genes were examined for their potential role as nitrogen fixation biomarkers and as indicators of internal nodule transcriptional temporal dynamics. Notably, among the genes withPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web the 2-up-5- down-10 expression pattern, the three most highly expressed were LEGHEMOGLOBIN (Lb) genes, which play a crucial role in nitrogen fixation. Specifically, these genes were Lb3 (Glyma.10G199100), Lb2 (Glyma.10G199000), and Lb1 (Glyma.10G198800), listed in descending order of expression. Due to their distinctive expression pattern and being that they are the highest expressing genes in nodules that share that pattern, the symbiotic leghemoglobin Lb1, Lb2, and Lb3 stand out as promising biomarkers for nodule nitrogen fixation due to their roles in regulating oxygen levels within nodules, which is crucial for sustaining nitrogenase activity and facilitating rhizobial respiration.

[0297] Other noteworthy genes with average FPKM >1000 and exhibiting 2-up-5-down- 10 expression patterns (Figure 11 D) included URICASE / URATE OXIDASE NODULIN 35 (Glyma.10G121524), SUCROSE SYNTHASE 4 (Glyma.13G114000), two glutamine synthetase genes GLN1 (Glyma.11 G215500 and Glyma.14G213300) and ARGONAUTE 5 (Glyma.11 G190900), listed in descending order of expression. Uricase plays a pivotal role in supporting symbiosis by efficiently managing nitrogen byproducts, particularly in nitrogen metabolism, facilitating nitrogen recycling and detoxification within the nodule environment (Nguyen et al. 2023). Sucrose synthase is essential for supplying carbon and energy for nitrogen-fixation, by converting sucrose into fructose and UDP-glucose, pivotal molecules in various metabolic pathways within the nodules (Morell and Copeland 1985). Glutamine synthetases play a crucial role in nitrogen assimilation in nodules, facilitating the conversion of ammonium from nitrogen fixation or nitrate from the environment into glutamine. In nodules, glutamine is either exported directly out of nodules to meet the nitrogen demands of the host plant or used within the nodules to synthesize asparagine (Li et al. 2023). Argonaute proteins play a central role in post-transcriptional gene silencing and, in conjunction with small RNAs, serve as master regulators of gene expression (Zhan and Meyers 2023).

[0298] Moreover, AG05 has emerged as a crucial protein in nodule establishment (Reyero- Saavedra et al. 2017). Downregulation of AG05 by RNAi in common bean (P. vulgaris cv. Negro Jamapa) and soybean (G. max cv. W82) led to impaired root hair curling, reduced nodule formation, and interfered with the induction of critical symbiotic genes. The presence of AG05 among the highly expressed 2-up-5-down-10 genes, suggests its involvement in fine-tuning the regulatory mechanisms essential for efficient nitrogen fixation, inPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web addition to its role in nodule establishment. It also suggests an important role of small regulatory RNAs in the nodulation process that will be explored in the next sections.Leghemoglobin Lb1 and Lb4 genes as potential biomarkers for nitrogen fixation in soybean nodules revealed by temporal expression patterning

[0299] In this study, five symbiotic Leghemoglobin genes were identified, Glyma.10G198800 (L ), Glyma.10G199000 (Lb2), Glyma.10G199100 (Lb3), Glyma.20G191200 (Lb4), and Glyma.10G198900 (Lb5) and two non-symbiotic hemoglobin genes, Glyma.11 G121700 (Hb1), and Glyma.11 G121800 (Hb2) within the soybean genome (Gmax_W82 v4.a1 ).

[0300] Expression analysis revealed the presence of all five leghemoglobin genes during the entire observation period — Lb3, Lb2, Lb1, Lb4, and Lb5, arranged in descending order of average expression (Figure 12A). In contrast, only one of the two non- symbiotic hemoglobin genes were detected, Hb2, in nodules. Notably, all leghemoglobin genes exhibited a similar temporal expression pattern, while Hb2 displayed a unique expression pattern, initiating at low levels, showing a minor peak at 6 wpi, and a major peak at 9 wpi, suggesting involvement in the decline of nitrogen fixation and nodule senescence.

[0301] Distinct expression peaks for each gene were observed, with Lb1 and Lb4 exhibiting their highest expression at 5 wpi. Notably, also peak nitrogenase activity at 5 wpi (Figure 12B) was observed. In contrast, Lb3 and Lb5 reached their peak expression levels at6 wpi. Lb2 expression likely peaked beween 5 wpi and 6 wpi. Following their peak expressions, all five Lb genes demonstrated an overall decline in expression from 7 wpi to 10 wpi. Additionally, a down and up oscillation of expression during the decline was observed, from7 wpi to 10 wpi, in all Lb genes.

[0302] Clustering analysis, indicated by the dendogram in Figure 12B, groups Lb 1 and Lb4 together, indicating similar temporal expression patterns. Similarly, Lb2, Lb3, and Lb5 are clustered together, suggesting they share a common expression profile. The temporal expression patterns and clustering results highlight distinct regulatory mechanisms and potential diverse functional roles of soybean leghemoglobin (Lb1 to Lb5) and hemoglobin genesPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web(Hb2), during multiple stages of nodule development, specifically during symbiotic nitrogen fixation and senescence.AGO5 and AGO2 emerge as potential biomarkers for nitrogen fixation

[0303] The high level of expression of Glyma.11 G190900 (AGO5) and its distinctive 2-up- 5-down- 10 expression pattern inspired us to further investigate soybean Argonaute transcription in nodules. In this study, 25 Argonaute (AGO) genes were identified within the soybean genome (Gmax_W82 v4.a1 ), including multiple copies of specific AGOs: AGO1 (n = 2), AGO2 (n = 2), AGO4 (n = 5), AGO5 (n = 3), AGO6 (n = 2), AGO7 (n = 2), AG010 (n = 8), and one additional AGO that is unclear if it is a duplication of AGO1 or AG010.

[0304] The expression analysis revealed the presence of 24 of 25 AGO genes in the nodule samples. However, a quarter of these AGO genes exhibited negligible expression (very low average FPKM values < 1 ), while ten AGO genes had low average FPKM values (< 50). The remaining eight soybean AGO genes showed high levels of expression, ranging from moderate (100 to 1000 avg. FPKM, n = 6) to high (> 1000 avg. FPKM, n = 2) throughout the observation period.

[0305] The analysis focused on the eight AGO genes with high expression levels, revealing two distinct expression patterns.. Six of the eight AGO genes - Glyma.09G167100 (AG01 / AG010), Glyma.16G217300 (AGO1), Glyma.20G052500 (AGO4), Glyma.12G083500 (AGO5), Glyma.02G274900 (AGO4), Glyma.14G041100 (AGO4) - arranged in descending order of average expression, exhibited peak transcription levels early in symbiosis at 2 wpi, followed by lower expression during periods of high nitrogen fixation (5 wpi to 6 wpi). AGO1 / 10, AGO1, and AGO4 (chromosome 20) showed increased expression from 8 wpi to 9 wpi, whereas AGO5 (chromosome 12) and the other two AGO4 genes - AGO4 (chromosome 2) and AGO4 (chromosome 14) - maintained low expression in later stages.Changes in expression levels from 9 wpi to 10 wpi varied. This indicates that the most highly expressed AGO genes in soybean nodules are primarily involved in the early and late stages of nodule development.

[0306] Conversely, Glyma.11G190900 (AGO5 on chromosome 11 ) and Glyma.20G022900 (AGO2) exhibited a low-to-high-to-low temporal expression pattern, withPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web peak expression occurring around 5 wpi (Figure 13A). This suggests that while most nodule AGO genes are active during early and late stages of nodule development, AG05 (chromosome 11 ) and AG02 are most active during stages of nitrogen fixation, indicating a potential specialized role for these genes in sustaining or promoting nitrogen fixation.

[0307] A bar plot based on the same data for AGO5 (chromosome 11 ) and AGO2 was generated to better understand their temporal expression patterns (Figure 13B). Both AGO5 and AGO2 exhibited strikingly similar patterns, with AGO5 showing higher overall expression, thus making it a more reliable biomarker for nitrogen fixation. The expression of both genes started at relatively low levels at 2 wpi and increased until reaching peak levels at 5 wpi. Additionally, AGO5 showed a more pronounced rise compared to AGO2, which had a more gradual increase to its peak. After peaking at 5 wpi, the expression levels of both genes dropped at 6 wpi, then rose again by 8 wpi, nearly reaching the levels observed at their 5 wpi peak. From 8 wpi to 9 wpi, expression levels dropped significantly, reaching the lowest point during the observation period. Notably, both genes exhibited a substantial increase in expression from 9 wpi to 10 wpi, suggesting that AGO5 and AGO2 play a role in the later stages of nodule development, in addition to stages of nitrogen fixation.Dicer-like (DCL) gene expression patterns in nodules reveal enrichment of DCL2 and DCL4 transcripts in early nodules, with DCL1 and DCL3 transcripts predominant in mature nodules

[0308] After the investigation of Argonaute gene expression, soybean Dicer-like (DCL) genes were explored, which, along with AGO genes, play crucial roles in the biogenesis of small RNAs in plants. DCL genes cleave longer precursor RNAs into specific sizes of small RNAs, with each particular DCL gene involved in processing specific small RNA types, which subsequently influences its function in PTGS. In this study, 11 DCL genes were identified within the soybean genome (Gmax_\N82 v4.a1 ), including multiple copies of specific DCLs'. DCL1 (n = 3), DCL2 (n = 4), DCL3 (n = 2), DCL4 (n = 2).

[0309] Results from expression analysis revealed the presence of all 11 DCL genes throughout the observation period of 2 wpi to 10 wpi. However, three of these DCL genes displayed low average FPKM values (< 5). Conversely, the remaining eight DCL genesPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web exhibited a relatively narrow range of expression, ranging from low to moderate level. Their average FPKM values spanned from 70 to 700 between samples throughout the observation period. Notably, Glyma.04G057400 (DC _3), the highest expressing DCL in nodules, exhibited an average FPKM value roughly two times higher than that of the next highest expressing DCL, Glyma.17G104100 (DCL4), with values of 742 and 335 average FPKM, respectively. Conversely, Glyma.09G025300 (DCL2) displayed the lowest average FPKM value among highly expressed nodule DCL genes (with average FPKM >50) throughout the observation period, with an average 78 FPKM.

[0310] Similar to the temporal expression patterns of Argonaute genes in nodules, two distinct DCL gene expression patterns were observed (Figure 14A). Among the eight low to moderately expressed DCL genes, DCL3 from chromosome 4 (highest expressing DCL in nodules), along with two DCL1 copies (Glyma.19G261200 and Glyma.03G262100), exhibited a general pattern of relative expression ranging from low to high. The average expression levels over the observation period for the two aforementioned DCL1 genes (from chromosome 19 and 13) were relatively similar, with respective average FPKM values of 297 and 217.

[0311] Conversely, five nodule DCL genes - Glyma.17G104100 (DCL4), Glyma.19G254900 (DCL2), Glyma.13G156500 (DCL4), Glyma.09G025400 (DCL2), and Glyma.09G025300 (DCL2), listed in order of descending expression - exhibited a pattern of high-to-low relative expression.

[0312] A bar plot based on the same data for nodule DCL genes was generated to better understand their temporal expression patterns (Figure 14B). Expression appears relatively consistent, with increases in expression never accounting for more than 2-fold change or less than 0.5-fold change. Additionally, none of the DCL genes demonstrated the distinct 2- up-5-down-10 as observed with AGO5 from chromosome 11 .

[0313] These results have unveiled two distinct temporal expression patterns for DCL genes in nodules, grouping the four DCL genes into two categories. Group 1 comprised five DCL genes - three DCL2 genes (from chromosomes 9(n=2) and 19) and two DCL4 genes (from chromosomes 13 and 17) - exhibited a pattern of high-to-low expression, suggesting their involvement in young nodules from 2 wpi to 4 wpi. Conversely, Group 2 consisted of three DCL genes - two DCL1 genes (from chromosomes 3 and 19) and one DCL3 gene fromPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web chromosome 4 - displaying increased expression later in nodule development, from 7 wpi to 10 wpi, indicating a role in nodule senescence, coinciding with the decline in nitrogen fixation activity.Nodules contain a high proportion of lowly expressed defense-related genes

[0314] Host immunity plays a crucial role in root nodule symbiosis, as the plant must balance defense mechanisms against potential pathogens while allowing beneficial rhizobia to infect and establish nodules. In this study, 440 defense-related genes were identified in the soybean genome (G / 7?ax_W82 v4.a1 ). Of these, 40% (n=175) exhibited minimal to no expression in nodules, with average FPKM values less than 1 over the period of observation from 2 wpi to 10 wpi. Additionally, 53% (n=233) of the identified genes showed low expression, with average FPKM values ranging from 1 to 100. Among the 265 genes with average FPKM values greater than 1 , 33 of them exhibited average FPKM values greater than 100. Notably, only one defense-related gene, Glyma.12G027100 (TIR- NBS-LRR class), had an average FPKM value exceeding 1000.

[0315] The genes were classified into two groups: lowly expressed genes with average FPKM values ranging from 1 to 100 (n=233) (Figure 15A), and moderately expressed genes with average FPKM values greater than 100 (n=32) (Figure 15B). A wide range of expression patterns was observed; however, young nodules (2 wpi) and mature nodules (9 wpi to 10 wpi) particularly appeared to exhibit the highest expression levels for most of the genes. This suggests that both early and late stages of nodule development are critical periods for the activation of defense-related genes, potentially reflecting the dynamic interplay between symbiosis and host immunity during these phases.A majority of symbiotic-related genes cluster into four distinct expression groups

[0316] The expression of genes previously identified was analyzed as playing roles in root nodule symbiosis from 2 wpi to 10 wpi. A list of 73 symbiotic-related soybean genes was compiled (Table 2), which was divided into seven functional categories. It was recognized that some genes could belong to multiple categories, as many gene families were grouped together for ease of analysis despite having the potential for diverse functions:PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0317] (i) Lysin-Motif receptor-like kinase (LysM-RLK) proteins (n=17), known for recognizing rhizobial signals and initiating symbiotic interactions. LysM-RLKs (LYK) have recently been identified in soybean roots as responsive to rhizobia and nitrate treatments, expanding their roles in both nitrogen fixation and nitrogen response processes (Yao et al. 2023).

[0318] (ii) Early Modulation genes (n=12), including Nodulin and NODULE INCEPTION (NIN) genes, essential for the early stages of nodule formation.

[0319] (iii) LEGHEMOGLOBIN (Lb) and HEMOGLOBIN (Hb) genes (n=6), which facilitate oxygen transport within nodules, thus enabling symbiotic nitrogen fixation. Notably, Lb genes in Medicago truncatula have been discovered to be regulated by NIN-like protein (NLP) transcription factors, particularly NLP2 and NIN, through nitrate-responsive element-like (NRE- like) promoter elements (Jiang et al. 2021 ).

[0320] (iv) Genes involved in the AON pathway (n=8), such as TOO MUCH LOVE (TML) and Rhizobia-lnduced CLE peptides (RICs), which together regulate the number of nodules formed to balance nitrogen fixation and plant growth (Lim et al. 2011 ; Ferguson et al. 2019).

[0321] (v) Nitrate regulation of nodulation genes (n=13), including NIN-like proteins(NLPs), Nitrogen-Induced CLE peptides (NICs) and NODULE AUTOREGULATION RECEPTOR KINASE (NARK). In response to nitrate, NIC1 is activated by NLP1 and NLP4 and mediates the nitrate regulation of nodulation pathway - in a NARK dependent manner (Fu et al. 2024). It is important to note, NARK expression in shoots has been demonstrated to be necessary for the autoregulation of nodulation, while NARK expression in roots is required for the nitrate regulation of nodulation (Reid et al. 2011 a). Based on that, the observed NARK expression in this study was attributed to be associated with the nitrate regulation of nodulation pathway rather than the autoregulation pathway.

[0322] (vi) Nitrogen metabolism and transport genes (n=12), including nitrate and ammonium transporters, as well as genes involved in assimilation of nitrogen derived from nitrogen fixation, such glutamine synthetases. Nitrate-transporter 2.1 (NRT2.1) is included in this group. NRT2.1 is activated by NIC1 , leading to increased nitrate uptake in roots. This, along with the abovementioned recognition of NIC1 by root-NARK, hinder nodulation in response to non-symbiotic nitrogen (Fu et al. 2024).PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0323] (vii) Miscellaneous genes (n=5), known to play a role in nodulation but not included in any of the previous categories.

[0324] This comprehensive categorization highlights the diverse genes and roles they play in facilitating and regulating the complex process of root nodule symbiosis in soybeans. It is important to note that the absence of a gene from this list does not imply a lack of significance in nodulation or symbiosis; rather, it may indicate that the gene was outside the scope of this study or was inadvertently overlooked.

[0325] Individual genes exhibited a wide-range of expression levels, averaged over the observation period, from low-to-high (1 to greater than 200,000 average FPKM). Based on average FPKM values, genes were classified as lowly expressed (1 to 100 FPKM, n=42), moderately expressed (100 to 1000 FPKM, n=16), or highly expressed (greater than 1000 FPKM, n=15).

[0326] To identify unique temporal gene expression patterns, the genes were further categorized into five groups based on expression pattern throughout the observation period. These groups included: (i) high-to-low (n=15), (ii) high-to-low-to-high (n=9), (iii) low-to-high-to- low (n=12), (iv) low-to-high (n=26), (v) steady or no discernable pattern of expression (n=11 ). Five heat maps corresponding to these groups were generated, visually representing the diverse temporal dynamics of gene expression throughout soybean nodule development (Figure 16).PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webGenes involved in nodulation initiation might have a dual role in nodule senescence

[0327] Based on observed expression patterns, 24 genes were identified that exhibited their highest expression levels early in nodule development (2 wpi to 3 wpi) (Figures 16A and 16B). Notably, more than a quarter of the early-expressing genes (n=7) are LYK genes. Six of the genes are involved in early nodulation, including nodulin-26 (N-26), three EARLY NODULIN genes including, ENOD36A (previously referred to as ENOD40 in an older genomePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web version (Wm82.a1.v1.1 )), two copies of ENOD93 (both on chromosome 17), RHIZOBIUM- INDUCED PEROXIDASE 1 -like (RIP1 ), and NIN1 a. Nodulin-26, an aquaporin protein and major component of the symbiosome membrane, facilitates water and solute transport between host and rhizobia (Rivers et al. 1997). Notably, NRT2.1 was included in this group, which is involved in the Nitrogen Regulation of Nodulation pathway.

[0328] This group also included several genes involved in nodulation that had been identified as targets of miRNAs. TARGET of EAT1-like 4a (TOE4a), an AP-2 transcription factor that represses flowering by restricting FLOWERING LOCUS T (FT) transcription, is regulated by miR172c, whose production is triggered by the presence of rhizobia (Yun et al. 2023). Nodulin RIP1 is regulated by miR4416 (Yan et al. 2016). SCARECROW-LIKE 6 (SCL6- 1 ), a GRAS-domain transcription factor crucial for proper nodule development and function, is regulated by miR171o (Hossain et al. 2019). Another member of the miR171 family, miR171 q regulates NODULATION SIGNALING PATHWAY 2 (NSP2.1 ) (Hossain et al. 2019). ENOD93, which plays a key role in nodule formation, is regulated by miR393j-3p (Yan et al. 2015).Notably, ENOD36a is activated by Nuclear Factor-y Subunit A (NFYA-C) (Glyma.10g082800), which is regulated by miR169c in the presence of high levels of non- symbiotic nitrogen (Xu et al. 2021 ).

[0329] Among the early-expressing genes, nine exhibited the high-to-low-to-high expression pattern, returning to higher expression levels late in development (9 wpi to 10 wpi) (Figure 16B). Notably, five of these genes are related to the AON pathway, including all three TML genes (TML1 a, TML1 b, and TML2) and the NOD Factor Receptor NFR5b. This group also included RIC2 peptides, which are known to be expressed in young nodules (Lim et al. 2011 ). This expression pattern suggests that these genes may have dual roles in both early nodulation and in nodule senescence.Genes involved in nitrogen fixation are transcriptionally most active around 4 wpi to 6 wpi

[0330] A third group of genes (n= 12) exhibited a low-to-high-to-low expression pattern, with peak accumulation around 4 wpi to 6 wpi, coinciding with the highest activity of nitrogen fixation (Figure 16C). This group included all five leghemoglobin (Lb1 to Lb5)PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web genes, as well as genes involved in nitrogen assimilation and transport, such as GS1b, GS1y, and ALN4. It is worth noting that ALN4 and GS1y peaked in expression at 3 and 4 wpi, which was earlier relative to the other genes in this group. Additionally, this group included two early nodulation genes, including a highly expressed nodulin gene, N-44, encoding a peribacteroid membrane protein, and NIN2A, as well as two LYK genes. The peribacteroid membrane, which encases the nitrogen-fixing bacteroids within the nodule, is crucial for maintaining an optimal environment for nitrogen fixation. Notably NLP2, identified as an activator of leghemoglobin gene expression in Medicago, was absent from this group.

[0331] However, NIN2a was present in this group, indicating a potential role in leghemoglobin activation in soybeans. Taken together, the genes included in this group play vital roles in nitrogen fixation and are transcriptionally regulated to increase their expression during peak stages of activity. Consequently, these genes can be considered strong candidates as biomarkers for nitrogen fixation.Transcription of key genes of the nitrate regulation of nodulation pathway are upregulated in mature nodules during senescence

[0332] The fourth group of genes (n = 26) exhibited an expression pattern from low- to-high, reaching its peak between 8 wpi and 10 wpi, indicative of their involvement in the nodule senescence process (Figure 16D). Among these genes, many are key players in (i) the Nitrate Regulation of Nodulation pathway, encompassing eight NLPs, NARK, and one NIC (NIC1), as well as (ii) Nitrogen Metabolism and Transport. Notably, two nodule inception genes, NIN1b and NIN2b, within this group exhibited heightened expression in later stages of nodule development, suggesting a potential alternative or dual function in nodule senescence. Additionally, this group encompassed RIC1, known to be enriched in mature nodules, and the nodulin gene N21 (VTLA), an iron transporter crucial for providing iron to bacteroids. Iron is an essential cofactor for nitrogenase and leghemoglobin synthesis in infected cells (Day and Smith 2021 ).Soybean nodules contain small RNAs of plant and bacterial originPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0333] To investigate the role that small RNAs play in symbiotic-related processes, the same samples previously used for RNAseq and constructed small RNA libraries were utilized. In total, 27 libraries, comprising three biological replicates for each of the nine time points sampled (2 wpi to 10 wpi), with an average of 39 million reads per sample were generated. Mapping these reads to both the soybean genome (Gmax_\N82 v4.a1 , from SoyBase) and the Bradyrhizobium LISDA110_ASM164267v1 genome (from NCBI), an average mapping rate of approximately 60% to the soybean genome and an additional -25% to the Bradyrhizobium genome were observed. Cumulatively, around 85% of the library reads were mapped to both genomes, ranging from 78 to 90% across samples (Figure 17).

[0334] The size distribution of sRNA reads originating from both the plant and rhizobia to dissect the sRNA composition within nodules was analyzed. sRNA reads mapped to the plant genome displayed three major peaks, at 21 , 22, and 24 nt (Figure 18A). This pattern, commonly observed in plant tissues, typically reflects a high abundance of 21 nt miRNAs, and a 24 nt peak corresponding to hc-siRNAs. However, during the early stages of nodulation (2 wpi to 3 wpi), it was observed that the highest peak was 22 nt, which was progressively overtaken by the peak at 21 nt by 4 wpi. By mapping all reads to different genome features, it was identified that this peak of 22 nt sRNAs primarily corresponds to ribosomal RNA fragments (rRFs) and transposable elements (TEs) (Figure 19). In contrast, for sRNAs originating from rhizobia, no distinct or dominant peak of any specific sRNA size was observed (Figure 18B). Instead, a broader distribution of sRNA sizes was detected, ranging from 17 to 35 nt in length. This observation suggests sRNAs originating from nodule-inhabiting rhizobia are diverse in size.

[0335] To describe the genomic origins of the sRNAs, all the reads were mapped to different annotated features of the soybean and Bradyrhizobium genomes (Figure 20). rnamer software (Lagesen et al. 2007) and tRNAscan (Chan and Lowe 2019) were used to identify ribosomal RNAs (rRNAs) and transfer RNAs (tRNAs) respectively for both the soybean and Bradyrhizobium genomes. It was observed that, as it commonly happens, a substantial portion of the reads originated from rRNAs of both plant and bacterial origin. It was also observed that the abundance of reads originating from 21 nt miRNAs remained relatively consistent across weeks (Figure 20).PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web miRNAs play a different role in each stage of nodule development

[0336] To understand the miRNA-mediated regulation across nodule development, ShortStack v4.4 was used to de novo annotate potential miRNAs that may have been overlooked before. ShortStack identified 180 confident miRNAs, and 196 miRNA candidates, all of which were already annotated in miRBase v22 (Kozomara et al. 2019). However, using the recommended parameters, no new miRNAs were identified. Therefore, the annotated soybean miRNAs from miRBase were used for the rest of this study. Out of the 756 annotated miRBase miRNAs in soybean, 748 were successfully identified, with 581 exhibiting at least five reads at one or more time points.

[0337] Leveraging this comprehensive list of nodule miRNAs, differential expression analysis was performed using the DESeq2 pipeline (Love et al. 2014). Principal Component Analysis (PCA) (Figure 21 A) revealed discernible differences primarily driven by the various stages of nodule development, with three distinct groups: (i) 2 wpi and 3 wpi, (ii) 4 wpi to 7 wpi, and (iii) 8 wpi to 10 wpi. Each stage was compared to its immediate predecessor and identified 55 distinct miRNAs that differentially accumulated (DA) during the transition between two nodules stages (one-week of growth) (Figure 21 B). Notably, most DA miRNAs appeared during the comparison between 2 wpi and 3 wpi, as well as between 6 wpi and 7 wpi, suggesting these stages or periods of nodule development might serve as pivotal points for miRNA-mediated transcriptional regulation in nodules.

[0338] It was observed that most of the DA miRNAs were specific to each stage of development (Figure 21 C). Additionally, considering both upregulated and downregulated DA miRNA, approximately 10% of the 55 distinct DA miRNAs (n=6) were identified across multiple comparisons separated by at least a 3-week span (Figure 21 C). Specifically, this analysis identified three miRNAs (all members of the miR395 family) that were consistently expressed in the 3 wpi to 4 wpi and 7 wpi to 8 wpi comparisons. Additionally, two miRNAs (members of the miR397 family) were found to be shared across the 2 wpi to 3 wpi, 3 wpi to 4 wpi, and 6 wpi to 7 wpi comparisons. Moreover, miR156e was detected in the 2 wpi to 3 wpi, 8 wpi to 9 wpi, and 9 wpi to 10 wpi comparisons. This overlapping expression of specific miRNAs inPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web different developmental comparisons suggests they may have critical roles in coordinating the various phases of nodule development and senescence. miRNAs involved in plant growth, development, and stress response processes are highly accumulated in nodules during peak nitrogen fixation

[0339] As previously mentioned in the RNAseq study, it was hypothesized that the expression of some miRNAs might change gradually, leading to no apparent differential accumulation (DA). To understand these changes, the same approach was taken and (i) checked for DA miRNAs that are up when comparing 2 wpi to 5 wpi, and down when comparing 5 wpi to 10 wpi, and (ii) conducted a hierarchical clustering analysis where miRNA expression is grouped according to their patterns.

[0340] The analysis of the 2-up-5-down-10 accumulation pattern, identified 22 miRNAs exhibiting this trend (Figure 22A). Among these, 19 miRNAs belong to nine distinct miRNA families: four members of the miR2111 family, two members of the miR393 family, three of the miR397 family, two of the miR398 family, four of the miR399 family, and four of the miR408 family. Many of these miRNA families play specific roles in plant growth and development, and stress response processes, suggesting their significant involvement in soybean nodulation.

[0341] Notably, miR2111 is integral in the AON pathway. In response to RICs from mature nodules, miR2111 expression is downregulated, allowing its target, TML, to inhibit new nodulation (Zhang et al. 2021 ). This study demonstrates that miR2111 family miRNAs followed the 2-up-5-down-10 expression pattern, mirroring the low-high-low trend observed in symbiotic nitrogen fixation. All three soybean TML genes - TML1a, TML1 b, and TML2 - show a contrasting high-low-high expression pattern, underscoring their regulation by miR2111 . This indicates a tightly controlled feedback mechanism where miR2111 and TML modulate nodulation in response to existing nodule activity.

[0342] miR393 targets auxin receptors, which are crucial for maintaining the homeostasis of auxin signal perception, affecting plant growth, development, and stress responses (Jiang et al. 2022). Auxin signaling plays a pivotal role in root architecture and nodule formation, making miR393 a key regulator in nodulation and stress adaptation processes. Additionally, miR393 is implicated in the regulation of genes involved in thePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web isoflavonoid biosynthetic pathway during stress responses, further highlighting its multifaceted role in plant stress physiology (Yan et al. 2015).

[0343] miR397 targets laccase (LAC) genes involved in lignin synthesis, contributing to plant growth, development, and stress responses (Huang et al. 2021 ). Lignin is essential for cell wall integrity and defense against pathogens. Previous studies have shown increased expression of miR397 from young to older nodules, though only up until 30 days postinoculation (around 4 wpi) (Yan et al. 2015). This study extends these findings by identifying a high-to-low expression pattern in miR397 family members in nodules from 5 wpi to 10 wpi, highlighting their sustained role in nodule maturation and nitrogen fixation.

[0344] miR398 has been described as a master regulator of plant development and stress responses (Li et al. 2022a) and is known to control oxidative stress in nodules (Yan et al. 2015). Oxidative stress management is crucial for maintaining nodule function and efficiency, as reactive oxygen species (ROS) can damage cellular components and inhibit nitrogenase activity. miR398, along with miR399 and miR408, has roles in phosphate starvation responses in soybean (Xu et al. 2013). Phosphate availability is critical for ATP production and energy transfer within cells, affecting overall plant health and nodule function.

[0345] This results provide comprehensive insights into the dynamic roles of these miRNAs in soybean nodule development and stress responses, emphasizing their regulatory significance in nitrogen fixation. The identification of these miRNAs and their expression patterns offers valuable insights for studying and potentially manipulating nodulation and nitrogen fixation efficiency in soybean, with broader implications for legume crop improvement and sustainable agriculture. miRNA clustering identifies additional miRNAs implicated in nitrogen fixation processes

[0346] Using the WGCNA software (Langfelder and Horvath 2008), 11 different clusters (Figure 22) were identified. Clusters ME8, ME1 , ME7, and ME10 (colored in red) showed high expression at 2 wpi, suggesting that these miRNAs might play a role in early nodule development. miRNAs in clusters ME9, ME11 , ME4, and ME5 (colored in blue) had high levels of accumulation in the later stages, between weeks 8 and 10, implying a possible role during developmental nodule senescence. Notably, miRNAs in clusters ME6, ME3 and ME2 had highPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web accumulation between weeks 4 and 6, corresponding with periods of high nitrogen fixation. Consistent with the observed high-to-low-to-high expression pattern identified in the survey of symbiotic-related gene expression, miRNA in clusters ME7 and ME10 demonstrate a similar pattern of expression. Taken together, these results indicate four conserved temporal expression patterns amongst nodule miRNAs.

[0347] Interestingly, miR2111 is part of cluster ME2, which comprises 32 other miRNAs. Notably, the miRNAs in this cluster are implicated in nitrogen fixation and are the same miRNAs identified in the 2-up-5-down-10 expression group. This finding corroborates the results of the previous differential accumulation analysis, further validating the role of these miRNAs in regulating nitrogen fixation processes.Contrasting expression patterns revealed in key miRNA-target pairs involved in different stages of nodule development

[0348] Previously reported miRNAs that regulate genes in the symbiotic- related genes list were examined. Notably, miR4416 and its target, RIP1, as well as miR171 q and its target, NSP2. 1, exhibited contrasting expression patterns. When RIP1 was highly expressed in nodules, miR4416 was at its lowest expression level, and conversely, when RIP1 expression was low later in nodule development, miR4416 expression peaked. Similarly, NSP2.1 showed a low-to-high expression pattern, whereas miR171q showed a high-to- low pattern. In contrast, miR171o and its target, SCL6-1, as well as miR169c and its target, NFYA-C, shared a low-to- high expression pattern. Of note, NFYA-C is a known activator of ENOD36a (formerly ENOD40) (Xu et al. 2021 ); however, in this study, ENOD36a exhibited a contrasting high-to- low expression pattern compared to its activator. Other known miRNAs that regulate symbiotic- related genes, such as miR172c and miR393j-3p, were not included in the cluster analysis, likely due to their low levels of accumulation. phasiRNA accumulation is stage-specific but occurs during all stages of nodule development

[0349] Additionally, three different families of miRNAs have been described as phasiRNA triggers in soybean, specifically miR1507, miR2109, and miR2118 (Wong et al.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web2014). To predict phasiRNAs in the samples, an older version of ShortStack (v3.8) was used. This analysis yielded a total of 83 clusters with a phasing score of 35 or higher. These loci had an average length of approximately 2100 nt (with a minimum of 197 nt and a maximum of 6475 nt), and were distributed across all chromosomes except chromosome 2, with a higher concentration on chromosomes 9, 10, 16, and 19. Among these PHAS loci, only two accumulated 24 nt sRNAs, while the majority produced 21 nt phasiRNAs (Figure 23B).Notably, 28 of these PHAS loci overlapped with known NBS-LRRs (pNLs), and one overlapped with a gene encoding a pentatricopeptide repeat (PPR) protein, both of which are known producers of phasiRNAs (Arikit et al. 2014).

[0350] The expression profiles of miRNAs known to trigger phasiRNAs (Figure 23A) were examined. Four miRNAs — miR2109-3p, miR2118a-5p, miR2118b-5p, and miR2109-5p— showed high expression levels during early stages of nodulation. Conversely, three miRNAs— miR1507a, miR2118a-3p, and miR2118b-3p — exhibited elevated expression levels at the late stages of nodulation. Additionally, miR1507c and miR1507b were expressed at both the early and later stages of nodulation. Correspondingly, phasiRNA expression per locus was distributed across all stages of nodule development, reflecting the temporal dynamics of their miRNA triggers (Figure 23C). Notably, the low-high-low expression pattern in phasiRNA expression analysis identified in symbiotic-related genes and miRNA expression analyses were not observe.5’ tRNA halves accumulate at late stages in nodule development, while 5’-tRFs accumulate early

[0351] tRNA-derived fragments (tRFs) play diverse roles across various organisms, including responses to abiotic and biotic stresses and facilitating cross kingdom communication (Ma et al. 2021 ). In the soybean-Rhizobium symbiosis, Bradyrhizobium tRFs target and regulate soybean genes involved in root hair development. The inhibition of these gene targets by rhizobial tRFs stimulates nodule formation, initiating the symbiotic relationship essential for nitrogen fixation and plant growth (Ren et al. 2019).

[0352] In this samples, reads mapping to tRFs from both the plant and the bacteria were identified. The size distribution of the plant tRFs revealed three major peaks. The first peak, atPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web16 nt, was expressed at all time points, from 2 wpi to 10 wpi, but showed high expression levels only from 2 wpi to 6 wpi, suggesting a potential role in nitrogen fixation. The second peak, at 27 nt, was only present in young nodules, from 2 wpi to 3 wpi, indicating a possible role in early nodule development. The third peak, at 31 nt, was prominent from 5 wpi to 10 wpi, suggesting a potential role in nodule senescence (Figure 24A). tRFs of these sizes are often derived from tRNA quarters and tRNA halves respectively.

[0353] The software Unitas (Gebert et al. 2017) was used to analyze the origin of the tRFs in the tRNA (Figure 24B). As observed in the size distribution, the most abundant fragments are 5p-tRFs (first quarter of the 5’ end of the tRNA) and 5p-tRNA-halves. It is important to note that due to the library construction method, the libraries could only capture the 5’ end of tRNAs, introducing a bias. However, The accumulation patterns of 5p-tRFs and 5p-tRNA-halves can be distinguished based on their differing size profiles and processing features.. The accumulation of the 5p-tRFs increases from 2 wpi to 6 wpi and decreases back to the same levels by 10 wpi. In contrast, the accumulation of 5p-tRNA-halves gradually increases from 2 wpi, reaching its maximum expression at 9 wpi. This differential accumulation suggests distinct roles for 5p-tRFs and 5p-tRNA halves during different stages of nodule development.

[0354] Regarding the type of tRNA, all the tRNA loci were grouped by their anticodon due to their sequence similarity (Figure 25). The analysis revealed that most of the tRFs originated from tRNAs encoding Glutamine (both anticodons UUC and CUC), followed by those encoding Alanine (both AGC and CGC) and Glycine (both GCC and UCC). The underlying reason for this distribution remains unclear, but it is important to consider that tRNAs are highly modified molecules, and the existing library preparation methods may not efficiently capture these modified RNAs. This potential bias should be taken into account when interpreting the data.

[0355] Regarding the bacterial tRFs, a size distribution distinct from that of plant tRFs was observed (Figure 26). Most samples displayed two prominent peaks at 28 nt and 30 nt, along with a double peak at 34 nt and 35 nt. It was hypothesized that these peaks correspond to tRNA-halves. However, Unitas did not yield any results, possibly due to intrinsic differences in bacterial tRNA structure. This discrepancy suggests that the unique structural features ofPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web bacterial tRNAs might influence the formation and detection of tRFs, underscoring the need for tailored approaches to analyze bacterial tRNAs and tRFs.DISCUSSION

[0356] To identify regulatory genes and small RNAs involved in the regulation of soybean nodule nitrogen fixation, the metatranscriptome of nodules was characterized, accounting for both plant (Glycine max cv. Williams-82) and bacterial (Bradyrhizobium diazoefficiens USDA110) RNA throughout nodule development, from 2 wpi to 10 wpi. RNA sequencing, small RNA sequencing, nitrogenase activity assays was integrated, and analysis of two symbiotic-related proteins to unravel the temporal transcriptional regulatory dynamics of soybean nodules.

[0357] In this study, nitrogen fixation via nitrogenase activity peaked at 5 wpi. However, this peak did not correlate with a distinct rise in the number of root nodules or their combined mass, nor was it identified in Bradyrhizobium diazoefficiens nifH expression or NifH protein level. Glycine max LBA protein exhibited a low-to-high-to-low pattern of accumulation, similar to nitrogenase activity, but both Lb3 expression and its LBA protein peaked at 6 wpi, one week after nitrogenase activity peaked. These results suggest that nitrogenase activity and thus nitrogen fixation is regulated by processes beyond these measured parameters.

[0358] Previous studies have indicated the existence of a systemic regulation pathway for nitrogenase activity (Yashima et al. 2003; Lyu et al. 2019, 2022). This pathway is distinct from the systemic regulation of nodule number by the Autoregulation of Nodulation (AON) pathway (Li et al. 2022b) and the localized nitrate-mediated inhibition of nodulation pathway (Fu et al. 2024), which is also broadly referred to as the Nitrogen Regulation of Nodulation pathway (Ferguson et al. 2019).

[0359] Analysis of nitrogenase activity were performed using the acetylene reduction assay (ARA) on soybean whole-root systems from 4 wpi to 7 wpi. The whole-root systems was assayed to capture comprehensive plant nitrogenase activity and avoid biases that may be introduced when assaying smaller subsets or fractions of nodulated root systems.

[0360] However, due to the substantial root size at 7 wpi, nitrogenase activity studies were limited to this time point, as further growth made measurements impractical.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webBradyrhizobium nifH gene expression was analyzed and NifH protein content from 2 wpi to 10 wpi, and noted a gradual and sustained rise in both. Interestingly, while nitrogenase activity peaked at 5 wpi and declined thereafter, NifH levels continued to increase from 5 wpi to 10 wpi. This mismatch in patterns led us to conclude that nifH expression does not correspond directly with nitrogenase activity and is therefore not a reliable indicator of nitrogen fixation activity. The nifH gene, though an essential component of the nitrogenase enzyme, is the most highly expressed nif gene in Bradyrhizobium USDA110 (Franck et al. 2018) and may be expressed in excess. This suggests that nifH regulation is primarily under the control of the rhizobia rather than the host plant.

[0361] The continued upregulation of nifH well after peak nitrogenase activity and into the early stages of nodule senescence implies that the rhizobia may continue to express nifH even when the nodule environment becomes suboptimal. Nodule senescence is characterized by the breakdown of nodule cells and a decline in metabolic activities, including nitrogen fixation. During this stage, the supply of carbon compounds from the host to the rhizobial bacteroids diminishes, leading to reduced energy availability for the rhizobia and nitrogen fixation. Despite the declining energy supply and nodule environment, the data indicates that rhizobia continue to transcribe nifH and produce NifH protein. This could be part of a stress response or in an effort to maintain nitrogenase activity under less favorable conditions, in order to acquire nitrogen for its own use.

[0362] Since it has been described that “the host controls the party” in the context of the legume Rhizobium symbiosis (Ferguson et al. 2019), the G.max Leghemoglobin-3 (Lb3) gene was investigated, the most highly expressed leghemoglobin gene in soybean nodules (Du et al. 2020), and the levels of its corresponding protein, LBA. Leghemoglobin proteins play a crucial role in modulating oxygen levels within nodules. It was observed that Lb3 and LBA both peaked at 6 wpi, notably one week after peak nitrogenase activity. This suggests that, similar to nifH / NifH, Lb3 / LBA are not good biomarkers for nitrogen fixation.

[0363] However, the timing of the Lb3 and LBA peaks, occurring after peak nitrogenase activity, indicates that nodule leghemoglobin components are involved in processes other than directly regulating nitrogenase activity. Following their peak levels, Lb3 expression gradually declined, whereas LBA protein remained relative stable for two weeks and then declined fromPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web8 wpi to 10 wpi. The stabilization of LBA protein levels from 6 wpi to 8 wpi, despite the decline in its transcript Lb3, suggests post-transcriptional regulation or protein stability mechanisms that maintain LBA levels temporarily. Notably, there was a significant increase in the total number of nodules per plant from 5 wpi to 6 wpi, coinciding with a striking elevation in LBA levels during the same period.

[0364] A recent study in Medicago truncatula revealed that leghemoglobin-encoding genes (leghemoglobins, hereafter) are activated by NODULE INCEPTION (NIN) and NIN-LIKE protein 2 (NLP2) transcription factors in a redundant manner (Jiang et al. 2021 ). Furthermore, the expression levels of individual leghemoglobins were found to correlate with the conservation of a nitrate-response element-like (NRE-like) promoter motif, a target site for Mt.NIN and Mt.NLP2. Specifically, leghemoglobins with highly conserved

[0365] NRE-like motifs exhibited higher levels of expression in nodules.

[0366] Jiang et al. (2021 ) also identified NRE-like target sites upstream of soybean Gm. Lb (Lb1 through 4) and Gm.Hbl and Hb2 genes. In support of their hypothesis, they compared expression levels (from Soybase) with the number of mismatches and indels (insertions or deletions) on each Lb gene’s respective NRE-like promoter motif. The results confirmed that leghemoglobins with highly conserved NRE-like motifs exhibited higher expression levels in soybean nodules. Additionally, Gm.Lb5 was investigated and confirmed the presence of an NRE-like promoter motif (61 bp in length) roughly 900 bp upstream of its transcriptional start site. RNAseq analysis corroborated that expression of each leghemoglobin and hemoglobin gene generally correlates with how conserved its NREIike promoter motif is, with minor differences. For instance, Lb3, the highest expressing Lb gene, has five mismatches, while Lb5, the lowest expressing gene, has 12 mismatches and one single base pair insertion. Similarly, Hb2, the only expressed non-symbiotic hemoglobin gene in soybean nodules, has 18 mismatches and exhibits moderate expression, whereas Hb1 , whose expression was not detected in the nodule samples, has 11 mismatches and one deletion. Additionally, Lb2, Lb1 , and Lb4 exhibit 9, 10, and 8 mismatches in the NRE-like promoter motifs, respectively. These findings support the hypothesis that leghemoglobin expression is dependent on the conservation of its NREIike promoter motif these findings.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0367] Additionally, Gm.NIN2a exhibited an expression pattern similar to the low-to- high-to-low expression pattern of Gm. Lb genes. In contrast, the soybean NLP2 genes, NLP2a and NLP2b, displayed a low-to-high pattern of expression. This suggests that NIN2a transcription factors may play a crucial role in recognizing and binding to NRE-like promoter motifs, thereby activating and regulating leghemoglobin expression in soybean nodules.

[0368] Upon further examination of the temporal expression patterns of all five leghemoglobin genes and Hb2, it was observed that while all Lb genes had similar expression patterns, there were distinct differences among them. Specifically, Lb1 and Lb4 exhibited peak expression at 5 wpi, while Lb3 and Lb5 peaked at 6 wpi. Lb2 expression peaked between 5 wpi and 6 wpi. This suggests specialized roles for each individual LB protein. Notably, Lb1 and Lb4 genes peaking at 5 wpi, coincided with peak nitrogenase activity, indicating that Lb1 and Lb4 could serve as a reliable biomarker for nitrogen fixation. However, no antibody currently exists for their corresponding proteins, LBC3 and LBC2, respectively. It would be valuable to have specific antibodies for each of the five LB proteins, but currently, only an antibody for LBA is commercially available.

[0369] An additional 50 genes were identified that exhibited a distinct 2-up-5-down-10 pattern of expression in nodules, which could serve as reliable biomarkers for symbiotic nitrogen fixation. Among these genes are Argonaute 5 (AG05), nodulin (N-44) peribacteroid membrane, and four glutamine synthetase (GS1 ) family members. The presence of AG05 suggests its involvement in fine-tuning the regulatory mechanisms essential for efficient nitrogen fixation, complementing its established role in nodule establishment (ReyeroSaavedra et al. 2017). This also indicates a significant role for small regulatory RNAs (sRNAs) in the nodulation process, a topic explored in the next sections.

[0370] Notably, Dicer-like (DCL) genes exhibited two distinct patterns of expression in nodules. DCL2 and DCL4, were predominately expressed in early nodules, whereas mature nodules were enriched in DCL1 and DCL3 transcripts. Each of these DCL proteins in involved in the biogenesis of a different type of small RNA, mediating the cleavage of the small RNA precursor into mature sRNAs of different size and function. This observation shows that diverse types of small RNAs are involved in different stages of nodule development.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0371] The early stages of nodule development, ranging from pre-inoculation to around 4 wpi, have been extensively studied. Previous studies have uncovered many diverse roles of miRNAs in nodules, particularly during nodule initiation and early nodule development (Subramanian et al. 2008; Simon et al. 2009; Yan et al. 2016; Hoang et al. 2020). However, due to the primary focus on early symbiosis, the understanding of sRNAs involved in later stages, such as nitrogen fixation and senescence, remains limited. The knowledge of miRNAs in nodules was expanded by extending the time frame of analysis from 2 wpi to 10 wpi. In this study, sRNA sequencing captured 581 miRNAs with at least five reads at one or more time points. The abundance and diversity of these miRNAs suggest many yet unidentified roles in regulating various aspects of nodule development and function. Specifically, 22 miRNAs exhibited the 2-up-5-down-10 pattern of expression, including four members of the miR2111 family. The miR2111 family is a known positive regulator of nodulation and is involved in the autoregulation of nodulation (AON) pathway. Other identified miRNAs are associated with plant growth, development, and stress responses. These miRNAs are likely involved in complex regulatory networks that fine-tune processes crucial for symbiosis, including nitrogen fixation and the transition to senescence. To further elucidate the functions of the understudied miRNAs, employing CRISPR knockout technology could be highly beneficial. This approach would allow us to disrupt specific miRNA precursors and observe the resulting phenotypic changes, thereby identifying their target genes and elucidating their roles in different stages of nodule development.

[0372] A total of 83 PHAS loci were identified, with the majority expressing 21 nt phasiRNAs throughout all stages of nodule development. Roughly one-third (n=28) of these PHAS loci mapped to NBS-LRR disease-related genes, highlighting the significance of phasiRNA regulation of disease resistance genes to facilitate rhizobial infection and persistence during symbiosis. The analysis revealed three distinct patterns of phasiRNA expression: high-to-low, high-to-low-to-high, and low-to-high. Interestingly, no phasiRNAs exhibited a low-to-high-to-low pattern of expression typically associated with nitrogen fixation. This finding suggests that while phasiRNAs are integral to various stages of nodule development, they may not directly target genes involved in the regulation of nitrogen fixation.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0373] Furthermore, four conserved expression patterns in soybean genes and miRNAs have been identified. These patterns include the following: high-to-low, high-to-low-to-high, low-tohigh-to-low, and low-to-high. This indicates that transcriptional regulation happens at the interphase between the three major stages of nodule development: early nodulation (2 wpi to 3 wpi), nitrogen fixation (4 wpi to 7 wpi) and the transition from nitrogen fixation to senescence (7 wpi to 10 wpi). The conserved presence of these distinct expression patterns suggests that the genetic elements involved in each pattern play specific roles and functions in nodules. Additionally, this observation highlights the complexity and precision of the transcriptome and its regulatory machinery within nodules across different developmental stages. Notably, it was discovered that nine symbiotic-related genes and 40 miRNAs, many of which are known to play roles in the AON pathway — such as NFR5b, TML1a, TML1 b, TML2, and RIC2 — exhibit low expression during early nodulation but show significantly elevated expression levels during the transition to senescence. This suggests a potential dual role for these genes and miRNAs, highlighting their importance not only in the initial stages of nodulation and the autoregulation of nodulation, but also in modulating the senescence process. This suggests that these genes and miRNAs may serve dual roles, not only in governing nodulation but also influencing the onset and progression of senescence within nodules. This dual functionality underscores the multifaceted nature of the regulatory mechanisms orchestrating nodule development and underscores the need for further investigation into the interplay between nitrogen fixation and senescence regulation.CONCLUSION

[0374] In conclusion, this study sheds light on the intricate regulatory mechanisms of nitrogen fixation in soybean nodules, emphasizing the dynamic interplay between the plant and its symbiotic bacterium throughout nodule development, nitrogen fixation, and senescence. By employing comprehensive metatranscriptome analysis, key regulatory genes and small RNAs that orchestrate these processes were identified. Notably, it was revealed that nitrogenase activity peaks at 5 weeks post-inoculation but does not align with conventional indicators like nodule number, mass, or nifH expression, underscoring the need for more reliable biomarkers such as leghemoglobin and specific small RNAs.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0375] The downregulation of miR2111 d and its regulatory relationship with TML1 b during the nitrogen response highlight the intricate control of nodule function by small RNAs. This study also emphasizes the integration of nitrogen and phosphate signaling pathways for optimal nodule performance. These insights provide a foundational understanding of the transcriptional regulation of nitrogen fixation, setting the stage for further investigations into how high nitrogen levels suppress this crucial process in subsequent examples. The identification of genes and small RNAs involved in the nitrogen response offers promising avenues for enhancing nitrogen use efficiency and developing sustainable agricultural practices that reduce reliance on synthetic nitrogen fertilizers.MATERIALS AND METHODSPlant and Bacterial Growth

[0376] All plants were cultivated in pots within the greenhouse facilities at the Donald Danforth Plant Science Center (St. Louis, Missouri, USA). The plants were maintained under a 1 - hour light / 10-hour dark cycle with temperatures of 25°C during the day and 20°C at night. Soybean seeds (Glycine max cv. Williams-82) were sown into 1 -gallon pots (two seeds per pot) containing a pre-rinsed substrate consisting of a 3:1 ratio of vermiculite to perlite. The plants were well-watered and fertilized regularly using a Dosatron system with reverse osmosis water and B&D nutrient solution formulated for growing legumes, which included minimal nitrogen supplementation (0.5 mM KNO3) (Broughton and Dilworth 1971 ).

[0377] The lesser of the two plantlets was sacrificed following the seven-day germinationperiod. Seven-day-old seedlings were then inoculated with 5m I of Bradyrhizobium diazoefficiens USDA110 diluted to 0.05 OD600nm. B. 79 diazoefficiens USDA110 (USDA-ARS culture collection, NRRL B-4361 ) was grown aerobically at 28°C in HM liquid medium at 6.8 pH prior to inoculation (Toth et al. 2016). Soybean (Glycine max cv. Williams-82) seed stocks used in this research were generated from seeds gifted by Doug Allen of the Donald Danforth Plant Science Center (St. Louis, Missouri, USA). Bradyrhizobium diazoefficiens USDA110 strain gifted by Gary Stacey of the University of Missouri - Columbia (Columbia, Missouri, USA).PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webAcetylene Reduction Assay (ARA) and calculation of Nitrogenase Activity

[0378] Nitrogenase activity was measured with the acetylene reduction assay, as detailed by Montez-Luz, B et al (Montez-Luz,B et al 2023). ARA measurements began at 4wpi and continued weekly until 7wpi, typically occurring between 10 and 11 am. Each plant was carefully excavated from its soil substrate, with a 10-minute interval between each extraction to ensure continuity between downstream GC-FID injections. Immediately following extraction, roots and shoots were separated and weighed independently. The entire root system was then placed in a 1 L airtight amber, wide-mouth, glass bottle with septum inlet (SKU 174832 Sci.Spec. Service Inc.). Using a large syringe, 5% of the air (50mL) was exchanged with acetylene gas, which was prepared in-house via the calcium carbide gas reaction, and incubated for 30 minutes at room temperature. Following incubation, a 500 pL gas sample was removed from the bottle and injected into a ThermoFisher Trace GC Ultra gas chromatograph with flame ionized detection; column #CP7584 PoraPLOT U (25m x 0.53mm x 20um). Gas samples were extracted and injected at two-minute intervals. A total of five gas injections were performed for each biological replicate over a 10-minute period or 30 to 40 minutes after the start of the initial acetylene incubation period.

[0379] Immediately after ARA sampling, root nodules were harvested from their respective root systems and weighed three hours after the start of the incubation period. Nodules were then counted by hand. Each root system served as a single biological replicate. Five root systems were sampled weekly. Four of the five plants underwent incubation with acetylene gas, while the fifth served as a negative control and remained untreated.Nitrogenase activity was calculated as the rate of ethylene produced (in nmols) per mg of nodule tissue per hour. An ethylene standard curve was generated and used to determine the amount of ethylene.Sampling (Nodule Collection)

[0380] Separate from plants designated for ARA sampling, soybean root nodules, aged 2 wpi to 10 wpi, were harvested weekly, typically between 9 and 10 am. Nodules were carefully collected in 2ml screw cap tubes, immersed in liquid nitrogen, and promptly stored at - 80oC. Each technical replicate (TR) comprised of three nodules in close proximity to the rootPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web crown of a single plant. One biological replicate (BR) corresponded to one plant. For each BR, four TRs to facilitate RNA and protein extractions were collected.RNA Extraction

[0381] Frozen nodules were manually grinded using pre-chilled (liquid N2) mortar and pestles. Ground tissue was further pulverized using a MM400 tissuelyzer (Retsch, Germany): 2x 45 sec at 30 Hz. Total nodule RNA was extracted using TRIreagent (Ambion, USA), following manufacturer’s instructions plus an additional isopropanol rinse to remove remaining polysaccharides (Protocol 1 : Soybean Nodule RNA Extraction).Quantitative Reverse Transcriptase Polymerase Chain Reaction (qRT-PCR)

[0382] cDNA was synthesized from 200ng of total nodule RNA using Maxima™ H Minus cDNA Synthesis Master Mix with dsDNase kit (Thermo Scientific, MA, USA), following manufacturer’s instructions. Random hexamer primers and oligo (dT)18’s was used for reverse transcription of both plant and bacterial RNA. Quantitative PCR (qPCR) was performed using primers designed for Bradyrhizobium USDA110 nifH and 16S genes. qPCR was performed using GoTaqTm qPCR Master Mix (Promega, Wl, USA) and Bio-Rad CFX384 Real-Time System with C1000 Touch Thermal Cycler (Bio-Rad Laboratories, California). Conditions included 95°C for 2min; 40 cycles (95°C for 15s and 60°C for 1 min), followed by melt curve from 65°C to 95°C, incrementally increasing 0.5°C every 5s. Bacterial nifH was quantified using qRT-PCR on nodule collected from soybeans grown in low nitrogen conditions (0.5mM KNO3) from 2 wpi to 10 wpi. Bradyrhizobium USDA110 16S gene was used as an endogenous control to evaluate relative transcript abundance with nifH. Relative expression values were calculated as the ratio of the expression value of the target gene to that of 16S using the 2-AACT method. Target gene-specific primers are listed in Table 1.RNA and small RNA sequencing and analysis

[0383] For RNA sequencing, 1 ug of DNAse l-treated total RNA was used (ThermoFisher Scientific, USA) for bacterial rRNA depletion using the commercial RiboMinus™ Bacteria 2.0 Transcriptome Isolation Kit (ThermoFisher Scientific, USA), directlyPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web followed by a second rRNA depletion using the plant specific commercial RiboMinus™ Plant Kit for RNA-Seq (ThermoFisher Scientific, USA). NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina was used (New England Biolabs, USA) to generate libraries. To ensure correct library size capture, a Bioanalyzer dsDNA HS chip assay was performed on the Agilent 2100 Bioanalyzer (Agilent Technologies, Inc.) for each library. All processes followed manufacturers’ instructions. All libraries were sequenced on a NovaSeq2000 instrument using 10O-bp paired-end reads.

[0384] For small RNA sequencing, 100ng of DNAse l-treated total RNA was used (ThermoFisher Scientific, USA) as input for the RealSeq-AC version two kit (Realseq Biosciences, USA). To ensure correct library size capture, a Bioanalyzer dsDNA HS chip assay was performed on the Agilent 2100 Bioanalyzer (Agilent Technologies, Inc.) for each library. All libraries were sequenced on a NovaSeq2000 instrument using 50-bp single-end reads.

[0385] For small RNA data analysis, the adaptors were trimmed using Cutadapt version 1.16 (Martin 2011 ) using a minimum insert size of 10 nt. Sequence quality was assessed using FastQC (http: / / www.bioinformatics.babraham.ac.uk / projects / fastqc / ). Clean reads were aligned to the Soybean genome Gmax_W82 v4.a1 (from Soybase) and the Bradyrhizobium USDA1 10_ASM164267 v1 genome (from NCBI) and all subsequent analyses were performed using the software Bowtie2 (Langmead and Salzberg 2012). For miRNA analyses, the latest version of miRbase was used (version 22; (Kozomara et al. 2019)). For the RNA-seq libraries were analyzed using HiSat2 and Stringtie pipeline (Pertea et al. 2016), and the annotation files of the genomes mentioned before. Differential accumulation analyses were performed using DESeq2 with default parameters, using reads that were not normalized as input (Love et al. 2014). In DESeq2, p-values were calculated using the Wald test and corrected for multiple testing using the Benjamini and Hochberg procedure. Graphical representations were generated using the software ggplot2 (Wickham 2016) in the R statistical environment.GO-term Enrichment (Shiny GO V0.80)

[0386] Shiny GO V0.80 software was used (Ge et al. 2020) for Gene Onthology (GO) enrichment analysis, with the recommended parameters and a False Discovery Rate cutoffPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web0.01 . For GO characterization without enrichment, the custom-made software of Soybase was used (Grant et al. 2010). In both cases, the Gmax_v4.a1 genome and annotation was used as a reference.Western blot analysis

[0387] Soybean Leghemoblobin-A (LBA) and Bradyrhizobium NifH proteins were extracted from soybean nodules and quantified utilizing Western Blot Analysis, facilitated by services rendered by Boster Bio (Pleasanton, CA, USA). Both LBA (anti-Rabbit) (Abbexa - abx345650) and NifH (anti-Chicken) (Agrisera - AS01 021 A) primary antibodies were used at 1 :1000 dilution. Soybean specific ACTIN (anti-Mouse) (Abclonal - AC009) primary antibody was used as an endogenous control at 1 :5000 dilution. Primary antibodies were both run on the same gel, using different channels. This was possible because LBA (16 kDa MW) and NifH (32 kDa MW) antibodies have different hosts and molecular weights.

[0388] Nodule protein was extracted using a urea-based proprietary method. Protein lysates were resolved on a 4-12% Bis-Tris Plus gel (Thermo Fisher) and subsequently transferred to a nitrocellulose membrane using Tris-Glycine buffer overnight. Each well was loaded with 10 pg of protein. Total protein was stained with Revert (LICOR). Blots were first probed with pooled primary antibodies for 16- to 24-hours at 2 to 8°C. Signal was detected by fluorophore conjugated secondary antibodies. Images were acquired by Odyssey CLx fluorescent imaging system (LICOR). Protein was quantified by analyzing band intensity using ImageStudio (LICOR).Example 2. Characterizing the Transcriptional Response During Nitrogen Regulation of Symbiosis in Soybean Nodules and Leaves

[0389] This study employs a comprehensive metatranscriptom ic analysis to investigate how nitrogen regulation influences nodulation and nitrogen fixation in soybean (Glycine max) during symbiosis with Bradyrhizobium diazoefficiens USDA110. Nitrogen, essential for plant growth, often necessitates synthetic fertilizers despite environmental concerns. Soybean forms root nodules that convert atmospheric nitrogen (N2) into ammonia (NH3) through intricate transcriptionally regulated molecular interactions. Soybean and Bradyrhizobium responsesPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web were assessed to high nitrogen across nodule development stages (4 to 6 weeks postinoculation), revealing nitrogen's potent regulatory effect on nitrogen fixation dynamics in nodules and leaves for both host plant and rhizobial symbiont. Younger nodules exhibited heightened nitrogen sensitivity, impacting nitrogenase activity and gene expression dynamics including plant leghemoglobin and rhizobial nifH levels. Tissue-specific regulatory mechanisms involving NIN-Like Proteins (NLPs) and non-symbiotic hemoglobins (Hb1 and Hb2) further delineate nitrogen metabolism and nodule function. Key genes and small RNAs were identified in the Autoregulation of odulation (AON) pathway, such as Nodule Autoregulation Receptor Kinase (NARK) and microRNA miR2111 , modulate nodule formation in response to nitrogen availability. Moreover, Bradyrhizobium adaptations to high nitrogen stress, evidenced by changes in genes like nirK and recQ helicase, underscore bacterial responses within the symbiotic relationship. These insights provide potential biomarkers and regulatory elements crucial for optimizing biological nitrogen fixation in soybean, thereby enhancing nitrogen-use efficiency and supporting sustainable agricultural practices. By reducing reliance on synthetic fertilizers while maintaining crop productivity, this findings contribute to sustainable food production strategies, emphasizing the balance between agricultural productivity and environmental stewardship.INTRODUCTION

[0390] Nitrogen is a vital nutrient for plant growth and development, essential for the synthesis of amino acids, proteins, and nucleic acids. Despite its abundance in the atmosphere, nitrogen is often a limiting factor in agricultural systems because plants cannot directly utilize atmospheric nitrogen (N2). This has led to the widespread use of synthetic nitrogen fertilizers, which, while effective, responsible for feeding over one billion people, pose significant environmental challenges such as soil degradation and waterway eutrophication (Jwaideh et al. 2022; Rosa and Gabrielli 2022). Thus, understanding the natural mechanisms of nitrogen acquisition and regulation in crops like soybean is crucial for developing more sustainable agricultural practices.

[0391] Soybean (Glycine max) has evolved a sophisticated symbiotic relationship with nitrogenfixing bacteria, primarily from the genus Bradyrhizobium. This symbiosis results in thePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web formation of root nodules, specialized structures where atmospheric nitrogen (N2) is converted into ammonia (NH3), a form that plants can readily assimilate, in a process known as symbiotic nitrogen fixation. The establishment and functioning of these nodules involve a complex interplay of plant and bacterial genes and molecular signals, tightly regulated, mainly by the host, at the transcriptional level (Ferguson et al. 2019; Zhang et al. 2021 ). Rhizobial signals, such as tRNA-derived fragments (tRFs), have also been implicated in nodule initiation and establishment (Ren et al. 2019).

[0392] Despite the natural mechanism of obtaining bioavailable nitrogen through symbiosis, modern high-yielding soybeans, which produce more than 60 bushels per acre (one bushel of soybean is 60 lbs), often receive nitrogen-rich fertilizer applications to maximize yields. This practice, while effective at increasing yields, can inhibit symbiotic nitrogen fixation activity and is therefore not efficient (Streeter 1985; Du et al. 2020). However, applying low levels of nitrogen can improve nodulation and nitrogen fixation, likely because early nitrogen application promotes root growth, thereby providing a greater area for nodulation and a larger source of photosynthetic-derived carbon from leaves to support rhizobia during symbiosis and nitrogen fixation (Mahon and Child 1979).

[0393] Moreover, Streeter et al. hypothesized a “nitrogen-threshold”, the point where maximal symbiotic nitrogen fixation activity is achieved with the highest amount of applied nitrogen (Streeter and Wong 1988). This implies that at some level of applied nitrogen, the host plant balances both nitrogen uptake and symbiosis. Beyond this nitrogenthreshold, the plant favor nitrogen uptake over symbiosis, leading to diminished benefits from additional fertilizer. At this point, the profits obtained from higher yield gains are minimized by the high costs associated with nitrogen fertilizer.

[0394] Understanding the plant and microbial regulatory mechanisms, involved in the nitrogen regulation of nodulation and nitrogen fixation will help optimize nitrogen fixation and improve nitrogen management practices for soybean growers. By gaining insights into these mechanisms, it may be possible to reduce reliance on synthetic fertilizers while maintaining maximum crop yields in an economically and environmentally sustainable manner.

[0395] Advances in transcriptom ic analysis have provided powerful tools to comprehensively examine the expression profiles of plant host and rhizobial genes involved inPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web the nitrogen regulation of nodulation and nitrogen fixation. By comparing transcriptomes of soybeans and rhizobia under high nitrogen conditions, researchers can identify key genes and regulatory networks that govern these processes. Such studies have revealed that nitrogen availability influences nodulation and nitrogen fixation through both local responses in the root environment, and systemic signaling pathways that integrate the plant’s overall nitrogen status with nodule formation and activity (Carter and Tegeder 2016; Ferguson et al. 2019; Li et al. 2022b; Lyu et al. 2022; Luo et al. 2023; Yao et al. 2023; Fu et al. 2024).

[0396] A critical aspect of nitrogen regulation in soybeans is the balance between systemic and local control of gene expression. Local regulation involves direct responses to nitrogen levels in the root environment, affecting nodule development and activity. Conversely, systemic regulation integrates signals from the entire plant, ensuring that nodulation and nitrogen fixation are aligned with the plant's overall growth and nutritional needs. The autoregulation of nodulation (AON) pathway provides systemic regulation of nodule formation in response to existing nodules. However, evidence supports that the nitrogen regulation of nodulation and nitrogen fixation pathways utilize different mechanisms than AON to exert local and systemic regulatory responses (Ferguson et al. 2019). Additionally, focus has been given to identifying components of the nitrogen regulation of nodulation pathway, but less attention has been given to identifying components of the nitrogen regulation of nitrogen fixation pathway. This may be due to the difficulty associated with distinguishing between the two pathways. Understanding the interplay between these regulatory mechanisms is crucial for enhancing nitrogen fixation efficiency and improving soybean productivity in sustainable agricultural systems.

[0397] In this study, a comprehensive transcriptom ic analysis was performed to investigate the effects of nitrogen regulation on nodulation and nitrogen fixation in soybean. By examining gene and small RNA (sRNA) expression profiles of both plant and bacterial genomes under high nitrogen conditions in nodules and leaves, the group aimed to elucidate the regulatory networks and key transcription factors involved in the soybean-Bradyhizobium symbiosis. The focus was specifically on the nitrogen response and regulation of both nodulation and nitrogen fixation. Eight symbiotic-related genes and three small RNAPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web biogenesis genes were identified differentially expressed in both nodules and leaves under high nitrogen conditions.

[0398] Additionally, genes involved in the AON pathway were identified that may play roles in both nitrogen regulation pathways. Notably, decreased expression of the shootderived gene was observed, Nodule Autoregulation Receptor Kinase (NARK), in leaves following high nitrogen treatments. NARK in shoots is known to respond to rhizobia-induced CLE (RICs) peptide signals from existing rhizobial populations and govern the expression of microRNA (miRNA) miR2111 (Lim et al. 2011 ; Zhang et al. 2021 ). This mobile miRNA targets the TOO MUCH LOVE (TML) gene in roots, inhibiting excessive nodulation by preventing the overproduction of nodules based on host’s nitrogen requirements.

[0399] The current understanding of the nitrogen regulation of nodulation involves the production of nitrogen-induced CLE (NICs) peptides, which are activated by NIN (Nodule inception)-like proteins (NLPs). These peptides target root-derived NARK receptors, triggering a local inhibition of nodulation (Fu et al. 2024). The involvement of shootderived NARK in the nitrogen response indicates a systemic regulatory component is involved in the nitrogen regulation of nodulation.

[0400] Notably, isoflavones (Lyu et al. 2022) and Lysin-Motif receptor-like kinase (LysM- RLK) proteins (Yao et al. 2023), known for recognizing rhizobial signals and initiating symbiotic interactions, have recently been identified in soybean roots as responsive to nitrogen treatments. These molecules have been suggested to be involved in the systemic regulation pathways governing nitrogen fixation. However, the specific mechanisms and signaling molecules governing the systemic nitrogen regulation of nitrogen fixation remain unclear.

[0401] These findings provide new insights into the molecular mechanisms underlying nitrogen regulation in soybeans. Potential biomarkers for nitrogen fixation and regulatory elements integral to the nitrogen regulation pathways were discovered. These discoveries significantly enhance understanding of the mechanisms involved. Further research and functional analysis could lead to the development of strategies for improving sustainable agricultural practices by enhancing symbiotic nitrogen fixation and increasing nitrogen-use efficiency in soybean and other nitrogen-fixing legumes. By optimizing these naturalPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web processes, it may be possible to reduce the reliance on synthetic fertilizers while maintaining or even increasing crop yields in an economically and environmentally sustainable manner.RESULTSHigh nitrogen treatments severely impair nitrogenase activity in soybean nodules

[0402] To observe the effect of high nitrogen on soybean nodule development, specifically on nitrogen fixation, the nitrogenase activity of soybean plants treated with high levels of nitrogen were compared (50 mM ammonium nitrate, NH4NO3) to that of soybeans receiving low levels of nitrogen (0.5 mM potassium nitrate, KNO3). The aim was to determine if the effect varied at different stages of nodule development, particularly during the period surrounding peak nitrogen fixation, from 4 weeks post inoculation (wpi) to 6 wpi.

[0403] Soybeans were treated with high nitrogen at either 4 wpi, 5 wpi, or 6 wpi and again two days after the first treatment (dpt). Samples were measured at 0 dpt (negative control), 2 dpt, or 4 dpt. Additional untreated (negative control) samples were included one week prior to treatments at 3 wpi and one week following treatments at 7 wpi. The group employed the acetylene reduction assay (ARA) to measure nitrogenase activity of whole soybean root systems treated with low or high levels of nitrogen (Figure 27).

[0404] In this study, peak nitrogen fixation activity was observed at 4 wpi. From 3 wpi to 4 wpi, activity increased by 17%, from 4 wpi to 5 wpi, activity declined slightly by 5%, from 5 wpi to 6 wpi it declined by 27%, and another 12% from 6 wpi to 7 wpi. From 4 to 7 wpi, activity declined by 39%, indicating that the pattern of nitrogen fixation activity was in decline from 5 wpi to 7 wpi (Figure 27A).

[0405] nitrogenase activity was observed to significantly declined in response to high nitrogen treatments at all stages measured compared to root systems that received low nitrogen treatments. The initial 2-day response to treatments at 4 wpi and 5 wpi was rapid and similar, whereas the response at 6 wpi was more gradual. The decline in activity from 0 dpt to 2 dpt in soybeans treated at 4 wpi and 5 wpi was 76% and 75%, respectively, whereas activity declined only 48% in soybeans at 6 wpi and 2 dpt. This indicates that younger nodules (4 wpi and 5 wpi) are more sensitive to high levels of nitrogen than older nodules (6 wpi). This could be a result of a more established symbiosis or attributed to rhizobial survival mechanisms.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0406] Following a second nitrogen treatment, a further 40% and 43% reduction in activity in treated soybeans at 4 wpi and 4 dpt, and 5 wpi and 4 dpt, respectively were observed. However, in 6 wpi and 4 dpt samples, a greater decline in activity of 61 % was observed, compared to the activity measured at 6 wpi and 2 dpt.

[0407] Similar results were observed in all samples that received two applications of high nitrogen, showing a comparable percentage decrease when compared to untreated samples at 0 dpt. Activity decreased by 86%, 86%, and 80%, from 4 wpi to 4 wpi and 4 dpt, 5 wpi to 5 wpi and 4 dpt, and 6 wpi to 6 wpi and 4 dpt, respectively. Of note, the nitrogenase activity values measured in all 4 dpt samples was similar: 2543 nmols mg-1 hr-1 at 4 wpi and 4 dpt, 2326 nmols mg-1 hr-1 at 5 wpi and 4 dpt, and 2472 nmols mg-1 hr-1 at 6 wpi and 4 dpt.

[0408] The results suggest that excessive nitrogen disrupts the nitrogen fixation process across all stages of nodule development from 4 wpi to 6 wpi. This disruption underscores the sensitivity of soybean nodules to elevated nitrogen levels during critical developmental periods. The consistent decline in nitrogenase activity across different developmental stages indicates that high nitrogen concentrations can universally impair the symbiotic efficiency of soybean nodules, leading to reduced nitrogen fixation. This highlights the importance of carefully managing nitrogen levels to ensure optimal nodule function and nitrogen fixation in soybeans.Shoots and roots respond differently to high nitrogen treatment

[0409] Prior to the ARA, roots were separated from shoots, measured root and shoot mass (Figure 28) and collected a small sample of 12 nodules from each biological replicate, split evenly into four tubes (3 nodules per tube) for downstream RNA and protein applications.

[0410] A response to high nitrogen treatments in shoot mass was not observed (Figure 28A), but did detect a slight inhibition of root growth (Figure 28B). This indicates that the presence of excess nitrogen in the soil stunts root growth while having no early effect on shoot growth at 4 dpt. The lack of response in shoot mass suggests that the shoots are not immediately affected by high nitrogen levels, possibly due to their ability to regulate nutrient uptake and distribution more effectively than roots. It is also possible that the roots have a delayed response past 4 dpt. On the other hand, the inhibition of root growth could bePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web attributed to the sensitivity of root systems to changes in soil nitrogen levels, which may disrupt root architecture and function. This differential response highlights the importance of understanding the distinct regulatory mechanisms governing root and shoot development in response to nutrient availability.Age-dependent regulation of soybean Lb1 transcripts shows immediate decline in older nodules and delayed decline in younger nodules following repeated high nitrogen treatment

[0411] In nodules, the rhizobial nitrogenase enzyme “fixes” atmospheric nitrogen (N2) by reducing it with hydrogen (H) to form ammonia (NH3), a bioavailable source of nitrogen for plants. This ammonia is then remobilized and provided to the host plant in exchange for host- derived sugars. The complex process of symbiotic nitrogen fixation relies on the host plant maintaining a low-oxygen environment within nodules, which is essential for both rhizobial growth and nitrogenase activity.

[0412] Oxygen (02) acts as a double-edged sword in nodules: excessive oxygen inhibits the oxygen-sensitive nitrogenase enzyme, while insufficient oxygen stunts the growth of rhizobial bacteroids. Legume leghemoglobin pigments play a crucial role in maintaining this low-oxygen environment by effectively buffering oxygen levels to ensure an optimal balance. Thus, the fine-tuning of oxygen levels within nodules by leghemoglobin is vital for effective nitrogen fixation.

[0413] In this study, the impact of high nitrogen levels on soybean nodule leghemoglobin (Lb) and rhizobial nitrogenase (nif) expression were investigated, specifically focusing on LEGHEMOGLOBIN 1 (Lb1 ) and NITROGENASE FE-COMPONENT (nifH). Additionally, the corresponding protein of nifH, NifH was examined. Previously, Lb1 was identified as a potential biomarker for symbiotic nitrogen fixation. Alternatively, nifH expression, including its protein NifH, displayed a gradual increase throughout nodule development, spanning 2 wpi to 10 wpi. It’s worth noting that at the time of this study, an antibody for LBC3 (the protein corresponding to Lb1 ) was not available on the market. This limitation underscores the current challenges in studying soybean specific proteins.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web

[0414] Using RT-qPCR, Gm.Lbl expression in nodules harvested from plants used in the ARAs were measured, spanning 3 to 7 wpi, and subjected to high nitrogen treatments at 4 wpi, 5 wpi and 6 wpi and again two days later at 2 dpt (Figure 27B). In untreated nodules collected from plants grown in low nitrogen, peak Lb1 expression at 6 wpi was observed. The overall response of Lb1 to high nitrogen was negative, showing a significant decline at 4 dpt following two treatments of high nitrogen across all time points: 4 wpi, 5 wpi, and 6 wpi. Specifically, Lb1 transcript levels decreased by 89% from 4 wpi to 4 wpi and 4 dpt, by 68% from 5 wpi to 5 wpi and 4 dpt, and by 74% from 6 wpi to 6 wpi and 4 dpt.

[0415] Conversely, the early response to high nitrogen by Lb1 at 2 dpt varied across weeks. Lb1 transcript levels increased by 1 .22-fold (22%) from 4 wpi to 4 wpi and 2 dpt, remained relatively unchanged with a 1 .04-fold (4%) increase from 5 wpi to 5 wpi and 2 dpt, and decreased by 0.82-fold (18%) from 6 wpi to 6 wpi and 2 dpt. This indicates that Lb1 transcription is not a good early indicator for inhibition of nitrogen fixation by nitrogen.

[0416] From 2 dpt to 4 dpt, a consistent and substantial decline in Lb1 transcript levels: a 0.17-fold reduction at 4 wpi and 4 dpt were observed, a 0.31 -fold reduction at 5 wpi and 4 dpt, and a 0.32-fold reduction at 6 wpi and 4 dpt. Notably, older nodules treated with high nitrogen showed a less pronounced decline in Lb1 transcripts. Specifically, Lb1 transcript levels increased from 13 at 4 wpi and 4 dpt to 19.8 at 5 wpi and 4 dpt, and to 22.7 at 6 wpi and 6 dpt, when relative expression values were averaged across 5 biological replicates (BR).

[0417] These findings suggest that the transcriptional regulation of Lb1 in response to high nitrogen is complex and varies with nodule age. Older nodules (6 wpi) showed an immediate decline in Lb1 transcripts, while younger nodules (4 wpi and 5 wpi) exhibited a delayed but increased response over time, following a repeated high nitrogen treatment. This differential regulation may be critical for understanding the adaptation of soybean nodules to high nitrogen environments and their overall nitrogen fixation capacity.Younger nodules exhibit immediate sensitivity to nitrogen demonstrated by early declines in nifH levels

[0418] Bradyrhizobium USDA110 nifH transcript levels using RT-qPCR (Figure 27C) were also measured. Consistent with previous results, nifH transcripts increased graduallyPATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web from 3 wpi to 7 wpi under low nitrogen conditions. However, when exposed to excess nitrogen in the current study, n if H levels declined after 2 dpt.

[0419] Notably, the second nitrogen treatment at 2 dpt had no effect on nifH abundance in the 4 wpi and 5 wpi samples after 4 dpt, but induced a 37% decline in nifH levels in the 6 wpi samples after 4 dpt. The initial decline in nifH levels following the first nitrogen treatment was less dramatic in the 6 wpi samples, ...

Claims

PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-webCLAIMSWhat is claimed is:1 . A non-destructive method for assessing nitrogen fixation status in legume plants, the method comprising: a. calculating a gene expression ratio (GER) for at least one polynucleotide pair selected from the polynucleotide pairs identified in Table B, wherein the GER is a ratio of an expression level of a first polynucleotide of the pair to an expression level of a second polynucleotide of the pair, in a leaf tissue sample; and b. comparing the calculated GER for the polynucleotide pair to a corresponding maximum or minimum nitrogen fixation threshold GER (GERNFT) predetermined for said pair of polynucleotides, wherein i. a maximum GERNFT represents a maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal, wherein a calculated GER of a polynucleotide pair equal to or below the maximum GERNFT indicates suppressed nitrogen fixation; or ii. a minimum GERNFT represents a minimum GER value above which nitrogen fixation is optimal and below which nitrogen fixation is suppressed, wherein a calculated GER of a polynucleotide pair equal to or above the minimum GERNFT indicates optimal nitrogen fixation; wherein the maximum or minimum GERNFT of each polynucleotide pair correlates GER values with measured nitrogen fixation activity in plants and wherein the expression level is the expression level of the polynucleotide, the expression level of a protein encoded by the polynucleotide, the expression level of a reporter under the regulatory control of the polynucleotide, or any combination thereof.2 The method of claim 1 , wherein the calculated GER for the polynucleotide pair is compared to a corresponding maximum GERNFT, wherein a maximum GERNFT represents a maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web3. The method of claim 1 or claim 2, further comprising predetermining the maximum or minimum GERNFT of a polynucleotide pair by: a. growing legume plants under low external nitrogen conditions that support optimal nitrogen fixation, and under external nitrogen conditions that suppress nitrogen fixation; b. determining expression levels of each polynucleotide of a polynucleotide pair in leaf samples obtained from the plants after nitrogen fertilizer treatment; c. measuring nitrogen fixation activity in root samples of the plants; d. calculating a GER in the leaf tissue samples from plants grown under each growth condition; and e. identifying the maximum GERNFT for the polynucleotide pair as the maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal; or identifying the minimum GERNFT for the polynucleotide pair as the minimum GER value above which nitrogen fixation is optimal and below which nitrogen fixation is suppressed.4 The method of claim 3, wherein the plants are grown under a range of external nitrogen concentrations ranging from external nitrogen concentrations that suppress nitrogen fixation to nitrogen concentrations that allow optimal nitrogen fixation, and identifying the maximum GERNFT for the polynucleotide pair as the maximum GER value below which nitrogen fixation is suppressed and above which nitrogen fixation is optimal, or identifying the minimum GERNFT for the polynucleotide pair as the minimum GER value above which nitrogen fixation is optimal and below which nitrogen fixation is suppressed, wherein the maximum or minimum GERNFT is determined from the range of GERs corresponding to the transition between suppressed and optimal nitrogen fixation.5 The method of claim 3 or claim 4, wherein the external nitrogen conditions comprise the application of nitrogen fertilizer.6 The method of any one of claims 3-5, wherein the low external nitrogen conditions that support optimal nitrogen fixation comprise about 0.5 mM available nitrogen.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web7. The method of any one of claims 3-6, wherein the external nitrogen conditions that suppress nitrogen fixation comprise about 100 mM available nitrogen.

8. The method of any one of the preceding claims, wherein nitrogen fixation is assessed at the stage of nodule development when nodules are fully formed and actively fixing nitrogen.9 The method of any one of the preceding claims, wherein the legume plant comprises indeterminate nodules.10 The method of any one of the preceding claims, wherein the legume plant comprises determinate nodules.11 The method of claim 10, wherein the nitrogen fixation status is assessed at the stage of determinate nodule development when nodules are fully formed and actively fixing nitrogen.12 The method of claim 10 or claim 11 , wherein the GERs are calculated at 4-6 weeks post inoculation (wpi) at 0 days post treatment (dpt) with nitrogen fertilizer, 2 dpt, and 4 dpt.13 The method of any one of the preceding claims, the method comprises comparing the calculated GER for the polynucleotide pair to a corresponding maximum nitrogen fixation threshold GER (GERNFT), wherein a calculated GER of a polynucleotide pair equal to or below the maximum GERNFT indicates suppressed nitrogen fixation.14 The method of any one of the preceding claims, wherein the maximum and minimum GERNFT for the pairs of polynucleotides is as shown in Table B.15 The method of any one of the preceding claims, wherein suppressed nitrogen fixation levels are due to stress conditions selected from high levels of nitrogen conditions, drought, salinity, heat, cold, pathogen infection, or nutrient deficiency.16 The method of any one of the preceding claims, wherein the tissue sample is a punch biopsy, excised leaflet, or sap extract.17 The method of any one of the preceding claims, wherein the GER is calculated using expression levels measured by protein abundance, mRNA transcript abundance, a reporter gene product.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web18. The method of any one of the preceding claims, wherein the expression level is determined by quantitative PCR (qPCR), digital PCR, microarray, RNA sequencing, or ELISA, a colorimetric, fluorometric, or chemiluminescent assay, a reporter gene assay.

19. The method of any one of the preceding claims, wherein an expression level is an RNAseq- derived metric.

20. The method of any one of the preceding claims, wherein an expression level is an RNAseq- derived average Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values.

21. The method of any one of the preceding claims, wherein the legume plant is soybean, alfalfa, clover, lentil, pea, or vetch.

22. The method of any one of the preceding claims, wherein the legume plant is soybean.

23. The method of claim 22, wherein the nitrogen fixation status is assessed during the vegetative growth stage of the soybean plant, coinciding with peak nodule activity and optimal nitrogen fixation efficiency.

24. The method of claim 22 or claim 23, wherein the nitrogen fixation status is assessed at the stage of determinate nodule development when nodules are fully formed and actively fixing nitrogen.

25. The method any one of claims 22-24, wherein the nitrogen fixation status is assessed at around 5 to 6 weeks post-inoculation.

26. The method of any one of claims 22-25, wherein each polynucleotide of the polynucleotide pairs comprises a soybean gene identified in Table B, or a variant, allele, fragment, or synthetic form thereof.

27. The method of any one of claims 22-26, wherein the GERNFT for the pairs of polynucleotides is as shown in Table B.

28. The method of any one of the preceding claims, wherein one or more of the polynucleotides comprise an endogenous gene, an exogenous gene, or any combination thereof.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web29. A non-destructive method for assessing nitrogen fixation status in legume plants, the method comprising: a. measuring the expression level in a leaf tissue sample of any combination of one or more polynucleotides identified in Table A, wherein the GR3.4, the bHLH13, the a / b hydrolase, and the SOS3-4 polynucleotides are predetermined to be downregulated and the GdAS1 -1 , the GdAS1 -2, the MtN21 , the cP450, and the HIRD11 -like polynucleotides are predetermined to be upregulated in plants grown under conditions that suppress nitrogen fixation; and b. determining that the plant has suppressed nitrogen fixation when the expression level of any one or more of the downregulated polynucleotides is equal to or below a predetermined untreated threshold expression level for the respective polynucleotide, the expression level of any one or more of the upregulated polynucleotides is equal to or above a predetermined untreated threshold expression level for the respective polynucleotide, or any combination of one or more downregulated or upregulated polynucleotide; or c. determining that the plant has optimal nitrogen fixation when the expression level of any one or more of the downregulated polynucleotides is equal to or above a predetermined treated threshold expression level for the respective polynucleotide, or the expression level of any one or more of the upregulated polynucleotides is equal to or below a predetermined treated threshold expression level for the respective polynucleotide, or any combination of one or more downregulated or upregulated polynucleotide; wherein the untreated threshold expression level is determined based on expression of the polynucleotide in plants grown under conditions supporting optimal nitrogen fixation, wherein the treated threshold expression level is determined based on expression of the polynucleotide in plants grown under conditions that suppress nitrogen fixation, wherein the expression level is the expression level of the polynucleotide, the expression level of a protein encoded by the polynucleotide, the expression level of a reporter under the regulatory control of the polynucleotide, or any combination thereof.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web30. The method of claim 29, further comprising predetermining the threshold expression levels of a polynucleotide by: a. growing legume plants under conditions supporting optimal nitrogen fixation to determine an untreated threshold expression level of a polynucleotide, growing legume plants under conditions that suppress nitrogen fixation to determine a treated threshold expression level of a polynucleotide, or both; b. determining expression levels of the polynucleotide in leaf samples of the plants; c. measuring nitrogen fixation activity in root samples of the plants; and d. setting the untreated threshold expression level for a downregulated polynucleotide as the expression level of the polynucleotide in a plant grown under conditions supporting optimal nitrogen fixation below which nitrogen fixation is suppressed, and for an upregulated polynucleotide as the expression level of the polynucleotide in a plant grown under conditions supporting optimal nitrogen fixation above which nitrogen fixation is suppressed, based on comparison to nitrogen fixation activity in the plants; setting the treated threshold expression level for a downregulated polynucleotide as the expression level measured under conditions that suppress nitrogen fixation above which nitrogen fixation is suppressed, and for an upregulated polynucleotide as the expression level measured under conditions that suppress nitrogen fixation below which nitrogen fixation is suppressed, based on comparison to nitrogen fixation activity in the plants; or both. The method of claim 30 or claim 31 , wherein the method comprises: a. measuring the expression level in a leaf tissue sample of any combination of one or more polynucleotides identified in Table A, wherein the GR3.4, the bHLH13, the a / b hydrolase, and the SOS3-4 polynucleotides are predetermined to be downregulated and the GdAS1 -1 , the GdAS1 -2, the MtN21 , the cP450, and the HIRD11 -like polynucleotides are predetermined to be upregulated in plants grown under conditions that suppress nitrogen fixation; and b. determining that the plant has suppressed nitrogen fixation when the expression level of any one or more of the downregulated polynucleotides is equal to or below a predetermined untreated threshold expression level for the respectivePATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web polynucleotide, the expression level of any one or more of the upregulated polynucleotides is equal to or above a predetermined untreated threshold expression level for the respective polynucleotide, or any combination of one or more downregulated or upregulated polynucleotide.

32. The method of any one of claims 29-31 , wherein the untreated and treated threshold expression level for each polynucleotide is as shown in Table A.

33. The method of any one of claims 29-32, wherein the legume plant is soybean.

34. The method of claim 33, wherein each polynucleotide comprises a soybean gene identified in Table A, or a variant, allele, fragment, or synthetic form thereof.

35. The method of claim 33 or claim 34, wherein the untreated and treated threshold expression levels for each polynucleotide is as shown in Table A.

36. A genetically modified reporter plant or a part, plant cell, or seed thereof for reporting nitrogen fixation status in a legume plant, the genetically modified plant comprising: a. a reporter construct comprising a reporter under the regulatory control of a polynucleotide listed in Table A; b. a pair of reporter constructs comprising a first reporter construct comprising a first reporter under the regulatory control of a first polynucleotide and a second reporter construct comprising a second reporter under the regulatory control of a second polynucleotide, wherein the first and second polynucleotides are selected from the polynucleotide pairs identified in Table B; or c. any combination of the expression constructs of (a) the pair of expression constructs of (b), or both, herein differential expression of the reporter construct, the pair of reporter constructs, or a GER calculated from expression levels of the pair of reporter constructs indicates the nitrogen ixation status of the plant.

37. The genetically modified reporter plant or a part, plant cell, or seed thereof of claim 36, wherein the reporter under the regulatory control of a polynucleotide is:PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web a. the polynucleotide itself, such that the endogenous gene functions as the reporter when introduced into a different organism; or b. a detectable reporter operably linked to one or more regulatory elements of the polynucleotide, including a promoter, enhancer, 5' or 3' untranslated region, or other cis-regulatory sequence, such that reporter expression reflects the regulatory activity of the polynucleotide.

38. The genetically modified reporter plant, plant cell, or seed of claim 36 or claim 37, wherein the reporter is selected from the group consisting of -glucuronidase (GUS), green fluorescent protein (GFP), yellow fluorescent protein (YFP), red fluorescent protein (RFP), luciferase (LUC), alkaline phosphatase, and chloramphenicol acetyltransferase (CAT).

39. The genetically modified reporter plant, plant cell, or seed of any one of claims 36-38, wherein the reporter gene expression is detectable by fluorescence microscopy, luminescence imaging, or colorimetric assay.

40. The genetically modified reporter plant, plant cell, or seed of any one of claims 36-39, wherein the reporter gene expression is quantifiable in a non-destructive assay.

41. A method of determining a nitrogen threshold for a legume plant, the method comprising: a. growing legume plants under untreated conditions and under a range of increasing nitrogen fertilizer concentrations; b. determining expression levels of polynucleotides of Table A or any combination thereof; c. calculating a GER using expression levels of pairs of polynucleotides of Table B in plants grown under each growth condition; and d. identifying the nitrogen threshold as the lowest nitrogen fertilizer concentration at which the GER indicates a significant reduction in nitrogen fixation status compared to untreated controls.PATENTDanforth Docket No.: DDPSC0172-401 -PCTVia EFS-web42. A method for selecting legume plants for breeding, guiding nitrogen fertilizer application, or monitoring field-level nitrogen fixation status, the method comprising a. determining a nitrogen threshold for a legume plant according to the method of claim 41 ; and b. selecting plants for breeding that maintain optimal nitrogen fixation status at higher external nitrogen concentrations relative to other plants in the population, as determined by the nitrogen threshold.

43. A kit for assessing nitrogen fixation status in a legume plant, the kit comprising: a. one or more reagents for detecting the expression level of a polynucleotide of Table A or a pair of nucleotides of Table B; b. one or more genetically modified reporter plant or a part, plant cell, or seed thereof for reporting nitrogen fixation status in a legume plant of claim 36; c. instructions for calculating a gene expression ratio (GER) and comparing the GER to a predetermined minimum or maximum GERNFT; or d. any combination of (a) to (c).

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