Method for identifying plant saline-alkali tolerant germplasm resources by multi-tissue transcriptome sequencing

Abstract

The present application relates to the field of transcriptomics, and specifically discloses a method for identifying plant salt-tolerant germplasm resources by using multi-tissue transcriptome sequencing, comprising the following steps: S1, salt-tolerance evaluation and grade division: placing the plant germplasm to be tested under a suitable concentration of salt stress conditions for seedling culture, measuring its morphological indicators and physiological and biochemical indicators, calculating the salt-tolerance coefficients of each indicator, and using multivariate statistical analysis methods to comprehensively evaluate and grade the salt-tolerance of the germplasm; the present application first constructs a standardized salt-tolerance identification process from the laboratory to field application, uses gradient salt solution to simulate the natural stress environment, measures multi-dimensional indicators such as growth morphology, photosynthetic physiology and antioxidant system at the key growth stages, and uses statistical methods such as salt-tolerance coefficient, membership function and principal component analysis for comprehensive evaluation and grade division, thereby realizing systematic, rapid and accurate identification of the salt-tolerance of a large number of corn inbred lines.

Description

Technical Field

[0001] This invention belongs to the field of transcriptomics technology, specifically relating to a method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing. Background Technology

[0002] In recent years, facing the serious threat to agricultural production posed by the increasing global soil salinization, research on plant salt tolerance has become one of the core issues in the field of agricultural biotechnology. Traditionally, the evaluation of plant salt tolerance mainly relied on field trials and the measurement of single physiological indicators, such as observing the growth status, survival rate, and yield of plants in saline-alkali soils. However, with the leaps in molecular biology and genomics technologies, transcriptome sequencing technology, due to its ability to comprehensively analyze gene expression changes, has gradually become an important tool for studying the mechanisms of plant stress responses. In particular, multi-tissue transcriptome sequencing technology, by simultaneously analyzing the gene expression profiles of different plant tissues under stress conditions, provides a new approach to revealing the complex molecular mechanisms of plant salt tolerance.

[0003] Nevertheless, current technologies for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing face the challenge of efficiently and accurately extracting key genes and regulatory networks directly related to plant salt tolerance from multi-tissue sequencing data. Existing methods often focus on the analysis of single tissues or a few genes, neglecting the specific and synergistic response mechanisms of different plant tissues under salt-alkali stress, resulting in an incomplete and in-depth understanding of overall plant salt tolerance. This limitation not only delays the precise discovery of salt-tolerant genes but also restricts the efficient identification and utilization of salt-tolerant plant germplasm resources, thus requiring improvement. Summary of the Invention

[0004] The purpose of this invention is to provide a method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing includes the following steps:

[0007] S1. Salt and alkali tolerance evaluation and grading: The plant germplasm to be tested was placed under suitable salt and alkali stress conditions for seedling culture, and its morphological and physiological and biochemical indicators were measured. The salt and alkali tolerance coefficients of each indicator were calculated, and the salt and alkali tolerance of the germplasm was comprehensively evaluated and graded using multivariate statistical analysis.

[0008] S2. Collection of multiple tissue samples: From the germplasms classified into different levels of salt and alkali tolerance in step S1, select representative germplasms of salt-tolerant and salt-sensitive types respectively, collect fresh samples of their specific tissues, and quickly freeze them at low temperature.

[0009] S3. Multi-tissue transcriptome sequencing: Total RNA was extracted from different tissue samples collected in step S2, sequencing libraries were constructed, and high-throughput transcriptome sequencing was performed to obtain clean read sequence data of each tissue sample.

[0010] S4. Transcriptome data analysis: The obtained clean reads are compared and annotated with reference genomes or public non-redundant protein sequence databases to obtain gene annotation information; differentially expressed genes are identified based on gene expression data among different salt-tolerant germplasms and different tissues.

[0011] S5. Mining of salt-alkali tolerance-related genes: Functional enrichment analysis and pathway analysis were performed on the differentially expressed genes identified in step S4 to screen candidate genes related to salt-alkali stress response and tolerance, which can be used as molecular markers for identifying and creating salt-alkali tolerant germplasm resources.

[0012] Preferably, in step S1, the appropriate concentration of salt-alkali stress conditions is determined through a preliminary experiment. The preliminary experiment uses a mixed salt-alkali solution prepared by NaCl, Na2SO4 and NaHCO3 in a molar ratio of 1:1:1, and sets at least two concentration gradients to stress the test germplasm.

[0013] Preferably, in step S1, the morphological indicators include at least one of plant height, root length, root-to-shoot ratio, and total root surface area; the physiological and biochemical indicators include at least one of chlorophyll content, photosynthetic rate, superoxide dismutase activity, peroxidase activity, malondialdehyde content, and proline content.

[0014] Preferably, in step S1, the multivariate statistical analysis method includes at least one of membership function analysis, principal component analysis, and cluster analysis.

[0015] Preferably, in step S2, the specific tissue includes at least one of root tissue and leaf tissue or stem-leaf tissue.

[0016] Preferably, in step S4, the public non-redundant protein sequence database includes NR, KEGG, and GO databases.

[0017] Preferably, the plant is maize, and the germplasm of the plant to be tested is a maize inbred line.

[0018] Compared with the prior art, the beneficial effects of the present invention are:

[0019] By establishing a comprehensive evaluation method that includes pre-experiment screening, multi-indicator stress identification at the seedling stage, and multivariate statistical analysis, this invention first constructs a standardized salt-alkali tolerance identification process from laboratory to field application. This process uses gradient salt-alkali solutions to simulate natural stress environments. It measures multi-dimensional indicators such as growth morphology, photosynthetic physiology, and antioxidant systems during key growth stages, and uses statistical methods such as salt-alkali tolerance coefficients, membership functions, and principal component analysis for comprehensive evaluation and grading. This enables a systematic, rapid, and accurate identification of salt-alkali tolerance in a large number of maize inbred lines, overcoming the limitations of single-indicator evaluation and the problems of long evaluation cycles and significant environmental interference in traditional field identification methods.

[0020] By employing a setup that simultaneously samples multiple tissues (roots and leaves) and performs high-throughput transcriptome sequencing, this invention, based on precise phenotypic identification, further elucidates the molecular mechanisms of maize's response to salt-alkali stress at the organ level. This design can simultaneously acquire gene expression profiles from roots (ion balance, signal transduction) and leaves (photosynthesis, redox balance). Through bioinformatics analysis, differentially expressed genes and metabolic pathways with tissue-specific and common responses are identified, thereby deeply exploring key genes and regulatory networks related to salt-alkali tolerance traits. This provides multi-dimensional molecular evidence for understanding the complex physiological mechanisms of maize's salt-alkali tolerance, overcoming the limitations of previous studies focusing on single tissues or a few genes.

[0021] By integrating phenotypic identification, gene mining, and marker-assisted breeding, this invention achieves a closed loop from gene discovery to breeding application. This strategy screens candidate genes based on transcriptome data, develops closely linked KASP molecular markers, and simultaneously uses seedling phenotypic screening and marker-assisted selection during backcross breeding, thereby significantly improving the efficiency and accuracy of salt-tolerant gene aggregation and germplasm creation. This method not only verifies the function of candidate genes but also directly transforms research results into usable breeding tools, accelerating the selection process for superior salt-tolerant germplasm.

[0022] By establishing a collaborative identification system of "laboratory seedling screening – multi-site field verification," this invention ensures the reliability and practicality of salt-alkali tolerance evaluation. After completing preliminary screening and grading of materials on a large scale under controlled conditions, the system further conducts field trials in representative saline-alkali areas to verify the consistency between laboratory identification results and actual production performance. This ensures that the selected breeding materials possess both stable salt-alkali tolerance and good agronomic adaptability, effectively reducing breeding risks and increasing the success rate of technology transfer to production.

[0023] By developing a simplified evaluation formula based on principal component analysis and setting functional markers based on key genes, this invention provides flexible tool selection for different application scenarios. The simplified evaluation formula only requires the measurement of eight core indicators to achieve rapid preliminary screening, making it suitable for large-scale germplasm resource surveys; while the KASP markers developed for key genes are suitable for high-precision assisted selection and gene aggregation, thus forming a technical toolkit that combines "rapid preliminary screening" and "precision breeding," meeting the needs of different stages and levels of precision in breeding practice, and improving the practicality and accessibility of the technology. Attached Figure Description

[0024] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Example 1:

[0027] Please see Figure 1 As shown, this study describes a method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing. The experimental materials consisted of 100 representative accessions selected from 1954 maize inbred lines preserved at the Maize Research Institute of the Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences. These materials represent diverse geographical origins and agronomic traits, exhibiting good diversity.

[0028] Determination of salt-alkali stress concentration: A preliminary experiment was conducted on 20 samples to determine the appropriate stress concentration. The specific steps are as follows:

[0029] Preparation of saline-alkali solutions: Prepare saline-alkali solutions with concentrations of 50, 100, 150, and 200 mmol / L by mixing NaCl, Na2SO4, and NaHCO3 in a molar ratio of 1:1:1, with distilled water as a control.

[0030] Germination test: Ten plump seeds were selected from each sample, sterilized with 1% sodium hypochlorite, and placed in a petri dish lined with double-layered filter paper. 10 mL of the corresponding concentration of saline-alkali solution was added to each dish, and the mixture was incubated at a constant temperature of 25℃.

[0031] Results Analysis: Germination potential on day 3 and germination rate on day 7 were measured. The results showed that at a concentration of 150 mmol / L, the difference in germination rate among different materials was most significant, with salt-tolerant materials having a germination rate >80% and sensitive materials <50%, and plant growth was not completely inhibited. Therefore, 150 mmol / L was selected as the concentration for subsequent experiments.

[0032] Treatment of salt and alkali stress during seedling stage:

[0033] Seedling raising: Prepare 300 culture boxes (10cm×12cm) and fill them with an equal amount of nutrient soil. Sow 10 sterilized seeds in each box and cultivate at a constant temperature of 28℃. After emergence, move them to an artificial climate chamber with the following conditions: day / night temperature 28℃ / 20℃, light intensity 12h / d, and light intensity 650μmol·m⁻². -2 ·s -1 Add 50mL of 0.5×MS nutrient solution to each pot after 7 days.

[0034] Stress treatment: When the seedlings have grown to two leaves and one bud, thin them out, keeping 5 healthy seedlings per box.

[0035] Control group: Irrigated with distilled water

[0036] Stress group: Irrigated with 150 mmol / L saline solution

[0037] Treat every 3 days for a total of 3 times, maintaining soil moisture at 60%-75%.

[0038] Indicator Measurement:

[0039] Measurement time:

[0040] After the final treatment, the seedlings were tested when they reached the three-leaf stage.

[0041] Technical indicators:

[0042] Plant height growth: Plant height was measured before treatment (two leaves and one bud) and after treatment (three leaves and one bud), and the difference was calculated.

[0043] Rhizome biomass: Separate the roots and aerial parts, and weigh them separately. After blanching at 105℃ for 30 min, dry at 80℃ to constant weight, weigh the dry weight, and calculate the root-to-shoot ratio.

[0044] Root morphology: The root system was scanned using a root scanner, and parameters such as total root length, root surface area, and root volume were analyzed using WinRHIZO software.

[0045] Physiological and biochemical indicators:

[0046] Photosynthetic parameters: Net photosynthetic rate (Pn), stomatal conductance (Gs), and intercellular CO2 concentration (Ci) were measured using a CIRAS-2F photosynthesis system.

[0047] Chlorophyll fluorescence: Fv / Fm was measured using PEAPocket after 20 min of dark adaptation.

[0048] Chlorophyll content: SPAD value was determined using SPAD-502.

[0049] Antioxidant enzyme activity: SOD activity was measured using the NBT method, and POD activity was measured using the guaiacol method.

[0050] Permeation substances: MDA content was determined by the thiobarbituric acid method, and proline content was determined by the sulfosalicylic acid method.

[0051] Abscisic acid (ABA): Measured using an ELISA kit.

[0052] Data processing and salt tolerance evaluation:

[0053] Calculation of salt and alkali tolerance coefficient:

[0054] For each indicator, calculate: Salt tolerance coefficient = (Average value of stress treatment / Average value of control treatment) × 100%

[0055] Membership function value calculation

[0056] Data is standardized using the membership function method:

[0057] Positive index (the higher the value, the greater the salt tolerance): U(X) = (XX) min ) / (X max -X min )

[0058] Negative index (the smaller the value, the more salt-tolerant): U(X) = 1 - (XX) min ) / (X max -X min )

[0059] Where X is the salt and alkali resistance coefficient of a certain material, X min and X max These are the minimum and maximum values ​​of this indicator for all materials.

[0060] Principal component analysis: Principal component analysis was performed on the membership function values ​​of the 15 indicators to extract principal components with eigenvalues ​​> 1. Four principal components were obtained, with a cumulative contribution rate of 86.42%. The comprehensive score D for each material was calculated.

[0061] Cluster analysis and hierarchical classification:

[0062] Based on the comprehensive score D, the 100 materials were divided into 3 classes using the systematic clustering method (Euclidean distance, class average method):

[0063] Salt and alkali resistant type (D>0.65): 32 parts of material;

[0064] Intermediate type (-0.35≤D≤0.65): 41 sets of materials;

[0065] Salt-alkali sensitive type (D<-0.35): 27 samples.

[0066] Evaluation system establishment: Based on the principal component analysis results, eight indicators with relatively high weights were selected to construct a simplified evaluation system: proline content, net photosynthetic rate, root-to-shoot ratio, SOD activity, root surface area, plant height growth, Fv / Fm, and total root length. A simplified evaluation formula D' was established, which was verified to be highly correlated with the complete evaluation results (r=0.943).

[0067] Technical effects: The method established in this embodiment can systematically evaluate the salt and alkali tolerance of maize inbred lines. The salt and alkali tolerant materials screened provide a foundation for subsequent molecular mechanism research and breeding utilization. The simplified evaluation formula established can be used for rapid screening of large-scale germplasm resources.

[0068] Example 2:

[0069] From the three levels defined in Example 1, the following are selected respectively:

[0070] Representative materials for salt and alkali resistant types: N-12, N-35, N-71;

[0071] Representative materials sensitive to salt and alkali: S-08, S-22, S-63;

[0072] Each group of materials was replicated three times biologically.

[0073] Sample collection:

[0074] Seedlings were subjected to salt-alkali stress treatment (150 mmol / L mixed salt-alkali solution) according to the method in Example 1. Samples were collected at the three-leaf-one-heart stage.

[0075] Select 3 plants with consistent growth from each replicate;

[0076] Root tissue (primary roots and lateral root segments 2-5 cm from the root tip) and leaf tissue (middle part of the second fully expanded leaf) were collected separately.

[0077] Immediately after collection, the samples were flash-frozen in liquid nitrogen and stored at -80°C.

[0078] RNA extraction, library preparation, and sequencing:

[0079] RNA extraction: Total RNA was extracted from each tissue sample using the TRIzol method. Concentration and purity were determined using Nanodrop (A260 / A280 = 1.8–2.0), and integrity (RIN > 7.0) was determined using an Agilent 2100 Bioanalyzer.

[0080] Library construction and sequencing:

[0081] Constructing sequencing libraries using the NEBNext Ultra™ RNA Library Prep Kit:

[0082] Oligo(dT) magnetic beads enrich mRNA;

[0083] After fragmentation, cDNA is synthesized;

[0084] End repair, adding A-tail, connecting connector;

[0085] For PCR amplification, select a fragment of 250-300 bp.

[0086] PE150 sequencing was performed using the Illumina NovaSeq 6000 platform, yielding 6 Gb of clean data per sample.

[0087] Transcriptome data analysis:

[0088] Data quality control and alignment: Low-quality reads and adapter sequences were removed using Fastp. Clean reads were aligned to the maize reference genome B73 RefGen_v4 using HISAT2.

[0089] Gene expression quantification and differential expression analysis: StringTie was used to calculate gene FPKM expression levels. DESeq2 was used for differential expression analysis, with the selection criteria being |log2FoldChange|>1 and a corrected p-value <0.05.

[0090] Functional annotation and enrichment analysis: Blast2GO was used for GO functional annotation. KEGG pathway enrichment analysis was performed using KOBAS (p-value < 0.05).

[0091] result:

[0092] Differentially expressed genes were identified: 1256 differentially expressed genes were identified in root tissue (687 upregulated and 569 downregulated); 892 differentially expressed genes were identified in leaf tissue (503 upregulated and 389 downregulated).

[0093] Functional enrichment analysis:

[0094] Differentially expressed genes in root tissues are mainly enriched in GO items such as ion transmembrane transport, oxidoreductase activity, and cell wall tissue; and KEGG pathways such as plant hormone signal transduction, MAPK signaling pathway, and phenylpropane biosynthesis.

[0095] The differentially expressed genes in leaf tissues are mainly enriched in GO items such as photosynthesis, reactive oxygen species metabolism, and abscisic acid response; and KEGG pathways such as photosynthetic antenna proteins, glutathione metabolism, and flavonoid biosynthesis.

[0096] Candidate gene screening:

[0097] Fifteen candidate genes that are specifically highly expressed in salt- and alkali-tolerant materials were screened, including:

[0098] Ion transporter genes: 3 (e.g., ZmHKT1);

[0099] Antioxidant enzyme genes: 5 (e.g., ZmSOD1, ZmAPX2);

[0100] Transcription factor genes: 4 (e.g., ZmbZIP72, ZmNAC48);

[0101] Osmotic regulation substance synthesis genes: 3 (e.g., ZmP5CS1).

[0102] Technical Results: This embodiment elucidates the molecular mechanism of salt tolerance in maize at the root and leaf levels through multi-tissue transcriptome sequencing, identifies key differentially expressed genes and metabolic pathways, and provides a foundation for the discovery of salt tolerance genes and the development of molecular markers.

[0103] Example 3:

[0104] Candidate gene expression verification: Five core candidate genes (ZmHKT1, ZmSOD1, ZmAPX2, ZmbZIP72, and ZmP5CS1) identified in Example 2 were selected, and their expression differences in the salt-tolerant material N-12 and the sensitive material S-08 were verified by qRT-PCR. The results showed that under salt-alkali stress, the expression levels of all candidate genes in N-12 were significantly higher than those in S-08.

[0105] Molecular marker development: KASP markers were developed targeting SNP sites in candidate genes. Genotyping was performed using 100 maize inbred lines as a validation population. The results showed that the Haplotype III haplotype of the ZmHKT1 gene was significantly associated with salt tolerance (p<0.01) and can be used as a molecular marker for auxiliary selection.

[0106] Salt-tolerant germplasm creation: Using the salt-tolerant backbone line N-35 (containing the lysine haplotype) as the donor and the salt-sensitive high-yielding line LH82 as the recipient, backcrossing was carried out.

[0107] In the BC2F2 population, salt-tolerant individual plants were screened using the seedling identification method in Example 1, while KASP markers were used to assist in selection.

[0108] Field verification was conducted at saline-alkali test sites in Hohhot and Ordos, Inner Mongolia (soil pH 8.5-9.0, electrical conductivity 1.2-1.8 dS / m).

[0109] Technical results: Under saline-alkali soil conditions, the yield increased by 18.7% compared to the recipient parent LH82, and the grain yield reached 85.3% of that under normal soil conditions. This embodiment verified the function of the candidate gene, developed molecular markers that can be used for breeding assistance, and created a new salt-alkali tolerant maize germplasm with production application value by combining traditional breeding with molecular marker-assisted selection.

[0110] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing, characterized in that, Includes the following steps: S1. Salt and alkali tolerance evaluation and grading: The plant germplasm to be tested was placed under suitable salt and alkali stress conditions for seedling culture, and its morphological and physiological and biochemical indicators were measured. The salt and alkali tolerance coefficients of each indicator were calculated, and the salt and alkali tolerance of the germplasm was comprehensively evaluated and graded using multivariate statistical analysis. S2. Collection of multiple tissue samples: From the germplasms classified into different levels of salt and alkali tolerance in step S1, select representative germplasms of salt-tolerant and salt-sensitive types respectively, collect fresh samples of their specific tissues, and quickly freeze them at low temperature. S3. Multi-tissue transcriptome sequencing: Total RNA was extracted from different tissue samples collected in step S2, sequencing libraries were constructed, and high-throughput transcriptome sequencing was performed to obtain clean read sequence data of each tissue sample. S4. Transcriptome data analysis: The obtained clean reads are compared and annotated with reference genomes or public non-redundant protein sequence databases to obtain gene annotation information; differentially expressed genes are identified based on gene expression data among different salt-tolerant germplasms and different tissues. S5. Mining of salt-alkali tolerance-related genes: Functional enrichment analysis and pathway analysis were performed on the differentially expressed genes identified in step S4 to screen candidate genes related to salt-alkali stress response and tolerance, which can be used as molecular markers for identifying and creating salt-alkali tolerant germplasm resources.

2. The method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing according to claim 1, characterized in that: In step S1, the appropriate concentration of salt-alkali stress conditions is determined through preliminary experiments. The preliminary experiments use a mixed salt-alkali solution prepared by NaCl, Na2SO4 and NaHCO3 in a molar ratio of 1:1:1, and set at least two concentration gradients to stress the test germplasm.

3. The method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing according to claim 1, characterized in that: In step S1, the morphological indicators include at least one of plant height, root length, root-to-shoot ratio, and total root surface area; the physiological and biochemical indicators include at least one of chlorophyll content, photosynthetic rate, superoxide dismutase activity, peroxidase activity, malondialdehyde content, and proline content.

4. The method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing according to claim 1, characterized in that: In step S1, the multivariate statistical analysis method includes at least one of membership function analysis, principal component analysis, and cluster analysis.

5. The method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing according to claim 1, characterized in that: In step S2, the specific tissue includes at least one of root tissue and leaf tissue or stem-leaf tissue.

6. The method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing according to claim 1, characterized in that: In step S4, the public non-redundant protein sequence database includes the NR, KEGG, and GO databases.

7. The method for identifying salt-tolerant plant germplasm resources using multi-tissue transcriptome sequencing according to claim 1, characterized in that: The plant is maize, and the germplasm of the plant to be tested is a maize inbred line.

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