Molecular marker linked with shade-tolerant character of soybean

Abstract

The invention discloses a molecular marker linked with the shade-tolerant character of soybeans, and belongs to the technical field of molecular breeding. After leaves of the soybean Nanxia bean 25 under shading treatment are collected, transcriptome and metabolome sequencing is carried out, and comprehensive transcriptome analysis is carried out, including DEGs analysis, KEGG enrichment analysis, DEGs identification participating in plant hormone signal channels, TF, photosynthesis, WGCNA and conjoint analysis of transcriptome and metabolome. On the basis of the analysis and gene functions, 12 candidate genes are finally screened out and are verified successfully through qRT-PCR (quantitative real-time polymerase chain reaction), so that the molecular marker linked with the shade-tolerant character of the soybean is screened and determined, and valuable resources are provided for the shade-tolerant molecular mechanism of the soybean and the molecular breeding of the shade-tolerant soybean.

Description

Technical Field

[0001] The invention belongs to the technical field of molecular breeding, and in particular relates to a molecular marker linked to a soybean shade tolerance trait. Background Art

[0002] Soybeans will fall over and grow over when shaded during their entire growth period. Especially in the soybean-corn strip-composite planting model, the yield difference between shade-tolerant and shade-intolerant varieties is significant, and the yield of shade-intolerant varieties will decrease significantly. Therefore, it is of great significance to carry out the mining of candidate genes related to soybean shade tolerance for breeding shade-tolerant soybean varieties.

[0003] Since the soybean seed shade tolerance trait is mostly a typical quantitative trait, which is easily affected by the environment, controlled by multiple genes, and has continuous variation, and most of them are micro-effect genes, it is relatively difficult to study the genetic basis of quantitative traits. Conventional QTL positioning methods cannot accurately locate micro-effect genes, and existing methods and publicly available molecular markers linked to soybean shade tolerance traits are inaccurate. With the emergence of multi-omics technology and the reduction of costs, using transcriptome sequencing to mine candidate genes has become a fast and effective way. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a molecular marker linked to the soybean shade tolerance trait and a screening method thereof, so as to solve the technical problem of inaccurate QTL positioning results.

[0005] To achieve the above object, the technical solution adopted by the present invention is: to provide a molecular marker screening method linked to soybean shade tolerance trait, comprising the following steps:

[0006] S1. Sowing and cultivating soybeans. After 40 days of sowing and cultivating, setting up a shading treatment group and a control group. The shading treatment group shades the soybeans with a shading net with a shading rate of 50%; the control group does not receive any treatment;

[0007] S2. On the 1st, 5th and 9th day after shading, the leaves of soybean plants in the control group and the shading treatment group were taken for transcriptome sequencing;

[0008] S3, performing weighted gene co-expression network analysis on the transcriptome sequencing data to determine candidate genes, performing quantitative PCR verification on the candidate genes, and entering step S4 with candidate genes that pass the quantitative PCR verification, otherwise, discarding candidate genes that fail the verification;

[0009] S4. Develop molecular markers for shade tolerance genes based on the physical location of candidate genes on the soybean genome;

[0010] S5. Position the molecular markers linked to the shade tolerance gene on the soybean heritage linkage map.

[0011] On the basis of the above technical solution, the present invention can also be improved as follows:

[0012] Further, step S2 is specifically as follows: picking soybean plant leaves from the control group and the shading treatment group, taking three replicates of the two groups of soybeans, taking leaves from at least three different soybean plants in the same group for each replicate, and collecting 18 samples at each time point for transcriptome sequencing.

[0013] Further, step S3 is specifically as follows: weighted gene co-expression network analysis is specifically as follows: estimating the weighted values ​​of genes for transcriptome sequencing data, and constructing a gene weighted matrix; performing correlation analysis on gene expression patterns and phenotypic values ​​of shade-tolerance physiological indicators according to the gene weighted matrix, screening out soybean shade-tolerance candidate genes, and using quantitative PCR to verify the candidate genes screened out by the correlation analysis; the correlation analysis includes differentially expressed gene DEGs analysis, KEGG enrichment analysis of differentially expressed gene DEGs, identification of DEGs involved in plant hormone signaling pathways, identification analysis of differentially expressed transcription factors, identification analysis of photosynthesis, weighted gene co-expression network analysis, and joint analysis of transcriptome and metabolome.

[0014] Furthermore, the soybean variety sown and cultivated is Nanxiadou 25.

[0015] The present invention also provides a molecular marker linked to the soybean shade tolerance trait obtained by screening using the above method, including:

[0016] SWU02SR01, the forward primer sequence is: ACATAGCCAAGCCATGCATG; the rear primer sequence is: TGGCCACTTATACTCGATCCT;

[0017] SWU05SR01, the forward primer sequence is: GCGCGTCTATCCAACGAAAT; the rear primer sequence is: AGAGAAGCGAGATACAGTACGT;

[0018] SWU07SR01, the forward primer sequence is: CGATGGGCCCTTAAAAGCTT; the rear primer sequence is: CAAGGAATATGGTGCCAACTTA;

[0019] SWU08SR01, the forward primer sequence is: TTTGTGTCCCCGTAAACTGC; the rear primer sequence is: ACGATACCTATTCCTCATTAACAT;

[0020] SWU08SR02, the forward primer sequence is: TTTGTGTCCCCGTAAACTGC; the rear primer sequence is: ACGATACCTATTCCTCATTAACAT;

[0021] SWU08SR03, the forward primer sequence is: ACCCATAGCCTTATCAAGCCA; the rear primer sequence is: TGACTGACTTGAGGACACCA;

[0022] SWU10SR01, the forward primer sequence is: AGCATTTTCTTGATTAGTTGCTCT; the rear primer sequence is: CCCAATCAACTTTCTCTTATCGCT;

[0023] SWU10SR02, the forward primer sequence is: TCATTTGTTTCACCAATTCACCA; the rear primer sequence is: ACGTCATGTTCAATTTGCAGT;

[0024] SWU10SR03, the forward primer sequence is: ACAGTAACCTTAAGAAGTTGAACT; the rear primer sequence is: TGGTCTTTTATGTCAAATGCAAGTG;

[0025] SWU13SR01, the forward primer sequence is: AGGGTCGGAGGTGTACAGTA; the rear primer sequence is: AGCCTTAAGAGCAGTGCAGA;

[0026] SWU17SR01, the forward primer sequence is: TGGGATGGCATGTCAGTTTT; the rear primer sequence is: CAAGAAAATCATGCATGGTAGACT;

[0027] SWU19SR01, the forward primer sequence is: TCCCCCTTTTCCATGCATCA; the rear primer sequence is: TCTCCCTTCCTCGTTGATAT.

[0028] The beneficial effects of the present invention are:

[0029] The present invention collects the leaves of soybean Nanxiadou 25 under shading treatment, and then performs transcriptome and metabolome sequencing, and conducts comprehensive transcriptome analysis, including DEGs analysis, KEGG enrichment analysis, identification of DEGs involved in plant hormone signaling pathways, TF, photosynthesis, WGCNA, and joint analysis of transcriptome and metabolome. Based on the above analysis and gene function, 12 candidate genes were finally screened out and successfully verified by qRT-PCR, thereby screening and determining the molecular markers linked to the soybean shade tolerance trait, providing valuable resources for the molecular mechanism of soybean shade tolerance and the utilization of shade-tolerant soybean molecular breeding. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1This is the agarose electrophoresis diagram of total RNA in the leaves of soybean Nanxiadou 25 after control and shading treatment;

[0031] Figure 2 Schematic diagram of correlation analysis of transcriptome sequencing results of three biological replicates among samples;

[0032] Figure 3 Volcano plot of differentially expressed genes;

[0033] Figure 4 is the cluster diagram of differentially expressed genes;

[0034] Figure 5 Schematic diagram of KEGG enrichment analysis of DEGs;

[0035] Figure 6 Schematic diagram of the analysis of DEGs in plant hormone signaling pathways;

[0036] Figure 7 Schematic diagram of transcription factor analysis;

[0037] Figure 8 Heat map of genes involved in photosynthesis;

[0038] Fig. 9 Schematic diagram of WGCNA co-expression network analysis;

[0039] Fig.10 Schematic diagram of the metabolome sequencing analysis of ND1 and SHND1 leaves;

[0040] Fig.11 Schematic diagram of the joint analysis of transcriptome and metabolome;

[0041] Fig.12 Schematic diagram of qRT-PCR validation of 12 soybean shade tolerance-related differentially expressed genes;

[0042] Fig.13 Schematic diagram of the position of molecular markers linked to shade tolerance genes on the genetic linkage map. DETAILED DESCRIPTION

[0043] The specific embodiments of the present invention are described below to facilitate the understanding of the present invention by those skilled in the art. If the specific conditions are not specified in the examples, the methods are carried out according to conventional conditions or conditions recommended by the manufacturer. If the manufacturers are not specified in the reagents or instruments used, they are all conventional products that can be purchased commercially. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention defined and determined by the attached claims, these changes are obvious, and all inventions and creations using the concept of the present invention are protected.

[0044] A method for screening molecular markers linked to soybean shade tolerance traits comprises the following steps:

[0045] S1. Sowing and cultivating soybeans. After 40 days of sowing and cultivating, setting up a shading treatment group and a control group. The shading treatment group shades the soybeans with a shading net with a shading rate of 50%; the control group does not receive any treatment;

[0046] This experiment was conducted at the undergraduate experimental teaching base of the College of Agriculture and Biotechnology of Southwest University in Beibei District, Chongqing. The shade-tolerant soybean variety "Nanxiadou 25" bred by the Nanchong Academy of Agricultural Sciences in Sichuan Province was selected. A total of 12 rows were sown, with a row length of 2 meters, a row spacing of 0.5 meters, and a nest spacing of 0.2 meters. After 40 days of sowing and cultivation, 6 rows were selected as the shade treatment group (SHND1): shaded with a shade net with a shading rate of 50%, and the remaining 6 rows were not shaded as the control group (ND1);

[0047] S2. On the 1st, 5th and 9th day after shading, the leaves of soybean plants in the control group and the shading treatment group were taken for transcriptome sequencing; in the specific implementation, the leaves of plants in three shading time periods were selected, and three biological replicates were taken in each time period, and RNA was extracted respectively, and then reverse transcribed into cDNA. The leaves of soybean plants in the control group and the shading treatment group were picked, and the two groups of soybeans were repeated 3 times. Each replicate took leaves of at least 3 different soybean plants in the same group. 18 samples were collected at each time point, and the samples were pretreated before transcriptome sequencing. The pretreatment adopted the conventional leaf pretreatment method, so it is not repeated.

[0048] Specifically, the Illumina HiSeq4000 platform was used for transcriptional sequencing, and the Vanquish UHPLC system and Orbitrap QExactiveTM HF mass spectrometer were used for metabolomics detection. A total of 6 library samples were constructed and sequenced using the Illumina HiSeqTM 4000 platform. A total of 38.41Gb of clean data were obtained from the 6 library samples. High-throughput RNA-Seq sequencing, the sequencing results are as follows Figure 1 As shown, the extracted RNA was reverse transcribed into cDNA and the correlation was evaluated. The evaluation results are shown in Figure 2 As shown by Figure 2 It can be seen that the six library samples showed high correlation between the same group of replicates. These clean reads were mapped to the reference genome with a match rate between 94.23-96.19%. The percentage of Q30 bases in each sample ranged from 93.58% to 94.47%, and the GC content ranged from 44.21% to 44.66%.

[0049] S3, performing weighted gene co-expression network analysis on the transcriptome sequencing data to determine candidate genes, performing quantitative PCR verification on the candidate genes, and entering step S4 with candidate genes that pass the quantitative PCR verification, otherwise, discarding candidate genes that fail the verification;

[0050] The weighted gene co-expression network analysis was specifically as follows: the weighted values ​​of genes were estimated using the WGCNA package in R software, and a gene weight matrix was constructed. The WGCNA package (version 1.6.6) in the R program was used to construct the weighted gene co-expression network of ND1 and SHND1. After inputting the normalized gene expression matrix, the weighted values ​​were calculated using SoftThreashold in the WGCNA package. The soft connection function was used to calculate the degree of connection of genes to obtain expression modules. The correlation between the three expression modules and shade-related traits (RaBisCO, chlorophyll a, chlorophyll b, carotenoids, and total chlorophyll) was analyzed. Cytoscape (version 3.9.1) was used to visualize the network in the module and screen out the core genes. The selection of core genes was based on the following factors. The correlation between the gene and other genes or the regulatory network in which it exists. If the gene is associated with more genes than the threshold, or the node position gene is in the regulatory network, the gene is a core gene, and the threshold of the correlation coefficient is >0.95.

[0051] The differentially expressed genes DEGs analysis was as follows: The differential expression analysis of ND1 and SHND1 yielded the following results: Figure 3 The DEGs volcano map shown in Figure 2, where each dot represents a differentially expressed gene (DEG), blue dots represent down-regulated DEGs, red dots represent up-regulated DEGs, and gray dots represent non-differentially expressed genes; Figure 3 A total of 265 differentially expressed genes were found between ND1 and SHND1, of which 144 DEGs had decreased expression levels after shading, and 121 DEGs had increased expression levels. Hierarchical clustering analysis was performed on the 265 DEGs screened, and the results were as follows: Figure 4 As shown, the colors represent the gene expression levels log10(FPKM+0.000001) in the samples, and DEGs with similar expression patterns are likely to have the same functions.

[0052] KEGG enrichment analysis was performed on the 265 differentially expressed gene DEGs screened out, and the results were as follows Figure 5 As shown, Figure 5 A is a bubble chart of KEGG enrichment analysis of DEGs. The higher the enrichment factor, the more significant the enrichment level of DEGs in the pathway. The color of the circle represents the q value. The size of the circle represents the number of genes enriched in the pathway; Figure 5 B is the heat map of DEGs in the enriched pathways; Figure 5A showed that DEGs were significantly enriched in histidine metabolism (Ko00340), riboflavin metabolism (Ko00740), vitamin B6 metabolism (Ko0.0750), glycerolipid metabolism (Ko00561), and cutin, suberin, and wax biosynthesis (Ko00073) (q value < 0.05). Figure 5 B As can be seen, KEGG analysis found that the top five pathways with the most differential gene enrichment were enriched with 22 differentially expressed genes, including histidine metabolism, riboflavin metabolism, vitamin B6 metabolism, glycerolipid metabolism pathway, cutin, suberin and wax biosynthesis, most of which were downregulated after shading.

[0053] The identification of DEGs involved in the plant hormone signaling pathway is as follows: the screened DEGs are tested for the plant hormone signaling pathway, and the test results are as follows Figure 6 As shown, Figure 6 A is a schematic diagram of the plant hormone signal transduction pathway. Figure 6 B is the heat map of DEGs involved in plant hormone signaling pathway; Figure 6 It can be seen that a total of 19 DEGs (14 up-regulated and 5 down-regulated) were involved in the plant hormone signaling pathway. Among them, 7 DEGs were involved in auxin metabolism, including 3 auxin response proteins, 2 AUX / IAA family, 1 auxin transporter-like protein, 1 hormone response factor and 2 membrane transporters, all of which were up-regulated after shading ( Figure 6 B). The cytokinin signaling pathway involved 6 genes, of which 5 were up-regulated and 1 was down-regulated. In addition, the gibberellin, abscisic acid, jasmonic acid, and salicylic acid metabolic pathways contained 1, 2, 2, and 1 differentially expressed genes, respectively.

[0054] The identification and analysis of differentially expressed transcription factors are as follows: transcription factor analysis is performed, and the analysis results are as follows: Figure 7 As shown, Figure 7 A is a schematic diagram of the number of identified TFs. Figure 7 B is a schematic diagram of the number of differentially expressed transcription factors; Figure 7 C is the heat map of differentially expressed genes; Figure 7It can be seen that 7035 transcription factors (TFs) were screened in 20 transcription factor families, mainly including MYB (330 genes), AP2 / ERF-ERF (309 genes), bHLH (313 genes) and RLK-Pelle_DLSV (278 genes). In addition, 34 differentially expressed transcription factors (DETFs) were identified, of which SHND1 group had 21 up-regulated and 13 down-regulated transcription factors. In particular, two AUX / IAA genes (Glyma.08G207900 and Glyma.10G031900) were identified, which were up-regulated after shading. Five genes, including one MYB (Glyma.02G013900), two bZIPs (Glyma.013G081700 and Glyma.12G184400), and two bHLHs (Glyma.13G368700 and Glyma.17G058600), were identified to be more highly expressed in the ND group.

[0055] The identification and analysis of photosynthesis specifically included screening and analysis of genes related to RuBisCO, photosystem I reaction center subunit (PSA), and chlorophyll ab binding (CAB) genes. Figure 8 As shown, Figure 8 A is the heat map of RuBisCO-related genes screened out. Figure 8 B is the heat map of the screened photosystem I reaction center subunit (PSA) genes, Figure 8 C is the heat map of the screened chlorophyll AB binding (CAB) genes; Figure 8 It can be seen that a total of 30 genes related to RuBisCO and 29 genes related to PSA were identified, all of which had no significant differences between ND1 and SHND1. A total of 47 CAB genes were identified, and 2 genes (Glyma.20G150600 and Glyma.10G243800) were downregulated in the shading group.

[0056] The weighted gene co-expression network analysis is as follows: all genes are analyzed using WGCNA to understand the regulatory network of soybean shade stress. Fig. 9 As shown, Fig. 9 A is a gene cluster dendrogram and module detection schematic diagram, Fig. 9 B is a schematic diagram of the association analysis between gene co-expression network modules and traits; Fig. 9 C is a schematic diagram of the gene co-expression network of core genes in the MEblue module; Fig. 9 D is the heat map of hub genes in the MEblue module; Fig. 9It can be seen that three expression modules were obtained: MEbrown, MEblue and MEturquoise. Except for chlorophyll b, all traits of RuBisCO, chlorophyll a, chlorophyll b, carotenoids and total chlorophyll were significantly negatively correlated with MEblue. The correlation analysis between genes, traits and modules showed that in the MEblue module, there were 20 core genes with MM (module membership) ≥ 0.95 and GS (gene significance) ≥ 0.95. The gene co-expression network in the MEblue module (weight> 0.7) was drawn using Cytoscape software, and 26 central genes were screened out. All these core genes and central genes were significantly downregulated after shading.

[0057] The combined analysis of transcriptome and metabolome was as follows: Non-targeted GC-MS analysis was performed on the leaves of ND1 and SHND1. Fig.10 As shown, Fig.10 A is the volcano plot of different metabolites. Fig.10 B shows the 20 most differentially expressed metabolites in the comparison group, red (upregulated) and green (downregulated); Fig.10 It can be seen that 101 differentially abundant metabolites (DAMs) were detected, including 26 up-regulated metabolites and 75 down-regulated metabolites after shading. After logarithmic transformation of the difference folds of the differential metabolites between ND1 and SHND1, the top 10 metabolites up-regulated and down-regulated in SHND1 are as follows Fig.10 As shown in B. In SHND1, 3-Deoxyaconitine increased the most (log2-fold charge = 15.6), and songorine decreased the most (log2-fold charge = -18.91).

[0058] KEGG enrichment analysis was performed on DAMs and DEGs, and the results were as follows Fig.11 As shown, Fig.11 A is a schematic diagram of the top 10 pathways of KEGG enrichment analysis of common DAMs and DEGs; Fig.11 B is the heat map of differentially expressed genes in the pathway; Fig.11 C is the network diagram of the correlation between metabolites and genes; Fig.11It can be seen that DAMs and DEGs were strongly enriched in starch and sucrose metabolism, amino acid biosynthesis, carbon metabolism, galactose metabolism, and flavonoid biosynthesis. Among the top 10 KEGG-enriched pathways, the starch and sucrose metabolism pathway had the most DEGs, with 7 genes, and the ABC transporter pathway had 7 DAMs. Among all KEGG-enriched pathways, 36 DEGs were identified, including 20 up-regulated genes and 16 down-regulated genes. To determine the correlation between DAMs and DEGs, correlation analysis was performed based on the Pearson correlation coefficient. A total of 23 DEGs were highly correlated with DAMs (correlation coefficient > 0.8), and a network diagram showing the correlation between metabolites and genes was drawn.

[0059] According to the above analysis, 12 candidate DEGs were screened, including Glyma.02G135400, Glyma.05G247900, Glyma.07G209500, Glyma.08G056400, Glyma.08G195100, Glyma.08G207900, Glyma.10G031900, Glyma.10G151800, Glyma.10G204200, Glyma.13G368700, Glyma.17G058600, and Glyma.19G177100; qRT-PCR was used to detect the expression levels of the 12 candidate DEGs in ND1 and SHND1. The results are shown in Figure 2. Fig.12 As shown, the bars represent the relative expression determined by qRT-PCR, and the broken lines represent the expression levels determined by RNA-seq (FPKM); Fig.12 It can be seen that the expression levels of the above 12 DEGs are basically consistent with the FPKM values ​​detected by RNA-Seq. The above 12 DEGs are all taken as candidate genes and enter step S4;

[0060] S4. Develop molecular markers for shade tolerance genes based on the physical location of candidate genes on the soybean genome;

[0061] Specifically, primers were designed and developed based on the flanking sequences of InDel using the Primer 5 tool. Based on the ID numbers of the 12 soybean shade-tolerant genes, the physical locations of the 12 genes were queried on the Phytozome website, and then InDel primers within the physical interval of the candidate genes or closest to the physical location of the genes were screened. InDel primers were developed based on the resequencing of the parents Changjiangchun 2 and Jiyu 166. The 10× resequencing data was compared with the soybean reference genome sequence (Wm82.a4.v1) to screen the InDel sites between the parents. In order to facilitate the identification of primer polymorphisms of the parents, InDels with >15bp were selected as candidate InDel markers. The primers were considered as molecular markers linked to the shade-tolerant gene.

[0062] The linkage markers and corresponding primers of the 12 candidate genes are shown in Table 1 ;

[0063] Table 1

[0064] Shade tolerance gene Linked markers Forward primer sequence Rear primer sequence Glyma.02G135400 SWU02SR01 ACATAGCCAAGCCATGCATG TGGCCACTTATACTCGATCCT Glyma.05G247900 SWU05SR01 GCGCGTCTATCCAACGAAAT AGAGAAGCGAGATACAGTACGT Glyma.07G209500 SWU07SR01 CGATGGGCCCTTAAAAGCTT CAAGGAATATGGTGCCAACTTA Glyma.08G056400 SWU08SR01 TTTGTGTCCCCGTAAACTGC ACGATACCTATTCCTCATTAACAT Glyma.08G195100 SWU08SR02 TTTGTGTCCCCGTAAACTGC ACGATACCTATTCCTCATTAACAT Glyma.08G207900 SWU08SR03 ACCCATAGCCTTATCAAGCCA TGACTGACTTGAGGACACCA Glyma.10G031900 SWU10SR01 AGCATTTTCTTGATTAGTTGCTCT CCCAATCAACTTTCTCTTATCGCT Glyma.10G151800 SWU10SR02 TCATTTGTTTCACCAATTCACCA ACGTCATGTTCAATTTGCAGT Glyma.10G204200 SWU10SR03 ACAGTAACCTTAAGAAGTTGAACT TGGTCTTTTATGTCAAATGCAAGTG Glyma.13G368700 SWU13SR01 AGGGTCGGAGGTGTACAGTA AGCCTTAAGAGCAGTGCAGA Glyma.17G058600 SWU17SR01 TGGGATGGCATGTCAGTTTT CAAGAAAATCATGCATGGTAGACT Glyma.19G177100 SWU19SR01 TTCCCCTTTTCCATGCATCA TCTCCCTTCCTCGTTGATAT

[0065] S5. Position the molecular markers linked to the shade tolerance gene on the soybean heritage linkage map.

[0066] Specifically, the SSR primers distributed on soybean chromosomes are selected to screen polymorphic primers, the primers are used to detect the marker genotype of the genetic population, the marker loci are subjected to genetic linkage analysis, and the genetic linkage map of soybean is constructed; the specific steps are:

[0067] S501. Extraction of soybean whole genome DNA: Obtain parental and second-generation F2 samples, including parental Changjiangchun 2 and Jiyu 166, and 186 individual plants of the F2 population, take 3g of fresh leaves from each of them, preserve them, number them, and extract soybean genomic DNA;

[0068] S502, PCR amplification: Pipette 12 μL of DNA into a PCR plate, add 88 μL of ddH2O, dilute 12 times as a template. The amplification system of 10 μL PCR is shown in Table 2. After the preparation is completed, put the PCR plate into a PCR instrument for amplification. The PCR reaction program is shown in Table 3;

[0069] Table 2

[0070] Reagents 10μL system Template DNA (50ng / μL) 2.0μL 2×T5SuperPCRMix 4.0μL Forward primer (10 μM / L) 0.4μL Post primer (10 μM / L) 0.4μL ddH2O 3.2μL

[0071] Table 3

[0072]

[0073] S503. Inspection of SSR amplification products: PCR products were subjected to 30% polyacrylamide gel electrophoresis (30% PAGE gel) to identify and screen SSR markers;

[0074] S504. Determination of protein, crude fat and fatty acids: Select uniform-sized seeds from the harvested soybean seeds and cover the petri dish with them as the soybean sample to be tested. Place the petri dish covered with seeds in the sample pool of the FOSS near-infrared system FOSS NIRSDS2500 (including detector and software) of the near-infrared analyzer to measure the protein, crude fat and fatty acids of the two parents and F2 and F 2:3 、F 2:4 and F 2:5 Phenotypic traits of the population;

[0075] S505, polymorphic primer screening and population marker genotype detection: SSR primer sequences were downloaded from the soybean marker public database Soybase (http: / / www.soybase.org / ), and the InDel primers designed for the two parents were synthesized by Shanghai Biotech. 2933 pairs of SSR primers and 162 pairs of InDel primers evenly distributed on the 20 chromosomes of soybean were selected to screen the parents Changjiangchun 2 and Jiyu 166 for primer polymorphism, and finally 518 pairs of SSR polymorphic primers were obtained, with a polymorphism ratio of 17.70%. The primer pairs with polymorphism (Changjiangchun 2×Jiyu 166) F2 population were tested for marker genotype. In the data statistics, the band type consistent with Changjiangchun 2 was recorded as A, the band type consistent with Jiyu 166 was recorded as B, the heterozygous type was recorded as H, and the missing band type was recorded as U. Using 518 pairs of screened polymorphic primers and 86 pairs of InDel primers designed according to the parents, 186 individuals in the F2 population (Changjiangchun 2×Jiyu 166) were tested for marker genotypes, and 518 polymorphic sites were obtained.

[0076] S506. Construction of soybean genetic linkage map: Using Joinmap4.0 analysis software, genetic linkage analysis was performed on polymorphic marker sites on chromosomes containing shade-tolerance gene molecular markers to construct a genetic linkage map of some chromosomes. Fig.13 shown.

Claims

1. Molecular markers linked to soybean shade tolerance traits, It is characterized in that include: SWU02SR01, the forward primer sequence is: ACATAGCCAAGCCATGCATG; the rear primer sequence is: TGGCCACTTATACTCGATCCT; SWU05SR01, the forward primer sequence is: GCGCGTCTATCCAACGAAAT; the rear primer sequence is: AGAGAAGCGAGATACAGTACGT; SWU07SR01, the forward primer sequence is: CGATGGGCCCTTAAAAGCTT; the rear primer sequence is: CAAGGAATATGGTGCCAACTTA; SWU08SR01, the forward primer sequence is: TTTGTGTCCCCGTAAACTGC; the rear primer sequence is: ACGATACCTATTCCTCATTAACAT; SWU08SR02, the forward primer sequence is: TTTGTGTCCCCGTAAACTGC; the rear primer sequence is: ACGATACCTATTCCTCATTAACAT; SWU08SR03, the forward primer sequence is: ACCCATAGCCTTATCAAGCCA; the rear primer sequence is: TGACTGACTTGAGGACACCA; SWU10SR01, the forward primer sequence is: AGCATTTTCTTGATTAGTTGCTCT; the rear primer sequence is: CCCAATCAACTTTCTCTTATCGCT; SWU10SR02, the forward primer sequence is: TCATTTGTTTCACCAATTCACCA; the rear primer sequence is: ACGTCATGTTCAATTTGCAGT; SWU10SR03, the forward primer sequence is: ACAGTAACCTTAAGAAGTTGAACT; the rear primer sequence is: TGGTCTTTTATGTCAAATGCAAGTG; SWU13SR01, the forward primer sequence is: AGGGTCGGAGGTGTACAGTA; the rear primer sequence is: AGCCTTAAGAGCAGTGCAGA; SWU17SR01, the forward primer sequence is: TGGGATGGCATGTCAGTTTT; the rear primer sequence is: CAAGAAAATCATGCATGGTAGACT; SWU19SR01, the forward primer sequence is: TCCCCCTTTTCCATGCATCA; the rear primer sequence is: TCTCCCTTCCTCGTTGATAT.

2. A method for screening molecular markers according to claim 1, It is characterized in that The following steps are involved: S1. Sowing and cultivating soybeans. After 40 days of sowing and cultivating, setting up a shading treatment group and a control group. The shading treatment group shades the soybeans with a shading net with a shading rate of 50%; the control group does not receive any treatment; S2. On the 1st, 5th and 9th day after shading, the leaves of soybean plants in the control group and the shading treatment group were taken for transcriptome sequencing; S3, performing weighted gene co-expression network analysis on the transcriptome sequencing data to determine candidate genes, performing quantitative PCR verification on the candidate genes, and entering step S4 with candidate genes that pass the quantitative PCR verification, otherwise, discarding candidate genes that fail the verification; S4. Develop molecular markers for shade tolerance genes based on the physical location of candidate genes on the soybean genome; S5. Position the molecular markers linked to the shade tolerance gene on the soybean heritage linkage map.

3. The molecular marker screening method according to claim 2, It is characterized in that The step S2 specifically includes: picking soybean plant leaves from the control group and the shading treatment group, taking 3 replicates of the two groups of soybeans, taking leaves from at least 3 different soybean plants in the same group for each replicate, and collecting 18 samples at each time point for transcriptome sequencing.

4. The molecular marker screening method according to claim 2, It is characterized in that The weighted gene co-expression network analysis is specifically as follows: estimating the weighted values ​​of genes for transcriptome sequencing data and constructing a gene weighted matrix; performing correlation analysis on gene expression patterns and phenotypic values ​​of shade-tolerance physiological indicators according to the gene weighted matrix, screening out soybean shade-tolerance candidate genes, and using quantitative PCR to verify the candidate genes screened out by the correlation analysis; the correlation analysis includes differentially expressed gene DEGs analysis, KEGG enrichment analysis of differentially expressed gene DEGs, identification of DEGs involved in plant hormone signaling pathways, identification analysis of differentially expressed transcription factors, identification analysis of photosynthesis, weighted gene co-expression network analysis, and joint analysis of transcriptome and metabolome.

5. The molecular marker screening method according to claim 2, It is characterized in that The soybean variety sown and cultivated is Nanxiadou 25.

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