Genome-wide association studies reveal novel QTLs for agronomic traits in soybean.

Introduction: Soybean, as a globally significant crop, has garnered substantial attention due to its agricultural importance. The utilization of molecular approaches to enhance grain yield in soybean has gained popularity. Methods: In this study, we conducted a genome-wide association study (GWAS) using 156 Chinese soybean accessions over a two-year period. We employed the general linear model (GLM) and the mixed linear model (MLM) to analyze three agronomic traits: pod number, grain number, and grain weight. Results: Our findings revealed significant associations between qgPNpP-98, qgGNpP-89 and qgHGW-85 QTLs and pod number, grain number, and grain weight, respectively. These QTLs were identified on chromosome 16, a region spanning 413171bp exhibited associations with all three traits. Discussion: These QTL markers identified in this study hold potential for improving yield and agronomic traits through marker-assisted selection and genomic selection in breeding programs.

Flowering time regulator qFT13-3 involved in soybean adaptation to high latitudes.

Soybean is a short-day plant that typically flowers earlier when exposed to short-day conditions. However, the identification of genes associated with earlier flowering time but without a yield penalty is rare. In this study, we conducted genome-wide association studies (GWAS) using two re-sequencing datasets that included 113 wild soybeans (G. soja) and 1192 cultivated soybeans (G. max), respectively, and simultaneously identified a candidate flowering gene, qFT13-3, which encodes a protein homologous to the pseudo-response regulator (PRR) transcription factor. We identified four major haplotypes of qFT13-3 in the natural population, with haplotype H4 (qFT13-3H4) being lost during domestication, while qFT13-3H1 underwent natural and artificial selection, increasing in proportion from 4.5% in G. soja to 43.8% in landrace and to 81.9% in improve cultivars. Notably, most cultivars harbouring qFT13-3H1 were located in high-latitude regions. Knockout of qFT13-3 accelerated flowering and maturity time under long-day conditions, indicating that qFT13-3 functions as a flowering inhibitor. Our results also showed that qFT13-3 directly downregulates the expression of GmELF3b-2 which is a component of the circadian clock evening complex. Field trials revealed that the qft13-3 mutants shorten the maturity period by 11 days without a concomitant penalty on yield. Collectively, qFT13-3 can be utilized for the breeding of high-yield cultivars with a short maturity time suitable for high latitudes.

Genome-wide signatures of the geographic expansion and breeding of soybean.

Soybean is a leguminous crop that provides oil and protein. Exploring the genomic signatures of soybean evolution is crucial for breeding varieties with improved adaptability to environmental extremes. We analyzed the genome sequences of 2,214 soybeans and proposed a soybean evolutionary route, i.e., the expansion of annual wild soybean (Glycine soja Sieb. & Zucc.) from southern China and its domestication in central China, followed by the expansion and local breeding selection of its landraces (G. max (L.) Merr.). We observed that the genetic introgression in soybean landraces was mostly derived from sympatric rather than allopatric wild populations during the geographic expansion. Soybean expansion and breeding were accompanied by the positive selection of flowering time genes, including GmSPA3c. Our study sheds light on the evolutionary history of soybean and provides valuable genetic resources for its future breeding.

Identification of Drought-Tolerance Genes in the Germination Stage of Soybean.

Drought stress influences the vigor of plant seeds and inhibits seed germination, making it one of the primary environmental factors adversely affecting food security. The seed germination stage is critical to ensuring the growth and productivity of soybeans in soils prone to drought conditions. We here examined the genetic diversity and drought-tolerance phenotypes of 410 accessions of a germplasm diversity panel for soybean and conducted quantitative genetics analyses to identify loci associated with drought tolerance of seed germination. We uncovered significant differences among the diverse genotypes for four growth indices and five drought-tolerance indices, which revealed abundant variation among genotypes, upon drought stress, and for genotype × treatment effects. We also used 158,327 SNP markers and performed GWAS for the drought-related traits. Our data met the conditions (PCA + K) for using a mixed linear model in TASSEL, and we thus identified 26 SNPs associated with drought tolerance indices for germination stage distributed across 10 chromosomes. Nine SNP sites, including, for example, Gm20_34956219 and Gm20_36902659, were associated with two or more phenotypic indices, and there were nine SNP markers located in or adjacent to (within 500 kb) previously reported drought tolerance QTLs. These SNPs led to our identification of 41 candidate genes related to drought tolerance in the germination stage. The results of our study contribute to a deeper understanding of the genetic mechanisms underlying drought tolerance in soybeans at the germination stage, thereby providing a molecular basis for identifying useful soybean germplasm for breeding new drought-tolerant varieties.

Profiling of naturally occurring folates in a diverse soybean germplasm by HPLC-MS/MS.

Soybean is a rich source of folates. We optimised the extraction and detection of folates from soybean seeds by HPLC-MS/MS and analysed the folate content and composition of 1074 accessions. Total folate content ranged from 64.51 to 691.24 µg/100 g fresh weight, with 10-fold variation, and 60 elite accessions with over 400 µg/100 g of total folate were identified. The most abundant component was 5-CHO-H4folate, which accounted for an average of 60% of total folate content. Seed-coat colour, seed weight, ecoregion, and accession type significantly affected soybean folate content. Furthermore, 5-CH3-H4folate correlated positively with seed protein (r = 0.24***) and negatively with oil (r = -0.26***). The geographical distribution of folate according to accession origin revealed that accessions from Northeast China contain higher amounts of total folate and 5-CHO-H4folate. This study provides comprehensive and novel insights into the folate profile of soybean, which will benefit soybean breeding for folate enhancement.

SoySNP618K array: A high-resolution single nucleotide polymorphism platform as a valuable genomic resource for soybean genetics and breeding.

Innovations in genomics have enabled the development of low-cost, high-resolution, single nucleotide polymorphism (SNP) genotyping arrays that accelerate breeding progress and support basic research in crop science. Here, we developed and validated the SoySNP618K array (618,888 SNPs) for the important crop soybean. The SNPs were selected from whole-genome resequencing data containing 2,214 diverse soybean accessions; 29.34% of the SNPs mapped to genic regions representing 86.85% of the 56,044 annotated high-confidence genes. Identity-by-state analyses of 318 soybeans revealed 17 redundant accessions, highlighting the potential of the SoySNP618K array in supporting gene bank management. The patterns of population stratification and genomic regions enriched through domestication were highly consistent with previous findings based on resequencing data, suggesting that the ascertainment bias in the SoySNP618K array was largely compensated for. Genome-wide association mapping in combination with reported quantitative trait loci enabled fine-mapping of genes known to influence flowering time, E2 and GmPRR3b, and of a new candidate gene, GmVIP5. Moreover, genomic prediction of flowering and maturity time in 502 recombinant inbred lines was highly accurate (>0.65). Thus, the SoySNP618K array is a valuable genomic tool that can be used to address many questions in applied breeding, germplasm management, and basic crop research.

Genome-wide association study of soybean seed germination under drought stress.

Drought stress, which is increasing with climate change, is a serious threat to agricultural sustainability worldwide. Seed germination is an essential growth phase that ensures the successful establishment and productivity of soybean, which can lose substantial productivity in soils with water deficits. However, only limited genetic information is available about how germinating soybean seeds may exert drought tolerance. In this study, we examined the germinating seed drought-tolerance phenotypes and genotypes of a panel of 259 released Chinese soybean cultivars panel. Based on 4616 Single-Nucleotide Polymorphisms (SNPs), we conducted a mixed-linear model GWAS that identified a total of 15 SNPs associated with at least one drought-tolerance index. Notably, three of these SNPs were commonly associated with two drought-tolerance indices. Two of these SNPs are positioned upstream of genes, and 11 of them are located in or near regions where QTLs have been previously mapped by linkage analysis, five of which are drought-related. The SNPs detected in this study can both drive hypothesis-driven research to deepen our understanding of genetic basis of soybean drought tolerance at the germination stage and provide useful genetic resources that can facilitate the selection of drought stress traits via genomic-assisted selection.

Identification of loci controlling adaptation in Chinese soya bean landraces via a combination of conventional and bioclimatic GWAS.

Landraces often contain genetic diversity that has been lost in modern cultivars, including alleles that confer enhanced local adaptation. To comprehensively identify loci associated with adaptive traits in soya bean landraces, for example flowering time, a population of 1938 diverse landraces and 97 accessions of the wild progenitor of cultivated soya bean, Glycine soja was genotyped using tGBS® . Based on 99 085 high-quality SNPs, landraces were classified into three sub-populations which exhibit geographical genetic differentiation. Clustering was inferred from STRUCTURE, principal component analyses and neighbour-joining tree analyses. Using phenotypic data collected at two locations separated by 10 degrees of latitude, 17 trait-associated SNPs (TASs) for flowering time were identified, including a stable locus Chr12:5914898 and previously undetected candidate QTL/genes for flowering time in the vicinity of the previously cloned flowering genes, E1 and E2. Using passport data associated with the collection sites of the landraces, 27 SNPs associated with adaptation to three bioclimatic variables (temperature, daylength, and precipitation) were identified. A series of candidate flowering genes were detected within linkage disequilibrium (LD) blocks surrounding 12 bioclimatic TASs. Nine of these TASs exhibit significant differences in flowering time between alleles within one or more of the three individual sub-populations. Signals of selection during domestication and/or subsequent landrace diversification and adaptation were detected at 38 of the 44 flowering and bioclimatic TASs. Hence, this study lays the groundwork to begin breeding for novel environments predicted to arise following global climate change.

Identification of the dwarf gene GmDW1 in soybean (Glycine max L.) by combining mapping-by-sequencing and linkage analysis.

KEY MESSAGE: GmDW1 encodes an ent-kaurene synthase (KS) acting at the early step of the biosynthesis pathway for gibberellins (GAs) and regulates the development of plant height in soybean. Plant height is an important component of plant architecture, and significantly affects crop breeding practices and yield. Here, we report the characterization of an EMS-induced dwarf mutant (dw) of the soybean cultivar Zhongpin 661 (ZDD23893). The dw mutant displayed reduced plant height and shortened internodes, both of which were mainly attributed to the longitudinally decreased cell length. The bioactive GA1 (gibberellin A1) and GA4 (gibberellin A4) were not detectable in the stem of dw, and the dwarf phenotype could be rescued by treatment with exogenous GA3. Genetic analysis showed that the dwarf trait of dw was controlled by a recessive nuclear gene. By combining linkage analysis and mapping-by-sequencing, we mapped the GmDW1 gene to an approximately 460-kb region on chromosome (Chr.) 8, containing 36 annotated genes in the reference Willliams 82 genome. Of these genes, we identified two nonsynonymous single nucleotide polymorphisms (SNPs) that are present in the encoding regions of Gmdw1 and Glyma.08G165100 in dw, respectively. However, only the SNP mutation (T>A) at nucleotide 1224 in Gmdw1 cosegregated with the dwarf phenotype. GmDW1 encodes an ent-kaurene synthase, and was expressed in various tissues including root, stem, and leaf. Further phenotypic analysis of the allelic variations in soybean accessions strongly indicated that GmDW1 is responsible for the dwarf phenotype in dw. Our results provide important information for improving our understanding of the genetics of soybean plant height and crop breeding.

Genome-wide association mapping of QTL underlying seed oil and protein contents of a diverse panel of soybean accessions.

To investigate the genetic basis of variation in oil and protein contents in soybean seeds, a diverse collection of 421 mainly Chinese soybean cultivars was genotyped using 1536 SNPs, mostly from candidate genes related to acyl-lipid metabolism and from regions harboring known QTL. Six significant associations were identified for each of seed oil and protein contents which individually explained 2.7-5.9% of the phenotypic variance. Six associations occurred in or near known QTL and the remaining are putative novel QTL. Ten significant associations influenced the oil content without decreasing protein content, and vice versa. One SNP was pleiotropic, with opposite effects on oil and protein contents. The genetic region covering Map-6076 and-6077 was shown to be involved in controlling oil content in soybean by integrating the results of association mapping with information on known QTL and tissue-specific expression data. This region was subject to strong selection during the genetic improvement of soybean. Our results not only confirm and refine the map positions of known QTL but also contribute to a further elucidation of the genetic architecture of protein and oil contents in soybean seeds by identifying new associations exhibiting pleiotropic effects on seed protein and oil contents.

Comparison of Genetic Diversity between Chinese and American Soybean (Glycine max (L.)) Accessions Revealed by High-Density SNPs.

Soybean is one of the most important economic crops for both China and the United States (US). The exchange of germplasm between these two countries has long been active. In order to investigate genetic relationships between Chinese and US soybean germplasm, 277 Chinese soybean accessions and 300 US soybean accessions from geographically diverse regions were analyzed using 5,361 SNP markers. The genetic diversity and the polymorphism information content (PIC) of the Chinese accessions was higher than that of the US accessions. Population structure analysis, principal component analysis, and cluster analysis all showed that the genetic basis of Chinese soybeans is distinct from that of the USA. The groupings observed in clustering analysis reflected the geographical origins of the accessions; this conclusion was validated with both genetic distance analysis and relative kinship analysis. FST-based and EigenGWAS statistical analysis revealed high genetic variation between the two subpopulations. Analysis of the 10 loci with the strongest selection signals showed that many loci were located in chromosome regions that have previously been identified as quantitative trait loci (QTL) associated with environmental-adaptation-related and yield-related traits. The pattern of diversity among the American and Chinese accessions should help breeders to select appropriate parental accessions to enhance the performance of future soybean cultivars.

Next-Generation Sequencing from Bulked-Segregant Analysis Accelerates the Simultaneous Identification of Two Qualitative Genes in Soybean.

Next-generation sequencing (NGS)-based bulked-segregant analysis (BSA) approaches have been proven successful for rapidly mapping genes in plant species. However, most such methods are based on mutants and usually only one gene controlling the mutant phenotype is identified. In this study, NGS-based BSA was employed to map simultaneously two qualitative genes controlling cotyledon color of seed in soybean. Yellow-cotyledon (YC) and green-cotyledon (GC) bulks from progenies of a biparental population (Zhonghuang 30 × Jiyu 102) were sequenced. The SNP-index of each SNP locus in YC and GC bulks was calculated and two genomic regions on chromosomes 1 and 11 harboring, respectively, loci qCC1 and qCC2 were identified by Δ(SNP-index) analysis. These two BSA-seq-derived loci were further validated with SSR markers and fine-mapped. qCC1 was mapped to a 30.7-kb region containing four annotated genes and qCC2 was mapped to a 67.7-kb region with nine genes. These two regions contained, respectively, genes D1 and D2, which had previously been identified by homology-based cloning as being associated with cotyledon color. Sequence analysis of the NGS data also identified a frameshift deletion in the coding region of D1. These results suggested that BSA-seq could accelerate the mapping of loci controlling qualitative traits, even if a trait is controlled by more than one locus.

Phenotypic characterization and genetic dissection of nine agronomic traits in Tokachi nagaha and its derived cultivars in soybean (Glycine max (L.) Merr.).

By using the soybean founder parent Tokachi nagaha and its 137 derived cultivars as materials, a genome-wide association analysis was performed to identify the single nucleotide polymorphisms (SNPs) underlying soybean yield and quality related traits at two planting densities. Results of ANOVA showed that genotype, environment, and genotype by environment interaction effects were all significant for each trait. The Tokachi nagaha-derived soybean population could be divided into two subpopulations based on molecular data, and accessions in each subpopulation were almost all from the same Chinese province. Relatedness was detected between pair-wise accessions within the population. Linkage disequilibrium was obvious and the level of intra-chromosome linkage disequilibrium was about 8370kb. A total of 40 SNPs with significant signal were detected and distributed across 18 chromosomes. Some SNP markers were located in or near regions where QTLs have been previously mapped by linkage analysis. Nineteen SNPs were identified both in low- and high- density planting treatments, indicating those loci were common and sTable Sixteen SNPs were co-associated with two or more different traits, suggesting that some of the QTLs/genes underlying those identified SNPs were likely to be pleiotropic.

Development and utilization of a new chemically-induced soybean library with a high mutation density .

Mutagenized populations have provided important materials for introducing variation and identifying gene function in plants. In this study, an ethyl methanesulfonate (EMS)-induced soybean (Glycine max) population, consisting of 21,600 independent M2 lines, was developed. Over 1,000 M4 (5) families, with diverse abnormal phenotypes for seed composition, seed shape, plant morphology and maturity that are stably expressed across different environments and generations were identified. Phenotypic analysis of the population led to the identification of a yellow pigmentation mutant, gyl, that displayed significantly decreased chlorophyll (Chl) content and abnormal chloroplast development. Sequence analysis showed that gyl is allelic to MinnGold, where a different single nucleotide polymorphism variation in the Mg-chelatase subunit gene (ChlI1a) results in golden yellow leaves. A cleaved amplified polymorphic sequence marker was developed and may be applied to marker-assisted selection for the golden yellow phenotype in soybean breeding. We show that the newly developed soybean EMS mutant population has potential for functional genomics research and genetic improvement in soybean.

Dissecting the Genetic Basis of Resistance to Soybean Cyst Nematode Combining Linkage and Association Mapping.

A set of 585 informative single-nucleotide polymorphism (SNP) loci was used to genotype both a panel of diverse accessions and a set of recombinant inbred lines (RILs) bred from the cross Zhongpin03-5373 (ZP; resistant to SCN) × Zhonghuang13 (ZH; susceptible). The SNP loci are mostly sited within genic sequence in regions of the soybean [ (L.) Merr.] genome thought to harbor genes determining resistance to the soybean cyst nematode (SCN, Ichinohe). The three strongest quantitative trait nucleotides (QTNs) identified by association mapping (AM) involved the genes (a component of the multigene locus ), and (an paralog), as well as some other loci with smaller effects. The linkage mapping (LM) analysis performed using the RILs revealed two putative quantitative trait loci (QTL): one mapping to and the other to an paralog; both of these loci were also identified by AM. The former locus explained 25.5% of the phenotypic variance for SCN resistance and the latter 5.8%. In combination, the two major loci acted nonadditively, providing a high level of SCN resistance.

GmSALT3, Which Confers Improved Soybean Salt Tolerance in the Field, Increases Leaf Cl- Exclusion Prior to Na+ Exclusion But Does Not Improve Early Vigor under Salinity.

Soil salinity reduces soybean growth and yield. The recently identified GmSALT3 (Glycine max salt Tolerance-associated gene on chromosome 3) has the potential to improve soybean yields in salinized conditions. Here we evaluate the impact of GmSALT3 on soybean performance under saline or non-saline conditions. Three sets of near isogenic lines (NILs), with genetic similarity of 95.6-99.3% between each pair of NIL-T and NIL-S, were generated from a cross between two varieties 85-140 (salt-sensitive, S) and Tiefeng 8 (salt-tolerant, T) by using marker-assisted selection. Each NIL-T; 782-T, 820-T and 860-T, contained a common ~1000 kb fragment on chromosome 3 where GmSALT3 was located. We show that GmSALT3 does not contribute to an improvement in seedling emergence rate or early vigor under salt stress. However, when 12-day-old seedlings were exposed to NaCl stress, the NIL-T lines accumulated significantly less leaf Na+ compared with their corresponding NIL-S, while no significant difference of K+ concentration was observed between NIL-T and NIL-S; the magnitude of Na+ accumulation within each NIL-T set was influenced by the different genetic backgrounds. In addition, NIL-T lines accumulated less Cl- in the leaf and more in the root prior to any difference in Na+; in the field they accumulated less pod wall Cl- than the corresponding NIL-S lines. Under non-saline field conditions, no significant differences were observed for yield related traits within each pair of NIL-T and NIL-S lines, indicating there was no yield penalty for having the GmSALT3 gene. In contrast, under saline field conditions the NIL-T lines had significantly greater plant seed weight and 100-seed weight than the corresponding NIL-S lines, meaning GmSALT3 conferred a yield advantage to soybean plants in salinized fields. Our results indicated that GmSALT3 mediated regulation of both Na+ and Cl- accumulation in soybean, and contributes to improved soybean yield through maintaining a higher seed weight under saline stress.

Potential of marker selection to increase prediction accuracy of genomic selection in soybean (Glycine max L.).

Genomic selection is a promising molecular breeding strategy enhancing genetic gain per unit time. The objectives of our study were to (1) explore the prediction accuracy of genomic selection for plant height and yield per plant in soybean [Glycine max (L.) Merr.], (2) discuss the relationship between prediction accuracy and numbers of markers, and (3) evaluate the effect of marker preselection based on different methods on the prediction accuracy. Our study is based on a population of 235 soybean varieties which were evaluated for plant height and yield per plant at multiple locations and genotyped by 5361 single nucleotide polymorphism markers. We applied ridge regression best linear unbiased prediction coupled with fivefold cross-validations and evaluated three strategies of marker preselection. For plant height, marker density and marker preselection procedure impacted prediction accuracy only marginally. In contrast, for grain yield, prediction accuracy based on markers selected with a haplotype block analyses-based approach increased by approximately 4 % compared with random or equidistant marker sampling. Thus, applying marker preselection based on haplotype blocks is an interesting option for a cost-efficient implementation of genomic selection for grain yield in soybean breeding.

Identification and Validation of Loci Governing Seed Coat Color by Combining Association Mapping and Bulk Segregation Analysis in Soybean.

Soybean seed coat exists in a range of colors from yellow, green, brown, black, to bicolor. Classical genetic analysis suggested that soybean seed color was a moderately complex trait controlled by multi-loci. However, only a couple of loci could be detected using a single biparental segregating population. In this study, a combination of association mapping and bulk segregation analysis was employed to identify genes/loci governing this trait in soybean. A total of 14 loci, including nine novel and five previously reported ones, were identified using 176,065 coding SNPs selected from entire SNP dataset among 56 soybean accessions. Four of these loci were confirmed and further mapped using a biparental population developed from the cross between ZP95-5383 (yellow seed color) and NY279 (brown seed color), in which different seed coat colors were further dissected into simple trait pairs (green/yellow, green/black, green/brown, yellow/black, yellow/brown, and black/brown) by continuously developing residual heterozygous lines. By genotyping entire F2 population using flanking markers located in fine-mapping regions, the genetic basis of seed coat color was fully dissected and these four loci could explain all variations of seed colors in this population. These findings will be useful for map-based cloning of genes as well as marker-assisted breeding in soybean. This work also provides an alternative strategy for systematically isolating genes controlling relative complex trait by association analysis followed by biparental mapping.

Phenotypic Characterization and Genetic Dissection of Growth Period Traits in Soybean (Glycine max) Using Association Mapping.

The growth period traits are important traits that affect soybean yield. The insights into the genetic basis of growth period traits can provide theoretical basis for cultivated area division, rational distribution, and molecular breeding for soybean varieties. In this study, genome-wide association analysis (GWAS) was exploited to detect the quantitative trait loci (QTL) for number of days to flowering (ETF), number of days from flowering to maturity (FTM), and number of days to maturity (ETM) using 4032 single nucleotide polymorphism (SNP) markers with 146 cultivars mainly from Northeast China. Results showed that abundant phenotypic variation was presented in the population, and variation explained by genotype, environment, and genotype by environment interaction were all significant for each trait. The whole accessions could be clearly clustered into two subpopulations based on their genetic relatedness, and accessions in the same group were almost from the same province. GWAS based on the unified mixed model identified 19 significant SNPs distributed on 11 soybean chromosomes, 12 of which can be consistently detected in both planting densities, and 5 of which were pleotropic QTL. Of 19 SNPs, 7 SNPs located in or close to the previously reported QTL or genes controlling growth period traits. The QTL identified with high resolution in this study will enrich our genomic understanding of growth period traits and could then be explored as genetic markers to be used in genomic applications in soybean breeding.

Targeted association mapping demonstrating the complex molecular genetics of fatty acid formation in soybean.

BACKGROUND: The relative abundance of five dominant fatty acids (FAs) (palmitic, stearic, oleic, linoleic and linolenic acids) is a major factor determining seed quality in soybean. METHODS: To clarify the currently poorly understood genetic architecture of FAs in soybean, targeted association analysis was conducted in 421 diverse accessions phenotyped in three environments and genotyped using 1536 pre-selected SNPs. RESULTS: The population of 421 soybean accessions displayed significant genetic variation for each FA. Analysis of the molecular data revealed three subpopulations, which reflected a trend depending on latitude of cultivation. A total of 37 significant (p < 0.01) associations with FAs were identified by association mapping analysis. These associations were represented by 33 SNPs (occurring in 32 annotated genes); another four SNPs had a significant association with two different FAs due to pleiotropic interactions. The most significant associations were cross-verified by known genes/QTL or consistency across cultivation year and subpopulations. CONCLUSION: The detected marker-trait associations represent a first important step towards the implementation of molecular-marker-based selection of FA composition with the potential to substantially improve the seed quality of soybean with benefits for human health and for food processing.