Soybean Accessions Research Articles

Natural variation of domestication-related genes contributed to latitudinal expansion and adaptation in soybean

Soybean is a major source of protein and edible oil worldwide. Originating from the Huang-Huai-Hai region, which has a temperate climate, soybean has adapted to a wide latitudinal gradient across China. However, the genetic mechanisms responsible for the widespread latitudinal adaptation in soybean, as well as the genetic basis, adaptive differentiation, and evolutionary implications of theses natural alleles, are currently lacking in comprehensive understanding. In this study, we examined the genetic variations of fourteen major gene loci controlling flowering and maturity in 103 wild species, 1048 landraces, and 1747 cultivated species. We found that E1, E3, FT2a, J, Tof11, Tof16, and Tof18 were favoured during soybean improvement and selection, which explained 75.5% of the flowering time phenotypic variation. These genetic variation was significantly associated with differences in latitude via the LFMM algorithm. Haplotype network and geographic distribution analysis suggested that gene combinations were associated with flowering time diversity contributed to the expansion of soybean, with more HapA clustering together when soybean moved to latitudes beyond 35°N. The geographical evolution model was developed to accurately predict the suitable planting zone for soybean varieties. Collectively, by integrating knowledge from genomics and haplotype classification, it was revealed that distinct gene combinations improve the adaptation of cultivated soybeans to different latitudes. This study provides insight into the genetic basis underlying the environmental adaptation of soybean accessions, which could contribute to a better understanding of the domestication history of soybean and facilitate soybean climate-smart molecular breeding for various environments.

Cold tolerance SNPs and candidate gene mining in the soybean germination stage based on genome-wide association analysis.

Three QTLs associated with low-temperature tolerance were identified by genome-wide association analysis, and 15 candidate genes were identified by haplotype analysis and gene expression analyses. Low temperature is a critical factor affecting the geographical distribution, growth, development, and yield of soybeans, with cold stress during seed germination leading to substantial productivity loss. In this study, an association panel comprising 260 soybean accessions was evaluated for four germination traits and four cold tolerance index traits, revealing extensive variation in cold tolerance. Genome-wide association study (GWAS) identified 10 quantitative trait nucleotides (QTNs) associated with cold tolerance, utilizing 30,799 single nucleotide polymorphisms (SNPs) and four GWAS models. Linkage disequilibrium (LD)analysis positioned these QTNs within three cold-tolerance quantitative trait loci (QTL) and, with QTL19-1, was positioned by three multi-locus models, underscoring its importance as a key QTL. Integrative haplotype analysis, supplemented by transcriptome analysis, uncovered 15 candidate genes. The haplotypes within the genes Glyma.18G044200, Glyma.18G044300, Glyma.18G044900, Glyma.18G045100, Glyma.19G222500, and Glyma.19G222600 exhibited significant phenotypic variations, with differential expression in materials with varying cold tolerance. The QTNs and candidate genes identified in this study offer substantial potential for marker-assisted selection and gene editing in breeding cold-tolerant soybeans, providing valuable insights into the genetic mechanisms underlying cold tolerance during soybean germination.

Effect of Origin, Seed Coat Color, and Maturity Group on Seed Isoflavones in Diverse Soybean Germplasm.

Soybeans are grown worldwide owing to their protein, oil, and beneficial bioactive compounds. Genetic and environmental factors influence soybean seed isoflavones. In the present study, we profiled the seed isoflavones in world diverse soybean germplasm grown in two locations over two years in China. Significant differences (p < 0.001) were observed between the accessions, accession origins, seed coat colors, and maturity groups for individual and total isoflavone (TIF) content. TIF content of the soybean accessions ranged from 677.25 μg g-1 to 5823.29 μg g-1, representing an 8-fold difference. USA soybean accessions showed the highest mean TIF content (3263.07 μg g-1), followed by Japan (2521.26 μg g-1). Soybean with black seed coat showed the highest (3236.08 μg g-1) TIF concentration. Furthermore, isoflavone levels were significantly higher in late-maturity groups. Correlation analysis revealed significant positive associations between individual and TIF content. Malonyldaidzin and malonylgenistin showed higher correlations with TIF content (r = 0.92 and r = 0.94, respectively). The soybean accessions identified as having high and stable TIF content can be utilized in the food and pharmaceutical industries and breeding programs to develop soybean varieties with enhanced isoflavone content.

Research advances on the hard seededness trait of soybean and the underlying regulatory mechanisms.

Soybean is one of the world's most economically significant crops and is widely utilized as an essential source of vegetable protein and edible oil. Cultivated soybean is domesticated from its annual counterpart, wild soybean, which is considered valuable germplasm for soybean breeding. However, wild soybean accessions generally produce seeds with impermeable coats, a trait known as hard seededness (HS), which is beneficial for long-term seed survival but is undesirable for the uniform water absorption and germination of seeds, thus limiting the utilization of wild soybeans in breeding. In addition, moderate HS can isolate the embryo from the surrounding environment and is thus beneficial for long-term seed storage and germplasm preservation. The HS trait is primarily associated with the structure and chemical composition of the seed coat. Moreover, its development is also influenced by various environmental conditions, such as water and temperature. Genetic analysis has revealed that HS of soybean is a complex quantitative trait controlled by multiple genes or minor quantitative trait loci (QTL), with many QTLs and several causal genes currently identified. Investigating the physiological and molecular mechanisms underlying this trait is crucial for soybean breeding, production, and food processing. For this article, the literature was reviewed and condensed to create a well-rounded picture of the current understanding of internal and external factors, QTLs, causal genes, and the regulatory mechanisms related to the HS of soybean, with the aim of providing reference for future research and utilization of this trait.

Whole-genome sequencing analysis of soybean diversity across different countries and selection signature of Korean soybean accession.

Soybean is an important agricultural crop known for its high protein and oil content, contributing to essential nutritional and health benefits for humans. Domesticated in China over 5,000 years ago, soybean has since adapted to diverse environments and spread worldwide. This study aimed to investigate the genomic characteristics and population structures of 2,317 publicly available soybean whole-genome sequences from diverse geographical regions, including China, Korea, Japan, Europe, North America, and South America. We used large-scale whole-genome sequencing data to perform high-resolution analyses to reveal the genetic characteristics of soybean accessions. Soybean accessions from China and Korea exhibited landrace characteristics, indicating higher genetic diversity and adaptation to local environments. On the other hand, soybean accessions from Japan, the European Union, and South America were found to have low genetic diversity due to artificial selection and breeding for agronomic traits. We also identified key variants and genes associated with the ability to adapt to different environments. In Korean soybean accessions, we observed strong selection signals for isoflavone synthesis, an adaptive trait critical for improving soybean adaptability, survival, and reproductive success by mitigating environmental stress. Identifying specific genomic regions showing unique patterns of selective sweeps for genes such as HIDH, CYP73A11, IFS1, and CYP81E11 associated with isoflavone synthesis provided valuable insights into potential adaptation mechanisms. Our research has significantly improved our understanding of soybean diversity at the genetic level. We have identified key genetic variants and genes influencing adaptability, laying the foundation for future advances in genomics-based breeding programs and crop improvement efforts.

Correction: Park et al. Identification of a Novel KTi-1 Allele Associated with Reduced Trypsin Inhibitor Activity in Soybean Accessions. Agriculture 2023, 13, 2070

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Genome-Wide Association Study and Candidate Gene Mining of Seed Size Traits in Soybean

Seed size traits, including seed length (SL), seed width (SW), and seed thickness (ST), are crucial appearance parameters that determine soybean seed weight, yield, and ultimate utilization. However, there is still a large gap in the understanding of the genetic mechanism of these traits. Here, 281 soybeans were utilized to analyze the genetic architecture of seed size traits in different years through multiple (single-locus and multi-locus) genome-wide association study (GWAS) models, and candidate genes were predicted by integrating information on gene function and transcriptome sequencing data. As a result, two, seven, and three stable quantitative trait nucleotides (QTNs) controlling SL, SW, and ST were detected in multiple environments using the single-locus GWAS model, and concurrently detected by the results of the multi-locus GWAS models. These stable QTNs are located on 10 linkage disequilibrium blocks, with single genome regions ranging in size from 20 to 440 kb, and can serve as the major loci controlling soybean seed size. Furthermore, by combining gene functional annotation and transcriptome sequencing data of seeds at different developmental stages from two extreme soybean accessions, nine candidate genes, including Glyma.05G038000, Glyma.05G244100, Glyma.05G246900, Glyma.07G070200, Glyma.11G010000, Glyma.11G012400, Glyma.17G165500, Glyma.17G166500, and Glyma.20G012600 within the major loci that may regulate soybean seed size, were mined. Overall, these findings offer valuable insights for molecular improvement breeding as well as gene functional studies to unravel the mechanism of soybean seed size.

Genome-Wide Association Analysis of Yield-Related Traits and Candidate Genes in Vegetable Soybean.

Owing to the rising demand for vegetable soybean products, there is an increasing need for high-yield soybean varieties. However, the complex correlation patterns among quantitative traits with genetic architecture pose a challenge for improving vegetable soybean through breeding. Herein, a genome-wide association study (GWAS) was applied to 6 yield-related traits in 188 vegetable soybean accessions. Using a BLINK model, a total of 116 single nucleotide polymorphisms (SNPs) were identified for plant height, pod length, pod number, pod thickness, pod width, and fresh pod weight. Furthermore, a total of 220 genes were found in the 200 kb upstream and downstream regions of significant SNPs, including 11 genes encoding functional proteins. Among them, four candidate genes, Glyma.13G109100, Glyma.03G183200, Glyma.09G102200, and Glyma.09G102300 were analyzed for significant haplotype variations and to be in LD block, which encode MYB-related transcription factor, auxin-responsive protein, F-box protein, and CYP450, respectively. The relative expression of candidate genes in V030 and V071 vegetable soybean (for the plant height, pod number, and fresh pod weight of V030 were lower than those of the V071 strains) was significantly different, and these genes could be involved in plant growth and development via various pathways. Altogether, we identified four candidate genes for pod yield and plant height from vegetable soybean germplasm. This study provides insights into the genomic basis for improving soybean and crucial genomic resources that can facilitate genome-assisted high-yielding vegetable soybean breeding.

Effects of fast and slow-wilting soybean genotypes on fall armyworm (Spodoptera frugiperda) growth and development

ABSTRACT Soybean (Glycine max) is the most important plant protein source, and Fall Armyworm (FAW, Spodoptera frugiperda) is considered a major pest. This study aimed to examine the impact of FAW feeding on soybean accessions that vary in their water use efficiency (WUE) traits, by examining FAW growth and life history parameters along with plant growth response to pest damage. Soybean accessions were grown in a greenhouse and exposed to FAW larval feeding for 48 h at three different soybean growth stages: V3, R3, and R6. The growth and development of the FAW and soybeans were monitored. Results showed that faster wilting soybean accessions grow taller and have more leaves than slower wilting accessions, but yield was higher in slower wilting soybean accessions. FAW experienced the highest mortality on mid-stage (R3) soybean plants, but they gained the least mass on early stage (V3) soybean plants. These results can assist in better understanding plant insect-interactions at different life stages in both soybean and FAW with implications for management.

Identification of soybean mosaic virus strain SC7 resistance loci and candidate genes in soybean [Glycine max (L.) Merr.

Soybean [Glycine max (L.) Merr.] is an important legume crop worldwide, which provides abundant plant protein and oil for human beings. Soybean mosaic virus (SMV) can cause serious damage to the yield and quality of soybean, but it is difficult to control SMV with chemicals, breeding SMV-resistant varieties has become the most effective way to control the disease. Therefore, it is important to identify SMV resistance genes from soybean resources and apply them to soybean breeding. In this study, the disease rates (DRs) of 219 soybean accessions to SMV strain SC7 in two environments were investigated. A high-density NJAU 355K SoySNP array was used for genome-wide association study (GWAS) of DR. A 274kb region on chromosome 15 (1,110,567bp to 1,384,173bp) was repeatedly detected in two environments. Six new significant single nucleotide polymorphisms (SNPs) on chromosome 15 were identified. Four of these six SNPs were located within two candidate genes, Glyma.15G015700 and Glyma.15G015800. The elite haplotype Glyma.15G015700Hap I with low DR exhibited strong resistance to SC7. The expression of Glyma.15G015700 in the SMV-resistant accession increased significantly after inoculation with SC7. Furthermore, most of the proteins predicted to interact with Glyma.15G015700 are heat shock proteins, which have been shown to be related to disease resistance. In summary, new SMV resistance loci and a new candidate gene, Glyma.15G015700, were identified and might be utilized in further soybean disease resistance breeding.

Developing an SNP dataset for efficiently evaluating soybean germplasm resources using the genome sequencing data of 3,661 soybean accessions

BackgroundSingle nucleotide polymorphism (SNP) markers play significant roles in accelerating breeding and basic crop research. Several soybean SNP panels have been developed. However, there is still a lack of SNP panels for differentiating between wild and cultivated populations, as well as for detecting polymorphisms within both wild and cultivated populations.ResultsThis study utilized publicly available resequencing data from over 3,000 soybean accessions to identify differentiating and highly conserved SNP and insertion/deletion (InDel) markers between wild and cultivated soybean populations. Additionally, a naturally occurring mutant gene library was constructed by analyzing large-effect SNPs and InDels in the population.ConclusionThe markers obtained in this study are associated with numerous genes governing agronomic traits, thus facilitating the evaluation of soybean germplasms and the efficient differentiation between wild and cultivated soybeans. The natural mutant gene library permits the quick identification of individuals with natural mutations in functional genes, providing convenience for accelerating soybean breeding using reverse genetics.

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

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. 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. 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. 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.

Deciphering genetic factors contributing to enhanced resistance against Cercospora leaf blight in soybean (Glycine max L.) using GWAS analysis.

Cercospora leaf blight (CLB), caused by Cercospora cf. flagellaris, C. kikuchii, and C. cf. sigesbeckiae, is a significant soybean [Glycine max (L.) Merr.] disease in regions with hot and humid conditions causing yield loss in the United States and Canada. There is limited information regarding resistant soybean cultivars, and there have been marginal efforts to identify the genomic regions underlying resistance to CLB. A Genome-Wide Association Study was conducted using a diverse panel of 460 soybean accessions from maturity groups III to VII to identify the genomic regions associated to the CLB disease. These accessions were evaluated for CLB in different regions of the southeastern United States over 3years. In total, the study identified 99 Single Nucleotide Polymorphism (SNPs) associated with the disease severity and 85 SNPs associated with disease incidence. Across multiple environments, 47 disease severity SNPs and 23 incidence SNPs were common. Candidate genes within 10kb of these SNPs were involved in biotic and abiotic stress pathways. This information will contribute to the development of resistant soybean germplasm. Further research is warranted to study the effect of pyramiding desirable genomic regions and investigate the role of identified genes in soybean CLB resistance.

Identification of QTNs, QTN-by-environment interactions, and their candidate genes for salt tolerance related traits in soybean

BackgroundSalt stress significantly reduces soybean yield. To improve salt tolerance in soybean, it is important to mine the genes associated with salt tolerance traits.ResultsSalt tolerance traits of 286 soybean accessions were measured four times between 2009 and 2015. The results were associated with 740,754 single nucleotide polymorphisms (SNPs) to identify quantitative trait nucleotides (QTNs) and QTN-by-environment interactions (QEIs) using three-variance-component multi-locus random-SNP-effect mixed linear model (3VmrMLM). As a result, eight salt tolerance genes (GmCHX1, GsPRX9, Gm5PTase8, GmWRKY, GmCHX20a, GmNHX1, GmSK1, and GmLEA2-1) near 179 significant and 79 suggested QTNs and two salt tolerance genes (GmWRKY49 and GmSK1) near 45 significant and 14 suggested QEIs were associated with salt tolerance index traits in previous studies. Six candidate genes and three gene-by-environment interactions (GEIs) were predicted to be associated with these index traits. Analysis of four salt tolerance related traits under control and salt treatments revealed six genes associated with salt tolerance (GmHDA13, GmPHO1, GmERF5, GmNAC06, GmbZIP132, and GmHsp90s) around 166 QEIs were verified in previous studies. Five candidate GEIs were confirmed to be associated with salt stress by at least one haplotype analysis. The elite molecular modules of seven candidate genes with selection signs were extracted from wild soybean, and these genes could be applied to soybean molecular breeding. Two of these genes, Glyma06g04840 and Glyma07g18150, were confirmed by qRT-PCR and are expected to be key players in responding to salt stress.ConclusionsAround the QTNs and QEIs identified in this study, 16 known genes, 6 candidate genes, and 8 candidate GEIs were found to be associated with soybean salt tolerance, of which Glyma07g18150 was further confirmed by qRT-PCR.

GmAP1d regulates flowering time under long-day photoperiods in soybean

Flowering time is important for adaptation of soybean (Glycine max) to different environments. Here, we conducted a genome-wide association study of flowering time using a panel of 1490 cultivated soybean accessions. We identified three strong signals at the qFT02-2 locus (Chr02: 12037319–12238569), which were associated with flowering time in three environments: Gongzhuling, Mengcheng, and Nanchang. By analyzing linkage disequilibrium, gene expression patterns, gene annotation, and the diversity of variants, we identified an AP1 homolog as the candidate gene for the qFT02-2 locus, which we named GmAP1d. Only one nonsynonymous polymorphism existed among 1490 soybean accessions at position Chr02:12087053. Accessions carrying the Chr02:12087053-T allele flowered significantly earlier than those carrying the Chr02:12087053-A allele. Thus, we developed a cleaved amplified polymorphic sequence (CAPS) marker for the SNP at Chr02:12087053, which is suitable for marker-assisted breeding of flowering time. Knockout of GmAP1d in the ‘Williams 82’ background by gene editing promoted flowering under long-day conditions, confirming that GmAP1d is the causal gene for qFT02-2. An analysis of the region surrounding GmAP1d revealed that GmAP1d was artificially selected during the genetic improvement of soybean. Through stepwise selection, the proportion of modern cultivars carrying the Chr02:12087053-T allele has increased, and this allele has become nearly fixed (95%) in northern China. These findings provide a theoretical basis for better understanding the molecular regulatory mechanism of flowering time in soybean and a target gene that can be used for breeding modern soybean cultivars adapted to different latitudes.

GmTCP40 Promotes Soybean Flowering under Long-Day Conditions by Binding to the GmAP1a Promoter and Upregulating Its Expression.

Soybean [Glycine max (L.) Merr.] is a short-day (SD) plant that is sensitive to photoperiod, which influences flowering, maturity, and even adaptation. TEOSINTE-BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) transcription factors have been shown to regulate photoperiodic flowering. However, the roles of TCPs in SD plants such as soybean, rice, and maize remain largely unknown. In this study, we cloned the GmTCP40 gene from soybean and investigated its expression pattern and function. Compared with wild-type (WT) plants, GmTCP40-overexpression plants flowered earlier under long-day (LD) conditions but not under SD conditions. Consistent with this, the overexpression lines showed upregulation of the flowering-related genes GmFT2a, GmFT2b, GmFT5a, GmFT6, GmAP1a, GmAP1b, GmAP1c, GmSOC1a, GmSOC1b, GmFULa, and GmAG under LD conditions. Further investigation revealed that GmTCP40 binds to the GmAP1a promoter and promotes its expression. Analysis of the GmTCP40 haplotypes and phenotypes of soybean accessions demonstrated that one GmTCP40 haplotype (Hap6) may contribute to delayed flowering at low latitudes. Taken together, our findings provide preliminary insights into the regulation of flowering time by GmTCP40 while laying a foundation for future research on other members of the GmTCP family and for efforts to enhance soybean adaptability.

Genetic dissection of ten photosynthesis-related traits based on InDel- and SNP-GWAS in soybean.

A total of 416 InDels and 112 SNPs were significantly associated with soybean photosynthesis-related traits. GmIWS1 and GmCDC48 might be related to chlorophyll fluorescence and gas-exchange parameters, respectively. Photosynthesis is one of the main factors determining crop yield. A better understanding of the genetic architecture for photosynthesis is of great significance for soybean yield improvement. Our previous studies identified 5,410,112 single nucleotide polymorphisms (SNPs) from the resequencing data of 219 natural soybean accessions. Here, we identified 634,106 insertions and deletions (InDels) from these 219 accessions and used these InDel variations to perform principal component and linkage disequilibrium analysis of this population. The genome-wide association study (GWAS) were conducted on six chlorophyll fluorescence parameters (chlorophyll content, light energy absorbed per reaction center, quantum yield for electron transport, probability that a trapped exciton moves an electron into the electron transport chain beyond primary quinone acceptor, maximum quantum yield of photosystem II primary photochemistry in the dark-adapted state, performance index on absorption basis) and four gas-exchange parameters (intercellular carbon dioxide concentration, stomatal conductance, net photosynthesis rate, transpiration rate) and revealed 416 significant InDels and 112 significant SNPs. Based on GWAS results, GmIWS1 (encoding a transcription elongation factor) and GmCDC48 (encoding a cell division cycle protein) with the highest expression in the mapping region were determined as the candidate genes responsible for chlorophyll fluorescence and gas-exchange parameters, respectively. Further identification of favorable haplotypes with higher photosynthesis, seed weight and seed yield were carried out for GmIWS1 and GmCDC48. Overall, this study revealed the natural variations and candidate genes underlying the photosynthesis-related traits based on abundant phenotypic and genetic data, providing valuable insights into the genetic mechanisms controlling photosynthesis and yield in soybean.

The Soybean Rpp3 Gene Encodes a TIR-NBS-LRR Protein that Confers Resistance to Phakopsora pachyrhizi.

Soybean rust is an economically significant disease caused by the fungus Phakopsora pachyrhizi that negatively impacts soybean (Glycine max [L.] Merr.) production throughout the world. Susceptible plants infected by P. pachyrhizi develop tan-colored lesions on the leaf surface that give rise to funnel-shaped uredinia as the disease progresses. While most soybean germplasm is susceptible, seven genetic loci (Rpp1 to Rpp7) that provide race-specific resistance to P. pachyrhizi (Rpp) have been identified. Rpp3 was first discovered and characterized in the soybean accession PI 462312 (Ankur), and it was also determined to be one of two Rpp genes present in PI 506764 (Hyuuga). Genetic crosses with PI 506764 were later used to fine-map the Rpp3 locus to a 371-kb region on chromosome 6. The corresponding region in the susceptible Williams 82 (Wm82) reference genome contains several homologous nucleotide binding site-leucine rich repeat (NBS-LRR) genes. To identify Rpp3, we designed oligonucleotide primers to amplify Rpp3 candidate (Rpp3C) NBS-LRR genes at this locus from PI 462312, PI 506764, and Wm82 using polymerase chain reaction (PCR). Five Rpp3C genes were identified in both Rpp3-resistant soybean lines, and co-silencing these genes compromised resistance to P. pachyrhizi. Gene expression analysis and sequence comparisons of the Rpp3C genes in PI 462312 and PI 506764 suggest that a single candidate gene, Rpp3C3, is responsible for Rpp3-mediated resistance. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2024.

Genome-wide transcriptome analysis reveals key regulatory networks and genes involved in the determination of seed hardness in vegetable soybean.

Seed hardness is an important quality trait of vegetable soybean. To determine the factors underlying seed hardness, two landraces with contrasting seed hardness, Niumaohuang (low seed hardness) and Pixiansilicao (high seed hardness), were selected from 216 soybean accessions originating from 26 provinces in China. The contents of the main components in vegetable soybean seeds such as water, soluble sugar, starch, protein and oil were measured, and transcriptome analyses performed during five stages of seed developmental. Transcriptome analysis indicates that during the middle and late stages of seed development, a large number of genes involved in the synthesis or degradation of starch, storage protein, and fatty acids were differentially expressed, leading to differences in the accumulation of stored substances during seed maturation among Niumaohuang and Pixiansilicao. The activity of cell proliferation and the formation of cell walls in the middle and late stages of seed development may also affect the hardness of seeds to a certain extent. In addition, weighted gene co-expression network analysis (WGCNA) was undertaken to identify co-expressed gene modules and hub genes that regulate seed hardness. Overexpression of a candidate seed hardness regulatory hub gene, GmSWEET2, resulted in increased seed hardness. In this study, the important role of GmSWEET2 in regulating the hardness of vegetable soybean seeds was verified and numerous potential key regulators controlling seed hardness and the proportion of seed components were identified, laying the groundwork for improving the texture of vegetable soybean.

Identification of superior and rare haplotypes to optimize branch number in soybean

Key messageUsing the integrated approach in the present study, we identified eleven significant SNPs, seven stable QTLs and 20 candidate genes associated with branch number in soybean.Branch number is a key yield-related quantitative trait that directly affects the number of pods and seeds per soybean plant. In this study, an integrated approach with a genome-wide association study (GWAS) and haplotype and candidate gene analyses was used to determine the detailed genetic basis of branch number across a diverse set of soybean accessions. The GWAS revealed a total of eleven SNPs significantly associated with branch number across three environments using the five GWAS models. Based on the consistency of the SNP detection in multiple GWAS models and environments, seven genomic regions within the physical distance of ± 202.4 kb were delineated as stable QTLs. Of these QTLs, six QTLs were novel, viz., qBN7, qBN13, qBN16, qBN18, qBN19 and qBN20, whereas the remaining one, viz., qBN12, has been previously reported. Moreover, 11 haplotype blocks, viz., Hap4, Hap7, Hap12, Hap13A, Hap13B, Hap16, Hap17, Hap18, Hap19A, Hap19B and Hap20, were identified on nine different chromosomes. Haplotype allele number across the identified haplotype blocks varies from two to five, and different branch number phenotype is regulated by these alleles ranging from the lowest to highest through intermediate branching. Furthermore, 20 genes were identified underlying the genomic region of ± 202.4 kb of the identified SNPs as putative candidates; and six of them showed significant differential expression patterns among the soybean cultivars possessing contrasting branch number, which might be the potential candidates regulating branch number in soybean. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable branch numbers.