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Introduction Legume crops are an important source of protein and oil for human health and in fixing atmospheric N2 for soil enrichment. With an objective to accelerate much-needed genetic analyses and breeding applications, draft genome assemblies were generated in several legume crops; many of them are not high quality because they are mainly based on short reads. However, the superior quality of genome assembly is crucial for a detailed understanding of genomic architecture, genome evolution, and crop improvement. Objectives Present study was undertaken with an objective of developing improved chromosome-length genome assemblies in six different legumes followed by their systematic investigation to unravel different aspects of genome organization and legume evolution. Methods We employed in situ Hi-C data to improve the existing draft genomes and performed different evolutionary and comparative analyses using improved genome assemblies. Results We have developed chromosome-length genome assemblies in chickpea, pigeonpea, soybean, subterranean clover, and two wild progenitor species of cultivated groundnut (A. duranensis and A. ipaensis). A comprehensive comparative analysis of these genome assemblies offered improved insights into various evolutionary events that shaped the present-day legume species. We highlighted the expansion of gene families contributing to unique traits such as nodulation in legumes, gravitropism in groundnut, and oil biosynthesis in oilseed legume crops such as groundnut and soybean. As examples, we have demonstrated the utility of improved genome assemblies for enhancing the resolution of “QTL-hotspot” identification for drought tolerance in chickpea and marker-trait associations for agronomic traits in pigeonpea through genome-wide association study. Genomic resources developed in this study are publicly available through an online repository, ‘Legumepedia’. Conclusion This study reports chromosome-length genome assemblies of six legume species and demonstrates the utility of these assemblies in crop improvement. The genomic resources developed here will have significant role in accelerating genetic improvement applications of legume crops.

Plant parasitic nematodes are a major yield-limiting factor of soybean in the United States and Canada. It has been indicated that soybean cyst nematode (SCN; Heterodera glycines Ichinohe) and reniform nematode (RN; Rotylenchulus reniformis Linford and Oliveira) resistance could be genetically related. For many years, fragmentary data have shown this relationship. This report evaluates RN reproduction on 418 plant introductions (PIs) selected from the U.S. Department of Agriculture Soybean Germplasm Collection with reported SCN resistance. The germplasm was divided into two tests of 214 PIs reported as resistant and 204 PIs reported as moderately resistant to SCN. The defining and reporting of RN resistance changed several times in the last 30 years, causing inconsistencies in RN resistance classification among multiple experiments. Comparison of four RN resistance classification methods was performed: (i) ≤10% as compared with the susceptible check, (ii) using normalized reproduction index (RI) values, and using (iii) transformed data log10(x), and (iv) transformed data log10(x + 1) in an optimal univariate k-means clustering analysis. The method of transformed data log10(x) was selected as the most accurate for classification of RN resistance. Among 418 PIs with reported SCN resistance, the log10(x) method grouped 59 PIs (15%) as resistant and 130 PIs (31%) as moderately resistant to RN. Genotyping of a subset of the most resistant PIs to both nematode species revealed their strong correlation with rhg1-a allele. This research identified genotypes with resistance to two nematode species and potential new sources of RN resistance that could be valuable to breeders in developing resistant cultivars.

Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources1. So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level2. Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic diversity across cultivated chickpea and its wild progenitor accessions. A divergence tree using genes present in around 80% of individuals in one species allowed us to estimate the divergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic diversity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic diversity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively., Whole-genome sequencing of 3,171 cultivated and 195 wild chickpea accessions is used to construct a chickpea pan-genome, providing insight into chickpea evolution and enabling breeding strategies that could improve crop productivity.

Genetic improvement of soybean, one of the major crops providing edible oil and protein-rich food, is important to ensure balanced nutrition for the growing world population. To make soybean cultiv...

Soybean acyl-ACP thioesterase gene family have been characterized; GmFATA1A mutants were discovered to confer high oleic acid, while GmFATB mutants presented low palmitic and high oleic acid seed content. Soybean oil stability and quality are primarily determined by the relative proportions of saturated versus unsaturated fatty acids. Commodity soybean typically contains 11% palmitic acid, as the primary saturated fatty acids. Reducing palmitic acid content is the principal approach to minimize the levels of saturated fatty acids in soybean. Though high palmitic acid enhances oxidative stability of soybean oil, it is negatively correlated with oil and oleic acid content and can cause coronary heart diseases for humans. For plants, acyl–acyl carrier protein (ACP) thioesterases (TEs) are a group of enzymes to hydrolyze acyl group and release free fatty acid from plastid. Among them, GmFATB1A has become the main target to genetically reduce the palmitic acid content in soybean. However, the role of members in soybean acyl-ACP thioesterase gene family is largely unknown. In this study, we characterized two classes of TEs, GmFATA, and GmFATB in soybean. We also denominated two GmFATA members and discovered six additional members that belong to GmFATB gene family through phylogenetic, syntenic, and in silico analysis. Using TILLING-by-Sequencing+, we identified an allelic series of mutations in five soybean acyl-ACP thioesterase genes, including GmFATA1A, GmFATB1A, GmFATB1B, GmFATB2A, and GmFATB2B. Additionally, we discovered mutations at GmFATA1A to confer high oleic acid (up to 34.5%) content, while mutations at GmFATB presented low palmitic acid (as low as 5.6%) and high oleic acid (up to 36.5%) phenotypes. The obtained soybean mutants with altered fatty acid content can be used in soybean breeding program for improving soybean oil composition traits.

Genetic analysis identified a unique combination of major QTL for resistance to important soybean nematodes concurrently present in a single soybean accession, which has not been reported earlier. An exotic soybean [Glycine max (L.) Merr.] accession, PI 567305, was reported to be highly resistant to three important nematode species, soybean cyst (SCN), root-knot (RKN), and reniform (RN) nematodes. However, genetic basis controlling broad-spectrum resistance in this germplasm has not been investigated. We report results of genetic analysis to identify genomic loci conferring resistance to these nematode species. A bi-parental population consisting of 242 F8-derived recombinant inbred lines (RILs) was developed from a cross of a nematode susceptible cultivar, Magellan, and resistant accession, PI 567305. The RILs were phenotyped for nematode resistance to three SCN HG types. They were genotyped using the Infinium SoySNP6K BeadChips and genotype-by-sequencing (GBS) methods in an attempt to evaluate the cost-effectiveness and efficiency of these two genotyping platforms. Genetic analysis confirmed the major QTL on chromosomes (Chrs) 10 and 18 with broad-spectrum resistance to the three nematodes present in this germplasm. Haplotype and copy number variation analyses of SCN resistance QTL indicated that PI 567305 has a different haplotype, which is associated with likely a unique SCN resistance mechanism different from Peking- or PI 88788-type resistance. The evaluations of both Infinium Beadchip- and GBS-based genotyping technologies provided comprehensive insights for researchers to choose a cost-effective and efficient platform for QTL mapping and for other genomic studies in soybeans.

There is a decrease in the land available for rice cultivation due to the rapid conversion to urban uses. Subsequently, acid soil could be an alternative land cultivating rice, but will require the use of aluminum (Al)-tolerant rice varieties. This Al tolerance trait is genetically controlled, and there is a need to discover more genes needed to develop Al-tolerant rice. Therefore, the objective of this study was to clone and characterize a novel Al tolerance gene isolated from a local cultivar of Indonesian rice. The gene cloning was conducted based on the rye/rice microsynteny relationship. In addition, the root growth and gene expression analyses were performed to verify the role of the gene on Al tolerance in gene-silenced rice and in overexpressed transgenic tobacco. The results showed an Al tolerance candidate gene, OsGERLP, was successfully cloned from rice cv. Hawara Bunar, with its gene encoding a protein similar to a bacterial ribosomal L32 protein. Additionally, the analysis showed that low gene expression caused the gene-silenced rice to be sensitive to Al, while high expression induced the Al tolerance in transgenic tobacco. Furthermore, it was discovered that the gene expression level in both plants was in line with the lower expression of the OsFRDL4 gene in the silenced rice and the high expression of the MATE gene in transgenic tobacco also with the higher citrate secretion from transgenic tobacco roots. In conclusion, the OsGERLP gene could act as a regulator for other Al tolerance genes, with the potential to develop Al-tolerant rice varieties.

Crop yield is a primary trait to select superior genotypes and evaluate breeding efficiency in breeding programs. Crops with high yield potential are usually selected from numerous breeding lines in multiple years and locations. However, the efficiency of conventional breeding programs is limited by the capacity of field phenotyping, which can be improved by developing high-throughput field phenotyping systems using emerging technologies, including Unmanned Aerial Vehicle (UAV) imagery and deep learning technologies. The goal of this study was to evaluate the performance of a UAV imaging system and convolutional neural network (CNN) in estimating yield of soybean breeding lines. In this study, 972 soybean breeding lines in three maturity groups were planted under rainfed conditions for testing their drought tolerance. Aerial images were taken at the late vegetation (V6), early (R1), and late reproductive (R6-R8) growth stages. Seven image features associated with plant height, canopy colour, and canopy texture were selected to estimate the yield of each breeding line. A mixed CNN model was built to estimate soybean yield by taking the seven image features and two categorical factors, i.e. maturity group and drought tolerance, as predictors. Results show that image features collected at the early and late reproductive growth stages are comparably promising in estimating soybean yield. The prediction model could explain 78% of the measured yield with a root mean square error of 391.0 kg·ha−1 (33.8% to the average yield), indicating that the UAV imagery and deep learning models are promising in estimating yield for soybean breeding purposes.

The qSCN10 locus with broad-spectrum SCN resistance was fine-mapped to a 379-kb region on chromosome 10 in soybean accession PI 567516C. Candidate genes and potential application benefits of this locus were discussed. Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most devastating pests of soybean, causing significant yield losses worldwide every year. Genetic resistance has been the major strategy to control this pest. However, the overuse of the same genetic resistance derived primarily from PI 88788 has led to the genetic shifts in nematode populations and resulted in the reduced effectiveness in soybean resistance to SCN. Therefore, novel genetic resistance resources, especially those with broad-spectrum resistance, are needed to develop new resistant cultivars to cope with the genetic shifts in nematode populations. In this study, a quantitative trait locus (QTL) qSCN10 previously identified from a soybean landrace PI 567516C was confirmed to confer resistance to multiple SCN HG Types. This QTL was further fine-mapped to a 379-kb region. There are 51 genes in this region. Four of them are defense-related and were regulated by SCN infection, suggesting their potential role in mediating resistance to SCN. The phylogenetic and haplotype analyses of qSCN10 as well as other information indicate that this locus is different from other reported resistance QTL or genes. There was no yield drag or other unfavorable traits associated with this QTL when near-isogenic lines with and without qSCN10 were tested in a SCN-free field. Therefore, our study not only provides further insight into the genetic basis of soybean resistance to SCN, but also identifies a novel genetic resistance resource for breeding soybean for durable, broad-spectrum resistance to this pest.

The qSCN18 QTL from PI 56756C was confirmed and fine-mapped to improve soybean resistance to the SCN population HG Type 2.5.7 using near-isogenic lines carrying recombination crossovers within the QTL region. The QTL underlying resistance was fine-mapped to a 166-Kbp region on chromosome 18, and the candidate genes were selected based on genomic analyses. Soybean cyst nematode (SCN, Heterodera glycines, Ichinohe) is the most devastating pathogen of soybean. Understanding the genetic basis of SCN resistance is crucial for managing this parasite in the field. Two major loci, rhg1 and Rhg4, were previously characterized as valuable resources for SCN resistance. However, their continuous use has caused shifts in the virulence of SCN populations, which can overcome the resistance conferred by these two major loci. Reduced effectiveness became a major concern in the soybean industry due to continuous use of rhg1 for decades. Thus, it is imperative to identify sources of SCN resistance for durable SCN management. A novel QTL qSCN18 was identified in PI567516C. To fine-map qSCN18 and identify resistance genes, a large backcross population was developed. Nineteen near-isogenic lines (NILs) carrying recombination crossovers within the QTL region were identified. The first phase of fine-mapping narrowed the QTL region to 549-Kbp, whereas the second phase confined the region to 166-Kbp containing 23 genes. Two flanking markers, MK-1 and MK-6, were developed and validated to detect the presence of the qSCN18 resistance allele. Haplotype analysis clustered the fine-mapped qSCN18 region from PI 567516C with the cqSCN-007 locus previously mapped in the wild soybean accession PI 468916. The NILs were developed to further characterize the causal gene(s) harbored in this QTL. This study also confirmed the previously identified qSCN18. The results will facilitate marker-assisted selection (MAS) introducing the qSCN18 locus from PI 567516C into high-yielding soybean cultivars with durable resistance to SCN.

Epigenetics is defined as changes in gene expression that are not associated with changes in DNA sequence but due to the result of methylation of DNA and post-translational modifications to the histones. These epigenetic modifications are known to regulate gene expression by bringing changes in the chromatin state, which underlies plant development and shapes phenotypic plasticity in responses to the environment and internal cues. This review articulates the role of histone modifications and DNA methylation in modulating biotic and abiotic stresses, as well as crop improvement. It also highlights the possibility of engineering epigenomes and epigenome-based predictive models for improving agronomic traits.

Summary Pigeon pea (Cajanus cajan) is an important orphan crop mainly grown by smallholder farmers in India and Africa. Here, we present the first pigeon pea pangenome based on 89 accessions mainly from India and the Philippines, showing that there is significant genetic diversity in Philippine individuals that is not present in Indian individuals. Annotation of variable genes suggests that they are associated with self‐fertilization and response to disease. We identified 225 SNPs associated with nine agronomically important traits over three locations and two different time points, with SNPs associated with genes for transcription factors and kinases. These results will lead the way to an improved pigeon pea breeding programme.

This review provides a wide-ranging assessment of approaches to reduce the impact of heat stress on food crops., To ensure the food security of future generations and to address the challenge of the ‘no hunger zone’ proposed by the FAO (Food and Agriculture Organization), crop production must be doubled by 2050, but environmental stresses are counteracting this goal. Heat stress in particular is affecting agricultural crops more frequently and more severely. Since the discovery of the physiological, molecular, and genetic bases of heat stress responses, cultivated plants have become the subject of intense research on how they may avoid or tolerate heat stress by either using natural genetic variation or creating new variation with DNA technologies, mutational breeding, or genome editing. This review reports current understanding of the genetic and molecular bases of heat stress in crops together with recent approaches to creating heat-tolerant varieties. Research is close to a breakthrough of global relevance, breeding plants fitter to face the biggest challenge of our time.

A whole-genome resequencing-derived SNP dataset identified six quantitative trait loci (QTL) significantly associated with colonization of soybean by an arbuscular mycorrhizal fungus (Rhizophagus intraradices). Candidate genes identified in these QTL regions include homologs to known nodulin protein families and other symbiosis-specific genes. Arbuscular mycorrhizal fungi (AMF) form associations with over 80% of all terrestrial plant species and assist their host plants by increasing their nutrient uptake, drought tolerance, and resilience against pathogens and pests. Genotypic variation of crop plants to AMF colonization has been identified in crops, including soybean; however, the genetics controlling levels of AMF colonization in soybean are unknown. The overall goal of our study was to identify genomic regions associated with mycorrhizal colonization in soybean using genome-wide association analysis. A diverse panel of 350 exotic soybean genotypes inoculated with Rhizophagus intraradices were microscopically evaluated for root colonization using a modified gridline intersect method. Root colonization differed significantly (P

Isoflavones are secondary metabolites that are abundant in soybean and other legume seeds providing health and nutrition benefits for both humans and animals. The objectives of this study were to construct a single nucleotide polymorphism (SNP)-based genetic linkage map using the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306), map quantitative trait loci (QTL) for seed daidzein, genistein, glycitein, and total isoflavone contents in two environments over two years (NC-2018 and IL-2020), identify candidate genes for seed isoflavone. The FXW82 SNP-based map was composed of 2075 SNPs and covered 4029.9 cM. A total of 27 QTL that control various seed isoflavone traits have been identified and mapped on chromosomes (Chrs.) 2, 4, 5, 6, 10, 12, 15, 19, and 20 in both NC-2018 (13 QTL) and IL-2020 (14 QTL). The six QTL regions on Chrs. 2, 4, 5, 12, 15, and 19 are novel regions while the other 21 QTL have been identified by other studies using different biparental mapping populations or genome-wide association studies (GWAS). A total of 130 candidate genes involved in isoflavone biosynthetic pathways have been identified on all 20 Chrs. And among them 16 have been identified and located within or close to the QTL identified in this study. Moreover, transcripts from four genes (Glyma.10G058200, Glyma.06G143000, Glyma.06G137100, and Glyma.06G137300) were highly abundant in Forrest and Williams 82 seeds. The identified QTL and four candidate genes will be useful in breeding programs to develop soybean cultivars with high beneficial isoflavone contents.

Soybean is the second largest source of oil worldwide. Developing soybean varieties with high levels of oleic acid is a primary goal of the soybean breeders and industry. Edible oils containing high level of oleic acid and low level of linoleic acid are considered with higher oxidative stability and can be used as a natural antioxidant in food stability. All developed high oleic acid soybeans carry two alleles, GmFAD2-1A and GmFAD2-1B. However, when planted in cold soil, a possible reduction in seed germination was reported when high seed oleic acid derived from GmFAD2-1 alleles were used. Besides the soybean fatty acid desaturase (GmFAD2-1) subfamily, the GmFAD2-2 subfamily is composed of five members, including GmFAD2-2A, GmFAD2-2B, GmFAD2-2C, GmFAD2-2D, and GmFAD2-2E. Segmental duplication of GmFAD2-1A/GmFAD2-1B, GmFAD2-2A/GmFAD2-2C, GmFAD2-2A/GmFAD2-2D, and GmFAD2-2D/GmFAD2-2C have occurred about 10.65, 27.04, 100.81, and 106.55 Mya, respectively. Using TILLING-by-Sequencing+ technology, we successfully identified 12, 8, 10, 9, and 19 EMS mutants at the GmFAD2-2A, GmFAD2-2B, GmFAD2-2C, GmFAD2-2D, and GmFAD2-2E genes, respectively. Functional analyses of newly identified mutants revealed unprecedented role of the five GmFAD2-2A, GmFAD2-2B, GmFAD2-2C, GmFAD2-2D, and GmFAD2-2E members in controlling the seed oleic acid content. Most importantly, unlike GmFAD2-1 members, subcellular localization revealed that members of the GmFAD2-2 subfamily showed a cytoplasmic localization, which may suggest the presence of an alternative fatty acid desaturase pathway in soybean for converting oleic acid content without substantially altering the traditional plastidial/ER fatty acid production.

It has been commonly accepted that soybean domestication originated in East Asia. Although East Asia has the historical merit in soybean production, the USA has become the top soybean producer in the world since 1950s. Following that, Brazil and Argentina have been the major soybean producers since 1970s and 1990s, respectively. China has once been the exporter of soybean to Japan before 1990s, yet she became a net soybean importer as Japan and the Republic of Korea do. Furthermore, the soybean yield per unit area in East Asia has stagnated during the past decade. To improve soybean production and enhance food security in these East Asian countries, much investment has been made, especially in the breeding of better performing soybean germplasms. As a result, China, Japan, and the Republic of Korea have become three important centers for soybean genomic research. With new technologies, the rate and precision of the identification of important genomic loci associated with desired traits from germplasm collections or mutants have increased significantly. Genome editing on soybean is also becoming more established. The year 2019 marked a new era for crop genome editing in the commercialization of the first genome-edited plant product, which is a high-oleic-acid soybean oil. In this review, we have summarized the latest developments in soybean breeding technologies and the remarkable progress in soybean breeding-related research in China, Japan, and the Republic of Korea.

Efficient crop improvement depends on the application of accurate genetic information contained in diverse germplasm resources. Here we report a reference-grade genome of wild soybean accession W05, with a final assembled genome size of 1013.2 Mb and a contig N50 of 3.3 Mb. The analytical power of the W05 genome is demonstrated by several examples. First, we identify an inversion at the locus determining seed coat color during domestication. Second, a translocation event between chromosomes 11 and 13 of some genotypes is shown to interfere with the assignment of QTLs. Third, we find a region containing copy number variations of the Kunitz trypsin inhibitor (KTI) genes. Such findings illustrate the power of this assembly in the analysis of large structural variations in soybean germplasm collections. The wild soybean genome assembly has wide applications in comparative genomic and evolutionary studies, as well as in crop breeding and improvement programs., Wild relatives of crop plants are invaluable germplasm for genetic improvement. Here, Xie et al. report a reference-grade wild soybean genome and show that it can be used to identify structural variation and refine quantitative trait loci.

Summary Soybean cyst nematode (SCN) is the most devastating plant‐parasitic nematode. Most commercial soybean varieties with SCN resistance are derived from PI88788. Resistance derived from PI88788 is breaking down due to narrow genetic background and SCN population shift. PI88788 requires mainly the rhg1‐b locus, while ‘Peking’ requires rhg1‐a and Rhg4 for SCN resistance. In the present study, whole genome re‐sequencing of 106 soybean lines was used to define the Rhg haplotypes and investigate their responses to the SCN HG‐Types. The analysis showed a comprehensive profile of SNPs and copy number variations (CNV) at these loci. CNV of rhg1 (GmSNAP18) only contributed towards resistance in lines derived from PI88788 and ‘Cloud’. At least 5.6 copies of the PI88788‐type rhg1 were required to confer SCN resistance, regardless of the Rhg4 (GmSHMT08) haplotype. However, when the GmSNAP18 copies dropped below 5.6, a ‘Peking’‐type GmSHMT08 haplotype was required to ensure SCN resistance. This points to a novel mechanism of epistasis between GmSNAP18 and GmSHMT08 involving minimum requirements for copy number. The presence of more Rhg4 copies confers resistance to multiple SCN races. Moreover, transcript abundance of the GmSHMT08 in root tissue correlates with more copies of the Rhg4 locus, reinforcing SCN resistance. Finally, haplotype analysis of the GmSHMT08 and GmSNAP18 promoters inferred additional levels of the resistance mechanism. This is the first report revealing the genetic basis of broad‐based resistance to SCN and providing new insight into epistasis, haplotype‐compatibility, CNV, promoter variation and its impact on broad‐based disease resistance in plants.

Symbiotic nitrogen fixation, which is carried out by the legume-rhizobia partnership, is a major source of nitrogen acquisition in natural ecosystems and in agriculture. The benefits to the plant gained through the rhizobial-legume symbiosis can be further enhanced by associations of the legume with arbuscular mycorrhiza. The progressive engagement of the legume host with the rhizobial bacteria and mycorrhizal fungi requires an extensive exchange of signalling molecules. These signals alter the transcriptional profiles of the partners, guiding and enabling extensive microbial and fungal proliferation in the roots. Such interactions and associations are greatly influenced by environmental stresses, which also severely limit the productivity of legume crops. Part II of the Special Issue on Legumes provides new insights into the mechanisms that underpin sustainable symbiotic partnerships, as well as the effects of abiotic stresses, such as drought, waterlogging, and salinity on legume biology. The requirement for germplasm and new breeding methods is discussed as well as the future of legume production in the face of climate change.

Two novel QTL for resistance to Pythium ultimum var. ultimum were identified in soybean using an Illumina SNP Chip and whole genome re-sequencing. Pythium ultimum var. ultimum is one of numerous Pythium spp. that causes severe pre- and post-emergence damping-off of seedlings and root rot of soybean [Glycine max (L.) Merr.]. The objective of this research was to identify quantitative trait loci (QTL) for resistance to P. ultimum var. ultimum in a recombinant inbred line population derived from a cross of 'Magellan' (moderately resistant) and PI 438489B (susceptible). Two different mapping approaches were utilized: the universal soybean linkage panel (USLP 1.0) and the bin map constructed from whole genome re-sequencing (WGRS) technology. Two genomic regions associated with variation in three disease-related parameters were detected using both approaches, with the bin map providing higher resolution. Using WGRS, the first QTL were mapped within a 350-kbp region on Chr. 6 and explained 7.5-13.5% of the phenotypic variance. The second QTL were positioned in a 260-kbp confidence interval on Chr. 8 and explained 6.3-16.8% of the phenotypic variation. Candidate genes potentially associated with disease resistance were proposed. High-resolution genetic linkage maps with a number of significant SNP markers could benefit marker-assisted breeding and dissection of the molecular mechanisms underlying soybean resistance to Pythium damping-off in 'Magellan.' Additionally, the outputs of this study may encourage more screening of diverse soybean germplasm and utilization of genome-wide association studies to understand the genetic basis of quantitative disease resistance.

Reniform nematode (RN, Rotylenchulus reniformis Linford & Oliveira) has emerged as one of the most important plant parasitic nematodes of soybean [Glycine max (L.) Merr.]. Planting resistant varieties is the most effective strategy for nematode management. The objective of this study was to identify quantitative trait loci (QTL) for RN resistance in an exotic soybean line, PI 438489B, using two linkage maps constructed from the Universal Soybean Linkage Panel (USLP 1.0) and next‐generation whole‐genome resequencing (WGRS) technology. Two QTL controlling RN resistance were identified—the soybean cyst nematode (SCN, Heterodera glycines) resistance gene GmSNAP18 at the rhg1 locus and its paralog GmSNAP11. Strong association between resistant phenotype and haplotypes of the GmSNAP11 and GmSNAP18 was observed. The results indicated that GmSNAP11 possibly could have epistatic effect on GmSNAP18, or vice versa, with the presence of a significant correlation in RN resistance of rhg1‐a GmSNAP18 vs. rhg1‐b GmSNAP18. Most importantly, our preliminary data suggested that GmSNAP18 and GmSNAP11 proteins physically interact in planta, suggesting that they belong to the same pathway for resistance. Unlike GmSNAP18, no indication of GmSNAP11 copy number variation was found. Moreover, gene‐based single nucleotide polymorphism (SNP) markers were developed for rapid detection of RN or SCN resistance at these loci. Our analysis substantiates synergic interaction between GmSNAP11 and GmSNAP18 genes and confirms their roles in RN as well as SCN resistance. These results could contribute to a better understanding of evolution and subfunctionalization of genes conferring resistance to multiple nematode species and provide a framework for further investigations.

The gene content of plants varies between individuals of the same species due to gene presence/absence variation, and selection can alter the frequency of specific genes in a population. Selection during domestication and breeding will modify the genomic landscape, though the nature of these modifications is only understood for specific genes or on a more general level (e.g., by a loss of genetic diversity). Here we have assembled and analyzed a soybean (Glycine spp.) pangenome representing more than 1,000 soybean accessions derived from the USDA Soybean Germplasm Collection, including both wild and cultivated lineages, to assess genomewide changes in gene and allele frequency during domestication and breeding. We identified 3,765 genes that are absent from the Lee reference genome assembly and assessed the presence/absence of all genes across this population. In addition to a loss of genetic diversity, we found a significant reduction in the average number of protein-coding genes per individual during domestication and subsequent breeding, though with some genes and allelic variants increasing in frequency associated with selection for agronomic traits. This analysis provides a genomic perspective of domestication and breeding in this important oilseed crop.

We report characteristics of soybean genetic diversity and structure from the resequencing of 481 diverse soybean accessions, comprising 52 wild (Glycine soja) selections and 429 cultivated (Glycine max) varieties (landraces and elites). This data was used to identify 7.8 million SNPs, to predict SNP effects relative to genic regions, and to identify the genetic structure, relationships, and linkage disequilibrium. We found evidence of distinct, mostly independent selection of lineages by particular geographic location. Among cultivated varieties, we identified numerous highly conserved regions, suggesting selection during domestication. Comparisons of these accessions against the whole U.S. germplasm genotyped with the SoySNP50K iSelect BeadChip revealed that over 95% of the re-sequenced accessions have a high similarity to their SoySNP50K counterparts. Probable errors in seed source or genotype tracking were also identified in approximately 5% of the accessions., Measurement(s) genetic variation • SNP • Linkage Disequilibrium Technology Type(s) DNA sequencing • bioinformatics analysis • computational phylogenetic analysis Sample Characteristic - Organism Glycine soja • Glycine max Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13568552

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.

Alternative splicing (AS) is a common post-transcriptional regulatory mechanism that modulates gene expression to increase proteome diversity. Increasing evidence indicates that AS plays an important role in regulating plant stress responses. However, the mechanism by which AS coordinates with transcriptional regulation to regulate drought responses in soybean remains poorly understood. In this study, we performed a genome-wide analysis of AS events in soybean (Glycine max) roots grown under various drought conditions using the high-throughput RNA-sequencing method, identifying 385, 989, 1429, and 465 AS events that were significantly differentially spliced under very mild drought stress, mild drought stress, severe drought stress, and recovery after severe drought conditions, respectively. Among them, alternative 3&prime, splice sites and skipped exons were the major types of AS. Overall, 2120 genes that experienced significant AS regulation were identified from these drought-treated root samples. Gene Ontology term analysis indicated that the AS regulation of binding activity has vital roles in the drought response of soybean root. Notably, the genes encoding splicing regulatory factors in the spliceosome pathway and mRNA surveillance pathway were enriched according to the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Splicing regulatory factor-related genes in soybean root also responded to drought stress and were alternatively spliced under drought conditions. Taken together, our data suggest that drought-responsive AS acts as a direct or indirect mode to regulate drought response of soybean roots. With further in-depth research of the function and mechanism of AS in the process of abiotic stress, these results will provide a new strategy for enhancing stress tolerance of plants.

Aluminium (Al) toxicity inhibits soybean root growth, leading to insufficient water and nutrient uptake. Two soybean lines (‘Magellan’ and PI 567731) were identified differing in Al tolerance, as determined by primary root length ratio, total root length ratio, and root tip number ratio under Al stress. Serious root necrosis was observed in PI 567731, but not in Magellan under Al stress. An F8 recombinant inbred line population derived from a cross between Magellan and PI 567731 was used to map the quantitative trait loci (QTL) for Al tolerance. Three QTL on chromosomes 3, 13, and 20, with tolerant alleles from Magellan, were identified. qAl_Gm13 and qAl_Gm20 explained large phenotypic variations (13–27%) and helped maintain root elongation and initiation under Al stress. In addition, qAl_Gm13 and qAl_Gm20 were confirmed in near-isogenic backgrounds and were identified to epistatically regulate Al tolerance via internal detoxification instead of Al3+ exclusion. Phylogenetic and pedigree analysis identified the tolerant alleles of both loci derived from the US ancestral line, A.K.[FC30761], originally from China. Our results provide novel genetic resources for breeding Al-tolerant soybean and suggest that internal detoxification contributes to soybean tolerance to excessive soil Al.

Transporters, a class of membrane proteins that facilitate exchange of solutes including diverse molecules and ions across the cellular membrane, are vital component for the survival of all organisms. Understanding plant transporters is important to get insight of the basic cellular processes, physiology, and molecular mechanisms including nutrient uptake, signaling, response to external stress, and many more. In this regard, extensive analysis of transporters predicted in soybean and other plant species was performed. In addition, an integrated database for soybean transporter protein, SoyTD, was developed that will facilitate the identification, classification, and extensive characterization of transporter proteins by integrating expression, gene ontology, conserved domain and motifs, gene structure organization, and chromosomal distribution features. A comprehensive analysis was performed to identify highly confident transporters by integrating various prediction tools. Initially, 7541 transmembrane (TM) proteins were predicted in the soybean genome; out of these, 3306 non-redundant transporter genes carrying two or more transmembrane domains were selected for further analysis. The identified transporter genes were classified according to a standard transporter classification (TC) system. Comparative analysis of transporter genes among 47 plant genomes provided insights into expansion and duplication of transporter genes in land plants. The whole genome resequencing (WGRS) and tissue-specific transcriptome datasets of soybean were integrated to investigate the natural variants and expression profile associated with transporter(s) of interest. Overall, SoyTD provides a comprehensive interface to study genetic and molecular function of soybean transporters. SoyTD is publicly available at http://artemis.cyverse.org/soykb_dev/SoyTD/.

Over the past 70 years, the world has witnessed extraordinary growth in crop productivity, enabled by a suite of technological advances, including higher yielding crop varieties, improved farm management, synthetic agrochemicals, and agricultural mechanization. While this “Green Revolution” intensified crop production, and is credited with reducing famine and malnutrition, its benefits were accompanied by several undesirable collateral effects (Pingali, 2012). These include a narrowing of agricultural biodiversity, stemming from increased monoculture and greater reliance on a smaller number of crops and crop varieties for the majority of our calories. This reduction in diversity has created vulnerabilities to pest and disease epidemics, climate variation, and ultimately to human health (Harlan, 1972). The value of crop diversity has long been recognized (Vavilov, 1992). A global system of genebanks (e.g., www.genebanks.org/genebanks/) was established in the 1970s to conserve the abundant genetic variation found in traditional “landrace” varieties of crops and in crop wild relatives (Harlan, 1972). While preserving crop variation is a critical first step, the time has come to make use of this variation to breed more resilient crops. The DivSeek International Network (https://divseekintl.org/) is a scientific, not-for-profit organization that aims to accelerate such efforts.

Some crops inhibit shoot growth but maintain root growth under water-deficit conditions. Unraveling the molecular mechanisms of root plasticity under water deficit conditions in plants remains a major challenge. We developed an efficient platform for identifying core transcription factors (TFs) that collectively regulate each other and/or themselves in response to water stress, and exploring their interconnected regulatory circuitry involved in root growth maintenance under water deficit in soybean. We performed multi-species phylogenetic footprinting combined with spatial-temporal transcriptome analysis of soybean (Glycine max) roots under water deficit to identify conserved motifs that function in the water-stress response. Using these functional conserved cis-motifs, we applied a new approach to trace back motifs-associated core TFs ingroup as signal mediators, which mediate signaling between abiotic and endogenous stimuli. We integrated a co-functional TF–TF network and conserved motif-centered TF–DNA networks to construct a core TF network defined by mutual cross-regulation among core TFs. We found that core TF ARG (Abscisic acid response element binding factor-like Root Growth regulator) represses BRG (Brassinosteroid enhanced expression-like Root Growth regulator) expression through binding to its promoter at a conserved binding site. ARG and BRG antagonistically regulate Phytochrome-interacting factor-like Root Growth regulator (PRG) and combinatorially regulate some other core TFs. These core TFs form complex regulatory circuits to integrate light and multiple hormone signaling pathways and maintain root growth in response to varying degrees of water stress. Our study provides valuable information to unravel the complicated mechanisms of molecular networks involved in the regulation of root growth under water deficit.

Wild soybean species (Glycine soja Siebold & Zucc.) comprise a unique resource to widen the genetic base of cultivated soybean [Glycine max (L.) Merr.] for various agronomic traits. An inter-specific mapping population derived from a cross of cultivar Williams 82 and PI 483460B, a wild soybean accession, was utilized for genetic characterization of root architecture traits. The objectives of this study were to identify and characterize quantitative trait loci (QTL) for seedling shoot and root architecture traits, as well as to determine additive/epistatic interaction effects of identified QTLs. A total of 16,469 single nucleotide polymorphisms (SNPs) developed for the Illumina beadchip genotyping platform were used to construct a high resolution genetic linkage map. Among the 11 putative QTLs identified, two significant QTLs on chromosome 7 were determined to be associated with total root length (RL) and root surface area (RSA) with favorable alleles from the wild soybean parent. These seedling root traits, RL (BARC_020495_04641 ~ BARC_023101_03769) and RSA (SNP02285 ~ SNP18129_Magellan), could be potential targets for introgression into cultivated soybean background to improve both tap and lateral roots. The RL QTL region harbors four candidate genes with higher expression in root tissues: Phosphofructokinase (Glyma.07g126400), Snf7 protein (Glyma.07g127300), unknown functional gene (Glyma.07g127900), and Leucine Rich-Repeat protein (Glyma.07g127100). The novel alleles inherited from the wild soybean accession could be used as molecular markers to improve root system architecture and productivity in elite soybean lines.

Soybean [Glycine max (L.) Merr] is an agronomically important oilseed crop in the world and an important source of protein and oil for both humans and animals. In addition, soybean is also becoming a major crop for bio-diesel production. Therefore, demand for soybean is increasing continuously worldwide. Soybean enriches the soil by fixing atmospheric nitrogen through symbiotic interaction with Rhizobia. With increasing challenges posed by climate change, it is predicted that incidents of drought will be more frequent and severe and it will further reduce crop yields. Abiotic stresses such as drought cause severe losses to soybean productivity worldwide by adversely affecting the plant growth, development, and yield. Introgression of genes controlling drought adaptive traits, yields related traits and root system architecture traits by breeding and molecular approaches will be very useful for enhancing drought stress tolerance in soybean, leading to cultivar development. Elucidation of function of genes and their integration in soybean genotypes by molecular breeding and genomic approaches and utilizing robust phenotyping tools to evaluate drought adaptive traits will be crucial for understanding response of soybean plants to drought stress. Recent advances in genomics lead identification, functional characterization, and introgression of genes associated with adaptation of soybean plants to drought stress. In order to perform genetic and genomic analysis, molecular markers have been employed on RIL or F2 populations. In addition, the genome typified with single nucleotide polymorphisms (SNPs) and its utilization in molecular breeding applications like QTL mapping, positional cloning, association mapping studies, genomic selection and genome editing is gaining impetus. Thus, the rapid development of soybean genomics and transcriptomics has provided tremendous opportunity for the genetic improvement of soybean for drought tolerance with yield stability.

Flooding threatens soybean production and limits soybean yields worldwide. The most effective and economic approach to decrease loss of yield due to flooding is to develop flood-tolerant soybean cultivars. The objective of this study was to identify genetic loci and candidate genes associated with flooding tolerance. A panel of 384 soybean plant introductions (PIs) was evaluated for flooding tolerance in two consecutive years in the field. The plant foliar damage score was used to index soybean response to flooding stress. A total of 42,291 SNP markers were obtained from the Illumina Infinium SoySNP50K BeadChip database. After filtration for quality control, 31,125 SNPs were used for genome-wide association mapping utilizing four different models (regression linear model (GLM), mixed linear model (MLM), compressed mixed linear model (CMLM), and enriched compressed mixed linear model (ECMLM)). Fourteen SNPs were identified to be associated with flooding tolerance across all environments and models at a significance level of −Log10 (P) ≥ 2.5. Five SNPs were located within the coding regions of five candidate genes. Several PIs with lower best linear unbiased prediction (BLUPs) of the breeding values and a large number of favorable flood-tolerant alleles were found as new genetic sources for use in soybean breeding programs.

Soybean [Glycine max (L.) Merr.] seed is a valuable source of protein and oil worldwide. Traditionally, the natural variations were heavily used in conventional soybean breeding programs to select desired traits. However, traditional plant breeding is encumbered with low frequencies of spontaneous mutations. In mutation breeding, genetic variations from induced mutations provide abundant sources of alterations in important soybean traits, this facilitated the development of soybean germplasm with modified seed composition traits to meet the different needs of end users. In this study, a total of 2366 &lsquo, Forrest&rsquo, derived M2 families were developed for both forward and reverse genetic studies. A subset of 881 M3 families was forward genetically screened to measure the contents of protein, oil, carbohydrates, and fatty acids. A total of 14 mutants were identified to have stable seed composition phenotypes observed in both M3 and M4 generations. Correlation analyses have been conducted among ten seed composition traits and compared to a collection of 103 soybean germplasms. Mainly, ethyl methanesulfonate (EMS) mutagenesis had a strong impact on the seed-composition correlation that was observed among the 103 soybean germplasms, which offers multiple benefits for the soybean farmers and industry to breed for desired multiple seed phenotypes.

Soybean is a widely grown grain legume and one of the most important economic crop species. Brassinosteroids play a crucial role in plant vegetative growth and reproductive development. However, it remains unclear how BRs regulate the developmental processes in soybean, and the molecular mechanism underlying soybean early development is largely unexplored. In this study, we first characterized how soybean early vegetative growth was specifically regulated by the BR biosynthesis inhibitor propiconazole; this characterization included shortened root and shoot lengths, reduced leaf area, and decreased chlorophyll content. In addition, the growth inhibition induced by Pcz could be rescued by exogenous brassinolide application. The RNA-seq technique was employed to investigate the BR regulatory networks during soybean early vegetative development. Identification and analysis of differentially expressed genes indicated that BRs orchestrate a wide range of cellular activities and biological processes in soybean under various BR concentrations. The regulatory networks between BRs and multiple hormones or stress-related pathways were investigated. The results provide a comprehensive view of the physiological functions of BRs and new insights into the molecular mechanisms at the transcriptional level of BR regulation of soybean early development.

Developing crops with better root systems is a promising strategy to ensure productivity in both optimum and stress environments. Root system architectural traits in 397 soybean accessions were characterized and a high-density single nucleotide polymorphisms (SNPs)-based genome-wide association study was performed to identify the underlying genes associated with root structure. SNPs associated with root architectural traits specific to landraces and elite germplasm pools were detected. Four loci were detected in landraces for lateral root number (LRN) and distribution of root thickness in diameter Class I with a major locus on chromosome 16. This major loci was detected in the coding region of unknown protein, and subsequent analyses demonstrated that root traits are affected with mutated haplotypes of the gene. In elite germplasm pool, 3 significant SNPs in alanine-glyoxalate aminotransferase, Leucine-Rich Repeat receptor/No apical meristem, and unknown functional genes were found to govern multiple traits including root surface area and volume. However, no major loci were detected for LRN in elite germplasm. Nucleotide diversity analysis found evidence of selective sweeps around the landraces LRN gene. Soybean accessions with minor and mutated allelic variants of LRN gene were found to perform better in both water-limited and optimal field conditions.

Summary The cultivated [Glycine max (L) Merr.] and wild [Glycine soja Siebold & Zucc.] soybean species comprise wide variation in seed composition traits. Compared to wild soybean, cultivated soybean contains low protein, high oil, and high sucrose. In this study, an interspecific population was derived from a cross between G. max (Williams 82) and G. soja (PI 483460B). This recombinant inbred line (RIL) population of 188 lines was sequenced at 0.3× depth. Based on 91 342 single nucleotide polymorphisms (SNPs), recombination events in RILs were defined, and a high‐resolution bin map was developed (4070 bins). In addition to bin mapping, quantitative trait loci (QTL) analysis for protein, oil, and sucrose was performed using 3343 polymorphic SNPs (3K‐SNP), derived from Illumina Infinium BeadChip sequencing platform. The QTL regions from both platforms were compared, and a significant concordance was observed between bin and 3K‐SNP markers. Importantly, the bin map derived from next‐generation sequencing technology enhanced mapping resolution (from 1325 to 50 Kb). A total of five, nine, and four QTLs were identified for protein, oil, and sucrose content, respectively, and some of the QTLs coincided with soybean domestication‐related genomic loci. The major QTL for protein and oil were mapped on Chr. 20 (qPro_20) and suggested negative correlation between oil and protein. In terms of sucrose content, a novel and major QTL were identified on Chr. 8 (qSuc_08) and harbours putative genes involved in sugar transport. In addition, genome‐wide association using 91 342 SNPs confirmed the genomic loci derived from QTL mapping. A QTL‐based haplotype using whole‐genome resequencing of 106 diverse soybean lines identified unique allelic variation in wild soybean that could be utilized to widen the genetic base in cultivated soybean.