Cultivated soybean [Glycine max (L.) Merr.] is a primary source of vegetable oil and protein. We report a landscape analysis of genome-wide genetic variation and an association study of major domestication and agronomic traits in soybean. A total of 106 soybean genomes representing wild, landraces, and elite lines were re-sequenced at an average of 17x depth with a 97.5% coverage. Over 10 million high-quality SNPs were discovered, and 35.34% of these have not been previously reported. Additionally, 159 putative domestication sweeps were identified, which includes 54.34 Mbp (4.9%) and 4,414 genes; 146 regions were involved in artificial selection during domestication. A genome-wide association study of major traits including oil and protein content, salinity, and domestication traits resulted in the discovery of novel alleles. Genomic information from this study provides a valuable resource for understanding soybean genome structure and evolution, and can also facilitate trait dissection leading to sequencing-based molecular breeding.

Soil salinity is a limiting factor of crop yield. The soybean is sensitive to soil salinity, and a dominant gene, Glyma03g32900 is primarily responsible for salt-tolerance. The identification of high throughput and robust markers as well as the deployment of salt-tolerant cultivars are effective approaches to minimize yield loss under saline conditions. We utilized high quality (15x) whole-genome resequencing (WGRS) on 106 diverse soybean lines and identified three major structural variants and allelic variation in the promoter and genic regions of the GmCHX1 gene. The discovery of single nucleotide polymorphisms (SNPs) associated with structural variants facilitated the design of six KASPar assays. Additionally, haplotype analysis and pedigree tracking of 93 U.S. ancestral lines were performed using publically available WGRS datasets. Identified SNP markers were validated, and a strong correlation was observed between the genotype and salt treatment phenotype (leaf scorch, chlorophyll content and Na+ accumulation) using a panel of 104 soybean lines and, an interspecific bi-parental population (F8) from PI483463 x Hutcheson. These markers precisely identified salt-tolerant/sensitive genotypes (>91%), and different structural-variants (>98%). These SNP assays, supported by accurate phenotyping, haplotype analyses and pedigree tracking information, will accelerate marker-assisted selection programs to enhance the development of salt-tolerant soybean cultivars.

Key message Genetic improvement of soybean protein meal is a complex process because of negative correlation with oil, yield, and temperature. This review describes the progress in mapping and genomics, identifies knowledge gaps, and highlights the need of integrated approaches. AbstractMeal protein derived from soybean [Glycine max (L) Merr.] seed is the primary source of protein in poultry and livestock feed. Protein is a key factor that determines the nutritional and economical value of soybean. Genetic improvement of soybean seed protein content is highly desirable, and major quantitative trait loci (QTL) for soybean protein have been detected and repeatedly mapped on chromosomes (Chr.) 20 (LG-I), and 15 (LG-E). However, practical breeding progress is challenging because of seed protein content’s negative genetic correlation with seed yield, other seed components such as oil and sucrose, and interaction with environmental effects such as temperature during seed development. In this review, we discuss rate-limiting factors related to soybean protein content and nutritional quality, and potential control factors regulating seed storage protein. In addition, we describe advances in next-generation sequencing technologies for precise detection of natural variants and their integration with conventional and high-throughput genotyping technologies. A syntenic analysis of QTL on Chr. 15 and 20 was performed. Finally, we discuss comprehensive approaches for integrating protein and amino acid QTL, genome-wide association studies, whole-genome resequencing, and transcriptome data to accelerate identification of genomic hot spots for allele introgression and soybean meal protein improvement.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-017-2955-8) contains supplementary material, which is available to authorized users.

BackgroundSWEET (MtN3_saliva) domain proteins, a recently identified group of efflux transporters, play an indispensable role in sugar efflux, phloem loading, plant-pathogen interaction and reproductive tissue development. The SWEET gene family is predominantly studied in Arabidopsis and members of the family are being investigated in rice. To date, no transcriptome or genomics analysis of soybean SWEET genes has been reported.ResultsIn the present investigation, we explored the evolutionary aspect of the SWEET gene family in diverse plant species including primitive single cell algae to angiosperms with a major emphasis on Glycine max. Evolutionary features showed expansion and duplication of the SWEET gene family in land plants. Homology searches with BLAST tools and Hidden Markov Model-directed sequence alignments identified 52 SWEET genes that were mapped to 15 chromosomes in the soybean genome as tandem duplication events. Soybean SWEET (GmSWEET) genes showed a wide range of expression profiles in different tissues and developmental stages. Analysis of public transcriptome data and expression profiling using quantitative real time PCR (qRT-PCR) showed that a majority of the GmSWEET genes were confined to reproductive tissue development. Several natural genetic variants (non-synonymous SNPs, premature stop codons and haplotype) were identified in the GmSWEET genes using whole genome re-sequencing data analysis of 106 soybean genotypes. A significant association was observed between SNP-haplogroup and seed sucrose content in three gene clusters on chromosome 6.ConclusionPresent investigation utilized comparative genomics, transcriptome profiling and whole genome re-sequencing approaches and provided a systematic description of soybean SWEET genes and identified putative candidates with probable roles in the reproductive tissue development. Gene expression profiling at different developmental stages and genomic variation data will aid as an important resource for the soybean research community and can be extremely valuable for understanding sink unloading and enhancing carbohydrate delivery to developing seeds for improving yield.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1730-y) contains supplementary material, which is available to authorized users.

We report reference-quality genome assemblies and annotations for two accessions of soybean (Glycine max) and for one accession of Glycine soja, the closest wild relative of G. max. The G. max assemblies provided are for widely used US cultivars: the northern line Williams 82 (Wm82) and the southern line Lee. The Wm82 assembly improves the prior published assembly, and the Lee and G. soja assemblies are new for these accessions. Comparisons among the three accessions show generally high structural conservation, but nucleotide difference of 1.7 single-nucleotide polymorphisms (snps) per kb between Wm82 and Lee, and 4.7 snps per kb between these lines and G. soja. snp distributions and comparisons with genotypes of the Lee and Wm82 parents highlight patterns of introgression and haplotype structure. Comparisons against the US germplasm collection show placement of the sequenced accessions relative to global soybean diversity. Analysis of a pan-gene collection shows generally high conservation, with variation occurring primarily in genomically clustered gene families. We found approximately 40-42 inversions per chromosome between either Lee or Wm82v4 and G. soja, and approximately 32 inversions per chromosome between Wm82 and Lee. We also investigated five domestication loci. For each locus, we found two different alleles with functional differences between G. soja and the two domesticated accessions. The genome assemblies for multiple cultivated accessions and for the closest wild ancestor of soybean provides a valuable set of resources for identifying causal variants that underlie traits for the domestication and improvement of soybean, serving as a basis for future research and crop improvement efforts for this important crop species.

Soybean production is greatly influenced by abiotic stresses imposed by environmental factors such as drought, water submergence, salt, and heavy metals. A thorough understanding of plant response to abiotic stress at the molecular level is a prerequisite for its effective management. The molecular mechanism of stress tolerance is complex and requires information at the omic level to understand it effectively. In this regard, enormous progress has been made in the omics field in the areas of genomics, transcriptomics, and proteomics. The emerging field of ionomics is also being employed for investigating abiotic stress tolerance in soybean. Omic approaches generate a huge amount of data, and adequate advancements in computational tools have been achieved for effective analysis. However, the integration of omic-scale information to address complex genetics and physiological questions is still a challenge. In this review, we have described advances in omic tools in the view of conventional and modern approaches being used to dissect abiotic stress tolerance in soybean. Emphasis was given to approaches such as quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). Comparative genomics and candidate gene approaches are also discussed considering identification of potential genomic loci, genes, and biochemical pathways involved in stress tolerance mechanism in soybean. This review also provides a comprehensive catalog of available online omic resources for soybean and its effective utilization. We have also addressed the significance of phenomics in the integrated approaches and recognized high-throughput multi-dimensional phenotyping as a major limiting factor for the improvement of abiotic stress tolerance in soybean.

Drought and flooding are two major causes of severe yield loss in soybean worldwide. A lack of knowledge of the molecular mechanisms involved in drought and flood stress has been a limiting factor for the effective management of soybeans; therefore, it is imperative to assess the expression of genes involved in response to flood and drought stress. In this study, differentially expressed genes (DEGs) under drought and flooding conditions were investigated using Illumina RNA-Seq transcriptome profiling. A total of 2724 and 3498 DEGs were identified under drought and flooding treatments, respectively. These genes comprise 289 Transcription Factors (TFs) representing Basic Helix-loop Helix (bHLH), Ethylene Response Factors (ERFs), myeloblastosis (MYB), No apical meristem (NAC), and WRKY amino acid motif (WRKY) type major families known to be involved in the mechanism of stress tolerance. The expression of photosynthesis and chlorophyll synthesis related genes were significantly reduced under both types of stresses, which limit the metabolic processes and thus help prolong survival under extreme conditions. However, cell wall synthesis related genes were up-regulated under drought stress and down-regulated under flooding stress. Transcript profiles involved in the starch and sugar metabolism pathways were also affected under both stress conditions. The changes in expression of genes involved in regulating the flux of cell wall precursors and starch/sugar content can serve as an adaptive mechanism for soybean survival under stress conditions. This study has revealed the involvement of TFs, transporters, and photosynthetic genes, and has also given a glimpse of hormonal cross talk under the extreme water regimes, which will aid as an important resource for soybean crop improvement.

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is a serious soybean pest. The use of resistant cultivars is an effective approach for preventing yield loss. In this study, 19,652 publicly available soybean accessions that were previously genotyped with the SoySNP50K iSelect BeadChip were used to evaluate the phylogenetic diversity of SCN resistance genes Rhg1 and Rhg4 in an attempt to identify novel sources of resistance. The sequence information of soybean lines was utilized to develop KASPar (KBioscience Competitive Allele-Specific PCR) assays from single nucleotide polymorphisms (SNPs) of Rhg1, Rhg4, and other novel quantitative trait loci (QTL). These markers were used to genotype a diverse set of 95 soybean germplasm lines and three recombinant inbred line (RIL) populations. SNP markers from the Rhg1 gene were able to differentiate copy number variation (CNV), such as resistant-high copy (PI 88788-type), low copy (Peking-type), and susceptible-single copy (Williams 82) numbers. Similarly, markers for the Rhg4 gene were able to detect Peking-type (resistance) genotypes. The phylogenetic information of SCN resistance loci from a large set of soybean accessions and the gene/QTL specific markers that were developed in this study will accelerate SCN resistance breeding programs.