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Key message An epistatic interaction between SCN resistance loci rhg1-a and rhg2 in PI 90763 imparts resistance against virulent SCN populations which can be employed to diversify SCN resistance in soybean cultivars. Abstract With more than 95% of the $46.1B soybean market dominated by a single type of genetic resistance, breeding for soybean cyst nematode (SCN)-resistant soybean that can effectively combat the widespread increase in virulent SCN populations presents a significant challenge. Rhg genes (for Resistance to Heterodera glycines) play a key role in resistance to SCN; however, their deployment beyond the use of the rhg1-b allele has been limited. In this study, quantitative trait loci (QTL) were mapped using PI 90763 through two biparental F3:4 recombinant inbred line (RIL) populations segregating for rhg1-a and rhg1-b alleles against a SCN HG type 1.2.5.7 (Race 2) population. QTL located on chromosome 18 (rhg1-a) and chromosome 11 (rhg2) were determined to confer SCN resistance in PI 90763. The rhg2 gene was fine-mapped to a 169-Kbp region pinpointing GmSNAP11 as the strongest candidate gene. We demonstrated a unique epistatic interaction between rhg1-a and rhg2 loci that not only confers resistance to multiple virulent SCN populations. Further, we showed that pyramiding rhg2 with the conventional mode of resistance, rhg1-b, is ineffective against these virulent SCN populations. This highlights the importance of pyramiding rhg1-a and rhg2 to maximize the impact of gene pyramiding strategies toward management of SCN populations virulent on rhg1-b sources of resistance. Our results lay the foundation for the next generation of soybean resistance breeding to combat the number one pathogen of soybean.

Key message Software for high imputation accuracy in soybean was identified. Imputed dataset could significantly reduce the interval of genomic regions controlling traits, thus greatly improve the efficiency of candidate gene identification. Abstract Genotype imputation is a strategy to increase marker density of existing datasets without additional genotyping. We compared imputation performance of software BEAGLE 5.0, IMPUTE 5 and AlphaPlantImpute and tested software parameters that may help to improve imputation accuracy in soybean populations. Several factors including marker density, extent of linkage disequilibrium (LD), minor allele frequency (MAF), etc., were examined for their effects on imputation accuracy across different software. Our results showed that AlphaPlantImpute had a higher imputation accuracy than BEAGLE 5.0 or IMPUTE 5 tested in each soybean family, especially if the study progeny were genotyped with an extremely low number of markers. LD extent, MAF and reference panel size were positively correlated with imputation accuracy, a minimum number of 50 markers per chromosome and MAF of SNPs > 0.2 in soybean line were required to avoid a significant loss of imputation accuracy. Using the software, we imputed 5176 soybean lines in the soybean nested mapping population (NAM) with high-density markers of the 40 parents. The dataset containing 423,419 markers for 5176 lines and 40 parents was deposited at the Soybase. The imputed NAM dataset was further examined for the improvement of mapping quantitative trait loci (QTL) controlling soybean seed protein content. Most of the QTL identified were at identical or at similar position based on initial and imputed datasets; however, QTL intervals were greatly narrowed. The resulting genotypic dataset of NAM population will facilitate QTL mapping of traits and downstream applications. The information will also help to improve genotyping imputation accuracy in self-pollinated crops.

We have estimated the average genetic diversity of two Glycine annual and six perennial species based upon 76 orthologous gene sets and performed phylogenetic analysis, divergence analysis and tests for departure from neutrality of the eight species using 52 orthologous gene sets. In addition, 367 orthologous gene sets were used to estimate the relationships of 11 G. canescens accessions. Among the perennials, G. canescens showed the highest nucleotide diversity. The other perennials, except for G. tomentella, had higher nucleotide diversity than the two annuals. Phylogenetic analysis of the Glycine showed a similar genome grouping with the previous report except for G. cyrtoloba and G. stenophita which formed a sister clade in the study. Divergence analysis supported the phylogenetic relationships that G. falcata was the most divergent from G. max, followed by G. cyrtoloba, G. syndetika, G. tomentella D3, G. stenophita and G. canescens. Most genic sequences were homogeneous in the levels of polymorphism and divergence between G. max and other Glycine species based on the HKA test, thus, Glycine perennials may have experienced a very similar evolution as inferred by trans-specific mutation analysis. The greater genetic diversity of most perennial Glycine species and their origins from the warmer and drier climates of Australia suggests the perennials maybe a potential source of heat and drought resistance that will be of value in the face of climate change.

In soybean, only one mitochondrial genome of cultispecies has been completely obtained. To explore the effect of mitochondrial genome on soybean cytoplasmic male sterility (CMS), two CMS lines and three maintainer lines were used for sequencing. Comparative analysis showed that mitochondrial genome of the CMS line was more compact than that of its maintainer line, but genes were highly conserved. Conserved and unique sequence coexisted in the genomes. Mitochondrial genomes contained different sequence lengths and copy numbers of repeats between CMS line and maintainer line. Large and short repeats mediated intramolecular and intermolecular recombination in mitochondria. Unique sequences and genes were also involved in recombination process and constituted a complex network. orf178 and orf261 were identified as CMS-associated candidate genes. They had sequence characteristics of reported CMS genes in other crops and could be transcribed in CMS lines but not in maintainer lines. This report reveals mitochondrial genome of soybean CMS lines and compares complete mitochondrial sequence between CMS lines and their maintainer lines. The information will be helpful in further understanding the characteristics of soybean mitochondrial genome and the mechanism underlying CMS.

Seed oil traits in soybean that are of benefit to human nutrition and health have been selected for during crop domestication. However, these domesticated traits have significant differences across various evolutionary types. In this study, we found that the integration of evolutionary population structure (evolutionary types) with genome-wide association studies increased the power of gene detection, and it identified one locus for traits related to seed size and oil content on chromosome 13. This domestication locus, together with another one in a 200-kb region, was confirmed by the GEMMA and EMMAX software. The candidate gene, GmPDAT, had higher expressional levels in high-oil and large-seed accessions than in low-oil and small-seed accessions. Overexpression lines had increased seed size and oil content, whereas RNAi lines had decreased seed size and oil content. The molecular mechanism of GmPDAT was deduced based on results from linkage analysis for triacylglycerols and on histocytological comparisons of transgenic soybean seeds. Our results illustrate a new approach for identifying domestication genes with pleiotropic effects.

SUMMARY The limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000–2000 genome‐wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based on their position in the soybean genome and haplotype block, polymorphism among accessions and genotyping quality. The assay includes 5000 single nucleotide polymorphisms (SNPs) from euchromatic and 1000 from heterochromatic regions. The percentage of SNPs with minor allele frequency >0.10 was 95% and 91% in the euchromatic and heterochromatic regions, respectively. Analysis of progeny from two large families genotyped with SoySNP50K versus BARCSoySNP6K showed that the position of the common markers and number of unique bins along linkage maps were consistent based on the SNPs genotyped with the two assays; however, the rate of redundant markers was dramatically reduced with the BARCSoySNP6K. The BARCSoySNP6K assay is proven as an excellent tool for detecting quantitative trait loci, genomic selection and assessing genetic relationships. The assay is commercialized by Illumina Inc. and being used by soybean breeders and geneticists and the list of SNPs in the assay is an ideal resource for SNP genotyping by targeted amplicon sequencing., Significance Statement Recombinant events in soybean biparental progeny and among germplasm are low, thus, it is unnecessary to genotype a large number of markers for quantitative trait loci mapping and genomic prediction and genomic selection. An assay containing 6000 SNPs was selected based on analysis of SNP position in soybean genome and haplotype block structure of > 18 000 cultivated soybean accessions. It is used in soybean research and proven efficient for quantitative trait loci detection and breeding selection.

Key message Two major QTLs associated with low seed coat deficiency of soybean seeds were identified in two biparental populations, and three SNP markers were validated to assist low-SCD natto soybean breeding selection. Abstract Soybean seed coat deficiency (SCD), known as seed coat cracking during soaking in the natto production process, is problematic because split or broken beans clog production lines and increases production costs. Development of natto soybean cultivars with low SCD is crucial to support the growth of the natto industry. Unfortunately, information on the genetic control of SCD in soybean, which is desperately needed to facilitate breeding selection, remains sparse. In this study, two F2 populations derived from V11-0883 × V12-1626 (Pop 1) and V11-0883 × V12-1885 (Pop 2) were developed and genotyped with BARCSoySNP6K Beadchips and F2-derived lines were evaluated for SCD in three consecutive years (2016–2018) in order to identify quantitative trait loci (QTLs) associated with low SCD in soybean. A total of 17 QTLs underlying SCD were identified in two populations. Among these, two major and stable QTLs, qSCD15 on chromosome 15 and qSCD20 on chromosome 20, were detected across multiple years. These QTLs explained up to 30.3% of the phenotypic variation for SCD in Pop 1 and 6.1% in Pop 2 across years. Three SNP markers associated with the qSCD20 were validated in additional four biparental populations. The average selection efficiency of low-SCD soybean was 77% based on two tightly linked markers, Gm20_34626867 and Gm20_34942502, and 64% based on the marker Gm20_35625615. The novel and stable QTLs identified in this study will facilitate elucidation of the genetic mechanism controlling SCD in soybean, and the markers will significantly accelerate breeding for low-SCD soybean through marker-assisted selection.

The soybean E1 gene is a major regulator that plays an important role in flowering time and maturity. However, it remains unclear how cultivars carrying the dominant E1 allele adapt to the higher latitudinal areas of northern China. We mapped the novel quantitative trait locus QNE1 (QTL near E1) for flowering time to the region proximal to E1 on chromosome 6 in two mapping populations. Positional cloning revealed Glyma.06G204300, encoding a TCP-type transcription factor, as a strong candidate gene for QNE1. Association analysis further confirmed that functional single nucleotide polymorphisms (SNPs) at nucleotides 686 and 1,063 in the coding region of Glyma.06G204300 were significantly associated with flowering time. The protein encoded by the candidate gene is localized primarily to the nucleus. Furthermore, soybean and Brassica napus plants overexpressing Glyma.06G204300 exhibited early flowering. We conclude that despite their similar effects on flowering time, QNE1 and E4 may control flowering time through different regulatory mechanisms, based on expression studies and weighted gene co-expression network analysis of flowering time-related genes. Deciphering the molecular basis of QNE1 control of flowering time enriches our knowledge of flowering gene networks in soybean and will facilitate breeding soybean cultivars with broader latitudinal adaptation.

Independent soybean breeding programs shape genetic diversity from unimproved germplasm to modern cultivars in similar ways, but distinct breeding populations retain unique genetic variation, preserving additional diversity. From the domestication of wild soybean (Glycine soja Sieb.Zucc.), over 3,000 years ago, to the modern soybean (Glycine max L. Merr) cultivars that provide much of the world's oil and protein, soybean populations have undergone fundamental changes. We evaluated the molecular impact of breeding and selection using 391 soybean accessions including US cultivars and their progenitors from the USDA Soybean Germplasm Collection (CGP), plus two new populations specifically developed to increase genetic diversity and high yield in two alternative gene pools: one derived from exotic G. max germplasm (AGP) and one derived from G. soja (SGP). Reduction in nucleotide genetic diversity (π) was observed with selection within gene pools, but artificial selection in the AGP maintained more diversity than in the CGP. The highest F

Background With advances in next-generation sequencing technologies, an unprecedented amount of soybean accessions has been sequenced by many individual studies and made available as raw sequencing reads for post-genomic research. Results To develop a consolidated and user-friendly genomic resource for post-genomic research, we consolidated the raw resequencing data of 1465 soybean genomes available in the public and 91 highly diverse wild soybean genomes newly sequenced. These altogether provided a collection of 1556 sequenced genomes of 1501 diverse accessions (1.5 K). The collection comprises of wild, landraces and elite cultivars of soybean that were grown in East Asia or major soybean cultivating areas around the world. Our extensive sequence analysis discovered 32 million single nucleotide polymorphisms (32mSNPs) and revealed a SNP density of 30 SNPs/kb and 12 non-synonymous SNPs/gene reflecting a high structural and functional genomic diversity of the new collection. Each SNP was annotated with 30 categories of structural and/or functional information. We further identified paired accessions between the 1.5 K and 20,087 (20 K) accessions in US collection as genomic “equivalent” accessions sharing the highest genomic identity for minimizing the barriers in soybean germplasm exchange between countries. We also exemplified the utility of 32mSNPs in enhancing post-genomics research through in-silico genotyping, high-resolution GWAS, discovering and/or characterizing genes and alleles/mutations, identifying germplasms containing beneficial alleles that are potentially experiencing artificial selection. Conclusion The comprehensive analysis of publicly available large-scale genome sequencing data of diverse cultivated accessions and the newly in-house sequenced wild accessions greatly increased the soybean genome-wide variation resolution. This could facilitate a variety of genetic and molecular-level analyses in soybean. The 32mSNPs and 1.5 K accessions with their comprehensive annotation have been made available at the SoyBase and Ag Data Commons. The dataset could further serve as a versatile and expandable core resource for exploring the exponentially increasing genome sequencing data for a variety of post-genomic research.

Trypsin inhibitors (TI), a common anti-nutritional factor in soybean, prevent animals’ protein digestibility reducing animal growth performance. No commercial soybean cultivars with low or null concentration of TI are available. The availability of a high throughput genotyping assay will be beneficial to incorporate the low TI trait into elite breeding lines. The aim of this study is to develop and validate a breeder friendly Kompetitive Allele Specific PCR (KASP) assay linked to low Kunitz trypsin inhibitor (KTI) in soybean seeds. A total of 200 F3:5 lines derived from PI 547656 (low KTI) X Glenn (normal KTI) were genotyped using the BARCSoySNP6K_v2 Beadchip. F3:4 and F3:5 lines were grown in Blacksburg and Orange, Virginia in three years, respectively, and were measured for KTI content using a quantitative HPLC method. We identified three SNP markers tightly linked to the major QTL associated to low KTI in the mapping population. Based on these SNPs, we developed and validated the KASP assays in a set of 93 diverse germplasm accessions. The marker Gm08_44814503 has 86% selection efficiency for the accessions with low KTI and could be used in marker assisted breeding to facilitate the incorporation of low KTI content in soybean seeds.

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

Soybean [Glycine max (L.) Merr.] is a crop of great interest worldwide. Exploring molecular approaches to increase yield genetic gain has been one of the main challenges for soybean breeders and geneticists. Agronomic traits such as maturity, plant height, and seed weight have been found to contribute to yield. In this study, a total of 250 soybean accessions were genotyped with 10,259 high-quality SNPs postulated from genotyping by sequencing (GBS) and evaluated for grain yield, maturity, plant height, and seed weight over three years. A genome-wide association study (GWAS) was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model. Genomic selection (GS) was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that 20, 31, 37, and 23 SNPs were significantly associated with maturity, plant height, seed weight, and yield, respectively; Many SNPs were mapped to previously described maturity and plant height loci (E2,E4, andDt1) and a new plant height locus was mapped to chromosome 20. Candidate genes were found in the vicinity of the two SNPs with the highest significant levels associated with yield, maturity, plant height, seed weight, respectively. A 11.5-Mb region of chromosome 10 was associated with both yield and seed weight. Overall, the accuracy of GS was dependent on the trait, year, and population structure, and high accuracy indicates that these agronomic traits can be selected in molecular breeding through GS. The SNP markers identified in this study can be used to improve yield and agronomic traits through the marker-assisted selection and GS in breeding programs.

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.

Seed protein, oil content and yield are highly correlated agronomically important traits that essentially account for the economic value of soybean. The underlying molecular mechanisms and selection of these correlated seed traits during soybean domestication are, however, less known. Here, we demonstrate that a CCT gene, POWR1, underlies a large-effect protein/oil QTL. A causative TE insertion truncates its CCT domain and substantially increases seed oil content, weight, and yield while decreasing protein content. POWR1 pleiotropically controls these traits likely through regulating seed nutrient transport and lipid metabolism genes. POWR1 is also a domestication gene. We hypothesize that the TE insertion allele is exclusively fixed in cultivated soybean due to selection for larger seeds during domestication, which significantly contributes to shaping soybean with increased yield/seed weight/oil but reduced protein content. This study provides insights into soybean domestication and is significant in improving seed quality and yield in soybean and other crop species.

Soybean is the world’s leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding.

Summary White mould of soya bean, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is a necrotrophic fungus capable of infecting a wide range of plants. To dissect the genetic architecture of resistance to white mould, a high‐density customized single nucleotide polymorphism (SNP) array (52 041 SNPs) was used to genotype two soya bean diversity panels. Combined with resistance variation data observed in the field and greenhouse environments, genome‐wide association studies (GWASs) were conducted to identify quantitative trait loci (QTL) controlling resistance against white mould. Results showed that 16 and 11 loci were found significantly associated with resistance in field and greenhouse, respectively. Of these, eight loci localized to previously mapped QTL intervals and one locus had significant associations with resistance across both environments. The expression level changes in genes located in GWAS‐identified loci were assessed between partially resistant and susceptible genotypes through a RNA‐seq analysis of the stem tissue collected at various time points after inoculation. A set of genes with diverse biological functionalities were identified as strong candidates underlying white mould resistance. Moreover, we found that genomic prediction models outperformed predictions based on significant SNPs. Prediction accuracies ranged from 0.48 to 0.64 for disease index measured in field experiments. The integrative methods, including GWAS, RNA‐seq and genomic selection (GS), applied in this study facilitated the identification of causal variants, enhanced our understanding of mechanisms of white mould resistance and provided valuable information regarding breeding for disease resistance through genomic selection in soya bean.

Background Ozone is an air pollutant widely known to cause a decrease in productivity in many plant species, including soybean (Glycine max (L.) Merr). While the response of cultivated soybean to ozone has been studied, very little information is available regarding the ozone response of its wild relatives. Results Ozone-resistant wild soybean accessions were identified by measuring the response of a genetically diverse group of 66 wild soybean (Glycine soja Zucc. and Sieb.) accessions to elevated ozone levels. RNA-Seq analyses were performed on leaves of different ages from selected ozone-sensitive and ozone-resistant accessions that were subjected to treatment with an environmentally relevant level of ozone. Many more genes responded to elevated ozone in the two ozone-sensitive accessions than in the ozone-resistant accessions. Analyses of the ozone response genes indicated that leaves of different ages responded differently to ozone. Older leaves displayed a consistent reduction in expression of genes involved in photosynthesis in response to ozone, while changes in expression of defense genes dominated younger leaf tissue in response to ozone. As expected, there is a substantial difference between the response of ozone-sensitive and ozone-resistant accessions. Genes associated with photosystem 2 were substantially reduced in expression in response to ozone in the ozone-resistant accessions. A decrease in peptidase inhibitors was one of several responses specific to one of the ozone resistant accessions. Conclusion The decrease in expression in genes associated with photosynthesis confirms that the photosynthetic apparatus may be an early casualty in response to moderate levels of ozone. A compromise of photosynthesis would substantially impact plant growth and seed production. However, the resistant accessions may preserve their photosynthetic apparatus in response to the ozone levels used in this study. Older leaf tissue of the ozone-resistant accessions showed a unique down-regulation of genes associated with endopeptidase inhibitor activity. This study demonstrates the existence of significant diversity in wild soybean for ozone response. Wild soybean accessions characterized in this study can be used by soybean breeders to enhance ozone tolerance of this important food crop. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3876-2) contains supplementary material, which is available to authorized users.

DNA methylation is a widespread epigenetic mark that contributes to transcriptome reprogramming during plant-pathogen interactions. However, the distinct role of DNA methylation in establishing resistant and susceptible responses remains largely unexplored. Here, we developed and used a pair of near-isogenic lines (NILs) to characterize DNA methylome landscapes of soybean roots during the susceptible and resistant interactions with soybean cyst nematode (SCN; Heterodera glycines). We also compared the methylomes of the NILs and their parents to identify introduced and stably inherited methylation variants. The genomes of the NILs were substantially differentially methylated under uninfected conditions. This difference was associated with differential gene expression that may prime the NIL responses to SCN infection. In response to SCN infection, the susceptible line exhibited reduced global methylation levels in both protein-coding genes and transposable elements, whereas the resistant line showed the opposite response, increased global methylation levels. Heritable and novel nonparental differentially methylated regions overlapping with genes associated with soybean response to SCN infection were identified and validated using transgenic hairy root system. Our analyses indicate that DNA methylation patterns associated with the susceptible and resistant interactions are highly specific and that novel and stably inherited methylation variants are of biological significance.

Symbiosis between soybean (Glycine max) and rhizobia is essential for efficient nitrogen fixation. Rhizobial effectors secreted through the type-III secretion system are key for mediating the interactions between plants and rhizobia, but the molecular mechanism remains largely unknown. Here, our genome-wide association study for nodule number identified G. max Nodule Number Locus 1 (GmNNL1), which encodes a new R protein. GmNNL1 directly interacts with the nodulation outer protein P (NopP) effector from Bradyrhizobium USDA110 to trigger immunity and inhibit nodulation through root hair infection. The insertion of a 179 bp short interspersed nuclear element (SINE)-like transposon into GmNNL1 leads to the loss of function of GmNNL1, enabling bradyrhizobia to successfully nodulate soybeans through the root hair infection route and enhancing nitrogen fixation. Our findings provide important insights into the coevolution of soybean-bradyrhizobia compatibility and offer a way to design new legume-rhizobia interactions for efficient symbiotic nitrogen fixation.

Glycine soja germplasm can be used to successfully introduce new alleles with the potential to add valuable new genetic diversity to the current elite soybean gene pool. Given the demonstrated narrow genetic base of the US soybean production, it is essential to identify beneficial alleles from exotic germplasm, such as wild soybean, to enhance genetic gain for favorable traits. Nested association mapping (NAM) is an approach to population development that permits the comparison of allelic effects of the same QTL in multiple parents. Seed yield, plant maturity, plant height and plant lodging were evaluated in a NAM panel consisting of 392 recombinant inbred lines derived from three biparental interspecific soybean populations in eight environments during 2016 and 2017. Nested association mapping, combined with linkage mapping, identified three major QTL for plant maturity in chromosomes 6, 11 and 12 associated with alleles from wild soybean resulting in significant increases in days to maturity. A significant QTL for plant height was identified on chromosome 13 with the allele increasing plant height derived from wild soybean. A significant grain yield QTL was detected on chromosome 17, and the allele from Glycine soja had a positive effect of 166 kg ha

Abnormal reactive oxygen species (ROS) may mediate cytoplasmic male sterility (CMS). To observe the effect of ROS on soybean CMS, metabolite content and antioxidant enzyme activity in the flower buds between soybean N8855-derived CMS line and its maintainer were compared. Of the 612 metabolites identified, a total of 74 metabolites were significantly differentiated in flower buds between CMS line and its maintainer. The differential metabolites involved 32 differential flavonoids, 13 differential phenolamides, and 1 differential oxidized glutathione (GSSG) belonging to a non-enzymatic ROS scavenging system. We observed lower levels of flavonoids and antioxidant enzyme activities in flower buds of the CMS line than in its maintainer. Our results suggest that deficiencies of enzymatic and non-enzymatic ROS scavenging systems in soybean CMS line cannot eliminate ROS in anthers effectively, excessive accumulation of ROS triggered programmed cell death and ultimately resulted in pollen abortion of soybean CMS line.

Genomic selection (GS) has become viable for selection of quantitative traits for which marker-assisted selection has often proven less effective. The potential of GS for soybean was characterized using 483 elite breeding lines, genotyped with BARCSoySNP6K iSelect BeadChips. Cross validation was performed using RR-BLUP and predictive abilities (rMP) of 0.81, 0.71, and 0.26 for protein, oil, and yield, were achieved at the largest tested training set size. Minimal differences were observed when comparing different marker densities and there appeared to be inflation in rMP due to population structure. For comparison purposes, two additional methods to predict breeding values for lines of four bi-parental populations within the GS dataset were tested. The first method predicted within each bi-parental population (WP method) and utilized a training set of full-sibs of the validation set. The second method utilized a training set of all remaining breeding lines except for full-sibs of the validation set to predict across populations (AP method). The AP method is more practical as the WP method would likely delay the breeding cycle and leverage smaller training sets. Averaging across populations for protein and oil content, rMP for the AP method (0.55, 0.30) approached rMP for the WP method (0.60, 0.52). Though comparable, rMP for yield was low for both AP and WP methods (0.12, 0.13). Based on increases in rMP as training sets increased and the effectiveness of WP vs. AP method, the AP method could potentially improve with larger training sets and increased relatedness between training and validation sets.

Plant breeders continually generate ever-higher yielding cultivars, but also want to improve seed constituent value, which is mainly protein and oil, in soybean [Glycine max (L.) Merr.]. Identification of genetic loci governing those two traits would facilitate that effort. Though genome-wide association offers one such approach, selective genotyping of multiple biparental populations offers a complementary alternative, and was evaluated here, using 48 F2:3 populations (n = ∼224 plants) created by mating 48 high protein germplasm accessions to cultivars of similar maturity, but with normal seed protein content. All F2:3 progeny were phenotyped for seed protein and oil, but only 22 high and 22 low extreme progeny in each F2:3 phenotypic distribution were genotyped with a 1536-SNP chip (ca. 450 bimorphic SNPs detected per mating). A significant quantitative trait locus (QTL) on one or more chromosomes was detected for protein in 35 (73%), and for oil in 25 (52%), of the 48 matings, and these QTL exhibited additive effects of ≥ 4 g kg–1 and R2 values of 0.07 or more. These results demonstrated that a multiple-population selective genotyping strategy, when focused on matings between parental phenotype extremes, can be used successfully to identify germplasm accessions possessing large-effect QTL alleles. Such accessions would be of interest to breeders to serve as parental donors of those alleles in cultivar development programs, though 17 of the 48 accessions were not unique in terms of SNP genotype, indicating that diversity among high protein accessions in the germplasm collection is less than what might ordinarily be assumed.

Soybean [Glycine max (L.) Merr.] was domesticated from wild soybean (G. soja Sieb. and Zucc.) and has been further improved as a dual-use seed crop to provide highly valuable oil and protein for food, feed, and industrial applications. However, the underlying genetic and molecular basis remains less understood. Having combined high-confidence bi-parental linkage mapping with high-resolution association analysis based on 631 whole sequenced genomes, we mapped major soybean protein and oil QTLs on chromosome15 to a sugar transporter gene (GmSWEET39). A two-nucleotide CC deletion truncating C-terminus of GmSWEET39 was strongly associated with high seed oil and low seed protein, suggesting its pleiotropic effect on protein and oil content. GmSWEET39 was predominantly expressed in parenchyma and integument of the seed coat, and likely regulates oil and protein accumulation by affecting sugar delivery from maternal seed coat to the filial embryo. We demonstrated that GmSWEET39 has a dual function for both oil and protein improvement and undergoes two different paths of artificial selection. A CC deletion (CC-) haplotype H1 has been intensively selected during domestication and extensively used in soybean improvement worldwide. H1 is fixed in North American soybean cultivars. The protein-favored (CC+) haplotype H3 still undergoes ongoing selection, reflecting its sustainable role for soybean protein improvement. The comprehensive knowledge on the molecular basis underlying the major QTL and GmSWEET39 haplotypes associated with soybean improvement would be valuable to design new strategies for soybean seed quality improvement using molecular breeding and biotechnological approaches., Author summary We map highly effective protein and oil QTLs to a seed coat-preferentially expressed sugar transporter (GmSWEET39) gene by a combination of association analysis based on 631 whole-genome sequencing data and a bi-parental linkage mapping, proving that GmSWEET39 has pleiotropic associations with two of the most important soybean traits, seed protein and oil. A 2-bp (CC) deletion in GmSWEET39 is associated with higher seed oil and lower seed protein, and has been extensively selected and used worldwide, likely for higher oil. The intensive use or fixation of the CC deletion in soybean breeding result in low protein in current soybean cultivars, which is a big problem facing the current soybean industry. The knowledge about the genetic basis and identification of two major haplotypes for high protein and high oil should be highly significant to address the issue related to low protein in the current soybean industry and meet dramatically increasing need for plant-based protein in the food industry. Our successful integrative and "big-data-driven” approach, which uses the huge amount of genome and transcriptome sequencing and phenotypic data available in the community, should provide an effective case study for post-genomic data-driven research.

Slow canopy wilting (SW) is a water conservation trait controlled by quantitative trait loci (QTLs) in late maturity group soybeans [Glycine max (L.) Merr.]. Recently, two exotic (landraces) plant introductions (PI 567690 and PI 567731) were identified as new SW lines in early maturity groups. Here, we show that the two PIs share the same water conservation strategy of limited maximum transpiration rates as PI 416937. However, in contrast to PI 416937, the transpiration rates of these PIs were sensitive to an aquaporin inhibitor, indicating an independence between limited maximum transpiration and the lack of silver-sensitive aquaporins. Yield tests of selected recombinant inbred lines from two elite/exotic crosses provide direct evidence to support the benefit of SW in drought tolerance. Four SW QTLs mapped in a Pana×PI 567690 cross at multiple environments were found to be co-located with previous reports. Moreover, two new SW QTLs were mapped on chromosomes 6 and 10 from a Magellan×PI 567731 cross. These two QTLs explain the observed relatively large contributions of 20-30% and were confirmed in a near-isogenic background. These findings demonstrate the importance of SW in yield protection under drought and provide genetic resources for improving drought tolerance in early maturity group soybeans.

Background Cytoplasmic male sterility (CMS) is a natural phenomenon of pollen abortion caused by the interaction between cytoplasmic genes and nuclear genes. CMS is a simple and effective pollination control system, and plays an important role in crop heterosis utilization. Circular RNAs (circRNAs) are a vital type of non-coding RNAs, which play crucial roles in microRNAs (miRNAs) function and post-transcription control. To explore the expression profile and possible functions of circRNAs in the soybean CMS line NJCMS1A and its maintainer NJCMS1B, high-throughput deep sequencing coupled with RNase R enrichment strategy was conducted. Results CircRNA libraries were constructed from flower buds of NJCMS1A and its maintainer NJCMS1B with three biological replicates. A total of 2867 circRNAs were identified, with 1009 circRNAs differentially expressed between NJCMS1A and NJCMS1B based on analysis of high-throughput sequencing. Of the 12 randomly selected circRNAs with different expression levels, 10 showed consistent expression patterns based on high-throughput sequencing and quantitative real-time PCR analyses. Tissue specific expression patterns were also verified with two circRNAs by quantitative real-time PCR. Most parental genes of differentially expressed circRNAs were mainly involved in biological processes such as metabolic process, biological regulation, and reproductive process. Moreover, 83 miRNAs were predicted from the differentially expressed circRNAs, some of which were strongly related to pollen development and male fertility; The functions of miRNA targets were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and the target mRNAs were significantly enriched in signal transduction and programmed cell death. Furthermore, a total of 165 soybean circRNAs were predicted to contain at least one internal ribosome entry site (IRES) element and an open reading frame, indicating their potential to encode polypeptides or proteins. Conclusions Our study indicated that the circRNAs might participate in the regulation of flower and pollen development, which could provide a new insight into the molecular mechanisms of CMS in soybean. Electronic supplementary material The online version of this article (10.1186/s12864-018-5054-6) contains supplementary material, which is available to authorized users.

Different loci associated with root resistance to F. virguliforme colonization and foliar resistance to phytotoxin damage in soybean. Use of resistant cultivars is the most efficacious approach to manage soybean sudden death syndrome (SDS), caused by Fusarium virguliforme. The objectives of this study were to (1) map the loci associated with root and foliar resistance to F. virguliforme infection and (2) decipher the relationships between root infection, foliar damage, and plot yield. A mapping population consisting of 153 F4-derived recombinant inbred lines from the cross U01-390489 × E07080 was genotyped by SoySNP6 K BeadChip assay. Both foliar damage and F. virguliforme colonization in roots were investigated in the field, and a weak positive correlation was identified between them. Foliar damage had a stronger negative correlation with plot yield than F. virguliforme colonization. Twelve loci associated with foliar damage were identified, and four of them were associated with multiple traits across environments. In contrast, only one locus associated with root resistance to F. virguliforme colonization was identified and mapped on Chromosome 18. It colocalized with the locus associated with foliar damage in the same environment. The locus on Chromosome 6, qSDS6-2, and the locus on Chromosome 18, qSDS18-1, were associated with resistance to SDS phytotoxins and resistance to F. virguliforme colonization of roots, respectively. Both loci affected plot yield. Foliar damage-related traits, especially disease index, are valuable indicators for SDS resistance breeding because of consistency of the identified loci and their stronger correlation with plot yield. The information provided by this study will facilitate marker-assisted selection to improve SDS resistance in soybean.

Using a combination of phenotypic screening and molecular, statistical, and linkage analyses, we have mapped a dominant soybean rust resistance gene in soybean PI 567104B. Asian soybean rust (SBR), caused by the fungus Phakopsora pachyrhizi Syd. and P. Syd., is one of the most economically important diseases that affect soybean production worldwide. A long-term strategy for minimizing the effects of SBR is the development of genetically resistant cultivars. The objectives of the study were to identify the location of a rust-resistance (Rpp) gene(s) in plant introduction (PI) 567104B, and to determine if the gene(s) in PI 567104B was different from previously mapped Rpp loci. The progeny of the cross of 'IAR 2001 BSR' × PI 567104B was phenotyped from field assays of the F 2:3 and F 4:5 generations and from a growth chamber assay of 253 F 5:6 recombinant inbred lines (RILs). For the growth chamber, the phenotyping was conducted by inoculation with a purified 2006 fungal isolate from Mississippi. A resistance gene locus on PI 567104B was mapped to a region containing the Rpp6 locus on chromosome 18. The high level of resistance of F 1 plants from two other crosses with PI 567104B as one of the parents indicated that the gene from PI 567104B was dominant. The interval containing the gene is flanked by the simple sequence repeat (SSR) markers Satt131 and Satt394, and includes the SSR markers BARCSOYSSR_18_0331 and BARCSOYSSR_18_0380. The results also indicated that the resistance gene from PI 567104B is different from the Rpp1 to the Rpp4 genes previously identified. To determine if the gene from PI 567104B is different from the Rpp6 gene from PI 567102B, additional research will be required.

There is limited information on the influence of genetic and environmental variability on soybean protein composition. This study aimed to determine the role of genotype (G), environments (E), and the interrelationship of genotype and environment (G×E) on soybean seed protein. Three sets of nine soybean genotypes were grown in replicated trials at Maryland, South Carolina, and South Dakota. At each location, the nine genotypes were grown with two planting/sowing dates. We applied two-dimensional gel electrophoresis and mass spectrometry to study the variability of soybean storage and allergen proteins. Statistical analysis of 47 storage and 8 allergen proteins, in terms of differentially expressed protein spots significant at the p

Ureides are the N-rich products of N-fixation that are transported from soybean nodules to the shoot. Ureides are known to accumulate in leaves in response to water-deficit stress, and this has been used to identify genotypes with reduced N-fixation sensitivity to drought. Our objectives in this research were to determine shoot ureide concentrations in 374 Maturity Group IV soybean accessions and to identify genomic regions associated with shoot ureide concentration. The accessions were grown at two locations (Columbia, MO, and Stuttgart, AR) in 2 yr (2009 and 2010) and characterized for ureide concentration at beginning flowering to full bloom. Average shoot ureide concentrations across all four environments (two locations and two years) and 374 accessions ranged from 12.4 to 33.1 µmol g−1 and were comparable to previously reported values. SNP–ureide associations within and across the four environments were assessed using 33,957 SNPs with a MAF ≥0.03. In total, 53 putative loci on 18 chromosomes were identified as associated with ureide concentration. Two of the putative loci were located near previously reported QTL associated with ureide concentration and 30 loci were located near genes associated with ureide metabolism. The remaining putative loci were not near chromosomal regions previously associated with shoot ureide concentration and may mark new genes involved in ureide metabolism. Ultimately, confirmation of these putative loci will provide new sources of variation for use in soybean breeding programs.

The United States Department of Agriculture, Soybean Germplasm Collection includes 18,480 domesticated soybean and 1168 wild soybean accessions introduced from 84 countries or developed in the United States. This collection was genotyped with the SoySNP50K BeadChip containing greater than 50K single-nucleotide polymorphisms. Redundant accessions were identified in the collection, and distinct genetic backgrounds of soybean from different geographic origins were observed that could be a unique resource for soybean genetic improvement. We detected a dramatic reduction of genetic diversity based on linkage disequilibrium and haplotype structure analyses of the wild, landrace, and North American cultivar populations and identified candidate regions associated with domestication and selection imposed by North American breeding. We constructed the first soybean haplotype block maps in the wild, landrace, and North American cultivar populations and observed that most recombination events occurred in the regions between haplotype blocks. These haplotype maps are crucial for association mapping aimed at the identification of genes controlling traits of economic importance. A case-control association test delimited potential genomic regions along seven chromosomes that most likely contain genes controlling seed weight in domesticated soybean. The resulting dataset will facilitate germplasm utilization, identification of genes controlling important traits, and will accelerate the creation of soybean varieties with improved seed yield and quality.

Genetic improvement toward optimized and stable agronomic performance of soybean genotypes is desirable for food security. Understanding how genotypes perform in different environmental conditions helps breeders develop sustainable cultivars adapted to target regions. Complex traits of importance are known to be controlled by a large number of genomic regions with small effects whose magnitude and direction are modulated by environmental factors. Knowledge of the constraints and undesirable effects resulting from genotype by environmental interactions is a key objective in improving selection procedures in soybean breeding programs. In this study, the genetic basis of soybean grain yield responsiveness to environmental factors was examined in a large soybean nested association population. For this, a genome-wide association to performance stability estimates generated from a Finlay-Wilkinson analysis and the inclusion of the interaction between marker genotypes and environmental factors was implemented. Genomic footprints were investigated by analysis and meta-analysis using a recently published multiparent model. Results indicated that specific soybean genomic regions were associated with stability, and that multiplicative interactions were present between environments and genetic background. Seven genomic regions in six chromosomes were identified as being associated with genotype-by-environment interactions. This study provides insight into genomic assisted breeding aimed at achieving a more stable agronomic performance of soybean, and documented opportunities to exploit genomic regions that were specifically associated with interactions involving environments and subpopulations.

Phytophthora sojae, an oomycete pathogen of soybean, causes stem and root rot, resulting in annual economic loss up to $2 billion worldwide. Varieties with P. sojae resistance are environmental friendly to effectively reduce disease damages. In order to improve the resistance of P. sojae and broaden the genetic diversity in Southern soybean cultivars and germplasm in the U.S., we established a P. sojae resistance gene pool that has high genetic diversity, and explored genomic regions underlying the host resistance to P. sojae races 1, 3, 7, 17 and 25. A soybean germplasm panel from maturity groups (MGs) IV and V including 189 accessions originated from 10 countries were used in this study. The panel had a high genetic diversity compared to the 6,749 accessions from MGs IV and V in USDA Soybean Germplasm Collection. Based on disease evaluation dataset of these accessions inoculated with P. sojae races 1, 3, 7, 17 and 25, which are publically available, five accessions in this panel were resistant to all races. Genome-wide association analysis identified a total of 32 significant SNPs, which were clustered in resistance-associated genomic regions, among those, ss715619920 was only 3kb away from the gene Glyma.14g087500, a subtilisin protease. Gene expression analysis showed that the gene was down-regulated more than 4 fold (log2 fold > 2.2) in response to P. sojae infection. The identified molecular markers and genomic regions that are associated with the disease resistance in this gene pool will greatly assist the U.S. Southern soybean breeders in developing elite varieties with broad genetic background and P. sojae resistance.

A set of nested association mapping (NAM) families was developed by crossing 40 diverse soybean [ (L.) Merr.] genotypes to the common cultivar. The 41 parents were deeply sequenced for SNP discovery. Based on the polymorphism of the single-nucleotide polymorphisms (SNPs) and other selection criteria, a set of SNPs was selected to be included in the SoyNAM6K BeadChip for genotyping the parents and 5600 RILs from the 40 families. Analysis of the SNP profiles of the RILs showed a low average recombination rate. We constructed genetic linkage maps for each family and a composite linkage map based on recombinant inbred lines (RILs) across the families and identified and annotated 525,772 high confidence SNPs that were used to impute the SNP alleles in the RILs. The segregation distortion in most families significantly favored the alleles from the female parent, and there was no significant difference of residual heterozygosity in the euchromatic vs. heterochromatic regions. The genotypic datasets for the RILs and parents are publicly available and are anticipated to be useful to map quantitative trait loci (QTL) controlling important traits in soybean.

Background Soybean (Glycine max (L.) Merr.) is a short day plant. Its flowering and maturity time are controlled by genetic and environmental factors, as well the interaction between the two factors. Previous studies have shown that both genetic and environmental factors, mainly photoperiod and temperature, control flowering time of soybean. Additionally, these studies have reported gene × gene and gene × environment interactions on flowering time. However, the effects of quantitative trait loci (QTL) in response to photoperiod and temperature have not been well evaluated. The objectives of the current study were to identify the effects of loci associated with flowering time under different photo-thermal conditions and to understand the effects of interaction between loci and environment on soybean flowering. Methods Different photoperiod and temperature combinations were obtained by adjusting sowing dates (spring sowing and summer sowing) or day-length (12 h, 16 h). Association mapping was performed on 91 soybean cultivars from different maturity groups (MG000-VIII) using 172 SSR markers and 5107 SNPs from the Illumina SoySNP6K iSelectBeadChip. The effects of the interaction between QTL and environments on flowering time were also analysed using the QTXNetwork. Results Large-effect loci were detected on Gm 11, Gm 16 and Gm 20 as in previous reports. Most loci associated with flowering time are sensitive to photo-thermal conditions. Number of loci associated with flowering time was more under the long day (LD) than under the short day (SD) condition. The variation of flowering time among the soybean cultivars mostly resulted from the epistasis × environment and additive × environment interactions. Among the three candidate loci, i.e. Gm04_4497001 (near GmCOL3a), Gm16_30766209 (near GmFT2a and GmFT2b) and Gm19_47514601 (E3 or GmPhyA3), the Gm04_4497001 may be the key locus interacting with other loci for controlling soybean flowering time. Conclusion The effects of loci associated with the flowering time of soybean were dependent upon the photo-thermal conditions. This study facilitates the understanding of the genetic mechanism of soybean flowering and molecular breeding for the improvement of soybean adaptability to specific and/or broad regions. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3778-3) contains supplementary material, which is available to authorized users.

Rag6 and Rag3c were delimited to a 49-kb interval on chromosome 8 and a 150-kb interval on chromosome 16, respectively. Structural variants in the exons of candidate genes were identified. The soybean aphid, an invasive species, has significantly threatened soybean production in North America since 2000. Host-plant resistance is known as an ideal management strategy for aphids. Two novel aphid-resistance loci, Rag6 and Rag3c, from Glycine soja 85-32, were previously detected in a 10.5-cM interval on chromosome 8 and a 7.5-cM interval on chromosome 16, respectively. Defining the exact genomic position of these two genes is critical for improving the effectiveness of marker-assisted selection for aphid resistance and for identification of the functional genes. To pinpoint the locations of Rag6 and Rag3c, four populations segregating for Rag6 and Rag3c were used to fine map these two genes. The availability of the Illumina Infinium SoySNP50K/8K iSelect BeadChip, combined with single-nucleotide polymorphism (SNP) markers discovered through the whole-genome re-sequencing of E12901, facilitated the fine mapping process. Rag6 was refined to a 49-kb interval on chromosome 8 with four candidate genes, including three clustered nucleotide-binding site leucine-rich repeat (NBS–LRR) genes and an amine oxidase encoding gene. Rag3c was refined to a 150-kb interval on chromosome 16 with 11 candidate genes, two of which are a LRR gene and a lipase gene. Moreover, by sequencing the whole-genome exome-capture of the resistant source (E12901), structural variants were identified in the exons of the candidate genes of Rag6 and Rag3c. The closely linked SNP markers and the candidate gene information presented in this study will be significant resources for integrating Rag6 and Rag3c into elite cultivars and for future functional genetics studies.

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. Abstract Meal 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 material The online version of this article (doi:10.1007/s00122-017-2955-8) contains supplementary material, which is available to authorized users.

Using genome-wide association studies, 39 SNP markers likely tagging 21 different loci for carbon isotope ratio (δ (13) C) were identified in soybean. Water deficit stress is a major factor limiting soybean [Glycine max (L.) Merr.] yield. Soybean genotypes with improved water use efficiency (WUE) may be used to develop cultivars with increased yield under drought. A collection of 373 diverse soybean genotypes was grown in four environments (2 years and two locations) and characterized for carbon isotope ratio (δ(13)C) as a surrogate measure of WUE. Population structure was assessed based on 12,347 single nucleotide polymorphisms (SNPs), and genome-wide association studies (GWAS) were conducted to identify SNPs associated with δ(13)C. Across all four environments, δ(13)C ranged from a minimum of -30.55‰ to a maximum of -27.74‰. Although δ(13)C values were significantly different between the two locations in both years, results were consistent among genotypes across years and locations. Diversity analysis indicated that eight subpopulations could contain all individuals and revealed that within-subpopulation diversity, rather than among-subpopulation diversity, explained most (80%) of the diversity among the 373 genotypes. A total of 39 SNPs that showed a significant association with δ(13)C in at least two environments or for the average across all environments were identified by GWAS. Fifteen of these SNPs were located within a gene. The 39 SNPs likely tagged 21 different loci and demonstrated that markers for δ(13)C can be identified in soybean using GWAS. Further research is necessary to confirm the marker associations identified and to evaluate their usefulness for selecting genotypes with increased WUE.

Soybean oil and meal are major contributors to world-wide food production. Consequently, the genetic basis for soybean seed composition has been intensely studied using family-based mapping. Population-based mapping approaches, in the form of genome-wide association (GWA) scans, have been able to resolve loci controlling moderately complex quantitative traits (QTL) in numerous crop species. Yet, it is still unclear how soybean’s unique population history will affect GWA scans. Using one of the populations in this study, we simulated phenotypes resulting from a range of genetic architectures. We found that with a heritability of 0.5, ∼100% and ∼33% of the 4 and 20 simulated QTL can be recovered, respectively, with a false-positive rate of less than ∼6×10−5 per marker tested. Additionally, we demonstrated that combining information from multi-locus mixed models and compressed linear-mixed models improves QTL identification and interpretation. We applied these insights to exploring seed composition in soybean, refining the linkage group I (chromosome 20) protein QTL and identifying additional oil QTL that may allow some decoupling of highly correlated oil and protein phenotypes. Because the value of protein meal is closely related to its essential amino acid profile, we attempted to identify QTL underlying methionine, threonine, cysteine, and lysine content. Multiple QTL were found that have not been observed in family-based mapping studies, and each trait exhibited associations across multiple populations. Chromosomes 1 and 8 contain strong candidate alleles for essential amino acid increases. Overall, we present these and additional data that will be useful in determining breeding strategies for the continued improvement of soybean’s nutrient portfolio.

Gene structural variation (SV) has recently emerged as a key genetic mechanism underlying several important phenotypic traits in crop species. We screened a panel of 41 soybean (Glycine max) accessions serving as parents in a soybean nested association mapping population for deletions and duplications in more than 53,000 gene models. Array hybridization and whole genome resequencing methods were used as complementary technologies to identify SV in 1528 genes, or approximately 2.8%, of the soybean gene models. Although SV occurs throughout the genome, SV enrichment was noted in families of biotic defense response genes. Among accessions, SV was nearly eightfold less frequent for gene models that have retained paralogs since the last whole genome duplication event, compared with genes that have not retained paralogs. Increases in gene copy number, similar to that described at the Rhg1 resistance locus, account for approximately one-fourth of the genic SV events. This assessment of soybean SV occurrence presents a target list of genes potentially responsible for rapidly evolving and/or adaptive traits.

Two novel QTLs conferring aphid resistance were mapped and validated on soybean chromosomes 8 and 16, respectively. Closely linked markers were developed to assist breeding for aphid resistance. Soybean aphid, Aphis glycines Matsumura, is a highly destructive pest for soybean production. E08934, a soybean advanced breeding line derived from the wild soybean Glycine soja 85-32, has shown strong resistance to aphids. To dissect the genetic basis of aphid resistance in E08934, a mapping population (070020) consisting of 140 F3-derived lines was developed by crossing E08934 with an aphid-susceptible line E00003. This mapping population was evaluated for aphid resistance in a greenhouse trial in 2010 and three field trials in 2009, 2010, and 2011, respectively. The broad-sense heritability across the field trials was 0.84. In the mapping population 070020, two major quantitative trait loci (QTL) were detected as significantly associated with aphid resistance, and designated as Rag6 and Rag3c, respectively. Rag6 was mapped to a 10.5 centiMorgan (cM) interval between markers MSUSNP08-2 and Satt209 on chromosome 8, explaining 19.5–46.4% of the phenotypic variance in different trials. Rag3c was located at a 7.5 cM interval between markers MSUSNP16-10 and Sat_370 on chromosome 16, explaining 12.5–22.9% of the phenotypic variance in different trials. Rag3c had less resistance effect than Rag6 across all the trials. Furthermore, Rag6 and Rag3c were confirmed in two validation populations with different genetic backgrounds. No significant interaction was detected between Rag6 and Rag3c in either the mapping population or the validation populations. Both Rag6 and Rag3c were indicated as conferring antibiosis resistance to aphids by a no-choice test. The new aphid-resistance gene(s) derived from the wild germplasm G. soja 85-32 are valuable in improving soybeans for aphid resistance.

Background Soybean seed weight is not only a yield component, but also a critical trait for various soybean food products such as sprouts, edamame, soy nuts, natto and miso. Linkage analysis and genome-wide association study (GWAS) are two complementary and powerful tools to connect phenotypic differences to the underlying contributing loci. Linkage analysis is based on progeny derived from two parents, given sufficient sample size and biological replication, it usually has high statistical power to map alleles with relatively small effect on phenotype, however, linkage analysis of the bi-parental population can’t detect quantitative trait loci (QTL) that are fixed in the two parents. Because of the small seed weight difference between the two parents in most families of previous studies, these populations are not suitable to detect QTL that have considerable effects on seed weight. GWAS is based on unrelated individuals to detect alleles associated with the trait under investigation. The ability of GWAS to capture major seed weight QTL depends on the frequency of the accessions with small and large seed weight in the population being investigated. Our objective was to identify QTL that had a pronounced effect on seed weight using a selective population of soybean germplasm accessions and the approach of GWAS and fixation index analysis. Results We selected 166 accessions from the USDA Soybean Germplasm Collection with either large or small seed weight and could typically grow in the same location. The accessions were evaluated for seed weight in the field for two years and genotyped with the SoySNP50K BeadChip containing >42,000 SNPs. Of the 17 SNPs on six chromosomes that were significantly associated with seed weight in two years based on a GWAS of the selective population, eight on chromosome 4 or chromosome 17 had significant Fst values between the large and small seed weight sub-populations. The seed weight difference of the two alleles of these eight significant SNPs varied from 8.1 g to 11.7 g/100 seeds in two years. We also identified haplotypes in three haplotype blocks with significant effects on seed weight. These findings were validated in a panel with 3753 accessions from the USDA Soybean Germplasm Collection. Conclusion This study highlighted the usefulness of selective genotyping populations coupled with GWAS and fixation index analysis for the identification of QTL with substantial effects on seed weight in soybean. This approach may help geneticists and breeders to more efficiently identify major QTL controlling other traits. The major regions and haplotypes we have identified that control seed weight differences in soybean will facilitate the identification of genes regulating this important trait. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3922-0) contains supplementary material, which is available to authorized users.

Background Phytophthora root and stem rot is one of the most yield-limiting diseases of soybean [Glycine max (L.) Merr], caused by the oomycete Phytophthora sojae. Partial resistance is controlled by several genes and, compared to single gene (Rps gene) resistance to P. sojae, places less selection pressure on P. sojae populations. Thus, partial resistance provides a more durable resistance against the pathogen. In previous work, plant introductions (PIs) originating from the Republic of Korea (S. Korea) have shown to be excellent sources for high levels of partial resistance against P. sojae. Results Resistance to two highly virulent P. sojae isolates was assessed in 1395 PIs from S. Korea via a greenhouse layer test. Lines exhibiting possible Rps gene immunity or rot due to other pathogens were removed and the remaining 800 lines were used to identify regions of quantitative resistance using genome-wide association mapping. Sixteen SNP markers on chromosomes 3, 13 and 19 were significantly associated with partial resistance to P. sojae and were grouped into seven quantitative trait loci (QTL) by linkage disequilibrium blocks. Two QTL on chromosome 3 and three QTL on chromosome 19 represent possible novel loci for partial resistance to P. sojae. While candidate genes at QTL varied in their predicted functions, the coincidence of QTLs 3-2 and 13-1 on chromosomes 3 and 13, respectively, with Rps genes and resistance gene analogs provided support for the hypothesized mechanism of partial resistance involving weak R-genes. Conclusions QTL contributing to partial resistance towards P. sojae in soybean germplasm originating from S. Korea were identified. The QTL identified in this study coincide with previously reported QTL, Rps genes, as well as novel loci for partial resistance. Molecular markers associated with these QTL can be used in the marker-assisted introgression of these alleles into elite cultivars. Annotations of genes within QTL allow hypotheses on the possible mechanisms of partial resistance to P. sojae. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2918-5) contains supplementary material, which is available to authorized users.

Soybean, an important source of vegetable oils and proteins for humans, has undergone significant phenotypic changes during domestication and improvement. However, there is limited knowledge about genes related to these domesticated and improved traits, such as flowering time, seed development, alkaline-salt tolerance, and seed oil content (SOC). In this study, more than 106,000 single nucleotide polymorphisms (SNPs) were identified by restriction site associated DNA sequencing of 14 wild, 153 landrace, and 119 bred soybean accessions, and 198 candidate domestication regions (CDRs) were identified via multiple genetic diversity analyses. Of the 1489 candidate domestication\ud genes (CDGs) within these CDRs, a total of 330 CDGs were\ud related to the above four traits in the domestication, gene ontology (GO) enrichment, gene expression, and pathway analyses. Eighteen, 60, 66, and 10 of the 330 CDGs were significantly associated with the above four traits, respectively. Of 134 traitassociated CDGs, 29 overlapped with previous CDGs, 11 were consistent with candidate genes in previous trait association studies, and 66 were covered by the domesticated and improved quantitative trait loci or their adjacent regions, having six common CDGs, such as one functionally characterized gene Glyma15 g17480 (GmZTL3). Of the 68 seed size (SS) and SOC CDGs, 37 were further confirmed by gene expression analysis. In addition, eight genes were found to be related to artificial selection\ud during modern breeding. Therefore, this study provides an\ud integrated method for efficiently identifying CDGs and valuable information for domestication and genetic research.

Soybean rust (SBR), caused by Phakopsora pachyrhizi Sydow, is one of the most economically important and destructive diseases of soybean [Glycine max (L.) Merr.] and the discovery of novel SBR resistance genes is needed because of virulence diversity in the pathogen. The objectives of this research were to map SBR resistance in plant introduction (PI) 561356 and to identify single nucleotide polymorphism (SNP) haplotypes within the region on soybean chromosome 18 where the SBR resistance gene Rpp1 maps. One-hundred F(2:3) lines derived from a cross between PI 561356 and the susceptible experimental line LD02-4485 were genotyped with genetic markers and phenotyped for resistance to P. pachyrhizi isolate ZM01-1. The segregation ratio of reddish brown versus tan lesion type in the population supported that resistance was controlled by a single dominant gene. The gene was mapped to a 1-cM region on soybean chromosome 18 corresponding to the same interval as Rpp1. A haplotype analysis of diverse germplasm across a 213-kb interval that included Rpp1 revealed 21 distinct haplotypes of which 4 were present among 5 SBR resistance sources that have a resistance gene in the Rpp1 region. Four major North American soybean ancestors belong to the same SNP haplotype as PI 561356 and seven belong to the same haplotype as PI 594538A, the Rpp1-b source. There were no North American soybean ancestors belonging to the SNP haplotypes found in PI 200492, the source of Rpp1, or PI 587886 and PI 587880A, additional sources with SBR resistance mapping to the Rpp1 region.

The evolutionary forces that govern the divergence and retention of duplicated genes in polyploids are poorly understood. In this study, we first investigated the rates of nonsynonymous substitution (Ka) and the rates of synonymous substitution (Ks) for a nearly complete set of genes in the paleopolyploid soybean (Glycine max) by comparing the orthologs between soybean and its progenitor species Glycine soja and then compared the patterns of gene divergence and expression between pericentromeric regions and chromosomal arms in different gene categories. Our results reveal strong associations between duplication status and Ka and gene expression levels and overall low Ks and low levels of gene expression in pericentromeric regions. It is theorized that deleterious mutations can easily accumulate in recombination-suppressed regions, because of Hill-Robertson effects. Intriguingly, the genes in pericentromeric regions—the cold spots for meiotic recombination in soybean—showed significantly lower Ka and higher levels of expression than their homoeologs in chromosomal arms. This asymmetric evolution of two members of individual whole genome duplication (WGD)-derived gene pairs, echoing the biased accumulation of singletons in pericentromeric regions, suggests that distinct genomic features between the two distinct chromatin types are important determinants shaping the patterns of divergence and retention of WGD-derived genes.

Background A landmark in soybean research, Glyma1.01, the first whole genome sequence of variety Williams 82 (Glycine max L. Merr.) was completed in 2010 and is widely used. However, because the assembly was primarily built based on the linkage maps constructed with a limited number of markers and recombinant inbred lines (RILs), the assembled sequence, especially in some genomic regions with sparse numbers of anchoring markers, needs to be improved. Molecular markers are being used by researchers in the soybean community, however, with the updating of the Glyma1.01 build based on the high-resolution linkage maps resulting from this research, the genome positions of these markers need to be mapped. Results Two high density genetic linkage maps were constructed based on 21,478 single nucleotide polymorphism loci mapped in the Williams 82 x G. soja (Sieb. & Zucc.) PI479752 population with 1083 RILs and 11,922 loci mapped in the Essex x Williams 82 population with 922 RILs. There were 37 regions or single markers where marker order in the two populations was in agreement but was not consistent with the physical position in the Glyma1.01 build. In addition, 28 previously unanchored scaffolds were positioned. Map data were used to identify false joins in the Glyma1.01 assembly and the corresponding scaffolds were broken and reassembled to the new assembly, Wm82.a2.v1. Based upon the plots of the genetic on physical distance of the loci, the euchromatic and heterochromatic regions along each chromosome in the new assembly were delimited. Genomic positions of the commonly used markers contained in BARCSOYSSR_1.0 database and the SoySNP50K BeadChip were updated based upon the Wm82.a2.v1 assembly. Conclusions The information will facilitate the study of recombination hot spots in the soybean genome, identification of genes or quantitative trait loci controlling yield, seed quality and resistance to biotic or abiotic stresses as well as other genetic or genomic research. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2344-0) contains supplementary material, which is available to authorized users.