USDA Soybean Germplasm Collection Research Articles

No Common Candidate Genes for Resistance to Fusarium graminearum, F. proliferatum, F. sporotrichioides, and F. subglutinans in Soybean Accessions from Maturity Groups 0 and I: Findings from Genome-wide Association Mapping.

Seedling diseases and root rot, caused by species of Fusarium, can limit soybean (Glycine max L.) production in the United States. Currently, there are few commercially available cultivars resistant to Fusarium. This study was conducted to assess the resistance of soybean maturity group (MG) accessions from 0 and I to Fusarium proliferatum, F. sporotrichioides, and F. subglutinans, as well as to identify common quantitative trait loci (QTLs) for resistance to these pathogens, in addition to F. graminearum, using a genome-wide association study (GWAS). A total of 155, 91, and 48 accessions from the United States Department of Agriculture (USDA) soybean germplasm collection from MG 0 and I were screened with a single isolate each of F. proliferatum, F. sporotrichioides, and F. subglutinans, respectively, using the inoculum layer inoculation method in the greenhouse. The disease severity was assessed 21 days postinoculation and analyzed using nonparametric statistics to determine the relative treatment effects (RTEs). Eleven and seven accessions showed significantly lower RTEs when inoculated with F. proliferatum and F. subglutinans, respectively, compared with the susceptible cultivar 'Williams 82'. One accession was significantly less susceptible to both F. proliferatum and F. subglutinans. The GWAS conducted with 41,985 single-nucleotide markers identified one QTL associated with resistance to both F. proliferatum and F. sporotrichioides, as well as another QTL for resistance to both F. subglutinans and F. graminearum. However, no common QTLs were identified for the four pathogens. The USDA accessions and QTLs identified in this study can be utilized to selectively breed resistance to multiple species of Fusarium.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Development and implementation of nested single-nucleotide polymorphism (SNP) assays for breeding and genetic research applications.

SoySNP50K and SoySNP6K are commonly used for soybean (Glycine max) genotyping. The SoySNP50K assay has been used to genetically analyze the entire USDA Soybean Germplasm Collection, while the SoySNP6K assay, containing a subset of 6000 single-nucleotide polymorphisms (SNPs) from SoySNP50K, has been used for quantitative trait loci mapping of different traits. To meet the needs for genomic selection, selection of parents for crosses, and characterization of breeding populations, especially early selection of ideal offspring from thousands of lines, we developed two assays, SoySNP3K and SoySNP1K, containing 3072 and 1252 SNPs, respectively, based on SoySNP50K and SoySNP6K mark sets. These two assays also contained the trait markers reported or contributed by soybean breeders. The SNPs in the SoySNP3K are a subset from SoySNP6K, while the SNPs in the SoySNP1K are a subset from SoySNP3K. These SNPs were chosen to reduce the SNP number in the large linkage blocks while capturing as much of the haplotype diversity as possible. They are highly polymorphic and of high quality. The mean minor allele frequencies of the SNPs in the southern and northern US elites were 0.25 and 0.27 for SoySNP3K, respectively, and 0.29 and 0.33 for SoySNP1K. The selected SNPs are a valuable source for developing targeted amplicon sequencing assay or beadchip assay in soybean. SoySNP3K and SoySNP1K assays are commercialized by Illumina Inc. and AgriPlex Genomics, respectively. Together with SoySNP50K and SoySNP6K, a series of nested assays with different marker densities will serve as additional low-cost genomic tools for genetic, genomic, and breeding research.

Elemental sulfur concentration can be used as a rapid, reliable, and cost-effective predictor of sulfur amino acid content of soybean seeds

In this study, we have examined the feasibility of using elemental sulfur content of soybean seeds as a proxy for the overall sulfur amino acid content of soybean seeds. Earlier, we have identified by high throughput ionomic phenotyping several high and low sulfur containing soybean lines from the USDA Soybean Germplasm Collection. Here, we measured the cysteine and methionine content of select soybean lines by high-performance liquid chromatography. Our results demonstrate that those soybean lines which had high elemental sulfur content also had a higher cysteine and methionine content when compared to soybean lines with low elemental sulfur. SDS-PAGE and immunoblot analysis revealed that the accumulation of Bowman Birk protease inhibitor and lunasin in soybean seeds may only be marginally correlated with the elemental sulfur levels. However, we found a positive correlation between the levels of trypsin and chymotrypsin inhibitor activities and elemental sulfur and sulfur amino acid content of the seeds. Thus, elemental sulfur content and/or protease inhibitor activity measurement can be utilized as a rapid and cost-effective method to predict the overall sulfur amino acid content of soybean seeds. Our findings will benefit breeders in their endeavors to develop soybean cultivars with enhanced sulfur amino acid content.

Identification and mapping of a recessive allele, dt3, specifying semideterminate stem growth habit in soybean

Key messageA locus, dt3, modulating semideterminancy in soybean, was discovered by a combination of genome-wide association studies and linkage mapping with multiple distinct biparental populations.Stem growth habit is a key architectural trait in many plants that contributes to plant productivity and environmental adaptation. In soybean, stem growth habit is classified as indeterminate, semideterminate, or determinate, of which semideterminacy is often considered as a counterpart of the “Green Revolution” trait in cereals that significantly increased grain yields. It has been demonstrated that semideterminacy in soybean is modulated by epistatic interaction between two loci, Dt1 on chromosome 19 and Dt2 on chromosome 18, with the latter as a negative regulator of the former. Here, we report the discovery of a third locus, Dt3, modulating soybean stem growth habit, which was delineated to a ~ 196-kb region on chromosome 10 by a combination of allelic and haplotypic analysis of the Dt1 and Dt2 loci in the USDA soybean Germplasm Collection, genome-wide association studies with three subsets of the collection, and linkage mapping with four biparental populations derived from crosses between one of two elite indeterminate cultivars and each of four semideterminate varieties possessing neither Dt2 nor dt1. These four semideterminate varieties are recessive mutants (i.e., dt3/dt3) in the Dt1/Dt1;dt2/dt2 background. As the semideterminacy modulated by the Dt2 allele has unfavorable pleotropic effects such as sensitivity to drought stress, dt3 may be an ideal alternative for use to develop semideterminate cultivars that are more resilient to such an environmental stress. This study enhances our understanding of the genetic factors underlying semideterminacy and enables more accurate marker-assisted selection for stem growth habit in soybean breeding.

Determining Genetic Markers and Seed Compositions Related to High Test Weight in Glycine max.

Test weight, one of the primary indicators of soybean seed quality, is measured as the amount of soybean seeds in kilograms that can fit into one hectoliter. The price that growers receive for their soybean is dependent on test weight. Over the past 50 years, growers have observed a decreasing trend in test weight. Therefore, it is imperative to understand better the relationship between soybean test weight and other traits to enable breeders to select parental lines with high test weights in breeding programs to ensure the grower's profitability. The objectives of the study were to identify genetic markers associated with high test weight in soybean and to determine the correlation between high test weight and five important seed composition traits (protein, oil, sucrose, raffinose, and stachyose content). Maturity group IV and V germplasms from the USDA soybean germplasm collection were grown in Blacksburg and Warsaw in Virginia from 2019 to 2021 and were measured for all of the above traits. Results show that test weight values ranged from 62-77 kg/hL over the three years. Multiple single-nucleotide polymorphisms (SNPs) significantly associated with high test weight were found on chromosome (Chr.) 15 along with a couple on chromosome 14, and 11 candidate genes were found near these SNPs. Test weight was found to be significantly negatively correlated with oil content, inconsistently correlated with protein content in all environments, and negatively correlated but not significantly with all three sugars except for raffinose in Blacksburg 2019. We concluded that the genes that underlie test weight might be on chromosome 15, and the validated associated SNPs might be used to assist breeding selection of test weight. Breeders should pay special attention to test weight while selecting for high oil content in soybean due to their negative correlation.

An assessment of the interaction between sucrose content and seed quality traits in soybeans

AbstractSoybean (Glycine max [L.] Merr.) cultivars with increased protein and sucrose content are desirable to enhance soybean meal quality; however, the complex interactions between soybean traits, mainly trade‐offs, make the plant breeders’ job challenging because traits cannot simultaneously be enhanced. Information about the interactions of seed carbohydrate composition with other seed traits remains inconclusive and contradictory; thus, this study explored the interactions among soluble carbohydrate content with other seed traits, flowering time, and maturity in a diverse panel of 1096 soybean accessions from the USDA Soybean Germplasm Collection. Trait interactions were explored through phenotypic, additive genetic, and residual correlations. We did not identify traits that can be useful in the indirect selection of sucrose. Additive genetic correlations of sucrose with flowering and maturity time suggest that obtaining cultivars with high sucrose content might be easier in earlier flowering and later maturing cultivars. Sucrose correlations with other seed traits were primarily driven by their additive genetic correlations, which make them more stable, whereas correlations of raffinose with oil and maturity were population and environment specific. The two main obstacles to enhancing soymeal quality are the trade‐offs of protein with sucrose and oil.

Identification of quantitative trait loci controlling soybean seed protein and oil content.

Soybean is a major source of seed protein and oil globally with an average composition of 40% protein and 20% oil in the seed. The goal of this study was to identify quantitative trait loci (QTL) conferring seed protein and oil content utilizing a population constructed by crossing an above average protein content line, PI 399084 to another line that had a low protein content value, PI 507429, both from the USDA soybean germplasm collection. The recombinant inbred line (RIL) population, PI 507429 x PI 399084, was evaluated in two replications over four years (2018-2021); the seeds were analyzed for seed protein and oil content using near-infrared reflectance spectroscopy. The recombinant inbred lines and the two parents were re-sequenced using genotyping by sequencing. A total of 12,761 molecular markers, which came from genotyping by sequencing, the SoySNP6k BeadChip and selected simple sequence repeat (SSR) markers from known protein QTL chromosomal regions were used for mapping. One QTL was identified on chromosome 2 explaining up to 56.8% of the variation for seed protein content and up to 43% for seed oil content. Another QTL identified on chromosome 15 explained up to 27.2% of the variation for seed protein and up to 41% of the variation for seed oil content. The protein and oil QTLs of this study and their associated molecular markers will be useful in breeding to improve nutritional quality in soybean.

Evaluation of exotic soybean accessions and their use in developing improved soybean lines with resistance to Phomopsis seed decay.

Poor seed quality of soybean is often associated with Phomopsis seed decay (PSD), which is one of the most economically important seed diseases. Diaporthe longicolla (syn. Phomopsis longicolla) is the primary cause of PSD. Control of PSD is best accomplished by planting PSD-resistant cultivars. Sixteen exotic soybean accessions from the USDA soybean germplasm collection were screened for reaction to PSD at Stoneville, Mississippi. They consisted of maturity groups (MG) II, III and IV. Seeds from inoculated and non-inoculated plots harvested either promptly at maturity, or after a two-week delay in harvest, were assessed for infection by D. longicolla. Seed infection ranged from 0 to 36.7%. Overall, PI 417050 (MG II), PI 417017 (MG III), and PI 594692 (MG IV) had significantly (P ≤ 0.05) lower percentages of seed infected by D. longicolla and higher seed germinations than other genotypes in the same maturity groups. PI 587982A also performed well. As a result of these findings, these resistant accessions were used over multiple cycles of breeding to develop improved breeding lines with resistance to PSD and low seed damage. Breeding line 11043-225-72, with combined resistance from both PIs 417050 and 587982A, had low scores for PSD (6.7%) and seed damage (3.4%), while DS65-1, deriving resistance from PI 587982A, had the lowest seed damage score (1.1%) and the highest seed germination (85.6%) among all lines tested in 2017. DS65-1 and 11043-225-72, along with five other improved breeding lines, were provided to public soybean breeders for developing improved cultivars and germplasm lines. DS31-243 (PI 700941), derived from PI 587982A, was publicly released by the USDA in 2022. This research will lead to future releases of improved germplasm lines and cultivars with PSD resistance and high seed quality. It will also aid in disease management and be a benefit to soybean producers and the industry at large.

Variation in Isolate Virulence and Accession Resistance Associated with Diaporthe aspalathi, D. caulivora, and D. longicolla in Soybean

Important stem and grain diseases of soybean ( Glycine max [L.] Merr.) caused by Diaporthe aspalathi, D. caulivora, and D. longicolla reduce yield in the United States. Sources of resistance to these pathogens have previously been reported; however, there is limited information regarding their resistance when exposed to geographically distinct isolates of the same species. In this study, four accessions from the USDA Soybean Germplasm Collection with reported resistance to D. aspalathi, D. caulivora, or D. longicolla were evaluated using geographically representative isolates within each species from the United States. For each fungus, a greenhouse experiment was conducted as a completely randomized design with a factorial arrangement (isolate × accession). Plants were inoculated at the second to third trifoliate growth stage using toothpicks infested with isolates of each Diaporthe species. Pathogenicity was assessed 21 days postinoculation as 0 = no lesion, 0.5 = lesion length > 1 cm, and 1 = dead plant. A significant isolate-by-accession interaction ( P < 0.05) was observed to affect pathogenicity as analyzed using nonparametric statistics (relative treatment effects [RTEs]), indicating that accessions responded differently to the isolates. Correlation analyses suggested that the RTEs on ‘Tracy-M’, ‘Dowling’, and ‘Crockett’ were weakly to moderately correlated with those of the D. aspalathi-susceptible ‘Bragg’, as well as for ‘PI567473B’ and ‘Century’ ( D. caulivora), and ‘PI417507’ ( D. longicolla), with the RTEs on ‘Hawkeye’ ( P > 0.05) indicating possible genetic variation for resistance within these accessions. Our results provide information related to the resistance of previously identified accessions to develop commercial cultivars with resistance to important pathogens within the genus Diaporthe. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Identification of genomic regions associated with soybean responses to off-target dicamba exposure.

The widespread adoption of genetically modified (GM) dicamba-tolerant (DT) soybean was followed by numerous reports of off-target dicamba damage and yield losses across most soybean-producing states. In this study, a subset of the USDA Soybean Germplasm Collection consisting of 382 genetically diverse soybean accessions originating from 15 countries was used to identify genomic regions associated with soybean response to off-target dicamba exposure. Accessions were genotyped with the SoySNP50K BeadChip and visually screened for damage in environments with prolonged exposure to off-target dicamba. Two models were implemented to detect significant marker-trait associations: the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) and a model that allows the inclusion of population structure in interaction with the environment (G×E) to account for variable patterns of genotype responses in different environments. Most accessions (84%) showed a moderate response, either moderately tolerant or moderately susceptible, with approximately 8% showing tolerance and susceptibility. No differences in off-target dicamba damage were observed across maturity groups and centers of origin. Both models identified significant associations in regions of chromosomes 10 and 19. The BLINK model identified additional significant marker-trait associations on chromosomes 11, 14, and 18, while the G×E model identified another significant marker-trait association on chromosome 15. The significant SNPs identified by both models are located within candidate genes possessing annotated functions involving different phases of herbicide detoxification in plants. These results entertain the possibility of developing non-GM soybean cultivars with improved tolerance to off-target dicamba exposure and potentially other synthetic auxin herbicides. Identification of genetic sources of tolerance and genomic regions conferring higher tolerance to off-target dicamba may sustain and improve the production of other non-DT herbicide soybean production systems, including the growing niche markets of organic and conventional soybean.

A transposon‐mediated reciprocal translocation promotes environmental adaptation but compromises domesticability of wild soybeans

Large structural variations frequently occur in higher plants; however, the impact of such variations on plant diversification, adaptation and domestication remains elusive. Here, we mapped and characterised a reciprocal chromosomal translocation in soybeans and assessed its effects on diversification and adaptation of wild (Glycine soja) and semiwild (Glycine gracilis) soybeans, and domestication of cultivated soybean (Glycine max), by tracing the distribution of the translocation in the USDA Soybean Germplasm Collection and population genetics analysis. We demonstrate that the translocation occurred through CACTA transposon-mediated chromosomal breakage in wild soybean c. 0.34 Ma and is responsible for semisterility in translocation heterozygotes and reduces their reproductive fitness. The translocation has differentiated Continental (i.e. China and Russia) populations from Maritime (i.e. Korea and Japan) populations of G.soja and predominately adapted to cold and dry climates. Further analysis revealed that the divergence of G.max from G.soja predates the translocation event and that G.gracilis is an evolutionary intermediate between G.soja and G.max. Our results highlight the effects of a chromosome rearrangement on the processes leading to plant divergence and adaptation, and provides evidence that suggests G.gracilis, rather than G.soja, as the ancestor of cultivated soybean.

Sequencing the USDA core soybean collection reveals gene loss during domestication and breeding.

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.

Identification of Prospective Soybean Accessions for the Creation of a Genebank Core Collection Based on High Density DNA Marker Data

Genebanks typically collect and conserve as many existing genetic variations as possible. However, a smaller core population that is representative of the whole collection but maintains as much diversity as possible is more practical for in-depth phenotypic characterization, genetic studies, and plant breeding. Here we describe genotype-based core collection development from USDA soybean germplasm collection, which contains 20,095 accessions that had been genotyped using 50,000 single nucleotide polymorphism DNA markers. Analysis using trimmed marker data and Core Hunter 3 software identified 382 accessions with maximum genetic distances from each other. Population structure analysis of the selected accessions indicated that the software favored admixed individuals instead of those with pure ancestor population genotypes. Allele frequencies of most markers are largely conserved in the core population, which indicates successful maintenance of alleles in the core population. Phenotypic variations for branch number and yield were largely similar to the original population, but slightly different for seed weight and maturity, where very high seed weight and high-latitude maturity groups were less prominent in the core collection. The resulting core population can be used as a base population for any institutions interested in utilizing worldwide soybean genetic diversity for breeding and genetic studies.

Association mapping identifies and confirms loci for soybean seed weight

AbstractSeed weight (SW) is a component of soybean [Glycine max (L.) Merr.] yield and it is also an important determinant of quality for food products such as edamame, soy nuts, and tofu. A better understanding of the genetic basis of SW is important for cultivar development and for use in various food industries. The objective of this study was to identify and confirm the genomic regions, favorable alleles, and candidate genes associated with SW. Genome‐wide association mapping was conducted on 36 panels including a diverse panel of 373 accessions grown in three environments (one panel) and 35 panels obtained from the Germplasm Resources Information Network. Association mapping identified 66 significant single nucleotide polymophisms (SNPs) that probably tagged 47 putative loci associated with SW that had allelic effects ranging from –7.8 to 6.9 g per 100 seeds. Of these 47 loci, 42 significant loci–SW associations were confirmed with previously identified SW quantitative trait loci (QTLs). One SNP on Gm17 and another SNP on Gm19 were present in 16 and 8 panels, respectively. There were 121 candidate genes found within the same linkage disequilibrium blocks as the identified SNPs; 97 of these genes had biological functions associated with seed components including protein, fatty acids (oil), carbohydrates, seeds, embryos, water, and cotyledons. The entire USDA soybean germplasm collection was explored for the favorable alleles. Favorable alleles, accessions identified from the germplasm collection, and candidate genes may be important resources for breeding for SW in soybean.

Mining germplasm panels and phenotypic datasets to identify loci for resistance to Phytophthora sojae in soybean.

Phytophthora sojae causes Phytophthora root and stem rot of soybean and has been primarily managed through deployment of qualitative Resistance to P. sojae genes (Rps genes). The effectiveness of each individual or combination of Rps gene(s) depends on the diversity and pathotypes of the P. sojae populations present. Due to the complex nature of P. sojae populations, identification of more novel Rps genes is needed. In this study, phenotypic data from previous studies of 16 panels of plant introductions (PIs) were analyzed. Panels 1 and 2 consisted of 448 Glycine max and 520 G. soja, which had been evaluated for Rps gene response with a combination of P. sojae isolates. Panels 3 and 4 consisted of 429 and 460 G. max PIs, respectively, which had been evaluated using individual P. sojae isolates with complex virulence pathotypes. Finally, Panels 5-16 (376 G. max PIs) consisted of data deposited in the USDA Soybean Germplasm Collection from evaluations with 12 races of P. sojae. Using these panels, genome-wide association (GWA) analyses were carried out by combining phenotypic and SoySNP50K genotypic data. GWA models identified two, two, six, and seven novel Rps loci with Panels 1, 2, 3, and 4, respectively. A total of 58 novel Rps loci were identified using Panels 5-16. Genetic and phenotypic dissection of these loci may lead to the characterization of novel Rps genes that can be effectively deployed in new soybean cultivars against diverse P. sojae populations.

Characterization of genetic heterogeneity within accessions in the USDA soybean germplasm collection.

Soybean breeding relies on the use of wild (Glycine soja Sieb. and Zucc.) and domesticated [Glycine max (L.) Merr.] germplasm for trait improvement. Soybeans are self-pollinating and accessions can be maintained as pure lines, however within-accession genetic variation has been observed in previous studies of some landraces and elite cultivars. The objective of this study was to characterize within-line variation in the accessions housed in the USDA Soybean Germplasm Collection. This collection includes over 20,000 accessions, each previously genotyped using the SoySNP50K Chip. Each SoySNP50K genotype was developed by pooling approximately three individuals per accession. Therefore, clusters of SNPs called as heterozygous within an accession can be inferred to represent putative regions of heterogeneity between the three individuals sampled. In this study, we found high-probability intervals of heterogeneity in 4% of the collection, representing 870 accessions. Heterogeneous loci were found on every chromosome and, collectively, covered 98.4% of the soybean genome and 99% of the gene models. Sanger sequencing confirmed regions of genomic heterogeneity among a subset of ten accessions. This dataset provides useful information and considerations for users of crop germplasm seed banks. Furthermore, the heterogeneous accessions and/or loci represent a unique genetic resource that is immediately available for forward and reverse genetics studies.

Genome-Wide Association Mapping of Host-Plant Resistance to Soybean Aphid.

Soybean aphid [ Matsumura (Hemiptera: Aphididae)] is the most damaging insect pest of soybean [ (L.) Merr.] in the Upper Midwest of the United States and is primarily controlled by insecticides. Soybean aphid resistance (i.e., genes) has been documented in some soybean accessions but more sources of resistance are needed. Incorporation of the resistance into marketed varieties has also been slow. Genome-wide association mapping can aid in identifying resistant accessions by correlating phenotypic data with single nucleotide polymorphisms (SNPs) across a genome. Aphid population measures from 2366 soybean accessions were collected from published studies screening cultivated soybean () and wild soybean ( Siebold & Zucc.) with aphids exhibiting Biotype 1, 2, or 3 characteristics. Genotypic data were obtained from the SoySNP50K high-density genotyping array previously used to genotype the USDA Soybean Germplasm Collection. Significant associations between SNPs and soybean aphid counts were found on 18 of the 20 soybean chromosomes. Significant SNPs were found on chromosomes 7, 8, 13, and 16 with known genes. SNPs were also significant on chromosomes 1, 2, 4 to 6, 9 to 12, 14, and 17 to 20 where genes have not yet been mapped, suggesting that many genes remain to be discovered. These SNPs can be used to determine accessions that are likely to have novel aphid resistance traits of value for breeding programs.

Genomewide association study of ionomic traits on diverse soybean populations from germplasm collections.

The elemental content of a soybean seed is a determined by both genetic and environmental factors and is an important component of its nutritional value. The elemental content is chemically stable, making the samples stored in germplasm repositories an intriguing source of experimental material. To test the efficacy of using samples from germplasm banks for gene discovery, we analyzed the elemental profile of seeds from 1,653 lines in the USDA Soybean Germplasm Collection. We observed large differences in the elemental profiles based on where the lines were grown, which lead us to break up the genetic analysis into multiple small experiments. Despite these challenges, we were able to identify candidate single nucleotide polymorphisms (SNPs) controlling elemental accumulation as well as lines with extreme elemental accumulation phenotypes. Our results suggest that elemental analysis of germplasm samples can identify SNPs in linkage disequilibrium to genes, which can be leveraged to assist in crop improvement efforts.

Genome-wide association mapping of resistance to Phytophthora sojae in a soybean [Glycine max (L.) Merr.] germplasm panel from maturity groups IV and V.

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.

Identification of QTL with large effect on seed weight in a selective population of soybean with genome-wide association and fixation index analyses

BackgroundSoybean 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.ResultsWe 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.ConclusionThis 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.