Genetic Diversity and Phylogenetic Relationships of Annual and Perennial Glycine Species.

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.

Genetic Architecture of Soybean Yield and Agronomic Traits.

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.

Genome-wide Scan for Seed Composition Provides Insights into Soybean Quality Improvement and the Impacts of Domestication and Breeding.

The complex genetic architecture of quality traits has hindered efforts to modify seed nutrients in soybean. Genome-wide association studies were conducted for seed composition, including protein, oil, fatty acids, and amino acids, using 313 diverse soybean germplasm accessions genotyped with a high-density SNP array. A total of 87 chromosomal regions were identified to be associated with seed composition, explaining 8%-89% of genetic variances. The candidate genes GmSAT1, AK-HSDH, SACPD-C, and FAD3A of known function, and putative MtN21 nodulin, FATB, and steroid-5-α-reductase involved in N2 fixation, amino acid biosynthesis, and fatty acid metabolism were found at the major-effect loci. Further analysis of additional germplasm accessions indicated that these major-effect loci had been subjected to domestication or modern breeding selection, and the allelic variants and distributions were relevant to geographic regions. We also revealed that amino acid concentrations related to seed weight and to total protein had a different genetic basis. This helps uncover the in-depth genetic mechanism of the intricate relationships among the seed compounds. Thus, our study not only provides valuable genes and markers for soybean nutrient improvement, both quantitatively and qualitatively, but also offers insights into the alteration of soybean quality during domestication and breeding.

Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population.

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.

Genetic Characterization of the Soybean Nested Association Mapping Population.

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.

Mapping novel aphid resistance QTL from wild soybean, Glycine soja 85-32.

KEY MESSAGE: 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.

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

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.

High-resolution mapping reveals linkage between genes in common bean cultivar Ouro Negro conferring resistance to the rust, anthracnose, and angular leaf spot diseases.

KEY MESSAGE: Co-segregation analysis and high-throughput genotyping using SNP, SSR, and KASP markers demonstrated genetic linkage between Ur-14 and Co-3 4 /Phg-3 loci conferring resistance to the rust, anthracnose and angular leaf spot diseases of common bean. Rust, anthracnose, and angular leaf spot are major diseases of common bean in the Americas and Africa. The cultivar Ouro Negro has the Ur-14 gene that confers broad spectrum resistance to rust and the gene cluster Co-3 4 /Phg-3 containing two tightly linked genes conferring resistance to anthracnose and angular leaf spot, respectively. We used co-segregation analysis and high-throughput genotyping of 179 F2:3 families from the Rudá (susceptible) × Ouro Negro (resistant) cross-phenotyped separately with races of the rust and anthracnose pathogens. The results confirmed that Ur-14 and Co-3 4 /Phg-3 cluster in Ouro Negro conferred resistance to rust and anthracnose, respectively, and that Ur-14 and the Co-3 4 /Phg-3 cluster were closely linked. Genotyping the F2:3 families, first with 5398 SNPs on the Illumina BeadChip BARCBEAN6K_3 and with 15 SSR, and eight KASP markers, specifically designed for the candidate region containing Ur-14 and Co-3 4 /Phg-3, permitted the creation of a high-resolution genetic linkage map which revealed that Ur-14 was positioned at 2.2 cM from Co-3 4 /Phg-3 on the short arm of chromosome Pv04 of the common bean genome. Five flanking SSR markers were tightly linked at 0.1 and 0.2 cM from Ur-14, and two flanking KASP markers were tightly linked at 0.1 and 0.3 cM from Co-3 4 /Phg-3. Many other SSR, SNP, and KASP markers were also linked to these genes. These markers will be useful for the development of common bean cultivars combining the important Ur-14 and Co-3 4 /Phg-3 genes conferring resistance to three of the most destructive diseases of common bean.

Molecular Characterization of Resistance to Soybean Rust (Phakopsora pachyrhizi Syd. & Syd.) in Soybean Cultivar DT 2000 (PI 635999).

Resistance to soybean rust (SBR), caused by Phakopsora pachyrhizi Syd. & Syd., has been identified in many soybean germplasm accessions and is conferred by either dominant or recessive genes that have been mapped to six independent loci (Rpp1 -Rpp6), but No U.S. cultivars are resistant to SBR. The cultivar DT 2000 (PI 635999) has resistance to P. pachyrhizi isolates and field populations from the United States as well as Vietnam. A F6:7 recombinant inbred line (RIL) population derived from Williams 82 × DT 2000 was used to identify genomic regions associated with resistance to SBR in the field in Ha Noi, Vietnam, and in Quincy, Florida, in 2008. Bulked segregant analysis (BSA) was conducted using the soybean single nucleotide polymorphism (SNP) USLP 1.0 panel along with simple sequence repeat (SSR) markers to detect regions of the genome associated with resistance. BSA identified four BARC_SNP markers near the Rpp3 locus on chromosome (Chr.) 6. Genetic analysis identified an additional genomic region around the Rpp4 locus on Chr. 18 that was significantly associated with variation in the area under disease progress curve (AUDPC) values and sporulation in Vietnam. Molecular markers tightly linked to the DT 2000 resistance alleles on Chrs. 6 and 18 will be useful for marker-assisted selection and backcrossing in order to pyramid these genes with other available SBR resistance genes to develop new varieties with enhanced and durable resistance to SBR.

Genome-Wide Association Study Identifies Candidate Loci Underlying Agronomic Traits in a Middle American Diversity Panel of Common Bean.

Common bean ( L.) breeding programs aim to improve both agronomic and seed characteristics traits. However, the genetic architecture of the many traits that affect common bean production are not completely understood. Genome-wide association studies (GWAS) provide an experimental approach to identify genomic regions where important candidate genes are located. A panel of 280 modern bean genotypes from race Mesoamerica, referred to as the Middle American Diversity Panel (MDP), were grown in four US locations, and a GWAS using >150,000 single-nucleotide polymorphisms (SNPs) (minor allele frequency [MAF] ≥ 5%) was conducted for six agronomic traits. The degree of inter- and intrachromosomal linkage disequilibrium (LD) was estimated after accounting for population structure and relatedness. The LD varied between chromosomes for the entire MDP and among race Mesoamerica and Durango-Jalisco genotypes within the panel. The LD patterns reflected the breeding history of common bean. Genome-wide association studies led to the discovery of new and known genomic regions affecting the agronomic traits at the entire population, race, and location levels. We observed strong colocalized signals in a narrow genomic interval for three interrelated traits: growth habit, lodging, and canopy height. Overall, this study detected ∼30 candidate genes based on a priori and candidate gene search strategies centered on the 100-kb region surrounding a significant SNP. These results provide a framework from which further research can begin to understand the actual genes controlling important agronomic production traits in common bean.

Genome-wide association mapping of partial resistance to Phytophthora sojae in soybean plant introductions from the Republic of Korea.

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.

Multi-Population Selective Genotyping to Identify Soybean [Glycine max (L.) Merr.] Seed Protein and Oil QTLs.

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 = âˆ¼224 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 R(2) 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.

Draft genome sequence of Diaporthe aspalathi isolate MS-SSC91, a fungus causing stem canker in soybean.

Diaporthe aspalathi (Syn. Diaporthe phaseolorum var. meridionalis) is the causal agent of the southern stem canker (SSC) disease in soybean. This disease can kill plants from the middle to the end of the growing season resulting in severe yield loss. The mechanisms of SSC disease development and pathogen invasion of soybean are not fully understood. The genome sequence of D. aspalathi has not been described. In this article, we report the successful assembly of the draft genome sequence of a D. aspalathi isolate, designated MS-SSC91, that was isolated from the stem of a field-grown soybean plant in Mississippi, USA in 2006. This study represents the first reported genome sequence of D. aspalathi in the Diaporthe-Phomopsis complex. The whole genome shotgun sequence of the MS-SSC91 isolate has been deposited at DDBJ/EMBL/GenBank under the accession LJJS00000000 and the sequences could be found at the site http://www.ncbi.nlm.nih.gov/assembly/GCA_001447215.1/. The MS-SSC91 genome sequences will provide information on the genetic basis of fungal infection of the soybean stem. It is valuable for studying soybean-fungal interactions and developing new control strategies for this pathogen.

Phenotypic variation and identification of quantitative trait loci for ozone tolerance in a Fiskeby III × Mandarin (Ottawa) soybean population.

KEY MESSAGE: Soybean quantitative trait loci for ozone response. Ground-level ozone reduces yield in crops such as soybean (Glycine max (L.) Merr.). Phenotypic variation has been observed for this trait in multiple species; however, breeding for ozone tolerance has been limited. A recombinant inbred population was developed from soybean genotypes differing in tolerance to ozone: tolerant Fiskeby III and sensitive Mandarin (Ottawa). Plants were exposed to ozone treatment for 5 days in greenhouse chambers followed by visual scoring for foliar injury. Mean injury score in the mid-canopy was 16 % for Fiskeby III, and 81 % for Mandarin (Ottawa). Injury scores were lower in younger leaves for both parents and progeny, compared to scores in the older leaves. Segregation was consistent with multigenic inheritance. Correlation coefficients for injury between leaf positions ranged from 0.34 to 0.81, with the closer leaf positions showing the greater correlation. Narrow sense heritability within an ozone treatment chamber was 0.59, 0.40, 0.29, 0.30, 0.19, and 0.35 for the 2nd, 3rd, 4th, 5th, 6th, and combined 3rd-5th main stem leaf positions (numbered acropetally), respectively, based on genotypic means over three independent replications. Quantitative trait loci (QTL) analysis showed that loci were associated with distinct leaf developmental stages. QTL were identified on Chromosome 17 for the 2nd and 3rd leaf positions, and on Chromosome 4 for the 5th and 6th leaf positions. Additional loci were identified on Chromosomes 6, 18, 19, and 20. Interacting loci were identified on Chromosomes 5 and 15 for injury on trifoliate 4. The ozone sensitive parent contributed one favorable allele for ozone response.

Construction of high resolution genetic linkage maps to improve the soybean genome sequence assembly Glyma1.01.

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.

Characterization of Soybean Storage and Allergen Proteins Affected by Environmental and Genetic Factors.

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<0.005 level, was performed. We found more spots that showed statistically significant differences in expression among E compared to G and G×E interaction.

Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max).

KEY MESSAGE: Twenty-two loci for soybean SW and candidate genes conditioning seed development were identified; and prediction accuracies of GS and MAS were estimated through cross-validation and validation with unrelated populations. Soybean (Glycine max) is a major crop for plant protein and oil production, and seed weight (SW) is important for yield and quality in food/vegetable uses of soybean. However, our knowledge of genes controlling SW remains limited. To better understand the molecular mechanism underlying the trait and explore marker-based breeding approaches, we conducted a genome-wide association study in a population of 309 soybean germplasm accessions using 31,045 single nucleotide polymorphisms (SNPs), and estimated the prediction accuracy of genomic selection (GS) and marker-assisted selection (MAS) for SW. Twenty-two loci of minor effect associated with SW were identified, including hotspots on Gm04 and Gm19. The mixed model containing these loci explained 83.4% of phenotypic variation. Candidate genes with Arabidopsis orthologs conditioning SW were also proposed. The prediction accuracies of GS and MAS by cross-validation were 0.75-0.87 and 0.62-0.75, respectively, depending on the number of SNPs used and the size of training population. GS also outperformed MAS when the validation was performed using unrelated panels across a wide range of maturities, with an average prediction accuracy of 0.74 versus 0.53. This study convincingly demonstrated that soybean SW is controlled by numerous minor-effect loci. It greatly enhances our understanding of the genetic basis of SW in soybean and facilitates the identification of genes controlling the trait. It also suggests that GS holds promise for accelerating soybean breeding progress. The results are helpful for genetic improvement and genomic prediction of yield in soybean.

Genomic consequences of selection and genome-wide association mapping in soybean.

BACKGROUND: Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits. RESULTS: To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified. CONCLUSIONS: These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

Genome-Wide Association Study of Ureide Concentration in Diverse Maturity Group IV Soybean [Glycine max (L.) Merr.] Accessions.

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.

SNP Assay Development for Linkage Map Construction, Anchoring Whole-Genome Sequence, and Other Genetic and Genomic Applications in Common Bean.

A total of 992,682 single-nucleotide polymorphisms (SNPs) was identified as ideal for Illumina Infinium II BeadChip design after sequencing a diverse set of 17 common bean (Phaseolus vulgaris L) varieties with the aid of next-generation sequencing technology. From these, two BeadChips each with >5000 SNPs were designed. The BARCBean6K_1 BeadChip was selected for the purpose of optimizing polymorphism among market classes and, when possible, SNPs were targeted to sequence scaffolds in the Phaseolus vulgaris 14× genome assembly with sequence lengths >10 kb. The BARCBean6K_2 BeadChip was designed with the objective of anchoring additional scaffolds and to facilitate orientation of large scaffolds. Analysis of 267 F2 plants from a cross of varieties Stampede × Red Hawk with the two BeadChips resulted in linkage maps with a total of 7040 markers including 7015 SNPs. With the linkage map, a total of 432.3 Mb of sequence from 2766 scaffolds was anchored to create the Phaseolus vulgaris v1.0 assembly, which accounted for approximately 89% of the 487 Mb of available sequence scaffolds of the Phaseolus vulgaris v0.9 assembly. A core set of 6000 SNPs (BARCBean6K_3 BeadChip) with high genotyping quality and polymorphism was selected based on the genotyping of 365 dry bean and 134 snap bean accessions with the BARCBean6K_1 and BARCBean6K_2 BeadChips. The BARCBean6K_3 BeadChip is a useful tool for genetics and genomics research and it is widely used by breeders and geneticists in the United States and abroad.