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.

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.

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.

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.

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.

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.

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.

Genome sequence of the palaeopolyploid soybean.

Soybean (Glycine max) is one of the most important crop plants for seed protein and oil content, and for its capacity to fix atmospheric nitrogen through symbioses with soil-borne microorganisms. We sequenced the 1.1-gigabase genome by a whole-genome shotgun approach and integrated it with physical and high-density genetic maps to create a chromosome-scale draft sequence assembly. We predict 46,430 protein-coding genes, 70% more than Arabidopsis and similar to the poplar genome which, like soybean, is an ancient polyploid (palaeopolyploid). About 78% of the predicted genes occur in chromosome ends, which comprise less than one-half of the genome but account for nearly all of the genetic recombination. Genome duplications occurred at approximately 59 and 13 million years ago, resulting in a highly duplicated genome with nearly 75% of the genes present in multiple copies. The two duplication events were followed by gene diversification and loss, and numerous chromosome rearrangements. An accurate soybean genome sequence will facilitate the identification of the genetic basis of many soybean traits, and accelerate the creation of improved soybean varieties.

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 for flowering time, maturity dates and plant height in early maturing soybean (Glycine max) germplasm.

BACKGROUND: Soybean (Glycine max) is a photoperiod-sensitive and self-pollinated species. Days to flowering (DTF) and maturity (DTM), duration of flowering-to-maturity (DFTM) and plant height (PH) are crucial for soybean adaptability and yield. To dissect the genetic architecture of these agronomically important traits, a population consisting of 309 early maturity soybean germplasm accessions was genotyped with the Illumina Infinium SoySNP50K BeadChip and phenotyped in multiple environments. A genome-wide association study (GWAS) was conducted using a mixed linear model that involves both relative kinship and population structure. RESULTS: The linkage disequilibrium (LD) decayed slowly in soybean, and a substantial difference in LD pattern was observed between euchromatic and heterochromatic regions. A total of 27, 6, 18 and 27 loci for DTF, DTM, DFTM and PH were detected via GWAS, respectively. The Dt1 gene was identified in the locus strongly associated with both DTM and PH. Ten candidate genes homologous to Arabidopsis flowering genes were identified near the peak single nucleotide polymorphisms (SNPs) associated with DTF. Four of them encode MADS-domain containing proteins. Additionally, a pectin lyase-like gene was also identified in a major-effect locus for PH where LD decayed rapidly. CONCLUSIONS: This study identified multiple new loci and refined chromosomal regions of known loci associated with DTF, DTM, DFTM and/or PH in soybean. It demonstrates that GWAS is powerful in dissecting complex traits and identifying candidate genes although LD decayed slowly in soybean. The loci and trait-associated SNPs identified in this study can be used for soybean genetic improvement, especially the major-effect loci associated with PH could be used to improve soybean yield potential. The candidate genes may serve as promising targets for studies of molecular mechanisms underlying the related traits in soybean.

Pericentromeric effects shape the patterns of divergence, retention, and expression of duplicated genes in the paleopolyploid soybean.

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.

Identification and evaluation of quantitative trait loci underlying resistance to multiple HG types of soybean cyst nematode in soybean PI 437655.

KEY MESSAGE: We performed QTL analysis for SCN resistance in PI 437655 in two mapping populations, characterized CNV of Rhg1 through whole-genome resequencing and evaluated the effects of QTL pyramiding to enhance resistance. Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most serious pests of soybean worldwide. PI 437655 has broader resistance to SCN HG types than PI 88788. The objectives of this study were to identify quantitative trait loci (QTL) underlying SCN resistance in PI 437655, and to evaluate the QTL for their contribution to SCN resistance. Two F6:7 recombinant inbred line populations, derived from cv. Williams 82 × PI 437655 and cv. Hutcheson × PI 437655 crosses, were evaluated for resistance to SCN HG types 1.2.5.7 (PA2), 0 (PA3), 1.3.5.6.7 (PA14), and 1.2.3.4.5.6.7 (LY2). The 1,536 SNP array was used to genotype the mapping populations and construct genetic linkage maps. Two significant QTL were consistently mapped on chromosomes (Chr.) 18 and 20 in these two populations. One QTL on Chr. 18, which corresponds to the known Rhg1 locus, contributed resistance to SCN HG types 1.2.5.7, 0, 1.3.5.6.7, and 1.2.3.4.5.6.7 (PA2, PA3, PA14, and LY2, respectively). Copy number variation (CNV) analysis by whole-genome resequencing showed that PI 437655 and PI 88788 had similar CNV at the Rhg1 locus. The QTL on Chr. 20 contributed resistance to SCN HG types 1.3.5.6.7 (PA14) and 1.2.3.4.5.6.7 (LY2). Evaluation of both QTL showed that pyramiding of Rhg1 and the QTL on Chr. 20 significantly improved the resistance to SCN HG types 1.3.5.6.7 (PA14) and 1.2.3.4.5.6.7 (LY2) in both populations. Our studies provided useful information for deploying PI 437655 as a donor for SCN resistance in soybean breeding through marker-assisted selection.

Genome-wide association study (GWAS) of carbon isotope ratio (δ13C) in diverse soybean [Glycine max (L.) Merr.] genotypes.

KEY MESSAGE: 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.

Confirmation of delayed canopy wilting QTLs from multiple soybean mapping populations.

KEY MESSAGE: QTLs for delayed canopy wilting from five soybean populations were projected onto the consensus map to identify eight QTL clusters that had QTLs from at least two independent populations. Quantitative trait loci (QTLs) for canopy wilting were identified in five recombinant inbred line (RIL) populations, 93705 KS4895 × Jackson, 08705 KS4895 × Jackson, KS4895 × PI 424140, A5959 × PI 416937, and Benning × PI 416937 in a total of 15 site-years. For most environments, heritability of canopy wilting ranged from 0.65 to 0.85 but was somewhat lower when averaged over environments. Putative QTLs were identified with composite interval mapping and/or multiple interval mapping methods in each population and positioned on the consensus map along with their 95% confidence intervals (CIs). We initially found nine QTL clusters with overlapping CIs on Gm02, Gm05, Gm11, Gm14, Gm17, and Gm19 identified from at least two different populations, but a simulation study indicated that the QTLs on Gm14 could be false positives. A QTL on Gm08 in the 93705 KS4895 × Jackson population co-segregated with a QTL for wilting published previously in a Kefeng1 × Nannong 1138-2 population, indicating that this may be an additional QTL cluster. Excluding the QTL cluster on Gm14, results of the simulation study indicated that the eight remaining QTL clusters and the QTL on Gm08 appeared to be authentic QTLs. QTL × year interactions indicated that QTLs were stable over years except for major QTLs on Gm11 and Gm19. The stability of QTLs located on seven clusters indicates that they are possible candidates for use in marker-assisted selection.

Application of in silico bulked segregant analysis for rapid development of markers linked to Bean common mosaic virus resistance in common bean.

BACKGROUND: Common bean was one of the first crops that benefited from the development and utilization of molecular marker-assisted selection (MAS) for major disease resistance genes. Efficiency of MAS for breeding common bean is still hampered, however, due to the dominance, linkage phase, and loose linkage of previously developed markers. Here we applied in silico bulked segregant analysis (BSA) to the BeanCAP diversity panel, composed of over 500 lines and genotyped with the BARCBEAN_3 6K SNP BeadChip, to develop codominant and tightly linked markers to the I gene controlling resistance to Bean common mosaic virus (BCMV). RESULTS: We physically mapped the genomic region underlying the I gene. This locus, in the distal arm of chromosome Pv02, contains seven putative NBS-LRR-type disease resistance genes. Two contrasting bulks, containing BCMV host differentials and ten BeanCAP lines with known disease reaction to BCMV, were subjected to in silico BSA for targeting the I gene and flanking sequences. Two distinct haplotypes, containing a cluster of six single nucleotide polymorphisms (SNP), were associated with resistance or susceptibility to BCMV. One-hundred and twenty-two lines, including 115 of the BeanCAP panel, were screened for BCMV resistance in the greenhouse, and all of the resistant or susceptible plants displayed distinct SNP haplotypes as those found in the two bulks. The resistant/susceptible haplotypes were validated in 98 recombinant inbred lines segregating for BCMV resistance. The closest SNP (~25-32 kb) to the distal NBS-LRR gene model for the I gene locus was targeted for conversion to codominant KASP (Kompetitive Allele Specific PCR) and CAPS (Cleaved Amplified Polymorphic Sequence) markers. Both marker systems accurately predicted the disease reaction to BCMV conferred by the I gene in all screened lines of this study. CONCLUSIONS: We demonstrated the utility of the in silico BSA approach using genetically diverse germplasm, genotyped with a high-density SNP chip array, to discover SNP variation at a specific targeted genomic region. In common bean, many disease resistance genes are mapped and their physical genomic position can now be determined, thus the application of this approach will facilitate further development of codominant and tightly linked markers for use in MAS.

Genome-wide association mapping of quantitative resistance to sudden death syndrome in soybean.

BACKGROUND: Sudden death syndrome (SDS) is a serious threat to soybean production that can be managed with host plant resistance. To dissect the genetic architecture of quantitative resistance to the disease in soybean, two independent association panels of elite soybean cultivars, consisting of 392 and 300 unique accessions, respectively, were evaluated for SDS resistance in multiple environments and years. The two association panels were genotyped with 52,041 and 5,361 single nucleotide polymorphisms (SNPs), respectively. Genome-wide association mapping was carried out using a mixed linear model that accounted for population structure and cryptic relatedness. RESULT: A total of 20 loci underlying SDS resistance were identified in the two independent studies, including 7 loci localized in previously mapped QTL intervals and 13 novel loci. One strong peak of association on chromosome 18, associated with all disease assessment criteria across the two panels, spanned a physical region of 1.2 Mb around a previously cloned SDS resistance gene (GmRLK18-1) in locus Rfs2. An additional variant independently associated with SDS resistance was also found in this genomic region. Other peaks were within, or close to, sequences annotated as homologous to genes previously shown to be involved in plant disease resistance. The identified loci explained an average of 54.5% of the phenotypic variance measured by different disease assessment criteria. CONCLUSIONS: This study identified multiple novel loci and refined the map locations of known loci related to SDS resistance. These insights into the genetic basis of SDS resistance can now be used to further enhance durable resistance to SDS in soybean. Additionally, the associations identified here provide a basis for further efforts to pinpoint causal variants and to clarify how the implicated genes affect SDS resistance in soybean.

A genome-wide association study of seed protein and oil content in soybean.

BACKGROUND: Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content. RESULTS: A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r2) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil. CONCLUSIONS: This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s).

Identification and validation of quantitative trait loci for seed yield, oil and protein contents in two recombinant inbred line populations of soybean.

Soybean seeds contain high levels of oil and protein, and are the important sources of vegetable oil and plant protein for human consumption and livestock feed. Increased seed yield, oil and protein contents are the main objectives of soybean breeding. The objectives of this study were to identify and validate quantitative trait loci (QTLs) associated with seed yield, oil and protein contents in two recombinant inbred line populations, and to evaluate the consistency of QTLs across different environments, studies and genetic backgrounds. Both the mapping population (SD02-4-59 × A02-381100) and validation population (SD02-911 × SD00-1501) were phenotyped for the three traits in multiple environments. Genetic analysis indicated that oil and protein contents showed high heritabilities while yield exhibited a lower heritability in both populations. Based on a linkage map constructed previously with the mapping population and using composite interval mapping and/or interval mapping analysis, 12 QTLs for seed yield, 16 QTLs for oil content and 11 QTLs for protein content were consistently detected in multiple environments and/or the average data over all environments. Of the QTLs detected in the mapping population, five QTLs for seed yield, eight QTLs for oil content and five QTLs for protein content were confirmed in the validation population by single marker analysis in at least one environment and the average data and by ANOVA over all environments. Eight of these validated QTLs were newly identified. Compared with the other studies, seven QTLs for seed yield, eight QTLs for oil content and nine QTLs for protein content further verified the previously reported QTLs. These QTLs will be useful for breeding higher yield and better quality cultivars, and help effectively and efficiently improve yield potential and nutritional quality in soybean.

Inheritance of soybean aphid resistance in 21 soybean plant introductions.

KEY MESSAGE: The Rag2 region was frequently identified among 21 F 2 populations evaluated for soybean aphid resistance, and dominant gene action and single-gene resistance were also commonly identified. The soybean aphid [Aphis glycines Matsumura (Hemiptera: Aphididae)] is one of the most important insect pests of soybean [Glycine max (L.) Merr] in the northern USA and southern Canada, and four resistance loci (Rag1-rag4) have been discovered since the pest was identified in the USA in 2000. The objective of this research was to determine whether resistance expression in recently identified soybean aphid-resistant plant introductions (PIs) was associated with the four Rag loci using a collection of 21 F2 populations. The F2 populations were phenotyped with soybean aphid biotype 1, which is avirulent on plants having any of the currently identified Rag genes, using choice tests in the greenhouse and were tested with genetic markers linked to the four Rag loci. The phenotyping results indicate that soybean aphid resistance is controlled by a single dominant gene in 14 PIs, by two genes in three PIs, and four PIs had no clear Mendelian inheritance patterns. Genetic markers flanking Rag2 were significantly associated with aphid resistance in 20 PIs, the Rag1 region was significantly identified in five PIs, and the Rag3 region was identified in one PI. These results show that single dominant gene action at the Rag2 region may be a major source for aphid resistance in the USDA soybean germplasm collection.

Mapping the low palmitate fap1 mutation and validation of its effects in soybean oil and agronomic traits in three soybean populations.

KEY MESSAGE: fap 1 mutation is caused by a G174A change in GmKASIIIA that disrupts a donor splice site recognition and creates a GATCTG motif that enhanced its expression. Soybean oil with reduced palmitic acid content is desirable to reduce the health risks associated with consumption of this fatty acid. The objectives of this study were: to identify the genomic location of the reduced palmitate fap1 mutation, determine its molecular basis, estimate the amount of phenotypic variation in fatty acid composition explained by this locus, determine if there are epistatic interactions between the fap1 and fap nc loci and, determine if the fap1 mutation has pleiotropic effects on seed yield, oil and protein content in three soybean populations. This study detected two major QTL for 16:0 content located in chromosome 5 (GmFATB1a, fap nc) and chromosome 9 near BARCSOYSSR_09_1707 that explained, with their interaction, 66-94 % of the variation in 16:0 content in the three populations. Sequencing results of a putative candidate gene, GmKASIIIA, revealed a single unique polymorphism in the germplasm line C1726, which was predicted to disrupt the donor splice site recognition between exon one and intron one and produce a truncated KASIIIA protein. This G to A change also created the GATCTG motif that enhanced gene expression of the mutated GmKASIIIA gene. Lines homozygous for the GmKASIIIA mutation (fap1) had a significant reduction in 16:0, 18:0, and oil content; and an increase in unsaturated fatty acids content. There were significant epistatic interactions between GmKASIIIA (fap1) and fap nc for 16:0 and oil contents, and seed yield in two populations. In conclusion, the fap1 phenotype is caused by a single unique SNP in the GmKASIIIA gene.