Association mapping of a locus that confers Southern stem canker resistance in soybean (original) (raw)
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Background Southern stem canker (SSC), caused by Diaporthe aspalathi (E. Jansen, Castl. & Crous), is an important soybean disease that has been responsible for severe losses in the past. The main strategy for controlling this fungus involves the introgression of resistance genes. Thus far, five main loci have been associated with resistance to SSC. However, there is a lack of information about useful allelic variation at these loci. In this work, a genome-wide association study (GWAS) was performed to identify allelic variation associated with resistance against Diaporthe aspalathi and to provide molecular markers that will be useful in breeding programs. Results We characterized the response to SSC infection in a panel of 295 accessions from different regions of the world, including important Brazilian elite cultivars. Using a GBS approach, the panel was genotyped, and we identified marker loci associated with Diaporthe aspalathi resistance through GWAS. We identified 19 SNPs assoc...
Molecular Breeding, 2017
Genetic resistance to soybean stem canker, caused by the fungus Diaporthe phaseolorum var. meridionalis (Dpm), is controlled by five major, dominant, nonallelic genes Rdm1 to Rdm5. A genomic region containing the Rdm4 and Rdm5 genes was first described in Hutcheson soybean, where they were found to confer specific resistance to Argentinean physiological races of Dpm. Here, we report the genetic mapping of Rdm4 and Rdm5 loci using two pheno-and genotypically characterized F 2:3 populations derived from Hutcheson cultivar. The mapping populations were screened with amplified fragment length polymorphism (AFLP) markers using bulk segregant analysis, and with simple sequence repeat (SSR) markers. Linkage analysis indicated that the Rdm4 and Rdm5 resistance loci were located in a genomic region collinear with the molecular linkage group (MLG) A2 (chromosome 8) of the soybean genetic map. The linkage group contains two SSR markers, Sat_162 and Satt233, flanking the Rdm4 and Rdm5 loci. These SSR will be useful to increase the efficiency of selection in breeding programs aimed to incorporate Rdm4 and Rdm5 genes into soybean elite germplasm.
Phytopathology, 2016
Genetic resistance is a key strategy for disease management in soybean. Over the last 50 years, soybean germplasm has been phenotyped for resistance to many pathogens, resulting in the development of disease-resistant elite breeding lines and commercial cultivars. While biparental linkage mapping has been used to identify disease resistance loci, genome-wide association studies (GWAS) using high-density and high-quality markers such as single nucleotide polymorphisms (SNPs) has become a powerful tool to associate molecular markers and phenotypes. The objective of our study was to provide a comprehensive understanding of disease resistance in the United States Department of Agriculture Agricultural Research Service Soybean Germplasm Collection by using phenotypic data in the public Germplasm Resources Information Network and public SNP data (SoySNP50K). We identified SNPs significantly associated with disease ratings from one bacterial disease, five fungal diseases, two diseases caus...
Genome Wide Association Mapping of Resistance in Soybean with a Genotyping-by-Sequencing Approach
The Plant Genome, 2014
Sclerotinia stem rot (SSR) is one of the most important pests in cool soybean growing regions of the Northeastern United States and Canada. However, the intensity of infestations varies considerably from year to year according to weather conditions, thus making it difficult for breeders to select under uniform disease pressure. Selection for resistance to SSR would be greatly facilitated by the use of molecular markers. In this work, a collection of 130 lines was inoculated using the cotton pad method and was genetically characterized using a genotyping-by-sequencing (GBS) protocol optimized for soybean. Genome-wide association mapping (AM) and linkage disequilibrium (LD) analyses were performed with 7864 single nucleotide polymorphisms (SNPs). Linkage disequilibrium varied considerably over physical distance, reaching a r 2 value of 0.2 after 8.5 Mb in the pericentromeric region and 0.5 Mb in the telomeric region. The mixed linear model (MLM) performed very well in accounting for population structure and relatedness, as only 5.5% of the observed p-values were < 0.05. The strongest association was found on chromosome Gm15 (p-value = 1.38 × 10 -6 ; q-value [adjusted p-value] = 0.011). Two additional SNP markers in the vicinity had a q-value < 0.1. This marker was validated in the progeny of a biparental cross, where F 4:6 lines carrying the susceptibility allele developed lesions 17.6 mm longer than lines carrying the resistance allele. Interestingly, other genes contributing to resistance to pathogens have been reported in this region of Gm15. Three other association peaks having a q-value < 0.1 were detected on chromosomes Gm01, Gm19, and Gm20.
Journal of Plant Genome Sciences, 2012
Soybeans [Glycine max (L.) Merr.] are susceptible to many diseases including fungal diseases such as soybean sudden death syndrome (SDS). Several studies reported SDS resistance quantitative trait loci (QTL) on the soybean genome using different recombinant inbred line (RIL) populations and low density genetic linkage maps. High density exclusively single nucleotide polymorphisms-based (SNP-based) maps were not yet reported in soybean. The objectives of this study were (1) to construct a high density SNP-based genetic linkage map of soybean using the 'PI438489B' by 'Hamilton' (PIxH, n=50) recombinant inbred line population, and (2) to map QTL for SDS resistance using this high-density reliable genetic SNP-based map. The PI438489B by Hamilton high-density SNP-based genetic map was a high density map composed of 31 LGs, 648 SNPs, and covered 1,524.7 cM with an average of 2.37 cM between two adjacent SNP markers. Fourteen significant QTL were identified for SDS resistance using interval mapping (IM) and composite interval mapping (CIM) with LOD scores that ranged between 2.6 and 5.0. Twelve QTL were identified for foliar disease severity (FDS) and three QTL for root rot severity (RRS) of which one QTL underlain both FDS and RRS. The fourteen QTL were mapped onto ten separate chromosomes of the soybean genome. Seven of the intervals encompassing the QTL had been identified previously (on LGs C1, C2, D1b, G, L, N and O) associated with resistance to SDS but seven were novel (LGs A2 (2), B1, C2, D1a, D1b and O). We constructed the first PI438489B by Hamilton exclusively SNP-Based map and identified fourteen QTL that underlie SDS resistance including both resistances to foliar and root rot symptoms caused by Fusarium virguliforme infection. The QTL discovered here for SDS resistance could be useful to include in breeding programs in developing soybean cultivars resistant to SDS.
Agrárias: Pesquisa e Inovação nas Ciências que Alimentam o Mundo VII, 2021
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Sclerotinia stem rot (SSR) is one of the most important pests in cool soybean growing regions of the Northeastern United States and Canada. However, the intensity of infestations varies considerably from year to year according to weather conditions, thus making it difficult for breeders to select under uniform disease pressure. Selection for resistance to SSR would be greatly facilitated by the use of molecular markers. In this work, a collection of 130 lines was inoculated using the cotton pad method and was genetically characterized using a genotyping-by-sequencing (GBS) protocol optimized for soybean. Genome-wide association mapping (AM) and linkage disequilibrium (LD) analyses were performed with 7864 single nucleotide polymorphisms (SNPs). Linkage disequilibrium varied considerably over physical distance, reaching a r 2 value of 0.2 after 8.5 Mb in the pericentromeric region and 0.5 Mb in the telomeric region. The mixed linear model (MLM) performed very well in accounting for population structure and relatedness, as only 5.5% of the observed p-values were < 0.05. The strongest association was found on chromosome Gm15 (p-value = 1.38 × 10 -6 ; q-value [adjusted p-value] = 0.011). Two additional SNP markers in the vicinity had a q-value < 0.1. This marker was validated in the progeny of a biparental cross, where F 4:6 lines carrying the susceptibility allele developed lesions 17.6 mm longer than lines carrying the resistance allele. Interestingly, other genes contributing to resistance to pathogens have been reported in this region of Gm15. Three other association peaks having a q-value < 0.1 were detected on chromosomes Gm01, Gm19, and Gm20.
From Hype to Hope: Genome-Wide Association Studies in Soybean
The Soybean Genome, 2017
Association mapping studies in plants including soybean contribute to not only detecting the genetic basis of variation in yield, physiological, developmental, and morphological traits but also bringing together researchers to assemble core collections and develop genetic platforms for genotyping, phenotyping, analysis, and interpretation. The establishment of the unified mixed model greatly facilitated association mapping studies in plants and further methodology work in general. Association mapping is well positioned to exploit the advances in next-generation genomic technologies and high-through-put phenotyping. Genome-wide association studies are expected to increase dramatically once genome sequences are obtained. Moving forward, researchers in soybean and all other major plant genetics need to develop improved genetic designs and computational tools to address several challenges such as missing heritability, new gene identification, genotyping-by-sequencing, rare variants, imputation, high-throughput phenotyping, and integration of collective biological information and analytical tools into GWAS. In this chapter, we describe major progress in understanding population structure, advancements in design, and implementation of association mapping and summarize examples of association mapping in soybean. Finally, major opportunities with potential implications in soybean genetics are discussed as well.
Genes, 2021
Fusarium wilt (Fusarium oxysporum f. sp. phaseoli, Fop) is one of the main fungal soil diseases in common bean. The aim of the present study was to identify genomic regions associated with Fop resistance through genome-wide association studies (GWAS) in a Mesoamerican Diversity Panel (MDP) and to identify potential common bean sources of Fop’s resistance. The MDP was genotyped with BARCBean6K_3BeadChip and evaluated for Fop resistance with two different monosporic strains using the root-dip method. Disease severity rating (DSR) and the area under the disease progress curve (AUDPC), at 21 days after inoculation (DAI), were used for GWAS performed with FarmCPU model. The p-value of each SNP was determined by resampling method and Bonferroni test. For UFV01 strain, two significant single nucleotide polymorphisms (SNPs) were mapped on the Pv05 and Pv11 for AUDPC, and the same SNP (ss715648096) on Pv11 was associated with AUDPC and DSR. Another SNP, mapped on Pv03, showed significance fo...
The Plant Genome, 2020
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.