Genome-wide association analyses of quantitative disease resistance in diverse sets of soybean [Glycine max (L.) Merr.] plant introductions

Rolling, William; Lake, Rhiannon; Dorrance, Anne E.; McHale, Leah K.

doi:10.1371/journal.pone.0227710

Cited by 20 publications

(23 citation statements)

References 99 publications

(163 reference statements)

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“…Many known Rps genes are not effective towards all populations of P. sojae (Anderson et al., 2012; Costamilan et al., 2013; Dorrance et al., 2016; Kaitany et al., 2001; Ryley et al., 1998; Yan & Nelson, 2019; Yang et al., 2019), yet a wealth of data exits for the resistance reaction of PIs to various isolates with complex pathotypes (Matthiesen et al., 2016; Rolling et al., 2020; USDA GRIN database). Thus, the purpose of our study was to identify novel P. sojae resistance loci via GWA analyses from panels of soybean PIs with available P. sojae reaction data, especially with several isolates of complex pathotypes.…”

Section: Resultsmentioning

confidence: 99%

“…A total of 429 (Panel 3) and 460 (Panel 4) G. max accessions were phenotyped for resistance against the complex P. sojae isolates, OH.121 and C2.S1, respectively (Rolling et al., 2020). In Panel 3 and Panel 4, 46 and 22 G. max lines showed resistance to OH.121 (10.7%) and C2.S1 (4.8%), respectively (Table 1).…”

Section: Resultsmentioning

confidence: 99%

“…1a, 1b, 1d, 1k, 2, 3a, 3c, 4, 5, 6, 7, 8) and PT2004 C2.S1 (vir. 1a, 1b, 1c, 1d, 1k, 2, 3a, 3c, 4, 5, 6, 7, 8) (Supplemental Table S2), as described in Rolling et al (2020) by the hypocotyl assay tested in the greenhouse. For GWA analyses, susceptible phenotype was assigned as "0," and resistance phenotype was assigned as "1".…”

Section: Plant Materials and Phenotypic Evaluationsmentioning

confidence: 99%

“…First, we used 448 G. max and 520 G. soja , known as a good source for genetic improvement in cultivated soybean (Hyten et al., 2006), accessions evaluated with a pool of three P. sojae isolates (Matthiesen et al., 2016). Secondly, we used two panels of 429 and 460 G. max PIs, examined with two highly virulent P. sojae isolates, respectively (Rolling, Schneider, Dorrance, & McHale, 2020). Finally, we collected publicly available data from USDA GRIN on the resistance phenotypes of G. max accessions against twelve races of P. sojae (Dorrance & Schmitthenner, 2000; Kyle, Nickell, Nelson, & Pedersen, 1998; Lohnes, Nickell, & Schmitthenner, 1996).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Plant Materials and Phenotypic Evaluationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…When available, MQTLs can be anchored to a reference genome, and relevant candidate genes could be proposed. A number of studies since 2009 are reported in crops for meta-QTL analysis of resistance against fungi and viruses, in order to propose valuable QTL to perform MAS, in particular in Theobroma cacao [ 78 ], barley [ 79 ], tetraploid cotton [ 80 , 81 ], pea [ 82 ], wheat [ 83 , 84 ], maize [ 85 ], peanut [ 86 ], grapevine [ 87 ], and soybean [ 88 ]. A study carried out in maize on the response to stem borers and storage pests feeding on leaves, stems, and kernels, from geographically diverse environments, pointed out the presence of a total of 104 resistance meta-QTLs from 382 individual QTLs, many of which were involved in several insect species, therefore generating a significant interest for multiple-insect resistance breeding [ 89 ].…”

Section: Toward the Identification Of Resistance Genes/locimentioning

confidence: 99%

Genomic Approaches to Identify Molecular Bases of Crop Resistance to Diseases and to Develop Future Breeding Strategies

Borrelli

Laidò

et al. 2021

IJMS

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Plant diseases are responsible for substantial crop losses each year and affect food security and agricultural sustainability. The improvement of crop resistance to pathogens through breeding represents an environmentally sound method for managing disease and minimizing these losses. The challenge is to breed varieties with a stable and broad-spectrum resistance. Different approaches, from markers to recent genomic and ‘post-genomic era’ technologies, will be reviewed in order to contribute to a better understanding of the complexity of host–pathogen interactions and genes, including those with small phenotypic effects and mechanisms that underlie resistance. An efficient combination of these approaches is herein proposed as the basis to develop a successful breeding strategy to obtain resistant crop varieties that yield higher in increasing disease scenarios.

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Mapping of partial resistance to Phytophthora sojae in soybean PIs using whole‐genome sequencing reveals a major QTL

et al. 2021

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In the last decade, more than 70 quantitative trait loci (QTL) related to soybean [Glycine max (L.) Merr.] partial resistance (PR) against Phytophthora sojae have been identified by genome‐wide association studies (GWAS). However, most of them have either a minor effect on the resistance level or are specific to a single phenotypic variable or one isolate, thereby limiting their use in breeding programs. In this study, we have used an analytical approach combining (a) the phenotypic characterization of a diverse panel of 357 soybean accessions for resistance to P. sojae captured through a single variable, corrected dry weight; (b) a new hydroponic assay allowing the inoculation of a combination of P. sojae isolates covering the spectrum of commercially relevant Rps genes; and (c) exhaustive genotyping through whole‐genome resequencing (WGS). This led to the identification of a novel P. sojae resistance QTL with a relatively major effect compared with the previously reported QTL. The QTL interval, spanning ∼500 kb on chromosome (Chr) 15, does not colocalize with previously reported QTL for P. sojae resistance. Plants carrying the favorable allele at this QTL were 60% more resistant. Eight genes were found to reside in the linkage disequilibrium (LD) block containing the peak single‐nucleotide polymorphism (SNP) including Glyma.15G217100, which encodes a major latex protein (MLP)‐like protein, with a functional annotation related to pathogen resistance. Expression analysis of Glyma.15G217100 indicated that it was nearly eight times more highly expressed in a group of plant introductions (PIs) carrying the resistant (R) allele compared with those carrying the susceptible (S) allele within a short period after inoculation. These results offer new and valuable options to develop improved soybean cultivars with broad resistance to P. sojae through marker‐assisted selection.

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Genome-wide association analyses of quantitative disease resistance in diverse sets of soybean [Glycine max (L.) Merr.] plant introductions

Cited by 20 publications

References 99 publications

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

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

Genomic Approaches to Identify Molecular Bases of Crop Resistance to Diseases and to Develop Future Breeding Strategies

Mapping of partial resistance to Phytophthora sojae in soybean PIs using whole‐genome sequencing reveals a major QTL

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