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

Abstract

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.

Identification of resistance loci toward Phytophthora sojae in South Korean soybean plant introductions 407974B and 424487B

“…Using publicly available data sets, a GWAS analysis of 189 PIs identified significant regions on Chromosomes 3, 4, 5, 10, 14, 13, and 18 toward P. sojae isolates 1, 3, 7, 17, and 25 (Qin et al., 2017). Recently, GWAS analysis of 16 soybean panels comprising 1,813 accessions identified a total of 75 novel Rps loci for P. sojae (Van et al., 2020).…”

“…Also, Van et al. (2020) detected three Rps loci (qGF18‐1, qGF18‐2, and qGF18‐3) located near the Rps4/6 region.…”

“…In this QTL interval, the marker BARC-SOYSSR_18_1949 (57.97 Mb in Wm82.a2.v1) was significantly associated with the QTL 18-2 and near to ss715632438. Also, Van et al (2020) detected three Rps loci (qGF18-1, qGF18-2, and qGF18-3) located near the Rps4/6 region.…”

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

“…Among the different genotyping approaches performed in previous GWAS of soybean resistance to P. sojae , simple sequence repeat genotyping captured ∼500 markers (Sun et al., 2014), restriction‐site‐associated DNA genotyping identified 60K SNPs (Li et al., 2016), and the publicly available genotypic data from the SoySNP50K iSelect BeadCheap covered ∼35K SNPs, offering an average density of one marker every 29 kb (Rolling et al., 2020). In this study, we performed GWAS using the WGS dataset of 357 soybean PIs, which provided a catalog of over 5 million high‐quality SNPs (approximately one every 200 bp) across the genome offering an unprecedented genome coverage compared with previous GWA analyses performed for disease resistance in soybean (Van et al., 2021; Ludke et al., 2019; Qin et al., 2017). Owing to the large computational requirements to process such a large SNP catalog, SNPs in very high LD ( r 2 > 0.9) were pruned, which resulted in an effective marker number of ∼691K SNPs that captured the majority of the soybean genome.…”

“…In the specific context of the soybean– P. sojae interaction, different genotyping approaches have been used. These include simple sequence repeats (Sun et al., 2014), sequence‐based restriction‐site‐associated DNA (Li et al., 2016), and chip‐based genotyping with the SoySNP50K iSelect BeadChip (Ludke et al., 2019; Qin et al., 2017; Rolling et al., 2020; Schneider et al., 2016; Van et al., 2021). Advances in high‐throughput sequencing technologies have enabled rapid, affordable, and accurate whole‐genome sequencing (WGS) of a large number of individuals (Huang et al., 2013; Mace et al., 2013; Zhou et al., 2015).…”