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

Abstract

BackgroundSudden 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.ResultA 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.ConclusionsThis 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.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-809) contains supplementary material, which is available to authorized users.

Genome-wide association study for soybean cyst nematode resistance in Chinese elite soybean cultivars

“…The inbreeding nature of soybean has resulted in a longrange LD decay. The long extent of LD decay estimate (220 kb) is very similar with previously published values (Wen et al 2014). The estimates of LD decay herein suggests that at least 5000 markers will be needed for whole genome scanning in soybean, as the soybean genome is known to extend over 1000 Mb.…”

“…However, due to the limited coverage of resistance sources, inadequate statistical procedures, and small mapping populations, many QTLs underlying SCN resistance, therefore, have remained un-detected. With the availability of a soybean reference genome sequence and the development of high-throughput single nucleotide polymorphism (SNP) assay platforms, association mapping (AM) has been demonstrated to be a powerful approach to dissect various traits, such as disease resistance, yield, and quality-related traits in soybean (Wen et al 2014(Wen et al , 2015Hao et al 2012a, b;Bastien et al 2014;Hwang et al 2014). Recent genomewide association study (GWAS) on 282 accessions of soybean breeding lines have detected significant signals at two loci corresponding to rhg1 and FGAM1, plus a third locus located at the end (55.9 Mb) of Chr.…”

Tracking footprints of selection associated with soybean adaptation to Central-East Europe environments

“…The identification of genes/ QTLs underlying phenotypic variation in soybean (Glycine max (L.) Merr.) has been based mostly on biparental linkage mapping (Salas et al 2006;Githiri et al 2007;Guzman et al 2007) and association mapping (Hu et al 2014;Wen et al 2014) approaches. To make association between phenotypic differences and the variability at molecular level more precise, these methods require a high level of segregating genetic and phenotypic variation at the genes of Electronic supplementary material The online version of this article (doi:10.1007/s10681-014-1313-z) contains supplementary material, which is available to authorized users.…”

Genome-wide association-mapping for fruit quality traits in tomato

“…It can be first used to detect the preliminary locations of QTLs to study the mechanisms underlying phenotypic variation, and then to use linkage analysis for more precise location of those QTLs that are of special interest (Mazzucato et al 2008;Atwell et al 2010;Xu et al 2013). Since the first use to dissect candidate genes on inbred maize lines (Thornsberry et al 2001), GWAS analyses have been widely constructed on a number of major plant species (Ruggieri et al 2014;Wen et al 2014;Hatzig et al 2015;Kumar et al 2015;Matsuda et al 2015;Pers et al 2015). Association mapping-also known as linkage disequilibrium (LD) mapping-is a promising genetic method for the dissection of complex traits in plants (Ersoz et al 2007;Saidou et al 2014).…”