Identification of new loci for salt tolerance in soybean by high-resolution genome-wide association mapping

Abstract

Background Salinity is an abiotic stress that negatively affects soybean [ Glycine max (L.) Merr.] seed yield. Although a major gene for salt tolerance was identified and consistently mapped to chromosome (Chr.) 3 by linkage mapping studies, it does not fully explain genetic variability for tolerance in soybean germplasm. In this study, a genome-wide association study (GWAS) was performed to map genomic regions for salt tolerance in a diverse panel of 305 soybean accessions using a single nucleotide polymorphism (SNP) dataset derived from the SoySNP50K iSelect BeadChip. A second GWAS was also conducted in a subset of 234 accessions using another 3.7 M SNP dataset derived from a whole-genome resequencing (WGRS) study. In addition, three gene-based markers (GBM) of the known gene, Glyma03g32900 , on Chr. 3 were also integrated into the two datasets. Salt tolerance among soybean lines was evaluated by leaf scorch score (LSS), chlorophyll content ratio (CCR), leaf sodium content (LSC), and leaf chloride content (LCC). Results For both association studies, a major locus for salt tolerance on Chr. 3 was confirmed by a number of significant SNPs, of which three gene-based SNP markers, Salt-20, Salt14056 and Salt11655, had the highest association with all four traits studied. Also, additional genomic regions on Chrs. 1, 8, and 18 were found to be associated with various traits measured in the second GWAS using the WGRS-derived SNP dataset. Conclusions A region identified on Chr. 8 was identified to be associated with all four traits and predicted as a new minor locus for salt tolerance in soybean. The candidate genes harbored in this minor locus may help reveal the molecular mechanism involved in salt tolerance and to improve tolerance in soybean cultivars. The significant SNPs will be useful for marker-assisted selection for salt tolerance in soybean breeding programs. Electronic supplementary material The online version of this article (10.1186/s12864-019-5662-9) contains supplementary material, which is available to authorized users.

Jasmonates and Plant Salt Stress: Molecular Players, Physiological Effects, and Improving Tolerance by Using Genome-Associated Tools

“…In this context, QTL mapping and GWASs provide a suitable opportunity to identify genes responsible for quantitative trait variation such as salt tolerance. In this regard, genetic factors associated with salt stress have been previously investigated in several crops, such as rice [ 41 , 196 , 197 ], barley [ 198 , 199 ], wheat [ 200 , 201 ], chickpea [ 202 ], sesame [ 203 ], cotton [ 204 , 205 ], and soybean [ 206 ].…”

Genomic interventions for sustainable agriculture

“…The edit(s) can be made in the actual gene, and hence, there are no position or dosage effects. Gene expression can be totally knocked out, which has previously been difficult using RNAi approaches, which usually lead to a diminution of gene expression but rarely to zero (Eamens et al, 2008). This also means that editing of candidate genes enables clear identification of single gene action.…”

“…Interestingly, the most significant SNP related to LSS was pinpointed in GmCHX1 gene, which explained 63% variation of the phenotype (Patil et al ., 2016). Likewise, GWAS of 234 lines elucidated genomic architecture of salinity tolerance in soybean with significant MTAs for leaf scorch score, chlorophyll content ratio, leaf sodium content and leaf chloride content (Do et al ., 2019).…”

Modulation of GmFAD3 expression alters responses to abiotic stress in soybean

“…Overexpression of fatty acid desaturases (FAD3 and FAD7) enhanced tolerance to cold stress in tomato (Dominguez et al ., 2010). In recent years, some novel genes/transcription factors have been characterized for modulating stress responsive genes associated with abiotic stress tolerance by genome-wide characterization (Li et al ., 2019;Do et al , 2019). Efforts have also been made to enhance abiotic stress tolerance in soybean by manipulating expression of several genes/transcription factors (Jumrani & Bhatia., 2019;Zhanget al ., 2019;Chen et al , 2019).…”