A Genome-Wide Association Study for Agronomic Traits in Soybean Using SNP Markers and SNP-Based Haplotype Analysis

Mapping quantitative trait loci through the use of linkage disequilibrium (LD) in populations of unrelated individuals provides a valuable approach for dissecting the genetic basis of complex traits in soybean (Glycine max). The haplotype-based genome-wide association study (GWAS) has now been propo...

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Veröffentlicht in:PloS one 2017-02, Vol.12 (2), p.e0171105-e0171105
Hauptverfasser: Contreras-Soto, Rodrigo Iván, Mora, Freddy, de Oliveira, Marco Antônio Rott, Higashi, Wilson, Scapim, Carlos Alberto, Schuster, Ivan
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Sprache:eng
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Zusammenfassung:Mapping quantitative trait loci through the use of linkage disequilibrium (LD) in populations of unrelated individuals provides a valuable approach for dissecting the genetic basis of complex traits in soybean (Glycine max). The haplotype-based genome-wide association study (GWAS) has now been proposed as a complementary approach to intensify benefits from LD, which enable to assess the genetic determinants of agronomic traits. In this study a GWAS was undertaken to identify genomic regions that control 100-seed weight (SW), plant height (PH) and seed yield (SY) in a soybean association mapping panel using single nucleotide polymorphism (SNP) markers and haplotype information. The soybean cultivars (N = 169) were field-evaluated across four locations of southern Brazil. The genome-wide haplotype association analysis (941 haplotypes) identified eleven, seventeen and fifty-nine SNP-based haplotypes significantly associated with SY, SW and PH, respectively. Although most marker-trait associations were environment and trait specific, stable haplotype associations were identified for SY and SW across environments (i.e., haplotypes Gm12_Hap12). The haplotype block 42 on Chr19 (Gm19_Hap42) was confirmed to be associated with PH in two environments. These findings enable us to refine the breeding strategy for tropical soybean, which confirm that haplotype-based GWAS can provide new insights on the genetic determinants that are not captured by the single-marker approach.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0171105