Abstract
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.
Highlights
One of the most important crops for global production of vegetable protein and oil is Soybean (Glycine max)
This study was undertaken to identify genomic regions associated with key complex traits in soybean, using a genome-wide association approach
An advantage of using a genetically broad panel is the opportunity to explore alleles that could potentially be used in a marker-assisted selection context to improve agronomic traits in soybean
Summary
One of the most important crops for global production of vegetable protein and oil is Soybean (Glycine max). Due to quantitative inheritance of agronomic traits (seed protein, oil content and seed weight, for instance), several efforts have been made to understand the genetic basis of such complex traits [1, 2, 3, 4, 5]. With improved analytical methods for analyzing genome-wide association studies (GWAS), genomic selection (GS) and cost effective genotyping techniques there are promising forecasts in improving complex genetic traits in soybean [5]. A Genome-Wide Association Study for Key Complex Traits in Soybean not have a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section
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