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BMC Genomics

, 16:671

Plant genomics


BackgroundCrop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean Glycine max L. Merr

The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits.

ResultsTo this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms SNPs, and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio XP-CLR method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies GWAS were conducted on 7 selection traits targeted in soybean breeding grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content and 2 non-selection traits pubescence and flower color. Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified.

ConclusionsThese findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

KeywordsSelective sweep Single nucleotide polymorphisms GWAS Soybean AbbreviationsXP-CLRCross-population composite likelihood ratio

GWASGenome-wide association

SNPsSingle nucleotide polymorphisms

LDLinkage disequilibrium

QTLQuantitative trait locus

MAFMinor allele frequency


PCAPrincipal components analysis


GLMGeneral linear model

MLMMixed linear model

Electronic supplementary materialThe online version of this article doi:10.1186-s12864-015-1872-y contains supplementary material, which is available to authorized users.

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Autor: Zixiang Wen - John F. Boyse - Qijian Song - Perry B. Cregan - Dechun Wang


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