Literature DB >> 23754189

Determination of the genetic architecture of seed size and shape via linkage and association analysis in soybean (Glycine max L. Merr.).

Zhenbin Hu1, Huairen Zhang, Guizhen Kan, Deyuan Ma, Dan Zhang, Guixia Shi, Delin Hong, Guozheng Zhang, Deyue Yu.   

Abstract

Seed-size traits, which are controlled by multiple genes in soybean, play an important role in determining seed yield, quality and appearance. However, the molecular mechanisms controlling the size of soybean seeds remain unclear, and little research has been done to investigate these mechanisms. In this study, we performed a genetic analysis to determine the genetic architecture of soybean seed size and shape via linkage and association analyses. We used 184 recombinant inbred lines (RILs) and 219 cultivated soybean accessions to evaluate seed length, seed width and seed height as seed-size traits, and their ratios of these values as seed-shape traits. Our results showed that all six traits had high heritability ranging from 92.46 to 98.47 %. Linkage analysis in the RILs identified 12 quantitative traits loci (QTLs), with five of these QTLs being associated with seed size, five with seed shape and two with the two first principal components of our principal component analysis (PCA). Association analysis in the 219 accessions detected 41 single nucleotide polymorphism (SNP)-trait associations, with 20 of these SNPs being associated with seed-size traits, seven with seed-shape traits and 14 with the two first principal components of our PCA. This analysis reveals that seed-size and seed-shape may be controlled by different genetic factors. Our results provide a greater understanding of phenotypic structure and genetic architecture of soybean seed, and the QTLs detected in this study form a basis for future fine mapping, quantitative trait gene cloning and molecular breeding in soybean.

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Year:  2013        PMID: 23754189     DOI: 10.1007/s10709-013-9723-8

Source DB:  PubMed          Journal:  Genetica        ISSN: 0016-6707            Impact factor:   1.082


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