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Genetic dissection of the relationship between plant architecture and yield component traits in soybean ( Glycine max ) by association analysis across multiple environments
Author(s) -
Zhang Huairen,
Hao Derong,
Sitoe Hélder Manuel,
Yin Zhitong,
Hu Zhenbin,
Zhang Guozheng,
Yu Deyue
Publication year - 2015
Publication title -
plant breeding
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.583
H-Index - 71
eISSN - 1439-0523
pISSN - 0179-9541
DOI - 10.1111/pbr.12305
Subject(s) - genetic architecture , biology , allele , epistasis , snp , genetics , yield (engineering) , quantitative trait locus , selection (genetic algorithm) , glycine soja , genetic association , glycine , genotype , gene , single nucleotide polymorphism , computer science , materials science , artificial intelligence , metallurgy , amino acid
Plant architecture and yield components are critical for the determination of seed yield in soybean. In this study, we performed genetic association analysis to dissect the relationships between plant architecture and yield component traits. Two hundred and nineteen accessions were employed, and eight agronomic traits were evaluated in six environments. Our results revealed strong positive correlations of plant architecture traits with yield components and the significant association of 4 SNP s with plant architecture traits and of 7 SNP s with yield component traits in two or more environments. Eight SNP s were co‐associated with two traits. Based on the phenotypic effects of the alleles of the detected SNP s, the best alleles were mined for twenty‐three distinct SNP s. Fifteen typical carrier materials harbouring the best allele effects were also mined. Twenty parental combinations were proposed by pyramiding possible alleles per SNP in one individual (excluding possible epistatic effects). These proposed combinations with the best alleles and carrier materials will aid in the improvement of targeted traits and marker‐assisted selection ( MAS ) efficiency in soybean breeding.