Selection of soybean elite cultivars based on phenotypic and genomic characters related to lodging tolerance | Zendy

Liu Zhangxiong | Zendy; Li Huihui | Zendy; Fan Xuhong | Zendy; Huang Wen | Zendy; Yang Jiyu | Zendy; Zheng Yuhong | Zendy; Wen Zixiang | Zendy; Li Yinghui | Zendy; Wang Dechun | Zendy; Wang Shuming | Zendy; Qiu Lijuan | Zendy

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Selection of soybean elite cultivars based on phenotypic and genomic characters related to lodging tolerance

Author(s) -

Liu Zhangxiong,

Li Huihui,

Fan Xuhong,

Huang Wen,

Yang Jiyu,

Zheng Yuhong,

Wen Zixiang,

Li Yinghui,

Wang Dechun,

Wang Shuming,

Qiu Lijuan

Publication year - 2017

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.12495

Subject(s) - biology , quantitative trait locus , cultivar , best linear unbiased prediction , allele , genotype , snp , selection (genetic algorithm) , trait , genetics , association mapping , plant breeding , marker assisted selection , microbiology and biotechnology , agronomy , single nucleotide polymorphism , gene , artificial intelligence , computer science , programming language

Soybean lodging can result in serious yield reduction. Detecting the quantitative trait loci ( QTL ) associated with lodging tolerance for their further application in marker‐assisted selection ( MAS ) has the potential to enhance soybean breeding efficiency. In this study, a genome‐wide association analysis ( GWAS ) was performed to identify soybean accessions that could potentially be used to produce lodging‐tolerant varieties, based on the comprehensive evaluation of lodging scores ( LS ) obtained for the parental cultivar “Tokachi nagaha” and its 137 derived cultivars. Results showed that genotype, environment and genotype × environment interaction significantly influenced LS . Of the 31 significant SNP s identified, 22 were consistently detected in two or more environments and 27 SNP s were located in or close to agronomically important QTL mapped by linkage analysis. Best linear unbiased predictors ( BLUP s) of LS tend to decrease with the elite alleles contained by accessions increasing. Some excellent accessions, with lower BLUP s and D i (stability coefficients) values and more elite alleles, were selected. This study contributed to understand the genetic mechanism of lodging, providing genetic and phenotypic information for MAS .

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