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

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

Research output: Contribution to journalArticlepeer-review

Abstract

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 SNPs identified, 22 were consistently detected in two or more environments and 27 SNPs were located in or close to agronomically important QTL mapped by linkage analysis. Best linear unbiased predictors (BLUPs) of LS tend to decrease with the elite alleles contained by accessions increasing. Some excellent accessions, with lower BLUPs and Di (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.

Original languageEnglish
Pages (from-to)526-538
Number of pages13
JournalPlant Breeding
Volume136
Issue number4
DOIs
StatePublished - Aug 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Blackwell Verlag GmbH

Keywords

  • additive main effects and multiplicative interaction model
  • genome-wide association analysis
  • lodging scores
  • lodging tolerance
  • soybean

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Genetics
  • Plant Science

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