Identification and validation of loci governing seed coat color by combining association mapping and bulk segregation analysis in soybean

Jian Song, Zhangxiong Liu, Huilong Hong, Yansong Ma, Long Tian, Xinxiu Li, Ying Hui Li, Rongxia Guan, Yong Guo, Li Juan Qiu

Research output: Contribution to journalArticlepeer-review

Abstract

Soybean seed coat exists in a range of colors from yellow, green, brown, black, to bicolor. Classical genetic analysis suggested that soybean seed color was a moderately complex trait controlled by multi-loci. However, only a couple of loci could be detected using a single biparental segregating population. In this study, a combination of association mapping and bulk segregation analysis was employed to identify genes/loci governing this trait in soybean. A total of 14 loci, including nine novel and five previously reported ones, were identified using 176,065 coding SNPs selected from entire SNP dataset among 56 soybean accessions. Four of these loci were confirmed and further mapped using a biparental population developed from the cross between ZP95-5383 (yellow seed color) and NY279 (brown seed color), in which different seed coat colors were further dissected into simple trait pairs (green/yellow, green/black, green/brown, yellow/black, yellow/brown, and black/brown) by continuously developing residual heterozygous lines. By genotyping entire F2 population using flanking markers located in fine-mapping regions, the genetic basis of seed coat color was fully dissected and these four loci could explain all variations of seed colors in this population. These findings will be useful for map-based cloning of genes as well as marker-assisted breeding in soybean. This work also provides an alternative strategy for systematically isolating genes controlling relative complex trait by association analysis followed by biparental mapping.

Original languageEnglish
Article numbere0159064
JournalPLoS ONE
Volume11
Issue number7
DOIs
StatePublished - Jul 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Song et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

ASJC Scopus subject areas

  • General

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