Dissection of the Genetic Basis of Yield-Related Traits in the Chinese Peanut Mini-Core Collection Through Genome-Wide Association Studies
文献类型: 外文期刊
第一作者: Zhou, Xiaojing
作者: Zhou, Xiaojing;Guo, Jianbin;Huang, Li;Luo, Huaiyong;Liu, Nian;Chen, Weigang;Lei, Yong;Liao, Boshou;Jiang, Huifang;Pandey, Manish K.;Varshney, Rajeev K.
作者机构:
关键词: yield-related traits; mini-core collection; GWAS; diagnostic marker; peanut
期刊名称:FRONTIERS IN PLANT SCIENCE ( 影响因子:5.754; 五年影响因子:6.612 )
ISSN: 1664-462X
年卷期: 2021 年 12 卷
页码:
收录情况: SCI
摘要: Peanut is an important legume crop worldwide. To uncover the genetic basis of yield features and assist breeding in the future, we conducted genome-wide association studies (GWAS) for six yield-related traits of the Chinese peanut mini-core collection. The seed (pod) size and weight of the population were investigated under four different environments, and these traits showed highly positive correlations in pairwise combinations. We sequenced the Chinese peanut mini-core collection using genotyping-by-sequencing approach and identified 105,814 high-quality single-nucleotide polymorphisms (SNPs). The population structure analysis showed essentially subspecies patterns in groups and obvious geographical distribution patterns in subgroups. A total of 79 significantly associated loci (P < 4.73 x 10(-7)) were detected for the six yield-related traits through GWAS. Of these, 31 associations were consistently detected in multiple environments, and 15 loci were commonly detected to be associated with multiple traits. Two major loci located on chromosomal pseudomolecules A06 and A02 showed pleiotropic effects on yield-related traits, explaining similar to 20% phenotypic variations across environments. The two genomic regions were found 46 putative candidate genes based on gene annotation and expression profile. The diagnostic marker for the yield-related traits from non-synonymous SNP (Aradu-A06-107901527) was successfully validated, achieving a high correlation between nucleotide polymorphism and phenotypic variation. This study provided insights into the genetic basis of yield-related traits in peanut and verified one diagnostic marker to facilitate marker-assisted selection for developing high-yield peanut varieties.
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