High-Resolution Genome-wide Association Study Identifies Genomic Regions and Candidate Genes for Important Agronomic Traits in Wheat

• 作者: Amy Bernardo Anfei Li Chunxia Liu Danfeng Wang Fang He Guihua Bai Honggang Wang Hongming Jiang Hongze Jia Huirui Zhang Lei Dong Liming Wang Lingrang Kong Linzhi Li Meng Zhao Paul St.Amand Shubing Liu Wenhui Li Xitong Shen Xiufang Yuan Yu Su Yue Lu Yunlong Liang Yunlong Pang Yuye Wu
• 来源期刊: 分子植物（英文版）
• 年，卷（期）: 2020,（9）
• 所属期刊栏目: Research Articles
• 页码范围: 1311-1327
• 页数: 17页
• 语种: 英文

摘要

Wheat (Triticum aestivum) is a major staple food crop worldwide.Genetic dissection of important agronomic traits is essential for continuous improvement of wheat yield to meet the demand of the world's growing population.We conducted a large-scale genome-wide association study (GWAS) using a panel of 768 wheat cultivars that were genotyped with 327 609 single-nucleotide polymorphisms generated by genotyping-by-sequencing and detected 395 quantitative trait loci (QTLs) for 12 traits under 7 environments.Among them,273 QTLs were delimited to ＜ 1.0-Mb intervals and 7 of them are either known genes (Rht-D,Vrn-B1,and Vm-D1) that have been cloned or known QTLs (TaGA2ox8,APO1,TaSus1-7B,and Rht12) that were previously mapped.Eight putative candidate genes were identified for three QTLs that enhance spike seed setting and grain size using gene expression data and were validated in three biparental populations.Protein sequence analysis identified 33 putative wheat orthologs that have high identity with dce genes in QTLs affecting similar traits.Large r2 values for additive effects observed among the QTLs for most traits indicated that the phenotypes of these identified QTLs were highly predictable.Results from this study demonstrated that significantly increasing GWAS population size and marker density greatly improves detection and identification of candidate genes underlying a QTL,solidifying the foundation for large-scale QTL fine mapping,candidate gene validation,and developing functional markers for genomics-based breeding in wheat.