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Phenomics-based GWAS analysis reveals the genetic architecture for drought resistance in cotton

文献类型： 外文期刊

作者： Li, Baoqi 1 ; Chen, Lin 1 ; Sun, Weinan 1 ; Wu, Di 2 ; Wang, Maojun 1 ; Yu, Yu 4 ; Chen, Guoxing 5 ; Yang, Wanneng 1 ; Lin, 1 ;

作者机构： 1.Huazhong Agr Univ, Natl Ctr Plant Gene Res Wuhan, Natl Key Lab Crop Genet Improvement, Wuhan, Hubei, Peoples R China

2.Huazhong Agr Univ, Hubei Key Lab Agr Bioinformat, Wuhan, Hubei, Peoples R China

3.Huazhong Agr Univ, Coll Engn, Wuhan, Hubei, Peoples R China

4.Xinjiang Acad Agr & Reclamat Sci, Cotton Inst, Shihezi, Xinjiang, Peoples R China

5.Huazhong Agr Univ, MOA Key Lab Crop Ecophysiol & Farming Syst Middle, Wuhan, Hubei, Peoples R China

关键词： cotton; drought resistance; GWAS; i-traits; novel DR-related genes; phenomics

期刊名称：PLANT BIOTECHNOLOGY JOURNAL （ 影响因子：9.803； 五年影响因子：9.555 ）

ISSN： 1467-7644

年卷期：

页码：

收录情况： SCI

摘要： Drought resistance (DR) is a complex trait that is regulated by a variety of genes. Without comprehensive profiling of DR-related traits, the knowledge of the genetic architecture for DR in cotton remains limited. Thus, there is a need to bridge the gap between genomics and phenomics. In this study, an automatic phenotyping platform (APP) was systematically applied to examine 119 image-based digital traits (i-traits) during drought stress at the seedling stage, across a natural population of 200 representative upland cotton accessions. Some novel i-traits, as well as some traditional i-traits, were used to evaluate the DR in cotton. The phenomics data allowed us to identify 390 genetic loci by genome-wide association study (GWAS) using 56 morphological and 63 texture i-traits. DR-related genes, includingGhRD2,GhNAC4,GhHAT22andGhDREB2, were identified as candidate genes by some digital traits. Further analysis of candidate genes showed thatGh_A04G0377andGh_A04G0378functioned as negative regulators for cotton drought response. Based on the combined digital phenotyping, GWAS analysis and transcriptome data, we conclude that the phenomics dataset provides an excellent resource to characterize key genetic loci with an unprecedented resolution which can inform future genome-based breeding for improved DR in cotton.

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