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

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,...

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Detalles Bibliográficos
Autores principales: Li, Baoqi, Chen, Lin, Sun, Weinan, Wu, Di, Wang, Maojun, Yu, Yu, Chen, Guoxing, Yang, Wanneng, Lin, Zhongxu, Zhang, Xianlong, Duan, Lingfeng, Yang, Xiyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680548/
https://www.ncbi.nlm.nih.gov/pubmed/32558152
http://dx.doi.org/10.1111/pbi.13431
Descripción
Sumario: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, including GhRD2, GhNAC4, GhHAT22 and GhDREB2, were identified as candidate genes by some digital traits. Further analysis of candidate genes showed that Gh_A04G0377 and Gh_A04G0378 functioned 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.