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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,...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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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 |
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author | Li, Baoqi Chen, Lin Sun, Weinan Wu, Di Wang, Maojun Yu, Yu Chen, Guoxing Yang, Wanneng Lin, Zhongxu Zhang, Xianlong Duan, Lingfeng Yang, Xiyan |
author_facet | Li, Baoqi Chen, Lin Sun, Weinan Wu, Di Wang, Maojun Yu, Yu Chen, Guoxing Yang, Wanneng Lin, Zhongxu Zhang, Xianlong Duan, Lingfeng Yang, Xiyan |
author_sort | Li, Baoqi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7680548 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76805482020-11-27 Phenomics‐based GWAS analysis reveals the genetic architecture for drought resistance in cotton Li, Baoqi Chen, Lin Sun, Weinan Wu, Di Wang, Maojun Yu, Yu Chen, Guoxing Yang, Wanneng Lin, Zhongxu Zhang, Xianlong Duan, Lingfeng Yang, Xiyan Plant Biotechnol J Research Articles 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. John Wiley and Sons Inc. 2020-07-08 2020-12 /pmc/articles/PMC7680548/ /pubmed/32558152 http://dx.doi.org/10.1111/pbi.13431 Text en © 2020 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Li, Baoqi Chen, Lin Sun, Weinan Wu, Di Wang, Maojun Yu, Yu Chen, Guoxing Yang, Wanneng Lin, Zhongxu Zhang, Xianlong Duan, Lingfeng Yang, Xiyan Phenomics‐based GWAS analysis reveals the genetic architecture for drought resistance in cotton |
title | Phenomics‐based GWAS analysis reveals the genetic architecture for drought resistance in cotton |
title_full | Phenomics‐based GWAS analysis reveals the genetic architecture for drought resistance in cotton |
title_fullStr | Phenomics‐based GWAS analysis reveals the genetic architecture for drought resistance in cotton |
title_full_unstemmed | Phenomics‐based GWAS analysis reveals the genetic architecture for drought resistance in cotton |
title_short | Phenomics‐based GWAS analysis reveals the genetic architecture for drought resistance in cotton |
title_sort | phenomics‐based gwas analysis reveals the genetic architecture for drought resistance in cotton |
topic | Research Articles |
url | 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 |
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