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Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat
AIM: To establish a gene co-expression network for identifying principal modules and hub genes that are associated with drought resistance mechanisms, analyzing their mechanisms, and exploring candidate genes. METHODS AND FINDINGS: 42 data sets including PRJNA380841 and PRJNA369686 were used to cons...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7458298/ https://www.ncbi.nlm.nih.gov/pubmed/32866164 http://dx.doi.org/10.1371/journal.pone.0236186 |
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author | Lv, Liangjie Zhang, Wenying Sun, Lijing Zhao, Aiju Zhang, Yingjun Wang, Limei Liu, Yuping Li, Ziqian Li, Hui Chen, Xiyong |
author_facet | Lv, Liangjie Zhang, Wenying Sun, Lijing Zhao, Aiju Zhang, Yingjun Wang, Limei Liu, Yuping Li, Ziqian Li, Hui Chen, Xiyong |
author_sort | Lv, Liangjie |
collection | PubMed |
description | AIM: To establish a gene co-expression network for identifying principal modules and hub genes that are associated with drought resistance mechanisms, analyzing their mechanisms, and exploring candidate genes. METHODS AND FINDINGS: 42 data sets including PRJNA380841 and PRJNA369686 were used to construct the co-expression network through weighted gene co-expression network analysis (WGCNA). A total of 1,896,897,901 (284.30 Gb) clean reads and 35,021 differentially expressed genes (DEGs) were obtained from 42 samples. Functional enrichment analysis indicated that photosynthesis, DNA replication, glycolysis/gluconeogenesis, starch and sucrose metabolism, arginine and proline metabolism, and cell cycle were significantly influenced by drought stress. Furthermore, the DEGs with similar expression patterns, detected by K-means clustering, were grouped into 29 clusters. Genes involved in the modules, such as dark turquoise, yellow, and brown, were found to be appreciably linked with drought resistance. Twelve central, greatly correlated genes in stage-specific modules were subsequently confirmed and validated at the transcription levels, including TraesCS7D01G417600.1 (PP2C), TraesCS5B01G565300.1 (ERF), TraesCS4A01G068200.1 (HSP), TraesCS2D01G033200.1 (HSP90), TraesCS6B01G425300.1 (RBD), TraesCS7A01G499200.1 (P450), TraesCS4A01G118400.1 (MYB), TraesCS2B01G415500.1 (STK), TraesCS1A01G129300.1 (MYB), TraesCS2D01G326900.1 (ALDH), TraesCS3D01G227400.1 (WRKY), and TraesCS3B01G144800.1 (GT). CONCLUSIONS: Analyzing the response of wheat to drought stress during different growth stages, we have detected three modules and 12 hub genes that are associated with drought resistance mechanisms, and five of those genes are newly identified for drought resistance. The references provided by these modules will promote the understanding of the drought-resistance mechanism. In addition, the candidate genes can be used as a basis of transgenic or molecular marker-assisted selection for improving the drought resistance and increasing the yields of wheat. |
format | Online Article Text |
id | pubmed-7458298 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74582982020-09-04 Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat Lv, Liangjie Zhang, Wenying Sun, Lijing Zhao, Aiju Zhang, Yingjun Wang, Limei Liu, Yuping Li, Ziqian Li, Hui Chen, Xiyong PLoS One Research Article AIM: To establish a gene co-expression network for identifying principal modules and hub genes that are associated with drought resistance mechanisms, analyzing their mechanisms, and exploring candidate genes. METHODS AND FINDINGS: 42 data sets including PRJNA380841 and PRJNA369686 were used to construct the co-expression network through weighted gene co-expression network analysis (WGCNA). A total of 1,896,897,901 (284.30 Gb) clean reads and 35,021 differentially expressed genes (DEGs) were obtained from 42 samples. Functional enrichment analysis indicated that photosynthesis, DNA replication, glycolysis/gluconeogenesis, starch and sucrose metabolism, arginine and proline metabolism, and cell cycle were significantly influenced by drought stress. Furthermore, the DEGs with similar expression patterns, detected by K-means clustering, were grouped into 29 clusters. Genes involved in the modules, such as dark turquoise, yellow, and brown, were found to be appreciably linked with drought resistance. Twelve central, greatly correlated genes in stage-specific modules were subsequently confirmed and validated at the transcription levels, including TraesCS7D01G417600.1 (PP2C), TraesCS5B01G565300.1 (ERF), TraesCS4A01G068200.1 (HSP), TraesCS2D01G033200.1 (HSP90), TraesCS6B01G425300.1 (RBD), TraesCS7A01G499200.1 (P450), TraesCS4A01G118400.1 (MYB), TraesCS2B01G415500.1 (STK), TraesCS1A01G129300.1 (MYB), TraesCS2D01G326900.1 (ALDH), TraesCS3D01G227400.1 (WRKY), and TraesCS3B01G144800.1 (GT). CONCLUSIONS: Analyzing the response of wheat to drought stress during different growth stages, we have detected three modules and 12 hub genes that are associated with drought resistance mechanisms, and five of those genes are newly identified for drought resistance. The references provided by these modules will promote the understanding of the drought-resistance mechanism. In addition, the candidate genes can be used as a basis of transgenic or molecular marker-assisted selection for improving the drought resistance and increasing the yields of wheat. Public Library of Science 2020-08-31 /pmc/articles/PMC7458298/ /pubmed/32866164 http://dx.doi.org/10.1371/journal.pone.0236186 Text en © 2020 Lv et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lv, Liangjie Zhang, Wenying Sun, Lijing Zhao, Aiju Zhang, Yingjun Wang, Limei Liu, Yuping Li, Ziqian Li, Hui Chen, Xiyong Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat |
title | Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat |
title_full | Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat |
title_fullStr | Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat |
title_full_unstemmed | Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat |
title_short | Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat |
title_sort | gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7458298/ https://www.ncbi.nlm.nih.gov/pubmed/32866164 http://dx.doi.org/10.1371/journal.pone.0236186 |
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