Cargando…

Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice

BACKGROUND: When plants are subjected to cold stress, they undergo a series of molecular and physiological changes to protect themselves from injury. Indica cultivars can usually withstand only mild cold stress in a relatively short period. Hormone-mediated defence response plays an important role i...

Descripción completa

Detalles Bibliográficos
Autores principales: Zeng, Zhichi, Zhang, Sichen, Li, Wenyan, Chen, Baoshan, Li, Wenlan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8974213/
https://www.ncbi.nlm.nih.gov/pubmed/35365095
http://dx.doi.org/10.1186/s12864-022-08438-3
_version_ 1784680217122439168
author Zeng, Zhichi
Zhang, Sichen
Li, Wenyan
Chen, Baoshan
Li, Wenlan
author_facet Zeng, Zhichi
Zhang, Sichen
Li, Wenyan
Chen, Baoshan
Li, Wenlan
author_sort Zeng, Zhichi
collection PubMed
description BACKGROUND: When plants are subjected to cold stress, they undergo a series of molecular and physiological changes to protect themselves from injury. Indica cultivars can usually withstand only mild cold stress in a relatively short period. Hormone-mediated defence response plays an important role in cold stress. Weighted gene co-expression network analysis (WGCNA) is a very useful tool for studying the correlation between genes, identifying modules with high phenotype correlation, and identifying Hub genes in different modules. Many studies have elucidated the molecular mechanisms of cold tolerance in different plants, but little information about the recovery process after cold stress is available. RESULTS: To understand the molecular mechanism of cold tolerance in rice, we performed comprehensive transcriptome analyses during cold treatment and recovery stage in two cultivars of near-isogenic lines (9311 and DC907). Twelve transcriptomes in two rice cultivars were determined. A total of 2509 new genes were predicted by fragment splicing and assembly, and 7506 differentially expressed genes were identified by pairwise comparison. A total of 26 modules were obtained by expression-network analysis, 12 of which were highly correlated with cold stress or recovery treatment. We further identified candidate Hub genes associated with specific modules and analysed their regulatory relationships based on coexpression data. Results showed that various plant-hormone regulatory genes acted together to protect plants from physiological damage under short-term low-temperature stress. We speculated that this may be common in rice. Under long-term cold stress, rice improved the tolerance to low-temperature stress by promoting autophagy, sugar synthesis, and metabolism. CONCLUSION: Through WGCNA analysis at the transcriptome level, we provided a potential regulatory mechanism for the cold stress and recovery of rice cultivars and identified candidate central genes. Our findings provided an important reference for the future cultivation of rice strains with good tolerance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08438-3.
format Online
Article
Text
id pubmed-8974213
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-89742132022-04-02 Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice Zeng, Zhichi Zhang, Sichen Li, Wenyan Chen, Baoshan Li, Wenlan BMC Genomics Research BACKGROUND: When plants are subjected to cold stress, they undergo a series of molecular and physiological changes to protect themselves from injury. Indica cultivars can usually withstand only mild cold stress in a relatively short period. Hormone-mediated defence response plays an important role in cold stress. Weighted gene co-expression network analysis (WGCNA) is a very useful tool for studying the correlation between genes, identifying modules with high phenotype correlation, and identifying Hub genes in different modules. Many studies have elucidated the molecular mechanisms of cold tolerance in different plants, but little information about the recovery process after cold stress is available. RESULTS: To understand the molecular mechanism of cold tolerance in rice, we performed comprehensive transcriptome analyses during cold treatment and recovery stage in two cultivars of near-isogenic lines (9311 and DC907). Twelve transcriptomes in two rice cultivars were determined. A total of 2509 new genes were predicted by fragment splicing and assembly, and 7506 differentially expressed genes were identified by pairwise comparison. A total of 26 modules were obtained by expression-network analysis, 12 of which were highly correlated with cold stress or recovery treatment. We further identified candidate Hub genes associated with specific modules and analysed their regulatory relationships based on coexpression data. Results showed that various plant-hormone regulatory genes acted together to protect plants from physiological damage under short-term low-temperature stress. We speculated that this may be common in rice. Under long-term cold stress, rice improved the tolerance to low-temperature stress by promoting autophagy, sugar synthesis, and metabolism. CONCLUSION: Through WGCNA analysis at the transcriptome level, we provided a potential regulatory mechanism for the cold stress and recovery of rice cultivars and identified candidate central genes. Our findings provided an important reference for the future cultivation of rice strains with good tolerance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08438-3. BioMed Central 2022-04-01 /pmc/articles/PMC8974213/ /pubmed/35365095 http://dx.doi.org/10.1186/s12864-022-08438-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zeng, Zhichi
Zhang, Sichen
Li, Wenyan
Chen, Baoshan
Li, Wenlan
Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice
title Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice
title_full Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice
title_fullStr Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice
title_full_unstemmed Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice
title_short Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice
title_sort gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8974213/
https://www.ncbi.nlm.nih.gov/pubmed/35365095
http://dx.doi.org/10.1186/s12864-022-08438-3
work_keys_str_mv AT zengzhichi genecoexpressionnetworkanalysisidentifiesspecificmodulesandhubgenesrelatedtocoldstressinrice
AT zhangsichen genecoexpressionnetworkanalysisidentifiesspecificmodulesandhubgenesrelatedtocoldstressinrice
AT liwenyan genecoexpressionnetworkanalysisidentifiesspecificmodulesandhubgenesrelatedtocoldstressinrice
AT chenbaoshan genecoexpressionnetworkanalysisidentifiesspecificmodulesandhubgenesrelatedtocoldstressinrice
AT liwenlan genecoexpressionnetworkanalysisidentifiesspecificmodulesandhubgenesrelatedtocoldstressinrice