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Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum

Environmental stresses significantly affect plant growth, development, and productivity. Therefore, a deeper understanding of the underlying stress responses at the molecular level is needed. In this study, to identify critical genetic factors associated with environmental stress responses, the enti...

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Autores principales: Lee, Junesung, Yeom, Seon-In
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570317/
https://www.ncbi.nlm.nih.gov/pubmed/37828130
http://dx.doi.org/10.1038/s41597-023-02592-3
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author Lee, Junesung
Yeom, Seon-In
author_facet Lee, Junesung
Yeom, Seon-In
author_sort Lee, Junesung
collection PubMed
description Environmental stresses significantly affect plant growth, development, and productivity. Therefore, a deeper understanding of the underlying stress responses at the molecular level is needed. In this study, to identify critical genetic factors associated with environmental stress responses, the entire 737.3 Gb clean RNA-seq dataset across abiotic, biotic stress, and phytohormone conditions in Capsicum annuum was used to perform individual differentially expressed gene analysis and to construct gene co-expression networks for each stress condition. Subsequently, gene networks were reconstructed around transcription factors to identify critical factors involved in the stress responses, including the NLR gene family, previously implicated in resistance. The abiotic and biotic stress networks comprise 233 and 597 hubs respectively, with 10 and 89 NLRs. Each gene within the NLR groups in the network exhibited substantial expression to particular stresses. The integrated analysis strategy of the transcriptome network revealed potential key genes for complex environmental conditions. Together, this could provide important clues to uncover novel key factors using high-throughput transcriptome data in other species as well as plants.
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spelling pubmed-105703172023-10-14 Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum Lee, Junesung Yeom, Seon-In Sci Data Analysis Environmental stresses significantly affect plant growth, development, and productivity. Therefore, a deeper understanding of the underlying stress responses at the molecular level is needed. In this study, to identify critical genetic factors associated with environmental stress responses, the entire 737.3 Gb clean RNA-seq dataset across abiotic, biotic stress, and phytohormone conditions in Capsicum annuum was used to perform individual differentially expressed gene analysis and to construct gene co-expression networks for each stress condition. Subsequently, gene networks were reconstructed around transcription factors to identify critical factors involved in the stress responses, including the NLR gene family, previously implicated in resistance. The abiotic and biotic stress networks comprise 233 and 597 hubs respectively, with 10 and 89 NLRs. Each gene within the NLR groups in the network exhibited substantial expression to particular stresses. The integrated analysis strategy of the transcriptome network revealed potential key genes for complex environmental conditions. Together, this could provide important clues to uncover novel key factors using high-throughput transcriptome data in other species as well as plants. Nature Publishing Group UK 2023-10-12 /pmc/articles/PMC10570317/ /pubmed/37828130 http://dx.doi.org/10.1038/s41597-023-02592-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) .
spellingShingle Analysis
Lee, Junesung
Yeom, Seon-In
Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum
title Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum
title_full Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum
title_fullStr Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum
title_full_unstemmed Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum
title_short Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum
title_sort global co-expression network for key factor selection on environmental stress rna-seq dataset in capsicum annuum
topic Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10570317/
https://www.ncbi.nlm.nih.gov/pubmed/37828130
http://dx.doi.org/10.1038/s41597-023-02592-3
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