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ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium

Plant genera with both diploid and polyploid species are a common evolutionary occurrence. Polyploids, especially allopolyploids such as cotton and wheat, are a great model system for heterosis research. Here, we have integrated genome sequences and transcriptome data of Gossypium species to constru...

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Detalles Bibliográficos
Autores principales: You, Qi, Xu, Wenying, Zhang, Kang, Zhang, Liwei, Yi, Xin, Yao, Dongxia, Wang, Chunchao, Zhang, Xueyan, Zhao, Xinhua, Provart, Nicholas J., Li, Fuguang, Su, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210623/
https://www.ncbi.nlm.nih.gov/pubmed/28053168
http://dx.doi.org/10.1093/nar/gkw910
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author You, Qi
Xu, Wenying
Zhang, Kang
Zhang, Liwei
Yi, Xin
Yao, Dongxia
Wang, Chunchao
Zhang, Xueyan
Zhao, Xinhua
Provart, Nicholas J.
Li, Fuguang
Su, Zhen
author_facet You, Qi
Xu, Wenying
Zhang, Kang
Zhang, Liwei
Yi, Xin
Yao, Dongxia
Wang, Chunchao
Zhang, Xueyan
Zhao, Xinhua
Provart, Nicholas J.
Li, Fuguang
Su, Zhen
author_sort You, Qi
collection PubMed
description Plant genera with both diploid and polyploid species are a common evolutionary occurrence. Polyploids, especially allopolyploids such as cotton and wheat, are a great model system for heterosis research. Here, we have integrated genome sequences and transcriptome data of Gossypium species to construct co-expression networks and identified functional modules from different cotton species, including 1155 and 1884 modules in G. arboreum and G. hirsutum, respectively. We overlayed the gene expression results onto the co-expression network. We further provided network comparison analysis for orthologous genes across the diploid and allotetraploid Gossypium. We also constructed miRNA-target networks and predicted PPI networks for both cotton species. Furthermore, we integrated in-house ChIP-seq data of histone modification (H3K4me3) together with cis-element analysis and gene sets enrichment analysis tools for studying possible gene regulatory mechanism in Gossypium species. Finally, we have constructed an online ccNET database (http://structuralbiology.cau.edu.cn/gossypium) for comparative gene functional analyses at a multi-dimensional network and epigenomic level across diploid and polyploid Gossypium species. The ccNET database will be beneficial for community to yield novel insights into gene/module functions during cotton development and stress response, and might be useful for studying conservation and diversity in other polyploid plants, such as T. aestivum and Brassica napus.
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spelling pubmed-52106232017-01-05 ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium You, Qi Xu, Wenying Zhang, Kang Zhang, Liwei Yi, Xin Yao, Dongxia Wang, Chunchao Zhang, Xueyan Zhao, Xinhua Provart, Nicholas J. Li, Fuguang Su, Zhen Nucleic Acids Res Database Issue Plant genera with both diploid and polyploid species are a common evolutionary occurrence. Polyploids, especially allopolyploids such as cotton and wheat, are a great model system for heterosis research. Here, we have integrated genome sequences and transcriptome data of Gossypium species to construct co-expression networks and identified functional modules from different cotton species, including 1155 and 1884 modules in G. arboreum and G. hirsutum, respectively. We overlayed the gene expression results onto the co-expression network. We further provided network comparison analysis for orthologous genes across the diploid and allotetraploid Gossypium. We also constructed miRNA-target networks and predicted PPI networks for both cotton species. Furthermore, we integrated in-house ChIP-seq data of histone modification (H3K4me3) together with cis-element analysis and gene sets enrichment analysis tools for studying possible gene regulatory mechanism in Gossypium species. Finally, we have constructed an online ccNET database (http://structuralbiology.cau.edu.cn/gossypium) for comparative gene functional analyses at a multi-dimensional network and epigenomic level across diploid and polyploid Gossypium species. The ccNET database will be beneficial for community to yield novel insights into gene/module functions during cotton development and stress response, and might be useful for studying conservation and diversity in other polyploid plants, such as T. aestivum and Brassica napus. Oxford University Press 2017-01-04 2016-10-07 /pmc/articles/PMC5210623/ /pubmed/28053168 http://dx.doi.org/10.1093/nar/gkw910 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
You, Qi
Xu, Wenying
Zhang, Kang
Zhang, Liwei
Yi, Xin
Yao, Dongxia
Wang, Chunchao
Zhang, Xueyan
Zhao, Xinhua
Provart, Nicholas J.
Li, Fuguang
Su, Zhen
ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium
title ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium
title_full ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium
title_fullStr ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium
title_full_unstemmed ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium
title_short ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium
title_sort ccnet: database of co-expression networks with functional modules for diploid and polyploid gossypium
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210623/
https://www.ncbi.nlm.nih.gov/pubmed/28053168
http://dx.doi.org/10.1093/nar/gkw910
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