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Genetic correlation network prediction of forest soil microbial functional organization

Soil ecological functions are largely determined by the activities of soil microorganisms, which, in turn, are regulated by relevant interactions between genes and their corresponding pathways. Therefore, the genetic network can theoretically elucidate the functional organization that supports compl...

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Autores principales: Ma, Bin, Zhao, Kankan, Lv, Xiaofei, Su, Weiqin, Dai, Zhongmin, Gilbert, Jack A., Brookes, Philip C., Faust, Karoline, Xu, Jianming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6155114/
https://www.ncbi.nlm.nih.gov/pubmed/30046166
http://dx.doi.org/10.1038/s41396-018-0232-8
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author Ma, Bin
Zhao, Kankan
Lv, Xiaofei
Su, Weiqin
Dai, Zhongmin
Gilbert, Jack A.
Brookes, Philip C.
Faust, Karoline
Xu, Jianming
author_facet Ma, Bin
Zhao, Kankan
Lv, Xiaofei
Su, Weiqin
Dai, Zhongmin
Gilbert, Jack A.
Brookes, Philip C.
Faust, Karoline
Xu, Jianming
author_sort Ma, Bin
collection PubMed
description Soil ecological functions are largely determined by the activities of soil microorganisms, which, in turn, are regulated by relevant interactions between genes and their corresponding pathways. Therefore, the genetic network can theoretically elucidate the functional organization that supports complex microbial community functions, although this has not been previously attempted. We generated a genetic correlation network based on 5421 genes derived from metagenomes of forest soils, identifying 7191 positive and 123 negative correlation relationships. This network consisted of 27 clusters enriched with sets of genes within specific functions, represented with corresponding cluster hubs. The clusters revealed a hierarchical architecture, reflecting the functional organization in the soil metagenomes. Positive correlations mapped functional associations, whereas negative correlations often mapped regulatory processes. The potential functions of uncharacterized genes were predicted based on the functions of located clusters. The global genetic correlation network highlights the functional organization in soil metagenomes and provides a resource for predicting gene functions. We anticipate that the genetic correlation network may be exploited to comprehensively decipher soil microbial community functions.
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spelling pubmed-61551142018-10-01 Genetic correlation network prediction of forest soil microbial functional organization Ma, Bin Zhao, Kankan Lv, Xiaofei Su, Weiqin Dai, Zhongmin Gilbert, Jack A. Brookes, Philip C. Faust, Karoline Xu, Jianming ISME J Article Soil ecological functions are largely determined by the activities of soil microorganisms, which, in turn, are regulated by relevant interactions between genes and their corresponding pathways. Therefore, the genetic network can theoretically elucidate the functional organization that supports complex microbial community functions, although this has not been previously attempted. We generated a genetic correlation network based on 5421 genes derived from metagenomes of forest soils, identifying 7191 positive and 123 negative correlation relationships. This network consisted of 27 clusters enriched with sets of genes within specific functions, represented with corresponding cluster hubs. The clusters revealed a hierarchical architecture, reflecting the functional organization in the soil metagenomes. Positive correlations mapped functional associations, whereas negative correlations often mapped regulatory processes. The potential functions of uncharacterized genes were predicted based on the functions of located clusters. The global genetic correlation network highlights the functional organization in soil metagenomes and provides a resource for predicting gene functions. We anticipate that the genetic correlation network may be exploited to comprehensively decipher soil microbial community functions. Nature Publishing Group UK 2018-07-25 2018-10 /pmc/articles/PMC6155114/ /pubmed/30046166 http://dx.doi.org/10.1038/s41396-018-0232-8 Text en © International Society for Microbial Ecology 2018 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Ma, Bin
Zhao, Kankan
Lv, Xiaofei
Su, Weiqin
Dai, Zhongmin
Gilbert, Jack A.
Brookes, Philip C.
Faust, Karoline
Xu, Jianming
Genetic correlation network prediction of forest soil microbial functional organization
title Genetic correlation network prediction of forest soil microbial functional organization
title_full Genetic correlation network prediction of forest soil microbial functional organization
title_fullStr Genetic correlation network prediction of forest soil microbial functional organization
title_full_unstemmed Genetic correlation network prediction of forest soil microbial functional organization
title_short Genetic correlation network prediction of forest soil microbial functional organization
title_sort genetic correlation network prediction of forest soil microbial functional organization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6155114/
https://www.ncbi.nlm.nih.gov/pubmed/30046166
http://dx.doi.org/10.1038/s41396-018-0232-8
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