气候变化领域集成服务门户(CCPortal): Towards omics-based predictions of planktonic functional composition from environmental data

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DOI	10.1038/s41467-021-24547-1
	Towards omics-based predictions of planktonic functional composition from environmental data
	Faure E.; Ayata S.-D.; Bittner L.
发表日期	2021
ISSN	2041-1723
卷号	12 期号:1
英文摘要	Marine microbes play a crucial role in climate regulation, biogeochemical cycles, and trophic networks. Unprecedented amounts of data on planktonic communities were recently collected, sparking a need for innovative data-driven methodologies to quantify and predict their ecosystemic functions. We reanalyze 885 marine metagenome-assembled genomes through a network-based approach and detect 233,756 protein functional clusters, from which 15% are functionally unannotated. We investigate all clusters’ distributions across the global ocean through machine learning, identifying biogeographical provinces as the best predictors of protein functional clusters’ abundance. The abundances of 14,585 clusters are predictable from the environmental context, including 1347 functionally unannotated clusters. We analyze the biogeography of these 14,585 clusters, identifying the Mediterranean Sea as an outlier in terms of protein functional clusters composition. Applicable to any set of sequences, our approach constitutes a step towards quantitative predictions of functional composition from the environmental context. © 2021, The Author(s).
语种	英语
scopus关键词	functional group; genome; genomics; global ocean; plankton; prediction; article; biogeographic region; biogeography; machine learning; Mediterranean Sea; prediction; quantitative analysis; sea; archaeon; bacterium; classification; ecosystem; genetics; metagenome; microbiology; phylogeny; phylogeography; plankton; protein analysis; Mediterranean Sea; sea water; Archaea; Bacteria; Classification; Ecosystem; Machine Learning; Mediterranean Sea; Metagenome; Phylogeny; Phylogeography; Plankton; Protein Interaction Maps; Seawater
来源期刊	Nature Communications
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/251386
作者单位	Sorbonne Université, CNRS, Laboratoire d’Océanographie de Villefranche, LOV, Villefranche-sur-Mer, France; Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum National d’Histoire Naturelle, CNRS, Sorbonne Université, EPHE, Université des Antilles, Paris, France; Institut Universitaire de France, Paris, France
推荐引用方式 GB/T 7714	Faure E.,Ayata S.-D.,Bittner L.. Towards omics-based predictions of planktonic functional composition from environmental data[J],2021,12(1).
APA	Faure E.,Ayata S.-D.,&Bittner L..(2021).Towards omics-based predictions of planktonic functional composition from environmental data.Nature Communications,12(1).
MLA	Faure E.,et al."Towards omics-based predictions of planktonic functional composition from environmental data".Nature Communications 12.1(2021).