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PeerJ. 2015 Jun 16;3:e1008. doi: 10.7717/peerj.1008. eCollection 2015.

Niche distribution and influence of environmental parameters in marine microbial communities: a systematic review.

Author information

1
Universidade Federal do Rio de Janeiro (UFRJ)/Instituto de Biologia (IB) , Rio de Janeiro , Brazil ; Radboud University Medical Centre, Radboud Institute for Molecular Life Sciences, Centre for Molecular and Biomolecular Informatics (CMBI) , Nijmegen , The Netherlands.
2
Universidade Federal do Rio de Janeiro (UFRJ)/Instituto de Biologia (IB) , Rio de Janeiro , Brazil.
3
Universidade Federal do Rio de Janeiro (UFRJ)/Instituto de Biologia (IB) , Rio de Janeiro , Brazil ; Radboud University Medical Centre, Radboud Institute for Molecular Life Sciences, Centre for Molecular and Biomolecular Informatics (CMBI) , Nijmegen , The Netherlands ; University of Utrecht (UU), Theoretical Biology and Bioinformatics , Utrecht , The Netherlands.
4
Universidade Federal do Rio de Janeiro (UFRJ)/Instituto de Biologia (IB) , Rio de Janeiro , Brazil ; Universidade Federal do Rio de Janeiro (UFRJ)/COPPE, SAGE , Rio de Janeiro , Brazil.

Abstract

Associations between microorganisms occur extensively throughout Earth's oceans. Understanding how microbial communities are assembled and how the presence or absence of species is related to that of others are central goals of microbial ecology. Here, we investigate co-occurrence associations between marine prokaryotes by combining 180 new and publicly available metagenomic datasets from different oceans in a large-scale meta-analysis. A co-occurrence network was created by calculating correlation scores between the abundances of microorganisms in metagenomes. A total of 1,906 correlations amongst 297 organisms were detected, segregating them into 11 major groups that occupy distinct ecological niches. Additionally, by analyzing the oceanographic parameters measured for a selected number of sampling sites, we characterized the influence of environmental variables over each of these 11 groups. Clustering organisms into groups of taxa that have similar ecology, allowed the detection of several significant correlations that could not be observed for the taxa individually.

KEYWORDS:

Community ecology; Global ocean; Metagenomics; Microbial ecology; Species interactions

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