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Ecological consistency of SSU rRNA-based operational taxonomic units at a global scale

Schmidt, Thomas S B; Matias Rodrigues, João F; von Mering, Christian (2014). Ecological consistency of SSU rRNA-based operational taxonomic units at a global scale. PLoS Computational Biology, 10(4):e1003594.

Abstract

Operational Taxonomic Units (OTUs), usually defined as clusters of similar 16S/18S rRNA sequences, are the most widely used basic diversity units in large-scale characterizations of microbial communities. However, it remains unclear how well the various proposed OTU clustering algorithms approximate 'true' microbial taxa. Here, we explore the ecological consistency of OTUs--based on the assumption that, like true microbial taxa, they should show measurable habitat preferences (niche conservatism). In a global and comprehensive survey of available microbial sequence data, we systematically parse sequence annotations to obtain broad ecological descriptions of sampling sites. Based on these, we observe that sequence-based microbial OTUs generally show high levels of ecological consistency. However, different OTU clustering methods result in marked differences in the strength of this signal. Assuming that ecological consistency can serve as an objective external benchmark for cluster quality, we conclude that hierarchical complete linkage clustering, which provided the most ecologically consistent partitions, should be the default choice for OTU clustering. To our knowledge, this is the first approach to assess cluster quality using an external, biologically meaningful parameter as a benchmark, on a global scale.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Molecular Life Sciences
08 Research Priority Programs > Systems Biology / Functional Genomics
08 Research Priority Programs > Evolution in Action: From Genomes to Ecosystems
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Life Sciences > Ecology, Evolution, Behavior and Systematics
Physical Sciences > Modeling and Simulation
Physical Sciences > Ecology
Life Sciences > Molecular Biology
Life Sciences > Genetics
Life Sciences > Cellular and Molecular Neuroscience
Physical Sciences > Computational Theory and Mathematics
Language:English
Date:2014
Deposited On:26 Jun 2014 09:55
Last Modified:11 Sep 2024 01:37
Publisher:Public Library of Science (PLoS)
ISSN:1553-734X
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1371/journal.pcbi.1003594
PubMed ID:24763141
Project Information:
  • Funder: FP7
  • Grant ID: 242870
  • Project Title: UMICIS - Uncultivated Microbes In Situ - a Computational Biology Approach to Determine Molecular Capabilities and Ecological Roles
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  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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