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      Can You Sequence Ecology? Metagenomics of Adaptive Diversification

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      PLoS Biology
      Public Library of Science

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          Abstract

          Identifying evolutionary and ecological phenomena directly from sequencing of microbial communities is surprisingly challenging, even for one as simple as a single species adapting and diversifying in the laboratory.

          Abstract

          Few areas of science have benefited more from the expansion in sequencing capability than the study of microbial communities. Can sequence data, besides providing hypotheses of the functions the members possess, detect the evolutionary and ecological processes that are occurring? For example, can we determine if a species is adapting to one niche, or if it is diversifying into multiple specialists that inhabit distinct niches? Fortunately, adaptation of populations in the laboratory can serve as a model to test our ability to make such inferences about evolution and ecology from sequencing. Even adaptation to a single niche can give rise to complex temporal dynamics due to the transient presence of multiple competing lineages. If there are multiple niches, this complexity is augmented by segmentation of the population into multiple specialists that can each continue to evolve within their own niche. For a known example of parallel diversification that occurred in the laboratory, sequencing data gave surprisingly few obvious, unambiguous signs of the ecological complexity present. Whereas experimental systems are open to direct experimentation to test hypotheses of selection or ecological interaction, the difficulty in “seeing ecology” from sequencing for even such a simple system suggests translation to communities like the human microbiome will be quite challenging. This will require both improved empirical methods to enhance the depth and time resolution for the relevant polymorphisms and novel statistical approaches to rigorously examine time-series data for signs of various evolutionary and ecological phenomena within and between species.

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          Author and article information

          Journal
          PLoS Biol
          PLoS Biol
          plos
          plosbiol
          PLoS Biology
          Public Library of Science (San Francisco, USA )
          1544-9173
          1545-7885
          February 2013
          February 2013
          19 February 2013
          : 11
          : 2
          : e1001487
          Affiliations
          [1 ]Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
          [2 ]Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America
          Author notes

          The author has declared that no competing interests exist.

          Primers provide a concise introduction into an important aspect of biology highlighted by a current PLOS Biology research article.

          Article
          PBIOLOGY-D-12-04986
          10.1371/journal.pbio.1001487
          3576389
          23431268
          30eb8e72-3e23-4a20-bbbb-afa475ae80b4
          Copyright @ 2013

          Marx. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

          History
          Page count
          Pages: 4
          Funding
          The author received no specific funding for this work.
          Categories
          Primer
          Biology
          Computational Biology
          Genomics
          Genome Evolution
          Metagenomics
          Population Genetics
          Natural Selection
          Ecosystem Modeling
          Evolutionary Modeling
          Sequence Analysis
          Ecology
          Microbial Ecology
          Microbiology
          Bacteriology
          Bacterial Evolution
          Microbial Ecology
          Microbial Evolution
          Population Biology
          Population Dynamics
          Population Ecology
          Population Genetics

          Life sciences
          Life sciences

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