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Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms (file : V4dataset.fna)

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Version 2 2015-02-03, 12:57
Version 1 2015-01-23, 20:16
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posted on 2015-02-03, 12:57 authored by Dominik Forster, Lucie BittnerLucie Bittner, Slim Karkar, Micah Dunthorn, Sarah Romac, Stéphane Audic, Philippe Lopez, Thorsten Stoeck, Eric Bapteste

file : V4dataset.fna

Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms (file : readme_Forster_et_al_BMC)

http://dx.doi.org/10.6084/m9.figshare.1264013

 

Background: High-throughput sequencing technologies are lifting major limitations to molecular-based ecological studies of eukaryotic microbial diversity, but in silico analyses of the resulting millions of short amplicons remain a major bottleneck for these approaches. Here, we introduced the analytical and statistical framework of sequence similarity networks, increasingly used in evolutionary studies and graph theory, into the field of ecology to analyze novel pyrosequenced V4 SSU-rDNA sequence data sets in the context of previous studies, including SSU-rDNA Sanger sequence data from cultured ciliates and from previous environmental diversity inventories.
Results: Our broadly applicable protocol quantified progress in the description of genetic diversity of ciliates by environmental rRNA amplicons studies, detected a fundamental historical bias, the tendency to recover already known groups, in these surveys, and revealed substantial amounts of hidden microbial diversity. Moreover, network measures demonstrated that ciliates are not globally dispersed, but present strong local patterns at intermediate geographical scale, as observed for bacteria, plants, and animals.
Conclusions: Although currently available ‘universal’ primers used for local in-depth sequencing surveys provide little hope to exhaust the significantly higher ciliate (and most likely microbial) diversity than previously thought, sequence similarity networks, since they identify groups of divergence sequences sharing distinctive similarities, offer a promising way to guide the design of novel primers and to further explore such a vast and structured microbial diversity.

 

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