Oligotyping : differentiating between closely related microbial taxa using 16S rRNA gene data
Figure S2. Aerial map of seven sampling stations at Little Sippewissett Marsh, Massachusetts, USA. (8.521Mb)
Figure S3. LEfSe analysis results for five categories used to define the origin of samples collected from individuals live in the United States. (18.58Kb)
Eren, A. Murat
Sul, Woo Jun
Murphy, Leslie G.
Grim, Sharon L.
Morrison, Hilary G.
Sogin, Mitchell L.
MetadataShow full item record
Bacteria comprise the most diverse domain of life on Earth, where they occupy nearly every possible ecological niche and play key roles in biological and chemical processes. Studying the composition and ecology of bacterial ecosystems and understanding their function are of prime importance. High-throughput sequencing technologies enable nearly comprehensive descriptions of bacterial diversity through 16S ribosomal RNA gene amplicons. Analyses of these communities generally rely upon taxonomic assignments through reference data bases or clustering approaches using de facto sequence similarity thresholds to identify operational taxonomic units. However, these methods often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial data sets. In this paper, we describe oligotyping, a novel supervised computational method that allows researchers to investigate the diversity of closely related but distinct bacterial organisms in final operational taxonomic units identified in environmental data sets through 16S ribosomal RNA gene data by the canonical approaches. Our analysis of two data sets from two different environments demonstrates the capacity of oligotyping at discriminating distinct microbial populations of ecological importance. Oligotyping can resolve the distribution of closely related organisms across environments and unveil previously overlooked ecological patterns for microbial communities. The URL http://oligotyping.org offers an open-source software pipeline for oligotyping.
© The Authors. Methods in Ecology and Evolution © 2013 British Ecological Society.. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Methods in Ecology and Evolution 4 (2013): 1111–1119, doi:10.1111/2041-210X.12114.
The following license files are associated with this item:
Except where otherwise noted, this item's license is described as Attribution-NonCommercial 3.0 Unported
Showing items related by title, author, creator and subject.
Ducklow, Hugh W. (Inter-Research, 2008-09-18)Bacteria, archaea and other microbes have dominated most biogeochemical processes on Earth for >99% of the history of life, but within the past few decades anthropogenic activity has usurped their dominance. Human activity ...
Autonomous Microbial Sampler (AMS), a device for the uncontaminated collection of multiple microbial samples from submarine hydrothermal vents and other aquatic environments Taylor, Craig D.; Doherty, Kenneth W.; Molyneaux, Stephen J.; Morrison, Archie T.; Billings, John D.; Engstrom, Ivory B.; Pfitsch, Don W.; Honjo, Susumu (2006-01-11)An Autonomous Microbial Sampler (AMS) is described that will obtain uncontaminated and exogenous DNA-free microbial samples from most marine, fresh water and hydrothermal ecosystems. Sampling with the AMS may be conducted ...
Development of a "genome-proxy" microarray for profiling marine microbial communities, and its application to a time series in Monterey Bay, California Rich, Virginia Isabel (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2008-09)This thesis describes the development and application of a new tool for profiling marine microbial communities. Chapter 1 places the tool in the context of the range of methods used currently. Chapter 2 describes the ...