Oligotyping: Differentiating between closely related microbial taxa using 16S rRNA gene data

By A. Eren, L. Maignien, W. Sul, L. Murphy, Sharon L. Grim, Hilary G. Morrison, Mitchell L Sogin. Methods in Ecology and Evolution, 2013

612 citations recorded by the source corpus.

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.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b8b3cd213112bc2b5108947a895520187703332f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Molecular Biology

Citations in the corpus

Exact sequence variants should replace operational taxonomic units in marker-gene data analysis (2017, methodology): “…have been developed that resolve sequence variants (SVs) from Illumina-scale amplicon data without imposing the arbitrary dissimilarity thresholds that define molecular OTUs (Eren et al, 2013; Tikhonov et al, 2015; Eren et al, 2015; Callahan et al, 2016a; Callahan et al, 2016b; Edgar, 2016).”
Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics (2016, background): “Importantly, higher resolution analytical tools have been published that overcome some of the limitations associated with clustering algorithms (Eren et al., 2013, 2014; Tikhonov et al., 2015).”
DNA Sequencing as a Tool to Monitor Marine Ecological Status (2017, background): “Several bioinformatic tools are available for microbial sequences that could aid this goal (Eren et al., 2013; Callahan et al., 2016; Amir et al., 2017).”
Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences (2014, methodology): “If splitting and lumping of OTUs is of concern on your dataset, you may want to experiment with the “slow” parameter settings, which are still accessible in QIIME and we also recommend exploring the use of Oligotyping (Eren et al., 2013).”
metaxa2: improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data (2015, background): “Such errors can have an impact on both estimates of diversity and species delimitation, as sequencing errors can be hard to distinguish from actual mutations or variants within the population (Eren et al. 2013).”
Minimum entropy decomposition: Unsupervised oligotyping for sensitive partitioning of high-throughput marker gene sequences (2014, methodology): “Such OTUs aggregate distinct organisms and conceal ecologically important findings (Eren et al. , 2013a).”