Abstract
A variety of methods are available to collapse 16S rRNA gene sequencing reads to the operational taxonomic units (OTUs) used in microbiome analyses. A number of studies have aimed to compare the quality of the resulting OTUs. However, in the absence of a standard method to define and enumerate the different taxa within a microbial community, existing comparisons have been unable to compare the ability of clustering methods to generate units that accurately represent functional taxonomic segregation. We have previously demonstrated heritability of the microbiome and we propose this as a measure of each methods’ ability to generate OTUs representing biologically relevant units. Our approach assumes that OTUs that best represent the functional units interacting with the hosts’ properties will produce the highest heritability estimates. Using 1,750 unselected individuals from the TwinsUK cohort, we compared 11 approaches to OTU clustering in heritability analyses. We find that de novo clustering methods produce more heritable OTUs than reference based approaches, with VSEARCH and SUMACLUST performing well. We also show that differences resulting from each clustering method are minimal once reads are collapsed by taxonomic assignment, although sample diversity estimates are clearly influenced by OTU clustering approach. These results should help the selection of sequence clustering methods in future microbiome studies, particularly for studies of human host-microbiome interactions.
Highlights
The field of microbiome research has seen rapid expansion this last decade (Jones, 2013)
Given that bacteria within the microbiome contain a range of functional properties, determined by their own genetics, we assume that the heritability of an operational taxonomic units (OTUs) is driven by a specific bacteria-host interaction
We would expect the OTU clustering approach that best groups reads sourced from bacterial units with similar functional properties to produce OTUs with the highest heritability estimates
Summary
The field of microbiome research has seen rapid expansion this last decade (Jones, 2013). One of the techniques most frequently used to profile microbial communities is 16S rRNA gene sequencing, where PCR amplification of variable marker regions is used to determine a sample’s microbial composition (Pace, 1997). How to cite this article Jackson et al (2016), A heritability-based comparison of methods used to cluster 16S rRNA gene sequences into operational taxonomic units. Reads within a 16S rRNA gene dataset are typically collapsed into operational taxonomic units (OTUs). This is carried out based on sequence similarity between reads. Convention is typically to group reads that share at least 97% identity, which is considered ‘‘species’’ level. Collapsing can be carried out to any threshold and there is no clear definition of what constitutes a bacterial species
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