Low sequencing efforts bias analyses of shared taxa in microbial communities
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu hodnotící studie, časopisecké články, práce podpořená grantem
- MeSH
- Bacteria klasifikace genetika izolace a purifikace MeSH
- biodiverzita MeSH
- DNA bakterií genetika MeSH
- fylogeneze MeSH
- mikrobiologie životního prostředí MeSH
- RNA ribozomální 16S genetika MeSH
- vysoce účinné nukleotidové sekvenování metody MeSH
- Publikační typ
- časopisecké články MeSH
- hodnotící studie MeSH
- práce podpořená grantem MeSH
- Názvy látek
- DNA bakterií MeSH
- RNA ribozomální 16S MeSH
The potential for comparing microbial community population structures has been greatly enhanced by developments in next generation sequencing methods that can generate hundreds of thousands to millions of reads in a single run. Conversely, many microbial community comparisons have been published with no more than 1,000 sequences per sample. These studies have presented data on levels of shared operational taxonomic units (OTUs) between communities. Due to lack of coverage, that approach might compromise the conclusions about microbial diversity and the degree of difference between environments. In this study, we present data from recent studies that highlight this problem. Also, we analyzed datasets of 16 rRNA sequences with small and high sequence coverage from different environments to demonstrate that the level of sequencing effort used for analyzing microbial communities biases the results. We randomly sampled pyrosequencing-generated 16S rRNA gene libraries with increasing sequence effort. Sequences were used to calculate Good's coverage, the percentage of shared OTUs, and phylogenetic distance measures. Our data showed that simple counts of presence/absence of taxonomic unities do not reflect the real similarity in membership and structure of the bacterial communities and that community comparisons based on phylogenetic tests provide a way to test statistically significant differences between two or more environments without need an exhaustive sampling effort.
Zobrazit více v PubMed
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