期刊
MICROBIOME
卷 3, 期 -, 页码 -出版社
BIOMED CENTRAL LTD
DOI: 10.1186/s40168-015-0081-x
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资金
- National Natural Science Foundation of China [NSFC 31270152, 31322003]
- COMRA project [DY125-15-R-01]
- Program for New Century Excellent Talents in University [NCET-11-0921]
- Guangdong Natural Science Foundation [S2011010004136]
- Educational Commission of Guangdong Province, China [2012KJCX0031]
- United States National Science Foundation [NSF/BDI 0960626]
- National Institutes of Health
- Howard Hughes Medical Institute
Background: The operational taxonomic unit (OTU) is widely used in microbial ecology. Reproducibility in microbial ecology research depends on the reliability of OTU-based 16S ribosomal subunit RNA (rRNA) analyses. Results: Here, we report that many hierarchical and greedy clustering methods produce unstable OTUs, with membership that depends on the number of sequences clustered. If OTUs are regenerated with additional sequences or samples, sequences originally assigned to a given OTU can be split into different OTUs. Alternatively, sequences assigned to different OTUs can be merged into a single OTU. This OTU instability affects alpha-diversity analyses such as rarefaction curves, beta-diversity analyses such as distance-based ordination (for example, Principal Coordinate Analysis (PCoA)), and the identification of differentially represented OTUs. Our results show that the proportion of unstable OTUs varies for different clustering methods. We found that the closed-reference method is the only one that produces completely stable OTUs, with the caveat that sequences that do not match a pre-existing reference sequence collection are discarded. Conclusions: As a compromise to the factors listed above, we propose using an open-reference method to enhance OTU stability. This type of method clusters sequences against a database and includes unmatched sequences by clustering them via a relatively stable de novo clustering method. OTU stability is an important consideration when analyzing microbial diversity and is a feature that should be taken into account during the development of novel OTU clustering methods.
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