Article

Identification and Quantification of Abundant Species from Pyrosequences of 16S rRNA by Consensus Alignment.

School of Informatics and Computing, Bloomington, IN 47408, U.S.A.
Proceedings. IEEE International Conference on Bioinformatics and Biomedicine 02/2011; 2010:153-157. DOI: 10.1109/BIBM.2010.5706555
Source: PubMed

ABSTRACT 16S rRNA gene profiling has recently been boosted by the development of pyrosequencing methods. A common analysis is to group pyrosequences into Operational Taxonomic Units (OTUs), such that reads in an OTU are likely sampled from the same species. However, species diversity estimated from error-prone 16S rRNA pyrosequences may be inflated because the reads sampled from the same 16S rRNA gene may appear different, and current OTU inference approaches typically involve time-consuming pairwise/multiple distance calculation and clustering. I propose a novel approach AbundantOTU based on a Consensus Alignment (CA) algorithm, which infers consensus sequences, each representing an OTU, taking advantage of the sequence redundancy for abundant species. Pyrosequencing reads can then be recruited to the consensus sequences to give quantitative information for the corresponding species. As tested on 16S rRNA pyrosequence datasets from mock communities with known species, AbundantOTU rapidly reported identified sequences of the source 16S rRNAs and the abundances of the corresponding species. AbundantOTU was also applied to 16S rRNA pyrosequence datasets derived from real microbial communities and the results are in general agreement with previous studies.

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Available from: Yuzhen Ye, Aug 28, 2015
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    • "Sequence reads were aligned with our own custom multiple alignment tool known as the Illinois-Mayo Taxon Operations for RNA Dataset Organization (IM-TORNADO) that merges paired end reads into a single multiple alignment and obtains taxa calls [19]. IM-TORNADO then clusters sequences into operational taxonomic units (OTUs) using AbundantOTU+ [20]. Further processing for visualization was performed using QIIME [21]. "
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    PLoS ONE 06/2014; 9(6):e98514. DOI:10.1371/journal.pone.0098514 · 3.23 Impact Factor
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    • "Reads with at least 400 nucleotides (nt) were trimmed and checked for chimerism (Edgar et al., 2011). We obtained consensus OTU clusters and representative sequences using abundant OTU (Ye, 2010). Representative sequences and the OTU table were used for further analysis with the QIIME pipeline as detailed above (Caporaso et al., 2010). "
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    The ISME Journal 10/2013; DOI:10.1038/ismej.2013.167 · 9.27 Impact Factor
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    • "We performed AbundantOTU [29] analyses to identify consensus sequences for non-rare OTUs present in the Vaginal Human Microbiome Project dataset of mid-vaginal reads. The purpose of this analysis was to obtain V1-V3 16S rDNA reference sequences for novel taxa and unnamed bacterial species that are present in vaginal samples. "
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