Format

Send to

Choose Destination
Bioinformatics. 2015 Jun 15;31(12):i35-43. doi: 10.1093/bioinformatics/btv231.

Reconstructing 16S rRNA genes in metagenomic data.

Author information

1
Computer Science and Engineering, Michigan State Univerisity, 428 South Shaw Rd East Lansing, MI 48824, USA and Center for Microbial Ecology, Michigan State University, East Lansing, MI 48824, USA.

Abstract

Metagenomic data, which contains sequenced DNA reads of uncultured microbial species from environmental samples, provide a unique opportunity to thoroughly analyze microbial species that have never been identified before. Reconstructing 16S ribosomal RNA, a phylogenetic marker gene, is usually required to analyze the composition of the metagenomic data. However, massive volume of dataset, high sequence similarity between related species, skewed microbial abundance and lack of reference genes make 16S rRNA reconstruction difficult. Generic de novo assembly tools are not optimized for assembling 16S rRNA genes. In this work, we introduce a targeted rRNA assembly tool, REAGO (REconstruct 16S ribosomal RNA Genes from metagenOmic data). It addresses the above challenges by combining secondary structure-aware homology search, zproperties of rRNA genes and de novo assembly. Our experimental results show that our tool can correctly recover more rRNA genes than several popular generic metagenomic assembly tools and specially designed rRNA construction tools.

AVAILABILITY AND IMPLEMENTATION:

The source code of REAGO is freely available at https://github.com/chengyuan/reago.

PMID:
26072503
PMCID:
PMC4765874
DOI:
10.1093/bioinformatics/btv231
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center