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Reconstructing 16S rRNA genes in metagenomic data
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 requi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4765874/ https://www.ncbi.nlm.nih.gov/pubmed/26072503 http://dx.doi.org/10.1093/bioinformatics/btv231 |
Sumario: | 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. Contact: yannisun@msu.edu |
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