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Computational identification of functional RNA homologs in metagenomic data.

ABSTRACT: A key step toward understanding a metagenomics data set is the identification of functional sequence elements within it, such as protein coding genes and structural RNAs. Relative to protein coding genes, structural RNAs are more difficult to identify because of their reduced alphabet size, lack of open reading frames, and short length. Infernal is a software package that implements "covariance models" (CMs) for RNA homology search, which harness both sequence and structural conservation when searching for RNA homologs. Thanks to the added statistical signal inherent in the secondary structure conservation of many RNA families, Infernal is more powerful than sequence-only based methods such as BLAST and profile HMMs. Together with the Rfam database of CMs, Infernal is a useful tool for identifying RNAs in metagenomics data sets.

SUBMITTER: Nawrocki EP

PROVIDER: S-EPMC3849165 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature

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Computational identification of functional RNA homologs in metagenomic data.

Nawrocki Eric P EP Eddy Sean R SR

RNA biology 20130520 7

A key step toward understanding a metagenomics data set is the identification of functional sequence elements within it, such as protein coding genes and structural RNAs. Relative to protein coding genes, structural RNAs are more difficult to identify because of their reduced alphabet size, lack of open reading frames, and short length. Infernal is a software package that implements "covariance models" (CMs) for RNA homology search, which harness both sequence and structural conservation when se ...[more]

PMID: 23722291

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