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BMC Bioinformatics. 2001;2:8. Epub 2001 Oct 10.

Noncoding RNA gene detection using comparative sequence analysis.

Author information

1
Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, Saint Louis, Missouri, USA. elena@genetics.wustl.edu

Abstract

BACKGROUND:

Noncoding RNA genes produce transcripts that exert their function without ever producing proteins. Noncoding RNA gene sequences do not have strong statistical signals, unlike protein coding genes. A reliable general purpose computational genefinder for noncoding RNA genes has been elusive.

RESULTS:

We describe a comparative sequence analysis algorithm for detecting novel structural RNA genes. The key idea is to test the pattern of substitutions observed in a pairwise alignment of two homologous sequences. A conserved coding region tends to show a pattern of synonymous substitutions, whereas a conserved structural RNA tends to show a pattern of compensatory mutations consistent with some base-paired secondary structure. We formalize this intuition using three probabilistic "pair-grammars": a pair stochastic context free grammar modeling alignments constrained by structural RNA evolution, a pair hidden Markov model modeling alignments constrained by coding sequence evolution, and a pair hidden Markov model modeling a null hypothesis of position-independent evolution. Given an input pairwise sequence alignment (e.g. from a BLASTN comparison of two related genomes) we classify the alignment into the coding, RNA, or null class according to the posterior probability of each class.

CONCLUSIONS:

We have implemented this approach as a program, QRNA, which we consider to be a prototype structural noncoding RNA genefinder. Tests suggest that this approach detects noncoding RNA genes with a fair degree of reliability.

PMID:
11801179
PMCID:
PMC64605
[Indexed for MEDLINE]
Free PMC Article
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