Nucleic Acids Research, 2002, Vol. 30, No. 9 2076-2082
© 2002 Oxford University Press
Searching for RNA genes using base-composition statistics
Center for Biomolecular Science and Engineering, 227 Sinsheimer Laboratories, University of California, 1156 High Street, Santa Cruz, CA 95064, USA
The hypothesis that genomic regions rich in non-protein-coding RNAs (ncRNAs) can be identified using local variations in single-base and dinucleotide statistics has been investigated. (G+C)%, (G–C)% difference, (A–T)% difference and dinucleotide-frequency statistics were compared among seven classes of ncRNAs and three genomes. Significant variations were observed in (G+C)% and, in Methanococcus jannaschii, in the frequency of the dinucleotide ‘CG’. Screening programs based on these two base-composition statistics were developed. With (G+C)% screening alone, a 1% fraction of the M.jannaschii genome containing all 44 known transfer RNAs, ribosomal RNAs and signal recognition particle RNAs could be identified. When (G+C)% combined with CG dinucleotide-frequency screening was used, 43 of the 44 known M.jannaschii structural ncRNAs were again identified, while the number of presumably false hits overlapping a known or putative protein-coding gene was reduced from 15 to 6. In addition, 19 candidate ncRNAs were identified including one with significant homology to several known archaeal RNaseP RNAs.
* Email: schattner{at}cse.ucsc.edu
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