Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110, USA.
Some genes produce noncoding transcripts that function directly as structural, regulatory, or even catalytic RNAs [1, 2]. Unlike protein-coding genes, which can be detected as open reading frames with distinctive statistical biases, noncoding RNA (ncRNA) gene sequences have no obvious inherent statistical biases [3]. Thus, genome sequence analyses reveal novel protein-coding genes, but any novel ncRNA genes remain invisible. Here, we describe a computational comparative genomic screen for ncRNA genes. The key idea is to distinguish conserved RNA secondary structures from a background of other conserved sequences using probabilistic models of expected mutational patterns in pairwise sequence alignments. We report the first whole-genome screen for ncRNA genes done with this method, in which we applied it to the "intergenic" spacers of Escherichia coli using comparative sequence data from four related bacteria. Starting from >23,000 conserved interspecies pairwise alignments, the screen predicted 275 candidate structural RNA loci. A sample of 49 candidate loci was assayed experimentally. At least 11 loci expressed small, apparently noncoding RNA transcripts of unknown function. Our computational approach may be used to discover structural ncRNA genes in any genome for which appropriate comparative genome sequence data are available.