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Open Access Highly Accessed Research article

Computational RNomics of Drosophilids

Dominic Rose1, Jörg Hackermüller23, Stefan Washietl4, Kristin Reiche1, Jana Hertel14, Sven Findeiß1, Peter F Stadler12346 and Sonja J Prohaska5*

Author Affiliations

1 Bioinformatics Group, Department of Computer Science, University of Leipzig, Härtelstraße 16-18, Leipzig, Germany, D-04107

2 Fraunhofer Institute for Cell Therapy and Immunology, Deutscher Platz 5e, Leipzig, Germany, D-04103

3 Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16-18, Leipzig, Germany, D-04107

4 Department of Theoretical Chemistry, University of Vienna, Währingerstraße 17,Wien, Austria, A-1090

5 Biomedical Informatics, Arizona State University, Tempe, PO-Box 878809, USA, AZ 85287

6 Santa Fe Institute,1399 Hyde Park Rd., Santa Fe, USA, NM 87501

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BMC Genomics 2007, 8:406  doi:10.1186/1471-2164-8-406

Published: 8 November 2007

Abstract

Background

Recent experimental and computational studies have provided overwhelming evidence for a plethora of diverse transcripts that are unrelated to protein-coding genes. One subclass consists of those RNAs that require distinctive secondary structure motifs to exert their biological function and hence exhibit distinctive patterns of sequence conservation characteristic for positive selection on RNA secondary structure.

The deep-sequencing of 12 drosophilid species coordinated by the NHGRI provides an ideal data set of comparative computational approaches to determine those genomic loci that code for evolutionarily conserved RNA motifs. This class of loci includes the majority of the known small ncRNAs as well as structured RNA motifs in mRNAs. We report here on a genome-wide survey using RNAz.

Results

We obtain 16 000 high quality predictions among which we recover the majority of the known ncRNAs. Taking a pessimistically estimated false discovery rate of 40% into account, this implies that at least some ten thousand loci in the Drosophila genome show the hallmarks of stabilizing selection action of RNA structure, and hence are most likely functional at the RNA level. A subset of RNAz predictions overlapping with TRF1 and BRF binding sites [Isogai et al., EMBO J. 26: 79–89 (2007)], which are plausible candidates of Pol III transcripts, have been studied in more detail. Among these sequences we identify several "clusters" of ncRNA candidates with striking structural similarities.

Conclusion

The statistical evaluation of the RNAz predictions in comparison with a similar analysis of vertebrate genomes [Washietl et al., Nat. Biotech. 23: 1383–1390 (2005)] shows that qualitatively similar fractions of structured RNAs are found in introns, UTRs, and intergenic regions. The intergenic RNA structures, however, are concentrated much more closely around known protein-coding loci, suggesting that flies have significantly smaller complement of independent structured ncRNAs compared to mammals.