Background: MicroRNAs have been identified as crucial regulators in both animals and plants. Here we report on a comprehensive comparative study of all known miRNA families in animals. We expand the MicroRNA Registry 6.0 by more than 1000 new homologs of miRNA precursors whose expression has been verified in at least one species. Using this uniform data basis we analyze their evolutionary history in terms of individual gene phylogenies and in terms of preservation of genomic nearness across species. This allows us to reliably identify microRNA clusters that are derived from a common transcript.Results: We identify three episodes of microRNA innovation that correspond to major developmental innovations: A class of about 20 miRNAs is common to protostomes and deuterostomes and might be related to the advent of bilaterians. A second large wave of innovations maps to the branch leading to the vertebrates. The third significant outburst of miRNA innovation coincides with placental (eutherian) mammals. In addition, we observe the expected expansion of the microRNA inventory due to genome duplications in early vertebrates and in an ancestral teleost. The non-local duplications in the vertebrate ancestor are predated by local (tandem) duplications leading to the formation of about a dozen ancient microRNA clusters.Conclusion: Our results suggest that microRNA innovation is an ongoing process. Major expansions of the metazoan miRNA repertoire coincide with the advent of bilaterians, vertebrates, and (placental) mammals.

Summary: Recently, genome-wide surveys for non-coding RNAs have provided evidence for tens of thousands of previously undescribed evolutionary conserved RNAs with distinctive secondary structures. The annotation of these putative ncRNAs, however, remains a difficult problem. Here we describe an SVM-based approach that, in conjunction with a non-stringent filter for consensus secondary structures, is capable of efficiently recognizing microRNA precursors in multiple sequence alignments. The software was applied to recent genome-wide RNAz surveys of mammals, urochordates, and nematodes. Availability: The program RNAmicro is available as source code and can be downloaded from Contact:Jana Hertel, Tel: ++49 341 97 16704, Fax: ++49 341 97 16709, {jana,studla}@bioinf.uni-leipzig.de

Ribosomal RNA (rRNA) genes are probably the most frequently used data source in phylogenetic reconstruction. Individual columns of rRNA alignments are not independent as a consequence of their highly conserved secondary structures. Unless explicitly taken into account, these correlation can distort the phylogenetic signal and/or lead to gross overestimates of tree stability. Maximum likelihood and Bayesian approaches are of course amenable to using RNA-specific substitution models that treat conserved base pairs appropriately, but require accurate secondary structure models as input. So far, however, no accurate and easy-to-use tool has been available for computing structure-aware alignments and consensus structures that can deal with the large rRNAs. The RNAsalsa approach is designed to fill this gap. Capitalizing on the improved accuracy of pairwise consensus structures and informed by a priori knowledge of group-specific structural constraints, the tool provides both alignments and consensus structures that are of sufficient accuracy for routine phylogenetic analysis based on RNA-specific substitution models. The power of the approach is demonstrated using two rRNA data sets: a mitochondrial rRNA set of 26 Mammalia, and a collection of 28S nuclear rRNAs representative of the five major echinoderm groups.

Summary: Unlike tRNAs and microRNAs, both classes of snoRNAs, which direct two distinct types of chemical modifications of uracil residues, have proved to be surprisingly difficult to find in genomic sequences. Most computational approaches so far have explicitly used the fact that snoRNAs predominantly target ribosomal RNAs and spliceosomal RNAs. The target is specified by a short stretch of sequence complementarity between the snoRNA and its target. This sequence complementarity to known targets crucially contributes to sensitivity and specificity of snoRNA gene finding algorithms. The discovery of ‘orphan’ snoRNAs, which either have no known target, or which target ordinary protein-coding mRNAs, however, begs the question whether this class of ‘housekeeping’ non-coding RNAs is much more widespread and might have a diverse set of regulatory functions. In order to approach this question, we present here a combination of RNA secondary structure prediction and machine learning that is designed to recognize the two major classes of snoRNAs, box C/D and box H/ACA snoRNAs, among ncRNA candidate sequences. The snoReport approach deliberately avoids any usage of target information. We find that the combination of the conserved sequence boxes and secondary structure constraints as a pre-filter with SVM classifiers based on a small set of structural descriptors are sufficient for a reliable identification of snoRNAs. Tests of snoReport on data from several recent experimental surveys show that the approach is feasible; the application to a dataset from a large-scale comparative genomics survey for ncRNAs suggests that there are likely hundreds of previously undescribed ‘orphan’ snoRNAs still hidden in the human genome. Availability: The snoReport software is implemented in ANSI C. The source code is available under the GNU Public License at http://www.bioinf.uni-leipzig.de/Software/snoReport . Supplementary Material is available at http://www.bioinf.uni-leipzig.de/Publications/SUPPLEMENTS/07-015 Contact:jana@bioinf.uni-leipzig.de Supplementary information: Supplementary data are available at Bioinformatics online.

Background: Schistosomes are trematode parasites of the phylum Platyhelminthes. They are considered the most important of the human helminth parasites in terms of morbidity and mortality. Draft genome sequences are now available forSchistosoma mansoniandSchistosoma japonicum. Non-coding RNA (ncRNA) plays a crucial role in gene expression regulation, cellular function and defense, homeostasis, and pathogenesis. The genome-wide annotation of ncRNAs is a non-trivial task unless well-annotated genomes of closely related species are already available.Results: A homology search for structured ncRNA in the genome ofS. mansoniresulted in 23 types of ncRNAs with conserved primary and secondary structure. Among these, we identified rRNA, snRNA, SL RNA, SRP, tRNAs and RNase P, and also possibly MRP and 7SK RNAs. In addition, we confirmed five miRNAs that have recently been reported inS. japonicumand found two additional homologs of known miRNAs. The tRNA complement ofS. mansoniis comparable to that of the free-living planarianSchmidtea mediterranea, although for some amino acids differences of more than a factor of two are observed: Leu, Ser, and His are overrepresented, while Cys, Meth, and Ile are underrepresented inS. mansoni. On the other hand, the number of tRNAs in the genome ofS. japonicumis reduced by more than a factor of four. Both schistosomes have a complete set of minor spliceosomal snRNAs. Several ncRNAs that are expected to exist in theS. mansonigenome were not found, among them the telomerase RNA, vault RNAs, and Y RNAs.Conclusion: The ncRNA sequences and structures presented here represent the most complete dataset of ncRNA from any lophotrochozoan reported so far. This data set provides an important reference for further analysis of the genomes of schistosomes and indeed eukaryotic genomes at large.

A detailed annotation of non-protein coding RNAs is typically missing in initial releases of newly sequenced genomes. Here we report on a comprehensive ncRNA annotation of the genome of Trichoplax adhaerens, the presumably most basal metazoan whose genome has been published to-date. Since blast identified only a small fraction of the best-conserved ncRNAs--in particular rRNAs, tRNAs and some snRNAs--we developed a semi-global dynamic programming tool, GotohScan, to increase the sensitivity of the homology search. It successfully identified the full complement of major and minor spliceosomal snRNAs, the genes for RNase P and MRP RNAs, the SRP RNA, as well as several small nucleolar RNAs. We did not find any microRNA candidates homologous to known eumetazoan sequences. Interestingly, most ncRNAs, including the pol-III transcripts, appear as single-copy genes or with very small copy numbers in the Trichoplax genome.