Genome sequencing of Helicobacter pylori has revealed the potential proteins and genetic diversity of this prevalent human pathogen, yet little is known about its transcriptional organization and noncoding RNA output. Massively parallel cDNA sequencing (RNA-seq) has been revolutionizing global transcriptomic analysis. Here, using a novel differential approach (dRNA-seq) selective for the 5' end of primary transcripts, we present a genome-wide map of H. pylori transcriptional start sites and operons. We discovered hundreds of transcriptional start sites within operons, and opposite to annotated genes, indicating that complexity of gene expression from the small H. pylori genome is increased by uncoupling of polycistrons and by genome-wide antisense transcription. We also discovered an unexpected number of approximately 60 small RNAs including the epsilon-subdivision counterpart of the regulatory 6S RNA and associated RNA products, and potential regulators of cis- and trans-encoded target messenger RNAs. Our approach establishes a paradigm for mapping and annotating the primary transcriptomes of many living species.

The RFAM database defines families of ncRNAs by means of sequence similarities that are sufficient to establish homology. In some cases, such as microRNAs and box H/ACA snoRNAs, functional commonalities define classes of RNAs that are characterized by structural similarities, and typically consist of multiple RNA families. Recent advances in high-throughput transcriptomics and comparative genomics have produced very large sets of putative noncoding RNAs and regulatory RNA signals. For many of them, evidence for stabilizing selection acting on their secondary structures has been derived, and at least approximate models of their structures have been computed. The overwhelming majority of these hypothetical RNAs cannot be assigned to established families or classes. We present here a structure-based clustering approach that is capable of extracting putative RNA classes from genome-wide surveys for structured RNAs. The LocARNA (local alignment of RNA) tool implements a novel variant of the Sankoff algorithm that is sufficiently fast to deal with several thousand candidate sequences. The method is also robust against false positive predictions, i.e., a contamination of the input data with unstructured or nonconserved sequences. We have successfully tested the LocARNA-based clustering approach on the sequences of the RFAM-seed alignments. Furthermore, we have applied it to a previously published set of 3,332 predicted structured elements in the Ciona intestinalis genome (Missal K, Rose D, Stadler PF (2005) Noncoding RNAs in Ciona intestinalis. Bioinformatics 21 (Supplement 2): i77–i78). In addition to recovering, e.g., tRNAs as a structure-based class, the method identifies several RNA families, including microRNA and snoRNA candidates, and suggests several novel classes of ncRNAs for which to date no representative has been experimentally characterized.

With ∼30 000 deaths annually in the United States, prostate cancer (PCa) is a major oncologic disease. Here we show that the microRNAs miR-130a, miR-203 and miR-205 jointly interfere with the two major oncogenic pathways in prostate carcinoma and are downregulated in cancer tissue. Using transcriptomics we show that the microRNAs repress several gene products known to be overexpressed in this cancer. Argonaute 2 (AGO2) co-immunoprecipitation, reporter assays and western blot analysis demonstrate that the microRNAs directly target several components of the mitogen-activated protein kinase (MAPK) and androgen receptor (AR) signaling pathways, among those several AR coregulators and HRAS (Harvey rat sarcoma viral oncogene homolog), and repress signaling activity. Both pathways are central for the development of the primary tumor and in particular the progression to its incurable castration-resistant form. Reconstitution of the microRNAs in LNCaP PCa cells induce morphological changes, which resemble the effect of androgen deprivation, and jointly impair tumor cell growth by induction of apoptosis and cell cycle arrest. We therefore propose that these microRNAs jointly act as tumor suppressors in prostate carcinoma and might interfere with progression to castration resistance.

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to ∼2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3Ј-UTRs. While we estimate a significant false discovery rate of ∼50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).[The sequenced fragments of verified ncRNA predictions and TEC were deposited to GenBank under accession nos. EF212232-EF212281 and EF212282-EF212289, respectively.]The goal of The ENCODE Project Consortium (Encyclopedia of DNA Elements [ENCODE]) is the comprehensive analysis of functional elements in the human genome. One of its main goals is the thorough annotation of transcripts in terms of structure and function. Both genome-wide studies (Bertone et al. 2004;Carninci et al. 2005;Cheng et al. 2005) and the far more detailed studies targeted to the ENCODE regions (The ENCODE Project Consortium 2007) show a much more extensive and complex transcriptional map than previously anticipated, comprising a mosaic of overlapping transcription, antisense transcripts, abundant alternative splicing, and a plethora of novel transcribed elements. Using a series of sensitive methods, it was demonstrated that 93% of the ENCODE regions exist in primary nuclear transcripts in at least one of the tested tissues.