An examination of 513 known pre-miRNAs and 237 other RNAs (tRNA, rRNA, and mRNA) revealed that miRNAs were significantly different from other RNAs (p < 0.001). miRNA genes were less conserved than other RNA genes, although their mature miRNA sequences were highly conserved. The A+U content of pre-miRNAs was higher than non-coding RNA (p < 0.001), but lower than mRNAs. The nucleotides in pre-miRNAs formed more hydrogen bonds and base pairs than in other RNAs. miRNAs had higher negative adjusted minimal folding free energies than other RNAs except tRNAs (p < 0.001). The MFE index (MFEI) was a sufficient criterion to distinguish miRNAs from all coding and non-coding RNAs (p < 0.001). The MFEI for miRNAs was 0.97, significantly higher than tRNAs (0.64), rRNAs (0.59), or mRNAs (0.65). Our findings should facilitate the prediction and identification of new miRNAs using computational and experimental strategies.

MicroRNAs are approximately 22-nucleotide (nt) RNAs processed from foldback segments of endogenous transcripts. Some are known to play important gene regulatory roles during animal and plant development by pairing to the messages of protein-coding genes to direct the post-transcriptional repression of these messages. Previously, we developed a computational method called MiRscan, which scores features related to the foldbacks, and used this algorithm to identify new miRNA genes in the nematode Caenorhabditis elegans. In the present study, to identify sequences that might be involved in processing or transcriptional regulation of miRNAs, we aligned sequences upstream and downstream of orthologous nematode miRNA foldbacks. These alignments showed a pronounced peak in sequence conservation about 200 bp upstream of the miRNA foldback and revealed a highly significant sequence motif, with consensus CTCCGCCC, that is present upstream of almost all independently transcribed nematode miRNA genes. Scoring the pattern of upstream/downstream conservation, the occurrence of this sequence motif, and orthology of host genes for intronic miRNA candidates, yielded substantial improvements in the accuracy of MiRscan. Nine new C. elegans miRNA gene candidates were validated using a PCR-sequencing protocol. As previously seen for bacterial RNA genes, sequence features outside of the RNA secondary structure can therefore be very useful for the computational identification of eukaryotic noncoding RNA genes. The total number of confidently identified nematode miRNAs now approaches 100. The improved analysis supports our previous assertion that miRNA gene identification is nearing completion in C. elegans with apparently no more than 20 miRNA genes now remaining to be identified.

Using an unsupervised pattern-discovery method, we processed the human intergenic and intronic regions and catalogued all variable-length patterns with identically conserved copies and multiplicities above what is expected by chance. Among the millions of discovered patterns, we found a subset of 127,998 patterns, termed pyknons, which have additional nonoverlapping instances in the untranslated and protein-coding regions of 30,675 transcripts from 20,059 human genes. The pyknons arrange combinatorially in the untranslated and coding regions of numerous human genes where they form mosaics. Consecutive instances of pyknons in these regions show a strong bias in their relative placement, favoring distances of approximately 22 nucleotides. We also found pyknons to be enriched in a statistically significant manner in genes involved in specific processes, e.g., cell communication, transcription, regulation of transcription, signaling, transport, etc. For approximately 1/3 of the pyknons, the intergenic/intronic instances of their reverse complement lie within 380,084 nonoverlapping regions, typically 60-80 nucleotides long, which are predicted to form double-stranded, energetically stable, hairpin-shaped RNA secondary structures; additionally, the pyknons subsume approximately 40% of the known microRNA sequences, thus suggesting a possible link with posttranscriptional gene silencing and RNA interference. Cross-genome comparisons reveal that many of the pyknons have instances in the 3? UTRs of genes from other vertebrates and invertebrates where they are overrepresented in similar biological processes, as in the human genome. These unexpected findings suggest potential unique functional connections between the coding and noncoding parts of the human genome.

Large numbers of noncoding RNA transcripts (ncRNAs) are being revealed by complementary DNA cloning and genome tiling array studies in animals. The big and as yet largely unanswered question is whether these transcripts are relevant. A paper by Willingham et al. shows the way forward by developing a strategy for large-scale functional screening of ncRNAs, involving small interfering RNA knockdowns in cell-based screens, which identified a previously unidentified ncRNA repressor of the transcription factor NFAT. It appears likely that ncRNAs constitute a critical hidden layer of gene regulation in complex organisms, the understanding of which requires new approaches in functional genomics.

Comprehensive identification of all functional elements encoded in the human genome is a fundamental need in biomedical research. Here, we present a comparative analysis of the human, mouse, rat and dog genomes to create a systematic catalogue of common regulatory motifs in promoters and 3? untranslated regions (3? UTRs). The promoter analysis yields 174 candidate motifs, including most previously known transcription-factor binding sites and 105 new motifs. The 3?-UTR analysis yields 106 motifs likely to be involved in post-transcriptional regulation. Nearly one-half are associated with microRNAs (miRNAs), leading to the discovery of many new miRNA genes and their likely target genes. Our results suggest that previous estimates of the number of human miRNA genes were low, and that miRNAs regulate at least 20% of human genes. The overall results provide a systematic view of gene regulation in the human, which will be refined as additional mammalian genomes become available.

MicroRNAs (miRNAs) are an extensive class of tiny RNA molecules that regulate the expression of target genes by means of complementary base pair interactions. Although the first miRNAs were discovered in Caenorhabditis elegans, >300 miRNAs were recently documented in animals and plants, both by cloning methods and computational predictions. We present a genome-wide computational approach to detect miRNA genes in the Arabidopsis thaliana genome. Our method is based on the conservation of short sequences between the genomes of Arabidopsis and rice (Oryza sativa) and on properties of the secondary structure of the miRNA precursor. The method was fine-tuned to take into account plant-specific properties, such as the variable length of the miRNA precursor sequences. In total, 91 potential miRNA genes were identified, of which 58 had at least one nearly perfect match with an Arabidopsis mRNA, constituting the potential targets of those miRNAs. In addition to already known transcription factors involved in plant development, the targets also comprised genes involved in several other cellular processes, such as sulfur assimilation and ubiquitin-dependent protein degradation. These findings considerably broaden the scope of miRNA functions in plants.

Thousands of mammalian messenger RNAs are under selective pressure to maintain 7-nucleotide sites matching microRNAs (miRNAs). We found that these conserved targets are often highly expressed at developmental stages before miRNA expression and that their levels tend to fall as the miRNA that targets them begins to accumulate. Nonconserved sites, which outnumber the conserved sites 10 to 1, also mediate repression. As a consequence, genes preferentially expressed at the same time and place as a miRNA have evolved to selectively avoid sites matching the miRNA. This phenomenon of selective avoidance extends to thousands of genes and enables spatial and temporal specificities of miRNAs to be revealed by finding tissues and developmental stages in which messages with corresponding sites are expressed at lower levels.

We used network-level conservation between pairs of fly (Drosophila melanogaster/D. pseudoobscura) and worm (Caenorhabditis elegans/C. briggsae) genomes to detect highly conserved mRNA motifs in 3? untranslated regions. Many of these elements are complementary to the 5? extremity of known microRNAs (miRNAs), and likely correspond to their target sites. We also identify known targets of RNA-binding proteins, and many novel sites not yet known to be functional. Coherent sets of genes with similar function often bear the same conserved elements, providing new insights into their cellular functions. We also show that target sites for distinct miRNAs are often simultaneously conserved, suggesting combinatorial regulation by multiple miRNAs. A genome-wide search for conserved stem-loops, containing complementary sequences to the novel sites, revealed many new candidate miRNAs that likely target them. We also provide evidence that posttranscriptional networks have undergone extensive rewiring across distant phyla, despite strong conservation of regulatory elements themselves.

MOTIVATION: The recent discoveries of large numbers of non-coding RNAs and computational advances in genome-scale RNA search create a need for tools for automatic, high quality identification and characterization of conserved RNA motifs that can be readily used for database search. Previous tools fall short of this goal. RESULTS: CMfinder is a new tool to predict RNA motifs in unaligned sequences. It is an expectation maximization algorithm using covariance models for motif description, featuring novel integration of multiple techniques for effective search of motif space, and a Bayesian framework that blends mutual information-based and folding energy-based approaches to predict structure in a principled way. Extensive tests show that our method works well on datasets with either low or high sequence similarity, is robust to inclusion of lengthy extraneous flanking sequence and/or completely unrelated sequences, and is reasonably fast and scalable. In testing on 19 known ncRNA families, including some difficult cases with poor sequence conservation and large indels, our method demonstrates excellent average per-base-pair accuracy?79% compared with at most 60% for alternative methods. More importantly, the resulting probabilistic model can be directly used for homology search, allowing iterative refinement of structural models based on additional homologs. We have used this approach to obtain highly accurate covariance models of known RNA motifs based on small numbers of related sequences, which identified homologs in deeply-diverged species.

MicroRNAs (miRNAs) affect the morphology of flowering plants by the posttranscriptional regulation of genes involved in critical developmental events. Understanding the spatial and temporal dynamics of miRNA activity during development is therefore central for understanding miRNA functions. We describe a microarray suitable for detection of plant miRNAs. Profiling of Arabidopsis thaliana miRNAs during normal development extends previous expression analyses, highlighting differential expression of miRNA families within specific organs and tissue types. Comparison of our miRNA expression data with existing mRNA microarray data provided a global intersection of plant miRNA and mRNA expression profiles and revealed that tissues in which a given miRNA is highly expressed are unlikely to also show high expression of the corresponding targets. Expression profiling was also used in a phylogenetic survey to test the depth of plant miRNA conservation. Of the 23 families of miRNAs tested, expression of 11 was detected in a gymnosperm and eight in a fern, directly demonstrating that many plant miRNAs have remained essentially unchanged since before the emergence of flowering plants. We also describe an empirical strategy for detecting miRNA target genes from unsequenced transcriptomes and show that targets in nonflowering plants as deeply branching as ferns and mosses are homologous to the targets in Arabidopsis. Therefore, several individual miRNA regulatory circuits have ancient origins and have remained intact throughout the evolution and diversification of plants.