Rfam is a collection of multiple sequence alignments and covariance models representing non-coding RNA families. Rfam is available on the web in the UK at http://www.sanger.ac.uk/Software/Rfam/ and in the US at http://rfam.wustl.edu/. These websites allow the user to search a query sequence against a library of covariance models, and view multiple sequence alignments and family annotation. The database can also be downloaded in flatfile form and searched locally using the INFERNAL package (http://infernal.wustl.edu/). The first release of Rfam (1.0) contains 25 families, which annotate over 50 000 non-coding RNA genes in the taxonomic divisions of the EMBL nucleotide database.

RNA silencing is a eukaryotic genome defence system that involves processing of double-stranded RNA (dsRNA) into 21-26 nt, short interfering RNA (siRNA). The siRNA mediates suppression of genes corresponding to the dsRNA through targeted RNA degradation. In some plant systems there are additional silencing processes, involving systemic spread of silencing and RNA-directed methylation/transcriptional suppression of homologous genomic DNA. We show here that siRNAs produced in plants from a green fluorescent protein (GFP) transgene are in short (21-22 nt) and long (24-26 nt) size classes, whereas those from endogenous retroelements are only in the long class. Viral suppressors of RNA silencing and mutations in Arabidopsis indicate that these classes of siRNA have different roles. The long siRNA is dispensable for sequence-specific mRNA degradation, but correlates with systemic silencing and methylation of homologous DNA. Conversely, the short siRNA class correlates with mRNA degradation but not with systemic signalling or methylation. These findings reveal an unexpected level of complexity in the RNA silencing pathway in plants that may also apply in animals.

Rfam is a comprehensive collection of non-coding RNA (ncRNA) families, represented by multiple sequence alignments and profile stochastic context-free grammars. Rfam aims to facilitate the identification and classification of new members of known sequence families, and distributes annotation of ncRNAs in over 200 complete genome sequences. The data provide the first glimpses of conservation of multiple ncRNA families across a wide taxonomic range. A small number of large families are essential in all three kingdoms of life, with large numbers of smaller families specific to certain taxa. Recent improvements in the database are discussed, together with challenges for the future. Rfam is available on the Web at http://www.sanger.ac.uk/Software/Rfam/ and http://rfam.wustl.edu/.

Gemin3 is a DEAD-box RNA helicase that binds to the Survival of Motor Neurons (SMN) protein and is a component of the SMN complex, which also comprises SMN, Gemin2, Gemin4, Gemin5, and Gemin6. Reduction in SMN protein results in Spinal muscular atrophy (SMA), a common neurodegenerative disease. The SMN complex has critical functions in the assembly/restructuring of diverse ribonucleoprotein (RNP) complexes. Here we report that Gemin3 and Gemin4 are also in a separate complex that contains eIF2C2, a member of the Argonaute protein family. This novel complex is a large approximately 15S RNP that contains numerous microRNAs (miRNAs). We describe 40 miRNAs, a few of which are identical to recently described human miRNAs, a class of small endogenous RNAs. The genomic sequences predict that miRNAs are likely to be derived from larger precursors that have the capacity to form stem-loop structures.

MicroRNAs (miRNAs) constitute a novel, phylogenetically extensive family of small RNAs ( approximately 22 nucleotides) with potential roles in gene regulation. Apart from the finding that miRNAs are produced by Dicer from the precursors of approximately 70 nucleotides (pre-miRNAs), little is known about miRNA biogenesis. Some miRNA genes have been found in close conjunction, suggesting that they are expressed as single transcriptional units. Here, we present in vivo and in vitro evidence that these clustered miRNAs are expressed polycistronically and are processed through at least two sequential steps:(i) generation of the approximately 70 nucleotide pre-miRNAs from the longer transcripts (termed pri-miRNAs); and (ii) processing of pre-miRNAs into mature miRNAs. Subcellular localization studies showed that the first and second steps are compartmentalized into the nucleus and cytoplasm, respectively, and that the pre-miRNA serves as the substrate for nuclear export. Our study suggests that the regulation of miRNA expression may occur at multiple levels, including the two processing steps and the nuclear export step. These data will provide a framework for further studies on miRNA biogenesis.

NONCODE is an integrated knowledge database dedicated to non-coding RNAs (ncRNAs), that is to say, RNAs that function without being translated into proteins. All ncRNAs in NONCODE were filtered automatically from literature and GenBank, and were later manually curated. The distinctive features of NONCODE are as follows:(i) the ncRNAs in NONCODE include almost all the types of ncRNAs, except transfer RNAs and ribosomal RNAs.(ii) All ncRNA sequences and their related information (e.g. function, cellular role, cellular location, chromosomal information, etc.) in NONCODE have been confirmed manually by consulting relevant literature: more than 80% of the entries are based on experimental data.(iii) Based on the cellular process and function, which a given ncRNA is involved in, we introduced a novel classification system, labeled process function class, to integrate existing classification systems.(iv) In addition, some 1100 ncRNAs have been grouped into nine other classes according to whether they are specific to gender or tissue or associated with tumors and diseases, etc.(v) NONCODE provides a user-friendly interface, a visualization platform and a convenient search option, allowing efficient recovery of sequence, regulatory elements in the flanking sequences, secondary structure, related publications and other information. The first release of NONCODE (v1.0) contains 5339 non-redundant sequences from 861 organisms, including eukaryotes, eubacteria, archaebacteria, virus and viroids. Access is free for all users through a web interface at http://noncode.bioinfo.org.cn.

BACKGROUND: MicroRNAs (miRNAs) are small noncoding RNAs that are processed from hairpin precursor transcripts by Dicer. miRNAs probably inhibit translation of mRNAs via imprecise antisense base-pairing. Small interfering RNAs (siRNAs) are similar in size to miRNAs, but they recognize targets by precise complementarity and elicit RNA-mediated interference (RNAi). We employed cDNA sequencing and comparative genomics to identify additional C. elegans small RNAs with properties similar to miRNAs and siRNAs. RESULTS: We found three broad classes of small RNAs in C. elegans:(1) 21 new miRNA genes (we estimate that C. elegans contains approximately 100 distinct miRNA genes, about 30% of which are conserved in vertebrates;(2), 33 distinct members of a class of tiny noncoding RNA (tncRNA) genes with transcripts that are similar in length to miRNAs (approximately 20-21 nt) and that are in some cases developmentally regulated but are apparently not processed from a miRNA-like hairpin precursor and are not phylogenetically conserved;(3) more than 700 distinct small antisense RNAs, about 20 nt long, that are precisely complementary to protein coding regions of more than 500 different genes and therefore seem to be endogenous siRNAs. CONCLUSIONS: The presence of diverse endogenous siRNAs in normal worms suggests ongoing, genome-wide gene silencing by RNAi. miRNAs and tncRNAs are not predicted to form complete Watson-Crick hybrids with any C. elegans RNA target, and so they are likely to regulate the activity of other genes by non-RNAi mechanisms. These results suggest that diverse modes of small RNA-mediated gene regulation are deployed in normal worms.

Eukaryotes produce various types of small RNAs of 19-28 nt in length. With rapidly increasing numbers of small RNAs listed in recent years, we have come to realize how widespread their functions are and how diverse the biogenesis pathways have evolved. At the same time, we are beginning to grasp the common features and rules governing the key steps in small RNA pathways. In this review, I will summarize the current classification, biogenesis, action mechanism and function of these fascinating molecules.