Biomedical subjects

Alexei Aravin

Publications and source records attributed to Alexei Aravin.

5 recordsLinked to original sources

PubMed2006

A novel class of small RNAs bind to MILI protein in mouse testes.

Small RNAs bound to Argonaute proteins recognize partially or fully complementary nucleic acid targets in diverse gene-silencing processes. A subgroup of the Argonaute proteins--known as the 'Piwi family'--is required for germ- and stem-cell development in invertebrates, and two Piwi members--MILI and MIWI--are essential for spermatogenesis in mouse. Here we describe a new class of small RNAs that bind to MILI in mouse male germ cells, where they accumulate at the onset of meiosis. The sequences of the over 1,000 identified unique molecules share a strong preference for a 5' uridine, but otherwise cannot be readily classified into sequence families. Genomic mapping of these small RNAs reveals a limited number of clusters, suggesting that these RNAs are processed from long primary transcripts. The small RNAs are 26-31 nucleotides (nt) in length--clearly distinct from the 21-23 nt of microRNAs (miRNAs) or short interfering RNAs (siRNAs)--and we refer to them as 'Piwi-interacting RNAs' or piRNAs. Orthologous human chromosomal regions also give rise to small RNAs with the characteristics of piRNAs, but the cloned sequences are distinct. The identification of this new class of small RNAs provides an important starting point to determine the molecular function of Piwi proteins in mammalian spermatogenesis.

Animals↗

PubMed2005

Identification of clustered microRNAs using an ab initio prediction method.

BACKGROUND: MicroRNAs (miRNAs) are endogenous 21 to 23-nucleotide RNA molecules that regulate protein-coding gene expression in plants and animals via the RNA interference pathway. Hundreds of them have been identified in the last five years and very recent works indicate that their total number is still larger. Therefore miRNAs gene discovery remains an important aspect of understanding this new and still widely unknown regulation mechanism. Bioinformatics approaches have proved to be very useful toward this goal by guiding the experimental investigations. RESULTS: In this work we describe our computational method for miRNA prediction and the results of its application to the discovery of novel mammalian miRNAs. We focus on genomic regions around already known miRNAs, in order to exploit the property that miRNAs are occasionally found in clusters. Starting with the known human, mouse and rat miRNAs we analyze 20 kb of flanking genomic regions for the presence of putative precursor miRNAs (pre-miRNAs). Each genome is analyzed separately, allowing us to study the species-specific identity and genome organization of miRNA loci. We only use cross-species comparisons to make conservative estimates of the number of novel miRNAs. Our ab initio method predicts between fifty and hundred novel pre-miRNAs for each of the considered species. Around 30% of these already have experimental support in a large set of cloned mammalian small RNAs. The validation rate among predicted cases that are conserved in at least one other species is higher, about 60%, and many of them have not been detected by prediction methods that used cross-species comparisons. A large fraction of the experimentally confirmed predictions correspond to an imprinted locus residing on chromosome 14 in human, 12 in mouse and 6 in rat. Our computational tool can be accessed on the world-wide-web. CONCLUSION: Our results show that the assumption that many miRNAs occur in clusters is fruitful for the discovery of novel miRNAs. Additionally we show that although the overall miRNA content in the observed clusters is very similar across the three considered species, the internal organization of the clusters changes in evolution.

Algorithms↗

PubMed2005

Identification and characterization of small RNAs involved in RNA silencing.

Double-stranded RNA (dsRNA) is a potent trigger of sequence-specific gene silencing mechanisms known as RNA silencing or RNA interference. The recognition of the target sequences is mediated by ribonucleoprotein complexes that contain 21- to 28-nucleotide (nt) guide RNAs derived from processing of the trigger dsRNA. Here, we review the experimental and bioinformatic approaches that were used to identify and characterize these small RNAs isolated from cells and tissues. The identification and characterization of small RNAs and their expression patterns is important for elucidating gene regulatory networks.

Animals↗

PubMed2005

Clustering and conservation patterns of human microRNAs.

MicroRNAs (miRNAs) are approximately 22 nt-long non-coding RNA molecules, believed to play important roles in gene regulation. We present a comprehensive analysis of the conservation and clustering patterns of known miRNAs in human. We show that human miRNA gene clustering is significantly higher than expected at random. A total of 37% of the known human miRNA genes analyzed in this study appear in clusters of two or more with pairwise chromosomal distances of at most 3000 nt. Comparison of the miRNA sequences with their homologs in four other organisms reveals a typical conservation pattern, persistent throughout the clusters. Furthermore, we show enrichment in the typical conservation patterns and other miRNA-like properties in the vicinity of known miRNA genes, compared with random genomic regions. This may imply that additional, yet unknown, miRNAs reside in these regions, consistent with the current recognition that there are overlooked miRNAs. Indeed, by comparing our predictions with cloning results and with identified miRNA genes in other mammals, we corroborate the predictions of 18 additional human miRNA genes in the vicinity of the previously known ones. Our study raises the proportion of clustered human miRNAs that are <3000 nt apart to 42%. This suggests that the clustering of miRNA genes is higher than currently acknowledged, alluding to its evolutionary and functional implications.

Base Sequence↗

PubMed2004

Human MicroRNA targets.

MicroRNAs (miRNAs) interact with target mRNAs at specific sites to induce cleavage of the message or inhibit translation. The specific function of most mammalian miRNAs is unknown. We have predicted target sites on the 3' untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments. We report about 2,000 human genes with miRNA target sites conserved in mammals and about 250 human genes conserved as targets between mammals and fish. The prediction algorithm optimizes sequence complementarity using position-specific rules and relies on strict requirements of interspecies conservation. Experimental support for the validity of the method comes from known targets and from strong enrichment of predicted targets in mRNAs associated with the fragile X mental retardation protein in mammals. This is consistent with the hypothesis that miRNAs act as sequence-specific adaptors in the interaction of ribonuclear particles with translationally regulated messages. Overrepresented groups of targets include mRNAs coding for transcription factors, components of the miRNA machinery, and other proteins involved in translational regulation, as well as components of the ubiquitin machinery, representing novel feedback loops in gene regulation. Detailed information about target genes, target processes, and open-source software for target prediction (miRanda) is available at http://www.microrna.org. Our analysis suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of all human genes.

3' Untranslated Regions↗