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      Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites

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          Abstract

          mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.

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          A tutorial on support vector regression

          Alex Smola, Bernhard Schölkopf (2004)
          Article 0 comments Cited 1285 times – based on 0 reviews     Review now
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            Ago HITS-CLIP decodes miRNA-mRNA interaction maps

            Sung Wook Chi, Julie B. Zang, Aldo Mele … (2009)
            Summary MicroRNAs (miRNAs) play critical roles in the regulation of gene expression. However, since miRNA activity requires base pairing with only 6-8 nucleotides of mRNA, predicting target mRNAs is a major challenge. Recently, high-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP) has identified functional protein-RNA interaction sites. Here we use HITS-CLIP to covalently crosslink native Argonaute (Ago) protein-RNA complexes in mouse brain. This produced two simultaneous datasets—Ago-miRNA and Ago-mRNA binding sites—that were combined with bioinformatic analysis to identify miRNA-target mRNA interaction sites. We validated genome-wide interaction maps for miR-124, and generated additional maps for the 20 most abundant miRNAs present in P13 mouse brain. Ago HITS-CLIP provides a general platform for exploring the specificity and range of miRNA action in vivo, and identifies precise sequences for targeting clinically relevant miRNA-mRNA interactions.
            Article 0 comments Cited 654 times – based on 0 reviews     Review now
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              MicroRNA-directed cleavage of HOXB8 mRNA.

              Soraya Yekta, I-Hung Shih, David Bartel (2004)
              MicroRNAs (miRNAs) are endogenous approximately 22-nucleotide RNAs, some of which are known to play important regulatory roles in animals by targeting the messages of protein-coding genes for translational repression. We find that miR-196, a miRNA encoded at three paralogous locations in the A, B, and C mammalian HOX clusters, has extensive, evolutionarily conserved complementarity to messages of HOXB8, HOXC8, and HOXD8. RNA fragments diagnostic of miR-196-directed cleavage of HOXB8 were detected in mouse embryos. Cell culture experiments demonstrated down-regulation of HOXB8, HOXC8, HOXD8, and HOXA7 and supported the cleavage mechanism for miR-196-directed repression of HOXB8. These results point to a miRNA-mediated mechanism for the posttranscriptional restriction of HOX gene expression during vertebrate development and demonstrate that metazoan miRNAs can repress expression of their natural targets through mRNA cleavage in addition to inhibiting productive translation.
              Article 0 comments Cited 442 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Genome Biol
                Title: Genome Biology
                Publisher: BioMed Central
                ISSN (Print): 1465-6906
                ISSN (Electronic): 1465-6914
                Publication date (Print): 2010
                Publication date (Electronic): 27 August 2010
                Volume: 11
                Issue: 8
                Page: R90
                Affiliations
                [1 ]Computational Biology Program, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, 10065, NY, USA
                [2 ]Department of Computer Science, Columbia University, 1214 Amsterdam Avenue, New York, 10027, NY, USA
                Article
                Publisher ID: gb-2010-11-8-r90
                DOI: 10.1186/gb-2010-11-8-r90
                PMC ID: 2945792
                PubMed ID: 20799968
                SO-VID: 58fb637a-1352-401a-8a35-c8dab4c363b5
                Copyright © Copyright ©2010 Betel et al; licensee BioMed Central Ltd.
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 26 April 2010
                Date accepted : 27 August 2010
                Categories
                Subject: Method

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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