Cargando…

CLIP-based prediction of mammalian microRNA binding sites

Prediction and validation of microRNA (miRNA) targets are essential for understanding functions of miRNAs in gene regulation. Crosslinking immunoprecipitation (CLIP) allows direct identification of a huge number of Argonaute-bound target sequences that contain miRNA binding sites. By analysing data...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Chaochun, Mallick, Bibekanand, Long, Dang, Rennie, William A., Wolenc, Adam, Carmack, C. Steven, Ding, Ye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3737542/
https://www.ncbi.nlm.nih.gov/pubmed/23703212
http://dx.doi.org/10.1093/nar/gkt435
_version_ 1782279876352409600
author Liu, Chaochun
Mallick, Bibekanand
Long, Dang
Rennie, William A.
Wolenc, Adam
Carmack, C. Steven
Ding, Ye
author_facet Liu, Chaochun
Mallick, Bibekanand
Long, Dang
Rennie, William A.
Wolenc, Adam
Carmack, C. Steven
Ding, Ye
author_sort Liu, Chaochun
collection PubMed
description Prediction and validation of microRNA (miRNA) targets are essential for understanding functions of miRNAs in gene regulation. Crosslinking immunoprecipitation (CLIP) allows direct identification of a huge number of Argonaute-bound target sequences that contain miRNA binding sites. By analysing data from CLIP studies, we identified a comprehensive list of sequence, thermodynamic and target structure features that are essential for target binding by miRNAs in the 3′ untranslated region (3′ UTR), coding sequence (CDS) region and 5′ untranslated region (5′ UTR) of target messenger RNA (mRNA). The total energy of miRNA:target hybridization, a measure of target structural accessibility, is the only essential feature common for both seed and seedless sites in all three target regions. Furthermore, evolutionary conservation is an important discriminating feature for both seed and seedless sites. These features enabled us to develop novel statistical models for the predictions of both seed sites and broad classes of seedless sites. Through both intra-dataset validation and inter-dataset validation, our approach showed major improvements over established algorithms for predicting seed sites and a class of seedless sites. Furthermore, we observed good performance from cross-species validation, suggesting that our prediction framework can be valuable for broad application to other mammalian species and beyond. Transcriptome-wide binding site predictions enabled by our approach will greatly complement the available CLIP data, which only cover small fractions of transcriptomes and known miRNAs due to non-detectable levels of expression. Software and database tools based on the prediction models have been developed and are available through Sfold web server at http://sfold.wadsworth.org.
format Online
Article
Text
id pubmed-3737542
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-37375422013-08-08 CLIP-based prediction of mammalian microRNA binding sites Liu, Chaochun Mallick, Bibekanand Long, Dang Rennie, William A. Wolenc, Adam Carmack, C. Steven Ding, Ye Nucleic Acids Res Methods Online Prediction and validation of microRNA (miRNA) targets are essential for understanding functions of miRNAs in gene regulation. Crosslinking immunoprecipitation (CLIP) allows direct identification of a huge number of Argonaute-bound target sequences that contain miRNA binding sites. By analysing data from CLIP studies, we identified a comprehensive list of sequence, thermodynamic and target structure features that are essential for target binding by miRNAs in the 3′ untranslated region (3′ UTR), coding sequence (CDS) region and 5′ untranslated region (5′ UTR) of target messenger RNA (mRNA). The total energy of miRNA:target hybridization, a measure of target structural accessibility, is the only essential feature common for both seed and seedless sites in all three target regions. Furthermore, evolutionary conservation is an important discriminating feature for both seed and seedless sites. These features enabled us to develop novel statistical models for the predictions of both seed sites and broad classes of seedless sites. Through both intra-dataset validation and inter-dataset validation, our approach showed major improvements over established algorithms for predicting seed sites and a class of seedless sites. Furthermore, we observed good performance from cross-species validation, suggesting that our prediction framework can be valuable for broad application to other mammalian species and beyond. Transcriptome-wide binding site predictions enabled by our approach will greatly complement the available CLIP data, which only cover small fractions of transcriptomes and known miRNAs due to non-detectable levels of expression. Software and database tools based on the prediction models have been developed and are available through Sfold web server at http://sfold.wadsworth.org. Oxford University Press 2013-08 2013-05-22 /pmc/articles/PMC3737542/ /pubmed/23703212 http://dx.doi.org/10.1093/nar/gkt435 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Liu, Chaochun
Mallick, Bibekanand
Long, Dang
Rennie, William A.
Wolenc, Adam
Carmack, C. Steven
Ding, Ye
CLIP-based prediction of mammalian microRNA binding sites
title CLIP-based prediction of mammalian microRNA binding sites
title_full CLIP-based prediction of mammalian microRNA binding sites
title_fullStr CLIP-based prediction of mammalian microRNA binding sites
title_full_unstemmed CLIP-based prediction of mammalian microRNA binding sites
title_short CLIP-based prediction of mammalian microRNA binding sites
title_sort clip-based prediction of mammalian microrna binding sites
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3737542/
https://www.ncbi.nlm.nih.gov/pubmed/23703212
http://dx.doi.org/10.1093/nar/gkt435
work_keys_str_mv AT liuchaochun clipbasedpredictionofmammalianmicrornabindingsites
AT mallickbibekanand clipbasedpredictionofmammalianmicrornabindingsites
AT longdang clipbasedpredictionofmammalianmicrornabindingsites
AT renniewilliama clipbasedpredictionofmammalianmicrornabindingsites
AT wolencadam clipbasedpredictionofmammalianmicrornabindingsites
AT carmackcsteven clipbasedpredictionofmammalianmicrornabindingsites
AT dingye clipbasedpredictionofmammalianmicrornabindingsites