4.8 Article

Computational identification of new structured cis-regulatory elements in the 3'-untranslated region of human protein coding genes

期刊

NUCLEIC ACIDS RESEARCH
卷 40, 期 18, 页码 8862-8873

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OXFORD UNIV PRESS
DOI: 10.1093/nar/gks684

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资金

  1. Human Frontier Science Foundation [RGP0031 2009]
  2. University of Otago Research Grant

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Messenger ribonucleic acids (RNAs) contain a large number of cis-regulatory RNA elements that function in many types of post-transcriptional regulation. These cis-regulatory elements are often characterized by conserved structures and/or sequences. Although some classes are well known, given the wide range of RNA-interacting proteins in eukaryotes, it is likely that many new classes of cis-regulatory elements are yet to be discovered. An approach to this is to use computational methods that have the advantage of analysing genomic data, particularly comparative data on a large scale. In this study, a set of structural discovery algorithms was applied followed by support vector machine (SVM) classification. We trained a new classification model (CisRNA-SVM) on a set of known structured cis-regulatory elements from 3'-untranslated regions (UTRs) and successfully distinguished these and groups of cis-regulatory elements not been strained on from control genomic and shuffled sequences. The new method outperformed previous methods in classification of cis-regulatory RNA elements. This model was then used to predict new elements from cross-species conserved regions of human 3'-UTRs. Clustering of these elements identified new classes of potential cis-regulatory elements. The model, training and testing sets and novel human predictions are available at: ext-link-type=uri xlink:href=http://mRNA.otago.ac.nz/CisRNA-SVM xmlns:xlink=http://www.w3.org/1999/xlink>http://mRNA.otago.ac.nz/CisRNA-SVM.

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