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Journal Article

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

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Chen,  Xiaowei Sylvia
Department of Biochemistry and Genetics Otago, University of Otago;
Language and Genetics Department, MPI for Psycholinguistics, Max Planck Society;

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Fulltext (public)

Chen_Nucl_Acids_Res_2012.pdf
(Publisher version), 4MB

Supplementary Material (public)

Chen_Suppl_Info_NAR_2012.pdf
(Supplementary material), 3MB

Chen_Suppl._info_TXT_NAR_2012
(Supplementary material), 41KB

Citation

Chen, X. S., & Brown, C. M. (2012). Computational identification of new structured cis-regulatory elements in the 3'-untranslated region of human protein coding genes. Nucleic Acids Research, 40, 8862-8873. doi:10.1093/nar/gks684.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-E553-E
Abstract
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: http://mRNA.otago.ac.nz/CisRNA-SVM.