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Genome-wide identification and predictive modeling of lincRNAs polyadenylation in cancer genome

Paper ID Volume ID Publish Year Pages File Format Full-Text
14989 1366 2014 8 PDF Available
Title
Genome-wide identification and predictive modeling of lincRNAs polyadenylation in cancer genome
Abstract

•Investigate the distribution of PASs respect to the lincRNA.•Acquire the distribution of lincRNA PAS in normal and cancer tissues.•Get the motifs surrounding lincRNA of normal and cancer tissues.•Propose a SVM-based lincRNA PASs identification method.

Long noncoding RNAs (lncRNAs) play essential regulatory roles in the human cancer genome. Many identified lncRNAs are transcribed by RNA polymerase II in which they are polyadenylated, whereby the long intervening noncoding RNAs (lincRNAs) have been widely used for the researches of lncRNAs. To date, the mechanism of lincRNAs polyadenylation related to cancer is rarely fully understood yet. In this paper, first we reported a comprehensive map of global lincRNAs polyadenylation sites (PASs) in five human cancer genomes; second we proposed a grouping method based on the pattern of genes expression and the manner of alternative polyadenylation (APA); third we investigated the distribution of motifs surrounding PASs. Our analysis reveals that about 70% of PASs are located in the sense strand of lincRNAs. Also more than 90% PASs in the antisense strand of lincRNAs are located in the intron regions. In addition, around 40% of lincRNA genes with PASs has APA sites. Four obvious motifs i.e., AATAAA, TTTTTTTT, CCAGSCTGG, and RGYRYRGTGG were detected in the sequences surrounding PASs in the normal and cancer tissues. Furthermore, a novel algorithm was proposed to recognize the lincRNAs PASs of tumor tissues based on support vector machine (SVM). The algorithm can achieve the accuracies up to 96.55% and 89.48% for identification the tumor lincRNAs PASs from the non-polyadenylation sites and the non-lincRNA PASs, respectively.

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Keywords
Long intervening noncoding RNA; Polyadenylation sites; Support vector machine
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Genome-wide identification and predictive modeling of lincRNAs polyadenylation in cancer genome
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Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 52, October 2014, Pages 1–8
Authors
, , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us