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Dynamic expression of 3' UTRs revealed by Poisson hidden Markov modeling of RNA-Seq: implications in gene expression profiling.

ABSTRACT: RNA sequencing (RNA-Seq) allows for the identification of novel exon-exon junctions and quantification of gene expression levels. We show that from RNA-Seq data one may also detect utilization of alternative polyadenylation (APA) in 3' untranslated regions (3' UTRs) known to play a critical role in the regulation of mRNA stability, cellular localization and translation efficiency. Given the dynamic nature of APA, it is desirable to examine the APA on a sample by sample basis. We used a Poisson hidden Markov model (PHMM) of RNA-Seq data to identify potential APA in human liver and brain cortex tissues leading to shortened 3' UTRs. Over three hundred transcripts with shortened 3' UTRs were detected with sensitivity >75% and specificity >60%. Tissue-specific 3' UTR shortening was observed for 32 genes with a q-value ? 0.1. When compared to alternative isoforms detected by Cufflinks or MISO, our PHMM method agreed on over 100 transcripts with shortened 3' UTRs. Given the increasing usage of RNA-Seq for gene expression profiling, using PHMM to investigate sample-specific 3' UTR shortening could be an added benefit from this emerging technology.

SUBMITTER: Lu J

PROVIDER: S-EPMC3902974 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Dynamic expression of 3' UTRs revealed by Poisson hidden Markov modeling of RNA-Seq: implications in gene expression profiling.

Lu Jun J Bushel Pierre R PR

Gene 20130709 2

RNA sequencing (RNA-Seq) allows for the identification of novel exon-exon junctions and quantification of gene expression levels. We show that from RNA-Seq data one may also detect utilization of alternative polyadenylation (APA) in 3' untranslated regions (3' UTRs) known to play a critical role in the regulation of mRNA stability, cellular localization and translation efficiency. Given the dynamic nature of APA, it is desirable to examine the APA on a sample by sample basis. We used a Poisson h ...[more]

PMID: 23845781

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Dataset Information

Dynamic expression of 3' UTRs revealed by Poisson hidden Markov modeling of RNA-Seq: implications in gene expression profiling.

Publications

Dynamic expression of 3' UTRs revealed by Poisson hidden Markov modeling of RNA-Seq: implications in gene expression profiling.

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