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Detection of novel 3' untranslated region extensions with 3' expression microarrays.


ABSTRACT: BACKGROUND: The 3' untranslated regions (UTRs) of transcripts are not well characterized for many genes and often extend beyond the annotated regions. Since Affymetrix 3' expression arrays were designed based on expressed sequence tags, many probesets map to intergenic regions downstream of genes. We used expression information from these probesets to predict transcript extension beyond currently known boundaries. RESULTS: Based on our dataset encompassing expression in 22 different murine tissues, we identified 845 genes with predicted 3'UTR extensions. These extensions have a similar conservation as known 3'UTRs, which is distinctly higher than intergenic regions. We verified 8 of the predictions by PCR and found all of the predicted regions to be expressed. The method can be extended to other 3' expression microarray platforms as we demonstrate with human data. Additional confirming evidence was obtained from public paired end read data. CONCLUSIONS: We show that many genes have 3'UTR regions extending beyond currently known gene regions and provide a method to identify such regions based on microarray expression data. Since 3' UTR contain microRNA binding sites and other stability determining regions, identification of the full length 3' UTR is important to elucidate posttranscriptional regulation.

SUBMITTER: Thorrez L 

PROVIDER: S-EPMC2858751 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Detection of novel 3' untranslated region extensions with 3' expression microarrays.

Thorrez Lieven L   Tranchevent Leon-Charles LC   Chang Hui Ju HJ   Moreau Yves Y   Schuit Frans F  

BMC genomics 20100326


<h4>Background</h4>The 3' untranslated regions (UTRs) of transcripts are not well characterized for many genes and often extend beyond the annotated regions. Since Affymetrix 3' expression arrays were designed based on expressed sequence tags, many probesets map to intergenic regions downstream of genes. We used expression information from these probesets to predict transcript extension beyond currently known boundaries.<h4>Results</h4>Based on our dataset encompassing expression in 22 different  ...[more]

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