An in-depth map of polyadenylation sites in cancer

Lin, Yuefeng, Li, Zhihua, Ozsolak, Fatih, Kim, Sang Woo, Arango-Argoty, Gustavo, Liu, Teresa T., Tenenbaum, Scott A., Bailey, Timothy, Monaghan, A. Paula, Milos, Patrice M. and John, Bino (2012) An in-depth map of polyadenylation sites in cancer. Nucleic Acids Research, 40 17: 8460-8471.


Author Lin, Yuefeng
Li, Zhihua
Ozsolak, Fatih
Kim, Sang Woo
Arango-Argoty, Gustavo
Liu, Teresa T.
Tenenbaum, Scott A.
Bailey, Timothy
Monaghan, A. Paula
Milos, Patrice M.
John, Bino
Title An in-depth map of polyadenylation sites in cancer
Journal name Nucleic Acids Research   Check publisher's open access policy
ISSN 0305-1048
1362-4962
Publication date 2012-09
Sub-type Article (original research)
DOI 10.1093/nar/gks637
Volume 40
Issue 17
Start page 8460
End page 8471
Total pages 12
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Collection year 2013
Language eng
Abstract We present a comprehensive map of over 1 million polyadenylation sites and quantify their usage in major cancers and tumor cell lines using direct RNA sequencing. We built the Expression and Polyadenylation Database to enable the visualization of the polyadenylation maps in various cancers and to facilitate the discovery of novel genes and gene isoforms that are potentially important to tumorigenesis. Analyses of polyadenylation sites indicate that a large fraction (∼30%) of mRNAs contain alternative polyadenylation sites in their 3′ untranslated regions, independent of the cell type. The shortest 3′ untranslated region isoforms are preferentially upregulated in cancer tissues, genome-wide. Candidate targets of alternative polyadenylation-mediated upregulation of short isoforms include POLR2K, and signaling cascades of cell–cell and cell–extracellular matrix contact, particularly involving regulators of Rho GTPases. Polyadenylation maps also helped to improve 3′ untranslated region annotations and identify candidate regulatory marks such as sequence motifs, H3K36Me3 and Pabpc1 that are isoform dependent and occur in a position-specific manner. In summary, these results highlight the need to go beyond monitoring only the cumulative transcript levels for a gene, to separately analysing the expression of its RNA isoforms.
Open Access Mandate Compliance Yes - Open Access (Publisher DOI)
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes First published online: June 29, 2012

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
Institute for Molecular Bioscience - Publications
 
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Created: Fri, 03 Aug 2012, 09:37:56 EST by Susan Allen on behalf of Institute for Molecular Bioscience