APADB : a database for alternative polyadenylation and microRNA regulation events

Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) site
Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3' untranslated region (3'UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3'UTR shortening accelerates disease progression, dedifferentiation and proliferation. Here we present APADB, a database of vertebrate PA sites determined by 3' end sequencing, using massive analysis of complementary DNA ends. APADB provides (A)PA sites for coding and non-coding transcripts of human, mouse and chicken genes. For human and mouse, several tissue types, including different cancer specimens, are available. APADB records the loss of predicted miRNA binding sites and visualizes next-generation sequencing reads that support each PA site in a genome browser. The database tables can either be browsed according to organism and tissue or alternatively searched for a gene of interest. APADB is the largest database of APA in human, chicken and mouse. The stored information provides experimental evidence for thousands of PA sites and APA events. APADB combines 3' end sequencing data with prediction algorithms of miRNA binding sites, allowing to further improve prediction algorithms. Current databases lack correct information about 3'UTR lengths, especially for chicken, and APADB provides necessary information to close this gap. Database URL: http://tools.genxpro.net/apadb/
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Metadaten
Author:Sören Müller, Lukas Rycak, Fabian Afonso-Grunz, Peter Winter, Adam M. Zawada, Ewa Damrath, Jessica Scheider, Juliane Schmäh, Ina Koch, Günter Kahl, Björn Rotter
URN:urn:nbn:de:hebis:30:3-346887
DOI:http://dx.doi.org/10.1093/database/bau076
ISSN:1758-0463
Pubmed Id:http://www.ncbi.nlm.nih.gov/pubmed?term=25052703
Parent Title (English):Database
Publisher:Oxford University Press
Place of publication:Oxford
Document Type:Article
Language:English
Year of Completion:2014
Date of first Publication:2014/07/22
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2014/07/25
Volume:2014
Issue:bau076
Pagenumber:11
First Page:1
Last Page:11
Note:
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
HeBIS PPN:366008706
Institutes:Biowissenschaften
Informatik
Medizin
Institut für Ökologie, Evolution und Diversität
Exzellenzcluster Makromolekulare Komplexe
Dewey Decimal Classification:570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Sondersammelgebiets-Volltexte
Licence (German):License LogoCreative Commons - Namensnennung 3.0

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