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Identification of gene 3′ ends by automated EST cluster analysis
Author(s) -
Enrique M. Muro,
Robert Herrington,
Salima Janmohamed,
Catherine Frelin,
Miguel A. AndradeNavarro,
Norman N. Iscove
Publication year - 2008
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0807813105
Subject(s) - polyadenylation , biology , gene , genetics , computational biology , human genome , genome , refseq , messenger rna
The properties and biology of mRNA transcripts can be affected profoundly by the choice of alternative polyadenylation sites, making definition of the 3' ends of transcripts essential for understanding their regulation. Here we show that 22-52% of sequences in commonly used human and murine "full-length" transcript databases may not currently end at bona fide polyadenylation sites. To identify probable transcript termini over the entire murine and human genomes, we analyzed the EST databases for positional clustering of EST ends. The analysis yielded 58,282 murine- and 86,410 human-candidate polyadenylation sites, of which 75% mapped to 23,091 known murine transcripts and 22,891 known human transcripts. The murine dataset correctly predicted 97% of the 3' ends in a manually curated and experimentally supported benchmark transcript set. Of currently known genes, 15% had no associated prediction and 25% had only a single predicted termination site. The remaining genes had an average of 3-4 alternative polyadenylation sites predicted for each murine or human transcript, respectively. The results are made available in the form of tables and an interactive web site that can be mined for rapid assessment of the validity of 3' ends in existing collections, enumeration of potential alternative 3' polyadenylation sites of known transcripts, direct retrieval of terminal sequences for design of probes, and detection of polyadenylation sites not currently mapped to known genes.

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