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QAPA: a new method for the systematic analysis of alternative polyadenylation from RNA-seq data

Alternative polyadenylation (APA) affects most mammalian genes. The genome-wide investigation of APA has been hampered by an inability to reliably profile it using conventional RNA-seq. We describe ‘Quantification of APA’ (QAPA), a method that infers APA from conventional RNA-seq data. QAPA is faste...

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Detalles Bibliográficos
Autores principales: Ha, Kevin C. H., Blencowe, Benjamin J., Morris, Quaid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5874996/
https://www.ncbi.nlm.nih.gov/pubmed/29592814
http://dx.doi.org/10.1186/s13059-018-1414-4
Descripción
Sumario:Alternative polyadenylation (APA) affects most mammalian genes. The genome-wide investigation of APA has been hampered by an inability to reliably profile it using conventional RNA-seq. We describe ‘Quantification of APA’ (QAPA), a method that infers APA from conventional RNA-seq data. QAPA is faster and more sensitive than other methods. Application of QAPA reveals discrete, temporally coordinated APA programs during neurogenesis and that there is little overlap between genes regulated by alternative splicing and those by APA. Modeling of these data uncovers an APA sequence code. QAPA thus enables the discovery and characterization of programs of regulated APA using conventional RNA-seq. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1414-4) contains supplementary material, which is available to authorized users.