Assessing gene-level translational control from ribosome profiling.
Bioinformatics
; 29(23): 2995-3002, 2013 Dec 01.
Article
em En
| MEDLINE
| ID: mdl-24048356
ABSTRACT
MOTIVATION The translational landscape of diverse cellular systems remains largely uncharacterized. A detailed understanding of the control of gene expression at the level of messenger RNA translation is vital to elucidating a systems-level view of complex molecular programs in the cell. Establishing the degree to which such post-transcriptional regulation can mediate specific phenotypes is similarly critical to elucidating the molecular pathogenesis of diseases such as cancer. Recently, methods for massively parallel sequencing of ribosome-bound fragments of messenger RNA have begun to uncover genome-wide translational control at codon resolution. Despite its promise for deeply characterizing mammalian proteomes, few analytical methods exist for the comprehensive analysis of this paired RNA and ribosome data. RESULTS:
We describe the Babel framework, an analytical methodology for assessing the significance of changes in translational regulation within cells and between conditions. This approach facilitates the analysis of translation genome-wide while allowing statistically principled gene-level inference. Babel is based on an errors-in-variables regression model that uses the negative binomial distribution and draws inference using a parametric bootstrap approach. We demonstrate the operating characteristics of Babel on simulated data and use its gene-level inference to extend prior analyses significantly, discovering new translationally regulated modules under mammalian target of rapamycin (mTOR) pathway signaling control.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Ribossomos
/
Biossíntese de Proteínas
/
Software
/
RNA Mensageiro
/
Perfilação da Expressão Gênica
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Sequenciamento de Nucleotídeos em Larga Escala
Tipo de estudo:
Prognostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2013
Tipo de documento:
Article
País de afiliação:
Estados Unidos