Assessing gene-level translational control from ribosome profiling

Bioinformatics. 2013 Dec 1;29(23):2995-3002. doi: 10.1093/bioinformatics/btt533. Epub 2013 Sep 18.


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Codon / metabolism
  • Computer Simulation
  • Gene Expression Profiling*
  • Gene Expression Regulation
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Protein Biosynthesis / genetics*
  • RNA, Messenger / genetics
  • RNA, Messenger / metabolism*
  • Ribosomes / genetics
  • Ribosomes / metabolism*
  • Software*
  • TOR Serine-Threonine Kinases / genetics
  • TOR Serine-Threonine Kinases / metabolism


  • Codon
  • RNA, Messenger
  • TOR Serine-Threonine Kinases