A Regression-Based Analysis of Ribosome-Profiling Data Reveals a Conserved Complexity to Mammalian Translation.

Mol Cell
Authors
Keywords
Abstract

A fundamental goal of genomics is to identify the complete set of expressed proteins. Automated annotation strategies rely on assumptions about protein-coding sequences (CDSs), e.g., they are conserved, do not overlap, and exceed a minimum length. However, an increasing number of newly discovered proteins violate these rules. Here we present an experimental and analytical framework, based on ribosome profiling and linear regression, for systematic identification and quantification of translation. Application of this approach to lipopolysaccharide-stimulated mouse dendritic cells and HCMV-infected human fibroblasts identifies thousands of novel CDSs, including micropeptides and variants of known proteins, that bear the hallmarks of canonical translation and exhibit translation levels and dynamics comparable to that of annotated CDSs. Remarkably, many translation events are identified in both mouse and human cells even when the peptide sequence is not conserved. Our work thus reveals an unexpected complexity to mammalian translation suited to provide both conserved regulatory or protein-based functions.

Year of Publication
2015
Journal
Mol Cell
Volume
60
Issue
5
Pages
816-27
Date Published
2015 Dec 03
ISSN
1097-4164
URL
DOI
10.1016/j.molcel.2015.11.013
PubMed ID
26638175
PubMed Central ID
PMC4720255
Links
Grant list
Howard Hughes Medical Institute / United States
T32 GM007618 / GM / NIGMS NIH HHS / United States
T32 GM008284 / GM / NIGMS NIH HHS / United States