Improved Ribosome-Footprint and mRNA Measurements Provide Insights into Dynamics and Regulation of Yeast Translation
Author(s)
Weinberg, David E.; Shah, Premal; Hussmann, Jeffrey A.; Plotkin, Joshua B.; Eichhorn, Stephen William; Bartel, David; ... Show more Show less
DownloadWeinberg-2016-Improved Ribosome-Fo.pdf (48.79Mb)
PUBLISHER_CC
Publisher with Creative Commons License
Creative Commons Attribution
Terms of use
Metadata
Show full item recordAbstract
Ribosome-footprint profiling provides genome-wide snapshots of translation, but technical challenges can confound its analysis. Here, we use improved methods to obtain ribosome-footprint profiles and mRNA abundances that more faithfully reflect gene expression in Saccharomyces cerevisiae. Our results support proposals that both the beginning of coding regions and codons matching rare tRNAs are more slowly translated. They also indicate that emergent polypeptides with as few as three basic residues within a ten-residue window tend to slow translation. With the improved mRNA measurements, the variation attributable to translational control in exponentially growing yeast was less than previously reported, and most of this variation could be predicted with a simple model that considered mRNA abundance, upstream open reading frames, cap-proximal structure and nucleotide composition, and lengths of the coding and 5′ UTRs. Collectively, our results provide a framework for executing and interpreting ribosome-profiling studies and reveal key features of translational control in yeast.
Date issued
2016-02Department
Massachusetts Institute of Technology. Department of Biology; Whitehead Institute for Biomedical ResearchJournal
Cell Reports
Publisher
Elsevier
Citation
Weinberg, David E., Premal Shah, Stephen W. Eichhorn, Jeffrey A. Hussmann, Joshua B. Plotkin, and David P. Bartel. “Improved Ribosome-Footprint and mRNA Measurements Provide Insights into Dynamics and Regulation of Yeast Translation.” Cell Reports 14, no. 7 (February 2016): 1787–99.
Version: Final published version
ISSN
22111247