Title |
Ribosome Traffic on mRNAs Maps to Gene Ontology: Genome-wide Quantification of Translation Initiation Rates and Polysome Size Regulation
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Published in |
PLoS Computational Biology, January 2013
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DOI | 10.1371/journal.pcbi.1002866 |
Pubmed ID | |
Authors |
Luca Ciandrini, Ian Stansfield, M. Carmen Romano |
Abstract |
To understand the complex relationship governing transcript abundance and the level of the encoded protein, we integrate genome-wide experimental data of ribosomal density on mRNAs with a novel stochastic model describing ribosome traffic dynamics during translation elongation. This analysis reveals that codon arrangement, rather than simply codon bias, has a key role in determining translational efficiency. It also reveals that translation output is governed both by initiation efficiency and elongation dynamics. By integrating genome-wide experimental data sets with simulation of ribosome traffic on all Saccharomyces cerevisiae ORFs, mRNA-specific translation initiation rates are for the first time estimated across the entire transcriptome. Our analysis identifies different classes of mRNAs characterised by their initiation rates, their ribosome traffic dynamics, and by their response to ribosome availability. Strikingly, this classification based on translational dynamics maps onto key gene ontological classifications, revealing evolutionary optimisation of translation responses to be strongly influenced by gene function. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 25% |
Norway | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
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Scientists | 2 | 50% |
Members of the public | 2 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | 4% |
Germany | 3 | 2% |
United Kingdom | 3 | 2% |
Portugal | 2 | 1% |
Switzerland | 1 | <1% |
Iran, Islamic Republic of | 1 | <1% |
France | 1 | <1% |
Estonia | 1 | <1% |
Argentina | 1 | <1% |
Other | 0 | 0% |
Unknown | 153 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 48 | 28% |
Student > Ph. D. Student | 46 | 27% |
Student > Master | 16 | 9% |
Student > Bachelor | 10 | 6% |
Student > Doctoral Student | 9 | 5% |
Other | 26 | 15% |
Unknown | 18 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 73 | 42% |
Biochemistry, Genetics and Molecular Biology | 41 | 24% |
Physics and Astronomy | 11 | 6% |
Computer Science | 9 | 5% |
Engineering | 5 | 3% |
Other | 13 | 8% |
Unknown | 21 | 12% |