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  Ribosome reinitiation can explain length-dependent translation of messenger RNA

Rogers, D. W., Böttcher, M. A., Traulsen, A., & Greig, D. (2017). Ribosome reinitiation can explain length-dependent translation of messenger RNA. PLoS Computational Biology, 13(6): e1005592. doi:10.1371/journal.pcbi.1005592.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002E-87E0-E Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002E-87E1-C
Genre: Journal Article

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 Creators:
Rogers, David W.1, Author              
Böttcher, Marvin A.2, Author              
Traulsen, Arne2, Author              
Greig, Duncan1, Author              
Affiliations:
1Max-Planck Research Group Experimental Evolution, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445640              
2Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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 Abstract: Author summary Recent advances in proteomics show that translation is strongly dependent on transcript length, but current theoretical models fail to capture this relationship. Here, we propose that the high initiation rates and protein yields of short transcripts result from terminating ribosomes reinitiating on the same transcript. The frequency of reinitiation depends on the time required to complete one full transit of a transcript, coupling transcript lengths and elongation rates to protein yield. Any slow step reduces the protein yield of shorter transcripts more than the yield of longer transcripts, generating stronger selective pressure to eliminate slow steps in shorter transcripts and explaining the widespread negative correlations in eukaryotes between transcript length and both 5' mRNA folding energy and codon adaptation. Our reinitiation-based model reconciles conflicting results from previous initiation-limited models with recent advances in biotechnology and identifies the mechanism underlying length-dependent translation, allowing powerful prediction of translational regulation across eukaryotes.

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Language(s): eng - English
 Dates: 2017-03-172017-05-252017-06-092017-06
 Publication Status: Published in print
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 Rev. Method: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1005592
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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: 19 Volume / Issue: 13 (6) Sequence Number: e1005592 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: /journals/resource/1000000000017180_1