Abstract

Most amino acids can be encoded by several synonymous codons, which are used at unequal frequencies. The significance of unequal codon usage remains unclear. One hypothesis is that frequent codons are translated relatively rapidly. However, there is little direct, in vivo evidence regarding codon-specific translation rates. Here, we generate high-coverage data using ribosome profiling in yeast, analyze using a novel algorithm, and deduce events at the A and P-sites of the ribosome. Different codons are decoded at different rates in the A-site. In general frequent codons are decoded more quickly than rare codons, and AT-rich codons are decoded more quickly than GC-rich codons. At the P-site, proline is slow in forming peptide bonds. We also apply our algorithm to short footprints from a different conformation of the ribosome, and find strong, amino-acid specific (not codon-specific) effects that may reflect interactions with the exit tunnel of the ribosome.

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  1. Justin Gardin

    Stony Brook University, Stony Brook, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Rukhsana Yeasmin

    Stony Brook University, Stony Brook, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Alisa Yurovsky

    Stony Brook University, Stony Brook, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Ying Cai

    Stony Brook University, Stony Brook, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Steve Skiena

    Stony Brook University, Stony Brook, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Bruce Futcher

    Stony Brook University, Stony Brook, United States
    For correspondence
    bfutcher@gmail.com
    Competing interests
    The authors declare that no competing interests exist.

Copyright

© 2014, Gardin et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Justin Gardin
  2. Rukhsana Yeasmin
  3. Alisa Yurovsky
  4. Ying Cai
  5. Steve Skiena
  6. Bruce Futcher
(2014)
Measurement of average decoding rates of the 61 sense codons in vivo
eLife 3:e03735.
https://doi.org/10.7554/eLife.03735

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https://doi.org/10.7554/eLife.03735