On the efficiency of the genetic code after frameshift mutations
Regine Geyer, Amir Madany Mamlouk
Published May 21, 2018
Author and article information
Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany
DOI: 10.7717/peerj.4825
Published 2018-05-21 Accepted 2018-05-02 Received 2017-10-02
Academic Editor Thomas Tullius
Subject Areas Bioinformatics, Evolutionary Studies, Genetics
Keywords Standard genetic code, Overlapping codes, Frameshift mutation, Polar requirement
Copyright
© 2018 Geyer and Madany Mamlouk
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
Cite this article
Geyer R, Madany Mamlouk A. (2018) On the efficiency of the genetic code after frameshift mutations. PeerJ 6:e4825 https://doi.org/10.7717/peerj.4825
Source/Fonte: NIH - U. S. National Library of Medicine
Abstract
Statistical and biochemical studies of the standard genetic code (SGC) have found evidence that the impact of mistranslations is minimized in a way that erroneous codes are either synonymous or code for an amino acid with similar polarity as the originally coded amino acid. It could be quantified that the SGC is optimized to protect this specific chemical property as good as possible. In recent work, it has been speculated that the multilevel optimization of the genetic code stands in the wider context of overlapping codes. This work tries to follow the systematic approach on mistranslations and to extend those analyses to the general effect of frameshift mutations on the polarity conservation of amino acids. We generated one million random codes and compared their average polarity change over all triplets and the whole set of possible frameshift mutations. While the natural code—just as for the point mutations—appears to be competitively robust against frameshift mutations as well, we found that both optimizations appear to be independent of each other. For both, better codes can be found, but it becomes significantly more difficult to find candidates that optimize all of these features—just like the SGC does. We conclude that the SGC is not only very efficient in minimizing the consequences of mistranslations, but rather optimized in amino acid polarity conservation for all three effects of code alteration, namely translational errors, point and frameshift mutations. In other words, our result demonstrates that the SGC appears to be much more than just “one in a million”.
Cite this as
Geyer R, Madany Mamlouk A. (2018) On the efficiency of the genetic code after frameshift mutations. PeerJ 6:e4825 https://doi.org/10.7717/peerj.4825
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