Lost in Translation: Bioinformatic Analysis of Variations Affecting the Translation Initiation Codon in the Human Genome

Lost in Translation: Bioinformatic Analysis of Variations Affecting the Translation Initiation... Abstract Motivation Translation is a key biological process controlled in eukaryotes by the initiation AUG codon. Variations affecting this codon may have pathological consequences by disturbing the correct initiation of translation. Unfortunately, there is no systematic study describing these variations in the human genome. Moreover, we aimed to develop new tools for in silico prediction of the pathogenicity of gene variations affecting AUG codons, because to date, these gene defects have been wrongly classified as missense. Results Whole-exome analysis revealed the mean of 12 gene variations per person affecting initiation codons, mostly with high (> 0:01) minor allele frequency (MAF). Moreover, analysis of Ensembl data (December 2017) revealed 11,261 genetic variations affecting the initiation AUG codon of 7,205 genes. Most of these variations (99.5%) have low or unknown MAF, probably reflecting deleterious consequences. Only 62 variations had high MAF. Genetic variations with high MAF had closer alternative AUG downstream codons than did those with low MAF. Besides, the high-MAF group better maintained both the signal peptide and reading frame. These differentiating elements could help to determine the pathogenicity of this kind of variation. Availability Data and scripts in Perl and R are freely available at https://github.com/fanavarro/hemodonacion Contact jfernand@um.es Supplementary information Supplementary data are available at Bioinformatics online. © The Author(s) (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bioinformatics Oxford University Press

Lost in Translation: Bioinformatic Analysis of Variations Affecting the Translation Initiation Codon in the Human Genome

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Publisher
Oxford University Press
Copyright
© The Author(s) (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
ISSN
1367-4803
eISSN
1460-2059
D.O.I.
10.1093/bioinformatics/bty453
Publisher site
See Article on Publisher Site

Abstract

Abstract Motivation Translation is a key biological process controlled in eukaryotes by the initiation AUG codon. Variations affecting this codon may have pathological consequences by disturbing the correct initiation of translation. Unfortunately, there is no systematic study describing these variations in the human genome. Moreover, we aimed to develop new tools for in silico prediction of the pathogenicity of gene variations affecting AUG codons, because to date, these gene defects have been wrongly classified as missense. Results Whole-exome analysis revealed the mean of 12 gene variations per person affecting initiation codons, mostly with high (> 0:01) minor allele frequency (MAF). Moreover, analysis of Ensembl data (December 2017) revealed 11,261 genetic variations affecting the initiation AUG codon of 7,205 genes. Most of these variations (99.5%) have low or unknown MAF, probably reflecting deleterious consequences. Only 62 variations had high MAF. Genetic variations with high MAF had closer alternative AUG downstream codons than did those with low MAF. Besides, the high-MAF group better maintained both the signal peptide and reading frame. These differentiating elements could help to determine the pathogenicity of this kind of variation. Availability Data and scripts in Perl and R are freely available at https://github.com/fanavarro/hemodonacion Contact jfernand@um.es Supplementary information Supplementary data are available at Bioinformatics online. © The Author(s) (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

BioinformaticsOxford University Press

Published: Jun 1, 2018

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