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Analytical Biases Associated with GC-Content in Molecular Evolution
Molecular evolution is being revolutionized by high-throughput sequencing allowing an increased amount of genome-wide data available for multiple species. While base composition summarized by GC-content is one of the first metrics measured in genomes, its genomic distribution is a frequently neglect...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309256/ https://www.ncbi.nlm.nih.gov/pubmed/28261263 http://dx.doi.org/10.3389/fgene.2017.00016 |
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author | Romiguier, Jonathan Roux, Camille |
author_facet | Romiguier, Jonathan Roux, Camille |
author_sort | Romiguier, Jonathan |
collection | PubMed |
description | Molecular evolution is being revolutionized by high-throughput sequencing allowing an increased amount of genome-wide data available for multiple species. While base composition summarized by GC-content is one of the first metrics measured in genomes, its genomic distribution is a frequently neglected feature in downstream analyses based on DNA sequence comparisons. Here, we show how base composition heterogeneity among loci and taxa can bias common molecular evolution analyses such as phylogenetic tree reconstruction, detection of natural selection and estimation of codon usage. We then discuss the biological, technical and methodological causes of these GC-associated biases and suggest approaches to overcome them. |
format | Online Article Text |
id | pubmed-5309256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-53092562017-03-03 Analytical Biases Associated with GC-Content in Molecular Evolution Romiguier, Jonathan Roux, Camille Front Genet Genetics Molecular evolution is being revolutionized by high-throughput sequencing allowing an increased amount of genome-wide data available for multiple species. While base composition summarized by GC-content is one of the first metrics measured in genomes, its genomic distribution is a frequently neglected feature in downstream analyses based on DNA sequence comparisons. Here, we show how base composition heterogeneity among loci and taxa can bias common molecular evolution analyses such as phylogenetic tree reconstruction, detection of natural selection and estimation of codon usage. We then discuss the biological, technical and methodological causes of these GC-associated biases and suggest approaches to overcome them. Frontiers Media S.A. 2017-02-15 /pmc/articles/PMC5309256/ /pubmed/28261263 http://dx.doi.org/10.3389/fgene.2017.00016 Text en Copyright © 2017 Romiguier and Roux. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Romiguier, Jonathan Roux, Camille Analytical Biases Associated with GC-Content in Molecular Evolution |
title | Analytical Biases Associated with GC-Content in Molecular Evolution |
title_full | Analytical Biases Associated with GC-Content in Molecular Evolution |
title_fullStr | Analytical Biases Associated with GC-Content in Molecular Evolution |
title_full_unstemmed | Analytical Biases Associated with GC-Content in Molecular Evolution |
title_short | Analytical Biases Associated with GC-Content in Molecular Evolution |
title_sort | analytical biases associated with gc-content in molecular evolution |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309256/ https://www.ncbi.nlm.nih.gov/pubmed/28261263 http://dx.doi.org/10.3389/fgene.2017.00016 |
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