Cargando…

ALF—A Simulation Framework for Genome Evolution

In computational evolutionary biology, verification and benchmarking is a challenging task because the evolutionary history of studied biological entities is usually not known. Computer programs for simulating sequence evolution in silico have shown to be viable test beds for the verification of new...

Descripción completa

Detalles Bibliográficos
Autores principales: Dalquen, Daniel A., Anisimova, Maria, Gonnet, Gaston H., Dessimoz, Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3341827/
https://www.ncbi.nlm.nih.gov/pubmed/22160766
http://dx.doi.org/10.1093/molbev/msr268
_version_ 1782231592412905472
author Dalquen, Daniel A.
Anisimova, Maria
Gonnet, Gaston H.
Dessimoz, Christophe
author_facet Dalquen, Daniel A.
Anisimova, Maria
Gonnet, Gaston H.
Dessimoz, Christophe
author_sort Dalquen, Daniel A.
collection PubMed
description In computational evolutionary biology, verification and benchmarking is a challenging task because the evolutionary history of studied biological entities is usually not known. Computer programs for simulating sequence evolution in silico have shown to be viable test beds for the verification of newly developed methods and to compare different algorithms. However, current simulation packages tend to focus either on gene-level aspects of genome evolution such as character substitutions and insertions and deletions (indels) or on genome-level aspects such as genome rearrangement and speciation events. Here, we introduce Artificial Life Framework (ALF), which aims at simulating the entire range of evolutionary forces that act on genomes: nucleotide, codon, or amino acid substitution (under simple or mixture models), indels, GC-content amelioration, gene duplication, gene loss, gene fusion, gene fission, genome rearrangement, lateral gene transfer (LGT), or speciation. The other distinctive feature of ALF is its user-friendly yet powerful web interface. We illustrate the utility of ALF with two possible applications: 1) we reanalyze data from a study of selection after globin gene duplication and test the statistical significance of the original conclusions and 2) we demonstrate that LGT can dramatically decrease the accuracy of two well-established orthology inference methods. ALF is available as a stand-alone application or via a web interface at http://www.cbrg.ethz.ch/alf.
format Online
Article
Text
id pubmed-3341827
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-33418272012-05-02 ALF—A Simulation Framework for Genome Evolution Dalquen, Daniel A. Anisimova, Maria Gonnet, Gaston H. Dessimoz, Christophe Mol Biol Evol Research Article In computational evolutionary biology, verification and benchmarking is a challenging task because the evolutionary history of studied biological entities is usually not known. Computer programs for simulating sequence evolution in silico have shown to be viable test beds for the verification of newly developed methods and to compare different algorithms. However, current simulation packages tend to focus either on gene-level aspects of genome evolution such as character substitutions and insertions and deletions (indels) or on genome-level aspects such as genome rearrangement and speciation events. Here, we introduce Artificial Life Framework (ALF), which aims at simulating the entire range of evolutionary forces that act on genomes: nucleotide, codon, or amino acid substitution (under simple or mixture models), indels, GC-content amelioration, gene duplication, gene loss, gene fusion, gene fission, genome rearrangement, lateral gene transfer (LGT), or speciation. The other distinctive feature of ALF is its user-friendly yet powerful web interface. We illustrate the utility of ALF with two possible applications: 1) we reanalyze data from a study of selection after globin gene duplication and test the statistical significance of the original conclusions and 2) we demonstrate that LGT can dramatically decrease the accuracy of two well-established orthology inference methods. ALF is available as a stand-alone application or via a web interface at http://www.cbrg.ethz.ch/alf. Oxford University Press 2012-04 2011-12-08 /pmc/articles/PMC3341827/ /pubmed/22160766 http://dx.doi.org/10.1093/molbev/msr268 Text en © The Author(s) 2011. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Dalquen, Daniel A.
Anisimova, Maria
Gonnet, Gaston H.
Dessimoz, Christophe
ALF—A Simulation Framework for Genome Evolution
title ALF—A Simulation Framework for Genome Evolution
title_full ALF—A Simulation Framework for Genome Evolution
title_fullStr ALF—A Simulation Framework for Genome Evolution
title_full_unstemmed ALF—A Simulation Framework for Genome Evolution
title_short ALF—A Simulation Framework for Genome Evolution
title_sort alf—a simulation framework for genome evolution
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3341827/
https://www.ncbi.nlm.nih.gov/pubmed/22160766
http://dx.doi.org/10.1093/molbev/msr268
work_keys_str_mv AT dalquendaniela alfasimulationframeworkforgenomeevolution
AT anisimovamaria alfasimulationframeworkforgenomeevolution
AT gonnetgastonh alfasimulationframeworkforgenomeevolution
AT dessimozchristophe alfasimulationframeworkforgenomeevolution