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A generalized birth and death process for modeling the fates of gene duplication

BACKGROUND: Accurately estimating the timing and mode of gene duplications along the evolutionary history of species can provide invaluable information about underlying mechanisms by which the genomes of organisms evolved and the genes with novel functions arose. Mechanistic models have previously b...

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Autores principales: Zhao, Jing, Teufel, Ashley I., Liberles, David A., Liu, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4672517/
https://www.ncbi.nlm.nih.gov/pubmed/26643106
http://dx.doi.org/10.1186/s12862-015-0539-2
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author Zhao, Jing
Teufel, Ashley I.
Liberles, David A.
Liu, Liang
author_facet Zhao, Jing
Teufel, Ashley I.
Liberles, David A.
Liu, Liang
author_sort Zhao, Jing
collection PubMed
description BACKGROUND: Accurately estimating the timing and mode of gene duplications along the evolutionary history of species can provide invaluable information about underlying mechanisms by which the genomes of organisms evolved and the genes with novel functions arose. Mechanistic models have previously been introduced that allow for probabilistic inference of the evolutionary mechanism for duplicate gene retention based upon the average rate of loss over time of the duplicate. However, there is currently no probabilistic model embedded in a birth-death modeling framework that can take into account the effects of different evolutionary mechanisms of gene retention when analyzing gene family data. RESULTS: In this study, we describe a generalized birth-death process for modeling the fates of gene duplication. Use of mechanistic models in a phylogenetic framework requires an age-dependent birth-death process. Starting with a single population corresponding to the lineage of a phylogenetic tree and with an assumption of a clock that starts ticking for each duplicate at its birth, an age-dependent birth-death process is developed by extending the results from the time-dependent birth-death process. The implementation of such models in a full phylogenetic framework is expected to enable large scale probabilistic analysis of duplicates in comparative genomic studies. CONCLUSIONS: We develop an age-dependent birth-death model for understanding the mechanisms of gene retention, which allows a gene loss rate dependent on each duplication event. Simulation results indicate that different mechanisms of gene retentions produce distinct likelihood functions, which can be used with genomic data to quantitatively distinguish those mechanisms.
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spelling pubmed-46725172015-12-09 A generalized birth and death process for modeling the fates of gene duplication Zhao, Jing Teufel, Ashley I. Liberles, David A. Liu, Liang BMC Evol Biol Research Article BACKGROUND: Accurately estimating the timing and mode of gene duplications along the evolutionary history of species can provide invaluable information about underlying mechanisms by which the genomes of organisms evolved and the genes with novel functions arose. Mechanistic models have previously been introduced that allow for probabilistic inference of the evolutionary mechanism for duplicate gene retention based upon the average rate of loss over time of the duplicate. However, there is currently no probabilistic model embedded in a birth-death modeling framework that can take into account the effects of different evolutionary mechanisms of gene retention when analyzing gene family data. RESULTS: In this study, we describe a generalized birth-death process for modeling the fates of gene duplication. Use of mechanistic models in a phylogenetic framework requires an age-dependent birth-death process. Starting with a single population corresponding to the lineage of a phylogenetic tree and with an assumption of a clock that starts ticking for each duplicate at its birth, an age-dependent birth-death process is developed by extending the results from the time-dependent birth-death process. The implementation of such models in a full phylogenetic framework is expected to enable large scale probabilistic analysis of duplicates in comparative genomic studies. CONCLUSIONS: We develop an age-dependent birth-death model for understanding the mechanisms of gene retention, which allows a gene loss rate dependent on each duplication event. Simulation results indicate that different mechanisms of gene retentions produce distinct likelihood functions, which can be used with genomic data to quantitatively distinguish those mechanisms. BioMed Central 2015-12-08 /pmc/articles/PMC4672517/ /pubmed/26643106 http://dx.doi.org/10.1186/s12862-015-0539-2 Text en © Zhao et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhao, Jing
Teufel, Ashley I.
Liberles, David A.
Liu, Liang
A generalized birth and death process for modeling the fates of gene duplication
title A generalized birth and death process for modeling the fates of gene duplication
title_full A generalized birth and death process for modeling the fates of gene duplication
title_fullStr A generalized birth and death process for modeling the fates of gene duplication
title_full_unstemmed A generalized birth and death process for modeling the fates of gene duplication
title_short A generalized birth and death process for modeling the fates of gene duplication
title_sort generalized birth and death process for modeling the fates of gene duplication
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4672517/
https://www.ncbi.nlm.nih.gov/pubmed/26643106
http://dx.doi.org/10.1186/s12862-015-0539-2
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