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A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome

Retrotransposons, DNA sequences capable of creating copies of themselves, compose about half of the human genome and played a central role in the evolution of mammals. Their current position in the host genome is the result of the retrotranscription process and of the following host genome evolution...

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Detalles Bibliográficos
Autores principales: Riba, Andrea, Fumagalli, Maria Rita, Caselle, Michele, Osella, Matteo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750997/
https://www.ncbi.nlm.nih.gov/pubmed/32986810
http://dx.doi.org/10.1093/gbe/evaa201
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author Riba, Andrea
Fumagalli, Maria Rita
Caselle, Michele
Osella, Matteo
author_facet Riba, Andrea
Fumagalli, Maria Rita
Caselle, Michele
Osella, Matteo
author_sort Riba, Andrea
collection PubMed
description Retrotransposons, DNA sequences capable of creating copies of themselves, compose about half of the human genome and played a central role in the evolution of mammals. Their current position in the host genome is the result of the retrotranscription process and of the following host genome evolution. We apply a model from statistical physics to show that the genomic distribution of the two most populated classes of retrotransposons in human deviates from random placement, and that this deviation increases with time. The time dependence suggests a major role of the host genome dynamics in shaping the current retrotransposon distributions. Focusing on a neutral scenario, we show that a simple model based on random placement followed by genome expansion and sequence duplications can reproduce the empirical retrotransposon distributions, even though more complex and possibly selective mechanisms can have contributed. Besides the inherent interest in understanding the origin of current retrotransposon distributions, this work sets a general analytical framework to analyze quantitatively the effects of genome evolutionary dynamics on the distribution of genomic elements.
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spelling pubmed-77509972020-12-28 A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome Riba, Andrea Fumagalli, Maria Rita Caselle, Michele Osella, Matteo Genome Biol Evol Research Article Retrotransposons, DNA sequences capable of creating copies of themselves, compose about half of the human genome and played a central role in the evolution of mammals. Their current position in the host genome is the result of the retrotranscription process and of the following host genome evolution. We apply a model from statistical physics to show that the genomic distribution of the two most populated classes of retrotransposons in human deviates from random placement, and that this deviation increases with time. The time dependence suggests a major role of the host genome dynamics in shaping the current retrotransposon distributions. Focusing on a neutral scenario, we show that a simple model based on random placement followed by genome expansion and sequence duplications can reproduce the empirical retrotransposon distributions, even though more complex and possibly selective mechanisms can have contributed. Besides the inherent interest in understanding the origin of current retrotransposon distributions, this work sets a general analytical framework to analyze quantitatively the effects of genome evolutionary dynamics on the distribution of genomic elements. Oxford University Press 2020-09-28 /pmc/articles/PMC7750997/ /pubmed/32986810 http://dx.doi.org/10.1093/gbe/evaa201 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research Article
Riba, Andrea
Fumagalli, Maria Rita
Caselle, Michele
Osella, Matteo
A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome
title A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome
title_full A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome
title_fullStr A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome
title_full_unstemmed A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome
title_short A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome
title_sort model-driven quantitative analysis of retrotransposon distributions in the human genome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750997/
https://www.ncbi.nlm.nih.gov/pubmed/32986810
http://dx.doi.org/10.1093/gbe/evaa201
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