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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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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. |
format | Online Article Text |
id | pubmed-7750997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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