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Multivariate analysis of genomic variables, effective population size, and mutation rate

OBJECTIVE: The relationship between genomic variables (genome size, gene number, intron size, and intron number) and evolutionary forces has two implications. First, they help to unravel the mechanism underlying genome evolution. Second, they provide a solution to the debate over discrepancy between...

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Autores principales: Bhattachan, Punit, Dong, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347809/
https://www.ncbi.nlm.nih.gov/pubmed/30683153
http://dx.doi.org/10.1186/s13104-019-4097-3
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author Bhattachan, Punit
Dong, Bo
author_facet Bhattachan, Punit
Dong, Bo
author_sort Bhattachan, Punit
collection PubMed
description OBJECTIVE: The relationship between genomic variables (genome size, gene number, intron size, and intron number) and evolutionary forces has two implications. First, they help to unravel the mechanism underlying genome evolution. Second, they provide a solution to the debate over discrepancy between genome size variation and organismal complexity. Previously, a clear correlation between genomic variables and effective population size and mutation rate (Neu) led to an important hypothesis to consider random genetic drift as a major evolutionary force during evolution of genome size and complexity. But recent reports also support natural selection as the leading evolutionary force. As such, the debate remains unresolved. RESULTS: Here, we used a multivariate method to explore the relationship between genomic variables and Neu in order to understand the evolution of genome. Previously reported patterns between genomic variables and Neu were not observed in our multivariate study. We found only one association between intron number and Neu, but no relationships were observed between genome size, intron size, gene number, and Neu, suggesting that Neu of the organisms solely does not influence genome evolution. We, therefore, concluded that Neu influences intron evolution, while it may not be the only force that provides mechanistic insights into genome evolution and complexity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-019-4097-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-63478092019-01-30 Multivariate analysis of genomic variables, effective population size, and mutation rate Bhattachan, Punit Dong, Bo BMC Res Notes Research Note OBJECTIVE: The relationship between genomic variables (genome size, gene number, intron size, and intron number) and evolutionary forces has two implications. First, they help to unravel the mechanism underlying genome evolution. Second, they provide a solution to the debate over discrepancy between genome size variation and organismal complexity. Previously, a clear correlation between genomic variables and effective population size and mutation rate (Neu) led to an important hypothesis to consider random genetic drift as a major evolutionary force during evolution of genome size and complexity. But recent reports also support natural selection as the leading evolutionary force. As such, the debate remains unresolved. RESULTS: Here, we used a multivariate method to explore the relationship between genomic variables and Neu in order to understand the evolution of genome. Previously reported patterns between genomic variables and Neu were not observed in our multivariate study. We found only one association between intron number and Neu, but no relationships were observed between genome size, intron size, gene number, and Neu, suggesting that Neu of the organisms solely does not influence genome evolution. We, therefore, concluded that Neu influences intron evolution, while it may not be the only force that provides mechanistic insights into genome evolution and complexity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-019-4097-3) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-25 /pmc/articles/PMC6347809/ /pubmed/30683153 http://dx.doi.org/10.1186/s13104-019-4097-3 Text en © The Author(s) 2019 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 Note
Bhattachan, Punit
Dong, Bo
Multivariate analysis of genomic variables, effective population size, and mutation rate
title Multivariate analysis of genomic variables, effective population size, and mutation rate
title_full Multivariate analysis of genomic variables, effective population size, and mutation rate
title_fullStr Multivariate analysis of genomic variables, effective population size, and mutation rate
title_full_unstemmed Multivariate analysis of genomic variables, effective population size, and mutation rate
title_short Multivariate analysis of genomic variables, effective population size, and mutation rate
title_sort multivariate analysis of genomic variables, effective population size, and mutation rate
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347809/
https://www.ncbi.nlm.nih.gov/pubmed/30683153
http://dx.doi.org/10.1186/s13104-019-4097-3
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