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Multifactorial genetic divergence processes drive the onset of speciation in an Amazonian fish

Understanding the processes that drive population genetic divergence in the Amazon is challenging because of the vast scale, the environmental richness and the outstanding biodiversity of the region. We addressed this issue by determining the genetic structure of the widespread Amazonian common sard...

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Autores principales: Jardim de Queiroz, Luiz, Torrente-Vilara, Gislene, Quilodran, Claudio, Rodrigues da Costa Doria, Carolina, Montoya-Burgos, Juan I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5738069/
https://www.ncbi.nlm.nih.gov/pubmed/29261722
http://dx.doi.org/10.1371/journal.pone.0189349
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author Jardim de Queiroz, Luiz
Torrente-Vilara, Gislene
Quilodran, Claudio
Rodrigues da Costa Doria, Carolina
Montoya-Burgos, Juan I.
author_facet Jardim de Queiroz, Luiz
Torrente-Vilara, Gislene
Quilodran, Claudio
Rodrigues da Costa Doria, Carolina
Montoya-Burgos, Juan I.
author_sort Jardim de Queiroz, Luiz
collection PubMed
description Understanding the processes that drive population genetic divergence in the Amazon is challenging because of the vast scale, the environmental richness and the outstanding biodiversity of the region. We addressed this issue by determining the genetic structure of the widespread Amazonian common sardine fish Triportheus albus (Characidae). We then examined the influence, on this species, of all previously proposed population-structuring factors, including isolation-by-distance, isolation-by-barrier (the Teotônio Falls) and isolation-by-environment using variables that describe floodplain and water characteristics. The population genetics analyses revealed an unusually strong structure with three geographical groups: Negro/Tapajós rivers, Lower Madeira/Central Amazon, and Upper Madeira. Distance-based redundancy analyses showed that the optimal model for explaining the extreme genetic structure contains all proposed structuring factors and accounts for up to 70% of the genetic structure. We further quantified the contribution of each factor via a variance-partitioning analysis. Our results demonstrate that multiple factors, often proposed as individual drivers of population divergence, have acted in conjunction to divide T. albus into three genetic lineages. Because the conjunction of multiple long-standing population-structuring processes may lead to population reproductive isolation, that is, the onset of speciation, we suggest that the multifactorial population-structuring processes highlighted in this study could account for the high speciation rate characterising the Amazon Basin.
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spelling pubmed-57380692017-12-29 Multifactorial genetic divergence processes drive the onset of speciation in an Amazonian fish Jardim de Queiroz, Luiz Torrente-Vilara, Gislene Quilodran, Claudio Rodrigues da Costa Doria, Carolina Montoya-Burgos, Juan I. PLoS One Research Article Understanding the processes that drive population genetic divergence in the Amazon is challenging because of the vast scale, the environmental richness and the outstanding biodiversity of the region. We addressed this issue by determining the genetic structure of the widespread Amazonian common sardine fish Triportheus albus (Characidae). We then examined the influence, on this species, of all previously proposed population-structuring factors, including isolation-by-distance, isolation-by-barrier (the Teotônio Falls) and isolation-by-environment using variables that describe floodplain and water characteristics. The population genetics analyses revealed an unusually strong structure with three geographical groups: Negro/Tapajós rivers, Lower Madeira/Central Amazon, and Upper Madeira. Distance-based redundancy analyses showed that the optimal model for explaining the extreme genetic structure contains all proposed structuring factors and accounts for up to 70% of the genetic structure. We further quantified the contribution of each factor via a variance-partitioning analysis. Our results demonstrate that multiple factors, often proposed as individual drivers of population divergence, have acted in conjunction to divide T. albus into three genetic lineages. Because the conjunction of multiple long-standing population-structuring processes may lead to population reproductive isolation, that is, the onset of speciation, we suggest that the multifactorial population-structuring processes highlighted in this study could account for the high speciation rate characterising the Amazon Basin. Public Library of Science 2017-12-20 /pmc/articles/PMC5738069/ /pubmed/29261722 http://dx.doi.org/10.1371/journal.pone.0189349 Text en © 2017 Jardim de Queiroz et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Jardim de Queiroz, Luiz
Torrente-Vilara, Gislene
Quilodran, Claudio
Rodrigues da Costa Doria, Carolina
Montoya-Burgos, Juan I.
Multifactorial genetic divergence processes drive the onset of speciation in an Amazonian fish
title Multifactorial genetic divergence processes drive the onset of speciation in an Amazonian fish
title_full Multifactorial genetic divergence processes drive the onset of speciation in an Amazonian fish
title_fullStr Multifactorial genetic divergence processes drive the onset of speciation in an Amazonian fish
title_full_unstemmed Multifactorial genetic divergence processes drive the onset of speciation in an Amazonian fish
title_short Multifactorial genetic divergence processes drive the onset of speciation in an Amazonian fish
title_sort multifactorial genetic divergence processes drive the onset of speciation in an amazonian fish
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5738069/
https://www.ncbi.nlm.nih.gov/pubmed/29261722
http://dx.doi.org/10.1371/journal.pone.0189349
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