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Geographic Life History Differences Predict Genomic Divergence Better than Mitochondrial Barcodes or Phenotype

Species diversity can be inferred using multiple data types, however, results based on genetic data can be at odds with patterns of phenotypic variation. Tiger beetles of the Cicindelidia politula (LeConte, 1875) species complex have been taxonomically problematic due to extreme phenotypic variation...

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Autores principales: Duran, Daniel P., Laroche, Robert A., Gough, Harlan M., Gwiazdowski, Rodger A., Knisley, Charles B., Herrmann, David P., Roman, Stephen J., Egan, Scott P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140875/
https://www.ncbi.nlm.nih.gov/pubmed/32121321
http://dx.doi.org/10.3390/genes11030265
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author Duran, Daniel P.
Laroche, Robert A.
Gough, Harlan M.
Gwiazdowski, Rodger A.
Knisley, Charles B.
Herrmann, David P.
Roman, Stephen J.
Egan, Scott P.
author_facet Duran, Daniel P.
Laroche, Robert A.
Gough, Harlan M.
Gwiazdowski, Rodger A.
Knisley, Charles B.
Herrmann, David P.
Roman, Stephen J.
Egan, Scott P.
author_sort Duran, Daniel P.
collection PubMed
description Species diversity can be inferred using multiple data types, however, results based on genetic data can be at odds with patterns of phenotypic variation. Tiger beetles of the Cicindelidia politula (LeConte, 1875) species complex have been taxonomically problematic due to extreme phenotypic variation within and between populations. To better understand the biology and taxonomy of this group, we used mtDNA genealogies and multilocus nuclear analyses of 34,921 SNPs to elucidate its evolutionary history and evaluate the validity of phenotypically circumscribed species and subspecies. Genetic analyses recovered two divergent species that are also ecologically distinct, based on adult life history. These patterns are incongruous with the phenotypic variation that informed prior taxonomy, and most subspecies were not supported as distinct evolutionary lineages. One of the nominal subspecies was found to be a cryptic species; consequently, we elevate C. p. laetipennis (Horn, 1913) to a full species. Although nuclear and mtDNA datasets recovered broadly similar evolutionary units, mito-nuclear discordance was more common than expected, being observed between nearly all geographically overlapping taxonomic pairs. Additionally, a pattern of ‘mitochondrial displacement’ was observed, where mitochondria from one species unidirectionally displace others. Overall, we found that geographically associated life history factors better predict genomic divergence than phenotype and mitochondrial genealogies, and consequently taxon identifications based on mtDNA (e.g., DNA barcodes) may be misleading.
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spelling pubmed-71408752020-04-10 Geographic Life History Differences Predict Genomic Divergence Better than Mitochondrial Barcodes or Phenotype Duran, Daniel P. Laroche, Robert A. Gough, Harlan M. Gwiazdowski, Rodger A. Knisley, Charles B. Herrmann, David P. Roman, Stephen J. Egan, Scott P. Genes (Basel) Article Species diversity can be inferred using multiple data types, however, results based on genetic data can be at odds with patterns of phenotypic variation. Tiger beetles of the Cicindelidia politula (LeConte, 1875) species complex have been taxonomically problematic due to extreme phenotypic variation within and between populations. To better understand the biology and taxonomy of this group, we used mtDNA genealogies and multilocus nuclear analyses of 34,921 SNPs to elucidate its evolutionary history and evaluate the validity of phenotypically circumscribed species and subspecies. Genetic analyses recovered two divergent species that are also ecologically distinct, based on adult life history. These patterns are incongruous with the phenotypic variation that informed prior taxonomy, and most subspecies were not supported as distinct evolutionary lineages. One of the nominal subspecies was found to be a cryptic species; consequently, we elevate C. p. laetipennis (Horn, 1913) to a full species. Although nuclear and mtDNA datasets recovered broadly similar evolutionary units, mito-nuclear discordance was more common than expected, being observed between nearly all geographically overlapping taxonomic pairs. Additionally, a pattern of ‘mitochondrial displacement’ was observed, where mitochondria from one species unidirectionally displace others. Overall, we found that geographically associated life history factors better predict genomic divergence than phenotype and mitochondrial genealogies, and consequently taxon identifications based on mtDNA (e.g., DNA barcodes) may be misleading. MDPI 2020-02-29 /pmc/articles/PMC7140875/ /pubmed/32121321 http://dx.doi.org/10.3390/genes11030265 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Duran, Daniel P.
Laroche, Robert A.
Gough, Harlan M.
Gwiazdowski, Rodger A.
Knisley, Charles B.
Herrmann, David P.
Roman, Stephen J.
Egan, Scott P.
Geographic Life History Differences Predict Genomic Divergence Better than Mitochondrial Barcodes or Phenotype
title Geographic Life History Differences Predict Genomic Divergence Better than Mitochondrial Barcodes or Phenotype
title_full Geographic Life History Differences Predict Genomic Divergence Better than Mitochondrial Barcodes or Phenotype
title_fullStr Geographic Life History Differences Predict Genomic Divergence Better than Mitochondrial Barcodes or Phenotype
title_full_unstemmed Geographic Life History Differences Predict Genomic Divergence Better than Mitochondrial Barcodes or Phenotype
title_short Geographic Life History Differences Predict Genomic Divergence Better than Mitochondrial Barcodes or Phenotype
title_sort geographic life history differences predict genomic divergence better than mitochondrial barcodes or phenotype
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140875/
https://www.ncbi.nlm.nih.gov/pubmed/32121321
http://dx.doi.org/10.3390/genes11030265
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