Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)

Unravelling the factors shaping the genetic structure of mobile marine species is challenging due to the high potential for gene flow. However, genetic inference can be greatly enhanced by increasing the genomic, geographic or environmental resolution of population genetic studies. Here we investiga...

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Main Authors: Vandamme, S. G., Maes, G. E., Raeymaekers, J. A. M., Cottenie, K., Imsland, A. K., Hellemans, B., Lacroix, G., Mac Aoidh, E., Martinsohn, J. T., Martínez, P., Robbens, J., Vilas, R., Volckaert, F. A. M.
Language:unknown
Published: 2013
Subjects:
Online Access:http://nbn-resolving.org/urn:nbn:nl:ui:13-66-xtjm
https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:83108
id ftdans:oai:easy.dans.knaw.nl:easy-dataset:83108
record_format openpolar
spelling ftdans:oai:easy.dans.knaw.nl:easy-dataset:83108 2023-07-02T03:33:12+02:00 Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus) Vandamme, S. G. Maes, G. E. Raeymaekers, J. A. M. Cottenie, K. Imsland, A. K. Hellemans, B. Lacroix, G. Mac Aoidh, E. Martinsohn, J. T. Martínez, P. Robbens, J. Vilas, R. Volckaert, F. A. M. 2013-12-10T18:50:04.000+01:00 http://nbn-resolving.org/urn:nbn:nl:ui:13-66-xtjm https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:83108 unknown doi:10.5061/dryad.21k5t/1 doi:10.1111/mec.12628 PMID:24354713 http://nbn-resolving.org/urn:nbn:nl:ui:13-66-xtjm doi:10.5061/dryad.21k5t https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:83108 OPEN_ACCESS: The data are archived in Easy, they are accessible elsewhere through the DOI https://dans.knaw.nl/en/about/organisation-and-policy/legal-information/DANSLicence.pdf Life sciences medicine and health care 2013 ftdans https://doi.org/10.5061/dryad.21k5t/110.1111/mec.1262810.5061/dryad.21k5t 2023-06-13T13:07:43Z Unravelling the factors shaping the genetic structure of mobile marine species is challenging due to the high potential for gene flow. However, genetic inference can be greatly enhanced by increasing the genomic, geographic or environmental resolution of population genetic studies. Here we investigated the population structure of turbot (Scophthalmus maximus) by screening 17 random and gene-linked markers in 999 individuals at 290 geographical locations throughout the Northeast Atlantic Ocean. A seascape genetics approach with the inclusion of high resolution oceanographic data was used to quantify the association of genetic variation with spatial, temporal and environmental parameters. Neutral loci identified three subgroups: an Atlantic group, a Baltic Sea group and one on the Irish Shelf. The inclusion of loci putatively under selection suggested an additional break in the North Sea, subdividing southern from northern Atlantic individuals. Environmental and spatial seascape variables correlated marginally with neutral genetic variation, but explained significant proportions (respectively 8.7 % and 10.3 %) of adaptive genetic variation. Environmental variables associated with outlier allele frequencies included salinity, temperature, bottom shear stress, dissolved oxygen concentration and depth of the pycnocline. Furthermore, levels of explained adaptive genetic variation differed markedly among basins (3% vs 12% in the North and Baltic Sea, respectively). We suggest that stable environmental selection pressure contributes to relatively strong local adaptation in the Baltic Sea. Our seascape genetic approach using a large number of sampling locations and associated oceanographic data proved useful for the identification of population units as the basis of management decisions. Other/Unknown Material Northeast Atlantic Scophthalmus maximus Turbot Data Archiving and Networked Services (DANS): EASY (KNAW - Koninklijke Nederlandse Akademie van Wetenschappen)
institution Open Polar
collection Data Archiving and Networked Services (DANS): EASY (KNAW - Koninklijke Nederlandse Akademie van Wetenschappen)
op_collection_id ftdans
language unknown
topic Life sciences
medicine and health care
spellingShingle Life sciences
medicine and health care
Vandamme, S. G.
Maes, G. E.
Raeymaekers, J. A. M.
Cottenie, K.
Imsland, A. K.
Hellemans, B.
Lacroix, G.
Mac Aoidh, E.
Martinsohn, J. T.
Martínez, P.
Robbens, J.
Vilas, R.
Volckaert, F. A. M.
Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
topic_facet Life sciences
medicine and health care
description Unravelling the factors shaping the genetic structure of mobile marine species is challenging due to the high potential for gene flow. However, genetic inference can be greatly enhanced by increasing the genomic, geographic or environmental resolution of population genetic studies. Here we investigated the population structure of turbot (Scophthalmus maximus) by screening 17 random and gene-linked markers in 999 individuals at 290 geographical locations throughout the Northeast Atlantic Ocean. A seascape genetics approach with the inclusion of high resolution oceanographic data was used to quantify the association of genetic variation with spatial, temporal and environmental parameters. Neutral loci identified three subgroups: an Atlantic group, a Baltic Sea group and one on the Irish Shelf. The inclusion of loci putatively under selection suggested an additional break in the North Sea, subdividing southern from northern Atlantic individuals. Environmental and spatial seascape variables correlated marginally with neutral genetic variation, but explained significant proportions (respectively 8.7 % and 10.3 %) of adaptive genetic variation. Environmental variables associated with outlier allele frequencies included salinity, temperature, bottom shear stress, dissolved oxygen concentration and depth of the pycnocline. Furthermore, levels of explained adaptive genetic variation differed markedly among basins (3% vs 12% in the North and Baltic Sea, respectively). We suggest that stable environmental selection pressure contributes to relatively strong local adaptation in the Baltic Sea. Our seascape genetic approach using a large number of sampling locations and associated oceanographic data proved useful for the identification of population units as the basis of management decisions.
author Vandamme, S. G.
Maes, G. E.
Raeymaekers, J. A. M.
Cottenie, K.
Imsland, A. K.
Hellemans, B.
Lacroix, G.
Mac Aoidh, E.
Martinsohn, J. T.
Martínez, P.
Robbens, J.
Vilas, R.
Volckaert, F. A. M.
author_facet Vandamme, S. G.
Maes, G. E.
Raeymaekers, J. A. M.
Cottenie, K.
Imsland, A. K.
Hellemans, B.
Lacroix, G.
Mac Aoidh, E.
Martinsohn, J. T.
Martínez, P.
Robbens, J.
Vilas, R.
Volckaert, F. A. M.
author_sort Vandamme, S. G.
title Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
title_short Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
title_full Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
title_fullStr Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
title_full_unstemmed Data from: Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
title_sort data from: regional environmental pressure influences population differentiation in turbot (scophthalmus maximus)
publishDate 2013
url http://nbn-resolving.org/urn:nbn:nl:ui:13-66-xtjm
https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:83108
genre Northeast Atlantic
Scophthalmus maximus
Turbot
genre_facet Northeast Atlantic
Scophthalmus maximus
Turbot
op_relation doi:10.5061/dryad.21k5t/1
doi:10.1111/mec.12628
PMID:24354713
http://nbn-resolving.org/urn:nbn:nl:ui:13-66-xtjm
doi:10.5061/dryad.21k5t
https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:83108
op_rights OPEN_ACCESS: The data are archived in Easy, they are accessible elsewhere through the DOI
https://dans.knaw.nl/en/about/organisation-and-policy/legal-information/DANSLicence.pdf
op_doi https://doi.org/10.5061/dryad.21k5t/110.1111/mec.1262810.5061/dryad.21k5t
_version_ 1770273056410828800