A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification

Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under eleva...

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Published in:Evolutionary Applications
Main Authors: Malvezzi, Alex J., Murray, Christopher S., Feldheim, Kevin A., DiBattista, Joseph, Garant, Dany, Gobler, Christopher J., Chapman, Demian D., Baumann, Hannes
Other Authors: King Abdullah University of Science and Technology (KAUST), Red Sea Research Center (RSRC), School of Marine and Atmospheric Sciences; Stony Brook University; Stony Brook NY USA, Department of Marine Sciences; University of Connecticut; Groton CT USA, Pritzker Laboratory for Molecular Systematics and Evolution; Field Museum of Natural History; Chicago IL USA, Département de Biologie; Université de Sherbrooke; Sherbrooke QC Canada
Format: Article in Journal/Newspaper
Language:unknown
Published: Wiley 2015
Subjects:
Online Access:http://hdl.handle.net/10754/346797
https://doi.org/10.1111/eva.12248
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spelling ftkingabdullahun:oai:repository.kaust.edu.sa:10754/346797 2023-12-31T10:21:31+01:00 A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification Malvezzi, Alex J. Murray, Christopher S. Feldheim, Kevin A. DiBattista, Joseph Garant, Dany Gobler, Christopher J. Chapman, Demian D. Baumann, Hannes King Abdullah University of Science and Technology (KAUST) Red Sea Research Center (RSRC) School of Marine and Atmospheric Sciences; Stony Brook University; Stony Brook NY USA Department of Marine Sciences; University of Connecticut; Groton CT USA Pritzker Laboratory for Molecular Systematics and Evolution; Field Museum of Natural History; Chicago IL USA Département de Biologie; Université de Sherbrooke; Sherbrooke QC Canada 2015-02-13 application/pdf http://hdl.handle.net/10754/346797 https://doi.org/10.1111/eva.12248 unknown Wiley Malvezzi, A., Murray, C. S., Feldheim, K. A., DiBattista, J. D., Garant, D., Gobler, C. J., … Baumann, H. (2015). A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification [Data set]. PANGAEA - Data Publisher for Earth & Environmental Science. https://doi.org/10.1594/pangaea.848012 DOI:10.1594/PANGAEA.848012 HANDLE:http://hdl.handle.net/10754/624153 Malvezzi, A. J., Murray, C. S., Feldheim, K. A., DiBattista, J. D., Garant, D., Gobler, C. J., … Baumann, H. (2015). Data from: A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification (Version 1) [Data set]. Dryad Digital Repository. https://doi.org/10.5061/dryad.bd6vs DOI:10.5061/DRYAD.BD6VS HANDLE:http://hdl.handle.net/10754/624177 http://doi.wiley.com/10.1111/eva.12248 A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification 2015:n/a Evolutionary Applications doi:10.1111/eva.12248 17524571 Evolutionary Applications PMC4408146 25926880 http://hdl.handle.net/10754/346797 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Article 2015 ftkingabdullahun https://doi.org/10.1111/eva.1224810.1594/PANGAEA.84801210.5061/dryad.bd6vs10.5061/DRYAD.BD6VS 2023-12-02T20:22:08Z Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under elevated CO2 conditions in a metazoan. Specifically, we reared offspring, selected from a wild coastal fish population (Atlantic silverside, Menidia menidia), at high CO2 conditions (~2300 μatm) from fertilization to 15 days posthatch, which significantly reduced survival compared to controls. Perished and surviving offspring were quantitatively sampled and genotyped along with their parents, using eight polymorphic microsatellite loci, to reconstruct a parent-offspring pedigree and estimate variance components. Genetically related individuals were phenotypically more similar (i.e., survived similarly long at elevated CO2 conditions) than unrelated individuals, which translated into a significantly nonzero heritability (0.20 ± 0.07). The contribution of maternal effects was surprisingly small (0.05 ± 0.04) and nonsignificant. Survival among replicates was positively correlated with genetic diversity, particularly with observed heterozygosity. We conclude that early life survival of M. menidia under high CO2 levels has a significant additive genetic component that could elicit an evolutionary response to OA, depending on the strength and direction of future selection. Article in Journal/Newspaper Ocean acidification King Abdullah University of Science and Technology: KAUST Repository Evolutionary Applications 8 4 352 362
institution Open Polar
collection King Abdullah University of Science and Technology: KAUST Repository
op_collection_id ftkingabdullahun
language unknown
description Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under elevated CO2 conditions in a metazoan. Specifically, we reared offspring, selected from a wild coastal fish population (Atlantic silverside, Menidia menidia), at high CO2 conditions (~2300 μatm) from fertilization to 15 days posthatch, which significantly reduced survival compared to controls. Perished and surviving offspring were quantitatively sampled and genotyped along with their parents, using eight polymorphic microsatellite loci, to reconstruct a parent-offspring pedigree and estimate variance components. Genetically related individuals were phenotypically more similar (i.e., survived similarly long at elevated CO2 conditions) than unrelated individuals, which translated into a significantly nonzero heritability (0.20 ± 0.07). The contribution of maternal effects was surprisingly small (0.05 ± 0.04) and nonsignificant. Survival among replicates was positively correlated with genetic diversity, particularly with observed heterozygosity. We conclude that early life survival of M. menidia under high CO2 levels has a significant additive genetic component that could elicit an evolutionary response to OA, depending on the strength and direction of future selection.
author2 King Abdullah University of Science and Technology (KAUST)
Red Sea Research Center (RSRC)
School of Marine and Atmospheric Sciences; Stony Brook University; Stony Brook NY USA
Department of Marine Sciences; University of Connecticut; Groton CT USA
Pritzker Laboratory for Molecular Systematics and Evolution; Field Museum of Natural History; Chicago IL USA
Département de Biologie; Université de Sherbrooke; Sherbrooke QC Canada
format Article in Journal/Newspaper
author Malvezzi, Alex J.
Murray, Christopher S.
Feldheim, Kevin A.
DiBattista, Joseph
Garant, Dany
Gobler, Christopher J.
Chapman, Demian D.
Baumann, Hannes
spellingShingle Malvezzi, Alex J.
Murray, Christopher S.
Feldheim, Kevin A.
DiBattista, Joseph
Garant, Dany
Gobler, Christopher J.
Chapman, Demian D.
Baumann, Hannes
A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification
author_facet Malvezzi, Alex J.
Murray, Christopher S.
Feldheim, Kevin A.
DiBattista, Joseph
Garant, Dany
Gobler, Christopher J.
Chapman, Demian D.
Baumann, Hannes
author_sort Malvezzi, Alex J.
title A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification
title_short A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification
title_full A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification
title_fullStr A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification
title_full_unstemmed A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification
title_sort quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification
publisher Wiley
publishDate 2015
url http://hdl.handle.net/10754/346797
https://doi.org/10.1111/eva.12248
genre Ocean acidification
genre_facet Ocean acidification
op_relation Malvezzi, A., Murray, C. S., Feldheim, K. A., DiBattista, J. D., Garant, D., Gobler, C. J., … Baumann, H. (2015). A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification [Data set]. PANGAEA - Data Publisher for Earth & Environmental Science. https://doi.org/10.1594/pangaea.848012
DOI:10.1594/PANGAEA.848012
HANDLE:http://hdl.handle.net/10754/624153
Malvezzi, A. J., Murray, C. S., Feldheim, K. A., DiBattista, J. D., Garant, D., Gobler, C. J., … Baumann, H. (2015). Data from: A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification (Version 1) [Data set]. Dryad Digital Repository. https://doi.org/10.5061/dryad.bd6vs
DOI:10.5061/DRYAD.BD6VS
HANDLE:http://hdl.handle.net/10754/624177
http://doi.wiley.com/10.1111/eva.12248
A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification 2015:n/a Evolutionary Applications
doi:10.1111/eva.12248
17524571
Evolutionary Applications
PMC4408146
25926880
http://hdl.handle.net/10754/346797
op_rights This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
op_doi https://doi.org/10.1111/eva.1224810.1594/PANGAEA.84801210.5061/dryad.bd6vs10.5061/DRYAD.BD6VS
container_title Evolutionary Applications
container_volume 8
container_issue 4
container_start_page 352
op_container_end_page 362
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