Cargando…

Population genetics provides new insights into biomarker prevalence in dab (Limanda limanda L.): a key marine biomonitoring species

Bioindicators are species for which some quantifiable aspect of its biology, a biomarker, is assumed to be sensitive to ecosystem health. However, there is frequently a lack of information on the underlying genetic and environmental drivers shaping the spatiotemporal variance in prevalence of the bi...

Descripción completa

Detalles Bibliográficos
Autores principales: Tysklind, Niklas, Taylor, Martin I, Lyons, Brett P, Goodsir, Freya, McCarthy, Ian D, Carvalho, Gary R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3779091/
https://www.ncbi.nlm.nih.gov/pubmed/24062799
http://dx.doi.org/10.1111/eva.12074
_version_ 1782285196688621568
author Tysklind, Niklas
Taylor, Martin I
Lyons, Brett P
Goodsir, Freya
McCarthy, Ian D
Carvalho, Gary R
author_facet Tysklind, Niklas
Taylor, Martin I
Lyons, Brett P
Goodsir, Freya
McCarthy, Ian D
Carvalho, Gary R
author_sort Tysklind, Niklas
collection PubMed
description Bioindicators are species for which some quantifiable aspect of its biology, a biomarker, is assumed to be sensitive to ecosystem health. However, there is frequently a lack of information on the underlying genetic and environmental drivers shaping the spatiotemporal variance in prevalence of the biomarkers employed. Here, we explore the relative role of potential variables influencing the spatiotemporal prevalence of biomarkers in dab, Limanda limanda, a species used as a bioindicator of marine contaminants. Firstly, the spatiotemporal genetic structure of dab around UK waters (39 samples across 15 sites for four years: 2005–2008) is evaluated with 16 microsatellites. Two temporally stable groups are identified corresponding to the North and Irish Seas (average between basin [Image: see text] = 0.007; [Image: see text] = 0.022). Secondly, we examine the association between biomarker prevalence and several variables, including genetic structuring, age and contaminant exposure. Genetic structure had significant interactive effects, together with age and some contaminants, in the prevalence of some of the biomarkers considered, namely hyperpigmentation and liver lesions. The integration of these data sets enhanced our understanding of the relationship between biomarker prevalence, exposure to contaminants and population-specific response, thereby yielding more informative predictive models of response and prospects for environmental remediation.
format Online
Article
Text
id pubmed-3779091
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Blackwell Publishing Ltd
record_format MEDLINE/PubMed
spelling pubmed-37790912013-09-23 Population genetics provides new insights into biomarker prevalence in dab (Limanda limanda L.): a key marine biomonitoring species Tysklind, Niklas Taylor, Martin I Lyons, Brett P Goodsir, Freya McCarthy, Ian D Carvalho, Gary R Evol Appl Original Articles Bioindicators are species for which some quantifiable aspect of its biology, a biomarker, is assumed to be sensitive to ecosystem health. However, there is frequently a lack of information on the underlying genetic and environmental drivers shaping the spatiotemporal variance in prevalence of the biomarkers employed. Here, we explore the relative role of potential variables influencing the spatiotemporal prevalence of biomarkers in dab, Limanda limanda, a species used as a bioindicator of marine contaminants. Firstly, the spatiotemporal genetic structure of dab around UK waters (39 samples across 15 sites for four years: 2005–2008) is evaluated with 16 microsatellites. Two temporally stable groups are identified corresponding to the North and Irish Seas (average between basin [Image: see text] = 0.007; [Image: see text] = 0.022). Secondly, we examine the association between biomarker prevalence and several variables, including genetic structuring, age and contaminant exposure. Genetic structure had significant interactive effects, together with age and some contaminants, in the prevalence of some of the biomarkers considered, namely hyperpigmentation and liver lesions. The integration of these data sets enhanced our understanding of the relationship between biomarker prevalence, exposure to contaminants and population-specific response, thereby yielding more informative predictive models of response and prospects for environmental remediation. Blackwell Publishing Ltd 2013-09 2013-05-23 /pmc/articles/PMC3779091/ /pubmed/24062799 http://dx.doi.org/10.1111/eva.12074 Text en © 2013 The Authors. Published by Blackwell Publishing Ltd http://creativecommons.org/licenses/by/2.5/ Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.
spellingShingle Original Articles
Tysklind, Niklas
Taylor, Martin I
Lyons, Brett P
Goodsir, Freya
McCarthy, Ian D
Carvalho, Gary R
Population genetics provides new insights into biomarker prevalence in dab (Limanda limanda L.): a key marine biomonitoring species
title Population genetics provides new insights into biomarker prevalence in dab (Limanda limanda L.): a key marine biomonitoring species
title_full Population genetics provides new insights into biomarker prevalence in dab (Limanda limanda L.): a key marine biomonitoring species
title_fullStr Population genetics provides new insights into biomarker prevalence in dab (Limanda limanda L.): a key marine biomonitoring species
title_full_unstemmed Population genetics provides new insights into biomarker prevalence in dab (Limanda limanda L.): a key marine biomonitoring species
title_short Population genetics provides new insights into biomarker prevalence in dab (Limanda limanda L.): a key marine biomonitoring species
title_sort population genetics provides new insights into biomarker prevalence in dab (limanda limanda l.): a key marine biomonitoring species
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3779091/
https://www.ncbi.nlm.nih.gov/pubmed/24062799
http://dx.doi.org/10.1111/eva.12074
work_keys_str_mv AT tysklindniklas populationgeneticsprovidesnewinsightsintobiomarkerprevalenceindablimandalimandalakeymarinebiomonitoringspecies
AT taylormartini populationgeneticsprovidesnewinsightsintobiomarkerprevalenceindablimandalimandalakeymarinebiomonitoringspecies
AT lyonsbrettp populationgeneticsprovidesnewinsightsintobiomarkerprevalenceindablimandalimandalakeymarinebiomonitoringspecies
AT goodsirfreya populationgeneticsprovidesnewinsightsintobiomarkerprevalenceindablimandalimandalakeymarinebiomonitoringspecies
AT mccarthyiand populationgeneticsprovidesnewinsightsintobiomarkerprevalenceindablimandalimandalakeymarinebiomonitoringspecies
AT carvalhogaryr populationgeneticsprovidesnewinsightsintobiomarkerprevalenceindablimandalimandalakeymarinebiomonitoringspecies