10.5061/DRYAD.J7C74
Tysklind, Niklas
Bangor University
Taylor, Martin I.
Bangor University
Lyons, Brett P.
Weymouth Cefas Laboratory; Weymouth; UK
Goodsir, Freya
Lowestoft Cefas Laboratory; Lowestoft; UK
McCarthy, Ian D.
Bangor University
Carvalho, Gary R.
Bangor University
Data from: Population genetics provides new insights into biomarker
prevalence in dab (Limanda limanda L.): a key marine biomonitoring species
Dryad
dataset
2013
Habitat Degradation
Ecotoxicology
Limanda limanda
Disease Biology
Holocene
Wildlife Management
2013-04-16T18:33:02Z
2013-04-16T18:33:02Z
en
https://doi.org/10.1111/eva.12074
779889 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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 G’ST =0.007; G’’ST=0.022). Secondly, we examine the association
among 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 datasets
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.
Dab population genetics raw data and biomarker modelling infilesThis is a
file containing raw information on dab, Limanda limanda, population
genetic structure, contaminant exposure, age and biomarker prevalence
around the British Isles (dab.popgen.biomonitoring.xlsx). Dab.genotypes:
microsatellite allele size data in GenAlex format. Further information on
sex, age, weight, length, inbreeding coefficients (IR and hL values) and
latitude and longitude is also included where available. Pop.models:
Information of sample-average age, contaminant exposure (liver
concentration), prevalence (%) of external biomarkers (HYP, LY, U, EP),
proxies of populations structure (ca.axis1 and ca.axis3) and sample level
genetic diversity (Ho) and inbreeding coefficient (Fis). Ind.models:
Individual information for 451 individuals on population membership
(ca.axis1, ca.axis3), inbreeding coefficients (IR, hL), length, weight,
age, sex, age-site average estimated exposure to contaminant, presence or
absence of external biomarkers, presence or absence of 32 internal
biomarkers classified by categories (CAT 1: healthy to CAT 5:malignant
neoplasms) and liver status (lv.sts: highest category of liver damage
present in an individual). For any questions in the data please contact
Niklas Tysklind
(ntysklind@univ.bangor.ac.uk).dab.popgen.biomonitoring.xlsx
English Channel
North Sea
Irish Sea
North East Atlantic
British Isles