ICES Journal of Marine Science (2011), 68(5), 901 –910. doi:10.1093/icesjms/fsr048
Genetic identification of farmed and wild Atlantic cod,
Gadus morhua, in coastal Norway
Kevin A. Glover*, Geir Dahle, and Knut E. Jørstad
Institute of Marine Research, PO Box, 1870 Nordnes, N-5817 Bergen, Norway
*Corresponding Author: tel: +47 55 236357; fax: +47 55 238531; e-mail: [email protected].
Glover, K. A., Dahle, G., and Jørstad, K. E. 2011. Genetic identification of farmed and wild Atlantic cod, Gadus morhua, in coastal Norway. –
ICES Journal of Marine Science, 68: 901 – 910.
Received 28 September 2010; accepted 23 February 2011
Each year thousands of Atlantic cod escape from Norwegian fish farms. To investigate the potential for the genetic identification of
farmed –escaped cod in the wild, three case studies were examined. Samples of farmed, recaptured farmed escapees, and wild cod
were screened for ten microsatellite loci and the Pan I locus. Variable genetic differences were observed among cod sampled from
different farms and cages (pairwise FST ¼ 0.0 –0.1), and in two of the case studies, the most likely farm(s) of origin for most of
the recaptured escapees were identified. In case study 2, wild cod were genetically distinct from both farmed fish (pairwise FST ¼
0.026 – 0.06) and recaptured farmed– escaped cod (pairwise FST ¼ 0.029 and 0.039), demonstrating the potential to detect genetic
interactions in that fjord. Genetic identification of escapees was more challenging in case study 3, and some morphologically characterized wild cod were found to most likely represent farmed escapees. It is concluded that where cod are farmed in the same region as
their own parents/grandparents were initially sourced, or where farmed escapees originate from multiple sources, quantifying genetic
interactions with wild populations will be challenging with neutral or nearly neutral markers such as microsatellites.
Keywords: aquaculture, domestication, escapees, genetic interaction, hybridization, introgression.
Introduction
The Atlantic cod, Gadus morhua, is both ecologically and economically important, and it has sustained commercial fisheries on
both the east and west sides of the North Atlantic. However, overexploitation has led to declines and stock collapses (Myers et al.,
1996), and in many regions, cod are regarded as threatened
(Jonzen et al., 2002; Svedang and Bardon, 2003; Trzcinski et al.,
2006; Arnason et al., 2009). Declines in abundance, along with
an established consumer market, have provided a catalyst stimulating widespread interest in the production of this species by
aquaculture.
Important advances in cod aquaculture have been made in
recent years (Rosenlund and Halldorsson, 2007). For example, heritability estimates of production-related traits have been published
(Gjerde et al., 2004; Kolstad et al., 2006; Odegard et al., 2009),
and commercial broodstocks have been established from wild captured fish. Because of high fecundity and relatively short generation
times, domestication selection in fish has the potential to be very
effective. Hence, although breeding programmes for cod are still
in their infancy, it is likely that considerable genetic changes will
be made in response to selection for traits such as growth and
disease-resistance. Genetic gains through selective breeding programmes will generate fish capable of enhanced productivity in
the aquaculture environment (Glover et al., 2009a), but it is very
likely that domestication will be at the expense of fitness in the
natural environment, as has been observed in the Atlantic salmon
(Salmo salar; McGinnity et al., 1997, 2003; Fleming et al., 2000).
# The
A big challenge with most forms of aquaculture is containment.
Cod-farming is no different, and although global production in
2008 was just 21 000 t (www.fao.org), large numbers of farmed escapees have been reported. For example, in Norway, where official statistics for the numbers of farmed escapees are kept, 308 000 escapees
were reported for 2008 (www.fiskeridir.no). Cod have a greater frequency of escaping from fish farms than salmonids (Moe et al.,
2007), and behavioural studies have indicated that escapees may
mix with wild cod (Uglem et al., 2008), providing opportunity for
a range of ecological and genetic interactions (Bekkevold et al.,
2006). Moreover, farmed cod may be able to interact with wild populations without physically escaping, when spawning in their cages
(Jørstad et al., 2008). Consequently, potential ecological and
genetic interactions between wild and farmed cod are of concern.
Knowledge of the genetic interactions between wild and farmed
marine fish is sparse, but several attempts at quantifying interactions between farmed and wild Atlantic salmon have been published (Crozier, 1993, 2000; Clifford et al., 1998a, b; Skaala et al.,
2006). These studies range from the quantification of gene flow
from single escapement events affecting specific wild populations,
to more ambitious investigations quantifying genetic changes in
historical and contemporary samples of wild populations that
have been subject to differing numbers of farmed escapees over
time. Both approaches have demonstrated genetic changes in
wild populations, although the full extent of introgression and
the long-term implications for conservation remain open to
debate.
Author 2011. Published by Oxford University Press on behalf of International Council for the Exploration of the Sea.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License
(http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in
any medium, provided the original work is properly cited.
902
Genetic studies of wild cod have revealed considerable differentiation among populations over varying geographic ranges
(Frydenberg et al., 1965; Dahle and Jørstad, 1993; Knutsen et al.,
2003; Pampoulie et al., 2006; Jorde et al., 2007; O’Leary et al.,
2007; Westgaard and Fevolden, 2007; Nielsen et al., 2009).
However, except for a study of genetic diversity within and
among farmed cod reared in sea cages (Glover et al., 2010a), and
a study of spawning in sea cages (Jørstad et al., 2008), no genetic
studies have addressed the identification of farmed –escaped cod
in the wild. Consequently, the aim here was to evaluate the potential for identifying farmed –escaped cod in the wild, to investigate
the potential for the delineation of interactions with wild conspecifics. Molecular genetic variation was compared among groups of
farmed cod reared in cages, farmed–escaped cod recaptured in the
wild, and wild cod captured in the same time and location as the
escapees.
Material and methods
Overall design and sampling
This work is built upon three independent case studies conducted
in Norway. All were initiated in response to public reports of
farmed–escaped cod being captured by a mixture of private and
commercial net fishers. Many of the samples on which the study
is based were collected in connection with an ongoing forensic
identification service (Glover et al., 2008, 2009b, 2010b; Glover,
2010) for the Norwegian Directorate of Fisheries (NDF), who
produce and enforce fisheries and aquaculture regulations.
Consequently, exact dates and locations remain anonymous.
Nevertheless, the source of the broodfish used to produce the
farmed cod analysed in the case studies is presented, and is
based upon available information received from the farms (see
the case studies below).
Each case study was conducted in a different fjord, and importantly, had slightly different objectives. Details pertaining to the
specific cases are described below, but the analytical details are
similar. The term “sample” is used throughout to describe a
group of fish of a given category collected in a specific location,
i.e. not an individual DNA isolate. For clarity, samples were
labelled sequentially between case studies, and the prefix “F” was
used to depict samples taken of farmed cod from single cages on
farms with samples taken from separate cages on a single farm
being labelled A, B, C, etc., “W” to depict captured wild cod,
and “E” to depict putatively identified farmed –escaped cod recaptured in the wild.
All fish sampled in the wild were captured by gillnet.
Researchers and technicians experienced in taking samples from
cod in fish farms and in the wild conducted the putative identifications of the wild and farmed–escaped cod unless stated otherwise. For simplicity, these are referred to as samples of wild fish
and farmed escapees, although these would more correctly be
described as putative identifications. In addition to fin erosion, a
combination of skeletal abnormalities (Fjelldal et al., 2009) with
exceptionally large and untimely development of gonads and
livers provides indicators of a cod having been reared in culture.
Nevertheless, some misclassification of individual cod cannot be
ruled out (see the Results section). Moreover, based upon morphological characteristics alone, it would not be possible to
exclude the possibility that any of the putatively identified wild
fish were the result of a farm × farm cross from within-cage
spawning releasing eggs into the surrounding water masses
K. A. Glover et al.
(Jørstad et al., 2008), or a naturally recruited hybrid between a previously escaped farmed cod and a wild cod.
Case study 1
Case study 1 comprised samples of farmed–escaped cod recaptured in a fjord in northern Norway in 2009 and samples of cod
from the only operational farm in the region. The nearest alternative cod farm was .150 km away by sea and was not considered a
potential source of the recaptured escapees. The primary objective
was to investigate whether analysis of molecular genetic markers
could indicate whether the farmed escapees originated from the
fish farm, or alternatively, to exclude this possibility.
A sample of 41 (E1A) escapees was recaptured in the immediate
(,500 m) vicinity of the cod farm in a single day by gillnet. The
fish overlapped in size with the cod in the farm, most being 2 –
3 kg, and information received from fishers operating in the area
indicated that these fish had appeared “suddenly”. The company
operating the farm did not report any loss of fish. However, individual data were taken from the assumed escapees, and all were
photographed for later inspection (data not presented). In
addition to distinct morphological appearances strongly
suggesting their recent escape from the farm, the otoliths were dissected out. A second sample of farmed–escaped cod was also taken
in the same fjord at the same time (11 cod, sample E1B). Those fish
were taken from a location 10 km from the farm, and once again
overlapped in size with the cod reared in the farm. No otoliths
were taken from those fish, but most were photographed, and all
displayed clear morphological characteristics strongly suggestive
of their having escaped recently from a fish farm.
From the farm, three samples of cod were taken (labelled F3A,
F3B, and F3C). Each sample represented a cage of fish that had
been delivered from a single juvenile producer, but on separate
dates. The geographic origin of the parent fish for the cod on
this farm was northern Norway, with the parents produced in
culture and the cod in the farm reported to be second or third generation. Additionally, all fish representing sample F3B had their
otoliths removed for comparison with the otoliths recovered
from the first sample of farmed escapees. No samples of wild
cod were included in this study, but samples of cod from farms
located on the west coast of Norway, labelled F1 and F2, were
included in the analysis. These were treated as control samples,
i.e. samples where the escapees could not have originated in the
genetic baselin for the identification of the escapees.
Otoliths from samples E1A and F3B were prepared and read
blind in a standard manner by two experienced investigators to
determine cod age (Mjanger et al., 2000). In addition, otolith
form was compared visually with a database of wild cod otoliths
stored at the Institute of Marine Research (IMR) (Høie et al.,
2009).
Case study 2
Case study 2 involved samples of farmed–escaped, wild, and
farmed cod collected in a fjord in mid-Norway. The primary
objective was to compare the samples of farmed cod, both escapees
and from cages, with wild cod in the region.
Under the guidance of the NDF, gillneting was conducted in
several locations in the fjord in an eight-week period in late
autumn 2009, and a sample consisting of 40 farmed escapees
(E2) and 45 wild cod (W1) was taken for genetic analysis. These
numbers do not include all the fish captured in the period, so
do not reflect relative abundance. Samples from the two active
Genetic identification of farmed and wild Atlantic cod in coastal Norway
farms that contained cod overlapping in size with the escapees in
the fjord were also collected. These included samples from two
cages on one farm (F4A and F4B) and a single sample from
another farm (F5AB). Sample F5AB was taken from two adjacent
cages that contained fish reputed to originate from a single cage.
Consequently, the sample was treated as a single sample despite
it having been collected from two cages, pilot data analysis indicating that the cod in the two cages were from an identical source.
The origin of the parent fish of cod in F4A and F4B was northern Norway (wild, captured parents, with the cod sampled from
the cage being therefore first generation in culture) and
mid-Norway (parents produced in culture, the cod in the cage
being second generation in culture), respectively. The origin of
the parent fish of the cod in F5AB was Scotland (parents produced
in culture, offspring reared in the cage of second or third generation). Finally, a second sample of wild cod, captured in the
fjord in the 2006 spawning season (n ¼ 30), was also included in
the analyses.
Case study 3
Case study 3 represents the most extensive, and potentially most
challenging, of the three investigations, and was conducted in a
fjord located in Southwest Norway in the period 2009/2010.
Gillnetting was conducted on three occasions over a period of
one year, and all wild and farmed– escaped cod were recorded
and their relative abundance in each catch noted. The study had
several objectives: to investigate whether the escapees were genetically similar to samples from the farm, to compare the farm
samples with wild samples, and finally to compare samples of
the escapees with wild fish in the three sampling periods.
Gillnetting was conducted in the fjord in March 2009 (E3, n ¼
55; W3, n ¼ 38), October 2009 (E4, n ¼ 30; W4, n ¼ 49), and
February 2010 (E5, n ¼ 28; W5, n ¼ 66). Four samples were collected from the only cod farm active in the fjord during the first
half of 2009 (F6A, n ¼ 47; F6B, n ¼ 47; F6C, n ¼ 46; F6D, n ¼
45). The origin of parental cod producing these groups of
farmed cod was from several unreported sources. Most likely,
the sample fish represented first- (wild, captured parents) or
second- (parents produced in culture) generation fish produced
in captivity. All the fish on the farm were slaughtered in
mid-2009 (exact dates unknown), so the farmed escapees captured
in February 2010 must have been fish that had escaped from the
farm several months before their capture, or alternatively came
from a farm located outside the fjord that was not sampled in
the present study.
Genotyping
DNA was isolated in “96-well format” using either a commercial
kit (Qiagen DNeasy) or by a sodium hydroxide and Tris method
(HotShot; Truett et al., 2000). Ten microsatellite loci were amplified in two PCR reactions: Gmo 3, Gmo 8, Gmo 19, Gmo 34, Gmo
35, and Gmo 37 (Miller et al., 2000); Gmo 2 and Gmo132 (Brooker
et al., 1994); and Tch 11 and Tch 13 (O’Reilly et al., 2000). In one of
the PCR reactions, the Pan I locus was genotyped in accordance
with a previously published protocol (Stenvik et al., 2006). In
short, one unlabelled forward primer and two different reverse
primers were used; one Pan I A specific primer labelled with
6-FAM, and one Pan I B specific primer labelled with PET.
Amplified fragments were separated on an ABI 3730 sequence analyser (Applied Biosystems) and scored with the software
Genemapper 4.0 (Applied Biosystems). PCR conditions are
903
available from the authors on request. In case study 1, GMO19 displayed amplification failure for some samples, and in case studies 2
and 3, some samples displayed amplification failure in locus
GMO37, so each dataset consisted of ten markers, excluding
GMO19 in case study 1 and GMO37 in case studies 2 and 3.
Statistical analysis
Microsatellite analysis (MA; Dieringer and Schlotterer, 2003) was
used to compute summary and F-statistics to compute exact tests,
and to produce input files for other programs. Genepop
(Raymond and Rousset, 1995) was used to test for deviation
from the Hardy –Weinberg equilibrium (HWE), and to test for
evidence of linkage disequilibrium (LD) between pairs of loci
within each sample. Both computations were statistically analysed
by Fisher’s exact test using the following parameters: dememorization 10 000, 100 batches, 5000 iterations. The significance level was
presented at a0.05 and a0.001, in addition to correction for multiple testing using Bonferroni. Genepop V3.3 was also used to estimate heterozygosity. Molecular Evolutionary Genetics Analysis
v4.0 (MEGA Tamura et al., 2007) was used to produce phylogenetic trees using the UPGMA method on matrices of pairwise
FST values. The trees were linearized assuming equal evolutionary
rates in all lineages (Takezaki et al., 1995).
A Bayesian clustering analysis implemented in STRUCTURE
2.2 (Pritchard et al., 2000; Falush et al., 2003) was used to assign
individual fish to groups without using prior information about
their origin. The program was run with k ¼ 1 –5 for each dataset
separately. Correlated allele frequencies and an admixture model
were assumed. Each run involved a burn-in of 100 000 Markov
chain Monte Carlo (MCMC) steps, followed by 200 000 steps.
Pilot runs varying the numbers of MCMC steps and burn-in
gave more or less identical results. The results are presented for
k ¼ 4, a value chosen for all three datasets after determining the
plateau for the probability of the data P(D) (Falush et al., 2003),
and visual inspection of the runs for each dataset independently.
The program Geneclass (Piry et al., 2004) was used to perform selfassignment simulations, i.e. testing for the ability to perform
genetic identification and directly assign recaptured farmed cod
to baseline samples. Baseline samples included both wild and
farmed cod, depending on the case study being analysed.
Self-assignment simulations and direct assignment were conducted with a semi-Bayesian analytical method (Rannala and
Mountain, 1997). Direct assignment places an individual into
the closest baseline sample irrespective of the absolute degree of
similarity. To test the similarity of escapees to the baseline
samples, and to complement direct assignment, exclusion from
baseline samples was computed for each escapee using rejection
levels of a0.05 and a0.001, i.e. 5 and 0.1% chance of false rejection
from baseline sample.
Results
Case study 1
The otoliths of the farmed–escaped cod were read successfully,
and 39 of the 41 fish in sample E1A were successfully aged as
2+ (birth year 2007). Age determination was also possible for
the fish representing cage sample F3B, where all the cod were
aged as 2+. In addition to the fact that fish representing both
samples were uniform in age, all otoliths from both samples displayed an unusual form that deviated from extensive reference
samples of wild cod (data not presented). Consequently, when
904
K. A. Glover et al.
Table 1. Summary statistics for genetic diversity observed within samples for three separate case studies.
Case study 1
Sample
F1
F2
F3A
F3B
F3C
E1A
E1B
–
–
–
Case study 2
n
47
47
47
50
47
41
11
–
–
–
AT
96
76
96
95
96
96
65
–
–
–
AR
59
50
62
60
61
63
65
–
–
–
Ho
0.68
0.66
0.69
0.66
0.71
0.68
0.67
–
–
–
n
45
30
40
46
46
47
–
–
–
–
Sample
W1
W2
E2
F4A
F4B
F5AB
–
–
–
–
AT
142
123
120
121
113
106
–
–
–
–
Case study 3
AR
124
123
113
109
106
97
–
–
–
–
Ho
0.69
0.70
0.69
0.68
0.69
0.69
–
–
–
–
Sample
F6A
F6B
F6C
F6D
E3
W3
E4
W4
E5
W5
n
47
47
46
45
55
38
30
49
28
66
AT
99
69
119
105
129
124
100
140
103
137
AR
88
66
107
97
107
114
99
119
102
112
Ho
0.68
0.67
0.71
0.67
0.70
0.65
0.61
0.68
0.65
0.65
Case study 1 is based upon a slightly different panel of loci from case studies 2 and 3 (Table 2). Consequently, direct comparison of allelic variation is only
valid between case studies 2 and 3.
AT is the total number of alleles observed, and AR the allelic richness computed with resample sizes of 10 (case study 1), 30 (case study 2), and 28 (case
study 3).
Table 2. Locus-specific FST values computed across all samples
included within each case study.
Marker
Gmo2
Gmo3
Gmo8
Gmo19
Gmo34
Gmo35
Gmo37
Gmo132
Tch11
Tch13
Pan I
All loci
Case study 1
0.042
,0.001a
0.037
n/a
0.079
0.021
0.037
0.034
0.026
0.032
0.12
0.040
Case study 2
0.019
0.005a
0.025
0.016
0.019
0.022
n/a
0.078
0.020
0.009
0.19
0.030
Case study 3
0.037
0.009a
0.019
0.025
0.025
0.029
n/a
0.034
0.016
0.014
0.11
0.026
a
Locus-specific FST value not significantly different from 0 following
correction for multiple tests.
n/a means locus not analysed.
the otolith data were considered with the other morphological
data, the putative identification of the escapees in case study 1
was considered to be highly robust.
Of 70 tests of HWE, five deviations were observed at a0.05, but
none remained at a0.001: none was significant following correction for multiple testing. Deviations were spread among loci and
samples. In all, 53 of 275 within-sample, locus-by-locus tests of
LD were significant at a0.05, dropping to 13 at a0.001 (12
remained significant following correction for multiple testing).
The deviations were unevenly distributed, with six in each of
samples F1 and F2, and a single observation in F3B. Allelic richness
was computed with a minimum population size of 10, and except
sample F2, which displayed lower levels of genetic variation, the
samples were similar (Table 1). This was also reflected by almost
identical values of Ho for all samples.
Overall, highly significant genetic differences were observed
among the samples for all loci except Gmo3 (Table 2). The locus
Pan I gave the strongest differences among samples. The locusspecific trends observed for case study 1 were similar to those
for case studies 2 and 3, and are therefore not commented upon
further here (Table 2).
Turning to pairwise comparisons, significant genetic differences were observed among samples taken from the three farms
(Table 3). In contrast, no genetic differences were observed
among the three samples collected on farm 3 that operated
within the fjord where the escapees were recaptured. This observation confirms the farm management’s report that these fish
had been sourced from the same supplier, despite being delivered
on separate dates. No genetic differences were observed between
the two independent samples of escapees, and furthermore,
neither of the two samples was significantly different from any
of the samples collected from farm 3. Cluster analysis
(Figure 1a) supported the genetic relationships described.
Because of the analyses referred to above indicating that the
samples taken from farm 3 were not significantly different from
each other, these samples (F3A, F3B, F3C) were pooled before conducting individual genetic assignment. Overall, correct selfassignment among the baseline samples (baseline ¼ farms 1, 2,
and 3) was 93%. A combination of direct assignment and exclusion demonstrated that most of the farmed escapees matched
the genetic profile of the samples collected from farm 3
(Table 4). Only one of the 52 escapees was directly assigned to a
baseline sample included as a control (F1 or F2), and most of
the 52 escapees were excluded from both control samples. Taken
together, these analyses provide compelling evidence that farm 3,
which is the only active cod farm in that fjord with fish overlapping
in size with the escapees, cannot be excluded as a potential source
of the unreported escapees.
Case study 2
Of 60 tests of HWE, 11 significant deviations were observed at
a0.05. At a0.001, two remained significant, both observed in
sample F5AB (loci GMO19 and Tch11). An identical result was
obtained following correction for multiple testing. LD was
observed in 55 of 252 tests at a0.05, dropping to 19 at a0.001,
and to 16 when correcting for multiple testing. At a0.001, 11 significant deviations were observed in F5AB, 7 in F4B, and 1 in F4A.
Allelic richness, based upon a resample size of 30, was slightly
lower in the farmed samples than in the wild samples (Table 1).
No clear differences in Ho were observed among the samples.
No genetic differentiation was observed between the two
samples of wild fish, demonstrating temporal stability over three
years (Table 5). In contrast, significant differentiation was
observed among all three samples from farms, confirming the
multiple origins of those fish. The largest pairwise values involved
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Genetic identification of farmed and wild Atlantic cod in coastal Norway
Table 3. Pairwise FST values (bottom left), and associated p-values (upper right) among eight samples of farmed (F) and farmed – escaped
(E) cod in case study 1.
Sample
F1
F2
F3A
F3B
F3C
E1A
E1B
F1
–
0.0997
0.0804
0.0763
0.0802
0.0659
0.0682
F2
0.0001
–
0.0392
0.0359
0.0557
0.0462
0.0388
F3A
0.0001
0.0001
–
20.0009
0.0038
0.0036
20.007
F3B
0.0001
0.0001
0.62
F3C
0.0001
0.0001
0.07
0.08
E1A
0.0001
0.0001
0.10
0.01
0.08
0.0038
20.0087
–
20.0048
–
0.0034
0.0073
20.009
–
E1B
0.0001
0.0013
0.82
0.92
0.94
0.74
–
Emboldened p-values are significant following multiple testing (adjusted a ¼ 0.0024).
Figure 1. Bayesian clustering of farmed (F), wild (W), and recaptured, escaped, farmed cod (E) constituting samples in (a) case study 1,
(b) case study 2, and (c) case study 3. All are presented for a population size set at k ¼ 4 after pilot runs at k ¼ 1– 5. Colours that depict
genetic clusters are not universal among the case studies.
sample F5AB. This was the sample reported to have originated
from a Scottish fish farm. Both samples of wild fish were significantly different from all samples of farmed fish and the group of
recaptured escapees. The recaptured escapees were significantly
different from all samples, except farm sample F4B.
A Bayesian cluster analysis confirmed the genetic relationships
among the samples as reported above, but also revealed significant
genetic substructure within some samples (Figure 1b). In farm
sample F5AB of Scottish origin, individual cod displayed little
admixture, and the sample appeared to have two distinct lineages,
depicted by green and yellow bars in Figure 1b. This suggests that
sample F5AB comprised fish from two strains that had been
physically mixed. As reported above, that sample was also responsible for most of the significant HWE and LD tests, supporting the
notion that they had been mixed.
Overall, correct self-assignment among the baseline samples
was 79% where the baseline here is defined as three farm
samples and both the wild-fish samples pooled into a single
sample. Looking closer at the self-assignment simulations, only
14 of 75 wild fish were incorrectly assigned to a farm sample,
and only 12 of 139 farm fish were assigned incorrectly to either
of the wild samples (88% correct identification to type). Direct
assignment of the 40 escapees placed 29 into farm samples and
11 into the combined wild sample (Table 6). Farm sample F4B
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K. A. Glover et al.
was clearly implicated in approximately half of the escapees, four
fish were placed directly into farm sample F4A, and another four
into sample F5AB. The latter observation was also confirmed in
the cluster analysis where these four cod in sample E2 were distinct. They are depicted yellow in Figure 1b. These analyses
suggest that the escapees recaptured in this fjord at that time originated from more than one farm or cage.
Case study 3
From 100 tests of HWE, 16 significant deviations were reported at
a0.05. At a0.001, only three deviations remained significant:
GMO132 and GMO19 in three separate samples. Again, an
Table 4. Summary of assignment of 52 recaptured farmed –
escaped cod in case study 1.
Sample
F1
F2
F3a
Direct assignment
0
1
51
Excluded a0.05
48
49
13
Excluded a0.001
38
39
0
a
Baseline samples F3A, F3B, and F3C pooled before analysis.
Table 5. Pairwise FST values (bottom left) and associated p-values
(upper right) among six samples of farmed (F), wild (W), and
farmed – escaped (E) cod in case study 2.
Sample
W1
W2
E2
F4A
F4B
F5AB
W1
–
0.0001
0.0293
0.0305
0.0265
0.0524
W2
0.45
–
0.0389
0.0357
0.0349
0.0601
E2
0.0001
0.0001
–
0.0199
0.0046
0.0359
F4A
0.0001
0.0001
0.0001
–
0.0162
0.0318
F4B
0.0001
0.0001
0.06
0.0001
–
0.0352
F5AB
0.0001
0.0001
0.0001
0.0001
0.0001
–
Emboldened p-values are significant following multiple testing (adjusted a
¼ 0.0033).
Table 6. Summary of assignment of 40 recaptured farmed –
escaped cod in case study 2.
Sample
W1 + W2
F4A
F4B
F5AB
Direct assignment
11
4
21
4
Excluded a0.05
4
12
9
29
Excluded a0.001
20
32
18
37
identical result was obtained following correction for multiple
testing. From 423 tests of LD, 92 were significant at a0.05 and
37 remained significant at a0.001, but this number dropped to
34 following correction for multiple testing. Significant LD
values at a0.001 were observed in samples F6A ¼ 7, F6B ¼ 5,
F6C ¼ 11, F6D ¼ 11, E3 ¼ 2, and W4 ¼ 1. As observed for the
other case studies, little difference in mean heterozygosity was
observed among samples (0.61 in E4, up to a high of 0.71 in
F6C), but the largest numbers of alleles, in addition to highest
allele richness, were observed for the three wild samples compared
with either samples of escapees or samples taken directly on the
farms (Table 1).
The genetic relationships among the samples on which case
study 3 is based are presented as both a matrix of pairwise FST
values with associated significance levels (Table 7) and a
UPGMA diagram, which illustrates the overall relationships
(Figure 2). All four samples collected from farm 6 were significantly different from each other. Except a marginally significant
difference between W3 and W5, which was not significant following correction for multiple testing, no significant genetic differences were observed among the three samples of wild cod,
which clustered together (Figure 2). All samples of wild cod
were significantly different from the samples taken on the farm
(Table 7), and all three samples of escapees were significantly
different from samples taken from the farms, although E5 was
only marginally significantly different from F6D. Some of the pairwise FST values among the samples of escapees were marginally significant, but they still clustered together (Figure 2).
Farm samples F6A and F6B displayed little or no hidden genetic
structure, but farm samples F6C and F6D displayed considerable
hidden structure, as did all samples of recaptured escapees and
wild fish (Figure 1c). All samples of farmed escapees contained
some cod belonging to the cluster associated with farm sample
F6B (depicted green in Figure 1), suggesting that those cod had
escaped from that cage. Because of the level of admixture represented within many of the samples, of all types, it was difficult
to separate wild and farmed fish within the diagram. Clearly,
farm samples F6C and F6D were similar to the wild fish in the
region, suggesting that the parental fish from which they were produced may have been sourced locally. Also, the sample of wild cod
captured in February 2010 (W5) contained three cod belonging to
a cluster associated with farm sample F6B, and displayed little or
no admixture. This suggests misidentification of these fish as
wild cod. Other potential misclassifications of farmed and wild
fish which are not so distinct from the cluster analysis may
also exist.
Table 7. Pairwise FST values (bottom left) and associated p-values (upper right) among 11 samples of farmed (F), wild (W), and farmed –
escaped (E) cod in case study 3.
Sample
F6A
F6B
F6C
F6D
E3
W3
E4
W4
E5
W5
F6A
–
0.0832
0.0302
0.0360
0.0380
0.0292
0.0432
0.0228
0.0252
0.0297
F6B
0.0001
–
0.0735
0.0645
0.0259
0.0677
0.0254
0.0630
0.0416
0.0600
F6C
0.0001
0.0001
–
0.0167
0.0229
0.0174
0.0252
0.0098
0.0140
0.0139
F6D
0.0001
0.0001
0.0001
–
0.0126
0.0125
0.0223
0.0127
0.0084
0.0233
E3
0.0001
0.0001
0.0001
0.0003
–
0.0134
0.0085
0.0109
0.0032
0.0136
Emboldened p-values remain significant following multiple testing (adjusted a ¼ 0.0011).
W3
0.0001
0.0001
0.0001
0.0002
0.0001
–
0.0256
0.0019
0.0048
0.0041
E4
0.0001
0.0001
0.0001
0.0001
0.0050
0.0001
–
0.0170
0.0067
0.0178
W4
0.0001
0.0001
0.0001
0.0001
0.0001
0.1934
0.0001
–
0.0017
0.0012
E5
0.0001
0.0001
0.0003
0.0179
0.1234
0.0745
0.0582
0.2473
–
0.0054
W5
0.0001
0.0001
0.0001
0.0001
0.0001
0.0380
0.0001
0.2349
0.0298
–
907
Genetic identification of farmed and wild Atlantic cod in coastal Norway
Figure 2. UPGMA diagram illustrating the genetic relationships among ten samples of cod sampled in case study 3.
Table 8. Summary of assignment of three groups of recaptured escaped cod (E3, E4, E5), and a group of wild cod (W5) for case study 3,
with assignment expressed as a percentage to facilitate comparisons between the four samples, where n varied between 28 and 66.
Exclusion a0.05
Direct assignment
Sample
n
E3
E4
E5
W5
55
30
28
66
Farm
69
87
43
24
Wild
31
13
57
76
Farm
51
20
32
65
Wild
29
23
18
17
Exclusion a0.001
All
22
17
11
17
Farm
11
3
11
27
Wild
0
0
0
0
All
0
0
0
0
“Farm” refers to farm samples F6A, F6B, F6C, and F6D combined, and “Wild” to W3 and W4 combined.
n is the number of observations for each sample.
For self-assignment simulations, a genetic baseline was conducted from the four farm samples, and the first two samples of
wild cod (W3 and W4) pooled into a single sample of wild cod.
Overall, correct self-assignment among the five baseline samples
was 75%. When self-assignment was conducted to type, i.e. wild
and farmed, pooling data post-assignment to specific samples,
the accuracy of self-assignment increased to 83%, with 21 of 185
farmed fish misclassified as wild and 24 of 87 wild fish misclassified as farmed.
The assignment of farmed–escaped cod (E3, E4, E5) and the
most recent sample of wild cod (W5) is presented in Table 8.
Assignment was conducted on the five samples used to generate
the genetic baseline in the self-assignment simulations, but those
data are summarized to type, i.e. farmed or wild. Several trends
can be observed from these results. First, although escapees were
assigned directly to a range of farm samples, F6B was the most frequent farm source with which the escapees were associated. Note
that assignment to a specific sample is not presented. Second,
the numbers of farmed escapees being associated with the farm
samples as a group varied between the three samples taken over
a period of 1 year. In sample E5, noticeably, more of the escapees
were directly assigned to the wild baseline sample than were the
farm samples. Third, most of the wild cod were directly assigned
to the wild samples, an observation conferred by the exclusion
tests in which only 17 and 0% of the 66 fish were rejected from
the wild sample at stringency levels a0.05 and a0.001, respectively.
Finally, a trend observed for all three samples of farmed escapees
was that few escapees could be excluded from the wild-cod reference population, whereas exclusion from “alternative” farm
samples was much greater. This is despite the fact that in
samples E3 and E4, most of the escapees were placed directly
into farm samples.
Discussion
To our knowledge, this paper is the first molecular genetic study of
farmed cod in the natural environment. The investigations presented illustrate contrasting situations in which molecular tools
were implemented to identify the most likely farm(s) of origin
for recaptured escapee cod, to quantify genetic differences
between wild and farmed fish, and finally to compare farmed –
escaped and wild cod captured at the same time and location in
the wild. The studies were brought together with the overall aim
of evaluating the potential to identify, monitor, and quantify
genetic interactions between farmed –escaped cod and their wild
conspecifics. Although the results demonstrate that molecular
genetic tools can be implemented to identify farmed–escaped
cod in the wild, that will depend on the specific question being
addressed, the location in which the investigation is being conducted, and not least the genetic origin of the farmed fish. The
last point is highly relevant given that genetic assignment is
more robust when there are larger genetic differences among
potential source populations. Therefore, where cod are reared in
the same region as their parents (or grandparents) were initially
sourced, separating the two groups with genetic methods may be
challenging. In turn, this may lead to difficulties in quantifying
genetic introgression of farmed escapees in wild populations.
The genetic identification of Atlantic salmon (Glover et al.,
2008, 2009a, b,2010b), and rainbow trout, Oncorhyncus mykiss
(Glover, 2008) escapees back to their farm of origin is a wellestablished technique in Norway. It has resulted in legal
908
investigations and fines for companies found in breach of aquaculture regulations (Glover, 2010). A recent study has also demonstrated proof-of-concept to identify farmed–escaped cod back to
farm and cage of origin (Glover et al., 2010a). However, case
study 1 presented here represents the first time that farmed–
escaped cod have been identified to their farm of origin in
response to a direct request from the authorities, representing an
important step in the implementation of aquaculture regulations
for cod, and it is to be hoped, in controlling the numbers of fishfarm escapees.
A recent study of farmed cod revealed significant genetic differentiation among groups of fish reared in different farms and cages
(Glover et al., 2010a). Significant differentiation among groups of
farmed cod were also observed here, reflecting both inter- and
intra-strain genetic differentiation as a result of founder effects
and genetic drift. However, the level of genetic differentiation
observed among groups of cod reared in cages is lower than that
typically observed among groups of Atlantic salmon reared in
cages (Glover et al., 2008, 2009b), and wild Atlantic salmon populations generally display greater population genetic differentiation
than Norwegian coastal cod (NCC). Consequently, although the
results of this study demonstrate that it will be possible, in some
cases, to quantify the genetic interactions between farmed –
escaped cod and wild conspecifics, e.g. in case study 2, it is likely
that this will be more challenging than reported for Atlantic
salmon (Skaala et al., 2006). Moreover, the issue may be complicated further given that, in some cases, the parents or grandparents
of farmed fish will have originated from the same region in which
the aquaculture was being carried out. The latter point is both
illustrated and supported by the fact that exclusion of the wild
populations as potential sources of the farmed escapees in case
studies 2 and 3 was more difficult than excluding alternative
farm samples as potential sources for the escapees (Tables 6
and 8). From a statistical perspective, this might be because the
greater genetic diversity observed in the wild populations than
farmed strains makes a composite genotype for a given farmed
fish more difficult to exclude from the wild source than from
alternative farmed sources.
The number of genetic markers implemented in the present
study is modest compared with the numbers typically
implemented to delineate fine genetic divergence or to conduct
individual assignment. The panel of markers chosen here were
selected on the basis that they have already been successfully
implemented to document genetic differences among cages of
farmed cod (Glover et al., 2010a). In addition, the Pan I locus
was chosen because it is almost diagnostic between northeast
Arctic cod (NEAC) and NCC (Fevolden and Pogson, 1997;
Pogson and Fevolden, 2003), and it differentiates farmed strains
where the percentage representation of NEAC and NCC varies
(Glover et al., 2010a). In general, the accuracy of the genetic
assignment increases with the number of loci, although the law
of diminishing returns comes into play, and among closely
related samples, individual genetic assignment will probably
never reach a fully diagnostic level with even large panels of
markers (Glover et al., 2010b). Although it is acknowledged that
the implementation of a larger panel of markers may have
increased precision in some of the assignments presented here,
we believe that our conclusions would not change. Nevertheless,
future attempts to quantify the genetic interactions between
farmed–escaped and wild cod should be conducted with more
loci to gain more diagnostic power.
K. A. Glover et al.
The process of genetic drift will ensure that the continued domestication of cod will lead to greater genetic divergence between
wild populations and farmed strains over time. In addition, a footprint of selection may be generated in the genome as a result of
domestication. This has been observed for Atlantic salmon,
where a genome scan revealed a panel of single nucleotide polymorphisms (SNPs) that were collectively able to identify fish as
farmed and wild irrespective of their specific populations of
origin (Karlsson et al., 2011). In future, it is likely that adaptive
changes to domestication, identified through the application of
rapidly developing molecular genetic resources (Moen et al.,
2008; Hubert et al., 2010), may also permit identification of
genetic markers that differentiate wild and farmed cod. These
markers will be important in the identification and monitoring
of the genetic interactions between them. Given some of the challenges outlined here, e.g. the complicated identification of escapees
when they arise from farmed strains founded on local broodstock
and fish escaping from multiple farm sources, genetic markers that
are type-diagnostic may be required in the future to elucidate and
quantify genetic interactions fully.
Farmed cod strains reared in Norway are almost exclusively
founded on NCC and NEAC populations. These stock components may vary greatly among the different breeding programmes. As suggested previously (Glover et al., 2010a), where
strains with a high representation of NEAC are reared, the locus
Pan I, which is more or less diagnostic between NEAC and NCC
(Fevolden and Pogson, 1997; Pogson and Fevolden, 2003), may
be used to track escapees in the natural environment. None of
the farmed strains investigated in case study 2 or 3 in the
present study displayed a high frequency of the Pan I B allele. If,
however, the strain of farmed cod reared in case study 1, which displayed a relatively high frequency of the Pan I B allele, had been
compared with the NCC populations analysed in case study 2 or
3, farmed escapees from that source would have been readily identifiable. With this line of thought, the sample of Scottish cod reared
on a farm in case study 2 displayed the greatest difference from the
wild samples in that study. We are not advocating the culture of
NEAC or cod of international origin in coastal regions of
Norway, or vice versa, however, because of the possibility of maladaptive genes being introduced. There is at present no legislation
in Norway to prevent farmers from culturing cod from outside
the region in which the strain originates. It therefore remains a
fact that in such situations, the identification of escapees with
genetic methods will be most successful.
A genetically marked population of Atlantic cod exists at IMR.
This has been successfully implemented to evaluate the survival of
released cod into the wild in connection with sea ranching
(Svåsand et al., 1991; Jørstad et al., 1994; Kristiansen et al.,
1997), and to document that spawning in fish farms can lead to
the production of viable larvae that mix with wild cod larvae
(Jørstad et al., 2008). It is suggested that given the identification
challenges unveiled in the present study, and the rapid development of genetic-marker resources for cod (Moen et al., 2008;
Hubert et al., 2010) and other marine species, domestic breeding
programmes for cod and other marine fish species could incorporate genetic markers as one of the breeding targets to provide robust
identification of potential escapees.
To conclude, the results of this study have demonstrated how
molecular genetic tools may be implemented to identify farmed
escapees in the wild, and potentially to quantify their interaction
with wild conspecifics. We concentrated on Atlantic cod, but the
Genetic identification of farmed and wild Atlantic cod in coastal Norway
results here are of universal relevance for a range of marine species
that are, or perhaps will be, subjected to aquaculture and domestication. Studying this topic is of importance given that many wild
populations are severely depleted and, as a result, are more vulnerable to potentially negative interactions with domesticated conspecifics. Ultimately, a reduction in the numbers of escapees and the
development of sterile farmed fish must be among the key policies
of the aquaculture industry in order to promote the coexistence of
sustainable aquaculture and healthy wild stocks.
Acknowledgements
We acknowledge the assistance of Ole I. Paulsen, Gunnar Bakke,
and Terje van der Meeren from IMR with the sampling of the
farmed and wild cod in case studies 2 and 3. Commercial and recreational fishers are acknowledged for permitting access to their
vessels and catch, the NDF for sampling assistance, and Harald
Senneset and Hildegunn Mjanger for reading the cod otoliths.
We also thank Anne G. S. Eide and Bjørghild B. Seliussen from
IMR for assisting with genetic analyses, and Øystein Skaala and
Terje Svåsand for discussions of case study 1. Finally, we are grateful to the anonymous reviewers for helpful comments on earlier
drafts of the paper. The study was financed by the IMR and the
Norwegian Ministry of Fisheries. Funding to pay the Open
Access publication charges was provided by the Institute of
Marine Research.
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