© 2005 International Council for the Exploration of the Sea
Deviation from Hardy–Weinberg equilibrium, and temporal instability in allele frequencies at microsatellite loci in a local population of Atlantic cod
NTNU, Department of Biology Trondhjem Biological Station, N-7491 Trondheim, Norway
*Correspondence to S. Karlsson: tel: +47 73598340; fax: +47 73591597. e-mail: stenk{at}bio.ntnu.no.
A total of 1455 spawning cod, sampled from a local spawning area in Trondheimsfjord (Norway) between 1985 and 2002, was screened at the microsatellite loci Gmo132 and Gmo2. Samples from 15 spawning years comprising 29 consecutive cohorts were analysed. At the Gmo132 locus, but not at Gmo2, allele frequencies varied significantly among sampling years as well as cohorts, corresponding to FST-values of 0.004 and 0.006, respectively. Both loci showed examples of significant deviations from Hardy–Weinberg expectation within sampling years as well as cohorts, manifested as deficiencies of heterozygotes. Combining the p-values from the single tests (Fisher's method) revealed an overall significant p-value for deviation from the Hardy–Weinberg expectations at Gmo132 but not at Gmo2. Trend tests showed significant HW deficiencies at both loci for annual samples but not for cohorts. Possible reasons for the deficiencies were discussed; inter alia the existence of null alleles, or a form of pseudo Wahlund effect due to a patchy distribution of habitats for settling O-group cod in the Trondheimsfjord. It was noted that there might be a relationship between the relatively high temporal within-population variability of allele frequencies at Gmo132 and the fact that among microsatellite loci studied so far, Gmo132 is the one that usually shows the highest genetic differentiation geographically in cod.
Keywords: Atlantic cod, Gmo132, Gmo2, microsatellite, temporal variation
Received 22 October 2004; accepted 15 May 2005.
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Introduction |
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Microsatellites are increasingly used for the study of genetic population structure of natural populations such as Atlantic cod (Bentzen et al., 1996; Ruzzante et al., 1998; Hutchinson et al., 2001; Knutsen et al., 2003). Most studies were based on point estimates in time (i.e. sampling each location only once), while a few also consider whether the local genetic characteristics were stable in time (Ruzzante et al., 1996, 2001; Hutchinson et al., 2003). The Gmo132 locus, frequently used in studies of cod, usually shows a higher degree of genetic differentiation compared with other microsatellite loci (Bentzen et al., 1996; Ruzzante et al., 1998, 2000a, b, 2001; Knutsen et al., 2003; Lage et al., 2004) (cf Table 1). From simulation analyses (Beaumont and Nichols, 1996) we generated a distribution of FST conditional on heterozygosity as implemented in the fdist2 programme (available at http://www.rubic.rdg.ac.uk/%126mab/software.html). This was possible in five of the seven studies mentioned above. In the study of Bentzen et al. (1996) the Gmo132 was a highly significant outlier (p
0) with respect to the FST estimate, and an almost significant outlier (p = 0.067) in the study of Lage et al. (2004). These observations might imply that the Gmo132 locus is affected by natural selection (but see Flint et al., 1999, and Storz et al., 2004, for the interpretation of markers with high mutation rates and heterozygosity). Beaumont and Nichols (1996) demonstrated a similar phenomenon among the cDNA RFLP loci of Pogson et al. (1995), where PanI showed much higher FST-values compared to the other loci included. Dynamics of the PanI polymorphism were studied by Karlsson and Mork (2003) using a time-series of cod collected from the same spawning population as in this study. The same approach is used in this study where we test for temporal stability of allele frequencies and conformance to the Hardy–Weinberg equilibrium as well as for possible effects of selection at two microsatellite loci in cod: Gmo132 and Gmo2. The Gmo2 locus was chosen for comparison reasons, i.e. as a microsatellite locus that has shown moderate level of differentiation among populations of cod, as most microsatellite loci do.
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Material and methods |
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Sample collection
Cod were collected during the spawning season in Verrasundet, a relatively narrow side-fjord in the inner part of Trondheimsfjord, Norway (Figure 1). Verrasundet is a long known and well defined spawning area in Trondheimsfjord (Dahl, 1899; Sundnes, 1980; Mork et al., 1985; Mork and Giæver, 1999). Samples from spawning cod were collected over an 18-year period with a bottom trawl (35 mm stretched mesh in the cod-end) by the RV "Harry Borthen I" from Trondhjem Biological Station, NTNU (The Norwegian University of Science and Technology).
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Laboratory methodology
In total, 1455 individuals were assayed for genotype at Gmo132 and Gmo2 (Table 2). Except for the sample taken in 1990, sex, age, gonad stage, and total body length were recorded for each individual. Age determination was performed by Ekli (1997 and unpublished) according to the breakage-and-side-illumination method of Rollefsen (1933). Determination of gonad maturation stage followed Sivertsen (1935): stage I, immature; stage II, maturing; stage III, running; and stage IV, spent. Samples of blood, white muscle, gills, heart, liver, and kidney were stored frozen or in ethanol and DNA was extracted from one of these tissue types, according to the phenol chloroform extraction procedure described in Sambrook et al. (1989), with some modifications described in Karlsson and Mork (2003).
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PCR analyses of Gmo132 and Gmo2 were first described by Brooker et al. (1994). The reverse primers were end-labelled with IRD800 (MWG-biotech AG, Ebersberg, Germany). The PCR reaction mixture contained 2 ng–5 µg template DNA, 0.26 µM labelled reverse primer, 0.26 µM forward primer, 53 mM KCl, 10.5 mM Tris–HCl (pH 9.0), 1.6 mM MgCl2, 217 mM dNTP, 0.12% Tween, 38 ng BSA, and 1 unit of Taq Polymerase (Amersham pharmacia biotech) in a 19-µl volume. PCR was carried out in a Hybaid® Omni-E thermal cycler programmed for 30 cycles of denaturation at 95°C (1 min), primer annealing at 52°C for Gmo132 and 50°C for Gmo2 (2 min), primer extension at 72°C (20 s). Depending on the strength of the amplification, the PCR products were diluted 1:10–1:50 with formamide loading dye (98% formamide, 10 µM EDTA, 1 mg/ml bromophenol blue). The diluted PCR product was denatured at 95°C for 5 min. After denaturing, the samples were put directly on ice, and 0.5 µl of the PCR product was subjected to gel electrophoresis on a 6% denaturing polyacrylamide gel. Electrophoresis was carried out on a LI-COR 4000 DNA sequencer with 25 cm electrophoresis plates. In each tenth well we loaded a commercial ladder (50–350 bp sizing standard, LI-COR, Inc) and an allelic ladder of known fragment sizes amplified from Gmo132 and Gmo2, respectively. The lengths of the fragments were determined in relation to the commercial ladder, and the lengths of following fragments were determined accordingly. All gel images were analysed manually.
Statistical analyses
Statistical analyses of continuous variables were performed by one-way analysis of variance (ANOVA) as implemented in STATGRAPHIC Plus 2.1 (STSC, Inc.). For discrete variables, 
2 and sign tests were used as appropriate. In situations with low expected values (i.e. more than 25% of cells with expected numbers <5), traditional 2 tests were replaced by the Monte Carlo based exact test (1000 iterations) of Zaykin and Pudovkin (1993). Probabilities that were estimated from individual exact tests were combined into an overall probability by the "omnibus" test of Fisher (1954). In order to compare body length independently of age, individual body length was multiplied by a factor derived from the relationship (linear regression in a double logarithmic plot) between age and mean length from all combined samples. Homogeneity tests based on allele frequencies over sampling year and cohort, as well as tests of conformance to Hardy–Weinberg genotypic expectations (the probability test option) were carried out with GENEPOP ver.3 (Raymond and Rousset, 1995). Estimates of the fixation index 
, the FST analogue of Weir and Cockerham (1984), were computed with the GDA program of Lewis and Zaykin (2001). We used MICRO-CHECKER, a free software designed to check microsatellite data for null alleles and scoring errors (available at http://www.microchecker.hull.ac.uk/). In principle, the program explores genotypic data by testing if there is an excess of homozygotes caused by null alleles, stuttering, or large allele dropout. If there is a general excess of homozygotes over most allele size classes, shown at one locus but not at other loci, it indicates the presence of null alleles. If, on the other hand, the observed excess of homozygotes can only be ascribed to larger alleles, it may indicate large allele dropout or deviation. Excess of homozygotes at only some alleles can be caused by deviation from panmixia. Finally, if there is a deficiency of heterozygote genotypes with alleles of one repeat unit difference, it may indicate stuttering.
Gmo132 and Gmo2 are highly polymorphic with large numbers of alleles. Analyses performed on these loci require large sample sizes, because the estimated allele frequencies of those alleles represented by very few individuals will have relatively large standard errors (Chakraborty, 1992). One procedure to compensate for low sample sizes, and thus large confidence intervals, is binning of alleles (Bentzen et al., 1991; O'Connell and Wright, 1997; Shaw et al., 1999). Even though the sample sizes in the present study were relatively large compared with recommendations by Ruzzante (1998), analyses were performed with both unbinned and binned alleles. The highly polymorphic and skewed allelic distributions observed at Gmo132 and Gmo2 result in samples with large numbers of low-frequency alleles, and hence tests of allele frequency homogeneity using all alleles will have relatively low statistical power. At both loci, therefore, all alleles except the most frequent one were binned as one allele class, resulting in 2-allele systems. For Gmo2, we additionally binned all alleles except the eight most frequent ones.
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Results |
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The annual sample sizes ranged from 42 to 159 individuals, with an overrepresentation of males. There was a large span of ages and body lengths. A majority of individuals had running gonads, but immature and spent specimens were also present (Table 2).
The total number of cod analysed was 1456 for Gmo132 and 1455 for Gmo2. Both the Gmo132 and the Gmo2 locus were highly polymorphic with 33 and 22 alleles and expected heterozygosities of 0.707 and 0.861, respectively. The lower expected heterozygosity at Gmo132 despite the large number of alleles was due to a highly skewed allele frequency distribution at this locus compared with Gmo2 (Figure 2). The cohort sample sizes were fairly large except for the four oldest and the two youngest cohorts, and as expected, the number of alleles represented in a cohort increased with increasing sample size (Table 3).
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We did not observe any significant association of genotype or allele frequency at Gmo132 or Gmo2 with phenotypic traits, such as body length, age, gonad stage, or sex. These analyses were performed within annual samples and within cohorts as well as on pooled material (i.e. all individuals pooled into one group).
Conformance to Hardy–Weinberg expectations
At the Gmo132 locus, four out of 15 annual samples showed significant departures from Hardy–Weinberg equilibrium, and overall the departure was highly significant (2[30] = 
, p 0) (Table 4). At the Gmo2 locus, three out of 15 annual samples showed significant departures from Hardy–Weinberg equilibrium, and overall the departure was almost significant (2[30] = 41.8, p = 0.074) (Table 4). At both Gmo132 and Gmo2, the departure was mainly due to a deficit of heterozygotes because at both loci, 12 out of 15 annual samples showed a significant trend (p = 0.036, two-way binomial sign test) towards a deficit of heterozygotes. Deficiencies at the two loci did however only coincide in 10 out of the 15 samples.
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The results were similar when analyses were performed on cohorts instead of annual samples. At Gmo132, four out of 26 cohorts showed significant departures from Hardy–Weinberg equilibrium, but overall the departure was highly significant (
2[52] = , p 0). At Gmo2, three out of 26 cohorts showed significant departures from Hardy–Weinberg equilibrium, and overall the departure was almost significant (2[52] = 67.6, p = 0.072). Compared with the annual samples, some of the cohort sample sizes were relatively small (Table 2) and hence had lower statistical power. At both loci the departure was mainly due to a deficit of heterozygotes. At Gmo2, 18 out of 26 cohorts showed a deficit of heterozygotes (p = 0.076, two-way binomial sign test). At Gmo132, 17 out of 26 cohorts showed deficits of heterozygotes (p = 0.168, two-way binomial sign test). Deficiencies at both loci were coincided in 12 cohorts. The MICRO-CHECKER software revealed evidence of a general excess of homozygotes for most allele size classes at Gmo2 in the 1999 sample and at Gmo132 in the 1995 sample. When all annual samples were pooled, there was a general excess of homozygotes of most allele size classes at both Gmo2 and Gmo132 (pooling annual samples was, however, not appropriate regarding Gmo132, because as shown below, there was significant heterogeneity in allele frequencies among annual samples at this locus). There were no indications of scoring errors attributable to stuttering or large allele dropout. The general excess of homozygotes for most allele size classes may hence indicate the presence of null alleles or a Wahlund effect. Because there was only weak evidence of null allele, it is likely to be rare and hence it would be unsafe to calculate corrected estimates of allele frequencies (Bill Hutchinson, University of Hull, UK pers. comm).
Temporal variation among annual samples
Figure 3 shows the arcsin-transformed allele frequency of the most common allele at Gmo132 and Gmo2 for each annual sample. The figure shows a more pronounced fluctuation in allele frequency at Gmo132 compared with Gmo2. Homogeneity tests of allele frequencies among annual samples were performed both on binned and unbinned alleles (Table 5). When alleles were not binned there was a highly significant variation among annual samples at Gmo132 (p = 0.009) but not at Gmo2 (p = 0.346). When all alleles except the most frequent ones were binned, the heterogeneity was even more pronounced at Gmo132 (p 0), but again not significant at Gmo2 (p = 0.388). The Gmo2 locus was further explored by binning all except the eight most frequent alleles. This 9-allele system did not reveal any significant heterogeneity among annual samples (p = 0.388).
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Estimates of the among-samples annual genetic variability (FST) revealed nearly significant heterogeneity (FST = 0.0039, p = 0.077) at the Gmo132 locus but not at the Gmo2 locus (FST = 0.0004, p
1) (Table 5).
Temporal variation among cohorts
Homogeneity tests of allele frequencies among cohorts showed results similar to tests among annual samples (Table 5). When alleles were not binned there was a highly significant variation among cohorts at Gmo132 (p 0) but not at Gmo2 (p = 0.095). When all alleles except the most frequent ones were binned, highly significant heterogeneity remained at Gmo132 (p 0), but was still not significant at Gmo2 (p = 0.520). When all except the eight most frequent alleles were binned there was no significant heterogeneity in allele frequencies among cohorts at the Gmo2 locus (p = 0.302)
Arcsin-transformed allele frequency of the most common allele at Gmo132 and Gmo2 for each cohort shows a more pronounced fluctuation in allele frequency at Gmo132 than at Gmo2 (Figure 4). Estimates of the among-cohort genetic variability (FST) revealed nearly significant heterogeneity at the Gmo132 locus (FST = 0.0064, p = 0.081) but not at the Gmo2 locus (FST = 0.0003, p 1) (Table 5).
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Discussion |
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In large panmictic and isolated populations, neutral genetic markers are expected to show no change in allele frequency through generations on a short evolutionary time scale. In the present study we did, however, find significant variation in allele frequency over time at one locus and also significant departures from Hardy–Weinberg expectation, mainly caused by heterozygote deficiencies at both loci. We will first discuss the observed deviations from Hardy–Weinberg equilibrium, followed by the observations of variation in allele frequencies among annual samples and cohorts. Finally, all observations are taken into account, in order to draw plausible conclusions of the main factors responsible for our findings.
Departure from Hardy–Weinberg equilibrium
The observed deficit of heterozygotes as compared with Hardy–Weinberg equilibrium observed at both Gmo132 and Gmo2 could be a result of physical mixing of populations with different allele frequencies (Wahlund effect) or it could be caused by natural selection, phenotypic assortative mating, inbreeding, and/or null alleles. Among these, we believe that natural selection, Wahlund effects, and/or null alleles are the most reasonable ones.
Wahlund effect
It is reasonable to assume that a Wahlund effect would be expressed in a sample of spawning individuals like in our annual samples but not in the cohorts if immigrants are spawning individuals. This is because immigrants coming into the spawning grounds and mixing with the local cod will result in a Wahlund effect, but the resulting cohort would be in Hardy–Weinberg equilibrium. There was, however, almost the same magnitude of deviation from Hardy–Weinberg expectation in the cohorts as in the annual samples, with respect to trend of heterozygote deficiency and overall departure from Hardy–Weinberg equilibrium. Also, there was no significant temporal trend in allele frequencies as would be expected by a frequent effect of immigrants from a population characterized by allele frequencies different from that of the local population.
Compared with several other microsatellite loci in cod, Gmo2 has shown the largest or among the largest heterozygote deficiencies in several independent studies, but has also shown relatively low or moderate levels of differentiation among populations (Bentzen et al., 1996; Ruzzante et al., 1996, 2000a, b). If this tendency of Gmo2 to show deficits of heterozygotes is caused by a Wahlund effect, it would require considerable differentiation among the involved populations, which apparently is not the case. The Gmo132 locus has, on the other hand, not shown a general tendency of Wahlund effects compared with other loci in the studies mentioned above, although Gmo132 showed the highest level of differentiation.
Null alleles
A Wahlund effect hypothesis is not consistent relative to observations in the present and previous studies of cod in Trondheimsfjord (e.g. Mork et al., 1985; Mork and Giæver, 1999; Karlsson and Mork, 2003). An alternative or additional explanation to the observed heterozygote deficiencies might be the presence of null alleles (O'Connell and Wright, 1997, and references therein). An attempt to check for null alleles in our microsatellite data did not give any clear-cut conclusion because the general trend of excess of homozygotes was seen at both loci. Such an observation could be ascribed to both null alleles and Wahlund effects. Apart from sequencing the flanking regions of Gmo2 and Gmo132, the only possible observations that could support the presence of null alleles at these two loci are the absence of heterozygote deficiencies at other loci. Previous isozyme studies on this spawning ground did not show any heterozygote deficiencies at PGM-1*, MDH-3*, IDHP-1*, and PGI-2* (Mork et al., 1985; Mork and Giæver, 1999). On the contrary, an excess of heterozygotes was observed at the PanI locus (Karlsson and Mork, 2003) among cod samples that included the same individuals as in the present study. The PanI locus is, however, an unreliable marker in detecting a Wahlund effect because it appears to be affected by natural selection (Karlsson and Mork, 2003; Pogson and Fevolden, 2003).
Temporal variation
The unusually high genetic differentiation among geographic populations at Gmo132 (Bentzen et al., 1996; Ruzzante et al., 1996, 1998, 2000a; Knutsen et al., 2003; Lage et al., 2004) prompted this study of the temporal stability of allele frequencies at this locus in one population. Our observations indicate that there may be a correlation between levels of local temporal variability and levels of geographic variability at Gmo132. This is similar to observations at the PanI locus in a previous study (Karlsson and Mork, 2003). The Gmo2 locus, on the other hand, has shown low or moderate levels of geographic differentiation and did not show local temporal variation.
If one or more relatively large populations of cod were giving off immigrants to the spawning population in Verrasundet, causing the observed variation in allele frequency at Gmo132, one would expect the allele frequencies to homogenize among the donor and the recipient populations in a relatively short period of time, and to exhibit a directional trend over time in allele frequencies within the local population. Alternatively, if donor populations giving off immigrants to Verrasundet were relatively small and influenced by strong genetic drift, a balance might develop between gene flow and genetic drift that could maintain the high allelic variability observed in Verrasundet, and also contribute to the observed variation in allele frequencies. Such a system would be very complicated, and the definition of the populations would be very difficult.
The Trondheimsfjord cod is very well studied. Results from tagging experiments (Sundnes, 1980) do not indicate the existence of more than one population of cod there. Sexually mature cod show a cyclical migration pattern within the fjord. After spawning in Verrasundet, cod disperse into the main fjord and remain there until the next spawning season. Only a small proportion (1.5%) of tagged fish have been recaptured outside Trondheimsfjord 5 years after release (Sundnes, 1980). Furthermore, tagging experiments performed by the Institute of Marine Research (IMR, Bergen, Norway) have shown that Trondheimsfjord receives virtually no individuals from coastal or oceanic areas outside the fjord (O.R. Godø, IMR, pers. comm.). We find it, therefore, reasonable to regard cod in Trondheimsfjord as a self-recruiting unit (local population). The eggs and larvae from the Verrasundet spawning will drift to different parts of the Trondheimsfjord by the estuarine circulation, and the pelagic codlings settle correspondingly. The environmental factors may be different at the various settling locations, and the size of the settled group may vary widely. These conditions may give rise to both selection effects (Levene, 1953) and genetic drift effects in the various groups, which will affect their characteristics when they assemble as matures to spawn in the Verrasundet some 4 years later. Hence, a pseudo Wahlund effect may occur in samples from the Verrasundet spawning population which merely reflects their different life histories prior to maturation. The dynamics of such a system could explain the maintenance of the high genetic variation, heterozygote deficiency, and temporal variation in allele frequencies observed in Verrasundet, both for neutral and non-neutral markers (see Karlsson and Mork, 2003). However, Mork et al. (1985) and Mork and Giæver (1999) did not observe deviations from Hardy–Weinberg equilibrium in Trondheimsfjord cod at isozyme loci. A Wahlund effect is expected to be locus-independent and could explain the observed deficiencies of heterozygotes at both loci. However, because there was a lack of temporal fluctuation in allele frequencies at Gmo2 compared with Gmo132, a Wahlund effect appears as an unlikely explanation. It is, therefore, reasonable to believe that there is a locus-dependent effect, such as null alleles, creating the deficiencies of heterozygotes, and natural selection, creating the observed temporal fluctuation in allele frequencies at Gmo132. Since there is no a priori support to assume that microsatellites are non-functional or selectively neutral (Kashi and Soller, 1999), we cannot exclude the possibility that the apparent differences observed between Gmo132 and Gmo2 are due to the effects of natural selection at Gmo132. It is, however, too early to draw such a conclusion. Instead, further investigations are needed to understand the dynamics of the Gmo132 polymorphisms in Trondheimsfjord. For example, information is needed on the genotypic composition of young-of-the-year cod, and the extent of genetic heterogeneity between young cod habitats.
In conclusion, the observed deficiencies of heterozygotes at Gmo132 and Gmo2 are most likely caused by null alleles, but some form of a pseudo Wahlund effect caused by a patchy distribution of habitats for young cod within the Trondheimsfjord cannot be ruled out as a cause. The difference between Gmo132 and Gmo2 in their temporal fluctuation in allele frequencies indicates that there is a locus-dependent effect, such as natural selection, responsible for the significant temporal instability of allele frequencies at Gmo132. In any case, the allele frequencies at Gmo132 in Trondheimsfjord cod show so much temporal heterogeneity that a characterization of the population by this locus is bound to be unreliable. This suggests that conclusions about genetic differentiation among geographically separated groups of cod based on this locus should be drawn with care.
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Acknowledgements |
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We would like to thank B. I. Honne and J. Gold for valuable advice, and Bill Hutchinson for the help with the interpretation of the results from the MICRO-CHECKER program. We also thank Pierre Pepin and two anonymous referees who greatly contributed to improving this paper. The study was supported by grant number: NFR 145336/432 from the Norwegian Research Council.
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References |
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