Allozymic variation in Northeast Atlantic and Mediterranean populations of Norway lobster, Nephrops norvegicus

Abstract

Allozyme starch gel electrophoresis was used to investigate the genetic structure of Nephrops norvegicus populations in an extended sampling scheme. Nine populations from the North Sea and Aegean Sea were sampled and analysed using ten enzymatic systems corresponding to 15 putative loci. Values of heterozygosity were similar between Atlantic and Mediterranean population samples, ranging from 0.165 to 0.187. Genetic distance estimates, F_ST analyses and tests for genetic differentiation revealed a heterogeneous genetic structure within the sampling area of N. norvegicus. No evidence was found of past separation of Atlantic and Mediterranean populations, agreeing with the results of previous allozymic and mitochondrial genetic studies of N. norvegicus. Data are compared with genetic studies of other marine crustaceans and fish, and the implications for management of N. norvegicus stocks are discussed.

Introduction

The Norway lobster, Nephrops norvegicus, is a relatively sedentary marine benthic crustacean with a wide geographical distribution. It extends from the North Sea, south to Morocco, and east into the whole Mediterranean Sea (Farmer, 1975). It is a species of great commercial interest throughout its geographic range, with annual landings of approximately 60 000 t (FAO, 1995), making it one of the most valuable lobster resources in the world.

Considerable research has been devoted to the study of N. norvegicus biology and fisheries throughout its geographic range with regard to reproduction, ethology, and growth (Froglia and Gramitto, 1987; Sardà, 1995; Maynou and Sardà, 1997; Stergiou et al., 1997; Tuck et al., 1997). Little information exists, however, about its population spatial structure. Its patchiness and varied density have been mainly correlated with the heterogeneous nature of the sediment and the production of pelagic larvae, whose dispersal is dependent on sea currents (Hill, 1990).

Analysis of genetic structure is especially important for species with ecological and commercial value. Genetic substructuring of a species is important knowledge for managing harvested species and can be used to predict whether a locally depleted population will be successfully repopulated by immigrants (Utter, 1991). Marine species in particular are expected to show shallow population structures because, inter alia, of their perceived large population sizes, great potential for dispersal, and the absence of restrictions to gene flow (Graves, 1998).

The use of genetic markers has contributed greatly to the understanding of evolutionary processes, relationships, and the genetic structure of taxa at inter- and intraspecific levels. It has contributed substantially to the definition of evolutionary significant units and management stocks, complementing other approaches such as morphological differences, temporo-spatial distribution of fisheries, and egg distribution (Carvalho and Hauser, 1995).

Molecular markers that have been used to shed light on the population structure of species have entailed mostly allozymes, mitochondrial DNA, and microsatellites (Lowe et al., 2004). Most work on N. norvegicus has focused on allozyme analyses of a limited number of populations. Early allozymic genetic studies based on small sample sizes of two Adriatic samples did not reveal population differentiation (Mantovani and Scali, 1992). Allozyme analyses on one Scottish and two Aegean populations (Passamonti et al., 1997) also failed to show genetic differentiation between these and the two Adriatic populations. Maltagliati et al. (1998), studying mostly Mediterranean populations as well as an additional one from Faro (off South Portugal), found significant levels of genetic differentiation, but without a clear geographical pattern. Microsatellite markers have shown remarkably high polymorphism within two populations from the Portuguese coast, but also no significant differentiation among them (Streiff et al., 2001). Finally, in the most extensive analysis of the genetic structure of 12 populations of N. norvegicus across the distribution of the species (based, this time, on mitochondrial RFLP analysis, Stamatis et al., 2004), results agreed with those of Maltagliati et al. (1998) in terms of the significant differentiation of populations, but without geographic structure.

Extended analyses of the genetic structure of N. norvegicus populations are few. The importance of a multidisciplinary approach, and the simultaneous analysis of different genetic markers with different characteristics (mode of mutation, evolution, etc) have often been stressed (Estoup et al., 1998). For example, mtDNA studies provide only a single “gene tree” that might not accurately reflect the “organismal tree”, because the entire mitochondrial genome acts as a single genetic locus (Degnan, 1993).

This work complements the study of Stamatis et al. (2004), because it analyses by means of starch gel electrophoresis most of the N. norvegicus population samples that have already been studied by mitochondrial DNA RFLP analysis in that study. The aim is to improve information on the population structure of Northeast Atlantic and Mediterranean Sea N. norvegicus populations. Results are also compared with other genetic studies of N. norvegicus and various marine crustacean or fish species. Possible differentiation between the Mediterranean Sea and the Atlantic Ocean is also tested. Results are also discussed with respect to biological parameters of N. norvegicus. These investigations help to determine whether the populations examined may be considered to have been drawn from the same pool.

Material and methods

The N. norvegicus samples examined came from nine different geographical sites (Figure 1, Table 1). Specimens were collected from commercial trawlers and arrived in the laboratory in ice. Tissues (white muscle and hepatopancreas) were removed from each specimen and kept at −40°C until analysed. Standard horizontal starch gel electrophoresis was used to investigate the genetic composition of these populations. Ten enzymatic systems were investigated: acid phosphatase (ACP, EC 3.1.3.2), adenosine deaminase (ADA, EC 3.5.4.4), alkaline phosphatase (AKP, EC 3.1.3.1), esterase (EST, EC 3.1.1.-), NAD-glucose dehydrogenase (GLC, EC 1.1.1.47), malate dehydrogenase (MDH, EC 1.1.1.37), malic enzyme (MEE, EC 1.1.1.40), 6-phosphate-glucose isomerase (PGI, EC 5.3.1.9), xanthine dehydrogenase (XDH, EC 1.2.1.37), and xanthine oxidase (XOO, EC 1.2.3.2) tissues, buffers, and electrophoretic conditions were according to Macaranas et al. (1995) and Mamuris et al. (1998). Nomenclature followed Shaklee et al. (1990).

Figure 1

Sampling sites for nine studied populations of Nephrops norvegicus.

Table 1

Sampling localities, corresponding list of abbreviations, and sample date for the nine Nephrops norvegicus populations studied.

	Sampling site	Abbreviation	Date
1	Pagasitikos	PAG	01/99
2	Platanias	PLA	05/00
3	Keramidi	KER	06/98
4	Evia	EVI	09/98
5	Alonnisos	ALO	01/99
6	North Sea 1	NS1	08/99
7	North Sea 2	NS2	08/99
8	North Sea 3	NS3	09/99
9	North Sea 4	NS4	09/99

Allele frequencies in population samples and genetic variation parameters, i.e. mean numbers of alleles per locus, unbiased expected heterozygosity (Nei, 1987), and observed heterozygosity values, were calculated with the program GENETIX 4.02 (Belkhir et al., 2001). The program GENEPOP 3.3 (Raymond and Rousset, 1995) was used to perform probability tests for conformance of genotypic distribution to Hardy–Weinberg expectations for each locus, and estimating the significance of allelic differentiation among the entire set or between pairwise population samples. Corrections for simultaneous multiple comparisons were applied using sequential Bonferroni correction (Rice, 1989).

The computer program FSTAT 2.9.3 (Goudet, 2001) was used to determine Weir and Cockerham's (1984) theta (θ) statistics [unbiased estimates of Wright (1951),F-statistics], and the statistical departure from zero of values of F_IS and F_ST using 5000 permutations in each case. The genetic distances between populations were estimated using Nei's (1978) distance with the program GENDIST, included in the package PHYLIP 3.6 (Felsenstein, 2004). Dendrograms were constructed and bootstrap estimates were calculated using various options of the PHYLIP 3.6 package (Felsenstein, 2004).

Results

The ten enzymatic systems analysed corresponded to 15 clearly recognizable presumptive gene loci. Nine of these 15 loci were monomorphic in the nine population samples examined, whereas loci ADA-1, ADA-2, EST-1, EST-2, GLC-1, and MEE-1 were polymorphic. In these 15 loci, 23 different alleles were found (Table 2). No locus presented more than three alleles. Only one allele was private for one population sample (allele EST-1∗2 in the ALO population), but in very low frequency. All the other alleles were shared between all samples. There was no evident cline in the frequencies of these alleles at any locus (Table 2).

Table 2

Loci, alleles, allele frequencies, sample size (n), mean number of alleles per locus (Mean), percentage of polymorphic loci (P), and observed (H_o) and expected (H_e) heterozygosity in the populations examined (s.e. in parenthesis).

	Population
Locus	PAG	PLA	KER	EVI	ALO	NS1	NS2	NS3	NS4
ADA-1
1	0.664*	0.581	0.545	0.575	0.650	0.450	0.600	0.500	0.510
2	0.336	0.419	0.455	0.425	0.350	0.550	0.400	0.500	0.490
ADA-2
1	0.452	0.403	0.477*	0.250	0.175	0.400	0.450	0.585	0.521
2	0.548	0.597	0.523	0.750	0.825	0.600	0.550	0.415	0.479
EST-1
1	1.000	1.000	1.000	1.000	0.975	1.000	1.000	1.000	1.000
2	0.000	0.000	0.000	0.000	0.025	0.000	0.000	0.000	0.000
EST-2
1	0.394*	0.565	0.545	0.575	0.525	0.550	0.520	0.671	0.510
2	0.337	0.274	0.250	0.275	0.225	0.250	0.160	0.207	0.240
3	0.269	0.161	0.205	0.150	0.250	0.200	0.320	0.122	0.250
GLC-1
1	0.351*	0.371*	0.500*	0.525*	0.625*	0.500*	0.360*	0.500*	0.396*
2	0.457	0.484	0.250	0.275	0.250	0.283	0.280	0.256	0.250
3	0.192	0.145	0.250	0.200	0.125	0.217	0.360	0.244	0.354
MEE-1
1	0.452	0.516	0.500	0.525	0.600	0.483	0.530	0.524	0.542
2	0.548	0.484	0.500	0.475	0.400	0.517	0.470	0.476	0.458
n	104	31	22	20	20	30	50	41	48
Mean	1.5	1.5	1.5	1.5	1.5	1.5	1.5	1.5	1.5
P†	0.33	0.33	0.33	0.33	0.40	0.33	0.33	0.33	0.33
Ho	0.108 (0.042)	0.151 (0.060)	0.167 (0.069)	0.113 (0.047)	0.140 (0.059)	0.140 (0.054)	0.141 (0.055)	0.122 (0.047)	0.142 (0.055)
He	0.183 (0.065)	0.180 (0.068)	0.185 (0.071)	0.174 (0.067)	0.165 (0.063)	0.183 (0.070)	0.184 (0.071)	0.176 (0.067)	0.187 (0.071)

Loci ACP-1, AKP-1, MDH-1, MDH-2, MDH-3, MEE-2, PGI-1, XDH-1, and XOO-1 were monomorphic in all populations examined.

*

Indicates deviation from Hardy–Weinberg equilibrium.

†

A locus is considered polymorphic if more than one allele was detected.

All population samples showed similar values of variability with similar mean number of alleles per locus (1.5) and percentages of polymorphic loci (33.3–40.0). The values of expected heterozygosity were also similar, ranging from 0.165 to 0.187 (Table 2). Most loci examined were in agreement with Hardy–Weinberg expectations. However, for the GLC-1 locus, the H–W exact tests were statistically significant for all nine population samples (even after Bonferroni correction), in all cases because of heterozygote deficiency. Only three additional tests of the remaining 37 tests for Hardy–Weinberg equilibrium were statistically significant (p < 0.05) in terms of deviation from expected results (Table 2).

The F_ST value for all N. norvegicus populations revealed a heterogeneous genetic structure among all samples (0.013, p < 0.001). This differentiation is mostly due to loci ADA-2 and GLC-1 (Table 3). This agrees with global genetic heterogeneity probability tests of N. norvegicus populations (not shown), which indicated that there are highly significant differences (p < 0.001) in the allele and genotypic frequency distributions only at these two loci.

Table 3

Estimates of Weir and Cockerham (1984)F_IS and F_ST statistics for each locus. Results of permutation testing of significant departure from zero are also given (*p < 0.05, **p < 0.01, and ***p < 0.001).

Locus	FIS	FST
ADA-1	0.267***	0.008
ADA-2	0.045	0.032***
EST-1	−0.013	0.015
EST-2	0.337***	0.011
GLC-1	0.539***	0.020*
MEE-1	0.132**	0.007
All	0.282***	0.013***

Results of pairwise genetic heterogeneity tests (based on allele frequency distributions) showed that 12 of 37 tests were statistically significant (six after Bonferroni correction), most concerning the comparison of the PAG and ALO population samples to NS2-4 samples. However, there were statistically significant differences even among close geographical samples (i.e. PAG–ALO and NS2–NS3). The absence of a clear geographical pattern of genetic differentiation among the populations studied is further evident in the UPGMA dendrogram (Figure 2), constructed on the basis of Nei's (1978) genetic distances (Table 4). Population samples cluster in three groupings: samples PAG with PLA, North Sea and KER samples, and EVI and ALO samples. These groupings are not supported by high bootstrap values (all were lower than 65%, out of 1000 iterations). The same groupings were also evident when constructing Neighbour Joining or CONTML dendrograms (not shown).

Figure 2

UPGMA clustering of nine Nephrops norvegicus populations, based on Nei's (1978) genetic distance.

Table 4

Values of Nei's (1978) genetic distance (below diagonal) among the populations examined, based on allozyme frequency data from 15 enzyme loci.

	PAG	PLA	KER	EVI	ALO	NS1	NS2	NS3	NS4
Pagasitikos
Platanias	0.0030
Keramidi	0.0056	0.0040
Evia	0.0090	0.0048	0.0046
Alonnisos	0.0141	0.0105	0.0104	0.0026
North Sea 1	0.0077	0.0041	0.0013	0.0034	0.0096
North Sea 2	0.0053	0.0054	0.0026	0.0072	0.0122	0.0048
North Sea 3	0.0114	0.0071	0.0021	0.0103	0.0186	0.0041	0.0063
North Sea 4	0.0068	0.0061	0.0014	0.0086	0.0158	0.0032	0.0016	0.0030

Discussion

Nephrops norvegicus populations seem to share similar values of genetic variability, exemplified by the results of this study. Populations sampled in both Mediterranean and Atlantic sites exhibit a value of 1.5 for mean number of alleles per locus, whereas expected heterozygosity levels were from 0.165 to 0.187 (Table 2). These levels are close to allozymic heterozygosity values reported for other marine invertebrates (0.131–0.298 for Chthamalus crustacean species, Pannacciulli et al., 1997; 0.043–0.066 for rose shrimp Aristeus antennatus, Sardà et al., 1998; 0.176 ± 0.052 for oysters, Saavedra et al., 1995; 0.022–0.076 for cuttlefish Sepia officinalis, Perez-Losada et al., 1999). Additionally, there does not seem to be any trend for Atlantic samples possessing lower variability than Mediterranean ones, as in oysters (Saavedra et al., 1995) or crustacean Chthamalus species (Pannacciulli et al., 1997), though see also the paper of Triantafyllidis et al. (2005) for a reverse trend in the European lobster).

Maltagliati et al. (1998) reported heterozygosity values for N. norvegicus populations between 0.052 and 0.142. These values are generally lower than those obtained in this study. Direct comparisons are, however, not easy to make owing to the different populations and sets of enzymes studied. The only common population sample between the two studies is from Evia (Greece). Additionally, only one polymorphic enzyme (MEE) from this study was also analysed by Maltagliati et al. (1998). The only other polymorphic locus of 11 polymorphic loci found by Maltagliati et al. (1998) that was included in this analysis was the XDH-1 locus, which was, however, monomorphic in our set of samples.

The GLC-1 locus did not conform to Hardy–Weinberg expectations in all populations. Additionally, F_IS values for each population (not shown) point to high heterozygote deficits. Often reported explanations in the literature (e.g. Garcia de Leon et al., 1997) such as inbreeding, the existence of subpopulations (Wahlund effect), or assortative mating phenomena can be ruled out because they affect the whole genome and not only one locus. Therefore, possible explanations are selection phenomena correlated with adaptive characteristics and/or technical artefacts (null alleles).

Results of this study based on genetic distance estimates, F_ST analyses, and tests for genetic differentiation revealed a heterogeneous genetic structure within N. norvegicus. The analysis of genetic differentiation by F_ST statistics gave a significant mean value (F_ST = 0.013, p < 0.001), indicating a low, but significant, population structuring across the distribution of the species. There were no signs, however, of an Atlantic–Mediterranean division. The UPGMA tree constructed (Figure 2) showed that populations form clusters, weakly supported by bootstrap analysis, which do not correspond to geographical proximity.

The differentiation found within the species is much lower than observed at allozyme, mitochondrial DNA, or nuclear DNA level for other marine species with an eastern Atlantic and Mediterranean distribution. Values of F_ST in the range 0.02–0.50 have been reported in the literature when comparing Atlantic with Mediterranean fish populations (Borsa et al., 1997, and references therein). In the few studies of marine invertebrates with a similar distribution, high differentiation has been found for European lobster (mitochondrial F_ST = 0.078, Triantafyllidis et al., 2005), oysters Ostrea edulis (allozymic F_ST = 0.082, Saavedra et al., 1995; and microsatellite F_ST = 0.019, Launey et al., 2002), cuttlefish Sepia officinalis (allozymic F_ST = 0.220, Perez-Losada et al., 1999; microsatellite F_ST = 0.061, Perez-Losada et al., 2002), and the crustacean Meganyctiphanes norvegica (F_ST = 0.1475, Zane et al., 2000), some of the above species presenting “Atlantic” alleles completely different from “Mediterranean” ones.

Molecular phylogeographic analyses have yielded contradictory results about the hypothesis that the Straits of Gibraltar constitute a boundary for a number of plankton-dispersing Mediterranean–Atlantic taxa. For some species there is no differentiation between the two basins (Borsa et al., 1997; Sardà et al., 1998; Pujolar et al., 2003; Karaiskou et al., 2004), whereas for other species, Atlantic and Mediterranean populations are clearly genetically heterogeneous. Genetic differences between the basins have been documented, e.g. in the molluscs Mytilus galloprovincialis (Quesada et al., 1998; Ladoukakis et al., 2002), Ostrea edulis (Saavedra et al., 1995; Launey et al., 2002), and Sepia officinalis (Perez-Losada et al., 1999, 2002), in crustaceans (Pannacciulli et al., 1997; Zane et al., 2000), and in a number of fish (Kotoulas et al., 1995; Borsa et al., 1997; Bargelloni et al., 2003). Phylogeographic breaks observed in several taxa at the Straits of Gibraltar or in the Alboran Sea region (western Mediterranean) have been attributed to hydrological conditions preventing migration either in the Pleistocene or recent times, or both. Yet the question remains open as to why different species react apparently differently to the same historical contingencies, with possible proposed reasons being differences in dispersal capacity and/or effective population sizes among species (Bargelloni et al., 2003).

Our results clearly agree with the results of earlier works on the genetic structure of N. norvegicus populations. Mitochondrial DNA analysis of the same population samples (plus two samples from Ireland and Portugal) has also revealed low, but significant, levels of genetic differentiation, without signs of an Atlantic–Mediterranean divide. However, the present article is based on diploid variation (nuclear genome) at allozyme loci, while the earlier one was based on evidently linked variation, because mitochondrial DNA generally constitutes a single genetic unit. Therefore, the lack of a phylogeographic pattern of genetic variation in this marine species is strongly supported both with diploid coding (supposedly independent) loci, and mitochondrial markers. As reported by Stamatis et al. (2004), it seems that the most likely explanation for this pattern of low differentiation is a recent demographic expansion of N. norvegicus populations, without sufficient time for the populations to diverge and to reach mutation/drift equilibrium. Therefore, no attempt was made to estimate parameters such as gene flow among populations.

The allozymic study of Maltagliati et al. (1998) of N. norvegicus populations also revealed no specific geographic structure, although the F_ST value for those data was an order of magnitude higher (F_ST = 0.122). This higher value may be attributable to the particular enzymes used in that study, which might be under the influence of selection phenomena.

Gene flow that prevents the accumulation of genetic drift among geographically distant populations cannot be ruled out for N. norvegicus populations. However, adult animals are burrowing, and their movements are affected and restricted by suitable habitat. Therefore, pelagic dispersal alone cannot support gene flow among such distant areas as the Mediterranean Sea and the North Sea. On the other hand, it cannot be excluded that within areas such as the Atlantic, single panmictic populations exist. This has been observed for the krill Meganyctiphanes norvegica (Zane et al., 2000). However, detailed microgeographical analyses are needed with molecular markers that can detect microdifferentiation. For example, most Atlantic populations of the European lobster Homarus gammarus seem to constitute one panmictic population, based on mitochondrial DNA analyses (Triantafyllidis et al., 2005), but microsatellite analyses of even closely situated populations reveal genetic differentiation even at a microgeographical level (Ferguson et al., 2002).

Our results (like previous studies on N. norvegicus cited already) indicate that the genetic population structuring of N. norvegicus populations fits an island model of structure. The management importance of recognizing such a population structure is that, if there is overharvesting, populations will not be replenished by recruitment from elsewhere in a meaningful time period. Additionally, managers and decision-makers need to take into account the fact that although the overall level of genetic differentiation among N. norvegicus populations is low, this does not mean that important interpopulation adaptive genetic differences are absent. Delimitation of a local stock is not straightforward, and should always be based on a combination of hydrographic, biological, and genetic information. The current results help in that direction, hopefully aiding better management of Norway lobster stocks. Given the high value of the resource and the decline of the stocks in several areas, all information that improves management should prove useful.

We are indebted to Professor C. Triantaphyllidis for many fruitful discussions, to Nick Bailey for arranging collection of the North Sea samples, to G. Petrakis for arranging collection of the Greek samples, and to V. Varfi for technical assistance. The financial support of the Prefecture of Magnesia, Greece, is gratefully acknowledged. Finally, we thank two anonymous reviewers and the editor for their useful comments on earlier drafts.