20. the molecular ecology of dogfish sharks - fisheries.org · the application of molecular genetic...

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* [email protected]

20. The Molecular Ecology of Dogfish SharksLorenz Hauser*

School of Aquatic & Fishery Sciences, University of Washington, Box 355020, Seattle, Washington 98195, USA

Abstract.—The molecular ecology of many elasmobranchs, including dogfish, is still in its infancy, with phylogeographic, population genetic, and mating structure data restricted to a few species. Here, I describe the applications of molecular genetic methods, in sharks in general and in dogfish specifi-cally, to issues ranging from broad-scale vertebrate phylogenies to taxonomic problems, identification of population structure and multiple paternity, and, as an outlook, genome-enabled investigations. New molecular data from dogfish are also presented. Sequence data suggest two distinct clades of dogfish in the North Pacific and Atlantic/South Pacific whose taxonomic position is uncertain but which repre-sent independent evolutionary lineages. No genetic differentiation was detected in populations in the northeast Pacific, though the evolutionary dynamics of molecular markers indicate that ecologically independent populations may still exist. A recent collection of large amounts of sequence data from coding genes of dogfish provides exciting opportunities for future research, which should be carried out in close integration with ecological and environmental data.

Biology and Management of Dogfish Sharks, 229–252© 2009 by the American Fisheries Society

IntroductionThe application of molecular genetic markers to questions in ecology and evolution has revolution-ized our understanding of the living world. From unambiguous phylogenies and species identification and the estimation of population differentiation and migration rates to the quantification of relatedness and parentage assignment, molecular genetics has provided powerful insights into the evolution and maintenance of biodiversity. Compared to more traditional methods, molecular genetics has led to important paradigm shifts in the natural sciences (Hauser and Carvalho 2008), such as a revision of metazoan evolution (Winchell et al. 2002), the development of metapopulation concepts (Olivieri and Gouyon 1997), speciation theories (Turelli et al. 2001), and a complete transformation of our understanding of sexual selection and reproductive success in wild populations (Andersson and Sim-mons 2006). Such insights are likely to be expanded to a more mechanistic understanding of local ad-aptation and selection owing to genome-enabled technologies that are rapidly allowing investigation

of nonmodel species (Wilson et al. 2005). Molecular genetic methods have therefore pervaded most of the biological sciences and are now an integral part of ecological research.

Elasmobranchs have generally received less at-tention than bony fish despite their ubiquitous pres-ence, increasing importance in commercial fisheries, conservation concerns, and charisma in the public opinion. In part, the concentration on bony fishes is due to their greater economic importance, though difficulties in acquiring sufficient samples in often cosmopolitan elasmobranch species is certainly a contributing factor. Nevertheless, molecular genetic data on elasmobranchs are accumulating, reflect-ing an increasing interest in this group of fishes that is due not only to fisheries and conservation concerns, but stems also from more fundamental scientific issues such as comparisons of genomic and ecological features among phylogenetically distant groups. Spiny dogfish Squalus acanthias has been the “model shark” for some time and has been used as a comparative species for many phylogenetic comparisons—there is therefore a plethora of genetic, morphological, and physiological data on dogfish that can be used to further investigate the biology of the species itself.

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Spiny dogfish are one of the most abundant sharks and as such support targeted fisheries in both the Atlantic and Pacific oceans. They have a worldwide antitropical distribution and have been described as different species, subspecies, and populations in dif-ferent parts of their distribution (Compagno 1984). Life-history parameters differ considerably between different parts of the species’ range: Atlantic and South Pacific populations attain smaller maximum length, mature faster, and are less long-lived than their North Pacific counterparts (Henderson et al. 2002). Dogfish are described as slow, inactive swim-mers, though seasonal migrations have been reported in the western Atlantic, and tagging experiments have provided evidence for occasional transoceanic migration in both the Atlantic (Templeman 1976) and Pacific (McFarlane and King 2003). Dogfish are ovoviviparous: offspring hatch internally from eggs without placental attachment to the mother (Tribuzio 2009, this volume). Reproduction is slow, with about 22 months gestation and 2–17 offspring per clutch. Slow reproduction together with slow growth makes the species particularly vulnerable to fishing pressure, and thus more information about biology and ecology is required to adequately manage fisheries and conserve the species.

Here, I provide an overview of the contribution of molecular genetics to the study of the ecology and evolution of sharks in general and dogfish spe-cifically, ranging from phylogenetics and species identification to population genetics and paternity determination. Rather than providing an exhaustive review of molecular applications, which are provided elsewhere (Park and Moran 1994; Parker et al.1998; Feral 2002; de Bruin et al. 2003; Schlötterer 2004), I will discuss pertinent questions in dogfish biology and ecology highlighting the power of molecular approaches. A summary of commonly used methods is presented in Table 1. I will also consider future re-search made possible by recent advances in genomic technology, which could be particularly relevant for dogfish research.

Phylogenetics and TaxonomyBroad-scale phylogenyMolecular data have contributed greatly to the recon-struction of chondrichthyan phylogenies and have resolved long standing disputes at several taxonomic levels. Elasmobranchs have long been considered to be a “primitive” group derived from a basal lineage

of the vertebrate tree. The last common ancestor of chondrichthyes, sarcopterygii (lobe-finned fishes), and actinopterygii (ray-finned fishes) lived about 450–500 million years ago, providing a deep split within the vertebrates that is useful for compara-tive investigations on vertebrate evolution (Martin 2001). Examples for such studies include genes of the major histocompatibility complex (MHC) that is involved in immune response (Hashimoto et al. 1999; Kulski et al. 2002), hox gene clusters (Chiu et al. 2002), genome duplication events in early vertebrate history (Robinson-Rechavi et al. 2004), the evolution of morphological features such as swim bladders and lungs, and the monophyly of crossopterygians (Arnason et al. 2004). A common assumption of such studies is that sharks represent the most basal gnathostomes (jawed vertebrates); that is, elasmobranchs split from the rest of the jawed vertebrates before any other group. For example, many vertebrates carry several often tissue-specific isoforms of the enzyme lactate-dehydrogenase (LDH). Comparisons of LDH sequences between dogfish and other vertebrates have suggested diver-gence between LDH-B and other loci before the split between teleosts and chondrichthyans (Stock and Powers 1998). However, the significance of this finding for the evolution of LDH in tetrapods depends on the assumption of a basal position of chondrichthyans in the evolutionary tree. Recent molecular research based on mitochondrial and nuclear genes questions this assumption (Arnason et al. 2001; Martin 2001; Naylor et al. 2005), and whole mitochondrial genomes support the idea of an early split between tetrapods and fishes and of teleosts and chondrichthyans as sister taxa (Arnason et al. 2004). Some nuclear gene trees support this notion while others do not, instead placing sharks at the base of the vertebrate tree (Martin 2001). Therefore, additional sampling of the nuclear genome and ver-tebrate taxa is necessary to resolve the phylogenetic relationships between chondrichthyans, teleosts, and tetrapods (Arnason et al. 2004).

Within elasmobranchs, phylogenetic relation-ships are similarly unresolved, despite 150 years of formal study (see Naylor et al. 2005 for a review). Morphologically based phylogenetic work has been hampered by ubiquitous character homoplasy and difficulty in establishing homology among characters (de Carvalho 1996). Although the long phylogenetic history of sharks also causes problems with mo-lecular analyses, molecular markers have provided

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DNA region Method Notes References

Phylogenetic reconstruction Mitochondrial DNA (mtDNA)

Sequencing, RFLP No recombination, hence easier reconstruc-tion of relationships; inherited as a single unit, but different sections have different mutation rates (e.g. COI vs. D-loop)

Rasmussen and Arna-son 1999; Arnason et al. 2004; Ballard and Whitlock 2004

Nuclear DNA Sequencing, RFLP Inherited independently from mtDNA and each other – provide additional gene trees

Shaw 2002; Winchell et al. 2004

Species identificationMitochondrial DNA (mtDNA)

Sequencing, RFLP See also Barcode of Life project (www.barcodinglife.org/)

Hebert et al. 2003; Ward et al. 2005

Population identification, migration ratesEnzyme coding loci Histochemical

staining—allozymesLow variability relatively low power, lim-ited number of loci

Richardson et al. 1986

MtDNA Sequencing, RFLP, SNPs

Maternally inherited smaller Ne, female migration only

Ovenden 1990

Microsatellites PCR—length variation Highly variable, higher power of statistical tests

Selkoe and Toonen 2006

Single nucleotide polymorphisms (SNPs)

Various—mostly PCR based without electro-phoresis

Higher screening throughput, difficult detec-tion. Can be mitochondrial or nuclear

Morin et al. 2004

ParentageMicrosatellites PCR—length variation Can be problematic because of incomplete

sampling and genotyping errorsWilson and Ferguson 2002

Table 1. Molecular methods commonly used in phylogenetics, species, and population identification, and in parentage analyses. The DNA regions commonly analyzed, methods used, pertinent features, and relevant references are shown.

additional systematic information, for example, by refuting the hypothesis that rays are derived sharks, instead placing Batoidea and other sharks into two distinct groups (Douady et al. 2003). Interestingly, molecular data also provided evidence for paraphyly of morphologically defined taxonomic groups, such as the catshark family (Scyliorhinidae) and the Triakidae (Iglesias et al. 2005; Human et al. 2006). Such taxonomic uncertainties emphasize the need for a revision of shark phylogenies: recent advances in genome technology now provide the means to assay a large number of sequences, which demonstrably improves the resolution of resulting phylogenetic trees (Sanderson and Shaffer 2002 ; Chen et al. 2004; Gatesy and Baker 2005; ).

Taxonomy of the genus SqualusDespite its commercial importance, ubiquity, and us-age as scientific “guinea pigs,” the genus Squalus still

is taxonomically difficult. The FAO species catalog (Compagno 1984) lists nine Squalus species: Squalus acanthias with a worldwide temperate distribution on both hemispheres, and eight other, more local-ized species (S. asper, S. blainvillei, S. cubensis, S. japonicus, S. megalops, S. melanurus, S. mitsukurii, S. rancureli) (see Kriwet and Klug 2009, this volume, for a fossil record perspective on squaliform sharks). In addition, six species have recently been described in Australia (Last et al. 2007), and other cryptic spe-cies may exist elsewhere. FishBase (Froese and Pauly 2006) lists a total of 34 species, and although many may be synonyms for the nine species described by Compagno (1984), others may constitute valid species requiring formal description. Both taxonomy and phylogeny of the genus Squalus need urgent revi-sion, in particular as Squalus species are increasingly the target of commercial fisheries that could easily endanger localized cryptic species.

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Since the onset of their development, molecular markers have been used for such taxonomic prob-lems. A recent and more concerted effort in that field is the Barcode of Life project (www.barcodinglife.org/), which aims to provide a database of DNA sequences (commonly, the mitochondrial DNA cy-tochrome oxidase I gene, COI) of all extant species on earth as barcodes, similar to commercial labeling (Hebert et al. 2003; Hebert and Gregory 2005). Although the barcoding approach may not be able to resolve recently diverged species (Kaila and Stahls 2006; Monaghan et al. 2006) and may produce erro-neous results in taxa with interspecific hybridization (e.g., Shaw 2002), it has sufficient resolution in most groups and thus is a valuable addition to traditional taxonomy. In addition, DNA techniques are very powerful for forensic applications and, for example, have been used to identify the source species of confiscated shark fins, thus allowing prosecution of illegal trade in protected species (Shivji et al. 2002; Shivji et al. 2005). Furthermore, with the continu-ing miniaturization of DNA sequencing equipment and advances in molecular technology (Summerbell et al. 2005), portable DNA sequencers allowing spe-cies identification in the field (similar to the famous tricorder in Star Trek—“It’s life, Jim, but not as we know it”) becomes a distinct possibility.

DNA barcoding has already been applied to Squalus species in Australia, where it suggested the occurrence of six additional Squalus species (Ward et al. 2005), which have recently been described for-mally (Last et al. 2007). We have collected additional samples from Chile, Japan, Russia, the U.S. west coast, the U.K. and the northwest Atlantic (Franks 2006), which Bronwyn Holmes and Bob Ward (CSIRO, Australia) kindly sequenced at COI. Se-quences were integrated with data presented in Ward et al. (2005, 2007), downloaded from the Barcode of Life Web site (www.barcodinglife.org/). The resulting phenogram (Figure 1) shows clear clustering into the different Squalus species, with bootstrap values supporting species between 55% and 99%. Spiny dogfish is clearly separated from other Squalus spe-cies, with a bootstrap support of 99%. The dogfish from the North Pacific form a clade distinct from its conspecifics in the South Pacific and Atlantic, with bootstrap values similar to those of other “good” Squalus species (66% and 83%, respectively). Aver-age sequence diversity within Squalus species (exclud-ing dogfish) was 0.24% (±0.28, mean ± standard error), average sequence divergence between species was 3.3 % (±2.15%, mean ± standard error). In

comparison, sequence divergence between the two dogfish clades was 0.89% (± 0.34%, mean ± standard error), thus falling between the values of between and within species sequence divergences in other species. Although barcoding can therefore not resolve the taxonomic status of the two clades of spiny dogfish, these data show that it appears to be effective for the identification of most Squalus species.

As discussed above, the use of the mtDNA COI gene for DNA barcoding has been criticized because the slow rate of evolution may hamper ef-fective separation between closely related species or phylogeographic groupings. The mtDNA D-loop region (also known as control region), a noncoding sequence of about 1,000 base pairs (bp), on the other hand, evolves faster in most species (Parker et al. 1998; Altukhov and Salmenkova 2002), with some exception among salmonid species (Froufe et al. 2005), and may thus be more useful for detecting phylogeographic divergence within species. Analysis of 1,146 bp control region sequences of dogfish from the Atlantic and Pacific (Franks 2006) largely confirmed results from Ward et al. (2005, 2007), reporting two clades separated by 0.7% sequence divergence and supported by high bootstrap values (Figure 2). Somewhat surprisingly, the D-loop sequences provided no evidence for geographic structure within the Atlantic/South Pacific clade: no clear differentiation was found between dogfish from Europe and New Zealand.

Despite the statistical support of the two clades by both COI and D-loop sequences, the taxonomic or conservation relevance of intraspecific mtDNA variation is uncertain. Mitochondrial DNA only provides information about the female line at a single locus (Edwards and Beerli 2000) and may be complicated by ancestral polymorphisms (Arbogast et al. 2002) or hybridization (Shaw 2002; Chan and Levin 2005). In the absence of evidence from nuclear DNA and morphological, life-history, and demographic parameters, mtDNA variation has to be interpreted with caution (Moritz 1994a). For example, despite 4% D-loop sequence divergence between Australian and South African populations of great white sharks Carcharadon carcharias, biparen-tally inherited microsatellites demonstrated sufficient male-mediated gene flow to effectively homogenize allele frequencies and prevent genetic divergence of populations (Pardini et al. 2001). Similar patterns of mtDNA differentiation and microsatellite homo-geneity have also been found in mako shark Isurus oxyrinchus (Schrey and Heist 2003) and blacktip


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Figure 1. Neighbor-joining tree of Kimura 2-parameter distances from COI sequences of Squalus and related species. Numbers at nodes are bootstrap values derived from 1,000 replicates. Labels with S. acanthias denote sampling sites (UK: United Kingdom, northeast Atlantic; NW: northwest Atlantic; CH: Chile, southeast Pacific; ARG: Argentina; AUS: Australia, southwest Pacific; J: Japan, northwest Pacific; WA: Washington, USA, northeast Pacific).

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Figure 2. Neighbor-joining tree of Kimura-2-parameter distances of 1,058 bp of mtDNA control region sequence of spiny dogfish collected throughout the species range (PS: Puget Sound, WA: Washington coast, AK: Alaska, CA: California, JP: Japan, RU: Russia, NZ: New Zealand, CH: Chile, UK: United Kingdom, NW: Northwest Atlantic, ARG: Argentina, SAF: South Africa). Numbers at the nodes are bootstrap values obtained from 1,000 replicates. Data from Franks 2006.


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Table 2. Results of an analysis of molecular variance of mtDNA D-loop sequence data and microsatellite allele frequencies in spiny dogfish. Variance components among samples, among samples within regions (North Pacific vs. Atlantic/South Pacific), and between the two regions are shown. *P < 0.05; ***P < 0.001. Data from Franks 2006.

Component Among Among samples Between samples within region regionsF FST FSC FCT

MtDNA D-loop 0.572*** 0.047* 0.551***

Microsatellites 0.147*** 0.003* 0.145***

shark Carcharhinus limbatus (Keeney et al. 2005). Female philopatry with male gene flow complicat-ing the interpretation of mtDNA patterns therefore seems to be common in elasmobranchs.

In dogfish, however, the taxonomic relevance of the two clades is also supported by other data. Analyses based on eight microsatellites (McCauley et al. 2004) show a similar division into two groups as mtDNA D-loop data: an AMOVA (analysis of molecular variance, Excoffier et al. 1992) dem-onstrated similar partitioning of genetic variation among populations of the two marker systems (Table 2). Furthermore, the two clades correspond to well-described groups with differing life-history parameters, such as growth, age and length at first maturity, fecundity, and longevity (Vega et al. 2009, this volume).

Should these two clades be considered distinct species? Species concepts have been the subject of much controversy, with a multitude of different ideas and associated disputes about the most appropriate definition (see Turner 1999 for a review). The most commonly applied species concepts are the biological species concept (BSC) and the phylogenetic species concept (PSC). The BSC, defining species as groups of randomly interbreeding individuals that are repro-ductively isolated from other groups (Mayr 1942), is “simple, obvious and ultimately flawed” (Agapow et al. 2004) because of practical difficulties in es-tablishing reproductive isolation among allopatric populations. Especially in long-lived species with late maturation such as dogfish, experiments establishing pre- or postzygotic reproductive isolation between

Atlantic and Pacific populations would be time-consuming, expensive, and futile. With the onset of molecular methodologies, the PSC attained more popularity, defining species as monophyletic groups (descending from a single ancestor) with characters specific to that group (Agapow et al. 2004). While immediately intuitive, such monophyly depends critically on the molecular marker and the samples assayed. For example, mitochondrial DNA is more likely to reveal monophyletic groups than nuclear DNA because of its mode of inheritance and hap-loidy (Palumbi et al. 2001). Furthermore, under scenarios of rapid speciation (e.g., Malawi cichlids), neutral molecular markers have simply not had suffi-cient time to become reciprocally monophyletic even in morphologically and ecologically very divergent species (Turner 1999).

It is worth returning to the godfather of evolu-tionary thinking in this context. In contrast to most of his contemporaries, Darwin (1859) considered species to be evolving rather than created entities and thus as ‘varieties’ in permanent flux. The lack of a discrete ‘reality’ of species was the key support of his evolutionary hypothesis (Mallet 1995). During the origin of species, there is a phase when varieties are said to be incipient species that may or may not eventually separate into distinct entities—an un-comfortable thought for those who consider species to be an objective reality (Turner 1999). It is never possible to say at what point one species becomes two, and thus the status of dogfish at this point in time is difficult to ascertain.

Despite such interesting but unsettling uncer-tainties of species concepts, the identification of units for conservation and management is a very practical necessity. In our particular case, if dogfish in both the Atlantic and Pacific Oceans became so overfished as to require protection, would they de-serve independent listing under the U.S. Endangered Species Act (ESA)? The ESA allows listing of species, subspecies and “any distinct population segment of any species of vertebrate fish or wildlife which interbreeds when mature” (16 U.S.C. 1532(16)). A population (or group of populations) must satisfy two criteria to be considered a distinct population segment (DPS): it must be “discrete,” and it must be “significant” (USFWS and NMFS 1996). The U.S. National Research Council (NRC) suggested that a DPS can be seen as a “evolutionarily distinct popu-lation segment that is geographically or otherwise isolated from other population segments” (Stout et

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al. 2001). In contrast to the BSC, allopatry is thus a sufficient determinant of reproductive isolation. The second criterion, significance, would be met if the population contributed substantially to the ecological/genetic diversity of the species as a whole or if the loss of the DPS would result in a significant gap in the distribution of the species (Stout et al. 2001). Because of the geographic separation and the clear demographic, life-history (Vega et al., 2009), and genetic differences between North Pacific and Atlantic/South Pacific dogfish, they clearly deserve DPS status and would thus warrant independent protection under the ESA if one or both clades became endangered.

Population Structure in Spiny DogfishPopulation concepts, shark biology, and the evolutionary dynamics of molecular variationWithin the two clades identified by both genetic and demographic differentiation, there may be smaller units, which albeit not constituting separate DPSs, may still be essentially self-recruiting and relevant for the management of the fishery. The identification of such populations, or management units (MUs; Moritz 1994b), is important for two reasons: first, being self-recruiting, such MUs are more affected by recruitment and mortality (including fishing) than by immigration and emigration and may thus react independently to exploitation. Second, because of environmental or genetic factors, life-history pa-rameters such as growth and fecundity may differ among MUs, thus requiring independent assessment of each unit.

Surprisingly, there are few quantitative criteria for the definition of populations or MUs, which are likely to occur on a continuum of separation (Figure 3). Broadly, ecological and evolutionary population definitions can be distinguished (see Waples and Gaggiotti 2006 for a review). Ecological defini-tions consider primarily demographic cohesiveness and thus are concerned with migration rates (m). One such definition posits that units connected by a migration rate of less than 10% would react

Figure 3. The continuum of stock concepts in fisheries biology. Circles represent populations that overlap and exchange migrants to varying degrees. Triangles on the right depict changes in various parameters. Modified and expanded from Waples and Gaggiotti (2006).

1 The transformation of genetic differentiation into gene flow has a range of fairly unrealistic assumptions, such as migration drift equilibrium, infinite number of subpopulations, and equal migration rates (Whitlock and McCauley 1999), but this does not affect the general principle.

independently to perturbation and thus would be ecologically meaningful populations (Hastings 1993). Evolutionary criteria, on the other hand, are concerned with levels of gene flow, generally measured as the number of migrants (Nem: effective population size [Ne] × migration rate [m], Figure 4). This discrepancy can cause considerable confusion and ambiguity in the identification of MUs (Palsboll et al. 2007) because the relationship between ecologi-cal and genetic criteria depends not only on migra-tion rates but also on population size (Figure 5). For example, consider a molecular approach that has the power to detect significant genetic differentiation (FST) as low as 0.001, equaling gene flow of about 200 individuals per generation (solid curve in Figure 5).1 In large populations (n = 10,000 or 104), 200 migrants would constitute a migration rate of only 2%. Mi-gration rates between 2% and 10% would thus be


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and basins, and clearly may become prevalent in spe-cies of conservation concern (Palsboll et al. 2007). However, dogfish populations may commonly be large and in such populations molecular genetic differentiation provides a conservative estimate of population structure: if differentiation is found, independent stocks exist, but the lack of genetic differentiation does not preclude the existence of such stocks (Bentzen 1998).

There are two additional factors that complicate the relationship between genetic and demographic populations. First, the population sizes above refer to genetically effective population sizes (Ne), which are notoriously difficult to estimate and may be very dif-ferent from ecological estimates of abundance (Wang 2005). In many marine species with high fecundity and high juvenile mortality, Ne may be orders of magnitude lower than the census population size, probably because of high variance in reproductive success among individuals and populations (e.g., Hauser et al. 2002; Turner et al. 2002). In sharks, however, with low fecundity and well-developed off-spring, variance in reproductive success may be much lower and Ne may be closer to census population size; demographic estimates may thus be suitable as an estimator of Ne in comparisons of demographic and genetic populations. However, empirical estimates of Ne in sharks are required to confirm this notion. Second, ecological migration estimates are usually measured per year, while gene flow is measured per generation. In long-lived species such as sharks, the difference in the time unit between the two measures may result in further discrepancies. Unfortunately, most models to date assume discrete generations and measure both gene flow and migration rate per generation; more research is needed on the effects of age structure on the relationship between genetic and demographic populations.

Another important consideration that pervades the applied literature less often is the time scale of different concepts and the methods identifying them. Units of fisheries management are based on the short-term reaction to exploitation, determined by year-to-year recruitment and short-term migration of large sectors of the populations. Genetic markers, on the other hand, provide estimates of migration integrated over extensive time periods, often includ-ing the last glaciation 10,000 years ago. Thus, even in the complete absence of contemporary gene flow, recently separated populations would appear geneti-cally homogenous if the populations had not had

No. migrants

Figure 4. Relationship between number of migrants per generation and FST values under equilibrium expecta-tions (Wright 1943).

Figure 5. Levels of genetic differentiation in populations of different sizes and migration rates. Larger populations connected by the same migration rate (m) show lower genetic differentiation because gene flow (number of mi-grants, Nem) is higher. Note the logarithmic scale of population sizes.

sufficiently low to cause independent reaction of populations to demographic perturbation (Hastings 1993), but would be too high to allow the identi-fication of such populations by molecular markers. In small populations (n = 1,000 or 103, Figure 5), on the other hand, our approach would genetically differentiate populations with migration rates of up to 20%, and may thus identify units that are not demographically independent (m > 10%, Hastings 1993). Although such small populations may not be common in sharks, they may occur in isolated atolls

F st

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0.00

0.10

0.20

0.30

0.40

0 200 400 600 800 1000

Generations

FSTF st

Generations

Figure 6. Increase of FST after complete separation of subpopulations. Note that in relatively large populations (large effective population size, Ne), FST takes thousands of generations to accumulate, even in the complete ab-sence of gene flow. Equation from Nei and Chakravarti (1977).

Ne = 1,000

Ne = 10,000Ne = 100,000

sufficient time to diverge from each other. In the ab-sence of migration, the time required for divergence to occur is directly proportional to population size (Crow and Aoki 1984), but even in relatively small populations it can take several thousand generations to reach an equilibrium between genetic drift and gene flow (Figure 6). Given the long generation time of many sharks, the time since separation of temperate populations after the last glaciation may be insufficient for genetic differentiation to accu-mulate: for example, assuming a generation time of 10 years and an effective population size of 10,000 for dogfish, FST between two populations that have separated at the end of the last glaciation (10,000 years or 1,000 generations ago) would be expected to be only about 0.05, even in the complete absence of migration (Figure 6). Genetic homogeneity may therefore be the result of recent (in evolutionary terms) population separation rather than extensive contemporary gene flow among populations.

In species with internal fertilization, such as sharks and marine mammals, genetic stock concepts may also differ spatially from demographic stocks. Sharks differ from most teleosts in their internal fertilization, thus potentially separating mating and parturition both temporally and spatially. This distinction is relevant, because for demographic considerations of recruitment, nursery areas are the central unit, while population genetic patterns are determined by mating and gene flow among popu-lations. In this respect, sharks resemble viviparous

cetacean species more than oviparous teleosts, and the relative timing of mating and parturition can determine patterns of genetic differentiation. For example, there are two well-described populations of gray whales Eschrichtius robustus in the Pacific Ocean that differ in morphology, abundance trends, distribution, and migration routes (see Swartz et al. 2006 for a review). The whales show seasonal north-south migration along the east and west coasts of the Pacific; mating occurs at the onset of the southward migration between late November and early January. After a gestation time of 13 months, calves are born during the southward migration or in the summer-ing grounds.

These patterns of migration and reproduction are reflected in genetic data: differentiation at maternally inherited mitochondrial DNA was higher than at biparentally inherited microsatellites (mtDNA FST = 0.062, microsatellite FST = 0.005), and the microsatellite FST was higher in females (FST = 0.016, P < 0.01) than in males (FST < 0.001, P = 0.423). These patterns suggest gene flow medi-ated by mating when the two populations overlap and relative philopatry of females to their own populations.

Similar patterns of sex-biased gene flow may be common in sharks. Female philopatry has been shown in lemon sharks Negaprion brevirostris from genetic parentage assignments (Feldheim et al. 2002a) but has also be inferred from higher mtDNA than nuclear population differentiation in several species (blacktip sharks, Keeney et al. 2005; great white sharks Carcharodon carcharias, Pardini et al. 2001; mako shark, Schrey and Heist 2003). However, while mtDNA differentiation does indeed demonstrate barriers to female migration, nuclear homogeneity does not necessarily prove male roam-ing. As in the case of the gray whales, nuclear homo-geneity and mtDNA divergence may also be caused by seasonal migration of homing populations with mating occurring in common feeding grounds but parturition in population-specific nursery grounds. Tagging data showing far-reaching migration of fe-male white sharks (Bonfil et al. 2005) support such an interpretation.

The points discussed demonstrate that the biology of sharks and properties of evolutionary change in large populations cause a large discrepancy between the units important to management and genetically differentiated populations identified by molecular markers. For example, large populations with very


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limited demographic exchange and divergence since the last ice age may essentially be undetectable with molecular markers. Mating behavior that promotes mating at sea and parturition in population-specific nursery areas would allow free gene flow while mak-ing populations demographically independent by maintaining separate female stocks. The point here is not that molecular approaches are inappropriate in the detection of population structure in sharks—indeed, such structure has been detected in several species (Heist et al. 1996; Gaida 1997; Keeney et al. 2003). Instead, genetic data need to be interpreted in context with the biology of the species in ques-tion. In many shark species, where such information is scarce, the interpretation of genetic data can be difficult, and should be carried out with caution and under consideration of the general principles outlined here.

Molecular markers in shark population studiesIncreasingly sophisticated molecular markers are being employed in attempts to detect ever lower levels of genetic differentiation in order to close the gap between genetic and demographic populations (Table 1). The power of population genetic stud-ies is directly proportional to the number of loci and the genetic diversity detected with each locus (Kalinowski 2002; Kalinowski 2004). Allozymes, the first molecular marker widely applied to wild populations, revealed only limited variability at a few polymorphic loci (Richardson et al. 1986), thus limiting their applicability in marine species. Possibly owing to lower mutation rates, the variability detect-able with allozymes is even lower in sharks than in marine teleosts (Heist 1999), further compromising the power of such approaches. In the late 1980s and early 1990s, methods were developed to assay varia-tion at the mitochondrial DNA; these methods not only revealed higher variability, they were predicted to show greater differentiation among populations because mtDNA haploidy and maternal inheritance reduce the effective population size to a quarter, thus accelerating the approach to equilibrium, and because higher mutation rates allow a faster accumu-lation of mutations in each subpopulation (Birky et al. 1989). However, this theoretical potential does not seem to have been realized in pelagic teleosts, where allozymes tend to detect more significant differentiation than does mtDNA, possibly because mtDNA is inherited as a single locus whereas many loci can be analyzed in nuclear markers (Hauser and

Ward 1998). MtDNA nucleotide diversity appears to be lower in sharks than in teleosts (Heist 1999), further limiting the power of the analysis, though the maternal inheritance of mtDNA in compari-son with nuclear DNA differentiation allowed the detection of sex-biased dispersal in several species (see previous).

The molecular markers currently most widely employed are microsatellites, which, because of their high variability, ubiquity in the genome, and rapid screenability, have provided the most powerful analyses of population structure in marine species. Microsatellites are short sequences (1–5 bp) that are repeated in tandem arrays of up to 500 bp in length. Variation in the number of tandem repeats can be readily assayed by estimating the length of the entire array using polymerase chain reaction (PCR) and primers specific to the sequence flanking the array. Because of replication errors changing the number of tandem repeats, mutation rates are higher than for other molecular markers (10−3–10−5), resulting in high variability and thus high power to resolve population structure, identify immigrants, and esti-mate migration rates. The main disadvantage of mic-rosatellites is the need for locus- and species-specific primers, whose isolation can be time-consuming and costly (Zane et al. 2002).

Given the apparent lower variability in allozymes and mtDNA in sharks than in other groups, the question arises whether microsatellite diversities are also lower, indicating lower power to identify independent stocks. Indeed, a survey of microsatel-lite studies in sharks, marine teleosts, and toothed whales (Table 3; Figure 7) shows that shark studies used significantly fewer loci (L) and detected sig-nificantly lower heterozygosity (HE) , but not fewer alleles (A) than teleosts (Mann–Whitney U-test: HE: P = 0.035, A: P = 0.418, L: P = 0.026). Toothed whales, with their protracted life history, late matura-tion, longevity, and predatory lifestyle may be a better comparison than teleosts, which are often pelagic with large population sizes. None of the comparisons between sharks and toothed whales are significant (Mann–Whitney U-test: HE: P = 0.833, A: P = 0.057, L: P = 0.117), though the power of these comparisons is likely to be low because of the limited number of published studies. Nevertheless, these results suggest that lower microsatellite variability in sharks may be due more to ecological factors than to having lower mutation rates than mammals (Martin et al. 1992; Martin 1999). Shark studies tend to employ far fewer

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Table 3. Expected heterozygosity (HE), number of alleles (A), and number of loci (L) surveyed in microsatellite studies of sharks, marine teleosts, and toothed whales (Odontoceti). Shark and toothed whale data are from all published studies known to the author. Teleost studies represent a small proportion of published microsatellites: to avoid tempo-ral bias caused by technique development, teleost studies were picked from the same issue of Molecular Ecology Notes as a shark study, or from the same month’s issue as a shark study in a different journal. Averages of each group are presented at the bottom of the table, together with a comparison with the survey by DeWoody and Avise (2000).

HE A L Reference

SharksSpot-tail Carcharhinus sorrah 0.54 9.8 5 Ovenden et al. 2006Autralian blacktip Carcharhinus tilstoni 0.64 10.8 5 Ovenden et al. 2006Sandbar Carcharhinus plumbeus 0.85 22.6 5 Portnoy et al. 2006Blacktip Carcharhinus limbatus 0.50 14.0 8 Keeney et al. 2005Lemon Negaprion brevirostris 0.79 25.6 9 Feldheim et al. 2002aHammerhead Sphyrna tiburo 0.69 13.5 4 Chapman et al. 2004Shortfin mako Isurus oxyrinchus 0.87 25.3 4 Schrey and Heist 2003Nurse Ginglymostoma cirratum 0.54 5.0 9 Heist et al. 2003White Carcharodon carcharias 0.70 10.0 5 Pardini et al. 2000Dogfish Squalus acanthias 0.70 5.5 8 McCauley et al. 2004Zebra shark Stegostoma fasciatum 0.74 9.9 14 Dudgeon et al. 2006

Marine teleostsJapanese mackerel Scomberomorus niphonius 0.78 26.4 6 Yokoyama et al. 2006Mangrove red snapper Lutjanus argentimaculatus 0.77 14.5 7 Zhang et al. 2006Japanese flounder Paralichthys olivaceus 0.89 22.4 8 Sanchez et al. 2006Olive flounder Paralichthys olivaceus 0.81 14.1 27 Kim et al. 2003Bicolor damselfish Stegastes partitus 0.94 29.7 11 Williams et al. 2003Common pandora Pagellus erythrinus 0.88 21.1 8 Ramsak et al. 2003Barfin flounder Verasper moseri 0.84 17.8 8 Ortega-Villaizan et al. 2003Tarpon Megalops atlanticus 0.39 4.6 16 Blandon et al. 2003Northern bluefin tuna Thunnus thynnus thynnus 0.66 6.3 7 McDowell et al. 2002Saddleback clownfish Amphiprion polym 0.76 15.9 9 Quenouille et al. 2004Europea sea bass Dicentrarchus labrax 0.81 16.4 5 Ciftci et al. 2002Swordfish, Xiphias gladius 0.66 8.0 11 Reeb et al. 2003Tarakhiri Nemadactylus macropterus 0.79 18.4 7 Burridge and Smolenski 2000Cardinalfish Apogon doederleini 0.88 13.6 8 Miller-Sims et al. 2004Senegal sole Solea senegalensis 0.81 9.0 10 Funes et al. 2004Banggai cardinalfish Pterapogon kauderni 0.7 9.2 11 Hoffman et al. 2004Bluehead wrasse Thalassoma bifasciatum 0.94 39.1 10 Williams et al. 2004Northern bluefin tuna Thunnus thynnus thynnus 0.72 10.4 25 Clark et al. 2006

Toothed whalesBottlenose dophin Tursiops truncatus 0.5 9.1 8 Caldwell et al. 2002Striped dolphin Stenella coeruleoalba 0.51 6.2 6 Mirimin et al. 2006Short-beaked common dolphin Delphinus delphis 0.75 8.4 10 Coughlan et al. 2006Burmeister’s porpoises Phocoena spinipinnis 0.72 7.2 11 Rosa et al. 2005Bottlenose dolphins Tursiops truncatus 0.67 7.5 12 Rosel et al. 2005Bottlenose dolphins Tursiops truncatus 0.38 5.9 7 Rooney et al. 1999Aduncus dolphins Tursiops aduncus 0.76 12.4 5 Krutzen et al. 2001Harbour porpoise Phocoena phocoena 0.87 13.1 7 Rosel et al. 1999Dusky dolphins Lagenorhynchus obscurus 0.72 8.3 9 Cassens et al. 2005Sperm whale Physeter macrocephalus 0.73 9.0 9 Lyrholm et al. 1999

AveragesSharks 0.69 13.8 6.9Marine teleosts 0.78 16.5 10.8Toothed whales 0.66 8.7 8.4Marine teleosts 0.79 20.6 5.5 DeWoody and Avise 2000


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loci than either marine teleosts or toothed whale studies (Figure 7): indeed only four studies exceed the mean number of loci for toothed whales and marine teleosts. Although laboratory-specific factors cannot be excluded, these differences suggest that microsatellites are rarer and more difficult to isolate from sharks than from teleosts or mammals (Heist 1999; Heist et al. 2003). The effect of this lower number of loci is an increase in sampling variance of FST (Kalinowski 2002) and thus a reduction of the power of statistical tests.

Even with the most variable and sensitive mo-lecular markers, the discrepancy in gene flow levels between ecological and genetic populations still exists, and molecular markers alone may not suf-fice to identify large demographic populations of a long-lived species. The integration of molecular data with results from phenotypic markers such as mor-phometrics, parasites, otolith microchemistry, and population parameters as well as with information on the ecology of the species, its demography and migrations, and oceanographic features will provide more powerful insights into the population structure of exploited fish species than any one technique alone (Cadrin et al. 2005). It is important to consider here that different methods can, but do not have to, provide similar results, because they essentially measure different parameters: for example, genetic results measure low-level, long-term gene flow (that is, the number of reproductively successful migrants), while tagging studies measure relatively short-term movements of individual fish without consideration of their reproductive success. Nevertheless, the com-

bination of both methods can provide much more detailed information than any single approach.

Population Structure of Dogfish Fine-scale studies of the genetic population structure of spiny dogfish are currently limited to the northeast Pacific (Franks 2006). Data from eight microsatel-lite loci (McCauley et al. 2004) and samples from the Bering Sea, the Gulf of Alaska, the Washington coast, Puget Sound, the Strait of Georgia, and the Californian/Oregon coast revealed no significant genetic differentiation, with an overall FST of 0.000. However, pairwise tests of differentiation between individual samples revealed small but significant differentiation between samples from the Bering Sea and the California/Oregon coast (FST = 0.006, P < 0.05, not significant after Bonferroni correction for multiple tests). Furthermore, a principal coordinate analysis of individual multilocus genotypes suggests some differentiation among samples (Figure 8). These data therefore provide no clear evidence for genetic population structure of dogfish in the north-east Pacific, which does not preclude the existence of different demographic populations relevant for management. Indeed, length-at-age data showed differences in growth rate along a latitudinal gradi-ent between Washington and California (Vega et al. 2009), suggesting incomplete mixing of dogfish along the U.S. west coast and potentially the exis-tence of independent management units.

The power of the data set may have been limited by low heterozygosity of microsatellite loci (aver-

Figure 7. Frequency histograms of average heterozygosity per locus (HE), average number of alleles per locus (A), and number of loci used in studies on sharks, marine teleosts and toothed whales. Data and references are shown in Table 2.

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age expected heterozygosity, HE = 0.62) and small sample size. In particular, the Bering Sea sample was the smallest in the sample set (n = 20), which may have caused false significant results, although small samples also complicate the detection of true genetic differentiation. Further studies with larger samples, more polymorphic microsatellites, or pos-sibly loci under differential selection may provide further insight into the population structure of Pacific dogfish.

In the Atlantic/South Pacific clade, two samples were analyzed (Franks 2006): one from the northwest Atlantic (Maine, USA) and one from the southeast Pacific (Chile). These two samples, from almost the opposite ends of the distribution of that clade, were highly significantly differentiated (FST = 0.013, P < 0.001), but levels of differentiation were still an order of magnitude lower than those between the North Pacific and the Atlantic/South Pacific clades (average FST = 0.140), suggesting more recent divergence or

some ongoing level of gene flow between these sites. In contrast to many other shark species (great white sharks, Pardini et al. 2001; mako shark, Schrey and Heist 2003; blacktip sharks, Keeney et al. 2005), there was no evidence that sex-biased gene flow caused higher mitochondrial than microsatellite divergence (Franks 2006).

Individual Identification and Parentage AssignmentThe high variability of microsatellites allows the identification not only of differentiated popula-tions, but also of individuals (Palsboll 1999). Such individual identification is commonly applied in human forensics and is increasingly used in place of mark–recapture studies of terrestrial mammals and birds (Petit and Valiere 2006). The main advantages of such genetic mark–recapture over conventional approaches are that tag shedding is not an issue, sam-pling can be noninvasive or less invasive (feces, hair, feathers, fin clippings), and genetic tags are heritable, thus potentially extending the tagging study to the next generation. For highly mobile marine species, genetic tagging may seem less appropriate because of the low recapture probability; however, genetic individual identification has already been used to estimate population size and migration distances in humpback whales Megaptera novaeangliae (Palsboll et al. 1997; Smith et al. 1999). In sharks, genetic mark–recapture studies have so far been limited to estimating loss of physical tags in lemon sharks (Feldheim et al. 2002b). However, with increasing genotyping throughput and decreasing costs, similar approaches become feasible for more abundant spe-cies such as dogfish.

The heritability of genetic tags opens interesting possibilities for transgenerational studies. On the simplest level, broods of embryos from females can be used to detect multiple paternity in sharks—and indeed all studies to date have detected multiple sires either in all investigated litters (lemon shark Negaprion brevirostris Feldheim et al. 2001; nurse shark Ginglymostoma cirratum Saville et al. 2002) or at least in some (hammerhead shark Sphyrna tiburo, Chapman et al. 2004). Like in other animals, multiple mating is thought to be a “bet-hedging strategy” whereby females maximize their chance of reproductive success by avoiding having all their offspring sired by a single male that may be ge-netically incompatible (Jennions and Petrie 2000).

Figure 8. Principal coordinate analysis of individual mul-tilocus microsatellite genotypes of northeast Pacific dog-fish, calculated in GENETIX 4.05 (Belkhir et al. 2004). Four populations were included (BS: Bering Sea, AK: Alaska, WA: Washington coast, CO: California/Oregon coast); Puget Sound and Strait of Georgia fish were not included. Some differentiation among populations, al-though not significant, is apparent and may justify fur-ther research. Little overlap exists between Bering Sea and California/Oregon fish, corresponding to the significant pairwise FST value.


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Interestingly, the incidence of multiple mating was lowest in the species with known sperm storage (hammerhead), suggesting sperm competition or, given smaller probabilities of meeting related indi-viduals in larger populations of hammerhead sharks, intricate adaptation of mating structure to prevailing population sizes (Chapman et al. 2004). It could be postulated that incidence of multiple mating would change with decreasing population size, either by de-creasing because of the lower chance to meet a mate at all, or by increasing as an adaptation to reduced population size. Thus, comparisons between less and more exploited populations of sharks may provide interesting insights into the effects of exploitation on the mating structure of viviparous species.

Genetic markers can also be used to reconstruct parental genotypes. In many shark species, sampling juveniles in nursery areas is easier than collecting roaming adults. In lemon sharks, genetic data from such juveniles were used to reconstruct parental genotypes and to infer mating behavior, migration patterns, and philopatry of females (Feldheim et al. 2004). The study showed that females tended to return to the nursery area every 2 years and had between 4 and 58 offspring in total. Most litters were sired by several males, but males did not sire more than one litter, suggesting that they may mate with females from a wider geographic area (Feldheim et al. 2004) and that, as in other sharks, gene flow among populations may be mainly male-mediated.

No published data are available on multiple pa-ternity in spiny dogfish, although preliminary data suggest multiple paternity in two of seven litters (Hauser et al., University of Washington, Seattle, un-published data). However, the low heterozygosity of dogfish microsatellites (McCauley et al. 2004) limits the power to detect multiple matings: for example, assuming a litter size of 10, with 8 pups sired by one male and each of the remaining two pups sired by an-other, the power to detect multiple paternity would be 0.855 (calculated with the software PrDM, Neff and Pitcher 2002). Smaller litter sizes would decrease the power rapidly, though more even distribution of paternity would increase it. In order to detect rare pups sired by alternate males, more polymorphic markers would be required. If such highly variable markers were available, it would be interesting to in-vestigate whether different life-history characters (age at maturity, longevity, fecundity) between Atlantic and Pacific dogfish are correlated with differences in the frequency of multiple mating and whether

the exploitation status of stocks has an effect on the incidence of multiple paternity.

The Future of Dogfish Molecular EcologyMolecular biology is advancing at an unprecedented speed, in particular by rapidly increasing sequence in-formation in publicly accessible databases, advances in sequencing and other molecular technology, and improvements in bioinformatics and data manage-ment (Hauser and Seeb 2008). Although some advances are currently apparent mainly in human genomics, gene expression analysis, physiology and microbial ecology, they are also becoming applicable to wild populations. For ecological research on sharks, and especially on dogfish, these advances are likely to be relevant for a more fine-scale resolution of population structure, the detection of adaptive diversity, and for bridging the gap between molecular genetics and phenotypic characters.

As outlined previously, the power of many molecular ecology studies in sharks may be limited by the low variability of many molecular markers, including allozymes, mtDNA, and microsatellites. Such lower variability can be offset by increasing the number of markers, though this is difficult with microsatellites and impossible with allozymes (be-cause of the limited number of stainable enzymes) and mtDNA (which is inherited as a single locus). However, a recently initiated EST (expressed se-quence tag) project on spiny dogfish at the Mount Desert Island Laboratory, Maine, USA, has already deposited over 16,500 DNA sequences in GenBank, a publicly available DNA database (http://www.ncbi.nlm.nih.gov). ESTs are short DNA sequences, which are parts of expressed genes, and which can be used to identify coding regions, aid gene discovery, and help genome sequence determination. ESTs may contain microsatellites, and owing to their large number, many independent loci can be isolated from available GenBank information (e.g., Vasemagi et al. 2005). More commonly, ESTs contain SNPs (single nucleotide polymorphisms), single base pair positions that are variable within a species (Morin et al. 2004). SNPs occur at a frequency of about one in 200–1,000 bp (Brumfield et al. 2003) and are thus common in the genome. It is therefore theoretically possible to isolate hundreds of such SNPs for dogfish with the available sequence data alone, resulting in an increase in the power of molecular genetic studies.

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In addition to their ubiquity, SNPs have other advantages as molecular markers. They can be screened by simple PCR without the need for size estimation by electrophoresis, thus allowing the generation of thousands of genotypes in a single day (Smith et al. 2005b). Furthermore, in contrast to microsatellite genotypes, which are often platform (DNA sequencer) specific and difficult to standard-ize among laboratories, SNP alleles are alternate bases (A,C,G,T) at a single position, and data can therefore easily be compared among studies (Smith et al. 2005b). SNPs have already been used for the detection of population differentiation and popula-tion assignment in Pacific salmon Oncorhynchus spp. (Smith et al. 2005c), with a resolution comparable to or higher than that of microsatellites. Indeed, a recent simulation study demonstrated that about 100 SNPs would be sufficient to allow parentage identification in populations of several thousand individuals (An-derson and Garza 2006), a feat currently very difficult with microsatellite markers because of their higher genotyping error (Hauser et al. 2007). As is the case for microsatellites, however, the discovery and optimization of high-throughput SNP assays may be time consuming and costly, though the availability of extensive sequence resources is a useful basis for SNP detection (Smith et al. 2005a).

The availability of many markers, especially if isolated from ESTs, also opens the exciting possibil-ity of bridging the gap between neutral molecular genetic and phenotypic variability (Naish and Hard 2008). The identification and measurement of ge-netic mechanisms underlying phenotypic variation in wild and cultured organisms has been an important research focus since Darwin and Mendel, in particu-lar in relation to breeding studies of domesticated plants and animals (Falconer 1960). Because of the nature of the experimental approach, these studies were almost entirely restricted to species that could easily be bred in captivity (that is, they are infeasible in sharks). The development of neutral genetic mark-ers for population genetics and molecular ecology oc-curred almost independently (Carvalho and Hauser 1998), and while providing powerful insights into migration patterns, population history, and mating systems, these tools never quite managed to describe genetic variation at phenotypic characters in wild populations (Carvalho et al. 2003). Only recently have further advances in molecular technology al-lowed an integration of the two fields by identifying adaptive genetic divergence at the molecular level

(Luikart et al. 2003; Naish and Hard 2008). Such identification can be done by estimating variation at candidate loci, such as genes involved in immune response (e.g., major histocompatibility complex genes, Miller et al. 2001), hemoglobin (Husebo et al. 2004), enzyme coding loci (Planes and Romans 2004), or proteins involved in membrane traffick-ing (e.g., pantophysin Pan I, Canino and Bentzen 2004, Canino et al. 2005). However, candidate genes are often found by chance (Fevolden and Pogson 1997), and so their detection is often risky and expensive. Furthermore, because only single loci are investigated, disentanglement of selective popula-tion differentiation and demographic history can be problematic: for example, the steep geographic cline in Pan I genotypes of Atlantic cod Gadus morhua could be due to either strong selection at the locus or secondary contact of differentiated populations (Case et al. 2005). Multilocus surveys, on the other hand, screen a large number of potential loci and identify outlier loci that exhibit patterns of differentiation and diversity deviating from the rest of the genome due to selection (Luikart et al. 2003). This genome scan (Storz 2005) or population genomics (Black et al. 2001) approach is based on genetic “hitchhiking,” that is, variation at neutral loci showing signatures of selection at physically adjacent functional genes (Schlötterer 2003). Comparison of such loci with unlinked neutral markers allows the separation of neutral and selective differentiation in space and time. For example, genome scans in lake whitefish Coregonus clupeaformis showed that only a small proportion of the genome (1.4–3.2%) is involved in the dramatic morphological and ecological dif-ferentiation between normal and dwarf ecotypes (Campbell and Bernatchez 2004). Similarly, 15 out of 275 loci showed striking differences between two morphotypes of the marine snail Littorina saxatilis, demonstrating the importance of selective divergence in population genetics (Wilding et al. 2001). Once many molecular markers are developed for dogfish, powerful investigations into selective differentiation among phenotypically divergent populations (Vega et al. 2009) will be possible.

However, dogfish EST databases also have other applications and allow the full utilization of current postgenomics tools (Hofmann et al. 2005; Wilson et al. 2005; Goetz and MacKenzie 2008). EST DNA fragments can be plotted on small slides (microar-rays) or incorporated onto gene chips, which can then be used to quantify gene expression under a


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variety of environmental conditions (Goetz and MacKenzie 2008). Such transcriptional profiling has already allowed functional surveys of the genes involved in development (Sarropoulou et al. 2005), maturation, immune response, toxin response (Let-tieri 2006), and response to hypoxia (Gracey et al. 2001) and temperature stress (Hofmann et al. 2005; Wilson et al. 2005). Expression of specific genes can also be studied by quantitative PCR (qPCR, Wong and Medrano 2005); for example, qPCR experi-ments could demonstrate an increased expression of the metallothionin gene in tiger shark Scyliorhinus torazame after exposure to heavy metals (Cho et al. 2005) and the involvement of cyclooxygenase in rectal gland chloride secretion of dogfish (Yang et al. 2002). In connection with the plethora of biochemical research using spiny dogfish as a model organism (reviewed in Amemiya et al. 2005), such approaches can be extremely powerful for ecological investigations in dogfish. In addition to providing mechanistic insights into the adaptation of dogfish to different environmental conditions, such stud-ies may also provide important molecular markers for the identification of phenotypically different populations.

Concluding RemarksResearch on dogfish molecular ecology is still in its infancy. There is thus much scope for further molecu-lar genetic research targeting taxonomic revisions, intraspecific phylogenies, population genetics, and mating behavior. However, the real scope of dogfish molecular ecology lies in its use as a model system for gene expression analyses and genome evolution and thus the availability of extensive EST databases. These databases are not only a tool to overcome limitations to molecular studies caused by low vari-ability in sharks of many molecular markers, they also offer the opportunity to investigate adaptive genetic differentiation in dogfish populations.

For all applications of molecular markers, it is important to integrate molecular data with infor-mation on the biology, ecology, and demography of dogfish as well as pertinent features of the environ-ment. For example, the interpretation of patterns of molecular differentiation in many shark species relies on detailed knowledge of reproductive be-havior, in particular mating and nursery areas and seasonal migrations. Similarly, an investigation of dogfish population structure is much more power-

ful when genetic and phenotypic data are combined (see Vega et al. 2009). While there is a plethora of demographic and life-history data on dogfish, much of their biology is still relatively unknown and needs further research.

The integration of information from different biological fields will probably become even more important once genomic resources are applied to dogfish research. Although dogfish transcriptome assays have been primarily aimed at phylogenetic comparisons with higher vertebrates, environmental studies could exploit the same resources to investigate responses to osmotic or thermal stress, adaptation to estuarine environments or to stressors at the edge of their distribution (e.g., Bering Sea and equator). Such data would provide valuable insights not only into the limits of the physiological tolerance and thus distribution of dogfish, but also into likely reaction to anthropogenically or naturally changing environments. However, recent research has shown that depending on the nature of environmental stres-sors, different gene or gene groups may be involved in stress response (Podrabsky and Somero 2004), illustrating the need for detailed environmental and biological information (or experimental manipula-tion, which is difficult in dogfish). Interdisciplinary research on a species with world-wide distribution, relatively high abundance, economic importance, taxonomic interest, and ecological adaptability may establish the lowly dogfish as one of the prime marine model species of ecological and evolution-ary research.

AcknowledgmentsI thank Vince Gallucci for his collaboration in the interdisciplinary project on spiny dogfish population structure (Potential for sustainable expansion of the dogfish fishery in the northeast Pacific, Saltonstall Kennedy Grant # 02-NWR-006) that led to this review paper. I also thank Jim Franks, who produced the data and some of the analyses presented here. Bob Ward and Bronwyn Holmes provided the barcode sequence information for Figure 1. Thanks are due to Robin Waples and Fred Utter for comments on an earlier draft of this manuscript. Funding for the dogfish research from the NOAA Saltonstall Ken-nedy Grant Program is gratefully acknowledged.

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