Journal of Heredity Advance Access originally published online on December 5, 2006
Journal of Heredity 2006 97(6):607-611; doi:10.1093/jhered/esl044
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Brief Communications |
Widespread Utility of Highly Informative AFLP Molecular Markers across Divergent Shark Species
From ReproGen, Faculty of Veterinary Science, University of Sydney, Camden, NSW, Australia (Zenger); the Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia (Stow and Briscoe); the School of Biological and Conservation Sciences (Westville), University of KwaZulu-Natal, Durban 4000, South Africa (Peddemors); and the Graduate School of the Environment, Macquarie University, Sydney, NSW 2109, Australia (Harcourt)
Address correspondence to Adam Stow at the address above or e-mail: astow{at}rna.bio.mq.edu.au.
Population numbers of many shark species are declining rapidly around the world. Despite the commercial and conservation significance, little is known on even the most fundamental aspects of their population biology. Data collection that relies on direct observation can be logistically challenging with sharks. Consequently, molecular methods are becoming increasingly important to obtain knowledge that is critical for conservation and management. Here we describe an amplified fragment length polymorphism method that can be applied universally to sharks to identify highly informative genome-wide polymorphisms from 12 primer pairs. We demonstrate the value of our method on 15 divergent shark species within the superorder Galeomorphii, including endangered species which are notorious for low levels of genetic diversity. Both the endangered sand tiger shark (Carcharodon taurus, N = 18) and the great white shark (Carcharodon carcharias, N = 7) displayed relatively high levels of allelic diversity. A total of 59 polymorphic loci (He = 0.373) and 78 polymorphic loci (He = 0.316) were resolved in C. taurus and C. carcharias, respectively. Results from other sharks (e.g., Orectolobus ornatus, Orectolobus sp., and Galeocerdo cuvier) produced remarkably high numbers of polymorphic loci (106, 94, and 86, respectively) from a limited sample size of only 2. A major constraint to obtaining much needed genetic data from sharks is the time-consuming process of developing molecular markers. Here we demonstrate the general utility of a technique that provides large numbers of informative loci in sharks.
Many shark species have life-history and ecological characteristics that render them particularly vulnerable to anthropogenic impacts such as harvesting, habitat loss, and habitat degradation (Smith et al. 1998; Baum et al. 2003). Information on basic population parameters, such as population structuring, dispersal, and effective population size, is nonexistent for most shark species. In the past, assessing genetic structuring of many shark species has been hampered due to low variability at allozyme loci and in mitochondrial DNA, possibly due to low rates of molecular evolution (Martin et al. 1992; Heist et al. 2003). More recently, some polymorphic microsatellite markers have been developed and applied in a handful of shark species (see Heist 2004), which also show limited utility in closely related taxa (e.g., Schrey and Heist 2002). However, many of these studies exhibit little or no detectable genetic differentiation between populations separated by vast distances (Feldheim et al. 2001; Pardini et al. 2001). The absence of measurable genetic structuring in many shark studies means that identification of stock structure and, therefore, the development of management plans remain a challenge.
Recently, amplified fragment length polymorphism (AFLP) has been advocated as a powerful genetic marker system for assessing population structure and individual identity (e.g., Gerber et al. 2000; Bensch and Akesson 2005). AFLP methods have already been shown to be a valuable tool for detecting subtle but significant genetic subdivisions in animal studies (Campbell et al. 2003; Whitehead et al. 2003; Wang et al. 2004). Some of the technical advantages of AFLP are that thousands of genome-wide bi-allelic dominant loci can be evaluated in a relatively short period of time and at a low cost. Although, each polymorphic AFLP locus has a low information content, the sheer number of loci investigated (hundreds to even thousands of loci) often means that this technique provides more information than traditional codominant methods (Campbell et al. 2003). In many studies where fewer traditional markers are used, a much greater bias in genetic estimates can result because few regions of the genome are analyzed (Mariette et al. 2002). Here we describe the development of a highly informative AFLP marker system in 15 divergent shark species belonging to the superorder Galeomorphii (Nelson 1994). We evaluate levels of polymorphism at AFLP loci in 5 species including Carcharodon taurus and C. carcharias, which are critically endangered or threatened throughout much of their distribution and for which conservation measures are paramount (Otway et al. 2004).
 |
Materials and Methods |
|---|
 Top Materials and Methods Results and DiscussionReferences |
|---|
Genomic DNA was extracted with QIAmp Tissue Kit (Qiagen Inc., Valencia, CA) from 15 divergent galeomorph species including sand tiger shark (Carcharodon taurus, N = 18, SE Australia), great white (Carcharodon carcharias, N = 7, SE Australia), shortfin mako (Isurus oxyrinchus, N = 1), herbst nurse (Odontaspis ferox, N = 1), goblin shark (Mitsukurina owstoni, N = 1), ornate wobbegong (Orectolobus ornatus, N = 2, SE Australia), dwarf wobbegong (Orectolobus sp., N = 2, SE Australia), black tip (Carcharhinus limbatus, N = 1), bronze whaler (Carcharhinus brachyurus, N = 1), java shark (Carcharhinus amboinensis, N = 1), bull shark (Carcharhinus leucas, N = 1), tiger shark (Galeocerdo cuvier, N = 2, South Africa), scalloped hammerhead (Sphyrna lewini, N = 1), smooth hammerhead (Sphyrna zygaena, N = 1), and angel shark (Squatina squatina, N = 1).
The AFLP assays largely followed universal methods described by Vos et al. (1995) but required substantial optimization to detect polymorphisms and achieve a manageable level of complexity. Methods tried were 1) using EcoRI as the rare cutter and MseI or TaqI as the frequent cutter; 2) selective amplification with EcoRI having three 3' selective nucleotides while MseI or TaqI having either 3 or 4 selective 3' nucleotides; and 3) modifying the selective polymerase chain reaction (PCR) conditions to be more stringent. Several combinations of these conditions were tested, with the optimal combination incorporating EcoRI and MseI restriction enzymes (TaqI produced spurious bands), 4 selective 3' nucleotides on MseI primer (Table 1), and a selective touchdown PCR.
|
Genomic DNA (200–400 ng) was digested with 5 U of each EcoRI and MseI (New England BioLabs [NEB], Beverly, MA) for 1 h at 37° C in a 40-µl reaction using manufacturers' recommendations. Adapters were ligated to restriction fragments in 10 µl of solution containing 5 pmol EcoRI adapter (5'-CTC GTA GAC TGC GTA CC-3' and 5'-AAT TGG TAC GCA GTC TAC-3'), 50 pmol MseI adapter (5'-GAC GAT GAG TCC TGA G-3' and 5'-TAC TCA GGA CTC AT-'3), 1 Weiss U T4 DNA ligase (NEB) and 1x T4 DNA ligase reaction buffer (NEB). Adapters were then added to 40 µl of restriction digest solution and incubated at 37° C overnight. Restriction fragments were amplified in 2 consecutive PCR rounds (preamplification and selective amplification) using an MJ research PTC200 thermocycler.
The preamplification PCR was performed in 20 µl containing 2 µl of undiluted restriction fragment products, 1.5 mM MgCl2, 0.2 mM each deoxynucleoside triphosphates (dNTPs), 1 U Taq polymerase (Qiagen), 1x Taq buffer (Qiagen), and 75 ng each of EcoRI and MseI primers (5'-GAC TGC GTA CCA ATT CA-3' and 5'-GAT GAG TCC TGA GTA AC-3', respectively) carrying one selective nucleotide. The preamplification PCR profile was as follows: 30 s at 94° C, 1 min at 56° C, and 1 min at 72° C for 26 cycles. The PCR product was diluted 1:10 with distilled H2O for subsequent use in the selective amplification.
The selective PCR amplification was carried out in 20 µl containing 3 µl of diluted template DNA, 1.5 mM MgCl2, 0.2 mM each dNTPs, 1 U Taq polymerase (Qiagen), 1x Taq buffer (Qiagen), 5 ng of fluorescently IRD700 terminally labeled 3+ EcoRI selective primers (LI-COR Inc.), and 30 ng of 4+ MseI selective primers (Table 1). Selective amplification was performed as follows: 30 s at 94° C, 30 s at 65° C (first annealing step), and 1 min at 72° C. At each cycle the annealing temperature was decreased 0.7° C until 58° C, at which temperature 26 further cycles were conducted. Amplified products were resolved on a 40-cm 6% polyacrylamide gel using LI-COR instrumentation. Allele frequencies were calculated using a Bayesian method implemented in AFLP-SURV v1.0 (Vekemans et al. 2002). Variability for each primer pair combination was measured using Nei's (1987) gene diversity (analogous to expected heterozygosity He) and polymorphic index content (PIC) (Anderson et al. 1993). Exclusion probabilities (one parent known) were calculated according to Gerber et al. (2000).
|
Results and Discussion |
|---|
|
TopMaterials and MethodsResults and DiscussionReferences |
|---|
A total of 32 primer combinations were tested using 3 selective nucleotides on the EcoRI primer and 4 selective nucleotides on the MseI primer. From these, 12 primer combinations were selected based on complexity reduction, band clarity, and polymorphism (Figures 1 and 2 and Table 1). This protocol sufficiently reduced banding complexity for each of the 15 shark species. Species with two or more individuals showed large numbers of polymorphisms among all the primer pairs tested. A total of 59 and 78 polymorphic bands were detected from 1363 and 1145 bands identified (50- to 550-bp range) in C. taurus (N = 18) and C. carcharias (N = 7) (Table 1). For these 2 species highly informative levels of genetic variation were detected as indicated by the average expected heterozygosity, average PIC, and cumulative probability of exclusion (one parent known) given in Table 1. Surprisingly, other shark species (O. ornatus, Orectolobus sp., and G. cuvier) generated even higher numbers of polymorphic loci (106, 94, 86, respectively; Figure 2) from only pairs of individuals. This result indicates that SE Australian C. taurus and C. carcharias populations may have lower genetic diversity compared with the other species tested. This is congruent with Stow et al. (2006), who propose that Australian C. taurus populations have low genetic variation as a consequence of historical genetic bottlenecks.
|
|
As with any molecular technique, it is important to establish reproducibility. Our data integrity was measured via replicate selective PCR batch runs for all individuals across each of the 12 primer pair combinations. In addition, a number of animals had new duplicate DNA samples included throughout the entire procedure. Based on these repeated tests, no errors were detected and all samples produced clear and identical banding patterns.
The morphological similarity of many shark species can cause considerable confusion in species identification, particularly when dealing with only portions of an individual (e.g., shark fin). Highly informative genome-wide genetic markers can be used to identify species and even hybrid individuals and introgression (Bensch and Akesson 2005). Our method shows great promise for these sorts of applications. Genetic relationships among the 15 divergent shark taxa were evaluated based on the proportion of common AFLP bands observed. Visual inspection of the banding patterns matched our expectations, given the phylogenetic relationships of the species (Figure 2). For example, the pointer sharks (C. carcharias and I. oxyrinchus); wobbegongs (O. ornatus and Orectolobus sp), and whaler sharks (C. limbatus, C. amboinensis, C. leucas, and C. brachyurus) each had a much higher proportion of shared bands within their groups than among these groups. In addition, the highest proportions of shared bands were between the most closely related species in each group (based on previous phylogenetic studies by Swartz and Maddock [2002]).
This AFLP protocol has generated large numbers of genome-wide informative loci across divergent shark species. As a result, this technique has many potential applications, including individual DNA fingerprinting, genetic diversity estimates, population structure analysis, identification of hybridization, and identifying adaptive traits and species phylogenies (e.g., Bensch and Akesson 2005; Stow et al. 2006). A potential advantage of this method over traditional markers is that hundreds to thousands of dominant bi-allelic loci are evaluated across the entire genome which can reduce errors in diversity estimates and increase sensitivity (Mariette et al. 2002; Bensch and Akesson 2005). Given the need for the rapid implementation of conservation strategies that target sharks, a highly informative genetic technique with general utility across divergent shark species will be of particular interest to many biologists.
|
Acknowledgments |
|---|
We thank Kate Umbers for assistance in the laboratory, Charlie Huveneers for collecting samples, and Macquarie University for financial support. The director and staff at the Natal Sharks Board, South Africa, are thanked for their assistance. V.P. was supported via an National Research Foundation mobility grant.
|
Footnotes |
|---|
Corresponding Editor: Brian Bowen
Received December 1, 2005
Accepted September 27, 2006
|
References |
|---|
|
TopMaterials and MethodsResults and DiscussionReferences |
|---|
-
Anderson JA, Churchill GA, Autrique JE, Tanksley SD, Sorrells ME. (1993) Optimizing parental selection for genetic linkage maps. Genome 36:181–186.
Baum JK, Myers RA, Kehler DG, Worm B, Harley SJ, Doherty PA. (2003) Collapse and conservation of shark populations in the Northwest Atlantic. Science 299:389–392.
Bensch S and Akesson M. (2005) Ten years of AFLP in ecology and evolution: why so few animals? Mol Ecol 14:2899–2914.[CrossRef][Medline]
Campbell D, Duchesne P, Bernatchez L. (2003) AFLP utility for population assignment studies: analytical investigation and empirical comparison with microsatellites. Mol Ecol 12:1979–1991.[CrossRef][Medline]
Gerber S, Mariette S, Streiff R, Bodénés C, Kremer A. (2000) Comparison of microsatellites and amplified fragment length polymorphism markers for parentage analysis. Mol Ecol 9:1037–1048.[CrossRef][Medline]
Feldheim KA, Gruber SH, Ashley MV. (2001) Population genetic structure of the lemon shark (Negaprion brevirostris) in the western Atlantic: DNA microsatellite variation. Mol Ecol 10:295–303.[CrossRef][Medline]
Heist EJ. (2004) Genetics of sharks, skates and rays. In Carrier JC, Musick JA, Heithaus MR (Eds.). Biology of sharks and their relatives(CRC Press, New York) pp. 471–485.
Heist EJ, Jenkot JL, Keeney DB, Lane RL, Moyer GR, Reading BJ, Smith NL. (2003) Isolation and characterization of polymorphic microsatellite loci in nurse shark (Ginglymostoma cirratum). Mol Ecol Notes 3:59–61.
Mariette S, Le Corre V, Austerlitz F, Kremer A. (2002) Sampling within the genome for measuring within-population diversity: trade-offs between markers. Mol Ecol 11:1145–1156.[CrossRef][Medline]
Martin AP, Naylor GJP, Palumbi SR. (1992) Rates of mitochondrial DNA evolution are slow in sharks compared to mammals. Nature 357:153–155.[CrossRef][Medline]
Nei M. (1987) Molecular evolutionary genetics. (Columbia University Press, New York).
Nelson JS. (1994) Fishes of the world. (Wiley, New York).
Otway NM, Bradshaw CJA, Harcourt RG. (2004) Estimating the rate of quasi-extinction of the Australian sand tiger shark (Carcharias taurus) population using deterministic age- and stage-classified models. Biol Conserv 119:341–350.[CrossRef]
Pardini AT, Jones CS, Noble LR, Kreiser B, Malcolm H, Bruce BD, Stevens JD, Cliff G, Scholl MC, Francis M, et al. (2001) Sex-biased dispersal of great white sharks. Nature 412:139–140.[CrossRef][Medline]
Schrey A and Heist EJ. (2002) Microsatellite markers for the shortfin mako and cross-species amplification in Lamniformes. Conserv Genet 3:459–461.[CrossRef]
Smith SE, Au DW, Show C. (1998) Intrinsic rebound potentials of 26 species of Pacific sharks. Aust J Marine Freshw Res 49:663–678.[CrossRef]
Stow A, Zenger K, Briscoe D, Gillings M, Peddemores V, Otway N, Harcourt R. (2006) Isolation and genetic diversity of endangered grey nurse shark (Carcharias taurus) populations. Biol Lett 2:308–311.[CrossRef][ISI][Medline]
Swartz FJ and Maddock MB. (2002) Cytogenetics of the elasmobranchs: genomic evolution and phylogenetic implications. Mar Freshw Res 53:491–502.[CrossRef]
Wang Z, Baker AJ, Hill GE, Edwards SV. (2004) Reconciling actual and inferred population histories in the house finch (Carpodacus mexicanus) by AFLP analysis. Evolution 57:2852–2864.[CrossRef]
Whitehead A, Anderson SL, Kuivila KM, Roach JL, May B. (2003) Genetic variation among interconnected populations of Catostomus occidentalis: implications for distinguishing impacts of contaminants from biogeographical structuring. Mol Ecol 12:2817–2833.[CrossRef][Medline]
Vekemans X, Beauwens T, Lemaire M, Roldan-Ruiz I. (2002) Data from amplified fragment length polymorphism (AFLP) markers show indication of size homoplasy and of a relationship between degree of homoplasy and fragment size. Mol Ecol 11:139–151.[CrossRef][Medline]
Vos P, Hogers R, Bleeker M, Reijans M, Van de Lee T, Hornes M, Frijters A, Pot J, Peleman J, Kuiper M, et al. (1995) AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res 23:4407–4414.
CiteULike 
Connotea 
Del.icio.us What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||