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Multiplexing of Novel Microsatellite Loci for the Vulnerable Slipper Lobster Scyllarus arctus (Linnaeus, 1758) JOÃO FARIA1,2*, MARCOS PÉREZ‐LOSADA1, PATRICIA CABEZAS3,4, PAULO ALEXANDRINO1, AND ELSA FROUFE2 1

CIBIO—Research Center in Biodiversity and Genetic Resources, Universidade do Porto, Vairão, Portugal 2 CIMAR/CIIMAR—Interdisciplinary Centre of Marine and Environmental Research, Universidade do Porto, Porto, Portugal 3 Department of Biology, Brigham Young University, Provo, Utah 4 Computational Biology Institute, George Washington University, Ashburn, Virginia

ABSTRACT

The marine slipper lobster Scyllarus arctus represents an important economic resource in the NE Atlantic, and in some regions it has been severely exploited for decades. Even so, the basic aspects of the biology and ecology of S. arctus remain largely unknown and there is very little information available for the species, especially in terms of stock assessment and population dynamics. The aim of this study was to develop novel microsatellite markers using 454 sequencing for the slipper lobster S. arctus. Ten novel loci were described and amplified in 114 individuals using 3 multiplex reactions. Overall, microsatellite loci were highly polymorphic, and the number of detected alleles per locus across all individuals ranged from 6 to 29. Conservation strategies in the NE Atlantic region may consider these novel markers to study the population structure of S. arctus throughout its distribution area so that future efforts could be focused on identifying scales of connectivity and preserving stocks that have been severely depleted. J. Exp. Zool. 321A:119–123, 2014. © 2013 Wiley Periodicals, Inc.

J. Exp. Zool. 321A:119–123, 2014

How to cite this article: Faria J, Pérez‐Losada M, Cabezas P, Alexandrino P, Froufe E. 2014. Multiplexing of novel microsatellite loci for the vulnerable slipper lobster Scyllarus arctus (Linnaeus, 1758). J. Exp. Zool. 321A:119–123.

Because of its great economic value, decapod lobsters have experienced harvesting pressure throughout its geographic range (Spanier and Lavalli, 2007). Larger ships and more efficient technology are harming the lucrative lobster industry, and worldwide catch of lobsters in 2009 was estimated to be over 256,000 tons (FAO, 2009). The overexploitation and illegal fishing of this marine resource has led to a severe crisis in the commercial fisheries in many world oceans, and catches per year have declined dramatically over the last decades (Holthuis, '91; FAO, 2009). Regulatory measures for management and conservation of such an important resource should be aimed at protecting, not only

Grant sponsor: Fundação para a Ciência e Tecnologia; grant number: PTDC/BIA‐BEC/098553/2008; grant sponsor: Fundación Caja Madrid; grant sponsor: European Regional Development Fund (ERDF); grant sponsor: FCT—Foundation for Science and Technology; grant number: PEst‐C/MAR/LA0015/2011. Conflicts of interest: None.  Correspondence to: João Faria, Department of Biology, University of Azores, Apartado 1422, 9501‐801 Ponta Delgada, Azores, Portugal. E‐mail: [email protected] Received 12 September 2013; Accepted 15 November 2013 DOI: 10.1002/jez.1848 Published online 5 December 2013 in Wiley Online Library (wileyonlinelibrary.com).

© 2013 WILEY PERIODICALS, INC.

120 specific species, habitats, or biodiversity hotspots, but also its genetic diversity and population connectivity throughout its distribution range. In fact, determining connectivity levels between marine populations is crucial to our understanding of genetic structuring, population dynamics, and the resiliency of populations to human exploitation (Cowen et al., 2006). The slipper lobster Scyllarus arctus (Linnaeus, 1758), also known as locust lobster, is a crustacean marine species distributed in the Mediterranean and NE Atlantic. This species is listed in the Annex III of the Bern Convention, and of the Barcelona Convention Protocol concerning specially protected areas and biological diversity in the Mediterranean (i.e., species whose exploitation is regulated). This species has been widely captured as a food resource and in some regions its economic value is surprisingly high (e.g., up to 180/kg in Galicia, Spain), depending on the season. Despite its importance, the basic aspects of the biology and ecology of S. arctus remain largely unknown and there is very little information available for the species, especially in terms of stock assessment and population dynamics. In the last decades, an increased interest in population genetics and phylogeography of species, have prompt researchers to develop and use new and fast‐ evolving molecular tools. Microsatellite, mitochondrial DNA and other single‐locus markers, have been widely applied in marine organisms, and have increased the power and accuracy of estimating a variety of important parameters in conservation of species (Allendorf et al., 2010). Additionally, recent advances in next‐generation DNA sequencing technology have proved to be less time‐consuming and more cost‐effectively, allowing researchers to easily retrieve huge and valuable amounts of genetic information, especially for non‐model organisms (Shendure and Ji, 2008). For instance, microsatellites or simple sequence repeats (SSRs), which are tandemly repeated motifs of one to six bases, can be readily identified and described using these new whole‐genome sequencing technologies (Guichoux et al., 2011). The high degree of length polymorphism and the relative ease of scoring (depending on species) represent two major features that makes them of exceptional interest in genetic applications, including ecological, evolutionary, and conservation studies. Here, the recent 454 sequencing technology (Roche Applied Science, Penzberg, Germany) will be used to describe 10 new microsatellite loci that can be use to investigate the population genetic structure and conservation status of S. arctus throughout its distribution area.

MATERIALS AND METHODS A total of 114 specimens of S. arctus were collected in three different locations from the NE Atlantic (Foz do Neiva FZN: 41° 360 N, 8°480 W/N ¼ 74; Sagres SAG: 36°590 N, 8°560 W/N ¼ 23; São Miguel SMI: 37°420 N, 25°290 W/N ¼ 17), with a minimum and maximum distances between locations of 500 and 1,450 km, respectively. Tissue samples from pereiopods or antennae were collected and immediately preserved in 95% ethanol. Genomic DNA was extracted from muscle tissue using a standard salting‐ J. Exp. Zool.

FARIA ET AL. out protocol following treatment with proteinase K. High molecular weight DNA was isolated by isopropanol precipitation and visualized by gel electrophoresis. DNA yield was quantified using Qubit1 Fluorometer (InvitrogenTM, Carlsbad, CA, USA) following manufacturer's protocol. A DNA mix (>10 mg/mL) of 10 individuals was sent to Ecogenics GmbH (Zürich, Switzerland) for building a microsatellite‐enriched library. Size selected fragments from genomic DNA were enriched for SSR content by using magnetic streptavidin beads and biotin‐labeled CT, GT, GTAT, and GATA repeat oligonucleotides. The enriched library was analyzed on a Roche 454 platform using the GS FLX titanium reagents (Malausa et al., 2011). The sequences were received as multiple fasta files with the corresponding quality files, and initial PCR reactions were performed in simplex to validate selected loci and optimize annealing temperatures. For each primer pair, a gradient of annealing temperatures was carried out in a final volume of 10 mL with approximately 15 ng DNA template, 1 QiagenTM Multiplex PCR Kit, 0.4 mM of each primer and ddH2O. PCR cycles consisted of an initial denaturation step of 15 min at 95°C, 35 cycles of amplification (denaturation at 95°C for 30 sec, annealing at 50–64°C for 1 min, and extension at 72°C for 30 sec), and a final elongation step of 10 min at 72°C. Forward primers for loci that amplified and generated a specific product of the expected size were fluorescently labeled with NED, VIC, PET, or 6‐FAM (Applied Biosystems, Foster City, CA, USA), and a GTTT‐sequence “pig‐tail” tag was added to the 50 end of all reverse primers (see Brownstein et al., '96). All loci were tested for polymorphism, and PCR conditions were the same as before except for annealing temperatures, which were fixed for each primer pair. Fragment length analysis was conducted in an ABI 3130  l automated DNA sequencer using GENEMAPPERTM v.4.2 software (Applied Biosystems). Polymorphic primer pairs were combined into three multiplex PCR reactions with each locus assigned to a given fluorescent dye (Table 1). Multiplex PCR schemes allow markers to be genotyped more rapidly and cost efficiently by simultaneously amplifying multiple loci. Multiplex groups were made according to annealing temperatures, expected allele sizes, and by avoiding the potential formation of primer–dimers and hairpin structures, as indicated in AUTODIMER (Vallone and Butler, 2004). MULTIPLEX MANAGER v.1.0 (Holleley and Gerts, 2009) was used to combine all markers into the most efficient number of PCR reactions. Multiplex PCR reactions were performed in a 10‐mL solution, using 20–50 ng of template DNA, 5 mL of 0.5 Qiagen Multiplex PCR Kit and variable concentrations of primer pairs and fluorescent dyes (see Table 1). To increase specificity, a touchdown protocol was applied in all multiplex reactions (initial denaturation at 95°C for 15 min, followed by nine cycles of 95°C for 30 sec, annealing at 60°C for 60 sec, where the annealing temperature was lowered by 0.5°C on each consecutive cycle, and 72°C for 30 sec; 25 cycles at 95°C for 30 sec, annealing at 56°C for 45 sec, and extension at 72°C for 30 sec; eight cycles at 95°C for 30 sec, 53°C for 45 sec, 72°C for 30 sec; and a final extension of 30 min at 60°C).

MICROSATELLITE MARKERS FOR Scyllarus arctus

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Table 1. Characterization of 10 microsatellite loci in Scyllarus arctus.

Locus

Repeat

Primer sequence (50 –30 )

Arc1

(AC)11

Arc2

(CT)13

Arc3

(GT)14

Arc5

(TG)11

Arc10

(AC)22

Arc11

(ACT)15

Arc15

(TCAT)9

Arc21

(TAG)7

Arc22

(AGT)12

Arc23

(AC)14

F: CGATGCACAGGATGTACGTATG R: TACCTCAAAAGACTGCGTCC F: GACAGGACACGCCCAAAAAG R: CTGGGAAGACTGGGAAGGTC F: GGATGGGTTCGTACAATGGG R: AGCCTAACACCGCTAACTCC F: GGGAATAACGTGAGATTCAATAACG R: TGGCTCAAAAGATGCACACTC F: GCCTACACCAGCATCAAAGC R: GAGCAGCACTGCATCGCC F: GGCAGATAAGCGGAAACCTG R: TGCGTGGAGTAGGGAAAGAG F: TCGTGCTGTAGGGATGTACC R: AGTGAGCTTGGATATTGGATTAGG F: AATACCTCGCACGCTTGTTC R: TCCTCACCAACTGCATCACC F: TGCACAATAGTCCCTCCCAC R: ATTGGGACCACCACCACTAC F: CCATCCTAAAAGAAAAAGCACGG R: GAAAGTGTGTTCCTCACCGC

Multiplex (fluorescent dye)

Primer concentration (mM)

Size range (bp)

GenBank accession no.

A1 (NED)

0.16

96–128

KC357753

A3 (NED)

0.20

93–141

KC357754

A1 (PET)

0.64

101–175

KC357755

A1 (VIC)

0.08

98–170

KC357756

A2 (NED)

0.24

135–205

KC357757

A2 (PET)

0.16

134–170

KC357758

A1 (FAM)

0.16

139–245

KC357759

A3 (PET)

0.70

160–263

KC357760

A2 (VIC)

0.08

137–202

KC357761

A2 (FAM)

0.16

158–181

KC357762

F, forward primer sequence; R, reverse primer sequence.

Labeled PCR amplicons were re‐suspended in 10 mL Hi‐DiTM formamide and their sizes were determined using the ABI 3130  l automated DNA sequencer, with GeneScan 500LIZ1 as an internal size standard. Allelic diversity, observed (HO) and expected (HE) heterozygosity, and inbreeding coefficients (FIS) were estimated in GENETIX v.4.05 (Belkhir et al., '96–2004). Allelic richness was also estimated following the rarefaction method implemented in ADZE v.1.0 (Szpiech et al., 2008). Micro‐Checker v.2.2.3 (Van Oosterhout et al., 2004) was used to test for large allele dropout and scoring errors due to stuttering. Frequencies of null alleles were estimated by using the expectation maximization algorithm implemented in FREENA (Chapuis and Estoup, 2007). Deviations from the Hardy–Weinberg equilibrium (HWE) and linkage disequilibrium were tested using GENEPOP v.4.1 (Raymond and Rousset, '95) and 10,000 iterations. Deviation from neutrality was evaluated for all microsatellite loci using the FST‐outlier method implemented in LOSITAN (Antao et al., 2008). Pairwise FST estimates among locations were calculated using FSTAT v.2.9.3 (Goudet, '95) and departures of FST from the null hypothesis of panmixia were evaluated via a permutation test (1,000 iterations). For all analyses involving multiple tests, significance levels were adjusted by the sequential Bonferroni correction method.

RESULTS A total of 5,568 reads with an average length of 152 base pairs were generated by means of 454 pyrosequencing. Of these, 370

contained a microsatellite insert (52% were dinucleotides, 37% trinucleotides, and 11% tetranucleotides) and suitable primer design was possible in 74 reads, of which 23 were tested for polymorphism. Fifteen loci amplified and generated a specific product of the expected size. Five primer pairs had to be discarded either because they showed tri‐allelic patterns, artifactual peaks interfering with allele calling, and/or were monomorphic for the test‐samples screened. All 114 specimens were successfully genotyped for 10 microsatellite loci using three multiplex reactions, and marker sequences have been deposited in the GenBank database under the accession numbers KC357753– KC357762 (Table 1). Overall, microsatellite loci were highly polymorphic and the number of detected alleles per locus across all individuals ranged from 6 to 29 (4.5–17.6 using rarefaction method; Table 2). Mean expected heterozygosity (HE) was 0.879  0.035 (SE), ranging from 0.590 to 0.970, and mean observed heterozygosity (HO) was lower (0.687  0.049). FIS values ranged from 0.100 to 0.758. Two loci deviated from HWE due to heterozygote deficiency in all three populations (Arc3 and Arc15) and no linkage disequilibrium between loci was observed. Micro‐ Checker analysis suggested the presence of null alleles for these two loci, with relatively high frequencies (Table 2). Based on LOSITAN analysis, one locus (Arc21) was identified as candidate for positive selection with P‐value (simulated FST/observed FST) > 0.99. The analysis of genetic differentiation, after the J. Exp. Zool.

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Table 2. Genetic variation of Scyllarus arctus in 3 populations from NE Atlantic for 10 microsatellite loci. Na

HE

HO

FIS

Locus

FZN

SAG

SMI

FZN

SAG

SMI

FZN

SAG

SMI

Arc1 Arc2 Arc3 Arc5 Arc10 Arc11 Arc15 Arc21 Arc22 Arc23

4.5 13.6 16.1 15.0 16.0 8.0 11.4 12.3 11.6 7.6

5.1 12.8 15.0 13.2 13.7 7.8 10.5 8.3 11.2 9.0

5.8 15.3 14.9 11.3 17.6 8.8 10.0 9.9 12.5 10.7

0.590 0.936 0.954 0.945 0.955 0.840 0.903 0.876 0.913 0.803

0.683 0.927 0.948 0.929 0.935 0.849 0.895 0.821 0.890 0.844

0.571 0.950 0.944 0.917 0.970 0.799 0.926 0.877 0.927 0.891

0.217 0.855 0.449 0.867 0.919 0.833 0.283 0.775 0.865 0.671

0.591 0.882 0.539 0.941 1.000 0.696 0.450 0.900 0.783 0.783

0.214 1.000 0.500 0.688 0.733 0.765 0.231 0.765 0.941 0.706

FZN

SAG

Null allele freq. SMI

FST

FZN

SAG

SMI

0.633 0.137 0.634 0.000 0.03 0.087 0.050 0.055 0.000 0.04 0.532 0.442 0.480 0.003 0.26 0.083 0.014 0.257 0.000 0.04 0.038 0.071 0.251 0.001 0.01 0.008 0.184 0.044 0.007 0.01 0.688 0.504 0.758 0.001 0.32 0.117 0.100 0.132 0.068 0.06 0.053 0.047 0.005 0.000 0.02 0.165 0.075 0.213 0.019 0.07

0.02 0.03 0.19 — — 0.08 0.23 — 0.03 0.03

0.12 — 0.22 0.12 0.11 — 0.36 0.06 — 0.09

Significant values after sequential Bonferroni correction are in bold (P < 0.05). Null allele presence determined by MICRO‐CHECKER are indicated in  . Na, allelic richness; HE, expected heterozygosity; HO, observed heterozygosity; FIS, inbreeding coefficient; FST, fixation index; Null allele freq., frequency of null alleles.

removal of three loci (Arc3, Arc15, and Arc21), showed that pairwise FST values among populations ranged from 0.001 to 0.007 (FZN–SAG: 0.006; FZN–SMI: 0.001; SAG–SMI: 0.007) and global FST among all populations was 0.005. None of the values showed significant differences before and after sequential Bonferroni correction. This study confirms the usefulness of next‐generation pyrosequencing for the rapid discovery of microsatellite loci, and also the labor‐ and cost‐effectiveness of using multiplex schemes to amplify multiple loci. Despite the non‐genetic differentiation observed among populations/stocks separated by more than 1,450 km, these new microsatellite markers present a great tool to address genetic differentiation between more geographically distant stocks of S. arctus and identify major barriers to gene flow. Still, additional sampling efforts are needed to confirm the genetic homogeneity observed. These novel markers can be particularly useful for comparing stocks of S. arctus among fishery and protected localities. In fact, identifying the genetic connectivity patterns among populations of vulnerable or endangered species is fundamental for the implementation of proper conservation policies. The analysis of genetic structure and patterns of gene flow/connectivity is particularly important in species with commercial value, and there is now a growing interest by policy makers, and academics on the applicability of such data to identify management units for future exploitation and/or to define marine protected areas (Palumbi, 2003). Genetic information not only can help to better assess marine biodiversity but also contribute to manage fisheries more efficiently. Despite the preliminary status of this study, the maintenance of genetic homogeneity in S. artus is most likely a result of the large dispersal ability of its planktonic larvae. Phyllosomas spend more than 3 months in the water column going through several J. Exp. Zool.

developmental stages (Sekiguchi et al., 2007). During this phase, it is thought that larval behavior can play an important role in controlling dispersion, while taking advantage of ocean currents (Booth et al., 2005). For instance, the capacity of vertical movement, triggered by positive or negative phototactic responses, may enable larvae to occupy particularly favorable strata in the water column (Minami et al., 2001). Moreover, several scyllarid genera have been observed to be associated with gelatinous zooplankton (e.g., medusae), which may provide an additional indirect way of exploiting water movement (Booth et al., 2005). The presence of ovigerous females all year round with several reproductive peaks (depending on region) with fecundities between 30,000 and 70,000 eggs can also enhance the dispersive capacity of S. arctus (Pessani and Mura, 2007). Still, recent studies on crustacean species with similar life cycle characteristics have shown signs of structuring between populations and identification of barriers to gene flow and marine connectivity over large geographic regions (e.g., Pascoal et al., 2009; Fernández et al., 2011; Palero et al., 2011). These novel microsatellite markers can then be useful in future studies, with wider sampling schemes, for a better understanding of the genetic diversity and population structure of S. arctus, a commercially exploited slipper lobster in the NE Atlantic and Mediterranean regions.

ACKNOWLEDGMENTS We would like to thank Albano Beja, Luís Gouveia, Sónia Ferreira for samples from the Azores. This study was partially supported by a grant from the Fundação para a Ciência e Tecnologia (PTDC/ BIA‐BEC/098553/2008) to M.P.‐L. P.C. was funded by a fellowship from Fundación Caja Madrid. This research was also supported by the European Regional Development Fund (ERDF) through the COMPETE—Operational Competitiveness Programme and

MICROSATELLITE MARKERS FOR Scyllarus arctus national funds through FCT—Foundation for Science and Technology, under the project “PEst‐C/MAR/LA0015/2011.” We thank Susana Lopes for technical advice.

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J. Exp. Zool.

Multiplexing of novel microsatellite loci for the vulnerable slipper lobster Scyllarus arctus (Linnaeus, 1758).

The marine slipper lobster Scyllarus arctus represents an important economic resource in the NE Atlantic, and in some regions it has been severely exp...
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