Characterization of highly informative cross-species microsatellite ...

Molecular Ecology Resources (2010) 10, 368–377

doi: 10.1111/j.1755-0998.2009.02761.x

PERMANENT GENETIC RESOURCES ARTICLE

Characterization of highly informative cross-species microsatellite panels for the Australian dugong (Dugong dugon) and Florida manatee (Trichechus manatus latirostris) including five novel primers MARGARET KELLOGG HUNTER,*† DAMIEN BRODERICK,‡ JENNIFER R. OVENDEN,‡ KIMBERLY PAUSE TUCKER,§ ROBERT K. BONDE,*† PETER M. MCGUIRE† and J A N E T M . L A N Y O N ¶ *Sirenia Project, Florida Integrated Science Center, U.S. Geological Survey, 2201 NW 40th Terrace, Gainesville, FL 32605, USA, †Department of Physiological Sciences, College of Veterinary Medicine, University of Florida, Box 100245 UFHSC, Gainesville, FL 32610, USA, ‡Molecular Fisheries Laboratory, Queensland Department of Primary Industries and Fisheries, Level 3 Ritchie Building, Research Lane, The University of Queensland, St. Lucia, Qld 4072, Australia, §College of Marine Science, University of South Florida, 140 7th Ave S. MSL 119, St. Petersburg, FL 33701, USA, ¶School of Biological Sciences, The University of Queensland, St. Lucia, Qld 4072, Australia

Abstract The Australian dugong (Dugong dugon) and Florida manatee (Trichechus manatus latirostris) are threatened species of aquatic mammals in the order Sirenia. Sirenian conservation and management actions would benefit from a more complete understanding of genetic diversity and population structure. Generally, species-specific microsatellite markers are employed in conservation genetic studies; however, robust markers can be difficult and costly to isolate. To increase the number of available markers, dugong and manatee microsatellite primers were evaluated for cross-species amplification. Furthermore, one manatee and four dugong novel primers are reported. After polymerase chain reaction optimization, 23 (92%) manatee primers successfully amplified dugong DNA, of which 11 (48%) were polymorphic. Of the 32 dugong primers tested, 27 (84%) yielded product in the manatee, of which 17 (63%) were polymorphic. Dugong and manatee primers were compared and the most informative markers were selected to create robust and informative marker-panels for each species. These crossspecies microsatellite marker-panels can be employed to assess other sirenian populations and can provide beneficial information for the protection and management of these unique mammals. Keywords: cross-species amplification, dugong, Dugong dugon, manatee, microsatellite primer, Trichechus manatus latirostris Received 1 April 2009; revision received 25 June 2009; accepted 3 July 2009

Introduction The Australian dugong (Dugong dugon) and Florida manatee (Trichechus manatus latirostris) are species in the order Sirenia, threatened by anthropogenic mortality and habitat degradation (Marsh et al. 2004; Reep & Bonde 2006). Limited reproductive growth potential (Rathbun et al. 1995) and small, fragmented populations (Laist &

Correspondence: Margaret Kellogg Hunter, Fax: (352) 374 8080; E-mail: [email protected]

Reynolds 2005) make the order highly susceptible to human exploitation (Bossart 1999; Bonde et al. 2004). Currently, all extant sirenian species are considered vulnerable to extinction on a global scale (IUCN 2008). The Florida manatee, located throughout the waters of the southeastern United States, is listed federally as endangered and is estimated to have a population of !3800 individuals (Florida Fish and Wildlife Research Institute 2009). As a result of their low reproductive rate, the annual mortality may exceed the population’s ability to produce a sufficient number of new recruits (O’Shea

Published 2009. This article is a US Government work and is in the public domain in the USA

P E R M A N E N T G E N E T I C R E S O U R C E S A R T I C L E 369 et al. 1985; Bossart 1999). Dugongs are found in the tropical Indian and Western Pacific Oceans, with the greatest population concentration in the marine waters of northern Australia. The largest populations, each with >14 000 dugongs, have been recorded in the Torres Strait (Marsh et al. 2004) and Shark Bay in Western Australia (Gales et al. 2004). The urban coast of Queensland, Australia, sustains a smaller population of !4200 dugongs (Marsh 2006). Australian dugongs are protected by the Environment Protection and Biodiversity Act 1999 (Department of the Environment and Heritage 1999). Conservation genetics is a useful tool to evaluate and monitor threatened species (Frankham et al. 2002; Avise 2004). Detailed information on the genetic status of threatened species can assist in the development of comprehensive long-term management and protection plans. Genetic studies can track migration of individuals and populations (Dixon et al. 2007), assist in modelling adult survival and reproductive rates (Lukacs & Burnham 2005), identify breeding populations and quantify diversity levels (King et al. 2006). Reduced genetic diversity in a species can decrease fecundity, compromise the ability to evolve or endure environmental change, and may ultimately result in extinction (Avise 2004). Microsatellites, short tandem repeats of nuclear DNA, are highly polymorphic co-dominant markers used to investigate the genetic health of small populations (Cerchio et al. 2005; Coltman et al. 2007; Dixon et al. 2007). They are especially useful in populations with limited genetic variation (Garcia-Verdugo et al. 2009). Typically, development of microsatellites for each new species demands considerable time, effort and cost. Cross-species comparisons can identify polymorphic microsatellite loci, so that fewer species-specific markers are needed to generate robust studies (Chbel et al. 2002; Maudet et al. 2004; Huang et al. 2005; Nguyen et al. 2007). In an effort to increase the number of primers for sirenian population and pedigree analyses, this study assesses the cross-species transferability and efficiency of previously developed dugong (Broderick et al. 2007) and manatee primers (Garcıá-Rodrı´guez et al. 2000; Pause et al. 2007) and five unpublished microsatellite loci. Using this information, the most effective Australian dugong and Florida manatee marker-panels are compiled, in which the identification of individual animals is achieved for each population.

Materials and methods Previously developed dugong (Broderick et al. 2007) and manatee (Garcıá-Rodrı´guez et al. 2000; Pause et al. 2007) microsatellite primers were employed following the reported conditions. Additionally, the unpublished dugong loci, DduA11, DduD02, DduE06 and DduG06,

developed by Broderick et al. (2007) and manatee locus TmlH23 were included. The polymerase chain reaction (PCR) conditions for the dugong and manatee samples amplified with dugong primers included 20 ng DNA, 10 pM each primer (Applied Biosystems), 3 mM MgCl2, 0.8 mM dNTPs, 0.5 lL QIAGEN’s Q-solution and 5 lL of QIAGEN’s multiplex master mix (kit contains HotStar Taq polymerase, MgCl2, dNTPs and PCR buffers). Amplifications were carried out on a PerkinElmer Thermal Cycler using the following conditions: initial denaturing at 94 !C for 15 min, 35 cycles at 94 !C for 30 s, at annealing temp (Tables 1 & 2) for 45 s, extension at 72 !C for 90 s, followed by a final extension at 72 !C for 45 min. The forward primer from each pair was modified on the 5¢ end with an engineered sequence (M13 tag, 5¢-GAGCGGATAACAATTTCACACAGG-3¢) to enable the use of a fluorescently labelled (FAM, PET, VIC and NED) third primer for detection on an Applied Biosystems PRISM 3130XL sequencer (Broderick et al. 2007). Alleles were sized against an internal size standard (GeneScan500LIZ) and scored using GeneMapper software (version 3.7; Applied Biosystems). The PCR conditions for the dugong and manatee samples amplified with manatee primers included 14 ng DNA, 0.8 mM dNTPs, 1x Sigma PCR buffer (10 mM Tris– HCl, pH 8.3, 50 mM KCl, 0.001% gelatin), 0.04 units Sigma Jump Start Taq polymerase and 0.24 lM of each primer (MWG Biotech). The addition of BSA to the manatee sample PCRs is indicated in Table 2. MgCl2 concentrations are reported in Tables 1 and 2. Amplifications were carried out on an MJ Research PTC-200 Thermal Cycler using the following conditions: initial denaturing at 95 !C for 5 min, 35 cycles at 94 !C for 30 s, annealing temp (Tables 1 & 2) for 1 min, 72 !C for 1 min, followed by a final extension at 72 !C for 10 min (Pause et al. 2007). Alleles were sized against an internal size standard (GeneScan-600ROX) on an Applied Biosystems 3730 sequencer and scored using GeneMarker software (version 1.5; Soft Genetics). A total of 32 dugong and 25 manatee microsatellites were tested for species-specific and cross-species amplification and polymorphism. Of those, 30 dugong and 21 manatee microsatellites were polymorphic and were tested across four study groups; (i) manatee samples amplified with manatee primers, (ii) dugong samples amplified with dugong primers, (iii) dugong samples amplified with manatee primers, and (iv) manatee samples amplified with dugong primers (Tables 1 and 2). The overall usefulness of the polymorphic loci, such as probability of identity, polymorphic information content (PIC) and effective number of alleles, was assessed among 98 dugong samples collected from the southern Queensland coast of Australia (Lanyon et al. 2002) and 91 Florida manatee samples representative of


370 P E R M A N E N T G E N E T I C R E S O U R C E S A R T I C L E Table 1 Characterization of Dugong dugon samples amplified by D. dugon and Trichechus manatus latirostris primers reported in this study and by Garcıá-Rodrı´guez et al. (2000), Pause et al. (2007) and Broderick et al. (2007). Loci are ranked by decreasing PIC values. The optimal Dugong dugon P(ID) was reached using the first 11 primers (denoted by the line)

Locus

GenBank Accession no. Primer sequence (5¢–3¢)

Repeat motif

Ta MgCl2 NA HO

DduB02

EF078600

(CA)26

58 3

10

0.802 0.797 0.764 4.820

(TG)16*(CG)6 62 3

7

0.734 0.790 0.757 4.645

(CA)27

58 3

8

0.765 0.788 0.753 4.622

(CA)20

58 3

6

0.593 0.789 0.751 4.643

(CA)28

58 3

6

0.780 0.772 0.734 4.313

(GT)19*

54 2

7

0.733 0.762 0.721 4.124

(TG)33

58 3

7

0.737 0.747 0.705 3.899

(TG)18

58 3

8

0.691 0.730 0.691 3.650

(GT)15

54 2

10

0.649 0.662 0.629 2.927

(TG)27

58 3

9

0.645 0.646 0.613 2.795

(TG)28

58 3

6

0.677 0.641 0.596 2.760

(CA)22

58 3

5

0.582 0.632 0.584 2.697

(CA)34*

58 3

6

0.612 0.575 0.540 2.339

(TG)20*

58 3

4

0.598 0.586 0.528 2.399

(TG)29*

58 2

5

0.538 0.607 0.526 2.522

(TG)19

58 3

5

0.459 0.551 0.491 2.212

(CA)13

54 2

6

0.532 0.509 0.484 2.026

(CA)16

58 3

6

0.531 0.515 0.479 2.050

(TG)17

58 3

3

0.602 0.552 0.458 2.216

(TG)17

58 3

3

0.531 0.526 0.436 2.097

(CA)18*

54 2

3

0.466 0.480 0.430 1.915

(TG)13

58 3

5

0.433 0.489 0.429 1.948

(TCTA)17*

58 3

3

0.510 0.462 0.414 1.849

(CA)17

58 3

4

0.542 0.509 0.407 2.026

(TG)22

58 3

4

0.453 0.445 0.387 1.792

(TC)13

58 3

3

0.485 0.450 0.380 1.809

TmaKb60 EF191342 DduC05

EF078613

DduD08

EF078625

DduE04

EF078631

TmaA04

AF223652

DduB01

EF078599

DduG11

EF078658

TmaA09

AF223653

DduG12

EF078659

DduE09

EF078636

DduH04

EF078663

DduC09

EF078614

DduC03

EF078611

TmaE7

EF191345

DduH09

EF078668

TmaE11

AF223658

DduA12

EF078598

DduH02

EF078661

DduE08

EF078635

TmaE08

AF223657

DduC11

EF078616

DduE11

EF078637

DduB05

EF078602

DduA01

EF078590

DduA07

EF078594

F:AAACCCAAATCGGATCATGT-FAM R:GCTGGGTTTTCCATTCTCAT F:TAGACACAGGCAAGCAGTGG-HEX R:AAGAGTGAGCGGAGATGTGG F:CCATTGGCATTACATTCGTG-FAM R:TGTTGTTCCCTTCTGAAGCA F:TGCATTGTTCTCTTTTGAATGG-PET R:TCGGTCTCATGCTACCTCAA F:TATCACAACACCCCATTCCA-NED R:CTGTCCAGAGGGAAAGGTCA F:GAACACAAGACCGCAATAAC-NED R:TGGTGTATCACTCAGGGTTC F:CACTGTGGTGAAAAGGGACA-VIC R:TTATTTGGCTTGGGACTTGG F:GGAGGCAAAAAGGAAAAAGC-FAM R:GCCTTTTCCTCACTCTGTGG F:GATGGGATACTGGGTTATGC-FAM R:ATGCAGACACTGGACATAGG F:TGGCACTTCTGAAACTTTGC-VIC R:TCTTCTCCAGCTTTGCCATT F:CCTGCCTGCTTCAGAGAATC-VIC R:CAGGAGCCAAACAGTGTCAA

F:CTGAATGCCCCTCACATCTT-VIC R:TATGCCCTTAGATGCCTTGG F:GCTTCTCTTTTGGGGTAGGC-VIC R:GGCATGGGGTCATTAGAAGA F:ACGGCCTAGAATCACATTGG-FAM R:CTTTGCAATGCCCTCACTC F:GCAAGCTTACATGTGTGTATGTG-HEX R:GTGGCTGACTTCTTGGAAGC F:GGAAGCCCTATGAAGCACAG-FAM R:TGGACGGGTATCGTATGTCA F:ACACACAACATCACTCATCCAC-FAM R:AAGCTGCGTTCTACTTCATATAATC F:ACAGAAGGCTCAAAGGCTGA-PET R:CAGCACTTTCTCCTCCAAGG F:GGAATCAACTCAACGGCAAT-NED R:CCCTTCTACCAGACCCTTCC F:GGGAAAAGGGGTAGGGAGTT-VIC R:TGAAGTGGCAAATGTTTTGTT F:GAATAGAGACTGGGCTAGAATCC-FAM R:GCCTTTTGGAGGGATAGAAGTAG F:GAAAGGCTTGCGACAATCAC-VIC R:GGATTTGCCAAAAAGCAGAC F:CCCAGCCAAACTGATACAGA-FAM R:CCATTCCTAAGGGTCAGCAA F:AAGCCTCACAGGAGACCTCA-FAM R:TGTAAACCTGCTGGAATCACC F:TTTAAAGGCAAAACCAGTATGTC-PET R:CAAAACGGGCCTAACCTACA F:AGACCCAGGCAGAGTTGAGA-NED R:CCCAAACTCTAGGGACCACA

HE

PIC

NE


P E R M A N E N T G E N E T I C R E S O U R C E S A R T I C L E 371 Table 1 Continued

Locus

GenBank Accession no.

Primer sequence (5¢–3¢)

Repeat motif

Ta

MgCl2

NA

HO

HE

PIC

NE

TmaE26

AF223659

(CA)25*

54

2

2

0.457

0.499

0.373

1.985

DduF07

EF078642

(CA)22

58

3

4

0.175

0.411

0.372

1.692

DduD11

EF078628

(TG)34*

58

3

4

0.435

0.392

0.363

1.640

TmaK01

EF191340

(CT)10(CA)11

56

1.5

4

0.433

0.353

0.307

1.540

TmaE4

EF191344

(GT)17*

58

2

4

0.325

0.317

0.293

1.459

DduF11

EF078646

(TG)19*

58

3

4

0.281

0.289

0.274

1.404

DduF06

EF078641

(TG)19*

58

3

2

0.245

0.216

0.192

1.274

DduE03

EF078630

(TG)15*

58

3

2

0.216

0.210

0.187

1.264

TmaE14

EF191346

(AT)7(GT)19*

61

2

2

0.195

0.198

0.177

1.244

DduG10

EF078657

(TG)27*

58

3

2

0.211

0.190

0.171

1.233

TmaA01

EF078590

F:CATTCCTGATCCACAAAATC-FAM R:CCTGTCTTCTCTCTGTTTCTCC F:TCCAGGGGAAGATTGATGAG-VIC R:GACCTATGCCCAGGCTGTTA F:CTGAAAGGCACAGGAGAAGG-PET R:CAGGCTGTCCAGGGAAAATA F:CTATCAAGCGGCATGTTCAA-HEX R:AGCTTGGGATCGTGTTTGTT F:CCTGACCAGTCCCTTTCC-FAM R:GGCTTTTCGGTTTCAACATA F:CCCCCAAATTTCCTAAATCA-FAM R:GCAGGTGGCTCTCCATTTTA F:CAGAGGTGGCTTGGAAGAAA-PET R:GGTAGATCAGTCCGGGTCCT F:TTTAGGGGCTCCAAAGGAAT-NED R:CTGCCATGCAAGTGACCTTA F:TTTTGGTAGTGGGATGACCA-FAM R:GTGGAGTAGGGTGGACCAGA F:AGTCCCGGTCCCAGGGC-NED R:CATGTCTGTGTTCCCCACTG F:TTTAAAGGCAAAACCAGTATGTC-FAM R:CAAAACGGGCCTAACCTACA

(TA)3(CA)10*

54

2

2

0.071

0.068

0.066

1.073

Ta, annealing temperature (!C); MgCl2 concentration (mM); NA, number of alleles; HO, observed heterozygosity; HE, expected heterozygosity; PIC, polymorphic information content, NE, effective number of alleles. *Interrupted repeat.

the four current management units identified in the state of Florida (USFWS 2007). The number of alleles (NA), observed and expected heterozygosities (HO and HE) and adherence to Hardy– Weinberg equilibrium (HWE) were assessed using Arlequin, version 3.1 (Schneider et al. 2000). The effective number of alleles (NE; Kimura & Crow 1964) was calculated using POPGENE, version 1.32 (Yeh & Boyle 1997). MICROCHECKER, version 2.2.3 (Van Oosterhout et al. 2004) tested for the presence of null alleles at a 95% confidence interval. Linkage disequilibrium was analysed by GENEPOP, version 3.2 (Raymond & Rousset 1995), and the PIC was tested using CERVUS (Kalinowski et al. 2007). GENECAP (Wilberg & Dreher 2004) calculated the unbiased probability of identity (PID), which is that the probability of two individuals drawn at random from a population will have the same genotype at the loci assessed (Paetkau & Strobeck 1994), and a related more conservative statistic for calculating PID among siblings [P(ID)sib; Evett & Weir 1998]. The majority of comparisons are not between siblings, so the population size in which individuals can accurately be identified is generally larger than the estimated P(ID)sib. Sample size is a critical parameter in sample–resample studies. The probability that two genotypes match by chance among n samples is !1 ) [1 ) P(ID)]n (Evett & Weir 1998) and is known as the shadow effect

(Mills et al. 2000). The shadow effect is exacerbated in large populations because the number of pairwise comparisons increases exponentially with sample size. As wild populations consist of both related and unrelated individuals, the actual probability that a pair of individuals in a given population will have the same genotype depends on the degree of relatedness in that population and hence lies between the two extremes of P(ID) and P(ID)sib. Therefore, GENALEX was used to calculate P(ID)observed to determine whether it was more appropriate to use the unbiased P(ID) or P(ID)sib when judging the discriminatory power of the markers (Waits et al. 2001). The most informative dugong and manatee markers were selected based on PIC scores and NE. Combinations of the highest-ranking loci were analysed until PID-values indicated that all individuals in the population have unique genotypes. Documented population sizes may be underestimated (Marsh et al. 2004) and intrapopulational breeding through long distance travel is possible (Fertl et al. 2005). Therefore, inflated population sizes of 20 000 and 4500 were used for the dugong and manatee PID-analyses respectively. PID-values were also calculated for the most informative species-specific primers. The number of primers that achieved similar PID-values in the cross-species and species-specific panels is reported.


372 P E R M A N E N T G E N E T I C R E S O U R C E S A R T I C L E Table 2 Characterization of Trichechus manatus latirostris samples amplified by Dugong dugon and T. m. latirostris primers reported here and by Garcıá-Rodrı´guez et al. (2000), Pause et al. (2007) and Broderick et al. (2007). Loci are ranked by decreasing PIC values. The optimal T. m. latirostris P(ID) was reached using the first 13 primers (denoted by the line)

Locus

GenBank Accession Primer no. sequence (5¢–3¢)

Repeat motif

TmaSC5

EF191349

(AC)5G(CA)18 60 2

)

8

0.612 0.771 0.731 4.283

(CA)13

58 3

)

8

0.681 0.669 0.625 2.992

(TG)29*

56 3

+

4

0.512 0.672 0.601 3.014

(CA)13

58 3

)

5

0.556 0.641 0.579 2.761

(TG)16*(CG)6

62 2

)

3

0.648 0.654 0.576 2.864

(TG)17

58 3

)

4

0.593 0.629 0.570 2.669

(CA)14

55 3

+

6

0.562 0.604 0.559 2.502

(AT)7(GT)19*

56 3

+

5

0.540 0.611 0.531 2.530

(CA)22

58 3

)

4

0.292 0.574 0.482 2.331

(CA)18*

60 3

)

4

0.527 0.572 0.480 2.319

(CA)28

58 3

)

3

0.527 0.502 0.403 1.998

(CT)10(CA)11

58 3

)

4

0.584 0.458 0.403 1.835

(GT)13

58 3

)

3

0.484 0.488 0.383 1.944

(CA)20

58 3

)

4

0.453 0.420 0.377 1.717

(AC)9

62 3

)

4

0.407 0.413 0.367 1.697

(CA)27

58 3

)

3

0.420 0.473 0.365 1.887

(TG)28

58 3

)

2

0.407 0.468 0.357 1.870

(GT)15

62 3

+

2

0.560 0.468 0.357 1.870

(GT)21

56 3

)

3

0.433 0.426 0.338 1.734

(CA)16

58 3

)

4

0.433 0.366 0.335 1.571

(CA)34*

58 3

)

2

0.113 0.418 0.329 1.709

(TCTA)13

54 2

)

3

0.389 0.357 0.326 1.550

(TG)19*

58 3

)

2

0.374 0.401 0.319 1.663

(TC)14*

54 3

)

3

0.352 0.385 0.318 1.621

(CA)22

58 3

)

3

0.389 0.362 0.317 1.562

F:ATTACCCAGCTCAGCATGTAC-FAM R:GCAACCTCTTCTGTTTTCAAA TmaE11 AF223658 F:ACACACAACATCACTCATCCAC-FAM R:AAGCTGCGTTCTACTTCATATAATC TmaE7 EF191345 F:GCAAGCTTACATGTGTGTATGTG-HEX R:GTGGCTGACTTCTTGGAAGC DduE06 EF078633 F:CACAACGCCTTCAGTGAAAA-VIC R:CATCTTTTTCCCCCAAAACA TmaKb60 EF191342 F:TAGACACAGGCAAGCAGTGG-HEX R:AAGAGTGAGCGGAGATGTGG DduE08 EF078635 F:GGGAAAAGGGGTAGGGAGTT-VIC R:TGAAGTGGCAAATGTTTTGTT TmaE1 EF191343 F:ATGGGTGAGTTTTGCT-HEX R:TGAAGAAATAGTGATGGTGT TmaE14 EF191346 F:TTTTGGTAGTGGGATGACCA-FAM R:GTGGAGTAGGGTGGACCAGA DduF07 EF078642 F:TCCAGGGGAAGATTGATGAG-VIC R:GACCTATGCCCAGGCTGTTA TmaE08 AF223657 F:GAATAGAGACTGGGCTAGAATCC-FAM R:GCCTTTTGGAGGGATAGAAGTAG DduE04 EF078631 F:TATCACAACACCCCATTCCA-NED R:CTGTCCAGAGGGAAAGGTCA TmaK01 EF191340 F:CTATCAAGCGGCATGTTCAA-HEX R:AGCTTGGGATCGTGTTTGTT TmaE02 AF223656 F:GTCTCTACGGCCTAGAATTGTG-HEX R:TTTCTCTACCTCTCCTCACACG DduD08

EF078625

F:TGCATTGTTCTCTTTTGAATGG-PET R:TCGGTCTCATGCTACCTCAA TmaJ02 EF191341 F:CACCATTGCCTCACAATCAG-HEX R:TGGTGGTTAACTTTCTGTGCAA DduC05 EF078613 F:CCATTGGCATTACATTCGTG-FAM R:TGTTGTTCCCTTCTGAAGCA DduE09 EF078636 F:CCTGCCTGCTTCAGAGAATC-VIC R:CAGGAGCCAAACAGTGTCAA TmaM79 AF223654 F:CCAATCATGTCCCAAACT-HEX R:CAATAGAAGAAGCAGCAG TmaSC13 EF191348 F:GGTTTGAAGAATCAGTTTGAA-FAM R:AATAAAGTTCTTCGTGTGCC DduA12 EF078598 F:ACAGAAGGCTCAAAGGCTGA-PET R:CAGCACTTTCTCCTCCAAGG DduC09 EF078614 F:GCTTCTCTTTTGGGGTAGGC-VIC R:GGCATGGGGTCATTAGAAGA TmaH13 EF191347 F:GCATCTTGGAAGATTTTTCCTT-FAM R:CACTGACAGATACGTGGTGGA DduF06 EF078641 F:CAGAGGTGGCTTGGAAGAAA-PET R:GGTAGATCAGTCCGGGTCCT TmaF14 AF223660 F:CTAAGACATTGCTCCAAAAGC-FAM R:GGGCAGTGGGATTTGAGATG DduH04 EF078663 F:CTGAATGCCCCTCACATCTT-VIC R:TATGCCCTTAGATGCCTTGG

Ta MgCl2 BSA NA HO

HE

PIC

NE


P E R M A N E N T G E N E T I C R E S O U R C E S A R T I C L E 373 Table 2 Continued

Locus

GenBank Primer Accession no. sequence (5¢–3¢)

DduG06 EF078653 TmaA02 AF223650 DduA11 EF078597 DduF11

EF078646

TmaE4

EF191344

TmlH23

FJ785428

DduA07 EF078594 DduD02 EF078619 TmaE26

AF223659

DduB05

EF078602

F:TCTGCAACTCCACCCTTACC-PET R:CCAGAGATGATGCCATGAGA F:CTCAGTCCAAACAGCTAATG-HEX R:TAGTCATTTGTGCAGAGTGC F:CATGGTGTCCGCTCTCAGTA-FAM R:AGCCCCTTCCATTTTCTGTT F:CCCCCAAATTTCCTAAATCA-FAM R:GCAGGTGGCTCTCCATTTTA F:CCTGACCAGTCCCTTTCC-FAM R:GGCTTTTCGGTTTCAACATA F:TTGAAGGCTAAGGACCATCG-HEX R:GGGACTTTCCAGCGTCTACA F:AGACCCAGGCAGAGTTGAGA-NED R:CCCAAACTCTAGGGACCACA F:TTGGTGGACTCTGAACGTGT-FAM R:TAGTCTCATAGCCCCGGTGT F:CATTCCTGATCCACAAAATC-FAM R:CCTGTCTTCTCTCTGTTTCTCC F:AAGCCTCACAGGAGACCTCA-FAM R:TGTAAACCTGCTGGAATCACC

Repeat motif

Ta MgCl2 BSA NA HO

HE

PIC

NE

(TG)10*(CG)5 58 3 (TG)12 (CA)16 54 3

)

2

0.356 0.386 0.310 1.622

)

2

0.352 0.357 0.292 1.551

(CA)18

58 3

)

2

0.308 0.332 0.276 1.493

(TG)19*

58 3

)

2

0.286 0.306 0.258 1.436

(GT)17*

55 3

+

2

0.264 0.262 0.226 1.352

(AGAT)14*

55 3

+

2

0.129 0.146 0.134 1.169

(TC)13

58 3

)

2

0.121 0.133 0.124 1.153

(CA)39*

58 3

)

3

0.132 0.125 0.117 1.141

(CA)25*

54 3

)

2

0.100 0.115 0.108 1.130

(CA)17

58 3

)

3

0.044 0.043 0.043 1.045

Ta, annealing temperature (!C); MgCl2 concentration (mM); BSA (0.4 mg ⁄ mL); NA, number of alleles; HO, observed heterozygosity; HE, expected heterozygosity; PIC, polymorphic information content, NE, effective number of alleles. *Interrupted repeat.

Results The majority of cross-species amplifications from the closely related sirenian species resulted in PCR fragments with proper microsatellite morphology and correct allele sizes, indicating homologous loci. Homology was not tested through sequence comparison. The dugong samples were amplified by 26 dugong and 11 manatee primers. The manatee samples were amplified by 17 dugong and 18 manatee primers. Thirteen of the dugong primers and seven of the manatee primers were employed in both species. Of the 25 manatee primers tested, 23 (92%) produced PCR product in the dugong. Of those that amplified, 11 (48%) were polymorphic. Of the 32 dugong microsatellite primers tested, 27 (84%) yielded PCR product in the manatee. Of those that amplified, 17 (63%) were polymorphic. The resultant combined primer values for each species are listed in Tables 1 and 2. The mean heterozygosity (HE), number of alleles (NA), PIC and effective number of alleles (NE) were determined for the various combinations of dugong and manatee primers (Table 3). The most informative marker-panels obtained a PID similar to that of the panels which used all of the available markers, while using fewer loci. The PID for each study group and that for the most informative marker-panels (using 11 markers for the dugong and 13 for the manatee) are reported in Table 4. The variability at each species-

specific microsatellite locus in this study was comparable with those formerly reported on dugongs and manatees.

Amplification of manatee loci in dugong All 11 polymorphic manatee microsatellites used to screen the dugong samples were determined to be in HWE. The number of alleles per locus ranged from 2 to 10. The single-locus observed heterozygosities ranged from 0.071 to 0.734. Linkage disequilibrium was not detected after 55 pairwise comparisons. No evidence of null alleles was observed. The mean proportion of individuals typed was 0.840. The eight manatee primers that amplified both dugong and manatee samples displayed more variation in the dugong samples. Manatee primers, TmaE4, TmaE7 and TmaKb60, identified larger NA, NE and PIC in the dugong than in the manatee samples (Tables 1 and 2). TmaKb60 identified considerably more alleles in the dugong than in the manatee samples (7 vs. 3 respectively).

Amplification of dugong loci in manatee The 17 polymorphic dugong microsatellites used to screen the manatee samples were determined to be in HWE after a sequential Bonferroni correction was applied. The number of alleles per locus ranged from 2 to


374 P E R M A N E N T G E N E T I C R E S O U R C E S A R T I C L E Table 3 Marker-panel summary for the dugong primers (DP), manatee primers (MP), all dugong and manatee primers together (AP), the most informative dugong (ID) and manatee (IM) specific primers and the most informative primer-panels for the dugong and manatee samples combined (IP). Averages are reported for the number of alleles (NA), observed and expected heterozygosity (HO and HE), polymorphic information content (PIC) and effective number of alleles (NE) NA Dugong samples DP 4.920 MP 4.727 AP 4.892 ID 6.615 IP 7.636 Manatee samples DP 2.940 MP 3.778 AP 3.370 IM 4.133 IP 4.690

HO

HE

PIC

NE

0.523 0.467 0.506 0.655 0.710

0.548 0.477 0.518 0.677 0.739

0.501 0.433 0.472 0.635 0.701

2.598 2.315 2.457 3.338 3.927

0.341 0.452 0.398 0.510 0.548

0.387 0.468 0.429 0.527 0.603

0.327 0.409 0.369 0.459 0.533

1.743 2.109 1.930 2.287 2.619

Table 4 Sibling [P(ID)sib] and unbiased [P(ID)] probability of identity values for the four study groups; dugong and manatee primers PCR amplified on dugong and manatee samples

Primer set

PID

Dugong samples

Manatee samples

Dugong primers

Sib P(ID) Sib P(ID) Sib P(ID)

2.70E-04 4.69E-09 7.10E-04 7.24E-09 5.15E-05 1.24E-11

8.90E-04 4.93E-07 9.03E-05 1.62E-09 1.39E-04 2.70E-09

Manatee primers Most informative primer set

5. Single-locus observed heterozygosities ranged from 0.044 to 0.593. Linkage disequilibrium was not detected after 136 pairwise comparisons. Evidence of null alleles was observed in DduC09 and DduF07. The mean proportion of individuals typed was 0.982. The 13 dugong primers that amplified both species identified equal or fewer alleles in the manatee than in the dugong (Tables 1 and 2). The dugong primers, DduE08, DduF06 and DduF07, identified equal NA and greater NE in the manatee than in the dugong samples. A greater PIC was observed for DduE08 and DduF07 in the manatee samples.

Most informative markers—dugong and manatee primers combined Dugong samples. The 37 dugong and manatee loci polymorphic in the dugong samples were sorted by PIC and NE. The top 11 loci produced an unbiased

P(ID) estimate of 1.24E-11 and a P(ID)sib estimate of 5.15E-05, in which unrelated individuals could be identified in a sample of 2.8E+05 and 140 respectively. Calculations in GENALEX determined that P(ID)observed was nearly identical to that of unbiased P(ID), indicating that relatedness in this population is unlikely to affect match probabilities to any great extent. After 55 pairwise comparisons, linkage disequilibrium was observed between TmaA04 ⁄ DduB01, TmaA09 ⁄ DduB02 and TmaA09 ⁄ DduE04. The cross-species panel PIC and NE-values were larger by 0.22 and 2.36 respectively, when compared to the dugong primers alone. It required two additional (N = 13) primers to obtain a similar PID-estimate [P(ID) 7.67E-12; P(ID)sib 2.93E-05] in the dugong-specific panel, resulting in less informative values at the other parameters. The mean values for the other marker-panels were lower than those for the combined-species marker-panel (Table 3).

Manatee samples. The 35 dugong and manatee loci polymorphic in the manatee samples were sorted by PIC and NE. The top 13 loci produced a P(ID)-estimate of 2.70E-09 and a P(ID)sib of 1.39E-04, in which unrelated individuals could be identified in population sizes of N = 1.9E+04 and 85 respectively. Calculations in GENALEX determined that P(ID)observed was midway between P(ID) and P(ID)sib. Linkage disequilibrium was not observed after 78 pairwise comparisons. The cross-species PIC and NE-values were larger by 0.21 and 0.88 respectively, when compared to the manatee primers alone. It required two additional (N = 15) manatee primers to obtain a similar PID-estimate [P(ID) 4.77E-09; P(ID)sib 1.54E-09] in the manatee-specific panel, resulting in less informative values at the other parameters. The mean values for the other marker-panels were lower than those for the combined primer set (Table 3). Overall, the manatee primers were more informative than the dugong primers in the cross-species studies. Of the 13 dugong primers that amplified in both species, three had a higher NE and two had a higher PIC in the manatee samples compared with the dugong samples. Of the nine manatee primers that amplified both species, six performed equally or better for all parameters in the dugong samples. Discussion The most informative markers from the combined manatee and dugong marker-panels produced more sensitive panels than the species-specific primers alone in both the dugong and manatee samples (Table 3). Although the panels may not be optimal for all dugong and manatee population studies, they are valuable during the initial phase of genetic analyses. The marker-panels used the


P E R M A N E N T G E N E T I C R E S O U R C E S A R T I C L E 375 fewest number of markers (decreasing cost and improving time effectiveness) required for individual identification. There was sufficient power in the combined-species panel to determine match probabilities confidently, while taking into account the relatedness, current population size and the potential for population growth. When compared with the most informative species-specific primers, the combined primer sets produced higher mean heterozygosity, number of alleles, effective alleles and PIC, and needed fewer primers to achieve similar PID-values. Overall, the dugong primers were more informative than the manatee primers in the dugong samples and the manatee primers were more informative than the dugong primers in the manatee samples tested (Table 3). In the cross-species studies, the manatee primers detected more alleles and were more informative than the dugong primers. Therefore, when the dugong and manatee primer sets were combined, the dugong samples had the greatest improvement and fewer loci were needed to obtain a lower PID. The dugong has larger population sizes and greater geographical distribution and habitat diversity than the Florida manatee subspecies or West Indian manatee populations. These circumstances can lead to an increase in genetic diversity (Garner et al. 2005; DiBattista 2007). Alternatively, the Florida manatee population has low DNA diversity, most likely resulting from a genetic bottleneck or founder event (Garcıá-Rodrı´guez et al. 1998).

Conservation implications The characterization of the most informative marker-panels for the Australian dugong and Florida manatee greatly enhances the conservation genetic tools for sirenians around the world. These molecular markers can be used to identify individuals and provide information on life history, disease processes and population sizes in conservation studies. Pedigree analyses can identify successful breeders and mating patterns (although markers for pedigree studies should take into account the effect of null alleles). Additionally, movement probabilities, adult survivorship (Langtimm et al. 2004) and reproductive rates gleaned from genetic studies can assist in population status modelling (O’Shea & Hartley 1995; Tringali et al. 2008). Genetic studies can also assist in identifying intrapopulational differentiation and genetically unique groups of animals that would benefit from increased protection. Manatee populations throughout the Caribbean and Central America have been severely depleted (Deutsch et al. 2008). The application of highly informative markers could help identify whether these populations are connected or should be considered distinct units for management actions (Hoffman et al. 2006; Coltman et al. 2007).

Likewise, microsatellite studies could assist conservation efforts where connectivity and relatedness are unknown for many dugong populations throughout the world. Identification and protection of source populations could lead to population growth and increased expatriation of individuals. The employment of more robust markers in sirenian population genetics studies should greatly facilitate the assessment, management and conservation efforts for the recovery of dugongs and manatees around the world.

Acknowledgements Dugong samples were collected by the University of Queensland Dugong Team under Scientific Purposes Permit no. WISP01660304, Moreton Bay Marine Park Permit no. QS2004 ⁄ CVL228 and University of Queensland Animal Ethics no. ZOO ⁄ ENT ⁄ 344 ⁄ 04 ⁄ NSF ⁄ CRL. Funding to screen manatee tissue against dugong primers was provided by the Winifred Violet Scott Foundation to J.M.L. Funding was provided to M.K.H. by the U.S. Geological Survey and the University of Florida College of Veterinary Medicine Marine Animal Health Program. Manatee samples were collected and provided by the USGS, under the USFWS Wildlife Research Permit MA791721. The authors would like to thank Coralie Nourisson for the TmlH23 primer sequence. Use of trade, product or firm names does not imply endorsement by the U.S. Government.

References Avise JC (2004) Molecular Markers, Natural History, and Evolution, 2nd edn. Sinauer Associates, Inc., Sunderland, MA. Bonde RK, Aguirre AA, Powell JA (2004) Manatees as sentinels of marine ecosystem health: are they the 2000-pound canaries? EcoHealth, 1, 255–262. Bossart GD (1999) The Florida manatee: on the verge of extinction? Journal of the American Veterinary Medical Association, 214, 1178–1183. Broderick D, Ovenden J, Slade R, Lanyon JM (2007) Characterization of 26 new microsatellite loci in the dugong (Dugong dugon). Molecular Ecology Notes, 7, 1275–1277. Cerchio S, Jacobsen JK, Cholewiak DM, Falcone EA, Merriwether DA (2005) Paternity in humpback whales, Megaptera novaeangliae: assessing polygyny and skew in male reproductive success. Animal Behaviour, 70, 267–277. Chbel F, Broderick D, Idaghdour Y, Korrida A, McCormick P (2002) Characterization of 22 microsatellites loci from the endangered Houbara bustard (Chlamydotis undulata undulata). Molecular Ecology Notes, 2, 484–487. Coltman DW, Stenson G, Hammill MO et al. (2007) Panmictic population structure in the hooded seal (Cystophora cristata). Molecular Ecology Notes, 16, 1639–1648. Department of the Environment and Heritage (1999) Report on the Operation of the Environment Protection and Biodiversity Conservation Act 1999. Department of the Environment and Heritage, Canberra, ACT, Australia. Deutsch C, Self-Sullivan C, Mignucci-Giannoni A (2008) Trichechus manatus. In: IUCN 2009. IUCN Red List of Threatened


376 P E R M A N E N T G E N E T I C R E S O U R C E S A R T I C L E Species. Ver. 2009.1. Available from http://www.iucnredlist. org (accessed on 15 September 2009). DiBattista JD (2007) Patterns of genetic variation in anthropogenically impacted populations. Conservation Genetics, 9, 141–156. Dixon JD, Oli MK, Wooten MC et al. (2007) Genetic consequences of habitat fragmentation and loss: the case of the Florida black bear (Ursus americanus floridanus). Conservation Genetics, 8, 455–464. Evett IW, Weir BS (1998) Interpreting DNA Evidence: Statistical Genetics for Forensic Scientists. Sinauer Associates, Inc., Sunderland, MA. Fertl D, Schiro AJ, Regan GT et al. (2005) Manatee occurrence in the northern Gulf of Mexico, west of Florida. Gulf and Caribbean Research, 17, 69–94. Florida Fish and Wildlife Research Institute (2009) Manatee Synoptic Surveys. Florida Fish and Wildlife Research Institute, St. Petersburg, FL, USA. Frankham R, Ballou JD, Briscoe DA (2002) Introduction to Conservation Genetics. Cambridge University Press, Cambridge. Gales N, McCauley R, Lanyon JM, Holley D (2004) Changes in abundance of dugongs in Shark Bay, Ningaloo and Exmouth Gulf, Western Australia: evidence for large scale migration. Wildlife Research, 31, 283–290. Garcıá-Rodrı´guez AI, Bowen BW, Domning DP et al. (1998) Phylogeography of the West Indian manatee (Trichechus manatus): how many populations and how many taxa? Molecular Ecology, 7, 1137–1149. Garcıá-Rodrı´guez AI, Moraga-Amador D, Farmerie WG, McGuire PM, King TL (2000) Isolation and characterization of microsatellite DNA markers in the Florida manatee (Trichechus manatus latirostris) and their application in selected sirenian species. Molecular Ecology, 9, 2161–2163. Garcia-Verdugo C, Fay MF, Granado-Yela C et al. (2009) Genetic diversity and differentiation processes in the ploidy series of Olea europaea L.: a multiscale approach from subspecies to insular populations. Molecular Ecology, 18, 454–467. Garner A, Rachlow JL, Hicks JF (2005) Patterns of genetic diversity and its loss in mammalian populations. Conservation Biology, 19, 1215–1221. Hoffman JI, Matson CW, Amos W, Loughlin TR, Bickham JW (2006) Deep genetic subdivision within a continuously distributed and highly vagile marine mammal, the Steller’s sea lion (Eumetopias jubatus). Molecular Ecology, 15, 2821–2832. Huang Y, Tu J, Cheng X et al. (2005) Characterization of 35 novel microsatellite DNA markers from the duck (Anas platyrhynchos) genome and cross-amplification in other birds. Genetics Selection Evolution, 37, 455–472. IUCN (2008) IUCN Red List of Threatened Species. Available from http://www.iucnredlist.org (accessed on 31 March 2009). Kalinowski S, Taper M, Marshall T (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology Notes, 16, 1099–1106. Kimura M, Crow JF (1964) The number of alleles that can be maintained in a finite population. Genetics, 49, 725–738. King TL, Switzer JF, Morrison CL et al. (2006) Comprehensive genetic analyses reveal evolutionary distinction of a mouse (Zapus hudsonius preblei) proposed for delisting from the US Endangered Species Act. Molecular Ecology, 15, 4331–4359.

Laist DW, Reynolds JE III (2005) Florida manatees, warm-water refuges, and an uncertain future. Coastal Management, 33, 279–295. Langtimm CA, Beck CA, Edwards HH et al. (2004) Survival estimates for Florida manatees from the photo-identification of individuals. Marine Mammal Science, 20, 438–463. Lanyon JM, Sneath HL, Kirkwood JM, Slade RW (2002) Establishing a mark-recapture program for dugongs in Moreton Bay, south-east Queensland. Australian Mammalogy, 24, 51–56. Lukacs PM, Burnham KP (2005) Review of capture-recapture methods applicable to noninvasive genetic sampling. Molecular Ecology, 14, 3909–3919. Marsh H (2008) Dugong dugon. In: IUCN 2009. IUCN Red List of Threatened Species. Ver. 2009.1. Available from http:// www.iucnredlist.org (accessed on 15 September 2009). Marsh H, Lawler I, Kwan D et al. (2004) Dugong distribution and abundance in Torres Strait. Australian Fisheries Management Authority Report, #R 01 ⁄ 0895, 45. Maudet C, Beja-Pereira A, Zeyl E et al. (2004) A standard set of polymorphic microsatellites for threatened mountain ungulates (Caprini, Artiodactyla). Molecular Ecology Notes, 4, 49–55. Mills L, Citta J, Lair K, Schwartz M, Tallmon D (2000) Estimating animal abundance using noninvasive DNA sampling: promise and pitfalls. Ecological Applications, 10, 283–294. Nguyen T, Genini S, Bui L et al. (2007) Genomic conservation of cattle microsatellite loci in wild gaur (Bos gaurus) and current genetic status of this species in Vietnam. BMC Genetics, 6, 77. O’Shea TJ, Hartley WC (1995) Reproduction and early-age survival of manatees at Blue Spring, Upper St. Johns River, Florida. In: Population Biology of the Florida Manatee (eds O’Shea TJ, Ackerman BB, Percival HF), pp. 157–170. National Biological Service Information and Technology Report 1, Washington, DC. O’Shea TJ, Beck CA, Bonde RK, Kochman HI, Odell DK (1985) An analysis of manatee mortality patterns in Florida. Journal of Wildlife Management, 49, 1–11. Paetkau D, Strobeck C (1994) Microsatellite analysis of genetic variation in black bear populations. Molecular Ecology, 3, 489–495. Pause KC, Nourisson C, Clark A et al. (2007) Polymorphic microsatellite DNA markers for the Florida manatee (Trichechus manatus latirostris). Molecular Ecology Notes, 7, 1073–1076. Rathbun GB, Reid JP, Bonde RK, Powell JA (1995) Reproduction in free-ranging Florida manatees. In: Population Biology of the Florida Manatee (eds O’Shea TJ, Ackerman BB, Percival HF), pp. 135–156. National Biological Service Information and Technology Report 1, Washington, DC. Raymond M, Rousset F (1995) GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. Journal of Heredity, 86, 248–249. Reep RL, Bonde RK (2006) The Florida Manatee: Biology and Conservation. University Press of Florida, Gainesville, FL. Schneider S, Roessli D, Excoffier L (2000) ARLEQUIN Ver. 2.001: A software for population genetics data analysis. Genetics and Biometry Laboratory, Department of Anthropology, University of Geneva, Geneva, Switzerland. Tringali MD, Seyoum S, Carney SL et al. (2008) Eighteen new polymorphic microsatellite markers for the endangered


P E R M A N E N T G E N E T I C R E S O U R C E S A R T I C L E 377 Florida manatee, Trichechus manatus latirostris. Molecular Ecology Resources, 8, 328–331. USFWS (2007) West Indian Manatee (Trichechus manatus) 5-Year Review: Summary and Evaluation. United States Fish and Wildlife Service, Atlanta, GA. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes, 4, 535–538. Waits LP, Luikart G, Taberlet P (2001) Estimating the probability of identity among genotypes in natural populations: cautions and guidelines. Molecular Ecology, 10, 249–256.

Wilberg MJ, Dreher BP (2004) GENECAP: a program for analysis of multilocus genotype data for non-invasive sampling and capture-recapture population estimation. Molecular Ecology Notes, 4, 783–785. Yeh FC, Boyle T (1997) Population genetic analysis of co-dominant and dominant markers and quantitative traits. Belgian Journal of Botany, 129, 157.
