A peer-reviewed version of this preprint was published in PeerJ on 30 August 2016. View the peer-reviewed version (peerj.com/articles/2205), which is the preferred citable publication unless you specifically need to cite this preprint. Mendes NJ, Cruz VP, Ashikaga FY, Camargo SM, Oliveira C, Piercy AN, Burgess GH, Coelho R, Santos MN, Mendonça FF, Foresti F. 2016. Microsatellite loci in the tiger shark and cross-species amplification using pyrosequencing technology. PeerJ 4:e2205 https://doi.org/10.7717/peerj.2205 Microsatellite loci in the tiger shark and cross-species amplification using pyrosequencing technology Natália J Mendes, Vanessa P Cruz, Fernando Y Ashikaga, Sâmia M Camargo, Claudio Oliveira, Andrew N Piercy, George H Burgess, Rui Coelho, Miguel N Santos, Fernando F Mendonça, Fausto Foresti The tiger shark (Galeocerdo cuvier) has a global distribution in tropical and warm temperate seas, and is caught in numerous fisheries worldwide, mainly as bycatch. It is currently assessed as near threatened by the International Union for Conservation of Nature (IUCN) Red List. In this study we identified 9 microsatellite loci through next generation sequencing (454 pyrosequencing) using 29 samples from the western Atlantic. The genetic diversity of these loci was assessed and revealed a total of 48 alleles ranging from 3 to 7 alleles per locus (average of 5.3 alleles). Cross-species amplification was assessed in three other species: Carcharhinus longimanus, C. acronotus and Alopias superciliosus. Given the potential applicability of genetic markers for biological conservation, these data may contribute to the population assessment of this and other species of sharks worldwide. PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2042v1 | CC-BY 4.0 Open Access | rec: 13 May 2016, publ: 13 May 2016 1 Microsatellite loci in the tiger shark and cross-species amplification using pyrosequencing 2 technology 3 4 Mendes NJ1, Cruz VP1, Ashikaga FY1, Camargo SM 5 Coelho R4, Santos MN4, Mendonça FF5, Foresti F1 1-5, Oliveira C1, Piercy A2, Burgess G3, 6 7 1Laboratório 8 Paulo, Brazil. 9 2Lake de Biologia e Genética de Peixes, Universidade Estadual Paulista, Botucatu, São Nona Campus, Valencia College, Florida, USA. 10 3Florida 11 Florida, USA. 12 4Portuguese 13 5Laboratório 14 Federal de São Paulo, Santos, São Paulo, Brazil. Program for Shark Research, Florida Museum of Natural History, University of Florida, Institute for the Ocean and Atmosphere, IPMA, Algarve, Portugal. de Genética Pesqueira e Conservação, Marine Sciences Institute, Universidade 15 16 Corresponding Author: Fernando Fernandes Mendonça 17 Universidade Federal de São Paulo – UNIFESP, Instituto do Mar, Laboratório de Genética 18 Pesqueira e Conservação, Av. Almirante Saldanha da Gama, 89. Ponta da Praia, Santos, SP – 19 Brasil - CEP 11030-400 e-mail: fernando.mendonca@unifesp.br 20 21 22 23 Running title: Microsatellite in the tiger shark by pyrosequencing 24 Abstract 25 The tiger shark (Galeocerdo cuvier) has a global distribution in tropical and warm temperate 26 seas, and is caught in numerous fisheries worldwide, mainly as bycatch. It is currently assessed 27 as near threatened by the International Union for Conservation of Nature (IUCN) Red List. In 28 this study we identified 9 microsatellite loci through next generation sequencing (454 29 pyrosequencing) using 29 samples from the western Atlantic. The genetic diversity of these loci 30 was assessed and revealed a total of 48 alleles ranging from 3 to 7 alleles per locus (average of 31 5.3 alleles). Cross-species amplification was assessed in three other species: Carcharhinus 32 longimanus, C. acronotus and Alopias superciliosus. Given the potential applicability of genetic 33 markers for biological conservation, these data may contribute to the population assessment of 34 this and other species of sharks worldwide. 35 36 37 38 39 40 41 42 43 44 45 46 47 Introduction 48 The tiger shark Galeocerdo cuvier (Péron & Lesueur 1822), is a shark from the order 49 Carcharhiniformes and family Carcharhinidae. It has a worldwide distribution in tropical and 50 temperate seas, and is considered a top predator generally requiring large foraging areas (Heupel 51 et al. 2014). Recent data show that this species can move long distances and occupies different 52 habitats, including coastal regions and is therefore more susceptible to anthropogenic threats 53 (Heupel et al. 2014). 54 Captured in many world fisheries as bycatch, the tiger shark is currently classified as 55 "Near Threatened" by the International Union for Conservation of Nature (IUCN). However, 56 some basic information, such as the characterization of population genetic structure, 57 identification of geographical restrictions to gene flow with possible local populations remain 58 broadly unknown. In light of this, information on their conservation status is difficult to assess. 59 For this reason, molecular markers have been increasingly used in species conservation and 60 management programs, including microsatellite molecular markers (Simple Sequence Repeats - 61 SSR). A range of SSR markers have been developed using the pyrosequencing technique, 62 generating information with millions of base pairs in a single run and in a short period of time. 63 Specifically for the tiger shark, nine SSR markers were previously developed on 64 specimens from the Hawaiian archipelago (Bernard et al. 2015), but cross-application was not 65 tested for other shark species. Thus, the objectives of this study were to identify other 66 microsatellites for the tiger shark in specimens from the Atlantic, and design additional 67 molecular markers that can be used in this and other shark species for population genetics 68 studies. 69 70 Material and Methods 71 Sampling 72 In fulfillment of data archiving guidelines (Baker 2013), primary data have been 73 deposited with Dryad. Samples of tiger shark were collected in landings of the fishing fleet from 74 São Paulo coast (n=12) and in scientific cruises in the Fernando de Noronha archipelago (n=6) 75 by researchers from the Biosciences Institute of Botucatu, São Paulo State University, and 76 Marine Sciences Institute of the São Paulo Federal University, in Brazil. Additionally, 11 77 samples were collected from the east coast of Florida, by the Florida Program for Shark 78 Research, University of Florida, USA. For evaluating the cross-amplification we used 6 samples 79 of Carcharhinus acronotus collected in São Paulo coast, 5 samples of C. longimanus and 5 80 samples of Alopias superciliosus, collected in the northeast Atlantic by onboard observers from 81 the Portuguese Institute for the Ocean and Atmosphere (IPMA), Portugal. All sampled tissues 82 were stored in 95% ethanol to ensure the integrity and quality of tissue for molecular analysis. 83 84 454 GS-FLX Pyrosequencing and Microsatellite Discovery 85 The total genomic DNA was extracted from each sample following the protocol 86 described by Ivanova et al. (2006). A sample of 100 µg of tiger-shark DNA from São Paulo coast 87 was sequenced on a Roche 454 GS FLX sequencer with Titanium platform “Genome sequencer 88 20 System” (Instituto Agrobiotecnológico de Rosário – INDEAR, Argentina), following 89 procedures described in Margulies et al. (2005). 90 To isolate microsatellites and design primers for population genetics all sequences of the 91 SSR were compiled using Primer3 (Rozen & Skaletsky 2000) and BatchPrimer3 (You et al. 92 2008). Primers were designed based on the following criteria: primer size of 20 bp (min = 18, 93 max = 22 bp), ideal annealing temperature of 60°C degrees (min = 55 ° C, max = 63 °C), GC 94 optimum of 60% (= 40% min, max = 80%) and the size of the amplified product ranging from 95 50-500 bp. The sequences were then grouped and aligned in the Clustal W software (Thompson 96 et al. 1994), identifying duplicated sequences for the same locus. 97 98 Novel Microsatellite Markers 99 The PCR amplifications to test the synthesized primers were performed in a Thermal 100 Cycler VeritiTM (Applied Biosystems™, Life Technologies) under the following conditions: 101 initial denaturing for 10 min at 95 °C; 30 cycles of 94 °C for 45s, the primer annealing 102 temperature (TA) was tested from of 51 °C to 57 °C for 50 s; 72 °C for 50s, and a final extension 103 at 72 °C for 20min. The total reaction volume was 10 µL and composed of 0.20 X PCR Buffer, 104 0.25 mM MgCl2, 0.05 mM of each dNTP, 0.5 units of Platinum Taq DNA polymerase 105 (Invitrogen™, Life Technologies, EUA), 0.10 µM reverse primer, 0.10 µM forward primer, and 106 30 ng of template DNA. 107 To verify the effectiveness of the reaction and the amplification of the fragments, 1.5 l 108 of the PCR product were subjected to electrophoresis on a 1% agarose gel. The amplified 109 products were compared with a 1Kb plus ladder (Invitrogen), subsequently visualized on a 110 transilluminator and photographed with a digital camera using the Kodak Digital Science 111 software. 112 Genotyping was done with the M13-tail PCR method of Schuelke (2000). The best loci, 113 that showed high polymorphism and quality of bands, were selected and further analyzed on an 114 ABI 3130xl sequencer (Applied Biosystems™, Life Technologies). The allele sizes were 115 determined using ROX 500 (Applied Biosystems) as an internal standard with the software 116 package GeneMapper 3.7 (Applied Biosystems). 117 We used the software GenAlex analysis 6.1 (Peakall & Smouse, 2006) to convert our 118 data to run in other analysis programs. Arlequin 3.5 (Guo & Thompson, 1992) was used to 119 calculate heterozygosity, number of alleles, Hardy-Weinberg equilibrium and linkage 120 disequilibrium. The program Cervus v.3.0.7 (Marshall et al. 1998) was used to test for the the 121 presence of null alleles and estimate, the inbreeding coefficient (Fis) and polymorphism 122 information content (PIC). 123 124 Results and Discussion 125 From the genomic material generated by the pyrosequencing technology, a total of 126 71,059 reads with an average size of 367 bp was obtained, consisting of 26,075,405 nucleotides, 127 which accounts for approximately 0.75% of the G. cuvier genome, assuming a genome size of 128 3.44Gb (estimated from the size of Rhincodon typus, Read et al. 2015). For the identification of 129 microsatellite sequences, the online software Batch Primer3 was used, and 615 microsatellite 130 loci were identified. A second filtration was subsequently performed with the software Primer 131 3.0 which identified 159 microsatellite loci. From these, we selected 30 loci which contained the 132 best scores of each primer pair with a size of 15 - 20bp, a GC of 40-50% and little variation in 133 the annealing temperature in the PCR reaction. Of these, 20 pairs of primers were synthesized 134 and tested, 9 being polymorphic with 1 trinucleotide and 8 dinucleotide (Table 1). The sequences 135 with polymorphic microsatellite markers in this study have been deposited in GenBank 136 (Accession numbers: KT598263-KT598271). 137 The application of the developed markers resulted in 48 alleles, with a minimum of 3 138 (TIG_25) to 7 (TIG_1, TIG_7, TIG_12) and average of 5.3 alleles per loci. Transferability tests 139 of the markers in other species showed positive amplification in C. longimanus, Alopias 140 superciliosus and C. acronotus. For the C. acronotus, two loci were polymorphic (TIG_17, 141 TIG_5), and for C. longimanus and A. superciliosus only one polymorphic locus were observed 142 in 5 samples of each species, TIG_15 and TIG_7 respectively (Table 2). 143 In tiger shark the observed heterozygosity (Ho) and expected heterozygosity (He) ranged 144 from 0.16 (TIG_17) to 1.0 (TIG_10) and 0.20 (TIG_25) to 0.72 (TIG_7) respectively. The Ho 145 was higher than He, suggesting an excess of heterozygotes relative to the model of Hardy- 146 Weinberg equilibrium (HWE). Significant differences from Hardy-Weinberg equilibrium after 147 Bonferroni correction (p<0.01) were detected in only 2 loci (TIG_10 and TIG_17). The deviation 148 in the Hardy-Weinberg equilibrium for locus TIG_17 (0.715) can be explained by a significant 149 value in intrapopulation inbreeding coefficient (Fis) (Kordicheva et al. 2010). This locus was the 150 only one with a positive value for the Fis, and may be evidence of a heterozygous deficiency 151 (Holsinger & Weir 2009), resulting in a decrease in genetic variability. 152 Imbalance values in Hardy-Weinberg equations when considering microsatellite locus 153 may be due to the presence of null alleles (Kordicheva et al. 2010). However, the presence of 154 null allele was not detected in the present study, indicating that the markers developed are of 155 high quality. Further, the polymorphism information content (PIC) was highly informative for all 156 the loci (PIC > 0.5), also indicating a high quality marker (Botstein et al. 1980). 157 In the present study, the average expected heterozygosity was approximately 0.50 and the 158 average observed heterozygosity was 0.55. The levels of genetic variability seen in this study 159 may be due to population differences resulting from remote sample locations. This is to be 160 expected given that the samples are coming from different oceans and the finding of significant 161 differences in the levels of heterozygosity among different groups would not be unforeseen. 162 163 Supplementary Material 164 Supplementary material can be found at http://www.ncbi.nlm.nih.gov/genbank/ 165 166 Acknowledgements 167 The authors thank all those who contributed to this study, including the researchers who 168 carried out the sample collection in Fernando de Noronha archipelago and the fishermen for 169 facilitating tissue collection during landings in the São Paulo coast. Sampling and data collection 170 from the Portuguese fishery were obtained and supported by the Programa Nacional de 171 Amostragem Biologica (PNAB) within the scope of the EU Data Collection Framework (DCF). 172 The authors are grateful to all fishery observers and longline skippers that helped collect samples 173 for this study. 174 175 References 176 177 178 Baker CS. 2013. Journal of Heredity Adopts Joint Data Archiving Policy. J Hered 104:1. doi: 10.1093/jhered/ess137 179 Bernard AM, Feldheim KA, Shivji MS. 2015. Isolation and characterization of polymorphic 180 microsatellite markers from a globally distributed marine apex predator, the tiger shark 181 (Galeocerdo cuvier). Conserv Genet Resour. 7:509–511. 182 183 184 185 186 187 188 189 Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet. 32: 314-331. Guo X, Elston RC. 1999. Linkage information content of polymorphic genetic markers. Hum Hered. 49: 112-118. Heupel M, Knip D, Simpfendorfer C, Dulvy N. 2014. Sizing up the ecological role of sharks as predators. Mar Ecol Prog Ser. 495: 291–298. Holsinger KE, Weir BS. 2009 Genetics in geographically structured populations: defining, estimating and interpreting FST. Nature Rev Genet. 10, 639–650. 190 Kordicheva SY, Rubtsova GA, Shitova MA, Shaikhaev GO, Afanasiev KI, Zhivotovsky LAA. 191 2010. Search for null alleles at the microsatellite locus of chum salmon (Oncorhynchus keta 192 Walbaum). Russ J Genet. 46: 1019-1022. 193 194 195 196 197 198 Margulies M, Egholm M, Altman W, Attiya S, Bader J, Bemben L. 2005. Genome sequencing in microfabricated high-density picolitre reactors. Nature. 437: 376–380. Marshall T, Slate J, Kruuk L, Pemberton J. 1998. Statistical confidence for likelihood-based paternity inference in natural populations. Mol Ecol. 7: 639–655 Peakall ROD, Smouse PE. 2006. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes. 6: 288-295. 199 Read TD, Petit III RA, Joseph SJ, Alam MT, RW, Ahmad M, Bhimani R, Vuong JS, Haase CP, 200 Webb H, Dove ADM. 2015 Draft sequencing and assembly of the genome of the world’s 201 largest fish, the whale shark: Rhincodon typus Smith 1828. PeerJ PrePrints 3:e1036 202 https://dx.doi.org/10.7287/peerj.preprints.837v1 203 204 Rozen S, Skaletsky H. 1999. Primer 3 on the WWW for general users and for biologist programmers. Totowa(NJ): Human Press Inc 205 206 Schuelke M. 2000. An economic method for the fluorescent labeling of PCR fragments. Nature Biotech. 18: 233-234. 207 Thompson JD, Higgins DG, Gibson TJ. 1994. CLUSTALW: improving the sensitivity of 208 progressive multiple sequence alignment through sequence weighting, position-specific gap 209 penalties and weight matrix choice. Nucleic Acids Res. 22: 4673-4680. 210 You FM, Huo N, Gu YQ, Luo MC, Ma Y, Hane D, Lazo GR, Dvorak J, Anderson OD. 2008. 211 BatchPrimer3: a high throughput web application for PCR and sequencing primer 212 design. BMC Bioinformatics. 9: 253. 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 Table 1. General information about the microsatellite analysis. 229 230 231 Table 2. Data for microsatellite loci of the cross-amplification in Carcharhinus longimanus, Carcharhinus acronotus and Alopias superciliosus. 232 233 234 235 236 Table 3. Data for microsatellite loci in the tiger shark, Galeocerdo cuvier. Table 1(on next page) General information about the microsatellite analysis. 1 Analyzes Number of reads 71.059 Selection of microsatellites (using BatchPrimer3) 615 Secondary selection of microsatellite (using Primer 3.0) 159 Amplification and control of PCR product on agarose gel 30 Microsatellite loci to synthesize with fluorescent dye 20 Polymorphism test with capillary sequencer 10 Microsatellite loci in linkage equilibrium 2 N of sequences 9 Table 2(on next page) Data for microsatellite loci of the cross-amplification in Carcharhinus longimanus, Carcharhinus acronotus and Alopias superciliosus. 1 2 C. acronotus 3 4 C. longimanus A. superciliosus Loci Na Range(bp) Na Range(bp) Na Range(bp) TIG_1 2 116-118 2 118-134 2 104-118 TIG_5 3 260-264 2 331-335 2 265-273 TIG_7 2 170-180 2 162-170 3 152-170 TIG_10 2 251-253 1 304 1 307 TIG_12 2 296-364 2 246-296 2 372-418 TIG_15 1 336 3 290-310 2 288-312 TIG_17 3 242-270 2 210-224 1 268 TIG_19 0 0 1 316 2 386-394 TIG_25 1 396 1 358 2 388-398 Na: number of alleles Table 3(on next page) Data for microsatellite loci in the tiger shark, Galeocerdo cuvier. 1 LOCI PRIMER SEQUENCE (5’→3’) MOTIF T ºC N NA RANGE(bp) HO HE HWE FIS PIC F(NULL) -0.194 TIG_1 F_ CTCTTGACGGTGCTCGATC (AC)10 53 29 7 116 - 154 0.758 0.642 0.711 -0.184 0.710 TIG_5 R_AATGGCAACTTTTCCTGTCC F_GCCAGCATCCATTCATACAG (CT)8 51 26 4 203-257 0.384 0.337 1.000 -0.141 0.589 (AC)15 57 27 7 169-183 0.925 0.726 0.318 -0.280 0.811 -0.101 (GT)10 59 29 5 256-276 1.000 0.655 0.000 -0.539 0.608 -0.245 (CA)11 53 28 7 364-376 0.535 0.520 0.543 -0.030 0.682 -0.213 (TG)15 55 25 6 231-241 0.520 0.463 0.675 -0.124 0.650 -0.233 (GT)11 57 25 4 268-286 0.160 0.554 0.000 0.715 0.734 -0.138 (TG)10 53 27 5 337-353 0.555 0.443 0.677 -0.260 0.627 -0.214 (CCT)5 55 27 3 331-349 0.222 0.206 1.000 -0.075 0.511 -0.285 -0.239 R_AGAGGGAAGTGGTGTGTGGT TIG_7 F_CACCAACCTCCCCATCAC R_CAGACATTCCTCCTCCATCC TIG_10 F_CTCAGCAGGTCTGGACAACA R_GGTGGTAGGAACATGGAACG TIG_12 F_TGCCATGAGTGCTGTTTTTC R_TGCCGCATTGTTACTGCTAC TIG_15 F_AACTGCCAAAAGGGACAAGA R_GTAAGCCCAACAGACCATCC TIG_17 F_TGAAGCTAACGAGGGGTCTG R_AGCGCAGAAGATCAAGAGGA TIG_19 F_TGCTTGTGTCTGAGGTGAGTG R_TTGGAGGTTCAATCCGAGAC TIG_25 F_CCGTGCCTATGTGGATTTCT R_CTTGAAGAGAGTGGGCGAAG 2 3 4 T ºC: primer annealing temperature, N: number of individuals analyzed, NA: number of alleles, He: expected heterozygosity, Ho: observed heterozygosity, HWE: probability of departure from Hardy–Weinberg equilibrium, Fis: inbreeding coefficient, PIC: polymorphism information content, F(Null): null alleles.