Reference: Biol. Bull. 215: 164 –172. (October 2008) © 2008 Marine Biological Laboratory

Discovery and Cross-Amplification of Microsatellite Polymorphisms in Asterinid Sea Stars CARSON C. KEEVER1, JENNIFER SUNDAY1, CHARLENE WOOD1,2, MARIA BYRNE3, AND MICHAEL W. HART1,* 1

Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada; 2Department of Renewable Resources, University of Alberta, Edmonton, Alberta T6G 2H1, Canada; and 3Department of Anatomy and Histology, F-13, University of Sydney, 2006, Australia

Abstract. Variation in tandem repeats of two- to six-base nucleotide motifs (microsatellites) can be used to obtain inexpensive and highly informative multi-locus data on population genetics.We developed and tested a large set of cross-amplifiable sea star (Asterinidae) microsatellite markers from a mixed pool of genomic DNA from eight species. We describe cloned sequences, primers, and PCR conditions, and characterize population-level variation for some species and markers. A few clones containing microsatellites showed considerable similarity to sequences (including genes of known function) in other sea stars and in sea urchins (from the Strongylocentrotus purpuratus complete genome). The pooled genomic DNA method was an efficient way to sample microsatellites from many species: we cloned 2–10 microsatellites from each of eight species, and most could be cross-amplified in 1–7 other species. At 12 loci in two species, we found 1–10 alleles per microsatellite, with a broad range of inbreeding coefficients. Measures of polymorphism were negatively correlated with the extent of cross-amplification.

cies with different dispersal biology over a small sympatric portion of their extensive geographic ranges. More recent population genetic studies used anonymous dominant nuclear markers (AFLPs; Baus et al., 2005) or a single mtDNA locus (Colgan et al., 2005). Other mtDNA surveys that emphasized phylogeographic hypotheses have been limited by the presence and diversity of cryptic species with population samples (Waters and Roy, 2004a; Hart et al., 2006) and small population samples (Waters and Roy, 2004b; Waters et al., 2004a). Analysis of the size variation in microsatellite alleles offers several advantages over other classes of genetic markers (Selkoe and Toonen, 2006): co-dominance, high polymorphism, low cost per sample and locus, large numbers of variable loci with potential broad coverage of the genome, and analysis of preserved or very small tissue samples (even single embryos). Microsatellites are known from one sea star species, the crown-of-thorns Acanthaster planci (Yasuda et al., 2006), but appear to be rare in the genomes of some other sea stars (Baus et al., 2005; Harper and Hart, 2005). Here we describe the development and application of a large new suite of microsatellite markers for comparative analysis of genetic variation in asterinid population genetics. Genotyping results from two species show among-locus variation in polymorphism, inbreeding coefficients, and range of cross-amplification. We note some correlations among these three variables, and discuss the implications for use of different marker combinations in analyses of population structure and gene flow.

Introduction The highly variable dispersal potential and mating systems of asterinid sea stars (e.g., Byrne, 1995, 2005, 2006; Byrne and Cerra, 1996; Byrne et al., 2003; Hart et al., 2006) combined with specific conservation concerns (Emson and Crump, 1984; Law and Kelly, 2004; Tasmania Threatened Species Protection Act 1995) makes these species particularly interesting for analysis of population genetics. An early study used multiple allozyme loci (Hunt, 1993) to compare two abundant intertidal Australian asterinid spe-

Materials and Methods Microsatellite identification from pooled genomic DNA

Received 11 February 2008; accepted 6 May 2008. * To whom correspondence should be addressed. E-mail: mike_hart@ sfu.ca

We used standard proteinase K digestion and phenolchloroform extraction methods to obtain genomic DNA 164

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from gonads (of large-bodied species) or whole rays (in some small-bodied species). We sampled two to five individuals from each of eight asterinid species in five genera collected from shallow coastal habitats of southern and eastern Australia and western North America: Cryptasterina hystera Dartnall et al. 2003 and C. pentagona (Mu¨ller and Troschel, 1842) from central and northern Queensland, respectively; Meridiastra calcar (Lamarck, 1816) and M. oriens O’Loughlin, 2002 (New South Wales); Parvulastra exigua (Lamarck, 1816) (New South Wales) and P. parvivipara Keough and Dartnall, 1978 (South Australia); Patiria miniata (Brandt, 1835) (British Columbia); Patiriella regularis (Verrill, 1867) (Tasmania). We chose these species in order to increase the likelihood that we would sample microsatellites from different clades, modes of reproduction, and biogeographic regions. Genetic Identification Services (GIS, Chatsworth, CA) pooled similar amounts of high molecular weight genomic DNA from each species above (one or two individuals per species; 10 individuals in total). This bulk genomic DNA was partially digested and then size-selected for fragments about 300 –700 bp in length. These fragments were cloned into plasmid libraries enriched for CA, ATG, CAG, and TAGA microsatellite motifs using a method (Jones et al., 2002) that eliminates the need for probing (for detailed methods and recent examples see Tarvin, 2006; Carlon and Lippe´, 2007; Hull et al., 2007). We deliberately sequenced and PCR-tested more ATG and CAG clones and fewer CA or TAGA clones as a compromise between the expected lower polymorphism of tetranucleotides and the higher rate of nonspecific stuttering (and errors in allele size estimation) in dinucleotide PCR amplifications. GIS sequenced randomly selected clones using standard DYEnamic ET Terminator cycle sequencing reagents on an ABI model 377 DNA sequencer. DesignerPCR 1.03 (Research Genetics, Inc.) was used to select PCR primer sequences of similar length and melting temperature for each candidate clone. Primers were then tested under standard PCR conditions. PCR cocktails contained 6.15 ␮l water, 1.0 ␮l of 10⫻ enzyme buffer, 0.4 ␮l of 50 mmol l⫺1 MgCl2, 0.8 ␮l of 2.5 mmol l⫺1 dNTP mix, 0.3 ␮l of 20 ␮mol l⫺1 forward and reverse primers, 0.05 ␮l of 5 units ␮l⫺1 BioTaq (Bioline USA Inc.), and 1 ␮l of 2 ng ␮l⫺1 template DNA. PCR reactions were denatured at 94 °C (180 s), followed by 35 cycles of 94 °C (40 s), 55–57 °C (40 s), 72 °C (30 s), and a final extension step of 72 °C (240 s). Annealing temperature varied slightly among microsatellites depending on predicted primer melting temperatures. PCR products were visualized on 1% agarose gels and scored for qualitative presence or absence of a product similar to the expected size (based on the cloned fragment). Sequence analysis of clones Primer pairs designed from 45 clone sequences (GenBank accession numbers EF106738 –EF106783) produced

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consistent amplification results under the standard conditions above. We searched these clones against other echinoderm sequences (txid: 7586) in the nonredundant nucleotide and protein databases using BLAST 2.2.17 (www.ncbi.nlm.nih.gov/BLAST). We used these results to identify microsatellite clones that were strongly similar to other nucleotide sequences (BLASTn, optimized for somewhat similar sequences) or to gene predictions or identified protein-coding genes (BLASTx). All sets of significant BLASTx matches included an open reading frame from the complete Strongylocentrotus purpuratus sea urchin genome. We further characterized these latter similarities by using the Basic Local Alignment Search Tool (BLAST) to compare individual sequences against the sea urchin database at the Human Genome Sequencing Center at Baylor College of Medicine (http://www.hgsc.bcm.tmc.edu/projects/ seaurchin/) to obtain provisional gene identifications (GLEAN3 gene names). We then searched the partially annotated sea urchin genome (http://annotation.hgsc.bcm. tmc.edu/Urchin/cgi-bin/pubLogin.cgi) for these GLEAN3 genes. Species assignment and cross-amplification of microsatellites For each microsatellite that successfully cross-amplified in two or more species in preliminary testing, we assigned the cloned sequence to a single species by genotyping each of the individual sea stars in those species for which genomic DNA was used in library construction. We used the GIS standard PCR conditions (above) with the following modifications: we used Tsg DNA polymerase (BioBasic) in place of BioTaq; we added 0.8 ␮l of 25 mmol l⫺1 MgCl2 stock to the PCR cocktail (and adjusted the dH20 amount accordingly); we labeled the 5⬘ end of one forward primer with LI-COR IRDye700 or IRDye800 infrared dyes; we diluted the 100 ␮mol l⫺1 labeled primer stock 1:99 in 10 ␮mol l⫺1 unlabeled primer (to reduce background signal); for one trinucleotide (B105) we slightly increased the annealing temperature (58 °C) and reduced the MgCl2 concentration (0.5 ␮l) to reduce shadow banding. These PCR products were resolved in 25 mm 6% acrylamide gels on a LI-COR 4300 genetic analyzer with IRDye-labeled size standards. Fragment sizes were scored from gel images analyzed in Gene ImagIR (release 2004; LI-COR). We further explored the cross-amplification of these microsatellites in the Atlantic genus (Asterina) that is the sister group to the major Indo-Pacific asterinid clade (Hart et al., 1997; O’Loughlin and Waters, 2004; Waters et al., 2004b; Keever and Hart, 2008) from which we sampled all eight species in our microsatellite libraries. We tested 11 loci that were known to broadly cross-amplify among Indo-Pacific species. We used a sample of 10 individual A. gibbosa genomic DNA extractions from a single population from Wales that had been included in a recent AFLP study (Baus

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et al., 2005). We used the modified PCR conditions noted above but with a lower annealing temperature (50 °C) and fewer amplification cycles (30). Population polymorphism We genotyped 30 individuals of Meridiastra calcar from one population (Shell Harbour, New South Wales) at seven polymorphic trinucleotide loci (B202, B236, C8, C112, C114, C204a, C232), and 48 individuals of Patiria miniata from one population (Bamfield, British Columbia) at two of the same loci (B202, C8) plus five others (B11, B201, B209, C113, C210). In both cases, these loci had been chosen independently (by CCK and JS, respectively) for ongoing population genetic analyses on the basis of preliminary surveys of polymorphism and repeatability of PCR amplification and allele size estimation. We extracted DNA from individual tube feet using a simple proteinase K digestion (Addison and Hart, 2004). We used the modified PCR conditions and methods noted above. We estimated allele and genotype frequencies, inbreeding coefficients (FIS, by the Weir and Cockerham method), departure from HardyWeinberg equilibrium (by the exact test), and linkage disequilibrium using the web-based version of GENEPOP ver. 3.1c (Raymond and Rousset, 1995). For the last two analyses, we used the Bonferroni correction for multiple tests. Results Microsatellite characteristics We obtained positive test results for 45 primer pairs that included five CA repeats (labeled A in Appendix Table 1), 19 ATG (B), 18 CAG (C), and 3 TAGA (D). All CA and TAGA repeats were simple and uninterrupted (with the minor exception of a probable A3 C transversion in clone A4). In contrast, 7 of 19 clones containing ATG repeats and 12 of 18 CAG repeats included nonrepetitive interruptions caused by deletions or substitutions, or consisted of two or three similar repeated motifs, or included a compound repeat consisting of two similar trinucleotides. BLASTn comparisons of cloned sea star sequences produced four notable matches to other echinoderm nucleotide sequences. One ATG trinucleotide clone (B101) was strongly similar (expectation value E ⫽ 5 ⫻ 10⫺24) to the 3⬘ untranslated region in the genomic DNA sequence for the DNA binding protein Ap-Zic from another asterinid, Patiria pectinifera (AB231872; Aruga et al., 2006). Two other clones (B202, B236) resembled sea urchin protein coding genes: B202 included an open reading frame strongly similar to the Nk-class homeodomain protein Sp-Nk7 (E ⫽ 8 ⫻ 10⫺28); B236 was similar to the cell surface protein SRCR (scavenger receptor cysteine-rich, E ⫽ 5 ⫻ 10⫺5). The 3⬘ flanking region of one CA dinucleotide clone (A4) was similar (E ⫽ 2 ⫻ 10⫺9) to the flanking sequence of a CA dinucleotide from Acanthaster planci (AB220018). Two

clones (C114, C227) showed highly significant (E ⫽ 10⫺129) nucleotide similarity to each other. These sequences might represent two alleles at a single locus, but the clones showed considerable sequence divergence (48 nucleotide substitutions, 11.8%). BLASTx comparisons to coding sequences produced three matches to sea urchin genes (Appendix Table 1). All matches involved ATG or CAG repeats. Two of these strong similarities were to the predicted protein sequences from some sea urchin open reading frames to which we also found significant nucleotide sequence matches (B202, SpNk7; E ⫽ 7 ⫻ 10⫺17) (B236, SRCR; E ⫽ 1 ⫻ 10⫺12). A third clone (B114) included an open reading frame similar (E ⫽ 1 ⫻ 10⫺5) to a sea urchin adhesion protein in the extracellular matrix (anosim-1 or KAL-1, defective in human Kallmann syndrome). This locus was also a highly similar match (E ⫽ 1.3 ⫻ 10⫺12) to a recent unannotated expressed sequence tag (DB439856) cloned from 45-h-old embryos of Patiria pectinifera (K. Tachibana, Y. Suzuki, T. Shin-i, Y. Kohara, M. Sugano, T. Kishimoto, Center for Genetic Resource Information, National Institute of Genetics, Shizuoka, Japan; unpubl. data). Species assignment of loci Of 45 clones, 39 (0.87) could be unambiguously assigned to one of eight species (and in some cases to individual sea stars in the genomic DNA pool). The number of clones assigned to each species varied from 2 to 10 (Appendix Table 2). A majority of clones (25) were isolated from one clade consisting of the sister genera Meridiastra ⫹ Patiria (Appendix Table 2). Six other microsatellites could not be reliably assigned to individual species either because the cloned allele size was found in individuals from two or more species (B106, B202, B234, B236) or because the cloned allele size was not found among any individuals that were genotyped (B222, C112). Cross-amplification patterns A majority of microsatellites (23/45) could be crossamplified in more than one Indo-Pacific species from the genomic DNA pool (Appendix Table 2). These included all of the clones with open reading frames similar to sea urchin genes that encode transcription factors and cell surface proteins. Two of these microsatellites could be amplified in all eight species from the genomic DNA pool, but one was fixed for a single allele (B236, SRCR), while the other was polymorphic within and between species (B202, Sp-Nk7; see below). We found no strong correlation between the number of amplifiable species (1– 8) and either (i) the cloned allele size (109 –299 bp; r ⫽ ⫺0.012, P ⫽ 0.934) or (ii) the length of the repeat motif (2– 4 bp; r ⫽ 0.079, P ⫽ 0.602). We found a weak association between motif type and broad cross-amplification: of the 13 microsatellites that could be broadly cross-amplified in four or more species, 12

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were ATG (4) or CAG (8) repeat motifs, but this slight difference between cross-amplification of trinucleotides (12/37) versus other motifs (1/8) was not significant by Fisher’s exact test (P ⫽ 0.252). We found a weak correlation (r ⫽ 0.444, P ⫽ 0.272) between the number of microsatellite clones assigned to a species (2–10) and the number of other microsatellites that could be cross-amplified in the same species (7–12). Five of 11 microsatellites that were broadly cross-amplified among Indo-Pacific species could also be amplified in the outgroup Asterina gibbosa. The success or failure of these cross-amplifications was not obviously associated with repeat motif or interruptions, species to which the clone was assigned, or the number of Indo-Pacific species in which the microsatellite could be amplified. All five of the successfully cross-amplified markers were fixed for a single allele size in our small sample of 10 A. gibbosa individuals. This lack of variation is surprising: three of these microsatellites (B202, C8, C204a) are known to be polymorphic in Indo-Pacific species (Appendix Table 3, see below), and previous studies show within-population variation in dominant AFLP fingerprints of A. gibbosa (Baus et al., 2005).

Population polymorphism Within single Patiria miniata and Meridiastra calcar population samples we found 2–10 alleles per microsatellite (Appendix Table 3) and broad ranges of observed (0.10 – 0.72) and expected (0.12– 0.79) heterozygosities. We found no pairs of microsatellites in significant linkage disequilibrium in either species. In each species, two microsatellites showed high inbreeding coefficients and significant heterozygote deficits relative to Hardy-Weinberg equilibrium expectations. We found the highest number of alleles (C210) and highest inbreeding coefficients (B11) at some loci that amplified in only one species (Appendix Table 3), and the lowest values of both variables at a locus that cross-amplified in all species tested (B202). Over all 14 samples (including pseudoreplication of B202 and C8), both number of alleles (r ⫽ ⫺0.566, P ⫽ 0.016) and inbreeding coefficient (r ⫽ ⫺0.567, P ⫽ 0.016) were significantly correlated with breadth of cross-amplification. However, this conclusion depended to some extent on including both samples of a microsatellite (B202) with the broadest cross-amplification and lowest genetic diversity. When we dropped two of the pseudoreplicated observations (n ⫽ 12) from either P. miniata or M. calcar, these four correlations were of similar sign and magnitude but of marginal statistical significance (0.039 ⱕ P ⱕ 0.084). We found similarly marginal statistical significance when we analyzed just the seven microsatellites from P. miniata that differed broadly in breadth of cross-amplification (number of alleles, r ⫽ ⫺0.625, P ⫽ 0.071; inbreeding coefficient, r ⫽ ⫺0.651, P ⫽ 0.060).

Discussion The among-species and among-clade differences in the number of cloned microsatellites highlight one of the potential pitfalls of our microsatellite isolation approach using pooled genomic DNA. The pooling approach helps to ensure that all microsatellites from different species are isolated simultaneously under identical enrichment conditions (and at 1/n the cost for libraries developed for each of n species). However, libraries enriched for microsatellites from single species (at higher cost) could have allowed us to find many more markers from Cryptasterina and Parvulastra species and avoid the potential effects of using mostly cross-amplified markers in population analyses of those species (see below). Many published microsatellite descriptions (primer notes) do not specifically include BLAST sequence comparisons to known genes, but we found some broadly crossamplifiable microsatellites that we confidently identify with coding sequences. Several empirical studies and reviews have noted broader cross-amplification among microsatellites in genes identified from expressed sequence tags than among microsatellites isolated from genomic DNA (see Bouck and Vision, 2007). Thus, these markers might be used in many asterinid species but should be scrutinized for unusual patterns of variation. These anomalies might include low allelic polymorphism or nonconformation to the Ewens-Watterson sampling distribution caused by functional constraints on the gene product (e.g., Li et al., 2002, 2004) or by strong allelic divergence associated with adaptive features of gene function and microsatellite allele size effects (e.g., Hammock and Young, 2004). Microsatellites often show high inbreeding coefficients that may be caused by segregation of null alleles. This can be due to evolutionary divergence of flanking sequences that include the PCR primer sites (Selkoe and Toonen, 2006). In two population samples we found a few examples of high inbreeding coefficients associated with significant heterozygote deficits (Appendix Table 3). High rates of sequence evolution and high frequencies of microsatellite and allozyme null alleles may be associated with biological and demographic variables such as mating system differences among species (Zouros and Foltz, 1984; Addison and Hart, 2005). One goal of our microsatellite development was the discovery of broadly cross-amplifiable markers. Cross-amplification varied considerably among loci (Appendix Table 2), and we found some evidence that breadth of crossamplification was negatively correlated with allelic diversity and inbreeding coefficients (Appendix Table 3). These associations are similar to the ascertainment bias frequently observed in microsatellite cross-amplifications and assumed to be caused by aspects of microsatellite enrichment or isolation that favor the discovery of longer alleles in the target species relative to shorter alleles (with less allelic

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diversity) at the same loci when cross-amplified in other species (e.g., Ellegren et al., 1995; Hutter et al., 1998). Other empirical studies and reviews have also suggested a broad correlation between the rate of microsatellite sequence evolution and allelic richness, inbreeding coefficients, and frequency of null alleles (Rungis et al., 2004; Pashley et al., 2006). These correlations suggest the need for awareness of among-marker variation and careful selection of markers in asterinid population analyses that use many cross-amplified markers in species or clades (Cryptasterina, Parvulastra) from which we cloned few microsatellites. Such studies could be biased toward lower allelic richness and lower inbreeding coefficients (compare to Primmer et al., 1996; Barbara´ et al., 2007). These patterns also argue for the development and use of improved standardization methods in estimates of population differentiation (Hedrick, 2005; Meirmans, 2006) in population analyses using these markers. Acknowledgments Thanks to Jason Addison (UC Davis), Mark Todd (Genetic Identification Services), Mando Beciaris, Kate Grozier, and Samson Wu (SFU) for laboratory assistance or comments. David Garfield (Duke University) helped us search for sea urchin genes. David Darrock and Mike Bruford (Cardiff University) gave us Asterina gibbosa DNA samples. This work was supported by research grants from the Natural Sciences and Engineering Research Council (MWH), Simon Fraser University (MWH), the Australian Research Council (MB), and the National Science Foundation (R. K. Grosberg and R. Toonen). Literature Cited Addison, J. A., and M. W. Hart. 2004. Analysis of population genetic structure of the green sea urchin (Strongylocentrotus droebachiensis) using microsatellites. Mar. Biol. 144: 243–251. Addison, J. A., and M. W. Hart. 2005. Spawning, copulation and inbreeding coefficients in marine invertebrates. Biol. Lett. 1: 450 – 453. Aruga, J., A. Kamiya, H. Takahashi, T. J. Fujimi, Y. Shimizu, K. Ohkawa, S. Yazawa, Y. Umesono, H. Noguchi, T. Shimizu, et al. 2006. A wide-range phylogenetic analysis of Zic proteins: implications for correlations between protein structure conservation and body plan complexity. Genomics 87: 783–792. Barbara´, T., C. Palma-Silva, G. M. Paggi, F. Bered, M. F. Fay, and C. Lexer. 2007. Cross-species transfer of nuclear microsatellite markers: potential and limitations. Mol. Ecol. 16: 3759 –3767. Baus, E., D. J. Darrock, and M. W. Bruford. 2005. Gene-flow patterns in Atlantic and Mediterranean populations of the Lusitanian sea star Asterina gibbosa. Mol. Ecol. 14: 3373–3382. Bouck, A., and T. Vision. 2007. The molecular ecologist’s guide to expressed sequence tags. Mol. Ecol. 16: 907–924. Byrne, M. 1995. Changes in larval morphology in the evolution of benthic development by Patiriella exigua (Asteroidea: Asterinidae), a comparison with the larvae of Patiriella species with planktonic development. Biol. Bull. 188: 293–305. Byrne, M. 2005. Viviparity in the sea star Cryptasterina hystera (Asterinidae)—Conserved and modified features in reproduction and development. Biol. Bull. 208: 81–91.

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Appendix Characterization, cross-amplification, and polymorphism of asterinid sea star microsatellite loci Appendix Table 1 Microsatellite sequence accession numbers, repeats, and PCR primers GenBank Name accession no.

Repeat

A4

EF106738.1

(CA)7CC(CA)6

A102

EF106739.1

(CA)7

A104

EF106740.1

(CA)14

A108

EF107741.1

(CA)11

A110

EF106742.1

(CA)13

B3

EF106743.1

(ATG)6

B4a

EF106744.1

(ATG)6ATA(ATG)2CTGATGATA(ATG)2

B6

EF106745.1

ATG(ATTG)2ATGAG(ATG)3

B11

EF106746.1

(ATG)8

B101

EF106747.1

(ATG)5

B105

EF106748.1

(ATG)2AGG(ATG)2(AGG)2(ATG)3(AGG)4(ATG)2GGGAGG(ATG)2

B106

EF106749.1

(ATG)5

B110

EF106750.1

(ATG)8

B114

EF106752.1

(ATG)9

B201

EF106753.1

(ATG)6

B202

EF106754.1

(ATG)5(ACG)2(ATG)5

B209

EF106755.1

(ATG)3GAG(ATG)4

Label

Primers

IRDye 700 5’ CGACGACGGAAGTAAGTTC GGGAAAACAAAGGAAAGTCC IRDye 800 5’ GCCTTATGAGGACCATTTG GCGTGGCTATTCAGAGAAC IRDye 700 5’ TCTTTGGAACAATACCCACTAC GGGGAATGGGATTTACTATTC IRDye 800 5’ ATGGATCTCACCAAGTAGACAG CACAGGACGTATGTAACAACAG IRDye 700 5’ GGTCGGTCGATATTAGATTGC GAAGGGGAGAGACAGCTCAG IRDye 700 5’ AGGGATAAAAACACCTGGTG TTTCTGTTGACTTGCAGTAACC IRDye 700 5’ AAGCATCAGCATCATTATTAGC AAGACGCCTTCAAGAAAATC IRDye 800 5’ GCATTCATCGGTCTCGTC GATCCAAGGGGAGGACTG IRDye 800 5’ ATCTCGGTTGTGTTATTAGAGG TCTCGACCATGAAATATACATG IRDye 700 5’ CACACCGTTTCGTTTTTAGTC TTTGGACCGCTATTCACTTAC IRDye 700 5’ CCCCGTGTCTTGGTTTTC ATGAGGAAGATGAAGGTGGAG IRDye 700 5’ TGACGGTAAAAAGAAGTTTGC GCCATAATCATCATCATCCTC IRDye 700 5’ GCAGATACTTCAGGGTTGTG ACGATGACGATGATGATGTT IRDye 800 5’ GCCCAGGACACAAGAAGTG GGAGCCATAGGGAGAAAGC IRDye 700 5’ CACTGCACATTGAGACTAACG CATCAGCAAGTACAAGGACAGT IRDye 700 5’ ACCTCCATCTCATCGTCAG GGCAGAAACAGAGCAGTG IRDye 800 5’ TTTCAGTTTCAGCAAGTAGACC AATCCTCTTCCATCTCCATATC

170

C. C. KEEVER ET AL. Appendix Table 1 Continued

Microsatellite sequence accession numbers, repeats, and PCR primers GenBank Name accession no.

Repeat

B212

EF106756.1

(ATG)7

B222

EF106757.1

(ATG)2AATTTG(ATG)4ATA(ATG)3

B227

EF106758.1

(ATG)7

B228

EF106759.1

(ATG)6

B231

EF106760.1

(ATG)8

B234

EF106761.1

(ATG)6

B236

EF106762.1

(ATG)5ATA(ATG)3

C8

EF106763.1

(CAG)4CAACAT(CAG)4CAC(CAG)2CAACCG(CAG)4

C104

EF106764.1

(CAG)11

C107

EF106765.1

C111

EF106766.1

(CAT)4(CAA)3GAA(CAA)2GAA(CAA)5GAACAAAAA(CAA)6 (CAG)8CAACAG(CAA)3(CAG)3 (ACC)3AGCAT(CAG)4

C112

EF106767.1

(CAG)3(CAA)2(CAG)3(CAA)2(CAG)5CAACAG(CAA)4(CAG)7

C113

EF106768.1

(CAG)7

C114

EF106769.1

(CAG)7

C115

EF106770.1

(CAG)8CAA(CAG)3(CAACAG)4(CAG)2

C204a EF106771.1

(CAG)2CAA(CAG)5(CAACAG)2

C207

EF106772.1

(CAG)4CACCAA(CAG)2CAA(CAG)3(CAA)2

C210

EF106773.1

(CAG)5(CAA)8CAT(CAG)2(CAA)4CATGAA(CAG)10(CAA)5

C212

EF106774.1

(CAA)3(CAG)3CAA(CAG)2CAA(CAG)3

C213

EF106775.1

(CAG)9

C216

EF106776.1

(CAG)7

C219

EF106777.1

(CAG)3CA(CAG)3

C227

EF106778.1

(CAG)7

C231

EF106779.1

(CAG)4CAA(CAG)4CAA(CAG)2CAA(CAG)3

C232

EF106780.1

D8

EF106781.1

(CAG)4CAACAGCAACTGCAGTGG(CAG)6CAA(CAG)2CAA (CAG)2 (TAGA)7

D114

EF106782.1

(TAGA)12

D127

EF106783.1

(TAGA)16

Label

Primers

IRDye 800 5’ GTGCCCGAGATGTTTTTC ACCGCAAGATGCTACAATG IRDye 700 5’ CTGCGTAGAATGGTCTTAGTTC CTTTGAAAACAGGGGTATGTC IRDye 700 5’ TTTTTACGCTTGTGGTTTGAC TCGCACTTTGCCTGATTC IRDye 800 5’ GACCAGTGAAGTGAACCAGTTC TTTTTCATGGCGAGTTAGGAC IRDye 700 5’ AGGGTATAGGAGACCCATCAG GCTTACTCAGCCACTTGAGAG IRDye 700 5’ TGGGTGACTTGTGATGAAC TGAATGTTGGACTTGATGTG IRDye 800 5’ CCACAACAAGTGCTCAAAC ATCAAGTATCGCCAACTGTC IRDye 700 5’ TTACGGCAGTAGAACCCAC TGGAGGAGTCAAAGGTGAG IRDye 800 5’ GCTGACTTTGTGGCTTGAC AATCGGTTTGTGCTGTCC IRDye 700 5’ TTATGACACCATTTCCCATATC CCATATCCCCTTGATCTCTC IRDye 700 5’ TTGCCACTGCTGTTGTAGG GCCAAATCGTGACAGGTG IRDye 700 5’ TTTTGTCGGGACTGAACTTC GTTTGAAAGCAGCCTGAGTG IRDye 700 5’ CCCAGGCACACTTGATTG TCGGTTGGACCACTTTTG IRDye 700 5’ GTGGCAAGGATACCTCGTC GGGTTGACAAATCGTGGAG IRDye 700 5’ GATGGTCCTGTGTGTTTACGAC TTGTTGGGCAAGCAGTTG IRDye 800 5’ GTTGCTGTTGGTTTGGATAC ATCTTCTGCCATTTTCAGTTC IRDye 800 5’ TATGCCAGAGGCTATTCAGA CTTGTTGCGAGGGAAGAG IRDye 700 5’ CAGTTTTCAACAACAGCAGATG GGTGGTATCATTGGAGAGTAGC IRDye 800 5’ GCTTGATTTTTTTTCCTCTCAC CACTGCTGCTGGTGTTACTG IRDye 700 5’ CTCTCGGCAATCCTCATAG GACCAAGCAAATCTACAAAGAC IRDye 700 5’ GACCTGTCTATGATGCCCATAC CAACCAGACTTACCTGTTGGAC IRDye 700 5’ CTGCTGTTGTTGCTGTTTC TGGAAGTTACCCGACTCC IRDye 800 5’ GCACACTTGTCGTAGCACTTG TCGGTCATCCAACACACAC IRDye 700 5’ CCACAATAGGAAATCGGTTAC GAAGCCAAGAAACAGAAGAAG IRDye 700 5’ TTGCTCAGGGAACTGTCC GCGGAACTGTTGTTGATTG IRDye 800 5’ CGTGTTTGTATGTGTGTGTTTG GTCAGTTGGACTACGATGTGTC IRDye 800 5’ AAACGGAAGGCACAGTTC TCTCAAATGTCACCCATCTG IRDye 700 5’ ACGGCCAAATCCAAAATG GGAGGGAACAAGCATTGC

Primer oligonucleotide sequences (5⬘ to 3⬘) are shown for each clone. Forward primers (top sequence for each microsatellite) were labeled with LI-COR infrared dyes (IRDye 700 or 800).

171

ASTERINID MICROSATELLITES Appendix Table 2 Microsatellite cross-amplification patterns

Genus

Cryptasterina

Patiriella

Meridiastra

Patiria

Parvulastra

Asterina Strongylocentrotus

C. pentagona C. hystera P. regularis M. calcar M. oriens P. miniata P. exigua P. parvivipara Total A. gibbosa

S. purpuratus GLEAN3 gene

A4 A102 A104 A108 A110 B3 B4a B6 B11 B101 B105 B106 B110 B114 B201 B202 B209 B212 B222 B227 B228 B231 B234 B236 C8 C104 C107 C111 C112 C113 C114 C115 C204a C207 C210 C212 C213 C216 C219 C227 C231 C232 D8 D114 D127 Assigned Cross-amplified

179 ⫹ ⫹ ⫹ 180 193 ⫹ ⫹ ⫹ ⫹ -

214 ⫹ ⫹ ⫹ ⫹ ⫹ ⫹ ⫹ ⫹ 200

⫹ 299 ⫹ ⫹ ⫹ 165 ⫹ ⫹ ⫹ 232 -

181 137 ⫹ ⫹ 256 ⫹ ⫹ ⫹ ⫹ ⫹ 264 ⫹ ⫹ ⫹ ⫹ ⫹ 202 283 143 -

⫹ 123 ⫹ 234 273 ⫹ ⫹ ⫹ ⫹ ⫹ 151 109 ⫹ ⫹ 292 199 194 ⫹ 187 ⫹ 279 -

122 ⫹ 154 286 294 ⫹ 148 208 ⫹ ⫹ 266 ⫹ ⫹ 231 ⫹ ⫹ -

⫹ 249 ⫹ ⫹ ⫹ ⫹ ⫹ ⫹ 287 ⫹ ⫹ ⫹ ⫹ -

226 ⫹ ⫹ 230 ⫹ ⫹ 249 272 ⫹ ⫹ ⫹ -

2 1 1 2 2 1 2 5 1 1 2 2 1 1 1 8 1 2 2 2 1 1 4 8 4 1 1 3 4 6 4 1 4 1 1 1 1 1 7 5 1 4 4 1 1

3 7

2 8

3 7

7 12

10 11

8 8

2 11

4 7

39 71

(Ap-Zic)

28470: anosim-1 ⫹

22573: Sp-Nk7

⫹

07839: SRCR

⫹ ⫹

⫹

-

Successful (⫹) and unsuccessful (-) cross-amplification of each microsatellite is indicated. Locus names are the same as in Appendix Table 1. Numbers under taxon names are PCR product size for clones from that species. Empty cells for Asterina gibbosa indicate amplifications not attempted. Row totals show the number of successful amplifications among Indo-Pacific asterinid species; column totals show number of clones isolated from each species and number of additional cross-amplifications. Homologies of four clones to sea urchin or sea star protein-coding genes are shown in the last column (and explained in the text). The branching diagram above the genus names shows well-known phylogenetic relationships based on mtDNA sequences (see Keever and Hart, 2008).

172

C. C. KEEVER ET AL. Appendix Table 3

Polymorphism at 12 microsatellites in single population samples of Meridiastra calcar (Mc) and Patiria miniata (Pm) # Alleles Name

# Species

B11 B201 B202 B209 B234 C8 C112 C113 C114 C204a C210 C232

1Pm 1Pm 8 1Pm 4 4 4 6Pm 4 4 1Pm 4Mc

Gene

Sp-Nk7

Pm 5 8 2 8 6

Hobs

Mc

3 7 3 7

8

Pm 0.104 0.542 0.229 0.604 0.125

Mc

0.200 0.200 0.166 0.566

0.729 3 9

10 8

Hexp Pm 0.585 0.647 0.204 0.752 0.120

FIS Mc

0.186 0.190 0.156 0.546

0.791 0.133 0.433

0.583

0.824 0.165 ⫺0.119 0.197 ⫺0.029

Mc

⫺0.084 ⫺0.045 ⫺0.058 ⫺0.036

0.081 0.293 0.660

0.791 0.600

Pm

0.550 0.348 0.266

0.736

0.189

Six microsatellites cloned from these species are indicated by superscript acronyms; six others were cloned in other asterinid species and cross-amplified in M. calcar (n ⫽ 30 individuals) or P. miniata (n ⫽ 48 individuals). Locus names are the same as in Appendix Table 1. Inbreeding coefficients (FIS) are based on observed (Hobs) and expected (Hexp) heterozygosities; those significantly different from zero after Bonferroni correction are shown in bold italics.