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versión impresa ISSN 0188-8897

Hidrobiológica vol.28 no.1 México ene./abr. 2018


Notas Científicas

Isolation and characterization of new microsatellite markers for the Pacific geoduck (Panopea generosa) using next generation sequencing

Aislamiento y caracterización de nuevos marcadores microsatélites para la almeja generosa (Panopea generosa) por medio de secuenciación de nueva generación

Celia Isabel Bisbal-Pardo1 

Miguel Ángel Del Río-Portilla2 

Ana Castillo-Páez1 

Axayácatl Rocha-Olivares1  * 

1Molecular Ecology Laboratory, Biological Oceanography Department, CICESE, Carretera Ensenada-Tijuana 3918, Zona Playitas, Ensenada, Baja California, 22860, México

2Genetics Laboratory, Aquaculture Department, CICESE, Carretera Ensenada-Tijuana 3918, Zona Playitas, Ensenada, Baja California, 22860, México



Panopea generosa is a large and long-lived infaunal clam with a considerable commercial value in Canada, United States and Mexico, in need of population genetic studies across its range of distribution.


We set to develop new genetic markers (microsatellites) specific for P. generosa.


We tested 30 microsatellite loci generated using next-generation genome sequencing (Illumina Hi-Seq 2500).


We identified eight as suitable polymorphic genetic markers. The number of alleles per locus ranged from 5 to 22 and heterozygosity from 0.429 to 0.818 (observed) and from 0.548 to 0.962 (expected). Deviation from Hardy-Weinberg equilibrium was found in three loci, after Dunn-Šidák correction, as a result of heterozygote deficiencies suggesting the presence of null alleles and linkage disequilibrium was found between two loci.


These markers are highly informative and useful for population genetic studies aimed at informing management and conservation measures of this valuable resource.

Keywords  Genetic markers; next-generation sequencing; microsatellite; Panopea generosa



Panopea generosa es una almeja de gran tamaño, infáunica y longeva con un valor comercial considerable en Canadá, Estados Unidos y México, y de la que se requiere conocer su estructura genética poblacional a lo largo de su rango de distribución.


Desarrollar nuevos marcadores microsatélites específicos para P. generosa.


En este reporte evaluamos 30 loci microsatélites generados mediante secuenciación genómica de siguiente generación (Illumina Hi-Seq 2500).


Se identificaron a ocho como marcadores genéticos polimórficos adecuados. El número de alelos por locus varió entre 5 y 22, la heterocigosidad observada entre 0.429 y 0.818 y la esperada entre 0.548 y 0.962. Tres marcadores se desviaron del equilibrio de Hardy-Weinberg, después de la corrección de Dunn-Šidák, como resultado de un déficit de heterocigosidad, sugiriendo la presencia de alelos nulos y se encontró desequilibrio de ligamiento entre dos microsatélites.


Estos marcadores son altamente informativos y útiles para estudios de genética poblacional encaminados a la implementación de medidas de administración y conservación de este valioso recurso.

Palabras clave  marcadores genéticos; microsatélites; Panopea generosa; secuenciación de siguiente generación

The Pacific geoduck, Panopea generosa Gould, 1850, is a large and long-lived infaunal clam, inhabiting sediments from the low intertidal to subtidal waters from Alaska, USA, to Baja California, México, and is the most important commercial geoduck (Bivalvia: Hiatellidae) in the northeast Pacific (Aragón-Noriega et al., 2012). Its commercial harvest started in 1970’s in the U.S. and Canada, and in early 2000 in Mexico (Aragón-Noriega et al., 2012). Commercial aquaculture operations started in the late 1990’s in the U.S. The species is sensible to over-exploitation because of its extended longevity, low recruitment, late sexual maturity, and slow growth (Bureau et al., 2002; Calderon-Aguilera et al., 2010; Orensanz et al., 2004; Sloan & Robinson, 1984). Therefore, assessing the structure and dynamics of wild populations is a prerequisite to address their potential for sustainable exploitation and to manage risk reduction in aquaculture (Straus et al., 2008). Genetic analyses using polymorphic loci are a powerful tool to investigate population genetic structure, and to assess levels of genetic variability, effective population size and extinction risk (Evans & Sheldon, 2008). Among molecular genetic markers, microsatellites show several advantages (Jarne & Lagoda, 1996) however, their isolation in a new species requires significant effort (time- and money-wise) and expertise (Zane et al., 2002). In addition, the genomic abundance of microsatellites is variable among taxa; and in some genomes, such as those of bivalves, they appear in low frequency (Peñarrubia et al., 2015). On the other hand, next generation DNA sequencing (NGS) technologies provide a cost-time-efficient means to isolate large number of microsatellites (Abdelkrim et al., 2009; Csencsics et al., 2010; Inoue et al., 2013; Lance et al., 2013).

Panopea generosa, formerly incorrectly named Panopea abrupta Conrad, 1849 (Vadopalas et al., 2010), has been subject to the development of seventeen specie-specific microsatellites using traditional cloning methods (Kaukinen et al., 2004; Vadopalas & Bentzen, 2000; Vadopalas et al., 2004). Some of which have been used repeatedly in population genetics studies with variable and sometimes limited success (Miller et al., 2006; Suárez-Moo et al., 2016; Vadopalas et al., 2004; Vadopalas et al., 2012). Suárez-Moo et al. (2016) and Vadopalas et al. (2012) found genetic homogeneity between samples of Baja California and Washington and among cohorts of Washington, respectively. On the other hand, Miller et al. (2006) and Vadopalas et al. (2004) revealed genetic heterogeneity in populations of Canada and USA. In this study, we aim at producing additional genetic markers and complement the molecular toolbox of the Pacific geoduck to increase the power of future genetic studies along its distribution. This information will prove valuable for managing the exploitation of wild populations and help direct aquaculture efforts along its distribution area.

DNA of gill tissue was extracted from two fresh organisms, collected near Ensenada, Baja California, using the DNeasy blood and tissue kit (QIAGEN, Hilden, Germany), obtaining in excess of 50 ng/μl of high quality (A260/A280 > 1.80) genomic DNA. All processes of library construction and Illumina sequencing were done as a described in Bisbal-Pardo et al. (2016). Bioinformatic analyses (quality control, ends trim, de novo assembly, microsatellite identification and primer design) were also carried out as described in Bisbal-Pardo (2014) and Bisbal-Pardo et al. (2016). For marker assessment, thirty microsatellite loci (9 di-, 10 tri- and 11 tetranucleotide) were selected (primer lengths ranging 19-24 bp, matching annealing temperature (Tm) between 54-60 °C, a minimum of 5X coverage and a product size of 140-400 bp, and their amplification was tested using the same PCR conditions of Bisbal-Pardo et al. (2016). Genotyping was performed using ABI-3130xl automated DNA sequencer. Alleles were scored with the program Gene Marker 2.4.0 and allele sizes were assigned to bins using FLEXIBIN (Amos et al., 2007). We identified genotyping errors (stutters, allele dropout, typographical) and evaluated the presence of null alleles with MICRO-CHECKER (Van Oosterhout et al., 2004). Loci were scored in a set of 35 organisms, 7 from Hood canal (47°40’58.92’’ N 122°44’51.66’’ W) and 7 from Alden Bank (48°49’43.2’’ N 122°49’50.6’’ W), Washington, EUA; 7 from Coronado Islands (32°25’00’’N 117°15’00’’ W), 7 from San Quintín (30°23’22.02’’ N 115°54’47.2’’ W) and 7 from Santa Rosaliíta (28°40’00’’ N 114°15’57’’ W), Baja California, Mexico. We estimated the number of alleles per locus (k), observed and expected heterozygosities (Ho and He) and polymorphic information content (PIC) using Mstools (Park, 2001). Next, we calculated the deviation from Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium (LD) with ARLEQUIN 3.1 (Excoffier et al., 2005). Significance was adjusted for multiple testing using Dunn-Šidák correction (Šidák, 1967). We obtained a total of 77,475,634 reads from NGS, after the trimming, the 0.76% was discarded and 7.52% were corrected resulting in reads of 99.5 bp of the average length. We identified 8,060 di-, 3,146 tri- and 2,830 tetranucleotide microsatellites in a total of 868,521 contigs of 443 bp average length, N50 was 461 bp and average coverage was 11.86 reads. Less than 26% of markers were suitable for PCR primer design. The great disparity in the number of microsatellite loci identified bioinformatically and those amenable to primer design has been reported repeatedly (Castoe et al., 2012; Castoe et al., 2010; Csencsics et al., 2010).

Of the 30 loci tested, only eight were consistently and accurately genotyped (Table 1). The yield obtained in this study (27%), defined as the fraction of microsatellite loci successfully genotyped from the total experimentally tested, is similar to others obtained from mollusk using NGS (43%, An & Lee, 2012; 35%, Cruz-Hernández et al., 2014; 22%, Greenley et al., 2012; 33%, O’Bryhim et al., 2012). In most studies, a large number of potential loci are discarded because of amplification problems, which is particularly frequent among bivalves (Selkoe & Toonen, 2006). Mollusk genomes have been found to possess a high frequency of repetitive elements that may interfere if they appear in the flanking regions of microsatellite loci, resulting in multicopy PCR products (McInerney et al., 2011). Also, sometimes the use of the M13 tail for fluorescently labeling the forward primer may decrease the efficiency of PCR reactions (Guichoux et al., 2011). We did not find evidence of genotyping errors.

Table 1 Polymerase chain reaction primers and levels of polymorphism of novel microsatellite loci developed for Panopea generosa Gould, 1850 using next generation sequencing. 

Locus Primer sequence (5’-3’) Tm Motif n Na Allelic range Dye HO HE PHWE PIC GenBank accession
Pgen2_3 F: GCGTTTGATTGCRGGTGTAT R: CAGGCATCGTCGTGTAATGG 55.6 (AT)8 34 5 159-167 FAM 0.559 0.673 0.311 0.6 MF668230
Pgen3_4 F: ACGGCGAAAGAACGAAATGG R: TTGGTGAGAGGTTGTTGCAG 55.6 (ACG)10 17 6 316-337 PET 0.529 0.617 0.223 0.559 MF668231
Pgen3_7 F: GACAAACACCGCCTACACTG R: TACGAATGCAGTCACCAAGC 66 (AAC)17 29 15 345-393 FAM 0.552 0.912 0.000* 0.888 MF668232
Pgen4_1 F: GSGTGGAATCCATTGGGGTA R: ACCACCCTGGACACTCCTTA 62 (ACAG)14 24 22 314-474 VIC 0.667 0.962 0.000* 0.939 MF668233
Pgen4_3 F: GTTTGCCTTGTCGTCTGCAG R: GGATCCCTGGAAAGTGTGGT 62 (AAAC)6 35 7 236-320 PET 0.429 0.548 0.141 0.488 MF668234
Pgen4_9 F: GTCAATCCAGCCAAGCACAG R: GCGTGTTAGCCCTCAATAGC 55.6 (AATC)9 33 13 281-381 PET 0.818 0.891 0.045 0.866 MF668235
Pgen4_10 F: AACCGCAGCAGAACAAAGTC R: ATCTTCGCTTAGGAGGCGG 56.6 (ACGC)6 28 13 345-409 VIC 0.724 0.823 0.039 0.786 MF668236
Pgen4_11 F: AAGTCAACCAGGATGTGCAC R: CCATTAAAGGGTCACACGGC 66 (ATCC)8 32 10 242-278 NED 0.625 0.848 0.002* 0.816 MF668237

Abbreviations: Tm (°C): annealing temperature, n: sample size; Na: number of alleles; Dye: fluorescent dye; HO: observed heterozygosity; HE: expected heterozygosity; PHWE: Hardy-Weinberg equilibrium test p-value (*) significant after Dunn-Sidák correction); PIC: polymorphism information content.

Most loci were characterized by moderate to high genetic variation, with an average of 11.4 alleles per locus (range = 5-22 alleles), heterozygosity estimates ranging between 0.429 and 0.818 (mean = 0.613) and PIC value between 0.488 and 0.939 (mean = 0.743). Three loci (Pgen3_7, Pgen4_1 and Pgen4_11) significantly deviated from HWE after the Dunn-Šidák correction (p < 0.006) due to heterozygote deficiencies, for which MICRO-CHECKER suggested the presence of null alleles. We found evidence of LD (p < 0.001) between Pgen4_1 and Pgen4_10. A similar range of alleles (4-23 per locus) were found in the congener P. abbreviata in microsatellite loci (n = 21) obtained from NGS (Ahanchede et al., 2013) and similar results have been reported in others mollusk (An & Lee, 2012; Greenley et al., 2012). The quality of a marker can be determined by its degree of polymorphism. In this study, the expected heterozygosity values are in the optimal range (0.6-0.8) to provide a good resolution (Taberlet & Luikart, 1999). Moreover, the PIC values of all loci are higher than 0.25, so they are informative for linkage analysis. The deviation from HWE found in some loci could be due to population phenomena such as inbreeding, Wahlund effect, and selection or genotyping errors, such as null alleles or homoplasy (Selkoe & Toonen, 2006). However, since populations of P. generosa have shown no genetic differentiation along the northeast Pacific it is unlikely that a Wahlund effect is playing a part in the observed disequilibria (Suárez-Moo et al., 2016). On the other hand, MICRO-CHECKER analysis indicated the possible presence of null alleles in some loci. Null alleles have been found to be very common in bivalves because of mutations in the flanking regions (Becquet et al., 2009; Hedgecock et al., 2004). Even though population genetic studies require the use of independent unlinked loci, linkage may be useful for mapping studies (Xiao et al., 2012).

Nowadays, NGS is the best option to identify a high number of microsatellite loci in non-model species because it is cheaper and faster than traditional methods (Castoe et al., 2010; Ekblom & Galindo, 2011). These technologies are enabling more extensive and robust genetic studies in a great variety of taxa (Castoe et al., 2012; Huang et al., 2015; Mira et al., 2014). In this study we developed a set of new polymorphic microsatellites in P. generosa. These markers will useful in genetic studies applicable to conservation and management fisheries and aquaculture activities.


Financial support was provided by the COFUPRO grant RGACCES-2013-031 to ARO. We thank Grupo Marítimo Miramar for providing live specimens. The first author benefited from a graduate fellowship from CONACYT to support her M. Sc. program in Marine Ecology at Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE) .


Abdelkrim, J., Robertson, B., Stanton, J. A. & Gemmell, N. 2009. Fast, cost-effective development of species-specific microsatellite markers by genomic sequencing. BioTechniques 46 (3):185-192. DOI: 10.2144/000113084. [ Links ]

Ahanchede, A. et al. 2013. Permanent Genetic Resources added to Molecular Ecology Resources Database 1 August 2012-30 September 2012. Molecular Ecology Resources 13 (1):158-159. DOI: 10.1111/1755-0998.12035. [ Links ]

Amos, W., Hoffman, J. I., Frodsham, A., Zhang, L., Best, S. & Hill, A. V. S.. 2007. Automated binning of microsatellite alleles: problems and solutions. Molecular Ecology Notes 7 (1):10-14. DOI: 10.1111/j.1471-8286.2006.01560.x. [ Links ]

An, H. S. & Lee, J. W.. 2012. Development of microsatellite markers for the Korean mussel, Mytilus coruscus (Mytilidae) using next-generation sequencing. International Journal of Molecular Sciences 13 (8):10583-10593. DOI: 10.3390/ijms130810583. [ Links ]

Aragón-Noriega, E. A., Alcántara-Razo, E., Calderón-Aguilera, L. E. & Sánchez-Fourcade, R.. 2012. Status of Geoduck clam fisheries in Mexico. Journal of Shellfish Research 31 (3):733-738. DOI: 10.2983/035.031.0317. [ Links ]

Becquet, V., Lanneluc, I., Simon-Bouhet, B. & García, P.. 2009. Microsatellite markers for the Baltic clam, Macoma balthica (Linne, 1758), a key species concerned by changing southern limit, in exploited littoral ecosystems. Conservation Genetics Resources 1(1): 265-267. DOI: 10.1007/s12686-009-9065-0. [ Links ]

Bisbal-Pardo, C. I. 2014. Secuenciación masiva de Panopea generosa y Panopea globosa para el desarrollo de marcadores moleculares. Tesis de maestría, Centro de Investigación Científica y de Educación Superior de Ensenada, B.C., México. [ Links ]

Bisbal-Pardo, C. I., Del Río-Portilla, M. Á., Castillo-Paéz, A. Y. & Rocha-Olivares, A.. 2016. Isolation and characterization of new microsatellite markers for the cortés Geoduck (Panopea globosa). CICIMAR Oceánides 31 (1): 17-22. [ Links ]

Bureau, D., Hajas, W., Surry, N., Hand, C., Dovey, G. & Campbell, A.. 2002. Age, size structure and growth parameters of geoducks (Panopea abrupta, Conrad 1849) from 34 locations in British Columbia sampled between 1993 and 2000. Canadian Technical Report of FIsheries and Aquatic Sciences 2413:1-84. [ Links ]

Calderón-Aguilera, L.E., Aragón-Noriega, E.A., Hand, C.M. & Moreno-Rivera, V. M.. 2010. Morphometric relationships, age, growth, and mortality of the geoduck clam, Panopea generosa, along the Pacific coast of Baja California, Mexico. Journal of Shellfish Research 29 (2): 319-326. DOI: 10.2983/035.029.0206. [ Links ]

Castoe, T. A., et al. 2012. Rapid microsatellite identification from Illumina paired-end genomic sequencing in two birds and a snake. PLoS One 7 (2): e30953. DOI: 10.1371/journal.pone.0030953. [ Links ]

Castoe, T. A., et al. 2010. Rapid identification of thousands of copperhead snake (Agkistrodon contortrix) microsatellite loci from modest amounts of 454 shotgun genome sequence. Molecular Ecology Resources 10 (2): 341-347. DOI: 10.1111/j.1755-0998.2009.02750.x. [ Links ]

Cruz-Hernández, P., Munguia-Vega, A., Leyva-Valencia, I., Lucero-Burquez, F. & Lluch-Cota, D. B. 2014. Development of 24 tetra-nucleotide microsatellite markers in Cortes Geoduck Panopea globosa by next-generation sequencing. Conservation Genetics Resources 6 (3): 531-533. DOI: 10.1007/s12686-014-0172-1. [ Links ]

Csencsics, D., Brodbeck, S. & Holderegger, R.. 2010. Cost-effective, species-specific microsatellite development for the endangered dwarf bulrush (Typha minima) using next-generation sequencing technology. Journal of Heredity 101 (6): 789-793. DOI: 10.1093/Jhered/Esq069. [ Links ]

Ekblom, R. & Galindo, J.. 2011. Applications of next generation sequencing in molecular ecology of non-model organisms. Heredity 107 (1):1. DOI: 10.1038/hdy.2010.152. [ Links ]

Evans, S. R. & Sheldon, B. C.. 2008. Interspecific patterns of genetic diversity in birds: correlations with extinction risk. Conservation Biology 22 (4): 1016-25. DOI: 10.1111/j.1523-1739.2008.00972.x. [ Links ]

Excoffier, L., Laval, G. & Schneider, S.. 2005. Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online 1: 47-50. [ Links ]

Greenley, A. P., Muguía-Vega, A., Saenz-Arroyo, A. & Micheli, F.. 2012. New tetranucleotide microsatellite loci in pink abalone (Haliotis corrugata) isolated via 454 pyrosequencing. Conservation Genetics Resources 4 (2): 265-268. DOI: 10.1007/s12686-011-9521-5. [ Links ]

Guichoux, E. et al. 2011. Current trends in microsatellite genotyping. Molecular Ecology Resources 11 (4): 591-611. DOI: 10.1111/J.1755-0998.2011.03014.X. [ Links ]

Hedgecock, D., Li, G., Hubert, S., Bucklin, K. & Ribes, V.. 2004. Widespread null alleles and poor cross-species amplification of microsatellite DNA loci cloned from the Pacific oyster, Crassostrea gigas. Journal of Shellfish Research 23 (2): 379-385. [ Links ]

Huang, J., et al. 2015. Genome-wide survey and analysis of microsatellites in giant panda (Ailuropoda melanoleuca), with a focus on the applications of a novel microsatellite marker system. BMC Genomics 16: 61. DOI: 10.1186/s12864-015-1268-z. [ Links ]

Inoue, K., Lang, B. K. & Berg, D. J.. 2013. Development and characterization of 20 polymorphic microsatellite markers for the Texas hornshell, Popenaias popeii (Bivalvia: Unionidae), through next-generation sequencing. Conservation Genetics Resources 5 (1): 195-198. DOI: 10.1007/s12686-012-9766-7. [ Links ]

Jarne, P. & Lagoda, P. J. L. 1996. Microsatellites, from molecules to populations and back. Trends in Ecology & Evolution 11 (10): 424-429. DOI: 10.1016/0169-5347(96)10049-5. [ Links ]

Kaukinen, K., Supernault, K. & Miller, K.. 2004. Enrichment of tetranucleotide microsatellite loci from invertebrate species. Journal of Shellfish Research 23 (2): 621-627. [ Links ]

Lance, S. L., Love, C. N., Nunziata, S. O., O’Bryhim, J. R., Scott, D. E., Flynn, R. W. & Jones, K. L.. 2013. 32 species validation of a new Illumina paired-end approach for the development of microsatellites. PLoS One 8 (11): e81853. DOI: 10.1371/journal.pone.0081853. [ Links ]

McInerney, C. E., Allcock, A. L., Johnson, M. P., Bailie, D. A. & Prodohl, P. A.. 2011. Comparative genomic analysis reveals species-dependent complexities that explain difficulties with microsatellite marker development in molluscs. Heredity 106 (1): 78-87. DOI: 10.1038/hdy.2010.36. [ Links ]

Miller, K. M., Supernault, K. J., Li, S. & Withler, R. E.. 2006. Population Structure in Two Marine Invertebrate Species (Panopea abrupta and Strongylocentrotus franciscanus) Targeted for Aquaculture and Enhancement in British Columbia. Journal of Shellfish Research 25 (1): 33-42. DOI: 10.2983/0730-8000(2006)25[33:psitmi];2. [ Links ]

Mira, Ó., Martínez, J. G., Dawson, D. A., Tinaut, A. & Sánchez-Prieto, C.. 2014. Twenty new microsatellite loci for population structure and parentage studies of Parnassius apollonevadensis (Lepidoptera; Papilionidae). Journal of insect conservation 18 (5): 771-779. DOI: 10.1007/s10841-014-9683-z. [ Links ]

O’Bryhim, J., Chong, J. P., Lance, S. L., Jones, K. L. & Roe, K. J.. 2012. Development and characterization of sixteen microsatellite markers for the federally endangered species: Leptodea leptodon (Bivalvia: Unionidae) using paired-end Illumina shotgun sequencing. Conservation Genetics Resources 4 (3): 787-789. DOI: 10.1007/s12686-012-9644-3. [ Links ]

Orensanz, J., Hand, C. M., Parma, A. M., Valero, J. & Hilborn, R.. 2004. Precaution in the harvest of Methuselah’s clams the difficulty of getting timely feedback from slow-paced dynamics. Canadian Journal of Fisheries and Aquatic Sciences 61 (8): 1355-1372. DOI: 10.1139/F04-136. [ Links ]

Park, S. 2001. MStools v 3 (Excel spreadsheet toolkit for data conversion). Smurfit Institute of Genetics. Trinity College, Dublin. [ Links ]

Peñarrubia, L., Sanz, N., Pla, C., Vidal, O. & Viñas, J. 2015. Using massive parallel sequencing for the development, validation, and application of population genetics markers in the invasive bivalve zebra mussel (Dreissena polymorpha). PLoS One 10 (3): e0120732. DOI: 10.1371/journal.pone.0120732. [ Links ]

Selkoe, K. A. & Toonen, R. J.. 2006. Microsatellites for ecologists: a practical guide to using and evaluating microsatellite markers. Ecology Letters 9 (5): 615-629. DOI: 10.1111/j.1461-0248.2006.00889.x. [ Links ]

Šidák, Z. K., 1967. Rectangular confidence regions for the means of multivariate normal distributions. Journal of the American Statistical Association 62 (318): 626-633. DOI: 10.1080/01621459.1967.10482935. [ Links ]

Sloan, N. & Robinson, S.. 1984. Age and gonadal development in the geoduck clam Panope abrupta (Conrad) from southern British Columbia, Canada. Journal of Shellfish Research 4:131-137. [ Links ]

Straus, K. M., Crosson, L. M. & Vadopalas, B.. 2008. Effects of Geoduck Aquaculture on the Environment: A Synthesis of Current Knowledge. School of Aquatic and Fishery Sciences, University of Washington, Washington, 67 p. [ Links ]

Suárez-Moo, P. J., Gilbert-Horvath, E. A., Vadopalas, B., Calderón-Aguilera, L. E., Garza, J. C. & Rocha-Olivares, A.. 2016. Genetic homogeneity of the geoduck clam Panopea generosa in the northeast Pacific. Biochemical Systematics and Ecology 65: 66-71. DOI:10.1016/j.bse.2016.02.003. [ Links ]

Taberlet, P. & Luikart, G.. 1999. Non-invasive genetic sampling and individual identification. Biological Journal of the Linnean Society 68 (1-2): 41-55. DOI: 10.1111/j.1095-8312.1999.tb01157.x. [ Links ]

Vadopalas, B. & Bentzen, P.. 2000. Isolation and characterization of di- and tetranucleotide microsatellite loci in geoduck clams, Panopea abrupta. Molecular Ecology 9 (9): 1435-1436. DOI: 10.1046/J.1365-294x.2000.01000-2.X. [ Links ]

Vadopalas, B., Leclair, L. L. & Bentzen, P.. 2004. Microsatellite and allozyme analyses reveal few genetic differences among spatially distinct aggregations of geoduck clams (Panopea abrupta, Conrad 1849). Journal of Shellfish Research 23 (3): 693-706. [ Links ]

Vadopalas, B., Leclair, L. L. & Bentzen, P.. 2012. Temporal Genetic Similarity Among Year-Classes of the Pacific Geoduck Clam (Panopea generosa Gould 1850): A Species Exhibiting Spatial Genetic Patchiness. Journal of Shellfish Research 31 (3): 697-709. DOI: 10.2983/035.031.0314. [ Links ]

Vadopalas, B., Pietsch, T. W. & Friedman, C. S.. 2010. The proper name for the geoduck: resurrection of Panopea generosa Gould, 1850, from the synonymy of Panopea abrupta (Conrad, 1849) (Bivalvia: Myoida: Hiatellidae). Malacologia 52 (1): 169-173. DOI: 10.4002/040.052.0111. [ Links ]

Van Oosterhout, C., Hutchinson, W. F., Wills, D. P. M. & Shipley, P.. 2004. MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4 (3): 535-538. [ Links ]

Xiao, Y. J., Cai, D. F., Yang, W., Ye, W., Younas, M., Wu, J. S. & Liu, K. D.. 2012. Genetic structure and linkage disequilibrium pattern of a rapeseed (Brassica napus L.) association mapping panel revealed by microsatellites. Theoretical and Applied Genetics 125 (3): 437-447. DOI: 10.1007/s00122-012-1843-5. [ Links ]

Zane, L., Bargelloni, L. & Patarnello, T.. 2002. Strategies for microsatellite isolation: a review. Molecular Ecology 11 (1): 1-16. DOI: 10.1046/j.0962-1083.2001.01418.x. [ Links ]

Received: January 31, 2017; Accepted: December 06, 2017

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