Conservation Genetics Resources

, Volume 3, Issue 4, pp 601–604 | Cite as

Development of 21 microsatellite markers for the threatened Yarra pygmy perch (Nannoperca obscura) through 454 shot-gun pyrosequencing

  • Daniel C. Carvalho
  • Clara J. Rodríguez-Zárate
  • Michael P. Hammer
  • Luciano B. Beheregaray
Technical Note

Abstract

Using a next generation sequencing approach, a set of 21 new microsatellites loci was developed from the threatened freshwater fish Yarra pygmy perch (YPP) Nannoperca obscura (Percichthyidae). All markers were successfully genotyped using 28 YPP kept in captivity. These animals represent an entire population rescued from the lower Murray-Darling Basin in Australia before its habitat dried out. As expected due to the critical conservation status of the population, we observed low genetic variation across most loci (mean number of alleles per locus = 2.76; mean heterozygosity = 0.28). No deviations from Hardy–Weinberg equilibrium or linkage disequilibrium were detected and only one locus (Nob30) showed evidence for null alleles. These molecular markers represent important resources for the ongoing YPP captive breeding program, and for upcoming restoration and landscape genetic studies of this species.

Keywords

Microsatellite development Next Generation DNA sequencing Nannoperca obscura Freshwater fish 

Notes

Acknowledgments

Funding for this study was provided by the Australian Research Council (LP100200409 to Beheregaray, Harris & Adams). Additional support was received by Department of Environment and Natural Resources SA, SA Museum, SA Murray Darling NRMB, PIRSA Fisheries and NFASA. We thank Mark Adams for providing tissue samples, Mike Gardner and Minami Sasaki for data analysis and laboratory assistance. DC is grateful to CAPES, for his postdoctoral fellowship (# 4095-09-0).

References

  1. Beheregaray LB, Sunnucks P (2000) Microsatellite loci isolated from Odontesthes argentinensis and the O. perugiae species group and their use in other South American silverside fish. Mol Ecol 9 (5):629–631. doi:10.1046/j.1365-294x.2000.00882.x Google Scholar
  2. Carvalho D, Beheregaray L (2010) Rapid development of microsatellites for the endangered neotropical catfish Conorhynchus conirostris using a modest amount of 454 shot-gun pyrosequencing. Conserv Genet Resour pp 1–3. doi: 10.1007/s12686-010-9365-4
  3. Faircloth BC (2008) Msatcommander: detection of microsatellite repeat arrays and automated, locus-specific primer design. Mol Ecol Resour 8(1):92–94. doi:10.1111/j.1471-8286.2007.01884.x PubMedCrossRefGoogle Scholar
  4. Hall A, Higham J, Hammer M, Brice C, Zampatti B (2009) Drought action plan for south australian murray-darling basin threatened freshwater fish populations 2009–2010; rescue to recovery. AdelaideGoogle Scholar
  5. Hammer, M. (2008). Status review of wild and captive Yarra pygmy perch in the Murray-Darling Basin. Report to department for environment and heritage, South Australian Government. Aquasave Consultants, Adelaide, p 27Google Scholar
  6. Hammer M, Wedderburn S, van Weenan J (2009) Action plan for South Australian freshwater fishes. Native Fish Australia (SA) Inc., Adelaide, p 206Google Scholar
  7. Hammer MP, Unmack PJ, Adams M, Johnson JB, Walker KF (2010) Phylogeographic structure in the threatened Yarra pygmy perch Nannoperca obscura (Teleostei: Percichthyidae) has major implications for declining populations. Conserv Genet 11:213–223. doi:10.1007/s10592-009-0024-9 CrossRefGoogle Scholar
  8. Holleley CE, Geerts PG (2009) multiplex manager 1.0: A cross-platform computer program that plans and optimizes multiplex PCR. Biotechniques 46 (7): 511–517. doi: 10.2144/000113156
  9. IUCN 2010. IUCN Red List of Threatened Species. Version 2010.4. < http://www.iucnredlist.org > . Downloaded on 27 Oct 2010
  10. Margulies M, Egholm M, Altman WE et al (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437(7057):376–380PubMedGoogle Scholar
  11. Meglécz E (2007) Microfamily (version 1): a computer program for detecting flanking-region similarities among different microsatellite loci. Mol Ecol Notes 7(1):18–20. doi:10.1038/nature03959 CrossRefGoogle Scholar
  12. Rice WR (1989) Analyzing tables of statistical tests. Evolution 43(1):223–225CrossRefGoogle Scholar
  13. Rousset F (2008) Genepop ‘007: a complete re-implementation of the Genepop software for Windows and Linux. Mol Ecol Resour 8(1):103–106. doi:10.1111/j.1471-8286.2007.01931.x PubMedCrossRefGoogle Scholar
  14. Rozen S, Skaletsky H (2000) Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol 132:365–386. doi:10.1385/1-59259-192-2:365 PubMedGoogle Scholar
  15. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) Micro-checker: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4(3):535–538. doi:10.1111/J.1471-8286.2004.00684.X CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Daniel C. Carvalho
    • 1
  • Clara J. Rodríguez-Zárate
    • 1
  • Michael P. Hammer
    • 2
  • Luciano B. Beheregaray
    • 1
  1. 1.Molecular Ecology Laboratory, School of Biological SciencesFlinders UniversityAdelaideAustralia
  2. 2.Evolutionary Biology UnitSouth Australian MuseumAdelaideAustralia

Personalised recommendations