Advertisement

Marine Biodiversity

, Volume 49, Issue 1, pp 509–513 | Cite as

Isolation and characterisation of 16 polymorphic microsatellite loci for the sooty tern (Onychoprion fuscatus; Sternidae), a super-abundant pan-tropical seabird, including a test of cross-species amplification using two noddies (Anous spp.)

  • D. K. DanckwertsEmail author
  • C. Lebarbenchon
  • M. Le Corre
  • L. Humeau
Short Communication

Abstract

We isolate and characterise 16 polymorphic microsatellite loci for the super-abundant, pan-tropical sooty tern (Onychoprion fuscatus), facilitating population genetic studies. In 70 samples from two breeding colonies, the total number of alleles per locus ranged between 5 and 21, observed heterozygosity ranged from 0.143 to 0.942, while estimated null allele frequency varied from −0.131 to 0.273. Polymerase chain reaction (PCR) conditions were optimised across loci, enabling multiplexing and rapid multilocus genotyping. These 16 loci will be useful for future studies of genetic diversity and population structure, and can be used as a proxy through which to assess ecosystem function and change. We additionally test cross-species amplification in the brown (Anous stolidus) and lesser (A. tenuirostris) noddies, illustrating a use of these microsatellites in other related Sternidae species.

Keywords

Sooty tern Onychoprion fuscatus Anous Sternidae Microsatellite Population genetics Conservation 

Notes

Acknowledgements

Primer development was co-funded by the Western Indian Ocean Marine Science Association (WIOMSA; grant MARG I_2015_03) and the South African Research Chairs Initiative (SARChI) of the South African Department of Science and Technology (DST) and the National Research Foundation (NRF). We are additionally grateful to Raylene Swanepoel for technical support, and to Matthieu Bastien, Sophie Bureau, Chris Feare, Audrey Jaeger and Christine Larose for sample collection. Extreme gratitude must also be paid to the Savy family, for providing access and support at Bird Island. All procedures performed in this study were in accordance with the ethical standards of the institutions (Department of Zoology and Entomology, Rhodes University, Animal Ethics reference number: ZOOL-01-2013) and organisations through which it was conducted. Finally, the authors declare that they have no conflict of interest.

References

  1. Agapow PM, Burt A (2001) Indices of multilocus linkage disequilibrium. Mol Ecol Resour 1(1–2):101–102CrossRefGoogle Scholar
  2. Bridge ES, Jones AW, Baker AJ (2005) A phylogenetic framework for the terns (Sternini) inferred from mtDNA sequences: implications for taxonomy and plumage evolution. Mol Phylogenet Evol 35:459–469CrossRefGoogle Scholar
  3. Catry T, Ramos JA, Catry I, Monticelli D, Granadeiro JP (2013) Inter-annual variability in the breeding performance of six tropical seabird species: influence of life-history traits and relationship with oceanographic parameters. Mar Biol 160:1189–1201CrossRefGoogle Scholar
  4. Danckwerts DK, McQuaid CD, Jaeger A, McGregor GK, Dwight R, Le Corre M, Jaquemet S (2014) Biomass consumption by breeding seabirds in the western Indian Ocean: indirect interactions with fisheries and implications for management. ICES J Mar Sci 71(9):2589–2598CrossRefGoogle Scholar
  5. Feare CJ, Jaquemet S, Le Corre M (2007) An inventory of Sooty Terns (Sterna fuscata) in the western Indian Ocean with special reference to threats and trends. Ostrich 78(2):423–434CrossRefGoogle Scholar
  6. Gochfeld M, Burger J (1996) Family Sternidae (terns). In: del Hoyo J, Elliott A, Sargatal J (eds) Handbook of birds of the world. Lynx Edicions, Barcelona, pp 624–667Google Scholar
  7. Kamvar ZN, Tabima JF, Grünwald NJ (2014) Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2:e281CrossRefGoogle Scholar
  8. Kamvar ZN, Brooks JC, Grünwald NJ (2015) Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality. Front Genet 6:208CrossRefGoogle Scholar
  9. Le Corre M, Jaquemet S (2005) Assessment of the seabird community of the Mozambique Channel and its potential use as an indicator of tuna abundance. Estuar Coast Shelf Sci 63:421–428CrossRefGoogle Scholar
  10. Lebarbenchon C, Jaeger A, Feare C, Bastien M, Dietrich M, Larose C, Lagadec E, Rocamora G, Shah N, Pascalis H, Boulinier T, Le Corre M, Stallknecht DE, Dellagi K (2015) Influenza a virus on oceanic islands: host and viral diversity in seabirds in the western Indian Ocean. PLoS Pathog 11(5):e1004925CrossRefGoogle Scholar
  11. Paradis E (2010) Peags: an R package for population genetics with an integrated-modular approach. Bioinformatics 26:419–420Google Scholar
  12. Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics 28:2537–2539CrossRefGoogle Scholar
  13. R Development Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/, accessed 20 Mar 2017
  14. Schreiber EA, Feare CJ, Harrington B, Murray B, Robertson WB, Robertson B, Woolfenden GE (2002) Sooty tern Sterna fuscata. In: Poole A, Gill F (eds) The birds of North America. The Birds of North America, Philadelphia, p 32Google Scholar
  15. Schuelke M (2000) An economic method for the fluorescent labeling of PCR fragments. Nat Biotechnol 18:233–234CrossRefGoogle Scholar
  16. Surman CA, Wooller RD (2003) Comparative foraging ecology of five sympatric terns at a sub-tropical island in the eastern Indian Ocean. J Zool (Lond) 259:219–230CrossRefGoogle Scholar
  17. Surman CA, Nicholson LW (2009) The good, bad and the ugly. ENSO driven oceanographic variability and its influence on seabird diet and reproductive performance at the Houtman Abrolhos, eastern Indian Ocean. Mar Ornithol 37:129–138Google Scholar
  18. van Oosterhout C, Hutchinson WF, Wills DP, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Resour 4:535–538CrossRefGoogle Scholar

Copyright information

© Senckenberg Gesellschaft für Naturforschung and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • D. K. Danckwerts
    • 1
    • 2
    Email author
  • C. Lebarbenchon
    • 3
  • M. Le Corre
    • 2
  • L. Humeau
    • 4
  1. 1.Coastal Research Group, Department of Zoology and EntomologyRhodes UniversityGrahamstownSouth Africa
  2. 2.UMR ENTROPIE (Université de La Réunion, IRD, CNRS)Ile de La RéunionFrance
  3. 3.Université de La Réunion, UMR Processus Infectieux en Milieu Insulaire Tropical (PIMIT), INSERM 1187, CNRS 9192, IRD 249, GIP CYROISainte-ClotildeFrance
  4. 4.UMR PVBMT (Université de La Réunion, CIRAD)Ile de La RéunionFrance

Personalised recommendations