Conservation Genetics

, Volume 7, Issue 6, pp 813–823 | Cite as

An empirical approach for reliable microsatellite genotyping of wolf DNA from multiple noninvasive sources

  • Massimo Scandura
  • Claudia Capitani
  • Laura Iacolina
  • Apollonio Marco


Wildlife management and conservation take advantage of the possibility to study free-living populations by collecting and analysing noninvasive samples. Nevertheless, the commonly adopted approaches, aimed at preventing results being affected by genotyping errors, considerably limit the applicability of noninvasive genotyping. An empirical approach is presented for achieving a reliable data set of wolf (Canis lupus) genotypes from multiple sources of DNA collected in a monitored population. This method relies on the relationship between sample quality and amplification outcome, which is ultimately related to the occurrence of typing errors (allelic dropout, false alleles). After DNA extraction, templates are amplified once at each locus and a conservative rating system (Q-score) is adopted to define the quality of single-locus amplifications. A significant relationship was found between quality scores and error rate (ER) (r 2=0.982). Thus it was possible to predict the chance a genotype has of being affected by errors on the basis of its Q-score. Genotypes not reaching a satisfactory confidence level can either be replicated to become reliable or excluded from the data set. Accordingly, in the present case study, 48–73% of all single-locus and 51–53% of all multilocus (ML) genotypes reached a sufficient (99 and 95%, respectively) reliability level after a single amplification per locus. Despite the possible decrease in overall yield, this method could provide a good compromise between accuracy in genotyping and effectiveness in screening large data sets for long-term or large-scale population surveys. However, to achieve complete and reliable data sets, replicated amplifications are necessary for those samples and loci providing poor results.


microsatellites noninvasive genotyping quality control scoring errors wolf 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



We wish to thank all the people who participated in the wolf monitoring program in the province of Arezzo, among whom we are particularly grateful to Elisa Avanzinelli, Alessia Viviani, Andrea Gazzola, Paolo Lamberti and Luca Mattioli. We also thank Francesca Di Benedetto for her contribution to lab activities and James Burge for linguistic revision. Suggestions by the associate editor and two anonymous reviewers allowed to improve the final draft of the manuscript. Financial support was provided by the Provincial Administration of Arezzo and by the Italian Ministry of University and Research (COFIN 2003, # prot. 2003053710).


  1. Beecham GW (2004) DNAMIX v.3 Available at:∼ ∼gwbeecha/
  2. Broquet T, Petit E (2004) Quantifying genotyping errors in noninvasive population genetics. Mol. Ecol., 13, 3601–3608.CrossRefPubMedGoogle Scholar
  3. Constable JL, Ashley MV, Goodall J, Pusey AE (2001) Noninvasive paternity assignment in Gombe chimpanzees. Mol. Ecol., 10, 1279–1300.CrossRefPubMedGoogle Scholar
  4. Creel S, Spong G, Sands JL, Rotella J, Zeigle J, Joe L, Murphy KM, Smith D (2003) Population size estimation in Yellowstone wolves with error-prone noninvasive microsatellite genotypes. Mol. Ecol., 12, 2003–2009.CrossRefPubMedGoogle Scholar
  5. Francisco LV, Langston AA, Mellersh CS, Neal CL, Ostrander EA (1996) A class of highly polymorphic tetranucleotide repeats for canine genetic mapping. Mamm. Genome, 7, 359–372.CrossRefPubMedGoogle Scholar
  6. Gagneux P, Boesch C, Woodruff DS (1997) Microsatellite scoring errors associated with noninvasive genotyping based on nuclear DNA amplified from shed hair. Mol. Ecol., 6, 861–868.PubMedGoogle Scholar
  7. Golenberg EM, Bickel A, Weihs P (1996) Effect of highly fragmented DNA on PCR. Nucleic Acids Res., 24, 5026–5033.CrossRefPubMedGoogle Scholar
  8. Goossens B, Waits LP, Taberlet P (1998) Plucked hair samples as a source of DNA: Reliability of dinucleotide microsatellite genotyping. Mol. Ecol., 7, 1237–1241.CrossRefPubMedGoogle Scholar
  9. Hedmark E, Flagstad Ø, Segerström P, Persson J, Landa A, Ellegren H (2004) DNA-Based individual and sex identification from wolverine (Gulo gulo) faeces and urine. Conserv. Genet., 5, 405–410.CrossRefGoogle Scholar
  10. Higuchi R, Von Beroldingen CH, Sensabaugh GH, Erlich HA (1988) DNA typing from single hairs. Nature, 332, 543–546.CrossRefPubMedGoogle Scholar
  11. Kohn MH, Wayne RK (1997) Facts from feces revisited. Trends Ecol. Evolut., 12, 223–227.CrossRefGoogle Scholar
  12. Lucchini V, Fabbri E, Marucco F, Ricci S, Boitani L, Randi E (2002) Noninvasive molecular tracking of colonizing wolf (Canis lupus) packs in the western Italian Alps. Mol. Ecol., 11, 857–868.CrossRefPubMedGoogle Scholar
  13. Maudet C, Luikart G, Dubray D, Von Hardenberg A, Taberlet P (2004) Low genotyping error rates in wild ungulate faeces sampled in winter. Mol. Ecol. Notes, 4, 772–775.CrossRefGoogle Scholar
  14. Miller CR, Joyce P, Waits LP (2002) Assessing allelic dropout and genotype reliability using maximum likelihood. Genetics, 160, 357–366.PubMedGoogle Scholar
  15. Morin PA, Woodruff DS (1996) Noninvasive genotyping for vertebrate conservation. In: Molecular Genetic Approaches in Conservation (eds. Smith TB, Wayne RK), pp. 298–313. Oxford University Press, New York.Google Scholar
  16. Morin PA, Chambers KE, Boesch C, Vigilant L (2001) Quantitative polymerase chain reaction analysis of DNA from noninvasive samples for accurate microsatellite genotyping of wild chimpanzees (Pan troglodytes verus). Mol. Ecol., 10, 1835–1844.CrossRefPubMedGoogle Scholar
  17. Murphy MA, Waits LP, Kendall KC (2003) The influence of diet on faecal DNA amplification and sex identification in brown bears (Ursus arctos). Mol. Ecol., 12, 2261–2265.CrossRefPubMedGoogle Scholar
  18. Navidi W, Arnheim N, Waterman MS (1992) A multiple-tubes approach for accurate genotyping of very small DNA samples by using PCR: Statistical considerations. Am. J. Hum. Genet., 50, 347–359.PubMedGoogle Scholar
  19. Ostrander EA, Sprague GF, Rine J (1993) Identification and characterization of dinucleotide repeat (CA)n markers for genetic mapping in dog. Genomics, 16, 207–213.CrossRefPubMedGoogle Scholar
  20. Ostrander EA, Mapa FA, Yee M, Rine J (1995) One hundred and one new simple sequence repeat-based markers for the canine genome. Mamm. Genome, 6, 192–195.CrossRefPubMedGoogle Scholar
  21. Paetkau D (2003) An empirical exploration of data quality in DNA-based population inventories. Mol. Ecol., 12, 1375–1387.CrossRefPubMedGoogle Scholar
  22. Parsons KM (2001) Reliable microsatellite genotyping of dolphin DNA from faeces. Mol. Ecol. Notes, 1, 341–344.Google Scholar
  23. Piggott MP, Taylor AC (2003) Remote collection of animal DNA and its applications in conservation management and understanding the population biology of rare and cryptic species. Wildl. Res., 30, 1–13.CrossRefGoogle Scholar
  24. Scandura M (2005) Individual sexing and genotyping from blood spots on the snow: A reliable source of DNA for noninvasive genetic surveys. Conserv. Genet., DOI 10.1007/s10592-005-9041-5.Google Scholar
  25. Sloane MA, Sunnucks P, Alpers D, Beheregaray LB, Taylor AC (2000) Highly reliable genetic identification of individual northern hairy-nosed wombats from single remotely collected hairs: A feasible censusing method. Mol. Ecol., 9, 1233–1240.CrossRefPubMedGoogle Scholar
  26. Sokal RR, Rohlf FJ (1995) Biometry: The principles and practice of statistics in biological research, 3rd edn. WH Freeman and Company, New York.Google Scholar
  27. Taberlet P, Griffin S, Goossens B, Questiau S, Manceau V, Escaravage N, Waits LP, Bouvet J (1996) Reliable genotyping of samples with very low DNA quantities using PCR. Nucleic Acids Res., 24, 3189–3194.CrossRefPubMedGoogle Scholar
  28. Taberlet P, Camarra J-J, Griffin S, Uhrès E, Hanotte O, Waits LP, Dubois-Paganon C., Burke T, Bouvet J (1997) Noninvasive genetic trasking of the endangered Pyrenean brown bear population. Mol. Ecol., 6, 869–876.CrossRefPubMedGoogle Scholar
  29. Taberlet P, Luikart G (1999) Non-invasive genetic sampling and individual identification. Biol. J. Linn. Soc., 68, 41–55.CrossRefGoogle Scholar
  30. Taberlet P, Waits LP, Luikart G (1999) Noninvasive genetic sampling: look before you leap. Trends Ecol. Evolut., 14, 323–327.CrossRefGoogle Scholar
  31. Triant DA, Pace RM, Stine M (2004) Abundance, genetic diversity and conservation of Louisiana black bears (Ursus americanus luteolus) as detected through noninvasive sampling. Conserv. Genet., 5, 647–659.CrossRefGoogle Scholar
  32. Valière N. (2002) GIMLET: A computer program for analysing genetic individual identification data. Mol. Ecol., 2, 377–379. Available at:
  33. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: A software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes, 4, 535–538. Available at:
  34. Walsh PS, Metzger DA, Higuchi R (1991) Chelex-100 as a medium for simple extraction of DNA for PCR-based typing from forensic material. Biotechniques, 10, 506–513.PubMedGoogle Scholar
  35. Woods JG, Paetkau D, Lewis D, McLellan BN, Proctor M, Strobeck C (1999) Genetic tagging of free-ranging black and brown bears. Wildl. Soc. Bull., 27, 616–627.Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Massimo Scandura
    • 1
    • 2
  • Claudia Capitani
    • 1
  • Laura Iacolina
    • 1
  • Apollonio Marco
    • 1
  1. 1.Department of Zoology and AnthropologyUniversity of SassariSassariItaly
  2. 2.Lehrstuhl für VerhaltensforschungUniversität BielefeldBielefeldGermany

Personalised recommendations