Conservation Genetics

, 10:797 | Cite as

The influence of evolutionary distance between cross-species microsatellites and primer base-pair composition on allelic dropout rates

  • Carl D. SoulsburyEmail author
  • Graziella Iossa
  • Keith J. Edwards
Technical Note


Allelic dropouts (ADO) are an important source of genotyping error and because of their negative impact on non-invasive sampling techniques, have become the focus of considerable attention. Previous studies have noted that ADO rates are greater with increasing allele size and in tetranucleotides. It has also been suggested, but not tested, that ADO rates may be higher in studies using cross-species microsatellites and that mutations may play a role in ADO rates. Here we examine the relationship between ADO rates and the relationship between evolutionary distance since divergence time between species for which the microsatellite was designed for and species on which it was used (divergence times), and how this may interact with median allele size. In addition, as the adenosine (A) and thymine (T) content of the primer may increase mutation rates, we also included total % AT content of the primer in the analyses. Finally, we examined whether other commonly associated causes of ADO (i.e. repeat motif length, median allele size and allele number) co-varied. We found that ADO rates were positively associated to divergence time and median allele size. Repeat motif length, median allele size and allele number positively covaried suggesting a link between mutability and these parameters. Results from previous studies that did not correct for co-variation among these parameters may have been confounded. AT content of the primer was positively associated with ADO rates. The best linear regression model contained divergence time, median allele size and total % AT content, explaining 21% of the variation in ADO rates. The available evidence suggests that mutations partly cause ADO and that studies using cross-species microsatellites may be at higher risk of ADO. Based on our results we highlight some important considerations in the selection of microsatellites for all conservation genetic studies.


Cross-species Genotyping error Microsatellites Phylogeny 



We are grateful to Biotechnology and Biological Sciences Research Council (KJE) for funding and the editor and referee for their comments.


  1. Bayes MK, Smith KL, Alberts SC, Altmann J, Bruford MW (2000) Testing the reliability of microsatellite typing from faecal DNA in the savannah baboon. Conserv Genet 1:173–176. doi: 10.1023/A:1026595324974 CrossRefGoogle Scholar
  2. Bininda-Emonds ORP, Gittleman JL, Purvis A (1999) Building large trees by combining phylogenetic information: a complete phylogeny of the extant Carnivora (Mammalia). Biol Rev 74:143–175. doi: 10.1017/S0006323199005307 PubMedCrossRefGoogle Scholar
  3. Boutrand L, Egyed B, Füredi S, Mommers N, Mertens G, Vandenberghe A (2001) Variations in primer sequences are the origin of allele drop-out at loci D13S317 and CD4. Int J Legal Med 114:295–297. doi: 10.1007/s004140000183 PubMedCrossRefGoogle Scholar
  4. Broquet T, Ménard N, Petit E (2007) Noninvasive population genetics: a review of sample source, diet, fragment length and microsatellite motif effects on amplification success and genotyping error rates. Conserv Genet 8:249–260. doi: 10.1007/s10592-006-9146-5 CrossRefGoogle Scholar
  5. Buchan JC, Archie EA, Van Horn RC, Moss CJ, Alberts SC (2005) Locus effect and sources of error in noninvasive genotyping. Mol Ecol Notes 5:680–683. doi: 10.1111/j.1471-8286.2005.01002.x CrossRefGoogle Scholar
  6. Cadwell RC, Joyce GF (1994) Mutagenic PCR. PCR Methods Appl 3:S136–S140PubMedGoogle Scholar
  7. Chakraborty R, Kimmel M, Stivers DN, Davison LJ, Deka R (1997) Relative mutation rates at di-, tri-, and tetranucleotide microsatellite loci. Proc Natl Acad Sci N Am 94:1041–1046. doi: 10.1073/pnas.94.3.1041 CrossRefGoogle Scholar
  8. Creel S, Spong G, Sands JL, Rotella J, Zeigle J, Joe L et al (2003) Population size estimation in Yellowstone wolves with error-prone noninvasive microsatellite genotypes. Mol Ecol 12:2003–2009. doi: 10.1046/j.1365-294X.2003.01868.x PubMedCrossRefGoogle Scholar
  9. Davis CS, Strombeck C (1998) Isolation, variability, and cross-species amplification of polymorphic microsatellite loci in the family Mustelidae. Mol Ecol 7:1771–1788. doi: 10.1046/j.1365-294x.1998.00501.x CrossRefGoogle Scholar
  10. Fernando P, Vidya TNC, Rajapakse C, Dangolla A, Melnick DJ (2003) Reliable noninvasive genotyping: fantasy or reality? J Hered 94:115–123. doi: 10.1093/jhered/esg022 PubMedCrossRefGoogle Scholar
  11. Fickel J, Hohmann U (2006) A methodological approach for non-invasive sampling for population size estimates in wild boar (Sus scrofa). Eur J Wildl Res 52:28–33. doi: 10.1007/s10344-005-0003-5 CrossRefGoogle Scholar
  12. Flagstad Ø, Røed K, Stacy JE, Jakobsen KS (1999) Reliable non-invasive genotyping based on excremental PCR of nuclear DNA purified with a magnetic bead protocol. Mol Ecol 8:879–883. doi: 10.1046/j.1365-294X.1999.00623.x PubMedCrossRefGoogle Scholar
  13. Frantz AC, Pope LC, Carpenter PJ, Roper TJ, Wilson GJ, Delahay RJ et al (2003) Reliable microsatellite genotyping of the Eurasian badger (Meles meles) using faecal DNA. Mol Ecol 12:1649–1661. doi: 10.1046/j.1365-294X.2003.01848.x PubMedCrossRefGoogle Scholar
  14. Frantzen MAJ, Silk JB, Ferguson JWH, Wayne RK, Kohn MH (1998) Empirical evaluation of preservation methods for faecal DNA. Mol Ecol 7:1423–1428. doi: 10.1046/j.1365-294x.1998.00449.x PubMedCrossRefGoogle Scholar
  15. Gagneux P, Boesch C, Woodruff DS (1997) Microsatellite scoring errors associated with non-invasive genotyping based on nuclear DNA amplified from shed hair. Mol Ecol 6:861–868. doi: 10.1111/j.1365-294X.1997.tb00140.x PubMedCrossRefGoogle Scholar
  16. Gagneux P, Woodruff DS, Boesch C (2001) Retraction: furtive mating in female chimpanzees. Nature 414:508Google Scholar
  17. Galbusera P, van Dongen S, Matthysen E (2000) Cross-species amplification of microsatellite primers in passerine birds. Conserv Genet 1:163–168. doi: 10.1023/A:1026587024065 CrossRefGoogle Scholar
  18. Gelfand DH, White TJ (1990) Thermostable DNA polymerases. In: Innis MA, Gelfand DH, Sninsky JJ, White TJ (eds) PCR protocols: a guide to methods and applications. Academic Press Inc, San DiegoGoogle Scholar
  19. Goossens B, Chikhi L, Utami SS, de Ruiter J, Bruford MW (2000) A multi-samples, multi-extracts approach for microsatellite analysis of faecal samples in an arboreal ape. Conserv Genet 1:157–162. doi: 10.1023/A:1026535006318 CrossRefGoogle Scholar
  20. Hoffman JI, Amos W (2005) Microsatellite genotyping errors: detection approaches, common sources and consequences for paternal exclusion. Mol Ecol 14:599–612. doi: 10.1111/j.1365-294X.2004.02419.x PubMedCrossRefGoogle Scholar
  21. Hung C-H, Li S-H, Lee LL (2004) Faecal DNA typing to determine the abundance and spatial organisation of otters (Lutra lutra) along two stream systems in Kinmen. Anim Conserv 7:301–311. doi: 10.1017/S1367943004001453 CrossRefGoogle Scholar
  22. Kijas JMH, Andersson L (2001) A phylogenetic study of the origin of the domestic pig estimated from the near-complete mtDNA genome. J Mol Evol 52:302–308PubMedGoogle Scholar
  23. Klukowska J, Strabel T, Mackowski M, Switonski M (2003) Microsatellite polymorphism and genetic distances between the dog, red fox and arctic fox. J Anim Breed Genet 120:88–94. doi: 10.1046/j.1439-0388.2003.00375.x CrossRefGoogle Scholar
  24. Kohn MH, Wayne RK (1997) Facts from feces revisited. Trends Ecol Evol 12:223–227. doi: 10.1016/S0169-5347(97)01050-1 CrossRefGoogle Scholar
  25. Lathuillière M, Ménard N, Gautier-Hion A, Crouau-Roy B (2001) Testing the reliability of noninvasive genetic sampling by comparing analyses of blood and fecal samples in Barbary macaques (Macaca sylvanus). Am J Primatol 55:151–158. doi: 10.1002/ajp.1048 PubMedCrossRefGoogle Scholar
  26. Launhardt K, Epplen C, Epplen JT, Winkler P (1998) Amplification of microsatellites adapted from human systems in faecal DNA of wild Hanuman langurs (Presbytis entellus). Electrophoresis 19:1356–1361. doi: 10.1002/elps.1150190826 PubMedCrossRefGoogle Scholar
  27. Litvaitis MK, Litvaitis JA (1996) Using mitochondrial DNA to inventory the distribution of remnant populations of New England cottontails. Wildl Soc Bull 24:725–730Google Scholar
  28. Lorenzini R, Posillico M, Lovari S, Petrella A (2004) Non-invasive genotyping of the endangered Apennine brown bear: a case study not to let one’s hair down. Anim Conserv 7:199–209. doi: 10.1017/S1367943004001301 CrossRefGoogle Scholar
  29. 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. doi: 10.1046/j.1365-294X.2002.01489.x PubMedCrossRefGoogle Scholar
  30. 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. doi: 10.1046/j.0962-1083.2001.01308.x PubMedCrossRefGoogle Scholar
  31. Murphy MA, Kendall KC, Robinson A, Waits LP (2007) The impact of time and field conditions on brown bear (Ursus arctos) faecal DNA amplification. Conserv Genet 8:1219–1224. doi: 10.1007/s10592-006-9264-0 CrossRefGoogle Scholar
  32. Parsons KM (2001) Reliable microsatellite genotyping of dolphin DNA from faeces. Mol Ecol Notes 1:341–344. doi: 10.1046/j.1471-8278.2001.00098.x CrossRefGoogle Scholar
  33. Palomares F, Godoy JA, Piriz A, O’Brien SJ, Johnson WE (2002) Faecal genetic analysis to determine the presence and distribution of elusive carnivores: design and feasibility for the Iberian lynx. Mol Ecol 11:2171–2182. doi: 10.1046/j.1365-294X.2002.01608.x PubMedCrossRefGoogle Scholar
  34. Pemberton JM, Slate J, Bancroft DR, Barrett JA (1995) Nonamplifying alleles at microsatellite loci: a caution for parentage and population studies. Mol Ecol 4:249–252. doi: 10.1111/j.1365-294X.1995.tb00214.x PubMedCrossRefGoogle Scholar
  35. Piggott MP (2004) Effect of sample age and season of collection on reliability of microsatellite genotyping of faecal DNA. Wildl Res 31:485–493. doi: 10.1071/WR03096 CrossRefGoogle Scholar
  36. 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. doi: 10.1071/WR02077 CrossRefGoogle Scholar
  37. Pompanon F, Bonin A, Bellemain E, Taberlet P (2005) Genotyping errors: causes, consequences and solutions. Nat Rev Genet 6:847–849. doi: 10.1038/nrg1707 PubMedCrossRefGoogle Scholar
  38. Primmer CR, Møller AP, Ellegren H (1996) A wide-range survey of cross-species microsatellite amplification in birds. Mol Ecol 5:365–378. doi: 10.1111/j.1365-294X.1996.tb00327.x PubMedCrossRefGoogle Scholar
  39. Prugh LR, Ritland CE, Arthur SM, Krebs CJ (2005) Monitoring coyote population dynamics by genotyping faeces. Mol Ecol 14:1585–1596. doi: 10.1111/j.1365-294X.2005.02533.x PubMedCrossRefGoogle Scholar
  40. Purvis A (1995) A composite estimate of primate phylogeny. Philos Trans R Soc Lond B Biol Sci 348:405–421. doi: 10.1098/rstb.1995.0078 PubMedCrossRefGoogle Scholar
  41. Ruell EW, Crooks KR (2007) Evaluation of noninvasive genetic sampling methods for felid and canid populations. J Wildl Manage 71:1690–1694. doi: 10.2193/2006-061 CrossRefGoogle Scholar
  42. 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. doi: 10.1046/j.1365-294x.2000.00993.x PubMedCrossRefGoogle Scholar
  43. Smith KL, Alberts SC, Bayes MK, Bruford MW, Altmann J, Ober C (2000) Cross-species amplification, non-invasive genotyping, and non-Mendelian inheritance of human STRPs in savannah baboons. Am J Primatol 51:219–227. doi :10.1002/1098-2345(200008)51:4<219::AID-AJP1>3.0.CO;2-GGoogle Scholar
  44. Soulsbury CD, Iossa G, Edwards KJ, Baker PJ, Harris S (2007) Allelic dropout in a high-quality DNA source. Conserv Genet 8:733–738. doi: 10.1007/s10592-006-9194-x CrossRefGoogle Scholar
  45. Taberlet P, Luikart G (1999) Non-invasive genetic sampling and individual identification. Biol J Linn Soc Lond 68:41–55CrossRefGoogle Scholar
  46. Taberlet P, Griffin S, Goossens B, Questiau S, Manceau V, Escaravage N et al (1996) Reliable genotyping of samples with very low DNA quantities using PCR. Nucleic Acids Res 24:3189–3194. doi: 10.1093/nar/24.16.3189 PubMedCrossRefGoogle Scholar
  47. Taberlet P, Camarra J-J, Griffin S, Uhrès E, Hanotte O, Waits LP et al (1997) Noninvasive genetic tracking of the endangered Pyrenean brown bear population. Mol Ecol 6:869–876. doi: 10.1111/j.1365-294X.1997.tb00141.x PubMedCrossRefGoogle Scholar
  48. Vege S, McCracken GF (2001) Microsatellite genotypes of big brown bats (Eptesicus fuscus: Vespertilionidae, Chiroptera) obtained from their feces. Acta Chiropt 3:237–244Google Scholar
  49. Walsh PS, Erlich HA, Higuchi R (1992) Preferential PCR amplification of alleles: mechanisms and solutions. PCR Methods Appl 1:241–250PubMedGoogle Scholar
  50. Wandeler P, Smith S, Morin PA, Pettifor RA, Funk SM (2003) Patterns of nuclear DNA degradation over time—a case study in historic teeth samples. Mol Ecol 12:1087–1093. doi: 10.1046/j.1365-294X.2003.01807.x PubMedCrossRefGoogle Scholar
  51. Weber JL, Wong C (1993) Mutation of human short tandem repeats. Hum Mol Genet 2:1123–1128. doi: 10.1093/hmg/2.8.1123 PubMedCrossRefGoogle Scholar
  52. Whittingham MJ, Stephens PA, Bradbury RB, Frecklton RP (2006) Why do we still use stepwise modelling in ecology and behaviour? J Anim Ecol 75:1182–1189. doi: 10.1111/j.1365-2656.2006.01141.x PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Carl D. Soulsbury
    • 1
    Email author
  • Graziella Iossa
    • 1
  • Keith J. Edwards
    • 1
  1. 1.School of Biological SciencesUniversity of BristolBristolUK

Personalised recommendations