Advertisement

Evolutionary Ecology

, Volume 24, Issue 6, pp 1417–1432 | Cite as

Consequences of genotyping errors for estimation of clonality: a case study on Populus euphratica Oliv. (Salicaceae)

  • M. SchnittlerEmail author
  • P. Eusemann
Original Paper

Abstract

A study including eight microsatellite loci for 1,014 trees from seven mapped stands of the partially clonal Populus euphratica was used to demonstrate how genotyping errors influence estimates of clonality. With a threshold of 0 (identical multilocus genotypes constitute one clone) we identified 602 genotypes. A threshold of 1 (compensating for an error in one allele) lowered this number to 563. Genotyping errors can seemingly merge (type 1 error), split really existing clones (type 2), or convert a unique genotype into another unique genotype (type 3). We used context information (sex and spatial position) to estimate the type 1 error. For thresholds of 0 and 1 the estimate was below 0.021, suggesting a high resolution for the marker system. The rate of genotyping errors was estimated by repeated genotyping for a cohort of 41 trees drawn at random (0.158), and a second cohort of 40 trees deviating in one allele from another tree (0.368). For the latter cohort, most of these deviations turned out to be errors, but 8 out of 602 obtained multilocus genotypes may represent somatic mutations, corresponding to a mutation rate of 0.013. A simulation of genotyping errors for populations with varying clonality and evenness showed the number of genotypes always to be overestimated for a system with high resolution, and this mistake increases with increasing clonality and evenness. Allowing a threshold of 1 compensates for most genotyping errors and leads to much more precise estimates of clonality compared with a threshold of 0. This lowers the resolution of the marker system, but comparison with context information can help to check if the resolution is sufficient to apply a higher threshold. We recommend simulation procedures to investigate the behavior of a marker system for different thresholds and error rates to obtain the best estimate of clonality.

Keywords

Clonal richness Clonal evenness Error simulation Microsatellites Somatic mutations 

Notes

Acknowledgments

We thank Prof. Nurbay Abdusalih, Xinjiang University and numerous Chinese students for their help and support in Urumqi and in the field. Anja Klahr, Greifswald University, provided valuable help in the lab. For very helpful comments and ideas we wish to thank Sophie Arnaud-Haond, Univ. do Algarve, Portugal. This research was supported by the Deutsche Forschungsgemeinschaft (DFG, grant number SCHN1081-1/1).

Supplementary material

10682_2010_9389_MOESM1_ESM.xls (8 mb)
XLS 8190 kb
10682_2010_9389_MOESM2_ESM.xls (8.2 mb)
XLS 8397 kb

References

  1. Anderson TJC, Su XZ, Roddam A, Day KP (2000) Complex mutations in a high proportion of microsatellite loci from the protozoan parasite Plasmodium falciparum. Mol Ecol 9:1599–1608CrossRefPubMedGoogle Scholar
  2. Arnaud-Haond S, Belkhir K (2007) GenClone: a computer program to analyze genotypic data, test for clonality and describe spatial organization. Mol Ecol Notes 7:15–17CrossRefGoogle Scholar
  3. Arnaud-Haond S, Alberto F, Teixeira S, Procaccini G, Serrao EA, Duarte CM (2005) Assessing genetic diversity in clonal organisms: low diversity or low resolution? Combining power and cost efficiency in selecting markers. J Hered 96:434–440CrossRefPubMedGoogle Scholar
  4. Arnaud-Haond S, Duarte CM, Alberto F, Serrão EA (2007) Standardizing methods to address clonality in population studies. Mol Ecol 16:5115–5139CrossRefPubMedGoogle Scholar
  5. Bonin A, Bellemain E, Bronken Eidesen P, Pompanon F, Brochmann C, Taberlet P (2004) How to track and assess genotyping errors in population genetics studies. Mol Ecol 13:3261–3273CrossRefPubMedGoogle Scholar
  6. Chakraborty R, Kimmel M, Stivers DM, Davison LJ, Deka R (1997) Relative mutation rates at di-, tri- and tetranucleotide microsatellite loci. Proc Natl Acad Sci USA 94:1041–1046CrossRefPubMedGoogle Scholar
  7. Dorken ME, Eckert CG (2001) Severely reduced sexual reproduction in northern populations of a clonal plant, Decodon verticillatus (Lythraceae). J Ecol 89:339–350CrossRefGoogle Scholar
  8. Douhovnikoff V, Dodd RS (2003) Intra-clonal variation and a similarity threshold for identification of clones: application to Salix exigua using AFLP molecular markers. Theor Appl Gen 106:1307–1315Google Scholar
  9. Eusemann P, Fehrenz S, Schnittler M (2009) Development of two microsatellite multiplex PCR systems for high throughput genotyping in Populus euphratica. J For Res 20:195–198CrossRefGoogle Scholar
  10. Halkett F, Simon J-C, Balloux F (2005) Tackling the population genetics of clonal and partially clonal organisms. Trends Ecol Evol 20:195–201CrossRefGoogle Scholar
  11. Hoffman JI, Amos W (2005) Microsatellite genotyping errors: detection approaches, common sources and consequences for paternal exclusion. Mol Ecol 14:599–612CrossRefPubMedGoogle Scholar
  12. Hood GM (2005) PopTools Version 2.6.7. Available online at http://www.cse.csiro.au/poptools/
  13. Klimeš L, Kilmesova J, Hendriks R, van Groenendael J (1997) Clonal plant architecture: a comparative analysis of form and function. In: de Kroon H, van Groenendael J (eds) The ecology and evolution of clonal plants. Backhuis Publishers, Leiden, pp 1–30Google Scholar
  14. Lepais O, Léger V, Gerber S (2006) Short note: high throughput microsatellite genotyping in oak species. Silvae Genet 55:238–240Google Scholar
  15. Li YC, Korol AB, Fahima T, Beiles A, Nevo E (2002) Microsatellites: genomic distribution, putative functions and mutational mechanisms: a review. Mol Ecol 11:2453–2465CrossRefPubMedGoogle Scholar
  16. Lian C, Oishi R, Miyashita N, Hogetsu T (2004) High somatic instability of a microsatellite locus in a clonal tree, Robinia pseudacacia. Theor Appl Gen 108:836–841CrossRefGoogle Scholar
  17. Magurran A (2004) Measuring biological diversity. Blackwell, MaldenGoogle Scholar
  18. Pareto V (1896–7) Cours d’Économie Politique. Professé à l’Université de Lausanne. 2 vols. F. Rouge, LausanneGoogle Scholar
  19. Pfeiffer T (2007) Vegetative multiplication and patch colonisation of Asarum europaeum subsp. europaeum L. (Aristolochiaceae) inferred by a combined morphological and molecular study. Flora 202:89–97Google Scholar
  20. Pompanon F, Bonin A, Bellemain E, Taberlet P (2005) Genotyping errors: causes, consequences and solutions. Nat Rev Genet 6:847–859CrossRefPubMedGoogle Scholar
  21. Rousset F (2008) Genepop’007: a complete re-implementation of the Genepop software for Windows and Linux. Mol Ecol Res 8:103–106CrossRefGoogle Scholar
  22. Selkoe KA, Toonen RJ (2006) Microsatellites for ecologists: a practical guide to using and evaluating microsatellite markers. Ecol Lett 9:615–629CrossRefPubMedGoogle Scholar
  23. Shannon CE, Weaver W (1963) The mathematical theory of communication. University Illinois Press, USAGoogle Scholar
  24. Smith B, Wilson JB (1996) A consumer’s guide to evenness indices. Oikos 76:70–82CrossRefGoogle Scholar
  25. Suzuki J, Herben T, Maki M (2004) An under-appreciated difficulty: sampling of plant populations for analysis using molecular markers. Evol Ecol 18:625–646CrossRefGoogle Scholar
  26. Thevs N, Zerbe S, Schnittler M, Abdusalih N, Succow M (2008) Structure, reproduction and flood-induced dynamics of riparian Tugai forests at the Tarim River in Xinjiang, NW China. Forestry 81:45–57CrossRefGoogle Scholar
  27. Vaughan SP, Russell K (2004) Characterization of novel microsatellites and development of multiplex PCR for large-scale population studies in wild cherry, Prunus avium. Mol Ecol Notes 4:429–431CrossRefGoogle Scholar
  28. Vos P, Hogers R, Bleeker M et al (1995) AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res 23:4407–4414CrossRefPubMedGoogle Scholar
  29. Wagner HW, Sefc KM (1999) IDENTITY 1.0. Centre for Applied Genetics, University of Agricultural Sciences Vienna, AustriaGoogle Scholar
  30. Wiehle M, Eusemann P, Thevs N, Schnittler M (2009) Root suckering patterns in Populus euphratica (Euphrates poplar, Salicaceae). Trees 23:991–1001CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of Botany and Landscape EcologyEMAU GreifswaldGreifswaldGermany

Personalised recommendations