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


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.


Clonal richness Clonal evenness Error simulation Microsatellites Somatic mutations 



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

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10682_2010_9389_MOESM2_ESM.xls (8.2 mb)
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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of Botany and Landscape EcologyEMAU GreifswaldGreifswaldGermany

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