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(American Journal of Botany. 2008;95:1466-1474.) doi: 10.3732/ajb.0800091 © 2008 Botanical Society of America, Inc.

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Nei’s to Bayes’: comparing computational methods and genetic markers to estimate patterns of genetic variation in Tolpis (Asteraceae)¹

² Department of Ecology and Evolutionary Biology and The Natural History Museum and Biodiversity Research Center, University of Kansas, Lawrence, Kansas 66045 USA ³ Jardín de Aclimatación de la Orotava, Puerto de la Cruz, Tenerife, Canary Islands, Spain

ABSTRACT

Accurate determination of patterns of genetic variation provides a powerful inferential tool for studies of evolution and conservation. For more than 30 years, enzyme electrophoresis was the preferred method for elucidating these patterns. As a result, evolutionary geneticists have acquired considerable understanding of the relationship between patterns of allozyme variation and aspects of evolutionary process. Myriad molecular markers and statistical analyses have since emerged, enabling improved estimates of patterns of genetic diversity. With these advances, there is a need to evaluate results obtained with different markers and analytical methods. We present a comparative study of gene statistic estimates (F_ST, G_ST, F_IS, H_S, and H_T) calculated from an intersimple sequence repeat (ISSR) and an allozyme data set derived from the same populations using both standard and Bayesian statistical approaches. Significant differences were found between estimates, owing to the effects of marker and analysis type. Most notably, F_ST estimates for codominant data differ between Bayesian and standard approaches. Levels of statistical significance are greatly affected by methodology and, in some cases, are not associated with similar levels of biological significance. Our results suggest that caution should be used in equating or comparing results obtained using different markers and/or methods of analysis.

Key Words: allozymes • arbitrarily amplified DNA (AAD) • Asteraceae • Bayesian analysis • codominant markers • genetic differentiation • genetic diversity • intersimple sequence repeat • ISSR • Tolpis

Received for publication 9 March 2008. Accepted for publication 25 August 2008.

FOOTNOTES

¹ The authors thank K. Holsinger, M. Holder, and J. Kelly for discussions of Bayesian methodology and its application to the current study. This research was supported by the Department of Ecology and Evolutionary Biology and the Natural History Museum & Biodiversity Research Center at the University of Kansas. A Kansas NSF EPSCoR Ecological Genomics postdoctoral award to J.A. helped to fund this research.

⁴ Author for correspondence (e-mail: levsenn{at}ku.edu)

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