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Nei's to Bayes’: comparing computational methods and genetic markers to estimate patterns of genetic variation in Tolpis (Asteraceae)
Author(s) -
Levsen Nicholas D.,
Crawford Daniel J.,
Archibald Jenny K.,
SantosGeurra Arnoldo,
Mort Mark E.
Publication year - 2008
Publication title -
american journal of botany
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.218
H-Index - 151
eISSN - 1537-2197
pISSN - 0002-9122
DOI - 10.3732/ajb.0800091
Subject(s) - biology , asteraceae , bayes' theorem , variation (astronomy) , evolutionary biology , genetic variation , genetics , bayesian probability , statistics , botany , gene , mathematics , physics , astrophysics
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.