Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris

Comparison of the level of differentiation at neutral molecular markers (estimated as F(ST) or G(ST)) with the level of differentiation at quantitative traits (estimated as Q(ST)) has become a standard tool for inferring that there is differential selection between populations. We estimated Q(ST) of...

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Bibliographic Details
Published in:Heredity 2005-06, Vol.94 (6), p.623-629
Main Authors: Waldmann, P, Garcia-Gil, M.R, Sillanpaa, M.J
Format: Article
Language:English
Subjects:
alleles
Bayes Theorem
Biomedical and Life Sciences
Biomedicine
bud initiation
bud set
Cytogenetics
Ecology
Evergreen trees
Evolutionary Biology
forest trees
Gene Frequency
genetic drift
Genetic Markers
Genetic Variation
Genetics, Population
geographical variation
Heterogeneity
Human Genetics
latitude
latitudinal clines
loci
microsatellite repeats
Models, Genetic
original-article
phenology
Pine trees
Pinus sylvestris
Pinus sylvestris - genetics
Plant Genetics and Genomics
Population structure
Quantitative Trait, Heritable
quantitative traits
Variance analysis
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Summary:Comparison of the level of differentiation at neutral molecular markers (estimated as F(ST) or G(ST)) with the level of differentiation at quantitative traits (estimated as Q(ST)) has become a standard tool for inferring that there is differential selection between populations. We estimated Q(ST) of timing of bud set from a latitudinal cline of Pinus sylvestris with a Bayesian hierarchical variance component method utilizing the information on the pre-estimated population structure from neutral molecular markers. Unfortunately, the between-family variances differed substantially between populations that resulted in a bimodal posterior of Q(ST) that could not be compared in any sensible way with the unimodal posterior of the microsatellite F(ST). In order to avoid publishing studies with flawed Q(ST) estimates, we recommend that future studies should present heritability estimates for each trait and population. Moreover, to detect variance heterogeneity in frequentist methods (ANOVA and REML), it is of essential importance to check also that the residuals are normally distributed and do not follow any systematically deviating trends.
ISSN:0018-067X
1365-2540
DOI:10.1038/sj.hdy.6800672