title: Taxon sampling effects in molecular clock dating: an example from the African Restionaceae.
abstract: Three commonly used molecular dating methods for correction of variable rates (non-parametric rate smoothing, penalized likelihood, and Bayesian rate correction) as well as the assumption of a global molecular clock were tested for sensitivity to taxon sampling. The test dataset of 6854 basepairs for 300 terminals includes a nearly complete sample of the Restio-clade of the African Restionaceae (272 of the 288 species), as well as 26 outgroup species. Of this, nested subsets of 35, 51, 80, 120, 150, and the full 300 species were used. Molecular dating experiments with these datasets showed that all methods are sensitive to undersampling, but that this effect is more severe in analyses that use more extreme rate smoothing. Additionally, the undersampling effect is positively related to distance from the calibration node. The combined effect of undersampling and distance from the calibration node resulted in up to threefold differences in the age estimation of nodes from the same dataset with the same calibration point. We suggest that the most suitable methods are penalized likelihood and Bayesian when a global clock assumption has been rejected, as these methods are more successful at finding optimal levels of smoothing to correct for rate heterogeneity, and are less sensitive to undersampling.
authors.affiliation: Institute for Systematic Botany, University of Zurich, Zollikerstrasse 107, CH-8008 Zurich, Switzerland. plinder@systbot.unizh.ch
authors.forename: H Peter
authors.initials: HP
authors.lastname: Linder
authors.forename: Christopher R
authors.initials: CR
authors.lastname: Hardy
authors.forename: Frank
authors.initials: F
authors.lastname: Rutschmann
mesh_terms: D000349:Africa; D001499:Bayes Theorem; D003627:Data Interpretation, Statistical; D019143:Evolution, Molecular; D019684:Magnoliopsida / Q000235:genetics*; D008957:Models, Genetic; D010802:Phylogeny; D015983:Selection Bias; D017422:Sequence Analysis, DNA / Q000706:statistics & numerical data*