Winding up the molecular clock in the genus Carabus (Coleoptera: Carabidae): assessment of methodological decisions on rate and node age estimation
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BMC Evolutionary Biology 2012, 12:40 doi:10.1186/1471-2148-12-40Published: 28 March 2012
Rates of molecular evolution are known to vary across taxa and among genes, and this requires rate calibration for each specific dataset based on external information. Calibration is sensitive to evolutionary model parameters, partitioning schemes and clock model. However, the way in which these and other analytical aspects affect both the rates and the resulting clade ages from calibrated phylogenies are not yet well understood. To investigate these aspects we have conducted calibration analyses for the genus Carabus (Coleoptera, Carabidae) on five mitochondrial and four nuclear DNA fragments with 7888 nt total length, testing different clock models and partitioning schemes to select the most suitable using Bayes Factors comparisons.
We used these data to investigate the effect of ambiguous character and outgroup inclusion on both the rates of molecular evolution and the TMRCA of Carabus. We found considerable variation in rates of molecular evolution depending on the fragment studied (ranging from 5.02% in cob to 0.26% divergence/My in LSU-A), but also on analytical conditions. Alternative choices of clock model, partitioning scheme, treatment of ambiguous characters, and outgroup inclusion resulted in rate increments ranging from 28% (HUWE1) to 1000% (LSU-B and ITS2) and increments in the TMRCA of Carabus ranging from 8.4% (cox1-A) to 540% (ITS2). Results support an origin of the genus Carabus during the Oligocene in the Eurasian continent followed by a Miocene differentiation that originated all main extant lineages.
The combination of several genes is proposed as the best strategy to minimise both the idiosyncratic behaviors of individual markers and the effect of analytical aspects in rate and age estimations. Our results highlight the importance of estimating rates of molecular evolution for each specific dataset, selecting for optimal clock and partitioning models as well as other methodological issues potentially affecting rate estimation.