Calibrating a molecular clock from phylogeographic data: moments and likelihood estimators

Area of Science:

• Population Genetics
• Molecular Evolution
• Phylogenetics

Background:

• Estimating DNA substitution rates is crucial for understanding evolutionary history.
• Existing methods often overlook ancestral coalescent processes, potentially leading to biased estimates.
• Variation in multitaxa datasets is not fully explained by current models.

Purpose of the Study:

• To develop and validate new statistical methods for estimating DNA substitution rates.
• To simultaneously estimate ancestral population sizes and test for differences among them.
• To explain observed variation in multitaxa datasets by incorporating ancestral coalescence and mutation processes.

Main Methods:

• Development of moments and likelihood methods for estimating DNA substitution rates.
• Utilizing closely related sister species pairs separated at an assumed time.
• Testing methods through simulations with varying sample sizes (≥5 species pairs).

Main Results:

• Both methods provide accurate estimates of DNA substitution rates and ancestral population sizes with sufficient sample sizes.
• Likelihood estimates improve when ancestral population sizes do not significantly differ.
• Variation in multitaxa datasets can be explained by variations in ancestral coalescence and mutation processes.

Conclusions:

• The proposed methods offer a more accurate way to estimate evolutionary parameters.
• Ancestral population size variation is a key factor explaining observed data variation, rather than divergence time or mutation rate.
• The methods were successfully applied to sea urchin and Alpheus snapping shrimp data.