New Routes to Phylogeography: A Bayesian Structured Coalescent Approximation.

Area of Science:

• Genetics
• Evolutionary Biology
• Computational Biology

Background:

• Phylogeographic methods analyze genetic data to reconstruct lineage history and migration.
• Pathogen phylogeography aids in understanding transmission, outbreak origins, and emergence.
• Discrete trait models offer computational efficiency but lack accuracy in phylogeographic inference.

Purpose of the Study:

• To evaluate the reliability of discrete trait models for phylogeographic inference.
• To introduce BASTA (Bayesian Structured coalescent Approximation) as an accurate and efficient alternative.
• To investigate the zoonotic transmission of Ebola virus using robust phylogeographic methods.

Main Methods:

• Comparison of discrete trait models with structured coalescent methods.
• Development and implementation of BASTA in BEAST2.
• Application to Ebola virus zoonotic transmission analysis.

Main Results:

• Discrete trait models demonstrate unreliability and sensitivity to sampling bias in inferring migration rates and root locations.
• BASTA combines structured coalescent accuracy with computational efficiency for multi-population analyses.
• Ebola virus analysis revealed successive human outbreaks seeded by an unsampled non-human reservoir, contradicting discrete trait model conclusions.

Conclusions:

• Discrete trait models can lead to implausible conclusions regarding pathogen transmission dynamics.
• BASTA provides a robust approach for accurate phylogeographic inference, crucial for infectious disease control.
• Accurate phylogeographic insights are vital for genomics-informed strategies in preventing and controlling infectious diseases.