Characterizing the informativeness of pathogen genome sequence datasets about transmission between population groups

Area of Science:

• Epidemiology
• Genomics
• Population Genetics

Background:

• Pathogen genome analysis is crucial for understanding transmission dynamics between populations.
• The accumulation of mutations within pathogen genomes dictates the resolution of transmission inference.
• Interplay between mutation rate, transmission events, population mixing, and sampling affects study power.

Purpose of the Study:

• To develop a framework to quantify the ability of pathogen sequences to capture between-group transmission history.
• To investigate the impact of mutation rate, transmission pace, population mixing, and sampling on phylogeographic analyses.
• To identify inherent limits in pathogen genomic study resolution.

Main Methods:

• Developed a conceptual probabilistic framework for phylogeographic analysis.
• Quantified sequence data informativeness for between-group transmission history.
• Conducted simulation studies varying sequencing intensity and sample size.

Main Results:

• Identified a pathogen-intrinsic limit on the scale of population mixing detectable by sequence data.
• Faster mutating pathogens enable finer spatial and temporal characterization of transmission.
• Sample size imposes a significant limit on resolving between-group transmission processes.

Conclusions:

• The resolvability of population mixing processes is inherently limited by the interplay of pathogen evolution, transmission dynamics, population structure, and sampling strategies.
• Understanding these limits is essential for designing effective pathogen genomic surveillance studies.
• Faster mutation rates enhance the granularity of transmission inference from pathogen genomic data.