Beta-PSMC

Beta-PSMC models detailed historical effective population size changes by integrating the probability density function of a beta distribution into the Pairwise Sequentially Markovian Coalescent (PSMC) framework to infer demographic history from genomic data.

Key Features:

• PSMC foundation: Builds on the Pairwise Sequentially Markovian Coalescent (PSMC) model.
• Beta distribution integration: Incorporates the probability density function of a beta distribution with diverse shapes into the PSMC framework.
• Within-interval population variability: Allows non-constant effective population size across each discretized time interval instead of assuming constancy.
• Improved accuracy and resolution: Models detailed fluctuations in population size within intervals to enhance accuracy and resolution of recent demographic inference, as demonstrated by simulations.
• Simulation validation: Demonstrated through simulations to uncover more nuanced demographic events compared to conventional methods.
• Empirical application: Applied to Adélie penguin genomic data, inferring population fluctuations between 15,000 and 27,000 years ago that did not correlate with temperature changes.

Scientific Applications:

• Demographic reconstruction: Infers detailed historical effective population size trajectories from genomic data.
• Analysis where constant-size assumptions fail: Suitable for studies in which the PSMC assumption of constant population size per time bin is inadequate.
• Studies of environmentally driven or rapid evolutionary change: Applicable to species with known environmental fluctuations or rapid evolutionary dynamics.

Methodology:

Integrates the beta distribution's probability density function into the PSMC framework to replace the constant-size assumption within discretized time intervals, with validation by simulations and application to Adélie penguin genomic data.