A new method for estimating the demographic history from DNA sequences: an importance sampling approach

Area of Science:

• Population Genetics
• Computational Biology
• Evolutionary Biology

Background:

• * Effective population size (Ne) over time, or demographic history, is crucial for understanding evolutionary processes.
• * Inferring demographic history from contemporary DNA sequences is a fundamental challenge in population genetics.

Purpose of the Study:

• * To introduce a novel importance sampling (IS) based methodology, the skywis plot, for reconstructing demographic histories.
• * To provide a more robust method for analyzing effective population size changes over time using DNA sequence data.

Main Methods:

• * Employing importance sampling (IS) to analyze a large number of genealogies.
• * Calculating a weighted average of effective population sizes across time intervals (epochs) based on IS weights.
• * Comparing the skywis plot's performance against the Bayesian skyline plot (BSP).

Main Results:

• * The skywis plot accurately reconstructs recent demographic history in simulations.
• * The method successfully identifies change points in effective population size.
• * Performance is comparable to the Bayesian skyline plot, with potential improvements for serially sampled data.

Conclusions:

• * The skywis plot offers a powerful new tool for inferring demographic history from DNA sequence data.
• * The method is particularly effective in capturing recent population size fluctuations.
• * Future applications may extend to serially sampled sequences and specific demographic scenarios like exponential expansion.