Jaatha: a fast composite-likelihood approach to estimate demographic parameters

Area of Science:

• Population genetics
• Evolutionary biology
• Genomics

Background:

• Species demographic history is crucial for population genetic analyses.
• Existing methods often fail to account for intralocus recombination or recent divergence, leading to long computation times.
• Accurate demographic inference is essential for understanding evolutionary processes.

Purpose of the Study:

• To introduce Jaatha, a novel composite-likelihood method for inferring species demographic history.
• To address limitations of existing methods regarding intralocus recombination and recent divergence.
• To provide a more accurate and efficient tool for population genetic analyses.

Main Methods:

• Development of Jaatha, a composite-likelihood method incorporating recent divergence and high intralocus recombination rates.
• Estimation of four key demographic parameters.
• Application of Jaatha to closely related wild tomato species (Solanum chilense and S. peruvianum) as a proof of concept.

Main Results:

• Jaatha demonstrates comparable accuracy to existing methods, outperforming them in cases of very recent divergence.
• Estimated divergence time between S. chilense and S. peruvianum as 1.44·N generations (N = effective population size of S. chilense).
• Evidence of post-divergence introgression between the two tomato species and a population expansion in S. peruvianum.

Conclusions:

• Jaatha offers a robust and accurate approach for inferring demographic history, particularly for recently diverged species.
• The method provides valuable insights into the evolutionary dynamics of wild tomato species.
• Jaatha advances the field of population genetics by offering a more versatile and efficient analytical tool.