Coalescent models derived from birth-death processes.

Area of Science:

• Population Genetics
• Mathematical Biology
• Evolutionary Dynamics

Background:

• Coalescent theory models the genetic ancestry of populations.
• Standard coalescent models often assume constant population size or specific demographic histories.
• Simulating complex demographic processes requires efficient modeling techniques.

Purpose of the Study:

• To develop a novel coalescent model, the Limit Birth-Death (LBD) coalescent, based on a birth-death process.
• To address the computational limitations of the exact LBD coalescent model for large sample sizes.
• To introduce approximations and a hybrid model for faster simulations.

Main Methods:

• Derivation of the LBD coalescent model from a birth-death process with a single founder.
• Scaling parameters and time as the present-day population size (N0) approaches infinity.
• Development of approximations assuming deterministic population size functions.
• Introduction of a hybrid LBD coalescent model combining exactness and speed.

Main Results:

• The LBD coalescent model provides a framework for samples from populations with a specific demographic history.
• Direct simulations of the LBD coalescent model are computationally intensive.
• Approximations and the hybrid model offer computationally feasible alternatives for LBD coalescent simulations.

Conclusions:

• The LBD coalescent model extends existing coalescent theory to a specific class of birth-death processes.
• Approximations and hybrid models are crucial for practical application of the LBD coalescent model.
• This work facilitates more efficient inference of demographic history from genetic data.