Ancestral Processes with Selection

Area of Science:

• Population Genetics
• Evolutionary Biology
• Computational Biology

Background:

• Understanding gene genealogy is crucial for evolutionary studies.
• Existing models like Kingman's coalescent process do not account for selection.
• Developing methods to incorporate selection into genealogical models is essential.

Purpose of the Study:

• To introduce and analyze the ancestral selection graph for gene genealogy.
• To compare the ancestral selection graph with Kingman's coalescent process.
• To investigate the impact of selection and mutation on genetic ancestry.

Main Methods:

• Construction and simulation of the ancestral selection graph.
• Analytical comparison with Kingman's coalescent process.
• Derivation of formulas for identity by descent and time to most recent common ancestor.

Main Results:

• The ancestral selection graph provides a comprehensive model for gene genealogy with selection and mutation.
• In the absence of mutation, selection does not alter the distribution of time to the most recent common ancestor.
• With mutation, identity by descent depends on both selection and mutation rates, differing from neutral models.

Conclusions:

• The ancestral selection graph is a powerful tool for studying the effects of selection on genetic ancestry.
• The model highlights key differences between neutral and selected scenarios in population genetics.
• Simulation algorithms based on the ancestral selection graph can approximate sample probabilities effectively.