Developing an evolutionary baseline model for humans: jointly inferring purifying selection with population history

Area of Science:

• Population Genetics
• Human Evolution
• Genomic Architecture

Background:

• Establishing baseline models is crucial for understanding population genetics and identifying selection.
• Models must account for constant genomic processes like purifying selection and population size changes.

Approach:

• Developed an approximate Bayesian model for the Yoruba population (West African ancestry).
• Jointly inferred demographic history and selective effects using background selection decay.
• Incorporated genomic architecture, including recombination rate heterogeneity and gene conversion.

Key Points:

• Inferred a recent 6-fold population growth in the Yoruba.
• Observed a distribution of fitness effects skewed towards effectively neutral mutations.
• Found strong or frequent positive selection inconsistent with the data.

Conclusions:

• Weak to moderate positive selection is possible but difficult to identify if rare.
• The developed model provides a robust baseline for human population genetics research.
• Highlights the importance of considering demographic history and background selection in evolutionary studies.