A two-locus neutrality test: applications to humans, E. coli and lodgepole pine

Area of Science:

• Population Genetics
• Molecular Evolution

Background:

• Genetic disequilibrium, the non-random association of alleles at different loci, is a key concept in population genetics.
• Understanding disequilibrium patterns helps infer evolutionary processes like selection, mutation, and recombination.

Purpose of the Study:

• To theoretically determine expected genetic disequilibrium between two loci under neutrality.
• To tabulate measures of disequilibrium with confidence intervals for varying population parameters.
• To compare theoretical expectations with empirical data from human, bacterial, and plant populations.

Main Methods:

• Calculated expected disequilibrium for a sample of size n from a neutral population.
• Tabulated three disequilibrium measures with 95% intervals across different sample sizes (n), allele numbers (k, l), and recombination rates (4Nc).
• Compared theoretical disequilibrium predictions with observed data from Human Leukocyte Antigen (HLA) loci, E. coli, and lodgepole pine.

Main Results:

• Genetic disequilibrium extent and pattern are strongly influenced by effective population size (N) and recombination rate (c), and moderately by sample size (n) and allele counts (k, l).
• Confidence intervals for disequilibrium measures are notably large, especially with fewer alleles and lower 4Nc values.
• Human HLA data exhibited greater disequilibrium than predicted by neutrality, while E. coli and lodgepole pine data showed less disequilibrium than expected.

Conclusions:

• Theoretical disequilibrium expectations provide a baseline for evaluating empirical genetic data.
• Deviations from neutrality predictions in empirical data suggest the influence of factors like selection or demographic history.
• The study highlights the importance of considering population size and recombination rates when interpreting genetic disequilibrium patterns.