A computer program to simulate multilocus genotype data with spatially autocorrelated allele frequencies

Area of Science:

• Population genetics
• Spatial genetics
• Bioinformatics

Background:

• Many population genetic models assume Hardy-Weinberg and linkage equilibrium within groups.
• This assumption is often violated by spatial structure from isolation by distance (IBD).
• IBD can lead to nonrandom mating and affect allele frequency distributions.

Purpose of the Study:

• To develop a flexible model and simulation program for data with spatial genetic structure.
• To assess how isolation by distance (IBD) impacts population genetic inference.
• To evaluate the effectiveness of different spatial sampling schemes.

Main Methods:

• Developed a computer program to simulate spatial variations in allele frequencies due to IBD and barriers.
• Used the program to assess the accuracy of cluster inference under panmixia assumptions.
• Investigated the effects of clumped versus uniform spatial sampling on inference accuracy.

Main Results:

• Isolation by distance can substantially inflate the number of inferred populations, creating spurious clusters.
• The effect of spatial sampling scheme on inference accuracy was minimal.
• Strong IBD relative to sampling domain size led to the most significant inference errors.

Conclusions:

• The developed simulation tool aids in evaluating statistical inference methods and designing spatial sampling strategies.
• IBD poses a significant challenge to accurate population genetic inference, often necessitating specialized models.
• The simulation program is integrated into the R package Geneland for broader accessibility.