f-Statistics estimation and admixture graph construction with Pool-Seq or allele count data using the R package...

Area of Science:

• Population Genetics
• Bioinformatics
• Evolutionary Biology

Background:

• Genetic variation patterns across populations are key to inferring demographic history.
• Existing statistics, like f-statistics, are effective but often require haplotype data.
• Pooled sequencing (Pool-Seq) offers a cost-effective alternative but requires specialized methods.

Purpose of the Study:

• To reinterpret f-statistics using the probability of gene identity.
• To derive unbiased estimators for both Pool-Seq and allele count data.
• To implement these estimators in an enhanced R package, poolfstat, for broader accessibility.

Main Methods:

• Reinterpretation of f-statistics based on gene identity probability.
• Development of unbiased estimators for SNP allele frequency differences.
• Implementation of admixture tests, treeness tests, admixture ratio estimation, and admixture graph construction within the poolfstat R package.

Main Results:

• Validated accuracy of new estimators on simulated Pool-Seq and allele count data, even with low sequencing coverage.
• Demonstrated effectiveness in analyzing real Pool-Seq data from Drosophila suzukii populations.
• Successfully refined demographic history and invasion routes for Drosophila suzukii.

Conclusions:

• The enhanced poolfstat package provides a unified and accurate framework for population genetic analyses.
• It supports user-friendly inference of demographic history from both Pool-Seq and individual genotype data.
• The tool is valuable for studying complex population genetic structures and histories.