hapFLK

hapFLK detects selection signatures in multiple-population genotyping datasets by comparing haplotype frequencies while accounting for hierarchical population structure to identify loci under selection.

Key Features:

• Haplotype frequency statistic: Implements a novel statistic that focuses on haplotype frequencies across populations rather than only allele frequency differences.
• Hierarchical population structure: Models the hierarchical structure of sampled populations to increase accuracy and power in detecting loci under selection.
• Robustness to demographic events: Demonstrates robust detection performance in simulations under scenarios involving genetic bottlenecks and migration events.
• Detection of incomplete selective sweeps: Identifies incomplete selective sweeps where favorable haplotypes are at intermediate frequencies in one or more populations.
• Empirical validation on sheep data: Applied to genotyping data from six sheep breeds across Northern Europe and identified seven genomic regions under selection and the populations affected.

Scientific Applications:

• Domestication and breeding studies: Detects genomic regions and populations under selection in domesticated species such as sheep.
• Conservation genetics: Identifies loci under selection relevant to population management and conservation efforts.
• Evolutionary inference: Reveals selection signals and incomplete sweeps useful for studies of recent adaptive history and population differentiation.

Methodology:

Computes a haplotype-frequency-based statistic, incorporates hierarchical population structure into the model, evaluates performance using computer simulations, and applies the statistic to multi-population genotyping data (e.g., six sheep breeds across Northern Europe).