Haplotype based testing for a better understanding of the selective architecture

Area of Science:

• Population genetics
• Genomics
• Evolutionary biology

Background:

• Identifying genomic regions under selection is crucial in population genetics.
• Current methods often rely on allele frequency changes at single nucleotide polymorphism (SNP) positions using temporal data.
• This study introduces a novel approach utilizing haplotype frequencies.

Purpose of the Study:

• To develop and evaluate a new statistical testing approach for detecting selection using haplotype frequencies.
• To compare the performance of the haplotype-based method against traditional SNP-based tests.
• To provide tools for understanding selection dynamics, including post hoc tests.

Main Methods:

• Developed a new statistical test based on haplotype frequencies.
• Utilized simulated data to assess the power and performance of the new method compared to SNP-based tests.
• Investigated methods for combining haplotypes to improve power with large haplotype numbers.
• Applied the method to a real dataset to demonstrate practical benefits.

Main Results:

• The haplotype-based approach demonstrated higher statistical power than SNP-based tests, particularly with small to moderate numbers of candidate haplotypes.
• Haplotype frequencies showed reduced noise compared to SNP frequencies, especially in pool sequencing scenarios.
• The method is less susceptible to false positives caused by spurious outlier SNPs.
• Post hoc tests were developed to analyze selection dynamics and coefficients.

Conclusions:

• Haplotype-based testing offers superior power over SNP-based tests in most scenarios due to reduced noise and less need for multiple testing correction.
• The new approach provides a more robust and accurate method for identifying genomic regions affected by selection.