Accurate Allele Frequencies from Ultra-low Coverage Pool-Seq Samples in Evolve-and-Resequence Experiments

Area of Science:

• Evolutionary biology
• Genomics
• Population genetics

Background:

• Evolve-and-resequence (E+R) experiments track allele frequency dynamics using next-generation sequencing.
• High-coverage sequencing is often required for accurate allele frequency estimation, increasing costs.
• Detecting adaptive alleles typically relies on comparing frequency trajectories across replicate populations.

Purpose of the Study:

• To develop a cost-effective method for accurate allele frequency estimation in E+R experiments.
• To enable the detection of adaptive alleles with reduced sequencing depth.
• To provide a broadly accessible tool for E+R experimental designs.

Main Methods:

• Haplotype inference in small genomic windows using shallow sequencing (<5x).
• Utilizing known founder haplotypes from sequenced homozygous strains.
• Validation using simulated and experimentally pooled Drosophila melanogaster samples.
• Development of a predictive linear model for accuracy across different designs.

Main Results:

• Haplotype inference significantly improves allele frequency accuracy (orders of magnitude) with shallow sequencing.
• The method is robust to moderate missing data and various selection regimes.
• Accuracy is maintained for up to 50 generations of recombination.
• A predictive model accurately estimates accuracy for new experimental designs.

Conclusions:

• Shallow sequencing with haplotype inference provides a cost-effective alternative to high-coverage sequencing for E+R studies.
• This approach increases the power to detect adaptive alleles by enabling higher replication and resolution.
• The open-source HAF-pipe software tool makes these methods accessible to researchers.
• The method is applicable to various model organisms and experimental setups.