K-mer-based Approaches to Bridging Pangenomics and Population Genetics.

Area of Science:

• Genomics
• Population Genetics
• Bioinformatics

Background:

• Multiple chromosome-scale genome assemblies reveal significant genetic diversity.
• Challenges exist in aligning references for pangenome construction, limiting study of genomic variation.
• K-mers offer a powerful, underutilized approach to bridge population genetics and pangenomics.

Purpose of the Study:

• To highlight the utility of k-mers in population genetics and pangenomics.
• To review k-mer applications in identifying, measuring, and explaining genetic variation.
• To evaluate k-mer-based genetic diversity measures in simulations.

Main Methods:

• Literature review of k-mer applications in population genetics.
• Population genetic simulations to test k-mer measures under varying parameters (k-mer length, coverage, compression).
• Analysis of k-mer dissimilarity approximation using bloom filters.

Main Results:

• K-mer genetic diversity measures correlate well with pairwise nucleotide diversity (π) up to π=0.025 (R²=0.97) in neutral populations.
• Shorter k-mers maintain scalability for higher variation (up to π=0.1).
• Bloom filters can approximate k-mer dissimilarity, reducing memory requirements.

Conclusions:

• K-mers are effective for studying genetic variation across population genetics and pangenomics.
• K-mer analysis is scalable and can be memory-efficient.
• Further development of k-mer methods for identifying selected loci is recommended.