An alignment- and reference-free strategy using <italic>k</italic>-mer present pattern for population genomic analyses.

Pangenomes are replacing single reference genomes to capture all variants within a species or clade, but their analysis predominantly leverages graph-based methods that require multiple high-quality genomes and computationally intensive multiple-genome alignments. <italic>K</italic>-mer decomposition is an alternative to graph-based pangenomes. However, how to directly use <italic>k</italic>-mers for the population genetic analyses is unknown. Here, we developed a novel strategy that uses the variants of <italic>k</italic>-mer count in the genome for population analyses. To test the effectivity of this method, we compared it directly to the SNP-based method on the analysis of population structure and genetic diversity of 267 <italic>Saccharomyces cerevisiae</italic> strains within two simulated datasets and a real sequence dataset. The population structure identified with <italic>k</italic>-mers recapitulates that obtained using SNPs, indicating the effectiveness of <italic>k</italic>-mer-based approach, and higher genetic diversity within real dataset supported <italic>k</italic>-mers contained more genetic variants. Based on <italic>k</italic>-mer frequency, we found not only SNP but also some insertion/deletion and horizontal gene transfer (HGT) fragments related to the adaptive evolution of <italic>S. cerevisiae</italic>. Our study creates a framework for the alignment- and reference-free (ARF) method in population genetic analyses, which will be more pronounced in the species with no complete genome or highly diverged species. [ABSTRACT FROM AUTHOR]