Alignment-Free k-mer Analysis Reveals Age-Associated k-mer Signals in Canine Buccal DNA and Cell-Free DNA
Aging is associated with progressive molecular and cellular changes that alter chromatin organization, epigenetic regulation, and microbial community structure. While DNA methylation-based biomarkers have demonstrated age-prediction performance, the potential of alignment-free sequence analysis for detecting age-associated signals remains unexplored. We performed a k-mer-based analysis of whole-genome sequencing datasets from two canine cohorts: 1,187 buccal DNA samples and 100 cell-free DNA (cfDNA) samples. Age-associated k-mers were identified through correlation analysis, and sequence motifs and nucleotide composition patterns were characterized across both sample types. Ridge regression models were used to predict age from k-mer frequency profiles, and synthetic datasets were generated under biological compositional assumptions to evaluate potential drivers of the observed signals. Age-associated k-mer signals were identified in both buccal DNA and cfDNA, with substantially stronger patterns observed in buccal samples. Buccal-derived k-mers exhibited more pronounced motif patterns, stronger GC and AT enrichment trends, and improved age-prediction performance relative to cfDNA. Nucleotide enrichment trends differed between sample types, suggesting that distinct biological processes may contribute to age-associated sequence composition changes in buccal DNA and cfDNA. Simulation analyses successfully reproduced major enrichment trends observed empirically, and age-associated signals were largely preserved following restriction to read-start sequence composition. These findings demonstrate that alignment-free k-mer analysis can detect age-associated sequence composition signals in canine DNA and highlight its potential as a computationally efficient complementary approach for aging biomarker discovery.