Widespread 3-Base Periodicity in Complex DNA Mixtures and an Alignment-Free Algorithm to Uncover its Source
Background: Protein-coding DNA exhibits characteristic three-base periodicity. In unaligned DNA libraries, however, this signal should cancel if fragment boundaries are uniformly distributed across codon phases. Yet, we find that in multiple metagenomic libraries, base frequencies depended systematically on distance from fragment boundaries, producing a period-3 pattern. We investigated the origin of this unexpected signal. Results: The signal was observed in modern metagenomic datasets and widely across ancient-DNA datasets. We developed a new alignment-free algorithm to infer latent triplet-phase structure from nucleotide composition. The inferred shifts were strongly nonuniform at fragment boundaries, explaining the read-coordinate periodicity. We initially suspected a protocol artifact. To test an alternative, we derived a probabilistic framework linking nucleotide-dependent boundary selection to codon-phase frequencies. The framework showed that, because nucleotide composition differs among codon positions, preferential breakage at particular nucleotides biases the phases represented at fragment boundaries. Simulations confirmed this mechanism: purine-associated fragmentation produced strong period-3 coherence in a coding-dense bacterial genome, whereas no comparable genome-wide effect appeared in the human reference genome. Conclusions: The observed read-coordinate three-base periodicity does not require an intrinsic phase bias in the source DNA. Instead, sequence-dependent fragment formation or recovery can couple boundaries to codon phase. Purine-associated post-mortem fragmentation plausibly explains the widespread phenomenon in ancient-DNA libraries, although PCR- or library-specific mechanisms may contribute to it in modern datasets. Our alignment-free algorithm provides a practical method for estimating and normalizing phase shifts before searching for positional nucleotide patterns, preventing boundary-associated bias from being mistaken for an intrinsic biological pattern.