Deterministic DNA-first discovery reveals recurrent genomic architectures

Genome mining typically begins with known genes or protein families, which can make systems defined primarily by genomic organization difficult to detect. We developed a DNA-first framework combining asymmetric-covariance natural-vector representations with generic positional recurrence, joining separately calibrated signals through genomic coordinates. In benchmarks of array-associated reverse transcriptase (ART) loci, the target-free mathematical arm localized seven of eight predeclared loci, including all seven with exact-array coordinates. Dual-arm signals occurred in none of three non-array RT controls and in one of five UG27 systems, indicating selectivity within these small control sets. A separate profile-guided search of 6.12 Gb identified five candidate array-associated RT-like systems. In an independent 54.38-Gb evaluation of this profile-guided arm, structural compatibility was 24/32 under a historical-rule mirror, 12/32 after novelty-only selection, and 0/17 for architecture-selected complete ORFs; the two 32-member panels shared six exact sequences. Together, these results suggest that mathematical features of raw DNA can complement protein-directed searches in nominating genomic architectures for experimental RNA-to-DNA studies.