LUNa-seq enables selective single-end UMI tagging for high-fidelity long-amplicon reconstruction and rare-species detection

Accurate analysis of long, structured, and repetitive integrated DNA elements is frequently confounded by PCR amplification bias and the intrinsically high error rates of long-read sequencing technologies. Lentiviral vectors (LVs), which are fundamental tools in clinical cell engineering, typically span 3–10 kb and contain GC-rich regulatory modules and terminal repeats. These features challenge current analytical assays, making it difficult to simultaneously characterize full-length structural integrity, estimate rare-species composition (< 1%), and monitor packaging-sequence recombination. Here, we introduce LUNa-seq (lentiviral UMI-guided Nanopore sequencing), an integrated experimental and computational workflow. By combining selective single-end unique molecular identifier (UMI) tagging with a three-round nested PCR architecture, LUNa-seq physically restricts exponential amplification to bona fide UMI-bearing molecules, structurally suppressing early-cycle off-target and template-switched artifacts. Validated across 24 lentiviral constructs and three human cell types, LUNa-seq yielded highly contiguous proviral reconstructions (averaging ~ 99% target span). By employing per-UMI consensus clustering, the pipeline effectively mitigated length- and GC-dependent PCR distortion and achieved apparent consensus-level error rates approaching the Q40 range under the tested lentiviral conditions once ≥ 5 reads per UMI were sampled. Under defined spike-in parameters, the workflow supported rare-species detection and approximate abundance estimation down to the 0.1% level. Furthermore, LUNa-seq facilitated direct molecular surveillance of packaging-sequence recombination, sensitively detecting engineered packaging-sequence junctions with a practical ~ 250 bp confidence threshold. By unifying molecular tracking, consensus-based error correction, and structural recombination monitoring into a single targeted assay, LUNa-seq provides a robust and auditable analytical framework for lentiviral-vector quality assessment. With appropriate system-specific validation, this strategy may offer a transferable blueprint for characterizing other complex, kilobase-scale genomic constructs.