BATMAN: BREAKPOINT ADAPTIVE TARGETING ALONGSIDE METHYLATION ANALYSIS ON NANOPORE

Abstract AIMS Structural rearrangements are increasingly understood to significantly alter the prognosis of a wide range of CNS tumours. For example, co-deletion of CDKN2A/B is a hallmark of high-grade astrocytoma, oligoden- droglioma and meningioma. Despite their clinical importance, detection of intra-chromosomal rearrangements is challenging using short-read technologies and copy number variations (CNV) are commonly inferred from methylation array. Such testing has limited resolution to detect small, intra-chromosomal CNV calls with high confidence. Nanopore technology is an emerging technique in CNS diagnostics, enabling targeted long-read sequencing alongside methylome classification. However, current implementations of adaptive targeting are restricted to an a priori defined set of key driver oncogenes. In contrast, genomic breakpoints underpinning SVs are unique to individual patients and are thus challenging to sequence at high coverages. METHODS Here, we present BATMAN, a development of the ROBIN diagnostic tool that enables real-time enrichment of patient-specific genomic breakpoints. BATMAN infers genomic breakpoint loci during sequencing and dynam- ically adapts the target panel in real-time. RESULTS We present the performance of BATMAN on CNS tumours harbouring a variety of CNVs. We demonstrate the potential to generate long-reads spanning deletion of CDKN2A/B in high-grade astrocytoma, oligodendroglioma, and glioblastoma. Furthermore, we demonstrate the ability of BATMAN to resolve complex rearrangements such as chromothripsis events and accurately infer genome-wide copy number variation load, an emerging prognostic biomarker. CONCLUSION BATMAN enables the sequencing of long reads spanning breakpoints at high coverages, enabling the robust detection of clinically relevant SVs.