A harmonized workflow to enable efficient tumor-normal matched whole genome sequencing from HMW gDNA and FFPE samples.

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e15116 Background: Whole genome sequencing (WGS) in clinical oncology offers a comprehensive approach to tumor genomic profiling, enabling detection of actionable mutations, structural variants, copy number alterations, and other genomic signatures that may be missed by targeted panels. As sequencing costs continue to decline and computational capacity expands, WGS is becoming increasingly accessible and represents a scalable alternative to targeted assays and whole exome sequencing. Importantly, tumor-normal matched WGS allows for accurate discrimination between somatic and germline variants, substantially reducing variant misclassification commonly observed with tumor-only analyses and thereby increasing confidence in biomarker identification and therapeutic decision-making. Methods: To support clinical implementation, we established a harmonized WGS workflow capable of processing both high molecular weight (HMW) genomic DNA (gDNA) and DNA extracted from formalin-fixed, paraffin-embedded (FFPE) tumor samples using a single standardized protocol. We evaluated the Watchmaker DNA Library Prep Kit with Fragmentation as a unified library preparation solution to generate consistent WGS libraries across diverse clinical sample types while minimizing turnaround time in a clinical testing environment. Performance was assessed using commercial FFPE samples and a combination of Genome in a Bottle HMW gDNA and FFPE reference materials. All sequencing data were analyzed using the Illumina DRAGEN WGS pipeline. Results: After optimizing DNA input, DNA fragmentation and PCR cycles, the Watchmaker DNA Library Prep Kit produced high-quality WGS libraries across all sample types, characterized by low duplication rates (≤10%) and uniform genome-wide coverage. Robust variant calling performance was observed, demonstrating strong concordance with reference datasets as well as high reproducibility across technical replicates, regardless of sample type. Conclusions: In summary, the Watchmaker DNA Library Prep Kit with Fragmentation enables efficient, high-quality WGS library generation through a harmonized workflow applicable to both HMW gDNA and FFPE samples. This approach supports accurate somatic variant detection with reduced turnaround time, providing a scalable and practical solution for implementing WGS in clinical oncology settings, like variant selection for tumor-informed MRD applications.

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