As artificial intelligence (AI) and machine learning (ML) increasingly shape the future of biomedical research, the demand for robust, high-resolution multi-omic data continues to rise. However, one of the richest sources of clinical specimens—formalin-fixed paraffin-embedded (FFPE) tissue—has historically remained underutilized due to the technical difficulties of extracting high-quality nucleic acids for next-generation sequencing (NGS).
In this whitepaper, Zymo Research introduces a scalable, automated workflow that overcomes the longstanding barriers of FFPE sample processing. By combining advanced DNA and RNA purification protocols with innovative NGS library preparation techniques, the study demonstrates successful generation of high-complexity whole genome sequencing (WGS) and transcriptomic (RNA-Seq) datasets from low-integrity FFPE brain tumor samples.
Key highlights include:
- An end-to-end protocol optimized for high-throughput platforms and automation, reducing hands-on time while maximizing nucleic acid yield and quality.
- Novel enzymatic methods enabling efficient recovery and sequencing of highly fragmented FFPE DNA and RNA, even at low input concentrations.
- Multi-omic profiling capabilities, supporting AI-ready data generation for population-scale studies, biomarker discovery, and precision medicine initiatives.
Whether you're working in translational genomics, bioinformatics, or biobanking, this whitepaper provides a roadmap for transforming archived FFPE specimens into actionable genomic data—without compromising quality, speed, or scalability.
Discover how Zymo’s cutting-edge sample prep and NGS solutions enable high-quality data generation from challenging samples and accelerate AI-driven breakthroughs in biomedical research.