Abstract
Next-generation RNA sequencing (RNA-seq) enables comprehensive transcriptomic profiling for disease characterization, biomarker discovery, and precision medicine. Despite its potential, RNA-seq has not yet been widely adopted for clinical applications, and a key barrier to its adoption is the variability introduced during processing and analysis. Quality controls (QCs) must be considered through all stages of biomarker discovery. This study describes a comprehensive QC framework for effective RNA-seq biomarker discovery. Multilayered quality metrics were established across preanalytical, analytical, and postanalytical processes. Total RNA-seq was performed by using RNA isolated from whole blood (PAXgene Blood RNA tubes). Bulk RNA controls were incorporated to monitor sequencing batches. This framework was applied to a catalog of prospectively collected or biobanked clinical specimens spanning multiple disease indications. Among all QCs, preanalytical metrics (specimen collection, RNA integrity, and genomic DNA contamination) exhibited the highest failure rates and resulted in the addition of a secondary DNase treatment, which reduced genomic DNA levels. The additional DNase treatment significantly lowered intergenic read alignment and provided sufficient RNA for downstream sequencing and analysis. This end-to-end QC framework for RNA-seq biomarker discovery was developed and implemented to enhance the confidence and reliability of results. To advance the clinical adoption of RNA-seq, developing and implementing standards will improve reliability, accelerate biomarker discovery, and facilitate its translation into clinically actionable diagnostics and therapeutics.