RNA‐Seq of Cultured Peripheral Blood Lymphocytes Improves Identification of Cryptic Splicing Defects in Rare Disease Diagnostics

Accurate identification of the genetic determinants of rare diseases is essential for effective recurrence-risk management and informed reproductive decision-making. Although whole-exome sequencing (WES) and whole-genome sequencing (WGS) have significantly improved diagnostic capabilities, a subset of affected families still receives no definitive molecular diagnosis. RNA sequencing (RNA-seq) has emerged as a promising complementary diagnostic tool, yet its clinical implementation in the context of preconception genetic counseling remains underexplored. We used phytohemagglutinin-activated peripheral blood cells (PHACs) as a robust RNA source and enhanced conventional RNA-seq through the integration of three analytical innovations: (1) transcript isoform distribution (TID) analysis, (2) realignment against the MANE (Matched Annotation from NCBI and EMBL-EBI) reference transcriptome, and (3) pharmacological induction-based cryptic splicing detection. This optimized pipeline was applied to 55 rare-disease families with negative WES/WGS results who were undergoing preconception genetic counseling. Based on prior evaluations, families were grouped as VUS (<i>n</i> = 7), suspected-gene/variant-negative (<i>n</i> = 10), and unsolved/no-candidate (<i>n</i> = 38). PHACs showed reduced interindividual variability and higher RNA integrity than fresh PBMCs (median RIN: 9.77 vs. 8.97; <i>p</i> < 0.0001). The optimized workflow improved diagnostic yield by 2.2-fold (20% vs. 9%). Stratified analysis revealed positive rates of 71% (VUS), 40% (suspected-gene/variant-negative), and 5.2% (unsolved/no-candidate). Among the 11 positive cases, 10 received definitive diagnoses, leading to diverse reproductive decisions. This enhanced RNA-seq workflow provides a clinically applicable and scalable strategy for improving molecular diagnostics in reproductive and preconception settings, offering a valuable model for future clinical transcriptomics.