SpliceUp: Predicting SF3B1 mutations in individual cells via aberrant splice site activation from scRNA-seq data

Myeloid neoplasms (MN) are clonal heterogeneous disorders initiated by somatic driver mutations in hematopoietic stem and progenitor cells (HSPCs). Among the most common are mutations in RNA splicing factors, which exert pleiotropic effects but are difficult to study due to altered hematopoietic differentiation and the inability to specifically isolate mutant HSPCs. Single-cell transcriptomics offers a powerful framework to dissect mutant cell states, yet direct genotyping is hampered by data sparsity and often requires costly, labor-intensive approaches. To overcome this limitation, we developed SpliceUp, a computational tool that identifies splice factor-mutant cells through their aberrant RNA splicing signatures. Applied to SF3B1-mutant samples, SpliceUp exploits cryptic 3 splice site usage and exon-skipping events to achieve more than a 7-fold increase in mutant cell detection from low-coverage 10x Genomics datasets. Differential expression analysis revealed cell typespecific programs, including MHC-II upregulation in SF3B1-mutated HSCs and enhanced RNA translation in SF3B1-mutated erythroid precursors.