Abstract

RNA processing, including splicing and alternative polyadenylation, is crucial to gene function and regulation, but methods to detect RNA processing from single-cell RNA sequencing data are limited by reliance on pre-existing annotations, peak calling heuristics, and collapsing measurements by cell type. We introduce ReadZS, an annotation-free statistical approach to identify regulated RNA processing in single cells. ReadZS discovers cell type-specific RNA processing in human lung and conserved, developmentally regulated RNA processing in mammalian spermatogenesis—including global 3′ UTR shortening in human spermatogenesis. ReadZS also discovers global 3′ UTR lengthening in Arabidopsis development, highlighting the usefulness of this method in under-annotated transcriptomes.

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