Abstract
RNA processing (RNAP), including splicing and alternative polyadenylation, is crucial to gene function and regulation, but methods to detect RNAP 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, the first annotation-free statistical approach to identify regulated RNAP in single cells. ReadZS discovers cell type-specific RNAP in the human lung and conserved, developmentally regulated RNAP in mammalian spermatogenesis - including global 3’ UTR shortening in human spermatogenesis. ReadZS also discovers global 3’ UTR lengthening in Arabidopsis root development, highlighting the usefulness of this method in under-annotated transcriptomes.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Background and results updated to clarify contribution of ReadZS method; additional section on Arabidopsis data analysis added.