Isoform- and pathway-specific regulation of post-transcriptional RNA processing in human cells

Steady-state levels of RNA transcripts are determined by their rates of synthesis and degradation. In this study, we use nascent RNA Bru-seq and BruChase-seq to investigate RNA dynamics across 16 human cell lines, as part of the ENCODE4 Deeply Profiled Cell Lines collection. Our analyses show that RNA turnover dynamics differ widely between transcripts of different genes and among different classes of RNA, but remain primarily cell-type independent. Gene set enrichment analysis (GSEA) reveals that transcripts encoding proteins belonging to the same pathway often show similar turnover dynamics. Furthermore, transcript isoforms exhibit distinct turnover profiles, suggesting that RNA turnover plays an important role in regulating mRNA isoform choice. Finally, splicing of newly synthesized transcripts appears to occur in a binary manner, largely happening either fully on both sides of 47,163 exons or not at all. These data sets generated as part of the ENCODE Project illustrate the intricate and coordinated regulation of RNA dynamics in controlling gene expression, allowing for the precise coordination of cellular functions.