PROJECT SUMMARY Cellular RNA levels in both healthy and diseased cells are highly dynamic, yet most analyses of RNA concentrations (RNA-sequencing, RNA-seq) capture only a static snapshot of cellular RNA. RNA levels are controlled at diverse steps in RNA metabolism including transcriptional initiation, transcriptional pausing, RNA processing, and RNA degradation. Further, each of these steps can lead to different transcript isoforms by influencing the transcript initiation site, splicing patterns, and termination positions, thereby leading to distinct transcript isoforms that can have different coding potential, localization, and stability. Comparisons of the kinetics of these steps under different conditions is therefore central to understanding regulation of gene expression. There is a pressing need for robust and accessible technologies that can be easily adapted to study the kinetic regulation of the broad range of steps in RNA metabolism. The overall objective of this ongoing work is to add a temporal dimension to RNA-seq, transforming it from a static endpoint assay into a robust technique to measure the kinetics of RNA metabolism and reveal the diverse ways these kinetics are regulated and impacted by disease and therapeutics. This platform is based on RNA metabolic labeling and improvements in nucleotide chemistry to study RNA dynamics at a range of timescales. Work supported by this grant has led to improved chemistry, a well-documented open-source software package to perform the first replicate- aware and robust comparisons across experimental conditions, new insights into promoter- proximal pausing of RNA polymerase II, and improved analyses of nascent transcription. To fulfill the potential of these approaches, this integrated platform still needs to be extended to transcript-isoform resolution, new sequencing formats, and provide improved integration across experiments and timescale. The work described in Aim 1 will extend this platform to provide robust detection of changes with transcript-isoform resolution. The work in Aim 2 will extend this platform to long-read sequencing formats and will include optimization of chemistry and processing for extended sequencing modalities. Aim 3 will establish experimental workflows to optimally integrate analyses across timescales and experimental steps, to provide broad insight into changes in RNA expression across the entire lifecycle of the transcript. Each of these aims will include specific applications to reveal new biology and establish the general applicability of the platform. Successful completion of these aims will establish nucleotide recoding chemistry as a general platform to reveal RNA dynamics with isoform resolution across distinct levels of gene expression.