Talk abstracts
Talk on Friday 02:00-02:15pm submitted by Deepak Sharma
KIN-CLIP: transcriptome-wide kinetics for RNA-protein interactions in cells
Deepak Sharma (Center for RNA Science and Therapeutics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106), Leah Zagore (Center for RNA Science and Therapeutics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106), Matthew Brister (Department of Chemistry, Case Western Reserve University, Cleveland, OH 44106), Carlos Crespo Hernandez (Department of Chemistry, Case Western Reserve University, Cleveland, OH 44106), Donny Licatalosi (Center for RNA Science and Therapeutics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106), Eckhard Jankowsky (Center for RNA Science and Therapeutics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106)
Abstract:
RNA-binding proteins (RBPs) often interact with many different RNAs at sometimes large numbers of binding sites. These interactions are highly dynamic. Association and dissociation rate constants by which an RBP interacts with each binding site thus determine global RNA binding patterns of the protein and ultimately its biological function. However, it has not been possible to measure kinetic parameters for protein binding at individual RNA sites in cells.
Here, we describe a transcriptome-wide approach to determine kinetic parameters for protein binding at individual RNA sites in cells. We combine time-resolved UV-crosslinking with a pulsed UV-laser, Immunoprecipitation, Next Generation Sequencing, and large scale kinetic modeling, to determine rate constants for association, dissociation, crosslinking as well as the fractional occupancy for thousands of binding sites for the mouse RBP Dazl in GC1 cells. This kinetic CLIP (KIN-CLIP) approach reveals that both association and dissociation rate constants for Dazl vary by 2 to 3 orders of magnitude among different binding sites, thus providing Dazl with a large dynamic range for binding to various sites. Crosslinking rate constants differ by only about one order of magnitude over all binding sites. Our data reveal that Dazl stays bound at its binding sites for only few seconds or less, and that discrimination between different binding sites occurs predominantly during the association step. The fractional occupancy for a majority of Dazl binding sites is smaller than ten percent, suggesting that regulation of binding site accessibility plays a large role for Dazl-RNA binding in the cell. We finally use multivariate machine learning to correlate the kinetic parameters with RNA features, cellular pathways, and ribosome profiling data and devise a detailed, quantitative model that links Dazl’s RNA binding kinetics to its impact on mRNA metabolism.
Collectively, our results show that the KIN-CLIP technique, by bridging biochemical and transcriptomic approaches, allows the measurement of previously inaccessible quantitative and biochemical parameters for RNA-protein interactions in cells and the use of these datasets can aid in generating quantitative mechanistic models of RNA-protein interactions in vivo.
Keywords: in vivo biochemistry, RNA binding kinetics, Multivariate RNA regulation