Exon recognition during constitutive pre-mRNA splicing

Columbia Univ New York Morningside, New York NY

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Abstract

DESCRIPTION (provided by applicant): RNA molecules guide cellular processes at many levels of gene expression. They do so through specific molecular interactions with RNA-binding proteins (RBPs) to form multi-protein ribonucleoprotein complexes (RNPs). Each RBP exhibits a preference for binding to a particular set of RNA sequences, but this set could be many. We will establish the biophysical parameters governing the molecular interactions that take place between specific RBPs and their specific RNA sequence targets in mammalian cells. This specificity is typically a continuous function, with the tightest binders accompanied by less and less tightly bound sequences. These latter are likely to compete for RBPs in the cell and indeed their weaker binding may be important to their function, as for example a transient binding that is a prerequisite in the assembly of a more stable multi-protein complex. Through the use of high throughput DNA sequencing technology (Illumina) we will measure biophysical binding constants for all 65,536 possible RNA sequences of 8 bases; a length of 8 is somewhat larger than a typical RNA target. These binding parameters will be comprised of the equilibrium dissociation constant (Kd) to measure overall tightness, and the important kinetic constants of the on-rate and the off-rate, a measure of accessibility and stability, respectively. Recombinant RBPs will be expressed in cultured mammalian cells and then purified and covalently immobilized on beads in a single step following transient transfection. The beads will be exposed to a library of RNA molecules comprising all possible 8-mers. The bead-bound molecules will be isolated after various times as well as at equilibrium and the number of molecules of each RNA sequence bound will be determined by deep sequencing. After establishment of the methodology using one model RBP (the pre- mRNA splicing factor Fox-2), the method will be extended to additional related splicing factors. As this sort of data is accumulated for additional RBPs, we will be able to model RNA-protein interactions that occur in the cell and better understand the combinatorial factors that make these RNPs so complex. In addition, such fundamental information will allow us to better predict how disturbances in RNA metabolism, commonly seen in genetic diseases and in cancer, can affect cell behavior.