Systematic discovery of structural elements governing stability of mammalian messenger RNAs

Decoding post-transcriptional regulatory programs in RNA is a critical step in the larger goal to develop predictive dynamical models of cellular behavior. Despite recent efforts1–3, the vast landscape of RNA regulatory elements remain largely uncharacterized. A longstanding obstacle is the contribution of local RNA secondary structure in defining interaction partners in a variety of regulatory contexts, including but not limited to transcript stability3, alternative splicing4 and localization3. There are many documented instances where the presence of a structural regulatory element dictates alternative splicing patterns (e.g. human cardiac troponin T) or affects other aspects of RNA biology5. Thus, a full characterization of post-transcriptional regulatory programs requires capturing information provided by both local secondary structures and the underlying sequence3,6. We have developed a computational framework based on context-free grammars3,7 and mutual information2 that systematically explores the immense space of small structural elements and reveals motifs that are significantly informative of genome-wide measurements of RNA behavior. The application of this framework to genome-wide mammalian mRNA stability data revealed eight highly significant elements with substantial structural information, for th