Human Frontier Science Program
In search of conserved mRNA localization and anchoring mechanisms
We have a new international collaborative program with Professor Anne Spang (Biozentrum, Basel, Switzerland) and Chris Brown (Otega University, NewZealand) to identify RNA localization zipcodes in yeast and mammalian cells and to test their conservation of function.
Although protein localization mechanisms have been intensively investigated over the last few decades, the localization of RNAs, which are at least as diverse as proteins, has been much less widely studied. Yet RNA localization is crucial for normal development, and defects in the process may underlie numerous diseases, particularly neuropathologies.
The sorting of transcripts to their particular subcellular destinations depends on trans-acting factors that recognize signals in RNAs, called zip codes. These codes have proven harder to decipher than the equivalent signals in proteins, because they often depend on secondary or tertiary structures within the RNAs, rather than on a consensus primary sequence. An important goal, therefore, is to develop robust algorithms that can identify these codes, but large RNA datasets are needed to test and use these tools. Many fundamental questions remain to be answered. How many RNAs are localized? How many different zip codes exist? Have these codes been conserved through evolution? Are transport codes and anchoring codes identical or separable? Is localization regulated by signaling inputs?
Through an international collaboration we now have a unique opportunity to answer these questions. Genome-wide screening has provided us with a large dataset of mammalian mRNAs that localize with the tumor suppressor APC to cell protrusions and axonal growth cones. We have also identified yeast mRNAs that change localization depending on the function of a small GTPase involved in vesicular transport. These datasets offer an unrivaled opportunity to develop new algorithms for zip code identification, and to refine these methods by testing predictions against experimental data. Evolutionary conservation of the zip codes will be tested by expressing the yeast zip codes in mammalian cells and vice versa.