Reprogramming genetic information at the RNA level: optimizing tools to address specific biological questions

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RNA editing is a robust and nearly ubiquitous modification (deamination) of RNA. Compared to most other modifications it is straightforward to identify as it alters nucleic acid sequence in a defined fashion (e.g. adenosine to inosine and cytosine to uracil, catalyzed by ADARs or APOBECs, respectively). It occurs reproducibly and with high prevalence in transcripts derived from cells of the immune system and the nervous system but also in transcripts derived from tumor cells from lung, breast, colon and most other tissues. Significant effort has been expended over the last decade to catalog editing, especially in the context of cancer. These efforts have led to correlations between editing load and disease outcomes. However, causality of editing of specific transcripts with biological outcomes has not been demonstrated, due to lack of proper tools to efficiently recapitulate editing of subsets of transcripts within specific cells, and to address the functional consequences of such targeted editing. Here, we propose to use (and continue to optimize) tools that allow efficient and multi-targeted ADAR editing, to recapitulate specific (natively occurring) editing events on groups of transcripts, which we have recovered from cancer cells, and to address the functional consequences of aggregate editing for pathways defined by the edited transcripts. We also propose to generate novel tools to allow targeted APOBEC editing which we can also apply to address the role of dual editing (ie both ADAR and APOBEC) on transcripts and the pathways those define.This proposal falls under the umbrella of Specific Priority Programme “Chemical Biology of Native Nucleic Acid Modifications ”. It brings together two groups with complementary expertise: the first group has been at the forefront of tool development for efficient and precise ADAR targeting. The other group has spent considerable time cataloguing instances of editing (in healthy tissue and in cancer) and then attempting to understand their functional relevance. In addition to gaining an understanding on the consequences of RNA editing, the tools we propose here to build will allow the targeting of RNAs in non-native settings (e.g. coding regions) and this will allow the re-coding of amino acids for therapeutic purposes.