DecodeDegRNA SIGNED

Project "DecodeDegRNA" data sheet

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 Project objective

Regulation of gene expression lies at the heart of fundamental biological processes, such as the formation of different cell types inside an embryo or responses to environmental stimuli. Living cells ensure that the right genes are expressed at the right time and place by carefully controlling every RNA molecule inside a cell from its ‘birth’ by transcription to its final ‘death’ by degradation. While vast efforts strive to understand the first part of this process – transcription, studies of RNA degradation have been more limited. Current knowledge largely relies on small-scale investigation of key – but anecdotal – cases, while technical and experimental difficulties limit its large-scale analysis. Therefore, we still lack a systematic and predictive understanding of RNA degradation: technologies to globally measure it, the molecular mechanisms involved, its functional and physiological implications and models to decode and predict it. Transcriptional silencing makes early embryos an ideal system to study RNA degradation and uncover its basic concepts, as I propose here. Aim 1 will decipher how genomic information within native RNA sequences determines their degradation in embryos. Aim 2 will develop the technology to investigate RNA degradation at single-cell resolution, and uncover its regulation within arising embryonic cell populations. Aim 3 will reveal the molecular implementation of the regulatory code of RNA degradation and determine its physiological roles that underlie the massive degradation of maternal mRNAs – a key regulatory event and a main developmental transition in early embryos of all animals. This work will uncover new principles of RNA degradation in early development and elicit its mechanisms and functions using the zebrafish as an in vivo model system. The assays and models to be developed will be broadly applicable to study RNA degradation in diverse contexts, ranging from disease mechanisms to engineering of RNA- protein interactions.