scTranslatomics · Development of novel integrated sequencing methods to explore translation and its regulatory mechanisms in single cells

In recent years novel single-cell sequencing methods have allowed an in-depth analysis of the diversity of cell types and states in a wide range of organisms. Due to the continuous optimization of experimental and computational methods by many research groups, it is now possible to sequence the transcriptomes of thousands to millions of individual cells. Albeit an exciting development, transcription only covers the first step in the central dogma. The second step, the process of translation, is currently much harder to explore in single cells. Building upon existing ribosome profiling protocols, our laboratory recently majorly increased the sensitivity of these assays allowing ribosome profiling in single cells. However, currently no methods exist to determine the translation efficiencies in single cells and to correlate translation efficiencies to tRNA levels and their modifications, RNA bound proteins, and m6A methylation of mRNA, all major regulatory mechanisms of translation. The overarching goal of this proposal is to develop several novel multi-omics approaches to quantify translation in single cells by integrating information on ribosome position along the transcript, tRNA expression levels, tRNA modifications, RNA-bound proteins, and the m6A methylation status of the transcript. These technologies will open novel avenues to start exploring translation and its regulatory mechanisms with single-cell resolution. Whereas major discoveries have been made during the last decade by exploring the genome, the epigenome, and the transcriptome using single-cell sequencing approaches, translation, the major second step in the central dogma, is still very much unexplored at the single-cell level. I hope that the tools, presented in this proposal will provide the community with methods to explore, and ultimately understand, how translation contributes to the astonishing heterogeneity among single cells.