Single-cell transcriptome analyses on developmental transitions in mouse pluripotent stem cells

Böttcher M. Single-cell transcriptome analyses on developmental transitions in mouse pluripotent stem cells. Bielefeld: Universität Bielefeld; 2020.We used an in vitro model of Pluripotent Stem Cell (PSC) development in mice to analyze dynamic changes in transcriptomes of hundreds of individual cells which were undergoing an induced transition from naïve mouse Embryonic Stem Cells (mESC) towards primed pluripotent Epiblast Stem Cells (EpiSC). The differentiation of mESCs to EpiSC-like cells takes about five days after induction. We collected cell samples in 24-hour intervals for four days after induction as well as untreated mESCs and primed state EpiSCs. Single-cell isolation and scRNA-seq library preparation for each time point were done on the commercial Fluidigm C1 platform. In addition, we sampled C1-Cap Analysis of Gene Expression (C1-CAGE) libraries for the same set of time points to enable detection of non- coding RNAs (ncRNAs) such as anti-sense RNAs or enhancer RNAs. This C1-CAGE protocol was new and still undergoing optimization at the beginning of our experiments. C1-CAGE was first published by Kouno *et al.* (2019) and the author of this thesis contributed as a co-author. Throughout the work on this project a data management platform called SCPortalen was developed to share all data among project collaborators. SCPortalen’s publication was also co-authored by the author of this thesis (Abugessaisa et al., 2018). The combination of transcriptome datasets from two different protocols allowed the elucidation of expression dynamics of the naïve- to-primed stem cell conversion. We independently identified two subpopulations of cells during the transition process with both the Fluidigm scRNA-seq and C1-CAGE dataset. Pseudotime analysis revealed the developmental trajectory of cells and is a powerful tool to reliably identify developmental stages of cells without prior knowledge of their actual stage. Among these two transition phase subpopu- lations, one showed wide-spread repression of gene expression. The small nuclear RNA (snRNA) *Rn7sk* was identified as one potential regulator of this population specific phenomenon. The second subpop- ulation shared some characteristics with primed EpiSCs such as cell morphology and the expression of known primed state marker genes, but it could be shown that cells from this population were still undergoing Epithelial-Mesenchymal Transition (EMT). That is a clear sign that these cells have not yet fully transitioned to primed pluripotent stem cells. Interestingly, the characteristics of this subpopulation largely match a predicted third pluripotency state called “formative” (Smith, 2017). Therefore, we believe that our dataset not only contains naïve and primed pluripotent stem cells, but also formative pluripotent stem cells. Thus, our dataset represents a unique resource to compare and study this proposed formative pluripotency state. Last but not least, we found several marker gene candidates for all developmental stages of the naïve-to-primed transition, which will facilitate classification of cells in future experiments. For example, we propose *Cd59a* as a highly specific marker gene for primed EpiSCs. The results of this thesis project have also been compiled into a manuscript for publication in a peer reviewed journal and will be submitted soon after the submission of this thesis