In WP1, we set out to determine the source of stochastic heart laterality fluctuations in the zebrafish. We discovered that this phenomenon is linked to global left/right signaling in the zebrafish embryo, and we could show that fluctuations in the number of dorsal forerunner cells, a small cell population specified at gastrulation stages, is responsible for stochastic heart inversion. Specifically, we could show by live microscopy that those embryos in which the number of dorsal forerunner cells is smallest develop laterality defects with much higher probability (Fig. 1). We found that these fluctuations are largely stochastic, with only a minor genetic component (Moreno-Ayala et al., Cell Reports, 2021).
In WP2, we proposed to develop a method for simultaneous cell type identification and lineage tracing in thousands of single cells. This project progressed exceedingly well and led to a high-level publication early in the funding period (Spanjaard et al., Nature Biotech, 2018). Specifically, we developed experimental approaches for generating lineage barcodes in zebrafish embryos by CRISPR/Cas9 and for detecting these barcodes by single cell transcriptomics (Fig. 2). Importantly, we characterized the diversity of the barcodes and the dynamics of cell labeling. Furthermore, we developed computational methods for lineage tree reconstruction based on this data. In summary, we now have a method that allows simultaneous cell type identification and lineage tracing in thousands of single cells. We continued to further improve the experimental technology throughout the funding period (manuscript in preparation).
In WP3, we used high-throughput lineage tracing to systematically identify the origin of transient cell types in the adult zebrafish heart that arise during regeneration after injury. By combining this data with functional experiments for targeted cell type depletion, we identified the origin and function of a transient population of pro-regenerative fibroblasts (Hu et al., Nat Genet, 2022). This work included improved computational analysis of high-throughput lineage data (compared to our earlier publication from WP2) as well as spatial transcriptomics analysis of the heart using tomo-seq.
