Periodic Reporting for period 4 - SPACEVAR (Quantitative analysis of variability and robustness in spatial pattern formation)
Reporting period: 2021-07-01 to 2022-12-31
The zebrafish heart is a powerful model system for studying variability, since heart positioning is inverted along the left/right axis in 5-10% of wildtype embryos. Here, we combined light microscopy and gene expression analysis to reveal the mechanisms and principles underlying variability in heart positioning. To expand our study of embryo-to-embryo variability, we further developed a method for high-throughput single-cell lineage tracing based on CRISPR-Cas9. This novel approach allows us to study embryo-to-embryo variability in developmental lineage specification systematically and on a massively parallel level. Finally, we used this strategy to explore the regenerative capacity of the zebrafish heart upon injury, which allowed us to reveal the origin and function of pro-regenerative fibroblasts. In summary, these quantitative experiments provided unprecedented insights into variability and robustness during development as well as regeneration of adult organs upon injury.
The concepts developed here can help us understand variable outcomes in human genetic disease, and one of our long-term goals is to develop strategies for regenerative therapies in humans. Furthermore, the methods established in this project will be useful for understanding mechanisms of disease in a broad range of systems.
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.
In WP2, we developed a method for high-throughput lineage tracing (Spanjaard et al., Nat Biotech, 2018), which allows to identify the lineage origin of thousands of single cells from the same animal. Together with several other papers, this manuscript was selected by Science as the "Breakthrough of the Year 2018". We continue to improve this method on the experimental and computational level by e.g. introducing additional barcodes, extending the period of lineage recording, optimizing barcode recovery during single-cell RNA-seq, and by improving algorithms for lineage tree reconstruction.
In WP3, we studied how the zebrafish heart reacts to injury, by focusing on understanding the origin of transient cell types that arise during regeneration in the adult heart. We identified the origin and function of a previously uncharacterized population of pro-regenerative fibroblasts (Hu et al., Nat Genet, 2022) by combining the methodology developed in WP2 with functional experiments for targeted cell type depletion.