With cell cycle phase and other ZGA-associated factors measured in our dataset, we show that this heterogeneity does not arise from stochastic fluctuations and that we can predict the transcriptional activity of individual cells with high accuracy, linking cellular state and transcriptional output.

Since cell cycle plays a key role in transcriptional activity, we developed a computational pipeline to infer cell cycle phase directly from our multiplexed imaging datasets of fixed embryos. 🤩

Using 3D-4i, we can visualize multiple protein and protein-state markers causally linked to regulating this process, both at single-cell level and across all embryos.

We applied 3D-4i to study the process of zygotic genome activation (ZGA), the stage where the embryo’s own genome takes control of development, which is highly heterogeneous at the single-cell level. 🤔

Very happy to share our latest work extending iterative immunofluorescence to in toto imaging of early zebrafish embryos (3D-4i), integrated with a 3D-dedicated image analysis pipeline! 🐟🔬📊
Huge kudos to Max Hess for this PhD milestone! 💪
@lucaspelkmans.bsky.social shorturl.at/cO0u7
Let's zoom in!

With cell cycle phase and other ZGA-associated factors measured in our dataset, we show that this heterogeneity does not arise from stochastic fluctuations and that we can predict the transcriptional activity of individual cells with high accuracy, linking cellular state and transcriptional output.

Since cell cycle plays a key role in transcriptional activity, we developed a computational pipeline to infer cell cycle phase directly from our multiplexed imaging datasets of fixed embryos. 🤩

Using 3D-4i, we can visualize multiple protein and protein-state markers causally linked to regulating this process, both at single-cell level and across all embryos.

We applied 3D-4i to study the process of zygotic genome activation (ZGA), the stage where the embryo’s own genome takes control of development, which is highly heterogeneous at the single-cell level. 🤔

With cell cycle phase and other ZGA-associated factors measured in our dataset, we show that this heterogeneity does not arise from stochastic fluctuations & that we can predict the transcriptional activity of individual cells with high accuracy, linking cellular state and transcriptional output.

Since the cell cycle plays a major role in transcriptional activity, Max developed a computational pipeline to infer cell cycle phase directly from our multiplexed imaging datasets of fixed embryos 🤩

📣 Symposium 2050 at the University of Zurich

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