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Updated: Jan 6, 2026
Author Spotlight: Manipulating Signaling in Zebrafish Embryos to Decode Cell Fate Decisions
Published on: October 27, 2023
Disrupted developmental signaling induces novel transcriptional states
Aleena L Patel1,2, Vanessa Gonzalez3, Triveni Menon3,4
1Department of Developmental Biology, Stanford University, Stanford, CA 94305.
Abstract:
Signaling pathways induce stereotyped transcriptional changes as stem cells progress into mature cell types during embryogenesis. Signaling perturbations are necessary to discover which genes are responsive or insensitive to pathway activity. However, gene regulation is additionally dependent on cell state-specific factors like chromatin modifications or transcription factor binding. Thus, transcriptional profiles need to be assayed in single cells to identify potentially multiple, distinct perturbation responses among heterogeneous cell states in an embryo. In perturbation studies, comparing heterogeneous transcriptional states among experimental conditions often requires samples to be collected over multiple independent experiments, which can introduce confounding batch effects. We present Design-Aware Integration of Single Cell ExpEriments (DAISEE), a new algorithm that models perturbation responses in single-cell datasets collected according to complex experimental designs. We demonstrate that DAISEE improves upon a previously available integrative nonnegative matrix factorization framework, more efficiently separating perturbation responses from confounding variation. We use DAISEE to integrate newly collected single-cell RNA sequencing datasets from 5-h-old zebrafish embryos expressing optimized photoswitchable MEK (psMEK), which globally activates the extracellular signal-regulated kinase (ERK), a signaling molecule involved in many cell specification events. psMEK drives some cells that are normally not exposed to ERK signals toward other wild type states and induces novel states expressing early-acting endothelial genes. Overactive signaling is therefore capable of producing unexpected gene expression states in developing embryos.
Insights
This study introduces DAISEE, a new algorithm for analyzing single-cell RNA sequencing data from complex experiments. DAISEE effectively separates signaling pathway responses from batch effects in developing zebrafish embryos.
Area of Science:
- Developmental Biology
- Systems Biology
- Genomics
Background:
- Cellular differentiation during embryogenesis involves complex signaling pathways and transcriptional changes.
- Understanding gene responses to signaling requires single-cell resolution due to cell state heterogeneity.
- Experimental batch effects can confound the analysis of single-cell transcriptomic data.
Purpose of the Study:
- To develop a novel algorithm, DAISEE, for integrating single-cell RNA sequencing datasets from complex experimental designs.
- To accurately model and separate perturbation responses from confounding variations in single-cell data.
- To investigate the effects of activating the extracellular signal-regulated kinase (ERK) pathway on zebrafish embryogenesis.
Main Methods:
- Development of the Design-Aware Integration of Single Cell ExpEriments (DAISEE) algorithm.
- Application of DAISEE to integrate single-cell RNA sequencing data from zebrafish embryos.
- Utilizing photoswitchable MEK (psMEK) to globally activate the ERK pathway in zebrafish embryos.
- Comparison of DAISEE with existing integrative nonnegative matrix factorization methods.
Main Results:
- DAISEE effectively models perturbation responses in complex single-cell experimental designs.
- The algorithm demonstrates improved separation of perturbation responses from confounding variation compared to previous methods.
- Activation of the ERK pathway in zebrafish embryos induced novel cell states and altered gene expression, including early-acting endothelial genes.
- Some cells exposed to ERK signals shifted toward wild-type states.
Conclusions:
- DAISEE provides a robust framework for analyzing perturbed single-cell transcriptomic data from complex experiments.
- Overactive signaling pathways, such as ERK, can lead to unexpected gene expression states and cell phenotypes during embryonic development.
- Single-cell analysis is crucial for dissecting heterogeneous responses to signaling perturbations in vivo.
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