bioRxivDevelopmental BiologyPreprint
Morphodynamic domains enable integration of live morphometrics and spatial transcriptomics
Adrien LeroyiD, Eric van LeeniD, Maria Balakireva, Lale AlpariD, Fabian GärtneriD, Isabelle GauguéiD, Stéphane PelletieriD, Rémi PigacheiD, Mehdi Ech-Chouini, Julien DelpierreiD, Stéphane U. RigaudiD, Floris BosveldiD, Lorette Noiret, Yohanns Bellaı̈cheiD
Abstract
Tissue development emerges from the coordinated behaviors of thousands of cells, orchestrated by gene regulatory networks. Recent methodological advances now enable high-resolution live imaging of cell- and tissue-scale dynamics and the construction of spatially resolved gene expression atlases. However, quantitatively linking these modalities remains a central challenge, limiting our ability to understand how gene regulatory networks drive cell- and tissue-scale behaviors. Here, using the Drosophila thorax epithelium as a model system, we introduce an analytical and computational framework based on tissue morphodynamic domains: regions defined by coherent cell and tissue dynamics extracted from live imaging morphometrics. Integrating morphodynamic domains with spatial transcriptomics enables the inference of gene regulatory networks associated with distinct spatial cell- and tissue-level behaviors. Statistical cross-scale analyses further allow the interrogation and validation of gene function, confirming or revealing regulators of specific morphogenetic dynamics. In particular, our framework uncovers a role for the Toll-like receptor Tollo in modulating tissue flow, contraction, and apoptosis. Together, our work establishes a framework that integrates spatial transcriptomics with quantitative, multiscale live morphometrics, providing a generalizable strategy to probe and understand developmental processes.
- organism: Drosophila
- assay: spatial transcriptomics
- assay: imaging
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Morphodynamic Atlas for Drosophila Development
Noah Mitchell, Matthew F Lefebvre, … Sebastian J. Streichan·bioRxiv·May 26, 2022
- Spateo: multidimensional spatiotemporal modeling of single-cell spatial transcriptomics
Xiaojie Qiu, Daniel Y. Zhu, … Yinqi Bai·bioRxiv·Dec 7, 2022
- Spatial Modeling of Tissues for Morphogenic Field Analysis
Aaron E. Osgood-Zimmerman, Micha Sam Brickman Raredon·bioRxiv·Dec 10, 2025
- MorphoGraphX 2.0: Providing context for biological image analysis with positional information
Soeren Strauss, Adam Runions, … Richard S. Smith·eLifePeer-reviewed·May 5, 2022
- High-resolution spatiotemporal transcriptomic maps of developing Drosophila embryos and larvae
Mingyue Wang, Qinan Hu, … Longqi Liu·bioRxiv·Oct 21, 2021
- A Computational Framework for Extracting Mechanistic Hypotheses from Quantitative Data of Morphological Dynamics
Koji Kyoda, Hatsumi Okada, Shuichi Onami·bioRxiv·Jun 15, 2026