High-content phenotyping reveals Golgi dynamics and their role in cell cycle regulation

Recent advances in quantitative bioimage analysis have enabled detailed analyses of cellular and subcellular morphological features, enhancing our understanding of cellular functions. Here, we introduce an image-based phenotyping pipeline designed for the comprehensive analysis of dynamic organelle morphology, particularly the Golgi apparatus and cilia, during cell cycle progression. Our approach emphasizes interpretable feature extraction, enabling detection of both prominent and subtle morphological changes. By using well-characterized morphological dynamics of intracellular structures as benchmarks, we demonstrated that our method can reliably detect established phenotypic changes and serves as a valid tool for quantitative profiling. Further investigation of the G0/G1 transition revealed an unexplored link between Golgi dynamics and ciliary disassembly. Specifically, inhibition of the G0/G1 transition correlated with ciliary persistence and unique Golgi dispersion, involving Aurora ..., , , # Data from: High-content phenotyping reveals Golgi dynamics and their role in cell cycle regulation

Dataset DOI: [10.5061/dryad.8gtht771s](https://doi.org/10.5061/dryad.8gtht771s)

#### Description of the data and file structure

This dataset accompanies our study investigating the dynamic morphological changes of cellular structures, including the Golgi apparatus and cilia, during the cell cycle, using image-based high-content phenotyping. These files include the uncropped immunofluorescence (IF) image and Western blot (WB) data, cell profile data, and Python code, used for analysis of cell morphological features and figure generation, as described in **Cao, Peng, Yang et al., J Cell Biol, 2025**. The files also include the cell phenotypic profile datasets generated in this article.

For detailed instructions on running the code, reproducing analyses, and understanding the file structure with schematic diagrams, please refer to `Readme.pdf`.

The image data and code are organized acc...