Temporal Analysis of Embryonic Epidermal Morphogenesis in Caenorhabditis elegans

The development of epidermis plays a central role in driving the morphogenesis of the <i>Caenorhabditis elegans</i> embryo. However, current research on epidermal morphogenesis focuses disproportionately on overt phenotypic abnormalities, potentially overlooking the crucial role of developmental timing. In this study, we developed a modular two-step deep learning-based image analysis pipeline. First, we used ResU-Net to extract completely developed embryos and suppress noise; second, ResNet was used to predict the corresponding embryonic stage. The predicted probabilities and their corresponding embryonic time points were subsequently utilized to construct a developmental timeline. Combining this pipeline with differential interference contrast time-lapse microscopy, we dynamically tracked the timeline of epidermal morphogenesis in RNAi-treated embryos (<i>ajm-1</i>, <i>tes-1</i>, <i>leo-1</i>) and mutant embryos (<i>clk-1</i>). By statistically comparing the duration of each embryonic stage, our approach enabled the detection of stage-specific developmental timing without relying on overt phenotypic abnormalities or fluorescent markers, successfully recapitulating and extending the known roles of these genes from a temporal perspective. Our work underscores the importance of incorporating developmental timing into morphogenetic analysis, offering a novel framework for revealing subtle developmental processes, deepening the understanding of morphogenetic dynamics, and bridging the methodological gap in <i>C. elegans</i> embryology.