Gene expression dynamics in wound healing: Comparative analysis between the wound edge and center

Abstract

Wound healing is a dynamic and spatially heterogeneous process involving coordinated activity across multiple cell types. We analyze a high-resolution porcine wound-healing transcriptomic dataset of 150 samples from wound edges and centers collected across 15 time points (days 0–21). Using correlation-based clustering and gene ontology analysis, we identify major groups of synchronously expressed genes representing immune activity, extracellular matrix (ECM) remodeling, epithelial repair and several tissue-specific clusters. Immune clusters peak on days 1–6 and are consistently higher at the wound center. ECM clusters show early suppression followed by gradual activation in both regions. Epithelial clusters remain high at the wound edge but show a day-1 drop and gradual recovery at the center. Additional hair, muscle and lipid clusters display abrupt, non-smooth patterns driven by sample heterogeneity. A low-dimensional projection of cluster means reveals a “round-trip” healing trajectory in immune–epithelial space. This analysis provides a transcriptomic reference for acute wound healing and highlights the importance of sampling precision in wound transcriptomics.