Myocardial infarction, a leading cause of human death according to World Health Organization data, results in a permanent fibrotic scar in the heart. In contrast, zebrafish hearts can regenerate throughout their lifetime, providing opportunities for novel target identification for potential therapies. Although previous studies have identified the cell types involved in this process, the mechanisms of their intercellular communications remain elusive.

To address this knowledge gap, we reanalyzed transcriptomic data from three studies, focusing on key cell types, and constructed a ligand-receptor network based on differentially expressed genes. Utilizing transcriptomic changes, network theory, and literature-based natural language processing, we identified crucial nodes in the network and created a ranked list of genes regulating the regeneration process.

Currently, we are validating our results using CRISPR Cas9-based knockout lines. We present our findings through a user-friendly Shiny app interface, enhancing accessibility. This app allows users to delve into various aspects of the network for deeper insights. Each node provides information on differential ligand receptors, gene expression fold changes, and interacting partners. The ranking table details the gene, its orthologues, synonyms, and the scores that contributed to its rank. The ranking can also be visualized through an interactive graph, highlighting the contribution of each parameter to the total score. Moreover, the option to visualize the data in a scatter plot offers insights into targets based on literature.

The user-friendly interface, with its interactive features for data exploration, provides researchers with freedom and independence in target identification, facilitating heart regeneration research across species.