Following injuries such as cardiomyopathy, the heart tends to experience an increased in sympathetic tone. This can lead to aberrant electrical activities and elevate the patient’s risk of developing future dangerous cardiac arrhythmias. While blocking the connection between stellate ganglia and the heart helps mitigate these risks, it is unknown how heart injury changes the biology of these ganglia to produce this elevation in sympathetic activity. In this project, we used single cell RNA sequencing (scRNAseq) to study the composition the stellate ganglia of six C57BL/6J (wild-type) mice, more particularly its fibroblasts. Fibroblasts were identified via the expression of Lum and Smoc2. Through unsupervised clustering, six sub-populations were obtained. Two of these clusters were excluded from further analysis because they expressed high levels of either (1) pro-inflammatory genes (e.g., Ifit3), or (2) markers of other cell types (i.e., Dbi/Plp1 for glial cells). Then, after in-depth analysis of genetic markers, we identified the remaining clusters as “Immature”, “Activating”, “Active”, and “Neurons-Interacting” fibroblasts. The “Neurons-Interacting” cluster was subsequently excluded as it needed to be further studied. Finally, we verified our findings with unbiased pseudotime analysis, which yielded a trajectory that traveled from “Immature” to “Activating” to “Active” sub-populations. Moving forward, we plan to compare these clusters with those obtained from heart-failure mice, as we aimed to elucidate a possible mechanism for how heart injury leads to an increase in sympathetic input from the stellate ganglia to the heart.