Abstract
Heart development involves dynamic signaling interactions between cells and their surrounding environment (niche). Single-cell mRNA sequencing (scRNA-seq) has been widely used to profile gene expression in individual cells, but it faces challenges in dissecting niche signals due to the need for cell dissociation. In contrast, spatial transcriptomics can preserve tissue structure and represents a potentially effective approach for this purpose. In this study, we used two spatial transcriptomics platforms, 10x Genomics Visium and Curio Slide-seq (Curio Seeker), to generate a spatial atlas of hearts at embryonic and neonatal stages. Using Visium data, we analyzed the spatial patterns of cell cycle phases, compact and trabecular myocardium signatures, and chamber-specific genes across developmental progression. We discovered that atrial cardiomyocytes exhibit a mature myocardium transcriptional signature. Additionally, we identified the spatial patterns of signaling activities at different stages. Using Slide-seq data, we identified cardiac conduction cells, including cardiac neurons, sinoatrial nodal cells, atrioventricular nodal cells, and Purkinje fiber cells, and further studied their niche signaling. Moreover, by combining lineage tracing and spatial transcriptomics, we identified four types of epicardial cell-derived cells (EPDCs) and analyzed their signaling interactions with niche cells. We then eliminated the EPDCs using a cell ablation system and observed reduced signaling in the ablated hearts through spatial transcriptomics analysis. In summary, we generated a spatial transcriptomic atlas for developing mouse hearts and identified niche signaling for cardiac conduction cells and EPDCs.
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Acknowledgements
We’d like to thank all the members in the Li laboratory for their insightful discussions of this work and thank Dr. Zibei Gao for her help in staining Pdgfra on heart sections. We are also thankful to the Health Sciences Sequencing Core at UPMC Children’s Hospital of Pittsburgh, Rangos Research Center (RRID:SCR_023116) for their assistance in processing the Visium samples. We are also grateful to the Center for Biologic Imaging (CBI) at the University of Pittsburgh for their support in imaging the stained samples. This research was supported in part by the University of Pittsburgh Center for Research Computing, RRID:SCR_022735, through the resources provided. Specifically, this work used the HTC cluster, which is supported by NIH award number S10OD028483.
Funding
This work was supported by R00HL133472 and DP2HL163745 from the NIH, Additional Ventures SVRF grant 1291906, and the CMRF grant from the University of Pittsburgh (G.L.). It was also supported in part by P01AI106684 and NSF2225775 (W.C.).
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Hu, J., He, H., Xu, J. et al. Spatial transcriptomic profiling of developing mouse hearts reveals a spatially patterned signaling environment. Commun Biol (2026). https://doi.org/10.1038/s42003-026-10259-z
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DOI: https://doi.org/10.1038/s42003-026-10259-z
