bioRxiv2026
Obtaining transcriptomes of adult cardiomyocytes at single-cell resolution remains challenging due to their large size, elongated morphology, and frequent multinucleation. Although spatial transcriptomics preserves tissue architecture and captures gene expression in situ, current analytical frameworks largely rely on nuclear-based segmentation and are therefore poorly suited to adult cardiomyocytes. Furthermore, individual tissue sections capture only a fraction of a cardiomyocyte, preventing reconstruction of complete cell-level transcriptomes. Here we present three-dimensional virtual cardiomyocyte (3D-VirtualCM), a membrane-guided framework that integrates cell-contour similarity and optimal transport to reconstruct volumetric cardiomyocyte transcriptomes from consecutive spatial transcriptomic sections. Applying 3D-VirtualCM to infarcted adult mouse hearts, we generated a panoramic transcriptomic atlas spanning 100 m thickness at single-cell resolution. 3D-VirtualCM identified spatially and transcriptionally distinct cardiomyocyte populations within the infarct border zone, enabled high-throughput quantification of cardiomyocytes re-entering the cell cycle together with their associated molecular signatures, and revealed heterogeneous RNA distribution along the longitudinal axis of individual cardiomyocytes. By integrating three-dimensional cellular morphology with in situ transcriptomic data, 3D-VirtualCM provides a scalable approach for resolving cardiomyocyte states and spatial organization in physiological and pathological cardiac remodeling.