Dataset related to article "Single-Cell and Single-Nucleus Multiomics Reveal Cardiac Endothelial Cell Heterogeneity and Novel Pathological Processes in Pressure Overload-Induced Hypertrophy"

This record contains raw data related to article “Single-Cell and Single-Nucleus Multiomics Reveal Cardiac Endothelial Cell Heterogeneity and Novel Pathological Processes in Pressure Overload-Induced Hypertrophy" Endothelial cells, the most prevalent cellular population in the heart, line the internal walls of coronary and lymphatic vessels and form the endocardium and cardiac valves. The heterogeneity of cardiac endothelium poses a challenge in fully understanding endothelial states. However, to better grasp the plasticity of endothelial cell phenotypes, it's crucial to distinguish the varied responses of endothelial populations to physiological and pathological stimuli. Endothelial dysfunction plays a significant role in the development and progression of heart failure, a condition impacting millions globally. For the heart to sustain pressure-overload-induced remodelling, endothelial cells must proliferate and generate new blood vessels. When cardiomyocyte hypertrophy and angiogenesis become uncoupled, it leads to decompensated heart failure. Despite this, the molecular mechanisms governing cardiac vascularization during pathological hypertrophy remain unclear. Transcriptional phenotyping methods have been widely used to capture endothelial cell plasticity and heterogeneity. However, only single-cell profiling has effectively resolved distinct phenotypes. While single-cell RNA sequencing can create detailed cellular maps and cell-to-cell communication networks, it does not fully elucidate how gene regulatory programs are established or how cell states, functions, and responses are specified. To address these gaps, multimodal omics approaches have been developed, allowing for simultaneous profiling of chromatin accessibility and gene expression within the same cell. In our study, we aimed to characterize the transcriptional and epigenetic profiles of cardiac endothelial cells in a mouse model of pressure-overload-induced hypertrophy using multiomics bioinformatic approaches at single-cell resolution. This innovative technology enabled us to uncover the regulatory mechanisms that drive endothelial cell sub-population specifications following banding. Our resulting atlas is intended to serve as a valuable reference and resource for future studies and the development of therapeutic strategies targeting endothelial cells in cardiovascular diseases.本数据集包含与论文《单细胞与单细胞核多组学（Single-Cell and Single-Nucleus Multiomics）揭示压力负荷诱导型肥厚中心脏内皮细胞异质性与新型病理过程》相关的原始数据。 内皮细胞是心脏中分布最为广泛的细胞群，衬贴于冠状动脉与淋巴管内壁，并构成心内膜与心脏瓣膜。心脏内皮细胞的异质性给全面解析内皮细胞状态带来了显著挑战。若要更好地理解内皮细胞表型的可塑性，关键在于区分不同内皮亚群对生理与病理刺激的差异化应答。内皮功能异常在心力衰竭的发生与进展中发挥关键作用，该疾病在全球范围内影响数百万人群。为维持压力负荷诱导的心脏重构，内皮细胞需要增殖并生成新生血管。当心肌细胞肥厚与血管生成发生解偶联时，会引发失代偿性心力衰竭。尽管如此，病理性肥厚过程中调控心脏血管生成的分子机制仍未明确。 转录组表型分析方法已被广泛用于解析内皮细胞的可塑性与异质性，但唯有单细胞分析（single-cell profiling）可有效区分不同的细胞表型。单细胞RNA测序（single-cell RNA sequencing）能够构建精细的细胞图谱与细胞间通讯网络，但无法完全阐明基因调控程序的建立机制，以及细胞状态、功能与应答的调控逻辑。为填补这一研究空白，多组学（multiomics）分析技术应运而生，可实现在单个细胞内同时检测染色质开放状态与基因表达水平。 本研究旨在通过单细胞分辨率的多组学生物信息学分析方法，对压力负荷诱导型肥厚小鼠模型中的心脏内皮细胞转录组与表观基因组特征进行解析。这项创新性技术帮助我们揭示了主动脉结扎造模后驱动内皮细胞亚群特化的调控机制。本研究构建的心脏内皮细胞图谱，可为未来心血管疾病内皮细胞靶向治疗策略的开发与相关研究提供极具价值的参考资源。