A time- and single-cell-resolved model of murine bone marrow hematopoiesis

Data, source code, singularity container, extended figures and tables for the article: "A time- and single-cell-resolved model of murine bone marrow hematopoiesis"

The paradigmatic hematopoietic tree model is increasingly recognized to be limited as it is based on heterogeneous populations and largely inferred from non-homeostatic cell fate assays. Here, we combine persistent labeling with time-series single-cell RNA-Seq to build a real-time, quantitative model of in vivo tissue dynamics for murine bone marrow hematopoiesis. We couple cascading single-cell expression patterns with dynamic changes in differentiation and growth speeds. The resulting explicit linkage between molecular states and cellular behavior reveals widely varying self-renewal and differentiation properties across distinct lineages. Transplanted stem cells show strong acceleration of differentiation at specific stages of erythroid and neutrophil production, illustrating how the new model can quantify the impact of perturbations. Our reconstruction of dynamic behavior from snapshot measurements is akin to how a kinetoscope allows sequential images to merge into a movie. We posit that this approach is generally applicable to understanding tissue scale dynamics at high resolution.

本数据集配套文章《小鼠骨髓造血的时间与单细胞分辨率模型》（A time- and single-cell-resolved model of murine bone marrow hematopoiesis）的相关数据、源代码、Singularity容器（Singularity Container）及扩展图表。经典造血树模型（paradigmatic hematopoietic tree model）因基于异质性细胞群体，且大多由非稳态细胞命运测定实验推导而来，其局限性日益凸显。本研究将持续性标记技术与时序单细胞RNA测序（time-series single-cell RNA-Seq）相结合，构建了小鼠骨髓造血的体内组织动力学实时定量模型。本研究将级联式单细胞表达谱与分化、增殖速度的动态变化相结合，由此建立的分子状态与细胞行为间的明确关联，揭示了不同细胞谱系间自我更新与分化特性的显著差异。移植干细胞在红系与中性粒细胞生成的特定阶段展现出分化速度的显著提升，该结果阐明了新模型可量化实验扰动所带来的影响。本研究从静态采样数据中重构动态行为的过程，恰似活动电影放映机（Kinetoscope）将连续帧图像合成为动态影片。我们认为该方法可广泛应用于高分辨率解析组织尺度的动态过程。