Shen Xunan, Zuo Lulu, Ye Zhongfei, Yuan Zhongyang, Huang Ke, Li Zeyu, Yu Qichao, Zou Xuanxuan, Wei Xiaoyu, Xu Ping, Deng Yaqi, Jin Xin, Xu Xun, Wu Liang, Zhu Hongmei, Qin Pengfei
BGI Research, Chongqing 401329, China; BGI Research, Beijing 102601, China.
BGI, Tianjin 300308, China.
Cell Syst. 2025 Feb 19;16(2):101194. doi: 10.1016/j.cels.2025.101194. Epub 2025 Feb 3.
The integration of cell transcriptomics and spatial position to organize differentiation trajectories remains a challenge. Here, we introduce SpaTrack, which leverages optimal transport to reconcile both gene expression and spatial position from spatial transcriptomics into the transition costs, thereby reconstructing cell differentiation. SpaTrack can construct detailed spatial trajectories that reflect the differentiation topology and trace cell dynamics across multiple samples over temporal intervals. To capture the dynamic drivers of differentiation, SpaTrack models cell fate as a function of expression profiles influenced by transcription factors over time. By applying SpaTrack, we successfully disentangle spatiotemporal trajectories of axolotl telencephalon regeneration and mouse midbrain development. Diverse malignant lineages expanding within a primary tumor are uncovered. One lineage, characterized by upregulated epithelial mesenchymal transition, implants at the metastatic site and subsequently colonizes to form a secondary tumor. Overall, SpaTrack efficiently advances trajectory inference from spatial transcriptomics, providing valuable insights into differentiation processes.
整合细胞转录组学和空间位置以组织分化轨迹仍然是一项挑战。在此，我们介绍SpaTrack，它利用最优传输将空间转录组学中的基因表达和空间位置协调到过渡成本中，从而重建细胞分化。SpaTrack可以构建反映分化拓扑结构的详细空间轨迹，并追踪多个样本在时间间隔内的细胞动态。为了捕捉分化的动态驱动因素，SpaTrack将细胞命运建模为受转录因子随时间影响的表达谱的函数。通过应用SpaTrack，我们成功地解开了蝾螈端脑再生和小鼠中脑发育的时空轨迹。揭示了在原发性肿瘤内扩展的多种恶性谱系。其中一个谱系以上皮-间质转化上调为特征，植入转移部位，随后定植形成继发性肿瘤。总体而言，SpaTrack有效地推进了从空间转录组学进行的轨迹推断，为分化过程提供了有价值的见解。
