Telethon Institute of Genetics and Medicine (TIGEM), Armenise/Harvard Laboratory of Integrative Genomics, Pozzuoli, Italy; Department of Translational Medicine, University of Naples Federico II, Naples, Italy; The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Molecular & Cellular Biology Program, University of Washington, Seattle, WA, USA; Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Cell Syst. 2018 Sep 26;7(3):258-268.e3. doi: 10.1016/j.cels.2018.07.006. Epub 2018 Sep 5.
Cellular reprogramming through manipulation of defined factors holds great promise for large-scale production of cell types needed for use in therapy and for revealing principles of gene regulation. However, most reprogramming systems are inefficient, converting only a fraction of cells to the desired state. Here, we analyze MYOD-mediated reprogramming of human fibroblasts to myotubes, a well-characterized model system for direct conversion by defined factors, at pseudotemporal resolution using single-cell RNA-seq. To expose barriers to efficient conversion, we introduce a novel analytic technique, trajectory alignment, which enables quantitative comparison of gene expression kinetics across two biological processes. Reprogrammed cells navigate a trajectory with branch points that correspond to two alternative decision points, with cells that select incorrect branches terminating at aberrant or incomplete reprogramming outcomes. Analysis of these branch points revealed insulin and BMP signaling as crucial molecular determinants of reprogramming. Single-cell trajectory alignment enables rigorous quantitative comparisons between biological trajectories found in diverse processes in development, reprogramming, and other contexts.
通过操纵定义因子进行细胞重编程为治疗中所需的细胞类型的大规模生产以及揭示基因调控原则提供了巨大的前景。然而,大多数重编程系统效率低下,只能将一小部分细胞转化为所需状态。在这里,我们使用单细胞 RNA-seq 以拟时间分辨率分析 MYOD 介导的人成纤维细胞向肌管的重编程,这是通过定义因子进行直接转化的一个很好的模型系统。为了揭示高效转化的障碍,我们引入了一种新的分析技术——轨迹对齐,它能够在两个生物过程之间进行基因表达动力学的定量比较。重编程细胞沿着具有分支点的轨迹导航,这些分支点对应于两个替代决策点,选择错误分支的细胞终止于异常或不完全的重编程结果。对这些分支点的分析表明,胰岛素和 BMP 信号是重编程的关键分子决定因素。单细胞轨迹对齐能够在不同发育、重编程和其他背景下的生物轨迹之间进行严格的定量比较。