德国计算生物学研究所法比安·泰斯研究组报道了CellRank 2——利用多视图映射单细胞图谱揭示细胞统一命运。该项研究成果发表在2024年6月13日出版的《自然-方法学》上。

研究人员研发了CellRank 2，这是一种多功能、可扩展的协议，可统一使用数百万个细胞的多视角单细胞数据研究细胞命运。CellRank 2能持续恢复人造血和内胚层发育过程中各种数据模式的终末状态和命运决定。该方法还能结合实验时间点内和实验时间点间的转变，研究人员利用这一特点恢复了咽内胚层发育过程中调控髓质胸腺上皮细胞形成的基因。

此外，研究人员还能从代谢标记数据中估算细胞特异性转录和降解速率，并将其应用于肠道类器官系统，以确定分化轨迹并精确揭示调控策略。

据介绍，通过单细胞RNA测序，人们可以利用表达相似性或RNA转录速率建立细胞动态和命运决定模型，从而重建状态变化轨迹；然而，轨迹推断并不包涵有价值的时间点信息，也没有利用额外的模式，而解决这些不同数据视图的方法无法合并或无法扩展。

附：英文原文

Title: CellRank 2: unified fate mapping in multiview single-cell data

Author: Weiler, Philipp, Lange, Marius, Klein, Michal, Peer, Dana, Theis, Fabian

Issue&Volume: 2024-06-13

Abstract: Single-cell RNA sequencing allows us to model cellular state dynamics and fate decisions using expression similarity or RNA velocity to reconstruct state-change trajectories; however, trajectory inference does not incorporate valuable time point information or utilize additional modalities, whereas methods that address these different data views cannot be combined or do not scale. Here we present CellRank 2, a versatile and scalable framework to study cellular fate using multiview single-cell data of up to millions of cells in a unified fashion. CellRank 2 consistently recovers terminal states and fate probabilities across data modalities in human hematopoiesis and endodermal development. Our framework also allows combining transitions within and across experimental time points, a feature we use to recover genes promoting medullary thymic epithelial cell formation during pharyngeal endoderm development. Moreover, we enable estimating cell-specific transcription and degradation rates from metabolic-labeling data, which we apply to an intestinal organoid system to delineate differentiation trajectories and pinpoint regulatory strategies.

DOI: 10.1038/s41592-024-02303-9

Source: https://www.nature.com/articles/s41592-024-02303-9