从空间转录组数据推断拓速度推断
Yichen Gu1, Jialin Liu2, Kun H Lee2
1Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, USA.
Nature biotechnology
|July 16, 2025
概括
本研究介绍了拓速度推理 (TopoVelo),这是一个新的模型,用于分析组织中的细胞命运过渡,使用空间转录基因数据. TopoVelo揭示了细胞相互作用和空间动态如何驱动组织发育和分化.
科学领域:
- 发展生物学 发展生物学
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 了解组织发育需要整合细胞命运转变的空间和时间动态.
- 细胞与细胞的相互作用,利基因素和迁移是组织形态发生的关键驱动因素.
- 当前的模型往往缺乏空间分辨率来捕捉这些复杂的动态.
研究的目的:
- 开发一个计算框架,拓速度推断 (TopoVelo),以共同推断空间和时间细胞命运动态.
- 将TopoVelo应用于空间转录基因数据,用于分析组织发育和细胞分化.
- 为模拟发育组织中的集体细胞行为提供基础.
主要方法:
- 扩展RNA速度框架使用空间合微分方程来建模单细胞基因表达动态.
- 从空间转录基因数据中估计细胞速度,特别是从正在发育的小鼠大脑皮层.
- 从体外人类发育模型中生成和分析幻灯片序列数据.
主要成果:
- TopoVelo成功地从空间转录基因数据中推断出空间和时间细胞命运动态.
- 该模型识别了可解释的空间细胞状态依赖关系,与配体受体基因表达相关.
- 揭示了小鼠神经管关闭的空间特征和早期人类差异化的空间模式.
结论:
- TopoVelo提供了一种新的方法,将空间和时间维度纳入细胞命运过渡建模中.
- 该框架促进了人们对局部细胞相互作用和组织范围内的动态如何促进发育的理解.
- 这项工作为未来研究复杂组织中细胞的集体动态奠定了基础.
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