使用潜伏动态系统和时间解析的转录学来重建发育轨迹
Rory J Maizels1, Daniel M Snell2, James Briscoe2
1The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK; University College, London, UK.
Cell systems
|May 16, 2024
概括
我们开发了sci-FATE2用于代谢标记和计算工具 (VelvetVAE,VelvetSDE),以建模细胞命运动态. 该框架增强了使用单细胞转录组学数据的发育过程的理解.
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:
- 单细胞转录学提供了细胞状态的快照,限制了像细胞命运决定这样的动态过程的研究.
- 现有的时间推断方法,如代谢标记和拼接分析,具有固有的局限性.
- 了解细胞命运动态对于发育生物学和再生医学至关重要.
研究的目的:
- 开发一个集成的实验和计算框架,用于高分辨率的动态建模细胞命运决策.
- 提高单细胞数据的质量和时间分辨率,以研究分化.
- 创建强大的计算工具来推断和模拟细胞轨迹.
主要方法:
- 开发了sci-FATE2,一种优化的代谢标记技术,以提高单细胞RNA测序数据质量.
- 应用VelvetVAE,一个变异性自编码器,用于准确的基因表达速度推断.
- 利用VelvetSDE,一个神经随机微分方程模型,模拟细胞轨迹分布.
主要成果:
- 通过使用sci-FATE2.2,对45,000个胚胎干细胞进行了分析,使其分化为神经管身份.
- 与现有工具相比,VelvetVAE在速度推断方面表现出优异的性能.
- VelvetSDE成功地回顾了数据集分布,捕捉了命运决策边界和基因表达动态.
结论:
- 开发的框架将单细胞分析从静态描述转变为生物过程的动态模型.
- 这种方法为研究发展细胞命运决定背后的复杂机制提供了强大的工具.
- 改进的实验方法和先进的计算建模的整合为研究细胞动态开辟了新的途径.
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