单细胞轨迹的基因水平配准

IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Nature Methods Pub Date : 2024-09-19 DOI:10.1038/s41592-024-02378-4
Dinithi Sumanaweera, Chenqu Suo, Ana-Maria Cujba, Daniele Muraro, Emma Dann, Krzysztof Polanski, Alexander S. Steemers, Woochan Lee, Amanda J. Oliver, Jong-Eun Park, Kerstin B. Meyer, Bianca Dumitrascu, Sarah A. Teichmann
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摘要

单细胞数据分析可以推断细胞群的动态变化,例如跨时间、跨空间或对扰动的反应,从而得出伪时间轨迹。目前比较轨迹的方法通常使用动态编程,但受到存在确定匹配等假设的限制。在此,我们介绍一种用于排列单细胞轨迹的贝叶斯信息论动态编程框架--Genes2Genes。它能捕捉参考轨迹和查询轨迹之间单个基因的连续匹配和不匹配,突出不同的配准模式群。在真实世界和模拟数据集上,它都能准确地推断出配准,并证明了它在疾病细胞状态轨迹分析中的实用性。在概念验证应用中,Genes2Genes 发现体外分化的 T 细胞与体内未成熟状态相匹配,但缺乏与 TNF 信号转导相关的基因表达。这表明,精确的轨迹比对可以精确定位与体内系统的差异,从而指导体外培养条件的优化。
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Gene-level alignment of single-cell trajectories

Single-cell data analysis can infer dynamic changes in cell populations, for example across time, space or in response to perturbation, thus deriving pseudotime trajectories. Current approaches comparing trajectories often use dynamic programming but are limited by assumptions such as the existence of a definitive match. Here we describe Genes2Genes, a Bayesian information-theoretic dynamic programming framework for aligning single-cell trajectories. It is able to capture sequential matches and mismatches of individual genes between a reference and query trajectory, highlighting distinct clusters of alignment patterns. Across both real world and simulated datasets, it accurately inferred alignments and demonstrated its utility in disease cell-state trajectory analysis. In a proof-of-concept application, Genes2Genes revealed that T cells differentiated in vitro match an immature in vivo state while lacking expression of genes associated with TNF signaling. This demonstrates that precise trajectory alignment can pinpoint divergence from the in vivo system, thus guiding the optimization of in vitro culture conditions.

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来源期刊
Nature Methods
Nature Methods 生物-生化研究方法
CiteScore
58.70
自引率
1.70%
发文量
326
审稿时长
1 months
期刊介绍: Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.
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