造血过程中转录组轨迹的动态系统处理

Simon L. Freedman, Bingxian Xu, S. Goyal, Madhav Mani
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引用次数: 7

摘要

受Waddington对表观遗传景观的描述的启发,细胞命运转变被设想为分叉的动力系统,其中外源信号的动力学与细胞极其复杂的信号传导和转录机制耦合,引发细胞集体状态的质的转变-它的命运。然而,目前尚不清楚的是,动力系统框架是否能够超越基于单词的系统漫画,并提供敏锐的定量见解,进一步加深我们对分化的理解。单细胞RNA测序(scRNA-seq)测量了大量分化细胞中可能的转录状态分布,提供了另一种观点,即发育是以无数基因的个体浓度变化为标志的。在这里,从形式化的数学推导开始,我们对这些转录组轨迹进行了严格的统计评估,以确定它们是否显示出与分岔一致的特征。在确定了造血分化中性粒细胞分支转录组轨迹上的分支后,我们能够进一步利用线性不稳定性的原始特征来确定基因表达空间中的单向,沿着该方向展开分支并确定可能的基因贡献者。该方案确定转录因子长期以来被认为在中性粒细胞分化过程中起着至关重要的作用,此外还确定了许多其他新的遗传参与者。最广泛地说,我们提供的证据表明,尽管非常高维,分岔的动力系统形式主义可能适用于细胞分化过程,并且可以利用它来提供见解。雄心勃勃地,我们的工作试图超越数据分析,朝着构建可证伪的数学模型,描述整个转录组的动态迈出一步。
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A dynamical systems treatment of transcriptomic trajectories in hematopoiesis
Inspired by Waddington’s illustration of an epigenetic landscape, cell-fate transitions have been envisioned as bifurcating dynamical systems, wherein the dynamics of an exogenous signal couples to a cell’s enormously complex signaling and transcriptional machinery, eliciting a qualitative transition in the collective state of a cell – its fate. It remains unclear, however, whether the dynamical systems framework can go beyond a word-based caricature of the system and provide sharp quantitative insights that further our understanding of differentiation. Single-cell RNA sequencing (scRNA-seq), which measures the distributions of possible transcriptional states in large populations of differentiating cells, provides an alternate view, in which development is marked by the individual concentration variations of a myriad of genes. Here, starting from formal mathematical derivations, we challenge these transcriptomic trajectories to a rigorous statistical evaluation of whether they display signatures consistent with bifurcations. After pinpointing bifurcations along transcriptomic trajectories of the neutrophil branch of hematopoeitic differentiation we are able to further leverage the primitive features of a linear instability to identify the single-direction in gene expression space along which the bifurcation unfolds and identify possible gene contributors. This scheme identifies transcription factors long viewed to play a crucial role in the process of neutrophil differentiation in addition to identifying a host of other novel genetic players. Most broadly speaking, we provide evidence that, though very high-dimensional, a bifurcating dynamical systems formalism might be appropriate for the process of cellular differentiation and that it can be leveraged to provide insights. Ambitiously, our work attempts to take a step beyond data-analysis and towards the construction of falsifiable mathematical models that describe the dynamics of the entire transcriptome.
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