CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, 200031, China.
Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Moscow, 143028, Russia.
BMC Genomics. 2018 Apr 17;19(1):262. doi: 10.1186/s12864-018-4649-2.
Neuron maturation is a critical process in neurogenesis, during which neurons gain their morphological, electrophysiological and molecular characteristics for their functions as the central components of the nervous system.
To better understand the molecular changes during this process, we combined the protein-protein interaction network and public single cell RNA-seq data of mature and immature neurons to identify functional modules relevant to the neuron maturation process in humans. Among the 109 functional modules in total, 33 showed significant gene expression level changes (discriminating modules) which participate in varied functions including energy consumption, synaptic functions and housekeeping functions such as translation and splicing. Based on the identified modules, we trained a neuron maturity index (NMI) model for the quantification of maturation states of single neurons or purified bulk neurons. Applied to multiple single neuron transcriptome data sets of neuron development in humans and mice, the NMI model made estimation of neuron maturity states which were significantly correlated with the neuron maturation trajectories in both species, implying the reproducibility and conservation of the identified transcriptome transition.
We identified 33 discriminating modules whose activities were significantly correlated with single neuron maturity states, which may play important roles in the neuron maturation process.
神经元成熟是神经发生过程中的一个关键步骤，在此过程中，神经元获得其形态、电生理和分子特征，作为神经系统的核心组成部分发挥功能。
为了更好地理解这一过程中的分子变化，我们将成熟和未成熟神经元的蛋白质-蛋白质相互作用网络和公共单细胞 RNA-seq 数据相结合，以鉴定与人类神经元成熟过程相关的功能模块。在总共 109 个功能模块中，有 33 个显示出显著的基因表达水平变化（区分模块），这些模块参与了各种功能，包括能量消耗、突触功能以及翻译和剪接等管家功能。基于鉴定的模块，我们为单个神经元或纯化的神经元群体的成熟状态量化训练了一个神经元成熟指数（NMI）模型。应用于人类和小鼠神经元发育的多个单细胞转录组数据集，NMI 模型对神经元成熟状态进行了估计，与两种物种的神经元成熟轨迹显著相关，这意味着鉴定的转录组转变具有可重复性和保守性。
我们鉴定了 33 个具有显著相关性的区分模块，其活性与单个神经元的成熟状态显著相关，这些模块可能在神经元成熟过程中发挥重要作用。
