Ministry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University, Beijing 100084, China.
Ministry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University, Beijing 100084, China.
Genomics Proteomics Bioinformatics. 2021 Jun;19(3):394-407. doi: 10.1016/j.gpb.2021.05.002. Epub 2021 Oct 1.
Isogenic cells growing in identical environments show cell-to-cell variations because of the stochasticity in gene expression. High levels of variation or noise can disrupt robust gene expression and result in tremendous consequences for cell behaviors. In this work, we showed evidence from single-cell RNA sequencing data analysis that microRNAs (miRNAs) can reduce gene expression noise at the mRNA level in mouse cells. We identified that the miRNA expression level, number of targets, target pool abundance, and miRNA-target interaction strength are the key features contributing to noise repression. miRNAs tend to work together in cooperative subnetworks to repress target noise synergistically in a cell type-specific manner. By building a physical model of post-transcriptional regulation and observing in synthetic gene circuits, we demonstrated that accelerated degradation with elevated transcriptional activation of the miRNA target provides resistance to extrinsic fluctuations. Together, through the integrated analysis of single-cell RNA and miRNA expression profiles, we demonstrated that miRNAs are important post-transcriptional regulators for reducing gene expression noise and conferring robustness to biological processes.
在相同环境中生长的同基因细胞由于基因表达的随机性而表现出细胞间的变异。高水平的变异或噪声会破坏稳健的基因表达，并对细胞行为产生巨大影响。在这项工作中，我们从单细胞 RNA 测序数据分析中得到证据表明，microRNAs（miRNAs）可以降低小鼠细胞中 mRNA 水平的基因表达噪声。我们确定 miRNA 的表达水平、靶标数量、靶标池丰度和 miRNA-靶标相互作用强度是抑制噪声的关键特征。miRNAs 倾向于在协同子网络中协同工作，以细胞类型特异性的方式协同抑制靶标噪声。通过构建转录后调控的物理模型，并在合成基因电路中进行观察，我们证明了 miRNA 靶标转录激活的加速降解提供了对外部波动的抵抗力。综上所述，通过单细胞 RNA 和 miRNA 表达谱的综合分析，我们证明了 miRNAs 是减少基因表达噪声和赋予生物过程稳健性的重要转录后调控因子。
