Single-cell Transcriptomes Reveal Characteristics of MicroRNAs in Gene Expression Noise Reduction

• 作 者: Tao Hu Lei Wei Shuailin Li Tianrun Cheng Xuegong Zhang Xiaowo Wang
• 机 构: Ministry of Education Key Laboratory of Bioinformatics Center for Synthetic and Systems Biology Bioi
• 出 处: 基因组蛋白质组与生物信息学报（英文版）
• 发表日期: 2021年3期
• 关键词: MicroRNA regulation Gene expression noise Competing RNA microRNA regulation netw

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 ex-pression noise and conferring robustness to biological processes.