Single-cell Transcriptomes Reveal Characteristics of MicroRNAs in Gene Expression Noise Reduction.
10.1016/j.gpb.2021.05.002
- Author:
Tao HU
1
;
Lei WEI
1
;
Shuailin LI
1
;
Tianrun CHENG
1
;
Xuegong ZHANG
1
;
Xiaowo WANG
2
Author Information
1. 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.
2. 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. Electronic address: xwwang@tsinghua.edu.cn.
- Publication Type:Journal Article
- Keywords:
Competing RNA;
Gene expression noise;
MicroRNA regulation;
Single-cell RNA sequencing;
microRNA regulation network
- From:
Genomics, Proteomics & Bioinformatics
2021;19(3):394-407
- CountryChina
- Language:English
-
Abstract:
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.
