Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data

Wendao Liu, Noam Shomron*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

MicroRNAs (miRNAs) regulate gene expression by binding to mRNAs, and thus reduce target gene expression levels and expression variability, also known as ‘noise’. Single-cell RNA sequencing (scRNA-seq) technology has been used to study miRNA and mRNA expression in single cells. To evaluate scRNA-seq as a tool for investigating miRNA regulation, we analyzed datasets with both mRNA and miRNA expression in single-cell format. We found that miRNAs slightly reduce the expression noise of target genes; however, this effect is easily masked by strong technical noise from scRNA-seq. We suggest improvements aimed at reducing technical noise, which can be implemented in experimental design and computational analysis prior to running scRNA-seq. Our study provides useful guidelines for experiments that evaluate the effect of miRNAs on mRNA expression from scRNA-seq.

Original languageEnglish
Article number1750
JournalJournal of Personalized Medicine
Volume12
Issue number10
DOIs
StatePublished - Oct 2022

Funding

FundersFunder number
Koret-UC Berkeley-Tel Aviv University
UCSF-Tel Aviv University
Tel Aviv University
Queensland Brain Institute
Ministry of Science and Technology, Israel
Horizon 2020

    Keywords

    • data analysis
    • gene expression
    • microRNA
    • single cell

    Fingerprint

    Dive into the research topics of 'Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data'. Together they form a unique fingerprint.

    Cite this