Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data.
Wendao LiuNoam ShomronPublished in: Journal of personalized medicine (2022)
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.
Keyphrases
- single cell
- rna seq
- gene expression
- poor prognosis
- high throughput
- dna methylation
- air pollution
- genome wide
- binding protein
- induced apoptosis
- long non coding rna
- big data
- cell death
- signaling pathway
- high intensity
- cell cycle arrest
- cell proliferation
- endoplasmic reticulum stress
- oxidative stress
- machine learning
- genome wide identification