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

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...

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Detalles Bibliográficos
Autores principales: Liu, Wendao, Shomron, Noam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605646/
https://www.ncbi.nlm.nih.gov/pubmed/36294889
http://dx.doi.org/10.3390/jpm12101750
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author Liu, Wendao
Shomron, Noam
author_facet Liu, Wendao
Shomron, Noam
author_sort Liu, Wendao
collection PubMed
description 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.
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spelling pubmed-96056462022-10-27 Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data Liu, Wendao Shomron, Noam J Pers Med Article 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. MDPI 2022-10-21 /pmc/articles/PMC9605646/ /pubmed/36294889 http://dx.doi.org/10.3390/jpm12101750 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Wendao
Shomron, Noam
Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data
title Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data
title_full Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data
title_fullStr Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data
title_full_unstemmed Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data
title_short Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data
title_sort analysis of microrna regulation and gene expression variability in single cell data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605646/
https://www.ncbi.nlm.nih.gov/pubmed/36294889
http://dx.doi.org/10.3390/jpm12101750
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