| Literature DB >> 33322800 |
Joanna Solich1, Maciej Kuśmider1, Agata Faron-Górecka1, Paulina Pabian1, Marta Dziedzicka-Wasylewska1.
Abstract
In the present study, we aim to identify the effect of restrain stress (RS) on the expression of miRNAs in mouse serum. We used three genotypes of animals (mice with knock-out of the gene-encoding norepinephrine transporter, NET-KO; C57BL/6J, and SWR/J) which had previously been shown to display different sensitivity to RS, and focused on miRNAs which were altered by RS in the serum of all three genotypes. An analysis of miRNAs expression allowed for the identification of a set of 25 differentially expressed miRNAs; 10 were down-regulated compared to an appropriate control group of animals, while 15 were up-regulated. The application of DIANA-miRPath v. 3.0 allowed for the identification of selected pathways (KEGG) and Gene Ontology (GO) categories that were significantly controlled by these miRNAs, while miRWalk v. 3.0-the platform that used the machine learning based algorithm, TaRPmiR-was used to find their targets. The results indicate that 25 miRNAs, identified as altered upon RS in three genotypes of mice, are responsible for regulation of mRNA-encoding proteins that are key for the main hypotheses of depression; therefore, they may help to understand the link between stress and depression at the molecular level.Entities:
Keywords: NET-KO mice; SWR/J mice; depression; machine learning algorithm; microRNA; stress
Year: 2020 PMID: 33322800 PMCID: PMC7763317 DOI: 10.3390/ijms21249469
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923