Dataset Information

MiRNA and mRNA Profiles in Ventral Tegmental Area From Juvenile Mice With Companion Communication of Improving CUMS-Induced Depression-Like Behaviors.

ABSTRACT: Under chronic stress, the appearance of depression-like behaviors may be related to the decline of the brain's reward circuit function which caused by long-term lack of reward. However, the effect of reward treatment on depressive-like behaviors induced by chronic stress and its molecular mechanism in the brain remain poorly understood. Here, accompanying with companion was used to imitate a reward to study the effect of reward on depression-like behaviors induced by chronic unpredicted mild stress (CUMS), and high-throughput sequencing was used to analyze the miRNA and mRNA profiles in ventral tegmental area (VTA) harvested from depression-like and resilient behaviors mice. We observed that CUMS-induced depression-like behaviors were ameliorated by accompanying with companion in mice, and 202 differentially expressed genes (DEGs) were found to be associated with depression-like behaviors, 27 DEGs associated with resilience, 159 DEGs associated with accompanying with companion. Importantly, we also obtained 228 differentially expressed miRNAs that associated with accompanying with companion. Furthermore, the miRNA-mRNA network associated with companion was established in ventral tegmental area, based on the miRNA and mRNA profiles. Altogether, our results uncover a new way to ameliorate depression-like behavior, as well as many potential drug targets to prevent or treat depression.

SUBMITTER: Song Z

PROVIDER: S-EPMC8044319 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Decades of research have revealed the remarkable complexity of the midbrain dopamine (DA) system, which comprises cells principally located in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). Neither homogenous nor serving a singular function, the midbrain DA system is instead composed of distinct cell populations that (1) receive different sets of inputs, (2) project to separate forebrain sites, and (3) are characterized by unique transcriptional and physiological signatures. To appreciate how these differences relate to circuit function, we first need to understand the anatomical connectivity of unique DA pathways and how this connectivity relates to DA-dependent motivated behavior. We and others have provided detailed maps of the input-output relationships of several subpopulations of midbrain DA cells and explored the roles of these different cell populations in directing behavioral output. In this study, we analyze VTA inputs and outputs as a high dimensional dataset (10 outputs, 22 inputs), deploying computational techniques well-suited to finding interpretable patterns in such data. In addition to reinforcing our previous conclusion that the connectivity in the VTA is dependent on spatial organization, our analysis also uncovered a set of inputs elevated onto each projection-defined VTADA cell type. For example, VTADA→NAcLat cells receive preferential innervation from inputs in the basal ganglia, while VTADA→Amygdala cells preferentially receive inputs from populations sending a distributed input across the VTA, which happen to be regions associated with the brain's stress circuitry. In addition, VTADA→NAcMed cells receive ventromedially biased inputs including from the preoptic area, ventral pallidum, and laterodorsal tegmentum, while VTADA→mPFC cells are defined by dominant inputs from the habenula and dorsal raphe. We also go on to show that the biased input logic to the VTADA cells can be recapitulated using projection architecture in the ventral midbrain, reinforcing our finding that most input differences identified using rabies-based (RABV) circuit mapping reflect projection archetypes within the VTA.

Dataset Information

MiRNA and mRNA Profiles in Ventral Tegmental Area From Juvenile Mice With Companion Communication of Improving CUMS-Induced Depression-Like Behaviors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets