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Cell Specific Gene Expression

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...

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Investigating Drivers of Antireward in Addiction Behavior with Anatomically Specific Single-Cell Gene Expression Methods

Investigating Drivers of Antireward in Addiction Behavior with Anatomically Specific Single-Cell Gene Expression Methods

Published on: August 4, 2022

Gene expression profiling in the human alcoholic brain.

Anna S Warden¹, R Dayne Mayfield²

¹Institute for Neuroscience, The University of Texas at Austin, 1 University Station, C7000, Austin, TX 78712, USA; Waggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, 2500 Speedway, A4800, Austin, TX 78712, USA.

Neuropharmacology

|March 4, 2017

Summary

This summary is machine-generated.

Long-term alcohol use alters human brain gene expression, potentially driving alcohol use disorder. Advanced bioinformatics and sequencing reveal complex regulatory networks involved in alcohol dependence.

Keywords:

Alcohol Co-expression networks Gene expression RNA-seq Transcriptional regulation

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Published on: March 8, 2020

Area of Science:

Neuroscience
Genetics
Molecular Biology

Background:

Long-term alcohol consumption induces significant alterations in human brain gene expression.
These molecular changes are implicated in the transition from occasional drinking to alcohol use disorder (AUD).

Purpose of the Study:

To provide an integrated overview of alcohol-responsive transcriptional changes in the human brain.
To elucidate the regulatory gene networks contributing to alcohol dependence.

Main Methods:

Review of transcriptome studies in human postmortem brain.
Application of bioinformatics techniques for systems-level transcriptome profiling.
Integration of next-generation sequencing data to identify coding/non-coding RNAs and alternative splicing.

Main Results:

Identification of specific gene candidates linked to alcohol dependence phenotypes.
Detection of known and novel RNAs, alternative splicing, and cell-type specific changes.
Characterization of alcohol-responsive transcriptional alterations and regulatory networks.

Conclusions:

Aberrant gene expression is a key factor in the development and progression of alcohol dependence.
Bioinformatics and advanced sequencing offer powerful tools for understanding the molecular basis of alcohol-related pathologies.
Understanding these regulatory networks is crucial for developing targeted interventions for alcohol use disorder.