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Abstract

Alcohol use disorder (AUD) causes long-lasting changes in brain gene expression and RNA splicing, particularly in the ventral hippocampus. This study analyzes RNA-Seq data from rats exposed to chronic alcohol and withdrawal to identify transcript-level and splicing alterations. An optimized RNA-Seq pipeline using STAR, FeatureCounts, edgeR, and WGCNA improved efficiency by 25-40% while maintaining consistency across 25 datasets. Results reveal changes in neural signaling and stress-response pathways associated with withdrawal. This work provides both biological insight into AUD and a reproducible computational framework for transcriptomic analysis.

Publication Date

2026

Subject Major(s)

Bioinformatics

Keywords

AUD, Alcohol Use Disorder, RNA splicing, Pharmacology, Toxicology, neurogenomics, gene expression

Disciplines

Bioinformatics | Computational Biology | Genomics | Other Neuroscience and Neurobiology | Pharmacology | Toxicology

Current Academic Year

Senior

Faculty Advisor/Mentor

Amy Lasek

Faculty Advisor/Mentor

Luana Martins de Carvalho

Rights

© The Author(s)

Identifying RNA Splicing Changes During Alcohol Withdrawal Using an Optimized RNA-Seq Analysis Pipeline

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