Alcohol use disorder (AUD) is a complex polygenic disease. Rodent models of alcohol dependence have been instrumental in modeling various aspects of dependence. Single-nucleus transcriptomics has enabled the profiling of cell-type-specific changes in gene expression in both human AUD and animal models.  In this study, we identified shared dysregulated transcriptomic networks (TN), comprising gene co-expression modules and gene regulatory networks (GRNs) in a mouse model of alcohol dependence and individuals with AUD. Through cell-type-specific TN analysis, we identified translationally relevant, conserved dependence dysregulated molecular signatures.  We identified conserved dependence-upregulated gene co-expression modules in astrocytes and oligodendrocytes, with hub genes Slc1a3 and Pde4b, respectively. These genes are linked to alcohol dependence mechanisms, such as glutamate signaling, a well-established target of alcohol’s effects, and PDE4, whose inhibition has been shown to reduce alcohol intake in preclinical and clinical studies. We then integrated publicly available human and mouse GRN data to identify upstream regulators of alcohol-dysregulated gene signatures in each cell type. This approach revealed a set of transcription factors (TFs), including Mef2a, Mef2c, Jund, Nr3c1, and Zeb1, that were upstream of most dysregulated genes in both the mouse and human datasets and have established relevance to addiction biology, representing promising targets for translational research.  Collectively, these findings demonstrate the utility of cross-species, cell-type-specific network analysis for uncovering conserved molecular mechanisms in alcohol dependence. The identification of shared dysregulated networks, cell type homology, and upstream regulators provides a foundation for developing translationally relevant targeting strategies that can be tested in animal models.