RNA molecules exist as orchestrated networks throughout the genome, and are regulated, in part, by genetic variants, alternative splicing, and epigenetic modifications. Transcriptome approaches are continually being refined, improving our understanding of the molecular etiology and progression of AUD. We can now investigate how alcohol changes DNA regulation via epigenetic modifications, or how it alters transcriptional regulation via miRNAs and lncRNAs, or even how gene expression changes in individual cell types potentially mediate the transition from alcohol use to the “dark side of addiction” (Koob and Volkow, 2010; Volkow et al., 2016) (Fig. 3). Sequence data can be integrated with protein data, physiological function, phenotypic traits, and other factors such as the microbiome, to create a more cohesive picture of the disease state (Farris and Mayfield, 2014). This information, coupled with corresponding information from animal models (Truitt et al, 2016), aims to uncover improved treatment strategies for AUD (Warden et al., 2016), and may one day be used to target an individual’s transcriptome profile. Advances in “precision” and “personalized” medicine could lead to improved therapies that surpass those obtained by current in silico bioinformatics approaches (Shin et al., 2016; Sliwczynski and Orlewska, 2016).
