This is a revision application to obtain funds for including information on females as well as males in a resource for systems genetic analysis of the rodent transcriptome. The core of our resource is a website, http://phenogen.ucdenver.edu that makes available gene expression data from recombinant inbred and inbred panels of mice and rats, as well as analytical tools to use the genetics of gene expression for identification of genes and transcriptional networks associated with complex traits such as addiction and other mental health problems. The parent R24 grant for this revision uses RNA-Seq methodology to characterize and quantify the brain and liver transcriptomes from male rats from the HXB/BXH recombinant inbred panel and a genetically diverse panel of inbred rat strains. In the past year, we have determined the genome sequence of the parental strains for the HXB/BXH RI panel (SHR/Ola and BN-Lx strains) and have used RNA-Seq data from the brains of these rats to perform a transcriptome reconstruction, using sequence-specific genomic alignment. We have also obtained stranded RNA-Seq data from two of the HXB/BXH RI strains and are developing methods for transcript quantification using ERCC spike-in standards. While continuing to develop the transcriptome data for the male rat panels, we propose to add brain and liver transcriptome data from female SHR/Ola and BN-Lx rats at each stage of the estrus cycle. We will also gather transcriptome data from the nucleus accumbens shell and core regions of both strains of male and female rats, as these regions are particularly important for the alcohol-related complex traits (reinforcement, reward response, learning) that are of interest to us and other investigators. We will, in our own work, measure the phenotypes of free-choice alcohol consumption and a number of variables related to alcohol metabolism in the female rats at each stage of the estrus cycle, for comparison to the studies of male rats in the parent R24 grant, and will integrate the transcriptome and phenotypic data to identify candidate transcripts predisposing to genetic, sex and estrus cycle dependent differences in these traits. All annotated and curated data will be made available to other investigators for their genetic, genomic and phenotypic analysis on the Phenogen website.