Omics approaches are broadly used to explore endocrine and toxicity-related pathways and functions. Nevertheless, there is still a significant gap in knowledge in terms of understanding the endocrine system and its numerous connections and intricate feedback loops, especially in non-model organisms. The fathead minnow (Pimephales promelas) is a widely used small fish model for aquatic toxicology and regulatory testing, particularly in North America. A draft genome has been published, but the amount of available genomic or transcriptomic information is still far behind that of other more broadly studied species, such as the zebrafish. Here, we used a proteogenomics approach to survey the tissue-specific proteome and transcriptome profiles in adult male fathead minnow. To do so, we generated a draft transcriptome using short and long sequencing reads from liver, testis, brain, heart, gill, head kidney, trunk kidney, and gastrointestinal tract. We identified 30,378 different putative transcripts overall, with the assembled contigs ranging in size from 264 to over 9,720 nts. Over 17,000 transcripts were >1,000 nts, suggesting a robust transcriptome that can be used to interpret RNA sequencing data in the future. We also performed RNA sequencing and proteomics analysis on four tissues, including the telencephalon, hypothalamus, liver, and gastrointestinal tract of male fish. Transcripts ranged from 0 to 600,000 copies per gene and a large portion were expressed in a tissue-specific manner. Specifically, the telencephalon and hypothalamus shared the most expressed genes, while the gastrointestinal tract and the liver were quite distinct. Using protein profiling techniques, we identified a total of 4,045 proteins in the four tissues investigated, and their tissue-specific expression pattern correlated with the transcripts at the pathway level. Similarly to the findings with the transcriptomic data, the hypothalamus and telencephalon had the highest degree of similarity in the proteins detected. The main purpose of this analysis was to generate tissue-specific omics data in order to support future aquatic ecotoxicogenomic and endocrine-related studies as well as to improve our understanding of the fathead minnow as an ecological model.