Improving the discoverability, accessibility, and citability of omics datasets: a case report

The Signaling Pathways Project, an integrated 'omics knowledgebase for mammalian cellular signaling pathways

Mining of integrated public transcriptomic and ChIP-Seq (cistromic) datasets can illuminate functions of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates community classifications of signaling pathway nodes (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules. We then mapped over 10,000 public transcriptomic or cistromic experiments to their pathway node or biosample of study. To enable prediction of pathway node-gene target transcriptional regulatory relationships through SPP, we generated consensus 'omics signatures, or consensomes, which ranked genes based on measures of their significant differential expression or promoter occupancy across transcriptomic or cistromic experiments mapped to a specific node family. Consensomes were validated using alignment with canonical literature knowledge, gene target-level integration of transcriptomic and cistromic data points, and in bench experiments confirming previously uncharacterized node-gene target regulatory relationships. To expose the SPP knowledgebase to researchers, a web browser interface was designed that accommodates numerous routine data mining strategies. SPP is freely accessible at https://www.signalingpathways.org .

Research Resource: A Reference Transcriptome for Constitutive Androstane Receptor and Pregnane X Receptor Xenobiotic Signaling

The pregnane X receptor (PXR) (PXR/NR1I3) and constitutive androstane receptor (CAR) (CAR/NR1I2) members of the nuclear receptor (NR) superfamily of ligand-regulated transcription factors are well-characterized mediators of xenobiotic and endocrine-disrupting chemical signaling. The Nuclear Receptor Signaling Atlas maintains a growing library of transcriptomic datasets involving perturbations of NR signaling pathways, many of which involve perturbations relevant to PXR and CAR xenobiotic signaling. Here, we generated a reference transcriptome based on the frequency of differential expression of genes across 159 experiments compiled from 22 datasets involving perturbations of CAR and PXR signaling pathways. In addition to the anticipated overrepresentation in the reference transcriptome of genes encoding components of the xenobiotic stress response, the ranking of genes involved in carbohydrate metabolism and gonadotropin action sheds mechanistic light on the suspected role of xenobiotics in metabolic syndrome and reproductive disorders. Gene Set Enrichment Analysis showed that although acetaminophen, chlorpromazine, and phenobarbital impacted many similar gene sets, differences in direction of regulation were evident in a variety of processes. Strikingly, gene sets representing genes linked to Parkinson's, Huntington's, and Alzheimer's diseases were enriched in all 3 transcriptomes. The reference xenobiotic transcriptome will be supplemented with additional future datasets to provide the community with a continually updated reference transcriptomic dataset for CAR- and PXR-mediated xenobiotic signaling. Our study demonstrates how aggregating and annotating transcriptomic datasets, and making them available for routine data mining, facilitates research into the mechanisms by which xenobiotics and endocrine-disrupting chemicals subvert conventional NR signaling modalities.