Dataset used to determine the predictive accuracy of the HDACi biomarker. This dataset is associated with the following publication: Cho, E., A. Rowan-Carroll, A. Williams, C. Corton, H. Li, A. Fornace, C. Hobbs, and C. Yauk. Development and Validation of the TGx-HDACi Transcriptomic Biomarker to Detect Histone Deacetylase Inhibitors in Human TK6 Cells. Archives of Toxicology. Springer, New York, NY, USA, 95(5): 1631-1645, (2021).

The dataset shows the results of the Running Fisher test between the TGx-DDI biomarker and each of the qPCR-generated gene lists from chemical treatments in TK6 cells. The results are divided into training and test sets. This dataset is associated with the following publication: Cho, E., J. Buick, A. Williams, R. Chen, H. Li, C. Corton, A. Fornace, J. Aubrecht, and C. Yauk. Assessment of the performance of the TGx-DDI biomarker to detect DNA damage-inducing agents using quantitative RT- PCR in TK6 cells. ENVIRONMENTAL AND MOLECULAR MUTAGENESIS. John Wiley & Sons, Inc, Hoboken, NJ, USA, 60(2): 122-133, (2019).

Gene Expression Omnibus and ArrayExpress identification numbers of studies used in the analysis. This dataset is associated with the following publication: Cervantes, P., and C. Corton. A Gene Expression Biomarker Predicts Heat Shock Factor 1 Activation in a Gene Expression Compendium. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 34(7): 1721-1737, (2021).

Datasets used in RD-023418: Adverse Outcome Pathway-Driven Identification of Rat Hepatocarcinogens in Short-Term Assays. This dataset is associated with the following publication: Rooney, J., T. Hill, C. Qin, F. Sistare, and C. Corton. Adverse outcome pathway-driven identification of rat liver tumorigens in short-term assays. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 356: 99-113, (2018).

We introduce a new high-throughput transcriptomics (HTTr) platform comprised of a collagen sandwich primary rat hepatocyte culture and the TempO-Seq assay for screening and prioritizing potential hepatotoxicants. We selected 14 chemicals based on their risk of drug-induced liver injury (DILI) and tested them in hepatocytes at two treatment concentrations. HTTr data was generated using the TempO-Seq whole transcriptome and S1500+ assays. The HTTr platform exhibited high reproducibility between technical replicates (r>0.9) but biological replication was greater for TempO-Seq S1500+ (r>0.85) than for the whole transcriptome (r>0.7). Reproducibility between biological replicates was dependent on the strength of transcriptional effects induced by a chemical treatment. Despite targeting a smaller number of genes, the S1500+ assay clustered chemical treatments and produced gene set enrichment analysis (GSEA) scores comparable to those of the whole transcriptome. Connectivity mapping showed a high-level of reproducibility between TempO-Seq data and Affymetrix GeneChip data from the Open TG-GATES project with high concordance between the S1500+ gene set and whole transcriptome. Taken together, our results provide guidance on selecting the number of technical and biological replicates and support the use of TempO-Seq S1500+ assay for a high-throughput platform for screening hepatotoxicants. FASTQ files and read counts data have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus (GEO) (GSE152128). This dataset is associated with the following publication: Lee, F., I. Shah, Y.T. Soong, J. Xing, I.C. Ng, F. Tasnim, and H. Yu. Reproducibility and Robustness of High-Throughput S1500+ Transcriptomics on Primary Rat Hepatocytes for Chemical-Induced Hepatotoxicity Assessment. Current Research in Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 2: 282-295, (2021).

We screened 44 chemicals in MCF7 cells in concentration response and generated HTTr data using the TempO-Seq hWTv1 assay. First, we provide an outline of the quality of the HTTr data based on a set of QC metrics we developed for this platform. Second, we evaluate the reproducibility and mechanistic accuracy of the HTTr platform using inter-plate analysis of reference samples and comparison of reference chemical treatment effects with CMAP signatures, respectively. Third, we summarize the concentration-dependent HTTr responses for all 44 chemicals to stratify them in terms of their overall effect on the transcriptome. Fourth, we present a new gene signature based concentration-response analysis that provides potency estimates for perturbation of cellular biology (ie, BPACs). This dataset is associated with the following publication: Harrill, J., L. Everett, D. Haggard, T. Sheffield, J. Bundy, C. Willis, R. Thomas, I. Shah, and R. Judson. High-Throughput Transcriptomics Platform for Screening Environmental Chemicals. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 181(1): 68-89, (2021).

Microarray experiments used in the study. This dataset is associated with the following publication: Corton, J., K. Korunes, J. Abedini, H. El-Masri, J. Brown, K. Friedman, Y. Liu, C. Martini, S. He, and J. Rooney. Thresholds Derived from Common Measures in Rat Studies are Predictive of Liver Tumorigenic Chemicals. TOXICOLOGIC PATHOLOGY. Society of Toxicology, RESTON, VA, 48(7): 857-874, (2020).

The files in this data release are RNA seq datafiles from a study that examined the effects of the synthetic anabolic steroid 17β hydroxyestra 4,9,11 trien-3-one, trenbolone (17βT - CAS 10161-33-8), a common contaminant of wastes from confined animal feeding operations (CAFOs). Japanese quail (Coturnix japonica) were exposed in the egg and through feed to multiple doses of 17βT and liver transcriptomes were examined to identify genes and pathways directly affected by this androgenic compound. RNA was extracted from liver of adults and embryos and analyzed (1x50 bp) on an Illumina HiSeq 2000. NCBI Biosample accessions and the raw counts that were input into the differential expression analysis are provided in this dataset. The raw sequence data are available at the NCBI Sequence Read Archive under Bioproject numbers PRJNA313918 and PRJNA313931.

A number of brominated flame retardants (BFRs) have been reported to interfere with the thyroid signaling pathway and cause oxidative stress in birds, yet the underlying shifts in gene expression associated with these effects remain poorly understood. In this study, we measured hepatic transcriptional responses of 31 genes in American kestrel hatchlings following in ovo exposure to one of three high-volume alternative BFRs: 1,2-bis(2,4,6-tribromophenoxy) ethane (BTPBE), bis(2-ethylhexyl)-2,3,4,5-tetrabromophthalate (TBPH), or 2-ethylhexyl-2,3,4,5-tetrabromobenzoate (EHTBB). Hatchling kestrels exhibited shifts in the expression of genes related to oxidative stress (CYP, GSTA, SOD, GPx), thyroid hormone metabolism and transport (DIO, TTR), lipid and protein metabolism (PPAR, HMGCR, FAB1, LPL), and cytokine-mediated inflammation (TLR, IL-18, IRF7, STAT3, RACK1, CEBPB). Male and female hatchlings differed in which genes were differentially expressed as well as the direction of the effect (up- vs. down-regulation). These results build upon our previous findings of increased oxidative stress and disrupted thyroid signaling pathway in the same hatchlings. Furthermore, our results indicate that inflammatory responses appear to occur in female hatchlings exposed to BTBPE and EHTBB in ovo. Gene expression analysis revealed multiple affected pathways, adding to the growing evidence that sublethal physio-logical effects are complex and are a concern for birds exposed to BTBPE, EHTBB, or TBPH in ovo.