RNA-seq data from HepaRG cells exposed for 2 hours to microcystin-LR and -RR at multiple concentrations each. This dataset is associated with the following publication: Biales, A., D. Bencic, R. Flick, A. Delacruz, D. Gordon, and W. Huang. Global transcriptomic profiling of microcystin-LR or -RR treated hepatocytes (HepaRG).. Toxicon: X. Elsevier B.V., Amsterdam, NETHERLANDS, 8: 100060, (2020).

data sets included in this study: Differential Expressed gene lists for nano Cu CuCl2 treated HepG2 cells through RNA sequencing. Differential Expressed microRNA lists for nano Cu and CuCl2 treated HepG2 cells through small RNA sequencing. Sequencing data was quantified using Partek annotation and the STAR-2.5.3a aligner, aligned to human genome hg19. Normalization and contrast were performed using DESeq2. MicroRNA expression was quantified with mirDeep2. Benjamini-Hochberg method for multi-testing correcton was included in DESeq2.

data sets included in this study: Differential Expressed gene lists for nano Cu CuCl2 treated HepG2 cells through RNA sequencing. Differential Expressed microRNA lists for nano Cu and CuCl2 treated HepG2 cells through small RNA sequencing. Sequencing data was quantified using Partek annotation and the STAR-2.5.3a aligner, aligned to human genome hg19. Normalization and contrast were performed using DESeq2. MicroRNA expression was quantified with mirDeep2. Benjamini-Hochberg method for multi-testing correcton was included in DESeq2.

The data include sequences, qPCR, RT-qPCR, water nutrients and cyanotoxins.

Differential expressed gene lists and altered canonical pathways in HepG2 cells after CeO2 particle treatment. This dataset is associated with the following publication: Thai, S., C. Jones, B. Robinette, H. Ren, B. Vallanat, A. Astriab Fisher, and K. Kitchin. Differential genomic effects of four nano-sized and one micro-sized CeO2 particles on HepG2 cells. Materials Express. American Scientific Publishers, VALENCIA, CA, USA, 13(10): 1799-1811, (2023).

Differential expressed gene lists and altered canonical pathways in HepG2 cells after CeO2 particle treatment. This dataset is associated with the following publication: Thai, S., C. Jones, B. Robinette, H. Ren, B. Vallanat, A. Astriab Fisher, and K. Kitchin. Differential genomic effects of four nano-sized and one micro-sized CeO2 particles on HepG2 cells. Materials Express. American Scientific Publishers, VALENCIA, CA, USA, 13(10): 1799-1811, (2023).

Dataset for Robarts et al., 'Hepatic Transcriptome Comparative In Silico Analysis Reveals Similar Pathways and Targets Altered by Legacy and Alternative Per- and Polyfluoroalkyl Substances in Mice' published in Toxics, DOI https://doi.org/10.3390/toxics11120963, PMCID 10748317. This dataset is associated with the following publication: Robarts, D., J. Dai, C. Lau, U. Apte, and J. Corton. Hepatic Transcriptome Comparative In Silico Analysis Reveals Similar Pathways and Targets Altered by Legacy and Alternative Per- and Polyfluoroalkyl Substances in Mice. Toxics. MDPI, Basel, SWITZERLAND, 11(12): 963, (2023).

(1) qPCR and RT-qPCR for cyanotoxin producing genes, and (2) some water quality parameters. This dataset is associated with the following publication: Duan, X., C. Zhang, I. Struewing, X. Li, H. Allen, and J. Lu. Cyanotoxin-encoding genes as powerful predictors of cyanotoxin production during harmful cyanobacterial blooms in an inland freshwater lake: Evaluating a novel early-warning system. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 830: 154568, (2022).

(1) qPCR and RT-qPCR for cyanotoxin producing genes, and (2) some water quality parameters. This dataset is associated with the following publication: Duan, X., C. Zhang, I. Struewing, X. Li, H. Allen, and J. Lu. Cyanotoxin-encoding genes as powerful predictors of cyanotoxin production during harmful cyanobacterial blooms in an inland freshwater lake: Evaluating a novel early-warning system. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 830: 154568, (2022).

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).