Integrating gene expression and splicing dynamics across dose-response oxidative modulators.

Toxicological risk assessment increasingly utilizes transcriptomics to derive point of departure (POD) and modes of action (MOA) for chemicals. One essential biological process that allows a single gene to generate several different RNA isoforms is called alternative splicing. To comprehensively assess the role of splicing dysregulation in toxicological evaluation and elucidate its potential as a complementary endpoint, we performed RNA-seq on A549 cells treated with five oxidative stress modulators across a wide dose range. Differential gene expression (DGE) showed limited pathway enrichment except at high concentrations. However, alternative splicing analysis revealed variable intron retention events affecting diverse pathways for all chemicals in the absence of significant expression changes. For instance, diazinon elicited negligible gene expression changes but progressive increase in the number of intron retention events, suggesting splicing alterations precede expression responses. Benchmark dose modeling of intron retention data highlighted relevant pathways overlooked by expression analysis. Systematic integration of splicing datasets should be a useful addition to the toxicogenomic toolkit. Combining both modalities paint a more complete picture of transcriptomic dose-responses. Overall, evaluating intron retention dynamics afforded by toxicogenomics may provide biomarkers that can enhance chemical risk assessment and regulatory decision making. This work highlights splicing-aware toxicogenomics as a possible additional tool for examining cellular responses.

Transcriptomic re-analyses of human hepatocyte spheroids treated with PFAS reveals chain length and dose-dependent modes of action.

To identify pathway perturbations and examine biological modes of action (MOAs) for various perfluoroalkyl substances, we re-analyzed published in vitro gene expression studies from human primary liver spheroids. With treatment times ranging from 10 to 14 days, shorter-chain PFAS (those with 6 or fewer fluorinated carbon atoms in the alkyl chain) showed enrichment for pathways of fatty acid metabolism and fatty acid beta-oxidation with upregulated genes. Longer-chain PFAS compounds, specifically PFOS (perfluorooctane sulfonate), PFDS (perfluorodecane sulfonate), and higher doses of PFOA (perfluorooctanoic acid), had enrichment for pathways involved in steroid metabolism, fatty acid metabolism, and biological oxidation for downregulated genes. Although PFNA (perfluorononanoic acid), PFDA (perfluorodecanoic acid), and PFUnDA (perfluoroundecanoic acid) were more toxic and could only be examined after a 1-day treatment, all three had enrichment patterns similar to those observed with PFOS. With PFOA there were dose-dependent changes in pathway enrichment, shifting from upregulation of fatty acid metabolism and downregulation of steroid metabolism to downregulation of both at higher doses. The response to PFHpS (perfluoroheptanesulfonic acid) was similar to the PFOA pattern at the lower treatment dose. Based on results of transcription factor binding sites analyses, we propose that downregulation of pathways of lipid metabolism by longer chain PFAS may be due to inhibitory interactions of PPARD on genes controlled by PPARA and PPARG. In conclusion, our transcriptomic analysis indicates that the biological MOAs of PFAS compounds differ according to chain length and dose, and that risk assessments for PFAS should consider these differences in biological MOAs when evaluating mixtures of these compounds.

Transcriptomic analysis of AHR wildtype and Knock-out rat livers supports TCDD's role in AHR/ARNT-mediated circadian disruption and hepatotoxicity.

Single, high doses of TCDD in rats are known to cause wasting, a progressive loss of 30 to 50% body weight and death within several weeks. To identify pathway perturbations at or near doses causing wasting, we examined differentially gene expression (DGE) and pathway enrichment in centrilobular (CL) and periportal (PP) regions of female rat livers following 6 dose levels of TCDD - 0, 3, 22, 100, 300, and 1000 ng/kg/day, 5 days/week for 4 weeks. At the higher doses, rats lost weight, had increased liver/body weight ratios and nearly complete cessation of liver cell proliferation, signs consistent with wasting. DGE curves were left shifted for the CL versus the PP regions. Canonical Phase I and Phase II genes were maximally increased at lower doses and remained elevated at all doses. At lower doses, ≤ 22 ng/kg/day in the CL and ≤ 100 ng/kg/day, upregulated genes showed transcription factor (TF) enrichment for AHR and ARNT. At the mid- and high-dose doses, there was a large number of downregulated genes and pathway enrichment for DEGs which showed downregulation of many cellular metabolism processes including those for steroids, fatty acid metabolism, pyruvate metabolism and citric acid cycle. There was significant TF enrichment of the hi-dose downregulated genes for RXR, ESR1, LXR, PPARalpha. At the highest dose, there was also pathway enrichment with upregulated genes for extracellular matrix organization, collagen formation, hemostasis and innate immune system. TCDD demonstrates most of its effects through binding the aryl hydrocarbon receptor (AHR) while the downregulation of metabolism genes at higher TCDD doses is known to be independent of AHR binding to DREs. Based on our results with DEG, we provide a hypothesis for wasting in which high doses of TCDD shift circadian processes away from the resting state, leading to greatly reduced synthesis of steroids and complex lipids needed for cell growth, and producing gene expression signals consistent with an epithelial-to-mesenchymal transition in hepatocytes.

Mining toxicogenomic data for dose-responsive pathways: implications in advancing next-generation risk assessment.

Introduction: While targeted investigation of key toxicity pathways has been instrumental for biomarker discovery, unbiased and holistic analysis of transcriptomic data provides a complementary systems-level perspective. However, in a systematic context, this approach has yet to receive comprehensive and methodical implementation. Methods: Here, we took an integrated bioinformatic approach by re-analyzing publicly available MCF7 cell TempO-seq data for 44 ToxCast chemicals using an alternative pipeline to demonstrate the power of this approach. The original study has focused on analyzing the gene signature approach and comparing them to in vitro biological pathway altering concentrations determined from ToxCast HTS assays. Our workflow, in comparison, involves sequential differential expression, gene set enrichment, benchmark dose modeling, and identification of commonly perturbed pathways by network visualization. Results: Using this approach, we identified dose-responsive molecular changes, biological pathways, and points of departure in an untargeted manner. Critically, benchmark dose modeling based on pathways recapitulated points of departure for apical endpoints, while also revealing additional perturbed mechanisms missed by single endpoint analyses. Discussion: This systems-toxicology approach provides multifaceted insights into the complex effects of chemical exposures. Our work highlights the importance of unbiased data-driven techniques, alongside targeted methods, for comprehensively evaluating molecular initiating events, dose-response relationships, and toxicity pathways. Overall, integrating omics assays with robust bioinformatics holds promise for improving chemical risk assessment and advancing new approach methodologies (NAMs).

Comparison of Rat Hepatocyte 2D-Monocultures and Hepatocytes Non-Parenchymal Cell Co-Cultures for Assessing Chemical Toxicity.

Liver responses are the most common endpoints used as the basis for setting exposure standards. Liver hepatocytes play a vital role in biotransformation of xenobiotics, but non-parenchymal cells (NPCs) in the liver are also involved in certain liver responses. Development of in vitro systems that more faithfully capture liver responses to reduce reliance on animals is a major focus of New Approach Methodology (NAMs). Since rodent regulatory studies are frequently the sole source safety assessment data, mode-of-action data, and used for risk assessments, in vitro rodent models that reflect in vivo responses need to be developed to reduce reliance on animal models. In the work presented in this paper, we developed a 2-D hepatocyte monoculture and 2-D liver cell co-culture system using rat liver cells. These models were assessed for conditions for short-term stability of the cultures and phenotypic and transcriptomic responses of 2 prototypic hepatotoxicants compounds - acetaminophen and phenobarbital. The optimized multi-cellular 2-D culture required use of freshly prepared hepatocytes and NPCs from a single rat, a 3:1 ratio of hepatocytes to NPCs and growth medium using 50% Complete Williams E medium (WEM) and 50% Endothelial Cell Medium (ECM). The transcriptomic responses of the 2 model systems to PB were compared to previous studies from TG-Gates on the gene expression changes in intact rats and the co-culture model responses were more representative of the in vivo responses. Transcriptomic read-outs promise to move beyond conventional phenotypic evaluations with these in vitro NAMs and provide insights about modes of action.

Biological system considerations for application of toxicogenomics in next-generation risk assessment and predictive toxicology.

There is increasing interest in using modern 'omics technologies, such as whole transcriptome sequencing, to inform decisions about human health safety and chemical toxicity hazard. High throughput methodologies using in vitro assays offer a path forward in reducing or eliminating animal testing. However, many aspects of these technologies need assessment before they will gain the trust of regulators and the public as viable alternative test methods for human health and safety. We used a high throughput whole transcriptome sequence assay (TempO-Seq) to assess the use of three widely used cancer cell lines (HepG2, MCF7, and Ishikawa cells) as in vitro systems for determination of cellular modes of action for two well studied compounds with canonical liver responses: ketoconazole and phenobarbital. We evaluated transcriptomic data to infer points of departure for use in risk analyses of compounds. Both compounds displayed shortcomings in evidence for canonical liver-related responses in any cell line, despite a strong dose response in all three. This raises questions about the competence of simple, mono-cultured cancer cell lines as appropriate surrogates for some adverse effects or toxic endpoints. Points of departure derived from benchmark doses were highly consistent across all three cell lines however, indicating the use of transcriptomic BMD analyses for such purposes would be a reliable and consistent approach.

RNA-sequencing (transcriptomic) data collected in liver and lung of male and female B6C3F1 mice exposed to various dose levels of 4-methylimidazole for 2, 5, or 28 days.

The National Toxicology Program (NTP) reported that chronic exposure to varying dietary concentrations of 4-methylimidazole (4-MeI) increased lung tumors in female and male mice [1]. In this study, mice (male and female B6C3F1 mice) were either administered 4-MeI by oral gavage (0, 50, 100, 200, or 300 mg/kg/day) for 2 days or exposed for 5 and 28 days to 4-MeI in the diet (0, 150, 300, 1250, or 2500 ppm) and whole transcriptome (RNA-Sequencing) data from 4-MeI-exposed B6C3F1 mice to determine whether changes occurred in the target (lung) and nontarget (liver) tissues. This analysis was conducted to provide information with which to evaluate biological processes affected by exposure to 4-MeI, with a focus on identifying key events that could be used to propose a plausible mode of action (MoA) for mouse lung tumors [2].

A systematic approach to evaluate plausible modes of actions for mouse lung tumors in mice exposed to 4-methylimidozole.

The National Toxicology Program (NTP) reported that chronic dietary exposure to 4-methylimidazole (4-MeI) increased the incidence of lung adenomas/carcinomas beyond the normally high spontaneous rate in B6C3F1 mice. To examine plausible modes of action (MoAs) for mouse lung tumors (MLTs) upon exposure to high levels of 4-MeI, and their relevance in assessing human risk, a systematic approach was used to identify and evaluate mechanistic data (in vitro and in vivo) in the primary and secondary literature, along with high-throughput screening assay data. Study quality, relevance, and activity of mechanistic data identified across the evidence-base were organized according to key characteristics of carcinogens (KCCs) to identify potential key events in known or novel MLT MoAs. Integration of these evidence streams provided confirmation that 4-MeI lacks genotoxic and cytotoxic activity with some evidence to support a lack of mitogenic activity. Further evaluation of contextual and chemical-specific characteristics of 4-MeI was consequently undertaken. Due to lack of genotoxicity, along with transcriptomic and histopathological lung changes up to 28 and 90 days of exposure, the collective evidence suggests MLTs observed following exposure to high levels of 4-MeI develop at a late stage in the mouse chronic bioassay, albeit the exact MoA remains unclear.

A toxicogenomic approach for the risk assessment of the food contaminant acetamide.

Acetamide (CAS 60-35-5) is detected in common foods. Chronic rodent bioassays led to its classification as a group 2B possible human carcinogen due to the induction of liver tumors in rats. We used a toxicogenomics approach in Wistar rats gavaged daily for 7 or 28 days at doses of 300 to 1500 mg/kg/day (mkd) to determine a point of departure (POD) and investigate its mode of action (MoA). Ki67 labeling was increased at doses ≥750 mkd up to 3.3-fold representing the most sensitive apical endpoint. Differential gene expression analysis by RNA-Seq identified 1110 and 1814 differentially expressed genes in male and female rats, respectively, following 28 days of treatment. Down-regulated genes were associated with lipid metabolism while up-regulated genes included cell signaling, immune response, and cell cycle functions. Benchmark dose (BMD) modeling of the Ki67 labeling index determined the BMD10 lower confidence limit (BMDL10) as 190 mkd. Transcriptional BMD modeling revealed excellent concordance between transcriptional POD and apical endpoints. Collectively, these results indicate that acetamide is most likely acting through a mitogenic MoA, though specific key initiating molecular events could not be elucidated. A POD value of 190 mkd determined for cell proliferation is suggested for risk assessment purposes.

Addressing systematic inconsistencies between in vitro and in vivo transcriptomic mode of action signatures.

Because of their broad biological coverage and increasing affordability transcriptomic technologies have increased our ability to evaluate cellular response to chemical stressors, providing a potential means of evaluating chemical response while decreasing dependence on apical endpoints derived from traditional long-term animal studies. It has recently been suggested that dose-response modeling of transcriptomic data may be incorporated into risk assessment frameworks as a means of approximating chemical hazard. However, identification of mode of action from transcriptomics lacks a similar systematic framework. To this end, we developed a web-based interactive browser-MoAviz-that allows visualization of perturbed pathways. We populated this browser with expression data from a large public toxicogenomic database (TG-GATEs). We evaluated the extent to which gene expression changes from in-life exposures could be associated with mode of action by developing a novel similarity index-the Modified Jaccard Index (MJI)-that provides a quantitative description of genomic pathway similarity (rather than gene level comparison). While typical compound-compound similarity is low (median MJI = 0.026), clustering of the TG-GATES compounds identifies groups of similar chemistries. Some clusters aggregated compounds with known similar modes of action, including PPARa agonists (median MJI = 0.315) and NSAIDs (median MJI = 0.322). Analysis of paired in vitro (hepatocyte)-in vivo (liver) experiments revealed systematic patterns in the responses of model systems to chemical stress. Accounting for these model-specific, but chemical-independent, differences improved pathway concordance by 36% between in vivo and in vitro models.

Assessing bioactivity-exposure profiles of fruit and vegetable extracts in the BioMAP profiling system.

The ToxCast program has generated in vitro screening data on over a thousand chemicals to assess potential disruption of important biological processes and assist in hazard identification and chemical testing prioritization. Few results have been reported for complex mixtures. To extend these ToxCast efforts to mixtures, we tested extracts from 30 organically grown fruits and vegetables in concentration-response in the BioMAP® assays. BioMAP systems use human primary cells primed with endogenous pathway activators to identify phenotypic perturbations related to proliferation, inflammation, immunomodulation, and tissue remodeling. Clustering of bioactivity profiles revealed separation of these produce extracts and ToxCast chemicals. Produce extracts elicited 87 assay endpoint responses per item compared to 20 per item for ToxCast chemicals. On a molar basis, the produce extracts were 10 to 50-fold less potent and when constrained to the maximum testing concentration of the ToxCast chemicals, the produce extracts did not show activity in as many assay endpoints. Using intake adjusted measures of dose, the bioactivity potential was higher for produce extracts than for agrichemicals, as expected based on the comparatively small amounts of agrichemical residues present on conventionally grown produce. The evaluation of BioMAP readouts and the dose responses for produce extracts showed qualitative and quantitative differences from results with single chemicals, highlighting challenges in the interpretation of bioactivity data and dose-response from complex mixtures.

A Qualitative Modeling Approach for Whole Genome Prediction Using High-Throughput Toxicogenomics Data and Pathway-Based Validation.

Efficient high-throughput transcriptomics (HTT) tools promise inexpensive, rapid assessment of possible biological consequences of human and environmental exposures to tens of thousands of chemicals in commerce. HTT systems have used relatively small sets of gene expression measurements coupled with mathematical prediction methods to estimate genome-wide gene expression and are often trained and validated using pharmaceutical compounds. It is unclear whether these training sets are suitable for general toxicity testing applications and the more diverse chemical space represented by commercial chemicals and environmental contaminants. In this work, we built predictive computational models that inferred whole genome transcriptional profiles from a smaller sample of surrogate genes. The model was trained and validated using a large scale toxicogenomics database with gene expression data from exposure to heterogeneous chemicals from a wide range of classes (the Open TG-GATEs data base). The method of predictor selection was designed to allow high fidelity gene prediction from any pre-existing gene expression data set, regardless of animal species or data measurement platform. Predictive qualitative models were developed with this TG-GATES data that contained gene expression data of human primary hepatocytes with over 941 samples covering 158 compounds. A sequential forward search-based greedy algorithm, combining different fitting approaches and machine learning techniques, was used to find an optimal set of surrogate genes that predicted differential expression changes of the remaining genome. We then used pathway enrichment of up-regulated and down-regulated genes to assess the ability of a limited gene set to determine relevant patterns of tissue response. In addition, we compared prediction performance using the surrogate genes found from our greedy algorithm (referred to as the SV2000) with the landmark genes provided by existing technologies such as L1000 (Genometry) and S1500 (Tox21), finding better predictive performance for the SV2000. The ability of these predictive algorithms to predict pathway level responses is a positive step toward incorporating mode of action (MOA) analysis into the high throughput prioritization and testing of the large number of chemicals in need of safety evaluation.

Strain-related differences in mouse lung gene expression over a two-year period of inhalation exposure to styrene: Relevance to human risk assessment.

Both CD-1 and C57BL/6 wildtype (C57BL/6-WT) mice show equivalent short-term lung toxicity from exposures to styrene, while long-term tumor responses are greater in CD-1 mice. We analyzed lung gene expression from styrene exposures lasting from 1-day to 2-years in male mice from these two strains, including a Cyp2f2(-/-) knockout (C57BL/6-KO) and a Cyp2F1/2A13/2B6 transgenic mouse (C57BL/6-TG). With short term exposures (1-day to 1-week), CD-1 and C57BL/6-WT mice had thousands of differentially expressed genes (DEGs), consistent with changes in pathways for cell proliferation, cellular lipid metabolism, DNA-replication and inflammation. C57BL/6-WT mice responded within a single day; CD-1 mice required several days of exposure. The numbers of exposure related DEGs were greatly reduced at longer times (4-weeks to 2-years) with enrichment only for biological oxidations in C57BL/6-WT and metabolism of lipids and lipoproteins in CD-1. Gene expression results indicate a non-genotoxic, mouse specific mode of action for short-term styrene responses related to activation of nuclear receptor signaling and cell proliferation. Greater tumor susceptibility in CD-1 mice correlated with the presence of the Pas1 loci, differential Cytochrome P450 gene expression, down-regulation of Nr4a, and greater inflammatory pathway activation. Very few exposure-related responses occurred at any time in C57BL/6-KO or -TG mice indicating that neither the short term nor long term responses of styrene in mice are relevant endpoints for assessing human risks.

Assessing molecular initiating events (MIEs), key events (KEs) and modulating factors (MFs) for styrene responses in mouse lungs using whole genome gene expression profiling following 1-day and multi-week exposures.

Styrene increased lung tumors in mice at chronic inhalation exposures of 20ppm and greater. MIEs, KEs and MFs were examined using gene expression in three strains of male mice (the parental C57BL/6 strain, a CYP2F2(-/-) knock out and a CYP2F2(-/-) transgenic containing human CYP2F1, 2A13 and 2B6). Exposures were for 1-day and 1, 4 and 26weeks. After 1-day exposures at 1, 5, 10, 20, 40 and 120ppm significant increases in differentially expressed genes (DEGs) occurred only in parental strain lungs where there was already an increase in DEGs at 5ppm and then many thousands of DEGs by 120ppm. Enrichment for 1-day and 1-week exposures included cell cycle, mitotic M-M/G1 phases, DNA-synthesis and metabolism of lipids and lipoproteins pathways. The numbers of DEGs decreased steadily over time with no DEGs meeting both statistical significance and fold-change criteria at 26weeks. At 4 and 26weeks, some key transcription factors (TFs) - Nr1d1, Nr1d2, Dbp, Tef, Hlf, Per3, Per2 and Bhlhe40 - were upregulated (|FC|>1.5), while others - Npas, Arntl, Nfil3, Nr4a1, Nr4a2, and Nr4a3 - were down-regulated. At all times, consistent changes in gene expression only occurred in the parental strain. Our results support a MIE for styrene of direct mitogenicity from mouse-specific CYP2F2-mediated metabolites activating Nr4a signaling. Longer-term MFs include down-regulation of Nr4a genes and shifts in both circadian clock TFs and other TFs, linking circadian clock to cellular metabolism. We found no gene expression changes indicative of cytotoxicity or activation of p53-mediated DNA-damage pathways.

Combining transcriptomics and PBPK modeling indicates a primary role of hypoxia and altered circadian signaling in dichloromethane carcinogenicity in mouse lung and liver.

Dichloromethane (DCM) is a lung and liver carcinogen in mice at inhalation exposures≥2000ppm. The modes of action (MOA) of these responses have been attributed to formation of genotoxic, reactive metabolite(s). Here, we examined gene expression in lung and liver from female B6C3F1 mice exposed to 0, 100, 500, 2000, 3000 and 4000ppm DCM for 90days. We also simulated dose measures - rates of DCM oxidation to carbon monoxide (CO) in lung and liver and expected blood carboxyhemoglobin (HbCO) time courses with a PBPK model inclusive of both conjugation and oxidation pathways. Expression of large numbers of genes was altered at 100ppm with maximal changes in the numbers occurring by 500 or 2000ppm. Most changes in genes common to the two tissues were related to cellular metabolism and circadian clock. At the lower concentrations, the changes in metabolism-related genes were discordant - up in liver and down in lung. These processes included organelle biogenesis, TCA cycle, and respiratory electron transport. Changes in circadian cycle genes - primarily transcription factors - showed strong concentration-related response at higher concentrations (Arntl, Npas2, and Clock were down-regulated; Cry2, Wee1, Bhlhe40, Per3, Nr1d1, Nr1d2 and Dbp) were up-regulated with similar directionality in both tissues. Overall, persistently elevated HbCO from DCM oxidation appears to cause extended periods of hypoxia, leading to altered circadian coupling to cellular metabolism. The dose response for altered circadian processes correlates with the cancer outcome. We found no evidence of changes in genes indicative of responses to cytotoxic, DNA-reactive metabolites.

Editor's Highlight: Screening ToxCast Prioritized Chemicals for PPARG Function in a Human Adipose-Derived Stem Cell Model of Adipogenesis.

The developmental origins of obesity hypothesis posits a multifaceted contribution of factors to the fetal origins of obesity and metabolic disease. Adipocyte hyperplasia in gestation and early childhood may result in predisposition for obesity later in life. Rodent in vitro and in vivo studies indicate that some chemicals may directly affect adipose progenitor cell differentiation, but the human relevance of these findings is unclear. The nuclear receptor peroxisome proliferator-activated receptor gamma (PPARG) is the master regulator of adipogenesis. Human adipose-derived stem cells (hASC) isolated from adipose tissue express endogenous isoforms of PPARG and represent a biologically relevant cell-type for evaluating activity of PPARG ligands. Here, a multi-endpoint approach based on a phenotypic adipogenesis assay was applied to screen a set of 60 chemical compounds identified in ToxCast Phase I as PPARG active (49) or inactive (11). Chemicals showing activity in the adipogenesis screen were further evaluated in a series of 4 orthogonal assays representing 7 different key events in PPARG-dependent adipogenesis, including gene transcription, protein expression, and adipokine secretion. An siRNA screen was also used to evaluate PPARG-dependence of the adipogenesis phenotype. A universal concentration-response design enabled inter-assay comparability and implementation of a weight-of-evidence approach for bioactivity classification. Collectively, a total of 14/49 (29%) prioritized chemicals were identified with moderate-to-strong activity for human adipogenesis. These results provide the first integrated screening approach of prioritized ToxCast chemicals in a human stem cell model of adipogenesis and provide insight into the capacity of PPARG-activating chemicals to modulate early life programming of adipose tissue.

Using gene expression profiling to evaluate cellular responses in mouse lungs exposed to V2O5 and a group of other mouse lung tumorigens and non-tumorigens.

Many compounds test positive for lung tumors in two-year NTP carcinogenicity bioassays in B6C3F1 mice. V2O5 was identified as a lung carcinogen in this assay, leading to its IARC (International Agency for Research on Cancer) classification as group 2b or a "possible" human carcinogen. To assess potential tumorigenic mode of action of V2O5, we compared gene expression and gene ontology enrichment in lung tissue of female B6C3F1 mice exposed for 13 weeks to a V2O5 particulate aerosol at a tumorigenic level (2.0 mg/m(3)). Relative to 12 other compounds also tested for carcinogenicity in 2-year bioassays in mice, there were 1026 differentially expressed genes with V2O5, of which 483 were unique to V2O5. Ontology analysis of the 1026 V2O5 differentially expressed genes showed enrichment for hyaluronan and sphingolipid metabolism, adenylate cyclase functions, c-AMP signaling and PKA activation/signaling. Enrichment of lipids/lipoprotein metabolism and inflammatory pathways were consistent with previously reported clinical findings. Enrichment of c-AMP and PKA signaling pathways may arise due to inhibition of phosphatases, a known biological action of vanadate. We saw no enrichment for DNA-damage, oxidative stress, cell cycle, or apoptosis pathway signaling in mouse lungs exposed to V2O5 which is in contrast with past studies evaluating in vivo gene expression in target tissues of other carcinogens (arsenic, formaldehyde, naphthalene and chloroprene).

MYC is an early response regulator of human adipogenesis in adipose stem cells.

Adipose stem cell (ASC) differentiation is necessary for the proper maintenance and function of adipose tissue. The procurement and characterization of multipotent ASCs has enabled investigation into the molecular determinants driving human adipogenesis. Here, the transcription factor MYC was identified as a significant regulator of ASC differentiation. Expression of MYC transcript and protein was found to accumulate during the initial course of differentiation. Loss-of-function analysis using siRNA mediated knockdown of MYC demonstrated inhibition of hormonally stimulated adipogenesis. MYC exhibited an early and sustained expression pattern that preceded down regulation of key suppressor genes, as well as induction of transcriptional and functional effectors. Glucocorticoid stimulation was identified as a necessary component for MYC induction and was found to impact adipogenesis in a concentration-dependent manner. Global gene expression analysis of MYC knockdown in ASC enriched for functional pathways related to cell adhesion, cytoskeletal remodeling, and transcriptional components of adipogenesis. These results identify a functional role for MYC in promotion of multipotent ASC to the adipogenic lineage.

IVT-seq reveals extreme bias in RNA sequencing.

BACKGROUND: RNA-seq is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value. RESULTS: We present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of over 1,000 in vitro transcribed RNAs from a full-length human cDNA library and sequenced them with polyA and total RNA-seq, the most common protocols. Because each cDNA is full length, and we show in vitro transcription is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find 50% of transcripts have more than two-fold and 10% have more than 10-fold differences in within-transcript sequence coverage. We also find greater than 6% of transcripts have regions of dramatically unpredictable sequencing coverage between samples, confounding accurate determination of their expression. We use a combination of experimental and computational approaches to show rRNA depletion is responsible for the most significant variability in coverage, and several sequence determinants also strongly influence representation. CONCLUSIONS: These results show the utility of IVT-seq for promoting better understanding of bias introduced by RNA-seq. We find rRNA depletion is responsible for substantial, unappreciated biases in coverage introduced during library preparation. These biases suggest exon-level expression analysis may be inadvisable, and we recommend caution when interpreting RNA-seq results.

Comparison of microarrays and RNA-seq for gene expression analyses of dose-response experiments.

Relative to microarrays, RNA-seq has been reported to offer higher precision estimates of transcript abundance, a greater dynamic range, and detection of novel transcripts. However, previous comparisons of the 2 technologies have not covered dose-response experiments that are relevant to toxicology. Male F344 rats were exposed for 13 weeks to 5 doses of bromobenzene, and liver gene expression was measured using both microarrays and RNA-seq. Multiple normalization methods were evaluated for each technology, and gene expression changes were statistically analyzed using both analysis of variance and benchmark dose (BMD). Fold-change values were highly correlated between the 2 technologies, whereas the -log p values showed lower correlation. RNA-seq detected fewer statistically significant genes at lower doses, but more significant genes based on fold change except when a negative binomial transformation was applied. Overlap in genes significant by both p value and fold change was approximately 30%-40%. Random sampling of the RNA-seq data showed an equivalent number of differentially expressed genes compared with microarrays at ~5 million reads. Quantitative RT-PCR of differentially expressed genes uniquely identified by each technology showed a high degree of confirmation when both fold change and p value were considered. The mean dose-response expression of each gene was highly correlated between technologies, whereas estimates of sample variability and gene-based BMD values showed lower correlation. Differences in BMD estimates and statistical significance may be due, in part, to differences in the dynamic range of each technology and the degree to which normalization corrects genes at either end of the scale.