Tissue- and strain-specific effects of a genotoxic carcinogen 1,3-butadiene on chromatin and transcription

Israel, Jennifer W.; Chappell, Grace A.; Simon, Jeremy M.; Pott, Sebastian; Safi, Alexias; Lewis, Lauren; Cotney, Paul; Boulos, Hala; Bodnar, Wanda M.; Lieb, Jason D.; Crawford, Gregory E.; Furey, Terrence S.; Rusyn, Ivan

doi:10.1007/s00335-018-9739-6

Cited by 21 publications

(26 citation statements)

References 43 publications

(78 reference statements)

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“…The literature search resulted in 59 papers for “genotoxicity & 3D in vitro model”, 73 papers for “genotoxicity & advanced in vitro model”, 134 papers for “genotoxicity & high throughput”, eight papers for “genotoxicity & high throughput & nanomaterials” [ 15 , 16 , 17 , 18 , 19 , 20 , 21 ] and six papers for “genotoxicity & high throughput & nanoparticles” (4 are the same as for “genotoxicity & high throughput & nanomaterials”) [ 16 , 17 , 18 , 19 , 21 , 22 ], seven papers for “genotoxicity & organ on chip“ [ 23 , 24 , 25 , 26 , 27 , 28 , 29 ], seven papers for “genotoxicity & 3D models & nanoparticles” [ 30 , 31 , 32 , 33 , 34 , 35 , 36 ], 11 papers for “genotoxicity & 3D models & nanomaterials” [ 30 , 31 , 33 , 36 , 37 , 38 , 39 , 40 , 41 ] for the period of 20 years (2000–2020), whereby the year 2020 was considered only from January to August. ( Table 1 ).…”

Section: Results Of Literature Searchmentioning

confidence: 99%

Genotoxicity of Nanomaterials: Advanced In Vitro Models and High Throughput Methods for Human Hazard Assessment—A Review

et al. 2020

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Changes in the genetic material can lead to serious human health defects, as mutations in somatic cells may cause cancer and can contribute to other chronic diseases. Genotoxic events can appear at both the DNA, chromosomal or (during mitosis) whole genome level. The study of mechanisms leading to genotoxicity is crucially important, as well as the detection of potentially genotoxic compounds. We consider the current state of the art and describe here the main endpoints applied in standard human in vitro models as well as new advanced 3D models that are closer to the in vivo situation. We performed a literature review of in vitro studies published from 2000–2020 (August) dedicated to the genotoxicity of nanomaterials (NMs) in new models. Methods suitable for detection of genotoxicity of NMs will be presented with a focus on advances in miniaturization, organ-on-a-chip and high throughput methods.

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Section: Results Of Literature Searchmentioning

confidence: 99%

Genotoxicity of Nanomaterials: Advanced In Vitro Models and High Throughput Methods for Human Hazard Assessment—A Review

et al. 2020

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“…Epigenetic effects of 1,3-butadiene are well established and have been studied in multiple tissues of male mice (Chappell et al 2017;Israel et al 2018;Koturbash et al 2011). These studies demonstrated that there are organ-and strain-dependent effects.…”

Section: Introductionmentioning

confidence: 98%

Sex-specific differences in genotoxic and epigenetic effects of 1,3-butadiene among mouse tissues

et al. 2018

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Exposure to environmental chemicals has been shown to have an impact on the epigenome. One example is a known human carcinogen 1,3-butadiene which acts primarily by a genotoxic mechanism, but also disrupts the chromatin structure by altering patterns of cytosine DNA methylation and histone modifications. Sex-specific differences in 1,3-butadiene-induced genotoxicity and carcinogenicity are well established; however, it remains unknown whether 1,3butadiene-associated epigenetic alterations are also sex-dependent. Therefore, we tested the hypothesis that inhalational exposure to 1,3-butadiene will result in sex-specific epigenetic alterations. DNA damage and epigenetic effects of 1,3-butadiene were evaluated in in liver, lung, and kidney tissues of male and female mice of two inbred strains (C57BL/6J and CAST/EiJ). Mice were exposed to 0 or 425 ppm of 1,3-butadiene by inhalation (6 hr/day, 5 days/week) for 2 weeks. Strain-and tissue-specific differences in 1,3-butadiene-induced DNA adducts and crosslinks we detected in the liver, lung and kidney; however, significant sex-specific differences in DNA damage were observed in the lung of C57BL/6J mice only. In addition, we assessed expression of the DNA repair genes and observed a marked up-regulation of Mgmt in the kidney in female C57BL/6J mice. Sex-specific epigenetic effects of 1,3-butadiene exposure were evident in alterations of cytosine DNA methylation and histone modifications in the liver and lung in both strains. Specifically, we observed a loss of cytosine DNA methylation in the liver and lung of male and female 1,3-butadiene-exposed C57BL/6J mice, whereas hypermethylation was found in the liver and lung in 1,3-butadiene-exposed female CAST/EiJ mice. Our findings suggest that strain and sex-specific effects of 1,3-butadiene on the epigenome may contribute to the known differences in cancer susceptibility.

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“…Our simulated ATAC-seq data suggested that DESeq/ DESeq2 had better specificity and edgeR had a better sensitivity. To better evaluate the performance of different methods in real ATAC-seq differential analysis, we first downloaded published ATAC-seq data of mouse liver and kidney 23 . In this analysis, six liver samples and six kidney samples were included [ Fig.…”

Section: Performance Of Deseq2 Limma and Edger In Differential Analmentioning

confidence: 99%

“…Down-sampling of ATAC-seq data. ATAC-seq data of mouse liver and kidney 39 , DLFC 24 , and human cartilage 33 were downloaded from GEO, and the QC check, data processing, and peak calling were performed by using AIAP (https://github.com/Zhang-lab/ATAC-seq_QC_analysis) 30 . Peaks identified in all samples were merged together if they had ≥1 bp overlap to generate common open chromatin regions (OCRs).…”

Section: Fpr Tpr Recall and Roc Curvesmentioning

confidence: 99%

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Comparison of differential accessibility analysis strategies for ATAC-seq data

Gontarz

Xing³

et al. 2020

Sci Rep

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ATAC-seq is widely used to measure chromatin accessibility and identify open chromatin regions (OCRs). OCRs usually indicate active regulatory elements in the genome and are directly associated with the gene regulatory network. The identification of differential accessibility regions (DARs) between different biological conditions is critical in determining the differential activity of regulatory elements. Differential analysis of ATAC-seq shares many similarities with differential expression analysis of RNAseq data. However, the distribution of ATAC-seq signal intensity is different from that of RNA-seq data, and higher sensitivity is required for DARs identification. Many different tools can be used to perform differential analysis of ATAC-seq data, but a comprehensive comparison and benchmarking of these methods is still lacking. Here, we used simulated datasets to systematically measure the sensitivity and specificity of six different methods. We further discussed the statistical and signal density cutoffs in the differential analysis of ATAC-seq by applying them to real data. Batch effects are very common in high-throughput sequencing experiments. We illustrated that batch-effect correction can dramatically improve sensitivity in the differential analysis of ATAC-seq data. Finally, we developed a user-friendly package, BeCorrect, to perform batch effect correction and visualization of corrected ATAC-seq signals in a genome browser. Gene regulation in the mammalian genome involves different types of regulatory elements, such as promoters, enhancers, and insulators. It was estimated that there are over two million regulatory elements in the human and mouse genomes 1,2 , and these regulatory elements recruit different epigenetic modifications to regulate the expression of genes in cell type-specific and developmental stage-specific manners 3-5. Active regulatory elements must remain in an accessible state to allow the binding of different transcription factors to activate or silence target genes. ATAC-seq (assay for transposase-accessible chromatin followed by sequencing) is a recently developed technique to measure genome-wide chromatin accessibility (or open chromatin) 6,7. Compared with other techniques, such as DNase-seq, Mnase-seq, and FAIRE-seq, ATAC-seq experiments are relatively easier to perform across different tissues and cell types. Furthermore, ATAC-seq experiments allow ultra-low input cell numbers, even down to the single-cell level 8. These advantages propelled ATAC-seq to be the most widely used technology to define open chromatin by many large genomics consortiums, including ENCODE 9 , TCGA 10 , PsychENCODE 11 , IHEC 12 , and TaRGET II 13. The peak-calling analysis used to identify open chromatin regions (OCRs) by using ATAC-seq is generally adapted from ChIP-seq data analysis. However, there are fundamental differences between ATAC-seq and ChIP-seq-most notably that ATAC-seq is performed without control or input samples. Nonetheless, peak callers, such as macs2 14 , can identify OCRs by evalua...

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Tissue- and strain-specific effects of a genotoxic carcinogen 1,3-butadiene on chromatin and transcription

Cited by 21 publications

References 43 publications

Genotoxicity of Nanomaterials: Advanced In Vitro Models and High Throughput Methods for Human Hazard Assessment—A Review

Genotoxicity of Nanomaterials: Advanced In Vitro Models and High Throughput Methods for Human Hazard Assessment—A Review

Sex-specific differences in genotoxic and epigenetic effects of 1,3-butadiene among mouse tissues

Comparison of differential accessibility analysis strategies for ATAC-seq data

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