Impact of CAR Agonist Ligand TCPOBOP on Mouse Liver Chromatin Accessibility

Impact of CAR Agonist Ligand TCPOBOP on Mouse Liver Chromatin Accessibility Abstract Activation of the nuclear receptor and transcription factor CAR (Nr1i3) by its specific agonist ligand TCPOBOP (1, 4-bis[2-(3, 5-dichloropyridyloxy)]benzene) dysregulates hundreds of genes in mouse liver and is linked to male-biased hepatocarcinogenesis. To elucidate the genomic organization of CAR-induced gene responses, we investigated the distribution of TCPOBOP-responsive RefSeq coding and long noncoding RNA (lncRNA) genes across the megabase-scale topologically associating domains (TADs) that segment the genome, and which provide a structural framework that functionally constrains enhancer-promoter interactions. We show that a subset of TCPOBOP-responsive genes cluster within TADs, and that TCPOBOP-induced genes and TCPOBOP-repressed genes are often found in different TADs. Further, using DNase-seq and DNase hypersensitivity site (DHS) analysis, we identified several thousand genomic regions (ΔDHS) where short-term exposure to TCPOBOP induces localized changes (increases or decreases) in mouse liver chromatin accessibility, many of which cluster in TADs together with TCPOBOP-responsive genes. Sites of chromatin opening were highly enriched nearby genes induced by TCPOBOP and chromatin closing was highly enriched nearby genes repressed by TCPOBOP, consistent with TCPOBOP-responsive ΔDHS serving as enhancers and promoters that positively regulate CAR-responsive genes. Gene expression changes lagged behind chromatin opening or closing for a subset of TCPOBOP-responsive ΔDHS. ΔDHS that were specifically responsive to TCPOBOP in male liver were significantly enriched for genomic regions with a basal male bias in chromatin accessibility; however, the male-biased response of hepatocellular carcinoma-related genes to TCPOBOP was not associated with a correspondingly male-biased ΔDHS response. These studies elucidate the genome-wide organization of CAR-responsive genes and of the thousands of associated genomic sites where TCPOBOP exposure induces both rapid and persistent changes in chromatin accessibility. gene expression/regulation, receptor, nuclear hormone, gene expression/regulation, bioinformatics, methods, hepatic, systems toxicology, DNase-Seq, cytochrome P450, biotransformation and toxicokinetics, constitutive androstane receptor The role of xenochemical receptors, including CAR (constitutive androstane receptor; Nr1i3) (Kobayashi et al., 2015; Yan and Xie, 2016), in the disruptive actions of environmental chemicals on gene expression has long been recognized; however, progress in understanding underlying mechanisms of action has been hampered by the complexity of gene responses and the multiplicity of pathways involved. CAR is activated by structurally diverse environmental chemicals derived from consumer products, pharmaceuticals, and industrial chemicals (Baldwin and Roling, 2009; Chang and Waxman, 2006; DeKeyser et al., 2011; Eveillard et al., 2009; Ito et al., 2012; Omiecinski et al., 2011; Ren et al., 2010). Notable examples of foreign chemical CAR activators include bisphenol-A, a xenoestrogen, DEHP, a phthalate ester and rodent hepatocarcinogen, and TCPOBOP (1, 4-bis[2-(3, 5-dichloropyridyloxy)]benzene), a potent and highly specific agonist ligand of CAR (Tzameli et al., 2000). Activation of CAR by TCPOBOP induces diverse pathogenic responses, including hepatomegaly, liver tumor promotion, and hepatocarcinogenesis (Diwan et al., 1992; Huang et al., 2005; Yamamoto et al., 2004), as well as nonalcoholic steatohepatitis (Takizawa et al., 2011; Yamazaki et al., 2007). The transcriptional effects of CAR in the liver have recently been characterized on a transcriptome-wide basis by RNA-seq (Cui and Klaassen, 2016; Lodato et al., 2017), which is more reliable in distinguishing RNAs from closely related genes in a family or superfamily than microarray technology, and has allowed us to elucidate early, nuclear transcriptomic changes in both male and female mouse liver, including changes in the expression of many liver-expressed (Melia et al., 2016) long noncoding RNA (lncRNA) genes (Lodato et al., 2017). Environmental chemicals have widespread effects on the epigenome, which is a key determinant of the responsiveness of the genome to chemical exposure, the persistence of effects, and overall biological outcomes (Bowers and McCullough, 2017; Tapia-Orozco et al., 2017). Environmental chemicals may impact the genome by covalent modification of histone tails (chromatin marks), leading to altered recruitment of factors that control DNA compaction, chromatin accessibility, and the availability of genomic DNA for transcription factor binding. Changes in DNA methylation of gene regulatory regions also occur (Messerlian et al., 2017), but are largely secondary to the loss of chromatin accessibility and transcription factor binding (Stadler et al., 2011; Thurman et al., 2012). Although there are many descriptive studies of the epigenetic effects of environmental chemicals (Burris and Baccarelli, 2014; Casati et al., 2015; Thomson et al., 2014), far less is known about the underlying mechanisms whereby foreign chemical exposure induces such changes and their relationship to changes in gene expression. Changes in chromatin accessibility are a hallmark of epigenetic regulation and developmental plasticity, and can be identified on a genome-wide basis by limited DNase-I digestion of isolated nuclei followed by massively parallel sequencing (DNase-Seq) to discover DNase-I hypersensitive sites (DHS) (Ling et al., 2010; Thurman, et al., 2012). DHS encompass a large fraction of functional cis-regulatory elements (notably, promoters, enhancers, silencers, and insulators) in mammalian cells (Shlyueva et al., 2014), including mouse liver (Sugathan and Waxman, 2013; Yue et al., 2014). Recent advances led by the Mouse ENCODE Consortium have identified several hundred thousand putative regulatory elements across many mouse cell lines and tissues, including liver, through a combination of DNase-seq and ChIP-seq analysis of histone modifications and transcription factor binding sites (Yue et al., 2014). However, the tissue samples analyzed were not subjected to any experimental treatments and thus the datasets produced have not identified regulatory elements that are dynamically activated or repressed following exposure to foreign chemicals, including those that activate transcription factors such as CAR. Historically, our understanding of how genomes are organized was based on a few select locus control regions that were known to influence the expression of genes regionally, within a localized cluster (Fraser and Grosveld, 1998). More recent studies reveal a segmentation of the mammalian genome into megabase-scale chromatin loops known as topologically associating domains (TADs) that are largely conserved between tissues (Bonev and Cavalli, 2016; Rao et al., 2014). TADs are identified as contact domains visualized in Hi-C interaction maps (Rowley et al., 2017) and are delineated by looped chromatin structures whose boundaries are established by the DNA-binding protein CTCF and the ring-shaped cohesin complex (Hansen et al., 2018). Importantly, the genomic architecture and chromatin structure within TADs play an important role in constraining potential contacts between promoters and distal enhancers to intra-TAD genomic sequences. Thus, a refined approach to identifying DNA regulatory elements that control target gene expression is to limit the consideration to interactions within TAD boundaries. Further, the insulated DNA loops that TADs form may allow for rapid, coordinated gene regulation of gene families within localized genomic clusters (Le Dily and Beato, 2015). Here, we characterize the TAD-based organization of TCPOBOP-responsive RefSeq and lncRNA genes (Lodato et al., 2017) to elucidate the structural and functional organization of CAR-responsive gene targets across the genome. We also use DNase-seq to identify several thousand sites (ΔDHS regions) where TCPOBOP exposure induces a significant change in chromatin accessibility, and we relate these ΔDHS to TAD organization and TCPOBOP-induced gene expression changes. Finally, we investigate the link between basal sex differences in gene expression and chromatin accessibility, TADs that show sex-dependent responses to TCPOBOP, and male-biased transcriptional responses associated with hepatocarcinogenesis. MATERIALS AND METHODS Animal procedures and liver extraction All animal work was conducted in accordance with accepted standards of humane animal care, in compliance with procedures and protocols approved by the Boston University Institutional Animal Care and Use Committee. Animal handling and treatments were performed as described previously (Lodato, et al., 2017). Briefly, male and female CD1 mice (ICR strain), 7-weeks old, were purchased from Charles River Laboratories (Wilmington, MA) and kept on a 12-h light cycle (7:30 am–7:30 pm). Mice were treated with TCPOBOP (Sigma, catalog no. T1443) at a dose of 3 mg/kg body weight or with vehicle alone (corn oil containing 1% DMSO) by i.p. injection between 8:00 am and 8:45 am on day 1. Livers were collected 3 h later, or after 27 h (3 h + 24 h), ie, between 11:00 am and 11:45 am on day 2, to control for the strong effects of circadian rhythm on gene expression in mouse liver (Kettner et al., 2016). Nuclei were isolated from individual vehicle-treated (control) and TCPOBOP-treated mouse livers as described (Lodato et al., 2017). Briefly, fresh liver tissue was homogenized in buffer on ice in a Potter-Elvehjem homogenizer. The homogenate was layered on fresh homogenization buffer and spun at 4°C in an ultracentrifuge for 35 min at 25 000 rpm. For DNase-I hypersensitivity assays (see below), pellets containing approximately 150 million nuclei were resuspended in 400 μl of nuclei storage buffer and stored at −80°C until used for DNase-I digestion and DHS analysis. DNase-I hypersensitivity assay Frozen liver nuclei in nuclei storage buffer, corresponding to ∼30 million nuclei, were rinsed three times in ice-cold Buffer A (15 mM Tris-Cl pH 8.0, 15 mM NaCl, 60 mM KCl, 1 mM EDTA pH 8.0, 0.5 mM EGTA pH 8.0, 0.5 mM spermidine, 0.3 mM spermine tetrahydrochloride) by adding 500 μl Buffer A and pelleting the nuclei at 1500 rpm for 10 min at 4°C. Following the final rinse, nuclear pellets were resuspended in Buffer D (Buffer A + 6 mM CaCl2, 75 mM NaCl) prewarmed to 37°C, to give a concentration of 5 × 106 nuclei per 0.85 ml. A total of 32 units of DNase-I enzyme (RQ1 RNase-Free DNase, 1 U/μl; Promega, catalog no. M610A) was added to 68 μl of prewarmed Buffer D in a 2-ml tube and incubated for 30 s at 37°C. The 0.85 ml containing 5 × 106 resuspended nuclei was added to the 2-ml tube and digested with DNase I for precisely 2 min. After 2 min, 950 μl of Stop Buffer (50 mM Tris-HCl pH 8.0, 100 mM NaCl, 0.1% [v/v] SDS, 100 mM EDTA pH 8.0, 1 mM spermidine, 0.3 mM spermine tetrahydrochloride, 20 μg/ml RNase A) was added and the sample was immediately placed in a 55°C water bath. DNase-I digestion was carried out using a total of 30 million nuclei per mouse liver, divided into six separate reaction tubes, which were processed in parallel for DNase digestion. Samples were then incubated at 55°C for >15 min. About 5 μl proteinase K was then added, and the samples were further incubated at 55°C overnight. The six parallel DNase digestions were pooled and the DNA was isolated by phenol: chloroform extraction. The final supernatant was adjusted to 0.8 M NaCl. Digested material was size selected by sucrose gradient centrifugation as follows. First, phenol: chloroform extracted material (11.4 ml) was loaded on a sucrose gradient containing the following layers (bottom to top): 12 ml of 20% sucrose buffer (20 mM Tris-HCl pH 8.0, 5 mM EDTA pH 8.0, 1 M NaCl, containing 20% sucrose) and then 3 ml each of 17.5%, 15.0%, 12.5%, and 10.0% sucrose buffer, for a total volume of 34.5 ml. The sucrose gradient was centrifuged at 25 000 rpm for 24 h at 25°C. Fractions (1.9 ml) were sequentially removed from the top of the gradient, and fractions numbered 7–11, corresponding to digested material ∼100 bp to ∼1000 bp in length, were isolated and pooled. Material from fractions 7–11 was further purified on a QIAprep 2.0 spin column (Qiagen) according to the manufacturer’s manual. Agencount AMPure XP bead purification was performed using the manufacturer’s protocol with ratios of 0.6x and 1.9x for double-sided size selection, designed to obtain 125–400 bp DNA fragments. DNase-seq libraries, sequencing, and data analysis DNase-seq was performed for each of the following four treatment groups and four control groups: livers from male and female mice treated with TCPOBOP for either 3 or 27 h (ie, four TCPOBOP treatment groups), and sex- and time-matched vehicle control (ie, four control groups). Two sequence libraries (biological replicate pools) were prepared for each of the 8 groups, for a total of 16 sequence libraries. Each biological replicate pool consisted of genomic DNA fragments released by DNase-I digestion of nuclei prepared from n = 3–5 individual livers as follows: DNase-I digestion reactions were set up in parallel using nuclei isolated from 3 to 5 individual mouse livers. DNase-released fragments were purified from each of the individual reactions, as described above, and then combined to give a single sample, which was used to prepare a single sequencing library. A second (biological replicate) sequence library was prepared in the same manner by digestion of nuclei isolated from n = 3–5 other livers from mice in the same treatment or control group. Each sequencing library was prepared from 5 ng of the pooled DNase-I released DNA fragments using the NEBNext Ultra DNA Library Prep Kit for Illumina (New England Biolabs). Sequencing was performed at the New York Genome Center (New York, New York) on an Illumina HiSeq-2500 instrument, and single-end sequence reads, 50 bp in length, were obtained at a sequencing depth ranging from 33 to 79 million total mapped reads for each condition. More detailed sequencing statistics are shown in Supplementary Table 1A. Raw and processed data are available at www.ncbi.nlm.nih.gov/gds under accession GSE104061. Sequencing data was analyzed using a custom DNase-seq pipeline. The pipeline processes raw FASTQ files and outputs various quality control metrics, including FASTQC reports (FASTX-Toolkit v0.0.13.2), confirmation of read length, verification of the absence of read strand bias, quantification of contaminating adapter sequence (Trim_galore v0.4.2). Reads were mapped to the mouse genome (release mm9) using Bowtie2 (v2.2.6) (Langmead et al., 2009). Regions of DNase hypersensitivity (DHS) were discovered as peaks identified by MACS2 (v2.1.0.20150731) (Zhang et al., 2008) using the options (–nomodel –shift-100 –extsize 200), to inhibit read shifting, and (–keep-dup), to retain all reads that contribute to a peak signal. Peaks were discovered for each of n = 4 DNase-seq samples per TCPOBOP treatment condition, ie, n = 2 vehicle-treated and n = 2 TCPOBOP-treated DNase-seq samples (n = 2 biological replicate pools, as described above) × 4 conditions (male and female, at 3 and 27 h). The final DHS peak list was filtered to remove ENCODE blacklisted regions (Consortium, 2012) as well as peaks comprised of >4 identical reads that do not overlap any other read (“straight peaks”). The 16 resultant DHS peak lists were merged using mergeBed (BEDtools) to give a single list of 61 220 DHS regions, corresponding to the union of all DHS peak regions. A subset comprised of 60 739 DHS mapped to TADs with at least one RefSeq or multi-exonic lncRNA gene (Supplementary Table 1B), and was used for all downstream analyses, which were TAD and gene target based. The 481 DHS omitted from these downstream analyses are listed in Supplementary Table 1C. DHS peak normalization DHS regions to be visualized in the UCSC genome browser (https://genome.ucsc.edu/, last accessed date April 9, 2018) were normalized using sequence reads in each DHS peak region per million mapped sequence reads (reads-in-peaks-per-million, RiPPM) as a scaling factor. First, to obtain a comprehensive list of DHS peak regions for each dataset (termed peak union), FASTQ files from individual biological replicates were concatenated to produce combined replicates. For each DNase-seq dataset, we generated a vehicle-treated combined sample, a TCPOBOP-treated combined sample, and an all-replicates (vehicle-treated + TCPOBOP-treated) combined sample. DHS peak regions identified in the individual and combined samples were concatenated into a single file, and then BEDtools merge was used to combine overlapping features to generate a single list of nonoverlapping DHS peaks. The fraction of reads in peaks for each sample was then calculated to obtain a scaling factor. Raw read counts were divided by this per-million scaling factor to obtain RiPPM normalized read counts. ΔDHS and static DHS Genomic regions that were more open or more closed (|fold-change| > 2 and FDR < 0.05 [Benjamini-Hochberg adjusted p-value]) following TCPOBOP exposure were discovered by diffReps analysis (Shen et al., 2013) using the nucleosome option (200 bp window size) and setting (–frag) to zero for all comparisons. diffReps-identified regions that overlap the set of 60 739 merged DHS regions that map to a TAD with one or more genes (Supplementary Table 1B; see above), as determined using BEDtools (Quinlan and Hall, 2010), were designated ΔDHS (ie, DHS regions that significantly open or that close under each condition of TCPOBOP exposure). In some cases, the diffReps-identified region was narrower than the overlapping merged DHS. A ΔDHS was designated robust if there was a >2-fold difference in normalized sequence read counts across the entire merged DHS region between the TCPOBOP-treated and vehicle control liver samples, based on read counts combined over all biological replicates for the exposure condition. All other ΔDHS regions were designated standard ΔDHS. The combined list of robust + standard ΔDHS was used in all analyses, except where noted. The subset of the 60 739 DHS regions that did not overlap a diffReps region were designated static DHS for that condition of TCPOBOP exposure. 55 866 of the 60 739 DHS regions did not show significant chromatin opening or closing under any of the four TCPOBOP exposures studied here, and were used for enrichment analysis (see below). DHS were mapped to TADs using BEDtools, based on genomic boundaries for each of 3617 mouse liver TADs defined previously (Vietri Rudan et al., 2015) (Supplementary Table 2A) and a minimum of 1 bp overlap, as listed in Supplementary Table 2B. A small number of DHS overlapped two TADs (ie, the DHS spanned a TAD boundary); these were arbitrarily assigned to the lower number TAD. A total of 148 of the TAD regions did not contain any RefSeq or liver-expressed multi-exonic lncRNA genes. Mapping of TCPOBOP-responsive genes to DHS and to TADs RefSeq and lncRNA genes that were significantly induced or repressed in male and/or in female mouse liver after 3 or 27 h TCPOBOP exposure were identified (Lodato et al., 2017) based on a gene list comprised of 24 197 RefSeq genes and 3152 multi-exonic lncRNA genes. The TCPOBOP-responsive gene sets used here were defined by a |fold change| >1.5 and adjusted p-value (FDR) <.001 (for RefSeq genes), and by |fold change| >2 and adjusted p-value (FDR) <.05 (lncRNA genes). A single putative gene target (RefSeq or lncRNA gene) was assigned to each DHS by using BEDtools to map each of the 60 739 DHS to the closest gene transcription start site within the same TAD (see above). Supplementary Table 1B presents the putative gene target of each of the 60 739 DHS and the gene’s response to each condition of TCPOBOP exposure, as well as the response of each DHS to TCPOBOP exposure (ΔDHS and static DHS). The number of genes within each TAD that were upregulated or downregulated by TCPOBOP exposure, and the number of opening and closing ΔDHS within each TAD, were counted for each of the four TCPOBOP exposures and are shown in Supplementary Table 2B. Enrichment analysis Enrichments of ΔDHS mapping to TCPOBOP-responsive genes were calculated for each ΔDHS set (eg, DHS that open in male liver after 3 h TCPOBOP exposure, and genes upregulated in male liver by that same exposure) as follows: Enrichment score = ratio A/ratio B, where: ratio A = number of ΔDHS that respond to a given TCPOBOP exposure that map to the corresponding set of TCPOBOP-responsive genes, divided by the number of ΔDHS from that same ΔDHS set whose putative target gene does not show the corresponding response to TCPOBOP at that time point; and ratio B = the number of static DHS mapping to the same given set of correspondingly TCPOBOP-responsive genes, divided by the number of static DHS whose putative target gene does not show the corresponding response to TCPOBOP. For example, in males treated with TCPOBOP for 3 h, 70 ΔDHS that open each map to a 3 h TCPOBOP-induced gene, and 402 other ΔDHS that open each map to a gene that is not induced by the same TCPOBOP exposure (70/402 = 0.174), whereas 393 static DHS each map to a 3 h TCPOBOP-induced gene, and 55 473 static DHS each map to a gene not induced by the same TCPOBOP exposure (393/55 473 = 0.007), which gives an enrichment score = 24.6 (A/B = 0.174/0.007 = 24.9). The static DHS used for these enrichment calculations correspond to the set of 55 866 DHS (393 + 55 473, in the above example) that map to a TAD containing at least one gene, and do not show DHS opening or DHS closing at any of the 4 TCPOBOP exposure conditions. Genes that are downstream targets of 10 known CAR-dependent upstream regulators of liver carcinogenesis (hepatocellular carcinoma, HCC), namely cyclin D1, p53, p21, FoxO1, FoxM1, Rb, β-catenin, E2f, Yap, and Myc, were those identified previously (Lodato et al., 2017). The sex bias in the 27 h TCPOBOP-induced ΔDHS that map to the downstream gene targets of these 10 HCC upstream regulators was calculated as follows: Enrichment score = ratio A/ratio B, where: ratio A = (27 h TCPOBOP-induced male liver ΔDHS that map to the HCC target gene set)/(all male liver DHS associated with those target genes); and ratio B = (27 h TCPOBOP-induced female liver ΔDHS that map to the HCC target gene set)/(all female liver DHS associated with those target genes). Enrichments were calculated for the following sets of HCC target genes: all downstream target genes of the 10 regulators (n = 4336 genes); all downstream targets that are TCPOBOP responsive (n = 378 genes); all downstream targets that are induced by 27 h TCPOBOP exposure in male liver but not in female liver (n = 153 genes); and all downstream targets that are induced by 27 h TCPOBOP exposure in both male and female liver or in female liver only (n = 225 genes) (Supplementary Table 3) (Lodato et al., 2017). Sex-biased TCPOBOP-responsive TADs and sex-biased genes and DHS TADs with at least two genes responsive to 27 h TCPOBOP exposure (RefSeq and/or lncRNA genes, using the thresholds for responsiveness defined above) were considered to have a sex-biased TCPOBOP response if all of the responsive genes in the TAD respond to TCPOBOP in one sex but not the other. For example, a TAD with three TCPOBOP-responsive genes was considered to be male-biased in its responsiveness if all three genes responded to 27 h TCPOBOP exposure in male but not female liver. Likewise, a TAD was considered female-biased if it contains two or more genes that responded to 27 h TCPOBOP exposure in female but not male liver. We did not require that all of the responsive genes within the TAD respond in the same direction, eg, one gene may be upregulated and two may be downregulated; however, all three genes must respond in the same sex to qualify. The numbers of TADs with single versus multiple TCPOBOP-responsive genes are shown in Supplementary Table 4, and the number of ΔDHS associated with those TADs are shown in Supplementary Table 5. Genes that showed a basal sex bias in expression at FDR < 0.01 (corresponding to minimum fold change of ∼1.4) were identified using a nuclear, polyA-selected RNA-seq dataset comprised of n = 3 sequencing libraries per sex (Connerney et al., 2017), with each library prepared from a pool of nuclear RNA samples derived from n = 8 to 11 individual mouse livers. A total of 597 such basal male-biased and 559 basal female-biased RefSeq genes were identified, as were 309 basal male-biased and 203 basal female-biased lncRNAs. Genomic regions with a basal sex bias in chromatin accessibility (2800 male-biased DHS and 1379 female-biased DHS) were part of a set of ∼72 000 mouse liver DHS identified earlier (Ling et al., 2010) and were overlapped with the set of 60 739 mouse liver DHS described here. TADs with a sex-biased response to TCPOBOP exposure (Supplementary Table 6A) and TADs with basally sex-biased DHS, as defined previously for untreated male and female mouse liver (Ling et al., 2010), are shown in Supplementary Table 6B. Statistical analysis Fisher Exact test was implemented in the analysis package R to assess the statistical significance of enrichment calculations. Student t test was implemented using Prism 7 (GraphPad) to assess pair-wise relationships. RESULTS TCPOBOP-Induced Genes Cluster in Different TADs Than TCPOBOP-Repressed Genes Mammalian genomes are functionally segmented into large megabase-scale DNA loops, called TADs. TADs insulate genomic regions by allowing for intra-TAD interactions while inhibiting inter-TAD interactions (Oti et al., 2016) and provide a structural framework that can facilitate coordinated transcriptional responses to stimuli (Le Dily and Beato, 2015). TAD boundaries are established for the 3617 TADs in mouse liver (Vietri Rudan et al., 2015), and can be used to map TCPOBOP-responsive genes (Lodato et al., 2017) to individual TAD regions. In male mouse liver, 173 genes that responded to 3 h TCPOBOP exposure (see Materials and Methods section) were distributed across 119 TAD regions, whereas in female liver, 287 genes responded to the same treatment and were distributed across 203 TADs (Figure 1A, Supplementary Table 4). The number of TAD regions with TCPOBOP-responsive genes increased up to 6-fold after 27 h, encompassing 14%–19% of all mouse liver TADs. Thus, TCPOBOP-responsive genes are widely distributed across the genome. Figure 1. View largeDownload slide TCPOBOP-responsive genes cluster in TADs. A, Distribution of the number of TADs that contain either a single TCPOBOP-responsive gene or multiple TCPOBOP-responsive genes in livers of mice treated with TCPOBOP for 3 or 27 h. Blue, TADs that contain gene(s) upregulated by TCPOBOP; red, TADs that contain gene(s) downregulated by TCPOBOP; gray, TADs that contain both upregulated genes and downregulated genes. Darker shades of blue and red indicate TADs with multiple TCPOBOP-responsive genes all responding in the same direction, as indicated. Pie chart sections are ordered as follows (counterclockwise): mixed, down (multiple, single), up (multiple, single). B, Percent of TADs with multiple TCPOBOP-responsive genes where all of the responsive genes in the TAD are either upregulated (blue), downregulated (red), or show a mixture of up and downregulatory responses (gray). See Supplementary Table 2B for a full listing of TCPOBOP-responsive TADs and the corresponding numbers of up and downregulated genes in each exposure group, and see Supplementary Table 4 for aggregate gene and TAD numbers (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 1. View largeDownload slide TCPOBOP-responsive genes cluster in TADs. A, Distribution of the number of TADs that contain either a single TCPOBOP-responsive gene or multiple TCPOBOP-responsive genes in livers of mice treated with TCPOBOP for 3 or 27 h. Blue, TADs that contain gene(s) upregulated by TCPOBOP; red, TADs that contain gene(s) downregulated by TCPOBOP; gray, TADs that contain both upregulated genes and downregulated genes. Darker shades of blue and red indicate TADs with multiple TCPOBOP-responsive genes all responding in the same direction, as indicated. Pie chart sections are ordered as follows (counterclockwise): mixed, down (multiple, single), up (multiple, single). B, Percent of TADs with multiple TCPOBOP-responsive genes where all of the responsive genes in the TAD are either upregulated (blue), downregulated (red), or show a mixture of up and downregulatory responses (gray). See Supplementary Table 2B for a full listing of TCPOBOP-responsive TADs and the corresponding numbers of up and downregulated genes in each exposure group, and see Supplementary Table 4 for aggregate gene and TAD numbers (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Next, we investigated whether TCPOBOP-responsive genes cluster in TADs. In both sexes, ∼20%–30% of the TADs with genes responding to TCPOBOP contain multiple (up to 12) TCPOBOP-responsive genes. These TADs encompass 44%–52% of all genes that respond to TCPOBOP under a given condition (Supplementary Table 4). TADs that contain multiple TCPOBOP-responsive genes were further classified by the concurrence of the directionality of TCPOBOP gene responses within the TAD. A majority (64%–91%) of TADs with multiple TCPOBOP-responsive genes showed consistent regulation within the TAD, ie, all of the TCPOBOP genes within the TAD are either upregulated or are downregulated (Figure 1B). Overall, the TADs with clustered, consistently responding genes encompass 31%–38% of all TCPOBOP-responsive genes (Supplementary Table 4). TCPOBOP Induces Widespread Changes in Chromatin Accessibility The impact of TCPOBOP on liver chromatin accessibility was determined by limited DNase digestion of liver nuclei harvested from vehicle control and from TCPOBOP-exposed mice. DNase-seq analysis of the genomic DNA fragments released by DNase digestion identified accessible chromatin regions (DNase hypersensitive sites, DHS), which encompass up to 90% of binding sites for liver-expressed transcription factors (Ling et al., 2010). DNase-seq signals were analyzed using diffReps (Shen et al., 2013) to discover genomic regions where TCPOBOP exposure induces a significant change in chromatin accessibility (ΔDHS regions) in either male or female liver (Figure 2A, Supplementary Table 1B). We found that TCPOBOP exposure stimulated DHS opening as well as DHS closing, with 500–600 ΔDHS regions seen 3 h after TCPOBOP exposure, and ∼2000–3000 ΔDHS regions seen after 27 h. The large increase in ΔDHS in the 27 h TCPOBOP-exposed livers is consistent with the larger number of genes and greater magnitude of gene induction responses in liver nuclei after 27 h compared with after 3 h TCPOBOP exposure (Lodato et al., 2017). Further, a majority ΔDHS were unique to one sex (Figure 2B), consistent with the sex differences in gene responses to TCPOBOP exposure described previously (Lodato et al., 2017). Figure 2. View largeDownload slide TCPOBOP-induced chromatin opening and closing: ΔDHS regions. A, Venn diagrams showing overlap of TCPOBOP-induced ΔDHS regions after 3 h versus 27 h exposure. B, Overlap of ΔDHS regions between male and female mouse liver at each TCPOBOP time point. ΔDHS regions were identified for each TCPOBOP exposure condition based on the merged list of 60 739 DHS regions (Supplementary Table 1B). Only ΔDHS that responded in the same direction at the time points compared (A) or in the comparison of sexes (B) were considered overlapping (eg, ΔDHS that open in males at 3 h and ΔDHS that open in males at 27 h; ΔDHS that close in males at 3 h and ΔDHS that close in males at 27 h, etc.). Up to 3 ΔDHS in each dataset showed inconsistent responses to TCPOBOP at 3 h versus 27 h (A), or between male and female livers (B), and were excluded from the numbers shown. C, ΔDHS regions shown in (A) are separated into sets of ΔDHS that open (left) or close (right) for each TCPOBOP exposure, and are counted based on whether they do (black) or do not (gray) contain at least one TCPOBOP-responsive gene at that time point whose transcription start site is in the same TAD as the ΔDHS region. D, ΔDHS regions that open or close and contain at least one TCPOBOP-responsive gene (black bars in C) are colored to indicate whether the TCPOBOP-responsive genes within the same TAD as the ΔDHS are all upregulated (red), downregulated (blue), or mixed with regard to the directionality of their responses to TCPOBOP (black). See Supplementary Table 5 for a more detailed listing (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 2. View largeDownload slide TCPOBOP-induced chromatin opening and closing: ΔDHS regions. A, Venn diagrams showing overlap of TCPOBOP-induced ΔDHS regions after 3 h versus 27 h exposure. B, Overlap of ΔDHS regions between male and female mouse liver at each TCPOBOP time point. ΔDHS regions were identified for each TCPOBOP exposure condition based on the merged list of 60 739 DHS regions (Supplementary Table 1B). Only ΔDHS that responded in the same direction at the time points compared (A) or in the comparison of sexes (B) were considered overlapping (eg, ΔDHS that open in males at 3 h and ΔDHS that open in males at 27 h; ΔDHS that close in males at 3 h and ΔDHS that close in males at 27 h, etc.). Up to 3 ΔDHS in each dataset showed inconsistent responses to TCPOBOP at 3 h versus 27 h (A), or between male and female livers (B), and were excluded from the numbers shown. C, ΔDHS regions shown in (A) are separated into sets of ΔDHS that open (left) or close (right) for each TCPOBOP exposure, and are counted based on whether they do (black) or do not (gray) contain at least one TCPOBOP-responsive gene at that time point whose transcription start site is in the same TAD as the ΔDHS region. D, ΔDHS regions that open or close and contain at least one TCPOBOP-responsive gene (black bars in C) are colored to indicate whether the TCPOBOP-responsive genes within the same TAD as the ΔDHS are all upregulated (red), downregulated (blue), or mixed with regard to the directionality of their responses to TCPOBOP (black). See Supplementary Table 5 for a more detailed listing (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Unexpectedly, only 22%–30% of 3 h TCPOBOP-responsive ΔDHS mapped to TADs that contain a TCPOBOP-responsive gene(s) (Figure 2C, Supplementary Table 5). This percentage increased to 40%–45% after 27 h TCPOBOP exposure. These percentages showed only marginal increases when robust ΔDHS (see Materials and Methods section) were considered (Supplementary Table 5, Part B). For the ΔDHS that do map to TADs containing TCPOBOP-responsive genes, DHS opening was primarily associated with gene induction and DHS closing with gene repression (Figure 2D). Thus, TCPOBOP-responsive ΔDHS are associated with positive regulation of gene expression. In most cases, the TCPOBOP gene-responsive TADs contain either upregulated genes or downregulated genes, rather than a mixture of up and downregulatory responses (Figure 2D, Supplementary Table 5). Overall, 84%–90% of the opening DHS associated with TCPOBOP-responsive TADs at 3 h were devoid of any downregulated genes in the TAD (Supplementary Table 5). After 27 h, this percentage decreased to 76%–78%, which may reflect the inclusion of secondary gene responses. Several TADs with TCPOBOP-responsive drug metabolizing enzyme gene families contain many ΔDHS, such as TAD3479, which contains up to 38 ΔDHS regions and 9–12 TCPOBOP-inducible Cyp2c genes (Table 1, Supplementary Table 2B). Highly active TADs with drug metabolizing enzyme gene families and multiple ΔDHS include: TAD1421, with Cyp2b genes (Figure 3A); TAD694, with Gstm genes (Figure 3B); and TAD3479, with Cyp2c genes (Figure 3C). Several ΔDHS nearby metallothionein genes Mt1 and Mt2 close after 27 h TCPOBOP exposure. Consistent with this, Mt1 and Mt2 and two nearby noncoding RNAs, lnc_7332 and lnc_7334, are downregulated after 27 h TCPOBOP exposure (Figure 3D). Table 1. Highly Active TADs Number of ΔDHS in TAD Number of TCPOBOP-responsive genes in TAD Annotation Male 3 h Male 27 h Female 3 h Female 27 h Male 3 h Male 27 h Female 3 h Female 27 h TAD3479_chr19 7 35 14 38 11 12 9 9 Cyp2c locus TAD1421_chr7 6 16 8 15 3 3 3 4 Cyp2b10 and lncRNAs TAD1132_chr5 8 13 7 5 4 4 4 3 Por and lncRNAs; Rhbdd2 TAD1860_chr9 1 11 0 11 1 4 0 5 LncRNAs; down regulated genes TAD1512_chr7 5 10 5 14 1 3 1 3 Tsku and lncRNA TAD1156_chr5 1 9 4 10 4 4 3 9 Cyp3a locus TAD694_chr3 1 8 0 11 1 4 1 3 Gstm locus TAD1937_chr9 6 5 4 11 2 4 2 7 Alas1 and lncRNA Number of ΔDHS in TAD Number of TCPOBOP-responsive genes in TAD Annotation Male 3 h Male 27 h Female 3 h Female 27 h Male 3 h Male 27 h Female 3 h Female 27 h TAD3479_chr19 7 35 14 38 11 12 9 9 Cyp2c locus TAD1421_chr7 6 16 8 15 3 3 3 4 Cyp2b10 and lncRNAs TAD1132_chr5 8 13 7 5 4 4 4 3 Por and lncRNAs; Rhbdd2 TAD1860_chr9 1 11 0 11 1 4 0 5 LncRNAs; down regulated genes TAD1512_chr7 5 10 5 14 1 3 1 3 Tsku and lncRNA TAD1156_chr5 1 9 4 10 4 4 3 9 Cyp3a locus TAD694_chr3 1 8 0 11 1 4 1 3 Gstm locus TAD1937_chr9 6 5 4 11 2 4 2 7 Alas1 and lncRNA Examples of TADs with many TCPOBOP-responsive DHS and genes in the TAD. Some of the TADs show a dramatic increase in responding DHS and in responding genes between 3 and 27h (eg, TAD1860 and TAD694). See Supplementary Table 2B for a complete listing. Table 1. Highly Active TADs Number of ΔDHS in TAD Number of TCPOBOP-responsive genes in TAD Annotation Male 3 h Male 27 h Female 3 h Female 27 h Male 3 h Male 27 h Female 3 h Female 27 h TAD3479_chr19 7 35 14 38 11 12 9 9 Cyp2c locus TAD1421_chr7 6 16 8 15 3 3 3 4 Cyp2b10 and lncRNAs TAD1132_chr5 8 13 7 5 4 4 4 3 Por and lncRNAs; Rhbdd2 TAD1860_chr9 1 11 0 11 1 4 0 5 LncRNAs; down regulated genes TAD1512_chr7 5 10 5 14 1 3 1 3 Tsku and lncRNA TAD1156_chr5 1 9 4 10 4 4 3 9 Cyp3a locus TAD694_chr3 1 8 0 11 1 4 1 3 Gstm locus TAD1937_chr9 6 5 4 11 2 4 2 7 Alas1 and lncRNA Number of ΔDHS in TAD Number of TCPOBOP-responsive genes in TAD Annotation Male 3 h Male 27 h Female 3 h Female 27 h Male 3 h Male 27 h Female 3 h Female 27 h TAD3479_chr19 7 35 14 38 11 12 9 9 Cyp2c locus TAD1421_chr7 6 16 8 15 3 3 3 4 Cyp2b10 and lncRNAs TAD1132_chr5 8 13 7 5 4 4 4 3 Por and lncRNAs; Rhbdd2 TAD1860_chr9 1 11 0 11 1 4 0 5 LncRNAs; down regulated genes TAD1512_chr7 5 10 5 14 1 3 1 3 Tsku and lncRNA TAD1156_chr5 1 9 4 10 4 4 3 9 Cyp3a locus TAD694_chr3 1 8 0 11 1 4 1 3 Gstm locus TAD1937_chr9 6 5 4 11 2 4 2 7 Alas1 and lncRNA Examples of TADs with many TCPOBOP-responsive DHS and genes in the TAD. Some of the TADs show a dramatic increase in responding DHS and in responding genes between 3 and 27h (eg, TAD1860 and TAD694). See Supplementary Table 2B for a complete listing. Figure 3. View largeDownload slide ΔDHS that respond to TCPOBOP, visualized in genome browser. A, Six strong ΔDHS upstream of Cyp2b10 are induced by TCPOBOP at both 3 and 27 h, in both male and female liver. Cyp2b10 and lnc_5998 (green; both isoforms are shown) are strongly induced under all 4 TCPOBOP conditions. B, 5 to 6 ΔDHS in the vicinity of Gstm3 are induced by TCPOBOP at 27 h, but not at 3 h, in both male and female liver. C, Many ΔDHS open in the vicinity of Cyp2c53-ps and Cyp2c29, which are both induced by all 4 TCPOBOP exposures. D, ΔDHS that close at 27 h, but not after 3 h TCPOBOP treatment, surrounding metallothionein genes Mt1 and Mt2 and two nearby lncRNA genes. At the 27 h time point, Mt1 and Mt2 are repressed in both male and female liver, lnc_7332 is repressed in female liver only, and lnc_7334 is repressed in male liver only. None of the four genes are repressed at the 3 h TCPOBOP time point, consistent with the delayed closing of the ΔDHS shown here. Six browser tracks with reads-in-peaks normalized Wig file DNase-seq data (see Materials and Methods) are shown in each panel: vehicle-treated controls and 3 h and 27 h TCPOBOP-treated males (blue) and females (pink/red), as marked. In panels B, C, and D, black, red, and blue bars above each track indicate locations of DHS discovered by MACS2 analysis. Static DHS are marked in black bars. Dark red and dark blue bars indicate robust ΔDHS that open and close, respectively; light red and light blue bars indicate standard ΔDHS that open and close, respectively (see Materials and Methods). Bottom track in each panel marks DHS regions identified in untreated male and female mouse liver in our prior study (Ling, et al., 2010), many of which match the DHS shown in the tracks above, indicating that these DHS are highly reproducible (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 3. View largeDownload slide ΔDHS that respond to TCPOBOP, visualized in genome browser. A, Six strong ΔDHS upstream of Cyp2b10 are induced by TCPOBOP at both 3 and 27 h, in both male and female liver. Cyp2b10 and lnc_5998 (green; both isoforms are shown) are strongly induced under all 4 TCPOBOP conditions. B, 5 to 6 ΔDHS in the vicinity of Gstm3 are induced by TCPOBOP at 27 h, but not at 3 h, in both male and female liver. C, Many ΔDHS open in the vicinity of Cyp2c53-ps and Cyp2c29, which are both induced by all 4 TCPOBOP exposures. D, ΔDHS that close at 27 h, but not after 3 h TCPOBOP treatment, surrounding metallothionein genes Mt1 and Mt2 and two nearby lncRNA genes. At the 27 h time point, Mt1 and Mt2 are repressed in both male and female liver, lnc_7332 is repressed in female liver only, and lnc_7334 is repressed in male liver only. None of the four genes are repressed at the 3 h TCPOBOP time point, consistent with the delayed closing of the ΔDHS shown here. Six browser tracks with reads-in-peaks normalized Wig file DNase-seq data (see Materials and Methods) are shown in each panel: vehicle-treated controls and 3 h and 27 h TCPOBOP-treated males (blue) and females (pink/red), as marked. In panels B, C, and D, black, red, and blue bars above each track indicate locations of DHS discovered by MACS2 analysis. Static DHS are marked in black bars. Dark red and dark blue bars indicate robust ΔDHS that open and close, respectively; light red and light blue bars indicate standard ΔDHS that open and close, respectively (see Materials and Methods). Bottom track in each panel marks DHS regions identified in untreated male and female mouse liver in our prior study (Ling, et al., 2010), many of which match the DHS shown in the tracks above, indicating that these DHS are highly reproducible (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Some ΔDHS Responses Precede Changes in Gene Expression We considered the possibility that the opening DHS that map to TADs without TCPOBOP-responsive genes (Figure 2C) might target genes whose RNAs respond to TCPOBOP with a delay compared with DHS opening. Supporting this idea, a substantial fraction of the 3 h TCPOBOP-stimulated opening DHS that map to a TAD without a 3 h TCPOBOP gene response become associated with a gene response at 27 h (Figure 4A; 128 out of 366 such opening DHS in male liver [37.5%], and 102 out of 358 such DHS in female liver [28.5%]). Further, a subset of the 3 h TCPOBOP-stimulated closing DHS that map to a TAD without a 3 h TCPOBOP gene response become associated with a gene response at 27 h (Figure 4A; 9 of 62 such closing DHS [14.5%] in male liver, and 32 of 87 such DHS [37%] in female liver). Thus, gene expression changes lag behind chromatin opening or closing for a subset of 3 h TCPOBOP-responsive ΔDHS. Furthermore, in male liver, 92 of the 128 ΔDHS whose opening is associated with a delayed gene response are in a TAD that contains upregulated gene(s), whereas 3 of the 9 closing ΔDHS linked to a delayed gene response are in a TAD that contains downregulated gene(s) (Figure 4B). Similarly, in female liver, 83 of the 102 opening DHS linked to a delayed gene response are in a TAD with an upregulated gene(s), whereas 22 of the 32 closing DHS linked to a delayed gene response are in a TAD that contains a downregulated gene(s) (Figure 4B). Figure 4. View largeDownload slide TCPOBOP-induced DHS opening, or closing, may precede gene activation or repression. A, ΔDHS induced by 3 h TCPOBOP exposure that do not have a 3 h TCPOBOP-responsive gene in the same TAD (gray bars in Figure 2 C) were analyzed to determine whether the TADs containing those ΔDHS either do (white bars) or do not (red bars) contain one or more TCPOBOP-responsive genes at the 27 h time point. B, The 3 h ΔDHS whose associated gene(s) in the same TAD show a delayed response to TCPOBOP (white bars in A) were analyzed to determine whether (blue bars) or not (yellow bars), for one or more genes in the TAD, DHS opening at 27 h is associated with gene induction, and DHS closing at 27 h is associated with gene repression (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 4. View largeDownload slide TCPOBOP-induced DHS opening, or closing, may precede gene activation or repression. A, ΔDHS induced by 3 h TCPOBOP exposure that do not have a 3 h TCPOBOP-responsive gene in the same TAD (gray bars in Figure 2 C) were analyzed to determine whether the TADs containing those ΔDHS either do (white bars) or do not (red bars) contain one or more TCPOBOP-responsive genes at the 27 h time point. B, The 3 h ΔDHS whose associated gene(s) in the same TAD show a delayed response to TCPOBOP (white bars in A) were analyzed to determine whether (blue bars) or not (yellow bars), for one or more genes in the TAD, DHS opening at 27 h is associated with gene induction, and DHS closing at 27 h is associated with gene repression (The reader is referred to the web version of this article to clarify the references to color in this figure legend). ΔDHS Are Highly Enriched Nearby TCPOBOP-Responsive Genes Putative gene targets for each DHS were assigned by mapping the DHS to the nearest gene transcription start site within the same TAD, considering both RefSeq genes and liver-expressed multi-exonic lncRNA genes (Supplementary Table 1B). Next, we examined the relationship between changes in chromatin accessibility and changes in gene expression (ie, nuclear RNA levels) for the set of 120 ΔDHS that open in both sexes at 3 h and remain open at 27 h (ie, ΔDHS common to all 4 TCPOBOP exposure conditions; Table 2). These ΔDHS, whose induced open chromatin state persists for at least 24 h in both sexes, showed an exceptionally strong, 102-fold enrichment (p < E-41; Fisher Exact test) for genes that showed a common response to TCPOBOP in all four treatments (Table 3). A total of 27 of these 120 ΔDHS mapped to 19 TCPOBOP-responsive genes, including 6 lncRNA genes. Protein-coding RefSeq genes in this group include Cyp2b10, Cyp2c53-ps, Cyp2c55, Cyp3a11, Gadd45b, Gstt1, and Por. Table 2. ΔDHS That Respond in Multiple Datasets Open Close TCPOBOP Response Profile Number of ΔDHS All TCPOBOP-responsive DHS 3422 1432 Common responses in all 4 TCPOBOP datasets 120 1 Responds in male liver only 902 484 Responds in female liver only 1403 806 Early responding (male, female, or both) 803 164 Late responding only (male, female, or both) 2619 1268 Open Close TCPOBOP Response Profile Number of ΔDHS All TCPOBOP-responsive DHS 3422 1432 Common responses in all 4 TCPOBOP datasets 120 1 Responds in male liver only 902 484 Responds in female liver only 1403 806 Early responding (male, female, or both) 803 164 Late responding only (male, female, or both) 2619 1268 Shown are the number of ΔDHS in each of the indicated categories. All TCPOBOP-responsive DHS refer to the number of ΔDHS regions discovered in any one of the 4 TCPOBOP exposure conditions. Common responses in all 4 TCPOBOP datasets refer to those ΔDHS that respond in all 4 conditions. Responds in male (or in female) liver only: those ΔDHS that respond in male liver (or female liver) at 3 and/or 27 h, but do not respond in the other sex at either time point. Early responding refers to ΔDHS that respond to TCPOBOP at 3 h, in either or both sexes, independent of their responsiveness at 27 h. Late responding only refers to ΔDHS that respond to TCPOBOP at 27 h, but that are static at 3 h, in either or in both sexes. The numbers shown exclude 19 of the 4873 “all TCPOBOP-responsive DHS” (ie, 0.4% of all ΔDHS), which show discrepant responses to TCPOBOP, eg, they open at one time point, or in one sex, but close at another time point or in the other sex, as is marked in Supplementary Table 1B. Table 2. ΔDHS That Respond in Multiple Datasets Open Close TCPOBOP Response Profile Number of ΔDHS All TCPOBOP-responsive DHS 3422 1432 Common responses in all 4 TCPOBOP datasets 120 1 Responds in male liver only 902 484 Responds in female liver only 1403 806 Early responding (male, female, or both) 803 164 Late responding only (male, female, or both) 2619 1268 Open Close TCPOBOP Response Profile Number of ΔDHS All TCPOBOP-responsive DHS 3422 1432 Common responses in all 4 TCPOBOP datasets 120 1 Responds in male liver only 902 484 Responds in female liver only 1403 806 Early responding (male, female, or both) 803 164 Late responding only (male, female, or both) 2619 1268 Shown are the number of ΔDHS in each of the indicated categories. All TCPOBOP-responsive DHS refer to the number of ΔDHS regions discovered in any one of the 4 TCPOBOP exposure conditions. Common responses in all 4 TCPOBOP datasets refer to those ΔDHS that respond in all 4 conditions. Responds in male (or in female) liver only: those ΔDHS that respond in male liver (or female liver) at 3 and/or 27 h, but do not respond in the other sex at either time point. Early responding refers to ΔDHS that respond to TCPOBOP at 3 h, in either or both sexes, independent of their responsiveness at 27 h. Late responding only refers to ΔDHS that respond to TCPOBOP at 27 h, but that are static at 3 h, in either or in both sexes. The numbers shown exclude 19 of the 4873 “all TCPOBOP-responsive DHS” (ie, 0.4% of all ΔDHS), which show discrepant responses to TCPOBOP, eg, they open at one time point, or in one sex, but close at another time point or in the other sex, as is marked in Supplementary Table 1B. Table 3. Enrichment Scores Enrichment Score p-Value Common ΔDHS mapping to common genes 101.7 <E-41 Male, 3 h Open ΔDHS mapping to up genes 24.9 <E-64 Close ΔDHS mapping to down genes 0 1 Male, 27 h Open ΔDHS mapping to up genes 8.3 <E-199 Close ΔDHS mapping to down genes 5.9 <E-27 Female, 3 h Open ΔDHS mapping to up genes 24.3 <E-92 Close ΔDHS mapping to down genes 5.2 <E-02 Female, 27 h Open ΔDHS mapping to up genes 10.6 <E-277 Close ΔDHS mapping to down genes 8.7 <E-64 Enrichment Score p-Value Common ΔDHS mapping to common genes 101.7 <E-41 Male, 3 h Open ΔDHS mapping to up genes 24.9 <E-64 Close ΔDHS mapping to down genes 0 1 Male, 27 h Open ΔDHS mapping to up genes 8.3 <E-199 Close ΔDHS mapping to down genes 5.9 <E-27 Female, 3 h Open ΔDHS mapping to up genes 24.3 <E-92 Close ΔDHS mapping to down genes 5.2 <E-02 Female, 27 h Open ΔDHS mapping to up genes 10.6 <E-277 Close ΔDHS mapping to down genes 8.7 <E-64 The 60 739 DHS regions (ΔDHS and static DHS) were each mapped to a single putative gene target (closest transcription start site within the same TAD) as shown in Supplementary Table 1B. Enrichment scores for the indicated TCPOBOP-responsive gene sets were calculated as described in Materials and Methods section. Enrichment of common peaks to common genes was calculated based on ΔDHS that open in all 4 TCPOBOP conditions and that map to genes that respond in all 4 conditions (males and females, 3 and 27 h). Table 3. Enrichment Scores Enrichment Score p-Value Common ΔDHS mapping to common genes 101.7 <E-41 Male, 3 h Open ΔDHS mapping to up genes 24.9 <E-64 Close ΔDHS mapping to down genes 0 1 Male, 27 h Open ΔDHS mapping to up genes 8.3 <E-199 Close ΔDHS mapping to down genes 5.9 <E-27 Female, 3 h Open ΔDHS mapping to up genes 24.3 <E-92 Close ΔDHS mapping to down genes 5.2 <E-02 Female, 27 h Open ΔDHS mapping to up genes 10.6 <E-277 Close ΔDHS mapping to down genes 8.7 <E-64 Enrichment Score p-Value Common ΔDHS mapping to common genes 101.7 <E-41 Male, 3 h Open ΔDHS mapping to up genes 24.9 <E-64 Close ΔDHS mapping to down genes 0 1 Male, 27 h Open ΔDHS mapping to up genes 8.3 <E-199 Close ΔDHS mapping to down genes 5.9 <E-27 Female, 3 h Open ΔDHS mapping to up genes 24.3 <E-92 Close ΔDHS mapping to down genes 5.2 <E-02 Female, 27 h Open ΔDHS mapping to up genes 10.6 <E-277 Close ΔDHS mapping to down genes 8.7 <E-64 The 60 739 DHS regions (ΔDHS and static DHS) were each mapped to a single putative gene target (closest transcription start site within the same TAD) as shown in Supplementary Table 1B. Enrichment scores for the indicated TCPOBOP-responsive gene sets were calculated as described in Materials and Methods section. Enrichment of common peaks to common genes was calculated based on ΔDHS that open in all 4 TCPOBOP conditions and that map to genes that respond in all 4 conditions (males and females, 3 and 27 h). For each of the four TCPOBOP exposure conditions, we observed strong enrichment of DHS that open for genes that are upregulated, when compared with a background set comprised of TCPOBOP-unresponsive DHS (ie, static DHS) (Table 3). Similarly, in both sexes, DHS that close were strongly enriched for genes that are downregulated by TCPOBOP at 27 h. There was also a weak enrichment of ΔDHS that close for genes that are downregulated at 3 h in females, but not in males. In all cases, enrichments were stronger when we considered robust ΔDHS (see Materials and Methods; Supplementary Table 7). These findings support the proposal that these sets of TCPOBOP-responsive DHS encompass regulatory elements (enhancers and promoters) for TCPOBOP-stimulated gene responses that are either activated by TCPOBOP, in the case of ΔDHS that open, or are repressed by TCPOBOP, in the case of ΔDHS that close. Impact of Basal Liver Sex Differences on TCPOBOP Response We investigated whether the sex-dependent effects of TCPOBOP on chromatin accessibility (Figure 2B) and gene expression (Lodato et al., 2017) reflect basal sex differences in gene expression or chromatin accessibility (Sugathan and Waxman, 2013). First, we examined TADs whose genes show a sexually dimorphic response to TCPOBOP exposure, which we defined as two or more genes that respond to TCPOBOP in one sex versus no genes that respond in the other sex. We identified 22 TADs with a female-biased gene response and 60 TADs with a male-biased gene response. These 82 TADs include 178 TCPOBOP-responsive genes, of which 41 genes (23%) show sex differential expression in untreated mouse liver (Supplementary Table 6A). However, 362 TADs with two or more TCPOBOP-responsive genes that do not show a sex-biased gene response to TCPOBOP contain an even higher percentage (28%) of TCPOBOP-responsive genes with a basal sex bias in their expression (ie, 183 of 643 TCPOBOP-responsive genes [28%] in those 362 TADs) (Supplementary Table 6B). Further, TADs with sex-biased genes were not enriched in the set of TADs that showed a sex-biased TCPOBOP response (32 [39%] of 82 TADs) compared with TADs without a sex-biased response (134 [37%] of 362 TADs). For 20 of the above 41 basally sex-biased genes in TADs showing a sex-biased response to TCPOBOP, TCPOBOP reinforces the basal sex bias in expression, by inducing male-biased genes (n = 10) and repressing female-biased genes (n = 5) in male liver only; and by inducing female-biased genes (n = 4) and repressing male-biased genes (n = 1) in female liver only. (Supplementary Table 6A). In these cases, TCPOBOP induced expression only in the sex where the gene is already in an activated state, and it repressed expression in the sex where the gene is in a more repressed state. For the other 21 sex-biased genes, TCPOBOP countered the basal sex bias in expression, by inducing female-biased genes (n = 7) and repressing male-biased genes (n = 8) in male liver only; and by inducing male-biased genes (n = 3) and repressing female-biased genes (n = 3) in female liver only (Supplementary Table 6A). In these cases, TCPOBOP activates genes from a more repressed basal state, and it represses genes from a more active basal state. Finally, we examined the sets of ΔDHS that were only responsive to TCPOBOP in one sex, after 3 h and/or after 27 h exposure (Figure 2B). ΔDHS that were specifically responsive to TCPOBOP in male liver were significantly enriched for overlap with chromatin regions with a basal male bias in accessibility (Ling et al., 2010), when compared with ΔDHS without a sex bias in TCPOBOP response (enrichment score = 1.79, p = 1.03E-3, Fisher Exact test); however, ΔDHS that were specifically responsive to TCPOBOP in female liver did not show a corresponding enrichment for basally female-biased chromatin regions (p = .4). ΔDHS Proximal to TCPOBOP-Responsive HCC Genes We previously observed a striking male bias for TCPOBOP activation of genes associated with CAR-dependent pathways that promote HCC, specifically after 27 h TCPOBOP exposure (Lodato et al., 2017). Conceivably, this sexually dimorphic gene response profile may be driven by a correspondingly male-biased ΔDHS response. To test this hypothesis, we examined the ΔDHS that map to gene targets of a set of 10 established upstream regulators linked to CAR-induced HCC defined previously (Lodato et al., 2017). Whereas the gene targets of these 10 upstream regulators showed a significant male bias in their responsiveness to TCPOBOP after 27 h exposure (Lodato et al., 2017), there was no significant sex bias in the number of 27 h TCPOBOP-induced ΔDHS that map to these downstream gene targets (enrichment score = 1.02, p = .75; Figure 5A), even when we restricted the analysis to the 378 target genes of the 10 upstream regulators that are responsive to TCPOBOP (enrichment score = 1.07, p = .58; Figure 5B) or to the subset comprised of 153 target genes that are responsive to TCPOBOP in male liver only (enrichment score = 0.82, p = .29; Figure 5C). In other analyses, 27 h TCPOBOP-stimulated ΔDHS that opened in male but not female liver mapped to the set of 153 genes induced by 27 h TCPOBOP exposure in male liver only, at the same frequency that they mapped to a control set of 225 TCPOBOP-responsive genes not showing male-specific responses (Supplementary Table 3 and data not shown). Finally, there was no difference in the frequency with which male-biased TCPOBOP-induced DHS opening was associated with a basal sex bias in chromatin accessibility between the 153 male-biased HCC pathway gene targets and the 225 nonmale-biased gene targets (data not shown). Thus, the HCC-linked male-biased genic responses to TCPOBOP are not associated with a male bias in local chromatin accessibility or its responsiveness to TCPOBOP. Figure 5. View largeDownload slide ΔDHS mapping to gene targets of regulators of HCC. Shown is the number of ΔDHS that map to gene targets of 10 CAR-dependent upstream regulators of liver carcinogenesis described previously (Lodato, et al., 2017). Despite the strong male bias in the TCPOBOP responsiveness of the gene targets of these upstream regulators (Lodato, et al., 2017), there was no significant sex bias in the number of ΔDHS that mapped to any of the following three gene sets (see text): A, the set of all downstream target genes of these 10 regulators (n = 4336 genes); B, the set of all downstream targets that are TCPOBOP-responsive (n = 378 genes); C, the set of all downstream targets induced by 27 h TCPOBOP exposure in male liver but not in female liver (n = 153 genes) (Supplementary Table 3) (Lodato, et al., 2017). Figure 5. View largeDownload slide ΔDHS mapping to gene targets of regulators of HCC. Shown is the number of ΔDHS that map to gene targets of 10 CAR-dependent upstream regulators of liver carcinogenesis described previously (Lodato, et al., 2017). Despite the strong male bias in the TCPOBOP responsiveness of the gene targets of these upstream regulators (Lodato, et al., 2017), there was no significant sex bias in the number of ΔDHS that mapped to any of the following three gene sets (see text): A, the set of all downstream target genes of these 10 regulators (n = 4336 genes); B, the set of all downstream targets that are TCPOBOP-responsive (n = 378 genes); C, the set of all downstream targets induced by 27 h TCPOBOP exposure in male liver but not in female liver (n = 153 genes) (Supplementary Table 3) (Lodato, et al., 2017). DISCUSSION The major disruptive actions of environmental chemicals on gene transcription and the role of xenochemical receptors, including the nuclear receptor/transcription factor CAR, in these processes have long been recognized. However, underlying regulatory mechanisms are only partially understood, and have primarily been studied on a gene-by-gene basis, without considering the overall genomic organization of responding genes, and with little known about the changes in chromatin structure and accessibility that are presumed to occur based on studies of other nuclear receptor family members (Grontved et al., 2015; He et al., 2014; Stavreva et al., 2015). Here, we use the CAR-specific agonist ligand TCPOBOP to identify several thousand genomic regions where TCPOBOP, presumably acting via CAR activation, stimulates either an increase or a decrease in chromatin accessibility, and we analyze these datasets in the context of the TAD-based genomic organization of TCPOBOP-responsive protein coding and long noncoding (lncRNA) genes. TCPOBOP-Responsive Genes Cluster in TADs We found that a subset of TCPOBOP-responsive genes cluster in TADs, and that TCPOBOP-inducible genes and TCPOBOP-repressible genes are often found in separate sets of TADs. Thus, the genomic sequences and/or the chromatin state and epigenetic environment of individual TADs may render these TADs, and at least a subset of their constituent genes, susceptible to either activation or repression by TCPOBOP. TADs provide a structural framework for organizing megabase-scale segments of the genome into distinct three-dimensional compartments (Dixon et al., 2016) and thereby enable linearly distant chromosomal regions to interact within the large TAD-based DNA loops that segment each chromosome (Faure et al., 2012; Nora et al., 2017; Rao et al., 2014). TADs insulate regulatory elements from neighboring genes present in adjacent TADs, which constrains enhancer-promoter interactions (Figure 6) and increases the specificity of regulatory interactions (Oti et al., 2016; Vietri Rudan et al., 2015). TADs that contain the Cyp2b, Cyp2c, and Cyp3a gene families were particularly responsive to the stimulatory actions of TCPOBOP on chromatin opening and target gene induction, as exemplified by TAD3479, which contains the Cyp2c cluster with its 12 TCPOBOP-responsive genes and up to 38 ΔDHS that respond to a single condition of TCPOBOP exposure (Table 1). Clustering of Cyps into large TAD regions that can be rapidly activated following xenobiotic exposure may be advantageous from an evolutionary perspective, by allowing for a limited number of common regulatory elements to induce multiple genes within the gene superfamily, thereby increasing a broad range of xenobiotic metabolic activities following xenobiotic exposure. Figure 6. View largeDownload slide Impact of TAD segmentation of the genome on the selection of genes for CAR-induced transcriptional activation. Shown is a model with two adjacent TADs. TAD1 contains a cluster of 3 TCPOBOP/CAR-inducible genes, which may be activated by CAR to different extents, as shown. TAD2 contains two genes that are not subject to the stimulatory effects of the enhancer DHS in TAD1 when it is bound by a CAR-RXR heterodimer, due to the strong insulation imposed by the TAD’s looped DNA structure (black loop). This insulation is apparent, even when the gene promoters in TAD2 are closer, in linear DNA length, to the CAR-bound enhancer DHS than the CAR target genes in TAD1. A single enhancer DHS may activate multiple CAR-responsive promoters within a TAD, as shown, and individual promoters may be activated through the cooperative actions of multiple enhancer DHS (not illustrated). Further constraints on enhancer-promoter interactions may be imposed by intra-TAD (subTAD) looped domains (not shown). TADs are formed by DNA loop extrusion through the ring-shaped cohesin complex, which associates with the sequence-specific DNA-binding protein CTCF, two copies of which are bound at directionally oriented binding sites near the base of the loop, as shown. Mouse liver TADs have a median length of ∼400 kb but may vary widely in size, as illustrated by the two TADs in this model. CAR target genes include many lncRNAs (Lodato, et al., 2017), some of which may modulate transcription of other CAR targets, either in cis (red arrow), or in trans (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 6. View largeDownload slide Impact of TAD segmentation of the genome on the selection of genes for CAR-induced transcriptional activation. Shown is a model with two adjacent TADs. TAD1 contains a cluster of 3 TCPOBOP/CAR-inducible genes, which may be activated by CAR to different extents, as shown. TAD2 contains two genes that are not subject to the stimulatory effects of the enhancer DHS in TAD1 when it is bound by a CAR-RXR heterodimer, due to the strong insulation imposed by the TAD’s looped DNA structure (black loop). This insulation is apparent, even when the gene promoters in TAD2 are closer, in linear DNA length, to the CAR-bound enhancer DHS than the CAR target genes in TAD1. A single enhancer DHS may activate multiple CAR-responsive promoters within a TAD, as shown, and individual promoters may be activated through the cooperative actions of multiple enhancer DHS (not illustrated). Further constraints on enhancer-promoter interactions may be imposed by intra-TAD (subTAD) looped domains (not shown). TADs are formed by DNA loop extrusion through the ring-shaped cohesin complex, which associates with the sequence-specific DNA-binding protein CTCF, two copies of which are bound at directionally oriented binding sites near the base of the loop, as shown. Mouse liver TADs have a median length of ∼400 kb but may vary widely in size, as illustrated by the two TADs in this model. CAR target genes include many lncRNAs (Lodato, et al., 2017), some of which may modulate transcription of other CAR targets, either in cis (red arrow), or in trans (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Whereas Cyp2b10 and the nearby lnc_5998 were highly induced, and several ΔDHS within the same TAD (TAD1421) were activated (opened) by TCPOBOP exposure, two adjacent, closely related genes in the same TAD, Cyp2b9 and Cyp2b13, did not respond to TCPOBOP, even after a 27 h exposure (Lodato et al., 2017). Presumably, Cyp2b9 and Cyp2b13 are insulated from the DNA looping that is expected to bring the promoter of Cyp2b10, but not the promoters of the other, nearby Cyp2b genes, in contact with the ΔDHS/putative regulatory elements that contribute to its rapid and robust transcriptional activation, despite their being in the same TAD. Cyp2b9 and Cyp2b13 become TCPOBOP inducible after 4 days of exposure (Cui and Klaassen, 2016), suggesting a requirement for secondary factors and perhaps a need for more complex epigenetic reprogramming than for Cyp2b10. Such a requirement could be related to the epigenetic suppression of Cyp2b9 and Cyp2b13 (but not Cyp2b10) that occurs in male but not female mouse liver (Sugathan and Waxman, 2013). Other drug metabolizing enzyme gene families also showed selective patterns of induction. Thus, Gstm3 was strongly induced by 3 h TCPOBOP exposure in both male and female liver, whereas other Gstm genes in the same TAD (TAD694), notably Gstm1, Gstm2, and Gstm4, responded at 27 h. While other Gstm genes on the same TAD (Gstm6, Gstm7) were unresponsive. It is not known what factors determine the specificity of TCPOBOP for particular genes within a responsive TAD, nor is it clear what causes the delayed induction of a subset of genes within a highly active gene cluster. One factor may be three-dimensional proximity to CAR-bound ΔDHS/enhancer elements, whose accessibility to certain genes within a TAD may be constrained by the presence of intra-TAD (subTAD) looped domains (Wijchers et al., 2016). Another important factor may be the basal chromatin state of each gene and its regulatory elements (Sugathan and Waxman, 2013), which may contribute to the time differences in responsiveness, as suggested by other studies of time-dependent responses to hormonal stimuli in the mouse liver model (Lau-Corona et al., 2017). Finally, it should be noted that TAD boundaries are not necessarily fixed, and that genomic rearrangements that accompany carcinogenesis may alter TAD boundaries and play an important role in cancer progression (Taberlay et al., 2016; Valton and Dekker, 2016). Further work is required to ascertain whether such processes contribute to CAR-dependent liver carcinogenesis. ΔDHS as Positive Regulators of Gene Expression We used DNase-seq analysis to identify several thousand genomic regions (ΔDHS) where short-term exposure to TCPOBOP induces localized changes (increases or decreases) in mouse liver chromatin accessibility. Mapping these ΔDHS regions to the closest RefSeq coding or multi-exonic long noncoding gene within the same TAD revealed a strong enrichment of opening ΔDHS that map to genes induced by TCPOBOP, and of closing DHS that map to genes that are repressed (Table 3). Both of these response patterns are consistent with these ΔDHS playing a positive regulatory role. Some of the ΔDHS regions opened rapidly, ie, within 3 h of TCPOBOP exposure, but many others did not respond until 27 h, consistent with the large expansion of TCPOBOP-stimulated gene responses seen at 27 h (Lodato et al., 2017). Further, we observed a temporal relationship between TCPOBOP-induced DHS opening (or DHS closing) and TCPOBOP-induced gene responses, with DHS opening and DHS closing preceding gene induction and repression, respectively, for a subset of the 27 h TCPOBOP-responsive genes. Together, these findings support the model that these ΔDHS regions comprise promoters and enhancers that positively regulate gene expression, and that factors bound to these genomic regions, such as TCPOBOP-activated CAR, stimulate target gene transcription. Precisely how these chromatin regions open or close in response to TCPOBOP exposure is not known, but it likely involves factors such as the SWI/SNF chromatin remodeling complex (Tang et al., 2010). The rapid, 3 h TCPOBOP-induced chromatin opening seen at several hundred ΔDHS regions may be driven by direct CAR binding, as suggested by the ability of nuclear receptors such as GR and PPAR to bind directly to closed chromatin (Nagaich et al., 2004; Siersbaek et al., 2011; Voss et al., 2011). Supporting the proposal is the high specificity of TCPOBOP for CAR (Tzameli et al., 2000) and the presence of a well characterized CAR binding motif (direct repeat-4 [DR4] sequence) (Honkakoski and Negishi, 1997) centered within a cluster of six opening ΔDHS in TAD1421, which are distributed across a 10 kb region upstream of Cyp2b10 (Figure 3A). PXR, a nuclear receptor family member closely related to CAR, also binds DR4 motifs upstream of several drug metabolizing enzyme genes induced in common by CAR and PXR, such as Gstm3 (Cui et al., 2010), where we also found multiple TCPOBOP-induced ΔDHS (Figure 3B). Given the high specificity of TCPOBOP for CAR and the short time frame (within 3 h) for the early ΔDHS responses, these changes in chromatin accessibility are most likely a primary genomic response to CAR activation. Comparatively few chromatin closing events were seen at the 3 h exposure point, suggesting that CAR activation is primarily associated with chromatin opening. Changes in chromatin accessibility at several thousand other ΔDHS did not occur until the 27 h TCPOBOP time point (Figure 2A), and include more similar numbers of DHS opening and closing events (Figure 2C). The set of 27 h ΔDHS likely includes many secondary genomic responses, some of which could result from the epigenetic actions of one or more of the few hundred multi-exonic lncRNA genes that are rapidly induced by TCPOBOP in mouse liver (Lodato et al., 2017). One example is lnc_5998 (Figure 3A), whose transcription start site is located 5.2 kb upstream of Cyp2b10, and which together with Cyp2b10, constitute a divergently transcribed lncRNA-mRNA pair (Lepoivre et al., 2013). Finally, we identified many ΔDHS that mapped to TADs without any TCPOBOP-responsive genes. Some of these ΔDHS may regulate genes whose responsiveness to TCPOBOP does not become apparent until a later time point. Further studies, including identification of transcriptional changes that occur at a later time point, are needed to test this hypothesis. Sex-Biased Responses to TCPOBOP Sex differences in mouse liver gene expression are widespread (Waxman and Holloway, 2009) and are under the control of growth hormone and its sexually dimorphic pattern of secretion by the pituitary gland. Growth hormone, in turn, regulates liver chromatin states, including chromatin accessibility, which both show major sex differences in localized regions throughout the genome (Ling et al., 2010; Sugathan and Waxman, 2013). Accordingly, we investigated whether the sex differences in the impact of TCPOBOP-induced CAR activation on chromatin accessibility (Figure 2) and gene expression (Lodato et al., 2017) relate to basal sex differences in gene expression or chromatin accessibility (Sugathan and Waxman, 2013). We found that ΔDHS that were specifically responsive to TCPOBOP in male liver were significantly enriched for genomic regions with a basal male bias in chromatin accessibility. Further, we identified 82 TADs containing 41 basally sex-biased genes that responded to TCPOBOP in a sex-dependent manner. For 20 of these sex-biased genes, TCPOBOP reinforced basal sex differences, by inducing gene expression only in the sex where the gene is already in an activated state, and by repressing expression only in the sex where the gene is in a more repressed state. For the other 21 sex-biased genes, TCPOBOP countered the basal sex bias in expression, activating genes from a more repressed basal state, and repressing genes that are in a more active basal state. These findings suggest that basal chromatin state differences between the sexes can impact TCPOBOP responses. ΔDHS Do Not Predict Sex-Biased HCC Response We previously reported a strong male bias in the activation of CAR-dependent HCC pathways in mouse liver after 27 h of TCPOBOP exposure (Lodato et al., 2017). Here, we used DNase-seq to map ΔDHS, ie, putative DNA regulatory elements, that respond to TCPOBOP in mouse liver, to the downstream gene targets of 10 previously identified CAR-dependent HCC upstream regulators; these include a set of 153 downstream targets that respond to TCPOBOP in a male-specific manner (Lodato et al., 2017). Remarkably, there was no male bias in the number of TCPOBOP-responsive ΔDHS that map to the downstream gene targets. Further, the HCC-linked male-biased gene responses to TCPOBOP were not associated with a male bias in basal chromatin accessibility or in a sex bias of the responsiveness of those genomic regions to TCPOBOP-induced chromatin accessibility. Thus, male-biased regulation of these genes is not driven by a sex bias in the number of sites with changes in chromatin accessibility, their basal sex bias, or the sex bias of their responses to TCPOBOP exposure. These findings point to sex differences in other factors required for the male-biased transcription of these genes, for example, sex differences in the activation state of cyclin-D1, p53, p21, or one of the other seven CAR-dependent HCC upstream regulators. CONCLUSIONS We presented a genome-wide view of the dynamic changes in chromatin accessibility that occur in mouse liver following short exposures to the mouse CAR agonist ligand TCPOBOP, and we utilized mouse liver TAD region definitions to map changes in DHS to putative gene targets. Our findings reveal coordinated regulation of CAR-responsive gene families grouped by TAD and their associated, rapidly opening DHS, along with widespread sex differences in TCPOBOP-stimulated changes in chromatin accessibility. The global maps of dysregulated chromatin accessibility that we identified constitute a rich resource for further research on foreign chemical effects on the epigenome and its chromatin states. Future studies may examine whether mouse liver TADs enriched with CAR-responsive genes, including those associated with HCC-related genes, and their regulatory elements, are conserved in other species (Vietri Rudan et al., 2015), including humans, where CAR activation has not been conclusively linked to increased incidence of liver tumors (Dong et al., 2015; Elcombe et al., 2014). SUPPLEMENTARY DATA Supplementary data are available at Toxicological Sciences online. FUNDING Supported in part by NIH grant ES024421 (to D.J.W.). Disclosure: The authors have nothing to disclose. REFERENCES Baldwin W. S. , Roling J. A. ( 2009 ). A concentration addition model for the activation of the constitutive androstane receptor by xenobiotic mixtures . Toxicol. Sci. 107 , 93 – 105 . 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Nature 515 , 355 – 364 . Google Scholar CrossRef Search ADS PubMed Zhang Y. , Liu T. , Meyer C. A. , Eeckhoute J. , Johnson D. S. , Bernstein B. E. , Nussbaum C. , Myers R. M. , Brown M. , Li W. et al. , . ( 2008 ). Model-based analysis of ChIP-Seq (MACS) . Genome Biol. 9 , R137. Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Toxicological Sciences Oxford University Press

Impact of CAR Agonist Ligand TCPOBOP on Mouse Liver Chromatin Accessibility

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Abstract

Abstract Activation of the nuclear receptor and transcription factor CAR (Nr1i3) by its specific agonist ligand TCPOBOP (1, 4-bis[2-(3, 5-dichloropyridyloxy)]benzene) dysregulates hundreds of genes in mouse liver and is linked to male-biased hepatocarcinogenesis. To elucidate the genomic organization of CAR-induced gene responses, we investigated the distribution of TCPOBOP-responsive RefSeq coding and long noncoding RNA (lncRNA) genes across the megabase-scale topologically associating domains (TADs) that segment the genome, and which provide a structural framework that functionally constrains enhancer-promoter interactions. We show that a subset of TCPOBOP-responsive genes cluster within TADs, and that TCPOBOP-induced genes and TCPOBOP-repressed genes are often found in different TADs. Further, using DNase-seq and DNase hypersensitivity site (DHS) analysis, we identified several thousand genomic regions (ΔDHS) where short-term exposure to TCPOBOP induces localized changes (increases or decreases) in mouse liver chromatin accessibility, many of which cluster in TADs together with TCPOBOP-responsive genes. Sites of chromatin opening were highly enriched nearby genes induced by TCPOBOP and chromatin closing was highly enriched nearby genes repressed by TCPOBOP, consistent with TCPOBOP-responsive ΔDHS serving as enhancers and promoters that positively regulate CAR-responsive genes. Gene expression changes lagged behind chromatin opening or closing for a subset of TCPOBOP-responsive ΔDHS. ΔDHS that were specifically responsive to TCPOBOP in male liver were significantly enriched for genomic regions with a basal male bias in chromatin accessibility; however, the male-biased response of hepatocellular carcinoma-related genes to TCPOBOP was not associated with a correspondingly male-biased ΔDHS response. These studies elucidate the genome-wide organization of CAR-responsive genes and of the thousands of associated genomic sites where TCPOBOP exposure induces both rapid and persistent changes in chromatin accessibility. gene expression/regulation, receptor, nuclear hormone, gene expression/regulation, bioinformatics, methods, hepatic, systems toxicology, DNase-Seq, cytochrome P450, biotransformation and toxicokinetics, constitutive androstane receptor The role of xenochemical receptors, including CAR (constitutive androstane receptor; Nr1i3) (Kobayashi et al., 2015; Yan and Xie, 2016), in the disruptive actions of environmental chemicals on gene expression has long been recognized; however, progress in understanding underlying mechanisms of action has been hampered by the complexity of gene responses and the multiplicity of pathways involved. CAR is activated by structurally diverse environmental chemicals derived from consumer products, pharmaceuticals, and industrial chemicals (Baldwin and Roling, 2009; Chang and Waxman, 2006; DeKeyser et al., 2011; Eveillard et al., 2009; Ito et al., 2012; Omiecinski et al., 2011; Ren et al., 2010). Notable examples of foreign chemical CAR activators include bisphenol-A, a xenoestrogen, DEHP, a phthalate ester and rodent hepatocarcinogen, and TCPOBOP (1, 4-bis[2-(3, 5-dichloropyridyloxy)]benzene), a potent and highly specific agonist ligand of CAR (Tzameli et al., 2000). Activation of CAR by TCPOBOP induces diverse pathogenic responses, including hepatomegaly, liver tumor promotion, and hepatocarcinogenesis (Diwan et al., 1992; Huang et al., 2005; Yamamoto et al., 2004), as well as nonalcoholic steatohepatitis (Takizawa et al., 2011; Yamazaki et al., 2007). The transcriptional effects of CAR in the liver have recently been characterized on a transcriptome-wide basis by RNA-seq (Cui and Klaassen, 2016; Lodato et al., 2017), which is more reliable in distinguishing RNAs from closely related genes in a family or superfamily than microarray technology, and has allowed us to elucidate early, nuclear transcriptomic changes in both male and female mouse liver, including changes in the expression of many liver-expressed (Melia et al., 2016) long noncoding RNA (lncRNA) genes (Lodato et al., 2017). Environmental chemicals have widespread effects on the epigenome, which is a key determinant of the responsiveness of the genome to chemical exposure, the persistence of effects, and overall biological outcomes (Bowers and McCullough, 2017; Tapia-Orozco et al., 2017). Environmental chemicals may impact the genome by covalent modification of histone tails (chromatin marks), leading to altered recruitment of factors that control DNA compaction, chromatin accessibility, and the availability of genomic DNA for transcription factor binding. Changes in DNA methylation of gene regulatory regions also occur (Messerlian et al., 2017), but are largely secondary to the loss of chromatin accessibility and transcription factor binding (Stadler et al., 2011; Thurman et al., 2012). Although there are many descriptive studies of the epigenetic effects of environmental chemicals (Burris and Baccarelli, 2014; Casati et al., 2015; Thomson et al., 2014), far less is known about the underlying mechanisms whereby foreign chemical exposure induces such changes and their relationship to changes in gene expression. Changes in chromatin accessibility are a hallmark of epigenetic regulation and developmental plasticity, and can be identified on a genome-wide basis by limited DNase-I digestion of isolated nuclei followed by massively parallel sequencing (DNase-Seq) to discover DNase-I hypersensitive sites (DHS) (Ling et al., 2010; Thurman, et al., 2012). DHS encompass a large fraction of functional cis-regulatory elements (notably, promoters, enhancers, silencers, and insulators) in mammalian cells (Shlyueva et al., 2014), including mouse liver (Sugathan and Waxman, 2013; Yue et al., 2014). Recent advances led by the Mouse ENCODE Consortium have identified several hundred thousand putative regulatory elements across many mouse cell lines and tissues, including liver, through a combination of DNase-seq and ChIP-seq analysis of histone modifications and transcription factor binding sites (Yue et al., 2014). However, the tissue samples analyzed were not subjected to any experimental treatments and thus the datasets produced have not identified regulatory elements that are dynamically activated or repressed following exposure to foreign chemicals, including those that activate transcription factors such as CAR. Historically, our understanding of how genomes are organized was based on a few select locus control regions that were known to influence the expression of genes regionally, within a localized cluster (Fraser and Grosveld, 1998). More recent studies reveal a segmentation of the mammalian genome into megabase-scale chromatin loops known as topologically associating domains (TADs) that are largely conserved between tissues (Bonev and Cavalli, 2016; Rao et al., 2014). TADs are identified as contact domains visualized in Hi-C interaction maps (Rowley et al., 2017) and are delineated by looped chromatin structures whose boundaries are established by the DNA-binding protein CTCF and the ring-shaped cohesin complex (Hansen et al., 2018). Importantly, the genomic architecture and chromatin structure within TADs play an important role in constraining potential contacts between promoters and distal enhancers to intra-TAD genomic sequences. Thus, a refined approach to identifying DNA regulatory elements that control target gene expression is to limit the consideration to interactions within TAD boundaries. Further, the insulated DNA loops that TADs form may allow for rapid, coordinated gene regulation of gene families within localized genomic clusters (Le Dily and Beato, 2015). Here, we characterize the TAD-based organization of TCPOBOP-responsive RefSeq and lncRNA genes (Lodato et al., 2017) to elucidate the structural and functional organization of CAR-responsive gene targets across the genome. We also use DNase-seq to identify several thousand sites (ΔDHS regions) where TCPOBOP exposure induces a significant change in chromatin accessibility, and we relate these ΔDHS to TAD organization and TCPOBOP-induced gene expression changes. Finally, we investigate the link between basal sex differences in gene expression and chromatin accessibility, TADs that show sex-dependent responses to TCPOBOP, and male-biased transcriptional responses associated with hepatocarcinogenesis. MATERIALS AND METHODS Animal procedures and liver extraction All animal work was conducted in accordance with accepted standards of humane animal care, in compliance with procedures and protocols approved by the Boston University Institutional Animal Care and Use Committee. Animal handling and treatments were performed as described previously (Lodato, et al., 2017). Briefly, male and female CD1 mice (ICR strain), 7-weeks old, were purchased from Charles River Laboratories (Wilmington, MA) and kept on a 12-h light cycle (7:30 am–7:30 pm). Mice were treated with TCPOBOP (Sigma, catalog no. T1443) at a dose of 3 mg/kg body weight or with vehicle alone (corn oil containing 1% DMSO) by i.p. injection between 8:00 am and 8:45 am on day 1. Livers were collected 3 h later, or after 27 h (3 h + 24 h), ie, between 11:00 am and 11:45 am on day 2, to control for the strong effects of circadian rhythm on gene expression in mouse liver (Kettner et al., 2016). Nuclei were isolated from individual vehicle-treated (control) and TCPOBOP-treated mouse livers as described (Lodato et al., 2017). Briefly, fresh liver tissue was homogenized in buffer on ice in a Potter-Elvehjem homogenizer. The homogenate was layered on fresh homogenization buffer and spun at 4°C in an ultracentrifuge for 35 min at 25 000 rpm. For DNase-I hypersensitivity assays (see below), pellets containing approximately 150 million nuclei were resuspended in 400 μl of nuclei storage buffer and stored at −80°C until used for DNase-I digestion and DHS analysis. DNase-I hypersensitivity assay Frozen liver nuclei in nuclei storage buffer, corresponding to ∼30 million nuclei, were rinsed three times in ice-cold Buffer A (15 mM Tris-Cl pH 8.0, 15 mM NaCl, 60 mM KCl, 1 mM EDTA pH 8.0, 0.5 mM EGTA pH 8.0, 0.5 mM spermidine, 0.3 mM spermine tetrahydrochloride) by adding 500 μl Buffer A and pelleting the nuclei at 1500 rpm for 10 min at 4°C. Following the final rinse, nuclear pellets were resuspended in Buffer D (Buffer A + 6 mM CaCl2, 75 mM NaCl) prewarmed to 37°C, to give a concentration of 5 × 106 nuclei per 0.85 ml. A total of 32 units of DNase-I enzyme (RQ1 RNase-Free DNase, 1 U/μl; Promega, catalog no. M610A) was added to 68 μl of prewarmed Buffer D in a 2-ml tube and incubated for 30 s at 37°C. The 0.85 ml containing 5 × 106 resuspended nuclei was added to the 2-ml tube and digested with DNase I for precisely 2 min. After 2 min, 950 μl of Stop Buffer (50 mM Tris-HCl pH 8.0, 100 mM NaCl, 0.1% [v/v] SDS, 100 mM EDTA pH 8.0, 1 mM spermidine, 0.3 mM spermine tetrahydrochloride, 20 μg/ml RNase A) was added and the sample was immediately placed in a 55°C water bath. DNase-I digestion was carried out using a total of 30 million nuclei per mouse liver, divided into six separate reaction tubes, which were processed in parallel for DNase digestion. Samples were then incubated at 55°C for >15 min. About 5 μl proteinase K was then added, and the samples were further incubated at 55°C overnight. The six parallel DNase digestions were pooled and the DNA was isolated by phenol: chloroform extraction. The final supernatant was adjusted to 0.8 M NaCl. Digested material was size selected by sucrose gradient centrifugation as follows. First, phenol: chloroform extracted material (11.4 ml) was loaded on a sucrose gradient containing the following layers (bottom to top): 12 ml of 20% sucrose buffer (20 mM Tris-HCl pH 8.0, 5 mM EDTA pH 8.0, 1 M NaCl, containing 20% sucrose) and then 3 ml each of 17.5%, 15.0%, 12.5%, and 10.0% sucrose buffer, for a total volume of 34.5 ml. The sucrose gradient was centrifuged at 25 000 rpm for 24 h at 25°C. Fractions (1.9 ml) were sequentially removed from the top of the gradient, and fractions numbered 7–11, corresponding to digested material ∼100 bp to ∼1000 bp in length, were isolated and pooled. Material from fractions 7–11 was further purified on a QIAprep 2.0 spin column (Qiagen) according to the manufacturer’s manual. Agencount AMPure XP bead purification was performed using the manufacturer’s protocol with ratios of 0.6x and 1.9x for double-sided size selection, designed to obtain 125–400 bp DNA fragments. DNase-seq libraries, sequencing, and data analysis DNase-seq was performed for each of the following four treatment groups and four control groups: livers from male and female mice treated with TCPOBOP for either 3 or 27 h (ie, four TCPOBOP treatment groups), and sex- and time-matched vehicle control (ie, four control groups). Two sequence libraries (biological replicate pools) were prepared for each of the 8 groups, for a total of 16 sequence libraries. Each biological replicate pool consisted of genomic DNA fragments released by DNase-I digestion of nuclei prepared from n = 3–5 individual livers as follows: DNase-I digestion reactions were set up in parallel using nuclei isolated from 3 to 5 individual mouse livers. DNase-released fragments were purified from each of the individual reactions, as described above, and then combined to give a single sample, which was used to prepare a single sequencing library. A second (biological replicate) sequence library was prepared in the same manner by digestion of nuclei isolated from n = 3–5 other livers from mice in the same treatment or control group. Each sequencing library was prepared from 5 ng of the pooled DNase-I released DNA fragments using the NEBNext Ultra DNA Library Prep Kit for Illumina (New England Biolabs). Sequencing was performed at the New York Genome Center (New York, New York) on an Illumina HiSeq-2500 instrument, and single-end sequence reads, 50 bp in length, were obtained at a sequencing depth ranging from 33 to 79 million total mapped reads for each condition. More detailed sequencing statistics are shown in Supplementary Table 1A. Raw and processed data are available at www.ncbi.nlm.nih.gov/gds under accession GSE104061. Sequencing data was analyzed using a custom DNase-seq pipeline. The pipeline processes raw FASTQ files and outputs various quality control metrics, including FASTQC reports (FASTX-Toolkit v0.0.13.2), confirmation of read length, verification of the absence of read strand bias, quantification of contaminating adapter sequence (Trim_galore v0.4.2). Reads were mapped to the mouse genome (release mm9) using Bowtie2 (v2.2.6) (Langmead et al., 2009). Regions of DNase hypersensitivity (DHS) were discovered as peaks identified by MACS2 (v2.1.0.20150731) (Zhang et al., 2008) using the options (–nomodel –shift-100 –extsize 200), to inhibit read shifting, and (–keep-dup), to retain all reads that contribute to a peak signal. Peaks were discovered for each of n = 4 DNase-seq samples per TCPOBOP treatment condition, ie, n = 2 vehicle-treated and n = 2 TCPOBOP-treated DNase-seq samples (n = 2 biological replicate pools, as described above) × 4 conditions (male and female, at 3 and 27 h). The final DHS peak list was filtered to remove ENCODE blacklisted regions (Consortium, 2012) as well as peaks comprised of >4 identical reads that do not overlap any other read (“straight peaks”). The 16 resultant DHS peak lists were merged using mergeBed (BEDtools) to give a single list of 61 220 DHS regions, corresponding to the union of all DHS peak regions. A subset comprised of 60 739 DHS mapped to TADs with at least one RefSeq or multi-exonic lncRNA gene (Supplementary Table 1B), and was used for all downstream analyses, which were TAD and gene target based. The 481 DHS omitted from these downstream analyses are listed in Supplementary Table 1C. DHS peak normalization DHS regions to be visualized in the UCSC genome browser (https://genome.ucsc.edu/, last accessed date April 9, 2018) were normalized using sequence reads in each DHS peak region per million mapped sequence reads (reads-in-peaks-per-million, RiPPM) as a scaling factor. First, to obtain a comprehensive list of DHS peak regions for each dataset (termed peak union), FASTQ files from individual biological replicates were concatenated to produce combined replicates. For each DNase-seq dataset, we generated a vehicle-treated combined sample, a TCPOBOP-treated combined sample, and an all-replicates (vehicle-treated + TCPOBOP-treated) combined sample. DHS peak regions identified in the individual and combined samples were concatenated into a single file, and then BEDtools merge was used to combine overlapping features to generate a single list of nonoverlapping DHS peaks. The fraction of reads in peaks for each sample was then calculated to obtain a scaling factor. Raw read counts were divided by this per-million scaling factor to obtain RiPPM normalized read counts. ΔDHS and static DHS Genomic regions that were more open or more closed (|fold-change| > 2 and FDR < 0.05 [Benjamini-Hochberg adjusted p-value]) following TCPOBOP exposure were discovered by diffReps analysis (Shen et al., 2013) using the nucleosome option (200 bp window size) and setting (–frag) to zero for all comparisons. diffReps-identified regions that overlap the set of 60 739 merged DHS regions that map to a TAD with one or more genes (Supplementary Table 1B; see above), as determined using BEDtools (Quinlan and Hall, 2010), were designated ΔDHS (ie, DHS regions that significantly open or that close under each condition of TCPOBOP exposure). In some cases, the diffReps-identified region was narrower than the overlapping merged DHS. A ΔDHS was designated robust if there was a >2-fold difference in normalized sequence read counts across the entire merged DHS region between the TCPOBOP-treated and vehicle control liver samples, based on read counts combined over all biological replicates for the exposure condition. All other ΔDHS regions were designated standard ΔDHS. The combined list of robust + standard ΔDHS was used in all analyses, except where noted. The subset of the 60 739 DHS regions that did not overlap a diffReps region were designated static DHS for that condition of TCPOBOP exposure. 55 866 of the 60 739 DHS regions did not show significant chromatin opening or closing under any of the four TCPOBOP exposures studied here, and were used for enrichment analysis (see below). DHS were mapped to TADs using BEDtools, based on genomic boundaries for each of 3617 mouse liver TADs defined previously (Vietri Rudan et al., 2015) (Supplementary Table 2A) and a minimum of 1 bp overlap, as listed in Supplementary Table 2B. A small number of DHS overlapped two TADs (ie, the DHS spanned a TAD boundary); these were arbitrarily assigned to the lower number TAD. A total of 148 of the TAD regions did not contain any RefSeq or liver-expressed multi-exonic lncRNA genes. Mapping of TCPOBOP-responsive genes to DHS and to TADs RefSeq and lncRNA genes that were significantly induced or repressed in male and/or in female mouse liver after 3 or 27 h TCPOBOP exposure were identified (Lodato et al., 2017) based on a gene list comprised of 24 197 RefSeq genes and 3152 multi-exonic lncRNA genes. The TCPOBOP-responsive gene sets used here were defined by a |fold change| >1.5 and adjusted p-value (FDR) <.001 (for RefSeq genes), and by |fold change| >2 and adjusted p-value (FDR) <.05 (lncRNA genes). A single putative gene target (RefSeq or lncRNA gene) was assigned to each DHS by using BEDtools to map each of the 60 739 DHS to the closest gene transcription start site within the same TAD (see above). Supplementary Table 1B presents the putative gene target of each of the 60 739 DHS and the gene’s response to each condition of TCPOBOP exposure, as well as the response of each DHS to TCPOBOP exposure (ΔDHS and static DHS). The number of genes within each TAD that were upregulated or downregulated by TCPOBOP exposure, and the number of opening and closing ΔDHS within each TAD, were counted for each of the four TCPOBOP exposures and are shown in Supplementary Table 2B. Enrichment analysis Enrichments of ΔDHS mapping to TCPOBOP-responsive genes were calculated for each ΔDHS set (eg, DHS that open in male liver after 3 h TCPOBOP exposure, and genes upregulated in male liver by that same exposure) as follows: Enrichment score = ratio A/ratio B, where: ratio A = number of ΔDHS that respond to a given TCPOBOP exposure that map to the corresponding set of TCPOBOP-responsive genes, divided by the number of ΔDHS from that same ΔDHS set whose putative target gene does not show the corresponding response to TCPOBOP at that time point; and ratio B = the number of static DHS mapping to the same given set of correspondingly TCPOBOP-responsive genes, divided by the number of static DHS whose putative target gene does not show the corresponding response to TCPOBOP. For example, in males treated with TCPOBOP for 3 h, 70 ΔDHS that open each map to a 3 h TCPOBOP-induced gene, and 402 other ΔDHS that open each map to a gene that is not induced by the same TCPOBOP exposure (70/402 = 0.174), whereas 393 static DHS each map to a 3 h TCPOBOP-induced gene, and 55 473 static DHS each map to a gene not induced by the same TCPOBOP exposure (393/55 473 = 0.007), which gives an enrichment score = 24.6 (A/B = 0.174/0.007 = 24.9). The static DHS used for these enrichment calculations correspond to the set of 55 866 DHS (393 + 55 473, in the above example) that map to a TAD containing at least one gene, and do not show DHS opening or DHS closing at any of the 4 TCPOBOP exposure conditions. Genes that are downstream targets of 10 known CAR-dependent upstream regulators of liver carcinogenesis (hepatocellular carcinoma, HCC), namely cyclin D1, p53, p21, FoxO1, FoxM1, Rb, β-catenin, E2f, Yap, and Myc, were those identified previously (Lodato et al., 2017). The sex bias in the 27 h TCPOBOP-induced ΔDHS that map to the downstream gene targets of these 10 HCC upstream regulators was calculated as follows: Enrichment score = ratio A/ratio B, where: ratio A = (27 h TCPOBOP-induced male liver ΔDHS that map to the HCC target gene set)/(all male liver DHS associated with those target genes); and ratio B = (27 h TCPOBOP-induced female liver ΔDHS that map to the HCC target gene set)/(all female liver DHS associated with those target genes). Enrichments were calculated for the following sets of HCC target genes: all downstream target genes of the 10 regulators (n = 4336 genes); all downstream targets that are TCPOBOP responsive (n = 378 genes); all downstream targets that are induced by 27 h TCPOBOP exposure in male liver but not in female liver (n = 153 genes); and all downstream targets that are induced by 27 h TCPOBOP exposure in both male and female liver or in female liver only (n = 225 genes) (Supplementary Table 3) (Lodato et al., 2017). Sex-biased TCPOBOP-responsive TADs and sex-biased genes and DHS TADs with at least two genes responsive to 27 h TCPOBOP exposure (RefSeq and/or lncRNA genes, using the thresholds for responsiveness defined above) were considered to have a sex-biased TCPOBOP response if all of the responsive genes in the TAD respond to TCPOBOP in one sex but not the other. For example, a TAD with three TCPOBOP-responsive genes was considered to be male-biased in its responsiveness if all three genes responded to 27 h TCPOBOP exposure in male but not female liver. Likewise, a TAD was considered female-biased if it contains two or more genes that responded to 27 h TCPOBOP exposure in female but not male liver. We did not require that all of the responsive genes within the TAD respond in the same direction, eg, one gene may be upregulated and two may be downregulated; however, all three genes must respond in the same sex to qualify. The numbers of TADs with single versus multiple TCPOBOP-responsive genes are shown in Supplementary Table 4, and the number of ΔDHS associated with those TADs are shown in Supplementary Table 5. Genes that showed a basal sex bias in expression at FDR < 0.01 (corresponding to minimum fold change of ∼1.4) were identified using a nuclear, polyA-selected RNA-seq dataset comprised of n = 3 sequencing libraries per sex (Connerney et al., 2017), with each library prepared from a pool of nuclear RNA samples derived from n = 8 to 11 individual mouse livers. A total of 597 such basal male-biased and 559 basal female-biased RefSeq genes were identified, as were 309 basal male-biased and 203 basal female-biased lncRNAs. Genomic regions with a basal sex bias in chromatin accessibility (2800 male-biased DHS and 1379 female-biased DHS) were part of a set of ∼72 000 mouse liver DHS identified earlier (Ling et al., 2010) and were overlapped with the set of 60 739 mouse liver DHS described here. TADs with a sex-biased response to TCPOBOP exposure (Supplementary Table 6A) and TADs with basally sex-biased DHS, as defined previously for untreated male and female mouse liver (Ling et al., 2010), are shown in Supplementary Table 6B. Statistical analysis Fisher Exact test was implemented in the analysis package R to assess the statistical significance of enrichment calculations. Student t test was implemented using Prism 7 (GraphPad) to assess pair-wise relationships. RESULTS TCPOBOP-Induced Genes Cluster in Different TADs Than TCPOBOP-Repressed Genes Mammalian genomes are functionally segmented into large megabase-scale DNA loops, called TADs. TADs insulate genomic regions by allowing for intra-TAD interactions while inhibiting inter-TAD interactions (Oti et al., 2016) and provide a structural framework that can facilitate coordinated transcriptional responses to stimuli (Le Dily and Beato, 2015). TAD boundaries are established for the 3617 TADs in mouse liver (Vietri Rudan et al., 2015), and can be used to map TCPOBOP-responsive genes (Lodato et al., 2017) to individual TAD regions. In male mouse liver, 173 genes that responded to 3 h TCPOBOP exposure (see Materials and Methods section) were distributed across 119 TAD regions, whereas in female liver, 287 genes responded to the same treatment and were distributed across 203 TADs (Figure 1A, Supplementary Table 4). The number of TAD regions with TCPOBOP-responsive genes increased up to 6-fold after 27 h, encompassing 14%–19% of all mouse liver TADs. Thus, TCPOBOP-responsive genes are widely distributed across the genome. Figure 1. View largeDownload slide TCPOBOP-responsive genes cluster in TADs. A, Distribution of the number of TADs that contain either a single TCPOBOP-responsive gene or multiple TCPOBOP-responsive genes in livers of mice treated with TCPOBOP for 3 or 27 h. Blue, TADs that contain gene(s) upregulated by TCPOBOP; red, TADs that contain gene(s) downregulated by TCPOBOP; gray, TADs that contain both upregulated genes and downregulated genes. Darker shades of blue and red indicate TADs with multiple TCPOBOP-responsive genes all responding in the same direction, as indicated. Pie chart sections are ordered as follows (counterclockwise): mixed, down (multiple, single), up (multiple, single). B, Percent of TADs with multiple TCPOBOP-responsive genes where all of the responsive genes in the TAD are either upregulated (blue), downregulated (red), or show a mixture of up and downregulatory responses (gray). See Supplementary Table 2B for a full listing of TCPOBOP-responsive TADs and the corresponding numbers of up and downregulated genes in each exposure group, and see Supplementary Table 4 for aggregate gene and TAD numbers (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 1. View largeDownload slide TCPOBOP-responsive genes cluster in TADs. A, Distribution of the number of TADs that contain either a single TCPOBOP-responsive gene or multiple TCPOBOP-responsive genes in livers of mice treated with TCPOBOP for 3 or 27 h. Blue, TADs that contain gene(s) upregulated by TCPOBOP; red, TADs that contain gene(s) downregulated by TCPOBOP; gray, TADs that contain both upregulated genes and downregulated genes. Darker shades of blue and red indicate TADs with multiple TCPOBOP-responsive genes all responding in the same direction, as indicated. Pie chart sections are ordered as follows (counterclockwise): mixed, down (multiple, single), up (multiple, single). B, Percent of TADs with multiple TCPOBOP-responsive genes where all of the responsive genes in the TAD are either upregulated (blue), downregulated (red), or show a mixture of up and downregulatory responses (gray). See Supplementary Table 2B for a full listing of TCPOBOP-responsive TADs and the corresponding numbers of up and downregulated genes in each exposure group, and see Supplementary Table 4 for aggregate gene and TAD numbers (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Next, we investigated whether TCPOBOP-responsive genes cluster in TADs. In both sexes, ∼20%–30% of the TADs with genes responding to TCPOBOP contain multiple (up to 12) TCPOBOP-responsive genes. These TADs encompass 44%–52% of all genes that respond to TCPOBOP under a given condition (Supplementary Table 4). TADs that contain multiple TCPOBOP-responsive genes were further classified by the concurrence of the directionality of TCPOBOP gene responses within the TAD. A majority (64%–91%) of TADs with multiple TCPOBOP-responsive genes showed consistent regulation within the TAD, ie, all of the TCPOBOP genes within the TAD are either upregulated or are downregulated (Figure 1B). Overall, the TADs with clustered, consistently responding genes encompass 31%–38% of all TCPOBOP-responsive genes (Supplementary Table 4). TCPOBOP Induces Widespread Changes in Chromatin Accessibility The impact of TCPOBOP on liver chromatin accessibility was determined by limited DNase digestion of liver nuclei harvested from vehicle control and from TCPOBOP-exposed mice. DNase-seq analysis of the genomic DNA fragments released by DNase digestion identified accessible chromatin regions (DNase hypersensitive sites, DHS), which encompass up to 90% of binding sites for liver-expressed transcription factors (Ling et al., 2010). DNase-seq signals were analyzed using diffReps (Shen et al., 2013) to discover genomic regions where TCPOBOP exposure induces a significant change in chromatin accessibility (ΔDHS regions) in either male or female liver (Figure 2A, Supplementary Table 1B). We found that TCPOBOP exposure stimulated DHS opening as well as DHS closing, with 500–600 ΔDHS regions seen 3 h after TCPOBOP exposure, and ∼2000–3000 ΔDHS regions seen after 27 h. The large increase in ΔDHS in the 27 h TCPOBOP-exposed livers is consistent with the larger number of genes and greater magnitude of gene induction responses in liver nuclei after 27 h compared with after 3 h TCPOBOP exposure (Lodato et al., 2017). Further, a majority ΔDHS were unique to one sex (Figure 2B), consistent with the sex differences in gene responses to TCPOBOP exposure described previously (Lodato et al., 2017). Figure 2. View largeDownload slide TCPOBOP-induced chromatin opening and closing: ΔDHS regions. A, Venn diagrams showing overlap of TCPOBOP-induced ΔDHS regions after 3 h versus 27 h exposure. B, Overlap of ΔDHS regions between male and female mouse liver at each TCPOBOP time point. ΔDHS regions were identified for each TCPOBOP exposure condition based on the merged list of 60 739 DHS regions (Supplementary Table 1B). Only ΔDHS that responded in the same direction at the time points compared (A) or in the comparison of sexes (B) were considered overlapping (eg, ΔDHS that open in males at 3 h and ΔDHS that open in males at 27 h; ΔDHS that close in males at 3 h and ΔDHS that close in males at 27 h, etc.). Up to 3 ΔDHS in each dataset showed inconsistent responses to TCPOBOP at 3 h versus 27 h (A), or between male and female livers (B), and were excluded from the numbers shown. C, ΔDHS regions shown in (A) are separated into sets of ΔDHS that open (left) or close (right) for each TCPOBOP exposure, and are counted based on whether they do (black) or do not (gray) contain at least one TCPOBOP-responsive gene at that time point whose transcription start site is in the same TAD as the ΔDHS region. D, ΔDHS regions that open or close and contain at least one TCPOBOP-responsive gene (black bars in C) are colored to indicate whether the TCPOBOP-responsive genes within the same TAD as the ΔDHS are all upregulated (red), downregulated (blue), or mixed with regard to the directionality of their responses to TCPOBOP (black). See Supplementary Table 5 for a more detailed listing (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 2. View largeDownload slide TCPOBOP-induced chromatin opening and closing: ΔDHS regions. A, Venn diagrams showing overlap of TCPOBOP-induced ΔDHS regions after 3 h versus 27 h exposure. B, Overlap of ΔDHS regions between male and female mouse liver at each TCPOBOP time point. ΔDHS regions were identified for each TCPOBOP exposure condition based on the merged list of 60 739 DHS regions (Supplementary Table 1B). Only ΔDHS that responded in the same direction at the time points compared (A) or in the comparison of sexes (B) were considered overlapping (eg, ΔDHS that open in males at 3 h and ΔDHS that open in males at 27 h; ΔDHS that close in males at 3 h and ΔDHS that close in males at 27 h, etc.). Up to 3 ΔDHS in each dataset showed inconsistent responses to TCPOBOP at 3 h versus 27 h (A), or between male and female livers (B), and were excluded from the numbers shown. C, ΔDHS regions shown in (A) are separated into sets of ΔDHS that open (left) or close (right) for each TCPOBOP exposure, and are counted based on whether they do (black) or do not (gray) contain at least one TCPOBOP-responsive gene at that time point whose transcription start site is in the same TAD as the ΔDHS region. D, ΔDHS regions that open or close and contain at least one TCPOBOP-responsive gene (black bars in C) are colored to indicate whether the TCPOBOP-responsive genes within the same TAD as the ΔDHS are all upregulated (red), downregulated (blue), or mixed with regard to the directionality of their responses to TCPOBOP (black). See Supplementary Table 5 for a more detailed listing (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Unexpectedly, only 22%–30% of 3 h TCPOBOP-responsive ΔDHS mapped to TADs that contain a TCPOBOP-responsive gene(s) (Figure 2C, Supplementary Table 5). This percentage increased to 40%–45% after 27 h TCPOBOP exposure. These percentages showed only marginal increases when robust ΔDHS (see Materials and Methods section) were considered (Supplementary Table 5, Part B). For the ΔDHS that do map to TADs containing TCPOBOP-responsive genes, DHS opening was primarily associated with gene induction and DHS closing with gene repression (Figure 2D). Thus, TCPOBOP-responsive ΔDHS are associated with positive regulation of gene expression. In most cases, the TCPOBOP gene-responsive TADs contain either upregulated genes or downregulated genes, rather than a mixture of up and downregulatory responses (Figure 2D, Supplementary Table 5). Overall, 84%–90% of the opening DHS associated with TCPOBOP-responsive TADs at 3 h were devoid of any downregulated genes in the TAD (Supplementary Table 5). After 27 h, this percentage decreased to 76%–78%, which may reflect the inclusion of secondary gene responses. Several TADs with TCPOBOP-responsive drug metabolizing enzyme gene families contain many ΔDHS, such as TAD3479, which contains up to 38 ΔDHS regions and 9–12 TCPOBOP-inducible Cyp2c genes (Table 1, Supplementary Table 2B). Highly active TADs with drug metabolizing enzyme gene families and multiple ΔDHS include: TAD1421, with Cyp2b genes (Figure 3A); TAD694, with Gstm genes (Figure 3B); and TAD3479, with Cyp2c genes (Figure 3C). Several ΔDHS nearby metallothionein genes Mt1 and Mt2 close after 27 h TCPOBOP exposure. Consistent with this, Mt1 and Mt2 and two nearby noncoding RNAs, lnc_7332 and lnc_7334, are downregulated after 27 h TCPOBOP exposure (Figure 3D). Table 1. Highly Active TADs Number of ΔDHS in TAD Number of TCPOBOP-responsive genes in TAD Annotation Male 3 h Male 27 h Female 3 h Female 27 h Male 3 h Male 27 h Female 3 h Female 27 h TAD3479_chr19 7 35 14 38 11 12 9 9 Cyp2c locus TAD1421_chr7 6 16 8 15 3 3 3 4 Cyp2b10 and lncRNAs TAD1132_chr5 8 13 7 5 4 4 4 3 Por and lncRNAs; Rhbdd2 TAD1860_chr9 1 11 0 11 1 4 0 5 LncRNAs; down regulated genes TAD1512_chr7 5 10 5 14 1 3 1 3 Tsku and lncRNA TAD1156_chr5 1 9 4 10 4 4 3 9 Cyp3a locus TAD694_chr3 1 8 0 11 1 4 1 3 Gstm locus TAD1937_chr9 6 5 4 11 2 4 2 7 Alas1 and lncRNA Number of ΔDHS in TAD Number of TCPOBOP-responsive genes in TAD Annotation Male 3 h Male 27 h Female 3 h Female 27 h Male 3 h Male 27 h Female 3 h Female 27 h TAD3479_chr19 7 35 14 38 11 12 9 9 Cyp2c locus TAD1421_chr7 6 16 8 15 3 3 3 4 Cyp2b10 and lncRNAs TAD1132_chr5 8 13 7 5 4 4 4 3 Por and lncRNAs; Rhbdd2 TAD1860_chr9 1 11 0 11 1 4 0 5 LncRNAs; down regulated genes TAD1512_chr7 5 10 5 14 1 3 1 3 Tsku and lncRNA TAD1156_chr5 1 9 4 10 4 4 3 9 Cyp3a locus TAD694_chr3 1 8 0 11 1 4 1 3 Gstm locus TAD1937_chr9 6 5 4 11 2 4 2 7 Alas1 and lncRNA Examples of TADs with many TCPOBOP-responsive DHS and genes in the TAD. Some of the TADs show a dramatic increase in responding DHS and in responding genes between 3 and 27h (eg, TAD1860 and TAD694). See Supplementary Table 2B for a complete listing. Table 1. Highly Active TADs Number of ΔDHS in TAD Number of TCPOBOP-responsive genes in TAD Annotation Male 3 h Male 27 h Female 3 h Female 27 h Male 3 h Male 27 h Female 3 h Female 27 h TAD3479_chr19 7 35 14 38 11 12 9 9 Cyp2c locus TAD1421_chr7 6 16 8 15 3 3 3 4 Cyp2b10 and lncRNAs TAD1132_chr5 8 13 7 5 4 4 4 3 Por and lncRNAs; Rhbdd2 TAD1860_chr9 1 11 0 11 1 4 0 5 LncRNAs; down regulated genes TAD1512_chr7 5 10 5 14 1 3 1 3 Tsku and lncRNA TAD1156_chr5 1 9 4 10 4 4 3 9 Cyp3a locus TAD694_chr3 1 8 0 11 1 4 1 3 Gstm locus TAD1937_chr9 6 5 4 11 2 4 2 7 Alas1 and lncRNA Number of ΔDHS in TAD Number of TCPOBOP-responsive genes in TAD Annotation Male 3 h Male 27 h Female 3 h Female 27 h Male 3 h Male 27 h Female 3 h Female 27 h TAD3479_chr19 7 35 14 38 11 12 9 9 Cyp2c locus TAD1421_chr7 6 16 8 15 3 3 3 4 Cyp2b10 and lncRNAs TAD1132_chr5 8 13 7 5 4 4 4 3 Por and lncRNAs; Rhbdd2 TAD1860_chr9 1 11 0 11 1 4 0 5 LncRNAs; down regulated genes TAD1512_chr7 5 10 5 14 1 3 1 3 Tsku and lncRNA TAD1156_chr5 1 9 4 10 4 4 3 9 Cyp3a locus TAD694_chr3 1 8 0 11 1 4 1 3 Gstm locus TAD1937_chr9 6 5 4 11 2 4 2 7 Alas1 and lncRNA Examples of TADs with many TCPOBOP-responsive DHS and genes in the TAD. Some of the TADs show a dramatic increase in responding DHS and in responding genes between 3 and 27h (eg, TAD1860 and TAD694). See Supplementary Table 2B for a complete listing. Figure 3. View largeDownload slide ΔDHS that respond to TCPOBOP, visualized in genome browser. A, Six strong ΔDHS upstream of Cyp2b10 are induced by TCPOBOP at both 3 and 27 h, in both male and female liver. Cyp2b10 and lnc_5998 (green; both isoforms are shown) are strongly induced under all 4 TCPOBOP conditions. B, 5 to 6 ΔDHS in the vicinity of Gstm3 are induced by TCPOBOP at 27 h, but not at 3 h, in both male and female liver. C, Many ΔDHS open in the vicinity of Cyp2c53-ps and Cyp2c29, which are both induced by all 4 TCPOBOP exposures. D, ΔDHS that close at 27 h, but not after 3 h TCPOBOP treatment, surrounding metallothionein genes Mt1 and Mt2 and two nearby lncRNA genes. At the 27 h time point, Mt1 and Mt2 are repressed in both male and female liver, lnc_7332 is repressed in female liver only, and lnc_7334 is repressed in male liver only. None of the four genes are repressed at the 3 h TCPOBOP time point, consistent with the delayed closing of the ΔDHS shown here. Six browser tracks with reads-in-peaks normalized Wig file DNase-seq data (see Materials and Methods) are shown in each panel: vehicle-treated controls and 3 h and 27 h TCPOBOP-treated males (blue) and females (pink/red), as marked. In panels B, C, and D, black, red, and blue bars above each track indicate locations of DHS discovered by MACS2 analysis. Static DHS are marked in black bars. Dark red and dark blue bars indicate robust ΔDHS that open and close, respectively; light red and light blue bars indicate standard ΔDHS that open and close, respectively (see Materials and Methods). Bottom track in each panel marks DHS regions identified in untreated male and female mouse liver in our prior study (Ling, et al., 2010), many of which match the DHS shown in the tracks above, indicating that these DHS are highly reproducible (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 3. View largeDownload slide ΔDHS that respond to TCPOBOP, visualized in genome browser. A, Six strong ΔDHS upstream of Cyp2b10 are induced by TCPOBOP at both 3 and 27 h, in both male and female liver. Cyp2b10 and lnc_5998 (green; both isoforms are shown) are strongly induced under all 4 TCPOBOP conditions. B, 5 to 6 ΔDHS in the vicinity of Gstm3 are induced by TCPOBOP at 27 h, but not at 3 h, in both male and female liver. C, Many ΔDHS open in the vicinity of Cyp2c53-ps and Cyp2c29, which are both induced by all 4 TCPOBOP exposures. D, ΔDHS that close at 27 h, but not after 3 h TCPOBOP treatment, surrounding metallothionein genes Mt1 and Mt2 and two nearby lncRNA genes. At the 27 h time point, Mt1 and Mt2 are repressed in both male and female liver, lnc_7332 is repressed in female liver only, and lnc_7334 is repressed in male liver only. None of the four genes are repressed at the 3 h TCPOBOP time point, consistent with the delayed closing of the ΔDHS shown here. Six browser tracks with reads-in-peaks normalized Wig file DNase-seq data (see Materials and Methods) are shown in each panel: vehicle-treated controls and 3 h and 27 h TCPOBOP-treated males (blue) and females (pink/red), as marked. In panels B, C, and D, black, red, and blue bars above each track indicate locations of DHS discovered by MACS2 analysis. Static DHS are marked in black bars. Dark red and dark blue bars indicate robust ΔDHS that open and close, respectively; light red and light blue bars indicate standard ΔDHS that open and close, respectively (see Materials and Methods). Bottom track in each panel marks DHS regions identified in untreated male and female mouse liver in our prior study (Ling, et al., 2010), many of which match the DHS shown in the tracks above, indicating that these DHS are highly reproducible (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Some ΔDHS Responses Precede Changes in Gene Expression We considered the possibility that the opening DHS that map to TADs without TCPOBOP-responsive genes (Figure 2C) might target genes whose RNAs respond to TCPOBOP with a delay compared with DHS opening. Supporting this idea, a substantial fraction of the 3 h TCPOBOP-stimulated opening DHS that map to a TAD without a 3 h TCPOBOP gene response become associated with a gene response at 27 h (Figure 4A; 128 out of 366 such opening DHS in male liver [37.5%], and 102 out of 358 such DHS in female liver [28.5%]). Further, a subset of the 3 h TCPOBOP-stimulated closing DHS that map to a TAD without a 3 h TCPOBOP gene response become associated with a gene response at 27 h (Figure 4A; 9 of 62 such closing DHS [14.5%] in male liver, and 32 of 87 such DHS [37%] in female liver). Thus, gene expression changes lag behind chromatin opening or closing for a subset of 3 h TCPOBOP-responsive ΔDHS. Furthermore, in male liver, 92 of the 128 ΔDHS whose opening is associated with a delayed gene response are in a TAD that contains upregulated gene(s), whereas 3 of the 9 closing ΔDHS linked to a delayed gene response are in a TAD that contains downregulated gene(s) (Figure 4B). Similarly, in female liver, 83 of the 102 opening DHS linked to a delayed gene response are in a TAD with an upregulated gene(s), whereas 22 of the 32 closing DHS linked to a delayed gene response are in a TAD that contains a downregulated gene(s) (Figure 4B). Figure 4. View largeDownload slide TCPOBOP-induced DHS opening, or closing, may precede gene activation or repression. A, ΔDHS induced by 3 h TCPOBOP exposure that do not have a 3 h TCPOBOP-responsive gene in the same TAD (gray bars in Figure 2 C) were analyzed to determine whether the TADs containing those ΔDHS either do (white bars) or do not (red bars) contain one or more TCPOBOP-responsive genes at the 27 h time point. B, The 3 h ΔDHS whose associated gene(s) in the same TAD show a delayed response to TCPOBOP (white bars in A) were analyzed to determine whether (blue bars) or not (yellow bars), for one or more genes in the TAD, DHS opening at 27 h is associated with gene induction, and DHS closing at 27 h is associated with gene repression (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 4. View largeDownload slide TCPOBOP-induced DHS opening, or closing, may precede gene activation or repression. A, ΔDHS induced by 3 h TCPOBOP exposure that do not have a 3 h TCPOBOP-responsive gene in the same TAD (gray bars in Figure 2 C) were analyzed to determine whether the TADs containing those ΔDHS either do (white bars) or do not (red bars) contain one or more TCPOBOP-responsive genes at the 27 h time point. B, The 3 h ΔDHS whose associated gene(s) in the same TAD show a delayed response to TCPOBOP (white bars in A) were analyzed to determine whether (blue bars) or not (yellow bars), for one or more genes in the TAD, DHS opening at 27 h is associated with gene induction, and DHS closing at 27 h is associated with gene repression (The reader is referred to the web version of this article to clarify the references to color in this figure legend). ΔDHS Are Highly Enriched Nearby TCPOBOP-Responsive Genes Putative gene targets for each DHS were assigned by mapping the DHS to the nearest gene transcription start site within the same TAD, considering both RefSeq genes and liver-expressed multi-exonic lncRNA genes (Supplementary Table 1B). Next, we examined the relationship between changes in chromatin accessibility and changes in gene expression (ie, nuclear RNA levels) for the set of 120 ΔDHS that open in both sexes at 3 h and remain open at 27 h (ie, ΔDHS common to all 4 TCPOBOP exposure conditions; Table 2). These ΔDHS, whose induced open chromatin state persists for at least 24 h in both sexes, showed an exceptionally strong, 102-fold enrichment (p < E-41; Fisher Exact test) for genes that showed a common response to TCPOBOP in all four treatments (Table 3). A total of 27 of these 120 ΔDHS mapped to 19 TCPOBOP-responsive genes, including 6 lncRNA genes. Protein-coding RefSeq genes in this group include Cyp2b10, Cyp2c53-ps, Cyp2c55, Cyp3a11, Gadd45b, Gstt1, and Por. Table 2. ΔDHS That Respond in Multiple Datasets Open Close TCPOBOP Response Profile Number of ΔDHS All TCPOBOP-responsive DHS 3422 1432 Common responses in all 4 TCPOBOP datasets 120 1 Responds in male liver only 902 484 Responds in female liver only 1403 806 Early responding (male, female, or both) 803 164 Late responding only (male, female, or both) 2619 1268 Open Close TCPOBOP Response Profile Number of ΔDHS All TCPOBOP-responsive DHS 3422 1432 Common responses in all 4 TCPOBOP datasets 120 1 Responds in male liver only 902 484 Responds in female liver only 1403 806 Early responding (male, female, or both) 803 164 Late responding only (male, female, or both) 2619 1268 Shown are the number of ΔDHS in each of the indicated categories. All TCPOBOP-responsive DHS refer to the number of ΔDHS regions discovered in any one of the 4 TCPOBOP exposure conditions. Common responses in all 4 TCPOBOP datasets refer to those ΔDHS that respond in all 4 conditions. Responds in male (or in female) liver only: those ΔDHS that respond in male liver (or female liver) at 3 and/or 27 h, but do not respond in the other sex at either time point. Early responding refers to ΔDHS that respond to TCPOBOP at 3 h, in either or both sexes, independent of their responsiveness at 27 h. Late responding only refers to ΔDHS that respond to TCPOBOP at 27 h, but that are static at 3 h, in either or in both sexes. The numbers shown exclude 19 of the 4873 “all TCPOBOP-responsive DHS” (ie, 0.4% of all ΔDHS), which show discrepant responses to TCPOBOP, eg, they open at one time point, or in one sex, but close at another time point or in the other sex, as is marked in Supplementary Table 1B. Table 2. ΔDHS That Respond in Multiple Datasets Open Close TCPOBOP Response Profile Number of ΔDHS All TCPOBOP-responsive DHS 3422 1432 Common responses in all 4 TCPOBOP datasets 120 1 Responds in male liver only 902 484 Responds in female liver only 1403 806 Early responding (male, female, or both) 803 164 Late responding only (male, female, or both) 2619 1268 Open Close TCPOBOP Response Profile Number of ΔDHS All TCPOBOP-responsive DHS 3422 1432 Common responses in all 4 TCPOBOP datasets 120 1 Responds in male liver only 902 484 Responds in female liver only 1403 806 Early responding (male, female, or both) 803 164 Late responding only (male, female, or both) 2619 1268 Shown are the number of ΔDHS in each of the indicated categories. All TCPOBOP-responsive DHS refer to the number of ΔDHS regions discovered in any one of the 4 TCPOBOP exposure conditions. Common responses in all 4 TCPOBOP datasets refer to those ΔDHS that respond in all 4 conditions. Responds in male (or in female) liver only: those ΔDHS that respond in male liver (or female liver) at 3 and/or 27 h, but do not respond in the other sex at either time point. Early responding refers to ΔDHS that respond to TCPOBOP at 3 h, in either or both sexes, independent of their responsiveness at 27 h. Late responding only refers to ΔDHS that respond to TCPOBOP at 27 h, but that are static at 3 h, in either or in both sexes. The numbers shown exclude 19 of the 4873 “all TCPOBOP-responsive DHS” (ie, 0.4% of all ΔDHS), which show discrepant responses to TCPOBOP, eg, they open at one time point, or in one sex, but close at another time point or in the other sex, as is marked in Supplementary Table 1B. Table 3. Enrichment Scores Enrichment Score p-Value Common ΔDHS mapping to common genes 101.7 <E-41 Male, 3 h Open ΔDHS mapping to up genes 24.9 <E-64 Close ΔDHS mapping to down genes 0 1 Male, 27 h Open ΔDHS mapping to up genes 8.3 <E-199 Close ΔDHS mapping to down genes 5.9 <E-27 Female, 3 h Open ΔDHS mapping to up genes 24.3 <E-92 Close ΔDHS mapping to down genes 5.2 <E-02 Female, 27 h Open ΔDHS mapping to up genes 10.6 <E-277 Close ΔDHS mapping to down genes 8.7 <E-64 Enrichment Score p-Value Common ΔDHS mapping to common genes 101.7 <E-41 Male, 3 h Open ΔDHS mapping to up genes 24.9 <E-64 Close ΔDHS mapping to down genes 0 1 Male, 27 h Open ΔDHS mapping to up genes 8.3 <E-199 Close ΔDHS mapping to down genes 5.9 <E-27 Female, 3 h Open ΔDHS mapping to up genes 24.3 <E-92 Close ΔDHS mapping to down genes 5.2 <E-02 Female, 27 h Open ΔDHS mapping to up genes 10.6 <E-277 Close ΔDHS mapping to down genes 8.7 <E-64 The 60 739 DHS regions (ΔDHS and static DHS) were each mapped to a single putative gene target (closest transcription start site within the same TAD) as shown in Supplementary Table 1B. Enrichment scores for the indicated TCPOBOP-responsive gene sets were calculated as described in Materials and Methods section. Enrichment of common peaks to common genes was calculated based on ΔDHS that open in all 4 TCPOBOP conditions and that map to genes that respond in all 4 conditions (males and females, 3 and 27 h). Table 3. Enrichment Scores Enrichment Score p-Value Common ΔDHS mapping to common genes 101.7 <E-41 Male, 3 h Open ΔDHS mapping to up genes 24.9 <E-64 Close ΔDHS mapping to down genes 0 1 Male, 27 h Open ΔDHS mapping to up genes 8.3 <E-199 Close ΔDHS mapping to down genes 5.9 <E-27 Female, 3 h Open ΔDHS mapping to up genes 24.3 <E-92 Close ΔDHS mapping to down genes 5.2 <E-02 Female, 27 h Open ΔDHS mapping to up genes 10.6 <E-277 Close ΔDHS mapping to down genes 8.7 <E-64 Enrichment Score p-Value Common ΔDHS mapping to common genes 101.7 <E-41 Male, 3 h Open ΔDHS mapping to up genes 24.9 <E-64 Close ΔDHS mapping to down genes 0 1 Male, 27 h Open ΔDHS mapping to up genes 8.3 <E-199 Close ΔDHS mapping to down genes 5.9 <E-27 Female, 3 h Open ΔDHS mapping to up genes 24.3 <E-92 Close ΔDHS mapping to down genes 5.2 <E-02 Female, 27 h Open ΔDHS mapping to up genes 10.6 <E-277 Close ΔDHS mapping to down genes 8.7 <E-64 The 60 739 DHS regions (ΔDHS and static DHS) were each mapped to a single putative gene target (closest transcription start site within the same TAD) as shown in Supplementary Table 1B. Enrichment scores for the indicated TCPOBOP-responsive gene sets were calculated as described in Materials and Methods section. Enrichment of common peaks to common genes was calculated based on ΔDHS that open in all 4 TCPOBOP conditions and that map to genes that respond in all 4 conditions (males and females, 3 and 27 h). For each of the four TCPOBOP exposure conditions, we observed strong enrichment of DHS that open for genes that are upregulated, when compared with a background set comprised of TCPOBOP-unresponsive DHS (ie, static DHS) (Table 3). Similarly, in both sexes, DHS that close were strongly enriched for genes that are downregulated by TCPOBOP at 27 h. There was also a weak enrichment of ΔDHS that close for genes that are downregulated at 3 h in females, but not in males. In all cases, enrichments were stronger when we considered robust ΔDHS (see Materials and Methods; Supplementary Table 7). These findings support the proposal that these sets of TCPOBOP-responsive DHS encompass regulatory elements (enhancers and promoters) for TCPOBOP-stimulated gene responses that are either activated by TCPOBOP, in the case of ΔDHS that open, or are repressed by TCPOBOP, in the case of ΔDHS that close. Impact of Basal Liver Sex Differences on TCPOBOP Response We investigated whether the sex-dependent effects of TCPOBOP on chromatin accessibility (Figure 2B) and gene expression (Lodato et al., 2017) reflect basal sex differences in gene expression or chromatin accessibility (Sugathan and Waxman, 2013). First, we examined TADs whose genes show a sexually dimorphic response to TCPOBOP exposure, which we defined as two or more genes that respond to TCPOBOP in one sex versus no genes that respond in the other sex. We identified 22 TADs with a female-biased gene response and 60 TADs with a male-biased gene response. These 82 TADs include 178 TCPOBOP-responsive genes, of which 41 genes (23%) show sex differential expression in untreated mouse liver (Supplementary Table 6A). However, 362 TADs with two or more TCPOBOP-responsive genes that do not show a sex-biased gene response to TCPOBOP contain an even higher percentage (28%) of TCPOBOP-responsive genes with a basal sex bias in their expression (ie, 183 of 643 TCPOBOP-responsive genes [28%] in those 362 TADs) (Supplementary Table 6B). Further, TADs with sex-biased genes were not enriched in the set of TADs that showed a sex-biased TCPOBOP response (32 [39%] of 82 TADs) compared with TADs without a sex-biased response (134 [37%] of 362 TADs). For 20 of the above 41 basally sex-biased genes in TADs showing a sex-biased response to TCPOBOP, TCPOBOP reinforces the basal sex bias in expression, by inducing male-biased genes (n = 10) and repressing female-biased genes (n = 5) in male liver only; and by inducing female-biased genes (n = 4) and repressing male-biased genes (n = 1) in female liver only. (Supplementary Table 6A). In these cases, TCPOBOP induced expression only in the sex where the gene is already in an activated state, and it repressed expression in the sex where the gene is in a more repressed state. For the other 21 sex-biased genes, TCPOBOP countered the basal sex bias in expression, by inducing female-biased genes (n = 7) and repressing male-biased genes (n = 8) in male liver only; and by inducing male-biased genes (n = 3) and repressing female-biased genes (n = 3) in female liver only (Supplementary Table 6A). In these cases, TCPOBOP activates genes from a more repressed basal state, and it represses genes from a more active basal state. Finally, we examined the sets of ΔDHS that were only responsive to TCPOBOP in one sex, after 3 h and/or after 27 h exposure (Figure 2B). ΔDHS that were specifically responsive to TCPOBOP in male liver were significantly enriched for overlap with chromatin regions with a basal male bias in accessibility (Ling et al., 2010), when compared with ΔDHS without a sex bias in TCPOBOP response (enrichment score = 1.79, p = 1.03E-3, Fisher Exact test); however, ΔDHS that were specifically responsive to TCPOBOP in female liver did not show a corresponding enrichment for basally female-biased chromatin regions (p = .4). ΔDHS Proximal to TCPOBOP-Responsive HCC Genes We previously observed a striking male bias for TCPOBOP activation of genes associated with CAR-dependent pathways that promote HCC, specifically after 27 h TCPOBOP exposure (Lodato et al., 2017). Conceivably, this sexually dimorphic gene response profile may be driven by a correspondingly male-biased ΔDHS response. To test this hypothesis, we examined the ΔDHS that map to gene targets of a set of 10 established upstream regulators linked to CAR-induced HCC defined previously (Lodato et al., 2017). Whereas the gene targets of these 10 upstream regulators showed a significant male bias in their responsiveness to TCPOBOP after 27 h exposure (Lodato et al., 2017), there was no significant sex bias in the number of 27 h TCPOBOP-induced ΔDHS that map to these downstream gene targets (enrichment score = 1.02, p = .75; Figure 5A), even when we restricted the analysis to the 378 target genes of the 10 upstream regulators that are responsive to TCPOBOP (enrichment score = 1.07, p = .58; Figure 5B) or to the subset comprised of 153 target genes that are responsive to TCPOBOP in male liver only (enrichment score = 0.82, p = .29; Figure 5C). In other analyses, 27 h TCPOBOP-stimulated ΔDHS that opened in male but not female liver mapped to the set of 153 genes induced by 27 h TCPOBOP exposure in male liver only, at the same frequency that they mapped to a control set of 225 TCPOBOP-responsive genes not showing male-specific responses (Supplementary Table 3 and data not shown). Finally, there was no difference in the frequency with which male-biased TCPOBOP-induced DHS opening was associated with a basal sex bias in chromatin accessibility between the 153 male-biased HCC pathway gene targets and the 225 nonmale-biased gene targets (data not shown). Thus, the HCC-linked male-biased genic responses to TCPOBOP are not associated with a male bias in local chromatin accessibility or its responsiveness to TCPOBOP. Figure 5. View largeDownload slide ΔDHS mapping to gene targets of regulators of HCC. Shown is the number of ΔDHS that map to gene targets of 10 CAR-dependent upstream regulators of liver carcinogenesis described previously (Lodato, et al., 2017). Despite the strong male bias in the TCPOBOP responsiveness of the gene targets of these upstream regulators (Lodato, et al., 2017), there was no significant sex bias in the number of ΔDHS that mapped to any of the following three gene sets (see text): A, the set of all downstream target genes of these 10 regulators (n = 4336 genes); B, the set of all downstream targets that are TCPOBOP-responsive (n = 378 genes); C, the set of all downstream targets induced by 27 h TCPOBOP exposure in male liver but not in female liver (n = 153 genes) (Supplementary Table 3) (Lodato, et al., 2017). Figure 5. View largeDownload slide ΔDHS mapping to gene targets of regulators of HCC. Shown is the number of ΔDHS that map to gene targets of 10 CAR-dependent upstream regulators of liver carcinogenesis described previously (Lodato, et al., 2017). Despite the strong male bias in the TCPOBOP responsiveness of the gene targets of these upstream regulators (Lodato, et al., 2017), there was no significant sex bias in the number of ΔDHS that mapped to any of the following three gene sets (see text): A, the set of all downstream target genes of these 10 regulators (n = 4336 genes); B, the set of all downstream targets that are TCPOBOP-responsive (n = 378 genes); C, the set of all downstream targets induced by 27 h TCPOBOP exposure in male liver but not in female liver (n = 153 genes) (Supplementary Table 3) (Lodato, et al., 2017). DISCUSSION The major disruptive actions of environmental chemicals on gene transcription and the role of xenochemical receptors, including the nuclear receptor/transcription factor CAR, in these processes have long been recognized. However, underlying regulatory mechanisms are only partially understood, and have primarily been studied on a gene-by-gene basis, without considering the overall genomic organization of responding genes, and with little known about the changes in chromatin structure and accessibility that are presumed to occur based on studies of other nuclear receptor family members (Grontved et al., 2015; He et al., 2014; Stavreva et al., 2015). Here, we use the CAR-specific agonist ligand TCPOBOP to identify several thousand genomic regions where TCPOBOP, presumably acting via CAR activation, stimulates either an increase or a decrease in chromatin accessibility, and we analyze these datasets in the context of the TAD-based genomic organization of TCPOBOP-responsive protein coding and long noncoding (lncRNA) genes. TCPOBOP-Responsive Genes Cluster in TADs We found that a subset of TCPOBOP-responsive genes cluster in TADs, and that TCPOBOP-inducible genes and TCPOBOP-repressible genes are often found in separate sets of TADs. Thus, the genomic sequences and/or the chromatin state and epigenetic environment of individual TADs may render these TADs, and at least a subset of their constituent genes, susceptible to either activation or repression by TCPOBOP. TADs provide a structural framework for organizing megabase-scale segments of the genome into distinct three-dimensional compartments (Dixon et al., 2016) and thereby enable linearly distant chromosomal regions to interact within the large TAD-based DNA loops that segment each chromosome (Faure et al., 2012; Nora et al., 2017; Rao et al., 2014). TADs insulate regulatory elements from neighboring genes present in adjacent TADs, which constrains enhancer-promoter interactions (Figure 6) and increases the specificity of regulatory interactions (Oti et al., 2016; Vietri Rudan et al., 2015). TADs that contain the Cyp2b, Cyp2c, and Cyp3a gene families were particularly responsive to the stimulatory actions of TCPOBOP on chromatin opening and target gene induction, as exemplified by TAD3479, which contains the Cyp2c cluster with its 12 TCPOBOP-responsive genes and up to 38 ΔDHS that respond to a single condition of TCPOBOP exposure (Table 1). Clustering of Cyps into large TAD regions that can be rapidly activated following xenobiotic exposure may be advantageous from an evolutionary perspective, by allowing for a limited number of common regulatory elements to induce multiple genes within the gene superfamily, thereby increasing a broad range of xenobiotic metabolic activities following xenobiotic exposure. Figure 6. View largeDownload slide Impact of TAD segmentation of the genome on the selection of genes for CAR-induced transcriptional activation. Shown is a model with two adjacent TADs. TAD1 contains a cluster of 3 TCPOBOP/CAR-inducible genes, which may be activated by CAR to different extents, as shown. TAD2 contains two genes that are not subject to the stimulatory effects of the enhancer DHS in TAD1 when it is bound by a CAR-RXR heterodimer, due to the strong insulation imposed by the TAD’s looped DNA structure (black loop). This insulation is apparent, even when the gene promoters in TAD2 are closer, in linear DNA length, to the CAR-bound enhancer DHS than the CAR target genes in TAD1. A single enhancer DHS may activate multiple CAR-responsive promoters within a TAD, as shown, and individual promoters may be activated through the cooperative actions of multiple enhancer DHS (not illustrated). Further constraints on enhancer-promoter interactions may be imposed by intra-TAD (subTAD) looped domains (not shown). TADs are formed by DNA loop extrusion through the ring-shaped cohesin complex, which associates with the sequence-specific DNA-binding protein CTCF, two copies of which are bound at directionally oriented binding sites near the base of the loop, as shown. Mouse liver TADs have a median length of ∼400 kb but may vary widely in size, as illustrated by the two TADs in this model. CAR target genes include many lncRNAs (Lodato, et al., 2017), some of which may modulate transcription of other CAR targets, either in cis (red arrow), or in trans (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Figure 6. View largeDownload slide Impact of TAD segmentation of the genome on the selection of genes for CAR-induced transcriptional activation. Shown is a model with two adjacent TADs. TAD1 contains a cluster of 3 TCPOBOP/CAR-inducible genes, which may be activated by CAR to different extents, as shown. TAD2 contains two genes that are not subject to the stimulatory effects of the enhancer DHS in TAD1 when it is bound by a CAR-RXR heterodimer, due to the strong insulation imposed by the TAD’s looped DNA structure (black loop). This insulation is apparent, even when the gene promoters in TAD2 are closer, in linear DNA length, to the CAR-bound enhancer DHS than the CAR target genes in TAD1. A single enhancer DHS may activate multiple CAR-responsive promoters within a TAD, as shown, and individual promoters may be activated through the cooperative actions of multiple enhancer DHS (not illustrated). Further constraints on enhancer-promoter interactions may be imposed by intra-TAD (subTAD) looped domains (not shown). TADs are formed by DNA loop extrusion through the ring-shaped cohesin complex, which associates with the sequence-specific DNA-binding protein CTCF, two copies of which are bound at directionally oriented binding sites near the base of the loop, as shown. Mouse liver TADs have a median length of ∼400 kb but may vary widely in size, as illustrated by the two TADs in this model. CAR target genes include many lncRNAs (Lodato, et al., 2017), some of which may modulate transcription of other CAR targets, either in cis (red arrow), or in trans (The reader is referred to the web version of this article to clarify the references to color in this figure legend). Whereas Cyp2b10 and the nearby lnc_5998 were highly induced, and several ΔDHS within the same TAD (TAD1421) were activated (opened) by TCPOBOP exposure, two adjacent, closely related genes in the same TAD, Cyp2b9 and Cyp2b13, did not respond to TCPOBOP, even after a 27 h exposure (Lodato et al., 2017). Presumably, Cyp2b9 and Cyp2b13 are insulated from the DNA looping that is expected to bring the promoter of Cyp2b10, but not the promoters of the other, nearby Cyp2b genes, in contact with the ΔDHS/putative regulatory elements that contribute to its rapid and robust transcriptional activation, despite their being in the same TAD. Cyp2b9 and Cyp2b13 become TCPOBOP inducible after 4 days of exposure (Cui and Klaassen, 2016), suggesting a requirement for secondary factors and perhaps a need for more complex epigenetic reprogramming than for Cyp2b10. Such a requirement could be related to the epigenetic suppression of Cyp2b9 and Cyp2b13 (but not Cyp2b10) that occurs in male but not female mouse liver (Sugathan and Waxman, 2013). Other drug metabolizing enzyme gene families also showed selective patterns of induction. Thus, Gstm3 was strongly induced by 3 h TCPOBOP exposure in both male and female liver, whereas other Gstm genes in the same TAD (TAD694), notably Gstm1, Gstm2, and Gstm4, responded at 27 h. While other Gstm genes on the same TAD (Gstm6, Gstm7) were unresponsive. It is not known what factors determine the specificity of TCPOBOP for particular genes within a responsive TAD, nor is it clear what causes the delayed induction of a subset of genes within a highly active gene cluster. One factor may be three-dimensional proximity to CAR-bound ΔDHS/enhancer elements, whose accessibility to certain genes within a TAD may be constrained by the presence of intra-TAD (subTAD) looped domains (Wijchers et al., 2016). Another important factor may be the basal chromatin state of each gene and its regulatory elements (Sugathan and Waxman, 2013), which may contribute to the time differences in responsiveness, as suggested by other studies of time-dependent responses to hormonal stimuli in the mouse liver model (Lau-Corona et al., 2017). Finally, it should be noted that TAD boundaries are not necessarily fixed, and that genomic rearrangements that accompany carcinogenesis may alter TAD boundaries and play an important role in cancer progression (Taberlay et al., 2016; Valton and Dekker, 2016). Further work is required to ascertain whether such processes contribute to CAR-dependent liver carcinogenesis. ΔDHS as Positive Regulators of Gene Expression We used DNase-seq analysis to identify several thousand genomic regions (ΔDHS) where short-term exposure to TCPOBOP induces localized changes (increases or decreases) in mouse liver chromatin accessibility. Mapping these ΔDHS regions to the closest RefSeq coding or multi-exonic long noncoding gene within the same TAD revealed a strong enrichment of opening ΔDHS that map to genes induced by TCPOBOP, and of closing DHS that map to genes that are repressed (Table 3). Both of these response patterns are consistent with these ΔDHS playing a positive regulatory role. Some of the ΔDHS regions opened rapidly, ie, within 3 h of TCPOBOP exposure, but many others did not respond until 27 h, consistent with the large expansion of TCPOBOP-stimulated gene responses seen at 27 h (Lodato et al., 2017). Further, we observed a temporal relationship between TCPOBOP-induced DHS opening (or DHS closing) and TCPOBOP-induced gene responses, with DHS opening and DHS closing preceding gene induction and repression, respectively, for a subset of the 27 h TCPOBOP-responsive genes. Together, these findings support the model that these ΔDHS regions comprise promoters and enhancers that positively regulate gene expression, and that factors bound to these genomic regions, such as TCPOBOP-activated CAR, stimulate target gene transcription. Precisely how these chromatin regions open or close in response to TCPOBOP exposure is not known, but it likely involves factors such as the SWI/SNF chromatin remodeling complex (Tang et al., 2010). The rapid, 3 h TCPOBOP-induced chromatin opening seen at several hundred ΔDHS regions may be driven by direct CAR binding, as suggested by the ability of nuclear receptors such as GR and PPAR to bind directly to closed chromatin (Nagaich et al., 2004; Siersbaek et al., 2011; Voss et al., 2011). Supporting the proposal is the high specificity of TCPOBOP for CAR (Tzameli et al., 2000) and the presence of a well characterized CAR binding motif (direct repeat-4 [DR4] sequence) (Honkakoski and Negishi, 1997) centered within a cluster of six opening ΔDHS in TAD1421, which are distributed across a 10 kb region upstream of Cyp2b10 (Figure 3A). PXR, a nuclear receptor family member closely related to CAR, also binds DR4 motifs upstream of several drug metabolizing enzyme genes induced in common by CAR and PXR, such as Gstm3 (Cui et al., 2010), where we also found multiple TCPOBOP-induced ΔDHS (Figure 3B). Given the high specificity of TCPOBOP for CAR and the short time frame (within 3 h) for the early ΔDHS responses, these changes in chromatin accessibility are most likely a primary genomic response to CAR activation. Comparatively few chromatin closing events were seen at the 3 h exposure point, suggesting that CAR activation is primarily associated with chromatin opening. Changes in chromatin accessibility at several thousand other ΔDHS did not occur until the 27 h TCPOBOP time point (Figure 2A), and include more similar numbers of DHS opening and closing events (Figure 2C). The set of 27 h ΔDHS likely includes many secondary genomic responses, some of which could result from the epigenetic actions of one or more of the few hundred multi-exonic lncRNA genes that are rapidly induced by TCPOBOP in mouse liver (Lodato et al., 2017). One example is lnc_5998 (Figure 3A), whose transcription start site is located 5.2 kb upstream of Cyp2b10, and which together with Cyp2b10, constitute a divergently transcribed lncRNA-mRNA pair (Lepoivre et al., 2013). Finally, we identified many ΔDHS that mapped to TADs without any TCPOBOP-responsive genes. Some of these ΔDHS may regulate genes whose responsiveness to TCPOBOP does not become apparent until a later time point. Further studies, including identification of transcriptional changes that occur at a later time point, are needed to test this hypothesis. Sex-Biased Responses to TCPOBOP Sex differences in mouse liver gene expression are widespread (Waxman and Holloway, 2009) and are under the control of growth hormone and its sexually dimorphic pattern of secretion by the pituitary gland. Growth hormone, in turn, regulates liver chromatin states, including chromatin accessibility, which both show major sex differences in localized regions throughout the genome (Ling et al., 2010; Sugathan and Waxman, 2013). Accordingly, we investigated whether the sex differences in the impact of TCPOBOP-induced CAR activation on chromatin accessibility (Figure 2) and gene expression (Lodato et al., 2017) relate to basal sex differences in gene expression or chromatin accessibility (Sugathan and Waxman, 2013). We found that ΔDHS that were specifically responsive to TCPOBOP in male liver were significantly enriched for genomic regions with a basal male bias in chromatin accessibility. Further, we identified 82 TADs containing 41 basally sex-biased genes that responded to TCPOBOP in a sex-dependent manner. For 20 of these sex-biased genes, TCPOBOP reinforced basal sex differences, by inducing gene expression only in the sex where the gene is already in an activated state, and by repressing expression only in the sex where the gene is in a more repressed state. For the other 21 sex-biased genes, TCPOBOP countered the basal sex bias in expression, activating genes from a more repressed basal state, and repressing genes that are in a more active basal state. These findings suggest that basal chromatin state differences between the sexes can impact TCPOBOP responses. ΔDHS Do Not Predict Sex-Biased HCC Response We previously reported a strong male bias in the activation of CAR-dependent HCC pathways in mouse liver after 27 h of TCPOBOP exposure (Lodato et al., 2017). Here, we used DNase-seq to map ΔDHS, ie, putative DNA regulatory elements, that respond to TCPOBOP in mouse liver, to the downstream gene targets of 10 previously identified CAR-dependent HCC upstream regulators; these include a set of 153 downstream targets that respond to TCPOBOP in a male-specific manner (Lodato et al., 2017). Remarkably, there was no male bias in the number of TCPOBOP-responsive ΔDHS that map to the downstream gene targets. Further, the HCC-linked male-biased gene responses to TCPOBOP were not associated with a male bias in basal chromatin accessibility or in a sex bias of the responsiveness of those genomic regions to TCPOBOP-induced chromatin accessibility. Thus, male-biased regulation of these genes is not driven by a sex bias in the number of sites with changes in chromatin accessibility, their basal sex bias, or the sex bias of their responses to TCPOBOP exposure. These findings point to sex differences in other factors required for the male-biased transcription of these genes, for example, sex differences in the activation state of cyclin-D1, p53, p21, or one of the other seven CAR-dependent HCC upstream regulators. CONCLUSIONS We presented a genome-wide view of the dynamic changes in chromatin accessibility that occur in mouse liver following short exposures to the mouse CAR agonist ligand TCPOBOP, and we utilized mouse liver TAD region definitions to map changes in DHS to putative gene targets. Our findings reveal coordinated regulation of CAR-responsive gene families grouped by TAD and their associated, rapidly opening DHS, along with widespread sex differences in TCPOBOP-stimulated changes in chromatin accessibility. The global maps of dysregulated chromatin accessibility that we identified constitute a rich resource for further research on foreign chemical effects on the epigenome and its chromatin states. Future studies may examine whether mouse liver TADs enriched with CAR-responsive genes, including those associated with HCC-related genes, and their regulatory elements, are conserved in other species (Vietri Rudan et al., 2015), including humans, where CAR activation has not been conclusively linked to increased incidence of liver tumors (Dong et al., 2015; Elcombe et al., 2014). SUPPLEMENTARY DATA Supplementary data are available at Toxicological Sciences online. FUNDING Supported in part by NIH grant ES024421 (to D.J.W.). Disclosure: The authors have nothing to disclose. REFERENCES Baldwin W. S. , Roling J. A. ( 2009 ). A concentration addition model for the activation of the constitutive androstane receptor by xenobiotic mixtures . Toxicol. Sci. 107 , 93 – 105 . 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Toxicological SciencesOxford University Press

Published: Apr 2, 2018

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