T Cell Responses + CD8 Developmentally Induced Aberrant

Linking the Aryl Hydrocarbon Receptor with Altered DNA Methylation Patterns and Developmentally Induced Aberrant Antiviral CD8 + T Cell Responses This information is current as of September 28, 2021. Bethany Winans, Anusha Nagari, Minho Chae, Christina M. Post, Chia-I Ko, Alvaro Puga, W. Lee Kraus and B. Paige Lawrence J Immunol published online 25 March 2015 http://www.jimmunol.org/content/early/2015/03/25/jimmun Downloaded from ol.1402044

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The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2015 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published March 25, 2015, doi:10.4049/jimmunol.1402044 The Journal of Immunology

Linking the Aryl Hydrocarbon Receptor with Altered DNA Methylation Patterns and Developmentally Induced Aberrant Antiviral CD8+ T Cell Responses

Bethany Winans,* Anusha Nagari,† Minho Chae,† Christina M. Post,* Chia-I Ko,‡ Alvaro Puga,‡ W. Lee Kraus,† and B. Paige Lawrence*

Successfully ﬁghting infection requires a properly tuned immune system. Recent epidemiological studies link exposure to pollutants that bind the aryl hydrocarbon receptor (AHR) during development with poorer immune responses later in life. Yet, how developmental triggering of AHR durably alters immune cell function remains unknown. Using a mouse model, we show that developmental activation of AHR leads to long-lasting reduction in the response of CD8+ T cells during inﬂuenza virus infection, cells

critical for resolving primary infection. Combining genome-wide approaches, we demonstrate that developmental activation alters Downloaded from DNA methylation and gene expression patterns in isolated CD8+ T cells prior to and during infection. Altered transcriptional proﬁles in CD8+ T cells from developmentally exposed mice reﬂect changes in pathways involved in proliferation and immuno- regulation, with an overall pattern that bears hallmarks of T cell exhaustion. Developmental exposure also changed DNA methylation across the genome, but differences were most pronounced following infection, where we observed inverse correlation between promoter methylation and gene expression. This points to altered regulation of DNA methylation as one mechanism by

which AHR causes durable changes in T cell function. Discovering that distinct gene sets and pathways were differentially http://www.jimmunol.org/ changed in developmentally exposed mice prior to and after infection further reveals that the process of CD8+ T cell activation is rendered fundamentally different by early life AHR signaling. These ﬁndings reveal a novel role for AHR in the developing immune system: regulating DNA methylation and gene expression as T cells respond to infection later in life. The Journal of Immunology, 2015, 194: 000–000.

properly functioning immune system underlies multiple vulnerable to disease. Many factors likely contribute to altered aspects of human health and well-being, including elim- immune function. Several epidemiological studies reveal striking ination of pathogens without excessive damage to healthy correlations between developmental exposures to anthropogenic A by guest on September 28, 2021 tissues. Impaired immune responses leave individuals and populations chemicals and increasing incidence or severity of infections and poorer responses to routine immunizations (1–6). Although rela- *Department of Environmental Medicine and Environmental Health Science Center, tively few studies have examined this, they create a compelling University of Rochester School of Medicine and Dentistry, Rochester, NY 14642; case that developmental exposure to pollutants fundamentally †Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences and Division of Basic Reproductive Biology Re- alters the responsive capacity of the immune system, leading to search, Department of Obstetrics and Gynecology, University of Texas Southwestern long-lasting impairments that contribute to the burden of infec- ‡ Medical Center, Dallas, TX 75390; and Department of Environmental Health and tious disease. Maternal and early life exposures have enduring Center for Environmental Genetics, University of Cincinnati College of Medicine, Cincinnati, OH 45267 adverse effects on other systems, including nervous, cardiovas- Received for publication August 15, 2014. Accepted for publication February 24, cular, endocrine, and reproductive, as well as cancer rates in 2015. offspring (7). Thus, it is not surprising that mounting evidence This work was supported by National Institutes of Health Grants R01-ES017250, suggests developmental exposures also affect immune function; R01-ES023260, R01-HL097141, T32-ES07026, and P30-ES01247. W.L.K. was supported by National Institutes of Health Grant R01-DK069710. C.-I.K. and A.P. were however, the factors that influence it are poorly understood. supported by National Institutes of Health Grants R01-ES006273 and P30-ES06096. One possible factor that links signals from the early life envi- The sequences presented in this article have been submitted to the Gene Expression ronment to the function of the immune system later in life is the Omnibus under accession number GSE60115. aryl hydrocarbon receptor (AHR). AHR is a ligand-activated Address correspondence and reprint requests to Dr. B. Paige Lawrence, Department transcription factor that modulates function of the fully mature of Environmental Medicine, Box 850, University of Rochester School of Medicine and Dentistry, 601 Elmwood Avenue, Rochester, NY 14642. E-mail address: (adult) immune system (8). AHR ligands include numerous ubiq- [email protected] uitous pollutants such as dioxins, polychlorinated biphenyls, and The online version of this article contains supplemental material. polycyclic aromatic hydrocarbons, as well as some naturally de- Abbreviations used in this article: AHR, aryl hydrocarbon receptor; AHRE, AHR rived chemicals, such as tryptophan metabolites (9). Several studies response element; ChIP, chromatin immunoprecipitation; DC, dendritic cell; DEG, indicate that early life exposure to commonly found AHR-binding differentially expressed gene; DMR, differentially methylated region; DNMT, DNA methyltransferase; FDR, false discovery rate; GD, gestation day; IAV, influenza A pollutants alters immune function later in life (10). Recent studies virus; IPA, Ingenuity Pathway Analysis; MeDIP-seq, methylated DNA immunopre- using low, environmentally relevant maternal doses of AHR ligands cipitation high-throughput sequencing; NP, nucleoprotein; PA, acid polymerase; demonstrated that persistent changes in host responses to influenza PND, postnatal day; qPCR, quantitative real-time PCR; RNA-seq, RNA high- throughput sequencing; RPM, reads per million; RT-qPCR, reverse transcription A virus (IAV) are observed in offspring, yet there are no differences quantitative PCR; TCDD, 2,3,7,8-tetrachlorodibenzo-p-dioxin; TSS, transcription in immune organ cellularity in naive offspring (11, 12). These start site; Veh, vehicle control. changes in immune function occur long after the window of de- Copyright Ó 2015 by The American Association of Immunologists, Inc. 0022-1767/15/$25.00 velopmental exposure (12, 13). Bone marrow cell transplantation

www.jimmunol.org/cgi/doi/10.4049/jimmunol.1402044 2 EARLY LIFE AHR ACTIVATION REPROGRAMS ANTIVIRAL IMMUNITY further reveals that these diminished adaptive immune responses dams were given either TCDD (1 mg/kg body weight) or peanut oil vehicle are intrinsic to hematopoietic cells (12). Yet, how triggering of (Veh) by gavage on GD0, GD7, and GD14 and on postnatal day 2 (PND2). AHR during development changes the function of the adult im- This dose of TCDD is not overtly toxic to the dam or the pups, and it does not lead to changes in the cellularity of the bone marrow, thymus, spleen, mune system remains undefined. Studies of developmental expo- or lymph nodes (11). Intranasal infection of adult offspring with IAV strain sures in other organ systems suggest that alterations in epigenetic HKx31 (H3N2) was performed as previously described (12). All proce- mechanisms may underlie persistent functional deregulation dures involving laboratory animals and infectious agents were reviewed (14–17). and approved by the University of Rochester Institutional Animal Care and DNA methylation is one type of epigenetic regulation that Use Committee and Institutional Biosafety Committee. The University has accreditation through the Association for Assessment and Accreditation of influences gene expression and cellular function, is sensitive to Laboratory Animal Care. All guidelines from the U.S. Public Health environmental cues, and influences the normal development of the Service Policy on Humane Care and Use of Laboratory Animals were immune system (18, 19). Whether activation of AHR via devel- followed in handling of vertebrate animals. opmental exposure to exogenous ligands alters DNA methylation Isolation of immune cells and flow cytometry in immune cells is unknown. Developmental exposure to the prototype AHR ligand 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) Peripheral lymph nodes (inguinal, axillary, brachial, cervical, mediastinal, and sacral), bone marrow, thymus, spleens, and liver were isolated from alters DNA methylation patterns in testes, mammary tissue, naive offspring either at PND7 or at maturity. Mediastinal lymph nodes were muscle, and liver, and elevates DNA methyltransfersase (DNMT) collected from mature offspring 9 d after IAV infection. Tissues were activity in preimplantation embryos (20–23), suggesting plausi- processed as previously described (11). Where indicated, total CD8+ T cells bility. Also, several studies demonstrate that developmental ex- or naive CD8+ T cells were enriched using MagCellect kits (R&D Sys- posure to other agents, such as heavy metals, maternal smoking, tems, Minneapolis, MN). For flow cytometry, cells were incubated with Downloaded from anti-mouse CD16/32 prior to incubation with the following fluorochrome- and air pollutants, modulates DNA methylation in cord blood conjugated Abs (BD Biosciences, San Jose, CA or eBioscience, San leukocytes (24–31). However, efforts to correlate changes in DNA Diego, CA): CD8a (53-6.7), CD44 (IM7), and CD62L (MEL-14). MHC methylation and gene expression profiles in mixed populations of class I tetramers corresponding to two immunodominant IAVepitopes (Db/ b blood cells with complex disease outcomes is confounded by the nucleoprotein [NP]366–374 and D /acid polymerase [PA]224–233) were used + distinct DNA methylation pattern of each type of immune cell to identify virus-specific CD8 T cells (12). For the identification of virus- specific CD8+ T cells in naive mice, CD3+ T cells were enriched from (32). Nevertheless, these prior studies collectively imply a con- peripheral lymph nodes, and the frequency of NP+ and PA+ CD44loCD8+ http://www.jimmunol.org/ nection between early life exposure to environmental agents and T cells was determined by flow cytometry. LSR II cytometers (BD Bio- altered DNA methylation in mixed leukocyte populations; how- sciences) were used for data acquisition ($500,000 events were collected ever, alterations in specific types of immune cells remain to be for cells from naive animals, and 300,000–500,000 events were collected determined. Thus, triggering AHR during development could alter for analyses of cells from infected mice), and data analysis was performed using FlowJo software (Tree Star, Ashland, OR). Given that the dam, DNA methylation patterns in cells of the immune system, con- rather than the offspring, is directly exposed, the dam is defined as the tributing to changes in gene expression patterns and cellular func- statistical unit for all experiments, and each offspring was from a dif- tion later in life. ferent treated dam. Data were analyzed using JMP software (SAS In- To address this issue, we selected CD8+ T cells because they are stitute, Cary, NC). Differences between mean values from each exposure the principal means for successful host resistance in a primary IAV group were considered significant when p # 0.05, as determined using by guest on September 28, 2021 aStudentt test. infection, and because their response to infection is profoundly and persistently changed by maternal exposure to the AHR agonist RNA and DNA isolation, immunoprecipitation, and TCDD (12, 33). Although its role is not fully understood, alter- high-throughput sequencing + ations in global DNA methylation patterns occur as naive CD8 RNA was isolated using the RNeasy Mini kit (Qiagen, Valencia, CA). RNA T cells differentiate and acquire effector function in response to quality was verified on the 2100 Bioanalyzer (Agilent Technologies, Santa infection, and we hypothesize that developmental activation of Clara, CA). TruSeq RNA sample preparation kit V2 (Illumina, San Diego, AHR alters this process (34). We first investigated whether the CA) was used per the manufacturer’s protocols. Methylated DNA immu- + noprecipitation high-throughput sequencing (MeDIP-seq) was performed altered CD8 T cell response to IAV is a result of developmental as previously published (36). Briefly, DNA was extracted from enriched exposure diminishing the number of naive, virus-specific T cells, CD8+ T cells ($90% purity) using the DNeasy blood and tissue kit and whether it requires AHR in the offspring. We then used un- (Qiagen), digested with MseI, and further isolated with the QIAquick biased, genome-wide approaches to investigate whether devel- PCR purification kit (Qiagen). Methyl sequencing library construction was opmental AHR activation alters DNA methylation and gene performed with a NEXTflex methyl sequencing kit (Bioo Scientific, + Austin, TX) per the manufacturer’s recommendations. Briefly, 1200 ng expression profiles of purified CD8 T cells prior to and during genomic DNA was sheared to an average size of 200–400 bp with the infection, and then assessed correlations between differentially Covaris S2 (Covaris, Woburn, MA). Sheared DNA sizing was confirmed methylated regions (DMRs) and differentially expressed genes with a Bioanlayzer 2100 (Agilent Technologies) and subsequent end re- (DEGs). Our findings reveal new pathways through which envi- pair, adenylation, and adaptor ligation were performed. DNA was heated to ronmentally derived AHR ligands influence the function of the 95˚C and incubated with anti–5-methylcytosine Ab (Epigentek, Farm- ingdale, NY). Methylated DNA was immunoprecipitated with Dynabeads immune system. (Life Technologies, Grand Island, NY) and released from the beads using proteinase K digestion. DNA was purified using the MinElute PCR puri- Materials and Methods fication kit (Qiagen), followed by library PCR amplification and gel size Developmental exposure and infection selection. For both RNA high-throughput sequencing (RNA-seq) and MeDIP-seq, single-end sequencing was performed using the Illumina Nulliparous C57BL/6 (National Cancer Institute, Frederick, MD) and GAIIx genome sequencer with an average of 20 million 72 bp reads per B6.Ahrtm1Bra+/2 (AHR+/2) females were paired with C57BL/6 or AHR+/2 sample. All sequence data have been submitted to the Gene Expression males, respectively. Pregnancy was determined by the presence of a vagi- Omnibus (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60115) un- nal plug (day 0 of gestation, GD0), and pregnant mice were individually der accession number GSE60115. Chromatin immunoprecipitation (ChIP) was housed for the remainder of the study. Offspring were weaned at 21 d of performed as previously published (37). Cells were harvested, cross-linked age. Offspring of AHR+/2 breeders were genotyped as previously de- and lysed, and chromatin was sheared by sonication with a Bioruptor scribed (35). All mice were housed in a pathogen-free facility in micro- (Diagenode, Denville, NJ). Diluted chromatin was combined with 3 mg isolator cages, and food and water were provided ad libitum. TCDD pertinent Ab for each ChIP assay and specific immune complexes were ($99% pure; Cambridge Isotope Laboratories, Woburn, MA) was pre- recovered by precipitation with 50:50 protein A/G agarose. After washes, pared and mice were dosed as previously described (12). Briefly, pregnant chromatin complexes were released with NaHCO3-SDS by vigorous The Journal of Immunology 3

shaking. Cross-links were reversed in the presence of RNAse A at 65˚C. ChIP-enriched DNA was purified and quantified using PicoGreen dsDNA dye (Invitrogen). DNA enrichment is represented as the percentage of total input after subtracting the values of the relevant control Abs. For some experiments, reverse transcription quantitative PCR (RT-qPCR) and quantitative real-time PCR (qPCR) was performed as previously described (38), and primers for Dnmt1, Dnmt3a, Dnmt3b, and L13 were used (39, 40). For other experiments, gene expression on PND7 was examined. RNA was extracted from liver, reverse transcription was performed, and Cyp1a1 was measured by qPCR, with L13 used as a control (41). Data were analyzed using the DDCt method (42). MeDIP-seq and RNA-seq analysis MeDIP-seq reads were aligned to mouse reference genome (mm9) using Bowtie (version 0.12.7 parameter set -n 2 -k 1 -m 1) allowing up to two nucleotide mismatches to the reference genome and considering only uniquely mappable reads for downstream analyses (43). MeDIP-seq data were analyzed with MEDIPS package in R (44). For each sample, the aligned reads were extended in the sequencing direction to a length of 400 nucleotides. The short read coverage of the extended reads was calculated at genome-wide 50-bp bins. MeDIP-seq reads were counted in the gene bodies of RefSeq genes and differential methylation in gene bodies was assessed with edgeR package in R (45). To identify the DMRs throughout Downloaded from the genome we used various functions of MEDIPS package in R. Mean reads per million (RPM) values were calculated for genome-wide 500-bp nonoverlapping windows using MEDIPS.methylProfiling function. For any given 500-bp nonoverlapping window, mean RPM were calculated with statistically significant DMRs having a p value of ,0.001 and a ratio of ,0.5 (hypomethylated) or .2 (hypermethylated) using MEDIPS.select-

Significants function of the MEDIPS package. Continuous adjacent sig- http://www.jimmunol.org/ nificant 500-bp DMRs were merged, indicating an extended DMR. The DMRs identified for each comparison were annotated using CEAS. A Wilcoxon test was used to determine whether the differences between groups were statistically significant. For visualizing the methylation levels in the promoter (2 kb upstream to transcription start site [TSS]), gene body (TSS to transcription end site), and downstream (2 kb downstream to transcription end site) we used metagene representation. Each region was divided into 20 equal nonoverlapping windows and all genes were normalized for length and sequencing depth, and average methylation was plotted as a metagene. To visualize the coverage density of MeDIP-seq reads, we calculated coverage density across the chromosomes using by guest on September 28, 2021 Rsamtools library, density function in R, and custom-written scripts (46). A two-sample Kolmogorov–Smirnov test was used to determine whether the differences between groups were statistically significant. RNA-seq analysis was performed using Tuxedo programs with default parameters (47). Reads were aligned to the mouse reference genome (NCBI37, mm9) using TopHat (v1.4.1), then assembled into transcripts FIGURE 1. Developmental exposure impairs the CTL response to IAV using Cufflinks (v.1.3.0). Differential analysis was performed using Cuff- + without altering frequency of naive CD8 T cells. (A) Key changes ac- diff (v.1.3.0). Data were analyzed through the use of Ingenuity Pathway companying CD8+ T cells postinfection. (B–D) Data in the left column are Analysis (IPA; Ingenuity Systems, http://www.ingenuity.com). DEGs be- from naive offspring. Peripheral lymph nodes were harvested from unin- tween Veh and TCDD (p # 0.05) were used. The p values of canonical fected adult mice developmentally exposed to Veh or TCDD. Isolated cells pathways were corrected with the Benjamini–Hochberg method for mul- , were stained with MHC class I–restricted tetramers and Abs, as described tiple testing, with a false discovery rate (FDR) of 5%. in Materials and Methods. Doublet discrimination, exclusion of dead cells, Correlations between MeDIP-seq and RNA-seq data were calculated using a Spearman rank correlation coefficient. Promoter regions (2 kb and gating on CD3+ cells were performed, and then CD8+CD44lo T cells, b + + b + + upstream, 500 bp downstream of the TSS) of DEGs with overlapping D /NP366–374 CD8 T cells, and D /PA224–233 CD8 T cells were defined DMRs (hyper- or hypomethylated) were binned into hypomethylated and/or B based on fluorescence minus one controls. ( ) The average number of naive hypermethylated promoters. Isolated RNA and MeDIP-ed DNA samples lo + (CD44 ) CD8 T cells in naive developmentally exposed mice is shown. from purified CD8+ T cells were used for gene-specific qPCR. RNA was b + b + (C) Representative dot plots depict D /NP366–374 and D /PA224–233 amplified with a WT-Ovation PicoSL kit (Nugen, San Carlos, CA), con- CD8+ T cells in lymph nodes from each group; the number on the plots is verted to cDNA, and RT-qPCR was performed using PrimeTime primers b the percentage in the gated region. (D) The average number of D /NP366–374 (Integrated DNA Technologies, Coralville, IA). L13 was used as a house- b + keeping gene, and analysis was performed by the DDCt method (42). and D /PA224–233 specific CD8 T cells per lymph node is shown. (E–H) Data from infected offspring are presented in the right column. (E and F) Immunoprecipitated DNA was prepared as above, followed by genome- wide amplification using a GenomePlex whole-genome amplification kit Developmentally exposed wild-type (Ahr+/+) mice were infected with IAV (Sigma-Aldrich, St. Louis, MO). qPCR on immunoprecipitated DNA was at maturity, and 9 d later the number of CTL effectors (CD44hiCD62Llo + + performed using EpiTect ChIP qPCR primers (Qiagen). Primer location CD8 T cells) and virus NP-specific and PA-specific CD8 T cells in the was chosen based on the location of the nearest DMR upstream of the TSS. mediastinal lymph nodes were determined by flow cytometry. (G and H) Input values were used for normalization using the DDCt method. Developmentally exposed Ahr2/2 (knockout [KO]) mice were infected with IAV at maturity, and 9 d later the number of CTL effectors and Db/ + b + + NP366–374 and D /PA224–233 CD8 T cells in the mediastinal lymph nodes were determined. Data are shown as means 6 SEM and depict group) was performed once; data from infected mice (five to six same sex findings from female offspring. Separate assessments using offspring of offspring from separate dams) are from one experiment that is represen- both sexes yielded similar results (data not shown). Evaluation of naive tative of at least two independent experiments. *p # 0.05 using a Student mice (eight to nine sex-matched offspring from separate dams for each t test. 4 EARLY LIFE AHR ACTIVATION REPROGRAMS ANTIVIRAL IMMUNITY

Results (Fig. 1G, 1H). Thus, based on assessment of known immunodo- Developmental exposure persistently changes CD8+ T cell minant viral epitopes, developmental AHR activation did not responses to infection discernibly change the overall number of CD8+ T cells in naive animals; however, it altered their responsive capacity to infection. During viral infection, naive CD8+ T cells with TCRs specific for Furthermore, this durable effect requires functional AHR protein IAV proliferate and differentiate, forming armed effector CTLs in the developing offspring, demonstrating that differences in the (Fig. 1A). Prior to infection, adult offspring of Veh- and TCDD- reaction of these cells to infection are driven by early life sig- treated dams had a similar number of naive (CD44lo) CD8+ T cells naling through AHR. (Fig. 1B). MHC class I–restricted tetramers were used to identify and enumerate CD8+ T cells with TCR specific for two immu- Developmental activation of AHR alters global DNA + nodominant peptide epitopes from IAV: NP366–372 and PA224–233. methylation profiles in CD8 T cells We did not observe differences in the percentage or number of We next determined whether developmental exposure alters global + virus-specific CD8 T cells in uninfected developmentally ex- DNA methylation profiles in CD8+ T cells isolated from the off- posed adult offspring, compared with offspring of control dams spring, and how these profiles change following infection. We (Fig. 1C, 1D). This observation is consistent with prior reports that hypothesized that altered DNA methylation due to early life AHR maternal exposure to this amount of TCDD did not alter thymic activation contributes to the poorer ability of naive CD8+ T cells to cellularity or the total number of T cells in lymphoid organs (11). become activated. To test this idea fully, it is critical to determine However, following IAV infection there was a significantly the profile of DNA methylation from the entire pool of CD8+ + blunted CD8 T cell response in offspring of TCDD-treated dams, T cells from developmentally exposed mice, rather than investi- Downloaded from with 3-fold fewer effector CTLs and 50% fewer NP-specific and gate changes in DNA methylation patterns only in cells that + PA-specific CD8 T cells in the developmentally exposed group were already activated. DNA was isolated from CD8+ T cells 2 (Fig. 1E, 1F). By dosing pregnant Ahr+/ dams and monitoring purified from naive and infected adult offspring of Veh- and 2 2 immune responses in Ahr+/+ (wild-type) and Ahr / (knockout) TCDD-treated dams. We used methylated DNA immunoprecipi- offspring, we found that the presence of the AHR in the fetus/ tation followed by next generation DNA sequencing (MeDIP-seq) + offspring is required for maternal exposure to perturb CD8 to enrich for and compare methylated DNA (Fig. 2A). MeDIP-seq http://www.jimmunol.org/ T cells later in life. Only infected Ahr+/+ offspring showed reduced generated 8–11 million reads per sample, with 70–82% alignment, CD8+ T cell responses to IAV, whereas Ahr2/2 littermates did not high correlation between independent replicates (R . 0.996,

FIGURE 2. DNA methylation is altered in CD8+

T cells following developmental AHR activation. by guest on September 28, 2021 (A) At maturity CD8+ T cells were isolated from naive or IAV-infected mice that were developmentally exposed to Veh or TCDD. To provide sufficient material, CD8+ T cells from up to 15 female littermates, derived from 2 to 3 dams, were pooled to create each sample. MeDIP-seq was performed. (B and C) Box plots of (B) genome- wide and (C) representative chromosome-specific DNA methylation (chromosomes 5 and 17) for Veh naive, TCDD naive, Veh infected, and TCDD infected are shown. The y-axis shows RPM. (D) Coverage plots of selected chromosomes are shown. (E) Metagene analysis of upstream (2 kb upstream to TSS), gene body (TSS to transcription end site), and downstream (transcription end site to 2 kb downstream) regions, in which all genes were normalized for length and the average methylation is shown. (F and G) The genome was scanned with a 500-bp window, and DMRs were identified. Hypomethylated and hypermethylated DMRs lo- cated in various genomic features for the comparisons (F) Veh naive versus TCDD naive groups and (G) Veh infected versus TCDD infected groups are shown. *p # 0.00001 between treatment groups of similar infection status using the Wilcoxon rank sum test. TI, developmentally exposed to TCDD and infected; TN, developmentally exposed to TCDD and naive; VI, developmentally exposed to Veh and infected; VN, developmentally exposed to Veh and naive. The Journal of Immunology 5 p value , 0.0001), and sufficient saturation (.0.98) and coverage body, and downstream regions for each gene were normalized and (Supplemental Fig. 1). parsed into windows revealed that, compared with the other three To identify DMRs, we compared genome-wide DNA methyl- groups, CD8+ T cells from TCDD infected offspring again stood ation in CD8+ T cells from each treatment group. The global out as distinct, with decreased methylation upstream and down- distribution of DNA methylation was surprisingly similar between stream of genes (Fig. 2E). Further refinement, in which the ge- CD8+ lymphocytes from uninfected offspring of Veh and TCDD nome was scanned using 500-bp windows revealed that in CD8+ treated dams (Veh naive versus TCDD naive group, Fig. 2B). lymphocytes from developmentally exposed mice, DMRs oc- However, relative to IAV-infected offspring of control-treated curred across all genomic features, with many found in promoter dams, genome-wide DNA methylation was distinctly different in regions, as well as noncoding (intergenic) regions and gene bodies CD8+ T cells from infected offspring of TCDD-treated dams (introns and coding exons, Fig. 2F, 2G). Whereas developmentally (Fig. 2B, comparing TCDD infected versus Veh infected groups), exposed naive mice had very similar genome- and chromosome- with overall skewing toward more hypomethylated DNA. Anal- wide DNA methylation profiles, this analysis revealed that many ysis of DNA methylation at individual chromosomes revealed a DMRs were present between Veh naive and TCDD naive groups, similar overall pattern, where TCDD infected offspring showed the consisting of hypermethylated and hypomethylated regions (Fig. 2F). most pronounced difference, with a general shift toward hypo- Infected mice also revealed significant differences based on devel- methylation in CD8+ lymphocytes in this group compared with all opmental exposure, as developmental activation of AHR led to many other groups (representative chromosomes 5 and 17 in Fig. 2C; DMRs in all genomic areas. Although these DMRs represented both box plots for all chromosomes in Supplemental Fig. 2). However, hyper- and hypomethylated regions, there were more hypomethy- analysis of CpG methylation along each chromosome revealed lated DMRs in promoter regions, coding exons, introns, and down- Downloaded from a more intricate pattern of altered methylation. Although the stream and distal intergenic regions of CD8+ lymphocytes from the overall level of DNA methylation in CD8+ T cells from TCDD TCDD infected group, consistent with the genome-wide shift to- infected offspring was generally skewed toward hypomethylation, ward hypomethylation (Fig. 2G). Thus, developmental exposure to both hyper- and hypomethylated regions were observed along an exogenous AHR ligand caused some modest changes in DNA many chromosomes (Fig. 2D, Supplemental Fig. 3). Thus, de- methylation patterns in naive CD8+ T cells. Yet, when these cells

velopmental AHR activation followed by infection altered the responded to viral infection, substantive changes in DNA methyl- http://www.jimmunol.org/ DNA methylation landscape in CD8+ T cells. These changes ation were revealed, with a shift predominantly but not exclusively covered large areas of chromosomes, were distributed across the toward hypomethylation. whole genome, and resulted in a general shift toward hypomethylation. Gene expression proﬁles are altered by developmental Although not fully understood, DNA methylation plays broad activation of AHR yet context-speciﬁc roles in cellular function, which include To examine whether developmental exposure also affects gene maintenance of genome stability and regulation of gene expression. expression in CD8+ T cells, RNA-seq was performed on the same In addition to methylation at gene promoters, gene body and sample set created for MeDIP-seq (Fig. 2A). RNA-seq generated intergenic methylation may also play important regulatory roles 15–20 million total reads per sample, with 87–89% of the reads by guest on September 28, 2021 (18). Metagene analyses, in which the length of upstream, gene aligning to the genome (Supplemental Fig. 1A). Consistent with

FIGURE 3. Many genes are differentially expressed following developmental signaling of AHR. Gene expression was measured in CD8+ T cells by RNA-seq from the four groups depicted in Fig. 2A. (A) The number of DEGs is shown for each comparison, at FDR , 5%. (B)Forthe Veh naive versus TCDD naive and Veh infected versus TCDD infected comparisons, the log2 (fold change) is plotted for each DEG. (C) For these same comparisons, IPA analysis was performed. Only pathways significantly enriched (Benjamini– Hochberg method for multiple testing, FDR , 5%) and relevant for the CD8+ T cell response to infection are shown. The x-axis indicates the ratio of DEGs to all genes in the IPA gene set. (D) Fold change values for selected genes involved in the immune response to IAV are listed. Values in bold font are statistically significant (FDR , 5%). Full list of DEGs is presented in Supplemental Table I. 6 EARLY LIFE AHR ACTIVATION REPROGRAMS ANTIVIRAL IMMUNITY the relatively quiescent state of naive CD8+ T cells compared with exposure window, but the upregulation of these genes was not CTLs (48), IAV infection led to a marked upregulation of genes, sustained in CD8+ T cells in developmentally exposed mice. This regardless of maternal exposure (Fig. 3A). Comparing CD8+ indicates that the DEGs are likely not AHR target genes them- T cells from Veh naive to TCDD naive groups, there were 69 selves, but rather reflect altered transcriptional regulation caused DEGs (Fig. 3A, 3B, Supplemental Table I). Thirty-three genes had by early life AHR activation. increased expression, whereas 36 had decreased expression. In To identify pathways represented by these DEGs, IPA was contrast to uninfected mice, after infection, 428 DEGs were performed comparing Veh naive to TCDD naive groups and Veh identified between CD8+ T cells from TCDD infected compared infected to TCDD infected groups. Of the few genes altered in the with Veh infected offspring, with almost all (402 genes) exhibiting Veh naive/TCDD naive comparison, most were enriched in TNFR increased expression in adult offspring of TCDD-treated dams or other signaling pathways. Similar to DMRs, changes in gene (Fig. 3A, 3B, Supplemental Table I). Given that AHR is a tran- expression in CD8+ lymphocytes from adult animals that were scription factor, increased transcription in CD8+ T cells, and ul- developmentally exposed became considerably more evident after timately impaired function, could reflect persistent upregulation of infection. The major pathways enriched in CD8+ T cells from defined AHR target genes. However, interrogation of the RNA-seq TCDD infected versus Veh infected groups included cell cycle dataset does not support this idea. Validated AHR target genes regulation and DNA damage (Fig. 3C, 3D). Genes and pathways were not significantly differentially expressed in adult offspring of involved in immune responses to IAV were also differentially TCDD-treated dams, compared with adult offspring of control expressed (Fig. 3D). Deregulation of these pathways corresponds dams (Fig. 4A). That is, statistically significantly enhanced ex- with altered CD8+ T cell clonal expansion and differentiation pression of AHR target genes is observed in developmentally observed in infected developmentally exposed mice. Another key Downloaded from exposed mice neither prior to nor following infection. In contrast, finding is that pathways involved in epigenetic regulation and developmental AHR activation caused transient and significant DNA methylation were not altered in offspring of TCDD-treated increases in AHR target genes in neonates. For example, enhanced dams (regardless of infection). Although Wu et al. (20) reported expression of Cyp1a1 was observed in neonatal mice (i.e., shortly increased DNMT activity in mouse embryos treated directly ex after maternal exposure to TCDD). Specifically, Cyp1a1 expres- vivo with TCDD, we observed no differences in the relative level + sion levels were 2292-fold higher in the TCDD naive group of expression of Dnmt1, Dnmt3a,orDnmt3b in purified CD8 http://www.jimmunol.org/ compared with the Veh naive group at PND7 (Fig. 4B). Thus, T cells from developmentally exposed mice (Fig. 5A). To further AHR activation induced expression of target genes during the explore the idea that AHR may play a role in the regulation of DNMTs, we identified putative binding sites for AHR (AHR response elements [AHREs]) in the upstream regulatory regions and gene bodies of all three Dnmt genes (Fig. 5B). Using ChIP, we next investigated whether maternal exposure leads to binding of AHR to these putative AHREs. We were unable to detect alterations in binding of AHR to these genes in bone marrow cells, thymocytes, or CD8+ T cells from developmentally exposed mice by guest on September 28, 2021 (Fig. 5C–E). Thus, whereas developmental exposure altered DNA methylation across the genome and influenced expression of many other genes, we found no evidence that this was achieved through AHR persistently or directly altering Dnmt gene expression. Correlations between DMRs and gene expression were observed following infection DNA methylation influences transcriptional regulation in a context-specific manner, and recent work indicates a role of DNA methylation in gene bodies as well as promoters (18). To directly examine correlations between DNA methylation and gene expression in these genomic locations, we integrated the MeDIP- seq and RNA-seq datasets. Consistent with other observations reported in the present study, differences in gene body methylation were more pronounced in CD8+ T cells from infected offspring. When comparing genes with differential gene body methylation in Veh infected and TCDD infected groups, we observed 1213 hypomethylated and 479 hypermethylated genes, with many involved in immune regulation, proliferation, transcription, and FIGURE 4. AHR target genes are modulated in neonates but not at epigenetic regulation differentially methylated (Fig. 6). However, maturity. (A) At maturity (6–8 wk of age), CD8+ T cells were isolated from there was little correlation between DMRs in gene bodies and developmentally exposed mice and gene expression was evaluated. Vali- gene expression. dated AHR target genes are listed, with the ratio of RNA-seq normalized DNA methylation of promoter regions across the genome was reads for TCDD/Veh for naive and infected shown. No statistically sig- significantly diminished in CD8+ T cells from TCDD infected , nificant differences were observed at FDR 5%. Similar results were offspring compared with all other groups (Fig. 7A). Considering obtained using qPCR (not shown). ND, not detected. (B) Mean Cyp1a1 DEGs in Veh naive versus TCDD naive groups and Veh infected expression at PND7. Livers were removed from 7-d-old offspring of different dams that were treated Veh or TCDD. Nucleic acids were prepared, versus TCDD infected groups, we determined whether the pro- reverse transcribed, and used for qPCR. Data were analyzed using the moter region for each DEG was differentially methylated (Fig. 7B, DDCt method, using L13 as an internal control. *p # 0.05 using a Student 7C). The Veh naive versus TCDD naive comparison had few t test. DEGs containing DMRs in their promoters (Fig. 7B). In contrast, The Journal of Immunology 7 Downloaded from http://www.jimmunol.org/ by guest on September 28, 2021

FIGURE 5. Developmental activation of AHR does not lead to changes in Dnmt expression. (A) Dnmt expression levels were measured by RT-qPCR in CD8+ T cells isolated from developmentally exposed mice. Relative expression is presented as DDCT normalized to L13. (B) Putative AHREs were identified upstream and in the gene bodies of Dnmt1, Dnmt3a, and Dnmt3b.(C–E) Binding of AHR to putative AHREs was measured by ChIP assay using isolated bone marrow cells, thymocytes, and CD8+ T cells. DNA enrichment is represented as the percentage of total input after subtracting the values of the relevant control Abs. Representative results are shown for the putative AHREs indicated by an asterisk in (B) and are consistent across the others tested. most DEGs in the Veh infected to TCDD infected comparison had To further affirm the observed DMRs and DEGs identified by either hypomethylation or a mixture of hyper- and hypomethyla- high-throughput sequencing, a subset of 25 genes from CD8+ tion at their promoters (Fig. 7C). We next examined whether T cells purified from developmentally exposed mice was exam- differential promoter methylation (hypo- or hypermethylation) ined. When visualized with a genome browser, the data show correlated with altered gene expression. For CD8+ T cells from consistently that cells from the TCDD-exposed and infected group Veh naive versus TCDD naive groups, changes in promoter have a methylation pattern that is distinct from the other groups. methylation and gene expression had no correlation (Fig. 7D). For example, promoter methylation of three representative genes, However, following infection, changes in promoter methylation Gzmb, Ccnb2, and Smarca4, which are involved in CD8+ T cell inversely correlated with gene expression in the Veh infected/ activation, cell cycle regulation, and DNA damage repair, re- TCDD infected comparison (Fig. 7E). spectively, showed notable differences upstream of the TSS 8 EARLY LIFE AHR ACTIVATION REPROGRAMS ANTIVIRAL IMMUNITY

FIGURE 6. Differential gene body methylation is observed following developmental activation of AHR. (A) Differential gene body methylation is compared in CD8+ T cells from infected adult offspring of Veh and TCDD treated dams. The graph depicts the log2 (fold change) of differentially methylated gene bodies for each gene, with hypermethylated genes shown in red and hypomethylated genes shown in blue. (B) IPA analysis was performed on these genes. Signiﬁcantly different pathways relevant for the CD8+ T cell response to infection are shown, indicating the contribution from hyper- and hypomethylated genes. The x-axis indicates the ratio of genes with differential gene body methylation to all genes in the indicated IPA pathway.

(Fig. 7F–H). Differential methylation and gene expression were time a whole-genome analysis of DNA methylation and gene independently examined by qPCR using CD8+ T cells isolated expression of CD8+ T cells in mice following developmental ac- from all four groups. In agreement with sequencing data, genes tivation of AHR has been performed, it was important to not ex- Downloaded from such Gzmb, Ccnb2,andSmarca4 had diminished promoter clude nonactivated cells a priori, because doing so could have methylation and elevated gene expression when isolated from biased the information obtained and missed critical differences. infected offspring that were developmentally exposed to TCDD Thus, in this study, we interrogated DNA methylation and gene versus those from infected offspring of Veh treated dams (Fig. 7I– expression profiles of the total pool of CD8+ T cells from devel- K). Thus, target gene approaches support the overall correlation opmentally exposed mice, not just in the cells that had acquired an between promoter methylation and gene expression that were effector phenotype. Using this unbiased approach, we discovered http://www.jimmunol.org/ observed using genome-wide approaches. Moreover, these data that early life activation of AHR skews gene promoters toward + show that developmental activation of AHR modifies promoter hypomethylation following infection in CD8 T cells, potentially methylation in CD8+ T cells that are responding to infection, and causing the inappropriately enhanced transcription observed. these changes correlate with altered gene transcription and with Disrupted transcriptional potential may result from differential reduced clonal expansion and differentiation. methylation at individual gene promoters, or from broader areas of differential methylation observed across chromosomes. For in- Discussion stance, it is possible that altered DNA methylation influences The AHR has been extensively studied as an environmental sensor regulation of enhancer regions and other genomic elements, as our data reveal that triggering AHR during development changes DNA by guest on September 28, 2021 that promotes the metabolism and elimination of pollutants, yet + it is now clear that it plays a much broader role, including regulation methylation in CD8 T cells across many genomic features. Given emerging understanding of the complex ways that DNA methyl- of the immune system (8). Although developmental exposure to ation contributes to transcriptional regulation in other cell types environmental AHR ligands alters immune function in animal (18), these changes outside of gene promoters may have broad and models and human populations, how AHR exerts these persistent yet-unrealized implications as to how early life activation of AHR changes has remained enigmatic (2, 6, 10). We demonstrated that influences T cell function. Likewise, it will be interesting and early life activation of AHR fundamentally alters the responsive important to determine which changes in DNA methylation reflect capacity of CD8+ T cells. However, this altered response was not changes in distinct subsets of the total CD8+ T cell pool (e.g., due to fewer CD8+ T cells in developmentally exposed animals naive versus effector), which may further reveal nuances in how prior to infection, nor was it due to sustained expression of AHR + developmental exposures leads to changes in DNA methylation target genes repressing CD8 T cell function. Instead, develop- patterns and how these are linked to an altered response later in mental signaling through AHR reprogrammed DNA methylation + life. and gene expression profiles of CD8 T cells, which likely con- Combined with genome-wide changes in DNA methylation tributes to their diminished response following infection. Sur- patterns, gene expression profiling demonstrates that early life prisingly, the mechanism is not simply AHR-mediated increases AHR activation durably alters the responsive capacity of T cells. + in DNA hypermethylation causing gene silencing in CD8 T cells. Based on the observed differences in gene expression in devel- Rather, this work reveals a more intricate mechanism. Changes in opmentally exposed infected mice, the defective CD8+ T cell re- DNA methylation and gene expression in T cells from develop- sponse is not simply due to these cells remaining in a naive state mentally exposed mice were relatively modest prior to infection, following infection, nor is it due to overt loss of expression of but became more evident and complex following infection. This genes required for effector function. Instead, developmental AHR indicates that AHR modifies the responsive capacity of developing activation alters the transcriptional profile in CD8+ T cells, and the + CD8 T cells and regulates their function by influencing multi- observed changes suggest several potential defects, which are not faceted interactions between DNA methylation and gene expres- mutually exclusive. For instance, infected, developmentally ex- sion during response to infection. posed mice had fewer CTLs and virus-specific CD8+ T cells, yet The underlying reason that developmental activation of AHR expression of effector genes remained high (e.g., Gzmb), which is results in a poorer CD8+ T cell response to influenza virus in- similar to exhausted T cells (49). Generally observed after pro- fection later in life is not known. It could be due to changes within longed exposure to Ag, such as in chronic infections, exhausted the effector cell subset, but it could also be due to other changes, T cells paradoxically lose effector function but retain expression such as negative regulatory signals in the CD8+ T cells that are not of genes for key effector molecules. Consistent with this overall CD44hiCD62Llo. Given that, to our knowledge, this is the first idea, AHR regulates, either directly or indirectly, proliferation The Journal of Immunology 9 Downloaded from http://www.jimmunol.org/ by guest on September 28, 2021

FIGURE 7. Changes in gene expression correlate with promoter methylation in infected and developmentally exposed mice. (A) Genome-wide methylation at promoters (2 kb upstream to TSS) is shown for Veh naive, TCDD naive, Veh infected and TCDD infected. (B and C) DMRs at gene promoters were determined for the DEGs in the (B) Veh naive versus TCDD naive and (C) Veh infected versus TCDD infected comparisons. Promoters were classiﬁed as containing only hypermethylated DMRs (Hyper), only hypomethylated DMRs (Hypo), both hyper- and hypomethylated DMRs (Both), or lacking any DMRs (No DMR), and the number of DEG promoters in each category is shown. (D and E) For the DEGs in the (D) Veh naive versus TCDD naive and (E) Veh infected versus TCDD infected comparisons that had a unidirectional change in promoter methylation (Hyper only or Hypo only), the

RPM difference in methylation is plotted on the x-axis, and the log2 (fold change) of gene expression is plotted on the y-axis. Correlation coefﬁcient and p value are indicated on each plot. *p # 0.00001 between treatment groups of similar infection status using the Wilcoxon rank sum test. (F–H) Visualization of promoter methylation using the University of California, Santa Cruz browser was performed. Maximal height for visualization was set at RPM of 1.5 for all MeDIP-seq tracks. Traces show relative DNA methylation across the promoter regions for Grzmb, Ccnb2, and Smarca4; TSS is indicated with an arrow. (I–K) CD8+ T cells were isolated from naive (not shown) and infected adult mice that had been exposed during development to Veh or TCDD. RNA and DNA were prepared separately from the same pool of puriﬁed CD8+ T cells. Following MeDIP, qPCR was used to evaluate and compare promoter methylation (black bars). Input DNA values were used for normalization. Gene expression in CD8+ T cells was determined using RT-qPCR (gray bars).

Data were analyzed using the DDCt method, with L13 serving as the internal control. The qPCR data are presented as log2 fold change in the TCDD infected group relative to cells from the Veh infected exposure group. TI, developmentally exposed to TCDD and infected; TN, developmentally exposedto TCDD and naive; VI, developmentally exposed to Veh and infected; VN, developmentally exposed to Veh and naive. capacity and exhaustion in hematopoietic stem cells, as well as those involved in cell cycle regulation and DNA repair (56). Re- cellular senescence in other cell types (50–55). Inappropriate early lated to tolerance and culling of inappropriately activated T cells life AHR signaling could also lead to an immune system that are apoptosis and deletion of improperly activated T cells, such as is improperly poised toward tolerance, an essential regulatory via activation-induced cell death. At higher doses of TCDD, en- mechanism that prevents self-reactive lymphocytes from re- hanced thymocyte apoptosis has been observed (57, 58). However, sponding. Indeed, deregulated tolerance underlies imbalanced we did not detect an increase in apoptotic CD8+ T cells from immunity and contributes to disease (56). Interestingly, CD8+ developmentally exposed mice (data not shown), nor did we find T cells from developmentally exposed and infected mice and differences in DNA methylation or expression of genes associated tolerized CD8+ T cells share a similar pattern of DEGs, including with apoptosis or activation-induced cell death. However, the 10 EARLY LIFE AHR ACTIVATION REPROGRAMS ANTIVIRAL IMMUNITY overall shift toward DNA hypomethylation could signify that DNA methylation patterns are sensitive to early life environ- developmental exposure leads to greater genomic instability in mental insults, although the functional consequences of such changes T cells. Genomic instability can enhance DNA damage (59, 60), are not fully understood, particularly in the context of immune potentially contributing to the reduced clonal expansion of CD8+ responses to infection. Early life exposure to AHR binding pollutants T cells after infection. Pathways involved in DNA damage repair causes enduring changes in the responsive capacity of the immune and cell cycle regulation were enriched among the DEGs. Moreover, system, including reduced CD8+ T cell clonal expansion and dif- although not examined in the context of developmental exposure, ferentiation in response to IAV. As CD8+ T cells respond to acute AHR agonists influence DNA stability (61). These observations primary infection, their DNA methylation profiles change, and this suggest that early life AHR activation influences CD8+ T cell is thought to influence acquisition of effector function (34). However, function later in life without causing overt immunotoxicity. mechanisms that lead to long-lasting functional deficits following Consistent with these potential mechanisms discussed in the early life exposures are unknown. In this study, we demonstrate that present study, recent human transcriptomic data show correlations activation of AHR during development alters DNA methylation and + between fetal exposure to AHR-binding pollutants, including gene expression profiles in CD8 T cells of adult offspring. Changes TCDD, and altered expression of genes involved in immune in DNA methylation are relatively subtle in the absence of infection. + regulation, cell cycle, and Ag processing and presentation in cord However, as CD8 T cells respond to viral infection, pronounced blood cells (62). differences in DNA methylation are revealed across the genome. We showed that developmental exposure to an AHR ligand These findings reveal that early life AHR activation alters the in- disrupts DNA methylation and gene expression profiles in CD8+ teraction between DNA methylation and gene expression, which

+ Downloaded from T cells. Yet, to fully understand how the early life environment could contribute to the reduced responsive capacity of CD8 Tcells. shapes the function of the immune system later in life, it will be The implications of this include a better understanding of how early important to investigate how AHR affects other epigenetic regu- life exposures to chemicals that bind AHR durably shape immunity latory mechanisms, and to integrate these changes in the context later in life, and provide a new line of thinking with regard to AHR of cell–cell interactions that are the foundation of antiviral T cell as a key regulator of the development and function of the immune responses. For instance, in addition to DNA methylation, DNA system. hydroxymethylation, histone modifications, and microRNAs http://www.jimmunol.org/ shape the epigenetic landscape to influence transcription and Acknowledgments cellular function. Although not examined in the context of de- We thank Shauna Marr, Dr. Steven Welle, and Michelle Zanche for tech- velopmental exposures, in nonimmune cells, AHR ligands alter nical advice and assistance, and Lisbeth Boule, Dr. Mike Bulger, and regulation of histone modifications (63–66). AHR activation in Dr. Steve Georas for critical evaluation of the manuscript. fetal thymocytes alters levels of many microRNAs that might be involved in T cell activation (67, 68). Thus, in addition to DNA Disclosures methylation, developmental AHR activation may alter other epi- The authors have no financial conflicts of interest.

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SUPPLEMENTAL FIGURE 1. Quality control assessments of MeDIP-seq and RNA- seq are shown. (A) Following high-throughput sequencing, MeDIP-seq and RNA-seq reads were aligned to the mouse genome. (B) Correlation determination of gene body methylation of two independently generated samples for each treatment group is shown.

MEDIPS.saturationAnalysis. (D) Sequence pattern coverage analysis was performed using the MEDIPS.coverageAnalysis function of MEDIPS R package.

SUPPLEMENTAL FIGURE 2. Overall DNA methylation of each chromosome is presented. Boxplot representations were used to quantitatively assess the methylation levels in purified CD8+ T cells from the Veh naïve (VN), TCDD naïve (TN), Veh Infected (VI) and TCDD infected (TI) groups. RPM values were plotted as boxplots using the boxplot function in R.

SUPPLEMENTAL FIGURE 3. DNA methylation across each chromosome in isolated CD8+ T cells from adult mice that were developmentally exposed to peanut oil vehicle (Veh) or TCDD is shown. Coverage density along the chromosomes was calculated, normalized to library size and plotted to visualize differences in methylation across different maternal exposure and infection of the adult offspring. Red = Veh naïve; Aquamarine = TCDD naïve; dark blue = Veh infected; green = TCDD infected.

Supplemental Table I

Veh naïve vs. TCDD naïve Gene Chromosome Start End Strand Veh naïve TCDD naïve Fold Change Log2(Fold Change) p-value q-value Dcpp2 chr17 24035688 24037754 + 1.68838 24.0749 14.26 3.83 0.00000000 0.00000000 Dcpp3 chr17 24054424 24056408 + 1.02464 14.2303 13.89 3.80 0.00000000 0.00000001 Abpe chr7 32087787 32089996 + 0.447863 5.97193 13.33 3.74 0.00013707 0.02390510 Abph chr7 32075537 32076835 - 0.724723 6.09426 8.41 3.07 0.00024787 0.03848990 Obp1a chrX 75330843 75336713 - 1.88565 14.1855 7.52 2.91 0.00000000 0.00000000 BC048546 chr6 128489839 128531624 - 0.120928 0.855967 7.08 2.82 0.00000084 0.00025058 Rag1 chr2 101478410 101489689 - 0.183758 1.00764 5.48 2.46 0.00000000 0.00000116 Gm5938 chrX 75370805 75375742 + 1.71591 8.69463 5.07 2.34 0.00000000 0.00000082 Gm1553 chr10 81949277 81955363 - 1.32016 6.49204 4.92 2.30 0.00002420 0.00510066 Car6 chr4 149561124 149575244 - 1.48222 7.08296 4.78 2.26 0.00000000 0.00000000 Dcpp1 chr17 24017842 24019820 + 1.13061 5.08321 4.50 2.17 0.00010290 0.01892450 Gm14743 chrX 75485800 75491260 - 2.98457 12.5281 4.20 2.07 0.00000000 0.00000000 Smr3a chr5 88431549 88437559 + 10.7304 39.1679 3.65 1.87 0.00000000 0.00000000 Bpifa2 chr2 153834011 153841809 + 31.4971 108.325 3.44 1.78 0.00000000 0.00000000 2310057J18Rik chr10 28692093 28706112 - 2.10405 6.61 3.14 1.65 0.00000002 0.00000641 Amy1 chr3 113258869 113280668 - 8.63406 26.4694 3.07 1.62 0.00000000 0.00000000 Chia chr3 105916299 105935034 + 2.95963 6.16452 2.08 1.06 0.00000470 0.00125194 Clcn4-2 chr7 7235026 7252222 - 15.103 24.8069 1.64 0.72 0.00000000 0.00000000 Acpp chr9 104190569 104240052 - 8.26675 13.1164 1.59 0.67 0.00000000 0.00000000 Coro2a chr4 46549808 46614801 - 6.61259 9.98516 1.51 0.59 0.00000002 0.00000641 N4bp3 chr11 51456590 51471183 - 4.09833 6.16442 1.50 0.59 0.00013365 0.02371780 Cfl2 chr12 55959805 55963864 - 6.3728 8.99114 1.41 0.50 0.00017914 0.02987890 Nrp2 chr1 62749890 62865266 + 2.96129 4.13959 1.40 0.48 0.00004504 0.00893312 Lgals1 chr15 78757154 78760895 + 32.0165 43.9401 1.37 0.46 0.00002215 0.00476677 Tbc1d16 chr11 119004356 119089813 - 3.34656 4.42136 1.32 0.40 0.00032504 0.04780600 Hsph1 chr5 150419419 150438890 - 41.8187 52.6586 1.26 0.33 0.00000456 0.00124753 Vamp1 chr6 125165598 125172324 + 17.6028 22.0276 1.25 0.32 0.00007830 0.01494350 Luc7l3 chr11 94152452 94183225 - 33.6216 40.9067 1.22 0.28 0.00019734 0.03168430 Tapbp chr17 34056422 34066235 + 149.414 166.661 1.12 0.16 0.00000061 0.00018760 Srsf1 chr11 87861172 87867259 + 70.2053 78.3087 1.12 0.16 0.00000289 0.00083477 Hdac7 chr15 97614795 97674933 - 75.8519 84.2117 1.11 0.15 0.00000001 0.00000511 Sipa1 chr19 5651184 5663707 - 66.819 74.1539 1.11 0.15 0.00000557 0.00144568 Dnmt1 chr9 20711649 20764332 - 36.8058 40.4777 1.10 0.14 0.00018860 0.03076880 Ddx6 chr9 44412974 44448814 + 126.792 119.089 0.94 -0.09 0.00023052 0.03643330 Foxp1 chr6 98875335 99385339 - 51.6981 47.5284 0.92 -0.12 0.00000636 0.00160900 Erbb2ip chr13 104608865 104710594 - 56.676 51.9424 0.92 -0.13 0.00006376 0.01240220 Satb1 chr17 51875511 51972615 - 139.75 127.183 0.91 -0.14 0.00000000 0.00000001 Ubr5 chr15 37897082 38008608 - 33.925 30.3623 0.89 -0.16 0.00001211 0.00284862 Cmah chr13 24419288 24569154 + 69.5646 61.3712 0.88 -0.18 0.00025115 0.03848990 Ino80d chr1 63094374 63160841 - 13.4753 11.818 0.88 -0.19 0.00002820 0.00582229 Tnrc6b chr15 80541742 80771516 + 21.7136 19.0222 0.88 -0.19 0.00000001 0.00000272 Txnip chr3 96359690 96370724 + 347.334 289.287 0.83 -0.26 0.00000000 0.00000000 Itga4 chr2 79095582 79269145 + 72.7364 60.569 0.83 -0.26 0.00016111 0.02762000 Macf1 chr4 123026875 123361603 - 116.849 95.8689 0.82 -0.29 0.00000004 0.00001325 Zfp36 chr7 29161802 29164247 - 77.1101 62.7344 0.81 -0.30 0.00008978 0.01681800 P2ry10 chrX 104284673 104300309 + 46.5771 37.7813 0.81 -0.30 0.00010809 0.01952440 Il7r chr15 9435913 9459631 - 217.491 175.74 0.81 -0.31 0.00001186 0.00284862 Mdn1 chr4 32744093 32862192 + 29.3075 23.6652 0.81 -0.31 0.00000773 0.00190821 Ifngr1 chr10 19311763 19330031 + 66.7863 53.9023 0.81 -0.31 0.00003835 0.00775827 Syne1 chr10 5151833 5326342 + 18.8977 15.1438 0.80 -0.32 0.00000016 0.00005268 Lpp chr16 24392641 24992664 + 3.18652 2.53094 0.79 -0.33 0.00032611 0.04780600 Fam46c chr3 100275458 100293115 - 23.1355 17.9516 0.78 -0.37 0.00018019 0.02987890 Ddx60 chr8 64406885 64516492 + 12.3424 9.51571 0.77 -0.38 0.00001678 0.00368889 Gm4759 chr7 113565063 113584587 - 30.5121 23.4602 0.77 -0.38 0.00000342 0.00096052 Lars2 chr9 123276057 123371782 + 512.265 391.747 0.76 -0.39 0.00001582 0.00355604 Zfp36l2 chr17 84583268 84587287 - 230.321 170.87 0.74 -0.43 0.00000000 0.00000038 Dusp2 chr2 127161894 127164113 + 119.215 88.1873 0.74 -0.43 0.00000000 0.00000094 Tnfaip3 chr10 18720716 18735216 - 21.4588 15.8126 0.74 -0.44 0.00000000 0.00000121 Tsc22d3 chrX 137074067 137135061 - 217.045 157.482 0.73 -0.46 0.00000000 0.00000001 Junb chr8 87500807 87502647 - 54.7248 39.109 0.71 -0.48 0.00000000 0.00000113 Ddit4 chr10 59412422 59414518 - 124.413 86.2809 0.69 -0.53 0.00000000 0.00000000 Cxcr4 chr1 130484775 130488876 - 101.464 68.4012 0.67 -0.57 0.00000000 0.00000000 Slc15a2 chr16 36750249 36785048 - 7.72456 4.95818 0.64 -0.64 0.00000019 0.00006117 Abca1 chr4 53043660 53172767 - 8.71989 5.35373 0.61 -0.70 0.00000000 0.00000000 Ppp1r15a chr7 52778287 52781638 - 11.5446 6.70696 0.58 -0.78 0.00000000 0.00000010 Dusp1 chr17 26642535 26645417 - 4.48836 2.15518 0.48 -1.06 0.00001415 0.00325201 Fos chr12 86814850 86818219 + 8.48935 2.96455 0.35 -1.52 0.00000000 0.00000000 Jun chr4 94715726 94718913 - 3.12004 1.06595 0.34 -1.55 0.00000000 0.00000071 Hspa1b chr17 35093373 35096183 - 0.812455 0.143266 0.18 -2.50 0.00028602 0.04318000

Veh infected vs. TCDD infected Gene Chromosome Start End Strand Veh infected TCDD infected Fold Change Log2(Fold Change) p-value q-value Atp6v0c-ps2 chr17 24300831 24306374 - 0 9.24701 Inf 0.00000023 0.00002112 Gm5111 chr6 48539443 48540583 + 0 0.913104 Inf 0.00156588 0.04201960 Rag1 chr2 101478410 101489689 - 0.0392739 2.23153 56.82 5.83 0.00000000 0.00000000 Hspa1b chr17 35093373 35096183 - 0.0651079 3.07092 47.17 5.56 0.00000001 0.00000090 Camkv chr9 107838250 107852022 + 0.0274514 0.898682 32.74 5.03 0.00167713 0.04434810 Gfra1 chr19 58311181 58528956 - 0.0538691 1.04024 19.31 4.27 0.00002544 0.00127389 Arpp21 chr9 111967594 112251429 - 0.131399 1.94622 14.81 3.89 0.00000087 0.00006912 S100a9 chr3 90496554 90499613 - 0.557528 7.7703 13.94 3.80 0.00001275 0.00071070 Fads2 chr19 10138653 10175993 - 0.143746 1.50602 10.48 3.39 0.00106187 0.03058130 Alas2 chrX 146981959 147005165 + 0.200757 1.64379 8.19 3.03 0.00007858 0.00329716 Hbb-b1 chr7 110961037 110962437 - 0.784073 5.67311 7.24 2.86 0.00003290 0.00159619 Hba-a1 chr11 32196488 32197310 + 2.78088 19.1744 6.90 2.79 0.00000000 0.00000000 S100a8 chr3 90472992 90473956 + 1.15489 7.76255 6.72 2.75 0.00045146 0.01473420 Endou chr15 97541449 97561836 - 0.302492 1.97952 6.54 2.71 0.00000108 0.00008322 Beta-s chr7 110975036 110976442 - 4.58891 27.7523 6.05 2.60 0.00000000 0.00000000 Klrb1b chr6 128763723 128776333 - 0.357467 1.94823 5.45 2.45 0.00000753 0.00044252 Rapgef3 chr15 97575200 97598097 - 0.161896 0.870353 5.38 2.43 0.00008008 0.00334736 Cdc25c chr18 34892650 34911187 - 0.404552 2.11661 5.23 2.39 0.00001777 0.00094195 Hepacam2 chr6 3407088 3444498 - 0.262696 1.17868 4.49 2.17 0.00087848 0.02608560 Fam64a chr11 71856003 71860872 + 0.837463 3.75341 4.48 2.16 0.00000082 0.00006522 Pon3 chr6 5170851 5206233 - 0.883323 3.86402 4.37 2.13 0.00000020 0.00001874 BC030867 chr11 102110195 102126497 + 0.277605 1.19751 4.31 2.11 0.00026429 0.00935410 Capn5 chr7 105270074 105333309 - 0.292697 1.22534 4.19 2.07 0.00000345 0.00021806 Chi3l3 chr3 105950471 105970482 - 0.637522 2.60947 4.09 2.03 0.00008691 0.00361904 Fkbp11 chr15 98554798 98558629 - 0.926927 3.72917 4.02 2.01 0.00106928 0.03058130 Fn1 chr1 71632096 71699745 - 0.641356 2.49836 3.90 1.96 0.00000000 0.00000000 Smo chr6 29685496 29711366 + 0.328939 1.27776 3.88 1.96 0.00001484 0.00080246 2010001M09Rik chr18 35806918 35809021 - 11.6127 44.1609 3.80 1.93 0.00000000 0.00000000 Sirpa chr2 129418574 129457964 + 0.455602 1.70299 3.74 1.90 0.00000047 0.00003932 Cd93 chr2 148262386 148269271 - 0.380881 1.41785 3.72 1.90 0.00000001 0.00000089 Pif1 chr9 65435011 65443769 + 0.447811 1.64093 3.66 1.87 0.00000400 0.00024413 Cacna1h chr17 25507497 25570728 - 0.314201 1.1479 3.65 1.87 0.00000001 0.00000107 Mki67 chr7 142881470 142908062 - 6.60571 23.621 3.58 1.84 0.00000000 0.00000000 Cenpf chr1 191464492 191511965 - 0.721849 2.56775 3.56 1.83 0.00000000 0.00000000 Itga1 chr13 115748288 115892172 - 0.363074 1.2744 3.51 1.81 0.00000038 0.00003272 Prr5 chr15 84511427 84534103 + 0.938333 3.23372 3.45 1.79 0.00001359 0.00075089 E2f8 chr7 56121798 56136411 - 1.1452 3.74048 3.27 1.71 0.00000000 0.00000002 Spag5 chr11 78115092 78135956 + 1.45339 4.69472 3.23 1.69 0.00000000 0.00000000 Emp1 chr6 135312948 135333191 + 1.00185 3.19791 3.19 1.67 0.00000051 0.00004235 Dntt chr19 41103764 41134015 + 3.92482 12.5123 3.19 1.67 0.00000000 0.00000000 Rhobtb1 chr10 68671299 68754532 + 0.266041 0.842993 3.17 1.66 0.00094789 0.02776740 Lamc1 chr1 155066051 155179916 - 0.49377 1.54691 3.13 1.65 0.00000001 0.00000084 Ccdc18 chr5 108561932 108661968 + 0.284505 0.888009 3.12 1.64 0.00026012 0.00923856 Kntc1 chr5 124199734 124271602 + 0.632325 1.96381 3.11 1.63 0.00000000 0.00000011 Ttk chr9 83728295 83765997 + 0.566086 1.74766 3.09 1.63 0.00009839 0.00402009 Gpr56 chr8 97501008 97538108 + 0.434051 1.32888 3.06 1.61 0.00025109 0.00897660 Mcm10 chr2 4911769 4933837 - 0.979019 2.99422 3.06 1.61 0.00000003 0.00000330 Csf1r chr18 61265225 61290793 + 0.442623 1.33714 3.02 1.59 0.00010457 0.00425631 Casc5 chr2 118872854 118929857 + 0.946212 2.85044 3.01 1.59 0.00000000 0.00000000 Mpp2 chr11 101918330 101949829 - 0.37252 1.09759 2.95 1.56 0.00042419 0.01405500 Esm1 chr13 113999866 114008312 + 1.03198 3.03036 2.94 1.55 0.00004447 0.00210129 Aspm chr1 141351349 141390665 + 0.728638 2.13705 2.93 1.55 0.00000000 0.00000000 Orc1 chr4 108252058 108287436 + 0.569675 1.66884 2.93 1.55 0.00016314 0.00626486 Clspn chr4 126234223 126271147 + 1.48037 4.30119 2.91 1.54 0.00000000 0.00000000 Ccne2 chr4 11118500 11181406 + 0.675996 1.94237 2.87 1.52 0.00075439 0.02307900 Dennd5b chr6 148936590 149050202 - 0.351197 1.00735 2.87 1.52 0.00000076 0.00006093 Itgam chr7 135206153 135262005 + 0.754914 2.16307 2.87 1.52 0.00000000 0.00000025 Shcbp1 chr8 4735979 4779534 - 1.42996 4.03533 2.82 1.50 0.00000364 0.00022479 Kif11 chr19 37450892 37496349 + 3.14335 8.87042 2.82 1.50 0.00000000 0.00000000 Rpl26 chr11 68715067 68718036 + 5.83725 16.4601 2.82 1.50 0.00158764 0.04229040 Gzmb chr14 56877694 56881097 - 16.6602 46.8529 2.81 1.49 0.00000000 0.00000000 Igj chr5 88948833 88956922 - 102.808 287.198 2.79 1.48 0.00000000 0.00000000 Ckap2l chr2 129093945 129122948 - 1.5773 4.37111 2.77 1.47 0.00000001 0.00000090 Espl1 chr15 102126723 102154787 + 0.982963 2.68748 2.73 1.45 0.00000000 0.00000005 Ckap4 chr10 83989049 83996633 - 1.39352 3.80083 2.73 1.45 0.00000034 0.00002994 Neil3 chr8 54672220 54724419 - 1.14 3.10747 2.73 1.45 0.00003255 0.00158619 Nusap1 chr2 119435267 119475896 + 2.96901 8.08801 2.72 1.45 0.00000000 0.00000000 Pbk chr14 66424747 66436659 + 1.13494 3.07733 2.71 1.44 0.00058546 0.01855760 Coro2b chr9 62267298 62384851 - 0.404615 1.09535 2.71 1.44 0.00174930 0.04537320 Gzma chr13 113884034 113891189 - 36.3571 98.0803 2.70 1.43 0.00000000 0.00000000 Cx3cr1 chr9 119957810 119977400 - 0.463037 1.24545 2.69 1.43 0.00071761 0.02209340 Slpi chr2 164179805 164182243 - 26.795 71.8872 2.68 1.42 0.00000000 0.00000000 Il2ra chr2 11564418 11614821 + 3.46072 9.28255 2.68 1.42 0.00000000 0.00000000 Raph1 chr1 60540028 60623609 - 0.326569 0.875319 2.68 1.42 0.00001857 0.00097516 Cdca2 chr14 68294410 68333898 - 1.19026 3.18426 2.68 1.42 0.00000001 0.00000115 Ube2c chr2 164595428 164598402 + 5.95002 15.7005 2.64 1.40 0.00000005 0.00000499 Melk chr4 44313788 44377547 + 1.00202 2.63786 2.63 1.40 0.00002936 0.00145060 Sgol1 chr17 53814111 53828640 - 0.822343 2.16468 2.63 1.40 0.00002366 0.00120157 Bub1 chr2 127625935 127657595 - 1.26342 3.32063 2.63 1.39 0.00000000 0.00000005 Fam129b chr2 32731653 32816775 + 1.00228 2.62499 2.62 1.39 0.00000358 0.00022387 Ncapg2 chr12 117643874 117702004 + 2.08084 5.3927 2.59 1.37 0.00000000 0.00000000 Stac2 chr11 97897937 97914776 - 0.711328 1.84171 2.59 1.37 0.00034755 0.01191540 Cenpe chr3 134875526 134936504 + 1.36755 3.52341 2.58 1.37 0.00000000 0.00000000 Stil chr4 114672722 114715803 + 0.617595 1.58059 2.56 1.36 0.00001813 0.00095657 Kif2c chr4 116832240 116855229 - 1.36589 3.48981 2.55 1.35 0.00000362 0.00022457 Ccna2 chr3 36451527 36470918 - 6.64967 16.9396 2.55 1.35 0.00000000 0.00000000 Nek2 chr1 193645351 193656928 + 2.04856 5.21464 2.55 1.35 0.00000001 0.00000121 Chdh chr14 30822185 31340242 + 0.441504 1.12379 2.55 1.35 0.00017459 0.00663430 Kif4 chrX 97821403 97922610 + 1.17977 3.00265 2.55 1.35 0.00000004 0.00000463 Lyz2 chr10 116714596 116719328 - 9.45487 24.0389 2.54 1.35 0.00000000 0.00000000 Birc5 chr11 117710550 117717057 + 7.39789 18.7856 2.54 1.34 0.00000000 0.00000016 Kif14 chr1 138364534 138428088 + 0.448183 1.13594 2.53 1.34 0.00000486 0.00029343 Prc1 chr7 87439350 87461145 + 2.74472 6.91928 2.52 1.33 0.00000000 0.00000003 Ccnb1 chr13 101548693 101556441 - 4.09422 10.2985 2.52 1.33 0.00000000 0.00000001 Ncapg chr5 46061163 46248779 + 2.51414 6.32027 2.51 1.33 0.00000000 0.00000002 Top2a chr11 98854260 98885503 - 11.0865 27.8634 2.51 1.33 0.00000000 0.00000000 Rorc chr3 94176747 94202161 + 0.943001 2.36803 2.51 1.33 0.00028413 0.00996086 Cit chr5 116295664 116456350 + 0.62701 1.56237 2.49 1.32 0.00000170 0.00012137 Tspan2 chr3 102524153 102576233 + 0.444204 1.10515 2.49 1.31 0.00037543 0.01267140 Gins2 chr8 123012765 123112975 - 2.11163 5.23378 2.48 1.31 0.00062962 0.01971950 Depdc1a chr3 159158396 159192919 + 1.21266 2.99556 2.47 1.30 0.00000111 0.00008483 Esco2 chr14 66437863 66452806 - 1.10201 2.71085 2.46 1.30 0.00006661 0.00283701 Hip1 chr5 135882387 136020992 - 1.11409 2.7363 2.46 1.30 0.00000000 0.00000005 Syk chr13 52678805 52744161 + 1.77937 4.36002 2.45 1.29 0.00000000 0.00000000 Kif18b chr11 102766832 102786438 - 1.11262 2.71296 2.44 1.29 0.00002451 0.00123710 Cdca8 chr4 124595708 124614161 - 4.16265 10.0905 2.42 1.28 0.00000003 0.00000342 Kif20a chr18 34758268 34811390 + 2.86639 6.92966 2.42 1.27 0.00000000 0.00000004 Tpx2 chr2 152673699 152721057 + 2.95022 7.13032 2.42 1.27 0.00000000 0.00000000 Itgax chr7 135273081 135294171 + 2.48786 6.00258 2.41 1.27 0.00000000 0.00000002 Rad51 chr2 118938552 118961806 + 2.35618 5.67477 2.41 1.27 0.00000251 0.00016632 1500009L16Rik chr10 83185609 83225507 + 4.09393 9.83895 2.40 1.27 0.00000845 0.00047918 Mxd3 chr13 55423415 55431091 - 2.18306 5.24101 2.40 1.26 0.00061056 0.01923350 Cdc6 chr11 98769202 98785256 + 1.00801 2.40817 2.39 1.26 0.00000838 0.00047918 Rrm2 chr12 25393118 25399011 + 11.1007 26.3764 2.38 1.25 0.00000000 0.00000000 Palm chr10 79256316 79283641 + 0.942125 2.23847 2.38 1.25 0.00006490 0.00278783 Anln chr9 22135657 22193650 - 0.741253 1.76085 2.38 1.25 0.00002459 0.00123710 Bub1b chr2 118423946 118467328 + 3.0315 7.18841 2.37 1.25 0.00000000 0.00000001 Lgals3 chr14 47993534 48005842 + 9.80689 23.2025 2.37 1.24 0.00000000 0.00000000 Slc9a5 chr8 107872157 107893781 + 0.43806 1.03611 2.37 1.24 0.00125029 0.03475220 2810417H13Rik chr9 65676732 65756601 + 9.08939 21.3894 2.35 1.23 0.00000000 0.00000000 5730590G19Rik chr7 86805081 86859072 + 0.698249 1.63968 2.35 1.23 0.00000377 0.00023152 Tk1 chr11 117676832 117701222 - 4.95634 11.6165 2.34 1.23 0.00000022 0.00002081 Aurkb chr11 68859144 68865164 + 2.8121 6.58664 2.34 1.23 0.00000207 0.00014201 Sdc1 chr12 8778201 8800493 + 1.36636 3.19931 2.34 1.23 0.00002847 0.00141280 Farp1 chr14 121434795 121682948 + 0.43259 1.0112 2.34 1.23 0.00170845 0.04495740 Cdk1 chr10 68799382 68815660 - 2.35898 5.5093 2.34 1.22 0.00000038 0.00003270 Pld4 chr12 113998865 114007197 + 2.87706 6.71777 2.33 1.22 0.00000146 0.00010668 Gtse1 chr15 85690136 85707003 + 1.27636 2.95977 2.32 1.21 0.00005430 0.00239891 Clec12a chr6 129300261 129315321 + 1.0717 2.48052 2.31 1.21 0.00150031 0.04096830 Ccnf chr17 24360176 24388354 - 2.3324 5.39763 2.31 1.21 0.00000014 0.00001389 Ncaph chr2 126929545 126959690 - 2.75013 6.3525 2.31 1.21 0.00000007 0.00000774 Prr11 chr11 86902657 86922216 - 1.34658 3.10503 2.31 1.21 0.00001006 0.00056628 Dna2 chr10 62409776 62436936 + 0.888885 2.03733 2.29 1.20 0.00010852 0.00438442 Cybb chrX 9012377 9046450 - 1.41874 3.24635 2.29 1.19 0.00000072 0.00005907 Eaf2 chr16 36792969 36874912 - 1.55864 3.54831 2.28 1.19 0.00028714 0.01003400 Lat2 chr5 135076134 135090893 - 1.86723 4.24086 2.27 1.18 0.00023906 0.00863170 Kif15 chr9 122860198 122927851 + 1.82707 4.14164 2.27 1.18 0.00000001 0.00000144 Rad51ap1 chr6 126873436 126889573 - 1.34199 3.03282 2.26 1.18 0.00151503 0.04114780 Gzmk chr13 113962081 113971105 - 7.38159 16.6144 2.25 1.17 0.00000798 0.00046148 Ccnb2 chr9 70255495 70269361 - 6.75175 15.1899 2.25 1.17 0.00000000 0.00000033 Klrc1 chr6 129624876 129628928 - 5.52355 12.4211 2.25 1.17 0.00011977 0.00476812 Fgl2 chr5 20798778 20930495 + 3.28589 7.37975 2.25 1.17 0.00000000 0.00000008 S100a4 chr3 90407691 90409967 + 32.2243 71.8685 2.23 1.16 0.00000000 0.00000000 C330027C09Rik chr16 48994300 49019818 + 2.84713 6.28348 2.21 1.14 0.00000000 0.00000067 Blnk chr19 41003416 41069025 - 1.84253 4.06389 2.21 1.14 0.00018875 0.00700096 Stmn1 chr4 134024234 134029758 + 28.4329 62.6921 2.20 1.14 0.00000000 0.00000000 Fignl1 chr11 11700290 11708965 - 2.36517 5.21459 2.20 1.14 0.00000015 0.00001490 Mybl2 chr2 162880370 162910423 + 2.01792 4.43641 2.20 1.14 0.00000059 0.00004898 Hmmr chr11 40514889 40546939 - 2.02543 4.44982 2.20 1.14 0.00000021 0.00001982 Plk1 chr7 129302950 129313389 + 3.85826 8.46811 2.19 1.13 0.00000023 0.00002098 Traip chr9 107853293 107874599 + 1.48188 3.22754 2.18 1.12 0.00019483 0.00720216 Cd24a chr10 43298974 43304071 + 6.15724 13.3948 2.18 1.12 0.00000002 0.00000231 Cep55 chr19 38129514 38148915 + 2.38555 5.14348 2.16 1.11 0.00000178 0.00012649 S100a6 chr3 90416815 90418336 + 32.4689 70.0015 2.16 1.11 0.00000000 0.00000000 Tns3 chr11 8331654 8564538 - 0.668849 1.44126 2.15 1.11 0.00004852 0.00220652 Alcam chr16 52249108 52453110 - 1.09079 2.33499 2.14 1.10 0.00005561 0.00243701 Dtl chr1 193361243 193399413 - 1.59534 3.41224 2.14 1.10 0.00000795 0.00046148 Nuf2 chr1 171428064 171461595 - 2.02097 4.31534 2.14 1.09 0.00008866 0.00367750 Rad54l chr4 115748069 115796295 - 1.15565 2.45991 2.13 1.09 0.00006683 0.00283701 Arhgap33 chr7 31307244 31320028 - 0.822452 1.74399 2.12 1.08 0.00075599 0.02307900 Slc43a3 chr2 84776802 84798666 + 2.12267 4.4985 2.12 1.08 0.00006602 0.00282466 Ell2 chr13 75844931 75909806 + 2.10704 4.45718 2.12 1.08 0.00000261 0.00017181 Arhgap21 chr2 20769545 20889348 - 0.555218 1.17436 2.12 1.08 0.00038033 0.01279700 Anxa2 chr9 69301489 69339592 + 27.2459 57.4778 2.11 1.08 0.00000000 0.00000000 Cdca3 chr6 124780193 124783719 + 6.59632 13.8921 2.11 1.07 0.00000014 0.00001383 Adam11 chr11 102622752 102641576 + 0.707882 1.49037 2.11 1.07 0.00005772 0.00249907 Sgol2 chr1 58042183 58083121 + 1.04691 2.20409 2.11 1.07 0.00000188 0.00013249 Tcf4 chr18 69504145 69847621 + 0.766897 1.61402 2.10 1.07 0.00000092 0.00007204 Zbtb32 chr7 31374699 31377961 - 2.83016 5.95293 2.10 1.07 0.00011902 0.00475541 Ptprj chr2 90269912 90420804 - 1.25866 2.6474 2.10 1.07 0.00000026 0.00002322 Chaf1a chr17 56179838 56207449 + 2.4677 5.16998 2.10 1.07 0.00000088 0.00006912 Anxa1 chr19 20447923 20465161 - 2.66967 5.59263 2.09 1.07 0.00070391 0.02180840 Ckap2 chr8 23278623 23296291 - 1.63941 3.43297 2.09 1.07 0.00037191 0.01259430 Diap3 chr14 87056129 87540921 - 1.65791 3.47051 2.09 1.07 0.00003390 0.00163767 Fancd2 chr6 113481675 113546279 + 0.831452 1.73985 2.09 1.07 0.00051677 0.01656730 Neb chr2 51992166 52194318 - 0.90315 1.88519 2.09 1.06 0.00000000 0.00000000 Dlgap5 chr14 48007453 48038082 - 2.95721 6.1555 2.08 1.06 0.00000001 0.00000111 Cks1b chr3 89219393 89222213 - 8.32091 17.3081 2.08 1.06 0.00003766 0.00179496 Osbpl3 chr6 50243325 50406169 - 1.55751 3.23011 2.07 1.05 0.00000000 0.00000000 Prdm1 chr10 44156980 44178493 - 1.18094 2.44497 2.07 1.05 0.00004945 0.00223907 Cdc20 chr4 118100697 118109948 - 6.38083 13.2013 2.07 1.05 0.00000004 0.00000410 Mis18bp1 chr12 66233720 66273567 - 1.13472 2.34095 2.06 1.04 0.00035155 0.01197680 Kifc1 chr17 34012610 34027578 - 2.34263 4.81411 2.06 1.04 0.00010713 0.00434435 4930427A07Rik chr12 114394631 114403669 + 2.6132 5.365 2.05 1.04 0.00000198 0.00013824 Tacc3 chr5 34000795 34014846 + 6.17415 12.6527 2.05 1.04 0.00000000 0.00000012 Prdx4 chrX 151758462 151772997 - 6.59669 13.4833 2.04 1.03 0.00005082 0.00227340 Syt6 chr3 103379203 103439102 + 5.73261 11.7032 2.04 1.03 0.00000000 0.00000000 Hmgb3 chrX 68809167 68813829 + 5.29388 10.8071 2.04 1.03 0.00000250 0.00016632 Aurka chr2 172181695 172196006 - 2.87521 5.8424 2.03 1.02 0.00012499 0.00493959 BC013712 chr4 132338271 132352279 - 1.54934 3.1245 2.02 1.01 0.00107665 0.03063110 Spats2 chr15 98957275 99042897 + 1.93042 3.88138 2.01 1.01 0.00107515 0.03063110 Nrp1 chr8 130882972 131029375 + 2.09267 4.20615 2.01 1.01 0.00000010 0.00000998 Foxm1 chr6 128313011 128335162 + 2.76277 5.53414 2.00 1.00 0.00000013 0.00001296 Ifitm1 chr7 148153327 148155726 + 8.96156 17.7952 1.99 0.99 0.00000163 0.00011829 Kit chr5 75971011 76052746 + 0.910059 1.7996 1.98 0.98 0.00077816 0.02355730 Cpd chr11 76590709 76660510 - 0.67406 1.33227 1.98 0.98 0.00017629 0.00667583 Srgap3 chr6 112667965 112897260 - 0.60005 1.18297 1.97 0.98 0.00037199 0.01259430 Cdca5 chr19 6085096 6091773 + 2.10789 4.15084 1.97 0.98 0.00180712 0.04655700 Entpd1 chr19 40734283 40816092 + 1.05293 2.06907 1.97 0.97 0.00122092 0.03403530 Cdc45 chr16 18780539 18812065 - 3.09324 6.06859 1.96 0.97 0.00000208 0.00014201 Arhgap19 chr19 41841077 41876574 - 2.17622 4.23576 1.95 0.96 0.00000041 0.00003485 Cks2 chr13 51740600 51746031 + 14.12 27.4277 1.94 0.96 0.00000780 0.00045588 Crmp1 chr5 37633318 37683372 + 1.62181 3.09697 1.91 0.93 0.00153717 0.04145400 Uhrf1 chr17 56442759 56462909 + 9.29759 17.7164 1.91 0.93 0.00000000 0.00000000 Brca1 chr11 101350077 101413269 - 1.40099 2.65674 1.90 0.92 0.00001368 0.00075089 4831426I19Rik chr12 106168158 106248019 - 2.64142 4.92224 1.86 0.90 0.00000000 0.00000000 H1f0 chr15 78858641 78860930 + 4.3283 8.06391 1.86 0.90 0.00002257 0.00116235 Ect2 chr3 26996143 27052800 - 2.42737 4.5111 1.86 0.89 0.00002301 0.00117802 Atf6 chr1 172634587 172797902 - 2.37649 4.40022 1.85 0.89 0.00000012 0.00001192 Cd163l1 chr7 147404165 147417044 + 4.00421 7.4021 1.85 0.89 0.00000141 0.00010486 E2f2 chr4 135728308 135751971 + 5.72824 10.5597 1.84 0.88 0.00000000 0.00000011 Xbp1 chr11 5420969 5425875 + 30.8021 56.5616 1.84 0.88 0.00000000 0.00000000 Bard1 chr1 71074108 71149546 - 1.41152 2.58686 1.83 0.87 0.00033142 0.01139820 Fanca chr8 125778094 125842476 - 1.6008 2.92713 1.83 0.87 0.00068845 0.02143870 Cd19 chr7 133551961 133558384 - 2.20675 4.03446 1.83 0.87 0.00172691 0.04533350 Rap1gap2 chr11 74196984 74403660 - 2.13619 3.90103 1.83 0.87 0.00000206 0.00014201 Phactr2 chr10 12927522 13194202 - 0.578195 1.05319 1.82 0.87 0.00020793 0.00763452 Lgals1 chr15 78757154 78760895 + 88.2335 160.602 1.82 0.86 0.00000000 0.00000000 Mef2c chr13 83643032 83806684 + 0.945861 1.71624 1.81 0.86 0.00018634 0.00698178 Brip1 chr11 85871637 86014695 - 0.922578 1.6556 1.79 0.84 0.00122136 0.03403530 Napsa chr7 51827814 51842216 + 4.02957 7.21773 1.79 0.84 0.00180779 0.04655700 Kif22 chr7 134171244 134185934 - 5.18286 9.27267 1.79 0.84 0.00003418 0.00164366 Adap1 chr5 139747829 139801418 - 3.77593 6.74416 1.79 0.84 0.00015600 0.00603349 Whsc1 chr5 34185760 34240615 + 5.67108 10.0487 1.77 0.83 0.00000000 0.00000000 Ern1 chr11 106258933 106349110 - 2.40241 4.25088 1.77 0.82 0.00012809 0.00504383 Plekhg3 chr12 77634546 77680026 + 1.38855 2.44545 1.76 0.82 0.00098511 0.02870280 Sox4 chr13 29042598 29045551 - 2.39773 4.22111 1.76 0.82 0.00126332 0.03502480 Ctla4 chr1 60965868 60972674 + 3.72798 6.5031 1.74 0.80 0.00182725 0.04683610 Sacs chr14 61757293 61877327 + 2.65175 4.62114 1.74 0.80 0.00041735 0.01387070 Cdk6 chr5 3344311 3522225 + 5.37336 9.26834 1.72 0.79 0.00004492 0.00211337 Atp2b4 chr1 135599250 135650324 - 3.66743 6.30491 1.72 0.78 0.00000001 0.00000133 Cd22 chr7 31650422 31665361 - 2.80755 4.81353 1.71 0.78 0.00005674 0.00247578 Ahnak chr19 9063773 9151409 + 21.4129 36.5355 1.71 0.77 0.00000000 0.00000015 Brca2 chr5 151325197 151372324 + 1.12544 1.91959 1.71 0.77 0.00001445 0.00078515 Tcf19 chr17 35649679 35653769 - 7.42904 12.6426 1.70 0.77 0.00000002 0.00000200 Arhgap11a chr2 113671649 113688818 - 3.83351 6.51936 1.70 0.77 0.00000221 0.00015015 Ndc80 chr17 71845439 71876197 - 4.25671 7.14394 1.68 0.75 0.00058569 0.01855760 Atad5 chr11 79902901 79949293 + 2.14365 3.59338 1.68 0.75 0.00002309 0.00117802 Lig1 chr7 13844315 13896776 + 9.09169 15.2273 1.67 0.74 0.00000010 0.00000997 Klrk1 chr6 129560338 129573859 - 9.39238 15.7058 1.67 0.74 0.00000000 0.00000000 Ccr2 chr9 124016921 124023879 + 7.24538 12.0949 1.67 0.74 0.00000122 0.00009185 Capg chr6 72494432 72512974 + 14.0236 23.4011 1.67 0.74 0.00000000 0.00000026 Hivep3 chr4 119487282 119808016 + 1.7862 2.97576 1.67 0.74 0.00002139 0.00111229 Hmgb2 chr8 59990639 59994796 + 54.5936 90.5873 1.66 0.73 0.00000000 0.00000001 Tiam1 chr16 89787355 89974944 - 1.16879 1.9369 1.66 0.73 0.00024553 0.00883574 Cobll1 chr2 64926395 65076683 - 1.60688 2.66228 1.66 0.73 0.00017055 0.00650370 Creld2 chr15 88650075 88657111 + 15.9348 26.2727 1.65 0.72 0.00000342 0.00021736 Lmnb1 chr18 56867466 56913079 + 24.4836 40.0883 1.64 0.71 0.00000000 0.00000016 Fanci chr7 86537223 86611159 + 2.5329 4.1407 1.63 0.71 0.00081670 0.02445150 Cdca7 chr2 72314275 72324947 + 7.80172 12.6939 1.63 0.70 0.00003154 0.00154401 6720401G13Rik chrX 47908920 47988435 - 1.38212 2.23516 1.62 0.69 0.00078284 0.02363320 Irf4 chr13 30841126 30858796 + 5.97308 9.6531 1.62 0.69 0.00000264 0.00017259 Zbtb37 chr1 162947886 162964390 - 3.81843 6.16803 1.62 0.69 0.00018759 0.00698178 Gmnn chr13 24843713 24853806 - 9.51011 15.335 1.61 0.69 0.00188544 0.04787620 Pola1 chrX 90550104 90877494 - 4.01821 6.45418 1.61 0.68 0.00001571 0.00084117 Myb chr10 20844735 20880790 - 13.2903 21.1589 1.59 0.67 0.00000000 0.00000006 Myadm chr7 3289038 3299350 + 3.25881 5.18606 1.59 0.67 0.00076863 0.02333360 Rrm1 chr7 109590208 109618285 + 15.2627 24.2587 1.59 0.67 0.00000003 0.00000293 Hipk2 chr6 38647838 38826189 - 5.23015 8.29253 1.59 0.66 0.00000001 0.00000075 Adam8 chr7 147164839 147178387 - 3.84844 6.09521 1.58 0.66 0.00105255 0.03058130 Hells chr19 39005479 39042767 + 6.99198 11.0532 1.58 0.66 0.00004721 0.00216503 Polq chr16 37011871 37095503 + 1.25444 1.98233 1.58 0.66 0.00151824 0.04114780 Tyms chr5 30384739 30400165 - 3.1149 4.89681 1.57 0.65 0.00081078 0.02434140 Cd74 chr18 60963502 60972306 + 133.393 208.576 1.56 0.64 0.00000000 0.00000000 Acpp chr9 104190569 104240052 - 9.28211 14.4775 1.56 0.64 0.00000041 0.00003519 Il18rap chr1 40572206 40606142 + 9.11682 14.1314 1.55 0.63 0.00004965 0.00223907 Ncapd2 chr6 125118024 125141604 - 14.6183 22.6444 1.55 0.63 0.00000009 0.00000934 Runx2 chr17 44740949 45256233 - 3.84366 5.93377 1.54 0.63 0.00000011 0.00001089 Wdfy4 chr14 33772732 33998252 - 2.72125 4.1981 1.54 0.63 0.00004601 0.00214605 Vasn chr16 4626883 4679720 + 4.13954 6.38128 1.54 0.62 0.00151764 0.04114780 Incenp chr19 9946786 9974023 - 11.2596 17.3559 1.54 0.62 0.00000249 0.00016632 Foxred2 chr15 77770951 77787152 - 2.40696 3.70705 1.54 0.62 0.00050835 0.01634540 Sytl3 chr17 6877959 6942393 + 23.0712 35.4076 1.53 0.62 0.00000001 0.00000115 Slamf7 chr1 173562533 173583168 - 6.86265 10.4929 1.53 0.61 0.00004703 0.00216503 Rnf216 chr5 143752571 143874699 - 2.46932 3.75269 1.52 0.60 0.00025694 0.00915531 Cenpa chr5 30969274 30977199 + 12.0859 18.325 1.52 0.60 0.00114981 0.03237330 2900026A02Rik chr5 113515342 113592333 - 2.40854 3.65179 1.52 0.60 0.00173796 0.04533450 Trnp1 chr4 133047014 133054465 - 17.711 26.7919 1.51 0.60 0.00004589 0.00214605 Myo5a chr9 74919012 75071494 + 2.55498 3.84414 1.50 0.59 0.00005083 0.00227340 Pou2af1 chr9 51021794 51048184 + 13.6466 20.4399 1.50 0.58 0.00004689 0.00216503 Kpna2 chr11 106849942 106860839 - 29.6233 44.1981 1.49 0.58 0.00000196 0.00013737 Ezh2 chr6 47480272 47545029 - 12.643 18.8025 1.49 0.57 0.00000021 0.00002003 Ldlr chr9 21528019 21554362 + 4.33751 6.40559 1.48 0.56 0.00082524 0.02457180 Gsg2 chr11 72904096 72960951 - 12.0689 17.6611 1.46 0.55 0.00006910 0.00292197 Pole chr5 110715337 110766472 + 3.36875 4.91221 1.46 0.54 0.00044688 0.01467290 Itgb1 chr8 131209553 131257479 + 57.0935 83.0261 1.45 0.54 0.00000335 0.00021389 H2-Ab1 chr17 34400171 34406363 + 42.8204 62.2222 1.45 0.54 0.00003083 0.00151591 Rrbp1 chr2 143773130 143836999 - 14.4862 20.9126 1.44 0.53 0.00000145 0.00010668 Csda chr6 131314875 131338468 - 19.8615 28.5526 1.44 0.52 0.00000818 0.00047062 Mast2 chr4 115979366 116136788 - 4.05846 5.83044 1.44 0.52 0.00000279 0.00018154 Fut8 chr12 78339090 78576983 + 14.0025 20.0812 1.43 0.52 0.00000001 0.00000129 Fam129a chr1 153418502 153566477 + 5.40175 7.73657 1.43 0.52 0.00153312 0.04144770 Baz2b chr2 59737419 59963797 - 4.61737 6.59916 1.43 0.52 0.00012906 0.00506378 Ccdc50 chr16 27389062 27452304 + 9.30244 13.1895 1.42 0.50 0.00000000 0.00000006 Hsp90b1 chr10 86153585 86168189 - 150.36 213.057 1.42 0.50 0.00006423 0.00276986 Smc2 chr4 52452120 52501131 + 10.2508 14.5015 1.41 0.50 0.00004820 0.00220122 Txndc5 chr13 38592143 38620329 - 34.9961 49.4377 1.41 0.50 0.00001407 0.00076826 D730040F13Rik chr4 56888884 56960301 - 7.16397 10.1014 1.41 0.50 0.00018216 0.00685019 Cd79b chr11 106172654 106175843 - 25.0797 35.261 1.41 0.49 0.00088494 0.02620580 Ciita chr16 10480164 10527657 + 1.91288 2.68124 1.40 0.49 0.00079698 0.02399320 Wdhd1 chr14 47860618 47896532 - 6.86155 9.608 1.40 0.49 0.00092084 0.02712120 Kif20b chr19 34996847 35050221 + 4.33713 6.06925 1.40 0.48 0.00157403 0.04203080 Gm4759 chr7 113565063 113584587 - 26.1986 36.6582 1.40 0.48 0.00005519 0.00242820 Fyco1 chr9 123698627 123761020 - 14.0992 19.6075 1.39 0.48 0.00000457 0.00027765 Acot7 chr4 151552208 151645964 + 11.6288 16.046 1.38 0.46 0.00032042 0.01109030 Pde1b chr15 103333728 103360483 + 12.1583 16.7639 1.38 0.46 0.00063375 0.01979200 Rad18 chr6 112569844 112646664 - 6.82619 9.37527 1.37 0.46 0.00070661 0.02181660 Dut chr2 125072983 125084785 + 14.8046 20.2988 1.37 0.46 0.00000123 0.00009185 Cd44 chr2 102651299 102741822 - 13.4436 18.3418 1.36 0.45 0.00019793 0.00729172 8-Sep chr11 53333237 53357598 + 2.89686 3.94822 1.36 0.45 0.00082336 0.02457180 Trip11 chr12 103075581 103151381 - 11.4334 15.5292 1.36 0.44 0.00015773 0.00607858 Fkbp5 chr17 28536039 28623057 - 35.3406 47.9891 1.36 0.44 0.00003982 0.00188998 Hip1r chr5 124423636 124453224 + 12.2865 16.6755 1.36 0.44 0.00032468 0.01120190 Mcm3 chr1 20793094 20810294 - 28.831 39.0812 1.36 0.44 0.00013264 0.00518521 Carns1 chr19 4164323 4175479 - 9.51385 12.8175 1.35 0.43 0.00155901 0.04193900 H2-Aa chr17 34419695 34424716 - 69.1243 92.6845 1.34 0.42 0.00062689 0.01969070 Itga4 chr2 79095582 79269145 + 69.6957 93.0326 1.33 0.42 0.00186519 0.04754700 Nfic chr10 80858935 80889918 - 6.28514 8.34668 1.33 0.41 0.00022708 0.00825371 Ctla2a chr13 61035515 61037986 - 19.4388 25.7897 1.33 0.41 0.00186734 0.04754700 Tfdp1 chr8 13339673 13377702 + 26.1637 34.6429 1.32 0.40 0.00178075 0.04607890 Tpi1 chr6 124758958 124764314 - 33.5171 44.3095 1.32 0.40 0.00117720 0.03305890 Lman1 chr18 66140392 66162289 - 11.5044 15.1765 1.32 0.40 0.00106753 0.03058130 Golgb1 chr16 36880604 36933171 + 9.32996 12.2956 1.32 0.40 0.00034964 0.01194940 Zmiz1 chr14 26278670 26486233 + 15.6506 20.6182 1.32 0.40 0.00045139 0.01473420 Ptprs chr17 56551848 56615903 - 4.96865 6.52787 1.31 0.39 0.00011521 0.00462012 Cbl chr9 43957344 44042129 - 39.9394 52.2603 1.31 0.39 0.00073526 0.02257280 Cbx5 chr15 103021976 103070247 - 14.7657 19.3207 1.31 0.39 0.00000348 0.00021840 Dbf4 chr5 8396968 8422716 - 12.0023 15.6779 1.31 0.39 0.00163405 0.04342020 Mcm5 chr8 77633426 77652338 + 23.2788 30.2891 1.30 0.38 0.00114047 0.03219380 Atxn1 chr13 45645124 46060360 - 3.94749 5.1252 1.30 0.38 0.00016861 0.00645240 Il18r1 chr1 40522396 40557699 + 37.4566 48.5128 1.30 0.37 0.00004669 0.00216503 Zbed6 chr1 135516447 135557957 - 17.486 22.6069 1.29 0.37 0.00143603 0.03951070 Tulp4 chr17 6106829 6240637 + 10.2739 13.2729 1.29 0.37 0.00000025 0.00002270 Camk4 chr18 33098694 33355421 + 10.4971 13.5417 1.29 0.37 0.00105963 0.03058130 Xrn1 chr9 95855178 95953448 + 16.2551 20.9434 1.29 0.37 0.00174317 0.04533450 Lpp chr16 24392641 24992664 + 3.78445 4.87051 1.29 0.36 0.00001766 0.00094090 Ankrd52 chr10 127814179 127831062 + 20.0574 25.7447 1.28 0.36 0.00120502 0.03375300 Cdc25b chr2 131012683 131024247 + 22.6742 29.0484 1.28 0.36 0.00000068 0.00005594 Cep110 chr2 34965011 35034342 + 37.9508 48.5698 1.28 0.36 0.00000001 0.00000177 Macf1 chr4 123026875 123361603 - 105.597 135.028 1.28 0.35 0.00039509 0.01321180 Akap9 chr5 3928185 4080204 + 11.4165 14.5622 1.28 0.35 0.00170780 0.04495740 Tom1l2 chr11 60040215 60166407 - 7.69296 9.78044 1.27 0.35 0.00147895 0.04058910 Nfat5 chr8 109817369 109903417 + 12.2438 15.4018 1.26 0.33 0.00000000 0.00000000 Rcbtb2 chr14 73542316 73583861 + 15.1652 19.0279 1.25 0.33 0.00076015 0.02314110 Cep250 chr2 155782293 155824636 + 14.8938 18.6439 1.25 0.32 0.00000000 0.00000002 Pik3cg chr12 32858261 32893514 - 15.8886 19.6199 1.23 0.30 0.00148427 0.04063250 Zfp280c chrX 45894802 45947629 - 13.4061 16.4746 1.23 0.30 0.00000498 0.00029729 Taf1d chr9 15087780 15162232 + 46.1427 56.5385 1.23 0.29 0.00015584 0.00603349 Zfp192 chr13 21605089 21622983 - 6.4649 7.90692 1.22 0.29 0.00163944 0.04345720 Ggta1 chr2 35255698 35316945 - 10.76 13.0629 1.21 0.28 0.00174363 0.04533450 Nin chr12 71112421 71212912 - 25.8502 30.9919 1.20 0.26 0.00021967 0.00801144 Abl2 chr1 158488917 158579750 + 8.4283 10.0652 1.19 0.26 0.00000847 0.00047918 Pou2f1 chr1 167718811 167932765 - 8.21566 9.79866 1.19 0.25 0.00106669 0.03058130 Klc1 chr12 112997059 113052052 + 18.6516 22.2441 1.19 0.25 0.00023670 0.00857473 Eif4g3 chr4 137549370 137762994 + 35.7142 42.5093 1.19 0.25 0.00000113 0.00008565 Dido1 chr2 180392668 180444704 - 24.2705 28.8544 1.19 0.25 0.00018699 0.00698178 Atp2a2 chr5 122903521 122952234 - 36.9594 43.7518 1.18 0.24 0.00174024 0.04533450 Jmjd1c chr10 66590005 66719074 + 22.4002 26.4068 1.18 0.24 0.00013633 0.00531046 Pan2 chr10 127740390 127758414 + 19.9635 23.5339 1.18 0.24 0.00024839 0.00890907 Smc5 chr19 23280930 23348387 - 11.7024 13.7503 1.17 0.23 0.00106464 0.03058130 Tnk2 chr16 32644728 32683579 + 21.7727 25.5133 1.17 0.23 0.00005695 0.00247578 Orc3 chr4 34497863 34562191 - 13.0445 15.2701 1.17 0.23 0.00030343 0.01053590 Kdm2b chr5 123320684 123439101 - 11.4803 13.4098 1.17 0.22 0.00110220 0.03119660 Cdk12 chr11 98064618 98114854 + 18.0938 21.0531 1.16 0.22 0.00000036 0.00003187 Ino80d chr1 63094374 63160841 - 13.5591 15.7223 1.16 0.21 0.00000169 0.00012137 Rbm3 chrX 7716100 7725089 - 370.863 429.848 1.16 0.21 0.00003437 0.00164558 4833420G17Rik chr13 120251565 120274924 + 39.6979 45.9551 1.16 0.21 0.00058757 0.01856320 Ubr5 chr15 37897082 38008608 - 30.9643 35.8405 1.16 0.21 0.00000034 0.00003045 Vps39 chr2 120142196 120178869 - 18.166 21.016 1.16 0.21 0.00045705 0.01487200 Tnpo1 chr13 99612035 99696339 - 41.7803 48.1939 1.15 0.21 0.00009579 0.00394324 Atp2a3 chr11 72774670 72806545 + 104.754 120.516 1.15 0.20 0.00000000 0.00000000 Ubr2 chr17 47065239 47147481 - 30.1701 34.6052 1.15 0.20 0.00005220 0.00232517 Phc3 chr3 30798216 30868337 - 21.7167 24.8817 1.15 0.20 0.00000598 0.00035318 Ncor1 chr11 62094974 62270834 - 62.2753 71.1717 1.14 0.19 0.00018160 0.00685019 Gabpb2 chr3 94985689 95021864 - 40.7483 46.4246 1.14 0.19 0.00000004 0.00000434 Atp13a3 chr16 30312509 30388616 - 39.1522 44.5292 1.14 0.19 0.00011220 0.00451609 Ciz1 chr2 32218529 32233833 + 25.2373 28.6863 1.14 0.18 0.00093336 0.02741540 Zfp207 chr11 80196780 80219375 + 90.2623 102.492 1.14 0.18 0.00043377 0.01432700 Tnrc6b chr15 80541742 80771516 + 21.5355 24.4231 1.13 0.18 0.00000104 0.00008091 Ncor2 chr5 125497522 125659584 - 20.2265 22.9126 1.13 0.18 0.00000014 0.00001383 Smarca4 chr9 21420612 21508674 + 31.9715 36.1845 1.13 0.18 0.00000000 0.00000000 Mink1 chr11 70376382 70427984 + 30.4138 34.3947 1.13 0.18 0.00008949 0.00369818 Tacc1 chr8 26265023 26311921 - 31.8701 35.9245 1.13 0.17 0.00009643 0.00395471 Trpm7 chr2 126617293 126701997 - 31.5063 35.5133 1.13 0.17 0.00039826 0.01327700 Ubp1 chr9 113840051 113935869 + 40.4668 45.5576 1.13 0.17 0.00110227 0.03119660 Myo9b chr8 73796612 73884611 + 39.2481 44.0691 1.12 0.17 0.00000489 0.00029343 Plekhg2 chr7 29144622 29157681 - 32.582 36.4095 1.12 0.16 0.00138760 0.03827510 Aak1 chr6 86799510 86953221 + 19.9326 22.2722 1.12 0.16 0.00000322 0.00020720 Prrc2b chr2 32006667 32090057 + 56.8607 63.1622 1.11 0.15 0.00012421 0.00492669 Tcof1 chr18 60973409 61008618 - 41.9952 46.631 1.11 0.15 0.00026827 0.00943528 Erbb2ip chr13 104608865 104710594 - 50.8063 56.151 1.11 0.14 0.00001543 0.00083016 Srsf11 chr3 157673456 157699603 - 67.4155 74.3196 1.10 0.14 0.00000012 0.00001233 Nolc1 chr19 46150352 46160020 + 31.1797 34.342 1.10 0.14 0.00026510 0.00935410 Txnip chr3 96359690 96370724 + 284.427 313.223 1.10 0.14 0.00000530 0.00031452 Cic chr7 26067197 26079167 + 40.7874 44.8905 1.10 0.14 0.00021079 0.00771320 Bclaf1 chr10 20032274 20062307 + 49.6633 54.5939 1.10 0.14 0.00000000 0.00000042 Srrt chr5 137736931 137748902 - 64.819 71.2328 1.10 0.14 0.00157034 0.04203080 Tcf12 chr9 71692058 71959626 - 43.3825 47.4063 1.09 0.13 0.00002229 0.00115379 Otud4 chr8 82163574 82201654 + 36.679 39.9081 1.09 0.12 0.00186810 0.04754700 Sbf1 chr15 89118666 89145742 - 70.0973 75.8389 1.08 0.11 0.00046673 0.01514170 Slc38a1 chr15 96401848 96473344 - 41.9327 45.3183 1.08 0.11 0.00007494 0.00315663 Dnm2 chr9 21229351 21314630 + 92.1961 99.4405 1.08 0.11 0.00000000 0.00000038 Hnrnpc chr14 52693054 52723703 - 124.601 119.393 0.96 -0.06 0.00001126 0.00063107 Samhd1 chr2 156923264 156960958 - 149.531 139.212 0.93 -0.10 0.00043503 0.01432700 D16Ertd472e chr16 78540580 78576933 - 27.8968 25.9676 0.93 -0.10 0.00038724 0.01298940 Gtf2i chr5 134713703 134790616 - 99.3811 91.0876 0.92 -0.13 0.00028977 0.01009360 Foxp1 chr6 98875335 99385339 - 48.5973 44.2328 0.91 -0.14 0.00000000 0.00000000 Tapbp chr17 34056422 34066235 + 169.977 153.997 0.91 -0.14 0.00048020 0.01553230 Ube2h chr6 30161288 30254539 - 64.1776 57.4049 0.89 -0.16 0.00181421 0.04661180 Irf9 chr14 56222821 56228867 + 64.1128 55.6208 0.87 -0.20 0.00090237 0.02664940 Rnf138 chr18 21159841 21186724 + 30.5337 25.4267 0.83 -0.26 0.00050736 0.01634540 Ifi27l1 chr12 104672398 104678455 + 95.6508 78.2059 0.82 -0.29 0.00002676 0.00133404 Ccr9 chr9 123676328 123692575 + 44.8095 36.0769 0.81 -0.31 0.00001362 0.00075089 Tgtp2 chr11 48851161 48948889 - 72.048 56.9009 0.79 -0.34 0.00005287 0.00234549 Slfn5 chr11 82724754 82778352 + 26.7938 20.3914 0.76 -0.39 0.00054802 0.01751720 Ifi27l2a chr12 104680376 104681890 - 150.988 110.682 0.73 -0.45 0.00097649 0.02852830 Art2b chr7 108727373 108729675 - 86.0613 63.0358 0.73 -0.45 0.00070434 0.02180840 Gm14446 chr19 34667377 34676458 - 78.9068 57.4356 0.73 -0.46 0.00000000 0.00000000 Irf7 chr7 148449081 148452323 - 72.6063 51.2472 0.71 -0.50 0.00000000 0.00000000 Isg15 chr4 155573532 155574927 - 36.0247 23.7927 0.66 -0.60 0.00137894 0.03813300 Rtp4 chr16 23610004 23614308 + 40.2341 24.8563 0.62 -0.69 0.00000075 0.00006093 Oas2 chr5 121180341 121199857 - 13.1092 8.04455 0.61 -0.70 0.00000316 0.00020461 Gbp10 chr5 105644717 105668552 - 6.38986 3.8756 0.61 -0.72 0.00058109 0.01851980 Ifit3 chr19 34658018 34663472 + 21.956 13.096 0.60 -0.75 0.00000225 0.00015208 Lars2 chr9 123276057 123371782 + 371.428 213.705 0.58 -0.80 0.00000003 0.00000388 Oasl2 chr5 115346942 115362254 + 9.59107 5.50266 0.57 -0.80 0.00001919 0.00100271 Ifit1 chr19 34715378 34724499 + 22.3374 12.4361 0.56 -0.84 0.00000001 0.00000131 Klra13-ps chr6 129922099 130336892 - 4.50487 0 0.00 0.00000145 0.00010668 SUPPLEMENTAL TABLE I. Differential gene expression is observed in CD8+ T cells from naïve mice developmentally exposed to Veh or TCDD, and from infected mice developmentally exposed to Veh or TCDD. Genes with differential expression at

FDR<5% are shown.