DOI: 10.5061/dryad.ffbg79d30
title: Data for: Developmental origins of Parkinson’s disease risk: perinatal exposure to the organochlorine pesticide dieldrin leads to sex-specific DNA modifications in critical neurodevelopmental pathways in the mouse midbrain

description: Epidemiological studies show that exposure to the organochlorine pesticide
 dieldrin is associated with increased risk of Parkinson’s disease (PD).
 Animal studies support a link between developmental dieldrin exposure and
 increased neuronal susceptibility in the α-synuclein preformed fibril
 (α-syn PFF) and MPTP models in adult male C57BL/6 mice. In a previous
 study, we showed that developmental dieldrin exposure was associated with
 sex-specific changes in DNA modifications within genes related to
 dopaminergic neuron development and maintenance at 12 weeks of age. Here,
 we used capture hybridization-sequencing with custom baits to interrogate
 DNA modifications across the entire genetic loci of the previously
 identified genes at multiple time points – birth, 6 weeks, 12 weeks, and
 36 weeks old. We identified largely sex-specific dieldrin-induced changes
 in DNA modifications at each time point that annotated to pathways
 important for neurodevelopment, potentially related to critical steps in
 early neurodevelopment, dopaminergic neuron differentiation,
 synaptogenesis, synaptic plasticity, and glial-neuron interactions.
 Despite large numbers of age-specific DNA modifications, longitudinal
 analysis identified a small number of DMCs with dieldrin-induced
 deflection of epigenetic aging. The sex-specificity of these results adds
 to evidence that sex-specific responses to PD-related exposures may
 underly sex-specific differences in disease. Overall, these data support
 the idea that developmental dieldrin exposure leads to changes in
 epigenetic patterns that persist after the exposure period and disrupt
 critical neurodevelopmental pathways, thereby impacting risk of late life
 diseases, including PD.  
description: <em>Animals</em>:<strong> </strong>Adult
 female and male C57BL/6 mice (RRID:MGI:2159769) were purchased from
 Jackson Laboratory (Bar Harbor, Maine). Seven-week-old female mice were
 allowed to habituate after arrival for 1 week prior to beginning the
 developmental dieldrin exposure. Male mice were 11 weeks old upon arrival
 and were also allowed 1 week to habituate prior to mating. Mice were
 maintained on a 12-hour:12-hour reverse light/dark cycle. Mice were housed
 in Thoren ventilated caging systems with automatic water and 1/8-inch
 Bed-O-Cobs bedding with Enviro-Dri for enrichment. Food and water were
 available <em>ad libitum</em>. Mice were maintained on Teklad
 8940 rodent diet (Envigo). After arrival, females were separated and
 individually housed during dieldrin dosing, except during the mating
 phase. After birth, F1 pups were group-housed by sex, with no more than 5
 animals housed in each cage. No singly housed F1 animals were used in this
 study; as animals aged, all cages included a “buddy” littermate to ensure
 that even animals used for the last time point were never individually
 housed. All procedures were conducted in accordance with the National
 Institutes of Health Guide for Care and Use of Laboratory Animals and
 approved by the Institutional Animal Care and Use Committee at Michigan
 State University. <em>Developmental dieldrin
 exposure: </em>Dieldrin exposure was carried out as previously
 described and is summarized in Figure 1 (Richardson<em> et
 al.</em>, 2006,Gezer<em> et al.</em>,
 2020,Kochmanski<em> et al.</em>, 2019,Boyd<em> et
 al.</em>, 2023). Adult (8-week-old) C57Bl/6 female mice (n=20 per
 group) were treated throughout breeding, gestation, and lactation.
 Following 3 days of habituation to peanut butter feeding, mice were
 administered 0.3 mg/kg dieldrin (ChemService) dissolved in corn oil
 vehicle and mixed with peanut butter pellets every 3 days
 (Richardson<em> et al.</em>, 2006,Gezer<em> et
 al.</em>, 2020,Kochmanski<em> et al.</em>,
 2019,Boyd<em> et al.</em>, 2023). Control mice received an
 equivalent amount of corn oil vehicle mixed in peanut butter. Mice were
 exposed via oral ingestion by the dam because the most likely route of
 exposure to dieldrin in humans is through ingestion of contaminated foods
 and ingestion of the resulting contaminated breast milk (ATSDR,
 2022). The dieldrin dose was based on previous results
 showing low toxicity, but clear effects on the epigenome and neuronal
 susceptibility to neurotoxic insults (Richardson<em> et
 al.</em>, 2006,Gezer<em> et al.</em>,
 2020,Kochmanski<em> et al.</em>, 2019,Boyd<em> et
 al.</em>, 2023). In addition, because dieldrin is a persistent
 compound, even though this daily dose is likely higher than human doses,
 this dose was chosen to produce a similar body burden in animals compared
 to known levels in humans. There is a very wide range of values reported
 for both brain (~4 ppb – 1 ppm) and adipose (~50 ppb – 50 ppm) tissue
 levels (U.S. Environmental Protection Agency, 1994,Corrigan<em> et
 al.</em>, 2000,Agency for Toxic Substances and Disease Registry,
 2022,Fleming, L.<em> et al.</em>, 1994) Our measurements in
 this cohort in dam brain and adipose tissue are within the reported ranges
 of multiple studies (Table 1). In this study, we measured these as a
 quality control step on a subset of animals, but the range of levels
 between animals suggests that there are variable exposure levels in the
 pups and that measuring dieldrin in dam and pup tissue in future studies
 is warranted. After four weeks of exposure, unexposed
 C57BL/6 males (12 weeks old) were introduced for breeding for 48 hours
 such that male mice were not present for any peanut butter pellet
 feedings. To ensure adequate animal numbers for each sex at all four time
 points, this was carried out in two cohorts: one to generate animals for
 the birth time point, and one to generate animals for the 6-week, 12-week,
 and 36-week time points. For the birth cohort, pups were sacrificed at
 PND0, tissue was collected for sex determination by genotyping, and whole
 brains were dissected and frozen. For the remaining cohort, F1 pups were
 weaned and separated by litter and by sex at 3 weeks of age, with 2-5
 animals per cage. At each time point, male and female littermates from
 independent litters were selected. Animals were assigned to cages such
 that for each experimental group and sex, all animals were from
 independent litters and no animals were singly housed.
 Group sizes were determined based on the previously published
 RRBS data that this analysis was based  (Kochmanski<em> et
 al.</em>, 2019). Based on that data, we determined prior to starting
 the exposure cohorts that a sample size of at least 7 per sex per
 treatment group per time point was sufficient to detect &gt;80% of all
 true differences with an effect size &gt;1.4 (among the smallest
 effect-sizes from our previous data). Samples sizes of 8-10 are powered to
 detect &gt;95% of effects &gt;1.8 (the median effect-size from the
 previous data). At the PND0 timepoint, we only generated 5 female and 4
 male control pups and 7 dieldrin exposed pups for each sex from
 independent litters, limiting our statistical power at birth to 80% power
 to detect &gt;80% of effects &gt;1.8. We have reported this birth
 analysis for completeness, but it is important to acknowledge that the
 statistical power at birth was lower than for other time points for
 smaller effect sizes. Sample sizes are shown in Table 2.
 The 12-week time point was selected based on previous results
 demonstrating increased neuronal susceptibility to MPTP and α-synuclein
 pre-formed fibrils (PFFs) administered at 12 weeks of age
 (Richardson<em> et al.</em>, 2006,Gezer<em> et
 al.</em>, 2020). The 9-month time point is equivalent to the 6-month
 post-PFF injection time point where we observed dieldrin-induced
 exacerbation of PFF-induced deficits in motor behavior and DA handling
 (Gezer<em> et al.</em>, 2020). Birth and six weeks were
 selected to address the question of whether dieldrin-associated changes
 reflect a change in establishment or maintenance of epigenetic marks
 across time. <em>Sex determination genotyping at
 birth: </em>At the birth time point, sex determination was not
 possible by visual inspection and was determined using PCR for
 <em>Rmb31x/y </em>gametologs using an established primer pair
 (Tunster, 2017). DNA was isolated from tail clips taken from neonatal mice
 during sacrifice using the Kapa Express Extract Kit (Kapa Biosystems, Cat.
 #KK7100) with one minor modification – sample lysis was assisted via
 physical homogenization using a 1.5 mL tube plastic pestle. After lysis,
 samples were briefly centrifuged to pellet cellular debris, and the DNA
 extract was diluted 10-fold with 10 mM Tris-HCl (pH 8.0–8.5) to dilute
 cellular debris and digested proteins to prevent inhibition of downstream
 PCR. PCR was performed using 1 µL of input DNA as described
 (Richardson<em> et al.</em>, 2006,Gezer<em> et
 al.</em>, 2020,Kochmanski<em> et al.</em>,
 2019,Boyd<em> et al.</em>, 2023). PCR products were visualized
 on a 1.2% Agarose TBE gel with ethidium bromide. During visualization, two
 bands of DNA were produced for male samples, and a single band of DNA was
 produced for female samples, allowing for accurate determination of sex at
 birth. <em>Mass spectrometry</em>: Dieldrin
 levels were measured from frozen neonatal brain, dam brain and dam adipose
 tissue by the RTSF Mass Spectrometry and Metabolomics core at MSU using
 established methods (Hong<em> et al.</em>, 2004,US EPA,
 2014). <em>SN microdissections: </em>Frozen
 brains were mounted on a freezing cryostat (Leica, Model CM3050S) and
 sliced to the midbrain. Unilateral substantia nigra (SN) punches were
 collected using a chilled 1.0 mm micropunch and immediately placed in a
 frozen 1.5 mL tube on dry ice. <em>DNA isolation:
 </em>DNA was isolated from unilateral SN punches using Qiagen QIAamp
 DNA Micro Kits (Qiagen, Cat. #56304) according to the included protocols
 with the following minor modifications. First, prior to adding ATL buffer
 to SN punches, 80 µL PBS was added to each sample and a 1.5 mL tube pestle
 was used to break up the sample. After that, 100 µL ATL buffer was added
 to each homogenized sample, which were allowed to equilibrate to room
 temperature. Second, for the proteinase K digestion step, the 56°C
 incubation time was extended to overnight. Third, carrier RNA was added to
 Buffer AL (this is an optional step). Fourth, the incubation time after
 addition of 100% EtOH was increased to 10 minutes, and the incubation time
 for the elution step was increased to 5 minutes. Lastly, to increase
 yield, the elution step was repeated by reapplying elution buffer to
 QIAamp MinElute column. DNA was eluted in 54 µL of 10 mM Tris-HCl, pH 8.0.
 DNA yield and purity were determined using a Qubit 3 fluorometer
 (ThermoFisher) and a NanoDrop spectrophotometer (ThermoFisher). Isolated
 DNA was stored at -80°C prior to sequencing.
 <em>Selection of candidate regions</em>: To select
 candidate regions, we targeted all intragenic genomic features and known
 enhancers at genes annotated to DMCs or DMRs in our previous study
 (Kochmanski<em> et al.</em>, 2019). Targeted regions include
 255 male-specific annotations and 1043 female-specific annotations and
 represent a total of ~11.4 Mb of genomic space (Supplementary File 1). We
 included regions identified for both male- and female-specific changes to
 determine if these are truly sex-specific. Intergenic regions annotated to
 our candidate genes account for 151 Mb of genomic space, making inclusion
 cost-prohibitive with the SeqCapEpi platform. In addition, these
 intergenic regions remain largely unexplored, making data generated from
 these regions of limited interpretability. SeqCapEpi custom bait probes
 for regions of interest were designed using the Roche NimbleDesign
 software (Supplementary File 2). Baits covered 91.6% of target bases for a
 total capture space of ~10.4 Mb. <em>Capture
 hybridization sequencing: </em>Capture hybridization-sequencing
 libraries were prepared by the Van Andel Genomics Core from 100 ng of high
 molecular weight DNA using the Accel-NGS Methyl-Seq DNA Library kit (v3.0)
 (Swift Biosciences, Cat. #30024). DNA was sheared following manufacturer’s
 protocol to an average size of 250bp, and sheared DNA was bisulfite
 converted using the EZ DNA Methylation-Gold kit (Zymo Research, Cat.
 #D5005) with an elution volume of 15 µL. Following adapter ligation, 8
 cycles of library amplification were performed. Amplified libraries were
 pooled in batches of 8 and targeted enrichment of a custom 11Mb region was
 performed using Roche SeqCapEpi developer probes and SeqCapHyperEpi
 workflow starting at step 4.0 with the following modification: the capture
 was performed using IDT xGen Universal blockers to replace the SeqCap HE
 Universal Oligo and SeqCap HE Index Oligo. The post-capture amplification
 was also adjusted to 11 cycles of amplification and the final extension
 changed from 30 seconds to 1 minute. Quality and quantity of the finished
 library pools were assessed using a combination of Agilent DNA High
 Sensitivity chip (Agilent Technologies, Inc.) and QuantiFluor® dsDNA
 System (Promega Corp.). Sequencing (100 bp, paired end) was performed on
 an Illumina NovaSeq6000 sequencer using an S4, 200 bp sequencing kit
 (Illumina Inc.) with 10% PhiX included to improve base diversity.  Base
 calling was done by Illumina Real Time Analysis 3 and output of NextSeq
 Control Software was demultiplexed and converted to FastQ format with the
 Illumina <em>Bcl2fastq</em> software (version
 1.9.0). <em>Data processing: </em>FastQ
 files were processed using a slightly modified form of the bioinformatics
 pipeline previously established by our group to analyze reduced
 representation bisulfite sequencing (RRBS) data (Richardson<em> et
 al.</em>, 2006,Gezer<em> et al.</em>,
 2020,Kochmanski<em> et al.</em>, 2019,Boyd<em> et
 al.</em>, 2023). Command line tools and the open-source statistical
 software R (version 4.1.2) were used for all analyses. For all sequencing
 data, the <em>FastQC</em> tool (version 0.11.7) was used for
 data quality control, and the <em>trim_galore </em>tool
 (version 0.4.5) was used for adapter trimming (Andrews, 2016,Krueger,
 2017). During adapter trimming, we used the default minimum quality score
 and added a stringency value of 6, thereby requiring a minimum overlap of
 6 bp. Trimmed CapHyb-seq reads were aligned to the <em>mm10
 </em>reference genome using<em> bismark </em>(version
 0.19.1) (Krueger and Andrews, 2011). Methylation data were extracted from
 the aligned reads in <em>bismark</em> using a minimum
 threshold of 5 reads to include a CpG site in analysis.
 <em>Verification of sequencing coverage</em>: To
 determine the sequencing coverage across the targeted regions, we used
 BedTools Basic Protocol 3 for measuring coverage in targeted DNA
 sequencing experiments as described (Quinlan, 2014). BAM files for each
 sample obtained from <em>bismark </em>were compared with
 targeted bases (Supplementary File 2) using the
 <em>coverage</em> and <em>multicov </em>functions
 from <em>bedtools</em> (version 2.31.0) to determine the
 fraction of target bases that were captured and their sequencing depths
 (Quinlan and Hall, 2010). In differential modification analysis, only
 sites with coverage ≥ 5 in all samples were included in analysis. Of 6604
 target regions, 1359 remained (21%), for ~2.8 Mb of captured
 sequence. <em>Differential modification analysis:
 </em>The <em>DSS</em> (version 2.48.0) and
 <em>DMRcate </em>(version 2.14.1) R packages were used to test
 CapHyb-seq data for differential methylation (Feng<em> et
 al.</em>, 2014,Peters<em> et al.</em>, 2015). Given that
 dieldrin exposure has shown sex-specific effects on the dopaminergic
 system, all differential modification models were stratified by sex
 (Kochmanski<em> et al.</em>, 2019,Boyd<em> et
 al.</em>, 2023,Richardson<em> et al.</em>, 2006). All
 pups included in modeling were from independent litters. Of note, we refer
 to DNA modifications, rather than DNA methylation, since our BS-based
 method does not differentiate between DNA methylation and
 hydroxymethylation. While DNA hydroxymethylation plays a critical role in
 gene expression in the brain and is particularly sensitive to
 environmental factors, methods for differentiating these marks remain
 limited and cost-prohibitive, especially across multiple time points
 (Kochmanski and Bernstein, 2020).  
 <em>Cross-sectional differential DNA modification analysis:
 </em>To test for differentially modified cytosines (DMCs) by
 dieldrin exposure at each cross-sectional timepoint, we used the
 <em>DMLtest </em>function in <em>DSS</em> to
 perform two-group Wald tests. For DMLtest modeling, the equal dispersion
 parameter was set to <em>FALSE</em> and smoothing was set to
 <em>TRUE</em>. DMCs were considered significant at false
 discovery rate (FDR) &lt;0.05. To test for differentially modified
 regions (DMRs) at each timepoint, we combined outputs from the
 <em>callDMR</em> function in DSS and the
 <em>dmrcate</em> function in DMRcate. For
 <em>callDMR</em> modeling, the p-value threshold was set to
 0.05, minimum length was set to 50 base pairs, and minimum CpGs was set to
 3. Meanwhile, for <em>dmrcate</em> modeling, the lambda value
 was set to 500, the C value was set to 4, and minimum CpGs was set to 3.
 DMR significance for the <em>dmrcate</em> output was set to a
 minimum smoothed FDR &lt; 0.05.
 <em>Longitudinal differential DNA modification analysis:
 </em>To test for DMCs by age, as well as simultaneous age and
 exposure in a multivariate model, we used the <em>DMLfit.multiFactor
 </em>function in <em>DSS</em> to perform linear models
 using a general experimental design. Given that age was an ordered
 variable, we coded each age group as a number for modeling – 6 weeks old =
 1, 12 weeks old = 2, and 36 weeks old = 3. The birth timepoint was not
 included in longitudinal models because the F1 offspring came from a
 separate cohort of exposed animals, meaning they were not matched
 littermates like the later three time points. In the model for age only,
 coded age was included as the only independent variable. Meanwhile, in the
 multivariate model, exposure was included as a two-group categorical
 variable (“dieldrin”, “control”), and age:exposure was included as an
 interaction term. For the age alone and age:exposure models, DMCs were
 considered significant at false discovery rate (FDR)
 &lt;0.05. <em>Genomic annotation:
 </em>After differential methylation testing, the<em>
 annotatr</em> R package (version 1.26.0) was used to annotate
 identified DMCs and DMRs to the reference <em>mm10</em> genome
 (Cavalcante and Sartor, 2017). Within <em>annotatr</em>, the
 <em>annotate_regions</em> function was used to generate CpG
 context, gene body, and regulatory feature annotations. Annotations for
 miRNA (miRbase), ENCODE predicted mouse midbrain enhancers (Accession:
 ENCSR114ZIJ), and custom full stack ChromHMM chromatin states for
 <em>mm10</em> databases were added to the annotation cache in
 <em>annotatr </em><em>(Vu and Ernst, 2023,Kozomara et
 al., 2019,Luo et al., 2020,Kundaje et al., 2012)</em>.
 <em>Data visualization: </em>Raw CapHyb-seq beta
 values were extracted using the <em>bsseq </em>R package
 (1.36.0). Volcano plots were generated using the<em> ggplot2
 </em>R package (version 3.4.4). Euler diagrams were generated with
 the <em>eulerr </em>R package (version 7.0.1) (Larsson, 2024).
 UpSet plots were generated using the <em>UpSetR</em> package
 (version 1.4.0) (Conway<em> et al.</em>, 2017). The
 <em>ComplexHeatmap</em> R package (version 2.18.0) was used to
 visualize beta value differences over time for all DMCs significant at one
 or more of the four time points. Specific genes of interest were
 visualized using the WASHU Epigenome Browser to determine genomic location
 and context of differentially modified (DM) regions; chromHMM annotations
 were loaded to compare DM loci with chromatin state annotations
 (Conway<em> et al.</em>, 2017,Li<em> et al.</em>,
 2022). The R packages <em>ggplot2</em>,
 <em>ggpubr</em> (version 0.6.0), and
 <em>ggeasy</em> (version 0.1.4) were used to generate violin
 plots to display raw beta values for premature aging DMCs
 (Carroll<em> et al.</em>, 2023,Kassambara, 2023).  
 <em>Pathway and Network Analysis: </em>Gene ontology
 (GO) term enrichment testing and pathway analysis was performed on genes
 annotated to male and female DMCs and DMRs using the ClueGO application in
 Cytoscape (version 3.10.1) (Bindea<em> et al.</em>,
 2009,Smoot<em> et al.</em>, 2011). For
 <em>ClueGO </em>testing, genes annotated to DMCs and DMRs
 stratified by sex and timepoint were input as separate gene lists,
 “groups” was selected as the visual style, and the GO- biological process
 (GOBP) term was included for enrichment testing. Network specificity was
 set to “Medium”, such that the GO Tree Interval minimum was equal to 3 and
 the maximum was equal to 8. Only terms with at least 3 genes and a
 Bonferroni-corrected p-value &lt; 0.05 were included in pathway
 visualizations. The connectivity score (Kappa) was set at 0.4, and default
 GO Term Grouping settings were used in all analyses. The genes found in
 enriched GOBP terms by <em>ClueGO</em> were used for STRING
 network analysis and to create UpSet plots for each sex displaying the
 overlap at different time points. Protein-protein
 interaction network analysis was performed using STRING (version 12.0)
 with the genes found in enriched GOBP terms by ClueGO as input
 (Szklarczyk<em> et al.</em>, 2017,Szklarczyk<em> et
 al.</em>, 2015). STRING network analysis was performed using default
 parameters, including a minimum required interaction score = 0.4 and all
 interaction sources activated.
description: # Data for: Developmental origins of Parkinson’s disease risk: perinatal
 exposure to the organochlorine pesticide dieldrin leads to sex-specific
 DNA modifications in critical neurodevelopmental pathways in the mouse
 midbrain
 [https://doi.org/10.5061/dryad.ffbg79d30](https://doi.org/10.5061/dryad.ffbg79d30) This dataset contains all code and output from the differential methylation analysis, as well as raw data and supporting analysis files for mass spectrometry. ## Description of the data and file structure **Supplementary Files** * Supplementary_File_1_primary_targets.bed: This bed file contains targeted regions and has the following columns: chromosome number, start coordinate, end coordinate, gene name. - Supplementary_File_2_capture_targets.bed: This bed file contains designed baits and has the following columns: chromosome number, start coordinate, end coordinate, gene name. - Supplementary_File_3\_ Consolidated_DMCs.csv: This csv file contains the merged results of the cross-sectional differential modification analysis for each sex and timepoint using the *DMLtest* function from the *DSS* R package, generated by Supplementary_File_13_CapHybSeq_DSS_DiffMeth_Exposure_Cross-sectional.Rmd. This file contains all standard output columns defined in the package documentation. Columns for sex and age were added to indicate which analysis each item came from, and a column for direction was added to indicate the direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin).  The columns are defined as follows: | Name | Value | | :-------- | :--------------------------------------------------------------------------------------------------------------------------------------------- | | chr | Chromosome number | | start | Start coordinate | | end | End coordinate | | mu1 | Methylation mean of group 1 | | mu2 | Methylation mean of group 2 | | diff | Difference of mean methylations of two groups (diff=mu1-mu2) | | diff.se | Standard error of the methylation difference | | stat | Wald statistic | | phi1 | Estimated dispersion in group 1 | | phi2 | Estimated dispersion in group 2 | | pval | P-values obtained from normal distribution | | fdr | False discovery rate | | direction | Direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin) | | sex | Sex of animals | | age | Age of animals | * Supplementary_File_4_Consolidated_DMRs_callDMR.csv: This csv file contains the merged results of the cross-sectional differential modification analysis for each sex and timepoint using the *callDMR* function from the *DSS* R package, generated by Supplementary_File_13_CapHybSeq_DSS_DiffMeth_Exposure_Cross-sectional.Rmd. This file contains all standard output columns defined in the package documentation. Columns for sex and age were added to indicate which analysis each item came from, and a column for direction was added to indicate the direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin). Columns are defined as follows: | Name | Value | | :--------- | :--------------------------------------------------------------------------------------------------------------------------------------------- | | chr | Chromosome number | | start | Start coordinate | | end | End coordinate | | length | Length of the DMR, in basepairs | | nCG | Number of CpG sites contained in the DMR | | meanMethy1 | Average methylation level in condition 1 | | meanMethy2 | Average methylation level in condition 2 | | diff.Methy | Difference in the methylation levels between two conditions (diff.Methy=meanMethy1-meanMethy2) | | areaStat | Sum of the test statistics of all CpG sites within the DMR | | direction | Direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin) | | sex | Sex of animals | | age | Age of animals | * Supplementary_File_5_Consolidated_DMRs_dmrcate.csv: This csv file contains the merged results of the cross-sectional differential modification analysis done for each sex and timepoint using the *dmrcate* function from the *DMRcate* R package, generated by Supplementary_File_13_CapHybSeq_DSS_DiffMeth_Exposure_Cross-sectional.Rmd. This file contains all standard output columns defined in the package documentation. Columns for sex and age were added to indicate which analysis each item came from, and a column for direction was added to indicate the direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin). Columns are defined as follows: | Name | Value | | :----------------- | :--------------------------------------------------------------------------------------------------------------------------------------------- | | seqnames | Chromosome number | | start | Start coordinate | | end | End coordinate | | width | width = start coordinate-end coordinate | | strand | Strand | | no.cpgs | Number of constituent CpG sites of DMR | | min\_smoothed\_fdr | Minimum FDR of the smoothed estimate | | Stouffer | Stouffer summary transform of the individual CpG FDRs | | HMFDR | Harmonic mean of the individual CpG FDRs | | Fisher | Fisher combined probability transform of the individual CpG FDRs | | maxdiff | Maximum differential within the DMR | | meandiff | Mean differential across the DMR | | overlapping.genes | Overlapping genes | | chr | Chromosome number | | direction | Direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin) | | sex | Sex of animals | | age | Age of animals | * Supplementary_File_6\_ Consolidated_DMCs \_Annotated.csv: This csv file contains the results of annotation with the *annotatr* R package of significant DMCs in Supplementary_File_3\_ Consolidated_DMCs.csv, generated by Supplementary_File_13_CapHybSeq_DSS_DiffMeth_Exposure_Cross-sectional.Rmd. This file contains all standard output columns defined in the package documentation for *DSS* and *annotatr*. Columns for sex and age were added to indicate which analysis each item came from, and a column for direction was added to indicate the direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin). Columns are defined as follows: | Name | Value | | :------------- | :--------------------------------------------------------------------------------------------------------------------------------------------- | | seqnames | Chromosome number | | start | Start coordinate | | end | End coordinate | | width | width = start coordinate-end coordinate | | strand | Strand | | mu1 | Methylation mean of group 1 | | mu2 | Methylation mean of group 2 | | diff | Difference of mean methylations of two groups (diff=mu1-mu2) | | diff.se | Standard error of the methylation difference | | stat | Wald statistic | | phi1 | Estimated dispersion in group 1 | | phi2 | Estimated dispersion in group 2 | | pvalue | P-values obtained from normal distribution | | fdr | False discovery rate | | direction | Direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin) | | sex | Sex of animals | | age | Age of animals | | annot.seqnames | Chromosome number of annotation | | annot.start | Start coordinate of annotation | | annot.end | End coordinate of annotation | | annot.width | annot.width = start coordinate of annotation-end coordinate of annotation | | annot.strand | Strand of annotation | | annot.id | Unique name for annotation | | annot.tx\_id | UCSC knownGene transcript ID | | annot.gene\_id | Entrez ID | | annot.symbol | Gene symbol from the org.\*.eg.db mapping from the Entrez ID | | annot.type | Type of annotation in the form \[genome]\_\[type]\_\[name] | *  Supplementary_File_7\_ Consolidated_DMRs \_Annotated.csv: This csv file contains the results of annotation with the *annotatr* R package of significant DMRs in Supplementary_File_4_Consolidated_DMRs_callDMR.csv and Supplementary_File_5_Consolidated_DMRs_dmrcate.csv, generated by Supplementary_File_13_CapHybSeq_DSS_DiffMeth_Exposure_Cross-sectional.Rmd.  Columns for sex and age were added to indicate which analysis each item came from, and a column for direction (DM_status) was added to indicate the direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin). Columns are defined as follows: | Name | Value | | :------------- | :--------------------------------------------------------------------------------------------------------------------------------------------- | | seqnames | Chromosome number | | start | Start coordinate | | end | End coordinate | | width | width = start coordinate-end coordinate | | strand | Strand | | DM\_status | Direction of change (negative beta value difference = hypermodified by dieldrin and positive beta value difference = hypomodified by dieldrin) | | meandiff | Mean differential across the DMR | | no.cpgs | Number of constituent CpG sites of DMR | | sex | Sex of animals | | age | Age of animals | | annot.seqnames | Chromosome number of annotation | | annot.start | Start coordinate of annotation | | annot.end | End coordinate of annotation | | annot.width | annot.width = start coordinate of annotation-end coordinate of annotation | | annot.strand | Strand of annotation | | annot.id | Unique name for annotation | | annot.tx\_id | UCSC knownGene transcript ID | | annot.gene\_id | Entrez ID | | annot.symbol | Gene symbol from the org.\*.eg.db mapping from the Entrez ID | | annot.type | Type of annotation in the form \[genome]\_\[type]\_\[name] | *  Supplementary_File_8_Consolidated_DMCs_and_DMRs_Gene_Lists.csv:  This csv file contains lists of all unique annotated genes in Supplementary_File_6\_ Consolidated_DMCs \_Annotated.csv and Supplementary_File_7\_ Consolidated_DMRs \_Annotated.csv by sex and timepoint. Column names indicate sex and timepoint as follows: | Name | Value | | :--------- | :------------------------------------------- | | f\_neo | Annotated genes found in females at birth | | m\_neo | Annotated genes found in males at birth | | f\_6weeks | Annotated genes found in females at 6 weeks | | m\_6weeks | Annotated genes found in males at 6 weeks | | f\_12weeks | Annotated genes found in females at 12 weeks | | m\_12weeks | Annotated genes found in males at 12 weeks | | f\_36weeks | Annotated genes found in females at 36 weeks | | m\_36weeks | Annotated genes found in males at 36 weeks | *  Supplementary_File_9_AgeOnlyControl_Consolidated_DMCs.csv:  This csv file contains the merged results of the age-only longitudinal differential modification analysis done for each sex using the *DMLtest.multiFactor* function from the *DSS* R package, generated by Supplementary_File_16_CapHybSeq_DSS_DiffMeth_Age_ONLYControl.Rmd. This file contains all standard output columns defined in the package documentation. Columns for sex and age were added to indicate which analysis each item came from, and a column for direction was added to indicate the sign of the interaction term (negative test statistic = negative and positive test statistic = positive). Columns are defined as follows: | Name | Value | | :-------- | :------------------------------------------------------------------------------------------------------- | | chr | Chromosome number | | start | Start coordinate | | end | End coordinate | | stat | Wald test statistic | | pvals | P-value | | fdrs | False discovery rate | | direction | Sign of the interaction term (negative test statistic = negative and positive test statistic = positive) | | sex | Sex of animals | *  Supplementary_File_10_AgeOnlyControl_Consolidated_DMCs_Annotated.csv: This csv file contains the results of annotation with the *annotatr* R package of significant age-related DMCs in Supplementary_File_9_AgeOnlyControl_Consolidated_DMCs.csv. This file contains all standard output columns defined in the package documentation for *DSS* and *annotatr*. Columns for sex and age were added to indicate which analysis each item came from, and a column for direction was added to indicate the sign of the interaction term (negative test statistic = negative and positive test statistic = positive). Columns are defined as follows: | Name | Value | | :------------- | :------------------------------------------------------------------------------------------------------- | | seqnames | Chromosome number | | start | Start coordinate | | end | End coordinate | | width | width = start coordinate-end coordinate | | strand | Strand | | test\_stat | Wald test statistic | | pvalue | P-value | | FDR | False discovery rate | | direction | Sign of the interaction term (negative test statistic = negative and positive test statistic = positive) | | annot.seqnames | Chromosome number of annotation | | annot.start | Start coordinate of annotation | | annot.end | End coordinate of annotation | | annot.width | annot.width = start coordinate of annotation-end coordinate of annotation | | annot.strand | Strand of annotation | | annot.id | Unique name for annotation | | annot.tx\_id | UCSC knownGene transcript ID | | annot.gene\_id | Entrez ID | | annot.symbol | Gene symbol from the org.\*.eg.db mapping from the Entrez ID | | annot.type | Type of annotation in the form \[genome]\_\[type]\_\[name] | | sex | Sex of animals | *  Supplementary_File_11_AgeExposure_Consolidated_DMCs.csv: This csv file contains the merged results of the longitudinal differential modification analysis done for each sex using the *DMLtest.multiFactor* function from the *DSS* R package, generated by Supplementary_File_17_CapHybSeq_DSS_DiffMeth_Age+Exposure.Rmd. This file contains all standard output columns defined in the package documentation. Columns for sex and age were added to indicate which analysis each item came from, and a column for direction was added to indicate the sign of the interaction term (negative test statistic = negative and positive test statistic = positive). Columns are defined as follows: | Name | Value | | :-------- | :------------------------------------------------------------------------------------------------------- | | chr | Chromosome number | | start | Start coordinate | | end | End coordinate | | stat | Wald test statistic | | pvals | P-value | | fdrs | False discovery rate | | direction | Sign of the interaction term (negative test statistic = negative and positive test statistic = positive) | | sex | Sex of animals | *  Supplementary_File_12_AgeExposure_Consolidated_DMCs_Annotated.csv: This csv file contains the results of annotation with the *annotatr *R package of significant DMCS in Supplementary_File_11_AgeExposure_Consolidated_DMCs.csv. This file contains standard output columns defined in the package documentation for *DSS* and *annotatr*. Columns for sex and age were added to indicate which analysis each item came from, and a column for direction was added to indicate the sign of the interaction term (negative test statistic = negative and positive test statistic = positive). Columns are defined as follows: | Name | Value | | :------------- | :------------------------------------------------------------------------------------------------------- | | seqnames | Chromosome number | | start | Start coordinate | | end | End coordinate | | width | width = start coordinate-end coordinate | | strand | Strand | | test\_stat | Wald test statistic | | pvalue | P-value | | FDR | False discovery rate | | direction | Sign of the interaction term (negative test statistic = negative and positive test statistic = positive) | | annot.seqnames | Chromosome number of annotation | | annot.start | Start coordinate of annotation | | annot.end | End coordinate of annotation | | annot.width | annot.width = start coordinate of annotation-end coordinate of annotation | | annot.strand | Strand of annotation | | annot.id | Unique name for annotation | | annot.tx\_id | UCSC knownGene transcript ID | | annot.gene\_id | Entrez ID                              | | annot.symbol | Gene symbol from the org.\*.eg.db mapping from the Entrez ID | | annot.type | Type of annotation in the form \[genome]\_\[type]\_\[name] | | sex | Sex of animals | *  Supplementary_File_13_CapHybSeq_DSS_DiffMeth_Exposure_Cross-sectional.Rmd: This Rmd file contains code for the cross-sectional differential modification. * Supplementary_File_14_CapHybSeq_DiffMeth_VolcanoPlots.Rmd: This Rmd file contains code for generating volcano plots of DMCs identified in the cross-sectional differential modification analysis. * Supplementary_File_15_CapHybSeq_DiffMeth_VolcanoPlots.html: This html file contains the knitted output of Supplementary_File_14_CapHybSeq_DiffMeth_VolcanoPlots.Rmd. * Supplementary_File_16_CapHybSeq_DSS_DiffMeth_Age_ONLYControl.Rmd:This Rmd file contains code for the longitudinal differential modification analysis by age. * Supplementary_File_17_CapHybSeq_DSS_DiffMeth_Age+Exposure.Rmd: This Rmd file contains code for the longitudinal differential modification analysis to identify significant DMCs by age and exposure. * Supplementary_File_18_Data_Visualizations.Rmd: This Rmd file contains code for generating Euler diagrams, heatmaps, UpSet plots, and violin plots used to visualize data. * Supplementary_File_19_Data_Visualizations.html: This html file contains the knitted output of Supplementary_File_18_Data_Visualizations.Rmd. * Supplementary_File_20_meta_v3.csv: This csv file contains meta data for all samples used in the analysis and has the following columns: | Name | Value | | :---------------- | :----------------------------------------------------------------------------------------------- | | ID | Identifier | | Pup\_ID | Identifier | | Sample\_Name | Identifier | | Sample\_ID | Unique ID | | Sample\_Number | Identifier | | DNAIsolationRound | Batch of DNA isolations | | Age | Age indicated by the following abbreviations: 1 = birth, 2 = 6 weeks, 3 = 12 weeks, 4 = 36 weeks | | SampleType | Type of tissue collected | | Sex | Indicates sex | | Exposure | Indicates experimental condition | * Supplementary_File_21_20200911_dieldrin_samples_V1_1.xlsx: This Excel file contains the raw and processed mass spectrometry data to calculate dieldrin concentration in tissue by weight (ng/g) In Sheet 1, columns A-Y were generated by the MSU RTSF Mass Spectrometry and Metabolomics core. Columns Α through AG contain processed data as follows. Empty cells in this file are intentionally empty. ΑA: final concentration (Column L) corrected for dilution (pg/µl) AB: amount found in volume loaded (pg) AC: Tissue weight (g) AD: Tissue concentration in 4 ml solvent (g/ml) AE: Tissue in 1 ml (g) AF: Amount of dieldrin in tissue (pg/g) AG: Amount of dieldrin in tissue (ng/g) * Supplementary_File_22_P10_NeonateBrain_Dieldrin_Concentration_120621.csv: This csv file contains the processed mass spectrometry data from Supplementary_File_21_20200911_dieldrin_samples_V1_1.xlsx, merged with sample meta deta. Columns are defined as follows: ID (identifier), Mouse_ID (identifier), Sample_Label (identifier), Sex, Age, Exposure_group (experimental conditions), Sample_type (tissue collected), Sample_storage (tube type), Submission_date (date submitted to core), Dieldrin_concentration (final concentration calculated in Supplementary_File_21_20200911_dieldrin_samples_V1_1.xlsx, rounded), Dieldrin_concentration_2 (final concentration calculated in Supplementary_File_21_20200911_dieldrin_samples_V1_1.xlsx) - Supplementary_File_23_Figure_7_P10E4-DieldrinMassSpec.pzfx: This GraphPad Prism file contains mass spectrometry data from Supplementary_File_22_P10_NeonateBrain_Dieldrin_Concentration_120621.csv to generate graphs of dieldrin levels. ## Sharing/Access information Preregistration: [https://doi.org/10.17605/OSF.IO/3QXFV](https://doi.org/10.17605/OSF.IO/3QXFV) Raw sequencing data: GEO Accession No. [GSE264165](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE264165) Preprint: [https://doi.org/10.1101/2024.04.26.590998](https://doi.org/10.1101/2024.04.26.590998) ## Code/Software R markdown files can be open and run in R and RStudio, which are freely available. All packages utilized are documented in the manuscript methods and the code itself. GraphPad Prism files (pzfx) can be opened in GraphPad Prism or viewed in the free Viewer mode, or data can be extracted by viewing files in a text editor.  csv files can be opened in a spreadsheet software or text editor bed files can be opened in a text editor html files can be opened in any internet browser