Prenatal Glucocorticoid Exposure Results in Changes in Gene Transcription and DNA Methylation in the Female Juvenile Guinea Pig Hippocampus Across Three Generations

Synthetic glucocorticoids (sGC) are administered to women at risk for pre-term delivery, to mature the fetal lung and decrease neonatal morbidity. sGC also profoundly affect the fetal brain. The hippocampus expresses high levels of glucocorticoid (GR) and mineralocorticoid receptor (MR), and its development is affected by elevated fetal glucocorticoid levels. Antenatal sGC results in neuroendocrine and behavioral changes that persist in three generations of female guinea pig offspring of the paternal lineage. We hypothesized that antenatal sGC results in transgenerational changes in gene expression that correlate with changes in DNA methylation. We used RNASeq and capture probe bisulfite sequencing to investigate the transcriptomic and epigenomic effects of antenatal sGC exposure in the hippocampus of three generations of juvenile female offspring from the paternal lineage. Antenatal sGC exposure (F0 pregnancy) resulted in generation-specific changes in hippocampal gene transcription and DNA methylation. Significant changes in individual CpG methylation occurred in RNApol II binding regions of small non-coding RNA (snRNA) genes, which implicates alternative splicing as a mechanism involved in transgenerational transmission of the effects of antenatal sGC. This study provides novel perspectives on the mechanisms involved in transgenerational transmission and highlights the importance of human studies to determine the longer-term effects of antenatal sGC on hippocampal-related function.


Results
Gene transcription. In F 1 , 285 genes were significantly differentially expressed in the hippocampi of sGC animals compared to control (FDR < 0.05; Fig. 1A). Of these, 69 genes are significantly down-regulated, while 216 genes are significantly up-regulated in sGC offspring (FDR < 0.05). GSEA revealed that 181 gene sets were enriched, with 146 sets negatively enriched (down-regulated) and 35 sets positively enriched (up-regulated) in sGC animals (NES > 1.6, FDR < 0.25; Supplementary Table S1). Down-regulated gene sets included hormone activity, neurotransmitter binding and corticosterone response pathways, and positively enriched gene sets included inflammatory response and locomotor behaviour pathways in the sGC animals (NES > 1.6, FDR < 0. 25). An example of the corticosterone response pathways gene set is presented in Fig. 2A.
In F 2 , only three genes were significantly differentially expressed in sGC animals compared to control (FDR < 0.05; Fig. 1A); the three genes exhibited reduced expression. GSEA results showed significant enrichment of 193 gene sets, with 20 down-regulated and 172 gene sets up-regulated (NES > 1.6, FDR < 0.25; Supplementary  Table S1). It is important to note that with regards to the GSEA, the individual genes within the gene sets are not significantly differentially expressed. Rather, a greater number of genes pertaining to these pathways are changed in the same direction than would be expected by chance; thus, these pathways are "enriched" 32 . Down-regulated gene sets were involved in vesicular docking and extracellular matrix organization, while up-regulated pathways were related to cytokine signaling (NES > 1.6, FDR < 0. 25). An example of the vesicular docking gene set is presented in Fig. 2B.
Not all of the DMRs significantly affected by sGC exposure were associated with coding genes (Supplementary Table S2). Figure 3D shows the number of hypo-or hypermethylated DMRs in each generation of offspring that were related to genes. There were 2 genes with differential methylation in all three generations of sGC offspring. These genes are Kif26b, and St6galnac5 (>10%, FDR < 0.05; Fig. 3D). Methylation of Kif26b is decreased in F 1 and F 2 and increased in F 3 , whereas methylation of St6galnac5 is decreased in F 1 and F 3 and increased in F 2 . overlap between changes in DnA methylation and gene expression. In F 1 , there were 5 genes (Ino80d, Zbtb44, Grin2a, Sacs, Prkca) that were both significantly differentially expressed (FDR < 0.05) and differentially methylated (>10%, FDR < 0.05; Fig. 4A). There was no overlap between gene expression and methylation in F 2 . In F 3 , 8 genes (App, Cacna2d1, Dym, Gria1, Lta4h, Sdhaf4, Syt1, Zc3h12c) were both significantly differentially expressed (FDR < 0.05) and differentially methylated (>10%, FDR < 0.05; Fig. 4B). All the methylation changes that overlapped gene expression in both F 1 and F 3 animals occurred in enhancer regions (Fig. 4).
Single-nucleotide resolution methylation changes are related to small non-coding RnAs (snR-nAs). To elucidate how antenatal sGC affect DNA methylation at the individual CpG level, we performed DNA methylation analysis with single-nucleotide resolution. In F 1 animals that had been exposed to prenatal sGC, there were 63 CpGs that were significantly differentially methylated (>10%, FDR < 0.05; 29 hypomethylated, 34 hypermethylated). There were 13 differentially methylated CpGs in unannotated regions, 5 were in regions related to coding genes, and 45 related to snRNA encoding genes. In F 2 sGC animals, there were 21 CpGs that were significantly differentially methylated (>10%, FDR < 0.05; 11 hypomethylated, 10 hypermethylated).

Figure 1. (A)
Venn diagram illustrating the number of genes that are significantly differentially expressed in the HPC of young female F 1 -F 3 offspring following prenatal synthetic glucocorticoid treatment of the F 0 pregnancy and the number of genes that overlap between generations (Veh F 1 (n = 6), F 2 (6), F 3 (6); sGC F 1 (5), F 2 (6), F 3 (7)). (B) Heatmap of the 18 genes that are differentially expressed in F 1 and F 3 female offspring. Values indicate the log-fold change in gene expression in sGC animals relative to control, color further indicates the direction of change (green: significantly down-regulated; red: significantly up-regulated; grey: not significant).
There were 4 differentially methylated CpGs in unannotated regions, 4 were in regions related to coding genes and 13 were related to snRNA genes. In F 3 sGC animals, there were 51 CpGs that were significantly differentially methylated (>10%, FDR < 0.05; 33 hypomethylated, 18 hypermethylated). There were 12 differentially   Heatmaps showing key hippocampal genes driving the gene set enrichment differences between sGC exposed offspring lineages and controls (Veh F 1 (n = 6), F 2 (6), F 3 (6); sGC F 1 (5), F 2 (6), F 3 (7)) in (A) F 1 juvenile females, the corticosterone response pathway was significantly down-regulated (NE > 1. 6 describes relationship between treatment with sGC and the expression of genes within a gene set, positiveincreased expression, negative-decreased expression. Size: number of genes in the gene set. NES: normalized enrichment score used to compare gene sets of different sizes. FDR: false discovery rate, the probability that a gene set with a specific NES is a false positive. (Veh F 1 (n = 6), F 2 (6), F 3 (6); sGC F 1 (5), F 2 (6), F 3 (7)). www.nature.com/scientificreports www.nature.com/scientificreports/ methylated CpGs in unannotated regions, 8 in regions related to coding genes, and 31 were related to snRNA genes. The significantly differentially methylated CpGs were distributed amongst promoter and enhancer regions. A list of affected snRNA genes is presented in Supplementary Table S4. sGC differentially methylated CpGs were enriched in RNApol II-PS5 binding regions. We investigated the enrichment of significantly differentially methylated CpGs among distinct genomic features. Since we designed a custom probe set to target specific regions of the genome, we were able to use this probe coverage to determine whether methylation changes were enriched in a certain region. Though over 85% of our capture was designed for enhancer regions, the significant changes in CpG methylation did not occur in enhancer regions, but rather occurred in promoter regions. The observed distribution of differentially methylated CpGs (which occurred in the promoter regions) was significantly different from the expected distribution generated by the custom probe capture design (which captured more enhancer regions than promoter regions) in F 1 (χ 2 = 155. 46, www.nature.com/scientificreports www.nature.com/scientificreports/ p = 2.2e-16), F 2 (χ 2 = 20.26, p = 4.4e-04), and F 3 (χ 2 = 77.42, p = 2.9e-15). In all three generations, differentially methylated CpGs occurred in promoter/RNAPol II-PS5 binding regions; F 1 (χ 2 = 562.71, p < 2.2e-16), F 2 (χ 2 = 16.51, p = 4.8e-05), and F 3 (χ 2 = 20078, p < 2.9e-16) (Fig. 5).

Control sGC
Differential expression of candidate genes. Since many studies have shown that antenatal sGC exposure alters gene expression in the hippocampus, we used these findings to generate a list of genes (Supplementary Table S5) that we hypothesized would be most affected with regards to gene expression and DNA methylation as a result of antenatal sGC exposure. In the F 1 sGC offspring, five genes from our a priori list (Kcnj6, Myo5a, Crhr2, Grin2a, Ncoa2) were differentially expressed. To test our hypothesis that the genes from our a priori list were most affected by antenatal sGC, we performed χ 2 to determine whether more genes from our a priori list were significantly differentially expressed than would be expected by chance. Contrary to our hypothesis, the number of observed genes was not significantly different than would be expected by chance (χ 2 = 0.0037, p = 0.95). There were no genes differentially expressed from the a priori list in F 2 . In the F 3 sGC offspring, 16 genes from the a priori list were significantly differentially expressed (Hmgb2, Shank1, Emp2, Gpm6b, Ssr4, Chd3, Gldc, Dlg4, Atp6v1c1, Gria1, Nr3c2, Snap25, Gad2, Dync1l1, Syp, Gad1), more than would be expected by chance (χ 2 = 7.13, p < 0.05).

Discussion
We have demonstrated, for the first time, that transgenerational changes in hippocampal gene expression and methylation occur over three generations in female offspring following antenatal sGC and paternal transmission. Strikingly, while only 3 genes were differentially expressed in the F 2 sGC offspring, there were over 280 genes differentially expressed in F 1 sGC offspring, and over 490 genes were differentially expressed in F 3 sGC offspring. There was no overlap between differentially expressed genes across all 3 generations. Furthermore, we observe generation-specific hippocampal methylation signatures in animals from the sGC-exposed lineage. Importantly, changes in methylation that are associated with changes in gene expression occur at enhancer www.nature.com/scientificreports www.nature.com/scientificreports/ regions, and methylation changes at the individual CpG level are enriched in RNApol II-PS5 binding regions of small non-coding RNAs (snRNAs). Thus, antenatal sGC exposure results in generation-specific methylation signatures in the hippocampus, which may function in concert with transcriptional machinery to alter phenotypes and transmit effects to subsequent generations.
In F 1 offspring exposed to prenatal sGC, 285 genes were significantly differentially expressed in the hippocampus. Previous research has shown that the expression of genes related to key signaling pathways are altered by prenatal exposures to excess glucocorticoids 6,10-14 . In the present study, using an in silico approach, we identified 199 genes linked to key hippocampal signaling pathways that related to published phenotypic outcomes in offspring following prenatal sGC exposure or maternal stress in pregnancy. At an individual gene level, only five genes from the a priori list (Kcnj6, Myo5a, Crhr2, Grin2a, Ncoa2) were differentially expressed in the hippocampus of F 1 offspring following prenatal exposure to sGC. Notwithstanding, we did observe down-regulation of gene set pathways related to the corticosteroid response. The hippocampus exerts inhibitory control over the PVN 33 , thus down-regulation of genes related to corticosteroid response (50 days after sGC exposure) may result in decreased inhibition of the PVN, and an increased HPA-response to stress. This would be consistent with the increased HPA-response observed in the F 1 sGC offspring after exposure to the open-field 21 .
Unexpectedly, we observed changes in the hippocampal expression of only three genes in F 2 female offspring in the sGC group (paternal transmission; F 1 fathers exposed to sGC when F 0 grandmothers treated during pregnancy) compared to controls. Interestingly, these animals showed the strongest behavioral phenotype (of the three generations), as well as substantial changes in gene expression in the hypothalamic paraventricular nucleus, and prefrontal cortex 21,26 . While individual genes may not have been significantly differentially expressed, we used gene set enrichment analysis, which examines whether there are small changes in gene expression in the same direction (up or down) for multiple genes related to the same pathway, to identify gene networks that are differentially regulated as a result of antenatal sGC. We observed that pathways involved in vesicular docking are down-regulated in the F 2 descendants of sGC-exposed pregnancies. In addition, pathways involved in blood-brain barrier integrity (collagen and extracellular matrix) were down-regulated in the F 2 sGC offspring hippocampus. Similar gene sets have previously been shown to be altered by antenatal glucocorticoids in the PVN 21,34 . Thus, very few individual genes are significantly differentially expressed in the F 2 sGC offspring, however, dysregulated gene networks may suggest altered hippocampus gene function in these animals.
In F 3 offspring, descendent of sGC treated mothers, 16 genes from the a priori list were significantly differentially expressed, which was more than was expected by chance. Furthermore, while the effects of antenatal sGC decrease in the F 3 compared to F 1 offspring in the PVN and PFC 21,26 in the present study, we demonstrated that in the hippocampus, more genes are significantly affected by sGC in the F 3 animals compared to the F 1 and F 2 offspring. Interestingly, we observed downregulation of Mr (Nr3c2), in the F 3 sGC exposed animals. Mr expression in the hippocampus plays an important role in HPA negative feedback regulation 35 , and decreased Mr signaling may be indicative of decreased HPA-inhibition. However, the F 3 sGC offspring did not display altered HPA response to stress, though they did demonstrate a hyperactive phenotype in the open-field 21 . These findings suggest that glucocorticoid signaling may be altered in the hippocampus of F 3 sGC animals and may relate to phenotypic outcomes. In the present study, we also observed down regulation of genes that are important for learning and memory (Gad1, Syp, Gad2, Gria1). Gad1 and Gad2 are enzymes involved in γ-aminobutyric acid (GABA) signaling 36 , and decreased expression of these genes in the hippocampus has previously been observed in patients with schizophrenia and bipolar disorder 37 . Syp is involved in regulating activity-dependent synapse formation 38 , and Gria1 expression is essential in new memory formation 39,40 . Though behavioral tests related to cognition were not performed in the present study, the gene expression changes observed in F 3 sGC offspring suggest these animals may have had learning deficits, and this can be tested in future studies.
We observed generation-specific effects of antenatal sGC exposure, with distinct methylation signatures occurring in each of the generations. We observed very little overlap between gene expression and methylation changes. We have previously shown that transcriptionally active enhancers are less methylated than poised enhancers 31 . However, the mRNA measure of transcription level is confounded by several regulatory processes downstream to transcription initiation 41 , meaning that enhancer methylation and mRNA content do not always correlate. This may be why there were so few changes in DNA methylation that correlate with steady-state expression. However, changes in methylation that are associated with changes in steady-state gene expression did occur in enhancer regions, consistent with the notion that DNA methylation in enhancer regions is more correlated with gene expression than promoter methylation 24,30 . Epigenetic mechanisms play a role in regulating gene expression patterns in response to environmental cues 42 . The animals in this study were euthanized in an unstressed basal state, and methylation signatures left by antenatal sGC may indicate that genes are poised to be expressed differently following environmental stimuli. It may be that stronger correlations between gene expression and methylation would occur when the animals are in an activated state (i.e. a stressful environment). Interestingly, very few genes from our a priori list displayed significant changes in methylation. Though previous research has demonstrated that antenatal sGC alters the methylation status of promoter regions of genes from this list 6 , these changes have also been shown to be dynamic, and may not remain as a permanent signature 50-days after final exposure to sGC 6 . Only two genes were differentially methylated across all three generations of offspring: Kif26b, a motor protein involved in organelle transport and intracellular signaling 43 ; and St6galnac5, a glycosyltransferase involved in cell-cell interactions 44 . Both genes demonstrated generation-specific changes in methylation but were not differentially expressed due to sGC exposure. Unlike our previous work in the PFC 26 , we did not observe consistent changes in DNA methylation and gene expression in the hippocampus, suggesting region-specific responses following prenatal sGC exposure.
Analyzing DMRs (100 bp windows of DNA methylation changes) provides an overview of the methylation signatures that result from antenatal sGC exposure. In the F 1 and F 3 sGC offspring, hypomethylated DMRs were related to glutamatergic signaling. While glutamate release is essential for cellular signaling processes, including www.nature.com/scientificreports www.nature.com/scientificreports/ learning and memory, the hippocampus is especially vulnerable to excitotoxicity from excess glutamate release. Chronic stress, and chronic exposure to glucocorticoids, is known to be a potent trigger of glutamate excitotoxicity, and results in cell death and mood disorders 45 . Corticosteroids potentiate the excitability of the hippocampus 46 and prime the hippocampal circuit for subsequent stimulation 47 . Corticosteroids have been shown to result in a rapid release of glutamate 46 and increased glutamatergic synaptic signaling has been shown to coincide with decreased levels of methylation 48,49 . Taken together, these findings suggest that the hypomethylation observed in the F 1 and F 3 sGC offspring is indicative of altered glutamatergic sensitivity, which may lead to decreased excitotoxicity resilience in the hippocampi of these animals. Surprisingly, this DNA methylation signature was not present in the F 2 sGC animals. In the F 2 sGC animals, hypomethylation was observed in genes related to GTP activity which is an essential part of G-coupled protein receptor signaling 50 . Rab GTPase activity has been shown to be involved in signal transduction of glutamate receptors 51 , thus it is possible that glutamate receptor activity may also be altered in F 2 sGC animals, but via a different mechanism.
The significantly differentially methylated CpGs in all three generations of sGC offspring were enriched in RNApol II-PS5 binding sites of small noncoding nucleolar and spliceosomal RNA genes. Small noncoding RNAs (snRNAs) are a secondary level of epigenetic control involved in the fine-tuning of gene expression 52,53 . Promoter methylation levels have been shown to regulate snRNA expression 54 , and expression of snRNAs has been shown to be dysregulated in the adult mouse brain after fetal alcohol exposure, which may suggest that altered snRNA expression can influence phenotype resulting from early life exposure 52 . In the current study, mRNA-enriched analyses were performed to quantify gene expression, which precludes us from assessing changes in the expression of snRNA and represents a limitation of this study. However, we observed differential methylation for snRNAs (Snora2) responsible for post-transcriptional modifications of spliceosomal RNA (U6) across all three generations of sGC offspring. U6 is involved in the removal of intronic regions of RNA primary transcript and assembly of exons to form mRNA 55 . Though the exact mechanisms remain to be elucidated, recent evidence suggests that altered snRNA activity is involved in alternative splicing 55 . Alternative splicing, a conserved process that increases the diversity of the transcriptome and proteome by allowing multiple mRNA products to result from a single gene, has been shown to be regulated by interplay between chromatin and DNA methylation [56][57][58] . Over 90% of human genes undergo alternative splicing 58 , and alternative splicing patterns have been shown to be sex-specific 59 , and heritable in a Mendelian fashion 60 . Thus, antenatal sGC results in transgenerational changes in DNA methylation in RNApol II-PS5 binding regions of snRNA genes involved in transcription machinery, implicating alternative splicing as a potential mechanism involved in the transgenerational transmission of the effects of antenatal sGC in the hippocampus. However, this important possibility needs to be tested in further detailed experiments.
In the present study, the fact that there are behavioural changes accompanied by changes in hippocampal DNA methylation and gene expression across three generations implicates male germ-line epigenetic transmission. A number of potential mechanisms, both direct and indirect, by which this might occur are emerging. Persistent changes in germline DNA methylation, as a mode of transgenerational transmission, are unlikely given the broad waves of DNA demethylation that occur during embryonic development. In support of this, a previous study has shown maternal malnutrition to be associated with differentially methylated regions within the sperm of F 1 offspring, but that no differences in methylation were maintained into the F 2 generation 61 . Another potential route of paternal transmission may be through small RNAs, including microRNA (miRNA) and transfer RNA. Sperm contain miRNA which can be delivered to the oocyte on fertilization 62 . Early life stress in males, resulted in an altered compliment of miRNA in sperm in adulthood, and an elegant series of subsequent studies determined that a number of these miRNA were driving phenotypic differences in subsequent offspring 62,63 . Other studies have indicated that histone modifications in sperm as a potential route for paternal inheritance. While the majority of histones in sperm are replaced by protamines, some histones remain 64 . After fertilization, paternal protamines are replaced by heavily acetylated maternal histones, while paternal histones remain largely untouched 65 . Thus, it is possible for epigenetic marks on these histones to be inherited.
Epigenetic inheritance paradigms have often considered potential mechanisms in isolation; however, it is likely that there is interplay between processes. In this regard, small RNAs can drive de novo cytosine methylation and alterations in chromatin structure 66 . Such integrated processes may be occurring in the model described in the present study, allowing the transmission of the effects of sGC exposure across multiple generations. The dynamic nature of the changes across 3 generations suggest that an initial epigenetic signal transmitted by the F 1 sperm is not a static epigenetic memory that is inherited across future generations. The picture that is emerging is more consistent with the initial epigenetic signal triggering a cascade of epigenetic events that include DNA methylation which keep changing dynamically across tissues and generations. Clearly further studies are required to determine the specific processes involved in this model.
There are some limitations with the present study. Focus was placed on DNA methylation and gene transcription and future studies should address the relationship of altered gene transcription with altered protein levels in the hippocampi across multiple generations. Analysis of DNA methylation was limited to 5-methylcytosine. We did not undertake analysis of downstream modifications by oxidation of 5 methylcytosine such as 5-hydroxymethylcytosine, 5-formylcytosine and 5-carboxylcytosine, which may also play a role in transgenerational transmission. We also acknowledge that our use of RNAPolII-Ser5 ChIP to assist in the identification of promoters may lead to some biases towards active rather than silenced genes. Our studies have highlighted the possibility that prenatal sGC may lead to alterations in transcript splicing. Due to the sequencing methodology used in this study, we were unable to investigate differential splicing, though this could be a focus of future studies. Due to budgetary constraints, analysis was limited to female juvenile offspring (where greatest phenotypes were observed). Future comparative analyses in males would certainly provide insight into the relationship between alterations in methylation, gene expression and phenotype following antenatal sGC exposure, as well as sex differences in the molecular actions of prenatal sGC exposure in the developing hippocampus. Finally, future studies are required to further elaborate the mechanisms involved in transgenerational transmission. www.nature.com/scientificreports www.nature.com/scientificreports/ conclusions This study demonstrates transgenerational changes in transcription and DNA methylation following antenatal sGC exposure over the paternal lineage. Changes in gene transcription and DNA methylation patterns following antenatal sGC are generation-specific and are highest in the third-generation offspring. DNA methylation changes associated with sGC exposure may be involved in altered glutamatergic signaling. Significant changes in individual CpG methylation occur in RNApol II-PS5 binding regions of snRNAs and may implicate alternative splicing as a mechanism involved in transgenerational transmission of the effects of antenatal sGC. These findings demonstrate that the effects of antenatal sGC exposure alter genetic and transcriptomic regulation of the hippocampus of three generations of offspring through the paternal lineage. These findings provide new perspectives on the mechanisms involved in transgenerational transmission and show that the effects of antenatal sGC on the hippocampus may potentiate with advancing generations. Thus, it is imperative to perform future studies in human cohorts to elucidate the long-term effects of antenatal sGC on the developing brain and identify interventions to prevent transmission to subsequent generations.  21 . Delivery in Dunkin-Hartley guinea pigs occurs at ~69 days, with an average of 3 offspring/litter in our colony. The sGC dose utilized in the present study is comparable to that given in pregnancies at risk of preterm delivery (~0.25 mg/kg), as the guinea pig glucocorticoid receptor (GR) has a 4-fold lower affinity for sGC 67 . While single course treatment with GC is currently standard of care, in the late 90's and early 2000's multiple course therapy was widespread 68 , and more recently the use of repeat 'rescue' sGC treatment has been adopted 69 .

Methods
First (F 1 ) generation male offspring, derived from independent mothers, were mated with non-experimental females (purchased from Charles River) to generate F 2 offspring, as previously described 21 . Third (F 3 ) generation offspring were generated by mating the F 2 males with non-experimental females. The males and non-experimental females were only bred once. Other than routine cage maintenance, F 1 and F 2 pregnancies were left undisturbed. A figure outlining the full breeding regimen has been published 21 . As we have reported previously, there was no significant effect of prenatal sGC treatment on breeding parameters in any of the generations, including litter size and sex ratio 21 . All protocols were approved by the Animal Care Committee at the University of Toronto in accordance with the Canadian Council on Animal Care.
Animals were euthanized in an unstressed basal state on post-natal day 40, as previously reported 21 , and both left and right hippocampi were removed and frozen immediately on dry ice. To analyze gene expression and DNA methylation from these tissues, genomic DNA and RNA were extracted simultaneously from 20 mg of powdered right hippocampus using the AllPrep DNA/RNA/miRNA Universal Kit (Qiagen, Ontario, Canada). In the present study, the hippocampi from female juvenile offspring (n = 5-7/gp; F 1 , F 2 , F 3 vehicle; F 1 , F 2 , F 3 sGC) were used for molecular analysis. Our previous studies had indicated that juvenile females showed the greatest differences in behavioural and neuroendocrine phenotypes (pituitary-adrenal function and open-filed activity) associated with prenatal sGC exposure 21 . All female offspring used in this study were derived from independent mothers, and each mother had been bred to a single F 1 or F 2 male. Custom design of capture arrays for bisulfite mapping of DNA methylation. We designed a custom targeted array (SeqCap Epi Enrichment, Roche), based on our previous study 31 , composed of enhancer and promoter regions of the guinea pig genome. Promoter regions were identified from the Ensemble database, as well as from a previous RNAPolII-Ser5 ChIP experiment, the serine 5 phosphorylation marks RNA polymerase 2 molecules engaged in turning on transcription 31 . Enhancer regions were identified in a previous H3K4me1 ChIP experiment, H3K4me1 mark is enriched at enhancers 31 . The SeqCap probe enrichment kit from Roche allowed for the capture of 210 Mb of gDNA. 550 bp of promoter regions centered around the TSS were covered for all genes (26129 promoters equating to 6.8% of the capture). RNA PolII-Ser5 peaks were captured, along with RNA PolII-Ser5 peaks that coincided with H3K4me1 peaks (66909 regions; 13% of capture). Enhancer peaks smaller than 550 base pairs were captured in their entirety (49866 enhancers, equating to 8.5% of capture) and 550 bp of larger enhancer peaks were captured to span the center of the peak (263249 enhancers; 69% of capture). Lastly, a list of gene networks that we hypothesized would be most affected by sGC, based on previous studies 6,10-14 was generated using 14 'seed' genes (Grin2b, Nr3c2, Nr3c1, Gad1, Drd1, Crh, Abcb1, Gria1, Sert, Dnmt1, Fos, Bdnf, Syp, Mbd2) for which the top 20 genes related to biological process were selected 61 . This resulted in a list of 199 genes of interest (Supplementary Table S5). Probes were designed to cover all promoters and enhancers for the genes of interest (1260 enhancers; 2% of capture).
Capture, bisulfite conversion. gDNA (1 µg; F 1 : Veh N = 6, sGC N = 6; F 2 : Veh N = 6, sGC N = 6; F 3 : Veh N = 7, sGC N = 5) was purified using the AMPure XP beads (Beckman Coulter, Ontario, Canada), following the manufacturer's instructions (1.8 v/v). Libraries were prepared from purified DNA, using the KAPA Library Prep Kit Illumina (Roche) and SeqCap Adapter kit (Roche) according to the SeqCap Epi Enrichment System User Guide. Libraries then underwent bisulfite conversion. Bisulfite conversion was performed using the EZ DNA Methylation-Gold Kit (Zymo Research), and bisulfite converted DNA was amplified using LM-PCR by a 15-cycle PCR and purified with AMPure XP beads (1 v/v) (Beckman Coulter). Size and quantity of the resulting libraries were verified using HSdna Bioanalyzer chip (Agilent, CA, USA) and Q-PCR, respectively (Kappa Library Quantification kit for Illumina sequencing). Bisulfite libraries were hybridized with our custom SeqCap Epi Probe pool. After washing and recovery of captured DNA, an amplification using LM-PCR was performed as described above. All captured samples were sequenced by 50  www.nature.com/scientificreports www.nature.com/scientificreports/ Methylation capture sequencing analyses. After bisulfite treatment and sequencing, reads were trimmed using Trimmomatic-0.32, then aligned to the guinea pig genome (cavPor3) using bsmap-2.74 v0.12.5. Picard-tools-1.93 was used to remove duplicates. Sequenced reads showed on average 68% on-target alignment with capture-probe design. Methylation levels were determined for individual CpG sites using bsmap-2.74 with a minimal coverage of 10 reads. Changes in methylation for 100 bp windows (50 bp apart) and individual CpGs were detected using the calculate DiffMeth function from MethylKit (v.1.4.0) in R (version 3.2.3). Data were annotated using Homer v4.6 with the annotatePeaks script and CavPor3 genome.
RnA sequencing. RNA quality was determined by Bioanalyzer (RNA 6000 Pico LabChip, Applied Biosystems, Ontario, Canada); all RNA (1 μg) samples RIN ≥ 7. mRNA library preparation was performed using Illumina TruSeq V2 mRNA enrichment using standard protocols. High-throughput sequencing was performed on an Illumina HiSeq. 2500 sequencing system using standard run, following the protocol recommended by Illumina for sequencing mRNA samples. Sequencing was done for each biological replicate (F 1 : Veh N = 6, sGC N = 5; F 2 : Veh N = 6, sGC N = 6; F 3 : Veh N = 6, sGC N = 7) at 1 × 51 bp by the Donnelly Centre for Cellular and Biomolecular Research (University of Toronto, Ontario, Canada). RNA-seq results were analyzed as previously described 21 . Briefly, differential gene expression was assessed using EdgeR's (version 3.12.1) 70,71 , general linear model likelihood ratio test and FDR-corrected p < 0.05 was considered significant. Genotype permutations (1000) were computed in Broad Institute's Gene Set Enrichment Analysis (GSEA) 32,72 to determine FDR, nominal p-value, and normalized enrichment score (NES) of each gene set. Gene sets with FDR ≤ 0.25, p ≤ 0.01, and NES ≥ 1.6 met significance thresholds 21 . All sequencing data can be accessed at GEO with accession number GSE109765.
Differentially methylated CpG distribution statistics test. The CpGs with minimum 10X coverage were categorized into 'Exon' , 'Intergenic' , 'Intron' , 'Promoter-TSS' , and 'TTS' (Transcription Termination Site) based on Homer v4.6 using the annotatePeaks script. The expected counts were calculated with the number of CpGs that were sequenced with 10X coverage. Statistics were calculated using multinomial goodness-of-fit Chi-square test (R; version 3.2.3). Post-hoc Chi-square tests were run on each category (genomic region and capture design region) versus the sum of all other categories to determine which category was driving the effect.
Gene expression (qRt-pcR). RNA (400 ng) was converted to cDNA using SensiFAST cDNA synthesis kit (Bioline, London, England) as per the manufacturer's instructions. The reaction included random hexamer primers and anchored oligo dT to ensure unbiased 3′ and 5′ coverage and reverse transcription of all regions. qRT-PCR was run using the SensiFAST SYBER Hi-ROX kit (20 μl reaction, Bioline) with forward and reverse primers according to the manufacturer's instructions. qRT-PCR was performed in a Bio Rad C1000 Thermal Cycler and quantified by a CFX96 Real-Time PCR Detection System using the following conditions: 95 °C for 30 sec; followed by 40 cycles of 95 °C for 5 s, and 60 °C for 5 s, for plate read. All samples were run in triplicate. Relative expression of target mRNA (Mineralocorticoid Receptor (Nr3c2), Glutamate Ionotropic Receptor NMDA type subunit 2 A (Grin2a), Glutamate Decarboxylase 1 (Gad1), Synaptophysin (Syp)) was normalized to Gapdh (see Supplementary Table S6 for primer sequences) by the 2 −ΔΔc(t) method. qPCR validation correlated 99% with RNAseq findings (Supplementary Fig. S5).

Data availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.