The Association between Long-Term DDT or DDE Exposures and an Altered Sperm Epigenome-a Cross-Sectional Study of Greenlandic Inuit and South African VhaVenda Men

Abstract

Background: The organochlorine dichlorodiphenyltrichloroethane (DDT) is banned worldwide owing to its negative health effects. It is exceptionally used as an insecticide for malaria control. Exposure occurs in regions where DDT is applied, as well as in the Arctic, where its endocrine disrupting metabolite, $p,p\text{'}$-dichlorodiphenyldichloroethylene ($p,p\text{'}$-DDE) accumulates in marine mammals and fish. DDT and $p,p\text{'}$-DDE exposures are linked to birth defects, infertility, cancer, and neurodevelopmental delays. Of particular concern is the potential of DDT use to impact the health of generations to come via the heritable sperm epigenome.

Objectives: The objective of this study was to assess the sperm epigenome in relation to $p,p\text{'}$-DDE serum levels between geographically diverse populations.

Methods: In the Limpopo Province of South Africa, we recruited 247 VhaVenda South African men and selected 50 paired blood serum and semen samples, and 47 Greenlandic Inuit blood and semen paired samples were selected from a total of 193 samples from the biobank of the INUENDO cohort, an EU Fifth Framework Programme Research and Development project. Sample selection was based on obtaining a range of $p,p\text{'}$-DDE serum levels ($\text{mean}=870.734\pm 134.030\text{ng}/\mathrm{mL}$). We assessed the sperm epigenome in relation to serum $p,p\text{'}$-DDE levels using MethylC-Capture-sequencing (MCC-seq) and chromatin immunoprecipitation followed by sequencing (ChIP-seq). We identified genomic regions with altered DNA methylation (DNAme) and differential enrichment of histone H3 lysine 4 trimethylation (H3K4me3) in sperm.

Results: Differences in DNAme and H3K4me3 enrichment were identified at transposable elements and regulatory regions involved in fertility, disease, development, and neurofunction. A subset of regions with sperm DNAme and H3K4me3 that differed between exposure groups was predicted to persist in the preimplantation embryo and to be associated with embryonic gene expression.

Discussion: These findings suggest that DDT and $p,p\text{'}$-DDE exposure impacts the sperm epigenome in a dose-response-like manner and may negatively impact the health of future generations through epigenetic mechanisms. Confounding factors, such as other environmental exposures, genetic diversity, and selection bias, cannot be ruled out. https://doi.org/10.1289/EHP12013.

Figure 1.

Association between $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene ($p,p\mathrm{\prime }$-DDE) serum levels and human sperm DNA methylation (DNAme). (A) Number of differentially methylated CpGs (DMCs), DNA methylation (DNAme) gain DMCs, and DNAme loss DMCs, in the sperm of DDT-exposed Greenland or South African men. Number of intermediate DMCs (DNAme between 20% and 80%) are indicated by grids and percentages on the bar graphs. See Excel Tables S1 and S2. (B) Scatter plot of overlapping DMCs in Greenland and South African sperm (3,472 overlapping DMCs). Orange dots correspond to DMCs that gain DNAme in both Greenland and South African sperm (2,180 DMCs; 62% of total DMCs). Blue dots correspond to DMCs that lose DNAme in both Greenland and South African sperm (422 DMCs; 12.1% of total DMCs). (C) Average percentage DNAme at DNAme gain or loss DMCs in Greenland or South African sperm relative to ${\log }_{10}$ serum $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene ($p,p\mathrm{\prime }$-DDE) concentration (in ng/mL) for each individual. Linear regression line is plotted in dashed black, and confidence interval is shaded in light gray. See Excel Tables S1 and S2. (D) Tracks at the ADARB2 locus showing percentage DNAme levels in Greenland and South African sperm categorized based on low or high serum $p,p\mathrm{\prime }$-DDE levels (Greenland: low in light blue $<350\text{\hspace{0.17em}ng}/\mathrm{mL}$, $n=17$ and high in dark blue $>900\text{\hspace{0.17em}ng}/\mathrm{mL}$, $n=18$; South Africa: low in yellow $<\mathrm{1,200}\text{\hspace{0.17em}ng}/\mathrm{mL}$, $n=19$ and high in brown $>\mathrm{14,000}\text{\hspace{0.17em}ng}/\mathrm{mL}$, $n=16$). All CpGs captured by MethylC-Capture-sequencing (MCC-seq) are represented in black, and intermediate CpGs are in gray. CpGs captured in the Greenland sperm data set are in blue, and CpGs captured in the South African sperm data set are in red. (E) Manhattan plots on hotspot analysis for Greenland (blue) or South African (orange) sperm. Cluster analysis was performed by calculating the ratio of DMCs with DNAme gain or loss over the total number of CpGs found within 1 Mb sliding windows over the genome; densities $>10\%$ (termed clusters) were extracted for further analysis. See Tables S5 and S6. Note: DDT, dichlorodiphenyltrichloroethane; $p,p\mathrm{\prime }$-DDE, $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene.

Figure 2.

Sperm differentially methylated regions association with TEs and regions that retain DNA methylation (DNAme) during embryogenesis. (A) Number of differentially methylated CpGs (DMCs), merged DMCs (mDMCs), and single CpGs in Greenland (dark blue) and South African (light orange) sperm. mDMCs were called by merging DMCs separated by a maximum distance of 500 bp. See Excel Tables S3 and S4. (B) Proportion of Greenlandic sperm mDMCs (6,787) that overlap South African sperm mDMCs ($\text{overlap}=\mathrm{1,187}$) and South African sperm mDMCs ($\text{overlap}=\mathrm{12,849}$) that overlap Greenlandic sperm mDMCs ($\text{overlap}=\mathrm{1,189}$). See Excel Tables S3 and S4. (C) Number of DNAme gain or loss mDMCs in Greenlandic or South African sperm. See Excel Tables S3 and S4. (D) Genomic distribution of mDMCs with DNAme gain or loss in Greenlandic or South African sperm relative to the transcriptional start site (TSS). (E–H) Selected significant pathways from GO analysis on genes at an mDMC with DNAme gain or loss in Greenlandic or South African sperm (weighed Fisher $p<0.05$). Size of circle corresponds to the number of genes from a significant pathway that overlap an mDMC. See Excel Tables S5–S8. (I) Enrichment of DNAme gain (dark blue for Greenlandic; dark red for South African) or loss (light blue for Greenlandic; bright yellow for South African) mDMCs in Greenlandic (white hashes) or South African (white dots) sperm at identified DNAme embryonic persistent regions [see Figure S3, primordial germ cell (PGC) escapees, and transposable element annotations (RepeatMasker hg19 library 20140131)]. Positive enrichments were determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from the targeted MCC-seq regions. (J) Distribution of DNAme gain (dark blue for Greenlandic; dark red for South African) or loss (light blue for Greenlandic; bright yellow for South African) mDMCs in Greenlandic (white hashes) or South African (white dots) sperm relative to age quarters of LTR-ERV1 TEs (significantly enriched in the four mDMC categories; Figure 2H). Age of LTR-ERV1 TEs was determined by partitioning the TEs’ percentage divergence scores into quarters, where first quarter = low percentage divergence and young LTR-ERV1; second quarter = mid-low percentage divergence and mid-young LTR-ERV1; third quarter = mid-high percentage divergence and mid-old LTR-ERV1; fourth quarter = high percentage divergence and old LTR-ERV1 (see Figure S3B). (K) Enrichment of DNAme gain (dark blue for Greenlandic; dark red for South African) or loss (light blue for Greenlandic; bright yellow for South African) mDMCs in Greenland (white hashes) or South African (white dots) sperm at putative tissue-specific enhancer classes. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from the targeted MCC-seq regions. Note: dyn, dynamic; GO, Gene Ontology; GTPase, guanosine triphosphatase; hESC, human embryonic stem cell; ICM, inner cell mass; MCC-seq, MethylC-Capture-sequencing; NMDA, NMDA, $N$-methyl-d-aspartate; $p,p\mathrm{\prime }$-DDE, $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene; TEs, transposable elements.

Figure 2.

Sperm differentially methylated regions association with TEs and regions that retain DNA methylation (DNAme) during embryogenesis. (A) Number of differentially methylated CpGs (DMCs), merged DMCs (mDMCs), and single CpGs in Greenland (dark blue) and South African (light orange) sperm. mDMCs were called by merging DMCs separated by a maximum distance of 500 bp. See Excel Tables S3 and S4. (B) Proportion of Greenlandic sperm mDMCs (6,787) that overlap South African sperm mDMCs ($\text{overlap}=\mathrm{1,187}$) and South African sperm mDMCs ($\text{overlap}=\mathrm{12,849}$) that overlap Greenlandic sperm mDMCs ($\text{overlap}=\mathrm{1,189}$). See Excel Tables S3 and S4. (C) Number of DNAme gain or loss mDMCs in Greenlandic or South African sperm. See Excel Tables S3 and S4. (D) Genomic distribution of mDMCs with DNAme gain or loss in Greenlandic or South African sperm relative to the transcriptional start site (TSS). (E–H) Selected significant pathways from GO analysis on genes at an mDMC with DNAme gain or loss in Greenlandic or South African sperm (weighed Fisher $p<0.05$). Size of circle corresponds to the number of genes from a significant pathway that overlap an mDMC. See Excel Tables S5–S8. (I) Enrichment of DNAme gain (dark blue for Greenlandic; dark red for South African) or loss (light blue for Greenlandic; bright yellow for South African) mDMCs in Greenlandic (white hashes) or South African (white dots) sperm at identified DNAme embryonic persistent regions [see Figure S3, primordial germ cell (PGC) escapees, and transposable element annotations (RepeatMasker hg19 library 20140131)]. Positive enrichments were determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from the targeted MCC-seq regions. (J) Distribution of DNAme gain (dark blue for Greenlandic; dark red for South African) or loss (light blue for Greenlandic; bright yellow for South African) mDMCs in Greenlandic (white hashes) or South African (white dots) sperm relative to age quarters of LTR-ERV1 TEs (significantly enriched in the four mDMC categories; Figure 2H). Age of LTR-ERV1 TEs was determined by partitioning the TEs’ percentage divergence scores into quarters, where first quarter = low percentage divergence and young LTR-ERV1; second quarter = mid-low percentage divergence and mid-young LTR-ERV1; third quarter = mid-high percentage divergence and mid-old LTR-ERV1; fourth quarter = high percentage divergence and old LTR-ERV1 (see Figure S3B). (K) Enrichment of DNAme gain (dark blue for Greenlandic; dark red for South African) or loss (light blue for Greenlandic; bright yellow for South African) mDMCs in Greenland (white hashes) or South African (white dots) sperm at putative tissue-specific enhancer classes. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from the targeted MCC-seq regions. Note: dyn, dynamic; GO, Gene Ontology; GTPase, guanosine triphosphatase; hESC, human embryonic stem cell; ICM, inner cell mass; MCC-seq, MethylC-Capture-sequencing; NMDA, NMDA, $N$-methyl-d-aspartate; $p,p\mathrm{\prime }$-DDE, $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene; TEs, transposable elements.

Figure 3.

Histone 3 lysine 4 trimethylation (H3K4me3) enrichment in sperm of South African men with different $p,p\mathrm{\prime }$-DDE serum levels. (A) Heatmap of normalized H3K4me3 counts at the 1,865 peaks with differentially enriched H3K4me3 (deH3K4me3; 851 peaks with H3K4me3 gain and 1,014 peaks with H3K4me3 loss; FDR $<0.2$) in sperm from South African men with low (ter1) or high (ter3) serum $p,p$-DDE levels. Serum $p,p$-DDE concentration, tertile, body mass index (BMI), and age of participants is indicated by colored boxes above the heatmap. (B) Genomic distribution of peaks with H3K4me3 gain in South African sperm relative to the TSS. (C) Genomic distribution of peaks with H3K4me3 loss in South African sperm relative to the TSS. (D–E) H3K4me3 signal intensity heatmaps at $\pm 5$ kb the center of the peaks with H3K4me3 gain in South African sperm (851 peaks) relative to the three $p,p$-DDE tertile levels. (E) H3K4me3 signal intensity heatmaps at $\pm 5$ kb the center of the peaks with H3K4me3 loss in South African sperm (1,014 peaks) relative to the three $p,p$-DDE tertile levels. (F) Estimator of the cumulative distribution function (ECDF) plot for ${\log }_2$ cpm of H3K4me3 counts at regions with H3K4me3 gain in ter1 (light yellow), ter2 (medium orange), and ter3 (dark red) sperm samples. Dose–response trends were assessed by via Kolmogorov–Smirnov tests with $p<0.0001$ for ter1 vs. ter2 at H3K4me3 gain regions, $p<0.05$. (G) ECDF plot for ${\log }_2$ cpm of H3K4me3 counts at regions with H3K4me3 gain in ter1 (dark green), ter2 (medium green), and ter3 (light green) sperm samples. Dose–response trends were assessed by via Kolmogorov–Smirnov tests with $p<0.0001$ for ter1 vs. ter2 at H3K4me3 gain regions, $p<0.0001$. (H) Representative Integrative Genome Viewer (IGV) tracks of peak with H3K4me3 gain in South African sperm at the FSIP1 genic region. (I) Representative IGV tracks of peak with H3K4me3 loss in South African sperm at the BRD1 promoter. Data for (A–I) are reported in Excel Table S15. Selected significant pathways for (J–K) are from GO analysis on genes with H3K4me3 gain (J) or loss (K) in South African sperm (weighed Fisher $p<0.05$). Size of circle corresponds to the number of genes from a significant pathway that overlap a peak with H3K4me3 gain. Shade intensity of the circle indicates $-{\log }_2$ (weightFisher) value of significant pathway. See Excel Tables S16 and S17. Note: cpm, counts per minute; GO, Gene Ontology; $p,p\mathrm{\prime }$-DDE, $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene; ter, tertile; TSS, transcriptional start site.

Figure 3.

Histone 3 lysine 4 trimethylation (H3K4me3) enrichment in sperm of South African men with different $p,p\mathrm{\prime }$-DDE serum levels. (A) Heatmap of normalized H3K4me3 counts at the 1,865 peaks with differentially enriched H3K4me3 (deH3K4me3; 851 peaks with H3K4me3 gain and 1,014 peaks with H3K4me3 loss; FDR $<0.2$) in sperm from South African men with low (ter1) or high (ter3) serum $p,p$-DDE levels. Serum $p,p$-DDE concentration, tertile, body mass index (BMI), and age of participants is indicated by colored boxes above the heatmap. (B) Genomic distribution of peaks with H3K4me3 gain in South African sperm relative to the TSS. (C) Genomic distribution of peaks with H3K4me3 loss in South African sperm relative to the TSS. (D–E) H3K4me3 signal intensity heatmaps at $\pm 5$ kb the center of the peaks with H3K4me3 gain in South African sperm (851 peaks) relative to the three $p,p$-DDE tertile levels. (E) H3K4me3 signal intensity heatmaps at $\pm 5$ kb the center of the peaks with H3K4me3 loss in South African sperm (1,014 peaks) relative to the three $p,p$-DDE tertile levels. (F) Estimator of the cumulative distribution function (ECDF) plot for ${\log }_2$ cpm of H3K4me3 counts at regions with H3K4me3 gain in ter1 (light yellow), ter2 (medium orange), and ter3 (dark red) sperm samples. Dose–response trends were assessed by via Kolmogorov–Smirnov tests with $p<0.0001$ for ter1 vs. ter2 at H3K4me3 gain regions, $p<0.05$. (G) ECDF plot for ${\log }_2$ cpm of H3K4me3 counts at regions with H3K4me3 gain in ter1 (dark green), ter2 (medium green), and ter3 (light green) sperm samples. Dose–response trends were assessed by via Kolmogorov–Smirnov tests with $p<0.0001$ for ter1 vs. ter2 at H3K4me3 gain regions, $p<0.0001$. (H) Representative Integrative Genome Viewer (IGV) tracks of peak with H3K4me3 gain in South African sperm at the FSIP1 genic region. (I) Representative IGV tracks of peak with H3K4me3 loss in South African sperm at the BRD1 promoter. Data for (A–I) are reported in Excel Table S15. Selected significant pathways for (J–K) are from GO analysis on genes with H3K4me3 gain (J) or loss (K) in South African sperm (weighed Fisher $p<0.05$). Size of circle corresponds to the number of genes from a significant pathway that overlap a peak with H3K4me3 gain. Shade intensity of the circle indicates $-{\log }_2$ (weightFisher) value of significant pathway. See Excel Tables S16 and S17. Note: cpm, counts per minute; GO, Gene Ontology; $p,p\mathrm{\prime }$-DDE, $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene; ter, tertile; TSS, transcriptional start site.

Figure 4.

Overlap between peaks with H3K4me3 loss in South African sperm, TEs, and regions that retain H3K4me3 in the preimplantation embryo. (A) Enrichment for peaks with H3K4me3 gain in South African sperm at transposable element annotations (RepeatMasker hg19 library 20140131). Positive and negative enrichments were determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from sperm H3K4me3 peaks. (B) Enrichment for peaks with H3K4me3 loss in South African sperm at transposable element annotations (RepeatMasker hg19 library 20140131). Positive and negative enrichments were determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from sperm H3K4me3 peaks. (C) Distribution for peaks with H3K4me3 gain in South African sperm relative to age quarters of LINE-1 and LTR ERV-MaLR transposable element classes [significantly enriched for peaks with H3K4me3 gain (A)]. Age of TEs was determined by partitioning the class percentage divergence score in quarters (see Figure S4G,H). (D) Distribution for peaks with H3K4me3 loss in South African sperm relative to age quarters of LINE-2, SINE-MIR, and SINE-Alu transposable element classes [significantly enriched for peaks with H3K4me3 loss (B)]. Age of TEs was determined by partitioning the class percentage divergence score in quarters (see Figure S4I–K). (E) Genomic distribution of peaks with H3K4me3 gain in South African sperm that overlap an old (4th quarter) LINE-1 (139) or LTR ERVL-MaLR (74) transposable element, relative to the TSS. (F) Genomic distribution of peaks with H3K4me3 loss in South African sperm that overlap a young (1st quarter) LINE-2 (187), SINE-MIR (267), or SINE-Alu (507) transposable element, relative to the TSS. (G) Selected significant pathways from GO analysis on promoter peaks with H3K4me3 loss in sperm that overlap a young (1st quarter) LINE-2 (324 promoters), SINE-MIR (442 promoters), or SINE-Alu (809 promoters) TEs at (weighed Fisher $p<0.05$). Size of dots corresponds to the number of genes from a significant pathway that overlap a peak with H3K4me3 loss. Color of the dots indicates $-{\log }_2$ (weightFisher) value of significant pathway. See Excel Tables S18–S20. (H) Enrichment for peaks with H3K4me3 gain (yellow) or loss (green) in South African sperm at tissue-specific putative enhancer annotations. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from sperm H3K4me3 peaks. Data are reported in Excel Table S19. (I) Sperm and preimplantation embryo (4-cell, 8-cell, ICM) H3K4me3 signal intensity heatmaps at $\pm 5$ kb the center of the peaks with H3K4me3 gain in South African sperm (851 peaks). Data are reported in Excel Table S20. (J) Sperm and preimplantation embryo (4-cell, 8-cell, ICM) H3K4me3 signal intensity heatmaps at $\pm 5$ kb the center of the peaks with H3K4me3 loss in South African sperm (1,014 peaks). (K–M) Scatter plots where the x-axis corresponds to the ${\log }_2$ (preimplantation embryo H3K4me3 promoter counts $+1$) and the y-axis corresponds to the ${\log }_2$ (sperm H3K4me3 promoter counts $+1$) at promoters with H3K4me3 loss in South African sperm that are expressed at the described stages of preimplantation embryo development (RPKM $>1$). Color of the scatter points correspond to the ${\log }_2$ preimplantation embryo RPKM gene expression $+1$. Dashed lines correspond to H3K4me3 promoter density cutoffs for preimplantation embryo (x-axis) or sperm (y-axis). Gray box denotes promoters with H3K4me3 in sperm and 4-cell (K), 8-cell (L), and ICM (M) preimplantation embryos. Note: GO, Gene Ontology; H3K4me3, histone H3 lysine 4 trimethylation; hESC, human embryonic stem cell; ICM, inner cell mass; NMDA, $N$-methyl-d-aspartate; NPC, neural progenitor cell; RPKM, reads per kilobase per million mapped reads; TEs, transposable elements; TSS, transcriptional start site.

Figure 4.

Overlap between peaks with H3K4me3 loss in South African sperm, TEs, and regions that retain H3K4me3 in the preimplantation embryo. (A) Enrichment for peaks with H3K4me3 gain in South African sperm at transposable element annotations (RepeatMasker hg19 library 20140131). Positive and negative enrichments were determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from sperm H3K4me3 peaks. (B) Enrichment for peaks with H3K4me3 loss in South African sperm at transposable element annotations (RepeatMasker hg19 library 20140131). Positive and negative enrichments were determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from sperm H3K4me3 peaks. (C) Distribution for peaks with H3K4me3 gain in South African sperm relative to age quarters of LINE-1 and LTR ERV-MaLR transposable element classes [significantly enriched for peaks with H3K4me3 gain (A)]. Age of TEs was determined by partitioning the class percentage divergence score in quarters (see Figure S4G,H). (D) Distribution for peaks with H3K4me3 loss in South African sperm relative to age quarters of LINE-2, SINE-MIR, and SINE-Alu transposable element classes [significantly enriched for peaks with H3K4me3 loss (B)]. Age of TEs was determined by partitioning the class percentage divergence score in quarters (see Figure S4I–K). (E) Genomic distribution of peaks with H3K4me3 gain in South African sperm that overlap an old (4th quarter) LINE-1 (139) or LTR ERVL-MaLR (74) transposable element, relative to the TSS. (F) Genomic distribution of peaks with H3K4me3 loss in South African sperm that overlap a young (1st quarter) LINE-2 (187), SINE-MIR (267), or SINE-Alu (507) transposable element, relative to the TSS. (G) Selected significant pathways from GO analysis on promoter peaks with H3K4me3 loss in sperm that overlap a young (1st quarter) LINE-2 (324 promoters), SINE-MIR (442 promoters), or SINE-Alu (809 promoters) TEs at (weighed Fisher $p<0.05$). Size of dots corresponds to the number of genes from a significant pathway that overlap a peak with H3K4me3 loss. Color of the dots indicates $-{\log }_2$ (weightFisher) value of significant pathway. See Excel Tables S18–S20. (H) Enrichment for peaks with H3K4me3 gain (yellow) or loss (green) in South African sperm at tissue-specific putative enhancer annotations. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions (of the same size) resampled from sperm H3K4me3 peaks. Data are reported in Excel Table S19. (I) Sperm and preimplantation embryo (4-cell, 8-cell, ICM) H3K4me3 signal intensity heatmaps at $\pm 5$ kb the center of the peaks with H3K4me3 gain in South African sperm (851 peaks). Data are reported in Excel Table S20. (J) Sperm and preimplantation embryo (4-cell, 8-cell, ICM) H3K4me3 signal intensity heatmaps at $\pm 5$ kb the center of the peaks with H3K4me3 loss in South African sperm (1,014 peaks). (K–M) Scatter plots where the x-axis corresponds to the ${\log }_2$ (preimplantation embryo H3K4me3 promoter counts $+1$) and the y-axis corresponds to the ${\log }_2$ (sperm H3K4me3 promoter counts $+1$) at promoters with H3K4me3 loss in South African sperm that are expressed at the described stages of preimplantation embryo development (RPKM $>1$). Color of the scatter points correspond to the ${\log }_2$ preimplantation embryo RPKM gene expression $+1$. Dashed lines correspond to H3K4me3 promoter density cutoffs for preimplantation embryo (x-axis) or sperm (y-axis). Gray box denotes promoters with H3K4me3 in sperm and 4-cell (K), 8-cell (L), and ICM (M) preimplantation embryos. Note: GO, Gene Ontology; H3K4me3, histone H3 lysine 4 trimethylation; hESC, human embryonic stem cell; ICM, inner cell mass; NMDA, $N$-methyl-d-aspartate; NPC, neural progenitor cell; RPKM, reads per kilobase per million mapped reads; TEs, transposable elements; TSS, transcriptional start site.

Figure 5.

Intersection between differentially enriched H3K4me3 (deH3K4me3) peaks and merged differentially methylated CpGs (mDMCs) in sperm of South African men with different $p,p\mathrm{\prime }$-DDE serum levels. (A) Proportion of MCC-seq target regions that overlap a H3K4me3 peak in sperm ($\text{overlap}=\mathrm{157,753}$; dark gray donut plot), proportion of H3K4me3 peaks in sperm that overlap a MCC-seq target region ($\text{overlap}=\mathrm{34,741}$; light gray donut plot), proportion of South Africa mDMCs that overlap a H3K4me3 peak in sperm ($\text{overlap}=\mathrm{1,744}$; dark green donut plot), proportion of H3K4me3 peaks in sperm that intersect a South Africa mDMC ($\text{overlap}=\mathrm{1,618}$; light green), proportion of South Africa mDMCs that overlap a deH3K4me3 peak in sperm ($\text{overlap}=106$; dark blue), proportion of South Africa deH3K4me3 peaks in sperm that intersect an mDMC in sperm ($\text{overlap}=99$; light blue). (B) Scatter plot corresponding to South African population ter3 to ter1 ${\log }_2$-fold change (H3K4me3 counts at overlapping mDMCs $+1$) relative to South Africa beta value at the mDMCs. Gray dots correspond to mDMCs that do not overlap with a deH3K4me3 peak. mDMCs intersecting a deH3K4me3 peak are denoted by color. H3K4me3 loss + DNAme gain overlap was the predominant overlap ($n=88$ of 106). (C) Distribution of peaks with H3K4me3 loss overlapped to DNAme gain mDMC (light blue) and DNAme gain mDMC overlapped to H3K4me3 loss region (dark green) relative to the TSS. (D) Enrichment for peaks with H3K4me3 loss overlapped to DNAme gain mDMC (light blue) and DNAme gain mDMC overlapped to H3K4me3 loss region (dark green) at genic and CpG annotations. Positive enrichments are determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions resampled from deH3K4me3 peaks (light blue) and mDMCs (dark green), respectively. (E) Enrichment for peaks with H3K4me3 loss overlapped to DNAme gain mDMC (blue) and DNAme gain mDMC overlapped to H3K4me3 loss region (green) at TE annotations and characterized DNAme/H3K4me3 persistent regions (see Figure S2 and S5). Positive enrichments are determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions resampled from deH3K4me3 peaks (light blue) and mDMCs (dark green), respectively. (F) Selected significant pathways from GO analysis on peak with H3K4me3 loss that overlaps a DNAme gain mDMC at promoters and 1–5 kb genic space. Size of dots corresponds to the number of significant genes in the pathway. Color and position of dots correspond to $-{\log }_2$ (weightFisher). See Excel Table S27. (G) Representative IGV tracks of peak with H3K4me3 loss and DNAme gain in South African sperm at an LTR-ERV1 and in the TRAPPC9 genic space. Purple shaded box corresponds to the mDMC. Tracks below are a zoom at the mDMC. Intermediate CpGs are indicated in purple. Note: ChiP-Seq, chromatin immunoprecipitation targeting histone H3K4me3 followed by sequencing; DNAme, DNA methylation; GO, Gene Ontology; H3K4me3, histone H3 lysine 4 trimethylation; hESC, human embryonic stem cell; ICM, inner cell mass; IGV, Integrative Genome Viewer; int, intermediate; MCC-seq, MethylC-Capture-sequencing; $p,p\mathrm{\prime }$-DDE, $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene; TE, transposable element; ter, tertile; TSS, transcriptional start site; UTR, untranslated region.

Figure 5.

Intersection between differentially enriched H3K4me3 (deH3K4me3) peaks and merged differentially methylated CpGs (mDMCs) in sperm of South African men with different $p,p\mathrm{\prime }$-DDE serum levels. (A) Proportion of MCC-seq target regions that overlap a H3K4me3 peak in sperm ($\text{overlap}=\mathrm{157,753}$; dark gray donut plot), proportion of H3K4me3 peaks in sperm that overlap a MCC-seq target region ($\text{overlap}=\mathrm{34,741}$; light gray donut plot), proportion of South Africa mDMCs that overlap a H3K4me3 peak in sperm ($\text{overlap}=\mathrm{1,744}$; dark green donut plot), proportion of H3K4me3 peaks in sperm that intersect a South Africa mDMC ($\text{overlap}=\mathrm{1,618}$; light green), proportion of South Africa mDMCs that overlap a deH3K4me3 peak in sperm ($\text{overlap}=106$; dark blue), proportion of South Africa deH3K4me3 peaks in sperm that intersect an mDMC in sperm ($\text{overlap}=99$; light blue). (B) Scatter plot corresponding to South African population ter3 to ter1 ${\log }_2$-fold change (H3K4me3 counts at overlapping mDMCs $+1$) relative to South Africa beta value at the mDMCs. Gray dots correspond to mDMCs that do not overlap with a deH3K4me3 peak. mDMCs intersecting a deH3K4me3 peak are denoted by color. H3K4me3 loss + DNAme gain overlap was the predominant overlap ($n=88$ of 106). (C) Distribution of peaks with H3K4me3 loss overlapped to DNAme gain mDMC (light blue) and DNAme gain mDMC overlapped to H3K4me3 loss region (dark green) relative to the TSS. (D) Enrichment for peaks with H3K4me3 loss overlapped to DNAme gain mDMC (light blue) and DNAme gain mDMC overlapped to H3K4me3 loss region (dark green) at genic and CpG annotations. Positive enrichments are determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions resampled from deH3K4me3 peaks (light blue) and mDMCs (dark green), respectively. (E) Enrichment for peaks with H3K4me3 loss overlapped to DNAme gain mDMC (blue) and DNAme gain mDMC overlapped to H3K4me3 loss region (green) at TE annotations and characterized DNAme/H3K4me3 persistent regions (see Figure S2 and S5). Positive enrichments are determined by $z$-scores using the Bioconductor package regioneR. For all annotations displayed, $p<0.0001$ and $n=\mathrm{10,000}$ permutations of random regions resampled from deH3K4me3 peaks (light blue) and mDMCs (dark green), respectively. (F) Selected significant pathways from GO analysis on peak with H3K4me3 loss that overlaps a DNAme gain mDMC at promoters and 1–5 kb genic space. Size of dots corresponds to the number of significant genes in the pathway. Color and position of dots correspond to $-{\log }_2$ (weightFisher). See Excel Table S27. (G) Representative IGV tracks of peak with H3K4me3 loss and DNAme gain in South African sperm at an LTR-ERV1 and in the TRAPPC9 genic space. Purple shaded box corresponds to the mDMC. Tracks below are a zoom at the mDMC. Intermediate CpGs are indicated in purple. Note: ChiP-Seq, chromatin immunoprecipitation targeting histone H3K4me3 followed by sequencing; DNAme, DNA methylation; GO, Gene Ontology; H3K4me3, histone H3 lysine 4 trimethylation; hESC, human embryonic stem cell; ICM, inner cell mass; IGV, Integrative Genome Viewer; int, intermediate; MCC-seq, MethylC-Capture-sequencing; $p,p\mathrm{\prime }$-DDE, $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene; TE, transposable element; ter, tertile; TSS, transcriptional start site; UTR, untranslated region.

Figure 6.

Overview and author interpretation of the main findings; a summary of the consequences of $p,p\mathrm{\prime }$-DDE exposure on the sperm epigenome of Greenlandic Inuit and South African VhaVenda men and the health implications for the next generation. We assessed the sperm epigenome (DNAme and H3K4me3) of two geographically diverse populations, Greenlandic Inuit and South African men, in relationship to $p,p\mathrm{\prime }$-DDE serum levels. Dose–response trends between sperm DNAme/H3K4me3 and $p,p\mathrm{\prime }$-DDE serum levels were observed within both populations. Regions with altered epigenetic marks in sperm were related to neurodevelopment and fertility, co-localized to young TEs, and overlapped regions that were predicted to resist epigenetic reprogramming in the preimplantation embryo. Note: ADD, attention deficit disorder; ADHD, attention deficit/hyperactivity disorder; ChIP-seq, chromatin immunoprecipitation targeting histone H3K4me3 followed by sequencing; DDT, dichlorodiphenyltrichloroethane; DMCs, differentially methylated CpGs; DNAme, DNA methylation; H3K4me3, histone H3 lysine 4 trimethylation; $p,p\mathrm{\prime }$-DDE, $p,p\mathrm{\prime }$-dichlorodiphenyldichloroethylene; TEs, transposable elements.