Perfluorooctanoic acid (PFOA) or perfluorooctane sulfonate (PFOS) and DNA methylation in newborn dried blood spots in the Upstate KIDS cohort.

Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are persistent organic pollutants which may alter prenatal development, potentially through epigenetic modifications. Prior studies examining PFOS/PFOA and DNA methylation have relatively few subjects (n < 200) and inconsistent results. We examined relations of PFOA/PFOS with DNA methylation among 597 neonates in the Upstate KIDS cohort study. PFOA/PFOS were quantified in newborn dried blood spots (DBS) using high-performance liquid chromatography/tandem mass spectrometry. DNA methylation was measured using the Infinium MethylationEPIC BeadChip with DNA extracted from DBS. Robust linear regression was used to examine the associations of PFOA/PFOS with DNA methylation at individual CpG sites. Covariates included sample plate, estimated cell type, epigenetically derived ancestry, infant sex and plurality, indicators of maternal socioeconomic status, and prior pregnancy loss. In supplemental analysis, we restricted the analysis to 2242 CpG sites previously identified as Correlated Regions of Systemic Interindividual Variation (CoRSIVs) which include metastable epialleles. At FDR<0.05, PFOA concentration >90th percentile was related to DNA methylation at cg15557840, near SCRT2, SRXN1; PFOS>90th percentile was related to 2 CpG sites in a sex-specific manner (cg19039925 in GVIN1 in boys and cg05754408 in ZNF26 in girls). When analysis was restricted to CoRSIVs, log-scaled, continuous PFOS concentration was related to DNA methylation at cg03278866 within PTBP1. In conclusion, there was limited evidence of an association between high concentrations of PFOA/PFOS and DNA methylation in newborn DBS in the Upstate KIDS cohort. These findings merit replication in populations with a higher median concentration of PFOA/PFOS.

Co-expression analysis aids in the identification of genes in the cuticular wax pathway in maize.

Epicuticular waxes provide a hydrophobic barrier that protects land plants from environmental stresses. To elucidate the molecular functions of maize glossy mutants that reduce the accumulation of epicuticular waxes, eight non-allelic glossy mutants were subjected to transcriptomic comparisons with their respective wild-type siblings. Transcriptomic comparisons identified 2279 differentially expressed (DE) genes. Other glossy genes tended to be down-regulated in glossy mutants; by contrast stress-responsive pathways were induced in mutants. Gene co-expression network (GCN) analysis found that glossy genes were clustered, suggestive of co-regulation. Genes that potentially regulate the accumulation of glossy gene transcripts were identified via a pathway level co-expression analysis. Expression data from diverse organs showed that maize glossy genes are generally active in young leaves, silks, and tassels, while largely inactive in seeds and roots. Through reverse genetics, a DE gene homologous to Arabidopsis CER8 and co-expressed with known glossy genes was confirmed to participate in epicuticular wax accumulation. GCN data-informed forward genetics approach enabled cloning of the gl14 gene, which encodes a putative membrane-associated protein. Our results deepen understanding of the transcriptional regulation of the genes involved in the accumulation of epicuticular wax, and provide two maize glossy genes and a number of candidate genes for further characterization.

Systemic interindividual DNA methylation variants in cattle share major hallmarks with those in humans.

BACKGROUND: We recently identified ~ 10,000 correlated regions of systemic interindividual epigenetic variation (CoRSIVs) in the human genome. These methylation variants are amenable to population studies, as DNA methylation measurements in blood provide information on epigenetic regulation throughout the body. Moreover, establishment of DNA methylation at human CoRSIVs is labile to periconceptional influences such as nutrition. Here, we analyze publicly available whole-genome bisulfite sequencing data on multiple tissues of each of two Holstein cows to determine whether CoRSIVs exist in cattle. RESULTS: Focusing on genomic blocks with ≥ 5 CpGs and a systemic interindividual variation index of at least 20, our approach identifies 217 cattle CoRSIVs, a subset of which we independently validate by bisulfite pyrosequencing. Similar to human CoRSIVs, those in cattle are strongly associated with genetic variation. Also as in humans, we show that establishment of DNA methylation at cattle CoRSIVs is particularly sensitive to early embryonic environment, in the context of embryo culture during assisted reproduction. CONCLUSIONS: Our data indicate that CoRSIVs exist in cattle, as in humans, suggesting these systemic epigenetic variants may be common to mammals in general. To the extent that individual epigenetic variation at cattle CoRSIVs affects phenotypic outcomes, assessment of CoRSIV methylation at birth may become an important tool for optimizing agriculturally important traits. Moreover, adjusting embryo culture conditions during assisted reproduction may provide opportunities to tailor agricultural outcomes by engineering CoRSIV methylation profiles.

Systemic interindividual epigenetic variation in humans is associated with transposable elements and under strong genetic control.

BACKGROUND: Genetic variants can modulate phenotypic outcomes via epigenetic intermediates, for example at methylation quantitative trait loci (mQTL). We present the first large-scale assessment of mQTL at human genomic regions selected for interindividual variation in CpG methylation, which we call correlated regions of systemic interindividual variation (CoRSIVs). These can be assayed in blood DNA and do not reflect interindividual variation in cellular composition. RESULTS: We use target-capture bisulfite sequencing to assess DNA methylation at 4086 CoRSIVs in multiple tissues from each of 188 donors in the NIH Gene-Tissue Expression (GTEx) program. At CoRSIVs, DNA methylation in peripheral blood correlates with methylation and gene expression in internal organs. We also discover unprecedented mQTL at these regions. Genetic influences on CoRSIV methylation are extremely strong (median R2=0.76), cumulatively comprising over 70-fold more human mQTL than detected in the most powerful previous study. Moreover, mQTL beta coefficients at CoRSIVs are highly skewed (i.e., the major allele predicts higher methylation). Both surprising findings are independently validated in a cohort of 47 non-GTEx individuals. Genomic regions flanking CoRSIVs show long-range enrichments for LINE-1 and LTR transposable elements; the skewed beta coefficients may therefore reflect evolutionary selection of genetic variants that promote their methylation and silencing. Analyses of GWAS summary statistics show that mQTL polymorphisms at CoRSIVs are associated with metabolic and other classes of disease. CONCLUSIONS: A focus on systemic interindividual epigenetic variants, clearly enhanced in mQTL content, should likewise benefit studies attempting to link human epigenetic variation to the risk of disease.

Sex-specific epigenetic development in the mouse hypothalamic arcuate nucleus pinpoints human genomic regions associated with body mass index.

Recent genome-wide association studies corroborate classical research on developmental programming indicating that obesity is primarily a neurodevelopmental disease strongly influenced by nutrition during critical ontogenic windows. Epigenetic mechanisms regulate neurodevelopment; however, little is known about their role in establishing and maintaining the brain's energy balance circuitry. We generated neuron and glia methylomes and transcriptomes from male and female mouse hypothalamic arcuate nucleus, a key site for energy balance regulation, at time points spanning the closure of an established critical window for developmental programming of obesity risk. We find that postnatal epigenetic maturation is markedly cell type and sex specific and occurs in genomic regions enriched for heritability of body mass index in humans. Our results offer a potential explanation for both the limited ontogenic windows for and sex differences in sensitivity to developmental programming of obesity and provide a rich resource for epigenetic analyses of developmental programming of energy balance.

A machine learning case-control classifier for schizophrenia based on DNA methylation in blood.

Epigenetic dysregulation is thought to contribute to the etiology of schizophrenia (SZ), but the cell type-specificity of DNA methylation makes population-based epigenetic studies of SZ challenging. To train an SZ case-control classifier based on DNA methylation in blood, therefore, we focused on human genomic regions of systemic interindividual epigenetic variation (CoRSIVs), a subset of which are represented on the Illumina Human Methylation 450K (HM450) array. HM450 DNA methylation data on whole blood of 414 SZ cases and 433 non-psychiatric controls were used as training data for a classification algorithm with built-in feature selection, sparse partial least squares discriminate analysis (SPLS-DA); application of SPLS-DA to HM450 data has not been previously reported. Using the first two SPLS-DA dimensions we calculated a "risk distance" to identify individuals with the highest probability of SZ. The model was then evaluated on an independent HM450 data set on 353 SZ cases and 322 non-psychiatric controls. Our CoRSIV-based model classified 303 individuals as cases with a positive predictive value (PPV) of 80%, far surpassing the performance of a model based on polygenic risk score (PRS). Importantly, risk distance (based on CoRSIV methylation) was not associated with medication use, arguing against reverse causality. Risk distance and PRS were positively correlated (Pearson r = 0.28, P = 1.28 × 10-12), and mediational analysis suggested that genetic effects on SZ are partially mediated by altered methylation at CoRSIVs. Our results indicate two innate dimensions of SZ risk: one based on genetic, and the other on systemic epigenetic variants.

DNA methylation at a nutritionally sensitive region of the PAX8 gene is associated with thyroid volume and function in Gambian children.

PAX8 is a key thyroid transcription factor implicated in thyroid gland differentiation and function, and PAX8 gene methylation is reported to be sensitive to the periconceptional environment. Using a novel recall-by-epigenotype study in Gambian children, we found that PAX8 hypomethylation at age 2 years is associated with a 21% increase in thyroid volume and an increase in free thyroxine (T4) at 5 to 8 years, the latter equivalent to 8.4% of the normal range. Free T4 was associated with a decrease in DXA-derived body fat and bone mineral density. Furthermore, offspring PAX8 methylation was associated with periconceptional maternal nutrition, and methylation variability was influenced by genotype, suggesting that sensitivity to environmental exposures may be under partial genetic control. Together, our results demonstrate a possible link between early environment, PAX8 gene methylation and thyroid gland development and function, with potential implications for early embryonic programming of thyroid-related health and disease.

Identification of cell type-specific methylation signals in bulk whole genome bisulfite sequencing data.

BACKGROUND: The traditional approach to studying the epigenetic mechanism CpG methylation in tissue samples is to identify regions of concordant differential methylation spanning multiple CpG sites (differentially methylated regions). Variation limited to single or small numbers of CpGs has been assumed to reflect stochastic processes. To test this, we developed software, Cluster-Based analysis of CpG methylation (CluBCpG), and explored variation in read-level CpG methylation patterns in whole genome bisulfite sequencing data. RESULTS: Analysis of both human and mouse whole genome bisulfite sequencing datasets reveals read-level signatures associated with cell type and cell type-specific biological processes. These signatures, which are mostly orthogonal to classical differentially methylated regions, are enriched at cell type-specific enhancers and allow estimation of proportional cell composition in synthetic mixtures and improved prediction of gene expression. In tandem, we developed a machine learning algorithm, Precise Read-Level Imputation of Methylation (PReLIM), to increase coverage of existing whole genome bisulfite sequencing datasets by imputing CpG methylation states on individual sequencing reads. PReLIM both improves CluBCpG coverage and performance and enables identification of novel differentially methylated regions, which we independently validate. CONCLUSIONS: Our data indicate that, rather than stochastic variation, read-level CpG methylation patterns in tissue whole genome bisulfite sequencing libraries reflect cell type. Accordingly, these new computational tools should lead to an improved understanding of epigenetic regulation by DNA methylation.

A genomic atlas of systemic interindividual epigenetic variation in humans.

BACKGROUND: DNA methylation is thought to be an important determinant of human phenotypic variation, but its inherent cell type specificity has impeded progress on this question. At exceptional genomic regions, interindividual variation in DNA methylation occurs systemically. Like genetic variants, systemic interindividual epigenetic variants are stable, can influence phenotype, and can be assessed in any easily biopsiable DNA sample. We describe an unbiased screen for human genomic regions at which interindividual variation in DNA methylation is not tissue-specific. RESULTS: For each of 10 donors from the NIH Genotype-Tissue Expression (GTEx) program, CpG methylation is measured by deep whole-genome bisulfite sequencing of genomic DNA from tissues representing the three germ layer lineages: thyroid (endoderm), heart (mesoderm), and brain (ectoderm). We develop a computational algorithm to identify genomic regions at which interindividual variation in DNA methylation is consistent across all three lineages. This approach identifies 9926 correlated regions of systemic interindividual variation (CoRSIVs). These regions, comprising just 0.1% of the human genome, are inter-correlated over long genomic distances, associated with transposable elements and subtelomeric regions, conserved across diverse human ethnic groups, sensitive to periconceptional environment, and associated with genes implicated in a broad range of human disorders and phenotypes. CoRSIV methylation in one tissue can predict expression of associated genes in other tissues. CONCLUSIONS: In addition to charting a previously unexplored molecular level of human individuality, this atlas of human CoRSIVs provides a resource for future population-based investigations into how interindividual epigenetic variation modulates risk of disease.