Differentially Methylated Cytosines Research Articles

Abstract B033: Identification of cell-specific DNA methylation alterations in the breast tumor microenvironment

Abstract The tumor microenvironment (TME) comprises diverse cell types whose interactions are crucial for cancer progression. Traditional bulk tissue analyses mask cell-type-specific epigenetic changes that may drive disease progression. We used DNA methylation data and a reference- based cell-type deconvolution algorithm — hierarchical tumor immune microenvironment epigenetic deconvolution (HiTIMED) — to quantify cell types in the TME. Then, we employed CellDMC, a statistical interaction testing framework that can use cell type proportions in conjunction with differential methylation analysis to identify cell-specific differential methylation. Genome-scale DNA methylation profiles from breast cancer tissue (n=609) and normal breast tissue (n=230) samples were accessed in GEO and GTEx. Our novel approach leverages bulk DNA methylation data to infer cell-type-specific epigenetic landscapes, circumventing challenges and limitations associated with direct single-cell methylation profiling, such as high costs and technical variability. Reference-based computational tools allow us to dissect complex tissue compositions and reveal distinct methylation patterns and pathways that may be unique to individual cell types, providing insights that are not discernible from traditional bulk tumor analysis approaches. Compared with nontumor normal samples, we identified significant DNA methylation alterations (FDR≤0.05) across tumor, stromal, endothelial, epithelial, lymphocytes, and myeloid cells in breast tumors. Tumor cells exhibited the highest number, 8,510, differentially methylated cytosines (DMCs) with 1,966 of these unique to tumor cells. Stromal, endothelial, and epithelial cells also showed considerable methylation alterations, with a total of 530, 440, 339 DMCs, respectively, with 5 DMCs unique to epithelial cells. Despite lower immune cell proportions in our samples, we identified 104 lymphocyte specific DMCs and 185 myeloid specific DMCs, with 14 and 20 DMCs unique to these cell types respectively. The unique DMCs identified in each cell type suggest distinct epigenetic landscapes that may drive specific cellular functions and interactions within the TME. Importantly, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the annotated cell-type-specific DMCs revealed distinct pathways that were not apparent in the pathway analysis of bulk tumor versus normal tissue, underscoring the value of examining epigenetic alterations at the cell-type level. Our findings highlight the opportunity to leverage DNA-based cell typing with DNA methylation data to discern cell-specific molecular alterations. By focusing on cell-type-specific alterations, we can better understand the epigenetic mechanisms driving TME crosstalk, such as the activation of stromal cells and the modulation of immune responses by tumor cells. Our findings underscore the need for targeted therapeutic strategies that consider the unique epigenetic landscapes of individual cell types within the TME, offering new avenues for improving cancer treatment outcomes. Citation Format: Barbara Karakyriakou, Brock C. Christensen, Lucas A. Salas. Identification of cell-specific DNA methylation alterations in the breast tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B033.

Epigenetic memory of temperature sensed during somatic embryo maturation in 2-year-old maritime pine trees.

Embryogenesis is a brief but potentially critical phase in the tree life cycle for adaptive phenotypic plasticity. Using somatic embryogenesis in maritime pine (Pinus pinaster Ait.), we found that temperature during the maturation phase affects embryo development and post-embryonic tree growth for up to three years. We examined whether this somatic stress memory could stem from temperature- and/or development-induced changes in DNA methylation. For this, we developed a 200 Mb custom sequence capture bisulfite analysis of genes and promoters to identify differentially methylated cytosines (DMCs) between temperature treatments (18, 23, and 28°C) and developmental stages (immature and cotyledonary embryos, shoot apical meristem of 2-year-old plants) and investigate if these differences can be mitotically transmitted from embryonic to post-embryonic development (epigenetic memory). We revealed a high prevalence of temperature-induced DMCs in genes (8-14%) compared to promoters (less than 1%) in all 3 cytosine contexts. Developmental DMCs showed a comparable pattern but only in the CG context and with a strong trend towards hypomethylation, particularly in the promoters. A high percentage of DMCs induced by developmental transitions were found memorized in genes (up to 45-50%) and promoters (up to 90%). In contrast, temperature-induced memory was lower and confined to genes after both embryonic (up to 14%) and post-embryonic development (up to 8%). Using stringent criteria, we identified ten genes involved in defense responses and adaptation, embryo development, and chromatin regulation that are candidates for the establishment of a persistent epigenetic memory of temperature sensed during embryo maturation in maritime pine. Here, we provide evidence that DNA methylation marks established during the embryonic phase are transmitted to the post-embryonic plant development phase.

Adjusting methylation levels with nucleus proportions highlights functional significance of differentially methylated cytosines associated with pre-eclampsia.

Studies on DNA methylation alterations associated with pre-eclampsia (PE) have improved our understanding of the mechanisms underlying this disorder. However, differentially methylated cytosines (DMCs) have not been adjusted for cell-type heterogeneity, hampering the identification of alterations that drive disease risk. Using a reference-based, cell-type deconvolution approach, we estimated the nuclear proportions of 335 placental samples based on DNA methylation data. We found that the nuclei of total trophoblast lineages accounted for more than 80% of the placental samples, with a significant increase in PE placentas. The nuclear proportions of stromal and Hofbauer cells decreased in PE placentas. Our nuclear proportion estimation reflected previous histological knowledge on the changes in cell type proportions in PE placentas. We corrected 2125 DMCs associated with early-onset PE for cell-type heterogeneity by adjusting for the nuclear proportions and observed a notable reduction in the association signals, with 145 probes not reaching epigenome-wide significance. After correction, the top 200 significant DMCs were strongly enriched in active enhancers in trophoblast lineages, whereas 145 non-significant probes were enriched in regions with a quiescent state of chromatin. Our results suggest that future epigenetic studies of PE should focus on functional regulatory sequences.

Predicting Differentially Methylated Cytosines in TET and DNMT3 Knockout Mutants via a Large Language Model.

DNA cytosine methylation is an epigenetic marker which regulates many cellular processes. Mammalian genomes typically maintain consistent methylation patterns over time, except in specific regulatory regions like promoters and certain types of enhancers. The dynamics of DNA methylation is controlled by a complex cellular machinery, in which the enzymes DNMT3 and TET play a major role. This study explores the identification of differentially methylated cytosines (DMCs) in TET and DNMT3 knockout mutants in mice and human embryonic stem cells. We investigate (i) whether a large language model can be trained to recognize DMCs in human and mouse from the sequence surrounding the cytosine of interest, (ii) whether a classifier trained on human knockout data can predict DMCs in the mouse genome (and vice versa), (iii) whether a classifier trained on DNMT3 knockout can predict DMCs for TET knockout (and vice versa). Our study identifies statistically significant motifs associated with the prediction of DMCs each mutant, casting a new light on the understanding of DNA methylation dynamics in stem cells. Our software tool is available at https://github.com/ucrbioinfo/dmc_prediction .

Targeted bisulfite sequencing of Scots pine adaptation-related genes

During environmental changes, epigenetic processes can enable adaptive responses faster than natural selection. In plants, very little is known about the role of DNA methylation during long-term adaptation. Scots pine is a widely distributed coniferous species which must adapt to different environmental conditions throughout its long lifespan. Thus, epigenetic modifications may contribute towards this direction. We provide bisulfite next-generation sequencing data from the putative promoters and exons of eight adaptation-related genes (A3IP2, CCA1, COL1, COL2, FTL2, MFT1, PHYO, and ZTL) in three Scots pine populations located in northern and southern parts of Finland. DNA methylation levels were studied in the two seed tissues: the maternal megagametophyte which contributes to embryo viability, and the biparental embryo which represents the next generation. In most genes, differentially methylated cytosines (DMCs) were in line with our previously demonstrated gene expression differences found in the same Scots pine populations. In addition, we found a strong correlation of total methylation levels between the embryo and megagametophyte tissues of a given individual tree, which indicates that DNA methylation can be inherited from the maternal parent. In conclusion, our results imply that DNA methylation differences may contribute to the adaptation of Scots pine populations in different climatic conditions.

131 DNA methylation profile in bovine fetal liver is affected by maternal vitamin and mineral supplementation during early gestation

Abstract Early gestation is the critical period for successful pregnancy establishment. During this period, maternal nutrition affects fetal development with potentially long-lasting consequences on offspring performance. Despite the known effects of vitamins and minerals on embryonic development, supplementation is still not a widely adopted practice. Here we focused on the effects of maternal vitamin and mineral supplementation from pre-breeding to d 83 of gestation. We hypothesized that the DNA methylation pattern of genes involved with fetal hepatic metabolism and function would be altered in response to vitamin and mineral supplementation during early gestation. Sixteen Angus crossbred heifers (~16 mo of age) were randomly assigned to either a treatment (vitamin and mineral supplementation, VTM, n = 8) or control (corn-based carrier without supplementation, NoVTM, n = 8) group. Supplemented heifers received 0.45 kg •heifer-1•d-1 of to provide 113 g of vitamin-mineral premix (Purina Wind & Rain Storm All-Season 7.5 Complete, Land O’Lakes, Inc., Arden Hills, MN) from d 71 to 148 before breeding to d 83 of gestation. All heifers received 100% of NRC recommended nutritional requirements targeting 0.28 kg •heifer-1•d-1 of gain. The heifers were bred through artificial insemination following a 7-d Co-Synch + CIDR estrus synchronization protocol. All pregnant heifers were surgically ovariohysterectomized on d 83, and liver samples were collected from the fetuses. DNA methylation profiles from 16 fetuses (8 per treatment) were determined using Reduced Representation Bisulfite Sequencing (RRBS). The analysis was conducted using methylKit pipeline where data was normalized using principal components. We identified 794 differentially methylated cytosines (DMCs) for the control (NoVTM) vs VTM comparison. Most of the DMCs were found in introns followed by intergenic, promoter, and exonic regions. Among these DMCs, 60% (479) were hypermethylated and 40% (315) were hypomethylated, potentially regulating 739 nearby genes (FDR < 0.1). Biological processes over-represented by these genes included transport of ions through voltage gated channels (KCNK13, KCNT1, CACNA1B, KCNK9, LRRC55, KCNAB2, CACNA1S, KCNJ2, CACNG5, CLIC5, TPCN2, KCNQ1), which may be associated to pregnancy establishment by inducing pregnancy-associated relaxation and uterine artery dilatation. Some genes associated with structural development were also regulated by VTM supplementation (i.e., TIAM1, COL18A1, DYSF, BMP10, RXRA, EHMT1, COL4A2, PLEC, ZFAT, MTMR2, NAV1, ANHX, ACACB, and LIMK2). Collectively, these results suggest that periconceptual maternal vitamin and mineral supplementation affects the methylation pattern and potentially regulates the expression of genes involved in fetal liver development and ion transport.

Acute Exercise Alters Skeletal Muscle DNA Methylation in Sedentary Participants

Skeletal muscle is a highly plastic tissue, adapting its structure and metabolism in response to various stimuli like exercise. This study aimed to determine the plasticity of skeletal muscle DNA methylation in response to an acute exercise bout in volunteers with a range of insulin sensitivities. We studied 14 sedentary participants (7 male/7 female): age = 34.5 ± 3.1 years, body mass index = 29.3 ± 1.9 kg/m2 and HbA1c = 5.3 ± 0.1 %. We performed VO2peak tests to determine exercise capacity (VO2peak = 25.5 ± 1.6 mL per Kg per minute) and euglycemic hyperinsulinemic clamps (Rd value = 5.9 ± 0.8 mg per Kg per minute) with vastus lateralis muscle biopsies before and 30 minutes after a single 48-minute exercise bout. We extracted DNA from the muscle biopsies and performed reduced representation bisulfite sequencing. After performing quality control on the sequencing data, 1,034,947 sites were included for downstream analyses. MethylSig analysis revealed 17,030 differentially methylated cytosines (DMC), 9,020 increased and 8,010 decreased. To identify biologically meaningful DMCs, we used a mean change of >10%, which resulted in 1,179 and 1,436 increased and decreased sites, respectively. Pathway analysis of the increased DMCs revealed an enrichment in efferocytosis, leukocyte transendothelial migration, and FOXO-mediated transcription of oxidative stress pathways. In addition, pathway analysis of the decreased DMCs revealed an enrichment in metabolic (type 2 diabetes/ PI3K-Akt signaling), actin cytoskeleton, integrin/extracellular matrix and calcium signaling pathways. Our study reveals that an acute exercise bout induces alterations in the DNA methylation of skeletal muscle, impacting specific pathways in individuals with varying degrees of insulin sensitivity. Notably, our findings underscore the remarkable plasticity of skeletal muscle tissue. This research was funded by the National Institutes of Health, grant number R01DK094013 (Dawn Coletta). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Cold exposure impacts DNA methylation patterns in cattle sperm.

DNA methylation is influenced by various exogenous factors such as nutrition, temperature, toxicants, and stress. Bulls from the Pacific Northwest region of the United States and other northern areas are exposed to extreme cold temperatures during winter. However, the effects of cold exposure on the methylation patterns of bovine sperm remain unclear. To address, DNA methylation profiles of sperm collected during late spring and winter from the same bulls were analyzed using whole genome bisulfite sequencing (WGBS). Bismark (0.22.3) were used for mapping the WGBS reads and R Bioconductor package DSS was used for differential methylation analysis. Cold exposure induced 3,163 differentially methylated cytosines (DMCs) with methylation difference ≥10% and a q-value < 0.05. We identified 438 differentially methylated regions (DMRs) with q-value < 0.05, which overlapped with 186 unique genes. We also identified eight unique differentially methylated genes (DMGs) (Pax6, Macf1, Mest, Ubqln1, Smg9, Ctnnb1, Lsm4, and Peg10) involved in embryonic development, and nine unique DMGs (Prmt6, Nipal1, C21h15orf40, Slc37a3, Fam210a, Raly, Rgs3, Lmbr1, and Gan) involved in osteogenesis. Peg10 and Mest, two paternally expressed imprinted genes, exhibited >50% higher methylation. The differential methylation patterns of six distinct DMRs: Peg10, Smg9 and Mest related to embryonic development and Lmbr1, C21h15orf40 and Prtm6 related to osteogenesis, were assessed by methylation-specific PCR (MS-PCR), which confirmed the existence of variable methylation patterns in those locations across the two seasons. In summary, cold exposure induces differential DNA methylation patterns in genes that appear to affect embryonic development and osteogenesis in the offspring. Our findings suggest the importance of replicating the results of the current study with a larger sample size and exploring the potential of these changes in affecting offspring development.

Characterization of genomic regions escaping epigenetic reprogramming in sheep.

The mammalian genome undergoes two global epigenetic reprogramming events during the establishment of primordial germ cells and in the pre-implantation embryo after fertilization. These events involve the erasure and re-establishment of DNA methylation marks. However, imprinted genes and transposable elements (TEs) maintain their DNA methylation signatures to ensure normal embryonic development and genome stability. Despite extensive research in mice and humans, there is limited knowledge regarding environmentally induced epigenetic marks that escape epigenetic reprogramming in other species. Therefore, the objective of this study was to examine the characteristics and locations of genomic regions that evade epigenetic reprogramming in sheep, as well as to explore the biological functions of the genes within these regions. In a previous study, we identified 107 transgenerationally inherited differentially methylated cytosines (DMCs) in the F1 and F2 generations in response to a paternal methionine-supplemented diet. These DMCs were found in TEs, non-repetitive regions, and imprinted and non-imprinted genes. Our findings suggest that genomic regions, rather than TEs and imprinted genes, have the propensity to escape reprogramming and serve as potential candidates for transgenerational epigenetic inheritance. Notably, 34 transgenerational methylated genes influenced by paternal nutrition escaped reprogramming, impacting growth, development, male fertility, cardiac disorders, and neurodevelopment. Intriguingly, among these genes, 21 have been associated with neural development and brain disorders, such as autism, schizophrenia, bipolar disease, and intellectual disability. This suggests a potential genetic overlap between brain and infertility disorders. Overall, our study supports the concept of transgenerational epigenetic inheritance of environmentally induced marks in mammals.

Comprehensive evaluation of the implementation of episignatures for diagnosis of neurodevelopmental disorders (NDDs)

Episignatures are popular tools for the diagnosis of rare neurodevelopmental disorders. They are commonly based on a set of differentially methylated CpGs used in combination with a support vector machine model. DNA methylation (DNAm) data often include missing values due to changes in data generation technology and batch effects. While many normalization methods exist for DNAm data, their impact on episignature performance have never been assessed. In addition, technologies to quantify DNAm evolve quickly and this may lead to poor transposition of existing episignatures generated on deprecated array versions to new ones. Indeed, probe removal between array versions, technologies or during preprocessing leads to missing values. Thus, the effect of missing data on episignature performance must also be carefully evaluated and addressed through imputation or an innovative approach to episignatures design. In this paper, we used data from patients suffering from Kabuki and Sotos syndrome to evaluate the influence of normalization methods, classification models and missing data on the prediction performances of two existing episignatures. We compare how six popular normalization methods for methylarray data affect episignature classification performances in Kabuki and Sotos syndromes and provide best practice suggestions when building new episignatures. In this setting, we show that Illumina, Noob or Funnorm normalization methods achieved higher classification performances on the testing sets compared to Quantile, Raw and Swan normalization methods. We further show that penalized logistic regression and support vector machines perform best in the classification of Kabuki and Sotos syndrome patients. Then, we describe a new paradigm to build episignatures based on the detection of differentially methylated regions (DMRs) and evaluate their performance compared to classical differentially methylated cytosines (DMCs)-based episignatures in the presence of missing data. We show that the performance of classical DMC-based episignatures suffers from the presence of missing data more than the DMR-based approach. We present a comprehensive evaluation of how the normalization of DNA methylation data affects episignature performance, using three popular classification models. We further evaluate how missing data affect those models’ predictions. Finally, we propose a novel methodology to develop episignatures based on differentially methylated regions identification and show how this method slightly outperforms classical episignatures in the presence of missing data.

DNA methylation and gene expression changes in mouse mammary tissue during successive lactations: part I – the impact of inflammation

ABSTRACT Mastitis is among the main reasons women cease breastfeeding, which leads to them supplementing breast milk with artificial formula. In farm animals, mastitis results in significant economic losses and the premature culling of some animals. Nevertheless, researchers do not know enough about the effect of inflammation on the mammary gland. This article discusses the changes to DNA methylation in mouse mammary tissue caused by lipopolysaccharide-induced inflammation (4 h post-injection of lipopolysaccharide). We analysed the expression of some genes related to mammary gland function, epigenetic regulation, and the immune response. The analysis focused on three comparisons: inflammation during the first lactation, inflammation during second lactation with no history of inflammation, and inflammation during second lactation with previous inflammation. We identified differentially methylated cytosines (DMCs), differentially methylated regions (DMRs), and some differentially expressed genes (DEGs) for each comparison. The three comparisons shared some DEGs; however, few DMCs and only one DMR were shared. These observations suggest that inflammation is one of several factors affecting epigenetic regulation during successive lactations. Furthermore, the comparison between animals in second lactation with and without inflammation, with no inflammation history during first lactation showed a different pattern compared to the other conditions in this experiment. This indicates that inflammation history plays an important role in determining epigenetic changes. The data presented in this study suggest that lactation rank and previous inflammation history are equally important when explaining mammary tissue gene expression and DNA methylation changes. Abbreviations: RRBS, reduced representation bisulfite sequencing; RT–qPCR, real-time quantitative polymerase chain reaction; MEC, mammary epithelial cells; TSS, transcription start site; TTS, transcription termination site; UTR, untranslated region; SINE, short interspersed nuclear element; LINE, long interspersed nuclear element; CGI, CpG island; DEG, differentially expressed gene; DMC, differentially methylated cytosine; DMR, differentially methylated region; GO term, gene ontology term; MF, molecular function; BP, biological process

Whole-genome DNA methylation analysis of the sperm in relation to bull fertility.

Bull fertility is an important economic trait, this study identified some DNA methylation biomarkers that are associated with bull fertility. Subfertile bulls may cause huge economic losses in dairy production since their semen could be used to inseminate thousands of cows by artificial insemination. This study adopted whole-genome enzymatic methyl sequencing and aimed to identify candidate DNA methylation markers in bovine sperm that correlate with bull fertility. Twelve bulls were selected (high bull fertility = 6; low bull fertility = 6) based on the industry's internally used Bull Fertility Index. After sequencing, a total of 450 CpG had a DNA methylation difference higher than 20% (q < 0.01) had been screened. The 16 most significant differentially methylated regions (DMRs) were identified using a 10% methylation difference cut-off (q < 5.88 × 10-16). Interestingly, most of the differentially methylated cytosines (DMCs) and DMRs were distributed on the X and Y chromosomes, demonstrating that the sex chromosomes play essential roles in bull fertility. Additionally, the functional classification showed that the beta-defensin family, zinc finger protein family, and olfactory and taste receptors could be clustered. Moreover, the enriched G protein-coupled receptors such as neurotransmitter receptors, taste receptors, olfactory receptors, and ion channels indicated that the acrosome reaction and capacitation processes are pivotal for bull fertility. In conclusion, this study identified the sperm-derived bull fertility-associated DMRs and DMCs at the whole genome level, which could complement and integrate into the existing genetic evaluation methods, increasing our decisive capacity to select good bulls and explain bull fertility better in the future.

Environmental and genealogical effects on DNA methylation in a widespread apomictic dandelion lineage.

DNA methylation in plant genomes occurs in different sequences and genomic contexts that have very different properties. DNA methylation that occurs in CG (mCG) sequence context shows transgenerational stability and high epimutation rate, and can thus provide genealogical information at short time scales. However, due to meta-stability and because mCG variants may arise due to other factors than epimutation, such as environmental stress exposure, it is not clear how well mCG captures genealogical information at micro-evolutionary time scales. Here, we analysed DNA methylation variation between accessions from a geographically widespread, apomictic common dandelion (Taraxacum officinale) lineage when grown experimentally under different light conditions. Using a reduced-representation bisulphite sequencing approach, we show that the light treatment induced differentially methylated cytosines (DMCs) in all sequence contexts, with a bias towards transposable elements. Accession differences were associated mainly with DMCs in CG context. Hierarchical clustering of samples based on total mCG profiles revealed a perfect clustering of samples by accession identity, irrespective of light conditions. Using microsatellite information as a benchmark of genetic divergence within the clonal lineage, we show that genetic divergence between accessions correlates strongly with overall mCG profiles. However, our results suggest that environmental effects that do occur in CG context may produce a heritable signal that partly dilutes the genealogical signal. Our study shows that methylation information in plants can be used to reconstruct micro-evolutionary genealogy, providing a useful tool in systems that lack genetic variation such as clonal and vegetatively propagated plants.

Transgenerational impact of grand-paternal lifetime exposures to both folic acid deficiency and supplementation on genome-wide DNA methylation in male germ cells.

DNA methylation (DNAme) erasure and reacquisition occur during prenatal male germ cell development; some further remodeling takes place after birth during spermatogenesis. Environmental insults during germline epigenetic reprogramming may affect DNAme, presenting a potential mechanism for transmission of environmental exposures across multiple generations. We investigated how germ cell DNAme is impacted by lifetime exposures to diets containing either low or high, clinically relevant, levels of the methyl donor folic acid and whether resulting DNAme alterations were inherited in germ cells of male offspring of subsequent generations. Female mice were placed on a control (FCD), 7-fold folic acid deficient (7FD) or10-to20-fold supplemented (10FS and 20FS) diet before and during pregnancy. Resulting F1 litters were weaned on the respective diets. F2 and F3 males received control diets. Genome-wide DNAme at cytosines (within CpG sites) was assessed in F1 spermatogonia, and in F1, F2 and F3 sperm. In F1 germ cells, a greater number of differentially methylated cytosines (DMCs) were observed in spermatogonia as compared with F1 sperm for all folic acid diets. DMCs were lower in number in F2 versus F1 sperm, while an unexpected increase was found in F3 sperm. DMCs were predominantly hypomethylated, with genes in neurodevelopmental pathways commonly affected in F1, F2 and F3 male germ cells. While no DMCs were found to be significantly inherited inter- or transgenerationally, we observed over-representation of repetitive elements, particularly young longinterspersednuclearelements(LINEs). These results suggest that the prenatal window is the time most susceptible to folate-induced alterations in sperm DNAme in male germ cells. Altered methylation of specific sites in F1 germ cells was not present in later generations. However, the presence of DNAme perturbations in the sperm of males of the F2 and F3 generations suggests that epigenetic inheritance mechanisms other than DNAme may have been impacted by the folate diet exposure of F1 germ cells.

Principal component analysis- and tensor decomposition-based unsupervised feature extraction to select more suitable differentially methylated cytosines: Optimization of standard deviation versus state-of-the-art methods

In contrast to RNA-seq analysis, which has various standard methods, no standard methods for identifying differentially methylated cytosines (DMCs) exist. To identify DMCs, we tested principal component analysis and tensor decomposition-based unsupervised feature extraction with optimized standard deviation, which has been shown to be effective for differentially expressed gene (DEG) identification. The proposed method outperformed certain conventional methods, including those that assume beta-binomial distribution for methylation as the proposed method does not require this, especially when applied to methylation profiles measured using high throughput sequencing. DMCs identified by the proposed method also significantly overlapped with various functional sites, including known differentially methylated regions, enhancers, and DNase I hypersensitive sites. The proposed method was applied to data sets retrieved from The Cancer Genome Atlas to identify DMCs using American Joint Committee on Cancer staging system edition labels. This suggests that the proposed method is a promising standard method for identifying DMCs.

Targeted bisulfite resequencing of differentially methylated cytosines in pre-eclampsia reveals a skewed dynamic balance in the DNA methylation of enhancers.

Pre-eclampsia (PE) is a major hypertensive disorder of pregnancy. Widespread differentially methylated cytosines (DMCs) with modest changes in methylation level are associated with PE, whereas their cause and biological significance remain unknown. We aimed to clarify DNA methylation patterns around DMCs in 103 placentas using MethylCap targeted bisulfite re-sequencing (MethylCap-seq) assays of 690 selected DMCs. We verified the MethylCap-seq method, then validated 677 (98.1%) of DMCs (vDMCs) in an independent cohort. The validated DMCs were strongly enriched in active placenta-specific enhancers and showed highly dynamic methylation levels. We found high epigenetic heterogeneity between vDMCs and adjacent CpG sites (r2 < 0.2) and a significant decrease in PE in the discovery and replication cohorts (P = 2.00 × 10-24 and 6.43 × 10-9, respectively). We replicated the methylation changes in a hypoxia/reoxygenation cell model. We constructed 112 methylation haplotype blocks and found that the frequencies of unmethylated haplotypes (UMHs) were dynamic with gestational age (GA) and were altered in maternal plasma of patients with PE. Our results uncovered additional DNA methylation features in PE placentas and suggested a model of skewed DNA methylation balance of enhancers in PE.

Methylome and transcriptome data integration reveals potential roles of DNA methylation and candidate biomarkers of cow Streptococcus uberis subclinical mastitis

BackgroundMastitis caused by different pathogens including Streptococcus uberis (S. uberis) is responsible for huge economic losses to the dairy industry. In order to investigate the potential genetic and epigenetic regulatory mechanisms of subclinical mastitis due to S. uberis, the DNA methylome (whole genome DNA methylation sequencing) and transcriptome (RNA sequencing) of milk somatic cells from cows with naturally occurring S. uberis subclinical mastitis and healthy control cows (n = 3/group) were studied.ResultsGlobally, the DNA methylation levels of CpG sites were low in the promoters and first exons but high in inner exons and introns. The DNA methylation levels at the promoter, first exon and first intron regions were negatively correlated with the expression level of genes at a whole-genome-wide scale. In general, DNA methylation level was lower in S. uberis-positive group (SUG) than in the control group (CTG). A total of 174,342 differentially methylated cytosines (DMCs) (FDR < 0.05) were identified between SUG and CTG, including 132,237, 7412 and 34,693 DMCs in the context of CpG, CHG and CHH (H = A or T or C), respectively. Besides, 101,612 methylation haplotype blocks (MHBs) were identified, including 451 MHBs that were significantly different (dMHB) between the two groups. A total of 2130 differentially expressed (DE) genes (1378 with up-regulated and 752 with down-regulated expression) were found in SUG. Integration of methylome and transcriptome data with MethGET program revealed 1623 genes with significant changes in their methylation levels and/or gene expression changes (MetGDE genes, MethGET P-value < 0.001). Functional enrichment of genes harboring ≥ 15 DMCs, DE genes and MetGDE genes suggest significant involvement of DNA methylation changes in the regulation of the host immune response to S. uberis infection, especially cytokine activities. Furthermore, discriminant correlation analysis with DIABLO method identified 26 candidate biomarkers, including 6 DE genes, 15 CpG-DMCs and 5 dMHBs that discriminated between SUG and CTG.ConclusionThe integration of methylome and transcriptome of milk somatic cells suggests the possible involvement of DNA methylation changes in the regulation of the host immune response to subclinical mastitis due to S. uberis. The presented genetic and epigenetic biomarkers could contribute to the design of management strategies of subclinical mastitis and breeding for mastitis resistance.

Long-term epigenetic and metabolomic changes in the mouse ventricular myocardium after exertional heat stroke.

Evidence from human epidemiological studies suggests that exertional heat stroke (EHS) results in an elevated risk of long-term cardiovascular and systemic disease. Previous results using a preclinical mouse model of EHS demonstrated severe metabolic imbalances in ventricular myocardium developing at 9-14 days of recovery. Whether this resolves over time is unknown. We hypothesized that the long-term effects of EHS on the heart reflect retained maladaptive epigenetic responses. In this study, we evaluated genome-wide DNA methylation, RNA-Seq, and metabolomic profiles of the left ventricular myocardium in female C57BL/6 mice, 30 days after EHS (exercise in 37.5°C; n = 7-8), compared with exercise controls. EHS mice ran to loss of consciousness, reaching core temperatures of 42.4 ± 0.2°C. All mice recovered quickly. After 30 days, the left ventricles were rapidly frozen for DNA methyl sequencing, RNA-Seq, and untargeted metabolomics. Ventricular DNA from EHS mice revealed >13,000 differentially methylated cytosines (DMCs) and >900 differentially methylated regions (DMRs; ≥5 DMCs with ≤300 bp between each CpG). Pathway analysis using DMRs revealed alterations in genes regulating basic cell functions, DNA binding, transcription, and metabolism. Metabolomics and mRNA expression revealed modest changes that are consistent with a return to homeostasis. Methylation status did not predict RNA expression or metabolic state at 30 days. We conclude that EHS induces a sustained DNA methylation memory lasting over 30 days of recovery, but ventricular gene expression and metabolism return to a relative homeostasis at rest. Such long-lasting alterations to the DNA methylation landscape could alter responsiveness to environmental or clinical challenges later in life.

A hypothetical model of skewed DNA methylation balance in the enhancer regions containing differentially methylated cytosines associated with non-malignant complex diseases

Epigenome-wide association studies have been widely conducted over the past decade to identify the epigenetic determinants of human complex diseases. Numerous differentially methylated cytosines (DMCs) associated with diseases or environmental exposure have been identified till date. An important hallmark of DMCs in non-malignant complex diseases is that they are strongly enriched in CpG sites showing small changes to intermediate levels of methylation. This paradigm of subtle change in DMC methylation hampers our understanding of epigenetic regulation in non-malignant complex diseases and the application of DMCs as biomarkers in clinical practice. Herein, we propose a hypothetical model of skewed DNA methylation balance in the enhancer regions containing differentially methylated cytosines associated with non-malignant complex diseases. The DMCs are strongly enriched in enhancers, which are characterized by a highly dynamic balance of DNA methylation. The DNA methylation balance plays an important role in cellular adaptation to adverse environment; however, in the case of certain diseases, the balance becomes skewed toward one end of dynamic range. Binding stress-inducible transcription factors determines DNA methylation at the enhancer region, resulting in epigenetic heterogeneity. The dynamics of DNA methylation balance can be evaluated by analyzing the DNA co-methylation status of DMCs and their neighboring CpG sites. Targeted bisulfite resequencing method is suggested to analyze the change in DNA co-methylation in both case-control and longitudinal cohort studies. Cell models are necessary to study the molecular mechanisms of DNA methylation changes. We also suggest that complex obstetrical syndromes associated with placental disorders may be excellent models for investigating common features of DNA methylation in non-malignant complex diseases.

Signatures of polygenic adaptation align with genome-wide methylation patterns in wild strawberry plants.

Epigenetic inheritance can drive adaptive evolution independently of DNA sequence variation. However, to what extent epigenetic variation represents an autonomous evolutionary force remains largely elusive. Through gene ontology and comparative analyses of genomic and epigenomic variation of wild strawberry plants raised in distinct drought settings, we characterised genome-wide covariation between single nucleotide polymorphisms (SNPs) and differentially methylated cytosines (DMCs). Covariation between SNPs and DMCs was independent of genomic proximity, but instead associated with fitness-related processes such as stress responses, genome regulation and reproduction. We expected this functional SNP-DMC covariation to be driven by adaptive evolution canalising SNP and DMC variation, but instead observed significantly lower covariation with DMCs for adaptive rather than for neutral SNPs. Drought-induced DMCs frequently co-varied with tens of SNPs, suggesting high genomic redundancy as a broad potential basis for polygenic adaptation of gene expression. Our findings suggest that stress-responsive DMCs initially co-vary with many SNPs under increased environmental stress, and that natural selection acting upon several of these SNPs subsequently reduces standing covariation with stress-responsive DMCs. Our study supports DNA methylation profiles that represent complex quantitative traits rather than autonomous evolutionary forces. We provide a conceptual framework for polygenic regulation and adaptation shaping genome-wide methylation patterns in plants.