Allele-specific methylation is prevalent and is contributed by CpG-SNPs in the human genome

Moura A, Filho ODMM, Pessoa C, Miranda Furtado CL. Hypomethylation at H19DMR in penile squamous cell carcinoma is not related to HPV infection

Penile squamous cell carcinoma (SCC) is a rare and aggressive tumour mainly related to lifestyle behaviour and human papillomavirus (HPV) infection. Environmentally induced loss of imprinting (LOI) at the H19 differentially methylated region (H19DMR) is associated with many cancers in the early events of tumorigenesis and may be involved in the pathogenesis of penile SCC. We sought to evaluate the DNA methylation pattern at H19DMR and its association with HPV infection in men with penile SCC by bisulfite sequencing (bis-seq). We observed an average methylation of 32.2% ± 11.6% at the H19DMR of penile SCC and did not observe an association between the p16INK4a+ (p = 0.59) and high-risk HPV+ (p = 0.338) markers with methylation level. The average methylation did not change according to HPV positive for p16INK4a+ or hrHPV+ (35.4% ± 10%) and negative for both markers (32.4% ± 10.1%) groups. As the region analysed has a binding site for the CTCF protein, the hypomethylation at the surrounding CpG sites might alter its insulator function. In addition, there was a positive correlation between intense polymorphonuclear cell infiltration and hypomethylation at H19DMR (p = 0.035). Here, we report that hypomethylation at H19DMR in penile SCC might contribute to tumour progression and aggressiveness regardless of HPV infection.

Variation within the non-coding genome influences genetic and epigenetic regulation of the human leukocyte antigen genes

Variation within the non-coding genome may influence the regulation and expression of important genes involved in immune control such as the human leukocyte antigen (HLA) system. Class I and Class II HLA molecules are essential for peptide presentation which is required for T lymphocyte activation. Single nucleotide polymorphisms within non-coding regions of HLA Class I and Class II genes may influence the expression of these genes by affecting the binding of transcription factors and chromatin modeling molecules. Furthermore, an interplay between genetic and epigenetic factors may also influence HLA expression. Epigenetic factors such as DNA methylation and non-coding RNA, regulate gene expression without changing the DNA sequence. However, genetic variation may promote or allow genes to escape regulation by epigenetic factors, resulting in altered expression. The HLA system is central to most diseases, therefore, understanding the role of genetics and epigenetics on HLA regulation will tremendously impact healthcare. The knowledge gained from these studies may lead to novel and cost-effective diagnostic approaches and therapeutic interventions. This review discusses the role of non-coding variants on HLA regulation. Furthermore, we discuss the interplay between genetic and epigenetic factors on the regulation of HLA by evaluating literature based on polymorphisms within DNA methylation and miRNA regulatory sites within class I and Class II HLA genes. We also provide insight into the importance of the HLA non-coding genome on disease, discuss ethnic-specific differences across the HLA region and provide guidelines for future HLA studies.

Intergenerational association of DNA methylation between parents and offspring

Early patterning of DNA methylation (DNAm) may play an important role in later disease development. To better understand intergenerational epigenetic inheritance, we investigated the correlation between DNAm in blood in mother-newborn and in father-newborn pairs in the Isle of Wight (IoW) birth cohort. For parent-newborn pairs (n = 48), offspring DNAm was measured in cord blood and the parent's DNAm in whole blood. Mothers' DNAm was analyzed at birth (Guthrie card), age 18, early and late pregnancy respectively, and fathers' DNAm was measured during the mother's pregnancy. Linear regressions were applied to assess the intergenerational correlation of parental DNAm with that of offspring. Among various pairs of mother-newborn and father-newborn DNAm, the pairs where the mothers' DNAm was measured at age 18 years exhibited the highest number of CpGs with significant intergenerational correlation in DNAm, with 1829 CpGs (0.54%) of the 338,526 CpGs studied (FDR < 0.05). Amongst these 1829 CpGs, 986 (54%) are known quantitative trait loci (QTL) for CpG methylation (methQTL). When the mother's DNAm was assessed at early pregnancy, the number of CpGs showing intergenerational correlation was the smallest (384 CpGs, 0.11%). The second smallest number of such CpGs (559 CpGs, 0.17%) was found when investigating DNAm in offspring cord blood and father pairs. The low proportions of intergenerationally correlated CpGs suggest that epigenetic inheritance is limited.

The effect of type 1 diabetes protection and susceptibility associated HLA class II genotypes on DNA methylation in immune cells

The HLA region, especially HLA class I and II genes, which encode molecules for antigen presentation to T cells, plays a major role in the predisposition to autoimmune disorders. To clarify the mechanisms behind this association, we examined genome-wide DNA methylation by microarrays to cover over 850,000 CpG sites in the CD4+ T cells and CD19+ B cells of healthy subjects homozygous either for DRB1*15-DQA1*01-DQB1*06:02 (DR2-DQ6, n = 14), associated with a strongly decreased T1D risk, DRB1*03-DQA1*05-DQB1*02 (DR3-DQ2, n = 19), or DRB1*04:01-DQA1*03-DQB1*03:02 (DR4-DQ8, n = 17), associated with a moderately increased T1D risk. In total, we discovered 14 differentially methylated CpG probes, of which 10 were located in the HLA region and six in the HLA-DRB1 locus. The main differences were between the protective genotype DR2-DQ6 and the risk genotypes DR3-DQ2 and DR4-DQ8, where the DR2-DQ6 group was hypomethylated compared to the other groups in all but four of the differentially methylated probes. The differences between the risk genotypes DR3-DQ2 and DR4-DQ8 were small. Our results indicate that HLA variants have few systemic effects on methylation and that their effect on autoimmunity is conveyed directly by HLA molecules, possibly by differences in expression levels or function.

Epigenomic insights into common human disease pathology

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Investigating the potential of single-cell DNA methylation data to detect allele-specific methylation and imprinting

Allele-specific methylation (ASM) is an epigenetic modification whereby one parental allele becomes methylated and the other unmethylated at a specific locus. ASM is most often driven by the presence of nearby heterozygous variants that influence methylation, but also occurs somatically in the context of genomic imprinting. In this study, we investigate ASM using publicly available single-cell reduced representation bisulfite sequencing (scRRBS) data on 608 B cells sampled from six healthy B cell samples and 1,230 cells from 11 chronic lymphocytic leukemia (CLL) samples. We developed a likelihood-based criterion to test whether a CpG exhibited ASM, based on the distributions of methylated and unmethylated reads both within and across cells. Applying our likelihood ratio test, 65,998 CpG sites exhibited ASM in healthy B cell samples according to a Bonferroni criterion (p < 8.4 × 10-9), and 32,862 CpG sites exhibited ASM in CLL samples (p < 8.5 × 10-9). We also called ASM at the sample level. To evaluate the accuracy of our method, we called heterozygous variants from the scRRBS data, which enabled variant-based calls of ASM within each cell. Comparing sample-level ASM calls to the variant-based measures of ASM, we observed a positive predictive value of 76%-100% across samples. We observed high concordance of ASM across samples and an overrepresentation of ASM in previously reported imprinted genes and genes with imprinting binding motifs. Our study demonstrates that single-cell bisulfite sequencing is a potentially powerful tool to investigate ASM, especially as studies expand to increase the number of samples and cells sequenced.

Epigenetics of prenatal stress in humans: the current research landscape

Fetal exposure to prenatal stress can have significant consequences on short- and long-term health. Epigenetic mechanisms, especially DNA methylation (DNAm), are a possible process how these adverse environmental events could be biologically embedded. We evaluated candidate gene as well as epigenome-wide association studies associating prenatal stress and DNAm changes in peripheral tissues; however, most of these findings lack robust replication. Prenatal stress-associated epigenetic changes have also been linked to child health including internalizing problems, neurobehavioral outcomes and stress reactivity. Future studies should focus on refined measurement and definition of prenatal stress and its timing, ideally also incorporating genomic as well as longitudinal information. This will provide further opportunities to enhance our understanding of the biological embedding of prenatal stress exposure.

A DNA methylation haplotype block landscape in human tissues and preimplantation embryos reveals regulatory elements defined by comethylation patterns

DNA methylation and associated regulatory elements play a crucial role in gene expression regulation. Previous studies have focused primarily on the distribution of mean methylation levels. Advances in whole-genome bisulfite sequencing (WGBS) have enabled the characterization of DNA methylation haplotypes (MHAPs), representing CpG sites from the same read fragment on a single chromosome, and the subsequent identification of methylation haplotype blocks (MHBs), in which adjacent CpGs on the same fragment are comethylated. Using our expert-curated WGBS data sets, we report comprehensive landscapes of MHBs in 17 representative normal somatic human tissues and during early human embryonic development. Integrative analysis reveals MHBs as a distinctive type of regulatory element characterized by comethylation patterns rather than mean methylation levels. We show the enrichment of MHBs in open chromatin regions, tissue-specific histone marks, and enhancers, including super-enhancers. Moreover, we find that MHBs tend to localize near tissue-specific genes and show an association with differential gene expression that is independent of mean methylation. Similar findings are observed in the context of human embryonic development, highlighting the dynamic nature of MHBs during early development. Collectively, our comprehensive MHB landscapes provide valuable insights into the tissue specificity and developmental dynamics of DNA methylation.

The Impact of Apolipoprotein E (APOE) Epigenetics on Aging and Sporadic Alzheimer's Disease

Sporadic Alzheimer's disease (AD) derives from an interplay among environmental factors and genetic variants, while epigenetic modifications have been expected to affect the onset and progression of its complex etiopathology. Carriers of one copy of the apolipoprotein E gene (APOE) ε4 allele have a 4-fold increased AD risk, while APOE ε4/ε4-carriers have a 12-fold increased risk of developing AD in comparison with the APOE ε3-carriers. The main longevity factor is the homozygous APOE ε3/ε3 genotype. In the present narrative review article, we summarized and described the role of APOE epigenetics in aging and AD pathophysiology. It is not fully understood how APOE variants may increase or decrease AD risk, but this gene may affect tau- and amyloid-mediated neurodegeneration directly or indirectly, also by affecting lipid metabolism and inflammation. For sporadic AD, epigenetic regulatory mechanisms may control and influence APOE expression in response to external insults. Diet, a major environmental factor, has been significantly associated with physical exercise, cognitive function, and the methylation level of several cytosine-phosphate-guanine (CpG) dinucleotide sites of APOE.

Transposon wave remodeled the epigenomic landscape in the rapid evolution of X-Chromosome dosage compensation

Sex chromosome dosage compensation is a model to understand the coordinated evolution of transcription; however, the advanced age of the sex chromosomes in model systems makes it difficult to study how the complex regulatory mechanisms underlying chromosome-wide dosage compensation can evolve. The sex chromosomes of Poecilia picta have undergone recent and rapid divergence, resulting in widespread gene loss on the male Y, coupled with complete X Chromosome dosage compensation, the first case reported in a fish. The recent de novo origin of dosage compensation presents a unique opportunity to understand the genetic and evolutionary basis of coordinated chromosomal gene regulation. By combining a new chromosome-level assembly of P. picta with whole-genome bisulfite sequencing and RNA-seq data, we determine that the YY1 transcription factor (YY1) DNA binding motif is associated with male-specific hypomethylated regions on the X, but not the autosomes. These YY1 motifs are the result of a recent and rapid repetitive element expansion on the P. picta X Chromosome, which is absent in closely related species that lack dosage compensation. Taken together, our results present compelling support that a disruptive wave of repetitive element insertions carrying YY1 motifs resulted in the remodeling of the X Chromosome epigenomic landscape and the rapid de novo origin of a dosage compensation system.

Allele-specific RNA N 6-methyladenosine modifications reveal functional genetic variants in human tissues

An intricate network of cis- and trans-elements acts on RNA N 6-methyladenosine (m6A), which in turn may affect gene expression and, ultimately, human health. A complete understanding of this network requires new approaches to accurately measure the subtle m6A differences arising from genetic variants, many of which have been associated with common diseases. To address this gap, we developed a method to accurately and sensitively detect transcriptome-wide allele-specific m6A (ASm6A) from MeRIP-seq data and applied it to uncover 12,056 high-confidence ASm6A modifications from 25 human tissues. We also identified 1184 putative functional variants for ASm6A regulation, a subset of which we experimentally validated. Importantly, we found that many of these ASm6A-associated genetic variants were enriched for common disease-associated and complex trait-associated risk loci, and verified that two disease risk variants can change m6A modification status. Together, this work provides a tool to detangle the dynamic network of RNA modifications at the allelic level and highlights the interplay of m6A and genetics in human health and disease.

Cell type deconvolution of methylated cell-free DNA at the resolution of individual reads

Cell-free DNA (cfDNA) are DNA fragments originating from dying cells that are detectable in bodily fluids, such as the plasma. Accelerated cell death, for example caused by disease, induces an elevated concentration of cfDNA. As a result, determining the cell type origins of cfDNA molecules can provide information about an individual's health. In this work, we aim to increase the sensitivity of methylation-based cell type deconvolution by adapting an existing method, CelFiE, which uses the methylation beta values of individual CpG sites to estimate cell type proportions. Our new method, CelFEER, instead differentiates cell types by the average methylation values within individual reads. We additionally improved the originally reported performance of CelFiE by using a new approach for finding marker regions that are differentially methylated between cell types. We show that CelFEER estimates cell type proportions with a higher correlation (r = 0.94 ± 0.04) than CelFiE (r = 0.86 ± 0.09) on simulated mixtures of cell types. Moreover, we show that the cell type proportion estimated by CelFEER can differentiate between ALS patients and healthy controls, between pregnant women in their first and third trimester, and between pregnant women with and without gestational diabetes.

Rare genetic variants underlie outlying levels of DNA methylation and gene-expression

Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on DNA methylation (DNAm) as effect sizes are expected to be larger for molecular traits compared with complex traits. Here, we investigate DNAm in healthy ageing populations-the Lothian Birth Cohorts of 1921 and 1936-and identify both transient and stable outlying DNAm levels across the genome. We find an enrichment of rare genetic single nucleotide polymorphisms (SNPs) within 1 kb of DNAm sites in individuals with stable outlying DNAm, implying genetic control of this extreme variation. Using a family-based cohort, the Brisbane Systems Genetics Study, we observed increased sharing of DNAm outliers among more closely related individuals, consistent with these outliers being driven by rare genetic variation. We demonstrated that outlying DNAm levels have a functional consequence on gene expression levels, with extreme levels of DNAm being associated with gene expression levels toward the tails of the population distribution. This study demonstrates the role of rare SNPs in the phenotypic variation of DNAm and the effect of extreme levels of DNAm on gene expression.

A global view of the genetic basis of Alzheimer disease

The risk of Alzheimer disease (AD) increases with age, family history and informative genetic variants. Sadly, there is still no cure or means of prevention. As in other complex diseases, uncovering genetic causes of AD could identify underlying pathological mechanisms and lead to potential treatments. Rare, autosomal dominant forms of AD occur in middle age as a result of highly penetrant genetic mutations, but the most common form of AD occurs later in life. Large-scale, genome-wide analyses indicate that 70 or more genes or loci contribute to AD. One of the major factors limiting progress is that most genetic data have been obtained from non-Hispanic white individuals in Europe and North America, preventing the development of personalized approaches to AD in individuals of other ethnicities. Fortunately, emerging genetic data from other regions - including Africa, Asia, India and South America - are now providing information on the disease from a broader range of ethnicities. Here, we summarize the current knowledge on AD genetics in populations across the world. We predominantly focus on replicated genetic discoveries but also include studies in ethnic groups where replication might not be feasible. We attempt to identify gaps that need to be addressed to achieve a complete picture of the genetic and molecular factors that drive AD in individuals across the globe.

NOMe-HiC: joint profiling of genetic variant, DNA methylation, chromatin accessibility, and 3D genome in the same DNA molecule

Cis-regulatory elements are coordinated to regulate the expression of their targeted genes. However, the joint measurement of cis-regulatory elements' activities and their interactions in spatial proximity is limited by the current sequencing approaches. We describe a method, NOMe-HiC, which simultaneously captures single-nucleotide polymorphisms, DNA methylation, chromatin accessibility (GpC methyltransferase footprints), and chromosome conformation changes from the same DNA molecule, together with the transcriptome, in a single assay. NOMe-HiC shows high concordance with state-of-the-art mono-omic assays across different molecular measurements and reveals coordinated chromatin accessibility at distal genomic segments in spatial proximity and novel types of long-range allele-specific chromatin accessibility.

Epigenetic and Genetic Population Structure is Coupled in a Marine Invertebrate

Delineating the relative influence of genotype and the environment on DNA methylation is critical for characterizing the spectrum of organism fitness as driven by adaptation and phenotypic plasticity. In this study, we integrated genomic and DNA methylation data for two distinct Olympia oyster (Ostrea lurida) populations while controlling for within-generation environmental influences. In addition to providing the first characterization of genome-wide DNA methylation patterns in the oyster genus Ostrea, we identified 3,963 differentially methylated loci between populations. Our results show a clear coupling between genetic and epigenetic patterns of variation, with 27% of variation in interindividual methylation differences explained by genotype. Underlying this association are both direct genetic changes in CpGs (CpG-SNPs) and genetic variation with indirect influence on methylation (mQTLs). When comparing measures of genetic and epigenetic population divergence at specific genomic regions this relationship surprisingly breaks down, which has implications for the methods commonly used to study epigenetic and genetic coupling in marine invertebrates.

DNA Methylation Signature of Aging: Potential Impact on the Pathogenesis of Parkinson's Disease

Regulation of gene expression by epigenetic modifications means lasting and heritable changes in the function of genes without alterations in the DNA sequence. Of all epigenetic mechanisms identified thus far, DNA methylation has been of particular interest in both aging and age-related disease research over the last decade given the consistency of site-specific DNA methylation changes during aging that can predict future health and lifespan. An increasing line of evidence has implied the dynamic nature of DNA (de)methylation events that occur throughout the lifespan has a role in the pathophysiology of aging and age-associated neurodegenerative conditions, including Parkinson's disease (PD). In this regard, PD methylome shows, to some extent, similar genome-wide changes observed in the methylome of healthy individuals of matching age. In this review, we start by providing a brief overview of studies outlining global patterns of DNA methylation, then its mechanisms and regulation, within the context of aging and PD. Considering diverging lines of evidence from different experimental and animal models of neurodegeneration and how they combine to shape our current understanding of tissue-specific changes in DNA methylome in health and disease, we report a high-level comparison of the genomic methylation landscapes of brain, with an emphasis on dopaminergic neurons in PD and in natural aging. We believe this will be particularly useful for systematically dissecting overlapping genome-wide alterations in DNA methylation during PD and healthy aging, and for improving our knowledge of PD-specific changes in methylation patterns independent of aging process.

Genomic imprinting-like monoallelic paternal expression determines sex of channel catfish

The X and Y chromosomes of channel catfish have the same gene contents. Here, we report allelic hypermethylation of the X chromosome within the sex determination region (SDR). Accordingly, the X-borne hydin-1 gene was silenced, whereas the Y-borne hydin-1 gene was expressed, making monoallelic expression of hydin-1 responsible for sex determination, much like genomic imprinting. Treatment with a methylation inhibitor, 5-aza-dC, erased the epigenetic marks within the SDR and caused sex reversal of genetic females into phenotypic males. After the treatment, hydin-1 and six other genes related to cell cycle control and proliferative growth were up-regulated, while three genes related to female sex differentiation were down-regulated in genetic females, providing additional support for epigenetic sex determination in catfish. This mechanism of sex determination provides insights into the plasticity of genetic sex determination in lower vertebrates and its connection with temperature sex determination where DNA methylation is broadly involved.

Noninvasive detection of pancreatic ductal adenocarcinoma using the methylation signature of circulating tumour DNA

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has the lowest overall survival rate primarily due to the late onset of symptoms and rapid progression. Reliable and accurate tests for early detection are lacking. We aimed to develop a noninvasive test for early PDAC detection by capturing the circulating tumour DNA (ctDNA) methylation signature in blood.

METHODS

Genome-wide methylation profiles were generated from PDAC and nonmalignant tissues and plasma. Methylation haplotype blocks (MHBs) were examined to discover de novo PDAC markers. They were combined with multiple cancer markers and screened for PDAC classification accuracy. The most accurate markers were used to develop PDACatch, a targeted methylation sequencing assay. PDACatch was applied to additional PDAC and healthy plasma cohorts to train, validate and independently test a PDAC-discriminating classifier. Finally, the classifier was compared and integrated with carbohydrate antigen 19-9 (CA19-9) to evaluate and maximize its accuracy and utility.

RESULTS

In total, 90 tissues and 546 plasma samples were collected from 232 PDAC patients, 25 chronic pancreatitis (CP) patients and 323 healthy controls. Among 223 PDAC cases with known stage information, 43/119/38/23 cases were of Stage I/II/III/IV. A total of 171 de novo PDAC-specific markers and 595 multicancer markers were screened for PDAC classification accuracy. The top 185 markers were included in PDACatch, from which a 56-marker classifier for PDAC plasma was trained, validated and independently tested. It achieved an area under the curve (AUC) of 0.91 in both the validation (31 PDAC, 26 healthy; sensitivity = 84%, specificity = 89%) and independent tests (74 PDAC, 65 healthy; sensitivity = 82%, specificity = 88%). Importantly, the PDACatch classifier detected CA19-9-negative PDAC plasma at sensitivities of 75 and 100% during the validation and independent tests, respectively. It was more sensitive than CA19-9 in detecting Stage I (sensitivity = 80 and 68%, respectively) and early-stage (Stage I-IIa) PDAC (sensitivity = 76 and 70%, respectively). A combinatorial classifier integrating PDACatch and CA19-9 outperformed (AUC=0.94) either PDACatch (0.91) or CA19-9 (0.89) alone (p < 0.001).

CONCLUSIONS

The PDACatch assay demonstrated high sensitivity for early PDAC plasma, providing potential utility for noninvasive detection of early PDAC and indicating the effectiveness of methylation haplotype analyses in discovering robust cancer markers.

mHapTk: a comprehensive toolkit for the analysis of DNA methylation haplotypes

SUMMARY

Bisulfite sequencing remains the gold standard technique to detect DNA methylation profiles at single-nucleotide resolution. The DNA methylation status of CpG sites on the same fragment represents a discrete methylation haplotype (mHap). The mHap-level metrics were demonstrated to be promising cancer biomarkers and explain more gene expression variation than average methylation. However, most existing tools focus on average methylation and neglect mHap patterns. Here, we present mHapTk, a comprehensive python toolkit for the analysis of DNA mHap. It calculates eight mHap-level summary statistics in predefined regions or across individual CpG in a genome-wide manner. It identifies methylation haplotype blocks, in which methylations of pairwise CpGs are tightly correlated. Furthermore, mHap patterns can be visualized with the built-in functions in mHapTk or external tools such as IGV and deepTools.

AVAILABILITY AND IMPLEMENTATION

https://jiantaoshi.github.io/mhaptk/index.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Methyl-SNP-seq reveals dual readouts of methylome and variome at molecule resolution while enabling target enrichment

Covalent modifications of genomic DNA are crucial for most organisms to survive. Amplicon-based high-throughput sequencing technologies erase all DNA modifications to retain only sequence information for the four canonical nucleobases, necessitating specialized technologies for ascertaining epigenetic information. To also capture base modification information, we developed Methyl-SNP-seq, a technology that takes advantage of the complementarity of the double helix to extract the methylation and original sequence information from a single DNA molecule. More specifically, Methyl-SNP-seq uses bisulfite conversion of one of the strands to identify cytosine methylation while retaining the original four-bases sequence information on the other strand. As both strands are locked together to link the dual readouts on a single paired-end read, Methyl-SNP-seq allows detecting the methylation status of any DNA even without a reference genome. Because one of the strands retains the original four nucleotide composition, Methyl-SNP-seq can also be used in conjunction with standard sequence-specific probes for targeted enrichment and amplification. We show the usefulness of this technology in a broad spectrum of applications ranging from allele-specific methylation analysis in humans to identification of methyltransferase specificity in complex bacterial communities.

The Mutagenic Consequences of DNA Methylation within and across Generations

DNA methylation is an epigenetic modification with wide-ranging consequences across the life of an organism. This modification can be stable, persisting through development despite changing environmental conditions. However, in other contexts, DNA methylation can also be flexible, underlying organismal phenotypic plasticity. One underappreciated aspect of DNA methylation is that it is a potent mutagen; methylated cytosines mutate at a much faster rate than other genetic motifs. This mutagenic property of DNA methylation has been largely ignored in eco-evolutionary literature, despite its prevalence. Here, we explore how DNA methylation induced by environmental and other factors could promote mutation and lead to evolutionary change at a more rapid rate and in a more directed manner than through stochastic genetic mutations alone. We argue for future research on the evolutionary implications of DNA methylation driven mutations both within the lifetime of organisms, as well as across timescales.

Promoter Methylation of QKI as a Potential Specific Biomarker for Early Detection of Colorectal Cancer

Early and specific detection of cancer provides an opportunity for appropriate treatment. Although studies have suggested that QKI is a tumor suppressor gene, no studies have evaluated the diagnostic utility of QKI methylation in colorectal cancer (CRC). Here, we evaluated the methylation status of QKI by integrating the methylation data of tissues and cell lines of multiple cancer types. The diagnostic performance of QKI was analyzed in the discovery dataset from the TCGA CRC 450K array (n = 440) and tested in the test sets (n = 845) from the GEO. The methylation level of QKI was further validated in our independent dataset (n = 388) using targeted bisulfite sequencing. All detected CpG sites in the QKI promoter showed CRC-specific hypermethylation in 31 types of tumor tissues. In the discovery dataset, six consecutive CpG sites achieved high diagnostic performances, with AUCs ranging from 0.821 to 0.930. In the test set, a region (chr6: 163,834,452–163,834,924) including four consecutive CpG sites had robust diagnostic ability in distinguishing CRC and adenoma from normal samples. In the validation dataset, similar robust results were observed in both early- and advanced-stage CRC patients. In addition, QKI exhibited hypermethylation in the cfDNA of patients with CRC (n = 14). Collectively, the QKI promoter is a CRC-specific methylation biomarker and holds great promise for improving the diagnosis using minimally invasive biopsy.

Allelic expression imbalance of PIK3CA mutations is frequent in breast cancer and prognostically significant

PIK3CA mutations are the most common in breast cancer, particularly in the estrogen receptor-positive cohort, but the benefit of PI3K inhibitors has had limited success compared with approaches targeting other less common mutations. We found a frequent allelic expression imbalance between the missense mutant and wild-type PIK3CA alleles in breast tumors from the METABRIC (70.2%) and the TCGA (60.1%) projects. When considering the mechanisms controlling allelic expression, 27.7% and 11.8% of tumors showed imbalance due to regulatory variants in cis, in the two studies respectively. Furthermore, preferential expression of the mutant allele due to cis-regulatory variation is associated with poor prognosis in the METABRIC tumors (P = 0.031). Interestingly, ER-, PR-, and HER2+ tumors showed significant preferential expression of the mutated allele in both datasets. Our work provides compelling evidence to support the clinical utility of PIK3CA allelic expression in breast cancer in identifying patients of poorer prognosis, and those with low expression of the mutated allele, who will unlikely benefit from PI3K inhibitors. Furthermore, our work proposes a model of differential regulation of a critical cancer-promoting gene in breast cancer.

Regulation of glutamate transport and neuroinflammation in a term newborn rat model of hypoxic–ischaemic brain injury

In the newborn brain, moderate-severe hypoxia–ischaemia induces glutamate excitotoxicity and inflammation, possibly via dysregulation of candidate astrocytic glutamate transporter ( Glt1) and pro-inflammatory cytokines (e.g. Tnfα, Il1β, Il6). Epigenetic mechanisms may mediate dysregulation. Hypotheses: (1) hypoxia–ischaemia dysregulates mRNA expression of these candidate genes; (2) expression changes in Glt1 are mediated by DNA methylation changes; and (3) methylation values in brain and blood are correlated. Seven-day-old rat pups ( n = 42) were assigned to nine groups based on treatment (for each timepoint: naïve ( n = 3), sham ( n = 3), hypoxia–ischaemia ( n = 8) and timepoint for tissue collection (6, 12 and 24 h post-hypoxia). Moderate hypoxic–ischemic brain injury was induced via ligation of the left common carotid artery followed by 100 min hypoxia (8% O2, 36°C). mRNA was quantified in cortex and hippocampus for the candidate genes, myelin ( Mbp), astrocytic ( Gfap) and neuronal ( Map2) markers (qPCR). DNA methylation was measured for Glt1 in cortex and blood (bisulphite pyrosequencing). Hypoxia–ischaemia induced pro-inflammatory cytokine upregulation in both brain regions at 6 h. This was accompanied by gene expression changes potentially indicating onset of astrogliosis and myelin injury. There were no significant changes in expression or promoter DNA methylation of Glt1. This pilot study supports accumulating evidence that hypoxia–ischaemia causes neuroinflammation in the newborn brain and prioritises further expression and DNA methylation analyses focusing on this pathway. Epigenetic blood biomarkers may facilitate identification of high-risk newborns at birth, maximising chances of neuroprotective interventions.

Integrating whole genome sequencing, methylation, gene expression, topological associated domain information in regulatory mutation prediction: a study of follicular lymphoma

A major challenge in human genetics is of the analysis of the interplay between genetic and epigenetic factors in a multifactorial disease like cancer. Here, a novel methodology is proposed to investigate genome-wide regulatory mechanisms in cancer, as studied with the example of follicular Lymphoma (FL). In a first phase, a new machine-learning method is designed to identify Differentially Methylated Regions (DMRs) by computing six attributes. In a second phase, an integrative data analysis method is developed to study regulatory mutations in FL, by considering differential methylation information together with DNA sequence variation, differential gene expression, 3D organization of genome (e.g., topologically associated domains), and enriched biological pathways. Resulting mutation block-gene pairs are further ranked to find out the significant ones. By this approach, BCL2 and BCL6 were identified as top-ranking FL-related genes with several mutation blocks and DMRs acting on their regulatory regions. Two additional genes, CDCA4 and CTSO, were also found in top rank with significant DNA sequence variation and differential methylation in neighboring areas, pointing towards their potential use as biomarkers for FL. This work combines both genomic and epigenomic information to investigate genome-wide gene regulatory mechanisms in cancer and contribute to devising novel treatment strategies.

Methylation of Immune-Related Genes in Peripheral Blood Leukocytes and Breast Cancer

Abnormal DNA methylation contributes to breast cancer (BC). Immune-related genes play crucial roles in BC development and progression. This study aims to investigate the effect of methylation of immune-related genes in peripheral blood leukocytes (PBLs) on BC risk. GSE51032 and GSE104942 datasets were used to identify significantly differentially methylated CpG sites (DMCs) of immune-related genes. A case-control study was conducted using MethylTarget sequencing to validate the relationship between the methylation levels of the screened genes and BC risk. We also evaluated the association between methylation haplotypes of screened genes and BC risk. Moreover, we sorted the blood leukocytes into T cells, B cells, and monocytes to detect the difference of DNA methylation in different cell subtypes. A total of five DMCs were screened from GEO datasets, including cg01760846 (PSMC1), cg07141527 (SPPL3), cg15658543 (CARD11), cg21568368 (PSMB8), and cg24045276 (NCF2). In the case-control study, there were significant associations between methylation of the CpG sites in the five genes and BC risk. Methylation haplotype burdens of PSMC1, CARD11, and PSMB8 were associated with reduced BC risk. Moreover, there were heterogeneities in the methylation levels of the genes in different cell subtypes. In conclusion, methylation of PSMC1, SPPL3, CARD11, PSMB8, and NCF2 in PBLs were associated with BC risk. The five-gene methylation could be the potential biomarkers for predicting BC risk.

Novel role for caspase recruitment domain family member 14 and its genetic variant rs11652075 in skin filaggrin homeostasis

BACKGROUND

Low epidermal filaggrin (FLG) is a risk factor for atopic dermatitis (AD) and allergic comorbidity. FLG mutations do not fully explain the variation in epidermal FLG levels, highlighting that other genetic loci may also regulate FLG expression.

OBJECTIVE

We sought to identify genetic loci that regulate FLG expression and elucidate their functional and mechanistic consequences.

METHODS

A genome-wide association study of quantified skin FLG expression in lesional and baseline non(never)-lesional skin of children with AD in the Mechanisms of Progression of Atopic Dermatitis to Asthma in Children cohort was conducted. Clustered regularly interspaced short palindromic repeat approaches were used to create isogenic human keratinocytes differing only at the identified variant rs11652075, and caspase recruitment domain family member 14 (CARD14)-deficient keratinocytes for subsequent mechanistic studies.

RESULTS

The genome-wide association study identified the CARD14 rs11652075 variant to be associated with FLG expression in non(never)-lesional skin of children with AD. Rs11652075 is a CARD14 expression quantitative trait locus in human skin and primary human keratinocytes. The T variant destroys a functional cytosine-phosphate-guanine site, resulting in reduced cytosine-phosphate-guanine methylation at this site (but not neighboring sites) in TT and CT compared with CC primary human keratinocytes and Mechanisms of Progression of Atopic Dermatitis to Asthma in Children children's skin samples, and rs11652075 increases CARD14 expression in an allele-specific fashion. Furthermore, studies in clustered regularly interspaced short palindromic repeat-generated CC and TT isogenic keratinocytes, as well as CARD14-haplosufficient and deficient keratinocytes, reveal that IL-17A regulates FLG expression via CARD14, and that the underlying mechanisms are dependent on the rs11652075 genotype.

CONCLUSIONS

Our study identifies CARD14 as a novel regulator of FLG expression in the skin of children with AD. Furthermore, CARD14 regulates skin FLG homeostasis in an rs11652075-dependent fashion.

rs62139665 Polymorphism in the Promoter Region of EpCAM Is Associated With Hepatitis C Virus-Related Hepatocellular Carcinoma Risk in Egyptians

Hepatocellular carcinoma (HCC) is a universal health problem that is particularly alarming in Egypt. The major risk factor for HCC is hepatitis C virus (HCV) infection which is a main burden in Egypt. The epithelial cell adhesion molecule (EpCAM) is a stem cell marker involved in the tumorigenesis and progression of many malignancies, including HCC. We investigated the association of -935 C/G single nucleotide polymorphism in EpCAM promoter region (rs62139665) with HCC risk, EpCAM expression and overall survival in Egyptians. A total of 266 patients (128 HCV and 138 HCC cases) and 117 age- and sex-matched controls participated in this study. Genotyping, performed using allelic discrimination and confirmed by sequencing, revealed a significant association between EpCAM rs62139665 and HCC susceptibility, with higher GG genotype and G allele distribution in HCC patients than in non-HCC subjects. Such association was not detected in HCV patients compared to controls. EpCAM gene expression levels, determined in blood by RT-qPCR, and its serum protein expression levels, determined by ELISA, were significantly higher in GG relative to GC+CC genotype carriers in HCV and HCC patients in a recessive model. ROC analysis of EpCAM protein levels revealed significant discriminatory power between HCC patients and non-HCC subjects, with improved diagnostic accuracy when combining α-fetoprotein and EpCAM compared to that of α-fetoprotein alone. Altogether, EpCAM rs62139665 polymorphism is significantly associated with HCC and with EpCAM gene and protein expression levels in the Egyptian population. Moreover, serum EpCAM levels may hold promise for HCC diagnosis and for improving the diagnostic accuracy of α-fetoprotein.

High-throughput Molecular Analysis of Pseudohypoparathyroidism 1b Patients Reveals Novel Genetic and Epigenetic Defects

CONTEXT

Patients with pseudohypoparathyroidism type 1b (PHP1b) show disordered imprinting of the maternal GNAS allele or paternal uniparental disomy (UPD). Genetic deletions in STX16 or in upstream exons of GNAS are present in many familial but not sporadic cases.

OBJECTIVE

Characterization of epigenetic and genetic defects in patients with PHP1b.

DESIGN AND PATIENTS

DNA from 84 subjects, including 26 subjects with sporadic PHP1b, 27 affected subjects and 17 unaffected and/or obligate gene carriers from 12 PHP1b families, 11 healthy individuals, and 3 subjects with PHP1a was subjected to quantitative pyrosequencing of GNAS differentially methylated regions (DMRs), microarray analysis, and microsatellite haplotype analysis.

SETTING

Academic medical center.

MAIN OUTCOME MEASUREMENTS

Molecular pathology of PHP1b.

RESULTS

Healthy subjects, unaffected family members and obligate carriers of paternal PHP1b alleles, and subjects with PHP1a showed normal methylation of all DMRs. All PHP1b subjects showed loss of methylation (LOM) at the exon A/B DMR. Affected members of 9 PHP1b kindreds showed LOM only at the exon A/B DMR, which was associated with a 3-kb deletion of STX16 exons 4 through 6 in 7 families and a novel deletion of STX16 and adjacent NEPEPL1 in 1 family. A novel NESP deletion was found in 1 of 2 other families with more extensive methylation defects. One sporadic PHP1b had UPD of 20q, 2 had 3-kb STX16 deletions, and 5 had apparent epigenetic mosaicism.

CONCLUSIONS

We found diverse patterns of defective methylation and identified novel or previously known mutations in 9 of 12 PHP1b families.

Epigenetic marks in suicide: a review

Suicide is a complex phenomenon and a global public health problem that involves several biological factors that could contribute to the pathophysiology of suicide. There is evidence that epigenetic factors influence some psychiatric disorders, suggesting a predisposition to suicide or suicidal behavior. Here, we review studies of molecular mechanisms of suicide in an epigenetic perspective in the postmortem brain of suicide completers and peripheral blood cells of suicide attempters. Besides, we include studies of gene-specific DNA methylation, epigenome-wide association, histone modification, and interfering RNAs as epigenetic factors. This review provides an overview of the epigenetic mechanisms described in different biological systems related to suicide, contributing to an understanding of the genetic regulation in suicide. We conclude that epigenetic marks are potential biomarkers in suicide, and they could become attractive therapeutic targets due to their reversibility and importance in regulating gene expression.

The DNA methylation haplotype (mHap) format and mHapTools

SUMMARY

Bisulfite sequencing (BS-seq) is currently the gold standard for measuring genome-wide DNA methylation profiles at single-nucleotide resolution. Most analyses focus on mean CpG methylation and ignore methylation states on the same DNA fragments [DNA methylation haplotypes (mHaps)]. Here, we propose mHap, a simple DNA mHap format for storing DNA BS-seq data. This format reduces the size of a BAM file by 40- to 140-fold while retaining complete read-level CpG methylation information. It is also compatible with the Tabix tool for fast and random access. We implemented a command-line tool, mHapTools, for converting BAM/SAM files from existing platforms to mHap files as well as post-processing DNA methylation data in mHap format. With this tool, we processed all publicly available human reduced representation bisulfite sequencing data and provided these data as a comprehensive mHap database.

AVAILABILITY AND IMPLEMENTATION

https://jiantaoshi.github.io/mHap/index.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mapping methylation quantitative trait loci in cardiac tissues nominates risk loci and biological pathways in congenital heart disease

Background

Most congenital heart defects (CHDs) result from complex interactions among genetic susceptibilities, epigenetic modifications, and maternal environmental exposures. Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation will enhance our understanding of pathogenesis in this important type of congenital disorder. We investigated cis-acting effects of genetic single nucleotide polymorphisms (SNPs) on local DNA methylation patterns within 83 cardiac tissue samples and prioritized their contributions to CHD risk by leveraging results of CHD genome-wide association studies (GWAS) and their effects on cardiac gene expression.

Results

We identified 13,901 potential methylation quantitative trait loci (mQTLs) with a false discovery threshold of 5%. Further co-localization analyses and Mendelian randomization indicated that genetic variants near the HLA-DRB6 gene on chromosome 6 may contribute to CHD risk by regulating the methylation status of nearby CpG sites. Additional SNPs in genomic regions on chromosome 10 (TNKS2-AS1 gene) and chromosome 14 (LINC01629 gene) may simultaneously influence epigenetic and transcriptomic variations within cardiac tissues.

Conclusions

Our results support the hypothesis that genetic variants may influence the risk of CHDs through regulating the changes of DNA methylation and gene expression. Our results can serve as an important source of information that can be integrated with other genetic studies of heart diseases, especially CHDs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00975-2.

Novel DNA methylation marker discovery by assumption-free genome-wide association analysis of cognitive function in twins

Privileged by rapid increase in available epigenomic data, epigenome-wide association studies (EWAS) are to make a profound contribution to understand the molecular mechanism of DNA methylation in cognitive aging. Current statistical methods used in EWAS are dominated by models based on multiple assumptions, for example, linear relationship between molecular profiles and phenotype, normal distribution for the methylation data and phenotype. In this study, we applied an assumption-free method, the generalized correlation coefficient (GCC), and compare it to linear models, namely the linear mixed model and kinship model. We use DNA methylation associated with a cognitive score in 400 and 206 twins as discovery and replication samples respectively. DNA methylation associated with cognitive function using GCC, linear mixed model, and kinship model, identified 65 CpGs (p < 1e-04) from discovery sample displaying both nonlinear and linear correlations. Replication analysis successfully replicated 9 of these top CpGs. When combining results of GCC and linear models to cover diverse patterns of relationships, we identified genes like KLHDC4, PAPSS2, and MRPS18B as well as pathways including focal adhesion, axon guidance, and some neurological signaling. Genomic region-based analysis found 15 methylated regions harboring 11 genes, with three verified in gene expression analysis, also the 11 genes were related to top functional clusters including neurohypophyseal hormone and maternal aggressive behaviors. The GCC approach detects valuable methylation sites missed by traditional linear models. A combination of methylation markers from GCC and linear models enriched biological pathways sensible in neurological function that could implicate cognitive performance and cognitive aging.

Elucidation of the Genomic-Epigenomic Interaction Landscape of Aggressive Prostate Cancer

Background

Majority of prostate cancer (PCa) deaths are attributed to localized high-grade aggressive tumours which progress rapidly to metastatic disease. A critical unmet need in clinical management of PCa is discovery and characterization of the molecular drivers of aggressive tumours. The development and progression of aggressive PCa involve genetic and epigenetic alterations occurring in the germline, somatic (tumour), and epigenomes. To date, interactions between genes containing germline, somatic, and epigenetic mutations in aggressive PCa have not been characterized. The objective of this investigation was to elucidate the genomic-epigenomic interaction landscape in aggressive PCa to identify potential drivers aggressive PCa and the pathways they control. We hypothesized that aggressive PCa originates from a complex interplay between genomic (both germline and somatic mutations) and epigenomic alterations. We further hypothesized that these complex arrays of interacting genomic and epigenomic factors affect gene expression, molecular networks, and signaling pathways which in turn drive aggressive PCa.

Methods

We addressed these hypotheses by performing integrative data analysis combining information on germline mutations from genome-wide association studies with somatic and epigenetic mutations from The Cancer Genome Atlas using gene expression as the intermediate phenotype.

Results

The investigation revealed signatures of genes containing germline, somatic, and epigenetic mutations associated with aggressive PCa. Aberrant DNA methylation had effect on gene expression. In addition, the investigation revealed molecular networks and signalling pathways enriched for germline, somatic, and epigenetic mutations including the STAT3, PTEN, PCa, ATM, AR, and P53 signalling pathways implicated in aggressive PCa.

Conclusions

The study demonstrated that integrative analysis combining diverse omics data is a powerful approach for the discovery of potential clinically actionable biomarkers, therapeutic targets, and elucidation of oncogenic interactions between genomic and epigenomic alterations in aggressive PCa.

Deciphering the genetic code of DNA methylation

DNA methylation plays crucial roles in many biological processes and abnormal DNA methylation patterns are often observed in diseases. Recent studies have shed light on cis-acting DNA elements that regulate locus-specific DNA methylation, which involves transcription factors, histone modification and DNA secondary structures. In addition, several recent studies have surveyed DNA motifs that regulate DNA methylation and suggest potential applications in diagnosis and prognosis. Here, we discuss the current biological foundation for the cis-acting genetic code that regulates DNA methylation. We review the computational models that predict DNA methylation with genetic features and discuss the biological insights revealed from these models. We also provide an in-depth discussion on how to leverage such knowledge in clinical applications, particularly in the context of liquid biopsy for early cancer diagnosis and treatment.

Role of DNA Methylation in Mediating Genetic Risk of Psychiatric Disorders

Psychiatric disorders are common, complex, and heritable conditions estimated to be the leading cause of disability worldwide. The last decade of research in genomics of psychiatry, performed by multinational, and multicenter collaborative efforts on hundreds of thousands of mental disorder cases and controls, provided invaluable insight into the genetic risk variants of these conditions. With increasing cohort sizes, more risk variants are predicted to be identified in the near future, but there appears to be a knowledge gap in understanding how these variants contribute to the pathophysiology of psychiatric disorders. Majority of the identified common risk single-nucleotide polymorphisms (SNPs) are non-coding but are enriched in regulatory regions of the genome. It is therefore of great interest to study the impact of identified psychiatric disorders' risk SNPs on DNA methylation, the best studied epigenetic modification, playing a pivotal role in the regulation of transcriptomic processes, brain development, and functioning. This work outlines the mechanisms through which risk SNPs can impact DNA methylation levels and provides a summary of current evidence on the role of DNA methylation in mediating the genetic risk of psychiatric disorders.

Intergenerational transfer of DNA methylation marks in the honey bee

The evolutionary significance of epigenetic inheritance is controversial. While epigenetic marks such as DNA methylation can affect gene function and change in response to environmental conditions, their role as carriers of heritable information is often considered anecdotal. Indeed, near-complete DNA methylation reprogramming, as occurs during mammalian embryogenesis, is a major hindrance for the transmission of nongenetic information between generations. Yet it remains unclear how general DNA methylation reprogramming is across the tree of life. Here we investigate the existence of epigenetic inheritance in the honey bee. We studied whether fathers can transfer epigenetic information to their daughters through DNA methylation. We performed instrumental inseminations of queens, each with four different males, retaining half of each male's semen for whole genome bisulfite sequencing. We then compared the methylation profile of each father's somatic tissue and semen with the methylation profile of his daughters. We found that DNA methylation patterns were highly conserved between tissues and generations. There was a much greater similarity of methylomes within patrilines (i.e., father-daughter subfamilies) than between patrilines in each colony. Indeed, the samples' methylomes consistently clustered by patriline within colony. Samples from the same patriline had twice as many shared methylated sites and four times fewer differentially methylated regions compared to samples from different patrilines. Our findings indicate that there is no DNA methylation reprogramming in bees and, consequently, that DNA methylation marks are stably transferred between generations. This points to a greater evolutionary potential of the epigenome in invertebrates than there is in mammals.

CTCF-Mediated Genome Architecture Regulates the Dosage of Mitotically Stable Mono-allelic Expression of Autosomal Genes

The mechanisms that guide the clonally stable random mono-allelic expression of autosomal genes remain enigmatic. We show that (1) mono-allelically expressed (MAE) genes are assorted and insulated from bi-allelically expressed (BAE) genes through CTCF-mediated chromatin loops; (2) the cell-type-specific dynamics of mono-allelic expression coincides with the gain and loss of chromatin insulator sites; (3) dosage of MAE genes is more sensitive to the loss of chromatin insulation than that of BAE genes; and (4) inactive alleles of MAE genes are significantly more insulated than active alleles and are de-repressed upon CTCF depletion. This alludes to a topology wherein the inactive alleles of MAE genes are insulated from the spatial interference of transcriptional states from the neighboring bi-allelic domains via CTCF-mediated loops. We propose that CTCF functions as a typical insulator on inactive alleles, but facilitates transcription through enhancer-linking on active allele of MAE genes, indicating widespread allele-specific regulatory roles of CTCF.

Association of CNVs with methylation variation

Germline copy number variants (CNVs) and single-nucleotide polymorphisms (SNPs) form the basis of inter-individual genetic variation. Although the phenotypic effects of SNPs have been extensively investigated, the effects of CNVs is relatively less understood. To better characterize mechanisms by which CNVs affect cellular phenotype, we tested their association with variable CpG methylation in a genome-wide manner. Using paired CNV and methylation data from the 1000 genomes and HapMap projects, we identified genome-wide associations by methylation quantitative trait locus (mQTL) analysis. We found individual CNVs being associated with methylation of multiple CpGs and vice versa. CNV-associated methylation changes were correlated with gene expression. CNV-mQTLs were enriched for regulatory regions, transcription factor-binding sites (TFBSs), and were involved in long-range physical interactions with associated CpGs. Some CNV-mQTLs were associated with methylation of imprinted genes. Several CNV-mQTLs and/or associated genes were among those previously reported by genome-wide association studies (GWASs). We demonstrate that germline CNVs in the genome are associated with CpG methylation. Our findings suggest that structural variation together with methylation may affect cellular phenotype.

pWGBSSimla: a profile-based whole-genome bisulfite sequencing data simulator incorporating methylation QTLs, allele-specific methylations and differentially methylated regions

MOTIVATION

DNA methylation plays an important role in regulating gene expression. DNA methylation is commonly analyzed using bisulfite sequencing (BS-seq)-based designs, such as whole-genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS) and oxidative bisulfite sequencing (oxBS-seq). Furthermore, there has been growing interest in investigating the roles that genetic variants play in changing the methylation levels (i.e. methylation quantitative trait loci or meQTLs), how methylation regulates the imprinting of gene expression (i.e. allele-specific methylation or ASM) and the differentially methylated regions (DMRs) among different cell types. However, none of the current simulation tools can generate different BS-seq data types (e.g. WGBS, RRBS and oxBS-seq) while modeling meQTLs, ASM and DMRs.

RESULTS

We developed profile-based whole-genome bisulfite sequencing data simulator (pWGBSSimla), a profile-based bisulfite sequencing data simulator, which simulates WGBS, RRBS and oxBS-seq data for different cell types based on real data. meQTLs and ASM are modeled based on the block structures of the methylation status at CpGs, whereas the simulation of DMRs is based on observations of methylation rates in real data. We demonstrated that pWGBSSimla adequately simulates data and allows performance comparisons among different methylation analysis methods.

AVAILABILITY AND IMPLEMENTATION

pWGBSSimla is available at https://omicssimla.sourceforge.io.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Disease-associated KIF3A variants alter gene methylation and expression impacting skin barrier and atopic dermatitis risk

Single nucleotide polymorphisms (SNPs) in the gene encoding kinesin family member 3A, KIF3A, have been associated with atopic dermatitis (AD), a chronic inflammatory skin disorder. We find that KIF3A SNP rs11740584 and rs2299007 risk alleles create cytosine-phosphate-guanine sites, which are highly methylated and result in lower KIF3A expression, and this methylation is associated with increased transepidermal water loss (TEWL) in risk allele carriers. Kif3a^K14∆/∆ mice have increased TEWL, disrupted junctional proteins, and increased susceptibility to develop AD. Thus, KIF3A is required for skin barrier homeostasis whereby decreased KIF3A skin expression causes disrupted skin barrier function and promotes development of AD.

Genetic variants in KIF3A are associated with atopic dermatitis (AD). Here, the authors identify two AD-risk alleles that show high methylation resulting in lower KIF3A expression. Mice with epidermis-specific loss of Kif3a show disrupted skin barrier homeostasis and increased AD susceptibility.

Natural Selection on Exonic SNPs Shapes Allelic Expression Imbalance (AEI) Adaptability in Lung Cancer Progression

Tumors are driven by a sequence of genetic and epigenetic alterations. Previous studies have mostly focused on the roles of somatic mutations in tumorigenesis, but how germline variants act is largely unknown. In this study, we hypothesized that allelic expression imbalance (AEI) participated in the process of germline variants on tumorigenesis. We screened single-nucleotide polymorphisms (SNPs) as representative germline variants. By using 127 patients’ RNA sequencing data from paired lung cancer and adjacent normal tissues from public databases, we analyzed the effects of the functional consequence of SNPs, function and conservativeness on genes with AEI. We found that natural selection can affect AEI. Functional adaptability of genes with a high frequency of AEI and a correlation of the incidence of AEI with conservativeness were observed in both adjacent tissues and tumor tissues. Moreover, we observed a higher incidence of AEI in genes with non-synonymous SNPs than in those with synonymous SNPs. However, we also found that AEI was affected by allele expression noise, especially in tumor tissues, which led to an increased proportion of AEI, weakened the effect of natural selection and eliminated the influence of the functional consequence of SNPs on AEI. We unveiled a previously unknown adaptive regulatory mechanism in which the effect of natural selection on SNPs can be reflected in allelic expression, which provides insight into a better understanding of cancer evolution.

The multifaceted functional role of DNA methylation in immune-mediated rheumatic diseases

Genomic predisposition cannot explain the onset of complex diseases, as well illustrated by the largely incomplete concordance among monozygotic twins. Epigenetic mechanisms, including DNA methylation, chromatin remodelling and non-coding RNA, are considered to be the link between environmental stimuli and disease onset on a permissive genetic background in autoimmune and chronic inflammatory diseases. The paradigmatic cases of rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), Sjogren's syndrome (SjS) and type-1 diabetes (T1D) share the loss of immunological tolerance to self-antigen influenced by several factors, with a largely incomplete role of individual genomic susceptibility. The most widely investigated epigenetic mechanism is DNA methylation which is associated with gene silencing and is due to the binding of methyl-CpG binding domain (MBD)-containing proteins, such as MECP2, to 5-methylcytosine (5mC). Indeed, a causal relationship occurs between DNA methylation and transcription factors occupancy and recruitment at specific genomic locus. In most cases, the results obtained in different studies are controversial in terms of DNA methylation comparison while fascinating evidence comes from the comparison of the epigenome in clinically discordant monozygotic twins. In this manuscript, we will review the mechanisms of epigenetics and DNA methylation changes in specific immune-mediated rheumatic diseases to highlight remaining unmet needs and to identify possible shared mechanisms beyond different tissue involvements with common therapeutic opportunities. Key Points • DNA methylation has a crucial role in regulating and tuning the immune system. • Evidences suggest that dysregulation of DNA methylation is pivotal in the context of immune-mediated rheumatic diseases. • DNA methylation dysregulation in FOXP3 and interferons-related genes is shared within several autoimmune diseases. • DNA methylation is an attractive marker for diagnosis and therapy.

Insights into the multifactorial causation of obesity by integrated genetic and epigenetic analysis

Obesity is a highly heritable multifactorial disease that places an enormous burden on human health. Its increasing prevalence and the concomitant-reduced life expectancy has intensified the search for new analytical methods that can reduce the knowledge gap between genetic susceptibility and functional consequences of the disease pathology. Although the influence of genetics and epigenetics has been studied independently in the past, there is increasing evidence that genetic variants interact with environmental factors through epigenetic regulation. This suggests that a combined analysis of genetic and epigenetic variation may be more effective in characterizing the obesity phenotype. To date, limited genome-wide integrative analyses have been performed. In this review, we provide an overview of the latest findings, advantages, and challenges and discuss future perspectives.

DAMEfinder: a method to detect differential allele-specific methylation

Background

DNA methylation is a highly studied epigenetic signature that is associated with regulation of gene expression, whereby genes with high levels of promoter methylation are generally repressed. Genomic imprinting occurs when one of the parental alleles is methylated, i.e., when there is inherited allele-specific methylation (ASM). A special case of imprinting occurs during X chromosome inactivation in females, where one of the two X chromosomes is silenced, to achieve dosage compensation between the sexes. Another more widespread form of ASM is sequence dependent (SD-ASM), where ASM is linked to a nearby heterozygous single nucleotide polymorphism (SNP).

Results

We developed a method to screen for genomic regions that exhibit loss or gain of ASM in samples from two conditions (treatments, diseases, etc.). The method relies on the availability of bisulfite sequencing data from multiple samples of the two conditions. We leverage other established computational methods to screen for these regions within a new R package called DAMEfinder. It calculates an ASM score for all CpG sites or pairs in the genome of each sample, and then quantifies the change in ASM between conditions. It then clusters nearby CpG sites with consistent change into regions. In the absence of SNP information, our method relies only on reads to quantify ASM. This novel ASM score compares favorably to current methods that also screen for ASM. Not only does it easily discern between imprinted and non-imprinted regions, but also females from males based on X chromosome inactivation. We also applied DAMEfinder to a colorectal cancer dataset and observed that colorectal cancer subtypes are distinguishable according to their ASM signature. We also re-discover known cases of loss of imprinting.

Conclusion

We have designed DAMEfinder to detect regions of differential ASM (DAMEs), which is a more refined definition of differential methylation, and can therefore help in breaking down the complexity of DNA methylation and its influence in development and disease.

Polymorphisms in JAK2 Gene are Associated with Production Traits and Mastitis Resistance in Dairy Cattle

The present study was designed to investigate the effects of single nucleotide polymorphisms (SNPs) in the JAK2 gene on the production and mastitis related traits in dairy cattle. Blood and milk samples were collected from 201 lactating dairy cattle of three breeds, i.e. Holstein Friesian (HF), Jersey (J) and Achai (A) and their crosses maintained at well-established dairy farms in Khyber Pakhtunkhwa, Pakistan. Generalized linear model was used to evaluate the association between genotypes and the studied traits. A DNA pool was made from randomly selected 30 samples which revealed three SNPs, i.e. SNP 1 in 5’ upstream region (G>A, rs379754157), SNP 2 in intron 15 (A>G, rs134192265), and SNP 3 in exon 20 (A>G, rs110298451) that were further validated in the population under study using SNaPshot technique. Of the three SNPs, SNP 1 did not obey Hardy-Weinberg equilibrium (P<0.05). SNP 2 and SNP 3 were found to be in strong linkage disequilibrium and allele G was highly prevalent compared to allele A in these SNPs. in SNP 1, the GG genotype was associated with significantly (P<0.01) higher SCC, whereas SNP 2 and SNP 3 were significantly (P<0.01) associated with higher lactose percentage compared to the other geno-types. The haplogroups association analysis revealed that H1H2 (GG GG AG) has significantly lower SCC than H2H2 (GG GG GG). The results infer that JAK2 could be an important candidate gene and the studied SNPs might be useful genetic markers for production and mastitis related traits.