Somatic reversion of pathogenic DOCK8 variants alters lymphocyte differentiation and function to effectively cure DOCK8 deficiency.

Inborn errors of immunity cause monogenic immune dysregulatory conditions such as severe and recurrent pathogen infection, inflammation, allergy, and malignancy. Somatic reversion refers to the spontaneous repair of a pathogenic germline genetic variant and has been reported to occur in a number of inborn errors of immunity, with a range of impacts on clinical outcomes of these conditions. DOCK8 deficiency due to biallelic inactivating mutations in DOCK8 causes a combined immunodeficiency characterized by severe bacterial, viral, and fungal infections, as well as allergic disease and some cancers. Here, we describe the clinical, genetic, and cellular features of 3 patients with biallelic DOCK8 variants who, following somatic reversion in multiple lymphocyte subsets, exhibited improved clinical features, including complete resolution of infection and allergic disease, and cure over time. Acquisition of DOCK8 expression restored defective lymphocyte signalling, survival and proliferation, as well as CD8+ T cell cytotoxicity, CD4+ T cell cytokine production, and memory B cell generation compared with typical DOCK8-deficient patients. Our temporal analysis of DOCK8-revertant and DOCK8-deficient cells within the same individual established mechanisms of clinical improvement in these patients following somatic reversion and revealed further nonredundant functions of DOCK8 in human lymphocyte biology. Last, our findings have significant implications for future therapeutic options for the treatment of DOCK8 deficiency.

The Medical Genome Reference Bank contains whole genome and phenotype data of 2570 healthy elderly.

Population health research is increasingly focused on the genetic determinants of healthy ageing, but there is no public resource of whole genome sequences and phenotype data from healthy elderly individuals. Here we describe the first release of the Medical Genome Reference Bank (MGRB), comprising whole genome sequence and phenotype of 2570 elderly Australians depleted for cancer, cardiovascular disease, and dementia. We analyse the MGRB for single-nucleotide, indel and structural variation in the nuclear and mitochondrial genomes. MGRB individuals have fewer disease-associated common and rare germline variants, relative to both cancer cases and the gnomAD and UK Biobank cohorts, consistent with risk depletion. Age-related somatic changes are correlated with grip strength in men, suggesting blood-derived whole genomes may also provide a biologic measure of age-related functional deterioration. The MGRB provides a broadly applicable reference cohort for clinical genetics and genomic association studies, and for understanding the genetics of healthy ageing.

Constitutively bound CTCF sites maintain 3D chromatin architecture and long-range epigenetically regulated domains.

The architectural protein CTCF is a mediator of chromatin conformation, but how CTCF binding to DNA is orchestrated to maintain long-range gene expression is poorly understood. Here we perform RNAi knockdown to reduce CTCF levels and reveal a shared subset of CTCF-bound sites are robustly resistant to protein depletion. The 'persistent' CTCF sites are enriched at domain boundaries and chromatin loops constitutive to all cell types. CRISPR-Cas9 deletion of 2 persistent CTCF sites at the boundary between a long-range epigenetically active (LREA) and silenced (LRES) region, within the Kallikrein (KLK) locus, results in concordant activation of all 8 KLK genes within the LRES region. CTCF genome-wide depletion results in alteration in Topologically Associating Domain (TAD) structure, including the merging of TADs, whereas TAD boundaries are not altered where persistent sites are maintained. We propose that the subset of essential CTCF sites are involved in cell-type constitutive, higher order chromatin architecture.

Methylome and transcriptome maps of human visceral and subcutaneous adipocytes reveal key epigenetic differences at developmental genes.

Adipocytes support key metabolic and endocrine functions of adipose tissue. Lipid is stored in two major classes of depots, namely visceral adipose (VA) and subcutaneous adipose (SA) depots. Increased visceral adiposity is associated with adverse health outcomes, whereas the impact of SA tissue is relatively metabolically benign. The precise molecular features associated with the functional differences between the adipose depots are still not well understood. Here, we characterised transcriptomes and methylomes of isolated adipocytes from matched SA and VA tissues of individuals with normal BMI to identify epigenetic differences and their contribution to cell type and depot-specific function. We found that DNA methylomes were notably distinct between different adipocyte depots and were associated with differential gene expression within pathways fundamental to adipocyte function. Most striking differential methylation was found at transcription factor and developmental genes. Our findings highlight the importance of developmental origins in the function of different fat depots.

Genome sequencing as a first-line genetic test in familial dilated cardiomyopathy.

PURPOSE: We evaluated genome sequencing (GS) as an alternative to multigene panel sequencing (PS) for genetic testing in dilated cardiomyopathy (DCM). METHODS: Forty-two patients with familial DCM underwent PS and GS, and detection rates of rare single-nucleotide variants and small insertions/deletions in panel genes were compared. Loss-of-function variants in 406 cardiac-enriched genes were evaluated, and an assessment of structural variation was performed. RESULTS: GS provided broader and more uniform coverage than PS, with high concordance for rare variant detection in panel genes. GS identified all PS-identified pathogenic or likely pathogenic variants as well as two additional likely pathogenic variants: one was missed by PS due to low coverage, the other was a known disease-causing variant in a gene not included on the panel. No loss-of-function variants in the extended gene set met clinical criteria for pathogenicity. One BAG3 structural variant was classified as pathogenic. CONCLUSION: Our data support the use of GS for genetic testing in DCM, with high variant detection accuracy and a capacity to identify structural variants. GS provides an opportunity to go beyond suites of established disease genes, but the incremental yield of clinically actionable variants is limited by a paucity of genetic and functional evidence for DCM association.

Evaluation of cross-platform and interlaboratory concordance via consensus modelling of genomic measurements.

MOTIVATION: A synoptic view of the human genome benefits chiefly from the application of nucleic acid sequencing and microarray technologies. These platforms allow interrogation of patterns such as gene expression and DNA methylation at the vast majority of canonical loci, allowing granular insights and opportunities for validation of original findings. However, problems arise when validating against a "gold standard" measurement, since this immediately biases all subsequent measurements towards that particular technology or protocol. Since all genomic measurements are estimates, in the absence of a "gold standard" we instead empirically assess the measurement precision and sensitivity of a large suite of genomic technologies via a consensus modelling method called the row-linear model. This method is an application of the American Society for Testing and Materials Standard E691 for assessing interlaboratory precision and sources of variability across multiple testing sites. Both cross-platform and cross-locus comparisons can be made across all common loci, allowing identification of technology- and locus-specific tendencies. RESULTS: We assess technologies including the Infinium MethylationEPIC BeadChip, whole genome bisulfite sequencing (WGBS), two different RNA-Seq protocols (PolyA+ and Ribo-Zero) and five different gene expression array platforms. Each technology thus is characterised herein, relative to the consensus. We showcase a number of applications of the row-linear model, including correlation with known interfering traits. We demonstrate a clear effect of cross-hybridisation on the sensitivity of Infinium methylation arrays. Additionally, we perform a true interlaboratory test on a set of samples interrogated on the same platform across twenty-one separate testing laboratories. AVAILABILITY AND IMPLEMENTATION: A full implementation of the row-linear model, plus extra functions for visualisation, are found in the R package consensus at https://github.com/timpeters82/consensus. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bisulphite Sequencing of Chromatin Immunoprecipitated DNA (BisChIP-seq).

Epigenetic regulation plays a critical role in gene expression, cellular differentiation, and disease. There is a complex interplay between the different layers of epigenetic information, including DNA methylation, nucleosome positions, histone modifications, histone variants, and other important epigenetic regulators. The different modifications do not act independently of each other and their relationship plays an important role in governing the regulation of the epigenome. Of these, DNA methylation is the best-studied epigenetic modification in mammals. However, the direct relationship between DNA methylation and chromatin modifications has been difficult to unravel with existing technologies, with epigenome-wide integration studies still based on "overlaying" independent chromatin modification and DNA methylation maps. Bisulphite sequencing enables the methylation state of every cytosine residue to be analyzed across a given molecule in a strand-specific context. Here, we describe a direct approach to interrogating the DNA methylation status of specific chromatin-marked DNA, using high-throughput sequencing of bisulphite-treated chromatin immunoprecipitated DNA (BisChIP-seq). This combined approach enables the exquisite relationship between chromatin-modified DNA or transcription factor-associated DNA and the methylation state of each targeted allele to be directly interrogated. BisChIP-Seq can now be widely applied genome-wide to further understand the molecular relationship between DNA methylation and other important epigenetic regulators.

Acetylated histone variant H2A.Z is involved in the activation of neo-enhancers in prostate cancer.

Acetylation of the histone variant H2A.Z (H2A.Zac) occurs at active promoters and is associated with oncogene activation in prostate cancer, but its role in enhancer function is still poorly understood. Here we show that H2A.Zac containing nucleosomes are commonly redistributed to neo-enhancers in cancer resulting in a concomitant gain of chromatin accessibility and ectopic gene expression. Notably incorporation of acetylated H2A.Z nucleosomes is a pre-requisite for activation of Androgen receptor (AR) associated enhancers. H2A.Zac nucleosome occupancy is rapidly remodeled to flank the AR sites to initiate the formation of nucleosome-free regions and the production of AR-enhancer RNAs upon androgen treatment. Remarkably higher levels of global H2A.Zac correlate with poorer prognosis. Altogether these data demonstrate the novel contribution of H2A.Zac in activation of newly formed enhancers in prostate cancer.

Genome-wide nucleosome occupancy and DNA methylation profiling of four human cell lines.

DNA methylation and nucleosome positioning are two key mechanisms that contribute to the epigenetic control of gene expression. During carcinogenesis, the expression of many genes is altered alongside extensive changes in the epigenome, with repressed genes often being associated with local DNA hypermethylation and gain of nucleosomes at their promoters. However the spectrum of alterations that occur at distal regulatory regions has not been extensively studied. To address this we used Nucleosome Occupancy and Methylation sequencing (NOMe-seq) to compare the genome-wide DNA methylation and nucleosome occupancy profiles between normal and cancer cell line models of the breast and prostate. Here we describe the bioinformatic pipeline and methods that we developed for the processing and analysis of the NOMe-seq data published by (Taberlay et al., 2014 [1]) and deposited in the Gene Expression Omnibus with accession GSE57498.

COBRA-Seq: Sensitive and Quantitative Methylome Profiling.

Combined Bisulfite Restriction Analysis (COBRA) quantifies DNA methylation at a specific locus. It does so via digestion of PCR amplicons produced from bisulfite-treated DNA, using a restriction enzyme that contains a cytosine within its recognition sequence, such as TaqI. Here, we introduce COBRA-seq, a genome wide reduced methylome method that requires minimal DNA input (0.1-1.0 mg) and can either use PCR or linear amplification to amplify the sequencing library. Variants of COBRA-seq can be used to explore CpG-depleted as well as CpG-rich regions in vertebrate DNA. The choice of enzyme influences enrichment for specific genomic features, such as CpG-rich promoters and CpG islands, or enrichment for less CpG dense regions such as enhancers. COBRA-seq coupled with linear amplification has the additional advantage of reduced PCR bias by producing full length fragments at high abundance. Unlike other reduced representative methylome methods, COBRA-seq has great flexibility in the choice of enzyme and can be multiplexed and tuned, to reduce sequencing costs and to interrogate different numbers of sites. Moreover, COBRA-seq is applicable to non-model organisms without the reference genome and compatible with the investigation of non-CpG methylation by using restriction enzymes containing CpA, CpT, and CpC in their recognition site.

De novo identification of differentially methylated regions in the human genome.

BACKGROUND: The identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the differential methylation (DM) signal. The method is agnostic to both genomic annotation and local change in the direction of the DM signal, removes the bias incurred from irregularly spaced methylation sites, and assigns significance to each DMR called via comparison to a null model. RESULTS: We show that, for both simulated and real data, the predictive performance of DMRcate is superior to those of Bumphunter and Probe Lasso, and commensurate with that of comb-p. For the real data, we validate all array-derived DMRs from the candidate methods on a suite of DMRs derived from whole-genome bisulfite sequencing called from the same DNA samples, using two separate phenotype comparisons. CONCLUSIONS: The agglomeration of genomically localised individual methylation sites into discrete DMRs is currently best served by a combination of DM-signal smoothing and subsequent threshold specification. The findings also suggest the design of the 450K array shows preference for CpG sites that are more likely to be differentially methylated, but its overall coverage does not adequately reflect the depth and complexity of methylation signatures afforded by sequencing. For the convenience of the research community we have created a user-friendly R software package called DMRcate, downloadable from Bioconductor and compatible with existing preprocessing packages, which allows others to apply the same DMR-finding method on 450K array data.

Reconfiguration of nucleosome-depleted regions at distal regulatory elements accompanies DNA methylation of enhancers and insulators in cancer.

It is well established that cancer-associated epigenetic repression occurs concomitant with CpG island hypermethylation and loss of nucleosomes at promoters, but the role of nucleosome occupancy and epigenetic reprogramming at distal regulatory elements in cancer is still poorly understood. Here, we evaluate the scope of global epigenetic alterations at enhancers and insulator elements in prostate and breast cancer cells using simultaneous genome-wide mapping of DNA methylation and nucleosome occupancy (NOMe-seq). We find that the genomic location of nucleosome-depleted regions (NDRs) is mostly cell type specific and preferentially found at enhancers in normal cells. In cancer cells, however, we observe a global reconfiguration of NDRs at distal regulatory elements coupled with a substantial reorganization of the cancer methylome. Aberrant acquisition of nucleosomes at enhancer-associated NDRs is associated with hypermethylation and epigenetic silencing marks, and conversely, loss of nucleosomes with demethylation and epigenetic activation. Remarkably, we show that nucleosomes remain strongly organized and phased at many facultative distal regulatory elements, even in the absence of a NDR as an anchor. Finally, we find that key transcription factor (TF) binding sites also show extensive peripheral nucleosome phasing, suggesting the potential for TFs to organize NDRs genome-wide and contribute to deregulation of cancer epigenomes. Together, our findings suggest that "decommissioning" of NDRs and TFs at distal regulatory elements in cancer cells is accompanied by DNA hypermethylation susceptibility of enhancers and insulator elements, which in turn may contribute to an altered genome-wide architecture and epigenetic deregulation in malignancy.

BayMeth: improved DNA methylation quantification for affinity capture sequencing data using a flexible Bayesian approach.

Affinity capture of DNA methylation combined with high-throughput sequencing strikes a good balance between the high cost of whole genome bisulfite sequencing and the low coverage of methylation arrays. We present BayMeth, an empirical Bayes approach that uses a fully methylated control sample to transform observed read counts into regional methylation levels. In our model, inefficient capture can readily be distinguished from low methylation levels. BayMeth improves on existing methods, allows explicit modeling of copy number variation, and offers computationally efficient analytical mean and variance estimators. BayMeth is available in the Repitools Bioconductor package.

Mining cancer methylomes: prospects and challenges.

There are over 28 million CpG sites in the human genome. Assessing the methylation status of each of these sites will be required to understand fully the role of DNA methylation in health and disease. Genome-wide analysis, using arrays and high-throughput sequencing, has enabled assessment of large fractions of the methylome, but each protocol comes with unique advantages and disadvantages. Notably, except for whole-genome bisulfite sequencing, most commonly used genome-wide methods detect <5% of all CpG sites. Here, we discuss approaches for methylome studies and compare genome coverage of promoters, genes, and intergenic regions, and capacity to quantitate individual CpG methylation states. Finally, we examine the extent of published cancer methylomes that have been generated using genome-wide approaches.

GWAS of DNA methylation variation within imprinting control regions suggests parent-of-origin association.

Imprinting control regions (ICRs) play a fundamental role in establishing and maintaining the non-random monoallelic expression of certain genes, via common regulatory elements such as non-coding RNAs and differentially methylated regions (DMRs) of DNA. We recently surveyed DNA methylation levels within four ICRs (H19-ICR, IGF2-DMR, KvDMR, and NESPAS-ICR) in whole-blood genomic DNA from 128 monozygotic (MZ) and 128 dizygotic (DZ) human twin pairs. Our analyses revealed high individual variation and intra-domain covariation in methylation levels across CpGs and emphasized the interaction between epigenetic variation and the underlying genetic sequence in a parent-of-origin fashion. Here, we extend our analysis to conduct two genome-wide screenings of single nucleotide polymorphisms (SNPs) underlying either intra-domain covariation or parent-of-origin-dependent association with methylation status at individual CpG sites located within ICRs. Although genome-wide significance was not surpassed due to sample size limitations, the most significantly associated SNPs found through multiple-trait genome-wide association (MQFAM) included the previously described rs10732516, which is located in the vicinity of the H19-ICR. Similarly, we identified an association between rs965808 and methylation status within the NESPAS-ICR. This SNP is positioned within an intronic region of the overlapping genes GNAS and GNAS-AS1, which are imprinted genes regulated by the NESPAS-ICR. Sixteen other SNPs located in regions apart from the analyzed regions displayed suggestive association with intra-domain methylation. Additionally, we identified 13 SNPs displaying parent-of-origin association with individual methylation sites through family-based association testing. In this exploratory study, we show the value and feasibility of using alternative GWAS approaches in the study of the interaction between epigenetic state and genetic sequence within imprinting regulatory domains. Despite the relatively small sample size, we identified a number of SNPs displaying suggestive association either in a domain-wide or in a parent-of-origin fashion. Nevertheless, these associations will require future experimental validation or replication in larger and independent samples.

Regional activation of the cancer genome by long-range epigenetic remodeling.

Epigenetic gene deregulation in cancer commonly occurs through chromatin repression and promoter hypermethylation of tumor-associated genes. However, the mechanism underpinning epigenetic-based gene activation in carcinogenesis is still poorly understood. Here, we identify a mechanism of domain gene deregulation through coordinated long-range epigenetic activation (LREA) of regions that typically span 1 Mb and harbor key oncogenes, microRNAs, and cancer biomarker genes. Gene promoters within LREA domains are characterized by a gain of active chromatin marks and a loss of repressive marks. Notably, although promoter hypomethylation is uncommon, we show that extensive DNA hypermethylation of CpG islands or "CpG-island borders" is strongly related to cancer-specific gene activation or differential promoter usage. These findings have wide ramifications for cancer diagnosis, progression, and epigenetic-based gene therapies.

Copy-number-aware differential analysis of quantitative DNA sequencing data.

Developments in microarray and high-throughput sequencing (HTS) technologies have resulted in a rapid expansion of research into epigenomic changes that occur in normal development and in the progression of disease, such as cancer. Not surprisingly, copy number variation (CNV) has a direct effect on HTS read densities and can therefore bias differential detection results. We have developed a flexible approach called ABCD-DNA (affinity-based copy-number-aware differential quantitative DNA sequencing analyses) that integrates CNV and other systematic factors directly into the differential enrichment engine.

Bisulfite sequencing of chromatin immunoprecipitated DNA (BisChIP-seq) directly informs methylation status of histone-modified DNA.

The complex relationship between DNA methylation, chromatin modification, and underlying DNA sequence is often difficult to unravel with existing technologies. Here, we describe a novel technique based on high-throughput sequencing of bisulfite-treated chromatin immunoprecipitated DNA (BisChIP-seq), which can directly interrogate genetic and epigenetic processes that occur in normal and diseased cells. Unlike most previous reports based on correlative techniques, we found using direct bisulfite sequencing of Polycomb H3K27me3-enriched DNA from normal and prostate cancer cells that DNA methylation and H3K27me3-marked histones are not always mutually exclusive, but can co-occur in a genomic region-dependent manner. Notably, in cancer, the co-dependency of marks is largely redistributed with an increase of the dual repressive marks at CpG islands and transcription start sites of silent genes. In contrast, there is a loss of DNA methylation in intergenic H3K27me3-marked regions. Allele-specific methylation status derived from the BisChIP-seq data clearly showed that both methylated and unmethylated alleles can simultaneously be associated with H3K27me3 histones, highlighting that DNA methylation status in these regions is not dependent on Polycomb chromatin status. BisChIP-seq is a novel approach that can be widely applied to directly interrogate the genomic relationship between allele-specific DNA methylation, histone modification, or other important epigenetic regulators.

Prognostic and diagnostic significance of DNA methylation patterns in high grade serous ovarian cancer.

OBJECTIVE: Altered DNA methylation patterns hold promise as cancer biomarkers. In this study we selected a panel of genes which are commonly methylated in a variety of cancers to evaluate their potential application as biomarkers for prognosis and diagnosis in high grade serous ovarian carcinoma (HGSOC); the most common and lethal subtype of ovarian cancer. METHODS: The methylation patterns of 10 genes (BRCA1, EN1, DLEC1, HOXA9, RASSF1A, GATA4, GATA5, HSULF1, CDH1, SFN) were examined and compared in a cohort of 80 primary HGSOC and 12 benign ovarian surface epithelium (OSE) samples using methylation-specific headloop suppression PCR. RESULTS: The genes were variably methylated in primary HGSOC, with HOXA9 methylation observed in 95% of cases. Most genes were rarely methylated in benign OSE, with the exception of SFN which was methylated in all HGSOC and benign OSE samples examined. Methylation of DLEC1 was associated with disease recurrence, independent of tumor stage and suboptimal surgical debulking (HR 3.5 (95% CI:1.10-11.07), p=0.033). A combination of the methylation status of HOXA9 and EN1 could discriminate HGSOC from benign OSE with a sensitivity of 98.8% and a specificity of 91.7%, which increased to 100% sensitivity with no loss of specificity when pre-operative CA125 levels were also incorporated. CONCLUSIONS: This study provides further evidence to support the feasibility of detecting altered DNA methylation patterns as a potential diagnostic and prognostic approach for HGSOC.