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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., The architectural protein CTCF is a mediator of chromatin conformation, but how CTCF binding to DNA is regulated remains poorly understood. Here the authors find that there is a shared subset of CTCF-bound sites resistant to protein depletion in different cell lines, which are enriched at domain boundaries and chromatin loops constitutive to all cell types.

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.

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.

The growth and progression of solid tumors involves dynamic cross-talk between cancer epithelium and the surrounding microenvironment. To date, molecular profiling has largely been restricted to the epithelial component of tumors; therefore, features underpinning the persistent protumorigenic phenotype of the tumor microenvironment are unknown. Using whole-genome bisulfite sequencing, we show for the first time that cancer-associated fibroblasts (CAFs) from localized prostate cancer display remarkably distinct and enduring genome-wide changes in DNA methylation, significantly at enhancers and promoters, compared to nonmalignant prostate fibroblasts (NPFs). Differentially methylated regions associated with changes in gene expression have cancer-related functions and accurately distinguish CAFs from NPFs. Remarkably, a subset of changes is shared with prostate cancer epithelial cells, revealing the new concept of tumor-specific epigenome modifications in the tumor and its microenvironment. The distinct methylome of CAFs provides a novel epigenetic hallmark of the cancer microenvironment and promises new biomarkers to improve interpretation of diagnostic samples.

Cancer is characterised by DNA hypermethylation and gene silencing of CpG island-associated promoters, including tumour-suppressor genes. The methyl-CpG-binding domain (MBD) family of proteins bind to methylated DNA and can aid in the mediation of gene silencing through interaction with histone deacetylases and histone methyltransferases. However, the mechanisms responsible for eliciting CpG island hypermethylation in cancer, and the potential role that MBD proteins play in modulation of the methylome remain unclear. Our previous work demonstrated that MBD2 preferentially binds to the hypermethylated GSTP1 promoter CpG island in prostate cancer cells. Here, we use functional genetic approaches to investigate if MBD2 plays an active role in reshaping the DNA methylation landscape at this locus and genome-wide. First, we show that loss of MBD2 results in inhibition of both maintenance and spread of de novo methylation of a transfected construct containing the GSTP1 promoter CpG island in prostate cancer cells and Mbd2−/− mouse fibroblasts. De novo methylation was rescued by transient expression of Mbd2 in Mbd2−/− cells. Second, we show that MBD2 depletion triggers significant hypomethylation genome-wide in prostate cancer cells with concomitant loss of MBD2 binding at promoter and enhancer regulatory regions. Finally, CpG islands and shores that become hypomethylated after MBD2 depletion in LNCaP cancer cells show significant hypermethylation in clinical prostate cancer samples, highlighting a potential active role of MBD2 in promoting cancer-specific hypermethylation. Importantly, co-immunoprecipiation of MBD2 shows that MBD2 associates with DNA methyltransferase enzymes 1 and 3A. Together our results demonstrate that MBD2 has a critical role in ‘rewriting’ the cancer methylome at specific regulatory regions.

Our knowledge of regulatory mechanisms of gene expression and other chromosomal processes related to DNA methylation and chromatin state is continuing to grow at a rapid pace. Understanding how these epigenomic phenomena vary between individuals will have an impact on understanding their broader role in determining variation in gene expression and biochemical, physiological, and behavioural phenotypes. In this review we survey recent progress in this area, focusing on data available from humans. We highlight the role of obligatory (sequence-dependent) epigenomic variation as an important mechanism for generating interindividual variation that could impact our understanding of the mechanistic basis of complex trait architecture.

Summary: The initial steps in the analysis of next-generation sequencing data can be automated by way of software ‘pipelines’. However, individual components depreciate rapidly because of the evolving technology and analysis methods, often rendering entire versions of production informatics pipelines obsolete. Constructing pipelines from Linux bash commands enables the use of hot swappable modular components as opposed to the more rigid program call wrapping by higher level languages, as implemented in comparable published pipelining systems. Here we present Next Generation Sequencing ANalysis for Enterprises (NGSANE), a Linux-based, high-performance-computing-enabled framework that minimizes overhead for set up and processing of new projects, yet maintains full flexibility of custom scripting when processing raw sequence data. Availability and implementation: Ngsane is implemented in bash and publicly available under BSD (3-Clause) licence via GitHub at https://github.com/BauerLab/ngsane. Contact: Denis.Bauer@csiro.au Supplementary information: Supplementary data are available at Bioinformatics online.