Extracellular Vesicles Allow Epigenetic Mechanotransduction between Chondrocytes and Osteoblasts

MicroRNAs (miRNAs) can be transported in extracellular vesicles (EVs) and are qualified as possible messengers for cell–cell communication. In the context of osteoarthritis (OA), miR-221-3p has been shown to have a mechanosensitive and a paracrine function inside cartilage. However, the question remains if EVs with miR-221-3p can act as molecular mechanotransducers between cells of different tissues. Here, we studied the effect of EV-mediated transport in the communication between chondrocytes and osteoblasts in vitro in a rat model. In silico analysis (Targetscan, miRWalk, miRDB) revealed putative targets of miRNA-221-3p (CDKN1B/p27, TIMP-3, Tcf7l2/TCF4, ARNT). Indeed, transfection of miRNA-221-3p in chondrocytes and osteoblasts resulted in regulation of these targets. Coculture experiments of transfected chondrocytes with untransfected osteoblasts not only showed regulation of these target genes in osteoblasts but also inhibition of their bone formation capacity. Direct treatment with chondrocyte-derived EVs validated that chondrocyte-produced extracellular miR-221-3p was responsible for this effect. Altogether, our study provides a novel perspective on a possible communication pathway of a mechanically induced epigenetic signal through EVs. This may be important for processes at the interface of bone and cartilage, such as OA development, physiologic joint homeostasis, growth or fracture healing, as well as for other tissue interfaces with differing biomechanical properties.

Integrative analysis of epigenetics data identifies gene-specific regulatory elements

Understanding how epigenetic variation in non-coding regions is involved in distal gene-expression regulation is an important problem. Regulatory regions can be associated to genes using large-scale datasets of epigenetic and expression data. However, for regions of complex epigenomic signals and enhancers that regulate many genes, it is difficult to understand these associations. We present StitchIt, an approach to dissect epigenetic variation in a gene-specific manner for the detection of regulatory elements (REMs) without relying on peak calls in individual samples. StitchIt segments epigenetic signal tracks over many samples to generate the location and the target genes of a REM simultaneously. We show that this approach leads to a more accurate and refined REM detection compared to standard methods even on heterogeneous datasets, which are challenging to model. Also, StitchIt REMs are highly enriched in experimentally determined chromatin interactions and expression quantitative trait loci. We validated several newly predicted REMs using CRISPR-Cas9 experiments, thereby demonstrating the reliability of StitchIt. StitchIt is able to dissect regulation in superenhancers and predicts thousands of putative REMs that go unnoticed using peak-based approaches suggesting that a large part of the regulome might be uncharted water.

Comparative Analysis of Histone H3K4me3 Distribution in Mouse Liver in Different Diets Reveals the Epigenetic Efficacy of Cyanidin-3-O-glucoside Dietary Intake

Background: Different diets result in significantly different phenotypes through metabolic and genomic reprogramming. Epigenetic marks, identified in humans and mouse models through caloric restriction, a high-fat diet or the intake of specific bioactives, suggest that genomic reprogramming drives this metabolic reprogramming and mediates the effect of nutrition on health. Histone modifications encode the epigenetic signal, which adapts genome functions to environmental conditions, including diets, by tuning the structure and properties of chromatin. To date, the effect of different diets on the genome-wide distribution of critical histone marks has not been determined. Methods: Using chromatin immunoprecipitation sequencing, we investigated the distribution of the trimethylation of lysine 4 of histone H3 in the liver of mice fed for one year with five different diets, including: chow containing yellow corn powder as an extra source of plant bioactives or specifically enriched with cyanidin-3-O-Glucoside, high-fat-enriched obesogenic diets, and caloric-restricted pro-longevity diets. Conclusions: Comparison of the resulting histone mark profiles revealed that functional food containing cyanidin determines a broad effect.

Histone H3K4me3 modification is a transgenerational epigenetic signal for lipid metabolism in Caenorhabditis elegans

As a major risk factor to human health, obesity presents a massive burden to people and society. Interestingly, the obese status of parents could affect progeny’s lipid accumulation through multi-generational epigenetic inheritance. To date, many questions remain as to how lipid accumulation leads to signals that are transmitted across generations. In this study, we established a model of C. elegans fed with a high fat diet (HFD) that led to obvious lipid accumulation, which can be propagated their progeny. Using this model, we discovered that transcription factors DAF-16/FOXO and SBP-1, nuclear receptors NHR-49 and NHR-80, and delta-9 desaturase (fat-5, fat-6, and fat-7) are required for transgenerational fat accumulation. Additionally, histone H3K4 tri-methylation (H3K4me3) marks genes related to lipid metabolism and increases their transcription response to multigenerational obesogenic effects. In summary, this study establishes that a network of lipid metabolic genes and chromatin modifications work together to achieve multigenerational obesogenic effects.

COCOA: coordinate covariation analysis of epigenetic heterogeneity

A key challenge in epigenetics is to determine the biological significance of epigenetic variation among individuals. We present Coordinate Covariation Analysis (COCOA), a computational framework that uses covariation of epigenetic signals across individuals and a database of region sets to annotate epigenetic heterogeneity. COCOA is the first such tool for DNA methylation data and can also analyze any epigenetic signal with genomic coordinates. We demonstrate COCOA’s utility by analyzing DNA methylation, ATAC-seq, and multi-omic data in supervised and unsupervised analyses, showing that COCOA provides new understanding of inter-sample epigenetic variation. COCOA is available on Bioconductor (http://bioconductor.org/packages/COCOA).

COCOA: Coordinate covariation analysis of epigenetic heterogeneity

A key challenge in epigenetics is to determine the biological significance of epigenetic variation among individuals. Here, we present Coordinate Covariation Analysis (COCOA), a computational framework that uses covariation of epigenetic signals across individuals and a database of region sets to annotate epigenetic heterogeneity. COCOA is the first such tool for DNA methylation data and can also analyze any epigenetic signal with genomic coordinates. We demonstrate COCOA’s utility by analyzing DNA methylation, ATAC-seq, and multi-omic data in supervised and unsupervised analyses, showing that COCOA provides new understanding of inter-sample epigenetic variation. COCOA is available as a Bioconductor R package (http://bioconductor.org/packages/COCOA).

Early cancer detection using multi-omic approach including epigenetic signal from ultra-small fragments.

e13561 Background: Genetic and epigenetic signals from plasma cell-free DNA (cfDNA) as well as proteins have been shown to detect cancer early. We have previously developed Circular Ligation and Amplification (CLAmp-seq) to detect mutations very sensitively and demonstrated higher performance than molecular barcode-based methods. The same single strand based technology yielded a much larger proportion of small fragments ( < 100 bp) than traditional methods typically relying on double stranded ligation, allowing us to investigate epigenetic signature of cancer in ultra-short fragments. We sought to measure the performance using a multi-omics approach of these genetic and epigenetic changes as well as proteins in detecting colorectal cancer (CRC), ovarian cancer (OC) and hepatocellular carcinoma (HCC). Methods: A healthy and a late stage cancer sample were assessed by whole genome sequencing (WGS) using CLAmp-seq. Then we analyzed cfDNA from plasma samples of 731 patients, including 69 CRC, 57 HCC, 49 OC patients and 556 age-matched healthy individuals. Out of the diseased samples, the numbers for stages I-IV are 49, 39, 71, and 16, respectively. CLAmp-seq WGS was performed on 58 healthy and 66 cancer samples to discover cancer epigenetic signature. In addition, all the samples were analyzed for a panel of proteins and a CLAmp-seq targeted panel that includes known mutation sites. Results: Using CLAmp-Seq in late stage cancer showed 33% of its fragments as smaller than 100 bp compared to 15% in healthy and < 1% in late stage by double stranded library prep. In addition, the difference in fragment size between late stage cancer and healthy was 29bp using CLAmp-Seq and 12bp using traditional double stranded prep. This focused our attention to detect epigenetic signature specific to cancer on the small fragments using CLAmp-Seq. Using data from whole genome analysis we demonstrated a performance using the epigenetic signature alone of 50% sensitivity at 97% specificity. Combined with mutations and proteins, we obtained at specificity of 97% sensitivities of 50%, 88%, 88%, and 100% in stage I, II, III, and IV, respectively. At the same 97% specificity we obtained the sensitivities of 73%, 100%, and 85% in CRC, OC, and HCC, respectively. Conclusions: We have demonstrated that CLAmp-Seq detects small fragments that are enriched in cancer. We have found predictive epigenetic signature in these small fragments. When combined with mutations and proteins we obtained a performance of 80% sensitivity at 97% specificity.

Weaver Syndrome and EZH2-Related Overgrowth Syndromes

Comprehensive details on Weaver syndrome, one of the best recognized of the overgrowth syndromes, are presented in this chapter. The syndrome is characterized by overgrowth of prenatal onset, a distinctive craniofacial appearance, camptodactyly, widened metaphysis, accelerated bone age, and developmental delay. Like other overgrowth syndromes, Weaver syndrome is accompanied by an increased risk of malignancies, neuroblastoma, leukemia, and lymphoma in particular. The diagnosis relied on clinical evaluation alone until 2012 when the causative gene, EZH2, was discovered. The gene product joins with other related proteins to form a polycomb repressive complex that functions as an epigenetic signal that compacts chromatin and silences genes by histone modifications.