Epigenetics of Genes Preferentially Expressed in Dissimilar Cell Populations: Myoblasts and Cerebellum.

While studying myoblast methylomes and transcriptomes, we found that had a remarkable preference for expression in both myoblasts and cerebellum. To understand how widespread such a relationship was and its epigenetic and biological correlates, we systematically looked for genes with similar transcription profiles and analyzed their DNA methylation and chromatin state and accessibility profiles in many different cell populations. Twenty genes were expressed preferentially in myoblasts and cerebellum (Myob/Cbl genes).

Promoter-Adjacent DNA Hypermethylation Can Downmodulate Gene Expression: in the Muscle Lineage.

TBX15, which encodes a differentiation-related transcription factor, displays promoter-adjacent DNA hypermethylation in myoblasts and skeletal muscle (psoas) that is absent from non-expressing cells in other lineages. By whole-genome bisulfite sequencing (WGBS) and enzymatic methyl-seq (EM-seq), these hypermethylated regions were found to border both sides of a constitutively unmethylated promoter. To understand the functionality of this DNA hypermethylation, we cloned the differentially methylated sequences (DMRs) in CpG-free reporter vectors and tested them for promoter or enhancer activity upon transient transfection.

Epigenetics and expression of key genes associated with cardiac fibrosis: and .

Excessive inflammatory signaling and pathological remodeling of the extracellular matrix drive cardiac fibrosis and require changes in gene expression. Using bioinformatics, both tissue-specific expression profiles and epigenomic profiles of some genes critical for cardiac fibrosis were examined, namely, (encodes angiotensin II precursors) and (post-transcriptionally regulates ). In monocytes, neutrophils, fibroblasts, venous cells, liver and brain, enhancers or super-enhancers were found that correlate with high expression of these genes.

Epigenetics of Muscle- and Brain-Specific Expression of KLHL Family Genes.

and the related genes encode components of the Cullin-E3 ubiquitin ligase complex and typically target tissue-specific proteins for degradation, thereby affecting differentiation, homeostasis, metabolism, cell signaling, and the oxidative stress response. Despite their importance in cell function and disease (especially, , , , , and ), previous studies of epigenetic factors that affect transcription were predominantly limited to promoter DNA methylation. Using diverse tissue and cell culture whole-genome profiles, we examined 17 or genes preferentially expressed in skeletal muscle or brain to identify tissue-specific enhancer and promoter chromatin, open chromatin (DNaseI hypersensitivity), and DNA hypomethylation.

Data showing atherosclerosis-associated differentially methylated regions are often at enhancers.

Atherosclerosis involves phenotypic modulation and transdifferentiation of vascular smooth muscle cells (SMCs). Data are given in tabular or figure format that illustrate genome-wide DNA methylation alterations in atherosclerotic vs. control aorta (athero DMRs).

Atherosclerosis-associated differentially methylated regions can reflect the disease phenotype and are often at enhancers.

Background And Aims: Atherosclerosis is a widespread and complicated disease involving phenotypic modulation and transdifferentiation of vascular smooth muscle cells (SMCs), the predominant cells in aorta, as well as changes in endothelial cells and infiltrating monocytes. Alterations in DNA methylation are likely to play central roles in these phenotypic changes, just as they do in normal differentiation and cancer.

Methods: We examined genome-wide DNA methylation changes in atherosclerotic aorta using more stringent criteria for differentially methylated regions (DMRs) than in previous studies and compared these DMRs to tissue-specific epigenetic features.

Developmentally linked human DNA hypermethylation is associated with down-modulation, repression, and upregulation of transcription.

DNA methylation can affect tissue-specific gene transcription in ways that are difficult to discern from studies focused on genome-wide analyses of differentially methylated regions (DMRs). To elucidate the variety of associations between differentiation-related DNA hypermethylation and transcription, we used available epigenomic and transcriptomic profiles from 38 human cell/tissue types to focus on such relationships in 94 genes linked to hypermethylated DMRs in myoblasts (Mb). For 19 of the genes, promoter-region hypermethylation in Mb (and often a few heterologous cell types) was associated with gene repression but, importantly, DNA hypermethylation was absent in many other repressed samples.

Tissue-specific epigenetics in gene neighborhoods: myogenic transcription factor genes.

Myogenic regulatory factor (MRF) genes, MYOD1, MYOG, MYF6 and MYF5, are critical for the skeletal muscle lineage. Here, we used various epigenome profiles from human myoblasts (Mb), myotubes (Mt), muscle and diverse non-muscle samples to elucidate the involvement of multigene neighborhoods in the regulation of MRF genes. We found more far-distal enhancer chromatin associated with MRF genes in Mb and Mt than previously reported from studies in mice.

Myogenic differential methylation: diverse associations with chromatin structure.

Employing a new algorithm for identifying differentially methylated regions (DMRs) from reduced representation bisulfite sequencing profiles, we identified 1972 hypermethylated and 3250 hypomethylated myogenic DMRs in a comparison of myoblasts (Mb) and myotubes (Mt) with 16 types of nonmuscle cell cultures. DMRs co-localized with a variety of chromatin structures, as deduced from ENCODE whole-genome profiles. Myogenic hypomethylation was highly associated with both weak and strong enhancer-type chromatin, while hypermethylation was infrequently associated with enhancer-type chromatin.

RNA CoMPASS: a dual approach for pathogen and host transcriptome analysis of RNA-seq datasets.

High-throughput RNA sequencing (RNA-seq) has become an instrumental assay for the analysis of multiple aspects of an organism's transcriptome. Further, the analysis of a biological specimen's associated microbiome can also be performed using RNA-seq data and this application is gaining interest in the scientific community. There are many existing bioinformatics tools designed for analysis and visualization of transcriptome data.

Modeling, simulation and analysis of methylation profiles from reduced representation bisulfite sequencing experiments.

The ENCODE project has funded the generation of a diverse collection of methylation profiles using reduced representation bisulfite sequencing (RRBS) technology, enabling the analysis of epigenetic variation on a genomic scale at single-site resolution. A standard application of RRBS experiments is in the location of differentially methylated regions (DMRs) between two sets of samples. Despite numerous publications reporting DMRs identified from RRBS datasets, there have been no formal analyses of the effects of experimental and biological factors on the performance of existing or newly developed analytical methods.

DNA methylation and differentiation: HOX genes in muscle cells.

Background: Tight regulation of homeobox genes is essential for vertebrate development. In a study of genome-wide differential methylation, we recently found that homeobox genes, including those in the HOX gene clusters, were highly overrepresented among the genes with hypermethylation in the skeletal muscle lineage. Methylation was analyzed by reduced representation bisulfite sequencing (RRBS) of postnatal myoblasts, myotubes and adult skeletal muscle tissue and 30 types of non-muscle-cell cultures or tissues.

Differences in gastric carcinoma microenvironment stratify according to EBV infection intensity: implications for possible immune adjuvant therapy.

Epstein-Barr virus (EBV) is associated with roughly 10% of gastric carcinomas worldwide (EBVaGC). Although previous investigations provide a strong link between EBV and gastric carcinomas, these studies were performed using selected EBV gene probes. Using a cohort of gastric carcinoma RNA-seq data sets from The Cancer Genome Atlas (TCGA), we performed a quantitative and global assessment of EBV gene expression in gastric carcinomas and assessed EBV associated cellular pathway alterations.

Early de novo DNA methylation and prolonged demethylation in the muscle lineage.

Myogenic cell cultures derived from muscle biopsies are excellent models for human cell differentiation. We report the first comprehensive analysis of myogenesis-specific DNA hyper- and hypo-methylation throughout the genome for human muscle progenitor cells (both myoblasts and myotubes) and skeletal muscle tissue vs. 30 non-muscle samples using reduced representation bisulfite sequencing.

Whole-genome sequencing of the Akata and Mutu Epstein-Barr virus strains.

Using a simple viral genome enrichment approach, we report the de novo assembly of the Akata and Mutu Epstein-Barr virus (EBV) genomes from a single lane of next-generation sequencing (NGS) reads. The Akata and Mutu viral genomes are type I EBV strains of approximately 171 kb in length. Evidence for genome heterogeneity was found for the Akata but not for the Mutu strain.

Gene expression during normal and FSHD myogenesis.

Background: Facioscapulohumeral muscular dystrophy (FSHD) is a dominant disease linked to contraction of an array of tandem 3.3-kb repeats (D4Z4) at 4q35. Within each repeat unit is a gene, DUX4, that can encode a protein containing two homeodomains.

A novel, fast, HMM-with-Duration implementation - for application with a new, pattern recognition informed, nanopore detector.

Background: Hidden Markov Models (HMMs) provide an excellent means for structure identification and feature extraction on stochastic sequential data. An HMM-with-Duration (HMMwD) is an HMM that can also exactly model the hidden-label length (recurrence) distributions - while the regular HMM will impose a best-fit geometric distribution in its modeling/representation.

Results: A Novel, Fast, HMM-with-Duration (HMMwD) Implementation is presented, and experimental results are shown that demonstrate its performance on two-state synthetic data designed to model Nanopore Detector Data.

Duration learning for analysis of nanopore ionic current blockades.

Background: Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties, with potential implications for DNA sequencing. The alpha-Hemolysin transmembrane channel interacts with a translocating molecule in a nontrivial way, frequently evidenced by a complex ionic flow blockade pattern. Typically, recorded current blockade signals have several levels of blockade, with various durations, all obeying a fixed statistical profile for a given molecule.

Cheminformatics methods for novel nanopore analysis of HIV DNA termini.

Background: Channel current feature extraction methods, using Hidden Markov Models (HMMs) have been designed for tracking individual-molecule conformational changes. This information is derived from observation of changes in ionic channel current blockade "signal" upon that molecule's interaction with (and occlusion of) a single nanometer-scale channel in a "nanopore detector". In effect, a nanopore detector transduces single molecule events into channel current blockades.