Angela H. Ting

MBD-isolated Genome Sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome

DNA methylation is an epigenetic modification involved in both normal developmental processes and disease states through the modulation of gene expression and the maintenance of genomic organization. Conventional methods of DNA methylation analysis, such as bisulfite sequencing, methylation sensitive restriction enzyme digestion and array-based detection techniques, have major limitations that impede high-throughput genome-wide analysis. We describe a novel technique, MBD-isolated Genome Sequencing (MiGS), which combines precipitation of methylated DNA by recombinant methyl-CpG binding domain of MBD2 protein and sequencing of the isolated DNA by a massively parallel sequencer. We utilized MiGS to study three isogenic cancer cell lines with varying degrees of DNA methylation. We successfully detected previously known methylated regions in these cells and identified hundreds of novel methylated regions. This technique is highly specific and sensitive and can be applied to any biological settings to identify differentially methylated regions at the genomic scale.

Brain Transcriptional and Epigenetic Associations with Autism

Background Autism is a common neurodevelopmental syndrome. Numerous rare genetic etiologies are reported; most cases are idiopathic. Methodology/Principal Findings To uncover important gene dysregulation in autism we analyzed carefully selected idiopathic autistic and control cerebellar and BA19 (occipital) brain tissues using high resolution whole genome gene expression and whole genome DNA methylation microarrays. No changes in DNA methylation were identified in autistic brain but gene expression abnormalities in two areas of metabolism were apparent: down-regulation of genes of mitochondrial oxidative phosphorylation and of protein translation. We also found associations between specific behavioral domains of autism and specific brain gene expression modules related to myelin/myelination, inflammation/immune response and purinergic signaling. Conclusions/Significance This work highlights two largely unrecognized molecular pathophysiological themes in autism and suggests differing molecular bases for autism behavioral endophenotypes.

Identification and functional analysis of epigenetically silenced micrornas in colorectal cancer cells

Abnormal microRNA (miRNA) expression has been linked to the development and progression of several human cancers, and such dysregulation can result from aberrant DNA methylation. While a small number of miRNAs is known to be regulated by DNA methylation, we postulated that such epigenetic regulation is more prevalent. By combining MBD-isolated Genome Sequencing (MiGS) to evaluate genome-wide DNA methylation patterns and microarray analysis to determine miRNA expression levels, we systematically searched for candidate miRNAs regulated by DNA methylation in colorectal cancer cell lines. We found 64 miRNAs to be robustly methylated in HCT116 cells; eighteen of them were located in imprinting regions or already reported to be regulated by DNA methylation. For the remaining 46 miRNAs, expression levels of 18 were consistent with their DNA methylation status. Finally, 8 miRNAs were up-regulated by 5-aza-2′-deoxycytidine treatment and identified to be novel miRNAs regulated by DNA methylation. Moreover, we demonstrated the functional relevance of these epigenetically silenced miRNAs by ectopically expressing select candidates, which resulted in inhibition of growth and migration of cancer cells. In addition to reporting these findings, our study also provides a reliable, systematic strategy to identify DNA methylation-regulated miRNAs by combining DNA methylation profiles and expression data.

A Requirement for DICER to Maintain Full Promoter CpG Island Hypermethylation in Human Cancer Cells

Promoter hypermethylation is a prevalent phenomenon, found in virtually all cancer types studied thus far, and accounts for tumor suppressor gene silencing in the absence of genetic mutations. The mechanism behind the establishment and maintenance of such aberrant hypermethylation has been under intense study. Here, we have uncovered a link between aberrant gene silencing associated with promoter CpG island DNA methylation and the siRNA/miRNA processing enzyme, DICER, in human cancer cells. By comparing demethylated HCT116 colon cancer cells with HCT116 cells genetically rendered hypomorphic for DICER, we identified a group of epigenetically silenced genes that became reactivated in the absence of functional DICER. This reactivation is associated with a dramatic loss of localized promoter DNA hypermethylation. Thus, intact DICER is required to maintain full promoter DNA hypermethylation of select epigenetically silenced loci in human cancer cells.

Dysregulation of cholesterol homeostasis in human prostate cancer through loss of ABCA1.

Recent epidemiologic data show that low serum cholesterol level as well as statin use is associated with a decreased risk of developing aggressive or advanced prostate cancer, suggesting a role for cholesterol in aggressive prostate cancer development. Intracellular cholesterol promotes prostate cancer progression as a substrate for de novo androgen synthesis and through regulation of AKT signaling. By conducting next-generation sequencing-based DNA methylome analysis, we have discovered marked hypermethylation at the promoter of the major cellular cholesterol efflux transporter, ABCA1, in LNCaP prostate cancer cells. ABCA1 promoter hypermethylation renders the promoter unresponsive to transactivation and leads to elevated cholesterol levels in LNCaP. ABCA1 promoter hypermethylation is enriched in intermediate- to high-grade prostate cancers and not detectable in benign prostate. Remarkably, ABCA1 downregulation is evident in all prostate cancers examined, and expression levels are inversely correlated with Gleason grade. Our results suggest that cancer-specific ABCA1 hypermethylation and loss of protein expression direct high intracellular cholesterol levels and hence contribute to an environment conducive to tumor progression.

Unique DNA methylome profiles in CpG island methylator phenotype colon cancers

A subset of colorectal cancers was postulated to have the CpG island methylator phenotype (CIMP), a higher propensity for CpG island DNA methylation. The validity of CIMP, its molecular basis, and its prognostic value remain highly controversial. Using MBD-isolated genome sequencing, we mapped and compared genome-wide DNA methylation profiles of normal, non-CIMP, and CIMP colon specimens. Multidimensional scaling analysis revealed that each specimen could be clearly classified as normal, non-CIMP, and CIMP, thus signifying that these three groups have distinctly different global methylation patterns. We discovered 3780 sites in various genomic contexts that were hypermethylated in both non-CIMP and CIMP colon cancers when compared with normal colon. An additional 2026 sites were found to be hypermethylated in CIMP tumors only; and importantly, 80% of these sites were located in CpG islands. These data demonstrate on a genome-wide level that the additional hypermethylation seen in CIMP tumors occurs almost exclusively at CpG islands and support definitively that these tumors were appropriately named. When these sites were examined more closely, we found that 25% were adjacent to sites that were also hypermethylated in non-CIMP tumors. Thus, CIMP is also characterized by more extensive methylation of sites that are already prone to be hypermethylated in colon cancer. These observations indicate that CIMP tumors have specific defects in controlling both DNA methylation seeding and spreading and serve as an important first step in delineating molecular mechanisms that control these processes.

Genome-wide analysis of DNA methylation and gene expression defines molecular characteristics of Crohn’s disease-associated fibrosis

BackgroundFibrosis of the intestine is a common and poorly understood complication of Crohn’s disease (CD) characterized by excessive deposition of extracellular matrix and accompanied by narrowing and obstruction of the gut lumen. Defining the molecular characteristics of this fibrotic disorder is a vital step in the development of specific prediction, prevention, and treatment strategies. Previous epigenetic studies indicate that alterations in DNA methylation could explain the mechanism by which mesenchymal cells adopt the requisite pro-fibrotic phenotype that promotes fibrosis progression. However, to date, genome-wide analysis of the DNA methylome of any type of human fibrosis is lacking. We employed an unbiased approach using deep sequencing to define the DNA methylome and transcriptome of purified fibrotic human intestinal fibroblasts (HIF) from the colons of patients with fibrostenotic CD.ResultsWhen compared with normal fibroblasts, we found that the majority of differential DNA methylation was within introns and intergenic regions and not associated with CpG islands. Only a low percentage occurred in the promoters and exons of genes. Integration of the DNA methylome and transcriptome identified regions in three genes that inversely correlated with gene expression: wingless-type mouse mammary tumor virus integration site family, member 2B (WNT2B) and two eicosanoid synthesis pathway enzymes (prostacyclin synthase and prostaglandin D2 synthase). These findings were independently validated by RT-PCR and bisulfite sequencing. Network analysis of the data also identified candidate molecular interactions relevant to fibrosis pathology.ConclusionsOur definition of a genome-wide fibrosis-specific DNA methylome provides new gene networks and epigenetic states by which to understand mechanisms of pathological gene expression that lead to fibrosis. Our data also provide a basis for development of new fibrosis-specific therapies, as genes dysregulated in fibrotic Crohn’s disease, following functional validation, can serve as new therapeutic targets.

Methylome-wide Sequencing Detects DNA Hypermethylation Distinguishing Indolent from Aggressive Prostate Cancer.

A critical need in understanding the biology of prostate cancer is characterizing the molecular differences between indolent and aggressive cases. Because DNA methylation can capture the regulatory state of tumors, we analyzed differential methylation patterns genome-wide among benign prostatic tissue and low-grade and high-grade prostate cancer and found extensive, focal hypermethylation regions unique to high-grade disease. These hypermethylation regions occurred not only in the promoters of genes but also in gene bodies and at intergenic regions that are enriched for DNA-protein binding sites. Integration with existing RNA-sequencing (RNA-seq) and survival data revealed regions where DNA methylation correlates with reduced gene expression associated with poor outcome. Regions specific to aggressive disease are proximal to genes with distinct functions from regions shared by indolent and aggressive disease. Our compendium of methylation changes reveals crucial molecular distinctions between indolent and aggressive prostate cancer.

Goldmine integrates information placing genomic ranges into meaningful biological contexts

Bioinformatic analysis often produces large sets of genomic ranges that can be difficult to interpret in the absence of genomic context. Goldmine annotates genomic ranges from any source with gene model and feature contexts to facilitate global descriptions and candidate loci discovery. We demonstrate the value of genomic context by using Goldmine to elucidate context dynamics in transcription factor binding and to reveal differentially methylated regions (DMRs) with context-specific functional correlations. The open source R package and documentation for Goldmine are available at http://jeffbhasin.github.io/goldmine.

MethylAction: detecting differentially methylated regions that distinguish biological subtypes

DNA methylation differences capture substantial information about the molecular and gene-regulatory states among biological subtypes. Enrichment-based next generation sequencing methods such as MBD-isolated genome sequencing (MiGS) and MeDIP-seq are appealing for studying DNA methylation genome-wide in order to distinguish between biological subtypes. However, current analytic tools do not provide optimal features for analyzing three-group or larger study designs. MethylAction addresses this need by detecting all possible patterns of statistically significant hyper- and hypo- methylation in comparisons involving any number of groups. Crucially, significance is established at the level of differentially methylated regions (DMRs), and bootstrapping determines false discovery rates (FDRs) associated with each pattern. We demonstrate this functionality in a four-group comparison among benign prostate and three clinical subtypes of prostate cancer and show that the bootstrap FDRs are highly useful in selecting the most robust patterns of DMRs. Compared to existing tools that are limited to two-group comparisons, MethylAction detects more DMRs with strong differential methylation measurements confirmed by whole genome bisulfite sequencing and offers a better balance between precision and recall in cross-cohort comparisons. MethylAction is available as an R package at http://jeffbhasin.github.io/methylaction.