Seungyeul Yoo

Epigenome-wide differences in pathology-free regions of multiple sclerosis–affected brains

Using the Illumina 450K array and a stringent statistical analysis with age and gender correction, we report genome-wide differences in DNA methylation between pathology-free regions derived from human multiple sclerosis–affected and control brains. Differences were subtle, but widespread and reproducible in an independent validation cohort. The transcriptional consequences of differential DNA methylation were further defined by genome-wide RNA-sequencing analysis and validated in two independent cohorts. Genes regulating oligodendrocyte survival, such as BCL2L2 and NDRG1, were hypermethylated and expressed at lower levels in multiple sclerosis–affected brains than in controls, while genes related to proteolytic processing (for example, LGMN, CTSZ) were hypomethylated and expressed at higher levels. These results were not due to differences in cellular composition between multiple sclerosis and controls. Thus, epigenomic changes in genes affecting oligodendrocyte susceptibility to damage are detected in pathology-free areas of multiple sclerosis–affected brains.

Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases

Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non‐demented controls, we investigated global disruptions in the co‐regulation of genes in two neurodegenerative diseases, late‐onset Alzheimers disease (AD) and Huntingtons disease (HD). We identified networks of differentially co‐expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242‐gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter‐connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter‐connection of these two processes and our key regulator prediction, we generated two brain‐specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 × 10−12), while Dnmt3a KO signature does not (P = 0.017).

Integrative Analysis of DNA Methylation and Gene Expression Data Identifies EPAS1 as a Key Regulator of COPD

Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a ‘causal’ role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology.

SiteComp: a server for ligand binding site analysis in protein structures

MOTIVATION Computational characterization of ligand-binding sites in proteins provides preliminary information for functional annotation, protein design and ligand optimization. SiteComp implements binding site analysis for comparison of binding sites, evaluation of residue contribution to binding sites and identification of sub-sites with distinct molecular interaction properties. AVAILABILITY AND IMPLEMENTATION The SiteComp server and tutorials are freely available at http://sitecomp.sanchezlab.org.

Functional Characterization of DNA Methylation in the Oligodendrocyte Lineage

Oligodendrocytes derive from progenitors (OPCs) through the interplay of epigenomic and transcriptional events. By integrating high-resolution methylomics, RNA-sequencing, and multiple transgenic lines, this study defines the role of DNMT1 in developmental myelination. We detected hypermethylation of genes related to cell cycle and neurogenesis during differentiation of OPCs, yet genetic ablation of Dnmt1 resulted in inefficient OPC expansion and severe hypomyelination associated with ataxia and tremors in mice. This phenotype was not caused by lineage switch or massive apoptosis but was characterized by a profound defect of differentiation associated with changes in exon-skipping and intron-retention splicing events and by the activation of an endoplasmic reticulum stress response. Therefore, loss of Dnmt1 in OPCs is not sufficient to induce a lineage switch but acts as an important determinant of the coordination between RNA splicing and protein synthesis necessary for myelin formation.

MODMatcher: multi-omics data matcher for integrative genomic analysis.

Errors in sample annotation or labeling often occur in large-scale genetic or genomic studies and are difficult to avoid completely during data generation and management. For integrative genomic studies, it is critical to identify and correct these errors. Different types of genetic and genomic data are inter-connected by cis-regulations. On that basis, we developed a computational approach, Multi-Omics Data Matcher (MODMatcher), to identify and correct sample labeling errors in multiple types of molecular data, which can be used in further integrative analysis. Our results indicate that inspection of sample annotation and labeling error is an indispensable data quality assurance step. Applied to a large lung genomic study, MODMatcher increased statistically significant genetic associations and genomic correlations by more than two-fold. In a simulation study, MODMatcher provided more robust results by using three types of omics data than two types of omics data. We further demonstrate that MODMatcher can be broadly applied to large genomic data sets containing multiple types of omics data, such as The Cancer Genome Atlas (TCGA) data sets.

A pilot systematic genomic comparison of recurrence risks of hepatitis B virus-associated hepatocellular carcinoma with low- and high-degree liver fibrosis

BackgroundChronic hepatitis B virus (HBV) infection leads to liver fibrosis, which is a major risk factor in hepatocellular carcinoma (HCC) and an independent risk factor of recurrence after HCC tumor resection. The HBV genome can be inserted into the human genome, and chronic inflammation may trigger somatic mutations. However, how HBV integration and other genomic changes contribute to the risk of tumor recurrence with regards to the different degree of liver fibrosis is not clearly understood.MethodsWe sequenced mRNAs of 21 pairs of tumor and distant non-neoplastic liver tissues of HBV-HCC patients and performed comprehensive genomic analyses of our RNAseq data and public available HBV-HCC sequencing data.ResultsWe developed a robust pipeline for sensitively identifying HBV integration sites based on sequencing data. Simulations showed that our method outperformed existing methods. Applying it to our data, 374 and 106 HBV host genes were identified in non-neoplastic liver and tumor tissues, respectively. When applying it to other RNA sequencing datasets, consistently more HBV integrations were identified in non-neoplastic liver than in tumor tissues. HBV host genes identified in non-neoplastic liver samples significantly overlapped with known tumor suppressor genes. More significant enrichment of tumor suppressor genes was observed among HBV host genes identified from patients with tumor recurrence, indicating the potential risk of tumor recurrence driven by HBV integration in non-neoplastic liver tissues. We also compared SNPs of each sample with SNPs in a cancer census database and inferred samples’ pathogenic SNP loads. Pathogenic SNP loads in non-neoplastic liver tissues were consistently higher than those in normal liver tissues. Additionally, HBV host genes identified in non-neoplastic liver tissues significantly overlapped with pathogenic somatic mutations, suggesting that HBV integration and somatic mutations targeting the same set of genes are important to tumorigenesis. HBV integrations and pathogenic mutations showed distinct patterns between low and high liver fibrosis patients with regards to tumor recurrence.ConclusionsThe results suggest that HBV integrations and pathogenic SNPs in non-neoplastic tissues are important for tumorigenesis and different recurrence risk models are needed for patients with low and high degrees of liver fibrosis.

Impact of non-neoplastic vs intratumoural hepatitis B viral DNA and replication on hepatocellular carcinoma recurrence

Background:This study aims to determine the impact of intracellular hepatitis B virus (HBV) DNA, covalently closed circular DNA (cccDNA) and viral replicative activity in both tumour and non-neoplastic liver on prognosis and to determine the relationship of viral replicative activity and Ishak fibrosis in predicting outcome following resection.Methods:A total of 99 prospectively enrolled patients treated with primary liver resection for HBV-HCC are included. Intracellular HBV DNA and cccDNA were quantitated by real-time PCR. The RNA-sequencing (RNA-seq) was performed in a subset of 21 patients who had either minimal liver fibrosis (Ishak stages 0–2) or end-stage fibrosis (Ishak stage 6).Results:Tumour tissue contained a lower cccDNA copy number compared with paired non-neoplastic liver, and larger tumours (>3 cm) had less cccDNA compared with small tumours (⩽3 cm). High viral replicative activity in non-neoplastic liver was associated with higher HCC recurrence rate independent of Ishak fibrosis stage. Genes correlated with viral replicative activity in non-neoplastic liver (620 genes) were distinct from those associated with end-stage fibrosis (1226 genes). Genes associated with viral replicative activity were preferentially distributed in regions on chr3, chr16 and chr19.Conclusions:Viral replicative activity in non-neoplastic liver is associated with HCC recurrence through mechanisms that are distinct from and independent of Ishak fibrosis stage.

Integrating epigenetic data into molecular casual networks

Genome-wide association studies (GWAS) have recently identified many risk loci for complex human diseases. However, genetics can explain only a fraction of disease variation. Epigenetics refers to cellular mechanisms that affect gene expression without modifying DNA sequence[1]. Epigenetic mechanisms reflect gene X environment interactions, which contribute to risk for many chronic diseases including obesity [2], hypertension [3], cancers [4], chronic inflammation [5], chronic pain [6], and chronic obstructive pulmonary disease (COPD) [7]. While these studies have provided an initial look into genetic or epigenetic factors affecting disease risk or disease severity, understanding the transcriptional regulation by genetic and epigenetic factors, such as DNA methylation and microRNA, may shed light on understanding the biological processes and molecular mechanisms associated complex human diseases. By integrating genetic, epigenetic, and transcriptomic data we developed genetic causality tests [8,9] and a novel methylation-based causality test. Then, we developed a method to construct a global Bayesian network [10-12] using the causal test results as priors. As a proof-of-concept, we applied these methods to genome-wide genetic, epigenetic, and transcriptomic data and phenotypic data generated from lung tissues of COPD patients and non-COPD controls, and identified multiple causal regulators for pathways associated with disease severity. We experimentally validated candidate genes in cell lines, mouse models, and in human tissues. Our results suggest that the integrative causal network can provide important insights into understanding the mechanisms underlying epigenetic regulations, altering transcriptional programs that lead to COPD pathogenesis and progression. These approaches can be applied to uncover molecular mechanisms underlying other diseases, such as chronic pain.

Oncogenic role of sFRP2 in P53-mutant osteosarcoma development via autocrine and paracrine mechanism

Osteosarcoma (OS), the most common primary bone tumor, is highly metastatic with high chemotherapeutic resistance and poor survival rates. Using induced pluripotent stem cells (iPSCs) generated from Li-Fraumeni syndrome (LFS) patients, we investigated an oncogenic role of secreted frizzled-related protein 2 (sFRP2) in P53 mutation-associated OS development. Interestingly, we found that high sFRP2 expression in OS patient samples correlates with poor survival. Systems-level analyses identified that expression of sFRP2 increases during LFS OS development and can induce angiogenesis. Ectopic sFRP2 overexpression in normal osteoblast precursors is sufficient to suppress normal osteoblast differentiation and to promote OS phenotypes through induction of oncogenic molecules such as FOXM1 and CYR61 in a β-catenin independent manner. Conversely, inhibition of sFRP2, FOXM1 or CYR61 represses the tumorigenic potential. In summary, these findings demonstrate the oncogenic role of sFRP2 in P53 mutation-associated OS development and that inhibition of sFRP2 is a potential therapeutic strategy.