Holger Heyn

Global Epigenomic Reconfiguration During Mammalian Brain Development

Introduction Several lines of evidence point to a key role for dynamic epigenetic changes during brain development, maturation, and learning. DNA methylation (mC) is a stable covalent modification that persists in post-mitotic cells throughout their lifetime, defining their cellular identity. However, the methylation status at each of the ~1 billion cytosines in the genome is potentially an information-rich and flexible substrate for epigenetic modification that can be altered by cellular activity. Indeed, changes in DNA methylation have been implicated in learning and memory, as well as in age-related cognitive decline. However, little is known about the cell type–specific patterning of DNA methylation and its dynamics during mammalian brain development. The DNA methylation landscape of human and mouse neurons is dynamically reconfigured through development. Base-resolution analysis allowed identification of methylation in the CG and CH context (H = A, C, or T). Unlike other differentiated cell types, neurons accumulate substantial mCH during the early years of life, coinciding with the period of synaptogenesis and brain maturation. Methods We performed genome-wide single-base resolution profiling of the composition, patterning, cell specificity, and dynamics of DNA methylation in the frontal cortex of humans and mice throughout their lifespan (MethylC-Seq). Furthermore, we generated base-resolution maps of 5-hydroxymethylcytosine (hmC) in mammalian brains by TAB-Seq at key developmental stages, accompanied by RNA-Seq transcriptional profiling. Results Extensive methylome reconfiguration occurs during development from fetal to young adult. In this period, coincident with synaptogenesis, highly conserved non-CG methylation (mCH) accumulates in neurons, but not glia, to become the dominant form of methylation in the human neuronal genome. We uncovered surprisingly complex features of brain cell DNA methylation at multiple scales, first by identifying intragenic methylation patterns in neurons and glia that distinguish genes with cell type–specific activity. Second, we report a novel mCH signature that identifies genes escaping X-chromosome inactivation in neurons. Third, we find >100,000 developmentally dynamic and cell type–specific differentially CG-methylated regions that are enriched at putative regulatory regions of the genome. Finally, whole-genome detection of 5-hydroxymethylcytosine (hmC) at single-base resolution revealed that this mark is present in fetal brain cells at locations that lose CG methylation and become activated during development. CG-demethylation at these hmC-poised loci depends on Tet2 activity. Discussion Whole-genome single-base resolution methylcytosine and hydroxymethylcytosine maps revealed profound changes during frontal cortex development in humans and mice. These results extend our knowledge of the unique role of DNA methylation in brain development and function, and offer a new framework for testing the role of the epigenome in healthy function and in pathological disruptions of neural circuits. Overall, brain cell DNA methylation has unique features that are precisely conserved, yet dynamic and cell-type specific. Epigenetic Brainscape Epigenetic modifications and their potential changes during development are of high interest, but few studies have characterized such differences. Lister et al. (1237905, published online 4 July; see the Perspective by Gabel and Greenberg) report whole-genome base-resolution analysis of DNA cytosine modifications and transcriptome analysis in the frontal cortex of human and mouse brains at multiple developmental stages. The high-resolution mapping of DNA cytosine methylation (5mC) and one of its oxidation derivatives (5hmC) at key developmental stages provides a comprehensive resource covering the temporal dynamics of these epigenetic modifications in neurons compared to glia. The data suggest that methylation marks are dynamic during brain development in both humans and mice. A genome-wide map shows that DNA methylation in neurons and glial cells changes during development in humans and mice. [Also see Perspective by Gabel and Greenberg] DNA methylation is implicated in mammalian brain development and plasticity underlying learning and memory. We report the genome-wide composition, patterning, cell specificity, and dynamics of DNA methylation at single-base resolution in human and mouse frontal cortex throughout their lifespan. Widespread methylome reconfiguration occurs during fetal to young adult development, coincident with synaptogenesis. During this period, highly conserved non-CG methylation (mCH) accumulates in neurons, but not glia, to become the dominant form of methylation in the human neuronal genome. Moreover, we found an mCH signature that identifies genes escaping X-chromosome inactivation. Last, whole-genome single-base resolution 5-hydroxymethylcytosine (hmC) maps revealed that hmC marks fetal brain cell genomes at putative regulatory regions that are CG-demethylated and activated in the adult brain and that CG demethylation at these hmC-poised loci depends on Tet2 activity.

Distinct DNA methylomes of newborns and centenarians

Human aging cannot be fully understood in terms of the constrained genetic setting. Epigenetic drift is an alternative means of explaining age-associated alterations. To address this issue, we performed whole-genome bisulfite sequencing (WGBS) of newborn and centenarian genomes. The centenarian DNA had a lower DNA methylation content and a reduced correlation in the methylation status of neighboring cytosine—phosphate—guanine (CpGs) throughout the genome in comparison with the more homogeneously methylated newborn DNA. The more hypomethylated CpGs observed in the centenarian DNA compared with the neonate covered all genomic compartments, such as promoters, exonic, intronic, and intergenic regions. For regulatory regions, the most hypomethylated sequences in the centenarian DNA were present mainly at CpG-poor promoters and in tissue-specific genes, whereas a greater level of DNA methylation was observed in CpG island promoters. We extended the study to a larger cohort of newborn and nonagenarian samples using a 450,000 CpG-site DNA methylation microarray that reinforced the observation of more hypomethylated DNA sequences in the advanced age group. WGBS and 450,000 analyses of middle-age individuals demonstrated DNA methylomes in the crossroad between the newborn and the nonagenarian/centenarian groups. Our study constitutes a unique DNA methylation analysis of the extreme points of human life at a single-nucleotide resolution level.

DNA methylation profiling in the clinic: applications and challenges

Knowledge of epigenetic alterations in disease is rapidly increasing owing to the development of genome-wide techniques for their identification. The ever-growing number of genes that show epigenetic alterations in disease emphasizes the crucial role of these epigenetic alterations — particularly DNA methylation — for future diagnosis, prognosis and prediction of response to therapies. This Review focuses on epigenetic profiling, which has started to be of clinical value in cancer and may in the future be extended to other diseases, such as neurological and autoimmune disorders.

A Landscape of Pharmacogenomic Interactions in Cancer

Summary Systematic studies of cancer genomes have provided unprecedented insights into the molecular nature of cancer. Using this information to guide the development and application of therapies in the clinic is challenging. Here, we report how cancer-driven alterations identified in 11,289 tumors from 29 tissues (integrating somatic mutations, copy number alterations, DNA methylation, and gene expression) can be mapped onto 1,001 molecularly annotated human cancer cell lines and correlated with sensitivity to 265 drugs. We find that cell lines faithfully recapitulate oncogenic alterations identified in tumors, find that many of these associate with drug sensitivity/resistance, and highlight the importance of tissue lineage in mediating drug response. Logic-based modeling uncovers combinations of alterations that sensitize to drugs, while machine learning demonstrates the relative importance of different data types in predicting drug response. Our analysis and datasets are rich resources to link genotypes with cellular phenotypes and to identify therapeutic options for selected cancer sub-populations.

DNA methylation contributes to natural human variation

DNA methylation patterns are important for establishing cell, tissue, and organism phenotypes, but little is known about their contribution to natural human variation. To determine their contribution to variability, we have generated genome-scale DNA methylation profiles of three human populations (Caucasian-American, African-American, and Han Chinese-American) and examined the differentially methylated CpG sites. The distinctly methylated genes identified suggest an influence of DNA methylation on phenotype differences, such as susceptibility to certain diseases and pathogens, and response to drugs and environmental agents. DNA methylation differences can be partially traced back to genetic variation, suggesting that differentially methylated CpG sites serve as evolutionarily established mediators between the genetic code and phenotypic variability. Notably, one-third of the DNA methylation differences were not associated with any genetic variation, suggesting that variation in population-specific sites takes place at the genetic and epigenetic levels, highlighting the contribution of epigenetic modification to natural human variation.

A Prognostic DNA Methylation Signature for Stage I Non–Small-Cell Lung Cancer

PURPOSE Non-small-cell lung cancer (NSCLC) is a tumor in which only small improvements in clinical outcome have been achieved. The issue is critical for stage I patients for whom there are no available biomarkers that indicate which high-risk patients should receive adjuvant chemotherapy. We aimed to find DNA methylation markers that could be helpful in this regard. PATIENTS AND METHODS A DNA methylation microarray that analyzes 450,000 CpG sites was used to study tumoral DNA obtained from 444 patients with NSCLC that included 237 stage I tumors. The prognostic DNA methylation markers were validated by a single-methylation pyrosequencing assay in an independent cohort of 143 patients with stage I NSCLC. RESULTS Unsupervised clustering of the 10,000 most variable DNA methylation sites in the discovery cohort identified patients with high-risk stage I NSCLC who had shorter relapse-free survival (RFS; hazard ratio [HR], 2.35; 95% CI, 1.29 to 4.28; P = .004). The study in the validation cohort of the significant methylated sites from the discovery cohort found that hypermethylation of five genes was significantly associated with shorter RFS in stage I NSCLC: HIST1H4F, PCDHGB6, NPBWR1, ALX1, and HOXA9. A signature based on the number of hypermethylated events distinguished patients with high- and low-risk stage I NSCLC (HR, 3.24; 95% CI, 1.61 to 6.54; P = .001). CONCLUSION The DNA methylation signature of NSCLC affects the outcome of stage I patients, and it can be practically determined by user-friendly polymerase chain reaction assays. The analysis of the best DNA methylation biomarkers improved prognostic accuracy beyond standard staging.

Comparative Analysis of Single-Cell RNA Sequencing Methods

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq, and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq, and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq, and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods, and it provides a framework for benchmarking further improvements of scRNA-seq protocols.

DNA methylation profiling in breast cancer discordant identical twins identifies DOK7 as novel epigenetic biomarker

Using whole blood from 15 twin pairs discordant for breast cancer and high-resolution (450K) DNA methylation analysis, we identified 403 differentially methylated CpG sites including known and novel potential breast cancer genes. Confirming the results in an independent validation cohort of 21 twin pairs determined the docking protein DOK7 as a candidate for blood-based cancer diagnosis. DNA hypermethylation of the promoter region was also seen in primary breast cancer tissues and cancer cell lines. Hypermethylation of DOK7 occurs years before tumor diagnosis, suggesting a role as a powerful epigenetic blood-based biomarker as well as providing insights into breast cancer pathogenesis.

A DNA Methylation Map of Human Atherosclerosis.

Background—Epigenetic alterations may contribute to the development of atherosclerosis. In particular, DNA methylation, a reversible and highly regulated DNA modification, could influence disease onset and progression because it functions as an effector for environmental influences, including diet and lifestyle, both of which are risk factors for cardiovascular diseases. Methods and Results—To address the role of DNA methylation changes in atherosclerosis, we compared a donor-matched healthy and atherosclerotic human aorta sample using whole-genome shotgun bisulfite sequencing. We observed that the atherosclerotic portion of the aorta was hypermethylated across many genomic loci in comparison with the matched healthy counterpart. Furthermore, we defined specific loci of differential DNA methylation using a set of donor-matched aortic samples and a high-density (>450 000 CpG sites) DNA methylation microarray. The functional importance in the disease was corroborated by crossing the DNA methylation signature with the corresponding expression data of the same samples. Among the differentially methylated CpGs associated with atherosclerosis onset, we identified genes participating in endothelial and smooth muscle functions. These findings provide new clues toward a better understanding of the molecular mechanisms of atherosclerosis. Conclusions—Our data identify an atherosclerosis-specific DNA methylation profile that highlights the contribution of different genes and pathways to the disorder. Interestingly, the observed gain of DNA methylation in the atherosclerotic lesions justifies efforts to develop DNA demethylating agents for therapeutic benefit.

Dynamics of DNA Methylation in Recent Human and Great Ape Evolution

DNA methylation is an epigenetic modification involved in regulatory processes such as cell differentiation during development, X-chromosome inactivation, genomic imprinting and susceptibility to complex disease. However, the dynamics of DNA methylation changes between humans and their closest relatives are still poorly understood. We performed a comparative analysis of CpG methylation patterns between 9 humans and 23 primate samples including all species of great apes (chimpanzee, bonobo, gorilla and orangutan) using Illumina Methylation450 bead arrays. Our analysis identified ∼800 genes with significantly altered methylation patterns among the great apes, including ∼170 genes with a methylation pattern unique to human. Some of these are known to be involved in developmental and neurological features, suggesting that epigenetic changes have been frequent during recent human and primate evolution. We identified a significant positive relationship between the rate of coding variation and alterations of methylation at the promoter level, indicative of co-occurrence between evolution of protein sequence and gene regulation. In contrast, and supporting the idea that many phenotypic differences between humans and great apes are not due to amino acid differences, our analysis also identified 184 genes that are perfectly conserved at protein level between human and chimpanzee, yet show significant epigenetic differences between these two species. We conclude that epigenetic alterations are an important force during primate evolution and have been under-explored in evolutionary comparative genomics.