Anthony D. Schmitt

A high-resolution map of the three-dimensional chromatin interactome in human cells

A large number of cis-regulatory sequences have been annotated in the human genome, but defining their target genes remains a challenge. One strategy is to identify the long-range looping interactions at these elements with the use of chromosome conformation capture (3C)-based techniques. However, previous studies lack either the resolution or coverage to permit a whole-genome, unbiased view of chromatin interactions. Here we report a comprehensive chromatin interaction map generated in human fibroblasts using a genome-wide 3C analysis method (Hi-C). We determined over one million long-range chromatin interactions at 5–10-kb resolution, and uncovered general principles of chromatin organization at different types of genomic features. We also characterized the dynamics of promoter–enhancer contacts after TNF-α signalling in these cells. Unexpectedly, we found that TNF-α-responsive enhancers are already in contact with their target promoters before signalling. Such pre-existing chromatin looping, which also exists in other cell types with different extracellular signalling, is a strong predictor of gene induction. Our observations suggest that the three-dimensional chromatin landscape, once established in a particular cell type, is relatively stable and could influence the selection or activation of target genes by a ubiquitous transcription activator in a cell-specific manner.

Human body epigenome maps reveal noncanonical DNA methylation variation

Understanding the diversity of human tissues is fundamental to disease and requires linking genetic information, which is identical in most of an individual’s cells, with epigenetic mechanisms that could have tissue-specific roles. Surveys of DNA methylation in human tissues have established a complex landscape including both tissue-specific and invariant methylation patterns. Here we report high coverage methylomes that catalogue cytosine methylation in all contexts for the major human organ systems, integrated with matched transcriptomes and genomic sequence. By combining these diverse data types with each individuals’ phased genome, we identified widespread tissue-specific differential CG methylation (mCG), partially methylated domains, allele-specific methylation and transcription, and the unexpected presence of non-CG methylation (mCH) in almost all human tissues. mCH correlated with tissue-specific functions, and using this mark, we made novel predictions of genes that escape X-chromosome inactivation in specific tissues. Overall, DNA methylation in several genomic contexts varies substantially among human tissues.

Integrative analysis of haplotype-resolved epigenomes across human tissues.

Allelic differences between the two homologous chromosomes can affect the propensity of inheritance in humans; however, the extent of such differences in the human genome has yet to be fully explored. Here we delineate allelic chromatin modifications and transcriptomes among a broad set of human tissues, enabled by a chromosome-spanning haplotype reconstruction strategy. The resulting large collection of haplotype-resolved epigenomic maps reveals extensive allelic biases in both chromatin state and transcription, which show considerable variation across tissues and between individuals, and allow us to investigate cis-regulatory relationships between genes and their control sequences. Analyses of histone modification maps also uncover intriguing characteristics of cis-regulatory elements and tissue-restricted activities of repetitive elements. The rich data sets described here will enhance our understanding of the mechanisms by which cis-regulatory elements control gene expression programs.

A Compendium of Chromatin Contact Maps Reveals Spatially Active Regions in the Human Genome.

The three-dimensional configuration of DNA is integral to all nuclear processes in eukaryotes, yet our knowledge of the chromosome architecture is still limited. Genome-wide chromosome conformation capture studies have uncovered features of chromatin organization in cultured cells, but genome architecture in human tissues has yet to be explored. Here, we report the most comprehensive survey to date of chromatin organization in human tissues. Through integrative analysis of chromatin contact maps in 21 primary human tissues and cell types, we find topologically associating domains highly conserved in different tissues. We also discover genomic regions that exhibit unusually high levels of local chromatin interactions. These frequently interacting regions (FIREs) are enriched for super-enhancers and are near tissue-specifically expressed genes. They display strong tissue-specificity in local chromatin interactions. Additionally, FIRE formation is partially dependent on CTCF and the Cohesin complex. We further show that FIREs can help annotate the function of non-coding sequence variants.

Genome-wide mapping and analysis of chromosome architecture

Chromosomes of eukaryotes adopt highly dynamic and complex hierarchical structures in the nucleus. The three-dimensional (3D) organization of chromosomes profoundly affects DNA replication, transcription and the repair of DNA damage. Thus, a thorough understanding of nuclear architecture is fundamental to the study of nuclear processes in eukaryotic cells. Recent years have seen rapid proliferation of technologies to investigate genome organization and function. Here, we review experimental and computational methodologies for 3D genome analysis, with special focus on recent advances in high-throughput chromatin conformation capture (3C) techniques and data analysis.

High Resolution Mapping of Chromatin Conformation in Cardiac Myocytes Reveals Structural Remodeling of the Epigenome in Heart Failure

Background: Cardiovascular disease is associated with epigenomic changes in the heart; however, the endogenous structure of cardiac myocyte chromatin has never been determined. Methods: To investigate the mechanisms of epigenomic function in the heart, genome-wide chromatin conformation capture (Hi-C) and DNA sequencing were performed in adult cardiac myocytes following development of pressure overload–induced hypertrophy. Mice with cardiac-specific deletion of CTCF (a ubiquitous chromatin structural protein) were generated to explore the role of this protein in chromatin structure and cardiac phenotype. Transcriptome analyses by RNA-seq were conducted as a functional readout of the epigenomic structural changes. Results: Depletion of CTCF was sufficient to induce heart failure in mice, and human patients with heart failure receiving mechanical unloading via left ventricular assist devices show increased CTCF abundance. Chromatin structural analyses revealed interactions within the cardiac myocyte genome at 5-kb resolution, enabling examination of intra- and interchromosomal events, and providing a resource for future cardiac epigenomic investigations. Pressure overload or CTCF depletion selectively altered boundary strength between topologically associating domains and A/B compartmentalization, measurements of genome accessibility. Heart failure involved decreased stability of chromatin interactions around disease-causing genes. In addition, pressure overload or CTCF depletion remodeled long-range interactions of cardiac enhancers, resulting in a significant decrease in local chromatin interactions around these functional elements. Conclusions: These findings provide a high-resolution chromatin architecture resource for cardiac epigenomic investigations and demonstrate that global structural remodeling of chromatin underpins heart failure. The newly identified principles of endogenous chromatin structure have key implications for epigenetic therapy.

Corrigendum: Human body epigenome maps reveal noncanonical DNA methylation variation

Author(s): Schultz, Matthew D; He, Yupeng; Whitaker, John W; Hariharan, Manoj; Mukamel, Eran A; Leung, Danny; Rajagopal, Nisha; Nery, Joseph R; Urich, Mark A; Chen, Huaming; Lin, Shin; Lin, Yiing; Jung, Inkyung; Schmitt, Anthony D; Selvaraj, Siddarth; Ren, Bing; Sejnowski, Terrence J; Wang, Wei; Ecker, Joseph R

Erratum: Human body epigenome maps reveal noncanonical DNA methylation variation (Nature (2015) 523 (212-216) DOI: 10.1038/nature14465)

Author(s): Schultz, Matthew D; He, Yupeng; Whitaker, John W; Hariharan, Manoj; Mukamel, Eran A; Leung, Danny; Rajagopal, Nisha; Nery, Joseph R; Urich, Mark A; Chen, Huaming; Lin, Shin; Lin, Yiing; Jung, Inkyung; Schmitt, Anthony D; Selvaraj, Siddarth; Ren, Bing; Sejnowski, Terrence J; Wang, Wei; Ecker, Joseph R

Integration of phased Hi-C and molecular phenotype data to study genetic and epigenetic effects on chromatin looping

While genetic variation at chromatin loops is relevant for human disease, the relationships between loop strength, genetics, gene expression, and epigenetics are unclear. Here, we quantitatively interrogate this relationship using Hi-C and molecular phenotype data across cell types and haplotypes. We find that chromatin loops consistently form across multiple cell types and quantitatively vary in strength, instead of exclusively forming within only one cell type. We show that large haplotype loop imbalance is primarily associated with imprinting and copy number variation, rather than genetically driven traits such as allele-specific expression. Finally, across cell types and haplotypes, we show that subtle changes in chromatin loop strength are associated with large differences in other molecular phenotypes, with a 2-fold change in looping corresponding to a 100-fold change in gene expression. Our study suggests that regulatory genetic variation could mediate its effects on gene expression through subtle modification of chromatin loop strength.

Integrating Hi-C links with assembly graphs for chromosome-scale assembly

Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA Author summary Hi-C technology was originally proposed to study the 3D organization of a genome. Recently, it has also been applied to assemble large eukaryotic genomes into chromosome-scale scaffolds. Despite this, there are few open source methods to generate these assemblies. Existing methods are also prone to small inversion errors due to noise in the Hi-C data. In this work, we address these challenges and develop a method, named SALSA2. SALSA2 uses sequence overlap information from an assembly graph to correct inversion errors and provide accurate chromosome-scale assemblies.