Jim R. Hughes

Genetic dissection of the α-globin super-enhancer in vivo

Many genes determining cell identity are regulated by clusters of Mediator-bound enhancer elements collectively referred to as super-enhancers. These super-enhancers have been proposed to manifest higher-order properties important in development and disease. Here we report a comprehensive functional dissection of one of the strongest putative super-enhancers in erythroid cells. By generating a series of mouse models, deleting each of the five regulatory elements of the α-globin super-enhancer individually and in informative combinations, we demonstrate that each constituent enhancer seems to act independently and in an additive fashion with respect to hematological phenotype, gene expression, chromatin structure and chromosome conformation, without clear evidence of synergistic or higher-order effects. Our study highlights the importance of functional genetic analyses for the identification of new concepts in transcriptional regulation.

How best to identify chromosomal interactions: a comparison of approaches

Chromosome conformation capture (3C) methods are central to understanding the link between nuclear structure and function, and the physical interactions between distal regulatory elements and promoters. However, no one method is appropriate to address all biological questions, as each variant differs markedly in resolution, reproducibility, throughput and biases. A thorough appreciation of the strengths and weaknesses of each technique is critical when choosing the correct method for a specific application or for gauging how best to interpret different sources of data. In addition, the analysis method must be carefully considered, as this choice can profoundly affect the output. In this Review, we describe and compare the different available 3C-based approaches, with a focus on the analysis of mammalian genomes.

Tissue-specific CTCF-cohesin-mediated chromatin architecture delimits enhancer interactions and function in vivo

The genome is organized via CTCF–cohesin-binding sites, which partition chromosomes into 1–5u2009megabase (Mb) topologically associated domains (TADs), and further into smaller sub-domains (sub-TADs). Here we examined inxa0vivo an ∼80u2009kb sub-TAD, containing the mouse α-globin gene cluster, lying within a ∼1u2009Mb TAD. We find that the sub-TAD is flanked by predominantly convergent CTCF–cohesin sites that are ubiquitously bound by CTCF but only interact during erythropoiesis, defining a self-interacting erythroid compartment. Whereas the α-globin regulatory elements normally act solely on promoters downstream of the enhancers, removal of a conserved upstream CTCF–cohesin boundary extends the sub-TAD to adjacent upstream CTCF–cohesin-binding sites. The α-globin enhancers now interact with the flanking chromatin, upregulating expression of genes within this extended sub-TAD. Rather than acting solely as a barrier to chromatin modification, CTCF–cohesin boundaries in this sub-TAD delimit the region of chromatin to which enhancers have access and within which they interact with receptive promoters.

DNA methylation of intragenic CpG islands depends on their transcriptional activity during differentiation and disease

Significance The human genome contains ∼30,000 CpG islands (CGIs), long stretches (0.5–2 kb) of DNA with unusually elevated levels of CpG dinucleotides. Many occur at genes promoters, and their DNA nearly always remains unmethylated. Conversely, intragenic CGIs are often, but not always, methylated, and thus inactive as internal promoters. The mechanisms underlying these contrasting patterns of CGI methylation are poorly understood. We show that methylation of intragenic CGIs is associated with transcription running across the island. Whether or not a particular intragenic CGI becomes methylated during development depends on its transcriptional activity relative to that of the gene within which it lies. Our findings explain how intragenic CGIs are epigenetically programmed in normal development and in human diseases, including malignancy. The human genome contains ∼30,000 CpG islands (CGIs). While CGIs associated with promoters nearly always remain unmethylated, many of the ∼9,000 CGIs lying within gene bodies become methylated during development and differentiation. Both promoter and intragenic CGIs may also become abnormally methylated as a result of genome rearrangements and in malignancy. The epigenetic mechanisms by which some CGIs become methylated but others, in the same cell, remain unmethylated in these situations are poorly understood. Analyzing specific loci and using a genome-wide analysis, we show that transcription running across CGIs, associated with specific chromatin modifications, is required for DNA methyltransferase 3B (DNMT3B)-mediated DNA methylation of many naturally occurring intragenic CGIs. Importantly, we also show that a subgroup of intragenic CGIs is not sensitive to this process of transcription-mediated methylation and that this correlates with their individual intrinsic capacity to initiate transcription in vivo. We propose a general model of how transcription could act as a primary determinant of the patterns of CGI methylation in normal development and differentiation, and in human disease.

VHL Deficiency Drives Enhancer Activation of Oncogenes in Clear Cell Renal Cell Carcinoma

Protein-coding mutations in clear cell renal cell carcinoma (ccRCC) have been extensively characterized, frequently involving inactivation of the von Hippel-Lindau (VHL) tumor suppressor. Roles for noncoding cis-regulatory aberrations in ccRCC tumorigenesis, however, remain unclear. Analyzing 10 primary tumor/normal pairs and 9 cell lines across 79 chromatin profiles, we observed pervasive enhancer malfunction in ccRCC, with cognate enhancer-target genes associated with tissue-specific aspects of malignancy. Superenhancer profiling identified ZNF395 as a ccRCC-specific and VHL-regulated master regulator whose depletion causes near-complete tumor elimination in vitro and in vivoVHL loss predominantly drives enhancer/superenhancer deregulation more so than promoters, with acquisition of active enhancer marks (H3K27ac, H3K4me1) near ccRCC hallmark genes. Mechanistically, VHL loss stabilizes HIF2α-HIF1β heterodimer binding at enhancers, subsequently recruiting histone acetyltransferase p300 without overtly affecting preexisting promoter-enhancer interactions. Subtype-specific driver mutations such as VHL may thus propagate unique pathogenic dependencies in ccRCC by modulating epigenomic landscapes and cancer gene expression.Significance: Comprehensive epigenomic profiling of ccRCC establishes a compendium of somatically altered cis-regulatory elements, uncovering new potential targets including ZNF395, a ccRCC master regulator. Loss of VHL, a ccRCC signature event, causes pervasive enhancer malfunction, with binding of enhancer-centric HIF2α and recruitment of histone acetyltransferase p300 at preexisting lineage-specific promoter-enhancer complexes. Cancer Discov; 7(11); 1284-305. ©2017 AACR.See related commentary by Ricketts and Linehan, p. 1221This article is highlighted in the In This Issue feature, p. 1201.

Robust detection of chromosomal interactions from small numbers of cells using low-input Capture-C

Abstract Chromosome conformation capture (3C) techniques are crucial to understanding tissue-specific regulation of gene expression, but current methods generally require large numbers of cells. This hampers the investigation of chromatin architecture in rare cell populations. We present a new low-input Capture-C approach that can generate high-quality 3C interaction profiles from 10 000–20 000 cells, depending on the resolution used for analysis. We also present a PCR-free, sequencing-free 3C technique based on NanoString technology called C-String. By comparing C-String and Capture-C interaction profiles we show that the latter are not skewed by PCR amplification. Furthermore, we demonstrate that chromatin interactions detected by Capture-C do not depend on the degree of cross-linking by performing experiments with varying formaldehyde concentrations.

HoxC5 and miR-615-3p target newly evolved genomic regions to repress hTERT and inhibit tumorigenesis.

The repression of telomerase activity during cellular differentiation promotes replicative aging and functions as a physiological barrier for tumorigenesis in long-lived mammals, including humans. However, the underlying mechanisms remain largely unclear. Here we describe how miR-615-3p represses hTERT expression. mir-615-3p is located in an intron of the HOXC5 gene, a member of the highly conserved homeobox family of transcription factors controlling embryogenesis and development. Unexpectedly, we found that HoxC5 also represses hTERT expression by disrupting the long-range interaction between hTERT promoter and its distal enhancer. The 3′UTR of hTERT and its upstream enhancer region are well conserved in long-lived primates. Both mir-615-3p and HOXC5 are activated upon differentiation, which constitute a feed-forward loop that coordinates transcriptional and post-transcriptional repression of hTERT during cellular differentiation. Deregulation of HOXC5 and mir-615-3p expression may contribute to the activation of hTERT in human cancers.The expression of telomerase catalytic subunit hTERT is frequently upregulated in many cancers. Here, the authors show HoxC5 and miR-615-3p can negatively regulate hTERT to impede tumorigenesis by targeting the newly evolved cis-regulatory genomic elements of hTERT.

A tissue-specific self-interacting chromatin domain forms independently of enhancer-promoter interactions

Self-interacting chromatin domains encompass genes and their cis-regulatory elements; however, the three-dimensional form a domain takes, whether this relies on enhancer–promoter interactions, and the processes necessary to mediate the formation and maintenance of such domains, remain unclear. To examine these questions, here we use a combination of high-resolution chromosome conformation capture, a non-denaturing form of fluorescence in situ hybridisation and super-resolution imaging to study a 70u2009kb domain encompassing the mouse α-globin regulatory locus. We show that this region forms an erythroid-specific, decompacted, self-interacting domain, delimited by frequently apposed CTCF/cohesinxa0binding sites early in terminal erythroid differentiation, and does not require transcriptional elongation for maintenance of the domain structure. Formation of this domain does not rely on interactions between the α-globin genes and their major enhancers, suggesting a transcription-independent mechanism for establishment of the domain. However, absence of the major enhancers does alter internal domain interactions. Formation of a loop domain therefore appears to be a mechanistic process that occurs irrespective of the specific interactions within.Self-interacting chromatin domains encompass genes and their cis-regulatory elements. Here the authors use high-resolution chromosome conformation capture and super-resolution imaging to study a 70 kb domain that includes the mouse α-globin regulatory locus and find that a tissue-specific self-interacting chromatin domain forms independently of enhancer-promoter interactions.

Between form and function: the complexity of genome folding

Abstract It has been known for over a century that chromatin is not randomly distributed within the nucleus. However, the question of how DNA is folded and the influence of such folding on nuclear processes remain topics of intensive current research. A longstanding, unanswered question is whether nuclear organization is simply a reflection of nuclear processes such as transcription and replication, or whether chromatin is folded by independent mechanisms and this per se encodes function? Evidence is emerging that both may be true. Here, using the α-globin gene cluster as an illustrative model, we provide an overview of the most recent insights into the layers of genome organization across different scales and how this relates to gene activity.

NGseqBasic - a single-command UNIX tool for ATAC-seq, DNaseI-seq, Cut-and-Run, and ChIP-seq data mapping, high-resolution visualisation, and quality control

With decreasing cost of next-generation sequencing (NGS), we are observing a rapid rise in the volume of ‘big data’ in academic research, healthcare and drug discovery sectors. The present bottleneck for extracting value from these ‘big data’ sets is data processing and analysis. Considering this, there is still a lack of reliable, automated and easy to use tools that will allow experimentalists to assess the quality of the sequenced libraries and explore the data first hand, without the need of investing a lot of time of computational core analysts in the early stages of analysis. NGseqBasic is an easy-to-use single-command analysis tool for chromatin accessibility (ATAC, DNaseI) and ChIP sequencing data, providing support to also new techniques such as low cell number sequencing and Cut-and-Run. It takes in fastq, fastq.gz or bam files, conducts all quality control, trimming and mapping steps, along with quality control and data processing statistics, and combines all this to a single-click loadable UCSC data hub, with integral statistics html page providing detailed reports from the analysis tools and quality control metrics. The tool is easy to set up, and no installation is needed. A wide variety of parameters are provided to fine-tune the analysis, with optional setting to generate DNase footprint or high resolution ChIP-seq tracks. A tester script is provided to help in the setup, along with a test data set and downloadable example user cases. NGseqBasic has been used in the routine analysis of next generation sequencing (NGS) data in high-impact publications 1,2. The code is actively developed, and accompanied with Git version control and Github code repository. Here we demonstrate NGseqBasic analysis and features using DNaseI-seq data from GSM689849, and CTCF-ChIP-seq data from GSM2579421, as well as a Cut-and-Run CTCF data set GSM2433142, and provide the one-click loadable UCSC data hubs generated by the tool, allowing for the ready exploration of the run results and quality control files generated by the tool. Availability Download, setup and help instructions are available on the NGseqBasic web site http://userweb.molbiol.ox.ac.uk/public/telenius/NGseqBasicManual/external/ Bioconda users can load the tool as library “ngseqbasic”. The source code with Git version control is available in https://github.com/Hughes-Genome-Group/NGseqBasic/releases. Contact jelena.telenius@imm.ox.ac.uk