Genetic perturbation of PU.1 binding and chromatin looping at neutrophil enhancers associates with autoimmune disease

Neutrophils play fundamental roles in innate immune response, shape adaptive immunity, and are a potentially causal cell type underpinning genetic associations with immune system traits and diseases. Here, we profile the binding of myeloid master regulator PU.1 in primary neutrophils across nearly a hundred volunteers. We show that variants associated with differential PU.1 binding underlie genetically-driven differences in cell count and susceptibility to autoimmune and inflammatory diseases. We integrate these results with other multi-individual genomic readouts, revealing coordinated effects of PU.1 binding variants on the local chromatin state, enhancer-promoter contacts and downstream gene expression, and providing a functional interpretation for 27 genes underlying immune traits. Collectively, these results demonstrate the functional role of PU.1 and its target enhancers in neutrophil transcriptional control and immune disease susceptibility.

Long-Range Enhancer Interactions Are Prevalent in Mouse Embryonic Stem Cells and Are Reorganized upon Pluripotent State Transition

Transcriptional enhancers, including super-enhancers (SEs), form physical interactions with promoters to regulate cell-type-specific gene expression. SEs are characterized by high transcription factor occupancy and large domains of active chromatin, and they are commonly assigned to target promoters using computational predictions. How promoter-SE interactions change upon cell state transitions, and whether transcription factors maintain SE interactions, have not been reported. Here, we used promoter-capture Hi-C to identify promoters that interact with SEs in mouse embryonic stem cells (ESCs). We found that SEs form complex, spatial networks in which individual SEs contact multiple promoters, and a rewiring of promoter-SE interactions occurs between pluripotent states. We also show that long-range promoter-SE interactions are more prevalent in ESCs than in epiblast stem cells (EpiSCs) or Nanog-deficient ESCs. We conclude that SEs form cell-type-specific interaction networks that are partly dependent on core transcription factors, thereby providing insights into the gene regulatory organization of pluripotent cells.

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Promoter-capture Hi-C identifies 3D interactions in mouse pluripotent cells

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Super-enhancers (SEs) form complex spatial networks contacting multiple promoters

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Rewiring of promoter-SE interactions between ESC and EpiSC pluripotent states

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Long-range SE interactions are a hallmark of mouse ESCs

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the spatio-temporal expression of their target genes through physical contact, often bridging considerable (in some cases hundreds of kilobases) genomic distances and bypassing nearby genes. The human genome harbors an estimated one million enhancers, the vast majority of which have unknown gene targets. Assigning distal regulatory regions to their target genes is thus crucial to understand gene expression control. We developed Promoter Capture Hi-C (PCHi-C) to enable the genome-wide detection of distal promoter-interacting regions (PIRs), for all promoters in a single experiment. In PCHi-C, highly complex Hi-C libraries are specifically enriched for promoter sequences through in-solution hybrid selection with thousands of biotinylated RNA baits complementary to the ends of all promoter-containing restriction fragments. The aim is to then pull-down promoter sequences and their frequent interaction partners such as enhancers and other potential regulatory elements. After high-throughput paired-end sequencing, a statistical test is applied to each promoter-ligated restriction fragment to identify significant PIRs at the restriction fragment level. We have used PCHi-C to generate an atlas of long-range promoter interactions in dozens of human and mouse cell types. These promoter interactome maps have contributed to a greater understanding of mammalian gene expression control by assigning putative regulatory regions to their target genes and revealing preferential spatial promoter-promoter interaction networks. This information also has high relevance to understanding human genetic disease and the identification of potential disease genes, by linking non-coding disease-associated sequence variants in or near control sequences to their target genes.

Chromosome contacts in activated T cells identify autoimmune disease candidate genes

Background

Autoimmune disease-associated variants are preferentially found in regulatory regions in immune cells, particularly CD4⁺ T cells. Linking such regulatory regions to gene promoters in disease-relevant cell contexts facilitates identification of candidate disease genes.

Results

Within 4 h, activation of CD4⁺ T cells invokes changes in histone modifications and enhancer RNA transcription that correspond to altered expression of the interacting genes identified by promoter capture Hi-C. By integrating promoter capture Hi-C data with genetic associations for five autoimmune diseases, we prioritised 245 candidate genes with a median distance from peak signal to prioritised gene of 153 kb. Just under half (108/245) prioritised genes related to activation-sensitive interactions. This included IL2RA, where allele-specific expression analyses were consistent with its interaction-mediated regulation, illustrating the utility of the approach.

Conclusions

Our systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1285-0) contains supplementary material, which is available to authorized users.

CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data

Capture Hi-C (CHi-C) is a method for profiling chromosomal interactions involving targeted regions of interest, such as gene promoters, globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments. We implement these procedures in CHiCAGO ( http://regulatorygenomicsgroup.org/chicago ), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs.

Polycomb repressive complex PRC1 spatially constrains the mouse embryonic stem cell genome

The Polycomb repressive complexes PRC1 and PRC2 maintain embryonic stem cell (ESC) pluripotency by silencing lineage-specifying developmental regulator genes. Emerging evidence suggests that Polycomb complexes act through controlling spatial genome organization. We show that PRC1 functions as a master regulator of mouse ESC genome architecture by organizing genes in three-dimensional interaction networks. The strongest spatial network is composed of the four Hox gene clusters and early developmental transcription factor genes, the majority of which contact poised enhancers. Removal of Polycomb repression leads to disruption of promoter-promoter contacts in the Hox gene network. In contrast, promoter-enhancer contacts are maintained in the absence of Polycomb repression, with accompanying widespread acquisition of active chromatin signatures at network enhancers and pronounced transcriptional upregulation of network genes. Thus, PRC1 physically constrains developmental transcription factor genes and their enhancers in a silenced but poised spatial network. We propose that the selective release of genes from this spatial network underlies cell fate specification during early embryonic development.

Comparison of Hi-C results using in-solution versus in-nucleus ligation

Background

Chromosome conformation capture and various derivative methods such as 4C, 5C and Hi-C have emerged as standard tools to analyze the three-dimensional organization of the genome in the nucleus. These methods employ ligation of diluted cross-linked chromatin complexes, intended to favor proximity-dependent, intra-complex ligation. During development of single-cell Hi-C, we devised an alternative Hi-C protocol with ligation in preserved nuclei rather than in solution. Here we directly compare Hi-C methods employing in-nucleus ligation with the standard in-solution ligation.

Results

We show in-nucleus ligation results in consistently lower levels of inter-chromosomal contacts. Through chromatin mixing experiments we show that a significantly large fraction of inter-chromosomal contacts are the result of spurious ligation events formed during in-solution ligation. In-nucleus ligation significantly reduces this source of experimental noise, and results in improved reproducibility between replicates. We also find that in-nucleus ligation eliminates restriction fragment length bias found with in-solution ligation. These improvements result in greater reproducibility of long-range intra-chromosomal and inter-chromosomal contacts, as well as enhanced detection of structural features such as topologically associated domain boundaries.

Conclusions

We conclude that in-nucleus ligation captures chromatin interactions more consistently over a wider range of distances, and significantly reduces both experimental noise and bias. In-nucleus ligation creates higher quality Hi-C libraries while simplifying the experimental procedure. We suggest that the entire range of 3C applications are likely to show similar benefits from in-nucleus ligation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0753-7) contains supplementary material, which is available to authorized users.

The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements

The mammalian genome harbors up to one million regulatory elements often located at great distances from their target genes. Long-range elements control genes through physical contact with promoters and can be recognized by the presence of specific histone modifications and transcription factor binding. Linking regulatory elements to specific promoters genome-wide is currently impeded by the limited resolution of high-throughput chromatin interaction assays. Here we apply a sequence capture approach to enrich Hi-C libraries for >22,000 annotated mouse promoters to identify statistically significant, long-range interactions at restriction fragment resolution, assigning long-range interacting elements to their target genes genome-wide in embryonic stem cells and fetal liver cells. The distal sites contacting active genes are enriched in active histone modifications and transcription factor occupancy, whereas inactive genes contact distal sites with repressive histone marks, demonstrating the regulatory potential of the distal elements identified. Furthermore, we find that coregulated genes cluster nonrandomly in spatial interaction networks correlated with their biological function and expression level. Interestingly, we find the strongest gene clustering in ES cells between transcription factor genes that control key developmental processes in embryogenesis. The results provide the first genome-wide catalog linking gene promoters to their long-range interacting elements and highlight the complex spatial regulatory circuitry controlling mammalian gene expression.