The genome is organised via CTCF/Cohesin binding sites, which partition chromosomes into 1-5Mb topologically associated domains (TADs), and further into smaller sub-domains (sub-TADs). Here we examined in vivo an ~80kb sub-TAD, containing the mouse α-globin gene cluster, lying within a ~1Mb TAD. We find that the sub-TAD is flanked by predominantly convergent CTCF/cohesin sites which 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.

Complex gene regulation is one of the key requirements for the evolution of higher eukaryotes. 1 In these organisms, many genes are regulated by enhancers that are 10 4 -10 6 base pairs (bp) distant from the promoter. Enhancer sequences usually contain multiple small transcription factor binding sites (typically ~10bp), and physical contact between the promoter and enhancer is thought to be required to modulate gene expression. 2 Current methods have extensively defined chromatin architecture at scales above 1 kb but until now it has not been possible to define physical contacts at the scale of the key proteins determining gene expression. Here we define the interactions between different classes of regulatory elements (enhancers, promoters and boundary elements) in unprecedented detail, using a novel chromosome conformation capture method (Micro Capture-C (MCC)), which allows physical contacts to be determined at base-pair resolution. We find that highly punctate contacts occur between enhancers, promoters and CCCTC-binding factor (CTCF) sites and we show, using base pair resolution plots of ligation junctions, that transcription factors generate a key component of the contacts between enhancers and promoters. Our data show that contacts from CTCF sites highly correlate with cooccupancy of cohesin and that interactions between CTCF sites are increased when active promoters and enhancers are located within the intervening chromatin. We also find that promoters make the strongest contacts with both enhancers and CTCF sites and that while CTCF sites contact promoters strongly they only make weak contacts with enhancers. The highly punctate nature of the contacts is an unexpected finding because the current view is that physical contacts are constrained by much larger domains such as topological associated domains (TADs). 3 Our results support a model in which chromatin loop extrusion 4-6 is dependent on cohesin loading at active promoters and enhancers, explaining the formation of tissue-specific chromatin domains without changes in CTCF binding. The data suggest that a separate mechanism to loop extrusion underlies enhancer-/promoter contacts, which likely involves DNA binding proteins at enhancers and promoters. The unprecedented

Predicting the impact of non-coding genetic variation requires interpreting it in the context of 3D genome architecture. We have developed deepC, a transfer learning based deep neural network that accurately predicts genome folding from megabase-scale DNA sequence. DeepC predicts domain boundaries at high-resolution, learns the sequence determinants of genome folding and predicts the impact of both large-scale structural and single base pair variations.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) disease (COVID-19) pandemic has caused millions of deaths worldwide. Genome-wide association studies (GWAS) identified the 3p21.31 region as conferring a two-fold increased risk of respiratory failure. Here, using a combined multiomics and machine-learning approach, we identify the gain-of-function risk A allele of a single-nucleotide polymorphism (SNP), rs17713054G>A, as a probable causative variant. We show with chromosome conformation capture and gene expression analysis that the rs17713054-affected enhancer upregulates the interacting gene, Leucine Zipper Transcription Factor Like 1 ( LZTFL1 ). Selective spatial transcriptomic analysis of COVID-19 patient lung biopsies shows the presence of signals associated with epithelial-mesenchymal transition (EMT), a viral response pathway that is regulated by LZTFL1 . We conclude that pulmonary epithelial cells undergoing EMT, rather than immune cells, are likely to be responsible for the 3p21.31 associated risk. As the 3p21.31 effect is conferred by a gain-of-function, LZTFL1 may provide a therapeutic target.

β-Thalassemia is one of the most common inherited anemias, with no effective cure for most patients. The pathophysiology reflects an imbalance between α- and β-globin chains with an excess of free α-globin chains causing ineffective erythropoiesis and hemolysis. When α-thalassemia is co-inherited with β-thalassemia, excess free α-globin chains are reduced significantly ameliorating the clinical severity. Here we demonstrate the use of CRISPR/Cas9 genome editing of primary human hematopoietic stem/progenitor (CD34+) cells to emulate a natural mutation, which deletes the MCS-R2 α-globin enhancer and causes α-thalassemia. When edited CD34+ cells are differentiated into erythroid cells, we observe the expected reduction in α-globin expression and a correction of the pathologic globin chain imbalance in cells from patients with β-thalassemia. Xenograft assays show that a proportion of the edited CD34+ cells are long-term repopulating hematopoietic stem cells, demonstrating the potential of this approach for translation into a therapy for β-thalassemia.

Hypoxia is a common phenomenon in solid tumors and is strongly linked to hallmarks of cancer. Recent evidence has shown that hypoxia promotes local immune suppression. Type I IFN supports cytotoxic T lymphocytes by stimulating the maturation of dendritic cells and enhancing their capacity to process and present antigens. However, little is known about the relationship between hypoxia and the type I IFN pathway, which comprises the sensing of double-stranded RNA and DNA (dsRNA/dsDNA) followed by IFNα/β secretion and transcriptional activation of IFN-stimulated genes (ISG). In this study, we determined the effects of hypoxia on the type I IFN pathway in breast cancer and the mechanisms involved. In cancer cell lines and xenograft models, mRNA and protein expressions of the type I IFN pathway were downregulated under hypoxic conditions. This pathway was suppressed at each level of signaling, from the dsRNA sensors RIG-I and MDA5, the adaptor MAVS, transcription factors IRF3, IRF7, and STAT1, and several ISG including RIG-I, IRF7, STAT1, and ADAR-p150. Importantly, IFN secretion was reduced under hypoxic conditions. HIF1α- and HIF2α-mediated regulation of gene expression did not explain most of the effects. However, ATAC-seq data revealed in hypoxia that peaks with STAT1 and IRF3 motifs had decreased accessibility. Collectively, these results indicate that hypoxia leads to an overall downregulation of the type I IFN pathway due to repressed transcription and lower chromatin accessibility in an HIF1/2α-independent manner, which could contribute to immunosuppression in hypoxic tumors. Significance: These findings characterize a new mechanism of immunosuppression by hypoxia via downregulation of the type I IFN pathway and its autocrine/paracrine effects on tumor growth.

Chromosome conformation capture (3C) provides an adaptable tool for studying diverse biological questions. Current 3C methods generally provide either low-resolution interaction profiles across the entire genome, or high-resolution interaction profiles at limited numbers of loci. Due to technical limitations, generation of reproducible high-resolution interaction profiles has not been achieved at genome-wide scale. Here, to overcome this barrier, we systematically test each step of 3C and report two improvements over current methods. We show that up to 30% of reporter events generated using the popular in situ 3C method arise from ligations between two individual nuclei, but this noise can be almost entirely eliminated by isolating intact nuclei after ligation. Using Nuclear-Titrated Capture-C, we generate reproducible high-resolution genome-wide 3C interaction profiles by targeting 8055 gene promoters in erythroid cells. By pairing high-resolution 3C interaction calls with nascent gene expression we interrogate the role of promoter hubs and super-enhancers in gene regulation.

SummaryDynamic cellular processes such as differentiation are driven by changes in the abundances of transcription factors (TFs). Yet, despite years of studies we still do not know the protein copy number of TFs in the nucleus. Here, by determining the absolute abundances of 103 TFs and co-factors during the course of human erythropoiesis, we provide a dynamic and quantitative scale for TFs in the nucleus. Furthermore, we establish the first Gene Regulatory Network of cell fate commitment that integrates temporal protein stoichiometry data with mRNA measurements. The model revealed quantitative imbalances in TFs cross-antagonistic relationships that underlie lineage determination. Finally, we made the surprising discovery that in the nucleus, corepressors are dramatically more abundant than coactivators at the protein, but not at the RNA level, with profound implications for understanding transcriptional regulation. These analyses provide a unique quantitative framework to understand transcriptional regulation of cell differentiation in a dynamic context.