An encyclopedia of enhancer-gene regulatory interactions in the human genome.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and largescale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 elementgene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancerpromoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Genome-wide Association Study Points to Novel Locus for Gilles de la Tourette Syndrome.

BACKGROUND: Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder of complex genetic architecture and is characterized by multiple motor tics and at least one vocal tic persisting for more than 1 year. METHODS: We performed a genome-wide meta-analysis integrating a novel TS cohort with previously published data, resulting in a sample size of 6133 individuals with TS and 13,565 ancestry-matched control participants. RESULTS: We identified a genome-wide significant locus on chromosome 5q15. Integration of expression quantitative trait locus, Hi-C (high-throughput chromosome conformation capture), and genome-wide association study data implicated the NR2F1 gene and associated long noncoding RNAs within the 5q15 locus. Heritability partitioning identified statistically significant enrichment in brain tissue histone marks, while polygenic risk scoring of brain volume data identified statistically significant associations with right and left thalamus volumes and right putamen volume. CONCLUSIONS: Our work presents novel insights into the neurobiology of TS, thereby opening up new directions for future studies.

Leveraging pleiotropy to discover and interpret GWAS results for sleep-associated traits.

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.

Associations Between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants and Risk of Coronavirus Disease 2019 (COVID-19) Hospitalization Among Confirmed Cases in Washington State: A Retrospective Cohort Study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with 7 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. METHODS: Our study includes individuals with positive SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) in the Washington Disease Reporting System with available viral genome data, from 1 December 2020 to 14 January 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. RESULTS: In total, 58 848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95% confidence interval [CI] 2.40-4.26), Beta (HR 2.85, 95% CI 1.56-5.23), Delta (HR 2.28 95% CI 1.56-3.34), or Alpha (HR 1.64, 95% CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95% CI .56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSIONS: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.

Differences in nanoscale organization of regulatory active and inactive human chromatin.

Methodological advances in conformation capture techniques have fundamentally changed our understanding of chromatin architecture. However, the nanoscale organization of chromatin and its cell-to-cell variance are less studied. Analyzing genome-wide data from 733 human cell and tissue samples, we identified 2 prototypical regions that exhibit high or absent hypersensitivity to deoxyribonuclease I, respectively. These regulatory active or inactive regions were examined in the lymphoblast cell line K562 by using high-throughput super-resolution microscopy. In both regions, we systematically measured the physical distance of 2 fluorescence in situ hybridization spots spaced by only 5 kb of DNA. Unexpectedly, the resulting distance distributions range from very compact to almost elongated configurations of more than 200-nm length for both the active and inactive regions. Monte Carlo simulations of a coarse-grained model of these chromatin regions based on published data of nucleosome occupancy in K562 cells were performed to understand the underlying mechanisms. There was no parameter set for the simulation model that can explain the microscopically measured distance distributions. Obviously, the chromatin state given by the strength of internucleosomal interaction, nucleosome occupancy, or amount of histone H1 differs from cell to cell, which results in the observed broad distance distributions. This large variability was not expected, especially in inactive regions. The results for the mechanisms for different distance distributions on this scale are important for understanding the contacts that mediate gene regulation. Microscopic measurements show that the inactive region investigated here is expected to be embedded in a more compact chromatin environment. The simulation results of this region require an increase in the strength of internucleosomal interactions. It may be speculated that the higher density of chromatin is caused by the increased internucleosomal interaction strength.

Associations between SARS-CoV-2 variants and risk of COVID-19 hospitalization among confirmed cases in Washington State: a retrospective cohort study.

BACKGROUND: The COVID-19 pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with seven SARS-CoV-2 variants. METHODS: Our study includes individuals with positive SARS-CoV-2 RT-PCR in the Washington Disease Reporting System with available viral genome data, from December 1, 2020 to January 14, 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. FINDINGS: 58,848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95%CI 2.40-4.26), Beta (HR 2.85, 95%CI 1.56-5.23), Delta (HR 2.28 95%CI 1.56-3.34) or Alpha (HR 1.64, 95%CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95%CI 0.56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSION: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance. SUMMARY: Hospitalization risk following infection with SARS-CoV-2 variant remains unclear. We find a higher hospitalization risk in cases infected with Alpha, Beta, Gamma, and Delta, but not Omicron, with vaccination lowering risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.

Discrete regulatory modules instruct hematopoietic lineage commitment and differentiation.

Lineage commitment and differentiation is driven by the concerted action of master transcriptional regulators at their target chromatin sites. Multiple efforts have characterized the key transcription factors (TFs) that determine the various hematopoietic lineages. However, the temporal interactions between individual TFs and their chromatin targets during differentiation and how these interactions dictate lineage commitment remains poorly understood. Here we perform dense, daily, temporal profiling of chromatin accessibility (DNase I-seq) and gene expression changes (total RNA-seq) along ex vivo human erythropoiesis to comprehensively define developmentally regulated DNase I hypersensitive sites (DHSs) and transcripts. We link both distal DHSs to their target gene promoters and individual TFs to their target DHSs, revealing that the regulatory landscape is organized in distinct sequential regulatory modules that regulate lineage restriction and maturation. Finally, direct comparison of transcriptional dynamics (bulk and single-cell) and lineage potential between erythropoiesis and megakaryopoiesis uncovers differential fate commitment dynamics between the two lineages as they exit the stem and progenitor stage. Collectively, these data provide insights into the temporally regulated synergy of the cis- and the trans-regulatory components underlying hematopoietic lineage commitment and differentiation.

Tissue context determines the penetrance of regulatory DNA variation.

Functional assessment of disease-associated sequence variation at non-coding regulatory elements is complicated by their high degree of context sensitivity to both the local chromatin and nuclear environments. Allelic profiling of DNA accessibility across individuals has shown that only a select minority of sequence variation affects transcription factor (TF) occupancy, yet low sequence diversity in human populations means that no experimental assessment is available for the majority of disease-associated variants. Here we describe high-resolution in vivo maps of allelic DNA accessibility in liver, kidney, lung and B cells from 5 increasingly diverged strains of F1 hybrid mice. The high density of heterozygous sites in these hybrids enables precise quantification of effect size and cell-type specificity for hundreds of thousands of variants throughout the mouse genome. We show that chromatin-altering variants delineate characteristic sensitivity profiles for hundreds of TF motifs. We develop a compendium of TF-specific sensitivity profiles accounting for genomic context effects. Finally, we link maps of allelic accessibility to allelic transcript levels in the same samples. This work provides a foundation for quantitative prediction of cell-type specific effects of non-coding variation on TF activity, which will facilitate both fine-mapping and systems-level analyses of common disease-associated variation in human genomes.

Inaccessible LCG Promoters Act as Safeguards to Restrict T Cell Development to Appropriate Notch Signaling Environments.

T cell development is restricted to the thymus and is dependent on high levels of Notch signaling induced within the thymic microenvironment. To understand Notch function in thymic restriction, we investigated the basis for target gene selectivity in response to quantitative differences in Notch signal strength, focusing on the chromatin architecture of genes essential for T cell differentiation. We find that high Notch signal strength is required to activate promoters of known targets essential for T cell commitment, including Il2ra, Cd3ε, and Rag1, which feature low CpG content (LCG) and DNA inaccessibility in hematopoietic stem progenitor cells. Our findings suggest that promoter DNA inaccessibility at LCG T lineage genes provides robust protection against stochastic activation in inappropriate Notch signaling contexts, limiting T cell development to the thymus.

Global reference mapping of human transcription factor footprints.

Combinatorial binding of transcription factors to regulatory DNA underpins gene regulation in all organisms. Genetic variation in regulatory regions has been connected with diseases and diverse phenotypic traits1, but it remains challenging to distinguish variants that affect regulatory function2. Genomic DNase I footprinting enables the quantitative, nucleotide-resolution delineation of sites of transcription factor occupancy within native chromatin3-6. However, only a small fraction of such sites have been precisely resolved on the human genome sequence6. Here, to enable comprehensive mapping of transcription factor footprints, we produced high-density DNase I cleavage maps from 243 human cell and tissue types and states and integrated these data to delineate about 4.5 million compact genomic elements that encode transcription factor occupancy at nucleotide resolution. We map the fine-scale structure within about 1.6 million DNase I-hypersensitive sites and show that the overwhelming majority are populated by well-spaced sites of single transcription factor-DNA interaction. Cell-context-dependent cis-regulation is chiefly executed by wholesale modulation of accessibility at regulatory DNA rather than by differential transcription factor occupancy within accessible elements. We also show that the enrichment of genetic variants associated with diseases or phenotypic traits in regulatory regions1,7 is almost entirely attributable to variants within footprints, and that functional variants that affect transcription factor occupancy are nearly evenly partitioned between loss- and gain-of-function alleles. Unexpectedly, we find increased density of human genetic variation within transcription factor footprints, revealing an unappreciated driver of cis-regulatory evolution. Our results provide a framework for both global and nucleotide-precision analyses of gene regulatory mechanisms and functional genetic variation.

Perspectives on ENCODE.

The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression1. The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.

Single-molecule regulatory architectures captured by chromatin fiber sequencing.

Gene regulation is chiefly determined at the level of individual linear chromatin molecules, yet our current understanding of cis-regulatory architectures derives from fragmented sampling of large numbers of disparate molecules. We developed an approach for precisely stenciling the structure of individual chromatin fibers onto their composite DNA templates using nonspecific DNA N6-adenine methyltransferases. Single-molecule long-read sequencing of chromatin stencils enabled nucleotide-resolution readout of the primary architecture of multikilobase chromatin fibers (Fiber-seq). Fiber-seq exposed widespread plasticity in the linear organization of individual chromatin fibers and illuminated principles guiding regulatory DNA actuation, the coordinated actuation of neighboring regulatory elements, single-molecule nucleosome positioning, and single-molecule transcription factor occupancy. Our approach and results open new vistas on the primary architecture of gene regulation.

Global Regulatory DNA Potentiation by SMARCA4 Propagates to Selective Gene Expression Programs via Domain-Level Remodeling.

The human genome encodes millions of regulatory elements, of which only a small fraction are active within a given cell type. Little is known about the global impact of chromatin remodelers on regulatory DNA landscapes and how this translates to gene expression. We use precision genome engineering to reawaken homozygously inactivated SMARCA4, a central ATPase of the human SWI/SNF chromatin remodeling complex, in lung adenocarcinoma cells. Here, we combine DNase I hypersensitivity, histone modification, and transcriptional profiling to show that SMARCA4 dramatically increases both the number and magnitude of accessible chromatin sites genome-wide, chiefly by unmasking sites of low regulatory factor occupancy. By contrast, transcriptional changes are concentrated within well-demarcated remodeling domains wherein expression of specific genes is gated by both distal element activation and promoter chromatin configuration. Our results provide a perspective on how global chromatin remodeling activity is translated to gene expression via regulatory DNA.

Highly Parallel Quantification and Compartment Localization of Transcription Factors and Nuclear Proteins.

Transcription factors and other chromatin-associated proteins are difficult to quantify comprehensively. Here, we combine facile nuclear sub-fractionation with data-independent acquisition mass spectrometry to achieve rapid, sensitive, and highly parallel quantification of the nuclear proteome in human cells. We apply this approach to quantify the response to acute degradation of BET bromodomains, revealing unexpected chromatin regulatory dynamics. The method is simple and enables system-level study of previously inaccessible chromatin and genome regulators.

Mapping and Dynamics of Regulatory DNA in Maturing Arabidopsis thaliana Siliques.

The genome is reprogrammed during development to produce diverse cell types, largely through altered expression and activity of key transcription factors. The accessibility and critical functions of epidermal cells have made them a model for connecting transcriptional events to development in a range of model systems. In Arabidopsis thaliana and many other plants, fertilization triggers differentiation of specialized epidermal seed coat cells that have a unique morphology caused by large extracellular deposits of polysaccharides. Here, we used DNase I-seq to generate regulatory landscapes of A. thaliana seeds at two critical time points in seed coat maturation (4 and 7 DPA), enriching for seed coat cells with the INTACT method. We found over 3,000 developmentally dynamic regulatory DNA elements and explored their relationship with nearby gene expression. The dynamic regulatory elements were enriched for motifs for several transcription factors families; most notably the TCP family at the earlier time point and the MYB family at the later one. To assess the extent to which the observed regulatory sites in seeds added to previously known regulatory sites in A. thaliana, we compared our data to 11 other data sets generated with 7-day-old seedlings for diverse tissues and conditions. Surprisingly, over a quarter of the regulatory, i.e. accessible, bases observed in seeds were novel. Notably, plant regulatory landscapes from different tissues, cell types, or developmental stages were more dynamic than those generated from bulk tissue in response to environmental perturbations, highlighting the importance of extending studies of regulatory DNA to single tissues and cell types during development.

Genetic history of the population of Crete.

The medieval history of several populations often suffers from scarcity of contemporary records resulting in contradictory and sometimes biased interpretations by historians. This is the situation with the population of the island of Crete, which remained relatively undisturbed until the Middle Ages when multiple wars, invasions, and occupations by foreigners took place. Historians have considered the effects of the occupation of Crete by the Arabs (in the 9th and 10th centuries C.E.) and the Venetians (in the 13th to the 17th centuries C.E.) to the local population. To obtain insights on such effects from a genetic perspective, we studied representative samples from 17 Cretan districts using the Illumina 1 million or 2.5 million arrays and compared the Cretans to the populations of origin of the medieval conquerors and settlers. Highlights of our findings include (1) small genetic contributions from the Arab occupation to the extant Cretan population, (2) low genetic contribution of the Venetians to the extant Cretan population, and (3) evidence of a genetic relationship among the Cretans and Central, Northern, and Eastern Europeans, which could be explained by the settlement in the island of northern origin tribes during the medieval period. Our results show how the interaction between genetics and the historical record can help shed light on the historical record.

eFORGE v2.0: updated analysis of cell type-specific signal in epigenomic data.

SUMMARY: The Illumina Infinium EPIC BeadChip is a new high-throughput array for DNA methylation analysis, extending the earlier 450k array by over 400 000 new sites. Previously, a method named eFORGE was developed to provide insights into cell type-specific and cell-composition effects for 450k data. Here, we present a significantly updated and improved version of eFORGE that can analyze both EPIC and 450k array data. New features include analysis of chromatin states, transcription factor motifs and DNase I footprints, providing tools for epigenome-wide association study interpretation and epigenome editing. AVAILABILITY AND IMPLEMENTATION: eFORGE v2.0 is implemented as a web tool available from https://eforge.altiusinstitute.org and https://eforge-tf.altiusinstitute.org/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.