Activity Of Regulatory Elements Research Articles

Histone H3 posttranslational modified enzymes defined neutrophil plasticity and their vulnerability to IL-10 in the course of the inflammation

BackgroundNeutrophils are a heterogeneous population capable of antimicrobial functions associated with pre-activation/activation and tissue regeneration. The specific polarisation of immune cells is mediated by the modification of ‘chromatin landscapes’, which enables differentiated access and activity of regulatory elements that guarantee their plasticity during inflammation No specific pattern within histone posttranslational modifications (PTMs) controlling this plasticity has been identified.MethodsUsing the in vitro model of inflammation, reflecting different states of neutrophils from resting, pre-activated cells to activated and reducing tissue regeneration, we have analysed 11 different histone posttranslational modifications (PTMs), PTM enzymes associated with remodelling neutrophil chromatin, and H3K4me3 ChIP-Seq Gene Ontology analysis focusing on the processes related to histone PTMs. These findings were verified by extrapolation to adequate clinical status, using neutrophils derived from the patients with sepsis (systemic septic inflammation with LPS-stimulated neutrophils), neuromyelitis optical spectrum disorders (aseptic inflammation with pre-activated neutrophils) and periodontitis (local self-limiting septic inflammation with IL-10-positive neutrophils).ResultsPhysiological activation of neutrophils comprises a pre-activation characterised by histone H3K27ac and H3K4me1, which position enhancers; direct LPS exposure is induced explicitly by H3K4me3 which marked Transcription Start Site (TSS) regions and low-level of H3K9me3, H3K79me2 and H3K27me3 which, in turn, marked repressed genes. Contrary to antimicrobial action, IL-10 positively induced levels of H3S10p and negatively H3K9me3, which characterised processes related to the activation of genes within heterochromatin mediated by CHD1 and H3K9me3 specific demethylase JMJD2A. IL-10 protects changes within histone PTMs induced by TNF or LPS that affected H3K4me3-specific methyltransferase SETD1A and MLL1. Neutrophils previously exposed to inflammatory factors become unvulnerable to IL-10 because previous LPS stimulation interrupts TSS regions marked by H3K4me3 of CHD1 and JMJD2A genes. Therefore, LPS-activated neutrophils are disabled to induce CHD1/JMJD2A enzymes by IL-10, making this process irreversible. Because transcription of JMJD2A and CHD1 also depends on TSS positioning by H3K4me3, neutrophils before LPS stimulation become insensitive to IL-10.ConclusionNeutrophils, once pre-activated by TNF or directly stimulated by LPS, become insensitive to the anti-inflammatory effects of IL-10, and vice versa; IL-10 protects neutrophils against these proinflammatory stimuli. This phenomenon is responsible for disturbing the natural process of resolving inflammation and tissue regeneration.Graphical

Integrative analysis of transcriptomic and epigenomic data reveals distinct patterns for developmental and housekeeping gene regulation

BackgroundRegulation of transcription is central to the emergence of new cell types during development, and it often involves activation of genes via proximal and distal regulatory regions. The activity of regulatory elements is determined by transcription factors (TFs) and epigenetic marks, but despite extensive mapping of such patterns, the extraction of regulatory principles remains challenging.ResultsHere we study differentially and similarly expressed genes along with their associated epigenomic profiles, chromatin accessibility and DNA methylation, during lineage specification at gastrulation in mice. Comparison of the three lineages allows us to identify genomic and epigenomic features that distinguish the two classes of genes.We show that differentially expressed genes are primarily regulated by distal elements, while similarly expressed genes are controlled by proximal housekeeping regulatory programs. Differentially expressed genes are relatively isolated within topologically associated domains, while similarly expressed genes tend to be located in gene clusters. Transcription of differentially expressed genes is associated with differentially open chromatin at distal elements including enhancers, while that of similarly expressed genes is associated with ubiquitously accessible chromatin at promoters.ConclusionBased on these associations of (linearly) distal genes’ transcription start sites (TSSs) and putative enhancers for developmental genes, our findings allow us to link putative enhancers to their target promoters and to infer lineage-specific repertoires of putative driver transcription factors, within which we define subgroups of pioneers and co-operators.

Omics-based construction of regulatory variants can be applied to help decipher pig liver-related traits

Genetic variants can influence complex traits by altering gene expression through changes to regulatory elements. However, the genetic variants that affect the activity of regulatory elements in pigs are largely unknown, and the extent to which these variants influence gene expression and contribute to the understanding of complex phenotypes remains unclear. Here, we annotate 90,991 high-quality regulatory elements using acetylation of histone H3 on lysine 27 (H3K27ac) ChIP-seq of 292 pig livers. Combined with genome resequencing and RNA-seq data, we identify 28,425 H3K27ac quantitative trait loci (acQTLs) and 12,250 expression quantitative trait loci (eQTLs). Through the allelic imbalance analysis, we validate two causative acQTL variants in independent datasets. We observe substantial sharing of genetic controls between gene expression and H3K27ac, particularly within promoters. We infer that 46% of H3K27ac exhibit a concomitant rather than causative relationship with gene expression. By integrating GWAS, eQTLs, acQTLs, and transcription factor binding prediction, we further demonstrate their application, through metabolites dulcitol, phosphatidylcholine (PC) (16:0/16:0) and published phenotypes, in identifying likely causal variants and genes, and discovering sub-threshold GWAS loci. We provide insight into the relationship between regulatory elements and gene expression, and the genetic foundation for dissecting the molecular mechanism of phenotypes.

Dimethylmonothioarsinic acid (DMMTAV) differentially modulates the expression of AHR-regulated cytochrome P450 1A enzymes in vivo and in vitro

Dimethylmonothioarsinic acid (DMMTAV), a pentavalent thio-arsenic derivative, has been found in bodily fluids and tissues including urine, liver, kidney homogenates, plasma, and red blood cells. Although DMMTAV is a minor metabolite in humans and animals, its substantial toxicity raises concerns about potential carcinogenic effects. This toxicity could be attributed to arsenicals' ability to regulate cytochrome P450 1 A (CYP1A) enzymes, pivotal in procarcinogen activation or detoxification. The current study investigates DMMTAV's impact on CYP1A1/2 expression, individually and in conjunction with its inducer, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). C57BL/6 mice were intraperitoneally injected with 6 mg/kg DMMTAV, alone or with 15 μg/kg TCDD, for 6 and 24 h. Similarly, Hepa-1c1c7 cells were exposed to DMMTAV (0.5, 1, and 2 μM) with or without 1 nM TCDD for 6 and 24 h. DMMTAV hindered TCDD-induced elevation of Cyp1a1 mRNA, both in vivo (at 6 h) and in vitro, associated with reduced CYP1A regulatory element activation. Interestingly, in C57BL/6 mice, DMMTAV boosted TCDD-induced CYP1A1/2 protein and activity, unlike Hepa-1c1c7 cells where it suppressed both. DMMTAV co-exposure increased TCDD-induced Cyp1a2 mRNA. While Cyp1a1 mRNA stability remained unchanged, DMMTAV negatively affected protein stability, indicated by shortened half-life. Baseline levels of CYP1A1/2 mRNA, protein, and catalytic activities showed no significant alterations in DMMTAV-treated C57BL/6 mice and Hepa-1c1c7 cells. Taken together, these findings indicate, for the first time, that DMMTAV differentially modulates the TCDD-mediated induction of AHR-regulated enzymes in both liver of C57BL/6 mice and murine Hepa-1c1c7 cells suggesting that thio-arsenic pentavalent metabolites are extremely reactive and could play a role in the toxicity of arsenic.

Analyzing histone ChIP-seq data with a bin-based probability of being signal.

Histone ChIP-seq is one of the primary methods for charting the cellular epigenomic landscape, the components of which play a critical regulatory role in gene expression. Analyzing the activity of regulatory elements across datasets and cell types can be challenging due to shifting peak positions and normalization artifacts resulting from, for example, differing read depths, ChIP efficiencies, and target sizes. Moreover, broad regions of enrichment seen in repressive histone marks often evade detection by commonly used peak callers. Here, we present a simple and versatile method for identifying enriched regions in ChIP-seq data that relies on estimating a gamma distribution fit to non-overlapping 5kB genomic bins to establish a global background. We use this distribution to assign a probability of being signal (PBS) between zero and one to each 5 kB bin. This approach, while lower in resolution than typical peak-calling methods, provides a straightforward way to identify enriched regions and compare enrichments among multiple datasets, by transforming the data to values that are universally normalized and can be readily visualized and integrated with downstream analysis methods. We demonstrate applications of PBS for both broad and narrow histone marks, and provide several illustrations of biological insights which can be gleaned by integrating PBS scores with downstream data types.

Beyond genome-wide association studies: Investigating the role of noncoding regulatory elements in primary sclerosing cholangitis.

Genome-wide association studies (GWAS) have identified 30 risk loci for primary sclerosing cholangitis (PSC). Variants within these loci are found predominantly in noncoding regions of DNA making their mechanisms of conferring risk hard to define. Epigenomic studies have shown noncoding variants broadly impact regulatory element activity. The possible association of noncoding PSC variants with regulatory element activity has not been studied. We aimed to (1) determine if the noncoding risk variants in PSC impact regulatory element function and (2) if so, assess the role these regulatory elements have in explaining the genetic risk for PSC. Available epigenomic datasets were integrated to build a comprehensive atlas of cell type-specific regulatory elements, emphasizing PSC-relevant cell types. RNA-seq and ATAC-seq were performed on peripheral CD4+ T cells from 10 PSC patients and 11 healthy controls. Computational techniques were used to (1) study the enrichment of PSC-risk variants within regulatory elements, (2) correlate risk genotype with differences in regulatory element activity, and (3) identify regulatory elements differentially active and genes differentially expressed between PSC patients and controls. Noncoding PSC-risk variants are strongly enriched within immune-specific enhancers, particularly ones involved in T-cell response to antigenic stimulation. In total, 250 genes and >10,000 regulatory elements were identified that are differentially active between patients and controls. Mechanistic effects are proposed for variants at 6 PSC-risk loci where genotype was linked with differential T-cell regulatory element activity. Regulatory elements are shown to play a key role in PSC pathophysiology.

KLF5 Promotes Tumor Progression and Parp Inhibitor Resistance in Ovarian Cancer.

One major characteristic of tumor cells is the aberrant activation of epigenetic regulatory elements, which remodelthe tumor transcriptome and ultimately promotecancer progression and drug resistance. However, the oncogenic functions and mechanisms of ovarian cancer (OC) remain elusive. Here, super-enhancer (SE) regulatory elements that are aberrantly activated in OC are identified and it is found that SEs drive the relative specific expression of the transcription factor KLF5 in OC patients and poly(ADP-ribose) polymerase inhibitor (PARPi)-resistant patients. KLF5 expression is associated with poor outcomes in OC patients and can drive tumor progression in vitro and in vivo. Mechanistically, KLF5 forms a transcriptional complex with EHF and ELF3 and binds to the promoter region of RAD51 to enhance its transcription, strengthening the homologous recombination repair (HRR) pathway. Notably, the combination of suberoylanilide hydroxamic acid (SAHA) and olaparib significantly inhibits tumor growth and metastasis of PARPi-resistant OC cells with high KLF5. In conclusion, it is discovered that SEs-driven KLF5 is a key regulatory factor in OC progression and PARPi resistance;and potential therapeutic strategies for OC patients with PARPi resistance and high KLF5 are identified.

Revealing metastatic castration-resistant prostate cancer master regulator through lncRNAs-centered regulatory network.

Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive form of cancer unresponsive to androgen deprivation therapy (ADT) that spreads quickly to other organs. Despite reduced androgen levels after ADT, mCRPC development and lethality continues to be conducted by the androgen receptor (AR) axis. The maintenance of AR signaling in mCRPC is a result of AR alterations, androgen intratumoral production, and the action of regulatory elements, such as noncoding RNAs (ncRNAs). ncRNAs are key elements in cancer signaling, acting in tumor growth, metabolic reprogramming, and tumor progression. In prostate cancer (PCa), the ncRNAs have been reported to be associated with AR expression, PCa proliferation, and castration resistance. In this study, we aimed to reconstruct the lncRNA-centered regulatory network of mCRPC and identify the lncRNAs which act as master regulators (MRs). We used publicly available RNA-sequencing to infer the regulatory network of lncRNAs in mCRPC. Five gene signatures were employed to conduct the master regulator analysis. Inferred MRs were then subjected to functional enrichment and symbolic regression modeling. The latter approach was applied to identify the lncRNAs with greater predictive capacity and potential as a biomarker in mCRPC. We identified 31 lncRNAs involved in cellular proliferation, tumor metabolism, and invasion-metastasis cascade. SNHG18 and HELLPAR were the highlights of our results. SNHG18 was downregulated in mCRPC and enriched to metastasis signatures. It accurately distinguished both mCRPC and primary CRPC from normal tissue and was associated with epithelial-mesenchymal transition (EMT) and cell-matrix adhesion pathways. HELLPAR consistently distinguished mCRPC from primary CRPC and normal tissue using only its expression. Our results contribute to understanding the regulatory behavior of lncRNAs in mCRPC and indicate SNHG18 and HELLPAR as master regulators and potential new diagnostic targets in this tumor.

Direct haplotype-resolved 5-base HiFi sequencing for genome-wide profiling of hypermethylation outliers in a rare disease cohort

Long-read HiFi genome sequencing allows for accurate detection and direct phasing of single nucleotide variants, indels, and structural variants. Recent algorithmic development enables simultaneous detection of CpG methylation for analysis of regulatory element activity directly in HiFi reads. We present a comprehensive haplotype resolved 5-base HiFi genome sequencing dataset from a rare disease cohort of 276 samples in 152 families to identify rare (~0.5%) hypermethylation events. We find that 80% of these events are allele-specific and predicted to cause loss of regulatory element activity. We demonstrate heritability of extreme hypermethylation including rare cis variants associated with short (~200 bp) and large hypermethylation events (>1 kb), respectively. We identify repeat expansions in proximal promoters predicting allelic gene silencing via hypermethylation and demonstrate allelic transcriptional events downstream. On average 30–40 rare hypermethylation tiles overlap rare disease genes per patient, providing indications for variation prioritization including a previously undiagnosed pathogenic allele in DIP2B causing global developmental delay. We propose that use of HiFi genome sequencing in unsolved rare disease cases will allow detection of unconventional diseases alleles due to loss of regulatory element activity.

Pioneer factor ASCL1 cooperates with the mSWI/SNF complex at distal regulatory elements to regulate human neural differentiation.

Pioneer transcription factors are thought to play pivotal roles in developmental processes by binding nucleosomal DNA to activate gene expression, though mechanisms through which pioneer transcription factors remodel chromatin remain unclear. Here, using single-cell transcriptomics, we show that endogenous expression of neurogenic transcription factor ASCL1, considered a classical pioneer factor, defines a transient population of progenitors in human neural differentiation. Testing ASCL1's pioneer function using a knockout model to define the unbound state, we found that endogenous expression of ASCL1 drives progenitor differentiation by cis-regulation both as a classical pioneer factor and as a nonpioneer remodeler, where ASCL1 binds permissive chromatin to induce chromatin conformation changes. ASCL1 interacts with BAF SWI/SNF chromatin remodeling complexes, primarily at targets where it acts as a nonpioneer factor, and we provide evidence for codependent DNA binding and remodeling at a subset of ASCL1 and SWI/SNF cotargets. Our findings provide new insights into ASCL1 function regulating activation of long-range regulatory elements in human neurogenesis and uncover a novel mechanism of its chromatin remodeling function codependent on partner ATPase activity.

Enhancer/gene relationships: Need for more reliable genome-wide reference sets.

Differences in cells' functions arise from differential activity of regulatory elements, including enhancers. Enhancers are cis-regulatory elements that cooperate with promoters through transcription factors to activate the expression of one or several genes by getting physically close to them in the 3D space of the nucleus. There is increasing evidence that genetic variants associated with common diseases are enriched in enhancers active in cell types relevant to these diseases. Identifying the enhancers associated with genes and conversely, the sets of genes activated by each enhancer (the so-called enhancer/gene or E/G relationships) across cell types, can help understanding the genetic mechanisms underlying human diseases. There are three broad approaches for the genome-wide identification of E/G relationships in a cell type: 1) genetic link methods or eQTL, 2) functional link methods based on 1D functional data such as open chromatin, histone mark or gene expression and 3) spatial link methods based on 3D data such as HiC. Since 1) and 3) are costly, the current strategy is to develop functional link methods and to use data from 1) and 3) as reference to evaluate them. However, there is still no consensus on the best functional link method to date, and method comparison remain seldom. Here, we compared the relative performances of three recent methods for the identification of enhancer-gene links, TargetFinder, Average-Rank, and the ABC model, using the three latest benchmarks from the field: a reference that combines 3D and eQTL data, called BENGI, and two genetic screening references, called CRiFF and CRiSPRi. Overall, none of the three methods performed best on the three references. CRiFF and CRISPRi reference sets are likely more reliable, but CRiFF is not genome-wide and CRiFF and CRISPRi are mostly available on the K562 cancer cell line. The BENGI reference set is genome-wide but likely contains many false positives. This study therefore calls for new reliable and genome-wide E/G reference data rather than new functional link E/G identification methods.

Targeting epigenetic regulation for cancer therapy using small molecule inhibitors.

Cancer cells display pervasive changes in DNA methylation, disrupted patterns of histone posttranslational modification, chromatin composition or organization and regulatory element activities that alter normal programs of gene expression. It is becoming increasingly clear that disturbances in the epigenome are hallmarks of cancer, which are targetable and represent attractive starting points for drug creation. Remarkable progress has been made in the past decades in discovering and developing epigenetic-based small molecule inhibitors. Recently, epigenetic-targeted agents in hematologic malignancies and solid tumors have been identified and these agents are either in current clinical trials or approved for treatment. However, epigenetic drug applications face many challenges, including low selectivity, poor bioavailability, instability and acquired drug resistance. New multidisciplinary approaches are being designed to overcome these limitations, e.g., applications of machine learning, drug repurposing, high throughput virtual screening technologies, to identify selective compounds with improved stability and better bioavailability. We provide an overview of the key proteins that mediate epigenetic regulation that encompass histone and DNA modifications and discuss effector proteins that affect the organization of chromatin structure and function as well as presently available inhibitors as potential drugs. Current anticancer small-molecule inhibitors targeting epigenetic modified enzymes that have been approved by therapeutic regulatory authorities across the world are highlighted. Many of these are in different stages of clinical evaluation. We also assess emerging strategies for combinatorial approaches of epigenetic drugs with immunotherapy, standard chemotherapy or other classes of agents and advances in the design of novel epigenetic therapies.

Mapping Transcription Regulation with Run-on and Sequencing Data Using the Web-Based tfTarget Gateway.

Run-on and sequencing assays like GRO-seq, PRO-seq, and ChRO-seq allow for joint profiling of transcription activity of transcriptional regulatory elements (TREs), i.e., promoters and active enhancers, and target genes. Variation in biological conditions, such as treated vs. control, results in changes in the activity of transcription factors (TFs), which induces concerted changes in TREs and target genes. By modeling the differences between two biological conditions, we developed the computational pipeline known as tfTarget that predicts a set of putative TREs and target genes responding to each TF under the biological condition of interest. In this chapter, we demonstrate the use of the new web-based tfTarget in mapping transcription regulation using run-on sequencing data.

Leveraging interindividual variability of regulatory activity for refining genetic regulation of gene expression in schizophrenia

Schizophrenia is a polygenic psychiatric disorder with limited understanding about the mechanistic changes in gene expression regulation. To elucidate on this, we integrate interindividual variability of regulatory activity (ChIP-sequencing for H3K27ac histone mark) with gene expression and genotype data captured from the prefrontal cortex of 272 cases and controls. By measuring interindividual correlation among proximal chromatin peaks, we show that regulatory element activity is structured into 10,936 and 10,376 cis-regulatory domains in cases and controls, respectively. The schizophrenia-specific cis-regulatory domains are enriched for fetal-specific (p = 0.0014, OR = 1.52) and depleted of adult-specific regulatory activity (p = 3.04 × 10−50, OR = 0.57) and are enriched for SCZ heritability (p = 0.001). By studying the interplay among genetic variants, gene expression, and cis-regulatory domains, we ascertain that changes in coordinated regulatory activity tag alterations in gene expression levels (p = 3.43 × 10−5, OR = 1.65), unveil case-specific QTL effects, and identify regulatory machinery changes for genes affecting synaptic function and dendritic spine morphology in schizophrenia. Altogether, we show that accounting for coordinated regulatory activity provides a novel mechanistic approach to reduce the search space for unveiling genetically perturbed regulation of gene expression in schizophrenia.

Development of dual reporter vector system for estimating translational activity of regulatory elements

BackgroundFor the needs of modern biotechnology, a quantitative approach to the control of regulatory elements at all stages of gene expression has long become indispensable. Such a control regime is impossible without a quantitative analysis of the role of each regulatory element or pattern used. Therefore, it seems important to modify and develop the accuracy, reproducibility, and availability of methods for quantifying the contribution of each regulatory code to the implementation of genetic information.ResultsA new vector system for transient expression in plants is described; this system is intended for quantitative analysis of the contribution of regulatory elements to transcription and translation efficiencies. The proposed vector comprises two expression cassettes carrying reporter genes (of the Clostridium thermocellum thermostable lichenase and E. coliβ-glucuronidase) under the control of different promoters. Herewith we also propose a new method for quantification of the effect of tested regulatory elements on expression, which relies on assessment of the enzyme activities of reporter proteins taking into account the transcription of their genes.ConclusionsIn our view, this approach makes it possible to precisely determine the amounts of reporter proteins and their transcripts at all stages of expression. The efficiency of the proposed system has been validated by the analysis of the roles of known translation enhancers at the stages of transcription and translation.

ChIP-Hub provides an integrative platform for exploring plant regulome

Plant genomes encode a complex and evolutionary diverse regulatory grammar that forms the basis for most life on earth. A wealth of regulome and epigenome data have been generated in various plant species, but no common, standardized resource is available so far for biologists. Here, we present ChIP-Hub, an integrative web-based platform in the ENCODE standards that bundles >10,000 publicly available datasets reanalyzed from >40 plant species, allowing visualization and meta-analysis. We manually curate the datasets through assessing ~540 original publications and comprehensively evaluate their data quality. As a proof of concept, we extensively survey the co-association of different regulators and construct a hierarchical regulatory network under a broad developmental context. Furthermore, we show how our annotation allows to investigate the dynamic activity of tissue-specific regulatory elements (promoters and enhancers) and their underlying sequence grammar. Finally, we analyze the function and conservation of tissue-specific promoters, enhancers and chromatin states using comparative genomics approaches. Taken together, the ChIP-Hub platform and the analysis results provide rich resources for deep exploration of plant ENCODE. ChIP-Hub is available at https://biobigdata.nju.edu.cn/ChIPHub/.

Emerging Functions of lncRNA Loci beyond the Transcript Itself.

Thousands of long noncoding RNAs (lncRNAs) are actively transcribed in mammalian genomes. This class of RNAs has important regulatory functions in a broad range of cellular processes and diseases. Numerous lncRNAs have been demonstrated to mediate gene regulation through RNA-based mechanisms. Simultaneously, non-functional lncRNA transcripts derived from the activity of lncRNA loci have been identified, which underpin the notion that a considerable fraction of lncRNA loci exert regulatory functions through mechanisms associated with the production or the activity of lncRNA loci beyond the synthesized transcripts. We particularly distinguish two main RNA-independent components associated with regulatory effects; the act of transcription and the activity of DNA regulatory elements. We describe the experimental approaches to distinguish and understand the functional mechanisms derived from lncRNA loci. These scenarios reveal emerging mechanisms important to understanding the lncRNA implications in genome biology.

Systematic Integration of Epigenomic Landscapes in Human and Mouse Blood Cells to Predict Activity and Targets of Regulatory Elements

Thousands of genome‐wide epigenetic (epigenomic) datasets determined in the past decade have generated maps of chromatin accessibility, histone modifications, and binding by transcription factors and structural proteins in a large number of cell types in humans and model species. Such maps have revealed many informative associations between groups of epigenetic features and different classes of cis‐regulatory elements (CREs), and they enable a prediction of the locations of candidate CREs (cCREs) in many genomes. The actuation (opening of chromatin) and epigenetic state (combination of features such as histone modifications) acquired at specific cCREs has been associated with specific gene activation. However, despite the large number and rich variety of available epigenomic datasets, it is difficult for researchers to effectively utilize all the data relevant to their projects. Furthermore, comprehensive rules and catalogs have not been established for which CREs regulate specific target genes and how. Integrative analysis can help meet these needs, and our VISION project provides a ValIdated Systematic IntegratiONof epigenomic data in hematopoiesis in human and mouse blood cells. After careful curation and normalization of epigenomic data from many sources, we systematically integrated these data to generate a comprehensive view of the regulatory landscape (epigenetic states) and predicted cCREs in differentiating hematopoietic cell types jointly in both mouse and human. Multiple machine learning approaches reveal target genes predicted to be regulated by each element in different cell types. These approaches include predicting the regulatory impact of each element on targets by regression models, finding linkages between distinctive clusters of elements and potential target genes from self‐organizing maps, and visual overlays of chromatin interaction maps. Directed mutation and expression analysis around selected genes supports the utility of the assignments. These catalogs of highly annotated regulatory elements are useful for many applications, including interpretation of the phenotypic impact of genetic variants in noncoding genomic regions. Resources from the VISION project are available at our website usevision.org.

Regional and Single Nucleotide Correction of Sequence Bias in Chromatin Accessibility Data

Chromatin accessibility assays directly measure which regions of DNA are actively regulated in the genome. Genomic chromatin accessibility data provide the gold standard of spatial and temporal resolution of regulatory landscapes in various cell types and conditions. Accessibility assays depend on enzymatic digestion of DNA and these enzymes are biased with respect to the sequences they recognize and cut. Sequence biases can lead to incorrect conclusions about the nature of the chromatin landscape within an experiment. Previous work from our group has shown that we can use observed k‐mer cut frequencies and k‐mer representation in the genome to correct the majority of this bias. However, these k‐mer scaling approaches did not effectively correct ATAC‐seq data, which assesses chromatin accessibility using the Tn5 transposase enzyme. Here, we find that the oligomeric state of Tn5 and wide sequence bias window precludes effective k‐mer scaling to account for Tn5 sequence bias. Tn5 sequence specificity is influenced by sequence content up to ten bases away from the Tn5 insertion site in both directions. In comparison, Benzonase, Cyanase, MNase, and DNase are primarily influenced by the sequence within 3 bases of the cleavage site. We could not effectively apply k‐mer scaling to ATAC‐seq data because the majority of insertion sites happen at unique 20‐mers in the genome and the method requires many genomic instances per k‐mer. To overcome this limitation, we applied an interpretable machine learning approach, prediction rules ensemble, to correct Tn5‐digested naked DNA. Application of a prediction rules ensemble effectively corrects local (single nucleotide resolution) sequence bias as well as sequence biases influenced by regional GC content. Correction of Tn5 sequence biases is important as the field continues to generate ATAC‐seq data at accelerating rates and use these data to accurately infer regulatory element activity.

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells.

Genome-wide association studies (GWASs) have uncovered hundreds of autoimmune disease-associated loci; however, the causal genetic variants within each locus are mostly unknown. Here, we perform high-throughput allele-specific reporter assays to prioritize disease-associated variants for five autoimmune diseases. By examining variants that both promote allele-specific reporter expression and are located in accessible chromatin, we identify 60 putatively causal variants that enrich for statistically fine-mapped variants by up to 57.8-fold. We introduced the risk allele of a prioritized variant (rs72928038) into a human T cell line and deleted the orthologous sequence in mice, both resulting in reduced BACH2 expression. Naive CD8 T cells from mice containing the deletion had reduced expression of genes that suppress activation and maintain stemness and, upon acute viral infection, displayed greater propensity to become effector T cells. Our results represent an example of an effective approach for prioritizing variants and studying their physiologically relevant effects.