Systematic mapping of functional enhancer-promoter connections with CRISPR interference

Deciphering enhancers of hearing loss genes for efficient and targeted gene therapy of hereditary deafness

Hereditary hearing loss accounts for about 60% of congenital deafness. Although adeno-associated virus (AAV)-mediated gene therapy shows substantial potential for treating genetic hearing impairments, there remain significant concerns regarding the specificity and safety of AAV vectors. The sophisticated nature of the cochlea further complicates the challenge of precisely targeting gene delivery. Here, we introduced an AAV-reporter-based in vivo transcriptional enhancer reconstruction (ARBITER) workflow, enabling efficient and reliable dissection of enhancers. With ARBITER, we successfully demonstrated that the conserved non-coding elements (CNEs) within the gene locus collaboratively regulate the expression of Slc26a5, which was further validated using knockout mouse models. We also assessed the potential of identified enhancers to treat hereditary hearing loss by conducting gene therapy in Slc26a5 mutant mice. Based on the original Slc26a5 enhancer with limited efficiency, we engineered a highly efficient and outer hair cell (OHC)-specific enhancer, B8, which successfully restored hearing of Slc26a5 knockout mice.

Single cell multiomics and 3D genome architecture reveal novel pathways of human heart failure

Heart failure is a leading cause of morbidity and mortality; yet gene regulatory mechanisms driving cell type-specific pathologic responses remain undefined. Here, we present the cell type-resolved transcriptomes, chromatin accessibility, histone modifications and chromatin organization of 36 non-failing and failing human hearts profiled from 776,479 cells spanning all cardiac chambers. Integrative analyses revealed dynamic changes in cell type composition, gene regulatory programs and chromatin organization, which expanded the annotation of cardiac cis-regulatory sequences by ten-fold and mapped cell type-specific enhancer-gene interactions. Cardiomyocytes and fibroblasts particularly exhibited complex disease-associated cellular states, gene regulatory programs and global chromatin reorganization. Mapping genetic association data onto cell type-specific regulatory programs revealed likely causal genetic contributors to heart failure. Together, these findings provide comprehensive, multimodal gene regulatory maps of the human heart in health and disease, offering a valuable framework for designing precise cell type-targeted therapies for treating heart failure.

ChromActivity: integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types

We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genomewide predictions of regulatory activity associated with each functional characterization dataset across many cell types based on available epigenomic data. It then for each cell type produces ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and ChromScore tracks of overall predicted regulatory activity. ChromActivity provides a resource for analyzing and interpreting the human regulatory genome across diverse cell types.

Selective Enhancer Dependencies in MYC-Intact and MYC-Rearranged Germinal Center B-cell Diffuse Large B-cell Lymphoma

SIGNIFICANCE

Aberrant MYC activity defines the most aggressive GCB-DLBCLs. We characterized a mechanism of MYC transcriptional activation via a native enhancer that is active in MYC-intact GCB-DLBCL, establishing fitness-sustaining cis- and trans-regulatory circuitry in GCB-DLBCL models that lack MYC enhancer-hijacking rearrangement. See related commentary by Mulet-Lazaro and Delwel, p. 149.

Bacterial pathogens hijack host cell peroxisomes for replication vacuole expansion and integrity

Pathogens manipulate host cell organelles to establish infection. There is extensive evidence of pathogen modulation of the endoplasmic reticulum, Golgi apparatus, mitochondria, endosomes, lysosomes, and nucleus. However, one organelle that has been largely overlooked in connection with bacterial pathogenesis is peroxisomes. Here, we demonstrate that Legionella actively recruits peroxisomes to its replication vacuole using a secreted bacterial effector protein. Defects in peroxisome metabolic function restrict expansion of the Legionella vacuole membrane and cause rupture of this compartment, inhibiting bacterial replication and leading to bacterial degradation. Similarly, peroxisome dysfunction causes Salmonella replication vacuole destabilization and reduced bacterial burden within host cells. Thus, these two intracellular bacterial pathogens exploit host cell peroxisomes to maintain their replication compartments, establishing a critical role for this organelle in disease.

Rewriting regulatory DNA to dissect and reprogram gene expression

Regulatory DNA provides a platform for transcription factor binding to encode cell-type-specific patterns of gene expression. However, the effects and programmability of regulatory DNA sequences remain difficult to map or predict. Here, we develop variant effects from flow-sorting experiments with CRISPR targeting screens (Variant-EFFECTS) to introduce hundreds of designed edits to endogenous regulatory DNA and quantify their effects on gene expression. We systematically dissect and reprogram 3 regulatory elements for 2 genes in 2 cell types. These data reveal endogenous binding sites with effects specific to genomic context, transcription factor motifs with cell-type-specific activities, and limitations of computational models for predicting the effect sizes of variants. We identify small edits that can tune gene expression over a large dynamic range, suggesting new possibilities for prime-editing-based therapeutics targeting regulatory DNA. Variant-EFFECTS provides a generalizable tool to dissect regulatory DNA and to identify genome editing reagents that tune gene expression in an endogenous context.

Cell type-specific enhancers regulate IL-22 expression in innate and adaptive lymphoid cells

IL-22, a signature cytokine of type 3 lymphoid cells, mediates epithelial homeostasis and protective pathogen responses in barrier tissues, while its deregulated expression drives chronic inflammation associated with colitis and psoriasis. Despite its therapeutic value, little is known about regulatory elements for IL-22 expression. We identify two conserved enhancers, E22-1 and E22-2, which differentially regulate Il22 in type 3 lymphoid subsets. These enhancers are required for steady-state expression of gut antimicrobial peptides, protection from C. rodentium infection, and development of IL-22-mediated psoriasis. E22-1 resembles many known enhancers, functioning in both Th-ILC counterparts. However, E22-2 is only required for IL-22 expression in ILC3s. Its ILC3 restriction relies on multiple Runx3 sites, combined with the lack of a functional RORγt motif, which is present in E22-1. Thus, although responding to similar stimuli, type 3 lymphoid cells use distinct cis-elements for IL-22 expression, with E22-2 likely serving as a homeostatic enhancer in barrier tissues.

Three-dimensional regulatory hubs support oncogenic programs in glioblastoma

Dysregulation of enhancer-promoter communication in the three-dimensional (3D) nucleus is increasingly recognized as a potential driver of oncogenic programs. Here, we profiled the 3D enhancer-promoter networks of patient-derived glioblastoma stem cells to identify central regulatory nodes. We focused on hyperconnected 3D hubs and demonstrated that hub-interacting genes exhibit high and coordinated expression at the single-cell level and are associated with oncogenic programs that distinguish glioblastoma from low-grade glioma. Epigenetic silencing of a recurrent hub-with an uncharacterized role in glioblastoma-was sufficient to cause downregulation of hub-connected genes, shifts in transcriptional states, and reduced clonogenicity. Integration of datasets across 16 cancers identified "universal" and cancer-type-specific 3D hubs that enrich for oncogenic programs and factors associated with worse prognosis. Genetic alterations could explain only a small fraction of hub hyperconnectivity and increased activity. Overall, our study provides strong support for the potential central role of 3D regulatory hubs in controlling oncogenic programs and properties.

Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation

Sequence-based machine-learning models trained on genomics data improve genetic variant interpretation by providing functional predictions describing their impact on the cis-regulatory code. However, current tools do not predict RNA-seq expression profiles because of modeling challenges. Here, we introduce Borzoi, a model that learns to predict cell-type-specific and tissue-specific RNA-seq coverage from DNA sequence. Using statistics derived from Borzoi's predicted coverage, we isolate and accurately score DNA variant effects across multiple layers of regulation, including transcription, splicing and polyadenylation. Evaluated on quantitative trait loci, Borzoi is competitive with and often outperforms state-of-the-art models trained on individual regulatory functions. By applying attribution methods to the derived statistics, we extract cis-regulatory motifs driving RNA expression and post-transcriptional regulation in normal tissues. The wide availability of RNA-seq data across species, conditions and assays profiling specific aspects of regulation emphasizes the potential of this approach to decipher the mapping from DNA sequence to regulatory function.

Optimizing in vitro Transcribed CRISPR-Cas9 Single-Guide RNA Libraries for Improved Uniformity and Affordability

We describe a scalable and cost-effective sgRNA synthesis workflow that reduces costs by over 70% through the use of large pools of microarray-derived oligos encoding unique sgRNA spacers. These subpool oligos are assembled into full-length dsDNA templates via Golden Gate Assembly before in vitro transcription with T7 RNA polymerase. RNA-seq analysis reveals severe biases in spacer representation, with some spacers being highly overrepresented while others are completely absent. Consistent with previous studies, we identify guanine-rich sequences within the first four nucleotides of the spacer, immediately downstream of the T7 promoter, as the primary driver of this bias. To address this issue, we introduced a guanine tetramer upstream of all spacers, which reduced bias by an average of 19% in sgRNA libraries containing 389 spacers. However, this modification also increased the presence of high-molecular-weight RNA species after transcription. We also tested two alternative bias-reduction strategies: compartmentalizing spacers within emulsions and optimizing DNA input and reaction volumes. Both methods independently reduced bias in 2,626-plex sgRNA libraries, though to a lesser extent than the guanine tetramer approach. These advancements enhance both the affordability and uniformity of sgRNA libraries, with broad implications for improving CRISPR-Cas9 screens and optimizing guide RNA design for other CRISPR and nuclease systems.

Simultaneous measurement of intrinsic promoter and enhancer potential reveals principles of functional duality and regulatory reciprocity

Growing evidence indicates that transcriptional regulatory elements can exert both promoter and enhancer activity; however, the relationship and determinants of this dual functionality remain poorly understood. We developed a massively parallel dual reporter assay that enables simultaneous assessment of the intrinsic promoter and enhancer potential exerted by the same sequence. Parallel quantification for thousands of elements reveals that canonical human promoters and enhancers can act as both promoters and enhancers under the same contexts, and that promoter activity may be necessary but not sufficient for enhancer function. We find that regulatory potential is intrinsic to element sequences, irrespective of downstream features typically associated with distinct element classes. Perturbations to element transcription factor binding motifs lead to disruptions in both activities, implicating a shared syntax for the two regulatory functions. Combinations of elements with different minimal promoters reveal reciprocal activity modulation between associated elements and a strong positive correlation between promoter and enhancer functions imply a bidirectional feedback loop used to maintain environments of high transcriptional activity. Finally, our results indicate that the magnitude and balance between promoter and enhancer functions are shaped by both intrinsic sequence properties and contextual regulatory influences, suggesting a degree of plasticity in regulatory action. Our approach provides a new lens for understanding fundamental principles of regulatory element biology.

Bidirectional epigenetic editing reveals hierarchies in gene regulation

CRISPR perturbation methods are limited in their ability to study non-coding elements and genetic interactions. In this study, we developed a system for bidirectional epigenetic editing, called CRISPRai, in which we apply activating (CRISPRa) and repressive (CRISPRi) perturbations to two loci simultaneously in the same cell. We developed CRISPRai Perturb-seq by coupling dual perturbation gRNA detection with single-cell RNA sequencing, enabling study of pooled perturbations in a mixed single-cell population. We applied this platform to study the genetic interaction between two hematopoietic lineage transcription factors, SPI1 and GATA1, and discovered novel characteristics of their co-regulation on downstream target genes, including differences in SPI1 and GATA1 occupancy at genes that are regulated through different modes. We also studied the regulatory landscape of IL2 (interleukin-2) in Jurkat T cells, primary T cells and chimeric antigen receptor (CAR) T cells and elucidated mechanisms of enhancer-mediated IL2 gene regulation. CRISPRai facilitates investigation of context-specific genetic interactions, provides new insights into gene regulation and will enable exploration of non-coding disease-associated variants.

Massively parallel characterization of transcriptional regulatory elements

The human genome contains millions of candidate cis-regulatory elements (cCREs) with cell-type-specific activities that shape both health and many disease states1. However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these cCREs. Here we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of more than 680,000 sequences, representing an extensive set of annotated cCREs among three cell types (HepG2, K562 and WTC11), and found that 41.7% of these sequences were active. By testing sequences in both orientations, we find promoters to have strand-orientation biases and their 200-nucleotide cores to function as non-cell-type-specific 'on switches' that provide similar expression levels to their associated gene. By contrast, enhancers have weaker orientation biases, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based models to predict cCRE function and variant effects with high accuracy, delineate regulatory motifs and model their combinatorial effects. Testing a lentiMPRA library encompassing 60,000 cCREs in all three cell types further identified factors that determine cell-type specificity. Collectively, our work provides an extensive catalogue of functional CREs in three widely used cell lines and showcases how large-scale functional measurements can be used to dissect regulatory grammar.

Engineered CRISPR-Cas12a for higher-order combinatorial chromatin perturbations

Multiplexed genetic perturbations are critical for testing functional interactions among coding or non-coding genetic elements. Compared to double-stranded DNA cutting, repressive chromatin formation using CRISPR interference (CRISPRi) avoids genotoxicity and is more effective for perturbing non-coding regulatory elements in pooled assays. However, current CRISPRi pooled screening approaches are limited to targeting one to three genomic sites per cell. We engineer an Acidaminococcus Cas12a (AsCas12a) variant, multiplexed transcriptional interference AsCas12a (multiAsCas12a), that incorporates R1226A, a mutation that stabilizes the ribonucleoprotein-DNA complex via DNA nicking. The multiAsCas12a-KRAB fusion improves CRISPRi activity over DNase-dead AsCas12a-KRAB fusions, often rescuing the activities of lentivirally delivered CRISPR RNAs (crRNA) that are inactive when used with the latter. multiAsCas12a-KRAB supports CRISPRi using 6-plex crRNA arrays in high-throughput pooled screens. Using multiAsCas12a-KRAB, we discover enhancer elements and dissect the combinatorial function of cis-regulatory elements in human cells. These results instantiate a group testing framework for efficiently surveying numerous combinations of chromatin perturbations for biological discovery and engineering.

Comprehensive dissection of cis-regulatory elements in a 2.8 Mb topologically associated domain in six human cancers

Cis-regulatory elements (CREs), such as enhancers and promoters, are fundamental regulators of gene expression and, across different cell types, the MYC locus utilizes a diverse regulatory architecture driven by multiple CREs. To better understand differences in CRE function, we perform pooled CRISPR inhibition (CRISPRi) screens to comprehensively probe the 2.8 Mb topologically-associated domain containing MYC in 6 human cancer cell lines with nucleotide resolution. We map 32 CREs where inhibition leads to changes in cell growth, including 8 that overlap previously identified enhancers. Targeting specific CREs decreases MYC expression by as much as 60%, and cell growth by as much as 50%. Using 3-D enhancer contact mapping, we find that these CREs almost always contact MYC but less than 10% of total MYC contacts impact growth when silenced, highlighting the utility of our approach to identify phenotypically-relevant CREs. We also detect an enrichment of lineage-specific transcription factors (TFs) at MYC CREs and, for some of these TFs, find a strong, tumor-specific correlation between TF and MYC expression not found in normal tissue. Taken together, these CREs represent systematically identified, functional regulatory regions and demonstrate how the same region of the human genome can give rise to complex, tissue-specific gene regulation.

Activation of the imprinted Prader-Willi syndrome locus by CRISPR-based epigenome editing

Epigenome editing with DNA-targeting technologies such as CRISPR-dCas9 can be used to dissect gene regulatory mechanisms and potentially treat associated disorders. For example, Prader-Willi syndrome (PWS) results from loss of paternally expressed imprinted genes on chromosome 15q11.2-q13.3, although the maternal allele is intact but epigenetically silenced. Using CRISPR repression and activation screens in human induced pluripotent stem cells (iPSCs), we identified genomic elements that control the expression of the PWS gene SNRPN from the paternal and maternal chromosomes. We showed that either targeted transcriptional activation or DNA demethylation can activate the silenced maternal SNRPN and downstream PWS transcripts. However, these two approaches function at unique regions, preferentially activating different transcript variants and involving distinct epigenetic reprogramming mechanisms. Remarkably, transient expression of the targeted demethylase leads to stable, long-term maternal SNRPN expression in PWS iPSCs. This work uncovers targeted epigenetic manipulations to reprogram a disease-associated imprinted locus and suggests possible therapeutic interventions.

Multi-locus CRISPRi targeting with a single truncated guide RNA

A critical goal in functional genomics is evaluating which non-coding elements contribute to gene expression, cellular function, and disease. Functional characterization remains a challenge due to the abundance and complexity of candidate elements. Here, we develop a CRISPRi-based approach for multi-locus screening of putative transcription factor binding sites with a single truncated guide. A truncated guide with hundreds of sequence match sites can reliably disrupt enhancer activity, which expands the targeting scope of CRISPRi while maintaining repressive efficacy. We screen over 13,000 possible CTCF binding sites with 24 guides at 10 nucleotides in spacer length. These truncated guides direct CRISPRi-mediated deposition of repressive H3K9me3 marks and disrupt transcription factor binding at most sequence match target sites. This approach can be a valuable screening step for testing transcription factor binding motifs or other repeated genomic sequences and is easily implemented with existing tools.

The application of CRISPR/Cas9-based genome-wide screening to disease research

High-throughput genetic screening serves as an indispensable approach for deciphering gene functions and the intricate relationships between phenotypes and genotypes. The CRISPR/Cas9 system, with its ability to precisely edit genomes on a large scale, has revolutionized the field by enabling the construction of comprehensive genomic libraries. This technology has become a cornerstone for genome-wide screenings in disease research. This review offers a comprehensive examination of how CRISPR/Cas9-based genetic screening has been leveraged to uncover genes that play a role in disease mechanisms, focusing on areas such as cancer development and viral replication processes. The insights presented in this review hold promise for the development of novel therapeutic strategies and precision medicine approaches.

Haplotype rather than single causal variants effects contribute to regulatory gene expression associations in human myeloid cells

Genome-wide association studies typically identify hundreds to thousands of loci, many of which harbor multiple independent peaks, each parsimoniously assumed to be due to the activity of a single causal variant. Fine-mapping of such variants has become a priority and since most associations are located within regulatory regions, it is also assumed that they colocalize with regulatory variants that influence the expression of nearby genes. Here we examine these assumptions by using a moderate throughput expression CROPseq protocol in which Cas9 nuclease is used to induce small insertions and deletions across the credible set of SNPs that may account for expression quantitative trait loci (eQTL) for genes associated with inflammatory bowel disease (IBD). Of the 4,384 SNPs targeted in 88 loci (an average of 50 per locus), 439 were significant and further examined for validation. From these, 98 significantly altered target gene expression in HL-60 myeloid cell line, 74 in induced macrophages from these HL-60 cells, and 78 in induced neutrophils for a total of 201 validated effects (46%), 43 of which were observed in at least two of the cell types. Considering the observed sensitivity and specificity of the controls, we estimate that there are at least 150 true positives per cell type, an average of almost 2.4 for each of the 64 eQTL for which putative causal variants have been fine-mapped. This implies that haplotype effects are likely to explain many of the associations. We also demonstrate that the same approach can be used to investigate the activity of very rare variants in regulatory regions for 89 genes, providing a rapid strategy for establishing clinical relevance of non-coding mutations.

Modular organization of enhancer network provides transcriptional robustness in mammalian development

Enhancer clusters, pivotal in mammalian development and diseases, can organize as enhancer networks to control cell identity and disease genes; however, the underlying mechanism remains largely unexplored. Here, we introduce eNet 2.0, a comprehensive tool for enhancer networks analysis during development and diseases based on single-cell chromatin accessibility data. eNet 2.0 extends our previous work eNet 1.0 by adding network topology, comparison and dynamics analyses to its network construction function. We reveal modularly organized enhancer networks, where inter-module interactions synergistically affect gene expression. Moreover, network alterations correlate with abnormal and dynamic gene expression in disease and development. eNet 2.0 is robust across diverse datasets. To facilitate application, we introduce eNetDB (https://enetdb.huanglabxmu.com), an enhancer network database leveraging extensive scATAC-seq (single-cell assay for transposase-accessible chromatin sequencing) datasets from human and mouse tissues. Together, our work provides a powerful computational tool and reveals that modularly organized enhancer networks contribute to gene expression robustness in mammalian development and diseases.

Enhancers and genome conformation provide complex transcriptional control of a herpesviral gene

Complex transcriptional control is a conserved feature of both eukaryotes and the viruses that infect them. Despite viral genomes being smaller and more gene dense than their hosts, we generally lack a sense of scope for the features governing the transcriptional output of individual viral genes. Even having a seemingly simple expression pattern does not imply that a gene's underlying regulation is straightforward. Here, we illustrate this by combining high-density functional genomics, expression profiling, and viral-specific chromosome conformation capture to define with unprecedented detail the transcriptional regulation of a single gene from Kaposi's sarcoma-associated herpesvirus (KSHV). We used as our model KSHV ORF68 - which has simple, early expression kinetics and is essential for viral genome packaging. We first identified seven cis-regulatory regions involved in ORF68 expression by densely tiling the ~154 kb KSHV genome with dCas9 fused to a transcriptional repressor domain (CRISPRi). A parallel Cas9 nuclease screen indicated that three of these regions act as promoters of genes that regulate ORF68. RNA expression profiling demonstrated that three more of these regions act by either repressing or enhancing other distal viral genes involved in ORF68 transcriptional regulation. Finally, we tracked how the 3D structure of the viral genome changes during its lifecycle, revealing that these enhancing regulatory elements are physically closer to their targets when active, and that disrupting some elements caused large-scale changes to the 3D genome. These data enable us to construct a complete model revealing that the mechanistic diversity of this essential regulatory circuit matches that of human genes.

Robust and inducible genome editing via an all-in-one prime editor in human pluripotent stem cells

Prime editing (PE) allows for precise genome editing in human pluripotent stem cells (hPSCs), such as introducing single nucleotide modifications, small insertions or deletions at a specific genomic locus. Here, we systematically compare a panel of prime editing conditions in hPSCs and generate a potent prime editor, "PE-Plus", through co-inhibition of mismatch repair and p53-mediated cellular stress responses. We further establish an inducible prime editing platform in hPSCs by incorporating the PE-Plus into a safe-harbor locus and demonstrated temporal control of precise editing in both hPSCs and differentiated cells. By evaluating disease-associated mutations, we show that this platform allows efficient creation of both monoallelic and biallelic disease-relevant mutations in hPSCs. In addition, this platform enables the efficient introduction of single or multiple edits in one step, demonstrating potential for multiplex editing. Our method presents an efficient and controllable multiplex prime editing tool in hPSCs and their differentiated progeny.

CEBPA repression by MECOM blocks differentiation to drive aggressive leukemias

Acute myeloid leukemias (AMLs) have an overall poor prognosis with many high-risk cases co-opting stem cell gene regulatory programs, yet the mechanisms through which this occurs remain poorly understood. Increased expression of the stem cell transcription factor, MECOM, underlies one key driver mechanism in largely incurable AMLs. How MECOM results in such aggressive AML phenotypes remains unknown. To address existing experimental limitations, we engineered and applied targeted protein degradation with functional genomic readouts to demonstrate that MECOM promotes malignant stem cell-like states by directly repressing pro-differentiation gene regulatory programs. Remarkably and unexpectedly, a single node in this network, a MECOM-bound cis-regulatory element located 42 kb downstream of the myeloid differentiation regulator CEBPA, is both necessary and sufficient for maintaining MECOM-driven leukemias. Importantly, targeted activation of this regulatory element promotes differentiation of these aggressive AMLs and reduces leukemia burden in vivo, suggesting a broadly applicable differentiation-based approach for improving therapy.

Three-dimensional regulatory hubs support oncogenic programs in glioblastoma

Dysregulation of enhancer-promoter communication in the context of the three-dimensional (3D) nucleus is increasingly recognized as a potential driver of oncogenic programs. Here, we profiled the 3D enhancer-promoter networks of primary patient-derived glioblastoma stem cells (GSCs) in comparison with neuronal stem cells (NSCs) to identify potential central nodes and vulnerabilities in the regulatory logic of this devastating cancer. Specifically, we focused on hyperconnected 3D regulatory hubs and demonstrated that hub-interacting genes exhibit high and coordinated expression at the single-cell level and strong association with oncogenic programs that distinguish IDH-wt glioblastoma patients from low-grade glioma. Epigenetic silencing of a recurrent 3D enhancer hub-with an uncharacterized role in glioblastoma-was sufficient to cause concordant downregulation of multiple hub-connected genes along with significant shifts in transcriptional states and reduced clonogenicity. By integrating published datasets from other cancer types, we also identified both universal and cancer type-specific 3D regulatory hubs which enrich for varying oncogenic programs and nominate specific factors associated with worse outcomes. Genetic alterations, such as focal duplications, could explain only a small fraction of the detected hyperconnected hubs and their increased activity. Overall, our study provides computational and experimental support for the potential central role of 3D regulatory hubs in controlling oncogenic programs and properties.

A genome-wide nucleosome-resolution map of promoter-centered interactions in human cells corroborates the enhancer-promoter looping model

The enhancer-promoter looping model, in which enhancers activate their target genes via physical contact, has long dominated the field of gene regulation. However, the ubiquity of this model has been questioned due to evidence of alternative mechanisms and the lack of its systematic validation, primarily owing to the absence of suitable experimental techniques. In this study, we present a new MNase-based proximity ligation method called MChIP-C, allowing for the measurement of protein-mediated chromatin interactions at single-nucleosome resolution on a genome-wide scale. By applying MChIP-C to study H3K4me3 promoter-centered interactions in K562 cells, we found that it had greatly improved resolution and sensitivity compared to restriction endonuclease-based C-methods. This allowed us to identify EP300 histone acetyltransferase and the SWI/SNF remodeling complex as potential candidates for establishing and/or maintaining enhancer-promoter interactions. Finally, leveraging data from published CRISPRi screens, we found that most functionally verified enhancers do physically interact with their cognate promoters, supporting the enhancer-promoter looping model.

Selective Enhancer Gain-of-Function Deregulates MYC Expression in Multiple Myeloma

MYC deregulation occurs in the majority of multiple myeloma cases and is associated with progression and worse prognosis. Enhanced MYC expression occurs in about 70% of patients with multiple myeloma, but it is known to be driven by translocation or amplification events in only ∼40% of myelomas. Here, we used CRISPR interference to uncover an epigenetic mechanism of MYC regulation whereby increased accessibility of a plasma cell-type-specific enhancer leads to increased MYC expression. This native enhancer activity was not associated with enhancer hijacking events but led to specific binding of cMAF, IRF4, and SPIB transcription factors that activated MYC expression in the absence of known genetic aberrations. In addition, focal amplification was another mechanism of activation of this enhancer in approximately 3.4% of patients with multiple myeloma. Together, these findings define an epigenetic mechanism of MYC deregulation in multiple myeloma beyond known translocations or amplifications and point to the importance of noncoding regulatory elements and their associated transcription factor networks as drivers of multiple myeloma progression. Significance: The discovery of a native developmental enhancer that sustains the expression of MYC in a subset of myelomas could help identify predictive biomarkers and therapeutic targets to improve the outcomes of patients with multiple myeloma.

Interrogation of the interplay between DNA N6-methyladenosine (6mA) and hypoxia-induced chromatin accessibility by a randomized empirical model (EnrichShuf)

N 6-Methyladenosine (6mA) is an epigenetic mark in eukaryotes regulating development, stress response and tumor progression. METTL4 has been reported as a 6mA methyltransferase induced by hypoxia. The detection and annotation of 6mA signals in mammalian cells have been hampered by the techniques and analytical methods developed so far. Here we developed a 6mA-ChIP-exo-5.1-seq to improve the sensitivity of detecting 6mAs in human cell lines. Furthermore, an EnrichShuf analysis tool for comprehensively comparing 6mA-ChIP-exo-5.1-seq, ATAC-seq, ChIP-seq and RNA-seq has been developed to annotate the functional relevance of 6mA in relation to chromatin accessibility and histone marks. Using a hypoxia-induced 6mA induction system as a model, we showed that hypoxic 6mA signals positively correlated with accessible chromatin regions. These 6mA signals correlate with their regulation by METTL4 under hypoxia, consistent with previous results. 6mAs also co-exist with H3K4me1, a histone mark for enhancers. Further analysis of enhancers using an ABC (active-by-contact) model shows that hypoxia-inducible factor-1α-induced H3K4me3 surrounds the 6mA/H3K4me1 site to augment active enhancers. These results suggest that correlation between 6mA and accessible chromatin regions plays a significant role in enhancer-promoter interactions during hypoxia-induced gene expression.

Noncoding variation near UBE2E2 orchestrates cardiometabolic pathophenotypes through polygenic effectors

Mechanisms underpinning signals from genome-wide association studies remain poorly understood, particularly for noncoding variation and for complex diseases such as type 2 diabetes mellitus (T2D) where pathogenic mechanisms in multiple different tissues may be disease driving. One approach is to study relevant endophenotypes, a strategy we applied to the UBE2E2 locus where noncoding single nucleotide variants (SNVs) are associated with both T2D and visceral adiposity (a pathologic endophenotype). We integrated CRISPR targeting of SNV-containing regions and unbiased CRISPR interference (CRISPRi) screening to establish candidate cis-regulatory regions, complemented by genetic loss of function in murine diet-induced obesity or ex vivo adipogenesis assays. Nomination of a single causal gene was complicated, however, because targeting of multiple genes near UBE2E2 attenuated adipogenesis in vitro; CRISPR excision of SNV-containing noncoding regions and a CRISPRi regulatory screen across the locus suggested concomitant regulation of UBE2E2, the more distant UBE2E1, and other neighborhood genes; and compound heterozygous loss of function of both Ube2e2 and Ube2e1 better replicated pathological adiposity and metabolic phenotypes compared with homozygous loss of either gene in isolation. This study advances a model whereby regulatory effects of noncoding variation not only extend beyond the nearest gene but may also drive complex diseases through polygenic regulatory effects.

A mathematical model clarifies the ABC Score formula used in enhancer-gene prediction

Enhancers are discrete DNA elements that regulate the expression of eukaryotic genes. They are important not only for their regulatory function, but also as loci that are frequently associated with disease traits. Despite their significance, our conceptual understanding of how enhancers work remains limited. CRISPR-interference methods have recently provided the means to systematically screen for enhancers in cell culture, from which a formula for predicting whether an enhancer regulates a gene, the Activity-by-Contact (ABC) Score, has emerged and has been widely adopted. While useful as a binary classifier, it is less effective at predicting the quantitative effect of an enhancer on gene expression. It is also unclear how the algebraic form of the ABC Score arises from the underlying molecular mechanisms and what assumptions are needed for it to hold. Here, we use the graph-theoretic linear framework, previously introduced to analyze gene regulation, to formulate the default model, a mathematical model of how multiple enhancers independently regulate a gene. We show that the algebraic form of the ABC Score arises from this model. However, the default model assumptions also imply that enhancers act additively on steady-state gene expression. This is known to be false for certain genes and we show how modifying the assumptions can accommodate this discrepancy. Overall, our approach lays a rigorous, biophysical foundation for future studies of enhancer-gene regulation.

[Targeted epigenome engineering]

Cellular differentiation and homeostasis rely on complex mechanisms to control gene expression, enabling the different cell lineages of an organism to establish and then "memorize" different epigenetic states. The processes that control gene expression are centered on chromatin, a complex of DNA, histone proteins and RNA, whose structure is finely regulated. Targeted epigenomic engineering tools make it possible to interfere with and study these processes, revealing the logic of epigenetic memory mechanisms. This article reviews the main classes of targeted epigenome modification tools and illustrates how they can be used to better understand and modify the epigenome of cells, paving the way for potentially revolutionary therapeutic prospects.

Downregulating human leucocyte antigens on mesenchymal stromal cells by epigenetically repressing a β2-microglobulin super-enhancer

Immune rejection caused by mismatches in human leucocyte antigens (HLAs) remains a major obstacle to the success of allogeneic cell therapies. Current strategies for the generation of 'universal' immune-compatible cells, particularly the editing of HLA class I (HLA-I) genes or the modulation of proteins that inhibit natural killer cells, often result in genomic instability or cellular cytotoxicity. Here we show that a β2-microglobulin super-enhancer (B2M-SE) that is responsive to interferon-γ is a critical regulator of the expression of HLA-I on mesenchymal stromal cells (MSCs). Targeted epigenetic repression of B2M-SE in MSCs reduced the surface expression of HLA-I below the threshold required to activate allogenic T cells while maintaining levels sufficient to evade cytotoxicity mediated by natural killer cells. In a humanized mouse model, the epigenetically edited MSCs demonstrated improved survival by evading the immune system, allowing them to exert enhanced therapeutic effects on LPS-induced acute lung injury. Targeted epigenetic repression of B2M-SE may facilitate the development of off-the-shelf cell sources for allogeneic cell therapy.

Mapping cis- and trans-regulatory target genes of human-specific deletions

Deletion of functional sequence is predicted to represent a fundamental mechanism of molecular evolution1,2. Comparative genetic studies of primates2,3 have identified thousands of human-specific deletions (hDels), and the cis-regulatory potential of short (≤31 base pairs) hDels has been assessed using reporter assays4. However, how structural variant-sized (≥50 base pairs) hDels influence molecular and cellular processes in their native genomic contexts remains unexplored. Here, we design genome-scale libraries of single-guide RNAs targeting 7.2 megabases of sequence in 6,358 hDels and present a systematic CRISPR interference (CRISPRi) screening approach to identify hDels that modify cellular proliferation in chimpanzee pluripotent stem cells. By intersecting hDels with chromatin state features and performing single-cell CRISPRi (Perturb-seq) to identify their cis- and trans-regulatory target genes, we discovered 20 hDels controlling gene expression. We highlight two hDels, hDel_2247 and hDel_585, with tissue-specific activity in the brain. Our findings reveal a molecular and cellular role for sequences lost in the human lineage and establish a framework for functionally interrogating human-specific genetic variants.

Analysis of single-cell CRISPR perturbations indicates that enhancers predominantly act multiplicatively

A single gene may have multiple enhancers, but how they work in concert to regulate transcription is poorly understood. To analyze enhancer interactions throughout the genome, we developed a generalized linear modeling framework, GLiMMIRS, for interrogating enhancer effects from single-cell CRISPR experiments. We applied GLiMMIRS to a published dataset and tested for interactions between 46,166 enhancer pairs and corresponding genes, including 264 "high-confidence" enhancer pairs. We found that enhancer effects combine multiplicatively but with limited evidence for further interactions. Only 31 enhancer pairs exhibited significant interactions (false discovery rate <0.1), none of which came from the high-confidence set, and 20 were driven by outlier expression values. Additional analyses of a second CRISPR dataset and in silico enhancer perturbations with Enformer both support a multiplicative model of enhancer effects without interactions. Altogether, our results indicate that enhancer interactions are uncommon or have small effects that are difficult to detect.

Interpreting cis-regulatory interactions from large-scale deep neural networks

The rise of large-scale, sequence-based deep neural networks (DNNs) for predicting gene expression has introduced challenges in their evaluation and interpretation. Current evaluations align DNN predictions with orthogonal experimental data, providing insights into generalization but offering limited insights into their decision-making process. Existing model explainability tools focus mainly on motif analysis, which becomes complex when interpreting longer sequences. Here we present cis-regulatory element model explanations (CREME), an in silico perturbation toolkit that interprets the rules of gene regulation learned by a genomic DNN. Applying CREME to Enformer, a state-of-the-art DNN, we identify cis-regulatory elements that enhance or silence gene expression and characterize their complex interactions. CREME can provide interpretations across multiple scales of genomic organization, from cis-regulatory elements to fine-mapped functional sequence elements within them, offering high-resolution insights into the regulatory architecture of the genome. CREME provides a powerful toolkit for translating the predictions of genomic DNNs into mechanistic insights of gene regulation.

Development of compact transcriptional effectors using high-throughput measurements in diverse contexts

Transcriptional effectors are protein domains known to activate or repress gene expression; however, a systematic understanding of which effector domains regulate transcription across genomic, cell type and DNA-binding domain (DBD) contexts is lacking. Here we develop dCas9-mediated high-throughput recruitment (HT-recruit), a pooled screening method for quantifying effector function at endogenous target genes and test effector function for a library containing 5,092 nuclear protein Pfam domains across varied contexts. We also map context dependencies of effectors drawn from unannotated protein regions using a larger library tiling chromatin regulators and transcription factors. We find that many effectors depend on target and DBD contexts, such as HLH domains that can act as either activators or repressors. To enable efficient perturbations, we select context-robust domains, including ZNF705 KRAB, that improve CRISPRi tools to silence promoters and enhancers. We engineer a compact human activator called NFZ, by combining NCOA3, FOXO3 and ZNF473 domains, which enables efficient CRISPRa with better viral delivery and inducible control of chimeric antigen receptor T cells.

Targeting the 3D genome by anthracyclines for chemotherapeutic effects

The chromatins are folded into three-dimensional (3D) structures inside cells, which coordinates the regulation of gene transcription by the non-coding regulatory elements. Aberrant chromatin 3D folding has been shown in many diseases, such as acute myeloid leukemia (AML), and may contribute to tumorigenesis. The anthracycline topoisomerase II inhibitors can induce histone eviction and DNA damage. We performed genome-wide high-resolution mapping of the chemotherapeutic effects of various clinically used anthracycline drugs. ATAC-seq was used to profile the histone eviction effects of different anthracyclines. TOP2A ChIP-seq was used to profile the potential DNA damage regions. Integrated analyses show that different anthracyclines have distinct target selectivity on epigenomic regions, based on their respective ATAC-seq and ChIP-seq profiles. We identified the underlying molecular mechanism that unique anthracycline variants selectively target chromatin looping anchors via disrupting CTCF binding, suggesting an additional potential therapeutic effect on the 3D genome. We further performed Hi-C experiments, and data from K562 cells treated with the selective anthracycline drugs indicate that the 3D chromatin organization is disrupted. Furthermore, AML patients receiving anthracycline drugs showed altered chromatin structures around potential looping anchors, which linked to distinct clinical outcomes. Our data indicate that anthracyclines are potent and selective epigenomic targeting drugs and can target the 3D genome for anticancer therapy, which could be used for personalized medicine to treat tumors with aberrant 3D chromatin structures.

Machine-guided design of cell-type-targeting cis-regulatory elements

Cis-regulatory elements (CREs) control gene expression, orchestrating tissue identity, developmental timing and stimulus responses, which collectively define the thousands of unique cell types in the body1-3. While there is great potential for strategically incorporating CREs in therapeutic or biotechnology applications that require tissue specificity, there is no guarantee that an optimal CRE for these intended purposes has arisen naturally. Here we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell-type specificity. We take advantage of innovations in deep neural network modelling of CRE activity across three cell types, efficient in silico optimization and massively parallel reporter assays to design and empirically test thousands of CREs4-8. Through large-scale in vitro validation, we show that synthetic sequences are more effective at driving cell-type-specific expression in three cell lines compared with natural sequences from the human genome and achieve specificity in analogous tissues when tested in vivo. Synthetic sequences exhibit distinct motif vocabulary associated with activity in the on-target cell type and a simultaneous reduction in the activity of off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs from massively parallel reporter assay models and demonstrate the required literacy to write fit-for-purpose regulatory code.

Integrative identification of non-coding regulatory regions driving metastatic prostate cancer

Large-scale sequencing efforts have been undertaken to understand the mutational landscape of the coding genome. However, the vast majority of variants occur within non-coding genomic regions. We designed an integrative computational and experimental framework to identify recurrently mutated non-coding regulatory regions that drive tumor progression. Applying this framework to sequencing data from a large prostate cancer patient cohort revealed a large set of candidate drivers. We used (1) in silico analyses, (2) massively parallel reporter assays, and (3) in vivo CRISPR interference screens to systematically validate metastatic castration-resistant prostate cancer (mCRPC) drivers. One identified enhancer region, GH22I030351, acts on a bidirectional promoter to simultaneously modulate expression of the U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. SF3A1 and CCDC157 promote tumor growth in vivo. We nominated a number of transcription factors, notably SOX6, to regulate expression of SF3A1 and CCDC157. Our integrative approach enables the systematic detection of non-coding regulatory regions that drive human cancers.

Tailoring a CRISPR/Cas-based Epigenome Editor for Programmable Chromatin Acylation and Decreased Cytotoxicity

Engineering histone acylation states can inform mechanistic epigenetics and catalyze therapeutic epigenome editing opportunities. Here, we developed engineered lysine acyltransferases that enable the programmable deposition of acetylation and longer-chain acylations. We show that targeting an engineered lysine crotonyltransferase results in weak levels of endogenous enhancer activation yet retains potency when targeted to promoters. We further identify a single mutation within the catalytic core of human p300 that preserves enzymatic activity while substantially reducing cytotoxicity, enabling improved viral delivery. We leveraged these capabilities to perform single-cell CRISPR activation screening and map enhancers to the genes they regulate in situ. We also discover acylation-specific interactions and find that recruitment of p300, regardless of catalytic activity, to prime editing sites can improve editing efficiency. These new programmable epigenome editing tools and insights expand our ability to understand the mechanistic role of lysine acylation in epigenetic and cellular processes and perform functional genomic screens.

Extrachromosomal DNA Associates with Nuclear Condensates and Reorganizes Chromatin Structures to Enhance Oncogenic Transcription

Extrachromosomal, circular DNA (ecDNA) is a prevalent oncogenic alteration in cancer genomes, often associated with aggressive tumor behavior and poor patient outcome. While previous studies proposed a chromatin-based mobile enhancer model for ecDNA-driven oncogenesis, its precise mechanism and impact remains unclear across diverse cancer types. Our study, utilizing advanced multi-omics profiling, epigenetic editing, and imaging approaches in three cancer models, reveals that ecDNA hubs are an integrated part of nuclear condensates and exhibit cancer-type specific chromatin connectivity. Epigenetic silencing of the ecDNA-specific regulatory modules or chemically disrupting liquid-liquid phase separation breaks down ecDNA hubs, displaces MED1 co-activator binding, inhibits oncogenic transcription, and promotes cell death. These findings substantiate the trans -activator function of ecDNA and underscore a structural mechanism driving oncogenesis. This refined understanding expands our views of oncogene regulation and opens potential avenues for novel therapeutic strategies in cancer treatment.

Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements

CRISPR-based gene activation (CRISPRa) is a strategy for upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis-regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to a library of 493 gRNAs targeting candidate cis-regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically upregulating intended target genes and no other neighboring genes within 1 Mb, including gRNAs yielding upregulation of six autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes in neurons. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans-acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate genes in a cell type-specific manner.

TGFβ primes alveolar-like macrophages to induce type I IFN following TLR2 activation

Alveolar macrophages (AMs) are key mediators of lung function and are potential targets for therapies during respiratory infections. TGFβ is an important regulator of AM differentiation and maintenance, but how TGFβ directly modulates the innate immune responses of AMs remains unclear. This shortcoming prevents effective targeting of AMs to improve lung function in health and disease. Here we leveraged an optimized ex vivo AM model system, fetal-liver derived alveolar-like macrophages (FLAMs), to dissect the role of TGFβ in AMs. Using transcriptional analysis, we first globally defined how TGFβ regulates gene expression of resting FLAMs. We found that TGFβ maintains the baseline metabolic state of AMs by driving lipid metabolism through oxidative phosphorylation and restricting inflammation. To better understand inflammatory regulation in FLAMs, we next directly tested how TGFβ alters the response to TLR2 agonists. While both TGFβ (+) and TGFβ (-) FLAMs robustly responded to TLR2 agonists, we found an unexpected activation of type I interferon (IFN) responses in FLAMs and primary AMs in a TGFβ-dependent manner. Surprisingly, mitochondrial antiviral signaling protein and the interferon regulator factors 3 and 7 were required for IFN production by TLR2 agonists. Together, these data suggest that TGFβ modulates AM metabolic networks and innate immune signaling cascades to control inflammatory pathways in AMs.

Deciphering the impact of genomic variation on function

Our genomes influence nearly every aspect of human biology-from molecular and cellular functions to phenotypes in health and disease. Studying the differences in DNA sequence between individuals (genomic variation) could reveal previously unknown mechanisms of human biology, uncover the basis of genetic predispositions to diseases, and guide the development of new diagnostic tools and therapeutic agents. Yet, understanding how genomic variation alters genome function to influence phenotype has proved challenging. To unlock these insights, we need a systematic and comprehensive catalogue of genome function and the molecular and cellular effects of genomic variants. Towards this goal, the Impact of Genomic Variation on Function (IGVF) Consortium will combine approaches in single-cell mapping, genomic perturbations and predictive modelling to investigate the relationships among genomic variation, genome function and phenotypes. IGVF will create maps across hundreds of cell types and states describing how coding variants alter protein activity, how noncoding variants change the regulation of gene expression, and how such effects connect through gene-regulatory and protein-interaction networks. These experimental data, computational predictions and accompanying standards and pipelines will be integrated into an open resource that will catalyse community efforts to explore how our genomes influence biology and disease across populations.

Culture Wars: Empirically Determining the Best Approach for Plasmid Library Amplification

DNA libraries are critical components of many biological assays. These libraries are often kept in plasmids that are amplified in E. coli to generate sufficient material for an experiment. Library uniformity is critical for ensuring that every element in the library is tested similarly and is thought to be influenced by the culture approach used during library amplification. We tested five commonly used culturing methods for their ability to uniformly amplify plasmid libraries: liquid, semisolid agar, cell spreader-spread plates with high or low colony density, and bead-spread plates. Each approach was evaluated with two library types: a random 80-mer library, representing high complexity and low coverage of similar sequence lengths, and a human TF ORF library, representing low complexity and high coverage of diverse sequence lengths. We found that no method was better than liquid culture, which produced relatively uniform libraries regardless of library type. However, when libraries were transformed with high coverage, the culturing method had minimal impact on uniformity or amplification bias. Plating libraries was the worst approach by almost every measure for both library types and, counterintuitively, produced the strongest biases against long sequence representation. Semisolid agar amplified most elements of the library uniformly but also included outliers with orders of magnitude higher abundance. For amplifying DNA libraries, liquid culture, the simplest method, appears to be best.

Super enhancer acquisition drives expression of oncogenic PPP1R15B that regulates protein homeostasis in multiple myeloma

Multiple myeloma is a hematological malignancy arising from immunoglobulin-secreting plasma cells. It remains poorly understood how chromatin rewiring of regulatory elements contributes to tumorigenesis and therapy resistance in myeloma. Here we generate a high-resolution contact map of myeloma-associated super-enhancers by integrating H3K27ac ChIP-seq and HiChIP from myeloma cell lines, patient-derived myeloma cells and normal plasma cells. Our comprehensive transcriptomic and phenomic analyses prioritize candidate genes with biological and clinical implications in myeloma. We show that myeloma cells frequently acquire SE that transcriptionally activate an oncogene PPP1R15B, which encodes a regulatory subunit of the holophosphatase complex that dephosphorylates translation initiation factor eIF2α. Epigenetic silencing or knockdown of PPP1R15B activates pro-apoptotic eIF2α-ATF4-CHOP pathway, while inhibiting protein synthesis and immunoglobulin production. Pharmacological inhibition of PPP1R15B using Raphin1 potentiates the anti-myeloma effect of bortezomib. Our study reveals that myeloma cells are vulnerable to perturbation of PPP1R15B-dependent protein homeostasis, highlighting a promising therapeutic strategy.

Harnessing the evolving CRISPR/Cas9 for precision oncology

The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas9 system, a groundbreaking innovation in genetic engineering, has revolutionized our approach to surmounting complex diseases, culminating in CASGEVY™ approved for sickle cell anemia. Derived from a microbial immune defense mechanism, CRISPR/Cas9, characterized as precision, maneuverability and universality in gene editing, has been harnessed as a versatile tool for precisely manipulating DNA in mammals. In the process of applying it to practice, the consecutive exploitation of novel orthologs and variants never ceases. It's conducive to understanding the essentialities of diseases, particularly cancer, which is crucial for diagnosis, prevention, and treatment. CRISPR/Cas9 is used not only to investigate tumorous genes functioning but also to model disparate cancers, providing valuable insights into tumor biology, resistance, and immune evasion. Upon cancer therapy, CRISPR/Cas9 is instrumental in developing individual and precise cancer therapies that can selectively activate or deactivate genes within tumor cells, aiming to cripple tumor growth and invasion and sensitize cancer cells to treatments. Furthermore, it facilitates the development of innovative treatments, enhancing the targeting efficiency of reprogrammed immune cells, exemplified by advancements in CAR-T regimen. Beyond therapy, it is a potent tool for screening susceptible genes, offering the possibility of intervening before the tumor initiative or progresses. However, despite its vast potential, the application of CRISPR/Cas9 in cancer research and therapy is accompanied by significant efficacy, efficiency, technical, and safety considerations. Escalating technology innovations are warranted to address these issues. The CRISPR/Cas9 system is revolutionizing cancer research and treatment, opening up new avenues for advancements in our understanding and management of cancers. The integration of this evolving technology into clinical practice promises a new era of precision oncology, with targeted, personalized, and potentially curative therapies for cancer patients.

EPInformer: a scalable deep learning framework for gene expression prediction by integrating promoter-enhancer sequences with multimodal epigenomic data

Transcriptional regulation, critical for cellular differentiation and adaptation to environmental changes, involves coordinated interactions among DNA sequences, regulatory proteins, and chromatin architecture. Despite extensive data from consortia like ENCODE, understanding the dynamics of cis-regulatory elements (CREs) in gene expression remains challenging. Deep learning is a powerful tool for learning gene expression and epigenomic signals from DNA sequences, exhibiting superior performance compared to conventional machine learning approaches. However, even the most advanced deep learning-based methods may fall short in capturing the regulatory effects of distal elements such as enhancers, limiting their predictive accuracy. In addition, these methods may require significant resources to train or to adapt to newly generated data. To address these challenges, we present EPInformer, a scalable deep-learning framework for predicting gene expression by integrating promoter-enhancer interactions with their sequences, epigenomic signals, and chromatin contacts. Our model outperforms existing gene expression prediction models in rigorous cross-chromosome validation, accurately recapitulates enhancer-gene interactions validated by CRISPR perturbation experiments, and identifies crucial transcription factor motifs within regulatory sequences. EPInformer is available as open-source software at https://github.com/pinellolab/EPInformer.

Epigenome editing technologies for discovery and medicine

Epigenome editing has rapidly evolved in recent years, with diverse applications that include elucidating gene regulation mechanisms, annotating coding and noncoding genome functions and programming cell state and lineage specification. Importantly, given the ubiquitous role of epigenetics in complex phenotypes, epigenome editing has unique potential to impact a broad spectrum of diseases. By leveraging powerful DNA-targeting technologies, such as CRISPR, epigenome editing exploits the heritable and reversible mechanisms of epigenetics to alter gene expression without introducing DNA breaks, inducing DNA damage or relying on DNA repair pathways.

SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model

Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method, to identify long-range enhancer-promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells. SnapHiC-G achieved high sensitivity in identifying long-range enhancer-promoter interactions. Moreover, SnapHiC-G can identify putative target genes for noncoding genome-wide association study (GWAS) variants, and the genetic heritability of neuropsychiatric diseases is enriched for single-nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types.

Cohesin-mediated 3D contacts tune enhancer-promoter regulation

Enhancers are key drivers of gene regulation thought to act via 3D physical interactions with the promoters of their target genes. However, genome-wide depletions of architectural proteins such as cohesin result in only limited changes in gene expression, despite a loss of contact domains and loops. Consequently, the role of cohesin and 3D contacts in enhancer function remains debated. Here, we developed CRISPRi of regulatory elements upon degron operation (CRUDO), a novel approach to measure how changes in contact frequency impact enhancer effects on target genes by perturbing enhancers with CRISPRi and measuring gene expression in the presence or absence of cohesin. We systematically perturbed all 1,039 candidate enhancers near five cohesin-dependent genes and identified 34 enhancer-gene regulatory interactions. Of 26 regulatory interactions with sufficient statistical power to evaluate cohesin dependence, 18 show cohesin-dependent effects. A decrease in enhancer-promoter contact frequency upon removal of cohesin is frequently accompanied by a decrease in the regulatory effect of the enhancer on gene expression, consistent with a contact-based model for enhancer function. However, changes in contact frequency and regulatory effects on gene expression vary as a function of distance, with distal enhancers (e.g., >50Kb) experiencing much larger changes than proximal ones (e.g., <50Kb). Because most enhancers are located close to their target genes, these observations can explain how only a small subset of genes - those with strong distal enhancers - are sensitive to cohesin. Together, our results illuminate how 3D contacts, influenced by both cohesin and genomic distance, tune enhancer effects on gene expression.