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Variation in the non-coding genome represents an understudied mechanism of disease and it remains challenging to predict if single nucleotide variants, small insertions and deletions, or structural variants in non-coding genomic regions will be detrimental. Our approach using complementary RNA-seq and targeted long-read DNA sequencing can prioritize identification of non-coding variants that lead to disease via alteration of gene splicing or expression. We have identified a patient with primary ciliary dyskinesia with a pathogenic coding variant on one allele of the SPAG1 gene, while the second allele appears normal by whole exome sequencing despite an autosomal recessive inheritance pattern. RNA sequencing revealed reduced SPAG1 transcript levels and exclusive allele specific expression of the known pathogenic allele, suggesting the presence of a non-coding variant on the second allele that impacts transcription. Targeted long-read DNA sequencing identified a heterozygous 3 kilobase deletion of the 5' untranslated region of SPAG1, overlapping the promoter and first non-coding exon. This non-coding deletion was missed by whole exome sequencing and gene-specific deletion/duplication analysis, highlighting the importance of investigating the non-coding genome in patients with "missing" disease-causing variation. This paradigm demonstrates the utility of both RNA and long-read DNA sequencing in identifying pathogenic non-coding variants in patients with unexplained genetic disease., (© 2024 Wiley Periodicals LLC.)

Motivation: Allele-specific expression (ASE) analyses aim to detect imbalanced expression of maternal versus paternal copies of an autosomal gene. Such allelic imbalance can result from a variety of cis-acting causes, including disruptive mutations within one copy of a gene that impact the stability of transcripts, as well as regulatory variants outside the gene that impact transcription initiation. Current methods for ASE estimation suffer from a number of shortcomings, such as relying on only one variant within a gene, assuming perfect phasing information across multiple variants within a gene, or failing to account for alignment biases and possible genotyping errors., Results: We developed BEASTIE, a Bayesian hierarchical model designed for precise ASE quantification at the gene level, based on given genotypes and RNA-Seq data. BEASTIE addresses the complexities of allelic mapping bias, genotyping error, and phasing errors by incorporating empirical phasing error rates derived from Genome-in-a-Bottle individual NA12878. BEASTIE surpasses existing methods in accuracy, especially in scenarios with high phasing errors. This improvement is critical for identifying rare genetic variants often obscured by such errors. Through rigorous validation on simulated data and application to real data from the 1000 Genomes Project, we establish the robustness of BEASTIE. These findings underscore the value of BEASTIE in revealing patterns of ASE across gene sets and pathways., Availability and Implementation: The software is freely available from https://github.com/x811zou/BEASTIE . BEASTIE is available as Python source code and as a Docker image., Supplementary Information: Additional information is available online.

Interactions between multiple genes or cis-regulatory elements (CREs) underlie a wide range of biological processes in both health and disease. High-throughput screens using dCas9 fused to epigenome editing domains have allowed researchers to assess the impact of activation or repression of both coding and non-coding genomic regions on a phenotype of interest, but assessment of genetic interactions between those elements has been limited to pairs. Here, we combine a hyper-efficient version of Lachnospiraceae bacterium dCas12a (dHyperLbCas12a) with RNA Polymerase II expression of long CRISPR RNA (crRNA) arrays to enable efficient highly-multiplexed epigenome editing. We demonstrate that this system is compatible with several activation and repression domains, including the P300 histone acetyltransferase domain and SIN3A interacting domain (SID). We also show that the dCas12a platform can perform simultaneous activation and repression using a single crRNA array via co-expression of multiple dCas12a orthologues. Lastly, demonstrate that the dCas12a system is highly effective for high-throughput screens. We use dHyperLbCas12a-KRAB and a ~19,000-member barcoded library of crRNA arrays containing six crRNAs each to dissect the independent and combinatorial contributions of CREs to the dose-dependent control of gene expression at a glucocorticoid-responsive locus. The tools and methods introduced here create new possibilities for highly multiplexed control of gene expression in a wide variety of biological systems.

Acquired resistance remains a major challenge for therapies targeting oncogene activated pathways. KRAS is the most frequently mutated oncogene in human cancers, yet strategies targeting its downstream signaling kinases have failed to produce durable treatment responses. Here, we developed multiple models of acquired resistance to dual-mechanism ERK/MAPK inhibitors across KRAS-mutant pancreatic, colorectal, and lung cancers, and then probed the long-term events enabling survival against this class of drugs. These studies revealed that resistance emerges secondary to large-scale transcriptional adaptations that are diverse and cell line-specific. Transcriptional reprogramming extends beyond the well-established early response, and instead represents a dynamic, evolved process that is refined to attain a stably resistant phenotype. Mechanistic and translational studies reveal that resistance to dual-mechanism ERK/MAPK inhibition is broadly susceptible to manipulation of the epigenetic machinery, and that Mediator kinase, in particular, can be co-targeted at a bottleneck point to prevent diverse, cell line-specific resistance programs., (© 2024. The Author(s).)

The ENCODE Consortium's efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE-gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome., (© 2024. The Author(s).)

Clinical response to adoptive T cell therapies is associated with the transcriptional and epigenetic state of the cell product. Thus, discovery of regulators of T cell gene networks and their corresponding phenotypes has potential to improve T cell therapies. Here we developed pooled, epigenetic CRISPR screening approaches to systematically profile the effects of activating or repressing 120 transcriptional and epigenetic regulators on human CD8 + T cell state. We found that BATF3 overexpression promoted specific features of memory T cells and attenuated gene programs associated with cytotoxicity, regulatory T cell function, and exhaustion. Upon chronic antigen stimulation, BATF3 overexpression countered phenotypic and epigenetic signatures of T cell exhaustion. Moreover, BATF3 enhanced the potency of CAR T cells in both in vitro and in vivo tumor models and programmed a transcriptional profile that correlates with positive clinical response to adoptive T cell therapy. Finally, we performed CRISPR knockout screens that defined cofactors and downstream mediators of the BATF3 gene network., (© 2023. The Author(s).)

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) caused by CNS-infiltrating leukocytes, including T H 17 cells that are critical mediators of disease pathogenesis. Although targeting leukocyte trafficking is effective in treating autoimmunity, there are currently no therapeutic interventions that specifically block encephalitogenic T H 17 cell migration. Here, we report integrin α3 as a T H 17 cell-selective determinant of pathogenicity in experimental autoimmune encephalomyelitis. CNS-infiltrating T H 17 cells express high integrin α3, and its deletion in CD4 + T cells or Il17a fate-mapped cells attenuated disease severity. Mechanistically, integrin α3 enhanced the immunological synapse formation to promote the polarization and proliferation of T H 17 cells. Moreover, the transmigration of T H 17 cells into the CNS was dependent on integrin α3, and integrin α3 deficiency enhanced the retention of CD4 + T cells in the perivascular space of the blood-brain barrier. Integrin α3-dependent interactions continuously maintain T H 17 cell identity and effector function. The requirement of integrin α3 in T H 17 cell pathogenicity suggests integrin α3 as a therapeutic target for MS treatment.

Evidence has long suggested that epidermal growth factor receptor (EGFR) may play a prominent role in triple-negative breast cancer (TNBC) pathogenesis, but clinical trials of EGFR inhibitors have yielded disappointing results. Using a candidate drug screen, we identified that inhibition of cyclin-dependent kinases 12 and 13 (CDK12/13) dramatically sensitizes diverse models of TNBC to EGFR blockade. This combination therapy drives cell death through the 4E-BP1-dependent suppression of the translation and translation-linked turnover of driver oncoproteins, including MYC. A genome-wide CRISPR/Cas9 screen identified the CCR4-NOT complex as a major determinant of sensitivity to the combination therapy whose loss renders 4E-BP1 unresponsive to drug-induced dephosphorylation, thereby rescuing MYC translational suppression and promoting MYC stability. The central roles of CCR4-NOT and 4E-BP1 in response to the combination therapy were further underscored by the observation of CNOT1 loss and rescue of 4E-BP1 phosphorylation in TNBC cells that naturally evolved therapy resistance. Thus, pharmacological inhibition of CDK12/13 reveals a long-proposed EGFR dependence in TNBC that functions through the cooperative regulation of translation-coupled oncoprotein stability.

Searches for the genetic underpinnings of uniquely human traits have focused on human-specific divergence in conserved genomic regions, which reflects adaptive modifications of existing functional elements. However, the study of conserved regions excludes functional elements that descended from previously neutral regions. Here, we demonstrate that the fastest-evolved regions of the human genome, which we term "human ancestor quickly evolved regions" (HAQERs), rapidly diverged in an episodic burst of directional positive selection prior to the human-Neanderthal split, before transitioning to constraint within hominins. HAQERs are enriched for bivalent chromatin states, particularly in gastrointestinal and neurodevelopmental tissues, and genetic variants linked to neurodevelopmental disease. We developed a multiplex, single-cell in vivo enhancer assay to discover that rapid sequence divergence in HAQERs generated hominin-unique enhancers in the developing cerebral cortex. We propose that a lack of pleiotropic constraints and elevated mutation rates poised HAQERs for rapid adaptation and subsequent susceptibility to disease., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

The cellular fate after infection with human coronaviruses (HCoVs) is typically death. Previous data suggest, however, that the transcriptional state of an individual cell may sometimes allow additional outcomes of infection. Here, to probe the range of interactions a permissive cell type can have with a HCoV, we perform a CRISPR activation screen with HCoV-229E. The screen identified the transcription factor ZBTB7A, which strongly promotes cell survival after infection. Rather than suppressing viral infection, ZBTB7A upregulation allows the virus to induce a persistent infection and homeostatic state with the cell. We also find that control of oxidative stress is a primary driver of cellular survival during HCoV-229E infection. These data illustrate that, in addition to the nature of the infecting virus and the type of cell that it encounters, the cellular gene expression profile prior to infection can affect the eventual fate., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Over a thousand different transcription factors (TFs) bind with varying occupancy across the human genome. Chromatin immunoprecipitation (ChIP) can assay occupancy genome-wide, but only one TF at a time, limiting our ability to comprehensively observe the TF occupancy landscape, let alone quantify how it changes across conditions. We developed TF occupancy profiler (TOP), a Bayesian hierarchical regression framework, to profile genome-wide quantitative occupancy of numerous TFs using data from a single chromatin accessibility experiment (DNase- or ATAC-seq). TOP is supervised, and its hierarchical structure allows it to predict the occupancy of any sequence-specific TF, even those never assayed with ChIP. We used TOP to profile the quantitative occupancy of hundreds of sequence-specific TFs at sites throughout the genome and examined how their occupancies changed in multiple contexts: in approximately 200 human cell types, through 12 h of exposure to different hormones, and across the genetic backgrounds of 70 individuals. TOP enables cost-effective exploration of quantitative changes in the landscape of TF binding., (© 2022 Luo et al.; Published by Cold Spring Harbor Laboratory Press.)

Background: Mechanisms governing the diversity of CFTR gene expression throughout the body are complex. Multiple intronic and distal regulatory elements are responsible for regulating differential CFTR expression across tissues., Methods: Drawing on published data, 18 high-priority genomic regions were identified and interrogated for CFTR-enhancer function using CRISPR/dCas9-based epigenome editing tools. Each region was evaluated by dCas9 p300 and dCas9 KRAB for its ability to enhance or repress CFTR expression, respectively., Results: Multiple genomic regions were tested for enhancer activity using CRISPR/dCas9 epigenome editing. dCas9 p300 mediates a significant increase in CFTR mRNA levels when targeted to the promoter and a region 44 kb upstream of the transcriptional start site in a CFTR-low expressing cell line. Multiple gRNAs targeting the promoter induced a robust increase in CFTR protein levels. In contrast, dCas9 KRAB -mediated repression is much more robust with 10 of the 18 evaluated genomic regions inducing CFTR protein knockdown. To evaluate the therapeutic efficacy of modulating CFTR gene regulation, dCas9 p300 was used to induce elevated levels of CFTR from the endogenous locus in ΔF508/ΔF508 human bronchial epithelial cells. Ussing chamber studies demonstrated a synergistic increase in ion transport in response to CRISPR-induced expression of ΔF508 CFTR mRNA along with VX809 treatment., Conclusions: CRISPR/dCas9-based epigenome-editing provides a previously unexplored tool for interrogating CFTR enhancer function. Here, we demonstrate that therapeutic interventions that increase the expression of CFTR may improve the efficacy of CFTR modulators. A better understanding CFTR regulatory mechanisms could uncover novel therapeutic interventions for the development of cystic fibrosis therapies., Competing Interests: Declaration of cc competing interests A.M.K and T.E.R are named inventors on patent applications related to this work. The work was funded by Element Genomics and UCB Biosciences. N.D. and I.M. are current employees of Element Genomics. L.D. is a current employee of UCB Biosciences., (Copyright © 2021. Published by Elsevier B.V.)

Despite widespread clinical genetic testing, many individuals with suspected genetic conditions lack a precise diagnosis, limiting their opportunity to take advantage of state-of-the-art treatments. In some cases, testing reveals difficult-to-evaluate structural differences, candidate variants that do not fully explain the phenotype, single pathogenic variants in recessive disorders, or no variants in genes of interest. Thus, there is a need for better tools to identify a precise genetic diagnosis in individuals when conventional testing approaches have been exhausted. We performed targeted long-read sequencing (T-LRS) using adaptive sampling on the Oxford Nanopore platform on 40 individuals, 10 of whom lacked a complete molecular diagnosis. We computationally targeted up to 151 Mbp of sequence per individual and searched for pathogenic substitutions, structural variants, and methylation differences using a single data source. We detected all genomic aberrations-including single-nucleotide variants, copy number changes, repeat expansions, and methylation differences-identified by prior clinical testing. In 8/8 individuals with complex structural rearrangements, T-LRS enabled more precise resolution of the mutation, leading to changes in clinical management in one case. In ten individuals with suspected Mendelian conditions lacking a precise genetic diagnosis, T-LRS identified pathogenic or likely pathogenic variants in six and variants of uncertain significance in two others. T-LRS accurately identifies pathogenic structural variants, resolves complex rearrangements, and identifies Mendelian variants not detected by other technologies. T-LRS represents an efficient and cost-effective strategy to evaluate high-priority genes and regions or complex clinical testing results., (Copyright © 2021 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

CRISPR-Cas9 technologies have dramatically increased the ease of targeting DNA sequences in the genomes of living systems. The fusion of chromatin-modifying domains to nuclease-deactivated Cas9 (dCas9) has enabled targeted epigenome editing in both cultured cells and animal models. However, delivering large dCas9 fusion proteins to target cells and tissues is an obstacle to the widespread adoption of these tools for in vivo studies. Here, we describe the generation and characterization of two conditional transgenic mouse lines for epigenome editing, Rosa26:LSL-dCas9-p300 for gene activation and Rosa26:LSL-dCas9-KRAB for gene repression. By targeting the guide RNAs to transcriptional start sites or distal enhancer elements, we demonstrate regulation of target genes and corresponding changes to epigenetic states and downstream phenotypes in the brain and liver in vivo, and in T cells and fibroblasts ex vivo. These mouse lines are convenient and valuable tools for facile, temporally controlled, and tissue-restricted epigenome editing and manipulation of gene expression in vivo., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

High-throughput reporter assays such as self-transcribing active regulatory region sequencing (STARR-seq) have made it possible to measure regulatory element activity across the entire human genome at once. The resulting data, however, present substantial analytical challenges. Here, we identify technical biases that explain most of the variance in STARR-seq data. We then develop a statistical model to correct those biases and to improve detection of regulatory elements. This approach substantially improves precision and recall over current methods, improves detection of both activating and repressive regulatory elements, and controls for false discoveries despite strong local correlations in signal., (© 2021 Kim et al.; Published by Cold Spring Harbor Laboratory Press.)

The AP-1 transcription factor (TF) dimer contributes to many biological processes and environmental responses. AP-1 can be composed of many interchangeable subunits. Unambiguously determining the binding locations of these subunits in the human genome is challenging because of variable antibody specificity and affinity. Here, we definitively establish the genome-wide binding patterns of five AP-1 subunits by using CRISPR to introduce a common antibody tag on each subunit. We find limited evidence for strong dimerization preferences between subunits at steady state and find that, under a stimulus, dimerization patterns reflect changes in the transcriptome. Further, our analysis suggests that canonical AP-1 motifs indiscriminately recruit all AP-1 subunits to genomic sites, which we term AP-1 hotspots. We find that AP-1 hotspots are predictive of cell type-specific gene expression and of genomic responses to glucocorticoid signaling (more so than super-enhancers) and are significantly enriched in disease-associated genetic variants. Together, these results support a model where promiscuous binding of many AP-1 subunits to the same genomic location play a key role in regulating cell type-specific gene expression and environmental responses., (© 2021 Seo et al.; Published by Cold Spring Harbor Laboratory Press.)

Gene regulatory network inference is essential to uncover complex relationships among gene pathways and inform downstream experiments, ultimately enabling regulatory network re-engineering. Network inference from transcriptional time-series data requires accurate, interpretable, and efficient determination of causal relationships among thousands of genes. Here, we develop Bootstrap Elastic net regression from Time Series (BETS), a statistical framework based on Granger causality for the recovery of a directed gene network from transcriptional time-series data. BETS uses elastic net regression and stability selection from bootstrapped samples to infer causal relationships among genes. BETS is highly parallelized, enabling efficient analysis of large transcriptional data sets. We show competitive accuracy on a community benchmark, the DREAM4 100-gene network inference challenge, where BETS is one of the fastest among methods of similar performance and additionally infers whether causal effects are activating or inhibitory. We apply BETS to transcriptional time-series data of differentially-expressed genes from A549 cells exposed to glucocorticoids over a period of 12 hours. We identify a network of 2768 genes and 31,945 directed edges (FDR ≤ 0.2). We validate inferred causal network edges using two external data sources: Overexpression experiments on the same glucocorticoid system, and genetic variants associated with inferred edges in primary lung tissue in the Genotype-Tissue Expression (GTEx) v6 project. BETS is available as an open source software package at https://github.com/lujonathanh/BETS., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: BEE is on the SAB for Freenome, Celsius Therapeutics, and Creyon Bio; is a consultant for Freenome; and was an employee of Genomics plc during a year of absence from Princeton University.

While a genetic component of preterm birth (PTB) has long been recognized and recently mapped by genome-wide association studies (GWASs), the molecular determinants underlying PTB remain elusive. This stems in part from an incomplete availability of functional genomic annotations in human cell types relevant to pregnancy and PTB. We generated transcriptome (RNA-seq), epigenome (ChIP-seq of H3K27ac, H3K4me1, and H3K4me3 histone modifications), open chromatin (ATAC-seq), and chromatin interaction (promoter capture Hi-C) annotations of cultured primary decidua-derived mesenchymal stromal/stem cells and in vitro differentiated decidual stromal cells and developed a computational framework to integrate these functional annotations with results from a GWAS of gestational duration in 56,384 women. Using these resources, we uncovered additional loci associated with gestational duration and target genes of associated loci. Our strategy illustrates how functional annotations in pregnancy-relevant cell types aid in the experimental follow-up of GWAS for PTB and, likely, other pregnancy-related conditions., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Technologies to reprogram cell-type specification have revolutionized the fields of regenerative medicine and disease modeling. Currently, the selection of fate-determining factors for cell reprogramming applications is typically a laborious and low-throughput process. Therefore, we use high-throughput pooled CRISPR activation (CRISPRa) screens to systematically map human neuronal cell fate regulators. We utilize deactivated Cas9 (dCas9)-based gene activation to target 1,496 putative transcription factors (TFs) in the human genome. Using a reporter of neuronal commitment, we profile the neurogenic activity of these factors in human pluripotent stem cells (PSCs), leading to a curated set of pro-neuronal factors. Activation of pairs of TFs reveals neuronal cofactors, including E2F7, RUNX3, and LHX8, that improve conversion efficiency, subtype specificity, and maturation of neuronal cell types. Finally, using multiplexed gene regulation with orthogonal CRISPR systems, we demonstrate improved neuronal differentiation with concurrent activation and repression of target genes, underscoring the power of CRISPR-based gene regulation for programming complex cellular phenotypes., Competing Interests: Declaration of Interests J.B.B., T.S.K., T.E.R., and C.A.G. are named inventors on patent applications related to genome engineering technologies. T.S.K., T.E.R., and C.A.G. are co-founders of Element Genomics. C.A.G. is a co-founder of Tune Therapeutics and Locus Biosciences and is an advisor to Tune Therapeutics, Sarepta Therapeutics, Levo Therapeutics, and Iveric Bio. J.B.B. and T.S.K. are co-founders and employees of Tune Therapeutics., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Premature preterm rupture of membranes (PPROM), rupture of fetal membranes before 37 weeks of gestation, is the leading identifiable cause of spontaneous preterm births. Often there is no obvious cause that is identified in a patient who presents with PPROM. Identifying the upstream molecular events that lead to fetal membrane weakening presents potentially actionable mechanisms which could lead to the identification of at-risk patients and to the development of new therapeutic interventions. Functional genomic studies have transformed understanding of the role of gene regulation in diverse cells and tissues involved health and disease. Here, we review the results of those studies in the context of fetal membranes. We will highlight relevant results from major coordinated functional genomics efforts and from targeted studies focused on individual cell or tissue models. Studies comparing gene expression and DNA methylation between healthy and pathological fetal membranes have found differential regulation between labor and quiescent tissue as well as in preterm births, preeclampsia, and recurrent pregnancy loss. Whole genome and exome sequencing studies have identified common and rare fetal variants associated with preterm births. However, few fetal membrane tissue studies have modeled the response to stimuli relevant to pregnancy. Fetal membranes are readily adaptable to cell culture and relevant cellular phenotypes are readily observable. For these reasons, this is now an unrealized opportunity for genomic studies isolating the effect of cell signaling cascades and mapping the fetal membrane responses that lead to PPROM and other pregnancy complications., (Copyright © 2020 Cunningham, Feng, Allen and Reddy.)

Motivation: High-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA., Results: We describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters., Availability and Implementation: The software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

CCR6- group 3 innate lymphoid cells (ILC3s) are mediators of intestinal immunity and barrier function that possess the capacity to acquire type 1 effector features and fully convert into ILC1s. The molecular mechanisms governing such plasticity are undefined. Here, we identified c-Maf as an essential regulator of ILC3 homeostasis and plasticity that limits physiological ILC1 conversion. Phenotypic analysis of effector status in Maf-deficient CCR6- ILC3s, coupled with evaluation of global changes in transcriptome, chromatin accessibility, and transcription factor motif enrichment, revealed that c-Maf enforces ILC3 identity. c-Maf promoted ILC3 accessibility and supported RORγt activity and expression of type 3 effector genes. Conversely, c-Maf antagonized type 1 programming, largely through restraint of T-bet expression and function. Mapping of the dynamic changes in chromatin landscape accompanying CCR6- ILC3 development and ILC1 conversion solidified c-Maf as a gatekeeper of type 1 regulatory transformation and a controller of ILC3 fate., (© 2019 Parker et al.)

Class 2 CRISPR-Cas systems, such as Cas9 and Cas12, have been widely used to target DNA sequences in eukaryotic genomes. However, class 1 CRISPR-Cas systems, which represent about 90% of all CRISPR systems in nature, remain largely unexplored for genome engineering applications. Here, we show that class 1 CRISPR-Cas systems can be expressed in mammalian cells and used for DNA targeting and transcriptional control. We repurpose type I variants of class 1 CRISPR-Cas systems from Escherichia coli and Listeria monocytogenes, which target DNA via a multi-component RNA-guided complex termed Cascade. We validate Cascade expression, complex formation and nuclear localization in human cells, and demonstrate programmable CRISPR RNA (crRNA)-mediated targeting of specific loci in the human genome. By tethering activation and repression domains to Cascade, we modulate the expression of targeted endogenous genes in human cells. This study demonstrates the use of Cascade as a CRISPR-based technology for targeted eukaryotic gene regulation, highlighting class 1 CRISPR-Cas systems for further exploration.

Environmental stimuli commonly act via changes in gene regulation. Human-genome-scale assays to measure such responses are indirect or require knowledge of the transcription factors (TFs) involved. Here, we present the use of human genome-wide high-throughput reporter assays to measure environmentally-responsive regulatory element activity. We focus on responses to glucocorticoids (GCs), an important class of pharmaceuticals and a paradigmatic genomic response model. We assay GC-responsive regulatory activity across >10 8 unique DNA fragments, covering the human genome at >50×. Those assays directly detected thousands of GC-responsive regulatory elements genome-wide. We then validate those findings with measurements of transcription factor occupancy, histone modifications, chromatin accessibility, and gene expression. We also detect allele-specific environmental responses. Notably, the assays did not require knowledge of GC response mechanisms. Thus, this technology can be used to agnostically quantify genomic responses for which the underlying mechanism remains unknown.

Changes in DNA methylation are involved in development, disease, and the response to environmental conditions. However, not all regulatory elements are functionally methylation-dependent (MD). Here, we report a method, mSTARR-seq, that assesses the causal effects of DNA methylation on regulatory activity at hundreds of thousands of fragments (millions of CpG sites) simultaneously. Using mSTARR-seq, we identify thousands of MD regulatory elements in the human genome. MD activity is partially predictable using sequence and chromatin state information, and distinct transcription factors are associated with higher activity in unmethylated versus methylated DNA. Further, pioneer TFs linked to higher activity in the methylated state appear to drive demethylation of experimentally methylated sites. MD regulatory elements also predict methylation-gene expression relationships across individuals, where they are 1.6x enriched among sites with strong negative correlations. mSTARR-seq thus provides a map of MD regulatory activity in the human genome and facilitates interpretation of differential methylation studies., Competing Interests: AL, CV, RJ, CD, LB, TR, JT No competing interests declared, (© 2018, Lea et al.)

Motivation: Genetic variation that disrupts gene function by altering gene splicing between individuals can substantially influence traits and disease. In those cases, accurately predicting the effects of genetic variation on splicing can be highly valuable for investigating the mechanisms underlying those traits and diseases. While methods have been developed to generate high quality computational predictions of gene structures in reference genomes, the same methods perform poorly when used to predict the potentially deleterious effects of genetic changes that alter gene splicing between individuals. Underlying that discrepancy in predictive ability are the common assumptions by reference gene finding algorithms that genes are conserved, well-formed and produce functional proteins., Results: We describe a probabilistic approach for predicting recent changes to gene structure that may or may not conserve function. The model is applicable to both coding and non-coding genes, and can be trained on existing gene annotations without requiring curated examples of aberrant splicing. We apply this model to the problem of predicting altered splicing patterns in the genomes of individual humans, and we demonstrate that performing gene-structure prediction without relying on conserved coding features is feasible. The model predicts an unexpected abundance of variants that create de novo splice sites, an observation supported by both simulations and empirical data from RNA-seq experiments. While these de novo splice variants are commonly misinterpreted by other tools as coding or non-coding variants of little or no effect, we find that in some cases they can have large effects on splicing activity and protein products and we propose that they may commonly act as cryptic factors in disease., Availability and Implementation: The software is available from geneprediction.org/SGRF., Supplementary Information: Supplementary information is available at Bioinformatics online.

Glucocorticoids are potent steroid hormones that regulate immunity and metabolism by activating the transcription factor (TF) activity of glucocorticoid receptor (GR). Previous models have proposed that DNA binding motifs and sites of chromatin accessibility predetermine GR binding and activity. However, there are vast excesses of both features relative to the number of GR binding sites. Thus, these features alone are unlikely to account for the specificity of GR binding and activity. To identify genomic and epigenetic contributions to GR binding specificity and the downstream changes resultant from GR binding, we performed hundreds of genome-wide measurements of TF binding, epigenetic state, and gene expression across a 12-h time course of glucocorticoid exposure. We found that glucocorticoid treatment induces GR to bind to nearly all pre-established enhancers within minutes. However, GR binds to only a small fraction of the set of accessible sites that lack enhancer marks. Once GR is bound to enhancers, a combination of enhancer motif composition and interactions between enhancers then determines the strength and persistence of GR binding, which consequently correlates with dramatic shifts in enhancer activation. Over the course of several hours, highly coordinated changes in TF binding and histone modification occupancy occur specifically within enhancers, and these changes correlate with changes in the expression of nearby genes. Following GR binding, changes in the binding of other TFs precede changes in chromatin accessibility, suggesting that other TFs are also sensitive to genomic features beyond that of accessibility., (© 2018 McDowell et al.; Published by Cold Spring Harbor Laboratory Press.)

The glucocorticoid receptor (GR) is a hormone-inducible transcription factor involved in metabolic and anti-inflammatory gene expression responses. To investigate what controls interactions between GR binding sites and their target genes, we used in situ Hi-C to generate high-resolution, genome-wide maps of chromatin interactions before and after glucocorticoid treatment. We found that GR binding to the genome typically does not cause new chromatin interactions to target genes but instead acts through chromatin interactions that already exist prior to hormone treatment. Both glucocorticoid-induced and glucocorticoid-repressed genes increased interactions with distal GR binding sites. In addition, while glucocorticoid-induced genes increased interactions with transcriptionally active chromosome compartments, glucocorticoid-repressed genes increased interactions with transcriptionally silent compartments. Lastly, while the architectural DNA-binding proteins CTCF and RAD21 were bound to most chromatin interactions, we found that glucocorticoid-responsive chromatin interactions were depleted for CTCF binding but enriched for RAD21. Together, these findings offer new insights into the mechanisms underlying GC-mediated gene activation and repression., (Copyright © 2018. Published by Elsevier Inc.)

Schizophrenia genome-wide association studies have identified >150 regions of the genome associated with disease risk, yet there is little evidence that coding mutations contribute to this disorder. To explore the mechanism of non-coding regulatory elements in schizophrenia, we performed ATAC-seq on adult prefrontal cortex brain samples from 135 individuals with schizophrenia and 137 controls, and identified 118,152 ATAC-seq peaks. These accessible chromatin regions in the brain are highly enriched for schizophrenia SNP heritability. Accessible chromatin regions that overlap evolutionarily conserved regions exhibit an even higher heritability enrichment, indicating that sequence conservation can further refine functional risk variants. We identify few differences in chromatin accessibility between cases and controls, in contrast to thousands of age-related differential accessible chromatin regions. Altogether, we characterize chromatin accessibility in the human prefrontal cortex, the effect of schizophrenia and age on chromatin accessibility, and provide evidence that our dataset will allow for fine mapping of risk variants.

Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP), which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.

Genomic regulatory elements that control gene expression play an important role in many traits and diseases. Identifying the regulatory elements associated with each gene or phenotype and understanding the function of that element remain a significant challenge. To address this technological need, we developed CRISPR/Cas9-based epigenomic regulatory element screening (CERES) for improved high-throughput screening of regulatory element activity in the native genomic context. This protocol includes detailed instructions for design and cloning of gRNA libraries, construction of endogenous reporter cell lines via CRISPR/Cas9-mediated knock-in of fluorescent proteins, overall screen design, and recovery of the gRNA library for enrichment analysis. This protocol will be generally useful for implementing genome engineering technologies for high-throughput functional annotation of putative regulatory elements in their native chromosomal context.

Gene regulation is fundamentally important for the coordination of diverse biologic processes including homeostasis and responses to developmental and environmental stimuli. Transcription factor (TF) binding sites are one of the major functional subunits of gene regulation. They are arranged in cis-regulatory modules (CRMs) that can be more active than the sum of their individual effects. Recently, we described a mechanism of glucocorticoid (GC)-induced gene regulation in which the glucocorticoid receptor (GR) binds coordinately to multiple CRMs that are 10s of kilobases apart in the genome. In those results, the minority of GR binding sites appear to involve direct TF:DNA interactions. Meanwhile, other GR binding sites in a cluster interact with those direct binding sites to tune their gene regulatory activity. Here, we consider the implications of those and related results in the context of existing models of gene regulation. Based on our analyses, we propose that the billboard and regulatory grammar models of cis-regulatory element activity be expanded to consider the influence of long-range interactions between cis-regulatory modules.

Large genome-mapping consortia and thousands of genome-wide association studies have identified non-protein-coding elements in the genome as having a central role in various biological processes. However, decoding the functions of the millions of putative regulatory elements discovered in these studies remains challenging. CRISPR-Cas9-based epigenome editing technologies have enabled precise perturbation of the activity of specific regulatory elements. Here we describe CRISPR-Cas9-based epigenomic regulatory element screening (CERES) for improved high-throughput screening of regulatory element activity in the native genomic context. Using dCas9 KRAB repressor and dCas9 p300 activator constructs and lentiviral single guide RNA libraries to target DNase I hypersensitive sites surrounding a gene of interest, we carried out both loss- and gain-of-function screens to identify regulatory elements for the β-globin and HER2 loci in human cells. CERES readily identified known and previously unidentified regulatory elements, some of which were dependent on cell type or direction of perturbation. This technology allows the high-throughput functional annotation of putative regulatory elements in their native chromosomal context.

Background: Transversions (Tv's) are more likely to alter the amino acid sequence of proteins than transitions (Ts's), and local deviations in the Ts:Tv ratio are indicative of evolutionary selection on genes. Whether the two different types of mutations have different effects in non-protein-coding sequences remains unknown. Genetic variants primarily impact gene expression by disrupting the binding of transcription factors (TFs) and other DNA-binding proteins. Because Tv's cause larger changes in the shape of a DNA backbone, we hypothesized that Tv's would have larger impacts on TF binding and gene expression., Results: Here, we provide multiple lines of evidence demonstrating that Tv's have larger impacts on regulatory DNA including analyses of TF binding motifs and allele-specific TF binding. In these analyses, we observed a depletion of Tv's within TF binding motifs and TF binding sites. Using massively parallel population-scale reporter assays, we also provided empirical evidence that Tv's have larger effects than Ts's on the activity of human gene regulatory elements., Conclusions: Tv's are more likely to disrupt TF binding, resulting in larger changes in gene expression. Although the observed differences are small, these findings represent a novel, fundamental property of regulatory variation. Understanding the features of functional non-coding variation could be valuable for revealing the genetic underpinnings of complex traits and diseases in future studies.

Motivation: The accurate interpretation of genetic variants is critical for characterizing genotype-phenotype associations. Because the effects of genetic variants can depend strongly on their local genomic context, accurate genome annotations are essential. Furthermore, as some variants have the potential to disrupt or alter gene structure, variant interpretation efforts stand to gain from the use of individualized annotations that account for differences in gene structure between individuals or strains., Results: We describe a suite of software tools for identifying possible functional changes in gene structure that may result from sequence variants. ACE ('Assessing Changes to Exons') converts phased genotype calls to a collection of explicit haplotype sequences, maps transcript annotations onto them, detects gene-structure changes and their possible repercussions, and identifies several classes of possible loss of function. Novel transcripts predicted by ACE are commonly supported by spliced RNA-seq reads, and can be used to improve read alignment and transcript quantification when an individual-specific genome sequence is available. Using publicly available RNA-seq data, we show that ACE predictions confirm earlier results regarding the quantitative effects of nonsense-mediated decay, and we show that predicted loss-of-function events are highly concordant with patterns of intolerance to mutations across the human population. ACE can be readily applied to diverse species including animals and plants, making it a broadly useful tool for use in eukaryotic population-based resequencing projects, particularly for assessing the joint impact of all variants at a locus., Availability and Implementation: ACE is written in open-source C ++ and Perl and is available from geneprediction.org/ACE., Contact: myandell@genetics.utah.edu or tim.reddy@duke.edu., Supplementary Information: Supplementary information is available at Bioinformatics online., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com)

Genetic variation in gene regulatory elements contributes to diverse human diseases, ranging from rare and severe developmental defects to common and complex diseases such as obesity and diabetes. Early examples of regulatory mechanisms of human diseases involve large chromosomal rearrangements that change the regulatory connections within the genome. Single nucleotide variants in regulatory elements can also contribute to disease, potentially via demonstrated associations with changes in transcription factor binding, enhancer activity, post-translational histone modifications, long-range enhancer-promoter interactions, or RNA polymerase recruitment. Establishing causality between non-coding genetic variants, gene regulation, and disease has recently become more feasible with advances in genome-editing and epigenome-editing technologies. As establishing causal regulatory mechanisms of diseases becomes routine, functional annotation of target genes is likely to emerge as a major bottleneck for translation into patient benefits. In this review, we discuss the history and recent advances in understanding the regulatory mechanisms of human disease, and new challenges likely to be encountered once establishing those mechanisms becomes rote., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

In a recent genome-wide association study, hexokinase domain-containing protein 1, or HKDC1, was found to be associated with gestational glucose levels during 2-hour glucose tolerance tests at 28 weeks of pregnancy. Because our understanding of the mediators of gestational glucose homeostasis is incomplete, we have generated the first transgenic mouse model to begin to understand the role of HKDC1 in whole-body glucose homeostasis. Interestingly, deletion of both HKDC1 alleles results in in utero embryonic lethality. Thus, in this study, we report the in vivo role of HKDC1 in whole-body glucose homeostasis using a heterozygous-deleted HKDC1 mouse model (HKDC1(+/-)) as compared with matched wild-type mice. First, we observed no weight, fasting or random glucose, or fasting insulin abnormalities with aging in male and female HKDC1(+/-) mice. However, during glucose tolerance tests, glucose levels were impaired in both female and male HKDC1(+/-) mice at 15, 30, and 120 minutes at a later age (28 wk of age). These glucose tolerance differences also existed in the female HKDC1(+/-) mice at earlier ages but only during pregnancy. And finally, the impaired glucose tolerance in HKDC1(+/-) mice was likely due to diminished whole-body glucose use, as indicated by the decreased hepatic energy storage and reduced peripheral tissue uptake of glucose in HKDC1(+/-) mice. Collectively, these data highlight that HKDC1 is needed to maintain whole-body glucose homeostasis during pregnancy but also with aging, possibly through its role in glucose use.

Overexpression of exogenous fate-specifying transcription factors can directly reprogram differentiated somatic cells to target cell types. Here, we show that similar reprogramming can also be achieved through the direct activation of endogenous genes using engineered CRISPR/Cas9-based transcriptional activators. We use this approach to induce activation of the endogenous Brn2, Ascl1, and Myt1l genes (BAM factors) to convert mouse embryonic fibroblasts to induced neuronal cells. This direct activation of endogenous genes rapidly remodeled the epigenetic state of the target loci and induced sustained endogenous gene expression during reprogramming. Thus, transcriptional activation and epigenetic remodeling of endogenous master transcription factors are sufficient for conversion between cell types. The rapid and sustained activation of endogenous genes in their native chromatin context by this approach may facilitate reprogramming with transient methods that avoid genomic integration and provides a new strategy for overcoming epigenetic barriers to cell fate specification., Competing Interests: CONFLIC OF INTEREST C.A.G. and J.B.B. have filed patent applications related to genome engineering technologies., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The glucocorticoid receptor (GR) binds the human genome at >10,000 sites but only regulates the expression of hundreds of genes. To determine the functional effect of each site, we measured the glucocorticoid (GC) responsive activity of nearly all GR binding sites (GBSs) captured using chromatin immunoprecipitation (ChIP) in A549 cells. 13% of GBSs assayed had GC-induced activity. The responsive sites were defined by direct GR binding via a GC response element (GRE) and exclusively increased reporter-gene expression. Meanwhile, most GBSs lacked GC-induced reporter activity. The non-responsive sites had epigenetic features of steady-state enhancers and clustered around direct GBSs. Together, our data support a model in which clusters of GBSs observed with ChIP-seq reflect interactions between direct and tethered GBSs over tens of kilobases. We further show that those interactions can synergistically modulate the activity of direct GBSs and may therefore play a major role in driving gene activation in response to GCs., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Epigenome editing with the CRISPR (clustered, regularly interspaced, short palindromic repeats)-Cas9 platform is a promising technology for modulating gene expression to direct cell phenotype and to dissect the causal epigenetic mechanisms of gene regulation. Fusions of nuclease-inactive dCas9 to the Krüppel-associated box (KRAB) repressor (dCas9-KRAB) can silence target gene expression, but the genome-wide specificity and the extent of heterochromatin formation catalyzed by dCas9-KRAB are not known. We targeted dCas9-KRAB to the HS2 enhancer, a distal regulatory element that orchestrates the expression of multiple globin genes, and observed highly specific induction of H3K9 trimethylation (H3K9me3) at the enhancer and decreased chromatin accessibility of both the enhancer and its promoter targets. Targeted epigenetic modification of HS2 silenced the expression of multiple globin genes, with minimal off-target changes in global gene expression. These results demonstrate that repression mediated by dCas9-KRAB is sufficiently specific to disrupt the activity of individual enhancers via local modification of the epigenome.

There are thousands of known associations between genetic variants and complex human phenotypes, and the rate of novel discoveries is rapidly increasing. Translating those associations into knowledge of disease mechanisms remains a fundamental challenge because the associated variants are overwhelmingly in noncoding regions of the genome where we have few guiding principles to predict their function. Intersecting the compendium of identified genetic associations with maps of regulatory activity across the human genome has revealed that phenotype-associated variants are highly enriched in candidate regulatory elements. Allele-specific analyses of gene regulation can further prioritize variants that likely have a functional effect on disease mechanisms; and emerging high-throughput assays to quantify the activity of candidate regulatory elements are a promising next step in that direction. Together, these technologies have created the ability to systematically and empirically test hypotheses about the function of noncoding variants and haplotypes at the scale needed for comprehensive and systematic follow-up of genetic association studies. Major coordinated efforts to quantify regulatory mechanisms across genetically diverse populations in increasingly realistic cell models would be highly beneficial to realize that potential., (© 2015 Lowe and Reddy; Published by Cold Spring Harbor Laboratory Press.)

Genome engineering technologies based on the CRISPR/Cas9 and TALE systems are enabling new approaches in science and biotechnology. However, the specificity of these tools in complex genomes and the role of chromatin structure in determining DNA binding are not well understood. We analyzed the genome-wide effects of TALE- and CRISPR-based transcriptional activators in human cells using ChIP-seq to assess DNA-binding specificity and RNA-seq to measure the specificity of perturbing the transcriptome. Additionally, DNase-seq was used to assess genome-wide chromatin remodeling that occurs as a result of their action. Our results show that these transcription factors are highly specific in both DNA binding and gene regulation and are able to open targeted regions of closed chromatin independent of gene activation. Collectively, these results underscore the potential for these technologies to make precise changes to gene expression for gene and cell therapies or fundamental studies of gene function., (© 2015 Polstein et al.; Published by Cold Spring Harbor Laboratory Press.)

We report a novel high-throughput method to empirically quantify individual-specific regulatory element activity at the population scale. The approach combines targeted DNA capture with a high-throughput reporter gene expression assay. As demonstration, we measured the activity of more than 100 putative regulatory elements from 95 individuals in a single experiment. In agreement with previous reports, we found that most genetic variants have weak effects on distal regulatory element activity. Because haplotypes are typically maintained within but not between assayed regulatory elements, the approach can be used to identify causal regulatory haplotypes that likely contribute to human phenotypes. Finally, we demonstrate the utility of the method to functionally fine map causal regulatory variants in regions of high linkage disequilibrium identified by expression quantitative trait loci (eQTL) analyses., (© 2015 Vockley et al.; Published by Cold Spring Harbor Laboratory Press.)

Personalizing treatments to account for genetically mediated differences in drug responses is an exciting opportunity to improve patient outcomes. In this issue, Soccio et al. reveal new mechanisms by which non-coding variants alter the activity of the anti-diabetic drug rosiglitazone., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Genetic reprogramming holds great potential for disease modeling, drug screening, and regenerative medicine. Genetic reprogramming of mammalian cells is typically achieved by forced expression of natural transcription factors that control master gene networks and cell lineage specification. However, in many instances, the natural transcription factors do not induce a sufficiently robust response to completely reprogram cell phenotype. In this study, we demonstrate that protein engineering of the master transcription factor MyoD can enhance the conversion of human dermal fibroblasts and adult stem cells to a skeletal myocyte phenotype. Fusion of potent transcriptional activation domains to MyoD led to increased myogenic gene expression, myofiber formation, cell fusion, and global reprogramming of the myogenic gene network. This work supports a general strategy for synthetically enhancing the direct conversion between cell types that can be applied in both synthetic biology and regenerative medicine.