Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors

A novel interpretable deep learning-based computational framework designed synthetic enhancers with broad cross-species activity

Enhancers play a critical role in dynamically regulating spatial-temporal gene expression and establishing cell identity, underscoring the significance of designing them with specific properties for applications in biosynthetic engineering and gene therapy. Despite numerous high-throughput methods facilitating genome-wide enhancer identification, deciphering the sequence determinants of their activity remains challenging. Here, we present the DREAM (DNA cis-Regulatory Elements with controllable Activity design platforM) framework, a novel deep learning-based approach for synthetic enhancer design. Proficient in uncovering subtle and intricate patterns within extensive enhancer screening data, DREAM achieves cutting-edge sequence-based enhancer activity prediction and highlights critical sequence features implicating strong enhancer activity. Leveraging DREAM, we have engineered enhancers that surpass the potency of the strongest enhancer within the Drosophila genome by approximately 3.6-fold. Remarkably, these synthetic enhancers exhibited conserved functionality across species that have diverged more than billion years, indicating that DREAM was able to learn highly conserved enhancer regulatory grammar. Additionally, we designed silencers and cell line-specific enhancers using DREAM, demonstrating its versatility. Overall, our study not only introduces an interpretable approach for enhancer design but also lays out a general framework applicable to the design of other types of cis-regulatory elements.

Massively parallel binding assay (MPBA) reveals limited transcription factor binding cooperativity, challenging models of specificity

DNA-binding domains (DBDs) within transcription factors (TFs) recognize short sequence motifs that are highly abundant in genomes. In vivo, TFs bind only a small subset of motif occurrences, which is often attributed to the cooperative binding of interacting TFs at proximal motifs. However, large-scale testing of this model is still lacking. Here, we describe a novel method allowing parallel measurement of TF binding to thousands of designed sequences within yeast cells and apply it to quantify the binding of dozens of TFs to libraries of regulatory regions containing clusters of binding motifs, systematically mutating all motif combinations. With few exceptions, TF occupancies were well explained by independent binding to individual motifs, with motif cooperation being of only limited effects. Our results challenge the general role of motif combinatorics in directing TF genomic binding and open new avenues for exploring the basis of protein-DNA interactions within cells.

Identifying transcription factors with cell-type specific DNA binding signatures

BACKGROUND

Transcription factors (TFs) bind to different parts of the genome in different types of cells, but it is usually assumed that the inherent DNA-binding preferences of a TF are invariant to cell type. Yet, there are several known examples of TFs that switch their DNA-binding preferences in different cell types, and yet more examples of other mechanisms, such as steric hindrance or cooperative binding, that may result in a "DNA signature" of differential binding.

RESULTS

To survey this phenomenon systematically, we developed a deep learning method we call SigTFB (Signatures of TF Binding) to detect and quantify cell-type specificity in a TF's known genomic binding sites. We used ENCODE ChIP-seq data to conduct a wide scale investigation of 169 distinct TFs in up to 14 distinct cell types. SigTFB detected statistically significant DNA binding signatures in approximately two-thirds of TFs, far more than might have been expected from the relatively sparse evidence in prior literature. We found that the presence or absence of a cell-type specific DNA binding signature is distinct from, and indeed largely uncorrelated to, the degree of overlap between ChIP-seq peaks in different cell types, and tended to arise by two mechanisms: using established motifs in different frequencies, and by selective inclusion of motifs for distint TFs.

CONCLUSIONS

While recent results have highlighted cell state features such as chromatin accessibility and gene expression in predicting TF binding, our results emphasize that, for some TFs, the DNA sequences of the binding sites contain substantial cell-type specific motifs.

An in vitro approach reveals molecular mechanisms underlying endocrine disruptor-induced epimutagenesis

Endocrine disrupting chemicals (EDCs) such as bisphenol S (BPS) are xenobiotic compounds that can disrupt endocrine signaling due to steric similarities to endogenous hormones. EDCs have been shown to induce disruptions in normal epigenetic programming (epimutations) and differentially expressed genes (DEGs) that predispose disease states. Most interestingly, the prevalence of epimutations following exposure to many EDCs persists over multiple generations. Many studies have described direct and prolonged effects of EDC exposure in animal models, but many questions remain about molecular mechanisms by which EDC-induced epimutations are introduced or subsequently propagated, whether there are cell type-specific susceptibilities to the same EDC, and whether this correlates with differential expression of relevant hormone receptors. We exposed cultured pluripotent (iPS), somatic (Sertoli and granulosa), and primordial germ cell-like (PGCLC) cells to BPS and found that differential incidences of BPS-induced epimutations and DEGs correlated with differential expression of relevant hormone receptors inducing epimutations near relevant hormone response elements in somatic and pluripotent, but not germ cell types. Most interestingly, we found that when iPS cells were exposed to BPS and then induced to differentiate into PGCLCs, the prevalence of epimutations and DEGs was largely retained, however, >90% of the specific epimutations and DEGs were replaced by novel epimutations and DEGs. These results suggest a unique mechanism by which an EDC-induced epimutated state may be propagated transgenerationally.

p53motifDB: integration of genomic information and tumor suppressor p53 binding motifs

The tumor suppressor gene TP53 encodes the DNA binding transcription factor p53 and is one of the most commonly mutated genes in human cancer. Tumor suppressor activity requires binding of p53 to its DNA response elements and subsequent transcriptional activation of a diverse set of target genes. Despite decades of close study, the logic underlying p53 interactions with its numerous potential genomic binding sites and target genes is not yet fully understood. Here, we present a database of DNA and chromatin-based information focused on putative p53 binding sites in the human genome to allow users to generate and test new hypotheses related to p53 activity in the genome. Users can query genomic locations based on experimentally observed p53 binding, regulatory element activity, genetic variation, evolutionary conservation, chromatin modification state, and chromatin structure. We present multiple use cases demonstrating the utility of this database for generating novel biological hypotheses, such as chromatin-based determinants of p53 binding and potential cell type-specific p53 activity. All database information is also available as a precompiled sqlite database for use in local analysis or as a Shiny web application.

Neuronal enhancers fine-tune adaptive circuit plasticity

Neuronal activity-regulated gene expression plays a crucial role in sculpting neural circuits that underpin adaptive brain function. Transcriptional enhancers are now recognized as key components of gene regulation that orchestrate spatiotemporally precise patterns of gene transcription. We propose that the dynamics of enhancer activation uniquely position these genomic elements to finely tune activity-dependent cellular plasticity. Enhancer specificity and modularity can be exploited to gain selective genetic access to specific cell states, and the precise modulation of target gene expression within restricted cellular contexts enabled by targeted enhancer manipulation allows for fine-grained evaluation of gene function. Mounting evidence also suggests that enduring stimulus-induced changes in enhancer states can modify target gene activation upon restimulation, thereby contributing to a form of cell-wide metaplasticity. We advocate for focused exploration of activity-dependent enhancer function to gain new insight into the mechanisms underlying brain plasticity and cognitive dysfunction.

Genomic binding of NF-Y in mouse and human cells

NF-Y is a Transcription Factor that regulates transcription through binding to the CCAAT-box. To understand its strategy, we analyzed 16 ChIP-seq datasets from human and mouse cells. Shared loci, mostly located in promoters of expressed genes of cell cycle, metabolism and gene expression pathways, are associated with histone marks of active chromatin and specific modules of TFs. Other peaks are in enhancers and Transposable Elements -TE- of retroviral origin in human and mouse. We evaluated the relationship with USF1, a common synergistic partner in promoters and MLT1 TEs, upon NF-YB inactivation: USF1 binding decreases in promoters, modestly in MLT1, suggesting a pioneering role of NF-Y in formers, not in the latters. These data define a common set of NF-Y functional targets across different mammalian cell types, suggesting a pioneering role in promoters with respect to TEs.

Systematic dissection of sequence features affecting binding specificity of a pioneer factor reveals binding synergy between FOXA1 and AP-1

Despite the unique ability of pioneer factors (PFs) to target nucleosomal sites in closed chromatin, they only bind a small fraction of their genomic motifs. The underlying mechanism of this selectivity is not well understood. Here, we design a high-throughput assay called chromatin immunoprecipitation with integrated synthetic oligonucleotides (ChIP-ISO) to systematically dissect sequence features affecting the binding specificity of a classic PF, FOXA1, in human A549 cells. Combining ChIP-ISO with in vitro and neural network analyses, we find that (1) FOXA1 binding is strongly affected by co-binding transcription factors (TFs) AP-1 and CEBPB; (2) FOXA1 and AP-1 show binding cooperativity in vitro; (3) FOXA1's binding is determined more by local sequences than chromatin context, including eu-/heterochromatin; and (4) AP-1 is partially responsible for differential binding of FOXA1 in different cell types. Our study presents a framework for elucidating genetic rules underlying PF binding specificity and reveals a mechanism for context-specific regulation of its binding.

TFscope: systematic analysis of the sequence features involved in the binding preferences of transcription factors

Characterizing the binding preferences of transcription factors (TFs) in different cell types and conditions is key to understand how they orchestrate gene expression. Here, we develop TFscope, a machine learning approach that identifies sequence features explaining the binding differences observed between two ChIP-seq experiments targeting either the same TF in two conditions or two TFs with similar motifs (paralogous TFs). TFscope systematically investigates differences in the core motif, nucleotide environment and co-factor motifs, and provides the contribution of each key feature in the two experiments. TFscope was applied to > 305 ChIP-seq pairs, and several examples are discussed.

BRD9 regulates normal human hematopoietic stem cell function and lineage differentiation

Bromodomain containing protein 9 (BRD9), a member of the non-canonical BRG1/BRM-associated factor (ncBAF) chromatin remodeling complex, has been implicated as a synthetic lethal target in AML but its function in normal human hematopoiesis is unknown. In hematopoietic stem and progenitor cells (HSPC) genomic or chemical inhibition of BRD9 led to a proliferative disadvantage and loss of stem cells in vitro. Human HSPCs with reduced BRD9 protein levels produced lower numbers of immature mixed multipotent GEMM colonies in semi-solid media. In lineage-promoting culture conditions, cells with reduced BRD9 levels failed to differentiate into the megakaryocytic lineage and showed delayed differentiation into erythroid cells but enhanced terminal myeloid differentiation. HSPCs with BRD9 knock down (KD) had reduced long-term multilineage engraftment in a xenotransplantation assay. An increased number of downregulated genes in RNAseq analysis after BRD9 KD coupled with a gain in chromatin accessibility at the promoters of several repressive transcription factors (TF) suggest that BRD9 functions in the maintenance of active transcription during HSC differentiation. In particular, the hematopoietic master regulator GATA1 was identified as one of the core TFs regulating the gene networks modulated by BRD9 loss in HSPCs. BRD9 inhibition reduced a GATA1-luciferase reporter signal, further suggesting a role for BRD9 in regulating GATA1 activity. BRD9 is therefore an additional example of epigenetic regulation of human hematopoiesis.

Endocrine disruptor-induced epimutagenesis in vitro : Insight into molecular mechanisms

Endocrine disrupting chemicals (EDCs) such as bisphenol S (BPS) are xenobiotic compounds that can disrupt endocrine signaling following exposure due to steric similarities to endogenous hormones within the body. EDCs have been shown to induce disruptions in normal epigenetic programming (epimutations) that accompany dysregulation of normal gene expression patterns that appear to predispose disease states. Most interestingly, the prevalence of epimutations following exposure to many different EDCs often persists over multiple subsequent generations, even with no further exposure to the causative EDC. Many previous studies have described both the direct and prolonged effects of EDC exposure in animal models, but many questions remain about molecular mechanisms by which EDCs initially induce epimutations or contribute to the propagation of EDC-induced epimutations either within the exposed generation or to subsequent generations. Additional questions remain regarding the extent to which there may be differences in cell-type specific susceptibilities to various EDCs, and whether this susceptibility is correlative with expression of relevant hormone receptors and/or the location of relevant hormone response elements (HREs) in the genome. To address these questions, we exposed cultured mouse pluripotent (induced pluripotent stem [iPS]), somatic (Sertoli and granulosa), and germ (primordial germ cell like [PGCLC]) cells to BPS and measured changes in DNA methylation levels at the epigenomic level and gene expression at the transcriptomic level. We found that there was indeed a difference in cell-type specific susceptibility to EDC-induced epimutagenesis and that this susceptibility correlated with differential expression of relevant hormone receptors and, in many cases, tended to generate epimutations near relevant HREs within the genome. Additionally, however, we also found that BPS can induce epimutations in a cell type that does not express relevant receptors and in genomic regions that do not contain relevant HREs, suggesting that both canonical and non-canonical signaling mechanisms can be disrupted by BPS exposure. Most interestingly, we found that when iPS cells were exposed to BPS and then induced to differentiate into PGCLCs, the prevalence of epimutations and differentially expressed genes (DEGs) initially induced in the iPSCs was largely retained in the resulting PGCLCs, however, >90% of the specific epimutations and DEGs were not conserved but were rather replaced by novel epimutations and DEGs following the iPSC to PGCLC transition. These results are consistent with a unique concept that many EDC-induced epimutations may normally be corrected by germline and/or embryonic epigenetic reprogramming but that due to disruption of the underlying chromatin architecture induced by the EDC exposure, many novel epimutations may emerge during the reprogramming process as well. Thus, it appears that following exposure to a disruptive agent such as an EDC, a prevalence of epimutations may transcend epigenetic reprogramming even though most individual epimutations are not conserved during this process.

Pioneer factors: nature or nurture?

Chromatin is densely packed with nucleosomes, which limits the accessibility of many chromatin-associated proteins. Pioneer factors (PFs) are usually viewed as a special group of sequence-specific transcription factors (TFs) that can recognize nucleosome-embedded motifs, invade compact chromatin, and generate open chromatin regions. Through this process, PFs initiate a cascade of events that play key roles in gene regulation and cell differentiation. A current debate in the field is if PFs belong to a unique subset of TFs with intrinsic "pioneering activity", or if all TFs have the potential to function as PFs within certain cellular contexts. There are also different views regarding the key feature(s) that define pioneering activity. In this review, we present evidence from the literature related to these alternative views and discuss how to potentially reconcile them. It is possible that both intrinsic properties, like tight nucleosome binding and structural compatibility, and cellular conditions, like concentration and co-factor availability, are important for PF function.

Construction of transcript regulation mechanism prediction models based on binding motif environment of transcription factor AoXlnR in Aspergillus oryzae

DNA-binding transcription factors (TFs) play a central role in transcriptional regulation mechanisms, mainly through their specific binding to target sites on the genome and regulation of the expression of downstream genes. Therefore, a comprehensive analysis of the function of these TFs will lead to the understanding of various biological mechanisms. However, the functions of TFs in vivo are diverse and complicated, and the identified binding sites on the genome are not necessarily involved in the regulation of downstream gene expression. In this study, we investigated whether DNA structural information around the binding site of TFs can be used to predict the involvement of the binding site in the regulation of the expression of genes located downstream of the binding site. Specifically, we calculated the structural parameters based on the DNA shape around the DNA binding motif located upstream of the gene whose expression is directly regulated by one TF AoXlnR from Aspergillus oryzae, and showed that the presence or absence of expression regulation can be predicted from the sequence information with high accuracy ([Formula: see text]-1.0) by machine learning incorporating these parameters.

Characterization of Undiscovered miRNA Involved in Tumor Necrosis Factor Alpha-Induced Atrophy in Mouse Skeletal Muscle Cell Line

Muscular atrophy is a complex catabolic condition that develops due to several inflammatory-related disorders, resulting in muscle loss. Tumor necrosis factor alpha (TNF-α) is believed to be one of the leading factors that drive inflammatory response and its progression. Until now, the link between inflammation and muscle wasting has been thoroughly investigated, and the non-coding RNA machinery is a potential connection between the candidates. This study aimed to identify specific miRNAs for muscular atrophy induced by TNF-α in the C2C12 murine myotube model. The difference in expression of fourteen known miRNAs and two newly identified miRNAs was recorded by next-generation sequencing between normal muscle cells and treated myotubes. After validation, we confirmed the difference in the expression of one novel murine miRNA (nov-mmu-miRNA-1) under different TNF-α-inducing conditions. Functional bioinformatic analyses of nov-mmu-miRNA-1 revealed the potential association with inflammation and muscle atrophy. Our results suggest that nov-mmu-miRNA-1 may trigger inflammation and muscle wasting by the downregulation of LIN28A/B, an anti-inflammatory factor in the let-7 family. Therefore, TNF-α is involved in muscle atrophy through the modulation of the miRNA cellular machinery. Here, we describe for the first time and propose a mechanism for the newly discovered miRNA, nov-mmu-miRNA-1, which may regulate inflammation and promote muscle atrophy.

Functional dissection of complex and molecular trait variants at single nucleotide resolution

Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types. We show that MPRA is able to discriminate between likely causal variants and controls, identifying 12,025 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% can plausibly be explained by the disruption of a known transcription factor (TF) binding motif. We dissect the mechanisms of 136 variants using saturation mutagenesis and assign impacted TFs for 91% of variants without a clear canonical mechanism. Finally, we provide evidence that epistasis is prevalent for variants in close proximity and identify multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants underlying complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.

Zmiz1 is a novel regulator of brain development associated with autism and intellectual disability

Neurodevelopmental disorders (NDDs) are a class of pathologies arising from perturbations in brain circuit formation and maturation with complex etiological triggers often classified as environmental and genetic. Neuropsychiatric conditions such as autism spectrum disorders (ASD), intellectual disability (ID), and attention deficit hyperactivity disorders (ADHD) are common NDDs characterized by their hereditary underpinnings and inherent heterogeneity. Genetic risk factors for NDDs are increasingly being identified in non-coding regions and proteins bound to them, including transcriptional regulators and chromatin remodelers. Importantly, de novo mutations are emerging as important contributors to NDDs and neuropsychiatric disorders. Recently, de novo mutations in transcriptional co-factor Zmiz1 or its regulatory regions have been identified in unrelated patients with syndromic ID and ASD. However, the role of Zmiz1 in brain development is unknown. Here, using publicly available databases and a Zmiz1 mutant mouse model, we reveal that Zmiz1 is highly expressed during embryonic brain development in mice and humans, and though broadly expressed across the brain, Zmiz1 is enriched in areas prominently impacted in ID and ASD such as cortex, hippocampus, and cerebellum. We investigated the relationship between Zmiz1 structure and pathogenicity of protein variants, the epigenetic marks associated with Zmiz1 regulation, and protein interactions and signaling pathways regulated by Zmiz1. Our analysis reveals that Zmiz1 regulates multiple developmental processes, including neurogenesis, neuron connectivity, and synaptic signaling. This work paves the way for future studies on the functions of Zmiz1 and highlights the importance of combining analysis of mouse models and human data.

Integration of transcription regulation and functional genomic data reveals lncRNA SNHG6's role in hematopoietic differentiation and leukemia

BACKGROUND

Long non-coding RNAs (lncRNAs) are pivotal players in cellular processes, and their unique cell-type specific expression patterns render them attractive biomarkers and therapeutic targets. Yet, the functional roles of most lncRNAs remain enigmatic. To address the need to identify new druggable lncRNAs, we developed a comprehensive approach integrating transcription factor binding data with other genetic features to generate a machine learning model, which we have called INFLAMeR (Identifying Novel Functional LncRNAs with Advanced Machine Learning Resources).

METHODS

INFLAMeR was trained on high-throughput CRISPR interference (CRISPRi) screens across seven cell lines, and the algorithm was based on 71 genetic features. To validate the predictions, we selected candidate lncRNAs in the human K562 leukemia cell line and determined the impact of their knockdown (KD) on cell proliferation and chemotherapeutic drug response. We further performed transcriptomic analysis for candidate genes. Based on these findings, we assessed the lncRNA small nucleolar RNA host gene 6 (SNHG6) for its role in myeloid differentiation. Finally, we established a mouse K562 leukemia xenograft model to determine whether SNHG6 KD attenuates tumor growth in vivo.

RESULTS

The INFLAMeR model successfully reconstituted CRISPRi screening data and predicted functional lncRNAs that were previously overlooked. Intensive cell-based and transcriptomic validation of nearly fifty genes in K562 revealed cell type-specific functionality for 85% of the predicted lncRNAs. In this respect, our cell-based and transcriptomic analyses predicted a role for SNHG6 in hematopoiesis and leukemia. Consistent with its predicted role in hematopoietic differentiation, SNHG6 transcription is regulated by hematopoiesis-associated transcription factors. SNHG6 KD reduced the proliferation of leukemia cells and sensitized them to differentiation. Treatment of K562 leukemic cells with hemin and PMA, respectively, demonstrated that SNHG6 inhibits red blood cell differentiation but strongly promotes megakaryocyte differentiation. Using a xenograft mouse model, we demonstrate that SNHG6 KD attenuated tumor growth in vivo.

CONCLUSIONS

Our approach not only improved the identification and characterization of functional lncRNAs through genomic approaches in a cell type-specific manner, but also identified new lncRNAs with roles in hematopoiesis and leukemia. Such approaches can be readily applied to identify novel targets for precision medicine.

Crosstalk between chromatin and Shavenbaby defines transcriptional output along the Drosophila intestinal stem cell lineage

The transcription factor Shavenbaby (Svb), the only member of the OvoL family in Drosophila, controls the fate of various epithelial embryonic cells and adult stem cells. Post-translational modification of Svb produces two protein isoforms, Svb-ACT and Svb-REP, which promote adult intestinal stem cell renewal or differentiation, respectively. To define Svb mode of action, we used engineered cell lines and develop an unbiased method to identify Svb target genes across different contexts. Within a given cell type, Svb-ACT and Svb-REP antagonistically regulate the expression of a set of target genes, binding specific enhancers whose accessibility is constrained by chromatin landscape. Reciprocally, Svb-REP can influence local chromatin marks of active enhancers to help repressing target genes. Along the intestinal lineage, the set of Svb target genes progressively changes, together with chromatin accessibility. We propose that Svb-ACT-to-REP transition promotes enterocyte differentiation of intestinal stem cells through direct gene regulation and chromatin remodeling.

The bone transcription factor Osterix controls extracellular matrix- and node of Ranvier-related gene expression in oligodendrocytes

Oligodendrocytes are the primary producers of many extracellular matrix (ECM)-related proteins found in the CNS. Therefore, oligodendrocytes play a critical role in the determination of brain stiffness, node of Ranvier formation, perinodal ECM deposition, and perineuronal net formation, all of which depend on the ECM. Nevertheless, the transcription factors that control ECM-related gene expression in oligodendrocytes remain unknown. Here, we found that the transcription factor Osterix (also known as Sp7) binds in proximity to genes important for CNS ECM and node of Ranvier formation and mediates their expression. Oligodendrocyte-specific ablation of Sp7 changes ECM composition and brain stiffness and results in aberrant node of Ranvier formation. Sp7 is known to control osteoblast maturation and bone formation. Our comparative analyses suggest that Sp7 plays a conserved biological role in oligodendrocytes and in bone-forming cells, where it mediates brain and bone tissue stiffness by controlling expression of ECM components.

A mouse model of Weaver syndrome displays overgrowth and excess osteogenesis reversible with KDM6A/6B inhibition

Weaver syndrome is a Mendelian disorder of the epigenetic machinery (MDEM) caused by germline pathogenic variants in EZH2, which encodes the predominant H3K27 methyltransferase and key enzymatic component of Polycomb repressive complex 2 (PRC2). Weaver syndrome is characterized by striking overgrowth and advanced bone age, intellectual disability, and distinctive facies. We generated a mouse model for the most common Weaver syndrome missense variant, EZH2 p.R684C. Ezh2R684C/R684C mouse embryonic fibroblasts (MEFs) showed global depletion of H3K27me3. Ezh2R684C/+ mice had abnormal bone parameters, indicative of skeletal overgrowth, and Ezh2R684C/+ osteoblasts showed increased osteogenic activity. RNA-Seq comparing osteoblasts differentiated from Ezh2R684C/+, and Ezh2+/+ BM-mesenchymal stem cells (BM-MSCs) indicated collective dysregulation of the BMP pathway and osteoblast differentiation. Inhibition of the opposing H3K27 demethylases KDM6A and KDM6B substantially reversed the excessive osteogenesis in Ezh2R684C/+ cells both at the transcriptional and phenotypic levels. This supports both the ideas that writers and erasers of histone marks exist in a fine balance to maintain epigenome state and that epigenetic modulating agents have therapeutic potential for the treatment of MDEMs.

Position-specific evolution in transcription factor binding sites, and a fast likelihood calculation for the F81 model

Transcription factor binding sites (TFBS), like other DNA sequence, evolve via mutation and selection relating to their function. Models of nucleotide evolution describe DNA evolution via single-nucleotide mutation. A stationary vector of such a model is the long-term distribution of nucleotides, unchanging under the model. Neutrally evolving sites may have uniform stationary vectors, but one expects that sites within a TFBS instead have stationary vectors reflective of the fitness of various nucleotides at those positions. We introduce 'position-specific stationary vectors' (PSSVs), the collection of stationary vectors at each site in a TFBS locus, analogous to the position weight matrix (PWM) commonly used to describe TFBS. We infer PSSVs for human TFs using two evolutionary models (Felsenstein 1981 and Hasegawa-Kishino-Yano 1985). We find that PSSVs reflect the nucleotide distribution from PWMs, but with reduced specificity. We infer ancestral nucleotide distributions at individual positions and calculate 'conditional PSSVs' conditioned on specific choices of majority ancestral nucleotide. We find that certain ancestral nucleotides exert a strong evolutionary pressure on neighbouring sequence while others have a negligible effect. Finally, we present a fast likelihood calculation for the F81 model on moderate-sized trees that makes this approach feasible for large-scale studies along these lines.

Improving Enhancer Identification with a Multi-Classifier Stacked Ensemble Model

Enhancers are DNA regions that are responsible for controlling the expression of genes. Enhancers are usually found upstream or downstream of a gene, or even inside a gene's intron region, but are normally located at a distant location from the genes they control. By integrating experimental and computational approaches, it is possible to uncover enhancers within DNA sequences, which possess regulatory properties. Experimental techniques such as ChIP-seq and ATAC-seq can identify genomic regions that are associated with transcription factors or accessible to regulatory proteins. On the other hand, computational techniques can predict enhancers based on sequence features and epigenetic modifications. In our study, we have developed a multi-classifier stacked ensemble (MCSE-enhancer) model that can accurately identify enhancers. We utilized feature descriptors from various physiochemical properties as input for our six baseline classifiers and built a stacked classifier, which outperformed previous enhancer classification techniques in terms of accuracy, specificity, sensitivity, and Mathew's correlation coefficient. Our model achieved an accuracy of 81.5%, representing a 2-3% improvement over existing models.

Validation of the new EPIC DNA methylation microarray (900K EPIC v2) for high-throughput profiling of the human DNA methylome

DNA methylation, one of the best characterized epigenetic marks in the human genome, plays a pivotal role in gene transcription regulation and other biological processes in humans. On top of that, the DNA methylome undergoes profound changes in cancer and other disorders. However, large-scale and population-based studies are limited by high costs and the need for considerable expertise in data analysis for whole-genome bisulphite-sequencing methodologies. Following the success of the EPIC DNA methylation microarray, the newly developed Infinium HumanMethylationEPIC version 2.0 (900K EPIC v2) is now available. This new array contains more than 900,000 CpG probes covering the human genome and excluding masked probes from the previous version. The 900K EPIC v2 microarray adds more than 200,000 probes covering extra DNA cis-regulatory regions such as enhancers, super-enhancers and CTCF binding regions. Herein, we have technically and biologically validated the new methylation array to show its high reproducibility and consistency among technical replicates and with DNA extracted from FFPE tissue. In addition, we have hybridized primary normal and tumoural tissues and cancer cell lines from different sources and tested the robustness of the 900K EPIC v2 microarray when analysing the different DNA methylation profiles. The validation highlights the improvements offered by the new array and demonstrates the versatility of this updated tool for characterizing the DNA methylome in human health and disease.

Systematic Dissection of Sequence Features Affecting the Binding Specificity of a Pioneer Factor Reveals Binding Synergy Between FOXA1 and AP-1

Despite the unique ability of pioneer transcription factors (PFs) to target nucleosomal sites in closed chromatin, they only bind a small fraction of their genomic motifs. The underlying mechanism of this selectivity is not well understood. Here, we design a high-throughput assay called ChIP-ISO to systematically dissect sequence features affecting the binding specificity of a classic PF, FOXA1. Combining ChIP-ISO with in vitro and neural network analyses, we find that 1) FOXA1 binding is strongly affected by co-binding TFs AP-1 and CEBPB, 2) FOXA1 and AP-1 show binding cooperativity in vitro, 3) FOXA1's binding is determined more by local sequences than chromatin context, including eu-/heterochromatin, and 4) AP-1 is partially responsible for differential binding of FOXA1 in different cell types. Our study presents a framework for elucidating genetic rules underlying PF binding specificity and reveals a mechanism for context-specific regulation of its binding.

eRNA co-expression network uncovers TF dependency and convergent cooperativity

Enhancer RNAs (eRNAs) are non-coding RNAs produced by transcriptional enhancers that are highly correlated with their activity. Using a capped nascent RNA sequencing (PRO-cap) dataset in human lymphoblastoid cell lines across 67 individuals, we identified inter-individual variation in the expression of over 80 thousand transcribed transcriptional regulatory elements (tTREs), in both enhancers and promoters. Co-expression analysis of eRNAs from tTREs across individuals revealed how enhancers are associated with each other and with promoters. Mid- to long-range co-expression showed a distance-dependent decay that was modified by TF occupancy. In particular, we found a class of "bivalent" TFs, including Cohesin, that both facilitate and isolate the interaction between enhancers and/or promoters, depending on their topology. At short distances, we observed strand-specific correlations between nearby eRNAs in both convergent and divergent orientations. Our results support a cooperative model of convergent eRNAs, consistent with eRNAs facilitating adjacent enhancers rather than interfering with each other. Therefore, our approach to infer functional interactions from co-expression analyses provided novel insights into the principles of enhancer interactions as a function of distance, orientation, and binding landscapes of TFs.

International Union of Basic and Clinical Pharmacology CXIII: Nuclear Receptor Superfamily-Update 2023

The NR superfamily comprises 48 transcription factors in humans that control a plethora of gene network programs involved in a wide range of physiologic processes. This review will summarize and discuss recent progress in NR biology and drug development derived from integrating various approaches, including biophysical techniques, structural studies, and translational investigation. We also highlight how defective NR signaling results in various diseases and disorders and how NRs can be targeted for therapeutic intervention via modulation via binding to synthetic lipophilic ligands. Furthermore, we also review recent studies that improved our understanding of NR structure and signaling. SIGNIFICANCE STATEMENT: Nuclear receptors (NRs) are ligand-regulated transcription factors that are critical regulators of myriad physiological processes. NRs serve as receptors for an array of drugs, and in this review, we provide an update on recent research into the roles of these drug targets.

Emerging insights into enhancer biology and function

Cell type-specific gene expression is coordinated by DNA-encoded enhancers and the transcription factors (TFs) that bind to them in a sequence-specific manner. As such, these enhancers and TFs are critical mediators of normal development and altered enhancer or TF function is associated with the development of diseases such as cancer. While initially defined by their ability to activate gene transcription in reporter assays, putative enhancer elements are now frequently defined by their unique chromatin features including DNase hypersensitivity and transposase accessibility, bidirectional enhancer RNA (eRNA) transcription, CpG hypomethylation, high H3K27ac and H3K4me1, sequence-specific transcription factor binding, and co-factor recruitment. Identification of these chromatin features through sequencing-based assays has revolutionized our ability to identify enhancer elements on a genome-wide scale, and genome-wide functional assays are now capitalizing on this information to greatly expand our understanding of how enhancers function to provide spatiotemporal coordination of gene expression programs. Here, we highlight recent technological advances that are providing new insights into the molecular mechanisms by which these critical cis-regulatory elements function in gene control. We pay particular attention to advances in our understanding of enhancer transcription, enhancer-promoter syntax, 3D organization and biomolecular condensates, transcription factor and co-factor dependencies, and the development of genome-wide functional enhancer screens.

Widespread effects of DNA methylation and intra-motif dependencies revealed by novel transcription factor binding models

Several studies suggested that transcription factor (TF) binding to DNA may be impaired or enhanced by DNA methylation. We present MeDeMo, a toolbox for TF motif analysis that combines information about DNA methylation with models capturing intra-motif dependencies. In a large-scale study using ChIP-seq data for 335 TFs, we identify novel TFs that show a binding behaviour associated with DNA methylation. Overall, we find that the presence of CpG methylation decreases the likelihood of binding for the majority of methylation-associated TFs. For a considerable subset of TFs, we show that intra-motif dependencies are pivotal for accurately modelling the impact of DNA methylation on TF binding. We illustrate that the novel methylation-aware TF binding models allow to predict differential ChIP-seq peaks and improve the genome-wide analysis of TF binding. Our work indicates that simplistic models that neglect the effect of DNA methylation on DNA binding may lead to systematic underperformance for methylation-associated TFs.

Transcription factor-binding k-mer analysis clarifies the cell type dependency of binding specificities and cis-regulatory SNPs in humans

BACKGROUND

Transcription factors (TFs) exhibit heterogeneous DNA-binding specificities in individual cells and whole organisms under natural conditions, and de novo motif discovery usually provides multiple motifs, even from a single chromatin immunoprecipitation-sequencing (ChIP-seq) sample. Despite the accumulation of ChIP-seq data and ChIP-seq-derived motifs, the diversity of DNA-binding specificities across different TFs and cell types remains largely unexplored.

RESULTS

Here, we applied MOCCS2, our k-mer-based motif discovery method, to a collection of human TF ChIP-seq samples across diverse TFs and cell types, and systematically computed profiles of TF-binding specificity scores for all k-mers. After quality control, we compiled a set of TF-binding specificity score profiles for 2,976 high-quality ChIP-seq samples, comprising 473 TFs and 398 cell types. Using these high-quality samples, we confirmed that the k-mer-based TF-binding specificity profiles reflected TF- or TF-family dependent DNA-binding specificities. We then compared the binding specificity scores of ChIP-seq samples with the same TFs but with different cell type classes and found that half of the analyzed TFs exhibited differences in DNA-binding specificities across cell type classes. Additionally, we devised a method to detect differentially bound k-mers between two ChIP-seq samples and detected k-mers exhibiting statistically significant differences in binding specificity scores. Moreover, we demonstrated that differences in the binding specificity scores between k-mers on the reference and alternative alleles could be used to predict the effect of variants on TF binding, as validated by in vitro and in vivo assay datasets. Finally, we demonstrated that binding specificity score differences can be used to interpret disease-associated non-coding single-nucleotide polymorphisms (SNPs) as TF-affecting SNPs and provide candidates responsible for TFs and cell types.

CONCLUSIONS

Our study provides a basis for investigating the regulation of gene expression in a TF-, TF family-, or cell-type-dependent manner. Furthermore, our differential analysis of binding-specificity scores highlights noncoding disease-associated variants in humans.

Predicting regional somatic mutation rates using DNA motifs

How the locus-specificity of epigenetic modifications is regulated remains an unanswered question. A contributing mechanism is that epigenetic enzymes are recruited to specific loci by DNA binding factors recognizing particular sequence motifs (referred to as epi-motifs). Using these motifs to predict biological outputs depending on local epigenetic state such as somatic mutation rates would confirm their functionality. Here, we used DNA motifs including known TF motifs and epi-motifs as a surrogate of epigenetic signals to predict somatic mutation rates in 13 cancers at an average 23kbp resolution. We implemented an interpretable neural network model, called contextual regression, to successfully learn the universal relationship between mutations and DNA motifs, and uncovered motifs that are most impactful on the regional mutation rates such as TP53 and epi-motifs associated with H3K9me3. Furthermore, we identified genomic regions with significantly higher mutation rates than the expected values in each individual tumor and demonstrated that such cancer-related regions can accurately predict cancer types. Interestingly, we found that the same mutation signatures often have different contributions to cancer-related and cancer-independent regions, and we also identified the motifs with the most contribution to each mutation signature.

Physical interaction between MSL2 and CLAMP assures direct cooperativity and prevents competition at composite binding sites

MSL2, the DNA-binding subunit of the Drosophila dosage compensation complex, cooperates with the ubiquitous protein CLAMP to bind MSL recognition elements (MREs) on the X chromosome. We explore the nature of the cooperative binding to these GA-rich, composite sequence elements in reconstituted naïve embryonic chromatin. We found that the cooperativity requires physical interaction between both proteins. Remarkably, disruption of this interaction does not lead to indirect, nucleosome-mediated cooperativity as expected, but to competition. The protein interaction apparently not only increases the affinity for composite binding sites, but also locks both proteins in a defined dimeric state that prevents competition. High Affinity Sites of MSL2 on the X chromosome contain variable numbers of MREs. We find that the cooperation between MSL2/CLAMP is not influenced by MRE clustering or arrangement, but happens largely at the level of individual MREs. The sites where MSL2/CLAMP bind strongly in vitro locate to all chromosomes and show little overlap to an expanded set of X-chromosomal MSL2 in vivo binding sites generated by CUT&RUN. Apparently, the intrinsic MSL2/CLAMP cooperativity is limited to a small selection of potential sites in vivo. This restriction must be due to components missing in our reconstitution, such as roX2 lncRNA.

The architecture of binding cooperativity between densely bound transcription factors

The binding of transcription factors (TFs) along genomes is restricted to a subset of sites containing their preferred motifs. TF-binding specificity is often attributed to the co-binding of interacting TFs; however, apart from specific examples, this model remains untested. Here, we define dependencies among budding yeast TFs that localize to overlapping promoters by profiling the genome-wide consequences of co-depleting multiple TFs. We describe unidirectional interactions, revealing Msn2 as a central factor allowing TF binding at its target promoters. By contrast, no case of mutual cooperation was observed. Particularly, Msn2 retained binding at its preferred promoters upon co-depletion of fourteen similarly bound TFs. Overall, the consequences of TF co-depletions were moderate, limited to a subset of promoters, and failed to explain the role of regions outside the DNA-binding domain in directing TF-binding preferences. Our results call for re-evaluating the role of cooperative interactions in directing TF-binding preferences.

The role of transcript regions and amino acid choice in nucleosome positioning

Eukaryotic DNA is organized and compacted in a string of nucleosomes, DNA-wrapped protein cylinders. The positions of nucleosomes along DNA are not random but show well-known base pair sequence preferences that result from the sequence-dependent elastic and geometric properties of the DNA double helix. Here, we focus on DNA around transcription start sites, which are known to typically attract nucleosomes in multicellular life forms through their high GC content. We aim to understand how these GC signals, as observed in genome-wide averages, are produced and encoded through different genomic regions (mainly 5' UTRs, coding exons, and introns). Our study uses a bioinformatics approach to decompose the genome-wide GC signal into between-region and within-region signals. We find large differences in GC signal contributions between vertebrates and plants and, remarkably, even between closely related species. Introns contribute most to the GC signal in vertebrates, while in plants the exons dominate. Further, we find signal strengths stronger on DNA than on mRNA, suggesting a biological function of GC signals along the DNA itself, as is the case for nucleosome positioning. Finally, we make the surprising discovery that both the choice of synonymous codons and amino acids contribute to the nucleosome positioning signal.

Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation

Despite the recent explosion in genome-wide studies in chromatin and gene regulation, we are still far from extracting a set of genetic rules that can predict the function of the regulatory genome. One major reason for this deficiency is that gene regulation is a multi-layered process that involves an enormous variable space, which cannot be fully explored using native genomes. This problem can be partially solved by introducing synthetic DNA libraries into cells, a method that can test the regulatory roles of thousands to millions of sequences with limited variables. Here, we review recent applications of this method to study transcription factor (TF) binding, nucleosome positioning, and transcriptional activity. We discuss the design principles, experimental procedures, and major findings from these studies and compare the pros and cons of different approaches.

Dynamic nucleosome remodeling mediated by YY1 underlies early mouse development

Nucleosome positioning can alter the accessibility of DNA-binding proteins to their cognate DNA elements, and thus its precise control is essential for cell identity and function. Mammalian preimplantation embryos undergo temporal changes in gene expression and cell potency, suggesting the involvement of dynamic epigenetic control during this developmental phase. However, the dynamics of nucleosome organization during early development are poorly understood. In this study, using a low-input MNase-seq method, we show that nucleosome positioning is globally obscure in zygotes but becomes well defined during subsequent development. Down-regulation of the chromatin assembly in embryonic stem cells can partially reverse nucleosome organization into a zygote-like pattern, suggesting a possible link between the chromatin assembly pathway and fuzzy nucleosomes in zygotes. We also reveal that YY1, a zinc finger-containing transcription factor expressed upon zygotic genome activation, regulates the de novo formation of well-positioned nucleosome arrays at the regulatory elements through identifying YY1-binding sites in eight-cell embryos. The YY1-binding regions acquire H3K27ac enrichment around the eight-cell and morula stages, and YY1 depletion impairs the morula-to-blastocyst transition. Thus, our study delineates the remodeling of nucleosome organization and its underlying mechanism during early mouse development.

Histone modifications regulate pioneer transcription factor cooperativity

Pioneer transcription factors have the ability to access DNA in compacted chromatin1. Multiple transcription factors can bind together to a regulatory element in a cooperative way, and cooperation between the pioneer transcription factors OCT4 (also known as POU5F1) and SOX2 is important for pluripotency and reprogramming2-4. However, the molecular mechanisms by which pioneer transcription factors function and cooperate on chromatin remain unclear. Here we present cryo-electron microscopy structures of human OCT4 bound to a nucleosome containing human LIN28B or nMATN1 DNA sequences, both of which bear multiple binding sites for OCT4. Our structural and biochemistry data reveal that binding of OCT4 induces changes to the nucleosome structure, repositions the nucleosomal DNA and facilitates cooperative binding of additional OCT4 and of SOX2 to their internal binding sites. The flexible activation domain of OCT4 contacts the N-terminal tail of histone H4, altering its conformation and thus promoting chromatin decompaction. Moreover, the DNA-binding domain of OCT4 engages with the N-terminal tail of histone H3, and post-translational modifications at H3K27 modulate DNA positioning and affect transcription factor cooperativity. Thus, our findings suggest that the epigenetic landscape could regulate OCT4 activity to ensure proper cell programming.

Potent and uniform fetal hemoglobin induction via base editing

Inducing fetal hemoglobin (HbF) in red blood cells can alleviate β-thalassemia and sickle cell disease. We compared five strategies in CD34+ hematopoietic stem and progenitor cells, using either Cas9 nuclease or adenine base editors. The most potent modification was adenine base editor generation of γ-globin -175A>G. Homozygous -175A>G edited erythroid colonies expressed 81 ± 7% HbF versus 17 ± 11% in unedited controls, whereas HbF levels were lower and more variable for two Cas9 strategies targeting a BCL11A binding motif in the γ-globin promoter or a BCL11A erythroid enhancer. The -175A>G base edit also induced HbF more potently than a Cas9 approach in red blood cells generated after transplantation of CD34+ hematopoietic stem and progenitor cells into mice. Our data suggest a strategy for potent, uniform induction of HbF and provide insights into γ-globin gene regulation. More generally, we demonstrate that diverse indels generated by Cas9 can cause unexpected phenotypic variation that can be circumvented by base editing.

Novel mouse model of Weaver syndrome displays overgrowth and excess osteogenesis reversible with KDM6A/6B inhibition

Weaver syndrome is a Mendelian disorder of the epigenetic machinery (MDEM) caused by germline pathogenic variants in EZH2, which encodes the predominant H3K27 methyltransferase and key enzymatic component of Polycomb repressive complex 2 (PRC2). Weaver syndrome is characterized by striking overgrowth and advanced bone age, intellectual disability, and distinctive facies. We generated a mouse model for the most common Weaver syndrome missense variant, EZH2 p.R684C. Ezh2R684C/R684C mouse embryonic fibroblasts (MEFs) showed global depletion of H3K27me3. Ezh2R684C/+ mice had abnormal bone parameters indicative of skeletal overgrowth, and Ezh2R684C/+ osteoblasts showed increased osteogenic activity. RNA-seq comparing osteoblasts differentiated from Ezh2R684C/+ and Ezh2+/+ bone marrow mesenchymal stem cells (BM-MSCs) indicated collective dysregulation of the BMP pathway and osteoblast differentiation. Inhibition of the opposing H3K27 demethylases Kdm6a/6b substantially reversed the excessive osteogenesis in Ezh2R684C/+ cells both at the transcriptional and phenotypic levels. This supports both the ideas that writers and erasers of histone marks exist in a fine balance to maintain epigenome state, and that epigenetic modulating agents have therapeutic potential for the treatment of MDEMs.

The molecular grammar of protein disorder guiding genome-binding locations

Intrinsically disordered regions (IDRs) direct transcription factors (TFs) towards selected genomic occurrences of their binding motif, as exemplified by budding yeast's Msn2. However, the sequence basis of IDR-directed TF binding selectivity remains unknown. To reveal this sequence grammar, we analyze the genomic localizations of >100 designed IDR mutants, each carrying up to 122 mutations within this 567-AA region. Our data points at multivalent interactions, carried by hydrophobic-mostly aliphatic-residues dispersed within a disordered environment and independent of linear sequence motifs, as the key determinants of Msn2 genomic localization. The implications of our results for the mechanistic basis of IDR-based TF binding preferences are discussed.

Integration site-dependent HIV-1 promoter activity shapes host chromatin conformation

HIV-1 integration introduces ectopic transcription factor binding sites into host chromatin. We postulate that the integrated provirus serves as an ectopic enhancer that recruits additional transcription factors to the integration locus, increases chromatin accessibility, changes 3D chromatin interactions, and enhances both retroviral and host gene expression. We used four well-characterized HIV-1-infected cell line clones having unique integration sites and low to high levels of HIV-1 expression. Using single-cell DOGMA-seq, which captured the heterogeneity of HIV-1 expression and host chromatin accessibility, we found that HIV-1 transcription correlated with HIV-1 accessibility and host chromatin accessibility. HIV-1 integration increased local host chromatin accessibility within an ∼5- to 30-kb distance. CRISPRa- and CRISPRi-mediated HIV-1 promoter activation and inhibition confirmed integration site-dependent HIV-1-driven changes of host chromatin accessibility. HIV-1 did not drive chromatin confirmation changes at the genomic level (by Hi-C) or the enhancer connectome (by H3K27ac HiChIP). Using 4C-seq to interrogate HIV-1-chromatin interactions, we found that HIV-1 interacted with host chromatin ∼100-300 kb from the integration site. By identifying chromatin regions having both increased transcription factor activity (by ATAC-seq) and HIV-1-chromatin interaction (by 4C-seq), we identified enrichment of ETS, RUNT, and ZNF-family transcription factor binding that may mediate HIV-1-host chromatin interactions. Our study has found that HIV-1 promoter activity increases host chromatin accessibility, and HIV-1 interacted with host chromatin within the existing chromatin boundaries in an integration site-dependent manner.

Prediction of mammalian tissue-specific CLOCK-BMAL1 binding to E-box DNA motifs

The Brain and Muscle ARNTL-Like 1 protein (BMAL1) forms a heterodimer with either Circadian Locomotor Output Cycles Kaput (CLOCK) or Neuronal PAS domain protein 2 (NPAS2) to act as a master regulator of the mammalian circadian clock gene network. The dimer binds to E-box gene regulatory elements on DNA, activating downstream transcription of clock genes. Identification of transcription factor binding sites and genomic features that correlate to DNA binding by BMAL1 is a challenging problem, given that CLOCK-BMAL1 or NPAS2-BMAL1 bind to several distinct binding motifs (CANNTG) on DNA. Using three different types of tissue-specific machine learning models with features based on (1) DNA sequence, (2) DNA sequence plus DNA shape, and (3) DNA sequence and shape plus histone modifications, we developed an interpretable predictive model of genome-wide BMAL1 binding to E-box motifs and dissected the mechanisms underlying BMAL1-DNA binding. Our results indicated that histone modifications, the local shape of the DNA, and the flanking sequence of the E-box motif are sufficient predictive features for BMAL1-DNA binding. Our models also provide mechanistic insights into tissue specificity of DNA binding by BMAL1.

Evolutionary constraint and innovation across hundreds of placental mammals

Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.

Histone modifications regulate pioneer transcription factor binding and cooperativity

Pioneer transcription factors have the ability to access DNA in compacted chromatin. Multiple transcription factors can bind together to a regulatory element in a cooperative way and cooperation between pioneer transcription factors Oct4 and Sox2 is important for pluripotency and reprogramming. However, the molecular mechanisms by which pioneer transcription factors function and cooperate remain unclear. Here we present cryo-EM structures of human Oct4 bound to a nucleosome containing human Lin28B and nMatn1 DNA sequences, which bear multiple binding sites for Oct4. Our structural and biochemistry data reveal that Oct4 binding induces changes to the nucleosome structure, repositions the nucleosomal DNA and facilitates cooperative binding of additional Oct4 and of Sox2 to their internal binding sites. The flexible activation domain of Oct4 contacts the histone H4 N-terminal tail, altering its conformation and thus promoting chromatin decompaction. Moreover, the DNA binding domain of Oct4 engages with histone H3 N-terminal tail, and posttranslational modifications at H3K27 modulate DNA positioning and affect transcription factor cooperativity. Thus, our data show that the epigenetic landscape can regulate Oct4 activity to ensure proper cell reprogramming.

Revealing eRNA interactions: TF dependency and convergent cooperativity

Enhancer RNAs (eRNAs) are non-coding RNAs produced from transcriptional enhancers that are highly correlated with their activities. Using capped nascent RNA sequencing (PRO-cap) dataset in human lymphoblastoid cell lines across individuals, we identified inter-individual variation of expression in over 80 thousand transcribed transcriptional regulatory elements (tTREs), in both enhancers and promoters. Co-expression analysis of eRNAs from tTREs across individuals revealed how enhancers interact with each other and with promoters. Mid-to-long range interactions showed distance-dependent decay, which was modified by TF occupancy. In particular, we found a class of 'bivalent' TFs, including Cohesin, which both facilitates and insulates the interaction between enhancers and/or promoters depending on the topology. In short ranges, we observed strand specific interactions between nearby eRNAs in both convergent or divergent orientations. Our finding supports a cooperative convergent eRNA model, which is compatible with eRNA remodeling neighboring enhancers rather than interfering with each other. Therefore, our approach to infer functional interactions from co-expression analyses provided novel insights into the principles of enhancer interactions depending on the distance, orientation, and the binding landscapes of TFs.

Deciphering the multi-scale, quantitative cis-regulatory code

Uncovering the cis-regulatory code that governs when and how much each gene is transcribed in a given genome and cellular state remains a central goal of biology. Here, we discuss major layers of regulation that influence how transcriptional outputs are encoded by DNA sequence and cellular context. We first discuss how transcription factors bind specific DNA sequences in a dosage-dependent and cooperative manner and then proceed to the cofactors that facilitate transcription factor function and mediate the activity of modular cis-regulatory elements such as enhancers, silencers, and promoters. We then consider the complex and poorly understood interplay of these diverse elements within regulatory landscapes and its relationships with chromatin states and nuclear organization. We propose that a mechanistically informed, quantitative model of transcriptional regulation that integrates these multiple regulatory layers will be the key to ultimately cracking the cis-regulatory code.

Retrotransposon insertions associated with risk of neurologic and psychiatric diseases

Transposable elements (TEs) are active in neuronal cells raising the question whether TE insertions contribute to risk of neuropsychiatric disease. While genome-wide association studies (GWAS) serve as a tool to discover genetic loci associated with neuropsychiatric diseases, unfortunately GWAS do not directly detect structural variants such as TEs. To examine the role of TEs in psychiatric and neurologic disease, we evaluated 17,000 polymorphic TEs and find 76 are in linkage disequilibrium with disease haplotypes (P < 10-6 ) defined by GWAS. From these 76 polymorphic TEs, we identify potentially causal candidates based on having insertions in genomic regions of regulatory chromatin and on having associations with altered gene expression in brain tissues. We show that lead candidate insertions have regulatory effects on gene expression in human neural stem cells altering the activity of a minimal promoter. Taken together, we identify 10 polymorphic TE insertions that are potential candidates on par with other variants for having a causal role in neurologic and psychiatric disorders.

A Method for Predicting DNA Motif Length Based On Deep Learning

A DNA motif is a sequence pattern shared by the DNA sequence segments that bind to a specific protein. Discovering motifs in a given DNA sequence dataset plays a vital role in studying gene expression regulation. As an important attribute of the DNA motif, the motif length directly affects the quality of the discovered motifs. How to determine the motif length more accurately remains a difficult challenge to be solved. We propose a new motif length prediction scheme named MotifLen by using supervised machine learning. First, a method of constructing sample data for predicting the motif length is proposed. Secondly, a deep learning model for motif length prediction is constructed based on the convolutional neural network. Then, the methods of applying the proposed prediction model based on a motif found by an existing motif discovery algorithm are given. The experimental results show that i) the prediction accuracy of MotifLen is more than 90% on the validation set and is significantly higher than that of the compared methods on real datasets, ii) MotifLen can successfully optimize the motifs found by the existing motif discovery algorithms, and iii) it can effectively improve the time performance of some existing motif discovery algorithms.

Impact on the Clinical Evolution of Patients with COVID-19 Pneumonia and the Participation of the NFE2L2/KEAP1 Polymorphisms in Regulating SARS-CoV-2 Infection

In patients with severe pneumonia due to COVID-19, the deregulation of oxidative stress is present. Nuclear erythroid factor 2 (NRF2) is regulated by KEAP1, and NRF2 regulates the expression of genes such as NFE2L2-KEAP1, which are involved in cellular defense against oxidative stress. In this study, we analyzed the participation of the polymorphisms of NFE2L2 and KEAP1 genes in the mechanisms of damage in lung disease patients with SARS-CoV-2 infection. Patients with COVID-19 and a control group were included. Organ dysfunction was evaluated using SOFA. SARS-CoV-2 infection was confirmed and classified as moderate or severe by ventilatory status and by the Berlin criteria for acute respiratory distress syndrome. SNPs in the gene locus for NFE2L2, rs2364723C>G, and KEAP1, rs9676881A>G, and rs34197572C>T were determined by qPCR. We analyzed 110 individuals with SARS-CoV-2 infection: 51 with severe evolution and 59 with moderate evolution. We also analyzed 111 controls. Significant differences were found for rs2364723 allele G in severe cases vs. controls (p = 0.02); for the rs9676881 allele G in moderate cases vs. controls (p = 0.04); for the rs34197572 allele T in severe cases vs. controls (p = 0.001); and in severe vs. moderate cases (p = 0.004). Our results showed that NFE2L2 rs2364723C>G allele G had a protective effect against severe COVID-19, while KEAP1 rs9676881A>G allele G and rs34197572C>T minor allele T were associated with more aggressive stages of COVID-19.

Computational prediction and characterization of cell-type-specific and shared binding sites

MOTIVATION

Cell-type-specific gene expression is maintained in large part by transcription factors (TFs) selectively binding to distinct sets of sites in different cell types. Recent research works have provided evidence that such cell-type-specific binding is determined by TF's intrinsic sequence preferences, cooperative interactions with co-factors, cell-type-specific chromatin landscapes and 3D chromatin interactions. However, computational prediction and characterization of cell-type-specific and shared binding sites is rarely studied.

RESULTS

In this article, we propose two computational approaches for predicting and characterizing cell-type-specific and shared binding sites by integrating multiple types of features, in which one is based on XGBoost and another is based on convolutional neural network (CNN). To validate the performance of our proposed approaches, ChIP-seq datasets of 10 binding factors were collected from the GM12878 (lymphoblastoid) and K562 (erythroleukemic) human hematopoietic cell lines, each of which was further categorized into cell-type-specific (GM12878- and K562-specific) and shared binding sites. Then, multiple types of features for these binding sites were integrated to train the XGBoost- and CNN-based models. Experimental results show that our proposed approaches significantly outperform other competing methods on three classification tasks. Moreover, we identified independent feature contributions for cell-type-specific and shared sites through SHAP values and explored the ability of the CNN-based model to predict cell-type-specific and shared binding sites by excluding or including DNase signals. Furthermore, we investigated the generalization ability of our proposed approaches to different binding factors in the same cellular environment.

AVAILABILITY AND IMPLEMENTATION

The source code is available at: https://github.com/turningpoint1988/CSSBS.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we develop Griffin, a framework for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing data. Griffin employs a GC correction procedure tailored to variable cfDNA fragment sizes, which generates a better representation of chromatin accessibility and improves the accuracy of cancer detection and tumor subtype classification. We demonstrate estrogen receptor subtyping from cfDNA in metastatic breast cancer. We predict estrogen receptor subtype in 139 patients with at least 5% detectable circulating tumor DNA with an area under the receive operator characteristic curve (AUC) of 0.89 and validate performance in independent cohorts (AUC = 0.96). In summary, Griffin is a framework for accurate tumor subtyping and can be generalizable to other cancer types for precision oncology applications.