Structural perspective of cooperative transcription factor binding

A large-scale cancer-specific protein-DNA interaction network

Cancer development and progression are generally associated with gene dysregulation, often resulting from changes in the transcription factor (TF) sequence or expression. Identifying key TFs involved in cancer gene regulation provides a framework for potential new therapeutics. This study presents a large-scale cancer gene TF-DNA interaction network, as well as an extensive promoter clone resource for future studies. Highly connected TFs bind to promoters of genes associated with either good or poor cancer prognosis, suggesting that strategies aimed at shifting gene expression balance between these two prognostic groups may be inherently complex. However, we identified potential for oncogene-targeted therapeutics, with half of the tested oncogenes being potentially repressed by influencing specific activators or bifunctional TFs. Finally, we investigate the role of intrinsically disordered regions within the key cancer-related TF ESR1 in DNA binding and transcriptional activity, and found that these regions can have complex trade-offs in TF function. Altogether, our study broadens our knowledge of the TFs involved in cancer gene regulation and provides a valuable resource for future studies and therapeutics.

GraphPro: An interpretable graph neural network-based model for identifying promoters in multiple species

Promoters are DNA sequences that bind with RNA polymerase to initiate transcription, regulating this process through interactions with transcription factors. Accurate identification of promoters is crucial for understanding gene expression regulation mechanisms and developing therapeutic approaches for various diseases. However, experimental techniques for promoter identification are often expensive, time-consuming, and inefficient, necessitating the development of accurate and efficient computational models for this task. Enhancing the model's ability to recognize promoters across multiple species and improving its interpretability pose significant challenges. In this study, we introduce a novel interpretable model based on graph neural networks, named GraphPro, for multi-species promoter identification. Initially, we encode the sequences using k-tuple nucleotide frequency pattern, dinucleotide physicochemical properties, and dna2vec. Subsequently, we construct two feature extraction modules based on convolutional neural networks and graph neural networks. These modules aim to extract specific motifs from the promoters, learn their dependencies, and capture the underlying structural features of the promoters, providing a more comprehensive representation. Finally, a fully connected neural network predicts whether the input sequence is a promoter. We conducted extensive experiments on promoter datasets from eight species, including Human, Mouse, and Escherichia coli. The experimental results show that the average Sn, Sp, Acc and MCC values of GraphPro are 0.9123, 0.9482, 0.8840 and 0.7984, respectively. Compared with previous promoter identification methods, GraphPro not only achieves better recognition accuracy on multiple species, but also outperforms all previous methods in cross-species prediction ability. Furthermore, by visualizing GraphPro's decision process and analyzing the sequences matching the transcription factor binding motifs captured by the model, we validate its significant advantages in biological interpretability. The source code for GraphPro is available at https://github.com/liuliwei1980/GraphPro.

Structural insights into the cooperative nucleosome recognition and chromatin opening by FOXA1 and GATA4

Mouse FOXA1 and GATA4 are prototypes of pioneer factors, initiating liver cell development by binding to the N1 nucleosome in the enhancer of the ALB1 gene. Using cryoelectron microscopy (cryo-EM), we determined the structures of the free N1 nucleosome and its complexes with FOXA1 and GATA4, both individually and in combination. We found that the DNA-binding domains of FOXA1 and GATA4 mainly recognize the linker DNA and an internal site in the nucleosome, respectively, whereas their intrinsically disordered regions interact with the acidic patch on histone H2A-H2B. FOXA1 efficiently enhances GATA4 binding by repositioning the N1 nucleosome. In vivo DNA editing and bioinformatics analyses suggest that the co-binding mode of FOXA1 and GATA4 plays important roles in regulating genes involved in liver cell functions. Our results reveal the mechanism whereby FOXA1 and GATA4 cooperatively bind to the nucleosome through nucleosome repositioning, opening chromatin by bending linker DNA and obstructing nucleosome packing.

Regulation of the Lewis Blood Group Antigen Expression: A Literature Review Supplemented with Computational Analysis

Background

The Lewis (Le) blood group system, unlike most other blood groups, is not defined by antigens produced internally to the erythrocytes and their precursors but rather by glycan antigens adsorbed on to the erythrocyte membrane from the plasma. These oligosaccharides are synthesized by the two fucosyltransferases FUT2 and FUT3 mainly in epithelial cells of the digestive tract and transferred to the plasma. At their place of synthesis, some Lewis blood group carbohydrate antigen variants also seem to be involved in various gastrointestinal malignancies. However, relatively little is known about the transcriptional regulation of FUT2 and FUT3.

Summary

To address this question, we screened existing literature and additionally used in silico prediction tools to identify novel candidate regulators for FUT2 and FUT3 and combine these findings with already known data on their regulation. With this approach, we were able to describe a variety of transcription factors, RNA binding proteins and microRNAs, which increase FUT2 and FUT3 transcription and translation upon interaction.

Key Messages

Understanding the regulation of FUT2 and FUT3 is crucial to fully understand the blood group system Lewis (ISBT 007 LE) phenotypes, to shed light on the role of the different Lewis antigens in various pathologies, and to identify potential new diagnostic targets for these diseases.

How Transcription Factor Clusters Shape the Transcriptional Landscape

In eukaryotic cells, gene transcription typically occurs in discrete periods of promoter activity, interspersed with intervals of inactivity. This pattern deviates from simple stochastic events and warrants a closer examination of the molecular interactions that activate the promoter. Recent studies have identified transcription factor (TF) clusters as key precursors to transcriptional bursting. Often, these TF clusters form at chromatin segments that are physically distant from the promoter, making changes in chromatin conformation crucial for promoter-TF cluster interactions. In this review, I explore the formation and constituents of TF clusters, examining how the dynamic interplay between chromatin architecture and TF clustering influences transcriptional bursting. Additionally, I discuss techniques for visualizing TF clusters and provide an outlook on understanding the remaining gaps in this field.

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.

Skipping events impose repeated binding attempts: profound kinetic implications of protein-DNA conformational changes

The kinetics of protein-DNA recognition, along with its thermodynamic properties, including affinity and specificity, play a central role in shaping biological function. Protein-DNA recognition kinetics are characterized by two key elements: the time taken to locate the target site amid various nonspecific alternatives; and the kinetics involved in the recognition process, which may necessitate overcoming an energetic barrier. In this study, we developed a coarse-grained (CG) model to investigate interactions between a transcription factor called the sex-determining region Y (SRY) protein and DNA, in order to probe how DNA conformational changes affect SRY-DNA recognition and binding kinetics. We find that, not only does a requirement for such a conformational DNA transition correspond to a higher energetic barrier for binding and therefore slower kinetics, it may further impede the recognition kinetics by increasing unsuccessful binding events (skipping events) where the protein partially binds its DNA target site but fails to form the specific protein-DNA complex. Such skipping events impose the need for additional cycles protein search of nonspecific DNA sites, thus significantly extending the overall recognition time. Our results highlight a trade-off between the speed with which the protein scans nonspecific DNA and the rate at which the protein recognizes its specific target site. Finally, we examine molecular approaches potentially adopted by natural systems to enhance protein-DNA recognition despite its intrinsically slow kinetics.

Glucocorticoid receptor action in prostate cancer: the role of transcription factor crosstalk

Prostate cancer is one of the most prevalent malignancies and is primarily driven by aberrant androgen receptor (AR) signaling. While AR-targeted therapies form the cornerstone of prostate cancer treatment, they often inadvertently activate compensatory pathways, leading to therapy resistance. This resistance is frequently mediated through changes in transcription factor (TF) crosstalk, reshaping gene regulatory programs and ultimately weakening treatment efficacy. Consequently, investigating TF interactions has become crucial for understanding the mechanisms driving therapy-resistant cancers. Recent evidence has highlighted the crosstalk between the glucocorticoid receptor (GR) and AR, demonstrating that GR can induce prostate cancer therapy resistance by replacing the inactivated AR, thereby becoming a driver of the disease. In addition to this oncogenic role, GR has also been shown to act as a tumor suppressor in prostate cancer. Owing to this dual role and the widespread use of glucocorticoids as adjuvant therapy, it is essential to understand GR's actions across different stages of prostate cancer development. In this review, we explore the current knowledge of GR in prostate cancer, with a specific focus on its crosstalk with other TFs. GR can directly and indirectly interact with a variety of TFs, and these interactions vary significantly depending on the type of prostate cancer cells. By highlighting these crosstalk interactions, we aim to provide insights that can guide the research and development of new GR-targeted therapies to mitigate its harmful effects in prostate cancer.

A high-throughput synthetic biology approach for studying combinatorial chromatin-based transcriptional regulation

The construction of synthetic gene circuits requires the rational combination of multiple regulatory components, but predicting their behavior can be challenging due to poorly understood component interactions and unexpected emergent behaviors. In eukaryotes, chromatin regulators (CRs) are essential regulatory components that orchestrate gene expression. Here, we develop a screening platform to investigate the impact of CR pairs on transcriptional activity in yeast. We construct a combinatorial library consisting of over 1,900 CR pairs and use a high-throughput workflow to characterize the impact of CR co-recruitment on gene expression. We recapitulate known interactions and discover several instances of CR pairs with emergent behaviors. We also demonstrate that supervised machine learning models trained with low-dimensional amino acid embeddings accurately predict the impact of CR co-recruitment on transcriptional activity. This work introduces a scalable platform and machine learning approach that can be used to study how networks of regulatory components impact gene expression.

Lineage regulators TFAP2C and NR5A2 function as bipotency activators in totipotent embryos

During the first lineage segregation, a mammalian totipotent embryo differentiates into the inner cell mass (ICM) and trophectoderm (TE). However, how transcription factors (TFs) regulate this earliest cell-fate decision in vivo remains elusive, with their regulomes primarily inferred from cultured cells. Here, we investigated the TF regulomes during the first lineage specification in early mouse embryos, spanning the pre-initiation, initiation, commitment, and maintenance phases. Unexpectedly, we found that TFAP2C, a trophoblast regulator, bound and activated both early TE and inner cell mass (ICM) genes at the totipotent (two- to eight-cell) stages ('bipotency activation'). Tfap2c deficiency caused downregulation of early ICM genes, including Nanog, Nr5a2, and Tdgf1, and early TE genes, including Tfeb and Itgb5, in eight-cell embryos. Transcription defects in both ICM and TE lineages were also found in blastocysts, accompanied by increased apoptosis and reduced cell numbers in ICMs. Upon trophoblast commitment, TFAP2C left early ICM genes but acquired binding to late TE genes in blastocysts, where it co-bound with CDX2, and later to extra-embryonic ectoderm (ExE) genes, where it cooperatively co-occupied with the former ICM regulator SOX2. Finally, 'bipotency activation' in totipotent embryos also applied to a pluripotency regulator NR5A2, which similarly bound and activated both ICM and TE lineage genes at the eight-cell stage. These data reveal a unique transcription circuity of totipotency underpinned by highly adaptable lineage regulators.

Structure-based learning to predict and model protein-DNA interactions and transcription-factor co-operativity in cis-regulatory elements

Transcription factor (TF) binding is a key component of genomic regulation. There are numerous high-throughput experimental methods to characterize TF-DNA binding specificities. Their application, however, is both laborious and expensive, which makes profiling all TFs challenging. For instance, the binding preferences of ∼25% human TFs remain unknown; they neither have been determined experimentally nor inferred computationally. We introduce a structure-based learning approach to predict the binding preferences of TFs and the automated modelling of TF regulatory complexes. We show the advantage of using our approach over the classical nearest-neighbor prediction in the limits of remote homology. Starting from a TF sequence or structure, we predict binding preferences in the form of motifs that are then used to scan a DNA sequence for occurrences. The best matches are either profiled with a binding score or collected for their subsequent modeling into a higher-order regulatory complex with DNA. Co-operativity is modelled by: (i) the co-localization of TFs and (ii) the structural modeling of protein-protein interactions between TFs and with co-factors. We have applied our approach to automatically model the interferon-β enhanceosome and the pioneering complexes of OCT4, SOX2 (or SOX11) and KLF4 with a nucleosome, which are compared with the experimentally known structures.

Viral cis-regulatory elements as sensors of cellular states and environmental cues

To withstand a hostile cellular environment and replicate, viruses must sense, interpret, and respond to many internal and external cues. Retroviruses and DNA viruses can intercept these cues impinging on host transcription factors via cis-regulatory elements (CREs) in viral genomes, allowing them to sense and coordinate context-specific responses to varied signals. Here, we explore the characteristics of viral CREs, the classes of signals and host transcription factors that regulate them, and how this informs outcomes of viral replication, immune evasion, and latency. We propose that viral CREs constitute central hubs for signal integration from multiple pathways and that sequence variation between viral isolates can rapidly rewire sensing mechanisms, contributing to the variability observed in patient outcomes.

Molecular regulation of PPARγ/RXRα signaling by the novel cofactor ZFP407

Cofactors interacting with PPARγ can regulate adipogenesis and adipocyte metabolism by modulating the transcriptional activity and selectivity of PPARγ signaling. ZFP407 was previously demonstrated to regulate PPARγ target genes such as GLUT4, and its overexpression improved glucose homeostasis in mice. Here, using a series of molecular assays, including protein-interaction studies, mutagenesis, and ChIP-seq, ZFP407 was found to interact with the PPARγ/RXRα protein complex in the nucleus of adipocytes. Consistent with this observation, ZFP407 ChIP-seq peaks significantly overlapped with PPARγ ChIP-seq peaks, with more than half of ZFP407 peaks overlapping with PPARγ peaks. Transcription factor binding motifs enriched in these overlapping sites included CTCF, RARα/RXRγ, TP73, and ELK1, which regulate cellular development and function within adipocytes. Site-directed mutagenesis of frequent PPARγ phosphorylation or SUMOylation sites did not prevent its regulation by ZFP407, while mutagenesis of ZFP407 domains potentially necessary for RXR and PPARγ binding abrogated any impact of ZFP407 on PPARγ activity. These data suggest that ZFP407 controls the activity of PPARγ, but does so independently of post-translational modifications, likely by direct binding, establishing ZFP407 as a newly identified PPARγ cofactor. In addition, ZFP407 ChIP-seq analyses identified regions that did not overlap with PPARγ peaks. These non-overlapping peaks were significantly enriched for the transcription factor binding motifs of TBX19, PAX8, HSF4, and ZKSCAN3, which may contribute to the PPARγ-independent functions of ZFP407 in adipocytes and other cell types.

Using synthetic genome readers/regulators to interrogate chromatin processes: A brief review

Aberrant gene expression underlies numerous human ailments. Hence, developing small molecules to target and remedy dysfunctional gene regulation has been a long-standing goal at the interface of chemistry and medicine. A major challenge for designing small molecule therapeutics aimed at targeting desired genomic loci is the minimization of widescale disruption of genomic functions. To address this challenge, we rationally design polyamide-based multi-functional molecules, i.e., Synthetic Genome Readers/Regulators (SynGRs), which, by design, target distinct sequences in the genome. Herein, we briefly review how SynGRs access chromatin-bound and chromatin-free genomic sites, then highlight the methods for the study of chromatin processes using SynGRs on positioned nucleosomes in vitro or disease-causing repressive genomic loci in vivo.

Circadian regulation of stereotypic chromatin conformations at enhancers

Cooperation between the circadian transcription factor (TF) CLOCK:BMAL1 and other TFs at cis-regulatory elements (CREs) is critical to daily rhythms of transcription. Yet, the modalities of this cooperation are unclear. Here, we analyzed the co-binding of multiple TFs on single DNA molecules in mouse liver using single molecule footprinting (SMF). We found that SMF reads clustered in stereotypic chromatin states that reflect distinguishable organization of TFs and nucleosomes, and that were remarkably conserved between all samples. DNA protection at CLOCK:BMAL1 binding motif (E-box) varied between CREs, from E-boxes being solely bound by CLOCK:BMAL1 to situations where other TFs competed with CLOCK:BMAL1 for E-box binding. SMF also uncovered CLOCK:BMAL1 cooperative binding at E-boxes separated by 250 bp, which structurally altered the CLOCK:BMAL1-DNA interface. Importantly, we discovered multiple nucleosomes with E-boxes at entry/exit sites that were removed upon CLOCK:BMAL1 DNA binding, thereby promoting the formation of open chromatin states that facilitate DNA binding of other TFs and that were associated with rhythmic transcription. These results demonstrate the utility of SMF for studying how CLOCK:BMAL1 and other TFs regulate stereotypical chromatin states at CREs to promote transcription.

New role for cardiomyocyte Bmal1 in the regulation of sex-specific heart transcriptomes

It has been well established that cardiovascular diseases exhibit significant differences between sexes in both preclinical models and humans. In addition, there is growing recognition that disrupted circadian rhythms can contribute to the onset and progression of cardiovascular diseases. However little is known about sex differences between the cardiac circadian clock and circadian transcriptomes in mice. Here, we show that the the core clock genes are expressed in common in both sexes but the circadian transcriptome of the mouse heart is very sex-specific. Hearts from female mice expressed significantly more rhythmically expressed genes (REGs) than male hearts and the temporal pattern of REGs was distinctly different between sexes. We next used a cardiomyocyte-specific knock out of the core clock gene, Bmal1, to investigate its role in sex-specific gene expression in the heart. All sex differences in the circadian transcriptomes were significantly diminished with cardiomyocyte-specific loss of Bmal1. Surprisingly, loss of cardiomyocyte Bmal1 also resulted in a roughly 8-fold reduction in the number of all the differentially expressed genes between male and female hearts. We conclude that cardiomyocyte-specific Bmal1, and potentially the core clock mechanism, is vital in conferring sex-specific gene expression in the adult mouse heart.

Structural mechanism of synergistic targeting of the CX3CR1 nucleosome by PU.1 and C/EBPα

Pioneer transcription factors are vital for cell fate changes. PU.1 and C/EBPα work together to regulate hematopoietic stem cell differentiation. However, how they recognize in vivo nucleosomal DNA targets remains elusive. Here we report the structures of the nucleosome containing the mouse genomic CX3CR1 enhancer DNA and its complexes with PU.1 alone and with both PU.1 and the C/EBPα DNA binding domain. Our structures reveal that PU.1 binds the DNA motif at the exit linker, shifting 17 bp of DNA into the core region through interactions with H2A, unwrapping ~20 bp of nucleosomal DNA. C/EBPα binding, aided by PU.1's repositioning, unwraps ~25 bp of entry DNA. The PU.1 Q218H mutation, linked to acute myeloid leukemia, disrupts PU.1-H2A interactions. PU.1 and C/EBPα jointly displace linker histone H1 and open the H1-condensed nucleosome array. Our study unveils how two pioneer factors can work cooperatively to open closed chromatin by altering DNA positioning in the nucleosome.

Transcription factor exchange enables prolonged transcriptional bursts

Single-molecule imaging inside living cells has revealed that transcription factors (TFs) bind to DNA transiently, but a long-standing question is how this transient binding is related to transcription activation. Here, we devised a microscopy method to simultaneously measure transient TF binding at a single locus and the effect of these binding events on transcription. We show that DNA binding of the yeast TF Gal4 activates transcription of a target gene within a few seconds, with at least ∼20% efficiency and with a high initiation rate of ∼1 RNA/s. Gal4 DNA dissociation decreases transcription rapidly. Moreover, at a gene with multiple binding sites, individual Gal4 molecules only rarely stay bound throughout the entire burst but instead frequently exchange during a burst to increase the transcriptional burst duration. Our results suggest a mechanism for enhancer regulation in more complex eukaryotes, where TF cooperativity and exchange enable robust and responsive transcription regulation.

Coactivator condensation drives cardiovascular cell lineage specification

During development, cells make switch-like decisions to activate new gene programs specifying cell lineage. The mechanisms underlying these decisive choices remain unclear. Here, we show that the cardiovascular transcriptional coactivator myocardin (MYOCD) activates cell identity genes by concentration-dependent and switch-like formation of transcriptional condensates. MYOCD forms such condensates and activates cell identity genes at critical concentration thresholds achieved during smooth muscle cell and cardiomyocyte differentiation. The carboxyl-terminal disordered region of MYOCD is necessary and sufficient for condensate formation. Disrupting this region's ability to form condensates disrupts gene activation and smooth muscle cell reprogramming. Rescuing condensate formation by replacing this region with disordered regions from functionally unrelated proteins rescues gene activation and smooth muscle cell reprogramming. Our findings demonstrate that MYOCD condensate formation is required for gene activation during cardiovascular differentiation. We propose that the formation of transcriptional condensates at critical concentrations of cell type-specific regulators provides a molecular switch underlying the activation of key cell identity genes during development.

Transcription factors BZR2/MYC2 modulate brassinosteroid and jasmonic acid crosstalk during pear dormancy

Bud dormancy is an important physiological process during winter. Its release requires a certain period of chilling. In pear (Pyrus pyrifolia), the abscisic acid (ABA)-induced expression of DORMANCY-ASSOCIATED MADS-box (DAM) genes represses bud break, whereas exogenous gibberellin (GA) promotes dormancy release. However, with the exception of ABA and GA, the regulatory effects of phytohormones on dormancy remain largely uncharacterized. In this study, we confirmed brassinosteroids (BRs) and jasmonic acid (JA) contribute to pear bud dormancy release. If chilling accumulation is insufficient, both 24-epibrassinolide (EBR) and methyl jasmonic acid (MeJA) can promote pear bud break, implying that they positively regulate dormancy release. BRASSINAZOLE RESISTANT 2 (BZR2), which is a BR-responsive transcription factor, inhibited PpyDAM3 expression and accelerated pear bud break. The transient overexpression of PpyBZR2 increased endogenous GA, JA, and JA-Ile levels. In addition, the direct interaction between PpyBZR2 and MYELOCYTOMATOSIS 2 (PpyMYC2) enhanced the PpyMYC2-mediated activation of Gibberellin 20-oxidase genes PpyGA20OX1L1 and PpyGA20OX2L2 transcription, thereby increasing GA3 contents and accelerating pear bud dormancy release. Interestingly, treatment with 5 μm MeJA increased the bud break rate, while also enhancing PpyMYC2-activated PpyGA20OX expression and increasing GA3,4 contents. The 100 μm MeJA treatment decreased the PpyMYC2-mediated activation of the PpyGA20OX1L1 and PpyGA20OX2L2 promoters and suppressed the inhibitory effect of PpyBZR2 on PpyDAM3 transcription, ultimately inhibiting pear bud break. In summary, our data provide insights into the crosstalk between the BR and JA signaling pathways that regulate the BZR2/MYC2-mediated pathway in the pear dormancy release process.

DNA-guided transcription factor cooperativity shapes face and limb mesenchyme

Transcription factors (TFs) can define distinct cellular identities despite nearly identical DNA-binding specificities. One mechanism for achieving regulatory specificity is DNA-guided TF cooperativity. Although in vitro studies suggest that it may be common, examples of such cooperativity remain scarce in cellular contexts. Here, we demonstrate how "Coordinator," a long DNA motif composed of common motifs bound by many basic helix-loop-helix (bHLH) and homeodomain (HD) TFs, uniquely defines the regulatory regions of embryonic face and limb mesenchyme. Coordinator guides cooperative and selective binding between the bHLH family mesenchymal regulator TWIST1 and a collective of HD factors associated with regional identities in the face and limb. TWIST1 is required for HD binding and open chromatin at Coordinator sites, whereas HD factors stabilize TWIST1 occupancy at Coordinator and titrate it away from HD-independent sites. This cooperativity results in the shared regulation of genes involved in cell-type and positional identities and ultimately shapes facial morphology and evolution.

A large-scale cancer-specific protein-DNA interaction network

Cancer development and progression are generally associated with dysregulation of gene expression, often resulting from changes in transcription factor (TF) sequence or expression. Identifying key TFs involved in cancer gene regulation provides a framework for potential new therapeutics. This study presents a large-scale cancer gene TF-DNA interaction network as well as an extensive promoter clone resource for future studies. Most highly connected TFs do not show a preference for binding to promoters of genes associated with either good or poor cancer prognosis, suggesting that emerging strategies aimed at shifting gene expression balance between these two prognostic groups may be inherently complex. However, we identified potential for oncogene targeted therapeutics, with half of the tested oncogenes being potentially repressed by influencing specific activator or bifunctional TFs. Finally, we investigate the role of intrinsically disordered regions within the key cancer-related TF estrogen receptor ɑ (ESR1) on DNA binding and transcriptional activity, and found that these regions can have complex trade-offs in TF function. Altogether, our study not only broadens our knowledge of TFs involved in the cancer gene regulatory network but also provides a valuable resource for future studies, laying a foundation for potential therapeutic strategies targeting TFs in cancer.

Hold out the genome: a roadmap to solving the cis-regulatory code

Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven to be exceedingly complex. Recently, advances in the scale and resolution of functional genomics assays and machine learning have enabled substantial progress towards deciphering this code. However, the cis-regulatory code will probably never be solved if models are trained only on genomic sequences; regions of homology can easily lead to overestimation of predictive performance, and our genome is too short and has insufficient sequence diversity to learn all relevant parameters. Fortunately, randomly synthesized DNA sequences enable testing a far larger sequence space than exists in our genomes, and designed DNA sequences enable targeted queries to maximally improve the models. As the same biochemical principles are used to interpret DNA regardless of its source, models trained on these synthetic data can predict genomic activity, often better than genome-trained models. Here we provide an outlook on the field, and propose a roadmap towards solving the cis-regulatory code by a combination of machine learning and massively parallel assays using synthetic DNA.

High-throughput data and modeling reveal insights into the mechanisms of cooperative DNA-binding by transcription factor proteins

Cooperative DNA-binding by transcription factor (TF) proteins is critical for eukaryotic gene regulation. In the human genome, many regulatory regions contain TF-binding sites in close proximity to each other, which can facilitate cooperative interactions. However, binding site proximity does not necessarily imply cooperative binding, as TFs can also bind independently to each of their neighboring target sites. Currently, the rules that drive cooperative TF binding are not well understood. In addition, it is oftentimes difficult to infer direct TF-TF cooperativity from existing DNA-binding data. Here, we show that in vitro binding assays using DNA libraries of a few thousand genomic sequences with putative cooperative TF-binding events can be used to develop accurate models of cooperativity and to gain insights into cooperative binding mechanisms. Using factors ETS1 and RUNX1 as our case study, we show that the distance and orientation between ETS1 sites are critical determinants of cooperative ETS1-ETS1 binding, while cooperative ETS1-RUNX1 interactions show more flexibility in distance and orientation and can be accurately predicted based on the affinity and sequence/shape features of the binding sites. The approach described here, combining custom experimental design with machine-learning modeling, can be easily applied to study the cooperative DNA-binding patterns of any TFs.

Transcriptional reprogramming by mutated IRF4 in lymphoma

Disease-causing mutations in genes encoding transcription factors (TFs) can affect TF interactions with their cognate DNA-binding motifs. Whether and how TF mutations impact upon the binding to TF composite elements (CE) and the interaction with other TFs is unclear. Here, we report a distinct mechanism of TF alteration in human lymphomas with perturbed B cell identity, in particular classic Hodgkin lymphoma. It is caused by a recurrent somatic missense mutation c.295 T > C (p.Cys99Arg; p.C99R) targeting the center of the DNA-binding domain of Interferon Regulatory Factor 4 (IRF4), a key TF in immune cells. IRF4-C99R fundamentally alters IRF4 DNA-binding, with loss-of-binding to canonical IRF motifs and neomorphic gain-of-binding to canonical and non-canonical IRF CEs. IRF4-C99R thoroughly modifies IRF4 function by blocking IRF4-dependent plasma cell induction, and up-regulates disease-specific genes in a non-canonical Activator Protein-1 (AP-1)-IRF-CE (AICE)-dependent manner. Our data explain how a single mutation causes a complex switch of TF specificity and gene regulation and open the perspective to specifically block the neomorphic DNA-binding activities of a mutant TF.

From Genotype to Phenotype: How Enhancers Control Gene Expression and Cell Identity in Hematopoiesis

Blood comprises a wide array of specialized cells, all of which share the same genetic information and ultimately derive from the same precursor, the hematopoietic stem cell (HSC). This diversity of phenotypes is underpinned by unique transcriptional programs gradually acquired in the process known as hematopoiesis. Spatiotemporal regulation of gene expression depends on many factors, but critical among them are enhancers-sequences of DNA that bind transcription factors and increase transcription of genes under their control. Thus, hematopoiesis involves the activation of specific enhancer repertoires in HSCs and their progeny, driving the expression of sets of genes that collectively determine morphology and function. Disruption of this tightly regulated process can have catastrophic consequences: in hematopoietic malignancies, dysregulation of transcriptional control by enhancers leads to misexpression of oncogenes that ultimately drive transformation. This review attempts to provide a basic understanding of enhancers and their role in transcriptional regulation, with a focus on normal and malignant hematopoiesis. We present examples of enhancers controlling master regulators of hematopoiesis and discuss the main mechanisms leading to enhancer dysregulation in leukemia and lymphoma.

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.

Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors

Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA region-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage and identify cooperativity and antagonism between human TFs and viral proteins from human papillomaviruses, Epstein-Barr virus, and other viruses. Altogether, pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions.

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.

Cooperative assembly confers regulatory specificity and long-term genetic circuit stability

A ubiquitous feature of eukaryotic transcriptional regulation is cooperative self-assembly between transcription factors (TFs) and DNA cis-regulatory motifs. It is thought that this strategy enables specific regulatory connections to be formed in gene networks between otherwise weakly interacting, low-specificity molecular components. Here, using synthetic gene circuits constructed in yeast, we find that high regulatory specificity can emerge from cooperative, multivalent interactions among artificial zinc-finger-based TFs. We show that circuits "wired" using the strategy of cooperative TF assembly are effectively insulated from aberrant misregulation of the host cell genome. As we demonstrate in experiments and mathematical models, this mechanism is sufficient to rescue circuit-driven fitness defects, resulting in genetic and functional stability of circuits in long-term continuous culture. Our naturally inspired approach offers a simple, generalizable means for building high-fidelity, evolutionarily robust gene circuits that can be scaled to a wide range of host organisms and applications.

Structural mechanism of synergistic targeting of the CX3CR1 nucleosome by PU.1 and C/EBPα

Pioneer transcription factors are vital for cell fate changes. PU.1 and C/EBPα work together to regulate hematopoietic stem cell differentiation. However, how they recognize in vivo nucleosomal DNA targets remain elusive. Here we report the structures of the nucleosome containing the mouse genomic CX3CR1 enhancer DNA and its complexes with PU.1 alone and with both PU.1 and the C/EBPα DNA binding domain. Our structures reveal that PU.1 binds the DNA motif at the exit linker, shifting 17 bp of DNA into the core region through interactions with H2A, unwrapping ~20 bp of nucleosomal DNA. C/EBPα binding, aided by PU.1's repositioning, unwraps ~25 bp entry DNA. The PU.1 Q218H mutation, linked to acute myeloid leukemia, disrupts PU.1-H2A interactions. PU.1 and C/EBPα jointly displace linker histone H1 and open the H1-condensed nucleosome array. Our study unveils how two pioneer factors can work cooperatively to open closed chromatin by altering DNA positioning in the nucleosome.

Prediction of cooperative homeodomain DNA binding sites from high-throughput-SELEX data

Homeodomain proteins constitute one of the largest families of metazoan transcription factors. Genetic studies have demonstrated that homeodomain proteins regulate many developmental processes. Yet, biochemical data reveal that most bind highly similar DNA sequences. Defining how homeodomain proteins achieve DNA binding specificity has therefore been a long-standing goal. Here, we developed a novel computational approach to predict cooperative dimeric binding of homeodomain proteins using High-Throughput (HT) SELEX data. Importantly, we found that 15 of 88 homeodomain factors form cooperative homodimer complexes on DNA sites with precise spacing requirements. Approximately one third of the paired-like homeodomain proteins cooperatively bind palindromic sequences spaced 3 bp apart, whereas other homeodomain proteins cooperatively bind sites with distinct orientation and spacing requirements. Combining structural models of a paired-like factor with our cooperativity predictions identified key amino acid differences that help differentiate between cooperative and non-cooperative factors. Finally, we confirmed predicted cooperative dimer sites in vivo using available genomic data for a subset of factors. These findings demonstrate how HT-SELEX data can be computationally mined to predict cooperativity. In addition, the binding site spacing requirements of select homeodomain proteins provide a mechanism by which seemingly similar AT-rich DNA sequences can preferentially recruit specific homeodomain factors.

A spatio-temporally constrained gene regulatory network directed by PBX1/2 acquires limb patterning specificity via HAND2

A lingering question in developmental biology has centered on how transcription factors with widespread distribution in vertebrate embryos can perform tissue-specific functions. Here, using the murine hindlimb as a model, we investigate the elusive mechanisms whereby PBX TALE homeoproteins, viewed primarily as HOX cofactors, attain context-specific developmental roles despite ubiquitous presence in the embryo. We first demonstrate that mesenchymal-specific loss of PBX1/2 or the transcriptional regulator HAND2 generates similar limb phenotypes. By combining tissue-specific and temporally controlled mutagenesis with multi-omics approaches, we reconstruct a gene regulatory network (GRN) at organismal-level resolution that is collaboratively directed by PBX1/2 and HAND2 interactions in subsets of posterior hindlimb mesenchymal cells. Genome-wide profiling of PBX1 binding across multiple embryonic tissues further reveals that HAND2 interacts with subsets of PBX-bound regions to regulate limb-specific GRNs. Our research elucidates fundamental principles by which promiscuous transcription factors cooperate with cofactors that display domain-restricted localization to instruct tissue-specific developmental programs.

Combinatorial transcription factor binding encodes cis-regulatory wiring of forebrain GABAergic neurogenesis

Transcription factors (TFs) bind combinatorially to genomic cis-regulatory elements (cREs), orchestrating transcription programs. While studies of chromatin state and chromosomal interactions have revealed dynamic neurodevelopmental cRE landscapes, parallel understanding of the underlying TF binding lags. To elucidate the combinatorial TF-cRE interactions driving mouse basal ganglia development, we integrated ChIP-seq for twelve TFs, H3K4me3-associated enhancer-promoter interactions, chromatin and transcriptional state, and transgenic enhancer assays. We identified TF-cREs modules with distinct chromatin features and enhancer activity that have complementary roles driving GABAergic neurogenesis and suppressing other developmental fates. While the majority of distal cREs were bound by one or two TFs, a small proportion were extensively bound, and these enhancers also exhibited exceptional evolutionary conservation, motif density, and complex chromosomal interactions. Our results provide new insights into how modules of combinatorial TF-cRE interactions activate and repress developmental expression programs and demonstrate the value of TF binding data in modeling gene regulatory wiring.

DNA-guided transcription factor cooperativity shapes face and limb mesenchyme

Transcription factors (TFs) can define distinct cellular identities despite nearly identical DNA-binding specificities. One mechanism for achieving regulatory specificity is DNA-guided TF cooperativity. Although in vitro studies suggest it may be common, examples of such cooperativity remain scarce in cellular contexts. Here, we demonstrate how 'Coordinator', a long DNA motif comprised of common motifs bound by many basic helix-loop-helix (bHLH) and homeodomain (HD) TFs, uniquely defines regulatory regions of embryonic face and limb mesenchyme. Coordinator guides cooperative and selective binding between the bHLH family mesenchymal regulator TWIST1 and a collective of HD factors associated with regional identities in the face and limb. TWIST1 is required for HD binding and open chromatin at Coordinator sites, while HD factors stabilize TWIST1 occupancy at Coordinator and titrate it away from HD-independent sites. This cooperativity results in shared regulation of genes involved in cell-type and positional identities, and ultimately shapes facial morphology and evolution.

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.

The E2F4/p130 Repressor Complex Cooperates with Oncogenic ΔNp73α To Inhibit Gene Expression in Human Papillomavirus 38 E6/E7-Transformed Keratinocytes and in Cancer Cells

Tumor suppressor p53 and its related proteins, p63 and p73, can be synthesized as multiple isoforms lacking part of the N- or C-terminal regions. Specifically, high expression of the ΔNp73α isoform is notoriously associated with various human malignancies characterized by poor prognosis. This isoform is also accumulated by oncogenic viruses, such as Epstein-Barr virus (EBV), as well as genus beta human papillomaviruses (HPV) that appear to be involved in carcinogenesis. To gain additional insight into ΔNp73α mechanisms, we have performed proteomics analyses using human keratinocytes transformed by the E6 and E7 proteins of the beta-HPV type 38 virus as an experimental model (38HK). We find that ΔNp73α associates with the E2F4/p130 repressor complex through a direct interaction with E2F4. This interaction is favored by the N-terminal truncation of p73 characteristic of ΔNp73 isoforms. Moreover, it is independent of the C-terminal splicing status, suggesting that it could represent a general feature of ΔNp73 isoforms (α, β, γ, δ, ε, ζ, θ, η, and η1). We show that the ΔNp73α-E2F4/p130 complex inhibits the expression of specific genes, including genes encoding for negative regulators of proliferation, both in 38HK and in HPV-negative cancer-derived cell lines. Such genes are not inhibited by E2F4/p130 in primary keratinocytes lacking ΔNp73α, indicating that the interaction with ΔNp73α rewires the E2F4 transcriptional program. In conclusion, we have identified and characterized a novel transcriptional regulatory complex with potential implications in oncogenesis. IMPORTANCE The TP53 gene is mutated in about 50% of human cancers. In contrast, the TP63 and TP73 genes are rarely mutated but rather expressed as ΔNp63 and ΔNp73 isoforms in a wide range of malignancies, where they act as p53 antagonists. Accumulation of ΔNp63 and ΔNp73, which is associated with chemoresistance, can result from infection by oncogenic viruses such as EBV or HPV. Our study focuses on the highly carcinogenic ΔNp73α isoform and uses a viral model of cellular transformation. We unveil a physical interaction between ΔNp73α and the E2F4/p130 complex involved in cell cycle control, which rewires the E2F4/p130 transcriptional program. Our work shows that ΔNp73 isoforms can establish interactions with proteins that do not bind to the TAp73α tumor suppressor. This situation is analogous to the gain-of-function interactions of p53 mutants supporting cellular proliferation.

A mini-TGA protein modulates gene expression through heterogeneous association with transcription factors

TGA (TGACG-binding) transcription factors, which bind their target DNA through a conserved basic region leucine zipper (bZIP) domain, are vital regulators of gene expression in salicylic acid (SA)-mediated plant immunity. Here, we investigated the role of StTGA2.1, a potato (Solanum tuberosum) TGA lacking the full bZIP, which we named a mini-TGA. Such truncated proteins have been widely assigned as loss-of-function mutants. We, however, confirmed that StTGA2.1 overexpression compensates for SA-deficiency, indicating a distinct mechanism of action compared with model plant species. To understand the underlying mechanisms, we showed that StTGA2.1 can physically interact with StTGA2.2 and StTGA2.3, while its interaction with DNA was not detected. We investigated the changes in transcriptional regulation due to StTGA2.1 overexpression, identifying direct and indirect target genes. Using in planta transactivation assays, we confirmed that StTGA2.1 interacts with StTGA2.3 to activate StPRX07, a member of class III peroxidases (StPRX), which are known to play role in immune response. Finally, via structural modeling and molecular dynamics simulations, we hypothesized that the compact molecular architecture of StTGA2.1 distorts DNA conformation upon heterodimer binding to enable transcriptional activation. This study demonstrates how protein truncation can lead to distinct functions and that such events should be studied carefully in other protein families.

Histone modification landscape and the key significance of H3K27me3 in myocardial ischaemia/reperfusion injury

Histone modifications play crucial roles in the pathogenesis of myocardial ischaemia/reperfusion (I/R) injury. However, a genome-wide map of histone modifications and the underlying epigenetic signatures in myocardial I/R injury have not been established. Here, we integrated transcriptome and epigenome of histone modifications to characterize epigenetic signatures after I/R injury. Disease-specific histone mark alterations were mainly found in H3K27me3-, H3K27ac-, and H3K4me1-marked regions 24 and 48 h after I/R. Genes differentially modified by H3K27ac, H3K4me1 and H3K27me3 were involved in immune response, heart conduction or contraction, cytoskeleton, and angiogenesis. H3K27me3 and its methyltransferase polycomb repressor complex 2 (PRC2) were upregulated in myocardial tissues after I/R. Upon selective inhibition of EZH2 (the catalytic core of PRC2), the mice manifest improved cardiac function, enhanced angiogenesis, and reduced fibrosis. Further investigations confirmed that EZH2 inhibition regulated H3K27me3 modification of multiple pro-angiogenic genes and ultimately enhanced angiogenic properties in vivo and in vitro. This study delineates a landscape of histone modifications in myocardial I/R injury, and identifies H3K27me3 as a key epigenetic modifier in I/R process. The inhibition of H3K27me3 and its methyltransferase might be a potential strategy for myocardial I/R injury intervention.

The JNK-EGR1 signaling axis promotes TNF-α-induced endothelial differentiation of human mesenchymal stem cells via VEGFR2 expression

Mesenchymal stem cells (MSCs) can differentiate into endothelial cells; however, the mechanisms underlying this process in the tumor microenvironment (TME) remain elusive. This study shows that tumor necrosis factor alpha (TNF-α), a key cytokine present in the TME, promotes the endothelial differentiation of MSCs by inducing vascular endothelial growth factor receptor 2 (VEGFR2) gene expression. EGR1 is a member of the zinc-finger transcription factor family induced by TNF-α. Our findings indicate that EGR1 directly binds to the VEGFR2 promoter and transactivates VEGFR2 expression. We also demonstrate that EGR1 forms a complex with c-JUN activated by c-JUN N-terminal kinase (JNK) to promote VEGFR2 transcription and endothelial differentiation in MSCs in response to TNF-α stimulation. The shRNA-mediated silencing of EGR1 or c-JUN abrogates TNF-α-induced VEGFR2 transcription and the endothelial differentiation of MSCs. To further evaluated the role of EGR1 in the endothelial differentiation of BM-MSCs, we used a syngenic tumor implantation model. 4T1 mouse mammary tumor cells were injected subcutaneously into BALB/c mice with primary mBM-MSCs isolated from wild-type (Egr1+/+) or Egr1-null (Egr1-/-) mice. CD31-positive cells were predominantly observed at the border of the tumor in the 4T1 plus wild-type MSC group, while staining less in the 4T1 alone or 4T1 plus Egr1-null MSC group. Collectively, these findings demonstrate that the JNK-EGR1 signaling axis plays a crucial role in the TNF-α-induced endothelial differentiation of MSCs in the TME, which could be a potential therapeutic target for solid tumors vasculatures.

Understanding the Target Search by Multiple Transcription Factors on Nucleosomal DNA

The association of multiple Transcription Factors (TFs) in the cis-regulatory region is imperative for developmental changes in eukaryotes. The underlying process is exceedingly complex, and it is not at all clear what orchestrates the overall search process by multiple TFs. In this study, by developing a theoretical model based on a discrete-state stochastic approach, we investigated the target search mechanism of multiple TFs on nucleosomal DNA. Experimental kinetic rate constants of different TFs are taken as input to estimate the Mean-First-Passage time to recognize the binding motifs by two TFs on a dynamic nucleosome model. The theory systematically analyzes when the TFs search their binding motifs hierarchically and when simultaneously by proceeding via the formation of a protein-protein complex. Our results, validated by extensive Monte Carlo simulations, elucidate the molecular basis of the complex target search phenomenon of multiple TFs on nucleosomal DNA.

Multi-scale gene regulation mechanism: Spatiotemporal transmission of genetic information

Gene expression is regulated by many factors, including transcription factors, chromatin three-dimensional topology, modifications of DNA and histone proteins, and non-coding RNAs. The execution of these complex mechanisms requires an effectively coordinated regulation system. In this review, we emphasize that the multi-scale heterogeneous DNA sequence plays a fundamental and important role for gene expression activity and usage of different means of epigenetic regulation. We illustrate here that the chromatin structure organization provides a stage for spatiotemporal regulation between different genes or gene modules and to realize their downstream functional cooperation. Such a perspective expands our understanding of the central dogma: In addition to one-dimensional sequence information, inter-gene interactions can also be transferred from DNA and RNA to protein levels.

TFSyntax: a database of transcription factors binding syntax in mammalian genomes

In mammals, transcriptional factors (TFs) drive gene expression by binding to regulatory elements in a cooperative manner. Deciphering the rules of such cooperation is crucial to obtain a full understanding of cellular homeostasis and development. Although this is a long-standing topic, there is no comprehensive database for biologists to access the syntax of TF binding sites. Here we present TFSyntax (https://tfsyntax.zhaopage.com), a database focusing on the arrangement of TF binding sites. TFSyntax maps the binding motif of 1299 human TFs and 890 mouse TFs across 382 cells and tissues, representing the most comprehensive TF binding map to date. In addition to location, TFSyntax defines motif positional preference, density and colocalization within accessible elements. Powered by a series of functional modules based on web interface, users can freely search, browse, analyze, and download data of interest. With comprehensive characterization of TF binding syntax across distinct tissues and cell types, TFSyntax represents a valuable resource and platform for studying the mechanism of transcriptional regulation and exploring how regulatory DNA variants cause disease.

"Stripe" transcription factors provide accessibility to co-binding partners in mammalian genomes

Regulatory elements activate promoters by recruiting transcription factors (TFs) to specific motifs. Notably, TF-DNA interactions often depend on cooperativity with colocalized partners, suggesting an underlying cis-regulatory syntax. To explore TF cooperativity in mammals, we analyze ∼500 mouse and human primary cells by combining an atlas of TF motifs, footprints, ChIP-seq, transcriptomes, and accessibility. We uncover two TF groups that colocalize with most expressed factors, forming stripes in hierarchical clustering maps. The first group includes lineage-determining factors that occupy DNA elements broadly, consistent with their key role in tissue-specific transcription. The second one, dubbed universal stripe factors (USFs), comprises ∼30 SP, KLF, EGR, and ZBTB family members that recognize overlapping GC-rich sequences in all tissues analyzed. Knockouts and single-molecule tracking reveal that USFs impart accessibility to colocalized partners and increase their residence time. Mammalian cells have thus evolved a TF superfamily with overlapping DNA binding that facilitate chromatin accessibility.

Web-MCOT Server for Motif Co-Occurrence Search in ChIP-Seq Data

(1) Background: The widespread application of ChIP-seq technology requires annotation of cis-regulatory modules through the search of co-occurred motifs. (2) Methods: We present the web server Motifs Co-Occurrence Tool (Web-MCOT) that for a single ChIP-seq dataset detects the composite elements (CEs) or overrepresented homo- and heterotypic pairs of motifs with spacers and overlaps, with any mutual orientations, uncovering various similarities to recognition models within pairs of motifs. The first (Anchor) motif in CEs respects the target transcription factor of the ChIP-seq experiment, while the second one (Partner) can be defined either by a user or a public library of Partner motifs being processed. (3) Results: Web-MCOT computes the significances of CEs without reference to motif conservation and those with more conserved Partner and Anchor motifs. Graphic results show histograms of CE abundance depending on orientations of motifs, overlap and spacer lengths; logos of the most common CE structural types with an overlap of motifs, and heatmaps depicting the abundance of CEs with one motif possessing higher conservation than another. (4) Conclusions: Novel capacities of Web-MCOT allow retrieving from a single ChIP-seq dataset with maximal information on the co-occurrence of motifs and potentiates planning of next ChIP-seq experiments.

Binding of the transcription activator-like effector augments transcriptional regulation by another transcription factor

DNA transcription is regulated by a range of diverse mechanisms and primarily by transcription factors that recruit the RNA polymerase complex to the promoter region on the DNA. Protein binding to DNA at nearby or distant sites can synergistically affect this process in a variety of ways, but mainly through direct interactions between DNA-binding proteins. Here we show that a Transcription Activator-Like Effector (TALE), which lacks an activation domain, can enhance transcription in mammalian cells when it binds in the vicinity of and without direct interaction with several different dimeric or monomeric transcription factors. This effect was observed for several TALEs regardless of the recognition sequences and their DNA-bound orientation. TALEs can exert an effect over the distance of tens of nucleotides and it also potentiated KRAB-mediated repression. The augmentation of transcriptional regulation of another transcription factor is characteristic of TALEs, as it was not observed for dCas9/gRNA, zinc finger, or Gal4 DNA-binding domains. We propose that this mechanism involves an allosteric effect exerted on DNA structure or dynamics. This mechanism could be used to modulate transcription but may also play a role in the natural context of TALEs.

Modeling binding specificities of transcription factor pairs with random forests

Background

Transcription factors (TFs) bind regulatory DNA regions with sequence specificity, form complexes and regulate gene expression. In cooperative TF-TF binding, two transcription factors bind onto a shared DNA binding site as a pair. Previous work has demonstrated pairwise TF-TF-DNA interactions with position weight matrices (PWMs), which may however not sufficiently take into account the complexity and flexibility of pairwise binding.

Results

We propose two random forest (RF) methods for joint TF-TF binding site prediction: and . We train models with previously published large-scale CAP-SELEX DNA libraries, which comprise DNA sequences enriched for binding of a selected TF pair. builds a random forest with sub-sequences selected from CAP-SELEX DNA reads with previously proposed pairwise PWM. outperforms (area under receiver operating characteristics curve, AUROC, 0.75) the current state-of-the-art method i.e. orientation and spacing specific pairwise PWMs (AUROC 0.59). Thus, may be utilized to improve prediction accuracy for pre-determined binding preferences. However, pairwise TF binding is currently considered flexible; a pair may bind DNA with different orientations and amounts of dinucleotide gaps or overlap between the two motifs. Thus, we developed , which utilizes random forests by considering simultaneously multiple orientations and spacings of the two factors. Our approach outperforms (AUROC 0.78) PWMs, as well as (p<0.00195). provides an approach for predicting TF-TF binding sites without prior knowledge on pairwise binding preferences. However, more research is needed to assess eligibility for practical applications.

Conclusions

Random forest is well suited for modeling pairwise TF-TF-DNA binding specificities, and provides an improvement to pairwise binding site prediction accuracy.

Multimericity Amplifies the Synergy of BCR and TLR4 for B Cell Activation and Antibody Class Switching

Sustained signaling through the B cell antigen receptor (BCR) is thought to occur only when antigen(s) crosslink or disperse multiple BCR units, such as by multimeric antigens found on the surfaces of viruses or bacteria. B cell-intrinsic Toll-like receptor (TLR) signaling synergizes with the BCR to induce and shape antibody production, hallmarked by immunoglobulin (Ig) class switch recombination (CSR) of constant heavy chains from IgM/IgD to IgG, IgA or IgE isotypes, and somatic hypermutation (SHM) of variable heavy and light chains. Full B cell differentiation is essential for protective immunity, where class switched high affinity antibodies neutralize present pathogens, memory B cells are held in reserve for future encounters, and activated B cells also serve as semi-professional APCs for T cells. But the rules that fine-tune B cell differentiation remain partially understood, despite their being essential for naturally acquired immunity and for guiding vaccine development. To address this in part, we have developed a cell culture system using splenic B cells from naive mice stimulated with several biotinylated ligands and antibodies crosslinked by streptavidin reagents. In particular, biotinylated lipopolysaccharide (LPS), a Toll-like receptor 4 (TLR4) agonist, and biotinylated anti-IgM were pre-assembled (multimerized) using streptavidin, or immobilized on nanoparticles coated with streptavidin, and used to active B cells in this precisely controlled, high throughput assay. Using B cell proliferation and Ig class switching as metrics for successful B cell activation, we show that the stimuli are both synergistic and dose-dependent. Crucially, the multimerized immunoconjugates are most active over a narrow concentration range. These data suggest that multimericity is an essential requirement for B cell BCR/TLRs ligands, and clarify basic rules for B cell activation. Such studies highlight the importance in determining the choice of single vs multimeric formats of antigen and PAMP agonists during vaccine design and development.

DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers

Enhancer sequences control gene expression and comprise binding sites (motifs) for different transcription factors (TFs). Despite extensive genetic and computational studies, the relationship between DNA sequence and regulatory activity is poorly understood, and de novo enhancer design has been challenging. Here, we built a deep-learning model, DeepSTARR, to quantitatively predict the activities of thousands of developmental and housekeeping enhancers directly from DNA sequence in Drosophila melanogaster S2 cells. The model learned relevant TF motifs and higher-order syntax rules, including functionally nonequivalent instances of the same TF motif that are determined by motif-flanking sequence and intermotif distances. We validated these rules experimentally and demonstrated that they can be generalized to humans by testing more than 40,000 wildtype and mutant Drosophila and human enhancers. Finally, we designed and functionally validated synthetic enhancers with desired activities de novo.