Probing transcription factor combinatorics in different promoter classes and in enhancers

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.

FOXF1 reverses lung fibroblasts transdifferentiation via inhibiting TGF-β/SMAD2/3 pathway in silica-induced pulmonary fibrosis

Silicosis is one of the most common and severe types of pneumoconiosis and is characterized by lung dysfunction, persistent lung inflammation, pulmonary nodule formation, and irreversible pulmonary fibrosis. The transdifferentiation of fibroblasts into myofibroblasts is one of the main reasons for the exacerbation of silicosis. However, the underlying mechanism of transcription factors regulating silicosis fibrosis has not been clarified. The aim of this study was to investigate the potential mechanism of transcription factor FOXF1 in fibroblast transdifferentiation in silica-induced pulmonary fibrosis. Therefore, a silicosis mouse model was established, and we found that FOXF1 expression level was significantly down-regulated in the silicosis group, and after overexpression of FOXF1 by adeno-associated virus (AAV), FOXF1 expression level was up-regulated, and silicosis fibrosis was alleviated. In order to further explore the specific regulatory mechanism of FOXF1 in silicosis, we established a fibroblasts transdifferentiation model induced by TGF-β in vitro. In the model, the expression levels of SMAD2/3 and P-SMAD2/3 were up-regulated, but the expression levels of SMAD2/3 and P-SMAD2/3 were down-regulated, inhibiting transdifferentiation and accumulation of extracellular matrix after the overexpressed FOXF1 plasmid was constructed. However, after silencing FOXF1, the expression levels of SMAD2/3 and P-SMAD2/3 were further up-regulated, aggravating transdifferentiation and accumulation of extracellular matrix. These results indicate that the activation of FOXF1 in fibroblasts can slow down the progression of silicosis fibrosis by inhibiting TGF-β/SMAD2/3 classical pathway, which provides a new idea for further exploration of silicosis treatment.

Transcription Factor STAT3-Activated LDHB Promotes Tumor Properties of Endometrial Cancer Cells by Inducing MDH2 Expression

The pathogenesis of endometrial cancer (EC) involves the regulation of lactate dehydrogenases. However, the role and mechanism of lactate dehydrogenase-B (LDHB) in EC progression have not been studied. The mRNA levels of LDHB and malate dehydrogenase 2 (MDH2) were detected by quantitative real-time polymerase chain reaction. Protein expression was checked by western blotting and immunohistochemistry assays. Cell proliferation, apoptosis, and invasion were analyzed by 5-Ethynyl-2'-deoxyuridine, transwell, and flow cytometry assay, respectively. Glycolysis was investigated using Glucose Assay Kit, CheKine™ Micro Lactate Assay Kit, and ADP/ATP ratio assay kit. An in vivo tumor formation assay was conducted to disclose the effect of LDHB on tumor growth in vivo. The associations among signal transducer and activator of transcription 3 (STAT3), LDHB, and MDH2 were predicted through JASPAR or GeneMANIA online database and identified by chromatin immunoprecipitation assay, dual-luciferase reporter assay, and co-immunoprecipitation assay. LDHB expression was increased in EC tissues and cells in comparison with normal endometrial tissues and human endometrial stromal cells. LDHB had the potential as a biomarker to predict the prognosis of EC patients. In addition, LDHB knockdown inhibited the proliferation, invasion, and glycolysis and promoted apoptosis of RL95-2 and Ishikawa cells. LDHB knockdown inhibited tumor property of Ishikawa cells in vivo. STAT3 bound to the promoter region of LDHB, and STAT3 silencing-induced effects were relieved after LDHB upregulation. LDHB interacted with and regulated MDH2 expression. Moreover, MDH2 overexpression rescued LDHB knockdown-induced effects on EC cell phenotypes. STAT3-activated LDHB promoted endometrial cancer cell malignancy by inducing MDH2 production.

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.

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.

Association between methylation in the promoter region of the GAD2 gene and opioid use disorder

DNA methylation is one of the epigenetic mechanisms involved in opioid use disorder. GAD2 is a key catalyticase in gamma amino butyric acid (GABA) synthesis from glutamate, that is implicated in opioid-induced rewarding effect. To reveal the relationship and the underlying mechanism between GAD2 gene methylation and opioid use disorder, we first examined and compared the methylation levels in the promoter region of the GAD2 gene in peripheral blood between 120 patients with opioid use disorder and 110 healthy controls by using a targeted approach. A diagnostic model with methylation biomarkers was established to distinguish opioid use disorder and healthy control groups. Correlations between methylation levels in the promoter region of the GAD2 gene and the duration and dosage of opioid use were then determined. Finally, the transcription factors that potentially bind to the target sequences including the detected CpG sites were predicted with the JASPAR database. Our results demonstrated that hypermethylation in the promoter region of the GAD2 gene was associated with opioid use disorder. A diagnostic model based on 10 methylation biomarkers could distinguish the opioid use disorder and healthy control groups. Several correlations between methylation levels in the GAD2 gene promoter and the duration and dosage of opioid use were observed. Transcription factors TFAP2A, Arnt and Runx1 were predicted to bind to the target sequences including several CpG sites detected in the present study in the GAD2 gene promoter. Our findings highlight and extend the role of DNA methylation in the GAD2 gene in opioid use disorder.

Complementary strategies for directing in vivo transcription factor binding through DNA binding domains and intrinsically disordered regions

DNA binding domains (DBDs) of transcription factors (TFs) recognize DNA sequence motifs that are highly abundant in genomes. Within cells, TFs bind a subset of motif-containing sites as directed by either their DBDs or DBD-external (nonDBD) sequences. To define the relative roles of DBDs and nonDBDs in directing binding preferences, we compared the genome-wide binding of 48 (∼30%) budding yeast TFs with their DBD-only, nonDBD-truncated, and nonDBD-only mutants. With a few exceptions, binding locations differed between DBDs and TFs, resulting from the cumulative action of multiple determinants mapped mostly to disordered nonDBD regions. Furthermore, TFs' preferences for promoters of the fuzzy nucleosome architecture were lost in DBD-only mutants, whose binding spread across promoters, implicating nonDBDs' preferences in this hallmark of budding yeast regulatory design. We conclude that DBDs and nonDBDs employ complementary DNA-targeting strategies, whose balance defines TF binding specificity along genomes.

Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology

Transcription factors (TFs) control gene expression, often acting synergistically. Classical thermodynamic models offer a biophysical explanation for synergy based on binding cooperativity and regulated recruitment of RNA polymerase. Because transcription requires polymerase to transition through multiple states, recent work suggests that "kinetic synergy" can arise through TFs acting on distinct steps of the transcription cycle. These types of synergy are not mutually exclusive and are difficult to disentangle conceptually and experimentally. Here, we model and build a synthetic circuit in which TFs bind to a single shared site on DNA, such that TFs cannot synergize by simultaneous binding. We model mRNA production as a function of both TF binding and regulation of the transcription cycle, revealing a complex landscape dependent on TF concentration, DNA binding affinity, and regulatory activity. We use synthetic TFs to confirm that the transcription cycle must be integrated with recruitment for a quantitative understanding of gene regulation.

Gene expression changes during the evolution of the tetrapod limb

Major changes in the vertebrate anatomy have preceded the conquest of land by the members of this taxon, and continuous changes in limb shape and use have occurred during the later radiation of tetrapods. While the main, conserved mechanisms of limb development have been discerned over the past century using a combination of classical embryological and molecular methods, only recent advances made it possible to identify and study the regulatory changes that have contributed to the evolution of the tetrapod appendage. These advances include the expansion of the model repertoire from traditional genetic model species to non-conventional ones, a proliferation of predictive mathematical models that describe gene interactions, an explosion in genomic data and the development of high-throughput methodologies. These revolutionary innovations make it possible to identify specific mutations that are behind specific transitions in limb evolution. Also, as we continue to apply them to more and more extant species, we can expect to gain a fine-grained view of this evolutionary transition that has been so consequential for our species as well.

Assessing Combinatorial Diversity of Aureochrome Basic Leucine Zippers through Genome-Wide Screening

Aureochromes are unique blue light-responsive light-oxygen-voltage (LOV) photoreceptors cum basic leucine zipper (bZIP) transcription factors (TFs), present exclusively in photosynthetic marine stramenopiles. Considering the availability of the complete genome sequence, this study focuses on aureochromes from Ectocarpus siliculosus. Aureochromes mediate light-regulated developmental responses in these brown photosynthetic algae. Both the LOV sensor and the bZIP effector show overall sequence-structure conservation. The structurally similar LOV + bZIP modules of aureochrome homologs/paralogs prefer a dimeric state. Besides a heterogeneous linker connecting the sensor-effector and a flexible N-terminal region, the sequence composition of both domains is vital. Aureochromes execute diverse cellular responses in different photosynthetic stramenopiles - though their activities can vary even within a given algal species. Therefore, it is important to understand whether aureochromes select dimerization partners from the same family or interact with other bZIPs as well. To regulate multifarious biological activities, it is possible that aureochromes activate the global TF interaction network. Following homo/heterodimer modeling, we address the compatibility of dimerization partners by screening through heptad repeats. We evaluate the dimer interface area in terms of gain in solvation energy and the number of hydrogen bonds/salt bridge interactions. We further explore the relative stability of these structures from a graph-theoretic perspective through well-studied measures such as the energy of the graph, average participation coefficient, and betweenness centrality. Furthermore, we also conduct an information-theoretic analysis using hitherto understudied measures such as network information centrality and Kullback-Leibler divergence. We find that all our investigations into the relative stability of the dimers using diverse methods from bioinformatics, network science, and information theory are in harmonious agreement. Coupling preferences of monomers in aureochromes can be further translated to design novel optogenetic tools useful for understanding human development and disease.

Causal Discovery in High-dimensional, Multicollinear Datasets

As the cost of high-throughput genomic sequencing technology declines, its application in clinical research becomes increasingly popular. The collected datasets often contain tens or hundreds of thousands of biological features that need to be mined to extract meaningful information. One area of particular interest is discovering underlying causal mechanisms of disease outcomes. Over the past few decades, causal discovery algorithms have been developed and expanded to infer such relationships. However, these algorithms suffer from the curse of dimensionality and multicollinearity. A recently introduced, non-orthogonal, general empirical Bayes approach to matrix factorization has been demonstrated to successfully infer latent factors with interpretable structures from observed variables. We hypothesize that applying this strategy to causal discovery algorithms can solve both the high dimensionality and collinearity problems, inherent to most biomedical datasets. We evaluate this strategy on simulated data and apply it to two real-world datasets. In a breast cancer dataset, we identified important survival-associated latent factors and biologically meaningful enriched pathways within factors related to important clinical features. In a SARS-CoV-2 dataset, we were able to predict whether a patient (1) had Covid-19 and (2) would enter the ICU. Furthermore, we were able to associate factors with known Covid-19 related biological pathways.

Interleukin-7 receptor signaling is crucial for enhancer-dependent TCRδ germline transcription mediated through STAT5 recruitment

γδ T cells play important roles in immune responses by rapidly producing large quantities of cytokines. Recently, γδ T cells have been found to be involved in tissue homeostatic regulation, playing roles in thermogenesis, bone regeneration and synaptic plasticity. Nonetheless, the mechanisms involved in γδ T-cell development, especially the regulation of TCRδ gene transcription, have not yet been clarified. Previous studies have established that NOTCH1 signaling plays an important role in the Tcrg and Tcrd germline transcriptional regulation induced by enhancer activation, which is mediated through the recruitment of RUNX1 and MYB. In addition, interleukin-7 signaling has been shown to be required for Tcrg germline transcription, VγJγ rearrangement and γδ T-lymphocyte generation as well as for promoting T-cell survival. In this study, we discovered that interleukin-7 is required for the activation of enhancer-dependent Tcrd germline transcription during thymocyte development. These results indicate that the activation of both Tcrg and Tcrd enhancers during γδ T-cell development in the thymus depends on the same NOTCH1- and interleukin-7-mediated signaling pathways. Understanding the regulation of the Tcrd enhancer during thymocyte development might lead to a better understanding of the enhancer-dependent mechanisms involved in the genomic instability and chromosomal translocations that cause leukemia.

Comparative chromatin accessibility upon BDNF stimulation delineates neuronal regulatory elements

Neuronal stimulation induced by the brain-derived neurotrophic factor (BDNF) triggers gene expression, which is crucial for neuronal survival, differentiation, synaptic plasticity, memory formation, and neurocognitive health. However, its role in chromatin regulation is unclear. Here, using temporal profiling of chromatin accessibility and transcription in mouse primary cortical neurons upon either BDNF stimulation or depolarization (KCl), we identify features that define BDNF-specific chromatin-to-gene expression programs. Enhancer activation is an early event in the regulatory control of BDNF-treated neurons, where the bZIP motif-binding Fos protein pioneered chromatin opening and cooperated with co-regulatory transcription factors (Homeobox, EGRs, and CTCF) to induce transcription. Deleting cis-regulatory sequences affect BDNF-mediated Arc expression, a regulator of synaptic plasticity. BDNF-induced accessible regions are linked to preferential exon usage by neurodevelopmental disorder-related genes and the heritability of neuronal complex traits, which were validated in human iPSC-derived neurons. Thus, we provide a comprehensive view of BDNF-mediated genome regulatory features using comparative genomic approaches to dissect mammalian neuronal stimulation.

Bioinformatic Design of Dendritic Cell-Specific Synthetic Promoters

Next-generation DNA vectors for cancer immunotherapies and vaccine development require promoters eliciting predefined transcriptional activities specific to target cell types, such as dendritic cells (DCs), which underpin immune response. In this study, we describe the de novo design of DC-specific synthetic promoters via in silico assembly of cis-transcription factor response elements (TFREs) that harness the DC transcriptional landscape. Using computational genome mining approaches, candidate TFREs were identified within promoter sequences of highly expressed DC-specific genes or those exhibiting an upregulated expression during DC maturation. Individual TFREs were then screened in vitro in a target DC line and off-target cell lines derived from skeletal muscle, fibroblast, epithelial, and endothelial cells using homotypic (TFRE repeats in series) reporter constructs. Based on these data, a library of heterotypic promoter assemblies varying in the TFRE composition, copy number, and sequential arrangement was constructed and tested in vitro to identify DC-specific promoters. Analysis of the transcriptional activity and specificity of these promoters unraveled underlying design rules, primarily TFRE composition, which govern the DC-specific synthetic promoter activity. Using these design rules, a second library of exclusively DC-specific promoters exhibiting varied transcriptional activities was generated. All DC-specific synthetic promoter assemblies exhibited >5-fold activity in the target DC line relative to off-target cell lines, with transcriptional activities ranging from 8 to 67% of the nonspecific human cytomegalovirus (hCMV-IE1) promoter. We show that bioinformatic analysis of a mammalian cell transcriptional landscape is an effective strategy for de novo design of cell-type-specific synthetic promoters with precisely controllable transcriptional activities.

OLOGRAM-MODL: mining enriched n-wise combinations of genomic features with Monte Carlo and dictionary learning

Most epigenetic marks, such as Transcriptional Regulators or histone marks, are biological objects known to work together in n-wise complexes. A suitable way to infer such functional associations between them is to study the overlaps of the corresponding genomic regions. However, the problem of the statistical significance of n-wise overlaps of genomic features is seldom tackled, which prevent rigorous studies of n-wise interactions. We introduce OLOGRAM-MODL, which considers overlaps between n ≥ 2 sets of genomic regions, and computes their statistical mutual enrichment by Monte Carlo fitting of a Negative Binomial distribution, resulting in more resolutive P-values. An optional machine learning method is proposed to find complexes of interest, using a new itemset mining algorithm based on dictionary learning which is resistant to noise inherent to biological assays. The overall approach is implemented through an easy-to-use CLI interface for workflow integration, and a visual tree-based representation of the results suited for explicability. The viability of the method is experimentally studied using both artificial and biological data. This approach is accessible through the command line interface of the pygtftk toolkit, available on Bioconda and from https://github.com/dputhier/pygtftk

Transcription factor control of virulence in phytopathogenic fungi

Plant-pathogenic fungi are a significant threat to economic and food security worldwide. Novel protection strategies are required and therefore it is critical we understand the mechanisms by which these pathogens cause disease. Virulence factors and pathogenicity genes have been identified, but in many cases their roles remain elusive. It is becoming increasingly clear that gene regulation is vital to enable plant infection and transcription factors play an essential role. Efforts to determine their regulatory functions in plant-pathogenic fungi have expanded since the annotation of fungal genomes revealed the ubiquity of transcription factors from a broad range of families. This review establishes the significance of transcription factors as regulatory elements in plant-pathogenic fungi and provides a systematic overview of those that have been functionally characterized. Detailed analysis is provided on regulators from well-characterized families controlling various aspects of fungal metabolism, development, stress tolerance, and the production of virulence factors such as effectors and secondary metabolites. This covers conserved transcription factors with either specialized or nonspecialized roles, as well as recently identified regulators targeting key virulence pathways. Fundamental knowledge of transcription factor regulation in plant-pathogenic fungi provides avenues to identify novel virulence factors and improve our understanding of the regulatory networks linked to pathogen evolution, while transcription factors can themselves be specifically targeted for disease control. Areas requiring further insight regarding the molecular mechanisms and/or specific classes of transcription factors are identified, and direction for future investigation is presented.

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

TAZ-CAMTA1 and YAP-TFE3 alter the TAZ/YAP transcriptome by recruiting the ATAC histone acetyltransferase complex

Epithelioid hemangioendothelioma (EHE) is a vascular sarcoma that metastasizes early in its clinical course and lacks an effective medical therapy. The TAZ-CAMTA1 and YAP-TFE3 fusion proteins are chimeric transcription factors and initiating oncogenic drivers of EHE. A combined proteomic/genetic screen in human cell lines identified YEATS2 and ZZZ3, components of the Ada2a-containing histone acetyltransferase (ATAC) complex, as key interactors of both fusion proteins despite the dissimilarity of the C terminal fusion partners CAMTA1 and TFE3. Integrative next-generation sequencing approaches in human and murine cell lines showed that the fusion proteins drive a unique transcriptome by simultaneously hyperactivating a TEAD-based transcriptional program and modulating the chromatin environment via interaction with the ATAC complex. Interaction of the ATAC complex with both fusion proteins indicates that it is a key oncogenic driver and unifying enzymatic therapeutic target for this sarcoma. This study presents an approach to mechanistically dissect how chimeric transcription factors drive the formation of human cancers.

The proliferation of human cells is tightly regulated to ensure that enough cells are made to build and repair organs and tissues, while at the same time stopping cells from dividing uncontrollably and damaging the body. To get the right balance, cells rely on physical and chemical cues from their environment that trigger the biochemical signals that regulate two proteins called TAZ and YAP. These proteins control gene activity by regulating the rate at which genes are copied to produce proteins. If this process becomes dysregulated, cells can grow uncontrollably, causing cancer.

In cancer cells, it is common to find TAZ and YAP fused to other proteins. In epithelioid hemangioendothelioma, a rare cancer that grows in the blood vessels, cancerous growth can be driven by a version of TAZ fused to the protein CAMTA1, or a version of YAP fused to the protein TFE3. While the role of TAZ and YAP in promoting gene activity is known, it is unclear how CAMTA1 and TFE3 contribute to cell growth becoming dysregulated.

Merritt, Garcia et al. studied sarcoma cell lines to show that these two fusion proteins, TAZ-CAMTA1 and YAP-TFE3, change the pattern of gene activity seen in the cells compared to TAZ or YAP alone. An analysis of molecules that interact with the two fusion proteins identified a complex called ATAC as the cause of these changes. This complex adds chemical markers to DNA-packaging proteins, which control which genes are available for activation. The fusion proteins combine the ability of TAZ and YAP to control gene activity and the ability of CAMTA1 and TFE3 to make DNA more accessible, allowing the fusion proteins to drive uncontrolled cancerous growth.

Similar TAZ and YAP fusion proteins have been found in other cancers, which can activate genes and potentially alter DNA packaging. Targeting drug development efforts at the proteins that complex with TAZ and YAP fusion proteins may lead to new therapies.

Identification of long regulatory elements in the genome of Plasmodium falciparum and other eukaryotes

Long regulatory elements (LREs), such as CpG islands, polydA:dT tracts or AU-rich elements, are thought to play key roles in gene regulation but, as opposed to conventional binding sites of transcription factors, few methods have been proposed to formally and automatically characterize them. We present here a computational approach named DExTER (Domain Exploration To Explain gene Regulation) dedicated to the identification of candidate LREs (cLREs) and apply it to the analysis of the genomes of P. falciparum and other eukaryotes. Our analyses show that all tested genomes contain several cLREs that are somewhat conserved along evolution, and that gene expression can be predicted with surprising accuracy on the basis of these long regions only. Regulation by cLREs exhibits very different behaviours depending on species and conditions. In P. falciparum and other Apicomplexan organisms as well as in Dictyostelium discoideum, the process appears highly dynamic, with different cLREs involved at different phases of the life cycle. For multicellular organisms, the same cLREs are involved in all tissues, but a dynamic behavior is observed along embryonic development stages. In P. falciparum, whose genome is known to be strongly depleted of transcription factors, cLREs are predictive of expression with an accuracy above 70%, and our analyses show that they are associated with both transcriptional and post-transcriptional regulation signals. Moreover, we assessed the biological relevance of one LRE discovered by DExTER in P. falciparum using an in vivo reporter assay. The source code (python) of DExTER is available at https://gite.lirmm.fr/menichelli/DExTER.

Fra-1 regulates its target genes via binding to remote enhancers without exerting major control on chromatin architecture in triple negative breast cancers

The ubiquitous family of dimeric transcription factors AP-1 is made up of Fos and Jun family proteins. It has long been thought to operate principally at gene promoters and how it controls transcription is still ill-understood. The Fos family protein Fra-1 is overexpressed in triple negative breast cancers (TNBCs) where it contributes to tumor aggressiveness. To address its transcriptional actions in TNBCs, we combined transcriptomics, ChIP-seqs, machine learning and NG Capture-C. Additionally, we studied its Fos family kin Fra-2 also expressed in TNBCs, albeit much less. Consistently with their pleiotropic effects, Fra-1 and Fra-2 up- and downregulate individually, together or redundantly many genes associated with a wide range of biological processes. Target gene regulation is principally due to binding of Fra-1 and Fra-2 at regulatory elements located distantly from cognate promoters where Fra-1 modulates the recruitment of the transcriptional co-regulator p300/CBP and where differences in AP-1 variant motif recognition can underlie preferential Fra-1- or Fra-2 bindings. Our work also shows no major role for Fra-1 in chromatin architecture control at target gene loci, but suggests collaboration between Fra-1-bound and -unbound enhancers within chromatin hubs sometimes including promoters for other Fra-1-regulated genes. Our work impacts our view of AP-1.

Transcriptional enhancers: from prediction to functional assessment on a genome-wide scale

Enhancers are cis-regulatory sequences located distally to target genes. These sequences consolidate developmental and environmental cues to coordinate gene expression in a tissue-specific manner. Enhancer function and tissue specificity depend on the expressed set of transcription factors, which recognize binding sites and recruit cofactors that regulate local chromatin organization and gene transcription. Unlike other genomic elements, enhancers are challenging to identify because they function independently of orientation, are often distant from their promoters, have poorly defined boundaries, and display no reading frame. In addition, there are no defined genetic or epigenetic features that are unambiguously associated with enhancer activity. Over recent years there have been developments in both empirical assays and computational methods for enhancer prediction. We review genome-wide tools, CRISPR advancements, and high-throughput screening approaches that have improved our ability to both observe and manipulate enhancers in vitro at the level of primary genetic sequences, chromatin states, and spatial interactions. We also highlight contemporary animal models and their importance to enhancer validation. Together, these experimental systems and techniques complement one another and broaden our understanding of enhancer function in development, evolution, and disease.

Histone ChIP-Seq identifies differential enhancer usage during chondrogenesis as critical for defining cell-type specificity

Epigenetic mechanisms are known to regulate gene expression during chondrogenesis. In this study, we have characterized the epigenome during the in vitro differentiation of human mesenchymal stem cells (hMSCs) into chondrocytes. Chromatin immunoprecipitation followed by next‐generation sequencing (ChIP‐seq) was used to assess a range of N‐terminal posttranscriptional modifications (marks) to histone H3 lysines (H3K4me3, H3K4me1, H3K27ac, H3K27me3, and H3K36me3) in both hMSCs and differentiated chondrocytes. Chromatin states were characterized using histone ChIP‐seq and cis‐regulatory elements were identified in chondrocytes. Chondrocyte enhancers were associated with chondrogenesis‐related gene ontology (GO) terms. In silico analysis and integration of DNA methylation data with chondrogenesis chromatin states revealed that enhancers marked by histone marks H3K4me1 and H3K27ac were de‐methylated during in vitro chondrogenesis. Similarity analysis between hMSC and chondrocyte chromatin states defined in this study with epigenomes of cell‐types defined by the Roadmap Epigenomics project revealed that enhancers are more distinct between cell‐types compared to other chromatin states. Motif analysis revealed that the transcription factor SOX9 is enriched in chondrocyte enhancers. Luciferase reporter assays confirmed that chondrocyte enhancers characterized in this study exhibited enhancer activity which may be modulated by DNA methylation and SOX9 overexpression. Altogether, these integrated data illustrate the cross‐talk between different epigenetic mechanisms during chondrocyte differentiation.