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At least 19 recordsLinked to original sources

PubMed2025

Short activation domains control chromatin association of transcription factors.

Transcription factors regulate gene expression with DNA-binding domains (DBDs) and activation domains. Despite mounting evidence to the contrary, it is frequently assumed that DBDs are solely responsible for interacting with DNA and chromatin. Here, we used single-molecule tracking of transcription factors in living cells to show that short activation domains can control the fraction of molecules bound to chromatin. Stronger activation domains have higher bound fractions and longer residence times on chromatin. Furthermore, mutations that increase activation domain strength also increase chromatin binding. This trend was consistent in four different activation domains and their mutants. This effect further held for activation domains appended to three different structural classes of DBDs. Stronger activation domains with high chromatin-bound fractions also exhibited increased binding to the p300 coactivator in proximity-assisted photoactivation experiments. Taken together, these results suggest that activation domains play a major role in tethering transcription factors to chromatin, challenging the traditional view that the DBD is the sole driver of genome binding.

Journal Article↗

PubMed2005

SUMO modification of the Ets-related transcription factor ERM inhibits its transcriptional activity.

A variety of transcription factors are post-translationally modified by SUMO, a 97-residue ubiquitin-like protein bound covalently to the targeted lysine. Here we describe SUMO modification of the Ets family member ERM at positions 89, 263, 293, and 350. To investigate how SUMO modification affects the function of ERM, Ets-responsive intercellular adhesion molecule 1 (ICAM-1) and E74 reporter plasmids were employed to demonstrate that SUMO modification causes inhibition of ERM-dependent transcription without affecting the subcellular localization, stability, or DNA-binding capacity of the protein. When the adenoviral protein Gam1 or the SUMO protease SENP1 was used to inhibit the SUMO modification pathway, ERM-dependent transcription was de-repressed. These results demonstrate that ERM is subject to SUMO modification and that this post-translational modification causes inhibition of transcription-enhancing activity.

Adenoviridae↗

PubMed2024

TFinder: A Python Web Tool for Predicting Transcription Factor Binding Sites.

Transcription is a key cell process that consists of synthesizing several copies of RNA from a gene DNA sequence. This process is highly regulated and closely linked to the ability of transcription factors to bind specifically to DNA. TFinder is an easy-to-use Python web portal allowing the identification of Individual Motifs (IM) such as Transcription Factor Binding Sites (TFBS). Using the NCBI API, TFinder extracts either promoter or gene terminal regulatory regions, through a simple query of NCBI gene name or ID. It enables simultaneous analysis across five different species for an unlimited number of genes. TFinder searches for Individual Motifs in different formats, including IUPAC codes and JASPAR entries. Moreover, TFinder also allows de novo generations of a Position Weight Matrix (PWM) and the use of already established PWM. Finally, the data are provided in a tabular and a graph format showing the relevance and the P-value of the Individual Motifs found as well as their location relative to the Transcription Start Site (TSS) or the terminal region of the gene. The results are then sent by email to users facilitating the subsequent data analysis and sharing. TFinder is written in Python and freely available on GitHub under the MIT license: https://github.com/Jumitti/TFinder. It can be accessed as a web application implemented in Streamlit at https://tfinder-ipmc.streamlit.app. Resources are available on Streamlit "Resources" tab. TFINDER strength is that it relies on an all-in-one intuitive tool allowing users inexperienced with bioinformatics tools to retrieve gene regulatory regions sequences in multiple species and to search for individual motifs in a huge number of genes.

Transcription Factors↗

PubMed2026

Systematic identification pepper CaE2F transcription factor reveals the role of CaDPb in drought stress response.

The EARLY 2 FACTOR (E2F) transcription factor (TF) family plays a pivotal role in regulating plant development and adaptations to environmental stresses. However, the physiological function of E2Fs in pepper (Capsicum annuum L.) are not well elucidated. In this work, we conduct a comprehensive genome-wide annotation of the E2F family within the Zunla-1 pepper genome and further explore the biological roles of CaDPb in response to drought stress. Through systematic bioinformatics analysis, we identify a total of nine CaE2F genes within the Zunla-1 genome, categorizing them into three distinct subgroups. Additionally, we discover multiple cis-regulatory elements in the CaE2F promoter regions associated with responses to plant hormones and drought stress. Public RNA-seq datasets reveal distinct expression profiles of CaE2F genes across various pepper tissues and their responses to environmental stimuli and plant hormones. Subsequently, the CaDPb gene is further functionally verified in drought response. Our findings indicate that TRV2:CaDPb silenced pepper plants are more sensitivity to drought. Furthermore, we show that CaDPb participates in the regulation of reactive oxygen species (ROS) production, the expression of drought-responsive genes, and the modulation of stomatal aperture. Taken together, our findings provide a comprehensive characterization of E2F genes in pepper and offer insights into the biological function of CaDPb in pepper drought stress response.

Capsicum↗

PubMed2026

Molecular evolution and immune expression analysis of ELF transcription factors in Lethenteron reissneri.

As important members of the ETS superfamily, the E74-like factor (ELF) transcription factor family regulates gene transcription through a conserved ETS domain and plays critical roles in immune regulation. However, the evolutionary characteristics and functions of this family in lampreys (Lethenteron reissneri) remain unclear. In this study, the ELF gene family of lampreys (Lr-ELF1, Lr-ELF2, Lr-ELF3, and Lr-ELF5) was systematically identified, and their molecular evolutionary features and immune response functions were investigated. Phylogenetic analysis revealed evolutionary characteristics reflecting the transition from jawless to jawed vertebrates. Domain architecture, gene structure, and three-dimensional structural analyses indicated that these genes appear to be conserved among vertebrates, with their three-dimensional structures showing high similarity to the core secondary structural elements of human homologous proteins. Synteny analysis demonstrated significant differences in the genomic neighborhoods of ELF genes between lampreys and jawed vertebrates. Quantitative real-time PCR (qRT-PCR) was performed with three biological and three technical replicates; relative expression levels were calculated using the ΔCt method, and statistical analysis was carried out with GraphPad Prism 9. Quantitative real-time PCR (qRT-PCR) results suggested that the ELF gene family may be involved in immune defense. This study not only enriches our understanding of the evolution of ELF genes but also provides new insights into the roles of lamprey ELFs in immune defense.

Animals↗

PubMed2025

Ubiquitination of transcription factors in cancer: unveiling therapeutic potential.

Transcription factors, pivotal in gene expression regulation, are essential in cancer progression. Their function is meticulously regulated by post-translational modifications, including ubiquitination. This process, which marks proteins for degradation, can either enhance or inhibit the function of transcription factors, contingent on the context. In cancers, dysregulated ubiquitination of transcription factors contributes to the hallmark of uncontrolled growth and survival of tumors. For example, tumor suppressors such as p53 might be degraded prematurely due to abnormal ubiquitination, causing genomic instability. On the other hand, oncogenic transcription factors may gain stability via ubiquitination, thus facilitating tumorigenesis. Targeting the ubiquitin-proteasome system (UPS) therefore could be a viable therapeutic approach in cancer. Emerging treatments aim to block the ubiquitination of oncogenic transcription factors or to stabilize tumor suppressors. This review underscores the critical impact of transcription factor-altered ubiquitination on cancer progression. Additionally, it outlines innovative therapeutic approaches that involve inhibitors or drugs directed at specific ubiquitin E3 ligases and deubiquitinases (DUBs) that regulate transcription factor activity.

Humans↗

PubMed2004

Regulation of cell cycle-specific gene expression through cyclin-dependent kinase-mediated phosphorylation of the forkhead transcription factor Fkh2p.

The forkhead transcription factor Fkh2p acts in a DNA-bound complex with Mcm1p and the coactivator Ndd1p to regulate cell cycle-dependent expression of the CLB2 gene cluster in Saccharomyces cerevisiae. Here, we demonstrate that Fkh2p is a target of cyclin-dependent protein kinases and that phosphorylation of Fkh2p promotes interactions between Fkh2p and the coactivator Ndd1p. These phosphorylation-dependent changes in the Fkh2p-Ndd1p complex play an important role in the cell cycle-regulated expression of the CLB2 cluster. Our data therefore identify an important regulatory target for cyclin-dependent kinases in the cell cycle and further our molecular understanding of the key cell cycle regulatory transcription factor Fkh2p.

Binding Sites↗

PubMed2026

Transcription Factor SP1 Drives Myocardial Ischemia/reperfusion Injury By Transcription Activation-mediated GADD45G Upregulation.

Myocardial ischemia-reperfusion injury (MIRI) is an unresolved clinically fatal complication in the management of acute myocardial infarction (AMI). Growth arrest and DNA damage-inducible gene 45 Gamma (GADD45G) plays a vital role in the regulation of MIRI. However, the underlying mechanisms remain unclear. GADD45G and SP1 expression were upregulated in hypoxia/reoxygenation (H/R)-treated H9C2 cells. H/R treatment repressed H9C2 cell viability, and induced apoptosis, oxidative stress, and inflammatory response. Moreover, GADD45G deficiency could relieve H/R-triggered H9C2 cell injury. In mechanism, SP1 was a transcription factor of GADD45G and activated the transcription of GADD45G via binding to its promoter region. Besides, SP1 knockdown alleviated MI/R-induced pathological damage in the myocardial tissue of rats by regulating GADD45G. In conclusion, SP1 could promote H/R-induced cardiomyocyte injury and MI/R-caused rat myocardial tissue pathological injury by increasing GADD45G, providing a promising therapeutic target for MIRI treatment.

Animals↗

PubMed2026

How negative sampling shapes the performance of transcription factor binding site prediction models.

MOTIVATION: Transcription factors (TFs) are key players in gene regulation and development, where they activate and repress gene expression through DNA binding. Predicting transcription factor binding sites (TFBSs) has long been an active area of research, with many deep learning methods developed to tackle this problem. These models are often trained on TF ChIP-seq data, which is generally seen as only providing positive samples. The choice of datasets and negative sampling techniques is a critical yet often overlooked aspect of this work. RESULTS: In this study, we investigate the impact of different negative sampling techniques on TFBS prediction performance. We create high-quality test datasets based on ChIP-seq and ATAC-seq data, where true negatives can be identified as positions that are accessible but not bound by the TF in question. We then train models using various negative sampling techniques, including genomic sampling, shuffling, dinucleotide shuffling, neighborhood sampling, and cell line specific sampling, simulating cases where matching ATAC-seq data is not available. Our results show that, generally, metrics calculated on training datasets give inflated performance scores. Of the tested techniques, genomic sampling of negatives based on similarity to the positives performed by far the best, although still not reaching the performance of baseline models trained on high-quality datasets. Models trained on dinucleotide shuffled negatives performed poorly, despite being a common practice in the field. Our findings highlight the importance of carefully selecting negative sampling techniques for TFBS prediction, as they can significantly impact model performance and the interpretation of results. AVAILABILITY AND IMPLEMENTATION: The code used in this study is available at https://github.com/NatanTourne/TFBS-negatives (DOI: 10.5281/zenodo.18007567).

Binding Sites↗

PubMed2026

Motif-Cluster: Motif driven prioritization of transcription factor binding clusters.

Genome-wide analyses of transcription factor (TF) motif binding sites have largely emphasized individual high-affinity sites, while overlooking the regulatory importance of locally repetitive motif clusters. Such clusters, including combinations of weak and strong binding sites, can collectively enhance TF occupancy and regulatory activity. Here we present Motif-Cluster, an open-source framework for motif-driven prioritization and visualization of TF binding clusters using sequence information alone. Motif-Cluster integrates a density-based clustering strategy with flexible modeling of binding-site gaps and affinity signals, enabling the identification and ranking of candidate regulatory regions without requiring experimental binding data. Through simulations and multiple real-data analyses, we show that combining gap distributions with binding affinity effectively balances cluster size and signal strength while reducing noise from weak sites. Application to ZNF410 successfully recovers the previously characterized binding clusters in the CHD4 promoter, which are conserved between human and mouse. Additional case studies involving PHB1, TWIST1, and EGR1 further demonstrate the general applicability of the method across diverse transcription factors. Motif-Cluster also provides intuitive visualization and reproducible workflows to facilitate interpretation of spatially dense motif patterns. Overall, Motif-Cluster offers a robust and flexible approach for prioritizing transcription factor regulatory regions from genome-wide motif scans, enabling biological discovery and guiding experimental design, particularly in settings where direct genome-wide binding assays are unavailable.

Transcription Factors↗

PubMed2026

Acidic transcription factors position the genome at nuclear speckles through transcription-dependent and -independent mechanisms.

A small fraction of the genome reproducibly positions near nuclear speckles (NSs), increasing the expression and/or splicing efficiency of NS-associated genes. How specific genomic regions in mammalian cells are targeted to NSs remains unclear. Here, we demonstrate the establishment of genome-wide NS association without active transcription. We show that DNA sequences derived from NS-associated regions, when integrated as transgenes, are autonomously targeted to NSs. By systematically dissecting one such genomic locus, the COL1A1-SGCA locus, we identified redundant NS-targeting cis-regulatory elements, including an ∼600-bp fragment with 17 binding motifs for 8 transcription factors (TFs). Four NS-targeting TFs within this fragment contain acidic activation domains (AADs) that provide both chromatin-context and transcription-dependent NS targeting, properties that appear to be common among several other tested AADs. A subset of acidic activator TFs contains an additional, transcription-independent NS-targeting activity. Our findings establish diverse and partially redundant NS-targeting activities, which may facilitate dynamic gene positioning at the NS periphery for context-specific transcriptional responses.

Transcription, Genetic↗

PubMed2023

H3.3 contributes to chromatin accessibility and transcription factor binding at promoter-proximal regulatory elements in embryonic stem cells.

BACKGROUND: The histone variant H3.3 is enriched at active regulatory elements such as promoters and enhancers in mammalian genomes. These regions are highly accessible, creating an environment that is permissive to transcription factor binding and the recruitment of transcriptional coactivators that establish a unique chromatin post-translational landscape. How H3.3 contributes to the establishment and function of chromatin states at these regions is poorly understood. RESULTS: We perform genomic analyses of features associated with active promoter chromatin in mouse embryonic stem cells (ESCs) and find evidence of subtle yet widespread promoter dysregulation in the absence of H3.3. Loss of H3.3 results in reduced chromatin accessibility and transcription factor (TF) binding at promoters of expressed genes in ESCs. Likewise, enrichment of the transcriptional coactivator p300 and downstream histone H3 acetylation at lysine 27 (H3K27ac) is reduced at promoters in the absence of H3.3, along with reduced enrichment of the acetyl lysine reader BRD4. Despite the observed chromatin dysregulation, H3.3 KO ESCs maintain transcription from ESC-specific genes. However, upon undirected differentiation, H3.3 KO cells retain footprinting of ESC-specific TF motifs and fail to generate footprints of lineage-specific TF motifs, in line with their diminished capacity to differentiate. CONCLUSIONS: H3.3 facilitates DNA accessibility, transcription factor binding, and histone post-translational modification at active promoters. While H3.3 is not required for maintaining transcription in ESCs, it does promote de novo transcription factor binding which may contribute to the dysregulation of cellular differentiation in the absence of H3.3.

Animals↗

PubMed2026

Oriented binding of transcription factors to nucleosomes remodels chromatin at human promoters.

Transcription factors (TFs) can access nucleosomes via five distinct modes: gyre-spanning, periodic-binding, dyad-binding, and end-binding modes as well as an oriented binding mode, where the TF binding motif shows orientational preference relative to the nucleosome. Here, we report the first structure of an oriented TF:nucleosome complex, where two ELF2 proteins bind to a double motif located at superhelical location +4, unwinding four helical turns of DNA from the nucleosome. We further show that unlike previously described pioneer factors, ELF2 is able to occupy all of its unmethylated, high-affinity double motifs in vivo. Motifs of ELF2 and another oriented nucleosome binder, YY1, are highly enriched downstream of transcription start sites (TSSs) of highly expressed genes, with the motifs oriented in such a way that the TSS becomes accessible upon TF binding. Our results suggest that oriented binding may be generally important for high transcriptional activity.

Nucleosomes↗

PubMed2026

An atlas of non-redundant sequences and structures of transcription factor assemblies across domains of life.

Transcription factors (TFs) regulate gene expression by controlling the recruitment of transcriptional machinery to regulatory regions of the genome. Nearly 10% of the human genome encodes TFs, making them one of the largest protein families. Despite their central roles in gene regulation, TFs are historically considered challenging therapeutic targets due to their complex interactions with DNA, RNA and associated proteins. Although recent progress in studying TFs both at molecular and structural level excels our understanding on their function, yet a universal rule decoding their recognition process remains elusive. Here, we present a curated non-redundant dataset of TFs with 3570 sequences and 377 structures. We further characterize "unique interfaces" by quantifying interface identity across interacting chains in TF assemblies. Surprisingly, our data shows that the "unique interfaces" have optimal size ranging from 2000 Å2 to 4000 Å2 irrespective of their quaternary assembly. To understand the functional diversity, we integrate sequence motifs, structural domains, subcellular localization and functional enrichment of TFs. We have also catalogued association of TFs with various human diseases. Our dataset provides a comprehensive platform to perform large scale analysis of TF-assemblies and aid in computational methods for their prediction across domains of life.

Gene regulation↗

PubMed2026

MegaPlantTF: a machine learning framework for comprehensive identification and classification of plant transcription factors.

MOTIVATION: Understanding the role of transcription factors (TFs) in plants is essential for the study of gene regulation and various biological processes. However, both TF detection and classification remain challenging due to the great diversity and complexity of these proteins. Conventional approaches, such as BLAST, often suffer from high computational complexity and limited performance on less common TF families. RESULTS: We introduce MegaPlantTF, the first comprehensive machine learning and deep learning framework for the prediction (TF versus non-TF) and classification (family-level) of plant TFs. Our method employs k-mer-based protein representations and a two-stage architecture combining a deep feed-forward neural network with a stacking ensemble classifier. To ensure robust performance assessment, we report micro-, macro-, and weighted-average performance metrics, providing a holistic evaluation of both frequent and underrepresented TF families. Additionally, we employ threshold-based evaluation to calibrate confidence in TF detection. The results show that MegaPlantTF achieves strong accuracy and precision, particularly with a k-mer size of 3 and a classification threshold of 0.5, and maintains stable performance even under stringent thresholds. In addition to the standard cross-validation tests, a use case study on Sorghum bicolor confirms that our method performs strongly in the genome-wide analysis, making it highly suitable for large-scale TF identification and classification tasks. MegaPlantTF represents a novel contribution by integrating k-mer encoding, binary family-specific classifiers, and a two-stage stacking ensemble into a unified, reproducible framework for large-scale plant TF identification and classification. AVAILABILITY AND IMPLEMENTATION: MegaPlantTF is freely accessible through a public web server available at https://bioinformatics.um6p.ma/MegaPlantTF. The complete source code, including pretrained models and example datasets, is available at https://github.com/Bioinformatics-UM6P/MegaPlantTF.

Transcription Factors↗

PubMed2025

Missense variants in human forkhead transcription factors reveal determinants of forkhead DNA bispecificity.

Recognition of specific DNA sequences by transcription factors (TFs) is a key step in transcriptional control of gene expression. While most forkhead (FH) TFs bind either an FKH (RYAAAYA) or an FHL (GACGC) recognition motif, some FHs can bind both motifs. Mechanisms that control whether an FH is monospecific vs. bispecific have remained unknown. Screening a library of 12 reference FH proteins, 61 naturally occurring missense variants including clinical variants, and 22 designed mutant FHs for DNA-binding activity using universal ("all 10-mer") protein-binding microarrays revealed non-DNA-contacting residues that control mono- vs. bispecificity. Variation in non-DNA-contacting amino acid residues of TFs is associated with human traits and may play a role in the evolution of TF DNA-binding activities and gene regulatory networks.

Humans↗

PubMed2026

Evolutionary architecture and lineage-specific diversification of Forkhead box transcription factors in Perna viridis.

The Forkhead box (Fox) transcription factors are evolutionarily conserved regulators of development, cell cycle, and apoptosis across metazoans. This study provides the first comprehensive genome-wide analysis of the Fox gene family in the Asian green mussel (Perna viridis). We identified 28 Fox genes distributed across 10 chromosomes. Comparative analysis reveals the absence of the FoxI, FoxQ1, FoxR and FoxS subfamily, consistent with other bivalves and indicative of lineage-specific gene loss during molluscan evolution. Notably, gene duplications in the FoxAB, FoxD, FoxH, FoxN1-4, FoxQ2 and FoxQD subfamilies may reflect functional diversification associated with environmental adaptation. Exon-intron structural variability, including intron loss in several paralogues, suggests structural diversification and potential regulatory variation. Phylogenetic reconstruction confirmed the monophyly of core Fox classes while highlighting divergent expansion patterns in lophotrochozoans. Selection analyses showed strong purifying selection across duplicated Fox paralogs, supporting functional conservation after lineage-specific expansion. Gene Ontology enrichment linked Fox genes to stress response, apoptosis, and transcriptional regulation. By integrating phylogenetic, structural, and transcriptomic analyses, this study provides a genomic framework for understanding Fox gene organisation, evolution, and tissue-associated expression patterns in Perna viridis and establishes a comparative resource for future functional studies in bivalves.

Animals↗

PubMed2026

Positional grammar of transcription factor binding partitions developmental and stress-response regulation in plants.

Understanding how transcription factor binding site (TFBS) position influences gene regulation remains a fundamental challenge in plants. Here, we integrate conserved multiDAP TFBS maps for 244 transcription factors (TFs) with single-nucleus chromatin accessibility, cell type-resolved gene expression, and hormone-response datasets across Brassicaceae species to determine how TFBS position relates to regulatory function. Although conserved TFBSs are enriched near transcription start sites (TSSs), TSS-proximal accessibility poorly predicts cell type-specific expression. Instead, cell type-specific expression correlates best with conserved TFBSs embedded in cell type-restricted chromatin, with TF family-specific distributions across distal promoters and introns. In contrast, TSS-proximal TFBSs in broadly accessible chromatin are associated with rapid transcriptional responses to abiotic and biotic stress hormones. Coding sequence TFBSs mark a distinct regulatory context in which the same DNA sequence encodes both amino acid sequence and TF motifs, including evidence that CDS-localized ABR1 binding may contribute to repression during hormone response. Finally, distal upstream regions contain conserved multi-family TF clusters with enhancer-like features overlapping rare cell type-specific accessible chromatin and enriched near genes controlling embryonic, meristematic, and hormone-dependent developmental patterning. Together, these results support a positional grammar in which TFBS position and chromatin context jointly partition developmental, stress-responsive, and repressive regulatory output in plants.

Transcription Factors↗