Sequence-specific interactions of transcription factors (TFs) with genomic DNA underlie many cellular processes. High-throughput in vitro binding assays coupled with machine learning have made it possible to accurately define such molecular recognition in a biophysically interpretable way for hundreds of TFs across many structural families, providing new avenues for predicting how the sequence preference of a TF is impacted by disease-associated mutations in its DNA binding domain. We developed a method based on a reference-free tetrahedral representation of variation in base preference within a given structural family that can be used to accurately predict the effect of mutations in the protein sequence of the TF. Using the basic helix-loop-helix (bHLH) and homeodomain families as test cases, our results demonstrate the feasibility of accurately predicting the shifts (ΔΔΔG/RT) in binding free energy associated with TF mutants by leveraging high-quality DNA binding models for sets of homologous wild-type TFs.

The continued rise in recurrence and mortality rates of cervical cancer suggests the need to find novel therapeutic targets. Previous studies suggest that TRIP4 acts as a transcription factor to regulate cervical carcinogenesis and progression. Our aim was to explore whether the key downstream genes of TRIP4 functions same as TRIP4 in promoting cervical cancer development. We analyzed and confirmed the downstream targets of TRIP4 by RNA sequencing in cervical cancer cells with TRIP4 knockdown. The expression correlation between TRIP4 and GATA2 and the effect of GATA2 on cervical cancer cell growth were determined respectively by Western Blot, Scratch, Spheroid, and MTT analyses. Pulldown and ChIP experiments were performed to analyze the binding of TRIP4 to the promoter of GATA2. The clinical significance of GATA2 and TRIP4 expression in cervical cancer patients was analyzed by tissue microarray staining. GATA2 was highly expressed in cervical cancer tissues. Knockdown of GATA2 inhibited the growth, metastasis and stemness of cervical cancer cells and sensitized cervical cancer cells to radiation therapy. The inhibitory effect of TRIP4 knockdown on cervical cancer cells was rescued by GATA2 overexpression. Furthermore, TRIP4 could bind to the specific GATA2 promoter region, thereby activating its transcription. Clinical tissue microarray analysis indicated that the expression of TRIP4 and GATA2 was positively correlated, and high expression of both predicted a poor prognosis in cervical cancer patients. Our study demonstrated that GATA2 functions as the key downstream target of TRIP4 to promote cervical cancer progression and effective intervention of TRIP4/GATA2 signaling is expected to be developed as potential cervical cancer therapeutic strategy.

Regulation of gene expression helps determine various phenotypes in most cellular life forms. It is orchestrated at different levels and at the point of transcription initiation by transcription factors (TFs). TFs bind to DNA through domains that are evolutionarily related, by shared membership of the same superfamilies (TF-SFs), to those found in other nucleic acid binding and protein-binding functions (nTFs for non-TFs). Here we ask how TF DNA binding sequence families in eukaryotes have evolved in relation to their nTF relatives. TF numbers scale by power law with the total number of protein-coding genes differently in different clades, with fungi usually showing sub-linear powers whereas chordates show super-linear scaling. The LECA probably encoded a complex regulatory machinery with both TFs and nTFs, but with an excess of nTFs when compared to the relative distribution of TFs and nTFs in extant organisms. Losses drive the evolution of TFs and nTFs, with the possible exception of TFs in animals for some tree topologies. TFs are highly dynamic in evolution, showing higher gain and loss rates than nTFs in some TF-SFs though both are conserved to similar extents. Gains of TFs and nTFs are driven by the appearance of a large number of new sequence clusters in a small number of nodes, which determine the presence of as many as a third of extant TFs and nTFs as well as the relative presence of TFs and nTFs. Whereas nodes showing explosion of TF numbers belong to multicellular clades, those for nTFs lie among the fungi and the protists.

Echinococcosis, a zoonotic disease, significantly impacts the liver, with alveolar echinococcosis (AE) often leading to liver fibrosis and, in severe cases, cirrhosis. However, the molecular mechanisms by which AE infection promotes liver fibrosis remain incompletely understood. This study utilized bioinformatic analysis of existing microarray data to explore the shared mechanisms between AE and liver fibrosis and to identify potential therapeutic drug candidates. We analyzed gene expression datasets to identify common differentially expressed genes (DEGs), followed by enrichment analyses using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes databases to determine biological functions and pathways. A protein-protein interaction network was constructed, and key hub genes were identified using Cytoscape software. Immune cell infiltration was evaluated and correlated with hub gene expression. Transcription factors regulating DEGs were predicted using the TRRUST database, and drug-target interactions were explored using DrugBank. A total of 260 DEGs were identified, primarily associated with cell cycle regulation and immune response pathways. Ten hub genes (DLGAP5, AURKA, MELK, CCNB2, CCNA2, NUF2, BUB1B, BUB1, TOP2A, and CCNB1) were highlighted for their significant interconnectivity and functional relevance. Immune infiltration analysis revealed dysregulation in immune responses, and transcription factor analysis identified E2F3 as a key regulatory factor with decreased expression in both AE and liver fibrosis. Finally, 135 candidate drugs targeting these hub genes were identified, offering new insights into therapeutic strategies. This study provides a foundation for understanding the molecular mechanisms underlying AE-related liver fibrosis and highlights potential drug candidates for clinical exploration.

POU-family transcription factors regulate metazoan gene expression via a bipartite DNA-binding domain consisting of two covalently linked helix-turn-helix subdomains, POUS and POUH. POU factors bind as dimers to DNA half-sites to form complexes with a variable quaternary structure. To enhance the knowledge of the physical chemistry of dimeric POU/DNA recognition, we carried out a crystallographic and titration analysis of the cooperative homodimer formed by the POU factor OCT2 and an optimized palindromic DNA site known as MORE. The data evidence strong heterogeneity in the binding and formation of secondary complexes in site-specific DNA recognition by OCT2 at thermodynamic equilibrium. These secondary complexes are strictly contingent to the site-specific complex, detectable at subsaturating OCT2 concentrations, and cooperate with nonspecific binding to guide the affinity of the site-specific complex. Modulation with salt and poly[d(I-C)] unmasks the compensation between nonspecific DNA depleting unbound OCT2 on the one hand while driving specific binding by intermolecular transfer of OCT2 via secondary complexes on the other. Molecular dynamics simulations extend a mechanism, previously proposed for POU monomers, in which the two subdomains dynamically cross-link DNA strands to form supramolecular dimeric POU/DNA complexes at equilibrium.

BCL11B is a Cys2-His2 zinc-finger (C2H2-ZnF) domain-containing, DNA-binding, transcription factor with established roles in the development of various organs and tissues, primarily the immune and nervous systems. BCL11B germline variants have been associated with a variety of developmental syndromes. However, genotype-phenotype correlations along with pathophysiologic mechanisms of selected variants mostly remain elusive. To dissect these, we performed genotype-phenotype correlations of 92 affected individuals harboring a pathogenic or likely pathogenic BCL11B variant, followed by immune phenotyping, analysis of chromatin immunoprecipitation DNA-sequencing data, dual-luciferase reporter assays, and molecular modeling. These integrative analyses enabled us to define three clinical subtypes of BCL11B-related disorders. It is likely that gene-disruptive BCL11B variants and missense variants affecting zinc-binding cysteine and histidine residues cause mild to moderate neurodevelopmental delay with increased propensity for behavioral and dental anomalies, allergies and asthma, and reduced type 2 innate lymphoid cells. Missense variants within C2H2-ZnF DNA-contacting α helices cause highly variable clinical presentations ranging from multisystem anomalies with demise in the first years of life to late-onset, hyperkinetic movement disorder with poor fine motor skills. Those not in direct DNA contact cause a milder phenotype through reduced, target-specific transcriptional activity. However, missense variants affecting C2H2-ZnFs, DNA binding, and "specificity residues" impair BCL11B transcriptional activity in a target-specific, dominant-negative manner along with aberrant regulation of alternative DNA targets, resulting in more severe and unpredictable clinical outcomes. Taken together, we suggest that the phenotypic severity and variability is largely dependent on the DNA-binding affinity and specificity of altered BCL11B proteins.

The protein interactome of p65/RELA, the most active subunit of the transcription factor (TF) NF-κB, has not been previously determined in living cells. Using p65-miniTurbo fusion proteins and biotin tagging, we identify >350 RELA interactors from untreated and IL-1α-stimulated cells, including many TFs (47% of all interactors) and >50 epigenetic regulators belonging to different classes of chromatin remodeling complexes. A comparison with the interactomes of two point mutants of p65 reveals that the interactions primarily require intact dimerization rather than DNA-binding properties. A targeted RNAi screen for 38 interactors and subsequent functional transcriptome and bioinformatics studies identify gene regulatory (sub)networks, each controlled by RELA in combination with one of the TFs ZBTB5, GLIS2, TFE3/TFEB, or S100A8/A9. The large, dynamic and versatile high-resolution interactome of RELA and its gene regulatory logics provides a rich resource and a new framework for explaining how RELA cooperativity determines gene expression patterns.

The pea aphid, Acyrthosiphon pisum, is an emerging model system in functional and comparative genomics, in part due to the availability of new genomic approaches and the different sequencing and annotation efforts that the community has dedicated to this important crop pest insect. The pea aphid is also used as a model to study fascinating biological traits of aphids, such as their extensive polyphenisms, their bacteriocyte-confined nutritional symbiosis, or their adaptation to the highly unbalanced diet represented by phloem sap. To get insights into the molecular basis of all these processes, it is important to have an appropriate annotation of transcription factors (TFs), which would enable the reconstruction/inference of gene regulatory networks in aphids. Using the latest version of the A. pisum genome assembly and annotation, which represents the first chromosome-level pea aphid genome, we annotated the complete repertoire of A. pisum TFs and complemented this information by annotating genes encoding chromatin-associated and basal transcription machinery proteins. These annotations were done combining information from the model Drosophila melanogaster, for which we also provide a revisited list of these proteins, and de novo prediction. The comparison between the two model systems allowed the identification of major losses or expansions in each genome, while a deeper analysis was made of ZNF TFs (with certain families expanded in the pea aphid), and the Hox gene cluster (showing reorganization in gene position in the pea aphid compared to D. melanogaster). All annotations are available to the community through the Aphid Transcription Factors database (ATFdb), consolidating the various annotations we generated. ATFdb serves as a valuable resource for gene regulation studies in aphids.

Transcription factor binding sites (TFBSs) are critical in regulating gene expression. Precisely locating TFBSs can reveal the mechanisms of action of different transcription factors in gene transcription. Various deep learning methods have been proposed to predict TFBS; however, these models often need help demonstrating ideal performance under limited data conditions. Furthermore, these models typically have complex structures, which makes their decision-making processes difficult to transparentize. Addressing these issues, we have developed a framework named BCDB. This framework integrates multi-scale DNA information and employs a dual-branch output strategy. Integrating DNABERT, convolutional neural networks (CNN), and multi-head attention mechanisms enhances the feature extraction capabilities, significantly improving the accuracy of predictions. This innovative method aims to balance the extraction of global and local information, enhancing predictive performance while utilizing attention mechanisms to provide an intuitive way to explain the model's predictions, thus strengthening the overall interpretability of the model. Prediction results on 165 ChIP-seq datasets show that BCDB significantly outperforms other existing deep learning methods in terms of performance. Additionally, since the BCDB model utilizes transfer learning methods, it can transfer knowledge learned from many unlabeled data to specific cell line prediction tasks, allowing our model to achieve cross-cell line TFBS prediction. The source code for BCDB is available on https://github.com/ZhangLab312/BCDB.

Common clinical findings in patients with 19p13.3 duplication include intrauterine growth restriction, intellectual disability, developmental delay, microcephaly, and distinctive facial features. In this study, we report the case of a patient with 19p13.3 microduplication and novel clinical findings, specifically nephrotic syndrome.

A 4-year-old girl was admitted to our hospital in December 2020 with a fever and cough that had persisted for 3 days. A series of treatments, chromosomal microarray analysis (CMA) and whole exome sequencing (WES) were performed. Relevant literature was reviewed using the search terms "19p13.3" and "19p13.3 microduplication syndrome" in the China Knowledge Network, Wanfang Database, Weipu Journal Service Platform, and PubMed (date range: database establishment to September 2023). In addition to common symptoms, such as developmental delay, microcephaly, distinctive facial features, and congenital heart defects, the patient also had nephrotic syndrome, a previously unreported phenomenon. CMA results showed a 3.6 Mb fragment duplication (copy number: 3) in the chr19p13.3 region, containing 127 protein-coding genes (including CELF5, NFIC, SMIM24, PIAS4, ATCAY, MAP2K2, and ZBTB7A). WES revealed a filamin C mutation (p.Glu309Valfs × 11). The mutation status of the patient and her father was heterozygous, whereas the mutation was not detected in the mother.

Microduplication in the 19p13.3 region could be one of the genetic factors contributing to the observed clinical phenotypes. However, patients with developmental delay, microcephaly, distinctive facial features, congenital heart defects, and urogenital system disorders may exhibit these manifestations due to various genetic syndromes; therefore, simply considering the possibility of 19p13.3 microduplication syndrome based on these non-specific features is not sufficient. Further comprehensive evaluations, including CMA, should be conducted in conjunction with other genetic tests and detailed clinical examinations to accurately determine the underlying genetic causes.

Phytochromes are essential photoreceptors in plants that sense red and far-red light, playing a vital role in regulating plant growth and development through light signal transduction. Despite extensive research on phytochromes in model plants like Arabidopsis and rice, they have received relatively little attention in wheat. In this study, we employed bioinformatics methods to identify eight TaAkPHY genes in the Aikang58 wheat variety. Based on gene structure, conserved domains, and phylogenetic relationships, the TaAkPHY gene family exhibits a high degree of conservation. Synteny analysis revealed the evolutionary history of the PHY genes in Aikang58 and Chinese Spring wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), rice (Oryza sativa L.), maize (Zea mays L.), quinoa (Chenopodium quinoa Willd.), soybean [Glycine max (L.) Merr.], and Arabidopsis [Arabidopsis thaliana (L.) Heynh.]. Among these species, wheat is most closely related to barley, followed by rice and maize. The cis-acting element analysis indicates that the promoter regions of TaAkPHY genes contain a large number of CAT-box, CGTCA-motif, GC-motif, etc., which are mainly involved in plant development, hormone response, and stress response. Gene expression profiling demonstrated that TaAkPHY genes exhibit varying expression levels across different tissues and are induced by various stress conditions and plant hormone treatments. Co-expression network analysis suggested that TaAkPHY genes may specifically regulate downstream genes associated with stress responses, chloroplast development, and circadian rhythms. Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. This method helps to quickly extract key influencing factors from a large amount of complex data. Overall, these findings provide new insights into the role of phytochromes in wheat growth, development, and stress responses, laying a foundation for future research on phytochromes in wheat.

Photochemically triggered, transient, and temporally oscillatory-modulated transcription machineries are introduced. The resulting dynamic transcription circuits are implemented to guide photochemically triggered, transient, and oscillatory modulation of thrombin toward temporal control over fibrinogenesis. One system describes the assembly of a reaction module leading to the photochemically triggered formation of an active transcription machinery that, in the presence of RNase H, guides the transient activation of thrombin toward fibrinogenesis. A second system introduces photochemical triggering of a reaction circuit consisting of two coupled transcription machineries, leading to the temporally oscillatory formation and depletion of an intermediate reaction product. The concept is applied to develop a photochemically triggered transcription circuit that, in the presence of RNase H, leads to the oscillatory generation of an intermediate anti-thrombin aptamer-modified product. The oscillating aptamer-modified product induces the rhythmic inhibition of thrombin, accompanied by the cyclic activation and deactivation of the fibrinogenesis process. The operation of the transient and oscillatory-modulated transcription machinery reaction circuits is accompanied by computational kinetic models, allowing to predict the dynamic behaviors of the system under different auxiliary conditions. The phototriggered transient transcription machinery and oscillatory circuit-guided fibrinogenesis is examined under physiological-like conditions and within a human plasma environment.

Clinical and epidemiological analyses have found an association between coronavirus disease 2019 (COVID-19) and knee osteoarthritis (KOA). Infection with COVID-19 may increase the risk of developing KOA.

This study aimed to investigate the potential causal relationship between COVID-19 and KOA using Mendelian randomization (MR) and to explore the underlying mechanisms through a systematic bioinformatics approach.

Our investigation focused on exploring the potential causal relationship between COVID-19, acute upper respiratory tract infection (URTI) and KOA utilizing a bidirectional MR approach. Additionally, we conducted differential gene expression analysis using public datasets related to these three conditions. Subsequent analyses, including transcriptional regulation analysis, immune cell infiltration analysis, single-cell analysis, and druggability evaluation, were performed to explore potential mechanisms and prioritize therapeutic targets.

The results indicate that COVID-19 has a one-way impact on KOA, while URTI does not play a causal role in this association. Ribosomal dysfunction may serve as an intermediate factor connecting COVID-19 with KOA. Specifically, COVID-19 has the potential to influence the metabolic processes of the extracellular matrix, potentially impacting the joint homeostasis. A specific group of genes (COL10A1, BGN, COL3A1, COMP, ACAN, THBS2, COL5A1, COL16A1, COL5A2) has been identified as a shared transcriptomic signature in response to KOA with COVID-19. Imatinib, Adiponectin, Myricetin, Tranexamic acid, and Chenodeoxycholic acid are potential drugs for the treatment of KOA patients with COVID-19.

This study uniquely combines Mendelian randomization and bioinformatics tools to explore the possibility of a causal relationship and genetic association between COVID-19 and KOA. These findings are expected to provide novel perspectives on the underlying biological mechanisms that link COVID-19 and KOA.

Transcriptional reprogramming plays a key role in a variety of biological processes. Recent advances in RNA imaging techniques have allowed to visualize, in vivo, transcription-related mechanisms in different organisms. The MS2 system constitutes a robust method that has been used for over two decades to image multiple steps of a transcript's life cycle from "birth to death" with high spatiotemporal resolution in the animal field. It is based on the high affinity binding of the MS2 bacteriophage coat protein to its RNA hairpin ligands. Despite its broad applicability, a limited number of studies have implemented the system in plants, but without exploiting its full potential. Here, we describe the transposition of the MS2 technique to Arabidopsis. Combined with microfluidics, it allows to visualize the transcriptional repression of a phosphate starvation induced gene (SPX1) upon phosphate refeeding in vivo. The system provided access to the transcriptional response kinetics of individual cells, gene expression heterogeneity, and revealed bursting phenomena in plantae. The described methods provide new insights for multiple applications.

Transcription factors (TFs) fulfill a critical role in the formation and maintenance of different cell types during the developmental process as well as disease. It is believed that cancer-associated fibroblasts (CAFs) are activation status of tissue-resident fibroblasts or derived from form other cell types via transdifferentiation or dedifferentiation. Despite a subgroup of CAFs exhibit anti-cancer effects, most of them are reported to exert effects on tumor progression, further indicating their heterogeneous origin.

This review aimed to summarize and review the roles of TFs in the reciprocal crosstalk between CAFs and tumor cells, discuss the emerging mechanisms, and their roles in cell-fate decision, cellular reprogramming and advancing our understanding of the gene regulatory networks over the period of cancer initiation and progression.

This manuscript delves into the key contributory factors of TFs that are involved in activating CAFs and maintaining their unique states. Additionally, it explores how TFs play a pivotal and multifaceted role in the reciprocal crosstalk between CAFs and tumor cells. This includes their involvement in processes such as epithelial-mesenchymal transition (EMT), proliferation, invasion, and metastasis, as well as metabolic reprogramming. TFs also have a role in constructing an immunosuppressive microenvironment, inducing resistance to radiation and chemotherapy, facilitating angiogenesis, and even 'educating' CAFs to support the malignancies of tumor cells. Furthermore, this manuscript delves into the current status of TF-targeted therapy and considers the future directions of TFs in conjunction with anti-CAFs therapies to address the challenges in clinical cancer treatment.

Both tissue-resident macrophages and monocytes recruited from the bone marrow that transform into tissue-resident cells play critical roles in mediating homeostasis as well as in the pathology of inflammatory diseases. Inorganic arsenic (iAs) is the most common drinking water contaminant worldwide and represents a major public health concern. There are numerous diseases caused by iAs exposure in which macrophages are involved, including cardiovascular disease, cancer, and increased risk of (respiratory) infectious diseases. Notably, prenatal iAs exposure is also associated with negative birth outcomes and developmental immunotoxicity (DIT) contributing to long-term adverse outcomes of these immune-related diseases. Therefore, understanding the effects of iAs exposure on macrophages, particularly during immune development or tissue injury and inflammation, can help us better grasp the full range of arsenic immunotoxicity and better design therapeutic targets for iAs-induced diseases particularly in exposed populations. In contrast to prior published studies which often only focused on the effect of iAs on mature macrophages after development, in this study, we analyzed the transcriptome of M0-, M1- and M2-polarized male and female murine bone marrow-derived macrophages (BMDMs) which were exposed to iAs during the differentiation phase, as a model to study iAs (developmental) immunotoxicity. We identified differentially expressed genes by iAs in a sex- and stimulation-dependent manner and used bioinformatics tools to predict protein-protein interactions, transcriptional regulatory networks, and associated biological processes. Overall, our data suggest that M1-stimulated, especially female-derived, BMDMs are most susceptible to iAs exposure during differentiation. Most notably, we observed significant downregulation of major proinflammatory transcription factors, like IRF8, and its downstream targets, as well as genes encoding proteins involved in pattern recognition and antigen presentation, such as TLR7, TLR8, and H2-D1, potentially providing causal insight regarding the role of (early-life) arsenic exposure in perturbing immune responses to infectious diseases. We also observed significant downregulation of genes involved in processes crucial to coordinating a proinflammatory response including leukocyte migration, differentiation, and cytokine and chemokine production and response. Finally, we discovered that 24 X-linked genes were dysregulated in iAs-exposed female stimulation groups compared to only 3 across the iAs-exposed male stimulation groups. These findings elucidate the potential mechanisms underlying the sex-differential iAs-associated immune-related disease risk.

Intermittent fasting remains a safe and effective strategy to ameliorate various age-related diseases, but its specific mechanisms are not fully understood. Considering that transcription factors (TFs) determine the response to environmental signals, here, we profiled the diurnal expression of 600 samples across four metabolic tissues sampled every 4 over 24 h from mice placed on five different feeding regimens to provide an atlas of TFs in biological space, time, and feeding regimen. Results showed that 1218 TFs exhibited tissue-specific and temporal expression profiles in ad libitum mice, of which 974 displayed significant oscillations at least in one tissue. Intermittent fasting triggered more than 90% (1161 in 1234) of TFs to oscillate somewhere in the body and repartitioned their tissue-specific expression. A single round of fasting generally promoted TF expression, especially in skeletal muscle and adipose tissues, while intermittent fasting mainly suppressed TF expression. Intermittent fasting down-regulated aging pathway and upregulated the pathway responsible for the inhibition of mammalian target of rapamycin (mTOR). Intermittent fasting shifts the diurnal transcriptome atlas of TFs, and mTOR inhibition may orchestrate intermittent fasting-induced health improvements. This atlas offers a reference and resource to understand how TFs and intermittent fasting may contribute to diurnal rhythm oscillation and bring about specific health benefits.

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here, we present the culmination of the efforts of the modENCODE (model organism Encyclopedia of DNA Elements) and modERN (model organism Encyclopedia of Regulatory Networks) consortia to systematically assay TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). These data sets comprise 605 TFs identifying 3.6 M sites in the fly and 356 TFs identifying 0.9 M sites in the worm, and represent the majority of the regulatory space in each genome. We demonstrate that TFs associate with chromatin in clusters termed "metapeaks," that larger metapeaks have characteristics of high-occupancy target (HOT) regions, and that the importance of consensus sequence motifs bound by TFs depends on metapeak size and complexity. Combining ChIP-seq data with single-cell RNA-seq data in a machine-learning model identifies TFs with a prominent role in promoting target gene expression in specific cell types, even differentiating between parent-daughter cells during embryogenesis. These data are a rich resource for the community that should fuel and guide future investigations into TF function. To facilitate data accessibility and utility, all strains expressing green fluorescent protein (GFP)-tagged TFs are available at the stock centers for each organism. The chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center, GEO, and through a direct interface that provides rapid access to processed data sets and summary analyses, as well as widgets to probe the cell-type-specific TF-target relationships.

The kidneys contribute to the overall health of an organism by maintaining systemic homeostasis. This process involves various biological mechanisms, in which the Krüppel-like factors (KLFs), a family of transcription factors, are essential for regulating development, differentiation, proliferation, and cellular apoptosis. They also play a role in the metabolic regulation of essential nutrients, such as glucose and lipids. The dysregulation of these transcription factors is associated with the development of various pathologies, which can ultimately lead to renal fibrosis, severely compromising kidney function. In this context, the present article provides a comprehensive review of the existing literature, offering an enriching analysis of the findings related to the role of KLFs in nephrology, while also highlighting their potential therapeutic role in the treatment of renal diseases.

HSCs differentiation has been difficult to study experimentally due to the high number of components and interactions involved, as well as the impact of diverse physiological conditions. From a 200-node network, that was grounded on experimental data, we derived a 21-node regulatory network by collapsing linear pathways and retaining the functional feedback loops. This regulatory network core integrates key nodes and interactions underlying HSCs differentiation, including transcription factors, metabolic, and redox signaling pathways. We used Boolean, continuous, and stochastic dynamic models to simulate the hypoxic conditions of the HSCs niche, as well as the patterns and temporal sequences of HSCs transitions and differentiation. Our findings indicate that HSCs differentiation is a plastic process in which cell fates can transdifferentiate among themselves. Additionally, we found that cell heterogeneity is fundamental for HSCs differentiation. Lastly, we found that oxygen activates ROS production, inhibiting quiescence and promoting growth and differentiation pathways of HSCs.

The neuroendocrine-immune (NEI) network is fundamental for maintaining body's homeostasis and health. While the roles of microRNAs (miRNAs) and transcription factors (TFs) in disease processes are well-established, their synergistic regulation within the NEI network has yet to be elucidated. In this study, we constructed a background NEI-related miRNA-TF regulatory network (NEI-miRTF-N) by integrating NEI signaling molecules (including miRNAs, genes, and TFs) and identifying miRNA-TF feed-forward loops. Our analysis reveals that the number of immune signaling molecules is the highest and suggests potential directions for signal transduction, primarily from the nervous system to both the endocrine and immune systems, as well as from the endocrine system to the immune system. Furthermore, disease-specific NEI-miRTF-Ns for depression, Alzheimer's disease (AD) and dilated cardiomyopathy (DCM) were constructed based on the known disease molecules and significantly differentially expressed (SDE) molecules. Additionally, we proposed a novel method using depth-first-search algorithm for identifying significantly dysregulated NEI-related miRNA-TF regulatory pathways (NEI-miRTF-Ps) and verified their reliability from multiple perspectives. Our study provides an effective approach for identifying disease-specific NEI-miRTF-Ps and offers new insights into the synergistic regulation of miRNAs and TFs within the NEI network. Our findings provide information for new therapeutic strategies targeting these regulatory pathways.

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

Human induced pluripotent stem cell-derived neural stem/progenitor cells (hiPSC-NSCs) hold promise for treating neurodegenerative and demyelinating disorders. However, comprehensive studies on their identity and safety remain limited. In this study, we demonstrate that hiPSC-NSCs adopt a radial glia-associated signature, sharing key epigenetic and transcriptional characteristics with human fetal neural stem cells (hfNSCs) while exhibiting divergent profiles from glioblastoma stem cells. Long-term transplantation studies in mice showed robust and stable engraftment of hiPSC-NSCs, with predominant differentiation into glial cells and no evidence of tumor formation. Additionally, we identified the Sterol Regulatory Element Binding Transcription Factor 1 (SREBF1) as a regulator of astroglial differentiation in hiPSC-NSCs. These findings provide valuable transcriptional and epigenetic reference datasets to prospectively define the maturation stage of NSCs derived from different hiPSC sources and demonstrate the long-term safety of hiPSC-NSCs, reinforcing their potential as a viable alternative to hfNSCs for clinical applications.

To develop targeted treatments, it is crucial to identify the full spectrum of genetic drivers in melanoma, including those in non-coding regions. However, recent efforts to explore non-coding regions have primarily focused on gene-adjacent elements such as promoters and non-coding RNAs, leaving intergenic distal regulatory elements largely unexplored.

We used Hi-C chromatin contact data from melanoma cells to map distal, non-coding, promoter-interacting regulatory elements genome-wide in melanoma. Using this "promoter-interaction network", alongside whole-genome sequence and gene expression data from the Pan Cancer Analysis of Whole Genomes, we developed multivariate linear regression models to identify distal somatic mutation hotspots that affect promoter activity.

We identified eight recurrently mutated hotspots that are novel, melanoma-specific, located in promoter-interacting distal regulatory elements, alter transcription factor binding motifs, and affect the expression of genes (e.g., HSPB7, CLDN1, ADCY9 and FDXR) previously implicated as tumour suppressors/oncogenes in various cancers.

Our study suggests additional non-coding drivers beyond the well-characterised TERT promoter in melanoma, offering new insights into the disruption of complex regulatory networks by non-coding mutations that may contribute to melanoma development. Furthermore, our study provides a framework for integrating multiple levels of biological data to uncover cancer-specific non-coding drivers.

Pleiotropy, measured as expression breadth across tissues, is one of the best predictors for protein sequence and expression conservation. In this study, we investigated its effect on the evolution of cis-regulatory elements (CREs). To this end, we carefully reanalyzed the Epigenomics Roadmap data for nine fetal tissues, assigning a measure of pleiotropic degree to nearly half a million CREs. To assess the functional conservation of CREs, we generated ATAC-seq and RNA-seq data from humans and macaques. We found that more pleiotropic CREs exhibit greater conservation in accessibility, and the mRNA expression levels of the associated genes are more conserved. This trend of higher conservation for higher degrees of pleiotropy persists when analyzing the transcription factor binding repertoire. In contrast, simple DNA sequence conservation of orthologous sites between species tends to be even lower for pleiotropic CREs than for species-specific CREs. Combining various lines of evidence, we propose that the lack of sequence conservation in functionally conserved pleiotropic CREs is owing to within-element compensatory evolution. In summary, our findings suggest that pleiotropy is also a good predictor for the functional conservation of CREs, even though this is not reflected in the sequence conservation of pleiotropic CREs.

Maintenance methylation, of palindromic CpG dinucleotides at DNA replication forks, is crucial for the faithful mitotic inheritance of genomic 5-methylcytosine (5mC) methylation patterns. MBD proteins use two arginine residues to recognize symmetrically-positioned methyl groups in fully-methylated 5mCpG/5mCpG and 5mCpA/TpG dinucleotides. In contrast, C2H2 zinc finger (ZF) proteins recognize CpG and CpA, whether methylated or not, within longer specific sequences in a site- and strand-specific manner. Unmethylated CpG sites, often within CpG island (CGI) promoters, need protection by protein factors to maintain their hypomethylated status. Members of the BEN domain proteins bind CGCG or CACG elements within CGIs to regulate gene expression. Despite their overall structural diversity, MBD, ZF and BEN proteins all use arginine residues to recognize guanine, adopting either a 'straight-on' or 'oblique' conformation. The straight-on conformation accommodates a methyl group in the (5mC/T)pG dinucleotide, while the oblique conformation can clash with the methyl group of 5mC, leading to preferential binding of unmethylated sequences.

Some transcription factors, MYC for example, bind sites of potentially methylated DNA. This may increase binding specificity as such sites are (1) highly under-represented in the genome, and (2) offer additional, tissue specific information in the form of hypo- or hyper-methylation. Fortunately, bisulfite sequencing data can be used to investigate this phenomenon.

We developed MethylSeqLogo, an extension of sequence logos which includes new elements to indicate DNA methylation and under-represented dimers in each position of a set binding sites. Our method displays information from both DNA strands, and takes into account the sequence context (CpG or other) and genome region (promoter versus whole genome) appropriate to properly assess the expected background dimer frequency and level of methylation. MethylSeqLogo preserves sequence logo semantics-the relative height of nucleotides within a column represents their proportion in the binding sites, while the absolute height of each column represents information (relative entropy) and the height of all columns added together represents total information RESULTS: We present figures illustrating the utility of using MethylSeqLogo to summarize data from several CpG binding transcription factors. The logos show that unmethylated CpG binding sites are a feature of transcription factors such as MYC and ZBTB33, while some other CpG binding transcription factors, such as CEBPB, appear methylation neutral.

Our software enables users to explore bisulfite and ChIP sequencing data sets-and in the process obtain publication quality figures.

The development of immunotherapies has proved to be clinically encouraging to re-establish the immune function modified by the expression of immune inhibitory molecules in tumors. However, there are still patients with poor survival rates following treatment. The elucidation of molecular mechanisms triggered by the neo-expression of particular IC in tumors would constitute a major step toward better understanding tumor evolution and would help to design future clinical protocols. To this end, we investigate the modifications triggered by the neo-expression of the immune checkpoints HLA-G in ccRCC tumor cells. We demonstrate, for the first time, that HLA-G modifies key genes implicated mainly in tumor development, angiogenesis, calcium flow and mitochondria dynamics. The involvement of HLA-G on the expression of genes belonging to these pathways such as ADAM-12, NCAM1 and NRP1 was confirmed by the CRISPR/Cas9-mediated edition of HLA-G. The data reveal multifaceted roles of HLA-G in tumor cells which are far beyond the well-known function of HLA-G in the immune anti-tumor response. This warrants further investigation of HLA-G and these new partners in tumors of different origin so as to propose future new treatments to improve health patient's outcome.

Glyphosate-based herbicides (GBHs) or its active ingredient, glyphosate (Gly), induce implantation failure in rats. We aimed to elucidate a mechanism of action of these compounds assessing the transcriptional and epigenetic status of the receptivity marker, leukemia inhibitory factor (Lif) gene. F0 rats were orally exposed to GBH or Gly at 3.8 or 3.9 mg Gly/kg/day, respectively, from gestational day (GD) 9 until weaning. F1 females were mated and uterine samples collected at GD5. Methylation-sensitive restriction enzymes (MSRE) sites and transcription factors were in silico predicted in regulatory regions of Lif gene. DNA methylation status and histone modifications (histone 3 and 4 acetylation (H3Ac and H4Ac) and H3 lysine-27-trimethylation (H3K27me3)) were assessed. GBH and Gly decreased Lif mRNA levels and caused DNA hypermethylation. GBH increased H3Ac levels, whereas Gly reduced them; both compounds enhanced H3K27me3 levels. Finally, both GBH and Gly induced similar epigenetic alterations in the regulatory regions of Lif.

DNA i-motif structures are formed in the nuclei of human cells and are believed to provide critical genomic regulation. While the existence, abundance, and distribution of i-motif structures in human cells has been demonstrated and studied by immunofluorescent staining, and more recently NMR and CUT&Tag, the abundance and distribution of such structures in human genomic DNA have remained unclear. Here we utilise high-affinity i-motif immunoprecipitation followed by sequencing to map i-motifs in the purified genomic DNA of human MCF7, U2OS and HEK293T cells. Validated by biolayer interferometry and circular dichroism spectroscopy, our approach aimed to identify DNA sequences capable of i-motif formation on a genome-wide scale, revealing that such sequences are widely distributed throughout the human genome and are common in genes upregulated in G0/G1 cell cycle phases. Our findings provide experimental evidence for the widespread formation of i-motif structures in human genomic DNA and a foundational resource for future studies of their genomic, structural, and molecular roles.

As the most abundant class of transcription factors in eukaryotes, C2H2-type zinc finger proteins (C2H2-ZFPs) play critical roles in various biological processes. Despite being extensively studied in mammals, C2H2-ZFPs remain poorly characterized in birds. Recent accumulation of multi-omics data for chicken enables the genome-wide investigation of C2H2-ZFPs in birds. The purpose of this study is to reveal the genomic occurrence and evolutionary signature of chicken C2H2-ZFPs, and further depict their expression profiles across diverse chicken tissues. Here, we annotated 301 C2H2-ZFPs in chicken genome, which are associated with different effector domains, including KRAB, BTB, HOMEO, PHD, SCAN, and SET. Among them, most KRAB-ZFPs lack orthologues in mammals and tend to form clusters by duplication, supporting their fast evolution in chicken. We also annotated a unique and previously unidentified SCAN-ZFP, which is lineage-specific and highly expressed in ovary and testis. By integrating 101 RNA-seq datasets for 32 tissues, we found that most C2H2-ZFPs have tissue-specific expression. Particularly, 74 C2H2-ZFPs-including 27 KRAB-ZFPs-show blastoderm-enriched expression, indicating their association with early embryo development. Overall, this study performs comprehensive annotation and expression profiling of C2H2 ZFPs in diverse chicken tissues, which gives new insights into the evolution and potential function of C2H2-ZFPs in avian species.

Diabetes mellitus type 2 (T2DM) is formed by defective insulin secretion with the addition of peripheral tissue resistance of insulin action. It has been affecting over 400 million people all over the world.

To explore the pathogenesis of T2DM and to develop and implement new prevention and treatment strategies for T2DM.

Receiver operating characteristic (ROC) curve analysis was used to conduct diagnostic markers. The expression level of genes was determined by reverse transcription-PCR as well as Western blot. Cell proliferation assays were performed by cell counting kit-8 (CCK-8) tests. At last, T2DM mice underwent Roux-en-Y gastric bypass surgery.

We found that NPAS2 was significantly up-regulated in islet β cell apoptosis of T2DM. The ROC curve revealed that NPAS2 was capable of accurately diagnosing T2DM. NPAS2 overexpression did increase the level of KANK1. In addition, the CCK-8 test revealed knocking down NPAS2 and KANK1 increased the proliferation of MIN6 cells. At last, we found that gastric bypass may treat type 2 diabetes by down-regulating NPAS2 and KANK1.

This study demonstrated that NPAS2 induced β cell dysfunction by regulating KANK1 expression in type 2 diabetes, and it may be an underlying therapy target of T2DM.

Polyploidization drives regulatory and phenotypic innovation. How the merger of different genomes contributes to polyploid development is a fundamental issue in evolutionary developmental biology and breeding research. Clarifying this issue is challenging because of genome complexity and the difficulty in tracking stochastic subgenome divergence during development. Recent single-cell sequencing techniques enabled probing subgenome-divergent regulation in the context of cellular differentiation. However, analyzing single-cell data suffers from high error rates due to high dimensionality, noise, and sparsity, and the errors stack up in polyploid analysis due to the increased dimensionality of comparisons between subgenomes of each cell, hindering deeper mechanistic understandings. In this study, we develop a quantitative computational framework, called "pseudo-genome divergence quantification" (pgDQ), for quantifying and tracking subgenome divergence directly at the cellular level. Further comparing with cellular differentiation trajectories derived from single-cell RNA sequencing data allows for an examination of the relationship between subgenome divergence and the progression of development. pgDQ produces robust results and is insensitive to data dropout and noise, avoiding high error rates due to multiple comparisons of genes, cells, and subgenomes. A statistical diagnostic approach is proposed to identify genes that are central to subgenome divergence during development, which facilitates the integration of different data modalities, enabling the identification of factors and pathways that mediate subgenome-divergent activity during development. Case studies have demonstrated that applying pgDQ to single-cell and bulk tissue transcriptomic data promotes a systematic and deeper understanding of how dynamic subgenome divergence contributes to developmental trajectories in polyploid evolution.

Alternative splicing is a pivotal mechanism of post-transcriptional modification that contributes to the transcriptome plasticity and proteome diversity in metazoan cells. Although many splicing regulations around the exon/intron regions are known, the relationship between promoter-bound transcription factors and the downstream alternative splicing largely remains unexplored.

In this study, we present computational approaches to unravel the regulatory relationship between promoter-bound transcription factor binding sites (TFBSs) and the splicing patterns. We curated a fine dataset that includes DNase I hypersensitive site sequencing and transcriptomes across fifteen human tissues from ENCODE. Specifically, we proposed different representations of TF binding context and splicing patterns to examine the associations between the promoter and downstream splicing events. While machine learning models demonstrated potential in predicting splicing patterns based on TFBS occupancies, the limitations in the generalization of predicting the splicing forms of singleton genes across diverse tissues was observed with carefully examination using different cross-validation methods. We further investigated the association between alterations in individual TFBS at promoters and shifts in exon splicing efficiency. Our results demonstrate that the convolutional neural network (CNN) models, trained on TF binding changes in the promoters, can predict the changes in splicing patterns. Furthermore, a systemic in silico substitutions analysis on the CNN models highlighted several potential splicing regulators. Notably, using empirical validation using K562 CTCFL shRNA knock-down data, we showed the significant role of CTCFL in splicing regulation.

In conclusion, our finding highlights the potential role of promoter-bound TFBSs in influencing the regulation of downstream splicing patterns and provides insights for discovering alternative splicing regulations.