The Human Transcription Factors

Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed

Most genetic variants associated with complex traits and diseases occur in non-coding genomic regions and are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterize 14,324 ancestrally diverse RNA-sequencing samples from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and integrate whole genome sequencing data to perform cis and trans expression and splicing quantitative trait locus (cis-/trans-e/sQTL) analyses in six tissues and cell types, most notably whole blood (N=6,454) and lung (N=1,291). We show this dataset enables greater detection of secondary cis-e/sQTL signals than was achieved in previous studies, and that secondary cis-eQTL and primary trans-eQTL signal discovery is not saturated even though eGene discovery is. Most TOPMed trans-eQTL signals colocalize with cis-e/sQTL signals, suggesting many trans signals are mediated by cis signals. We fine-map European UK BioBank GWAS signals from 164 traits and colocalize the resulting 34,107 fine-mapped GWAS signals with TOPMed e/sQTL signals, finding that of 10,611 GWAS signals with a colocalization, 7,096 GWAS signals colocalize with at least one secondary e/sQTL signal. These results demonstrate that larger e/sQTL analyses will continue to uncover secondary e/sQTL signals, and that these new signals will benefit GWAS interpretation.

Cell type-specific epigenetic regulatory circuitry of coronary artery disease loci

Coronary artery disease (CAD) is the leading cause of death worldwide. Recently, hundreds of genomic loci have been shown to increase CAD risk, however, the molecular mechanisms underlying signals from CAD risk loci remain largely unclear. We sought to pinpoint the candidate causal coding and non-coding genes of CAD risk loci in a cell type-specific fashion. We integrated the latest statistics of CAD genetics from over one million individuals with epigenetic data from 45 relevant cell types to identify genes whose regulation is affected by CAD-associated single nucleotide variants (SNVs) via epigenetic mechanisms. Applying two statistical approaches, we identified 1,580 genes likely involved in CAD, about half of which have not been associated with the disease so far. Enrichment analysis and phenome-wide association studies linked the novel candidate genes to disease-specific pathways and CAD risk factors, corroborating their disease relevance. We showed that CAD-SNVs are enriched to regulate gene expression by affecting the binding of transcription factors (TFs) with cellular specificity. Of all the candidate genes, 23.5% represented non-coding RNAs (ncRNA), which likewise showed strong cell type specificity. We conducted a proof-of-concept biological validation for the novel CAD ncRNA gene IQCH-AS1 . CRISPR/Cas9-based gene knockout of IQCH-AS1 , in a human preadipocyte strain, resulted in reduced preadipocyte proliferation, less adipocyte lipid accumulation, and atherogenic cytokine profile. The cellular data are in line with the reduction of IQCH-AS1 in adipose tissues of CAD patients and the negative impact of risk alleles on its expression, suggesting IQCH-AS1 to be protective for CAD. Our study not only pinpoints CAD candidate genes in a cell type-specific fashion but also spotlights the roles of the understudied ncRNA genes in CAD genetics.

Exploring the dynamic responses of group 3 innate lymphoid cells at different times in response to LPS challenge

Group 3 innate lymphoid cells (ILC3s) have clear roles in regulating mucosal immunity and tissue homeostasis in the intestine, though the immunological functions in lungs remain unclear. This study aimed to demonstrate the dynamic responses of ILC3s to acute inflammation upon LPS challenge. Microarray data and single-cell RNA sequencing (scRNA-seq) data obtained from the GEO database were combined to analyze the function of ILC3 subset, confirmed by flow cytometry assay and qRT-PCR. The gene enrichment analysis of intersected genes identified between microarray data in bacterial pneumonia and single-cell RNA sequencing of intestinal ILC3s were closely related to TNF-alpha effects on cytokine activity, cell motility and apoptosis pathway, indicating the possibility of intestinal ILC3s migration to the lung. Furthermore, the cellular landscapes of ILC3s in lung and intestine at different times after pulmonary infection exhibited varied ILC3 statuses. ILC3s in lung expanded a lot at 48 h while intestinal ILC3s decreased at 72 h response to LPS challenge, with higher expression of marked genes related to TNF-alpha effects on cytokine activity, cell motility and apoptosis pathway. The main findings in our study may serve as valuable resources for understanding the roles that ILC3s play upon LPS challenge, which may offer opportunities for translating ILC3s as therapeutic targets to regulate LPS-induced pulmonary inflammation.

Mapping of the T-cell Landscape of Biliary Tract Cancer Unravels Anatomic Subtype-Specific Heterogeneity

Biliary tract cancer (BTC), encompassing diseases such as intrahepatic (ICC), extrahepatic cholangiocarcinoma (ECC), and gallbladder cancer, is not only increasing but also poses a significant and urgent health threat due to its high malignancy. Genomic differences point to the possibility that these subtypes represent distinct diseases. Elucidation of the specific distribution of T-cell subsets, critical to cancer immunity, across these diseases could provide better insights into the unique biology of BTC subtypes and help identify potential precision medicine strategies. To address this, we conducted single-cell RNA sequencing and T-cell receptor sequencing on CD3+ T cells from 36 samples from 16 patients with BTC across all subtypes and analyzed 355 pathologic slides to examine the spatial distribution of T cells and tertiary lymphoid structures. Compared with ICC and gallbladder cancer, ECC possessed a unique immune profile characterized by T-cell exhaustion, elevated CXCL13 expression in CD4+ T helper-like and CD8+CXCL13+ exhausted T cells, more mature tertiary lymphoid structures, and fewer desert immunophenotypes. Conversely, ICC displayed an inflamed immunophenotype with an enrichment of IFN-related pathways and high expression of LGALS1 in activated regulatory T cells, associated with immunosuppression. Inhibition of LGALS1 reduced tumor growth and regulatory T-cell prevalence in ICC mouse models. Overall, this study unveils T-cell diversity across BTC subtypes at the single-cell and spatial level that could open paths for tailored immunotherapies. Significance: Single-cell and spatial analyses detailed the T-cell characteristics specific to anatomic subtypes of biliary tract cancer, identifying unique immunologic features that could potentially be harnessed to improve patient outcomes.

The combinatorial binding syntax of transcription factors in forebrain-specific enhancers

Tissue-specific gene regulation in mammals involves the coordinated binding of multiple transcription factors (TFs). Using the forebrain as a model, we investigated the syntax of TF occupancy to determine tissue-specific enhancer regions. We analyzed forebrain-exclusive enhancers from the VISTA Enhancer Browser and a curated set of 23 TFs relevant to forebrain development and disease. Our findings revealed multiple distinct patterns of combinatorial TF binding, with the HES5-FOXP2-GATA3 triad being the most frequent in forebrain-specific enhancers. This syntactic structure was detected in 2614 enhancers from a genome-wide catalog of 25,000 predicted human forebrain enhancers. Notably, this catalog represents a computationally predicted dataset, distinct from the in vivo validated set of enhancers obtained from the VISTA Enhancer Browser. The shortlisted 2614 enhancers were further analyzed using genome-wide epigenetic data and evaluated for evolutionary conservation and disease relevance. Our findings highlight the value of these 2614 enhancers in forebrain-specific gene regulation and provide a framework for discovering tissue-specific enhancers, enhancing the understanding of enhancer function.

The spatial choreography of mRNA biosynthesis

Properly timed gene expression is essential for all aspects of organismal physiology. Despite significant progress, our understanding of the complex mechanisms governing the dynamics of gene regulation in response to internal and external signals remains incomplete. Over the past decade, advances in technologies like light and cryo-electron microscopy (Cryo-EM), cryo-electron tomography (Cryo-ET) and high-throughput sequencing have spurred new insights into traditional paradigms of gene expression. In this Review, we delve into recent concepts addressing 'where' and 'when' gene transcription and RNA splicing occur within cells, emphasizing the dynamic spatial and temporal organization of the cell nucleus.

Dynamic properties of transcriptional condensates modulate CRISPRa-mediated gene activation

CRISPR activation (CRISPRa) is a powerful tool for endogenous gene activation, yet the mechanisms underlying its optimal transcriptional activation remain unclear. By monitoring real-time transcriptional bursts, we find that CRISPRa modulates both burst duration and amplitude. Our quantitative imaging reveals that CRISPR-SunTag activators, with three tandem VP64-p65-Rta (VPR), form liquid-like transcriptional condensates and exhibit high activation potency. Although visible CRISPRa condensates are associated with some RNA bursts, the overall levels of phase separation do not correlate with transcriptional bursting or activation strength in individual cells. When the number of SunTag scaffolds is increased to 10 or more, solid-like condensates form, sequestering co-activators such as p300 and MED1. These condensates display low dynamicity and liquidity, resulting in ineffective gene activation. Overall, our studies characterize various phase-separated CRISPRa systems for gene activation, highlighting the foundational principles for engineering CRISPR-based programmable synthetic condensates with appropriate properties to effectively modulate gene expression.

Changes in the Expression Profile of Growth-Associated Protein 43 in Degenerative Lumbosacral Stenosis

Background: Degenerative spinal stenosis is a common condition associated with structural degeneration and pain, yet its molecular underpinnings remain incompletely understood. Growth-associated protein 43 (GAP-43), a key player in neuronal plasticity and regeneration, may serve as a biomarker for disease progression and pain severity. This study investigates the expression of GAP-43 at the mRNA and protein levels in the ligamentum flavum of affected patients. Methods: Samples were collected from 96 patients with degenerative spinal stenosis and 85 controls. GAP-43 mRNA expression was analyzed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR), while protein levels were quantified via enzyme-linked immunosorbent assay (ELISA) and Western blot. Pain severity was assessed using the visual analog scale (VAS), and associations with lifestyle factors were analyzed. Results:GAP-43 mRNA expression was significantly downregulated in the study group compared to the controls (fold change = 0.58 ± 0.12, p < 0.05), with an inverse correlation to VAS pain severity (fold change = 0.76 at VAS 4 vs. 0.36 at VAS 10). Conversely, GAP-43 protein levels were markedly elevated in the study group (5.57 ± 0.21 ng/mL) when compared to controls (0.54 ± 0.87 ng/mL, p < 0.0001). Protein levels were also correlated with lifestyle factors, including smoking and alcohol consumption (p < 0.05). Conclusions: GAP-43 shows potential as a biomarker for pain severity and disease progression in degenerative spinal stenosis, in a manner influenced by lifestyle factors. Further research is needed to explore its diagnostic and therapeutic applications.

Comparative transcriptomics reveals a mixed basal, club, and hillock epithelial cell identity in castration-resistant prostate cancer

Inhibiting the androgen receptor (AR) is effective for treatment of advanced prostate cancers because of their AR-dependent luminal epithelial cell identity. Tumors progress during therapy to castration-resistant prostate cancer (CRPC) by restoring AR signaling and maintaining luminal identity or by converting through lineage plasticity to a neuroendocrine (NE) identity or double-negative CRPC (DNPC) lacking luminal or NE identities. Here, we show that DNPC cells express genes defining basal, club, and hillock epithelial cells from benign prostate. We identified KLF5 as a regulator of genes defining this mixed basal, club, and hillock cell identity in DNPC models. KLF5-mediated upregulation of RARG uncovered a DNPC sensitivity to growth inhibition by retinoic acid receptor agonists, which down-regulated KLF5 and up-regulated AR. These findings offer CRPC classifications based on prostate epithelial cell identities and nominate KLF5 and RARG as therapeutic targets for CRPC displaying a mixed basal, club, and hillock identity.

Modeling and designing enhancers by introducing and harnessing transcription factor binding units

Enhancers serve as pivotal regulators of gene expression throughout various biological processes by interacting with transcription factors (TFs). While transcription factor binding sites (TFBSs) are widely acknowledged as key determinants of TF binding and enhancer activity, the significant role of their surrounding context sequences remains to be quantitatively characterized. Here we propose the concept of transcription factor binding unit (TFBU) to modularly model enhancers by quantifying the impact of context sequences surrounding TFBSs using deep learning models. Based on this concept, we develop DeepTFBU, a comprehensive toolkit for enhancer design. We demonstrate that designing TFBS context sequences can significantly modulate enhancer activities and produce cell type-specific responses. DeepTFBU is also highly efficient in the de novo design of enhancers containing multiple TFBSs. Furthermore, DeepTFBU enables flexible decoupling and optimization of generalized enhancers. We prove that TFBU is a crucial concept, and DeepTFBU is highly effective for rational enhancer design.

Regulatory Network Inference of Induced Senescent Midbrain Cell Types Reveals Cell Type-Specific Senescence-Associated Transcriptional Regulators

Cellular senescence of brain cell types has become an increasingly important perspective for both aging and neurodegeneration, specifically in the context of Parkinson's Disease (PD). The characterization of classical hallmarks of senescence is a widely debated topic, whereby the context in which a senescence phenotype is being investigated, such as the cell type, the inducing stressor, and/or the model system, is an extremely important aspect to consider when defining a senescent cell. Here, we describe a cell type-specific profile of senescence through the investigation of various canonical senescence markers in five human midbrain cell lines using chronic 5-Bromodeoxyuridine (BrdU) treatment as a model of DNA damage-induced senescence. We used principal component analysis (PCA) and subsequent regulatory network inference to define both unique and common senescence profiles in the cell types investigated, as well as revealed senescence-associated transcriptional regulators (SATRs). Functional characterization of one of the identified regulators, transcription factor AP4 (TFAP4), further highlights the cell type-specificity of the expression of the various senescence hallmarks. Our data indicates that SATRs modulate cell type-specific profiles of induced senescence in key midbrain cell types that play an important role in the context of aging and PD.

Identifying Reproducible Transcription Regulator Coexpression Patterns with Single Cell Transcriptomics

The proliferation of single cell transcriptomics has potentiated our ability to unveil patterns that reflect dynamic cellular processes such as the regulation of gene transcription. In this study, we leverage a broad collection of single cell RNA-seq data to identify the gene partners whose expression is most coordinated with each human and mouse transcription regulator (TR). We assembled 120 human and 103 mouse scRNA-seq datasets from the literature (>28 million cells), constructing a single cell coexpression network for each. We aimed to understand the consistency of TR coexpression profiles across a broad sampling of biological contexts, rather than examine the preservation of context-specific signals. Our workflow therefore explicitly prioritizes the patterns that are most reproducible across cell types. Towards this goal, we characterize the similarity of each TR's coexpression within and across species. We create single cell coexpression rankings for each TR, demonstrating that this aggregated information recovers literature curated targets on par with ChIP-seq data. We then combine the coexpression and ChIP-seq information to identify candidate regulatory interactions supported across methods and species. Finally, we highlight interactions for the important neural TR ASCL1 to demonstrate how our compiled information can be adopted for community use.

Meta-analysis reveals transcription factors and DNA binding domain variants associated with congenital heart defect and orofacial cleft

Many structural birth defect patients lack genetic diagnoses because there are many disease genes as yet to be discovered. We applied a gene burden test incorporating de novo predicted-loss-of-function (pLoF) and likely damaging missense variants together with inherited pLoF variants to a collection of congenital heart defect (CHD) and orofacial cleft (OC) parent-offspring trio cohorts (n = 3,835 and 1,844, respectively). We identified 17 novel candidate CHD genes and 10 novel candidate OC genes, of which many were known developmental disorder genes. Shorter genes were more powered in a "de novo only" analysis as compared to analysis including inherited pLoF variants. TFs were enriched among the significant genes; 14 and 8 transcription factor (TF) genes showed significant variant burden for CHD and OC, respectively. In total, 30 affected children had a de novo missense variant in a DNA binding domain of a known CHD, OC, and other developmental disorder TF genes. Our results suggest candidate pathogenic variants in CHD and OC and their potentially pleiotropic effects in other developmental disorders.

Innateness transcriptome gradients characterize mouse T lymphocyte populations

A fundamental dichotomy in lymphocytes separates adaptive T and B lymphocytes, with clonally expressed antigen receptors, from innate lymphocytes, which carry out more rapid responses. Some T cell populations, however, are intermediates between these 2 poles, with the capacity to respond rapidly through T cell receptor activation or by cytokine stimulation. Here, using publicly available datasets, we constructed linear mixed models that not only define a gradient of innate gene expression in common for mouse innate-like T cells, but also are applicable to other mouse T lymphoid populations. A similar gradient could be identified for chromatin landscape based on ATAC-seq (assay for transposase-accessible chromatin using sequencing) data. The gradient included increased transcripts related to many traits of innate immune responses, with increased scores related to evidence for antigen experience. While including genes typical for T helper 1 (Th1) responses, the innateness gene program could be separated from Th1, Th2, and Th17 responses. Lymphocyte populations with higher innateness scores correlated with lower calcium-dependent T cell receptor-mediated cell activation, with some downstream signaling proteins dependent on calcium or affecting metabolism prephosphorylation. Therefore, as a group, different mouse innate-like T cell populations had related gene expression programs and activation pathways that are different from naive CD4 and CD8 T cells.

The proximity-based protein interactome and regulatory logics of the transcription factor p65 NF-κB/RELA

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.

Annotation of transcription factors, chromatin-associated factors, and basal transcription machinery in the pea aphid, Acyrthosiphon pisum, and development of the ATFdb database, a resource for studies of transcriptional regulation

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.

BCDB: A dual-branch network based on transformer for predicting transcription factor binding sites

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.

A Regulatory Circuits Analysis Tool, "miRCuit," Helps Reveal Breast Cancer Pathways: Toward Systems Medicine in Oncology

A systems medicine understanding of the regulatory molecular circuits that underpin breast cancer is essential for early cancer detection and precision/personalized medicine in clinical oncology. Transcription factors (TFs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) control gene expression and cell biology, and by extension, serve as pillars of the regulatory circuits that determine human health and disease. We report here the development of a regulatory circuit analysis program, miRCuit, constructing 10 different types of regulatory elements involving messenger RNA, miRNA, lncRNA, and TFs. Using the miRCuit, we analyzed expression profiling data from 179 invasive ductal breast carcinoma and 51 normal tissue samples from the Gene Expression Omnibus database. We identified eight circuit types along with two special types of circuits, one of which highlighted the significant roles of lncRNA CASC15, miR-130b-3p, and TF KLF5 in breast cancer development and progression. These findings advance our understanding of the regulatory molecules associated with breast cancer. Moreover, miRCuit offers a new avenue for users to construct circuits from regulatory molecules for potential applications to decipher disease pathogenesis.

The E2F family: a ray of dawn in cardiomyopathy

Cardiomyopathies are a group of heterogeneous diseases, characterized by abnormal structure and function of the myocardium. For many years, it has been a hot topic because of its high morbidity and mortality as well as its complicated pathogenesis. The E2Fs, a group of transcription factors found extensively in eukaryotes, play a crucial role in governing cell proliferation, differentiation, and apoptosis, meanwhile their deregulated activity can also cause a variety of diseases. Based on accumulating evidence, E2Fs play important roles in cardiomyopathies. In this review, we describe the structural and functional characteristics of the E2F family and its role in cardiomyocyte processes, with a focus on how E2Fs are associated with the onset and development of cardiomyopathies. Moreover, we discuss the great potential of E2Fs as biomarkers and therapeutic targets, aiming to provide a reference for future research.

Transcription factors in the development and treatment of immune disorders

Immune function is highly controlled at the transcriptional level by the binding of transcription factors (TFs) to promoter and enhancer elements. Several TF families play major roles in immune gene expression, including NF-κB, STAT, IRF, AP-1, NRs, and NFAT, which trigger anti-pathogen responses, promote cell differentiation, and maintain immune system homeostasis. Aberrant expression, activation, or sequence of isoforms and variants of these TFs can result in autoimmune and inflammatory diseases as well as hematological and solid tumor cancers. For this reason, TFs have become attractive drug targets, even though most were previously deemed "undruggable" due to their lack of small molecule binding pockets and the presence of intrinsically disordered regions. However, several aspects of TF structure and function can be targeted for therapeutic intervention, such as ligand-binding domains, protein-protein interactions between TFs and with cofactors, TF-DNA binding, TF stability, upstream signaling pathways, and TF expression. In this review, we provide an overview of each of the important TF families, how they function in immunity, and some related diseases they are involved in. Additionally, we discuss the ways of targeting TFs with drugs along with recent research developments in these areas and their clinical applications, followed by the advantages and disadvantages of targeting TFs for the treatment of immune disorders.

Modeling Drug Responses and Evolutionary Dynamics Using Patient-Derived Xenografts Reveals Precision Medicine Strategies for Triple-Negative Breast Cancer

The intertumor and intratumor heterogeneity of triple-negative breast cancers, which is reflected in diverse drug responses, interplays with tumor evolution. In this study, we developed a preclinical experimental and analytical framework using patient-derived tumor xenografts (PDTX) from patients with treatment-naïve triple-negative breast cancers to test their predictive value in personalized cancer treatment approaches. Patients and their matched PDTXs exhibited concordant drug responses to neoadjuvant therapy using two trial designs and dosing schedules. This platform enabled analysis of nongenetic mechanisms involved in relapse dynamics. Treatment resulted in permanent phenotypic changes, with functional and therapeutic consequences. High-throughput drug screening methods in ex vivo PDTX cells revealed patient-specific drug response changes dependent on first-line therapy. This was validated in vivo, as exemplified by a change in olaparib sensitivity in tumors previously treated with clinically relevant cycles of standard-of-care chemotherapy. In summary, PDTXs provide a robust tool to test patient drug responses and therapeutic regimens and to model evolutionary trajectories. However, high intermodel variability and permanent nongenomic transcriptional changes constrain their use for personalized cancer therapy. This work highlights important considerations associated with preclinical drug response modeling and potential uses of the platform to identify efficacious and preferential sequential therapeutic regimens. Significance: Patient-derived tumor xenografts from treatment-naïve breast cancer samples can predict patient drug responses and model treatment-induced phenotypic and functional evolution, making them valuable preclinical tools.

Versatile roles of disordered transcription factor effector domains in transcriptional regulation

Transcription, a crucial step in the regulation of gene expression, is tightly controlled and involves several essential processes, such as chromatin organization, recognition of the specific genomic sequences, DNA binding, and ultimately recruiting the transcriptional machinery to facilitate transcript synthesis. At the center of this regulation are transcription factors (TFs), which comprise at least one DNA-binding domain (DBD) and an effector domain (ED). Although the structure and function of DBDs have been well studied, our knowledge of the structure and function of effector domains is limited. EDs are of particular importance in generating distinct transcriptional responses between protein members of the same TF family that have similar DBDs and specificities. The study of transcriptional activity conferred by effector domains has traditionally been conducted through examining protein-protein interactions. However, recent research has uncovered alternative mechanisms by which EDs regulate gene expression, such as the formation of condensates that increase the local concentration of transcription factors, cofactors, and coregulated genes, as well as DNA binding. Here, we provide a comprehensive overview of the known roles of transcription factor EDs, with a specific focus on disordered regions. Additionally, we emphasize the significance of intrinsically disordered regions (IDRs) during transcriptional regulation. We examine the mechanisms underlying the establishment and maintenance of transcriptional specificity through the structural properties of predominantly disordered EDs. We then provide a comprehensive overview of the current understanding of these domains, including their physical and chemical characteristics, as well as their functional roles.

Integrated transcriptomic analysis of human induced pluripotent stem cell-derived osteogenic differentiation reveals a regulatory role of KLF16

Osteogenic differentiation is essential for bone development, metabolism, and repair; however, the underlying regulatory relationships among genes remain poorly understood. To elucidate the transcriptomic changes and identify novel regulatory genes involved in osteogenic differentiation, we differentiated mesenchymal stem cells (MSCs) derived from 20 human iPSC lines into preosteoblasts (preOBs) and osteoblasts (OBs). We then performed transcriptome profiling of MSCs, preOBs and OBs. The iPSC-derived MSCs and OBs showed similar transcriptome profiles to those of primary human MSCs and OBs, respectively. Differential gene expression analysis revealed global changes in the transcriptomes from MSCs to preOBs, and then to OBs, including the differential expression of 840 genes encoding transcription factors (TFs). TF regulatory network analysis uncovered a network comprising 451 TFs, organized into five interactive modules. Multiscale embedded gene co-expression network analysis (MEGENA) identified gene co-expression modules and key network regulators (KNRs). From these analyses, KLF16 emerged as an important TF in osteogenic differentiation. We demonstrate that overexpression of Klf16 in vitro inhibited osteogenic differentiation and mineralization, while Klf16 +/- mice exhibited increased bone mineral density, trabecular number, and cortical bone area. Our study underscores the complexity of osteogenic differentiation and identifies novel regulatory genes such as KLF16, which plays an inhibitory role in osteogenic differentiation both in vitro and in vivo.

mRNA-LM: full-length integrated SLM for mRNA analysis

The success of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) messenger RNA (mRNA) vaccine has led to increased interest in the design and use of mRNA for vaccines and therapeutics. Still, selecting the most appropriate mRNA sequence for a protein remains a challenge. Several recent studies have shown that the specific mRNA sequence can have a significant impact on the translation efficiency, half-life, degradation rates, and other issues that play a major role in determining vaccine efficiency. To enable the selection of the most appropriate sequence, we developed mRNA-LM, an integrated small language model for modeling the entire mRNA sequence. mRNA-LM uses the contrastive language-image pretraining integration technology to combine three separate language models for the different mRNA segments. We trained mRNA-LM on millions of diverse mRNA sequences from several different species. The unsupervised model was able to learn meaningful biology related to evolution and host-pathogen interactions. Fine-tuning of mRNA-LM allowed us to use it in several mRNA property prediction tasks. As we show, using the full-length integrated model led to accurate predictions, improving on prior methods proposed for this task.

Genomic clustering tendency of transcription factors reflects phase-separated transcriptional condensates at super-enhancers

Many transcription factors (TFs) have been shown to bind to super-enhancers, forming transcriptional condensates to activate transcription in various cellular systems. However, the genomic and epigenomic determinants of phase-separated transcriptional condensate formation remain poorly understood. Questions regarding which TFs tend to associate with transcriptional condensates and what factors influence their association are largely unanswered. Here we systematically analyzed 571 DNA sequence motifs across the human genome and 6650 TF binding profiles across different cell types to identify the molecular features contributing to the formation of transcriptional condensates. We found that the genomic distributions of sequence motifs for different TFs exhibit distinct clustering tendencies. Notably, TF motifs with a high genomic clustering tendency are significantly associated with super-enhancers. TF binding profiles showing a high genomic clustering tendency are further enriched at cell-type-specific super-enhancers. TFs with a high binding clustering tendency also possess high liquid-liquid phase separation abilities. Compared to nonclustered TF binding, densely clustered TF binding sites are more enriched at cell-type-specific super-enhancers with higher chromatin accessibility, elevated chromatin interaction and stronger association with cancer outcomes. Our results indicate that the clustered genomic binding patterns and the phase separation properties of TFs collectively contribute to the formation of transcriptional condensates.

Sine oculis homeobox homolog family function in gastrointestinal cancer: Progression and comprehensive analysis

The sine oculis homeobox homolog (SIX) family, a group of transcription factors characterized by a conserved DNA-binding homology domain, plays a critical role in orchestrating embryonic development and organogenesis across various organisms, including humans. Comprising six distinct members, from SIX1 to SIX6, each member contributes uniquely to the development and differentiation of diverse tissues and organs, underscoring the versatility of the SIX family. Dysregulation or mutations in SIX genes have been implicated in a spectrum of developmental disorders, as well as in tumor initiation and progression, highlighting their pivotal role in maintaining normal developmental trajectories and cellular functions. Efforts to target the transcriptional complex of the SIX gene family have emerged as a promising strategy to inhibit tumor development. While the development of inhibitors targeting this gene family is still in its early stages, the significant potential of such interventions holds promise for future therapeutic advances. Therefore, this review aimed to comprehensively explore the advancements in understanding the SIX family within gastrointestinal cancers, focusing on its critical role in normal organ development and its implications in gastrointestinal cancers, including gastric, pancreatic, colorectal cancer, and hepatocellular carcinomas. In conclusion, this review deepened the understanding of the functional roles of the SIX family and explored the potential of utilizing this gene family for the diagnosis, prognosis, and treatment of gastrointestinal cancers.

Autism-Associated Genes and Neighboring lncRNAs Converge on Key Gene Regulatory Networks

The diversity of genes implicated in autism spectrum disorder (ASD) creates challenges for identifying core pathophysiological mechanisms. Aggregation of seven different classes of genetic variants implicated in ASD, in a database we call Consensus-ASD, reveals shared features across distinct types of ASD variants. Functional interrogation of 19 ASD genes and 9 neighboring long non-coding RNAs (lncRNAs) using CRISPR-Cas13 strikingly revealed differential gene expression profiles that were significantly enriched for other ASD genes. Furthermore, construction of a gene regulatory network (GRN) enabled the identification of central regulators that exhibit convergently altered activity upon ASD gene disruption. Thus, this study reveals how perturbing distinct ASD-associated genes can lead to shared, broad dysregulation of GRNs with critical relevance to ASD. This provides a crucial framework for understanding how diverse genes, including lncRNAs, can play convergent roles in key neurodevelopmental processes and ultimately contribute to ASD.

Unveiling cell-type-specific microRNA networks through alternative polyadenylation in glioblastoma

BACKGROUND

Glioblastoma multiforme (GBM) is characterized by its cellular complexity, with a microenvironment consisting of diverse cell types, including oligodendrocyte precursor cells (OPCs) and neoplastic CD133 + radial glia-like cells. This study focuses on exploring the distinct cellular transitions in GBM, emphasizing the role of alternative polyadenylation (APA) in modulating microRNA-binding and post-transcriptional regulation.

RESULTS

Our research identified unique APA profiles that signify the transitional phases between neoplastic cells and OPCs, underscoring the importance of APA in cellular identity and transformation in GBM. A significant finding was the disconnection between differential APA events and gene expression alterations, indicating that APA operates as an independent regulatory mechanism. We also highlighted the specific genes in neoplastic cells and OPCs that lose microRNA-binding sites due to APA, which are crucial for maintaining stem cell characteristics and DNA repair, respectively. The constructed networks of microRNA-transcription factor-target genes provide insights into the cellular mechanisms influencing cancer cell survival and therapeutic resistance.

CONCLUSIONS

This study elucidates the APA-driven regulatory framework within GBM, spotlighting its influence on cell state transitions and microRNA network dynamics. Our comprehensive analysis using single-cell RNA sequencing data to investigate the microRNA-binding sites altered by APA profiles offers a robust foundation for future research, presenting a novel approach to understanding and potentially targeting the complex molecular interplay in GBM.

Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.)

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.

Transcription factor specificity protein (SP) family in renal physiology and diseases

Dysregulated specificity proteins (SPs), members of the C2H2 zinc-finger family, are crucial transcription factors (TFs) with implications for renal physiology and diseases. This comprehensive review focuses on the role of SP family members, particularly SP1 and SP3, in renal physiology and pathology. A detailed analysis of their expression and cellular localization in the healthy human kidney is presented, highlighting their involvement in fatty acid metabolism, electrolyte regulation, and the synthesis of important molecules. The review also delves into the diverse roles of SPs in various renal diseases, including renal ischemia/reperfusion injury, diabetic nephropathy, renal interstitial fibrosis, and lupus nephritis, elucidating their molecular mechanisms and potential as therapeutic targets. The review further discusses pharmacological modulation of SPs and its implications for treatment. Our findings provide a comprehensive understanding of SPs in renal health and disease, offering new avenues for targeted therapeutic interventions and precision medicine in nephrology.

Translation efficiency covariation across cell types is a conserved organizing principle of mammalian transcriptomes

Characterization of shared patterns of RNA expression between genes across conditions has led to the discovery of regulatory networks and novel biological functions. However, it is unclear if such coordination extends to translation, a critical step in gene expression. Here, we uniformly analyzed 3,819 ribosome profiling datasets from 117 human and 94 mouse tissues and cell lines. We introduce the concept of Translation Efficiency Covariation (TEC), identifying coordinated translation patterns across cell types. We nominate potential mechanisms driving shared patterns of translation regulation. TEC is conserved across human and mouse cells and helps uncover gene functions. Moreover, our observations indicate that proteins that physically interact are highly enriched for positive covariation at both translational and transcriptional levels. Our findings establish translational covariation as a conserved organizing principle of mammalian transcriptomes.

Abundant repressor binding sites in human enhancers are associated with the fine-tuning of gene regulation

The regulation of gene expression relies on the coordinated action of transcription factors (TFs) at enhancers, including both activator and repressor TFs. We employed deep learning (DL) to dissect HepG2 enhancers into positive (PAR), negative (NAR), and neutral activity regions. Sharpr-MPRA and STARR-seq highlight the dichotomy impact of NARs and PARs on modulating and catalyzing the activity of enhancers, respectively. Approximately 22% of HepG2 enhancers, termed "repressive impact enhancers" (RIEs), are predominantly populated by NARs and transcriptional repression motifs. Genes flanking RIEs exhibit a stage-specific decline in expression during late development, suggesting RIEs' role in trimming enhancer activities. About 16.7% of human NARs emerge from neutral rhesus macaque DNA. This gain of repressor binding sites in RIEs is associated with a 30% decrease in the average expression of flanking genes in humans compared to rhesus macaque. Our work reveals modulated enhancer activity and adaptable gene regulation through the evolutionary dynamics of TF binding sites.

Altered Expression of Epigenetic and Transcriptional Regulators in ERβ Knockout Rat Ovaries During Postnatal Development

We analyzed the transcriptome data of wildtype and estrogen receptor β knockout (ErβKO) rat ovaries during the early postnatal period and detected remarkable changes in epigenetic regulators and transcription factors. Compared with postnatal day (PD) 4.5 ovaries, PD 6.5 wildtype ovaries possessed 581 differentially expressed downstream transcripts (DEDTs), including 17 differentially expressed epigenetic regulators (DEERs) and 23 differentially expressed transcription factors (DETFs). Subsequently, compared with PD 6.5 ovaries, PD 8.5 wildtype ovaries showed 920 DEDTs, including 24 DEERs and 68 DETFs. The DEDTs, DEERs, and DETFs in wildtype ovaries represented the gene expression during primordial follicle activation and the gradual development of primary follicles of first-wave origin because the second-wave follicles remained dormant during this developmental period. When we compared the transcriptome data of age-matched ErβKO ovaries, we observed that PD 6.5 ErβKO ovaries had 744 DEDTs compared with PD 4.5 ovaries, including 46 DEERs and 55 DETFs. The loss of ERβ rapidly activated the primordial follicles of both first- and second-wave origin on PD 6.5 and showed a remarkable increase in DEDTs (744 vs. 581). However, compared with PD 6.5 ovaries, PD 8.5 ErβKO ovaries showed only 191 DEDTs, including 8 DEERs and 10 DETFs. This finding suggests that the PD 8.5 ErβKO ovaries did not undergo remarkable ovarian follicle activation greater than that had already occurred in PD 6.5 ErβKO ovaries. The results also showed that the numbers of DEERs and DETFs were associated with increased changes in DEDTs; the greater the number of DEERs or DETFs, the larger the number of DEDTs. In addition to the quantitative differences in DEERs and DETFs between the wildtype and ErβKO ovaries, the differentially expressed regulators showed distinct patterns. We identified that 17 transcripts were tied to follicle assembly, 6 to follicle activation, and 12 to steroidogenesis. Our observations indicate that a loss of ERβ dysregulates the epigenetic regulators and transcription factors in ErβKO ovaries, which disrupts the downstream genes in ovarian follicles and increases follicle activation. Further studies are required to clarify if ERβ directly or indirectly regulates DEDTs, including DEERs and DETFs, during the neonatal development of rat ovarian follicles.

Characterizing tumor biology and immune microenvironment in high-grade serous ovarian cancer via single-cell RNA sequencing: insights for targeted and personalized immunotherapy strategies

Background

High-grade serous ovarian cancer (HGSOC), the predominant subtype of epithelial ovarian cancer, is frequently diagnosed at an advanced stage due to its nonspecific early symptoms. Despite standard treatments, including cytoreductive surgery and platinum-based chemotherapy, significant improvements in survival have been limited. Understanding the molecular mechanisms, immune landscape, and drug sensitivity of HGSOC is crucial for developing more effective and personalized therapies. This study integrates insights from cancer immunology, molecular profiling, and drug sensitivity analysis to identify novel therapeutic targets and improve treatment outcomes. Utilizing single-cell RNA sequencing (scRNA-seq), the study systematically examines tumor heterogeneity and immune microenvironment, focusing on biomarkers influencing drug response and immune activity, aiming to enhance patient outcomes and quality of life.

Methods

scRNA-seq data was obtained from the GEO database in this study. Differential gene expression was analyzed using gene ontology and gene set enrichment methods. InferCNV identified malignant epithelial cells, while Monocle, Cytotrace, and Slingshot software inferred subtype differentiation trajectories. The CellChat software package predicted cellular communication between malignant cell subtypes and other cells, while pySCENIC analysis was utilized to identify transcription factor regulatory networks within malignant cell subtypes. Finally, the analysis results were validated through functional experiments, and a prognostic model was developed to assess prognosis, immune infiltration, and drug sensitivity across various risk groups.

Results

This study investigated the cellular heterogeneity of HGSOC using scRNA-seq, focusing on tumor cell subtypes and their interactions within the tumor microenvironment. We confirmed the key role of the C2 IGF2+ tumor cell subtype in HGSOC, which was significantly associated with poor prognosis and high levels of chromosomal copy number variations. This subtype was located at the terminal differentiation of the tumor, displaying a higher degree of malignancy and close association with stage IIIC tissue types. The C2 subtype was also associated with various metabolic pathways, such as glycolysis and riboflavin metabolism, as well as programmed cell death processes. The study highlighted the complex interactions between the C2 subtype and fibroblasts through the MK signaling pathway, which may be closely related to tumor-associated fibroblasts and tumor progression. Elevated expression of PRRX1 was significantly connected to the C2 subtype and may impact disease progression by modulating gene transcription. A prognostic model based on the C2 subtype demonstrated its association with adverse prognosis outcomes, emphasizing the importance of immune infiltration and drug sensitivity analysis in clinical intervention strategies.

Conclusion

This study integrates molecular oncology, immunotherapy, and drug sensitivity analysis to reveal the mechanisms driving HGSOC progression and treatment resistance. The C2 IGF2+ tumor subtype, linked to poor prognosis, offers a promising target for future therapies. Emphasizing immune infiltration and drug sensitivity, the research highlights personalized strategies to improve survival and quality of life for HGSOC patients.

Targeting MXD1 sensitises pancreatic cancer to trametinib

BACKGROUND

The resistance of pancreatic ductal adenocarcinoma (PDAC) to trametinib therapy limits its clinical use. However, the molecular mechanisms underlying trametinib resistance in PDAC remain unclear.

OBJECTIVE

We aimed to illustrate the mechanisms of resistance to trametinib in PDAC and identify trametinib resistance-associated druggable targets, thus improving the treatment efficacy of trametinib-resistant PDAC.

DESIGN

We established patient-derived xenograft (PDX) models and primary cell lines to conduct functional experiments. We also applied single-cell RNA sequencing, Assay for Transposase-accessible Chromatin with sequencing and Cleavage Under Targets and Tagmentation sequencing to explore the relevant molecular mechanism.

RESULTS

We have identified a cancer cell subpopulation featured by hyperactivated viral mimicry response in trametinib-resistant PDXs. We have demonstrated that trametinib treatment of PDAC PDXs induces expression of transcription factor MAX dimerisation protein 1 (MXD1), which acts as a cofactor of histone methyltransferase mixed lineage leukaemia 1 to increased H3K4 trimethylation in transposable element (TE) loci, enhancing chromatin accessibility and thus the transcription of TEs. Mechanistically, enhanced transcription of TEs produces excessive double-stranded RNAs, leading to the activation of viral mimicry response and downstream oncogenic interferon-stimulated genes. Inhibiting MXD1 expression can recover the drug vulnerability of trametinib-resistant PDAC cells to trametinib.

CONCLUSIONS

Our study has discovered an important mechanism for trametinib resistance and identified MXD1 as a druggable target in treatment of trametinib-resistant PDAC.

Concurrent RB1 and P53 pathway disruption predisposes to the development of a primitive neuronal component in high-grade gliomas depending on MYC-driven EBF3 transcription

The foremost feature of glioblastoma (GBM), the most frequent malignant brain tumours in adults, is a remarkable degree of intra- and inter-tumour heterogeneity reflecting the coexistence within the tumour bulk of different cell populations displaying distinctive genetic and transcriptomic profiles. GBM with primitive neuronal component (PNC), recently identified by DNA methylation-based classification as a peculiar GBM subtype (GBM-PNC), is a poorly recognized and aggressive GBM variant characterised by nodules containing cells with primitive neuronal differentiation along with conventional GBM areas. In addition, the presence of a PNC component has been also reported in IDH-mutant high-grade gliomas (HGGs), and to a lesser extent to other HGGs, suggesting that regardless from being IDH-mutant or IDH-wildtype, peculiar genetic and/or epigenetic events may contribute to the phenotypic skewing with the emergence of the PNC phenotype. However, a clear hypothesis on the mechanisms responsible for this phenotypic skewing is still lacking. We assumed that the biphasic nature of these entities represents a unique model to investigate the relationships between genetic alterations and their phenotypic manifestations. In this study we show that in HGGs with PNC features both components are highly enriched in genetic alterations directly causing cell cycle deregulation (RB inactivation or CDK4 amplification) and p53 pathway inactivation (TP53 mutations or MDM2/4 amplification). However, the PNC component displays further upregulation of transcriptional pathways associated with proliferative activity, including overexpression of MYC target genes. Notably, the PNC phenotype relies on the expression of EBF3, an early neurogenic transcription factor, which is directly controlled by MYC transcription factors in accessible chromatin sites. Overall our findings indicate that the concomitant presence of genetic alterations, impinging on both cell cycle and p53 pathway control, strongly predisposes GBM to develop a concomitant poorly differentiated primitive phenotype depending on MYC-driven EBF3 transcription in a subset of glioma stem-like progenitor cells.

Cortical arealization of interneurons defines shared and distinct molecular programs in developing human and macaque brains

Cortical interneurons generated from ganglionic eminence via a long-distance journey of tangential migration display evident cellular and molecular differences across brain regions, which seeds the heterogeneous cortical circuitry in primates. However, whether such regional specifications in interneurons are intrinsically encoded or gained through interactions with the local milieu remains elusive. Here, we recruit 685,692 interneurons from cerebral cortex and subcortex including ganglionic eminence within the developing human and macaque species. Our integrative and comparative analyses reveal that less transcriptomic alteration is accompanied by interneuron migration within the ganglionic eminence subdivisions, in contrast to the dramatic changes observed in cortical tangential migration, which mostly characterize the transcriptomic specification for different destinations and for species divergence. Moreover, the in-depth survey of temporal regulation illustrates species differences in the developmental dynamics of cell types, e.g., the employment of CRH in primate interneurons during late-fetal stage distinguishes from their postnatal emergence in mice, and our entropy quantifications manifest the interneuron diversities gradually increase along the developmental ages in human and macaque cerebral cortices. Overall, our analyses depict the spatiotemporal features appended to cortical interneurons, providing a new proxy for understanding the relationship between cellular diversity and functional progression.

Cross-species analyses of thymic mimetic cells reveal evolutionarily ancient origins and both conserved and species-specific elements

Thymic mimetic cells are molecular hybrids between medullary-thymic-epithelial cells (mTECs) and diverse peripheral cell types. They are involved in eliminating autoreactive T cells and can perform supplementary functions reflective of their peripheral-cell counterparts. Current knowledge about mimetic cells derives largely from mouse models. To provide the high resolution that proved revelatory for mice, we performed single-cell RNA sequencing on purified mimetic-cell compartments from human pediatric donors. The single-cell profiles of individual donors were surprisingly similar, with diversification of neuroendocrine subtypes and expansion of the muscle subtype relative to mice. Informatic and imaging studies on the muscle-mTEC population highlighted a maturation trajectory suggestive of skeletal-muscle differentiation, some striated structures, and occasional cellular groupings reminiscent of neuromuscular junctions. We also profiled thymic mimetic cells from zebrafish. Integration of data from the three species identified species-specific adaptations but substantial interspecies conservation, highlighting the evolutionarily ancient nature of mimetic mTECs. Our findings provide a landscape view of human mimetic cells, with anticipated relevance in autoimmunity.

Systematic characterization of zinc in a series of breast cancer cell lines reveals significant changes in zinc homeostasis

An optimal amount of labile zinc (Zn 2+ ) is essential for proliferation of human cells, where Zn 2+ levels that are too high or too low cause cell cycle exit. Tumors of the breast have been characterized by high levels of total Zn 2+ . Given the role of Zn 2+ in proliferation of human cells and elevation of zinc in breast cancer tumors, we examined the concentration of total and labile Zn 2+ across a panel of 5 breast cancer cell lines, compared to the normal MCF10A cell line. We found that three cell lines (MDA-MB-231, MDA-MB-157, and SK-Br-3) showed elevated labile Zn 2+ in the cytosol, while T-47D showed significantly lower Zn 2+ , and MCF7 showed no change compared to MCF10A cells. There was no change in total Zn 2+ across the cell lines, as measured by ICP-MS, but we did observe a difference in the cells ability to accumulate Zn 2+ when Zn 2+ in the media was elevated. Therefore, we examined how proliferation of each cell line was affected by increases and decreases in the media. We found striking differences, where three cancer cell lines (MDA-MB-231, MDA-MB-157, and MCF7) showed robust proliferation in high Zn 2+ at concentrations that killed MCF10A, T-47D, and SK-Br-3 cells. We also discovered that 4 of the 5 cancer cell lines demonstrate compromised proliferation and increased cell death in low Zn 2+ , suggesting these cells may be addicted to Zn 2+ . Overall, our study suggests significant differences in Zn 2+ homeostasis and regulation in different types of breast cancer cells, with consequences for both proliferation and cell viability.

Single-Cell RNA Sequencing Reveals LEF1-Driven Wnt Pathway Activation as a Shared Oncogenic Program in Hepatoblastoma and Medulloblastoma

(1) Background: Hepatoblastoma and medulloblastoma are two types of pediatric tumors with embryonic origins. Both tumor types can exhibit genetic alterations that affect the β-catenin and Wnt pathways; (2) Materials and Methods: This study used bioinformatics and integrative analysis of multi-omics data at both the tumor and single-cell levels to investigate two distinct pediatric tumors: medulloblastoma and hepatoblastoma; (3) Results: The cross-transcriptome analysis revealed a commonly regulated expression signature between hepatoblastoma and medulloblastoma tumors. Among the commonly upregulated genes, the transcription factor LEF1 was significantly expressed in both tumor types. In medulloblastoma, LEF1 upregulation is associated with the WNT-subtype. The analysis of LEF1 genome binding occupancy in H1 embryonic stem cells identified 141 LEF1 proximal targets activated in WNT medulloblastoma, 13 of which are involved in Wnt pathway regulation: RNF43, LEF1, NKD1, AXIN2, DKK4, DKK1, LGR6, FGFR2, NXN, TCF7L1, STK3, YAP1, and NFATC4. The ROC curve analysis of the combined expression of these 13 WNT-related LEF1 targets yielded an area under the curve (AUC) of 1.00, indicating 100% specificity and sensitivity for predicting the WNT subtype in the PBTA medulloblastoma cohort. An expression score based on these 13 WNT-LEF1 targets accurately predicted the WNT subtype in two independent medulloblastoma transcriptome cohorts. At the single-cell level, the WNT-LEF1 expression score was exclusively positive in WNT-medulloblastoma tumor cells. This WNT-LEF1-dependent signature was also confirmed as activated in the hepatoblastoma tumor transcriptome. At the single-cell level, the WNT-LEF1 expression score was higher in tumor cells from both human hepatoblastoma samples and a hepatoblastoma patient-derived xenotransplant model; (4) Discussion: This study uncovered a shared transcriptional activation of a LEF1-dependent embryonic program, which orchestrates the regulation of the Wnt signaling pathway in tumor cells from both hepatoblastoma and medulloblastoma.

Transcriptome profiling of maize transcription factor mutants to probe gene regulatory network predictions

Transcription factors play important roles in regulation of gene expression and phenotype. A variety of approaches have been utilized to develop gene regulatory networks to predict the regulatory targets for each transcription factor, such as yeast-1-hybrid screens and gene co-expression network analysis. Here we identified potential transcription factor targets and used a reverse genetics approach to test the predictions of several gene regulatory networks in maize. Loss-of-function mutant alleles were isolated for 22 maize transcription factors. These mutants did not exhibit obvious morphological phenotypes. However, transcriptomic profiling identified differentially expressed genes in each of the mutant genotypes, and targeted metabolic profiling indicated variable phenolic accumulation in some mutants. An analysis of expression levels for predicted target genes based on yeast-1-hybrid screens identified a small subset of predicted targets that exhibit altered expression levels. The analysis of predicted targets from gene co-expression network-based methods found significant enrichments for prediction sets of some transcription factors, but most predicted targets did not exhibit altered expression. This could result from false-positive gene co-expression network predictions, a transcription factor with a secondary regulatory role resulting in minor effects on gene regulation, or redundant gene regulation by other transcription factors. Collectively, these findings suggest that loss-of-function for single uncharacterized transcription factors might have limited phenotypic impacts but can reveal subsets of gene regulatory network predicted targets with altered expression.

Chromatin enables precise and scalable gene regulation with factors of limited specificity

Biophysical constraints limit the specificity with which transcription factors (TFs) can target regulatory DNA. While individual nontarget binding events may be low affinity, the sheer number of such interactions could present a challenge for gene regulation by degrading its precision or possibly leading to an erroneous induction state. Chromatin can prevent nontarget binding by rendering DNA physically inaccessible to TFs, at the cost of energy-consuming remodeling orchestrated by pioneer factors (PFs). Under what conditions and by how much can chromatin reduce regulatory errors on a global scale? We use a theoretical approach to compare two scenarios for gene regulation: one that relies on TF binding to free DNA alone and one that uses a combination of TFs and chromatin-regulating PFs to achieve desired gene expression patterns. We find, first, that chromatin effectively silences groups of genes that should be simultaneously OFF, thereby allowing more accurate graded control of expression for the remaining ON genes. Second, chromatin buffers the deleterious consequences of nontarget binding as the number of OFF genes grows, permitting a substantial expansion in regulatory complexity. Third, chromatin-based regulation productively co-opts nontarget TF binding for ON genes in order to establish a "leaky" baseline expression level, which targeted activator or repressor binding subsequently up- or down-modulates. Thus, on a global scale, using chromatin simultaneously alleviates pressure for high specificity of regulatory interactions and enables an increase in genome size with minimal impact on global expression error.

Super-enhancers in hepatocellular carcinoma: regulatory mechanism and therapeutic targets

Super-enhancers (SEs) represent a distinct category of cis-regulatory elements notable for their robust transcriptional activation capabilities. In tumor cells, SEs intricately regulate the expression of oncogenes and pivotal cancer-associated signaling pathways, offering significant potential for cancer treatment. However, few studies have systematically discussed the crucial role of SEs in hepatocellular carcinoma (HCC), which is one of the most common liver cancers with late-stage diagnosis and limited treatment methods for advanced disease. Herein, we first summarize the identification methods and the intricate processes of formation and organization of super-enhancers. Subsequently, we delve into the roles and molecular mechanisms of SEs within the framework of HCC. Finally, we discuss the inhibitors targeting the key SE-components and their potential effects on the treatment of HCC. In conclusion, this review meticulously encapsulates the distinctive characteristics of SEs and underscores their pivotal roles in the context of hepatocellular carcinoma, presenting a novel perspective on the potential of super-enhancers as emerging therapeutic targets for HCC.

Identification of Endometriosis Pathophysiologic-Related Genes Based on Meta-Analysis and Bayesian Approach

Endometriosis is a complex disease with diverse etiologies, including hormonal, immunological, and environmental factors; however, its exact pathogenesis remains unknown. While surgical approaches are the diagnostic and therapeutic gold standard, identifying endometriosis-associated genes is a crucial first step. Five endometriosis-related gene expression studies were selected from the available datasets. Approximately, 14,167 genes common to these 5 datasets were analyzed for differential expression. Meta-analyses utilized fold-change values and standard errors obtained from each analysis, with the binomial and continuous datasets contributing to endometriosis presence and endometriosis severity meta-analysis, respectively. Approximately 160 genes showed significant results in both meta-analyses. For Bayesian analysis, endometriosis-related single nucleotide polymorphisms (SNPs), the human transcription factor catalog, uterine SNP-related gene expression, disease-gene databases, and interactome databases were utilized. Twenty-four genes, present in at least three or more databases, were identified. Network analysis based on Pearson's correlation coefficients revealed the HLA-DQB1 gene with both a high score in the Bayesian analysis and a central position in the network. Although ZNF24 had a lower score, it occupied a central position in the network, followed by other ZNF family members. Bayesian analysis identified genes with high confidence that could support discovering key diagnostic biomarkers and therapeutic targets for endometriosis.

Gene Doping Detection From the Perspective of 3D Genome

Since the early 20th century, the concept of doping was first introduced. To achieve better athletic performance, chemical substances were used. By the mid-20th century, it became gradually recognized that the illegal use of doping substances can seriously endangered athletes' health and compromised the fairness of sports competitions. Over the past 30 years, the World Anti-Doping Agency (WADA) has established corresponding rules and regulations to prohibit athletes from using doping substances or restrict the use of certain drugs, and isotope, chromatography, and mass spectrometry techniques were accredited to detect doping substances. With the development of gene editing technology, many genetic diseases have been effectively treated, but enabled by the same technology, doping has also the potential to pose a threat to sports in the form of gene doping. WADA has explicitly indicated gene doping in the Prohibited List as a prohibited method (M3) and approved qPCR detection. However, gene doping can easily evade detection, if the target genes' upstream regulatory elements are considered, the task became more challenging. Hi-C experiment driven 3D genome technology, through perspectives such as topologically associating domain (TAD) and chromatin loop, provides a more comprehensive and in-depth understanding of gene regulation and expression, thereby better preventing the potential use of 3D genome level gene doping. In this work, we will explore gene doping from a different perspective by analyzing recent studies on gene doping and explore related genes under 3D genome.

Asymmetry of Motif Conservation Within Their Homotypic Pairs Distinguishes DNA-Binding Domains of Target Transcription Factors in ChIP-Seq Data

Transcription factors (TFs) are the main regulators of eukaryotic gene expression. The cooperative binding of at least two TFs to genomic DNA is a major mechanism of transcription regulation. Massive analysis of the co-occurrence of overrepresented pairs of motifs for different target TFs studied in ChIP-seq experiments can clarify the mechanisms of TF cooperation. We categorized the target TFs from M. musculus ChIP-seq and A. thaliana ChIP-seq/DAP-seq experiments according to the structure of their DNA-binding domains (DBDs) into classes. We studied homotypic pairs of motifs, using the same recognition model for each motif. Asymmetric and symmetric pairs consist of motifs of remote and close recognition scores. We found that asymmetric pairs of motifs predominate for all TF classes. TFs from the murine/plant 'Basic helix-loop-helix (bHLH)', 'Basic leucine zipper (bZIP)', and 'Tryptophan cluster' classes and murine 'p53 domain' and 'Rel homology region' classes showed the highest enrichment of asymmetric homotypic pairs of motifs. Pioneer TFs, despite their DBD types, have a higher significance of asymmetry within homotypic pairs of motifs compared to other TFs. Asymmetry within homotypic CEs is a promising new feature decrypting the mechanisms of gene transcription regulation.

Single-cell mapping of regulatory DNA:Protein interactions

Gene expression is coordinated by a multitude of transcription factors (TFs), whose binding to the genome is directed through multiple interconnected epigenetic signals, including chromatin accessibility and histone modifications. These complex networks have been shown to be disrupted during aging, disease, and cancer. However, profiling these networks across diverse cell types and states has been limited due to the technical constraints of existing methods for mapping DNA:Protein interactions in single cells. As a result, a critical gap remains in understanding where TFs or other chromatin remodelers bind to DNA and how these interactions are perturbed in pathological contexts. To address this challenge, we developed a transformative single-cell immuno-tethering DNA:Protein mapping technology. By coupling a species-specific antibody-binding nanobody to a cytosine base editing enzyme, this approach enables profiling of even weak or transient factor binding to DNA, a task that was previously unachievable in single cells. Thus, our Docking & Deamination followed by sequencing (D&D-seq) technique induces cytosine-to-uracil edits in genomic regions bound by the target protein, offering a novel means to capture DNA:Protein interactions with unprecedented resolution. Importantly, this technique can be seamlessly incorporated into common single-cell multiomics workflows, enabling multimodal analysis of gene regulation in single cells. We tested the ability of D&D-seq to record TF binding both in bulk and at the single-cell level by profiling CTCF and GATA family members, obtaining high specificity and efficiency, with clear identification of TF footprint and signal retention in the targeted cell subpopulations. Furthermore, the deamination reaction showed minimal off-target activity, with high concordance to bulk ChIP-seq reference data. Applied to primary human peripheral blood mononuclear cells (PBMCs), D&D-seq successfully identified CTCF binding sites and enabled integration with advanced machine-learning algorithms for predicting 3D chromatin structure. Furthermore, we integrated D&D-seq with single-cell genotyping to assess the impact of IDH2 mutations on CTCF binding in a human clonal hematopoiesis sample, uncovering altered binding and chromatin co-accessibility patterns in mutant cells. Altogether, D&D-seq represents an important technological advance enabling the direct mapping of TF or chromatin remodeler binding to the DNA in primary human samples, opening new avenues for understanding chromatin and transcriptional regulation in health and disease.

Progressive plasticity during colorectal cancer metastasis

As cancers progress, they become increasingly aggressive-metastatic tumours are less responsive to first-line therapies than primary tumours, they acquire resistance to successive therapies and eventually cause death1,2. Mutations are largely conserved between primary and metastatic tumours from the same patients, suggesting that non-genetic phenotypic plasticity has a major role in cancer progression and therapy resistance3-5. However, we lack an understanding of metastatic cell states and the mechanisms by which they transition. Here, in a cohort of biospecimen trios from same-patient normal colon, primary and metastatic colorectal cancer, we show that, although primary tumours largely adopt LGR5+ intestinal stem-like states, metastases display progressive plasticity. Cancer cells lose intestinal cell identities and reprogram into a highly conserved fetal progenitor state before undergoing non-canonical differentiation into divergent squamous and neuroendocrine-like states, a process that is exacerbated in metastasis and by chemotherapy and is associated with poor patient survival. Using matched patient-derived organoids, we demonstrate that metastatic cells exhibit greater cell-autonomous multilineage differentiation potential in response to microenvironment cues compared with their intestinal lineage-restricted primary tumour counterparts. We identify PROX1 as a repressor of non-intestinal lineage in the fetal progenitor state, and show that downregulation of PROX1 licenses non-canonical reprogramming.

Moonlighting Proteins of Human and Some Other Eukaryotes. Evolutionary Aspects

This review presents materials on formation of the concept of moonlighting proteins and general characteristics of different similar proteins. It is noted that the concept under consideration is based on the data on the existence in different organisms of individual genes, protein products of which have not one, but at least two fundamentally different functions, for example, depending on cellular or extracellular location. An important feature of these proteins is that their functions can be switched. As a result, in different cellular compartments or outside the cells, as well as under a number of other circumstances, one of the possible functions can be carried out, and under other conditions, another. It is emphasized that the significant interest in moonlighting proteins is due to the fact that information is currently accumulating about their involvement in many vital molecular processes (glycolysis, translation, transcription, replication, etc.). Alternative hypotheses on the evolutionary origin of moonlighting proteins are discussed.