The Human Transcription Factors

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.

Single-Cell Transcriptomes of Immune Cells from Multiple Compartments Redefine the Ontology of Myeloid Subtypes Post-Stroke

The activation and infiltration of immune cells are hallmarks of ischemic stroke. However, the precise origins and the molecular alterations of these infiltrating cells post-stroke remain poorly characterized. Here, a murine model of stroke (permanent middle cerebral artery occlusion [p-MCAO]) is utilized to profile single-cell transcriptomes of immune cells in the brain and their potential origins, including the calvarial bone marrow (CBM), femur bone marrow (FBM), and peripheral blood mononuclear cells (PBMCs). This analysis reveals transcriptomically distinct populations of cerebral myeloid cells and brain-resident immune cells after stroke. These include a novel CD14+ neutrophil subpopulation that transcriptomically resembles CBM neutrophils. Moreover, the sequential activation of transcription factor regulatory networks in neutrophils during stroke progression is delineated, many of which are unique to the CD14+ population and underlie their acquisition of chemotaxis and granule release capacities. Two distinct origins of post-stroke disease-related immune cell subtypes are also identified: disease inflammatory macrophages, likely deriving from circulating monocytes in the skull, and transcriptionally immature disease-associated microglia, possibly arising from pre-existing homeostatic microglia. Together, a comprehensive molecular survey of post-stroke immune responses is performed, encompassing both local and distant bone marrow sites and peripheral blood.

Selective phase separation of transcription factors is driven by orthogonal molecular grammar

Protein production is critically dependent on gene transcription rates, which are regulated by RNA polymerase and a large collection of different transcription factors (TFs). How these transcription factors selectively address different genes is only partially known. Recent discoveries show that the differential condensation of separate TF families through phase separation may contribute to selectivity. Here we address this by conducting phase separation studies on six TFs from three different TF families with residue-scale coarse-grained molecular dynamics simulations. Our exploration of ternary TF phase diagrams reveals four dominant sticker motifs and two orthogonal driving forces that dictate the resultant condensate morphology, pointing to sequence-dependent orthogonal molecular grammar as a generic molecular mechanism that drives selective transcriptional condensation in gene expression.

Architecture of genome-wide transcriptional regulatory network reveals dynamic functions and evolutionary trajectories in Pseudomonas syringae

The model Gram-negative plant pathogen Pseudomonas syringae utilises hundreds of transcription factors (TFs) to regulate its functional processes, including virulence and metabolic pathways that control its ability to infect host plants. Although the molecular mechanisms of regulators have been studied for decades, a comprehensive understanding of genome-wide TFs in Psph 1448A remains limited. Here, we investigated the binding characteristics of 170 of 301 annotated TFs through chromatin immunoprecipitation sequencing (ChIP-seq). Fifty-four TFs, 62 TFs, and 147 TFs were identified in top-level, middle-level, and bottom-level, reflecting multiple higher-order network structures and direction of information flow. More than 40,000 TF pairs were classified into 13 three-node submodules which revealed the regulatory diversity of TFs in Psph 1448A regulatory network. We found that bottom-level TFs performed high co-associated scores to their target genes. Functional categories of TFs at three levels encompassed various regulatory pathways. Three and 25 master TFs were identified to involve in virulence and metabolic regulation, respectively. Evolutionary analysis and topological modularity network revealed functional variability and various conservation of TFs in P. syringae (Psph 1448A, Pst DC3000, Pss B728a, and Psa C48). Overall, our findings demonstrated a global transcriptional regulatory network of genome-wide TFs in Psph 1448A. This knowledge can advance the development of effective treatment and prevention strategies for related infectious diseases.

An updated compendium and reevaluation of the evidence for nuclear transcription factor occupancy over the mitochondrial genome

In most eukaryotes, mitochondrial organelles contain their own genome, usually circular, which is the remnant of the genome of the ancestral bacterial endosymbiont that gave rise to modern mitochondria. Mitochondrial genomes are dramatically reduced in their gene content due to the process of endosymbiotic gene transfer to the nucleus; as a result most mitochondrial proteins are encoded in the nucleus and imported into mitochondria. This includes the components of the dedicated mitochondrial transcription and replication systems and regulatory factors, which are entirely distinct from the information processing systems in the nucleus. However, since the 1990s several nuclear transcription factors have been reported to act in mitochondria, and previously we identified 8 human and 3 mouse transcription factors (TFs) with strong localized enrichment over the mitochondrial genome using ChIP-seq (Chromatin Immunoprecipitation) datasets from the second phase of the ENCODE (Encyclopedia of DNA Elements) Project Consortium. Here, we analyze the greatly expanded in the intervening decade ENCODE compendium of TF ChIP-seq datasets (a total of 6,153 ChIP experiments for 942 proteins, of which 763 are sequence-specific TFs) combined with interpretative deep learning models of TF occupancy to create a comprehensive compendium of nuclear TFs that show evidence of association with the mitochondrial genome. We find some evidence for chrM occupancy for 50 nuclear TFs and two other proteins, with bZIP TFs emerging as most likely to be playing a role in mitochondria. However, we also observe that in cases where the same TF has been assayed with multiple antibodies and ChIP protocols, evidence for its chrM occupancy is not always reproducible. In the light of these findings, we discuss the evidential criteria for establishing chrM occupancy and reevaluate the overall compendium of putative mitochondrial-acting nuclear TFs.

FLT3 inhibition upregulates OCT4/NANOG to promote maintenance and TKI resistance of FLT3-ITD+ acute myeloid leukemia

Up to 30% of acute myeloid leukemia (AML) patients face unfavorable outcomes due to the FMS-like receptor tyrosine kinase-3 (FLT3) internal tandem duplication (ITD) mutation. Although FLT3 inhibitors show encouraging outcomes in treatment, they fail to eliminate leukemia stem cells, the origin of persistent and resistant lesions. Exploration of the mechanism in FLT3-ITD+ AML maintenance and chemoresistance is crucial for the development of novel therapeutic approaches. The manifestation of pluripotency transcription factors (TFs) and their link to clinical outcomes have been documented in various tumors. This study investigates the correlation between core pluripotency TF and treatment in AML. We discovered that FLT3 inhibition induced upregulation of OCT4 and NANOG in FLT3-ITD+ AML cells. Subsequently, we demonstrated that downregulation of OCT4 or NANOG inhibited cell growth, promoted apoptosis, and induced G0/G1 cell cycle phase arrest in FLT3-ITD+ AML cells. Knockdown of OCT and NANOG inhibited tumor growth in a mouse tumor model. OCT4 promotes the malignant biological behavior of FLT3-ITD+ AML by enhancing the abnormal FLT3 signaling pathway through transcriptional activation of NANOG. Importantly, downregulation of OCT4 or NANOG increased responsiveness to FLT3-tyrosine kinase inhibitor (TKI) (Gilteritinib), implying that OCT4 and NANOG may contribute to TKI resistance in FLT3-ITD+ AML. Our study verifies the involvement of OCT4/NANOG in regulating TKI sensitivity and targeting them may improve the cytotoxicity of FLT3-TKIs in FLT3-ITD+ AML.

Transcription factor addictions: exploring the potential Achilles' Heel of endometriosis

A considerable number of women of reproductive age suffer from endometriosis worldwide. There is a significant physical, mental, and financial burden on patients affected by this condition in terms of pelvic pain, either continuously or intermittently, dysmenorrhea, infertility, and a higher risk of certain types of cancer. Several treatments available in clinical settings for endometriosis management do not provide adequate efficacy and have undesirable side effects. Transcription factors (TFs) are crucial regulators of key biological processes involved in endometriosis. Here, we elaborated on the research progress regarding the crucial roles of TFs in endometriosis, emphasizing their implications for clinical outcomes and critical therapeutic contributions. By delving into their involvement in key processes, such as cell proliferation and apoptosis, we revealed the multifaceted role of key TFs in disease progression. We aimed to provide a systemic understanding of TFs regulation in endometriosis pathogenesis, establishing a foundation for innovative treatment approaches.

Elucidating neuroepigenetic mechanisms to inform targeted therapeutics for brain disorders

The evolving field of neuroepigenetics provides important insights into the molecular foundations of brain function. Novel sequencing technologies have identified patient-specific mutations and gene expression profiles involved in shaping the epigenetic landscape during neurodevelopment and in disease. Traditional methods to investigate the consequences of chromatin-related mutations provide valuable phenotypic insights but often lack information on the biochemical mechanisms underlying these processes. Recent studies, however, are beginning to elucidate how structural and/or functional aspects of histone, DNA, and RNA post-translational modifications affect transcriptional landscapes and neurological phenotypes. Here, we review the identification of epigenetic regulators from genomic studies of brain disease, as well as mechanistic findings that reveal the intricacies of neuronal chromatin regulation. We then discuss how these mechanistic studies serve as a guideline for future neuroepigenetics investigations. We end by proposing a roadmap to future therapies that exploit these findings by coupling them to recent advances in targeted therapeutics.

TAF7 directly targets SAA1 to enhance triple-negative breast cancer metastasis via phosphorylating E-cadherin and N-cadherin

Identification of metastasis drivers of triple-negative breast cancer (TNBC) is a multifaceted challenge. Here, we identified TATA-box binding protein associated factor 7 (TAF7) as a candidate to modulate TNBC metastasis. TAF7 exhibited high expression in metastatic TNBC patients, and its elevated expression showed a negative correlation with overall survival in TNBC patients. The knockdown of TAF7 suppressed the migration and invasion of TNBC, suggesting TAF7 plays a role in the metastatic processes. Further, TAF7 was enhancing serum amyloid A1 (SAA1) transcription by binding to a specific motif in the SAA1 gene promoter. The elevated SAA1 in TNBC cells directly increased E-cadherin and N-cadherin phosphorylation thereby regulating cell adhesion. Mechanistically, TAF7 modulated cell invasion, migration, and lung metastasis through an SAA1-dependent manner in vitro and in vivo experiments. Taken together, it is likely that TAF7 could directly act on the SAA1 gene promoter, upregulating SAA1 and consequently promoting TNBC metastasis.

Decoy-PROTAC for specific degradation of "Undruggable" STAT3 transcription factor

Signal transducer and activator of transcription 3 (STAT3) is widely recognized as an attractive target for cancer therapy due to its significant role in the initiation and progression of tumorigenesis. However, existing STAT3 inhibitors have suffered from drawbacks including poor efficacy, limited specificity, and undesirable off-target effects, due to the challenging nature of identifying active sites or allosteric regulatory pockets on STAT3 amenable to small-molecule inhibition. In response to these obstacles, we utilize the innovative proteolysis targeting chimera (PROTAC) technology to create a highly specific decoy-targeted protein degradation system for STAT3 protein, termed D-PROTAC. This system fuses DNA decoy that targets STAT3 with an E3 ligase ligand, utilizing a click chemistry approach. Experimental results demonstrate that D-PROTAC efficiently mediates the degradation of the STAT3 protein across various cancer cell types, leading to the downregulation of crucial downstream STAT3 targets, inhibiting tumor cell growth, triggering cell cycle arrest and apoptosis, and suppressing tumor immune evasion. Furthermore, D-PROTAC is capable of achieving significant tumor suppression in xenograft models. Overall, our research validates that D-PROTAC can successfully target and eliminate the "undruggable" STAT3, showcasing specificity and potent antitumor effects. This strategy will suggest a promising avenue for the development of targeted therapies against the critical functions of STAT3 in human cancers and potentially other diseases.

E2F4 Promotes Malignant Behaviors of Prostate Cancer Through Activating MUC1 Expression Transcriptionally

BACKGROUND

The malignant features of prostate cancer (PC) threaten the patient's life. MUC1 was observably enhanced in PC. However, the reason for higher MUC1 expression in PC is still unclear and deserves to be further investigated.

METHODS

The abundance of MUC1 and E2F4 was evaluated using RT-qPCR in PC patients and PC cells. Pearson correlation coefficient analyzed the relationship between E2F4 and MUC1 in tissues from PC patients. Malignant phenotypes were examined using clone formation, scratch tests, transwell, and flow cytometry. The JASPAR website, luciferase activity assay, and ChIP were employed for validating interplays between E2F4 and the MUC1 promoter.

RESULTS

MUC1 and E2F4 were abnormally elevated in samples of PC patients and PC cells. MUC1 silencing resulted in suppression of growth and metastasis and promotion of cell apoptosis of PC cells. Additionally, E2F4 could provoke the transcriptional activity of MUC1 to enhance MUC1 expression. Furthermore, E2F4 knockdown inhibited malignant features of PC cells, which was abolished by MUC1 overexpression.

CONCLUSION

Our findings revealed that E2F4 silencing led to the suppression of growth and metastasis and the promotion of cell apoptosis of PC cells through reducing MUC1 expression, which offered targeting molecules for PC treatment.

Single-cell spatial transcriptomic atlas of the whole mouse brain

A comprehensive atlas of genes, cell types, and their spatial distribution across a whole mammalian brain is fundamental for understanding the function of the brain. Here, using single-nucleus RNA sequencing (snRNA-seq) and Stereo-seq techniques, we generated a mouse brain atlas with spatial information for 308 cell clusters at single-cell resolution, involving over 4 million cells, as well as for 29,655 genes. We have identified cell clusters exhibiting preference for cortical subregions and explored their associations with brain-related diseases. Additionally, we pinpointed 155 genes with distinct regional expression patterns within the brainstem and unveiled 513 long non-coding RNAs showing region-enriched expression in the adult brain. Parcellation of brain regions based on spatial transcriptomic information revealed fine structure for several brain areas. Furthermore, we have uncovered 411 transcription factor regulons showing distinct spatiotemporal dynamics during neurodevelopment. Thus, we have constructed a single-cell-resolution spatial transcriptomic atlas of the mouse brain with genome-wide coverage.

Cooperation of a polymerizing SAM domain and an intrinsically disordered region enables full SAMD1 function on chromatin

Transcription factors orchestrate gene expression through a myriad of complex mechanisms, encompassing collaborations with other transcription factors and the formation of multimeric complexes. The chromatin-binding protein SAMD1 [sterile alpha motif (SAM) domain-containing protein 1] binds to unmethylated CpG-rich DNA utilizing its N-terminal winged-helix (WH) domain. Additionally, its C-terminal SAM domain, which mediates interactions with itself and with L3MBTL3, is crucial for chromatin binding. The precise role of the SAM domain in this process remains unclear. Using structural analyses, we elucidated the distinct homopolymerization modes within the SAM domains of L3MBTL3 and SAMD1, alongside their heterodimerization architecture. Interestingly, SAMD1 necessitates not only the WH and SAM domain but also a proline/alanine-rich intrinsically disordered region (IDR) for efficient chromatin binding. The IDR is essential for the ability of SAMD1 to form large polymers, with its functionality determined by integrity rather than the specific sequence. Mutagenesis studies underscore the critical role of arginines within the IDR for polymerization, chromatin binding, and the biological function of SAMD1. These findings propose a model in which structured and unstructured regions of SAMD1 cooperate in a coordinated fashion to facilitate chromatin binding. This work provides new insights into the diverse mechanisms transcription factors employ to interact with chromatin and regulate gene expression.

Single-cell sequencing in non-obstructive azoospermia: insights from primary and re-analysis studies

Non-obstructive azoospermia (NOA) constitutes one of the most severe forms of male infertility. Recent advancements in single-cell sequencing have significantly contributed to understanding the molecular landscape of NOA in human testicular tissues, elucidating the factors that underpin spermatogenic dysfunction. This technology has improved our understanding of the condition at a cellular level. Concurrently, bioinformatics developments have facilitated the re-analysis of publicly available single-cell datasets, offering novel insights into the disorder. Nevertheless, a comprehensive review integrating primary and re-analysis studies of single-cell sequencing in NOA is lacking. This review systematically evaluates 10 primary studies reporting original single-cell sequencing data of human NOA testicular samples and 22 secondary studies that re-analyzed these published data. We explore single-cell sequencing applications in germ cells, Sertoli cells, and Leydig cells, offering a comprehensive overview of molecular insights into spermatogenic dysfunction. Our review highlights novel findings in secondary studies, including the roles of transcriptional regulators, RNA transcription, endocrine disruptors, and microtubular cytoskeleton, thereby bridging primary studies and re-analysis studies. Additionally, we discussed future research directions and the challenges of translating single-cell research findings into clinical applications. In summary, single-cell sequencing offers a high-resolution, single-cell perspective of NOA testicular tissue, paving the way for innovative therapeutic strategies in male infertility.

Deciphering the Transcription Factor Landscape in Prostate Cancer Progression: A Novel Approach to Understand NE Transdifferentiation

Prostate cancer (PCa) stands as a leading cause of cancer-related mortality among men, with treatment-induced neuroendocrine prostate cancer (NEPC) posing a challenge as an ARPI-resistant subtype. The role of transcription factors (TFs) in PCa progression and NEPC transdifferentiation remains inadequately understood, underscoring a critical gap in current research. In this study, an internal Z score-based approach is developed to identify lineage-specific TF profiles in prostatic adenocarcinoma and NEPC for a nuanced understanding of TF expression dynamics. Distinct TF profiles for adenocarcinoma and NEPC are unveiled, identifying 126 shared TFs, 46 adenocarcinoma-TFs, and 56 NEPC-TFs, validated across multiple cohorts. Gene Ontology is employed to validate their biological and functional roles in PCa progression. Implications are revealed in cell development, differentiation, and lineage determination. Knockdown experiments suggest that lineage-TFs are functionally important in maintaining lineage-specific cell proliferation. Additionally, a longitudinal study on NE transdifferentiation highlights dynamic TF expression shifts, proposing a three-phases hypothesis for PCa progression mechanisms. This study introduces a groundbreaking approach for deciphering the TF landscape in PCa, providing a molecular basis for adenocarcinoma to NEPC progression, and paving the way for innovative treatment strategies with potential impact on patient outcomes.

CelEst: a unified gene regulatory network for estimating transcription factor activities in C. elegans

Transcription factors (TFs) play a pivotal role in orchestrating critical intricate patterns of gene regulation. Although gene expression is complex, differential expression of hundreds of genes is often due to regulation by just a handful of TFs. Despite extensive efforts to elucidate TF-target regulatory relationships in Caenorhabditis elegans, existing experimental datasets cover distinct subsets of TFs and leave data integration challenging. Here, I introduce CelEst, a unified gene regulatory network designed to estimate the activity of 487 distinct C. elegans TFs-∼58% of the total-from gene expression data. To integrate data from ChIP-seq, DNA-binding motifs, and eY1H screens, optimal processing of each data type was benchmarked against a set of TF perturbation RNA-seq experiments. Moreover, I showcase how leveraging TF motif conservation in target promoters across genomes of related species can distinguish highly informative interactions, a strategy which can be applied to many model organisms. Integrated analyses of data from commonly studied conditions including heat shock, bacterial infection, and sex differences validates CelEst's performance and highlights overlooked TFs that likely play major roles in coordinating the transcriptional response to these conditions. CelEst can infer TF activity on a standard laptop computer within minutes. Furthermore, an R Shiny app with a step-by-step guide is provided for the community to perform rapid analysis with minimal coding required. I anticipate that widespread adoption of CelEsT will significantly enhance the interpretive power of transcriptomic experiments, both present and retrospective, thereby advancing our understanding of gene regulation in C. elegans and beyond.

Deciphering of SOX9 Functions in Pancreatic Cancer Cells

SOX9 is widely regarded as a key master regulator of gene transcription, responsible for the development and differentiation programs within tissue and organogenesis, particularly in the pancreas. SOX9 overexpression has been observed in multiple tumor types, including pancreatic cancer, and is discussed as a prognostic marker. In order to gain a more profound understanding of the role of SOX9 in pancreatic cancer, we have performed SOX9 knockdown in the COLO357 and PANC-1 cells using RNA interference, followed by full-transcriptome analysis of the siRNA-transfected cells. The molecular pathway enrichment analysis between SOX9-specific siRNA-transfected cells and control cells reveals the activation of processes associated with cellular signaling, cell differentiation, transcription, and methylation, alongside the suppression of genes involved in various stages of the cell cycle and apoptosis, upon the SOX9 knockdown. Alterations of the expression of transcription factors, epithelial-mesenchymal transition markers, oncogenes, tumor suppressor genes, and drug resistance-related genes upon SOX9 knockdown in comparison of primary and metastatic pancreatic cancer cells are discovered. The expression levels of genes comprising prognostic signatures for pancreatic cancer were also evaluated following SOX9 knockdown. Additional studies are needed to assess the properties and prognostic significance of SOX9 in pancreatic cancer using other biological models.

A convenient single-cell newly synthesized transcriptome assay reveals FLI1 downregulation during T-cell activation

Sequencing newly synthesized transcriptome alongside regular transcriptome in single cells enables the study of gene expression temporal dynamics during rapid chromatin and gene regulation processes. Existing assays for profiling single-cell newly synthesized transcriptome often require specialized technical expertise to achieve high cellular throughput, limiting their accessibility. Here, we developed NOTE-seq, a method for simultaneous profiling of regular and newly synthesized transcriptomes in single cells with high cellular throughput. NOTE-seq integrates 4-thiouridine labeling of newly synthesized RNA, thiol-alkylation-based chemical conversion, and a streamlined 10X Genomics workflow, making it accessible and convenient for biologists without extensive single-cell expertise. Using NOTE-seq, we investigated the temporal dynamics of gene expression during early-stage T-cell activation, identified transcription factors and regulons in Jurkat and naïve T cells, and uncovered the down-regulation of FLI1 as a master transcription factor upon T-cell stimulation. Notably, topoisomerase inhibition led to the depletion of both topoisomerases and FLI1 in T cells through a proteasome-dependent mechanism driven by topoisomerase cleavage complexes, highlighting potential complications topoisomerase-targeting cancer chemotherapies could pose to the immune system.

Multi-omics analysis to uncover the molecular basis of tumor budding in head and neck squamous cell carcinoma

Tumor budding (TB) is a prognostic biomarker in HPV-negative and HPV-positive head and neck squamous cell carcinoma (HNSCC). Analyzing TCGA and CPTAC mutation, RNA, and RPPA data and performing proteomics and IHC in two independent in-house cohorts, we uncovered molecular correlates of TB in an unprecedentedly comprehensive manner. NSD1 mutations were associated with lower TB in HPV-negative HNSCC. Comparing budding and nonbudding tumors, 66 miRNAs, including the miRNA-200 family, were differentially expressed in HPV-negative HNSCC. 3,052 (HPV-negative HNSCC) and 360 (HPV-positive HNSCC) RNAs were differentially expressed. EMT, myogenesis, and other cancer hallmarks were enriched in the overexpressed RNAs. In HPV-negative HNSCC, 88 proteins were differentially expressed, significantly overlapping with the differentially expressed RNAs. CAV1 and MMP14 protein expression investigated by IHC increased gradually from nonbudding tumors to the bulk of budding tumors and tumor buds. The molecular insights gained support new approaches to therapy development and guidance for HNSCC.

Time-course transcriptome analysis reveals gene co-expression networks and transposable element responses to cold stress in cotton

BACKGROUND

Cold stress significantly challenges cotton growth and productivity, yet the genetic and molecular mechanisms underlying cold tolerance remain poorly understood.

RESULTS

We employed RNA-seq and iterative weighted gene co-expression network analysis (WGCNA) to investigate gene and transposable element (TE) expression changes at six cold stress time points (0 h, 2 h, 4 h, 6 h, 12 h, 24 h). Thousands of differentially expressed genes (DEGs) were identified, exhibiting time-specific patterns that highlight a phase-dependent transcriptional response. While the A and D subgenomes contributed comparably to DEG numbers, numerous homeologous gene pairs showed differential expression, indicating regulatory divergence. Iterative WGCNA uncovered 125 gene co-expression modules, with some enriched in specific chromosomes or chromosomal regions, suggesting localized regulatory hotspots for cold stress response. Notably, transcription factors, including MYB73, ERF017, MYB30, and OBP1, emerged as central regulators within these modules. Analysis of 11 plant hormone-related genes revealed dynamic expression, with ethylene (ETH) and cytokinins (CK) playing significant roles in stress-responsive pathways. Furthermore, we documented over 15,000 expressed TEs, with differentially expressed TEs forming five distinct clusters. TE families, such as LTR/Copia, demonstrated significant enrichment in these expression clusters, suggesting their potential role as modulators of gene expression under cold stress.

CONCLUSIONS

These findings provide valuable insights into the complex regulatory networks underlying cold stress response in cotton, highlighting key molecular components involved in cold stress regulation. This study provides potential genetic targets for breeding strategies aimed at enhancing cold tolerance in cotton.

LATS1-modulated ZBTB20 perturbing cartilage matrix homeostasis contributes to early-stage osteoarthritis

Osteoarthritis (OA) is one of the most common degenerative joint diseases in the elderly, increasing in prevalence and posing a substantial socioeconomic challenge, while no disease-modifying treatments available. Better understanding of the early molecular events will benefit the early-stage diagnosis and clinical therapy. Here, we observed the nucleus accumulation of ZBTB20, a member of ZBTB-protein family, in the chondrocytes of early-stage OA. Chondrocytes-specific depletion of Zbtb20 in adult mice attenuated DMM-induced OA progress, restored the balance of extracellular matrix anabolism and catabolism. The NF-κB signaling mediated disturbance of ECM maintenance by ZBTB20 requires its suppression of Pten and consequent PI3K-Akt signaling activation. Furthermore, the subcellular localization of ZBTB20 was modulated by the kinase LATS1. Independent approaches to modulating ZBTB20 via utilizing TRULI and DAPA can restore ECM homeostasis, improving the abnormal behavior and moderating cartilage degeneration. The compounds TRULI and DAPA modulating ZBTB20 may serve as anti-OA drugs.

Transcriptome Complexity Disentangled: A Regulatory Molecules Approach

Transcription factors (TFs) and microRNAs (miRNAs) are fundamental regulators of gene expression, cell state, and biological processes. This study investigated whether a small subset of TFs and miRNAs could accurately predict genome-wide gene expression. We analyzed 8895 samples across 31 cancer types from The Cancer Genome Atlas and identified 28 miRNA and 28 TF clusters using unsupervised learning. Medoids of these clusters could differentiate tissues of origin with 92.8% accuracy, demonstrating their biological relevance. We developed Tissue-Agnostic and Tissue-Aware models to predict 20,000 gene expressions using the 56 selected medoid miRNAs and TFs. The Tissue-Aware model attained an R2 of 0.70 by incorporating tissue-specific information. Despite measuring only 1/400th of the transcriptome, the prediction accuracy was comparable to that achieved by the 1000 landmark genes. This suggests the transcriptome has an intrinsically low-dimensional structure that can be captured by a few regulatory molecules. Our approach could enable cheaper transcriptome assays and analysis of low-quality samples. It also provides insights into genes that are heavily regulated by miRNAs/TFs versus alternative mechanisms. However, model transportability was impacted by dataset discrepancies, especially in miRNA distribution. Overall, this study demonstrates the potential of a biology-guided approach for robust transcriptome representation.

SWI/SNF-type complexes-transcription factor interplay: a key regulatory interaction

ATP-dependent switch/sucrose nonfermenting-type chromatin remodeling complexes (SWI/SNF CRCs) are multiprotein machineries altering chromatin structure, thus controlling the accessibility of genomic DNA to various regulatory proteins including transcription factors (TFs). SWI/SNF CRCs are highly evolutionarily conserved among eukaryotes. There are three main subtypes of SWI/SNF CRCs: canonical (cBAF), polybromo (pBAF), and noncanonical (ncBAF) in humans and their functional Arabidopsis counterparts SYD-associated SWI/SNF (SAS), MINU-associated SWI/SNF (MAS), and BRAHMA (BRM)-associated SWI/SNF (BAS). Here, we highlight the importance of interplay between SWI/SNF CRCs and TFs in human and Arabidopsis and summarize recent advances demonstrating their role in controlling important regulatory processes. We discuss possible mechanisms involved in TFs and SWI/SNF CRCs-dependent transcriptional control of gene expression. We indicate that Arabidopsis may serve as a valuable model for the identification of evolutionarily conserved SWI/SNF-TF interactions and postulate that further exploration of the TFs and SWI/SNF CRCs-interplay, especially in the context of the role of particular SWI/SNF CRC subtypes, TF type, as well as cell/tissue and conditions, among others, will help address important questions related to the specificity of SWI/SNF-TF interactions and the sequence of events occurring on their target genes.

Transcriptome Complexity Disentangled: A Regulatory Molecules Approach

Transcription factors (TFs) and microRNAs (miRNAs) are fundamental regulators of gene expression, cell state, and biological processes. This study investigated whether a small subset of TFs and miRNAs could accurately predict genome-wide gene expression. We analyzed 8895 samples across 31 cancer types from The Cancer Genome Atlas and identified 28 miRNA and 28 TF clusters using unsupervised learning. Medoids of these clusters could differentiate tissues of origin with 92.8% accuracy, demonstrating their biological relevance. We developed Tissue-Agnostic and Tissue-Aware models to predict 20,000 gene expressions using the 56 selected medoid miRNAs and TFs. The Tissue-Aware model attained anR 2 of 0.70 by incorporating tissue-specific information. Despite measuring only 1/400th of the transcriptome, the prediction accuracy was comparable to that achieved by the 1000 landmark genes. This suggests the transcriptome has an intrinsically low-dimensional structure that can be captured by a few regulatory molecules. Our approach could enable cheaper transcriptome assays and analysis of low-quality samples. It also provides insights into genes that are heavily regulated by miRNAs/TFs versus alternative mechanisms. However, model transportability was impacted by dataset discrepancies, especially in miRNA distribution. Overall, this study demonstrates the potential of a biology-guided approach for robust transcriptome representation.

TF-chRDP: a method for simultaneously capturing transcription factor binding chromatin-associated RNA, DNA and protein

Transcription factors (TFs) play a crucial role in the regulation of gene expression and the structural organization of chromatin. They interact with proteins, RNA, and chromatin DNA to exert their functions. Therefore, an efficient and straightforward experimental approach that simultaneously captures the interactions of transcription factors with DNA, RNA, and proteins is essential for studying these regulatory proteins. In this study, we developed a novel method, TF-chRDP (Transcription Factor binding Chromatin-associated RNA, DNA, and Protein), which allows for the concurrent capture of these biomolecules in a single experiment. We enriched chromatin complexes using specific antibodies and divided the chromatin into three fractions: one for DNA library preparation to analyze the genomic binding sites of transcription factors, another for RNA library preparation to investigate the RNA associated with transcription factor binding, and the third for proteomic analysis to identify protein cofactors interacting with transcription factors. We applied this method to study the transcription factor p53 and its associated chromatin complexes. The results demonstrated high specificity in the enrichment of DNA, RNA and proteins. This method provides an efficient tool for simultaneously capturing chromatin-associated RNA, DNA and protein bound to specific TF, making it particularly useful for analyzing the role of protein-DNA-RNA complexes in transcriptional regulation.

Protein codes promote selective subcellular compartmentalization

Cells have evolved mechanisms to distribute ~10 billion protein molecules to subcellular compartments where diverse proteins involved in shared functions must assemble. In this study, we demonstrate that proteins with shared functions share amino acid sequence codes that guide them to compartment destinations. We developed a protein language model, ProtGPS, that predicts with high performance the compartment localization of human proteins excluded from the training set. ProtGPS successfully guided generation of novel protein sequences that selectively assemble in the nucleolus. ProtGPS identified pathological mutations that change this code and lead to altered subcellular localization of proteins. Our results indicate that protein sequences contain not only a folding code but also a previously unrecognized code governing their distribution to diverse subcellular compartments.

ROR1 facilitates glioblastoma growth via stabilizing GRB2 to promote c-Fos expression in glioma stem cells

BACKGROUND

Glioma stem cells (GSCs) are the root cause of tumorigenesis, recurrence, and therapeutic resistance in glioblastoma (GBM), the most prevalent and lethal type of primary adult brain malignancy. The exploitation of novel methods targeting GSCs is crucial for the treatment of GBM. In this study, we investigate the function of the novel ROR1-GRB2-c-Fos axis in GSCs maintenance and GBM progression.

METHODS

The expression characteristics of ROR1 in GBM and GSCs were assessed by bioinformatic analysis, patient specimens, and patient-derived GSCs. Lentivirus-mediated gene knockdown and overexpression were conducted to evaluate the effect of ROR1 on GSCs proliferation and self-renewal both in vitro and in vivo. The downstream signaling of ROR1 in GSCs maintenance was unbiasedly determined by RNA-seq and validated both in vitro and in vivo. Finally, rescue assays were performed to further validate the function of the ROR1-GRB2-c-Fos axis in GSCs maintenance and GBM progression.

RESULTS

ROR1 is upregulated in GBM and preferentially expressed in GSCs. Disruption of ROR1 markedly impairs GSC proliferation and self-renewal, and inhibits GBM growth in vivo. Moreover, ROR1 stabilizes GRB2 by directly binding and reducing its lysosomal degradation, and ROR1 knockdown significantly inhibits GRB2/ERK/c-Fos signaling in GSCs. Importantly, ectopic expression of c-Fos counteracts the effects caused by ROR1 silencing both in vitro and in vivo.

CONCLUSIONS

ROR1 plays essential roles in GSCs maintenance through binding to GRB2 and activation of ERK/c-Fos signaling, which highlights the therapeutic potential of targeting the ROR1-GRB2-c-Fos axis.

Identification of microproteins with transactivation activity by polyalanine motif selection

Microproteins are an emerging class of proteins that are encoded by small open reading frames (smORFs) less than or equal to 100 amino acids. The functions of several microproteins have been illuminated through phenotypic screening or protein-protein interaction studies, but thousands of microproteins remain uncharacterized. The functional characterization of microproteins is challenging due to a lack of sequence homology. Here, we demonstrate a strategy to enrich microproteins that contain specific motifs as a means to more rapidly characterize microproteins. Specifically, we used the fact that polyalanine motifs are associated with nuclear proteins to select 58 candidate microproteins to screen for transactivation function. We identified three microproteins with transactivation activity when tested as GAL4-fusions in a cell-based luciferase assay. The results support the continued use of the motif selection strategy for the discovery of microprotein function.

Bioinformatics analysis of electroacupuncture treatment for ischemic stroke: exploring transcriptional regulatory mechanisms mediated by super-enhancers

Background

Ischemic stroke is a leading cause of disability and mortality, imposing substantial physical, emotional, and economic burdens on patients and society. This study aimed to explore the regulatory effects of super-enhancers (SEs) on gene expression in the context of ischemic stroke and their potential transcriptional regulatory mechanisms.

Methods

Super-enhancers were identified via H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq) and ROSE software. RNA-sequencing (RNA-seq) was employed to screen for differentially expressed genes. A comparative analysis of ChIP-seq and RNA-seq data initially identified SE target genes, followed by further screening of key core differentially expressed SE target genes via the random forest method. The identified core SE target genes were initially validated through immunofluorescence and immunoblotting techniques. Additionally, potential core transcriptional regulatory circuits were preliminarily screened via the Coltron algorithm.

Results

We identified SE-associated genes in the ischemic stroke model and electroacupuncture-treated groups, revealing 41 genes uniquely regulated by SEs in the electroacupuncture group compared with 367 in the model group. Enrichment analyses revealed that pathways involved in axon guidance, regulation of lipolysis in adipocytes and sphingolipid signaling pathway were significantly enriched in the SE target genes, suggesting that these pathways may be involved in the therapeutic effects of electroacupuncture. Notably, HDAC7 emerged as a key SE-driven gene; its expression was significantly reduced following electroacupuncture treatment, indicating its potential as a therapeutic target. Protein expression analyses confirmed elevated levels of HDAC7 in the model group, which were reduced by electroacupuncture intervention (p < 0.05). Furthermore, core transcriptional regulatory circuitries involving SOX8, FOXK1, and KLF13 were identified, highlighting their roles in the modulation of SE-mediated gene regulation by acupuncture in the ischemic stroke context.

Conclusion

Overall, our findings provide novel insights into the molecular mechanisms by which acupuncture may treat ischemic stroke, identifying key SE target genes and transcriptional circuits as promising targets for future therapeutic strategies. Further research is warranted to validate these findings in clinical settings and explore the translational potential of acupuncture in ischemic stroke treatment.

Regulation of gene expression through protein-metabolite interactions

Organisms have to adapt to changes in their environment. Cellular adaptation requires sensing, signalling and ultimately the activation of cellular programs. Metabolites are environmental signals that are sensed by proteins, such as metabolic enzymes, protein kinases and nuclear receptors. Recent studies have discovered novel metabolite sensors that function as gene regulatory proteins such as chromatin associated factors or RNA binding proteins. Due to their function in regulating gene expression, metabolite-induced allosteric control of these proteins facilitates a crosstalk between metabolism and gene expression. Here we discuss the direct control of gene regulatory processes by metabolites and recent progresses that expand our abilities to systematically characterize metabolite-protein interaction networks. Obtaining a profound map of such networks is of great interest for aiding metabolic disease treatment and drug target identification.

Cell states and neighborhoods in distinct clinical stages of primary and metastatic esophageal adenocarcinoma

Esophageal adenocarcinoma (EAC) is a highly lethal cancer of the upper gastrointestinal tract with rising incidence in western populations. To decipher EAC disease progression and therapeutic response, we performed multiomic analyses of a cohort of primary and metastatic EAC tumors, incorporating single-nuclei transcriptomic and chromatin accessibility sequencing, along with spatial profiling. We identified tumor microenvironmental features previously described to associate with therapy response. We identified five malignant cell programs, including undifferentiated, intermediate, differentiated, epithelial-to-mesenchymal transition, and cycling programs, which were associated with differential epigenetic plasticity and clinical outcomes, and for which we inferred candidate transcription factor regulons. Furthermore, we revealed diverse spatial localizations of malignant cells expressing their associated transcriptional programs and predicted their significant interactions with microenvironmental cell types. We validated our findings in three external single-cell RNA-seq and three bulk RNA-seq studies. Altogether, our findings advance the understanding of EAC heterogeneity, disease progression, and therapeutic response.

Enhancer reprogramming: critical roles in cancer and promising therapeutic strategies

Transcriptional dysregulation is a hallmark of cancer initiation and progression, driven by genetic and epigenetic alterations. Enhancer reprogramming has emerged as a pivotal driver of carcinogenesis, with cancer cells often relying on aberrant transcriptional programs. The advent of high-throughput sequencing technologies has provided critical insights into enhancer reprogramming events and their role in malignancy. While targeting enhancers presents a promising therapeutic strategy, significant challenges remain. These include the off-target effects of enhancer-targeting technologies, the complexity and redundancy of enhancer networks, and the dynamic nature of enhancer reprogramming, which may contribute to therapeutic resistance. This review comprehensively encapsulates the structural attributes of enhancers, delineates the mechanisms underlying their dysregulation in malignant transformation, and evaluates the therapeutic opportunities and limitations associated with targeting enhancers in cancer.

Experimental approaches to investigate biophysical interactions between homeodomain transcription factors and DNA

Homeodomain transcription factors (TFs) bind to specific DNA sequences to regulate the expression of target genes. Structural work has provided insight into molecular identities and aided in unraveling structural features of these TFs. However, the detailed affinity and specificity by which these TFs bind to DNA sequences is still largely unknown. Qualitative methods, such as DNA footprinting, Electrophoretic Mobility Shift Assays (EMSAs), Systematic Evolution of Ligands by Exponential Enrichment (SELEX), Bacterial One Hybrid (B1H) systems, Surface Plasmon Resonance (SPR), and Protein Binding Microarrays (PBMs) have been widely used to investigate the biochemical characteristics of TF-DNA binding events. In addition to these qualitative methods, bioinformatic approaches have also assisted in TF binding site discovery. Here we discuss the advantages and limitations of these different approaches, as well as the benefits of utilizing more quantitative approaches, such as Mechanically Induced Trapping of Molecular Interactions (MITOMI), Microscale Thermophoresis (MST) and Isothermal Titration Calorimetry (ITC), in determining the biophysical basis of binding specificity of TF-DNA complexes and improving upon existing computational approaches aimed at affinity predictions.

The establishment of the 3D genome structure during zygotic genome activation

During zygotic genome activation (ZGA) and early development, hierarchical levels of chromatin structure undergo remarkable perturbations: changes in the nuclear-to-cytoplasmic ratio of various components; changes in chromatin accessibility; histone exchange; and the formation of 3D structures such as loops, topologically associated domains, and compartments. Here, we review the peculiarities, variability, and emergence of the chromatin structural features during ZGA in different organisms. Focusing on newly found structures called fountains, we describe the prerequisites for cohesin loading on DNA and possible mechanisms of genome organization in early development. Fountains resulting from asymmetric bidirectional cohesin extrusion spread from cohesin-loading points in a CTCF-independent manner. We discuss that fountains may not possess specific functions, unlike conventional chromatin structures, and could be found in other biological processes where cohesin loading occurs.

The contribution of genetic determinants of blood gene expression and splicing to molecular phenotypes and health outcomes

The biological mechanisms through which most nonprotein-coding genetic variants affect disease risk are unknown. To investigate gene-regulatory mechanisms, we mapped blood gene expression and splicing quantitative trait loci (QTLs) through bulk RNA sequencing in 4,732 participants and integrated protein, metabolite and lipid data from the same individuals. We identified cis-QTLs for the expression of 17,233 genes and 29,514 splicing events (in 6,853 genes). Colocalization analyses revealed 3,430 proteomic and metabolomic traits with a shared association signal with either gene expression or splicing. We quantified the relative contribution of the genetic effects at loci with shared etiology, observing 222 molecular phenotypes significantly mediated by gene expression or splicing. We uncovered gene-regulatory mechanisms at disease loci with therapeutic implications, such as WARS1 in hypertension, IL7R in dermatitis and IFNAR2 in COVID-19. Our study provides an open-access resource on the shared genetic etiology across transcriptional phenotypes, molecular traits and health outcomes in humans ( https://IntervalRNA.org.uk ).

Integrated analysis of ATAC-seq and RNA-seq reveals the chromatin accessibility and transcriptional landscape of immunoglobulin a nephropathy

BACKGROUNDS

The association between chromatin accessibility in CD4+ T cells and Immunoglobulin A nephropathy (IgAN) remains unclear.

METHODS

We performed the assay for transposase accessible chromatin with sequencing (ATAC-seq) and RNA sequencing (RNA-seq) on CD4+ T cells. ATAC-seq and RNA-seq were conducted to identify differentially accessible regions and differentially expressed genes (DEGs), respectively (P < 0.05, |log2 Fold Change| >1). QRT-PCR was utilized to validate target gene expression.

RESULTS

We identified 100,865 differentially accessible regions, of which 7225 exhibited higher accessibility in IgAN. Functional analysis revealed that these regions are enriched in T lymphocyte activation and immune pathways. ELF3, MEIS1, and NFYC were identified as key TFs associated with IgAN. QRT-PCR indicated a significant upregulation of hub genes including MEIS1 in IgAN.

CONCLUSION

We identified key TFs and genes by integrating ATAC-seq and RNA-seq, which provide novel therapeutic targets for IgAN and insights into its pathogenesis from an epigenetic perspective.

Molecular and cellular role of variants of the promoter region of HAND1 gene in sporadic and isolated ventricular septal defect

Ventricular septal defect (VSD) is the most common type of congenital heart disease. HAND1 gene plays a crucial role in the development of the heart, but the role of the variants in the HAND1 gene promoter region in patients with VSD has not been explored yet. From 588 participants (300 with isolated and sporadic VSD and 288 healthy controls), DNA was extracted from blood samples. Variants at the HAND1 gene promoter region were analyzed through Sanger sequencing. Subsequently, cell functional validation was conducted through cell experiments, including dual-luciferase reporter gene analysis, electrophoretic mobility shift analysis, and bioinformatics analysis was also conducted. The promoter region of HAND1 gene had a total of 9 identified variant sites. Among them, 4 variants were exclusively found in VSD patients, and 1 variant (g.3631A>C) was newly discovered. Cell functional experiments indicated that all four variants decreased the transcriptional activity of HAND1 gene promoter with three of them reached statistical significance (p < 0.05). Subsequent analysis using JASPAR (a transcription factor binding profile database) suggests that these variants may alter the binding sites of transcription factors, potentially contributing to the formation of VSD. Our study for the first time identified variants in the promoter region of HAND1 gene in Chinese patients with isolated and sporadic VSD. These variants significantly decreased the expression of HAND1 gene, impacting transcription factor binding sites, and thereby demonstrating pathogenicity. This study offers new insights into the role of HAND1 gene promoter region, contributing to a better understanding of the genetic basis of VSD formation.

Integrative analysis identifies the atypical repressor E2F8 as a targetable transcriptional activator driving lethal prostate cancer

Acquired resistance to androgen receptor (AR)-targeted therapies underscores the need to identify alternative therapeutic targets for treating lethal prostate cancer. In this study, we evaluated the prognostic significance of 1635 human transcription factors (TFs) by analyzing castration-resistant prostate cancer (CRPC) datasets from the West and East Stand Up to Cancer (SU2C) cohorts. Through this screening approach, we identified E2F8, a putative transcriptional repressor, as a TF consistently associated with poorer patient outcomes in both cohorts. Notably, E2F8 is highly expressed and active in AR-negative CRPC compared to AR-positive CRPC. Integrative profiling of E2F8 cistromes and transcriptomes in AR-negative CRPC cells revealed that E2F8 directly and non-canonically activates target oncogenes involved in cancer-associated pathways. To target E2F8 in CRPC, we employed the CRISPR/CasRx system to knockdown E2F8 mRNA, resulting in effective and specific downregulation of E2F8 and its target oncogenes, as well as significant growth inhibition in AR-negative CRPC in both cultured cells and xenograft models. Our findings identify and characterize E2F8 as a targetable transcriptional activator driving CRPC, particularly the growth of AR-negative CRPC.

KLF6-mediated recruitment of the p300 complex enhances H3K23su and cooperatively upregulates SEMA3C with FOSL2 to drive 5-FU resistance in colon cancer cells

Histone lysine succinylation, an emerging epigenetic marker, has been implicated in diverse cellular functions, yet its role in cancer drug resistance is not well understood. Here we investigated the genome-wide alterations in histone 3 lysine 23 succinylation (H3K23su) and its impact on gene expression in 5-fluorouracil (5-FU)-resistant HCT15 colon cancer cells. We utilized CUT&Tag assays to identify differentially enriched regions (DERs) of H3K23su in 5-FU-resistant HCT15 cells via integration with ATAC-seq and RNA sequencing data. The regulatory network involving transcription factors (TFs), notably FOSL2 and KLF6, and their downstream target genes was dissected using motif enrichment analysis and chromatin immunoprecipitation assays. Our results revealed a strong positive correlation between H3K23su DERs, differentially expressed genes (DEGs) and H3K27ac, indicating that H3K23su enrichment is closely related to gene activation. The DEGs associated with the H3K23su GAIN regions were significantly enriched in pathways related to colorectal cancer, including the Wnt, MAPK and p53 signaling pathways. FOSL2 and KLF6 emerged as pivotal TFs potentially modulating DEGs associated with H3K23su DERs and were found to be essential for sustaining 5-FU resistance. Notably, we discovered that FOSL2 and KLF6 recruit the PCAF-p300/CBP complex to synergistically regulate SEMA3C expression, which subsequently modulates the canonical Wnt-β-catenin signaling pathway, leading to the upregulation of MYC and FOSL2. This study demonstrated that H3K23su is a critical epigenetic determinant of 5-FU resistance in colon cancer cells, exerting its effects through the modulation of critical genes and TFs. These findings indicate that interventions aimed at targeting TFs or enzymes involved in H3K23su modification could represent potential therapeutic strategies for treating colorectal cancers that are resistant to 5-FU treatment.

Thermodynamic for biological development: A hypothesis

This paper proposes a thermodynamic model of biological development. Several key thoughts are presented: 1) in view of thermodynamics, biological development processes irreversibly; 2) in view of thermodynamics and molecular biology, positive autoregulation, or self-regulation, of transcription factors is the only way to ensure irreversibility of a thermodynamic process of biology; 3) change in the autoregulation of transcription factors can irreversibly result in alterations in the physiological state) a physiological state is a system of signaling networks; 5) a cell and its physiological state can be identified by the pattern of its transcription factors. 6) from points aforementioned, we can analyze some thermodynamic properties of biological development by knowledge of molecular biology and biochemistry. The possible mechanisms of plant vernalization are also proposed.

Functional analysis of cancer-associated germline risk variants

Single-nucleotide variants (SNVs) in regulatory DNA are linked to inherited cancer risk. Massively parallel reporter assays of 4,041 SNVs linked to 13 neoplasms comprising >90% of human malignancies were performed in pertinent primary human cell types and then integrated with matching chromatin accessibility, DNA looping and expression quantitative trait loci data to nominate 380 potentially regulatory SNVs and their putative target genes. The latter highlighted specific protein networks in lifetime cancer risk, including mitochondrial translation, DNA damage repair and Rho GTPase activity. A CRISPR knockout screen demonstrated that a subset of germline putative risk genes also enables the growth of established cancers. Editing one SNV, rs10411210 , showed that its risk allele increases rhophilin RHPN2 expression and stimulus-responsive RhoA activation, indicating that individual SNVs may upregulate cancer-linked pathways. These functional data are a resource for variant prioritization efforts and further interrogation of the mechanisms underlying inherited risk for cancer.

Active repression of cell fate plasticity by PROX1 safeguards hepatocyte identity and prevents liver tumorigenesis

Cell fate plasticity enables development, yet unlocked plasticity is a cancer hallmark. While transcription master regulators induce lineage-specific genes to restrict plasticity, it remains unclear whether plasticity is actively suppressed by lineage-specific repressors. Here we computationally predict so-called safeguard repressors for 18 cell types that block phenotypic plasticity lifelong. We validated hepatocyte-specific candidates using reprogramming, revealing that prospero homeobox protein 1 (PROX1) enhanced hepatocyte identity by direct repression of alternative fate master regulators. In mice, Prox1 was required for efficient hepatocyte regeneration after injury and was sufficient to prevent liver tumorigenesis. In line with patient data, Prox1 depletion caused hepatocyte fate loss in vivo and enabled the transition of hepatocellular carcinoma to cholangiocarcinoma. Conversely, overexpression promoted cholangiocarcinoma to hepatocellular carcinoma transdifferentiation. Our findings provide evidence for PROX1 as a hepatocyte-specific safeguard and support a model where cell-type-specific repressors actively suppress plasticity throughout life to safeguard lineage identity and thus prevent disease.

Chemokine Ligands and Receptors Regulate Macrophage Polarization in Atherosclerosis: A Comprehensive Database Mining Study

Background

Atherosclerosis is a systemic disease involving multiple blood vessels and a major cause of cardiovascular disease. Current treatment methods (eg, statins) for atherosclerosis can reduce the risk of cardiovascular diseases effectively, but they are insufficient to completely reverse existing atherosclerosis. Macrophages play a central role in development of atherosclerosis. Chemokines, the main mediators of macrophage chemotaxis, are important in immune and inflammatory responses. The effects of chemokines on mechanisms involved in atherosclerosis are unknown. This study preliminarily investigated these effects and mechanisms via bioinformatics methods.

Methods

In this study, data on chemokine ligands and receptors were obtained by mining public databases (the National Center of Biotechnology Information-Gene Expression Omnibus [NCBI-GEO] database, ArrayExpress database, and single-cell RNA sequencing [scRNA-seq] database), and an extensive literature search was performed. The expression levels of chemokines in mouse tissues were analyzed via Metascape software for signalling pathway enrichment, scRNA-seq data for chemokine expression in atherosclerotic plaque progression and regression, and GEO2R data for chemokine expression during macrophage polarization. Ingenuity Pathway Analysis (IPA) software was used to analyze regulatory factors such as transcription factors and microRNAs that are significantly differentially expressed upstream of chemokines in macrophage polarization. Finally, a model of the chemokine regulation of atherosclerosis was established on the basis of these results.

Results

There are 5 main findings: (1) In atherosclerosis, chemokines are regulated by transcription factors and microRNAs. (2) The transcription factor STAT1 promotes the polarization of dormant (M0) macrophages into classically activated (M1) macrophages and alternative activated (M2) macrophages by regulating chemokines. The transcription factors STAT1, IRF7 and IRF1 regulate the polarization of M0 macrophages into M2a and M2b macrophages via different chemokines. For example, some transcription factors promote M1 polarization of M0 macrophages through CCL4, but M2 macrophage polarization is regulated via CCL19, CCL5 and CCR7. (3) Transcription factors can promote and inhibit, whereas miRNAs can only inhibit atherosclerosis. (4) CCL4 existed in all 5 different chemokine-regulated macrophage models, whereas CXCL3 only existed in the M2b macrophage transcriptional regulation model, indicating that CXCL3 may promote the M2b type macrophages polarization of M0 macrophages. (5) CCL5 and CCR7 can promote the M2a macrophages and M2b macrophages polarization of M0 macrophages.

Conclusions

Atherosclerosis can be treated by regulating chemokines and regulating the polarization of macrophages. The chemokines CCL4, CCL5, CCL8, CCL19, CXCL3, CXCL10, CXCL13, and CCR7 may play key roles in the progression and regression of atherosclerosis.

TFIIH kinase CDK7 drives cell proliferation through a common core transcription factor network

How cyclin-dependent kinase 7 (CDK7) coordinately regulates the cell cycle and RNA polymerase II transcription remains unclear. Here, high-resolution cryo-electron microscopy revealed how two clinically relevant inhibitors block CDK7 function. In cells, CDK7 inhibition rapidly suppressed transcription, but constitutively active genes were disproportionately affected versus stimulus-responsive. Distinct transcription factors (TFs) regulate constitutive versus stimulus-responsive genes. Accordingly, stimulus-responsive TFs were refractory to CDK7 inhibition whereas constitutively active "core" TFs were repressed. Core TFs (n = 78) are predominantly promoter associated and control cell cycle and proliferative gene expression programs across cell types. Mechanistically, rapid suppression of core TF function can occur through CDK7-dependent phosphorylation changes in core TFs and RB1. Moreover, CDK7 inhibition depleted core TF protein levels within hours, consistent with durable target gene suppression. Thus, a major but unappreciated biological function for CDK7 is regulation of a TF cohort that drives proliferation, revealing an apparent universal mechanism by which CDK7 coordinates RNAPII transcription with cell cycle CDK regulation.

Deep learning-based cell-specific gene regulatory networks inferred from single-cell multiome data

Gene regulatory networks (GRNs) provide a global representation of how genetic/genomic information is transferred in living systems and are a key component in understanding genome regulation. Single-cell multiome data provide unprecedented opportunities to reconstruct GRNs at fine-grained resolution. However, the inference of GRNs is hindered by insufficient single omic profiles due to the characteristic high loss rate of single-cell sequencing data. In this study, we developed scMultiomeGRN, a deep learning framework to infer transcription factor (TF) regulatory networks via unique integration of single-cell genomic (single-cell RNA sequencing) and epigenomic (single-cell ATAC sequencing) data. We create scMultiomeGRN to elucidate these networks by conceptualizing TF network graph structures. Specifically, we build modality-specific neighbor aggregators and cross-modal attention modules to learn latent representations of TFs from single-cell multi-omics. We demonstrate that scMultiomeGRN outperforms state-of-the-art models on multiple benchmark datasets involved in diseases and health. Via scMultiomeGRN, we identified Alzheimer's disease-relevant regulatory network of SPI1 and RUNX1 for microglia. In summary, scMultiomeGRN offers a deep learning framework to identify cell type-specific gene regulatory network from single-cell multiome data.

Hematopoietic stem cells undergo bidirectional fate transitions in vivo

Transitions between subsets of differentiating hematopoietic cells are widely regarded as unidirectional in vivo. Here, we introduce clonal phylogenetic tracer (CP-tracer) that sequentially introduces genetic barcodes, enabling high-resolution analysis of ~100,000 subclones derived from ~500 individual hematopoietic stem cells (HSC). This revealed previously uncharacterized HSC functional subsets and identified bidirectional fate transitions between myeloid-biased and lineage-balanced HSC. Contrary to the prevailing view that the more self-renewing My-HSCs unidirectionally transition to balanced-HSCs, phylogenetic tracing revealed durable lineage bidirectionality with the transition favoring My-HSC accumulation over time1,2. Further, balanced-HSCs mature through distinct intermediates My-HSCs and lymphoid-biased-HSCs with lymphoid competence here shown by CRISPR/Cas9 screening to be dependent on the homeobox gene, Hhex. Hhex enables Ly-HSC differentiation, but its expression declines with age. These findings establish HSC plasticity and Hhex as a determinant of myeloid-lymphoid balance with each changing over time to favor the age-related myeloid bias of the elderly.

Temporal Transcriptomic Analysis of Periodontal Disease Progression and Its Molecular Links to Systemic Diseases

Periodontal disease, a prevalent oral inflammatory condition, is implicated in exacerbating systemic diseases. However, the molecular mechanisms underlying this association remain unclear. In this study, we performed RNA sequencing of gingival tissue samples collected from a mouse model of periodontal disease at multiple time points to investigate dynamic transcriptomic changes during disease progression. Our analysis revealed distinct temporal gene expression patterns associated with the key inflammatory and immune response pathways. These findings suggest stepwise molecular progression in the periodontal inflammatory process, potentially contributing to systemic inflammation through shared signaling networks. We further identified specific genes and pathways that may mediate the bidirectional relationship between periodontal disease and systemic conditions such as cardiovascular disease and diabetes. By elucidating the temporal dynamics of molecular changes in periodontal disease, this study provides insights into the pathogenesis and its systemic implications. It identifies potential biomarkers and therapeutic targets for local and systemic disease management.

CRISPR screening identifies regulators of enhancer-mediated androgen receptor transcription in advanced prostate cancer

Amplification of the androgen receptor (AR) locus is the most frequent alteration in metastatic castration-resistant prostate cancer (CRPC). Recently, it was discovered that an enhancer of the AR is co-amplified with the AR gene body and contributes to increased AR transcription and resistance to androgen deprivation therapy. However, the mechanism of enhancer activation in advanced disease is unknown. Here, we used CRISPR-Cas9 screening to identify transcription factors that bind to the AR enhancer and modulate enhancer-mediated AR transcription. We demonstrate that HOXB13, GATA2, and TFAP2C bind the AR enhancer in patient-derived xenografts and directly impact features associated with an active chromatin state. Interestingly, the AR enhancer belongs to a set of regulatory elements that require HOXB13 to maintain FOXA1 binding, further delineating the role of HOXB13 in CRPC. This work provides a framework to functionally identify trans-acting factors required for the activation of disease-related noncoding regulatory elements.

Edaravone mitigates TDP-43 mislocalization in human amyotrophic lateral sclerosis neurons with potential implication of the SIRT1-XBP1 pathway

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive motor neuron loss along with pathological mislocalization of TAR DNA-binding protein 43 (TDP-43), a protein implicated in RNA metabolism. Although edaravone, a free-radical scavenger, has been approved for ALS treatment, its precise mechanism of action is not fully understood, particularly in relation to TDP-43 pathology. Here, we investigated the effects of edaravone on induced pluripotent stem cell (iPSC)-derived motor neurons in a patient with ALS harboring a TDP-43 mutation. Our results demonstrated that edaravone significantly attenuated neurodegeneration, as evidenced by neurite preservation, neuronal cell death reduction, and correction of aberrant cytoplasmic localization of TDP-43. These neuroprotective effects were not observed with vitamin C, indicating a unique mechanism of action for edaravone, distinct from its antioxidative properties. RNA sequencing revealed that edaravone rapidly modulated gene expression, including protein quality control pathway, such as the ubiquitin-proteasome system. Further analysis identified X-box binding protein (XBP1), a key regulator of the endoplasmic reticulum stress response, as a critical factor in the therapeutic effects of edaravone. This study suggests that edaravone may offer a multifaceted therapeutic approach for ALS by targeting oxidative stress and TDP-43 mislocalization through distinct molecular pathways.

Unveiling Novel miRNA-mRNA Interactions and Their Prognostic Roles in Triple-Negative Breast Cancer: Insights into miR-210, miR-183, miR-21, and miR-181b

Triple-negative breast cancer (TNBC) poses a major clinical challenge due to its aggressive progression and limited treatment options, making early diagnosis and prognosis critical. MicroRNAs (miRNAs) are crucial post-transcriptional regulators that influence gene expression. In this study, we unveil novel miRNA-mRNA interactions and introduce a prognostic model based on miRNA-target interaction (MTI), integrating miRNA-mRNA regulatory correlation inference and the machine learning method to effectively predict the survival outcomes in TNBC cohorts. Using this method, we identified four key miRNAs (miR-181b-5p, miR-21-5p, miR-210-3p, miR-183-5p) targeting eight downstream target genes, forming a novel regulatory network of 19 validated miRNA-mRNA pairs. A prognostic model constructed based on the top 10 significant MTI pairs using random forest combination effectively classified patient survival outcomes in both TCGA and independent dataset GSE19783 cohorts, demonstrating good predictive accuracy and valuable prognostic insights for TNBC patients. Further analysis uncovered a complex network of 71 coherent feed-forward loops involving transcription factors, miRNAs, and target genes, shedding light on the mechanisms driving TNBC progression. This study underscores the importance of considering regulatory networks in cancer prognosis and provides a foundation for new therapeutic strategies aimed at improving TNBC treatment outcomes.