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PubMed2026

Dysregulated Sheddase Signalling as a Molecular Driver of Plaque Instability Revealed by Integrative Transcriptomics.

Atherosclerosis is a major cause of mortality due to chronic and progressive low-grade inflammation and fibroproliferative remodelling of the intima of arteries. Comprehensive understanding of the interplay between plaque biology and the mechanisms underlying plaque vulnerability and rupture is essential. Here, we aimed to investigate the transcriptomic profiles of stable and unstable atherosclerotic plaques using RNA sequencing data from human carotid atherosclerotic plaque samples based on next-generation knowledge discovery (NGKD) methods. High-throughput RNA-seq data from plaques dissected in stable and unstable regions of four patients were obtained from the Gene Expression Omnibus (GEO) database. GEO RNA-seq Experiments Interactive Navigator (GREIN) software was used to obtain raw gene-level counts and filtered metadata for this dataset. The data were further filtered and normalized using Express analyst to derive differentially expressed genes (DEGs) in unstable plaques compared to stable plaques. The DEGs were further analysed using WebGestalt, STRING DB, preranked gene set enrichment analysis (GSEA), and Ingenuity Pathway Analysis (IPA) software. We identified 4792 DEGs in unstable plaques based on a p-value cutoff of < 0.05. NGKD analysis revealed that the sheddase pathway, collagen degradation, activation of matrix metalloproteinases (MMPs), and extracellular matrix (ECM) degradation ranked among the top five upregulated pathways, whereas the inhibition of MMPs and smooth muscle contraction pathways were identified as the most prominent downregulated pathways in unstable plaques. We found that the sheddase pathway was one of the most significantly upregulated canonical pathways in unstable plaques and this finding opens new avenues for potential therapeutic interventions in patients with atherosclerosis.

Humans↗

PubMed2026

Insights into the regulatory roles of LIKE-HETEROCHROMATIN PROTEIN 1 and its targeting to different nuclear compartments modulated by NLS and the conserved domains in the moss Physcomitrium patens.

LIKE-HETEROCHROMATIN PROTEIN 1 (LHP1) is a polycomb group protein that exists in shared multiprotein complexes that harbor core PRC1 and PRC2 proteins. We previously characterized LHP1 in the moss Physcomitrium patens and showed that its function is closely linked with regulation of RNA metabolic processes and the protein is distributed in the nucleoplasm, subnuclear foci, and the nucleolus. To gain mechanistic insight into PpLHP1-mediated gene regulation, in the present study genome-wide changes in transcript profiles of genes affected by loss-of-PpLHP1 function were studied using pplhp1 mutants. RNA-seq analysis reveals a key role for PpLHP1 in regulating energy metabolic processes, ribosome-related pathways, stress signaling/responsive pathways, DNA transcription, etc. ChIP using H3K27me3 coupled with qRT-PCR shows that PpLHP1 suppresses transcription at 5S rRNA promoters and the untimely activation of genes regulating developmental transition by PRC2-dependent and independent mechanisms. To study how PpLHP1 finds its targets in different nuclear compartments and the roles of the multiple NLSs and the conserved domains in guiding the protein, FRAP and deletion studies were performed. These show that PpLHP1 is a mobile protein that diffuses freely in the nucleoplasmic space showing different retention times in the nucleolus, nucleoplasm, and the subnuclear foci indicating its differential affinity for targets at these sites. Expression of PpLHP1 fragments in protonema cells and its subsequent visualization under confocal microscope shows that localization of PpLHP1 to different subnuclear compartments is guided by the monopartite NLS2, CD, and CSD that also play a key role in promoting subnuclear foci formation in the nucleoplasm.

Bryopsida↗

PubMed2026

Transcriptional and phytohormonal regulation of positional ear development reveals yield strategies in maize.

Maize (Zea mays L.) is a vital global crop, contributing ∼37% of annual grain production. Enhancing yield per unit area is crucial for food security, yet research has primarily focused on single-ear traits, overlooking the regulation of double ears-a key determinant of prolificacy. While secondary ears drive yield variability under prolificacy-favoring conditions, the mechanisms governing ear formation across shoot positions remain poorly understood. Here, we performed high-resolution transcriptomic analysis of 66 samples from three ear types (primary, secondary and third) in maize inbred B73. We uncovered distinct hormonal developmental dynamics: strigolactone (SL) signaling genes, particularly SBP transcription factors, dominated in primary (I) ears, whereas ethylene-related genes (e.g., ZmEREB131, ZmACCO35) were enriched in third (III) ears. Functional validation confirmed that knockout of ZmEREB131 and ZmACCO35 accelerated development and elongated ears compared to wild-type, implicating ethylene (ETH) signaling in ear maturation arrest. Notably, SL inhibitor application synchronized primary and secondary ear development, boosting total yield by >20% without compromising primary ear performance. Our study elucidates the transcriptional networks underlying differential ear development and provides actionable strategies for yield improvement through targeted hormonal modulation. These findings advance the understanding of maize inflorescence biology and offer molecular tools for breeding high-yielding varieties.

RNA-seq↗

PubMed2026

Influenza A virus co-infection alters Streptococcus pneumoniae gene expression during upper respiratory tract colonization.

Streptococcus pneumoniae (Spn) asymptomatically colonizes the upper respiratory tract (URT), a niche from which it can transmit to another host or cause invasive disease in the same host. The in vivo transcriptional adaptations that Spn undergoes during nasopharyngeal colonization, particularly during influenza A virus (IAV) co-infection, are poorly understood. Here, we leveraged an established infant mouse model of colonization, shedding, and transmission to perform genome-wide transcriptomic profiling of Spn during mono- and during IAV co-infection. Compared with broth-grown controls, pneumococci isolated from the URT exhibited distinct transcriptional programs, with over 200 genes differentially expressed across time points. Genes involved in carbohydrate uptake and metabolism, glycan degradation, amino sugar and nucleotide sugar metabolism, and amino acid biosynthesis were consistently enriched during colonization, highlighting metabolic adaptation to the nasopharyngeal niche. In contrast, IAV co-infection induced a markedly distinct transcriptional signature, including upregulation of branched-chain amino acid biosynthesis, bacteriocin production, and phosphate acquisition systems. Notably, the pilus islet-1 locus was upregulated during Spn-IAV co-infection. Functional studies demonstrated that while the pilus was dispensable for colonization under mono- and co-infection conditions, it promoted high-shedding events and enhanced inflammatory responses during IAV co-infection. However, reduced inflammation and reduced high-shedding events from pups inoculated with a pilus-deficient mutant did not alter transmission frequency in the infant mouse model. Collectively, our findings define the in vivo transcriptional landscape of Spn during URT colonization and reveal distinct bacterial adaptations during viral co-infection, providing insight into mechanisms that influence pneumococcal persistence, inflammation, and transmission.

RNA-seq↗

PubMed2026

Isoform-Level Analysis Reveals Reproducible Early Changes in Transcript Usage During Human Vaccine Responses.

Vaccine-induced transcriptional responses have been extensively characterized at the gene level, but whether vaccination also alters transcript isoform usage remains largely unexplored. Here, we reanalyzed longitudinal whole-blood RNA-seq data from a discovery cohort of mRNA COVID-19 vaccine recipients using the IsoformSwitchAnalyzeR framework and validated the findings in an independent cohort. Key findings were validated by full-length RNA long-read sequencing and extended to four additional vaccine cohorts covering distinct platforms and pathogens. mRNA vaccination induced a rapid and transient wave of differential transcript usage, peaking at 24 h post-vaccination with 131 isoforms significantly altered across 107 genes, before largely resolving by Day 14. Isoform switching events were reproducible across independent cohorts and confirmed by full-length RNA long-read sequencing. Structural annotation of switching transcripts, including RMI2, WARS1, and NT5C3A, revealed changes affecting predicted protein domains and signal peptides. Notably, highly concordant isoform switching patterns were observed across MVA-based SARS-CoV-2, influenza, and Ebola vaccine cohorts and showed dose-dependent modulation. Overall, differential transcript isoform usage is a rapid and transient feature of the early human immune response to vaccination that was observed across multiple vaccine platforms. These findings reveal an underappreciated layer of transcriptional regulation that complements conventional gene-level analyses and warrants integration into future vaccine immunogenicity studies.

Humans↗

PubMed2025

Transcriptome-Wide Analysis of the 5' Cap Status of RNA Using 5' Monophosphate-Dependent Exonuclease Digestion and RNA Sequencing.

Eukaryotic mRNAs carry an N7-methylguanosine (m7G) cap structure at their 5' extremity, which protects them from the degradation by 5'-3' exoribonucleases and plays a pivotal role in mRNA metabolism, promoting splicing, nuclear export, and translation. Decapping, the enzymatic process that removes this structure, is a key event during cytoplasmic mRNA 5'-3' decay, leading to the degradation of the transcript body by Xrn1. In this chapter, we describe a procedure to assess the cap status of RNA at the transcriptome level. It is based on a treatment of total RNA extracts with a 5' monophosphate-dependent exonuclease, which like Xrn1 specifically degrades decapped RNAs harboring 5' monophosphate extremities, but not RNAs with intact m7G cap. The digested RNAs are then analyzed by RNA sequencing.

Exoribonucleases↗

PubMed2026

Mineral-driven molecular signatures of energy metabolism underpin sperm motility in buffalo.

The success of spermatogenesis depends on the interplay of various biomolecules that ultimately determine sperm quality. In this study, RNA-seq analysis of frozen-thawed buffalo sperm (n = 8) revealed the presence of 263 mineral-associated genes (>1 FPKM) in high (n = 4) and 181 in low motile (n = 4) sperm groups. Among these, 177 mineral-associated genes were commonly expressed between them, and the majority were upregulated (>1 fold), LOC102391588 (ncRNA; 37-fold), ZNF699 (26.5-fold), MYZAP (13-fold), etc., in the high motile group. The expression of selected mineral-associated genes was validated. The top enriched functions in commonly expressed genes were regulation of transcription by RNA polymerase II (FDR: 4.7 × 10⁻2; ZNF331, ZNF692, ZNF180, etc.), followed by spermatogenesis (FDR: 2.9 × 10⁻2; CALR3, ADAM18, ADAM29, etc.), proton transmembrane transport (FDR: 4.0 × 10⁻2; ATP6V0E1, ATP1A4, ATP6V1B2, etc.) and flagellated sperm motility (FDR: 2.3 × 10⁻1; CATSPERD, EFCAB6, CABS1, etc.). Additionally, the chromatin remodeling pathway (FDR: 3 × 10⁻2; PTP4A1, PPM1A, DUSP1, etc.) emerged as the most significant and may suggest that these minerals influence genome packaging and sperm functionality. Mineral-associated genes were predominantly associated with zinc (49%), followed by calcium (20%), phosphorus (10%), iron (5%), sodium (2%), potassium (2%), copper (1%) and other trace elements (11%). Although the current study uses frozen-thawed sperm, the findings indicate that mineral-associated genes are crucial for promoting membrane stability, energy production, motility and chromatin integrity, which may contribute to the superior fertilizing ability of sperm.

Animals↗

PubMed2026

Pervasive noise in human pre-mRNA splice site selection.

RNA splicing has historically been thought to be highly efficient and accurate, with little opportunity for deviation from regulated alternative splicing. This dogma has been challenged by recent observations that biological noise may contribute substantially to transcriptome diversity. However, quantitative understanding of stochastic splicing variation is challenging because these transcripts are likely subject to rapid degradation. Here, we use deep sequencing across RNA compartments to track splicing intermediates in human cells and see abundant cryptic splicing associated with genomic features that promote splicing noise. We observe pervasive usage of low-fidelity splice sites, likely due to stochasticity in recruitment or binding of the spliceosome. These sites are turned over quickly and show evidence for nuclear and cytoplasmic degradation, suggesting widespread surveillance and rapid quality control of non-productive transcripts. Our findings provide insights into the propensity for error in RNA processing mechanisms and regulation of alternative splice sites across a gene.

Humans↗

PubMed2026

Firemaster 550 differentially alters gene expression underlying synaptic function in amygdala of prairie voles after gestational or lactational exposure.

Neurodevelopmental disorders often share similar behavioral diagnostic criteria including socioemotional and cognitive deficits. The prairie vole is a uniquely suitable model to study these deficits because they demonstrate strong social affiliation, bi-parental care, and partner attachment. Previously, we have shown that developmental exposure to the flame-retardant mixture Firemaster 550 (FM 550) impairs socioemotional behavior in the prairie vole and alters underlying neuroanatomy and function. However, the mechanisms for impaired pair bonding in males and increased anxiety in females remain unknown, along with the specific critical window(s) of vulnerability. Herein, we exposed prairie vole dams to FM 550 during gestation or lactation, and performed bulk RNA-seq on the amygdala, a hub of socioemotional processing, in their adult offspring. Two mathematically orthogonal methods were utilized for analysis, a linear statistical method and an ensemble machine learning method, incorporating sex as a biological variable. Gene ontology (GO) pathway analysis was performed following both and results compared to identify potential mechanisms of toxicity. GO results indicated consistent expression changes in the Synapse cellular component in all conditions, and implicated glutamatergic signaling specifically. Additionally, gestational exposure (GE) altered genes underlying modulation of synaptic transmission and neural development, while lactational exposure (LE) impacted genes underlying synaptic plasticity, axon guidance, and mitophagy. Machine learning identified disruption of endocrine system development, regulation of biosynthetic processes in GE animals, and suppression of various neuroinflammatory genes across multiple groups. Finally, we performed RNA expression analysis using Nanostring and demonstrated stronger correlation with the differentially expressed genes (DEG) of interest in females than males. Overall, this study demonstrates both the intersecting and distinct impacts of FM 550 exposure on amygdalar gene expression depending on sex and timing of exposure.

Animals↗

PubMed2026

A latent activated olfactory stem cell state revealed by single-cell transcriptomic and epigenomic profiling.

The olfactory epithelium is one of the few regions of the nervous system that sustains neurogenesis throughout life. Its experimental accessibility makes it especially tractable for studying molecular mechanisms that drive neural regeneration in response to injury. In this study, we used single-cell sequencing to identify transcriptional and epigenetic processes involved in determining olfactory epithelial stem cell fate during injury-induced regeneration. By combining gene expression and accessible chromatin profiles of individual lineage-traced olfactory stem cells, we identified transcriptional heterogeneity among activated stem cells at a stage when cell fates are being specified. We further identified a subset of resting cells that appears poised for activation, characterized by accessible chromatin around silent genes prior to their expression in response to injury. These results provide evidence for a latent activated stem cell state in which a subset of quiescent olfactory epithelial stem cells are epigenetically primed to support injury-induced regeneration.

Animals↗

PubMed2026

Integrated single-cell and bulk transcriptomic analysis identifies a novel senescent fibroblast subtype associated with poor prognosis in acral melanoma.

BACKGROUND: Acral melanoma (AM) exhibits significant intratumoral heterogeneity, but its tumor microenvironment (TME) and immune regulation remain unclear. This study aims to dissect TME heterogeneity and establish a prognostic model based on key cell subpopulations. METHODS: We collected AM single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Unsupervised clustering, CellChat, and Scissor analysis were performed to characterize cellular heterogeneity, cell-cell communication, and prognosis-related cell subpopulations. Kaplan-Meier analysis was used to assess the prognostic value of key genes, which were further validated by multiplex immunohistochemistry (mIHC). RESULTS: In AM, Mel_C2, C7, and C9 with high SEMA6A and KIT expression were strongly linked to poor prognosis. We further identified a senescent fibroblast subpopulation (sCAF_CDKN2A) characterized by high fibroblast senescence signature (FSS) scores. Integrating Scissor analysis of fibroblast subtypes with bulk prognostic data, we identified COL3A1, VCAN, and KIT as prognosis-associated genes upregulated in poor-outcome-related fibroblast subsets. Cell-cell communication analysis revealed that sCAF_CDKN2A engages in an immunosuppressive network, interacting with regulatory T cells (Tregs) via MIF signaling and receiving signals from exhausted CD8+ T cells through PPIA-BSG interactions. Using transcription factor expression patterns from these fibroblast subtypes, we constructed a prognostic model that effectively stratified patients into distinct risk groups with significant differences in overall survival (OS). mIHC confirmed significantly higher protein levels of SEMA6A and COL3A1 in tumor tissues compared to matched normal tissues. CONCLUSIONS: We established a novel prognostic model for AM and identified sCAF_CDKN2A as an immunosuppressive senescent fibroblast subpopulation driving poor prognosis.

Acral melanoma↗

PubMed2026

Single-cell multiomics reveals exosome-mediated reprogramming and clonotypic remodeling of T cells in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive and immunogenic subtype lacking targeted therapies. While tumor-derived exosomes are known to modulate immune function, their direct impact on human T cell plasticity and antigen specificity remains poorly defined. Here, we conducted a comprehensive single-cell multiomic analysis of primary human T cells exposed to exosomes derived from 17 genomically diverse TNBC cell lines and 35 patient samples. Integrating single-cell RNA-seq, V(D)J sequencing, non-coding RNA profiling, bulk and single-cell cytokine analyses, we uncovered conserved and subtype-specific immunomodulatory programs induced by TNBC exosomes. Exosome-treated T cells displayed skewing toward regulatory and dysfunctional phenotypes, including Th17-like, Treg, and PD-1⁺/PD-L1⁺ Tfh cells. Functional profiling revealed suppression of early activation markers and cytokine responses, alongside selective preservation of cytotoxic features in γδ T and NKT subsets. Transcriptomic and miRNA network analyses demonstrated widespread downregulation of immune effector genes (e.g., HBEGF and TNFSF9) mediated by exosome-delivered regulatory miRNAs (has-miR-98-5p). Notably, exosome-stimulated T cells displayed distinct clonotypic expansions, characterized by the emergence of five tumor-specific γδ TCR clonotypes and 30 unique αβ TCR CDR3 sequences that were absent in mock-treated controls, underscoring the role of exosomes in shaping TCR repertoire dynamics.

Humans↗

PubMed2026

Predicting gene-specific regulation with transcriptomic and epigenetic single-cell data.

MOTIVATION: Analysis of single cell ATAC-seq and RNA-seq data has allowed to gain unprecedented insights into gene regulation by allowing to define cell type-specific regulatory regions and their effects on gene expression. While powerful, such analysis is challenging due to the inherent sparsity of single cell data. RESULTS: We present a new approach, MetaFR, to learn gene-specific models that link open-chromatin variation from scATAC-seq data to gene expression from scRNA-seq. Using efficient regression trees, we illustrate that accurate expression prediction models can be learned on the single-cell or meta-cell level. Validation was done using fine-mapped eQTLs. Meta-cell models were found to outperform single-cell models for most genes. Comparison to the SOTA method SCARlink revealed advantages of MetaFR in terms of runtime and prediction performance. MetaFR thus allows time-efficient analysis and obtains reliable models of gene expression prediction, which can be used to study gene regulation in any organism for which scRNA-seq and scATAC-seq data is available. AVAILABILITY AND IMPLEMENTATION: MetaFR is available under https://github.com/SchulzLab/MetaFR.

Single-Cell Analysis↗

PubMed2026

ARCADIA reveals spatially dependent transcriptional programs through integration of scRNA-seq and spatial proteomics.

MOTIVATION: Cellular states are strongly influenced by spatial context, but single-cell RNA sequencing (scRNA-seq) loses information about local tissue organization, while spatial proteomic assays capture limited marker panels that constrain transcriptomic inference. Integrating these modalities can elucidate how spatial niches shape transcriptional programs, yet existing approaches depend on either feature-level correspondence such as gene-protein linkage or cell-level barcode pairing, which is often unavailable. RESULTS: We present ARCADIA (ARchetype-based Clustering and Alignment with Dual Integrative Autoencoders), a generative framework for cross-modal integration that operates without cell barcode pairing and does not assume direct feature-to-feature correspondence. ARCADIA identifies modality-specific archetypes, that is, convex combinations of cells representing extreme phenotypic states, and aligns these anchors across modalities by minimizing the discrepancy between their cell-type composition profiles. The aligned archetypes define a shared coordinate system that anchors dual variational autoencoders (VAEs) trained with cross-modal geometric regularization, preserving archetype structure and spatial neighborhood information while enabling bidirectional translation between modalities. On semi-synthetic CITE-seq data, ARCADIA outperforms existing weak-linkage methods. Applied to independent human tonsil scRNA-seq and CODEX data, ARCADIA reconstructs known tissue architecture and reveals spatially dependent transcriptional programs linking B-cell maturation and T-cell activation or exhaustion to microenvironmental niches. AVAILABILITY AND IMPLEMENTATION: Source code is accessible at https://github.com/azizilab/ARCADIA_public. Reproducibility scripts and data are available at https://github.com/azizilab/arcadia_reproducibility.

Proteomics↗

PubMed2026

The Small Noncoding RNA, RsaC, Is Essential for Staphylococcus aureus Virulence.

BACKGROUND: Bacterial small noncoding RNAs (sRNAs) play critical roles in virulence, stress adaptation, and host-pathogen interactions. Transcriptomic analyses during infection can help reveal pathogen-derived sRNAs required for pathogenesis, providing valuable insights for the development of novel therapeutic strategies. However, the low abundance of pathogen biomass within the host tissues poses a significant challenge for such analyses. METHODS: We employed 2-step cell disruption to enrich Staphylococcus aureus cells from infected mouse organs and conducted RNA sequencing (RNA-seq) analysis to examine staphylococcal sRNAs expressed during infection. qRT-PCR was used to confirm the gene expression. A knockout mutant of highly expressed sRNA, RsaC, was generated, and RNA-seq under in vivo as well as in vitro aerobic and anaerobic conditions were compared between the wild-type and ΔrsaC strains. Virulence of S. aureus was assessed using both mouse and silkworm survival assays. RESULTS: We identified RsaC as one of the most highly expressed sRNAs in mouse organs with consistent increment over time postinfection. Through gene disruption and complementation, we demonstrated that RsaC is an independent virulence determinant required for full pathogenicity of S. aureus in a murine infection model. In addition, RsaC influenced gene expression in response to oxygen availability and host-associated stress. Further analysis revealed that mutation of 2 genes downregulated in ΔrsaC in vivo, NWMN_RS03420 (sodium: proton antiporter) and NWMN_RS12015 (hypothetical protein), reduced S. aureus virulence in a silkworm model. CONCLUSIONS: These findings identify RsaC as a novel independent virulence determinant that supports S. aureus adaptation within the host.

Animals↗

PubMed2026

Trichoderma reesei Nsd3 transcription factor: pleiotropic roles in development, stress response, secondary metabolism, and cellulase production.

Trichoderma reesei is known for its ability to secrete high amounts of cellulases, enzymes of fundamental importance in generating products from lignocellulosic biomass. Diverse signaling pathways and transcription factors (TFs) control the cellulolytic repertoire in T. reesei to ensure correct adaptation to the environment. Here, we analyzed RNA-Seq data and identified a new potential regulator of cellulase production in T. reesei: a novel TF named Nsd3, a homolog of NsdC from Aspergilli. Deletion of nsd3 reduced vegetative growth and conidiation on solid medium. Phenotypic characterization of the Δnsd3 strain showed that it is more sensitive to osmotic stress, but more resistant to cell wall and oxidative stresses. Our results showed that Nsd3 is a repressor of cellulase expression by directly regulating key genes in the cellulolytic pathway, an unreported role for this TF in fungi. Loss of nsd3 leads to a faster and more robust induction of cellulolytic genes, and higher cellulase and hemicellulase activities. Transcriptional profiling by RNA-Seq, chromatin accessibility profiling by ATAC-Seq, and protein-DNA interaction assays showed that sugar transporters are important targets of Nsd3 during cellulase expression regulation. Combined with microscopy and gene expression analyses, the ATAC-Seq data also highlighted Nsd3 as a central regulator of cell wall remodeling and organization. Furthermore, the transcriptomics also showed that Nsd3 regulates genes involved in secondary metabolism. These results showed that Nsd3 regulates several physiological processes and provide novel insights into the regulatory system of cellulases in T. reesei that can be used in the design of high-performance strains for biorefinery.IMPORTANCETrichoderma reesei is a key player in the production of hydrolytic enzymes for the degradation of lignocellulose biomass, and transcription factors are important targets for genetic engineering to construct cellulase-hyperproducing strains. Here, we identified the transcription factor Nsd3 and characterized its role as a regulator of cellulase production in T. reesei. We applied two powerful genomics methods (transcriptome sequencing and chromatin accessibility sequencing) to unravel the global role of Nsd3 and its regulatory mechanism. Nsd3 participates in various biological processes in T. reesei, including cell wall remodeling, calcium metabolism, and secondary metabolism, in addition to regulating the expression of sugar transporters. Protein-DNA interaction assays demonstrate that Nsd3 acts through important genes to regulate cellulase expression, including ace4, crt1, stp1, and cel1b. Our study provides mechanistic insights about how Nsd3 regulates diverse physiological processes in T. reesei. This work also applied ATAC-Seq for the first time to study chromatin accessibility in T. reesei.

ATAC-Seq↗

PubMed2026

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BACKGROUND: Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n = 150) and Latin American (n = 96) ancestries. RESULTS: Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R2 ≥ 0.93 for eQTL effect sizes and R2 ≥ 0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 genes with high-confidence (posterior probability > 90%) candidate regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. CONCLUSIONS: These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations. More broadly, this study highlights the value of paired multi-omic datasets from diverse cohorts for interpreting disease-associated genetic variation.

Humans↗

PubMed2026

BHLHE40 and ChREBP associate with hepatic enhancer clusters containing PPARα, RXRα, and HNF4 nuclear receptors.

BHLHE40/DEC1 is a basic helix-loop-helix transcription factor (TF) that regulates circadian rhythm and T-cell responses. In hepatocytes, its function and interplay with other TFs are poorly understood. Employing a genome-wide approach, we show that its genomic binding strongly overlapped with that of carbohydrate response-element binding protein, a sugar-sensing TF and known inducer of BHLHE40 expression. Transcriptomic analysis of primary mouse hepatocytes revealed reduced expression of genes involved in genomic stability on Bhlhe40 knockdown by siRNA. Bhlhe40 depletion potentiated fructose responsiveness of genes involved in cell-cycle regulation. Strikingly, genomic binding of BHLHE40 extensively overlapped with enhancers occupied by PPARα, RXRα, and HNF4 nuclear receptors and BHLHE40 fine-tuned the expression of PPARα target genes. Using HEK293 cells, we further observed that BHLHE40 physically interacted with RXRα and PPARα cofactors. Collectively, our data suggest that through cooperation with carbohydrate response-element binding protein and nuclear receptors, BHLHE40 is a central regulator of hepatic gene expression with potential to integrate inputs from nutrient signals contributing to the metabolic flexibility of the liver.

Animals↗