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PubMed2026

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans↗

PubMed2026

Cell-of-origin Discovery in Infant Leukemia through Integration of 3D Models and Patient Transcriptomic Data.

Pediatric hematological malignancies remain challenging to investigate and model due to the age group-specificity of certain genetic abnormalities. In utero origin has been demonstrated for a subset of pediatric leukemias, placing their respective cell of origin (CoO) during embryonic development. We recently reported a 3D hemogenic gastruloid (haemGx) model of embryonic blood formation derived from mouse embryonic stem cells, resolving the spatio-temporal complexity of developmental hematopoiesis. Importantly, it allows genetic engineering to introduce disease-relevant mutations. Using haemGx, we modeled the most common acute myeloid leukemia exclusive to infants (infAML), subtype t(7;12)(q36;p13), which arises in utero and is characterized by MNX1 overexpression. Here, we detail a method to define susceptibility to specific mutations that integrate phenotypic and transcriptional changes in the haemGx system and compares them with patient data. By proxy of our MNX1-overexpression haemGx, we show a pipeline from cell engineering to downstream analyses of leukemogenic potential. In particular, we focus on the clinical relevance of the model by integrating single-cell and/or bulk RNA sequencing from the haemGx platform with patient data to extract cellular composition and temporal placement of the putative CoO. This method is adaptable to the introduction of other oncogenic mutations, chromosomal rearrangements, or epigenetic modifications, as well as to chemical perturbations, including drug vulnerability and growth factor dependence. This flexibility allows for broad application across diverse disease contexts, enabling mechanistic dissection of how specific alterations disrupt early developmental trajectories with clinical relevance.

Humans↗

PubMed2026

Early oligodendrocyte dysfunction signature in Alzheimer's disease: Insights from DNA methylomics and transcriptomics.

Much research into the aetiology of Alzheimer's disease (AD) has focused on neuronal cell types, while studies on the contribution of glial cells, particularly oligodendrocytes (OLGs), are only starting to emerge. Altered brain DNA methylation, an epigenetic modification that provides the interplay between genetics and environmental cues to tightly regulate gene expression, is well documented in AD. Yet, cell-type-specific investigations remain limited. Here, we examine the role of DNA methylation and OLGs in AD, and how such changes may impact gene expression. We performed weighted-gene correlation network analysis (WGCNA) on multiple brain omics AD datasets across species: human DNA methylation data from 4 brain regions, human brain single-nuclei RNA sequencing data and mouse brain RNA sequencing data. We compared AD-associated network modules enriched for OLG genes across AD brain regions, as well as with other neurodegenerative disease DNA methylation datasets. We identified a DNA methylation signature associated with AD, enriched for OLGs, and preserved across brain regions representing early and late AD pathology stages. Genes within this signature showed altered expression in AD OLGs, confirming cell-type specificity and relevance to AD. This OLG signature was also preserved in transgenic mice with early Aβ pathology and in other neurodegenerative diseases without Aβ pathology. We reveal a consistent pattern of OLG dysfunction spanning early to late stages of AD, across DNA methylation and gene expression. Our findings highlight OLG-associated DNA methylation changes as important in AD pathogenesis, and possibly in other neurodegenerative diseases, opening new avenues for therapeutic development.

Alzheimer Disease↗

PubMed2024

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis.

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.

Humans↗

PubMed2025

Genome topology analysis and transcriptomics of human osteoclasts reveals enhancer-promoter interactions at loci for bone traits and diseases.

Genome-wide association studies (GWAS) relevant to osteoporosis have identified hundreds of loci; however, understanding how these variants influence the phenotype is complicated because most reside in non-coding DNA sequence that serves as transcriptional enhancers and repressors. To advance knowledge on these regulatory elements in osteoclasts (OCs), we performed Micro-C analysis, which informs on the genome topology of these cells and integrated the results with transcriptome and GWAS data to further define loci linked to BMD. Using blood cells isolated from 4 healthy participants aged 31-61 yr, we cultured OC in vitro and generated a Micro-C chromatin conformation capture dataset. We characterized chromatin loops (CLs) in OC from among more than 69 million chromatin interactions identified in the genome. Of the CL identified in OC, >16 000 were unique compared to precursor cells. When sentinel single nucleotide polymorphisms from osteoporosis and bone-related GWAS and those in linkage disequilibrium at r 2 > 0.6 were mapped to CL for OC, 12 588 of these variants were observed within chromatin contact regions. Notable in differential gene ontology enrichment analyses of the topology data for OC and precursors were pathways regulating pluripotency of stem cells, Wnt signaling, nucleotide-binding oligomerization domain (NOD)-like receptor signaling and chemokine signaling. These data, in combination with other 3D genome architecture and epigenetic data (eg, histone modifications and chromatin accessibility), will be useful in modeling to predict genome-wide, which enhancers regulate which genes in OC. This data will therefore also be informative for resolving GWAS hits. In conclusion, we have generated a high-resolution genome topology dataset for human OC and have used this to identify CLs relevant to studies of the genetics of osteoporosis. This data will serve as a powerful resource to inform future functional studies of OC biology.

BMD↗

PubMed2026

Translating single-cell RNA sequencing into monocyte direct leukocyte subpopulation-transcript abundance assay ratio-based biomarkers (IFI27/PSAP or IFI27/CTSS) for clinical detection of viral infection.

A rapid method for triaging febrile patients by aetiology (e.g., viral or bacterial infection) using gene expression in peripheral blood (PB) is an intensively researched area. However, gene expression in blood represents a composite sum of gene expression of all the component cell types present in the sample. As a result, numerous genes are measured in most proposed signatures. Herein, we propose a simple ratio-based biomarker (RBB) called direct leukocyte subpopulation-transcript abundance assay (DIRECT LS-TA) that recapitulates gene expressions of a single cell type in PB (i.e., monocytes). Based on single-cell RNA sequencing (scRNAseq) data and bulk expression data, IFI27 and SIGLEC1 are found as interferon-stimulated genes (ISGs) predominantly expressed by monocytes. The DIRECT LS-TA method can use a simple ratio of two genes measured in PB as an RBB to represent the target gene expression in monocytes without the need for monocyte purification. Both scRNAseq and bulk RNA sequencing datasets were used to evaluate the correlation between ISG expression in monocytes and PB, with a particular focus on monocyte expression of IFI27. An iceberg plot of bulk transcriptome data was used to identify genes that were predominantly expressed by monocytes in PB. DIRECT LS-TA RBBs of the three genes (IFI27, IFI44L and SIGLEC1) were evaluated by group-wise comparison, receiver operating characteristic and meta-analysis. In addition, the conventional interferon (IFN) score was evaluated for comparison of diagnostic performance. In viral infection datasets, DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) was most intensely activated (p value by t test <1e-9) and had the best area under the curve (0.94) among the three potential monocyte ISGs analysed. DIRECT LS-TA SIGLEC1 was also another monocyte biomarker but showed a lower activation (p<9e-5). IFI27/PSAP showed better diagnostic performance than the conventional IFN score. On the other hand, IFI44L was not a predominant monocyte expression gene. DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) measured in PB was the best biomarker of viral infection and IFN activation among ISGs predominantly expressed by monocytes. It performed even better than the conventional IFN score which required quantification of eight genes. The results suggest that DIRECT LS-TA of IFI27 is a monocyte-informative biomarker which is easy to determine in PB without the need for cell sorting.

Humans↗

PubMed2001

Discovering altered genomic expression patterns in heart: transcriptome determination by serial analysis of gene expression.

The development of cardiovascular diseases such as heart failure involve functional changes that are beneficial short-term, but may be fatal long-term. Current therapeutic approaches are tailored to limit progression of a disease and to maintain quality of life. At a molecular level, these disease processes involve quantitative and qualitative changes in gene expression. Although some changes in mRNA abundance may not have direct protein correlates, analysis of all the mRNAs present in a cell population (the cells transcriptome) has become a focal point of genomic research. The aim is to provide information about the dynamics of total genome expression in response to environmental changes and point to candidate genes responsible for the cascade of events that result in a disease state. One way of performing these analyses utilizes the technique of Serial Analysis of Gene Expression (SAGE). This method evaluates thousands of expressed transcripts both quantitatively and qualitatively in a single assay. In the first of two reviews on transcriptome analysis, we describe the current state of genomic research for determination of the transcriptome by Serial Analysis of Gene Expression, present the first limited SAGE analysis of rodent heart gene expression, and discuss how results generated with this approach can be applied to the study and treatment of cardiovascular diseases.

Cardiovascular Diseases↗

PubMed2026

Spatially Contextualized Integrative Genomics Highlights Neuronal and Glial Regulatory Programs in Low Back Pain.

PURPOSE: Low back pain (LBP) is a heterogeneous pain condition with a measurable genetic contribution, but the genes, brain cell types, and spatial tissue contexts through which inherited risk is expressed remain unclear. We aimed to define cell-type-specific and spatially contextualized genetic mechanisms underlying LBP. METHODS: FinnGen R12 LBP GWAS summary statistics (42,521 cases and 353,224 controls) were integrated with brain single-nuclei eQTL data across eight major brain cell classes. We evaluated genome-wide polygenic signal using LDSC, prioritized genes using MAGMA and PoPS, and performed brain cell-type-specific eQTL-anchored Mendelian randomization, primarily based on single-instrument Wald ratio estimates, followed by Bayesian colocalization. Spatial genetic mapping was conducted using gsMap in an E16.5 murine embryonic atlas and two adult human lumbar spinal cord Visium sections. Selected candidates were assessed by RT-qPCR in neuronal-like and astroglial-like inflammatory cell models. RESULTS: LDSC supported interpretable polygenic signal for LBP. MAGMA and PoPS showed partial gene-level convergence, with TCF4 and TMEFF2 supported by both approaches. Across 1641 tested gene-cell type exposures, significant eQTL-anchored MR associations were concentrated in excitatory neurons, oligodendrocytes, inhibitory neurons, and astrocytes. Integrated eQTL-anchored MR, colocalization, and gene-prioritization evidence highlighted CLEC18A, QPRT, and GMPPB as higher-priority non-MHC candidates with moderate, but not strong, colocalization support. gsMap localized LBP-associated enrichment to neuroaxis-related embryonic regions, including brain, spinal cord, sympathetic nerve, and dorsal root ganglion, and to neuronal-like niches in adult lumbar spinal cord. RT-qPCR showed model-dependent expression changes, with QPRT and LGI4 preferentially responsive in neuronal-like SH-SY5Y cells and GMPPB and DPYSL5 responsive in astroglial-like U251 cells. CONCLUSION: These findings support neuronal and glial regulatory programs as plausible contributors to LBP genetic susceptibility and highlight CLEC18A, QPRT, and GMPPB as higher-priority non-MHC candidates with moderate colocalization support. The results provide a spatially contextualized framework for candidate prioritization in LBP, while emphasizing the need for larger cell-type-specific eQTL resources and functional validation before therapeutic or mechanistic conclusions can be drawn.

Mendelian randomization↗

PubMedDate not supplied

Multilineage gene expression in human bone marrow stromal cells as evidenced by single-cell microarray analysis.

The nonhematopoietic stromal cells of the bone marrow are critical for the development of hematopoietic stem cells into functionally competent blood cells. This study addresses the question of whether bone marrow stromal cell cultures in the Dexter system propagate multiple different mesenchymal stromal cell types or one stromal cell type that expresses multiple phenotypes. Results show that isolated single stromal cells simultaneously express transcripts associated with osteoblast, fibroblast, muscle, and adipocyte differentiation. Furthermore, isolated single stromal cells simultaneously express transcripts characteristic of epithelial cells, endothelial cells, and neural/glial cells. Isolated single stromal cells also express transcripts for CD45, CD19, CD10, CD79a, and representative proto-oncogenes and transcription factors, which are typically associated with normal and neoplastic hematopoietic cells. These findings suggest that the nonhematopoietic mesenchymal cells and the hematopoietic B-lymphocytes have a common progenitor. This is consistent with the idea that progenitor cells express genes that are characteristic of the multiple lineage paths that such cells may be capable of adopting. This study demonstrates the technical feasibility of transcriptome analysis of individual primary cell-culture grown stromal cells and supports the concept that bone marrow stromal cells are relatively homogeneous and show a phenotypic signature of potential multilineage differentiation capacity.

Adult↗

PubMed2025

Multi-ancestry genome-wide and transcriptome-wide association analyses identified new risk loci and genes for inflammatory bowel disease.

To advance genetic understanding of inflammatory bowel disease (IBD), we conducted genome-wide association meta-analyses of 63,415 IBD cases of European and East Asian descendants and identified 90 previously unknown risk loci. Integrating multi-ancestry transcriptome-wide association studies (TWAS), cell type-specific TWAS, alternative splicing (AS-WAS), and alternative polyadenylation (APA-WAS) analyses using RNA-seq data from normal colon tissues of 707 European and 364 East Asian individuals, we uncovered 506 high-confidence IBD risk genes, including 384 not previously reported. These genes converge on immune regulation, microbial interaction, and other pathways central to IBD pathogenesis, with over half showing transcriptional dysregulation supported by single-cell and spatial omics analyses. Notably, 46 risk genes are targeted by 225 drugs that have been approved or in Phase II/III trials, including sulfasalazine already used in IBD therapy. Our study findings deepen the understanding of IBD genetics and support the development of precision medicine for its prevention and treatment.

GWAS↗

PubMed2026

Monocarboxylate Transporter 2 (MCT2) Reduction Is Associated with Increased Lung Tumor Growth and Alterations in the Immune Microenvironment in a Subcutaneous Tumor Model.

Monocarboxylate transporter 2 (MCT2; SLC16A7) is a high-affinity pyruvate transporter implicated in cancer metabolism. However, its role in lung cancer progression and the tumor microenvironment remains unclear. This study examined the effects of MCT2 reduction on tumor growth and cell-type-specific transcriptional changes within the tumor microenvironment. MCT2 loxP/loxP mice were crossed with mCre-Tg mice, and MCT2 deletion was induced by tamoxifen. Control (CO) mice received vehicle treatment. TC1 cells (100,000 cells/mouse) were injected subcutaneously, and tumors were harvested after 24 days. Single-nucleus RNA sequencing (snRNA-seq) was performed on isolated tumor nuclei (4000 nuclei/sample; n = 3 per group) using the 10x Genomics Chromium platform. Data were processed with Cell Ranger v3.0.2 and Seurat v5.2.1, followed by differential expression and pathway enrichment analyses integrated with macrophage bulk RNA-seq data. Tumors in mice with systemic MCT2 reduction grew significantly faster than those in control mice, demonstrating an association between host MCT2 reduction and increased tumor growth. Transcriptomic analysis generated high-quality profiles from 6864 CO and 10,055 KO nuclei. Clustering identified 12 cellular populations and cell types. MCT2 reduction altered pathways involved in glycolysis, the tricarboxylic acid cycle, oxidative phosphorylation, and fatty acid metabolism across multiple populations. Macrophages showed prominent transcriptional changes, including enrichment of MAPK, PI3K-Akt, IgSF-CAM, ECM, and cytokine-cytokine signaling pathways. These findings were supported by macrophage bulk RNA-seq data. Systemic MCT2 reduction was associated with increased tumor growth and broad transcriptional alterations within the tumor micro-environment. Differences in metabolic and immune-related transcriptional programs, particularly in macrophages, identify potential mechanisms associated with tumor progression that warrant further functional investigation.

Animals↗

PubMed2026

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on characterizing oocytes and ovarian tissue composition, as well as understanding the molecular mechanisms that guide ovarian function throughout its lifecycle. High-throughput omics technologies have enabled the characterization of different molecular layers, leading to substantial advances in our understanding of their complex dynamics. However, not all molecular aspects are studied equally, and studies examining the same modalities often show inconsistencies, underscoring the need for data standardization and highlighting the potential for using transformative artificial intelligence and machine-learning (AI/ML) methods for ovary studies. OBJECTIVE AND RATIONALE: This study aims to evaluate how multi-omic studies have advanced our understanding of the ovarian lifecycle from fetal development to postmenopause. We systematically reviewed published studies that have investigated molecular/omic layers, including the genome, methylome, transcriptome, and proteome throughout ovarian development and aging. Our analysis identified key molecular and cellular patterns, highlighted inconsistencies across studies and addressed gaps in data analysis, interpretation, and reproducibility to guide future research. SEARCH METHODS: We conducted a systematic literature search of Medline (PubMed), Embase (Ovid), and Web of Science Core Collection (Clarivate) using a combination of controlled and free text terms for human ovary, oogenesis, folliculogenesis, ovary development and (epi)genome, transcriptome, proteome, and multi-omic mechanisms to find relevant articles published before August 2025. To focus the scope of the current review, studies of domesticated and farm animals, rodents and other model organisms, non-human primates, as well as those examining various human ovarian pathologies were excluded. OUTCOMES: The search identified 23 546 studies for screening, of which 637 full-text studies were assessed for eligibility. Subsequently, we extracted data from 121 studies. Most studies analyzed the transcriptome of oocytes, granulosa cells, and ovarian tissue from reproductive-age individuals (n = 91), with fewer studies examining samples from individuals of advanced reproductive age (n = 45) and fetal (n = 16) samples. Transcriptome analyses were most common (n = 103, 85%), followed by proteome (n = 19, 16%) and epigenome (n = 14, 12%) studies. We found substantial variation in how studies defined and reported participants' groups as well as in their sequencing technologies and data analysis methods, with a lack of standardized reporting of background clinical information, data analysis methods, and pipeline details. The key findings underscore the prevailing consensus on genes defining major ovarian cell types and their roles throughout the ovarian lifespan, from prenatal development to postmenopausal transformation. This review highlighted the underrepresentation of certain patient groups, particularly prepubertal and peri-/postmenopausal individuals, among researched populations, due to obvious clinical and ethical reasons. WIDER IMPLICATIONS: This scoping review offers a comprehensive overview and benchmark of the current state of high-throughput omics-based research on ovarian cellular composition and molecular dynamics. To address these shortcomings, we propose general recommendations for multi-omics ovary studies and emphasize the necessity for more thorough multi-omic data integration by effectively applying novel AI/ML approaches. They can potentially improve the quality of multi-omics analyses at both single-cell and tissue levels despite limited sample sizes and enable integration of molecular profiling data with clinical and radiology datasets, enabling a more comprehensive understanding of ovarian biology. Such advancements can enhance reproducibility of research findings and guide future research to deepen our understanding of ovarian biology and ultimately support the development of medical technologies for better preserving fertility and alleviating infertility. REGISTRATION NUMBER: A protocol was published a priori on the Open Science Framework (https://osf.io/z38gb/).

Female↗

PubMed2026

Integrative transcriptomic, spatial and functional-genomic analysis identifies a UFMylation-related vascular-stromal program and prioritizes WWTR1 in glioblastoma.

Glioblastoma (GBM) contains spatially organized stress-adaptive and vascular niches. Because transcript abundance does not measure UFM1 conjugation, we asked whether a UFMylation-related transcriptional axis identifies a reproducible tissue program and alters candidate prioritization. In 518 unique primary TCGA-GBM tumors profiled on the Affymetrix HT Human Genome U133A array, weighted gene co-expression network analysis of 8,000 variable genes yielded 12 modules. The 278-gene green module ranked first across nine prespecified traits (mean |r|=0.637). Direct overlap comprised 1/3 measurable UFMylation-core, 5/19 ER-stress/UPR, and 2/15 proteostasis genes; after excluding overlapping genes, correlations with the green eigengene remained significant (r = 0.373, 0.831, 0.639, and 0.699 for UFMylation-core, ER-stress/UPR, proteostasis, and composite scores, respectively). The green score was associated with overall survival per standard-deviation increase (HR 1.17, 95% CI 1.07-1.28), although clinical adjustment attenuated the estimate. In a 10-sample single-cell dataset, sample-level scores were higher in pericytes and endothelial cells than in malignant cells. Donor-aware IvyGAP analysis supported regional organization, whereas one Visium section showed stronger concordance with ER-stress/UPR and mesenchymal scores than with the UFMylation-core score. CellChat indicated pathway-selective rather than global remodeling of inferred vascular communication. Layer ablation moved WWTR1 from rank 48 using WGCNA alone to rank 4 overall and rank 1 among non-common-essential genes after cross-platform integration. These findings define an ER-stress/mesenchymal-weighted, UFMylation-related vascular-stromal transcriptional association and nominate WWTR1 for experimental testing.

Humans↗

PubMed2026

Reduced R-loop abundance at proinflammatory loci: a shared epigenetic mechanism in inflammatory and metabolic diseases.

INTRODUCTION: R-loops, RNA-DNA hybrid structures with a displaced single-stranded DNA loop, are key regulators of transcriptional control, chromatin architecture, and genome stability and have emerging roles in inflammatory signaling. However, the relationship between R-loop abundance and strongly modulated inflammatory effector genes in metabolic inflammation and influenza virus infection remains underexplored. METHODS: We performed a locus-centric integrative analysis combining robust differentially expressed genes (DEGs) from multiple inflammatory and infection-related murine and human transcriptomic disease models with experimentally validated multi-cell R-loop annotations from the reference atlas RLoopBase. Our correlation framework evaluated the directional relationship between R-loop abundance and inflammatory gene expression rather than assuming disease-sample-matched R-loop measurements. We further analyzed R-loop regulatory proteins, NRF2-associated R-loop regulators, and overlaps between R-loop regulators and CRISPRi-identified mitochondrial and cellular reactive oxygen species (ROS) regulators. RESULTS: In angiotensin II-infused apolipoprotein E-deficient (ApoE-/-) mice, a model of abdominal aortic aneurysm (AAA), genomic regions encoding the top significantly upregulated genes exhibited significantly fewer R-loops than those encoding downregulated genes at days 14 and 28. Similarly, in atherosclerotic ApoE-/- mice fed a high-fat diet for 32 and 78 weeks, upregulated genes were associated with fewer R-loops than downregulated genes. Reduced R-loop abundance was also observed in genomic regions encoding the top significantly upregulated genes in liver tissues from patients with non-alcoholic steatohepatitis (NASH), as well as in monosodium urate (MSU)-stimulated lymphatic endothelial cells (LECs) and influenza virus-infected human umbilical vein endothelial cells (HUVECs). R-loop regulatory proteins upregulated during metabolic inflammation were enriched in immune and inflammatory pathways. NRF2 was identified as a regulator of 27 R-loop regulatory proteins, including 10 positively and 17 negatively regulated proteins. Furthermore, 54 R-loop regulatory proteins overlapped with CRISPRi-identified mitochondrial and cellular ROS regulators, suggesting potential reciprocal regulation between R-loop homeostasis and ROS signaling. Disease-associated changes in pro-ROS and anti-ROS R-loop regulatory proteins further linked R-loop regulation to inflammatory and oxidative stress pathways. DISCUSSION: These findings identify reduced R-loop abundance at genomic regions encoding strongly upregulated inflammatory genes as a shared feature across multiple models of metabolic inflammation and influenza virus infection. The results further suggest that immune-associated R-loop regulatory proteins and the NRF2-ROS axis may contribute to R-loop remodeling during inflammatory disease. This integrative framework provides new insight into the potential role of R-loops and ROS-sensitive R-loop regulators in inflammatory and metabolic diseases and identifies candidate pathways for future mechanistic investigation and therapeutic targeting.

R-loop regulatory proteins↗

PubMed2024

Adaptation for Staphylococcus aureus to hosts via insertion mutation in the accessory gene regulator agrC gene: decreased virulence and enhanced persistence capacity.

UNLABELLED: Staphylococcus aureus is an important human pathogen due to its vast array of virulence factors regulated by multiple regulatory mechanisms, including the accessory gene regulator. In this study, two S. aureus strains were simultaneously isolated from the blood of a febrile patient, belonging to the same clone, designated as 23H with a complete hemolytic phenotype, and 23B, exhibiting an incomplete hemolytic phenotype. The genomic comparison between strains 23B and 23H revealed that 23B had a single adenine base insertion at position 923 in the agrC gene, leading to a functional loss of the encoded AgrC. Experimental findings showed that strain 23B had decreased hemolytic activity, lower cytotoxicity against human alveolar epithelial A549 cells and in the Galleria mellonella model, and a reduced ability to survive intracellularly after infecting macrophages, in comparison to 23H. Conversely, 23B exhibited enhanced biofilm formation, greater adherence to A549 cells, and increased persistence in the face of vancomycin and daptomycin treatment. Transcriptomic analysis revealed that 23B upregulated surface protein-encoding genes while simultaneously reducing the expression levels of virulence factors, highlighting the intricate regulatory adjustments facilitating its persistence and reducing pathogenic potential. ATP assay results indicated that 23B maintained elevated ATP levels during the exponential phase yet exhibited reduced levels in the stationary phase when compared with 23H. Our findings suggested that the mutation in the agrC gene of S. aureus results in diminished virulence but markedly enhances persistence. This mutated strain warrants clinical attention because it may lead to treatment failures and persist in patients. IMPORTANCE: In clinical antimicrobial therapy, bacterial strains often develop resistance to antimicrobial agents. Additionally, mutations in their gene regulatory networks can increase their persistence, especially in immunocompromised patients. This study identified an insertion mutation in the accessory gene regulator, agrC gene, carried by a Staphylococcus aureus strain isolated from the blood of a febrile patient, leading to the functional loss of AgrC. Further research revealed that despite the reduced virulence of the mutated strain, it significantly bolstered the capacity to adapt and endure within the host during prolonged infections. This was evidenced by increased adhesion and biofilm formation capabilities, development of antimicrobial tolerance, and decreased ATP levels linked to persistence. Therefore, monitoring these mutations in S. aureus is crucial clinically, as they can complicate treatment strategies.

Staphylococcus aureus↗

PubMed2026

Genetics-Informed Mapping Identifies a CRIM1-Associated Endocardial Inflammatory Remodeling State in Acute Myocardial Infarction.

BACKGROUND Acute myocardial infarction (AMI) reflects inherited susceptibility and inflammatory remodeling, but the cellular contexts linking genetic risk to disease remain unclear. MATERIAL AND METHODS We integrated a meta-transcriptome-wide association study (TWAS) with a human cardiac single-nucleus RNA-sequencing atlas contained 11 individuals (5 AMI and 6 donor) to identify genetics-informed cellular programs. Composite program states were defined by global score quartiles. A fixed 5-gene panel was evaluated for nucleus-level endocardial low-transcriptional-state (Endo_LTS) vs endocardial high-transcriptional-state (Endo_HTS) discrimination within the AMI endocardium using 5-fold leave-1-patient-out cross-validation. Functional follow-up used CRIM1 silencing in hypoxia-treated human induced pluripotent stem cell (hiPSC)-derived endocardial endothelial-like cells and complementary peripheral blood analyses. RESULTS The endocardium exhibited the most prominent infarction-associated increase in TWAS-anchored program activity, with expansion of program-high states and higher CytoTRACE scores. A consensus 5-gene panel (RPS8, PLEC, CFDP1, CRIM1, TNS2) was identified. Among 2163 AMI endocardial nuclei from 5 patients, the state classifier included 364 Endo_LTS and 751 Endo_HTS nuclei; 1048 Endo_MTS nuclei were excluded. Pooled out-of-fold ROC-AUCs ranged from 0.665 to 0.831. The panel also showed discriminatory value in an independent peripheral-blood AMI-vs-control cohort. CRIM1 was prioritized as a candidate linked to the remodeling program. CRIM1 silencing attenuated ACTA2/alpha-SMA, vimentin, LDHA, CCL2, and VEGFA and partially restored CD31, whereas TGF-ß remained elevated. CONCLUSIONS These findings identify a genetics-informed endocardial inflammatory remodeling state in AMI and define a 5-gene surrogate of its activated state. CRIM1 is prioritized as a candidate linked to selected inflammatory, metabolic, and structural outputs. Persistent TGF-b elevation after CRIM1 silencing argues against a simple linear regulatory model and indicates that further mechanistic validation is required.

Humans↗

PubMed2026

Recurrent reversible mutations at gaf1 driving metastable TORC1 inhibitor resistance in fission yeast.

Metastable phenotypic inheritance is often attributed to epigenetic mechanisms, but reversible genetic alterations can produce similar instability. Here, we investigated the basis of unstable resistance to TORC1 inhibitor (rapamycin plus caffeine) in Schizosaccharomyces pombe. Six independent, metastable resistant mutants were isolated. Genetic mapping positioned the causal lesion to a single Mendelian locus, which sequencing identified as gaf1, encoding a GATA transcription factor and a key negative regulator of growth downstream of TORC1. In each mutant, distinct loss-of-function mutations (insertions, deletions, or point mutations) were found in gaf1 in the resistant state, and these mutations precisely reverted to the wild-type sequence upon loss of resistance. Restoring the wild-type gaf1 allele abolished resistance, indicating that reversible genetic disruption of gaf1 is both necessary and sufficient for the metastable phenotype. Furthermore, strong resistance in several strains from a genome-wide deletion library was due to secondary, inactivating mutations in gaf1, underscoring its role as a recurrent adaptive target under rapamycin plus caffeine treatment. Mechanistically, gaf1 inactivation established a distinct basal transcriptome and pronounced derepression of translation and metabolic programs upon drug treatment. While rapamycin plus caffeine triggered extensive chromatin remodeling and H3K9 methylation contributed partially to resistance, these epigenetic changes were most consistent with a downstream modifying layer. Our study shows that metastable drug resistance in fission yeast is predominantly associated with recurrent, reversible genetic inactivation of the central transcriptional regulator gaf1, demonstrating how rapidly reversible genetic switches can drive adaptive evolution.IMPORTANCEDistinguishing between genetic and epigenetic inheritance is fundamental to understanding how cells adapt to environmental stress. In the fission yeast Schizosaccharomyces pombe, rapid and reversible drug resistance is often assumed to be driven by epigenetic switches that change gene activity without altering DNA. However, our study reveals that this instability can be caused by physical mutations in a single gene, gaf1, which acts as a genetic toggle. These mutations appear under drug pressure and precisely revert to the original sequence when the drug is removed. We also demonstrate that these spontaneous mutations can contaminate standard laboratory yeast collections, leading to potential misinterpretation of experimental data. These findings broaden our understanding of unstable inheritance and show that DNA sequences can be far more dynamic than previously recognized during rapid evolution and the development of drug resistance.

TORC1 signaling↗

PubMed2003

Laser-controlled microdissection of tissues opens a window of new opportunities.

Gene expression analysis using total RNA of bulk tissue usually cannot assign specific messages to particular cell types. Cell-specific RNA expression profiling, though, may be crucial for a better understanding ofthe role of each distinct cell type within a physiological or pathophysiological setting. RNA profiling based on laser-controlled microdissection (LCM) of defined cells of a tissue now provides a useful tool for studying molecular crosstalk between different cell types within a tissue. The LCM technique allows for efficient isolation of single cells with no or very low contamination of surrounding tissue components, simultaneously leaving the intracellular structure and molecules intact. In this review, different issues of the LCM technique and the RNA amplification procedure for microarray analysis are discussed. An exemplary summary of results obtained from gene profiling of epithelial and stromal cells from human prostate tumors is presented, demonstrating the power of LCM-based molecular analysis. Finally, we discuss the potential use of the LCM technique i) to study the transcriptome of distinct cells from formalin-fixed and paraffin-embedded tissues in subcellular RNA profiling and ii) high resolution proteomic and metabolistic studies.

Dissection↗