Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “transcriptomic”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22Linked to original sources
PubMed2025

Transcriptomic and enzymological evidence for plastid peptidoglycan synthesis in the gymnosperm Picea abies.

It is understood that a cyanobacterium was the progenitor of plastids and that the biosynthesis of cell wall peptidoglycan was lost during chloroplast evolution. However, accumulated data, especially from the moss Physcomitrium patens, suggest that peptidoglycan remains essential for plastid division in some land plants. A fundamental set of peptidoglycan biosynthesis (Mur) genes has been identified in the genomes of these land plants, while many angiosperms no longer encode some core Mur genes, including a bifunctional penicillin-binding protein (PBP). Ten incomplete Mur genes were previously identified in the genome of the gymnosperm Picea abies but these could be pseudogenes or encode proteins that have been repurposed. For instance, mutant albino maize and Arabidopsis seedlings possess a defective UDP-N-acetylmuramoyl-l-alanyl-d-glutamate--2,6-diaminopimelate ligase (MurE), an intact MurE ligase being essential for peptidoglycan synthesis. In this study, we isolated a full set of cDNAs for peptidoglycan biosynthesis from P. abies. GFP fusion proteins with either P. abies (Pa)MurE or PaPBP were detected in chloroplasts. Cross-species complementation assays with PaMurE in Arabidopsis albino MurE mutants and Physcomitrium MurE chloroplast division mutants showed that the gymnosperm MurE completely rescued both mutant phenotypes. Enzymatic assay of recombinant PaMurE proteins revealed they catalyze the same reaction performed by their bacterial MurE homologs. Moreover, the expression of the PaPbp cDNA partially rescued the giant chloroplast phenotype in the moss Pbp knockout line. These results are consistent with the operation of a functional Mur gene set in the Norway spruce genome.

Peptidoglycan↗
PubMed2026

Integrated transcriptomic and immunogenomic analysis unravels the immunological functions and prognostic landscape of WD repeat domain 76.

BackgroundWD Repeat Domain 76 (WDR76) plays a potential role in cellular regulation; however, its comprehensive landscape across human malignancies and its specific biological function in hepatocellular carcinoma (HCC) remain largely unexplored.MethodsWe conducted a systematic pan-cancer analysis utilizing multi-omics data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) atabases to evaluate WDR76 expression, subcellular localization, and its correlation with clinicopathologic features, genomic instability, and immune infiltration. Diagnostic and prognostic values were assessed via Receiver operating characteristic (ROC) and Kaplan-Meier analyses. Furthermore, the functional role of WDR76 in HCC was validated in vitro using Hep-3B and Huh7 cell lines through siRNA-mediated knockdown, followed by CCK-8, wound-healing, and transwell assays.ResultsWDR76 was significantly upregulated in the majority of tumor types, including LIHC, LUAD, and COAD, while exhibiting nuclear localization. Elevated WDR76 expression correlated with advanced tumor staging, metastasis, and poor clinical outcomes across multiple cohorts, particularly in ACC, KIRP, and LIHC. ROC analysis highlighted its exceptional diagnostic precision in cancers such as GBM and LIHC. Immunologically, WDR76 expression was intricately linked to immune cell infiltration, immune checkpoint markers, and genomic instability parameters, suggesting a role in shaping the tumor microenvironment. Drug sensitivity profiling revealed that high WDR76 levels correlate with resistance to specific chemotherapeutic agents. Experimentally, silencing WDR76 in HCC cells significantly suppressed cell proliferation, migration, and invasion capabilities.ConclusionOur study establishes WDR76 as a robust pan-cancer prognostic biomarker and a potential immunotherapeutic target. Specifically, we provide experimental evidence that WDR76 functions as an oncogenic driver in liver cancer, promoting malignant phenotypes and offering a novel avenue for targeted therapeutic intervention.

Humans↗
PubMed2026

Integrated phenotype, endogenous hormones and transcriptome analysis revealed the mechanism of response of Phoebe bournei seedlings to shade signals.

Understory tree seedlings are subjected to prolonged shading stress imposed by the canopy foliage, which significantly impedes their growth. A hallmark of shaded environments is a reduced red to far-red light ratio (R: FR). This study elucidates the physiological and molecular responses of the endangered tree species Phoebe bournei to shading signals. Seedlings were exposed to white light (control) and simulated shading environments with R: FR ratios of 1.5, 0.8, and 0.2. The findings reveal that an increase in the proportion of far-red light significantly enhances seedling height, root-collar diameter, internode length, petiole length, leaf surface area, and leaf biomass. Differentially expressed genes (DEGs) in each treatment group predominantly enrich pathways associated with hormone signaling, stress responses, and photosynthesis. Validation experiments demonstrate that shading promotes the activity of Rubisco and RCA enzymes, total chlorophyll (Chl) accumulation, and elevated levels of hormones including indole-3-acetic acid (IAA), gibberellic acid (GA3), salicylic acid (SA)/methyl salicylate (MeSA), cytokinins (CK), abscisic acid (ABA), and jasmonic acid (JA). Weighted Gene Co-expression Network Analysis (WGCNA) identifies seven hub genes linked to photosynthesis and plant hormone regulation: MYB, KSC, SUAR, CESA POD, CESA, and SAUR. Collectively, shading signals induce P. bournei seedlings to elongate their stems and petioles, enhance photosynthetic enzyme activity, and accumulate specific hormones, with pertinent genes actively participating in light signal transduction. This research sheds light on the shading response mechanism of P. bournei, providing a robust theoretical framework for the breeding of shade-tolerant trees and the conservation of endangered species.

Transcriptome↗
PubMed2024

Construction of a molecular diagnostic system for neurogenic rosacea by combining transcriptome sequencing and machine learning.

Patients with neurogenic rosacea (NR) frequently demonstrate pronounced neurological manifestations, often unresponsive to conventional therapeutic approaches. A molecular-level understanding and diagnosis of this patient cohort could significantly guide clinical interventions. In this study, we amalgamated our sequencing data (n = 46) with a publicly accessible database (n = 38) to perform an unsupervised cluster analysis of the integrated dataset. The eighty-four rosacea patients were partitioned into two distinct clusters. Neurovascular biomarkers were found to be elevated in cluster 1 compared to cluster 2. Pathways in cluster 1 were predominantly involved in neurotransmitter synthesis, transmission, and functionality, whereas cluster 2 pathways were centered on inflammation-related processes. Differential gene expression analysis and WGCNA were employed to delineate the characteristic gene sets of the two clusters. Subsequently, a diagnostic model was constructed from the identified gene sets using linear regression methodologies. The model's C index, comprising genes PNPLA3, CUX2, PLIN2, and HMGCR, achieved a remarkable value of 0.9683, with an area under the curve (AUC) for the training cohort's nomogram of 0.9376. Clinical characteristics from our dataset (n = 46) were assessed by three seasoned dermatologists, forming the NR validation cohort (NR, n = 18; non-neurogenic rosacea, n = 28). Upon application of our model to NR diagnosis, the model's AUC value reached 0.9023. Finally, potential therapeutic candidates for both patient groups were predicted via the Connectivity Map. In summation, this study unveiled two clusters with unique molecular phenotypes within rosacea, leading to the development of a precise diagnostic model instrumental in NR diagnosis.

Humans↗
PubMed2024

Transcriptome-wide N6-methyladenosine modification profiling of long non-coding RNAs in patients with recurrent implantation failure.

N6-methyladenosine (m6A) is involved in most biological processes and actively participates in the regulation of reproduction. According to recent research, long non-coding RNAs (lncRNAs) and their m6A modifications are involved in reproductive diseases. In the present study, using m6A-modified RNA immunoprecipitation sequencing (m6A-seq), we established the m6A methylation transcription profiles in patients with recurrent implantation failure (RIF) for the first time. There were 1443 significantly upregulated m6A peaks and 425 significantly downregulated m6A peaks in RIF. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that genes associated with differentially methylated lncRNAs are involved in the p53 signalling pathway and amino acid metabolism. The competing endogenous RNA network revealed a regulatory relationship between lncRNAs, microRNAs and messenger RNAs. We verified the m6A methylation abundances of lncRNAs by using m6A-RNA immunoprecipitation (MeRIP)-real-time polymerase chain reaction. This study lays a foundation for further exploration of the potential role of m6A modification in the pathogenesis of RIF.

Humans↗
PubMed2024

Effects of different temperatures on chondrocyte growth: a transcriptomic analysis.

BACKGROUND: Our previous study demonstrated that temperature-related microwave ablation (MWA) can safely modulate growth plates of piglets' vertebrae. Therefore, this study is designed to investigate the effects of different temperatures on chondrocyte viability and the underlying molecular mechanisms in vitro. METHODS: Following a 10-minute treatment at different temperatures (37 °C, 40 °C, 42 °C, 44 °C, 46 °C, 48 °C, and 50 °C), CCK-8 assay was used to examine the viability of ATDC5 cells at 12 h. Differentially expressed genes (DEGs) and the hub genes in ATDC5 cells treated at 37 °C, 40 °C and 44 °C were identified using RNA-seq. The expression of hub genes in ATDC5 cells was validated using RT-qPCR. RESULTS: Compared with 37 °C, exposure to 40 °C significantly increased the viability of ATDC5 cells, while 42 °C had no significant effect. Additionally, exposure to 44 °C, 46 °C, 48 °C, and 50 °C exhibited the opposite pattern, with ATDC5 cells being particularly less than 50% active after treatment at 46 °C, 48 °C, and 50 °C. Differential expression analysis identified 179, 374 and 221 DEGs in the comparisons of 40 °C vs. 37 °C, 44 °C vs. 37 °C, and 44 °C vs. 40 °C, respectively. These DEGs predominantly regulated proliferation, differentiation, necrosis, inflammatory and immune responses, and ECM synthesis/degradation. Furthermore, they were associated with the Ras, PI3K/AKT, mTOR, cAMP, and MAPK pathways. Agt, Hspa1a, Hspb1, and Nlrc4 were identified as hub genes in DEGs, and RT-qPCR confirmed that the mRNA expression patterns of these hub genes in ATDC5 cells were largely consistent with the RNA-seq results. CONCLUSION: The regulation of chondrocyte viability by temperature is associated with Ras, PI3K/AKT, mTOR, cAMP, and MAPK pathways. Additionally, Agt, Hspa1a, Hspb1, and Nlrc4 may be the key regulatory genes in this process.

Chondrocytes↗
PubMed2025

Transcriptomics-based exploration of ubiquitination-related biomarkers and potential molecular mechanisms in laryngeal squamous cell carcinoma.

BACKGROUND: One of the most common and prevalent cancers is laryngeal squamous cell carcinoma (LSCC), which poses a great threat to the life and health of the patient. Nonetheless, it has been demonstrated that ubiquitination is crucial for the development and course of LSCC. Therefore, it is particularly important to identify biomarkers for ubiquitination-related genes (UbRGs) in LSCC. METHODS: Differentially expressed genes (DEGs) in the LSCC versus controls were obtained by differential expression analysis. Also, key modular genes associated with LSCC were obtained using weighted gene co-expression network analysis (WGCNA). Next, DEGs, key module genes, and UbRGs were taken to intersect to obtain candidate genes. And then machine algorithms were to screen potential biomarkers, further their diagnostic value were analyzed and validated. Then, therapeutic agents for biomarkers were predict. In addition, the regulatory networks of the biomarkers were mapped. The expression levels of biomarkers were detected in clinical samples using reverse transcription-quantitative PCR (RT-qPCR). RESULTS: A total of eight candidate genes were acquired by the overlap 1,911 DEGs, the key modular genes of WGCNA, and 1,393 UbRGs. A sum of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) were identified by two machine learning, then these four biomarkers were validated in GSE127165 and the expression trend was consistent with TCGA-LSCC, they were recorded as biomarkers. Moreover, the accuracy of the biomarkers in predicting clinical aspects of LSCC was confirmed by the receiver operating characteristic (ROC) curves. Subsequently, cancers such as malignant neoplasms, colorectal cancers, tumors, and primary malignant neoplasms were significantly associated with the biomarkers, which further suggests that these four biomarkers were strongly associated with cancer. Meanwhile, the drugs garcinol, cocaine, and triazolam, among others, used for LSCC treatment were predicted. Finally, transcription factors (TFs) (BRD4, MYC, AR, and CTCF) were predicted to regulate the biomarkers. RT-qPCR assays illustrated that the expression trends of KAT2B, LNX1 and NBEAL2 remained consistent with the dataset. CONCLUSION: The identification of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) associated with UbRGs could ultimately serve as a predictive clinical diagnosis of LSCC and provide insight into the molecular mechanisms of LSCC.

Humans↗
PubMed2026

TNFα-induced endothelial extracellular vesicles regulate astrocyte function: an integrated transcriptomic and proteomic study.

Endothelial cells and astrocytes are critical structural and functional components of the blood-brain barrier. In many neuroinflammatory diseases, endothelial cells are among the first to respond to inflammatory stimuli and release extracellular vesicles (EVs). However, whether inflammatory stimulation alters EV RNA cargo and subsequently regulates astrocyte function remains unclear. In this study, we performed integrated RNA sequencing and proteomic analyses to investigate the effects of TNFα-stimulated endothelial EVs on astrocytes. RNA profiling revealed significant alterations in EV cargo after TNFα stimulation, including 867 upregulated and 577 downregulated mRNAs, 317 upregulated and 15 downregulated lncRNAs, and 88 upregulated and 62 downregulated miRNAs. The results of functional enrichment analysis suggested that altered EV RNAs may primarily promote inflammatory responses, cell migration, and RNA splicing in astrocytes while reducing their regulatory effects on neuronal projection and calcium homeostasis. Further integrative analysis of EV RNAs and astrocytic proteomics revealed key overlapping targets, including upregulated expression of ICAM1, SOD2, TFPI2, and TNFAIP8, whereas NFKBIA expression was consistently decreased. Network analysis revealed NF-κB as the central regulatory node. Reduced levels of EV-derived NFKBIA mRNA were associated with decreased IκBα protein levels in astrocytes, which promoted NF-κB activation and inflammatory cytokine release. Finally, overexpression of IκBα in astrocytes significantly attenuated TNFα EV-induced IL-1β and IL-6 secretion. Collectively, these findings demonstrate that TNFα-stimulated endothelial EVs coordinately regulate astrocyte function through mRNA, lncRNA, and miRNA cargo and that the IκBα/NF-κB axis may be a key mechanism underlying endothelial EV-mediated inflammatory disruption of the blood-brain barrier.

Astrocytes↗
PubMed2026

Transcriptome-based epigenetic screening identifies DNA hypermethylation signatures as prognostic biomarkers in oral squamous cell carcinoma.

Promoter DNA hypermethylation is a key epigenetic mechanism of gene silencing in cancer, yet the DNA hypermethylome of oral squamous cell carcinoma (OSCC) and its prognostic relevance remain poorly characterized. Here, we systematically identified and validated novel hypermethylated genes with prognostic significance in OSCC using a genome-wide discovery and multi-platform validation strategy. Candidate genes were first identified by pharmacologic demethylation combined with RNA sequencing across OSCC cell lines, then validated by quantitative RT-PCR, methylation-specific PCR, and bisulfite sequencing in OSCC cell lines, normal oral mucosa, and primary OSCC tumors, with independent confirmation in the TCGA-HNSC dataset. Immunohistochemistry confirmed protein-level silencing, and Kaplan-Meier survival analysis assessed prognostic significance across both cohorts. This pipeline identified five candidate genes, GPX3, ANG, CTGF, GPRC5B, and BAMBI, exhibiting cancer-specific promoter hypermethylation associated with transcriptional and protein silencing in OSCC. Validation in oral cavity tumor samples extracted from the TCGA-HNSC dataset confirmed tumor-specific hypermethylation and revealed significant inverse correlations between methylation and expression for GPX3, GPRC5B, and CTGF. Notably, CTGF hypermethylation was independently associated with poor overall survival in both cohorts (institutional cohort, p=0.03; oral tumor subset from TCGA-HNSC, p=0.01), and a combined ANG+CTGF methylation signature showed superior and reproducible prognostic performance across both platforms. Pathway analysis linked these genes to epithelial-mesenchymal transition and interferon response signaling. This study establishes the first validated DNA methylation biomarker panel for OSCC prognosis, identifying CTGF hypermethylation as a robust prognostic driver with translational potential for clinical risk stratification.

Humans↗
PubMed2025

Revealing cancer driver genes through integrative transcriptomic and epigenomic analyses with Moonlight.

Cancer involves dynamic changes caused by (epi)genetic alterations such as mutations or abnormal DNA methylation patterns which occur in cancer driver genes. These driver genes are divided into oncogenes and tumor suppressors depending on their function and mechanism of action. Discovering driver genes in different cancer (sub)types is important not only for increasing current understanding of carcinogenesis but also from prognostic and therapeutic perspectives. We have previously developed a framework called Moonlight which uses a systems biology multi-omics approach for prediction of driver genes. Here, we present an important development in Moonlight2 by incorporating a DNA methylation layer which provides epigenetic evidence for deregulated expression profiles of driver genes. To this end, we present a novel functionality called Gene Methylation Analysis (GMA) which investigates abnormal DNA methylation patterns to predict driver genes. This is achieved by integrating the tool EpiMix which is designed to detect such aberrant DNA methylation patterns in a cohort of patients and further couples these patterns with gene expression changes. To showcase GMA, we applied it to three cancer (sub)types (basal-like breast cancer, lung adenocarcinoma, and thyroid carcinoma) where we discovered 33, 190, and 263 epigenetically driven genes, respectively. A subset of these driver genes had prognostic effects with expression levels significantly affecting survival of the patients. Moreover, a subset of the driver genes demonstrated therapeutic potential as drug targets. This study provides a framework for exploring the driving forces behind cancer and provides novel insights into the landscape of three cancer sub(types) by integrating gene expression and methylation data.

Humans↗
PubMed2026

Integrated single-cell transcriptomics, Mendelian randomization, and machine learning identify CEBPZ as an immune-related biomarker in oral lichen planus.

BACKGROUND: Oral lichen planus (OLP) is a chronic, immune-mediated oral mucosal disease with complex pathophysiology and potential for malignant transformation. Understanding its molecular basis is critical for the development of precise diagnostic and therapeutic strategies. OBJECTIVES: We aimed to identify key immune-related biomarkers and characterize cellular dynamics in OLP, with a particular focus on the role of CEBPZ in disease pathogenesis. MATERIAL AND METHODS: We analyzed single-cell RNA sequencing (scRNA-seq) data from OLP lamina propria samples (GSE211630) to identify disease-specific T-cell subpopulations using high-dimensional weighted gene co-expression network analysis (hdWGCNA) for oxidative stress-related gene modules.-data-based Mendelian randomization (SMR) integrated FinnGen genome-wide association study (GWAS; 342,499 Europeans) data with Genotype-Tissue Expression (GTEx) expression quantitative trait loci (eQTL) data to identify causal genes. Machine learning (ML) models (least absolute shrinkage and selection operator (LASSO) and convolutional neural network (CNN)) were developed using bulk RNA-seq datasets (GSE52130 and GSE38616) for diagnostic purposes. RESULTS: We identified OLP-specific T-cell populations (clusters 0, 3, 5, 7, 13, and 15) with enhanced migration inhibition factor (MIF) pathway signaling toward B cells and monocytes. Two oxidative stress-associated modules contained hub genes, including CEBPZ. Summary-data-based Mendelian randomization analysis identified 231 OLP-associated genes, with CEBPZ uniquely intersecting LASSO-selected markers (odds ratio (OR) = 1.057, 95% confidence interval (95% CI) = 1.013-1.102, p = 0.010). Machine learning models achieved area under the curve (AUC) values ranging from 0.653 to 0.745, with the CNN model reaching a validation accuracy of 0.735. CEBPZ showed elevated expression in OLP T cells and correlated with enhanced MIF-(CD74+CXCR4) signaling. CONCLUSIONS: This integrative approach identifies CEBPZ as a pivotal biomarker linking genetic susceptibility, oxidative stress, and immune dysregulation in OLP. Our diagnostic models offer promising tools for OLP management.

CEBPZ↗
PubMed2026

Meta-Merging the Transcriptomes of Gastric Tumors Redefines the Connections among Molecular and Clinical Subtypes.

INTRODUCTION: The availability of a large number of cancer expression profiles presents an excellent opportunity to re-investigate various biological and clinical questions. While several expression profiles have been established for different cancers, merging them may provide a more powerful platform for extensively extrapolating molecular and clinical features across multiple cohorts. MATERIALS AND METHODS: In this study, five gastric tumor expression profiles from the Gene Expression Omnibus [GEO] and one in-house cohort comprising a total of 1,060 samples were merged. The batch effect was removed using non-parametric ComBat analysis, and the seamless merging of datasets was confirmed through various parameters. RESULTS: Extrapolation of ACRG [Asian Cancer Research Group] and TCGA [The Cancer Genome Atlas] molecular subtypes in the merged cohort of 1,060 gastric tumors revealed nine distinct clusters. Notably, the following patterns were observed: [i] mutual exclusivity between Epithelial to Mesenchymal Transition [EMT] and Microsatellite Instability [MSI] subtypes in 90% of tumors; [ii] overlapping occurrence of EMT and MSI subtypes in the remaining tumors; [iii] overlap between MSI and Epstein-Barr Virus [EBV] subtype tumors; [iv] both commonalities and differences between EMT and Genomically Stable [GS] subtypes; and [v] an association between EBV positivity and PI3K mutation. CONCLUSION: The current study demonstrates that compiling a larger expression profile is valuable for revisiting the molecular features and epidemiology associated with molecular subtypes, thereby aiding in the development of novel diagnostics and targeted therapeutics.

Humans↗
PubMed2026

Single-cell transcriptomics reveals distinct microglial state remodeling associated with the (R)-nicotine/diosmetin combination and galantamine in LPS-challenged BV2 cells.

BACKGROUND: Microglial neuroinflammation contributes to the progression of neurodegenerative diseases, yet it remains challenging to attenuate inflammatory responses while preserving cellular function. The effects of (R)-nicotine, diosmetin, their combined administration, and galantamine on heterogeneous BV2 transcriptional states have not been compared at single-cell resolution. METHODS: LPS-stimulated BV2 microglial-like cells were treated with (R)-nicotine, diosmetin, their combination (DR), or galantamine. Single-cell RNA sequencing was performed with three biological replicates per group and integrated with RNA velocity and SCENIC regulon inference to characterize treatment-associated state redistribution, inferred local transcriptional directionality and regulon-activity patterns. Functional validation included CCK-8 metabolic activity assays, multiplex cytokine ELISA, BDNF/GDNF quantification, qPCR, and high-content immunofluorescence analysis of iNOS and Arg1 at single-cell resolution. RESULTS: LPS decreased the relative abundance of the Itgae+/Plk4+ cluster while increasing the Nmur1+/Limk2+ cluster and inflammatory effector programs. DR treatment suppressed pro-inflammatory cytokine release without significantly reducing CCK-8-assessed metabolic activity, increased the Itgae+/Plk4+ cluster proportion, and increased BDNF/GDNF relative to LPS. RNA velocity and SCENIC analyses suggested that DR and galantamine showed distinct transcriptional and regulatory patterns: DR attenuated Batf-associated inflammatory regulons and was associated with increased Atf3-linked stress-response activity, whereas galantamine preferentially engaged DNA repair and genome-maintenance programs. CONCLUSION: These findings indicate that the DR condition was associated with remodeling of LPS-challenged BV2 microglial-like states, attenuation of inflammatory programs, and increased neurotrophic outputs relative to LPS, without significantly reducing CCK-8-assessed metabolic activity. This study provides a single-cell characterization of distinct treatment-associated responses to (R)-nicotine, diosmetin, their combined administration, and galantamine.

Microglia↗
PubMed2026

Genome-Wide Identification of the PAL Gene Family in Idesia polycarpa and Transcriptomic Responses to Botryosphaeria dothidea Infection.

Idesia polycarpa is a woody oil tree threatened by stem canker caused by Botryosphaeria dothidea, yet the organization and infection-responsive behavior of its phenylalanine ammonia-lyase (PAL) gene family remain poorly understood. Here, we identified five IpPAL genes and characterized their phylogenetic relationships, conserved features, duplication patterns, promoter cis-elements, and infection-associated expression profiles. Segmental and tandem duplication contributed to IpPAL family evolution, and all duplicated pairs showed Ka/Ks ratios below 1, consistent with purifying selection. RNA sequencing (RNA-seq) of contrasting Chengdu and Zhangjiajie provenances revealed distinct temporal responses. In Chengdu, IpPAL2-IpPAL4 were significantly upregulated at 24 h after inoculation, whereas all five genes were upregulated at 96 h. In Zhangjiajie, all five IpPAL genes were significantly upregulated at 24 h, while IpPAL2-IpPAL5 remained upregulated at 96 h. No IpPAL gene met the differential-expression criteria between provenances under mock conditions or at 24 h; at 96 h, IpPAL1 and IpPAL3 were lower and IpPAL5 was higher in Zhangjiajie than in Chengdu. Scanning electron microscopy (SEM) provided complementary qualitative evidence of provenance-associated tissue responses. These findings demonstrate time- and gene-specific IpPAL responses to B. dothidea and identify candidate genes for further functional analysis.

Ascomycota↗
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

Genetic Association of the Transcriptome and Immunoglobulin G N-glycome with Cognitive Function.

OBJECTIVE: Immunoglobulin G (IgG) N-glycosylation is associated with mild cognitive impairment through the regulation of inflammatory balance; however, the underlying mechanisms remain unclear. METHODS: Our study utilized a post-genome-wide association studies (GWAS) method that integrated GWAS data for cognitive function with gene expression quantitative trait loci (eQTL), protein QTL (pQTL), and IgG N-glycan-QTL data. RESULTS: Mendelian randomization (MR) analyses suggested bidirectional causalities between glycan peaks (GPs) and cognitive function, with GP7, GP12, and GP19 showing a causal effect on cognitive function, while cognitive function conversely showed a causal effect on GP1 and GP8. Two proteins and 10 genes were implicated in the regulation of IgG N-glycosylation. Furthermore, multivariable MR results suggested complex causalities between genes/proteins and IgG N-glycans, which jointly promote or independently affect cognitive function. CONCLUSION: Our study reveals a novel mechanism by which genes, proteins, and modified IgG N-glycans converge to pathologically affect cognitive function.

Immunoglobulin G↗
PubMed2026

Exploring genomic regions regulating the liver transcriptome and energy homeostasis in pigs.

In pigs, energy homeostasis has an impact on meat quality and health. In a Duroc pig population, 30 quantitative trait locus (QTL) regions associated with fatty acid (FA) composition in adipose tissue, plasma, liver and muscle were previously identified. Mapping of expression quantitative trait locus (eQTL) regions will provide a molecular hypothesis for genotype-phenotype interactions and may allow the identification of shared causal variants, key to increasing our understanding of the genetic regulation of FA composition and energy homeostasis. However, gene expression is impacted by environmental factors, while individual-level allelic imbalance (AI) can be more reliable and can be surveyed via allelic-specific expression (ASE) analysis. Furthermore, treatment of ASE as a quantitative trait allows the identification of allele-specific expression quantitative trait loci (aseQTLs), which are variants whose heterozygosity is linked to the AI of a nearby single-nucleotide polymorphism (SNP), pointing to regulatory elements. In this study, liver was selected as a key metabolic hub with an important role in the regulation of energy homeostasis, and 310 liver RNA sequencing samples were analysed using a combination of (1) eQTL mapping, (2) ASE analysis, and (3) aseQTL mapping methods. A total of 2 188 eQTL regions were identified, mostly cis-eQTL regions (73.17%). ASE analysis reported 1 964 ASE SNPs, associated with 633 genes. Finally, aseQTL mapping reported 64 172 aseQTL, associated with the AI of 31 genes. Colocalisation analysis combined with ASE analysis showed that the expression of FADS1 and FADS2 genes is associated with the polyunsaturated FA composition in several tissues, where microRNA regulation may be present. Finally, in the DGAT2 gene, annotated in a QTL region associated with multiple FAs in adipose tissue, ASE revealed allelic imbalance in the 3' untranslated region (UTR) of this gene. Allelic differential expression can be caused by a 13-bp insertion affecting messenger RNA stability, previously described, exemplifying how allelic imbalance is caused by a post-transcriptional regulatory mechanism undetectable by eQTL mapping. Furthermore, aseQTLs were associated with this gene, linked to a previously identified copy number variant not yet associated with DGAT2 expression. These results demonstrate how ASE analysis and aseQTL mapping can complement eQTL mapping, as they resolved a complex region affected by allelic heterogeneity, a main confounding effect of QTL mapping. In conclusion, the combination of eQTL mapping, ASE analysis and aseQTL mapping allowed the characterisation of the regulation of liver gene expression, improving our understanding of the genetic determinism of energy homeostasis.

Allele-specific expression↗