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Transcriptome-wide analysis reveals potential roles of CFD and ANGPTL4 in fibroblasts regulating B cell lineage for extracellular matrix-driven clustering and novel avenues for immunotherapy in breast cancer.

BACKGROUND: The remodeling of the extracellular matrix (ECM) plays a pivotal role in tumor progression and drug resistance. However, the compositional patterns of ECM in breast cancer and their underlying biological functions remain elusive. METHODS: Transcriptome and genome data of breast cancer patients from TCGA database was downloaded. Patients were classified into different clusters by using non-negative matrix factorization (NMF) based on signatures of ECM components and regulators. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify core genes related to ECM clusters. Additional 10 independent public cohorts including Metabric, SCAN_B, GSE12276, GSE16446, GSE19615, GSE20685, GSE21653, GSE58644, GSE58812, and GSE88770 were collected to construct Training or Testing cohort, following machine learning calculating ECM correlated index (ECI) for survival analysis. Pathway enrichment and correlation analysis were used to explore the relationship among ECM clusters, ECI and TME. Single-cell transcriptome data from GSE161529 was processed for uncovering the differences among ECM clusters. RESULTS: Using NMF, we identified three ECM clusters in the TCGA database: C1 (Neuron), C2 (ECM), and C3 (Immune). Subsequently, WGCNA was employed to pinpoint cluster-specific genes and develop a prognostic model. This model demonstrated robust predictive power for breast cancer patient survival in both the Training cohort (n = 5,392, AUC = 0.861) and the Testing cohort (n = 1,344, AUC = 0.711). Upon analyzing the tumor microenvironment (TME), we discovered that fibroblasts and B cell lineage were the core cell types associated with the ECM cluster phenotypes. Single-cell RNA sequencing data further revealed that angiopoietin like 4 (ANGPTL4)+ fibroblasts were specifically linked to the C2 phenotype, while complement factor D (CFD)+ fibroblasts characterized the other ECM clusters. CellChat analysis indicated that ANGPTL4+ and CFD+ fibroblasts regulate B cell lineage via distinct signaling pathways. Additionally, analysis using the Kaplan-Meier Plotter website showed that CFD was favorable for immunotherapy response, whereas ANGPTL4 negatively impacted the outcomes of cancer patients receiving immunotherapy. CONCLUSION: We identified distinct ECM clusters in breast cancer patients, irrespective of molecular subtypes. Additionally, we constructed an effective prognostic model based on these ECM clusters and recognized ANGPTL4+ and CFD+ fibroblasts as potential biomarkers for immunotherapy in breast cancer.

Humans

Integrated 16 S rRNA and transcriptome analysis reveal molecular and microbial mechanisms of cold-tolerant germination in hulless barley.

BACKGROUND: Elucidating the mechanisms underlying cold-tolerant germination is crucial for enhancing crop resilience to low temperatures. Hulless barley (Hordeum vulgare var. coeleste L.), with remarkable natural cold adaptation, serves as an ideal model to study cold stress tolerance mechanisms in gramineous crops. In this study, cold-tolerant variety 37 and cold-sensitive variety 44 were screened and used to investigate the molecular mechanisms of cold-tolerant germination, via seed germination assays, combined with phytohormone determination, transcriptome sequencing and 16 S rRNA amplicon sequencing. RESULTS: Low temperature significantly inhibited hulless barley seed germination: the germination rate of cold-sensitive variety 44 decreased by 69%, while that of cold-tolerant variety 37 only decreased by 2%. Transcriptome analysis identified 2,647 and 2,392 differentially expressed genes (DEGs) in variety 37 and 44, respectively. Weighted gene co-expression network analysis (WGCNA) revealed a green module significantly positively correlated with gibberellic acid (GA) content, containing 10 core genes such as late embryogenesis abundant protein (LEA) and Homeobox genes. 16 S rRNA sequencing showed that the cold-tolerant variety 37 had enriched abundances of dominant endophytes including Sphingomonas and Pelomonas, with correlation coefficients of 0.70 and 0.87 with GA content, respectively. Additionally, exogenous GA treatment significantly increased germination rates under cold stress by 176.67% in cold-sensitive variety 44. CONCLUSIONS: This study confirms that the enhanced cold tolerance of hulless barley during seed germination originates from the synergistic interaction between beneficial endophytes (Sphingomonas, Pelomonas), GA, and core genes (e.g., LEA, Homeobox). Exogenous GA application can significantly restore the germination ability of cold-sensitive varieties. These findings provide a critical theoretical basis for improving cold tolerance in hulless barley germplasm.

Hordeum

Comparative transcriptome analysis of Qinchuan and Wagyu cattle reveals lnc11599 as a negative regulator of intramuscular fat deposition.

BACKGROUND: Intramuscular fat (IMF) content is a critical factor determining beef quality, influenced by various factors including breed and age. However, the regulatory role of long non-coding RNAs (lncRNAs) in IMF deposition remains unclear. METHODS: This study investigated IMF deposition in the longissimus dorsi muscle of one- and two-year-old Qinchuan and Wagyu cattle through histological examination and fat content measurement. Based on transcriptome sequencing data of intramuscular fat tissue, differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify lncRNAs associated with IMF deposition. The effects of a key candidate lncRNA on the adipogenic differentiation of cattle intramuscular preadipocytes were further examined. RESULTS: Results showed that Wagyu cattle exhibited stronger IMF deposition capacity than Qinchuan cattle across all age groups, with IMF content increasing with age in both breeds. We identified 7,910 lncRNAs from intramuscular fat tissue transcriptome data, including 6,455 novel lncRNAs. Through integrated differential expression analysis and WGCNA, 88 lncRNAs closely associated with IMF deposition were screened from two-year-old Qinchuan and Wagyu cattle. Notably, lnc11599 was significantly upregulated in Qinchuan cattle intramuscular fat tissue, but its expression decreased during intramuscular preadipocyte differentiation. Functional experiments demonstrated that lnc11599 knockdown enhanced adipogenic differentiation capacity, manifested as a highly significant increase in lipid accumulation, upregulation of key adipogenic genes at the mRNA level, together with increases in total fatty acid content and unsaturated fatty acid proportion. CONCLUSIONS: This study established the lncRNA expression profiles in intramuscular fat tissue of Qinchuan and Wagyu cattle across different developmental stages, and demonstrated that lnc11599 acts as a negative regulator of intramuscular fat deposition. These findings provide new directions for elucidating the mechanisms of cattle IMF deposition and offer potential targets for genetic improvement of beef quality.

Animals

Characterization and analysis of the full-length transcriptome of Frankliniella occidentalis (Thysanoptera: Thripidae).

BACKGROUND: Frankliniella occidentalis, an insect belonging to the order Thysanoptera, causes severe damage to agricultural and horticultural crops, resulting in significant economic losses worldwide. The development of molecular and sequencing technologies has helped elucidate the molecular mechanisms regulating its growth and development as well as its damaging activity. However, much remains to be explored. To further investigate the molecular complexity of this species, we sequenced the full-length transcriptome of mixed samples obtained from specimens at all developmental stages. RESULTS: Of all transcripts, 89.04% matched with the reference genome; additionally, 29,750 alternative splicing events, 2,342 genes with poly(A) sites, and 153 candidate fusion transcript events were identified, and 4,235 long noncoding RNAs were discovered. CONCLUSIONS: This is the first full-length transcriptome of F. occidentalis reported to date. This study greatly contributes to the understanding of the molecular complexity and diversity of this insect, providing a basis to develop specific molecular targets as well as resources for gene function studies in other insects.

Animals

Unravelling the transcriptomic characteristics of bronchoalveolar lavage in post-covid pulmonary fibrosis.

BACKGROUND: Post-Covid Pulmonary Fibrosis (PCPF) has emerged as a significant global issue associated with a poor quality of life and significant morbidity. Currently, our understanding of the molecular pathways of PCPF is limited. Hence, in this study, we performed whole transcriptome sequencing of the RNA isolated from the bronchoalveolar lavage (BAL) samples of PCPF and compared it with idiopathic pulmonary fibrosis (IPF) and non-ILD (Interstitial Lung Disease) control to understand the gene expression profile and associated pathways. METHODS: BAL samples from PCPF (n = 3), IPF (n = 3), and non-ILD Control (n = 3) (individuals with apparent healthy lung without interstitial lung disease) groups were obtained and RNA were isolated for whole transcriptomic sequencing. Differentially Expressed Genes (DEGs) were determined followed by functional enrichment analysis and qPCR validation. RESULTS: A panel of differentially expressed genes were identified in bronchoalveolar lavage fluid cells (BALF) of PCPF as compare to control and IPF. Our analysis revealed dysregulated pathways associated with cell cycle regulation, immune responses, and neuroinflammatory processes. Real-time validation further supported these findings. The PPI network and module analysis shed light on potential biomarkers and underscore the complex interplay of molecular mechanisms in PCPF. The comparison of PCPF and IPF identified a significant downregulation of pathways that were more prominent in IPF. CONCLUSION: This investigation provides crucial insights into the molecular mechanism of PCPF and also outlines avenues for prospective research and the development of therapeutic approaches.

Humans

Novel insights into hypoxia-driven transcriptomic and epigenetic landscapes in grade 3 meningioma.

BACKGROUND: Meningiomas are among the most prevalent central nervous system (CNS) tumors, with up to 20% of cases exhibiting recurrence or aggressive behavior. Hypoxia is a key driver of malignant transformation and therapeutic resistance, yet its molecular basis in meningioma remains poorly understood. METHODS: We conducted integrative transcriptomic and epigenomic profiling of IOMM-Lee cells (grade 3 meningioma) cultured under hypoxic (0.2% O₂) and normoxic conditions. RNA-sequencing and Illumina MethylationEPIC v2.0 data were analyzed in R using DESeq2 and minfi, respectively. Functional enrichment, transcription-factor binding analysis, and pathway mapping (clusterProfiler, enrichR) were performed. Findings were cross-validated in public meningioma datasets, in Indian meningioma patient cohort and cell line via RT-qPCR, and azacytidine-based demethylation assay. Functional role of the candidate gene was elucidated in vitro via cellular assays. RESULTS: Hypoxia triggered a canonical HIF1A-driven transcriptional program activating glycolytic and angiogenic pathways while downregulating genes associated with DNA repair and replication in meningioma. Several differentially expressed genes (DEGs) were identified as known oncogenes, tumor-suppressors, or associated with immune regulation and stemness. Promoter motif analysis identified HIF1, SP1, TP53, BRCA1, and E2F1 as enriched transcriptional regulators. We validated hypoxia and HIF1-mediated regulation of some of the top DEGs. DNA-methylation analysis revealed epigenetic silencing of RTN4IP1 and ZBTB7C under hypoxia, reversible upon azacytidine treatment. Integrative comparison with patient datasets highlighted SLITRK2, PDE4C, SGCD, and LRP1B as hypoxia-responsive genes associated with poor prognosis. Several hypoxia-regulated genes also showed significant correlation with known hypoxia biomarkers, VEGFA and CA9. IGFBP3 and NDRG1 were among the top hypoxia-associated upregulated genes, and IGFBP3 expression was linked to advanced meningioma grades. Knockdown of IGFBP3 via siRNA in hypoxia-treated IOMM-Lee cells was associated with reduced cell proliferation and migration. CONCLUSIONS: This study presents the first integrated transcriptomic–epigenomic landscape of hypoxia in grade 3 meningioma, uncovering regulatory networks and candidate biomarkers with prognostic and therapeutic potential. These findings provide a foundation for future translational studies targeting hypoxia-driven tumor progression in meningioma.

Humans

Transcriptome changes in circulating immune cells of critical COVID-19 patients predict a specific metabolic and epigenetic imprint.

BACKGROUND: The progression to critical COVID-19 arises predominantly from a dysregulated host immune response although the underlying regulatory mechanisms still remain partially elusive. This limits a prompt prediction of the disease progression, reduces the therapeutic options and restrains our understanding of “long COVID”. METHODS: Here, we analyzed the transcriptome of peripheral blood mononuclear cells (PBMCs) collected from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients enrolled in the clinical trial COntAGIouS as well as independent bulk RNA-seq, single-cell RNA-seq and proteomic datasets. RESULTS: In critical COVID-19 patients, the integrative analysis of transcriptomic data revealed an altered regulatory network involving microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and coding genes that control mRNA translation-related genes, epigenetics, and metabolism. In parallel, we observed an upregulation of tRNA aminoacylation genes in critical COVID-19 patients by the analysis of either bulk or single-cell RNA-seq data from publicly available independent cohorts. Additionally, we found increased expression of coding genes enriched for the cognate amino acids (glycine, alanine, isoleucine and tyrosine), all related to protein localization, post-translational modifications, and cell metabolism in our cohort. Similar alterations in amino acid frequency were found in an independent proteomic dataset. CONCLUSIONS: Collectively, our findings indicate a broad perturbation of the gene expression landscape that characterizes the aberrant host immune response in critical COVID-19 patients and is potentially coordinated by miRNA and tRNA metabolism alterations. TRIAL REGISTRATION: COntAGIouS, NCT04327570. Registered 26 March 2020, https://clinicaltrials.gov/ct2/show/NCT04327570 .

Female

Sparse deconvolution of cell type medleys in spatial transcriptomics.

Mapping cell distributions across spatial locations with whole-genome coverage is essential for understanding cellular responses and signaling However, current deconvolution models aim to estimate the proportions of distinct cell types in each spatial transcriptomics spot by integrating reference single-cell data. These models often assume strong overlap between the reference and spatial datasets, neglecting biology-grounded constraints such as sparsity and cell-type variations, as well as technical sparsity. As a result, these methods rely on over-permissive algorithms that ignore given constraints leading to inaccurate predictions, particularly in heterogeneous or unmatched datasets. We introduce Weight-Induced Sparse Regression (WISpR), a machine learning algorithm that integrates spot-specific hyperparameters and sparsity-driven modeling. Unlike conventional approaches that neglect biology-grounded constraints, WISpR accurately predicts cell-type distributions while preserving biological coherence, i.e., spatially and functionally consistent cell-type localization, even in unmatched datasets. Benchmarking against five alternative methods across ten datasets, WISpR consistently outperformed competitors and predicted cellular landscapes in both normal and cancerous tissues. By leveraging sparse cell-type arrangements, WISpR provides biologically informed, high-resolution cellular maps. Its ability to decode tissue organization in both healthy and diseased states highlights WISpR's practical utility for spatial transcriptomics, particularly in challenging settings involving noise, sparsity, or reference mismatches.

Humans

Transcriptome analysis under pecan scab infection reveals the molecular mechanisms of the defense response in pecans.

Pecan scab, caused by the fungal pathogen Venturia effusa, is the most devastating disease of pecan (Carya illinoinensis) in the southeastern United States. Resistance to this pathogen is determined by a complex interaction between host genetics and disease pathotype with even field-susceptible cultivars being resistant to most scab isolates. To understand the underlying molecular mechanisms of scab resistance in pecan, we performed a transcriptome analysis of the pecan cultivar, 'Desirable', in response to inoculation with a pathogenic and a non-pathogenic scab isolate at three different time points (24, 48, and 96 hrs. post-inoculation). Differential gene expression and gene ontology enrichment analyses showed contrasting gene expression patterns and pathway enrichment in response to the contrasting isolates with varying pathogenicity. The weighted gene co-expression network analysis of differentially expressed genes detected 11 gene modules. Among them, two modules had significant enrichment of genes involved with defense responses. These genes were particularly upregulated in the resistant reaction at the early stage of fungal infection (24 h) compared to the susceptible reaction. Hub genes in these modules were predominantly related to receptor-like protein kinase activity, signal reception, signal transduction, biosynthesis and transport of plant secondary metabolites, and oxidoreductase activity. Results of this study suggest that the early response of pathogen-related signal transduction and development of cellular barriers against the invading fungus are likely defense mechanisms employed by pecan cultivars against non-virulent scab isolates. The transcriptomic data generated here provide the foundation for identifying candidate resistance genes in pecan against V. effusa and for exploring the molecular mechanisms of disease resistance.

Carya

Effect of acupuncture on brain microenvironment in rats with post-stroke limb spasticity based on single-cell transcriptome sequencing technology.

OBJECTIVE: To investigate the possible mechanisms by which acupuncture improves post-stroke limb spasticity using single-cell sequencing technology. METHODS: Thirty-two rats were randomly assigned to four groups: Control, Sham, Model, and Acupuncture. The middle cerebral artery occlusion (MCAO) model was established, and the acupuncture groups received acupuncture treatment. After treatment, brain morphological changes and the degree of neurological impairment were assessed. The effect of acupuncture on the proportion of brain cell types in the ischemic penumbra of MCAO rats was analyzed using single-cell transcriptomics, and the expression and enrichment of differentially expressed genes were examined. Finally, selected differential genes were validated by Western blot and quantitative real-time polymerase chain reaction. RESULTS: Triphenyltetrazolium chloride staining showed that the infarct area in MCAO rats was significantly reduced after acupuncture. Garcia scoring, hematoxylin-eosin staining, Nissl staining, and terminal deoxynucleotidyl transferase dUTP nick end labeling demonstrated that acupuncture reduced brain damage. Enzyme-linked immunosorbent assay results showed that acupuncture significantly decreased serum inflammatory factors, including interleukin-1 beta (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Single-cell transcriptome analysis revealed marked changes in cell type proportions between the Acupuncture and Model groups. A total of 207 differential genes were identified, including 157 upregulated and 50 downregulated genes. Analysis of macrophage-specific differential genes in the ischemic penumbra showed enrichment in Gene Ontology terms such as Ras protein signal transduction and regulation of GTPase activity, and Kyoto Encyclopedia of Genes and Genomes pathways including lysosome, axon guidance, and mitogen-activated protein kinase signaling. S100a8 and leukocyte specific transcript 1 (LST1) were identified as key differential genes. CONCLUSION: These findings suggest that the key differential genes S100a8 and LST1 may alleviate post-stroke limb spasticity by regulating the inflammatory response in the ischemic penumbra.

Animals

Transcriptome Analysis, Machine Learning, and Experimental Identification of CDK7 Affecting the Progression of Pregnancy-induced Hypertension by Influencing Macrophage Polarization.

INTRODUCTION: Pregnancy-induced hypertension (PIH) is a severe pregnancy complication characterized by placental insufficiency, abnormal vascular remodeling, and immune dysregulation, but personalized therapeutic markers remain unclear. This study aimed to identify key genes and explore immune mechanisms in PIH using transcriptome analysis, machine learning, and experimental validation. METHODS: We analyzed the GSE204835 transcriptomic dataset to screen differentially expressed genes (DEGs) and performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Set Enrichment Analysis (GSEA) for functional annotation. Immune infiltration analysis was also performed to examine the immune landscape in PIH. Least Absolute Shrinkage and Selection Operator (LASSO) regression identified key genes, which were validated in a PIH cell model. Flow cytometry and immunofluorescence assays assessed the effect of CDK7 knockdown on macrophage polarization. RESULTS: A total of 1,598 DEGs (1,123 upregulated, 475 downregulated) were identified. Enrichment analyses highlighted associations with embryonic organ development, oxidative phosphorylation, angiogenesis, and oxidative stress. Immune infiltration analysis revealed altered eosinophil and macrophage polarization in PIH. LASSO regression selected 12 key genes, with CDK7 showing the most significant upregulation in the PIH model. CDK7 knockdown promoted macrophage polarization toward the anti-inflammatory M2 phenotype. DISCUSSION: These findings link CDK7 to immune dysregulation in PIH by modulating macrophage polarization, expanding our understanding of PIH's molecular mechanisms. The study's limitations include reliance on public datasets and in vitro models, warranting in vivo validation. CONCLUSION: CDK7 emerges as a potential therapeutic target for PIH, offering new insights into immunoregulatory interventions for this complication.

Female

Transcriptomic Changes Associated with Electroacupuncture in a DMCAO Model of Delayed Cognitive Impairment.

INTRODUCTION: Delayed Cognitive Impairment (DCIS) occurs in approximately 31% to 77% of individuals following stroke. Clinical findings have indicated that electroacupuncture may alleviate post-stroke DCIS. However, insights derived from animal models remain limited. The present study utilized a Distal Middle Cerebral Artery Occlusion (DMCAO) mouse model to investigate the potential mechanisms of electroacupuncture through hippocampal transcriptomic analysis. MATERIALS AND METHODS: Adult male BALB/c mice were subjected to DMCAO and received electroacupuncture treatment. High-throughput RNA sequencing of hippocampal tissue was performed to identify Differentially Expressed Genes (DEGs). Enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, hierarchical clustering, and Protein-Protein Interaction (PPI) network analysis, were performed to elucidate potential biological mechanisms. RESULTS: The DMCAO model exhibited features consistent with DCIS. Electroacupuncture treatment was associated with improved cognitive performance and enhanced hippocampal neuroplasticity. A total of 116 DEGs were identified in the DMCAO group compared with the sham group, while 69 DEGs were identified in the DMCAO + electroacupuncture group compared with the untreated DMCAO group. DISCUSSION: GO enrichment analysis indicated that electroacupuncture modulated biological processes related to nerve fibers, axonal development, neuronal regulation, cellular processes, and cardiovascular protection. KEGG pathway analysis indicated involvement in pathways associated with neuronal recovery and axonal function. The PPI network comprised 28 nodes and 33 interactions, with hub genes such as Gna13, Hipk2, and Stambp playing key roles. Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) results were consistent with RNA sequencing findings. CONCLUSION: Electroacupuncture improved DCIS in the DMCAO mouse model. Transcriptomic analysis of the hippocampus provided preliminary evidence of the potential mechanisms underlying the therapeutic effects of electroacupuncture treatment following ischemic stroke.

Animals

Multi-level Transcriptomic and Machine-learning Analyses Identify MZT1 as a Proliferation-associated Prognostic Marker in Lung Adenocarcinoma.

BACKGROUND/AIM: Lung adenocarcinoma (LUAD) exhibits substantial molecular heterogeneity and variable clinical outcomes, highlighting the need for biomarkers that reflect core tumor biological processes. Centrosome-associated proteins regulate mitotic fidelity and genome stability, yet their roles in LUAD remain incompletely defined. In this study, we systematically characterized mitotic spindle organizing protein 1 (MOZART1; MZT1) and related family members in LUAD. MATERIALS AND METHODS: We performed integrated analyses combining bulk transcriptomic datasets, survival modeling, gene set enrichment, immune deconvolution, machine-learning based prognostic modeling, and single-cell RNA sequencing. Expression patterns and clinical associations of MZT family genes were evaluated across pan-cancer and LUAD cohorts. RESULTS: MZT family genes were consistently upregulated in tumor tissues, with MZT1 showing the most robust expression pattern. Elevated MZT1 expression was significantly associated with reduced overall survival. Functional analyses revealed coordinated activation of proliferative and genome maintenance pathways, including G2/M checkpoint regulation, E2F and MYC signaling, and DNA repair. A multivariable analysis indicated that the prognostic association of MZT1 was reduced after adjusting for canonical proliferation markers, suggesting partial overlap with established proliferation signals. The LASSO-based Cox model demonstrated stable time-dependent predictive performance at 1-, 3-, and 5-year survival. Immune analyses indicated associations between MZT1 expression and tumor microenvironmental features. Single-cell analysis showed that MZT1 expression was predominantly enriched in malignant epithelial cells and associated with proliferative cellular states. Protein-level validation supported concordance with transcriptomic findings. CONCLUSION: MZT1 is a proliferation-associated marker that integrates clinical risk, transcriptional programs, cellular heterogeneity, and predictive modeling in LUAD, providing a potential framework for biomarker development and risk stratification.

Humans

Rapid transcriptional reprogramming underlies Fusarium wilt resistance in strawberry: insights from comparative physiological and transcriptomic analyses.

INTRODUCTION: Fusarium wilt caused by Fusarium oxysporum f. sp. fragariae (Fof) severely constrains strawberry production, yet the underlying resistance mechanisms remain unclear. METHODS: A total of 64 strawberry germplasm accessions were evaluated for Fusarium wilt resistance. Integrated physiological and transcriptomic analyses were subsequently performed using the highly resistant cultivar 'Akihime' (ZJ) and the highly susceptible cultivar 'Ning Yu' (NY). RESULTS: Resistant resources were abundant, particularly among wild strawberry accessions. Compared with NY, ZJ exhibited higher soluble sugar accumulation, reduced oxidative damage, and increased peroxidase (POD) and phenylalanine ammonia-lyase (PAL) activities. Transcriptomic analyses revealed distinct temporal response patterns: ZJ underwent rapid and extensive transcriptional reprogramming at 24 h post-inoculation, whereas NY showed limited early responses but pronounced changes at 120 h. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that the early response of ZJ was mainly associated with stress-related processes, jasmonic acid-mediated signaling, transmembrane transport, plant-pathogen interaction, mitogen-activated protein kinase (MAPK) signaling, glutathione metabolism, plant hormone signal transduction, and secondary metabolism. Quantitative real-time polymerase chain reaction (qRT-PCR) validation supported the RNA-seq results and identified candidate genes associated with pathogen recognition, signaling, redox regulation, and protein homeostasis. DISCUSSION: These results indicate that rapid early immune activation and coordinated physiological and metabolic reprogramming are closely associated with strawberry resistance to Fof and provide useful germplasm and candidate genes for future functional validation and resistance breeding.

Fusarium oxysporum f. sp. fragariae

FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.

Transcriptome-wide association studies (TWAS) integrate genome wide association studies with expression quantitative trait locus reference panels to identify genes associated with traits of interest. However, linkage disequilibrium and correlated gene expression can induce spurious TWAS signals, motivating fine mapping methods to prioritize putatively causal genes within associated loci. The rapid growth of large-scale phenomic resources (e.g. electronic health records (EHRs)) has shifted genetic studies from single-trait analyses to phenome-wide investigations that jointly evaluate many closely related phenotypes. We introduce FM-GPT (Fine-mapping of causal Genes for Phenome-wide Transcriptome-wide association studies), a novel Bayesian fine mapping method for prioritizing causal genes across multiple correlated phenotypes with potentially mixed outcome types (e.g., binary, count or continuous) in phenome-wide TWAS. FM-GPT performs gene-guided dimension reduction of the phenotypes and reveals pleiotropic or phenotype-specific effects of the identified genes. In simulations, FM-GPT identified true causal genes more accurately than other fine mapping methods while controlling false positives. We applied FM-GPT to two applications using data from UK Biobank: a brain-wide genetic analysis of MRI data derived regional cortical thickness measures and a phenome-wide genetic analysis of clinical phenotypes derived from EHR data. FM-GPT greatly narrowed down the set size of putatively causal genes and identified: 1. genes with pleiotropic effects on regional cortical thickness across the cerebral cortex, including five genes BCAS3, LRRC37A, NOS2P3, ARL17B and UBB on chromosome 17 regulating neuronal morphology and cortical organization; and 2. genes that influence multiple medical conditions across the circulatory, metabolic, digestive, respiratory and genitourinary systems, revealing two major axes of variation among these conditions that point to a potential trade-off in gene regulation between immune and metabolic functions. These results highlight FM-GPT's power to disentangle complex gene-phenotype relationships in large-scale phenome-wide studies, uncovering shared biological mechanisms across diverse human traits and advancing translational and comorbidity research.

Bayesian fine mapping

Retinal Transcriptome-Wide Association Study Identifies Novel Alzheimer's Disease Risk Genes.

INTRODUCTION: Alzheimer's disease (AD) is the leading cause of dementia worldwide. The retina shares molecular pathways with the brain, yet no study has systematically linked retinal gene expression to AD risk. METHODS: We performed transcriptome-wide association studies (TWAS) using two independent retinal eQTL panels (Strunz et al., n = 311; EyeGEx, n = 406) and a large meta-analyzed AD genome-wide association study (GWAS) (Bellenguez et al., 111,326 cases, 677,663 controls). Genes were further validated with GWAS in the independent Alzheimer's Disease Sequencing Project (ADSP) using a matched eQTL-panel strategy. RESULTS: We identified 62 AD-associated genes across the two eQTL panels using Bellenguez et al. as the discovery cohort. Of these, 31 were replicated in the ADSP cohort. The findings highlight shared complement-mediated immune dysregulation (CD55, CD46, TREM2) and provide functional transcriptomic evidence to prioritize novel causal drivers of AD pathogenesis, including STYX and the LRRC37 gene family. DISCUSSION: Retinal data capture core AD genetic architecture and reveal novel risk genes, highlighting the retina as a molecularly informative tissue for dementia research.

Alzheimer’s disease

MKMC enables reference-free transcriptomic analysis using k-mer representations.

Traditional RNA-seq analysis depends heavily on genome alignment and gene annotation, limiting its utility in non-model organisms and introducing biases that can obscure regulatory complexity. We present MKMC (Multi-sample Kmer Counter), a scalable, reference-free toolkit for RNA-seq analysis that leverages k-mer-based statistics to detect biological variation without requiring alignment. MKMC integrates fast k-mer counting, abundance matrix generation, normalization, dimensionality reduction, and differential analysis into a unified workflow. Across diverse datasets, MKMC recapitulates key biological signals-including sex differences in killifish liver-and matches alignment-based pipelines in differential expression analysis and transcriptomic age prediction. Notably, MKMC detects isoform-specific events missed by traditional methods, one of which we validated using in situ hybridization. These results reveal previously hidden isoform-level regulatory events that contribute to sex- and age-associated transcriptional programs. MKMC offers a robust, extensible alternative to alignment-based approaches, enabling transcriptomic discovery across both model and non-model systems. While we focus here on RNA-seq as a primary application, MKMC is broadly applicable to any k-mer-based analysis of next-generation sequencing data.

MKMC

A single-nucleus and spatial transcriptomic atlas of poplar leaves reveals the regulation of leaf polarity and cuticle deposition.

Leaf adaxial-abaxial polarity is fundamental for plant morphogenesis and environmental adaptation through asymmetric cell differentiation. Emerging evidence reveals dorsoventral metabolic gradients act downstream of transcriptional networks to fine-tune cellular specialization. While conserved transcription factors (e.g., HD-ZIP III and KANADI) establish initial polarity, the molecular networks driving position-specific cellular differentiation and their integration with metabolic adaptation remain unclear. Leveraging single-nucleus and spatial transcriptomics, we resolve major cell classes (mesophyll, epidermal, and vascular-associated) and their adaxial-abaxial subtypes, revealing dorsoventral polarity in transcriptional profiles and metabolic pathways. Adaxial cells are enriched in phenylpropanoid/flavonoid biosynthesis, while abaxial cells show preferential activation of stress and hormone signaling. Notably, we identify MYC2 as a key regulator of adaxial cuticle biosynthesis, binding to promoters of lipid biosynthetic and transport genes (e.g., CER10 and LTPG1) and promoting cuticle thickening. Our study uncovers how positional identity shapes transcriptional and metabolic polarity in leaves, with MYC2 emerging as a central regulator coordinating organ-specific adaptations. These findings provide insights into the spatial regulation of plant development and stress resilience, offering potential strategies for engineering stress-tolerant woody crops.

Plant Leaves