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PubMed2025

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↗

PubMed2026

Comparative transcriptome analysis reveals ncRNA-mediated regulatory networks associated with muscle crispiness in grass carp.

Non-coding RNAs (ncRNAs) have been demonstrated to be involved in muscle development and to function as key regulators. However, the molecular mechanism underlying muscle crispiness in grass carp (GC) remains poorly understood, and whether these ncRNAs are involved in its regulation is still unknown. In the current investigation, differentially expressed (DE) RNAs (including lncRNAs, circRNAs, miRNAs, and mRNAs) were identified; concomitantly, target genes prediction was conducted, and functional and signaling pathway enrichment analyses were performed. Pathways related to muscle crispiness were identified, and the competitive endogenous RNA (ceRNA) (lncRNA/circRNA-miRNA-mRNA) regulatory network was further constructed. The results showed that a total of 126 DE-lncRNAs, 17 DE-circRNAs, 329 DE-miRNAs, and 442 DE-mRNAs were identified in muscle tissues of both the GC and crisp grass carp (CGC). GO and KEGG enrichment analyses revealed that target genes of DE-ncRNAs were significantly enriched in signaling pathways, including structural constituents of muscle, apoptosis, oxidative phosphorylation, and regulation of actin cytoskeleton, suggesting that these pathways may be involved in muscle texture remodeling. Subsequently, DE-RNAs enriched in related pathways were identified, and a core ceRNA regulation network comprising 3 lncRNAs, 4 circRNAs, 3 miRNAs, and 17 mRNAs was constructed. Additionally, 10 DE-RNAs from randomly selected groups were validated by qRT-PCR. Our findings not only provide scientific evidence elucidating the molecular mechanisms underlying muscle crispiness in GC but also establish a foundation for studying changes in muscle textural qualities across other fish species.

Animals↗

PubMed2026

Integrated methylome and transcriptome analysis provides insight into DNA methylation-mediated networks in sexual dimorphism of Vernicia montana.

BACKGROUND: Sexual dimorphism is fundamental to reproduction in dioecious plants and is regulated by both genetic and epigenetic mechanisms. DNA methylation is a central epigenetic mark known to influence phenotypic variation in plants. However, its specific role in shaping sexual dimorphism in dioecious trees remains poorly understood. To address this question, we performed integrated genome-wide DNA methylome and transcriptome analyses of four tissue types in the dioecious tung tree (Vernicia montana), including male and female flower buds and their corresponding leaves. RESULTS: Our analysis revealed distinct DNA methylation patterns between male and female tissues. Notably, the coordination between DNA methylation reprogramming and transcriptional regulation appeared to be more strongly associated with reproductive development than with vegetative growth in V. montana. We identified a set of sex-biased genes that may reflect different reproductive strategies between the sexes. Further analysis identified several key transcription factors (TFs) potentially associated with promoter differentially methylated regions (DMRs), including flowering-time regulators (e.g., FRS5, REM16, and VRN1) and TFs involved in hormone signaling pathways such as jasmonic acid, auxin, and salicylic acid signaling. Cis-regulatory element analysis showed that some promoter DMRs overlapped with hormone response elements related to abscisic acid, auxin, and gibberellin. Co-expression network analysis further revealed potential regulatory correlations among promoter DMR-mediated TFs, hormone-responsive pathways, and key floral development regulators. CONCLUSIONS: Collectively, our results suggest that interactions among DNA methylation, transcriptional regulation, and hormone-responsive pathways may contribute to the establishment of sexual dimorphism in V. montana. This study provides the first integrated view of these regulatory layers in V. montana and supports a species-specific regulatory framework for understanding the epigenetic basis of sexual dimorphism in this economically important dioecious tree. The proposed framework is based on multi-omics analyses and warrants further validation through targeted functional studies.

DNA Methylation↗

PubMed2026

Stage-Independent Real-Time Subtype Classification and Comprehensive Biopsy Profiling of Urothelial Carcinomas by the Lund Taxonomy System.

Bladder cancer is a heterogeneous malignancy with diverse clinical outcomes, and conventional pathological assessment alone is insufficient to capture its underlying biology. Gene expression profiling can stratify tumors into molecular subtypes with prognostic and predictive potential, but the reliability of transcriptomic classification and its clinical utility remains to be established. The translational/observational UROSCANSEQ study (ISRCTN15459149) prospectively evaluates RNA-based Lund Taxonomy (LundTax) molecular subtype classification in a clinical setting. Among 784 consecutive biopsies collected between 2018 and 2022, RNA sequencing was successful for 90% of all biopsies, encompassing 662 bladder cancer patients with a stage distribution of 48% Ta, 27% T1, 24% ≥T2, and 1% CIS. We demonstrate that the LundTax subtype classification algorithm, applied to individual samples, accurately identifies cancer cell phenotypes with characteristic gene and protein expression patterns in a manner robust to RNA quality, data preprocessing strategies, and batch effects, supporting its clinical feasibility across both non-muscle-invasive and muscle-invasive disease. We further extend the LundTax framework by incorporating single-sample molecular risk scores reflecting tumor grade, proliferation, and progression risk, as well as tumor microenvironment signatures. Both risk scores and overall immune and stromal content in biopsies were significantly associated with an increased risk of clinical progression in noninvasive disease. In a separate analysis of the relative cellular composition of the tumor microenvironment, however, only the fraction of natural killer cells remained significant. Together, the expanded LundTax system provides a comprehensive molecular portrait of individual tumor biopsies. By explicitly separating cancer cell-intrinsic phenotypes, prognostic indexes, and microenvironmental signals, the framework minimizes biological confounding and establishes a strong foundation for future studies evaluating clinical outcomes and treatment responses.

Humans↗

PubMed2025

Dual genetic loci and flavonoid metabolism orchestrate fruiting body coloration in Flammulina filiformis: a multi-omic roadmap for fungal pigmentation.

BACKGROUND: The fruiting bodies of macrofungi exhibit diverse coloration, traditionally attributed to melanin and carotenoid biosynthesis. This study is the first to reveal that flavonoids, rather than these classical pigments, are the predominant contributors to yellow pigmentation in the Flammulina filiformis. OBJECTIVE: To uncover the genetic basis and key regulatory genes involved in pigment formation in F. filiformis fruiting bodies, and to establish a model framework for studying color genetics in macrofungi. METHODS: Metabolomic profiling was conducted on yellow and white F. filiformis fruiting bodies to identify key pigment components. A segregating population was constructed, followed by integrated multi-omics analyses-including bulk segregant analysis (BSA), genome-wide association study (GWAS), and transcriptomics-to map regulatory loci and candidate genes. Functional roles were validated via genetic transformation and protein structural modeling. RESULTS: Flavonoid accumulation was identified as the biochemical hallmark of pigmented fruiting bodies. Genetic analysis revealed a dual regulatory mechanism: a qualitative locus governing pigmentation presence and a quantitative trait determining color intensity. Combined BSA and GWAS pinpointed a major locus, Ffcrs, within a recombination-suppressed region. Transcriptomic analysis identified two key regulators, Ffakr (a transcriptional activator) and Ffpal (encoding phenylalanine ammonia-lyase). Functional verification via transformation, structural modeling, and metabolite profiling in transgenic lines confirmed their essential roles in flavonoid biosynthesis and pigmentation. CONCLUSION: This study uncovers a flavonoid-based pigmentation mechanism in F. filiformis and elucidates a complex genetic architecture shaped by both qualitative and quantitative loci, providing a new paradigm for understanding pigment formation in macrofungi. The identified regulatory factors establish a molecular foundation for the precise manipulation of economically important pigmentation traits in edible mushroom.

Flavonoids↗

PubMed2026

Epigenetic alterations of AKT1 orchestrate a metabolic reprogramming in advanced lipedema: translational insights from an integrated multi-omics study.

BACKGROUND: lipedema is a chronic, progressive adipose disorder predominantly affecting women, characterized by painful, symmetrical subcutaneous fat accumulation, and typically resistant to lifestyle interventions. The pathophysiology of advanced-stage lipedema remains poorly defined, and no validated biomarkers or targeted therapies are currently available. METHODS: in this observational study, we applied a comprehensive multi-omics approach to dissect the molecular and metabolic alterations underlying late-stage lipedema. RESULTS: Genome-wide DNA methylation profiling identified over 5,000 differentially methylated CpG sites affecting genes involved in receptor tyrosine kinase signaling, phospho-metabolism, and immune pathways. Transcriptomic analysis revealed profound downregulation of mitochondrial functions, including oxidative phosphorylation, the TCA cycle, and fatty acid β-oxidation, alongside disruption of the sirtuin pathway and extracellular matrix remodeling. Integrative analysis pinpointed AKT1 as a central regulatory node: its promoter region was hypomethylated, correlating with increased gene expression and protein phosphorylation. Metabolomic profiling confirmed AKT1-linked metabolic dysregulation, including altered levels of L-arginine, NADP+, ATP, guanosine, glycerol, and glutamate, indicating impaired redox balance and energy metabolism. Trans-omic network analysis positioned AKT1 at the intersection of multiple dysregulated pathways, suggesting its key role in advanced-stage lipedema. CONCLUSIONS: the consistent enhancing of AKT pathway signaling across omic layers highlights its potential not only as a biomarker for disease stratification but also as a putative druggable target for therapeutic intervention. These findings offer new mechanistic insights into lipedema pathophysiology and provide a rationale for future personalized treatment strategies guided by AKT1-centric molecular profiling.

Proto-Oncogene Proteins c-akt↗

PubMed2025

CD40 transcriptomic expression patterns across malignancies: implications for clinical trials of CD40 agonists.

BACKGROUND: CD40 is a T-cell co-stimulatory receptor targeted by next-generation immunotherapies. We conducted a pan-cancer transcriptome analysis of CD40, its ligand, and related immune markers to evaluate co-expression patterns and clinical outcomes. METHODS: We analyzed transcriptome data for CD40, its ligand, and other common checkpoints and co-stimulators (PD-1, PD-L1, PD-L2, CTLA-4, LAG-3, ICOS, CD27, CD28, OX40, and GITR). RNA expression was classified as high (75-100th percentile), moderate (25-74th), or low (0-24th) against a reference population of 735 previously tested solid tumors. RESULTS: Of 514 patients, 114 (22%) showed high, 247 (48%) moderate, and 153 (30%) low CD40 RNA expression. High CD40 expression was most frequent in liver and bile duct (42%), pancreatic (42%), and ovarian (40%) cancers. Both high CD40 and low-moderate CD40 ligand expression-potentially conducive to CD40 agonist therapy-was most frequent in ovarian (33%) and pancreatic (24%) cancer. In both UCSD (N = 514) and TCGA (N = 10,953) cohorts, high CD40 expression significantly correlated with high CD28 and GITR. High CD40 RNA levels were not prognostic for overall survival (OS) from metastatic disease (P = 0.2) (n = 272 immune checkpoint inhibitor (ICI)-naïve patients). High CD40 expression correlated with longer OS from immunotherapy initiation (n = 217 ICI-treated patients; P = 0.04, univariable analysis), but not multivariable analysis, suggesting it may not be an independent predictive biomarker. CONCLUSION: High CD40 expression correlated with liver and bile duct, pancreatic, and ovarian cancers, as well as with CD28 and GITR transcripts. Immune marker co-expression in individual patients merits further exploration for the development of CD40-based and other immunotherapy interventions.

Humans↗

PubMed2026

Genome-wide analysis of the plant-specific PLATZ gene family in Taraxacum kok-saghyz and its roles in response to drought and salt tolerance.

Abiotic stress severely limits plant growth and productivity. Taraxacum kok-saghyz Rodin (TKS), known for its environmental resilience, represents a valuable resource for identifying stress-tolerant genes to improve stress-adaptive crops. Plant AT-rich protein and zinc-binding protein (PLATZ) transcription factors serve as core regulators of plant growth, developmental processes, and adaptive responses to various stress conditions; however, they remain uncharacterized in TKS. Here, we identified 10 TksPLATZ genes through a whole-genome analysis. Phylogenetically, these genes were grouped into five distinct evolutionary branches. Promoter sequence analysis revealed multiple types of cis-acting regulatory elements that are connected with hormonal signal responses and environmental stress adaptation. Integrated analysis of transcriptome datasets and RT-qPCR validation demonstrated that TksPLATZ genes display tissue-specific expression profiles and show distinct responsive patterns to drought and salt stress treatments. Among them, TksPLATZ1, TksPLATZ2 and TksPLATZ7 were markedly induced under both stressors and were selected for further functional study. We demonstrated that TksPLATZ1, TksPLATZ2 and TksPLATZ7 localize to the cell nucleus and act as transcriptional activators and repressors, respectively. Phenotypic data from overexpression experiments in plants confirm that heterologous expression of TksPLATZ1, TksPLATZ2, and TksPLATZ7 enhances the tolerance of Arabidopsis to salt and osmotic stress. These findings provide valuable genetic resources for improving plant tolerance to environmental stresses.

Salt Tolerance↗

PubMed2025

Single-cell analysis of dup15q syndrome reveals developmental and postnatal molecular changes in autism.

Duplication 15q (dup15q) syndrome is a leading genetic cause of autism spectrum disorder, offering a key model for studying autism-related mechanisms. Using single-cell and single-nucleus RNA sequencing of cortical organoids from dup15q patient-derived iPSCs and post-mortem brain samples, we identify increased glycolysis, disrupted layer-specific marker expression, and aberrant morphology in deep-layer neurons during fetal-stage organoid development. In adolescent-adult postmortem brains, upper-layer neurons exhibit heightened transcriptional burden related to synaptic signaling, a pattern shared with idiopathic autism. Using spatial transcriptomics, we confirm these cell-type-specific disruptions in brain tissue. By gene co-expression network analysis, we reveal disease-associated modules that are well preserved between postmortem and organoid samples, suggesting metabolic dysregulation that may lead to altered neuron projection, synaptic dysfunction, and neuron hyperexcitability in dup15q syndrome.

Humans↗

PubMed2026

In silico analysis of SH3BP2 genomic alterations and expression profiles in CRC.

AIM: Colorectal cancer (CRC) is a widespread health issue that attains high mortality. The adaptor protein SH3BP2 amplification results in metabolic changes, oxidative stress, NK cell activity, and inflammation. The NK cells are capable of destroying tumor cells without prior activation, help prevent metastasis, and have prognostic value. Targeting SH3BP2 to regulate NK cell activity in the TME could enhance CRC-based immunotherapy. MATERIALS AND METHODS: The cancer hallmark tool helps in understanding SH3BP2 hallmark annotation. Utilizing the STRING tool and the KEGG pathway, protein functional enrichment and PPI networking were analyzed. TIMER 2.0 was used for immune cell infiltration correlation analysis, and UALCAN was used for CPTAC-based protein expression profiling. RESULTS AND CONCLUSIONS: The GEO (GSE9348) dataset showed SH3BP2 is upregulated in CRC (log2 fold change = 1.18). GEO, TCGA, and cBioPortal revealed SH3BP2 alterations in CRC cases, potentially aiding immune evasion. Mutations in SH3BP2 influence cancer growth, suppressing tumors or promoting them by activating NF-κB and affecting immune responses through WNT/β-catenin, PI3K, MAPK, and JAK-STAT pathways. Overall, SH3BP2 plays a key role in cancer growth and immune regulation, making it a promising target for CRC therapy. Further experimental validation is needed to demonstrate its diagnostic and therapeutic potency.

Humans↗

PubMed2026

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

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

Single-Cell Analysis↗

PubMed2026

NextLongIso: a comprehensive Nextflow pipeline for multi-dimensional long-read RNA-seq analysis.

SUMMARY: Long-read RNA sequencing technologies, including Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), enable direct characterization of full-length transcripts and transcriptome complexity. However, analysis of long-read RNA-seq data remains fragmented across multiple tools, limiting the ability to obtain a unified view of transcript structure, expression, and regulatory variation in long-read transcriptomes. We present NextLongIso, a scalable and reproducible Nextflow pipeline that enables coordinated analysis of multiple layers of transcript regulation. Rather than focusing solely on transcript reconstruction, NextLongIso integrates transcript discovery with downstream regulatory analyses to jointly characterize alternative splicing, isoform switching, transcript boundary dynamics (including alternative promoters and polyadenylation), and transposable element-associated transcription from both PacBio and ONT datasets. By eliminating complex cross-tool data harmonization, this unified framework facilitates the transition from transcript identification to functional interpretation of transcriptomic variation. AVAILABILITY AND IMPLEMENTATION: NextLongIso is implemented in Nextflow and is freely available at github: https://github.com/YidanSunResearchLab/nf-LongIso.git and Zenodo: https://doi.org/10.5281/zenodo.21049837.

Software↗

PubMed2026

Structural and functional gastrointestinal abnormalities in ACTA2 R179H mice modeling multisystemic smooth muscle dysfunction syndrome.

Multisystemic smooth muscle dysfunction syndrome (MSMDS) is a rare disorder caused by ACTA2 mutations, including the R179H variant, which alters actin filament stability and dynamics and smooth muscle contractility. Cardiovascular complications dominate its clinical presentation, but gastrointestinal (GI) dysfunction significantly affects quality of life. To investigate the structural, functional, and cellular basis of gut dysmotility in MSMDS, we reviewed clinical data from 24 patients with MSMDS and studied the ACTA2 R179H mouse model. Patients exhibited severe gut dysmotility, with 75% requiring medication for chronic constipation. ACTA2 mutant mice displayed cecal and colonic dilatation, reduced intestinal length, and disrupted colonic migrating motor complexes. Delayed whole-gut transit and impaired contractile responses to electrical and pharmacological stimulation were observed. Transcriptomic analysis revealed significant actin cytoskeleton-related gene changes in smooth muscle cells, and immune profiling identified increased lymphocytic infiltration. Despite functional abnormalities, there were no obvious changes in the enteric nervous system. These findings establish ACTA2 mice as a robust model for studying GI pathology in MSMDS, elucidating the role of smooth muscle dysfunction in gut dysmotility. This model provides a foundation for developing targeted therapies aimed at restoring intestinal motility by directly addressing actin cytoskeletal disruptions in smooth muscle cells.

Animals↗

PubMed2026

Transcriptome-based high-frequency recurrence index predicts frequent recurrence in non-muscle-invasive bladder cancer after Bacillus Calmette-Guérin therapy.

BACKGROUND: High-frequency recurrence (HfR, ≥ 2 recurrences) in non-muscle-invasive bladder cancer (NMIBC) poses a significant clinical burden. Current risk models, such as the European Organization for Research and Treatment of Cancer (EORTC), the European Association of Urology (EAU), and the UROMOL classification, offer limited predictive accuracy for identifying patients at risk for frequent recurrence despite appropriate treatment. METHODS: A 75-gene high-frequency recurrence index (HfRI) was constructed by selecting recurrence-associated genes using differential expression and Cox regression analyses. The HfRI was computed as a weighted sum of normalized gene expression values. The model was trained on a discovery cohort and validated in multiple cohorts (n = 1379) using machine-learning approaches. Clinical relevance was assessed using recurrence-free survival (RFS) and Cox models, and predictive performance was compared with that of the EORTC, EAU, and UROMOL classifications using the area under the curve (AUC) and the concordance index (c-index). RESULTS: The HfRI robustly stratified patients into high-risk and low-risk groups across six independent NMIBC cohorts. Patients classified as HfRI-high had a significantly greater likelihood of experiencing ≥ 2 recurrences (χ2, p = 0.001) and showed markedly reduced RFS (log-rank test, p < 0.001). The adverse prognostic effect of the HfRI persisted even among patients treated with BCG therapy (log-rank test, p = 0.02). Multivariate analysis revealed that the HfRI was an independent predictor of HfR (HR = 2.82, 95% CI = 1.89-4.20, p < 0.001). Compared with established clinical risk classifiers, the HfRI demonstrated superior predictive performance (AUC = 0.736, c-index = 0.673) in terms of the EORTC (AUC = 0.594), EAU (AUC = 0.557) risk groups, and UROMOL2021 (AUC = 0.596) classification. Pathway analysis revealed that HfRI-high tumors were characterized by upregulation of cell cycle progression and DNA replication pathways, accompanied by suppression of immune signaling pathways. These biological features provide a mechanistic explanation for the reduced responsiveness to intravesical BCG therapy, underscoring the role of HfRI not only as a predictor of recurrence risk but also as a biomarker capable of identifying patients unlikely to benefit from standard BCG treatment. CONCLUSIONS: HfRI represents a robust, transcriptome-based tool for predicting frequent recurrence in NMIBC patients. The HfRI supports earlier identification of patients at risk of high-frequency recurrence, thereby supporting personalized treatment strategies.

Humans↗

PubMed2000

Dynamic architecture of the yeast cell cycle uncovered by wavelet decomposition of expression microarray data.

Wavelet analysis has been applied to yeast cell cycle expression microchip data to reveal large-scale temporal structures and ubiquitous oscillations in mRNA levels. Discrete intervals in time within the cell cycle when expression levels changed were visualized as contour maps in which points of transition in gene expression among all 6178 genes were plotted as a function of cell cycle time. Time-frequency analysis using wavelet transforms supported the direct visualization and led to the conclusion that the predominant period is not the cell cycle but a higher frequency, 40 min, submultiple of the cycle. Each of the 6178 gene expression profiles was dissected by wavelet decomposition into all permitted frequencies from the Nyquist limit to roughly twice the cell cycle length. Transitions associated with maximum up- or down-regulation of mRNA levels appear as bands at circa 40-min intervals, half the length of the cycle, through two cell cycles. More than two thirds of the genes, including many of the cyclins, showed this half-cycle periodicity. Gene expression and events within the yeast cell cycle may be regulated by an attractor whose fundamental period is an emergent property of dynamic interactions within the yeast transcriptome.

Cell Cycle↗

PubMed2000

Comprehensive analyses of prostate gene expression: convergence of expressed sequence tag databases, transcript profiling and proteomics.

Several methods have been developed for the comprehensive analysis of gene expression in complex biological systems. Generally these procedures assess either a portion of the cellular transcriptome or a portion of the cellular proteome. Each approach has distinct conceptual and methodological advantages and disadvantages. We have investigated the application of both methods to characterize the gene expression pathway mediated by androgens and the androgen receptor in prostate cancer cells. This pathway is of critical importance for the development and progression of prostate cancer. Of clinical importance, modulation of androgens remains the mainstay of treatment for patients with advanced disease. To facilitate global gene expression studies we have first sought to define the prostate transcriptome by assembling and annotating prostate-derived expressed sequence tags (ESTs). A total of 55000 prostate ESTs were assembled into a set of 15953 clusters putatively representing 15953 distinct transcripts. These clusters were used to construct cDNA microarrays suitable for examining the androgen-response pathway at the level of transcription. The expression of 20 genes was found to be induced by androgens. This cohort included known androgen-regulated genes such as prostate-specific antigen (PSA) and several novel complementary DNAs (cDNAs). Protein expression profiles of androgen-stimulated prostate cancer cells were generated by two-dimensional electrophoresis (2-DE). Mass spectrometric analysis of androgen-regulated proteins in these cells identified the metastasis-suppressor gene NDKA/nm23, a finding that may explain a marked reduction in metastatic potential when these cells express a functional androgen receptor pathway.

DNA, Complementary↗

PubMed2026

Single-cell capture of on-ART SIV transcription reveals TGF-β-mediated metabolic control of viral latency.

We previously demonstrated that blocking TGF-β with galunisertib, a safe, orally available small drug, reactivated latent SIV in vivo by shifting T cells toward a transitional effector phenotype. Here, we investigated the mechanisms underlying this effect using single-cell RNA sequencing, metabolic profiling, and high-dimensional spectral flow cytometry of samples from SIV-infected, antiretroviral therapy-treated (ART-treated) macaques before and after galunisertib. To characterize virus-transcribing, infected cells during ART, we developed a novel, sensitive SIV Transcripts Capture Assay (SCAP) that detected 127 SIV-expressing cells within lymph node single-cell transcriptome libraries. Galunisertib drove broad metabolic reprogramming in CD4+ T cells, with transcriptional upregulation of inflammatory and mitochondrial biosynthesis pathways, confirmed by Seahorse profiling. Metabolomics revealed increased energy metabolites and amino acids and enhanced metabolic flux without proliferation. SIV transcript-positive cells before galunisertib were metabolically quiescent compared with cells without detectable viral transcripts. After galunisertib, virus-expressing cells showed a dramatic metabolic activation, with upregulation of glycolysis, fatty acid metabolism, and TNF-α signaling. High-dimensional flow cytometry demonstrated effects beyond CD4+ T cells, including fewer tissue-resident memory T cells, but more inflammatory macrophages. In conclusion, SCAP represents a specific tool for characterizing rare SIV-infected cells transcribing virus during ART, and it reveals TGF-β as a key mediator of viral latency in vivo through metabolic suppression.

Virus Latency↗

PubMed2026

Integrating GWAS and Transcriptome Analysis Identifies Candidate Genes for Kernel Starch Quality Traits in Maize.

Maize (Zea mays L.) starch quality is a complex trait with significant implications for grain processing and industrial applications. However, the genetic basis underlying starch quality, particularly for gelatinization and thermodynamic properties, remains poorly understood. In this study, we evaluated 12 starch quality traits, including seven gelatinization characteristics, four thermodynamic traits, and kernel starch content (KSC) in a diverse panel of 335 maize inbred lines. Considerable phenotypic variation was observed for all traits. A total of 228 quantitative trait loci (QTLs) were significantly associated with 12 starch quality traits through genome-wide association studies (GWAS). By integrating a dynamic transcriptome analysis of two maize inbred lines with contrasting starch quality, we identified 60 candidate genes. One gene, waxy1, encoding a starch synthase, was found to be associated with enthalpy of gelatinization (ΔHgel) and pasting temperature (Ptemp). Six variants in waxy1 contributed to natural variation in ΔHgel and Ptemp, and a cost-effective InDel and two PARMS-based molecular markers were developed and validated in 144 maize inbred lines, enabling efficient marker-assisted selection. Our findings provide key genes and molecular markers for high-quality maize breeding with improved starch properties.

Zea mays↗