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PubMed2026

High-fat diet-responsive DNM1 promotes hepatocellular carcinoma progression and predicts poor prognosis in viral-associated patients.

Hepatocellular carcinoma (HCC) arises from diverse etiologies, among which metabolic dysfunction-associated liver disease and chronic viral hepatitis are the two major drivers worldwide. However, the molecular mechanisms linking metabolic stress to HCC progression remain incompletely understood. Dynamin-1 (DNM1), primarily known for its role in vesicular trafficking, has emerged as a potential oncogene, yet its prognostic and functional significance in HCC remains largely unexplored. Here, we investigated the role of DNM1 in high-fat diet (HFD)-associated hepatocarcinogenesis. Transcriptomic profiling was conducted to identify differentially expressed genes between normal and high-fat diet murine models, with human orthologs mapped. Clinical relevance was validated using The Cancer Genome Atlas (TCGA-LIHC) dataset. Survival analysis, GSEA (Gene Set Enrichment Analysis), and subgroup stratifications based on viral hepatitis status were performed. In vitro, loss-of-function assays (shRNA knockdown) were executed in HepG2 and SK-Hep1 cell lines to assess cell viability and migration. DNM1 was significantly upregulated in high-fat diet models. In the TCGA-LIHC cohort, high DNM1 expression was an independent risk factor for poor overall survival (HR=1.44, P=0.039) and correlated with advanced tumor stages (Stage III+IV, P=0.010). In vitro knockdown of DNM1 profoundly impaired cell proliferation and migration in HCC cell lines. Strikingly, DNM1 expression was further elevated in patients with concurrent viral hepatitis (P=0.009). GSEA revealed that high DNM1 expression was positively associated with viral infection pathways and negatively correlated with critical immune responses, including interferon-alpha/gamma responses and host immune cytolysis. Survival analysis stratified by four subgroups demonstrated that patients with both viral infection and high DNM1 expression exhibited the worst prognosis (Overall Log-rank P < 0.001). Our findings identify DNM1 as a high-fat diet-responsive regulator that links metabolic stress to hepatocellular carcinoma progression. Elevated DNM1 expression promotes malignant phenotypes in HCC and identifies a subgroup of viral-associated patients with particularly poor prognosis, highlighting DNM1 as a potential prognostic biomarker and therapeutic target.

Hepatocellular carcinoma (HCC)↗

PubMed2026

Functional Annotation of the Major Histocompatibility Complex Locus.

The human major histocompatibility complex (MHC) locus has the greatest density of disease-associations in the human genome, including links to over 100 polygenic disorders. Its complex haplotype structure, rich gene density, and high degree of linkage disequilibrium combine to make deciphering the gene regulatory logic of the MHC locus extremely challenging. Employing complementary high-throughput CRISPR interference (CRISPRi) and activation (CRISPRa) epigenetic screens coupled with single-cell transcriptome profiling across three distinct human cell types, we identified hundreds of new connections between cis -regulatory elements (CREs) and their target genes in this locus. These CRE-gene links are largely cell type-specific and act as enhancers. Additionally, some CREs have complex features, including harboring both active and repressive histone marks, lacking chromatin accessibility, targeting multiple genes, or acting as silencers. Computational methods fail to predict a majority of these CRE-gene connections. These findings emphasize the potential for functional perturbation experiments to dissect complex loci and reveal shared and cell type-specific regulatory mechanisms relevant to genomics of complex diseases. Collectively, this study provides a unique resource for understanding the complex regulatory landscape within the MHC locus and supports the need for creating new models that encompass CRE-gene interactions, cell type-specific gene expression, and disease genetics in the noncoding genome.

Journal Article↗

PubMed2026

STN1 upregulation promotes PARPi resistance in BRCA2-deficient cancer cells via replication fork protection and suppression of ssDNA gap formation.

PARPi are effective therapy for BRCA1/2 mutant cancers, yet recurrent PARPi resistance frequently develops. The underlying mechanism of PARPi resistance remains largely unresolved. Here, we identify STN1, a component of the CTC1/STN1/TEN1 (CST) complex, as a modulator of PARPi resistance in BRCA2-deficient cells. RNA-seq analysis of PARPi-resistant cancer cells from BRCA2-mutated backgrounds shows largely distinct transcriptomic profiles with limited overlap, suggesting multiple routes to resistance. Notably, STN1 is consistently upregulated in resistant cells. We observe that overexpression of STN1 enhances Olaparib resistance in multiple BRCA2-deficient cell lines and alleviates DNA damage under replication stress. Mechanistically, we find that STN1 overexpression increases RAD51 loading to stalled replication forks while restricting MRE11 recruitment in BRCA2-deficient cells, thereby protecting stalled forks from nascent-strand degradation. Furthermore, STN1 overexpression rescues the accumulation of ssDNA gaps, a major determinant of PARPi sensitivity in BRCA2-deficient cells. Taken together, these findings suggest that elevated STN1 levels can partially compensate for BRCA2 loss by stabilizing stalled replication forks and limiting ssDNA gap accumulation. Our study uncovers a STN1-dependent pathway of replication stress tolerance that promotes PARPi resistance independently of homologous recombination restoration, highlighting STN1 as a potential biomarker and mechanistic contributor to therapeutic resistance in BRCA2-mutated cancers.

PARPi resistance↗

PubMed2026

Influenza A Virus Coinfection Alters Streptococcus pneumoniae Gene Expression during Upper Respiratory Tract Colonization.

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

Journal Article↗

PubMed2003

Hepatocellular carcinoma and hepatitis virus.

Integrated hepatitis B virus (HBV) DNA is present in many hepatocellular carcinomas (HCC), suggesting that HBV has a direct oncogenic effect through interaction with transformation-associated genes. Many genes involved in cell cycle regulation (cyclins, kinases, negative regulators, Wnt-beta-catenin) and the transcriptome profile are deregulated or altered in most HCC patients. The HBx protein, potentially oncogenic via multistep carcinogenesis, modifies apoptosis, inhibits nucleotide excision and repair of damaged cellular DNA, and modulates transcriptional activation of cellular growth regulating genes. Hepatocyte transformation may be indirectly influenced by HBV DNA integration, by the generation of mutagenic oxygen reactive species, or by acquisition of mutations in association with necroinflammatory disease. HBV replication, which may occur in HCC, affects the long-term survival of patients. Prevention of HBV infection is expected to decrease the incidence of endemic HCC.

Carcinoma, Hepatocellular↗

PubMed2006

Deconfounding microarray analysis - independent measurements of cell type proportions used in a regression model to resolve tissue heterogeneity bias.

OBJECTIVES: Microarray analysis requires standardized specimens and evaluation procedures to achieve acceptable results. A major limitation of this method is caused by heterogeneity in the cellular composition of tissue specimens, which frequently confounds data analysis. We introduce a linear model to deconfound gene expression data from tissue heterogeneity for genes exclusively expressed by a single cell type. METHODS: Gene expression data are deconfounded from tissue heterogeneity effects by analyzing them using an appropriate linear regression model. In our illustrating data set tissue heterogeneity is being measured using flow cytometry. Gene expression data are determined in parallel by real time quantitative polymerase chain reaction (qPCR) and microarray analyses. Verification of deconfounding is enabled using protein quantification for the respective marker genes. RESULTS: For our illustrating dataset, quantification of cell type proportions for peripheral blood mononuclear cells (PBMC) from tuberculosis patients and controls revealed differences in B cell and monocyte proportions between both study groups, and thus heterogeneity for the tissue under investigation. Gene expression analyses reflected these differences in celltype distribution. Fitting an appropriate linear model allowed us to deconfound measured transcriptome levels from tissue heterogeneity effects. In the case of monocytes, additional differential expression on the single cell level could be proposed. Protein quantification verified these deconfounded results. CONCLUSIONS: Deconfounding of transcriptome analyses for cellular heterogeneity greatly improves interpretability, and hence the validity of transcriptome profiling results.

Cell Physiological Phenomena↗

PubMed2026

Integrated bioinformatics and SEM analysis reveal GPAM as a key mediator of fibrosis in NAFLD with metabolic dysfunction.

Nonalcoholic fatty liver disease (NAFLD) is a complex condition influenced by metabolic and genetic factors, yet the shared genetic architecture underlying its progression remains poorly understood. The aim of this study was to employ genomic structural equation modeling (GSEM) to elucidate the genetic architecture linking NAFLD with key metabolic traits-including insulin resistance, body mass index (BMI), hemoglobin A1c (HbA1c), and liver fibrosis using summary statistics from large-scale genome-wide association studies. By harmonizing 2.18 million variants across five genome-wide association studies (GWAS) datasets, we identified 134 genome-wide significant loci that mapped to 24 genes. GSEM revealed a latent genetic structure composed of two distinct dimensions: a metabolic regulation factor primarily driven by insulin resistance, BMI, and HbA1c; and a structural pathology factor specifically associated with liver fibrosis. These factors explained 65.5% and 78.1% of the genetic variance in BMI and fibrosis, respectively, with minimal correlation (rg = 0:07), indicating their genetic distinctness. Additionally, integrating Mendelian randomization with liver transcriptome profiling, we characterized how the 24 genes contribute to disease and identified mitochondrial glycerol-3-phosphate acyltransferase (GPAM) as the key gene that causally links lipid metabolism to fibrogenesis. In conclusion, we present the first genetically grounded mechanism for the progression of NAFLD to fibrosis. This mechanism encompasssses genetic variants, dysregulated gene expression, metabolic disturbances, and the processes involved in fibrotic remodeling. This research establishes a genetic framework for understanding the pathogenesis of NAFLD and highlights novel therapeutic targets for intervention.

Non-alcoholic Fatty Liver Disease↗

PubMed2006

Transcriptome and proteome profiling to understanding the biology of high productivity CHO cells.

A combined transcriptome and proteome analysis was carried out to identify key genes and proteins differentially expressed in Chinese hamster ovary (CHO) cells producing high and low levels of dhfr-GFP fusion protein. Comparison of transcript levels was performed using a proprietary 15K CHO cDNA microarray chip, whereas proteomic analysis was performed using iTRAQ quantitative protein profiling technique. Microarray analysis revealed 77 differentially expressed genes, with 53 genes upregulated and 24 genes downregulated. Proteomic analysis gave 75 and 80 proteins for the midexponential and stationary phase, respectively. Although there was a general lack of correlation between mRNA levels and quantitated protein abundance, results from both datasets concurred on groups of proteins/genes based on functional categorization. A number of genes (20%) and proteins (45 and 23%) were involved in processes related to protein biosynthesis. We also identified three genes/proteins involved in chromatin modification. Enzymes responsible for opening up chromatin, Hmgn3 and Hmgb1, were upregulated whereas enzymes that condense chromatin, histone H1.2, were downregulated. Genes and proteins that promote cell growth (Igfbp4, Ptma, S100a6, and Lgals3) were downregulated, whereas those that deter cell growth (Ccng2, Gsg2, and S100a11) were upregulated. Other main groups of genes and proteins include carbohydrate metabolism, signal transduction, and transport. Our findings show that an integrated genomic and proteomics approach can be effectively utilized to monitor transcriptional and posttranscriptional events of mammalian cells in culture.

Animals↗

PubMed2026

POU2F3 expression in lung squamous cell carcinoma: transcriptomic and immunohistochemical profiling with prognosis.

BACKGROUND: Lung squamous cell carcinoma (LUSC) lacks well-defined molecular targets. This study investigated the clinical and biological relevance of POU class 2 homeobox 3 (POU2F3), a tuft cell-associated transcription factor, in LUSC. METHODS: RNA sequencing data of patients with LUSC from The Cancer Genome Atlas (TCGA cohort, n = 190) was analysed and compared to a cohort of surgically resected cases analyzed via immunohistochemistry (IHC cohort, n = 137). Prognostic impact was assessed via survival analyses. Transcriptomic features, pathway enrichment, and immune profiles were evaluated via differentially expressed gene analysis, Gene Set Enrichment Analysis, and CIBERSORTx. RESULTS: High POU2F3 expression independently predicted poor overall survival in the TCGA cohort (HR = 2.06, 95% CI: 1.04-4.08, P = 0.039). In contrast, POU2F3 expression was not prognostic in the IHC cohort (P = 0.995). Morphologically, POU2F3-positive tumours were enriched for non-keratinizing and poorly differentiated subtypes. Transcriptomic analysis showed suppression of proliferation and immune-related pathways (FDR < 0.001), with suggestive enrichment of the TGF-β (FDR = 0.143) and p53 (FDR = 0.229) signaling pathways. On immune deconvolution, POU2F3-high tumours showed a nominal increase in activated dendritic cells, which did not withstand multiple testing correction. POU2F3 protein was detected in 12.4% of tumours and was significantly associated with p53 or RB1 abnormalities (single or double) (P = 0.028). CONCLUSIONS: POU2F3 marks a transcriptionally distinct, early-stage subtype of LUSC with keratinization-related features. Its prognostic relevance appears context-dependent and requires prospective validation in uniformly treated cohorts.

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↗

PubMed2026

Integrative Transcriptomic and Proteomic Profiling Identifies S100P as a Potential Functional Biomarker for Sessile Serrated Lesions.

BACKGROUND: Sessile serrated lesions (SSLs) account for 15% of colorectal cancers (CRCs) but detection remains difficult due to flat morphology, mucinous features, and subtle histology. AIMS: This study aimed to identify novel and functionally relevant biomarkers of SSLs using transcriptomic screening and multi-omics validation. METHODS: Paired SSL and normal mucosa specimens (n = 6) underwent RNA sequencing. Differentially expressed genes (DEGs) were filtered for membrane or secretory proteins and validated across TCGA and adenoma transcriptomes. Functional significance was assessed using CRISPR dependency profiling, proteotranscriptomic concordance, pharmacogenomic sensitivity, and connectivity map analysis. RESULTS: We identified 216 upregulated genes in SSLs, including 68 encoding secretory/membrane proteins that better discriminated SSLs from controls and were enriched for adhesion and neuronal signaling while suppressing TNFα-NFκB inflammatory pathways. Cross-cohort comparison revealed five overlapping candidates between SSLs and TCGA CMS1 tumors. Among them, S100P emerged as the primary biomarker candidate, showing consistent upregulation in SSLs and CMS1 tumors while remaining low in normal mucosa and conventional adenomas. TFF1 also showed RNA-level upregulation but appeared more context-dependent. S100P demonstrated strong RNA-protein concordance in CRC cell-line profiling, supporting its detectability as a biomarker candidate. Pharmacogenomic profiling of LS411N cells revealed marked sensitivity to SN-38 and fluoropyrimidines, consistent with serrated CRC vulnerabilities. Connectivity map analysis identified perturbations, including MAPK1 and histone acetyltransferase suppression, that may reverse parts of the SSL transcriptional program. CONCLUSION: These findings prioritize S100P as a promising biomarker candidate for SSLs that warrants further validation in larger cohorts and clinically applicable platforms.

Humans↗

PubMed2026

Transcriptomic and Metabolomic Profiling Identifies a Core Gene-Metabolite Axis Driving African Swine Fever Virus Replication in the Soft Tick Ornithodoros lahorensis.

African swine fever virus (ASFV) causes an incurable swine disease with nearly 100% mortality, posing a catastrophic threat to global pig production. The soft tick Ornithodoros lahorensis acts as a critical biological vector that sustains persistent ASFV replication and mediates long-distance viral transmission, yet the molecular mechanisms governing ASFV-tick interplay remain poorly understood. Here, we integrated transcriptomics and metabolomics to systematically dissect molecular changes in O. lahorensis across three infection stages: Uninfected control, early infection (7 days post-infection, dpi), and late persistent infection (21 dpi). Multi-omics integration revealed that ASFV extensively remodels tick host metabolism, predominantly activating purine/pyrimidine metabolism, lipid biosynthesis, and energy metabolism. We further characterized a conserved regulatory module consisting of 12 core genes and 8 signature metabolites that collectively support ASFV genome replication and virion assembly. Three hub metabolic genes (TK1, ATP5F1B, and IMPDH) were selected for functional validation via siRNA silencing in ticks; individual gene silencing suppressed ASFV loads by 89.2%, 91.5%, and 87.8%, respectively (p < 0.001***). This work represents the first comprehensive multi-omics investigation of ASFV infection in O. lahorensis. We identified tick-specific molecular targets to block vector-mediated ASFV spread and established a standardized multi-omics analytical pipeline for tick-virus interaction research. Our findings elucidate the mechanistic basis of long-term ASFV persistence in soft ticks and deliver novel actionable clues for developing vector-targeted ASF intervention strategies.

Animals↗

PubMed2026

Distinct molecular responses to acute cold exposure revealed by comparative transcriptomic and metabolomic profiling in the bay scallop Argopecten irradians.

Acute cold stress can elicit distinct molecular responses even when bay scallop populations show similar phenotypic outcomes. We compared a seventh-generation fast-growing bay scallop line (BS) with a commercial control population (CC) during a 72-h acute cold exposure at -1 ± 0.3 °C. RNA-seq was used as the discovery layer, representative BS cold-responsive genes were evaluated by qRT-PCR, and paired LC-MS profiles provided a comparative metabolic layer. At baseline, 138 genes differed between BS and CC; after cold exposure, 134 of these baseline differences disappeared and 61 of 65 cold-state differences newly emerged. BS showed a larger transcriptomic response magnitude than CC, with 1129 cold-responsive genes compared with 28 genes in CC, and this ordering remained robust across multiple sensitivity analyses. Survival after 72 h was identical in BS and CC (83/90, 92.2% in each population). Biochemical responses were time-dependent and marker-specific: CAT, LZM, T-SOD and T-AOC showed population-by-time interactions, whereas GSH-Px and MDA did not, and the 72-h differences were not consistently favourable to BS. Metabolomic cold effects were strongly concordant between populations, and no feature showed a significant population-by-cold interaction. Features putatively assigned to arachidonic acid metabolism were enriched, but this provider-annotated pathway signal remains exploratory because authentic-standard confirmation was not performed. These findings indicate population-specific differences in molecular responsiveness but do not establish superior cold tolerance in BS.

Animals↗

PubMed2005

Circadian profiling of the transcriptome in immortalized rat SCN cells.

Endogenous oscillations in gene expression are a prevalent feature of the circadian clock in the mammalian suprachiasmatic nucleus (SCN) and similar timekeeping systems in other organisms. To determine whether immortalized cells derived from the rat SCN (SCN2.2) retain these intrinsic rhythm-generating properties, oscillatory behavior of the SCN2.2 transcriptome was analyzed and compared with that found in the rat SCN in vivo using rat U34A Affymetrix GeneChips. In SCN2.2 cells, 116 unique genes and 46 ESTs or genes of unknown function exhibited circadian fluctuations with a 1.5-fold or greater difference in their mRNA abundance for two cycles. Many (35%) of these rhythmically regulated genes in SCN2.2 cells also exhibited circadian profiles of mRNA expression in the rat SCN in vivo. Functional analyses and cartography indicate that a diverse set of cellular pathways are strategically regulated by the circadian clock in SCN2.2 cells and that the largest categories of rhythmic genes are those involved in cellular and systems-level communication or in metabolic processes like cellular respiration, fatty acid recycling, and steroid synthesis. Because many of the same genes or nodes within these functional categories were rhythmically expressed in both SCN2.2 cells and the rat SCN, the circadian regulation of these pathways may be important in modulating input to or output from the SCN clock mechanism. In summary, global expression and circadian regulation of the SCN2.2 transcriptome retain many SCN-like properties, suggesting that genes displaying rhythmic profiles in both experimental models may be integral to their function as both circadian oscillators and pacemakers.

Animals↗

PubMed2026

Machine learning-integrated multi-omics risk prediction for pulmonary fungal infection in COPD and lung cancer: a transcriptomic and immune profiling study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and lung cancer are major risk factors for invasive pulmonary fungal infection (IPFI), carrying an attributable mortality of 30%-80%. Their coexistence further amplifies immunosuppression, while current diagnostic criteria remain inadequate for early risk identification. METHODS: Transcriptomic data from the GEO dataset GSE296912 (scRNA-seq; 12,078 cells from normal and COPD lung tissue) and The Cancer Genome Atlas (TCGA)-lung adenocarcinoma (LUAD) bulk RNA-seq cohort (539 tumor and 59 normal samples) underwent differential expression and cross-omics integration analysis. Five machine learning models were constructed: logistic regression, SVM, random forest, XGBoost, and LASSO. Candidate genes were validated by qRT-PCR in A549 cells and THP-1-derived macrophages stimulated with heat-inactivated Aspergillus fumigatus conidia, a protocol selected to ensure BSL-2 biosafety compliance and isolate PAMP-mediated innate immune signaling. Model performance was evaluated using 5-fold stratified cross-validation with AUC, calibration curves, and decision curve analysis. RESULTS: Single-cell transcriptomic analysis of 12,078 cells identified 14 distinct cell populations, with marked myeloid expansion and immune dysregulation in COPD lung tissue. Cross-omics integration with TCGA-LUAD data identified 1,145 shared genes (79 immune-related), converging on NF-κB, TLR4, and cytokine receptor signaling. The random forest model achieved excellent discriminative performance (5-fold CV AUC = 0.988), with Treg infiltration, TLR4, and MMP9 as the top predictors. qRT-PCR confirmed significant upregulation of all five candidate genes (DEFB4A, S100A8, IL-8, MMP9, and TLR4) in both A549 and THP-1 cells following fungal stimulation. CONCLUSION: This multi-omics machine learning model integrating scRNA-seq and TCGA transcriptomic data demonstrates excellent discriminative performance (AUC = 0.988), with mechanistic convergence of NF-κB, TLR4, and oncogenic signaling pathways identified across shared immune gene signatures. In vitro qRT-PCR validation confirms the biological relevance of five key antifungal immune genes, providing a transcriptomic foundation for future prospective IPFI risk stratification in patients with COPD and lung cancer.

TLR4↗

PubMed2025

Transcriptome and metabolome profiling of the medicinal plant Dictamnus dasycarpus reveal key genes involved in quinoline alkaloids biosynthesis and limonoids biosynthesis.

BACKGROUND: As a member of Rutaceae family, Dictamnus dasycarpus Turcz. represents a prominent medicinal plant and economically valuable crop in traditional Chinese medicine, and is renowned for its therapeutic efficacy in treating dermatological conditions. The pharmacological activity of this species primarily stems from quinoline alkaloids and limonoids, which predominantly accumulate in the taproots. These bioactive compounds serve as critical determinants of both medicinal quality and crop yield. Nevertheless, the molecular mechanisms governing their dynamic accumulation patterns in D. dasycarpus taproots remain uncertain, and the fundamental biochemical basis underlying this process has yet to be elucidated. RESULTS: Metabolomic and transcriptomic analyses were carried out to investigate metabolites and gene expression during the development of D. dasycarpus taproots. The differentially accumulated secondary metabolites (DAMs) mainly included quinoline alkaloids and limonoids, and the accumulation of total alkaloids and total limonoids primarily occurred during 2- and 4-year-old. The differentially expressed genes (DEGs) are related to Glycolysis/Gluconeogenesis, Phenylalanine, tyrosine and tryptophan biosynthesis, Tryptophan metabolism, Terpenoid backbone biosynthesis, Sesquiterpenoid and triterpenoid biosynthesis, which had a close relationship with the accumulation of quinoline alkaloids and limonoids. Furthermore, we identified that some CYP450s, acetyltransferase, isomerase, 2-ODDs and others may play an important role in the process of producing quinoline alkaloids and limonoids. CONCLUSION: These results elucidated the molecular mechanisms and metabolic changes underlying the dynamic accumulation process occurring in the taproots of D. dasycarpus. These findings provide a theoretical basis for the planting and harvesting of D. dasycarpus.

Limonins↗

PubMed2026

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

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

Animals↗

PubMed2003

Open architecture expression profiling of plant transcriptomes and gene discovery using GeneCalling technology.

The recent rapid developments in genomics tools, technologies, and bioinformatics have revolutionized gene expression analysis. It is now routine to measure gene expression modulation at the genomic level. GeneCalling technology is an open architecture system capable of assaying more than 95% of genes expressed in a tissue. Unlike the closed systems, GeneCalling is not dependent upon an existing sequence or clone database. GeneCalling uses as low as 50 pg of the cDNA from samples and identifies cDNA fragments that are differentially modulated within a set of samples. With the use of 96 pairs of restriction enzymes, more than 30,000 cDNA fragments are routinely assayed to identify those that are differentially modulated. Specific processes, such as SeqCalling, Trace Poisoning, and GeneCall Poisoning, are set up to not only confirm the known genes, but also to clone and analyze unknown and novel genes that have an interesting expression profile. GeneCalling has been successfully applied to expression profiling of several plant and fungal species, and resulted in identification and characterization of genes that are useful in commercial applications towards improving agriculturally important traits in plants.

DNA, Complementary↗