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PubMed2026

A per- and polyfluoroalkyl substances-based gene signature links prognosis to immune landscapes in thyroid cancer.

BACKGROUND: Thyroid cancer (THCA) is the most common endocrine malignancy with a rising global incidence and significant heterogeneity. Although per- and polyfluoroalkyl substances (PFAS) exposure is linked to thyroid dysfunction, the prognostic value of per- and polyfluoroalkyl substances-related genes (PFASRGs) and their role in the tumor immune microenvironment (TME) remain poorly understood. This study aims to systematically screen key PFASRGs and evaluate their prognostic value as biomarkers for THCA. METHODS: Utilizing The Cancer Genome Atlas (TCGA)-THCA transcriptomic data and PFASRGs, we constructed a prognostic model through differential expression analysis, univariate and multivariate Cox regression analyses, and the least absolute shrinkage and selection operator (LASSO). The model's robustness was validated using receiver operating characteristic (ROC) curves, Kaplan-Meier analysis, and clinical nomograms. Furthermore, the TME, immunotherapy response, and drug sensitivities were systematically evaluated. Distinct molecular landscapes were characterized by stratifying the cohort via unsupervised consensus clustering analysis. RESULTS: The eight-gene prognostic model demonstrated robust performance, with area under the curve (AUC) values exceeding 0.85 across all validation cohorts. High-risk patients exhibited significantly shorter overall survival and an "inflamed" TME characterized by high immune scores and checkpoint expression. In contrast, the therapeutic efficacy of anti-programmed death-ligand 1 (PD-L1) agents was more pronounced in the low-risk category, as evidenced by a superior objective response. Furthermore, distinct molecular subtypes and risk-specific sensitivities to targeted agents, such as sorafenib and sunitinib, were identified, highlighting the model's clinical utility for personalized treatment. CONCLUSIONS: We established a novel THCA prognostic framework based on eight PFASRGs. This model exhibits superior performance in risk stratification, effectively distinguishing cohorts with divergent clinical trajectories, unique immune microenvironment features, and varied therapeutic responses. Our findings provide a powerful predictive tool for refining prognostic evaluation and facilitating the implementation of personalized management strategies for THCA patients.

Per- and polyfluoroalkyl substances-related genes ↗

PubMed2003

[Analysis of the poly-genes expression changes in liver by gene expression profile chip in gut ischemia-reperfusion rats].

OBJECTIVE: To investigate the difference of poly-genes expression between control and gut ischemia-reperfusion rats. METHODS: One thousand one hundred and seventy-six known genes expression in the liver was investigated by means of the cDNA microarray technology to reveal the differential expression genes between control and gut ischemia-reperfusion rats. RESULTS: The analysis data of the cDNA microarray showed that there were 111 genes expression changed over 5 times including 64 genes upregulated and 47 genes downregulated, some of which had not been reported to associated with gut ischemia-reperfusion injury. CONCLUSION: There are many structural and functional genes expression changed in liver of gut ischemia-reperfusion rats, which might be involved in the initiation and the development of SIRS and MODS.

Animals↗

PubMed2004

Correction of sequence-based artifacts in serial analysis of gene expression.

MOTIVATION: Serial Analysis of Gene Expression (SAGE) is a powerful technology for measuring global gene expression, through rapid generation of large numbers of transcript tags. Beyond their intrinsic value in differential gene expression analysis, SAGE tag collections afford abundant information on the size and shape of the sample transcriptome and can accelerate novel gene discovery. These latter SAGE applications are facilitated by the enhanced method of Long SAGE. A characteristic of sequencing-based methods, such as SAGE and Long SAGE is the unavoidable occurrence of artifact sequences resulting from sequencing errors. By virtue of their low-random incidence, such tag errors have minimal impact on differential expression analysis. However, to fully exploit the value of large SAGE tag datasets, it is desirable to account for and correct tag artifacts. RESULTS: We present estimates for occurrences of tag errors, and an efficient error correction algorithm. Error rate estimates are based on a stochastic model that includes the Polymerase chain reaction and sequencing error contributions. The correction algorithm, SAGEScreen, is a multi-step procedure that addresses ditag processing, estimation of empirical error rates from highly abundant tags, grouping of similar-sequence tags and statistical testing of observed counts. We apply SAGEScreen to Long SAGE libraries and compare error rates for several processing scenarios. Results with simulated tag collections indicate that SAGEScreen corrects 78% of recoverable tag errors and reduces the occurrences of singleton tags. AVAILABILITY: The SAGEScreen software is available for academic users from the first author.

Algorithms↗

PubMed2016

Early leukocyte gene expression associated with age, burn size, and inhalation injury in severely burned adults.

BACKGROUND: In the patient with burn injury, older age, larger percentage of total body surface area (TBS) burned, and inhalation injury are established risk factors for death, which typically results from multisystem organ failure and sepsis, implicating burn-induced immune dysregulation as a contributory mechanism. We sought to identify early transcriptomic changes in circulating leukocytes underlying increased mortality associated with these three risk factors. METHODS: We performed a retrospective analysis of the Glue Grant database. From 2003 to 2010, 324 adults with 20% or greater TBS burned were prospectively enrolled at five US burn centers, and 112 provided blood samples within 1 week after burn. RNA was extracted from pooled leukocytes for hybridization onto Affymetrix HU133 Plus 2.0 GeneChips. A multivariate regression model was constructed to determine risk factors for mortality. Testing for differential gene association associated with age, burn size, and inhalation injury was based on linear models using a fold change threshold of 1.5 and false discovery rate of 0.05. RESULTS: After adjusting for potential confounders, age greater than 60 years (relative risk [RR], 4.53; 95% confidence interval [CI], 2.93-6.99), burn size greater than 40% TBS (RR, 4.24; 95% CI, 2.61-6.91), and inhalation injury (RR, 2.08; 95% CI, 1.35-3.21) were independently associated with mortality. No genes were differentially expressed in association with age greater than 60 years or inhalation injury. Fifty-one probe sets representing 39 unique genes were differentially expressed in leukocytes from patients with burn size greater than 40% TBS; these genes were associated with platelet activation and degranulation/exocytosis, and gene-set enrichment analysis suggested increased cellular proliferation and down-regulation of proinflammatory cytokines. CONCLUSION: Among adults with large burns, older age, increasing burn size, and inhalation injury have a modest effect on the leukocyte transcriptome in the context of the "genomic storm" induced by a 20% or greater than TBS burned. The 39-gene signature we identified may provide novel targets for the development of therapies to reduce morbidity and mortality associated with burns greater than 40% TBS. LEVEL OF EVIDENCE: Epidemiologic study, level III.

Adult↗

PubMed2003

Modification of the transcriptomic response to renal ischemia/reperfusion injury by lipoxin analog.

BACKGROUND: Lipoxins are lipoxygenase-derived eicosanoids with anti-inflammatory and proresolution bioactivities in vitro and in vivo. We have previously demonstrated that the stable synthetic LXA4 analog 15-epi-16-(FPhO)-LXA4-Me is renoprotective in murine renal ischemia/reperfusion injury, as gauged by lower serum creatinine, attenuated leukocyte infiltration, and reduced morphologic tubule injury. METHODS: We employed complementary oligonucleotide microarray and bioinformatic analyses to probe the transcriptomic events that underpin lipoxin renoprotection in this setting. RESULTS: Microarray-based analysis identified three broad categories of genes whose mRNA levels are altered in response to ischemia/reperfusion injury, including known genes previously implicated in the pathogenesis of ischemia/reperfusion injury [e.g., intercellular adhesion molecule-1 (ICAM-1), p21, KIM-1], known genes not previously associated with ischemia/reperfusion injury, and cDNAs representing yet uncharacterized genes. Characterization of expressed sequence tags (ESTs) displayed on microarrays represents a major challenge in studies of global gene expression. A bioinformatic annotation pipeline successfully annotated a large proportion of ESTs modulated during ischemia/reperfusion injury. The differential expression of a representative group of these ischemia/reperfusion injury-modulated genes was confirmed by real-time polymerase chain reaction. Prominent among the up-regulated genes were claudin-1, -3, and -7, and ADAM8. Interestingly, the former response was claudin-specific and was not observed with other claudins expressed by the kidney (e.g., claudin-8 and -6) or indeed with other components of the renal tight junctions (e.g., occludin and junctional adhesion molecule). Noteworthy among the down-regulated genes was a cluster of transport proteins (e.g., aquaporin-1) and the zinc metalloendopeptidase meprin-1 beta implicated in renal remodeling. CONCLUSION: Treatment with the lipoxin analog 15-epi-16-(FPhO)-LXA4-Me prior to injury modified the expression of many differentially expressed pathogenic mediators, including cytokines, growth factors, adhesion molecules, and proteases, suggesting a renoprotective action at the core of the pathophysiology of acute renal failure (ARF). Importantly, this lipoxin-modulated transcriptomic response included many genes expressed by renal parenchymal cells and was not merely a reflection of a reduced renal mRNA load resulting from attenuated leukocyte recruitment. The data presented herein suggest a framework for understanding drivers of kidney injury in ischemia/reperfusion and the molecular basis for renoprotection by lipoxins in this setting.

ADAM Proteins↗

PubMed2026

Integrative analysis and experiment validation of SLC12A8 as a biomarker for the malignant transition from endometriosis to endometriosis associated ovarian cancer.

Endometriosis (EM) is a chronic inflammatory, estrogen‑dependent benign gynecological disorder. A subset of patients with EM may subsequently develop endometriosis‑associated ovarian cancer (EAOC), implying a biological continuum between these two conditions. Nevertheless, the molecular events underlying the progression from benign endometriotic lesions toward EAOC remain incompletely characterized. In this study, transcriptomic datasets retrieved from the GEO database were interrogated through differentially expressed gene screening, functional enrichment analysis, and weighted gene co‑expression network analysis (WGCNA) to identify key genes and pathways relevant to EM and EAOC. Candidate genes were further prioritized by integrating survival analysis via the Kaplan‑Meier Plotter, LASSO regression, random‑forest modeling, and CIBERSORT immune‑infiltration profiling. Loss and gain‑of‑function cellular models were established using siRNA and overexpression plasmids, and in‑vitro functional assays were performed to characterize the phenotypic effects of target genes.We identified several candidate genes associated with EM and EAOC and evaluated their discriminatory performance. Among them, SLC12A8 elevated expression across EM and EAOC tissues and exhibited moderate diagnostic capacity. Higher SLC12A8 expression was also associated with poorer prognosis in EAOC patients. In‑vitro experiments further demonstrated that SLC12A8 modulates proliferation, invasion, and migration in both EM and EAOC cell lines. Collectively, our exploratory research findings support SLC12A8 as a candidate functional mediator and potential biomarker linked to EM‑EAOC pathological progression, thereby extending the mechanistic understanding of these disorders.

Female↗

PubMed2005

cDNA microarray analysis of HBV transgenic mouse liver identifies genes in lipid biosynthetic and growth control pathways affected by HBV.

Hepatitis B virus (HBV) transgenic mice that replicate HBV in the liver generally do not exhibit gross liver pathology, while maintaining a high level (10(7) or greater) of viral titer in the blood. We have used this model to determine the minimum effects of HBV replication in the liver on cellular gene transcription, using cDNA microarrays. cDNA microarray data from sets of HBV versus control cDNA microarrays revealed a very small impact of HBV on the cellular transcriptome. After deletion of genes that were variable in control cDNA microarrays and applying significance analysis of microarrays (SAM), an application to detect statistically significantly regulated genes, we identified 18 upregulated genes and 14 downregulated genes. Most of the regulated genes show a change in expression with respect to control of less than 40% in either direction, demonstrating small effects of HBV. The largest functional category for upregulated genes was lipid biosynthesis, in which ATP citrate lyase, fatty acid synthase, sterol regulatory element binding factor 2, and retinol binding protein 1 were all upregulated. The most strongly downregulated genes were in the cytochrome p450 group, particularly p450, 4a14. Several growth regulatory genes including cyclin D1, IGF binding protein 3, and PCNA were moderately upregulated. These data are the first to specifically identify enzymes involved in fatty acid and NADPH-electron transport pathways that are altered by the presence of HBV. The data also demonstrates that HBV is well adapted to non-cytopathic replication in hepatocytes. Cellular genes expected to be affected by viral secretion from membranes are clearly upregulated, and upregulation of growth regulatory genes may facilitate replacement of dying hepatocytes during persistent infection.

Animals↗

PubMed2026

Artificial Intelligence-Driven Multi-Omics Analysis Reveals Hydroxytyrosol Targeting of the TXNIP-NLRP3 Inflammasome Axis in Traumatic Brain Injury.

Traumatic brain injury (TBI) induces secondary neuroinflammation driven by oxidative stress, inflammasome activation, and immune remodeling, yet specific mechanism-guided pharmacological interventions remain limited. This study established an artificial intelligence (AI)-integrated network pharmacology and multi-omics framework to evaluate whether hydroxytyrosol (HT), an olive-derived natural polyphenol, may regulate TBI-related neuroinflammatory targets centered on the TXNIP/NLRP3 inflammasome axis. Starting from the SMILES structure of HT, potential targets were predicted using PharmMapper, SwissTargetPrediction, and the Similarity Ensemble Approach and were standardized to UniProt identifiers. TBI-associated genes were integrated from GeneCards, DisGeNET, OMIM, and the Therapeutic Target Database. The overlapping target set was analyzed using STRING-based protein-protein interaction (PPI) networks, MCODE, CytoHubba, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Public GEO transcriptomic datasets (GSE123831 and GSE104687) were used for cross-platform expression validation, differential expression analysis, and exploratory CIBERSORT-based immune infiltration estimation. Random forest (RF), multilayer perceptron (MLP), graph convolutional network (GCN), graph attention network (GAT), SHAP/LIME explainability analysis, LASSO inflammatory-risk scoring, and two-sample Mendelian randomization (MR) were further applied for target prioritization, immune phenotype mapping, and genetic association analysis. Seventy-three overlapping HT-TBI targets were identified. PPI and topology analyses prioritized TXNIP, NLRP3, CASP1, MAPK1, and TP53 as key hubs enriched in inflammasome activation, oxidative stress, apoptosis, and NOD-like receptor signaling. TXNIP, NLRP3, and CASP1 were consistently upregulated in both TBI transcriptomic datasets. LM22-based immune deconvolution suggested increased pro-inflammatory immune signatures and a positive TXNIP-M1 macrophage association (r = 0.63, p < 0.001), which should be interpreted as a transcriptome-derived hypothesis rather than validated murine immune-cell proportions. AI-based models consistently ranked TXNIP/NLRP3 as high-contribution features under internal validation, and removal of these targets reduced model performance. A five-gene inflammatory score achieved an internally evaluated AUC of 0.87, while two-sample MR supported positive genetic associations involving TXNIP expression, TBI risk, NLRP3 and IL-1β expression. Collectively, these findings prioritize the TXNIP/NLRP3/CASP1 module as a computationally supported candidate mechanism through which HT may influence oxidative stress-inflammasome-immune coupling in TBI. This study provides an interpretable drug-target-pathway-phenotype framework and identifies TXNIP, NLRP3, and CASP1 as priority nodes for future experimental validation.

Artificial Intelligence↗

PubMed2005

Activation of stem-cell specific genes by HOXA9 and HOXA10 homeodomain proteins in CD34+ human cord blood cells.

There is growing evidence for a role of HOX homeodomain proteins in normal hematopoiesis. Several HOX genes, including HOXA9 and HOXA10, are expressed in primitive hematopoietic cells, implying a role in early hematopoietic differentiation. To identify potential target genes of these two closely related transcription factors, human CD34+ umbilical cord blood cells were transduced with vectors expressing either HOXA9 or HOXA10 and analyzed with cDNA micro-arrays. Statistical analysis using significance analysis of microarrays revealed a common signature of several hundred genes, demonstrating that the transcriptomes of HOXA9 and HOXA10 largely overlap in this cellular context. Seven genes that were upregulated by both HOX proteins were validated by real-time reverse transcription polymerase chain reaction. HOXA9 and HOXA10 showed positive regulation of genes in the Wnt pathway, including Wnt10B and two Wnt receptors Frizzled 1 and Frizzled 5, an important pathway for hematopoietic stem cell (HSC) self-renewal. Other validated genes included v-ets-related gene (ERG), Iroquois 3 (IRX3), aldehyde dehydrogenase 1 (ALDH1), and very long-chain acyl-CoA synthetase homolog 1 (VLCS-H1). GenMAPP (Gene Micro Array Pathway Profiler) analysis indicated that HOXA10 repressed expression of several genes involved in heme biosynthesis and three globin genes, indicating a general suppression of erythroid differentiation. A number of genes regulated by HOXA9 and HOXA10 are expressed in normal HSC populations.

Animals↗

PubMed2004

Functional genomics of cell elongation in developing cotton fibers.

Cotton fibers are single-celled seed trichomes of major economic importance. Factors that regulate the rate and duration of cell expansion control fiber morphology and important agronomic traits. For genetic characterization of rapid cell elongation in cotton fibers, approximately 14,000 unique genes were assembled from 46,603 expressed sequence tags (ESTs) from developmentally staged fiber cDNAs of a cultivated diploid species ( Gossypium arboreum L.). Conservatively, the fiber transcriptome represents 35-40% of the genes in the cotton genome. In silico expression analysis revealed that rapidly elongating fiber cells exhibit significant metabolic activity, with the bulk of gene transcripts, represented by three major functional groups - cell wall structure and biogenesis, the cytoskeleton and energy/carbohydrate metabolism. Oligonucleotide microarrays revealed dynamic changes in gene expression between primary and secondary cell wall biogenesis showing that fiber genes in the dbEST are highly stage-specific for cell expansion - a conclusion supported by the absence of known secondary cell wall-specific genes from our fiber dbEST. During the developmental switch from primary to secondary cell wall syntheses, 2553 "expansion-associated" fiber genes are significantly down regulated. Genes (81) significantly up-regulated during secondary cell wall synthesis are involved in cell wall biogenesis and energy/carbohydrate metabolism, which is consistent with the stage of cellulose synthesis during secondary cell wall modification in developing fibers. This work provides the first in-depth view of the genetic complexity of the transcriptome of an expanding cell, and lays the groundwork for studying fundamental biological processes in plant biology with applications in agricultural biotechnology.

Cell Growth Processes↗

PubMed2026

Identifying JAK2 and ANXA5 as Key Genes Linking Obstructive Sleep Apnea and Oxidative Stress via Machine Learning and Multilayer Transcriptomic Integration With Functional Validation.

Obstructive sleep apnea (OSA) is a common and severe sleep disorder closely associated with oxidative stress (OS). This study aims to identify and validate potential OS-related genes associated with OSA through bioinformatics methods. We successfully identified OS-related differentially expressed genes (OS-DEGs) by combining the limma test, weighted correlation network analysis (WGCNA), and OS-related genes from the GeneCards database. Key genes and potential biological roles were further identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), enrichment analysis, protein-protein interaction (PPI) network analysis, Lasso regression analysis, random forest algorithm, and support vector machine recursive feature elimination (SVM-RFE) method. Evaluate and validate the accuracy of key genes through receiver operating characteristic (ROC) curve analysis. The human single-cell RNA sequencing (scRNA-seq) dataset is used for cell classification annotation, analysis of key gene single-cell expression profiles, and virtual gene knockout experiments based on the scTenifoldKnk algorithm. Integrating scRNA-seq sequencing, pseudotime trajectory inference, cell-cell communication analysis, and bulk immune infiltration deconvolution reveals monocyte subtype remodeling in OSA. Finally, the expression levels of key genes in clinical samples were validated using real-time quantitative PCR (RT-qPCR) and Western blotting. A total of 57 common DEGs, indicating significant enrichment in OS, inflammation, and tumor pathways, particularly prominent in the immunometabolism pathway. By integrating DEGs, WGCNA, PPI results, and machine learning methods, key genes Janus kinase 2 (JAK2) and ANXA5 were screened out. JAK2 was significantly upregulated under disease conditions, while ANXA5 was significantly downregulated. ROC curve exhibited high accuracy (area under the curve [AUC] > 0.85). Human scRNA-seq analysis revealed that key genes were predominantly highly expressed in monocytes. Virtual knockout experiments demonstrated that these key genes play a crucial role in regulating immune responses and inflammatory reactions. PPI networks and enrichment analysis verified that downstream genes S100P, ALOX5AP, PROK2, and PADI4 may collaboratively participate in immune response and inflammation regulation. Finally, clinical sample experiment further validated the results of bioinformatics analysis. This study provides new research insights for the diagnosis, mechanism research, and treatment development of OSA in the future by integrating multilayer transcriptomic and machine learning techniques.

Humans↗

PubMed2003

Comprehensive evaluation of the extraocular muscle critical period by expression profiling in the dark-reared rat and monocularly deprived monkey.

PURPOSE: To address the consequences of visual deprivation paradigms in rat (dark rearing) and monkey (monocular deprivation) on extraocular muscle (EOM) development using genome-wide expression profiling. METHODS: Serial analysis of gene expression (SAGE) was used to determine alterations in the EOM transcriptome induced by dark rearing of rats from birth to postnatal day 45. Data were compared with previously published normal EOM SAGE library. DNA microarray similarly assessed changes in gene expression patterns of EOMs of monkeys reared from birth to 4 months of age with monocular deprivation. RESULTS: Dark rearing produced changes in expression of 280 transcripts in rat EOM. Of these, 71 were known genes representing functional categories that included energy metabolism/mitochondrial-related (21%), protein synthesis and modification (14%), lipid metabolism (13%), and muscle-related (6%) transcripts. Together, the predominant pattern reflected an energetic shift toward fatty acid beta-oxidation and integrated alterations in both myofibers and supportive tissues. The response of monkey rectus muscles to monocular deprivation was considerably less severe. CONCLUSIONS: The visual deprivation paradigms used in this study mimic alterations that are associated with the common disorders of strabismus, congenital cataract, and amblyopia. These data show that postnatal EOM maturation is broadly susceptible to changes in activity patterns that are a consequence of visuomotor maldevelopment. The data extend the concept of an EOM-critical period and establish that activity patterns in developing eye movement systems play vital determinant roles in the novel EOM phenotype.

Animals↗

PubMed2005

Sexually dimorphic gene expression in the hypothalamus, pituitary gland, and cortex.

We examined sex differences in the transcriptomes of hypothalamus, pituitary gland, and cortex of male and female mice using serial analysis of gene expression. In total 940,669 tags were sequenced. In hypothalamus, 3 transcripts are differentially expressed by gender, including growth hormone (neuromodulation) and 3beta-hydroxysteroid dehydrogenase-1 (steroidogenesis). In pituitary gland, 43 transcripts are differentially expressed, including RAS guanyl-releasing protein 2 (cell signaling), ornithine transporter (mitochondrial transport), H3 histone family 3B (chromatin structure), heterogeneous nuclear ribonucleoprotein U (chromatin remodeling), NADH dehydrogenase (mitochondrial oxidative phosphorylation), neuronatin (cell differentiation), and ribosomal protein S27a (protein metabolism). EST X (inactive)-specific transcript antisense is expressed at a higher level in the three female organs, whereas growth hormone and NADH dehydrogenase are expressed at higher levels in female cortex. Thus, the current study has characterized key sexual dimorphisms in the transcriptomes of the hypothalamus, pituitary, and cortex.

Animals↗

PubMed2005

Proteomic resources: integrating biomedical information in humans.

Recent improvements in high-throughput proteomic technologies have unleashed the potential for generating vast amounts of data. Managing and sharing proteomic data is not an easy task. In this article, we will discuss some of the high-throughput proteomic techniques that are commonly used today. We will also review the major issues in sharing and dissemination of proteomic data and the recent community initiatives to standardize data formats and ontologies. An overview of the web-based resources and databases for analysis of proteomic data is also provided. Integration of disparate proteomic data sources with genomic and transcriptomic data should make systems biology type of approaches feasible in the near future.

Amino Acid Sequence↗

PubMed2026

A High-Resolution Stereo-Seq Spatial Transcriptomic Resource for Adult Holstein Cattle Liver.

The bovine liver is a highly compartmentalized organ that plays essential roles in continuous gluconeogenesis and nitrogen recycling; however, its spatial molecular architecture has remained largely uncharacterized due to the limitations of traditional bulk and single-cell approaches. To address this gap, Spatial Enhanced Resolution Omics-sequencing (Stereo-seq) was utilized to generate a subcellular-resolution (500 nm) transcriptomic map of an adult Holstein cattle liver, and a refined reference-guided workflow was implemented to overcome standard annotation limitations in livestock. Raw sequencing data were processed using the Stereo-seq Analysis Workflow and analyzed with Stereopy, Seurat, SingleR, and reference-guided workflows. Spatial aggregation was evaluated at Bin20, Bin50, Bin100, Bin150, and Bin200. Increasing bin size increased molecular identifier counts and detected-gene complexity while progressively reducing spatial granularity. Bin50, corresponding to 50 × 50 DNA nanoballs and an approximate nominal footprint of 25 × 25 µm, was therefore selected as a practical intermediate aggregation level for the primary analyses. Quality-control assessment, Leiden clustering, UMAP visualization, reference-based cell-type annotation, cluster-marker analysis, and spatial mapping of canonical hepatic genes demonstrated preservation of biologically interpretable liver transcriptional organization. Raw sequencing data processed spatial matrices, annotated objects, and analysis code are publicly available to support reanalysis and computational benchmarking. In summary, we present a Stereo-seq spatial transcriptomic resource generated from liver tissue of an adult Holstein cow. This initial resource provides a valuable foundation for future studies of bovine liver biology, comparative genomics, and the spatial basis of livestock health and production traits.

Animals↗

PubMed2005

Modulation of yeast genome expression in response to defective RNA polymerase III-dependent transcription.

We used genome-wide expression analysis in Saccharomyces cerevisiae to explore whether and how the expression of protein-coding, RNA polymerase (Pol) II-transcribed genes is influenced by a decrease in RNA Pol III-dependent transcription. The Pol II transcriptome was characterized in four thermosensitive, slow-growth mutants affected in different components of the RNA Pol III transcription machinery. Unexpectedly, we found only a modest correlation between altered expression of Pol II-transcribed genes and their proximity to class III genes, a result also confirmed by the analysis of single tRNA gene deletants. Instead, the transcriptome of all of the four mutants was characterized by increased expression of genes known to be under the control of the Gcn4p transcriptional activator. Indeed, GCN4 was found to be translationally induced in the mutants, and deleting the GCN4 gene eliminated the response. The Gcn4p-dependent expression changes did not require the Gcn2 protein kinase and could be specifically counteracted by an increased gene dosage of initiator tRNA(Met). Initiator tRNA(Met) depletion thus triggers a GCN4-dependent reprogramming of genome expression in response to decreased Pol III transcription. Such an effect might represent a key element in the coordinated transcriptional response of yeast cells to environmental changes.

Basic-Leucine Zipper Transcription Factors↗

PubMed2004

Analysis of gene expression data using functional principal components.

The large amount of data involved in DNA microarrays implies the development of efficient computer algorithms to analyze the gene expressions, and thus to study the transcriptome. Numerous techniques already exist and we propose a new method based on the key idea that gene profiles may be considered as continuous curves. The analysis of the set of curves stemming from the DNA microarray may be then performed using a functional analysis which can exhibit the main modes of variations in this set, gather genes with similar variations and extract characteristic parameters of gene profiles. We aim here at introducing this method, called the Functional Principal Component Analysis. A prospective study has been performed on two available datasets, concerning on the one hand the sporulation data of the Saccharomyces cerevisiae, and on the other hand data of tumor cell lines. Results are very promising: the method is able to extract characteristic parameters from the datasets, to extract significant modes of variations in the set of gene profiles, and to link these variations to biological processes already studied in literature.

Algorithms↗

PubMed2002

Serial analysis of gene expression in normal p53 null mammary epithelium.

Much evidence has accumulated implicating the p53 gene as of importance in breast carcinogenesis. However, much still remains to be uncovered on the specific downstream pathways influenced by this important activator/repressor of transcription. This study investigated the effects of a p53 null genotype on the transcriptome of 'normal' mouse mammary epithelium using a unique in vivo model of preneoplastic transformation. We used SAGE for the comparative analysis of p53 wild type (wt) and null mammary epithelium unexposed and exposed to hormonal stimulation. Analysis of the hormone exposed samples provided a comprehensive view of the dramatic changes in gene expression as consequence of the functional differentiation of the mammary epithelium in an in vivo system. We detected the dysregulation in p53(null) epithelium of <1% of the transcriptome. Changes in expression affected not only known p53 target genes, but also several unexpected genes such as Expi (Wdnm1), Cyp1b1, Gelsolin, Ramp2 and class I MHC genes. The dysregulation of specific genes and their potential use as preneoplastic markers was further validated using an independent model of premalignant mammary outgrowth lines. This is the first study to examine the transcriptome of very early stages of preneoplastic progression in an in vivo model that mimics human breast cancer.

Animals↗