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PubMed2002

Transcriptome analysis of human autosomal trisomy.

We present transcriptome analyses of primary cultures of human fetal cells from pregnancies affected with trisomy 21 (t21) and trisomy 13 (t13). Pooled mRNA samples from t21 and t13 cases were used for comparative hybridizations to cDNA arrays with pooled mRNA from normal cells. When the array cDNAs were grouped by chromosomal location the relevant trisomic chromosome could be clearly identified as showing the most significant misregulation. The average level of transcription on the trisomic chromosome was increased only approximately 1.1-fold compared to normal cells on array analysis. Since the karyotype could be accurately predicted by the transcriptome this could provide a novel method of detecting aneusomy of unknown position. Subsequent analysis of individuals cases demonstrated that variation in transcriptional profiles between samples within each class made transcriptional karyotyping difficult without pooling or the use of arrays with a higher proportion of all human cDNAs. Interestingly, consistent differences in the relative expression levels between chromosomes were detected suggesting that genomic control mechanisms may act over larger distances than previously thought. Most (>95%) >+/-2 SD misregulated genes did not map to the trisomic chromosome and significant misregulation was more common in t13 than t21. These data support a model of a subtle primary upregulation of genes on the trisomic chromosome resulting in a secondary, generalized and more extreme transcriptional misregulation. It seems likely that the degree of this misregulation determines the severity of the phenotype in most aneuploidy.

Chromosomes, Human, Pair 13↗
PubMed2006

DeepSAGE--digital transcriptomics with high sensitivity, simple experimental protocol and multiplexing of samples.

Digital transcriptomics with pyrophosphatase based ultra-high throughput DNA sequencing of di-tags provides high sensitivity and cost-effective gene expression profiling. Sample preparation and handling are greatly simplified compared to Serial Analysis of Gene Expression (SAGE). We compare DeepSAGE and LongSAGE data and demonstrate greater power of detection and multiplexing of samples derived from potato. The transcript analysis revealed a great abundance of up-regulated potato transcripts associated with stress in dormant potatoes compared to harvest. Importantly, many transcripts were detected that cannot be matched to known genes, but is likely to be part of the abiotic stress-response in potato.

Diphosphates↗
PubMed2005

Full transcriptome analysis of rhabdomyosarcoma, normal, and fetal skeletal muscle: statistical comparison of multiple SAGE libraries.

Rhabdomyosarcoma (RMS) is the most frequent soft tissue sarcoma in children. Improved treatment strategies have increased overall survival, but the response of approximately one-third of the patients is still poor. To increase the knowledge of RMS pathogenesis, we performed the first full transcriptome analysis of RMS using serial analysis of gene expression (SAGE). With a G-test for the simultaneous comparison of subsets of SAGE libraries of normal skeletal muscle, embryonal (ERMS) and alveolar (ARMS) RMS, we identified 251 differentially expressed genes. A literature-mining procedure demonstrated that 158 of these genes have not previously been associated with RMS or normal muscle. Gene Ontology (GO) analysis assigned 198 of the 251 genes to muscle-specific classes, including those involved in normal myogenic development, as well as tumor-related classes. Prominent GO classes were those associated with proliferation and actin reorganization, which are processes that play roles during early muscle development, muscle function, and tumor progression. Using custom microarrays, we confirmed the (up- or down-) regulation of 80% of 98 differentially expressed genes. Another SAGE library of 19- to 22-week-old fetal skeletal muscle was compared with the RMS and normal muscle transcriptomes. Cluster analysis showed that the RMS and fetal muscle SAGE libraries formed one cluster distinct from normal muscle samples. Moreover, the expression profile of 86% of the differentially expressed genes between normal muscle and RMS was highly similar in fetal muscle and RMS. In conclusion, the G-test is a robust tool for analyzing groups of SAGE libraries and correctly identifies genes marking the difference between fully differentiated skeletal muscle and RMS. This study not only substantiates the close association between embryonic myogenesis and RMS development but also provides a rich source of candidate genes to further elucidate the etiology of RMS or to identify diagnostic and/or prognostic markers.

Cell Adhesion↗
PubMed2003

G protein-coupled receptor genes in the FANTOM2 database.

G protein-coupled receptors (GPCRs) comprise the largest family of receptor proteins in mammals and play important roles in many physiological and pathological processes. Gene expression of GPCRs is temporally and spatially regulated, and many splicing variants are also described. In many instances, different expression profiles of GPCR gene are accountable for the changes of its biological function. Therefore, it is intriguing to assess the complexity of the transcriptome of GPCRs in various mammalian organs. In this study, we took advantage of the FANTOM2 (Functional Annotation Meeting of Mouse cDNA 2) project, which aimed to collect full-length cDNAs inclusively from mouse tissues, and found 410 candidate GPCR cDNAs. Clustering of these clones into transcriptional units (TUs) reduced this number to 213. Out of these, 165 genes were represented within the known 308 GPCRs in the Mouse Genome Informatics (MGI) resource. The remaining 48 genes were new to mouse, and 14 of them had no clear mammalian ortholog. To dissect the detailed characteristics of each transcript, tissue distribution pattern and alternative splicing were also ascertained. We found many splicing variants of GPCRs that may have a relevance to disease occurrence. In addition, the difficulty in cloning tissue-specific and infrequently transcribed GPCRs is discussed further.

Alternative Splicing↗
PubMed2005

Serial analysis of gene expression in adrenocortical hyperplasia caused by a germline PRKAR1A mutation.

CONTEXT: Adrenocortical tumors have been studied at the molecular genetic and cytogenetic levels, but the gene expression profiles of normal and tumor adrenal tissue have not been extensively investigated. OBJECTIVE: The objective of this study was to obtain information about transcriptome differences in hyperplastic adrenal cells. DESIGN AND PATIENTS: We performed serial analysis of gene expression (SAGE) on control adrenal tissue and primary pigmented nodular adrenocortical disease (PPNAD) tissue from two adolescent female patients. MAIN OUTCOME MEASURE: The main outcome measure was to provide quantitative datasets of the vast majority of the transcripts implicated in normal and pathogenic adrenal functioning. RESULTS: The libraries of 28,705 and 31,278 tags represented 14,846 and 16,698 unique mRNAs from the control and PPNAD tissue, respectively. A total of 842 tags from the two libraries did not match any known sequences. We found 127 tags, including 70 no-match tags, to be expressed almost exclusively in control and/or PPNAD adrenals and to be absent or very rare in other human tissues. Examples of well-characterized genes expressed at significantly higher levels in PPNAD included steroidogenic acute regulator, chromogranin A, and those coding for the steroidogenic enzymes P450 cytochromes CYP17A1 and CYP21A2. Pathway analysis revealed Wnt signaling as the most up-regulated in PPNAD. These data were confirmed for selected genes by quantitative RT-PCR and/or immunohistochemistry. CONCLUSIONS: This study was the first of its kind for adrenal tissue and provides important information about the adrenal transcriptome and aberrant signaling in an inherited form of adrenocortical hyperplasia.

Adrenal Cortex Neoplasms↗
PubMed2004

Benefits and pitfalls of using microarrays to monitor bacterial gene expression during infection.

The understanding of bacterial pathogenesis is dependent on techniques that elucidate the underlying genetic and biochemical mechanisms. To study the mechanism of bacterial survival and proliferation within host cells we need accurate tools that tell us what is occurring within the infecting organism. It has now become possible to determine the transcriptional status of in vivo-derived bacteria at the level of the whole genome. Such expression profiles serve as a monitor of the host cell environment as well as an indicator of the bacterial adaptation to its intracellular niche. Here, we review the methods used to produce microarray data for defining the bacterial intracellular transcriptome, and examine the pitfalls in extracting bacterial RNA from the infected host compartment.

Animals↗
PubMed2006

Escherichia coli transcriptome dynamics during the transition from anaerobic to aerobic conditions.

Escherichia coli is a metabolically versatile bacterium that is able to grow in the presence and absence of oxygen. Several previous transcript-profiling experiments have compared separate anaerobic and aerobic cultures. Here the process of adaptation was investigated by determining changes in transcript profiles when anaerobic steady-state cultures were perturbed by the introduction of air. Within 5 min of culture aeration the abundances of transcripts associated with anaerobic metabolism were decreased, whereas transcripts associated with aerobic metabolism were increased. In addition to the rapid switch to aerobic central metabolism, transcript profiling, supported by experiments with relevant mutants, revealed transient changes suggesting that the peroxide stress response, methionine biosynthesis, and degradation of putrescine play important roles during the adaptation to aerobic conditions.

Adaptation, Physiological↗
PubMed2025

PLAID: ultrafast single-sample gene set enrichment scoring.

SUMMARY: In recent years, computational methods have emerged that calculate enrichment of gene signatures within individual samples. These signatures offer critical insights into the coordinated activity of functionally related genes, proteins or metabolites, enabling the identification of unique molecular profiles in individual cells and patients. This strategy is pivotal for patient stratification and advancement of personalized medicine. However, the rise of large-scale datasets, including single-cell profiles and population biobanks, has exposed significant computational inefficiencies in existing methods. Current methods often demand excessive runtime and memory resources, becoming impractical for large datasets. Overcoming these limitations is a focus of current efforts by bioinformatics teams in academia and the pharmaceutical industry, as essential to support basic and clinical biomedical research. To address this critical need, we developed PLAID (Pathway Level Average Intensity Detection), an ultrafast and memory optimized single sample gene set enrichment algorithm that utilizes sparse matrix computation. PLAID delivers highly accurate gene set scoring and surpasses the performance of current methods in single-cell and bulk transcriptomics, and proteomics data. PLAID uniquely integrates the most widely used gene set scoring algorithms, enabling researchers to apply multiple methods for cross-validation with outstanding runtime efficiency and minimal memory requirement. AVAILABILITY AND IMPLEMENTATION: PLAID is implemented in the R language for statistical computing. PLAID source code and installation instructions are available with no restrictions at https://github.com/bigomics/plaid.

Algorithms↗
PubMed2026

CAGNet: a structure-aware clustering-alternated graph network for cell-cell interaction inference in spatial transcriptomics.

MOTIVATION: Understanding cell-cell interactions (CCIs) in spatial transcriptomics is crucial for uncovering the spatial organization and functional heterogeneity of tissues. However, existing graph-based models typically rely on static clustering or fixed adjacency structures, which limits their ability to capture dynamic cellular relationships. RESULTS: We propose CAGNet, a two-stage framework for CCI inference from spatial transcriptomics data. In Stage 1, a Graph Attention Network encoder with joint feature and graph reconstruction learns structure-aware node embeddings from spatial gene expression profiles. In Stage 2, an alternating optimization mechanism iteratively updates cluster centers via KL-guided soft assignment and refines node embeddings through spatial graph reconstruction, establishing a closed-loop between representation learning and clustering. Experiments on three 10x Genomics Visium datasets demonstrate that CAGNet consistently outperforms six CCI inference baselines across ACC, AUC, AP, Precision, Recall, and F1. CAGNet also achieves the highest Adjusted Rand Index on all three datasets against six spatial domain identification methods, confirming that the learned embeddings capture biologically relevant spatial organization. Information-theoretic analysis further shows that CAGNet retains the highest mutual information between input features and learned embeddings among all compared methods. Ablation studies and 5-fold cross-validation confirm the contribution of each component and the reproducibility of the results. AVAILABILITY: The proposed method is implemented in the CAGNet package available at http://github.com/mahan1233333-maker/CAGNet .

Spatial Transcriptomics↗
PubMed2026

Transcriptomic and Proteomic Insights into Mucosal Immune Responses of Asian Seabass (Lates calcarifer) After Sequential Mucosal Vaccination Against Bacterial Pathogens.

Bacterial diseases caused by Flavobacterium covae (Fc), Vibrio harveyi (Vh), Vibrio vulnificus (Vv) and Photobacterium damselae (Pd) seriously constrain Asian seabass aquaculture. Here we dissect the mucosal immune mechanisms engaged by a five-month sequential vaccination strategy that combines nanoemulsion immersion priming with multivalent oral hydrogel boosting. Juvenile seabass were vaccinated, then challenged with F. covae by freshwater immersion and with a Vibrio-Photobacterium (Vh/Vv/Pd) mix by immersion or intraperitoneal injection. Gills were sampled after immersion challenges and intestine after injection, and profiled by RNA sequencing and label-free quantitative proteomics, with selected genes validated by RT-qPCR. Principal component analysis showed clear separation of vaccinated and control fish in all tissues and challenges, indicating a strong and coherent transcriptional reprogramming. Vaccination markedly increased the number of upregulated genes, with Gene Ontology enrichment revealing dominant signatures of ribosome biogenesis, RNA processing, lysosomal organization and immune response. KEGG analysis highlighted cytokine receptor interaction; NOD and Toll-like receptor signaling; oxidative phosphorylation; and phagosome, lysosome and cell adhesion molecule pathways, consistent with heightened antimicrobial readiness. Volcano plots and focused heatmaps showed strong induction of interferon-stimulated genes, cytokines and chemokine receptors, complement components, macrophage mannose receptor, epithelial barrier mediators and numerous immunoglobulin transcripts, with tissue- and challenge-specific patterns. Proteomics corroborated these trends, demonstrating a higher abundance of immunoglobulin heavy chains, complement proteins, cathepsins, heat shock and redox chaperones, ribosomal proteins and cytoskeletal and adhesion regulators in vaccinated mucosae. Integrated pathway mapping linked endothelial adhesion molecules and leukocyte integrins with T cell costimulation networks and an intestinal immune network for immunoglobulin production, including enhanced pIgR-mediated transcytosis. Overall, the sequential vaccination regimen was associated with coordinated transcriptomic and proteomic signatures related to epithelial responses, innate immunity, and humoral immune functions across gill and intestinal tissues. These molecular patterns were accompanied by improved survival following bacterial challenge; however, the present data do not directly demonstrate the functional activity of the inferred immune mechanisms in Asian seabass.

Animals↗
PubMed2026

Malignant epithelial states drive immune dysfunction in ampulla of Vater carcinoma.

BACKGROUND: Ampulla of Vater (AoV) carcinoma is a rare malignancy arising at the junction of intestinal and pancreatobiliary epithelium. Its heterogeneous clinical behavior and histological diversity have hindered therapeutic advances, and the cellular basis of this heterogeneity remains unclear. We aimed to construct a single-cell transcriptomic atlas of AoV carcinoma, with a focus on identifying epithelial subtypes and their interactions with the tumor microenvironment (TME). METHODS: We performed single-cell RNA sequencing on eight primary AoV tumors and four matched normal tissues. Comprehensive clustering and transcriptomic analyses identified cell-type composition, epithelial heterogeneity, and tumor-immune interactions. Findings were validated using deconvolution of bulk RNA-seq data from 62 AoV carcinoma patients. Results Malignant epithelial cells were categorized into four distinct subtypes: Int-Wnt, PB-KRAS, Int-Hypoxia, and Cycling stage. PB-KRAS cells exhibited stem-like transcriptional programs and high genomic instability. Deconvolution analysis of bulk RNA-seq data from the independent AoV cohort revealed that enrichment of the PB-KRAS subtype correlated with tumor recurrence and poor survival. Our immune profiling analysis discovered a significant association between PB-KRAS subtype and GZMK+ CD8+ T cells, which are in a pre-dysfunctional state, alongside SPP1+ macrophages exhibiting immunosuppressive traits. Spatial transcriptome data further supports the immunosuppressive natures of TME around PB-KRAS subtype malignant epithelial cells in AoV carcinoma. CONCLUSIONS: Our study presents a single-cell atlas of AoV carcinoma, highlighting the molecular diversity of malignant epithelium and its association with the immune microenvironment. The PB-KRAS subtype emerges as a stem-like, immunosuppressive tumor state associated with poor prognosis, providing insights for future therapeutic targeting.

Ampulla of Vater carcinoma↗
PubMed2006

A leuC mutation leading to increased L-lysine production and rel-independent global expression changes in Corynebacterium glutamicum.

We previously found by transcriptome analysis that global induction of amino acid biosynthetic genes occurs in a classically derived industrial L-lysine producer, Corynebacterium glutamicum B-6. Based on this stringent-like transcriptional profile in strain B-6, we analyzed the relevant mutations from among those identified in the genome of the strain, with special attention to the genes that are involved in amino acid biosynthesis and metabolism. Among these mutations, a Gly-456-->Asp mutation in the 3-isopropylmalate dehydratase large subunit gene (leuC) was defined as a useful mutation. Introduction of the leuC mutation into a defined L-lysine producer, AHD-2 (hom59 and lysC311), by allelic replacement led to the phenotype of a partial requirement for L-leucine and approximately 14% increased L-lysine production. Transcriptome analysis revealed that many amino acid biosynthetic genes, including lysC-asd operon, were significantly upregulated in the leuC mutant in a rel-independent manner.

Corynebacterium glutamicum↗
PubMed2006

Transcriptional profiling in the adrenal gland reveals circadian regulation of hormone biosynthesis genes and nucleosome assembly genes.

The master circadian pacemaker of the suprachiasmatic nuclei coordinates behavioral and physiological rhythms via synchronization of subordinate peripheral oscillators in the central nervous system and organs throughout the body. Among these organs, the adrenal glands hold a prime position because of their regulatory influence on numerous physiological functions via rhythmic secretion of catecholamines and corticoid hormones into the bloodstream. In this report, the authors perform whole genome microarray hybridization to characterize the circadian transcriptome of the murine adrenal. They show that ~5% of the mouse genome is under circadian control in this gland. Using gene ontology analysis, they identify classes of transcripts that may synchronize adrenal hormone production. The authors' expression profiling also revealed that multiple histone genes implicated in either DNA replication or transcriptional regulation are clock controlled, suggesting a novel way by which the circadian clock may regulate the chromatin state.

Adrenal Glands↗
PubMed2005

Interferon-gamma-induced gene expression in CD34 cells: identification of pathologic cytokine-specific signature profiles.

Hematopoietic effects of interferon-gamma (IFN-gamma) may be responsible for certain aspects of the pathology seen in bone marrow failure syndromes, including aplastic anemia (AA), paroxysmal nocturnal hemoglobinuria (PNH), and some forms of myelodysplasia (MDS). Overexpression of and hematopoietic inhibition by IFN-gamma has been observed in all of these conditions. In vitro, IFN-gamma exhibits strong inhibitory effects on hematopoietic progenitor and stem cells. Previously, we have studied the transcriptome of CD34 cells derived from patients with bone marrow failure syndromes and identified characteristic molecular signatures common to some of these conditions. In this report, we have investigated genome-wide expression patterns after exposure of CD34 and bone marrow stroma cells derived from normal bone marrow to IFN-gamma in vitro and have detected profound changes in the transcription profile. Some of these changes were concordant in both stroma and CD34 cells, whereas others were specific to CD34 cells. In general, our results were in agreement with the previously described function of IFN-gamma in CD34 cells involving activation of apoptotic pathways and immune response genes. Comparison between the IFN-gamma transcriptome in normal CD34 cells and changes previously detected in CD34 cells from AA and PNH patients reveals the presence of many similarities that may reflect molecular signature of in vivo IFN-gamma exposure.

Antigens, CD34↗
PubMed2006

Expression profiling of Chondrus crispus (Rhodophyta) after exposure to methyl jasmonate.

Methyl jasmonate (MeJA) is a plant hormone important for the mediation of signals for developmental processes and defence reactions in higher plants. The effects of MeJA and the signalling pathways on other photosynthetic organism groups are largely unknown, even though MeJA may have very important roles. Therefore the effects of MeJA in a red alga were studied. A medium-scale expression profiling approach to identify genes regulated by MeJA in the red seaweed Chondrus crispus is described here. The expression profiles were studied 0, 2, 4, 6, 12, and 24 h after the addition of MeJA to the seawater surrounding the algae. The changes in the transcriptome were monitored using cDNA microarrays with 1920 different cDNA representing 1295 unique genes. The responses of selected genes were verified with real-time PCR and the correlation between the two methods was generally satisfying. The study showed that 6% of genes studied showed a response to the addition of MeJA and the most dynamic response was seen after 6 h. Genes that showed up-regulation included several glutathione S-transferases, heat shock protein 20, a xenobiotic reductase, and phycocyanin lyase. Down-regulated transcripts included glucose kinase, phosphoglucose isomerase, and a ribosomal protein. A comparison between different functional groups showed an up-regulation of stress-related genes and a down-regulation of genes involved in energy conversion and general metabolism. It is concluded that MeJA, or a related compound, has a physiological role as a stress hormone in red algae. This study represents to our knowledge the first analysis of gene expression using cDNA microarrays in a red macroalga.

Acetates↗
PubMed2006

Pathognomonic genetic expression profile within peripheral blood mononuclear cells of rheumatic heart disease patients.

The present study was addressed to understand as to how the expression of genes, that play crucial role in both inflammation and autoimmune process, within blood mononuclear cells are effected by the molecular mimicry between streptococcal antigen and heart tissue recognized as main contributor towards the genesis of rheumatic heart disease (RHD). Such a study for the first time revealed that as compared to genomic profile within normal blood mononuclear cells, the cells derived from rheumatic heart disease patients exhibited significantly higher expression of genes coding for IL-8, IFN-gamma and CX3CR1 coupled with significant downregulation of CD36 mRNA expression. Based upon these results, we propose that maintenance of such a pathognomonic transcriptome within blood mononuclear cells may be responsible for the initiation and progression of rheumatic heart disease.

Adult↗
PubMed2026

Cooccurrence of Homologous Recombination Deficiency and Mismatch Repair Deficiency in Colorectal Cancer.

Homologous recombination deficiency (HRD) in colorectal cancer (CRC) remains largely unexplored. In contrast, mismatch repair deficiency (dMMR) occurs in ∼15% of patients with CRC. Although HRD and dMMR have historically been regarded as mutually exclusive, emerging evidence suggests that this mutual exclusivity may not be absolute. Here, we conducted a retrospective cohort study utilizing genomic and transcriptomic data to define HRD status in a Chinese dMMR CRC cohort (n = 99). Multiple machine learning approaches were employed to analyze the expression profiles of these tumors and to develop a classifier distinguishing HRD from homologous recombination proficiency (HRP) in dMMR CRCs. In the Chinese dMMR CRC cohort, 66% of tumors were classified as HRD. Compared with the HRP group, the HRD group had a significantly higher tumor mutational burden and better outcomes. The derived expression signature, comprising eight genes, successfully predicted HRD status in dMMR tumors with high accuracy in the training set (AUC = 0.88, Naïve Bayes) and the test set (AUC = 0.87). In this study, a subset of dMMR CRC tumors with co-occurring HRD was identified, which may have potential implications for patient stratification and the application of targeted therapies, such as PARP inhibitors, in this molecular subgroup.

colorectal cancer↗
PubMed2005

Genomic technologies and the interrogation of the transcriptome.

Functional genomics refers to the study of whole genomes and the function of its constituent parts to explain biological processes. Though these investigations may involve whole proteome analysis, the primary focus is on the transcriptome and how it is regulated. Recent advances in technologies that can interrogate cellular transcripts on a genome-wide scale seek the complete disclosure of the transcriptome over time-intervals and across many different cellular states. This massively complex data when viewed as a whole can provide surprisingly precise assessment of cellular conditions. Moreover, these data can define hierarchies of importance and have shown us new transcriptional elements. Herein, we describe the technologies and the experimental strategies to study the transcriptome that would be pertinent to cancer and ageing research.

Animals↗