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PubMed2026

Dual-transcriptomic analysis of human nasal transcriptome and microbiome reveals host-bacteria associations in symptomatic respiratory infection.

BACKGROUND: The human nasopharynx is colonized by a diverse community of commensal microbiota linked to many respiratory diseases, yet their associations with the host remain unclear. RESULTS: In this study, we introduced a dual-transcriptomics analysis strategy, which can characterize the host transcriptome and microbiome from nasal samples simultaneously. We applied this workflow to a local SARS-CoV-2 cohort with 76 asymptomatic infected patients, among whom 52 (68.42%) developed symptomatic infection during a 1-week follow-up period. Nasal swabs were collected from all 76 patients at enrollment and from 73 patients at one-week later follow-up. We detected a median of 8.94% reads that did not map to the human genome across all 149 samples, among which around half (median 49.68%) were successfully mapped to microbiome genome. Meta-transcriptomic analysis detected significantly higher SARS-related coronavirus loads in samples from the symptomatic group at enrollment (P = 0.004), and both groups showed decreased loads one week later (symptomatic, P = 0.001; asymptomatic, P = 0.035). Compared with benchmarking 16 S rRNA sequencing on 53 samples, our computational strategy showed high correlation of relative abundance in all top 20 genera (median Rho = 0.90, Pmax < 0.001). A total of 670 bacteria species were identified to show a relative abundance ≥ 0.01% in at least 10% samples. Differential abundance analysis identified 76 species (DASs) from six phyla with significantly decreased abundance in samples from the symptomatic group (log2(fold change or FC) < -1 and adjusted P < 0.05) compared to the asymptomatic group at enrollment. Integrating these symptom-associated DASs with host's gene expression using an expression quantitative trait bacteria (eQTB) model, we found 45 symptom-associated DASs identified at enrollment were significantly associated with one to 14 genes (adjusted P < 0.05). GSEA showed a series of symptom-associated DASs were significantly correlated with pathways related to olfactory function, keratinocyte differentiation, and DNA methylation. CONCLUSIONS: In summary, our dual-transcriptomic analysis strategy effectively characterized host-microbiome associations, offering insights into microbial contributions to respiratory diseases.

Humans↗

PubMed2025

Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator.

Single-cell RNA-sequencing (scRNA-seq) techniques can measure gene expression at single-cell resolution but lack spatial information. Spatial transcriptomics (ST) techniques simultaneously provide gene expression data and spatial information. However, the data quality of the spatial resolution or gene coverage is still much lower than the quality of the single-cell transcriptomics data. To this end, we develop a ST-Aided Locator for single-cell transcriptomics (STALocator) to localize single cells to corresponding ST data. Applications on simulated data showed that STALocator performed better than other localization methods. When applied to the human brain and squamous cell carcinoma data, STALocator could robustly reconstruct the relative spatial organization of critical cell populations. Moreover, STALocator could enhance gene expression patterns for Slide-seqV2 data and predict genome-wide gene expression data for fluorescence in situ hybridization (FISH) and Xenium data, leading to the identification of more spatially variable genes and more biologically relevant Gene Ontology (GO) terms compared with the raw data. A record of this paper's transparent peer review process is included in the supplemental information.

Single-Cell Analysis↗

PubMed2026

Transcriptome-wide association analysis of Alzheimer's disease: construction and clinical validation of transcriptomic risk scores.

Early identification of individuals at high risk for Alzheimer's disease (AD) is crucial for disease prevention and intervention. This study aims to develop AD-specific transcriptomic risk scores (TRSs) through multi-tissue transcriptome-wide association study (TWAS) and to evaluate its clinical utility in AD diagnosis and risk prediction. Using GWAS summary statistics combined with expression quantitative trait loci (eQTL) data from 14 tissues, a multi-tissue TWAS approach was applied to identify AD-associated genes. Peripheral blood RNA expression data from the ADNI and GEO databases were used to construct the AD-specific TRSs. The associations of TRSs with AD pathological features and cognitive function were assessed in two independent cohorts. Furthermore, the diagnostic performance, differential diagnostic capability, and risk prediction efficiency of TRSs were evaluated. The TWAS identified 131 genes significantly associated with AD. The TRSs were significantly elevated in patients with AD and mild cognitive impairment (MCI) compared to cognitively normal (CN) individuals, and showed significant correlations with AD pathological markers and cognitive performance. When combined with APOE4 status, the TRSs demonstrated robust diagnostic ability for AD and MCI. When combined with age, the TRSs showed good diagnostic performance in distinguishing AD from frontotemporal dementia (FTD) (AUC = 0.86). Additionally, the TRSs effectively predicted the risk of progression to AD in non-AD individuals (HR = 1.74). The AD-specific TRSs developed in this study shows promising clinical utility in AD diagnosis, differential diagnosis, and risk prediction, providing valuable translational medical evidence for early screening and precision prevention of Alzheimer's disease.

Humans↗

PubMed2005

Cell-type-specific transcriptomics in chimeric models using transcriptome-based masks.

Regulatory networks involving different cell types control inflammation, morphogenesis and tissue homeostasis. Cell-type-specific transcriptional profiling offers a powerful tool for analyzing such cross-talk but is often hampered by mingling of cells within a tissue. Here, we present a novel method that performs cell-type-specific expression measurements without prior cell separation. This involves inter-species transplantation or chimeric co-culture models among which the human mouse system is frequently used. Here, we exploit the sufficiently divergent transcriptomes of human and mouse in conjunction with high-density oligonucleotide arrays. This required a masking procedure based on transcriptome databases and exhaustive fuzzy mapping of oligonucleotide probes onto these data. The approach was tested in a human-mouse experiment, demonstrating that we can efficiently measure species-specific transcriptional profiles in chimeric RNA samples without physically separating cells. Our results stress the importance of transcriptome databases with accurate 3' mRNA termination for computational prediction of accurate probe masks. We find that most human and mouse 3'-untranslated region contain unique stretches to allow for an effective control of cross-hybridization between the two species. This approach can be applied to xenograft models studying tumor-host interactions, morphogenesis or immune responses.

Animals↗

PubMed2006

Insights into the immune transcriptome of the shrimp Litopenaeus vannamei: tissue-specific expression profiles and transcriptomic responses to immune challenge.

Infectious disease constitutes a major obstacle to the sustainability of shrimp aquaculture worldwide and a significant threat to natural populations of shrimp and other crustacea. The study of the shrimp immune system, including the response to viral infection, has been hampered by a relative lack of molecular genetic information and of tools suitable for high-throughput assessment of gene expression. In this report, the generation of a cDNA microarray encompassing 2,469 putative unigenes expressed in gills, circulating hemocytes, and hepatopancreas of Litopenaeus vannamei is described. The unigenes printed on the microarray were derived from the analyses of 7,021 expressed sequence tags obtained from standard cDNA libraries as well as from libraries generated by suppression subtractive hybridization, after challenging shrimp with a variety of immune stimuli. The general utility of the cDNA microarray was demonstrated by interrogating the array with labeled RNA from four different shrimp tissues (gills, hemocytes, hepatopancreas, and muscle) and by analyzing the transcriptomic response of shrimp to a lethal challenge with white spot syndrome virus. Our results indicate that white spot syndrome virus infection upregulates (in the hepatopancreas) genes encoding known and potential antimicrobial effectors, while some genes involved in protection from oxidative stress were found to be downregulated by the virus.

Animals↗

PubMed2004

[Transcriptome analyses and transcriptome databases].

Explore the source record for details and available documents.

Animals↗

PubMed2000

Analysis of the yeast transcriptome with structural and functional categories: characterizing highly expressed proteins.

We analyzed 10 genome expression data sets by large-scale cross-referencing against broad structural and functional categories. The data sets, generated by different techniques (e.g. SAGE and gene chips), provide various representations of the yeast transcriptome (the set of all yeast genes, weighted by transcript abundance). Our analysis enabled us to determine features more prevalent in the transcriptome than the genome: i.e. those that are common to highly expressed proteins. Starting with simplest categories, we find that, relative to the genome, the transcriptome is enriched in Ala and Gly and depleted in Asn and very long proteins. We find, furthermore, that protein length and maximum expression level have a roughly inverse relationship. To relate expression level and protein structure, we assigned transmembrane helices and known folds (using PSI-blast) to each protein in the genome; this allowed us to determine that the transcriptome is enriched in mixed alpha-beta structures and depleted in membrane proteins relative to the genome. In particular, some enzymatic folds, such as the TIM barrel and the G3P dehydrogenase fold, are much more prevalent in the transcriptome than the genome, whereas others, such as the protein-kinase and leucine-zipper folds, are depleted. The TIM barrel, in fact, is overwhelmingly the 'top fold' in the transcriptome, while it only ranks fifth in the genome. The most highly enriched functional categories in the transcriptome (based on the MIPS system) are energy production and protein synthesis, while categories such as transcription, transport and signaling are depleted. Furthermore, for a given functional category, transcriptome enrichment varies quite substantially between the different expression data sets, with a variation an order of magnitude larger than for the other categories cross-referenced (e.g. amino acids). One can readily see how the enrichment and depletion of the various functional categories relates directly to that of particular folds.

Amino Acids↗

PubMed2006

The hepatic transcriptome in human liver disease.

The transcriptome is the mRNA transcript pool in a cell, organ or tissue with the liver transcriptome being amongst the most complex of any organ. Functional genomics methodologies are now being widely utilized to study transcriptomes including the hepatic transcriptome. This review outlines commonly used methods of transcriptome analysis, especially gene array analysis, focusing on publications utilizing these methods to understand human liver disease. Additionally, we have outlined the relationship between transcript and protein expressions as well as summarizing what is known about the variability of the transcriptome in non-diseased liver tissue. The approaches covered include gene array analysis, serial analysis of gene expression, subtractive hybridization and differential display. The discussion focuses on primate whole organ studies and in-vitro cell culture systems utilized. It is now clear that there are a vast number research opportunities for transcriptome analysis of human liver disease as we attempt to better understand both non-diseased and disease hepatic mRNA expression. We conclude that hepatic transcriptome analysis has already made significant contributions to the understanding of human liver pathobiology.

Journal Article↗

PubMed2026

Coordinated inflammatory macrophage and vascular smooth muscle cell remodeling signatures in human atherosclerosis: An integrative single-cell and bulk transcriptomic analysis.

Atherosclerotic plaque progression is shaped by coordinated inflammatory and remodeling programs involving immune cells and vascular wall cells. Inflammatory macrophage activation and vascular smooth muscle cell (VSMC) phenotypic remodeling are central features of human atherosclerosis, but their transcriptomic relationships during plaque progression remain incompletely characterized. This study integrated single-cell and bulk transcriptomic datasets to examine highly inflammatory macrophage states, VSMC remodeling-related transcriptional programs, and candidate ligand-receptor expression patterns in human atherosclerotic plaques. Human atherosclerotic plaque single-cell RNA sequencing data from GSE260657 and bulk transcriptomic data from GSE28829 were analyzed. After quality control, 7628 cells were retained for single-cell analysis. Major cell types were annotated using canonical markers, followed by reclustering of macrophages and VSMC-related cells. Functional module scoring, differential expression analysis, Gene Ontology biological process enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed to characterize macrophage transcriptional states. Slingshot was applied to infer VSMC pseudotime ordering. CellChat and NicheNet were used to prioritize candidate ligand-receptor expression patterns and ligand-associated VSMC target gene programs. External bulk transcriptomic analysis was performed to examine whether single-cell-derived inflammatory and remodeling signatures were represented at the tissue-transcriptome level during plaque progression. Macrophage reclustering identified a highly inflammatory macrophage state characterized by prominent inflammatory activation, cytokine-response, and stress-response features. Genes upregulated in this population were enriched in pathways related to tumor necrosis factor (TNF) response, nuclear factor kappa B signaling, leukocyte activation, cytokine signaling, lipid and atherosclerosis, toll-like receptor signaling, and inflammasome-associated inflammation. VSMC reclustering revealed contractile VSMCs, PTHLH+ synthetic VSMCs, KRT7+ VSMC-like cells, interferon-responsive VSMCs, pericyte-like mural cells, and osteogenic/modulated VSMCs. Pseudotime analysis showed a broad contractile-to-osteogenic/modulated transcriptional continuum accompanied by increased expression of remodeling-associated genes and selected inflammatory or remodeling-associated receptor genes. CellChat and NicheNet analyses prioritized candidate ligand-receptor and ligand-associated target gene expression patterns involving SPP1-CD44, TNF-TNFRSF1A, IL1B-IL1R1/IL1RAP, MIF-ACKR3, PDGFB-PDGFRB, and FN1-SDC1/ITGB1. In GSE28829, inflammatory macrophage-, osteogenic/modulated VSMC-, candidate ligand-receptor expression-, SPP1-CD44 candidate axis-, and NicheNet-prioritized target program-related signatures were more prominent in advanced plaques and were positively correlated with each other. This integrative transcriptomic analysis identified a highly inflammatory macrophage state and a VSMC remodeling continuum in human atherosclerotic plaques. Candidate ligand-receptor and ligand-associated target gene expression patterns linked inflammatory macrophage activation with osteogenic/modulated VSMC remodeling at the computational level. External bulk data further showed coordinated enrichment of inflammatory and remodeling signatures in advanced plaques. These findings provide a descriptive and hypothesis-generating transcriptomic framework for understanding inflammatory macrophage activation and VSMC remodeling in human atherosclerosis.

atherosclerosis↗

PubMed2026

Evolutionary Reorganization of Transcriptomic Architecture Across a UVB Tolerance Gradient in Fish.

Environmental stressors such as ultraviolet radiation impose strong selective pressures on organisms, yet how adaptation to such stressors shapes transcriptomic responses at the network level remains poorly understood. Although stratospheric ozone is recovering globally, substantial regional variation in UV exposure persists, particularly in high-altitude environments where extreme UV levels can occur. Here, we compared three fish models representing distinct biological responses to UVB exposure: wild-type zebrafish (Danio rerio), a melanin-deficient zebrafish mutant (nacre) lacking a major protective mechanism against UVB damage, and the high-altitude Andean killifish Orestias ascotanensis, a species naturally exposed to extreme UVB radiation. Together, these models define a gradient spanning physiological protection, impaired protection, and evolutionary adaptation to UVB stress. Using RNA-seq and protein-protein interaction networks, we show that transcriptomic responses differ markedly across this gradient. Wild-type and nacre zebrafish exhibited relatively limited transcriptomic changes (∼2%-2.4% of genes changing), whereas O. ascotanensis displayed a large-scale and highly coordinated response (∼21.6% of genes changing) characterized by functionally specialized networks enriched in DNA repair pathways. These differences involved not only transcriptomic magnitude but also marked reorganization of transcriptomic architecture. Integration with positive selection analyses revealed that positively selected genes were concentrated within highly interconnected regions of transcriptomic networks, consistent with adaptation involving network reorganization. Furthermore, ortholog-based analyses suggest that adaptive responses involve differential reorganization of a conserved functional background. Together, our results support a model in which adaptation to environmental stress is associated with the reorganization of conserved transcriptomic networks across physiological and evolutionary contexts, providing a systems-level perspective on the molecular basis of adaptation.

UVB radiation↗

PubMed2004

Dynamic transcriptome of mice.

Life science in the 21st century is developing rapidly through the structural analysis of biomolecules, the completion of the human genome sequence and the analysis of transcriptomes. The mouse transcriptome has been comprehensively analyzed using a gene discovery approach to collect full-length cDNA (FL-cDNA) clones. The framework of the transcriptome was then mapped out by an international Functional ANnoTation Of Mouse cDNA (FANTOM) effort, and a significant new population of noncoding transcripts was discovered. The geographical analogy of a second "RNA continent," separate from the "continent" of expressed proteins, aids the visualization of this concept. An unexpected number of variations was discovered in the mouse transcriptome. The animal transcriptome has evolved to produce several transcripts and proteins from a single "transcriptional unit". Transcriptome analysis has given rise to the FL-cDNA database and to the 60 770 FANTOM FL-cDNA clone set, and the DNABook was developed as an easier way to distribute these clones. In conjunction with genome sequence databases, transcriptome databases and clone banks will be platforms for developing advanced databases of gene function (e.g. the Genome Function Database). This will enable life science to make rapid progress towards understanding life as a system of molecules.

Animals↗

PubMed2005

The role of transcriptome analysis in pre-clinical toxicology.

A major benefit of the genomics revolution in biomedical research has been the establishment of transcriptome analysis as an enabling technology in the drug development process. Nowhere in the realm of drug development has the expectation of the impact of transcriptome analysis been greater than in the area of pre-clinical toxicology. Transcriptome analysis, along with other new high-content data generating technologies, has the potential to radically improve the drug safety assessment process by allowing drug development teams to identify potential toxicity liabilities earlier, and thus proceed only with those molecules that have both efficacy at the target and a low potential for toxicity in the human population. In this review we will briefly describe the major ways in which transcriptome analysis is being applied in the pre-clinical safety assessment process, focusing primarily on four areas where transcriptome analysis has already begun to have impact. These include using transcriptome analysis to: 1) understand mechanisms of toxicity: 2) predict toxicity: 3) develop in vivo and in vitro surrogate models and screens; and, 4) develop toxicity biomarkers. We will close by briefly addressing future trends and needs in the application of transcriptome analysis to drug safety assessment.

Amyloid Precursor Protein Secretases↗

PubMed2026

Transcriptomic responses of gill and intestinal tissues in Nile tilapia (Oreochromis niloticus) to bacterial infection following sequential nanoimmersion and hydrogel-based multivalent vaccination.

Bacterial pathogens, including Flavobacterium oreochromis, Aeromonas veronii, Streptococcus agalactiae, and Edwardsiella tarda, represent major infectious threats to Nile tilapia (Oreochromis niloticus). A multivalent vaccination strategy integrating cationic nanoemulsion immersion with oral hydrogel boosters was developed to investigate tissue-specific immune responses at the transcriptomic level. Gill tissues were collected following immersion challenge and intestinal tissues following intraperitoneal injection challenge, reflecting the physiologically relevant infection biology of each pathogen and the mechanistic rationale of each delivery platform. RNA sequencing (RNA-seq) generated high-quality datasets (mapping rate > 81.64%) with strong concordance to quantitative real-time PCR (qRT-PCR) validation (r = 0.83). Comparative transcriptomic analysis revealed distinct yet complementary immune signatures between tissues. Gill transcriptomes were enriched in phagosome, focal adhesion, extracellular matrix-receptor interaction (ECM-receptor interaction), and cytokine-cytokine receptor interaction pathways, accompanied by increased expression of major histocompatibility complex class I/II (MHC class I/II), mannose receptor, αVβ3 integrin, and calnexin, indicating innate activation, enhanced phagocytic capacity, epithelial barrier reinforcement, and adaptive immune coordination. Intestinal transcriptomes showed predominant enrichment of adaptive immune pathways, including the intestinal immune network for immunoglobulin (Ig) production, Forkhead box O (FoxO) signaling, and mitogen-activated protein kinase (MAPK) signaling, with increased expression of T-cell receptor (TCR), inducible T-cell co-stimulator ligand (ICOS-L), C-X-C chemokine receptor type 4 (CXCR4), and polymeric immunoglobulin receptor (pIgR), reflecting T and B cell coordination, lymphocyte trafficking, and mucosal immunoglobulin transport, alongside innate engagement through phagosome pathway enrichment. Shared upregulation of MHC class II, B-cell receptor (BCR) signaling, integrin alpha M (ITGAM), and immunoglobulin-associated components across both tissues suggests coordinated mucosal immune activation through a conserved immune module, warranting direct experimental validation. Collectively, these findings provide transcriptomic evidence that this vaccination strategy elicits an integrated, tissue-specialized immune response, advancing mechanistic understanding of gill and intestinal immunity in vaccine-induced protection of teleost fish.

Animals↗

PubMed2026

Dynamic effects of short-term storage temperature and duration on the transcriptome and functional pathways of umbilical cord blood-derived NK cells.

OBJECTIVE: This study aims to elucidate the dynamic impact of different storage conditions (temperature and time) on the function of natural killer (NK) cells derived from umbilical cord blood (UCB) at the transcriptome level, providing a theoretical basis for optimizing the standardized post-collection processing protocol of UCB in clinical settings. METHODS: Four healthy full-term UCB samples were collected and assigned to a fresh control group (0H) and experimental groups stored at 4 °C (4C) or 25 °C (RT) for 24 h (24H) and 72 h (72H). Umbilical cord blood mononuclear cells (CBMCs) were isolated and expanded in vitro to derive NK cells. Using RNA sequencing (RNA-seq) technology, combined with principal component analysis (PCA), screening of differentially expressed genes (DEGs), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, the effects of storage conditions on the transcriptome of NK cells were comprehensively analyzed. RESULTS: The results indicated that storage time was the primary factor causing transcriptomic differences. Compared to the 0H group, storage for 24 h induced a limited number of Differentially Expressed Genes (DEGs) (only 11 in the 24H-RT group), indicating overall transcriptome stability. In contrast, storage for 72 h triggered profound transcriptomic reprogramming, with DEGs significantly enriched in immune activation-related pathways. Specifically, at the 72-h time point, storage at 4 °C compared to 25 °C prevented the downregulation of key metabolic pathways such as 'response to decreased oxygen levels' and 'regulation of leukocyte cell-cell adhesion'. CONCLUSION: CBMC-derived NK cells can tolerate up to 24 h of ex vivo storage while maintaining transcriptome and core functional stability. However, extending the ex vivo storage period to 72 h leads to significant reprogramming in the expression of immune and metabolism-related genes. Notably, the degree of metabolic suppression under refrigerated conditions at 4 °C was less pronounced than that at 25 °C room temperature storage. This study recommends that the ex vivo storage time of UCB should ideally be limited to within 24 h, with room temperature storage being a viable option. If prolonged storage is necessary, refrigeration at 4 °C is advised.

Humans↗

PubMed2026

Exogenous ABA enhances cold tolerance of Rhododendron yedoense var. poukhanense under subzero temperature: integrating physiology, transcriptome, and proteome.

Low temperature limits the growth and ornamental value of evergreen shrubs. Rhododendron yedoense var. poukhanense, an important ornamental shrub from Northeast China, frequently suffers freezing damage during winter. While exogenous abscisic acid (ABA) enhances cold tolerance in many plants, its molecular mechanisms at subzero temperatures remain poorly understood in non-model species lacking chromosome-level reference genomes. This study investigated the effects of exogenous ABA on freezing tolerance in R. yedoense var. poukhanense at -4 °C using an integrated physiological, transcriptomic, and proteomic approach. Cutting seedlings were subjected to four treatments: CK (22°C control), A (22°C + ABA), LT (-4°C), and ALT (-4°C + ABA). Photosynthetic pigments, osmotic regulation substances, antioxidant enzyme activities, and malondialdehyde (MDA) content were measured. Transcriptome sequencing and quantitative proteomics were performed, and transcriptome data were validated by quantitative real-time PCR (qRT-PCR) of 15 selected genes. ABA pretreatment reduced visible cold injury severity, partially preserved photosynthetic pigments, decreased MDA content by 28.7%, and promoted recovery of catalase (+43.6%), superoxide dismutase (+31.1%), and peroxidase (+20.0%) activities under freezing stress. Transcriptome analysis revealed 8, 444 differentially expressed genes (DEGs) in LT versus CK and 6, 481 DEGs in ALT versus CK, representing a 23% reduction in transcriptional reprogramming scope attributable to ABA priming. The ALT versus LT comparison identified only 1, 690 additional DEGs, indicating that most cold-responsive genes were pre-activated during the ABA priming phase. Proteome analysis identified 1, 461 differentially expressed proteins (DEPs) in ALT versus CK. Integrated analysis revealed extensive post-transcriptional regulation, with transcript-protein concordance of only 1.0-4.1%, and co-enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in both omics layers. qRT-PCR validation confirmed high reliability of the transcriptome data (R2 = 0.8500). These findings demonstrate that exogenous ABA enhances freezing tolerance through multi-layered molecular regulation encompassing transcriptional buffering, translational reprogramming, and functional reallocation from photosynthesis to stress protection. This study provides the first integrated physiology-transcriptome-proteome framework for ABA-mediated freezing tolerance in an evergreen ornamental shrub and offers theoretical support for ABA-based winter protection strategies.

Rhododendron yedoense var. Poukhanense↗

PubMed2026

Comprehensive transcriptomics and proteomics analysis of neointima formation in human saphenous vein: implications for bypass graft disease.

Human saphenous veins (SVs) are widely used as grafts in coronary artery bypass (CABG) surgery but often fail due to neointima formation. Little is known, however, regarding the cellular, transcriptomic, and proteomic dynamics of neointima formation in human veins. Here, we performed transcriptomics and proteomics analysis in an ex vivo tissue culture model of neointima formation in human SVs procured for CABG surgery. Histological examination demonstrated significant elastin degradation and neointima formation (indicated by increased neointima area and neointima-to-media ratio) in SVs subjected to tissue culture. Analysis of data from 72 patients suggests that the progression of SV remodeling and neointima formation differs according to sex and body mass index, which is negatively associated with neointima formation in males only. RNA sequencing demonstrated upregulation of proinflammatory and proliferation-related genes during neointima formation and identified novel processes, including increased cellular stress and DNA damage responses, reflecting tissue trauma associated with vein harvesting. Proteomic analysis identified upregulated extracellular matrix-related and coagulation/thrombosis proteins and downregulated metabolic proteins. Spatial transcriptomics, used to infer regionally enriched gene expression, suggested dynamic alterations in fibroblast and vascular smooth muscle cell (VSMC) states during neointima formation. Specifically, we identified the emergence of HES1+ and matrix metalloproteinase 2- and 14-positive (MMP2+/MMP14+) expression in VSMCs and fibroblasts, respectively, during neointima formation. Furthermore, our data suggest that MIR647, identified through screening, maintains VSMC contractile gene expression. Our findings suggest dynamic transcriptomic and proteomic changes during neointima formation in human veins and provide useful mechanistic information for the pathogenesis of SV graft disease.NEW & NOTEWORTHY Using multiomics and spatial transcriptomics, we uncover dynamic molecular and cellular changes driving neointima proliferation in human saphenous veins, the most common conduit for bypass surgery. Our study highlights sex- and body mass index-associated differences, novel fibroblast and smooth muscle cell states, and a role for microRNA-647 in preserving vascular contractile phenotype. These findings provide new insight into the mechanisms of vein graft failure and may guide future strategies to improve coronary bypass outcomes.

Humans↗

PubMed2006

Integrative investigation of metabolic and transcriptomic data.

BACKGROUND: New analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time, existing methods are being modified to serve the objectives of systems biology and permit the interpretation of the huge datasets currently being generated by high-throughput methods. RESULTS: Transcriptomic and metabolic data from chemostat fermentors were collected with the aim of investigating the relationship between these two data sets. The variation in transcriptome data in response to three physiological or genetic perturbations (medium composition, growth rate, and specific gene deletions) was investigated using linear modelling, and open reading-frames (ORFs) whose expression changed significantly in response to these perturbations were identified. Assuming that the metabolic profile is a function of the transcriptome profile, expression levels of the different ORFs were used to model the metabolic variables via Partial Least Squares (Projection to Latent Structures--PLS) using PLS toolbox in Matlab. CONCLUSION: The experimental design allowed the analyses to discriminate between the effects which the growth medium, dilution rate, and the deletion of specific genes had on the transcriptome and metabolite profiles. Metabolite data were modelled as a function of the transcriptome to determine their congruence. The genes that are involved in central carbon metabolism of yeast cells were found to be the ORFs with the most significant contribution to the model.

Algorithms↗

PubMed2006

Prognostic testing in uveal melanoma by transcriptomic profiling of fine needle biopsy specimens.

Many uveal melanoma patients die of metastasis despite ocular treatment. Transcriptomic profiling of enucleated tumors can identify patients at high metastatic risk. Because most uveal melanomas do not require enucleation, a biopsy would be required for this analysis. Here, we establish the feasibility of transcriptomic analysis of uveal melanomas from fine needle aspirates. Transcriptomic profiles were analyzed from postenucleation "mock" needle biopsies and matching tumors from eight enucleated eyes and from fine needle aspirates in 17 uveal melanomas before radiotherapy. Predictive accuracy was assessed using a weighted voting classifier optimized for probe set selection using a minimal redundancy/maximum relevance algorithm. Transcriptomic profiles from mock biopsies were highly similar to those from their matching tumor samples (P < 0.0001). Transcriptomic profiles from fine needle aspirates clustered into two classes with discriminating probe sets that overlapped significantly with those for our published classification (P < 0.00001). No loss of predictive accuracy was identified among eight needle aspirates obtained from a distant location. Thus, it is feasible to obtain RNA of adequate quality and quantity to perform transcriptomic analysis on uveal melanoma samples obtained by fine needle biopsy. This method can be applied to specimens obtained from distant geographic locations and can stratify uveal melanoma patients based on metastatic risk.

Adult↗