SEARCH · PubMed Health

Results for “Transcriptomics”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources

PubMed2025

Longitudinal Multi-Organ Transcriptomic Atlas of Salt-Induced Hypertension.

BACKGROUND: Salt-sensitive hypertension is a prevalent and clinically significant subtype of hypertension, where increased dietary salt intake elevates blood pressure and causes injury to multiple organ systems. Despite extensive research, dynamic molecular changes and conserved versus organ-specific transcriptional programs in hypertensive multi-organ damage remain poorly understood. Defining complex molecular pathways both in a temporal sequence and in an organ-specific manner is essential for developing targeted, precision therapies to mitigate hypertensive disease burden. METHODS: We generated a longitudinal multi-organ transcriptomic atlas of salt-sensitive hypertension using RNA sequencing of kidney cortex, kidney medulla, heart, and liver from Dahl salt-sensitive rats across four disease stages. A comprehensive bioinformatic analysis mapped dynamic transcriptional programs, evaluated 50 biological pathways, and defined upstream regulators. Histological and biochemical assays complemented transcriptomic analysis, while integration with human genome-wide association studies (GWAS) and compound-transcriptome analysis provided translational insights and identified candidate therapeutics. RESULTS: Salt-induced hypertension elicited both shared and tissue-specific transcriptional programs that evolved with disease progression. The kidney medulla showed robust early immune activation with metabolic suppression, while the cortex exhibited transient metabolic activation before declining and initiating immune activation. The liver and heart showed time-dependent metabolic and inflammatory remodeling. Cross-organ comparisons revealed a shared early proliferative response that converged on proinflammatory and fibrotic signatures. Upstream regulator analysis identified 79 time- and tissue-specific transcription factors associated with gene expression dynamics. GWAS integration analysis revealed endocrine signaling, ion transport, lipid metabolism, and detoxification as conserved pathways across species, underscoring the translational relevance of the model and study. Predictive compound-transcriptome analyses identified kinase inhibitors targeting phosphoinositide 3-kinase, mechanistic target of rapamycin and cyclin-dependent kinases as top candidates to counteract maladaptive transcriptional programs. CONCLUSIONS: This study defines temporal and tissue-specific transcriptomic remodeling in salt-sensitive hypertension and highlights the need for precision interventions to prevent progressive organ damage.

Journal Article↗

PubMed2026

Transcriptomic Profiling Reveals NF-κB-Associated Immune Regulatory Signatures Underlying the Regenerative Effects of Hypoxia-Preconditioned Tendon Stem Cell-Derived Extracellular Vesicles.

Remodeling of the immune microenvironment is a critical determinant of tissue regeneration, yet the molecular programs associated with the enhanced therapeutic activity of hypoxia-preconditioned extracellular vesicles remain incompletely defined. In this study, we investigated the regenerative and immunomodulatory effects of hypoxia-preconditioned tendon stem cell-derived extracellular vesicles (Hypo-EVs) and employed transcriptomic profiling to identify molecular signatures associated with their biological activity. The therapeutic effects of Hypo-EVs were evaluated using a rat patellar tendon defect model and lipopolysaccharide-stimulated RAW 264.7 macrophages. Histological analysis, immunostaining, biomechanical testing, and reverse transcription-quantitative polymerase chain reaction were performed to assess tendon healing and macrophage polarization, while RNA sequencing was conducted in macrophages treated with Hypo-EVs or normoxia-derived EVs, followed by Gene Set Enrichment Analysis, Gene Ontology, and Kyoto Encyclopaedia of Genes and Genomes pathway analyses. Hypo-EVs significantly alleviated local inflammatory responses, improved collagen organization and biomechanical properties of repaired tendons, and promoted macrophage polarization toward a reparative M2 phenotype both in vivo and in vitro. Consistent with these biological effects, transcriptomic profiling revealed extensive remodeling of inflammation-related gene expression programs, including significant suppression of NF-κB, TNF, IL-17, and cytokine-cytokine receptor interaction pathways. Integrative bioinformatic analyses identified an NF-κB-associated immune-regulatory signature that distinguished Hypo-EV-treated macrophages from those receiving normoxic EVs. Mechanistically, Hypo-EVs attenuated NF-κB activation, as evidenced by reduced phosphorylation of p65 and IκBα, whereas TNF-α-mediated NF-κB activation partially diminished their macrophage-repolarizing effects. Collectively, these findings demonstrate that hypoxic preconditioning enhances the immunomodulatory and regenerative functions of tendon stem cell-derived EVs. Transcriptomic analyses identified an NF-κB-associated immune-regulatory signature linked to the biological activity of Hypo-EVs, providing a molecular framework for understanding EV-mediated immune modulation and supporting the development of transcriptome-guided molecular signatures for regenerative therapies targeting tendon immune homeostasis.

Animals↗

PubMed2026

Integrated single-cell and spatial transcriptomic analyses reveal malignant epithelial glycolytic heterogeneity and spatial niche remodeling during colorectal cancer progression.

Colorectal cancer (CRC) progression is shaped by metabolic reprogramming and complex interactions within the tumor microenvironment. However, the cellular heterogeneity, spatial organization, and clinical relevance of glycolytic activity in CRC remain incompletely understood. In this study, we integrated single-cell RNA sequencing, bulk transcriptomics, and spatial transcriptomics data to systematically characterize glycolytic heterogeneity in CRC. Glycolytic activity was quantified using five independent scoring methods, consistently showing that epithelial cells exhibited the highest glycolytic activity across the two single-cell cohorts. Stratification of CopyKAT-verified aneuploid malignant epithelial cells into high-glycolysis (HG) and low-glycolysis (LG) subgroups by glycolysis scores revealed that HG cells exhibited higher stemness scores and chromosomal copy number variations. Cell-cell communication analysis revealed that, compared with LG cells, HG cells exhibited increased interaction frequency and strength with immune and stromal populations, indicating enhanced malignant epithelial-microenvironment crosstalk. Spatial transcriptomics analyses further revealed that glycolytic activity varied across normal colorectal tissue, primary CRC, and colorectal liver metastases, accompanied by progressive remodeling of epithelial-associated spatial niches and MIF-mediated intercellular communication. Bulk transcriptomic analysis identified a glycolysis-related prognostic signature with robust predictive performance, which served as an independent prognostic factor for overall survival in CRC cohorts. Collectively, these findings indicate that glycolytic heterogeneity is a key feature of CRC malignant epithelial cells and is closely associated with tumor progression, microenvironmental remodeling, and clinical outcomes.

Humans↗

PubMed2026

Genome-guided stage- and tissue-resolved transcriptome analysis of Serrodes campana identifies sex-biased antennal expression and candidate chemosensory-related genes.

Serrodes campana is an erebid moth of ecological and forestry relevance; its larvae are mainly associated with the soapberry tree, Sapindus mukorossi, whereas adults exhibit fruit-piercing behavior. However, stage- and tissue-resolved transcriptomic resources for this species remain limited. Here, using a chromosome-level reference genome, we performed a genome-guided transcriptome analysis of S. campana based on 12 RNA-seq libraries representing major developmental stages and key adult tissues. Global transcriptomic analyses revealed pronounced transcriptional differentiation across developmental stages and tissue types. Tissue-enriched gene sets and functional enrichment analyses identified distinct molecular signatures associated with developmental, sensory, and pheromone-associated tissues. Comparative analysis of female and male antennae further revealed sex-biased expression of several candidate chemosensory-related genes. Among 153 curated chemosensory-related candidate genes, most odorant receptor genes showed strong antennal enrichment, whereas other major chemosensory gene families displayed broader but still tissue-preferential expression patterns. In addition, an exploratory comparison of female terminal abdominal gland tissue and male terminal abdominal coremata revealed divergent expression profiles and highlighted candidate genes potentially associated with pheromone-related physiology, reproduction, and tissue-specific signaling. Together, this study provides the first genome-guided stage- and tissue-resolved transcriptomic resource for S. campana and offers a useful foundation for future studies of chemosensory detection, sex-biased gene expression, and pheromone-associated biology in this species.

Animals↗

PubMed2026

Beyond ion channel dysfunction: Integration of the transcriptome and proteome from patient-specific re-engineered cardiac cells, and population-level QT genome-wide association study reveals broad cellular dysfunction.

BACKGROUND: Congenital long QT syndrome (LQTS) is a cardiac channelopathy with increased risk of cardiac-triggered syncope/seizures, sudden cardiac arrest, and sudden cardiac death. OBJECTIVE: This study aimed to describe the transcriptomic and proteomic profiles in patient-derived inducible pluripotent stem cell-derived cardiomyocyte (iPSC-CM) models of the 3 canonical genotypes of congenital LQTS: LQT1, LQT2, and LQT3 and integrate these omics-level findings with each other and with population/clinical level QT-genome-wide association study (GWAS) data. METHODS: LQT1, LQT2, LQT3 and respective isogenic control iPSC-CMs were cultured, and RNA and protein samples were collected. RNA sequencing and mass spectrometry-enabled proteomic analysis was performed. PrediXcan analysis was performed using QT GWAS summary statistics and transcriptome expression data. Differential gene and protein expression and ingenuity pathway analysis (IPA) was performed comparing each LQT genotype with its respective isogenic control. RESULTS: 1645 differentially expressed genes (DEGs) were identified; 13 were altered in all 3 LQTS genotypes. IPA analysis of DEGs revealed 301 altered pathways; 47 were altered in all LQTS genotypes. Proteomic analysis identified 2561 differentially expressed proteins (DEPs); 30 were altered in all 3 genotypes. IPA analysis of DEPs identified 646 altered pathways. 306 genes/proteins were identified as significantly altered in both the transcriptome and proteome; pathway analysis of these 301 genes identified 201 altered pathways. 7 pathways were altered in all 3 LQTS genotypes in both the transcriptome and proteome. Integration of the population-level PrediXcan results and the cardiomyocyte-derived omics results identified multiple shared pathways. CONCLUSION: Multi-omics analysis of LQTS and integration of omics results with QT GWAS data reveals that primary LQTS-causative ion channel defects precipitate secondary alterations in a wide range of cellular pathways. Our findings suggest more broad molecular level changes throughout the cell. This study lays the foundation for further exploration of broad cellular changes resulting from ion channel disturbances and how they contribute to disease mechanism.

Humans↗

PubMed2026

Dynamic Alterations in the Blood Transcriptome Characterize Drug Use Behavior and Co-Morbidities in Cocaine Use Disorder: A Preliminary Study.

Individuals with cocaine use disorder (CUD) who attempt abstinence experience craving and relapse that can benefit from multimodal treatment monitoring. Longitudinal studies linking behavioral manifestations in CUD to the blood transcriptome are not only limited but also computationally complex. Therefore, we developed an analytical pipeline to investigate the connection between drug use behaviors during abstinence and change in the blood transcriptome. We conducted a longitudinal study with CUD (n = 12 subjects) and collected behavioral metrics and blood RNA-seq at baseline, 3, 6, and 9 months. Our analytical pipeline of the high-dimensional data encompasses hierarchical k-means clustering to classify subjects to responder groups based on behavioral scores and abstinence duration, in silico cell deconvolution, differential analysis with correlated multivariate testing over time, gene set enrichment analysis, and gene co-expression with time splines and RNA-seq data. The pipeline captured dynamic changes in behavioral scores and abstinence duration in responder groups. Genes showing differential transcript-level expression were enriched in substance use and cardiovascular disease-associated genetic risk loci in responder groups. Lastly, time-dependent gene co-expression revealed dynamic changes related to immune processes, cell cycle, RNA-protein synthesis, and second messenger signaling for days of abstinence. This is a preliminary investigation, providing an innovative and scalable pipeline for blood-based longitudinal RNA-seq studies in CUD, potentially applicable to other substance use disorders. It outlines a data-driven approach for analyzing composite longitudinal drug use behavioral phenotypes with blood-based transcriptomics. We also demonstrate changes in drug use behaviors and the blood transcriptome during drug abstinence.

Humans↗

PubMed2025

Growth-limiting drought increases sensitivity of Asian rice (Oryza sativa) leaves to heat shock through physiological and spatially distinct transcriptomic responses.

Growth-limiting droughts (GLD) impair tissue expansion and delay developmental transitions but are often not considered as stressors, as many physiological traits are only slightly altered relative to well-watered counterparts. Concurrently, cell size, biochemical makeup, and transcriptome profiles vary along the leaf blade in accordance with the partitioning of distinct functions to spatially defined regions of the leaf. This suggests that because different parts of the leaf have underlying differences in their transcriptome profiles, they might respond to GLD in distinctive ways. Moreover, how antagonistic stressors influence physiology and gene expression in different zones of leaves is an open question. In this study, we profiled growth, anatomy, and gas exchange in Asian rice (Oryza sativa) leaves developed in well-watered and GLD conditions, with or without a secondary heat shock. We dissected leaves into seven equal-length segments for transcriptome analysis in these conditions. We hypothesized that GLD would make the leaves more sensitive to heat shock and would disrupt the underlying heterogeneity of the leaf transcriptome. GLD plants were more strongly affected by heat shock with respect to gas exchange and the number and types of genes that were differentially expressed and that these differences varied along the leaf blade. We developed an eFP browser tool with these data to facilitate exploration and hypothesis testing. These findings show that even mild drought treatments are sufficient to impact responses to antagonistic stressors and that substantial within-organ variance exists with respect to stress responses.

Oryza↗

PubMed2026

Transcriptomic profiling across stages of non-muscle-invasive bladder cancer identifies fibroblast activation protein-alpha as a stromal biomarker associated with progression.

BACKGROUND: T1 non-muscle-invasive bladder cancer (NMIBC) represents a biologically aggressive subgroup with substantial heterogeneity in recurrence and progression risk. Current clinicopathological risk stratification tools lack sufficient precision to identify patients at the highest risk of progression to muscle-invasive bladder cancer (MIBC). OBJECTIVE: To characterize transcriptomic differences between T1 and < T1 (Ta/Tis) NMIBC and to explore the association of fibroblast activation protein-α (FAP) gene expression with disease progression. METHODS: Transcriptomic profiling was performed on formalin-fixed paraffin-embedded (FFPE) tumor tissue from 66 patients with primary, treatment-naïve NMIBC and 5 patients with T2 disease (included for exploratory comparisons). Analyses included differential gene expression, gene set enrichment analysis (GSEA), molecular subtyping, immune cell deconvolution, and evaluation of FAP expression in relation to recurrence and progression. External validation of FAP was conducted in three independent NMIBC cohorts. RESULTS: T1 tumors demonstrated a distinct transcriptomic profile compared with < T1 tumors, characterized by enrichment of cell cycle-related and metabolic pathways and a higher prevalence of aggressive molecular subtypes. Despite these molecular differences, no statistically significant differences in recurrence-free, progression-free, cancer-specific, and overall survival were observed, likely reflecting limited event numbers. Among recurrent tumors, early recurrences (≤ 24 months) were associated with epithelial-mesenchymal transition signatures. FAP expression increased with tumor stage (p = 0.0005) and was associated with progression (p = 0.002) and mortality (p = 0.01). Patients with tumors in the highest quartile of FAP expression had worse progression-free survival. This association was consistently observed in three external NMIBC cohorts. CONCLUSIONS: T1 NMIBC exhibits distinct transcriptomic features suggestive of increased biological aggressiveness. Elevated FAP expression is reproducibly associated with progression risk across multiple cohorts, supporting its potential role as a biomarker of aggressive disease. Given the limited number of progression events, these findings should be considered hypothesis-generating and warrant prospective validation before clinical implementation.

Humans↗

PubMed2024

Transcriptomic analysis reveals key molecular signatures across recovery phases of hemorrhagic fever with renal syndrome.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS), a life-threatening zoonosis caused by hantavirus, poses significant mortality risks and lacks specific treatments. This study aimed to delineate the transcriptomic alterations during the recovery phases of HFRS. METHODS: RNA sequencing was employed to analyze the transcriptomic alterations in peripheral blood mononuclear cells from HFRS patients across the oliguric phase (OP), diuretic phase (DP), and convalescent phase (CP). Twelve differentially expressed genes (DEGs) were validated using quantitative real-time PCR in larger sample sets. RESULTS: Our analysis revealed pronounced transcriptomic differences between DP and OP, with 38 DEGs showing consistent expression changes across all three phases. Notably, immune checkpoint genes like CD83 and NR4A1 demonstrated a monotonic increase, in contrast to a monotonic decrease observed in antiviral and immunomodulatory genes, including IFI27 and RNASE2. Furthermore, this research elucidates a sustained attenuation of immune responses across three phases, alongside an upregulation of pathways related to tissue repair and regeneration. CONCLUSION: Our research reveals the transcriptomic shifts during the recovery phases of HFRS, illuminating key genes and pathways that may serve as biomarkers for disease progression and recovery.

Hemorrhagic Fever with Renal Syndrome↗

PubMed2025

Distinct spatial transcriptomic patterns of substantia Nigra in Parkinson disease and Parkinsonian subtype of multiple system atrophy.

To investigate transcriptomic signatures of Parkinson's disease (PD) and the Parkinsonian subtype of Multiple System Atrophy (MSA-P) in substantia nigra pars compacta (SNpc), we conducted transcriptome analysis using in-situ hybridization on paraffin-embedded SNpc tissues from post-mortem brains. The study included 2 MSA-P patients, 2 PD patients, and 2 healthy controls (HC), with 12 regions of interest (ROIs) selected from the dorsal to ventral and medial to lateral aspects of the SNpc. A total of 72 ROIs from 6 participants were analyzed, and differentially expressed genes (DEGs) were identified by comparing MSA-P, PD and HC groups. The MSA-P group showed 88 upregulated DEGs and 326 downregulated DEGs (adjusted 𝑝<0.05) compared to HC. The downregulated DEGs were significantly enriched in pathways related to ribosomal translation, immune processes, mitochondrial function, and autophagy. Notably, the dorsomedial quadrant was uniquely linked to antigen presentation, while other quadrants showed downregulation of protein synthesis. The PD group exhibited 165 upregulated DEGs and 350 downregulated DEGs (adjusted 𝑝<0.05) compared to HC, with downregulated DEGs associated with ribosomal translation, mitochondrial function, and the ubiquitin-proteasome system. In both MSA-P and PD, the upregulated DEGs were not associated with any pathways or biological process in gene enrichment analysis. In network propagation analysis, amyloid precursor protein was the most significant network hub among DEGs in both MSA-P and PD. Comparing the transcriptomic signatures of SNpc between MSA-P and PD, we found immune/inflammation, mitochondrial function and neural signaling related genes were significantly downregulated in MSA-P compared to PD. Overall, the transcriptomic signature of the SNpc in MSA-P and PD revealed overlapping but distinct features, including alterations in protein synthesis, immune processes, mitochondrial function, and protein degradation systems. Future studies with larger cohorts and functional validation are needed to further elucidate these findings.

Humans↗

PubMed2026

Whole-transcriptome-scale isoform-resolved spatial imaging of single cells in tissues.

Cell and tissue functions arise from complex interactions among numerous genes, and a systematic understanding of these functions requires isoform-resolved transcriptomic analysis of single cells with high spatial resolution. Here, we introduce an in situ RNA amplification method and its integration with multiplexed error-robust fluorescence in situ hybridization (MERFISH) to detect short RNA sequences and enable whole-transcriptome-scale, isoform-resolved spatial transcriptomics of individual cells in intact tissues. Using this approach, we imaged ∼33,000 distinct RNAs-including ∼23,000 genes and ∼10,000 isoforms-in the mouse brain. Our data enabled systematic analyses of region- and cell-type-specific gene programs and ligand-receptor-based cell-cell communications. These data further revealed rich spatial diversity and cell-type specificity in isoform usage across numerous genes, as well as brain structures particularly rich in isoform specificity. We anticipate broad application of this method for characterizing the molecular and cellular basis of tissue functions, unlocking previously inaccessible discoveries in cell and organismal biology.

Animals↗

PubMed2026

Integrative genomic and transcriptomic analyses identify key regulators of skin pigmentation in Larimichthys crocea.

The yellow body coloration of large yellow croaker (Larimichthys crocea) constitutes a crucial economic trait, yet its underlying genetic regulatory mechanisms remain poorly understood. This study systematically elucidated the molecular basis of body color variation by integrating genome resequencing and skin transcriptome analyses, combined with the contextual analysis of key pigmentation-related genes and phenotypic histological validation. 200 phenotyped individuals (including yellow-selected lines, F1 progeny, and normal control groups, all derived from a well-characterized aquaculture stock) identified 39 significantly associated SNPs (-log₁₀(P) ≥ 6), mapping to multiple candidate genes. These genes were significantly enriched in pathways related to pigment deposition (GO:0033059), melanosome organization (GO:0032438), melanogenesis, and tyrosine metabolism. Cross-developmental stage transcriptome analysis revealed 2395 differentially expressed genes (DEGs). Multi-omics integration identified eight overlapping candidate genes, including tyrp1, slc45a2, oca2, and dgat2, among which tyrp1 was prioritized for in-depth validation based on its core regulatory role in eumelanin synthesis, significant SNP association signal, and consistent downregulation in transcriptomic data. Experimental validation demonstrated that the g.895C > T mutation in exon 2 of tyrp1b was strongly significantly associated with the yellow phenotype: the frequency of mutant genotypes (TT/CT) reached 92.86%in the yellow-selected group, whereas the control group exclusively exhibited the wild-type genotype (CC). qPCR confirmed significantly downregulated tyrp1b expression in the skin of yellow individuals, consistent with the transcriptome trend. Histological and stereomicroscopic observations of skin tissues further validated the physiological basis of the yellow phenotype, revealing a significant reduction in melanophore number and abnormal melanosome morphology in yellow-phenotype individuals, accompanied by increased xanthophore density. These results suggest that tyrp1b mutation is strongly associated with the yellow phenotype. However, the presence of a wild-type CC individual in the yellow group indicates that this mutation is not strictly required for yellow coloration, suggesting that other genetic or environmental factors may also contribute to the phenotype, Additionally, downregulation of the carotenoid metabolism gene bco2 coupled with upregulation of xdh, together with the functional changes of slc45a2 and oca2, may synergistically promote xanthophore pigment deposition, contributing to the yellow phenotype. As melanin synthesis in large yellow croaker relies on the conserved tyrosinase pathway and transporter proteins, mutations in associated genes (tyrp1b, slc45a2, oca2) represent a primary underlying cause for the loss of melanin-based coloration and transition to a yellow phenotype in L. crocea. These findings provide key molecular targets and a theoretical foundation for molecular breeding of body color in this species, and also enrich the understanding of xanthism regulatory mechanisms in teleosts.

Animals↗

PubMed2026

Transcriptomic responses to developmental temperature in two field-collected Spodoptera exigua populations from Korea.

The beet armyworm, Spodoptera exigua, is a polyphagous insect whose development and seasonal occurrence are strongly influenced by temperature. However, transcriptomic responses to developmental thermal regimes remain insufficiently characterized in field-collected populations. In this study, we compared two Korean field-collected populations of S. exigua: a Haenam population collected in May and initially maintained at 15 ± 1 °C (HN), and a Jeju population collected in July and initially maintained at 27 ± 1 °C (JJ). F1 larvae from each population were reared under three fluctuating developmental temperature regimes: low (15-21 °C), middle (21-27 °C), and high (27-33 °C), followed by RNA-seq analysis. Differential expression analysis revealed population-associated variation in transcriptomic responses across developmental temperatures. HN exhibited a larger number of differentially expressed genes under the high-temperature regime, suggesting stronger transcriptomic sensitivity to elevated developmental temperature. Functional enrichment analyses identified population-associated differences in pathways related to heat response, oxidative metabolism, cytoskeletal organization, cuticle-associated processes, lipid metabolism, and immune-related functions. In JJ, heat-response and cuticle-related expression patterns were more prominent under warmer developmental conditions, whereas HN showed broader changes in stress- and metabolism-associated pathways under high temperature. Overall, this study provides a comparative transcriptomic analysis of two field-collected S. exigua populations under different developmental temperature regimes and identifies RNA-seq-based molecular response patterns associated with population-specific thermal response profiles.

Animals↗

PubMed2025

Cell fate specification modes shape transcriptome evolution in the highly conserved spiral cleavage.

Early animal development can be remarkably variable, influenced by lineage-specific reproductive strategies and adaptations. Yet, early embryogenesis is also strikingly conserved in certain groups, such as Spiralia. In this clade, a shared cleavage program (i.e., spiral cleavage) and similar cell lineages are ancestral to at least seven phyla. Why early development is so conserved in specific groups and plastic in others is not fully understood. Here, we investigated two annelid species (Owenia fusiformis and Capitella teleta) with spiral cleavage but different modes of specifying their primary progenitor cells. By generating high-resolution transcriptomic time courses from the oocyte to gastrulation, we demonstrate that transcriptional dynamics differ markedly between these species during spiral cleavage and instead reflect their distinct timings of embryonic organiser specification. However, the end of cleavage and gastrulation exhibit high transcriptomic similarity, when orthologous transcription factors share gene expression domains, suggesting this period is a previously overlooked mid-developmental transition in annelid embryogenesis. Together, our data reveal hidden transcriptomic plasticity during spiral cleavage, indicating an evolutionary decoupling of morphological and transcriptomic conservation during early embryogenesis.

Animals↗

PubMed2025

HUMESS: integrating quantitative transcriptomic analysis and metabolic modeling to unveil condition-specific gene signatures.

SUMMARY: Transcriptomic analysis is a key tool for exploring gene expression, but the complexity of biological systems often limits its insights. In particular, the lack of intermodal or multi-layered analysis hinders the ability to fully capture key cellular functions such as metabolism from transcriptomic data alone. Here, we introduce a novel approach that informs transcriptomic data analysis with metabolic network modeling to address this. Unlike traditional methods, HUman MEtabolism Specific Signature (HUMESS) uses genome-scale metabolic modeling and flux analysis to highlight reactions and involved genes based on their metabolic significance, offering a deeper understanding of transcriptomic data. Our computational pipeline, supported by a user-friendly Rshiny application, enhances gene expression analysis by uncovering metabolic phenotypic signatures. AVAILABILITY AND IMPLEMENTATION: HUMESS is open source and available under GitLab https://gitlab.univ-nantes.fr/bird_pipeline_registry/humess with the complete documentation available at https://gitlab.univ-nantes.fr/bird_pipeline_registry/humess/-/wikis/Home. A zenodo archive is also available at the following DOI: https://doi.org/10.5281/zenodo.15487717. An RShiny application has been developed to facilitate the exploration and analysis of HUMESS's results. The app is available online at the following address: https://shiny-bird.univ-nantes.fr/app/shinymess but can also be installed locally, available under GitLab https://gitlab.univ-nantes.fr/pare-l/shinymess.

Humans↗

PubMed2026

Tissue-Level Transcriptomic Entropy Reveals Organ-Specific Aging Patterns and Predicts Cancer Progression.

Although aging and cancer share complex molecular mechanisms, distinguishing causative factors from byproducts remains challenging. Here, we investigated the role of tissue transcriptomic entropy-a measure of transcriptional disorder-in aging and cancer processes by analyzing RNA-sequencing data from over 25,000 samples from human and mouse tissues. We found that entropy changes during aging are highly tissue-specific, with some tissues showing increased entropy while others exhibit decreased or stable entropy levels. Moreover, transcriptomic entropy strongly correlates with age-related processes, showing positive associations with proliferation, cellular senescence, somatic mutation burden, and cellular reprogramming, whereas it negatively correlates with stemness. In cancer, we observed that primary tumors generally display higher entropy than normal tissue, with its levels further increasing in metastatic stages. Cancer treatment modulated entropy patterns in multiple contexts, with changes suggesting a role for transcriptional complexity in tumor plasticity and therapy resistance. Elevated entropy levels predicted poor survival outcomes in multiple cancer types, suggesting its potential as a prognostic marker. Furthermore, differential expression analysis revealed that entropy-associated genes are enriched in developmental processes and depleted in metabolic pathways, indicating a possible link to cellular dedifferentiation. Finally, we found increased entropy in various age-related disorders beyond cancer, suggesting that transcriptomic entropy may be a common feature in age-related diseases. Our findings establish transcriptomic entropy as a fundamental parameter in aging and cancer progression, offering new insights into disease mechanisms.

Humans↗

PubMed2025

De novo transcriptome assembly and gene expression analysis of Cnidium officinale under high-temperature conditions.

BACKGROUND: The medicinal plant Cnidium officinale (CO) is widespread in Northeast Asia and vulnerable to heat stress. The naturally occurring composition of pharmacological ingredients of CO results in overall physiological consequences; therefore, it is crucial to have a comprehensive understanding of metabolic response to ambient heat in terms of acclimation to estimate how much CO is exposed to threatening environmental conditions. RESULTS: Transcriptome analysis is critical for understanding the consequences of long-term physiological adaptation of CO to abiotic stress. However, transcriptome analysis on this species, particularly under prolonged stress conditions, has remained limited. We employed a temperature gradient tunnel (TGT) to subject CO to high-temperature exposure for four months, enabling us to observe the cumulative effects of heat and assess its acclimation mechanisms. In the absence of genome sequencing data, we performed de novo transcriptome assembly and compared DEGs from temperature treatment plots of a TGT and a growth chamber (GC). Since interpreting transcriptomic data can be complex, we employed a sequential analytical approach, including DEG clustering, GO enrichment, KEGG pathway mapping, miRNA-target gene analysis, and multiple rounds of RNA sequencing validation. DEGs were classified into two categories: genes exhibiting significant fold changes and genes showing significant count changes rather than fold changes. Then, we analyzed the functional roles of DEGs to determine which pathways respond to ambient and stressful high temperatures and validated the findings through cross-comparison with GC. Additionally, we conducted miRNA analysis to investigate post-transcriptional regulation under high temperatures. CO grown under higher ambient temperatures exhibited slight upregulation of pathways related to protein stability and turnover, ABA biosynthesis, and energy production, such as photosynthesis and oxidative phosphorylation. However, under extreme heat stress, most metabolic pathways were downregulated except for those involved in transcription, translation, oxidative phosphorylation and the biosynthesis of cutin, suberin, and wax. CONCLUSION: This study demonstrated that proper clustering of genes based on expression levels and fold changes in two different experimental conditions, along with pathway mapping, may provide a comprehensive understanding of CO's response to heat stress. These insights could contribute to future research on heat tolerance and crop improvement.

Gene Expression Profiling↗

PubMed2025

RNAcare: integrating clinical data with transcriptomic evidence using rheumatoid arthritis as a case study.

BACKGROUND: Gene expression analysis is a crucial tool for uncovering the biological mechanisms that underlie differences between patient subgroups, offering insights that can inform clinical decisions. However, despite its potential, gene expression analysis remains challenging for clinicians due to the specialised skills required to access, integrate, and analyse large datasets. Existing tools primarily focus on RNA-Seq data analysis, providing user-friendly interfaces but often falling short in several critical areas: they typically do not integrate clinical data, lack support for patient-specific analyses, and offer limited flexibility in exploring relationships between gene expression and clinical outcomes in disease cohorts. Users, including clinicians with a general knowledge of transcriptomics, however, who may have limited programming experience, are increasingly seeking tools that go beyond traditional analysis. To overcome these issues, computational tools must incorporate advanced techniques, such as machine learning, to better understand how gene expression correlates with patient symptoms of interest. RESULTS: Our RNAcare platform, addresses these limitations by offering an interactive and reproducible solution specifically designed for analysing transcriptomic data from patient samples in a clinical context. This enables researchers to directly integrate gene expression data with clinical features, perform exploratory data analysis, and identify patterns among patients with similar diseases. By enabling users to integrate transcriptomic and clinical data, and customise the target label, the platform facilitates the analysis of the relationships between gene expression and clinical symptoms like pain and fatigue. This allows users to generate hypotheses and illustrative visualisations/reports to support their research. As proof of concept, we use RNAcare to link inflammation-related genes to pain and fatigue in rheumatoid arthritis (RA) and detect signatures in the drug response group, confirming previous findings. CONCLUSION: We present a novel computational platform allowing the interpretation of clinical and transcriptomics data in real-time. The platform can be used for data generated by the user, such as the patient data presented here or using published datasets. The platform is available at https://rna-care.mvls.gla.ac.uk/ , and its source code is https://github.com/sii-scRNA-Seq/RNAcare/ .

Humans↗