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PubMed2004

Analysis of differentially expressed parasite genes and proteins using transcriptomics and proteomics.

At any particular point in time, the full complement of transcribed RNAs and relevant proteins of a cell are known as the transcriptome and proteome, respectively. The composition of these two populations changes throughout the life cycle of a parasite or in response to environmental factors, such as drug treatments. Comparing the changes in the composition of the transcriptome and proteome between different life-cycle stages or in the same stage but under different conditions can be of particular interest, as it can allow the identification of potentially important differentially expressed genes and proteins. Combining the analysis of both the transcriptome and proteome in tandem allows changes in RNA transcripts to be followed right through to changes in the level of protein expression. The protocols in this chapter describe methods for analyzing the transcriptome, by using suppression subtraction hybridization to construct subtracted complementary DNA libraries, and the proteome, by using two-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis. These two methods are then integrated to allow the global changes in RNA and protein expression to be examined. The protocols have been adapted for working on parasites and contain extensive notes.

Animals↗
PubMed2026

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

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

TLR4↗
PubMed2026

Integrated dual transcriptome sequencing and experimental validation reveal potential mechanisms of baicalin against pneumocystis pneumonia in immunosuppressed rats.

BACKGROUND: Pneumocystis pneumonia (PCP) remains a major cause of morbidity and mortality in immunocompromised individuals. Although baicalin (Ba), a natural bioactive flavonoid, has demonstrated protective and therapeutic effects against PCP, its molecular mechanisms remain undefined. We employed dual RNA sequencing (dual RNA-seq) to characterize host and pathogen transcriptional responses to Ba treatment in an immunosuppressed rat model of PCP. METHODS: Comparative transcriptomic analyses identified differentially expressed genes in both the host and Pneumocystis, followed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses. Candidate targets were further investigated using network pharmacology, protein-protein interaction analysis, molecular docking, and molecular dynamics simulations. Key findings were validated by immunohistochemistry, enzyme-linked immunosorbent assay, and quantitative PCR. RESULTS: Ba markedly remodeled host and pathogen transcriptomes. Host transcriptomic analyses showed that Ba attenuated inflammatory and oxidative stress responses by modulating immune-related pathways, including Toll-like receptor, NF-κB, cytokine-cytokine receptor interaction, chemokine signaling, Th17 cell differentiation, and antigen processing and presentation. Experimental validation demonstrated that Ba reduced pulmonary expression of indoleamine 2,3-dioxygenase 1 (IDO1), Toll-like receptor 2 (TLR2), and TLR4 while increasing nuclear factor erythroid 2-related factor 2 (Nrf2) and its downstream antioxidant enzyme heme oxygenase-1 (HO-1). Pathogen transcriptomic analysis identified Pneumocystis Rtt109 (PcRtt109), a fungal histone acetyltransferase, as a potential pathogen-specific target that was significantly downregulated after Ba treatment. Molecular docking and molecular dynamics simulations supported stable interactions between Ba and IDO1, Nrf2, TLR2, TLR4, and PcRtt109, with the strongest predicted binding observed for PcRtt109. CONCLUSION: Dual RNA-seq revealed that Ba exerts anti-PCP activity through coordinated modulation of host and pathogen molecular networks. Its therapeutic effects are associated with suppression of inflammatory signaling, enhancement of antioxidant defenses, and inhibition of a fungal virulence-associated target. These findings provide mechanistic insights into host-pathogen interactions during PCP and support Ba as a potential therapeutic candidate for PCP.

Nrf2↗
PubMed2003

Transcriptome fingerprints distinguish hallucinogenic and nonhallucinogenic 5-hydroxytryptamine 2A receptor agonist effects in mouse somatosensory cortex.

Most neuropharmacological agents and many drugs of abuse modulate the activity of heptahelical G-protein-coupled receptors. Although the effects of these ligands result from changes in cellular signaling, their neurobehavioral activity may not correlate with results of in vitro signal transduction assays. 5-Hydroxytryptamine 2A receptor (5-HT2AR) partial agonists that have similar pharmacological profiles differ in the behavioral responses they elicit. In vitro studies suggest that different agonists acting at the same receptor may establish distinct patterns of signal transduction. Testing this hypothesis in the brain requires a global signal transduction assay that is applicable in vivo. To distinguish the cellular effects of the different 5-HT2AR agonists, we developed an assay for global signal transduction on the basis of high throughput quantification of rapidly modulated transcripts. Study of the responses to agonists in human embryonic kidney 293 cells stably expressing 5-HT2ARs demonstrated that each agonist elicits a distinct transcriptome fingerprint. We therefore studied behavioral and cortical signal transduction responses in wild-type and 5-HT2AR null-mutant mice. The hallucinogenic chemicals (+/-)-2,5-dimethoxy-4-iodoamphetamine (DOI) and lysergic acid diethylamide (LSD) stimulated a head-twitch behavioral response that was not observed with the nonhallucinogenic lisuride hydrogen maleate (LHM) and was absent in receptor null-mutant mice. We also found that DOI, LSD, and LHM each induced distinct transcriptome fingerprints in somatosensory cortex that were absent in 5-HT2AR null-mutants. Moreover, DOI and LSD showed similarities in the transcriptome fingerprints obtained that were not observed with the behaviorally inactive drug LHM. Our results demonstrate that chemicals acting at the 5-HT2AR induce specific cellular response patterns in vivo that are reflected in unique changes in the somatosensory cortex transcriptome.

Animals↗
PubMed2006

Analysis of SAGE data in human platelets: features of the transcriptome in an anucleate cell.

A comprehensive SAGE (serial analysis of gene expression) library of purified human platelets was established. Twenty-five thousand (25,000) tags were sequenced, and after removal of mitochondrial tags, 12,609 (51%) non-mitochondrial-derived tags remained, corresponding to 2,300 different transcripts with expression levels of up to 30,000 tags per million. This new, highly purified SAGE library of platelets is enriched in specific transcripts. The complexity in terms of tag distribution is similar to cells that are still able to replenish their mRNA pool by transcription. We show that our SAGE data are consistent with recently published microarray data but show further details of the platelet transcriptome, including (i) longer UTR regions and more stable folding in the enriched mRNAs, (ii) biologically interesting new candidate mRNAs that show regulatory elements, including elements for RNA stabilization or for translational control, and (iii) significant enrichment of specific, highly transcribed mRNAs compared to a battery of SAGE libraries from other tissues. Among several regulatory mRNA elements known to be involved in mRNA localization and translational control, CPE elements are in particular enriched in the platelet transcriptome. mRNAs previously reported to be translationally regulated were found to be present in the library and were validated by real-time PCR. Furthermore, specific molecular functions such as signal transduction activity were found to be significantly enriched in the platelet transcriptome. These findings emphasize the richness and diversity of the platelet transcriptome.

3' Untranslated Regions↗
PubMed2026

De novo transcriptome meta-analysis reveals candidate genes involved in life-stage transitions for RNAi-mediated management of the citrus root weevil (Diaprepes abbreviatus).

BACKGROUND: The citrus root weevil, Diaprepes abbreviatus, is a destructive agricultural pest for which molecular control options remain limited due to historically sparse genomic resources. Leveraging a comprehensive de novo transcriptome, we investigated developmental gene regulation across larval, pupal, and adult stages and identified essential targets for RNA interference (RNAi)-based intervention. RESULTS: Stage-resolved transcriptomic analyses revealed extensive transcriptional reprogramming associated with metabolism, detoxification, cuticle biosynthesis, endocrine signaling, and sensory perception. Among these, chitin synthase (DaCHS) emerged as a critical developmental gene, exhibiting pronounced up-regulation during late larval and pupal stages corresponding to intensive cuticle synthesis. Phylogenetic and structural analyses demonstrated that DaCHS is highly conserved among insects and retains canonical catalytic domains and transmembrane topology. Alpha Fold-based structural modeling and molecular docking confirmed stable interaction of DaCHS with its substrate, N-acetylglucosamine, supporting functional conservation of enzymatic activity. Oral delivery of DaCHS double-stranded RNA induced robust transcript suppression, leading to significant mortality and severe developmental defects, including larval and pupal abnormalities, and adults with disrupted wing and abdominal morphogenesis. CONCLUSION: These findings establish DaCHS as an indispensable gene for D. abbreviates development and validate transcriptome-guided RNAi as a powerful framework for target discovery. This work provides a strong molecular foundation for developing RNAi-based strategies that can be integrated into sustainable management programs for citrus root weevil control. © 2026 Society of Chemical Industry.

Animals↗
PubMed2025

Comprehensive transcriptomic analysis of myostatin-knockout pigs: insights into muscle growth and lipid metabolism.

Pigs are a vital source of protein worldwide, contributing approximately 43% of global meat production. Recent genetic advancements in the myostatin (MSTN) gene have facilitated the development of double-muscling traits in livestock. In this study, we investigate the transcriptomic profiles of second-generation MSTN-knockout (MSTN-/-) pigs, generated through CRISPR/Cas9 gene editing and somatic cell nuclear transfer (SCNT). Using RNA sequencing, we compared the transcriptomic landscapes of muscle tissues from MSTN-/- pigs and wild-type (WT) counterparts. The sequencing yielded an average unique read mapping rate of 86.7% to the Sus scrofa reference genome. Our analysis revealed 15,142 differentially expressed genes (DEGs), including 121 novel genes, with 2554 genes upregulated and 1629 downregulated in the MSTN-/- group relative to the wild-type group. Notable transcriptomic changes were identified in genes associated with muscle development, lipid metabolism, and other physiological processes. These findings provide valuable insights into the molecular consequences of MSTN inactivation, with potential applications in the optimization of livestock breeding and advancements in biomedical research.

Animals↗
PubMed2026

Advancing insect research through cell line transcriptomics.

This review emphasizes the significance of insect cell lines in transcriptomic research, highlighting their role as vital tools for uncovering cellular and molecular mechanisms of insect physiology, immune responses, and adaptation to environmental stressors. Cell lines derived from tissues such as the midgut, fat body, nervous system, and reproductive organs enable researchers to examine gene expression changes in a controlled setting, making discoveries that are difficult to achieve through whole-organism studies. High-throughput sequencing and single-cell RNA sequencing (scRNA-seq) have identified genes linked to detoxification, stress response, development, and immune defense, offering valuable insights for future applications in agriculture, pest control, and biotechnology. To organize this information clearly, we have summarized key findings in a table, providing an accessible overview of each cell line's important roles in transcriptomic research. This method not only highlights the adaptability of insect cell lines in functional genomics but also underscores their usefulness as model systems in pest management, virology, and bioengineering. Through utilizing transcriptomics, insect cell lines continue to advance our understanding of insect biology and foster the development of innovative strategies for sustainable crop protection and biotechnological use.

Animals↗
PubMed2026

Integrative Genomic and Transcriptomic Insights into High-Altitude Adaptation in Changthangi Goats.

The Changthangi goat, native to the high-altitude Ladakh Plateau in northern India, thrives in oxygen-deficient environments above 4,000 m. This study investigated the genetic basis of high-altitude adaptation in Changthangi goats by integrating comparative genomics and transcriptomics, using the tropical lowland Jamunapari goat as a comparative model. Whole-genome sequence data from 15 individuals per breed were analyzed using complementary selection sweep metrics, including nucleotide diversity, Tajima's D, iHS, CLR, XP-EHH, and FST. These analyses identified candidate genomic regions under strong selective pressure, encompassing genes involved in hypoxia sensing (HIF-1α, HIF-2α/EPAS1, EGLN1), angiogenesis (VEGFA, AGGF1, ZEB1), cardiovascular regulation (PRKCB, ESR1, RYR2), mitochondrial and energy metabolism (ACADSB, ACSS3, ACSL1), cellular stress tolerance (BCL2, ATM), and thermogenesis (UCP1, FGF21). Unlike previous caprine studies that primarily infer hypoxia adaptation from genomic signals alone, our study integrates cardiac transcriptomics to demonstrate that genomic selection in Changthangi goats is accompanied by coordinated transcriptional remodeling across interconnected physiological systems in a physiologically relevant tissue. Comparative cardiac transcriptomic profiling revealed concordant expression divergence in genes associated with oxygen transport, vascular remodeling, mitochondrial function, substrate utilization, redox balance, and genome maintenance. This integrative multi-omics framework provides a mechanistic view of caprine high-altitude adaptation and highlights the value of combining genomic selection analyses with tissue-specific transcriptional profiling to resolve complex adaptive traits.

Animals↗
PubMed2026

Comparative genomics and full-length transcriptome profiling of wing morphs in Tetrix grossus (Orthoptera: Tetrigidae).

Wing polymorphism represents a paradigmatic dispersal-reproduction trade-off, yet its molecular basis remains uncharacterised in the phylogenetically distant pygmy grasshoppers (Tetrigidae). Here we integrate comparative genomics across ten orthopteran species with full-length transcriptomics of long-winged (FL) and short-winged (FS) Tetrix grossus. OrthoFinder recovered 118 orthogroups specific to T. grossus. Against a backdrop of pronounced gene-family contraction (36 expansions versus 222 contractions; net -186, mirrored at the ancestral Tetrix node, +37/-140), we identified an ancestral, Tetrix-specific expansion of hormone-regulation (12 genes; fold enrichment 7.93) and lipid/carbohydrate-metabolic families organised into syntenic clusters, alongside 513 positively selected genes enriched for integrin-mediated cell adhesion (6 genes), a process relevant to epithelial and appendage morphogenesis. Full-length transcriptomics of one long-winged (FL) and one short-winged (FS) adult female detected 7530 (FL) and 7515 (FS) expressed genes, with 794 FL- and 776 FS-restricted transcriptome-derived SNP-associated genes. The FL morph was enriched for an EGFR/Ras-Rho developmental-patterning axis and neuromuscular flight genes, whereas the FS morph was enriched for insulin/peptide-hormone response and growth-regulatory loci. Overall, we present genomic resources and testable hypotheses concerning the evolution and regulation of wing morphs in Tetrigidae rather than a validated genetic architecture of wing-morph determination.

Animals↗
PubMed2026

Uncovering molecular regulatory networks of low-temperature stress response in Trachinotus ovatus via integrated transcriptome and metabolome analyses.

Golden pompano (Trachinotus ovatus) is one of the most economically important marine fish species in China. It is susceptible to low-temperature stress, which significantly challenges its production and supply. Nevertheless, study on the regulatory mechanisms underlying low-temperature stress responses in golden pompano remains limited. Here, we firstly performed a time-series transcriptome analysis to reconstruct dynamic response patterns under low-temperature stress in golden pompano. Transcriptome profiling identified common differentially expressed genes (DEGs), including fos, hlf, and hmgb1, as well as condition-specific DEGs across distinct low-temperature stress groups. Based on cluster analysis, all DEGs were classified into five distinct expression patterns, reflecting diversified regulation of expression in golden pompano during low-temperature stress. Furthermore, condition-specific regulatory modules were explored via weighted gene co-expression network analysis (WGCNA), highlighting that the two module hub genes, serbf2 and lipc, might respond to low-temperature stress by regulating the lipid catabolic process. Subsequently, untargeted metabolomic analysis revealed that glycerophospholipid metabolism was a significantly enriched common pathway, highlighting its crucial role in mediating the response to low-temperature stress. Finally, by integrating transcriptomic and metabolomic analyses, a gene-metabolite interaction network associated with glycerophospholipid metabolism under low-temperature stress was established. These findings underscore the significance of multiple candidate genes and glycerophospholipid metabolism in golden pompano's response to low-temperature stress, thereby laying a solid molecular foundation for the development of low-temperature-tolerant fish strains.

Animals↗
PubMed2025

Inferring cell trajectories of spatial transcriptomics via optimal transport analysis.

The integration of cell transcriptomics and spatial position to organize differentiation trajectories remains a challenge. Here, we introduce SpaTrack, which leverages optimal transport to reconcile both gene expression and spatial position from spatial transcriptomics into the transition costs, thereby reconstructing cell differentiation. SpaTrack can construct detailed spatial trajectories that reflect the differentiation topology and trace cell dynamics across multiple samples over temporal intervals. To capture the dynamic drivers of differentiation, SpaTrack models cell fate as a function of expression profiles influenced by transcription factors over time. By applying SpaTrack, we successfully disentangle spatiotemporal trajectories of axolotl telencephalon regeneration and mouse midbrain development. Diverse malignant lineages expanding within a primary tumor are uncovered. One lineage, characterized by upregulated epithelial mesenchymal transition, implants at the metastatic site and subsequently colonizes to form a secondary tumor. Overall, SpaTrack efficiently advances trajectory inference from spatial transcriptomics, providing valuable insights into differentiation processes.

Animals↗
PubMed2026

A reproducible computational transcriptomic framework for cell-type-resolved fibroinflammatory-AKT remodeling in human heart failure.

BACKGROUND: Human heart failure involves multicellular transcriptional remodeling, but public transcriptomic studies often remain disconnected from cell-type localization and perturbational interpretation. METHODS: We developed a reproducible computational workflow integrating human left-ventricular bulk transcriptomes, donor-level cell-type pseudobulk results from a human heart-failure single-cell/single-nucleus atlas, external snRNA-seq support, curated module scoring, focused ligand-receptor prioritization and LINCS/L1000 perturbational matching. RESULTS: Cross-cohort analysis identified 14,358 same-direction HF-associated genes, including 1633 replicated HF-up and 785 replicated HF-down genes. Donor-level pseudobulk analysis localized disease remodeling to cardiomyocyte, fibroblast and myeloid compartments. Activated fibroblast and inflammatory myeloid programs defined a fibroinflammatory remodeling axis connected to context-dependent AKT-associated transcriptional shifts. External snRNA-seq support was strongest for fibroblast activation and AKT-associated remodeling, with etiology-dependent heterogeneity across validation resources. L1000FWD screening prioritized safety-aware perturbational hypotheses, including glimepiride and simvastatin as interpretable candidates requiring experimental validation. CONCLUSIONS: This study provides a computational transcriptomic framework linking reproducible human HF signatures, cell-type-resolved fibroinflammatory remodeling and perturbational genomic prioritization without claiming drug efficacy or AKT causality.

Humans↗
PubMed2025

Genomic and Transcriptomic Landscape of Epstein-Barr Virus-Positive Inflammatory Follicular Dendritic Cell Sarcoma: A Multicenter Study.

Epstein-Barr virus (EBV)-positive inflammatory follicular dendritic cell sarcoma (EBV+ IFDCS) is a rare indolent malignant neoplasm, which occurs almost exclusively in the liver or spleen and may arise from a common EBV-infected mesenchymal cell that differentiates along the follicular or fibroblastic dendritic cell pathway. Despite its rarity, it presents a pressing need for an improved understanding of its genetic underpinnings and potential treatment strategies for recurrent or disseminated cases. To address this, we conducted comprehensive whole-exome sequencing and transcriptome sequencing (mRNA-seq) analyses on 31 and 6 cases of EBV+ IFDCS, respectively, collected from multiple centers in China. We also compared the genetic features of EBV+ IFDCS with those of other EBV-associated malignancies. Our analyses revealed a relatively high somatic mutation rate and widespread copy number variations affecting the major histocompatibility complex-I/II in EBV+ IFDCS. Integrated mutational profiling identified key signaling pathways involved in epigenetic regulation, NF-κB signaling, RTK/RAS/PI(3)K, and the Hippo pathway. Furthermore, we identified several frequently altered genes that could serve as potential therapeutic targets in EBV+ IFDCS. Transcriptomic analysis unveiled significant upregulation of pathways related to virus infection, immune responses, and multiple immune checkpoint genes in EBV+ IFDCS. Comparative analysis demonstrated clear genetic distinctions between EBV+ IFDCS and other EBV-associated tumors. In conclusion, our study provides comprehensive insights into the unique genomic and transcriptomic landscape of EBV+ IFDCS. We have identified multiple genetic alterations that likely contribute to the development and progression of this malignancy. Our results suggest that targeted therapy and immune checkpoint inhibitors may hold promise as potential therapeutic approaches for patients with recurrent or disseminated EBV+ IFDCS.

Humans↗
PubMed2026

Enhancing pan-cancer spatial transcriptomics at single-cell resolution with stPainter.

Subcellular spatial transcriptomics can resolve tissue architecture at cellular scale, but sparse gene panels and limited detection sensitivity constrain downstream analysis. Existing enhancement methods often require tissue-matched single-cell RNA sequencing (scRNA-seq) references and dataset-specific retraining. Here we show that stPainter, a conditional generative model pretrained on a pan-cancer scRNA-seq atlas, can enhance spatial transcriptomics data without matched references or retraining. Using a latent diffusion architecture guided by Stochastic Differential Equations (SDE), stPainter reconstructs expanded expression profiles from sparse measurements and produces latent representations for clustering and cell-state analysis. When we apply stPainter upon 6 spatial transcriptomics datasets of different cancer types, we demonstrate that our model empowers downstream biological analyses, including fine-grained subpopulation clustering and pathway enrichment. Comparison with spatially resolved proteomics (CODEX) provided independent support for regional agreement between imputed cellular compositions and protein-level tissue organization. These results establish stPainter as a scalable approach for analyzing tumor microenvironments without auxiliary sequencing data.

Spatial Transcriptomics↗
PubMed2026

Epigenetics and In Silico Transcriptome Analysis of Pediatric Acute Myeloid Leukemia.

Pediatric acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy that accounts for about 15%-20% of childhood leukemias. Despite therapeutic advances, relapses remain common, and survival for high-risk patients is below 60%. Unlike adult AML, pediatric AML displays distinct genetic mutations, including FLT3-ITD, NPM1, KMT2A rearrangements, and core-binding factors (CBF) fusions, as well as extensive epigenetic dysregulation. Aberrant DNA methylation, histone modifications, and altered non-coding RNA expressions disrupt hematopoietic differentiation and activate oncogenic transcriptional networks. Recent advances in silico transcriptomic analysis have transformed the study of pediatric AML by integrating gene expression and epigenetic data to identify molecular drivers and regulatory networks. Computational RNA-seq pipelines and pathway analyses have highlighted key epigenetic regulators, including DNMT3A, TET2, and HDACs, as potential therapeutic targets. Multi-omics approaches combining transcriptomic, methylomic, and chromatin accessibility data are increasingly used to define biomarkers for diagnosis, prognosis, and therapeutic response. This review provides a comprehensive overview of the molecular and epigenetic landscape of pediatric AML, emphasizing the power of in silico transcriptome analysis to uncover disease mechanisms, refine patient stratification, and guide the development of precision-based epigenetic therapies aimed at improving long-term outcomes in children with AML.

Humans↗
PubMed2026

Transposable elements as modulators of homoeologous gene expression in bread wheat: lessons from the pan-transcriptome era.

Bread wheat (Triticum aestivum L.) is an allohexaploid (AABBDD) whose three ancestral subgenomes generate complex patterns of gene regulation. Most genes exist as homoeologous triads, and the relative expression balance among copies, homoeolog expression bias, is central to polyploid evolution and adaptation. Recent high-quality assemblies, long-read transcriptomics, and pan-transcriptome resources have uncovered extensive cultivar-specific transcriptional diversity. Because transposable elements (TEs) compose over 80% of the wheat genome, they are prime candidates for shaping subgenome asymmetry. We synthesize recent pan-genomic and transcriptomic evidence, including genome-wide associations between TE insertions and genome-specific expression, and propose a unifying framework in which TEs modulate homoeolog expression by donating cis-regulatory sequences, altering chromatin states, producing small RNAs, and driving structural variation. We discuss experimental and computational challenges for establishing causality, and outline future functional and translational strategies to leverage TE-associated regulatory diversity in wheat breeding.

Triticum↗
PubMed2026

Drug repurposing using transcriptomics: principles and unmet needs in cardiovascular disease.

Although cardiovascular disease is the leading cause of death globally, therapeutic development in this field is slow. Given the high cost of developing new drugs and running clinical trials for cardiovascular disease, repurposing of drugs with approved safety profiles is an attractive strategy for therapeutic development that can significantly reduce the time and cost investment before phase II clinical trials. In the era of "Omics," various new methods and several large databases have been developed to enable the use of transcriptomics data for drug repurposing. This review summarizes the principles and workflow of signature mapping, which forms the foundation of statistical models used for transcriptome-based drug repurposing. We highlight the features of different analysis pipelines and databases that have been developed for signature mapping. These analysis pipelines prioritize genes that are statistically important, an approach that fundamentally differs from the pharmacological approach of identifying disease-driving and therapeutically targetable pathways. Outcomes of signature mapping pipelines are sensitive to the quality of input data, and results are not always reproducible. Moreover, all widely used RNA-seq databases are derived from cancer research and lack high-quality molecular data for cardiovascular disease. These unmet needs call for interdisciplinary collaboration and large networks of cardiovascular research-oriented biobanks to create the databases needed for transcriptomic-based signature mapping for drug repurposing efforts.

Drug Repositioning↗