SEARCH · PubMed Health

Results for “comparative 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 145 records · Page 8Linked to original sources

PubMed2025

EucaMOD: a comprehensive multi-omics database for functional genomics research and molecular breeding of fast-growing eucalyptus trees.

Eucalyptus, one of the most widely planted plantation tree species globally, is primarily found in tropical and subtropical regions and contributes significantly to economic and social benefits. With advances in sequencing technologies, there is an increasing demand for the systematic analysis of multi-omics data among Eucalyptus species to enhance genetic breeding efforts. Although several early genomic databases have been established for eucalyptus, they have not been updated in a timely manner and lack recent multi-omics data, rendering them insufficient for current research needs. To address this gap, we developed the eucalyptus multi-omics database (EucaMOD, http://eucalyptusggd.net/eucamod), a comprehensive resource for cross-omics studies. In this study, we functionally annotated 45 eucalyptus genomes and structurally annotated 15, conducting comparative genomics and pan-proteomics analyses across all genomes. Additionally, we analyzed eucalyptus transcriptome, epigenome, and variome data through standardized workflows, enabling the in-depth mining and reanalysis of multi-omics datasets. EucaMOD is the most comprehensive multi-omics database for eucalyptus to date and includes data from 45 genomes (39 species), 870 mRNA-seq samples, 17 miRNA-seq samples, 52 epigenomic datasets (histone modifications and transcription factor binding), and genetic variation data from 1219 samples. To support functional genomics and molecular breeding research, the database is organized into the following 11 modules: Home, Species, Genomics, Comparative genomics, Pan-proteomics, Transcriptomics, Epigenetics, Variomics, Tools, Download, and Help. EucaMOD also offers online analysis tools for data mining, providing free public services to aid eucalyptus gene function and genetic engineering studies.

Eucalyptus↗

PubMed2025

Prior vaccination prevents overactivation of innate immune responses during COVID-19 breakthrough infection.

At this stage in the COVID-19 pandemic, most infections are "breakthrough" infections that occur in individuals with prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure. To refine long-term vaccine strategies against emerging variants, we examined both innate and adaptive immunity in breakthrough infections. We performed single-cell transcriptomic, proteomic, and functional profiling of primary and breakthrough infections to compare immune responses from unvaccinated and vaccinated individuals during the SARS-CoV-2 Delta wave. Breakthrough infections were characterized by a less activated transcriptomic profile in monocytes and natural killer cells, with induction of pathways limiting monocyte migratory potential and natural killer cell proliferation. Furthermore, we observed a female-specific increase in transcriptomic and proteomic activation of multiple innate immune cell subsets during breakthrough infections. These insights suggest that prior SARS-CoV-2 vaccination prevents overactivation of innate immune responses during breakthrough infections with discernible sex-specific patterns and underscore the potential of harnessing vaccines in mitigating pathologic immune responses resulting from overactivation.

Immunity, Innate↗

PubMed2026

A 3D in vitro co-culture model to investigate tumor-endothelial interactions in Neurofibromatosis type 2-associated meningiomas.

BACKGROUND: Neurofibromatosis type 2 (NF2)-associated meningiomas and schwannomas are vascular tumors, and while vascular endothelial growth factor (VEGF) inhibition with bevacizumab has benefited some NF2-related schwannomas, most NF2-associated meningiomas remain nonresponsive. METHODS: Leveraging our transcriptomic data, we performed Gene Ontology (GO) analysis comparing NF2-deficient meningioma cells with NF2-expressing arachnoid cells (ACs). We then established a 3D in vitro angiogenesis model by co-culturing NF2-null meningioma cells with human umbilical vein endothelial cells (HUVECs). Endothelial sprouting was assessed by CD31/PECAM immunostaining. Effects of third-generation mechanistic target of rapamycin complex 1 (mTORC1)-selective inhibitor RMC-6272 as well as APLN knock-out using CRISPR-Cas9 gene editing were also examined. RESULTS: GO analysis identified vascular development among the top significantly upregulated pathways in NF2-deficient cells. In 3D co-culture, ECs formed radially sprouting tube-like networks from the spheroid surface, and our data supports an angiogenesis phenotype driven by meningioma cells. Given these results along with hyperactivation of mTORC1 upon NF2-deficiency, we examined whether RMC-6272 disrupts meningioma-driven angiogenesis. RMC-6272 potently suppressed EC sprouting. Cross-referencing baseline transcriptomic data, we identified Apelin (APLN), the ligand for APLN receptor (APLNR), as a basally upregulated angiogenic factor in NF2-deficient meningiomas. Quantitative RT-PCR (qRT-PCR) confirmed increased APLN expression in NF2-null immortalized and patient-derived meningioma lines, with reduced expression upon mTORC1 inhibition. Apelin-13 stimulation enhanced sprouting, whereas APLN deletion reduced endothelial sprouting. CONCLUSIONS: Here we establish a 3D-tumoroid model and implicate tumor-derived Apelin as an important contributor to NF2-associated meningioma angiogenesis. Our data also suggest that APLN expression is regulated, at least in part, by mTORC1. Together, these results provide a preclinical platform for investigating angiogenic vulnerabilities beyond VEGF in NF2-deficient meningiomas.

3D tumoroid model↗

PubMed2026

De Novo Genome Sequence Assembly of the Algal Endosymbiont Micractinium conductrix Derived From Its Host Paramecium bursaria 186b.

Endosymbiosis is a major driver of evolutionary innovation and underpins the function of diverse ecosystems. The origins and evolution of endosymbiosis are challenging to study experimentally due to the short-lived culturability of many microbial strains derived from endosymbiotic interactions. The facultative endosymbiosis between the ciliate, Paramecium bursaria, and the green alga, Micractinium conductrix (Chlorellaceae, Trebouxiophyceae), is ecologically widespread and has emerged as a powerful lab-tractable model system. This endosymbiosis is founded upon a reciprocal nutrient exchange, but each of the species can be cultured independently enabling quantification of symbiotic fitness effects, new partnerships to be generated in the lab, and co-associations to be subject to experimental evolution. To date, evolve-and-resequence approaches have been limited due to a lack of high-quality genome assemblies enabling gene variants to be identified. Here, we report a near telomere-to-telomere genome assembly for M. conductrix 186b, using a range of sequencing technologies. Comparative analysis shows that this is one of the most complete Chlorellaceae algal genome assemblies available to date. To aid accurate gene calling and annotation, we conducted both RNAseq and Iso-Seq transcriptome sequencing experiments. Collectively, these 'omics datasets will facilitate: (i) comparative genomics studies of endosymbiont evolution, (ii) evolve-and-resequence experiments, (iii) genome-scale metabolic modeling studies, and (iv) identification of targets for genetic modification experiments and biotechnological applications.

Symbiosis↗

PubMed2026

scGPA: an LLM-assisted workflow for directional virtual gene perturbation analysis from single-cell transcriptomes.

BACKGROUND: Existing virtual perturbation methods can often infer directional changes by comparing predicted post-perturbation expression profiles with control cells. However, workflows that directly return direction-specific downstream candidate genes together with confidence scores, evidence support and interpretable summaries remain limited. We developed scGPA, an LLM-assisted workflow system for directional single-cell virtual gene perturbation analysis. METHODS: scGPA starts from raw single-cell RNA sequencing data and performs quality control, normalization, dimensionality reduction, clustering and cell-group selection. It then constructs cell-group-specific wild-type regulatory networks using repeated subsampling, principal component regression (PCR)/Ridge-based network inference and CP tensor denoising. Based on these networks, scGPA simulates dose-aware virtual knockdown of the target gene and applies signed perturbation propagation to estimate the magnitude and direction of downstream transcriptional responses. LLM assistance is used for marker-based cell-type annotation, evidence-guided candidate prioritization and user-facing biological summarization. RESULTS: We benchmarked scGPA across five public Perturb-seq datasets and compared its performance with GEARS, scGPT and a random baseline. The overall correct prediction rate of scGPA was 23.0%, exceeding those of GEARS (20.7%), scGPT (15.1%) and the random baseline (13.6%). These results indicate that scGPA achieved a higher correct prediction rate than the two comparator models and the random baseline. We subsequently evaluated scGPA using a public osteosarcoma single-cell dataset and performed qRT-PCR validation in 143B osteosarcoma cells. Among genes with significant experimental changes, scGPA achieved a directional concordance of 76.9%. When all tested downstream genes were counted, 37.0% were directionally correct, 51.9% showed no significant change and 11.1% changed in the opposite direction. CONCLUSIONS: scGPA provides a practical workflow system for predicting and prioritizing direction-specific downstream transcriptional responses after target-gene perturbation. By integrating single-cell regulatory network inference, signed virtual perturbation and LLM-assisted interpretation, scGPA supports target-gene function inference and downstream mechanistic investigation from single-cell transcriptomic data.

Single-Cell Gene Expression Analysis↗

PubMed2026

Multi-omics reveal molecular changes during suspension adaptation of HEK293 cells.

Human embryonic kidney 293 (HEK293) cells have been successfully adapted from adherent to suspension culture and widely applied in both scientific research and the pharmaceutical industry. Although some studies investigated the variances between established adherent and suspension HEK293 cells of different strains, specific alterations in the cells during this consecutive process of suspension adaptation and possible factors driving this process have not been well described. Here, we adapted adherent HEK293 to suspension with desirable cell growth and high productivity for recombinant adenoviral vectors, and cells at several stages throughout the process were characterized. Slower cell growth, lower glucose uptake, increased lactate production, and weaker cell-surface adhesion were observed in suspension cells compared to their adherent counterparts. We further performed transcriptomics, proteomics, and metabolomics analysis to identify key cellular switches. A total of 2476 differentially expressed genes were found, including 1218 upregulated and 1258 downregulated genes in suspension cells. A similar and correlated pattern was observed in the proteomic study, and 702 differentially expressed metabolites were identified by untargeted metabolomics. In light of enrichment analysis, we summarized that HEK293 adherent cells survived and adapted to suspension culture via structural remodeling, metabolic shift and stress resistance. Our results provide a molecular enlightenment for suspension adaptation and potential directions for rational modification of HEK293 cell lines for future use. KEY POINTS: • Suspension adaptation reduced adhesion and reshaped the HEK293 cytoskeleton. • Multi-omics revealed metabolic rewiring and enhanced stress resistance. • An optimized suspension line outperformed an internal HEK293 suspension reference.

Humans↗

PubMed2025

Alevin-fry-atac enables rapid and memory frugal mapping of single-cell ATAC-seq data using virtual colors for accurate genomic pseudoalignment.

SUMMARY: Ultrafast mapping of short reads via lightweight mapping techniques such as pseudoalignment has significantly accelerated transcriptomic and metagenomic analyses with minimal accuracy loss compared to alignment-based methods. However, applying pseudoalignment to large genomic references, like chromosomes, is challenging due to their size and repetitive sequences. We introduce a new and modified pseudoalignment scheme that partitions each reference into "virtual colors." These are essentially overlapping bins of fixed maximal extent on the reference sequences that are treated as distinct "colors" from the perspective of the pseudoalignment algorithm. We apply this modified pseudoalignment procedure to process and map single-cell ATAC-seq data in our new tool alevin-fry-atac. We compare alevin-fry-atac to both Chromap and Cell Ranger ATAC. Alevin-fry-atac is highly scalable and, when using 32 threads, is 2.8 times faster than Chromap (the second fastest approach) while using only 33% of the memory required by Chromap. The resulting peaks and clusters generated from alevin-fry-atac show high concordance with those obtained from both Chromap and the Cell Ranger ATAC pipeline, demonstrating that virtual color-enhanced pseudoalignment directly to the genome provides a fast, memory-frugal, and accurate alternative to existing approaches for single-cell ATAC-seq processing. The development of alevin-fry-atac brings single-cell ATAC-seq processing into a unified ecosystem with single-cell RNA-seq processing (via alevin-fry) to work toward providing a truly open alternative to many of the varied capabilities of CellRanger. AVAILABILITY AND IMPLEMENTATION: Alevin-fry-atac is written in Rust and C++17, and is freely-available under a BSD 3-clause license. It is integrated into piscem (https://github.com/COMBINE-lab/piscem) and alevin-fry (https://github.com/COMBINE-lab/alevin-fry), and is also supported directly as part of simpleaf (https://github.com/COMBINE-lab/simpleaf).

Single-Cell Analysis↗

PubMed2026

Genomic characterization and phylogenetic placement of Matryoshka RNA virus 1 associated with Plasmodium vivax malaria in Africa.

Plasmodium vivax is a major cause of human malaria. It harbours Matryoshka RNA virus 1 (MaRNAV-1), a bi-segmented positive-sense RNA virus. MaRNAV-1 was first described in P. vivax and is now recognized as part of a wider group of Matryoshka viruses. These viruses also infect other haemosporidian parasites such as Leucocytozoon and Haemoproteus. The presence of MaRNAV-1 in African-origin human P. vivax, however, has not been clearly established. This study investigated whether MaRNAV-1 is present in public African-origin P. vivax transcriptomic datasets. Any viral sequences recovered were characterized using comparative genomic and phylogenetic analyses. A secondary in silico analysis targeted African-origin P. vivax RNA-seq runs from public repositories. Although the search covered Africa, only Ethiopian datasets could be confidently identified, retrieved and compiled at the time. After quality control and screening for MaRNAV-1 RNA-dependent RNA polymerase (RdRp) signals, three high-confidence runs were selected for further analysis. Reference-guided reconstruction, ORF prediction, blast-based validation and RdRp phylogenetic analysis were performed. MaRNAV-1 was identified in three Ethiopian P. vivax malaria transcriptomes. This was supported by strong segment-level mapping, near-complete coverage, high mean depth and minimal low-depth masking. The recovered genomes showed the expected bisegmented organization of MaRNAV-1. Segment I was highly conserved and encoded the canonical RdRp in all three consensus sequences. Segment II showed the conserved organization of two overlapping hypothetical ORFs in all three consensus sequences. Blast analyses confirmed close similarity to MaRNAV-1 reference sequences. Phylogenetic inference grouped the Ethiopian sequences within the broader P. vivax-associated MaRNAV-1 lineage, alongside other recognized MaRNAV lineages distinct from more divergent narna-like viruses. These findings provide genomic evidence for MaRNAV-1 in publicly available African-origin P. vivax transcriptomic datasets and add to the emerging evidence for the virus in the African malaria context.

MaRNAV↗

PubMed2026

Integrative pooled transcriptomic analysis reveals shared and distinct molecular signatures in adult T-cell leukemia/lymphoma and peripheral T-cell lymphoma.

Adult T-cell leukemia/lymphoma (ATLL) and peripheral T-cell lymphomas (PTCLs) are aggressive neoplasms of mature T cells with poor prognosis and limited therapies. ATLL originates from HTLV-1 infection, while PTCL comprises heterogeneous subtypes without a defined etiologic factor. Comparative molecular profiling of these malignancies remains limited. We conducted an integrative pooled transcriptomic analysis of publicly available Gene Expression Omnibus (GEO) microarray datasets to compare ATLL, PTCL, and normal T-cell samples. Differential expression, functional enrichment, and protein-protein interaction (PPI) network analyses were performed using STRING, Cytoscape, and Gephi. Key hub genes and functional modules were further analyzed through KEGG and Enrichr databases. Comparative analyses revealed upregulation of extracellular matrix (ECM) components (COL1A1, COL3A1, FN1, SPARC, THBS1) and immune-regulatory molecules (CD163, CXCL12-CXCR4, complement subunits). Shared pathways included ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling. PTCL showed enrichment in coagulation and angiogenesis, while ATLL displayed distinct enrichment of cytoskeletal, chemokine, immune-regulatory, and signaling-associated pathways. PPI networks identified ECM and chemokine signaling as key hubs, with subtype-specific modules related to immune regulation, proliferation, and metabolism. This integrative approach uncovers common and distinct oncogenic programs in ATLL and PTCL, emphasizing ECM remodeling and immune modulation as shared hallmarks. Hub genes such as COL1A1, FN1, and CXCL12-CXCR4 may represent candidate molecular signatures that warrant validation in independent patient cohorts and functional studies before their clinical utility can be established.

Humans↗

PubMed2026

Extracellular vesicle miR-93-5p cargo regulates glomerular endothelial cell damage in Alport syndrome.

Modulation of miRNA expression in glomerular cells is associated with renal disease. Here, we investigated the role of miR-93-5p in mitigating glomerular damage in Alport syndrome and whether the disease-modifying activity of extracellular vesicles from human amniotic fluid stem cells (hAFSC-EVs) is mediated by their miR-93-5p cargo. We identified downregulation of miR-93-5p specifically in glomerular endothelial cells in Alport syndrome along disease progression. Silencing of miR-93-5p in hAFSC-EVs changed the transcriptomic and proteomic profile, regulating EV disease-modifying activity. Compared with naive hAFSC-EVs, silenced hAFSC-EVs did not rescue glomerular endothelial function in vitro and did not restore kidney function in vivo. We established that hAFSC-EVs regulate VEGFR1 and VEGFR2 signaling by miR-93-5p cargo transfer, highlighting that miR-93-5p can restore glomerular endothelial cell biology. Spatial transcriptomics analysis of hAFSC-EV-injected kidneys showed that these EVs can reverse pathways altered during disease progression by stimulating proregenerative processes, specifically in the glomerulus, by regulating miR-93-5p targets. Alteration of glomerular endothelial cell transcriptomics and miR-93-5p targets was also confirmed in biopsies of patients with Alport syndrome using spatial molecular imaging. We demonstrated the critical role of miR-93-5p in glomerular endothelial cells and the capability of hAFSC-EVs to regulate miR-93-5p and its targets in Alport syndrome.

Humans↗

PubMed2014

A better understanding of why murine models of trauma do not recapitulate the human syndrome.

OBJECTIVE: Genomic analyses from blood leukocytes have concluded that mouse injury poorly reflects human trauma at the leukocyte transcriptome. Concerns have focused on the modest severity of murine injury models, differences in murine compared with human age, dissimilar circulating leukocyte populations between species, and whether similar signaling pathways are involved. We sought to examine whether the transcriptomic response to severe trauma in mice could be explained by these extrinsic factors, by utilizing an increasing severity of murine trauma and shock in young and aged mice over time, and by examining the response in isolated neutrophil populations. DESIGN: Preclinical controlled in vivo laboratory study and retrospective cohort study. SETTING: Laboratory of Inflammation Biology and Surgical Science and multi-institution level 1 trauma centers. SUBJECTS: Six- to 10-week-old and 20- to 24-month-old C57BL/6 (B6) mice and two cohorts of 167 and 244 severely traumatized (Injury Severity Score > 15) adult (> 18 yr) patients. INTERVENTIONS: Mice underwent one of two severity polytrauma models of injury. Total blood leukocyte and neutrophil samples were collected. MEASUREMENTS AND MAIN RESULTS: Fold expression changes in leukocyte and neutrophil genome-wide expression analyses between healthy and injured mice (p < 0.001) were compared with human total and enriched blood leukocyte expression analyses of severe trauma patients at 0.5, 1, 4, 7, 14, and 28 days after injury (Glue Grant trauma-related database). We found that increasing the severity of the murine trauma model only modestly improved the correlation in the transcriptomic response with humans, whereas the age of the mice did not. In addition, the genome-wide response to blood neutrophils (rather than total WBC) was also not well correlated between humans and mice. However, the expression of many individual gene families was much more strongly correlated after injury in mice and humans. CONCLUSIONS: Although overall transcriptomic association remained weak even after adjusting for the severity of injury, age of the animals, timing, and individual leukocyte populations, there were individual signaling pathways and ontogenies that were strongly correlated between mice and humans. These genes are involved in early inflammation and innate/adaptive immunity.

Adult↗

PubMed2026

Integrative Multi-Omics Analysis of Stem Growth Habit Divergence in Wild Soybean (Glycine soja).

Stem architecture is a major determinant of lodging resistance, biomass accumulation, and harvest efficiency in soybean. However, the molecular features associated with contrasting stem growth habits in wild soybean remain incompletely characterised. Here, we performed an integrated transcriptomic, metabolomic, and epigenomic analysis of stem growth-habit divergence in wild soybean, comparing the wild-type accession ZYD7068 with contrasting vining and erect mutant lines derived from carbon-ion beam mutagenesis. Pairwise transcriptomic comparisons identified between 20 311 and 28 705 differentially expressed genes per contrast, with a core set of 2672 genes consistently altered across the comparisons. Functional enrichment, gene set variation analysis, and gene set enrichment analysis converged on xylem and phloem pattern formation as a prominent molecular pathway associated with growth-habit divergence. Random forest analysis identified BBR-BPC and ARF transcription factor families as major molecular discriminators, while metabolomic profiling revealed distinct metabolic profiles involving amino-acid-derived and lipid-associated metabolites. Whole-genome bisulfite sequencing revealed context-specific DNA methylation differences, including substantial variation in CHG methylation among erect mutant lines. Integrated network and in silico perturbation analyses prioritised four candidate genes associated with vascular development for future functional validation. Together, these results provide a multi-layer molecular resource for investigating stem growth-habit divergence in G. soja and establish testable candidate pathways and genes for subsequent functional studies and soybean improvement.

glycine soja↗

PubMed2026

Lower androgen sulfate metabolites in women with hypermobile Ehlers-Danlos syndrome may be associated with changed metabolism and disposition.

Hypermobile Ehlers-Danlos Syndrome (hEDS), characterized by joint hypermobility and multisystem involvement, is the most common type of EDS. Its comorbidities are wide-ranging, reflecting the involvement of connective tissue and its role in a multitude of processes. hEDS has been hypothesized to have hormonal aspects since the disorder is diagnosed more often in women and symptom changes closely correlate with hormonal shifts. To better understand the etiology and biochemical changes in hEDS and its comorbidities, a multiple-omics study was performed in women, controls (n = 45) and those with hEDS (n = 45), alongside the collection of questionnaires related to symptom severity. Metabolomic evaluation was performed on serum samples and RNA isolated from fibroblasts cultured from skin punches was analyzed for transcriptomics. Samples from hEDS patients had statistically significantly lower levels of multiple androgen sulfate metabolites, compared with controls, driven largely by participants aged 30-49. Changes to other classes of steroid hormones (corticosteroids, progestogens, and estrogens) were largely not significant between hEDS and control groups. Transcriptomics of skin fibroblasts from hEDS patients revealed downregulation of multiple enzymes involved in biosynthesis, metabolism, and disposition of androgens, compared with controls. Multiple steroid hormones correlated with symptoms surveyed in 18-29 year old participants with hEDS. Shifts in steroid hormone metabolites in hEDS compared with controls may be due to changes to metabolism and disposition, but more validation is necessary to be conclusive. This data provides insights into the unclear links between steroid hormones and hEDS and its comorbidities.

Humans↗

PubMed2026

Multi-omics-based study on the biological characteristics of kidney renal deficiency and blood stasis in ankylosing spondylitis.

OBJECIVE: To explore the objective biological evidence for the classification and diagnosis of Traditional Chinese Medicine (TCM) syndromes in ankylosing spondylitis (AS) using multiomics analysis. METHODS: Patients with AS were categorized into kidney deficiency and blood stasis syndrome (SX group) and damp-heat stasis syndrome (SR group). Transcriptomic sequencing and quantitative plasma proteomics were performed on patients with AS and healthy volunteers. Multiomics integration was used to characterize the biological basis of AS with renal deficiency and blood stasis syndrome. Specific proteins were validated by quantitative reverse transcription-polymerase chain reaction (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA). RESULTS: Transcriptomic sequencing identified 31 significantly upregulated genes in patients with AS compared to healthy controls. These genes were primarily involved in tumor necrosis factor, interleukin-17, and nuclear factor kappa-B signaling pathways, as well as osteoblast differentiation and various viral infection pathways. Differentially expressed genes, including intercellular adhesion molecule 1 (ICAM1), 6-phosphofructo-2-kinase, cyclin-dependent kinase inhibitor 1A, interleukin 1 receptor antagonist, integrin alpha IIb, and myosin light chain 9 were more upregulated in the SX group than in the SR group. Quantitative proteomics identified 723 differential proteins associated with the disease and 788 differential proteins between the SX and SR groups. Notable proteins such as myeloperoxidase, cluster of differentiation 14, macrophage simulating 1 (MST1), and Ras homolog enriched in brain may serve as characteristic proteins of the SX group. By integrating transcriptomic and proteomic data, 45 associated differential molecules involved in platelet activation, pathogenic intestinal flora infection, glycolysis/gluconeogenesis, and T-cell receptor signaling pathways were identified in patients with AS compared to healthy controls. Additionally, ICAM1, MST1, C-X-C motif chemokine ligand 8 (CXCL8), suppressor of cytokine signaling 3 (SOCS3), and insulin-like growth factor binding protein 1 (IGFBP1) were detected in TCM syndromes by RT-qPCR and ELISA, showing upregulation in AS renal deficiency and blood stasis syndromes, which is consistent with the proteomic and transcriptomic results. CONCLUSIONS: ICAM1, MST1, CXCL8, SOCS3, and IGFBP1 were identified as biomarkers of renal deficiency and blood stasis syndrome in AS. This study provides a biological basis for the differential diagnosis of TCM syndromes in AS, offering new insights into Chinese medicine evidence and more precise Chinese medicine treatments for AS.

Humans↗

PubMed2026

Transcriptomic and network analyses identify epigenetic regulators of drug-tolerant persister (DTP) subsets in EGFR-mutant HCC827 non-small cell lung cancer.

BACKGROUND: The clinical efficacy of osimertinib, a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI), in EGFR-mutant non-small cell lung cancer (NSCLC) is limited by the inevitable acquired resistance. Drug-tolerant persister (DTP) cells, which survive initial therapy, are considered a key reservoir for this resistance. Understanding the molecular characteristics of DTPs is essential for developing strategies to prevent relapse. OBJECTIVE: This study aimed to characterize the transcriptomic landscape of osimertinib-tolerant DTP cells and identify key epigenetic regulators associated with the DTP phenotype in EGFR-mutant HCC827 NSCLC cells through integrated transcriptomic and network analyses. METHODS: We established an in vitro model of osimertinib tolerance using an EGFR-mutant (exon 19 deletion) HCC827 NSCLC cell line. Parental HCC827 cells and DTP subsets were subjected to transcriptomic analysis by RNA sequencing (RNA-seq). Differentially expressed genes were identified, followed by bioinformatics analyses, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interaction (PPI) network analyses to identify key biological processes driving the DTP phenotype. Key findings were validated using quantitative real-time PCR (qPCR). RESULTS: Osimertinib treatment induced a morphologically distinct DTP population. Transcriptomic profiling revealed a marked shift in gene expression compared to parental cells. Functional enrichment analysis showed significant upregulation of epigenetic pathways. PPI network analysis identified a core module of eight hub genes, including histone deacetylases (HDAC5, HDAC9), sirtuins (SIRT1, SIRT2), and histone acetyltransferase (KAT2B). qPCR confirmed increased expression of HDAC5, HDAC9, and SIRT1. CONCLUSION: Epigenetic reprogramming accompanies the transition to an osimertinib-tolerant state in EGFR-mutant HCC827 cells. Targeting HDACs and sirtuins may represent a promising strategy to eliminate DTP subpopulations and delay or prevent acquired resistance.

Drug-tolerant persister↗

PubMed2025

Alevin-fry-atac enables rapid and memory frugal mapping of single-cell ATAC-seq data using virtual colors for accurate genomic pseudoalignment.

Ultrafast mapping of short reads via lightweight mapping techniques such as pseudoalignment has significantly accelerated transcriptomic and metagenomic analyses, often with minimal accuracy loss compared to alignment-based methods. However, applying pseudoalignment to large genomic references, like chromosomes, is challenging due to their size and repetitive sequences. We introduce a new and modified pseudoalignment scheme that partitions each reference into "virtual colors…. These are essentially overlapping bins of fixed maximal extent on the reference sequences that are treated as distinct "colors" from the perspective of the pseudoalignment algorithm. We apply this modified pseudoalignment procedure to process and map single-cell ATAC-seq data in our new tool alevin-fry-atac . We compare alevin-fry-atac to both Chromap and Cell Ranger ATAC . Alevin-fry-atac is highly scalable and, when using 32 threads, is approximately 2.8 times faster than Chromap (the second fastest approach) while using approximately one third of the memory and mapping slightly more reads. The resulting peaks and clusters generated from alevin-fry-atac show high concordance with those obtained from both Chromap and the Cell Ranger ATAC pipeline, demonstrating that virtual colorenhanced pseudoalignment directly to the genome provides a fast, memory-frugal, and accurate alternative to existing approaches for single-cell ATAC-seq processing. The development of alevin-fry-atac brings single-cell ATAC-seq processing into a unified ecosystem with single-cell RNA-seq processing (via alevin-fry ) to work toward providing a truly open alternative to many of the varied capabilities of CellRanger . Furthermore, our modified pseudoalignment approach should be easily applicable and extendable to other genome-centric mapping-based tasks and modalities such as standard DNA-seq, DNase-seq, Chip-seq and Hi-C.

Journal Article↗

PubMed2026

Deep FLASH-seq profiling of purified canine sensory neurons uncovers species-specific signatures relevant to pain and itch.

Naturally occurring pain and itch disorders in the domestic dog represent an important and underexploited opportunity for translational sensory neuroscience. These conditions largely mirror human disease, highlighting the need for detailed comparative understanding of canine somatosensory neurobiology. Here, we present a single-cell transcriptomic characterisation of the canine dorsal root ganglion (DRG), providing molecular insights into sensory neuron diversity in a species of direct veterinary and biomedical relevance. We develop a novel mechanical dissociation and fluorescence-activated cell sorting strategy enabling purification of intact whole neurons from adult canine DRG, followed by deep, full-length RNA sequencing using FLASH-seq. This approach yields high-quality transcriptional profiles with molecular depth analogous to deep neuronal profiling in human DRG, enabling resolution of neuronal identities and subtype-specific gene programs. Using these data, we identify canine sensory neuron clusters conforming to conserved principles of DRG molecular organization observed across species, including peptidergic and noncanonical peptidergic nociceptors, low-threshold mechanoreceptors, proprioceptors, and thermosensory populations. Cross-species comparisons with human and mouse DRG datasets reveal broad conservation of pain- and itch-relevant pathways and therapeutic targets, alongside biologically meaningful divergence. We further identify species-specific differences in subtype-restricted expression of the pharmacologically relevant receptors IL31RA and SSTR2 , which we validate using in situ hybridization and contextualize with human spatial transcriptomic data. Finally, we provide evidence that domestication-associated genes are nonrandomly enriched in specific sensory neurons, suggesting that evolutionary history may have shaped somatosensory function. These data represent a resource for comparative sensory neuroscience and inform translational interpretation of pain and itch therapeutics across species.

Animals↗

PubMed2026

Single-cell transcriptome revealed the aberrant keratinocytes activation in antigen presentation in atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD), a common chronic inflammatory skin disease, has been extensively studied using single-cell genomics. However, keratinocytes, as key effector cells in AD, have underlying mechanisms remain incompletely understood and require further investigation. METHODS: We integrated single-cell transcriptomic data from skin tissues of healthy controls, chronic active AD patients, spontaneously healed AD (SHAD) patients, and an ovalbumin-induced AD mouse model. The study particularly emphasized the gene expression and cellular dynamics of keratinocytes across the different groups, as well as their interactions with immune cells. RESULTS: Compared to healthy controls, we observed significant changes in the keratinocyte transcriptome, cellular state, and keratinocyte-immune cell ligand-receptor interactions in AD skin, particularly the marked activation of genes involved in antigen processing and presentation. Interestingly, such gene activation was not observed in keratinocytes from the ovalbumin-induced AD mouse model, despite its phenotype closely resembling human AD. Furthermore, in SHAD, we identified a recovery of both the ligand-receptor interaction patterns and antigen processing and presentation genes, accompanied by a notable shift in the transcriptome. This involved a significant downregulation of genes related to cytoplasmic transcription and oxidative phosphorylation. Notably, this pattern was not observed in the self-healing mouse model following the removal of ovalbumin stimulation. CONCLUSION: Our results suggest that the persistent activation of antigen processing and presentation pathways in keratinocytes may be a key driver of chronic inflammation in AD. Therefore, redirecting anti-allergic therapeutic strategies from solely targeting immune cells to targeting of keratinocyte-mediated antigen presentation may offer a more effective approach. Furthermore, we raise concerns about the use of ovalbumin-induced mouse models to recapitulate human chronic AD, as the underlying mechanisms may differ significantly.

Dermatitis, Atopic↗