SEARCH · PubMed Health

Results for “omics analysis”

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

PubMed2026

Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.

Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P = 0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3 °C; +4.5 °C relative to CK_M), and its group-mean temperature remained ≥ 60 °C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.

Bacillus↗

PubMed2026

Multi-omics analysis reveals Protein Kinase A-associated regulatory remodeling during adaptation of Trichoderma reesei to lignocellulosic substrate.

The filamentous fungus Trichoderma reesei is a major industrial source of holocellulolytic enzymes, and its response to complex carbon sources is regulated by nutrient-sensing mechanisms, including the cyclic adenosine monophosphate (cAMP)-protein kinase A (PKA) signaling pathway. Here, we integrated transcriptomics, quantitative proteomics, and phosphoproteomics to analyze PKAc1-associated responses in the parental strain QM9414 and a Δpkac1 strain cultivated under glucose or sugarcane bagasse conditions. Deletion of pkac1 was associated with altered growth-related phenotypes and reduced extracellular activities of selected biomass-depolymerizing enzymes. Multi-omics profiling revealed condition-dependent changes affecting subsets of carbohydrate-active enzymes (CAZymes) genes and proteins, nutrient transporters, stress-associated proteins, and regulatory factors. Phosphoproteomics identified phosphorylation-state changes associated with pkac1 deletion, including reduced phosphorylation at sites enriched for the PKA consensus motif. In silico peptide docking was used to prioritize candidate PKAc1-associated substrates for future validation, including a Sec 7-derived peptide with favorable docking behavior relative to the control peptide. Together, these data support a working model in which PKAc1 contributes to regulatory and phosphorylation-state remodeling during adaptation to sugarcane bagasse, with effects on the magnitude and/or timing of selected CAZyme-related outputs in T. reesei.

Trichoderma↗

PubMed2025

Integrative multi-omics analysis proposes a metabolic classification of gliomas: distinct metabolic states, immune infiltration, and prognosis.

BACKGROUND: The tumor microenvironment (TME) of glioma harbors diverse cell types; however, cell metabolic heterogeneity remains to be explored. This study aims to characterize the metabolic features of different cell types in the TME by integrating multiple datasets, including genomics, bulk and single-cell transcriptomics, and metabolomics. METHODS: Unsupervised machine learning was used to construct an energy metabolic classifier based on the metabolic pathways identified from bulk RNA-seq of gliomas in the TCGA dataset. The classifier was externally validated using multiple datasets, including genomics, bulk RNA-seq, snRNA-seq, and the metabolomics data. Furthermore, metabolic heterogeneity associated with the classifier was further characterized at single-cell resolution. RESULTS: The energy metabolism-based classifier stratified patients into two prognostic clusters: patients in cluster 1 were characterized by high pathway activity of glycolysis, the pentose phosphate pathway (PPP), and fatty acid oxidation (FAO), whereas patients in cluster 2 exhibited higher activity in glutaminolysis. This metabolic classifier revealed both intratumoral and intertumoral metabolic heterogeneity, and the complexity was further validated by the metabolomics profiling and snRNA-seq data from the CPTAC dataset. Notably, OSMR, highly expressed in cluster 1, showed significant co-expression with key glycolytic enzyme genes. The OSM/OSMR/JAK1/STAT3 axis potently drives malignant progression of glioma cells, specially enhancing their invasive and migratory capabilities. Single-cell resolution analyses demonstrated that tumor metabolic heterogeneity is primarily driven by malignant cells rather than non-malignant components, while tumor microenvironment (TME) factors were also found to modulate malignant cell metabolism. Significantly, glycolytic activity in glioma cells increased during the phenotypic transition from PN (proneural) to MES (mesenchymal), with cluster 1 metabolic phenotypes predominating in the tumor core. Compared to cluster 2, cluster 1 patients exhibited higher mRNA expression of immunosuppressive checkpoint genes, which correlated with pronounced immunosuppression in the TME. Furthermore, various immune cells demonstrated distinct metabolic preferences at single-cell resolution. CONCLUSIONS: This study developed an energy metabolic-based classifier for gliomas with prognostic and therapeutic potential. Metabolic reprogramming was linked with the PN-to-MES transition of glioma cells and immunosuppression in the tumor microenvironment. Multi-omics data, especially snRNA-seq, offered insights into metabolism heterogeneity at single-cell resolution, enabling personalized treatment strategies.

Humans↗

PubMed2025

Multi-Omics Analysis of the Potential Mechanisms of Skin Albinism in Edangered Percocypris pingi: Abnormal Ubiquitination and Calcium Signal Inhibition.

Percocypris pingi is an endangered protected fish species in China. Its albino variants exhibit growth retardation and physiological abnormalities. Understanding its albinism mechanism holds significant scientific importance for molecular breeding programs and disease model development. This study integrated transcriptomic and proteomic analyses, combined with histopathological and molecular biological techniques, to systematically compare molecular differences in skin tissues between albino and wild-type P. pingi, with a focus on elucidating the multidimensional regulatory mechanisms underlying skin albinism. Our findings suggest that albinism in P. pingi is synergistically driven by hyperactivation of ubiquitin-mediated proteolysis (which suppressed TYR/TYRP1 enzymatic activity and disrupted the pH homeostasis of melanosomes), and inhibition of calcium signaling (which impeded melanin transport). This discovery provides novel insights into the mechanisms of pigment loss in fish species and offers a valuable reference for molecular breeding of endangered species as well as research on pigmentation-related disorders.

Animals↗

PubMed2026

Multi-omics analysis identifies key genes and functional loci affecting teat number in American Large White and Landrace pigs and their application in optimizing genomic selection models.

BACKGROUND: Teat number is a crucial economic trait in pigs. It directly affects the ability of sows to lactate, which in turn influences the survival and health of piglets. The teat number of French Large White pigs is close to 16, while the teat number of American Large White and Landrace pigs is about 14. In order to improve the teat number of American Landrace and Large White pigs through molecular approaches and precise breeding techniques, we genotyped 2,131 American Landrace and 4,564 American Large White with teat number phenotype using a 50 K SNP chip. Then, the SNP-chip data was imputed to the level of whole-genome sequencing (iWGS). Based on iWGS data, we conducted GWAS to identify novel, significant SNPs associated with teat number and to incorporate them into genomic selection. RESULTS: In Landrace pigs, significant SNPs for TTN mapped to SSC2, SSC7, SSC8, and SSC14; the SSC8 and SSC14 effects are novel. LTN mapped to SSC7, RTN to SSC7 and SSC8. The lead SSC7 SNP explained 2.60% of TTN phenotypic variance. In Large White pigs, significant SNPs were detected on SSC7 and SSC10 for TTN; SSC7, SSC10, and SSC12 for LTN; and SSC7 and SSC10 for RTN. The most significant locus on SSC7 accounted for 2.99% of the phenotypic variance in TTN. Additionally, a multi-population meta-analysis detected significant novel SNPs for LTN on SSC1 and SSC8. By utilizing Bayesian fine mapping, the most precise QTL confidence interval on SSC7 for both TTN and RTN in Large White pigs was reduced to 40 kb. By integrating functional gene annotation with RNA-seq and ATAC-seq data from Erhualian and Bamaxiang pigs mammary placodes at embryonic day 26, we prioritized PTPN13, TRPV3, ZDHHC13, and BRD2 as novel candidate genes for teat number. We then incorporated the significant SNPs to GBLUP and benchmarked genomic-selection accuracy. In both breeds, fitting the top SNP as fixed maximized prediction for TTN and RTN, whereas treating all significant loci as an additional random effect optimized LTN. CONCLUSIONS: Our findings provide a theoretical basis for dissecting new key genes affecting teat number and for advancing molecular breeding of teat number in pigs.

Animals↗

PubMed2026

Secondary metabolite profiling of rare Micromonospora spp. from cold desert of NW Himalayas via multi-omics analysis.

INTRODUCTION: The genus Micromonospora is a prolific producer of specialized metabolites with pharmacological and agronomic relevance. Natural products derived from the genus Micromonospora have a distinctive chemical diversity and enormous therapeutic potential, thus represent a potential source for drugs and drug leads. OBJECTIVE: To explore the biosynthetic potential of four Micromonospora strains isolated from cold desert of NW Himalayas through genome mining and to correlate predicted biosynthetic gene clusters with chemical features detected by untargeted LC-HRMS metabolomics. METHOD: High-quality genomes were annotated for BGCs and matched against untargeted LC-HRMS features (peak picking, alignment, and annotation to chemical classes). Each isolate was grown in triplicate, and fermented broth was pooled for further metabolomic studies. RESULTS: By integrating genomic and metabolomic approaches, specialized biosynthetic gene clusters and strain-based putative metabolite classes were identified. LRS1 showed elevated xanthines (RiPP/siderophore), LRS3 had phenolic glycosides (hybrid PKS/NRPS), LRS4 showed 70-fold hydroxycinnamate enrichment (Type II PKS), and LRS5 displayed p-benzoquinone enrichment (Type III PKS). The metabolite profile of each strain aligned with its predicted biosynthetic gene cluster composition. CONCLUSION: Under a single growth regime, each Micromonospora strain exhibits a distinct metabolomic profile. This metabologenomics workflow can be further explored to isolate specialized metabolites with potential therapeutic and agricultural value.

Micromonospora↗

PubMed2025

Integrated multi-omics analysis reveals TMEM147 as an immunosuppressive prognostic biomarker in LUAD.

TMEM147, an endoplasmic reticulum (ER) membrane protein, is implicated in lung adenocarcinoma (LUAD) progression, although its precise role remains unclear. To elucidate its function, this study integrated bioinformatics analyses with experimental validation. First, TMEM147 expression was assessed using TCGA and GEO datasets, with validation performed in LUAD cell lines. Survival analysis evaluated its prognostic significance. Subsequently, Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and single-sample gene set enrichment analysis (ssGSEA) were employed to identify associated functional pathways and interactions within the tumor immune microenvironment. Transcription factor binding predictions and in vitro functional assays (migration, invasion, proliferation) further characterized TMEM147's role. Results indicated that TMEM147 was significantly upregulated in LUAD and correlated with poor outcomes in patients. FLI1 was predicted as a key transcriptional regulator of TMEM147. Furthermore, TMEM147 expression influenced immune cell infiltration profiles and was associated with pathways involved in ribonucleoprotein biogenesis and oxidative phosphorylation (OXPHOS). Importantly, silencing TMEM147 significantly reduced cancer cell migration, invasion, and proliferation. These findings collectively suggest that TMEM147 promotes LUAD progression and holds potential as both a prognostic biomarker and a therapeutic target.

Bioinformatics analysis↗

PubMed2026

Multi-omics analysis reveals stage-associated differences in gut immunity and microbiota between juvenile and adult common carp (Cyprinus carpio).

In vertebrates, the development of intestinal immunity is closely associated with dynamic changes in the gut microbiota. However, stage-associated differences in intestinal immunity and gut microbial communities remain poorly characterized in teleost fish. In this study, transcriptomic analysis combined with 16S rRNA gene sequencing was employed to characterize intestinal immunity and gut microbial communities in juvenile and adult common carp (Cyprinus carpio). Transcriptomic profiling revealed marked developmental differences in intestinal immune function. Juvenile carp exhibited a predominantly innate immune phenotype, characterized by elevated expression of pro-inflammatory cytokines, antimicrobial peptides, and lysozyme-related genes. This immune profile was accompanied by enhanced mucosal barrier function and a relatively pro-inflammatory intestinal environment. In contrast, adult carp displayed increased expression of genes associated with adaptive immunity, suggesting that adult common carp exhibit relatively stronger adaptive immune characteristics than juvenile fish. Gut microbiota analysis demonstrated significant stage-dependent differences in microbial diversity and community composition. Juvenile fish were enriched with bacterial taxa potentially associated with innate immune activation, whereas adult fish harbored distinct microbial communities linked to intestinal homeostasis and barrier maintenance. Furthermore, correlation analyses identified significant associations between specific microbial taxa and innate immune-related gene expression, suggesting a close association between gut microbiota composition and intestinal immune characteristics in juvenile and adult common carp. Collectively, these findings reveal stage-associated differences in intestinal immunity and gut microbial communities between juvenile and adult common carp, thereby providing insights into intestinal immune characteristics at different developmental stages in teleost fish.

Animals↗

PubMed2025

Exploring the shared genetic basis of attention-deficit/hyperactivity disorder and obstructive sleep apnea: A multi-omics analysis.

BACKGROUND: Observational studies have suggested an association between attention-deficit/hyperactivity disorder (ADHD) and obstructive sleep apnea (OSA), but these findings are often inconsistent due to potential biases from medication use, and varying diagnostic criteria. Genetic analyses can help mitigate these confounding factors, providing additional evidence. METHODS: This study evaluated the genetic correlations between ADHD and OSA using Genome-wide association study (GWAS) summary data, applying linkage disequilibrium score regression (LDSC) and SUPER GeNetic cOVariance Analyzer (SUPERGNOVA). Cross-trait association and colocalization analysis identify potential pleiotropic loci. Tissue enrichment analysis and gene-level analysis of shared genes between OSA and ADHD was conducted. Additionally, bidirectional Mendelian randomization was used to assess potential causal relationships. RESULTS: We found significant genetic correlations between ADHD and OSA (rg = 0.309, p = 3.252E-27), and identified 8 novel pleiotropic loci through cross-trait association analysis. Tissue enrichment analysis showed that these shared genes were primarily concentrated in brain tissues, particularly in deep gray matter regions, and were associated with immune and inflammatory pathways. Forward Mendelian Randomization analysis showed that ADHD was significantly associated with the risk of OSA (OR 1.070, 95 % CI 1.013-1.130, p = 0.016), and reverse analysis showed that OSA was significantly associated with the risk of ADHD (OR 1.240, 95 % CI 1.106-1.390, p = 2.213E-4). CONCLUSION: The findings of this study show a significant positive genetic correlation between ADHD and OSA and each is a risk factor for the other. Inflammation in specific brain regions may be the underlying mechanism for their comorbidity.

Humans↗

PubMed2025

Live-Cell Monitoring and Omics Analysis of Liquid-Solid Transitions of Biomolecular Condensates.

Biomolecular condensates, or so-called membraneless organelles, transition from liquid into more solid-like states over time, contributing to the development of pathological conditions. The present study proposes a simple method using photoactive yellow protein (PYP) and its specific fluorescent covalent ligands to distinguish between the liquid and solid states of protein condensates in live cells. The method, compatible with fluorescence-activated cell sorting (FACS), correlates the stiffness of specific protein condensates with their accessibility to PYP ligands, enabling quantitative multicolor monitoring of condensate solidification. We applied this technique to 12 phase-separating proteins and their mutants, finding that TDP-43, particularly its A315T mutant linked to familial amyotrophic lateral sclerosis, most readily forms solid aggregates. Furthermore, this FACS-compatible strategy enabled the isolation of distinct cell populations based on condensate states, allowing for subsequent proteomic and transcriptomic analyses. Our findings demonstrate that condensate solidification is accompanied by the upregulated expression of extracellular matrix proteins, suggesting a previously unrecognized link between solid aggregate formation and extracellular matrix hardening.

Humans↗

PubMed2026

Immune cell-specific genetic architecture of Alzheimer's disease revealed by multi-omics analysis for therapeutic target discovery and prioritization.

Alzheimer's disease (AD) is a multifactorial neurodegenerative condition in which accumulating genetic and molecular evidence implicates dysregulation of peripheral immune processes in disease pathogenesis. Nevertheless, the contribution of distinct peripheral immune cell subsets and associated gene regulatory landscapes to AD risk remains incompletely defined. To address this gap, we integrated single-cell expression quantitative trait loci (sc‑eQTL) data from the OneK1K cohort with AD GWAS summary statistics. We systematically interrogated immune cell-specific genes for their contributions to AD risk by integrating genetic causal inference with Bayesian colocalization analyses, and identified 24 eGenes that passed both the MR significance threshold (P < 0.05) and the criterion for strong shared genetic signals (PP.H4 > 0.8). Notable candidates included GATS, HLA-DOB, HLA-DQA1, PM20D1, and others, with each gene demonstrating a cell-type-specific association restricted to its corresponding immune cell type, such as monocytes, CD8 + T cells, or B cells. Independent peripheral blood single-cell transcriptomic data further supported disease-associated shifts in cell-type-specific expression patterns in AD. Phenome-wide association studies (PheWAS) indicated limited associations with off-target traits, indicating a favorable safety profile for therapeutic intervention, with the exceptions of B4GALNT3, PM20D1, and CNN2. Integration of immune gene targets with pharmacological databases yielded three candidate compound, including NSC321521 (targeting HLA-DQA1), phenoxybenzamine (targeting GSTP1), and rimexolone (targeting BIN1). Among these compounds, Predicted blood-brain barrier permeability was observed only for phenoxybenzamine and rimexolone, with docking studies indicating stable interactions, such as those between NSC321521 and HLA-DQA1, phenoxybenzamine and GSTP1, and rimexolone and BIN1. This integrative approach highlights key immune‑cell‑specific genes involved in AD and proposes repurposable drugs with central nervous system potential, paving the way for more targeted immunomodulatory strategies in AD.

Humans↗

PubMed2022

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses.

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

Epidermal Growth Factor↗

PubMed2026

Integrated Multi-Omics Analysis Reveals the Genetic Basis of Phenotypic Variation in Tibetan Sheep.

Body size is a key economic trait influencing the profitability of farmed animals. This study used genome-wide association studies (GWAS) to identify five single nucleotide polymorphisms (SNPs) significantly associated with body size in the Tibetan sheep population, advancing molecular breeding and providing a basis for genomic selection. These SNPs are located within five candidate genes. SNaPshot validated GWAS results, demonstrating significant correlations between candidate SNPs and body size traits in Tibetan sheep. Concurrently, hematoxylin and eosin staining, alongside muscle fiber analysis, confirmed pronounced morphological differences in muscle tissue between sheep of varying conformation. Therefore, transcriptome and proteomics were performed on the longest dorsi muscle from large and small Tibetan sheep of both sexes. The transcriptome, together with weighted gene co-expression network analysis (WGCNA), identified VEPH1 and PRKG1 as core genes regulating body characteristics in Tibetan sheep through their involvement in the PI3K-Akt signaling pathway and pathways related to fat deposition. The integrative analyses demonstrated significantly different expression of CARNS1 and CRYAB at both transcriptional and protein levels between the muscles of large- and small-sized Tibetan sheep of both sexes, suggesting their importance in body size traits by influencing muscle morphology. This study provides valuable genomic resources that advance sheep genetics research.

GWAS↗

PubMed2025

Multi-Omics Analysis of Experimentally Evolved Candida auris Isolates Reveals Modulation of Sterols, Sphingolipids, and Oxidative Stress in Acquired Amphotericin B Resistance.

Clinical isolates of Candida auris show a high prevalence of resistance to Amphotericin B (AmB)-an uncommon trait in most Candida species. Alterations in ergosterol biosynthesis can contribute to acquired AmB resistance in C. auris laboratory strains but are rarely seen in clinical isolates. In this study, we experimentally evolved two drug-susceptible Clade II isolates of C. auris to develop AmB resistance. The evolved strains displayed a four to eight fold increase in MIC50 compared to the parental cells. We analyzed changes in their karyotype, genome, lipidome, and transcriptome associated with this acquired resistance. In one lineage, AOX2 was upregulated, and its deletion reversed the AmB resistance phenotype. The aox2Δ mutant also failed to evolve AmB resistance under experimental conditions. In the same lineage, restoring the UPC2 S332R and RTG3 S101T mutations to the wild-type allele restored AmB susceptibility. In another lineage, the ergosterol and sphingolipid pathways were observed to play a critical role, and upregulation of the ERG genes elevated the total sterol content, while significant downregulation of HSX11 (glucosylceramide synthase) resulted in lower levels of glucosylceramides. To our knowledge, this study is the first to show that AmB resistance in C. auris can be acquired through mechanisms both dependent on or independent of sterol content modulation, highlighting Aox2 and Upc2 as key regulators of amphotericin resistance.

Amphotericin B↗

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↗

PubMed2025

Multi-omics analysis of ubiquitin E2 genes in Setaria: evidence for the roles of E2 genes in various aspects of plant development, stress tolerance, and domestication.

Ubiquitin E2 enzymes (E2s) are critical mediators in the ubiquitination cascade, a post-translational modification process that regulates protein stability, activity, localization, and degradation. Here, we analyzed the E2 gene family in foxtail millet (Setaria italica), integrating comparative genomics, transcriptomics, and functional studies. A total of 52 E2 genes were identified and classified into four subfamilies (UBC, UEV, SCE, and RCE) based on phylogenetic analysis across 49 species. Notably, foxtail millet exhibited significant gene expansion. Tissue-specific expression profiling revealed distinct roles of E2 genes in growth and development. Haplotype and quantitative trait loci analyses demonstrated that several E2 genes, including SiUBC39, are associated with key agronomic traits, such as plant height, flowering time, and stress tolerance. Using CRISPR/Cas9, we validated the functional role of SiUBC39, finding that its disruption led to phenotypes resembling wild species (Setaria viridis), such as early flowering and reduced plant height and grain yield. IP-MS and transcriptome analysis revealed SiUBC39's involvement in growth and development regulation, drought stress response, and immune response. SiPIP2;1 and SiEhd2 were identified as interactors of SiUBC39, explaining its roles in blast resistance and flowering time control. Furthermore, domestication analysis identified an A/G mutation in the SiUBC39 promoter TATA box, distinguishing domesticated and wild haplotypes and highlighting its role in domestication selection. This study underscores the essential roles of E2 genes in regulating crop agronomic traits and stress responses, providing valuable insights for genetic improvement in foxtail millet and other cereals.

Setaria Plant↗

PubMed2026

Multi-omics analysis of glucocorticoid receptor crosstalk with Type I and Type II inflammatory signaling in human airway smooth muscle cells.

Airway smooth muscle (ASM) dysfunction in obstructive airway disease is treated with glucocorticoids. Through RNA-seq analysis of cultured human ASM, we identified repressive effects of dexamethasone, a glucocorticoid, on the baseline expression of a subset of genes that are induced by either IL1B or IL13, which model Type I and Type II inflammation, respectively. ChIP-seq analysis of glucocorticoid receptor (GR) and the p65 subunit of NFkB occupancy indicated canonical motifs for both factors occur at sites of p65 occupancy but did not provide biochemical support for significant repressive tethering between GR and p65. Instead, ATAC-seq revealed significant chromatin remodeling and increased accessibility at binding motifs for the NFkB complex in association with dex + IL1B co-treatment in comparison to IL1B treatment alone. Our data support a competition-based primary repressive effect of glucocorticoids on both IL1B and IL13 signaling and provide evidence for transcriptional cooperation between GR and NFkB on a genome-wide basis in ASM, including at regulatory elements that control expression of anti-inflammatorygenes.

chromatin↗

PubMed2026

Gut microbiota dysbiosis and host metabolite-immune crosstalk drives the pathogenesis of neonatal lupus erythematosus: a multi-omics analysis.

BACKGROUND: Neonatal lupus erythematosus (NLE) is a rare autoimmune condition triggered by the transplacental transfer of maternal antibodies. Despite its recognized clinical manifestations, the underlying pathogenesis remains incompletely understood. This study seeks to explore the disruption of the gut microbiota-host metabolism-immune axis in anti-Ro/La-positive neonates, and to assess its potential role in the development of NLE. METHODS: This multicenter, cross-sectional study included 90 neonates, divided into three groups: 30 with neonatal lupus erythematosus (NLE), 30 with positive antibodies but without clinical manifestations (No-NLE), and 30 healthy controls. We performed 16 S rRNA sequencing to analyze gut microbiota composition, untargeted plasma metabolomic profiling, and proteomic analysis to identify alterations associated with the pathogenesis of NLE. RESULTS: We identified significant alterations in the gut microbiota, plasma metabolome, and proteome profiles of anti-Ro/La-positive neonates. NLE infants exhibited marked enrichment of Enterobacteriaceae and depletion of Bifidobacterium and Clostridium butyricum. Metabolomic analysis revealed hyperactivation of β-alanine and purine metabolism, along with impaired α-linolenic acid metabolism and endocannabinoid signaling. Proteomic profiling indicated aberrant protein expression that modulated IFN signaling, particularly within the C-type lectin receptor pathway. Dysregulation of the spleen tyrosine kinase (SYK) and high-affinity immunoglobulin epsilon receptor subunit gamma (FCER1G) decoupling was observed, correlating with elevated IFN-α and NF-κB p65 levels. Integrated correlation analysis revealed significant associations among differential microbial taxa, plasma metabolites, and proteins. Notably, E. coli-associated metabolites and proteins displayed inverse relationships with those associated with C. butyricum. CONCLUSIONS: These findings represent comprehensive evidence of dysregulation along the "gut microbiota-host metabolism-immune" axis in neonatal lupus erythematosus (NLE), providing novel insights into the disease's underlying heterogeneity.

Humans↗