SEARCH · PubMed Health

Results for “Gene co-expression network”

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

Comparative transcriptome analysis of Qinchuan and Wagyu cattle reveals lnc11599 as a negative regulator of intramuscular fat deposition.

BACKGROUND: Intramuscular fat (IMF) content is a critical factor determining beef quality, influenced by various factors including breed and age. However, the regulatory role of long non-coding RNAs (lncRNAs) in IMF deposition remains unclear. METHODS: This study investigated IMF deposition in the longissimus dorsi muscle of one- and two-year-old Qinchuan and Wagyu cattle through histological examination and fat content measurement. Based on transcriptome sequencing data of intramuscular fat tissue, differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify lncRNAs associated with IMF deposition. The effects of a key candidate lncRNA on the adipogenic differentiation of cattle intramuscular preadipocytes were further examined. RESULTS: Results showed that Wagyu cattle exhibited stronger IMF deposition capacity than Qinchuan cattle across all age groups, with IMF content increasing with age in both breeds. We identified 7,910 lncRNAs from intramuscular fat tissue transcriptome data, including 6,455 novel lncRNAs. Through integrated differential expression analysis and WGCNA, 88 lncRNAs closely associated with IMF deposition were screened from two-year-old Qinchuan and Wagyu cattle. Notably, lnc11599 was significantly upregulated in Qinchuan cattle intramuscular fat tissue, but its expression decreased during intramuscular preadipocyte differentiation. Functional experiments demonstrated that lnc11599 knockdown enhanced adipogenic differentiation capacity, manifested as a highly significant increase in lipid accumulation, upregulation of key adipogenic genes at the mRNA level, together with increases in total fatty acid content and unsaturated fatty acid proportion. CONCLUSIONS: This study established the lncRNA expression profiles in intramuscular fat tissue of Qinchuan and Wagyu cattle across different developmental stages, and demonstrated that lnc11599 acts as a negative regulator of intramuscular fat deposition. These findings provide new directions for elucidating the mechanisms of cattle IMF deposition and offer potential targets for genetic improvement of beef quality.

Animals↗

PubMed2026

Metabolic-cell-death gene trio predicts survival and cuproptosis sensitivity in colorectal cancer.

BACKGROUND: Metabolic cell death (MCD) modulates colorectal cancer (CRC) progression, yet its prognostic value remains unexplored. We aimed to build an MCD-centred gene signature for outcome prediction and precision therapy. METHODS: Transcriptomes of 1,174 CRC patients were integrated. Weighted gene co-expression network analysis, differential expressions and least absolute shrinkage and selection operator (LASSO) + random survival forest were successively applied to derive a three-gene (CDKN2A/MPC1/AHCY) risk model. Functional, immune-infiltration, drug-sensitivity and genomic analyses were performed, followed by validation in fresh clinical specimens and cell lines. RESULTS: Integrative metabolic-death transcriptomics identified CDKN2A, MPC1 and AHCY as the hub drivers of CRC. Their three-gene signature robustly stratified patients into high- and low-risk subsets [3-year area under the curve (AUC) 0.83-0.85, P<0.001]. High-risk tumors were enriched for extracellular matrix (ECM)-receptor-interaction pathways, displayed abundant myeloid-derived suppressor cell (MDSC) infiltration and were more vulnerable to AZD8186, AZ960 and JAK inhibitors. Guided by these in-silico findings, we functionally confirmed that CDKN2A silencing markedly repressed proliferation, invasion and migration of SW480/HCT116 cells and potentiated cuproptosis via up-regulation of lipoylated DLAT/DLST and CTR1. CONCLUSIONS: We report the first MCD-derived prognostic platform for CRC that simultaneously predicts survival and therapeutic response. Targeting CDKN2A-enhanced cuproptosis represents a promising metabolic-precision strategy for high-risk patients.

Colorectal cancer (CRC)↗

PubMed2026

Decoding age-stratified clinical and molecular heterogeneity in male breast cancer through multiomic profiling.

OBJECTIVE: Age-associated molecular heterogeneity is well described in female breast cancer but remains insufficiently characterized in male breast cancer (MBC). We profiled age-stratified clinical and molecular differences between younger (≤55 years) male breast cancer (YMBC) and older (>55 years) male breast cancer (OMBC). METHODS: We retrospectively analyzed 347 patients with MBC diagnosed at Fudan University Shanghai Cancer Center by integrating clinicopathological data, RNA sequencing, and whole-exome sequencing (WES). Survival, differential expression, and mutational signature analyses were performed. Tumor microenvironment features were inferred using xCell and ESTIMATE, and weighted gene co-expression network analysis (WGCNA) was conducted to identify age-associated co-expression modules. Candidate therapeutics were prioritized using the Genomics of Drug Sensitivity in Cancer (GDSC) resource and evaluated using patient-derived organoids (PDOs). RESULTS: Compared with OMBC, YMBC more frequently had human epidermal growth factor receptor 2 (HER2)-positive status (14.91% vs. 4.02%) and triple-negative tumors (4.92% vs. 1.78%), and had worse 5-year recurrence-free survival (hazard ratio=2.19, P=0.018). Transcriptomic analyses indicated enrichment of neural-related programs and reduced immune-related signaling in YMBC, and xCell/ESTIMATE supported lower immune infiltration. Consistently, WGCNA identified age-associated modules linking neural-related programs with reduced immune infiltration. Immunohistochemistry supported increased perineural invasion and lower CD8+ T cell infiltration in YMBC. GDSC-guided prioritization with PDO testing nominated sepantronium bromide (YM155) as a candidate vulnerability in YMBC. WES showed a higher NBPF10 mutation frequency in YMBC (54.5% vs. 14.3%, P<0.05). CONCLUSIONS: Integrated multi-omics profiling revealed age-stratified clinical and molecular heterogeneity in MBC. YMBC patients demonstrated inferior recurrence-free survival, neural signaling enrichment, an immune-cold microenvironment, and enriched NBPF10 mutations. These findings support age as a meaningful stratification variable in MBC risk assessment and treatment planning, and highlight the need for caution when considering treatment de-escalation in younger patients, while nominating YM155 as a candidate agent for prospective evaluation.

Male breast cancer↗

PubMed2026

Genome-wide cis-expression Quantitative Trait Loci (eQTL) and transcriptomic signals reveal distinct molecular regulation across correlated feed efficiency traits.

INTRODUCTION: Feed efficiency (FE) is a complex trait which determines livestock production profitability, yet the molecular mechanisms behind it remain unclear. This study investigated the blood transcriptomic profile of lambs, alongside genotype data with the aim to uncover the genetic basis of FE traits such as absolute dry matter intake (DMIabsolute), DMI adjusted for body size (DMIadjusted), average daily live weight gain (ADG), and residual feed intake (RFI). MATERIALS AND METHODS: Bulk RNA-Seq and genotype data were analysed using three complementary approaches: differential gene expression (DGE) analysis, weighted gene co-expression network analysis (WGCNA), and cis-expression Quantitative Trait Loci (cis-eQTL) mapping. These methods were used independently to identify genes and regulatory networks associated with FE traits and to investigate evidence supporting multi-trait candidate gene selection. RESULTS: DGE analysis revealed 2, 24, 85 and 4 differentially expressed genes for DMIabsolute, DMIadjusted, ADG, and RFI (Padjusted < 0.05), functionally enriched in sensory perception, ATP-dependent chromatin remodeling, Notch signaling and immune response pathways. 9 gene modules significantly associated with the FE traits (P ≤ 0.05) with correlations ranging from r = -0.56 to 0.49, were identified using WGCNA. Single nucleotide polymorphism (SNP)-level cis-eQTL analysis identified 93 eSNPs associated with 74 genes (false discovery rate (FDR) < 0.05), while permutation-derived gene level analysis identified 280 eGenes (FDR < 0.2, empirical P < 0.03). Across the three analyses, applying thresholds of DGE (Padjusted < 0.05), WGCNA (correlation, P ≤ 0.05), and cis-eQTL gene-level significance (empirical P < 0.05), multiple overlapping genes were identified including DNMT3A, KANSL1, NCOR1 for DMIadjusted, ACOX2, FANCF, CIMIP2B, LOC101115106, ARMH2, LOC132657496 for ADG, and LOC114114576 for RFI representing regulators of variations in FE. DISCUSSION: The integration of DGE, WGCNA, and cis-eQTL analyses identified key genes and regulatory mechanisms associated with variation in FE traits. These results highlight that integrated multi-trait candidate gene identification approaches can reveal key genes that lower feed intake while maintaining animal growth, supporting breeding strategies aimed at improving efficiency and long-term economic sustainability in sheep.

average daily gain (ADG)↗

PubMed2026

S100P as a Shared Biomarker in Inflammatory Bowel Disease, Colorectal Cancer, and Pancreatic Adenocarcinoma: An Integrated Transcriptomic Analysis.

Inflammatory bowel disease (IBD) is associated with an increased risk of colorectal cancer (CRC) and pancreatic adenocarcinoma (PAAD), yet the molecular features shared among these diseases remain incompletely understood. This study aimed to identify common genes and biological pathways associated with IBD, CRC, and PAAD through integrated transcriptomic analysis and experimental validation. Gene expression datasets for IBD, CRC, and PAAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Weighted gene co-expression network analysis and differential expression analysis were performed to identify disease-associated and shared genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (analyses were used to explore enriched biological functions and pathways. Immune cell infiltration was evaluated using Cell-type Identification by Estimating Relative Subsets of RNA Transcripts. Receiver operating characteristic analysis was performed to assess the diagnostic performance of common genes. Single-cell RNA sequencing analysis was conducted to examine the cellular distribution of S100P. In addition, the effects of S100P downregulation were evaluated in lipopolysaccharide (LPS)-stimulated colonic epithelial cells. A total of 162 disease-associated genes and four common genes were identified. Functional enrichment analyses indicated significant enrichment of immune- and inflammation-related pathways, including the interleukin-17 signaling pathway. Immune infiltration analysis revealed similar trends in several immune cell populations across IBD, CRC, and PAAD. Single-cell analysis showed elevated S100P expression in epithelial cells from all three diseases. Downregulation of S100P restored the proliferative capacity of LPS-stimulated colonic epithelial cells and reduced inflammatory cytokine expression. Integrated transcriptomic analysis identified S100P as a biomarker associated with IBD, CRC, and PAAD and highlighted shared immune-related features across these diseases.

Humans↗

PubMed2026

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3 : 1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC > 0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans↗

PubMed2026

Construction of molecular signatures based on the co-expression network of NECSO-related gene TRPM4 and its prognostic value in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) demonstrates significant prognostic variability that is not entirely accounted for by traditional staging systems. Necrosis by sodium overload (NECSO) is an emerging programmed cell death pathway, but its clinical relevance in HCC remains undefined. Therefore, this study aimed to identify TRPM4-associated core genes, develop and validate a prognostic signature, and investigate its relationship with the tumor immune microenvironment, tumor mutational burden, and single-cell expression patterns in HCC. METHODS: We integrated transcriptomic, clinical, and mutational datasets from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) (n=421) and Gene Expression Omnibus (GEO) cohorts (n=115) to identify genes co-expressed with TRPM4-a key NECSO mediator-and those differentially expressed in HCC. A prognostic signature was developed using least absolute shrinkage and selection operator (LASSO)-Cox regression and validated through survival analysis, time-dependent receiver operating characteristic (ROC) curves, and multivariate Cox regression analysis. The immune landscape was characterized using CIBERSORT, somatic mutation data were used to calculate tumor mutational burden (TMB) and assess its correlation with the risk score, and single-cell RNA sequencing (scRNA-seq) resolved cell-type-specific expression patterns. RESULTS: From 294 TRPM4-associated core genes, we identified an 11-gene signature (BRSK1, MMP1, GRIN2D, GP6, MYOM2, N4BP3, CCDC112, TSEN54, MAP3K9, SPP1, B3GNT4) that independently predicted overall survival (OS) (hazard ratio =5.419, P<0.001) with areas under the curve (AUCs) of 0.779, 0.693, and 0.701 at 1, 3, and 5 years. These values were superior or comparable to conventional clinicopathologic variables after direct comparison. High-risk patients exhibited an immunosuppressive microenvironment, characterized by enrichment of M0 macrophage, a higher M2/M1 ratio (P<0.001) and distinct immune checkpoint profiles. When integrated with TMB, the prognostic stratification was further refined: high-TMB/high-risk patients had poorest outcomes (median OS, 15.3 months), while low-TMB/low-risk patients had the most favorable survival (median OS, 68.7 months). Single-cell analysis revealed that MMP1 was induced in cancer-associated fibroblasts (CAFs) and SPP1 was downregulated in macrophages, single-cell risk scores confirmed TAFs and macrophages as the main contributors to the prognostic model. CONCLUSIONS: The TRPM4-centered 11-gene signature provides robust and independent prognostic stratification in HCC by integrating immune, mutational, and single-cell features. This signature serves as a potential tool for prognostic evaluation and may help inform immunotherapeutic strategies for HCC.

Hepatocellular carcinoma (HCC)↗

PubMed2026

Context matters: coordinated transcriptional regulation and root plasticity under multinutrient conditions.

Plants often encounter simultaneous imbalances in multiple nutrients, but the regulatory logic coordinating their responses remains poorly understood. We aimed to uncover shared transcriptional programs and regulatory nodes underpinning multinutrient adaptation in Arabidopsis thaliana roots. We analyzed publicly available RNA-seq datasets spanning 15 nutrient and beneficial element conditions using differential expression, co-expression network (WGCNA), and gene regulatory network analysis. Selected transcription factors (TFs) were validated via root phenotyping, suberin staining, and ionomic profiling under two-nutrient stress conditions. We identified a core set of 2050 genes responsive to multiple nutrient treatments, enriched for suberin biosynthesis, and structured into modular co-expression clusters. Eight prioritized candidate TFs (ARR10, GBF3, HHO5, NAC32, NF-YA3, NF-YB2, SARD1, and WRKY33) were shown to modulate root system architecture under specific nutrient combinations. WRKY33 and NF-YB2, in particular, regulated nutrient-responsive suberin deposition and ionomic plasticity. These findings reveal suberin remodeling as a shared downstream process in multinutrient responses and suggest that plasticity is not a fixed trait but a modular, polygenic, and context-dependent outcome. Repurposed TFs with pleiotropic functions coordinate structural and physiological traits, providing regulatory entry points for improving nutrient resilience.

Plant Roots↗

PubMed2026

Evidence for dual pathways of Tc1/mariner domestication in Drosophila.

BACKGROUND: The domestication of transposable elements is a key source of evolutionary innovation, yet the pathways by which their functional modules are repurposed by the host remain poorly understood. The Tc1/mariner superfamily is a widespread group of DNA transposons, but the prevalence and patterns of their domestication are underexplored. RESULTS: We performed a systematic genomic screen across 43 drosophilid species using stringent criteria for molecular domestication. This analysis identified five high-confidence, evolutionarily conserved genes derived from Tc1/mariner transposases. Phylogenetic and structural analyses suggest domestication via two distinct molecular pathways: co-option of the DNA-binding module and co-option of the catalytic domain. The DNA-binding module pathway includes CG4570, the previously known genes cag and toy (the latter fused with a homeodomain), and a lineage-restricted gene in the Drosophila obscura group that exhibits signatures of recent domestication. In contrast, the catalytic domain pathway is represented solely by CG14478. Structural modeling reveals that CG14478 protein preserves a canonical DDE endonuclease fold. Co-expression network analysis suggests potential cellular roles of these genes: CG14478 is linked to RNA/chromatin-related processes, CG4570 to cell cycle/chromosome functions, cag to ciliary and nuclear functions, and toy to neuronal development. CONCLUSIONS: This study establishes a stringent framework for identifying domesticated TEs, demonstrating that Tc1/mariner elements are co-opted via two distinct pathways: retention of either catalytic or DNA-binding modules. Our findings suggest that domestication is a dynamic continuum, ranging from recent, lineage-specific events to ancient, conserved genes, and underscore how genomic conflict with TEs can drive eukaryotic evolution and regulatory complexity.

Animals↗

PubMed2026

Network based approach identifies miR-145-3p as a central regulatory hub associated to the progression from localized to metastatic medullary thyroid carcinoma.

Medullary thyroid carcinoma (MTC) is a neuroendocrine tumor originating from calcitonin producing C-cells and accounts for 1-5% of thyroid cancers. Total thyroidectomy is curative in localized disease (N0), whereas lymph node metastases (N1) are associated with poorer prognosis. However, the molecular mechanisms driving the metastatic shift remain poorly understood. This study aimed to identify miRNA features linked to metastatic spread in MTC, focusing on the transition from N0 to N1. Co-expression networks were constructed for N0 and N1 tumors, and differential connectivity analysis was used to identify key miRNAs acting as regulatory hubs. Functional annotation of their target genes was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Reactome pathway analyses. Validation experiments were carried out in MTC cells to evaluate the effects of selected miRNAs on cell proliferation, survival, and MAPK pathway activation. Network analysis revealed distinct miRNA co-expression patterns between N0 and N1 tumors. Differential network analysis highlighted miR-145-3p as a central regulatory hub, exhibiting 29 altered co-expression changes and a marked loss of connectivity in N1. Target enrichment identified 59 validated genes, including key oncogenic drivers such as MYC, PTEN, BCL2, PIK3CA, AKT1, and MAPK7. In MTC cells, simultaneous inhibition of miR-145-3p together with its top co-expressed miRNAs increased proliferation and survival, and enhanced ERK phosphorylation, indicating MAPK pathway activation and a shift toward a more aggressive phenotype. In conclusion, this study identifies a miRNA regulatory hub centered on miR-145-3p that is associated with metastatic progression and highlights the value of network-based approaches in uncovering mechanisms of cancer dissemination. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

MAPK signaling↗

PubMed2026

Temporal DIA-MS proteomics reveals coordinated metabolic reprogramming associated with oil accumulation in oil palm mesocarp.

Oil palm (Elaeis guineensis Jacq.) is the most productive oil-bearing crop globally, yet the molecular basis of mesocarp development and lipid accumulation remains poorly understood. Ultra-deep data-independent acquisition mass spectrometry (DIA-MS) was applied to characterize proteome dynamics in two contrasting genotypes, seedless (KS) and thin-shelled (TS), across five developmental stages (P1-P5) spanning fruit development to mature oil accumulation. Phenotypic analysis revealed higher mesocarp proportion and oil content in KS during late maturation. A total of 137,615 peptides corresponding to 12,163 protein groups were identified, providing a temporal proteomic landscape of mesocarp development. Multivariate analysis indicated that developmental progression was the primary contributor to proteomic variation, whereas genotype-associated differences increased during lipid accumulation. Differentially abundant proteins were mainly associated with carbohydrate metabolism, photosynthesis, proteolysis, antioxidant responses, and lipid biosynthesis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and KOG analyses suggested extensive remodeling of metabolic networks, including developmental changes in photosynthesis-associated proteins and increased representation of lipid-associated pathways during maturation. Weighted protein co-expression network analysis identified 17 modules associated with developmental progression and lipid accumulation, highlighting candidate proteins involved in carbon metabolism, energy production, and cellular protection. Genes encoding selected hub protein candidates were further examined by RT-qPCR. Biochemical analyses supported these proteomic patterns, showing increased acetyl-CoA availability, enhanced antioxidant enzyme activities (SOD, CAT, APX, and GR), improved GSH/GSSG balance, and reduced oxidative damage in KS. Together, these findings provide a temporal proteomic and biochemical framework for understanding genotype-associated differences in oil accumulation and identify candidate metabolic networks for functional studies.

Carbon metabolism↗

PubMed2026

Integrative multi-omics reveals a fibroblast-centered, ZFHX3-prioritized regulatory framework linking sick sinus syndrome and atrial fibrillation.

OBJECTIVE: To define shared genetic and multi-scale mechanisms underlying comorbidity between sick sinus syndrome (SSS) and atrial fibrillation (AF). METHODS: We integrated genome-wide association study (GWAS) summary statistics for SSS and AF with Genotype-Tissue Expression (GTEx) expression and splicing quantitative trait loci (eQTL/sQTL), atrial single-cell and spatial transcriptomics, and epigenomics. We identified trait-relevant tissues and pathways, prioritized shared cell types, quantified genome-wide and local genetic sharing, detected joint loci by cross-trait meta-analysis, and linked loci to regulatory programs via colocalization and cell-prioritized co-expression networks. RESULTS: Both traits showed strongest enrichment in cardiac tissue, especially Heart Atrial Appendage. Fibroblasts from the left atrial appendage were consistently prioritized as the key shared cell population. SSS and AF displayed significant positive genome-wide genetic correlation, with multiple locally shared regions, including six major loci. Cross-trait meta-analysis identified eight joint-phenotype SNPs implicating four susceptibility genes. ZFHX3 was the leading tissue-cell-gene candidate, acting as a hub in fibroblast co-expression modules and colocalizing with cardiac regulatory signals. CONCLUSION: Shared liability for SSS and AF is highly tissue- and cell-specific, converging on regulatory networks in atrial appendage fibroblasts, with ZFHX3 serving as a central mechanistic and biomarker node.

Humans↗

PubMed2026

MetaCCI: meta cell-cell interaction inference and its application to CCIs characteristics of MDS.

MOTIVATION: Cell-cell interactions (CCIs) are fundamental to multicellular organisms and play crucial roles in diverse biological processes and disease mechanisms. Understanding CCIs is vital for deciphering disease pathogenesis and developing therapeutic strategies. Although numerous computational methods have been developed to infer CCIs from complex biological data, most existing approaches rely primarily on single-gene expression levels and ligand-receptor databases, often failing to capture the nuanced network-wide changes characteristic of disease states. RESULT: We propose MetaCCI, a novel computational strategy that integrates meta-information into CCI inference by extending the traditional gene expression-based analysis to a gene regulatory network framework. MetaCCI meticulously combines established ligand-receptor pairs with quantitative insights into gene behavior within complex gene networks, enabling the precise extraction of relevant targets for CCI inference. Subsequently, CCI inference was performed using an eigen cell co-expression network, providing a more holistic view of cell-cell communication. Monte Carlo simulations demonstrated that MetaCCI consistently outperforms existing methods in CCI inference. We applied MetaCCI to characterize cell-cell communication in Myelodysplastic Syndromes (MDS). Our results identified distinct interaction patterns in MDS compared with normal cell populations, specifically highlighting the loss of CCIs between "Dendritic cells and Hematopoietic precursor cells" and between "Dendritic cells and Hematopoietic multipotent progenitor cells" as characteristic features of MDS. Furthermore, FABP5, CD63, and HMGB1 were identified as MDS-specific markers. These findings suggest that diminished CCIs involving dendritic cells, hematopoietic precursor cells, and multipotent progenitor cells are pivotal to MDS pathogenesis. AVAILABILITY AND IMPLEMENTATION: The MetaCCI software is freely available at https://github.com/HeewonGitHub/MetaCCI. An archived version of the software and example datasets used in this study is available at Zenodo: https://doi.org/10.5281/zenodo.20101527.

Myelodysplastic Syndromes↗

PubMed2026

Quantum computing-assisted validation of a conserved macrophage suppression module shared by ASFV and PEDV.

BACKGROUND: African swine fever virus (ASFV) and porcine epidemic diarrhea virus (PEDV) differ in viral biology and cellular tropism, yet both pathogens suppress macrophage-mediated immune responses in pigs. OBJECTIVE: To identify a conserved macrophage suppression module shared by ASFV and PEDV and evaluate quantum computing as an independent framework for biological network validation. METHODS: Integrated analysis of publicly available GEO datasets (GSE231435 for ASFV and GSE306895) identified 471 shared downregulated genes. A network- and multi-omics-informed 20-gene core was selected and encoded as a 20-qubit modularity-based Quadratic Unconstrained Binary Optimization (QUBO) problem. Community detection was benchmarked using the Quantum Approximate Optimization Algorithm (QAOA) on both the IBM Quantum Aer simulator and the 156-qubit IBM Fez (Heron r2) quantum processor and compared with brute-force enumeration and simulated annealing. RESULTS: A conserved macrophage suppression module shared by ASFV and PEDV was identified. For the STRING protein-protein interaction network, QAOA at circuit depth p = 3 reproduced the brute-force optimum with an approximation ratio of 1.000. In contrast, performance progressively declined in the denser co-expression network with increasing circuit depth, consistent with noise accumulation under current Noisy Intermediate-Scale Quantum (NISQ) conditions. Multi-run consensus analysis identified stable hub genes, including MMP9 and SLA-DOA, as well as genes exhibiting variable community assignments. CONCLUSION: These findings reveal a conserved macrophage suppression module shared between ASFV and PEDV and demonstrate that quantum computing can serve as an independent validation framework for biologically meaningful host-response networks. Network topology emerged as a key determinant of QAOA performance on real NISQ hardware.

Animals↗

PubMed2026

Genes associated with translation and oxidative phosphorylation as components of the translational response in nodulated and water-restricted soybean.

BACKGROUND: Soybean primarily acquires nitrogen through symbiosis with nitrogen-fixing bacteria. Water deficit (WD) is a major stress limiting crop yield. Nodulation may enhance drought tolerance in legumes by modulating nitrogen and hormone metabolism, osmotic adjustment, and antioxidant defenses; however, the molecular basis underlying the differential WD responses between N-fix and N-fed plants remain unclear. Translational control of gene expression is a key regulatory mechanism during stress. RESULTS: We compared the transcriptome and translatome of soybean roots from N-fix and N-fed plants exposed to WD across four combined treatments. N-fix plants under WD exhibited more complex responses in terms of total differentially expressed genes (DEGs) compared to N-fed plants. This increased complexity was also evident among translationally regulated DEGs and differentially expressed transcription factors, whose involvement in WD responses of N-fix plants is novel. Co-expression network analysis identified modules associated with core biological processes encompassing nodulation, WD, and notably, their interplay was particularly prominent in Module 1, which was enriched in genes related to ribosomal protein synthesis and oxidative phosphorylation (OXPHOS). Guilt-by-Association analysis enabled the prediction of novel functions for differentially expressed, uncharacterized hub genes related to stress and/or nodulation responses. CONCLUSIONS: Translational regulation of genes involved in OXPHOS and translation initiation emerged as a central response in N-fix plants under WD. These findings reveal distinct molecular adaptations in N-fix soybean roots facing WD and highlight translational control as a key regulatory layer. We also identified promising candidate genes-including transcription factors and uncharacterized hub genes under translational regulation-that represent potential targets for improving drought tolerance in legumes once validated functionally.

Glycine max↗

PubMed2026

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks↗

PubMed2026

Unveiling the molecular basis of gonadal development: Multi-omics uncovers sex-related genes and steroid pathways in Sinonovacula constricta.

The razor clam Sinonovacula constricta is an economically important cultured mollusk in China, but the molecular mechanism of its gonadal development and sexual differentiation remains unclear. This study integrated gonadal transcriptomic, proteomic, and metabolomic analysis to identify key sex-related molecules. Transcriptome analysis identified 2795 DELs and 6497 DEGs between sexes, including the sex-related genes Fem-1b, Fem-1c, GUCY1B2 and FAT4, as well as a regulatory network of 39 lncRNA-mRNA pairs involving Tektin-4, Ropporin-1, Histone H1, and FoxN4. Proteomic analysis revealed 3217 DEPs: Tektin family members, Ropporin-1 and Tssk proteins were upregulated in the testis, while histone H1 and FAT4 were upregulated in the ovary. Metabolomic analysis detected 409 DEMs, with uridine identified as a potential sex differential marker (upregulated in the ovary), and 23 gonadal development-related DEMs showed sex-specific upregulation. Integrative transcriptome-proteome analysis identified 1543 co-expressed DEGs/DEPs enriched in nucleosome assembly, oxidative phosphorylation, and carbon metabolism, including key sex-related genes AKAP14, Tektin/Tssk families, Histone H1, and FAT4. Transcriptome-metabolome integration identified 32 shared KEGG pathways (e.g., biosynthesis of unsaturated fatty acids, pyrimidine metabolism), while proteome-metabolome integration revealed 5 (positive ion) and 6 (negative ion) co-enriched pathways, with alanine, aspartate and glutamate metabolism and oxidative phosphorylation being functionally relevant to gonadal development. Collectively, these results reveal the molecular basis of gonadal development, highlight critical sex-related genes and steroid metabolic pathways, and provide valuable resources for future reproduction and breeding in S. constricta.

Animals↗

PubMed2026

Natural leaf shape variation reveals diverse transcriptional targets of GmJAG1 during soybean leaf development.

The JAGGED transcription factor family regulates lateral organ development across angiosperms. In soybean (Glycine max Merr.), a D9H mutation in the EAR repression motif of GmJAG1 causes a narrow-leaflet phenotype and explains over 70% of phenotypic variance in leaf shape. Because this mutation does not affect the zinc finger DNA-binding domain, both alleles bind identical targets but differ in repressor recruitment. Previous studies mapped GmJAG1 binding sites, but the functional targets controlling leaf morphology are uncharacterized. Here, we used comparative transcriptomics across four soybean genotypes with contrasting leaf shape, spanning a developmental time series from shoot apex to mature leaf, and identified 1567 putative candidate target genes. GmJAG1 expression was confined to the shoot apex, yet 99.1% of candidate targets maintained differential expression throughout development. We found that neither Kip-Related Protein (KRP) cell cycle inhibitors nor Cyclin-Dependent Kinases (CDKs) showed differential expression despite binding evidence in Arabidopsis. However, D-type cyclins were upregulated in narrow-leaf genotypes suggesting that soybean GmJAG1 acts through cyclin-mediated rather than KRP-mediated cell cycle regulation described in Arabidopsis- a divergence in regulatory logic between the two species. Pathway analysis revealed enrichment of auxin (1.8-fold, P = 0.02) and salicylic acid (fourfold, P = 0.016) genes among JAG1D9H targets. Filtering by differential expression, binding data, phenotype correlation, and co-expression network membership identified 79 high-confidence targets, including orthologs of NPH3 (phototropin-mediated leaf flattening), MIK2 (cell wall integrity sensing), RD22 (ABA-responsive stress signaling), and SCL23 (GRAS transcription factor in bundle sheath development). These candidates provide targets for functional validation and breeding in legumes.

Glycine max↗