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PubMed2026

Mapping the Immune cell-specific gene regulatory network in bipolar disorder: A framework from scTWMR to exploratory drug-target annotation.

BACKGROUND: Although the involvement of the immune system in the genetic susceptibility of bipolar disorder (BD) is widely acknowledged, the causal relationship between gene expression in specific immune cell subtypes and BD requires systematic elucidation. METHODS: We implemented an analytical framework integrating single-cell transcriptome-wide Mendelian randomization (scTWMR) with colocalization analysis. This approach utilized cis-expression quantitative trait loci (cis-eQTLs) derived from 14 distinct immune cell types as instrumental variables to interrogate BD genome-wide association study (GWAS) summary statistics (comprising 41,917 cases and 371,549 controls). Subsequent investigations encompassed functional enrichment analysis, protein-protein interaction (PPI) network construction, phenome-wide association study (PheWAS), and performed an exploratory drug-target annotation. RESULTS: Our analysis identified 33 gene-immune cell associations. Colocalization analysis provided robust evidence (PPH4 > 90%) for shared causal variants implicating the MAD1L1, APOM, and NFKBIL1 loci. Significantly enriched biological pathways included cell cycle regulation, circadian rhythm entrainment, and neuroinflammation. The PPI network revealed a core regulatory module centered on histone-encoding and immune-related genes. Exploratory drug-target annotation nominated compounds for further investigation for compounds targeting APOM, TMEM258, and NFKBIL1. CONCLUSION: This study systematically delineates a genetically supported regulatory network of immune cell-specific gene expression in BD, predominantly implicating CD8⁺ effector T cells, plasma cells, and B cells. The findings corroborate established pathological pathways while uncovering novel cell type-specific therapeutic targets, thereby providing a genetic framework for prioritizing candidate targets for future investigation.

Bipolar disorder↗

PubMed2026

Cell-specific DNA methylation in human alpha and beta cells regulates gene expression in type 2 diabetes.

Epigenome-wide studies of pancreatic islets provide valuable insights into type 2 diabetes (T2D) but lack methylomes from individual cell types. Here we show changes to alpha and beta cell-specific methylomes and transcriptomes from people with or without T2D, using whole-genome bisulfite sequencing and RNA sequencing. We discover 22,544 differentially methylated regions annotated to 7,975 genes in alpha versus beta cells, such as INS, GCG, PDX1 and PCSK1, with ~50% showing differential expression. CRISPR-dCas9-DNMT3A-based epigenetic editing increases INS and TH DNA methylation, while CRISPR-dCas9-TET1-based editing decreases GCG methylation, each altering INS, TH or GCG expression and content in beta cells. Pre-T2D/T2D-associated differentially methylated regions in alpha and beta cells overlap 12-18% of T2D-associated genome-wide association study candidates. Additionally, ONECUT2 is epigenetically upregulated in beta cells from people with pre-T2D/T2D and elevated in male Goto-Kakizaki rat islets. ONECUT2 overexpression in beta cells/islets downregulates gene sets impacting insulin secretion and glucose homeostasis, and reduces mitochondrial activity, ATP/ADP ratio and insulin secretion. We also provide 'alpha-beta-methylome' ( https://alpha-beta-methylome.serve.scilifelab.se/app/alpha-beta-methylome/ ), a resource exploring T2D, age and sex associations on methylation, highlighting cell-specific epigenetic regulation and dysfunctions contributing to T2D.

Humans↗

PubMed2026

Identification of the R2R3-MYB gene family in wild jujube (Ziziphus jujuba var. spinosa) and analysis of its expression under drought stress.

BACKGROUND: R2R3-MYB gene family serves as a pivotal regulatory factor in plant growth, development, and responses to environmental stresses. To investigate its function in the drought stress response of wild jujube (Ziziphus jujuba Mill. var. spinosa), a typical eco-economic forest species, this study performed genome-wide identification and relevant analyses of R2R3-MYB genes. RESULTS: A total of 91 R2R3-MYB genes (designated as ZjMYB1 to ZjMYB91) were identified, which were unevenly distributed across 12 chromosomes. These genes mainly encode hydrophilic and unstable proteins, 97.8% of which are localized in the nucleus. Phylogenetic analysis classified these genes into 25 clades, showing evolutionary conservation and species-specific divergence with the R2R3-MYB protein family. The expansion of the ZjMYB family is mainly characterized by segmental duplication, and all duplicated gene pairs have undergone purifying selection. ZjMYBs are widely involved in plant growth and development as well as abiotic stress responses, with the highest expression level particularly in leaf tissues; a total of 13 genes were specifically annotated as water deficit response-related genes in drought stress and abscisic acid (ABA) signaling pathways. Integrating the above analyses together with transcriptome data and qRT-PCR validation results revealed that ZjMYB5, ZjMYB53, ZjMYB57 and ZjMYB85 function as core drought-responsive genes, which display both tissue-specific and time-dependent expression patterns under drought stress. CONCLUSIONS: This study systematically elucidated the functional characteristics and regulatory network of the R2R3-MYB gene family in wild jujube, providing critical genetic resources and a theoretical basis for dissecting the molecular mechanisms underlying drought tolerance in wild jujube and breeding drought-resistant cultivars.

Ziziphus↗

PubMed2024

Multi-omics association study of hexadecane degradation in haloarchaeal strain Halogranum rubrum RO2-11.

Haloarchaea with the capacity to degrade alkanes is promising to deal with petroleum pollution in hypersaline environments. However, only a limited number of haloarchaeal species are investigated, and their pathway and mechanism for alkane degradation remain unclear. In this study, Halogranum rubrum RO2-11, a haloarchaeal strain, verified the ability to degrade kerosene and hexadecane in 184 g/L NaCl, with 53% and 52% degradation rates after 9 and 4 days, respectively. Genome sequencing and gene annotation indicated that strain RO2-11 possesses a complete potential alkane-degrading pathway, of which alkane hydroxylases may include CYP450, AlmA, and LadA. Transcriptome and metabolome analyses revealed that the upregulation of related genes in TCA cycle, lysine biosynthesis, and acetylation may help improve hexadecane degradation. Additionally, an alternative degrading pathway of hexadecane based on dual-terminal β-oxidation may occur in strain RO2-11. It is likely to be the first report of alkane degradation by the genus Halogranum, which may be helpful for applications of oil-pollution bioremediation under high-salt conditions.

Alkanes↗

PubMed2026

Network methods for diagonal integration of unpaired single-cell multiomics data: a review.

MOTIVATION: Advances in single-cell sequencing have enabled multiomics profiling at unprecedented resolution; however, mass spectrometry-based single-cell proteomics (scMS) remains inherently destructive, precluding simultaneous transcriptomic capture. Unlike antibody-based methods such as CITE-seq, which permit paired profiling but are restricted to targeted protein panels, scMS provides unbiased, genome-scale coverage of the intracellular proteome yet necessitates post hoc integration of unpaired datasets. This diagonal integration challenge, where transcriptomes and proteomes are measured in separate cells lacking shared anchors, remains underserved by existing reviews, which focus predominantly on vertical integration strategies enabled by non-destructive assays. RESULTS: We survey the complete computational pipeline for constructing mechanistic proteogenomic networks from unpaired single-cell data, covering: (i) unimodal network inference such as knowledge-based approaches, probabilistic graphical models, temporal directionality inference, and generative and foundation model strategies that establish the transcriptomic scaffold; (ii) cross-modal integration architectures such as network propagation, graph neural networks (scMRDR, scmFormer, scCotag), and consensus frameworks designed explicitly for the unpaired proteomics setting; and (iii) benchmarking paradigms spanning network reconstruction (BEELINE, GRETA, CausalBench) and multi-task integration evaluation (scMultiBench, SCMMIB), with guidance on metric selection under network sparsity and class imbalance. We identify three principal axes of future development: generative proteomic translation from transcriptomic precursors, inductive prior embedding in next-generation architectures, and perturbation-based causal benchmarking. AVAILABILITY AND IMPLEMENTATION: This is a review article; no novel software is distributed. A curated benchmark resource table, methods starter guide, and per-method bottleneck annotations are provided in the Supplementary Material.

Multiomics↗

PubMed2026

Association of MPO Expression with the Immune Microenvironment in Breast Cancer: Insights from Bioinformatics and Single-Cell Analyses.

Breast cancer remains a major cause of cancer-related mortality, and exploratory computational workflows can help prioritize immune-associated markers for further investigation. Here, we used the cancer genome atlas breast invasive carcinoma (TCGA-BRCA) bulk transcriptomic data and the public single-cell dataset GSE161529 to examine associations between myeloperoxidase (MPO) expression, clinical outcomes, immune infiltration, methylation, upstream-regulator annotations, single-cell expression patterns, virtual knockdown sensitivity outputs, drug-gene interaction retrieval, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) annotation. MPO expression was lower in breast cancer tissues than in adjacent non-tumor tissues. Higher MPO expression was associated with a longer progression-free interval, whereas its associations with overall survival and disease-specific survival were not statistically significant. Receiver operating characteristic (ROC) analysis suggested tumor-normal separation within the analyzed public dataset, but this should not be interpreted as clinical diagnostic validation. Immune deconvolution and enrichment analyses indicated that MPO expression mainly tracked with immune- and myeloid-related transcriptional features, rather than establishing tumor-intrinsic regulation of the immune microenvironment. At single-cell resolution, the MPO signal was sparse, with only 85 MPO-positive cells detected before k-nearest neighbor (KNN)-based neighborhood expansion. Detectable MPO signal and MPO-associated scores were interpreted cautiously because they may be influenced by sparse expression, cell-type annotation uncertainty, dropout, doublets, or ambient RNA. In silico virtual knockdown suggested candidate immune- and inflammatory-related transcriptional changes, but these results were considered exploratory and require validation. Drug-gene interaction database (DGIdb)-based drug-gene retrieval and ADMET annotation were used only as preliminary chemical annotations and were not interpreted as therapeutic evidence. Overall, this study provides a reproducible in silico workflow for generating hypotheses about MPO-associated immune/myeloid features in breast cancer, which require external cohort validation and experimental confirmation.

Humans↗

PubMed2025

Comparative genomics and transcriptomics of the Spiroplasma glossinidia strain sGff reveal insights into host interaction and trypanosome resistance in Glossina fuscipes fuscipes.

Tsetse (Glossina spp.) are vectors of African trypanosomes, the causative agents of Human and African Animal trypanosomiases, diseases that remain significant medical and socioeconomic challenges in sub-Saharan Africa. In addition to trypanosomes, tsetse harbor both obligate and facultative symbiotic bacteria that can influence vector competence and reproductive biology. One such facultative symbiont, Spiroplasma glossinidia, infects several tsetse species within the Palpalis subgroup. In Glossina fuscipes fuscipes (Gff), the Spiroplasma glossinidia strain sGff induces a trypanosome-refractory phenotype and negatively impacts reproductive fitness by reducing female fecundity. However, the mechanisms behind these Spiroplasma-derived phenotypes remain poorly understood. Here, we report successful in vitro cultivation of sGff and present complete genomes from three sources: in vitro cultured sGff and sGff isolated from both laboratory-maintained and wild-caught (Uganda) Gff flies. Comparative genomic analyses revealed a high degree of similarity in gene content and synteny among these sGff samples, confirming that they represent isolates of the same strain. Phylogenomic analyses placed sGff within the Spiroplasma poulsonii clade. The sGff genome is highly dynamic, containing numerous mobile genetic elements. Additionally, in silico annotations indicate that sGff relies on its host for both lipids and carbohydrates and produces several toxins, all of which could be implicated in the observed trypanosome refractory phenotype. Finally, comparative transcriptomic analysis of sGff from host hemolymph versus in vitro culture provided insights into potential factors relevant to host-symbiont interactions. Our findings provide a foundation for understanding the nutritional dialogue between sGff and its host and identify symbiotic products that may contribute to trypanosome resistance. Furthermore, the establishment of an in vitro culture system for sGff represents a significant resource for future functional studies with potential implications for vector control.

Glossina fuscipes fuscipes↗

PubMed2000

The prostate expression database (PEDB): status and enhancements in 2000.

The Prostate Expression Database (PEDB) is an online resource designed to access and analyze gene expression information derived from the human prostate. PEDB archives >55 000 expressed sequence tags (ESTs) from 43 cDNA libraries in a curated relational database that provides detailed library information including tissue source, library construction methods, sequence diversity and sequence abundance. The differential expression of each EST species can be viewed across all libraries using a Virtual Expression Analysis Tool (VEAT), a graphical user interface written in Java for intra- and inter-library species comparisons. Recent enhancements to PEDB include: (i) the functional categorization of annotated EST assemblies using a classification scheme developed at The Institute for Genome Research; (ii) catalogs of expressed genes in specific prostate tissue sources designated as transcriptomes; and (iii) the addition of prostate proteome information derived from two-dimensional electrophoreses and mass spectrometry of prostate cancer cell lines. PEDB may be accessed via the WWW at http://www.mbt.washington.edu/PEDB/

Databases, Factual↗

PubMed2026

Transcriptome Analysis, Machine Learning, and Experimental Identification of CDK7 Affecting the Progression of Pregnancy-induced Hypertension by Influencing Macrophage Polarization.

INTRODUCTION: Pregnancy-induced hypertension (PIH) is a severe pregnancy complication characterized by placental insufficiency, abnormal vascular remodeling, and immune dysregulation, but personalized therapeutic markers remain unclear. This study aimed to identify key genes and explore immune mechanisms in PIH using transcriptome analysis, machine learning, and experimental validation. METHODS: We analyzed the GSE204835 transcriptomic dataset to screen differentially expressed genes (DEGs) and performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Set Enrichment Analysis (GSEA) for functional annotation. Immune infiltration analysis was also performed to examine the immune landscape in PIH. Least Absolute Shrinkage and Selection Operator (LASSO) regression identified key genes, which were validated in a PIH cell model. Flow cytometry and immunofluorescence assays assessed the effect of CDK7 knockdown on macrophage polarization. RESULTS: A total of 1,598 DEGs (1,123 upregulated, 475 downregulated) were identified. Enrichment analyses highlighted associations with embryonic organ development, oxidative phosphorylation, angiogenesis, and oxidative stress. Immune infiltration analysis revealed altered eosinophil and macrophage polarization in PIH. LASSO regression selected 12 key genes, with CDK7 showing the most significant upregulation in the PIH model. CDK7 knockdown promoted macrophage polarization toward the anti-inflammatory M2 phenotype. DISCUSSION: These findings link CDK7 to immune dysregulation in PIH by modulating macrophage polarization, expanding our understanding of PIH's molecular mechanisms. The study's limitations include reliance on public datasets and in vitro models, warranting in vivo validation. CONCLUSION: CDK7 emerges as a potential therapeutic target for PIH, offering new insights into immunoregulatory interventions for this complication.

Female↗

PubMed2000

[Cancer genome or the development of molecular portraits of tumors].

The rapid development of cancer genomics is due to important progresses in oncogenesis, human genome sequencing and emergence of new technologies in genome and transcriptome analysis. In this context, the aim of the French program 'Cartes d'Identites des Tumeurs--Molecular Portraits of Tumors' is to build a public data base containing a pan genome assessment of genome and transcriptome alterations in the major types of tumors as well as in relevant normal cells and experimental models. Data mining is done in the context of genome annotations and clinical and biological informations attached to the enrolled samples. The goal of the program is to define new tests useful for diagnostic procedures in clinical laboratories and new targets for biological treatments of tumors.

France↗

PubMed2026

Comparative transcriptome analysis provides insights into dorso-ventral color pattern formation of Holothuria edulis.

Animal body color patterns are highly diverse and play critical roles in camouflage, intraspecific communication, and environmental adaptation. Holothuria edulis, an important echinoderm inhabiting tropical waters, exhibits a typical dorsoventral dichromatism. This unique body color difference represents a key phenotypic trait for its habitat adaptation; however, the core differential genes regulating this trait remain to be elucidated. In this study, comparative transcriptome sequencing was performed on the dorsal and ventral body wall tissues of H. edulis, leading to the identification of a number of differentially expressed genes (DEGs), followed by GO functional annotation and KEGG pathway enrichment analysis. GO enrichment analysis indicated that the DEGs were significantly enriched in functional categories such as extracellular region, peptidase inhibitor activity, and tetrapyrrole binding. KEGG pathway analysis further revealed significant enrichment of protein digestion and absorption, the TNF signaling pathway, and cholesterol metabolism. Notably, the pigmentation-related gene FMO2 was highly expressed in the dorsal body wall tissue, whereas cyp1a1, ZIC1, Slc7a11, WNT-1, and ADAMTS20 were highly expressed in the ventral body wall tissue. This study identified DEGs and enriched pathways associated with dorsoventral body color differences in H. edulis, providing new insights into the molecular regulatory mechanisms underlying body color pattern formation. From the perspective of aquaculture applications, body color is one of the important traits affecting the quality and market value of sea cucumber products. Elucidating the molecular mechanisms of body color variation can provide a scientific basis for molecular marker-assisted breeding of superior sea cucumber variety.

Animals↗

PubMed2026

Genus-Wide Pan-Genome Analysis of Populus bZIP Transcription Factors with Reanalysis of Public Salt-Stress Transcriptomes.

Basic leucine zipper (bZIP) transcription factors regulate plant development and stress responses, but their genus-wide diversity in Populus remains unclear. We analyzed 19 Populus genomes and retained 1764 bZIP proteins, including 21 independent new loci and four annotation corrections. Of these, 1762 were assigned to 79 orthologous gene groups (OGGs), comprising 43 core, 20 soft-core, 15 shell and one cloud OGG, of which 59 showed copy-number variation. Phylogenetic analysis assigned 74 representative pangenes to 13 subfamilies, with five remaining unclassified and motif patterns differing among subfamilies. Whole-genome duplication (WGD)/segmental duplication accounted for 81.0% of OGG-assigned proteins and contributed predominantly to the conserved component. Although 72.2% of bZIP proteins overlapped a transposable element within the gene body or 2-kb flanks, this proportion was modestly lower than in matched non-bZIP genes, and copy-number-variable OGGs showed no greater TE coverage than invariant OGGs. Among retained homologous comparisons, 97.6% had Ka/Ks ≤ 1, supporting predominant purifying selection. Across the heterogeneous public salt-stress RNA-seq datasets analyzed, no OGG showed a significant, directionally concordant response in at least two Populus taxa. These results reveal a conserved bZIP framework shaped mainly by ancient duplication alongside variable genomic contexts and transcriptional responses.

Populus↗

PubMed2025

Transcriptome-wide root causal inference.

Root causal genes correspond to the first gene expression levels perturbed during pathogenesis by genetic or non-genetic factors. Targeting root causal genes has the potential to alleviate disease entirely by eliminating pathology near its onset. No existing algorithm has been designed to discover root causal genes from observational data alone. We therefore propose the Transcriptome-Wide Root Causal Inference (TWRCI) algorithm that identifies root causal genes and their causal graph using a combination of genetic variant and unperturbed bulk RNA sequencing data. TWRCI uses a novel competitive regression procedure to annotate cis and trans-genetic variants to the gene expression levels they directly cause. The algorithm simultaneously determines the sequence in which gene expression changes propagate through the system to pinpoint the underlying causal graph and estimate root causal effects. TWRCI outperforms alternative approaches across a diverse group of metrics by directly targeting root causal genes while accounting for distal relations, linkage disequilibrium, patient heterogeneity and widespread pleiotropy. We demonstrate the algorithm by uncovering the root causal mechanisms of two complex diseases, which we confirm by replication using independent genome-wide summary statistics.

Algorithms↗

PubMed2026

Integration of GWAS and WGCNA reveals novel candidate genes for cottonseed oil content in Gossypium hirsutum L.

Genetic improvement of cottonseed oil content represents a crucial strategy for enhancing the comprehensive utilization of cotton. Here, genome-wide association study (GWAS) and weighted gene co-expression network analysis (WGCNA) were integrated to elucidate the genetic control underlying oil content. Phenotypic evaluation of 159 cotton accessions revealed extensive genetic variation, with kernel oil content ranging from 17.81% to 39.50%. Population structure analysis based on 20,213 single nucleotide polymorphisms (SNPs) classified the accessions into two major subpopulations. A total of 18 SNPs exhibited significant associations with oil content, two of which were stably detected across multiple environments using the FarmCPU model. Further haplotype analysis within linkage disequilibrium (LD) blocks confirmed a favorable haplotype on chromosome A05 that was strongly correlated with elevated oil content. Integration of publicly available transcriptome data from 11 ovule developmental stages with WGCNA identified modules significantly linked to oil content. Of the 74 candidate genes within LD intervals, 17 were assigned to WGCNA modules. Functional annotation and enrichment analyses highlighted four putative candidate genes (GH_A05G1503, GH_A05G1506, GH_A05G1531, and GH_A10G2150) involved in oil biosynthesis. These findings deepen our understanding of the genetic mechanisms governing cottonseed oil biosynthesis and lay a foundation for breeding high-oil cotton varieties.

Gossypium↗

PubMed2026

TFPI-high myofibroblast states and a meta-program-related five-gene prognostic signature in breast cancer.

Intratumoral heterogeneity and tumor-microenvironment interactions limit prognostic stratification in breast cancer, but the prognostic relevance and cellular context of recurrent transcriptional meta-programs remain unclear. We aimed to derive a meta-program-related prognostic signature and characterize its component transcripts at single-cell resolution. Six paired institutional tumors and adjacent non-tumor tissues served as a proof-of-concept comparison. Univariable Cox screening and least absolute shrinkage and selection operator Cox regression were used to derive a five-gene score from a prespecified meta-program-related candidate set in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) training cohort; the score was tested internally and assessed in GSE20685 using fixed coefficients and cohort-specific median cutoffs. GSE161529 single-cell transcriptomic data were used to map signature transcripts across 136,526 quality-controlled cells, while donor-aware pseudobulk analysis compared upper- and lower-quartile TFPI expression states in annotated myofibroblasts. The score comprised TCN1, FOXJ1, PIGR, SLAIN1, and TFPI and was associated with overall survival in the training, testing, and external cohorts, with concordance indices of 0.782, 0.756, and 0.721, respectively. TFPI transcripts were detected across endothelial, fibroblast, and myofibroblast compartments. TFPI-high myofibroblasts showed transcriptional enrichment of extracellular matrix and collagen fibril organization, transforming growth factor beta signaling, epithelial-mesenchymal transition, and myogenesis, together with lower oxidative phosphorylation and fatty acid metabolism programs. In bulk TCGA-BRCA tissue, TFPI expression correlated positively with stromal (r = 0.48), immune (r = 0.25), and composite microenvironment scores (r = 0.40; all p < 0.001). These findings identify a hypothesis-generating five-gene bulk-tissue prognostic signature and an expression-associated TFPI-high myofibroblast state but do not establish a discrete lineage, the cellular source of bulk TFPI, a TFPI-dependent mechanism, or clinical utility. Independent prospective cohorts, spatial and protein-level validation, and functional perturbation studies are required.

Journal Article↗

PubMed2025

OLS4: a new Ontology Lookup Service for a growing interdisciplinary knowledge ecosystem.

SUMMARY: The Ontology Lookup Service (OLS) is an open source search engine for ontologies which is used extensively in the bioinformatics and chemistry communities to annotate biological and biomedical data with ontology terms. Recently, there has been a significant increase in the size and complexity of ontologies due to new scales of biological knowledge, such as spatial transcriptomics, new ontology development methodologies, and curation on an increased scale. Existing Web-based tools for ontology browsing such as BioPortal and OntoBee do not support the full range of definitions used by today's ontologies. In order to support the community going forward, we have developed OLS4, implementing the complete OWL2 specification, internationalization support for multiple languages, and a new user interface with UX enhancements such as links out to external databases. OLS4 has replaced OLS3 in production at EMBL-EBI and has a backward compatible API supporting users of OLS3 to transition. AVAILABILITY AND IMPLEMENTATION: The source code of OLS is available at https://github.com/EBISPOT/ols4 and DOI 10.5281/zenodo.14960290 with Apache 2.0 License. A freely available implementation is accessible at https://www.ebi.ac.uk/ols4.

Biological Ontologies↗

PubMed2026

Bacteria and phage consortia modulate cecal SCFA production and host metabolism to enhance feed efficiency in ducks.

BACKGROUND: The gut microbiota influences poultry health, nutrition, feed efficiency (FE), and overall productivity. However, the relationship between gut microbes, including bacteria and phages, and FE in ducks remains underexplored. To address this, we integrated cecal 16S amplicon, metagenome, microbiota-derived short-chain fatty acids (SCFAs) profiling, liver transcriptome, and serum metabolome data to illustrate the contribution of the gut microbiome (bacteria and viruses) to duck FE. RESULTS: We reconstructed viral genomes and prokaryotic metagenome-assembled genomes (MAGs) and annotated their genes using comprehensive databases. Prokaryotic hosts of viruses were also predicted to understand virus-host dynamics within the gut ecosystem. Our results revealed that high-FE ducks have higher concentration of propionate and butyrate in cecum compared with low-FE ducks. The metagenome sequencing revealed distinct cecal microbiota profiles between two groups, with increased relative abundance of representative SCFA producers, especially Paraprevotella sp905215575 and Bacteroides sp944322345, and enhanced SCFA-biosynthesis pathways in high-FE ducks. Virome genome assembly identified two phages encoding auxiliary metabolic genes (AMGs) involved in pyruvate metabolism, enhancing nutrient availability for host bacteria to produce SCFAs (e.g., temperate phage-encoded pyruvate phosphate dikinase) or exploiting host central metabolic pathways for viral replication (e.g., lytic phage-encoded formate C-acetyltransferase). Furthermore, these representative SCFA-producing bacteria and phage consortia were associated with serum metabolites (including L-histidine and 4-hydroxydecanedioylcarnitine) linked to duck FE. CONCLUSION: Collectively, these findings provide novel insights into the gut microbial factors regulating FE in ducks, offering potential strategies to optimize poultry nutrition and productivity. Video Abstract.

Animals↗

PubMed2026

Uncovering hub genes and key pathways responsive to drought stress in rice via meta-analysis of transcriptomic data.

Drought stress presents a formidable threat to global rice cultivation, triggering complex molecular responses that impact plant growth and productivity. To decipher the underlying gene expression dynamics, we performed a comprehensive meta-analysis of transcriptomic datasets derived from drought-tolerant rice genotypes. Via microarray data from three independent studies, we identified a set of consistently expressed differentially expressed genes (DEGs) under drought conditions. Integration of functional annotation tools, including GO and KEGG pathway enrichment, revealed key biological processes and signaling cascades involved in stress mitigation, such as ABA signaling, protein folding, and photosynthesis suppression. Protein-protein interaction (PPI) network construction, followed by hub gene identification via maximal clique centrality (MCC), highlighted pivotal regulators including LEA proteins, dehydrins, HSP70, and several transcription factors. Machine learning approaches further prioritize potential biomarkers, with Random Forest models achieving high classification accuracy and pinpointing key predictive genes. Chromosomal localization analysis provided spatial insights into the distribution of these hub genes, whose expression patterns were further compared against qRT-PCR data from previously published studies. This integrative approach identifies candidate genomic markers and mechanistic insights that may support future breeding strategies for drought-tolerant rice, pending experimental validation.

Cytoscape↗