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Results for “Gene functional annotation”

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PubMed2025

Quantitative proteomic analysis of the brain reveals the potential antidepressant mechanism of Jiawei Danzhi Xiaoyao San in a chronic unpredictable mild stress mouse model of depression.

OBJECTIVE: To reveal the antidepressant mechanisms of Jiawei DanZhiXiaoYaoSan (,JD) in chronic unpredictable mild stress (CUMS)-induced depression in mice. METHODS: Using the CUMS mouse model of depression, the antidepressant effects of JD were assessed using the sucrose preference test (SPT), forced swimming test (FST), and tail suspension test (TST). Tandem mass tag (TMT)-based quantitative proteomic analysis of the brain was performed following JD treatment. Hierarchical clustering, Gene Ontology function annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interactions (PPIs) were used to analyze differentially expressed proteins (DEPs), which were further validated using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. RESULTS: Behavioral tests confirmed the anti-depressant effects of JD, and bioinformatics analysis revealed 59 DEPs, including 33 up-regulated and 26 down-regulated proteins, between the CUMS and JD-M groups. KEGG and PPI analyses revealed that neuro-filament proteins and the Ras signaling pathway may be key targets of JD in the treatment of depression. qRT-PCR and Western blotting results demonstrated that CUMS reduced the protein expression of neurofilament light (NEFL) and medium (NEFM) and inhibited the phosphorylation of extracellular regulated kinase 1/2 (ERK1/2), whereas JD promoted the phosphorylation of ERK1/2 and up-regulated the protein expression of NEFL and NEFM. CONCLUSIONS: The antidepressant mechanism of JD may be related to the up-regulation of p-ERK1/2 and neurofilament proteins.

Animals↗

PubMed2025

Fishing for a reelGene: evaluating gene models with evolution and machine learning.

Assembled genomes and their associated annotations have transformed our study of gene function. However, each new annotated assembly generates new gene models. Inconsistencies between annotations likely arise from biological and technical causes, including pseudogene misclassification, transposon activity, and intron retention from sequencing of unspliced transcripts. To evaluate gene model predictions, we developed reelGene, a pipeline of machine learning models focused on (1) transcription boundaries, (2) mRNA integrity, and (3) protein structure. The first two models leverage sequence characteristics and evolutionary conservation across related taxa to learn the grammar of conserved transcription boundaries and mRNA sequences, while the third uses the conserved evolutionary grammar of protein sequences to predict whether a gene can produce a protein. Evaluating 1.8 million transcript models in Zea mays ssp. mays (maize), reelGene classified 28% as incorrectly annotated or non-functional. We find that reelGene classifies 92.2% of genes in the maize proteome and 99.2% of genes within the maize classical gene list as functional. reelGene also provides a way to further investigate genome biology- for instance, reelGene indicates that 10.3% of dispensable genes in B73 are functional, and within retained duplicate genes, reelGene identifies a 30% bias toward the retention of the M1 subgenome when one copy is functional and the other is non-functional. As an annotation-evaluating tool, reelGene is directly applicable to species of the Andropogoneae tribe, including other important crops like sorghum and miscanthus. As a community resource, reelGene has been integrated onto MaizeGDB both as a browser track and as an individual Shiny App, allowing researchers to evaluate gene model accuracy and further investigate genome biology.

Machine Learning↗

PubMed2026

Characterization of a draft chromosome-scale genome assembly for the mutton snapper, Lutjanus analis.

BACKGROUND: The mutton snapper (Lutjanus analis) is a reef fish commonly found in tropical waters of the Western Atlantic Ocean. Genomic studies of this species are needed to support conservation efforts and breeding programs. OBJECTIVE: Here, we report the development of a chromosome-scale reference assembly for the mutton snapper and conduct an initial comparative genomic analysis with other lutjanids. METHODS: The genome of one mutton snapper specimen was sequenced using PAC-Bio HiFi long reads and Illumina short reads. Contigs and scaffolds were assembled in the Flye pipeline and anchored using Hi-C proximity guided assembly. Gene prediction and functional annotations were obtained in AUGUSTUS and eggNOG-mapper, respectively. The mutton snapper genome was compared to those of other lutjanids to infer gene family evolution and chromosome synteny conservation. RESULTS: Assembly and polishing yielded 946 contigs and 926 scaffolds (N50 of 3.16 Mb, complete BUSCO score 98.1%) that were anchored using Hi-C scaffolding in 24 draft chromosomes. The anchored assembly featured a N50 of 42.47 Mb and contained 97.6% of the unanchored assembly length. The 24 mutton snapper chromosomes showed a one-to-one syntenic relationship with their counterparts in medaka, and other Lutjanids. AUGUSTUS predicted 29,023 genes, 24,335 of which (83.85%) could be functionally annotated. Gene family evolution analysis revealed 1,014 significantly expanded or contracted hierarchical ortholog groups in mutton snapper. Expansions and contractions were linked to several biological functions including growth, oocyte maturation, and response to exogenous stressors. CONCLUSION: The draft genome will be a valuable tool for forthcoming applied genomic studies of mutton snapper.

Animals↗

PubMed2026

A Network Pharmacology and Molecular Docking Study of TongBi Formula for Osteoarthritis.

This study applied network pharmacology combined with molecular docking to predict the potential therapeutic targets and molecular mechanisms of TongBi Formula (TBF) in osteoarthritis (OA). Active components and corresponding targets of TBF were retrieved from the traditional Chinese medicine Systems Pharmacology Database and Analysis Platform, while OA-related targets were collected from Online Mendelian Inheritance in Man, GeneCards, DrugBank, and Therapeutic Target Database. A network visualization and analysis software was used to construct compound-target and protein-protein interaction (PPI) networks. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery platform. Molecular docking analysis was conducted using a molecular docking software to evaluate the predicted binding affinity between key active compounds and core target proteins. A total of 47 overlapping targets between TBF and OA were identified. PPI network analysis highlighted JUN, RELA, IL6, MAPK1, and IL10 as potential hub targets. Enrichment analysis suggested that TBF may regulate inflammation, lipid metabolism, and multiple intracellular signaling pathways associated with OA progression. Molecular docking results demonstrated favorable predicted binding affinities between core active compounds and key OA-related protein targets. These findings provide a computational framework for understanding the potential mechanisms of TBF against OA and support further experimental validation.

Molecular Docking Simulation↗

PubMed2026

Whole genome sequencing analysis and functional characterization of Lacticaseibacillus rhamnosus HP-B1083.

Lacticaseibacillus rhamnosus is an important strain for the biotransformation of natural products, and its crude extract exhibits biotransformation effect on glycosidic compounds such as baicalin. To further explore the potential of this strain, particularly given its previously demonstrated high-efficiency β-glucuronidase activity for baicalin conversion, whole-genome sequencing and functional annotation of Lacticaseibacillus rhamnosus HP-B1083 were performed in this study, and its acid tolerance, bile salt tolerance, short-term heat resistance and antibacterial activity were evaluated. The results showed that the strain possessed a circular chromosome with a full length of 3,090,505 bp and a GC content of 46.69%. Gene annotation revealed that the genome contained 2941 coding sequences (CDS) and 112 non-coding RNA genes, including 60 tRNA genes, 1 tmRNA gene, 36 misc_RNA genes and 15 rRNA genes. The functional annotations further reveal that this genome is rich in genes related to carbohydrate metabolism, hydrolases, and transferases, which is highly consistent with its phenotypic characteristics in glycoside transformation and the synthesis of antibacterial substances. In addition, acid tolerance, bile salt tolerance and short-term heat resistance experiments verified that HP-B1083 had acid resistance, bile salt resistance and short-term heat resistance. Antibacterial activity tests confirmed that HP-B1083 produced inhibition zone diameters over 10 mm against common foodborne pathogenic bacteria such as Escherichia coli and Bacillus cereus. Therefore, Lacticaseibacillus rhamnosus HP-B1083 has important application prospects in the development of functional foods, preparation of enzyme preparations and pharmaceutical industry.

Whole Genome Sequencing↗

PubMed2026

B cell pathways implicate shared genetic architecture between schizophrenia and immune-mediated diseases.

BACKGROUND: Schizophrenia and immune-mediated diseases are globally prevalent and highly heritable conditions that frequently co-occur, posing major public health burdens. However, their shared genetic architecture remains poorly understood. METHODS: We applied the bivariate causal mixture model (MiXeR) to investigate the polygenic overlap between schizophrenia and eight common immune-mediated diseases, using genome-wide association study summary statistics comprising 2,489 to 67,323 cases and 9,066 to 497,622 controls. Shared loci were identified through conditional/conjunctional false discovery rate (cond/conjFDR), local genetic correlation (LAVA), and colocalization analyses. Subsequently, gene mapping, functional annotation, expression-trait association, and drug-gene interaction analyses were performed to explore shared genes and enriched pathways, and genetic risk scores (GRS) from the UK Biobank were used to validate the findings. RESULTS: MiXeR estimated substantial polygenic overlap between schizophrenia and immune-mediated diseases, and conjFDR identified 133 shared loci, with eight prioritized through local genetic correlation and colocalization signals. These eight loci were mapped to 85 protein-coding genes enriched in pathways essential for B cell function. Among them, S-PrediXcan analyses identified 14 genes whose expression in brain tissues or blood was associated with both diseases. These genes also interact with immunomodulatory or antihypertensive drugs. Additionally, 11 of the 14 genes were linked to innate immunity and/or cognitive traits. Using UK Biobank data, we further confirmed that overall, shared gene, and B cell activation and receptor signaling pathway–specific genetic risk for schizophrenia is associated with immune-mediated disease susceptibility. CONCLUSIONS: These findings underscore the shared genetic architecture of schizophrenia and immune-mediated diseases, advancing insights at the interface of psychiatric genetics and immunology.

Schizophrenia↗

PubMed2026

Changes of DNA methylation and gene expression profile in placental villi and chorioamniotic membranes under preeclampsia.

BACKGROUND: Preeclampsia (PE) is a serious pregnancy complication with elusive pathogenesis. Although epigenetic dysregulation is implicated, its layer-specific placental roles are poorly defined. This study aimed to identify shared and layer-specific epigenetic alterations in PE by profiling DNA methylation and gene expression in placental villi (PV) and chorioamniotic membranes (CAM). RESEARCH DESIGN AND METHODS: PV and CAM samples were collected from 7 normal and 8 PE pregnancies, and three public DNA methylation datasets (GSE98224, GSE44667, GSE75196) were integrated. Differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified based on whole-genome methylation and transcriptome sequencing. Layer-specific and shared gene sets were identified by cross-analysis, with functional annotation using Gene Ontology (GO). RESULTS: EM-seq revealed a hypermethylation-dominant, tissue-specific methylation landscape in PE placentas. Cross-tissue comparison identified shared DMGs between the two layers, including nine key genes consistently altered in public datasets. Integrated analysis in PV further identified 22 co-dysregulated genes, enriched in thermoregulation, maternal-fetal immunity, signal transduction, and cell differentiation. CONCLUSIONS: This study elucidates the shared and layer-specific dysregulation of gene networks at methylomic and transcriptomic levels in PE placenta. Comparing PV and CAM highlights placental epigenetic heterogeneity and dysfunction, offering novel clues for mechanistic research and layer-targeted therapies.

Humans↗

PubMed2026

Draft genome assembly of the green-bronze dung beetle, Onthophagus orpheus.

Dung beetles (Coleoptera: Scarabaeinae) are ecologically important insects, yet genomic resources for this diverse lineage remain limited. Here, we present a high-quality genome assembly for Onthophagus orpheus, an understudied species that is abundant in urban forests in the eastern United States. The assembled genome is a scaffold-level assembly, with a high degree of genic completeness as assessed by Benchmarking Universal Single-Copy Ortholog (BUSCO) analyses, indicating robust representation of conserved protein-coding genes. Structural and functional annotation recovered a comprehensive gene set consistent with expectations for coleopteran genomes. This genome assembly provides an important resource for future work on the behavioral ecology and population genetics of Onthophagus orpheus, specifically, and Scarabaeidae more broadly.

Onthophagus↗

PubMed2026

Chromosome-level genome assembly of Manglietia pachyphylla.

Manglietia pachyphylla, an endangered evergreen tree within the Magnoliaceae family, is renowned for its exceptional ornamental value in landscape horticulture. Despite its classification as a Category II nationally protected plant species in China, the genetic basis of its adaptive traits and conservation priorities remains poorly understood. To address this, we present the first chromosome-scale genome assembly of M. pachyphylla utilizing an integrated approach combining PacBio HiFi long-read and Hi-C chromosome conformation capture sequencing technologies. The assembled genome spans 2.15 Gb (contig N50 = 43.57 Mb), exhibiting a heterozygosity rate of 0.78% and repeat content of 78.64%, predominantly comprising long terminal repeat (LTR) retrotransposons (52.86%). Hi-C scaffolding anchored 99.57% of the assembly to 19 pseudochromosomes, achieving a BUSCO completeness score of 96.4%. Annotation revealed 42,505 putative protein-coding genes, with 84.46% of predicted genes were functionally annotated. Phylogenomic analysis positioned M. pachyphylla and Oyama sieboldii clustered together in a well-supported group. This high-contiguity genome assembly enables future investigations into adaptive evolution, functional genomics, and evidence-based conservation strategies for this endangered species.

Chromosomes, Plant↗

PubMed2023

Functional Annotation Routines Used by ABRF Bioinformatics Core Facilities - Observations, Comparisons, and Considerations.

The functional annotation of gene lists is a common analysis routine required for most genomics experiments, and bioinformatics core facilities must support these analyses. In contrast to methods such as the quantitation of RNA-Seq reads or differential expression analysis, our research group noted a lack of consensus in our preferred approaches to functional annotation. To investigate this observation, we selected 4 experiments that represent a range of experimental designs encountered by our cores and analyzed those data with 6 tools used by members of the Association of Biomolecular Resource Facilities (ABRF) Genomic Bioinformatics Research Group (GBIRG). To facilitate comparisons between tools, we focused on a single biological result for each experiment. These results were represented by a gene set, and we analyzed these gene sets with each tool considered in our study to map the result to the annotation categories presented by each tool. In most cases, each tool produces data that would facilitate identification of the selected biological result for each experiment. For the exceptions, Fisher's exact test parameters could be adjusted to detect the result. Because Fisher's exact test is used by many functional annotation tools, we investigated input parameters and demonstrate that, while background set size is unlikely to have a significant impact on the results, the numbers of differentially expressed genes in an annotation category and the total number of differentially expressed genes under consideration are both critical parameters that may need to be modified during analyses. In addition, we note that differences in the annotation categories tested by each tool, as well as the composition of those categories, can have a significant impact on results.

Computational Biology↗

PubMed2025

Chromosome-level genome assembly of Sinocyclocheilus jii based on PacBio HiFi and Hi-C sequencing.

Sinocyclocheilus jii, a cavefish species endemic to China, belongs to the genus Sinocyclocheilus within the family Cyprinidae. Species within this genus exhibit significant morphological differentiation, making it not only the most species-rich genus within Cyprinidae in China but also the most diverse group of cavefishes worldwide. However, the limited availability of genomic resources has limited investigations into the genetic basis of trait variations, phylogenetic relationships, and adaptive evolution in this genus. In this study, we assembled a chromosome-level reference genome for S. jii by integrating PacBio HiFi long reads, Illumina short reads, and Hi-C sequencing data. Flow cytometry was used to estimate the genome size prior to assembly, providing a key step in technical validation. The final genome assembly spans 1.75 Gb with a contig N50 of 35.0 Mb. Using Hi-C sequencing data, the assembled scaffolds were successfully anchored to 50 chromosomes. The completeness of the chromosome-level assembly was estimated at 98.9% by BUSCO analysis. Genome annotation identified 855.5 Mb of repetitive sequences and predicted a total of 52,867 protein-coding genes, of which 51,932 genes were functionally annotated. This study presents a high-quality chromosome-level genome assembly and annotation of S. jii, providing a fundamental genomic resource for future phylogenetic and evolutionary studies.

Animals↗

PubMed2026

Pinpointing genomic regions conferring herbicide tolerance in cassava via genome-wide association mapping.

Cassava (Manihot esculenta Crantz) is a tropical crop of major socioeconomic importance, whose productivity can be limited by sensitivity to herbicides used for weed management. This study aimed to perform a genome-wide association study (GWAS) in 194 cassava genotypes to identify genomic regions associated with tolerance to the herbicides mesotrione, S-metolachlor, and chloransulam-methyl. The evaluations performed at 3, 6, 9, 15, and 30 days after application (DAA) were used to characterize the temporal progression of phytotoxicity. Based on this analysis, the phenotype obtained at 9 days after application (PhytoX9DAA) was selected for genome-wide association analyses because it represented the period of greatest symptom expression and the highest discrimination among genotypes. GWAS analyses were performed using de-regressed BLUPs and the MLM, MLMM, and BLINK models, incorporating kinship (K) and population structure (Q) matrices. Significant markers were detected across multiple chromosomes, and the corresponding genomic windows contained candidate genes with functional annotations related to herbicide response. The predominant functional categories included membrane transport, channel activity, signal peptide processing, protein phosphorylation, cellular signaling, and metabolic regulation. Key candidate genes included Manes.02G151900 and Manes.02G152700 (chromosome 2), associated with transmembrane transport and signal peptide processing; Manes.09G060900 (chromosome 9), associated with protein kinase activity, ATP binding, and protein phosphorylation; and Manes.15G083800 and Manes.15G084000 (chromosome 15), associated with S-adenosylmethionine-dependent methyltransferase activity, membrane-related functions, and protein phosphorylation. These genes participate in biochemical pathways involved in cellular signaling, membrane transport, and metabolic regulation that may contribute to herbicide tolerance. Overall, the results demonstrate that herbicide tolerance in cassava is a quantitative and polygenic trait governed by numerous small-effect loci. The integration of cellular signaling, metabolic regulation, and membrane transport supports the physiological resilience of the species under chemical exposure, providing valuable insights for breeding strategies and marker-assisted selection.

Genome-Wide Association Study↗

PubMed2026

Genomes of the ex-type strains of Elsinoë mangiferae and E. perseae, the causal agents of scab on mango and avocado.

Elsinoë species are slow-growing, hemibiotrophic to necrotrophic fungi that cause scab diseases on economically important fruit crops. Genome resources for many host-specific species remain limited. We report high-quality draft genome assemblies for the ex-type strains of Elsinoë mangiferae (CBS 226.50) and E. perseae (CBS 406.34), causal agents of mango and avocado scab, respectively. Among 5 approaches tested, a Nanopore-only NextDenovo assembly produced the most contiguous genomes, yielding 24.5 Mb (E. mangiferae) and 25.1 Mb (E. perseae) assemblies with 13 and 18 contigs, respectively, BUSCO completeness scores of ∼94%, and multiple putative telomere-to-telomere chromosomes. Gene prediction identified 9,134 and 9,243 genes, respectively. Functional annotation revealed enrichment of metabolic and regulatory pathways, including those involved in posttranslational modification, protein transport, and secondary metabolism. Carbohydrate-active enzyme repertoires were small but conserved, consistent with stealth pathogenicity strategies and low plant cell wall degradation. Both genomes encoded large secretomes (>850 proteins), diverse protease repertoires (>300 proteins), Ecp2-like effector proteins, and multiple biosynthetic gene clusters, including clusters with similarity to those associated with elsinochrome and ACT-toxin II biosynthesis, some of which may contribute to host-pathogen interactions and disease development. A large fraction of genes lacked functional characterization, suggesting incomplete databases and/or the presence of lineage-specific genes potentially involved in virulence or host adaptation. These genome resources fill critical gaps for underrepresented Elsinoë species and provide taxonomically anchored references essential for diagnostics, comparative genomics, and research into the molecular basis of host specificity and pathogenicity in scab-causing fungi.

Persea↗

PubMed2023

Discussion on the mechanism of Lingguizhugan Decoction in treating hypertension based on network pharmacology and molecular simulation technology.

To explore the mechanism of Lingguizhugan Decoction in treating hypertension based on network pharmacology and molecular simulation. The active ingredients and potential targets were screened by the Systematic Pharmacological Analysis Platform of Traditional Chinese Medicine (TCMSP). Hypertension-related targets were obtained from OMIM and GeneCards databases. Common targets between drug and hypertension were screened in the Venny platform. A protein-protein interaction (PPI) network was constructed in the STRING database using intersection targets. Key targets in PPI network were analyzed by Cytoscape. R language program was used for Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, the binding abilities of the main active ingredients to critical targets were verified by molecular simulation. Naringenin, quercetin, kaempferol, and β-sitosterol in Lingguizhugan Decoction, and potential targets such as STAT3, AKT1, TNF, IL6, JUN, PTGS2, MMP9, CASP3, TP53, and MAPK3, were screened out. KEGG Enrichment analysis revealed that the common targets of Lingguizhugan Decoction and hypertension are mainly involved in the lipid and atherosclerosis signaling pathway, AGE-RAGE signaling pathway in diabetic complications, fluid shear stress and atherosclerosis, and IL17 signaling pathway. The molecular simulation results showed that naringenin-MAPK3, quercetin-MMP9, quercetin-PTGS2, and quercetin-TP53 were the top four in the docking scores. Naringenin-MAPK3 and quercetin-MMP9 were stable, with binding free energies of -27.97 ± 1.41 kcal/mol and -21.15 ± 3.17 kcal/mol, respectively. The possible mechanism of Lingguizhugan Decoction in treating hypertension is characterized of multi-component, multi-target, and multi-pathway.Communicated by Ramaswamy H. Sarma.

Network Pharmacology↗

PubMed2026

[Effects and mechanisms of ethanol extract of Salvia miltiorrhiza on liver fibrosis in mice].

To identify clinically advantageous TCMs for anti-hepatic fibrosis and to elucidate the effects and molecular mechanisms of Salvia miltiorrhiza ethanol extract in the intervention of liver fibrosis, this study screened high-frequency anti-hepatic fibrosis TCMs through a review of clinical literature. The S. miltiorrhiza active components, potential targets, and liver fibrosis-related disease targets were obtained using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), the GeneCards database, and other databases. Gene Ontology(GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were performed on the shared targets between drugs and diseases. Molecular docking was conducted to evaluate the binding affinities between key components and core targets. In animal experiments, male Kunming mice were used to establish a liver fibrosis model induced by carbon tetrachloride(CCl_4). The mice were administered low, medium, and high doses of S. miltiorrhiza ethanol extract by gavage. The liver index, as well as serum aspartate aminotransferase(AST) and alanine aminotransferase(ALT) levels, were measured. Histopathological changes in liver tissue were observed using hematoxylin-eosin(HE) staining and Masson's trichrome staining. Western blot analysis was used to detect the protein expression levels of α-smooth muscle actin(α-SMA), Collagen Ⅰ, and heat shock protein 90 alpha family class A member 1(HSP90AA1) in liver tissue. The results showed that S. miltiorrhiza was the most frequently used TCM in clinical anti-hepatic fibrosis. A total of 65 active components and 135 potential targets were identified, and 109 common targets were obtained by intersecting these with liver fibrosis-related targets. The core targets included tumor protein p53(TP53), serine/threonine protein kinase AKT1(AKT1), Jun proto-oncogene(JUN), signal transducer and activator of transcription 3(STAT3), and HSP90AA1, which were mainly enriched in pathways related to cancer, hepatitis B, and the PI3K-AKT signaling pathway. Molecular docking indicated that the main active components of S. miltiorrhiza bound stably to the core targets, with the strongest binding affinity observed for HSP90AA1. Animal experiments demonstrated that the liver index, serum ALT and AST levels, and the expression of α-SMA, Collagen Ⅰ, and HSP90AA1 in liver tissue were significantly increased in the model group, accompanied by obvious pathological manifestations of fibrosis. Compared with the model group, different dose groups of S. miltiorrhiza ethanol extract reduced the liver index and serum ALT and AST levels to varying degrees, alleviated pathological damage and collagen deposition in liver tissue, and downregulated the protein expression of α-SMA, Collagen Ⅰ, and HSP90AA1. In conclusion, S. miltiorrhiza ethanol extract exerts a significant protective effect on CCl_4-induced liver fibrosis in mice, and its mechanisms may be related to the inhibition of HSP90AA1 expression and the regulation of liver fibrosis-related signaling pathways.

Animals↗

PubMed2024

Metagenomic Analysis of Gut Microbiome of Persistent Pulmonary Hypertension of the Newborn.

Persistent pulmonary hypertension of the newborn (PPHN) is one of the most common diseases in the neonatal intensive care unit which severely affects neonatal survival. Gut microbes play an increasingly important role in human health, but there are rarely reported how gut microbiota contribute to PPHN. In our study, the metagenomic sequencing of feces from 12 PPHN's neonates and 8 controls were performed to expose the relation between neonatal gut microbes and PPHN disease. Firstly, we found that the abundance of Actinobacteria, Proteobacteria, Bacteroidetes were significantly increased in PPHN compared with controls, but the Firmicutes components was reduced. And some pathogenic strains (like Vibrio metschnikovii) were significantly enriched in the PPHN compared with controls. Secondly, functional annotation of genes found that PPHN up-regulated transmembrane transport, but down-regulated ribosome and ATP binding. Lastly, microbial metabolic pathway enrichment analysis indicated that some metabolic pathway in PPHN were conflicting and contradictory, showed that an abnormally increased metabolism, disturbed protein synthesis and genomic instability in the PPHN neonate. Our results contribute to understanding the changes in the species and function of gut microbiota in PPHN, thus providing a theoretical basis for the explanation and treatment of PPHN.

Gastrointestinal Microbiome↗

PubMed2026

Phage bioinformatics tools: a review of computational approaches for bacteriophage research.

Rising clinical interest in phage therapy and the exponential growth of metagenomic sequence catalogues have driven a rapid expansion of bacteriophage bioinformatics. More than 80 dedicated tools, mostly published since 2020, now span identification, assembly, annotation, taxonomy, lifestyle prediction, defence-system detection, and host prediction. Aimed at experienced practitioners and developers, this review synthesizes the field through the lens of three successive computational paradigms: sequence homology, bounded by database completeness; machine learning, constrained by labelled training data; and foundation models, which now achieve Matthews correlation coefficients above 0.95 in identification tasks and, through structure-informed prediction, raise functional annotation to over half of phage genes. Furthermore, we map the upstream components, namely, gene callers, homology engines, protein language models, and structural search tools, that underpin most downstream pipelines, exposing shared infrastructure and ecosystem-level fragility when dependencies change. To translate this into practice, we propose web-based and command-line reference workflows calibrated to user expertise and sample types. Finally, we set an agenda for the next wave of tool development. Roughly half of phage genes still resist functional annotation despite structural methods; no broadly generalizable strain-level host predictor exists for phage therapy; varying true-positive rates (0%-97%) underscore the absence of standardized community benchmarks analogous to Critical Assessment of Structure Prediction or Critical Assessment of Metagenome Interpretation. As generative genome models begin designing synthetic phages, progress will depend less on producing standalone tools than on rigorous evaluation, interoperable infrastructure, and clinically meaningful prediction targets.

Computational Biology↗

PubMed2026

Unraveling 'F' factor: towards a genetic-clinical framework for the musculoskeletal-heart crosstalk in metabolic aging.

BACKGROUND: The rising co-occurrence of cardiometabolic diseases and musculoskeletal degeneration poses a critical challenge to healthy aging, yet the shared biological mechanisms underlying this multimorbidity remain poorly defined. This study aimed to establish an integrative clinical-genetic framework to elucidate the common frailty factor, the 'F' factor, that captures the systemic vulnerability linking cardiometabolic multimorbidity (CMM) and musculoskeletal aging. METHODS: Utilizing the prospective China Health and Retirement Longitudinal Study (CHARLS) cohort, we developed and validated novel Frailty-Integrated Indices for CMM risk prediction, evaluated with machine learning models interpreted via SHapley Additive exPlanations (SHAP). Independently, we applied genomic structural equation modeling (Genomic-SEM) to integrate genome-wide association data from six traits-coronary artery disease, type 2 diabetes, hypertension, bone mineral density, frailty, and telomere length-to model a shared latent genetic factor ('F' factor). This was followed by multivariate GWAS, fine-mapping, transcriptome-wide association study (TWAS), gene-based analysis, and functional annotation to prioritize causal genes, pathways, and cell types. RESULTS: Clinically, several Frailty-Integrated Indices significantly improved CMM risk prediction, with the optimal model achieving an AUC of 0.727. Genetically, we modeled a significant shared latent genetic factor ('F' factor), pinpointing novel risk loci and implicating key genes such as APOE and SLC22A3. These genes were enriched in pathways including cellular senescence and cholesterol metabolism and showed specific expression patterns in developmental brain stages and across multi-organ endothelial cells. CONCLUSION: Our findings provide converging evidence for Musculoskeletal‑Heart crosstalk of metabolic aging and inferred the 'F' factor as a genetic correlate of a transdiagnostic state, which links genetic predisposition to metabolic dysregulation, and systemic functional decline. This work provides a multi-level biological characterization of multimorbidity liability, informing early-risk detection and preventive strategies for complex aging-related comorbidities.

Humans↗