Forest soils contain diverse microorganisms adapted to plant-derived aromatic compounds released during lignin decomposition. Genome-based characterization of these microorganisms provides insights into their genomic diversity and metabolic potential. In this study, strain APP145 was isolated from forest soil using enrichment cultures containing lignin-derived aromatic compounds, and integrated phenotypic, phylogenetic, and comparative genomic analyses were performed to determine its taxonomic position and genomic characteristics. Genome-based analyses identified strain APP145 as Pantoea cypripedii. Whole-genome sequencing revealed a multipartite genome comprising one chromosome and four large secondary replicons. Comparative genomic analyses demonstrated a large accessory genome, with many APP145-specific gene clusters within the analyzed genome set located on secondary replicons and assigned to diverse functional categories, including transport, metabolism, regulation, and defense-related functions. Genome mining identified genes associated with portions of the β-ketoadipate pathway together with diverse oxidoreductases, transporters, carbohydrate-active enzymes, and stress response systems, suggesting the potential for aromatic compound metabolism and responses to diverse environmental conditions. Several biosynthetic gene clusters, including terpene-related, and siderophore-related clusters, were also identified. Overall, the chromosome predominantly encoded core metabolic functions, whereas secondary replicons contained a substantial proportion of accessory genes associated with diverse predicted functions. The genome of Pantoea cypripedii APP145 exhibits a modular organization consisting of a conserved chromosomal backbone and a large secondary-replicon-associated accessory genome. These genomic features illustrate strain-level genomic diversity within the genus Pantoea and provide a genomic resource for future studies of aromatic compound metabolism and the functional roles of accessory genes in soil-associated bacteria.
Cluster compactness is a major agronomic trait influencing fruit quality and disease susceptibility in table grape cultivars. To investigate transcriptional mechanisms underlying cluster architecture and the effects of gibberellin (GA) treatment, we performed RNA-seq on cluster tissues of Vitis vinifera cv. Sistan Yaghooti collected at three developmental stages from GA-treated and control vines. Libraries were prepared using the TruSeq Stranded Total RNA (plant) kit and sequenced on an Illumina HiSeq 2500 platform, generating 380,460,946 paired-end reads (101 bp). Analysis identified 19,194 alternative splicing (AS) events, 2,021 long non-coding RNAs (lncRNAs), and 3,715 high-confidence circular RNAs (circRNAs) across developmental stages. Read quality, mapping rates to the PN40024 reference genome, and assembly metrics indicate high technical quality of the dataset. Sequencing data have been deposited in the NCBI SRA under accession PRJNA1098654. These openly shared data provide a resource for dissecting the molecular basis of cluster formation and compactness in Sistan Yaghooti grape and will support marker discovery and breeding strategies aimed at improving bunch architecture and fruit quality.
To evaluate the association of HLA-C*06:02 allele and serum total immunoglobulin E (IgE) with ustekinumab response in biologic-naive Chinese patients with plaque psoriasis. A single-center retrospective study was conducted, enrolling 42 Chinese patients with plaque psoriasis. Genome-wide microarray analysis and clinical data assessment were performed for all participants received ustekinumab at week 0, 4, 16 and 28. HLA-C*06:02 allele positive patients achieved significantly higher PASI 50 response rates at week 4 and PASI 75 response rates at week 16 compared to HLA-C*06:02 allele negative patients (all Ps < 0.05). At week 28, all patients in both groups attained PASI 75, the PASI 90 response rate was numerically higher in the HLA-C*06:02 allele positive group, but the difference was not statistically significant (P > 0.05). Patients with elevated baseline total IgE (> 60 IU/mL) also showed superior PASI 75 response at weeks 4 and 16, and a higher PASI 90 response rate at week 16 and 28 (all Ps < 0.05). Multivariate binary logistic regression analysis showed that HLA-C*06:02 allele positivity was associated with achieving PASI 75 at week 16. HLA-C*06:02 allele positivity and elevated baseline total IgE were associated with a favorable ustekinumab response in biologic-naive Chinese patients with plaque psoriasis, although the findings are exploratory and require validation.
Predicting enzyme function in non-model fish species remains challenging because of scarce experimental annotations and poor cross-species generalization of existing methods. Deep learning approaches using protein embeddings offer an efficient alternative, yet existing dropout mechanisms lack adaptability to embedding spaces and often fail to generalize across species. We propose VARDON (Variational Adaptive Real Dropout), a family of five novel dropout mechanisms with learnable per-neuron rates and Bayesian approximation. Using pre-computed UniProt embeddings (1024-dimensional) from 4,568 manually curated proteins across 12 fish species, we evaluated VARDON configurations against five baselines using 10-fold cross-validation, independent test sets, and leave-one-species-out (LOSO) cross-validation. VARDON variants demonstrated competitive performance on standard benchmarks (MCC = 0.8606, only 0.0008 behind the best baseline), while achieving superior cross-species generalization with VARDON_AdaptiveVD attaining the highest mean LOSO MCC (0.8823), essentially tied with the top-performing baseline (Residual_MLP: 0.8824) and outperforming Gaussian_Dropout_NN (0.8556) by 3.1
Necrotic enteritis (NE) is one of the most economically important diseases affecting the poultry industry worldwide. Understanding the regulatory mechanisms that control host resistance to NE is essential for identifying molecular markers associated with disease resilience. Promoter regions and microRNAs (miRNAs) play critical roles in regulating gene expression and coordinating immune responses; therefore, their characterization may provide valuable insights into the molecular basis of disease resistance. The present study aimed to identify key regulatory elements, including promoter motifs, transcription factors, and miRNAs, associated with upregulated genes in resistant White Leghorn chicken line co-infected with Eimeria maxima and Clostridium perfringens. In this study, gene networks, gene ontologies, biological pathways, identification of hub genes, promoter interactions and interactions between miRNAs and hub genes in the spleens of Marek’s disease-resistant Leghorn chickens infected with C. perfringens and E. maxima were investigated. Bioinformatics tools were used to conduct this study. For the gene interaction analysis, 216 genes with a p-value of less than 0.01 and a fold change of greater than two relative to the control group were used. miRNA targets of hub genes were predicted using miRDB, and only high-confidence interactions (score > 80) were considered. The results revealed that a substantial proportion of the analyzed upregulated genes were involved in immune-related processes, and several hub genes, including CD molecules and cytokines, were identified. In addition, network analysis revealed hub genes and their interactions led to the identification of three functional clusters. The KEGG pathways of cell adhesion molecules, the intestinal immune network for IgA production, and cytokine-cytokine receptor interactions were commonly identified across all three clusters, indicating their importance in the network. Promoter motif analysis revealed notable binding sites for the upregulated hub genes. Six effective motif binding sites were identified for the upregulated genes. The transcription factors MIX-A, PHOX2B, ZNF384, KLF15, ZNF610, and PATZ1 were found at all six of these loci. The top five gene ontology terms predicted for these motifs were protein transport, translation, regulation of transcription, and DNA dependent, which are common biological processes. The integrated analysis of upregulated genes in resistant chickens revealed that immune-related pathways, key hub genes, transcription factor binding motifs, and miRNA-gene interactions collectively contribute to the host response against necrotic enteritis. The identified regulatory network suggests that both transcriptional and post-transcriptional mechanisms are involved in disease resistance. In particular, hub genes such as TNFSF13B and PTPRC emerged as central regulatory components and may represent promising candidates for future functional validation and biomarker development. These findings provide insights into the molecular mechanisms underlying the immune response to necrotic enteritis in poultry, which could contribute to the development of new strategies for disease control.
