Rice breeding faces numerous challenges in selecting potential materials that combine high grain yield with enhanced adaptability to diverse conditions and stress-prone environments. We sequenced the genomes of 70 conventional japonica rice varieties from Zhejiang Province to assess their genetic diversity and provide genomic support for future rice breeding efforts. Whole-genome resequencing technology serves as an effective tool for elucidating genetic diversity, deciphering population structure, and exploring adaptive evolution of rice germplasm, providing valuable insights for advancing molecular breeding efforts. To enhance the utilization of japonica genetic resources and facilitate the breeding of new varieties, a study utilizing whole-genome resequencing analysis was performed on genetic data from 70 japonica rice accessions originating in Zhejiang Province, China. We systematically investigated genetic diversity, population structure, and selection signatures through phylogenetic tree construction, principal component analysis (PCA), and select elimination analysis. Our findings revealed that the conventional japonica rice varieties in this region exhibit substantial genetic diversity, with distinct population stratification into two genetically divergent subgroups. Through select elimination analysis, 112 genomic regions that had undergone selection pressure during the breeding process were identified. Subsequent KEGG and GO enrichment analyses of candidate genes within these selected genomic regions provided a foundation for future research on gene function. Additionally, haplotype analysis further revealed significant allelic variations correlated with agronomic traits, providing valuable genetic information for improving rice varieties. This research establishes a robust genomic foundation for precision breeding and provides actionable insights to optimize the development of improved japonica rice varieties. Our findings reveal two genetically distinct subgroups among Zhejiang japonica rice varieties, with different levels of diversity reflecting their breeding histories. We identified multiple genomic regions and candidate genes that likely experienced selection. These results provide a genomic basis for more targeted use of Zhejiang japonica germplasm in future breeding efforts.
Although many achievements have been made in understanding the mechanisms underlying age-dependent and induced leaf senescence, the precise regulatory pathway involved remains to be elucidated. AtWDS1, which is a nuclear-localized negative senescence regulator in Arabidopsis thaliana, was characterized in a previous study. In this study, AtATO, encoding an SF3a factor, was identified when AtWDS1-interacting proteins were screened and was further verified using yeast two-hybrid assays and bimolecular fluorescence complementation. YFP-tagged AtATO protein in A. thaliana mesophyll protoplasts revealed that AtATO localized to the nucleus and cytoplasm. An analysis of the AtATO T-DNA insertion mutant (atato) revealed a premature senescence phenotype, chlorophyll loss, and up-regulated expression of senescence-associated genes. Compared with those from the wild-type plants, the leaves from the atato mutant became chlorotic faster and had greater H2O2 accumulation under dark conditions. Phenotyping of the atato mutant indicated that AtATO suppressed developmental and dark-induced leaf senescence. In addition, atato mutants presented reduced tolerance to oxidative stress, accompanied by changes in the transcription levels of genes associated with the oxidative stress response and increased cell death. Taken together, these results suggest that AtATO functions as a novel modulator of leaf senescence in A. thaliana in response to developmental and stress signals.
Crohn’s disease (CD) is a chronic recurrent inflammatory bowel disease (IBD). Transglutaminase 2 (TGM2) participates in CD progression, yet its regulatory mechanism remains elusive. Here, transcriptomic, single-cell transcriptomic, metabolomic, and apoptosis-related datasets from GEO, Metabolomics Workbench, and GeneCards were integrated, followed by bioinformatic analyses using R 4.5.1 and MetaboAnalyst 5.0. In vitro experiments included Western blot, cell transfection, TUNEL, ELISA, ROS detection, ChIP, dual-luciferase reporter assay, and RT-qPCR. Bioinformatic analyses identified distinct gene expression profiles, aberrant immune cell infiltration, and disrupted energy and lipid metabolism in CD, yielding 23 candidate targets. TGM2 was enriched in fibroblasts, enterocytes, and myeloid cells, modulating apoptosis, inflammation, and oxidative stress to aggravate CD phenotypes. Mechanistically, interferon regulatory factor 1 (IRF1) directly bound to the TGM2 promoter and enhanced its transcription. The IRF1-TGM2 axis regulated apoptosis, inflammation, and ROS levels, with TGM2 overexpression reversing the inhibitory effects of IRF1 knockdown. IRF1 transcriptionally upregulates TGM2 to promote apoptosis and oxidative stress, providing a plausible mechanistic framework for CD-associated epithelial injury.
This study aimed to prioritize potential therapeutic candidates for age-related macular degeneration (AMD) using an integrated multi-omics Mendelian randomization (MR) framework. We performed two-sample MR using 2,816 cis-pQTLs from four proteome-wide association studies to identify AMD-associated plasma proteins. Validation included summary-based MR (SMR), colocalization, protein–protein interaction analysis, pathway enrichment, retinal expression profiling, and druggability assessment. We identified 22 AMD-associated proteins, including both known (e.g., CFB, APOE, C3) and novel candidates (e.g., CTRL, LCAT, TNFRSF10A). Four targets (C3, CTRL, LCAT, TNFRSF10A) were prioritized as Tier 1 candidates based on consistent MR and colocalization evidence. These targets were enriched in complement activation, coagulation, and lipid metabolism pathways. This study proposed 22 potential therapeutic targets for AMD, with C3, CTRL, LCAT, and TNFRSF10A representing high-confidence candidates for further mechanistic and clinical investigation.
Gallbladder cancer (GBC) is a rare but aggressive hepatobiliary malignancy associated with high mortality rates. It has multi-factorial etiology with a poor diagnosis and prognosis. Despite aggressive disease phenotype, GBC treatment options remain limited mostly due to inadequate scientific understanding and data. Here, we present “GallMine” ( https://www2.tezu.ernet.in/gallmine/ ), an interactive knowledgebase that systematically integrates widely scattered and unstructured scientific information on GBC into a unified repository organized across multiple tabs. GallMine encompasses information on eight GBC transcriptome datasets, along with differential expression profiles and curated data for 1,423 tumor-specific genes and 337 lncRNAs, alongside 459 and 54 GBC-specific proteins and metabolite signatures, respectively. Users can browse, download, and contribute information on GBC-associated genes, lncRNAs, proteins, and metabolites. Additionally, GallMine incorporates curated content from 301 published literature, comprising 124 multi-omics studies on GBC, 60 studies on gallstone disease, 40 on the clinical and molecular profiles of GBC across diverse sample types, and 77 focused on its risk factors. GallMine serves as a consolidated resource containing structured information on GBC. It serves as a hub for large-scale computational analysis of molecular signatures critical for GBC pathogenesis, supporting AI/ML data integration and training, biomarker discovery, and improved therapeutic interventions. In subsequent versions GallMine may be expanded to include information on other gallbladder-related diseases.
