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Correctly estimating the age of a gene or gene family is important for a variety of fields, including molecular evolution, comparative genomics, and phylogenetics, and increasingly for systems biology and disease genetics. However, most studies use only a point estimate of a gene's age, neglecting the substantial uncertainty involved in this estimation. Here, we characterize this uncertainty by investigating the effect of algorithm choice on gene-age inference and calculate consensus gene ages with attendant error distributions for a variety of model eukaryotes. We use 13 orthology inference algorithms to create gene-age datasets and then characterize the error around each age-call on a per-gene and per-algorithm basis. Systematic error was found to be a large factor in estimating gene age, suggesting that simple consensus algorithms are not enough to give a reliable point estimate. We also found that different sources of error can affect downstream analyses, such as gene ontology enrichment. Our consensus gene-age datasets, with associated error terms, are made fully available at so that researchers can propagate this uncertainty through their analyses (geneages.org).
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http://dx.doi.org/10.1093/gbe/evw113 | DOI Listing |
mSystems
September 2025
Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
Genome-scale metabolic models (GEMs) are widely used in systems biology to investigate metabolism and predict perturbation responses. Automatic GEM reconstruction tools generate GEMs with different properties and predictive capacities for the same organism. Since different models can excel at different tasks, combining them can increase metabolic network certainty and enhance model performance.
View Article and Find Full Text PDFOncol Res
September 2025
Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Studies have reported the special value of PANoptosis in cancer, but there is no study on the prognostic and therapeutic effects of PANoptosis in bladder cancer (BLCA). This study aimed to explore the role of PANoptosis in BLCA heterogeneity and its impact on clinical outcomes and immunotherapy response while establishing a robust prognostic model based on PANoptosis-related features. Gene expression profiles and clinical data were collected from public databases.
View Article and Find Full Text PDFInt J Biol Macromol
September 2025
Faculty of Applied Sciences, Macao Polytechnic University, Macao. Electronic address:
Osteosarcoma (OS), the most prevalent primary bone malignancy in adolescents, is characterized by aggressive progression and early metastasis. However, the epigenetic drivers of its metastatic heterogeneity remain poorly understood. Herein, we integrated bulk DNA methylation profiling and single-cell RNA sequencing (scRNA-seq) to elucidate the epigenetic mechanisms driving OS metastatic heterogeneity.
View Article and Find Full Text PDFInt Immunopharmacol
August 2025
Department of Anesthesiology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China; Shanghai Engineering Research Center of Lung Transplantation, Shanghai, China. Electronic address:
Background: Protein lactylation has been implicated in stress-responsive cellular mechanisms, yet its role in lung transplantation-associated ischemia-reperfusion injury (IRI) remains undefined.
Methods: Transcriptomic profiles from GSE145989 were analyzed through differential expression analysis (limma) and weighted gene co-expression network analysis (WGCNA). Integrating the identified genes with lactylation-related signatures uncovered key lactylation-related genes (LRGs) as potential targets.
Oncogene
September 2025
Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, 985805 Nebraska Medical Center, Omaha, NE, USA.
Androgen receptor (AR)-mediated signaling is essential for PC tumorigenesis. In the TCGA database we observed a positive correlation between ECD and AR expression. Consistently, Dihydrotestosterone (DHT) treatment of PC cell lines increased ECD mRNA and protein levels, and AR knockdown (KD) reduced ECD expression.
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