Increasingly available genomic sequencing data are exploited to identify genes and variants contributing to diseases, particularly cancer. Traditionally, methods to find such variants have relied heavily on allele frequency and/or familial history, often neglecting to consider any mechanistic understanding of their functional consequences. Thus, while the set of known cancer-related genes has increased, for many, their mechanistic role in the disease is not completely understood. This issue highlights a wide gap between the disciplines of genetics, which largely aims to correlate genetic events with phenotype, and molecular biology, which ultimately aims at a mechanistic understanding of biological processes. Fortunately, new methods and several systematic studies have proved illuminating for many disease genes and variants by integrating sequencing with mechanistic data, including biomolecular structures and interactions. These have provided new interpretations for known mutations and suggested new disease-relevant variants and genes. Here, we review these approaches and discuss particular examples where these have had a profound impact on the understanding of human cancers.
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http://dx.doi.org/10.1002/1873-3468.12988 | DOI Listing |
Water Res
January 2025
Faculty of Geosciences and Civil Engineering, Kanazawa University, Kanazawa 920-1192, Japan; Center for Infectious Disease Education and Research (CiDER), Osaka University, 565-0871, Japan. Electronic address:
Treated effluent of wastewater treatment plants (WWTPs) are major sources of extracellular antimicrobial resistance genes (eARGs) into aquatic environments. This study aimed to clarify the fate and origins of eARGs from influent to treated effluent at a full-scale WWTP. The compositions of eARG and intracellular ARG (iARG) were acquired via shotgun metagenomic sequencing in influent wastewater, activated sludge, and treated effluent of the target WWTP, where identical wastewater was treated by conventional activated sludge (CAS) and membrane bioreactor (MBR) processes.
View Article and Find Full Text PDFJCO Precis Oncol
January 2025
Karmanos Cancer Institute and Department of Oncology, Wayne State University School of Medicine, Detroit, MI.
Purpose: Although lung cancer is one of the most common malignancies, the underlying genetics regarding susceptibility remain poorly understood. We characterized the spectrum of pathogenic/likely pathogenic (P/LP) germline variants within DNA damage response (DDR) genes among lung cancer cases and controls in non-Hispanic Whites (NHWs) and African Americans (AAs).
Materials And Methods: Rare, germline variants in 67 DDR genes with evidence of pathogenicity were identified using the ClinVar database.
PLoS One
January 2025
School of Health and Biomedical Sciences, RMIT University, Bundoora, Victoria, Australia.
The cytotoxic T-lymphocyte antigen-4 (CTLA4) is essential in controlling T cell activity within the immune system. Thus, uncovering the molecular dynamics of single nucleotide polymorphisms (SNPs) within the CTLA4 gene is critical. We identified the non-synonymous SNPs (nsSNPs), examined their impact on protein stability, and identified the protein sequences associated with them in the human CTLA4 gene.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Computer Science and Engineering, University of Chittagong, Chattogram, Bangladesh.
Rice blast, caused by Magnaporthe oryzae, is one of the most destructive fungal diseases in rice, resulting in major economic losses worldwide. Genetic and genomic studies have identified key genes and proteins, such as AvrPik variants and MAX proteins, that are crucial for the pathogen's virulence. These effector proteins interact with specific alleles of the Pik gene family on rice chromosome 11, modulating the host's immune response.
View Article and Find Full Text PDFDiabetes
January 2025
Division of Endocrinology and Metabolism, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
PPARγ is the pharmacological target of thiazolidinediones (TZDs), potent insulin sensitizers that prevent metabolic disease morbidity but are accompanied by side effects such as weight gain, in part due to non-physiological transcriptional agonism. Using high throughput genome engineering, we targeted nonsense mutations to every exon of PPARG, finding an ATG in Exon 2 (chr3:12381414, CCDS2609 c.A403) that functions as an alternative translational start site.
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