Mammalian Genome最新文献

Despite the fact that HPV vaccines are likely to lead to a significant reduction in cervical cancer occurrence, there remains cervical cancer incidence independent of the vaccine and cervical cancer arising in the absence of vaccination. Thus, continued efforts are needed to address the potential parameters of cervical cancer that could impact therapy and could lead to additional ways of reducing cervical cancer death rates. Adaptive immune receptor recombinations were obtained from the cancer genome atlas (TCGA) cervical cancer database through tumor exome and RNAseq files as well as from the independent Cancer Genome Characterization Initiative (CGCI) cervical cancer dataset. T-cell receptor (TCR) complementarity determining region-3's (CDR3s) were then assessed, based on chemical complementarity to human papillomavirus (HPV) T-cell epitopes. Results indicated increased overall survival probabilities consistently across the three TCR datasets with TCR CDR3 chemical complementarity to the same HPV epitopes, specifically immune epitope database (IEDB) designations: IEDB-1625373, IEDB-174148, and IEDB-110943. Among other potential applications of these results, the results may indicate HPV epitopes that could be useful targets for immunotherapy.

There is a thriving, worldwide, biomedical research community working to understand the molecular bases of diseases of all types, continuously driving improved diagnostics and therapies. Developments in genetics and experimental medicine are yielding novel genetic therapies that were hardly dreamt of 40 years ago. But along with these scientific achievements, there exist challenges in ensuring that 21st century medical interventions are accessible to all who need them. This perspective will discuss how preclinical research, with a focus on rare diseases, can better contribute to healthcare ecosystems that are oriented towards greater health equity. This contribution may require changes to the prevailing scientific research culture that will need support from relevant institutions and the wider community.

TDP-43 is a normally nuclear RNA binding protein that under pathological conditions may be excluded from the nucleus and deposited in the cytoplasm in the form of insoluble polyubiquitinated and polyphosphorylated inclusions. This nuclear exclusion coupled with cytoplasmic accumulation is called TDP-43 pathology and contributes to a range of disorders collectively known as TDP-43 proteinopathies. These include the great majority of amyotrophic lateral sclerosis (ALS) cases, all limbic-predominant age-related TDP-43 encephalopathy (LATE), as well as up to 50% of frontotemporal lobar degeneration (FTLD) and Alzheimer's disease (AD) cases. Thus, TDP-43 pathology is a common feature underlying a wide range of neurodegenerative conditions. However, modelling it has proven to be challenging, particularly generating models with concomitant TDP-43 loss of nuclear function and cytoplasmic inclusions. Here, focussing exclusively on mice, we discuss TDP-43 genetic models in terms of the presence of TDP-43 pathology, and we consider other models with TDP-43 pathology due to mutations in disparate genes. We also consider manipulations aimed at producing TDP-43 pathology, and we look at potential strategies to develop new, much needed models to address the many outstanding questions regarding how and why TDP-43 protein leaves the nucleus and accumulates in the cytoplasm, causing downstream dysfunction and devastating disease.

Background: Coronary artery disease (CAD) is the leading cause of death worldwide, and aberrant phagocytosis may be involved in its development. Understanding this aspect may provide new avenues for prompt CAD diagnosis.

Methods: CAD-related information was obtained from Gene Expression Omnibus datasets GSE66360, GSE113079, and GSE59421. We identified 995 upregulated and 1086 downregulated differentially expressed genes (DEGs) in GSE66360. Weighted gene co-expression network analysis revealed a module of 503 genes relevant to CAD. Using clusterProfiler, we revealed 32 CAD-related PRFs. Eight candidate genes were identified in a protein-protein interaction network. Machine learning algorithms identified CAD biomarkers that underwent gene set enrichment analysis, immune cell analysis with CIBERSORT, microRNA (miRNA) prediction using the miRWalk database, transcription factor (TF) level predication through ChEA3, and drug prediction with DGIdb. Cytoscape visualized the miRNA -mRNA- TF, miRNA-single nucleotide polymorphism-mRNA, and biomarker-drug networks.

Results: IL1B, TLR2, FCGR2A, SYK, FCER1G, and HCK were identified as CAD biomarkers. The area under the curve of a diagnostic model based on the six biomarkers was > 0.7 for the GSE66360 and GSE113079 datasets. Gene set enrichment analysis revealed differences in their biological pathways. CIBERSORT revealed that 10 immune cell types were differentially expressed between the CAD and control groups. The TF-mRNA-miRNA network showed that has-miR-1207-5p regulates HCK and FCER1G expression and that RUNX1 and SPI may be important TFs. Ninety-five drugs were predicted, including aspirin, which influenced ILIB and FCERIG.

Conclusion: In this study, six biomarkers (IL1B, TLR2, FCGR2A, SYK, FCER1G, and HCK) related to CAD phagocytic regulatory factors were identified, and their expression regulatory relationships in CAD were further studied, providing a deeper understanding of the pathogenesis, diagnosis, and potential treatment strategies of CAD.

Gene therapy offers significant promise for treating inner ear disorders, but its clinical translation requires robust preclinical validation, often reliant on animal models. This review examines the role of these models in advancing gene therapeutics for inherited inner ear disorders, focusing on successes, challenges, and treatment solutions. By providing a precise understanding of disease mechanisms, these models offer a versatile preclinical platform that is essential for assessing and validating therapies. Successful gene supplementation and editing have shown potential in restoring hearing and balance functions and preventing their decline. However, challenges such as limitations in gene delivery methods, surgical access, immune responses, and discrepancies in disease manifestation between animal models and humans hinder clinical translation. Current efforts are dedicated to developing innovative strategies aimed at enhancing the efficiency of gene delivery, overcoming physical barriers such as the blood-labyrinth barrier, improving target specificity, and maximizing therapeutic efficacy while minimizing adverse immune responses. Diverse gene supplementation and editing strategies, along with evolving technologies, hold promise for maximizing therapeutic outcomes using disease relevant models. The future of inner ear gene therapeutics will hinge on personalized therapies and team science fueling interdisciplinary collaborations among researchers, clinicians, companies, and regulatory agencies to expedite the translation from bench to bedside and unlock the immense potential of precision medicine in the inner ear.

Large animal models of inherited retinal diseases, particularly dogs, have been extensively used over the past decades to study disease natural history and evaluate therapeutic interventions. Our group of investigators at the University of Pennsylvania, School of Veterinary Medicine, has played a pivotal role in characterizing several of these animal models, documenting the natural history of their diseases, developing gene therapies, and conducting proof-of-concept studies. Additionally, we have assessed the potential toxicity of these therapies for human clinical trials, contributing to the regulatory approval of voretigene neparvovec-rzyl (Luxturna^®) by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) for the treatment of patients with confirmed biallelic mutation-associated retinal dystrophy. In this review, we aim to summarize the clinical features of a subset of these diseases and reflect on the challenges encountered in integrating canine models into the translational pipeline.

Huge genetic diversity is evident among the diverse goat breeds in terms of production, reproduction, adaptability, growth, disease resistance and thermo-tolerance. This diversity is an outcome of both natural and artificial selection acting on the caprine genome over the years. A fine characterization of whole genome variation is now possible by employing Next Generation Sequencing (NGS) technologies. To explore underlying genetics, genome-wide analysis of genetic markers is the best resolution. The study strived to capture variation in terms of CNV/CNVRs among 11 Indian goat breeds. In this study, the first ever resequencing-based CNV/CNVR distribution of Indigenous goat breeds was delineated, providing a sizable addition to the prior caprine CNVRs reported. Different diversity metrics were analyzed using identified CNVR. Principal component analysis (PCA) showed separate clustering of Kanniadu (KAN) and Jharkhand Black (JB) from other breeds under the study, indicating their unique genetic profile as the former breeds were sampled from institutional farms. The admixture analysis and introgression revealed by f3 statistics suggested distinct genetic structuring of JB, KAN and TEL(Tellicherry) as compared to the rest of the studied populations. Apart from this, we also identified 32 selection signatures through V_ST (Variance-stabilizing transformation) method and key genes such as ZBTB7C, BHLHE22, AGT were found elucidating the genetic architecture of hot and cold adaptation in Indian goats. Information generated hereby in the form of 32,711 autosomal CNVRs and the custom scripts ( https://github.com/kkokay07/Climate-Variables-Analysis.git , https://github.com/chau-mau/SelectCNVR.git and https://github.com/chau-mau/CNVrecaller.git ) will be of relevance in further studies on copy number based genetics.

Mouse models serve as the most important laboratory resource for both biomedical research and preclinical study of drug development. National Resource Center of Mutant Mice (NRCMM) of China was initiated in 2001 and became one of the 31 members of National Science and Technology Resource Sharing Platform in 2019. Currently, NRCMM is co-managed by Model Animal Research Center of Nanjing University and Gempharmatech (GPT, a Shanghai Exchange enlisted public company). Dedicated to produce and collect genetic edited mouse models, NRCMM holds more than 22,000 mouse strains in 2024, compared with 18,500 strains reported in 2022. This review provides an update on our Knock-Out All Project (KOAP) and highlights resources available for immune system reconstitution models, disease models, and chromosome substitution strains at NRCMM.