Stratification of candidate genes for Parkinson’s disease using weighted protein interaction network analysis

Genome wide association studies (GWAS) have helped identify large numbers of genetic loci that significantly associate with increased risk of developing diseases. However, translating genetic knowledge into understanding of the molecular mechanisms underpinning disease (i.e. disease-specific impacted biological processes) has to date proved to be a major challenge. This is primarily due to difficulties in confidently defining candidate genes at GWAS-risk loci. The goal of this study was to better characterize candidate genes within GWAS loci using a protein interactome based approach and with Parkinson's disease (PD) data as a test case.We applied a recently developed Weighted Protein-Protein Interaction Network Analysis (WPPINA) pipeline as a means to define impacted biological processes, risk pathways and therein key functional players. We used previously established Mendelian forms of PD to identify seed proteins, and to construct a protein network for genetic Parkinson's and carried out functional enrichment analyses. We isolated PD-specific processes indicating 'mitochondria stressors mediated cell death', 'immune response and signaling', and 'waste disposal' mediated through 'autophagy'. Merging the resulting protein network with data from Parkinson's GWAS we confirmed 10 candidate genes previously selected by pure proximity and were able to nominate 17 novel candidate genes for sporadic PD.With this study, we were able to better characterize the underlying genetic and functional architecture of idiopathic PD, thus validating WPPINA as a robust pipeline for the in silico genetic and functional dissection of complex disorders

Mechanisms of human telomerase reverse transcriptase (hTERT) regulation: clinical impacts in cancer

Background Limitless self-renewal is one of the hallmarks of cancer and is attained by telomere maintenance, essentially through telomerase (hTERT) activation. Transcriptional regulation of hTERT is believed to play a major role in telomerase activation in human cancers. Main body The dominant interest in telomerase results from its role in cancer. The role of telomeres and telomere maintenance mechanisms is well established as a major driving force in generating chromosomal and genomic instability. Cancer cells have acquired the ability to overcome their fate of senescence via telomere length maintenance mechanisms, mainly by telomerase activation. hTERT expression is up-regulated in tumors via multiple genetic and epigenetic mechanisms including hTERT amplifications, hTERT structural variants, hTERT promoter mutations and epigenetic modifications through hTERT promoter methylation. Genetic (hTERT promoter mutations) and epigenetic (hTERT promoter methylation and miRNAs) events were shown to have clinical implications in cancers that depend on hTERT activation. Knowing that telomeres are crucial for cellular self-renewal, the mechanisms responsible for telomere maintenance have a crucial role in cancer diseases and might be important oncological biomarkers. Thus, rather than quantifying TERT expression and its correlation with telomerase activation, the discovery and the assessment of the mechanisms responsible for TERT upregulation offers important information that may be used for diagnosis, prognosis, and treatment monitoring in oncology. Furthermore, a better understanding of these mechanisms may promote their translation into effective targeted cancer therapies. Conclusion Herein, we reviewed the underlying mechanisms of hTERT regulation, their role in oncogenesis, and the potential clinical applications in telomerase-dependent cancers.info:eu-repo/semantics/publishedVersio

Comprehensive analysis of lncRNAs and mRNAs in skeletal muscle of rainbow trout (Oncorhynchus mykiss) exposed to estradiol

Abstract Estradiol (E2) is a steroid hormone that negatively affects muscle growth in rainbow trout (Oncorhynchus mykiss), but the mechanisms directing with this response are not fully understood. To better characterize the effects of E2 in muscle, we identified differentially regulated mRNAs and lncRNAs in juvenile rainbow trout exposed to E2. Here, we performed next-generation RNA sequencing and comprehensive bioinformatics analyses to characterize the transcriptome profiles, including mRNAs and long noncoding RNAs (lncRNAs), in skeletal muscle of rainbow trout injected with E2. A total of 226 lncRNAs and 253 mRNAs were identified as differentially regulated. We identified crucial pathways, including several signal transduction pathways, hormone response, oxidative response and protein, carbon and fatty acid metabolism pathways. Subsequently, a functional lncRNA-mRNA co-expression network was constructed, which consisted of 681 co-expression relationships between 164 lncRNAs and 201 mRNAs. Moreover, a lncRNA-pathway network was constructed. A total of 65 key lncRNAs were identified that regulate 20 significantly enriched pathways. Overall, our analysis provides insights into mRNA and lncRNA networks in rainbow trout skeletal muscle and their regulation by E2 while understanding the molecular mechanism of lncRNAs