Browsing by Subject "Gene ontology"

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Open Access
An integrative framework for clinical diagnosis and knowledge discovery from exome sequencing data
(2024-02) Shojaei, Mona; Mohammadvand, Navid; Dogan, Tunca; Alkan, Can; Atalay, Rengül Çetin; Acar, Aybar C.
Non-silent single nucleotide genetic variants, like nonsense changes and insertion-deletion variants, that affect protein function and length substantially are prevalent and are frequently misclassified. The low sensitivity and specificity of existing variant effect predictors for nonsense and indel variations restrict their use in clinical applications. We propose the Pathogenic Mutation Prediction (PMPred) method to predict the pathogenicity of single nucleotide variations, which impair protein function by prematurely terminating a protein's elongation during its synthesis. The prediction starts by monitoring functional effects (Gene Ontology annotation changes) of the change in sequence, using an existing ensemble machine learning model (UniGOPred). This, in turn, reveals the mutations that significantly deviate functionally from the wild-type sequence. We have identified novel harmful mutations in patient data and present them as motivating case studies. We also show that our method has increased sensitivity and specificity compared to state-of-the-art, especially in single nucleotide variations that produce large functional changes in the final protein. As further validation, we have done a comparative docking study on such a variation that is misclassified by existing methods and, using the altered binding affinities, show how PMPred can correctly predict the pathogenicity when other tools miss it. PMPred is freely accessible as a web service at https://pmpred.kansil.org/, and the related code is available at https://github.com/kansil/PMPred
Open Access
Identification of differentially expressed microRNAs during lipotoxic endoplasmic reticulum stress in RAW264.7 macrophages
(Turkish Biochemistry Society, 2016-06) Nadir, M.; Tufanlı, Ö.; Erbay, E.; Atalay, A.
Objective: Increased fatty acids in the circulation and their accumulation in non-adipose tissues play a significant role in the development of obesity related metabolic and inflammatory disorders such as insulin resistance, diabetes and atherosclerosis. While fat tissue has the ability to store excess fatty acids, uptake of excess fatty acids to other tissues burdens intracellular metabolic organelles such as mitochondria and endoplasmic reticulum (ER), leading to stress response and lipotoxic cell death. Unfolded protein response (UPR) is a key adaptation of the ER to stress. It is still not completely clear how lipids engage the UPR and how UPR manages both the adaptive and destructive consequences under its control. Increasing evidence point to the importance of miRNA regulation of the UPR as well as UPR’s role in miRNA biogenesis. In order to understand how lipids engage the UPR, we set forth to identify microRNAs regulated by lipotoxic ER stress in macrophages. Methods: We stressed the mouse macrophage cell line (RAW 264.7) with a saturated fatty acid, 500μM palmitate, reflecting the levels found in the circulation of obese patients. We analyzed the microRNAome profiles of this cell line using QRT-PCR based miScript miRNA PCR array which contained all known mouse microRNAs in miRBase release16 and performed pathway analysis for potential targets. Results: 227 microRNAs showed altered expression levels; 43 microRNAs above 2 fold difference and 13 microRNAs 3-24 fold difference. Pathway analysis enriched the target mRNAs of these lipotoxic ER stress associated miRNAs. Conclusion: When exposed to high concentrations of saturated fatty acids that can induce ER stress, macrophages display a dynamic range of changes in their microRNAome profiles. Our findings reflect the consequences of lipotoxic stress on circulating monocytes and tissue-associated macrophages in obesity. Further studies are needed to deliniate which UPR arm is reponsible for the microRNA changes reported here.