Biyoinformatik yöntemler yardımıyla, CD40 polimorfizmlerinin tespiti ve olası hastalıklarla ilişkinin araştırılması

Abstract

Giriş: Cluster of differentiation 40 olgun B hücreleri, monositler, dendritik hücreler ve sinyal iletimi ile ilgili epitel hücrelerde bulunan ve hücre aktivasyonuna, çoğalmasına, yapışmasına veya farklılaşmasına yol açan tip I transmembran proteinidir ve cluster of differentiation 40; B hücreli kronik lenfositik lösemiler, lenfomalar ve bazı karsinomlarda eksprese edilir. Bu çalışmada amaç; cluster of differentiation 40’ın biyoinformatik yöntemler yardımıyla tek nükleotid değişimlerinin bulunması ve olası hastalıklarla ilişkilerinin araştırılmasıdır. Gereç ve Yöntem: Çalışmamızda; cluster of differentiation 40’ın olası genlerle ilişkisini araştırmak için GeneMANIA, benzer fonksiyona sahip muhtemel ilişkili dizileri seçmek için SIFT, popülasyonlara özel değişikleri analiz etmek ve şüpheli tek nükleotid değişimlerinin tespiti için Exome Variant Server, 3’UTR tek nükleotid değişimlerinin miRNA bağlanması üzerindeki etkisini tahmin etmek için mr tek nükleotid değişimlerinin Software, tek nükleotid değişimlerde untranslated bölgelerin analizi için UTRscan, proteindeki potansiyel ubikuitinasyon bölgesinin tahmini için UbPred ve protein domainin fonksiyonel karakterizasyonunu tanımlamak için Prosite kullanıldı. Bulgular: Çalışmamızda farklılaşma 40 geni kümesi için toplam 85 adet tek nükleotid polimorfizmi ve rs147677886, rs11569321, rs7273698, rs11086998 ve rs139300926 şüpheli tek nükleotid polimorfizmleri olarak tespit edildi. Ayrıca, bu tek nükleotid polimorfizmleri multipl skleroz (MS), romatoid artrit (RA) ve Kawasaki hastalığı ile bağlantılı olabilir. Sonuç: Biyoinformatik yöntemlerle tespit ettiğimiz 40 farklılaşma gen kümesinin tek nükleotid polimorfizmleri ile ilgili literatürde şu anda herhangi bir çalışma bulunmamaktadır. Gelecekte bu çalışmayı laboratuvarda deneysel olarak değerlendirmeyi ve popülasyona özel çalışmalara katkı sağlamayı hedefliyoruz.

Keywords

• Biyoinformatik
• CD40
• SNP
• mutasyon
• in silico

Detection of CD40 polymorphisms and investigation of their relationship with possible diseases by bioinformatics methods

Abstract

Introduction: Cluster of differentiation 40 is a type I transmembrane protein present on B cells, macrophages, dendritic cells, and endothelial cells, which leads to cell activation, proliferation, adhesion or differentiation. Previous studies have been shown that cluster of differentiation 40 polymorphisms have an effect on some autoimmune diseases. The purpose of this study is to investigate all single nucleotide polymorphisms found on cluster of differentiation 40 gene and their relationship with possible diseases by bioinformatics methods. Material and Method: In our study, while GeneMANIA was used to investigate the relationship between cluster of differentiation 40 gene with other genes, SIFT was employed to select sequences with similar functions as cluster of differentiation 40 gene. Exome cariant server was used for the detection of changes between populations and suspected single nucleotide polymorphisms. Mr single nucleotide polymorphisms Software was used to predict the effect of binding of 3’untranslated regions single nucleotide polymorphisms to miRNA. In order to analyze the untranslated regions on single nucleotide polymorphisms, UTRscan tool was used. UbPred was used for the estimation of the potential ubiquitination site on proteins, and Prosite was used to define the functional characterization of the protein domain. Results: In our study, a total of 85 single nucleotide polymorphisms were found for cluster of differentiation 40 gene, and rs147677886, rs11569321, rs7273698, rs11086998, and rs139300926 were detected as suspected single nucleotide polymorphisms. Moreover, these single nucleotide polymorphisms may be associated with multiple sclerosis (MS), rheumatoid arthritis (RA), and Kawasaki disease. Conclusion: Currently, there are no studies in the literature about single nucleotide polymorphisms of cluster of differentiation 40 gene that we detected by bioinformatics methods. In the future, we aim to evaluate this study experimentally in the laboratory and contribute to population-specific studies.

Keywords

• SNP
• in silico
• Bioinformatics
• CD40
• mutation

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