Volume 7, Issue 1, June 2019, Page: 5-10
Prediction of Single Nucleotide Polymorphisms in TNFSF4 and Confirmation of Its Relationship with AITD and SLE: Bioinformatics Approach
Sevgi Kalkanli Tas, Department of Immunology, Faculty of Medicine, University of Health Sciences, Istanbul, Turkey
Eylem Cagiltay, Department of Endocrinology, Sultan Abdulhamid Han Training & Research Hospital, Istanbul, Turkey
Duygu Kirkik, Department of Medical Biology, Faculty of Medicine, University of Health Sciences, Istanbul Turkey
Nevin Kalkanli, Department of Dermatology, Ozel Diyarlife Hospital, Diyarbakir, Turkey
Received: Jun. 27, 2019;       Accepted: Jul. 17, 2019;       Published: Jul. 30, 2019
DOI: 10.11648/j.cbb.20190701.12      View  570      Downloads  118
Tumor Necrosis Factor Ligand Superfamily Member4 (TNFSF4) has a huge family of physically homologous transmembrane proteins that regulate various functions in responding cells containing proliferation, differentiation, apoptosis, and inflammatory gene expression. TNFSF4 can play significant role in inflammatory diseases that its polymorphisms of the TNFSF4 gene are mostly related with Sjogren's syndrome, and systemic lupus erythematosus (SLE). The aim of this study is to investigate the genetic variations that may alter the expression, function and role of the TNFSF4 by using in silico methods. Single Nucleotide Polymorphisms (SNPs) on TNFSF4 are analyzed by GeneMania, SIFT, PolyPhen2, UTRscan programme, U.S. National Library of Medicine Database, ClinVar. 37 variants of TNFSF4 were found that among these 9 missense, 8 coding synonymous, 1 coding, 1 splice-3, 1 UTR-3, 11 intron, 5 UTR-5 variants. Moreover, two of them SNPs that these are rs199835957, rs372063551 were detected probably damaging by PolyPhen2 and they should be noted that vital candidates in causing diseases related to TNFSF4 and they were identified missense variants that weren’t reported in ClinVar. In the future, genes of TNFSF4, TNFSFR and CD40 may be studied on polymorphisms with experimental analysis in order to contribute to science by helping to identify disease pathogenesis.
AITD, SLE, TNFSF4, Bioinformatics, in silico
To cite this article
Sevgi Kalkanli Tas, Eylem Cagiltay, Duygu Kirkik, Nevin Kalkanli, Prediction of Single Nucleotide Polymorphisms in TNFSF4 and Confirmation of Its Relationship with AITD and SLE: Bioinformatics Approach, Computational Biology and Bioinformatics. Vol. 7, No. 1, 2019, pp. 5-10. doi: 10.11648/j.cbb.20190701.12
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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