Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2015, Article ID 359835, 17 pages
http://dx.doi.org/10.1155/2015/359835
Research Article

How to Use SNP_TATA_Comparator to Find a Significant Change in Gene Expression Caused by the Regulatory SNP of This Gene’s Promoter via a Change in Affinity of the TATA-Binding Protein for This Promoter

1Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
2Department of Natural Sciences, Novosibirsk State University, Novosibirsk 630090, Russia
3Children’s Hospital Los Angeles, University of Southern California, Los Angeles, CA 90027, USA

Received 3 July 2015; Accepted 24 August 2015

Academic Editor: Jorge H. Leitão

Copyright © 2015 Mikhail Ponomarenko et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The use of biomedical SNP markers of diseases can improve effectiveness of treatment. Genotyping of patients with subsequent searching for SNPs more frequent than in norm is the only commonly accepted method for identification of SNP markers within the framework of translational research. The bioinformatics applications aimed at millions of unannotated SNPs of the “1000 Genomes” can make this search for SNP markers more focused and less expensive. We used our Web service involving Fisher’s -score for candidate SNP markers to find a significant change in a gene’s expression. Here we analyzed the change caused by SNPs in the gene’s promoter via a change in affinity of the TATA-binding protein for this promoter. We provide examples and discuss how to use this bioinformatics application in the course of practical analysis of unannotated SNPs from the “1000 Genomes” project. Using known biomedical SNP markers, we identified 17 novel candidate SNP markers nearby: rs549858786 (rheumatoid arthritis); rs72661131 (cardiovascular events in rheumatoid arthritis); rs562962093 (stroke); rs563558831 (cyclophosphamide bioactivation); rs55878706 (malaria resistance, leukopenia), rs572527200 (asthma, systemic sclerosis, and psoriasis), rs371045754 (hemophilia B), rs587745372 (cardiovascular events); rs372329931, rs200209906, rs367732974, and rs549591993 (all four: cancer); rs17231520 and rs569033466 (both: atherosclerosis); rs63750953, rs281864525, and rs34166473 (all three: malaria resistance, thalassemia).