Obesity-related known and candidate SNP markers can significantly change affinity of TATA-binding protein for human gene promoters

BMC Genomics

Research

Petr M Ponomarenko¹  Olga V Arkova²  Ludmila K Savinkova²  Tatjana V Arshinova²  Irina A Drachkova²  Dmitry A Rasskazov²  Nikolay A Kolchanov³  Mikhail P Ponomarenko⁴ 

[1] Children's Hospital Los Angeles, University of Southern California, 4640 Hollywood Boulevard, 90027, Los Angeles, CA, USA;Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10 Lavrentyeva Avenue, 630090, Novosibirsk, Russia;Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10 Lavrentyeva Avenue, 630090, Novosibirsk, Russia;Novosibirsk State University, 2 Pirogova Street, 630090, Novosibirsk, Russia;Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10 Lavrentyeva Avenue, 630090, Novosibirsk, Russia;Novosibirsk State University, 2 Pirogova Street, 630090, Novosibirsk, Russia;Laboratory of Evolutionary Bioinformatics and Theoretical Genetics, Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10 Lavrentyev Avenue, 630090, Novosibirsk, Russia;

关键词: Obesity;    gene;    promoter;    TATA-binding protein;    TBP;    single nucleotide polymorphism;    SNP;    TBP/promoter affinity change;    statistical significance;    candidate SNP marker;    in silico;    in vitro;   

DOI  :  10.1186/1471-2164-16-S13-S5

来源: Springer

【 摘 要 】

BackgroundObesity affects quality of life and life expectancy and is associated with cardiovascular disorders, cancer, diabetes, reproductive disorders in women, prostate diseases in men, and congenital anomalies in children. The use of single nucleotide polymorphism (SNP) markers of diseases and drug responses (i.e., significant differences of personal genomes of patients from the reference human genome) can help physicians to improve treatment. Clinical research can validate SNP markers via genotyping of patients and demonstration that SNP alleles are significantly more frequent in patients than in healthy people. The search for biomedical SNP markers of interest can be accelerated by computer-based analysis of hundreds of millions of SNPs in the 1000 Genomes project because of selection of the most meaningful candidate SNP markers and elimination of neutral SNPs.ResultsWe cross-validated the output of two computer-based methods: DNA sequence analysis using Web service SNP_TATA_Comparator and keyword search for articles on comorbidities of obesity. Near the sites binding to TATA-binding protein (TBP) in human gene promoters, we found 22 obesity-related candidate SNP markers, including rs10895068 (male breast cancer in obesity); rs35036378 (reduced risk of obesity after ovariectomy); rs201739205 (reduced risk of obesity-related cancers due to weight loss by diet/exercise in obese postmenopausal women); rs183433761 (obesity resistance during a high-fat diet); rs367732974 and rs549591993 (both: cardiovascular complications in obese patients with type 2 diabetes mellitus); rs200487063 and rs34104384 (both: obesity-caused hypertension); rs35518301, rs72661131, and rs562962093 (all: obesity); and rs397509430, rs33980857, rs34598529, rs33931746, rs33981098, rs34500389, rs63750953, rs281864525, rs35518301, and rs34166473 (all: chronic inflammation in comorbidities of obesity). Using an electrophoretic mobility shift assay under nonequilibrium conditions, we empirically validated the statistical significance (α < 0.00025) of the differences in TBP affinity values between the minor and ancestral alleles of 4 out of the 22 SNPs: rs200487063, rs201381696, rs34104384, and rs183433761. We also measured half-life (t1/2), Gibbs free energy change (ΔG), and the association and dissociation rate constants, ka and kd, of the TBP-DNA complex for these SNPs.ConclusionsValidation of the 22 candidate SNP markers by proper clinical protocols appears to have a strong rationale and may advance postgenomic predictive preventive personalized medicine.

【 授权许可】

Unknown   
© Arkova et al. 2015. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.