Tag Single Nucleotide Polymorphisms Selection Research Articles

Association of TGFBR2 gene polymorphisms (rs6785358 and rs764522) with congenital heart disease susceptibility in Egyptians

Aim: Transforming growth factor beta (TGF-β) receptor II (TGFBR2) is a basic constituent of TGF-β signalling pathway and is important in heart development. This study investigates the relationship between TGFBR2 gene variance and congenital heart defects (CHD) among Egyptians. Methods: The study involved 75 CHD-affected subjects and 100 healthy controls. Genotyping of two selected tag single nucleotide polymorphisms (tagSNPs, rs6785358, rs764522) within the TGFBR2 gene was conducted using polymerase chain reaction-restriction fragment length polymorphism method (PCR-RFLP) assays. Results: Significant genotype differences were found for rs764522 and rs6785358 (P < 0.05). In the case of rs6785358, the G/G genotype was more prevalent in cases than controls (18.7% vs. 4.0%). This significance was observed in both the codominant model [A/A vs. A/G vs. G/G; odds ratio (OR) = 0.20, 95% confidence interval (CI) = 0.06–0.66, P = 0.0073] and the recessive model (A/A + A/G vs. G/G; OR = 0.19, 95% CI = 0.06–0.60, P = 0.0018). For rs764522, the G/G genotype was more prevalent in cases than controls (21.3% vs. 0.0%). Significant associations were observed in the codominant model (C/C vs. C/G vs. G/G; OR = 0.43, 95% CI = 0.02–0.90, P < 0.0001), as well as in the dominant model (C/C vs. C/G + G/G) and recessive model (C/C + C/G vs. G/G; P < 0.0001). Gender-specific analysis indicated that the C/G genotype was less common in male cases compared to females and controls (OR = 0.24, 95% CI = 0.07–0.84). For rs6785358, the G/G genotype frequency was higher in male cases compared to females and controls (OR = 0.10, 95% CI = 0.01–0.88 and OR = 0.22, 95% CI = 0.05–0.94, respectively). Conclusions: These findings indicate that TGFBR2 gene SNPs (rs6785358 and rs764522) may be risk factors for CHD in Egyptians.

Assessing effectiveness of many-objective evolutionary algorithms for selection of tag SNPs.

Studies on genome-wide associations help to determine the cause of many genetic diseases. Genome-wide associations typically focus on associations between single-nucleotide polymorphisms (SNPs). Genotyping every SNP in a chromosomal region for identifying genetic variation is computationally very expensive. A representative subset of SNPs, called tag SNPs, can be used to identify genetic variation. Small tag SNPs save the computation time of genotyping platform, however, there could be missing data or genotyping errors in small tag SNPs. This study aims to solve Tag SNPs selection problem using many-objective evolutionary algorithms. Tag SNPs selection can be viewed as an optimization problem with some trade-offs between objectives, e.g. minimizing the number of tag SNPs and maximizing tolerance for missing data. In this study, the tag SNPs selection problem is formulated as a many-objective problem. Nondominated Sorting based Genetic Algorithm (NSGA-III), and Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), which are Many-Objective evolutionary algorithms, have been applied and investigated for optimal tag SNPs selection. This study also investigates different initialization methods like greedy and random initialization. optimization. The evaluation measures used for comparing results for different algorithms are Hypervolume, Range, SumMin, MinSum, Tolerance rate, and Average Hamming distance. Overall MOEA/D algorithm gives superior results as compared to other algorithms in most cases. NSGA-III outperforms NSGA-II and other compared algorithms on maximum tolerance rate, and SPEA2 outperforms all algorithms on average hamming distance. Experimental results show that the performance of our proposed many-objective algorithms is much superior as compared to the results of existing methods. The outcomes show the advantages of greedy initialization over random initialization using NSGA-III, SPEA2, and MOEA/D to solve the tag SNPs selection as many-objective optimization problem.

LmTag: functional-enrichment and imputation-aware tag SNP selection for population-specific genotyping arrays.

Despite the rapid development of sequencing technology, single-nucleotide polymorphism (SNP) arrays are still the most cost-effective genotyping solutions for large-scale genomic research and applications. Recent years have witnessed the rapid development of numerous genotyping platforms of different sizes and designs, but population-specific platforms are still lacking, especially for those in developing countries. SNP arrays designed for these countries should be cost-effective (small size), yet incorporate key information needed to associate genotypes with traits. A key design principle for most current platforms is to improve genome-wide imputation so that more SNPs not included in the array (imputed SNPs) can be predicted. However, current tag SNP selection methods mostly focus on imputation accuracy and coverage, but not the functional content of the array. It is those functional SNPs that are most likely associated with traits. Here, we propose LmTag, a novel method for tag SNP selection that not only improves imputation performance but also prioritizes highly functional SNP markers. We apply LmTag on a wide range of populations using both public and in-house whole-genome sequencing databases. Our results show that LmTag improved both functional marker prioritization and genome-wide imputation accuracy compared to existing methods. This novel approach could contribute to the next generation genotyping arrays that provide excellent imputation capability as well as facilitate array-based functional genetic studies. Such arrays are particularly suitable for under-represented populations in developing countries or non-model species, where little genomics data are available while investment in genome sequencing or high-density SNP arrays is limited. $\textrm{LmTag}$ is available at: https://github.com/datngu/LmTag.

Evaluation of Bayesian methods of genomic association via chromosomic regions using simulated data

The development of efficient methods for genome–wide association studies (GWAS) between quantitative trait loci (QTL) and genetic values is extremely important to animal and plant breeding programs. Bayesian approaches that aim to select regions of single nucleotide polymorphisms (SNPs) proved to be efficient, indicating genes with important effects. Among the selection criteria for SNPs or regions, selection criterion by percentage of variance can be explained by genomic regions (%var), selection of tag SNPs, and selection based on the window posterior probability of association (WPPA). To also detect potentially associated regions, we proposed measuring posterior probability of the interval PPint), which aims to select regions based on the markers of greatest effects. Therefore, the objective of this work was to evaluate these approaches, in terms of efficiency in selecting and identifying markers or regions located within or close to genes associated with traits. This study also aimed to compare these methodologies with single–marker analyses. To accomplish this, simulated data were used in six scenarios, with SNPs allocated in non–overlapping genomic regions. Considering traits with oligogenic inheritance, WPPA criterion followed by %var and PPint criteria were shown to be superior, presenting higher values of detection power, capturing higher percentages of genetic variance and larger areas. For traits with polygenic inheritance, PPint and WPPA criteria were considered superior. Single–marker analyses identified SNPs associated only in oligogenic inheritance scenarios and was lower than the other criteria.

TagSNP-set selection for genotyping using integrated data

Single-nucleotide polymorphisms (SNPs) are vital in identifying genetic level variations in complex disease. It was found that the information of SNPs on adjacent or identical genes can be represented by a few tagSNPs (called tag SNP-set or tagSNP-set). In this work, we propose a novel method called TagSNP-set Selection by Optimal Iteration with Linkage Disequilibrium (TSOILD) and develop a quantificationally analytical tagSNP-set prediction method called Physical Distance-Linkage Disequilibrium Prediction Method (PDLDPM). To verify the validity of TSOILD method and PDLDPM, a large amount of test data is generated by simulation software HAPGEN2. According to the experimental results, the prediction accuracy of TSOILD is improved by 6.73%, 3.19%, 6.52% and 1.72% over the Random Sampling, Genetic Algorithm (GA) , Greedy Algorithm and TagSNP-Set Selection Method with Maximum Information (TSMI) respectively. In addition, PDLDPM, Linkage Coverage and selection of tag SNPs to maximize prediction accuracy (STAMPA) are used to evaluate the tagSNP-set selected by Random Sampling, GA, Greedy Algorithm and TSMI. Results show that the PDLDPM performs better than the other two methods. These methods provide effective assistance for the study of genetic level variation of complex diseases.

Effects of AQP4 and KCNJ10 Gene Polymorphisms on Drug Resistance and Seizure Susceptibility in Chinese Han Patients with Focal Epilepsy.

Background and PurposeEpilepsy is a common chronic neurological disorder. About one third of epilepsy patients will suffer from drug resistance after rational selection of antiepileptic drug treatment. The formation of drug-resistant epilepsy has quite a few causes of which genetic factors are considered to be the most important. Previous studies have suggested that the aquaporin 4(AQP4) and inward rectifier potassium ion channel Kir4.1 (encoded by gene KCNJ10) may act in concert to adjust water homeostasis and concentration of potassium ions in extracellular spaces of the central nervous system. Therefore, these two molecules would play a major role in the regulation of the excitability of neurons. In order to explore the potential mechanism of genetic factors related to AQP4 and Kir4.1, we conducted a study to analyze the effects of the AQP4 and KCNJ10 genes' single nucleotide polymorphisms (SNPs) on epileptic drug resistance and seizure susceptibility in a group of Chinese Han patients with focal epilepsy.Materials and MethodsIn total, 510 patients with focal-onset seizures and 206 healthy controls were recruited. Among the patients, 222 were drug resistant and 288 were responsive. The selection of tag SNPs was based on the Hapmap database and Haploview software. Genotyping of three loci of the AQP4 gene (rs1058424, rs3763043 and rs35931) and nine loci of the KCNJ10 gene (rs12122979, rs1186685, rs6690889, rs2486253, rs1186675, rs12402969, rs12729701, rs1890532 and rs3795339) was conducted on the Sequenom MassARRAY iPLEX platform.ResultsThe distribution of genotype and allele frequencies of selected SNP loci of AQP4 and KCNJ10 genes showed no significant difference between the drug-resistant and drug-responsive groups (p>0.05), and no significant difference between all the idiopathic focal epilepsy patients and healthy controls either.ConclusionAQP4 and KCNJ10 genetic polymorphisms may not be associated with drug resistance or seizure susceptibility of focal epilepsy in the Chinese Han population.

Common variants in glyoxalase I do not increase chronic pancreatitis risk.

IntroductionChronic pancreatitis (CP) may be caused by oxidative stress. An important source of reactive oxygen species (ROS) is the methylglyoxal-derived formation of advanced glycation endproducts (AGE). Methylglyoxal is detoxified by Glyoxalase I (GLO1). A reduction in GLO1 activity results in increased ROS. Single nucleotide polymorphisms (SNPs) of GLO1 have been linked to various inflammatory diseases. Here, we analyzed whether common GLO1 variants are associated with alcoholic (ACP) and non-alcoholic CP (NACP).MethodsUsing melting curve analysis, we genotyped a screening cohort of 223 ACP, 218 NACP patients, and 328 controls for 11 tagging SNPs defined by the SNPinfo LD TAG SNP Selection tool and the functionally relevant variant rs4746. For selected variants the cohorts were extended to up to 1,441 patient samples.ResultsIn the ACP cohort, comparison of genotypes for rs1937780 between patients and controls displayed an ambiguous result in the screening cohort (p = 0.08). However, in the extended cohort of 1,441 patients no statistically significant association was found for the comparison of genotypes (p = 0.11), nor in logistic regression analysis (p = 0.214, OR 1.072, 95% CI 0.961–1.196). In the NACP screening cohort SNPs rs937662, rs1699012, and rs4746 displayed an ambiguous result when patients were compared to controls in the recessive or dominant model (p = 0.08, 0.08, and 0.07, respectively). Again, these associations were not confirmed in the extended cohorts (rs937662, dominant model: p = 0.07, logistic regression: p = 0.07, OR 1.207, 95% CI 0.985–1.480) or in the replication cohorts for rs4746 (Germany, p = 0.42, OR 1.080, 95% CI 0.673–1.124; France, p = 0.19, OR 0.90, 95% CI 0.76–1.06; China, p = 0.24, OR 1.18, 95% CI 0.90–1.54) and rs1699012 (Germany, Munich; p = 0.279, OR 0.903, 95% CI 0.750–1.087).ConclusionsCommon GLO1 variants do not increase chronic pancreatitis risk.

Tag SNP selection for prediction of tick resistance in Brazilian Braford and Hereford cattle breeds using Bayesian methods

BackgroundCattle resistance to ticks is known to be under genetic control with a complex biological mechanism within and among breeds. Our aim was to identify genomic segments and tag single nucleotide polymorphisms (SNPs) associated with tick-resistance in Hereford and Braford cattle. The predictive performance of a very low-density tag SNP panel was estimated and compared with results obtained with a 50 K SNP dataset.ResultsBayesB (π = 0.99) was initially applied in a genome-wide association study (GWAS) for this complex trait by using deregressed estimated breeding values for tick counts and 41,045 SNP genotypes from 3455 animals raised in southern Brazil. To estimate the combined effect of a genomic region that is potentially associated with quantitative trait loci (QTL), 2519 non-overlapping 1-Mb windows that varied in SNP number were defined, with the top 48 windows including 914 SNPs and explaining more than 20% of the estimated genetic variance for tick resistance. Subsequently, the most informative SNPs were selected based on Bayesian parameters (model frequency and t-like statistics), linkage disequilibrium and minor allele frequency to propose a very low-density 58-SNP panel. Some of these tag SNPs mapped close to or within genes and pseudogenes that are functionally related to tick resistance. Prediction ability of this SNP panel was investigated by cross-validation using K-means and random clustering and a BayesA model to predict direct genomic values. Accuracies from these cross-validations were 0.27 ± 0.09 and 0.30 ± 0.09 for the K-means and random clustering groups, respectively, compared to respective values of 0.37 ± 0.08 and 0.43 ± 0.08 when using all 41,045 SNPs and BayesB with π = 0.99, or of 0.28 ± 0.07 and 0.40 ± 0.08 with π = 0.999.ConclusionsBayesian GWAS model parameters can be used to select tag SNPs for a very low-density panel, which will include SNPs that are potentially linked to functional genes. It can be useful for cost-effective genomic selection tools, when one or a few key complex traits are of interest.

New multilocus linkage disequilibrium measure for tag SNP selection.

Numerous approaches have been proposed for selecting an optimal tag single-nucleotide polymorphism (SNP) set. Most of these approaches are based on linkage disequilibrium (LD). Classical LD measures, such as D' and r2, are frequently used to quantify the relationship between two marker (pairwise) linkage disequilibria. Despite of their successful use in many applications, these measures cannot be used to measure the LD between multiple-marker. These LD measures need information about the frequencies of alleles collected from haplotype dataset. In this study, a cluster algorithm is proposed to cluster SNPs according to multilocus LD measure which is based on information theory. After that, tag SNPs are selected in each cluster optimized by the number of tag SNPs, prediction accuracy and so on. The experimental results show that this new LD measure can be directly applied to genotype dataset collected from the HapMap project, so that it saves the cost of haplotyping. More importantly, the proposed method significantly improves the efficiency and prediction accuracy of tag SNP selection.

Tag Single-Nucleotide Polymorphism Selection Based on Sparse Representation

Tag Single-Nucleotide Polymorphism Selection Based on Sparse Representation

Effect of ERCC8 tagSNPs and their association with H. pylori infection, smoking, and alcohol consumption on gastric cancer and atrophic gastritis risk.

Excision repair cross-complementing group 8 (ERCC8) plays a critical role in DNA repair. Genetic polymorphisms in ERCC8 may contribute to the risk of cancer development. We selected tag single nucleotide polymorphisms (tagSNPs) in Chinese patients from the HapMap database to investigate associations with gastric cancer and its precursors. Genomic DNA was extracted from 394 controls, 394 atrophic gastritis, and 394 gastric cancer cases in northern Chinese patients, and genotypes were identified using the Sequenom MassARRAY system. We found that the ERCC8 rs158572 GG+GA genotype showed a 1.651-fold (95 % confidence interval (CI) = 1.109-2.457, P = 0.013) increased risk of gastric cancer compared with the AA genotype, especially in diffuse type. Stratified analysis comparing the common genotype revealed significantly increased gastric cancer risk in males and individuals older than 50 years with rs158572 GA/GG/GG+GA genotypes, while individuals older than 50 years with rs158916 CT/CC+CT genotypes were less susceptible to atrophic gastritis. Haplotype analysis showed that the G-T haplotype was associated with increased risk of gastric cancer. Statistically significant interactions between the two ERCC8 tagSNPs and Helicobacter pylori infection were observed for gastric cancer and atrophic gastritis risk (P < 0.05). Smokers and drinkers with ERCC8 rs158572 GG+GA genotype were more susceptible to gastric cancer compared with non-smokers and non-drinkers homozygous for AA. Our findings suggested that ERCC8 rs158572 and rs158916, alone or together with environmental factors, might be associated with gastric cancer and atrophic gastritis susceptibility. Further validation of our results in larger populations along with additional studies evaluating the underlying molecular function is required.

Association Study of Serotonin Transporter SLC6A4 Gene with Chinese Han Irritable Bowel Syndrome

ObjectiveIrritable bowel syndrome (IBS) is a common clinical gastrointestinal dysfunction disorders. 5-sertonon (5-hydroxytryptamine, 5-HT) is a very important neurotransmitter, which is involved in gastrointestinal motion and sensation. Solute carrier family 6 member 4 (SLC6A4) gene encode serotonin transporter (SERT) which function is to rapidly reuptake the most of 5-HT. Therefore, it is needed to explore the association between SLC6A4 gene polymorphisms and IBS.Methods119 patients and 238 healthy controls were administrated to detect the SLC6A4 gene polymorphisms including 5-HT-transporter-gene-linked polymorphic region (5-HTTLPR), variable number of tandem repeats (VNTRs) and three selected tag Single Nucleotide Polymorphisms (SNPs) rs1042173, rs3794808, rs2020936 by using polymerase chain reaction (PCR) and TaqMan® SNP Genotyping.ResultsThere were significant difference for 5-HTTLPR between IBS and control groups (X2 = 106.168, P<0.0001). In control group, genotypes were mainly L/L (58.4%), however, the genotypes in IBS were S/S (37.8%). The significant difference was shown in D-IBS subjects when compared to the controls (X2 = 50.850, P<0.0001) for 5-HTTLPR. For STin2 VNTR, rs1042173, rs3794808, and rs2020936 polymorphisms, there were no any significant differences between IBS and control groups. There were no statistical significantly haplotypes for 5-HTTLPR, VNTRs and the three SNPs between IBS and controls.ConclusionThe S allele in 5-HTTLPR was a susceptible allele with Chinese Han IBS, but other associations of VNTRs, three selected Tag SNPs and positive haplotype with IBS were not found. It is indicated that much research are needed to study the relationship between other polymorphisms in SLC6A4 gene and IBS.

Selection of human p75NTR tag SNPs and its biological significance for clinical association studies.

To select tag single nucleotide polymorphisms (SNPs) within and around human p75 neurotrophin receptor (p75NTR) gene in Chinese Han population, the sequence involving p75NTR gene as well as the upstream and downstream of the gene was identified according to the data from National Center for Biotechnology Information (NCBI) GenBank database, and the SNP genotype data involving 63 SNPs in the regions were obtained from Chinese Han Beijing (CHB) population of HapMap database. Then, Haploview (version 4.2) was used to calculate linkage disequilibrium (LD) statistics for the selected 32 common SNPs with a minor allele frequence (MAF) more than 0.05. Haplotype blocks were constructed throughout the p75NTR gene according to the upper and the lower 95% confidence bound of D' value, and the tag SNPs were selected based on the r2 and LOD values between SNPs as well as the results of bioinformatics analysis. The results indicated that five haplotype blocks were constructed within and around p75NTR gene and 12 tag SNPs including rs2537710, rs603769, rs614455, rs2537706, rs534561, rs2072445, rs2072446, rs7219709, rs734194, rs741071, rs741073 and rs2671641 were selected to represent the other 51 SNPs in p75NTR gene. Therefore, the 12 selected SNPs may act as tag SNPs for the entire p75NTR gene in Chinese Han population, which will provide an effective way to select tag SNPs in a whole gene, and its biological significance is to further guide the clinical association studies between the candidate gene and disease susceptibility.

How to Select Tag SNPs in Genetic Association Studies? The CLONTagger Method with Parameter Optimization

Selection of genetic variants is a crucial first step in the rational design of studies aimed at explaining individual differences in susceptibility to complex human diseases or health intervention outcomes; for example, in the emerging fields of pharmacogenomics, nutrigenomics, and vaccinomics. While single nucleotide polymorphisms (SNPs) are frequently employed in these studies, the cost of genotyping a huge number of SNPs remains a limiting factor, particularly in low and middle income countries. Therefore, it is important to detect a subset of SNPs to represent the rest of SNPs with maximum possible accuracy. The present study introduces a new method, CLONTagger with parameter optimization, which uses Support Vector Machine (SVM) to predict the rest of SNPs and Clonal Selection Algorithm (CLONALG) to select tag SNPs. Furthermore, the Particle Swarm Optimization algorithm is preferred for the optimization of C and γ parameters of the Support Vector Machine. Additionally, using many datasets, we compared the proposed new method with the tag SNP selection algorithms present in literature. Our results suggest that the CLONTagger with parameter optimization can identify tag SNPs with better prediction accuracy than other methods. Application-oriented studies are warranted to evaluate the utility of this method in future research in human genetics and study of the genetic components of variable responses to drugs, nutrition, and vaccines.

Abstract 1668: Understanding cancer associated SNPs in the TERT-CLPTM1L locus through population genetics

Abstract Telomeres form the ends of eukaryotic chromosomes and are vital in maintaining genetic integrity. TERT encodes the telomerase reverse transcriptase, which is responsible for maintaining telomere ends by addition of (TTAGGG)n nucleotide repeats at the telomere. Recent genome-wide association studies have found common genetic variants at theTERT-CLPTM1L locus (5p15.33) associated with increased risk of several cancers, including glioma, basal cell carcinoma, testicular, pancreatic, breast and lung cancers, and possibly overall cancer risk. Our prior studies of common single nucleotide polymorphisms (SNPs) in the TERT gene region found low differentiation among populations and higher than expected levels of haplotype diversity in data from the Human Genome Diversity Panel (HGDP) and the International HapMap Project. In the current study we significantly expanded the population genetic analyses by utilizing data from the 1000 Genomes Project (2011 October release). Genetic variation from a total of 1092 individuals from 14 populations with European, East Asian, West African or American ancestry was evaluated. Data were acquired for 3468 variants in a 206kb region on 5p15.33, which included the TERT-CLPTM1L gene and flanking regions. The GLU genetics’ ld.tagzilla module was used for the tag analysis with a linkage disequilibrium (LD) pairwise r2 threshold of 0.8. Arlequin (3.5) and Genepop (4.1) packages were used to estimate diversity, LD, heterozygosity, and differentiation (FST) among populations. Pairwise LD was analyzed separately for the 4 ancestral groups (European, East Asian, West African and American) and used to select tag SNPs for each region. The 4 ancestral groups had differing LD patterns with the lowest level of LD occurring in individuals from Africa, as expected. These data were used to create the appropriate haplotype-tagging SNPs for the TERT-CLPTM1L region in each population; we present recommended tagging SNPs by ancestral group. The TERT-CLPTM1L gene region had low nucleotide diversity (mean 2 x 10−4) and differentiation among ancestral groups (90% of loci in this region had FST &amp;lt;0.10). The limited diversity in this region may be due to its critical role in telomere maintenance and chromosomal stability. The recently identified cancer associated SNPs in this region had differing genotype frequencies among ancestral groups. Variation in cancer associated alleles among ancestral groups may correlate to varying disease risks. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1668. doi:1538-7445.AM2012-1668

Genetic polymorphisms in homologous recombination repair genes in healthy Slovenian population and their influence on DNA damage

BackgroundHomologous recombination (HR) repair is an important mechanism involved in repairing double-strand breaks in DNA and for maintaining genomic stability. Polymorphisms in genes coding for enzymes involved in this pathway may influence the capacity for DNA repair. The aim of this study was to select tag single nucleotide polymorphisms (SNPs) in specific genes involved in HR repair, to determine their allele frequencies in a healthy Slovenian population and their influence on DNA damage detected with comet assay.Materials and methodsIn total 373 individuals were genotyped for nine tag SNPs in three genes: XRCC3 722C>T, XRCC3 -316A>G, RAD51 -98G>C, RAD51 -61G>T, RAD51 1522T>G, NBS1 553G>C, NBS1 1197A>G, NBS1 37117C>T and NBS1 3474A>C using competitive allele-specific amplification (KASPar assay). Comet assay was performed in a subgroup of 26 individuals to determine the influence of selected SNPs on DNA damage.ResultsWe observed that age significantly affected genotype frequencies distribution of XRCC3 -316A>G (P = 0.039) in healthy male blood donors. XRCC3 722C>T (P = 0.005), RAD51 -61G>T (P = 0.023) and NBS1 553G>C (P = 0.008) had a statistically significant influence on DNA damage.ConclusionsXRCC3 722C>T, RAD51 -61G>T and NBS1 553G>C polymorphisms significantly affect the repair of damaged DNA and may be of clinical importance as they are common in Slovenian population.

Relationship between the 17q21 locus and adult asthma in a Czech population

Several whole-genome association studies have shown a significant link between childhood asthma and the 17q12 chromosome region. We selected tagging single nucleotide polymorphisms (SNPs) in the ORMDL3 gene (17q12) to investigate gene variability in relation to adult allergic asthma and asthma/atopy traits in a Czech Caucasian population of adults. We conducted a case-control association study comprising 668 unrelated subjects (337 asthmatic and 331 control subjects). Four selected SNPs (rs17608925, rs12603332, rs8076131, and rs3169572) were genotyped using the TaqMan SNP Genotyping Assays. The single locus analysis showed only a borderline association between rs3169572 variant and asthma ( p = 0.030, p corr > 0.05). However, seven different haplotypes were identified; among them, the TTAA haplotype was marginally associated with asthma ( p = 0.045, p corr > 0.05) and TCAG haplotype was significantly associated with asthma in males ( p = 0.009, p corr < 0.05, odds ratio = 1.48, 95% confidence interval = 1.10–2.00). In addition, associations between the ORMDL3 genotypes and the total IgE level ( p = 0.05, p corr > 0.05) and hypersensitivity to the pollen ( p = 0.007, p corr < 0.05) were established. However, no relationship between ORMDL3 SNPs and the pulmonary functions was found ( p > 0.05). These findings suggest that the genetic variability in the 17q21 region may be one of the risk factors also for adult asthma, especially in male individuals.

Association of variants in MMEL1 and CTLA4 with rheumatoid arthritis in the Han Chinese population

BackgroundThe genome-wide association study era has made great progress in identifying susceptibility genes and genetic loci for rheumatoid arthritis (RA) in populations of White European ancestry. However, few studies have...

Prioritization of candidate SNPs in colon cancer using bioinformatics tools: An alternative approach for a cancer biologist

The genetics of human phenotype variation and especially, the genetic basis of human complex diseases could be understood by knowing the functions of Single Nucleotide Polymorphisms (SNPs). The main goal of this work is to predict the deleterious non-synonymous SNPs (nsSNPs), so that the number of SNPs screened for association with disease can be reduced to that most likely alters gene function. In this work by using computational tools, we have analyzed the SNPs that can alter the expression and function of cancerous genes involved in colon cancer. To explore possible relationships between genetic mutation and phenotypic variation, different computational algorithm tools like Sorting Intolerant from Tolerant (evolutionary-based approach), Polymorphism Phenotyping (structure-based approach), PupaSuite, UTRScan and FASTSNP were used for prioritization of high-risk SNPs in coding region (exonic nonsynonymous SNPs) and non-coding regions (intronic and exonic 5' and 3'-untranslated region (UTR) SNPs). We developed semi-quantitative relative ranking strategy (non availability of 3D structure) that can be adapted to a priori SNP selection or post hoc evaluation of variants identified in whole genome scans or within haplotype blocks associated with disease. Lastly, we analyzed haplotype tagging SNPs (htSNPs) in the coding and untranslated regions of all the genes by selecting the force tag SNPs selection using iHAP analysis. The computational architecture proposed in this review is based on integrating relevant biomedical information sources to provide a systematic analysis of complex diseases. We have shown a "real world" application of interesting existing bioinformatics tools for SNP analysis in colon cancer.

Genetic variation in the RANKL/RANK/OPG signaling pathway is associated with bone turnover and bone mineral density in men

The aim of this study was to determine if single-nucleotide polymorphisms (SNPs) in RANKL, RANK, and OPG influence bone turnover and bone mineral density (BMD) in men. Pairwise tag SNPs (r(2) > or = 0.8) were selected for RANKL, RANK, and OPG and their 10-kb flanking regions. Selected tag SNPs plus five SNPs near RANKL and OPG, associated with BMD in published genome-wide association studies (GWAS), were genotyped in 2653 men aged 40 to 79 years of age recruited for participation in a population-based study of male aging, the European Male Ageing Study (EMAS). N-terminal propeptide of type I procollagen (PINP) and C-terminal cross-linked telopeptide of type I collagen (CTX-I) serum levels were measured in all men. BMD at the calcaneus was estimated by quantitative ultrasound (QUS) in all men. Lumbar spine and total-hip areal BMD (BMD(a)) was measured by dual-energy X-ray absorptiometry (DXA) in a subsample of 620 men. Multiple OPG, RANK, and RANKL SNPs were associated with bone turnover markers. We also identified a number of SNPs associated with BMD, including rs2073618 in OPG and rs9594759 near RANKL. The minor allele of rs2073618 (C) was associated with higher levels of both PINP (beta = 1.83, p = .004) and CTX-I (beta = 17.59, p = 4.74 x 10(-4)), and lower lumbar spine BMD(a) (beta = -0.02, p = .026). The minor allele of rs9594759 (C) was associated with lower PINP (beta = -1.84, p = .003) and CTX-I (beta = -27.02, p = 6.06 x 10(-8)) and higher ultrasound BMD at the calcaneus (beta = 0.01, p = .037). Our findings suggest that genetic variation in the RANKL/RANK/OPG signaling pathway influences bone turnover and BMD in European men.