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Evaluation of Influence of Single Nucleotide Polymorphisms in Cytochrome P450 2B6 on Substrate Recognition Using Computational Docking and Molecular Dynamics Simulation  [PDF]
Kana Kobayashi, Ohgi Takahashi, Masahiro Hiratsuka, Noriyuki Yamaotsu, Shuichi Hirono, Yurie Watanabe, Akifumi Oda
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0096789
Abstract: In this study, we investigated the influence of single nucleotide polymorphisms on the conformation of mutated cytochrome P450 (CYP) 2B6 proteins using molecular dynamics (MD) simulation. Some of these mutations influence drug metabolism activities, leading to individual variations in drug efficacy and pharmacokinetics. Using computational docking, we predicted the structure of the complex between the antimalarial agent artemether and CYP2B6 whose conformations were obtained by MD simulation. The simulation demonstrated that the entire structure of the protein changes even when a single residue is mutated. Moreover, the structural flexibility is affected by the mutations and it may influence the enzyme activity. The results suggest that some of the inactive mutants cannot recognize artemether due to structural changes caused by the mutation.
A Monte Carlo test of linkage disequilibrium for single nucleotide polymorphisms
Hongyan Xu, Varghese George
BMC Research Notes , 2011, DOI: 10.1186/1756-0500-4-124
Abstract: We develop a Monte Carlo based test for LD based on the null distribution of the r2 statistic. Our test is based on r2 and can be reported together with r2. Simulation studies show that it offers slightly better power than existing methods.Our approach provides an alternative test for LD and has been implemented as a R program for ease of use. It also provides a general framework to account for other haplotype inference methods in LD testing.Genetic association studies, especially large-scale genome-wide association studies have become very popular in recent years due to the rapid advancement of genotyping technologies and the completion of the Human Genome Project [1,2]. More than 400 susceptibility regions have been identified through genome-wide association approach. This approach relies on the linkage disequilibrium information between genetic markers, mostly single-nucleotide polymorphisms (SNPs), hence been termed linkage disequilibrium mapping. Linkage disequilibrium (LD) refers to the nonrandom association of alleles at different loci on the same haplotype. The underlying assumption of genetic association studies is that there are some disease causing loci in the genome, and if the SNPs under investigation (i.e. markers) and the disease-causing loci are in close proximity, the marker alleles will be associated with the alleles at the disease-causing loci. In other words, those markers are in LD with the disease causing loci if they are in close proximity. Since markers in high LD are highly correlated, testing the significance of LD between alleles of markers is also useful in finding LD blocks and tag-SNPs. This could reduce the number of markers required in genome-wide studies. In addition to gene mapping, LD information also proves to be useful in evolutionary studies of gene dynamics, tracing human origin and history, and studies of genome structure and forensic science.Consider two bi-allelic SNPs, marker A and marker B. The two alleles at marker A are
Polymorphisms of arylamine N-acetyltransferase2 and risk of lung and colorectal cancer
Mahasneh, Amjad;Jubaili, Amal;El Bateiha, Ahmed;Al-Ghazo, Mohammad;Matalka, Ismail;Malkawi, Mousa;
Genetics and Molecular Biology , 2012, DOI: 10.1590/S1415-47572012005000074
Abstract: the arylamine n-acetyltransferase 2 (nat2) enzymes detoxify a wide range of naturally occurring xenobiotics including carcinogens and drugs. point mutations in the nat2 gene result in the variant alleles m1 (nat2 *5a), m2 (nat2*6a), m3 (nat2*7) and m4 (nat2 *14a) from the wild-type wt (nat2 *4) allele. the current study was aimed at screening genetic polymorphisms of nat2 gene in 49 lung cancer patients, 54 colorectal cancer patients and 99 cancer-free controls, using pcr-rflp. there were significant differences in allele frequencies between lung cancer patients and controls in the wt, m2 and m3 alleles (p < 0.05). however, only m2 and m3 allele frequencies were different between colorectal cancer patients and controls (p < 0.05). there was a marginal significant difference in the distribution of rapid and slow acetylator genotypes between lung cancer patients and controls (p = 0.06 and p = 0.05, respectively), but not between colorectal cancer patients and controls (p = 1.0 and p = 0.95, respectively). risk of lung cancer development was found to be lower in slow acetylators [odds ratio (or): 0.51, 95% confidence interval (95% ci): 0.25, 1.02, p-value = 0.07]. no effect was observed in case of colorectal cancer. our results showed that nat2 genotypes and phenotypes might be involved in lung cancer but not colorectal cancer susceptibility in jordan.
N-Acetyltransferase 2 genetic polymorphisms and risk of colorectal cancer  [cached]
Tiago Donizetti da Silva,Aledson Vitor Felipe,Jacqueline Miranda de Lima,Celina Tizuko Fujiyama Oshima
World Journal of Gastroenterology , 2011,
Abstract: AIM: To investigate the possible association between meat intake, cigarette smoking and N-acetyltransferase 2 (NAT2) genetic polymorphisms on colorectal cancer (CRC) risk.METHODS: Patients with CRC were matched for gender and age to healthy controls. Meat intake and cigarette smoking were assessed using a specific frequency questionnaire. DNA was extracted from peripheral blood and the genotypes of the polymorphism were assessed by polymerase chain reaction-restriction fragment length polymorphism. Five NAT2 alleles were studied (WT, M1, M2, M3 and M4) using specific digestion enzymes.RESULTS: A total of 147 patients with colorectal cancer (76 women and 90 men with colon cancer) and 212 controls were studied. The mean age of the two groups was 62 years. More than half the subjects (59.8% in the case group and 51.9% in the control group) were NAT2 slow acetylators. The odds ratio for colorectal cancer was 1.38 (95% CI: 0.90-2.12) in slow acetylators. Although the number of women was small (n = 76 in the case group), the cancer risk was found to be lower in intermediate (W/Mx) acetylators [odds ratio (OR): 0.55, 95% confidence interval (95% CI): 0.29-1.02]. This difference was not observed in men (OR: 0.56, 95% CI: 0.16-2.00). Among NAT2 fast acetylators (W/W or W/Mx), meat consumption more than 3 times a week increased the risk of colorectal cancer (OR: 2.05, 95% CI: 1.01-4.16). In contrast, cigarette smoking increased the risk of CRC among slow acetylators (OR: 1.97, 95% CI: 1.02-3.79).CONCLUSION: The risk of CRC was higher among fast acetylators who reported a higher meat intake. Slow NAT2 acetylation was associated with an increased risk of CRC.
Genomic lineages of Rhizobium etli revealed by the extent of nucleotide polymorphisms and low recombination
José L Acosta, Luis E Eguiarte, Rosa I Santamaría, Patricia Bustos, Pablo Vinuesa, Esperanza Martínez-Romero, Guillermo Dávila, Víctor González
BMC Evolutionary Biology , 2011, DOI: 10.1186/1471-2148-11-305
Abstract: We identified high levels of DNA polymorphism in R. etli, and found that there was an average divergence of 4% to 6% among the tested strain pairs. DNA recombination events were estimated to affect 3% to 10% of the genomic sample analyzed. In most instances, the nucleotide diversity (π) was greater in DNA segments with recombinant events than in non-recombinant segments. However, this degree of recombination was not sufficiently large to disrupt the congruence of the phylogenetic trees, and further evaluation of recombination in strains quartets indicated that the recombination levels in this species are proportionally low.Our data suggest that R. etli is a species composed of separated lineages with low homologous recombination among the strains. Horizontal gene transfer, particularly via the symbiotic plasmid characteristic of this species, seems to play an important role in diversity but the lineages maintain their evolutionary cohesiveness.Bacterial species typically contain large amounts of genetic variation in the form of single nucleotide polymorphisms (SNPs), which originate by mutation and have dynamics that depend on the balance between natural selection and genetic drift [1,2]. There is some debate on whether or not most of these polymorphisms are selectively neutral at the molecular level [3]. Species have been genetically defined through the analysis of DNA variation using comparative techniques such as hybridization, the sequencing of gene markers, and (more recently) complete genome sequences [4,5]. It has been proposed that similarity values greater than 70% obtained in DNA-DNA hybridization experiments are sufficient to define a coherent group of organisms as belonging to the same species [6]. These estimates are very rough, subject to experimental variation, and they only indirectly measure similarity (i.e. via hybridization efficiency) [7]. A comparative analysis of complete genomes minimizes most of these limitations. Several measures of genomic
Detection for Single Nucleotide Polymorphisms
单核苷酸多态性的研究技术 Detection for Single Nucleotide Polymorphisms

LUO Huai rong,SHI Peng,ZHANG Ya ping,
罗怀容
,施鹏,张亚平

遗传 , 2001,
Abstract: Based on summarizing the single nucleotide polymorphisms (SNP) of human genome,14 methods for detection were reviewed in detail,including the principle,operational point,the advantages and the disadvantages of each method.
Comprehensive Analysis of Single Nucleotide Polymorphisms in Human MicroRNAs  [PDF]
Miao Han, Yun Zheng
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0078028
Abstract: MicroRNAs (miRNAs) are endogenous small non-coding RNAs that repress their targets at post transcriptional level. Single Nucleotide Polymorphisms (SNPs) in miRNAs can lead to severe defects to the functions of miRNAs and might result in diseases. Although several studies have tried to identify the SNPs in human miRNA genes or only in the mature miRNAs, there are only limited endeavors to explain the distribution of SNPs in these important genes. After a genome-wide scan for SNPs in human miRNAs, we totally identified 1899 SNPs in 961 out of the 1527 reported miRNA precursors of human, which is the most complete list of SNPs in human miRNAs to date. More importantly, to explain the distributions of SNPs existed in human miRNAs, we comprehensively and systematically analyzed the identified SNPs in miRNAs from several aspects. Our results suggest that conservation, genomic context, secondary structure, and functional importance of human miRNAs affect the accumulations of SNPs in these genes. Our results also show that the number of SNPs with significantly different frequencies among various populations in the HapMap and 1000 Genome Project data are consistent with the geographical distributions of these populations. These analyses provide a better insight of SNPs in human miRNAs and the spreading of the SNPs in miRNAs in different populations.
Network analysis of single nucleotide polymorphisms in asthma
Jutta Renkonen, Sakari Joenv r , Ville Parviainen, et al
Journal of Asthma and Allergy , 2010, DOI: http://dx.doi.org/10.2147/JAA.S14459
Abstract: work analysis of single nucleotide polymorphisms in asthma Original Research (3678) Total Article Views Authors: Jutta Renkonen, Sakari Joenv r , Ville Parviainen, et al Published Date December 2010 Volume 2010:3 Pages 177 - 186 DOI: http://dx.doi.org/10.2147/JAA.S14459 Jutta Renkonen1,2, Sakari Joenv r 1,2, Ville Parviainen1,2, Pirkko Mattila1,2, Risto Renkonen1,2 1Transplantation Laboratory and Infection Biology Research Program, Haartman Institute, University of Helsinki, Helsinki; 2HUSLAB, Helsinki University Central Hospital, Helsinki, Finland Background: Asthma is a chronic inflammatory disease of the airways with a complex genetic background. In this study, we carried out a meta-analysis of single nucleotide polymorphisms (SNPs) thought to be associated with asthma. Methods: The literature (PubMed) was searched for SNPs within genes relevant in asthma. The SNP-modified genes were converted to corresponding proteins, and their protein–protein interactions were searched from six different databases. This interaction network was analyzed using annotated vocabularies (ontologies), such as the Gene Ontology and Nature pathway interaction databases. Results: In total, 127 genes with SNPs related to asthma were found in the literature. The corresponding proteins were then entered into a large protein–protein interaction network with the help of various databases. Ninety-six SNP-related proteins had more than one interacting protein each, and a network containing 309 proteins and 644 connections was generated. This network was significantly enriched with a gene ontology entitled "protein binding" and several of its daughter categories, including receptor binding and cytokine binding, when compared with the background human proteome. In the detailed analysis, the chemokine network, including eight proteins and 13 toll-like receptors, were shown to interact with each other. Of great interest are the nonsynonymous SNPs which code for an alternative amino acid sequence of proteins and, of the toll-like receptor network, TLR1, TLR4, TLR5, TLR6, TLR10, IL4R, and IL13 are among these. Conclusions: Protein binding, toll-like receptors, and chemokines dominated in the asthma-related protein interaction network. Systems level analysis of allergy-related mutations can provide new insights into the pathogenetic mechanisms of disease.
Empirical Bayes analysis of single nucleotide polymorphisms
Holger Schwender, Katja Ickstadt
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-144
Abstract: In this paper, we propose a modification of this empirical Bayes analysis that can be used to analyze high-dimensional categorical SNP data. This approach along with a generalized version of the original empirical Bayes method are available in the R package siggenes version 1.10.0 and later that can be downloaded from http://www.bioconductor.org webcite.As applications to two subsets of the HapMap data show, the empirical Bayes analysis of microarrays cannot only be used to analyze continuous gene expression data, but also be applied to categorical SNP data, where the response is not restricted to be binary. In association studies in which typically several ten to a few hundred SNPs are considered, our approach can furthermore be employed to test interactions of SNPs. Moreover, the posterior probabilities resulting from the empirical Bayes analysis of (prespecified) interactions/genotypes can also be used to quantify the importance of these interactions.Whole-genome experiments comprise data of hundreds of thousands of single nucleotide polymorphisms (SNPs), where a SNP is the most common type of genetic variations that occurs when at a single base pair position different base alternatives exist in a population. SNPs are typically biallelic. Therefore, SNPs can be interpreted as categorical variables having three realizations: the homozygous reference genotype (if both chromosomes show the more frequent variant), the heterozygous genotype (if one chromosome shows the more frequent, and the other the less frequent variant), and the homozygous variant genotype (if both bases explaining the SNP are of the less frequent variant).Since SNPs can alter the risk for developing a disease, an important goal in studies concerned with SNPs is the identification of the SNPs that show a distribution of the genotypes that differs substantially between different groups (e.g., cancer vs. non-cancer). Detecting such SNPs requires methods that can cope with this vast multiple testing
Myosin individualized: single nucleotide polymorphisms in energy transduction
Thomas P Burghardt, Kevin L Neff, Eric D Wieben, Katalin Ajtai
BMC Genomics , 2010, DOI: 10.1186/1471-2164-11-172
Abstract: An automated routine identifying human nonsynonymous SNP amino acid missense substitutions for any MHC gene mined the NCBI SNP data base. The routine tested 22 MHC genes coding muscle and non-muscle isoforms and identified 89 missense mutation positions in the motor domain with 10 already implicated in heart disease and another 8 lacking sequence homology with a skeletal MHC isoform for which a crystallographic model is available. The remaining 71 SNP substitutions were found to be distributed over MHC with 22 falling outside identified functional sub-domains and 49 in or very near to myosin sub-domains assigned specific crucial functions in energy transduction. The latter includes the active site, the actin binding site, the rigid lever-arm, and regions facilitating their communication. Most MHC isoforms contained SNPs somewhere in the motor domain.Several functional-crucial sub-domains are infiltrated by a large number of SNP substitution sites suggesting these domains are engineered by evolution to be too-robust to be disturbed by otherwise intrusive sequence changes. Two functional sub-domains are SNP-free or relatively SNP-deficient but contain many disease implicated mutants. These sub-domains are apparently highly sensitive to any missense substitution suggesting they have failed to evolve a robust sequence paradigm for performing their function.Single nucleotide polymorphisms (SNPs) are common single base DNA sequence variants that account for a sizable portion of the genetic variability between individuals. Some SNPs are common and have minor allele frequencies that approach 50%, while others are found much less frequently. There is some conceptual overlap between rare SNPs (with minor allele frequencies of less than 1%) and disease implicated mutations, but in common usage the term polymorphism is restricted to non-pathogenic sequence changes. Genome SNP patterns are fingerprints identifying subpopulations with common heritage that potentially instigate su
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