Number Of Significant Single Nucleotide Polymorphisms Research Articles

DNA TYPING BY TELOMERASE REVERSE GENE TRANSCRIPTASE (TERT)

The length of the telomeric DNA and polymorphism of the TERT (Telomerase Reverse Transcriptase) gene can be the basis for the development of molecular genetic markers for the productive traits of agricultural animals, in particular pigs.
 The purpose of the work was to analyze the databases of the primary structure of the pig TERT gene, to determine single nucleotide polymorphisms (SNPs), to develop a DNA system for animal typing based on the TERT gene.
 Samples of biomaterials (blood, bristles) for DNA typing were selected from the leading farms of Ukraine in groups of 4 breeds of pigs and hybrid animals. Isolation of DNA from biomaterial was carried out using the Chelex 100 reagent. Genotyping of animals by the telomerase locus was carried out on the basis of standard methods of polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP). The alignment of nucleotide sequences during the analysis of the primary structure of the TERT gene was carried out using the MegaX software and the Blast service. Design of the structure of oligonucleotide primers for PCR was carried out using the computer program Primer3Plus.
 During the development of the method of pigs genotyping according to TERT gene, a database analysis was carried out regarding the primary structure of the gene, a region of the gene with a significant number of SNPs was identified, and oligonucleotide primers were designed for PCR amplification of this region of the gene. The study presents the conditions of amplification of the TERT gene fragment, its cleavage by restriction endonuclease RsaI at the location of SNP rs698799571, electrophoresis of the obtained restriction DNA fragments in an 8% polyacrylamide gel, and the genotypes of the animals are also determined. The developed DNA typing technique for the TERT gene was used to analyze its polymorphism in groups of 4 purebred pigs and a group of hybrid anjmals. Monomorphic homozygous TERTAA genotype was present in purebred pigs. The polymorphism of the TERT gene by SNP rs698799571 was detected in a group of pigs of the final Irish hybrid (LW x L) x Maxgro (TERTAT genotype).
 Considering the fact that studies on the telomerase gene and determination of the TERT polymorphism for SNP rs698799571 in pigs have not yet been conducted in Ukraine, the developed technique of DNA typing by the telomerase gene has a perspective for further determination of the distribution of alleles and genotypes in domestic and imported breeds, as well as in marker-associated selection.

The Effect of the Allelics of Ser680Asn Polymorphisms of Follicle-Stimulating Hormone Receptor Gene in IVF/ICSI Cycles: a Systematic Review and Meta-analysis.

A significant number of single-nucleotide polymorphisms (SNPs) of the follicle-stimulating hormone receptor (FSHr) can modify the response to exogenous FSH administration. A significant diversity in response to controlled ovarian stimulation (COS) in assisted reproductive technologies (ART) according to the type of allelic has been reported. We aimed to evaluate the relation between the Asn680Ser allelics and COS. A total of 4 electronic databases were searched for articles published up to August 2021. Prospective and retrospective comparative studies which reported outcomes after COS in patients who underwent genotyping for the detection of FSHr polymorphisms were considered eligible. A total of 11 studies including 4343 patients with Asn680Ser polymorphisms of the FSHr were included. Patients carrying the Asn/Asn allelic provide elevated E2 on the day of human chorionic gonadotropin (hCG) administration (1549 patients MD 262.39pg/ml, p = 0.0007), but less transferrable embryos as compared with Ser/Ser genotype (283 patients MD - 0.11 embryos, p = 0.04). Ans/Ser versus Ser/Ser genotypes showed a higher E2 on the day of hCG administration (1799 patients, MD 207.86pg/ml, p = 0.02). Pregnancy rates were similar in all combination of genotypes. There is currently no strong evidence suggesting that the examination of one gene in relation to genotypes can be effectively used as single tool to improve COS. However, polygenic analysis of different polymorphisms by analyzing the genetic profile of each individual could be useful. Further research is warranted to develop an algorithm that will enable simultaneous analysis of many genes, which combined with hormonal profile could promote treatment individualization.

NADPH oxidase 5 and renal disease.

To highlight the latest novel developments in renal NADPH oxidase 5 (Nox5) biology, with an emphasis not only on diabetic nephropathy but also on many of the other renal disease contexts in which oxidative stress is implicated. Nox-derived reactive oxygen species have been shown to contribute to a wide variety of renal diseases, particularly in the settings of chronic renal disease such as diabetic nephropathy. Although much emphasis has been placed on the role of NADPH oxidase 4 in this setting, a growing body of work continues to uncover the key roles for other Nox family members, not only in diabetic kidney disease, but also in a diverse array of renal pathological conditions. The most recently identified member of the Nox family, Nox5, has for the most part been overlooked in renal disease, partly owing to its absence from the rodent genome. New evidence suggests that Nox5 may be a contributing factor in glomerulopathies and altered tubular physiology. Furthermore, Nox5 appears to harbor a significant number of single-nucleotide polymorphisms that alter its enzymatic activity. Given the unique structure and expression pattern of Nox5, it may prove to be an attractive therapeutic target in the treatment of renal disease.

Genome-wide interaction of genotype by erythrocyte n-3 fatty acids contributes to phenotypic variance of diabetes-related traits.

BackgroundLittle is known about the interplay between n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level. The present study aimed to examine variance contributions of genotype by environment (GxE) interactions for different erythrocyte n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level in a non-Hispanic white population living in the U.S.A. (n = 820). A tool for Genome-wide Complex Trait Analysis (GCTA) was used to estimate the genome-wide GxE variance contribution of four diabetes-related traits: HOMA-Insulin Resistance (HOMA-IR), fasting plasma insulin, glucose and adiponectin. A GxE genome-wide association study (GWAS) was conducted to further elucidate the GCTA results. Replication was conducted in the participants of the Boston Puerto Rican Health Study (BPRHS) without diabetes (n = 716).ResultsIn GOLDN, docosapentaenoic acid (DPA) contributed the most significant GxE variance to the total phenotypic variance of both HOMA-IR (26.5%, P-nominal = 0.034) and fasting insulin (24.3%, P-nominal = 0.042). The ratio of arachidonic acid to eicosapentaenoic acid + docosahexaenoic acid contributed the most significant GxE variance to the total variance of fasting glucose (27.0%, P-nominal = 0.023). GxE variance of the arachidonic acid/eicosapentaenoic acid ratio showed a marginally significant contribution to the adiponectin variance (16.0%, P-nominal = 0.058). None of the GCTA results were significant after Bonferroni correction (P < 0.001). For each trait, the GxE GWAS identified a far larger number of significant single-nucleotide polymorphisms (P-interaction ≤ 10E-5) for the significant E factor (significant GxE variance contributor) than a control E factor (non-significant GxE variance contributor). In the BPRHS, DPA contributed a marginally significant GxE variance to the phenotypic variance of HOMA-IR (12.9%, P-nominal = 0.068) and fasting insulin (18.0%, P-nominal = 0.033).ConclusionErythrocyte n-3 fatty acids contributed a significant GxE variance to diabetes-related traits at the genome-wide level.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-781) contains supplementary material, which is available to authorized users.

Genome Wide Screening of Candidate Genes for Improving Piglet Birth Weight Using High and Low Estimated Breeding Value Populations

Birth weight is an economically important trait in pig production because it directly impacts piglet growth and survival rate. In the present study, we performed a genome wide survey of candidate genes and pathways associated with individual birth weight (IBW) using the Illumina PorcineSNP60 BeadChip on 24 high (HEBV) and 24 low estimated breeding value (LEBV) animals. These animals were selected from a reference population of 522 individuals produced by three sires and six dam lines, which were crossbreds with multiple breeds. After quality-control, 43,257 SNPs (single nucleotide polymorphisms), including 42,243 autosomal SNPs and 1,014 SNPs on chromosome X, were used in the data analysis. A total of 27 differentially selected regions (DSRs), including 1 on Sus scrofa chromosome 1 (SSC1), 1 on SSC4, 2 on SSC5, 4 on SSC6, 2 on SSC7, 5 on SSC8, 3 on SSC9, 1 on SSC14, 3 on SSC18, and 5 on SSCX, were identified to show the genome wide separations between the HEBV and LEBV groups for IBW in piglets. A DSR with the most number of significant SNPs (including 7 top 0.1% and 31 top 5% SNPs) was located on SSC6, while another DSR with the largest genetic differences in FST was found on SSC18. These regions harbor known functionally important genes involved in growth and development, such as TNFRSF9 (tumor necrosis factor receptor superfamily member 9), CA6 (carbonic anhydrase VI) and MDFIC (MyoD family inhibitor domain containing). A DSR rich in imprinting genes appeared on SSC9, which included PEG10 (paternally expressed 10), SGCE (sarcoglycan, epsilon), PPP1R9A (protein phosphatase 1, regulatory subunit 9A) and ASB4 (ankyrin repeat and SOCS box containing 4). More importantly, our present study provided evidence to support six quantitative trait loci (QTL) regions for pig birth weight, six QTL regions for average birth weight (ABW) and three QTL regions for litter birth weight (LBW) reported previously by other groups. Furthermore, gene ontology analysis with 183 genes harbored in these 27 DSRs suggested that protein, metal, ion and ATP binding, viral process and innate immune response present important pathways for deciphering their roles in fetal growth or development. Overall, our study provides useful information on candidate genes and pathways for regulating birth weight in piglets, thus improving our understanding of the genetic mechanisms involved in porcine embryonic or fetal development.

Development of GMDR-GPU for Gene-Gene Interaction Analysis and Its Application to WTCCC GWAS Data for Type 2 Diabetes

Although genome-wide association studies (GWAS) have identified a significant number of single-nucleotide polymorphisms (SNPs) associated with many complex human traits, the susceptibility loci identified so far can explain only a small fraction of the genetic risk. Among other possible explanations, the lack of a comprehensive examination of gene–gene interaction (G×G) is often considered a source of the missing heritability. Previously, we reported a model-free Generalized Multifactor Dimensionality Reduction (GMDR) approach for detecting G×G in both dichotomous and quantitative phenotypes. However, the computational burden and less efficient implementation of the original programs make them impossible to use for GWAS. In this study, we developed a graphics processing unit (GPU)-based GMDR program (named GWAS-GPU), which is able not only to analyze GWAS data but also to run much faster than the earlier version of the GMDR program. As a demonstration of the program, we used the GMDR-GPU software to analyze a publicly available GWAS dataset on type 2 diabetes (T2D) from the Wellcome Trust Case Control Consortium. Through an exhaustive search of pair-wise interactions and a selected search of three- to five-way interactions conditioned on significant pair-wise results, we identified 24 core SNPs in six genes (FTO: rs9939973, rs9940128, rs9922047, rs1121980, rs9939609, rs9930506; TSPAN8: rs1495377; TCF7L2: rs4074720, rs7901695, rs4506565, rs4132670, rs10787472, rs11196205, rs10885409, rs11196208; L3MBTL3: rs10485400, rs4897366; CELF4: rs2852373, rs608489; RUNX1: rs445984, rs1040328, rs990074, rs2223046, rs2834970) that appear to be important for T2D. Of these core SNPs, 11 in FTO, TSPAN8, and TCF7L2 have been reported to be associated with T2D, obesity, or both, providing an independent replication of previously reported SNPs. Importantly, we identified three new susceptibility genes; i.e., L3MBTL3, CELF4, and RUNX1, for T2D, a finding that warrants further investigation with independent samples.

RS-SNP: a random-set method for genome-wide association studies

BackgroundThe typical objective of Genome-wide association (GWA) studies is to identify single-nucleotide polymorphisms (SNPs) and corresponding genes with the strongest evidence of association (the 'most-significant SNPs/genes' approach). Borrowing ideas from micro-array data analysis, we propose a new method, named RS-SNP, for detecting sets of genes enriched in SNPs moderately associated to the phenotype. RS-SNP assesses whether the number of significant SNPs, with p-value P ≤ α, belonging to a given SNP set is statistically significant. The rationale of proposed method is that two kinds of null hypotheses are taken into account simultaneously. In the first null model the genotype and the phenotype are assumed to be independent random variables and the null distribution is the probability of the number of significant SNPs in greater than observed by chance. The second null model assumes the number of significant SNPs in depends on the size of and not on the identity of the SNPs in . Statistical significance is assessed using non-parametric permutation tests.ResultsWe applied RS-SNP to the Crohn's disease (CD) data set collected by the Wellcome Trust Case Control Consortium (WTCCC) and compared the results with GENGEN, an approach recently proposed in literature. The enrichment analysis using RS-SNP and the set of pathways contained in the MSigDB C2 CP pathway collection highlighted 86 pathways rich in SNPs weakly associated to CD. Of these, 47 were also indicated to be significant by GENGEN. Similar results were obtained using the MSigDB C5 pathway collection. Many of the pathways found to be enriched by RS-SNP have a well-known connection to CD and often with inflammatory diseases.ConclusionsThe proposed method is a valuable alternative to other techniques for enrichment analysis of SNP sets. It is well founded from a theoretical and statistical perspective. Moreover, the experimental comparison with GENGEN highlights that it is more robust with respect to false positive findings.

2151 ASSOCIATION OF PROSTATE CANCER RISK SNPS WITH AGE AT TREATMENT: POTENTIAL FOR PREDICTION OF EARLY ONSET OF DISEASE

You have accessJournal of UrologyProstate Cancer: Detection and Screening V1 Apr 20102151 ASSOCIATION OF PROSTATE CANCER RISK SNPS WITH AGE AT TREATMENT: POTENTIAL FOR PREDICTION OF EARLY ONSET OF DISEASE Jianfeng Xu, Jielin Sun, Seong-Tae Kim, A. Karim Kader, Patrick Walsh, Alan Partin, Henrik Gronberg, Siqun Zheng, and William Isaacs Jianfeng XuJianfeng Xu Winston-Salem, NC More articles by this author , Jielin SunJielin Sun Winston-Salem, NC More articles by this author , Seong-Tae KimSeong-Tae Kim Winston-Salem, NC More articles by this author , A. Karim KaderA. Karim Kader Winston-Salem, NC More articles by this author , Patrick WalshPatrick Walsh Baltimore, MD More articles by this author , Alan PartinAlan Partin Baltimore, MD More articles by this author , Henrik GronbergHenrik Gronberg Stockholm, Sweden More articles by this author , Siqun ZhengSiqun Zheng Winston-Salem, NC More articles by this author , and William IsaacsWilliam Isaacs Baltimore, MD More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.2253AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Multiple single nucleotide polymorphisms (SNPs) have been associated with prostate cancer (PCa) risk through genome-wide association studies. These SNPs are common in the general population and the associations have been consistently replicated in several populations of European descent. One of the most important clinical utilities of these SNPs is their potential to identify those men at risk for early-onset PCa. METHODS Thirty-one PCa risk-associated SNPs were genotyped in 8,055 PCa cases treated by radical prostatectomy at the Johns Hopkins Hospital between 1988 and 2008. The association of each SNP with age at treatment was first evaluated using a univariate analysis under an additive model. Cumulative effect of multiple SNPs on age at treatment was tested by regression analysis between age at treatment and number of risk alleles. RESULTS Eight SNPs were independently associated with age at treatment (P < 0.05). The number of significant SNPs is considerably more than expected by chance (expected less than 2 SNPs under the null hypothesis with a significance level of 5%). More importantly, for each of these significant SNPs, patients carrying PCa risk-associated alleles were significantly younger at time of treatment. These results suggest that the associations of these 8 SNPs with age at treatment represent true findings. Furthermore, when the cumulative effect of these 8 SNPs on age at treatment was tested using the variable of number of risk alleles, it was highly significant (P = 6 x 10-6). Importantly, none of the 8 SNPs associated with early onset PCa are associated with PSA levels. We postulate that the relationship between these SNPs and early onset PCa would be even stronger in a population which was not subject to biases related to PSA screening or treatment. CONCLUSIONS Many PCa-risk associated SNPs are independently and additively associated with age at treatment of PCa. These SNPs have the potential to be used to identify men at risk for early onset PCa. © 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e836 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jianfeng Xu Winston-Salem, NC More articles by this author Jielin Sun Winston-Salem, NC More articles by this author Seong-Tae Kim Winston-Salem, NC More articles by this author A. Karim Kader Winston-Salem, NC More articles by this author Patrick Walsh Baltimore, MD More articles by this author Alan Partin Baltimore, MD More articles by this author Henrik Gronberg Stockholm, Sweden More articles by this author Siqun Zheng Winston-Salem, NC More articles by this author William Isaacs Baltimore, MD More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Quantitative Analysis of Single Nucleotide Polymorphisms within Copy Number Variation

BackgroundSingle nucleotide polymorphisms (SNPs) have been used extensively in genetics and epidemiology studies. Traditionally, SNPs that did not pass the Hardy-Weinberg equilibrium (HWE) test were excluded from these analyses. Many investigators have addressed possible causes for departure from HWE, including genotyping errors, population admixture and segmental duplication. Recent large-scale surveys have revealed abundant structural variations in the human genome, including copy number variations (CNVs). This suggests that a significant number of SNPs must be within these regions, which may cause deviation from HWE.ResultsWe performed a Bayesian analysis on the potential effect of copy number variation, segmental duplication and genotyping errors on the behavior of SNPs. Our results suggest that copy number variation is a major factor of HWE violation for SNPs with a small minor allele frequency, when the sample size is large and the genotyping error rate is 0∼1%.ConclusionsOur study provides the posterior probability that a SNP falls in a CNV or a segmental duplication, given the observed allele frequency of the SNP, sample size and the significance level of HWE testing.