935 resultados para single-nucleotide polymorphisms (SNPs)


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A SNP genotyping method was developed for E. faecalis and E. faecium using the 'Minimum SNPs' program. SNP sets were interrogated using allele-specific real-time PCR. SNP-typing sub-divided clonal complexes 2 and 9 of E. faecalis and 17 of E. faecium, members of which cause the majority of nosocomial infections globally.

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SNPNB is a user-friendly and platform-independent application for analyzing Single Nucleotide Polymorphism NeighBoring sequence context and nucleotide bias patterns, and subsequently evaluating the effective SNP size for the bias patterns observed from the whole data. It was implemented by Java and Perl. SNPNB can efficiently handle genome-wide or chromosome-wide SNP data analysis in a PC or a workstation. It provides visualizations of the bias patterns for SNPs or each type of SNPs.

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We report here for the first time 12 polymorphic single nucleotide polymorphisms (SNPs) in a commercially important gastropod, Pacific abalone (Haliotis discus hannai) that were identified by searching expressed sequence tag database. These SNP loci (seven nuclear and five mitochondrial SNPs) were polymorphic among 37 wild abalone individuals, based on a four-primer allele-specific polymerase chain reaction analysis. All loci had two alleles and the minor allele frequency ranged from 0.027 to 0.473. For the seven nuclear SNPs, the expected and observed heterozygosities ranged from 0.053 to 0.499 and from 0.054 to 0.811, respectively.

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Most of the cultivated species of citrus have narrow genetic basis. Relationships among species and cultivars are obscured by sexual compatibility, polyembryony, apomixis and a high incidence of somatic mutations. DNA analysis is crucial in genetic studies not only for citrus breeding programs but also for characterization of hybrids and species. In this paper, single nucleotide polymorphisms ( SNPs) were investigated in 58 accessions of Citrus, hybrids and related genera. Genomic sequences of 'Pera IAC' sweet orange ( Citrus sinensis L. Osbeck) were used for primer design and selection of sequence tagged sites (STSs) for identification of SNPs. Analysis of 36 STSs showed identical sequences among 40 of the 41 sweet orange accessions studied. However, these accessions were heterozygous for many SNPs. Ten selected STSs were analyzed in 17 additional accessions from 13 species and hybrids. Comparing to the 'Pera IAC' sweet orange accession, a total of 150 polymorphic nucleotides were identified and most of the alterations were transitions ( 52.7%). The greatest number of SNPs was observed in Poncirus trifoliata ( L.) Raf. and the smallest in 'Ponkan' mandarin ( Citrus reticulata Blanco). At the intra-specific level, 'Bafa Gigante' ( Citrus sinensis L. Osbeck) was the only sweet orange accession with a divergent SNPs genotype, which corroborates the hypothesis of a hybrid origin for this accession. Although the STSs analyzed represent randomly sampled genomic sequences, they provided consistent information about the level of polymorphism and showed the potential of SNPs markers for characterization and phylogenetic studies.

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Single nucleotide polymorphisms (SNPs) may be used in biodiversity studies and commercial tasks like traceability, paternity testing and selection for suitable genotypes. Twenty-seven SNPs were characterized and genotyped on 250 individuals belonging to eight Italian goat breeds. Multilocus genotype data were used to infer population structure and assign individuals to populations. To estimate the number of groups (K) to test in population structure analysis we used likelihood values and variance of the bootstrap samples, deriving optimal K from a drop in the likelihood and a rise in the variance plots against K.

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Systemic sclerosis (SSc) or Scleroderma is a complex disease and its etiopathogenesis remains unelucidated. Fibrosis in multiple organs is a key feature of SSc and studies have shown that transforming growth factor-β (TGF-β) pathway has a crucial role in fibrotic responses. For a complex disease such as SSc, expression quantitative trait loci (eQTL) analysis is a powerful tool for identifying genetic variations that affect expression of genes involved in this disease. In this study, a multilevel model is described to perform a multivariate eQTL for identifying genetic variation (SNPs) specifically associated with the expression of three members of TGF-β pathway, CTGF, SPARC and COL3A1. The uniqueness of this model is that all three genes were included in one model, rather than one gene being examined at a time. A protein might contribute to multiple pathways and this approach allows the identification of important genetic variations linked to multiple genes belonging to the same pathway. In this study, 29 SNPs were identified and 16 of them located in known genes. Exploring the roles of these genes in TGF-β regulation will help elucidate the etiology of SSc, which will in turn help to better manage this complex disease. ^

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Purpose Improved survival for men with prostate cancer has led to increased attention to factors influencing quality of life (QOL). As protein levels of vascular endothelial growth factor (VEGF) and insulin-like growth factor 1 (IGF-1) have been reported to be associated with QOL in people with cancer, we sought to identify whether single-nucleotide polymorphisms (SNPs) of these genes were associated with QOL in men with prostate cancer. Methods Multiple linear regression of two data sets (including approximately 750 men newly diagnosed with prostate cancer and 550 men from the general population) was used to investigate SNPs of VEGF and IGF-1 (10 SNPs in total) for associations with QOL (measured by the SF-36v2 health survey). Results Men with prostate cancer who carried the minor ‘T’ allele for IGF-1 SNP rs35767 had higher mean Role-Physical scale scores (≥0.3 SD) compared to non-carriers (p < 0.05). While this association was not identified in men from the general population, one IGF-1 SNP rs7965399 was associated with higher mean Bodily Pain scale scores in men from the general population that was not found in men with prostate cancer. Men from the general population who carried the rare ‘C’ allele had higher mean Bodily Pain scale scores (≥0.3 SD) than non-carriers (p < 0.05). Conclusions Through identifying SNPs that are associated with QOL in men with prostate cancer and men from the general population, this study adds to the mapping of complex interrelationships that influence QOL and suggests a role for IGF-I in physical QOL outcomes. Future research may identify biomarkers associated with increased risk of poor QOL that could assist in the provision of pre-emptive support for those identified at risk.

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Single nucleotide polymorphisms (SNPs) have been classically used for dissecting various human complex disorders using candidate gene studies. During the last decade, large scale SNP analysis i.e. genome-wide association studies (GWAS) have provided an agnostic approach to identify possible genetic loci associated with heterogeneous disease such as cancer susceptibility, prognosis of survival or drug response. Further, the advent of new technologies, including microarray based genotyping as well as high throughput next generation sequencing has opened new avenues for SNPs to be used in clinical practice. It is speculated that the utility of SNPs to understand the mechanisms, biology of variable drug response and ultimately treatment individualization based on the individual’s genome composition will be indispensable in the near future. In the current review, we discuss the advantages and disadvantages of the clinical utility of genetic variants in disease risk-prediction, prognosis, clinical outcome and pharmacogenomics. The lessons and challenges for the utility of SNP based biomarkers are also discussed, including the need for additional functional validation studies.

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The principal objective of this study was to determine if Campylobacter jejuni genotyping methods based upon resolution optimised sets of single nucleotide polymorphisms (SNPs) and binary genetic markers were capable of identifying epidemiologically linked clusters of chicken-derived isolates. Eighty-eight C. jejuni isolates of known flaA RFLP type were included in the study. They encompassed three groups of ten isolates that were obtained at the same time and place and possessed the same flaA type. These were regarded as being epidemiologically linked. Twenty-six unlinked C. jejuni flaA type I isolates were included to test the ability of SNP and binary typing to resolve isolates that were not resolved by flaA RFLP. The remaining isolates were of different flaA types. All isolates were typed by real-time PCR interrogation of the resolution optimised sets of SNPs and binary markers. According to each typing method, the three epidemiologically linked clusters were three different clones that were well resolved from the other isolates. The 26 unlinked C. jejuni flaA type I isolates were resolved into 14 SNP-binary types, indicating that flaA typing can be unreliable for revealing epidemiological linkage. Comparison of the data with data from a fully typed set of isolates associated with human infection revealed that abundant lineages in the chicken isolates that were also found in the human isolates belonged to clonal complex (CC) -21 and CC-353, with the usually rare C-353 member ST-524 being especially abundant in the chicken collection. The chicken isolates selected to be diverse according to flaA were also diverse according to SNP and binary typing. It was observed that CC-48 was absent in the chicken isolates, despite being very common in Australian human infection isolates, indicating that this may be a major cause of human disease that is not chicken associated.

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In this report, we describe a simple correction for multiple testing of single-nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with each other, on the basis of the spectral decomposition (SpD) of matrices of pairwise LD between SNPs. This method provides a useful alternative to more computationally intensive permutation tests. Additionally, output from SNPSpD includes eigenvalues, principal-component coefficients, and factor "loadings" after varimax rotation, enabling the selection of a subset of SNPs that optimize the information in a genomic region.

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Luteal insufficiency affects fertility and hence study of mechanisms that regulate corpus luteum (CL) function is of prime importance to overcome infertility problems. Exploration of human genome sequence has helped to study the frequency of single nucleotide polymorphisms (SNPs). Clinical benefits of screening SNPs in infertility are being recognized well in recent times. Examining SNPs in genes associated with maintenance and regression of CL may help to understand unexplained luteal insufficiency and related infertility. Publicly available microarray gene expression databases reveal the global gene expression patterns in primate CL during the different functional state. We intend to explore computationally the deleterious SNPs of human genes reported to be common targets of luteolysin and luteotropin in primate CL Different computational algorithms were used to dissect out the functional significance of SNPs in the luteinizing hormone sensitive genes. The results raise the possibility that screening for SNPs might be integrated to evaluate luteal insufficiency associated with human female infertility for future studies. (C) 2012 Elsevier B.V. All rights reserved,

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Accurate and fast genotyping of single nucleotide polymorphisms (SNPs) is important in the human genome project. Here an automated fluorescent method that can rapidly and accurately genotype multiplex known SNPs was developed by using a homemade kit, which has lower cost but higher resolution than commercial kit. With this method, oncogene K-ras was investigated, four known SNPs of K-ras gene exon 1 in 31 coloerctal cancer patients were detected. Results indicate that mutations were present in 8(26%) of 31 patients, and most mutations were localized in codon 12. The presence of these mutations is thought to be a critical step and plays an important role in human colorectal carcinogenesisas. (C) 2003 Elsevier B.V. All rights reserved.

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Although single nucleotide polymorphisms (SNPs) are important resources for population genetics, pedigree analysis and genomic mapping, such loci have not been reported in Pacific abalone so far. In this study, a bioinformatics strategy was adopted to discover SNPs within the expressed sequences (ESTs) of Pacific abalone, Haliotis discus hannai, and furthermore, polymerase chain reaction direct sequencing (PCR-DS) and allele-specific PCR (AS-PCR) were used for SNPs detection and genotype scoring respectively. A total of 5893 ESTs were assembled and 302 putative SNPs were identified. The average density of SNPs in ESTs was 1%. Fifty-two sets of sequencing primers were designed from SNPs flanking ESTs to amplify the genomic DNA, and 13 could generate products of expected size. Polymerase chain reaction direct sequencing of the amplification products from pooled DNA samples revealed 40 polymorphic SNP loci. Using a modified tetra-primer AS-PCR, seven mitochondrial and six nuclear SNPs were typed and characterized among 37 wild abalones. In conclusion, it is feasible to discover SNPs from number limited ESTs and the AS-PCR as a simple, robust and reliable assay could be a primary method for small- and medium-scale SNPs detection in abalones as well as other non-model organisms.

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Background Single 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. Results We 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%. Conclusions Our 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.