Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Polymorphism, Single Nucleotide”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources
PubMed2003

Mapping genetic alterations in tumors with single nucleotide polymorphisms.

Single nucleotide polymorphisms are the most abundant genetic markers in the human genome whose analyses can be easily conducted on a large scale. Most established methods for high-throughput single nucleotide polymorphism analyses are qualitative and are not suitable for genetic analysis of archived tumor specimens, which have compromised tissue integrity and normal tissue contaminations. Recent studies have focused on the development of quantitative methods for single nucleotide polymorphism analyses that can tolerate such imperfections in archived tissues. These methods have been used to measure the rate of allelic imbalance in small adenocarcinomas and to reveal novel correlations between allelic imbalance and disease progression in colorectal cancer. Therefore, quantitative single nucleotide polymorphism analysis provides a powerful tool for the identification of novel tumor markers and for the characterization of genetic alterations in human tumors.

Allelic Imbalance↗
PubMed2000

[The research development of single nucleotide polymorphism].

Single nucleotide polymorphism(SNP) is a novel set of polymorphism based on the single nucleotide variations at the genomic level, which distributes widely across the human genome and has high polymorphism information content (PIC). Now, tens of thousands SNPs have been discovered among the human genome and are introduced by many biological medicine networks. With the development of identification and analysis technique for SNP, especially the combination with DNA chips, they, as the third generation of genetic markers, are gradually fitable for fine-scale mapping of diseases, especially the complex diseases susceptibility genes and will eventually substitute for the most commonly used microsatellite markers presently.

Genetic Markers↗
PubMed2001

[Recent progress of study on single nucleotide polymorphisms].

Single nucleotide polymorphisms (SNPs) is a new genetic marker system following RFLP and microsatellite polymorphism. It has been shown to have the characteristics of high-density, inheritance stability and facilitation in analysis automation. SNPs can be detected by electrophoresis, endonuclease-cleavage, PCR and sequencing, and can be used extensively in gene mapping, disease-correlativity analysis, population genetics and drug research.

Chromosome Mapping↗
PubMed2005

[Progress in detection methods of single nucleotide polymorphisms].

Single nucleotide polymorphism (SNP) is the third generation genetic marker. SNP detection now is becoming increasingly important means in molecular diagnostics, clinical assay and novel drug development. It plays an essential role in drug resistance and anaphylactic reaction and has the importance in theoretical studies of gene location, hereditary diseases and human origin. With the accomplishment of human genome sequencing, the genotyping and discovering of SNP are becoming hot subjects in genetics and biomedicine researches. The methods for SNP detection were renewed rapidly and developed fast in past few years. In this review, several newly established detection methods including gene chip, molecular probe, fluorescence polarization and resonance, mass spectrometry, and bacterial magnetic particle are discussed. It could be expected that an accurate and sensitive, simple and easy-to-handle SNP technology with low cost and high throughput will be available on the basis of research breakthroughs of biochemistry, engineering and analytic software.

Fluorescence Polarization↗
PubMed2003

Detection of single nucleotide polymorphisms.

Single nucleotide polymorphism (SNP) detection technologies are used to scan for new polymorphisms and to determine the allele(s) of a known polymorphism in target sequences. SNP detection technologies have evolved from labor intensive, time consuming, and expensive processes to some of the most highly automated, efficient, and relatively inexpensive methods. Driven by the Human Genome Project, these technologies are now maturing and robust strategies are found in both SNP discovery and genotyping areas. The nearly completed human genome sequence provides the reference against which all other sequencing data can be compared. Global SNP discovery is therefore only limited by the amount of funding available for the activity. Local, target, SNP discovery relies mostly on direct DNA sequencing or on denaturing high performance liquid chromatography (dHPLC). The number of SNP genotyping methods has exploded in recent years and many robust methods are currently available. The demand for SNP genotyping is great, however, and no one method is able to meet the needs of all studies using SNPs. Despite the considerable gains over the last decade, new approaches must be developed to lower the cost and increase the speed of SNP detection.

Alleles↗
PubMed2003

Haplotype information and linkage disequilibrium mapping for single nucleotide polymorphisms.

Single nucleotide polymorphisms in the human genome have become an increasingly popular topic in that their analyses promise to be a key step toward personalized medicine. We investigate two related questions, how much the haplotype information contributes to linkage disequilibrium (LD) mapping and whether an in silico haplotype construction preceding the LD analysis can help. For disease gene mapping, using both simulated and real data sets on cystic fibrosis and the Alzheimer disease, we reached the following conclusions: (1) for simple Mendelian diseases, in which case a tractable full statistical model can be developed, the loss of haplotype information for either control or disease data do not have a great impact on LD fine mapping, and haplotype inference should be carried out jointly with LD mapping; (2) for complex diseases, inferring haplotype phases for individuals prior to LD mapping helps achieve a better accuracy. An improved version of the linkage disequilibrium mapping program, BLADE v2, is available at http://www.fas.harvard.edu/junliu/TechRept/03folder/bladev2.tgz.

Algorithms↗
PubMed2005

A sparse marker extension tree algorithm for selecting the best set of haplotype tagging single nucleotide polymorphisms.

Single nucleotide polymorphisms (SNPs) play a central role in the identification of susceptibility genes for common diseases. Recent empirical studies on human genome have revealed block-like structures, and each block contains a set of haplotype tagging SNPs (htSNPs) that capture a large fraction of the haplotype diversity. Herein, we present an innovative sparse marker extension tree (SMET) algorithm to select optimal htSNP set(s). SMET reduces the search space considerably (compared to full enumeration strategy), and therefore improves computing efficiency. We tested this algorithm on several datasets at three different genomic scales: (1) gene-wide (NOS3, CRP, IL6 PPARA, and TNF), (2) region-wide (a Whitehead Institute inflammatory bowel disease dataset and a UK Graves' disease dataset), and (3) chromosome-wide (chromosome 22) levels. SMET offers geneticists with greater flexibilities in SNP tagging than lossless methods with adjustable haplotype diversity coverage (phi). In simulation studies, we found that (1) an initial sample size of 50 individuals (100 chromosomes) or more is needed for htSNP selection; (2) the SNP tagging strategy is considerably more efficient when the underlying block structure is taken into account; and (3) htSNP sets at 80-90% phi are more cost-effective than the lossless sets in term of relative power, relative risk ratio estimation, and genotyping efforts. Our study suggests that the novel SMET algorithm is a valuable tool for association tests.

Algorithms↗
PubMed1999

True pedigree errors more frequent than apparent errors for single nucleotide polymorphisms.

Single nucleotide polymorphisms (SNPs) are currently being developed for use in disequilibrium analyses. These SNPs consist of two alleles with varying degrees of polymorphism. A natural design for use with SNPs is the 'haplotype relative risk' sampling design in which a father, mother, and child are typed at an SNP locus. Given such a trio of genotypes, we ask: what is the probability that a pedigree error (a change from one allele to the other) at an SNP locus will be detected using only Mendel's laws as a check? We calculate the probability of detecting such errors for a hypothetical SNP locus with varying degrees of polymorphism and for various true error rates. For the sets of allele frequencies considered, we find that the detection rates range between 25 and 30%, the detection rate being lowest when the two alleles have equal frequencies and the highest when one allele has a frequency of 10%. Based on this detection rate, we determine that the true error rate is roughly 3.3-4 times that of the apparent error rate at an SNP locus. The greatest discrepancy between true and apparent error rates occurs when allele frequencies are equal.

Alleles↗
PubMed2005

The common polymorphisms (single nucleotide polymorphism [SNP] +45 and SNP +276) of the adiponectin gene predict the conversion from impaired glucose tolerance to type 2 diabetes: the STOP-NIDDM trial.

Adiponectin is an adipose tissue-specific protein with insulin-sensitizing and antiatherogenic properties. Therefore, the adiponectin gene is a promising candidate gene for type 2 diabetes. We investigated the single nucleotide polymorphisms (SNPs) +45T/G and +276G/T of the adiponectin gene as predictors for the conversion from impaired glucose tolerance to type 2 diabetes in the STOP-NIDDM trial, which aimed to investigate the effect of acarbose compared with placebo on the prevention of type 2 diabetes. Compared with the TT genotype, the G-allele of SNP +45 was associated with a 1.8-fold risk for type 2 diabetes (95% CI 1.12-3.00, P = 0.015) in the placebo group. Subjects treated with placebo and simultaneously having the G-allele of SNP +45 and the T-allele of SNP +276 (the risk genotype combination) had a 4.5-fold (1.78-11.3, P = 0.001) higher risk of developing type 2 diabetes compared with subjects carrying neither of these alleles. Women carrying the risk genotype combination had an especially high risk of conversion to diabetes (odds ratio 22.2, 95% CI 2.7-183.3, P = 0.004). In conclusion, the G-allele of SNP +45 is a predictor for the conversion to type 2 diabetes. Furthermore, the combined effect of SNP +45 and SNP +276 on the development of type 2 diabetes was stronger than that of each SNP alone.

Acarbose↗
PubMed2005

nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms.

Nonsynonymous single nucleotide polymorphisms (nsSNPs) are prevalent in genomes and are closely associated with inherited diseases. To facilitate identifying disease-associated nsSNPs from a large number of neutral nsSNPs, it is important to develop computational tools to predict the nsSNP's phenotypic effect (disease-associated versus neutral). nsSNPAnalyzer, a web-based software developed for this purpose, extracts structural and evolutionary information from a query nsSNP and uses a machine learning method called Random Forest to predict the nsSNP's phenotypic effect. nsSNPAnalyzer server is available at http://snpanalyzer.utmem.edu/.

Algorithms↗
PubMed2003

Fluorescence polarization for single nucleotide polymorphism genotyping.

Single nucleotide polymorphisms (SNPs) are the most abundant variations in the human genome and have become the primary markers for genetic studies for mapping and identifying susceptible genes for complex diseases. Methods that genotype SNPs quickly and economically are of high values for these studies because they require a large amount of genotyping. Fluorescence polarization (FP) is a robust technique that can detect products without separation and purification and it has been applied for SNP genotyping. In this article the applications of FP in SNP genotyping are reviewed and one of the methods, the FP-TDI assay, is discussed in details. It is hoped that readers could get useful information for the applications of FP in SNP genotyping and some insights of the FP-TDI assay.

Animals↗
PubMed2004

Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms.

MOTIVATION: Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans. SNPs causing amino acid substitutions are of particular interest as candidates for loci affecting susceptibility to complex diseases, such as diabetes and hypertension. To efficiently screen SNPs for disease association, it is important to distinguish neutral variants from deleterious ones. RESULTS: We describe the use of Pfam protein motif models and the HMMER program to predict whether amino acid changes in conserved domains are likely to affect protein function. We find that the magnitude of the change in the HMMER E-value caused by an amino acid substitution is a good predictor of whether it is deleterious. We provide internet-accessible display tools for a genomewide collection of SNPs, including 7391 distinct non-synonymous coding region SNPs in 2683 genes. AVAILABILITY: http://lpgws.nci.nih.gov/cgi-bin/GeneViewer.cgi

Amino Acid Motifs↗
PubMed2002

A high-density SNP map for the FRAX region of the X chromosome. Single-nucleotide polymorphisms.

Single-nucleotide polymorphisms (SNPs) are the most common type of genetic variation within the human genome, occurring approximately once every kilobase. However, for association studies, SNPs are not as informative as microsatellite markers and a large number of SNPs and substantial population sizes are required for linkage and mapping studies. A SNP map was generated for the FRAX region of the X chromosome, approximately 0.8 Mb proximal and 1.8 Mb distal to the FRAXA repeat, at a density of at least 1 SNP every 100 kb. SNPs were identified in a population of 28 women with a FRAXA expan-sion (including three women with a FRAXE expansion) on a background of different DXS548, CA1 and CA2 haplotypes, and a normal X chromosome with a different microsatellite haplotype. Fifty-four polymorphisms were identified in a total of 52 257 bp distributed over 2.6 Mb. This represented about 1 SNP every 1024 bp, which was consistent with a nondesert region (1 : 1000 bp). Because the SNPs identified in this study have haplotype and frequency data from an affected population, they should provide a useful resource for researchers to investigate the genetic mechanisms behind instability and expansion of both FRAXA and FRAXE triplet repeats.

Chromosome Mapping↗
PubMed2004

Gene therapy for the circumvention of inborn errors of metabolism (IEM) caused by single-nucleotide-polymorphisms (SNPs).

Single nucleotide polymorphisms (SNPs) are the result of point mutations in nuclear (and mitochondrial) DNA. Such localised damage to DNA (and its replicative mechanisms) may not be excised fully by the DNA repair mechanism in the genome: and therefore can become inheritable; subsequently to manifest later as an inborn error of metabolism (IEM). Causes of mutagenic damage to the DNA can include background radiation (such as emitted by radon gas), and by reactive oxygen species (ROS): and also by mutagenic chemicals that occur naturally (inter alia in the diet). Other causes of DNA damage are variable environmental hazards such as solar-derived short wave ultraviolet light A. Gene therapy involves the placement of missing genes into particular tissues by the harnessing of suitable vectors (originally these were animal viruses such as SV40). For example, gene therapy in the rat for diabetes has succeeded by liver-production of insulin (using genes obtained from pancreatic Islets of Langerhans cells). Many inborn errors of metabolism could be treated in this way: examples may include 100 haemoglobinopathies (such as sickle cell anaemia), phenylketonuria; and other diseases caused by lack of tissue-production of a particular enzyme (in its catalytically-active conformation).

Diabetes Mellitus↗
PubMed2006

Determinants of specific RNA interference-mediated silencing of human beta-globin alleles differing by a single nucleotide polymorphism.

A single nucleotide polymorphism (SNP) in the sickle beta-globin gene (beta(S)) leads to sickle cell anemia. Sickling increases sharply with deoxy sickle Hb concentration and decreases with increasing fetal gamma-globin concentration. Measures that decrease sickle Hb concentration should have an antisickling effect. RNA interference (RNAi) uses small interfering (si)RNAs for sequence-specific gene silencing. A beta(S) siRNA with position 10 of the guide strand designed to align with the targeted beta(S) SNP specifically silences beta(S) gene expression without affecting the expression of the gamma-globin or normal beta-globin (beta(A)) genes. Silencing is increased by altering the 5' end of the siRNA antisense (guide) strand to enhance its binding to the RNA-induced silencing complex (RISC). Specific beta(S) silencing was demonstrated by using a luciferase reporter and full-length beta(S) cDNA transfected into HeLa cells and mouse erythroleukemia cells, where it was expressed in the context of the endogenous beta-globin gene promoter and the locus control region enhancers. When this strategy was used to target beta(E), silencing was not limited to the mutant gene but also targeted the normal beta(A) gene. siRNAs, mismatched with their target at position 10, guided mRNA cleavage in all cases except when two bulky purines were aligned. The specific silencing of the beta(S)-globin gene, as compared with beta(E), as well as studies of silencing SNP mutants in other diseases, indicates that siRNAs developed to target a disease-causing SNP will be specific if the mutant residue is a pyrimidine and the normal residue is a purine.

Base Sequence↗
PubMed2006

Twin probes as a novel tool for the detection of single-nucleotide polymorphisms.

Single-nucleotide polymorphisms (SNPs) are the most common form of DNA sequence variation. There is a strong interest from both academy and industry to develop rapid, sensitive and cost effective methods for SNP detection. Here we report a novel structural concept for DNA detection based on fluorescence dequenching upon hybridization. The so-called "twin probe" consists of a central fluorene derivative as fluorophore to which two identical oligonucleotides are covalently attached. This probe architecture is applied in homogeneous hybridization assays with subsequent fluorescence spectroscopic analysis. The bioorganic hybrid structure is well suited for sequence specific DNA detection and even SNPs are identified with high efficiency. Additionally, the photophysical properties of the twin probe were investigated. The covalent attachment of two single stranded oligonucleotides leads to strong quenching of the central fluorescence dye induced by the nucleobases. The twin probe is characterized by supramolecular aggregate formation accompanied by red-shifted emission and broad fluorescence spectra.

Biochemistry↗
PubMed2000

Electrophoretic detection of single-nucleotide polymorphisms.

Single-nucleotide polymorphisms (SNPs) represent the most prevalent class of genetic markers available for linkage disequilibrium or cladistic analyses. PCR primers may be labeled with fluorescent dyes and used to rapidly and accurately differentiate among alleles that are defined by a single-nucleotide differences. Here, we describe the primer-mediated detection of SNPs based on primer mismatch during allele-specific amplification of preamplified target sequences. Primers are labeled with different fluors at their 5' nucleotides, with their 3' termini at the transition mutation that defines allelic variation at the target locus. Each primer perfectly matches one of the two available alleles for each locus. Electrophoretic detection permits characterization of the product both by size and fluor. This report demonstrates some of the capabilities of this assay, including heterozygote determination and multiplexed analysis.

Alleles↗
PubMed2000

A microsphere-based assay for multiplexed single nucleotide polymorphism analysis using single base chain extension.

A rapid, high throughput readout for single-nucleotide polymorphism (SNP) analysis was developed employing single base chain extension and cytometric analysis of an array of fluorescent microspheres. An array of fluorescent microspheres was coupled with uniquely identifying sequences, termed complementary ZipCodes (cZipCodes), which allowed for multiplexing possibilities. For a given assay, querying a polymorphic base involved extending an oligonucleotide containing both a ZipCode and a SNP-specific sequence with a DNA polymerase and a pair of fluoresceinated dideoxynucleotides. To capture the reaction products for analysis, the ZipCode portion of the oligonucleotide was hybridized with its cZipCodes on the microsphere. Flow cytometry was used for microsphere decoding and SNP typing by detecting the fluorescein label captured on the microspheres. In addition to multiplexing capability, the ZipCode system allows multiple sets of SNPs to be analyzed by a limited set of cZipCode-attached microspheres. A standard set of non-cross reactive ZipCodes was established experimentally and the accuracy of the system was validated by comparison with genotypes determined by other technologies. From a total of 58 SNPs, 55 SNPs were successfully analyzed in the first pass using this assay format and all 181 genotypes across the 55 SNPs were correct. These data demonstrate that the microsphere-based single base chain extension (SBCE) method is a sensitive and reliable assay. It can be readily adapted to an automated, high-throughput genotyping system. [Primer sequences used in this study are available as online supplementary materials at www.genome.org.]

DNA, Complementary↗