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At least 73 records · Page 4Linked to original sources
PubMed2005

Single-nucleotide polymorphism versus microsatellite markers in a combined linkage and segregation analysis of a quantitative trait.

Increasingly, single-nucleotide polymorphism (SNP) markers are being used in preference to microsatellite markers. However, methods developed for microsatellites may be problematic when applied to SNP markers. We evaluated the results of using SNPs vs. microsatellites in Monte Carlo Markov chain (MCMC) oligogenic combined segregation and linkage analysis methods. These methods were developed with microsatellite markers in mind. We selected chromosome 7 from the Collaborative Study on the Genetics of Alcoholism dataset for analysis because linkage to an electrophysiological trait had been reported there. We found linkage in the same region of chromosome 7 with the Affymetrix SNP data, the Illumina SNP data, and the microsatellite marker data. The MCMC sampler appears to mix with both types of data. The sampler implemented in this MCMC oligogenic combined segregation and linkage analysis appears to handle SNP data as well as microsatellite data and it is possible that the localizations with the SNP data are better.

Chromosome Mapping↗
PubMed2005

Rapid determination of trisomy 21 from amniotic fluid cells using single-nucleotide polymorphic loci.

OBJECTIVES: Rapid detection of trisomy 21 is an important goal for prenatal genetic centers. Fluorescent-PCR and DNA fragment analysis was developed a decade ago and thousands of samples were analyzed in routine practice using this method. Quantitative real-time PCR with melting curve analysis using SNP markers for trisomy 21 detection was described recently. We studied the reliability of this method on a cohort of samples of Hungarian patients. METHODS: DNA was isolated with silica adsorption method from amniotic fluid cells. We investigated 67 trisomy 21 and 62 diploid samples in the study. Quantitative real-time PCR was performed using hybridization probes combined with melting curve analysis. Peak areas under the derivative curves were determined and analyzed. RESULTS: The SNP marker WIAF 899 was informative in 41.86% of cases and WIAF 2643 in 48.83%. The melting curve area ratios were significantly different between trisomic and normal cases for WIAF 899 (trisomic 0.5246 +/- 0.2498 vs 0.8347 +/- 0.5234; p < 0.001), while in the case of WIAF 2643, they were not different. CONCLUSION: Combined and selected SNP markers could be valuable tools for rapid trisomy 21 detection in prenatal genetic screening.

Alleles↗
PubMed2002

Predicting the success of primer extension genotyping assays using statistical modeling.

Using an empirical panel of more than 20 000 single base primer extension (SNP-IT) assays we have developed a set of statistical scores for evaluating and rank ordering various parameters of the SNP-IT reaction to facilitate high-throughput assay primer design with improved likelihood of success. Each score predicts either signal magnitude from primer extension or signal noise caused by mispriming of primers and structure of the PCR product. All scores have been shown to correlate with the success/failure rate of the SNP-IT reaction, based on analysis of assay results. A logistic regression analysis was applied to combine all scored parameters into one measure predicting the overall success/failure rate of a given SNP marker. Three training sets for different types of SNP-IT reaction, each containing about 22 000 SNP markers, were used to assign weights to each score and optimize the prediction of the combined measure. c-Statistics of 0.69, 0.77 and 0.72 were achieved for three training sets. This new statistical prediction can be used to improve primer design for the SNP-IT reaction and evaluate the probability of genotyping success for a given SNP based on analysis of the surrounding genomic sequence.

DNA Primers↗
PubMed2004

Assessment of positional candidate genes myf5 and igf1 for growth on bovine chromosome 5 in commercial lines of Bos taurus.

Quantitative trait loci for growth traits in beef cattle have been previously reported and fine-mapped in three chromosomal regions of 0 to 30 cM, 55 to 70 cM, and 70 to 80 cM of bovine chromosome 5. In this study, we further examined the association between gene-specific single nucleotide polymorphisms (SNP) of two positional candidate genes, bovine myogenic factor 5 (myf5) and insulin-like growth factor-1 (igf1), in the QTL regions and the birth weight (BWT), preweaning average daily gain (PWADG), and average daily gain on feed (ADGF) in commercial lines of Bos taurus. The QTL regions for the growth traits identified using a haplotype association analysis, which included the gene-specific SNP markers for both genes in this study, were in agreement with previous studies. The gene-specific SNP marker association analysis indicated that the SNP in myf5 had a significant additive effect on PWADG in the M1 line of Beefbooster Inc. (P < 0.10), and a significant additive effect (P < 0.05) and a significant dominance effect (P < 0.10) on ADGF in the M3 line of Beefbooster Inc. When the data from the two commercial lines were pooled, the SNP in myf5 showed a significant association with PWADG (P < 0.10) and with ADGF (P < 0.05). The association between the SNP and BWT, however, did not reach a significance level in the M1 line, the M3 line, or across the lines. For igf1, no significant association between the SNP and the growth traits was detected in either the M1 line or the M3 line, whereas there was only a significant dominance effect (P < 0.10) on BWT detected for the SNP in igfl when the data from the two commercial lines were pooled. These results suggest that myf5 is a strong candidate gene that influences PWADG and ADGF in beef cattle. The SNP of igf1 may not be a causative or close to the causative mutation that affects the three growth traits in the populations of beef cattle examined in this study. Other SNP of igf1 and myf5 or other genes in their respective chromosomal regions, however, should also be studied.

Alleles↗
PubMed2004

A comparison of different strategies for computing confidence intervals of the linkage disequilibrium measure D'.

Many linkage disequilibrium (LD) measures have been used to study LD patterns and for haplotype block partitioning. We examine the properties of one of these measures, Lewontin's D', in order to understand the dependency of its confidence interval (CI) to allele frequency and sample size as well as its applications in defining haplotype blocks. This measure and its CIs were used to partition haplotypes into blocks by Gabriel et al. as well as in many other applications. Gabriel et al. utilized a bootstrap approach to calculate the CI for D'. Under this method, over 1,000 bootstrap samples may be needed to obtain an accurate estimate of the CI for each pair of single nucleotide polymorphism (SNP) markers which can be very computationally intensive, particularly when many SNP markers are involved. We develop two alternative methods for calculating the CI for D' without bootstrap: one based on the approximate variance of D' given by Zapata et al. and the other based on a maximum likelihood estimate (MLE) of D' together with Fisher Information theory. Both methods depend on normal approximation for the estimates of D' for large sample sizes. We assess and compare the coverage of the CIs using the three methods through extensive simulations. We define the coverage as the fraction of times the estimated CI contains the true value of D'. In general, the average coverage of the bootstrap method is less than the pre-specified coverage. When the sample size is small (< or = 100), the remaining two methods slightly under estimate the coverage with MLE approach having smaller standard error compared to Zapata's method. When the sample size is large (> or = 200) , the estimated coverage from both Zapata's and MLE methods are very close to the pre-specified coverage with the MLE method having the smallest standard error among all three methods. In most typical scenarios, we recommend the use of MLE method for all sample sizes. Only under rare specific cases, would the bootstrap method be better suited for determining the CI, i.e. small sample size, at extreme allele frequencies and -3 < D' < 0.

Computational Biology↗
PubMed2005

SNPLINK: multipoint linkage analysis of densely distributed SNP data incorporating automated linkage disequilibrium removal.

SUMMARY: SNPLINK is a Perl script that performs full genome linkage analysis of high-density single nucleotide polymorphism (SNP) marker sets. The presence of linkage disequilibrium (LD) between closely spaced SNP markers can falsely inflate linkage statistics. SNPLINK removes LD from the marker sets in an automated fashion before carrying out linkage analysis. SNPLINK can compute both parametric and non-parametric statistics, utilizing the freely available Allegro and Merlin software. Graphical outputs of whole genome multipoint linkage statistics are provided allowing comparison of results before and after the removal of LD.

Algorithms↗
PubMed2006

High-density SNP analysis of 642 Caucasian families with rheumatoid arthritis identifies two new linkage regions on 11p12 and 2q33.

We have completed a genome wide linkage scan using >5700 informative single-nucleotide polymorphism (SNP) markers (Illumina IV SNP linkage panel) in 642 Caucasian families containing affected sibling pairs with rheumatoid arthritis (RA), ascertained by the North American Rheumatoid Arthritis Consortium. The results show striking new evidence of linkage at chromosomes 2q33 and 11p12 with logarithm of odds (LOD) scores of 3.52 and 3.09, respectively. In addition to a strong and broad linkage interval surrounding the major histocompatibility complex (LOD>16), regions with LOD>2.5 were observed on chromosomes 5 and 10. Additional linkage evidence (LOD scores between 1.46 and 2.35) was also observed on chromosomes 4, 7, 12, 16 and 18. This new evidence for multiple regions of genetic linkage is partly explained by the significantly increased information content of the Illumina IV SNP linkage panel (75.6%) compared with a standard microsatellite linkage panel utilized previously (mean 52.6%). Stratified analyses according to whether or not the sibling pair members showed elevated anticyclic citrullinated peptide titers indicates significant variation in evidence for linkage among strata on chromosomes 4, 5, 6 and 7. Overall, these new linkage data should reinvigorate efforts to utilize positional information to identify susceptibility genes for RA.

Arthritis, Rheumatoid↗
PubMed2006

Haplotype-based quantitative trait mapping using a clustering algorithm.

BACKGROUND: With the availability of large-scale, high-density single-nucleotide polymorphism (SNP) markers, substantial effort has been made in identifying disease-causing genes using linkage disequilibrium (LD) mapping by haplotype analysis of unrelated individuals. In addition to complex diseases, many continuously distributed quantitative traits are of primary clinical and health significance. However the development of association mapping methods using unrelated individuals for quantitative traits has received relatively less attention. RESULTS: We recently developed an association mapping method for complex diseases by mining the sharing of haplotype segments (i.e., phased genotype pairs) in affected individuals that are rarely present in normal individuals. In this paper, we extend our previous work to address the problem of quantitative trait mapping from unrelated individuals. The method is non-parametric in nature, and statistical significance can be obtained by a permutation test. It can also be incorporated into the one-way ANCOVA (analysis of covariance) framework so that other factors and covariates can be easily incorporated. The effectiveness of the approach is demonstrated by extensive experimental studies using both simulated and real data sets. The results show that our haplotype-based approach is more robust than two statistical methods based on single markers: a single SNP association test (SSA) and the Mann-Whitney U-test (MWU). The algorithm has been incorporated into our existing software package called HapMiner, which is available from our website at http://www.eecs.case.edu/~jxl175/HapMiner.html. CONCLUSION: For QTL (quantitative trait loci) fine mapping, to identify QTNs (quantitative trait nucleotides) with realistic effects (the contribution of each QTN less than 10% of total variance of the trait), large samples sizes (>or= 500) are needed for all the methods. The overall performance of HapMiner is better than that of the other two methods. Its effectiveness further depends on other factors such as recombination rates and the density of typed SNPs. Haplotype-based methods might provide higher power than methods based on a single SNP when using tag SNPs selected from a small number of samples or some other sources (such as HapMap data). Rank-based statistics usually have much lower power, as shown in our study.

Algorithms↗
PubMed2005

Estimation of the extent of linkage disequilibrium in seven regions of the porcine genome.

Linkage disequilibrium (LD) refers to the correlation among neighboring alleles, reflecting non-random patterns of association between alleles at (nearby) loci. A better understanding of LD in the porcine genome is of direct relevance for identification of genes and mutations with a certain effect on the traits of interest. Here, 215 SNPs in seven genomic regions were genotyped in individuals of three breeds. Pairwise linkage disequilibrium was calculated for all marker pairs. To estimate the extent of LD, all pairwise LD values were plotted against the distance between the markers. Based on SNP markers in four genomic regions analyzed in three panels from populations of Large White, Dutch Landrace, and Meishan origin, useful LD is estimated to extend for approximately 40 to 60 kb in the porcine genome.

Animals↗
PubMed2002

Detection of allelic imbalance in ascitic supernatant by digital single nucleotide polymorphism analysis.

PURPOSE: Cytological examination of ascitic fluid is critical for clinical management of patients with peritoneal or pelvic diseases. Such morphological examination can only achieve a sensitivity of <62%, and thus a molecular test that is able to distinguish benign versus malignant ascites could be clinically useful. In this study we determined the presence of allelic imbalance (AI) in tumor-released DNA in ascitic supernatant by directly counting the alleles using a newly developed technology, digital single nucleotide polymorphism (SNP) analysis. EXPERIMENTAL DESIGN: Allelic status was assessed using a total of seven SNP markers that commonly demonstrated AI in ovarian, colorectal, and pancreatic cancers. RESULTS: With digital SNP analysis, AI in at least one SNP marker was found in 19 of 20 (95%) ascitic fluid DNA samples obtained from patients with cytologically proven carcinomas in ascitic fluid. In contrast, AI was detected in only 1 of 20 patients with negative cytology. This latter patient with AI in her ascites had known stage III ovarian carcinoma at the time of cytology sampling. The ascitic specimen of this patient demonstrated the presence of carcinoma cells in culture with an identical AI pattern found in the ascitic supernatant and surgical specimen. CONCLUSIONS: These findings suggest that detection of AI using digital SNP analysis can be a useful adjunct for the detection of ovarian and other types of cancer in ascitic fluid.

Alleles↗
PubMed2006

Meta-analysis shows strong positive association of the neuregulin 1 (NRG1) gene with schizophrenia.

Chromosome 8p22-p11 has been identified as a locus for schizophrenia in several genome-wide scans and confirmed by meta-analysis of published linkage data. Systematic fine mapping using extended Icelandic pedigrees identified an associated haplotype in the gene neuregulin 1 (NRG1), also known as heuregulin, glial growth factor, NDF43 and ARIA. A 290 kb core at risk haplotype at the 5' end of the gene (HAP(ICE)), defined by five SNPs and two microsatellite polymorphisms was found to be associated with schizophrenia in the Icelandic and Scottish populations. A number of subsequent independent studies have attempted to replicate the association, and while some have been successful, the associated haplotype is not always HAP(ICE). Furthermore, no obviously functional or pathogenic variants have been identified, and the relationship between the gene and schizophrenia has remained inconclusive. To reconcile these conflicting findings and to give a comprehensive picture of the genetic architecture of this important gene, we performed a meta-analysis of 13 published population-based and family-based association studies up to November 2005. We analysed data from the SNP markers SNP8NRG241930, SNP8NRG243177, SNP8NRG221132 and SNP8NRG221533, and the microsatellite markers 478B14-848, 420M9-1395. Across these studies, strong positive association was found for all six polymorphisms. The haplotype analysis also showed significant association in the pooled international populations (OR=1.22, 95% CI 1.15-1.3, P=8 x 10(-10)). In Asian populations, the risk haplotype was focused around the two microsatellite markers, 478B14-848, 420M9-1395 (haplotype block B), and in Caucasian populations with the remaining four SNP markers (haplotype block A). This meta-analysis supports the involvement of NRG1 in the pathogenesis of schizophrenia, but with association between two different but adjacent haplotypes blocks in the Caucasian and Asian populations.

Asian People↗
PubMed2004

Development of a SNP genotyping panel for genetic monitoring of the laboratory mouse.

We have developed a genotyping system for detecting genetic contamination in the laboratory mouse based on assaying single-nucleotide polymorphism (SNP) markers positioned on all autosomes and the X chromosome. This system provides a fast, reliable, and cost-effective way for genetic monitoring, while maintaining a very high degree of confidence. We describe the allelic distribution of 235 SNPs in 48 mouse strains, thereby creating a database of polymorphisms useful for genotyping purposes. The SNP markers used in this study were chosen from publicly available SNP databases. Four genotyping methods were evaluated, and dynamic two-tube allele-specific PCR assays were developed for each marker and tested on a set of 48 inbred mouse strains. The minimal number of assays sufficient to distinguish groups consisting of different numbers of mouse strains was estimated, and a panel of 28 SNPs sufficient to distinguish virtually all of the inbred strains tested was selected. Amplifluor SNP detection assays were developed for these markers and tested on an extended list of 96 strains. This panel was used as a genetic quality control approach to monitor the genotypes of nearly 300 inbred, wild-derived, congenic, consomic, and recombinant inbred strains maintained at The Jackson Laboratory. We have concluded that this marker panel is sufficient for genetic contamination monitoring in colonies containing a large number of genetically diverse mouse strains and that reduced versions of the panel could be implemented in facilities housing a lower number of strains.

Alleles↗
PubMed2005

Selection of single-nucleotide polymorphisms in disease association data.

We studied several methods for selecting single-nucleotide polymorphisms (SNPs) in a disease association study. Two major categories for analytical strategy are the univariate and the set selection approaches. The univariate approach evaluates each SNP marker one at a time, while the set selection approach tests disease association of a set of SNP markers simultaneously. We examined various test statistics that can be utilized in testing disease association and also reviewed several multiple testing procedures that can properly control the family-wise error rates when the univariate approach is applied to multiple markers. The set association methods were then briefly reviewed. Finally, we applied these methods to the data from Collaborative Study on the Genetics of Alcoholism (COGA).

Databases, Genetic↗
PubMed2003

Genetic maps of microsatellite and single-nucleotide polymorphism markers: are the distances accurate?

Genetic maps play an important role in gene mapping. Inaccurate genetic maps can hinder gene mapping by biasing lod scores and reducing the power to map a trait to a particular region. Although sequence-based physical maps can provide a unique order for markers, they do not provide information on genetic map distances. By simulation studies, I investigated how many meioses are necessary to accurately estimate genetic map distances for maps constructed from microsatellite and single-nucleotide polymorphism (SNP) markers for various intermarker distances and marker heterozygosity. To evaluate the accuracy of the generated genetic maps, the length of the 95% confidence interval for intermarker genetic distances was examined. In addition, the power to separate two adjacent markers by a nonzero map distance was investigated. The number of meioses necessary to accurately estimate map distances depends greatly not only on intermarker distances but also on marker heterozygosity. For example, for a genetic map with intermarker distances of 0.5 cM generated with 1,000 meioses, when marker heterozygosity was high (0.90), for 96% of the markers there was a nonzero map distance between adjacent markers. However, when marker heterozygosity was low (0.32), only 48% of the markers mapped to a unique position. For identical numbers of meioses and intermarker distances, genetic maps constructed from microsatellite markers will be more precise than maps assembled from SNP markers, due to the higher levels of heterozygosity for microsatellite markers.

Adult↗
PubMed2002

New generation pharmacogenomic tools: a SNP linkage disequilibrium Map, validated SNP assay resource, and high-throughput instrumentation system for large-scale genetic studies.

Since public and private efforts announced the first draft of the human genome last year, researchers have reported great numbers of single nucleotide polymorphisms (SNPs). We believe that the availability of well-mapped, quality SNP markers constitutes the gateway to a revolution in genetics and personalized medicine that will lead to better diagnosis and treatment of common complex disorders. A new generation of tools and public SNP resources for pharmacogenomic and genetic studies--specifically for candidate-gene, candidate-region, and whole-genome association studies--will form part of the new scientific landscape. This will only be possible through the greater accessibility of SNP resources and superior high-throughput instrumentation-assay systems that enable affordable, highly productive large-scale genetic studies. We are contributing to this effort by developing a high-quality linkage disequilibrium SNP marker map and an accompanying set of ready-to-use, validated SNP assays across every gene in the human genome. This effort incorporates both the public sequence and SNP data sources, and Celera Genomics' human genome assembly and enormous resource ofphysically mapped SNPs (approximately 4,000,000 unique records). This article discusses our approach and methodology for designing the map, choosing quality SNPs, designing and validating these assays, and obtaining population frequency ofthe polymorphisms. We also discuss an advanced, high-performance SNP assay chemisty--a new generation of the TaqMan probe-based, 5' nuclease assay-and high-throughput instrumentation-software system for large-scale genotyping. We provide the new SNP map and validation information, validated SNP assays and reagents, and instrumentation systems as a novel resource for genetic discoveries.

Alleles↗
PubMed1997

The homozygous complete hydatidiform mole: a unique resource for genome studies.

The most frequent type of complete hydatidiform mole is a 46, XX homozygote formed by the fertilization of an empty ovum by a single haploid sperm that later duplicates its chromosomes to give a diploid tumor. The homozygous nature of these complete hydatidiform moles makes them unique resources for human genome studies. They can serve as homozygous controls in the development of single nucleotide polymorphism (SNP) markers and provide a way to obtain long-range haplotypes that are useful in population studies. The use of a homozygous control makes it possible to estimate the allele frequencies of the SNP markers in any population by sequencing pooled DNA samples. In this report, we present evidence of homozygosity of a complete hydatidiform mole using 20 diallelic markers distributed across the genome. Furthermore, its usefulness as a homozygous control in SNP development and as a resource for long-range haplotype determination is demonstrated using 11 newly discovered loci in the BRCA2 region on chromosome 13q12-q13.

BRCA2 Protein↗
PubMed2004

Association study of dopamine transporter gene and schizophrenia in Korean population using multiple single nucleotide polymorphism markers.

Inherited or acquired dysfunction of the dopamine system is believed to underlie the core symptoms of schizophrenia, and there are some evidences that dopamine transporter activity may be altered in schizophrenic patients. Therefore, dopamine transporter gene (DAT1) has been traditionally considered a probable candidate gene for the association study of schizophrenia. Until now, association studies of the dopamine transporter gene (DAT1) with schizophrenia have yielded largely negative results. However, these results cannot be regarded as conclusive in that they were all obtained from just a single marker, that is, 3' untranslated region variable number of tandem repeat (VNTR). We have therefore tried to find other single nucleotide polymorphisms (SNPs) in DAT1 gene and to use them as additional markers for the association study of schizophrenia. Searching for the SNPs had been done with 50 Korean schizophrenic patients. DNA sequences encompassing the whole exon and flanking exon-intron junctions were amplified and searched for the presence of SNPs. Total of five SNPs were found. Among these, three SNPs (1215A>G, 1398C>T, IVS11+14G>A) as well as the 3' untranslated region VNTR were selected as the markers to be genotyped. The allelic and genotypic frequencies of these markers were determined in 252 schizophrenic patients and 271 controls and compared between them. The frequencies of algorithmically derived haplotypes were also compared. No evidence of association was found between any of these markers and schizophrenia. The result using haplotypes was also negative. However, when the patient subgroup with verified familial history and the subgroup with early age of onset were re-analyzed, weak trend of association between 1398C>T SNP marker with schizophrenia was found in both cases. In accordance with the previous literature, we could not find any evidence of association between DAT1 gene and schizophrenia. This result acquired more certainty because not only the VNTR but several SNPs present in DAT1 gene and newly constructed haplotypes were also used as additional markers. However, the finding of weak association between one of the SNP markers (1398C>T) and the specific subgroups of schizophrenia patients added further support to the importance of defining more homogenous subgroups in association studies.

3' Untranslated Regions↗
PubMed2004

Comparison of microsatellites versus single-nucleotide polymorphisms in a genome linkage screen for prostate cancer-susceptibility Loci.

Prostate cancer is one of the most common cancers among men and has long been recognized to occur in familial clusters. Brothers and sons of affected men have a 2-3-fold increased risk of developing prostate cancer. However, identification of genetic susceptibility loci for prostate cancer has been extremely difficult. Although the suggestion of linkage has been reported for many chromosomes, the most promising regions have been difficult to replicate. In this study, we compare genome linkage scans using microsatellites with those using single-nucleotide polymorphisms (SNPs), performed in 467 men with prostate cancer from 167 families. For the microsatellites, the ABI Prism Linkage Mapping Set version 2, with 402 microsatellite markers, was used, and, for the SNPs, the Early Access Affymetrix Mapping 10K array was used. Our results show that the presence of linkage disequilibrium (LD) among SNPs can lead to inflated LOD scores, and this seems to be an artifact due to the assumption of linkage equilibrium that is required by the current genetic-linkage software. After excluding SNPs with high LD, we found a number of new LOD-score peaks with values of at least 2.0 that were not found by the microsatellite markers: chromosome 8, with a maximum model-free LOD score of 2.2; chromosome 2, with a LOD score of 2.1; chromosome 6, with a LOD score of 4.2; and chromosome 12, with a LOD score of 3.9. The LOD scores for chromosomes 6 and 12 are difficult to interpret, because they occurred only at the extreme ends of the chromosomes. The greatest gain provided by the SNP markers was a large increase in the linkage information content, with an average information content of 61% for the SNPs, versus an average of 41% for the microsatellite markers. The strengths and weaknesses of microsatellite versus SNP markers are illustrated by the results of our genome linkage scans.

Chromosome Mapping↗