SEARCH · PubMed Health

Results for “Haplotypes”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 1,351 records · Page 75Linked to original sources

PubMed2003

Selection of genetic markers for association analyses, using linkage disequilibrium and haplotypes.

The genotyping of closely spaced single-nucleotide polymorphism (SNP) markers frequently yields highly correlated data, owing to extensive linkage disequilibrium (LD) between markers. The extent of LD varies widely across the genome and drives the number of frequent haplotypes observed in small regions. Several studies have illustrated the possibility that LD or haplotype data could be used to select a subset of SNPs that optimize the information retained in a genomic region while reducing the genotyping effort and simplifying the analysis. We propose a method based on the spectral decomposition of the matrices of pairwise LD between markers, and we select markers on the basis of their contributions to the total genetic variation. We also modify Clayton's "haplotype tagging SNP" selection method, which utilizes haplotype information. For both methods, we propose sliding window-based algorithms that allow the methods to be applied to large chromosomal regions. Our procedures require genotype information about a small number of individuals for an initial set of SNPs and selection of an optimum subset of SNPs that could be efficiently genotyped on larger numbers of samples while retaining most of the genetic variation in samples. We identify suitable parameter combinations for the procedures, and we show that a sample size of 50-100 individuals achieves consistent results in studies of simulated data sets in linkage equilibrium and LD. When applied to experimental data sets, both procedures were similarly effective at reducing the genotyping requirement while maintaining the genetic information content throughout the regions. We also show that haplotype-association results that Hosking et al. obtained near CYP2D6 were almost identical before and after marker selection.

Alleles↗

PubMed2003

A haplotype implicated in schizophrenia susceptibility is associated with reduced COMT expression in human brain.

The gene encoding catechol-O-methyltransferase (COMT) is a strong candidate for schizophrenia susceptibility, owing to the role of COMT in dopamine metabolism, and the location of the gene within the deleted region in velocardiofacial syndrome, a disorder associated with high rates of schizophrenia. Recently, a highly significant association was reported between schizophrenia and a COMT haplotype in a large case-control sample (Shifman et al. 2002). In addition to a functional valine-->methionine (Val/Met) polymorphism, this haplotype included two noncoding single-nucleotide polymorphisms (SNPs) at either end of the COMT gene. Given the role of COMT in dopamine catabolism and that deletion of 22q11 (containing COMT) is associated with schizophrenia, we postulated that the susceptibility COMT haplotype is associated with low COMT expression. To test this hypothesis, we have applied quantitative measures of allele-specific expression using mRNA from human brain. We demonstrate that COMT is subject to allelic differences in expression in human brain and that the COMT haplotype implicated in schizophrenia (Shifman et al. 2002) is associated with lower expression of COMT mRNA. We also show that the 3' flanking region SNP that gave greatest evidence for association with schizophrenia in that study is transcribed in human brain and exhibits significant differences in allelic expression, with lower relative expression of the associated allele. Our results indicate that COMT variants other than the Val/Met change are of functional importance in human brain and that the haplotype implicated in schizophrenia susceptibility is likely to exert its effect, directly or indirectly, by down-regulating COMT expression.

Brain↗

PubMed2003

Confirmation of the type 2 myotonic dystrophy (CCTG)n expansion mutation in patients with proximal myotonic myopathy/proximal myotonic dystrophy of different European origins: a single shared haplotype indicates an ancestral founder effect.

Myotonic dystrophy (DM), the most common form of muscular dystrophy in adults, is a clinically and genetically heterogeneous neuromuscular disorder. DM is characterized by autosomal dominant inheritance, muscular dystrophy, myotonia, and multisystem involvement. Type 1 DM (DM1) is caused by a (CTG)(n) expansion in the 3' untranslated region of DMPK in 19q13.3. Multiple families, predominantly of German descent and with clinically variable presentation that included proximal myotonic myopathy (PROMM) and type 2 DM (DM2) but without the DM1 mutation, showed linkage to the 3q21 region and were recently shown to segregate a (CCTG)(n) expansion mutation in intron 1 of ZNF9. Here, we present linkage to 3q21 and mutational confirmation in 17 kindreds of European origin with PROMM and proximal myotonic dystrophy, from geographically distinct populations. All patients have the DM2 (CCTG)(n) expansion. To study the evolution of this mutation, we constructed a comprehensive physical map of the DM2 region around ZNF9. High-resolution haplotype analysis of disease chromosomes with five microsatellite and 22 single-nucleotide polymorphism markers around the DM2 mutation identified extensive linkage disequilibrium and a single shared haplotype of at least 132 kb among patients from the different populations. With the exception of the (CCTG)(n) expansion, the available markers indicate that the DM2 haplotype is identical to the most common haplotype in normal individuals. This situation is reminiscent of that seen in DM1. Taken together, these data suggest a single founding mutation in DM2 patients of European origin. We estimate the age of the founding haplotype and of the DM2 (CCTG) expansion mutation to be approximately 200-540 generations.

Base Sequence↗

PubMed2003

Haplotypes in the dystrophin DNA segment point to a mosaic origin of modern human diversity.

Although Africa has played a central role in human evolutionary history, certain studies have suggested that not all contemporary human genetic diversity is of recent African origin. We investigated 35 simple polymorphic sites and one T(n) microsatellite in an 8-kb segment of the dystrophin gene. We found 86 haplotypes in 1,343 chromosomes from around the world. Although a classical out-of-Africa topology was observed in trees based on the variant frequencies, the tree of haplotype sequences reveals three lineages accounting for present-day diversity. The proportion of new recombinants and the diversity of the T(n) microsatellite were used to estimate the age of haplotype lineages and the time of colonization events. The lineage that underwent the great expansion originated in Africa prior to the Upper Paleolithic (27,000-56,000 years ago). A second group, of structurally distinct haplotypes that occupy a central position on the tree, has never left Africa. The third lineage is represented by the haplotype that lies closest to the root, is virtually absent in Africa, and appears older than the recent out-of-Africa expansion. We propose that this lineage could have left Africa before the expansion (as early as 160,000 years ago) and admixed, outside of Africa, with the expanding lineage. Contemporary human diversity, although dominated by the recently expanded African lineage, thus represents a mosaic of different contributions.

Africa↗

PubMed2004

Incorporating genotyping uncertainty in haplotype inference for single-nucleotide polymorphisms.

The accuracy of the vast amount of genotypic information generated by high-throughput genotyping technologies is crucial in haplotype analyses and linkage-disequilibrium mapping for complex diseases. To date, most automated programs lack quality measures for the allele calls; therefore, human interventions, which are both labor intensive and error prone, have to be performed. Here, we propose a novel genotype clustering algorithm, GeneScore, based on a bivariate t-mixture model, which assigns a set of probabilities for each data point belonging to the candidate genotype clusters. Furthermore, we describe an expectation-maximization (EM) algorithm for haplotype phasing, GenoSpectrum (GS)-EM, which can use probabilistic multilocus genotype matrices (called "GenoSpectrum") as inputs. Combining these two model-based algorithms, we can perform haplotype inference directly on raw readouts from a genotyping machine, such as the TaqMan assay. By using both simulated and real data sets, we demonstrate the advantages of our probabilistic approach over the current genotype scoring methods, in terms of both the accuracy of haplotype inference and the statistical power of haplotype-based association analyses.

Algorithms↗

PubMed2002

Single-nucleotide polymorphisms and haplotype analysis in beta-defensin genes in different ethnic populations.

Beta-defensins are cationic antimicrobial peptides expressed by epithelial cells and exhibit antibacterial, antifungal, and antiviral properties. The defensins are part of the innate host defense network and may have a significant protective role in the oral cavity and other mucosa. Defects or alteration in expression of the beta-defensins may be associated with susceptibility to infection and mucosal disorders. We examined the occurrence of single-nucleotide polymorphisms (SNPs) in the human beta-defensin genes DEFB1 and DEFB2 encoding human beta-defensin-1 and -2 (hBD-1, hBD-2), respectively, in five ethnic populations and defined haplotypes in these populations. Fifteen SNPs were identified in both DEFB1 and DEFB2. Coding region SNPs were found in very low frequency in both genes. One nonsynonymous DEFB1 SNP, G1654A (Val --> Ile), and one nonsynonymous DEFB2 SNP, T2312A (Leu --> His), were identified. Seven sites in each gene exhibited statistically significant differences in frequency between ethnic groups, with the greatest variation in the promoter and in the 5'-untranslated region of DEFB1. DEFB1 displayed 10 common haplotypes, including one cosmopolitan haplotype. Eight common haplotypes were found in DEFB2, including one cosmopolitan haplotype shared among all five ethnic groups. Our results show that genotypic variability among ethnic groups will need to be addressed when performing associative genetic studies of innate defense mechanisms and susceptibility to disease.

Haplotypes↗

PubMed2006

An optimal algorithm for perfect phylogeny haplotyping.

Inferring haplotype data from genotype data is a crucial step in linking SNPs to human diseases. Given n genotypes over m SNP sites, the haplotype inference (HI) problem deals with finding a set of haplotypes so that each given genotype can be formed by a combining a pair of haplotypes from the set. The perfect phylogeny haplotyping (PPH) problem is one of the many computational approaches to the HI problem. Though it was conjectured that the complexity of the PPH problem was O(nm), the complexity of all the solutions presented until recently was O(nm (2)). In this paper, we make complete use of the column-ordering that was presented earlier and show that there must be some interdependencies among the pairwise relationships between SNP sites in order for the given genotypes to allow a perfect phylogeny. Based on these interdependencies, we introduce the FlexTree (flexible tree) data structure that represents all the pairwise relationships in O(m) space. The FlexTree data structure provides a compact representation of all the perfect phylogenies for the given set of genotypes. We also introduce an ordering of the genotypes that allows the genotypes to be added to the FlexTree sequentially. The column ordering, the FlexTree data structure, and the row ordering we introduce make the O(nm) OPPH algorithm possible. We present some results on simulated data which demonstrate that the OPPH algorithm performs quiet impressively when compared to the previous algorithms. The OPPH algorithm is one of the first O(nm) algorithms presented for the PPH problem.

Algorithms↗

PubMed2003

Efficient selective screening of haplotype tag SNPs.

UNLABELLED: Haplotypes defined by common single nucleotide polymorphisms (SNPs) have important implications for mapping of disease genes and human traits. Often only a small subset of the SNPs is sufficient to capture the full haplotype information. Such subsets of markers are called haplotype tagging SNPs (htSNPs). Although htSNPs can be identified by eye, efficient computer algorithms and flexible interactive software tools are required for large datasets such as the human genome haplotype map. We describe a java-based program, SNPtagger, which screens for minimal sets of SNP markers to represent given haplotypes according to various user requirements. The program offers several options for inclusion/exclusion of specific markers and presents alternative panels for final selection. AVAILABILITY: The www-based program is available at http://www.well.ox.ac.uk/~xiayi/haplotype/index.html.

Algorithms↗

PubMed2003

HaploBlockFinder: haplotype block analyses.

UNLABELLED: Recent studies have unveiled discrete block-like structures of linkage disequilibrium (LD) in the human genome. We have developed a set of computer programs to analyze the block-like LD structures (haplotype blocks) based on haplotype data. Three definitions of haplotype block are supported, including minimal LD range, no historic recombination, and chromosome coverage. Tagged SNPs that uniquely distinguish common haplotypes are identified. A greedy algorithm was used to improve the efficiency. Two separate utilities were also provided to assist visual inspection of haplotype block structure and pattern of linkage disequilibrium. AVAILABILITY: A web interface for the HaploBlockFinder is available at http://cgi.uc.edu/cgi-bin/kzhang/haploBlockFinder.cgi the source codes are also freely available on the web site.

Algorithms↗

PubMed2004

High density linkage disequilibrium mapping using models of haplotype block variation.

MOTIVATION: The presence of millions of single nucleotide polymorphisms (SNPs) in the human genome has spurred interest in genetic mapping methods based on linkage disequilibrium. The recently discovered haplotype block structure of human variation promises to improve the effectiveness of these methods. A key difficulty for mapping techniques is the cost involved in separately identifying the haplotypes on each of an individual's chromosomes. RESULTS: We present a new approach for performing linkage disequilibrium mapping using high density haplotype or genotype data. Our method is based on a statistical model of haplotype block variation, which takes account of recombination hotspots, bottlenecks, genetic drift and mutation. We test our technique on two empirically determined high density datasets, attempting to recover the location of an SNP which was hidden and converted into phenotype information. We compare the results against a mapping method based on individual SNPs as well as a competing haplotype-based approach. We show that our strategy significantly outperforms these other approaches when used as a guide for resequencing and that it can also deal with both unphased genotype data and low penetrance diseases. AVAILABILITY: HaploBlock executables for Linux, Mac OS X and Sun OS, as well as user documentation, are available online at http://bioinfo.cs.technion.ac.il/haploblock/

Artificial Intelligence↗

PubMed2005

Haplotype reconstruction from SNP fragments by minimum error correction.

MOTIVATION: Haplotype reconstruction based on aligned single nucleotide polymorphism (SNP) fragments is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. An important computational model of this problem is the minimum error correction (MEC) model, which has been mentioned in several literatures. The model retrieves a pair of haplotypes by correcting minimum number of SNPs in given genome fragments coming from an individual's DNA. RESULTS: In the first part of this paper, an exact algorithm for the MEC model is presented. Owing to the NP-hardness of the MEC model, we also design a genetic algorithm (GA). The designed GA is intended to solve large size problems and has very good performance. The strength and weakness of the MEC model are shown using experimental results on real data and simulation data. In the second part of this paper, to improve the MEC model for haplotype reconstruction, a new computational model is proposed, which simultaneously employs genotype information of an individual in the process of SNP correction, and is called MEC with genotype information (shortly, MEC/GI). Computational results on extensive datasets show that the new model has much higher accuracy in haplotype reconstruction than the pure MEC model.

Algorithms↗

PubMed2005

A parsimonious tree-grow method for haplotype inference.

MOTIVATION: Haplotype information has become increasingly important in analyzing fine-scale molecular genetics data, such as disease genes mapping and drug design. Parsimony haplotyping is one of haplotyping problems belonging to NP-hard class. RESULTS: In this paper, we aim to develop a novel algorithm for the haplotype inference problem with the parsimony criterion, based on a parsimonious tree-grow method (PTG). PTG is a heuristic algorithm that can find the minimum number of distinct haplotypes based on the criterion of keeping all genotypes resolved during tree-grow process. In addition, a block-partitioning method is also proposed to improve the computational efficiency. We show that the proposed approach is not only effective with a high accuracy, but also very efficient with the computational complexity in the order of O(m2n) time for n single nucleotide polymorphism sites in m individual genotypes. AVAILABILITY: The software is available upon request from the authors, or from http://zhangroup.aporc.org/bioinfo/ptg/ CONTACT: chen@elec.osaka-sandai.ac.jp SUPPLEMENTARY INFORMATION: Supporting materials is available from http://zhangroup.aporc.org/bioinfo/ptg/bti572supplementary.pdf

Algorithms↗

PubMed2006

WHAP: haplotype-based association analysis.

UNLABELLED: We describe a software tool to perform haplotype-based association analysis, for quantitative and qualitative traits, in population and family samples, using single nucleotide polymorphism or multiallelic marker data. A range of tests is offered: omnibus and haplotype-specific tests; prospective and retrospective likelihoods; covariates and moderators; sliding window analyses; permutation P-values. We focus on the ability to flexibly impose constraints on haplotype effects, which allows for a range of conditional haplotype-based likelihood ratio tests: for example, whether an allele has an effect independent of its haplotypic background, or whether a single variant can explain the overall association at a locus. We illustrate using these tests to dissect a multi-locus association. AVAILABILITY: WHAP is a C/C++ program, freely available from the author's website: http://pngu.mgh.harvard.edu/purcell/whap/

Algorithms↗

PubMed2003

Estimating haplotype frequencies and standard errors for multiple single nucleotide polymorphisms.

Estimating haplotype frequencies becomes increasingly important in the mapping of complex disease genes, as millions of single nucleotide polymorphisms (SNPs) are being identified and genotyped. When genotypes at multiple SNP loci are gathered from unrelated individuals, haplotype frequencies can be accurately estimated using expectation-maximization (EM) algorithms (Excoffier and Slatkin, 1995; Hawley and Kidd, 1995; Long et al., 1995), with standard errors estimated using bootstraps. However, because the number of possible haplotypes increases exponentially with the number of SNPs, handling data with a large number of SNPs poses a computational challenge for the EM methods and for other haplotype inference methods. To solve this problem, Niu and colleagues, in their Bayesian haplotype inference paper (Niu et al., 2002), introduced a computational algorithm called progressive ligation (PL). But their Bayesian method has a limitation on the number of subjects (no more than 100 subjects in the current implementation of the method). In this paper, we propose a new method in which we use the same likelihood formulation as in Excoffier and Slatkin's EM algorithm and apply the estimating equation idea and the PL computational algorithm with some modifications. Our proposed method can handle data sets with large number of SNPs as well as large numbers of subjects. Simultaneously, our method estimates standard errors efficiently, using the sandwich-estimate from the estimating equation, rather than the bootstrap method. Additionally, our method admits missing data and produces valid estimates of parameters and their standard errors under the assumption that the missing genotypes are missing at random in the sense defined by Rubin (1976).

Algorithms↗

PubMed2006

A Belgian ancestral haplotype harbours a highly prevalent mutation for 17q21-linked tau-negative FTLD.

Among patients with frontotemporal lobar degeneration (FTLD), the respective frequencies of dominant 17q21-linked tau-negative FTLD (with unidentified molecular defect) and 17q21-linked tau-positive FTLD (due to MAPT mutations) remain unknown. Here, in a series of 98 genealogically unrelated Belgian FTLD patients, we identified an ancestral 8 cM MAPT containing haplotype in two patients belonging to multiplex families DR2 and DR8, without demonstrable MAPT mutations, in which FTLD was conclusively linked to 17q21 [maximum summed log of the odds (LOD) score of 5.28 at D17S931]. Interestingly, the same DR2-DR8 ancestral haplotype was observed in five additional familial FTLD patients, indicative of a founder effect. In the FTLD series, the DR2-DR8 ancestral haplotype explained 7% (7 out of 98) of FTLD and 17% (7 out of 42) of familial FTLD and was seven times more frequent than MAPT mutations (1 out of 98 or 1%). Clinically, DR2-DR8 haplotype carriers presented with FTLD often characterized by language impairment, and in one carrier the neuropathological diagnosis was FTLD with rare tau-negative ubiquitin-positive inclusions. Together, these results strongly suggest that the DR2-DR8 founder haplotype at 17q21 harbours a tau-negative FTLD causing mutation that is a much more frequent cause of FTLD in Belgium than MAPT mutations.

Adolescent↗

PubMed1995

P53 germ line haplotypes associated with increased risk for colorectal cancer.

Three p53 DNA polymorphisms (BstU I and Msp I restriction fragment length polymorphisms (RFLPs) in exon 4 and intron 6 respectively, and a 16 bp duplication in intron 3) and their haplotype combinations were studied in patients with colorectal cancer and compared with patients with ulcerative colitis and healthy controls. There were only minor differences between patients with ulcerative colitis and controls, the only significant difference was observed in the distribution of BstU I-Msp I haplotypes. When single polymorphisms were studied, a significantly lower frequency of the 16 bp duplication was found in patients with colorectal cancer. The protective effect of the 16 bp duplication was more pronounced in haplotype combinations with the BstU I A1 and Msp I A1 alleles, whereas these alleles in combination with the 16 bp A1 allele (no duplication) were associated with an increased risk for colorectal cancer. The genotypic combination BstU I 2-1, 16 bp 1-I, Msp I 2-1 was found in 8.4% of cases among patients with colorectal cancer and 0.5% of cases in the controls (odds ratio = 18.8). The extended haplotype responsible for the high cancer risk of this genotype appears to be BstU I A1-16 bp A1-Msp I A1. The results of this study indicate that the haplotype approach to the identification of p53 germ line alleles associated with increased susceptibility to cancer is far more powerful than the analysis of single polymorphisms, since the capacity to identify germ line alleles predisposing to cancer should increase with the number of polymorphic sites included in the analysis.

Alleles↗

PubMed2006

Polymorphisms and haplotypes of the NBS1 gene are associated with risk of sporadic breast cancer in non-Hispanic white women <or=55 years.

DNA double-strand breaks (DSBs) may lead to genomic instability and cancer if unrepaired. Nijmegen breakage syndrome 1 (NBS1) protein is one of the key proteins that participates in recognition and repair of DSBs in humans. We hypothesized that polymorphisms of NBS1 are associated with breast cancer risk. We selected three NBS1 haplotype-tagging polymorphisms (i.e. 924T>C, 8360G>C and 30537G>C) to represent all common (>or=5%) haplotypes reported in the National Institute of Environmental Health Sciences database and to reconstruct haplotypes. In a hospital-based case-control study of 421 non-Hispanic white patients with sporadic breast cancer ( C polymorphism. Furthermore, the derived haplotypes were associated with risk in a dose-response manner as the number of variant (risk) alleles (i.e. 8360C, 924C or 30537C) increased (adjusted OR = 1.07, 95% CI = 0.78-1.46 for 1-2 variant alleles; adjusted OR = 2.47, 95% CI = 1.48-4.14 for 3-6 variant alleles; P(trend) = 0.006). These findings suggest that NBS1 polymorphisms and haplotypes may contribute to the etiology of sporadic breast cancer in young non-Hispanic white women. Large studies are warranted to confirm these findings.

Aged↗

PubMed2006

C-reactive protein gene haplotypes and risk of coronary heart disease: the Rotterdam Study.

AIMS: C-reactive protein is associated with risk of cardiovascular disease. However, whether C-reactive protein is a marker of severity of cardiovascular disease or actually is involved in its pathogenesis remains unknown. We investigated the relation between C-reactive protein haplotypes, representing the comprehensive variation of the C-reactive protein gene, and coronary heart disease. METHODS AND RESULTS: The Rotterdam Study is a prospective population-based study among men and women aged 55 years and older. C-reactive protein was associated with risk of coronary heart disease, with a multivariable adjusted hazard ratio of 1.9 (95% CI 1.5-2.4) for the highest vs. the lowest quartile. Four C-reactive protein haplotypes were present with overall frequencies of 32.8, 31.7, 29.5, and 5.9%. C-reactive protein serum levels were significantly different according to C-reactive protein haplotypes. C-reactive protein haplotypes were not associated with coronary heart disease. CONCLUSION: Steady-state C-reactive protein serum level is influenced by C-reactive protein gene haplotypes. Although elevated C-reactive protein level has lately been found to be a consistent and relatively strong risk factor for cardiovascular disease, our study does not support that the common variation in the C-reactive protein gene has a large effect on the occurrence of coronary heart disease.

Aged↗