Home About us Contact
|
Home About us Contact | ||
|
|
||
Haplotype Data (haplotype + data)
Selected AbstractsMeasuring and partitioning the high-order linkage disequilibrium by multiple order Markov chainsGENETIC EPIDEMIOLOGY, Issue 4 2008Yunjung Kim Abstract A map of the background levels of disequilibrium between nearby markers can be useful for association mapping studies. In order to assess the background levels of linkage disequilibrium (LD), multilocus LD measures are more advantageous than pairwise LD measures because the combined analysis of pairwise LD measures is not adequate to detect simultaneous allele associations among multiple markers. Various multilocus LD measures based on haplotypes have been proposed. However, most of these measures provide a single index of association among multiple markers and does not reveal the complex patterns and different levels of LD structure. In this paper, we employ non-homogeneous, multiple order Markov Chain models as a statistical framework to measure and partition the LD among multiple markers into components due to different orders of marker associations. Using a sliding window of multiple markers on phased haplotype data, we compute corresponding likelihoods for different Markov Chain (MC) orders in each window. The log-likelihood difference between the lowest MC order model (MC0) and the highest MC order model in each window is used as a measure of the total LD or the overall deviation from the gametic equilibrium for the window. Then, we partition the total LD into lower order disequilibria and estimate the effects from two-, three-, and higher order disequilibria. The relationship between different orders of LD and the log-likelihood difference involving two different orders of MC models are explored. By applying our method to the phased haplotype data in the ENCODE regions of the HapMap project, we are able to identify high/low multilocus LD regions. Our results reveal that the most LD in the HapMap data is attributed to the LD between adjacent pairs of markers across the whole region. LD between adjacent pairs of markers appears to be more significant in high multilocus LD regions than in low multilocus LD regions. We also find that as the multilocus total LD increases, the effects of high-order LD tends to get weaker due to the lack of observed multilocus haplotypes. The overall estimates of first, second, third, and fourth order LD across the ENCODE regions are 64, 23, 9, and 3%. Genet. Epidemiol. 2008. © 2008 Wiley-Liss, Inc. [source] Quantifying bias due to allele misclassification in case-control studies of haplotypesGENETIC EPIDEMIOLOGY, Issue 7 2006Usha S. Govindarajulu Abstract Objectives Genotyping errors can induce biases in frequency estimates for haplotypes of single nucleotide polymorphisms (SNPs). Here, we considered the impact of SNP allele misclassification on haplotype odds ratio estimates from case-control studies of unrelated individuals. Methods We calculated bias analytically, using the haplotype counts expected in cases and controls under genotype misclassification. We evaluated the bias due to allele misclassification across a range of haplotype distributions using empirical haplotype frequencies within blocks of limited haplotype diversity. We also considered simple two- and three-locus haplotype distributions to understand the impact of haplotype frequency and number of SNPs on misclassification bias. Results We found that for common haplotypes (>5% frequency), realistic genotyping error rates (0.1,1% chance of miscalling an allele), and moderate relative risks (2,4), the bias was always towards the null and increases in magnitude with increasing error rate, increasing odds ratio. For common haplotypes, bias generally increased with increasing haplotype frequency, while for rare haplotypes, bias generally increased with decreasing frequency. When the chance of miscalling an allele is 0.5%, the median bias in haplotype-specific odds ratios for common haplotypes was generally small (<4% on the log odds ratio scale), but the bias for some individual haplotypes was larger (10,20%). Bias towards the null leads to a loss in power; the relative efficiency using a test statistic based upon misclassified haplotype data compared to a test based on the unobserved true haplotypes ranged from roughly 60% to 80%, and worsened with increasing haplotype frequency. Conclusions The cumulative effect of small allele-calling errors across multiple loci can induce noticeable bias and reduce power in realistic scenarios. This has implications for the design of candidate gene association studies that utilize multi-marker haplotypes. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source] Determination of HLA-A, -B and -DRB1 haplotypes based on allelic homozygosity data in selected bone marrow donors of the Taiwanese marrow donor registryINTERNATIONAL JOURNAL OF IMMUNOGENETICS, Issue 5 2007K. L. Yang Summary From 120 unrelated Taiwanese marrow stem cell donors with allelic homozygosities at human leucocyte antigen (HLA)-A, -B and -DRB1 loci, we determined 85 distinguishable haplotypes. Using the predetermined haplotype data, we deduced 418 haplotypes from 1903 unrelated individual stem cell donors selected for HLA confirmatory test. Eighteen of the 20 (90%) most frequently observed haplotypes determined in Asian Americans using computer prediction were found in this study. In comparison with haplotypes determined by maximum likelihood algorithm in Korean population, 18 of the 29 (62.07%) Korean haplotypes with a frequency over 0.5% were also among the haplotypes determined in this investigation. Randomized family studies confirmed that over 50% of the haplotypes observed in the families were among the haplotypes deduced based on allelic homozygosity, suggesting that proportionally additional haplotypes can be determined as the number of donors being studied is increased. Haplotypes carrying low incidence allele characteristics of Taiwanese were also observed in this study. This established haplotype information will be beneficial for patients searching for stem cell donors in our registry domestically and internationally. [source] Phylogeography of the greater horseshoe bat, Rhinolophus ferrumequinum: contrasting results from mitochondrial and microsatellite dataMOLECULAR ECOLOGY, Issue 2 2009JON FLANDERS Abstract Phylogeographical studies are typically based on haplotype data, occasionally on nuclear markers such as microsatellites, but rarely combine both. This is unfortunate because the use of markers with contrasting modes of inheritance and rates of evolution might provide a more accurate and comprehensive understanding of a species' history. Here we present a detailed study of the phylogeography of the greater horseshoe bat, Rhinolophus ferrumequinum, using 1098 bp of the mitochondrial ND2 gene from 45 localities from across its Palaearctic range to infer population history. In addition, we re-analysed a large microsatellite data set available for this species and compared the results of both markers to infer population relationships and the historical processes influencing them. We show that mtDNA, the most popular marker in phylogeography studies, yielded a misleading result, and would have led us to conclude erroneously that a single expansion had taken place in Europe. Only by combining the mitochondrial and microsatellite data sets are we able to reconstruct the species' history and show two colonization events in Europe, one before the Last Glacial Maximum (LGM) and one after it. Combining markers also revealed the importance of Asia Minor as an ancient refugium for this species and a source population for the expansion of the greater horseshoe bat into Europe before the LGM. [source] A comparison of techniques for assessing dispersal behaviour in gundis: revealing dispersal patterns in the absence of observed dispersal behaviourMOLECULAR ECOLOGY, Issue 15 2008KAREN J NUTT Abstract Knowledge of the dispersal status of group members is important to understanding how sociality may have evolved within a species. I assessed the effectiveness of four techniques for elucidating dispersal behaviour in a rock-dwelling rodent (Ctenodactylus gundi) with small group sizes (2,10 animals): genetic parentage assignment, haplotype data and kinship analyses, assignment testing, and F -statistics. The first two methods provided the greatest insight into gundi dispersal behaviour. Assignment testing and F -statistics proved of limited use for elucidating fine-scale dispersal, but could detect large-scale patterns despite low sex-biased dispersal intensity (1.9 : 1) because of moderate genetic differentiation among groups (FST = 0.10). Findings are discussed in light of current dispersal theory. In general, gundi dispersal is plastic, and seems to be dependent on body weight (for males), group composition, and scale of analysis (total dispersal events recorded within the population were almost twice the immigration rate into the population). Most groups were comprised of a single matriline and one immigrant male. Immigrant rather than philopatric males bred with group females. Dispersal among groups was male-biased, but dispersal or philopatry could occur by either sex. During a drought, both sexes delayed dispersal and cooperative social units formed. Whether such behaviour resulted directly from the drought or not remains unclear, however, since comparative information was not available from nondrought years. Combining fine-scale analyses with information on large-scale patterns provided substantial insight into gundi dispersal behaviour despite the limited movement of animals during a drought, and may prove useful for elucidating dispersal behaviour in other social animals. [source] Variability patterns and positively selected sites at the gametophytic self-incompatibility pollen SFB gene in a wild self-incompatible Prunus spinosa (Rosaceae) populationNEW PHYTOLOGIST, Issue 3 2006Maria D. S. Nunes Summary ,,Current models for the generation of new gametophytic self-incompatibility specificities require that neutral variability segregates within specificity classes. Furthermore, one of the models predicts greater ratios of nonsynonymous to synonymous substitutions in pollen than in pistil specificity genes. All models assume that new specificities arise by mutation only. ,,To test these models, 21 SFB (the pollen S -locus) alleles from a wild Prunus spinosa (Rosaceae) population were obtained. For seven of these, the corresponding S -haplotype was also characterized. The SFB data set was also used to identify positively selected sites. Those sites are likely to be the ones responsible for defining pollen specificities. ,,Of the 23 sites identified as being positively selected, 21 are located in the variable (including a new region described here) and hypervariable regions. Little variability is found within specificity classes. There is no evidence for selective sweeps being more frequent in pollen than in pistil specificity genes. The S-RNase and the SFB genes have only partially correlated evolutionary histories. ,,None of the models is compatible with the variability patterns found in the SFB and the S -haplotype data. [source] Multipoint Linkage Disequilibrium Mapping Using Multilocus Allele Frequency DataANNALS OF HUMAN GENETICS, Issue 4 2005T. Johnson Summary This paper describes a likelihood based fine scale linkage disequilibrium mapping method for estimating the position of a disease predisposing gene relative to a battery of typed marker loci. The method uses multilocus allele frequency data from a sample of unrelated diseased individuals and from a sample of unrelated control individuals, that is, a case and control type design. This type of data could be obtained by typing DNA pools, which is less expensive than typing individuals separately. The method described uses a nonparametric model that makes it robust to the shape of the genealogy at the disease locus. It can be implemented efficiently, making a multipoint analysis of a data set of a thousand markers feasible. An example power analysis uses simulations to estimate the amount of information that can be extracted from fully resolved haplotype data, relative to multilocus allele frequency data. For the assumed parameter values and a battery of 10 markers, roughly three times narrower region estimates can be derived from haplotype data than from allele frequency data only. Depending on how we choose to measure information, allele frequency data at an additional ,18 or ,33 markers is needed to compensate for this loss of information. [source] Analysis of high-resolution HLA-A, -B, -Cw, -DRB1, and -DQB1 alleles and haplotypes in 718 Chinese marrow donors based on donor,recipient confirmatory typingsINTERNATIONAL JOURNAL OF IMMUNOGENETICS, Issue 5 2009A.-L. Hei Summary High-resolution human leucocyte antigen (HLA)-A, -B, -Cw, -DRB1, and -DQB1 alleles and haplotype frequencies were analysed from 718 Chinese healthy donors selected from the Chinese Marrow Donor Program registry based on HLA donor,recipient confirmatory typings. A total of 28 HLA-A, 61 HLA-B, 30 HLA-Cw, 40 HLA-DRB1 and 18 HLA-DQB1 alleles were identified, and HLA-A*1101, A*2402, A*0201, B*4001, Cw*0702, Cw*0102, Cw*0304, DRB1*0901, DRB1*1501, DQB1*0301, DQB1*0303 and DQB1*0601 were found with frequencies higher than 10% in this study population. Multiple-locus haplotype analysis by the maximum-likelihood method revealed 45 A,B, 38 Cw,B, 47 B,DRB1, 29 DRB1,DQB1, 24 A,B,DRB1, 38 A,Cw,B, 23 A,Cw,B,DRB1, 33 Cw,B,DRB1,DQB1 and 22 A,Cw,B,DRB1,DQB1 haplotypes with frequencies >0.5%. The most common two-, three-, four- and five-locus haplotypes in this population were: A*0207,B*4601 (7.34%), Cw*0102,B*4601 (8.71%), B*1302,DRB1*0701 (6.19%), DRB1*0901,DQB1*0303 (14.27%), A*3001,B*1302,DRB1*0701 (5.36%), A*0207,Cw*0102,B*4601 (7.06%), A*3001,Cw*0602,B*1302,DRB1*0701 (5.36%), Cw*0602,B*1302,DRB1*0701,DQB1*0202 (6.12%) and A*3001,Cw*0602,B*1302,DRB1*0701,DQB1*0202 (5.29%). Presentation of the high-resolution alleles and haplotypes data at HLA-A, -B, -Cw, -DRB1 and -DQB1 loci will be useful for HLA matching in transplantation as well as for other medical and anthropological applications in the Chinese population. [source] | ||||||||||