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At least 19 recordsLinked to original sources
PubMed2004

Large-scale single-nucleotide polymorphism (SNP) and haplotype analyses, using dense SNP Maps, of 199 drug-related genes in 752 subjects: the analysis of the association between uncommon SNPs within haplotype blocks and the haplotypes constructed with haplotype-tagging SNPs.

To optimize the strategies for population-based pharmacogenetic studies, we extensively analyzed single-nucleotide polymorphisms (SNPs) and haplotypes in 199 drug-related genes, through use of 4,190 SNPs in 752 control subjects. Drug-related genes, like other genes, have a haplotype-block structure, and a few haplotype-tagging SNPs (htSNPs) could represent most of the major haplotypes constructed with common SNPs in a block. Because our data included 860 uncommon (frequency <0.1) SNPs with frequencies that were accurately estimated, we analyzed the relationship between haplotypes and uncommon SNPs within the blocks (549 SNPs). We inferred haplotype frequencies through use of the data from all htSNPs and one of the uncommon SNPs within a block and calculated four joint probabilities for the haplotypes. We show that, irrespective of the minor-allele frequency of an uncommon SNP, the majority (mean +/- SD frequency 0.943+/-0.117) of the minor alleles were assigned to a single haplotype tagged by htSNPs if the uncommon SNP was within the block. These results support the hypothesis that recombinations occur only infrequently within blocks. The proportion of a single haplotype tagged by htSNPs to which the minor alleles of an uncommon SNP were assigned was positively correlated with the minor-allele frequency when the frequency was <0.03 (P<.000001; n=233 [Spearman's rank correlation coefficient]). The results of simulation studies suggested that haplotype analysis using htSNPs may be useful in the detection of uncommon SNPs associated with phenotypes if the frequencies of the SNPs are higher in affected than in control populations, the SNPs are within the blocks, and the frequencies of the SNPs are >0.03.

Computational Biology↗
PubMed2006

How well do HapMap haplotypes identify common haplotypes of genes? A comparison with haplotypes of 334 genes resequenced in the environmental genome project.

One of the goals of the International HapMap Project is the identification of common haplotypes in genes. However, HapMap uses an incomplete catalogue of single nucleotide polymorphisms (SNPs) and might miss some common haplotypes. We examined this issue using data from the Environmental Genome Project (EGP) which resequenced 335 genes in 90 people, and thus, has a nearly complete catalogue of gene SNPs. The EGP identified a total of 45,243 SNPs, of which 10,780 were common SNPs (minor allele frequency >or=0.1). Using EGP common SNP genotype data, we identified 1,459 haplotypes with frequency >or=0.05 and we use these as "benchmark" haplotypes. HapMap release 16 had genotype information for 1,573 of 10,780 (15%) EGP common SNPs. Using these SNPs, we identified common HapMap haplotypes (frequency >or=0.05) in each of the four HapMap ethnic groups. To compare common HapMap haplotypes to EGP benchmark haplotypes, we collapsed benchmark haplotypes to the set of 1,573 SNPs. Ninety-eight percent of the collapsed benchmark haplotypes could be found as common HapMap haplotypes in one or more of the four HapMap ethnic groups. However, collapsing benchmark haplotypes to the set of SNPs available in HapMap resulted in a loss of haplotype information: 545 of 1,459 (37%) benchmark haplotypes were uniquely identified, and only 25% of genes had all their benchmark haplotypes uniquely identified. We resampled the EGP data to examine the effect of increasing the number of HapMap SNPs to 5 million, and estimate that approximately 40% of common SNPs in genes will be sampled and that half of the genes will have sufficient SNPs to identify all common haplotypes. This inability to distinguish common haplotypes of genes may result in loss of power when examining haplotype-disease association.

Base Sequence↗
PubMed2006

Linkage disequilibrium and haplotype blocks in the MHC vary in an HLA haplotype specific manner assessed mainly by DRB1*03 and DRB1*04 haplotypes.

First generation linkage disequilibrium (LD) and haplotype maps of the human major histocompatibility complex (MHC) have been generated in order to aid the unraveling of the numerous disease predisposing genes in this region by offering a first set of haplotype tagSNPs. Several parameters, like the population studied, the marker map used, the density of polymorphisms and the applied algorithm, are influencing the appearance of haplotype blocks and selection of tags. The MHC comprises a limited number of ancestral, conserved haplotypes. We address the impact of the underlying HLA haplotypes on the LD patterns, haplotype blocks and tag selection throughout the entire extended MHC (xMHC) by studying DR-DQ haplotypes, mainly those carrying DRB1*03 and DRB1*04 alleles. We observed significantly different degree and extent of LD calculated on different HLA backgrounds, as well as variation in the size and boundaries of the defined haplotype and tags selected. Our results demonstrate that the underlying ancestral HLA haplotypic architecture is yet another parameter to take into consideration when constructing LD maps of the xMHC. This may be essential for mapping of disease susceptibility genes since many diseases are associated with and map on particular HLA haplotypes.

Chromosome Mapping↗
PubMed2004

Association test algorithm between a qualitative phenotype and a haplotype or haplotype set using simultaneous estimation of haplotype frequencies, diplotype configurations and diplotype-based penetrances.

Analysis of the association between haplotypes and phenotypes is becoming increasingly important. We have devised an expectation-maximization (EM)-based algorithm to test the association between a phenotype and a haplotype or a haplotype set and to estimate diplotype-based penetrance using individual genotype and phenotype data from cohort studies and clinical trials. The algorithm estimates, in addition to haplotype frequencies, penetrances for subjects with a given haplotype and those without it (dominant mode). Relative risk can thus also be estimated. In the dominant mode, the maximum likelihood under the assumption of no association between the phenotype and presence of the haplotype (L(0max)) and the maximum likelihood under the assumption of association (L(max)) were calculated. The statistic -2 log(L(0max)/L(max)) was used to test the association. The present algorithm along with the analyses in recessive and genotype modes was implemented in the computer program PENHAPLO. Results of analysis of simulated data indicated that the test had considerable power under certain conditions. Analyses of two real data sets from cohort studies, one concerning the MTHFR gene and the other the NAT2 gene, revealed significant associations between the presence of haplotypes and occurrence of side effects. Our algorithm may be especially useful for analyzing data concerning the association between genetic information and individual responses to drugs.

Algorithms↗
PubMed2006

Haplotypes in the lipoprotein lipase gene influence fasting insulin and discovery of a new risk haplotype.

CONTEXT: Prior studies of Mexican Americans described association of lipoprotein lipase (LPL) gene haplotypes with insulin sensitivity/resistance and atherosclerosis. The most common haplotype (haplotype 1) was protective, whereas the fourth most common haplotype (haplotype 4) conferred risk for insulin resistance and atherosclerosis. OBJECTIVE: In this study of Hispanics in the Insulin Resistance Atherosclerosis Study Family Study, we sought to replicate LPL haplotype association with insulin sensitivity/resistance. DESIGN: LPL haplotypes based on 12 single nucleotide polymorphisms were analyzed for association with indexes of insulin sensitivity and other metabolic and adiposity measures. SETTING: This study was conducted in the general community of San Antonio, Texas, and San Luis Valley, Colorado. PARTICIPANTS: Participants in this study were 978 members of 86 Hispanic families. MAIN OUTCOME MEASURES: LPL haplogenotype, metabolic phenotypes, and adiposity were measured in this study. RESULTS: The haplotype structure was identical with that observed in prior studies. Among 978 phenotyped subjects, haplotype 1 was associated with decreased fasting insulin (P = 0.01), and haplotype 4 was associated with increased fasting insulin (P = 0.02) and increased visceral fat mass (P = 0.002). Insulin sensitivity, derived from iv glucose tolerance testing, tended (P > 0.1) to be higher with haplotype 1 (S(I) = 1.72) and lower with haplotype 4 (S(I)=1.38). Haplotype 2 was associated with increases in fasting insulin, triglycerides (TGs), TG to high-density lipoprotein-cholesterol ratio, and apolipoprotein B (P = 0.01-0.04). CONCLUSIONS: This study independently replicates our prior results of LPL haplotypes 1 and 4 as associated with measures of insulin sensitivity and resistance, respectively. Haplotype 4 may confer insulin resistance by increasing visceral fat. Haplotype 2 was identified as a new risk haplotype, suggesting the complex nature of LPL's effect on features of the insulin resistance syndrome.

Fasting↗
PubMed2005

"Extended" A1, B8, DR3 haplotype shows remarkable linkage disequilibrium but is similar to nonextended haplotypes in terms of diabetes risk.

To evaluate potential differential diabetes risk of DR3 haplotypes we have evaluated class I alleles as well as two microsatellites previously associated with differential risk associated with DR3 haplotypes. We found that over one-third of patient DR3 chromosomes consisted of an extended DR3 haplotype, from DQ2 to D6S2223 (DQ2, DR3, D6S273-143, MIC-A5.1, HLA-B8, HLA-Cw7, HLA-A1, and D6S2223-177) with an identical extended haplotype in controls. The extended haplotype was present more frequently (35.1% of autoimmune-associated DR3 haplotypes, 39.4% of control DR3 haplotypes) than other haplotypes (no other haplotype >5% of DR3 haplotypes) and remarkably conserved, but it was not transmitted from parents to affected children more frequently than nonconserved DR3-bearing haplotypes. This suggests that if all alleles are truly identical for the major A1, B8, DR3 haplotype (between A1 and DR3), with different alleles on nonconserved haplotypes without differential diabetes risk, then in this region of the genome DR3-DQ2 may be the primary polymorphisms of common haplotypes contributing to diabetes risk.

Diabetes Mellitus, Type 1↗
PubMed1992

Haplotypes in SS patients from Nigeria; characterization of one atypical beta S haplotype no. 19 (Benin) associated with elevated HB F and high G gamma levels.

We have determined the haplotypes of 669 beta S and 109 beta A chromosomes from numerous members of 297 Nigerian families of various ethnic backgrounds. Among the beta S chromosomes, haplotype 19 was detected in 93.2%, haplotype 17 in 3.4%, and haplotype 20 in 0.1%, while 2.4% represented atypical haplotypes. As many as 60.6% of the beta A chromosomes exhibited haplotype 19 mutations, 8.2% had haplotype 3, and 1.8% had haplotype 20. Two siblings with elevated Hb F and G gamma levels were heterozygous for a beta S chromosome with haplotype 19 and a second chromosome with a hybrid haplotype (termed 19 B). In this hybrid chromosome, haplotype 3-like locus control region (LCR) [hypersensitive site-2 (HS-2)] sequences are in juxtaposition to those of the 5' flanking region of the G gamma promoter of a beta S chromosome with haplotype 19. The presence of this hybrid chromosome is associated with high G gamma values in individuals with both sickle cell anemia (SS) and sickle cell trait (AS); it closely resembles another hybrid beta S chromosome, termed 19 A, observed in a previously reported Turkish SS patient who was homozygous for this chromosome and had high Hb F and high G gamma values. In both instances, it is hypothesized that the haplotype 3-like sequences of the LCR HS-2 contain genetic determinants that can combine with factors produced during hematopoietic stress, resulting in increased gamma-globin gene expression.

Adolescent↗
PubMed1999

Mhc-DQ-DRB haplotype analysis in the rhesus macaque: evidence for a number of different haplotypes displaying a low allelic polymorphism.

In the HLA-DRB subregion of man, five major groups of haplotypes, often displaying a remarkable polymorphism, are distinguishable. The polymorphism is thought to be generated by point mutation, microgene conversion and gene rearrangement by recombination. In order to gain insight into the organization of the rhesus macaque major histocompatibility complex (MHC) class II region, DRB genes from monkeys of different origins previously typed for their DQ genes were analyzed. At first DRB haplotypes were deduced from DQ-homozygous monkeys. The stability of these haplotypes was then examined in DQ-heterozygous monkeys by sequence-based typing for the presence of members of the DRB1*03 and DRB1*04 lineage, and for seven single alleles detected on the haplotypes. Six DRB haplotypes linked to the five most frequent and three haplotypes linked to less frequent DQ haplotypes were identified. Six novel DRB alleles were detected. The number of DRB genes per haplotype varied between two and four. The results altogether suggest that in rhesus macaques, in comparison to man, the DQ haplotypes are linked to only a small number of DRB haplotypes, the number and diversity of DRB haplotypes is larger, and the allelic polymorphism of a given haplotype is smaller. The diversity of the DRB haplotypes was partly due to the varying number and identity of genes linked to DRB1*03 and DRB1*04. Furthermore, the number of DRB1 genes themselves varied from zero to two.

Alleles↗
PubMed2006

Comparison of statistical models for analyzing genotype, inferred haplotype, and molecular haplotype data.

This report compares statistical models based on molecular and inferred haplotypes of the human paraoxonase-1 gene (PON1). In a study of 402 women comprising three race/ethnicities, 137 women had ambiguous inferred haplotypes. The inferred haplotypes (the one with highest posterior probability) for 20 of these women differed from molecular haplotypes, while based on the posterior distribution from the imputation method, 30 discrepancies were expected. We examined the proportion of the variance in PON1 enzymatic activity (phenotype) explained by genotype, and by inferred and molecular haplotype information. For Caucasians, there was an improvement in adjusted R(2) from 16% for the genotype count model, to 29% for imputed haplotypes, and a further improvement to 33% for molecular haplotypes. For Hispanics and African-Americans, there was no indication that haplotypes helped in explaining PON1 activity, and the imputed model gave essentially the same R(2) as the molecular model. For African-Americans, none of the models had adjusted R(2) that exceeded 4%, while for Hispanics they were all about 21-22%. We propose a new parsimonious model which uses all the genotype information and selected haplotype information. For PON1, this model achieves essentially the same adjusted R(2) as the all-haplotype model, with a potential cost savings and without giving the extreme predictions for uncommon haplotype combinations that the all-haplotype models provides.

Aryldialkylphosphatase↗
PubMed2002

HLA in coeliac disease families: a novel test of risk modification by the 'other' haplotype when at least one DQA1*05-DQB1*02 haplotype is carried.

Predisposition to coeliac disease (CD) involves HLA genes. We investigated whether any haplotypes modify risk when carried trans to a known high-risk haplotype, DQA1*05-DQB1*02. Earlier attempts to rank levels of risk contributed by the 'other' haplotype were burdened by use of case-control populations; haplotype frequencies were estimated and homozygosity was only presumed. In contrast, exact haplotypes can be determined and allele transmission can be traced in families. A similar study in narcolepsy reported strata of different degrees of predisposition, attributable to the 'other' haplotype. A gene dosage effect similar to that described for DQB1*02 in CD, has also been reported in narcolepsy. We genotyped 439 simplex/multiplex trios for DQA1 and DQB1. We designed a new statistic to test risk modulation by the trans haplotype, even if the affected offspring was homozygous. We tested for significant deviation in transmission of the 'other' haplotype, i.e., modification of DQA1*05-DQB1*02 risk. We also addressed the proposed difference in risk, between DQA1*05-DQB1*02 homozygotes and DQA1*05-DQB1*02/DQA1*0201-DQB1*02 heterozygotes, reported in Southern Europe. We confirmed a DQB1*02 gene dosage effect. However, no haplotypes were found to modify risk when carried trans to DQA1*05-DQB1*02, except DQA1*05-DQB1*02 and DQA1*0201-DQB1*02 which were already known. We did not find credible evidence for a difference in risk conferred by DQA1*05-DQB1*02 and DQA1*0201-DQB1*02, when carried with DQA1*05-DQB1*02. The new test, which directly inspects haplotype transmissions rather than estimated haplotype frequencies, was used to demonstrate that the 'other' haplotype (except DQA1*05-DQB1*02 and DQA1*0201-DQB1*02) does not modify risk conferred by DQA1*05-DQB1*02. The test is applicable to other diseases.

Celiac Disease↗
PubMed1995

Sharing of MHC haplotypes among patients with systemic lupus erythematosus from unrelated Caucasian multicase families: disease association with the extended haplotype [HLA-B8, SC01, DR17].

OBJECTIVE: Systemic lupus erythematosus (SLE) is an autoimmune rheumatic disease often clustered in families. We investigated the association between MHC haplotypes and SLE in multicase Caucasian families. METHODS: Ten consecutive families with 2 or more patients with SLE, in total 27 patients among 66 individuals, were studied. MHC haplotypes were determined by typing for HLA-A, B, C, DR, and DQ by serological and DNA methods. Complotypes were determined by protein typing and C4 gene polymorphism by DNA analysis. RESULTS: Fifty-four independent MHC haplotypes were found. Ten of the 31 haplotypes in the patients with SLE were examples of the extended haplotype [HLA-B8,SC01,DR17]. Six of these were found in 2 or more patients with SLE within the same family. All the 14 SLE sib-pairs in the families shared at least one haplotype and in 9 of the sib-pairs the shared haplotype was [HLA-B8,SCO1,DR17]. Three SLE associated haplotypes were [HLA-B7,SC31,DR15]. Four of the 27 patients with SLE were C4A deficient. Two C2 deficient siblings were homozygous for the haplotype [HLA-B18,S042,DR15]. CONCLUSION: We demonstrate that a very limited number of MHC haplotypes are associated with familial SLE. The haplotype [HLA-B8,SCO1,DR17] was closely related with the disease. There was no evidence suggesting familial SLE constitutes a disease subset. Determination of MHC haplotypes in multicase families is of value for assessment of disease susceptibility.

Adult↗
PubMed2006

A comparison of several methods for haplotype frequency estimation and haplotype reconstruction for tightly linked markers from general pedigrees.

Haplotype inference for tightly linked markers from general pedigrees remains a challenging problem. Only a few methods are available to efficiently and accurately estimate haplotype frequencies and reconstruct haplotypes for a large number of tightly linked markers from general pedigrees in the presence of missing data, and their performance has not been carefully and extensively evaluated. In this paper, we compare four published methods for haplotype reconstruction and frequency estimation for tightly linked markers from general pedigrees, including HAPLORE, GENEHUNTER, PedPhase, and MERLIN. We review these methods and discuss the differences between them in terms of the models and computational strategies employed. We assess their performance based on simulations using pedigrees and haplotypes on tightly linked single nucleotide polymorphisms from real studies. We investigate the effect of several factors, including the missing rate, the departure from Hardy-Weinberg Equilibrium, and the sample size, on the accuracy for haplotype inference. We also compare these methods with a widely used method for haplotype inference from unrelated individuals, PHASE, by treating individuals within a pedigree as unrelated samples. This comparison allows us to investigate the relative efficiency in haplotype inference using pedigree data. Our results indicate that incorporation of pedigree information can improve the precision for haplotype frequency estimation and the accuracy for haplotype reconstruction. Among four haplotyping methods capable of analyzing general pedigrees, HAPLORE and MERLIN have comparable performance and outperform the other two methods in almost all situations.

Computer Simulation↗
PubMed2002

Definition of gene content for nine common group B haplotypes of the Caucasoid population: KIR haplotypes contain between seven and eleven KIR genes.

The segregation of killer cell immunoglobulin-like receptor ( KIR) genes was determined for a panel of 21 Caucasoid families: 23 different KIR gene patterns were found and could be assigned to combinations of 16 different haplotypes. Four loci were held in common by all haplotypes: KIR2DL4, KIR3DL2, the putative pseudogene KIR3DL3 and KIR2DL2/KIR2DL3, the latter likely being alleles of one gene. Group A haplotypes, which have a unique combination of seven KIR genes, were found at 80% frequency in the family panel, the polygenic group B haplotypes at 65% frequency. KIR gene segregation was fully determined for the nine group B haplotypes, which occurred at highest frequencies in both the family panel and a panel of unrelated individuals. The group B haplotypes carried between seven and 11 KIR genes and encoded inhibitory KIR for one, two, or all three major HLA class I epitopes. Analysis of human leucocyte antigen (HLA) class I genotypes revealed that most, but not all, individuals possess an inhibitory KIR for a self HLA class I epitope. The number of stimulatory KIR genes in group B haplotypes varied considerably between one and five. The data show that group B haplotypes possess a broad spectrum of KIR gene patterns, which is largely complementary to the KIR gene set of group A haplotypes. The results suggest that rapid diversification of group B haplotypes is the result of pathogen-mediated selection for KIR genotypes that have more than the set of KIR genes provided by the group A haplotype.

Female↗
PubMed2003

New HLA haplotype frequency reference standards: high-resolution and large sample typing of HLA DR-DQ haplotypes in a sample of European Americans.

A collaborative study involving a large sample of European Americans was typed for the histocompatibility loci of the HLA DR-DQ region and subjected to intensive typing validation measures in order to accurately determine haplotype composition and frequency. The resulting tables have immediate application to HLA typing and allogeneic transplantation. The loci within the DR-DQ region are especially valuable for such an undertaking because of their tight linkage and high linkage disequilibrium. The 3798 haplotypes, derived from 1899 unrelated individuals, had a total of 75 distinct DRB1-DQA1-DQB1 haplotypes. The frequency distribution of the haplotypes was right skewed with haplotypes occurring at a frequency of less than 1% numbering 59 and yet constituting less than 12% of the total sample. Given DRB1 typing, it was possible to infer the exact DQA1 and DQB1 composition of a haplotype with high confidence (>90% likelihood) in 21 of the 35 high-resolution DRB1 alleles present in the sample. Of the DRB1 alleles without high reliability for DQ haplotype inference, only *0401, *0701 and *1302 were common, the remaining 11 DRB1 alleles constituting less than 5% of the total sample. This approach failed for the 13 serologically equivalent DR alleles in which only 33% of DQ haplotypes could be reliably inferred. The 36 DQA1-DQB1 haplotypes present in the total sample conformed to the known pattern of permissible heterodimers. Four DQA1-DQB1 haplotypes, all rare, are reported here for the first time. The haplotype frequency tables are suitable as a reference standard for HLA typing of the DR and DQ loci in European Americans.

Gene Frequency↗
PubMed2005

Haplotype study of intermediate-length alleles at the fragile X (FMR1) gene: ATL1, FMRb, and microsatellite haplotypes differ from those found in common-size FMR1 alleles.

The CGG repeat within the X-chromosome-linked FMR1 gene, which in hyperexpansion (> 200 copies) results in fragile X syndrome, is highly polymorphic. The mechanism of expansion is not well understood, but CGG repeats called intermediate-length or gray zone alleles (approximately equal 35-60 repeats) are thought to make up the FMR1 alleles showing initial steps in this expansion process. It has been hypothesized that the background haplotype of these alleles plays a role in their susceptibility to expansion. In this study we investigate whether or not the frequencies of alleles and haplotypes at four marker loci in the FMR1 gene region (microsatellites DXS548 and FRAXAC1 and SNPs ATL1 and FMRb) in 84 intermediate-length male chromosomes differ from those in 94 common-size male alleles. The ATL1*G and FMRB*A alleles were more frequent among intermediate-length alleles than among common alleles. In addition, the DXS548-FRAXAC1 T50-T42 and T40-T42 haplotypes were strongly associated with intermediate-length alleles between 41 and 60 CGG repeats (p < 0.001). Two extended haplotypes, DXS548-FRAXAC1-ATL1-FMRb T50-T42-G-A and T40-T42-G-A, are strongly associated (p < 0.001) with intermediate-length alleles between 41 and 60 CGG repeats, and these haplotypes have also been reported as fragile X associated haplotypes in European populations. These data suggest that these haplotypes are among the most susceptible to further expansion among the intermediate-length alleles. T50-T42-G-A was also much more prevalent in males with 35-40 CGG repeats than in males with common-size alleles. ATL1 did not increase discrimination among intermediate-length alleles beyond that detected by DXS548-FRAXAC1 haplotypes, but the FMRb locus did, particularly for the DXS548-FRAXAC1-ATL1 T50-T42-G and T40-T42-G haplotypes. Comparison with fragile X associated haplotypes, from the literature, suggests that repeat hyperexpansion occurs most frequently on chromosomes carrying FMRB*A. Within the intermediate-length allele category, however, there were some significant differences in haplotype frequencies between smaller and larger alleles, and this finding has implications for future studies.

Adolescent↗
PubMed2001

Haplotyping and estimation of haplotype frequencies for closely linked biallelic multilocus genetic phenotypes including nuclear family information.

With the discovery of single nucleotide polymorphisms (SNP) along the genome, genotyping of large samples of biallelic multilocus genetic phenotypes for (fine) mapping of disease genes or for population studies has become standard practice. A genetic trait, however, is mainly caused by an underlying defective haplotype, and populations are best characterized by their haplotype frequencies. Therefore, it is essential to infer from the phase-unknown genetic phenotypes in a sample drawn from a population the haplotype frequencies in the population and the underlying haplotype pairs in the sample in order to find disease predisposing genes by some association or haplotype sharing algorithm. Haplotype frequencies and haplotype pairs are estimated via a maximum likelihood approach by a well-known expectation maximization (EM) algorithm, adapting it to a large number (up to 30) of biallelic loci (SNP), and including nuclear family information, if available, into the analysis. Parents are treated as an independent sample from the population. Their genotyped offspring reduces the number of potential haplotype pairs for both parents, resulting in a higher accuracy of the estimation, and may also reduce computation time. In a series of simulations our approach of including nuclear family information has been tested against both the EM algorithm without nuclear family information and an alternative approach using GENEHUNTER for the haplotyping of the families, using the locus-by-locus allele counts of the sample. Our new approach is more precise in haplotyping in cases of a high number of heterozygous loci, whereas for a moderate number of heterozygous positions in the sample all three different approaches gave the same perfect results.

Algorithms↗
PubMed2000

High-resolution Y chromosome haplotypes of Israeli and Palestinian Arabs reveal geographic substructure and substantial overlap with haplotypes of Jews.

High-resolution Y chromosome haplotype analysis was performed in 143 paternally unrelated Israeli and Palestinian Moslem Arabs (I&P Arabs) by screening for 11 binary polymorphisms and six microsatellite loci. Two frequent haplotypes were found among the 83 detected: the modal haplotype of the I&P Arabs (approximately 14%) was spread throughout the region, while its one-step microsatellite neighbor, the modal haplotype of the Galilee sample (approximately 8%), was mainly restricted to the north. Geographic substructuring within the Arabs was observed in the highlands of Samaria and Judea. Y chromosome variation in the I&P Arabs was compared to that of Ashkenazi and Sephardic Jews, and to that of North Welsh individuals. At the haplogroup level, defined by the binary polymorphisms only, the Y chromosome distribution in Arabs and Jews was similar but not identical. At the haplotype level, determined by both binary and microsatellite markers, a more detailed pattern was observed. Single-step microsatellite networks of Arab and Jewish haplotypes revealed a common pool for a large portion of Y chromosomes, suggesting a relatively recent common ancestry. The two modal haplotypes in the I&P Arabs were closely related to the most frequent haplotype of Jews (the Cohen modal haplotype). However, the I&P Arab clade that includes the two Arab modal haplotypes (and makes up 32% of Arab chromosomes) is found at only very low frequency among Jews, reflecting divergence and/or admixture from other populations.

Arabs↗
PubMed1996

Tumor necrosis factor (TNF) microsatellite haplotypes in relation to extended haplotypes, susceptibility to diseases associated with the major histocompatibility complex and TNF secretion.

TNFabc microsatellite haplotypes were determined on normal, type I diabetes and multiple sclerosis Caucasian MHC haplotypes in family studies. Although independent examples of conserved extended haplotypes usually had the same TNFabc haplotypes, there were a number of exceptions, suggesting that these loci are more mutable than most loci in the human MHC. Some TNFabc haplotypes were characteristic of only one extended haplotype, whereas others were shared by several different extended haplotypes. From the analysis of TNFabc on extended haplotype fragments, and assuming that the fragments arose by ancient homologous crossing over, it was possible to "map" TNF and how that it was somewhat closer to HLA-B than the complement region, corresponding to the physical map of this region. TNF haplotype associations with type I diabetes and multiple sclerosis were attributable to the known extended haplotype associations of these diseases. There was also a trend for higher TNF-alpha secretion by peripheral blood mononuclear cells from individuals homozygous for [HLA-B8, SC01, DR3] than from individuals homozygous for [HLA-B7, SC31, DR2].

Alleles↗