De novo myotonic dystrophy mutation in a Nigerian kindred.

An expansion of an unstable (CTG)n trinucleotide repeat in the 3' UTR of a gene encoding a putative serine/threonine protein kinase (DMPK) on human chromosome 19q13.3 has been shown to be specific for the myotonic dystrophy (DM) disease phenotype. In addition, a single haplotype composed of nine alleles within and flanking DMPK over a physical distance of 30 kb has been shown to be in complete linkage disequilibrium with DM. This has led to two hypotheses: (1) predisposition for (CTG)n instability results from a founder effect that occurred only once or a few times in human evolution; and (2) elements within the disease haplotype may predispose the (CTG)n repeat to instability. A detailed haplotype analysis of the DM region was conducted on a Nigerian (Yoruba) DM family, the only indigenous sub-Saharan DM case reported to date. Each affected member of this family had an expanded (CTG)n repeat in one of his or her DMPK alleles. However, unlike all other DM populations studied thus far, disassociation of the (CTG)n repeat expansion from other alleles of the putative predisposing haplotype was found. We conclude that the expanded (CTG)n repeat in this family is the result of an independent mutational event. Consequently, the origin of DM is unlikely to be a single mutational event, and the hypothesis that a single ancestral haplotype predisposes to repeat expansion is not compelling.     

Incorporating single-locus tests into haplotype cladistic analysis in case-control studies

In case-control studies, genetic associations for complex diseases may be probed either with single-locus tests or with haplotype-based tests. Although there are different views on the relative merits and preferences of the two test strategies, haplotype-based analyses are generally believed to be more powerful to detect genes with modest effects. However, a main drawback of haplotype-based association tests is the large number of distinct haplotypes, which increases the degrees of freedom for corresponding test statistics and thus reduces the statistical power. To decrease the degrees of freedom and enhance the efficiency and power of haplotype analysis, we propose an improved haplotype clustering method that is based on the haplotype cladistic analysis developed by Durrant et al. In our method, we attempt to combine the strengths of single-locus analysis and haplotype-based analysis into one single test framework. Novel in our method is that we develop a more informative haplotype similarity measurement by using p-values obtained from single-locus association tests to construct a measure of weight, which to some extent incorporates the information of disease outcomes. The weights are then used in computation of similarity measures to construct distance metrics between haplotype pairs in haplotype cladistic analysis. To assess our proposed new method, we performed simulation analyses to compare the relative performances of (1) conventional haplotype-based analysis using original haplotype, (2) single-locus allele-based analysis, (3) original haplotype cladistic analysis (CLADHC) by Durrant et al., and (4) our weighted haplotype cladistic analysis method, under different scenarios. Our weighted cladistic analysis method shows an increased statistical power and robustness, compared with the methods of haplotype cladistic analysis, single-locus test, and the traditional haplotype-based analyses. The real data analyses also show that our proposed method has practical significance in the human genetics field.     

Association mapping via regularized regression analysis of single-nucleotide-polymorphism haplotypes in variable-sized sliding windows

Large-scale haplotype association analysis, especially at the whole-genome level, is still a very challenging task without an optimal solution. In this study, we propose a new approach for haplotype association analysis that is based on a variable-sized sliding-window framework and employs regularized regression analysis to tackle the problem of multiple degrees of freedom in the haplotype test. Our method can handle a large number of haplotypes in association analyses more efficiently and effectively than do currently available approaches. We implement a procedure in which the maximum size of a sliding window is determined by local haplotype diversity and sample size, an attractive feature for large-scale haplotype analyses, such as a whole-genome scan, in which linkage disequilibrium patterns are expected to vary widely. We compare the performance of our method with that of three other methods--a test based on a single-nucleotide polymorphism, a cladistic analysis of haplotypes, and variable-length Markov chains--with use of both simulated and experimental data. By analyzing data sets simulated under different disease models, we demonstrate that our method consistently outperforms the other three methods, especially when the region under study has high haplotype diversity. Built on the regression analysis framework, our method can incorporate other risk-factor information into haplotype-based association analysis, which is becoming an increasingly necessary step for studying common disorders to which both genetic and environmental risk factors contribute.     

Friedreich ataxia in Louisiana Acadians: demonstration of a founder effect by analysis of microsatellite-generated extended haplotypes.

Eleven Acadian families with Friedreich ataxia (FA) who were from southwest Louisiana were studied with a series of polymorphic markers spanning 310 kb in the D9S5-D9S15 region previously shown to be tightly linked to the disease locus. In particular, three very informative microsatellites were tested. Evidence for a strong founder effect was found, since a specific extended haplotype spanning 230 kb from 26P (D9S5) to MCT112 (D9S15) was present on 70% of independent FA chromosomes and only once (6%) on the normal ones. There was no evident correlation between haplotypes and clinical expression. The typing of an additional microsatellite (GS4) located 80 kb from MCT112 created a divergence of the main FA-linked haplotype, generating four minor and one major haplotype. A similar split was observed with GS4 in a patient homozygous for a rare 26P-to-MCT112 haplotype. These results suggest that GS4 is flanking marker for the disease locus, although other interpretations are possible.     

Genomic control for association studies: a semiparametric test to detect excess-haplotype sharing

Individuals who share a disease mutation from a common ancestor often share alleles at genetic markers adjacent to the mutation, even if the common ancestor is remote. The alleles at these adjacent markers, called the haplotype, can be visualized as a string of realizations of random variables, which may be dependent when individuals are related in some fashion. Ideally, for a sample of individuals all having the same (genetic) disease, this dependence-measured as haplotype-sharing-will be greater in the vicinity of disease genes than in other regions of the genome. In this paper we present a semiparametric test for haplotype-sharing. We begin by developing a model assuming that the ancestral haplotype is known and thus the extent of haplotype-sharing from a common ancestor can be determined unambiguously. The amount of overlap at markers far from the disease is treated as a random variable with an unknown distribution F, which we estimate non-parametrically. Overlap of markers surrounding disease genes are modeled as a mixture pF(x - theta) + (1 - p)F(x), in which p is the fraction of subjects with the disease mutation. Testing for a disease gene then amounts to testing whether p = 0. Next we drop the assumption that the ancestral haplotype is known. To detect excess clustering of haplotypes, we measure the pairwise overlap of a set of haplotypes. As in the simpler scenario, this distribution is modeled as a location-shift mixture. To test the hypothesis we construct a score test with a simple limiting distribution.     

Haplotype association analysis of human disease traits using genotype data of unrelated individuals

Haplotype inference has become an important part of human genetic data analysis due to its functional and statistical advantages over the single-locus approach in linkage disequilibrium mapping. Different statistical methods have been proposed for detecting haplotype - disease associations using unphased multi-locus genotype data, ranging from the early approach by the simple gene-counting method to the recent work using the generalized linear model. However, these methods are either confined to case - control design or unable to yield unbiased point and interval estimates of haplotype effects. Based on the popular logistic regression model, we present a new approach for haplotype association analysis of human disease traits. Using haplotype-based parameterization, our model infers the effects of specific haplotypes (point estimation) and constructs confidence interval for the risks of haplotypes (interval estimation). Based on the estimated parameters, the model calculates haplotype frequency conditional on the trait value for both discrete and continuous traits. Moreover, our model provides an overall significance level for the association between the disease trait and a group or all of the haplotypes. Featured by the direct maximization in haplotype estimation, our method also facilitates a computer simulation approach for correcting the significance level of individual haplotype to adjust for multiple testing. We show, by applying the model to an empirical data set, that our method based on the well-known logistic regression model is a useful tool for haplotype association analysis of human disease traits.     

Autoimmune diabetes mellitus, Hodgkin's disease and Graves' ophthalmopathy in a patient with 8.1 ancestral haplotype.

In this report, we describe the case of a 43-year-old woman affected by type 1 diabetes mellitus diagnosed 8 years before, who developed Graves' disease 2 years after chemotherapy and mantle radiotherapy treatment for Hodgkin's disease. Bilateral Graves' ophthalmopathy appeared four months before our observations. Intravenous methyl-prednisolone therapy was started, but was interrupted due to severe metabolic failure. Autoantibodies (anti-islet cells, anti-thyroid, thyroid-stimulating, non-organ-specific) were positive. Since the clinical picture suggested a genetic immunological ground predisposing to autoimmunity, we evaluated her HLA haplotype. Genomic typing of the patient permitted identification of the 8.1 ancestral haplotype, a Caucasoid haplotype unique in its association with many immunopathological diseases. Moreover, we also observed a haplotype unusual in Caucasians, trans DRB1*1101, DQA1*0103, DQB1*0603. To our knowledge, HLA-related genetic risk of developing thyroid autoimmunity after neck irradiation has never been studied. Although we cannot confirm a direct association between the 8.1 ancestral haplotype or DRB1*1101, DQA1*0103, DQB1*0603 and the diseases described, we suggest considering immunological parameters and HLA typing in candidate patients for mantle radiation therapy for Hodgkin's disease or other tumors. HLA haplotype determination could be useful in identifying the patients at raised risk of developing autoimmune diseases after irradiation, thus permitting a more appropriate follow-up schedule.     

A method for detecting recent selection in the human genome from allele age estimates

Mutations that have recently increased in frequency by positive natural selection are an important component of naturally occurring variation that affects fitness. To identify such variants, we developed a method to test for recent selection by estimating the age of an allele from the extent of haplotype sharing at linked sites. Neutral coalescent simulations are then used to determine the likelihood of this age given the allele's observed frequency. We applied this method to a common disease allele, the hemochromatosis-associated HFE C282Y mutation. Our results allow us to reject neutral models incorporating plausible human demographic histories for HFE C282Y and one other young but common allele, indicating positive selection at HFE or a linked locus. This method will be useful for scanning the human genome for alleles under selection using the haplotype map now being constructed.     

Inference on haplotype effects in case-control studies using unphased genotype data

A variety of statistical methods exist for detecting haplotype-disease association through use of genetic data from a case-control study. Since such data often consist of unphased genotypes (resulting in haplotype ambiguity), such statistical methods typically apply the expectation-maximization (EM) algorithm for inference. However, the majority of these methods fail to perform inference on the effect of particular haplotypes or haplotype features on disease risk. Since such inference is valuable, we develop a retrospective likelihood for estimating and testing the effects of specific features of single-nucleotide polymorphism (SNP)-based haplotypes on disease risk using unphased genotype data from a case-control study. Our proposed method has a flexible structure that allows, among other choices, modeling of multiplicative, dominant, and recessive effects of specific haplotype features on disease risk. In addition, our method relaxes the requirement of Hardy-Weinberg equilibrium of haplotype frequencies in case subjects, which is typically required of EM-based haplotype methods. Also, our method easily accommodates missing SNP information. Finally, our method allows for asymptotic, permutation-based, or bootstrap inference. We apply our method to case-control SNP genotype data from the Finland-United States Investigation of Non-Insulin-Dependent Diabetes Mellitus (FUSION) Genetics study and identify two haplotypes that appear to be significantly associated with type 2 diabetes. Using the FUSION data, we assess the accuracy of asymptotic P values by comparing them with P values obtained from a permutation procedure. We also assess the accuracy of asymptotic confidence intervals for relative-risk parameters for haplotype effects, by a simulation study based on the FUSION data.     

HapScope: a software system for automated and visual analysis of functionally annotated haplotypes

We have developed a software analysis package, HapScope, which includes a comprehensive analysis pipeline and a sophisticated visualization tool for analyzing functionally annotated haplotypes. The HapScope analysis pipeline supports: (i) computational haplotype construction with an expectation-maximization or Bayesian statistical algorithm; (ii) SNP classification by protein coding change, homology to model organisms or putative regulatory regions; and (iii) minimum SNP subset selection by either a Brute Force Algorithm or a Greedy Partition Algorithm. The HapScope viewer displays genomic structure with haplotype information in an integrated environment, providing eight alternative views for assessing genetic and functional correlation. It has a user-friendly interface for: (i) haplotype block visualization; (ii) SNP subset selection; (iii) haplotype consolidation with subset SNP markers; (iv) incorporation of both experimentally determined haplotypes and computational results; and (v) data export for additional analysis. Comparison of haplotypes constructed by the statistical algorithms with those determined experimentally shows variation in haplotype prediction accuracies in genomic regions with different levels of nucleotide diversity. We have applied HapScope in analyzing haplotypes for candidate genes and genomic regions with extensive SNP and genotype data. We envision that the systematic approach of integrating functional genomic analysis with population haplotypes, supported by HapScope, will greatly facilitate current genetic disease research.     

Homozygosity haplotype allows a genomewide search for the autosomal segments shared among patients

A promising strategy for identifying disease susceptibility genes for both single- and multiple-gene diseases is to search patients' autosomes for shared chromosomal segments derived from a common ancestor. Such segments are characterized by the distinct identity of their haplotype. The methods and algorithms currently available have only a limited capability for determining a high-resolution haplotype genomewide. We herein introduce the homozygosity haplotype (HH), a haplotype described by the homozygous SNPs that are easily obtained from high-density SNP genotyping data. The HH represents haplotypes of both copies of homologous autosomes, allowing for direct comparisons of the autosomes among multiple patients and enabling the identification of the shared segments. The HH successfully detected the shared segments from members of a large family with Marfan syndrome, which is an autosomal dominant, single-gene disease. It also detected the shared segments from patients with model multigene diseases originating with common ancestors who lived 10-25 generations ago. The HH is therefore considered to be useful for the identification of disease susceptibility genes in both single- and multiple-gene diseases.     

单倍型分析技术研究进展

单倍型是指共存于单条染色体上的一系列遗传变异位点的组合,每条染色体都有自己独特的单倍型。单倍型分析技术作为一种常用的数据分析方法,是寻找单染色体上杂合SNP变异位点的有效方法,也对挖掘致病基因、寻找疾病治疗新方法有重要作用。它主要包括间接推断法和直接实验法。文中介绍了各种单倍型分析方法及应用,尤其详细介绍了单分子稀释法和保留邻近性的转座酶测序法,同时对单倍型分析技术的应用前景进行了展望。     

Diversity in and evidence for selection on the mitochondrial genome of Phytophthora infestans

Two extant nomenclature systems were reconciled to relate six mitochondrial DNA (mtDNA) haplotypes of Phytophthora infestans, the oomycete pathogen causing late blight disease on potato and tomato. Carter's haplotypes I-a and I-b were included in Goodwin's haplotype A, while Carter's haplotypes II-a and II-b were included in Goodwin's haplotype B. In addition, haplotypes E and F were included in Carter's haplotype I-b. The mutational differences separating the various haplotypes were determined, and we propose that either haplotype I-b(A) or haplotype I-a(A) is the putative ancestral mtDNA of P. infestans, because either can center all the other haplotypes in a logical stepwise network of mutational changes. The occurrence of the six haplotypes in 548 isolates worldwide was determined. Haplotypes I-a and II-a were associated with diverse genotypes worldwide. As previously suggested, haplotype I-b was found only in the US-1 clonal lineage and its variants (n = 99 isolates from 16 countries on 5 continents), and haplotype II-b was limited to the US-6 clonal lineage and its derivatives (n = 36). In a confirmation of a previous suggestion, the randomly mating population in the Toluca Valley of central Mexico (n = 78) was monomorphic for mtDNA haplotype I-a(A). We hypothesize that selection there may be driving the dominance of that single mtDNA haplotype.     

Extracting haplotypes from diploid organisms

Each diploid organism has two alleles at every gene locus. In sexual organisms such as most plants, animals and fungi, the two alleles in an individual may be genetically very different from each other. DNA sequence data from individual alleles (called a haplotype) can provide powerful information to address a variety of biological questions and guide many practical applications. The advancement in molecular technology and computational tools in the last decade has made obtaining large-scale haplotypes feasible. This review summarizes the two basic approaches for obtaining haplotypes and discusses the associated techniques and methods. The first approach is to experimentally obtain diploid sequence information and then use computer algorithms to infer haplotypes. The second approach is to obtain haplotype sequences directly through experimentation. The advantages and disadvantages of each approach are discussed. I then discussed a specific example on how the direct approach was used to obtain haplotype information to address several fundamental biological questions of a pathogenic yeast. With increasing sophistication in both bioinformatics tools and high-throughput molecular techniques, haplotype analysis is becoming an integrated component in biomedical research.     

Randomly distributed crossovers may generate block-like patterns of linkage disequilibrium: an act of genetic drift

There is considerable interest in identifying and characterizing block-like patterns of linkage disequilibrium (LD; haplotype blocks) in the human genome as these may facilitate the identification of complex disease genes via genome-wide association studies. Although recombination hot-spots have been suggested as the primary mechanism to explain the block-like pattern of LD, other forces, such as genetic drift, may also be important. To this end, we have studied the effect of various recombination models on patterns of LD by using extensive simulations. As expected, haplotype blocks were observed under a model allowing recombination hot-spots. However, we also observed similar block-like patterns in the models where recombination crossovers are randomly and uniformly distributed, and we demonstrate that these blocks are generated by genetic drift. We caution that genetic drift may be an alternative mechanism (in addition to recombination hot-spots) that can lead to block-like patterns of LD. Our findings highlight the necessity of characterizing haplotype blocks in world-wide populations.     

The trimmed-haplotype test for linkage disequilibrium

Single-marker linkage-disequilibrium (LD) methods cannot fully describe disequilibrium in an entire chromosomal region surrounding a disease allele. With the advent of myriad tightly linked microsatellite markers, we have an opportunity to extend LD analysis from single markers to multiple-marker haplotypes. Haplotype analysis has increased statistical power to disclose the presence of a disease locus in situations where it correctly reflects the historical process involved. For maximum efficiency, evidence of LD ought to come not just from a single haplotype, which may well be rare, but in addition from many similar haplotypes that could have descended from the same ancestral founder but have been trimmed in succeeding generations. We present such an analysis, called the "trimmed-haplotype method." We focus on chromosomal regions that are small enough that disequilibrium in significant portions of them may have been preserved in some pedigrees and yet that contain enough markers to minimize coincidental occurrence of the haplotype in the absence of a disease allele: perhaps regions 1-2 cM in length. In general, we could have no idea what haplotype an ancestral founder carried generations ago, nor do we usually have a precise chromosomal location for the disease-susceptibility locus. Therefore, we must search through all possible haplotypes surrounding multiple locations. Since such repeated testing obliterates the sampling distribution of the test, we employ bootstrap methods to calculate significance levels. Trimmed-haplotype analysis is performed on family data in which genotypes have been assembled into haplotypes. It can be applied either to conventional parent-affected-offspring triads or to multiplex pedigrees. We present a method for summarizing the LD evidence, in any pedigree, that can be employed in trimmed-haplotype analysis as well as in other methods.     

The relationship between bovine major histocompatibility complex class II polymorphism and disease studied by use of bull breeding values

The predictive value of class II DQ and DYA polymorphisms of the bovine major histocompatibility (MHC) complex (BoLA) for the incidence of disease in dairy cattle was estimated in a sample of 196 progeny-tested AI bulls of the Swedish Red and White breed. The BoLA DQ and DYA types of the bulls were determined by analysing restriction fragment length polymorphisms (RFLPs). Breeding values of bulls for clinical mastitis, all diseases including clinical mastitis and diseases other than clinical mastitis were used as measures of disease resistance or susceptibility. The relationship between MHC polymorphism and bull breeding values for disease resistance was evaluated statistically by linear regression analysis. A significant association between the haplotype DQ1A and susceptibility to clinical mastitis was revealed. No other DQ haplotype nor the DYA locus has a significant effect on any of the disease traits studied.     

An ancient haplotype containing antimicrobial peptide gene variants is associated with severe fungal skin disease in Persian cats

Dermatophytosis, also known as ringworm, is a contagious fungal skin disease affecting humans and animals worldwide. Persian cats exhibit severe forms of the disease more commonly than other breeds of cat, including other long-haired breeds. Certain types of severe dermatophytosis in humans are reportedly caused by monogenic inborn errors of immunity. The goal of this study was to identify genetic variants in Persian cats contributing to the phenotype of severe dermatophytosis. Whole-genome sequencing of case and control Persian cats followed by a genome-wide association study identified a highly divergent, disease-associated haplotype on chromosome F1 containing the S100 family of genes. S100 calcium binding protein A9 (S100A9), which encodes a subunit of the antimicrobial heterodimer known as calprotectin, contained 13 nonsynonymous variants between cases and controls. Evolutionary analysis of S100A9 haplotypes comparing cases, controls, and wild felids suggested the divergent disease-associated haplotype was likely introgressed into the domestic cat lineage and maintained via balancing selection. We demonstrated marked upregulation of calprotectin expression in the feline epidermis during dermatophytosis, suggesting involvement in disease pathogenesis. Given this divergent allele has been maintained in domestic cat and wildcat populations, this haplotype may have beneficial effects against other pathogens. The pathogen specificity of this altered protein should be investigated before attempting to reduce the allele frequency in the Persian cat breed. Further work is needed to clarify if severe Persian dermatophytosis is a monogenic disease or if hidden disease-susceptibility loci remain to be discovered. Consideration should be given to engineering antimicrobial peptides such as calprotectin for topical treatment of dermatophytosis in humans and animals.     

Detecting disease-predisposing variants: the haplotype method.

For many HLA-associated diseases, multiple alleles-- and, in some cases, multiple loci--have been suggested as the causative agents. The haplotype method for identifying disease-predisposing amino acids in a genetic region is a stratification analysis. We show that, for each haplotype combination containing all the amino acid sites involved in the disease process, the relative frequencies of amino acid variants at sites not involved in disease but in linkage disequilibrium with the disease-predisposing sites are expected to be the same in patients and controls. The haplotype method is robust to mode of inheritance and penetrance of the disease and can be used to determine unequivocally whether all amino acid sites involved in the disease have not been identified. Using a resampling technique, we developed a statistical test that takes account of the nonindependence of the sites sampled. Further, when multiple sites in the genetic region are involved in disease, the test statistic gives a closer fit to the null expectation when some--compared with none--of the true predisposing factors are included in the haplotype analysis. Although the haplotype method cannot distinguish between very highly correlated sites in one population, ethnic comparisons may help identify the true predisposing factors. The haplotype method was applied to insulin-dependent diabetes mellitus (IDDM) HLA class II DQA1-DQB1 data from Caucasian, African, and Japanese populations. Our results indicate that the combination DQA1#52 (Arg predisposing) DQB1#57 (Asp protective), which has been proposed as an important IDDM agent, does not include all the predisposing elements. With rheumatoid arthritis HLA class II DRB1 data, the results were consistent with the shared-epitope hypothesis.