Approximating identity-by-descent matrices using multiple haplotype configurations on pedigrees

Identity-by-descent (IBD) matrix calculation is an important step in quantitative trait loci (QTL) analysis using variance component models. To calculate IBD matrices efficiently for large pedigrees with large numbers of loci, an approximation method based on the reconstruction of haplotype configurations for the pedigrees is proposed. The method uses a subset of haplotype configurations with high likelihoods identified by a haplotyping method. The new method is compared with a Markov chain Monte Carlo (MCMC) method (Loki) in terms of QTL mapping performance on simulated pedigrees. Both methods yield almost identical results for the estimation of QTL positions and variance parameters, while the new method is much more computationally efficient than the MCMC approach for large pedigrees and large numbers of loci. The proposed method is also compared with an exact method (Merlin) in small simulated pedigrees, where both methods produce nearly identical estimates of position-specific kinship coefficients. The new method can be used for fine mapping with joint linkage disequilibrium and linkage analysis, which improves the power and accuracy of QTL mapping.     

A rapid conditional enumeration haplotyping method in pedigrees

Haplotyping in pedigrees provides valuable information for genetic studies (e.g., linkage analysis and association study). In order to identify a set of haplotype configurations with the highest likelihoods for a large pedigree with a large number of linked loci, in our previous work, we proposed a conditional enumeration haplotyping method which sets a threshold for the conditional probabilities of the possible ordered genotypes at every unordered individual-marker to delete some ordered genotypes with low conditional probabilities and then eliminate some haplotype configurations with low likelihoods. In this article we present a rapid haplotyping algorithm based on a modification of our previous method by setting an additional threshold for the ratio of the conditional probability of a haplotype configuration to the largest conditional probability of all haplotype configurations in order to eliminate those configurations with relatively low conditional probabilities. The new algorithm is much more efficient than our previous method and the widely used software SimWalk2.     

Multipoint quantitative-trait linkage analysis in general pedigrees.

Multipoint linkage analysis of quantitative-trait loci (QTLs) has previously been restricted to sibships and small pedigrees. In this article, we show how variance-component linkage methods can be used in pedigrees of arbitrary size and complexity, and we develop a general framework for multipoint identity-by-descent (IBD) probability calculations. We extend the sib-pair multipoint mapping approach of Fulker et al. to general relative pairs. This multipoint IBD method uses the proportion of alleles shared identical by descent at genotyped loci to estimate IBD sharing at arbitrary points along a chromosome for each relative pair. We have derived correlations in IBD sharing as a function of chromosomal distance for relative pairs in general pedigrees and provide a simple framework whereby these correlations can be easily obtained for any relative pair related by a single line of descent or by multiple independent lines of descent. Once calculated, the multipoint relative-pair IBDs can be utilized in variance-component linkage analysis, which considers the likelihood of the entire pedigree jointly. Examples are given that use simulated data, demonstrating both the accuracy of QTL localization and the increase in power provided by multipoint analysis with 5-, 10-, and 20-cM marker maps. The general pedigree variance component and IBD estimation methods have been implemented in the SOLAR (Sequential Oligogenic Linkage Analysis Routines) computer package.     

HAPLORE: a program for haplotype reconstruction in general pedigrees without recombination

MOTIVATION: Haplotype reconstruction is an essential step in genetic linkage and association studies. Although many methods have been developed to estimate haplotype frequencies and reconstruct haplotypes for a sample of unrelated individuals, haplotype reconstruction in large pedigrees with a large number of genetic markers remains a challenging problem. METHODS: We have developed an efficient computer program, HAPLORE (HAPLOtype REconstruction), to identify all haplotype sets that are compatible with the observed genotypes in a pedigree for tightly linked genetic markers. HAPLORE consists of three steps that can serve different needs in applications. In the first step, a set of logic rules is used to reduce the number of compatible haplotypes of each individual in the pedigree as much as possible. After this step, the haplotypes of all individuals in the pedigree can be completely or partially determined. These logic rules are applicable to completely linked markers and they can be used to impute missing data and check genotyping errors. In the second step, a haplotype-elimination algorithm similar to the genotype-elimination algorithms used in linkage analysis is applied to delete incompatible haplotypes derived from the first step. All superfluous haplotypes of the pedigree members will be excluded after this step. In the third step, the expectation-maximization (EM) algorithm combined with the partition and ligation technique is used to estimate haplotype frequencies based on the inferred haplotype configurations through the first two steps. Only compatible haplotype configurations with haplotypes having frequencies greater than a threshold are retained. RESULTS: We test the effectiveness and the efficiency of HAPLORE using both simulated and real datasets. Our results show that, the rule-based algorithm is very efficient for completely genotyped pedigree. In this case, almost all of the families have one unique haplotype configuration. In the presence of missing data, the number of compatible haplotypes can be substantially reduced by HAPLORE, and the program will provide all possible haplotype configurations of a pedigree under different circumstances, if such multiple configurations exist. These inferred haplotype configurations, as well as the haplotype frequencies estimated by the EM algorithm, can be used in genetic linkage and association studies. AVAILABILITY: The program can be downloaded from http://bioinformatics.med.yale.edu.     

A Bayesian approach to copy-number-polymorphism analysis in nuclear pedigrees

Segmental copy-number polymorphisms (CNPs) represent a significant component of human genetic variation and are likely to contribute to disease susceptibility. These potentially multiallelic and highly polymorphic systems present new challenges to family-based genetic-analysis tools that commonly assume codominant markers and allow for no genotyping error. The copy-number quantitation (CNP phenotype) represents the total number of segmental copies present in an individual and provides a means to infer, rather than to observe, the underlying allele segregation. We present an integrated approach to meet these challenges, in the form of a graphical model in which we infer the underlying CNP phenotype from the (single or replicate) quantitative measure within the analysis while assuming an allele-based system segregating through the pedigree. This approach can be readily applied to the study of any form of genetic measure, and the construction permits extension to a wide variety of hypothesis tests. We have implemented the basic model for use with nuclear families, and we illustrate its application through an analysis of the CNP located in gene CCL3L1 in 201 families with asthma.     

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     

A variance-covariance model for analysis of pedigrees with inbreeding

A variance-covariance model is suggested for plotting the distribution of a quantitative trait analyzed in animal pedigrees resulting from crosses of outbred lines. The model takes inbreeding into account. A special parameter characterizing the degree of inbreeding has been introduced, which makes the model versatile. Pedigrees with the same structure that contain or not contain inbred individuals have been compared to analyze the effect of inbreeding on the parameters of the trait distribution, such as the mean genotypic value and variance of the trait.     

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.     

A coalescence-guided hierarchical Bayesian method for haplotype inference

Haplotype inference from phase-ambiguous multilocus genotype data is an important task for both disease-gene mapping and studies of human evolution. We report a novel haplotype-inference method based on a coalescence-guided hierarchical Bayes model. In this model, a hierarchical structure is imposed on the prior haplotype frequency distributions to capture the similarities among modern-day haplotypes attributable to their common ancestry. As a consequence, the model both allows distinct haplotypes to have different a priori probabilities according to the inferred hierarchical ancestral structure and results in a proper joint posterior distribution for all the parameters of interest. A Markov chain-Monte Carlo scheme is designed to draw from this posterior distribution. By using coalescence-based simulation and empirically generated data sets (Whitehead Institute's inflammatory bowel disease data sets and HapMap data sets), we demonstrate the merits of the new method in comparison with HAPLOTYPER and PHASE, with or without the presence of recombination hotspots and missing genotypes.     

A genetic study of panic disorder pedigrees.

Pedigree analysis is done on 19 kindreds of panic disorder, and the results suggest that this disorder is transmitted as an autosomal dominant trait. Seven of these 19 kindreds were ascertained through a panic disorder proband with mitral valve prolapse. When the analysis is done omitting these seven kindreds, the results also suggest that panic disorder without prolapse is transmitted as an autosomal dominant trait.     

A variance-covariance model for analysis of hybrid pedigrees with inbreeding

A variance-covariance model is suggested for plotting the distribution of a quantitative trait analyzed in animal pedigrees resulting from crosses of outbred lines. The model takes inbreeding into account. A special parameter characterizing the degree of inbreeding has been introduced, which makes the model versatile. Pedigrees with the same structure that contain or not contain inbred individuals have been compared to analyze the effect of inbreeding on the parameters of the trait distribution, such as the genotypic mean and variance of the trait.     

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。     

A variance component analysis on recombination rate in the COGA pedigrees

We estimated the crossover frequency in 1,232 gametes from 356 subjects in pedigrees from the Collaborative Study on the Genetics on Alcoholism. We examined the effect of covariates including age, ethnicity, and years with ALDX1 on recombination rate, and found a positive correlation between recombination rate and years with ALDX1. By variance-component analysis, we estimated the heritability of recombination rate to be around 0.5, and provided suggestive evidence for a locus linked to recombination rate.     

A new method for haplotype inference including full-sib information

Recent literature has suggested that haplotype inference through close relatives, especially from nuclear families, can be an alternative strategy in determining linkage phase and estimating haplotype frequencies. In the case of no possibility to obtain genotypes for parents, and only full-sib information being used, a new approach is suggested to infer phase and to reconstruct haplotypes. We present a maximum-likelihood method via an expectation-maximization algorithm, called FSHAP, using only full-sib information when parent information is not available. FSHAP can deal with families with an arbitrary number of children, and missing parents or missing genotypes can be handled as well. In a simulation study we compare FSHAP with another existing expectation-maximization (EM)-based approach (FAMHAP), the conditioning approach implemented in FBAT and GENEHUNTER, which is only pedigree based and assumes linkage equilibrium. In most situations, FSHAP has the smallest discrepancy of haplotype frequency estimation and the lowest error rate in haplotype reconstruction, only in some cases FAMHAP yields comparable results. GENEHUNTER produces the largest discrepancy, and FBAT produces the highest error rate in offspring in most situations. Among the methods compared, FSHAP has the highest accuracy in reconstructing the diplotypes of the unavailable parents. Potential limitations of the method, e.g., in analyzing very large haplotypes, are indicated and possible solutions are discussed.     

A two-stage linkage analysis of Chinese schizophrenia pedigrees in 10 target chromosomes

We performed a two-stage linkage scan involving 25 Chinese schizophrenia families, focusing on 10 target chromosomes which have already been the subject of considerable research. We initially genotyped 237 individuals with 186 markers, five candidate regions were then chosen for fine mapping and 49 additional markers were genotyped. In region 1q21-23, a maximum multipoint HLOD (HLOD=2.38) was observed between D1S484 and D1S2705, under the dominant model. In region 5q35, dominant HOLD of 2.36, 2.04, and 2.31 were found at marker D5S2030, D5S408, and D5S2006, respectively. Consistent multipoint results also supported linkage to this region under the same dominant model, with a highest HOLD of 2.47. Furthermore, single-point HLODs (HLOD=1.95 at D22S274, and HLOD=1.91 at D22S1157) were found in region 22q13, under the dominant model. Evidence from these three regions satisfied the criteria for suggestive linkage and should help in identifying schizophrenia susceptibility genes.