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.     

Multipoint linkage analysis in Menkes disease.

Linkage analyses were performed in 11 families with X-linked Menkes disease. In each family more than one affected patient had been diagnosed. Forty informative meioses were tested using 11 polymorphic DNA markers. From two-point linkage analyses high lod scores are seen for DXS146 (pTAK-8; maximal lod score 3.16 at recombination fraction [theta] = .0), for DXS1 (p-8; maximal lod score 3.44 at theta = .0), for PGK1 (maximal lod score 2.48 at theta = .0), and for DXS3 (p19-2; maximal lod score 2.90 at theta = .0). This indicates linkage to the pericentromeric region. Multilocus linkage analyses of the same data revealed a peak for the location score between DXS146(pTAK-8) and DXYS1X(pDP34). The most likely location is between DXS159 (cpX289) and DXYS1X(pDP34). Odds for this location relative to the second-best-supported region, between DXS146(pTAK-8) and DXS159 (cpX289), are better than 74:1. Visualization of individual recombinant X chromosomes in two of the Menkes families showed the Menkes locus to be situated between DXS159(cpX289) and DXS94(pXG-12). Combination of the present results with the reported absence of Menkes symptoms in male patients with deletions in Xq21 leads to the conclusion that the Menkes locus is proximal to DXSY1X(pDP34) and located in the region Xq12 to Xq13.3.     

Multipoint genetic mapping with uniparental disomy data

Uniparental disomy (UPD) refers to the presence of two copies of a chromosome from one parent and none from the other parent. In genetic studies of UPDs, many genetic markers are usually used to identify the stage of nondisjunction that leads to UPD and to uncover the associated unusual patterns of recombinations. However, genetic information in such data has not been fully utilized because of the limitations of the existing statistical methods for UPD data. In the present article, we develop a multilocus statistical approach that has the advantages of being able to simultaneously consider all genetic markers for all individuals in the same analysis and to allow general models for the crossover process to incorporate crossover interference. In particular, for a general crossover-process model that assumes only that there exists in each interval at most one crossover, we describe how to use the expectation-maximization algorithm to examine the probability distribution of the recombination events underlying meioses leading to UPD. We can also use this flexible approach to create genetic maps based on UPD data and to inspect recombination differences between meioses exhibiting UPD and normal meioses. The proposed method has been implemented in a computer program, and we illustrate the proposed approach through its application to a set of UPD15 data.     

Nonparametric estimation of age-at-onset distributions from censored kin-cohort data

We present a nonparametric estimator of genotype-specific age-at-onsetdistributions from kin-cohort data. Standard error calculationsare derived and the methodology is illustrated through an analysisof the influence of mutations of the Parkin gene on Parkinson'sdisease. Semiparametric efficiency considerations are brieflydiscussed.     

Comparative lipidomic analysis of mouse and human brain with Alzheimer disease

Lipids are key regulators of brain function and have been increasingly implicated in neurodegenerative disorders including Alzheimer disease (AD). Here, a systems-based approach was employed to determine the lipidome of brain tissues affected by AD. Specifically, we used liquid chromatography-mass spectrometry to profile extracts from the prefrontal cortex, entorhinal cortex, and cerebellum of late-onset AD (LOAD) patients, as well as the forebrain of three transgenic familial AD (FAD) mouse models. Although the cerebellum lacked major alterations in lipid composition, we found an elevation of a signaling pool of diacylglycerol as well as sphingolipids in the prefrontal cortex of AD patients. Furthermore, the diseased entorhinal cortex showed specific enrichment of lysobisphosphatidic acid, sphingomyelin, the ganglioside GM3, and cholesterol esters, all of which suggest common pathogenic mechanisms associated with endolysosomal storage disorders. Importantly, a significant increase in cholesterol esters and GM3 was recapitulated in the transgenic FAD models, suggesting that these mice are relevant tools to study aberrant lipid metabolism of endolysosomal dysfunction associated with AD. Finally, genetic ablation of phospholipase D(2), which rescues the synaptic and behavioral deficits of an FAD mouse model, fully normalizes GM3 levels. These data thus unmask a cross-talk between the metabolism of phosphatidic acid, the product of phospholipase D(2), and gangliosides, and point to a central role of ganglioside anomalies in AD pathogenesis. Overall, our study highlights the hypothesis generating potential of lipidomics and identifies novel region-specific lipid anomalies potentially linked to AD pathogenesis.     

Genetic susceptibility to Alzheimer disease

Alzheimer disease (AD) is the leading cause of dementia in the elderly. Less than a decade ago, it was questioned as to whether or not genes were even involved in anything but rare early onset AD. Since that time, using a variety of genetic epidemiological and molecular biological techniques, four loci have been identified that play a role in the genetic susceptibility of AD, AD presents as a prototype of the power of genetic techniques in defining the etiology of a complex disease.     

Quantitative trait locus analysis of longitudinal quantitative trait data in complex pedigrees

There is currently considerable interest in genetic analysis of quantitative traits such as blood pressure and body mass index. Despite the fact that these traits change throughout life they are commonly analyzed only at a single time point. The genetic basis of such traits can be better understood by collecting and effectively analyzing longitudinal data. Analyses of these data are complicated by the need to incorporate information from complex pedigree structures and genetic markers. We propose conducting longitudinal quantitative trait locus (QTL) analyses on such data sets by using a flexible random regression estimation technique. The relationship between genetic effects at different ages is efficiently modeled using covariance functions (CFs). Using simulated data we show that the change in genetic effects over time can be well characterized using CFs and that including parameters to model the change in effect with age can provide substantial increases in power to detect QTL compared with repeated measure or univariate techniques. The asymptotic distributions of the methods used are investigated and methods for overcoming the practical difficulties in fitting CFs are discussed. The CF-based techniques should allow efficient multivariate analyses of many data sets in human and natural population genetics.     

Multipoint estimation of identity-by-descent probabilities at arbitrary positions among marker loci on general pedigrees

OBJECTIVES: To describe, implement, and test an efficient algorithm to obtain multipoint identity-by-descent (IBD) probabilities at arbitrary positions among marker loci for general pedigrees. Unlike existing programs, our algorithm can analyze data sets with large numbers of people and markers. The algorithm has been implemented in the SimWalk2 computer package. METHODS: Using a rigorous testing regimen containing five pedigrees of various sizes with realistic marker data, we compared several widely used IBD computation programs: Allegro, Aspex, GeneHunter, MapMaker/Sibs, Mendel, Sage, SimWalk2, and Solar. RESULTS: The testing revealed a few discrepancies, particularly on consanguineous pedigrees, but overall excellent results in the deterministic multipoint packages. SimWalk2 was also found to be in good agreement with the deterministic multipoint programs, usually matching to two decimal places the kinship coefficient that ranges from 0 to 1. However, the packages based on single-point IBD estimation, while consistent with each other, often showed poor results, disagreeing with the multipoint kinship results by as much as 0.5. CONCLUSIONS: Our testing has clearly shown that multipoint IBD estimation is much better than single-point estimation. In addition, our testing has validated our algorithm for estimating IBD probabilities at arbitrary positions on general pedigrees.     

Multipoint linkage analysis with many multiallelic or dense diallelic markers: Markov chain-Monte Carlo provides practical approaches for genome scans on general pedigrees

Computations for genome scans need to adapt to the increasing use of dense diallelic markers as well as of full-chromosome multipoint linkage analysis with either diallelic or multiallelic markers. Whereas suitable exact-computation tools are available for use with small pedigrees, equivalent exact computation for larger pedigrees remains infeasible. Markov chain-Monte Carlo (MCMC)-based methods currently provide the only computationally practical option. To date, no systematic comparison of the performance of MCMC-based programs is available, nor have these programs been systematically evaluated for use with dense diallelic markers. Using simulated data, we evaluate the performance of two MCMC-based linkage-analysis programs--lm_markers from the MORGAN package and SimWalk2--under a variety of analysis conditions. Pedigrees consisted of 14, 52, or 98 individuals in 3, 5, or 6 generations, respectively, with increasing amounts of missing data in larger pedigrees. One hundred replicates of markers and trait data were simulated on a 100-cM chromosome, with up to 10 multiallelic and up to 200 diallelic markers used simultaneously for computation of multipoint LOD scores. Exact computation was available for comparison in most situations, and comparison with a perfectly informative marker or interprogram comparison was available in the remaining situations. Our results confirm the accuracy of both programs in multipoint analysis with multiallelic markers on pedigrees of varied sizes and missing-data patterns, but there are some computational differences. In contrast, for large numbers of dense diallelic markers, only the lm_markers program was able to provide accurate results within a computationally practical time. Thus, programs in the MORGAN package are the first available to provide a computationally practical option for accurate linkage analyses in genome scans with both large numbers of diallelic markers and large pedigrees.     

Hybrid hierarchical clustering with applications to microarray data

In this paper, we propose a hybrid clustering method that combines the strengths of bottom-up hierarchical clustering with that of top-down clustering. The first method is good at identifying small clusters but not large ones; the strengths are reversed for the second method. The hybrid method is built on the new idea of a mutual cluster: a group of points closer to each other than to any other points. Theoretical connections between mutual clusters and bottom-up clustering methods are established, aiding in their interpretation and providing an algorithm for identification of mutual clusters. We illustrate the technique on simulated and real microarray datasets.     

Mapping oligogenic resistance to powdery mildew in mungbean with RFLPs

We have used restriction fragment length polymorphisms (RFLPs) to map genes in mungbean (Vigna radiata) that confer partial resistance to the powdery mildew fungus, Erysiphe polygoni. DNA genotypes for 145 RFLP loci spanning 1570 centimorgans of the mungbean genome were assayed in a population of 58 F₂ plants. This population was derived from a cross between a moderately powdery mildew resistant (VC3980A) and a susceptible (TC1966) mungbean parent. F₃ lines derived from the F₂ plants were assayed in the field for powdery mildew response and the results were compared to the RFLP genotype data, thereby identifying loci associated with powdery mildew response. A total of three genomic regions were found to have an effect on powdery mildew response, together explaining 58% of the total variation. At 65 days after planting, two genomic regions were significantly associated with powdery mildew resistance. For both loci, the allele from VC3890A was associated with increased resistance. At 85 days, a third genomic region was also associated with powdery mildew response. For this locus, the allele from the susceptible parent (TC1966) was the one associated with higher levels of powdery mildew resistance. These results indicate that putative partial resistance loci for powdery mildew in mungbean can be identified with DNA markers, even in a population of modest size analyzed at a single location in a single year.     

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.     

Fitting bent lines to data, with applications to allometry

Change-point models, in which a linear or non-linear relation is generalized by allowing it to change at a point not fixed in advance, are of growing importance in allometric and other types of modeling. Frequently, the change-point is picked "by eye" and separate regressions are run for each resultant subdomain. This procedure is deficient, however, for the following reasons: first, a repeatable and objective procedure for estimating the change-point has not been used; second, the subsequent analysis usually does not take into account the fact that the change-point is estimated from the data; and last, the usually desirable requirement of continuity at the change-point is ignored. This paper describes various methods for jointly estimating linear relations and the intervening change-point from the data. In the simplest case, with normal errors and a linear relation of one variable upon another, this amounts to fitting a "bent line" via least squares techniques. In addition, tests and graphical diagnostics for the presence of change-points are presented. An example is given where a change-point and slopes are estimated for the relation of running speed with size among land mammals. In the past, these data have been fit with a straight line or a parabola. It is shown here that superior fit and interpretability are achieved using a change-point model.     

Models for chromatid interference with applications to recombination data

Genetic interference means that the occurrence of one crossover affects the occurrence and/or location of other crossovers in its neighborhood. Of the three components of genetic interference, two are well modeled: the distribution of the number and the locations of chiasmata. For the third component, chromatid interference, there exists only one model. Its application to real data has not yet been published. A further, new model for chromatid interference is presented here. In contrast to the existing model, it is assumed that chromatid interference acts only in the neighborhood of a chiasma. The appropriateness of this model is demonstrated by its application to three sets of recombination data. Both models for chromatid interference increased fit significantly compared to assuming no chromatid interference, at least for parts of the chromosomes. Interference does not necessarily act homogeneously. After extending both models to allow for heterogeneity of chromatid interference, a further improvement in fit was achieved.     

QTL analysis in arbitrary pedigrees with incomplete marker information

Mapping quantitative trait loci (QTL) in arbitrary outbred pedigrees is complicated by the combinatorial possibilities of allele flow relationships and of the founder allelic configurations. Exact methods are only available for rather short and simple pedigrees. Stochastic simulation using Markov chain Monte Carlo (MCMC) integration offers more flexibility. MCMC methods are less natural in a frequentist than in a Bayesian context, which we therefore adopt. Among the MCMC algorithms for updating marker locus genotypes, we implement the descent-graph algorithm. It can be used to update marker locus allele flow relationships and can handle arbitrarily complex pedigrees and missing marker information. Compared with updating marker genotypic information, updating QTL parameters, such as position, effects, and the allele flow relationships is relatively easy with MCMC. We treat the effect of each diploid combination of founder alleles as a random variable and only estimate the variance of these effects, ie, we model diploid genotypic effects instead of the usual partition in additive and dominance effects. This is a variant of the random model approach. The number of QTL alleles is generally unknown. In the Bayesian context, the number of QTL present on a linkage group can be treated as variable. Computer simulations suggest that the algorithm can indeed handle complex pedigrees and detect two QTL on a linkage group, but that the number of individuals in a single extended family is limited to about 50 to 100 individuals.     

Neuronal protein trafficking associated with Alzheimer disease

Aberrant and/or cumulative amyloid-beta (Aβ) production, resulting from proteolytic processing of the amyloid precursor protein (APP) by β and γ-secretases, have been postulated to be a main etiological basis of Alzheimer disease (AD). A number of proteins influence the subcellular trafficking itinerary of APP and the b-site APP-cleaving enzyme (BACE1) between the cell surface, endosomes and the trans-Golgi network (TGN). Available evidence suggests that co-residence of APP and BACE1 in the endosomal compartments promotes amyloidogenesis. Retrograde transport of APP out of the endosome to the TGN reduces Aβ production, while APP routed to and kept at the cell surface enhances its non-amyloidogenic, α-secretase-mediated processing. Changes in post-Golgi membrane trafficking in aging neurons that may influence APP processing is particularly relevant to late-onset, idiopathic AD. Dystrophic axons are key features of AD pathology, and impaired axonal transport could play crucial roles in the pathogenesis of idiopathic AD. Recent evidence has also indicated that Aβ-induced synaptic defects and memory impairment could be explained by a loss of both AMPA and NMDA receptors through endocytosis. Detail understanding of factors that influence these neuronal trafficking processes will open up novel therapeutic avenues for preventing or delaying the onset of symptomatic AD.     

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.