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PubMed2005

Combined linkage and association mapping of quantitative trait loci by multiple markers.

Using multiple diallelic markers, variance component models are proposed for high-resolution combined linkage and association mapping of quantitative trait loci (QTL) based on nuclear families. The objective is to build a model that may fully use marker information for fine association mapping of QTL in the presence of prior linkage. The measures of linkage disequilibrium and the genetic effects are incorporated in the mean coefficients and are decomposed into orthogonal additive and dominance effects. The linkage information is modeled in variance-covariance matrices. Hence, the proposed methods model both association and linkage in a unified model. On the basis of marker information, a multipoint interval mapping method is provided to estimate the proportion of allele sharing identical by descent (IBD) and the probability of sharing two alleles IBD at a putative QTL for a sib-pair. To test the association between the trait locus and the markers, both likelihood-ratio tests and F-tests can be constructed on the basis of the proposed models. In addition, analytical formulas of noncentrality parameter approximations of the F-test statistics are provided. Type I error rates of the proposed test statistics are calculated to show their robustness. After comparing with the association between-family and association within-family (AbAw) approach by Abecasis and Fulker et al., it is found that the method proposed in this article is more powerful and advantageous based on simulation study and power calculation. By power and sample size comparison, it is shown that models that use more markers may have higher power than models that use fewer markers. The multiple-marker analysis can be more advantageous and has higher power in fine mapping QTL. As an application, the Genetic Analysis Workshop 12 German asthma data are analyzed using the proposed methods.

Alleles↗
PubMed2002

[Molecular mapping of quantitative trait loci (QTL) for characters of vascular bundles in peduncle related to indica-japonica differentiation in rice (Oryza sativa L.)].

A doubled-haploid population, consisting of 81 DH lines derived from the F1 hybrid of a cross between an indica cultivar and a japonica cultivar, was used to map quantitative trait loci (QTL) controlling numbers of vascular bundles in peduncle, primary rachis branches and the ratio of vascular bundles to primary rachis branches (V/R ratio). For vascular bundles, three QTL were detected. Among them, the QTL qVB-8 with the largest effect individually accounted for 31.1% of the total variation. Two QTL controlling primary rachis branches were identified and they were co-located with 2 of the 3 QTL for vascular bundles respectively. Three QTL for the V/R ratio were mapped on chromosome 1, 2 and 8, respectively. Of the three QTL, the QTL qV/R-1 with the largest additive effect, explained 25.3% of the total variation, was located on chromosome 1 and found to be closely linked to the gene sh-2, a major gene underlying grain-shattering ability. In addition, four and two pairs of significant epistatic QTL were detected for vascular bundles and the V/R ratio, respectively, but none for rachis branches. Our results suggested that the numbers of vascular bundles and primary rachis branches were independently controlled by different polygenic systems, but the two polygenic systems shared a fraction of quantitative trait loci. It was also shown that the chromosome region carrying the QTL qV/R-1 on chromosome 1 might play an important role in the processes of indica-japonica differentiation in rice.

Chromosome Mapping↗
PubMed1997

Multiple marker mapping of quantitative trait loci of Finnish dairy cattle by regression.

A total of 453 bulls belonging to 11 half-sib families of Finnish Ayrshires were genotyped for six microsatellite markers on chromosome 9. The data were used in an attempt to map quantitative trait loci applying regression as a multimarker approach. For association analysis with a granddaughter design, the EBV for 12 traits were used: milk yield, protein yield, fat percentage, protein percentage, daughter weight, bull growth, calf mortality, days open, fertility treatments, nonreturn rate, SCC, and clinical mastitis. The empirical values of significance thresholds were determined using a permutation test on the experimental data. Although no significant effects were found, the results indicate some support for the existence of a locus on chromosome 9 that affects milk and protein yields.

Adipose Tissue↗
PubMedDate not supplied

Gene-environment interaction and the mapping of complex traits: some statistical models and their implications.

The manifestation of many complex diseases or traits is very likely the result of an inextricable interplay of the biological and the environmental. Yet the role of environmental effect has traditionally been played down, for various reasons. In this paper, some simple statistical models that incorporate gene-environment interaction (GEI) have been proposed and their behavior and implications investigated. These implications concern the conditional independence assumption in likelihood calculation of pedigree data, the fine-tuning of the sib pair method for mapping quantitative traits, apportioning of disease or trait variation due to specific causes. In addition, they concern properties of gene mapping methods that do not take GEI into account, and they bring into question the utility of commonly used measures of genetic effects such as recurrence risk ratio for relative pairs, twin concordance rates, and heritability coefficients. In the presence of GEI, all these measures are functions not only of genetic effects and gene frequency, but also of environmental effects, the distribution of environmental factors in the population, and of GEI. Above all, these measures are all measures of familial aggregation, since they can be significant even in the absence of any genetic component of the disease. Thus their use as indicators of the genetic basis of complex diseases is cast into doubt.

Chromosome Mapping↗
PubMed1999

Testing the correspondence between map positions of quantitative trait loci.

There are several instances in which quantitative trait locus (QTL) mapping experiments have been independently carried out for similar traits in different laboratories. We develop a permutation test of the correspondence between the test statistics obtained from genome-wide QTL scans in two such experiments to test whether the same QTLs are segregating in the experimental pair. In simulations, we show that the permutation test has the desired properties if chromosomes are of equal length, but bias can occur if chromosomes are of unequal length, a problem connected with autocorrelation of test statistic values. We apply the test to data from three recent mouse body weight QTL mapping experiments. The results from the test are non-significant, and imply a lack of overall concordance between the QTLs that were segregating in these experiments.

Animals↗
PubMed2004

Ordered subset analysis in genetic linkage mapping of complex traits.

Etiologic heterogeneity is a fundamental feature of complex disease etiology; genetic linkage analysis methods to map genes for complex traits that acknowledge the presence of genetic heterogeneity are likely to have greater power to identify subtle changes in complex biologic systems. We investigate the use of trait-related covariates to examine evidence for linkage in the presence of heterogeneity. Ordered-subset analysis (OSA) identifies subsets of families defined by the level of a trait-related covariate that provide maximal evidence for linkage, without requiring a priori specification of the subset. We propose that examining evidence for linkage in the subset directly may result in a more etiologically homogeneous sample. In turn, the reduced impact of heterogeneity will result in increased overall evidence for linkage to a specific region and a more distinct lod score peak. In addition, identification of a subset defined by a specific trait-related covariate showing increased evidence for linkage may help refine the list of candidate genes in a given region and suggest a useful sample in which to begin searching for trait-associated polymorphisms. This method provides a means to begin to bridge the gap between initial identification of linkage and identification of the disease predisposing variant(s) within a region when mapping genes for complex diseases. We illustrate this method by analyzing data on breast cancer age of onset and chromosome 17q [Hall et al., 1990, Science 250:1684-1689]. We evaluate OSA using simulation studies under a variety of genetic models.

Breast Neoplasms↗
PubMed1999

Chromosomal mapping of quantitative trait loci that influence renal hemodynamic functions.

BACKGROUND: Impaired renal hemodynamic function has been suspected to be responsible for hypertension in the spontaneously hypertensive rat (SHR). METHODS AND RESULTS: We measured renal hemodynamic functions, including the glomerular filtration rate, renal plasma flow, and renal vascular resistance, in an F2 rat population derived from spontaneously hypertensive and Wistar-Kyoto (WKY) rats and performed a genome-wide screening to map quantitative trait loci that influence these functions to gain insight into the relationship between renal hemodynamic functions and blood pressure control. The D1 Mit7 locus was identified as a major locus that influenced renal hemodynamic functions, and we transferred the SHR chromosomal segment around the D1 Mit7 locus into the WKY strain. The congenic rats exhibited impaired renal hemodynamic functions. The systolic blood pressure of the congenic rats was significantly higher than that of age-matched WKY rats, but only at nighttime. No significant differences in systolic blood pressure during daytime or diastolic blood pressure were observed between the 2 strains. CONCLUSIONS: We have identified a chromosome segment that influences renal hemodynamic function. The SHR chromosome segment around the D1 Mit7 locus had significant, but not dramatic, effects in increasing blood pressure in the WKY genetic background. However, further studies will be necessary to determine the significance of this locus in SHR hypertension.

Animals↗
PubMed2002

Linkage mapping of quantitative trait loci in humans: an overview.

In this article, we provide an overview of the different statistical procedures that have been developed for linkage mapping of quantitative trait loci. We outline the model assumptions, the data requirements and the underlying tests for linkage for the different methods.

Chromosome Mapping↗
PubMed2004

Detection and mapping of quantitative trait loci that determine responsiveness of mice to nitrous oxide antinociception.

Exposure to 70% N(2)O evokes a robust antinociceptive effect in C57BL/6 (B6) but not in DBA/2 (D2) inbred mice. This study was conducted to identify quantitative trait loci (QTL) in the mouse genome that might determine responsiveness to N(2)O. Offspring from the F(2) generation bred from B6 and D2 progenitors exhibited a broad range of responsiveness to N(2)O antinociception as determined by the acetic acid-induced abdominal constriction test. QTL analysis was then used to dissect this continuous trait distribution into component loci, and to map them to broad chromosomal regions. To this end, 24 spleens were collected from each of the following four groups: male and female F(2) mice responding to 70% N(2)O in oxygen with 100% response (high-responders); and male and female F(2) mice responding with 0% response (low-responders). Genomic DNA was extracted from the spleens and genotyped with simple sequence length polymorphism MapPairs markers. Findings were combined with findings from the earlier QTL analysis from BXD recombinant inbred mice [Brain Res 725 (1996) 23]. Combined results revealed two significant QTL that influence responsiveness to nitrous oxide on proximal chromosome 2 and distal chromosome 5, and one suggestive QTL on midchromosome 18. The chromosome 2 QTL was evident only in males. A significant interaction was found between a locus on chromosome 6 and another on chromosome 13 with a substantial effect on N(2)O antinociception.

Animals↗
PubMed2000

Deficiency mapping of quantitative trait loci affecting longevity in Drosophila melanogaster.

In a previous study, sex-specific quantitative trait loci (QTL) affecting adult longevity were mapped by linkage to polymorphic roo transposable element markers, in a population of recombinant inbred lines derived from the Oregon and 2b strains of Drosophila melanogaster. Two life span QTL were each located on chromosomes 2 and 3, within sections 33E-46C and 65D-85F on the cytological map, respectively. We used quantitative deficiency complementation mapping to further resolve the locations of life span QTL within these regions. The Oregon and 2b strains were each crossed to 47 deficiencies spanning cytological regions 32F-44E and 64C-76B, and quantitative failure of the QTL alleles to complement the deficiencies was assessed. We initially detected a minimum of five and four QTL in the chromosome 2 and 3 regions, respectively, illustrating that multiple linked factors contribute to each QTL detected by recombination mapping. The QTL locations inferred from deficiency mapping did not generally correspond to those of candidate genes affecting oxidative and thermal stress or glucose metabolism. The chromosome 2 QTL in the 35B-E region was further resolved to a minimum of three tightly linked QTL, containing six genetically defined loci, 24 genes, and predicted genes that are positional candidates corresponding to life span QTL. This region was also associated with quantitative variation in life span in a sample of 10 genotypes collected from nature. Quantitative deficiency complementation is an efficient method for fine-scale QTL mapping in Drosophila and can be further improved by controlling the background genotype of the strains to be tested.

Animals↗
PubMed2005

High-resolution association mapping of quantitative trait loci: a population-based approach.

In this article, population-based regression models are proposed for high-resolution linkage disequilibrium mapping of quantitative trait loci (QTL). Two regression models, the "genotype effect model" and the "additive effect model," are proposed to model the association between the markers and the trait locus. The marker can be either diallelic or multiallelic. If only one marker is used, the method is similar to a classical setting by Nielsen and Weir, and the additive effect model is equivalent to the haplotype trend regression (HTR) method by Zaykin et al. If two/multiple marker data with phase ambiguity are used in the analysis, the proposed models can be used to analyze the data directly. By analytical formulas, we show that the genotype effect model can be used to model the additive and dominance effects simultaneously; the additive effect model takes care of the additive effect only. On the basis of the two models, F-test statistics are proposed to test association between the QTL and markers. By a simulation study, we show that the two models have reasonable type I error rates for a data set of moderate sample size. The noncentrality parameter approximations of F-test statistics are derived to make power calculation and comparison. By a simulation study, it is found that the noncentrality parameter approximations of F-test statistics work very well. Using the noncentrality parameter approximations, we compare the power of the two models with that of the HTR. In addition, a simulation study is performed to make a comparison on the basis of the haplotype frequencies of 10 SNPs of angiotensin-1 converting enzyme (ACE) genes.

Alleles↗
PubMed2005

How useful is the fine-scale mapping of complex trait linkage peaks? Evaluating the impact of additional microsatellite genotyping on the posterior probability of linkage.

The two-stage linkage mapping protocol for complex traits (a primary genome scan with low marker density followed by the high-density genotyping around linkage peaks) is a near-universal practice. The behavior (an increase or a decrease) of the peak upon such fine mapping frequently leads to inferences regarding the veracity of the primary scan finding, namely a true, or a false, positive. We examined by simulation, under the null hypothesis of no linkage and the alternative hypothesis of true linkage, the inferences that can be made regarding the posterior probability of linkage given either a peak increase, or alternatively, a peak decrease, following fine mapping. We considered different models of missing genotype data, fine-mapping LOD score thresholds, and prior probabilities of linkage. Our simulations show that evidence for linkage can increase frequently upon fine mapping under both null and alternative hypotheses, although large increases in LOD scores are more common under the alternative hypothesis. Increased LOD scores accompany an increased posterior probability of linkage, and large LOD score changes and the presence of dominance at the trait locus accentuate this effect. We demonstrate that the greatest changes in the posterior probability of linkage occur when the genotyping data are least complete (and especially when parental genotypes are missing), and the LOD score threshold for fine mapping is relaxed.

Algorithms↗
PubMed2004

Interval mapping of quantitative trait loci for resistance to late blight [Phytophthora infestans (Mont.) de Bary], height and maturity in a tetraploid population of potato (Solanum tuberosum subsp. tuberosum).

Interval mapping of quantitative trait loci (QTL) for resistance to late blight, height, and maturity was performed on a tetraploid full-sib family of potato comprising 227 clones from a cross between a susceptible parent, 12601ab1, and a resistant cultivar, Stirling, which were of similar height and main crop maturity. Thirty-eight AFLP primer combinations provided 585 informative markers, and 23 SSRs proved useful for identifying linkage groups (LGs). A simplex QTL allele was found on LGV of Stirling close to marker STM3179, which was associated with early maturity, short plants, and susceptibility to blight and explained 54.7, 26.5, 26.3, and 17.5% of the variation for maturity, height, tuber blight, and foliage blight. When the residuals from the regressions of foliage and tuber blight on maturity were analyzed, there was no significant effect of a QTL on LGV, but a duplex QTL allele for resistance was found on LGIV of Stirling, which explained 30.7 and 13.6% of the variation for foliage and tuber blight on an additive model. Partial dominance for resistance explained even more of the variation, up to 37.2% for foliage blight. A major gene for blight resistance in Stirling was also mapped to LGXI.

Chromosome Mapping↗
PubMed1997

Fine-scale mapping of quantitative trait loci using historical recombinations.

With increasing popularity of QTL mapping in economically important animals and experimental species, the need for statistical methodology for fine-scale QTL mapping becomes increasingly urgent. The ability to disentangle several linked QTL depends on the number of recombination events. An obvious approach to increase the recombination events is to increase sample size, but this approach is often constrained by resources. Moreover, increasing the sample size beyond a certain point will not further reduce the length of confidence interval for QTL map locations. The alternative approach is to use historical recombinations. We use analytical methods to examine the properties of fine QTL mapping using historical recombinations that are accumulated through repeated intercrossing from an F2 population. We demonstrate that, using the historical recombinations, both simple and multiple regression models can reduce significantly the lengths of support intervals for estimated QTL map locations and the variances of estimated QTL map locations. We also demonstrate that, while the simple regression model using historical recombinations does not reduce the variances of the estimated additive and dominant effects, the multiple regression model does. We further determine the power and threshold values for both the simple and multiple regression models. In addition, we calculate the Kullback-Leibler distance and Fisher information for the simple regression model, in the hope to further understand the advantages and disadvantages of using historical recombinations relative to F2 data.

Algorithms↗
PubMed2005

A logistic regression mixture model for interval mapping of genetic trait loci affecting binary phenotypes.

Often in genetic research, presence or absence of a disease is affected by not only the trait locus genotypes but also some covariates. The finite logistic regression mixture models and the methods under the models are developed for detection of a binary trait locus (BTL) through an interval-mapping procedure. The maximum-likelihood estimates (MLEs) of the logistic regression parameters are asymptotically unbiased. The null asymptotic distributions of the likelihood-ratio test (LRT) statistics for detection of a BTL are found to be given by the supremum of a chi2-process. The limiting null distributions are free of the null model parameters and are determined explicitly through only four (backcross case) or nine (intercross case) independent standard normal random variables. Therefore a threshold for detecting a BTL in a flanking marker interval can be approximated easily by using a Monte Carlo method. It is pointed out that use of a threshold incorrectly determined by reading off a chi2-probability table can result in an excessive false BTL detection rate much more severely than many researchers might anticipate. Simulation results show that the BTL detection procedures based on the thresholds determined by the limiting distributions perform quite well when the sample sizes are moderately large.

Algorithms↗
PubMed1998

Mapping of complex traits by single-nucleotide polymorphisms.

Molecular geneticists are developing the third-generation human genome map with single-nucleotide polymorphisms (SNPs), which can be assayed via chip-based microarrays. One use of these SNP markers is the ability to locate loci that may be responsible for complex traits, via linkage/linkage-disequilibrium analysis. In this communication, we describe a semiparametric method for combined linkage/linkage-disequilibrium analysis using SNP markers. Asymptotic results are obtained for the estimated parameters, and the finite-sample properties are evaluated via a simulation study. We also applied this technique to a simulated genome-scan experiment for mapping a complex trait with two major genes. This experiment shows that separate linkage and linkage-disequilibrium analyses correctly detected the signals of both major genes; but the rates of false-positive signals seem high. When linkage and linkage-disequilibrium signals were combined, the analysis yielded much stronger and clearer signals for the presence of two major genes than did two separate analyses.

Biosensing Techniques↗
PubMed1998

A mixture model approach to the mapping of quantitative trait loci in complex populations with an application to multiple cattle families.

A mixture model approach is presented for the mapping of one or more quantitative trait loci (QTLs) in complex populations. In order to exploit the full power of complete linkage maps the simultaneous likelihood of phenotype and a multilocus (all markers and putative QTLs) genotype is computed. Maximum likelihood estimation in our mixture models is implemented via an Expectation-Maximization algorithm: exact, stochastic or Monte Carlo EM by using a simple and flexible Gibbs sampler. Parameters include allele frequencies of markers and QTLs, discrete or normal effects of biallelic or multiallelic QTLs, and homogeneous or heterogeneous residual variances. As an illustration a dairy cattle data set consisting of twenty half-sib families has been reanalyzed. We discuss the potential which our and other approaches have for realistic multiple-QTL analyses in complex populations.

Animals↗
PubMed2005

Pedigree linkage disequilibrium mapping of quantitative trait loci.

In this paper, we propose to use pedigrees of any size and any types of relatives in joint high-resolution linkage disequilibrium (LD) and linkage mapping of quantitative trait loci (QTL) by variance component models. Two or multiple markers can be simultaneously used in modeling association with the trait locus, instead of using one marker a time in the analysis. The proposed method can provide a unified result by using two or multiple markers in the modeling. This may avoid the complications of different results obtained from the separate analysis of marker by marker. The models simultaneously incorporate both linkage and LD information. The measures of LD are modeled by mean coefficients, and linkage information is modeled by variance-covariance matrix. Using analytical formulas to calculate the regression coefficients, the genetic effects are shown to be decomposed into additive and dominance components. The noncentrality parameter approximations of test statistics of LD are provided to make power calculations. Power and type I error rates are explored to investigate the merit of the proposed method by both the analytical formulas and simulations. Comparing with the association between-family and association within-family ('AbAw') approach of Fulker and Abecasis et al, it is evident that the method proposed in this article is more powerful. The method is applied to investigate the relation between polymorphisms in the angiotensin 1-converting enzyme (ACE) genes and circulating ACE levels, with a better result than that of the 'AbAw' approach. Moreover, two markers I/D and 4656(CT)3/2 can fully interpret association with the trait locus at a 0.01 significance level, which provides a unique result for the ACE data.

Animals↗