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PubMed2005

Two novel quantitative trait linkage analysis statistics based on the posterior probability of linkage: application to the COGA families.

BACKGROUND: In this paper we apply two novel quantitative trait linkage statistics based on the posterior probability of linkage (PPL) to chromosome 4 from the GAW 14 COGA dataset. Our approaches are advantageous since they use the full likelihood, use full phenotypic information, do not assume normality at the population level or require population/sample parameter estimates; and like other forms of the PPL, they are specifically tailored to accumulate linkage evidence, either for or against linkage, across multiple sets of heterogeneous data. RESULTS: The first statistic uses all quantitative trait (QT) information from the pedigree (QT-posterior probability of linkage, PPL); we applied the QT-PPL to the trait ecb21 (resting electroencephalogram). The second statistic allows simultaneous incorporation of dichotomous trait data into the QT analysis via a threshold model (QTT-PPL); we applied the QTT-PPL to combined data on ecb21 and ALDX1. We obtained a QT-PPL of 96% at GABRB1 and a QT-PPL of 18% at FABP2 while the QTT-PPL was 4% and 2% at the same two loci, respectively. By comparison, the variance-components (VC) method, as implemented in SOLAR, yielded multipoint VC LOD scores of 2.05 and 2.21 at GABRB1 and FABP2, respectively; no other VC LODs were greater than 2. CONCLUSION: The QTT-PPL was only 4% at GABARB1, which might suggest that the underlying ecb21 gene does not also cause ALDX1, although features of the data complicate interpretation of this result.

Alcoholism↗
PubMed2005

A likelihood approach for quantitative-trait-locus mapping with selected pedigrees.

Selective sampling is a cost-effective design for mapping quantitative trait loci (QTLs). A unified framework, which naturally combines two complementary sources of linkage information in the data, is proposed for the mapping of QTLs using selected pedigrees. Score statistics for detecting linkage are introduced for single-locus models (univariate or bivariate phenotypes) and two-locus epistasis models. A computer implementation of the methods for single-locus univariate-phenotype models is provided for nuclear families with arbitrary number of sibs and is freely available.

Algorithms↗
PubMed2004

Genetic investigation of quantitative traits related to autism: use of multivariate polygenic models with ascertainment adjustment.

Autism is a severe developmental disorder of unknown etiology but with evidence for genetic influences. Here, we provide evidence for a genetic basis of several quantitative traits that are related to autism. These traits, from the Broader Phenotype Autism Symptom Scale (BPASS), were measured in nuclear families, each ascertained through two probands affected by autism spectrum disorder. The BPASS traits capture the continuum of severity of impairments and may be more informative for genetic studies than are the discrete diagnoses of autism that have been used by others. Using a sample of 201 nuclear families consisting of a total of 694 individuals, we implemented multivariate polygenic models with ascertainment adjustment to estimate heritabilities and genetic and environmental correlations between these traits. Our ascertainment adjustment uses conditioning on the phenotypes of probands, requires no modeling of the ascertainment process, and is applicable to multiplex ascertainment and multivariate traits. This appears to be the first such implementation for multivariate quantitative traits. The marked difference between heritability estimates of the trait for language onset with and without an ascertainment adjustment (0.08 and 0.22, respectively) shows that conclusions are sensitive to whether or not an ascertainment adjustment is used. Among the five BPASS traits that were analyzed, the traits for social motivation and range of interest/flexibility show the highest heritability (0.19 and 0.16, respectively) and also have the highest genetic correlation (0.92). This finding suggests a shared genetic basis of these two traits and that they may be most promising for future gene mapping and for extending pedigrees by phenotyping additional relatives.

Adolescent↗
PubMed2003

Segregation and linkage analysis for longitudinal measurements of a quantitative trait.

We present a method for using slopes and intercepts from a linear regression of a quantitative trait as outcomes in segregation and linkage analyses. We apply the method to the analysis of longitudinal systolic blood pressure (SBP) data from the Framingham Heart Study. A first-stage linear model was fit to each subject's SBP measurements to estimate both their slope over time and an intercept, the latter scaled to represent the mean SBP at the average observed age (53.7 years). The subject-specific intercepts and slopes were then analyzed using segregation and linkage analysis. We describe a method for using the standard errors of the first-stage intercepts and slopes as weights in the genetic analyses. For the intercepts, we found significant evidence of a Mendelian gene in segregation analysis and suggestive linkage results (with LOD scores >or= 1.5) for specific markers on chromosomes 1, 3, 5, 9, 10, and 17. For the slopes, however, the data did not support a Mendelian model, and thus no formal linkage analyses were conducted.

Adult Children↗
PubMed1997

Congenic strains for the blood pressure quantitative trait locus on rat chromosome 2.

A quantitative trait locus (QTL) for blood pressure was previously detected by linkage analysis in a region of rat chromosome 2 using segregating populations derived from crosses of the Dahl salt-sensitive (Dahl S) rat with rats of the Wistar-Kyoto (WKY) strain or Milan normotensive strain (MNS). Two congenic strains, S.WKY-D2N35/Nep and S.MNS-Adh/D2Mit5, have been constructed by replacing a region of chromosome 2 of the Dahl S rat with the homologous region (ie, low blood pressure QTL allele) of either the WKY or MNS rat, respectively. Systolic pressures of congenic strains S.WKY-D2N35/Nep and S.MNS-Adh/D2Mit5 fed a 2% NaCl diet for 24 days were 44+/-4.6 and 29+/-4.5 mm Hg lower, respectively, than that of the comparably treated Dahl S rats. The differences between congenic and Dahl S rats in blood pressure were highly significant (P<.001) and were corroborated by significantly (P<.001) lower ratio of heart weight to body weight in the congenic strains compared with Dahl S rats. The data from two congenic strains combined unequivocally establish the existence of a blood pressure QTL on rat chromosome 2.

Alleles↗
PubMed2004

Theoretical and empirical power of regression and maximum-likelihood methods to map quantitative trait loci in general pedigrees.

Both theoretical calculations and simulation studies have been used to compare and contrast the statistical power of methods for mapping quantitative trait loci (QTLs) in simple and complex pedigrees. A widely used approach in such studies is to derive or simulate the expected mean test statistic under the alternative hypothesis of a segregating QTL and to equate a larger mean test statistic with larger power. In the present study, we show that, even when the test statistic under the null hypothesis of no linkage follows a known asymptotic distribution (the standard being chi(2)), it cannot be assumed that the distribution under the alternative hypothesis is noncentral chi(2). Hence, mean test statistics cannot be used to indicate power differences, and a comparison between methods that are based on simulated average test statistics may lead to the wrong conclusion. We illustrate this important finding, through simulations and analytical derivations, for a recently proposed new regression method for the analysis of general pedigrees to map quantitative trait loci. We show that this regression method is not necessarily more powerful nor computationally more efficient than a maximum-likelihood variance-component approach. We advocate the use of empirical power to compare trait-mapping methods.

Chromosome Mapping↗
PubMed1998

Identification of quantitative trait loci for prolificacy and growth in mice.

Marker-quantitative trait locus (QTL) linkage was evaluated in F2 intercross and backcross mouse populations derived from stocks differing dramatically in prolificacy and mature weight. A highly prolific outbred Quackenbush-Swiss mouse line, or an inbred line derived from it (16.62 +/- 0.22 and 14.64 +/- 0.27 pups per litter, respectively) were used as one of the grandparents in these populations. The less prolific C57BL/6J inbred mouse line (6.67 +/- 0.37 pups per litter) was used as the other grandparent. Linkage was evaluated in a three-step process that involved selective genotyping of F2 intercross progeny representing extremes for prolificacy, genotyping of the full F2 for chromosomal regions potentially associated with prolificacy, and genotyping of the backcross for genomic regions significantly associated with prolificacy in the F2. Segments of Chromosomes (Chrs) 2 and 4 were significantly (P < 0.05, experiment-wise error rate) associated with prolificacy, and LOD scores suggestive of linkage were observed for litter size on Chr 9 and growth on Chrs 4 and 11. Existence of growth QTL was also supported by marker effects that were significant (P < 0.05) or approaching significance (P < 0.10) in the backcross. Additive litter size QTL effects ranged from 0.56 to 0.79 pups per litter, and dominance deviations ranged from -0.56 to 1.19 pups per litter, suggesting overdominance as a possible mode of gene action in some cases. The observation of pleiotropic or linked QTL for growth and prolificacy corresponds well with results from many selection experiments identifying positively correlated responses to selection for these two traits.

Analysis of Variance↗
PubMed2003

Mapping quantitative trait loci for vertebral trabecular bone volume fraction and microarchitecture in mice.

UNLABELLED: BMD, which reflects both cortical and cancellous bone, has been shown to be highly heritable; however, little is known about the specific genetic factors regulating trabecular bone. Genome-wide linkage analysis of vertebral trabecular bone traits in 914 adult female mice from the F2 intercross of C57BL/6J and C3H/HeJ inbred strains revealed a pattern of genetic regulation derived from 13 autosomes, with 5-13 QTLs associated with each of the traits. Ultimately, identification of genes that regulate trabecular bone traits may yield important information regarding mechanisms that regulate mechanical integrity of the skeleton. INTRODUCTION: Both cortical and cancellous bone influence the mechanical integrity of the skeleton, with the relative contribution of each varying with skeletal site. Whereas areal BMD, which reflects both cortical and cancellous bone, has been shown to be highly heritable, little is known about the genetic determinants of trabecular bone density and architecture. MATERIALS AND METHODS: To identify heritable determinants of vertebral trabecular bone traits, we evaluated the fifth lumbar vertebra from 914 adult female mice from the F2 intercross of C57BL/6J (B6) and C3H/HeJ (C3H) progenitor strains. High-resolution microCT was used to assess total volume (TV), bone volume (BV), bone volume fraction (BV/TV), trabecular thickness (Tb.Th), separation (Tb.Sp), and number (Tb.N) of the trabecular bone in the vertebral body in the progenitors (n = 8/strain) and female B6C3H-F2 progeny (n = 914). Genomic DNA from F2 progeny was screened for 118 PCR-based markers discriminating B6 and C3H alleles on all 19 autosomes. RESULTS AND CONCLUSIONS: Despite having a slightly larger trabecular bone compartment, C3H progenitors had dramatically lower vertebral trabecular BV/TV (-53%) and Tb.N (-40%) and higher Tb.Sp (71%) compared with B6 progenitors (p < 0.001 for all). Genome-wide quantitative trait analysis revealed a pattern of genetic regulation derived from 13 autosomes, with 5-13 quantitative trait loci (QTLs) associated with each of the vertebral trabecular bone traits, exhibiting adjusted LOD scores ranging from 3.1 to 14.4. The variance explained in the F2 population by each of the individual QTL after adjusting for contributions from other QTLs ranged from 0.8% to 5.9%. Taken together, the QTLs explained 22-33% of the variance of the vertebral traits in the F2 population. In conclusion, we observed a complex pattern of genetic regulation for vertebral trabecular bone volume fraction and microarchitecture using the F2 intercross of the C57BL/6J and C3H/HeJ inbred mouse strains and identified a number of QTLs, some of which are distinct from those that were previously identified for total femoral and vertebral BMD. Identification of genes that regulate trabecular bone traits may ultimately yield important information regarding the mechanisms that regulate the acquisition and maintenance of mechanical integrity of the skeleton.

Animals↗
PubMed2001

Replication of linkage to quantitative trait loci: variation in location and magnitude of the lod score.

Replication of linkage signals from independent samples is considered an important step toward verifying the significance of linkage signals in studies of complex traits. The purpose of this empirical investigation was to examine the variability in the precision of localizing a quantitative trait locus (QTL) by analyzing multiple replicates of a simulated data set with the use of variance components-based methods. Specifically, we evaluated across replicates the variation in both the magnitude and the location of the peak lod scores. We analyzed QTLs whose effects accounted for 10-37% of the phenotypic variance in the quantitative traits. Our analyses revealed that the precision of QTL localization was directly related to the magnitude of the QTL effect. For a QTL with effect accounting for > 20% of total phenotypic variation, > 90% of the linkage peaks fall within 10 cM from the true gene location. We found no evidence that, for a given magnitude of the lod score, the presence of interaction influenced the precision of QTL localization.

Chromosome Mapping↗
PubMed2002

Mapping of quantitative trait loci based on growth models.

An approach called growth model-based mapping (GMM) of quantitative trait loci (QTLs) is proposed in this paper. The principle of the approach is to fit the growth curve of each individual or line with a theoretical or empirical growth model at first and then map QTLs based on the estimated growth parameters with the method of multiple-trait composite interval mapping. In comparison with previously proposed approaches of QTL mapping based on growth data, GMM has several advantages: (1) it can greatly reduce the amount of phenotypic data for QTL analysis and thus alleviate the burden of computation, particularly when permutation tests or simulation are performed to estimate significance thresholds; (2) it can efficiently analyze unbalanced phenotype data because both balanced and unbalanced data can be used for fitting growth models; and (3) it may potentially help us to better understand the genetic basis of quantitative trait development because the parameters in a theoretical growth model may often have clear biological meanings. A practical example of rice leaf-age development is presented to demonstrate the utility of GMM.

Journal Article↗
PubMed1998

The quantitative LOD score: test statistic and sample size for exclusion and linkage of quantitative traits in human sibships.

We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

Chromosome Mapping↗
PubMed1997

A linkage strategy for detection of human quantitative-trait loci. I. Generalized relative risk ratios and power of sib pairs with extreme trait values.

We generalize the concept of the relative risk ratio (lambda) to the case of quantitative traits, to take into account the various trait outcomes of a relative pair. Formulas are derived to express the expected proportions of genes shared identical by descent by a sib pair, in terms of the generalized lambda's for sib pairs (lambda S), parent-offspring pairs (lambda O), and monozygotic twins (lambda M) and in terms of the recombination fraction, with the assumption of no residual correlations. If residual correlations are nonzero among relative pairs, we assume that they are the same among sib pairs, parent-offspring pairs, and monozygotic twins, and we employ a slightly different definition for the generalized lambda so that the same set of formulas still hold. The power (or, the sample size necessary) to detect quantitative-trait loci (QTLs) by use of extreme sib pairs (ESPs) is shown to be a function of the three generalized lambda's. Since lambda M can be derived by use of values of lambda S and lambda O, estimates of the latter two lambda's will suffice for the analysis of power and the necessary sample sizes of ESPs, for a QTL linkage study.

Female↗
PubMed2004

Identification of quantitative trait loci for wood and fibre properties in two full-sib properties of Eucalyptus globulus.

Regions of the genome influencing wood and fibre traits in Eucalyptus globulus Labill. have been identified in two full-sib pedigrees that share a common male parent. The first pedigree, cross A, contains 148 progeny, and the second pedigree, cross B, contains 135 progeny. Subsets of progeny of these two controlled crosses were planted at seven sites throughout Australia in 1990. Wood cores were taken at 0.9 m above ground in 1997, and wood and fibre traits were analysed for each individual. Three quantitative trait loci (QTL) affecting wood density, one QTL affecting pulp yield and one QTL affecting microfibril angle have been located in both pedigrees, using single-factor analysis of variance. Other QTLs affecting these traits, as well as fibre length and cellulose content, were located in cross A only.

Analysis of Variance↗
PubMed2004

Quantitative trait loci affecting plant regeneration from protoplasts of Brassica oleracea.

Quantitative trait loci (QTLs) controlling the plant-regeneration ability of Brassica oleracea protoplasts were mapped in a population of 128 F(2) plants derived from a cross between the high-responding, rapid-cycling line and a low-responding, broccoli breeding line of B. oleracea. A modified bulked segregant analysis with AFLP markers identified two QTLs for plant regeneration. In a multiple regression analysis, the two QTLs explained 83% of the total genetic variation for regeneration recorded 15 weeks after initial transfer of microcalli to regeneration medium. Both QTLs showed additive effects, and the alleles contributing to the high regeneration frequencies were derived from the high-responding, rapid-cycling line. Using microsatellites with known location, the two QTLs were mapped to linkage groups O2 and O9 on the map published by Sebastian et al. [(2000) Theor Appl Genet 100:75-81] or to chromosomes C8 and C7 on the map published by Saal et al. [(2001) Theor Appl Genet 102:695-699]. QTLs for the early flowering trait of the rapid-cycling parent have previously been mapped to the same two linkage groups. Association between flowering time and regeneration ability was, however, not found in the present material, indicating that plant-regeneration ability can be transferred between cultivars independently of the early flowering trait. The detection of two major QTLs for plant regeneration in B. oleracea may provide the initial step towards the identification of markers suitable for marker-assisted selection of regeneration ability.

Brassica↗
PubMed1997

Multipoint oligogenic linkage analysis of quantitative traits.

We present an overview of pedigree-based variance component linkage methods and discuss their extension to oligogenic inheritance. As an example, oligogenic linkage analyses were performed using the quantitative trait Q4 from the GAW10 simulated data set. A strategy involving sequential oligogenic analyses was found to have increased power to detect the three quantitative trait loci (QTL) influencing Q4 when compared to the classical marginal approach of requiring each locus to have a lod score > or = 3. However, it is shown that requiring conditional lod scores > or = 3 in the sequential analyses may be overly conservative and alternative criteria for the acceptance of multilocus models are discussed.

Analysis of Variance↗
PubMed2001

Bayesian association mapping for quantitative traits in a mixture of two populations.

We introduce a novel Bayesian approach to estimate and account for population structure simultaneously with association mapping of multiple quantitative trait loci. The method is designed for an analysis of unrelated individuals from a mixture of two populations (no admixture), where the individual population memberships are unknown. In our approach, the population structure is estimated and accounted for by using data on additional "grouping" markers which are assumed to be in Hardy-Weinberg equilibrium within the populations but have different allele frequencies between the populations. We use Bayesian hierarchical modeling and Markov chain Monte Carlo estimation, where we allow both population stratification and genetic heterogeneity. In our model the number of quantitative trait loci and their positions are treated as random variables, and we obtain their posterior distributions. Here we select the candidate and the grouping markers based on results from a preliminary SOLAR analysis.

Bayes Theorem↗
PubMed2003

On the power to detect SNP/phenotype association in candidate quantitative trait loci genomic regions: a simulation study.

We use coalescent methods to investigate the ability of linked neutral "markers" to reveal in simulated population samples the presence of one or more single nucleotide polymorphisms that is contributing to a trait having a complex genetic basis (QTN: quantitative trait nucleotide). Realistic mutation and recombination rates in our simulations allow us to generate SNP data appropriate for analyzing human variation across short chromosomal intervals corresponding to approximately 100 kilobases. We investigate the performance of both single marker and multiple-marker (haplotype) data for several ad hoc procedures. Our results with single SNP markers indicate that (1) the density of SNP markers need not be much higher than 10% in order to achieve near-maximal detection of a QTN; (2) a higher density of markers does not improve much on the ability to localize a QTN within an interval unless the recombination rate is high. Haplotype-based tests were investigated for the case in which more than one QTN is present in the studied interval. Larger sample sizes improve both the probability of detecting the haplotype with the largest number of QTNs, as well as the ability to infer correct haplotypes from genotypic data. Testing a series of short haplotypes across a longer interval can also be beneficial. The rate of false positives (i.e., when the most significant haplotype does not contain the greatest number of QTNs in the sample) can be very high when the contribution of individual QTNs to a trait is small. The elimination of low-frequency haplotypes does not substantially reduce the probability of detecting the haplotype with the largest number of QTNs but it can reduce the rate of false positives.

Computational Biology↗
PubMed2006

Major quantitative trait locus on chromosome 2 for glucose tolerance in diabetic SMXA-5 mouse established from non-diabetic SM/J and A/J strains.

AIMS/HYPOTHESIS: The SMXA-5 mouse is one of the SMXA recombinant inbred substrains established from the non-diabetic SM/J and A/J strains, and is a model for polygenic type 2 diabetes, characterised by moderately impaired glucose tolerance and hyperinsulinaemia. These diabetic traits are worsened by feeding a high-fat diet. The aim of this study was to dissect the diabetogenic loci in the A/J regions of the SMXA-5 genome that contribute to diabetes-related traits. MATERIALS AND METHODS: We analysed the quantitative trait loci (QTL) for diabetes-related traits and obesity in (SM/JxSMXA-5)F(2) intercross mice fed a high-fat diet. To verify the function of the responsible locus that was mapped in the present study, we constructed a congenic strain and characterised its diabetes-related traits. RESULTS: A major QTL for glucose tolerance, free-fed blood glucose concentration and BMI was mapped on chromosome 2. This locus existed near D2Mit15, with the highest logarithm of the odds score (12.6) for glucose concentration at 120 min in a glucose tolerance test, and was designated T2dm2sa. The diabetogenic allele of T2dm2sa originated in the A/J strain. SM.A-T2dm2sa, a congenic strain that introgressed the T2dm2sa region of A/J genome into SM/J, exhibited overt impaired glucose tolerance and hyperinsulinaemia. CONCLUSIONS/INTERPRETATION: The development of impaired glucose tolerance in SM.A-T2dm2sa mice confirmed the results of QTL analysis for diabetes-related traits in F(2) intercross mice. The present results suggest that there are latent diabetogenic loci in the genomes of non-diabetic A/J and SM/J mice, and that the coexistence of these loci, including T2dm2sa, causes impaired glucose tolerance in SMXA-5 and SM.A-T2dm2sa mice.

Animals↗