Empirical threshold values for quantitative trait mapping

Identification of Quantitative Trait Loci Governing Arthritis Severity and Humoral Responses in the Murine Model of Lyme Disease

A spectrum of disease severity has been observed in patients with Lyme disease, with ∼60% of untreated individuals developing arthritis. The murine model of Lyme disease has provided strong evidence that the genetic composition of the host influences the severity of arthritis following infection with Borrelia burgdorferi: infected C3H mice develop severe arthritis while infected C57BL/6N mice develop mild arthritis. Regions of the mouse genome controlling arthritis severity and humoral responses during B. burgdorferi infection were identified in the F2 intercross generation of C3H/HeNCr and C57BL/6NCr mice. Rear ankle swelling measurements identified quantitative trait loci (QTL) on chromosomes 4 and 5, while histopathological scoring identified QTL on a unique region of chromosome 5 and on chromosome 11. The identification of QTL unique for ankle swelling or histopathological severity suggests that processes under distinct genetic control are responsible for these two manifestations of Lyme arthritis. Additional QTL that control the levels of circulating Igs induced by B. burgdorferi infection were identified on chromosomes 6, 9, 11, 12, and 17. Interestingly, the magnitude of the humoral response was not correlated with the severity of arthritis in infected F2 mice. This work defines several genetic loci that regulate either the severity of arthritis or the magnitude of humoral responses to B. burgdorferi infection in mice, with implications toward understanding the host-pathogen interactions involved in disease development.

Whole genome scan in chickens for quantitative trait loci affecting growth and feed efficiency

A feed efficiency experiment was conducted in a population consisting of progeny from 10 full sib families of a cross between two broiler lines. Microsatellite genotypes were determined on Generation (G) 1 and 2. In G3, BW at 23 and 48 d and feed intake were measured and were used to calculate growth between 23 and 48 d, feed intake adjusted for BW, and feed efficiency. Average adjusted progeny trait values were calculated for G2 animals after adjusting phenotypic observations on offspring for fixed effects, covariables, maternal genetic effects, the additive genetic contribution of the mate, and heterogeneity between sexes and were used as dependent variable in the quantitative trait loci (QTL) analysis. A full sib interval mapping approach was applied using genotypes from 420 markers on 27 autosomal linkage groups. Four QTL exceeded significance thresholds. The most significant QTL was located on Chromosome 1 at 235 cM and had a 4% genomewise significance for feed intake between 23 and 48 d. Furthermore, this QTL exceeded suggestive linkage for growth between 23 and 48 d and BW at 48 d. A second QTL was located on linkage group WAU26 at 16 cM and showed suggestive linkage for feed intake between 23 and 48 d. On Chromosome 4, at 147 cM a third QTL, which had an effect on both feed intake traits, was found. Finally, a fourth QTL, which affected feed intake adjusted for BW, was located on Chromosome 2 at 41 cM.

Time-related mapping of quantitative trait loci underlying tiller number in rice

Using time-related phenotypic data, methods of composite interval mapping and multiple-trait composite interval mapping based on least squares were applied to map quantitative trait loci (QTL) underlying the development of tiller number in rice. A recombinant inbred population and a corresponding saturated molecular marker linkage map were constructed for the study. Tiller number was recorded every 4 or 5 days for a total of seven times starting at 20 days after sowing. Five QTL were detected on chromosomes 1, 3, and 5. These QTL explained more than half of the genetic variance at the final observation. All the QTL displayed an S-shaped expression curve. Three QTL reached their highest expression rates during active tillering stage, while the other two QTL achieved this either before or after the active tillering stage.

Statistical methods for mapping quantitative trait loci from a dense set of markers

Lander and Botstein introduced statistical methods for searching an entire genome for quantitative trait loci (QTL) in experimental organisms, with emphasis on a backcross design and QTL having only additive effects. We extend their results to intercross and other designs, and we compare the power of the resulting test as a function of the magnitude of the additive and dominance effects, the sample size and intermarker distances. We also compare three methods for constructing confidence regions for a QTL: likelihood regions, Bayesian credible sets, and support regions. We show that with an appropriate evaluation of the coverage probability a support region is approximately a confidence region, and we provide a theroretical explanation of the empirical observation that the size of the support region is proportional to the sample size, not the square root of the sample size, as one might expect from standard statistical theory.

Genetic Determinants of Autoimmune Disease and Coronary Vasculitis in the MRL-lpr/lpr Mouse Model of Systemic Lupus Erythematosus

MRL-lpr/lpr (MRL/lpr) mice are a model of human autoimmune disease. They exhibit a number of characteristics of systemic lupus erythematosus, including anti-DNA Abs, anti-cardiolipin Abs, immune complex-mediated vasculitis, lymphadenopathy, and severe glomerulonephritis. Although the autoimmune disorder is mediated primarily by mutation of the Fas gene (lpr), which interferes with lymphocyte apoptosis, MRL/lpr mice also have other predisposing genetic factors. In an effort to identify these additional factors, we have applied quantitative trait locus (QTL) mapping using an intercross between MRL/lpr mice and the nonautoimmune inbred strain BALB/cJ. A complete linkage map spanning the entire genome was constructed for 189 intercross progeny, and genetic loci contributing to features of the autoimmunity were identified using statistical analytic procedures. As expected, the primary genetic determinant of autoimmune disease in this cross was the Fas gene on mouse chromosome 19, exhibiting a lod score of 60. In addition, two novel loci, one on chromosome 2 (lod score, 4.3) and one on chromosome 11 (lod score, 3.1), were found to contribute to levels of anti-DNA Abs. Interestingly, the chromosome 19 and chromosome 11 QTLs, but not the chromosome 2 QTL, also exhibited associations with anti-cardiolipin Abs (lod scores, 38.4 and 2.6). We further examined the effects of these QTLs on the development of coronary vasculitis in the F2 mice. Our results indicate that the QTLs on chromosomes 11 and 19 also control the development of vasculitis, demonstrating common genetic determinants of autoantibody levels and vasculitis.

A new approach to the problem of multiple comparisons in the genetic dissection of complex traits

Saturated genetic marker maps are being used to map individual genes affecting quantitative traits. Controlling the "experimentwise" type-I error severely lowers power to detect segregating loci. For preliminary genome scans, we propose controlling the "false discovery rate," that is, the expected proportion of true null hypotheses within the class of rejected null hypotheses. Examples are given based on a granddaughter design analysis of dairy cattle and simulated backcross populations. By controlling the false discovery rate, power to detect true effects is not dependent on the number of tests performed. If no detectable genes are segregating, controlling the false discovery rate is equivalent to controlling the experimentwise error rate. If quantitative loci are segregating in the population, statistical power is increased as compared to control of the experimentwise type-I error. The difference between the two criteria increases with the increase in the number of false null hypotheses. The false discovery rate can be controlled at the same level whether the complete genome or only part of it has been analyzed. Additional levels of contrasts, such as multiple traits or pedigrees, can be handled without the necessity of a proportional decrease in the critical test probability.

Test of candidate gene--quantitative trait locus association applied to fatness in mice

We test for the contribution of five strong candidate genes for obesity to quantitative variation for fatness in mice. The candidate loci are known through their major mutant phenotypes. We propose a randomization test for overall contribution of candidate genes, based on the empirical distribution of LOD scores from a quantitative trait locus (QTL) genome scan. The test is applied to data on body fat content and male gonadal fatpad weight from a QTL genome scan with an F2 population of C57BL/6J and DBA/2J inbred mice. The test is nonsignificant in this experiment for overall body fat content. QTLs detected at an experiment-wide significance level on chromosome 4, 6, 13 and 15 have effects on mean fatness of up to 19% between the homozygotes, but map to locations where there is no strong candidate gene. The test is significant for gonadal fat pad weight in males, and gives weak support for an association with the diabetes gene.

A quantitative genetic approach towards volatile anesthetic mechanisms in C. elegans

Quantitative genetics is the study of the heritability of continuous traits such as height or IQ. Quantitative trait loci (QTLs) represent the genes that are responsible for these quantitative traits. Sensitivity to the volatile anesthetic halothane is a genetically controlled quantitative trait in the nematode C. elegans. The QTLs that are responsible for the 12-fold range in halothane EC50 in these strains map to a few places with at least one major effect locus on chromosome V. Congenic strains for chromosome V confirmed these loci and offer the means to finely map them for positional cloning.

Multiple phenotype modeling in gene-mapping studies of quantitative traits: power advantages

Genomewide searches for loci influencing complex human traits and diseases such as diabetes, hypertension, and obesity are often plagued by low power and interpretive difficulties. Attempts to remedy these difficulties have typically relied on, and have promoted the use of, novel subject-ascertainment schemes, larger sample sizes, a greater density of DNA markers, and more-sophisticated statistical modeling and analysis strategies. Many of these remedies can be costly to implement. We investigate the utility of a simple statistical model for the mapping of quantitative-trait loci that incorporates multiple phenotypic or diagnostic endpoints into a gene-mapping analysis. The approach considers finding a linear combination of multiple phenotypic values that maximizes the evidence for linkage to a locus. Our results suggest that substantial increases in the power to map loci can be obtained with the proposed technique, although the increase in power obtained is a function of the size and direction of the residual correlation among the phenotypes used in the analysis. Extensive simulation studies are described that justify these claims, for cases in which two phenotypic measures are analyzed. This approach can be easily extended to cover more-complex situations and may provide a basis for more insightful genetic-analysis paradigms.

A nonparametric bootstrap method for testing close linkage vs. pleiotropy of coincident quantitative trait loci

A novel method using the nonparametric bootstrap is proposed for testing whether a quantitative trait locus (QTL) at one chromosomal position could explain effects on two separate traits. If the single-QTL hypothesis is accepted, pleiotropy could explain the effect on two traits. If it is rejected, then the effects on two traits are due to linked QTLs. The method can be used in conjunction with several QTL mapping methods as long as they provide a straightforward estimate of the number of QTLs detectable from the data set. A selection step was introduced in the bootstrap procedure to reduce the conservativeness of the test of close linkage vs. pleiotropy, so that the erroneous rejection of the null hypothesis of pleiotropy only happens at a frequency equal to the nominal type I error risk specified by the user. The approach was assessed using computer simulations and proved to be relatively unbiased and robust over the range of genetic situations tested. An example of its application on a real data set from a saline stress experiment performed on a recombinant population of wheat (Triticum aestivum L. ) doubled haploid lines is also provided.

Genetic analysis of a mammalian wound-healing trait

Wound healing of mammalian tissue is an essential process in the maintenance of body integrity. The general mechanism of wound healing usually studied in adult mammals is repair, in contrast to the regeneration seen in more primitive vertebrates. We recently have discovered that MRL/MpJ mice, unlike all other strains of mice tested, undergo rapid and complete wound closure that resembles regeneration. Specifically, through-and-through surgical ear hole wounds close without scarring in <4 weeks with normal gross and microanatomic architecture, including chondrogenesis. We also demonstrated that this healing is a heritable trait in inbred mice. In this study, we present results pertaining to its genetic control in progeny segregating for this phenotype. To identify the genetic loci that control the wound closure process, a genome-wide scan was performed on (MRL/MpJ-Faslpr x C57BL/6)F2 and backcross populations. In the primary screens of these populations, quantitative trait loci that control the extent of wound closure were detected on chromosomes 8, 12, and 15 and at two separate locations on chromosome 13. Evidence of further genetic control of healing was found on chromosome 7. All alleles that contribute to full wound closure are derived from the MRL/MpJ-Faslpr parent except for the quantitative trait locus on chromosome 8, which is derived from C57BL/6.

Quantitative trait loci affecting body weight and fatness from a mouse line selected for extreme high growth

Quantitative trait loci (QTL) influencing body weight were mapped by linkage analysis in crosses between a high body weight selected line (DU6) and a control line (DUKs). The two mouse lines differ in body weight by 106% and in abdominal fat weight by 100% at 42 days. They were generated from the same base population and maintained as outbred colonies. Determination of line-specific allele frequencies at microsatellite markers spanning the genome indicated significant changes between the lines on 15 autosomes and the X chromosome. To confirm these effects, a QTL analysis was performed using structured F2 pedigrees derived from crosses of a single male from DU6 with a female from DUKs. QTL significant at the genome-wide level were mapped for body weight on chromosome 11; for abdominal fat weight on chromosomes 4, 11, and 13; for abdominal fat percentage on chromosomes 3 and 4; and for the weights of liver on chromosomes 4 and 11, of kidney on chromosomes 2 and 9, and of spleen on chromosome 11. The strong effect on body weight of the QTL on chromosome 11 was confirmed in three independent pedigrees. The effect was additive and independent of sex, accounting for 21-35% of the phenotypic variance of body weight within the corresponding F2 populations. The test for multiple QTL on chromosome 11 with combined data from all pedigrees indicated the segregation of two loci separated by 36 cM influencing body weight.

Restricted maximum likelihood analysis of linkage between genetic markers and quantitative trait loci for a granddaughter design

A REML for the estimation of location and variance of a single quantitative trait locus, together with polygenic and residual variance, is described for the analysis of a granddaughter design. The method is based on a mixed linear model that includes the allelic effects of the quantitative trait locus, which are assumed to be normally distributed. Information from four marker loci situated on a single chromosome was available to derive the covariances at the linked quantitative trait locus. A derivative-free algorithm is described that makes use of the specific structure of the granddaughter design. The procedure has been applied to simulated data for a granddaughter design with 50 grandsire families of 40 sires each. Error variance was 60, and total additive genetic variance equaled 40; the quantitative trait locus explained either 10 or 25% of the latter variance. The size of the marker bracket containing the quantitative trait locus was either 10 or 30 cM. The power of detecting the quantitative trait locus ranged from 19 to 99%. Estimates of total genetic variance and variance explained by the quantitative trait locus were found to be empirically unbiased. A small bias was found in location estimates, especially when markers were not fully informative. The accuracy of parameter estimates was greatly improved by the use of information from individual daughters.

New Genetic Loci That Control Susceptibility and Symptoms of Experimental Allergic Encephalomyelitis in Inbred Mice

Experimental allergic encephalomyelitis (EAE), the principal animal model of multiple sclerosis, is a genetically determined phenotype. In this study, analyses of the cumulative disease frequencies in parental, F1 hybrid, and F2 mice, derived from the EAE-susceptible SJL/J strain and the EAE-resistant B10.S/DvTe strain, confirmed that susceptibility to EAE is not inherited as a simple Mendelian trait. Whole genome scanning, using 150 informative microsatellite markers and a panel of 291 affected and 390 unaffected F2 progeny, revealed significant linkage of EAE susceptibility to marker loci on chromosomes 7 (eae4) and 17, distal to H2 (eae5). Quantitative trait loci for EAE severity, duration, and onset were identified on chromosomes 11 (eae6, and eae7), 2 (eae8), 9 (eae9), and 3 (eae10). While each locus reported in this study is important in susceptibility or disease course, interactions between marker loci were not statistically significant in models of genetic control. One locus, eae7, colocalizes to the same region of chromosome 11 as Orch3 and Idd4, susceptibility loci in autoimmune orchitis and insulin-dependent diabetes mellitus, respectively. Importantly, eae5 and eae7 are syntenic with human chromosomes 6p21 and 17q22, respectively, two regions of potential significance recently identified in human multiple sclerosis genome scans.

Genotype-environment interaction at quantitative trait loci affecting sensory bristle number in Drosophila melanogaster

The magnitude of segregating variation for bristle number in Drosophila melanogaster exceeds that predicted from models of mutation-selection balance. To evaluate the hypothesis that genotype-environment interaction (GEI) maintains variation for bristle number in nature, we quantified the extent of GEI for abdominal and sternopleural bristles among 98 recombinant inbred lines, derived from two homozygous laboratory strains, in three temperature environments. There was considerable GEI for both bristle traits, which was mainly attributable to changes in rank order of line means. We conducted a genome-wide screen for quantitative trait loci (QTLs) affecting bristle number in each sex and temperature environment, using a dense (3.2-cM) marker map of polymorphic insertion sites of roo transposable elements. Nine sternopleural and 11 abdominal bristle number QTLs were detected. Significant GEI was exhibited by 14 QTLs, but there was heterogeneity among QTLs in their sensitivity to thermal and sexual environments. To further evaluate the hypothesis that GEI maintains variation for bristle number, we require estimates of allelic effects across environments at genetic loci affecting the traits. This level of resolution may be achievable for Drosophila bristle number because candidate loci affecting bristle development often map to the same location as bristle number QTLs.

Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree

Quantitative trait loci (QTL) affecting milk production and health of dairy cattle were mapped in a very large Holstein granddaughter design. The analysis included 1794 sons of 14 sires and 206 genetic markers distributed across all 29 autosomes and flanking an estimated 2497 autosomal cM using Kosambi's mapping function. All families were analyzed jointly with least-squares (LS) and variance components (VC) methods. A total of 6 QTL exceeding approximate experiment-wise significance thresholds, 24 QTL exceeding suggestive thresholds, and 34 QTL exceeding chromosome-wise thresholds were identified. Significance thresholds were determined via data permutation (for LS analysis) and chi-square distribution (for VC analysis). The average bootstrap confidence interval for the experiment-wise significant QTL was 48 cM. Some chromosomes harbored QTL affecting several traits, and these were always in coupling phase, defined by consistency with genetic correlations among traits. Chromosome 17 likely harbors 2 QTL affecting milk yield, and some other chromosomes showed some evidence for 2 linked QTL affecting the same trait. In each of these cases, the 2 QTL were in repulsion phase in those families appearing to be heterozygous for both QTL, a finding which supports the build-up of linkage disequilibrium due to selection.

Reaction norm functions and QTL-environment interactions for flowering time in Arabidopsis thaliana

Many plant traits are phenotypically plastic in response to resource levels that vary continuously among environments. To be able to predict phenotypes in new environments, it is useful to model reaction norms as functions, rather than as a collection of discrete character states. Flowering date and rosette leaf number were measured in 100 recombinant inbred lines of Arabidopsis thaliana, grown on a gradient of light intensity. The results show that there is genetic variation among the recombinant inbred lines for parameters of the reaction norm functions. Genetic variances for leaf number and flowering date are highest under low light conditions. Underlying quantitative trait loci (QTLs) affecting the shape of the reaction norm functions were mapped by modifying Haley & Knott (1992) regressions to include polynomial effects of the environment. Quantitative trait loci of large effect were generally insensitive to the resource gradient. Seven QTLs affecting flowering date and eight QTLs for rosette leaf number were identified, of which only two had significant effects on the linear and quadratic components of the reaction norm function. These results suggest that the genotype-environment interactions for flowering time are controlled by many minor genes, whose effects are below the detection limit in most mapping experiments.

A rank-based nonparametric method for mapping quantitative trait loci in outbred half-sib pedigrees: application to milk production in a granddaughter design

We describe the development of a multipoint nonparametric quantitative trait loci mapping method based on the Wilcoxon rank-sum test applicable to outbred half-sib pedigrees. The method has been evaluated on a simulated dataset and its efficiency compared with interval mapping by using regression. It was shown that the rank-based approach is slightly inferior to regression when the residual variance is homoscedastic normal; however, in three out of four other scenarios envisaged, i.e., residual variance heteroscedastic normal, homoscedastic skewed, and homoscedastic positively kurtosed, the latter outperforms the former one. Both methods were applied to a real data set analyzing the effect of bovine chromosome 6 on milk yield and composition by using a 125-cM map comprising 15 microsatellites and a granddaughter design counting 1158 Holstein-Friesian sires.

Multiple marker mapping of quantitative trait loci in a cross between outbred wild boar and large white pigs

A quantitative trait locus (QTL) analysis of growth and fatness data from a three generation pig experiment is presented. The population of 199 F2 animals was derived from a cross between wild boar and Large White pigs. Animals were typed for 240 markers spanning 23 Morgans of 18 autosomes and the X chromosome. A series of analyses are presented within a least squares framework. First, these identify chromosomes containing loci controlling trait variation and subsequently attempt to map QTLs to locations within chromosomes. This population gives evidence for a large QTL affecting back fat and another for abdominal fat segregating on chromosome 4. The best locations for these QTLs are within 4 cM of each other and, hence, this is likely to be a single QTL affecting both traits. The allele inherited from the wild boar causes an increase in fat deposition. A QTL for intestinal length was also located in the same region on chromosome 4 and could be the same QTL with pleiotropic effects. Significant effects, owing to multiple QTLs, for intestinal length were identified on chromosomes 3 and 5. A single QTL affecting growth rate to 30 kg was located on chromosome 13 such that the Large White allele increased early growth rate, another QTL on chromosome 10 affected growth rate from 30 to 70 kg and another on chromosome 4 affected growth rate to 70 kg.

Two sites in the Delta gene region contribute to naturally occurring variation in bristle number in Drosophila melanogaster

A restriction enzyme survey of a 57-kb region including the gene Delta uncovered 53 polymorphic molecular markers in a sample of 55 naturally occurring chromosomes. A permutation test, which assesses the significance of the molecular marker with the largest effect on bristle variation in four genetic backgrounds relative to permuted data-sets, found two sites that were independently associated with variation in bristle number. A common site in the second intron of Delta affected only sternopleural bristle number, and another common site in the fifth intron affected only abdominal bristle number in females. Under an additive genetic model, the polymorphism in the second intron may account for 12% of the total genetic variation in sternopleural bristle number due to third chromosomes, and the site in the fifth intron may account for 6% of the total variation in female abdominal bristle number due to the third chromosomes. These results suggest the following: (1) models that incorporate balancing selection are more consistent with observations than deleterious mutation-selection equilibrium models, (2) mapped quantitative trait loci of large effect may not represent a single variable site at a genetic locus, and (3) linkage disequilibrium can be used as a tool for understanding the molecular basis of quantitative variation.

Quantitative trait loci affecting differences in floral morphology between two species of monkeyflower (Mimulus)

Conspicuous differences in floral morphology are partly responsible for reproductive isolation between two sympatric species of monkeyflower because of their effect on visitation of the flowers by different pollinators. Mimulus lewisii flowers are visited primarily by bumblebees, whereas M. cardinalis flowers are visited mostly by hummingbirds. The genetic control of 12 morphological differences between the flowers of M. lewisii and M. cardinalis was explored in a large linkage mapping population of F2 plants n = 465 to provide an accurate estimate of the number and magnitude of effect of quantitative trait loci (QTLs) governing each character. Between one and six QTLs were identified for each trait. Most (9/12) traits appear to be controlled in part by at least one major QTL explaining >/=25% of the total phenotypic variance. This implies that either single genes of individually large effect or linked clusters of genes with a large cumulative effect can play a role in the evolution of reproductive isolation and speciation.

Autoimmune orchitis, epididymitis, and vasitis are immunogenetically distinct lesions

Experimental allergic orchitis (EAO), the principle animal model of noninfectious testicular inflammatory disease, is a genetically determined phenotype. Classical EAO, induced by inoculation with testicular homogenate and the appropriate adjuvants, is characterized by inflammatory infiltrates in the testis (orchitis), epididymis (epididymitis), and vas deferens (vasitis). In this study, the genetic control of susceptibility and resistance to these three lesions was analyzed in the mouse. The results obtained with independent inbred strains and H2 congenic mice show that the genetic control of all three lesions is complex and involves both H2 and non-H2-linked genes. Whole-genome exclusion mapping was performed on a backcross population segregating for all three phenotypes. Permutation-derived thresholds provided experimentwise, chromosomewise, comparisonwise, and marker-specific chromosomewise thresholds for declaration of significant regions linked to marker loci. Unique loci were identified on chromosome 8 for orchitis, chromosome 16 for epididymitis, and chromosome 1 for vasitis and have been designated as Orch6, Epd1, and Vas1, respectively. These results show that autoimmune orchitis, epididymitis, and vasitis are immunogenetically distinct lesions.

Mapping of serum amylase-1 and quantitative trait loci for milk production traits to cattle chromosome 4

The present study was undertaken to confirm and refine the mapping of a quantitative trait locus in cattle for milk fat percentage that had earlier been reported to be linked to the serum amylase-1 locus, AM1. Five half-sib families from the previous study and 7 new ones were genotyped for nine microsatellite markers spanning chromosome 4. AM1 was mapped between the microsatellite markers BMS648 and BR6303. In a granddaughter design, interval mapping based on multiple-marker regression was utilized for an analysis of five milk production traits: milk yield, fat percentage and yield, and protein percentage and yield. In the families reported on previously, significant effects for fat and protein percentages were detected. In the new families, an effect on milk and fat yields was found. The most likely positions of the quantitative trait locus in both groups of families were in the same area of chromosome 4 in the vicinity of the obese locus. Direct effects of the obese locus were tested for using polymorphism in two closely linked microsatellites located 2.5 and 3.6 top downstream of the coding sequence. No firm evidence was found for an association between the obese locus and the tested traits.

Chromosome 14 contains determinants that regulate susceptibility to Theiler's virus-induced demyelination in the mouse

Theiler's murine encephalomyelitis virus causes a chronic demyelinating disease in susceptible strains of mice that is similar to human multiple sclerosis. Several nonmajor histocompatibility complex-linked genes have been implicated as determinants of susceptibility or resistance to either demyelination or virus persistence. In this study, we used linkage analysis of major histocompatibility complex identical H-2d (DBA/2J x B10.D2) F2 intercross mice to identify loci associated with susceptibility to virus-induced demyelinating disease. In a 20-cM region on chromosome 14, we identified four markers, D14Mit54, D14Mit60, D14Mit61, and D14Mit90 that are significantly associated with demyelination. Because two peaks were identified, one near D14Mit54 and one near D14Mit90, it is possible that two loci in this region are involved in controlling demyelination.

Quantitative trait loci for honey bee stinging behavior and body size

A study was conducted to identify quantitative trait loci (QTLs) that affect colony-level stinging behavior and individual body size of honey bees. An F1 queen was produced from a cross between a queen of European origin and a drone descended from an African subspecies. Haploid drones from the hybrid queen were individually backcrossed to sister European queens to produce 172 colonies with backcross workers that were evaluated for tendency to sting. Random amplified polymorphic DNA markers were scored from the haploid drone fathers of these colonies. Wings of workers and drones were used as a measure of body size because Africanized bees in the Americas are smaller than European bees. Standard interval mapping and multiple QTL models were used to analyze data. One possible QTL was identified with a significant effect on tendency to sting (LOD 3.57). Four other suggestive QTLs were also observed (about LOD 1.5). Possible QTLs also were identified that affect body size and were unlinked to defensive-behavior QTLs. Two of these were significant (LOD 3.54 and 5.15).

Bayesian mapping of multiple quantitative trait loci from incomplete inbred line cross data

A novel fine structure mapping method for quantitative traits is presented. It is based on Bayesian modeling and inference, treating the number of quantitative trait loci (QTLs) as an unobserved random variable and using ideas similar to composite interval mapping to account for the effects of QTLs in other chromosomes. The method is introduced for inbred lines and it can be applied also in situations involving frequent missing genotypes. We propose that two new probabilistic measures be used to summarize the results from the statistical analysis: (1) the (posterior) QTL intensity, for estimating the number of QTLs in a chromosome and for localizing them into some particular chromosomal regions, and (2) the locationwise (posterior) distributions of the phenotypic effects of the QTLs. Both these measures will be viewed as functions of the putative QTL locus, over the marker range in the linkage group. The method is tested and compared with standard interval and composite interval mapping techniques by using simulated backcross progeny data. It is implemented as a software package. Its initial version is freely available for research purposes under the name Multimapper at URL http://www.rni.helsinki.fi/mjs.

Further investigation on the regression method of mapping quantitative trait loci

The simple regression method of mapping quantitative trait loci (QTL) is further investigated in comparison with the mixture model maximum likelihood method under high heritabilities, dominant and missing markers. No significant difference between the two methods is detected in terms of errors of parameter estimation and statistical powers, with the exception that the estimation of residual variance provided by the regression method is confounded with part of the QTL variance. The test statistic profiles show some difference between the two methods, but the difference is only detectable at the micro level. An alternative method, referred to as iteratively reweighted least squares, is proposed, which can correct the deficiency of parameter confounding in the regression method yet retains the properties of simplicity and rapidity of the ordinary regression method. Like the existing regression method, the weighted least squares method can be useful in QTL mapping in conjunction with the permutation tests and construction of confidence intervals by bootstrapping.

Autosomal genomic scan for loci linked to obesity and energy metabolism in Pima Indians

An autosomal genomic scan to search for linkage to obesity and energy metabolism was completed in Pima Indians, a population prone to obesity. Obesity was assessed by percent body fat (by hydrodensitometry) and fat distribution (the ratio of waist circumference to thigh circumference). Energy metabolism was measured in a respiratory chamber as 24-h metabolic rate, sleeping metabolic rate, and 24-h respiratory quotient (24RQ), an indicator of the ratio of carbohydrate oxidation to fat oxidation. Five hundred sixteen microsatellite markers with a median spacing of 6.4 cM were analyzed, in 362 siblings who had measurements of body composition and in 220 siblings who had measurements of energy metabolism. These comprised 451 sib pairs in 127 nuclear families, for linkage analysis to obesity, and 236 sib pairs in 82 nuclear families, for linkage analysis to energy metabolism. Pointwise and multipoint methods for regression of sib-pair differences in identity by descent, as well as a sibling-based variance-components method, were used to detect linkage. LOD scores >=2 were found at 11q21-q22, for percent body fat (LOD=2.1; P=.001), at 11q23-q24, for 24-h energy expenditure (LOD=2.0; P=.001), and at 1p31-p21 (LOD=2.0) and 20q11.2 (LOD=3.0; P=.0001), for 24RQ, by pointwise and multipoint analyses. With the variance-components method, the highest LOD score (LOD=2.3 P=.0006) was found at 18q21, for percent body fat, and at 1p31-p21 (LOD=2.8; P=.0003), for 24RQ. Possible candidate genes include LEPR (leptin receptor), at 1p31, and ASIP (agouti-signaling protein), at 20q11.2.

QTL analysis in plants; where are we now?

We have briefly reviewed the methods currently available for QTL analysis in segregating populations and summarized some of the conclusions arising from such analyses in plant populations. We show that the analytical methods locate QTL with poor precision (10-30 cM), unless the heritability of an individual QTL is high. Also the estimates of the QTL effects, particularly the dominance effects tend to be inflated because only large estimates are significant. Estimates of numbers of QTL per trait are generally low (< 8) for individual trials. This may suggest that there are few QTL but probably reflects the power of the methods. There is no large correlation between the numbers of QTL found and the amount of the variation explained. Of those cases where dominance is measurable, dominance ratios are often > 1, but seldom significantly greater. These latter cases need further analysis. Many QTL map close to candidate genes, and there is growing evidence from synteny studies of corresponding chromosome regions carrying similar QTL in different species. However, unreliability of QTL location may suggest false candidates.

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.

Genetic mapping of quantitative trait loci affecting susceptibility to Marek's disease virus induced tumors in F2 intercross chickens

Marek's disease (MD) is a lymphoproliferative disease caused by the MD virus (MDV), which costs the poultry industry nearly $1 billion annually. To identify quantitative trait loci (QTL) affecting MD susceptibility, the inbred lines 6(3) (MD resistant) and 7(2) (MD susceptible) were mated to create more than 300 F2 chickens. The F2 chickens were challenged with MDV JM strain, moderately virulent) at 1 wk of age and assessed for MD susceptibility. The QTL analysis was divided into three stages. In stage 1, 65 DNA markers selected from the chicken genetic maps were typed on the 40 most MD-susceptible and the 40 most MD-resistant F2 chickens, and 21 markers residing near suggestive QTL were revealed by analysis of variance (ANOVA). In stage 2, the suggestive markers plus available flanking markers were typed on 272 F2 chickens, and three suggestive QTL were identified by ANOVA. In stage 3, using the interval mapping program Map Manager and permutation tests, two significant and two suggestive MD QTL were identified on four chromosomal subregions. Three to five loci collected explained between 11 and 23% of the phenotypic MD variation, or 32-68% of the genetic variance. This study constitutes the first report in the domestic chicken on the mapping of non-major histocompatibility complex QTL affecting MD susceptibility.

Least squares interval mapping of quantitative trait loci under the infinitesimal genetic model in outbred populations

Genetic marker and phenotypic data for a quantitative trait were simulated on 20 paternal half-sib families with 100 progeny to investigate properties of within-family-regression interval mapping of a postulated single quantitative trait locus (QTL) in a marker interval under the infinitesimal genetic model, which has been the basis of the application of quantitative genetics to genetic improvement programs, and to investigate use of the infinitesimal model as null hypothesis in testing for presence of a major QTL. Genetic effects on the marked chromosome were generated based on a major gene model, which simulated a central biallelic QTL, or based on 101 biallelic QTL of equal effect, which approximated the infinitesimal model. The marked chromosome contained 0, 3.3%, 13.3%, or 33.3% of genetic variance and heritability was 0.25 or 0.70. Under the polygenic model with 3.3% of genetic variance on the marked chromosome, which corresponds to the infinitesimal model for the bovine, significant QTL effects were found for individual families. Correlations between estimates of QTL effects and true chromosome substitution effects were 0.29 and 0.47 for heritabilities of 0.25 and 0.70 but up to 0.85 with 33.3% of polygenic variance on the marked chromosome. These results illustrate the potential of marker-assisted selection even under the infinitesimal genetic model. Power of tests for presence of QTL was substantially reduced when the polygenic model with 3.3% of genetic variance on the chromosome was used as a null hypothesis. The ability to determine whether genetic variance on a chromosome was contributed by a single QTL of major effect or a large number of QTL with minor effects, corresponding to the infinitesimal model, was limited.

Empirical nonparametric bootstrap strategies in quantitative trait loci mapping: conditioning on the genetic model

Several nonparametric bootstrap methods are tested to obtain better confidence intervals for the quantitative trait loci (QTL) positions, i.e., with minimal width and unbiased coverage probability. Two selective resampling schemes are proposed as a means of conditioning the bootstrap on the number of genetic factors in our model inferred from the original data. The selection is based on criteria related to the estimated number of genetic factors, and only the retained bootstrapped samples will contribute a value to the empirically estimated distribution of the QTL position estimate. These schemes are compared with a nonselective scheme across a range of simple configurations of one QTL on a one-chromosome genome. In particular, the effect of the chromosome length and the relative position of the QTL are examined for a given experimental power, which determines the confidence interval size. With the test protocol used, it appears that the selective resampling schemes are either unbiased or least biased when the QTL is situated near the middle of the chromosome. When the QTL is closer to one end, the likelihood curve of its position along the chromosome becomes truncated, and the nonselective scheme then performs better inasmuch as the percentage of estimated confidence intervals that actually contain the real QTL's position is closer to expectation. The nonselective method, however, produces larger confidence intervals. Hence, we advocate use of the selective methods, regardless of the QTL position along the chromosome (to reduce confidence interval sizes), but we leave the problem open as to how the method should be altered to take into account the bias of the original estimate of the QTL's position.

Natural variation in neuron number in mice is linked to a major quantitative trait locus on Chr 11

Common genetic polymorphisms-as opposed to rare mutations-generate almost all heritable differences in the size and structure of the CNS. Surprisingly, these normal variants have not previously been mapped or cloned in any vertebrate species. In a recent paper (), we suggested that much of the variation in retinal ganglion cell number in mice, and the striking bimodality of strain averages, are caused by one or two quantitative trait loci (QTLs). To test this idea, and to map genes linked to this variable and highly heritable quantitative trait, we have counted ganglion cells in 38 recombinant inbred strains (BXD and BXH) derived from parental strains that have high and low cell numbers. A genome-wide search using simple and composite interval-mapping techniques revealed a major QTL on chromosome (Chr) 11 in a 3 cM interval between Hoxb and Krt1 (LOD = 6.8; genome-wide p = 0.001) and possible subsidiary QTLs on Chr 2 and Chr 8. The Chr 11 locus, neuron number control 1 (Nnc1), accounts for one third of the genetic variance among BXH strains and more than half of that among BXD strains, but Nnc1 has no known effects on brain weight, eye weight, or total retinal cell number. Three strong candidate genes have been mapped previously to the same region as Nnc1. These genes-Rara, Thra, and Erbb2- encode receptors for retinoic acid, thyroxine, and neuregulin, respectively. Each receptor is expressed in the retina during development, and their ligands affect the proliferation or survival of retinal cells.

Adaptive evolution via a major gene effect: paedomorphosis in the Mexican axolotl

Although adaptive evolution is thought to depend primarily on mutations of small effect, major gene effects may underlie many of the important differences observed among species in nature. The Mexican axolotl (Ambystoma mexicanum) has a derived mode of development that is characterized by metamorphic failure (paedomorphosis), an adaptation for an entirely aquatic life cycle. By using an interspecific crossing design and genetic linkage analysis, a major quantitative trait locus for expression of metamorphosis was identified in a local map of amplified fragment length polymorphisms. These data are consistent with a major gene hypothesis for the evolution of paedomorphosis in A. mexicanum.

Interleukin 9: a candidate gene for asthma

Asthma is a complex heritable inflammatory disorder of the airways associated with clinical signs of atopy and bronchial hyperresponsiveness. Recent studies localized a major gene for asthma to chromosome 5q31-q33 in humans. Thus, this segment of the genome represents a candidate region for genes that determine susceptibility to bronchial hyperresponsiveness and atopy in animal models. Homologs of candidate genes on human chromosome 5q31-q33 are found in four regions in the mouse genome, two on chromosome 18, and one each on chromosomes 11 and 13. We assessed bronchial responsiveness as a quantitative trait in mice and found it linked to chromosome 13. Interleukin 9 (IL-9) is located in the linked region and was analyzed as a gene candidate. The expression of IL-9 was markedly reduced in bronchial hyporesponsive mice, and the level of expression was determined by sequences within the qualitative trait locus (QTL). These data suggest a role for IL-9 in the complex pathogenesis of bronchial hyperresponsiveness as a risk factor for asthma.

Advances in statistical methods to map quantitative trait loci in outbred populations

Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown.

Sex-specific quantitative trait loci affecting longevity in Drosophila melanogaster

Senescence, the decline in survivorship and fertility with increasing age, is a near-universal property of organisms. Senescence and limited lifespan are thought to arise because weak natural selection late in life allows the accumulation of mutations with deleterious late-age effects that are either neutral (the mutation accumulation hypothesis) or beneficial (the antagonistic pleiotropy hypothesis) early in life. Analyses of Drosophila spontaneous mutations, patterns of segregating variation and covariation, and lines selected for late-age fertility have implicated both classes of mutation in the evolution of aging, but neither their relative contributions nor the properties of individual loci that cause aging in nature are known. To begin to dissect the multiple genetic causes of quantitative variation in lifespan, we have conducted a genome-wide screen for quantitative trait loci (QTLs) affecting lifespan that segregate among a panel of recombinant inbred lines using a dense molecular marker map. Five autosomal QTLs were mapped by composite interval mapping and by sequential multiple marker analysis. The QTLs had large sex-specific effects on lifespan and age-specific effects on survivorship and mortality and mapped to the same regions as candidate genes with fertility, cellular aging, stress resistance and male-specific effects. Late age-of-onset QTL effects are consistent with the mutation accumulation hypothesis for the evolution of senescence, and sex-specific QTL effects suggest a novel mechanism for maintaining genetic variation for lifespan.

Intrinsic and extrinsic control of hemopoietic stem cell numbers: mapping of a stem cell gene

We evaluated in vivo interactions between extrinsic (growth factor induced) and intrinsic (genetically determined) effectors of mouse primitive hemopoietic stem cell proliferation and numbers. Accordingly, stem cell frequency and cell cycle kinetics were assessed in eight strains of inbred mice using the cobblestone area-forming cell (CAFC) assay. A strong inverse correlation was observed between mouse lifespan and the number of autonomously cycling progenitors (CAFC day 7) in the femur. The population size of primitive stem cells (CAFC day 35) varied widely (up to sevenfold) among strains, unlike total CAFC day 7 numbers (cycling and quiescent), which were similar. Administration of the early acting cytokine flt-3 ligand to these strains resulted in activation of quiescent primitive stem cells exclusively in strains with high endogenous stem cell numbers (DBA and AKR), but was unrelated to strain-specific progenitor cell cycling. To map loci affecting stem cell frequency, we quantified stem cells in BXD recombinant inbred mice (offspring of C57BL/6 and DBA/2). The resulting strain distribution pattern showed high concordance with a marker that mapped to chromosome 18 (19 cM). Linkage with this genomic interval was associated with a likelihood of odds score of 3.3, surpassing the level required for significance. Interestingly, this segment, containing the EGR-1 gene, shows synteny with human chromosome 5q, a region strongly associated with various hematological malignancies. Our findings indicate that a gene mapping to this region is mutated in either C57BL/6 or DBA/2 (and possibly AKR) mice. These studies in apparently healthy mice may facilitate the identification of a gene implicated in human 5q-syndromes.

Quantitative trait loci controlling halothane sensitivity in Caenorhabditis elegans

Genetic analysis is an essential tool for defining the molecular mechanisms whereby volatile anesthetics (VA) disrupt nervous system function. However, the degree of natural variation of the genetic determinants of VA sensitivity has not been determined nor have mutagenesis approaches been very successful at isolating significantly resistant mutant strains. Thus, a quantitative genetic approach was taken toward these goals. Recombinant-inbred strains derived from two evolutionarily distinct lineages of the nematode Caenorhabditis elegans were tested for sensitivity to clinically relevant concentrations (0.3-0.5 mM) of the VA halothane. The halothane sensitivities of coordinated movement and male mating behavior were highly variant among the recombinant-inbred strains with a range of EC50 values of 13- and 4-fold, respectively. Both traits were highly heritable (H2 = 0.82, 0.87, respectively). Several strains were found to be significantly resistant to halothane when compared with the wild-type strain N2. A major locus or loci mapping to the middle of chromosome V accounted for more than 40% of the phenotypic variance for both traits. Five weaker loci, four of which interact, explained most of the remaining variance. None of the halothane-sensitivity quantitative trait loci significantly affected behavior in the absence of halothane or halothane's potency for C. elegans immobilization, which requires 5-fold higher drug concentrations. Thus, the quantitative trait loci are unlikely to result from differences in halothane-independent (native) behavior or differences in halothane metabolism or permeability. Rather, these loci may code for targets and/or downstream effectors of halothane in the C. elegans nervous system or for modifiers of such gene products.

Estimation of effects of quantitative trait loci in large complex pedigrees

A method was derived to estimate effects of quantitative trait loci (QTL) using incomplete genotype information in large outbreeding populations with complex pedigrees. The method accounts for background genes by estimating polygenic effects. The basic equations used are very similar to the usual linear mixed model equations for polygenic models, and segregation analysis was used to estimate the probabilities of the QTL genotypes for each animal. Method R was used to estimate the polygenic heritability simultaneously with the QTL effects. Also, initial allele frequencies were estimated. The method was tested in a simulated data set of 10,000 animals evenly distributed over 10 generations, where 0, 400 or 10,000 animals were genotyped for a candidate gene. In the absence of selection, the bias of the QTL estimates was < 2%. Selection biased the estimate of the Aa genotype slightly, when zero animals were genotyped. Estimates of the polygenic heritability were 0.251 and 0.257, in absence and presence of selection, respectively, while the simulated value was 0.25. Although not tested in this study, marker information could be accommodated by adjusting the transmission probabilities of the genotypes from parent to offspring according to the marker information. This renders a QTL mapping study in large multi-generation pedigrees possible.

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.

Evidence for individual and between-family variability of the recombination rate in cattle

We have conducted a study based on single sperm typing in a family design to assess patterns of variability of the male recombination rate in cattle. 2214 sperm of 37 bulls were typed for 11 loci on bovine Chromosomes (Chrs) 6, 23, and the sex chromosomes. Statistically significant individual variability of the recombination rate was observed for one interval in the pseudoautosomal region (PAR) of the bovine sex chromosomes; one marker interval on bovine Chr 23 exhibited individual variability that was close to significance. Thirty-five of the bulls were members of six paternal halfsib groups, and highly significant variability between families was found for one interval in the PAR. This variability may be due to DNA sequence differences in the PAR or to a genetic control of the recombination activity in this region. It is demonstrated that differences in the recombination rate of the magnitude observed in the present study may have a considerable impact on the power of QTL mapping experiments as well as on the sustainability of marker-assisted selection strategies.

Toward genetic dissection of high and low antibody responsiveness in Biozzi mice

Several distinct chromosomal segments were recently identified by cosegregation analysis of polymorphic markers with antibody responsiveness in an F2 cross between high (H) and low (L) antibody responder lines of Biozzi mice. The effect associated with the relevant markers has now been investigated in backcross populations (toward the L line) bred from H and L mice made coisogenic at the H-2 locus. The antibody titers, measured on days 5 and 14 of the primary response to sheep red blood cells, were considered to be two distinct quantitative phenotypes. The results of single or multilocus analyses demonstrated the significant involvement, at one or the two titration times, of Im gene(s) on four distinct chromosomes: 4, 8, 12, and 18. The regions on chromosomes 6 and 10 have a lesser but still suggestive effect. The contribution of each locus ranged from 3% to 13%, and together these loci accounted for about 40% of the phenotypic variance at each titration time. The data are compatible with an additive effect of the relevant loci and suggestive of some interaction effects. In a second backcross toward L line, the H line alleles of the putative Im genes on chromosomes 6, 8, and 12 were isolated from each other and their effects were still detected.

Quantitative trait loci analysis for five milk production traits on chromosome six in the Dutch Holstein-Friesian population

Twenty Dutch Holstein-Friesian families, with a total of 715 sires, were evaluated in a granddaughter experiment design for marker-QTL associations. Five traits-milk, fat and protein yield and fat and protein percent-were analyzed. Across-family analysis was undertaken using multimarker regression principles. One and two QTL models were fitted. Critical values for the test statistic were calculated empirically by permuting the data. Individual trait distributions of permuted test statistics differed and, thus distributions, had to be calculated for each trait. Experimentwise critical values, which account for evaluating marker-QTL associations on all 29 autosomal-bovine chromosomes and for five traits, were calculated. A QTL for protein percent was identified in one, and two QTL models and was significant at the 1 and 2% level, respectively. Extending the multimarker regression approach to an analysis including two QTL was limited by families not being informative at all markers, which resulted in singularity. Below average heterozygosity for the first and last marker lowered information content for the first and last marker bracket. Highly informative markers at the ends of the mapped chromosome would overcome the decrease in information content in the first and last marker bracket and singularity for the two QTL model.