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PubMed1992

The effects of selection on linkage analysis for quantitative traits.

The effects of within-sample selection on the outcome of analyses detecting linkage between genetic markers and quantitative traits were studied. It was found that selection by truncation for the trait of interest significantly reduces the differences between marker genotype means thus reducing the power to detect linked quantitative trait loci (QTL). The size of this reduction is a function of proportion selected, the magnitude of the QTL effect, recombination rate between the marker locus and the QTL, and the allele frequency of the QTL. Proportion selected was the most influential of these factors on bias, e.g., for an allele substitution effect of one standard deviation unit, selecting the top 80%, 50% or 20% of the population required 2, 6 or 24 times the number of progeny, respectively, to offset the loss of power caused by this selection. The effect on power was approximately linear with respect to the size of gene effect, almost invariant to recombination rate, and a complex function of QTL allele frequency. It was concluded that experimental samples from animal populations which have been subjected to even minor amounts of selection will be inefficient in yielding information on linkage between markers and loci influencing the quantitative trait under selection.

Animals↗
PubMed2006

Fine mapping reveals sex bias in quantitative trait loci affecting growth, skeletal size and obesity-related traits on mouse chromosomes 2 and 11.

Previous speed congenic analysis has suggested that the expression of growth and obesity quantitative trait loci (QTL) on distal mouse chromosomes (MMU) 2 and 11, segregating between the CAST/EiJ (CAST) and C57BL/6J-hg/hg (HG) strains, is dependent on sex. To confirm, fine map, and further evaluate QTL x sex interactions, we constructed congenic by recipient F2 crosses for the HG.CAST-(D2Mit329-D2Mit457)N(6) (HG2D) and HG.CAST-(D11Mit260-D11Mit255)N(6) (HG11) congenic strains. Over 700 F2 mice were densely genotyped and phenotyped for a panel of 40 body and organ weight, skeletal length, and obesity-related traits at 9 weeks of age. Linkage analysis revealed 20 QTL affecting a representative subset of phenotypes in HG2DF2 and HG11F2 mice. The effect of sex was quantified by comparing two linear models: the first model included sex as an additive covariate and the second incorporated sex as an additive and an interactive covariate. Of the 20 QTL, 8 were sex biased, sex specific, or sex antagonistic. Most traits were regulated by single QTL; however, two closely linked loci were identified for five traits in HG2DF2 mice. Additionally, the confidence intervals for most QTL were significantly reduced relative to the original mapping results, setting the stage for quantitative trait gene (QTG) discovery. These results highlight the importance of assessing the contribution of sex in complex trait analyses.

Animals↗
PubMed1999

Whole genome scan in chickens for quantitative trait loci affecting carcass traits.

An experiment was conducted to enable quantitative trait loci (QTL) mapping for carcass traits. The population consisted of 10 full-sib families originating from a cross between male and female founders chosen from two different outcross broiler lines. Founder animals, parents, offspring, and grandoffspring are denoted as generation (G) 0, 1, 2, and 3 animals, respectively. Microsatellite marker genotypes were collected on G1 and G2 animals. Phenotypic observations were collected on G3 animals. Recorded traits were BW at 48 d, carcass weight, carcass percentage, breast meat color, and leg score. Average adjusted progeny trait values were calculated for each G2 animal and for each trait after adjusting phenotypic observations on G3 animals for fixed effects, covariables, the additive genetic contribution of the other parent, and differences between sexes. The average adjusted progeny trait values were used as the dependent variable in the QTL analysis. A QTL analysis was undertaken by modeling the segregation from G1 to G2, using a full-sib across family regression interval mapping approach. In total, 27 autosomal linkage groups covered with 420 markers were analyzed. Genomewise significance thresholds were derived using the permutation test and a Bonferroni correction. Two QTL, affecting two of the five analyzed traits, exceeded suggestive linkage. The most significant QTL was located on Chromosome 1 at 466 cM and showed an effect on carcass percentage. The other QTL, which affected meat color, was located on Chromosome 2 and gave a peak at 345 and 369 cM.

Animals↗
PubMed2006

Virulence attributes and hyphal growth of C. neoformans are quantitative traits and the MATalpha allele enhances filamentation.

Cryptococcus neoformans is a fungal human pathogen with a bipolar mating system. It undergoes a dimorphic transition from a unicellular yeast to hyphal filamentous growth during mating and monokaryotic fruiting. The traditional sexual cycle that leads to the production of infectious basidiospores involves cells of both alpha and a mating type. Monokaryotic fruiting is a modified form of sexual reproduction that involves cells of the same mating type, most commonly alpha, which is the predominant mating type in both the environment and clinical isolates. However, some a isolates can also undergo monokaryotic fruiting. To determine whether mating type and other genetic loci contribute to the differences in fruiting observed between alpha and a cells, we applied quantitative trait loci (QTL) mapping to an inbred population of F2 progeny. We discovered that variation in hyphal length produced during fruiting is a quantitative trait resulting from the combined effects of multiple genetic loci, including the mating type (MAT) locus. Importantly, the alpha allele of the MAT locus enhanced hyphal growth compared with the a allele. Other virulence traits, including melanization and growth at 39 degrees C, also are quantitative traits that share a common QTL with hyphal growth. The Mac1 transcription factor, encoded in this common QTL, regulates copper homeostasis. MAC1 allelic differences contribute to phenotypic variation, and mac1Delta mutants exhibit defects in filamentation, melanin production, and high temperature growth. Further characterization of these QTL regions will reveal additional quantitative trait genes controlling biological processes central to fungal development and pathogenicity.

Alleles↗
PubMed2005

Modeling quantitative trait Loci and interpretation of models.

A quantitative genetic model relates the genotypic value of an individual to the alleles at the loci that contribute to the variation in a population in terms of additive, dominance, and epistatic effects. This partition of genetic effects is related to the partition of genetic variance. A number of models have been proposed to describe this relationship: some are based on the orthogonal partition of genetic variance in an equilibrium population. We compare a few representative models and discuss their utility and potential problems for analyzing quantitative trait loci (QTL) in a segregating population. An orthogonal model implies that estimates of the genetic effects are consistent in a full or reduced model in an equilibrium population and are directly related to the partition of the genetic variance in the population. Linkage disequilibrium does not affect the estimation of genetic effects in a full model, but would in a reduced model. Certainly linkage disequilibrium would complicate the detection of QTL and epistasis. Using different models does not influence the detection of QTL and epistasis. However, it does influence the estimation and interpretation of genetic effects.

Gene Frequency↗
PubMed1998

Mutation and conflicts between artificial and natural selection for quantitative traits.

There is substantial new variation for quantitative traits generated by mutation that can be utilised by artificial selection. With long-term selection, however, response is often attenuated and a selection limit sometimes reached, even though genetic variation is frequently still present in these lines. In this paper, the theoretical bases of long-term response and variability of populations that come from mutational variance are reviewed, and the relation between them is related to the strength and mode of the natural selection, whether due to pleiotropic effects of mutant genes or stabilising selection. Simple formulae to predict the consequence of relaxed or reversed selection are derived. Results from long-term selection experiments in mice in this laboratory are described and related to the theoretical analyses with the aim of reconciling the evidence for substantial standing variation with the low rate of response.

Animals↗
PubMed2000

Mapping quantitative trait loci in tetraploid populations.

Knowledge of quantitative trait locus (QTL) mapping in polyploids is almost void, albeit many exquisite strategies of QTL mapping have been proposed and extensive investigations have been carried out in diploid animals and plants. In this paper we develop a simple algorithm which uses an iteratively reweighted least square method to map QTLs in tetraploid populations. The method uses information from all markers in a linkage group to infer the probability distribution of QTL genotype under the assumption of random chromosome segregation. Unlike QTL mapping in diploid species, here we estimate and test the compound 'gametic effect', which consists of the composite 'genic effect' of alleles and higher-order gene interactions. The validity and efficiency of the proposed method are investigated through simulation studies. Results show that the method can successfully locate QTLs and separates different sources (e.g. additive and dominance) of variance components contributed by the QTLs.

Algorithms↗
PubMed1999

An experimental method for evaluating the contribution of deleterious mutations to quantitative trait variation.

Unconditionally deleterious mutations could be an important source of variation in quantitative traits. Deleterious mutations should be rare (segregating at low frequency in the population) and at least partially recessive. In this paper, I suggest that the contribution of rare, partially recessive alleles to quantitative trait variation can be assessed by comparing the relative magnitudes of two genetic variance components: the covariance of additive and homozygous dominance effects (Cad) and the additive genetic variance (Va). If genetic variation is due to rare recessives, then the ratio of Cad to Va should be equal to or greater than 1. In contrast, Cad/Va should be close to zero or even negative if variation is caused by alleles at intermediate frequencies. The ratio of Cad to Va can be estimated from phenotypic comparisons between inbred and outbred relatives, but such estimates are likely to be highly imprecise. Selection experiments provide an alternative estimator for Cad/Va, one with favourable statistical properties. When combined with other biometrical analyses, the ratio test can provide an incisive test of the deleterious mutation model.

Genetic Variation↗
PubMed2005

Survival analysis of life span quantitative trait loci in Drosophila melanogaster.

We used quantitative trait loci (QTL) mapping to evaluate the age specificity of naturally segregating alleles affecting life span. Estimates of age-specific mortality rates were obtained from observing 51,778 mated males and females from a panel of 144 recombinant inbred lines (RILs). Twenty-five QTL were found, having 80 significant effects on life span and weekly mortality rates. Generation of RILs from heterozygous parents enabled us to contrast effects of QTL alleles with the means of RIL populations. Most of the low-frequency alleles increased mortality, especially at younger ages. Two QTL had negatively correlated effects on mortality at different ages, while the remainder were positively correlated. Chromosomal positions of QTL were roughly concordant with estimates from other mapping populations. Our findings are broadly consistent with a mix of transient deleterious mutations and a few polymorphisms maintained by balancing selection, which together contribute to standing genetic variation in life span.

Alleles↗
PubMed2002

Powerful regression-based quantitative-trait linkage analysis of general pedigrees.

We present a new method of quantitative-trait linkage analysis that combines the simplicity and robustness of regression-based methods and the generality and greater power of variance-components models. The new method is based on a regression of estimated identity-by-descent (IBD) sharing between relative pairs on the squared sums and squared differences of trait values of the relative pairs. The method is applicable to pedigrees of arbitrary structure and to pedigrees selected on the basis of trait value, provided that population parameters of the trait distribution can be correctly specified. Ambiguous IBD sharing (due to incomplete marker information) can be accommodated in the method by appropriate specification of the variance-covariance matrix of IBD sharing between relative pairs. We have implemented this regression-based method and have performed simulation studies to assess, under a range of conditions, estimation accuracy, type I error rate, and power. For normally distributed traits and in large samples, the method is found to give the correct type I error rate and an unbiased estimate of the proportion of trait variance accounted for by the additive effects of the locus-although, in cases where asymptotic theory is doubtful, significance levels should be checked by simulations. In large sibships, the new method is slightly more powerful than variance-components models. The proposed method provides a practical and powerful tool for the linkage analysis of quantitative traits.

Chromosome Mapping↗
PubMedDate not supplied

Quantitative trait loci influencing honeybee alarm pheromone levels.

Quantitative trait loci (QTL) mapping procedures were used to identify loci that influence the levels of alarm pheromones found in the stinging apparatus of worker honeybees. 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 European queens to produce 172 colonies. Samples of stings were taken from backcross workers of these colonies. Alarm pheromone levels were determined by gas chromatography. RAPD markers were scored from the haploid drone fathers of these colonies. The multiple-QTL model (MQM) of MapQTL was used to identify QTLs that influence the levels of four alarm pheromone components. Seven independent, potential QTLs were identified with LOD scores greater than two, and one at LOD 1.88. We identified one QTL for n-decyl acetate, three for n-octanol, four for isopentyl acetate, and one for hexyl acetate. One region of linkage group XI shows a strong influence on body size and the levels of three alarm pheromone components. This locus explained 40% of the variance for the amount of n-decyl acetate (LOD 6.57). In general, the QTLs influencing alarm pheromone levels were independent of previously identified loci that influenced the stinging behavior of these colonies. The only exception was a potential locus influencing levels of n-octanol, which was inversely correlated with stinging behavior.

1-Octanol↗
PubMed2004

Quantitative trait loci affecting starvation resistance in Drosophila melanogaster.

The ability to withstand periods of scarce food resources is an important fitness trait. Starvation resistance is a quantitative trait controlled by multiple interacting genes and exhibits considerable genetic variation in natural populations. This genetic variation could be maintained in the face of strong selection due to a trade-off in resource allocation between reproductive activity and individual survival. Knowledge of the genes affecting starvation tolerance and the subset of genes that affect variation in starvation resistance in natural populations would enable us to evaluate this hypothesis from a quantitative genetic perspective. We screened 933 co-isogenic P-element insertion lines to identify candidate genes affecting starvation tolerance. A total of 383 P-element insertions induced highly significant and often sex-specific mutational variance in starvation resistance. We also used deficiency complementation mapping followed by complementation to mutations to identify 12 genes contributing to variation in starvation resistance between two wild-type strains. The genes we identified are involved in oogenesis, metabolism, and feeding behaviors, indicating a possible link to reproduction and survival. However, we also found genes with cell fate specification and cell proliferation phenotypes, which implies that resource allocation during development and at the cellular level may also influence the phenotypic response to starvation.

Analysis of Variance↗
PubMedDate not supplied

Extreme selection strategies in gene mapping studies of oligogenic quantitative traits do not always increase power.

It is well known that obtaining adequate statistical power to detect linkage to or association with genes for complex quantitative traits can be very difficult. In response, investigators have developed a number of power-enhancing strategies that consider restraints such as genotyping (and/or phenotyping) costs. In the context of both association and sib pair linkage studies of quantitative traits, one of the most widely discussed techniques is the selective sampling of phenotypically extreme individuals. Several papers have demonstrated that such extreme sampling can markedly increase power (under certain circumstances). However, the parenthetical phrase in the previous sentence has generally not been made explicit and it appears to be implied that the more phenotypically extreme the individuals, the more power one has. In this paper, we show by simulation that this is not true under all circumstances. In particular, we show that under oligogenic models, where some biallelic quantitative trait loci (QTLs) have markedly asymmetric allele frequencies and large mean displacement among genotypes, and others have less asymmetric allele frequencies and smaller mean displacement among genotypes, power to detect linkage to or association with the latter QTL can actually decrease by sampling more extreme sib pairs. This suggests that more extreme sampling is not always better. The 'optimal' sampling scheme may depend on both what one suspects the underlying genetic architecture to be and which of the oligogenic QTL one has greatest interest in detecting.

Chromosome Mapping↗
PubMed1990

Power of daughter and granddaughter designs for determining linkage between marker loci and quantitative trait loci in dairy cattle.

There is considerable interest in bovine DNA-level polymorphic marker loci as a means of mapping quantitative trait loci (QTL) of economic importance in cattle. Progeny of a sire heterozygous for both a marker locus and a linked QTL, which inherit different alleles for the marker, will have different trait means. Based on this, power to detect QTL, as a function of QTL effect, heritability of the trait, and number of animals tested was determined for 1) daughter design, marker genotype and quantitative trait values assessed on daughters of sires heterozygous for the markers; and 2) granddaughter design, a newly devised alternative design in which marker genotype is determined on sons of heterozygous sires and quantitative trait value measured on daughters of the sons. For equal numbers of assays, power increased with the number of daughters per sire (design 1) and sons per grandsire (design 2). For equal power and heritability less than or equal to .2, design 2 required half as many marker assays as design 1, e.g., with heritability of .2, QTL effect of .2 SD units, and type 1 error of .01, power was .70 if 400 daughters of each of 10 sires were assayed for the markers and .95 if markers were assayed on 100 sons of each of 20 sires with 50 granddaughters per son.

Alleles↗
PubMed2006

Locus-specific heritability estimation via the bootstrap in linkage scans for quantitative trait loci.

BACKGROUND/AIMS: In genome-wide linkage analysis of quantitative trait loci (QTL), locus-specific heritability estimates are biased when the original data are used to both localize linkage and estimate effects, due to maximization of the LOD score over the genome. Positive bias is increased by adoption of stringent significance levels to control genome-wide type I error. We propose multi-locus bootstrap resampling estimators for bias reduction in the situation in which linkage peaks at more than one QTL are of interest. METHODS: Bootstrap estimates were based on repeated sample splitting in the original dataset. We conducted simulation studies in nuclear families with 0 to 5 QTLs and applied the methods in a genome-wide analysis of a blood pressure phenotype in extended pedigrees from the Framingham Heart Study (FHS). RESULTS: Compared to naïve estimates in the original simulation samples, bootstrap estimates had reduced bias and smaller mean squared error. In the FHS pedigrees, the bootstrap yielded heritability estimates as much as 70% smaller than in the original sample. CONCLUSIONS: Because effect estimates obtained in an initial study are typically inflated relative to those expected in an independent replication study, successful replication will be more likely when sample size requirements are based on bias-reduced estimates.

Cardiovascular Diseases↗
PubMed2002

In silico discovery of gene-coding variants in murine quantitative trait loci using strain-specific genome sequence databases.

BACKGROUND: The identification of genes underlying complex traits has been aided by quantitative trait locus (QTL) mapping approaches, which in turn have benefited from advances in mammalian genome research. Most recently, whole-genome draft sequences and assemblies have been generated for mouse strains that have been used for a large fraction of QTL mapping studies. Here we show how such strain-specific mouse genome sequence databases can be used as part of a high-throughput pipeline for the in silico discovery of gene-coding variations within murine QTLs. As a test of this approach we focused on two QTLs on mouse chromosomes 1 and 13 that are involved in physical dependence on alcohol. RESULTS: Interstrain alignment of sequences derived from the relevant mouse strain genome sequence databases for 199 QTL-localized genes spanning 210,020 base-pairs of coding sequence identified 21 genes with different coding sequences for the progenitor strains. Several of these genes, including four that exhibit strong phenotypic links to chronic alcohol withdrawal, are promising candidates to underlie these QTLs. CONCLUSIONS: This approach has wide general utility, and should be applicable to any of the several hundred mouse QTLs, encompassing over 60 different complex traits, that have been identified using strains for which relatively complete genome sequences are available.

Alcohol Withdrawal Seizures↗
PubMedDate not supplied

Characterization of a major X-linked quantitative trait locus influencing body weight of mice.

Growth rate in mice is an archetypal quantitative trait that has long been studied genetically, physiologically, and metabolically, but its genetic basis is still poorly understood due to its complex inheritance and the influence of environment. We measured differences in 17 growth-related traits between a pair of partially congenic lines that differ for a segment of the X chromosome containing a quantitative trait locus (QTL) that we identified in a genomewide QTL scan. The QTL has a large effect on mean body weight of approximately 20% at all ages, and affects early growth rate to a greater extent than late growth rate. Feed is converted to body mass more efficiently in the high chromosome segment-bearing line than the low line. The weights of various internal organs are affected to a somewhat greater extent by the QTL than body weight. The proportional change in body length is smaller than body weight, but this may be an effect of scale. Body weight at late ages appears to allow the most efficient detection of allelic differences at the QTL, although assignment of genotypic state based on phenotype is never unambiguous.

Animals↗
PubMed2006

Replication of small effect quantitative trait loci for behavioral traits facilitated by estimation of effect size from independent cohorts.

Quantitative trait locus (QTL) mapping is often done in a single segregating population, such as a backcross or an intercross. Both QTL location and effect size are then estimated from the same dataset. This approach results in an over-estimate of effect size for two reasons: (1) LOD scores, which are maximized over numerous point-wise tests, are correlated with estimated effect size and (2) small effect QTLs are often undetected in underpowered experiments, yielding inflated effect sizes for detected QTLs (the Beavis effect). When it is impractical to maintain or generate large population sizes, an alternative is to use two populations, one for initial detection and localization and a second for a locus-matched estimate of effect size, not conditioned on significance. Recombinant inbred (RI) panels are eminently suitable for this approach, as each strain genotype can be sampled repeatedly. We present mapping results from the LXS RI panel for two behavioral phenotypes relating to ethanol response: low-dose ethanol activation and loss of righting following high-dose injection. Both the phenotypes were measured in two or three independent cohorts, which were then used to re-estimate effect size. Many small-effect QTLs replicated using this approach, but in all cases, effect size, in the replicate cohorts, was reduced from the initial estimate, often substantially. Such a reduction will have important consequences for power analyses in which sample sizes are determined for subsequent confirmation studies.

Alcoholism↗