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PubMed1995

The contribution of quantitative trait loci and neutral marker loci to the genetic variances and covariances among quantitative traits in random mating populations.

Using Cockerham's approach of orthogonal scales, we develop genetic models for the effect of an arbitrary number of multiallelic quantitative trait loci (QTLs) or neutral marker loci (NMLs) upon any number of quantitative traits. These models allow the unbiased estimation of the contributions of a set of marker loci to the additive and dominance variances and covariances among traits in a random mating population. The method has been applied to an analysis of allozyme and quantitative data from the European oyster. The contribution of a set marker loci may either be real, when the markers are actually QTLs, or apparent, when they are NMLs that are in linkage disequilibrium with hidden QTLs. Our results show that the additive and dominance variances contributed by a set of NMLs are always minimum estimates of the corresponding variances contributed by the associated QTLs. In contrast, the apparent contribution of the NMLs to the additive and dominance covariances between two traits may be larger than, equal to or lower than the actual contributions of the QTLs. We also derive an expression for the expected variance explained by the correlation between a quantitative trait and multilocus heterozygosity. This correlation explains only a part of the genetic variance contributed by the markers, i.e., in general, a combination of additive and dominance variances and, thus, provides only very limited information relative to the method supplied here.

Alleles↗
PubMed2000

Power of selective genotyping in genetic association analyses of quantitative traits.

A power calculation is described in which the power of selective genotyping in genetic association studies of quantitative traits is evaluated. The method of selective genotyping implies the selection of the extremely high and low scoring individuals from the continuous distribution of a quantitative trait. The selected individuals are genotyped and association is tested. In the power calculation the following parameters are varied: total sample size of the phenotyped group (1000, 1500, 2000); selection of extremely high and low scoring individuals (2.5%, 5%, 10%); allele frequency of the risk increasing allele (0.10 to 0.90); mode of inheritance and proportion of variance explained by the quantitative trait locus (QTL) (omega 2 = 0.01, 0.05, 0.10). We conclude that the method of selective genotyping is a powerful method to detect association for a quantitative trait.

Chromosome Mapping↗
PubMed1997

[Identification of major gene and polygene mixed inheritance model and estimation of genetic parameters of a quantitative trait from F2 progeny].

It has been proved by many field experiments and QTL mapping results that among genes affecting some quantitative traits there are some major genes with larger genetic effect and some polygenes with smaller genetic effect. For such traits, the distribution of segregating population demonstrates multimodality, and this is the characteristic of the mixture of more than one distributions. Mixture distribution models have been used extensively as models in a wide variety of practical situations where data can be viewed as arising from two or more populations mixed in certain proportions. Akaike's Information Criterion(AIC) has been used to identify the existence of major genes affecting quantitative traits. Under the existence of major genes, the genetic effects of these genes and their genetic variance were estimated through segregation analysis. The genotype of major gene of F2 individuals of were determined by clustering using Bayesian criterion. With P1, P2, F1 and F2 populations, the likelihood ratio test was used to test the existence of polygenes. In the end, the inheritance of soybean flowering date is analyzed. One major gene was found in F2 population derived from Guludou x Shanghaihongmangzao.

Models, Genetic↗
PubMed2006

From genetical genomics to systems genetics: potential applications in quantitative genomics and animal breeding.

This article reviews methods of integration of transcriptomics (and equally proteomics and metabolomics), genetics, and genomics in the form of systems genetics into existing genome analyses and their potential use in animal breeding and quantitative genomic modeling of complex traits. Genetical genomics or the expression quantitative trait loci (eQTL) mapping method and key findings in this research are reviewed. Various procedures and potential uses of eQTL mapping, global linkage clustering, and systems genetics are illustrated using actual analysis on recombinant inbred lines of mice with data on gene expression (for diabetes- and obesity-related genes), pathway, and single nucleotide polymorphism (SNP) linkage maps. Experimental and bioinformatics difficulties and possible solutions are discussed. The main uses of this systems genetics approach in quantitative genomics were shown to be in refinement of the identified QTL, candidate gene and SNP discovery, understanding gene-environment and gene-gene interactions, detection of candidate regulator genes/eQTL, discriminating multiple QTL/eQTL, and detection of pleiotropic QTL/eQTL, in addition to its use in reconstructing regulatory networks. The potential uses in animal breeding are direct selection on heritable gene expression measures, termed "expression assisted selection," and genetical genomic selection of both QTL and eQTL based on breeding values of the respective genes, termed "expression-assisted evaluation."

Animals↗
PubMed2006

Multilocus genetics and the coevolution of quantitative traits.

We develop and analyze an explicit multilocus genetic model of coevolution. We assume that interactions between two species (mutualists, competitors, or victim and exploiter) are mediated by a pair of additive quantitative traits that are also subject to direct stabilizing selection toward intermediate optima. Using a weak-selection approximation, we derive analytical results for a symmetric case with equal locus effects and no mutation, and we complement these results by numerical simulations of more general cases. We show that mutualistic and competitive interactions always result in coevolution toward a stable equilibrium with no more than one polymorphic locus per species. Victim-exploiter interactions can lead to different dynamic regimes including evolution toward stable equilibria, cycles, and chaos. At equilibrium, the victim is often characterized by a very large genetic variance, whereas the exploiter is polymorphic in no more than one locus. Compared to related one-locus or quantitative genetic models, the multilocus model exhibits two major new properties. First, the equilibrium structure is considerably more complex. We derive detailed conditions for the existence and stability of various classes of equilibria and demonstrate the possibility of multiple simultaneously stable states. Second, the genetic variances change dynamically, which in turn significantly affects the dynamics of the mean trait values. In particular, the dynamics tend to be destabilized by an increase in the number of loci.

Biological Evolution↗
PubMed1995

A nonparametric approach for mapping quantitative trait loci.

Genetic mapping of quantitative trait loci (QTLs) is performed typically by using a parametric approach, based on the assumption that the phenotype follows a normal distribution. Many traits of interest, however, are not normally distributed. In this paper, we present a nonparametric approach to QTL mapping applicable to any phenotypic distribution. The method is based on a statistic ZW, which generalizes the nonparametric Wilcoxon rank-sum test to the situation of whole-genome search by interval mapping. We determine the appropriate significance level for the statistic ZW, by showing that its asymptotic null distribution follows an Ornstein-Uhlenbeck process. These results provide a robust, distribution-free method for mapping QTLs.

Animals↗
PubMed2000

A population genetics model for multiple quantitative traits exhibiting pleiotropy and epistasis.

We study a population genetics model of an organism with a genome of L(tot)loci that determine the values of T quantitative traits. Each trait is controlled by a subset of L loci assigned randomly from the genome. There is an optimum value for each trait, and stabilizing selection acts on the phenotype as a whole to maintain actual trait values close to their optima. The model contains pleiotropic effects (loci can affect more than one trait) and epistasis in fitness. We use adaptive walk simulations to find high-fitness genotypes and to study the way these genotypes are distributed in sequence space. We then simulate the evolution of haploid and diploid populations on these fitness landscapes and show that the genotypes of populations are able to drift through sequence space despite stabilizing selection on the phenotype. We study the way the rate of drift and the extent of the accessible region of sequence space is affected by mutation rate, selection strength, population size, recombination rate, and the parameters L and T that control the landscape shape. There are three regimes of the model. If LT< >L(tot), there are many small peaks that can be spread over a wide region of sequence space. Compensatory neutral mutations are important in the population dynamics in this case.

Animals↗
PubMed2005

High-throughput double quantitative competitive polymerase chain reaction for determination of genetically modified organisms.

Quantitative competitive polymerase chain reaction (PCR), especially the double competitive PCR methods (DC-PCR), have evolved as reliable approaches to quantification of genetically modified organisms (GMO) in food. However, DC-PCR is a low-throughput method because it requires titration of each sample with various amounts of a competitive internal standard, a protocol that involves several PCRs per sample followed by electrophoresis and densitometry. To address this drawback, we have developed a new method for GMO quantification, namely, a high-throughput double quantitative competitive PCR (HT-DCPCR). In HT-DCPCR, electrophoresis and densitometry are replaced by a rapid, microtiter well-based bioluminometric hybridization assay and there is no need for titration of each sample. The determination of GM soya was chosen as a model. We have constructed internal standards (DNA competitors) both for the 35S promoter sequence and for a plant-specific reference gene (lectin). The competitors have identical size and share the same primer binding sites with the target sequences but differ in a 24-bp internal segment. Each target sequence (35S and lectin) is coamplified with a constant amount (1000 copies) of the respective competitor. The four amplified fragments are hybridized with specific probes and captured on a universal solid phase to achieve simplicity and high throughput. The hybrids are determined by using streptavidin conjugated to the photoprotein aequorin. The ratio of the luminescence values obtained for the target and the competitor is linearly related to the starting amount of target DNA. The limit of quantification for the 35S promoter is 24 copies. The proposed method was evaluated by determining the GMO content of soybean powder certified reference materials. Also HT-DCPCR was compared to real-time PCR in a variety of real samples.

Calibration↗
PubMed1996

Genetic markers linked to quantitative traits in poultry.

This study utilized DNA fingerprints and crosses of two genetically distinct lines of layer-type chickens to identify genetic markers linked to quantitative trait loci (QTL). In phase I, backcross (BC1) hens were separately ranked for each of eight traits and then blood pools were produced in groups along each phenotypic distribution. The DNA was isolated from the blood pools and used in a gradient analysis to screen for DNA fingerprint bands that exhibited intensity gradients associated with the phenotypic traits. To identify linkage of bands with QTL and to estimate band effects, F2 progeny were produced in phase II from the phase I BC1 population. A single-trait animal model was used for analysis of associations of all individual DNA fingerprint bands of sires and their progeny phenotypic performance. Twenty fingerprint bands, only two of which had shown trait-associated gradients in phase I, were identified by the animal model analysis of the progeny test as QTL linked (P < or = 0.05) to specific traits of growth, reproduction and egg quality. These 20 bands warrant further study as potentially valuable molecular markers for QTL.

Animals↗
PubMed2002

Psychiatric genetics: the case of single gene disorders.

Quantitative and molecular genetics have made important developments in the last three decades. There is increasing evidence of the role of heredity in the field of neuropsychiatric disorders in children. So far, only a few pathways between genes and behaviour have been unravelled. Quantitative genetics puts polygenic inheritance models forward. Molecular genetic research based on these models seems promising, but until now has provided only a limited explanation for the variance in the studied neuropsychiatric disorders. In these models the complexity of the expression of a single gene grows exponentially with the number of genes involved. Consequently, research on the gene-phenotype relationships and phenotypical variability in such models is extremely complex.The candidate gene approach, in which the gene-phenotype pathway of a single gene is studied, is more manageable, and in our opinion essential in understanding multiple gene models. We discuss recent findings in the field and their relevance for neuropsychiatric phenotypes. Single gene defects will only explain a part of the range of neuropsychiatric disorders in children, but the evidence that this approach can generate may help to clarify neuropsychiatric phenotypes. The discovery of single gene disorders in subgroups of subjects with a neuropsychiatric phenotype may result in new perspectives for their treatment.

Autistic Disorder↗
PubMed1999

Neutral additive genetic variance in a metapopulation.

For neutral, additive quantitative characters, the amount of additive genetic variance within and among populations is predictable from Wright's FST, the effective population size and the mutational variance. The structure of quantitative genetic variance in a subdivided metapopulation can be predicted from results from coalescent theory, thereby allowing single-locus results to predict quantitative genetic processes. The expected total amount of additive genetic variance in a metapopulation of diploid individual is given by 2Ne sigma m2 (1 + FST), where FST is Wright's among-population fixation index, Ne is the eigenvalue effective size of the metapopulation, and sigma m2 is the mutational variance. The expected additive genetic variance within populations is given by 2Ne sigma e2(1-FST), and the variance among demes is given by 4FSTNe sigma m2. These results are general with respect to the types of population structure involved. Furthermore, the dimensionless measure of the quantitative genetic variance among populations, QST, is shown to be generally equal to FST for the neutral additive model. Thus, for all population structures, a value of QST greater than FST for neutral loci is evidence for spatially divergent evolution by natural selection.

Animals↗
PubMed1984

The immune response in sheep: analysis of age, sex and genetic effects on the quantitative antibody response to chicken red blood cells.

The purpose of the present work was to investigate the influence of age, sex and genetic factors on the quantitative antibody response of sheep, when environmental conditions were kept under strict control. Data provided by this experiment show that sheep of 3 months old are capable of developing a measureable response to a single intravenous injection of chicken red blood cells, but the average level of haemagglutinins produced by young lambs is significantly lower than that found in adults (2 to 5 years old) of the same sex (p less than 0.001). At 7 to 8 months of age, the antibody response observed in lambs reached the adult level. There is also a tendency for a better response in females than in males, but the observed difference is small (0.6 log2) and statistically not significant. Heritability estimates clearly indicate a genetic influence on the quantitative antibody response of sheep to chicken red blood cells.

Age Factors↗
PubMed1987

Estimation of genetical parameters for a quantitative trait subject to major gene influences.

Both regression and correlation estimates of genetical variance and heritability for a quantitative trait influenced by a major gene can be obtained from the error variance-covariance matrix of MANOVA using relative-relative phenotype pairs as factors. The method is illustrated with parent-offspring data on red cell acid phosphatase phenotypes and serum acid phosphatase activity.

Acid Phosphatase↗
PubMed1998

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.

Chromosome Mapping↗
PubMed1987

Plant genetic resources: prediction by isozyme markers and ecology.

Linkage or association of genetic markers to quantitative traits of agronomic importance can substantially simplify the genetic analysis of complex quantitative traits. Enzyme marker genes are ideal candidates for quantitative genetic analysis. We have recently applied this powerful methodology to the analysis of genetic resources of wild cereals in Israel, primarily wild emmer wheat, Triticum dicoccoides, and wild barley, Hordeum spontaneum, the progenitors of cultivated wheats and barley, respectively. We have found that allelic isozyme markers and ecological factors provide an important predictive method for identifying elite genotypes characterized by single or multiple disease resistances, high protein content, and a variety of quantitative traits of agronomic importance including germination, earliness, biomass, and yield variables. Our predictive methodology could be improved by additional crossing tests in an attempt to verify the results derived from the correlation analysis and thus establish the linkage relationships between the marker gene and the quantitative trait under discussion. This methodology, if further developed by additional isozyme and DNA markers, verified by crossing tests and gene mapping, could substantially contribute to the sampling and utilization of the genetic resources of wild gene pools for crop improvement.

Agriculture↗
PubMed2002

Effect of low stressful temperature on genetic variation of five quantitative traits in Drosophila melanogaster.

A half-sib analysis was used to investigate genetic variation for three morphological traits (thorax length, wing length and sternopleural bristle number) and two life-history traits (developmental time and larva-to-adult viability) in Drosophila melanogaster reared at a standard (25 degrees C) and a low stressful (13 degrees C) temperature. Both phenotypic and environmental variation showed a significant increase under stressful conditions in all traits. For estimates of genetic variation, no statistically significant differences were found between the two environments. Narrow heritabilities tended to be higher at 13 degrees C for sternopleural bristle number and viability and at 25 degrees C for wing length and developmental time, whereas thorax length did not show any trend. However, the pattern of genetic variances and evolvability indices (coefficient of genetic variation and evolvability), considered in the context of literature evidence, indicated the possibility of an increase in additive genetic variation for the morphological traits and viability and in nonadditive genetic variation for developmental time. The data suggest that the effect of stressful temperature may be trait-specific and this warns against generalizations about the behaviour of genetic variation under extreme conditions.

Analysis of Variance↗
PubMed2003

Nonparametric longitudinal allele-sharing model.

Basically no methods are available for the analysis of quantitative traits in longitudinal genetic epidemiological studies. We introduce a nonparametric factorial design for longitudinal data on independent sib pairs, modelling the phenotypic quadratic differences as the dependent variable. Factors are the number of alleles shared identically by descent (IBD) and the age categories at which the dependent variable is measured, allowing for dependence due to age. To identify a linked marker a rank statistic tests the influence of IBD group on phenotypic quadratic differences. No assumptions are made on normality or variances of the dependent variable. We apply our method to 71 sib pairs from the Framingham Heart Study data provided at the Genetic Analysis Workshop 13. For all 15 available markers on chromosome 17 we analyzed the influence on systolic blood pressure. In addition, different selection strategies to sample from the whole data are discussed.

Adult↗