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PubMed2001

Assessment of parent-of-origin effects in linkage analysis of quantitative traits.

Methods are presented for incorporation of parent-of-origin effects into linkage analysis of quantitative traits. The estimated proportion of marker alleles shared identical by descent is first partitioned into a component derived from the mother and a component derived from the father. These parent-specific estimates of allele sharing are used in variance-components or Haseman-Elston methods of linkage analysis so that the effect of the quantitative-trait locus carried on the maternally derived chromosome is potentially different from the effect of the locus on the paternally derived chromosome. Statistics for linkage between trait and marker loci derived from either or both parents are then calculated, as are statistics for testing whether the effect of the maternally derived locus is equal to that of the paternally derived locus. Analyses of data simulated for 956 siblings from 263 nuclear families who had participated in a linkage study revealed that type I error rates for these statistics were generally similar to nominal values. Power to detect an imprinted locus was substantially increased when analyzed with a model allowing for parent-of-origin effects, compared with analyses that assumed equal effects; for example, for an imprinted locus accounting for 30% of the phenotypic variance, the expected LOD score was 4.5 when parent-of-origin effects were incorporated into the analysis, compared with 3.1 when these effects were ignored. The ability to include parent-of-origin effects within linkage analysis of quantitative traits will facilitate genetic dissection of complex traits.

Alleles↗
PubMed2003

Combining quantitative trait Loci analysis and an ecophysiological model to analyze the genetic variability of the responses of maize leaf growth to temperature and water deficit.

Ecophysiological models predict quantitative traits of one genotype in any environment, whereas quantitative trait locus (QTL) models predict the contribution of alleles to quantitative traits under a limited number of environments. We have combined both approaches by dissecting into effects of QTLs the parameters of a model of maize (Zea mays) leaf elongation rate (LER; H. Ben Haj Salah, F. Tardieu [1997] Plant Physiol 114: 893-900). Response curves of LER to meristem temperature, water vapor pressure difference, and soil water status were established in 100 recombinant inbred lines (RILs) of maize in six experiments carried out in the field or in the greenhouse. All responses were linear and common to different experiments, consistent with the model. A QTL analysis was carried out on the slopes of these responses by composite interval mapping confirmed by bootstrap analysis. Most QTLs were specific of one response only. QTLs of abscisic acid concentration in the xylem sap colocalized with QTLs of response to soil water deficit and conferred a low response. Each parameter of the ecophysiological model was computed as the sum of QTL effects, allowing calculation of parameters for 11 new RILs and two parental lines. LERs were simulated and compared with measurements in a growth chamber experiment. The combined model accounted for 74% of the variability of LER, suggesting that it has a general value for any RIL under any environment.

Abscisic Acid↗
PubMed2006

Models and partition of variance for quantitative trait loci with epistasis and linkage disequilibrium.

BACKGROUND: A genetic model about quantitative trait loci (QTL) provides a basis to interpret the genetic basis of quantitative traits in a study population, such as additive, dominance and epistatic effects of QTL and the partition of genetic variance. The standard quantitative genetics model is based on the least squares partition of genetic effects and also genetic variance in an equilibrium population. However, over years many specialized QTL models have also been proposed for applications in some specific populations. How are these models related? How to analyze and partition a QTL model and genetic variance when both epistasis and linkage disequilibrium are considered? RESULTS: Starting from the classical description of Cockerham genetic model, we first represent the model in a multiple regression setting by using indicator variables to describe the segregation of QTL alleles. In this setting, the definition of additive, dominance and epistatic effects of QTL and the basis for the partition of genetic variance are elaborated. We then build the connection between this general genetic model and a few specialized models (a haploid model, a diploid F2 model and a general two-allele model), and derive the genetic effects and partition of genetic variance for multiple QTL with epistasis and linkage disequilibrium for these specialized models. CONCLUSION: In this paper, we study extensively the composition and property of the genetic model parameters, such as genetic effects and partition of genetic variance, when both epistasis and linkage disequilibrium are considered. This is the first time that both epistasis and linkage disequilibrium are considered in modeling multiple QTL. This analysis would help us to understand the structure of genetic parameters and relationship of various genetic quantities, such as allelic frequencies and linkage disequilibrium, on the definition of genetic effects, and will also help us to understand and properly interpret estimates of the genetic effects and variance components in a QTL mapping experiment.

Algorithms↗
PubMed1995

Identification of a locus on mouse chromosome 17 associated with high-affinity choline uptake using BXD recombinant inbred mice and quantitative trait loci analysis.

Using the quantitative trait loci (QTL) approach, preliminary identification has been made of a region on mouse chromosome 17 that influences high-affinity choline uptake (HACU) in the mouse brain. The rate of HACU was measured in synaptosomes prepared from the frontal cortex, hippocampus, and striatum of C57BL/6J (B6), DBA/2J (D2), and 25 BXD recombinant inbred (RI) strains of mice, using a final concentration of 0.5 microM [3H]choline. The strain means of HACU in each area were then correlated with the strain distribution pattern of each of 1300 known genetic markers using a point biserial correlation and 0 (B6 allele) and 1 (D2 allele). Correlations of P < 0.00001 were found between striatal HACU and chromosome 17 markers D17Tu50 and Tcp1. Correlations of P < 0.0001 were found between striatal HACU and chromosome 17 markers D17Leh66e, D17Leh119, D17Rp17e, Plg, D17Leh66d, Ckb-rs2, and Trp53-ps. QTL analyses of HACU in the frontal cortex and hippocampus also revealed correlations with these markers at the level of P < 0.05 and P < 0.01. These data suggest that at least one locus located on mouse chromosome 17 near or between 6 and 13 cM from the centromere influences HACU in the striatum and possibly the frontal cortex and hippocampus of the mouse.

Animals↗
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↗
PubMed2004

Evidence for multiple alleles at the DGAT1 locus better explains a quantitative trait locus with major effect on milk fat content in cattle.

A quantitative trait locus (QTL) for milk fat percentage has been mapped consistently to the centromeric region of bovine chromosome 14 (BTA14). Two independent studies have identified the nonconservative mutation K232A in the acylCoA-diacylglycerol-acyltransferase 1 (DGAT1) gene as likely to be causal for the observed variation. Here we provide evidence for additional genetic variability at the same QTL that is associated with milk fat percentage variation within the German Holstein population. Namely, we show that alleles of the DGAT1 promoter derived from the variable number of tandem repeat (VNTR) polymorphism are associated with milk fat content in animals homozygous for the allele 232A at DGAT1. Our results present another example for more than two trait-associated alleles being involved in a major gene effect on a quantitative trait. The segregation of multiple alleles affecting milk production traits at the QTL on BTA14 has to be considered whenever marker-assisted selection programs are implemented in dairy cattle. Due to the presence of a potential transcription factor binding site in the 18mer element of the VNTR, the variation in the number of tandem repeats of the 18mer element might be causal for the variability in the transcription level of the DGAT1 gene.

Acyltransferases↗
PubMed1996

Quantitative trait loci in genetically hypertensive rats. Possible sex specificity.

We performed a total genome screen in an F2 cross derived from the stroke-prone spontaneously hypertensive rat and the normotensive Wistar-Kyoto rat. Blood pressure at baseline and after 1% NaCl was measured by radiotelemetry; other phenotypes included heart rate, motor activity, left ventricle weight to body weight ratio, and vascular smooth muscle cell polyploidy, a measure of vascular hypertrophy. Quantitative trait loci affecting a given phenotype were mapped relative to microsatellite markers by using the MAPMAKER/QTL 1.1 computer package. We identified three blood pressure quantitative trait loci, two on rat chromosome 2 and one on rat chromosome 3. The quantitative trait loci close to genetic markers D2Mgh12 ("suggestive" linkage, with a maximal logarithm of the odds [LOD] score of 3.1) and D3Mgh16 (significant linkage, with a maximal LOD score of 5.6) showed possible sex specificity in the male F2 cohort only. This was confirmed by the likelihood ratio test for the difference in locus effects between the sexes. We also identified a new quantitative trait locus for LV hypertrophy on rat chromosome 14 ("suggestive" linkage, with a maximal LOD score of 3.1). The sex specificity of blood pressure quantitative trait loci will be important in designing congenic strains and substrains for fine genetic mapping and for identifying genes that regulate blood pressure.

Animals↗
PubMed1988

Comparison of sequential and fixed-structure sampling of pedigrees in complex segregation analysis of a quantitative trait.

In designing a study to demonstrate the existence of a major locus for a quantitative trait, an investigator chooses a sampling rule to ascertain pedigrees. The choice of sampling rule can significantly affect the study's power. Here, we compare two types of sampling rules for family studies: fixed-structure rules, in which the same set of relatives are sampled for each proband, and sequential rules, in which the relative or relatives to be sampled next may depend on the trait values of the individuals already observed. We compare fixed-structure and sequential sampling in the setting of extended pedigrees, a quantitative trait, and the genetic mixed model. Using computer simulation, we show that sequential sampling can increase power to detect segregation at a dominant major locus by over 60% in comparison with fixed-structure sampling. Just as important, this substantially increased power is obtained with an easily implemented sampling rule, one that might reasonably be employed in a family study of a quantitative trait.

Alleles↗
PubMed2005

Interaction between two quantitative trait loci affects fetal haemoglobin expression.

The biological mechanisms controlling complex quantitative traits are likely to be affected by interactions between genetic factors, sometimes referred to as epistasis. The identification of interacting loci through genetic analyse faces many challenges, and few examples of replicated findings of interaction exist for humans and model system organisms. The replication of an interaction, or the non-independence, of two quantitative trait loci (QTL) affecting the developmental switch from the expression of fetal to adult haemoglobin is reported here. Fetal haemoglobin expression in adults is a highly heritable, yet complex, phenotype. Using a sample of 874 dizygotic twin pairs of European descent, we found linkage to a QTL on chromosome 8 to be conditional on the twin pairs' genotypes at a polymorphism in the beta-globin complex; an interaction originally identified in a large Asian Indian kindred. The beta-globin polymorphism has been previously shown to be associated with fetal haemoglobin levels in adults. This study reports the first known replication of a genetic interaction between QTLs influencing a complex human trait.

Chromosomes, Human, Pair 8↗
PubMed1990

Sample-size guidelines for linkage analysis of a dominant locus for a quantitative trait by the method of lod scores.

Sample-size guidelines for linkage studies of quantitative traits partially determined by a dominant major locus are needed to provide a rough estimate of the amount of pedigree material that should be sampled to map the loci that influence such traits. After pedigrees are sampled, a specific power calculation can be carried out to evaluate the linkage information provided by the sampled pedigrees. Using computer simulation, I provide sample-size guidelines for linkage studies by the method of lod scores of quantitative traits partially determined by a dominant major locus. I consider the effects of a trait model, marker characteristics, and sampling strategy, with particular attention to sampling strategy because it is the one factor which the investigator can fully control. My results suggest that linkage studies of quantitative traits are practical, particularly if the investigator chooses an efficient sampling design and an efficient strategy to select pedigrees for linkage analysis.

Female↗
PubMed2005

[Segregation analysis of genetic system of quantitative traits in plants].

Based on the traditional polygene inheritance model of quantitative traits, the mixed major gene and polygene inheritance model was raised and considered as the general model, while pure major gene or pure polygene inheritance model being only the specific case of the general model. From the proposed theory, the segregation analysis procedure was established for studying the genetic system of quantitative traits of plants. At present this procedure can be used to evaluate the genetic effects of individual major genes (up to 2-3 major genes) and the collective genetic effects of polygenes as well as their heritability values. The present paper introduces the process of the establishment of the procedure, main achievements and application results. An example was given to illustrate the steps, methods and effectiveness of the procedure.

Crosses, Genetic↗
PubMed2002

Score test for detecting linkage to quantitative traits.

The two most popular methods to detect linkage of a quantitative trait to a marker are the Haseman-Elston regression method and the variance components likelihood-ratio test. In the literature, these methods are frequently compared and the relative advantages and disadvantages of each method are well known. In this article, we derive a score test for the variance component attributable to a specific quantitative trait locus and show that for sib-pairs it is mathematically equivalent to a recently proposed version of the Haseman-Elston method that optimally combines the sum squared and the difference squared of the centered phenotype values of the sibs. Because score tests and likelihood-ratio tetsts are equivalent for large sample sizes, the variance components likelihood-ratio test is also asymptotically equivalent to this optimal Haseman-Elston test. This fact gives a theoretical explanation of the empirical observation from simulation studies reporting similar power of the variance components likelihood-ratio test and the optimal Haseman-Elston method. Perhaps more importantly for practical purposes, the score test can also be extended in a natural way to support the simultaneous analysis of more than two subjects and multivariate phenotypes.

Chromosome Mapping↗
PubMed1990

RFLP mapping in soybean: association between marker loci and variation in quantitative traits.

We have constructed a genetic map for soybean and identified associations between genetic markers and quantitative trait loci. One-hundred-fifty restriction fragment length polymorphisms (RFLPs) were used to identify genetic linkages in an F2 segregating population from an interspecific cross (Glycine max x Glycine soja). Twenty-six genetic linkage groups containing ca. 1200 recombination units are reported. Progeny-testing of F2-derived families allowed quantitative traits to be evaluated in replicated field trials. Genomic regions, which accounted for a portion of the genetic variation (R2 = 16 to 24%) in several reproductive and morphological traits, were linked to RFLP markers. Significant associations between RFLP markers and quantitative trait loci were detected for eight of nine traits evaluated. The ability to identify genes within a continuously varying trait has important consequences for plant breeding and for understanding evolutionary processes.

Chromosome Mapping↗
PubMed1997

Multilocus quantitative trait analysis using the multipoint identity-by-descent method.

The multipoint identity-by-descent method (MIM) was extended to test for evidence of quantitative trait loci in two independent genetic regions. This method is a fast and feasible implementation of a multiple-marker, two-region linkage analysis for quantitative traits. It tests for significant evidence of quantitative trait loci (QTL) in neither, one or both genetic regions tested, and could be extended to an arbitrary number of independent genetic regions. A two-stage analysis was used for the nuclear family data from GAW10. Initially, an analysis of the genomic search was carried out using single-region MIM, with sets of six adjacent markers. Chromosomal regions that showed some evidence of linkage were identified and used in a two-region MIM analysis.

Chromosome Mapping↗
PubMed2005

Quantitative trait analysis in the investigation of function and aging of hematopoietic stem cells.

Extensive genetically determined quantitative variation exists in the number and function of hematopoietic stem cells in inbred mouse strains. Furthermore, aging of hematopoietic stem cells is genetically determined. Gene identification of quantitative trait loci involved in the regulation and aging of hematopoietic stem cells would provide novel insights into regulatory mechanisms that are relevant in vivo and may be clinically important. Here we describe strategies for mapping and gene identification of quantitative trait loci applied to traits contributing to the regulation of hematopoietic stem cells.

Aging↗
PubMed2000

Quantitative trait locus mapping using human pedigrees.

In the past decade phenomenal progress has been made in molecular and statistical genetic methods for localizing quantitative trait loci. Because of these advances, we can anticipate a long period of active genetic research in which the genes influencing human quantitative variability will be mapped and their effects accurately evaluated. Here, we review the current state of the science in statistical genetic methods for quantitative trait linkage analysis. In particular, we detail a variance component-based framework for localizing quantitative trait loci and for accurately estimating their relative effect sizes. Attention is paid to the optimal design of human family studies for localizing genes of small to moderate effect. In addition, methods and strategies are described for dealing with the most important complications of quantitative variation, including the assessment of genotype x environment interaction and epistasis.

Bias↗
PubMed1999

Testing the robustness of the likelihood-ratio test in a variance-component quantitative-trait loci-mapping procedure.

Detection of linkage to genes for quantitative traits remains a challenging task. Recently, variance components (VC) techniques have emerged as among the more powerful of available methods. As often implemented, such techniques require assumptions about the phenotypic distribution. Usually, multivariate normality is assumed. However, several factors may lead to markedly nonnormal phenotypic data, including (a) the presence of a major gene (not necessarily linked to the markers under study), (b) some types of gene x environment interaction, (c) use of a dichotomous phenotype (i.e., affected vs. unaffected), (d) nonnormality of the population within-genotype (residual) distribution, and (e) selective (extreme) sampling. Using simulation, we have investigated, for sib-pair studies, the robustness of the likelihood-ratio test for a VC quantitative-trait locus-detection procedure to violations of normality that are due to these factors. Results showed (a) that some types of nonnormality, such as leptokurtosis, produced type I error rates in excess of the nominal, or alpha, levels whereas others did not; and (b) that the degree of type I error-rate inflation appears to be directly related to the residual sibling correlation. Potential solutions to this problem are discussed. Investigators contemplating use of this VC procedure are encouraged to provide evidence that their trait data are normally distributed, to employ a procedure that allows for nonnormal data, or to consider implementation of permutation tests.

Analysis of Variance↗
PubMed2003

Genetics of quantitative traits in Arabidopsis thaliana.

The genetic control of 22 quantitative traits, including developmental rates and sizes, was examined in generations of Arabidopsis thaliana derived from the cross between the ecotypes, Columbia (Col) and Landsberg erecta (Ler). The data were obtained from three sets of families raised in the same trial: the 16 basic generations, that is, parents, F(1)'s, F(2)'s, backcrosses, recombinant inbred lines (RILs) and a triple test cross (TTC), the latter produced by crossing the RILs to Col, Ler and their F(1). The data were analysed by two approaches. The first (approach A) involved traditional generation mean and variance component analysis and the second (B), based around the RILs and TTC families, involved marker-based QTL analysis. From (A), genetic differences between Col and Ler were detected for all traits with moderate heritabilities. Height at flowering was the only trait to show heterosis. Dominance was partial to complete for all height traits, and there was no overdominance but there was strong evidence for directional dominance. For most other traits, dominance was ambidirectional and incomplete, with average dominance ratios of around 80%. Epistasis, particularly of the duplicate type that opposes dominance, was a common feature of all traits. The presence of epistasis must imply multiple QTL for all traits. The QTL analysis located 38 significant effects in four regions of chromosomes I, II, IV and V, but not III. QTL affecting rosette size and leaf number were identified in all four regions, with days to maturity on chromosomes IV and V. The only QTL for height was located at the expected position of the erecta gene (chromosome II; 50 cM), but the additive and dominance effects of this single QTL did not adequately explain the generation means. The possible involvement of other interacting height QTL is discussed.

Analysis of Variance↗