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At least 307 records · Page 17Linked to original sources
PubMed2003

Quantitative trait locus analysis of fungal disease resistance factors on a molecular map of grapevine.

A full-sibling F1 population comprising 153 individuals from the cross of 'Regent' x 'Lemberger' was employed to construct a genetic map based on 429 molecular markers. The newly-bred red grapevine variety 'Regent' has multiple field-resistance to fungal diseases inherited as polygenic traits, while 'Lemberger' is a traditional fungus-susceptible cultivar. The progeny segregate quantitatively for resistances to Plasmopara viticola and Uncinula necator, fungal pathogens that threaten viticulture in temperate areas. A double pseudo-testcross strategy was employed to construct the two parental maps under high statistical stringency for linkage to obtain a robust marker frame for subsequent quantitative trait locus (QTL) analysis. In total, 185 amplified fragment length polymorphism, 137 random amplified polymorphic DNA, 85 single sequence repeat and 22 sequence characterized amplified region or cleaved amplified polymorphic sequence markers were mapped. The maps were aligned by co-dominant or doubly heterozygous dominant anchor markers. Twelve pairs of homologous linkage groups could be integrated into consensus linkage groups. Resistance phenotypes and segregating characteristics were scored as quantitative traits in three or four growing seasons. Interval mapping reproducibly localized genetic factors that correlated with fungal disease resistances to specific regions on three linkage groups of the maternal 'Regent' map. A QTL for resistance to Uncinula necator was identified on linkage group 16, and QTLs for endurance to Plasmopara viticola on linkage groups 9 and 10 of 'Regent'. Additional QTLs for the onset of berry ripening ("veraison"), berry size and axillary shoot growth were identified. Berry color segregated as a simple trait in this cross of two red varieties and was mapped as a morphological marker. Six markers derived from functional genes could be localized. This dissection of polygenic fungus disease resistance in grapevine allows the development of marker-assisted selection for breeding, the characterization of genetic resources and the isolation of the corresponding genes.

Chromosome Mapping↗
PubMed2004

Detecting epistatic interactions contributing to quantitative traits.

The restricted partition method (RPM) is a partitioning algorithm for examining multi-locus genotypes as (potentially non-additive) predictors of a quantitative trait. The motivating application was to develop a robust method to examine quantitative phenotypes for epistasis (gene-gene interactions), but the method can be applied without modification to gene-environment interactions. Simulation results indicate that the method provides an efficient way to identify loci contributing epistatically to a quantitative trait, even if the loci have no single locus effects. Statistical significance can be estimated through permutation testing. An example using real data involving the metabolism of a chemotherapy drug is included for illustration. Although the examples in this article involve 2-locus interactions, the RPM is computationally feasible for the analysis of more than two loci or factors.

Algorithms↗
PubMed2005

Mapping quantitative trait loci in multiple populations of Arabidopsis thaliana identifies natural allelic variation for trichome density.

The majority of biological traits are genetically complex. Mapping the quantitative trait loci (QTL) that determine these phenotypes is a powerful means for estimating many parameters of the genetic architecture for a trait and potentially identifying the genes responsible for natural variation. Typically, such experiments are conducted in a single mapping population and, therefore, have only the potential to reveal genomic regions that are polymorphic between the progenitors of the population. What remains unclear is how well the QTL identified in any one mapping experiment characterize the genetics that underlie natural variation in traits. Here we provide QTL mapping data for trichome density from four recombinant inbred mapping populations of Arabidopsis thaliana. By aligning the linkage maps for these four populations onto a common physical map, the results from each experiment were directly compared. Seven of the nine QTL identified are population specific while two were mapped in all four populations. Our results show that many lineage-specific alleles that either increase or decrease trichome density persist in natural populations and that most of this genetic variation is additive. More generally, these findings suggest that the use of multiple populations holds great promise for better understanding the genetic architecture of natural variation.

Arabidopsis↗
PubMed2001

Quantitative trait analysis of nickel-induced acute lung injury in mice.

The genetic determinants underlying susceptibility to acute lung injury have not been identified. Recently, we found that the strain distribution pattern for mean survival time (MST) to three irritants-ozone, ultrafine Teflon, and nickel sulfate- was shared between inbred mouse strains. For ozone-induced acute lung injury, survival was found to be a complex trait controlled by at least three quantitative trait loci (QTLs), designated Aliq1, Aliq2, and Aliq3. To explore whether similar genes might be involved in survival to acute lung injury induced by nickel sulfate, we took advantage of the 2-fold difference in MSTs between the sensitive A/J and resistant C57BL/6J mice. QTL analysis of 307 backcross mice generated from these strains identified significant linkage to chromosome 6 (proposed as Aliq4) and suggestive linkage on chromosomes 1 and 12. Loci on chromosomes 9 and 16 had lod scores (log of the odds ratio, which equals the log of the "likelihood of linkage divided by the likelihood of no linkage") below significance, but contributed to the overall response. Comparing MSTs of backcross mice with similar haplotypes identified an allelic combination of four QTLs that could account for the survival time difference between the parental strains. Similar QTL intervals on chromosomes 6 and 12 were previously identified with ozone, suggesting that the interplay between different combinations of relatively few genes might be important for irritant-induced acute lung injury survival.

Administration, Inhalation↗
PubMed2002

Score test for mapping quantitative-trait loci with sibships of arbitrary size when the dominance effect is not negligible.

In the linakge analysis of quantitative traits, an additive model that assumes no dominance effect is often adopted. Intuitively, when the no-dominance-effect assumption does not hold, such a practice does not make efficient use of the data, and its power to detect linkage can be improved. Here we introduce a score statistic for detecting quantitative trait loci when the dominance effect is not neglible or the dominance effect is a concern. This statistic is derived from a normal likelihood function for sibships of arbitrary size. In the derivation, the inherent genetic constraints on model parameters are fully taken into consideration. This score statistic is asymptotically equivalent to the corresponding likelihood ratio statistic, but it is much easier to compute. The asymptotic distribution of this statistic is derived, which is a mixture of chi(0) (2), chi(1) (2), and chi(2) (2). Weights for distribution components are functions of the informativeness of the marker data. The type I error rate and the power of the proposed statistic in finite sample are evaluated via simulations.

Chromosome Mapping↗
PubMed2006

Quantitative trait loci modifying cardiac atrial septal morphology and risk of patent foramen ovale in the mouse.

Atrial septal defect (ASD) is a common congenital heart disease (CHD) occurring in 5 to 7 per 10,000 live births. Mutations in 5 human genes (NKX2.5, TBX5, GATA4, MYHC, ACTC) are known to cause dominant ASD, but these account for a minority of cases. Human and mouse data suggest that ASD exists in an anatomical continuum with milder septal variants patent foramen ovale (PFO) and atrial septal aneurysm, strongly associated with ischemic stroke and migraine. We have previously shown in inbred mice that the incidence of PFO strongly correlates with length of the interatrial septum primum, defining a quantitative trait underlying PFO risk. To better understand genetic causation of atrial septal abnormalities, we mapped quantitative trait loci (QTL) influencing septal morphology using mouse strains (QSi5 and 129T2/SvEms) maximally informative for PFO incidence and 3 quantitative septal anatomical traits including septum primum length. [QSi5x129T2/SvEms]F2 intercross animals (n=1437) were phenotyped and a whole genome scan performed at an average 17-cM interval. Statistical methodology scoring PFO as a binary phenotype was developed as a confirmatory mapping technique. We mapped 7 significant and 6 suggestive QTL modifying quantitative phenotypes, with 4 supported by binary analysis. Quantitative traits, although strongly associated with PFO (P<0.001), correlated poorly with each other and in all but 1 case QTL for different traits were nonoverlapping. Thus, multiple anatomical processes under separate genetic control contribute to risk of PFO. Our findings demonstrate the feasibility of modeling the genetic basis of common CHD using animal genetic and genomic technologies.

Animals↗
PubMed2002

Estimation of quantitative trait loci effects in dairy cattle populations.

Standard animal model programs can be modified to include the effect of a quantitative gene, even if only a fraction of the population is genotyped. Five methods to estimate the effect of a diallelic quantitative gene affecting a quantitative trait were compared to a standard animal model (model I) on simulated populations, based on mean squared errors and bias. In models II, III, and IV complete linkage between a single genetic marker and the quantitative trait gene was assumed. In models II and III the elements of the incidence matrix for the gene effect were 0 or 1 for genotyped individuals, and the probabilities of the possible candidate gene genotypes for individuals that were not genotyped. In model III segregation analysis was used to compute these probabilities. If only some of the cows were genotyped, the model III estimates were nearly unbiased, while model II underestimated the simulated effects. When only sires were genotyped, model II overestimated the simulated effect. In models V and VI two markers bracketing the quantitative gene with recombination frequencies of 0.1 and 0.2 with the quantitative gene were simulated, and the algorithm of Whittaker et al. (1996) was used to derive estimates of gene effect and location. In model V marker allele effects were included in the animal model analysis. In model VI, the model I genetic evaluations were analyzed. Model V estimates for both effect and location of the quantitative gene were unbiased, while model VI estimates were only 0.25 of the simulated effect.

Animals↗
PubMed2006

On the generalized poisson regression mixture model for mapping quantitative trait loci with count data.

Statistical methods for mapping quantitative trait loci (QTL) have been extensively studied. While most existing methods assume normal distribution of the phenotype, the normality assumption could be easily violated when phenotypes are measured in counts. One natural choice to deal with count traits is to apply the classical Poisson regression model. However, conditional on covariates, the Poisson assumption of mean-variance equality may not be valid when data are potentially under- or overdispersed. In this article, we propose an interval-mapping approach for phenotypes measured in counts. We model the effects of QTL through a generalized Poisson regression model and develop efficient likelihood-based inference procedures. This approach, implemented with the EM algorithm, allows for a genomewide scan for the existence of QTL throughout the entire genome. The performance of the proposed method is evaluated through extensive simulation studies along with comparisons with existing approaches such as the Poisson regression and the generalized estimating equation approach. An application to a rice tiller number data set is given. Our approach provides a standard procedure for mapping QTL involved in the genetic control of complex traits measured in counts.

Algorithms↗
PubMed2006

Genetic differentiation of neutral markers and quantitative traits in predominantly selfing metapopulations: confronting theory and experiments with Arabidopsis thaliana.

The comparison of the genetic differentiation of quantitative traits (QST) and molecular markers (FST) can inform on the strength and spatial heterogeneity of selection in natural populations, provided that markers behave neutrally. However, selection may influence the behaviour of markers in selfing species with strong linkage disequilibria among loci, therefore invalidating this test of detection of selection. We address this issue by monitoring the genetic differentiation of five microsatellite loci (FST) and nine quantitative traits (QST) in experimental metapopulations of the predominantly selfing species Arabidopsis thaliana, that evolved during eight generations. Metapopulations differed with respect to population size and selection heterogeneity. In large populations, the genetic differentiation of neutral microsatellites was much larger under heterogeneous selection than under uniform selection. Using simulations, we show that this influence of selection heterogeneity on FST can be attributable to initial linkage disequilibria among loci, creating stronger genetic differentiation of QTL than expected under a simple additive model with no initial linkage. We found no significant differences between FST and QST regardless of selection heterogeneity, despite a demonstrated effect of selection on QST values. Additional data are required to validate the role of mating system and linkage disequilibria in the joint evolution of neutral and selected genetic differentiation, but our results suggest that FST/QST comparisons can be conservative tests to detect selection in selfing species.

Arabidopsis↗
PubMed2004

Multipoint linkage analysis of quantitative traits on sex-chromosomes.

Variance component models form a powerful and flexible tool for multipoint linkage analysis of quantitative traits. Estimates of genetic similarity are needed for the variance component model to detect linkage and to locate genes, and two methods are commonly used to calculate multipoint identity-by-descent (IBD) estimates for autosomes. Fulker et al. ([1995] Am. J. Hum. Genet. 56: 1229-1233) and Almasy and Blangero ([1998] Am. J. Hum. Genet. 62: 119-121) used multiple regression to estimate the IBD sharing along a chromosome, while the approach of Kruglyak and Lander ([1995] Am. J. Hum. Genet. 57: 439-454) is based on a hidden Markov model. In this paper, we modify the variance component model to accommodate sex-chromosomes, and we extend both multipoint IBD estimation methods to accommodate sex-linked loci. Simulation studies demonstrate the power and precision of the variance component model to detect QTLs located on the sex-chromosome. The two multipoint IBD estimation methods have the same accuracy to identify QTL position, but the hidden Markov model yields a larger average maximum LOD score to detect linkage than the regression model. The extension of the multipoint IBD estimation methods and the variance component model to the X chromosome shows that the variance component model is a powerful and flexible tool for linkage analysis of quantitative traits on both autosomes and sex-chromosomes.

Algorithms↗
PubMed2004

The DGAT1 K232A mutation is not solely responsible for the milk production quantitative trait locus on the bovine chromosome 14.

The gene, acyl-CoA:diacylglycerol acyltransferase1 (DGAT1), was recently identified as the one underlying the quantitative trait locus (QTL) for milk production traits in the centromeric region of the bovine chromosome 14. Until now, 2 alleles, the lysine variant (increasing fat yield, fat and protein percentage) and the alanine variant (increasing protein and milk yield), were postulated at DGAT1. This study investigated whether the diallelic DGAT1 polymorphism is responsible for all the genetic variation at the centromeric region of this chromosome for milk, fat, and protein yield and fat and protein percentage. A statistical model was applied to a granddaughter design to analyze 16 German Holstein families. The model included the diallelic DGAT1 effect and the QTL transition probability estimated for each chromosomal position by a multiple marker approach. Because the regression coefficient of this probability was corrected for the diallelic DGAT1 polymorphism, it represented a putative conditional QTL effect. The effect of the DGAT1 gene was always highly significant. The conditional QTL effect was significant genomewise for fat percentage at the proximal end of the chromosome and for protein percentage at a more distal chromosomal region. Additional chromosomewise significance was found for fat and protein yield. Our results suggest an additional source of genetic variance on this chromosome for these traits; either one or more additional alleles segregating at DGAT1 that were not previously detected, a second quantitative trait locus affecting these traits, or both.

Acyltransferases↗
PubMed1995

Complete multipoint sib-pair analysis of qualitative and quantitative traits.

Sib-pair analysis is an increasingly important tool for genetic dissection of complex traits. Current methods for sib-pair analysis are primarily based on studying individual genetic markers one at a time and thus fail to use the full inheritance information provided by multipoint linkage analysis. In this paper, we describe how to extract the complete multipoint inheritance information for each sib pair. We then describe methods that use this information to map loci affecting traits, thereby providing a unified approach to both qualitative and quantitative traits. Specifically, complete multipoint approaches are presented for (1) exclusion mapping of qualitative traits; (2) maximum-likelihood mapping of qualitative traits; (3) information-content mapping, showing the extent to which all inheritance information has been extracted at each location in the genome; and (4) quantitative-trait mapping, by two parametric methods and one nonparametric method. In addition, we explore the effects of marker density, marker polymorphism, and availability of parents on the information content of a study. We have implemented the analysis methods in a new computer package, MAPMAKER/SIBS. With this computer package, complete multipoint analysis with dozens of markers in hundreds of sib pairs can be carried out in minutes.

Chromosome Mapping↗
PubMed1999

[Inheritance of quantitative traits in hybrid pedigrees: mixed models].

Mixed models have been extended to make them applicable to description of inheritance of quantitative traits in pedigrees obtained via interbreed or interpopulation hybridization. Additional assumptions specify definite relationships between the parameters that characterize the inheritance of the trait in two parental populations. It is assumed that (1) parental populations differ from each other only in the allelic frequencies in the major gene locus and polygenic loci and (2) the patterns of phenotype formation based on an individual genotype and the transmission of genes to the next generation are the same in both parental populations, as well as in their hybrids. Based on these assumptions, the likelihood function for a hybrid pedigree is derived, and the heterosis effect is formalized. The results of this study offer new possibilities for estimating the contribution of the major gene effect to interpopulation and interbreed differences in the expression of quantitative traits.

Female↗
PubMed2006

Quantitative trait loci for baseline erythroid traits.

A substantial genetic contribution underlies variation in baseline peripheral blood counts. We performed quantitative trait locus/loci (QTL) analyses to identify chromosome (Chr) regions harboring genes influencing the baseline erythroid parameters in F2 intercrosses between NZW/LacJ, SM/J, and C57BLKS/J inbred mice. We identified multiple significant QTL for red blood cell (RBC) count, hemoglobin (Hgb) and hematocrit (Hct) levels, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean cell hemoglobin concentration (CHCM). We identified four RBC count QTL: Rbcq1 (Chr 1, peak LOD score at 62 cM,), Rbcq2 (Chr 4, 60 cM), Rbcq3 (Chr 11, 34 cM), and Rbcq4 (Chr 10, 60 cM). Three MCV QTL were identified: Mcvq1 (Chr 7, 30 cM), Mvcq2 (Chr 11, 6 cM), and Mcvq3 (Chr 10, 60 cM). Single significant loci for Hgb (Hgbq1, Chr 16, 32 cM), Hct (Hctq1, Chr 3, 42 cM), and MCH (Mchq1, Chr 10, 60 cM) were identified. The data support the existence of a common RBC/MCH/MCV locus on Chr 10. Two QTL for CHCM (Chcmq1, Chr 2, 48 cM; Chcmq2, Chr 9, 44 cM) and an interaction between Chcmq2 with a locus on Chr 19 were identified. These analyses emphasize the genetic complexity underlying the regulation of erythroid peripheral blood traits in normal populations and suggest that genes not previously recognized as significantly impacting normal erythropoiesis exist.

Animals↗
PubMed2003

Mapping quantitative trait loci underlying triploid endosperm traits.

Endosperm, which is derived from two polar nuclei fusing with one sperm, is a triploid tissue in cereals. Endosperm tissue determines the grain quality of cereals. Improving grain quality is one of the important breeding objectives in cereals. However, current statistical methods for mapping quantitative trait loci (QTL) under diploid genetic control have not been effective for dealing with endosperm traits because of the complexity of their triploid inheritance. In this paper, we derive for the first time the conditional probabilities of F(3) endosperm QTL genotypes given different flanking marker genotypes in F(2) plants. Using these probabilities, we develop a multiple linear regression method implemented via the iteratively reweighted least-squares (IRWLS) algorithm and a maximum likelihood method (ML) implemented via the expectation-maximization (EM) algorithm to map QTL underlying endosperm traits. We use the mean value of endosperm traits of F(3) seeds as the dependent variable and the expectations of genotypic indicators for additive and dominance effect of a putative QTL flanked by a pair of markers as independent variables for IRWLS mapping. However, if an endosperm trait is measured quantitatively using a single endosperm sample, the ML mapping method can be used to separate the two dominance effects. Efficiency of the methods is verified through extensive Monte Carlo simulation studies. Results of simulation show that the proposed methods provide accurate estimates of both the QTL effects and locations with very high statistical power. With these methods, we are now ready to map endosperm traits, as we can for regular quantitative trait under diploid control.

Chromosome Mapping↗
PubMed1994

Quantitative trait locus analysis of susceptibility to diet-induced atherosclerosis in recombinant inbred mice.

Quantitative trait locus (QTL) analysis is a statistical method that can be applied to identify loci making a significant impact on a phenotype. For the phenotype of susceptibility to diet-induced atherosclerosis in the mouse, we have studied four quantitative traits: area of aortic fatty streaks and serum concentrations of high-density lipoprotein-bound cholesterol (HDL-cholesterol), apolipoprotein A-I, and apolipoprotein A-II (apo A-II). QTL analysis revealed a significant locus on chromosome 1 distal impacting serum apo A-II concentration on a high-fat diet and serum HDL-cholesterol concentration on a chow diet. This locus is presumably Apoa-2, the structural gene for apo A-II. QTL analysis of aortic fatty streaks failed to reveal a significant locus.

Animals↗
PubMed1999

Joint multipoint linkage analysis of multivariate qualitative and quantitative traits. II. Alcoholism and event-related potentials.

The availability of robust quantitative biological markers that are correlated with qualitative psychiatric phenotypes can potentially improve the power of linkage methods to detect quantitative-trait loci influencing psychiatric disorders. We apply a variance-component method for joint multipoint linkage analysis of multivariate discrete and continuous traits to the extended pedigree data from the Collaborative Study on the Genetics of Alcoholism, in a bivariate analysis of qualitative alcoholism phenotypes and quantitative event-related potentials. Joint consideration of the DSM-IV diagnosis of alcoholism and the amplitude of the P300 component of the Cz event-related potential significantly increases the evidence for linkage of these traits to a chromosome 4 region near the class I alcohol dehydrogenase locus ADH3. A likelihood-ratio test for complete pleiotropy is significant, suggesting that the same quantitative-trait locus influences both risk of alcoholism and the amplitude of the P300 component.

Alcohol Dehydrogenase↗
PubMed2000

A recombination hotspot delimits a wild-species quantitative trait locus for tomato sugar content to 484 bp within an invertase gene.

In nature, genetic variation usually takes the form of a continuous phenotypic range rather than discrete classes. The genetic variation underlying quantitative traits results from the segregation of numerous interacting quantitative trait loci (QTLs), whose expression is modified by the environment. To uncover the molecular basis of this variation, we characterized a QTL (Brix9-2-5) derived from the green-fruited tomato species Lycopersicon pennellii. The wild-species allele increased glucose and fructose contents in cultivated tomato fruits in various genetic backgrounds and environments. Using nearly isogenic lines for the QTL, high-resolution mapping analysis delimited Brix9-2-5 to a single nucleotide polymorphism-defined recombination hotspot of 484 bp spanning an exon and intron of a fruit-specific apoplastic invertase. We suggest that the differences between the Brix9-2-5 alleles of the two species are associated with a polymorphic intronic element that modulates sink strength of tomato fruits. Our results demonstrate a link between naturally occurring DNA variation and a Mendelian determinant of a complex phenotype for a yield-associated trait.

Alleles↗