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PubMed1989

Robust methods for the detection of genetic linkage for quantitative data from pedigrees.

The robust method for detecting linkage developed by Haseman and Elston [The investigation of linkage between a quantitative trait and a marker locus. Behav Genet 2:3-19, 1972] for data from sib pairs is extended to any type of noninbred relative pair. The regression of the squared relative-pair trait difference on the estimated proportion of genes identical by descent (i.b.d.) at a marker locus is shown to depend upon the recombination fraction between the two loci; the regression coefficient is negative if the trait and marker loci are linked. A test for linkage based on data from any informative type of relative pair can thus be obtained by testing that this regression coefficient is less than zero. Formulae for the asymptotic power of such tests for linkage based upon independent relative pairs are developed. Results are also given for the special case in which the proportion of genes shared i.b.d. for relative pairs is known. Finally, a general algorithm is described that will incorporate all available pedigree data to calculate an estimate of the proportion of genes that a relative pair shares i.b.d. at a marker locus.

Genetic Linkage↗
PubMedDate not supplied

Interlaboratory transfer of a real-time polymerase chain reaction assay for quantitative detection of genetically modified maize event TC-1507.

A real-time polymerase chain reaction (QPCR) assay was developed for quantitative detection of a genetically modified (GM) maize event TC-1507 and modification to conventional PCR for qualitative purposes. Sequences 5'-flanking TC-1507 full-length insert were characterized and showed multiple rearrangements involving insert and maize chloroplast fragments. The event specificity of the TC-1507 assays was based on the detection of transgene and plant rearranged sequences found to 5' flank the insertion site. They were fully specific and exhibited a limit of detection below 10 target copies, allowing consistent detection of 0.1% GM levels. The QPCR was highly linear and efficient and proved adequate for quantification of GM contents, aiming at the fulfillment of legal requirements established in the European Union (i.e., compulsory labeling of TC-1507 levels >0.9%). It satisfactorily determined TC-1507 contents on different matrixes and was successfully transferred a different laboratory.

Base Sequence↗
PubMed2004

Genetic investigation of quantitative traits related to autism: use of multivariate polygenic models with ascertainment adjustment.

Autism is a severe developmental disorder of unknown etiology but with evidence for genetic influences. Here, we provide evidence for a genetic basis of several quantitative traits that are related to autism. These traits, from the Broader Phenotype Autism Symptom Scale (BPASS), were measured in nuclear families, each ascertained through two probands affected by autism spectrum disorder. The BPASS traits capture the continuum of severity of impairments and may be more informative for genetic studies than are the discrete diagnoses of autism that have been used by others. Using a sample of 201 nuclear families consisting of a total of 694 individuals, we implemented multivariate polygenic models with ascertainment adjustment to estimate heritabilities and genetic and environmental correlations between these traits. Our ascertainment adjustment uses conditioning on the phenotypes of probands, requires no modeling of the ascertainment process, and is applicable to multiplex ascertainment and multivariate traits. This appears to be the first such implementation for multivariate quantitative traits. The marked difference between heritability estimates of the trait for language onset with and without an ascertainment adjustment (0.08 and 0.22, respectively) shows that conclusions are sensitive to whether or not an ascertainment adjustment is used. Among the five BPASS traits that were analyzed, the traits for social motivation and range of interest/flexibility show the highest heritability (0.19 and 0.16, respectively) and also have the highest genetic correlation (0.92). This finding suggests a shared genetic basis of these two traits and that they may be most promising for future gene mapping and for extending pedigrees by phenotyping additional relatives.

Adolescent↗
PubMed1994

Genetic mapping of quantitative trait loci for growth and fatness in pigs.

The European wild boar was crossed with the domesticated Large White pig to genetically dissect phenotypic differences between these populations for growth and fat deposition. The most important effects were clustered on chromosome 4, with a single region accounting for a large part of the breed difference in growth rate, fatness, and length of the small intestine. The study is an advance in genome analyses and documents the usefulness of crosses between divergent outbred populations for the detection and characterization of quantitative trait loci. The genetic mapping of a major locus for fat deposition in the pig could have implications for understanding human obesity.

Adipose Tissue↗
PubMed1999

Multipoint genetic mapping of quantitative trait loci with dominant markers in outbred populations.

We present a multipoint algorithm for mapping quantitative trait loci (QTLs) using dominant markers. The algorithm is designed for outbred populations and is particularly suited for large families. The algorithm works with either codominant or dominant markers, either of which may be interspersed within the same linkage map. Concurrently, the algorithm also partitions dominance variance at the QTL. Computer simulations show that with large families, QTL mapping with dominant markers can be almost as powerful as with bi-allelic, codominant markers. Yet despite this, other situations show a large standard deviation in the estimate of the QTL position, thus making QTL mapping with dominant markers in outbred populations a useful detection tool, albeit limited in its resolution.

Algorithms↗
PubMed1973

The analysis of quantitative traits for simple genetic models from parental, F 1 and backcross data.

THE FOLLOWING MODELS ARE CONSIDERED FOR THE GENETIC DETERMINATION OF QUANTITATIVE TRAITS: segregation at one locus, at two linked loci, at any number of equal and additive unlinked loci, and at one major locus and an indefinite number of equal and additive loci. In each case an appropriate likelihood is given for data on parental, F(1) and backcross individuals, assuming that the environmental variation is normally distributed. Methods of testing and comparing the various models are presented, and methods are suggested for the simultaneous analysis of two or more traits.

Biometry↗
PubMed1998

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

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

Animals↗
PubMed2006

The association of DNA sequence variation at the MAOA genetic locus with quantitative behavioural traits in normal males.

Monoamine oxidase A (MAOA) catalyses the oxidative deamination of biogenic amines including neurotransmitters, mainly norepinephrine and serotonin in the brain and peripheral tissues. A nonsense mutation in the gene was shown to be involved in a rare X-linked behavioural syndrome, which includes impaired impulse control, aggression and borderline mental retardation (Brunner syndrome). Several recent studies have shown the association of genetic variation of a VNTR in the gene promoter with various pathological behavioural traits. In the present study the association of MAOA genetic variation with a large set of quantitative behavioural traits in normal individuals has been examined. DNA samples from 421 unrelated males were genotyped for 14 SNPs and for the promoter VNTR at the MAOA locus. An additional 16 SNPs were genotyped at apparently neutral loci across the X chromosome to serve as a genomic control for possible false positive associations due to population structure. Behavioural traits were measured using the NEO psychometric questionnaire, which is based on a 5-axis model of personality, and consists of 30 different quantitative traits. There was a robust association of the A2 ("straightforwardness") facet with common allelic variants at the promoter VNTR. Most of the tested traits were not associated with the VNTR despite reasonable power, thus demonstrating that the VNTR influence on quantitative behavioural traits in normal males may be very specific. In contrast, several traits of the C ("conscientiousness") axis were associated with less common SNP-defined haplotypes. Hence, it appears that common genetic variation at the VNTR contributes to the behavioural attribute of "straightforwardness", while rare haplotypes defined by SNPs downstream of the transcription start site may contribute to "conscientiousness". This study is used to address the validation, interpretation and limitation of genetic association studies of quantitative behavioural traits.

Black or African American↗
PubMed2002

Common variations in noncoding regions of the human natriuretic peptide receptor A gene have quantitative effects.

Genetic susceptibility to common conditions, such as essential hypertension and cardiac hypertrophy, is probably determined by various combinations of small quantitative changes in the expression of many genes. NPR1, coding for natriuretic peptide receptor A (NPRA), is a potential candidate, because NPRA mediates natriuretic, diuretic, and vasorelaxing actions of the nariuretic peptides, and because genetically determined quantitative changes in the expression of this gene affect blood pressure and heart weight in a dose-dependent manner in mice. To determine whether there are common quantitative variants in human NPR1, we have sequenced the entire human NPR1 gene and identified 10 polymorphic sites in its non-coding sequence by using DNA from 34 unrelated human individuals. Five of the sites are single nucleotide polymorphisms; the remaining five are length polymorphisms, including a highly variable complex dinucleotide repeat in intron 19. There are three common haplotypes 5' to this dinucleotide repeat and three 3' to it, but the 5' haplotypes and 3' haplotypes appear to be randomly associated. Transient expression analysis in cultured cells of reporter plasmids with the proximal promoter sequences of NPR1 and its 3' untranslated regions showed that these polymorphisms have functional effects. We conclude that common NPR1 alleles can alter expression of the gene as much as two-fold and could therefore significantly affect genetic risks for essential hypertension and cardiac hypertrophy in humans.

Animals↗
PubMed2005

A microarray data-based semi-kinetic method for predicting quantitative dynamics of genetic networks.

BACKGROUND: Elucidating the dynamic behaviour of genetic regulatory networks is one of the most significant challenges in systems biology. However, conventional quantitative predictions have been limited to small networks because publicly available transcriptome data has not been extensively applied to dynamic simulation. RESULTS: We present a microarray data-based semi-kinetic (MASK) method which facilitates the prediction of regulatory dynamics of genetic networks composed of recurrently appearing network motifs with reasonable accuracy. The MASK method allows the determination of model parameters representing the contribution of regulators to transcription rate from time-series microarray data. Using a virtual regulatory network and a Saccharomyces cerevisiae ribosomal protein gene module, we confirmed that a MASK model can predict expression profiles for various conditions as accurately as a conventional kinetic model. CONCLUSION: We have demonstrated the MASK method for the construction of dynamic simulation models of genetic networks from time-series microarray data, initial mRNA copy number and first-order degradation constants of mRNA. The quantitative accuracy of the MASK models has been confirmed, and the results indicated that this method enables the prediction of quantitative dynamics in genetic networks composed of commonly used network motifs, which cover considerable fraction of the whole network.

Amino Acid Motifs↗
PubMed2004

Genetic mapping of quantitative trait loci affecting body weight, egg character and egg production in F2 intercross chickens.

Phenotypic measurements of chicken egg character and production traits are restricted to mature females only. Marker assisted selection of immature chickens using quantitative trait loci (QTL) has the potential to accelerate the genetic improvement of these traits in the chicken population. The QTL for 12 traits (i.e. body weight (BW), six for egg character, three for egg shell colour and two for egg production) of chickens were identified. An F2 population comprising 265 female chickens obtained by crossing White Leghorn and Rhode Island Red breeds and genotyped for 123 microsatellite markers was used for detecting QTL. Ninety-six markers were mapped on 25 autosomal linkage groups, and 13 markers were mapped on one Z chromosomal linkage group. Eight previous unmapped markers were assigned to their respective chromosomes in this study. Significant QTL were detected for BW on chromosomes 4 and 27, egg weight on chromosome 4, the short length of egg on chromosome 4, and redness of egg shell colour (using the L*a*b* colour system) on chromosome 11. A significant QTL on the Z chromosome was linked with age at first egg. Significant QTL could account for 6-19% of the phenotypic variance in the F2 population.

Analysis of Variance↗
PubMed2000

Genetic mapping of quantitative trait loci influencing left ventricular mass in rats.

High blood pressure is the leading cause of left ventricular hypertrophy (LVH); however, not all hypertensive patients develop LVH. Genetic factors are important in the development of LVH. With the use of F2 male rats from spontaneously hypertensive rats and Lewis rats, we performed a study to identify the quantitative trait loci (QTL) that influence left ventricular mass (LVM). Mean arterial pressure (MAP) was measured by the direct intra-arterial method in conscious animals, and LVM was determined at 24 wk of age. QTL analysis was done using 160 microsatellite markers for a genome-wide scan. Two loci that influenced body weight-adjusted LVM with logarithm of the odds scores >3.4 were found. One locus on chromosome 17 influenced LVM independently of MAP. Another locus on chromosome 7 influenced LVM and MAP. These findings indicate not only the existence of a gene on chromosome 7 that influences LVM in a manner dependent on blood pressure but also the existence of a gene on chromosome 17 that influences LVM independently of blood pressure.

Animals↗
PubMed1995

The genetic basis of quantitative variation: numbers of sensory bristles of Drosophila melanogaster as a model system.

The numbers of sensory hairs of Drosophila melanogaster present an ideal model system to elucidate the genetic basis of morphological quantitative variation. Loci affecting bristle number can be identified and their properties studied by accumulating spontaneous mutations, by P element mutagenesis, by mapping factors causing divergence between selection lines and by the association of phenotype variation with molecular variation at candidate neurogenic loci. The consensus emerging from the application of all approaches is that much of the mutational and segregating variation affecting bristle number is attributable to alleles with large phenotype effects at a small number of candidate loci.

Animals↗
PubMed1988

Molecular dosimetry of alkylating agents: quantitative comparison of genetic effects on the basis of DNA adduct formation.

This is a review of the work on molecular dosimetry carried out by several laboratories within the third Environmental Programme of the Commission of the European Communities. The molecular dosimetry project is a coordinated research project in which several laboratories cooperated on various aspects of quantitative comparative mutagenesis. This involved (i) development of assay systems for measurement of DNA adducts using radioactively labelled mutagens; (ii) development of immunological assays for detection and quantification of DNA adducts; (iii) isolation and characterization of monoclonal antibodies against DNA adducts; (iv) quantitative comparison of genetic effects of the model compounds within one assay system; and (v) extrapolation of genetic effects of the model compounds from in vitro systems to whole animal studies.

Alkylating Agents↗
PubMed2004

Contrasting patterns of quantitative and neutral genetic variation in locally adapted populations of the natterjack toad, Bufo calamita.

The relative importance of natural selection and genetic drift in determining patterns of phenotypic diversity observed in nature is still unclear. The natterjack toad (Bufo calamita) is one of a few amphibian species capable of breeding in saline ponds, even though water salinity represents a considerable stress for them. Results from two common-garden experiments showed a pattern of geographic variation in embryonic salinity tolerance among populations from either fresh or brackish environments, consistent with the hypothesis of local adaptation. Full-sib analysis showed increased variation in survival among sibships within population for all populations as osmotic stress was increased (broad-sense heritability increased as salinity raised). Nevertheless, toads native to the brackish water environment had the highest overall survival under brackish conditions. Levels of population genetic differentiation for salinity tolerance were higher than those of neutral genetic differentiation, the latter obtained through the analysis of eight microsatellite loci. Microsatellite markers also revealed little population differentiation, lack of an isolation-by-distance pattern, and moderate gene flow connecting the populations. Therefore, environmental stress tolerance appears to have evolved in absence of geographic isolation, and consequently we reject the null hypothesis of neutral differentiation.

Adaptation, Physiological↗
PubMed2001

Genetic linkage methods for quantitative traits.

We discuss methods for detecting genetic linkage for quantitative data. The usual LOD score method uses a pseudolikelihood formulation and has optimal power provided all parameters are correctly specified, but can lead to erroneous estimates of the location for the locus influencing a trait under misspecification of parameters describing the variance of the trait. Alternative methods, in which attention focuses upon modelling covariation among relatives as a function of genetic marker, similarity lead to unbiased estimates of the location and major gene heritability of the trait influencing locus. The Haseman-Elston approach uses a regression method to perform linkage analysis and its properties have been widely studied. This method is generally less powerful than variance components procedures, but the maximum likelihood-based variance components procedures require normality of the trait to ensure robustness of the genetic linkage tests (i.e. a correct false positive rate). When samples are non-randomly selected an ascertainment correction is generally required in order to obtain unbiased parameter estimates when applying variance components methods. For quantitative traits, ascertainment corrections usually condition either on the proband exceeding a threshold, or on the trait value of the proband. We summarize simulations that show that both approaches lead to similar efficiencies for estimating genetic effects. Finally, we discuss methods for analysing diseases that include time-to-onset information. A variety of methods are available for the linkage analysis of quantitative traits. Here, we have reviewed the most commonly used methods.

Biometry↗
PubMed2006

Bayes factor for testing the genetic background of quantitative threshold traits.

The recent development of the Bayes factor methodology to test between nested competing models has allowed to evaluate the genetic component of continuous traits through a methodology based on the reparameterization of a variance component model in terms of intra-class correlation. In this study, we present a modification of that procedure to compare between threshold models that only differ in a bounded variable. An extra data-augmentation step is required to sample liability, an underlying continuous variable related with phenotypic records through an adequate number of thresholds. In this context, we describe a procedure to sample from a truncated multivariate normal distribution with non-null covariances between records, taking as starting point the Cholesky factorization and the inclusion of linear restrictions. The method was tested by computer simulations with satisfactory results.

Animals↗