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At least 433 records · Page 24Linked to original sources
PubMed1998

Identification of two quantitative trait loci involved in antibody production on mouse chromosome 8.

Several quantitative trait loci (QTLs) contributing to the extreme phenotypes of the selected high (H) and low (L) antibody-responder lines of mice were mapped on distinct chromosomes. Successive backcrosses were bred to reduce the length of the QTL-bearing segment detected on chromosome 8 and to produce congenic lines to test gene effect independently of the other QTLs. An increase in antibody responses was repeatedly found to be associated with inheritance of the H-line allele at two markers separated by 30 cM on that chromosome. In the successive backcrosses, background and unlinked involved genes of H-line origin were progressively eliminated; however, unexpected within-progeny variations persisted in the third and even fourth backcross. Nevertheless, the presence of two QTLs within the considered interval was definitely demonstrated in distinct progenies of the fourth backcross which separately inherited one of the two gene-marker H-line alleles. The previously identified chromosome 8 segment therefore contains at least two QTLs involved in antibody responsiveness.

Animals↗
PubMed2002

Improving the power of sib pair quantitative trait loci detection by phenotype winsorization.

OBJECTIVES: In sib pair studies, quantitative trait loci (QTL) identification may be adversely affected by non-normality in the phenotypic distribution, particularly when subjects falling in the tails of the distribution bias the trait mean or variance. We evaluated the robustness and power of reducing the influence of subjects with extreme phenotypic values by Winsorizing non-normal distributions in three versions of Haseman-Elston regression-based methods of QTL linkage analysis. METHODS: Data were simulated for normal and non-normal distributions. Phenotypic values that correspond to cutoff points at the omega and 1 - omega percentiles of the distribution were identified, and phenotypic values falling outside the boundaries of the omega and 1 - omega cutoff points were replaced by the omega and 1 - omega values, respectively. One million replications were performed for the three tests of linkage for Winsorized and non-Winsorized data. RESULTS: Winsorization reduced conservatism in the tails of the empirical type I error rate for the vast majority of the tests of linkage, increased the power of QTL detection in non-normal data and created a slight negative bias in symmetrical phenotypic distributions. CONCLUSIONS: Winsorizing can improve the power of QTL detection with certain non-normal distributions but can also introduce bias into the estimate of the QTL effect.

Genetic Predisposition to Disease↗
PubMed1998

Multipoint quantitative-trait linkage analysis in general pedigrees.

Multipoint linkage analysis of quantitative-trait loci (QTLs) has previously been restricted to sibships and small pedigrees. In this article, we show how variance-component linkage methods can be used in pedigrees of arbitrary size and complexity, and we develop a general framework for multipoint identity-by-descent (IBD) probability calculations. We extend the sib-pair multipoint mapping approach of Fulker et al. to general relative pairs. This multipoint IBD method uses the proportion of alleles shared identical by descent at genotyped loci to estimate IBD sharing at arbitrary points along a chromosome for each relative pair. We have derived correlations in IBD sharing as a function of chromosomal distance for relative pairs in general pedigrees and provide a simple framework whereby these correlations can be easily obtained for any relative pair related by a single line of descent or by multiple independent lines of descent. Once calculated, the multipoint relative-pair IBDs can be utilized in variance-component linkage analysis, which considers the likelihood of the entire pedigree jointly. Examples are given that use simulated data, demonstrating both the accuracy of QTL localization and the increase in power provided by multipoint analysis with 5-, 10-, and 20-cM marker maps. The general pedigree variance component and IBD estimation methods have been implemented in the SOLAR (Sequential Oligogenic Linkage Analysis Routines) computer package.

Computer Simulation↗
PubMed2001

Affected sibling pair linkage analysis of qualitative and quantitative traits for schizophrenia on chromosome 22 in a Chinese population.

We performed nonparametric linkage analysis on 136 families with two or more siblings with schizophrenia from Sichuan, southwestern China. In addition to categorical diagnosis, we used quantitative trait information from the Positive and Negative Symptom Scale and the modified Overt Aggression Scale. Categorical analysis using the diagnosis of schizophrenia and a maximum likelihood identity-by-descent method produced scores of close to 0 throughout the whole region tested. Multipoint analysis allowed exclusion of most markers with a relative risk of > 2, but did not exclude the possibility of a relative risk of < 1.5 for four of the markers. Our results provide no significant evidence for a locus for schizophrenia on chromosome 22. Quantitative linkage analysis using the PANSS-G scale score produced a maximum LOD score of approximately 1.2 with the marker D22S310, using either the Haseman-Elston method or maximum likelihood variance estimation with or without dominance. PANSS-N produced a maximum LOD score of 1.2 at the D22S283 locus. LOD score of about 1 are easily produced by chance. Thus, we conclude that under quantitative trait we also find no evidence of linkage between schizophrenia and markers on chromosome 22 in our Chinese sibling pair sample.

Adolescent↗
PubMed2006

PAPPA2, an enzyme that cleaves an insulin-like growth-factor-binding protein, is a candidate gene for a quantitative trait locus affecting body size in mice.

Identifying genes responsible for quantitative variation remains a major challenge. We previously identified a quantitative trait locus (QTL) affecting body size that segregated between two inbred strains of mice. By fine mapping, we have refined the location of this QTL to a genomic region containing only four protein-coding genes. One of these genes, PAPPA2, is a strong candidate because it codes for an enzyme that cleaves insulin-like growth-factor-binding protein 5 (IGFBP-5), an important stimulator of bone formation. Among littermates that segregate only for the four-gene region, we show that the QTL has a significant effect on the circulating levels of IGFBP-5 and IGFBP-3 (the latter subject to limited degradation by PAPPA2), but not on levels of IGFBP-2 and IGFBP-4, which are not cleaved by PAPPA2. There are 14 nonsynonymous SNPs among QTL alleles, which may affect the activity of the translated protein. The refinement of the target region to four genes and the finding that the QTL affects IGFBP-5 levels suggest that PAPPA2 may be involved with normal postnatal growth. Our mapping results also illustrate the potentially fractal nature of QTL: as we mapped our QTL with increasing resolution, what appeared to be a single QTL resolved into three closely linked QTL (previous work), and then one of these was further dissected into two in this study.

Animals↗
PubMed2004

Mapping quantitative traits with random and with ascertained sibships.

Use of a robust score statistic based on a variance components model to map quantitative trait loci in randomly sampled pedigrees is reviewed. Sibships ascertained through a single proband are discussed. Under a standard assumption of multivariate normality, two suggested methods of ascertainment correction are shown to be asymptotically equivalent when the number of sibships is large.

Chromosome Mapping↗
PubMed2001

A new nonparametric linkage statistic for mapping both qualitative and quantitative trait loci.

We describe an alternative nonparametric linkage (NPL) statistic to that of Kruglyak et al. [Am. J. Hum. Genet. 58:1347-63, 1996] that can be used with qualitative phenotypes, and is easily extended for use with quantitative phenotypes. We analyzed the Genetic Analysis Workshop 12 simulated isolated population data, replicate 1, using two phenotypes; affected status (AFF) a dichotomous phenotype and quantitative trait Q5, which was chosen since it was the most strongly associated with AFF. One false positive significant NPL score was observed for the AFF phenotype. For Q5 a single region on chromosome 1 reached genome-wide significance. The peak of this signal was for marker D01G137 at 135.1 cM with a quantitative trait locus (QTL)-NPL score of 4.19. The nearest marker to the true location of the major gene (MG5 at 137.1 cM) was D01G139 at position 135.8 cM, where the QTL-NPL score was still high at 4.08.

Chromosome Mapping↗
PubMed2002

Mapping quantitative trait loci with epistatic effects.

Epistatic variance can be an important source of variation for complex traits. However, detecting epistatic effects is difficult primarily due to insufficient sample sizes and lack of robust statistical methods. In this paper, we develop a Bayesian method to map multiple quantitative trait loci (QTLs) with epistatic effects. The method can map QTLs in complicated mating designs derived from the cross of two inbred lines. In addition to mapping QTLs for quantitative traits, the proposed method can even map genes underlying binary traits such as disease susceptibility using the threshold model. The parameters of interest are various QTL effects, including additive, dominance and epistatic effects of QTLs, the locations of identified QTLs and even the number of QTLs. When the number of QTLs is treated as an unknown parameter, the dimension of the model becomes a variable. This requires the reversible jump Markov chain Monte Carlo algorithm. The utility of the proposed method is demonstrated through analysis of simulation data.

Algorithms↗
PubMed1993

Extended multipoint identity-by-descent analysis of human quantitative traits: efficiency, power, and modeling considerations.

Goldgar introduced a novel marker-based method for partitioning the variation of a quantitative trait into specific chromosomal regions. Unlike traditional linkage mapping methods, Goldgar's method does not require the estimation of statistical quantities characterizing each locus thought to influence the trait under scrutiny (e.g., allele frequencies, penetrances, etc.). Goldgar's method is thus more flexible and less model dependent than many traditional marker-based genetic analysis techniques. Unfortunately, however, many of the properties of Goldgar's method have not been investigated. In this paper, the utility of an extended version of Goldgar's approach is studied in settings in which sibships are taken as the sampling unit of interest. The extensions discussed resolve around the incorporation of a wider variety of effects and factors into Goldgar's basic model. Analytic studies pertaining to power, sample-size requirements, and estimation procedures for the proposed extended version of Goldgar's method are described. Hypothesis-testing strategies are also discussed. The results of the analytic studies indicate that, although an extended sib-pair version of Goldgar's variance-partitioning approach to modeling the chromosomal determinants of a quantitative trait will be useful only for traits with high heritabilities or when fine-scale genetic maps can be employed. Goldgar's technique as a whole has promise, as it can be made relatively robust statistically, refined through some simple and intuitive extensions, and can be easily adapted to work with more complex sampling units. Further extensions of Goldgar's methods are proposed, and areas in need of additional research are discussed.

Genetic Markers↗
PubMed2006

Quantitative trait loci analysis of egg and meat production traits in a red junglefowlxWhite Leghorn cross.

Egg and production traits are of considerable economic importance in chickens. Using a White Leghorn x red junglefowl F(2) intercross, standard production measures of liver weight and colour, egg size, eggshell thickness, egg taste and meat quality were taken. A total of 160 markers covering 29 autosomes and the Z chromosome were genotyped on 175-243 individuals, depending on the trait under consideration. A total of nine significant quantitative trait loci (QTL) and three suggestive QTL were found on chicken chromosomes 1, 2, 4, 5, 7, 8, 10, 12, E47W24 and E22C19W28.

Animals↗
PubMed2000

Power comparison of regression methods to test quantitative traits for association and linkage.

George et al. [1999 Am J Hum Genet 65:236-245] proposed a regression-based TDT method for quantitative traits consisting of regressing the trait on the parental transmission of a marker allele. Zhu and Elston [2000] also developed a TDT method for quantitative traits by defining a linear transformation to condition out founder information. Both methods test the null hypothesis of no linkage or association and can be applied to general pedigree structures. In this paper, we compare the power of these two methods through simulation, sampling those nuclear families with at least one heterozygous parent. Overall, we find that a variant of Zhu and Elston's method with 2 d.f. is more powerful. However, if the mode of inheritance is known, then a most powerful test with 1 d.f. can be found. All these regression TDT tests require linkage to detect association, but a test that does not require linkage will be more powerful.

Alleles↗
PubMed2006

Nonparametric trend statistic incorporating dispersion differences in sib pair linkage for quantitative traits.

The Haseman-Elston (HE) regression method and its extensions are widely used in genetic studies for detecting linkage to quantitative trait loci (QTL) using sib pairs. The principle underlying the simple HE regression method is that the similarity in phenotypes between two siblings increases as they share an increasing number of alleles identical by descent (IBD) from their parents at a particular marker locus. In such a procedure, similarity was identified with the locations, that is, means of groups of sib pairs sharing 0, 1, and 2 alleles IBD. A more powerful, rank-based nonparametric test to detect increasing similarity in sib pairs is presented by combining univariate trend statistics not only of locations, but also of dispersions of the squared phenotypic differences of two siblings for three groups. This trend test does not rely on distributional assumptions, and is applicable to the skewed or leptokurtic phenotypic distributions, in addition to normal or near normal phenotypic distributions. The performances of nonparametric trend statistics, including nonparametric regression slope, are compared with the HE regression methods as genetic linkage strategies.

Computer Simulation↗
PubMed2001

Assessment of the ratio of pollen to seed flow in a cline for genetic variation in a quantitative trait.

A dispersal-selection cline model is analysed to evaluate the role of the ratio of pollen to seed flow (r) in spatial genetic variation, with a focus on clines in additive and dominant variances of major genes affecting a quantitative trait, assuming one locus with two alleles, no genetic drift and no mutation. It is shown that under weak selection, steady-state departures from the value at Hardy-Weinberg equilibrium (HWE) for genotype frequency (D) and additive variance (DeltaVa) generally display a small value on one side of the selection boundary point, a high value around the point, and a moderate value on the other side of the boundary point. A large value of r can enhance formation of this pattern. However, this is not the case for clines in the average effect of a gene substitution (Deltaalpha) or in dominance variance (DeltaVd), where large values of r can eradicate the clines. Direct use of their values at HWE to approximate the real case is acceptable. There is an expected turning point that divides clines of either additive variance or dominance variance into two subclines, each with a shorter width than that of allele frequency. Integration of these properties can help to indicate the existence of major genes affecting a quantitative trait.

Gene Frequency↗
PubMed1992

The use of CXB recombinant inbred mice to detect quantitative trait loci in behavior.

Although recombinant inbred (RI) series of mice have been developed to identify and map single-gene characteristics, they can also be used to identify quantitative trait loci (QTL) that account for small amounts of variance in quantitative traits such as behavior. We applied an RI QTL approach to the analysis of published behavioral data from seven studies that used the CXB RI series of mice. Nearly all of the behaviors showed strain distribution patterns indicative of multiple-gene rather than single-gene influence. Although the CXB series is limited to seven RI strains, RI QTL association analysis suggests QTL candidate markers for several behaviors, including avoidance and exploration.

Animals↗
PubMed2003

"Are we there yet?": Deciding when one has demonstrated specific genetic causation in complex diseases and quantitative traits.

Although mathematical relationships can be proven by deductive logic, biological relationships can only be inferred from empirical observations. This is a distinct disadvantage for those of us who strive to identify the genes involved in complex diseases and quantitative traits. If causation cannot be proven, however, what does constitute sufficient evidence for causation? The philosopher Karl Popper said, "Our belief in a hypothesis can have no stronger basis than our repeated unsuccessful critical attempts to refute it." We believe that to establish causation, as scientists, we must make a serious attempt to refute our own hypotheses and to eliminate all known sources of bias before association becomes causation. In addition, we suggest that investigators must provide sufficient data and evidence of their unsuccessful efforts to find any confounding biases. In this editorial, we discuss what "causation" means in the context of complex diseases and quantitative traits, and we suggest guidelines for steps that may be taken to address possible confounders of association before polymorphisms may be called "causative."

Cystic Fibrosis↗
PubMed2006

Identification, isolation and pyramiding of quantitative trait loci for rice breeding.

Many agronomically important traits are governed by several genes known as quantitative trait loci (QTLs). The identification of important, QTL-controlled agricultural traits has been difficult because of their complex inheritance; however, completion of the rice genomic sequence has facilitated the cloning of QTLs and their pyramiding for breeding. Because QTLs are derived from natural variation, the use of a wider range of variations such as that found in wild species is important. In addition, Introgression Lines (ILs) developed from wild species in combination with Marker Assisted Selection should facilitate efficient gene identification. This review describes recent developments in rice QTL analysis including mapping, cloning and pyramiding QTLs.

Breeding↗
PubMed2005

Isolation of a rice regeneration quantitative trait loci gene and its application to transformation systems.

Regeneration of plant organs is often the essential step in genetic transformation; however, the regeneration ability of a plant varies depending on the genetic background. By conventional crosses of low-regeneration rice strain Koshihikari with high-regeneration rice strain Kasalath, we identified some quantitative trait loci, which control the regeneration ability in rice. Using a map-based cloning strategy, we isolated a main quantitative trait loci gene encoding ferredoxin-nitrite reductase (NiR) that determines regeneration ability in rice. Molecular analyses revealed that the poor regeneration ability of Koshihikari is caused by lower expression than in Kasalath and the specific activity of NiR. Using the NiR gene as a selection marker, we succeeded in selectively transforming a foreign gene into rice without exogenous marker genes. Our results demonstrate that nitrate assimilation is an important process in rice regeneration and also provide an additional selectable marker for rice transformation.

Amino Acid Sequence↗
PubMed1995

Major quantitative trait loci affecting honey bee foraging behavior.

We identified two genomic regions that affect the amount of pollen stored in honey bee colonies and influence whether foragers will collect pollen or nectar. We selected for the amount of pollen stored in combs of honey bee colonies, a colony-level trait, and then used random amplified polymorphic DNA (RAPD) markers and interval mapping procedures with data from backcross colonies to identify two quantitative trait loci (pln1 and pln2, LOD 3.1 and 2.3, respectively). Quantitative trait loci effects were confirmed in a separate cross by demonstrating the cosegregation of marker alleles with the foraging behavior of individual workers. Both pln1 and pln2 had an effect on the amount of pollen carried by foragers returning to the colony, as inferred by the association between linked RAPD marker alleles, D8-.3f and 301-.55, and the individual pollen load weights of returning foragers. The alleles of the two marker loci were nonrandomly distributed with respect to foraging task. The two loci appeared to have different effects on foraging behavior. Individuals with alternative alleles for the marker linked to pln2 (but not pln1) differed with respect to the nectar sugar concentration of their nectar loads.

Animals↗