Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “quantitative trait”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50Linked to original sources
PubMed1995

Interval mapping of quantitative trait loci employing correlated trait complexes.

An approach to increase the resolution power of interval mapping of quantitative trait (QT) loci is proposed, based on analysis of correlated trait complexes. For a given set of QTs, the broad sense heritability attributed to a QT locus (QTL) (say, A/a) is an increasing function of the number of traits. Thus, for some traits x and y, H(xy)2(A/a) > or = H(x)2(A/a). The last inequality holds even if y does not depend on A/a at all, but x and y are correlated within the groups AA, Aa and aa due to nongenetic factors and segregation of genes from other chromosomes. A simple relationship connects H2 (both in single trait and two-trait analysis) with the expected LOD value, ELOD = -1/2N log(1-H2). Thus, situations could exist that from the inequality H(xy)2(A/a) > or = H(x)2(A/a) a higher resolution is provided by the two-trait analysis as compared to the single-trait analysis, in spite of the increased number of parameters. Employing LOD-score procedure to simulated backcross data, we showed that the resolution power of the QTL mapping model can be elevated if correlation between QTs is taken into account. The method allows us to test numerous biologically important hypotheses concerning manifold effects of genomic segments on the defined trait complex (means, variances and correlations).

Analysis of Variance↗
PubMed1996

Less-than-additive epistatic interactions of quantitative trait loci in tomato.

Epistasis plays a role in determining the phenotype yet quantitative trait loci (QTL) mapping has uncovered little evidence for it. To address this apparent contradiction, we analyzed interactions between individual Lycopersicon pennellii chromosome segments introgressed into an otherwise homogeneous genetic background of L. esculentum (cv. M82). Ten different homozygous introgression lines, each containing from 4 to 58 cM of introgressed DNA, were crossed in a half diallele scheme. The 45 derived double heterozygotes were evaluated in the field for four yield-associated traits, along with the 10 single heterozygotes and M82. Of 180 (45 x 4) tested interactions, 28% were epistatic (P < 0.05) on both linear and geometric scales. The detected epistasis was predominantly less-than-additive, i.e., the effect of the double heterozygotes was smaller than the sum of the effects of the corresponding single heterozygotes. Epistasis was also found for homozygous linked QTL affecting fruit mass and total soluble solids. Although the frequency of epistasis was high, additivity was the major component in the interaction of pairs of QTL. We propose that the diminishing additivity of QTL effects is amplified when more loci are involved; this mode of epistasis may be an important factor in phenotype canalization and in breeding.

Epistasis, Genetic↗
PubMed2004

Multiple-interval mapping for quantitative trait loci controlling endosperm traits.

Endosperm traits are trisomic inheritant and are of great economic importance because they are usually directly related to grain quality. Mapping for quantitative trait loci (QTL) underlying endosperm traits can provide an efficient way to genetically improve grain quality. As the traditional QTL mapping methods (diploid methods) are usually designed for traits under diploid control, they are not the ideal approaches to map endosperm traits because they ignore the triploid nature of endosperm. In this article, a statistical method considering the triploid nature of endosperm (triploid method) is developed on the basis of multiple-interval mapping (MIM) to map for the underlying QTL. The proposed triploid MIM method is derived to broadly use the marker information either from only the maternal plants or from both the maternal plants and their embryos in the backcross and F2 populations for mapping endosperm traits. Due to the use of multiple intervals simultaneously to take multiple QTL into account, the triploid MIM method can provide better detection power and estimation precision, and as shown in this article it is capable of analyzing and searching for epistatic QTL directly as compared to the traditional diploid methods and current triploid methods using only one (or two) interval(s). Several important issues in endosperm trait mapping, such as the relation and differences between the diploid and triploid methods, variance components of genetic variation, and the problems if effects are present and ignored, are also addressed. Simulations are performed to further explore these issues, to investigate the relative efficiency of different experimental designs, and to evaluate the performance of the proposed and current methods in mapping endosperm traits. The MIM-based triploid method can provide a powerful tool to estimate the genetic architecture of endosperm traits and to assist the marker-assisted selection for the improvement of grain quality in crop science. The triploid MIM FORTRAN program for mapping endosperm traits is available on the worldwide web (http://www.stat.sinica.edu.tw/chkao/).

Chromosome Mapping↗
PubMed2000

Genotype-environment interaction for quantitative trait loci affecting life span in Drosophila melanogaster.

The nature of genetic variation for Drosophila longevity in a population of recombinant inbred lines was investigated by estimating quantitative genetic parameters and mapping quantitative trait loci (QTL) for adult life span in five environments: standard culture conditions, high and low temperature, and heat-shock and starvation stress. There was highly significant genetic variation for life span within each sex and environment. In the analysis of variance of life span pooled over sexes and environments, however, the significant genetic variation appeared in the genotype x sex and genotype x environment interaction terms. The genetic correlation of longevity across the sexes and environments was not significantly different from zero in these lines. We estimated map positions and effects of QTL affecting life span by linkage to highly polymorphic roo transposable element markers, using a multiple-trait composite interval mapping procedure. A minimum of 17 QTL were detected; all were sex and/or environment-specific. Ten of the QTL had sexually antagonistic or antagonistic pleiotropic effects in different environments. These data provide support for the pleiotropy theory of senescence and the hypothesis that variation for longevity might be maintained by opposing selection pressures in males and females and variable environments. Further work is necessary to assess the generality of these results, using different strains, to determine heterozygous effects and to map the life span QTL to the level of genetic loci.

Animals↗
PubMed1999

Quantitative trait loci approach to the genetics of sleep in recombinant inbred mice.

Sleep is a complex trait controlled by many genes, the environment, and probably by gene-environment interactions. Among different approaches to the genetics of sleep, analysis of quantitative traits (QTL) has the advantage of being able to detect, along with major genes, minor and/or modifier genes influencing different quantitative aspects of sleep. We have used QTL analysis in two different sets of recombinant inbred (RI) strains and sought for confirmation of several localizations in eight histocompatibility congenic strains. Several QTLs were identified which influenced the amount of vigilance states. In a first RI series (seven strains) the only QTLs identified were those affecting paradoxical sleep (PS), whereas analysis in a second RI series (25 strains) revealed QTLs influencing PS, slow-wave sleep, and total sleep. Among these, a single QTL on chromosome 5 was associated with all vigilance states, suggesting the presence of a major gene influencing a basic aspect of sleep amount. Search for candidate genes around the identified QTLs indicated several immune related genes that have been implicated in sleep regulation. Transgenic animals carrying loss-of-function and/or gain-of-function mutations affecting these candidate genes should confirm these findings.

Alleles↗
PubMed2000

Quantitative trait loci and candidate gene mapping of bud set and bud flush in populus.

The genetic control of bud phenology in hybrid poplar was studied by mapping quantitative trait loci (QTL) affecting the timing of autumn bud set and spring bud flush. The founders of the mapping pedigree were collected from widely separated latitudes to maximize segregating variation for dormancy-related traits in the F(2) generation-the female Populus trichocarpa parent is from Washington State (48 degrees N) and the male P. deltoides parent is from Texas (31 degrees N). Bud set and bud flush timing were measured on the F(2) generation in a replicated clonal field trial. Using a linkage map constructed of AFLP and microsatellite markers, three QTL controlling bud set and six QTL controlling bud flush were detected. Additionally, five candidate genes believed to be involved in perception of photoperiod (PHYB1, PHYB2) or transduction of abscisic acid response signals (ABI1B, ABI1D, and ABI3) were placed on the QTL map. PHYB2 and ABI1B were found to be coincident with QTL affecting bud set and bud flush.

Base Sequence↗
PubMed2000

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

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

Animals↗
PubMed2001

A quick method for computing approximate thresholds for quantitative trait loci detection.

This article proposes a quick method for computing approximate threshold levels that control the genome-wise type I error rate of tests for quantitative trait locus (QTL) detection in interval mapping (IM) and composite interval mapping (CIM). The procedure is completely general, allowing any population structure to be handled, e.g., BC(1), advanced backcross, F(2), and advanced intercross lines. Its main advantage is applicability in complex situations where no closed form approximate thresholds are available. Extensive simulations demonstrate that the method works well over a range of situations. Moreover, the method is computationally inexpensive and may thus be used as an alternative to permutation procedures. For given values of the likelihood-ratio (LR)-profile, computations involve just a few seconds on a Pentium PC. Computations are simple to perform, requiring only the values of the LR statistics (or LOD scores) of a QTL scan across the genome as input. For CIM, the window size and the position of cofactors are also needed. For the approximation to work well, it is suggested that scans be performed with a relatively small step size between 1 and 2 cM.

Biometry↗
PubMed2002

Exploring alternative models for sex-linked quantitative trait loci in outbred populations: application to an iberian x landrace pig intercross.

We present a very flexible method that allows us to analyze X-linked quantitative trait loci (QTL) in crosses between outbred lines. The dosage compensation phenomenon is modeled explicitly in an identity-by-descent approach. A variety of models can be fitted, ranging from considering alternative fixed alleles within the founder breeds to a model where the only genetic variation is within breeds, as well as mixed models. Different genetic variances within each founder breed can be estimated. We illustrate the method with data from an F(2) cross between Iberian x Landrace pigs for intramuscular fat content and meat color component a*. The Iberian allele exhibited a strong overdominant effect for intramuscular fat in females. There was also limited evidence of one or more regions affecting color component a*. The analysis suggested that the QTL alleles were fixed in the Iberian founders, whereas there was some evidence of segregation in Landrace for the QTL affecting a* color component.

Animals↗
PubMed2002

Meta-analysis of genetic-linkage analysis of quantitative-trait loci.

Meta-analysis is an important tool in linkage analysis. The pooling of results across primary linkage studies allows greater statistical power to detect quantitative-trait loci (QTLs) and more-precise estimation of their genetic effects and, hence, yields conclusions that are stronger relative to those of individual studies. Previous methods for the meta-analysis of linkage studies have been proposed, and, although some methods address the problem of between-study heterogeneity, most methods still require linkage analysis at the same marker or set of markers across studies, whereas others do not result in an estimate of genetic variance. In this study, we present a meta-analytic procedure to evaluate evidence from several studies that report Haseman-Elston statistics for linkage to a QTL at multiple, possibly distinct, markers on a chromosome. This technique accounts for between-study heterogeneity and estimates both the location of the QTL and the magnitude of the genetic effect more precisely than does an individual study. We also provide standard errors for the genetic effect and for the location (in cM) of the QTL, using a resampling method. The approach can be applied under other conditions, provided that the various studies use the same linkage statistic.

Computer Simulation↗
PubMed2002

Estimation of quantitative trait locus allele frequency via a modified granddaughter design.

A method is described on the basis of a modification of the granddaughter design to obtain estimates of quantitative trait loci (QTL) allele frequencies in dairy cattle populations and to determine QTL genotypes for both homozygous and heterozygous grandsires. The method is based on determining the QTL allele passed from grandsires to their maternal granddaughters using haplotypes consisting of several closely linked genetic markers. This method was applied to simulated data of 10 grandsire families, each with 500 granddaughters, and a QTL with a substitution effect of 0.4 phenotypic standard deviations and to actual data for a previously analyzed QTL in the center of chromosome 6, with substitution effect of 1 phenotypic standard deviation on protein percentage. In the simulated data the standard error for the estimated QTL substitution effect with four closely linked multiallelic markers was only 7% greater than the expected standard error with completely correct identification of QTL allele origin. The method estimated the population QTL allelic frequency as 0.64 +/- 0.07, compared to the simulated value of 0.7. In the actual data, the frequency of the allele that increases protein percentage was estimated as 0.63 +/- 0.06. In both data sets the hypothesis of equal allelic frequencies was rejected at P < 0.05.

Analysis of Variance↗
PubMed2006

Functional implication of an Arg307Gly substitution in corticosteroid-binding globulin, a candidate gene for a quantitative trait locus associated with cortisol variability and obesity in pig.

We previously reported that corticosteroid-binding globulin gene (Cbg) may be the causal gene of a quantitative trait locus associated with cortisol levels, fat deposition, and muscle content in a pig intercross. Sequence analysis of parental animals allowed us to identify four amino-acid substitutions. Here we have examined if any of these single amino acid substitutions could be responsible for the difference in CBG binding and affinity for cortisol between the parental breeds, using in vitro assays of Cbg variants after transfection of mammalian cells. Additionally, the Cbg coding region was analyzed in samples from a synthetic pig line to study association between polymorphism and CBG biochemical properties, carcass composition, and meat quality. Both in vitro transfection assays and the association studies suggest a role of the Arg307Gly mutation in increasing CBG capacity (by >70%) and decreasing CBG affinity for cortisol (by 30%). The Ile265Val substitution may also have an effect on decreasing CBG affinity for cortisol by 25%. The mutations Ser15Ile and Thr257Met do not seem to have an effect on CBG parameters. The Arg307Gly substitution was the only mutation associated with a parameter of meat quality and no mutation was linked to carcass composition.

Amino Acid Substitution↗
PubMed2003

Quantitative trait loci with opposing blood pressure effects demonstrating epistasis on Dahl rat chromosome 3.

Our previous linkage studies indicated that there might be a blood pressure (BP) quantitative trait locus (QTL) on chromosome 3 (Chr 3) contrasting between the Dahl salt-sensitive (S) strain and the Lewis (LEW) strain. To prove and then to narrow down the segment containing this QTL, five congenic strains have been generated by replacing various segments of the S rats with the homologous segments of the LEW rats. They are designated as S.L1, S.L2, S.L3, S.L4, and S.L5, respectively. S.L2, S.L3, S.L4, and S.L5 are substrains of S.L1, i.e., they contain substitutions of smaller sections within the large fragment defined by S.L1. The construction of these congenic strains was facilitated by a genome-wide marker screening process. BPs of the rats were measured by telemetry. S.L2 and S.L3 shared a fragment of Chr 3 in common and both showed a BP-lowering effect, indicating the existence of "-BP" QTL alleles from LEW compared with S. In contrast, S.L4 involves a section with no overlap with either S.L2 or S.L3, and S.L4 showed a BP significantly higher than that of S rats, indicating the presence of "+BP" QTL alleles from LEW compared with S. Interestingly, the combined effect of the -BP QTL and +BP QTL alleles was "-" in S.L1, implying that the "-" QTL is epistatic to "+" QTL.

Animals↗
PubMed2002

The effects of selected sampling on the transmission disequilibrium test of a quantitative trait locus.

We investigate how sampling of parents or children based on their extreme phenotypic values selected from clinical databases would affect the power of identification of quantitative trait loci (QTL) by a transmission disequilibrium test (TDT). We consider three selective sampling schemes based on the selection of phenotypic values of parents or children in nuclear families: (1) two children, one of extreme value, the other random; (2) two children extremely discordant; (3) one parent of extreme value. Other family members not specified will be recruited randomly with regard to phenotypic values. Our study shows that the second sampling scheme can always enhance the power for QTL identification, sometimes dramatically so. The increase in the statistical power of the TDT is particularly dramatic when h2 at the QTL under test is small or intermediate (e.g. 0.05 or 0.10). For the other two sampling schemes, under dominant effects at the QTL, the power is always increased relative to random sampling; however, under recessive or additive genetic effects, the power gain is generally minor or even decreased a little sometimes. Allele frequencies at the QTL and the selection stringency are important for determining the effect of selective sampling on the power of QTL identification. Our study is useful as a practical guideline on how to perform the TDT efficiently in practice by taking advantage of the extensive databases accumulated that are enriched with people of extreme phenotypic values.

Disease Transmission, Infectious↗
PubMed2006

High-resolution quantitative trait locus mapping reveals sign epistasis controlling ovariole number between two Drosophila species.

Identifying the genes underlying genetically complex traits is of fundamental importance for medicine, agriculture, and evolutionary biology. However, the level of resolution offered by traditional quantitative trait locus (QTL) mapping is usually coarse. We analyze here a trait closely related to fitness, ovariole number. Our initial interspecific mapping between Drosophila sechellia (8 ovarioles/ovary) and D. simulans (15 ovarioles/ovary) identified a major QTL on chromosome 3 and a minor QTL on chromosome 2. To refine the position of the major QTL, we selected 1038 additional recombinants in the region of interest using flanking morphological markers (selective phenotyping). This effort generated approximately one recombination event per gene and increased the mapping resolution by approximately seven times. Our study thus shows that using visible markers to select for recombinants can efficiently increase the resolution of QTL mapping. We resolved the major QTL into two epistatic QTL, QTL3a and QTL3b. QTL3a shows sign epistasis: it has opposite effects in two different genetic backgrounds, the presence vs. the absence of the QTL3b D. sechellia allele. This property of QTL3a allows us to reconstruct the probable order of fixation of the QTL alleles during evolution.

Animals↗
PubMed2005

Pedigree linkage disequilibrium mapping of quantitative trait loci.

In this paper, we propose to use pedigrees of any size and any types of relatives in joint high-resolution linkage disequilibrium (LD) and linkage mapping of quantitative trait loci (QTL) by variance component models. Two or multiple markers can be simultaneously used in modeling association with the trait locus, instead of using one marker a time in the analysis. The proposed method can provide a unified result by using two or multiple markers in the modeling. This may avoid the complications of different results obtained from the separate analysis of marker by marker. The models simultaneously incorporate both linkage and LD information. The measures of LD are modeled by mean coefficients, and linkage information is modeled by variance-covariance matrix. Using analytical formulas to calculate the regression coefficients, the genetic effects are shown to be decomposed into additive and dominance components. The noncentrality parameter approximations of test statistics of LD are provided to make power calculations. Power and type I error rates are explored to investigate the merit of the proposed method by both the analytical formulas and simulations. Comparing with the association between-family and association within-family ('AbAw') approach of Fulker and Abecasis et al, it is evident that the method proposed in this article is more powerful. The method is applied to investigate the relation between polymorphisms in the angiotensin 1-converting enzyme (ACE) genes and circulating ACE levels, with a better result than that of the 'AbAw' approach. Moreover, two markers I/D and 4656(CT)3/2 can fully interpret association with the trait locus at a 0.01 significance level, which provides a unique result for the ACE data.

Animals↗
PubMed2006

An integrative approach for the identification of quantitative trait loci.

The genetic dissection of complex traits is one of the most difficult and most important challenges facing science today. We discuss here an integrative approach to quantitative trait loci (QTL) mapping in mice. This approach makes use of the wealth of genetic tools available in mice, as well as the recent advances in genome sequence data already available for a number of inbred mouse strains. We have developed mapping strategies that allow a stepwise narrowing of a QTL mapping interval, prioritizing candidate genes for further analysis with the potential of identifying the most probable candidate gene for the given trait. This approach integrates traditional mapping tools, fine mapping tools, sequence-based analysis, bioinformatics and gene expression.

Animals↗
PubMed2003

Molecular mapping in tropical maize (Zea mays L.) using microsatellite markers. 2. Quantitative trait loci (QTL) for grain yield, plant height, ear height and grain moisture.

A previous genetic map containing 117 microsatellite loci and 400 F(2) plants was used for quantitative trait loci (QTL) mapping in tropical maize. QTL were characterized in a population of 400 F(2:3) lines, derived from selfing the F(2) plants, and were evaluated with two replications in five environments. QTL determinations were made from the mean of these five environments. Grain yield (GY), plant height (PH), ear height (EH) and grain moisture (GM) were measured. Variance components for genotypes (G), environments (E) and GxE interaction were highly significant for all traits. Heritability was 0.69 for GY, 0.66 for PH, 0.67 for EH and 0.23 for GM. Using composite interval mapping (CIM), a total of 13 distinct QTLs were identified: four for GY, four for PH and five for EH. No QTL was detected for GM. The QTL explained 32.73 % of the phenotypic variance of GY, 24.76 % of PH and 20.91 % of EH. The 13 QTLs displayed mostly partial dominance or overdominance gene action and mapped to chromosomes 1, 2, 7, 8 and 9. Most QTL alleles conferring high values for the traits came from line L-14-4B. Mapping analysis identified genomic regions associated with two or more traits in a manner that was consistent with correlation among traits, supporting either pleiotropy or tight linkage among QTL. The low number of QTLs found, can be due to the great variation that exists among tropical environments.

Microsatellite Repeats↗