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Results for “QTL mapping”

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PubMed1998

Quantitative genetic analysis of copia retrotransposon activity in inbred Drosophila melanogaster lines.

The rates of transcription and transposition of retrotransposons vary between lines of Drosophila melanogaster. We have studied the genetics of differences in copia retrotransposon activity by quantitative trait loci (QTL) mapping. Ninety-eight recombinant inbred lines were constructed from two parental lines exhibiting a 10-fold difference in copia transcript level and a 100-fold difference in transposition rate. The lines were scored for 126 molecular markers, copia transcript level, and rate of copia transposition. Transcript level correlated with copia copy number, and the difference in copia copy number between parental lines accounted for 45.1% of copia transcript-level difference. Most of the remaining difference was accounted for by two transcript-level QTL mapping to cytological positions 27B-30D and 50F-57C on the second chromosome, which accounted for 11.5 and 30.4%, respectively. copia transposition rate was controlled by interacting QTL mapping to the region 27B-48D on the second and 61A-65A and 97D-100A on the third chromosome. The genes controlling copia transcript level are thus not necessarily those involved in controlling copia transposition rate. Segregation of modifying genes, rather than mutations, might explain the variability in copia retrotransposon activity between lines.

Animals↗

PubMed2003

A RAPD, AFLP and SSR linkage map, and QTL analysis in European beech (Fagus sylvatica L.).

The genetic linkage map of European beech ( Fagus sylvatica L.) that we report here is the first to our knowledge. Based on a total of 312 markers (28 RAPDs, 274 AFLPs, 10 SSRs) scored in 143 individuals from a F(1) full-sib family. Two maps (one for each parent) were constructed according to a "two-way pseudo-testcross" mapping strategy. In the male map 119 markers could be clustered in 11 major groups (971 cM), while in the female map 132 markers were distributed in 12 major linkage groups (844 cM). In addition, four and one minor linkage groups (doublets and triplets) were obtained for the male and female map respectively. The two maps cover about 82% and 78% of the genome. Based on the position of 15 AFLP and 2 SSR loci segregating in both parents, seven homologous linkage groups could be identified. In the same pedigree we investigated the association with genetic markers of several quantitative traits: leaf area, leaf number and shape in 2 different years, specific leaf area, leaf carbon-isotope discrimination and tree height. A composite interval-mapping approach was used to estimate the number of QTLs, the amount of variation explained by each of them, and their position on the genetic linkage maps. Eight QTLs associated with leaf traits were found that explained between 15% and 35% of the trait variation, five on the female map and three on the male map.

Chromosome Mapping↗

PubMed2006

Confirmation of quantitative trait loci for ethanol sensitivity and neurotensin receptor density in crosses derived from the inbred high and low alcohol sensitive selectively bred rat lines.

RATIONALE: Genetically influenced alcohol sensitivity is thought to be an important risk factor for the development of alcoholism. An effective first step for identifying genes that mediate variation in alcohol sensitivity is through quantitative trait loci (QTL) mapping in model organisms. OBJECTIVE: Fourteen provisional QTLs related to alcohol sensitivity were previously mapped in an F2 derived from the IHAS1 and ILAS1 rat lines. The objective of the current study was to confirm those QTLs in an independently derived F2 and in congenics that were bred for two of the loci. MATERIALS AND METHODS: IHAS1 X ILAS1 F2 (n=450) were tested for alcohol-induced loss of righting reflex (LORR), blood ethanol concentration at regain of righting reflex (BECRR), sensitivity and acute tolerance on the Rotarod, and neurotensin receptor density (NTR1). Rats were genotyped at the 14 candidate loci and QTL mapping was conducted. Reciprocal congenic strains were bred for loci on chromosomes 2 and 5 and tested for LORR and BECRR. RESULTS: Four LORR QTLs were mapped at the suggestive or significant level (chromosomes 2, 5, 12, and 13). BECRR was mapped to chromosomes 5, 12, and 13 either in the original or current experiment. Results of the congenic experiment also support QTLs for LORR and BECRR on chromosomes 2 and 5. QTLs for NTR1 density and behavior on the Rotarod were not confirmed. CONCLUSIONS: QTL mapping in crosses derived from the IHAS1 and ILAS1 has successfully identified loci related to alcohol sensitivity. Recombinant congenics are now being bred to more finely map the confirmed QTLs.

Alcoholism↗

PubMed2006

A method for identification of the expression mode and mapping of QTL underlying embryo-specific characters.

Embryos of crop seeds are one of the major sources of the plant protein and lipid for human nutrition. The genetic expression for embryo-specific characters in crop seeds can be controlled exclusively by the embryo or the maternal genotypes and sometimes by both simultaneously. However, current methods for mapping quantitative trait loci (QTLs) underlying characters of maternal plants have not been effective in dealing with the QTL analysis of embryo characters. On the basis of the expression feature of embryo, a statistical method was proposed for the identification of expression mode and mapping of QTL controlling embryo traits. The maximum likelihood method implemented via the expectation maximization algorithm was used to estimate parameters of a putative embryo-specific QTL. The QTL expression mode was identified by the likelihood ratio test statistic. Statistical power and other properties of the proposed method were investigated under a variety of scenarios through simulation studies. The results showed that the mapping method neglecting the effects of embryo genotype or maternal effects could neither identify the expression mode of QTL nor estimate its genetic effects accurately, whereas the proposed method could effectively map the embryo-specific QTL of various expression modes.

Algorithms↗

PubMed2003

Studies of natural allele effects in mice can be used to identify genes causing common human obesity.

Although genes causing rare Mendelian forms of human obesity have provided much useful information about underlying causes of obesity, these genes do not explain significant proportions of common obesity. This review presents evidence that animal models can be used to uncover subtle genetic effects on obesity and can provide a powerful rigorous compliment to human association studies. We discuss the advantages of animal models of obesity, various approaches to discovering obesity genes, and the future of mapping and isolating naturally occurring alleles of obesity genes. We review evidence that it is important to map naturally occurring obesity genes using quantitative trait locus (QTL) mapping, instead of mutagenesis and knockout models because the latter do not allow study of interactions and because naturally occurring obesity alleles can interfere with cloning from mutagenesis projects. Because a substantial percentage of human obesity results from complex interactions, the underlying genes can only be identified by direct studies in humans, which are still very difficult, or by studies in mice that begin with QTL mapping. Finally, we emphasize that animal model studies can be used to prove that a specific gene, only associated with obesity in humans, can indeed be the underlying cause of obesity in mammals.

Animals↗

PubMed2006

Dissecting the regulation of fructan metabolism in perennial ryegrass (Lolium perenne) with quantitative trait locus mapping.

Quantitative trait locus (QTL) mapping, which can be a useful tool for dissecting complex traits, has been used here to study the regulation of fructan metabolism in temperate forage grasses. An F2 mapping family, derived from a high water-soluble carbohydrate (WSC) x low WSC cross, was used to map fructans and the other components of WSC (sucrose, glucose and fructose) in leaves and tiller bases of perennial ryegrass (Lolium perenne) in spring and autumn. To characterize regions of the genome that control basic carbohydrate metabolism, a strategy to minimize the impact of genotype (G) x environment (E), and E-effects on the characterization of G-effects, was adopted. Most traits were highly variable within the family. There was also considerable year-to-year environmental variation. However, significant genetic effects were detected, and several traits had high broad-sense heritability. QTL were identified on chromosomes 1, 2, 5 and 6. Leaf and tiller base QTL did not coincide. Individual QTL explained between 8 and 59% of the total phenotypic variation in the traits. Fructan turnover, metabolism and their genetic control, and the effect of environment, are discussed in the context of the results.

Biomarkers↗

PubMed2006

A review of statistical methods for expression quantitative trait loci mapping.

With high-throughput technologies now widely available, investigators can easily measure thousands of phenotypes for quantitative trait loci (QTL) mapping. Microarray measurements are particularly amenable to QTL mapping, as evidenced by a number of recent studies demonstrating utility across a broad range of biological endeavors. The early success stories have impelled a rapid increase in both the number and complexity of expression QTL (eQTL) experiments. Consequently, there is a need to consider the statistical principles involved in the design and analysis of these experiments and the methods currently being used. In this article we review these principles and methods and discuss the open questions most likely to yield significant progress toward increasing the amount of meaningful information obtained from eQTL mapping experiments.

Animals↗

PubMed1998

Sib mating designs for mapping quantitative trait loci.

The power to separate the variance of a quantitative trait locus (QTL) from the polygenic variance is determined by the variability of genes identical by descent (IBD) at the QTL. This variability may increase with inbreeding. Selfing, the most extreme form of inbreeding, increases the variability of the IBD value shared by siblings, and thus has a higher efficiency for QTL mapping than random mating. In self-incompatible organisms, sib mating is the closest form of inbreeding. Similar to selfing, sib mating may also increase the power of QTL detection relative to random mating. In this study, we develop an IBD-based method under sib mating designs for QTL mapping. The efficiency of sib mating is then compared with random mating. Monte Carlo simulations show that sib mating designs notably increase the power for QTL detection. When power is intermediate, the power to detect a QTL using full-sib mating is, on average, 7% higher than under random mating. In addition, the IBD-based method proposed in this paper can be used to combine data from multiple families. As a result, the estimated QTL parameters can be applied to a wide statistical inference space relating to the entire reference population.

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↗

PubMed2006

Multitrait quantitative trait Loci mapping for milk production traits in danish Holstein cattle.

The aims of this study were (1) to confirm previously identified quantitative trait loci (QTL) on bovine chromosomes 6, 11, 14, and 23 in the Danish Holstein cattle population, (2) to assess the pleiotropic nature of each QTL on milk production traits by building multitrait and multi-QTL models, and (3) to include pedigree information on nongenotyped individuals to improve the estimation of genetic parameters underlying the random QTL model. Nineteen grandsire families were analyzed by single-trait (ST) and multitrait (MT) QTL mapping methods. The variance component-based QTL mapping model was implemented via restricted maximum likelihood (REML) to estimate QTL position and parameters. Segregation of the previously identified QTL was confirmed on bovine chromosomes 6, 11, and 14, but not on 23. A highly significant (1% chromosome-wise level) QTL was found on chromosome 6, between 37 and 73 cM. This QTL had a strong effect on protein percentage (PP) and fat percentage (FP) according to ST analyses, and effects on PP, FP, milk yield (MY), fat yield (FY), and protein yield (PY) in MT analyses. A QTL affecting PP was detected on chromosome 11 (at 70 cM) using ST analysis. The MT analysis revealed a second QTL (at 67 cM) approaching significance with an effect on MY. The ST analysis identified a QTL for MY and FP on chromosome 14, between 10 and 24 cM. The extended pedigree (nongenotyped animals) was included to estimate genetic parameters underlying the random QTL model; that is, additive polygenic and QTL variances. In general, the estimates of the QTL variance components were smaller but more precise when the extended pedigree was considered in the analysis.

Animals↗

PubMed2002

[The construction of the genetic map and QTL locating analysis on chromosome 2 in swine].

The study constructed the genetic linkage map of porcine chromosome 2 and further analysis of quantitative trait loci was conducted. The results of the study demonstrated that all 7 microsatellite loci we chose were with relatively high polymorphism, and its polymorphic information content was from 0.40182 to 0.58477. The genetic map we constructed for resource family was 152.9 cM in length, with the order of all loci highly consistent with the USDA map. All marker intervals were longer than USDA map with the interval between marker Sw2516 and Sw1201 as an exception. Furthermore, we conducted QTLs locating analysis by combining the genetic map with the phenotypic data. QTLs affecting lively estimated traits such as lean meat percentage, were located at 60-65 cM on chromosome 2, while QTLs for the height and marbling of Longissmus dorsi muscle were located at 20 cM and 55 cM, respectively Among them, QTL for estimated lean meat percentage was significant at chromosome-wise level (P < 0.01) and was responsible for 21.55% of the phenotypic variance. QTLs for the height and marbling of Longissmus dorsi muscle were responsible for 10.12% and 10.97% of the phenotypic variance, respectively. The additive and dominance effect of lively estimated traits were in the inverse tendency, while the QTL for the height of Longissmus dorsi muscle had its additive and dominance effect in the same tendency and was with advantageous allele in Large White. The QTLs we detected had relatively large effect on phenotype and built a basis for molecular marker assisted selection and breeding.

Animals↗

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↗

PubMed2005

Model selection in binary trait locus mapping.

Quantitative trait locus (QTL) mapping methodology for continuous normally distributed traits is the subject of much attention in the literature. Binary trait locus (BTL) mapping in experimental populations has received much less attention. A binary trait by definition has only two possible values, and the penetrance parameter is restricted to values between zero and one. Due to this restriction, the infinitesimal model appears to come into play even when only a few loci are involved, making selection of an appropriate genetic model in BTL mapping challenging. We present a probability model for an arbitrary number of BTL and demonstrate that, given adequate sample sizes, the power for detecting loci is high under a wide range of genetic models, including most epistatic models. A novel model selection strategy based upon the underlying genetic map is employed for choosing the genetic model. We propose selecting the "best" marker from each linkage group, regardless of significance. This reduces the model space so that an efficient search for epistatic loci can be conducted without invoking stepwise model selection. This procedure can identify unlinked epistatic BTL, demonstrated by our simulations and the reanalysis of Oncorhynchus mykiss experimental data.

Animals↗

PubMed1999

Quantitative trait locus mapping of airway responsiveness to chromosomes 6 and 7 in inbred mice.

Quantitative trait locus (QTL) mapping was used to identify chromosomal regions contributing to airway hyperresponsiveness in mice. Airway responsiveness to methacholine was measured in A/J and C3H/HeJ parental strains as well as in progeny derived from crosses between these strains. QTL mapping of backcross [(A/J x C3H/HeJ) x C3H/HeJ] progeny (n = 137-227 informative mice for markers tested) revealed two significant linkages to loci on chromosomes 6 and 7. The QTL on chromosome 6 confirms the previous report by others of a linkage in this region in the same genetic backgrounds; the second QTL, on chromosome 7, represents a novel locus. In addition, we obtained suggestive evidence for linkage (logarithm of odds ratio = 1.7) on chromosome 17, which lies in the same region previously identified in a cross between A/J and C57BL/6J mice. Airway responsiveness in a cross between A/J and C3H/HeJ mice is under the control of at least two major genetic loci, with evidence for a third locus that has been previously implicated in an A/J and C57BL/6J cross; this indicates that multiple genetic factors control the expression of this phenotype.

Animals↗

PubMed2003

Genetic mapping and QTL analysis of fiber-related traits in cotton ( Gossypium).

Cotton, the leading natural fiber crop, is largely produced by two primary cultivated allotetraploid species known as Upland or American cotton ( Gossypium hirsutum L.) and Pima or Egyptian cotton ( G. barbadense L.). The allotetraploid species diverged from each other and from their diploid progenitors (A or D genome) through selection and domestication after polyploidization. To analyze cotton AD genomes and dissect agronomic traits, we have developed a genetic map in an F2 population derived from interspecific hybrids between G. hirsutum L. cv. Acala-44 and G. barbadense L. cv. Pima S-7. A total of 392 genetic loci, including 333 amplified fragment length polymorphisms (AFLPs), 47 simple sequence repeats (SSRs), and 12 restriction fragment length polymorphisms (RFLPs), were mapped in 42 linkage groups, which span 3,287 cM and cover approximately 70% of the genome. Using chromosomal aneuploid interspecific hybrids and a set of 29 RFLP and SSR framework markers, we assigned 19 linkage groups involving 223 loci to 12 chromosomes. Comparing four pairs of homoeologous chromosomes, we found that with one exception linkage distances in the A-subgenome chromosomes were larger than those in their D-subgenome homoeologues, reflecting higher recombination frequencies and/or larger chromosomes in the A subgenome. Segregation distortion was observed in 30 out of 392 loci mapped in cotton. Moreover, approximately 29% of the RFLPs behaved as dominant loci, which may result from rapid genomic changes. The cotton genetic map was used for quantitative trait loci (QTL) analysis using composite interval mapping and permutation tests. We detected seven QTLs for six fiber-related traits; five of these were distributed among A-subgenome chromosomes, the genome donor of fiber traits. The detection of QTLs in both the A subgenome in this study and the D subgenome in a previous study suggests that fiber-related traits are controlled by the genes in homoeologous genomes, which are subjected to selection and domestication. Some chromosomes contain clusters of QTLs and presumably contribute to the large amount of phenotypic variation that is present for fiber-related traits.

Chromosome Mapping↗

PubMed1999

Testing the correspondence between map positions of quantitative trait loci.

There are several instances in which quantitative trait locus (QTL) mapping experiments have been independently carried out for similar traits in different laboratories. We develop a permutation test of the correspondence between the test statistics obtained from genome-wide QTL scans in two such experiments to test whether the same QTLs are segregating in the experimental pair. In simulations, we show that the permutation test has the desired properties if chromosomes are of equal length, but bias can occur if chromosomes are of unequal length, a problem connected with autocorrelation of test statistic values. We apply the test to data from three recent mouse body weight QTL mapping experiments. The results from the test are non-significant, and imply a lack of overall concordance between the QTLs that were segregating in these experiments.

Animals↗

PubMed1999

High-resolution mapping of quantitative trait loci in outbred mice.

Screening the whole genome of a cross between two inbred animal strains has proved to be a powerful method for detecting genetic loci underlying quantitative behavioural traits, but the level of resolution offered by quantitative trait loci (QTL) mapping is still too coarse to permit molecular cloning of the genetic determinants. To achieve high-resolution mapping, we used an outbred stock of mice for which the entire genealogy is known. The heterogeneous stock (HS) was established 30 years ago from an eight-way cross of C57BL/6, BALB/c, RIII, AKR, DBA/2, I, A/J and C3H inbred mouse strains. At the time of the experiment reported here, the HS mice were at generation 58, theoretically offering at least a 30-fold increase in resolution for QTL mapping compared with a backcross or an F2 intercross. Using the HS mice we have mapped a QTL influencing a psychological trait in mice to a 0.8-cM interval on chromosome 1. This method allows simultaneous fine mapping of multiple QTLs, as shown by our report of a second QTL on chromosome 12. The high resolution possible with this approach makes QTLs accessible to positional cloning.

Animals↗

PubMed2006

Using dominance relationship coefficients based on linkage disequilibrium and linkage with a general complex pedigree to increase mapping resolution.

Dominance (intralocus allelic interactions) plays often an important role in quantitative trait variation. However, few studies about dominance in QTL mapping have been reported in outbred animal or human populations. This is because common dominance effects can be predicted mainly for many full sibs, which do not often occur in outbred or natural populations with a general pedigree. Moreover, incomplete genotypes for such a pedigree make it infeasible to estimate dominance relationship coefficients between individuals. In this study, identity-by-descent (IBD) coefficients are estimated on the basis of population-wide linkage disequilibrium (LD), which makes it possible to track dominance relationships between unrelated founders. Therefore, it is possible to use dominance effects in QTL mapping without full sibs. Incomplete genotypes with a complex pedigree and many markers can be efficiently dealt with by a Markov chain Monte Carlo method for estimating IBD and dominance relationship matrices (D(RM)). It is shown by simulation that the use of D(RM) increases the likelihood ratio at the true QTL position and the mapping accuracy and power with complete dominance, overdominance, and recessive inheritance modes when using 200 genotyped and phenotyped individuals.

Chromosome Mapping↗