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PubMed2004

Quantitative trait loci affecting dengue midgut infection barriers in an advanced intercross line of Aedes aegypti.

Quantitative trait loci (QTL) affecting the ability of the Aedes aegypti midgut to become infected with Dengue 2 virus (DEN2) were mapped in the F5 generation of an advanced intercross line (AIL). A strain of Ae. aegypti previously selected for DEN2 susceptibility was crossed to a new strain selected for refractoriness to midgut infection. In P1 and F1 parents and 147 F5 offspring, genotypes at forty-four cDNA loci were analysed. A new sex linked QTL and a second QTL on chromosome II with genotypes subject to balancing selection were detected that condition midgut susceptibility. Alleles at these QTL contributed additively in determining susceptibility and accounted for approximately 24% of the phenotypic variance. Markers associated with a midgut escape barrier were inconsistently supported.

Aedes↗
PubMed1998

A nonparametric bootstrap method for testing close linkage vs. pleiotropy of coincident quantitative trait loci.

A novel method using the nonparametric bootstrap is proposed for testing whether a quantitative trait locus (QTL) at one chromosomal position could explain effects on two separate traits. If the single-QTL hypothesis is accepted, pleiotropy could explain the effect on two traits. If it is rejected, then the effects on two traits are due to linked QTLs. The method can be used in conjunction with several QTL mapping methods as long as they provide a straightforward estimate of the number of QTLs detectable from the data set. A selection step was introduced in the bootstrap procedure to reduce the conservativeness of the test of close linkage vs. pleiotropy, so that the erroneous rejection of the null hypothesis of pleiotropy only happens at a frequency equal to the nominal type I error risk specified by the user. The approach was assessed using computer simulations and proved to be relatively unbiased and robust over the range of genetic situations tested. An example of its application on a real data set from a saline stress experiment performed on a recombinant population of wheat (Triticum aestivum L. ) doubled haploid lines is also provided.

Computer Simulation↗
PubMed2000

Localization of a quantitative trait locus via a Bayesian approach.

A Bayesian approach to the direct mapping of a quantitative trait locus (QTL), fully utilizing information from multiple linked gene markers, is presented in this paper. The joint posterior distribution (a mixture distribution modeling the linkage between a biallelic QTL and N gene markers) is computationally challenging and invites exploration via Markov chain Monte Carlo methods. The parameter's complete marginal posterior densities are obtained, allowing a diverse range of inferences. Parameters estimated include the QTL genotype probabilities for the sires and the offspring, the allele frequencies for the QTL, and the position and additive and dominance effects of the QTL. The methodology is applied through simulation to a half-sib design to form an outbred pedigree structure where there is an entire class of missing information. The capacity of the technique to accurately estimate parameters is examined for a range of scenarios.

Algorithms↗
PubMedDate not supplied

A method to optimize selection on multiple identified quantitative trait loci.

A mathematical approach was developed to model and optimize selection on multiple known quantitative trait loci (QTL) and polygenic estimated breeding values in order to maximize a weighted sum of responses to selection over multiple generations. The model allows for linkage between QTL with multiple alleles and arbitrary genetic effects, including dominance, epistasis, and gametic imprinting. Gametic phase disequilibrium between the QTL and between the QTL and polygenes is modeled but polygenic variance is assumed constant. Breeding programs with discrete generations, differential selection of males and females and random mating of selected parents are modeled. Polygenic EBV obtained from best linear unbiased prediction models can be accommodated. The problem was formulated as a multiple-stage optimal control problem and an iterative approach was developed for its solution. The method can be used to develop and evaluate optimal strategies for selection on multiple QTL for a wide range of situations and genetic models.

Animals↗
PubMed2000

Maximum likelihood analysis of quantitative trait loci under selective genotyping.

Selective genotyping is a cost-saving strategy in mapping quantitative trait loci (QTLs). When the proportion of individuals selected for genotyping is low, the majority of the individuals are not genotyped, but their phenotypic values, if available, are still included in the data analysis to correct the bias in parameter estimation. These ungenotyped individuals do not contribute much information about linkage analysis and their inclusion can substantially increase the computational burden. For multiple trait analysis, ungenotyped individuals may not have a full array of phenotypic measurements. In this case, unbiased estimation of QTL effects using current methods seems to be impossible. In this study, we develop a maximum likelihood method of QTL mapping under selective genotyping using only the phenotypic values of genotyped individuals. Compared with the full data analysis (using all phenotypic values), the proposed method performs well. We derive an expectation-maximization (EM) algorithm that appears to be a simple modification of the existing EM algorithm for standard interval mapping. The new method can be readily incorporated into a standard QTL mapping software, e.g. MAPMAKER. A general recommendation is that whenever full data analysis is possible, the full maximum likelihood analysis should be performed. If it is impossible to analyse the full data, e.g. sample sizes are too large, phenotypic values of ungenotyped individuals are missing or composite interval mapping is to be performed, the proposed method can be applied.

Algorithms↗
PubMed2004

Mapping of multiple quantitative trait loci affecting bovine spongiform encephalopathy.

A whole-genome scan was conducted to map quantitative trait loci (QTL) for BSE resistance or susceptibility. Cows from four half-sib families were included and 173 microsatellite markers were used to construct a 2835-cM (Kosambi) linkage map covering 29 autosomes and the pseudoautosomal region of the sex chromosome. Interval mapping by linear regression was applied and extended to a multiple-QTL analysis approach that used identified QTL on other chromosomes as cofactors to increase mapping power. In the multiple-QTL analysis, two genome-wide significant QTL (BTA17 and X/Y(ps)) and four genome-wide suggestive QTL (BTA1, 6, 13, and 19) were revealed. The QTL identified here using linkage analysis do not overlap with regions previously identified using TDT analysis. One factor that may explain the disparity between the results is that a more extensive data set was used in the present study. Furthermore, methodological differences between TDT and linkage analyses may affect the power of these approaches.

Animals↗
PubMed2000

Power of linkage versus association analysis of quantitative traits, by use of variance-components models, for sibship data.

Optimal design of quantitative-trait loci (QTL) mapping studies requires a precise understanding of the power of QTL linkage versus QTL association analysis, under a range of different conditions. In this article, we investigate the power of QTL linkage and association analyses for simple random sibship samples, under the variance-components model proposed by Fulker et al. After a brief description of an extension of this variance-components model, we show that the powers of both linkage and association analyses are crucially dependent on the proportion of phenotypic variance attributable to the QTL. The main difference between the two tests is that, whereas the power of association is directly related to the QTL heritability, the power of linkage is related more closely to the square of the QTL heritability. We also describe both how the power of linkage is attenuated by incomplete linkage and incomplete marker information and how the power of association is attenuated by incomplete linkage disequilibrium.

Chi-Square Distribution↗
PubMed1999

Two blood pressure/cardiac mass quantitative trait loci on chromosome 3 in Dahl rats.

Interval mapping was used to identify putative quantitative trait loci (QTL) for blood pressure and cardiac mass on Chromosome (Chr) 3 in F1(S x R) x S population of 150 rats raised on an 8% NaCl diet. Two genetic markers 95.7 cM apart, D3Wox3 and D3Mco5 (tightly linked to Edn3), showed "suggestive" linkage to blood pressure (LOD = 2.0 and 1.8 respectively). In addition, D3Wox3 showed "suggestive" linkage to heart weight (LOD = 2.5), and D3Mco5 showed "suggestive" linkage to body weight-adjusted heart weight (LOD = 2.1). Congenic rats (designated S.R-Edn3) were constructed by introgressing the R-rat Edn3 allele (and flanking loci) into the S strain. On a 2% NaCl diet, S.R-Edn3 rats had lower blood pressure (21.4 mm Hg, P = 0. 0005) and heart weight (59 mg, P = 0.0038) compared with S rats, confirming the existence of a blood pressure QTL on Chr 3 near Edn3 even though QTL linkage analysis of blood pressure did not achieve stringent statistical criteria for significance. The results of the congenic experiment and the large distance between the two putative QTL suggest the presence of at least two independent blood pressure/cardiac mass QTL detectable on Chr 3 in the Dahl rat model of genetic hypertension.

Analysis of Variance↗
PubMed2006

Strategy for mapping quantitative trait loci (QTL) by using human metapopulations.

AIM: To present a novel strategy for mapping quantitative trait loci (QTL), using human metapopulations. The strategy is based on the expectation that in geographic clusters of small and distinct human isolates, a combination of founder effect and genetic drift can dramatically increase population frequency of rare QTL variants with large effect. In such cases, the distribution of QT measurements in an (affected) isolate is expected to deviate from that observed in neighboring isolates. METHODS: We tested this hypothesis in 9 villages from a larger Croatian isolate resource, where 7 Mendelian disorders have been previously reported. The values of 10 physiological and biochemical QTs were measured in a random sample of 1001 individuals (100 inhabitants of each of 9 villages and 101 immigrant controls). RESULTS: Significant over- or under- representation of individuals from specific villages in extreme ends of standardized QT measurement distribution was found 10 times more frequently than expected by chance. The large majority of such clusters of individuals with extreme QT values (34/36, 94.4%) originated from the 6 villages with the most pronounced geographic isolation and endogamy. CONCLUSION: Early epidemiological assessment supports the feasibility of the proposed strategy. Clusters of individuals with extreme QT values responsible for over-representation of single villages can usually be linked to a larger pedigree and may be useful for further QTL mapping, using linkage analysis.

Body Height↗
PubMed2003

Quantitative trait locus mapping of pyrethroid resistance in Colorado potato beetle, Leptinotarsa decemlineata (Say) (Coleoptera: Chrysomelidae).

Quantitative trait locus (QTL) mapping is a valuable new tool for locating genomic regions that underlie variation in important traits such as insecticide resistance. Because QTL mapping complements a candidate gene strategy for understanding the genetic architecture of important traits, it may also facilitate the identification of genes causing important variation. After mapping the QTL locations, markers closely linked to QTL can be used for genetic analysis of population structure and to measure the spread and increase of resistance-causing QTL alleles. In this study, QTL influencing resistance to the pyrethroid insecticide esfenvalerate were mapped in the Colorado potato beetle Leptinotarsa decemlineata (Say) (CPB). Three QTL contributing to esfenvalerate resistance were identified from a mapping population of 79 individuals analyzed at 90 marker loci. One QTL had a large effect and two QTL had smaller effects. The major QTL occurs on the X chromosome, overlapping the position of a candidate gene (Leptinotarsa decemlineata Voltage sensitive sodium channel [LdVssc1]) previously implicated in pyrethroid resistance. Resistance-increasing alleles at the two minor-effect QTL originated with the susceptible parent, suggesting that alleles of small effect may be segregating in susceptible populations. Comparison of the New York population from which the susceptible parent originated with a more-susceptible population from North Carolina suggests that the minor-effect loci identified here may explain some of the variation in tolerance observed among susceptible populations. DNA sequencing of a portion of LdVssc1 shows that the resistance-conferring allele from the resistant parent does not contain the kdr mutation previously found in CPB and typically observed in other insects that are resistant to pyrethroid insecticides because of changes in this gene.

Animals↗
PubMed2000

Quantitative trait loci that control vector competence for dengue-2 virus in the mosquito Aedes aegypti.

Quantitative trait loci (QTL) affecting the ability of the mosquito Aedes aegypti to become infected with dengue-2 virus were mapped in an F(1) intercross. Dengue-susceptible A. aegypti aegypti were crossed with dengue refractory A. aegypti formosus. F(2) offspring were analyzed for midgut infection and escape barriers. In P(1) and F(1) parents and in 207 F(2) individuals, regions of 14 cDNA loci were analyzed with single-strand conformation polymorphism analysis to identify and orient linkage groups with respect to chromosomes I-III. Genotypes were also scored at 57 RAPD-SSCP loci, 5 (TAG)(n) microsatellite loci, and 6 sequence-tagged RAPD loci. Dengue infection phenotypes were scored in 86 F(2) females. Two QTL for a midgut infection barrier were detected with standard and composite interval mapping on chromosomes II and III that accounted for approximately 30% of the phenotypic variance (sigma(2)(p)) in dengue infection and these accounted for 44 and 56%, respectively, of the overall genetic variance (sigma(2)(g)). QTL of minor effect were detected on chromosomes I and III, but these were not detected with composite interval mapping. Evidence for a QTL for midgut escape barrier was detected with standard interval mapping but not with composite interval mapping on chromosome III.

Aedes↗
PubMed2003

Comprehensive congenic coverage revealing multiple blood pressure quantitative trait loci on Dahl rat chromosome 10.

Chromosome mapping based on congenic strains can restrict quantitative trait loci (QTLs) for blood pressure (BP) into small intervals that are otherwise indistinguishable in linkage analysis. Also, congenic strains can be created to test a candidate gene to be a BP QTL. Taking full advantage of these features, we produced 10 congenic strains by replacing various segments of chromosome (Chr) 10 of the Dahl salt-sensitive (DSS) rat with those of the Lewis (LEW) rat. These strains were made to systematically cover an entire section of Chr 10. Three of the strains were designed to narrow the intervals that harbor previously mapped QTL1 and QTL2. Two of the strains were designed for the express purpose of testing the QTL candidacy of loci for inducible nitric oxide synthase (Nos2) and angiotensin-converting enzyme (Ace) genes. BPs of these strains were measured by telemetry and compared with those of the DSS rat. Consequently, QTL1 and QTL2 were narrowed to segments of 53.5 and 100.4 centiRays, respectively. A new QTL, QTL3, was found between QTL1 and QTL2. Both Nos2 and Ace have been disqualified as QTLs in the DSS and LEW comparison. Therefore, there are no obvious candidate genes in the segments that harbor these 3 QTLs, which represent genes previously not thought to be involved in BP regulation. These QTLs will likely have an influence on studies of human hypertension because of their homology with the human CHR 17 region in which QTLs for BP have been found.

Animals↗
PubMed2004

[Mapping quantitative trait loci for meat quality trait in a Large White x Meishan cross].

To search for the chromosome regions for quantitative trait loci (QTL) affecting meat quality in pigs, a three-generation resource family was developed in China using three Large White grand sires and seven Meishan grand dams. A total of 147 F2 progenies derived from two populations in 1998 (n = 81) and 2000 (n = 66) were phenotyped for meat quality. All animals were typed for 48 microsatellite markers covering six chromosomes: 1, 2, 3, 4, 6 and 7. Linear model and least square analyses were used for interval mapping meat quality in jointed population and single population, permutation for empirical threshold. The strongest linkage at chromosome-wide level (P < 0.01) and genome-wide level (P < 0.05) on chromosome 4 affecting intramuscular fat (IMF) QTL from the population in 2000 was detected with explained phenotypic variance of 5.24%, and Meishan's QTL increased the intramuscular fat content. There was a suggestive QTL for IMF near the threshold of chromosome-wide in the same region in jointly population. The QTL for pH value in m. Semispinalis Capitis and m. Biceps Femoris were located on chromosomes 1 and 3, respectively. One and three QTL affecting WHC reached the thresholds of chromosome-wide level in the populations of 1998 and 2000, respectively. In the population of 1998, QTL for moisture content at chromosome-wide level was on SSC6 and in jointed populations were on SSC2, 6 and 7. There were imprinting effects in moisture content QTL, and Meishan and Large White pigs all had favorable effects influencing moisture on different chromosomes.

Adipose Tissue↗
PubMed2004

Epistasis of quantitative trait loci under different gene action models.

Modeling and detecting nonallelic (epistatic) effects at multiple quantitative trait loci (QTL) often assume that the study population is in zygotic equilibrium (i.e., genotypic frequencies at different loci are products of corresponding single-locus genotypic frequencies). However, zygotic associations can arise from physical linkages between different loci or from many evolutionary and demographic processes even for unlinked loci. We describe a new model that partitions the two-locus genotypic values in a zygotic disequilibrium population into equilibrium and residual portions. The residual portion is of course due to the presence of zygotic associations. The equilibrium portion has eight components including epistatic effects that can be defined under three commonly used equilibrium models, Cockerham's model, F2-metric, and F(infinity)-metric models. We evaluate our model along with these equilibrium models theoretically and empirically. While all the equilibrium models require zygotic equilibrium, Cockerham's model is the most general, allowing for Hardy-Weinberg disequilibrium and arbitrary gene frequencies at individual loci whereas F2-metric and F(infinity)-metric models require gene frequencies of one-half in a Hardy-Weinberg equilibrium population. In an F2 population with two unlinked loci, Cockerham's model is reduced to the F2-metric model and thus both have a desirable property of orthogonality among the genic effects; the genic effects under the F(infinity)-metric model are not orthogonal but they can be easily translated into those under the F2-metric model through a simple relation. Our model is reduced to these equilibrium models in the absence of zygotic associations. The results from our empirical analysis suggest that the residual genetic variance arising from zygotic associations can be substantial and may be an important source of bias in QTL mapping studies.

Crosses, Genetic↗
PubMed2002

Reciprocal congenics defining individual quantitative trait Loci for sedative/hypnotic sensitivity to ethanol.

BACKGROUND: We have identified four major genes or quantitative trait loci (QTLs) that determine duration of loss of righting reflex (LORR), induced by sedative doses of ethanol: Lore1, Lore2, Lore4, and Lore5. Together these genes explain more than 50% of the phenotypic variance for sensitivity to the sedative/hypnotic effects of ethanol between the Inbred Long Sleep (ILS) and Inbred Short Sleep (ISS) strains of mice. The derivation of these strains is reviewed here. METHODS: Each QTL has been bred onto the opposite background (ILS or ISS) through 10 rounds of backcrossing by using QTL-marker-assisted counter selection to produce reciprocal congenic strains. Mice were genotyped for markers that flanked each of the QTLs. Selection for the donor at the desired QTL, and against donor markers at the other four QTLs, allowed rapid fixation of the genetic background. Phenotypic assessment in the ISS-recipient congenic strains was conducted throughout the backcross. RESULTS: By the N5 generation, phenotypic assessments failed to detect significant effects in some sublines; these sublines were discarded and positive lines split to create new replicate sublines. In the N10, all sublines retained the phenotypic difference between heterozygotes and ISS homozygotes; however, the expected additive effect was not found in the Lore1 congenics. On the ILS background, each Lore was captured, as shown by the expected differential LORR. Two strains on the ILS background, and one on the ISS, exhibited the differential effect on blood ethanol concentration associated with the donor strain. CONCLUSIONS: Congenic strains represent an important resource for confirmation of previously identified QTLs, for identification and mapping of additional phenotypes, and for exclusion of candidate genes. QTL-marker-assisted selection rapidly stabilized the genetic background within four generations (based on phenotypic assessments); however, phenotypic selection during the backcrossing to generate congenic strains did not contribute to the successful capture of the ISS QTLs.

Animals↗
PubMed2005

Optimal haplotype structure for linkage disequilibrium-based fine mapping of quantitative trait loci using identity by descent.

A linkage disequilibrium-based method for fine mapping quantitative trait loci (QTL) has been described that uses similarity between individuals' marker haplotypes to determine if QTL alleles are identical by descent (IBD) to model covariances among individuals' QTL alleles for a mixed linear model. Mapping accuracy with this method was found to be sensitive to the number of linked markers that was included in the haplotype when fitting the model at a putative position of the QTL. The objective of this study was to determine the optimal haplotype structure for this IBD-based method for fine mapping a QTL in a previously identified QTL region. Haplotypes consisting of 1, 2, 4, 6, or all 10 available markers were fit as a "sliding window" across the QTL region under ideal and nonideal simulated population conditions. It was found that using haplotypes of 4 or 6 markers as a sliding "window" resulted in the greatest mapping accuracy under nearly all conditions, although the true IBD state at a putative QTL position was most accurately predicted by IBD probabilities obtained using all markers. Using 4 or 6 markers resulted in greater discrimination of IBD probabilities between positions while maintaining sufficient accuracy of IBD probabilities to detect the QTL. Fitting IBD probabilities on the basis of a single marker resulted in the worst mapping accuracy under all conditions because it resulted in poor accuracy of IBD probabilities. In conclusion, for fine mapping using IBD methods, marker information must be used in a manner that results in sensitivity of IBD probabilities to the putative position of the QTL while maintaining sufficient accuracy of IBD probabilities to detect the QTL. Contrary to expectation, use of haplotypes of 4-6 markers to derive IBD probabilities, rather than all available markers, best fits these criteria. Thus for populations similar to those simulated here, optimal mapping accuracy for this IBD-based fine-mapping method is obtained with a haplotype structure including a subset of all available markers.

Crosses, Genetic↗
PubMed2002

Quantitative trait loci for bone density in mice: the genes determining total skeletal density and femur density show little overlap in F2 mice.

Bone mineral density variation is a highly heritable trait and is the best predictor of skeletal fragility. Total skeletal density was determined by PIXIMUS, and femur density was determined by pQCT. The data were analyzed for quantitative trait loci (QTL) to determine if bone density at a specific skeletal site (femur) would identify new gene loci or the same gene loci as total body (PIXIMUS). In order to show concordance and differences in QTL for total body bone density versus femur bone density, we performed a genome-wide scan from 633 (MRL x SJL) F2 mice. The bone mineral density (BMD) data from pQCT were used to identify nine QTL on chromosomes 1, 3, 4, 9, 12, 17, and 18, while nine QTL on chromosomes 1, 2, 4, 9, 11, 14, and 15 were identified by PIXIMUSdata, accounting for 32.5% and 30.4% variation in F2 mice, respectively. QTL on chromosomes 1, 2, 3, 9, 11, 12, 14, 15, 17, and 18 are unique to our study, as they have never been described before. Chromosome 1 (D1Mit33 and D1Mit362) had similar QTL between pQCT and PIXIMUS. Several QTL were identified for both femur and total body BMD but only two QTL were common for both of these phenotypes. This suggests that genes regulating bone density differ depending on the skeletal site analyzed.

Animals↗
PubMed2003

The mapping of quantitative trait loci underlying strain differences in locomotor activity between 129S6 and C57BL/6J mice.

Performance in the open field and rotarod paradigms, two common assessments of locomotor function, have been demonstrated to be strain dependent in mice. In this study, eight significant quantitative trait loci (QTL) for behavior phenotypes in either the open field or rotarod paradigms were identified between the 129S6 (129/SvEvTac) and C57BL/6J strains. These strains were chosen for comparison because of their frequent use in the generation of mutant mice from gene-targeted, embryonic stem cells. Two of the QTLs for horizontal distance traveled are located on Chromosomes (Chrs) 1 and 12 and closely replicate the findings of other groups using different strains of mice. Rotarod performance was influenced in an oppositional manner by two separate QTLs on Chr 1 and 2. Additionally, examination of several different aspects of behavior in the open field revealed significant QTLs for average speed (Chr 12), duration (Chrs 2, 16, and 18), time spent in motion (Chr 16), vertical movements (rearing) (Chrs 6 and 12), and vertical time (rearing time) (Chrs 6 and 12). Our finding of independent QTLs for these topographic components of open field activity supports the idea that they are separate and distinct from total horizontal distance traveled and should be studied independently. The QTLs described in this study, in combination with our panel of polymorphic chromosomal markers for 129S6 and C57BL/6J strains, will be useful in assessing the potential epistatic effects of parental strain background on the phenotypes of genetically modified mice.

Animals↗