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PubMed2000

[Computer system for simulating population dynamic patterns of polygenes and mobile genetic elements upon truncation selection for a quantitative trait].

A computer system was developed for simulation of population dynamics of interacting polygene patterns and mobile genetic elements (MGEs) under selection for a quantitative trait. The system is stochastic (Monte Carlo) and takes into account the main sources of random change in the patterns (recombinations, transpositions, excisions), genetic drift, and determined trends of selection and other genetic processes in a finite population. Using this model, it is possible to analyze the dynamics of many population parameters that cannot be experimentally estimated: frequencies of polygenic alleles, proportions of adaptive and random fixations, average heterozygosities of polygenes and MGEs, coefficient of inbreeding, heritability, etc. In addition, the model can be used to test various hypotheses on polygene-MGE interaction.

Adaptation, Physiological↗
PubMed1998

Alcohol preference in AXB/BXA recombinant inbred mice: gender differences and gender-specific quantitative trait loci.

The purpose of the present study was to characterize the C57BL/6J, A/J, and AXB/BXA Recombinant Inbred (RI) strains of mice for voluntary alcohol consumption. Quantitative Trait Locus (QTL) analysis was used to provide provisional location of QTLs for alcohol consumption. The inbred strains were screened for levels of alcohol intake (calculated as alcohol preference and absolute alcohol consumption) by receiving 4 days of forced exposure to a 10% (wt/vol) solution of alcohol, followed by 3 weeks of free choice between water and 10% alcohol. A wide and continuous distribution of values for alcohol consumption and preference was obtained in the AXB/BXA RI strains, confirming polygenic influences on alcohol-related behaviors. Significant gender differences were found for both alcohol preference [F28,651 = 2.12, p < 0.001] and absolute alcohol consumption [F28,647 = 2.57, p < 0.001]. In males, putative QTLs were mapped to chromosomes (Chrs) 2, 5, 7, 10, 11, and 16. Multiple regression analysis indicated that approximately 75% of the genetic variance in alcohol preference in males could be accounted for by three of the QTL regions. Several of the putative QTLs appeared to be male-specific (Tyr on Chr 7; D10Mit126 on Chr 10; D11Mit61 on Chr 11). In females, seven putative QTLs were mapped to Chrs 2, 4, 5, 7, 11, 16, and 19. Approximately 90% of the genetic variance in alcohol preference in females could be accounted for by four QTL regions, as determined by multiple regression. The QTL on Chr 11 near D11Mit35 appeared to be female-specific. This site was close to a female-specific QTL (Alcp2) previously mapped in C57BL/6J x DBA/2J backcrosses by Melo and coworkers (Nat Genet 13, 147, 1996). The QTLs mapped for alcohol preference in the present study must be considered suggestive at the present time, since only D2Mit74 met very strict statistical criteria for significance. However, the concordance across several studies for the loci on Chrs 2, 4, 7, 9, and 11 suggest that some common QTLs influencing alcohol preference have been identified. Confirmation of QTLs mapped in the present study is currently being conducted in a new series of recombinant congenic (RC) strains developed from reciprocal backcrosses between the A/J and C57BL/6J progenitors. The concomitant use of both RI and RC strains developed from the same progenitors should provide a powerful means of detecting, confirming, and mapping QTLs for alcohol-related traits.

Alcohol Drinking↗
PubMed2005

Genome scan for quantitative trait loci influencing HDL levels: evidence for multilocus inheritance in familial combined hyperlipidemia.

Several genome scans in search of high-density lipoprotein (HDL) quantitative trait loci (QTLs) have been performed. However, to date the actual identification of genes implicated in the regulation of common forms of HDL abnormalities remains unsuccessful. This may be due, in part, to the oligogenic and multivariate nature of HDL regulation, and potentially, pleiotropy affecting HDL and other lipid-related traits. Using a Bayesian Markov Chain Monte Carlo (MCMC) approach, we recently provided evidence of linkage of HDL level variation to the APOA1-C3-A4-A5 gene complex, in familial combined hyperlipidemia pedigrees, with an estimated number of two to three large QTLs remaining to be identified. We also presented results consistent with pleiotropy affecting HDL and triglycerides at the APOA1-C3-A4-A5 gene complex. Here we use the same MCMC analytic strategy, which allows for oligogenic trait models, as well as simultaneous incorporation of covariates, in the context of multipoint analysis. We now present results from a genome scan in search for the additional HDL QTLs in these pedigrees. We provide evidence of linkage for additional HDL QTLs on chromosomes 3p14 and 13q32, with results on chromosome 3 further supported by maximum parametric and variance component LOD scores of 3.0 and 2.6, respectively. Weaker evidence of linkage was also obtained for 7q32, 12q12, 14q31-32 and 16q23-24.

Adolescent↗
PubMed1998

A rank-based nonparametric method for mapping quantitative trait loci in outbred half-sib pedigrees: application to milk production in a granddaughter design.

We describe the development of a multipoint nonparametric quantitative trait loci mapping method based on the Wilcoxon rank-sum test applicable to outbred half-sib pedigrees. The method has been evaluated on a simulated dataset and its efficiency compared with interval mapping by using regression. It was shown that the rank-based approach is slightly inferior to regression when the residual variance is homoscedastic normal; however, in three out of four other scenarios envisaged, i.e., residual variance heteroscedastic normal, homoscedastic skewed, and homoscedastic positively kurtosed, the latter outperforms the former one. Both methods were applied to a real data set analyzing the effect of bovine chromosome 6 on milk yield and composition by using a 125-cM map comprising 15 microsatellites and a granddaughter design counting 1158 Holstein-Friesian sires.

Animals↗
PubMed2002

Detection of quantitative trait loci for protein percentage in muscle in resource pig population.

An intercross between Meishan and Large White pig population was used to map quantitative trait loci(QTL) for protein percentage in muscle. In the present study, all 135 F2 animals, their parents and their grandparents were genotyped for 24 microsatellites, which were in 1, 2 and 6 chromosome. The marker genotypes were used to calculate the additive and dominant coefficients at fixed position in the genome of each F2 animal, and the protein percentage were regressed on to the coefficients in intervals of 1 cM. Three significant QTLs effects were found for protein percentage in muscle. They were located between markers Sw1332 and Sw2130 at chromosome 1, between Sw2516 and Sw1201 at chromosome 2 and between Sw322 and Sw607 at chromosome 6(P < 0.05), and the explained residual variance were 0.91%, 12.76% and 4.60%, respectively. The results show that QTLs, which affect protein percentage, may be located in different chromosomes.

Animals↗
PubMed2005

Combined linkage and association mapping of quantitative trait loci by multiple markers.

Using multiple diallelic markers, variance component models are proposed for high-resolution combined linkage and association mapping of quantitative trait loci (QTL) based on nuclear families. The objective is to build a model that may fully use marker information for fine association mapping of QTL in the presence of prior linkage. The measures of linkage disequilibrium and the genetic effects are incorporated in the mean coefficients and are decomposed into orthogonal additive and dominance effects. The linkage information is modeled in variance-covariance matrices. Hence, the proposed methods model both association and linkage in a unified model. On the basis of marker information, a multipoint interval mapping method is provided to estimate the proportion of allele sharing identical by descent (IBD) and the probability of sharing two alleles IBD at a putative QTL for a sib-pair. To test the association between the trait locus and the markers, both likelihood-ratio tests and F-tests can be constructed on the basis of the proposed models. In addition, analytical formulas of noncentrality parameter approximations of the F-test statistics are provided. Type I error rates of the proposed test statistics are calculated to show their robustness. After comparing with the association between-family and association within-family (AbAw) approach by Abecasis and Fulker et al., it is found that the method proposed in this article is more powerful and advantageous based on simulation study and power calculation. By power and sample size comparison, it is shown that models that use more markers may have higher power than models that use fewer markers. The multiple-marker analysis can be more advantageous and has higher power in fine mapping QTL. As an application, the Genetic Analysis Workshop 12 German asthma data are analyzed using the proposed methods.

Alleles↗
PubMed2002

Application of a mixed inheritance model to the detection of quantitative trait loci in swine.

The primary goal of this study was to investigate statistical properties of a mixed inheritance model for the localization of quantitative trait loci (QTL). This is based on the analysis of phenotypic data for the amount of intramuscular fat (IMF) scored on 305 individuals originating from a cross between Duroc and Norwegian Landrace breeds. Marker genotype information is available for F1 and F2 generations. Statistical procedures compared involve i) the interval mapping, ii) the composite interval mapping, iii) a regression method, and iv) a mixed inheritance model accounting for a random animal additive genetic effect and relationships between individuals. The basic statistical properties of the latter approach are then assessed using Monte Carlo simulations showing slight unconservativeness as compared to chi(2)2df and reasonable power to detect QTL of moderate effects. In the analysis of IMF data, the significant evidence for the existing QTL is detected on chromosome 6. A chromosomal region recommended for a second-step fine mapping analysis is identified between markers SW1823 and S0228, based on three types of confidence intervals derived by using: i) the Jackknife algorithm, ii) the numerical variance approximation, and iii) the LOD score approach. The Jackknife algorithm was additionally used to quantify each family's contribution to the test statistic and to the estimate of QTL position.

Animals↗
PubMed2002

Improved confidence intervals in quantitative trait loci mapping by permutation bootstrapping.

The nonparametric bootstrap approach is known to be suitable for calculating central confidence intervals for the locations of quantitative trait loci (QTL). However, the distribution of the bootstrap QTL position estimates along the chromosome is peaked at the positions of the markers and is not tailed equally. This results in conservativeness and large width of the confidence intervals. In this study three modified methods are proposed to calculate nonparametric bootstrap confidence intervals for QTL locations, which compute noncentral confidence intervals (uncorrected method I), correct for the impact of the markers (weighted method I), or both (weighted method II). Noncentral confidence intervals were computed with an analog of the highest posterior density method. The correction for the markers is based on the distribution of QTL estimates along the chromosome when the QTL is not linked with any marker, and it can be obtained with a permutation approach. In a simulation study the three methods were compared with the original bootstrap method. The results showed that it is useful, first, to compute noncentral confidence intervals and, second, to correct the bootstrap distribution of the QTL estimates for the impact of the markers. The weighted method II, combining these two properties, produced the shortest and less biased confidence intervals in a large number of simulated configurations.

Chromosome Mapping↗
PubMed2001

A comprehensive search for quantitative trait loci affecting growth and carcass composition of cattle segregating alternative forms of the myostatin gene.

The objective of this study was to identify quantitative trait loci for economically important traits in two families segregating an inactive copy of the myostatin gene. Two half-sib families were developed from a Belgian Blue x MARC III (n = 246) and a Piedmontese x Angus (n = 209) sire. Traits analyzed were birth, weaning, and yearling weight (kg); preweaning average daily gain (kg/d); postweaning average daily gain (kg/d); hot carcass weight (kg); fat depth (cm); marbling score; longissimus muscle area (cm2); estimated kidney, pelvic, and heart fat (%); USDA yield grade; retail product yield (%); fat yield (%); and wholesale rib-fat yield (%). Meat tenderness was measured as Warner-Bratzler shear force at 3 and 14 d postmortem. The effect of the myostatin gene was removed using phase information from six microsatellite markers flanking the locus. Interactions of the myostatin gene with other loci throughout the genome were also evaluated: The objective was to use markers in each family, scanning the genome approximately every 25 to 30 centimorgans (cM) on 18 autosomal chromosomes, excluding 11 autosomal chromosomes previously analyzed. A total of 89 markers, informative in both families, were used to identify genomic regions potentially associated with each trait. In the family of Belgian Blue inheritance, a significant QTL (expected number of false-positives = 0.025) was identified for marbling score on chromosome 3. Suggestive QTL for the same family (expected number of false-positives = 0.5) were identified for retail product yield on chromosome 3, for hot carcass weight and postweaning average daily gain on chromosome 4, for fat depth and marbling score on chromosome 8, for 14-d Warner-Bratzler shear force on chromosome 9, and for marbling score on chromosome 10. Evidence suggesting the presence of an interaction for 3-d Warner-Bratzler shear force between the myostatin gene and a QTL on chromosome 4 was detected. In the family of Piedmontese and Angus inheritance, evidence indicates the presence of an interaction for fat depth between the myostatin gene and chromosome 8, in a similar position where the evidence suggests the presence of a QTL for fat depth in the family with Belgian Blue inheritance. Regions identified underlying QTL need to be assessed in other populations. Although the myostatin gene has a considerable effect, other loci with more subtle effects are involved in the expression of the phenotype.

Alleles↗
PubMed2006

Quantitative trait loci affecting fertility and calving traits in Swedish dairy cattle.

Impaired fertility is the main reason for involuntary culling of dairy cows in Sweden. The objective of this study was to map quantitative trait loci (QTL) influencing fertility and calving traits in the Swedish dairy cattle population. The traits analyzed were number of inseminations, 56-d nonreturn rate, interval from calving to first insemination, fertility treatments, heat intensity score, stillbirth, and calving performance. A genome scan covering 20 bovine chromosomes was performed using 145 microsatellite markers. The mapping population consisted of 10 sires and their 417 sons in a granddaughter design. Nine of the sires were of the Swedish Red Breed, and one was a Swedish Holstein. Least squares regression was used to map loci affecting the analyzed traits, and permutation tests were used to set significance thresholds. Cofactors were used in the analyses of individual chromosomes to adjust for QTL found on other chromosomes. The use of cofactors increased both the number of QTL found and the significance level. In the initial analysis, we found 13 suggestive QTL that were mapped to chromosomes 6, 7, 9, 11, 13, 15, 20, and 29. When cofactors were included, 30 QTL were detected on chromosomes 1, 3, 4, 18, 19, 22, and 25, in addition to the 8 previously mentioned chromosomes. Some of the results from the cofactor analysis may be false positives and require further validation. In conclusion, we were able to map several QTL affecting fertility and calving traits in Swedish dairy cattle.

Animals↗
PubMedDate not supplied

Quantitative trait loci for acute behavioral sensitivity to paraoxon.

Genetic mechanisms responsible for organophosphate (OP)-induced behavioral changes remain obscure. In the present study, provisional quantitative trait loci (QTL) associated with acute sensitivity or insensitivity to hypolocomotion produced by the OP paraoxon were identified. Naive adult male and female mice of the BXD/Ty series (22 different BXD strains plus C57BL/6J and DBA/2J progenitor strains) received 0 or 0.25 mg/kg paraoxon (IP), immediately before placement in an activity chamber for a 30-min test. As expected, based on dose-response and time course studies with Swiss-Webster, C57BL/6, and DBA/2 mice, paraoxon treatment reduced locomotor activity in most, but not all BXD strains. Heritability (proportion of phenotypic variability attributed to genetic differences) was 0. 58 for the paraoxon treatment effect. Difference scores (strain mean for vehicle activity minus strain mean for paraoxon activity), and percent change in activity of paraoxon-treated mice compared to vehicle-treated mice were calculated for each BXD strain. QTL analyses using activity difference scores and percentage change in activity were conducted using a database with over 1300 unique genetic markers. Several provisional QTL found on different chromosomes were associated with the activity phenotype. Of these, several markers attained p<0.01 or greater. These were as follows: Chr 1: Ly9, p<0.006; Chr 6: D6Ncvs44, p<0.0005; Chr 9: D9Mit15, p<0. 003; Chr 11: D11Ncvs76, p<0.002; Chr 15: Tstap198, p<0.008. In addition, several markers on chromosome 3 approached p<0.01. Identified genes found near these regions include two plasma carboxylesterase alleles on chromosomes 6 and 9, a glutamate receptor subtype on chromosome 11 and a glycine receptor subunit on chromosome 11, raising the possibility that these genes could be the basis for these provisional QTLs.

Animals↗
PubMed1992

A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

The use of flanking marker methods has proved to be a powerful tool for the mapping of quantitative trait loci (QTL) in the segregating generations derived from crosses between inbred lines. Methods to analyse these data, based on maximum-likelihood, have been developed and provide good estimates of QTL effects in some situations. Maximum-likelihood methods are, however, relatively complex and can be computationally slow. In this paper we develop methods for mapping QTL based on multiple regression which can be applied using any general statistical package. We use the example of mapping in an F(2) population and show that these regression methods produce very similar results to those obtained using maximum likelihood. The relative simplicity of the regression methods means that models with more than a single QTL can be explored and we give examples of two lined loci and of two interacting loci. Other models, for example with more than two QTL, with environmental fixed effects, with between family variance or for threshold traits, could be fitted in a similar way. The ease, speed of application and generality of regression methods for flanking marker analysis, and the good estimates they obtain, suggest that they should provide the method of choice for the analysis of QTL mapping data from inbred line crosses.

Animals↗
PubMed2004

Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome.

Genetic architecture of flowering time in maize was addressed by synthesizing a total of 313 quantitative trait loci (QTL) available for this trait. These were analyzed first with an overview statistic that highlighted regions of key importance and then with a meta-analysis method that yielded a synthetic genetic model with 62 consensus QTL. Six of these displayed a major effect. Meta-analysis led in this case to a twofold increase in the precision in QTL position estimation, when compared to the most precise initial QTL position within the corresponding region. The 62 consensus QTL were compared first to the positions of the few flowering-time candidate genes that have been mapped in maize. We then projected rice candidate genes onto the maize genome using a synteny conservation approach based on comparative mapping between the maize genetic map and japonica rice physical map. This yielded 19 associations between maize QTL and genes involved in flowering time in rice and in Arabidopsis. Results suggest that the combination of meta-analysis within a species of interest and synteny-based projections from a related model plant can be an efficient strategy for identifying new candidate genes for trait variation.

Chromosome Mapping↗
PubMed1998

A mixture model approach to the mapping of quantitative trait loci in complex populations with an application to multiple cattle families.

A mixture model approach is presented for the mapping of one or more quantitative trait loci (QTLs) in complex populations. In order to exploit the full power of complete linkage maps the simultaneous likelihood of phenotype and a multilocus (all markers and putative QTLs) genotype is computed. Maximum likelihood estimation in our mixture models is implemented via an Expectation-Maximization algorithm: exact, stochastic or Monte Carlo EM by using a simple and flexible Gibbs sampler. Parameters include allele frequencies of markers and QTLs, discrete or normal effects of biallelic or multiallelic QTLs, and homogeneous or heterogeneous residual variances. As an illustration a dairy cattle data set consisting of twenty half-sib families has been reanalyzed. We discuss the potential which our and other approaches have for realistic multiple-QTL analyses in complex populations.

Animals↗
PubMed1998

Confirmation of quantitative trait loci for alcohol preference in mice.

An F2 intercross derived from C57BL/6 and DBA/2 progenitor inbred strains was used to test for replication of quantitative trait loci (QTLs) for alcohol preference nominated by a previous study using BXD recombinant inbred (RI) strains (Rodriguez et al., Alcohol. Clin. Exp. Res. 19:367-379, 1995). Fourteen provisional QTLs were nominated in the original RI study with a p < 0.05 criterion. In the present study, a genome scan (101 microsatellite markers) was conducted on an F2 population (n = 218). Three significant QTLs were detected on chromosomes 1, 4, and 9, and three suggestive QTLs were detected on chromosomes 2, 3, and 10. Of these six QTLs, four were consistent with the previous RI nominations. The replication rate of 28.6% (4 of 14) is in agreement with the results of simulation studies performed by Belknap et al. (Behav. Genet. 26:149-160, 1996) and supports the methodological argument for a multistage research design for nominating and replicating QTLs.

Alcohol Drinking↗
PubMed2000

fw2.2: a quantitative trait locus key to the evolution of tomato fruit size.

Domestication of many plants has correlated with dramatic increases in fruit size. In tomato, one quantitative trait locus (QTL), fw2.2, was responsible for a large step in this process. When transformed into large-fruited cultivars, a cosmid derived from the fw2.2 region of a small-fruited wild species reduced fruit size by the predicted amount and had the gene action expected for fw2.2. The cause of the QTL effect is a single gene, ORFX, that is expressed early in floral development, controls carpel cell number, and has a sequence suggesting structural similarity to the human oncogene c-H-ras p21. Alterations in fruit size, imparted by fw2.2 alleles, are most likely due to changes in regulation rather than in the sequence and structure of the encoded protein.

Alleles↗
PubMed2005

Quantitative trait locus (QTL) isogenic recombinant analysis: a method for high-resolution mapping of QTL within a single population.

In the quest for fine mapping quantitative trait loci (QTL) at a subcentimorgan scale, several methods that involve the construction of inbred lines and the generation of large progenies of such inbred lines have been developed (Complex Trait Consortium 2003). Here we present an alternative method that significantly speeds up QTL fine mapping by using one segregating population. As a first step, a rough mapping analysis is performed on a small part of the population. Once the QTL have been mapped to a chromosomal interval by standard procedures, a large population of 1000 plants or more is analyzed with markers flanking the defined QTL to select QTL isogenic recombinants (QIRs). QIRs bear a recombination event in the QTL interval of interest, while other QTL have the same homozygous genotype. Only these QIRs are subsequently phenotyped to fine map the QTL. By focusing at an early stage on the informative individuals in the population only, the efforts in population genotyping and phenotyping are significantly reduced as compared to prior methods. The principles of this approach are demonstrated by fine mapping an erucic acid QTL of rapeseed at a subcentimorgan scale.

Brassica rapa↗
PubMed2004

Quantitative trait linkage analysis by generalized estimating equations: unification of variance components and Haseman-Elston regression.

Two of the major approaches for linkage analysis with quantitative traits in humans include variance components and Haseman-Elston regression. Previously, these were viewed as quite separate methods. We describe a general model, fit by use of generalized estimating equations (GEE), for which the variance components and Haseman-Elston methods (including many of the extensions to the original Haseman-Elston method) are special cases, corresponding to different choices for a working covariance matrix. We also show that the regression-based test of Sham et al. ([2002] Am. J. Hum. Genet. 71:238-253) is equivalent to a robust score statistic derived from our GEE approach. These results have several important implications. First, this work provides new insight regarding the connection between these methods. Second, asymptotic approximations for power and sample size allow clear comparisons regarding the relative efficiency of the different methods. Third, our general framework suggests important extensions to the Haseman-Elston approach which make more complete use of the data in extended pedigrees and allow a natural incorporation of environmental and other covariates.

Algorithms↗