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PubMed1993

Linkage between quantitative trait and marker loci: methods using all relative pairs.

Relative-pair methods for detection of linkage between a quantitative trait and a marker locus have been proposed by a number of authors [e.g., Haseman and Elston, Behav Genet 3-19, 1972; Amos and Elston, Genet Epidemiol 349-360, 1989]. However, development of tests of significance that combine information from different types of relative pairs has been hampered by the presence of correlations between relative pairs from the same pedigree. In this paper, the methodology of generalized estimating equations is used to provide an estimate of the robust covariance matrix of the estimates of the set of relative-pair-type-specific regression parameters. Using this matrix, an asymptotically most powerful test of linkage which optimally combines the information contained in the different types of relative pairs is constructed. This test requires optimal weights that depend on unknown values of heritability and recombination fraction to be chosen a priori. However, simulations show that, in the regions of recombination fraction and heritability of practical interest, the power of the test does not depend strongly on the assumptions made when choosing the optimal weights; as a result, weights that depend only on the number of each type of relative pair and the variability of the marker identity-by-descent probabilities work well in practice. In addition, an approximation to the regression model leads to a simple approach to testing linkage in which only a single regression parameter is estimated from data containing different types of relative pairs. The resulting test is slightly less powerful than the test described above, but its computational simplicity and lack of dependence on a priori weighting schemes suggest potential usefulness in large linkage studies.

Epidemiologic Methods↗
PubMed1996

Multivariate multipoint linkage analysis of quantitative trait loci.

Resolution of the genetic components of complex disorders may require simultaneous analysis of the contribution of individual quantitative trait loci (QTLs) to multiple variables. A likelihood approach is used to illustrate how the complexities of multivariate data may be resolved with multipoint linkage analysis. Sibling pair data were simulated from a model in which two QTLs and trait-specific polygenic effects explained all the sibling resemblance within and between five variables. Multipoint linkage analysis was used to obtain individual pair probabilities of having zero, one, or two alleles identical by descent, and these probabilities were applied in a weighted maximum-likelihood fit function. The results were compared with those obtained using conventional linear structural equation modeling to estimate the contribution of latent genetic factors to the genetic covariance in the multiple measures. Both analyses were conducted using the Mx package. Relatively poor agreement was found between genetic factors defined in purely statistical terms by varimax rotation of the first two factors of the genetic covariance matrix and the structure obtained by fitting a model jointly to the phenotypic and the multipoint linkage data.

Animals↗
PubMed1998

Mapping quantitative trait loci affecting sternopleural bristle number in Drosophila melanogaster using changes of marker allele frequencies in divergently selected lines.

Quantitative trait loci (QTLs) responsible for variation in sternopleural bristle number in crosses between the laboratory lines of Drosophila melanogaster OregonR and CantonS were mapped using information from allele frequency changes of two families of retrotransposon markers in divergently selected populations. QTL effects and positions were inferred by likelihood, using transition matrix iteration and Monte Carlo interval mapping. Individuals from the selected population were genotyped for markers spaced at an average distance 4.4 cM. Four QTLs of moderate effect ranging from 0.6 to 1.32 bristles accounted for most of the selection response. A permutation test of the correspondence between the mapped QTLs and the positions of bristle number candidate genes suggested that alleles at these candidate genes were no more strongly associated with selected changes in marker allele frequency than were randomly chosen positions in the genome.

Alleles↗
PubMed1991

Inbreeding and heterosis effects on quantitative traits in a White Leghorn population under long-term reciprocal recurrent selection.

1. Inbreeding and heterosis effects for quantitative traits were estimated in two White Leghorn lines selected with reciprocal recurrent selection (RRS) since 1950. 2. Pedigreed progeny were produced from full-sib, half-sib and unrelated pure line as well as reciprocal cross line matings to estimate inbreeding and heterosis effects "within sires". 3. Inbreeding effects estimated as linear regressions agreed well with estimates considering inbreeding as fixed effect. The inbreeding depression per 10% inbreeding was highest for hatchability (6-7%), intermediate for production-related traits (3%), and about 1% for shell quality, body weight and egg weight. 4. Heterosis effects were estimated by comparing pure line and cross line progeny of the same sires. 5. Results indicate considerably less heterosis for egg production than found earlier, which is interpreted as a consequence of pure line selection.

Animals↗
PubMed1991

Mendelian factors underlying quantitative traits in tomato: comparison across species, generations, and environments.

As part of ongoing studies regarding the genetic basis of quantitative variation in phenotype, we have determined the chromosomal locations of quantitative trait loci (QTLs) affecting fruit size, soluble solids concentration, and pH, in a cross between the domestic tomato (Lycopersicon esculentum Mill.) and a closely-related wild species, L. cheesmanii. Using a RFLP map of the tomato genome, we compared the inheritance patterns of polymorphisms in 350 F2 individuals with phenotypes scored in three different ways: (1) from the F2 progeny themselves, grown near Davis, California; (2) from F3 families obtained by selfing each F2 individual, grown near Gilroy, California (F3-CA); and (3) from equivalent F3 families grown near Rehovot, Israel (F3-IS). Maximum likelihood methods were used to estimate the approximate chromosomal locations, phenotypic effects (both additive effects and dominance deviations), and gene action of QTLs underlying phenotypic variation in each of these three environments. A total of 29 putative QTLs were detected in the three environments. These QTLs were distributed over 11 of the 12 chromosomes, accounted for 4.7-42.0% of the phenotypic variance in a trait, and showed different types of gene action. Among these 29 QTLs, 4 were detected in all three environments, 10 in two environments, and 15 in only a single environment. The two California environments were most similar, sharing 11/25 (44%) QTLs, while the Israel environment was quite different, sharing 7/20 (35%) and 5/26 (19%) QTLs with the respective California environments. One major goal of QTL mapping is to predict, with maximum accuracy, which individuals will produce progeny showing particular phenotypes. Traditionally, the phenotype of an individual alone has been used to predict the phenotype of its progeny. Our results suggested that, for a trait with low heritability (soluble solids), the phenotype of F3 progeny could be predicted more accurately from the genotype of the F2 parent at QTLs than from the phenotype of the F2 individual. For a trait with intermediate heritability (fruit pH), QTL genotype and observed phenotype were about equally effective at predicting progeny phenotype. For a trait with high heritability (mass per fruit), knowing the QTL genotype of an individual added little if any predictive value, to simply knowing the phenotype. The QTLs mapped in the L. esculentum X L. cheesmanii F2 appear to be at similar locations to many of those mapped in a previous cross with a different wild tomato (L. chmielewskii).(ABSTRACT TRUNCATED AT 400 WORDS)

Biological Evolution↗
PubMed1994

High resolution of quantitative traits into multiple loci via interval mapping.

A very general method is described for multiple linear regression of a quantitative phenotype on genotype [putative quantitative trait loci (QTLs) and markers] in segregating generations obtained from line crosses. The method exploits two features, (a) the use of additional parental and F1 data, which fixes the joint QTL effects and the environmental error, and (b) the use of markers as cofactors, which reduces the genetic background noise. As a result, a significant increase of QTL detection power is achieved in comparison with conventional QTL mapping. The core of the method is the completion of any missing genotypic (QTL and marker) observations, which is embedded in a general and simple expectation maximization (EM) algorithm to obtain maximum likelihood estimates of the model parameters. The method is described in detail for the analysis of an F2 generation. Because of the generality of the approach, it is easily applicable to other generations, such as backcross progenies and recombinant inbred lines. An example is presented in which multiple QTLs for plant height in tomato are mapped in an F2 progeny, using additional data from the parents and their F1 progeny.

Chromosome Mapping↗
PubMed1995

Mapping quantitative trait loci controlling milk production in dairy cattle by exploiting progeny testing.

We have exploited "progeny testing" to map quantitative trait loci (QTL) underlying the genetic variation of milk production in a selected dairy cattle population. A total of 1,518 sires, with progeny tests based on the milking performances of > 150,000 daughters jointly, was genotyped for 159 autosomal microsatellites bracketing 1645 centimorgan or approximately two thirds of the bovine genome. Using a maximum likelihood multilocus linkage analysis accounting for variance heterogeneity of the phenotypes, we identified five chromosomes giving very strong evidence (LOD score > or = 3) for the presence of a QTL controlling milk production: chromosomes 1, 6, 9, 10 and 20. These findings demonstrate that loci with considerable effects on milk production are still segregating in highly selected populations and pave the way toward marker-assisted selection in dairy cattle breeding.

Animals↗
PubMed1996

The use of multiple markers in a Bayesian method for mapping quantitative trait loci.

Information on multiple linked genetic markers was used in a Bayesian method for the statistical mapping of quantitative trait loci (QTL). Bayesian parameter estimation and hypothesis testing were implemented via Markov chain Monte Carlo algorithms. Variables sampled were the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage or nonlinkage, and the parameters. The parameter vector included allele frequencies at the markers and the QTL, map distances of the markers and the QTL, QTL substitution effect, and polygenic and residual variances. The criterion for QTL detection was the marginal posterior probability of a QTL being located on the chromosome carrying the markers. The method was evaluated empirically by analyzing simulated granddaughter designs consisting of 2000 sons, 20 related sires, and their ancestors.

Algorithms↗
PubMed2002

Quantitative trait loci in Two Soybean Recombinant Inbred Line Populations Segregating for Yield and Disease Resistance.

Molecular makers linked to quantitative trait loci (QTL) can assist soybean [Glycine max (L.) Merr.] breeders to combine traits of low heritability, such as yield, with disease resistance. The objective of this study was to identify markers linked to yield QTL in two recombinant inbred line (RIL) populations ['Essex' x 'Forrest' (ExF; n = 100) and 'Flyer' x 'Hartwig' (FxH; n = 94)] that also segregate for soybean cyst nematode (SCN) resistance genes (rhg1 and Rhg4). Each population was yield tested in four environments between 1996 and 1999. The resistant parents produced lower yields. Heritability of yield across four environments was 47% for ExF and 57% for FxH. Yield was normally distributed in both populations. High yielding, SCN resistant transgressive segregants were not observed. In the ExF RIL population, 134 microsatellite markers were compared against yield by ANOVA and MAPMAKER QTL. Regions associated with yield were identified by SATT294 on linkage group (LG.) C1 (P = 0.006, R(2) = 10%), SATT440 on LG. I (P = 0.007, R(2) = 10%), and SATT337 on LG. K (P = 0.004, R(2) = 10%). Essex provided the beneficial allele at SATT337. Mean yields among FxH RILs were compared against 33 microsatellite markers from LG. K. In addition 136 markers from randomly selected LGs were compared with extreme phenotypes by bulk segregant analysis. Two regions on LG. K (20 cM apart) associated with yield were identified by SATT326 (P = 0.0004, R(2) = 15%) and SATT539 (P = 0.0008, R(2) = 14%). Flyer provided both beneficial alleles. Both populations revealed a yield QTL in the interval (5 cM) between SATT337 and SATT326. These populations may share a common allele for yield in this region, given that about 40% of Flyer genome derived from Essex.

Journal Article↗
PubMed1996

Using the expectation or the distribution of the identity by descent for mapping quantitative trait loci under the random model.

We examine the ability of four implementations of the random model to map quantitative trait loci (QTLs). The implementations use either the expectation or the distribution of the identity-by-descent value at a putative QTL and either a 2 x 1 vector of sib-pair traits or their scalar difference. When the traits of both sibs are used, there is little difference between the expectation and distribution methods, while the expectation method suffers in both precision and power when the difference between traits is used. This is consistent with the prediction that the difference between the expectation and distribution methods is inversely proportional to the amount of information available for mapping. We find, though, that the amount of information must be very low for this difference to be noticeable. This is exemplified when both marker loci are fixed. In this case, while the expectation method is powerless to detect the QTL, the distribution method can still detect the presence (but not the position) of the QTL 59% of the time (when using trait values) or 14% of the time (when using trait differences). We also note a confounding between estimates of the QTL, polygenic, and error variance. The degree of confounding is small when the vector of trait values is used but can be substantial when the expectation method and trait differences are used. We discuss this in light of the general ability of the random model to partition these components.

Chromosome Mapping↗
PubMed2006

Review of quantitative trait loci identified in the chicken.

Methods for mapping QTL are actively used in the chicken to identify chromosomal regions contributing to variation in traits related to growth, disease resistance, egg production, behavior, and metabolic parameters. However, higher-resolution mapping and better knowledge of the genetic architecture underlying QTL are needed for successful application of this information into breeding programs. Therefore, this paper summarizes and integrates original, primary QTL studies in the chicken to identify basic information on the genetic architecture of quantitative traits in chickens. The results of this review show several instances of consensus of QTL locations for similar traits from independent studies. Furthermore, the consensus of QTL location for different traits and evidence for QTL with parent-of-origin effect, transgressive alleles, epistatic QTL, and QTL x sex interaction in chicken are presented and discussed. This information can be helpful in identifying genes or mutations underlying the QTL and in the application of genomic information in marker-assisted breeding programs.

Animals↗
PubMed2002

A quantitative trait locus influencing anxiety in the laboratory rat.

A critical test for a gene that influences susceptibility to fear in animals is that it should have a consistent pattern of effects across a broad range of conditioned and unconditioned models of anxiety. Despite many years of research, definitive evidence that genetic effects operate in this way is lacking. The limited behavioral test regimes so far used in genetic mapping experiments and the lack of suitable multivariate methodologies have made it impossible to determine whether the quantitative trait loci (QTL) detected to date specifically influence fear-related traits. Here we report the first multivariate analysis to explore the genetic architecture of rodent behavior in a battery of animal models of anxiety. We have mapped QTLs in an F2 intercross of two rat strains, the Roman high and low avoidance rats, that have been selectively bred for differential response to fear. Multivariate analyses show that one locus, on rat chromosome 5, influences behavior in different models of anxiety. The QTL influences two-way active avoidance, conditioned fear, elevated plus maze, and open field activity but not acoustic startle response or defecation in a novel environment. The direction of effects of the QTL alleles and a coincidence between the behavioral profiles of anxiolytic drug and genetic action are consistent with the QTL containing at least one gene with a pleiotropic action on fear responses. As the neural basis of fear is conserved across species, we suggest that the QTL may have relevance to trait anxiety in humans.

Alleles↗
PubMed2001

Identification of wound healing/regeneration quantitative trait loci (QTL) at multiple time points that explain seventy percent of variance in (MRL/MpJ and SJL/J) mice F2 population.

Studies on genetic mechanisms of wound healing in mammals are very few, although injury is a leading cause of the global burden of disease. In this study, we performed a high-density, genome-wide scan using 633 (MRL/MPJ x SJL/J) F(2) intercross at multiple time points (days 15, 21, and 25) to identify quantitative trait loci (QTL) involved in wound healing/regeneration. The hypothesis of the study was that QTL and unique epistatic interactions are involved at each time point to promote wound healing/regeneration. Ten QTL were identified from chromosomes 1, 4, 6, 7, 9, and 13. Of the 10 QTL, eight from chromosomes 1, 4, 6, and 9 were novel as compared to QTL identified in the study. The 10 QTL altogether explained 70% of variance in F(2) mice. The same QTL were identified at each time point, with simple linear correlation between days 15, 21, and 25, showing very high significant relationships (R >0.92, P <0.0001). Unique epistatic interactions were identified at each time point except those from chromosomes 4, 6, 9, and 13 that were found at all three time points, showing that some loci are involved at all the three time points of wound healing (days 15, 21, and 25). Therefore, loci-to-loci interactions may play a major role in wound healing. Information from these studies may help in the identification of genes that could be involved in wound healing/regeneration.

Analysis of Variance↗
PubMed2007

Detection of novel quantitative trait loci for cutaneous melanoma by genome-wide scan in the MeLiM swine model.

Human cutaneous melanoma is a complex trait inherited in about 10% of cases. Although 2 high-risk genes, CDKN2A and CDK4, and 1 low risk gene, MC1R, have been identified, susceptibility genes remain to be discovered. Here, we attempted to determine new genomic regions linked to melanoma using the pig MeLiM strain, which develops hereditary cutaneous melanomas. We applied quantitative trait loci (QTL) mapping method to a significant genome-wide scan performed on 331 backcross pigs derived from this strain. QTLs were detected at chromosome-wide level for a melanoma synthetic trait corresponding to the development of melanoma. The peak positions on Sus scrofa chromosomes (SSC) were at 49.4 and 88.0 cM (SSC1), 56.0 cM (SSC13), 86.5 cM (SSC15) and 39.8 cM (SSC17), and, on SSC2, at 16.9 cM, in families derived from F1 males only (p < 0.05, except for SSC13, p < 0.01). Analysis of 7 precise specific traits revealed highly significant QTLs on SSC10 (ulceration), on SSC12 (presence of melanoma at birth), on SSC13 (lesion type), and on SSC16 and SSC17 (number of aggressive melanomas) at the respective positions 42.0, 95.6, 81.0, 45.3 and 44.8 cM (p < 0.001 and p < 0.05 respectively at the chromosome- and genome-wide levels). We also showed that MeLiM MC1R*2 allele, which determines black coat colour in pigs, predisposes significantly to melanoma. Interactions were observed between MC1R and markers located on SSC1 (p < 0.05). Taken together, these results indicate that MeLiM swine is a model for human multigenic diseases. Comparative mapping revealed human regions of interest to search for new melanoma susceptibility candidates.

Alleles↗
PubMed2001

The effect of pedigree complexity on quantitative trait linkage analysis.

Due to the computational difficulties of performing linkage analysis on large complex pedigrees, most investigators resort to simplifying such pedigrees by some ad hoc strategy. In this paper, we suggest an analytical method to compare the power of various pedigree simplification schemes by using the asymptotic distribution of the likelihood-ratio statistic. We applied the method to the large Hutterine pedigree. Our results indicate that the breaking and reduction of inbreeding loops can greatly diminish the power to localize quantitative trait loci. We also present an efficient Monte Carlo method for estimating identity-by-descent allele sharing in large complex pedigrees. This method is used to facilitate a linkage analysis of serum IgE levels in the Hutterites without simplifying the pedigree.

Adult↗
PubMed2005

Comparison of single-nucleotide polymorphisms and microsatellites in detecting quantitative trait loci for alcoholism: the Collaborative Study on the Genetics of Alcoholism.

BACKGROUND: The feasibility of effectively analyzing high-density single nucleotide polymorphism (SNP) maps in whole genome scans of complex traits is not known. The purpose of this study was to compare variance components linkage results using different density marker maps in data from the Collaborative Study on the Genetics of Alcoholism (COGA). Marker maps having an average spacing of 10 cM (microsatellite), 0.78 cM (SNP1), and 0.31 cM (SNP2) were used to identify quantitative trait loci (QTLs) affecting maximum number of alcoholic drinks consumed in a 24-hour period (Inmaxalc). RESULTS: Heritability of Inmaxalc was estimated to be 15%. Multipoint variance components linkage analysis revealed similar linkage patterns among the three marker panels, with the SNP maps consistently yielding higher LOD scores. Robust LOD scores > 1.0 were observed on chromosomes 1 and 13 for all three marker maps. Additional LODs > 1.0 were observed on chromosome 4 with both SNP maps and on chromosomes 18 and 21 with the SNP2 map. Peak LOD scores for Inmaxalc were observed on chromosome 1, although none reached genome-wide statistical significance. Quantile-quantile plots revealed that the multipoint distribution of SNP results appeared to fit the asymptotic null distribution better than the twopoint results. CONCLUSION: In conclusion, variance-components linkage analysis using high-density SNP maps provided higher LOD scores compared with the standard microsatellite map, similar to studies using nonparametric linkage methods. Widespread application of SNP maps will depend on further improvements in the computational methods implemented in current software packages.

Alcoholism↗
PubMed2005

Quantitative trait loci with age-specific effects on fecundity in Drosophila melanogaster.

Life-history theory and evolutionary theories of aging assume the existence of alleles with age-specific effects on fitness. While various studies have documented age-related changes in the genetic contribution to variation in fitness components, we know very little about the underlying genetic architecture of such changes. We used a set of recombinant inbred lines to map and characterize the effects of quantitative trait loci (QTL) affecting fecundity of Drosophila melanogaster females at 1 and 4 weeks of age. We identified one QTL on the second chromosome and one or two QTL affecting fecundity on the third chromosome, but these QTL affected fecundity only at 1 week of age. There was more genetic variation for fecundity at 4 weeks of age than at 1 week of age and there was no genetic correlation between early and late-age fecundity. These results suggest that different loci contribute to the variation in fecundity as the organism ages. Our data provide support for the mutation accumulation theory of aging as applied to reproductive senescence. Comparing the results from this study with our previous work on life-span QTL, we also find evidence that antagonistic pleiotropy may contribute to the genetic basis of senescence in these lines as well.

Aging↗
PubMed2001

Further characterization and high-resolution mapping of quantitative trait loci for ethanol-induced locomotor activity.

Differential sensitivity to the stimulant effects of ethanol on locomotor activity is determined in part by genetic differences. Among inbred strains of mice, moderate doses of ethanol (1-2 g/kg) stimulate locomotor activity in some strains, e.g., the DBA/2J (D2), but only mildly affect activity in other strains, e.g., C57BL/6J (B6) (Crabbe et al., 1982, 1983; Crabbe, 1986; Dudek and Phillips, 1990; Dudek et al., 1991; Dudek and Tritto, 1994). Quantitative trait loci (QTL) for the acute ethanol (1.5 g/kg) locomotor response has been identified in the BXD recombinant inbred (RI) series (N = 25 strains), a C57BL/6J x DBA/2J (B6D2) F2 intercross (N = 1800), and heterogeneous stock (HS) mice (N = 550). QTLs detected (p < .01) in the RI series were found on chromosomes 1, 2, and 6 and these QTLs were expressed in a time-dependent fashion. The QTLs on chromosomes 1 and 2 were confirmed in the F2 intercross at p < 10(-7) or better. HS mice from G32 to G35 were used to fine-map the chromosome 2 QTL. Compared to the consensus map, the genetic map in the HS animals was expanded 10- to 15-fold. Over the region flanked by D2Mit94 to D2Mit304, three separate QTLs were detected in the HS animals. The data obtained confirm the usefulness of HS mice for the fine-mapping of QTLs to a resolution of 2 cM or less.

Animals↗