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PubMed2006

Bayesian reanalysis of a quantitative trait locus accounting for multiple environments by scaling in broilers.

A Bayesian method was developed to handle QTL analyses of multiple experimental data of outbred populations with heterogeneity of variance between sexes for all random effects. The method employed a scaled reduced animal model with random polygenic and QTL allelic effects. A parsimonious model specification was applied by choosing assumptions regarding the covariance structure to limit the number of parameters to estimate. Markov chain Monte Carlo algorithms were applied to obtain marginal posterior densities. Simulation demonstrated that joint analysis of multiple environments is more powerful than separate single trait analyses of each environment. Measurements on broiler BW obtained from 2 experiments concerning growth efficiency and carcass traits were used to illustrate the method. The population consisted of 10 full-sib families from a cross between 2 broiler lines. Microsatellite genotypes were determined on generations 1 and 2, and phenotypes were collected on groups of generation 3 animals. The model included a polygenic correlation, which had a posterior mean of 0.70 in the analyses. The reanalysis agreed on the presence of a QTL in marker bracket MCW0058-LEI0071 accounting for 34% of the genetic variation in males and 24% in females in the growth efficiency experiment. In the carcass experiment, this QTL accounted for 19% of the genetic variation in males and 6% in females.

Animal Husbandry↗
PubMed2005

Dissection of heterogeneous phenotypes for quantitative trait mapping.

We discuss analyses of Genetic Analysis Workshop 14 data from the Collaborative Study on the Genetics of Alcoholism (COGA) as well as from a simulated complex disease, Kofendrerd personality disorder (KPD), with both genetic and phenotypic heterogeneity. Both data sets included numerous related phenotypes in addition to disease definitions. All analyses either chose from the given selection of phenotypes or defined new ones, including traits that may not have been related to alcoholism or KPD. Some contributors evaluated the genetic components of the trait. Many investigated genome-wide linkage and/or association, using microsatellites and/or single-nucleotide polymorphism (SNP) chip data. Here we will focus on methodological issues that the investigators faced. Their results depended on phenotype selection, whether continuous or discrete, the covariates included, and ethnicity of the study population. For SNP chip data, members of our group detected no difference in results for Affymetrix or Illumina chips, although higher marker density for association studies appeared to be advantageous. Overall, there were some observations that different chromosomal segments, i.e., physical locations on the p-arm, q-arm, or middle segment, might lead to possible differences in type I error rates. This finding and others highlight the importance of empirical determination of P-values to determine significance.

Alcoholism↗
PubMed2001

Mapping of multiple quantitative trait loci by simple regression in half-sib designs.

Detection of QTL in outbred half-sib family structures has mainly been based on interval mapping of single QTL on individual chromosomes. Methods to account for linked and unlinked QTL have been developed, but most of them are only applicable in designs with inbred species or pose great demands on computing facilities. This study describes a strategy that allows for rapid analysis, involving multiple QTL, of complete genomes. The methods combine information from individual analyses after which trait scores for a specific linkage group are adjusted for identified QTL at other linkage groups. Regression methods are used to estimate QTL positions and effects; permutation tests are used to obtain empirical threshold values. The description of the methods is complemented by an example of the combined analysis of 28 bovine chromosomes and their associations with milk yield in Finnish Ayrshire cattle. In this example, the individual analysis revealed five suggestive QTL affecting milk yield. Following the strategy presented in this paper, the final combined analysis showed eight significant QTL affecting milk yield. This clearly demonstrates the potential gain of using the combined analysis. The use of regression methods, with low demands on computing resources, makes this approach very practical for total genome scans.

Animals↗
PubMed2003

Generation and analysis of an artificial gene dosage series in tomato to study the mechanisms by which the cloned quantitative trait locus fw2.2 controls fruit size.

It has been proposed that fw2.2 encodes a negative fruit-growth regulator that underlies natural fruit-size variation in tomato (Lycopersicon spp.) via heterochronic allelic variation of fw2.2 expression, rather than by variation in the structural protein itself. To further test the negative regulator and the transcriptional control hypotheses, a gene dosage series was constructed, which produced a wider range of fw2.2 transcript accumulation than can be found in natural tomato populations. Fruit developmental analyses revealed that fw2.2 transcript levels were highly correlated (negatively) with fruit mass, supporting the negative regulator and transcriptional regulation hypotheses. Further, the effect of fw2.2 on fruit mass was mediated by repressing three- and two-dimensional cell division in placental and pericarp tissues, respectively. Finally, fw2.2 had little effect on fertility and seed size/number, indicating that fruit size effects of fw2.2 are due largely to expression in the maternal tissues of developing fruit and not mediated through fertility or seed-setting-related processes.

Alleles↗
PubMed2001

Quantitative trait locus mapping in laboratory mice derived from a replicated selection experiment for open-field activity.

Bidirectional selection in rodents has been used to derive animal models of human behavior. An important question is whether selection for behavior operates on a limited number of QTL or whether the number and individual contribution of QTL varies between selection experiments. To address this question, we mapped QTL in two large F2 intercrosses (N = 815 and 821) from the four lines derived from a replicated selection experiment for open-field activity, an animal model for susceptibility to anxiety. Our analyses indicate that selection operated on the same relatively small number of loci in both crosses. Haplotype information and the direction of effect of each QTL allele were used to confirm that the QTL mapped in the two crosses lie in the same chromosomal regions, although we were unable to determine whether QTL in the two crosses represent the same genes. We conclude that the genetic architecture of the selected strains is similar and relatively simple.

Animals↗
PubMed2004

Quantitative trait loci affecting life span in replicated populations of Drosophila melanogaster. I. Composite interval mapping.

Composite interval mapping was used to identify life-span QTL in F2 progeny of three crosses between different pairs of inbred lines. Each inbred line was derived from a different outbred population that had undergone long-term selection for either long or short life span. Microsatellite loci were used as genetic markers, and confidence intervals for QTL location were estimated by bootstrapping. A minimum of 10 QTL were detected, nine of which were located on the two major autosomes. Five QTL were present in at least two crosses and five were present in both sexes. Observation of the same QTL in more than one cross was consistent with the hypothesis that genetic variation for life span is maintained by balancing selection. For all QTL except one, allelic effects were in the direction predicted on the basis of outbred source population. Alleles that conferred longer life were always at least partially dominant.

Analysis of Variance↗
PubMed1998

The association of flowering time quantitative trait loci with duplicated regions and candidate loci in Brassica oleracea.

A population of 150 doubled haploid lines of rapid cycling Brassica oleracea, derived from an F1 from a var. alboglabra x var. italica cross, was scored for flowering time in two trials. Using information on 82 mapped molecular markers, spread evenly across the nine linkage groups, QTL were identified at six locations; one each on linkage groups O2 and O3 and two each on linkage groups O5 and O9. In total, these QTL explained 58 and 93% of the genetical variation in the two trials. Three of these QTL, on linkage groups O2, O3, and O9, were situated in regions showing considerable homology both with each other and with chromosome regions of B. nigra that have been shown to affect flowering time. These same regions are all homologous to a single tract of Arabidopsis chromosome 5, which contains a number of the flowering-related genes, one or more of which may be candidates for the QTL found in Brassica.

Brassica↗
PubMed2003

Molecular dissection of a quantitative trait locus: a phenylalanine-to-tyrosine substitution in the transmembrane domain of the bovine growth hormone receptor is associated with a major effect on milk yield and composition.

We herein report on our efforts to improve the mapping resolution of a QTL with major effect on milk yield and composition that was previously mapped to bovine chromosome 20. By using a denser chromosome 20 marker map and by exploiting linkage disequilibrium using two distinct approaches, we provide strong evidence that a chromosome segment including the gene coding for the growth hormone receptor accounts for at least part of the chromosome 20 QTL effect. By sequencing individuals with known QTL genotype, we identify an F to Y substitution in the transmembrane domain of the growth hormone receptor gene that is associated with a strong effect on milk yield and composition in the general population.

Amino Acid Substitution↗
PubMed2004

Mapping of a milk production quantitative trait locus to a 420-kb region on bovine chromosome 6.

A QTL affecting milk production traits was previously mapped to an interval of 7.5 cM on chromosome 6 in Norwegian dairy cattle. This article aimed to refine this position by increasing the map density in the region by a set of single-nucleotide polymorphisms and analyzing the data with a combined linkage and linkage disequilibrium approach. Through a series of single- and multitrait and single- and multipoint analyses, the QTL was positioned to an interval surrounded by the genes ABCG2 and LAP3. As no recombinations were detected in this interval, physical mapping was required for further refining. By using radiation hybrid mapping as well as BAC clones, the bovine and human comparative maps in the region are resolved, and the QTL is mapped within a distance of 420 kb.

Animals↗
PubMed2006

A quantitative trait locus for recognition of foreign eggs in the host of a brood parasite.

Avian brood parasites reduce the reproductive output of their hosts and thereby select for defence mechanisms such as ejection of parasitic eggs. Such defence mechanisms simultaneously select for counter-defences in brood parasites, causing a coevolutionary arms race. Although coevolutionary models assume that defences and counter-defences are genetically influenced, this has never been demonstrated for brood parasites. Here, we give strong evidence for genetic differences between ejector and nonejectors, which could allow the study of such host defence at the genetic level, as well as studies of maintenance of genetic variation in defences. Briefly, we found that magpies, that are the main host of the great spotted cuckoo in Europe, have alleles of one microsatellite locus (Ase64) that segregate between accepters and rejecters of experimental parasitic eggs. Furthermore, differences in ejection rate among host populations exploited by the brood parasite covaried significantly with the genetic distance for this locus.

Animals↗
PubMed2004

Derivation of a Bayes factor to distinguish between linked or pleiotropic quantitative trait loci.

A simple procedure to calculate the Bayes factor between linked and pleiotropic QTL models is presented. The Bayes factor is calculated from the marginal prior and posterior densities of the locations of the QTL under a linkage and a pleiotropy model. The procedure is computed with a Gibbs sampler, and it can be easily applied to any model including the location of the QTL as a variable. The procedure was compared with a multivariate least-squares method. The proposed procedure showed better results in terms of power of detection of linkage when low information is available. As information increases, the performance of both procedures becomes similar. An example using data provided by an Iberian by Landrace pig intercross is presented. The results showed that three different QTL segregate in SSC6: a pleiotropic QTL affects myristic, palmitic, and eicosadienoic fatty acids; another pleiotropic QTL affects palmitoleic, stearic, and vaccenic fatty acids; and a third QTL affects the percentage of linoleic acid. In the example, the Bayes factor approach was more powerful than the multivariate least-squares approach.

Animals↗
PubMed1997

Marker-assisted introgression of quantitative trait loci.

The use of molecular markers for the introgression of one or several superior QTL alleles into a recipient line is investigated using analytic and simulation results. The positions of the markers devoted to the control of the genotype at the QTLs in a "foreground selection" step are optimized given the confidence interval of the QTL position. Results demonstrate that using at least three markers per QTL allows a good control over several generations. Population sizes that should be recommended for various numbers of QTLs are calculated and are used to determine the limit in the number of QTLs that can be monitored simultaneously. If "background selection" devoted to accelerate the return to the recipient parent genotype outside the QTL regions is applied, the positions of the markers devoted to the control of the QTLs have to be reconsidered. When several QTLs are monitored simultaneously, background selection among the limited number of individuals resulting from the foreground selection step accelerates the increase in genomic similarity with the recipient parent, with only limited costs. Background selection is even more efficient in a pyramidal backcross program where QTLs are first monitored one by one.

Alleles↗
PubMed2006

Fine-mapping of coccidia-resistant quantitative trait loci in chickens.

Two commercial, pure broiler lines with different susceptibility to coccidiosis were used to fine-map QTL associated with the previously identified marker LEI0101, located at 259 cM on chromosome 1 and shown to be significantly associated with disease resistance. Eight additional microsatellite markers linked to LEI0101 were used for genotyping of F(1) parents and F(2) offspring (n = 314), and their associations with oocyst shedding, as a marker of disease resistance, were determined in birds experimentally infected with Eimeria maxima. Single-point analysis of 4 families showed that logarithm of odds (LOD) scores at all marker loci were > 0.5, with the exception of marker LEI0071, located at 242 cM (LOD score = 2.45). Multipoint analysis showed a maximum LOD score between LEI0071 and LEI0101 at 254 cM (LOD score = 3.74). Although the LEI0071 marker was mapped near LEI0101 by linkage analysis, the physical location of LEI0071 was not identified. Further studies to determine the physical locations of these and other markers will allow additional application association mapping techniques using single nucleotide polymorphism markers.

Animals↗
PubMed2000

Quantitative trait loci mapping in F(2) crosses between outbred lines.

We develop a mixed-model approach for QTL analysis in crosses between outbred lines that allows for QTL segregation within lines as well as for differences in mean QTL effects between lines. We also propose a method called "segment mapping" that is based in partitioning the genome in a series of segments. The expected change in mean according to percentage of breed origin, together with the genetic variance associated with each segment, is estimated using maximum likelihood. The method also allows the estimation of differences in additive variances between the parental lines. Completely fixed random and mixed models together with segment mapping are compared via simulation. The segment mapping and mixed-model behaviors are similar to those of classical methods, either the fixed or random models, under simple genetic models (a single QTL with alternative alleles fixed in each line), whereas they provide less biased estimates and have higher power than fixed or random models in more complex situations, i.e., when the QTL are segregating within the parental lines. The segment mapping approach is particularly useful to determining which chromosome regions are likely to contain QTL when these are linked.

Chromosome Mapping↗
PubMed2005

Simulating the collaborative cross: power of quantitative trait loci detection and mapping resolution in large sets of recombinant inbred strains of mice.

It has been suggested that the collaborative cross, a large set of recombinant inbred strains derived from eight inbred mouse strains, would be a powerful resource for the dissection of complex phenotypes. Here we use simulation to investigate the power of the collaborative cross to detect and map small genetic effects. We show that for a fixed population of 1000 individuals, 500 RI lines bred using a modified version of the collaborative cross design are adequate to map a single additive locus that accounts for 5% of the phenotypic variation to within 0.96 cM. In the presence of strong epistasis more strains can improve detection, but 500 lines still provide sufficient resolution to meet most goals of the collaborative cross. However, even with a very large panel of RILs, mapping resolution may not be sufficient to identify single genes unambiguously. Our results are generally applicable to the design of RILs in other species.

Animals↗
PubMed2000

Combined analyses of data from quantitative trait loci mapping studies. Chromosome 4 effects on porcine growth and fatness.

For many species several similar QTL mapping populations have been produced and analyzed independently. Joint analysis of such data could be used to increase power to detect QTL and evaluate population differences. In this study, data were collated on almost 3000 pigs from seven different F(2) crosses between Western commercial breeds and either the European wild boar or the Chinese Meishan breed. Genotypes were available for 31 markers on chromosome 4 (on average 8.3 markers per population). Data from three traits common to all populations (birth weight, mean backfat depth at slaughter or end of test, and growth rate from birth to slaughter or end of test) were analyzed for individual populations and jointly. A QTL influencing birth weight was detected in one individual population and in the combined data, with no significant interaction of the QTL effect with population. A QTL affecting backfat that had a significantly greater effect in wild boar than in Meishan crosses was detected. Some evidence for a QTL affecting growth rate was detected in all populations, with no significant differences between populations. This study is the largest F(2) QTL analysis achieved in a livestock species and demonstrates the potential of joint analysis.

Adipose Tissue↗
PubMed2001

Mapping epistatic quantitative trait loci with one-dimensional genome searches.

The discovery of epistatically interacting QTL is hampered by the intractability and low power to detect QTL in multidimensional genome searches. We describe a new method that maps epistatic QTL by identifying loci of high QTL by genetic background interaction. This approach allows detection of QTL involved not only in pairwise but also higher-order interaction, and does so with one-dimensional genome searches. The approach requires large populations derived from multiple related inbred-line crosses as is more typically available for plants. Using maximum likelihood, the method contrasts models in which QTL allelic values are either nested within, or fixed over, populations. We apply the method to simulated doubled-haploid populations derived from a diallel among three inbred parents and illustrate the power of the method to detect QTL of different effect size and different levels of QTL by genetic background interaction. Further, we show how the method can be used in conjunction with standard two-locus QTL detection models that use two-dimensional genome searches and find that the method may double the power to detect first-order epistasis.

Alleles↗
PubMed2000

Identification of quantitative trait loci affecting birth characters and accumulation of backfat and weight in a Meishan-White Composite resource population.

A search for genomic regions affecting birth characters and accretion of weight and backfat was conducted in a Meishan-White Composite reciprocal backcross resource population. Birth traits analyzed (n = 750) were vigor score, number of nipples, and birth weight. Subsequent measures on gilts and barrows (n = 706) analyzed were weaning weight, 8-wk weight, ADG from 8 to 18 wk of age, ADG from 18 to 26 wk of age, 26-wk weight, and backfat over the first rib, last rib, and last lumbar vertebrae at 14 and 26 (n = 599) wk of age. Feed intake and growth of 92 individually penned barrows were also analyzed. A genomic scan was conducted with microsatellite markers spaced at approximately 20-cM intervals, a least squares regression interval analysis was implemented, and significance values were converted to genomewide levels. No associations were detected for traits measured at birth except for number of nipples, where one significant and two suggestive regions were identified on chromosomes (SSC) 10, 1, and 3, respectively. Early growth was affected by a region on SSC 1 as evidenced by associations with weights collected at weaning and 8 wk of age and ADG from 8 to 18 wk of age. Other regions detected for early growth rate were on SSC 2, 12, and X. Chromosomal regions on SSC 6 and 7 affected ADG from 18 to 26 wk of age. All measures of backfat were affected by regions on SSC 1 and X, whereas SSC 7 consistently affected backfat measures recorded at 26 wk of age. Suggestive evidence for QTL affecting backfat at 14 wk of age was also detected on SSC 2, 6, 8, and 9. These results have improved our knowledge about the genetics of growth rate and fat accretion at the molecular level in swine.

Adipose Tissue↗