Showing papers by "Chris Haley published in 2002"

QTL Express: mapping quantitative trait loci in simple and complex pedigrees

Abstract: QTL Express is the first application for Quantitative Trait Locus (QTL) mapping in outbred populations with a web-based user interface. User input of three files containing a marker map, trait data and marker genotypes allows mapping of single or multiple QTL by the regression approach, with the option to perform permutation or bootstrap tests.

Quantitative Trait Loci Analysis in Animals

Abstract: Most traits of economic importance in livestock and of medical importance in man are quantitative in nature, and hence the ability to unravel the genetics of quantitative traits is of major importance. Before the arrival of genetic markers, animal breeders had developed very effective tools to analyse quantitative trait variation. This knowledge was very effectively exploited through the prediction and selection of animals with high breeding values using statistical tools and information obtained from phenotypes and the pedigree alone and this had led to great improvements in the efficiency of livestock production. So effective were the tools developed by animal breeders that many questioned the value of dissecting and exploiting the individual quantitative trait loci (QTL) using marker information. However, traits such as disease resistance and meat quality can be difficult to improve by the traditional methods and direct genomic selection could add significantly to genetic progress for such traits. Thus over the last 10 years there has thus been a rapid growth of studies designed to map and ultimately identify genes underlying quantitative variation in animals. Joel Weller has been at the forefront of developing methods for QTL analysis in livestock (as well as making significant contributions in other areas of livestock genetics). Thus it is welcome to see his textbook on the analysis of QTL in animals, which presents much of the published material relevant to QTL detection by linkage in a coherent and accessible manner. The text takes the reader from setting the scene with the historical perspective through QTL mapping in inbred line crosses to QTL mapping using the various study designs possible in livestock. In a series of further chapters the book explores issues such as statistical power to detect QTL and optimisation of experimental designs, the setting significance thresholds and methods for fine mapping of QTL and multiple trait QTL analysis. Four chapters at the end explore selection in livestock, including theory and simulation studies in marker assisted selection and introgression. The book focuses mainly on the theoretical aspects of QTL analysis and results of simulation studies. There is little discussion of actual results or summaries of conclusions so far. There is also little discussion of the various software available for QTL analysis, thus the book will be of more interest to the theoretically minded, rather than the practitioner who wants to get their hands dirty with analysis. The ‘animal’ in the title does not include humans, so there is little direct mention of developments specifically applied in studies of man. The biggest omission as far as livestock are concerned is that the book stops short of mapping applications that utilise disequilibrium at the population level and this must be an area where many QTL studies in livestock will be undertaken in future. I would not agree with all of the conclusions presented in the book. For example the use of canononical transformation in multiple trait analyses has significant drawbacks and the interpretation of the false discovery rate criteria for assessing detected QTL has to be treated with care. Overall, however, there is much of value here and the book is certainly a must-have for anyone involved in the statistical analysis of QTL studies in livestock. It will also be of value to those interested in QTL analysis generally or in animal breeding and livestock genetics and a useful textbook for advanced undergraduate and postgraduate students. Experimentalists should not expect to be able to plunge straight into data analysis having read this book, but an understanding based on this text would be of great value in helping them avoid the pitfalls that can often trap the unwary in such a statistical subject as QTL analysis.

Genome-wide search for markers associated with bovine spongiform encephalopathy.

Abstract: A genome-wide search for markers associated with BSE incidence was performed by using Transmission-Disequilibrium Tests (TDTs). Significant segregation distortion, i.e., unequal transmission probabilities of alleles within a locus, was found for three marker loci on Chromosomes (Chrs) 5, 10, and 20. Although TDTs are robust to false associations owing to hidden population substructures, it cannot distinguish segregation distortion caused by a true association between a marker and bovine spongiform encephalopathy (BSE) from a population-wide distortion. An interaction test and a segregation distortion analysis in half-sib controls were used to disentangle these two alternative hypotheses. None of the markers showed any significant interaction between allele transmission rates and disease status, and only the marker on Chr 10 showed a significant segregation distortion in control individuals. Nevertheless, the control group may have been a mixture of resistant and susceptible but unchallenged individuals. When new genotypes were generated in the vicinity of these three markers, evidence for an association with BSE was confirmed for the locus on Chr 5.

No detectable association of the ESR PvuII mutation with sow productivity in a Meishan x Large White F2 population.

Abstract: The polymorphism at the PvuII recognition site in the ESR gene showed no statistically significant association with sow productivity traits in a Meishan x Large White F2 population. Estimates of the effect on litter size were, however, in the opposite direction and statistically different from previously published estimates. Taken together with results from other publications, results here indicate that this PvuII polymorphism displays different degrees of linkage disequilibrium with a gene or genes controlling litter size in different populations.

Genome-wide search for markers associated with bovine spongiform encephalopathy

Abstract: A genome-wide search for markers associated with BSE incidence was performed by using Transmission-Disequilibrium Tests (TDTs). Significant segregation distortion, i.e., unequal transmission probabilities of alleles within a locus, was found for three marker loci on Chromosomes (Chrs) 5, 10, and 20. Although TDTs are robust to false associations owing to hidden population substructures, it cannot distinguish segregation distortion caused by a true association between a marker and bovine spongiform encephalopathy (BSE) from a population-wide distortion. An interaction test and a segregation distortion analysis in half-sib controls were used to disentangle these two alternative hypotheses. None of the markers showed any significant interaction between allele transmission rates and disease status, and only the marker on Chr 10 showed a significant segregation distortion in control individuals. Nevertheless, the control group may have been a mixture of resistant and susceptible but unchallenged individuals. When new genotypes were generated in the vicinity of these three markers, evidence for an association with BSE was confirmed for the locus on Chr 5.

Approaches to interval mapping of QTL in a multigeneration pedigree: the example of porcine chromosome 4.

Abstract: Quantitative trait loci (QTLs) have been mapped in many studies of F 2 populations derived from crosses between diverse lines. One approach to confirming these effects and improving the mapping resolution is genetic chromosome dissection through a backcrossing programme. Analysis by interval mapping of the data generated is likely to provide additional power and resolution compared with treating data marker by marker. However, interval mapping approaches for such a programme are not well developed, especially where the founder lines were outbred. We explore alternative approaches to analysis using, as an example, data from chromosome 4 in an intercross between wild boar and Large White pigs where QTLs have been previously identified. A least squares interval mapping procedure was used to study growth rate and carcass traits in a subsequent second backcross generation (BC 2 ). This procedure requires the probability of inheriting a wild boar allele for each BC 2 animal for locations throughout the chromosome. Two methods for obtaining these probabilities were compared: stochastic or deterministic. The two methods gave similar probabilities for inheriting wild boar alleles and, hence, gave very similar results from the QTL analysis. The deterministic approach has the advantage of being much faster to run but requires specialized software. A QTL for fatness and for growth were confirmed and, in addition, a QTL for piglet growth from weaning at 5 weeks up to 7 weeks of age and another for carcass length were detected.

On the mapping of quantitative trait loci at marker and non-marker locations.

Abstract: Previous studies have noted that the estimated positions of a large proportion of mapped quantitative trait loci (QTLs) coincide with marker locations and have suggested that this indicates a bias in the mapping methodology. In this study we predict the expected proportion of QTLs with positions estimated to be at the location of a marker and further examine the problem using simulated data. The results show that the higher proportion of putative QTLs estimated to be at marker positions compared with non-marker positions is an expected consequence of the estimation methods. The study initially focused on a single interval with no QTLs and was extended to include multiple intervals and QTLs of large effect. Further, the study demonstrated that the larger proportion of estimated QTL positions at the location of markers was not unique to linear regression mapping. Maximum likelihood produced similar results, although the accumulation of positional estimates at outermost markers was reduced when regions outside the linkage group were also considered. The bias towards marker positions is greatest under the null hypothesis of no QTLs or when QTL effects are small. This study discusses the impact the findings could have on the calculation of thresholds and confidence intervals produced by bootstrap methods.

Simple deterministic identity-by-descent coefficients and estimation of QTL allelic effects in full and half sibs.

Abstract: Accurate and rapid methods for the detection of quantitative trait loci (QTLs) and evaluation of consequent allelic effects are required to implement marker-assisted selection in outbred populations. In this study, we present a simple deterministic method for estimating identity-by-descent (IBD) coefficients in full- and half-sib families that can be used for the detection of QTLs via a variance-component approach. In a simulated dataset, IBD coefficients among sibs estimated by the simple deterministic and Markov chain Monte Carlo (MCMC) methods with three or four alleles at each marker locus exhibited a correlation of greater than 0.99. This high correlation was also found in QTL analyses of data from an outbred pig population. Variance component analysis used both the simple deterministic and MCMC methods to estimate IBD coefficients. Both procedures detected a QTL at the same position and gave similar test statistics and heritabilities. The MCMC method, however, required much longer computation than the simple method. The conversion of estimated QTL genotypic effects into allelic effects for use in marker-assisted selection is also demonstrated.

Mapping of qtls for prolificacy traits on ssc8 using a candidate gene approach

Abstract: INTRODUCTION Sow prolificacy is a critical factor affecting the profitability of the swine industry. While there have been large increases in productivity attributable to improvement in genetics and management, litter size has remained unchanged for several decades. Genetic improvement has been difficult to achieve using traditional selection methods due to the low heritabilities of traits involved (Roehe and Kennedy, 1995). Meishan pigs are perhaps one of the most prolific breeds of pig in the world. They reach puberty at 2.5 3 months of age, achieve high embryo survival rates, and a large litter size of 15 16 pigs. Although a few Meishan-synthetic gilts appeared on the market in the early 1990s, the promise of a commercial boost to litter productivity has not yet been realized. The reason is that the large advantages in litter size are finely balanced with equally large disadvantages in growth and carcass value. Therefore, the identification and introduction of only alleles for the high prolificacy of Taihu pigs into highly productive European/American breeds would have obvious commercial value.

QTL detection in outbred populations; comparison of variance component and simple methods.

Abstract: INTRODUCTION In poultry and pigs, many QTL have been successfully mapped in experimental populations (Andersson, 2001). These experimental populations are mostly analysed by regression methods under a line-cross model (Haley et al., 1994) or a half-sib model (Knott et al., 1996). However, the regression methods do not take all relationships in a complex pedigree into account, do not generally include polygenic components and provide no genotypic value for the individual animals. Methods to jointly estimate QTL and polygenic effects have been suggested by Fernando and Grossman (1989). George et al. (2000) present a two-step approach for a variance component analysis of QTL. In the first step, the identity by descent (IBD) proportions at pre-defined genome locations are estimated between all related individuals, while in the second step the QTL and the polygenic effects are estimated by Residual Maximum Likelihood (REML). The IBD proportions are calculated using Monte Carlo Markov Chain (MCMC) methods, which require a large number of iterations (Heath, 1997). Pong-Wong et al. (2001) present a deterministic alternative for the estimation of IBD proportions, which increases the computation speed dramatically. When genotyping is only performed on two generations, and there are few additional relationships between families, the estimation of IBD proportions can be restricted to those within half-sib and full-sib families. Nagamine et al. (submitted) have developed a “simple” deterministic IBD approach that estimates within family IBD proportions. In this paper we compare the performance of the simple deterministic method (SMD) to that of the MCMC based method and the half-sib regression method, using data from commercial pig breeds.

PIGQTECH - transferring QTL technology to the pig breeding industry.

Abstract: INTRODUCTION In recent years there have been many publications detailing Quantitative Trait Loci (QTL) responsible for commercially important traits in domestic agricultural livestock. In pigs many QTLs such as fatness, growth, meat quality and reproductive traits have been reported (reviewed by Andersson 2001). In general however, industry has failed to capitalise on the wealth of QTL information available and apply these results to commercial populations. One reason for this is that these studies utilise an experimental resource population set up specifically for the purpose QTL mapping. Such populations are established to give the greatest likelihood of detection by crossing two lines or breeds of extreme phenotype. This is not the case in commercial populations which would hence require much larger samples of animals than from a line cross to provide similar power for detection of QTL. To address some of these issues this EC funded demonstration project was initiated to discover whether it was possible to detect segregation of published QTL in commercial populations. To study the applicability across different facets of the European pig breeding industry, we studied the effect of the same QTL region within different populations from around Europe. These populations were selected to span the range of relevant breeding companies from those of a large multinational breeding company (PIC, UK) to those from regional co-operative (Copaga, Lleida, Spain) and national breeding schemes (Quality Genetics, Sweden).