Quantitative genetic analysis using molecular markers with applications to fish populations

This doctoral thesis presents statistical methods for the analysis of existing and new designs of quantitative trait loci (QTL) mapping experiments that are applicable in fish. These designs include both crosses between inbred lines and the use of existing outbred populations. A review of the literature evidenced the lack of information regarding the exploitation of the biology and the possibility of using gynogenesis or androgenesis to map QTL in fish. Simulation results show the great advantages in terms of power of using double haploids from crosses between clonal lines to map QTL. Under the inbred line cross design, posterior evidence for the presence of QTL influencing components of early development in rainbow trout was assessed with Bayesian inference in a double haploid population obtained from a cross between clonal lines. These lines show significant differences in early development traits. The Bayesian model was developed in order to accomodate environmental factors influencing the phenotypic expression of the quantitative traits. Simulation was used to assess the behaviour of the method. The Bayesian analysis revealed QTL for time at hatching, embryonic length and weight. The posterior expectation of the number of QTL in different linkage groups shows that at least four QTL are needed to explain the observed differences of early development between the clonal lines. The Bayesian method implemented proved to be an efficient tool for QTL analysis using the double haploid design. I developed a novel method to compute the power to detect QTL using the double haploid (DH), full sib (FS) and hierarchical (HI) designs implemented in outbred fish populations for interval mapping using deterministic methods. The power was consistently greater for the DH design compared to the standard FS and HI designs. Overall, the results suggested that the DH design could be a very useful tool for QTL mapping in fish, and of particular importance when the effects of the QTL are small. It is likely that QTL experiments in fish using chromosomal manipulations will be carried out using existing outbred populations, however current methods could not combine information from related double haploids and full sibs in the same analysis. I developed the variance component method of linkage to enable QTL to be mapped in these outbred structures. Including double haploids in the outbred mapping population, in a range of scenarios likely to be found in practice, gave greater power to detect QTL compared to standard outbred structures (i.e. full sib families). A relatively large increase in the precision of estimated genetic parameters was obtained when combining information from double haploids and full sibs obtained from the same family unit. There is a lack of research regarding the incorporation of dominance in the model of analysis to map QTL using the variance component method. Many experiments from crosses between inbred lines have found a varying degree of dominance for many traits of economic importance whereas the usual model assumes additive effects for the QTL. It is not clear to what extent incorporating dominance effects may increase the chance of detecting a dominant QTL. I extended the variance component method to include the estimation of the dominance variance at the postulated QTL and found that neglecting dominance produced biased estimates of the additive genetic variance, but power was very similar compared to the strategy in which the full covariance structure (with additive and dominance components) was used to map the QTL. Using only the covariance structure of additive effects appeared to be an efficient way to search for QTL, irrespective of the degree of dominance. I also investigated the extension of the variance component method to the analysis of multiple, correlated traits simultaneously to map QTL and to distinguish between linkage and pleiotropy. Even relaxing some of the stringent assumptions proposed in the literature, the method did not perform well in terms of detecting the correct underlying genetic model. This was due to the fact that, to be computationally feasible, a number of assumptions regarding the base population being in linkage equilibrium are needed. Overall, the research carried out highlights the possibilities of integrating molecular markers with phenotypic information in order to investigate genes affecting the expression of quantitative traits in fish populations. The incorporation into the mapping population of genetically manipulated fish to produce double haploid individuals can substantially improve the ability to detect these genes and accurately estimate their effects.