Molecular Dissection Of Pleiotropic Component Of Genetic Correlation

Genetic correlation is an important genetic parameter to reveal the between-trait relationships, which has been applied in a wide spectrum of fields such as animal breeding and evolution. The genetic mechanism underlying the phenomena of genetic correlation is mainly involved in pleiotropy and linkage disequilibrium. From a quantitative variation perspective, there have different components contributing to the shape of genetic correlation. However, up to date, the estimation of genetic correlation is chiefly based on a holistic evaluation of the total genome from a blackbox consideration. When the time comes that the unveiling of the molecular base of quantitative traits has become one of the research highlight in the sector of life sciences, it is necessary to undertake a quantitative dissection of subcomponents of genetic correlation from the gene level. For the molecular anatomy of gene pleiotropy, there has high scientific importance to establish the methodological frame for fine dissection of the subcomponents of genetic correlation, which embodies the acceleration of elaborate understanding of the genetic relationships among multitraits as well as the practical support of multitrait breeding program at the molecular level.Based on the subject of quantitative genetic analysis of pleiotropy, the main effort of this investigation was to explore the issue concerning the fine dissection of pleiotropic component of genetic correlation through candidate gene approach. The work was performed in accordance with the historic development pattern of quantitative genetic theories and methods, the main aspects of which included the achievements of principia, mathematical model and calculation formula for quantitative dissection of pleiotropy after the proposal of a set of novel concepts. The data involving in the FSHβgene and reproduction traits from Jiangquhai sows was later utilized to conduct the case analysis. The highlighted results of this investigation are summarized as following:1. Proposed a set of novel concepts including partial genetic correlation, partial additive correlation, partial dominant correlation, partial epistatic correlation, residual genetic correlation, partial heritability, residual heritability, comprehensive heritability, comprehensive partial heritability, comprehensive residual heritability, contribution coefficient of correlation, etc., and gave their linguistic definitions for the first time. From the standpoint of scientific philosophy, concept is theoretically the organizer of a theoretical frame, and the above-mentioned concepts have provided the conceptual base for the subsequent establishments of estimation approaches of pleiotropic component of genetic correlation. 2. Redescribed the concepts including total genetic correlation, partial genetic correlation, residual genetic correlation, residual correlation, etc. in algebraic language, and provided the mathematical annotation and illustration of the quantificational relationships between genetic correlation and its components in details.3. Based on the proposal of the novel concepts, the methods for dissection of the pleiotropic components were systematically established. The two-model strategy was utilized to configure the estimation methods of partial genetic correlation, partial additive correlation and partial dominant correlation, and their calculation formulae were derived through the variance-covariance components of the genotype and allele, respectively.4. Under the condition of more than one gene, the three-model strategy was utilized to configure the estimation methods of epistatic correlation, and according to conditions that the genes are independent or partially linkaged, based on the variance-covariance components being dissected from the combined genotype, genotype and allele, the calculation formulae for partial genetic correlation, partial additive correlation, partial dominant correlation and epistatic correlation were derived, respectively.5. In the subsequent case analysis, the research strategy for evaluating milk performance in cows was introduced into evaluating the reproduction performance in sows. By making use of the raw data from Jiangquhai sows, according to the phenotypic characteristics of life-cycle and fluctuation with parities, four mathematical models including Poisson cycle model, cubic polynomial model, modified quadratic polynomial model I and modified quadratic polynomial model II were respectively used to fit the litter size model. From the viewpoints of statistics and biological meaning, modified quadratic curve I was the optimum model of litter size. the heritabilities of total number born (TNB), number born alive (NBA), litter weight at birth (LWB), average daily gains (ADG) (0-20 days), age at puberty (AP), weaning to service interval (WSI), preweaning number dead (PND), intra-individual SD in litter size (IISDLS) and optimum model parameters were estimated.6. A preliminary analysis was performed to affirm the traits on which the FSHβgene has a significant genetic effect, and the primarily confirmed traits included the optimum model parameter C of total number born, the acme of optimum model (A-B~2/4C), litter weight at birth, total number born and number born alive, which hinted that the FSHβgene plays a pleiotropic role of on the reproduction traits of sows. Finally, bivariate animal models of each trait pair were run to dissect the pleiotropic components of genetic correlation on the FSHβgene, and the partial genetic correlations, partial additive correlations, partial dominant correlations and their contribution coefficients were obtained.