Study On The Methods Of Haplotype Analysis In Animal Quantitative Trait's Candidate Genes

In recent years, many researchers studied candidate gene of quantitative trait through candidate gene methods. However, we found that the candidate gene analysis both in statistical methodology or in the presence of their applications have a large number of issues: there are a number of polymorphic loci in a candidate gene, different conclusions were got through analyzing the different polymorphic loci, and often minimal effect, it is difficult to detect. In addition, the ultimate aim of the candidate gene analysis was for conservation or selection. However, the use of the candidate gene or marker-assisted selection, have been a complex problem. Here is divided into two situations: First, assume that there is only one candidate gene, its effect even big enough to be called a major gene, the effect is still relatively small. It will be biased even if a supplement to its complementary role will be very limited. Second, a separate analysis of a number of candidate gene polymorphism loci, often in the same individual with a different gene loci on the merits may be inconsistent, and can not makes advantage of the most outstanding individual.Currently, in the human genome research, haplotype analysis has been applied to the association analysis between the SNP loci with complex diseases. Haplotype is a group linked SNP sites located in a region or a chromosome. Much of the evidence shows that in a single gene cis-location (such as in the same haplotype) mutations can be composed of a super alleles, and to play a major phenotypic role. Obviously, haplotype analysis provides a mechanism for a more convenient, more efficient way for the use of SNP to research complex genetic traits.Research contents are as following:1 Establishment of haplotype animal model:Haplotype animal model was established combining the haplotype statistical advantages and animal models. We developed Gibbs sampling method for the estimation and prediction of haplotype fixed effects and other random effect variance components. Hypothesis tests were tested through simulation of the type I error and the power. The values of Haplotype and the traits were simulated under the haplotype frequencies, the SNP haplotype diversity and environmental effects. Simulation studies show that haplotype diversity SNP and haplotype frequency have little influence on the overall situation. Type I errors of global test are very close to the normal lelvel. Whether or not to consider other fixed effects, the haplotype animal model analysis methods have better fitting results, and we can see that the model has good stability. The power of global test results show that simulated detection effectiveness, whether or not containing consider other fixed effects, the haplotype animal models have higher detection power, but the low haplotype diversity and middle haplotype diversity has slightly higher detection power than high haplotype diversity. Types I error of haplotype specific test showed that when haplotype diversity is high and the haplotype frequencies is smaller, the type I error rate deviated from the normal level. The test results were inconsistent with the globle test, and the suggestion was that we should first find tag SNP or used other methods to reduce dimension of haplotype, and then re-use our model to solve effect value. The power of haplotype specific test showed that whether bananced sampling of not, there is not significant difference, but both lose power when the haplotype diversity was high and the haplotype frequencies was much lower (q=0.1).2 Establishment of haplotype random regression model:Quantitative trait such as mild yield in dairy cows, litter size in pigs and fruit size in tomatoes are kown to change over time; they are inherently longitudinal in nature. The exploration of such traits candidate gene haplotype analysis methods, can rich quantitative trait genetic research theories and accelerate their genetic with improvement speed. This study extended application areas of haplotype association analysis. Gibbs sampling method was used for the estimation of haplotype fixed effects and prediction of random regression coefficient. Hypothesis tests were tested through simulation of the type I error and the power. Type I error of global test showed that, the type I error, regardlessα= 0.05 or 0.01, the data in the table are very close to the normal value. Regardless of the banlanced and unbanlanced sampling, the haplotype random regression analysis model has better fitting effect. Based on different haplotype diversity and haplotype tag SNP frequency on the model, the type I error has little effect on the stability of the model. The power of global test simulation results showed that the detection power of our proposed haplotype random regression model approached 1, and the banlanced sampling had slightly higher detection power than unbanlanced samping, which suggested that researchers should sample banlanced samples as far as possible in the experimental design. Types I error of haplotype specific test study showed that banlanced sampling, regardlessα= 0.05 or 0.01, the data in the table are very close to the normal value. In unbanlanced sampling, when the haplotype diversity high, and the specific haplotype frequencies was lower (q = 0.1), type I error rate slightly deviated from the normal level. The power of haplotype specific test showed that the detection power was no significant differences between banlanced sampling and unbanlanced sampling. Higher haplotype diversity, and lower specific haplotype frequencies (q = 0.1), detection power has decreased based on both the banlanced sampling and unbanlanced sampling.3 Meishan pigs ESR gene haplotypes analysis:Meishan pig is famous for the outstanding reproduction performance. It is necessary to preserve the precious genetic resource for the economic benefit and sustainable development of pig industry. This study did series of researches on the conserved population of Meishan pig from Jiading Meishan pig breeding center, Shanghai, and acquired many instructional results. We established haplotype random regression model to apply to the Meishan porcine reproductive traits candidate gene studies to guide pig factory haplotype-assisted selection and conservation, with a view to accelerating genetic improvement of their speed. We analysis three polymorphic sites (PvuII, AvaI and MspA1I) of ESR gene composed of haplotype. Results showed that haplotype ABB has a significant effect on litter size. Domestic and foreign scholars on PvuII site studies show that the BB genotype is the advantage, but our studies show that the first site for the T nucleotide on the haplotype has not significant effects on reproduction performance, but the the haplotype ABB which the first site si the C nucleotide sites has significant impact on litter size, probably because the study population has relatively unique genetic resources. In order to facilitate the genetic improvement, the results will be sought by haplotype effect and the remaining minor genes EBV value. By the results, 1-12 parity breeding value and the ABB haplotype effects are inconsistent with the order of ranking. Outstanding individual may be wrong screening according to a separate screening indicator. The results of a comprehensive study fully considering the significant impact on the litter size haplotype ABB and residual effects of minor genes breeding value could be developed relatively reasonable selection and matching program in accordance with both phenotypic and molecular information.4 haplotype association analysis software system development:We developed a friendly interface, powerful, easy-to-use haplotype association analysis application software systems, and two of these received software copyrights for the promotion of application. In accordance with the functions, the software system will be divided into several modules for system design and development. System modules can independently accomplish the tasks assigned, but also mutual coordination and complete simulation of statistical analysis to a series of statistical analysis functions. These include genotype data and time covariable management and preconditioning module, phenotypic data generated simulation module, haplotype and tag-SNPs analysis module, model evaluated module, haplotype animal model statistical analysis module and haplotype random regression model statistical analysis module.In summary, we established haplotype animal model and haplotype random regression model to screen the significant haplotypes. The simulation study has confirmed the reliability of the model and the models were used for the application study of Meishan pigs'reproductive traits. Especially for complex pedigree information and longitudinal data, our study put forwarded the more reliable haplotype association analysis methods. The results of this study will not only promote the quantitative trait candidate gene studies, but also provide a theoretical foundation of the implementation of haplotype marker-assisted selection, as well as provide convenient application software systems for breeding workers and researchers.