Based On Bayesian Algorithm Carcass Traits Genomic Selection Preliminary Study In Chinese Simmental Cattle

Meuwissen since 2001 with theory of Genomic Selection, animal breeding technology from molecular marker assisted selection level to raise the level of the genome selection of omics, realize one time span of the animal breeding technology. With biochip technology, high-throughput sequencing technology and the rapid development of computer technology, make in the present field of life science, big data era genome selection techniques to be applied in the field of animal breeding.This study used 821 individuals of Chinese simmental cattle resources group of dragon, tmilong,knuckle,silver,hindshank and buttom five traits, based on high density genotyping chip data for research of GS.First, use of the above five traits were significant environmental effects of study, and build environmental effect equation;The above five traits were ST-Bayes theorem, A ST-Bayes theorem and ST B-the Bayes CPi three algorithms of single character GEBV estimates.Including ST-GEBV estimation accuracy of the Bayes method B is best, ST-Bayes theorem and ST-A Bayes theorem of CPi estimate accuracy, the accuracy of the single and ST-the Bayes CPi algorithm was slightly better than ST-Bayes theorem A algorithm;GWAS analysis, is studied by using the above five traits to site more significant than five as a site of significant standard, among them, the five traits of GWAS analysis, site focuses on chromosome 3 significantly.This research studied the screening of GS site using GPOPSIM data simulation in the first place, and the estimation Accuracy evaluation method based on the screening of loci (PA, Prediction Accuracy) research.Based on regression coefficient CV (Cross Validation) method and the traditional CV method, and prove the CV method based on regression coefficient compared to traditional methods of CV reflects a certain advantage.And CV method of regression coefficient parameters optimization. Studies have shown that screening sites based on ST-Bayes theorem, A algorithm of accuracy is estimated based on the PA process 2 times and repeat 8 times of CV algorithm using ST-Bayes theorem, A best estimate accuracy.Screening sites using the same genetic distance, ST-Bayes theorem and ST-A Bayes algorithm estimates the effect of B value and the P value of GWAS four site strategy for site selection and use of ST-the Bayes algorithm for estimation of GEBV A.ST -Bayes theorem is used to study proved A and ST-the Bayes algorithm estimates the effect of B value filtering site effect is best, at about 7 to 8 k can achieve higher accuracy, and the second is considered equal to the genetic distance of site selection strategy, to reach A plateau at about 15 k, and force the P value effect of GWAS increased significantly at low densities, around 40 k compared to the uniform method of site selection reflects the advantage.