952
Changes in Variance of Top SNP Windows over Generations under Selection for Three Traits in Broiler Chicken

Tuesday, July 22, 2014
Exhibit Hall AB (Kansas City Convention Center)
Breno d Fragomeni , University of Georgia, Athens, GA
Ignacy Misztal , University of Georgia, Athens, GA
Daniela Lourenco , University of Georgia, Athens, GA
Ignacio Aguilar , Instituto Nacional de Investigación Agropecuaria, Las Brujas, Uruguay
Rachel Hawken , Cobb-Vantress Inc., Siloam Springs, AR
Abstract Text:

The purpose of this study was to determine whether the top SNP windows that explain the most variance are stable over multiple generations of selection in a GWAS analysis using single-step GBLUP. Phenotypes were available for five generations of a pure line of broiler chicken for body weight, breast meat, and leg score. Pedigrees included 297,017 animals, of which 294,632 had phenotypic records over 5 generations. Genotypes of 57,635 SNP were available for 4,922 animals. After quality checks, 41,036 SNP and 4,866 animals remained in the genomic file. SNP effects were calculated by a GWAS type analysis using single-step GBLUP approach. In each run, the generations were grouped from 1-3, 2-4, 3-5, and 1-5. The evaluation model included sex and contemporary group as fixed effects, animal additive and maternal permanent environmental as random. In GWAS by single-step GBLUP, genomic breeding values (GEBV) are converted to SNP effects. Variances of SNP effects were derived iteratively in 3 iterations without re-estimation of GEBV. As individual SNP explained very small portion of the total genetic variation, variances were then calculated for windows of 20 SNP and interpreted as the percentage of the total genetic variance. Ten windows for each trait were identified that explained the largest fraction of the variance in any combination of generations. All the top 10 windows explained at least 0.5% (but less than 2%) of the total genetic variance in all the traits. The variance explained by each window varied greatly among the combinations of generations. In several cases, a window identified as top for one combination of generations explained less than 0.1% variance in the remaining combinations. Top windows of SNP variance in the broiler population are unstable and unsuitable for direct selection. Results in this study could be influenced by many generations of intensive selection in broiler chicken and by a small number of genotypes.  

Keywords: Genomic Selection, genome-wide association study, ssGBLUP