Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: July 20, 2014
Publication Date: July 20, 2014
Citation: Cheng, H.H., Perumbakkam, S., Black Pyrkosz, A.A., Dunn, J.R., Muir, W.M. 2014. Genomic selection for genetic resistance to Marek's disease [abstract]. In: Proceeding of 10th International Symposium on Marek's Disease and Avian Herpesviruses, July 20-23, 2014, East Lansing, Michigan. p. 45. Technical Abstract: Enhancing genetic resistance to Marek’s disease (MD) is another control strategy to augment MD vaccines. Ideally selection would use genetic markers linked to the underlying genes that confer MD genetic resistance, which would avoid having to expose elite lines to Marek’s disease virus (MDV). To identify these genetic markers, a three-step process was tested using ADOL line 6 (MD resistant) and line 7 (MD susceptible). First, splenic RNAs from uninfected and MDV-infected F1 chicks were sequenced, SNPs identified, and then screened for differences in allelic ratios. This resulted in 4,528 SNPs in 3,718 genes that exhibited allele-specific expression (ASE) in response to MDV infection. Second, to associate SNPs with MD genetic resistance, a ~1,000 6x7 F6 MD resource population was genotyped with a custom 9K SNP chip that included 1,824 ASE SNPs. The analysis revealed heritability of MD genetic resistance was 0.53 and the SNPs accounted for 83% of the genetic variability. Furthermore, the significant associations were with ASE SNPs and, on average, each ASE SNP accounted for twice as much of the genetic variation compared to other SNPs. And third, 60 sires with predicted MD genetic resistance (high or low) were progeny tested to validate the GEBVs (genomic estimated breeding values). The MD incidence in the progeny clearly demonstrated that we could select for increased or decreased MD genetic resistance. Thus, this study provides a model for genomic selection to enhance MD genetic resistance, which is applicable to improving genetic resistance to other infectious pathogens. Furthermore, our data clearly supports that the major underlying mechanism for complex traits is variation in gene expression.