Location: Avian Disease and Oncology Research
Project Number: 6040-31320-009-10-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Apr 1, 2012
End Date: Mar 31, 2017
Use genomic selection to enhance genetic resistance to Marek's disease.
With high-density chicken rearing, control of infectious diseases is critical for economic viability and maintaining public confidence in poultry products. Among poultry diseases, Marek’s disease (MD), a lymphoproliferative disease caused by the highly oncogenic a-herpesvirus Marek's disease virus (MDV), continues to be a major concern. The fear of MD is further enhanced by unpredictable vaccine breaks that result in devastating losses. The field of genomics offers one of the more exciting avenues for enhancing control of MD. By identifying genes that confer genetic resistance, it should become possible to select for birds with superior disease resistance. Genetic resistance to MD is a complex trait controlled by many genes. Most genome-wide efforts for complex traits rely on linkage between the causative gene and a genetic marker, which results in limited detection power and resolution of gene location. An alternate method is to screen for allele-specific expression (ASE), a simple yet powerful approach, where the expression of each gene allele is compared within an RNA sample. When the expression of the alleles is not equal, then one can unequivocally declare ASE and the presence of a polymorphic cis-acting (genetic) element for that gene as linkage disequilibrium (LD) is confined to the transcriptional unit. The only requirements for ASE to work are: (1) the assumption that variation in expression between alleles of a gene are responsible for part of the phenotypic variation, and (2) the existence of a cSNP to monitor the alleles. Response to MDV infection in chickens was evaluated in F1 progeny from ADOL inbred lines 6 and 7 using next generation sequencing on a limited number of samples to query for ASE followed by Illumina GoldenGate assays to validate and expand the number of samples. In brief, our ability to identify and validate almost all of the 5,360 cSNPs in 3,773 genes clearly demonstrates that ASE is an efficient method to identify potentially most or all of the genes responding to viral infection for this complex trait. In this proposal, we now address whether the expression differences are linked to measurable phenotypic changes (e.g., disease incidence) and, if so, can the cSNPs be used in a genomic selection program? Specifically, we address the following objectives: 1. Using line 6 and 7 advanced intercross lines, determine the relatively influence of each cSNP on MD incidence and which allele confers MD resistance or susceptibility. 2. Validate predictions by selecting birds that are predicted to be most MD resistant or susceptible, intermate within predicted susceptibility class, and conduct MDV challenge studies from their progeny. 3. Repeat the same process using commercial layer lines, which will translate the results into the public domain.