|PERUMBAKKAM, SUDEEP - Purdue University|
|Black Pyrkosz, Alexis|
|SUBRAMANIAM, SUGALESINI - Michigan State University|
|PREEYANON, LIKIT - Michigan State University|
|VAN SAMBEEK, FRANS - Hendrix Genetics|
|ANSAH, GEORGE - Hendrix Genetics|
|MUIR, WILLIAM - Purdue University|
Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 9/25/2013
Publication Date: 9/25/2013
Citation: Cheng, H.H., Perumbakkam, S., Black Pyrkosz, A.A., Subramaniam, S., Preeyanon, L., Dunn, J.R., Van Sambeek, F., Ansah, G., Muir, W.M. 2013. The Genetic Architecture of Genetic Resistance to Marek's Disease. In: Proceedings of the 8th European Symposium on Poultry Genetics, September 25-27, 2013, Venice, Italy. p. 12-13.
Technical Abstract: Marek’s disease (MD), a T cell lymphoma induced by the oncogenic Marek’s disease virus (MDV), is one of the most serious chronic disease problems for the poultry industry. While MD is controlled through vaccination and biosecurity, it still costs more than $2 billion worldwide annually due to meat condemnation and reduced egg production. Combined with the emergence of more virulent MDV field strains, there is a need for alternate MD control strategies. Increasing genetic resistance to MD is an attractive solution as it has a proven track record and will also enhance animal welfare. To identify the underlying genes and alleles, over the past 15 years, we have employed and integrated various genomic and functional genomic screens at the DNA (e.g., QTL scans), RNA (e.g., microarray), and protein (e.g., two-hybrid screen) levels, which have identified three MD resistance genes and many more candidates along with greater knowledge of the associated biological pathways. More recently, we have incorporated allele-specific expression (ASE) screens in response to MDV infection, a simple yet powerful approach that identifies SNPs and genes that show variation in transcriptional response to virus challenge. Using these ASE SNPs for genomic selection in experimental lines, we found that they accounted for the majority of the observed genetic variance. This result strongly suggests that differences in MD genetic resistance is due to variation in transcriptional regulation and not other classes of polymorphisms (e.g., nonsynonymous amino acid changes, CNVs). This conclusion is further supported by some of our other efforts. For example, we have identified SNPs that can lead to alternative splicing following MDV infection or binding of the MDV Meq oncoprotein, a bZIP transcription factor. Currently, experimental and commercial layers are being selected with ASE SNPs and progeny tested to validate this approach. If our genomic predictions are confirmed, then this would suggest that the ASE approach to identify polymorphisms that influence transcriptional regulation can be applied to other complex traits, especially those involving infectious pathogens. Furthermore, for specific traits, ASE SNPs should be incorporated in SNP chips for genomic selection as they provide added value compared to randomly selected SNPs.