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United States Department of Agriculture

Agricultural Research Service


item Cheng, Hans
item Liu, Hsiao Ching
item Niikura, Masa

Submitted to: Plant and Animal Genome Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 1/10/2004
Publication Date: 1/10/2004
Citation: Cheng, H.H., Liu, H., Niikura, M. 2004. A comprehensive screen for Marek's disease virus-chicken protein interactions to identify disease resistance genes. Plant and Animal Genome Conference Proceedings. p. 293.

Interpretive Summary:

Technical Abstract: Marek's disease (MD) is a lymphoproliferative disease of chickens and an estimated $1 billion problem annually to the worldwide poultry industry. The causative agent is the Marek's disease virus (MDV), a ubiquitous herpesvirus. Vaccines limit tumor incidence but do not block MDV replication and spread. Consequently, more virulent MDV strains have emerged. Genetic resistance, and more specifically marker-assisted selection, has been proposed to augment MD control. Previously, we identified 14 QTL conferring MD resistance. Unfortunately, it is extremely difficult to fine-map these QTL primarily due to the small size of effects and the large variability associated with MD trait measurements. To identify the causative gene(s), we have been integrating functional genomic screens (e.g., DNA microarrays and two-hybrid assays) and genetic association tests to reveal positional candidate genes. With the MDV genome sequence (175 kb) and two-hybrid assays, it was feasible to conduct a comprehensive screen of MDV proteins unique to virulent strains. As a result, we identified and confirmed by in vitro binding assay eight unique MDV-chicken protein interactions. More importantly, three of corresponding genes are significantly associated with MD resistance. The conclusion that these are true MD resistance genes is supported by gene profiling studies and the known function of each gene product. Even if a gene is not associated with MD resistance, its identity provides considerable insight as to what biological pathways might be influenced by the viral pathogen. It is our belief that integration of genomic and functional genomics methods is a powerful approach to identify disease resistance genes and pathways.

Last Modified: 05/26/2017
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