Page Banner

United States Department of Agriculture

Agricultural Research Service

Title: Integrating Quantitative and Molecular Techniques in Selection for Disease Resistance

Authors
item Dodgson, Jerry - MSU EAST LANSING MI
item Cheng, Hans
item Burnside, Joan - UNIV DELAWARE NEWARK, DE

Submitted to: Poultry Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 20, 2000
Publication Date: N/A

Interpretive Summary: With the rapid advance in genomics, the field of whole genome genetics, it has become possible to identify chromosomal segments and/or genes that control complex traits such as disease. This paper describes the latest scientific techniques to identify disease resistance genes in chickens. Particular emphasis is placed on how the emphasis will shift from identifying genes to identifying gene function and biological pathways. The role of transgenic animals is also discussed. The ultimate goal is to incorporate this information for the enhancement of genetic improvement in animal breeding programs. Successful implementation will benefit the poultry industry through many efficient selections for disease resistance, reduced animal mortality and increased production. These benefits will be passed on to consumers in the form of more economical and safe poultry food products.

Technical Abstract: Integration of molecular genetic analysis of resistance traits into classical breeding programs will be difficult, though financially attractive, due to the unique features of disease- related quantitative trait loci (QTL). Research with chickens has provided some of the best examples of major genes which influence disease resistance, including the tva, tvb, and tvc loci, the major histocompatibility complex (B-complex), and recent studies of the NRAMP1 gene. The major challenge to the molecular geneticist now is to identify the genes encoding the many other disease resistance QTL alleles of interest, especially those which might segregate in commercial populations. New technologies based on full genome DNA sequence analysis, microarrays, comparative genome maps, high throughput single nucleotide polymorphism (SNP) assays, and proteomics can provide the extra information that is critical in narrowing the list of possible candidate genes. Perhaps the greatest challenge will be to verify the identity of the causative QTL alleles, for example, using transgenic animals.

Last Modified: 10/23/2014
Footer Content Back to Top of Page