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United States Department of Agriculture

Agricultural Research Service

Title: Identification of Qtl for Production Traits in Chickens

Authors
item Hansen, C - UNIV OF ALBERTA EDMONTON
item Yi, N - UNIV OF CALIFORNIA
item Zhang, Y - UNIV OF CALIFORNIA
item Xu, S - UNIV OF CALIFORNIA
item Gavora, J - AG/AGRI-FOOD CANADA
item Cheng, Hans

Submitted to: Animal Biotechnology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 3, 2005
Publication Date: May 20, 2005
Citation: Hansen, C., Yi, N., Zhang, Y.M., Xu, S., Gavora, J., Cheng, H.H. 2005. Identification of QTL for production traits in chickens. Animal Biotechnology. 16:67-79.

Interpretive Summary: Poultry meat and eggs continue to be very important agricultural commodities for the US and the world. In order for the poultry industry to continue to flourish, advances in poultry genetics are essential. In this paper, we describe the identification of regions in the chicken genome that control important agronomic traits. With this information in hand, it may be possible to develop genetic tests based on DNA that can be used to select superior chickens. In addition, candidate genes contained within the region can be more readily revealed, which helps us understand the complex molecular pathways of production traits. Ultimately, consumers will benefit from more efficient poultry breeding and selection.

Technical Abstract: An initial scan of the chicken genome using 65 microsatellite markers was carried out on a meat-type x egg-type resource population (wide cross) measured for production and egg quality traits. Using a Bayesian analysis, potential QTL for a number of traits were identified on several chromosomes. Evidence of eight QTL regions associated with a total of eight traits (specific gravity, albumin height, Haugh score, shell shape, total number of eggs, final body weight, gain and feed efficiency) was found. Two of these regions were associated with multiple QTL. A genome scan of a layer, or narrow (within type), cross was performed using the majority of the same microsatellite markers in order to verify whether the QTL identified in the wide cross were also segregating in this population. Our analysis, with the possible exception of a QTL region on GGA01 associated with albumin height and Haugh score, failed to find the same QTL segregating in both populations. However, thirteen QTL regions associated with a total of six traits (weight at 1 year of age, specific gravity, egg weight, albumin height, Haugh score and total number of eggs produced) were identified in the narrow cross.

Last Modified: 11/26/2014
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