|Atzmon, G - EINSTEIN COLLEGE BRONX NY|
|Ronin, Y - UNIV OF HAIFA ISRAEL|
|Korol, A - UNIV OF HAIFA ISRAEL|
|Yonash, N - HAZERA GENETICS LTD.|
|Hillel, J - HEBREW UNIV OF JERUSALEM|
Submitted to: Animal Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 7, 2006
Publication Date: August 1, 2006
Citation: Atzmon, G., Ronin, Y.I., Korol, A., Yonash, N., Cheng, H.H., Hillel, J. 2006. QTLs associated with growth traits and abdominal fat weight and their interactions with gender and hatch in commercial meat-type chickens. Animal Genetics. 37(4):352-358. Interpretive Summary: Poultry is the third largest agricultural commodity in the United States. Primarily due to the utilization of advanced methods of selection in breeding programs, tremendous progress in production traits have been achieved to meet the growing demands of consumers. With the advent of molecular genetic maps, it is now possible to identify specific regions and genes in the chicken genome that contain one or more genes that control a trait. In this study, several regions in the chicken genome were identified that influence growth and fat deposition. Furthermore, different methods to identify these important regions were compared, which allows scientists to determine which analysis method is most appropriate. As a result, genetic marker can be used by poultry breeders to more accurately select chickens with superior production traits. Ultimately, the consumer will benefit from more efficient animal breeding.
Technical Abstract: Associations between microsatellite markers and traits related to growth and fatness were sought in a resource broiler population established by Arbor Acres Farm. A male - "F1" resulting from a cross between the sire line L-03 and the dam line L-14 was backcrossed to twelve females of the dam line L-14 to produce 24 sires and 47 dams of generation "BC1". These 71 parents were genotyped for 76 microsatellite markers. Following full-sib mating among the parents, 234 "BC1-F2" progeny were obtained and phenotyped for six quantitative traits. Two statistical approaches were applied to estimate the marker effects and to evaluate their statistical significance: Least Squares (regression) and Maximum Likelihood (ML). The Maximum Likelihood approach was found to be more robust with far fewer false positive trait-marker associations than the Least Square (regression) method. The non-weighted regression was found to suffer from both false positive as well as false negative associations. Two QTLs were found to be involved with growth traits on chromosomes 1 and 3 at the vicinities of 394 cM and 288 cM, respectively,and four QTLs with abdominal fat deposition located on chromosomes 1, 2, 4 and 12 in the vicinities of 173 cM, 286 cM, 153 cM and 0 cM, respectively.