Submitted to: Poultry Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/1/2006
Publication Date: 10/1/2006
Citation: Zhou, H., Deeb, N., Clover, C.M., Ashwell, C.M., Lamont, S.J. 2006. Genome-wide linkage analysis to identify chromosomal regions affecting phenotypic traits in the chicken. I. Growth and average daily gain. Poultry Science. 85:1700-1711. Interpretive Summary: The development of molecular biology techniques for uncovering genetic variation at the DNA level has opened new avenues to identify genes affecting phenotypic traits. Genetic variation is caused by intrapopulation and interpopulation differences for many traits of biological, medical, and agricultural importance. Being able to dissect the genetic variation of complex traits in poultry can greatly advance our understanding of biology and physiology of phenotypic variation observed in the population. Identification of genetic variation provides the opportunity for more rapid genetic improvement in selection programs. The position and effects of quantitative trait loci are different depending on the genetic population studied. In this study the resource population was developed by crossing 1 modern broiler sire line with 2 Leghorn and Fayoumi lines of chickens. Eight growth traits were analyzed for variation in this study. The results of this study showed that variation exists in the growth hormone and the receptors for several other hormones or important growth-related proteins. This information can be used by geneticists to select for desired growth traits in broiler chickens. This information will be of interest to poultry geneticists and other scientists.
Technical Abstract: A genome scan was used to detect chromosomal regions and QTL that control quantitative traits of economic importance in chickens. Two unique F2 crosses generated from a commercial broiler male line and 2 genetically distinct inbred lines (Leghorn and Fayoumi) were used to identify QTL affecting BW and daily average gain traits in chickens. Body weight at 2, 4, 6, and 8 wk was measured in the 2 F2 crosses. Birds were genotyped for 269 microsatellite markers across the entire genome. Linkage distance among microsatellite markers was estimated by the CRIMAP program. The program QTL Express was used for QTL detection. Significance levels were obtained using the permutation test. For the 8 traits, a total of 18 and 13 significant QTL were detected at a 1% chromosome-wise significance level, of which 17 and 10 were significant at the 5% genome-wise level for the broiler-Leghorn cross and broiler-Fayoumi cross, respectively. Highly correlated growth traits showed similar QTL profiles within each cross but different QTL profiles between the 2 crosses. Most QTL for growth traits in the current study were detected in Gga 1, 2, 4, 7, and 14 for the broiler-Leghorn cross and Gga 1, 2, 4, 5, 8, and 13 for the broiler-Fayoumi cross. Potential candidate genes within the QTL region for growth traits at 1% chromosome-wise significance level were discussed. The results in the current study lay the foundations for fine mapping these traits in the advanced intercross lines and provide a start point for identification causative genes responsible for growth traits in chickens.