Associations between microsatellite markers and traits related to performance, carcass and organs in chickens

• Autor(a) principal: Boschiero, C. [UNESP]
• Data de Publicação: 2009
• Outros Autores: Rosário, M. F., Ledur, M. C., Campos, R. L. R., Ambo, M., Coutinho, L. L., Moura, A. S. A. M. T. [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.3923/ijps.2009.615.620; http://hdl.handle.net/11449/71109
• topic: Body weight; Broiler; Heart weight; Poultry; Single marker analysis; Gallus gallus

Associations between four microsatellite markers on chromosome 11 and five on chromosome 13 with performance, carcass and organs traits were investigated in chickens using a least-squares approach applied to single-marker analysis. Three hundred and twenty seven F 2 chickens from the EMBRAPA broiler×layer experimental population were evaluated for 16 traits: five related to performance, five to carcass and five to organs, plus the hematocrit. Two significance thresholds were considered: p<0.05 and p<0.0056; the last value resulted from the application of a multiple tests analyses correction. On chromosome 11, six associations (p<0.05) between the genotypes of two markers with four growth related and one carcass trait were found. On chromosome 13, six associations (p<0.05) between marker genotypes and three performance traits, eight associations (p<0.05) between marker genotypes and two carcass traits and eight associations (p<0.05) between marker genotypes and four organs traits were detected. These associations were indications of the presence of quantitative trait loci on these chromosomes, especially on chromosome 13. In this chromosome, the strongest evidence was for body weight at 41 days of age and percentage of carcass because the p-values exceeded the multiple test threshold (p<0.0056), but also for breast percentage and heart weight due to the large number of markers (four) on chromosome 13 associated with each one of these traits. These associations should be further investigated by interval mapping analyses to find QTL positions and to allow the estimation of their effects. © Asian Network for Scientific Information, 2009.