tailieunhanh - Báo cáo sinh học: " Reduced animal model for marker assisted selection using best linear unbiased prediction"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Reduced animal model for marker assisted selection using best linear unbiased prediction | 221 Genet Sei Evol 1991 23 221-233 Elsevier INRA ặ Original article Reduced animal model for marker assisted selection using best linear unbiased prediction RJC Cantet c Smith University of Guelph Centre for Genetic Improvement of Livestock Department of Animal and Poultry Science Guelph Ontario NIG 2W1 Canada Received 15 October 1990 accepted 11 April 1991 Summary - A reduced animal model RAM version of the animal model AM incorporating independent marked quantitative trait loci MQTL s of Fernando and Grossman 1989 is presented. Both AM and RAM permit obtaining Best Linear Unbiased Predictions of MQTL effects plus the remaining portion of the breeding value that is not accounted for by independent MQTL s. RAM reduces computational requirements by a reduction in the size of the system of equations. Non-parental MQTL effects are expressed as a linear function of parental MQTL effects using marker information and the recombination rate r between the marker locus and the MQTL. The resulting fraction of the MQTL variance that is explained by the regression on parental MQTL effects is 2 1 r 2 r2 2 when the individual is not inbred and both parents are known. Formulae are obtained to simplify the computations when backsolving for non-parental MQTL and breeding values in case all non-parents have one record. A small numerical example is also presented. maker assisted selection I best linear unbiased prediction reduced animal model genetic marker Resume Un modèle animal réduit pour la selection assistée par marqueurs avec BLUP. Une version du modèle animal réduit RAM basée sur le modèle animal AM de Fernando et Grossman 1989 avec loci indépendants de caractères quantitatifs marques MQTL est presentee. Dans les 2 cas RAM et AM on obtient les meilleurs predictions linéaires sans biais BLUP des effets des MQTL en plus de la portion restante de la valeur génétique inexpliquée par les MQTL indépendants. L emploi de RAM diminue les exigences de calcul par une reduction de la .

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