EFFECT OF SMALL-HERD CLUSTERING ON THE GENETIC CONNECTEDNESS OF THE PORTUGUESE HOLSTEIN CATTLE POPULATION J.Vasconcelos and J.Carvalheira

no. 424; Session G4.44 [email protected] EFFECT OF SMALL-HERD CLUSTERING ON THE GENETIC CONNECTEDNESS OF THE PORTUGUESE HOLSTEIN CATTLE POPULATION J.Vasconcelos and J.Carvalheira Centro Investigação em Biodiversidade e Recursos Genéticos (CIBIO), Universidade do Porto, Rua Padre Armando Quintas, 4485-661 Vairão, PORTUGAL, ICBAS-Universidade do Porto INTRODUCTION Accuracy of genetic evaluations is directly related with connectedness (Kennedy and Trus, 1993; Hanocq and Boichard, 1999) between management groups (MG). Contemporary groups in test-day (TD) models may have an unacceptable number of observations (e.g., less then 4) depending on the herd size. Clustering these herds based on, for example, the simultaneous similarity between phenotypic mean and STD may prevent the loss of this information. However, these techniques may induce a false increase in genetic connectedness (GC), inflating the accuracy of EBV and promote preferential treatment for some sires. The aim of this study was to evaluate possible effects of clustering herds on the GC of the Portuguese Holstein cattle. MATERIAL AND METHODS The Portuguese National Association of Dairy Cattle Breeders (ANABLE) provided TD data, produced by 194,980 animals from 1997 to 2003. Ideally, average prediction error variance of differences (PEVd) in EBV between animals on different MG should be the basis of measurement of GC (Foulley et al, 1992; Kennedy and Trus, 1993). In a dataset of this dimension the estimation of PEVd is computationally infeasible. Two alternative methods were applied to compute the degree of GC: GLT Total number of direct genetic links between MG (Roso et al., 2004), defined in this work as herd/year: GLT was calculated by summing the total number of common sires and dams in pairs of MG, forming genetic links (Fries, 1998). For each MG, the overall number of genetic links with all other MG was calculated. GDV Genetic drift variance (Kennedy and Trus, 1993): It was obtained from X’ZAZ’X matrix, that measures the sum of genetic relationship between and within MG. Average relationship between and within MG were obtained by dividing diagonal elements of X’ZAZ’X matrix by the square of the number of records in the MG and the off-diagonal elements by the product of the number of records in each of the MG considered. The resulting matrix, Ā, can be interpreted as the components of the genetic drift (co)variances. The average GDV for each MG with all other was calculated as the average of all variance differences with respect to that MG.