Genetic correlations for foal and studbook traits with racing traits and implications for selection strategies in the Finnhorse and Standardbred trotter.

Genetic correlations for body measurements and conformation and functional traits in foals and studbook horses with racing traits were estimated in the Finnhorse and Standardbred. Genetic response and accuracy were estimated using records of animal, half-sibs and parents in selection scenarios for racing traits, for foal and racing traits, for studbook and racing traits, and using records of animal, half-sibs and parents for foal traits and racing traits of parents. Racing time and earnings were the breeding objective. Low-to-moderate genetic correlations for body measurements and racing traits indicated that selection favours bigger horses at all ages. Being mainly favourable for the breeding objective, genetic correlations for conformation and functional traits with racing traits were highest for the foal traits of type, trot and overall grade and for the studbook traits of character and movements. Genetic correlations for foal and studbook conformation with racing traits were low in the Finnhorse and moderate to high in the Standardbred. In foals, the highest genetic correlations were for trot with racing time (-0.54) and with earnings (0.52) in the Finnhorse, and for overall grade with racing time (-0.54) and with earnings (0.54) in the Standardbred. In studbook horses, genetic correlations were high for character with racing time and earnings in the Finnhorse (-0.68, 0.61) and in the Standardbred (-0.63, 0.70), and for movements with racing time and earnings in the Finnhorse (-0.70, 0.69) and in the Standardbred (-0.90, 0.88). To increase accuracy of conformation and functional traits, foal traits would be more useful in the index with racing traits, as being less preselected than studbook traits. The foal traits (type, trot, overall grade) having moderate heritability and genetic correlations with racing traits would be useful in multi-trait index before a racing career, where the greatest gain is because of a shorter generation interval. It would be feasible to implement for AI stallions.