Osteochondrosis in pigs diagnosed with computed tomography: heritabilities and genetic correlations to weight gain in specific age intervals.

The aim of this study was to develop a method for scoring osteochondrosis (OC) by using information from computed tomography (CT), as well as to estimate the heritability for OC scored by means of CT (OCwCT) of the medial and lateral condyles at the distal end of the humerus or the femur of the right and left leg and the sum of these scores (OCT). In addition, we were aiming at revealing the genetic relationship between OCwCT traits and growth in different periods (days from birth to 30 kg (D30), days from 30 to 50 kg (D30_50), days from 50 to 70 kg (D50_70), days from 70 to 90 kg (D70_90), days from 90 to 100 kg (D90_100) and days from birth to 100 kg (D100)). The OCwCT was assessed for 1449 boars, and growth data were collected for these 1449 boars and additional 3779 boars tested in the same time period. All boars were tested as part of the Norsvin Landrace boar test and in the same test station. Heritabilities for OCwCT on anatomical locations varied from 0.21 (s.e. = 0.08) on the medial condyle of the right humerus to 0.06 (s.e. = 0.06) on the lateral condyle of the left femur, whereas OCT exhibited the highest heritability (h² = 0.31, s.e. = 0.09). Genetic correlations between OCT and OCwCT for the anatomical locations ranged from 0.94 (s.e. = 0.07) for OCT and OCwCT score for the medial condyle of the humerus right side to 0.26 (s.e. = 0.39) for OCT and the lateral condyle of the femur left side. Genetic correlations between D30 and OCT were medium high and unfavourable (r(g) = -0.74). As the boar gain weight, the relationship between growth rate--expressed as number of days spent growing from one interval to the next--and OCT decreased to 0.12 (s.e. = 0.19, i.e. not significantly different from zero) for the trait D90_100 kg. These changes of genetic correlation coefficients coincide with the maturing of the joint cartilage and skeletal structures. In this study, we demonstrate that CT could be used for selection against OC in breeding programmes in pigs and that the genetic correlations between growth periods and OC are decreasing over time.

Simultaneous estimation of daily weight and feed intake curves for growing pigs by random regression.

In this study, random regression models were used to estimate covariance functions between feed intake and BW in boars from the two breeds: the Norwegian Landrace and the Norwegian Duroc. In total, 1476 animals of the Norwegian Landrace breed and 1300 animals of the Norwegian Duroc breed had registrations on daily feed intake and growth from 54 to 180 days of age. Random regressions on the Legendre polynomials of age were used to describe genetic and permanent environmental curves in BW (up to the second order) and feed intake (up to the first order) for both the breeds. Heritabilities on BW increased over time for the Landrace (0.18 to 0.24), but were approximately constant for the Duroc (0.33 to 0.35). Average heritabilities for feed intake were approximately the same in both the breeds (0.09 to 0.11), and the estimates decreased over time, most pronounced in Duroc. On the basis of the current data, daily feed intake was seemingly controlled by the same genetic factors throughout the test period for Duroc; however, for Landrace, genetic correlations between test days decreased with increasing distance in time. For BW, the genetic correlations between test days were in general high, and did not go below 0.8 for any of the two breeds in this study. For both feed intake and BW, permanent environmental correlations between start and end of the test were reduced with increasing difference in days, most pronounced in Duroc. This study indicates that weight of the animal at the end of the test was more closely genetically correlated to feed intake of earlier periods compared with later periods of growth for both the breeds. This may be explained by the fact that BW is the cumulative growth of an individual, which is likely to be heavily affected by the feed intake during the most intense growth period.

An algorithm to compute optimal genetic contributions in selection programs with large numbers of candidates.

A novel algorithm, OCSELECT, is presented for the calculation of optimal genetic contributions with a restricted rate of inbreeding when the number of selection candidates is very large. The calculation of optimal genetic contributions requires the relationship matrix between the candidates and its inverse. The relationship matrix was written as: A = ZA(p)Z' + D, where A(p) is the relationship matrix of the parents, D is a diagonal matrix of Mendelian sampling variances, and Z contains genetic contributions from parents to offspring. Therefore, A(-1) = d(-1) - d(-1)Z(Z'd(-1)Z + A(P)(-1))(-1) Z'd(-1), requires only inversion of matrices of the size of the number of parents instead of the number of offspring. The new algorithm was compared with the software package GENCONT on a salmon data set containing 39,214 selection candidates and 45,846 pedigreed fish in total. Because GENCONT could not handle such a large data set, this data set was split into 19 smaller data sets. Both algorithms gave the same solution with respect to the genetic gain and very similar solutions with respect to the number of selected animals. The OCSELECT algorithm was able to calculate the optimal contributions for the complete data set of 39,214, and therefore no preselection of the 39,214 fish was necessary before entering the fish into the new optimal contribution selection procedure.