Genetic variation and genetic trends in hip and elbow dysplasia in Swedish Rottweiler and Bernese Mountain Dog.

The aim of this study was to estimate genetic parameters and genetic trends for hip (HD) and elbow dysplasia (ED) in Swedish Rottweiler (RW) and Bernese Mountain Dog (BMD). Analyses were based on screening results of hip status for 14 693 RW and 8221 BMD and elbow status for 11 891 RW and 7963 BMD, as well as pedigree data for 16 614 RW and 9835 BMD, recorded by the Swedish Kennel Club. Components of (co)variance and breeding values were obtained with a mixed linear animal model. The model included the fixed effects of sex, birth month, age at screening and a combined random effect of clinic and year of examination. The need to include genetic groups for phantom parents in the model was evaluated by comparison of two different models: with and without genetic groups. Estimated heritabilities for HD and ED were between 0.34 and 0.42. The genetic correlation between the traits was weak and positive for RW (r(g) = 0.23 +/- 0.05) and not different from zero for BMD (r(g) = 0.06 +/- 0.06). F-statistics of the genetic group effects were not significant, implying that genetic groups do not need to be included in the model. Genetic trends indicated a genetic improvement in both traits. However, a faster genetic progress is expected if selection is based on predicted breeding values rather than phenotype. Based on the results, a statistical model for routine prediction of breeding values for HD and ED in Swedish dogs was suggested.

Frequencies of genes for coat colour and horns in Nordic cattle breeds.

Gene frequencies of coat colour and horn types were assessed in 22 Nordic cattle breeds in a project aimed at establishing genetic profiles of the breeds under study. The coat colour loci yielding information on genetic variation were: extension, agouti, spotting, brindle, dun dilution and colour sided. The polled locus was assessed for two alleles. A profound variation between breeds was observed in the frequencies of both colour and horn alleles, with the older breeds generally showing greater variation in observed colour, horn types and segregating alleles than the modern breeds. The correspondence between the present genetic distance matrix and previous molecular marker distance matrices was low (r = 0.08 - 0.12). The branching pattern of a neighbour-joining tree disagreed to some extent with the molecular data structure. The current data indicates that 70% of the total genetic variation could be explained by differences between the breeds, suggesting a much greater breed differentiation than typically found at protein and microsatellite loci. The marked differentiation of the cattle breeds and observed disagreements with the results from the previous molecular data in the topology of the phylogenetic trees are most likely a result of selection on phenotypic characters analysed in this study.

Genetic diversity and population structure of 20 North European cattle breeds.

Blood samples were collected from 743 animals from 15 indigenous, 2 old imported, and 3 commercial North European cattle breeds. The samples were analyzed for 11 erythrocyte antigen systems, 8 proteins, and 10 microsatellites, and used to assess inter- and intrabreed genetic variation and genetic population structures. The microsatellites BoLA-DRBP1 and CSSM66 were nonneutral markers according to the Ewens-Watterson test, suggesting some kind of selection imposed on these loci. North European cattle breeds displayed generally similar levels of multilocus heterozygosity and allelic diversity. However, allelic diversity has been reduced in several breeds, which was explained by limited effective population sizes over the course of man-directed breed development and demographic bottlenecks of indigenous breeds. A tree showing genetic relationships between breeds was constructed from a matrix of random drift-based genetic distance estimates. The breeds were classified on the basis of the tree topology into four major breed groups, defined as Northern indigenous breeds, Southern breeds, Ayrshire and Friesian breeds, and Jersey. Grouping of Nordic breeds was supported by documented breed history and geographical divisions of native breeding regions of indigenous cattle. Divergence estimates between Icelandic cattle and indigenous breeds suggested a separation time of more than 1,000 years between Icelandic cattle and Norwegian native breeds, a finding consistent with historical evidence.

Culling before testing in swine: identification of culling strategy and estimation of culling precision.

The aim of this simulation study was to identify culling strategy and to estimate culling precision based on various characteristics available in field data in order to evaluate the ability to detect situations in which adjustment for missing data should be applied in genetic evaluation. Data were simulated for age at 100 kg of live weight (AGE) measured on the farm. Culling was done within (C-W/IN) or over (C-OVER) litters by deleting records from the simulated datasets with culling intensities of .33 and .67. The culling variate (CVAR) used indicated the culling precision and had genetic and phenotypic correlations of 1.00, .75, .50, .25, or .00 with AGE (r(CVAR,AGE)). We were able to distinguish between culling strategies C-OVER and C-W/IN by means of decision rules based on proportion of tested animals per litter. Estimates of r(CVAR,AGE) were obtained from calibration curves for linear regression coefficients of litter average or within-litter variance for AGE on proportion of tested animals, and within- and between-litter variance (V(W) and V(B)) for AGE. Moderate to high r(CVAR,AGE) could be identified with little error by using V(W) or V(B) in C-W/IN and V(W) in C-OVER. Within-litter variance and the weighted average of the estimates from all four characteristics were well able to detect r(CVAR,AGE) values of .50 and higher in both C-W/IN and C-OVER. In conclusion, characteristics of swine field data with missing observations contain information that makes it possible to determine culling strategy, intensity, and precision. This information can be used to decide whether missing data should be replaced by their expected values in genetic evaluation.

"Quasi-REML" correlation estimates between production and health traits in the presence of selection and confounding: a simulation study.

Performance of the "quasi-REML" method for estimating correlations between a continuous trait and a categorical trait, and between two categorical traits, was studied with Monte Carlo simulations. Three continuous, correlated traits were simulated for identical populations and three scenarios with either no selection, selection for one moderately heritable trait (Trait 1, h2 = .25), and selection for the same trait plus confounding between sires and management groups. The "true" environmental correlations between Traits 2 (h2 = .10) and 3 (h2 = .05) were always of the same absolute size (.20), but further data scenarios were generated by setting the sign of environmental correlation to either positive or negative. Observations for Traits 2 and 3 were then reassigned to binomial categories to simulate health or reproductive traits with incidences of 15 and 5%, respectively. Genetic correlations (r(g12), r(g13), and r(g23) and environmental correlations (r(e12), r(e13), and r(e23)) were estimated for the underlying continuous scale (REML) and the visible categorical scales ("quasi-REML") with linear multiple-trait sire and animal models. Contrary to theory, practically all "quasi-REML" genetic correlations were underestimated to some extent with the sire and animal models. Selection inflated this negative bias for sire model estimates, and the sign of r(e23) noticeably affected r(g23) estimates for the animal model, with greater bias and SD for estimates when the "true" r(e23) was positive. Transformed "quasi-REML" environmental correlations between a continuous and a categorical trait were estimated with good efficiency and little bias, and corresponding correlations between two categorical traits were systematically overestimated. Confounding between sires and contemporary groups negatively affected all correlation estimates on the underlying and the visible scales, especially for sire model "quasi-REML" estimates of genetic correlation. Selection, data structure, and the (co)variance structure influences how well correlations involving categorical traits are estimated with "quasi-REML" methods.

Adjusting for missing data due to culling before testing in genetic evaluations of swine.

The aim of this study was to evaluate data augmentation in genetic evaluations as a method of adjusting for missing data due to culling of pigs before testing. A stochastic simulation was used to generate 10 yr of data for age at test (AGE) and fat thickness (FAT) in a breeding unit with 100 sows and 15 boars. Culling was performed at random (C-RAND), within litters (C-W/IN) or over litters (C-OVER), by deleting two-thirds of the records from the simulated data sets. The culling variate (CVAR) used had genetic and phenotypic correlations of 1.00, .75, .50, and .25 with AGE [r(CVAR, AGE)], whereas culling was uncorrelated with AGE in C-RAND. Missing records for AGE were replaced with their expectations (dummy records), based on the phenotypic average of the tested animals and selection intensities applied. With missing records, predictions were seriously biased for AGE in C-W/IN and especially in C-OVER, when r(CVAR, AGE) exceeded .50 and .25, respectively. The ranking of the animals was more affected in C-OVER than in C-W/IN. With dummy records, bias was removed effectively in cases with a high r(CVAR, AGE) in C-W/IN and C-OVER, whereas a larger bias was created in the opposite direction when r(CVAR, AGE) was less than .50 and for C-RAND. In conclusion, this method was beneficial for adjusting missing data owing to culling, when the correlation between CVAR and AGE was .50 or greater.

Associations of breeding values for disease traits and genetic markers in dairy cattle estimated with a mixed model.

Since 1985, all veterinary treatments on dairy cows in Sweden have been recorded and utilized for estimation of sire breeding values for resistance to clinical mastitis and to diseases other than clinical mastitis. The purpose of the present investigation was to study the relationship of blood groups and blood protein polymorphisms with these traits and to extend a method previously applied to international comparisons of dairy sires for milk production to estimation of marker gene effects. The data comprised 1171 AI sires of the Swedish Red and White dairy breed that had a blood typing record and breeding values for disease resistance. Information was available on the breeding values of sires, the number of daughters of each sire, and the relationships among sires. This information was used to deregress the sire breeding values to average daughter performances, which then were analyzed by a mixed linear model. The reduction in error variance that was due to inclusion of the markers in the model was small. Several substitution effects of the markers were statistically significant. The largest effects corresponded to a deviation of .7 percentage units for the frequency of veterinary treatments among the average daughters of the sires.

The relationship between bovine major histocompatibility complex class II polymorphism and disease studied by use of bull breeding values.

The predictive value of class II DQ and DYA polymorphisms of the bovine major histocompatibility (MHC) complex (BoLA) for the incidence of disease in dairy cattle was estimated in a sample of 196 progeny-tested AI bulls of the Swedish Red and White breed. The BoLA DQ and DYA types of the bulls were determined by analysing restriction fragment length polymorphisms (RFLPs). Breeding values of bulls for clinical mastitis, all diseases including clinical mastitis and diseases other than clinical mastitis were used as measures of disease resistance or susceptibility. The relationship between MHC polymorphism and bull breeding values for disease resistance was evaluated statistically by linear regression analysis. A significant association between the haplotype DQ1A and susceptibility to clinical mastitis was revealed. No other DQ haplotype nor the DYA locus has a significant effect on any of the disease traits studied.

Associations between blood groups, blood protein polymorphisms and breeding values for production traits in Swedish Red and White Dairy bulls.

The relationships of nine blood group systems and two blood protein polymorphisms with breeding values for several production traits were examined in dairy cattle of the Swedish Red and White (SRB) breed. The material consisted of 2212 bulls; the bulls were performance tested for growth rate and their breeding values for milk yield, fat and protein content in milk were estimated from progeny tests. The direct effect of marker alleles or marker phenotypes was analysed in a multiple regression model. Several significant associations were found; many supported earlier findings. However, the contribution of the markers to the total variation of the breeding values was very small. Linkage between marker loci and production loci was studied in offspring from heterozygous sires by estimating the interactions between sire and marker alle using a model eliminating the direct effects of sire and marker alle. There were strong indications of linkage between some marker loci (e.g. B, J and Am-1 loci) and loci with large effects on production traits.

Genetic parameters for clinical mastitis, somatic cell counts, and milk production estimated by multiple-trait restricted maximum likelihood.

Heritabilities and genetic correlations for mastitis, SCC, and milk production in first lactation were calculated using data from the Swedish disease recording system. Genetic parameters were estimated from sire components of variance and covariance obtained from a multiple-trait restricted maximum likelihood procedure. Data were stratified into three subsets according to breed and AI stud. The numbers of cows were 46,431, 25,373, and 25,201, respectively. Heritabilities of mastitis and SCC averaged .014 and .080, but breed differences were seen. Genetic correlations between mastitis and SCC were moderately high, averaging .6. Milk production showed a slightly unfavorable genetic correlation with mastitis and SCC.