Jørgen Ødegård

Quantitative trait loci affecting clinical mastitis and somatic cell count in dairy cattle

Abstract. Norway has a field recording system for dairy cattle that includes recording of all veterinary treatments on an individual animal basis from 1978 onwards. Application of these data in a genome search for quantitative trait loci (QTL) verified genome-wise significant QTL affecting clinical mastitis on Chromosome (Chr) 6. Additional putative QTL for clinical mastitis were localized to Chrs. 3, 4, 14, and 27. The comprehensive field recording system includes information on somatic cell count as well. This trait is often used in selection against mastitis when direct information on clinical mastitis is not available. The absence of common QTL positions for the two traits in our study indicates that the use of somatic cell count data in QTL studies aimed for reducing the incidence of mastitis should be carefully evaluated.

Family association between immune parameters and resistance to Aeromonas hydrophila infection in the Indian major carp, Labeo rohita.

Seven innate immune parameters were investigated in 64 full-sib families (the offspring of 64 sires and 45 dams) from two year-classes of farmed rohu carp (Labeo rohita). Survival rates were also available from Aeromonas hydrophila infection (aeromoniasis) recorded in controlled challenge tests on a different sample of individuals from the same families. Due to strong confounding between the animal additive genetic effect and the family effects (common environmental+non-additive genetic), reliable additive (co)variance components and hence heritabilities and genetic correlations could not be obtained for the investigated parameters. Therefore, estimates of the association of challenge test survival with the studied immune parameters were obtained as product moment correlations between family least square means. These correlations revealed statistically significant (p<0.05) negative correlations of survival with bacterial agglutination titre (-0.48), serum haemolysin titre (-0.29) and haemagglutination titre (-0.34); and significant positive correlation with ceruloplasmin level (0.51). The correlations of survival to aeromoniasis with myeloperoxidase activity, superoxide production and lysozyme activity were found to be not significantly different from zero (p>0.05). Assuming that the negatively correlated candidate traits are not favourable as indirect selection criteria, the results suggest that ceruloplasmin level could potentially be a marker for resistance to aeromoniasis in rohu. The use of this immune parameter as an indirect selection criterion for increased resistance to aeromoniasis in rohu will, however, require that the parameter shows significant additive genetic variation and a significant genetic correlation with survival. Further studies are therefore needed to obtain a reliable heritability estimate for ceruloplasmin and its genetic correlation with survival from aeromoniasis.

Epithelial Cadherin Determines Resistance to Infectious Pancreatic Necrosis Virus in Atlantic Salmon

Infectious pancreatic necrosis virus (IPNV) is the cause of one of the most prevalent diseases in farmed Atlantic salmon (Salmo salar). A quantitative trait locus (QTL) has been found to be responsible for most of the genetic variation in resistance to the virus. Here we describe how a linkage disequilibrium-based test for deducing the QTL allele was developed, and how it was used to produce IPN-resistant salmon, leading to a 75% decrease in the number of IPN outbreaks in the salmon farming industry. Furthermore, we describe how whole-genome sequencing of individuals with deduced QTL genotypes was used to map the QTL down to a region containing an epithelial cadherin (cdh1) gene. In a coimmunoprecipitation assay, the Cdh1 protein was found to bind to IPNV virions, strongly indicating that the protein is part of the machinery used by the virus for internalization. Immunofluorescence revealed that the virus colocalizes with IPNV in the endosomes of homozygous susceptible individuals but not in the endosomes of homozygous resistant individuals. A putative causal single nucleotide polymorphism was found within the full-length cdh1 gene, in phase with the QTL in all observed haplotypes except one; the absence of a single, all-explaining DNA polymorphism indicates that an additional causative polymorphism may contribute to the observed QTL genotype patterns. Cdh1 has earlier been shown to be necessary for the internalization of certain bacteria and fungi, but this is the first time the protein is implicated in internalization of a virus.

Genomic prediction in an admixed population of Atlantic salmon (Salmo salar)

Reliability of genomic selection (GS) models was tested in an admixed population of Atlantic salmon, originating from crossing of several wild subpopulations. The models included ordinary genomic BLUP models (GBLUP), using genome-wide SNP markers of varying densities (1–220 k), a genomic identity-by-descent model (IBD-GS), using linkage analysis of sparse genome-wide markers, as well as a classical pedigree-based model. Reliabilities of the models were compared through 5-fold cross-validation. The traits studied were salmon lice (Lepeophtheirus salmonis) resistance (LR), measured as (log) density on the skin and fillet color (FC), with respective estimated heritabilities of 0.14 and 0.43. All genomic models outperformed the classical pedigree-based model, for both traits and at all marker densities. However, the relative improvement differed considerably between traits, models and marker densities. For the highly heritable FC, the IBD-GS had similar reliability as GBLUP at high marker densities (>22 k). In contrast, for the lowly heritable LR, IBD-GS was clearly inferior to GBLUP, irrespective of marker density. Hence, GBLUP was robust to marker density for the lowly heritable LR, but sensitive to marker density for the highly heritable FC. We hypothesize that this phenomenon may be explained by historical admixture of different founder populations, expected to reduce short-range lice density (LD) and induce long-range LD. The relative importance of LD/relationship information is expected to decrease/increase with increasing heritability of the trait. Still, using the ordinary GBLUP, the typical long-range LD of an admixed population may be effectively captured by sparse markers, while efficient utilization of relationship information may require denser markers (e.g., 22 k or more).

Incorporating Desirable Genetic Characteristics From an Inferior Into a Superior Population Using Genomic Selection

Resistance to specific diseases may be improved by crossing a recipient line with a donor line (a distantly related strain) that is characterized by the desirable trait. However, considerable losses in the total merit index are expected when crossing recipient and donor lines. Repeated backcrossing with the recipient line will improve total merit index, but usually at the expense of the newly introgressed disease resistance, especially if this is due to polygenic effects rather than to a known single major QTL. This study investigates the possibilities for a more detailed introgression program based on marker-trait associations using dense marker genotyping and genomic selection. Compared with classical selection, genomic selection increased genetic gain, with the largest effect on low heritability traits and on traits not recorded on selection candidates (due to within-family selection). Further, within a wide range of economic weights and initial differences in the total merit index between donor and recipient lines, genomic selection produced backcrossed lines that were similar or better than the purebred lines within three to five generations. When using classical selection in backcrossing schemes, the long-term genetic contribution of the donor line was low. Hence, such selection schemes would usually perform similarly to simple purebreeding selection schemes.

Genetic Relationship Between Culling, Milk Production, Fertility, and Health Traits in Norwegian Red Cows

First-lactation records on 836,452 daughters of 3,064 Norwegian Red sires were used to examine associations between culling in first lactation and 305-d protein yield, susceptibility to clinical mastitis, lactation mean somatic cell score (SCS), nonreturn rate within 56 d in heifers and primiparous cows, and interval from calving to first insemination. A Bayesian multivariate threshold-linear model was used for analysis. Posterior mean of heritability of liability to culling of primiparous cows was 0.04. The posterior means of the genetic correlations between culling and the other traits were -0.41 to 305-d protein yield, 0.20 to lactation mean SCS, 0.36 to clinical mastitis, 0.15 to interval from calving to first insemination, -0.11 to 56-d nonreturn as heifer, and -0.04 to 56-d nonreturn as primiparous cow. As much as 66% of the genetic variation in culling was explained by genetic variation in protein yield, clinical mastitis, interval of calving to first insemination, and 56-d nonreturn in heifers, whereas contribution from the SCS and 56-d nonreturn as primiparous cow was negligible, after taking the other traits into account. This implies that for breeds selected for a broad breeding goal, including functional traits such as health and fertility, most of the genetic variation in culling will probably be covered by other traits in the breeding goal. However, in populations where data on health and fertility is scarce or not available at all, selection against early culling may be useful in indirect selection for improved health and fertility. Regression of average sire posterior mean on birth-year of the sire indicate a genetic change equivalent to an annual decrease of the probability of culling in first-lactation Norwegian Red cattle by 0.2 percentage units. This genetic improvement is most likely a result of simultaneous selection for improved milk yield, health, and fertility over the last decades.

The importance of identity-by-state information for the accuracy of genomic selection

BackgroundIt is commonly assumed that prediction of genome-wide breeding values in genomic selection is achieved by capitalizing on linkage disequilibrium between markers and QTL but also on genetic relationships. Here, we investigated the reliability of predicting genome-wide breeding values based on population-wide linkage disequilibrium information, based on identity-by-descent relationships within the known pedigree, and to what extent linkage disequilibrium information improves predictions based on identity-by-descent genomic relationship information.MethodsThe study was performed on milk, fat, and protein yield, using genotype data on 35 706 SNP and deregressed proofs of 1086 Italian Brown Swiss bulls. Genome-wide breeding values were predicted using a genomic identity-by-state relationship matrix and a genomic identity-by-descent relationship matrix (averaged over all marker loci). The identity-by-descent matrix was calculated by linkage analysis using one to five generations of pedigree data.ResultsWe showed that genome-wide breeding values prediction based only on identity-by-descent genomic relationships within the known pedigree was as or more reliable than that based on identity-by-state, which implicitly also accounts for genomic relationships that occurred before the known pedigree. Furthermore, combining the two matrices did not improve the prediction compared to using identity-by-descent alone. Including different numbers of generations in the pedigree showed that most of the information in genome-wide breeding values prediction comes from animals with known common ancestors less than four generations back in the pedigree.ConclusionsOur results show that, in pedigreed breeding populations, the accuracy of genome-wide breeding values obtained by identity-by-descent relationships was not improved by identity-by-state information. Although, in principle, genomic selection based on identity-by-state does not require pedigree data, it does use the available pedigree structure. Our findings may explain why the prediction equations derived for one breed may not predict accurate genome-wide breeding values when applied to other breeds, since family structures differ among breeds.

Analysis of inbreeding depression in the first litter size of mice in a long-term selection experiment with respect to the age of the inbreeding

An understanding of inbreeding and inbreeding depression are important in evolutionary biology, conservation genetics, and animal breeding. A new method was developed to detect departures from the classical model of inbreeding; in particular, it investigated differences between the effects of inbreeding in recent generations from that in the more distant past. The method was applied in a long-term selection experiment on first-litter size in mice. The total pedigree included 74 630 animals with ∼30 000 phenotypic records. The experiment comprised several different lines. The highest inbreeding coefficients (F) within a line ranged from 0.22 to 0.64, and the average effective population size (Ne) was 58.1. The analysis divided F into two parts, corresponding to the inbreeding occurring in recent generations (‘new’) and that which preceded it (‘old’). The analysis was repeated for different definitions of ‘old’ and ‘new’, depending on length of the ‘new’ period. In 15 of these tests, ‘new’ inbreeding was estimated to cause greater depression than ‘old’. The estimated depression ranged from −11.53 to −0.79 for the ‘new’ inbreeding and from −5.22 to 15.51 for ‘old’. The difference was significant, the ‘new’ period included at least 25 generations of inbreeding. Since there were only small differences in Ne between lines, and near constant Ne within lines, the effect of ‘new’ and ‘old’ cannot be attributed to the effects of ‘fast’ versus ‘slow’ inbreeding. It was concluded that this departure from the classical model, which predicts no distinction between this ‘old and ‘new’ inbreeding, must implicate natural selection and purging in influencing the magnitude of depression.

Variance components and genetic trend for somatic cell count in Norwegian Cattle

Abstract First-lactation mean somatic cell score (LSCS) in Norwegian Cattle, sampled during 1978–1995 for 1.3 million cows from 2043 sires, were used in genetic analyses. Variance components and genetic trends were estimated for four linear sire models with alternative definitions of contemporary group effects. Model validation demonstrated necessity to separate environmental time trends from genetic trends by modelling contemporary groups as fixed. A model with fixed effect of herd×year was chosen, because it was the simplest and had less significant bias. The heritability estimate for LSCS using this model was 0.11. The resulting genetic trend for all relevant progeny tested bulls was approximately flat, but bull sires born 1984, onwards, showed consistently favourable selection differential for LSCS, most likely due to indirect selection resulting from selection on clinical mastitis.

Accuracy of genomic selection for a sib-evaluated trait using identity-by-state and identity-by-descent relationships.

BackgroundGBLUP (genomic best linear unbiased prediction) uses high-density single nucleotide polymorphism (SNP) markers to construct genomic identity-by-state (IBS) relationship matrices. However, identity-by-descent (IBD) relationships can be accurately calculated for extremely sparse markers. Here, we compare the accuracy of prediction of genome-wide breeding values (GW-BV) for a sib-evaluated trait in a typical aquaculture population, assuming either IBS or IBD genomic relationship matrices, and by varying marker density and size of the training dataset.MethodsA simulation study was performed, assuming a population with strong family structure over three subsequent generations. Traditional and genomic BLUP were used to estimate breeding values, the latter using either IBS or IBD genomic relationship matrices, with marker densities ranging from 10 to ~1200 SNPs/Morgan (M). Heritability ranged from 0.1 to 0.8, and phenotypes were recorded on 25 to 45 sibs per full-sib family (50 full-sib families). Models were compared based on their predictive ability (accuracy) with respect to true breeding values of unphenotyped (albeit genotyped) sibs in the last generation.ResultsAs expected, genomic prediction had greater accuracy compared to pedigree-based prediction. At the highest marker density, genomic prediction based on IBS information (IBS-GS) was slightly superior to that based on IBD information (IBD-GS), while at lower densities (≤100 SNPs/M), IBD-GS was more accurate. At the lowest densities (10 to 20 SNPs/M), IBS-GS was even outperformed by the pedigree-based model. Accuracy of IBD-GS was stable across marker densities performing well even down to 10 SNPs/M (2.5 to 6.1% reduction in accuracy compared to ~1200 SNPs/M). Loss of accuracy due to reduction in the size of training datasets was moderate and similar for both genomic prediction models. The relative superiority of (high-density) IBS-GS over IBD-GS was more pronounced for traits with a low heritability.ConclusionsUsing dense markers, GBLUP based on either IBD or IBS relationship matrices proved to perform better than a pedigree-based model. However, accuracy of IBS-GS declined rapidly with decreasing marker densities, and was even outperformed by a traditional pedigree-based model at the lowest densities. In contrast, the accuracy of IBD-GS was very stable across marker densities.