Quantitative trait loci (QTL) associated with resistance of rainbow trout Oncorhynchus mykiss against the parasitic ciliate Ichthyophthirius multifiliis.

The parasitic ciliate Ichthyophthirius multifiliis has a low host specificity eliciting white spot disease (WSD) in a wide range of freshwater fishes worldwide. The parasite multiplies rapidly whereby the infection may reach problematic levels in a host population within a few days. The parasite targets both wild and cultured fish but the huge economic impact of the protozoan is associated with mortality, morbidity and treatment in aquacultural enterprises. We have investigated the potential for genetic selection of WSD-resistant strains of rainbow trout. Applying the DNA typing system Affymetrix® and characterizing the genome of the individual fish by use of 57,501 single nucleotide polymorphisms (SNP) and their location on the rainbow trout chromosomes, we have genetically characterized rainbow trout with different levels of natural resistance towards WSD. Quantitative trait loci (QTL) used for the selection of breeders with specific markers for resistance are reported. We found a significant association between resistance towards I. multifiliis infection and SNP markers located on the two specific rainbow trout chromosomes Omy 16 and Omy 17. Comparing the expression of immune-related genes in fish-with and without clinical signs-we recorded no significant difference. However, trout surviving the infection showed high expression levels of genes encoding IgT, T-cell receptor TCRß, C3, cathelicidins 1 and 2 and SAA, suggesting these genes to be associated with protection.

Differential effects of epidermal growth factor (EGF) receptor ligands on receptor binding, downstream signalling pathways and DNA synthesis in hepatocytes.

Hepatocytes are responsive to mitogenic effects of several ligands acting via EGFR. Studying primary cultures of rat hepatocytes, we found that, as compared to EGF, HB-EGF had a markedly higher affinity of the EGFR, while AR and TGFα had lower affinity. HB-EGF was also more potent compared to the other growth factors regarding phosphorylation of EGFR, Shc, ERK1/2 and Akt. All ligands induced phosphorylation of ErbB2, indicating receptor heterodimerization. TGFα, despite having much lower receptor affinity, was about equally potent and efficacious as HB-EGF as a stimulator of DNA synthesis. In contrast, EGF had relatively high affinity but markedly lower efficacy in stimulation of DNA synthesis. The results suggest that amplifying and/or inhibitory mechanisms may modulate the mitogenic responses downstream of the initial signalling steps, and that this may affect the effects of the EGFR ligands differentially.

Longitudinal monitoring of gene expression in ultra-low-volume blood samples self-collected at home.

Blood transcriptional profiles could serve as biomarkers of clinical changes in subjects at-risk for or diagnosed with diabetes. However, transcriptional variation over time is poorly understood due to the impracticality of frequent longitudinal phlebotomy in large patient cohorts. We have developed a novel transcriptome assessment method that could be applied to fingerstick blood samples self-collected by study volunteers. Fifteen µL of blood from a fingerstick yielded sufficient RNA to analyse > 176 transcripts by high-throughput quantitative polymerase chain reaction (PCR). We enrolled 13 subjects with type 1 diabetes and 14 controls to perform weekly collections at home for a period of 6 months. Subjects returned an average of 24 of 26 total weekly samples, and transcript data were obtained successfully for > 99% of samples returned. A high degree of correlation between fingerstick data and data from a standard 3 mL venipuncture sample was observed. Increases in interferon-stimulated gene expression were associated with self-reported respiratory infections, indicating that real-world transcriptional changes can be detected using this assay. In summary, we show that longitudinal monitoring of gene expression is feasible using ultra-low-volume blood samples self-collected by study participants at home, and can be used to monitor changes in gene expression frequently over extended periods.

Genetic relationships between boar feed efficiency and sow piglet production, body condition score, and stayability in Norwegian Landrace pigs.

Both feed efficiency and sow production are economically important traits in pig breeding. One challenge in a maternal line such as Norwegian Landrace is to breed for highly feed efficient fattening pigs and, at the same time, produce sows with high daily feed intake to maintain their BCS in multiple parities. The aim of this study was to estimate genetic correlations among novel feed efficiency measurements on Norwegian Landrace boars and piglet production, stayability, and body condition in Norwegian Landrace sows. The feed efficiency measurements were lean meat and fat efficiency. These measurements were calculated using an extended residual feed intake model where total feed intake in the test period was the response variable and fat (kg) and lean meat (kg) on the carcass were included as both fixed and random regressions. The random regression coefficients that resulted from this model were breeding values, which represented the amount of feed used to produce an extra kilogram of lean meat and fat. The sow traits were stayability of the sow from first to second parity, BCS at weaning, litter weight at 3 wk, and total number of piglets born. All traits were recorded on first parity purebred Norwegian Landrace and analyzed using multivariate animal models. All genetic correlations between fat efficiency and sow traits were low. Significant genetic correlations were found only between fat efficiency and stayability (0.21 ± 0.11) and between fat efficiency and total litter weight at 3 wk (0.21 ± 0.10). The results indicate that selection for efficient deposition of fat could give poor stayability and lower litter weight at 3 wk in first parity sows. The genetic correlations between lean meat efficiency and sow traits were not significantly different from 0 and signified no genetic relationships between these traits. Selection for efficient deposition of lean meat should not affect the sow traits and is, therefore, beneficial.

NETosis-associated serum biomarkers are reduced in type 1 diabetes in association with neutrophil count.

As the immune pathways involved in the pathogenesis of type 1 diabetes (T1D) are not fully understood, biomarkers implicating novel mechanisms of disease are of great interest and call for independent evaluation. Recently, it was reported that individuals with T1D display dramatic elevations in circulating components of neutrophil extracellular traps (NETs), indicating a potential role for NETosis in T1D. Our aim was to evaluate further the potential of NET-associated proteins as novel circulating biomarkers in T1D. We tested serum from subjects with T1D (n = 44) with a median age of 26·5 years and a median duration of 2·2 years, along with 38 age-matched controls. T1D subjects did not show elevations in either neutrophil elastase (NE) or proteinase 3 (PR3), as reported previously. In fact, both NE and PR3 levels were reduced significantly in T1D subjects, particularly in subjects within 3 years of diagnosis, consistent with the known reduction in neutrophil counts in recent-onset T1D. Indeed, levels of both NE and PR3 correlated with absolute neutrophil counts. Therefore, while not ruling out potential local or transient spikes in NETosis activity, the levels of these serum markers do not support a role for systemically elevated NETosis in the T1D population we studied. Rather, a modest reduction in these markers may reflect other important aspects of disease activity associated with reduced neutrophil numbers.

Genetic variation in efficiency to deposit fat and lean meat in Norwegian Landrace and Duroc pigs.

Feed costs amount to approximately 70% of the total costs in pork production, and feed efficiency is, therefore, an important trait for improving pork production efficiency. Production efficiency is generally improved by selection for high lean growth rate, reduced backfat, and low feed intake. These traits have given an effective slaughter pig but may cause problems in piglet production due to sows with limited body reserves. The aim of the present study was to develop a measure for feed efficiency that expressed the feed requirements per 1 kg deposited lean meat and fat, which is not improved by depositing less fat. Norwegian Landrace ( = 8,161) and Duroc ( = 7,202) boars from Topigs Norsvin's testing station were computed tomography scanned to determine their deposition of lean meat and fat. The trait was analyzed in a univariate animal model, where total feed intake in the test period was the dependent variable and fat and lean meat were included as random regression cofactors. These cofactors were measures for fat and lean meat efficiencies of individual boars. Estimation of fraction of total genetic variance due to lean meat or fat efficiency was calculated by the ratio between the genetic variance of the random regression cofactor and the total genetic variance in total feed intake during the test period. Genetic variance components suggested there was significant genetic variance among Norwegian Landrace and Duroc boars in efficiency for deposition of lean meat (0.23 ± 0.04 and 0.38 ± 0.06) and fat (0.26 ± 0.03 and 0.17 ± 0.03) during the test period. The fraction of the total genetic variance in feed intake explained by lean meat deposition was 12% for Norwegian Landrace and 15% for Duroc. Genetic fractions explained by fat deposition were 20% for Norwegian Landrace and 10% for Duroc. The results suggested a significant part of the total genetic variance in feed intake in the test period was explained by fat and lean meat efficiency. These new efficiency measures may give the breeders opportunities to select for animals with a genetic potential to deposit lean meat efficiently and at low feed costs in slaughter pigs rather than selecting for reduced the feed intake and backfat.

Genetic analysis of vibriosis and viral nervous necrosis resistance in Atlantic cod (Gadus morhua L.) using a cure model.

The aim of this study was to investigate whether observed time-until-death of Atlantic cod (Gadus morhua L.) juveniles in separate challenge tests with Vibrio anguillarum (causes vibriosis) and nodavirus [causes viral nervous necrosis (VNN)] are due to differences in susceptibility (whether at risk or not) or increased endurance (individual hazard, given that the animal is susceptible) using a cure mixture (CURE) model with Gibbs sampling. Observed time-until-death, prepared as sequential binary records, were analyzed with the CURE model and results were compared with cross-sectional threshold (SIMPLE) and an ordinary longitudinal survival score (NAÏVE) model (i.e., assuming that all animals are susceptible). Overall mortality at the end of the test was 86 and 71% for vibriosis and VNN, respectively. But the CURE model estimated 92 and 82% of the population to be susceptible to vibriosis and VNN, respectively. Hence, a substantial fraction among the survivors were considered to be susceptible but with high endurance. The underlying heritability of susceptibility was moderate for vibriosis (0.33) and extremely high for VNN (0.91), somewhat greater compared with classical SIMPLE model (0.19 and 0.76 for vibriosis and VNN, respectively), analyzing end survival as a cross-sectional binary trait. Estimates of the underlying heritability were low for single test-day scores of both endurance (0.02 and 0.15 for vibriosis and VNN, respectively) in the CURE model and for the NAÏVE model (0.02 and 0.18 for vibriosis and VNN, respectively). Based on the CURE model, the genetic correlation between susceptibility and endurance was low to moderately positive and significantly different from unity (P < 0.01) for both vibriosis (0.13) and VNN (0.47). Estimated breeding values from the SIMPLE and NAÏVE models showed moderate to high correlations (0.41 to 0.96) with EBV for susceptibility and endurance in the CURE model. The analyses indicate that susceptibility and endurance are apparently distinct genetic traits. Still, the genetic variation estimated in the SIMPLE and NAÏVE models seems to a large extent to be controlled by susceptibility and an efficient genetic selection for reduced susceptibility to vibriosis and VNN is therefore likely feasible even when using classical (noncure) models. Earlier termination of the challenge test or back truncation of survival data is not recommended as this likely shifts the focus of selection towards endurance rather than susceptibility.

Comparison of random regression and repeatability models to predict breeding values from test-day records of Norwegian goats.

One aim of the research was to challenge a previously selected repeatability model with 2 other repeatability models. The main aim, however, was to evaluate random regression models based on the repeatability model with lowest mean-squared error of prediction, using Legendre polynomials up to third order for both animal additive genetic and permanent environmental effects. The random regression and repeatability models were compared for model fit (using likelihood-ratio testing, Akaike information criterion, and the Bayesian information criterion) and the models' mean-squared errors of prediction, and by cross-validation. Cross-validation was carried out by correlating excluded observations in one data set with the animals' breeding values as predicted from the pedigree only in the remaining data, and vice versa (splitting proportion: 0.492). The data was from primiparous goats in 2 closely tied buck circles (17 flocks) in Norway, with 11,438 records for daily milk yield and 5,686 to 5,896 records for content traits (fat, protein, and lactose percentages). A simple pattern was revealed; for daily milk yield with about 5 records per animal in first lactation, a second-order random regression model should be chosen, whereas for content traits that had only about 3 observations per goat, a first-order polynomial was preferred. The likelihood-ratio test, Akaike information criterion, and mean-squared error of prediction favored more complex models, although the results from the latter and the Bayesian information criterion were in the direction of those obtained with cross-validation. As the correlation from cross-validation was largest with random regression, genetic merit was predicted more accurate with random regression models than with the repeatability model.

A method for the prediction of multitrait breeding values for use in stochastic simulation to compare progeny-testing schemes, with large progeny groups for proven sires.

A method of approximating estimated breeding values (EBV) from a multivariate distribution of true breeding values (TBV) and EBV is proposed for use in large-scale stochastic simulation of alternative breeding schemes with a complex breeding goal. The covariance matrix of the multivariate distributions includes the additive genetic (co)variances and approximated prediction error (co)variances at different selection stages in the life of the animal. The prediction error (co)variance matrix is set up for one animal at a time, utilizing information on the selection candidate and its offspring, the parents, as well as paternal and maternal half- sibs. The EBV are a regression on TBV taking individual uncertainty into account, but with additional 'free' variation drawn at random. With the current information included in the calculation of the prediction error variance of a selection candidate, it is concluded that the method can be used to optimize progeny-testing schemes, where the progeny-tested sires are utilized with large progeny groups, e.g. through artificial insemination.

Genetic parameters between slaughter pig efficiency and growth rate of different body tissues estimated by computed tomography in live boars of Landrace and Duroc.

In this study, computed tomography (CT) technology was used to measure body composition on live pigs for breeding purposes. Norwegian Landrace (L; n = 3835) and Duroc (D; n = 3139) boars, selection candidates to be elite boars in a breeding programme, were CT-scanned between August 2008 and August 2010 as part of an ongoing testing programme at Norsvin's boar test station. Genetic parameters in the growth rate of muscle (MG), carcass fat (FG), bone (BG) and non-carcass tissue (NCG), from birth to ∼100 kg live weight, were calculated from CT data. Genetic correlations between growth of different body tissues scanned using CT, lean meat percentage (LMP) calculated from CT and more traditional production traits such as the average daily gain (ADG) from birth to 25 kg (ADG1), the ADG from 25 kg to 100 kg (ADG2) and the feed conversion ratio (FCR) from 25 kg to 100 kg were also estimated from data on the same boars. Genetic parameters were estimated based on multi-trait animal models using the average information-restricted maximum likelihood (AI-REML) methodology. The heritability estimates (s.e. = 0.04 to 0.05) for the various traits for Landrace and Duroc were as follows: MG (0.19 and 0.43), FG (0.53 and 0.59), BG (0.37 and 0.58), NCG (0.38 and 0.50), LMP (0.50 and 0.57), ADG1 (0.25 and 0.48), ADG2 (0.41 and 0.42) and FCR (0.29 and 0.42). Genetic correlations for MG with LMP were 0.55 and 0.68, and genetic correlations between MG and ADG2 were -0.06 and 0.07 for Landrace and Duroc, respectively. LMP and ADG2 were clearly unfavourably genetically correlated (L: -0.75 and D: -0.54). These results showed the difficulty in jointly improving LMP and ADG2. ADG2 was unfavourably correlated with FG (L: 0.84 and D: 0.72), thus indicating to a large extent that selection for increased growth implies selection for fatness under an ad libitum feeding regime. Selection for MG is not expected to increase ADG2, but will yield faster growth of the desired tissues and a better carcass quality. Hence, we consider MG to be a better biological trait in selection for improved productivity and carcass quality. CT is a powerful instrument in conjunction with breeding, as it combines the high accuracy of CT data with measurements taken from the selection candidates. CT also allows the selection of new traits such as real body composition, and in particular, the actual MG on living animals.

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.

Validation of alternative models in genetic evaluation of racing performance in North Swedish and Norwegian cold-blooded trotters.

There have been several approaches to the estimation of breeding values of performance in trotters, and the objective of this study was to validate different alternatives for genetic evaluation of racing performance in the North Swedish and Norwegian cold-blooded trotters. The current bivariate approach with the traits racing status (RACE) and earnings (EARN) was compared with a threshold-linear animal model and the univariate alternative with the performance trait only. The models were compared based on cross-validation of standardized earnings, using mean-squared errors of prediction (MSEP) and the correlation between the phenotype (Y) and the estimated breeding value (EBV). Despite possible effects of selection, a rather high estimate of heritability of EARN was found in our univariate analysis. The genetic trend estimate for EARN was clearly higher in the bivariate specification than in the univariate model, as a consequence of the considerable size of estimated heritability of RACE and its high correlation with EARN (approximately 0.8). RACE is highly influenced by ancestry rather than the on-farm performance of the horse itself. Consequently, the use of RACE in the genetic analysis may inflate the genetic trend of EARN because of a double counting of pedigree information. Although, because of the higher predictive ability of the bivariate specification, the improved ranking of animals within a year-class and the inability to discriminate between models for genetic trend, we propose to base prediction of breeding values on the current bivariate model.

Quantitative genetics of disease resistance in vaccinated and unvaccinated Atlantic salmon (Salmo salar L.).

Furunculosis (Aeromonoas salmonicida) is an important disease in Atlantic salmon (Salmo salar) farming. Vaccination and selective breeding for increased resistance to the disease on the basis of challenge tests of unvaccinated fish are used as complementary prophylactic methods. An important issue is whether genetic predisposition to infection is consistent across vaccinated and unvaccinated fish. Hence, the main objective of this study was to determine the magnitude of the genetic associations (correlations) between resistance to furunculosis in vaccinated and unvaccinated fish, and to estimate the magnitude of the correlation of resistance to furunculosis with resistance to the viral diseases infectious pancreatic necrosis (IPN) and infectious salmon anaemia (ISA). Sub-samples of unvaccinated and vaccinated salmon from 150 full-sib families were subjected to separate cohabitation challenge tests. Substantial genetic variation was found in resistance to furunculosis in both the unvaccinated (heritabilities of 0.51 ± 0.05) and vaccinated (0.39 ± 0.06) fish. However, the genetic correlation between resistance to furunculosis in the two groups was low (0.32 ± 0.13), indicating a weak genetic association between resistance in the two groups. Hence, the current selection strategy on the basis of challenge tests of unvaccinated fish is likely to produce low genetic improvement in resistance to furunculosis under field conditions, where fish are vaccinated with an effective vaccine. Evidence was found of significantly favourable genetic associations of resistance to furunculosis in unvaccinated (but less so for vaccinated) fish with resistance to both IPN and ISA (unvaccinated fish), indicating that vaccination 'mask' genetic associations between resistance to different diseases.

Genetic parameters of fat quality in pigs measured by near-infrared spectroscopy.

Subcutaneous fat from Norwegian Landrace (n=3230) and Duroc (n=1769) pigs was sampled to investigate the sources of variation and genetic parameters of various fatty acids, fat moisture percentage and fat colour, with the lean meat percentage (LMP) also included as a trait representing the leanness of the pig. The pigs were from half-sib groups of station-tested boars included in the Norwegian pig breeding scheme. They were fed ad libitum to obtain an average of 113 kg live weight. Near-infrared spectroscopy (NIRS) was applied for prediction of the fatty acids and fat moisture percentage, and Minolta was used for the fat colour measurements. Heritabilities and genetic correlations were estimated with a multi-trait animal model using average information-restricted maximum likelihood (AI-REML) methodology. Fat from Landrace pigs had considerably more monounsaturated fatty acids, polyunsaturated fatty acids (PUFAs) and fat moisture, as well as less saturated fatty acids (SFAs) than fat from Duroc pigs. The heritability estimates (s.e. 0.03 to 0.08) for the various fatty acids were as follows: Palmitic, C16:0 (0.39 and 0.51 for Landrace and Duroc pigs, respectively); Palmitoleic, C16:1n-7 (0.41 and 0.50); Steric, C18:0 (0.46 and 0.54); Oleic, C18:1n-9 (0.67 and 0.57); Linoleic, C18:2n-6 (0.44 and 0.46); α-linolenic, C18:3n-3 (0.37 and 0.25) and n-6/n-3 ratio (0.06 and 0.01). The other fat quality traits revealed the following heritabilities: fat moisture (0.28 and 0.33), colour values in subcutaneous fat: L* (whiteness; 0.22 and 0.21), a* (redness; 0.13 and 0.24) and b* (yellowness; 0.07 and 0.17) and LMP (0.46 and 0.47). LMP showed high positive genetic correlations to PUFA (C18:2n-6 and C18:3n-3), which implies that selecting leaner pigs changes the fatty acid composition and deteriorates the quality of fat. Higher concentrations of PUFA are not beneficial as the ratio of n-6 and n-3 fatty acids becomes unfavourably high. Owing to the high genetic correlation between C18:2n-6 and C18:3n-3 and a low heritability for this ratio, the latter is difficult to change through selection. However, a small reduction in the ratio should be expected if selection aims at reducing the level of C18:2n-6. Selection for more C18:1n-9 is possible in view of the genetic parameters, which are favourable for eating quality, technological quality and human nutrition. The NIRS technology and the high heritabilities found in this study make it possible to implement fat quality traits to achieve the breeding goal in the selection of a lean pig with better fat quality.

Prediction of fat quality in pig carcasses by near-infrared spectroscopy.

This study was conducted to evaluate the potential of near-infrared (NIR) spectroscopy (NIRS) technology for prediction of the chemical composition (moisture content and fatty acid composition) of fat from fast-growing, lean slaughter pig samples coming from breeding programmes. NIRS method I: a total of 77 samples of intact subcutaneous fat from pigs were analysed with the FOSS FoodScan NIR spectrophotometer (850 to 1050 nm) and then used to predict the moisture content by using partial least squares (PLS) regression methods. The best equation obtained has a coefficient of determination for cross-validation (CV; R(2)(cv)) and a root mean square error of a CV (RMSECV) of 0.88 and 1.18%, respectively. The equation was further validated with (n = 15) providing values of 0.83 and 0.42% for the coefficient of determination for validation (R(2)(val)) and root mean square error of prediction (RMSEP), respectively. NIRS method II: in this case, samples of melted subcutaneous fat were analysed in an FOSS XDS NIR rapid content analyser (400 to 2500 nm). Equations based on modified PLS regression methods showed that NIRS technology could predict the fatty acid groups, the main fatty acids and the iodine value accurately with R(2)(cv), RMSECV, R(2)(val) and RMSEP of 0.98, 0.38%, 0.95 and 0.49%, respectively (saturated fatty acids), 0.94, 0.45%, 0.97 and 0.65%, respectively (monounsaturated fatty acids), 0.97, 0.28%, 0.99 and 0.34%, respectively (polyunsaturated fatty acids), 0.76, 0.61%, 0.84 and 0.87%, respectively (palmitic acid, C16:0), 0.75, 0.16%, 0.89 and 0.10%, respectively (palmitoleic acid, C16:1n-7), 0.93, 0.41%, 0.96 and 0.64%, respectively (steric acid, C18:0), 0.90, 0.51%, 0.94 and 0.44%, respectively (oleic acid, C18:1n-9), 0.97, 0.25%, 0.98 and 0.29% (linoleic acid, C18:2n-6), 0.68, 0.09%, 0.57 and 0.16% (α-linolenic acid, C18:3n-3) and 0.97, 0.57, 0.97 and 1.22, respectively (iodine value, calculated). The magnitude of this error showed quite good accuracy using these rapid methods in prediction of the moisture and fatty acid composition of fat from pigs involved in breeding schemes.

A sequential threshold cure model for genetic analysis of time-to-event data.

In analysis of time-to-event data, classical survival models ignore the presence of potential nonsusceptible (cured) individuals, which, if present, will invalidate the inference procedures. Existence of nonsusceptible individuals is particularly relevant under challenge testing with specific pathogens, which is a common procedure in aquaculture breeding schemes. A cure model is a survival model accounting for a fraction of nonsusceptible individuals in the population. This study proposes a mixed cure model for time-to-event data, measured as sequential binary records. In a simulation study survival data were generated through 2 underlying traits: susceptibility and endurance (risk of dying per time-unit), associated with 2 sets of underlying liabilities. Despite considerable phenotypic confounding, the proposed model was largely able to distinguish the 2 traits. Furthermore, if selection is for improved susceptibility rather than endurance, the error of applying a classical survival model was nonnegligible. The difference was most pronounced for scenarios with substantial underlying genetic variation in endurance and when the 2 underlying traits were lowly genetically correlated. In the presence of nonsusceptible individuals, the method provides a novel and more accurate tool for utilization of time-to-event data, and has also been proven successful when applied to zero-inflated longitudinal binary data.

Genetic parameters of meat quality traits in two pig breeds measured by rapid methods.

To study genetic variation in meat quality traits measured by rapid methods, data were recorded between 2005 and 2008 on samples of M. longissimus dorsi (LD) in Landrace (n = 3838) and Duroc (n = 2250) pigs included in the Norwegian pig breeding scheme. In addition, ultimate pH levels in the glycolytic LD (loin muscle) and M. gluteus medius (GM, ham muscle), and in the oxidative m. gluteus profundus (GP, ham muscle) were recorded as an extended data set (n = 16 732 and n = 7456 for Landrace and Duroc, respectively) from 1998 to 2008. Data were analysed with a multi-trait animal model using AI-REML methodology. Meat from Duroc had considerably more intramuscular fat (IMF), less moisture and protein, appeared darker with higher colour intensity and had lower drip loss than meat from Landrace. The heritability estimates (s.e. 0.01 to 0.07) for pH in LD (0.19 and 0.27 for Landrace and Duroc, respectively), GM (0.12 and 0.22) and GP (0.19 and 0.38), drip loss (0.23 and 0.33), colour values: L* (lightness) (0.41 and 0.28), a* (redness) (0.46 and 0.43), b* (yellowness) (0.31 and 0.33), IMF (0.50 and 0.62), muscle moisture (0.31 and 0.50) and muscle protein content (0.40 and 0.54) in LD all demonstrated moderate-to-high genetic variation for these traits in both breeds. Near infrared spectroscopy and EZ-DripLoss are modern technologies used in this study for the determination of chemical components and drip loss in meat. These methods gave higher heritabilities than more traditional methods used to measure these traits. The estimated genetic correlations between moisture and IMF in Duroc, and pH and drip loss in Duroc were both -0.89. Interesting differences between the two breeds in numerical value of some genetic correlations were observed, probably reflecting the differences in physiology and selection history between Landrace and Duroc. The estimated genetic correlation between drip loss and pH was much stronger in Duroc than in Landrace (-0.89 and -0.63, respectively). This might be due to the high pH in Duroc, whereas Landrace had a lower pH closer to the iso-electric point for muscle proteins. The positive genetic correlation between the L* value in meat and IMF in Duroc (0.50) was an effect of differences in visible marbling, rather than meat colour. For Landrace, this correlation was negative (-0.20). IMF content showed favourable genetic correlations to drip loss (-0.36 and -0.35 for Landrace and Duroc, respectively).

Predictive abilities of different statistical models for analysis of survival data in dairy cattle.

The objective of this study was to compare alternative trait definitions and statistical models for genetic evaluation of survival in dairy cattle. Data from the first 5 lactations of 808,750 first-crop daughters of 3,064 Norwegian Red sires were analyzed. Seven sire models were used for genetic analyses: linear and threshold cross-sectional models for binary survival scores from first lactation; a linear multi-trait model for survival scores from the first 3 lactations; linear and threshold repeatability models for survival scores from the first 5 lactations; a Weibull frailty model for herd life in first lactation; and a Weibull frailty model for herd life in the first 5 lactations. The models were compared to assess predictive ability of sire estimated breeding values with respect to average survival 365 d after first calving for second-crop daughters (not included in calculation of predicted transmitting abilities) of 375 elite sires. Generally, the linear multi-trait model analyzing survival in the first 3 lactations as correlated traits gave more-accurate predicted sire breeding values compared with both linear and Weibull frailty models using data from first lactation only, even when the latter models were extended to include data up to the sixth lactation. The Weibull frailty models did not improve predictive ability of sire estimated breeding values over what was obtained using a simple cross-sectional linear model for binary survival in first lactation.

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.