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Pig mortality is a big welfare and economic challenge. This study investigated the feasibility of reducing mortality of pigs from day 5 to slaughter and from birth to slaughter by breeding. Data of 163,782 female pigs were from DanBred Yorkshire breeding herds. Variances and breeding values were estimated using a linear, a logit and a probit model based on mortality record (0, 1) at individual level. Estimates of direct heritabilities ranged from 0.013 to 0.017 and maternalheritabilities from 0.005 to 0.017. Estimated breeding values (EBVs) from the three models were highly consistent. Although low heritabilities, validation accuracies of EBVs ranged from 0.415 to 0.420 for direct EBVs, from 0.192 to 0.392 for maternal EBVs, and from 0.357 to 396 for total EBVs. The results indicate that reducing pig mortality by breeding is feasible, and linear model is efficient for genetic evaluation of pig mortality.

This study compared four genotyping scenarios of genomic prediction for survival in a simulated pig population with survival rate of 80%. Breeding values were predicted using a linear mixed model and a logit model, based on individual records. The scenarios in order of prediction accuracy were: genotyping all individuals, randomly genotyping 80% individuals, genotyping alive individuals, and no genotyping. Using variance components estimated from pedigree-based model, genomic predictions with genotypes only from alive animals were unbiased. Given the same number of genotyped individuals, random genotyping 80% individuals led to higher prediction accuracy than only genotyping alive individuals, indicating the importance of genotype information of dead pigs. Moreover, the linear and the logit models achieved similar accuracy. We concludethat genotyping dead individuals should be considered, and a linear model can be used for predicting breeding values of survival in pigs.

Grise er sociale dyr, som interagerer med de dyr, som de går sammen med. Derfindes grise, som gør noget godt for de andre grise, og der findes grise, som haren negativ indflydelse på andre grise. I arbejdet med at øge dyrevelfærden igriseproduktionen og forbedre produktiviteten har forskere fra danske SEGESSvineproduktion, Aarhus Universitet og SRUC (Scotland's Rural College)undersøgt, om de sociale egenskaber hos grise kan forbedres gennem avl.Resultaterne tyder på, at det faktisk er muligt. Forskningen er gennemført medstøtte fra GUDP (Grønt Udviklings- og Demonstrationsprogram) underLandbrugs- og Fiskeristyrelsen. Målet har været at udvikle en metode til atberegne en social avlsværdi til avlsgrise og dermed udvælge de grise med debedste sociale gener som forældre til fremtidens grise for avlsselskabetDanBred.

Records on groups of individuals could be valuable for predicting breeding values when a trait is difficult or costly to measure on single individuals, such as feed intake and egg production. Adding genomic information has shown improvement in the accuracy of genetic evaluation of quantitative traits with individual records. Here, we investigated the value of genomic information for traits with group records. Besides, we investigated the improvement in accuracy of genetic evaluation for group-recorded traits when including information on a correlated trait with individual records. The study was based on a simulated pig population, including three scenarios of group structure and size. The results showed that both the genomic information and a correlated trait increased the accuracy of estimated breeding values (EBVs) for traits with group records. The accuracies of EBV obtained from group records with a size 24 were much lower than those with a size 12. Random assignment of animals to pens led to lower accuracy due to the weaker relationship between individuals within each group. It suggests that group records are valuable for genetic evaluation of a trait that is difficult to record on individuals, and the accuracy of genetic evaluation can be considerably increased using genomic information. Moreover, the genetic evaluation for a trait with group records can be greatly improved using a bivariate model, including correlated traits that are recorded individually. For efficient use of group records in genetic evaluation, relatively small group size and close relationships between individuals within one group are recommended.

Additional file 1: Figure S1. Scatter plot of Pearson’s correlations of (genomic) estimated breeding value ((G)EBV) based on full and reduced datasets ( $$\rho_{f,r}$$ ρ f , r ) versus the absolute difference in (G)EBV between the full and reduced datasets ( $$d_{f,r}$$ d f , r ) for all 323 groups for univariate PBLUP (panel A), bivariate PBLUP (panel B), univariate ssGBLUP (panel C), and bivariate ssGBLUP (panel D).

Changes in funerary practices are key to the understanding of social transformations of past societies. Over the course of the Nordic Bronze Age, funerary practices changed from inhumation to cremation. The aim of this study is to shed light on this fundamental change through a cross-examination of archaeometric provenance data and archaeological discussions of the context and layouts of early cremation graves. To this end, we conducted 19 new provenance analyses of strontium isotopes from Early Nordic Bronze age contexts in Thisted County and Zealand and Late Bronze Age contexts from Thisted County and Vesthimmerland (Denmark). These data are subsequently compared with data from other extant relevant studies, including those from Late Bronze Age Fraugde on the Danish island of Fyn.Overall, the variations within our provenience data suggest that the integration and establishment of cremation may not have had a one-to-one relationship with in-migration to Nordic Bronze Age Denmark. Moreover, there seems to be no single blanket scenario which dictated the uptake of cremation as a practice within this part of Southern Scandinavia. By addressing habitus in relation to the deposition of cremations as juxtaposed with these provenance data¸ we hypothesize several potential pathways for the uptake of cremation as a new cultural practice within the Danish Nordic Bronze Age and suggest that this may have been a highly individual process, whose tempo may have been dictated by the specificities of the region(s) concerned.

Additional file 1. Investigation of predictive performance.

The aim of this study was to examine (i) the genetic variation in macro-environmental sensitivity (macro-ES) for ADG in Danish Duroc pigs, (ii) the genetic heterogeneity among sexes, and (iii) residual variance heterogeneity among herds. Record of ADG for 32,297 boars (19 herds) and 42,724 gilts (16 herds) was used for analysis. The data were provided by the National Danish Pig Research Centre. The analysis was performed by fitting univariate reaction norm models with the herd-year-month on test (HYM) effect as environmental covariates and herd-specific residual variance for boars and gilts separately under a Bayesian setting. The environmental covariate was inferred simultaneously with other parameters of the model. Gibbs sampling was used to sample model dispersion and location parameters. The posterior means and highest posterior density intervals of the additive genetic variance, genetic correlations for ADG, and heritability were calculated over the continuous environmental range of −3σh to +3σh (SD of the HYM effect). The coheritability of ADG at the average environmental level and ADG in the environments along the −3σh to +3σh environmental gradient were also calculated. The analysis showed significant variation in macro-ES, revealing genotype by environment interactions (G × E) for ADG. The presence of G × E resulted in changes in additive genetic variance and heritability across the −3σh to +3σh range. The genetic correlations were high and positive between ADG in environments differing by 1σh units or less and decreased to moderately positive between ADG in the extreme environments in both sexes. The coheritability of ADG in the environment at the average level and the −3σh environment for boars were greater than the heritability in the environment at the average level, while it was less for gilts. The coheritability of ADG in the environment at the average level and the +3σh environment for boars was less than heritability in the environment at the average level, while it was either the same or greater for gilts, depending on the residual variance. Boars had larger additive genetic and residual variances than gilts. Heterogeneity of residual variances across herds was shown for both sexes. In conclusion, this study shows the presence of macro-ES, genetic variance heterogeneity among sexes for ADG in pigs, and residual variance heterogeneity across herds. The aim of this study was to examine (i) the genetic variation in macro-environmental sensitivity (macro-ES) for ADG in Danish Duroc pigs, (ii) the genetic heterogeneity among sexes, and (iii) residual variance heterogeneity among herds. Record of ADG for 32,297 boars (19 herds) and 42,724 gilts (16 herds) was used for analysis. The data were provided by the National Danish Pig Research Centre. The analysis was performed by fitting univariate reaction norm models with the herd-year-month on test (HYM) effect as environmental covariates and herd-specific residual variance for boars and gilts separately under a Bayesian setting. The environmental covariate was inferred simultaneously with other parameters of the model. Gibbs sampling was used to sample model dispersion and location parameters. The posterior means and highest posterior density intervals of the additive genetic variance, genetic correlations for ADG, and heritability were calculated over the continuous environmental range of -3σh to +3σh (SD of the HYM effect). The coheritability of ADG at the average environmental level and ADG in the environments along the -3σh to +3σh environmental gradient were also calculated. The analysis showed significant variation in macro-ES, revealing genotype by environment interactions (G × E) for ADG. The presence of G × E resulted in changes in additive genetic variance and heritability across the -3σh to +3σh range. The genetic correlations were high and positive between ADG in environments differing by 1σh units or less and decreased to moderately positive between ADG in the extreme environments in both sexes. The coheritability of ADG in the environment at the average level and the -3σh environment for boars were greater than the heritability in the environment at the average level, while it was less for gilts. The coheritability of ADG in the environment at the average level and the +3σh environment for boars was less than heritability in the environment at the average level, while it was either the same or greater for gilts, depending on the residual variance. Boars had larger additive genetic and residual variances than gilts. Heterogeneity of residual variances across herds was shown for both sexes. In conclusion, this study shows the presence of macro-ES, genetic variance heterogeneity among sexes for ADG in pigs, and residual variance heterogeneity across herds.

Additional file 2: Figure S2. Manhattan plot of GWAS in Yorkshire pigs for (a) FRONT, (b) BACK, (c) HIND and (d) CONF. The data provided represent the Manhattan plot of single-trait association analyses in Yorkshire pigs for four traits studied.

International audience; Crossbreding is predominant and intensively used in commercial meat production systems, especially in poultry and swine. Genomic evaluation has been successfully applied for breeding within purebreds but also offers opportunities of selecting purebreds for crossbred performance by combining information from purebreds with information from crossbreds. However, it generally requires that all relevant animals are genotyped, which is costly and presently does not seem to be feasible in practice. Recently, a novel single-step BLUP method for genomic evaluation of both purebred and crossbred performance has been developed that can incorporate marker genotypes into a traditional animal model. This new method has not been validated in real data sets. In this study, we applied this single-step method to analyze data for the maternal trait of total number of piglets born in Danish Landrace, Yorkshire, and two-way crossbred pigs in different scenarios. The genetic correlation between purebred and crossbred performances was investigated first, and then the impact of (crossbred) genomic information on prediction reliability for crossbred performance was explored. The results confirm the existence of a moderate genetic correlation, and it was seen that the standard errors on the estimates were reduced when including genomic information. Models with marker information, especially crossbred genomic information, improved model-based reliabilities for crossbred performance of purebred boars and also improved the predictive ability for crossbred animals and, to some extent, reduced the bias of prediction. We conclude that the new single-step BLUP method is a good tool in the genetic evaluation for crossbred performance in purebred animals.

A novel Horizontal model is presented for multitrait analysis of longitudinal traits through random regression analysis combined with single recorded traits. Weekly ADFI on test for Danish Duroc, Landrace, and Yorkshire boars were available from the national test station and were collected from 30 to 100 kg BW. Single recorded production traits of ADG from birth to 30 kg BW (ADG30), ADG from 30 to 100 kg BW (ADG100), and lean meat percentage (LMP) were available from breeding herds or the national test station. The Horizontal model combined random regression analysis of feed intake (FI) with single recorded traits of ADG100, LMP, and ADG30. In the Horizontal model, the FI data were horizontally structured with FI on each week as a "trait." The additive genetic and litter effects were modeled to be common across different FI records by reducing the rank of the covariance matrices using second- and first-order Legendre polynomials of age on test, respectively. The fixed effect and random residual variance were estimated for each weekly FI trait. Residual feed intake (RFI) was derived from the conditional distribution of FI given the breeding values of ADG100 and LMP. The heritability of FI varied by week on test in Duroc (0.12 to 0.19), Landrace (0.13 to 0.22), and Yorkshire (0.21 to 0.23). The heritability of RFI was lowest and highest in wk 6 (0.03) and 10 (0.10), respectively, in Duroc and wk 7 (0.04 and 0.02) and 1 (0.09 and 0.20), respectively, in Landrace and Yorkshire. The proportion of FI genetic variance explained by RFI ranged from 20 to 75% in Duroc, from 19 to 75% in Landrace, and from 11 to 91% in Yorkshire. Average daily gain from 30 to 100 kg BW and ADG30 heritabilities were moderate in Duroc (0.24 and 0.22, respectively), Landrace (0.34 and 0.25, respectively), and Yorkshire (0.34 and 0.22, respectively). Lean meat percentage heritability was moderate in Duroc (0.37) and large in Landrace (0.62) and Yorkshire (0.60). The genetic correlation of FI with ADG100 increased by week on test followed by a 32% decrease from wk 7 in Duroc and a 7% decrease in dam line breeds. Defining RFI as genetically independent of production traits leads to consistent and easy interpretable breeding values. The genetic parameters of traits in the feed efficiency complex and their dynamics over the test period showed breed differences that could be related to the fatness and growth potential of the breeds. The Horizontal model can be used to simultaneously analyze repeated and single recorded traits through proper modeling of the environmental variances and covariances.

Genomic selection has offered a new paradigm for livestock breeding within purebred populations, but it also offers greater opportunities for incorporating information from crossbred individuals and selection for crossbred performance. Wei and van der Werf (1994) presented a model for genetic evaluation using information from both purebred and crossbred animals for a two-breed crossbreeding system. The model provides breeding values for both purebred and crossbred performances. However, an extension of that model to incorporate genomic data has not been made yet. Here, a single-step method for genomic evaluation of both purebred and crossbred performances is presented. The model is on the one hand a reformulation and extension of the model by Wei van der Werf (1994), and on the other hand it extends previously studied genomic models for crossbred animals to include phenotypes on purebred animals and incorporate information on non-genotyped animals

We reasoned that there are diminishing marginal returns from genomic selection as the proportion of genotyped selection candidates is increased and breeding values based on a priori information are used to choose the candidates that are genotyped. We tested this premise by stochastic simulation of breeding schemes that resembled those used for pigs. We estimated rates of genetic gain and inbreeding realized by genomic selection in breeding schemes where candidates were phenotyped before genotyping and 0-100% of the candidates were genotyped based on predicted breeding values. Genotypings were allocated to male and female candidates at ratios of 100:0, 75:25, 50:50, 25:75, and 0:100. For genotyped candidates, a direct-genomic value (DGV) was sampled with reliabilities 0.10, 0.50, and 0.90. Ten sires and 300 dams with the highest breeding values after genotyping were selected at each generation. Selection was for a single trait with heritability 0.20. We found that the marginal returns did diminish as the genotyping proportion was increased, while the rate at which the returns diminished slowed as the DGV became more reliable. With DGV reliability 0.10, genotyping as little as 5% of the selection candidates realized 86% of the additional genetic gain and 67% of the reduction in inbreeding that was realized by genotyping 100% of the candidates. All of the genetic gain and reduction in inbreeding was realized by genotyping 40 and 50% of the candidates. When the reliability was increased to 0.90, genotyping 20% of the candidates was required to realize 76% of the genetic gain and 85% of the reduction in inbreeding. Genotyping 50% of the selection candidates with DGV reliability 0.90 realized 91% of the genetic gain and 94% of the reduction in inbreeding. Regardless of the DGV reliability, returns at low genotyping proportions of 0.5-10% were maximized when only male candidates were genotyped. At the high genotyping proportions of 20-50%, returns were maximized by genotyping both males and females. Our findings indicate that, provided a priori information is available, only 5-20% of the selection candidates need to be genotyped to realize most of the benefits from genomic selection. At these genotyping proportions, it is best to target males in schemes when the selection intensity for males is greater than females. Our findings should be welcomed by breeders because they suggest that large investments in genotyping are not required to reap most of the benefits from genomic selection

I et globaliseret, senmoderne, hyperkomplekst samfund præget af refleksion og metarefleksion vinder m°albarhed frem som kvalitativt parameter i forhold til fænomener som undervisning og læring. Dette kan ses som en konsekvens af at vi ikke fuldt ud forst°ar de bagvedliggende mekanismer og derfor med udgangspunkt i New Public Management-tænkning definerer læring ud fra et kriterium om m°alopfyldelse. Specialet tager med udgangspunkt i denne og afledte problemstillinger livtag med musikfagets aktuelle position i det almene gymnasium med en overordnet p°astand om markedsorienterede diskursers indflydelse p°a tænkningen af uddannelsessystemets form°al og indretning som indirekte °arsag til reformens nedprioritering af faget og som en fortsat udfordring i kampen for et musikfagligt tilbud i gymnasiet., Music in the Gymnasium. Set of assumptions and terms in music education through a discourse analytical approach.