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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.

The transitions from foraging to farming and later to pastoralism in Stone Age Eurasia (c. 11-3 thousand years before present, BP) represent some of the most dramatic lifestyle changes in human evolution. We sequenced 317 genomes of primarily Mesolithic and Neolithic individuals from across Eurasia combined with radiocarbon dates, stable isotope data, and pollen records. Genome imputation and co-analysis with previously published shotgun sequencing data resulted in >1600 complete ancient genome sequences offering fine-grained resolution into the Stone Age populations. We observe that: 1) Hunter-gatherer groups were more genetically diverse than previously known, and deeply divergent between western and eastern Eurasia. 2) We identify hitherto genetically undescribed hunter-gatherers from the Middle Don region that contributed ancestry to the later Yamnaya steppe pastoralists; 3) The genetic impact of the Neolithic transition was highly distinct, east and west of a boundary zone extending from the Black Sea to the Baltic. Large-scale shifts in genetic ancestry occurred to the west of this “Great Divide”, including an almost complete replacement of hunter-gatherers in Denmark, while no substantial ancestry shifts took place during the same period to the east. This difference is also reflected in genetic relatedness within the populations, decreasing substantially in the west but not in the east where it remained high until c. 4,000 BP; 4) The second major genetic transformation around 5,000 BP happened at a much faster pace with Steppe-related ancestry reaching most parts of Europe within 1,000-years. Local Neolithic farmers admixed with incoming pastoralists in eastern, western, and southern Europe whereas Scandinavia experienced another near-complete population replacement. Similar dramatic turnover-patterns are evident in western Siberia; 5) Extensive regional differences in the ancestry components involved in these early events remain visible to this day, even within countries. Neolithic farmer ancestry is highest in southern and eastern England while Steppe-related ancestry is highest in the Celtic populations of Scotland, Wales, and Cornwall (this research has been conducted using the UK Biobank resource); 6) Shifts in diet, lifestyle and environment introduced new selection pressures involving at least 21 genomic regions. Most such variants were not universally selected across populations but were only advantageous in particular ancestral backgrounds. Contrary to previous claims, we find that selection on the FADS regions, associated with fatty acid metabolism, began before the Neolithisation of Europe. Similarly, the lactase persistence allele started increasing in frequency before the expansion of Steppe-related groups into Europe and has continued to increase up to the present. Along the genetic cline separating Mesolithic hunter-gatherers from Neolithic farmers, we find significant correlations with trait associations related to skin disorders, diet and lifestyle and mental health status, suggesting marked phenotypic differences between these groups with very different lifestyles. This work provides new insights into major transformations in recent human evolution, elucidating the complex interplay between selection and admixture that shaped patterns of genetic variation in modern populations.Competing Interest StatementThe authors have declared no competing interest.

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.

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.

In pigs litter size has increased during the last decades and number of weaned piglets is an important issue. The aim of this study was to develop a new trait of nurse capacity (NC) of crossbred sows viewed as crossbred performances in the two purebred parent lines, and estimate the genetic correlation to fertility and litter size five days after birth. An experiment recording phenotypes of crossbred sows was conducted in three large production herds with 11,247 first litter Danish Landrace x Yorkshire sows. All terminal sires used were Duroc AI boars. The experiment was running from 2010 to 2013. At farrowing, the total number born (TNB) was recorded. Five days after farrowing the litter size of the biological mother (LS5) was recorded. During the first three days after farrowing the number of piglets at each nurse sow was equalized to 14 piglets and after three weeks the NC was recorded and defined as the number of piglets nursed. Additional records on TNB and LS5 from related sows in nucleus and multiplier herds were added to obtain a data set with both purebred and crossbred information. A reduced animal model including both purebred and crossbred records was used and parameters were estimated. The results show that NC recorded on crossbred first litter sows had heritabilities of 0.05 and 0.07 for crossbred performance in the purebred populations of Landrace and Yorkshire, respectively. Estimated genetic correlations between TNB in purebreds and crossbreds show that nearly 50% of genetic gain in the purebred populations was transferred to crossbreds. Unfavorable genetic correlations between TNB in purebreds and NC in crossbreds were observed. For LS5 the genetic (co)variances show that 61% of the genetic gain in the two purebred lines was transferred to the commercial pig production of crossbred first litter sows, but no statistically significant genetic correlation to NC was obtained.

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.

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

A 30° Green Magnet based on permanent NdFeB magnets has been developed and installed in the injection line at the ASTRID2 synchrotron light source. The cost efficient design is optimized for a 1 T field at a length of 1 m using shaped iron poles to surpass the required field homogeneity. The inherent temperature dependence of NdFeB has been passively compensated to below 30 ppm/°C. A study of potential demagnetization effects has been performed by irradiation of NdFeB samples placed directly in a 100 MeV e-beam. A high permanent magnet work point was found to result in enhanced robustness, and the risk of demagnetization was found to be negligible for typical synchrotron applications. The magnet has successfully been in operation at ASTRID2 since autumn 2013., Proceedings of the 5th Int. Particle Accelerator Conf., IPAC2014, Dresden, Germany

Selection for litter size at d 5 after farrowing (LS5) was introduced in 2004 to increase the number of piglets weaned and to reduce piglet mortality in Danish Landrace and Yorkshire. The objective of this study was to investigate selection responses for LS5, total number born (TNB), and mortality [MORT, defined as (TNB - LS5)/TNB] when selection for increasing LS5 was a part of the breeding goal. Data were collected from nucleus herds recorded from 2004 to 2010, including first litters of 42,807 Landrace sows and 33,225 Yorkshire sows. The data were analyzed using a 3-trait animal model of TNB, MORT, and LS5. Significant (co) variances were estimated between the 3 traits in both populations. The heritabilities of TNB, MORT, and LS5 were 0.10, 0.09, and 0.09 in Landrace and 0.12, 0.10, and 0.10 in Yorkshire. The genetic correlations were 0.28 and 0.22 between TNB and MORT, 0.74 and 0.68 between TNB and LS5, and -0.43 and -0.57 between MORT and LS5 in Landrace and Yorkshire, respectively. The results show that the genetic improvement of LS5 was a combination of increased TNB and reduced MORT. During the observation period, the genetic improvement was 1.7 piglets per litter for LS5, 1.3 piglets per litter for TNB, and 4.7% for MORT in Landrace and 2.2 piglets per litter, 1.9 piglets per litter, and 5.9% in Yorkshire. Phenotypic improvement was 1.4 piglets per litter for LS5, 0.3 piglets per litter for TNB, and 7.9% for MORT in Landrace and 2.1 piglets per litter, 1.3 piglets per litter, and 7.6% in Yorkshire. In addition, genetic gain was evaluated in 3 phenotypic groups of TNB, representing the 25% smallest litters, the 50% medium litters, and the 25% largest litters. In all 3 groups, the genetic and phenotypic gains of TNB and LS5 increased, whereas MORT reduced in both populations.

Feed conversion ratio (FCR) is an economically important trait in pigs and feed accounts for a significant proportion of the costs involved in pig production. In this study we used a high density SNP chip panel, Porcine SNP60 BeadChip, to identify association between FCR and SNP markers and to study the genetic architecture of the trait. After quality control, a total of 30,847 SNPs that could be mapped to the 18 porcine autosomes (SSC) following the pig genome assembly 10.2, were used in the analyses. Deregressed estimated breeding value was used as the response variable. A total of 3,071 Duroc pigs had both FCR data and genotype data. The linkage disequilibrium (r2) between adjacent markers was 0.56. Two association mapping approaches were used: linear mixed model (LMM) based on single locus regression analysis and a Bayesian variable selection approach (BVS). A total of 79 significant (p < 0.0001) SNP associations on six chromosomes were identified by LMM analyses. Out of these, ten SNPs crossed the genome-wide significance threshold. These ten SNPs were all located on the chromosomes 4 and 14. In the BVS analysis, a total of 44 SNPs located on 12 chromosomes had posterior probability more than or equal to 0.05, i.e. Bayes factor ≥ 10. Thirteen SNPs were identified both by LMM and BVS. These 13 SNPs were located on four chromosomes 4, 7, 8 and 14. Hypoxia inducible factor 1, alpha subunit inhibitor (HIF1AN) and Ladybird homeobox 1 (LBX1) are two possible candidate genes affecting FCR on chromosomes 4 and 14, respectively. The study provides a list of SNPs associated with FCR and also offers valuable information on the genetic architecture and candidate genes for this trait

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

Breeding for increased litter size in Danish Landrace and Yorkshire started in 1992. Since then, litter size has in-creased significantly. Commercial pig producers and nucleus breeders argue that increases in litter size increase the number of dead piglets. Pig breeders in Denmark responded by including the total number of live piglets at day five (TN5) in the breeding goal. The objective of this study was to investigate whether breeding for TN5 has affected total number of born (TNB) and the mortality rate in five-day-old piglets. Data included records of first litter from 43,432 Landrace sows and 34,446 Yorkshire sows in Danish nucleus herds from January 2004 to December 2010. At far-rowing, litter size was recorded as TNB including number of still-births.Litter size and mortality rate up to day five after birth were analyzed using a two-trait animal model assuming normality. The heritabilities of maternal effect on litter size were 0.079 and 0.095 in Landrace and Yorkshir e. The heritabilities of maternal effect on piglet-mortality rates were 0.069 and 0.082 in Landrace and Yorkshire. The genetic correlation between litter size and mortality rate were unfavourable; and the estimates were 0.36 and 0.25 for the Landrace and Yorkshire. These findings indicate that breeding for TNB has increased the mortality rate from 1991 to 2004. However the introduction of TN5 in the breeding goal reduced mortality. The annual means of BLUP values related to piglet mortality showed that the ge-netic gain has reduced the piglet mortality rate by 4 %-points in Landrace and Yorkshire from 2004 to 2010. The genetics gain was confirmed by decreased phenotypic annual mortality rates in the breeding and multiplier herds.