The structure of the equine sector implies the need for collaborative approaches to implement genomic applications in sport horse breeding. Based on a multi-breed reference population of 5,000 horses from five breeds, a single step genomic evaluation system for linear conformation and performance traits was developed. Using two different validation approaches, forward and cross validation, medium (around 0.6) to high (over 0.9) correlations of genomic estimated breeding values (GEBVs) indicated stability of the developed system. Different relatedness between the breeds was reflected in the results, but the benefit of available genotypic data with regard to the variance of the GEBVs was found for each breed. According to the findings of this study, single-step genomic evaluation using a multi-breed reference population is a feasible approach for routine implementation of genomic selection in sport horses.

In equine parentage control, the current common practice is the use of an internationally agreed upon microsatellite (MS) marker panel. In German horse breeding the goal is to transition to a SNP-based parentage control system. To facilitate the change from one method to another, an intermediate solution is the imputation of MS markers based on SNP genotypes. The feasibility and accuracy of such an imputation has been tested with a learning dataset of horses (n=2,607) from five different breeds. Horses have been genotyped for 11 to 17 MS markers, depending on studbook policies, and have been SNP-genotyped with an Illumina BeadChip (GGP Equine 70k or GGP Equine plus). The imputation has been conducted with Beagle 5. Results indicated that an average imputation accuracy 95.69% could be achieved for the 12 MS markers that belong to the mandatory panel of the International Society for Animal Genetics (ISAG).

Numerous quantitative trait loci (QTL) have been identified for growth and feed intake in pigs, however, there are currently no reports of interactions between QTL (epistasis) for these traits at different stages of growth. A genomic scan for epistatic QTL was conducted on animals from a three generation full-sib population, created by crossing Pietrain sires with a crossbred dam line. All types of two-locus interactions were fitted in the model using Cockerham's decomposition, by regressing on a linear combination of the individual QTL origin probabilities. This study is the first to report epistatic QTL for growth, feed intake and chemical body composition in pigs. Eighteen significant epistatic QTL pairs were identified, seven affecting growth, six affecting feed intake or food conversion ratio, and five affecting chemical body composition. Most interacting QTL resided on different chromosomes; only two were located on the same chromosome. The identified QTL pairs explained substantial proportions of the phenotypic variance, from 5% to 10.3%. All types of digenic epistatic effects were identified with the additive-by-additive effect being the most prevalent. These findings suggest that epistasis is important in the genomic regulation of growth, feed intake and chemical body composition. Furthermore, interactions occur between different pairs of epistatic QTL for the same trait depending on the growth stage, increasing the complexity of genomic networks. This agrees with studies on gene expression levels which showed that those are time and tissue dependent.

The aim of this study was to analyze different mastitis data sets with different statistical models and compare results. Data recording took place on 3 commercial milk farms with an average herd size of 3,200 German Holstein cows. Recording started in February 1998 and was completed in December 2005. During this period, 63,540 treatments for clinical mastitis were recorded. Five different data sets were analyzed and the number of cows varied between 12,972 and 13,618, depending on the data set. Data collection periods contained either the first 50 or the first 300 d of lactation. When the data-recording period ended after 50 d of lactation, data sets were analyzed with a lactation threshold model (LTM), a multiple threshold lactation model (MTLM), and a test-day threshold model (TDTM). In the LTM analysis, mastitis was treated as a binary trait coded as 0 (no mastitis) or 1 (mastitis), whereas in MTLM mastitis, codes were between 0 and 4, depending on the number of estimated days with mastitis. The TDTM treated each day as a single observation coded similarly to that of the LTM. When the data collection period included the first 300 d of lactation, data sets were analyzed with the LTM or MTLM only, because the TDTM was computationally infeasible. Mastitis frequencies in LTM data sets were 25.8 and 39.2%, and 26.9 and 39.2% in MTLM data sets, when data recording ended after 50 and 300 d of lactation, respectively. The mastitis frequency in the TDTM data set was 5.2%. Respective heritability estimates of liability to clinical mastitis were 0.08 and 0.09 using the LTM, and 0.08 and 0.11 using the MTLM. When the TDTM was used, the estimated heritability was 0.15. Rank correlation between breeding values of the different data sets ranged between 0.40 and 0.97. Rank correlation between the LTM and MTLM were higher (0.78 to 0.97) than those between these 2 models and the TDTM (0.40 to 0.59).The MTLM combined the positive effects of both the LTM, with respect to the size of the data sets, and the TDTM, with respect to the lack of information.

Antimicrobial peptides are key molecules in local host defense. With the aim to better understand the possible involvement of these peptides in the prevention of bovine mastitis, we determined, for the first time to our knowledge, the spatial pattern of constitutive expression of 5 bovine beta-defensins and bovine psoriasin (S100A7) across 5 localizations of the bovine mammary gland applying a quantitative real-time PCR approach. We observed 3 different expression patterns in the healthy udder: 1) constitutive expression of the lingual and tracheal antimicrobial peptides (LAP and TAP), as well that of bovine neutrophil beta-defensins 4 and 10 (BNBD4 and BNBD10), is essentially restricted to the mammary lymph node; 2) bovine beta-defensin 1 (DEFB1) is mainly expressed in the cisternal epithelium and the Rosette of Fürstenberg; 3) strong constitutive mRNA expression of the calcium-binding protein S100A7, which is also known as psoriasin and which has been reported to be highly active against Escherichia coli, was detected in the streak canal. These results indicate a crucial role of S100A7 in the early-stage prevention of coliform mastitis, and the analyzed beta-defensins might be regarded as inducible weapons against already invading pathogens.

The aim of this study was to quantify the possible contribution of gestation length as an information trait for breeding value estimation of dystocia and stillbirth rate in Holstein cattle.Data comprised the information of calving ease, stillbirth and gestation length of 14,095 calvings. Additionally birth weight was available for 12,968 calves. Only single births with a normal gestation length (265 to 295 days) were considered. Variance components and subsequently breeding values were estimated by REML with a multivariate linear animal model.The inclusion of gestation length resulted in 0 to 10 percent higher reliabilities of breeding values for dystocia and stillbirth rate depending on breeding trait and size of half sib groups. The alternative consideration of birth weight led to reliabilities which are relatively improved by 8 to 36 percent.

The present study focused on the identification of epistatic QTL pairs for body composition traits (carcass cut, lean tissue, and fat tissue weights) measured at slaughter weight (140 kg of BW) in a 3-generation full-sib population developed by crossing Pietrain sires with a crossbred dam line. Depending on the trait, phenotypic observations were available for 306 to 315 F(2) animals. For the QTL analysis, 386 animals were genotyped for 88 molecular markers covering chromosomes SSC1, SSC2, SSC4, SSC6, SSC7, SSC8, SSC9, SSC10, SSC13, and SSC14. In total, 23 significant epistatic QTL pairs were identified, with the additive x additive genetic interaction being the most prevalent. Epistatic QTL were identified across all chromosomes except for SSC13, and epistatic QTL pairs accounted for between 5.8 and 10.2% of the phenotypic variance. Seven epistatic QTL pairs were between QTL that resided on the same chromosome, and 16 were between QTL that resided on different chromosomes. Sus scrofa chromosome 1, SSC2, SSC4, SSC6, SSC8, and SSC9 harbored the greatest number of epistatic QTL. The epistatic QTL pair with the greatest effect was for the entire loin weight between 2 locations on SSC7, explaining 10.2% of the phenotypic variance. Epistatic associations were identified between regions of the genome that contain the IGF-2 or melanocortin-4 receptor genes, with QTL residing in other genomic locations. Quantitative trait loci in the region of the melanocortin-4 receptor gene and on SSC7 showed significant positive dominance effects for entire belly weight, which were offset by negative dominance x dominance interactions between these QTL. In contrast, the QTL in the region of the IGF-2 gene showed significant negative dominance effects for entire ham weight, which were largely overcompensated for by positive additive x dominance genetic effects with a QTL on SSC9. The study shows that epistasis is of great importance for the genomic regulation of body composition in pigs and contributes substantially to the variation in complex traits.

Most quantitative trait loci (QTL) studies have focussed on the identification of individual QTL effects (additive, dominance and imprinting) in the absence of interactions (epistasis). There are numerous reports in the literature for QTL associated with growth and body composition of pigs, however much less effort has focussed around the identification of epistatic QTL for these traits. Growth and body composition of pigs are probably influenced by numerous QTL located throughout the genome as well as interactions between QTL. Therefore the objective of this study was to investigate the contribution of epistasis to the genomic regulation of growth and body composition of pigs.

OC was diagnosed in the fetlock 24%, in the hock 7% and in the stifle 12% of all animals. The number of OC positive radiographic findings decreased from the first to the second period about 13%. The fixed effect breeding farm influences significantly OCD in total and OC/OCD in the fetlock as well as in the stifle, whereas traumata were influenced highly significant. The heritabilities for the traits OC/OCD were estimated on a low until middle level and should be seen as a tendency. A significant positive correlation between height at withers and the trait trauma was shown in the first period, whereas in the second period a significant influence of the bodyweight and the height at withers on positive OC/OCD findings in the stifle was detected. The results show that to reduce the frequency of the radiographic findings basically the environment has to be improved. Recommendable is also a critically view towards the analysed traits, for example the height at withers in connection with the radiographic traits, because the constitution of health doesn't follow the still increasing potential of performance.

Data from 32 nucleus and multiplier herds in Germany was used to estimate variance components and breeding values for five maternal behaviour traits in sows. The estimation was performed univariately using an animal threshold model. About 31,000 farrowings recorded from December 2003 until July 2005 were included. The heritability coefficients were 0.07 (0.06) for group behaviour, 0.06 (0.03) for attitude to people, 0.05 (0.01) for maternal ability, 0.03 (0.01) for crushing of piglets and 0.02 (0.02) for savaging of piglets. Additionally, genetic correlations between the behaviour traits and between the behaviour traits and litter size, respectively, were estimated multivariately by REML with a linear model. Low heritability and weak genetic correlation to litter size at birth indicate that it may be difficult to genetically improve the maternal behaviour, and that selection for better mothering ability is not necessarily accompanied by reduced litter size at birth.

At the dairy research farm Karkendamm, the individual roughage intake was measured since 1 September 2005 using a computerised scale system to estimate daily energy balances as the difference between energy intake and calculated energy requirements for lactation and maintenance. Data of 289 heifers with observations between the 11th and 180th day of lactation over a period of 487 days were analysed. Average energy-corrected milk yield, feed intake, live weight and energy balance were 31.8kg, 20.6kg, 584 kg and 13.6 MJ NEL (net energy lactation), respectively, per day. Fixed and random regression models were used to estimate repeatabilities, correlations between cow effects and genetic parameters. The resulting genetic correlations in different lactation stages demonstrate that feed intake and energy balance at the beginning and the middle of lactation are genetically different traits. Heritability of feed intake is low with h2=0.06 during the first days after parturition and increases in the middle of lactation, whereas the energy balance shows the highest heritability with h2=0.34 in the first 30 days of lactation. Genetic correlations between energy balance and feed intake and milk yield, respectively, illustrate that energy balance depends more on feed intake than on milk yield. Genetic correlation between body condition score and energy balance decreases rapidly within the first 100 days of lactation. Hence, to avoid negative effects on health and reproduction as consequences of strong energy deficits at the beginning of lactation, the energy balance itself should be measured and used as a selection criterion in this lactation stage. Since the number of animals is rather small for a genetic analysis, the genetic parameters have to be evaluated on a more comprehensive dataset.

In this study, quantitative trait loci (QTL) for chemical and physical body composition, growth and feed intake in pigs were identified in a three-generation full-sib population, developed by crossing Pietrain sires with a commercial dam line. Phenotypic data from 315 F(2) animals were available for protein and lipid deposition measured in live animals by the deuterium dilution technique at 30-, 60-, 90-, 120- and 140-kg body weight. At 140-kg body weight, carcass characteristics were measured by the AutoFOM grading system and after dissection. Three hundred and eighty-six animals from 49 families were genotyped for 51 molecular markers covering chromosomes SSC2, SSC4, SSC8, SSC9, SSC10 and SSC14. Novel QTL for protein (lipid) content at 60-kg body weight and protein (lipid) accretion from 120 to 140 kg were detected on SSC9 near several previously detected QTL for lean and fat tissue in neck, shoulder and ham cuts. Another QTL for lipid accretion was found on SSC8, closely associated with a QTL for intramuscular fat content. QTL for daily feed intake were detected on SSC2 and SSC10. The favourable allele of a QTL for food conversion ratio (FCR) on SSC2 was associated with alleles for increased lean tissue and decreased fat tissue. Because no QTL for growth rate were found in the region, the QTL for FCR is most likely due to a change in body composition. These QTL provide insights into the genomic regulation of chemical or physical body composition and its association with feed intake, feed efficiency and growth.

One aspect of the study was the monitoring of growth development of 297 young stallions (Holstein Warmblood) sired by 76 stallions. In addition the influence of the environment and genetics were estimated. Standards of growth of Warmblood horses aged between six and 24 months using polynom and spline approximations were developed. Growth of body weight and height at withers was almost linear within the first year of life and decreased almost continuously afterwards. The fixed effects breeding farm, month of measurement and age compared to the season of birth had a highly significant influence on all four growth traits. Increasing heritabilities for bodyweight (h(2)=0.07-0.12) and height at withers (h(2)=0.19-0.26) with growing age, showed a higher dependency of bodyweight development by environmental influences. In practise therefore monthly monitoring of growth makes an important contribution to optimize rearing of young horses. Significant deviations from the estimated growth curves make corrections of the rearing conditions reasonable. Regularly weighing and measuring of the height of withers are objective evaluation criterias and together with the judgement of the feeding condition of the growing horses using the body condition scoring they are able to improve the rearing conditions significant. An individual feeding and exercise management balanced on that therefore allow a healthy and optimal growth development.

Genetic comparisons of homozygous negative (NN) and heterozygous negative (Nn) Pietrain boars in relation to the six economically important traits daily gain, loin eye area, ham proportion, lean meat content, pH, loin and meat colour were made to describe effects on this traits in the case of eradicating the n-allele. Data of 11,422 female pigs tested in two test stations of Lower Saxony in the years 2000 to 2007 were analysed. Pietrain purebred and crossbred progenies were kept in two-pig pens, and crossbred progenies were also kept in groups of ten pigs. The crossbred progenies originated from hybrid sows (German Landrace * German Large White). For statistical analysis three animal groups were defined: purebreds in two-pig pens, crossbreds in two-pig pens, and crossbreds in groups with ten pigs. Variance components were estimated simultaneously for all three animal groups with an animal model by REML. Statistical models considered the fixed effects month at the beginning of the fattening period within station (fattening), day of slaughtering within station (carcass and meat quality), regression on carcass weight and the random effects of test group and animal. Adjacent a breeding value estimation was conducted by using the same models and the estimated variance components. Between purebreds and crossbreds kept in two-pig pens the genetic correlations ranged from r(g)=0.67 to r(g)=0.99. Between purebreds and crossbreds kept in groups with ten pigs the genetic correlations resulted in r(g)=0.56 to r(g)=0.77, and finally, between the two crossbred groups the genetic correlations are r(g)=0.70 to r(g)=0.99. Thus, genotype x environment interactions resulting in rank displacements are possible between purebreds and crossbreds kept in two-pig pens for the traits daily gain and pH(1) loin and between purebreds and crossbreds kept in groups with ten pigs for all traits. Actually only few progeny tested boars have the genotype nn, but more than 50 of the boars are heterozygous gene carriers (Nn). Mean breeding values were calculated with respect to year of birth, MHS genotype, and animal group. in daily gain and in the two traits of meat quality homozygous negative sires (NN) have a genetic superiority compared to the heterozygous negative sires (Nn). In contrast the gene carriers (Nn) have somewhat higher breeding values in the three carcass traits, but over the years the differences between the two genotypes decreased clearly. Assuming that this trend will be continued an eradication of the n-allele will result in increasing daily gains and decreasing meat quality deficiencies combined with similar lean meat contents.

Variance components and breeding values were estimated for 3 reproductive traits in a pure line of White Leghorn laying hens. The traits were proportion of fertile eggs of eggs set, proportion of first quality chicks of eggs set, and proportion of first-quality chicks of fertile eggs. A total of 3,020 hens were tested up to 3 times over a period of 7 d. For the definition of the traits, each egg was scored for each trait either as 0 or 1. To account for the binomial distribution of the data, a Bayesian animal threshold model implemented in a Gibbs sampler was applied that considered the record of each egg set as a repeated observation of the hen. The estimated heritability was 0.067, 0.126, and 0.136 for the traits proportion of fertile eggs of eggs set, proportion of first quality chicks of eggs set, and proportion of first-quality chicks of fertile eggs, respectively, and the SE were small. It was shown that the heritability estimates were substantially higher from their expected values based on linear models. This results in a higher genetic progress and consequently favors the applied Bayesian threshold model for a genetic evaluation of binomial distributed reproductive traits.

Quantitative trait loci (QTL) associated with physical and chemical body composition of the pig are of substantial economic interest. Previous studies have reported QTL for physical body composition such as lean and fat tissue traits (Roehe et al., 2003). In contrast, QTL associated with chemical body composition and for the change in deposition of such components during growth have only been reported in one previous study (Mohrmann et al., 2006). Knowledge of the genomic regulation of body composition during growth is important to accurately estimate nutritional requirements, optimise the entire production system, characterise the population of interest, and to optimise food intake capacity by breeding.

Economic values for meat quality traits for breeding purposes are often calculated assuming normal distribution of the trait. Phenotypic data on drip loss measurements regarding case-ready meat (CRM) and premium cuts (PC) from a field trial of 374 commercially slaughtered pigs revealed lognormal distribution rather than normal distribution for this population. Three different approaches of calculating the economic values (assuming normal distribution, lognormal distribution and shifted lognormal distribution) were compared considering in a first scenario four quality classes and in a second scenario linear weight loss. Differences among the approaches of calculation of economic values were found in magnitude and position of the maximum absolute economic value. The highest absolute economic values for case-ready meat drip loss of the ham regarding four quality classes were obtained at population means of 4.20, 4.48 and 4.80% with − 0.67, − 0.80 and − 0.85 EUR per unit drip loss using approaches assuming normal distribution, lognormal distribution and shifted lognormal distribution, respectively. Economic values calculated under the assumption of linear weight loss resulted in a large range of similar economic values for all three methods. Besides the type of distribution, the relation between standard deviation and width of the meat quality classes and the position of the meat quality classes were found to be main factors influencing the economic value functions. For the present data, the better fit of lognormal distribution to the data and the differences in highest absolute economic values favoured the approach accounting for appropriate distribution in particular when only few meat quality classes are used.

Serial measurements of three milkability traits from two commercial dairy farms in Germany were used to estimate heritabilities and breeding values (BVs). Overall, 6352 cows in first, second and third lactations supplied 2 188 810 records based on daily values recorded from 1998 to 2003. Only the records between day 8 and day 305 after calving were considered. The estimated genetic correlations between different parities within the three milkability traits ranged from rg = 0.88 to 0.98, i.e. they were sufficiently high to warrant a repeatability model. The resulting estimated heritability coefficients were h2 = 0.42 for average milk flow, h2 = 0.56 for maximum milk flow and h2 = 0.38 for milking time. We analysed the genetic correlation between milkability and somatic cell score (SCS) and between milkability and the liability to mastitis, respectively, as the optimum milk flow for udder health is not well defined. There were 66 146 records with information on somatic cell count. Furthermore, 23 488 days of medical treatment for udder diseases were available, resulting in 2 600 302 days of observation in total. Heritabilities for the liability to mastitis, estimated with a test-day threshold model, were h2 = 0.19 and h2 = 0.13, depending on the data-recording period (first 50 days of lactation and first 305 days of lactation, respectively). With respect to the relationship between milkability and udder health, the results indicated a slight and linear correlation insofar as one can assume: the higher the milk flow, the worse the udder health. For this reason, bulls and cows with high BVs for milk flow should be excluded from breeding to avoid a deterioration of udder health. The establishment of a special data-recording scheme for functional traits such as milkability and mastitis on commercial dairy farms may be possible according to these results.

Genetic correlations between genotypes and housing systems for seventeen traits of the complexes fattening, carcass and meat quality were estimated in order to show possible genotype x environment interactions and the degree of accordance between purebred and crossbred performance. Data of 8945 female pigs tested in two test stations of Lower Saxony in the years 2000 to 2005 were analysed. Pietrain purebred and crossbred progenies were kept in two-pig pens, and crossbred progenies were also kept in groups with ten pigs. The crossbred progenies originated from hybrid sows (German Landrace * German Large White). For statistical analysis three animal groups were defined: purebreds in twopig pens, crossbreds in two-pig pens, and crossbreds in groups with ten pigs. Variance components were estimated simultaneously for all three animal groups with an animal model by REML. Statistical models considered the fixed effects month at the beginning of the fattening period within station (fattening), day of slaughtering within station (carcass and meat quality), regression on carcass weight and the random effects of test group and animal. Between the crossbreds of the two housing systems the averaged genetic correlation for all traits is r(g)=0,87 (0,51 to 0,99). The mean correlation between purebreds and crossbreds kept in two-pig pens resulted in r(g)=0,72 (0,17 to 0,99). Finally, between purebreds and crossbreds kept in groups with ten pigs the mean correlation is r(g)=0,63 (0,02 to 0,99). For fattening and carcass traits the estimated correlations are higher than for meat quality traits. Considering the important traits daily gain, meat content and pH(1)-value cutlet the results do not indicate the existence of genotype x environment interactions between crossbreds in the two different housing systems. Also a wide accordance can be stated between purebreds and crossbreds kept in two-pig pens. The correlations for the combination purebred and crossbred in groups with ten pigs show a good accordance with the exception that the group size influences the daily gain (r(g) = 0,65). So, for this trait moderate differences in the ranking of the purebred boars can be expected.

Phenotypic information on 1155 market pigs for several pig meat quality traits, was collected. Genotypes on 12 DNA markers, including RYR1 and PRKAG3 I199V, were also obtained on all pigs to investigate the relationship between genetic markers and meat quality. The RYR1 gene had the highest impact on meat quality, however, several other markers showed significant effects on one or more traits. Animals heterozygous at the RYR1 locus were significantly inferior in almost all meat quality traits, except ultimate pH value, initial conductivity and redness of the meat. Drip loss from case-ready meat (measured from 1 to 7 days post-mortem) was 43% higher for heterozygotes than animals of the stress resistant genotype. The homozygous genotype II at position I199V of the PRKAG3 locus also resulted in less drip loss than genotypes IV and VV, regardless of the method and time of measurement. Furthermore, the favourable genotype related to higher ultimate pH and darker meat. Both loci significantly affected the intercept, linear and quadratic terms of fitted drip loss development curves. The favourable genotypes showed a lower drip loss after one day of measurement and a slower increase and a more linear development over time. Whilst the RYR1 and PRKAG3 markers influenced numerous meat quality traits, some of the other markers were also found to have significant effects on one or two meat quality traits. Markers at MC4R and HMGA1 loci significantly affected drip loss, whereas LDHA, CAST (Hpy188I) and ATP2A1 influenced pH value. In addition, the marker ATP2A1 was associated with variation in intramuscular fat content in M. longissimus dorsi. GLUT4 affected temperature 45min post-mortem and several markers (MC4R, LDHA, GLUT4, HMGA1, CAST (Hpy188I and PvuII)) influenced one or two of the different colour measurements. The markers at MC4R, CKM, AGRP, PRKAG3, and HMGA1 loci were tested for their interactions with RYR1 regarding drip loss. Only AGRP showed a significant interaction, but this was based on only a few animals with the homozygous genotype for one allele. Our results suggest that genetic markers provide a useful tool to improve meat quality in pigs independently from RYR1, especially the mutation I199V in the PRKAG3 gene.