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Milk fatty acids (FA) have been suggested as biomarkers for early-lactation metabolic diseases and for female fertility status. The aim of the present study was to infer associations between FA, the metabolic disorder ketosis (KET), and the interval from calving to first insemination (ICF) genetically and genomically. In this regard, we focused on a single-step genomic BLUP approach, allowing consideration of genotyped and ungenotyped cows simultaneously. The phenotypic data set considered 38,375 first-lactation Holstein cows, kept in 45 large-scale co-operator herds from 2 federal states in Germany. The calving years for these cows were from 2014 to 2017. Concentrations in milk from the first official milk recording test-day for saturated, unsaturated (UFA), monounsaturated (MUFA), polyunsaturated, palmitic, and stearic (C18:0) FA were determined via Fourier-transform infrared spectroscopy. Ketosis was defined as a binary trait according to a veterinarian diagnosis key, considering diagnoses within a 6-wk interval after calving. A subset of 9,786 cows was genotyped for 40,989 SNP markers. Variance components and heritabilities for all Gaussian distributed FA and for ICF, and for binary KET were estimated by applying single-step genomic BLUP single-trait linear and threshold models, respectively. Genetic correlations were estimated in series of bivariate runs. Genomic breeding values for the single-step genomic BLUP estimations were dependent traits in single-step GWAS. Heritabilities for FA were moderate in the range from 0.09 to 0.20 (standard error = 0.02-0.03), but quite small for ICF (0.08, standard error = 0.01) and for KET (0.05 on the underlying liability scale, posterior standard deviation = 0.02). Genetic correlations between KET and UFA, MUFA, and C18:0 were large (0.74 to 0.85, posterior standard deviation = 0.14-0.19), and low positive between KET and ICF (0.17, posterior standard deviation = 0.22). Genetic correlations between UFA, MUFA, and C18:0 with ICF ranged from 0.34 to 0.46 (standard error = 0.12). In single-step GWAS, we identified a large proportion of overlapping genomic regions for the different FA, especially for UFA and MUFA, and for saturated and palmitic FA. One identical significantly associated SNP was identified for C18:0 and KET on BTA 15. However, there was no genomic segment simultaneously significantly affecting all trait categories ICF, FA, and KET. Nevertheless, some of the annotated potential candidate genes DGKA, IGFBP4, and CXCL8 play a role in lipid metabolism and fertility mechanisms, and influence production diseases in early lactation. Genetic and genomic associations indicate that Fourier-transform infrared spectroscopy FA concentrations in milk from the first official test-day are valuable predictors for KET and for ICF.

Energy demand for milk production in early lactation exceeds energy intake, especially in high-yielding Holstein cows. Energy deficiency causes increasing susceptibility to metabolic disorders. In addition to several blood parameters, the fat-to-protein ratio (FPR) is suggested as an indicator for ketosis, because a FPR >1.5 refers to high lipolysis. The aim of this study was to analyze phenotypic, quantitative genetic, and genomic associations between FPR and ketosis. In this regard, 8,912 first-lactation Holstein cows were phenotyped for ketosis according to a veterinarian diagnosis key. Ketosis was diagnosed if the cow showed an abnormal carbohydrate metabolism with increased content of ketone bodies in the blood or urine. At least one entry for ketosis in the first 6 wk after calving implied a score = 1 (diseased); otherwise, a score = 0 (healthy) was assigned. The FPR from the first test-day was defined as a Gaussian distributed trait (FPRgauss), and also as a binary response trait (FPRbin), considering a threshold of FPR = 1.5. After imputation and quality controls, 45,613 SNP markers from the 8,912 genotyped cows were used for genomic studies. Phenotypically, an increasing ketosis incidence was associated with significantly higher FPR, and vice versa. Hence, from a practical trait recording perspective, first test-day FPR is suggested as an indicator for ketosis. The ketosis heritability was slightly larger when modeling the pedigree-based relationship matrix (pedigree-based: 0.17; SNP-based: 0.11). For FPRbin, heritabilities were larger when modeling the genomic relationship matrix (pedigree-based: 0.09; SNP-based: 0.15). For FPRgauss, heritabilities were almost identical for both pedigree and genomic relationship matrices (pedigree-based: 0.14; SNP-based: 0.15). Genetic correlations between ketosis with FPRbin and FPRgauss using either pedigree- or genomic-based relationship matrices were in a moderate range from 0.39 to 0.71. Applying genome-wide association studies, we identified the specific SNP rs109896020 (BTA 5, position: 115,456,438 bp) significantly contributing to ketosis. The identified potential candidate gene PARVB in close chromosomal distance is associated with nonalcoholic fatty liver disease in humans. The most important SNP contributing to FPRbin was located within the DGAT1 gene. Different SNP significantly contributed to ketosis and FPRbin, indicating different mechanisms for both traits genomically.

To measure methane (CH4) emissions from cattle on-farm, a number of methods have been developed. Combining measurements made with different methods in one data set could lead to an increased power of further analyses. Before combining the measurements, their agreement must be evaluated. We analysed data obtained with a handheld laser methane detector (LMD) and the GreenFeed system (GF), as well as data obtained with LMD and Fourier Transformed Infrared (FTIR) and Non-dispersive Infrared (NDIR) breath analysers (sniffers) installed in the feed bin of automatic milking systems. These devices record short-term breath CH4 concentrations from cows and make it possible to estimate daily CH4 production in g/d which is used for national CH4 emission inventories and genetic studies. The CH4 is released by cows during eructation and breathing events, resulting in peaks of CH4 concentrations during a measurement which represent the respiratory cycle. For LMD, the average CH4 concentration of all peaks during the measurement (P_MEAN in ppm × meter) was compared with the average daily CH4 production (g/d) measured by GF on 11 cows. The comparison showed a low concordance correlation coefficient (CCC; 0.02) and coefficient of individual agreement (CIA; 0.06) between the methods. The repeated measures correlation (rp) of LMD and GF, which can be seen as a proxy for the genetic correlation, was, however, relatively strong (0.66). Next, based on GF, a prediction equation for estimating CH4 in g/d (LMD_cal) using LMD measurements was developed. LMD_cal showed an improved agreement with GF (CCC = 0.22, CIA = 0.99, rp = 0.74). This prediction equation was used to compare repeated LMD measurements (LMD_val in g/d) with CH4 (g/d) measured with FTIR (n = 34 cows; Data Set A) or NDIR (n = 39 cows; Data Set B) sniffer. A low CCC (A: 0.28; B: 0.17), high CIA (A: 0.91; B: 0.87) and strong rp (A: 0.57; B: 0.60) indicated that there was some agreement and a minimal re-ranking of the cows between sniffer and LMD. Possible sources of disagreement were cow activity (LMD: standing idle; sniffer: eating and being milked) and the larger influence of wind speed on LMD measurement. The LMD measurement was less repeatable (0.14–0.27) than the other techniques studied (0.47–0.77). Nevertheless, GF, LMD and the sniffers ranked the cows similarly. The LMD, due to its portability and flexibility, could be used to study CH4 emissions on herd or group level, as a validation tool, or to strengthen estimates of genetic relationships between small-scale research populations.

In this study, the handheld laser methane detector (LMD) was discussed as a tool for estimating the methane emissions of individual dairy cows by measuring the profiles of the exhaled air. Data obtained with the most recent generation of the device were compared with those of indirect open-circuit respiration chambers, which are commonly used to quantify methane emissions from ruminants. Data from two LaserMethane Mini-Green LMD units (Tokyo Gas Engineering Solutions) exhibited high agreement with those from four respiration chambers, two at the AgroVet-Strickhof, Eschikon, Lindau (Switzerland) and two at the Leibniz Institute for Farm Animal Biology (FBN) Dummerstorf (Germany). The results were determined using Pearson and concordance correlations and the Bland–Altman method. An inverse regression analysis was used to predict the amount of methane in the chambers from the LMD data. The two LMD units also agreed well with each other in the same respiration chamber and under farm conditions. Both the LMDs and chambers were suitable for detecting differences in mean methane concentrations in the spent air produced by dairy cows during different cow activities in the chamber (p

In this review, the history of breeding for polled cattle is compiled from literature as well as graphic representations of cattle in art and science. Domesticated taurine cattle originated around 8500 years BCE in the Near East and spread from there to Africa as well as to Europe. Earliest findings of polled domesticated cattle are from today’s Slovakia and Germany from 6000 years BCE. Textual findings and especially graphic displays can be found of polled cattle in Ancient Egypt. Although archaeological finds of skulls that can be evaluated for natural polledness are rare, archaeological texts and graphical displays indicate that genetically polled cattle in Ancient Egypt were present and quite numerous. Polled cattle apparently were also kept by Germanic tribes and can be followed through medieval times into the 17th and 18th century where textual accounts are more frequent. In Scandinavian countries and Great Britain polled cattle have survived in greater proportions up to today while in the middle of Europe polled cattle were not well regarded by farmers and almost became extinct. Among the British breeds, Angus and Galloway were established as beef cattle breeds in the 17th/18th century, and still flourish. However, the British polled dairy breed Suffolk became extinct. It was one of the ancestral breeds of the Red Polled beef breed and was used in attempts to promote polled dairy cattle in France in the 19th century. Reports of single individuals in polled cattle found in predominantly horned populations possibly indicate several origins of the polled mutations. Recently, at least two different types of mutations, located on BTA01, have been found to be responsible for the mutation commonly referred to as the polled allele. One is the so-called ‘Celtic’ type, found in Scandinavia and Britain while the’‘Friesian’ type is found in cattle of the Holstein family. Today, aspects of animal welfare more and more influence farmers’ attitudes towards naturally polled cattle and also governmental policies play an important role. For the important horned dairy breeds of central Europe, e.g. Holstein, Brown Swiss and Fleckvieh, as well as for the beef breed Charolais, breeding programs for the introgression of the polled allele are starting and will be aided by new tools such as genomic selection.

The objective of the present study was to compare genetic gain and inbreeding coefficients of dairy cattle in organic breeding program designs by applying stochastic simulations. Evaluated breeding strategies were: (i) selecting bulls from conventional breeding programs, and taking into account genotype by environment (G×E) interactions, (ii) selecting genotyped bulls within the organic environment for artificial insemination (AI) programs and (iii) selecting genotyped natural service bulls within organic herds. The simulated conventional population comprised 148 800 cows from 2976 herds with an average herd size of 50 cows per herd, and 1200 cows were assigned to 60 organic herds. In a young bull program, selection criteria of young bulls in both production systems (conventional and organic) were either 'conventional' estimated breeding values (EBV) or genomic estimated breeding values (GEBV) for two traits with low (h 2=0.05) and moderate heritability (h 2=0.30). GEBV were calculated for different accuracies (r mg), and G×E interactions were considered by modifying originally simulated true breeding values in the range from r g=0.5 to 1.0. For both traits (h 2=0.05 and 0.30) and r mg⩾0.8, genomic selection of bulls directly in the organic population and using selected bulls via AI revealed higher genetic gain than selecting young bulls in the larger conventional population based on EBV; also without the existence of G×E interactions. Only for pronounced G×E interactions (r g=0.5), and for highly accurate GEBV for natural service bulls (r mg>0.9), results suggests the use of genotyped organic natural service bulls instead of implementing an AI program. Inbreeding coefficients of selected bulls and their offspring were generally lower when basing selection decisions for young bulls on GEBV compared with selection strategies based on pedigree indices. peerReviewed

Feet and leg problems have a major effect on the well-being and lifespan of the dairy cow and thus are economically important to the dairy farmer. Apart from approaches using genetic selection for classical traits from conformation scoring, attempts for genetic improvement can be based either on records of individual disease cases or on records of disorder status at time of hoof trimming. In this study, 1,962 first-lactation cows were subjected to hoof trimming with an assessment of disorder status for sole hemorrhage as a binary trait. Cows were from 7 large commercial herds in Mecklenburg-Western Pomerania (northeastern Germany) that had similar housing with cubicles, slatted flooring, little use of straw for bedding, and total mixed ration feeding. Cows were trimmed and assessed once, focusing on cows in the first half of the lactation. Herds were visited at intervals to enable recording of cohorts at a similar stage of lactation. Each cohort or herd-visit included between 31 and 165 cows. Additional measurements included body weight, back fat thickness, and body condition at time of trimming. Further data on dairy production, conformation scores, and reproductive performance were merged after collection of records had finished. The DNA extracted from blood of 1,183 cows was used for analysis with a custom-made array of 384 single nucleotide polymorphisms (SNP). The SNP were selected according to results from the literature for effects in classical conformation traits, from biochemical pathway analysis, and from comparative analysis of putative candidate genes in cattle, pigs, and sheep. Selection of cohorts of cows for SNP chip analysis was such that cohorts with extreme frequencies of disorders and cohorts with slightly deviating housing systems were excluded in this first step. The results from a mixed threshold model analysis with genotype included as a fixed effect and accounting for relationships among animals revealed that the intronic SNP rs29017173 (A/G) within the IQ motif-containing GTPase-activating protein 1 (IQGAP1, Bos taurus autosome 21) was significantly associated with disorder status. Back-transformed means of disorder status for the 3 genotypes were 0.37 (AA), 0.52 (AG), and 0.56 (GG). Using the full data set of 1,962 cows, including the less-suitable cohorts, gave back-transformed means of 0.51 (AA), 0.58 (AG), and 0.62 (GG). As SNP rs29017173 is included on the Illumina BovineSNP50 DNA Analysis BeadChip (Illumina Inc., San Diego, CA), a sample of 2,394 artificial insemination sires from the German calibration sample for genomic selection from birth years 1998 to 2003 was studied for possible correlated effects. The A/G polymorphism of SNP rs29017173 studied here was also associated with substantial effects for feet and leg traits from the classical conformation score system. Selection using this polymorphism will be facilitated by the fact that the same allele is favored for all traits with substantial effects.

Udder diseases are a major problem in dairy cattle herds. Apart from the improvement of hygiene and food quality, udder health can be improved by genetic selection. This study used disease treatment data of 29,698 Holstein cows from 21 German contract testing herds to evaluate different trait definitions with respect to variance components, breeding values, and genetic correlations to somatic cell score (SCS) and milk yield. Considering the first 305 days of a lactation, four traits were defined: a binary trait, the number of udder health treatments (TRS), the number of sickness periods (NUMS) and the days a cow was considered to be sick. Additionally the number of treatments and the number of sickness periods defined from the treatments were analyzed based on a model with an underlying Poisson distribution. Results from analyses with single and multiple trait sire and animal models showed low heritabilities, ranging from 0.05 to 0.13. The genetic correlation of 305 day average somatic cell score with all disease treatment traits defined in this study was high but differed clearly from one. Genetic correlations with 305 day milk yield were unfavorable and remarkably higher than genetic correlations of SCS with milk yield. Reliabilities of estimated breeding values (EBV) were the highest for NUMS. Spearman correlations of EBV for binary and linear trait definitions differed considerably from unity. Correlations of EBV between the disease treatment traits defined in this study and SCS were similar to genetic correlations. An exception was found for the correlation between EBV of TRS and SCS (0.46) which was remarkably lower than the corresponding genetic correlation. In summary, this study demonstrates the differences between various disease treatment traits as well as the benefits of using a more precise trait definition instead of the binary option. Despite the lower heritabilities, the discrepancy between the correlations of disease treatment traits and SCS to milk yield showed the necessity to include disease treatment traits, i.e. case data on mastitis, into breeding objectives and selection indices.

A designed field study was conducted on 1,962 first-lactation Holstein cows kept on 7 large-scale dairy farms in Germany, in loose-housing systems on standard slatted flooring. Records of hoof disorders at trimming composed of subclinical as well as clinical cases were combined with body measurements and body condition scores, test-day records, and further individual cow data. The 6 most frequent disorders were laminitis, also known as sole hemorrhage (57.3% of all cows), dermatitis digitalis (17.0%), dermatitis interdigitalis (7.9%), white line disease (12.6%), sole ulcer (7.1%), and interdigital hyperplasia (5.5%). The most important environmental effects were herd-visit date and stage of lactation. Heifers between 50 and 99 d in milk had the highest frequencies for laminitis. Lighter cows were less susceptible to laminitis and white line disease, but had a higher prevalence of interdigital hyperplasia. Relationships between stature and white line disease as well as relationships between body condition score and dermatitis digitalis were nonlinear, resulting in an improved disorder status of cows with an intermediate condition score and average stature. Increased biomechanical stress caused by different factors (weight, social rank, standing time) is a presumed effect that leads to an increased susceptibility for hoof diseases. From a management perspective, under- and overconditioning should be avoided. Milk production traits differed between cows with and without laminitis-related claw horn lesions. Fat percentage and fat-to-protein ratio in the first month before trimming were significantly decreased for cows with a positive laminitis status. Hence, this finding points to metabolic disorders being associated with a higher risk for hoof diseases. Estimates of heritabilities for laminitis, dermatitis digitalis, dermatitis interdigitalis, white line disease, and sole ulcer were 0.09, 0.14, 0.10, 0.11, and 0.06 when applying a threshold model with a probit link function.

The objectives of this study were (1) to analyze the agreement of a standard laboratory ELISA for progesterone (P4) with an automated on-farm ELISA kit operated under commercial conditions in 1,297 milk samples from 50 dairy cows; (2) to study the influence of the method of detection of luteal activity on genetic parameters of fertility traits based on P4 measured with an automated on-farm ELISA once weekly from wk 3 to 9 postpartum in the milk of 1,304 cows; and (3) to study the influence of sampling frequency (once or twice weekly from wk 3 to 9) on the same traits from 296 cows. Luteal activity can be detected when there is an active corpus luteum in the ovary producing P4 and indicating the onset of reproductive cyclicity after calving. The on-farm ELISA overestimated P4 contents by a mean square error of prediction of 2.76 ng/mL and had an intermediate Spearman correlation with the laboratory kit (0.54). For the second objective, the postpartum interval to the commencement of luteal activity (C-LA), proportion of luteal activity between d 15 and 63 postpartum (P-LA), calculated as the number of samples above the threshold for high P4 values divided by the number of all samples, and delay of first ovulation (DOV1), defined as C-LA occurring later than d 45 postpartum, were derived from the P4 profiles. Both C-LA and DOV1 were determined by (a) thorough qualitative visual inspection of the profile, (b) the profile's mean as threshold for the first increase in P4 postpartum, indicating commencement of luteal activity, and (c) 3 ng/mL as threshold for the first increase in P4, a value that has been used by many other studies. Similarly, P-LA was determined by using methods (b) and (c). Estimates of heritability were 0.04 to 0.13 for C-LA, 0.12 to 0.23 for P-LA, and 0.03 to 0.07 for DOV1. Genetic correlation of P-LA with C-LA and with the profile's mean P4 was −1.00. The profile's mean had a higher estimate of heritability (0.11–0.12) than C-LA or DOV1. It can be calculated as the arithmetic mean of all P4 values of a profile, whereas C-LA, P-LA, and DOV1 need a definition of a threshold for high P4 values. We therefore suggest the profile's mean as a promising candidate for further research. For the third objective, once-weekly sampling was mimicked by neglecting every second sample, and C-LA and DOV1 shifted toward a later onset of cyclicity. Thus, a common standard for sampling regimen and detection algorithm is essential to avoid incompatibility between studies.

In modern dairy cattle breeding, genomic breeding programs have the potential to increase efficiency and genetic gain. At the same time, the requirements and the availability of genotypes and phenotypes present a challenge. The set-up of a large enough reference population for genomic prediction is problematic for numerically small breeds but also for hard to measure traits. The first part of this study is a review of the current literature on strategies to overcome the lack of reference data. One solution is the use of combined reference populations from different breeds, different countries, or different research populations. Results reveal that the level of relationship between the merged populations is the most important factor. Compiling closely related populations facilitates the accurate estimation of marker effects and thus results in high accuracies of genomic prediction. Consequently, mixed reference populations of the same breed, but from different countries are more promising than combining different breeds, especially if those are more distantly related. The use of female reference information has the potential to enlarge the reference population size. Including females is advisable for small populations and difficult traits, and maybe combined with genotyping females and imputing those that are un-genotyped. The efficient use of imputation for un-genotyped individuals requires a set of genotyped related animals and well-considered selection strategies which animals to choose for genotyping and phenotyping. Small populations have to find ways to derive additional advantages from the cost-intensive establishment of genomic breeding schemes. Possible solutions may be the use of genomic information for inbreeding control, parentage verification, within-herd selection, adjusted mating plans or conservation strategies. The second part of the paper deals with the issue of high-quality phenotypes against the background of new, difficult and hard to measure traits. The use of contracted herds for phenotyping is recommended, as additional traits, when compared to standard traits used in dairy cattle breeding can be measured at set moments in time. This can be undertaken even for the recording of health traits, thus resulting in complete contemporary groups for health traits. Future traits to be recorded and used in genomic breeding programs, at least partly will be traits for which traditional selection based on widespread phenotyping is not possible. Enabling phenotyping of sufficient numbers to enable genomic selection will rely on cooperation between scientists from different disciplines and may require multidisciplinary approaches.

The prediction of breeding values depends on the reliable estimation of variance components. This complex task leads to nonlinear minimization problems that have to be solved by numerical algorithms. In order to evaluate the reliability of these algorithms benchmark problems have to be constructed where the exact solution is a priori known. We develop techniques to construct such benchmark problems for mixed models including fixed and random effects, ANOVA, ML and REML predictors, balanced and unbalanced data for 1-way classification. Besides the construction of artificial data that produce the desired variance components we describe a projection method to construct benchmark data from simulated data. We discuss the cases where exact expressions for the projection can be given and where a numerical approximation procedure has to be used.

Brown Swiss × Holstein crossbred cows and pure Holstein cows were compared in a designed experiment. All cows were housed in a freestall barn at the experimental station of the federal state of Saxony-Anhalt, Germany, and calved from July 2005 to August 2008. Brown Swiss × Holstein crossbred cows were mated to Holstein AI bulls for first calving and mated to Fleckvieh artificial insemination (AI) bulls for second and third calvings. Pure Holstein cows were consistently mated to Holstein AI bulls. At first calving, Holstein-sired calves from Brown Swiss × Holstein crossbred dams (282 d) had longer gestation length than Holstein-sired calves from Holstein dams (280 d). For second and third calvings, gestation length was significantly longer for Fleckvieh-sired calves from Brown Swiss × Holstein crossbred dams (284 d) than for Holstein-sired calves from Holstein dams (278 d). Holstein-sired calves from Brown Swiss × Holstein crossbred dams (43 kg) and Holstein-sired calves from pure Holstein dams (42 kg) were not significantly different for calf weight at birth for first calving. For second and third calvings, Fleckvieh-sired calves from Brown Swiss × Holstein crossbred dams (50 kg) had significantly heavier calf weight at birth than Holstein-sired calves from pure Holstein dams (44 kg). For calving difficulty and stillbirth, Brown Swiss × Holstein crossbred cows were not different from pure Holstein cows at first calving or at second and third calving. Brown Swiss × Holstein crossbred cows (71 d) were not significantly different from pure Holstein cows (75 d) for days to first breeding during first lactation; however, Brown Swiss × Holstein crossbred cows (81 d) had significantly fewer days to first breeding than pure Holstein cows (89 d) during second lactation, and the crossbred cows (85 d) tended to have fewer days to first breeding than pure Holstein cows (92 d) during third lactation. For days open, Brown Swiss × Holstein crossbred cows were not significantly different than pure Holstein cows during any of the first 3 lactations. For body weight, Brown Swiss × Holstein crossbred cows were significantly heavier than pure Holstein cows during first lactation (621 kg versus 594 kg) and second lactation (678 kg versus 656 kg). Also, Brown Swiss × Holstein crossbred cows (18.20mm) had significantly more backfat thickness than pure Holstein cows (15.81 mm) during first lactation. Brown Swiss × Holstein crossbred cows (48 cm) had significantly greater chest width than pure Holstein cows (46 cm). Furthermore, Brown Swiss × Holstein crossbred cows had significantly longer front heel walls (5.2 cm versus 5.0 cm), significantly longer rear heel walls (4.2 cm versus 4.0 cm), and significantly more depth of the front heel (4.4 cm vs. 4.1cm) than pure Holstein cows. This study has shown that F(1) of Brown Swiss × Holstein cows are competitive with pure Holstein cows for all traits analyzed here. For fertility, crossbred Brown Swiss × Holstein cows exhibited fewer days to first breeding during second lactation than pure Holstein cows.

Summary Background & aims The present study was conducted to study whether oxidative stress is the trigger of long-term physiological effects of temporary consumption of a soy protein isolate (SPI) based diet with an imbalanced amino acid pattern. Material and methods Hepatic expression of 19 genes that are involved in and co-regulated with oxidative stress response and showing diet-associated expression after chronic SPI feeding using quantitative RT-PCR, growth and liver composition were investigated in a model of protein-underfeeding juvenile pigs, which were fed a casein (CAS) based diet for four weeks subsequent to a four week consumption of an SPI diet in comparison with chronically CAS fed animals. Results Temporary feeding of SPI diet resulted in prolonged up-regulation of genes involved in oxidative/cellular stress response (glutathione-S-transferase, peptide methionine sulfoxide reductase, calnexin, organic anion transport polypeptide 2). Cluster analysis of gene expression data indicated persistent SPI-related co-regulation of the genes involved in stress response with genes involved in the regulation of protein biosynthesis and in neuronal signalling for at least four weeks after replacement of SPI by CAS. Gene expression data are negatively correlated with body weight and liver protein content. Conclusion Significant association of oxidative stress responsiveness with growth retardation and liver composition underline the possible impact of diet-affected oxidative stress for long-lasting deleteriously metabolic consequences.

Bovine digital dermatitis (DD) is an increasing claw health problem in all cattle production systems worldwide. The objective of this study was to evaluate the use of an improved scoring of the clinical status for DD via M-scores accounting for the dynamics of the disease; that is, the transitions from one stage to another. The newly defined traits were then subjected to a genetic analysis to determine the genetic background for susceptibility to DD. Data consisted of 6,444 clinical observations from 729 Holstein heifers in a commercial dairy herd, collected applying the M-score system. The M-score system is a classification scheme for stages of DD that allows a macroscopic scoring based on clinical inspections of the bovine foot, thus it describes the stages of lesion development. The M-scores were used to define new DD trait definitions with different complexities. Linear mixed models and logistic models were used to identify fixed environmental effects and to estimate variance components. In total, 68% of all observations showed no DD status, whereas 11% were scored as infectious for and affected by DD, and 21% of all observations exhibited an affected but noninfectious status. For all traits, the probability of occurrence and clinical status were associated with age at observation and period of observation. Risk of becoming infected increased with age, and month of observation significantly affected all traits. Identification of the optimal month concerning DD herd status was consistent for all trait definitions; the last month of the trial was identified. In contrast, months exhibiting the highest least squares means of transformed scores differed depending on trait definition. In this respect, traits that can distinguish between healthy, infectious, and noninfectious stages of DD can account for the infectious potential of the herd and can serve as an alert tool. Estimates of heritabilities of traits studied ranged between 0.19 (±0.11) and 0.52 (±0.17), revealing a tendency for higher values for more complex trait definitions. In terms of genetic selection, all trait definitions identified the best (i.e., most resistant) animals, but only the new trait definitions were able to distinguish between animals with average and high predispositions for DD. Considering repeated measurements resulted in heritability estimates ranging between 0.13 (±0.05) and 0.29 (±0.10).

The melanocortin 4 receptor is expressed in virtually all brain regions of mammals and plays an important role in energy homeostasis. Polymorphisms in this gene may thus be related to growth and obesity. In pigs, a non-synonymous polymorphic site was described (Asp298Asn) and demonstrated to affect cAMP production and to alter adenylyl cyclase signalling. Association studies revealed significant linkage of this mutation with production trait in pigs. In this study, 207 Lithuanian White pigs were genotyped at the MC4R locus and analysed on relationships between genotype and breeding values for several performance traits. The observed allele and genotype frequencies did not deviate significantly from Hardy-Weinberg equilibrium (wildtype allele 0.59; mutant allele 0.41) and are comparable with those described in other Large White populations. The mutant Asn298 allele of the MC4R gene was significantly associated with increased test daily gain, higher lean meat percentage and lower backfat thickness. There was a trend towards an improved feed conversion ratio (p = 0.065) in animals with the mutant allele whereas no significant effect was found on lifetime daily gain. These results indicate that the MC4R polymorphism should be integrated in selection programmes in the Lithuanian White to improve carcass composition.

Sulfate is one of the most important macronutrients in cells and the major sulfur source in many organisms as well as one of the most abundant anions in the serum. As sulfate is a hydrophilic anion, movement across the lipid bilayer is mediated by transporters that regulate efflux and influx. Here, we report the molecular cloning, mapping, and functional analysis of the bovine solute carrier/sulfate transporter SLC26a2 gene, the first member of this family to be cloned in cattle. A recombinant phage library was screened, and single phages harbouring the SLC26a2 gene was isolated and sequenced. A fragment of 6295 base pairs (bp) of the bovine SLC26a2 gene harbouring exon 2 and exon 3 was used for further analysis. Similar to the human, ovine, mouse, and rat SLC26a2 gene, the bovine ortholog consists of two coding exons. The open reading frame harbours 2202 nucleotides (nt), coding for a protein of 734 amino acids with a calculated molecular weight of 81.5 kilodaltons (kDa) and a statistical isoelectric point (p I ) of 8.77. The bovine SLC26a2 gene was mapped to chromosome 7q23–q24 (BTA 7q23–q24) by fluorescence in situ hybridisation (FISH) analysis. Two point mutations were identified comparing the DNAs of 300 Holstein Frisian cattle, one of them resulting in an isoleucine to serine amino acid exchange at position 520. The Ile520Ser exchange influences the sulfate uptake as measured in primary fibroblasts isolated from testis and in immortalized fibroblastoid bovine cell lines.

Title of the paper: Examinations using the results of breeding value estimation for Holstein sires and cows in Germany Besides for selection purposes, estimated breeding values can be used to analyze genetic trends and structures in populations. Using data of 2,440,261 cows from four regions in Germany, genetic trends for all cows under test (registered and grade) were calculated for the period of birth years 1992 to 1999. For milk, fat, and protein yield annual trends on average were 111 kg, 3.2 kg, and 3.3 kg, respectively. An analysis of the use of proven sires revealed that a relatively large proportion of bulls get second crop daughters. Most of them, however, are used in a very limited way. The differential use of sires by breeders besides production is highly influenced by type proofs although in this respect clear differences exist between regions. An analysis comparing first proofs of young bulls with their later proofs based on additional second crop daughters for all German Holstein breeding organisations showed a high degree of agreement between the two proofs. However, this analysis was based on only 127 sires that were used more widely (plus > 500 second crop daughters).

Based on the lactation curves ofa total of 817 cows from three herds the Variation of the shape of lactation curves is illustrated stratified by herd, lactation number and total lactation produetion. The data was collected from on-farm Computers connected to recording of yields on a daily basis. The results from this ongoing project show that a differentiation of cows according to total yield per lactation or 305-day yield based on records from early lactations is difficult and thus highly questions the set-up of yield groups in the beginning ofthe lactation. The results also illustrate that it is still debatable what kind of criterion for the persistency of lactation produetion should be used. This question should be answered in relation to the desired length of lactation. Today, random regression models for the genetic evaluation of dairy animals seem to be a promising alternative to more traditional methods. Future research in this field should make use of data from daily recordings since by this the impaet ofthe data structure can be analysed by mimicking different recording scenarios.

Lactation persistency, often simply called persistency, in general can be defined as the ability to maintain yields during the lactation. Persistency has an impact on food costs, health, and fertility. Of these three components affected by persistency, the impact of persistency on health, i.e. metabolic stress of the cow leading to health problems, may be most important nowadays. Numerous suggestions for criteria of persistency exist. Often simple ratios of part-lactation yields, e.g. the ratio of yield in the first and last 100 days of lactation, have been used. New approaches have used results from the application of random regression test day models developed for the genetic evaluation of yield traits. Many studies unfortunately have neglected the effect of gestation on persistency but acknowledged that an improved persistency should lead to an improved reproductive performance. Both relationships should be considered in genetic analyses and recommendations for improvement of management decisions. Today the correct description of persistency plays a prominent rôle to obtain correct genetic evaluations based on test day yields. But, although apparently trivial, a direct genetic analysis of lactation persistency and even more an inclusion of this trait into selection programmes clearly is a complicated task. A reason for this, amongst others, is that management strategies for feeding during the lactation and handling of the reproductive performance that are most often not recorded, are likely to mask the real persistency. Future studies on the genetics of persistency should also seek a strong interaction of geneticists and physiologists as persistency is fundamentally confounded with the problem of metabolic stress. Today, a recommendation of the inclusion of persistency in selection programmes appears to be premature and more studies, e. g. on the association of persistency with longevity, could aid in this process.

Among the expressed sequence tags (ESTs) with different expression in M. biceps femoris of healthy and splay leg piglets there were several fragments lacking an annotation (MAAK et al., 2001). The aims of this study were (1) to identify the gene represented by one of these anonymous ESTs (GenBank accession no. AJ271018) through inter-species comparison and (2) to determine its chromosomal location in swine by radiation hybrid and in-silico mapping. Identification of the function of the gene and its mapping should clarify whether the gene can be considered a candidate for congenital splay leg.

Based on a total of 2,305,000 records for protein yield in days 1–100 of first lactation and in the entire first lactation variance components were estimated within 36 subregions from northwestern Germany using REML with an animal model. For days 1–100, heritability estimates ranged from 0.27 to 0.40, and estimates for phenotypic variances ranged from 73.8 kg 2 to 122.6 kg 2 . Pattern of results for the entire first lactation was very similar. Phenotypic variances as well as heritabilities were concluded to be heterogeneous across subregions. To account for heterogeneous heritabilities in an evaluation assuming a common heritability records were standardized. Adjustment factors were derived by first calculating the optimum fractions to be selected from each subregion and then calculating the corresponding adjusted phenotypic variances so that the differences in heritabilities between the subregions were reflected in the phenotypic variances. Using this method and comparing it to an evaluation with unadjusted records more cows were selected from subregions with higher heritabilities, thus showing that this method may be useful to reduce potential bias from heterogeneous heritabilities.

Previous research has found that a quantitative trait locus exists affecting calving and conformation traits on Bos taurus autosome 18 that may be related to increased calf birth weights, which are not routinely recorded in the United States. Birth weight data from large, intensively managed dairies in eastern Germany with management systems similar to those commonly found in the United States were used to develop a selection index predictor for predicted transmitting ability (PTA) of birth weight. The predictor included body depth, rump width, sire calving ease, sire gestation length, sire stillbirth, stature, and strength. Genetic and phenotypic correlations and heritabilities from the United States were substituted for the German values, and birth weight PTA predicted for 31,984 bulls with US genetic evaluations. A genome-wide association study was conducted on the predicted birth weight PTA with the 2-step genomic BLUP procedure used for routine evaluations in the United States. Allele substitution effects were predicted for 43,188 single nucleotide polymorphisms (SNP). Genotypes were available for 53,644 predictor animals. Gene set enrichment analysis was performed on the 100 SNP that had the largest effects expressed in additive genetic standard deviations. Several SNP related to growth and development were found among the 25 SNP with the largest effects, including markers located within or near (≤ 100 kbp) ABCA12, FLRT2, LHX4, MAP3K5, NRAC, NTNG1, PIGN, and ZNF75A. The gene set enrichment analysis identified the Kyoto Encyclopedia of Genes and Genomes "Regulation of actin cytoskeleton" pathway (bta04810) as being enriched. That pathway includes the ROCK gene, which is involved in placental function in the human, as well as other developmental genes (e.g., FAK and PAK). Prediction equations derived from one population are useful for identifying genes and gene networks associated with phenotypes that are not directly measured in a second population. This approach will identify only genes associated with the traits used to construct the birth weight predictor, and not loci that affect only birth weight.

White Galloway cattle exhibit three different white coat colour phenotypes, that is, well marked, strongly marked and mismarked. However, mating of individuals with the preferred well or strongly marked phenotype also results in offspring with the undesired mismarked and/or even fully black coat colour. To elucidate the genetic background of the coat colour variations in White Galloway cattle, we analysed four coat colour relevant genes: mast/stem cell growth factor receptor (KIT), KIT ligand (KITLG), melanocortin 1 receptor (MC1R) and tyrosinase (TYR). Here, we show that the coat colour variations in White Galloway cattle and White Park cattle are caused by a KIT gene (chromosome 6) duplication and aberrant insertion on chromosome 29 (Cs29 ) as recently described for colour-sided Belgian Blue. Homozygous (Cs29 /Cs29 ) White Galloway cattle and White Park cattle exhibit the mismarked phenotype, whereas heterozygous (Cs29 /wt29 ) individuals are either well or strongly marked. In contrast, fully black individuals are characterised by the wild-type chromosome 29. As known for other cattle breeds, mutations in the MC1R gene determine the red colouring. Our data suggest that the white coat colour variations in White Galloway cattle and White Park cattle are caused by a dose-dependent effect based on the ploidy of aberrant insertions and inheritance of the KIT gene on chromosome 29.

Summary Phenotypic and genetic parameters were estimated for three criteria of persistency of lactation production of milk, fat, and protein yield. The criteria included the ratio of yield in last to first trimester of lactation, the ratio of the maximum divided by the mean of test-day production, and the standard deviation of test-day records. Data comprised 15 756 first-lactation yields from north-western Germany with at least 8 recorded test days. Heritability estimates were in the range 0.10-0.15 for milk yields and slightly lower for fat and protein. Heritabilities varied only little among the three criteria and across various models, including or neglecting covariates for lactation yield or length of lactation. For a bivariate analysis of persistency and milk yield, the latter was either defined in the traditional way as 305-day lactation records, or a test-day model was applied considering test-day records directly in the form of a repeatability model. The results showed that genetic correlations between milk yield and persistency were favourable for selection on yield for the two ratios (rg = 0.50/ −0.50) and unfavourable for the standard deviation (rg = 0.30), although correlations among criteria of persistency were favourable. No apparent differences existed between using 305-day records or test-day records. For the latter definition of yield, this could also be confirmed when only test-day records from mid-lactation were used in the test-day model. Zusammenfassung Die genetische Beziehung zwischen der Laktationspersistenz und der Milchleistung Fur drei Kriterien der Persistenz von Laktationsleistungen fur Milch-, Fett-und Eiweis-menge wurden phanotypische und genetische Parameter geschatzt. Die Kriterien umfasten den Quotienten aus der Leistung im letzten Drittel der Laktation dividiert durch die des ersten Drittels, den Quotienten aus der maximalen Kontrolltagsleistung dividiert durch das Mittel der Kontrollen, sowie die Standardabweichung der Kontrolltagsleistung. Das Daten-material beinhaltete 15 756 Erstlaktationsleistungen aus Nord-West-Deutschland, fur die jeweils mindestens acht Kontrolltagsleistungen vorlagen. Die Schatzwerte fur die Heritabilitat lagen im Bereich von 0, 10-0, 15 fur die Milchmenge und etwas niedriger fur die Mengenleistung in Fett und Eiweis. Die Heritabilitaten variierten nur wenig zwischen den drei Kriterien und zwischen verschiedenen Modellen mit und ohne Berucksichtigung der Kovariablen Mengenleistung oder Laktationslange. Fur eine bivariate Analyse der Persistenz und der Milchleistung wurde die Milchleistung entweder mittels traditioneller 305-Tage-Leistungen oder durch ein Kontrolltagsmodell mit direkter Berucksichtigung einzelner Kontrolltagsleistungen in Form eines Wiederholbarkeitsmodells definiert. Die Ergebnisse zeigten, das die genetische Korrelation zwischen Milchmenge und Persistenz fur die zwei Quotienten zuchterisch positiv fur eine Selektion auf Milchmenge ist (r =0,50 bzw. −0,50); fur die Standardabweichung ergab sich allerdings eine zuchterisch ungunstige Korrelation (rg = 0,30). Die genetischen Korrelationen zwischen den Persistenzkriterien waren zuchterisch gunstig. Zwischen der Berucksichtigung der Milchmenge als 305-Tage-Leistung und der direkten Einbeziehung der Kontrolltagsleistungen ergaben sich keine Unterschiede. Fur die letztere Methode konnte dieses Ergebnis auch bestatigt werden, wenn nur Kontrolltagsleistungen aus der Mitte der Laktation berucksichtigt wurden.

Background The most common application of imputation is to infer genotypes of a high-density panel of markers on animals that are genotyped for a low-density panel. However, the increase in accuracy of genomic predictions resulting from an increase in the number of markers tends to reach a plateau beyond a certain density. Another application of imputation is to increase the size of the training set with un-genotyped animals. This strategy can be particularly successful when a set of closely related individuals are genotyped. Methods Imputation on completely un-genotyped dams was performed using known genotypes from the sire of each dam, one offspring and the offspring’s sire. Two methods were applied based on either allele or haplotype frequencies to infer genotypes at ambiguous loci. Results of these methods and of two available software packages were compared. Quality of imputation under different population structures was assessed. The impact of using imputed dams to enlarge training sets on the accuracy of genomic predictions was evaluated for different populations, heritabilities and sizes of training sets. Results Imputation accuracy ranged from 0.52 to 0.93 depending on the population structure and the method used. The method that used allele frequencies performed better than the method based on haplotype frequencies. Accuracy of imputation was higher for populations with higher levels of linkage disequilibrium and with larger proportions of markers with more extreme allele frequencies. Inclusion of imputed dams in the training set increased the accuracy of genomic predictions. Gains in accuracy ranged from close to zero to 37.14%, depending on the simulated scenario. Generally, the larger the accuracy already obtained with the genotyped training set, the lower the increase in accuracy achieved by adding imputed dams. Conclusions Whenever a reference population resembling the family configuration considered here is available, imputation can be used to achieve an extra increase in accuracy of genomic predictions by enlarging the training set with completely un-genotyped dams. This strategy was shown to be particularly useful for populations with lower levels of linkage disequilibrium, for genomic selection on traits with low heritability, and for species or breeds for which the size of the reference population is limited.

Understanding the basis for differences in nutrient requirements and for nutrient effects on health and performance requires an appreciation of the links between nutrition and gene expression. We developed and applied molecular probes to characterize diet-associated postabsorptive hepatic gene expression in growing pigs chronically fed protein-restricted diets based on either casein (CAS) or soy protein isolate (SPI). Eighty-eight expressed sequence tags (ESTs) were identified on the basis of diet-related changes in expression, by using an mRNA differential display method. Expression profiling based on transcription analysis by real-time reverse transcriptase-polymerase chain reaction showed that the SPI diet significantly changed the pattern of gene expression as compared with the CAS diet and allowed identification of coregulated genes. The expression of six genes involved in the metabolism of stress response (glutathione S-transferase, peptide methionine sulfoxide reductase, apolipoprotein A-I, organic anion transport polypeptide 2, calnexin, heat shock transcription factor 1) exhibited significant changes in the transcription level and indicated an increased oxidative stress response in pigs fed the SPI diet. Hierarchical clustering of gene expression data of all 33 ESTs analyzed across 14 pigs fed the two different diets resulted in clustering of genes related to the oxidative stress response with genes related to the regulation of gene expression and neuronal signaling.

Brown Swiss × Holstein (BS × HO) crossbred cows (n = 55) and purebred Holstein (HO) cows (n = 50) were compared for milk yield, fat and protein production, somatic cell score, milking speed, and udder measurements for the first 3 lactations. Cows from a designed experiment were housed in a freestall barn at the experimental station of the federal state of Saxony-Anhalt, Germany, and calved from July 2005 to August 2008. Best prediction was used to determine actual production for 305-d lactations from test-day observations. For the first 3 lactations, BS × HO cows and HO cows were not significantly different for milk yield, fat and protein production, or SCS. Average milking time was significantly longer for BS × HO cows than for HO cows for first, second, and third lactations by 35, 51, and 30s, respectively. Average milking speed expressed as average yield per minute was significantly lower for BS × HO cows than for HO cows for the first 3 lactations by 0.19, 0.35, and 0.19 kg/min, respectively. Front and rear teats were significantly longer for BS × HO cows than for HO cows. Furthermore, front and rear udder clearance was significantly lower for BS × HO cows compared with HO cows in first and second lactations.

Summary Field data on weight recordings provided by the Australian Simmental Breeders Association was analysed. From a data set of 64,962 animals, which had either birth (BW), weaning (WW), yearling (YW), or final weight (FW) records a subset of 17 herds comprising 18,083 animals was used to obtain uni- and bivariate estimates of variance components. This subset had to be subdivided into six further subsets, called group herds. The models used allowed for additive genetic, maternal genetic, and permanent environmental effects and for a covariance between additive direct and maternal genetic effects. Estimates were pooled across group herds. The results for BW, WW, YW, FW were .33, .35, .37, and .30, respectively, for heritabilities and .074, .18, and .11 for maternal heritabilities (not estimated for FW). Significant correlations between direct and maternal genetic effects (rAM) existed for WW and YW in the magnitude of -.39 and -.22. However, further research is needed due to the problems associated with the estimation of rAM. Zusammenfassung Schatzung direkter und maternaler (Ko)Varianz-Komponenten fur Wachstumsmerkmale bei australischem Fleckvieh Gegenstand der Untersuchung waren im Feld erhobene Gewichte, die von der Australischen Simmental Breeders Association bereitgestellt worden waren. Aus einer Datei von 64.962 Tieren, die entweder ein Geburtsgewicht (GG), ein Absetzgewicht (AG), ein Jahrlingsgewicht (JG) oder ein Endgewicht (EG) aufwiesen, wurde ein Teildatensatz von 18.083 Tieren extrahiert und einer uni- und bivariaten Schatzung von Varianzkomponenten unterzogen. Diese Datei muste weiterhin in sechs verschiedene Dateien aufgeteilt werden; diese wurden Gruppenherden genannt. Die verwendeten Modelle erlaubten additiv-genetische, maternal-genetische und permanente Umwelteffekte sowie das Vorhandensein einer Kovarianz zwischen additiv-genetischem und maternal-genetischem Effekt. Die Schatzwerte wurden uber die Gruppenherden gepoolt. Die Ergebnisse in der Reihenfolge GG, AG, JG und EG waren 0,33, 0,35, 0,37 und 0,30 fur die Heritabilitaten sowie 0,074, 0,18 und 0,11 fur die maternalen Heritabilitaten (nicht geschatzt fur EG). Signifikante Korrelationen zwischen direktem und maternal-genetischem Effekt (rAM) existierten fur AG und JG in der Grosenordnung von −0,39 und −0,22. Trotz dieses Ergebnisses sind weitere Untersuchungen notig, weil die Schatzung von rAM problematisch ist.

The objective of the present study was to conduct a stochastic simulation study on the possible benefits of an application of genomic selection in dairy cattle breeding programs according to a variety of selection schemes. In addition, the heritability of the trait in question, the accuracy of genomic breeding values, and the number of animals to be genotyped were varied. Specifically, the question of genotyping males, females, or both, was addressed. Selection schemes were compared with a young bull breeding program. The main criterion for comparison was the average of true breeding values of selected young males to be used as replacements for artificial insemination bulls. Stochastic simulations were run with 50 repetitions each to generate individuals with phenotypes, breeding values estimated by BLUP, and true breeding values. Genomic breeding values were generated from true breeding values with defined accuracy. Examined scenarios included a group of selection schemes that featured genotyping of parents of future bulls only. Such schemes can be viewed as improvements of young bull programs, and they were found to be competitive with or superior to a classical young bull program. However, a genomic breeding program usually involves at least genotyping young male candidates. A second group of selection schemes reflected this requirement. Scenarios in this group were found to be superior over the young bull program by 1.0 to 1.2 standard deviations of the average true breeding value of young male candidates. Within this group of scenarios, one scheme referred to an ideal situation under which genotypes for male calves were available without limitation. Using the average of true breeding values as the criterion for comparison, this idealistic scenario was competitive with other scenarios only if the reliability of genomic breeding values was larger than 0.50. Conventionally, not all males available will have genotypes, and the 2 most promising scenarios included a preselection step for dams of future bulls. This preselection step can be based on conventional BLUP estimated breeding values for bull dams, because differences with a scheme under which both parents and the resulting male offspring are genotyped were marginal. Genotyping of young male candidates should be the focus of activities of today's breeding organizations.

Summary In the present study data consisting of 244,189 service periods of heifers, first calf cows, and older cows were analyzed. In addition to the fixed effects usually incorporated in models for the analysis of female fertility (herd, year, season, etc.), the data could be differentiated as electronically recorded via a handheld computer or recorded as usual, i. e. handwritten receipts had been issued. The means of the fertility parameters in both data subsets were clearly different. However, this could not be attributed to the recording scheme. Estimates of heritabilities in general were low and in agreement with literature values. Heritability estimates within subsets of the data did not show an effect of the type of recording. Differencies in heritabilities were found between age groups with the highest values for heifers. Zusammenfassung Schatzung genetischer Parameter fur unterschiedlich erhobene Fruchtbarkeitsdaten beim Milchrind In der vorliegenden Arbeit wurden 244,189 Serviceperioden von Farsen, Erstkalbskuhen und alteren Kuhen ausgewertet. Zusatzlich zu den fixen Effekten, die ublicherweise in Modellen zur Analyse der weiblichen Fruchtbarkeit enthalten sind (Herden, Jahre, Saison etc.) konnten die Daten differenziert werden in einen Teil, der elektronisch mittels Handheld-Computer aufgenommen worden war, und einen anderen Teil, welcher auf ubliche Weise erhoben worden war, d. h. handgeschriebene Belege waren ausgestellt worden. Die Mittelwerte des Fruchtbarkeitsparameters in den beiden Teildatensatzen waren deutlich verschieden. Dies konnte allerdings nicht auf die Erhebungsart zuruckgefuhrt werden. Schatzwerte fur die Heritabilitaten waren allgemein niedrig und in guter Ubereinstimmung mit Werten aus der Literatur. Innerhalb der Teildatensatze zeigte sich kein Unterschied in den Heritabilitatsschatzwerten je nach Art der Datenerhebung. Unterschiedliche Heritabilitaten wurden fur die verschiedenen Altersgruppen gefunden, wobei die Schatzwerte fur Farsen am hochsten waren.

The availability of genomic estimated breeding values (GEBV) allows for possible modifications to existing dairy cattle breeding programs. Selection index calculations including genomic and phenotypic observations as index sources were used to determine the optimal number of offspring per genotyped sire with a focus on functional traits and the design of cooperator herds, and to evaluate the importance of a central station test for genotyped bull dams. Evaluation criteria to compare different breeding strategies were correlations between index and aggregate genotype (r(TI)), and the relative selection response percentage (RSR) of an index without single nucleotide polymorphism information in relation to a single nucleotide polymorphism-based index. The number of required daughter records per sire to achieve a predefined r(TI) strongly depends on the accuracy of GEBV (r(mg)) and the heritability of the trait. For a desired r(TI) of 0.8, h(2) = 0.10, and r(mg) = 0.5, at least 57 additional daughters have to be included in the genetic evaluation. Daughter records of genotyped sires are not necessary for optimal scenarios where r(mg) is greater than or equal to r(TI). There still is a substantial need for phenotypic daughter records, especially for low-heritability functional traits and r(mg)0.7. Phenotypic records from genotyped potential bull dams have no relevance for increasing r(TI), even with a low value for r(mg) of 0.5. Hence, genomic breeding programs should focus on recording functional traits within progeny groups, preferably in cooperator herds. For low-heritability traits and with r(mg)0.7, the RSR of conventional breeding programs was only 10% of RSR from genomic breeding strategies. As shown in scenarios including 2 traits in the index as well as in the aggregate genotype, the availability of highly accurate GEBV for production traits and low-accuracy GEBV for functional traits increased the risk of widening the gap between selection responses in production and functionality. Counteractions are possible, such as via higher economic weights for low-heritability functional traits. Finally, an alternative selection strategy considering only 2 pathways of selection for genotyped male calves and for cow dams was evaluated. This strategy is competitive with a 4-pathway genomic breeding program if the fraction of selected male calves for the artificial insemination program is below 1% and if selection is focused on functionality, thus pointing to substantial insufficiencies caused by low reliabilities of breeding values for cows for such traits in conventional bull dam selection schemes.

ZDHHC9 (zinc finger, DHHC-type containing 9) is a protein acyl transferase involved in palmitoylation of basic signaling molecules. We found ZDHHC9 expression increased in hind leg muscles of newborn splay leg piglets. In order to elucidate the background of this increased expression we determined the structure of the porcine gene, including sequence variation, and analyzed the structure and expression of microRNAs potentially targeting the gene. We confirmed the expression results by RT Real-time PCR. The porcine ZDHHC9 gene has a similar structure to the human gene with two transcripts resulting in an identical protein. None of the 17 single nucleotide polymorphisms (SNPs) identified in the porcine gene affects the protein or putative microRNA binding sites, respectively. Two microRNAs (93 [minor] and 106b) were assayed in the muscles. Their expression variation proved to be independent from ZDHHC9 expression thus eliminating them as causally related to congenital splay leg.

Effectiveness of cluster analysis in detecting application of bST was examined. Field data were manipulated by adding a specified percentage of the true performance to original test day records to simulate application of bST. The partly manipulated data then were analyzed using cluster analysis. Test day milk production data came from 42,779 cows of the Bretagne (Northwestern France) that had test days between 1986 and 1989. As criteria in the cluster analysis for differentiation between treated and untreated cows, parameters of the incomplete gamma function along with other variables calculated from test day records were used. The best differentiation was achieved when a persistency parameter, defined as the ratio of second divided by first trimester production, was used as a variable in the cluster analysis. For the assumed scenario of bST application, more than 80% of all cows were classified correctly under random use of bST. Systematic treatment led to improved results.

The validity of national genetic evaluations depends on the quality of input data, on the model of analysis, and on the correctness of genetic evaluation software. A general strategy was developed to validate national breeding value prediction software: performances from a real data file were replaced with simulated ones, created from simulated fixed and random effects and residuals in such a way that BLUP estimates from the evaluation software must be equal to the simulated effects. This approach was implemented for a multiple-trait model and a random regression test-day model. An example was presented on test-day observations analyzed with a random regression animal model including a lactation curve described as a sum of fixed polynomial regression and fixed spline regression on days in milk, and with genetic and permanent environmental effects modeled by using Legendre polynomials of order 2. Residuals had heterogeneous variances, and phantom parent groups were included. This method can be easily extended to other linear models. The comparison of genetic evaluation results with simulated true effects is used to demonstrate the great efficiency and usefulness of the proposed method.

The myogenic factors (MYF) 5 and 6 are integral to the initiation and development of skeletal muscle and to the maintenance of its phenotype. Thus, they are candidate genes for growth- and meat quality-related traits. We performed a comparative sequence analysis of the MYF5/MYF6 locus in swine, cattle, dog, chicken and zebrafish on the basis of structural and functional information from human and mouse. Beside the characterization of upstream regulatory elements recently identified in mice, we demonstrate the existence of further highly conserved elements (E1 to E4) which may play a role in the regulation of MYF5 and MYF6 expression. Comparative sequence analysis of putative regulatory sequences in swine revealed a total of 21 single nucleotide polymorphisms (SNP) including 1 and 6 SNPs new for the promoters of MYF5 and MYF6, respectively. The conserved organization of the locus in vertebrates indicates a common basic mechanism of muscle development. However, the existence of numerous regulatory elements at large distances to MYF5 and MYF6 points to a very complex pattern of the gene regulation with significant differences between species.

Genotype by environment interaction can be detected via the estimation of genetic correlations between environments under an animal model based on data comprising genetic links between the strata. Genetic correlations were estimated for protein yield of Holstein cows within and across regions of Germany using REML under an animal model for lactation and test-day records. Subsets of the entire data were created, stratified by region or herd size within region, and comprised between 16,307 and 132,972 cows with first-lactation records. Substantial heterogeneity exists between regions in Western and Eastern Germany. In Western states, most farms are small, with typical herd sizes of 30 to 60 cows, whereas in Eastern states, mostly large herds with herd sizes of 500 to 2000 cows are common. The results show drastic differences for residual and permanent environmental variance components between Eastern and Western regions with increases of around 30% for Eastern regions. Additive genetic variances were of similar magnitude in both regions. Genetic correlations between Eastern and Western states were between 0.90 and 0.95 but dropped to 0.79 when data from an Eastern state were reduced to contain large herds only. The results indicate that differences in herd size account for more of the differences in genetic correlation than do geographic regional differences.

In survival analysis, type traits can be included as covariates to evaluate their use as predictors for survival. One problem in such an analysis is the availability of suitable data. Whereas data on the length of productive life (LPL) of individual cows can be retrieved from milk recording data, for type traits, all cows in the population must be scored for type at least once. In the present analysis, a dataset from the Osnabruck region in northwestern Germany, which fulfilled this requirement in recent years, was used. Data consisted of 169,733 cows with information on LPL for calving years 1980 to 1996 (dataset I) and of 39,233 cows with information on LPL and type for calving years 1990 to 1996 (dataset II). A further dataset (III) contained 43,116 cows from calving years 1987 to 1996 and included information on the housing system for each herd. The basic model included stage of lactation, relative production within herd, change of herd size, and year-season as time dependent effects; age at calving as a time-independent effect; and herd-year-season and sire as random effects. Other effects (information on type, housing system) were included additionally. For data-set II, the scores for 15 linear type traits were also included as corrected phenotypic values, estimated breeding values, and residuals from a previous BLUP analysis. The package Survival Kit 3.0 was used for all analyses. The results indicate a moderate heritability of 0.17 and 0.18 for true and functional LPL (dataset I). Almost all type traits analyzed (dataset II) exceeded a 0.001 level of significance in their effect on survival. The strongest relationships between survival and type were found for udder depth, fore udder attachment, and front teat placement. The main result from the comparison of housing systems (dataset III) was that bedding has a positive effect on survival.

In test-day (TD) models, records from individual test days are used to determine lactation production instead of aggregating records. Test-day models have recently gained considerable interest because they are more flexible in handling records from different recording schemes. Compared with only using records of complete lactations, they can reduce the generation interval through frequent genetic evaluations with the latest data. Test-day models can predict total production more accurately by accounting for time-dependent environmental effects. Test-day models may be separated into three groups: First, two-step models under which corrections are carried out at TD level and subsequently corrected TD records are processed in an aggregated form as lactation records. Second, fixed regression models assume that TD records within a lactation are repeated records. Because yields in the course of the lactation follow a curvilinear pattern, this curve can be considered by using suitable covariates. Third, random regression models additionally define the animal's genetic effect by using regression coefficients and allowing for covariances among them. The difference between random regression and fixed regression models is that the genetic merit of an individual is allowed to differ in the course of the lactation in random regression models. Random regressions are related to the approach of defining covariance functions for longitudinal data. Computationally, TD models are very demanding. For evaluations on a national scale, the size of the equation system can go to hundreds of millions of equations, depending on the size of the database and the specific model defined.

The present study estimated genetic parameters for yields of milk, fat, and protein applying REML procedures under test day animal models. The data consisted of 155,494 test day records from 15,756 Friesian cows in first lactation from one region in northern Germany. The models applied included a traditional herd-year-season model for the analysis of single test days and 305-d records and two test day models differing by the definition of contemporary groups, either as herd-year-season of calving or as herd-test day. For single test days, heritabilities were highest for midlactation yields. For test day models, estimates of heritability varied with the number of test day records included for each cow. Estimates of .32, .19, and .20 for yields of milk, fat, and protein, respectively, were highest when only test d 3 to 7 were included; the corresponding estimates for 305-d records were .39, .32, and .30. Estimates of residual variances were reduced when test day records were converted to records of average yield in standardized intervals of 30 d. Breeding values were estimated for 305-d and test day models. A comparison of both sets of breeding values indicates only minor changes in sire rank, but more drastic reranking for individual cows.

Die Rolle des DV-Anwenders aus der Sicht eines Universitatsinstitutes hat sich in den letzten Jahren gewandelt. Die Grunde dafur liegen vornehmlich in den technischen Neuerungen auf dem Gebiet der Datenverarbeitung, insbesondere in der Verfugbarkeit anwenderfreundlicher Software, den heute verfugbaren Rechenkapazitaten und der Vernetzung von Geraten und den sie nutzenden Personen. Das Institut fur Tierzucht und Haustiergenetik der Universitat Gottingen betreibt Forschung und Lehre auf dem Gebiet der landwirtschaftlichen Tierproduktion. Ein Schwerpunkt ist die genetisch-statistische Analyse von Leistungsdaten, welche durch die auf dem Gebiet der Tierproduktion und insbesondere der Tierzucht tatigen Organisationen an Tieren auf landwirtschaftlichen Betrieben erhoben werden. Ein weiterer Schwerpunkt liegt in der Anlage, Durchfuhrung und Auswertung von experimentellen Versuchen unter kontrollierten und definierten Umweltbedingungen.

Variance and covariance components were estimated for milk-production traits in the first 3 lactations. The data set comprised 95 910 first, 74 088 second and 55 371 third lactation records of cows, sired by 603 black and white AI bulls in Lower Saxony (F.R.G.). Estimation was by two multiple trait restricted maximum likelihood procedures, differing by allowance of non-zero residual covariances (MT-O-REML and MT-REML). Further, correlations between traits within lactations were estimated using Henderson's method III (H-III). The results revealed a clearly antagonistic relationship between milk yield and percentages of fat and protein, with correlations in the range -0.40 to -0.50. In comparison with H-III estimates, genetic variances and especially covariances increased markedly when using REML and all available data. Error (co) variances were of the same magnitude for all methods used. Estimated genetic correlations between corresponding traits in Lactations 1 and 2 were greater than 0.90, while for Lactations 2 and 3 the correlation was unity. Results suggest that dairy performance in the first 3 lactations, at least in Lactation 2 and 3, genetically should be regarded as one trait.

In sire evaluation using the best linear unbiased prediction (BLUP) method a relationship matrix including only the relationships among sires can be used. The aim of the present study was to show properties of this method when models with or without grouping of sires are applied. The examination consisted of Monte-Carlo simulation of special situations occurring in dairy sire evaluation. Up to 20 repetitions were generated for each data set. Sire effects were equal for all repetitions of a particular set, cow and residual effects being sampled afresh. Thus, in addition to the correlation between true and estimated breeding value, the true standard deviation of estimated breeding value could be calculated from the results of repeated sire evaluation. With respect to these parameters, the results show that models which do not contain sire grouping but include relationships were superior to grouping models even when relationships are considered in addition. This superiority increases with decreasing number of daughters per sire. The hypothesis that a model without sire grouping but including a relationship matrix leads to a bias in the estimation of breeding values when dams of bulls are selected, could not be confirmed. On condition that the frequency of sires which are related to other sires is high, a model including a relationship matrix but without grouping can be recommended.