In the present study, 6 different mastitis data sets of 3 dairy herds with an overall herd size of 3200 German Holstein cows were analyzed. Data collection periods included the first 50, 100, or 300 d of lactation. The 3 data collection periods were analyzed with a lactation model and a test-day model. All models were animal threshold models. Mastitis frequencies in the lactation model data sets varied between 29 and 45%, and varied between 3 and 6% in the test-day model data sets. Depending on the period of data collection, heritabilities of liability to mastitis in the lactation models were 0.05 (50 d), 0.06 (100 d), and 0.07 (300 d). In the test-day models, heritabilities were slightly higher with values of 0.09 (50 and 100 d), and 0.06 (300 d). Between lactation models, the rank correlations between the relative breeding values were high and varied between 0.86 and 0.94. Rank correlations between the relative breeding values of the test-day models ranged from 0.68 to 0.87. The rank correlations between the relative breeding values of lactation models and test-day models varied from 0.51 and 0.80. Genetic correlations between mastitis and milk production traits were estimated with a linear animal test-day model. The correlations with mastitis were 0.29 (milk yield), 0.30 (fat yield), 0.20 (fat content), 0.34 (protein yield), and 0.20 (protein content). The estimated genetic correlation between mastitis and somatic cell score was 0.84.

An understanding of inbreeding and inbreeding depression are important in evolutionary biology, conservation genetics, and animal breeding. A new method was developed to detect departures from the classical model of inbreeding; in particular, it investigated differences between the effects of inbreeding in recent generations from that in the more distant past. The method was applied in a long-term selection experiment on first-litter size in mice. The total pedigree included 74 630 animals with B30 000 phenotypic records. The experiment comprised several different lines. The highest inbreeding coefficients (F) within a line ranged from 0.22 to 0.64, and the average effective population size (N e ) was 58.1. The analysis divided F into two parts, corresponding to the inbreeding occurring in recent generations ('new') and that which preceded it ('old'). The analysis was repeated for different definitions of 'old' and 'new', depending on length of the 'new' period. In 15 of these tests, 'new' inbreeding was estimated to cause greater depression than 'old'. The estimated depression ranged from À11.53 to À0.79 for the 'new' inbreeding and from À5.22 to 15.51 for 'old'. The difference was significant, the 'new' period included at least 25 generations of inbreeding. Since there were only small differences in N e between lines, and near constant N e within lines, the effect of 'new' and 'old' cannot be attributed to the effects of 'fast' versus 'slow' inbreeding. It was concluded that this departure from the classical model, which predicts no distinction between this 'old and 'new' inbreeding, must implicate natural selection and purging in influencing the magnitude of depression.

Data from 3,200 Holstein cows from 3 commercial dairy farms in Germany were used to estimate heritabilities and breeding values for liability to udder diseases (UD), fertility diseases (FD), metabolic diseases (MD), and claw and leg diseases (CLD) using single-trait threshold sire models. A total of 92,722 medical treatments recorded from 1998 to 2003 were included in the analysis. Approximate genetic correlations between persistency of milk yield, fat yield, protein yield, and persistency of milk energy yield and liability to the health traits were calculated based on correlations between EBV. Posterior means of heritability of liability ranged from 0.05 to 0.08 for UD, from 0.04 to 0.07 for FD, from 0.08 to 0.12 for MD, and from 0.04 to 0.07 for CLD. Approximate genetic correlations of the disease traits with the persistency traits were favorable, except for MD in all lactations, which were unfavorable, and UD, which were around zero. Highest correlations in the range of 0.13 to 0.46 were found between the different persistency traits and CLD.

In this study, the effect of different measurements of ancestral inbreeding on birthweight, calving ease and stillbirth were analysed. Three models were used to estimate the effect of ancestral inbreeding, and the estimated regression coefficient of phenotypic data on different measurements of ancestral inbreeding was used to quantify the effect of ancestral inbreeding. The first model included only one measurement of inbreeding, whereas the second model included the classical inbreeding coefficients and one alternative inbreeding coefficient. The third model included the classical inbreeding coefficients, the interaction between classical inbreeding and ancestral inbreeding, and the classical inbreeding coefficients of the dam. Phenotypic data for this study were collected from February 1998 to December 2008 on three large commercial milk farms. During this time, 36,477 calving events were recorded. All calves were weighed after birth, and 8.08% of the calves died within 48 h after calving. Calving ease was recorded on a scale between 1 and 4 (1 = easy birth, 4 = surgery), and 69.95, 20.91, 8.92 and 0.21% of the calvings were scored with 1, 2, 3 and 4, respectively. The average inbreeding coefficient of inbred animals was 0.03, and average ancestral inbreeding coefficients were 0.08 and 0.01, depending on how ancestral inbreeding was calculated. Approximately 26% of classically non-inbred animals showed ancestral inbreeding. Correlations between different inbreeding coefficients ranged between 0.46 and 0.99. No significant effect of ancestral inbreeding was found for calving ease, because the number of animals with reasonable high level of ancestral inbreeding was too low. Significant effects of ancestral inbreeding were estimated for birthweight and stillbirth. Unfavourable effects of ancestral inbreeding were observed for birthweight. However, favourable purging effects were estimated for stillbirth, indicating that purging could be partly beneficial for genetic improvement of stillbirth.

Over the last decades, a dramatic decrease in reproductive performance has been observed in Holstein cattle and fertility problems have become the most common reason for a cow to leave the herd. The premature removal of animals with high breeding values results in both economic and breeding losses. For efficient future Holstein breeding, the identification of loci associated with low fertility is of major interest and thus constitutes the aim of this study. To reach this aim, a genome-wide combined linkage disequilibrium and linkage analysis (cLDLA) was conducted using data on the following 10 calving and fertility traits in the form of estimated breeding values: days from first service to conception of heifers and cows, nonreturn rate on d 56 of heifers and cows, days from calving to first insemination, days open, paternal and maternal calving ease, paternal and maternal stillbirth. The animal data set contained 2,527 daughter-proven Holstein bulls from Germany that were genotyped with Illumina's BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). For the cLDLA, 41,635 sliding windows of 40 adjacent single nucleotide polymorphisms (SNP) were used. At each window midpoint, a variance component analysis was executed using ASReml. The underlying mixed linear model included random quantitative trait locus (QTL) and polygenic effects. We identified 50 genome-wide significant QTL. The most significant peak was detected for direct calving ease at 59,179,424 bp on chromosome 18 (BTA18). Next, a mixed-linear model association (MLMA) analysis was conducted. A comparison of the cLDLA and MLMA results with special regard to BTA18 showed that the genome-wide most significant SNP from the MLMA was associated with the same trait and located on the same chromosome at 57,589,121 bp (i.e., about 1.5 Mb apart from the cLDLA peak). The results of 5 different cLDLA and 2 MLMA models, which included the fixed effects of either SNP or haplotypes, suggested that the cLDLA method outperformed the MLMA in accuracy and precision. The haplotype-based cLDLA method allowed for a more precise mapping and the definition of ancestral and derived QTL alleles, both of which are essential for the detection of underlying quantitative trait nucleotides.