In 2 epidemiological studies, we evaluated the effect of mastitis induced by gram-positive Streptococcus and gram-negative Escherichia coli on impaired reproductive performance in lactating Holstein cows. In the first study, 52,202 cows from 178 dairy farms throughout Israel were divided into groups based on infection before first artificial insemination (AI) with Streptococcus or E. coli, 3 groups with elevated somatic cell count (SCC) without infection by those pathogens [low SCC (200-400) × 103 cell/mL; medium SCC (401-1,000) × 103 cell/mL; high SCC, >1,000 × 103 cell/mL], and uninfected controls. Pregnancy per first AI (P/1stAI) and pregnancy rate at 300 d in milk (PREG 300) were analyzed by the GLIMMIX procedure (SAS); number of AI per pregnancy (AI/P), days open, and rest days (calving to first AI) were analyzed by the MIXED procedure (SAS Institute Inc., Cary, NC). Values of P/1stAI were similarly low for Streptococcus and E. coli (27-28%) versus 42% in controls; PREG 300 was lower for Streptococcus (76%) than for E. coli (79%) versus 88% for uninfected controls and a mean 83% for the elevated SCC groups. Days open and number of AI/P were higher than in controls and similar in Streptococcus and E. coli groups. The second study included 778 cows on 6 dairy farms; the cows were infected before first AI by Streptococcus or E. coli or uninfected. Resumption of cyclicity was determined by an automated activity-monitoring system, and data were sorted by time of infection before or after cyclicity resumed. The Streptococcus group had lower P/1stAI before and after cyclicity (26 and 27%, respectively) than the E. coli group (31 and 34%, respectively) and uninfected controls (42%). Notably, PREG 300 in the Streptococcus group before (73%) and after (67%) cyclicity was much lower than for the E. coli group (85 and 93%, respectively) and the controls (95%). A marked rise in day of cyclicity resumption (∼80 d) was observed in cows that were infected early on. Number of AI/P was higher in the mastitic groups than in uninfected controls. Uterine disease postpartum, although more prevalent among Streptococcus cows, did not substantially alter the larger reduction in P/1stAI and PREG 300 in Streptococcus versus E. coli cows. Thus, long-term Streptococcus-induced mastitis disrupted fertility more than short-term acute E. coli-induced mastitis, resulting in a much higher percentage of Streptococcus cows in late lactation that did not conceive due to reproduction failure.

Genomic evaluation has been successfully implemented in the United States, Canada, Great Britain, Ireland, New Zealand, Australia, France, the Netherlands, Germany, and the Scandinavian countries. Adoption of this technology in the major dairy producing countries has led to significant changes in the worldwide dairy industry. Gradual elimination of the progeny test system has led to a reduction in the number of sires with daughter records and fewer genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of “single-step” methodologies. Although genomic selection has been successful in increasing rates of genetic gain, we still know very little about the genetic architecture of quantitative variation. Apparently, a very large number of genes affect nearly all economic traits, in accordance with the infinitesimal model for quantitative traits. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and on environmentally friendly production with reduced waste and gas emission. Genetic variance for economic traits is maintained by the increase in frequency of rare alleles, new mutations, and changes in selection goals and management. Thus, it is unlikely that a selection plateau will be reached in the near future.

Given the day-to-day variation in milk components, especially fat, the standard DHIA procedure of measuring milk components in just 1 milking per month, may not be very representative of total production. The combination of much more frequently, but less accurately analyzed milk components, may be more representative of a cow's longer-term milk composition. The AfiLab system (Afimilk, Kibbutz Afikim, Israel) is a real-time individual cow milk analyzer that uses near-infrared spectroscopy for on-line milk analysis. AfiLab records for milk production and fat and protein concentration collected from January 2014 through January 2016 from 47 large Kibbutz (communal) herds distributed throughout Israel with a total of 37,486 Israeli Holstein cows were compared with the same statistics derived from monthly test day records derived by Bentley and Foss milk analyzers at the central laboratory of the Israel Cattle Breeders Association (ICBA). The SD for first and second parity daily records scored by the ICBA and AfiLab system were very similar for all traits, except for fat percentage. The SD for complete lactation production were slightly lower for the AfiLab results for all traits, except protein production. The lactation means for all traits were quite similar by the two methods in both parities, except for fat production, which was higher for the ICBA records. This corresponds to the fat lactation curves, which show that the ICBA results were higher with low DIM, but nearly equal to the AfiLab results after 125 DIM. AfiLab overestimated protein percentage before 150 DIM, and underestimated protein percentage in the second half of the lactation. First parity heritabilities (see table) were higher for AfiLab lactations for all traits, except for protein percentage. For AfiLab records, coefficients of determination to predict future lactation production from truncated lactations were greatest and root mean squared errors were smallest if the mean production from the last 2 wk before the truncation date were used to estimate future production. AfiLab first parity partial lactations with < 150 DIM predicted future lactation more accurately than the corresponding ICBA partial lactations. With only 30 DIM, genetic correlations between predicated and actual lactations ranged from 0.73 to 0.79 for the 3 traits. Further study is required to compare results of individual cows on multiple lactations, and to determine the optimum interval between calibrations for AfiLab meters.

Although it now standard practice to genotype thousands of female calves, genotyping of bull calves is generally limited to progeny of elite cows. In addition to genotyping costs, increasing the pool of candidate sires requires purchase, isolation, and identification of calves until selection decisions are made. We economically optimized via simulation a genomic breeding program for a population of approximately 120,000 milk-recorded cows, corresponding to the Israeli Holstein population. All 30,000 heifers and 60,000 older cows of parities 1 to 3 were potential bull dams. Animals were assumed to have genetic evaluations for a trait with heritability of 0.25 derived by an animal model evaluation of the population. Only bull calves were assumed to be genotyped. A pseudo-phenotype corresponding to each animal's genetic evaluation was generated, consisting of the animal's genetic value plus a residual with variance set to obtain the assumed reliability for each group of animals. Between 4 and 15 bulls and between 200 and 27,000 cows with the highest pseudo-phenotypes were selected as candidate bull parents. For all progeny of the founder animals, genetic values were simulated as the mean of the parental values plus a Mendelian sampling effect with variance of 0.5. A probability of 0.3 for a healthy bull calf per mating, and a genomic reliability of 0.43 were assumed. The 40 bull calves with the highest genomic evaluations were selected for general service for 1 yr. Costs included genotyping of candidate bulls and their dams, purchase of the calves from the farmers, and identification. Costs of raising culled calves were partially recovered by resale for beef. Annual costs were estimated as $10,922 + $305 × candidate bulls. Nominal profit per cow per genetic standard deviation was $106. Economic optimum with a discount rate of 5%, first returns after 4 yr, and a profit horizon of 15 yr were obtained with genotyping 1,620 to 1,750 calves for all numbers of bull sires. However, 95% of the optimal profit can be achieved with only 240 to 300 calves. The higher reliabilities achieved through addition of genomic information to the selection process contribute not only in obtaining higher genetic gain, but also in obtaining higher absolute profits. In addition, the optimal profits are obtained for a lower number of calves born in each generation. Inbreeding, as allowed within genomic selection for the Israeli herd, had virtually no effect on genetic gain or on profits, when compared with the case of exclusion of all matings that generate inbreeding. Annual response to selection ranged from 0.35 to 0.4 genetic standard deviation for 4 to 15 bull sires, as compared with 0.25 to 0.3 for a comparable half-sib design without genomic selection.

The objective was to test the hypothesis that more frequent but less accurately analyzed milk components may give a more representative measure of a cow’s total lactation production. Daily records for milk production and fat and protein concentration collected by the AfiLab recording system (Afimilk, Kibbutz Afikim, Israel) from January 2014 to January 2016 from 47 large kibbutz (communal) herds distributed throughout Israel with a total of 37,486 Israeli Holstein cows were compared with the same statistics derived from monthly test day records derived by Bentley and Foss milk analyzers at the central laboratory of the Israel Cattle Breeders Association. The lactation means for all traits were quite similar for the 2 methods in both parities, except for fat production, which was lower for the daily records. This finding corresponded to fat lactation curves, which showed that daily results were lower with low days in milk (DIM) but almost equal to the monthly results after 125 DIM. Relative to monthly records, daily records overestimated protein percentage before 150 DIM and underestimated protein percentage in the second half of the lactation. The standard deviation for first- and second-parity daily records scored by the monthly and daily system were least similar for fat percentage, but even for this trait the difference was no more than 0.1 percentage points. The standard deviations for complete lactation production were slightly lower for the daily results for all traits but protein production. First-parity heritabilities were higher for lactations computed from daily records for all traits except for protein percentage, but differences were not significant. For daily records, coefficients of determination to predict future milk, fat, and protein lactation production from truncated lactations were greatest and root mean squared errors were least if the mean production from the last 2 weeks before the truncation date was used to estimate future production. Daily first-parity partial lactations for milk, fat, and protein production with <150 DIM predicted future lactation more accurately than corresponding monthly partial lactations. With only 30 DIM, genetic correlations between predicted and actual lactations ranged from 0.73 to 0.79 for milk, fat, and protein production. Real-time daily recording of fat and protein concentration by the daily recording system may be preferable to monthly analysis for herd-management decisions and genetic evaluation. Further study is required to compare the results of individual cows in multiple lactations.

A total of 1922 first generation crossbred cows born between 2005 and 2012 produced by inseminating purebred Israeli Holstein cows with Norwegian Red semen, and 7487 purebred Israeli Holstein cows of the same age in the same 50 herds were analyzed for production, calving traits, fertility, calving diseases, body condition score, abortion rate and survival under intensive commercial management conditions. Holstein cows were higher than crossbreds for 305-day milk, fat and protein production. Differences were 764, 1244, 1231 for kg milk; 23.4, 37.4, 35.6 for kg fat, and 16.7, 29.8, 29.8 for kg protein; for parities 1 through 3. Differences for fat concentration were not significant; while crossbred cows were higher for protein concentration by 0.06% to 0.08%. Differences for somatic cells counts were not significant. Milk production persistency was higher for Holstein cows by 5, 8.3 and 8% in parities 1 through 3. Crossbred cows were higher for conception status by 3.1, 3.6 and 4.7% in parities 1 through 3. Rates of metritis for Holsteins were higher than the crossbred cows by 7.8, 4.6 and 3.4% in parities 1 to 3. Differences for incidence of abortion, dystocia, ketosis and milk fever were not significant. Holstein cows were lower than crossbred cows for body condition score for all three parities, with differences of 0.2 to 0.4 units. Contrary to comparisons in other countries, herd-life was higher for Holsteins by 79 days. A total of 6321 Holstein cows born between 2007 and 2011 were higher than 765 progeny of crossbred cows backcrossed to Israeli Holsteins of the same ages for milk, fat and protein production. Differences were 279, 537, 542 kg milk; 10.5, 17.7, 17.0 kg fat and 6.2, 12.9, 13.2 kg protein for parities 1 through 3. Differences for fat concentration were not significant, while backcross cows were higher for protein percentage by 0.02% to 0.04%. The differences for somatic cell score, conception rate, and calving diseases other than metritis, were not significant. Holstein cows were lower than backcross cows by 1.5% to 2.5% for conception status in parities 1 to 3 and lower for body condition score for parities 1 and 2, with differences in the range of 0.06 to 0.09 units. Culling rates were higher, and herd-life lower for the crossbred cows. The gains obtained in secondary traits for crossbred cows did not compensate for the major reduction in production.

Mastitis, particularly in its subclinical form, is a widely spread disease that reduces the fertility of lactating cows.A major cause of poor conception risk has been associated with delayed ovulation of a large subgroup of subclinical mastitic cows.This study examined 2 approaches to improve fertility in this subgroup.Subclinical mastitic cows were defined by somatic cell count elevated above a threshold of 150,000 cells/mL of milk determined in all monthly test day samples collected before AI.Uninfected (control) cows were defined by somatic cell count below threshold.In experiment 1, we examined a hormonal approach aimed to correct the timing of ovulation in mastitic cows in which it would otherwise be delayed.The probability of conception of mastitic and uninfected groups following Ovsynch (OVS) and timed AI versus AI following detected estrus (E) was examined (n = 1,553 AI) and analyzed by a multivariable, logistic model statement using the GLIMMIX procedure of SAS.The OVS protocol significantly elevated the probability of conception of mastitic cows to a level similar to that of their uninfected counterparts.Actual mean conception risks for uninfected-E, subclinical-E, uninfected-OVS, and subclinical-OVS groups were 41.8, 26.4,39.3, and 40.5%, respectively.The OVS protocol did not improve probability of conception in cows diagnosed with uterine disease postpartum.In experiment 2, a management approach aimed to better synchronize timing of ovulation with timing of AI in subclinical mastitic cows was examined.A second AI was added 24 h after the first (routine) AI, following detection of natural estrus.Probability of conception did not differ between subclinical mastitic cows inseminated once or twice.Lack of improvement in conception risk might be related to low preovulatory LH surge in mastitic cows, which is likely to induce not only delayed ovulation but also disruption of oocyte maturation.Thus the OVS protocol can improve fertility of subclinical mastitic cows, probably due to "corrected" timing of ovulation in cows in which it would otherwise be delayed.

The objectives were to investigate the effects of various environmental factors that may affect herd-life of Israeli Holsteins, including first-calving age and season, calving ease, number of progeny born, and service sire for first calving in complete and truncated records; and to estimate heritabilities and genetic correlations between herd-life and the other traits included in the Israeli breeding index. The basic data set consisted of 590,869 cows in milk recording herds with first freshening day between 1985 and at least 8 yr before the cut-off date of September 15, 2013. Herd-life was measured as days from first calving to culling. The phenotypic and genetic trends for herd-life were 5.7 and 16.8 d/yr. The genetic trend was almost linear, whereas the phenotypic trend showed 4 peaks and 3 valleys. Cows born in February and March had the shortest herd-life, whereas cows born in September had the longest herd-life. Herd-life was maximal with calving age of 23 mo, which is 1 mo less than the mean calving age, and minimal at 19 and 31 mo of calving age. Dystocia and twinning on first-parity calving reduced herd-life by approximately180 and 120 d, but the interaction effect increased herd-life by 140 d. Heritability for herd-life was 0.14. Despite the fact that the service sire effect was significant in the fixed model analysis, service sire effect accounted for <0.05% of the total variance. In the analysis of 1,431,938 truncated records, the effects of dystocia and twinning rate were very similar but less than 50% of the effects found in the analysis of complete records. Pregnancy at the truncation date increased expected herd-life by 432 d. The correlation between actual herd-life and predicted herd-life based on truncated records was 0.44. Genetic correlations between the truncated records and actual herd-life were 0.75 for records truncated after 6 mo but approached unity for records truncated after 3 yr. The genetic correlations of herd-life with first-parity milk, fat, and protein production, somatic cell score (SCS), and female fertility were all positive, except for SCS, in which negative values are economically favorable. The highest correlations with herd-life in absolute value were with female fertility and SCS.

The objectives were to investigate the accuracy of genomic evaluations obtained for a small dairy cattle population (Israeli Holsteins) via joint evaluation with a larger population (Dutch Holsteins), and to evaluate the use of pedigree data from foreign bulls computed by Interbull without daughter records in Israel. The training population included 4,010 Dutch bulls and 713 Israeli bulls. The validation population included 185 Israeli bulls with daughter records for milk production traits and slightly fewer bulls for the nonproduction traits. Milk, fat, and protein yields, somatic cell score, longevity, female fertility, direct and maternal calving ease, direct and maternal stillbirth, and the Israeli breeding index were analyzed. The genomic prediction model was based on the Bayesian multi-QTL model of Meuwissen and Goddard, where the effects of dense single nucleotide polymorphisms across the whole genome are fitted directly, without the use of haplotypes or identical-by-descent probabilities. Correlations of May 2014 estimated breeding values (EBV14) with genomic EBV (GEBV) were higher than the correlations of EBV14 with parent averages (PA) computed from the June 2009 evaluation for all traits. For the Israel selection index, the difference between EBV14 and GEBV correlation on the one hand and EBV14 and PA computed using Interbull data on the other hand was 15 percentage points. For protein, the difference between the corresponding correlations was 14 percentage points. Generally, correlations of EBV14 with PA based on Israeli EBV only were similar to correlations of EBV14 with PA including Interbull evaluations. Relative to EBV14, milk production traits were biased upwards for both GEBV and PA, but the bias was greater for PA. The Y-intercepts of regressions of EBV14 were significantly different from zero for regression on GEBV for all 3 milk production traits and the Israeli selection index. This was not the case for regression of EBV14 on PA. The regression line intersected with the line of unbiased estimation near the EBV of the bulls with highest values. Because only bulls with high evaluations are of interest for selection, GEBV for these bulls were less biased compared with that of bulls with lower evaluations. The difference in mean EBV14 between bulls born during 2007-2008 selected by GEBV and PA was 65 units. If half of all inseminations are by young bulls, then the annual genetic gain obtained by implementation of genomic evaluation will be 8 units per year (65/8). Because annual gain is currently 107 units, this is a gain of 7%.

Five alternative models were applied for analysis of dystocia and stillbirth in first and second parities. Models 1 and 2 were included only to estimate the parameters required for model 4, and models 3 and 5 are included only as comparisons to the model 4 estimates. Variance components were estimated by multi-trait REML, including cows with valid calving records for both parities. For the effects of sire of calf on first and second parities, variance components were estimated including only calvings with the same sire of calf for both parities. All heritabilities for the cow effect were quite low, but higher for dystocia than for stillbirth and higher in first parity. The sire-of-calf heritabilities were higher than the cow effect heritabilities, except for stillbirth in parity 2. Unlike the effect of cow correlations, all sire of calf correlations were >0.6, and the correlations for the same trait in parities 1 and 2 were >0.9. Thus, a multi-trait analysis should yield a significant gain in accuracy with respect to the sire of calf effects for bulls not mated to virgin heifers. A multi-trait individual animal model algorithm was developed for joint analysis of dystocia and stillbirth in first and second parities. Relationships matrices were included both for the effects of cow and sire of calf. In addition, random herd-year-season and fixed sex of calf effects were included in the model. Records were preadjusted for calving month and age. A total of 899,223 Israeli Holstein cows with first calvings since 1985 were included in the complete analysis. Approximate reliabilities were computed for both sire of cow and sire of calf effects. Correlations between these reliabilities and reliabilities obtained by direct inversion of the coefficient matrix for a sire of cow-sire of calf model were all close to 0.99. Phenotypic trends for cows born from 1983 through 2007 were economically unfavorable for dystocia and favorable for stillbirth in both parities. Genetic trends were economically unfavorable for both dystocia and stillbirth in first parity. First-parity sire of calf trends were unfavorable for dystocia, but favorable for stillbirth. All environmental trends were nearly zero. Regressions of evaluations of the complete analysis on a model including only calvings before 2011 were all >0.8. All evaluations met the Interbull Method 3 criterion for unbiasedness. Model 4, which computed genetic evaluations for all animals for all 4 traits accounting for all known relationships and correlations among the traits, is recommended for routine genetic evaluation of calving traits.

Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R(2)) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R(2) and regression coefficients was observed from parities 1 through 3. Fat and protein yields had the lowest R(2) for all the methods. On average, R(2) was lowest for parent averages, followed by GBLUP, BayesC, ssGBLUP, and WssGBLUP. For some traits, R(2) for direct genomic values from BayesC and GBLUP were lower than those for parent averages. Genomic estimated breeding values using ssGBLUP were the least biased, and this method appears to be a suitable tool for genomic evaluation of a small genotyped population, as it automatically accounts for parental index, allows for inclusion of female genomic information without preadjustments in evaluations, and uses the same model as in traditional evaluations. Weighted ssGBLUP has the potential for higher evaluation accuracy.

Several studies have shown that computation of genomic estimated breeding values (GEBV) with accuracies significantly greater than parent average (PA) estimated breeding values (EBVs) requires genotyping of at least several thousand progeny-tested bulls. For all published analyses, GEBV computed from the selected samples of markers have lower or equal accuracy than GEBV derived on the basis of all valid single nucleotide polymorphisms (SNPs). In the current study, we report on four new methods for selection of markers. Milk, fat, protein, somatic cell score, fertility, persistency, herd life and the Israeli selection index were analyzed. The 972 Israeli Holstein bulls genotyped with EBV for milk production traits computed from daughter records in 2012 were assigned into a training set of 844 bulls with progeny test EBV in 2008, and a validation set of 128 young bulls. Numbers of bulls in the two sets varied slightly among the nonproduction traits. In EFF12, SNPs were first selected for each trait based on the effects of each marker on the bulls' 2012 EBV corrected for effective relationships, as determined by the SNP matrix. EFF08 was the same as EFF12, except that the SNPs were selected on the basis of the 2008 EBV. In DIFmax, the SNPs with the greatest differences in allelic frequency between the bulls in the training and validation sets were selected, whereas in DIFmin the SNPs with the smallest differences were selected. For all methods, the numbers of SNPs retained varied over the range of 300 to 6000. For each trait, except fertility, an optimum number of markers between 800 and 5000 was obtained for EFF12, based on the correlation between the GEBV and current EBV of the validation bulls. For all traits, the difference between the correlation of GEBV and current EBV and the correlation of the PA and current EBV was >0.25. EFF08 was inferior to EFF12, and was generally no better than PA EBV. DIFmax always outperformed DIFmin and generally outperformed EFF08 and PA. Furthermore, GEBV based on DIFmax were generally less biased than PA. It is likely that other methods of SNP selection could improve upon these results.

Based on pairwise identity-by-state (IBS) distances and whole-genome SNP data, kinship was investigated in the Israeli Holstein population. A total of 789 bulls, including most of the artificial insemination sires in service since 1987, were genotyped by the BovineSNP50 BeadChip. This sample included up to five generations. For each bull-by-bull combination, three states are possible for each marker: no match, a single match and both alleles match. Summing over all markers, the 932 598 IBS scores (three match frequencies*310 866 bull-by-bull combinations) were visualized using three-dimensional coordinates that corresponded to the frequencies of the three possible states. Results were reduced to two dimensions using the transformations x' = 0.7071(1 + freq1-freq2) and y' = 1.2247freq0. Bull-by-bull pairs were grouped according to their level of kinship, and canonical scores were calculated using discriminant analysis and the x' and y' features. Of the 474 pairs of recorded maternal grandsire-grandson with both individuals genotyped, the probability for 28 pairs to belong to this level of kinship was low (P < 0.05), suggesting an error rate of around 3% per generation in pedigree determination.

An efficient algorithm for genomic selection of moderately sized populations based on single nucleotide polymorphism chip technology is described. A total of 995 Israeli Holstein bulls with genetic evaluations based on daughter records were genotyped for either the BovineSNP50 BeadChip or the BovineSNP50 v2 BeadChip. Milk, fat, protein, somatic cell score, female fertility, milk production persistency and herd-life were analyzed. The 400 markers with the greatest effects on each trait were first selected based on individual analysis of each marker with the genetic evaluations of the bulls as the dependent variable. The effects of all 400 markers were estimated jointly using a 'cow model,' estimated from the data truncated to exclude lactations with freshening dates after September 2006. Genotype probabilities for each locus were computed for all animals with missing genotypes. In Method I, genetic evaluations were computed by analysis of the truncated data set with the sum of the marker effects subtracted from each record. Genomic estimated breeding values for the young bulls with genotypes, but without daughter records, were then computed as their parent averages combined with the sum of each animal's marker effects. Method II genomic breeding values were computed based on regressions of estimated breeding values of bulls with daughter record on their parent averages, sum of marker effects and birth year. Method II correlations of the current breeding values of young bulls without daughter records in the truncated data set were higher than the correlations of the current breeding values with the parent averages for fat and protein production, persistency and herd-life. Bias of evaluations, estimated as a difference between the mean of current breeding values of the young bulls and their genomic evaluations, was reduced for milk production traits, persistency and herd-life. Bias for milk production traits was slightly negative, as opposed to the positive bias of parent averages. Correlations of Method II with the means of daughter records adjusted for fixed effects were higher than parent averages for fat, protein, fertility, persistency and herd-life. Reducing the number of markers included in the analysis from 400 to 300 did not reduce correlations of genomic breeding values for protein with current breeding values, but did slightly reduce correlations with means of daughter records. Method II has the advantages as compared with the method of VanRaden in that genotypes of cows can be readily incorporated into the Method II analysis, and it is more effective for moderately sized populations.

Strong selection in the Israeli Holstein dairy cattle population over the last three decades should have left clear signatures of selection. Two experimental approaches were applied to detect evidence of contemporary selection based on the 54K BeadChip genotypes of 1000 Israeli Holstein bulls: (i) the long-range haplotype test, which searches for structural evidence resulting from selective sweep, and (ii) direct analysis of the changes in haplotypes frequencies over time combined with linkage disequilibrium blocks haplotype-based association analysis. Ten traits were analyzed: the PD07 Israeli selection index, milk, milk fat, % fat, milk protein, % protein, somatic cell score, female fertility, milk production persistency and herd life. The long-range haplotype test detected 15% of the 3288 haplotypes that showed significant positive frequency trends (P<0.05) and was significantly correlated with the substitution effects of the haplotypes and the selection intensities for the different traits. Thirty signatures of recent selection, which correspond to both approaches and affect the Israeli PD07 selection index, were identified on 17 of the 29 autosomes. The second experimental approach also was used to estimate the selection intensity of the different traits. The correlation between the selection intensities for the traits analyzed, derived from changes in haplotype frequencies in the population of bulls, and those derived from trait-based analysis of the cow population was 0.93 over all traits. Thus, the changes in haplotypes frequencies in the bulls population accurately estimate genetic trends in the general cow population and can be used to detect signatures of recent selection.

Paratuberculosis (Johne's disease) is an infectious enteric disease in dairy cattle and other species that causes substantial economic loss worldwide. In this study, two recursive Gaussian-threshold models were employed in order to infer the effects of Johne's disease on milk yield, fat yield, and protein yield while simultaneously estimating genetic parameters (i.e. heritability and genetic correlation) in an Israeli Holstein population. Disease diagnosis was based on ELISA serum antibody tests. Data were available for 4694 daughters of 361 sires; 3.5% were positive; and 1.6% were suspect for the disease test. Disease status was coded either as a binary character (negative vs. positive) or as an ordered categorical trait (negative, suspect, and positive) in the two recursive models and as a binary trait in a linear model. Among sires with ≥ 50 daughters, predicted probability of Mycobacterium avium ssp. paratuberculosis (MAP) infection in future daughters ranged from <1% to 16.5%. Heritability estimates for Johne's disease were near 0.15, confirming a genetic contribution to disease susceptibility. Genetic correlation estimates for Johne's disease with the three yield traits were 0.15-0.22. Residual correlations for Johne's disease with the yield traits were between -0.01 and -0.10. For the linear regression model, yield losses associated with a positive disease diagnosis during 305 days of lactation were 300 kg milk and around 10 kg for fat and protein. Yield loss estimates from the recursive models were 25-50% less than linear model estimates. Recursive modeling has theoretical advantages over linear models for these phenotypes, but the estimated genetic parameters in this study did not differ significantly between the two types of models.

The aim was to evaluate the effects of mastitis, determined by the pattern and level of somatic cell count (SCC) around first artificial insemination (AI), on conception rate (CR). Data from 287,192 first AI and milk records covering a 7-yr period were obtained from the Israeli Herd Book. Analyses examined the association of probability of conception with SCC elevation relative to timing of AI, using generalized linear mixed models. A SCC threshold of 150,000 cells/mL of milk was set to distinguish between uninfected cows and cows with mastitis. Accordingly, cows with high SCC before and low SCC after AI were designated cured, those with low SCC before and high SCC after AI were designated newly infected, and cows with high SCC before and after AI were designated chronic (likely subclinical) mastitic cows. Compared with uninfected cows, the cured, newly infected, and chronic subgroups showed reduced CR (39.4±0.1, 36.6±0.2, 32.9±0.3, and 31.5±0.2, respectively). In the chronic, subclinical group, probability of conception was lowered by 14.5% in the mild and moderately elevated SCC subgroups and by 20.5% in cows with high SCC elevation compared with the uninfected group (CR of 29.7 vs. 39.4%, respectively). A single high elevation of SCC (>10(6) cells/mL on only 1 milk test day) lowered the probability of conception by 23.6% when it occurred during the 10 d immediately before AI, but not when it occurred earlier. For 30 d after AI, probability of conception was lowered by about 23%, as reflected in a CR of about 27% compared with the uninfected group. Probability of conception was lowered in cows with uterine and foot health problems (33.9%), in multiparous cows (34.1%), and in cows in the summer (29.1%), but no interactions with mastitis were detected. Results indicate that SCC elevation around AI, typical for subclinical mastitis, was associated with a significant reduction in probability of conception, and that even mild SCC elevation reduced CR. Severe elevation of SCC before AI, typical for clinical intramammary infection, reduced the probability of conception.

A single nucleotide polymorphism in the intergenic region upstream of the ZNF496 gene on Bos taurus chromosome 7 displayed significant population-wide linkage disequilibrium with milk protein percentage in the Israeli Holstein population. The frequency of the allele associated with increased protein concentration was 10%. This single nucleotide polymorphism was located in the promoter region from which a 10-exon transcript of the bovine and the ovine ZNF496 genes are transcribed. The gene architecture was similar to the mouse ortholog Zkscan17. A 5-exon murine antisense transcript was complementary to the 5' untranslated Zkscan17 region that included a sequence domain conserved between mouse and ruminants, suggesting a regulatory function. In the bovine ZNF496 chromosomal region, segregation of a quantitative trait locus (QTL) for milk protein percentage was confirmed in a daughter design sire family. Concordance was not obtained between QTL status of bulls and any of the polymorphisms in the functional elements of ZNF496. This excludes these variations as the causative polymorphism under the assumption of no epigenetic effect for this locus. However, ZNF496 variants were differentially expressed in bovine ovaries, and only the paternal variant was expressed in liver and kidney in a sheep family with polymorphic ZNF496 sequence. Thus, the search for the mutation underlying the minor QTL allele, which is a top economically favorable allele in Israeli Holstein cattle, may be complicated by the presence of an imprinting center in this QTL confidence interval.

Summary Incorrect paternity assignment in cattle can have a major effect on rates of genetic gain. Of the 576 Israeli Holstein bulls genotyped by the BovineSNP50 BeadChip, there were 204 bulls for which the father was also genotyped. The results of 38 828 valid single nucleotide polymorphisms (SNPs) were used to validate paternity, determine the genotyping error rates and determine criteria enabling deletion of defective SNPs from further analysis. Based on the criterion of >2% conflicts between the genotype of the putative sire and son, paternity was rejected for seven bulls (3.5%). The remaining bulls had fewer conflicts by one or two orders of magnitude. Excluding these seven bulls, all other discrepancies between sire and son genotypes are assumed to be caused by genotyping mistakes. The frequency of discrepancies was >0.07 for nine SNPs, and >0.025 for 81 SNPs. The overall frequency of discrepancies was reduced from 0.00017 to 0.00010 after deletion of these 81 SNPs, and the total expected fraction of genotyping errors was estimated to be 0.05%. Paternity of bulls that are genotyped for genomic selection may be verified or traced against candidate sires at virtually no additional cost.