Comparison of dairy beef genetics and dietary roughage levels

The objectives of these trials were to investigate the performance of Jersey steers in relation to Holsteins under current management practices when fed diets differing in energy density and subsequent effects on carcass characteristics. In experiment 1, twelve Jersey and 12 Holstein steers were offered dietary treatments with differing roughage levels. Roughage levels investigated on a dry matter basis were 55% reduced to 25% versus 25% followed by 12.5% (HIGH and LOW, respectively) with all animals receiving the same finishing diet containing 6.5% roughage. Holstein steers were heavier than Jerseys at the initiation of the trial (228 vs. 116 kg). A diet response was observed for gain efficiency during the first period in which LOW was greater than HIGH. Holstein steers had higher dry matter intakes and rates of gain than Jerseys. However, gain efficiency was better for Jersey steers during the first and last periods. Carcass traits were influenced by breed but not diet. Holsteins had heavier hot carcass weights, greater dressing percentages, more backfat, and larger longissimus muscle area, whereas marbling scores were similar to Jerseys. The increased efficiency of Jersey steers and significant reduction in carcass value due to light carcass weights suggested that Jersey steers should be fed to heavier live weights. Experiment 2 utilized 85 steers to investigate continuous feeding of a low-roughage, high-concentrate diet versus a phase-feeding strategy. Jersey (n = 40) and Holstein (n = 45) steers were assigned to a diet containing 20% corn silage on a dry matter basis (HEN) or a phase-feeding program (PHASE) in which corn silage was reduced from 60 to 40% followed by the same diet as HEN. Initial body weights were similar for dietary treatments but differed by breed. A diet response was observed for live weight at the end of the first and second period, first period average daily gain (ADG), overall ADG, and days on feed with HEN having higher ADG than PHASE and fewer days on feed. Breed affected all body weight and gain variables with Holsteins being heavier and gaining more rapidly than Jersey steers. Jersey carcasses were lighter, had the highest percentage trim loss, least amount of backfat, and lowest numerical yield grade. Holstein steers had a greater propensity for gain, whereas the Jersey steers were equally or more efficient. These findings suggest that phase feeding Jersey steers higher-roughage diets has minimal effect on carcass traits.     

The impact of 3 strategies for incorporating polled genetics into a dairy cattle breeding program on the overall herd genetic merit

Dehorning in cattle has been associated with behavioral, physiological, and neuroendocrine responses indicative of pain. Unaddressed, the pain associated with a routine production procedure could contribute to a negative public perception of livestock production practices. Alternative considerations of dehorning include the selection of polled cattle within herds, thereby avoiding pain and production loss. As polledness results from an autosomal dominant pattern of inheritance, genetic selection for polled cattle could reduce the prevalence of the horned trait. Herein we discuss 3 strategies to incorporate polled genetics into a cow herd and the estimated impact on the overall genetic merit of the herd. Furthermore, the availability and genetic merit of polled artificial insemination bulls in the United States is summarized. Both Holstein and Jersey dairy bulls registered with the National Association of Animal Breeders from December 2010 through April 2013 were queried. Polled bulls were identified as either being homozygous (PP) or heterozygous (Pp) and the average net merit (NM) predicted transmitting ability (PTA) of each sire group was calculated. The percentage of polled calves born each year over a 10-yr period was calculated for the following 3 scenarios: (A) various percentages of horned cows were randomly mated to Pp bulls, (B) various percentages of horned cows were preferentially mated to Pp bulls, and (C) horned cows were selectively mated to PP bulls, heterozygous cows to Pp bulls, and homozygous polled cows to horned bulls. Additionally, the change in NM PTA of the cow herd was calculated over the same period. The highest percentage of polled animals (87%) was achieved in scenario C. An evaluation of the herd NM PTA highlights the trade-offs associated with increasing polled genetics. Given the current genetic merit of horned and polled bulls, increasing the percentage of polled calves will decrease the NM PTA in Holstein, but may have minimal impact in Jersey herds. Decisions regarding selective breeding to increase polled genetics will need to be evaluated in the context of production objectives, cost of dehorning, and impact on overall genetic merit.     

Application of single-step genomic evaluation using multiple-trait random regression test-day models in dairy cattle

Test-day traits are important for genetic evaluation in dairy cattle and are better modeled by multiple-trait random regression models (RRM). The reliability and bias of genomic estimated breeding values (GEBV) predicted using multiple-trait RRM via single-step genomic best linear unbiased prediction (ssGBLUP) were investigated in the 3 major dairy cattle breeds in Canada (i.e., Ayrshire, Holstein, and Jersey). Individual additive genomic random regression coefficients for the test-day traits were predicted using 2 multiple-trait RRM: (1) one for milk, fat, and protein yields in the first, second, and third lactations, and (2) one for somatic cell score in the first, second, and third lactations. The predicted coefficients were used to derive GEBV for each lactation day and, subsequently, the daily GEBV were compared with traditional daily parent averages obtained by BLUP. To ensure compatibility between pedigree and genomic information for genotyped animals, different scaling factors for combining the inverse of genomic (G^?1) and pedigree (A^?1₂₂) relationship matrices were tested. In addition, the inclusion of only genotypes from animals with accurate breeding values (defined in preliminary analysis) was compared with the inclusion of all available genotypes in the analyzes. The ssGBLUP model led to considerably larger validation reliabilities than the BLUP model without genomic information. In general, scaling factors used to combine the G^?1 and A^?1₂₂ matrices had small influence on the validation reliabilities. However, a greater effect was observed in the inflation of GEBV. Less inflated GEBV were obtained by the ssGBLUP compared with the parent average from traditional BLUP when using optimal scaling factors to combine the G^?1 and A^?1₂₂ matrices. Similar results were observed when including either all available genotypes or only genotypes from animals with accurate breeding values. These findings indicate that ssGBLUP using multiple-trait RRM increases reliability and reduces bias of breeding values of young animals when compared with parent average from traditional BLUP in the Canadian Ayrshire, Holstein, and Jersey breeds.     

Economic considerations of breeding for polled dairy cows versus dehorning in the United States

This paper examines the costs and benefits of selecting for polled dairy heifers versus traditional dehorning practices. Stochastic budgets were developed to analyze the expected costs (EC) associated with polled dairy genetics. The economic assessment was expanded beyond on-farm cash costs by incorporating cost and benefit estimates to generate industry-wide discussion, and preliminary economic evaluations, surrounding the public acceptance and attitude toward polled genetics versus dehorning calves. Triangular distributions, commonly used to represent distributions with limited data, were used to represent labor costs for dehorning, the likelihood of treatment of calf, and the cost of veterinary treatment. In total, 10,000 iterations were run using @Risk v 6.0 (Palisade Corp., Newfield, NY). The EC of the 4 traditional dehorning methods evaluated in this study ranged from $6 to $25/head, with a mean EC around $12 to $13/head. The EC of incorporating polled genetics into a breeding program ranged from $0 to $26/head depending on the additional cost, or premium, associated with polled relative to horned genetics. Estimated breakeven premiums associated with polled genetics indicate that, on average, producers could spend up to $5.95/head and $11.90/head more for heterozygous and homozygous polled genetics, respectively, compared with conventional horned genetics (or $2.08 and $4.17/straw of semen at an assumed average conception rate of 35%). Given the parameters outlined, sensitivity to individual farm semen and dehorning costs are likely to swamp these differences. Beyond on-farm costs, industry-wide discussion may be warranted surrounding the public's acceptance and attitude toward polled genetics versus dehorning or disbudding of calves. The value of avoiding dehorning may be larger for the industry, and perhaps some individual farms, than initially suggested if additional value is put on calf comfort and possible worker aversion to dehorning. If public perception of dehorning influences market access, the EC of dehorning may be large but that cost is unknown at present.     

Optimization of a genomic breeding program for a moderately sized dairy cattle population

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.     

Short communication: Phenotypic and genetic effects of the polled haplotype on yield,longevity, and fertility in US Brown Swiss,Holstein, and Jersey cattle

Phenotypes from the December 2018 US national genetic evaluations were used to compute effects of the polled haplotype in US Brown Swiss (BS), Holstein (HO), and Jersey (JE) cattle on milk, fat, and protein yields, somatic cell score, single-trait productive life, daughter pregnancy rate, heifer conception rate, and cow conception rate. Lactation records pre-adjusted for nongenetic factors and direct genomic values were used to estimate phenotypic and genetic effects of the polled haplotype, respectively. No phenotypic or direct genomic values effects were different from zero for any trait in any breed. Genomic PTA (gPTA) for the lifetime net merit (NM$) selection index of bulls born since January 1, 2012, that received a marketing code from the National Association of Animal Breeders (Madison, WI), and cows born on or after January 1, 2015, were compared to determine whether there was a systematic benefit to polled or horned genetics. Horned bulls had the highest average gPTA for NM$ in all 3 breeds, but that difference was significant only in HO and JE (HO: 615.4 ± 1.9, JE: 402.3 ± 3.4). Homozygous polled BS cows had significantly higher average gPTA for NM$ than their heterozygous polled or horned contemporaries (PP = 261.4 ± 43.5, Pp = 166.1 ± 13.7, pp = 174.1 ± 1.8), but the sample size was very small (n = 9). In HO and JE, horned cows had higher gPTA for NM$ (HO = 378.3 ± 0.2, JE = 283.3 ± 0.3). Selection for polled cattle should not have a detrimental effect on yield, fertility, or longevity, but these differences show that, in the short term, selection for polled over horned cattle will result in lower rates of genetic gain.     

Association of the OLR1 gene with milk composition in Holstein dairy cattle

Oxidized low-density lipoprotein receptor (OLR1) is the major protein that binds, internalizes, and degrades oxidized low-density lipoprotein. The role of OLR1 in lipid metabolism and the results of previous whole-genome scan studies prompted the investigation of OLR1 as a candidate gene affecting milk composition traits. Direct cDNA and genomic sequencing of OLR1 revealed 2 single nucleotide polymorphisms (SNP) in exon 4, 5 SNP in intron 4, and 1 in the 3′ untranslated region (UTR). Four intragenic haplotypes comprising SNP positions 7,160, 7,161, 7,278, 7,381, 7,409, 7,438, 7,512, and 8,232 were inferred. Haplotype analysis showed that one of the haplotypes was associated with a significant increase in fat yield and fat percentage. Single SNP analysis showed that allele C of SNP 8,232 (in the 3′-UTR) had significant effects on fat yield and fat percentage, whereas SNP 7,160 and 7,161 (in exon 4) had no significant effects. Both single SNP and haplotype analyses indicate that SNP 8,232 in the 3′-UTR is associated with milk fat yield and percentage and it may be in linkage disequilibrium with the functional polymorphism. To provide support for the hypothesis that SNP 8,232 is responsible for OLR1 expression, OLR1 expression levels in individuals bearing different genotypes were assessed. It was found that OLR1 expression was reduced in genotype AA individuals compared with CC and AC individuals, suggesting that A at position 8,232 may be the nucleotide causing decreased OLR1 expression. The 3′-UTR polymorphism found in this study might control translation or stability of OLR1 mRNA.     

Quantitative trait loci mapping of functional traits in the German Holstein cattle population

A whole-genome scan to detect quantitative trait loci (QTL) for functional traits was performed in the German Holstein cattle population. For this purpose, 263 genetic markers across all autosomes and the pseudoautosomal region of the sex chromosomes were genotyped in 16 granddaughter-design families with 872 sons. The traits investigated were deregressed breedingvalues for maternal and direct effects on dystocia (DYSm, DYSd) and stillbirth (STIm, STId) as well as maternal and paternal effects on nonreturn rates of 90 d (NR90m, NR90p). Furthermore, deregressed breeding values for functional herd life (FHL) and daughter yield deviation for somatic cell count (SCC) were investigated. Weighted multimarker regression analyses across families and permutation tests were applied for the detection of QTL and the calculation of statistical significance. A ten percent genomewise significant QTL was localized for DYSm on chromosome 8 and for SCC on chromosome 18. A further 24 putative QTL exceeding the 5% chromosomewise threshold were detected. On chromosomes 7, 8, 10, 18, and X/Yps, coincidence of QTL for several traits was observed. Our results suggest that loci with influence on udder health may also contribute to genetic variance of longevity. Prior to implementation of these QTL in marker assisted selection programs for functional traits, information about direct and correlated effects of these QTL as well as fine mapping of their chromosomal positions is required.     

甜菜线粒体atp6基因RNA编辑位点研究

RNA编辑现象普遍存在于高等植物的线粒体中,是线粒体中产生功能蛋白所不可或缺的加工步骤。以甜菜细胞质雄性不育系DY5-CMS及其保持系DY5-O为材料,通过PCR、RT—PCR以及PCR产物直接测序等方法,对甜菜线粒体atp6基因转录本的RNA编辑位点进行了研究。结果表明,啤而基因转录本的保守区域共有8个编辑位点,均发生在密码子的第一、二位点上,这些位点的编辑将导致氨基酸种类的变化,如第二个编辑位点上发生的由丝氨酸（疏水参数0．8）到亮氨酸（疏水参数3．8）的转变。通过分析可看出atp6基因RNA编辑有着改变蛋白质疏水性的作用。     

Economic evaluation of the breeding goal for Norwegian Red dairy cattle

In this paper, a translog profit function was applied to estimate the economic values of the traits included in the breeding goal for Norwegian Red dairy cattle. The following 10 traits are included in the breeding goal: milk, meat, mastitis resistance, fertility, calving difficulties, stillbirths, other diseases, udder, temperament, and legs. An empirical implementation that locally approximates the unknown true profit function was suggested and estimated, taking farm heterogeneity into account. The model was applied to a panel data set of 3,259 Norwegian dairy farms over the period 1999 to 2003. Panel data, also called longitudinal or cross-sectional time-series data, are multiple cases (cows, farms, countries, etc.) observed over 2 or more time periods. The data set consisted of farm-level data, including production and economic data from the farm and the estimated breeding values for each cow's sire. The estimated economic values make it possible to test whether genetic selection has been profitable for the farmer, and the extent to which the currently used economic values were optimal during the period 1999 to 2003. Although the translog profit function is quite flexible, it is rather complex, and a simplified version of the model, a Cobb-Douglas profit function, was also estimated. However, the hypothesis that this simpler function adequately describes the data compared with the full translog model was rejected. Further, the hypothesis that the estimated breeding values are profit neutral was rejected (i.e., the hypothesis that there are no interactions between input and output prices on one hand and estimated breeding values on the other). These results indicated that selection not only leads to a parallel shift in profits, but also to changes in input use. Seven of the 10 traits had a significant effect on the farmers’ profit. The 3 traits that were not significant were calving difficulty, stillbirth, and other diseases. The results showed that the breeding program for Norwegian Red cattle has been fairly successful in improving farmers’ profits. However, a slight modification of the breeding goal, such as a reduction in the weights for stillbirths and other diseases and an increase in the weights for meat and temperament, would increase farm profits.     

Genetic determination of the onset of heat stress on daily milk production in the US Holstein cattle

Existence of individual variation in the onset of heat stress for daily milk yield of dairy cows was assessed. Data included 353,376 test-day records of 38,383 first-parity Holsteins from a random sample of US herds. Three hierarchical models were investigated. Model 1 inferred the value of a temperature-humidity index (THI) at which mean yield began to decline as well as the extent of that decline. Model 2 assumed individual variation in yield decline beyond a common THI threshold. Model 3 additionally assumed individual variation for the onset of heat stress. Deviance information criteria indicated the superiority of model 3 over model 2. For model 2, genetic correlation between milk yield in the absence of heat stress and the THI threshold for heat stress was −0.4 (0.11) [marginal posterior mean (marginal posterior standard deviation)]. For model 3, genetic correlations were −0.53 (0.05) between milk yield and THI threshold and −0.62 (0.08) between milk yield and yield decay beyond the THI threshold. Total standard deviation (sum of additive genetic and permanent environmental standard deviations) for the THI threshold was 3.95 (0.06), and more than half of that variation had an additive genetic origin [56% (5%)]. Because of the high genetic correlation [0.95 (0.03)] between yield decay and THI threshold with model 3, using only one of them as a selection criterion for heat tolerance would modify the other in the desired direction.     

Statistical modeling of candidate gene effects on milk production traits in dairy cattle

A major objective of dairy cattle genomic research is to identify genes underlying the variability of milk production traits that could be useful in breeding programs. The candidate gene approach provides tools for searching for causative polymorphisms affecting quantitative traits. Genes with a possible effect on milk traits in cattle can be involved in different physiological pathways, such as triglyceride synthesis [acyl-CoA:diacylglycerol acyltransferase 1 gene (DGAT1)], fat secretion from the mammary epithelial tissue (butyrophilin), or entire-body energy homeostasis regulation (leptin and leptin receptor). In this study, based on data from 252 Black and White bulls from the active Polish dairy population, effects and potential interactions of 9 single nucleotide polymorphisms in the butyrophilin, DGAT1, leptin, and leptin receptor genes were investigated. Additionally, the effect of the number of additive, dominance, and epistatic genetic effects fitted into the model on the estimates of model parameters and model selection was illustrated. Phenotypic records were daughter yield deviations for milk, fat, and protein yields, obtained from a routine national genetic evaluation. Out of all the analyzed polymorphisms, DGAT1 K232A had a much larger effect on milk traits than the other single nucleotide polymorphisms considered. Estimates of the additive genetic effect of K232A expressed as half of the difference between Lys- and Ala-encoding variants were −107.4 kg of milk, 5.4 kg of fat, and −1.6 kg of protein at first parity, as well as −120 kg of milk and 6.8 kg of fat at second parity. In terms of model selection, it was demonstrated that the modified version of Bayesian information criterion selects models with the parameterization reflecting the genetic background of the analyzed trait, while the Bayesian information criterion chooses models that are too highly parameterized.     

Optimal strategies for the use of genomic selection in dairy cattle breeding programs

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.     

Underlying genetic architecture of resistance to mastitis in dairy cattle: A systematic review and gene prioritization analysis of genome-wide association studies

Mastitis, the most frequent disease in dairy cattle. Resistance to mastitis is a complex, polygenic trait controlled by several genes, each with small effects. Genome-wide association studies have been widely used to identify genomic variants associated with complex traits, including resistance to mastitis, to elucidate the underlying genetic architecture of the trait. However, no systematic review and gene prioritization analysis have been conducted to date on GWAS results for resistance to mastitis in dairy cattle. Hence, the objective was to perform a systematic review and gene prioritization analysis of GWAS studies to identify potential functional candidate genes associated with resistance to mastitis-related traits in dairy cattle. Four electronic databases were searched from inception to December 2020, supplemented with multiple sources of gray literature, to identify eligible articles. Annotation for genes and quantitative trait loci (QTL), and QTL enrichment analysis were conducted using GALLO. Gene prioritization analysis was performed by a guilty-by-association approach using GUILDify and ToppGene. From 52 articles included within this systematic review, 30 articles were used for further functional analyses. Gene and QTL annotation resulted in 9,125 and 43,646 unique genes and QTL, respectively, from 39 studies. In general, overlapping of genes across studies was very low (mean ± SD = 0.02% ± 0.07%). Most annotated genes were associated with somatic cell count-related traits and the Holstein breed. Within all annotated genes, 74 genes were shared among Holstein, Jersey, and Ayrshire breeds. Approximately 7.5% of annotated QTL were related to QTL class “health.” Within the health QTL class, 2.6 and 2.2% of QTL were associated with clinical mastitis and somatic cell count-related traits. Enrichment analysis of QTL demonstrated that many enriched QTL were associated with somatic cell score located in Bos taurus autosomes 5, 6, 16, and 20. The prioritization analysis resulted in 427 significant genes after multiple test correction (false discovery rate of 5%) from 26 studies. Most prioritized genes were located in Bos taurus autosomes 19 and 7, and most top-ranked genes were from the cytokine superfamily (e.g., chemokines, interleukins, transforming growth factors, and tumor necrosis factor genes). Although most prioritized genes (397) were associated with somatic cell count-related traits, only 54 genes were associated with clinical mastitis-related traits. Twenty-four genes (ABCC9, ACHE, ADCYAP1, ARC, BCL2L1, CDKN1A, EPO, GABBR2, GDNF, GNRHR, IKBKE, JAG1, KCNJ8, KCNQ1, LIFR, MC3R, MYOZ3, NFKB1, OSMR, PPP3CA, PRLR, SHARPIN, SLC1A3, and TNFRSF25) were reported for both somatic cell count and clinical mastitis-related traits. Prioritized genes were mainly associated with immune response, regulation of secretion, locomotion, cell proliferation, and development. In conclusion, this study provided a fine-mapping of previously identified genomic regions associated with resistance to mastitis and identified key functional candidate genes for resistance to mastitis, which can be used to develop enhanced genomic strategies to combat mastitis by increasing mastitis resistance through genetic selection.     

Comparison of performance records and national breeding values as input into international genetic evaluation

The purpose of this investigation was to compare accuracy and precision of variance components and breeding values for international genetic evaluations based on national breeding values or animal performance records. A conventional progeny test scheme was simulated for 3 countries. True breeding values and observations were generated specific to production environments. Two production environments were considered, and both balanced and unbalanced distribution of production environments over countries were considered. True breeding values for both production environments were generated as bivariate normal deviates, and low (0.70) and high (0.90) genetic correlations between performance in production environments were considered. Each cow had an observation in one country only. Performance records were generated as the sum of the true breeding value, a contemporary group effect, and a random residual. Eight generations of data were simulated, and the entire simulated data set was used to compare 3 methods for international genetic evaluation: 1) multiple-trait across-country evaluation based on national predicted breeding values of bulls (Mace), 2) international genetic evaluation across country using performance records, and 3) international genetic evaluation across production environment using performance records. Estimated genetic parameters were biased for all models in this study. Genetic correlations between countries were generally more biased for Mace than for the across-country analyses using performance records. Bias in within-country genetic variances was smaller for Mace. Even genetic parameters obtained with the international evaluation across production environment using performance records were biased, despite the fact that this model was closest to the true, simulated model. The root mean square error of predicted breeding values was similar between models for most of the situations considered. The difference between models was largest when the distribution of production environments over countries was unbalanced and the genetic correlation between performance in production environments was low (0.70). Using breeding values obtained with the across-production environment international genetic evaluation based on performance records will increase the response to selection.     

The effect of using cow genomic information on accuracy and bias of genomic breeding values in a simulated Holstein dairy cattle population

Using cow data in the training population is attractive as a way to mitigate bias due to highly selected training bulls and to implement genomic selection for countries with no or limited proven bull data. However, one potential issue with cow data is a bias due to the preferential treatment. The objectives of this study were to (1) investigate the effect of including cow genotype and phenotype data into the training population on accuracy and bias of genomic predictions and (2) assess the effect of preferential treatment for different proportions of elite cows. First, a 4-pathway Holstein dairy cattle population was simulated for 2 traits with low (0.05) and moderate (0.3) heritability. Then different numbers of cows (0, 2,500, 5,000, 10,000, 15,000, or 20,000) were randomly selected and added to the training group composed of different numbers of top bulls (0, 2,500, 5,000, 10,000, or 15,000). Reliability levels of de-regressed estimated breeding values for training cows and bulls were 30 and 75% for traits with low heritability and were 60 and 90% for traits with moderate heritability, respectively. Preferential treatment was simulated by introducing upward bias equal to 35% of phenotypic variance to 5, 10, and 20% of elite bull dams in each scenario. Two different validation data sets were considered: (1) all animals in the last generation of both elite and commercial tiers (n = 42,000) and (2) only animals in the last generation of the elite tier (n = 12,000). Adding cow data into the training population led to an increase in accuracy (r) and decrease in bias of genomic predictions in all considered scenarios without preferential treatment. The gain in r was higher for the low heritable trait (from 0.004 to 0.166 r points) compared with the moderate heritable trait (from 0.004 to 0.116 r points). The gain in accuracy in scenarios with a lower number of training bulls was relatively higher (from 0.093 to 0.166 r points) than with a higher number of training bulls (from 0.004 to 0.09 r points). In this study, as expected, the bull-only reference population resulted in higher accuracy compared with the cow-only reference population of the same size. However, the cow reference population might be an option for countries with a small-scale progeny testing scheme or for minor breeds in large counties, and for traits measured only on a small fraction of the population. The inclusion of preferential treatment to 5 to 20% of the elite cows led to an adverse effect on both accuracy and bias of predictions. When preferential treatment was present, random selection of cows did not reduce the effect of preferential treatment.     

Testing candidate gene effects on milk production traits in dairy cattle under various parameterizations and modes of inheritance

The major objectives of this study were 1) to assess the statistical properties of models commonly used for the estimation of single nucleotide polymorphism (SNP) effects under the assumption of various modes of inheritance and various parameterizations of SNP genotypes using simulated data, and 2) to compare effects of the selected polymorphisms located within butyrophilin (BTN1A1), diacylglycerol acyltransferase 1 (DGAT1), leptin (LEP), and leptin receptor (LEPR) candidate genes on milk production traits using data from 2 dairy cattle breeds (190 Jersey cows and 475 Polish Holstein-Friesian cows). Simulation results showed that type I error and power were not dependent on the assumed parameterization, but differences were observed regarding confidence intervals of estimated SNP effects. In the presence of epistasis, correct confidence intervals for all (epistatic and nonepistatic) SNP and all modes of inheritance were provided only by the parameterization proposed by C. H. Kao and Z. B. Zeng in 2002. However, if no dominance effect was included in the model, confidence intervals for SNP effects were correct for all parameterizations. Results based on real data showed that for both breeds the additive effects of polymorphisms were generally similar, except for LEPR, which had a different allele associated with increased fat content in Holstein-Friesians than in Jerseys. In both breeds, DGAT1 had the largest additive effect of the polymorphisms considered, but its effect on most milk traits was more pronounced in Jerseys than in Holstein-Friesians. Evidence of epistasis was found between LEPR and DGAT1, as well as between LEPR and BTN1A1, but only for milk content traits and only in the Holstein-Friesian breed. There was also more evidence for dominance in the Holstein-Friesian breed than in the Jersey breed.     

The effect of lameness on the fertility of dairy cattle in a seasonally breeding pasture-based system

The effect of lameness on the fertility of dairy cattle is well recognized. But, the effect of lameness on the fertility of seasonally breeding cattle in pasture-based systems is less well characterized. This prospective cohort study of 463 cows on 1 farm in the lower North Island of New Zealand was designed to assess the effect of clinical lameness, as identified by farm staff, on the hazard of conception after the planned start-of-mating date. A Cox proportional hazards model with time-varying covariates was used. After controlling for the effect of parity, breed, body weight at calving, and calving-to-planned start of mating interval, the daily hazard of conception for cows identified as lame was 0.78 (95% confidence interval: 0.68-0.86) compared with non-lame cows. Lame cows took 12 d longer to get pregnant compared with their non-lame counterparts.