Evaluating sire selection practices using lifetime net income functions

Dairy farmers do not take full advantage of opportunities available for genetic improvement through use of artificial insemination, perhaps because economic advantages of good sire selection may not be fully recognized or understood. This study was undertaken to document differences between use of AI and non-AI bulls and to develop prediction equations to compare lifetime economic merit of future progeny from alternative sire selection policies. We describe the use of two methods of measuring lifetime economic merit, with and without adjustment for opportunity cost of a postponed replacement. Comparison of lifetime relative net income adjusted for opportunity cost on groups of cows sired by different kinds of bulls showed that daughters of proven AI bulls generated $148 and $120 more lifetime net income under fluid and manufactured milk market conditions than daughters of non-AI bulls. Daughters of proven AI bulls produced $60 more than daughters of AI young sires in progeny testing programs at the time of daughter conception. We developed prediction equations from combinations of genetic evaluations for production, productive life, SCS, and linear type traits on sires to predict lifetime relative net income of progeny produced from alternative sire selection strategies. Prediction equations explained 14 to 18% of variation in relative net income (not adjusted for opportunity cost), but herd and year of first freshening accounted for considerably more variation than did genetic evaluations on the sire of the cow. Finally, two independent data sets were used to develop and test predictions of lifetime relative net income adjusted for opportunity cost using genetic evaluations based on the eight traits included in the Merit indexes for the sire of each cow. Prediction equations from odd numbered herds were used to predict lifetime economic merit in even numbered herds and vice versa. Coefficients of determination ranged from 0.088 to 0.103 and averaged 0.004 higher than prediction equations with Net or Fluid Merit. Accuracy of predictions showed that Net and Fluid Merit were robust and useful indexes that accurately identified bulls whose daughters generated highest lifetime economic merit.     

Prediction of most recent evaluations of Holstein bulls from first available pedigree information

The objectives of this study were to predict most recent evaluations of young bulls entering artificial insemination (AI) sampling programs from pedigree information available at time of sampling and investigate whether prediction equations differ among AI organizations. Data were pedigree information and most recent USDA evaluations on bulls entering AI sampling programs from 1989 through 1994. Pedigree information included earliest available parent average, predicted transmitting abilities (PTA) of sire, dam, and maternal grand sire. Most recent evaluations were from May 2000 evaluations and included PTA and daughter yield deviations for milk, fat, and protein. Regression coefficients on PTA of sire and PTA of dam were less than the expected coefficient of 0.50. Accuracy of prediction as determined by R-square values was less than 12%. Inclusion of PTA of maternal grand sire after PTA of sire and dam increased the accuracy of prediction by less than 1%, but regression coefficients on PTA of maternal grand sire differed from 0. Regressions on parent average were not different among AI organizations for prediction of PTA and daughter yield deviations. Partial regression coefficients on PTA of sire differed among AI organizations for prediction of fat and protein but did not differ for milk. Coefficients on PTA of dam did not differ among organizations. These results indicate that AI organizations put different emphasis on PTA of sire in selection of sons for fat and protein.     

Efficient use of genomic information for sustainable genetic improvement in small cattle populations

In this study, we compared genetic gain, genetic variation, and the efficiency of converting variation into gain under different genomic selection scenarios with truncation or optimum contribution selection in a small dairy population by simulation. Breeding programs have to maximize genetic gain but also ensure sustainability by maintaining genetic variation. Numerous studies have shown that genomic selection increases genetic gain. Although genomic selection is a well-established method, small populations still struggle with choosing the most sustainable strategy to adopt this type of selection. We developed a simulator of a dairy population and simulated a model after the Slovenian Brown Swiss population with ～10,500 cows. We compared different truncation selection scenarios by varying (1) the method of sire selection and their use on cows or bull-dams, and (2) selection intensity and the number of years a sire is in use. Furthermore, we compared different optimum contribution selection scenarios with optimization of sire selection and their usage. We compared scenarios in terms of genetic gain, selection accuracy, generation interval, genetic and genic variance, rate of coancestry, effective population size, and conversion efficiency. The results showed that early use of genomically tested sires increased genetic gain compared with progeny testing, as expected from changes in selection accuracy and generation interval. A faster turnover of sires from year to year and higher intensity increased the genetic gain even further but increased the loss of genetic variation per year. Although maximizing intensity gave the lowest conversion efficiency, faster turnover of sires gave an intermediate conversion efficiency. The largest conversion efficiency was achieved with the simultaneous use of genomically and progeny-tested sires that were used over several years. Compared with truncation selection, optimizing sire selection and their usage increased the conversion efficiency by achieving either comparable genetic gain for a smaller loss of genetic variation or higher genetic gain for a comparable loss of genetic variation. Our results will help breeding organizations implement sustainable genomic selection.     

Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls

Genomic selection has the potential to revolutionize dairy cattle breeding because young animals can be accurately selected as parents, leading to a much shorter generation interval and higher rates of genetic gain. The aims of this study were to assess the effects of genomic selection and reduction of the generation interval on the rate of genetic gain and rate of inbreeding. Furthermore, the merit of proven bulls relative to young bulls was studied. This is important for breeding organizations as it determines the relative importance of progeny testing. A closed nucleus breeding scheme was simulated in which 1,000 males and 1,000 females were born annually, 200 bulls were progeny tested, and 20 sires and 200 dams were selected to produce the next generation. In the “proven” (PROV) scenario, only cows with own performance records and progeny-tested bulls were selected as parents. The proportion of the genetic variance that was explained by simulated marker information (M) was varied from 0 to 100%. When M increased from 0 to 100%, the rate of genetic gain increased from 0.238 to 0.309 genetic standard deviations (σ) per year (+30%), whereas the rate of inbreeding reduced from 1.00 to 0.42% per generation. Alternatively, when young cows and bulls were selected as parents (YNG scenario), the rate of genetic gain for M = 0% was 0.292 σ/yr but the corresponding rate of inbreeding increased substantially to 3.15% per generation. A realistic genomic selection scheme (YNG with M = 40%) gave 108% higher rate of genetic gain (0.495 σ/yr) and approximately the same rate of inbreeding per generation as the conventional system without genomic selection (PROV with M = 0%). The rate of inbreeding per year, however, increased from 0.18 to 0.52% because the generation interval in the YNG scheme was much shorter. Progeny-testing fewer bulls reduced the rate of genetic gain and increased the rate of inbreeding for PROV, but had negligible effects for YNG because almost all sires were young bulls. In scenario YNG with M = 40%, the best young bulls were superior to the best proven bulls by 1.27 σ difference in genomic estimated breeding value. This superiority increased even further when fewer bulls were progeny tested. This stochastic simulation study shows that genomic selection in combination with a severe reduction in the generation interval can double the rate of genetic gain at the same rate of inbreeding per generation, but with a higher rate of inbreeding per year. The number of progeny-tested bulls can be greatly reduced, although this will slightly affect the quality of the proven bull team. Therefore, it is important for breeding organizations to predict the future demand for proven bull semen in light of the increasing superiority of young bulls.     

Genomic evaluation of Brown Swiss dairy cattle with limited national genotype data and integrated external information

This study demonstrated the feasibility of a genomic evaluation for the dairy cattle population for which the small national training population can be complemented with foreign information from international evaluations. National test-day milk yield data records for the Slovenian Brown Swiss cattle population were analyzed. Genomic evaluation was carried out using the single-step genomic best linear unbiased prediction method (ssGBLUP), resulting in genomic estimated breeding values (GEBV). The predominantly female group of genotyped animals, representing the national training population in the single-step genomic evaluation, was further augmented with 7,024 genotypes of foreign progeny-tested sires from an international Brown Swiss InterGenomics genomic evaluation (https://interbull.org/ib/whole_cop). Additionally, the estimated breeding values for the altogether 7,246 genotyped domestic and foreign sires from the 2019 sire multiple across-country evaluation (MACE), were added to the ssGBLUP as external pseudophenotypic information. The ssGBLUP method, with integration of MACE information by avoiding double counting, was then performed, resulting in MACE-enhanced GEBV (GEBVM). The methods were empirically validated with forward prediction. The validation group consisted of 315 domestic males and 1,041 domestic females born after 2012. Increase, inflation, and bias of the GEBV(M) reliability (REL) were assessed for the validation group with a focus on females. All individuals in the validation benefited from genomic evaluations using both methods, but the GEBV(M) REL increased most for the youngest selection candidates. Up to 35 points of GEBV REL could be assigned to national genomic information, and up to 17 points of GEBVM REL could additionally be attributed to the integration of foreign sire genomic and MACE information. Results indicated that the combined foreign progeny-tested sire genomic and external MACE information can be used in the single-step genomic evaluation as an equivalent replacement for domestic phenotypic information. Thus, an equal or slightly higher genomic breeding value REL was obtained sooner than the pedigree-based breeding value REL for the female selection candidates. When the abundant foreign progeny-tested sire genomic and MACE information was used to complement available national genomic and phenotypic information in single-step genomic evaluation, the genomic breeding value REL for young-female selection candidates increased approximately 10 points. Use of international information provides the possibility to upgrade small national training populations and obtain satisfying reliability of genomic breeding values even for the youngest female selection candidates, which will help to increase selection efficiency in the future.     

A comparison of dairy cattle breeding designs that use genomic selection

Different dairy cattle breeding schemes were compared using stochastic simulations, in which the accuracy of the genomic breeding values was dependent on the structure of the breeding scheme, through the availability of new genotyped animals with phenotypic information. Most studies that predict the gain by implementing genomic selection apply a deterministic approach that requires assumptions about the accuracy of the genomic breeding values. The achieved genetic gain, when genomic selection was the only selection method to directly identify elite sires for widespread use and progeny testing was omitted, was compared with using genomic selection for preselection of young bulls for progeny testing and to a conventional progeny test scheme. The rate of inbreeding could be reduced by selecting more sires every year. Selecting 20 sires directly on their genomic breeding values gave a higher genetic gain than any progeny testing scheme, with the same rate of inbreeding as the schemes that used genomic selection for preselection of bulls before progeny testing. The genomic selection breeding schemes could reduce the rate of inbreeding and still increase genetic gain, compared with the conventional breeding scheme. Since progeny testing is expensive, the breeding scheme omitting the progeny test will be the cheapest one. Keeping the progeny test and use of genomic selection for preselection still has some advantages. It gives higher accuracy of breeding values and does not require a complete restructuring of the breeding program. Comparing at the same rate of inbreeding, using genomic selection for elite sire selection only gives a 13% increase in genetic gain, compared with using genomic selection for preselection. One way to reduce the costs of the scheme where genomic selection was used for preselection is to reduce the number of progeny tested bulls. This was here achieved without getting lower genetic gain or a higher rate of inbreeding.     

Breeding practices on Illinois Holstein farms

Questionnaires requesting breeding information were mailed to 1,148 Illinois Holstein herds in the Dairy Herd Improvement program. A total of 591 questionnaires (51%) were returned. Dairy producers with herds producing over 7,100 kg of milk returned 64% of their questionnaires whereas 34% of dairy producers with herds producing less than 5,900 kg returned their questionnaires. State average and standard errors were: 23 +/- 1 bulls used per 100 cows, 78 +/- 2% dairy producers select the bulls, 96 +/- 1% herds use artificial insemination, 2.1 +/- .1 artificial insemination organizations per herd, 29 +/- 2% herds participate in young sire testing programs, 87 +/- 1% farmers consider calving ease indicators in mating heifers, and 17 +/- 2% farmers consider calving ease indicators in mating cows. Breeding practices positively associated with increasing rolling herd average milk production were number of bulls per herd and per 100 cows, self as bull selector, use of artificial insemination, number of artificial insemination organizations, and participation in young sire testing programs. Three breeding practices were negatively associated with increasing rolling herd average milk production: artificial-insemination technician as bull selector and consideration of calving ease for mating heifers and cows. Dairy producers also were asked to rate the emphasis placed on traits in bull and cow selection. For bull selection, udder conformation and Predicted Difference milk were most important. In cow selection, milk production, followed by udder conformation, feet and legs, and fat percentage, was the most important trait.     

Improving an Aggregate Phenotype in Replacements by Selecting Their Sires Conditioned on Dam Phenotypes

An indexing of total merit in expected progeny is outlined when the constituent merit from each trait is defined as a discrete quadratic equation. Information consisting of an estimated breeding value for each trait on each potential parent is used to define a trait index or a trait merit index for progeny. The selection of a specific sire for each mating, vis-a-vis the selection of a high ranking sire independent of any particular mating, is indicated more frequently when an interval along a trait scale exhibits strongly curvilinear merit and also spans the variation in trait index values among alternative matings. Variability in a trait index increases as heritability increases. Nonlinearity in a merit function dynamically describes the direction and relative selection pressure from one trait relative to another when indexes depend on dam or herd mean phenotypes. A method is proposed to quantify the role of merit from each trait relative to total merit. An example using three traits, milk yield, udder depth score, and rear leg score, is illustrated and evaluated.     

Progeny testing and selection intensity for Holstein bulls in different countries

International Bull Evaluation Service (Interbull) Holstein evaluations from February 1995 through February 2003 were used to determine characteristics of progeny testing for Holstein bulls in Australia, Canada, Denmark, France, Germany, Italy, New Zealand, Sweden, The Netherlands, and the United States. The decision to graduate a bull from progeny test (PT) was assumed to have been made based on the second Interbull evaluation, and graduation was defined as the addition of 200 daughters in the period 2.5 to 4.5 yr later. Mean bull age at PT decision varied across countries by 12 mo. Mean numbers of herds and daughters ranged from 39 to 111 and 54 to 144, respectively. Countries with higher requirements for official evaluations generally had more herds and daughters but older bulls at PT decision. Mean estimated breeding values for yield traits of sires of tested bulls were most similar across countries for fat, differing by only 6.4 kg. The four countries highest for sire protein differed only by 1 kg; however, the range was 12 kg. Percentages of bulls graduated ranged from 4.4 to 14.7 across countries. Selection intensities (standardized selection differentials) tended to be about 1.0 for yield traits. Selection intensities for somatic cell score were generally unfavorable, reflecting selection for negatively correlated yield traits. Reflecting variation in national breeding goals, selection intensities for stature were positive for most countries and highly negative for New Zealand. Selection intensity for fore udder was generally the lowest among the traits examined. All but one country showed positive selection for udder support. These statistics permit comparison of the components of PT programs across country, illustrating possible opportunities for improvement.     

Controlling inbreeding by constraining the average relationship between parents of young bulls entering AI progeny test programs

In breeding is known to impair the health, fertility, and productivity of dairy cattle and other livestock species. Mating programs can address inbreeding concerns on the farm, at least in the short term, but long-term control of inbreeding in a dairy population requires consideration of relationships between young bulls entering AI progeny test programs. The present study discusses an application of optimal contribution methodology to selection of young AI bulls in the five major US dairy breeds. Elite cows and active AI sires from the Ayrshire, Brown Swiss, Guernsey, Holstein, and Jersey breeds were considered as potential bull parents. Genetic merit of selected sires and dams was maximized subject to various constraints on the mean additive genetic relationship within the selected group. Relationships between selected parents can be reduced substantially relative to current levels, but the corresponding reduction in genetic merit may be large. This loss in genetic merit occurs due to lower selection intensity, although it is mainly a reflection of a larger number of bull parents (with progeny more evenly distributed among these parents), rather than selection of genetically inferior "outcross" parents that wouldn't otherwise have been considered. Selected parents were generally older and slightly less inbred than those that would have been chosen had inbreeding been ignored. Although severe restrictions on relationships can be costly, in terms of lost genetic progress, it appears that moderate constraints can keep relationships at a manageable level without a significant loss in genetic merit. Cooperation between breed associations and several competing AI companies may be required to facilitate implementation of this methodology in dispersed populations, but if this can be accomplished, prospects for achieving a balance between inbreeding and selection seem positive.     

Potential genetic gains from producing bulls with only sires as parents

Micromanipulation of sperm and ova has been suggested as a means to produce progeny of two sires instead of a sire and dam. Selection schemes taking advantage of this technology could produce genetic gains 1.5 to 2 times current gains. An optimum strategy both genetically and economically would be to breed 99% of the population to young sires and 1% to progeny-tested sires. The genetic pathway from sires to sons could become the only pathway affecting genetic gain; this would eliminate problems of cow evaluation and would give artificial insemination organizations more control over quality of young sires. Inbreeding would not be a problem, and few other technologies could offer superior rates of genetic gain.     

Genetic progress in multistage dairy cattle breeding schemes using genetic markers

The aim of this paper was to explore general characteristics of multistage breeding schemes and to evaluate multistage dairy cattle breeding schemes that use information on quantitative trait loci (QTL). Evaluation was either for additional genetic response or for reduction in number of progeny-tested bulls while maintaining the same response. The reduction in response in multistage breeding schemes relative to comparable single-stage breeding schemes (i.e., with the same overall selection intensity and the same amount of information in the final stage of selection) depended on the overall selection intensity, the selection intensity in the various stages of the breeding scheme, and the ratio of the accuracies of selection in the various stages of the breeding scheme. When overall selection intensity was constant, reduction in response increased with increasing selection intensity in the first stage. The decrease in response was highest in schemes with lower overall selection intensity. Reduction in response was limited in schemes with low to average emphasis on first-stage selection, especially if the accuracy of selection in the first stage was relatively high compared with the accuracy in the final stage.Closed nucleus breeding schemes in dairy cattle that use information on QTL were evaluated by deterministic simulation. In the base scheme, the selection index consisted of pedigree information and own performance (dams), or pedigree information and performance of 100 daughters (sires). In alternative breeding schemes, information on a QTL was accounted for by simulating an additional index trait. The fraction of the variance explained by the QTL determined the correlation between the additional index trait and the breeding goal trait. Response in progeny test schemes relative to a base breeding scheme without QTL information ranged from +4.5% (QTL explaining 5% of the additive genetic variance) to +21.2% (QTL explaining 50% of the additive genetic variance). A QTL explaining 5% of the additive genetic variance allowed a 35% reduction in the number of progeny tested bulls, while maintaining genetic response at the level of the base scheme. Genetic progress was up to 31.3% higher for schemes with increased embryo production and selection of embryos based on QTL information. The challenge for breeding organizations is to find the optimum breeding program with regard to additional genetic progress and additional (or reduced) cost.     

Hot topic: Effect of breeding strategies using genomic information on fitness and health

A complex deterministic approach was used to model the breeding goal and breeding structure for the Austrian Fleckvieh (dual-purpose Simmental) breed. The reference breeding goal corresponded to the current total merit index (TMI-R), where dairy traits have a relative weight of 37.9% and fitness traits of 43.7% (beef traits 16.5%; milkability 2%). The breeding program was characterized by 280,000 cows under performance recording, 3,200 bull dams, 100 test bulls with a test capacity of 25%, and 15 proven bulls and 8 bull sires per year. The annual monetary genetic gain (AMGG) was generated mainly by increases in milk fat and milk protein yield (80.6%) and only to a small extent by fitness traits (6.6%). The inclusion of direct health traits (early reproductive disorders, cystic ovaries, and mastitis) with their economic weights increased the relative AMGG for fitness traits from 6.6 to 11.2%. The presently slightly negative AMGG for fertility index and udder health changed in a positive direction. Increasing the weight on the direct health traits by 50% resulted in a further shift toward fitness and health. The effect of strategies using genomic information in a total merit index (TMI) with varying weights on fitness and health traits was also analyzed. The conventional progeny-testing scheme was defined as the reference breeding program. A breeding program was considered to be genomically enhanced (GS50) when 50% of inseminations of herdbook cows and of bull dams were from young bulls with a genomic TMI, and a second program (GS100) did not rely on progeny-tested bulls at all. For GS50, a clear shift of the relative gain in AMGG toward fitness and health traits was observed for all 3 TMI scenarios, as a result of larger progeny groups and a shorter generation interval. For GS100, where no gene flow from progeny-tested bulls was assumed, the genetic gain per generation was lower for the fertility and udder health index but higher per year. The results based on natural genetic gain per year showed that no positive genetic response for fertility and udder health index were achieved for TMI-R (without the inclusion of direct health traits) in GS50 and GS100. The direction of the genetic trend was determined by the weights given to fertility and udder health indices within the TMI. When appropriate weights generated a clear positive trend, GS50 and GS100 reinforced this trend.     

Sire Evaluation for Conformation of Jersey Cows

A procedure for sire evaluation was developed for Jersey type data; the model contained fixed effects for herd-year and genetic group and random effects for sires, herds-by-sires, and cows.In initial calculations artificial insemination and natural service bulls were grouped separately by year of birth with little evidence of genetic trend for final score. These evaluations then were used for pedigree indexes based on sire and maternal grandsire. Bulls of similar pedigree index for each trait were grouped for new evaluations. The correlation between pedigree index and evaluation for final score on 726 bulls with type information on sire and maternal grandsire and 10 or more classified daughters was .64. The correlation for 533 bulls with evaluation on sires only was .58. The regressions of evaluations for final score on pedigree indexes were .73 ± .03 and .77 ± .05. Predicted Difference milk had correlations of .18, .13, .55, .13, and ?.04 with evaluations for final score, general appearance, dairy character, body capacity, and mammary system. Other correlations ranged from ?.09 for back, rump, and tail to .20 for breed character. Correlations between these evaluations and previous estimates of genetic merit, daughter averages of latest score, were .63, .61, .54, .48, and .69 for final score, general appearance, dairy character, body capacity, and mammary system. Similar correlations for other traits ranged from .47 for breed character to .76 for stature. An index combined estimated transmitting ability for milk, fat, and final score. Bulls were ranked by indexes; different weights were used for production and type. The progress that could be expected from selection with each index was shown.     

Response to alternative genetic-economic indices for Holsteins across 2 generations

Four US genetic-economic indices for dairy cattle were retrofitted to illustrate differences in phenotypic response observed for retrospective selection over 2 generations for currently evaluated traits, even though producers did not have evaluations available at the time for direct selection for those traits. Differences among cows were compared based on ranking of their sires and maternal grandsires (MGS) for the 4 retrofitted indices. Holstein artificial insemination bulls (106,471) were categorized by quintile for each index, and 25 cow groups were formed based on quintiles for sire and MGS (2 generations). Data included records from 1,756,805 cows in 26,106 herds for yield traits, productive life, pregnancy rate, and somatic cell score; 692,656 cows in 9,967 herds for calving difficulty; and 270,564 cows in 4,534 herds for stillbirths. For each index, least squares differences between the 25 cow groups were examined for 8 first-parity traits (milk, fat, and protein yields; productive life; somatic cell score; pregnancy rate; calving difficulty; and stillbirth) that had been standardized for age. Analysis removed effects of herd and cow birth year. Seven of 25 cow groups were consolidated into 3 groups based on index ranking for their male ancestors (low, medium, and high). The cow group with high sire and MGS rankings for the 2006 net merit index produced more milk (219 kg), fat (21 kg), and protein (11 kg) and had longer productive life (6.3 mo), lower somatic cell score (0.21), higher pregnancy rate (1.2 percentage units), fewer difficult births in heifers (3.8 percentage units), and lower stillbirth rate (4.6 percentage units) than did the group with low sire and MGS rankings. For cow groups based on sire and MGS rankings for 1971 (milk and fat) and 1977 (milk, fat, and protein) indices, advantages for the group with high sire and MGS rankings were much larger for yield traits but smaller (and sometimes even unfavorable) for other traits. Cow groups based on sire and MGS rankings for the 1994 net merit index generally had differences that were intermediate to groups based on sire and MGS rankings for the 1977 and 2006 indices. Phenotypic differences revealed retrospectively between genetic-economic indices indicate that genetic improvement should be made for all traits included in recent net merit indices.     

Adding cows to the reference population makes a small dairy population competitive

Small dairy breeds are challenged by low reliabilities of genomic prediction. Therefore, we evaluated the effect of including cows in the reference population for small dairy cattle populations with a limited number of sires in the reference population. Using detailed simulations, 2 types of scenarios for maintaining and updating the reference population over a period of 15 yr were investigated: a turbo scheme exclusively using genotyped young bulls and a hybrid scheme with mixed use of genotyped young bulls and progeny-tested bulls. Two types of modifications were investigated: (1) number of progeny-tested bulls per year was tested at 6 levels: 15, 40, 60, 100, 250, and 500; and (2) each year, 2,000 first-lactation cows were randomly selected from the cow population for genotyping or, alternatively, an additional 2,000 first-lactation cows were randomly selected and typed in the first 2 yr. The effects were evaluated in the 2 main breeding schemes. The breeding schemes were chosen to mimic options for the Danish Jersey cattle population. Evaluation criteria were annual monetary genetic gain, rate of inbreeding, reliability of genomic predictions, and variance of response. Inclusion of cows in the reference population increased monetary genetic gain and decreased the rate of inbreeding. The increase in genetic gain was larger for the turbo schemes with shorter generation intervals. The variance of response was generally higher in turbo schemes than in schemes using progeny-tested bulls. However, the risk was reduced by adding cows to the reference population. The annual genetic gain and the reliability of genomic predictions were slightly higher with more cows in the reference population. Inclusion of cows in the reference population is a rapid way to increase reliabilities of genomic predictions and hence increase genetic gain in a small population. An economic evaluation shows that genotyping of cows is a profitable investment.     

Genomic selection strategies in a small dairy cattle population evaluated for genetic gain and profit

The objective of this study was to evaluate a genomic breeding scheme in a small dairy cattle population that was intermediate in terms of using both young bulls (YB) and progeny-tested bulls (PB). This scheme was compared with a conventional progeny testing program without use of genomic information and, as the extreme case, a juvenile scheme with genomic information, where all bulls were used before progeny information was available. The population structure, cost, and breeding plan parameters were chosen to reflect the Danish Jersey cattle population, being representative for a small dairy cattle population. The population consisted of 68,000 registered cows. Annually, 1,500 bull dams were screened to produce the 500 genotyped bull calves from which 60 YB were selected to be progeny tested. Two unfavorably correlated traits were included in the breeding goal, a production trait (h² = 0.30) and a functional trait (h² = 0.04). An increase in reliability of 5 percentage points for each trait was used in the default genomic scenario. A deterministic approach was used to model the different breeding programs, where the primary evaluation criterion was annual monetary genetic gain (AMGG). Discounted profit was used as an indicator of the economic outcome. We investigated the effect of varying the following parameters: (1) increase in reliability due to genomic information, (2) number of genotyped bull calves, (3) proportion of bull dam sires that are young bulls, and (4) proportion of cow sires that are young bulls. The genomic breeding scheme was both genetically and economically superior to the conventional breeding scheme, even in a small dairy cattle population where genomic information causes a relatively low increase in reliability of breeding values. Assuming low reliabilities of genomic predictions, the optimal breeding scheme according to AMGG was characterized by mixed use of YB and PB as bull sires. Exclusive use of YB for production cows increased AMGG up to 3 percentage points. The results from this study supported our hypothesis that strong interaction effects exist. The strongest interaction effects were obtained between increased reliabilities of genomic estimated breeding values and more intensive use of YB. The juvenile scheme was genetically inferior when the increase in reliability was low (5 percentage points), but became genetically superior at higher reliabilities of genomic estimated breeding values. The juvenile scheme was always superior according to discounted profit because of the shorter generation interval and minimizing costs for housing and feeding waiting bulls.     

Genetics of parity-dependant production increase and its relationship with health, fertility, longevity, and conformation in swiss holsteins

Genetic analysis of production increase (ProdI), defined as an increase in production from early to later lactations, was conducted using data from the Holstein Association of Switzerland. This production increase describes the maturity rate of the cow. The data set contained 42,807 cows with a ProdI value. All cows had completed the first 3 lactations. Different formulas were derived for the computation of ProdI using 1) milk yields or energy-corrected milk yields and 2) yields from all 3 lactations or only 2 of them (first and second, first and third, second and third). Heritabilities of ProdI and genetic and phenotypic correlations of ProdI with somatic cell score, days to first service, nonreturn rate, longevity, and 27 conformation traits were estimated by univariate and bivariate sire models that included relationship among sires. Heritabilities for ProdI were low (0.06 to 0.08), but genetic variation among sires existed. For nonreturn rate and longevity, regressions on the sire estimated breeding values were estimated. Additive genetic correlations of ProdI were moderately favorable with somatic cell score (-0.22 to -0.33) and chest width (0.21 to 0.30), i.e., with traits often associated with long-lasting cows. Unfavorable correlations were found with angularity (-0.18 to -0.26). Regression coefficients from regressing ProdI on sire estimated breeding values for longevity tend to show favorable relationships between these 2 traits (0.10 to 0.20). Results show that animals can be selected for ProdI, as there is good genetic variation between bulls. ProdI is a potential trait to be included in selection indices, as it has favorable genetic relationships with economically important functional traits such as health, conformation, and longevity.     

Effects of sire fertility and daughter stayability on profitability of sire selection.

Holstein sires (n = 340) with milk, milk fat, semen unit fertility, daughter stayability evaluations, and semen price for 1986 were studied. Effects of variation in sire fertility and daughter stayability on profitability of sire selection using the net present value criterion were estimated. The model estimated expected profit from a cow bred to pregnancy from future production and from cattle disposal and replacement after discounting costs and returns to the time of insemination. Effects of semen sexing and semen unit dilution on profitability to determine optimal breeding strategies for dairy herds were examined. Sire profitability increased with herd average conception rate and sire selection intensity. Daughter stayability had a greater impact on profitability than semen unit fertility when profit maximization was computed under the criterion of breeding a cow to pregnancy. Genetic progress for production was compromised when selecting to maximize profit. Dilution of semen units seems profitable only when semen availability is limited for high demand sires. The use of sexed female semen may only be appropriate when it can generate additional income from the sale of surplus heifers.     

Application of a posteriori granddaughter and modified granddaughter designs to determine Holstein haplotype effects

A posteriori and modified granddaughter designs were applied to determine haplotype effects for Holstein bulls and cows with BovineSNP50 [~50,000 single nucleotide polymorphisms (SNP); Illumina Inc., San Diego, CA] genotypes. The a posteriori granddaughter design was applied to 52 sire families, each with ≥100 genotyped sons with genetic evaluations based on progeny tests. For 33 traits (milk, fat, and protein yields; fat and protein percentages; somatic cell score; productive life; daughter pregnancy rate; heifer and cow conception rates; service-sire and daughter calving ease; service-sire and daughter stillbirth; 18 conformation traits; and net merit), the analysis was applied to the autosomal segment with the SNP with the greatest effect in the genomic evaluation of each trait. All traits except 2 had a within-family haplotype effect. The same design was applied with the genetic evaluations of sons corrected for SNP effects associated with chromosomes besides the one under analysis. The number of within-family contrasts was 166 without adjustment and 211 with adjustment. Of the 52 bulls analyzed, 36 had BovineHD (high density; Illumina Inc.) genotypes that were used to test for concordance between sire quantitative trait loci and SNP genotypes; complete concordance was not obtained for any effects. Of the 31 traits with effects from the a posteriori granddaughter design, 21 were analyzed with the modified granddaughter design. Only sires with a contrast for the a posteriori granddaughter design and ≥200 granddaughters with a record usable for genetic evaluation were included. Calving traits could not be analyzed because individual cow evaluations were not computed. Eight traits had within-family haplotype effects. With respect to milk and fat yields and fat percentage, the results on Bos taurus autosome (BTA) 14 corresponded to the hypothesis that a missense mutation in the diacylglycerol O-acyltransferase 1 (DGAT1) gene is the main causative mutation, although other polymorphisms in that gene also modify fat yield and percentage. The positive allele for protein concentration was less frequent, which indicated that selection on that locus could be effective. Although the results can be used to determine causative polymorphisms for most of the analyzed traits, complete DNA sequencing of most of the analyzed sires probably will be required.