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.     

Benefits of cooperation between breeding programs in the presence of genotype by environment interaction

Dairy cattle breeding programs and dairy farmers are selecting sires and dams across environments. Genotype × environment interaction (G × E) limits the possibilities for cooperation between breeding programs operating in different environments. The objectives of this study were 2-fold: 1) to investigate the effects of heritability, selection intensity, number of progeny per bull, and size of breeding programs on possibilities for cooperation between dairy cattle breeding programs in the short and long term in the presence of G × E, and 2) to quantify the effect of such cooperation on genetic gain. A dairy cattle situation with 2 breeding programs operating in 2 environments was simulated using a deterministic pseudo-BLUP selection index model. Long-term cooperation between the 2 breeding programs was possible in the presence of G × E, when the genetic correlation was higher than 0.80 to 0.90, resulting in up to 15% extra genetic gain. In addition, in the initial generations of selection, the breeding programs could benefit from mutually selecting sires and dams from each other when the genetic correlation was as low as 0.40 to 0.60. With more intense selection, breeding programs were less likely to benefit from cooperation with breeding programs in other environments. Heritability and number of progeny per bull had little effect on possibilities for cooperation, unless the heritabilities and the number of progeny per bull were extremely different in the 2 environments. Small breeding programs benefited more from cooperation than did large breeding programs, and benefits were possible even at lower values (i.e., <0.80) of the genetic correlation. Possibilities for cooperation across environments would affect the optimal design of dairy cattle breeding programs considering genetic gain, inbreeding, and costs.     

Comparison of gene editing versus conventional breeding to introgress the POLLED allele into the US dairy cattle population

Disbudding and dehorning are commonly used cattle management practices to protect animals and humans from injury. They are unpleasant, costly processes subject to increased public scrutiny as an animal welfare issue. Horns are a recessively inherited trait, so one option to eliminate dehorning is to breed for polled (hornlessness). However, due to the low genetic merit and scarcity of polled dairy sires, this approach has not been widely adopted. In March 2018, only 3 Holstein and 0 Jersey active homozygous polled sires were registered with the National Association of Animal Breeders. Alternatively, gene editing to produce high-genetic-merit polled sires has been proposed. To further explore this concept, introgression of the POLLED allele into both the US Holstein and Jersey cattle populations via conventional breeding or gene editing (top 1% of bulls/year) was simulated for 3 polled mating schemes and compared with baseline selection on lifetime net merit (NM$) alone, over the course of 20 yr. Scenarios were replicated 10 times and the changes in HORNED allele frequency, inbreeding, genetic gain (NM$), and number of unique sires used were calculated. Gene editing decreased the frequency of the HORNED allele to <0.1 after 20 yr, which was as fast or faster than conventional breeding for both breeds. In the mating scheme that required the use of only existing homozygous polled sires, inbreeding reached 17% (Holstein) and 14% (Jersey), compared with less than 7% in the baseline scenarios. However, gene editing in the same mating scheme resulted in significantly less inbreeding, 9% (Holstein) and 8% (Jersey). Also, gene editing resulted in significantly higher NM$ after 20 yr compared with conventional breeding for both breeds. Additionally, the gene editing scenarios of both breeds used a significantly greater number of unique sires compared with either the conventional breeding or baseline scenarios. Overall, our simulations show that, given the current genetic merit of horned and polled dairy sires, the use of conventional breeding methods to decrease the frequency of the HORNED allele will increase inbreeding and slow genetic improvement. Furthermore, this study demonstrates how gene editing could be used to rapidly decrease the frequency of the HORNED allele in US dairy cattle populations while maintaining the rate of genetic gain, constraining inbreeding to acceptable levels, and simultaneously addressing an emerging animal welfare concern.     

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.     

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.     

Inbreeding trends and application of optimized selection in the UK Holstein population

Important increases in the rates of inbreeding have recently been observed in dairy cattle populations, and methods have been proposed to address these increases. The aims of this study were to estimate the current level and rates of inbreeding in the UK Holstein population and to investigate the potential of applying optimized selection to manage the rates of inbreeding. Inbreeding coefficients were calculated for the entire UK Holstein population using 1940 as the base year. Rates of inbreeding were obtained for 3 time periods by regressing mean inbreeding coefficients on the year of birth of the animals. The expected average pedigree index and expected inbreeding of offspring using optimized contributions for a given set of selection candidates was compared to the expected pedigree index and inbreeding of offspring for the same set of selection candidates using observed contributions. The rate of inbreeding in the UK Holstein population has increased substantially since 1990 when compared to previous time periods. This increase is most likely due to the large influence of a few related sires on the breed in the mid- to late 1980s. The introduction of the individual animal model in the early 1990s may also have contributed to increased inbreeding. Optimized selection appears to represent a promising selection tool, not only to manage rates of inbreeding, but also to increase genetic gain at the same rate of inbreeding.     

Superiority of QTL-assisted selection in dairy cattle breeding schemes

The superiority of selection schemes employing information about a known quantitative trait locus (QTL) over conventional schemes is examined for dairy cattle breeding schemes. Stochastic simulation of a dairy cattle population with selection practices, structures, and parameters similar to the US Holstein population was implemented. Additive genetic effects were estimated by an animal model. Two schemes were compared: a QTL-assisted selection scheme in which the genotype of a known QTL was accounted for in the animal model as a fixed factor, and a QTL-free selection scheme in which the QTL was simulated but was not fit separately in the animal model. Under the QTL-assisted selection scheme, all animals in the mixed model were assumed to be genotyped for the QTL. The effect of using QTL information on the genetic response, the frequency of the favorable QTL allele, and the accuracy of evaluation were examined. Moreover, the effect was studied in four distinct paths of selection: active sires, proven young bulls, bull dams, and first-lactation cows. Average superiority values of 4.6, 7.6, 11.7, and 1.1% for genetic response were observed over 16 yr of selection for active sires, young bulls, bull dams, and first-lactation cows, respectively. Frequency of the favorable QTL allele changed faster in bull dams than males, and was the slowest in first-lactation cows. Finally, accuracy of evaluation under the QTL-assisted selection scheme was higher than under the QTL-free selection scheme. Young bulls ofthe QTL-assisted selection scheme on average had 0.049 higher accuracy, and first-lactation cows had on average 0.185 higher accuracy than corresponding animals of the QTL-free selection scheme.     

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.     

Breeding schemes with optimum-contribution selection or truncation selection for beef cattle destined for use on dairy females

We tested the hypothesis that the size of a beef cattle population destined for use on dairy females is smaller under optimum-contribution selection (OCS) than under truncation selection (TRS) at the same genetic gain (ΔG) and the same rate of inbreeding (ΔF). We used stochastic simulation to estimate true ΔG realized at a 0.005 ΔF in breeding schemes with OCS or TRS. The schemes for the beef cattle population also differed in the number of purebred offspring per dam and the total number of purebred offspring per generation. Dams of the next generation were exclusively selected among the one-year-old heifers. All dams were donors for embryo transfer and produced a maximum of 5 or 10 offspring. The total number of purebred offspring per generation was: 400, 800, 1,600 or 4,000 calves, and it was used as a measure of population size. Rate of inbreeding was predicted and controlled using pedigree relationships. Each OCS (TRS) scheme was simulated for 10 discrete generations and replicated 100 (200) times. The OCS scheme and the TRS scheme with a maximum of 10 offspring per dam required approximately 783 and 1,257 purebred offspring per generation to realize a true ΔG of €14 and a ΔF of 0.005 per generation. Schemes with a maximum of 5 offspring per dam required more purebred offspring per generation to realize a similar true ΔG and a similar ΔF. Our results show that OCS and multiple ovulation and embryo transfer act on selection intensity through different mechanisms to achieve fewer selection candidates and fewer selected sires and dams than under TRS at the same ΔG and a fixed ΔF. Therefore, we advocate the use of a breeding scheme with OCS and multiple ovulation and embryo transfer for beef cattle destined for use on dairy females because it is favorable both from an economic perspective and a carbon footprint perspective.     

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.     

How genomic selection has increased rates of genetic gain and inbreeding in the Australian national herd,genomic information nucleus,and bulls

Genomic selection has been commonly used for selection for over a decade. In this time, the rate of genetic gain has more than doubled in some countries, while inbreeding per year has also increased. Inbreeding can result in a loss of genetic diversity, decreased long-term response to selection, reduced animal performance and ultimately, decreased farm profitability. We quantified and compared changes in genetic gain and diversity resulting from genomic selection in Australian Holstein and Jersey cattle populations. To increase the accuracy of genomic selection, Australia has had a female genomic reference population since 2013, specifically designed to be representative of commercial populations and thus including both Holstein and Jersey cows. Herds that kept excellent health and fertility data were invited to join this population and most their animals were genotyped. In both breeds, the rate of genetic gain and inbreeding was greatest in bulls, and then the female genomic reference population, and finally the wider national herd. When comparing pre- and postgenomic selection, the rates of genetic gain for the national economic index has increased by ~160% in Holstein females and ~100% in Jersey females. This has been accompanied by doubling of the rates of inbreeding in female populations, and the rate of inbreeding has increased several fold in Holstein bulls since the widespread use of genomic selection. Where cow genotype data were available to perform a more accurate genomic analysis, greater rates of pedigree and genomic inbreeding were observed, indicating actual inbreeding levels could be underestimated in the national population due to gaps in pedigrees. Based on current rates of genetic gain, the female reference population is progressing ahead of the national herd and could be used to infer and track the future inbreeding and genetic trends of the national herds.     

Short communication: Implementation of a breeding value for heat tolerance in Australian dairy cattle

Excessive ambient temperature and humidity can impair milk production and fertility of dairy cows. Selection for heat-tolerant animals is one possible option to mitigate the effects of heat stress. To enable selection for this trait, we describe the development of a heat tolerance breeding value for Australian dairy cattle. We estimated the direct genomic values of decline in milk, fat, and protein yield per unit increase of temperature-humidity index (THI) using 46,726 single nucleotide polymorphisms and a reference population of 2,236 sires and 11,853 cows for Holsteins and 506 sires and 4,268 cows for Jerseys. This new direct genomic value is the Australian genomic breeding value for heat tolerance (HT ABVg). The components of the HT ABVg are the decline in milk, fat, and protein per unit increase in THI when THI increases above the threshold of 60. These components are weighted by their respective economic values, assumed to be equivalent to the weights applied to milk, fat, and protein yield in the Australian selection indices. Within each breed, the HT ABVg is then standardized to have a mean of 100 and standard deviation (SD) of 5, which is consistent with the presentation of breeding values for many other traits in Australia. The HT ABVg ranged from ?4 to +3 SD in Holsteins and ?3 to +4 SD in Jerseys. The mean reliabilities of HT ABVg among validation sires, calculated from the prediction error variance and additive genetic variance, were 38% in both breeds. The range in ABVg and their reliability suggests that HT can be improved using genomic selection. There has been a deterioration in the genetic trend of HT, and to moderate the decline it is suggested that the HT ABVg should be included in a multitrait economic index with other traits that contribute to farm profit.     

Realized genetic selection differentials in Canadian Ayrshire,Jersey, and Brown Swiss dairy cattle populations

Estimated breeding values of a selection index, production, durability, health, and fertility traits from Canadian Ayrshire, Jersey, and Brown Swiss bulls and cows were used to study genetic selection differentials (GSD). The bulls and cows were born from 1950 and 1960, respectively. The GSD for the 3 Canadian dairy populations were studied along the 4-path selection model: sire-to-bull (SB), dam-to-bull (DB), sire-to-cow (SC), and dam-to-cow (DC) pathways. We also determined the variations in realized GSD due to herd and herd × year of conception in addition to the effects of some environmental factors on realized GSD of the SC and DC paths. The mean realized GSD of the DB were higher than those of other paths and were increasing for lifetime performance index, 305-d milk yield, 305-d fat yield, and 305-d protein yield in all 3 dairy cattle populations. We observed no clear trends in realized GSD for type traits in all 3 dairy cattle breeds except for the apparent increasing trends in realized GSD of mammary system, dairy strength, and feet and legs in the DB and SC paths of the Ayrshire breed. No clear patterns were observed in the realized GSD of daughter fertility in the SB, DB, and SC paths of all dairy cattle breeds. Realized GSD for somatic cell score showed increasing and favorable trends in the 3 most influential selection paths (SB, DB, and SC). Year of conception influenced realized GSD of artificial insemination bulls in Ayrshire, Jersey, and Brown Swiss dairy populations. Selection emphases for the SC path generally increased with time. There was considerable variation among herds in selection pressures applied in the SC and DC pathways but no clear association with housing system or region. This study demonstrates that variations exist among herds of minor dairy cattle breeds in their selection for economically important traits. These variations offer opportunities for further improvements in these populations.     

Genetic analysis of leukosis incidence in United States Holstein and Jersey populations

Bovine leukosis (BL) is a retroviral disease caused by the bovine leukosis virus that affects only cattle. It is associated with decreased milk production and increased cull rates due to development of lymphosarcoma. The virus also affects the immune system. Infected cows display a weak response to some vaccinations. It is important to determine if the heritability of BL susceptibility is greater than zero, or if the environment is the only factor that can be used to reduce the transmission and incidence of the disease. Accordingly, the aim of this study was to estimate the heritability for BL incidence and the genetic merit of sires for leukosis resistance in Holstein and Jersey cattle. Continuous scores and binary milk ELISA results for 13,217 Holstein cows from 114 dairy herds across 16 states and 642 Jersey cows from 8 dairy herds were considered. Data were obtained from commercial testing records at Antel BioSystems (Lansing, MI). Out of the 13,859 animals tested, 38% were found to be infected with the disease. Linear and threshold animal models were used to analyze the continuous and binary data, respectively. Results from both models were similar in terms of estimated breeding values and variance components in their respective scales. Estimates of heritability obtained with the 2 approaches were approximately 8% for both breeds, indicating a considerable genetic component underlying BL disease incidence. The correlation between the estimated breeding values from the 2 models was larger than 0.90, and the lists of top 10% bulls selected from each model had about 80% overlap for both breeds. In summary, results indicate that a simple linear model using the continuous ELISA scores as the response variable was a reasonable approach for the genetic analysis of BL incidence in cattle. In addition, the levels of heritability found indicate that genetic selection could also be used to decrease susceptibility to bovine leukosis virus infection in Holstein and Jersey cattle. Further research is necessary to investigate the genetic correlations of BL with other production and reproduction traits, and to search for potential genomic regions harboring major genes affecting BL susceptibility.     

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.     

Results of a producer survey regarding crossbreeding on US dairy farms

Comprehensive surveys were sent to 528 US dairy producers who are currently practicing crossbreeding in their herds. Fifty usable surveys were returned, and the resulting data included qualitative responses regarding facilities, milk recording plans, milk pricing, crossbreeding goals, breed selection, advantages, disadvantages, and future plans. Quantitative variables included producer scores on a 1 to 5 scale for questions regarding ability to fit into the free stalls and milking parlor, milk volume, component percentages, involuntary culling rate, conception rate, calving difficulty, calf mortality, and prices for breeding stock, cull cows, market steers, and bull calves. The most common first generation crosses involved Jersey and Brown Swiss bulls mated to Holstein cows, and backcrosses to one of these parental breeds were most common in the next generation. Producers who responded to this survey desired, and indicated that they achieved, improvements in fertility, calving ease, longevity, and component percentages through crossbreeding. Respondents indicated that crosses involving the Jersey and Brown Swiss breeds had a clear advantage in longevity relative to purebred Holsteins, and conception rates for crosses of Jersey or Brown Swiss sires on Holstein cows were similar to the (high) conception rates typically achieved in purebred Jersey matings. Respondents also indicated that milk composition was improved in the crossbred cattle, but producers cited some difficulties in marketing crossbred breeding stock and bull calves, and noted that the lack of uniformity within the milking herd created management challenges. Based on results of this survey, it appears that crossbreeding can improve the health, fertility, longevity, and profitability of commercial dairy cattle. However, further research is needed regarding specific heterosis estimates for functional traits in crosses involving each of the major dairy breeds, and improvements are needed in systems for recording the ancestry and breed composition of crossbred animals.     

Development of a breeding program for improving the milk yield performance of Butana cattle under smallholder production conditions using a stochastic simulation approach

Butana is one of the local dairy cattle breeds of Sudan commonly kept by smallholder producers. This breed has been strongly promoted to advance the dairy production sector in the country. The main problem, however, is the lack of a systematic breeding program that involves smallholder producers. The aim of the current study was to identify the most promising design for a breeding program to improve the milk yield performance of Butana cattle under smallholder production conditions. In total, 3 breeding scenarios, including (1) the use of farm bulls, (2) the use of village bulls, and (3) the rotational use of village bulls within village groups, were simulated using a stochastic simulation approach. For each breeding scenario, 3 selection methods for bulls were considered, namely random mating, phenotypic selection, and selection based on estimated breeding value (EBV). The results showed that no genetic gain was realized with random mating in all breeding scenarios. In the farm bull breeding scenario, annual genetic gain (standard deviation units) ranged from 0.01 to 0.19 (phenotypic selection) and from 0.01 to 0.39 (selection based on EBV). In the village bull breeding scenarios, the annual genetic gain ranged from 0.01 to 0.21 (phenotypic selection) and 0.01 to 0.45 (selection based on EBV). The lowest genetic gain was realized for the rotational use of village bulls among villages within groups. Through the rotational use of village bulls, however, a higher genetic variance was maintained than in the farm and village bull breeding scenarios. We concluded that a village bull breeding program with selection based on EBV of young bulls was the most promising breeding design for achieving the breeding goal. Further studies are needed to assess the organizational feasibility of such a breeding program to ensure the participation of smallholder producers and its sustainability.     

Genetic heterogeneity of feed intake,energy-corrected milk,and body weight across lactation in primiparous Holstein,Nordic Red,and Jersey cows

In this study, we aimed to estimate and compare the genetic parameters of dry matter intake (DMI), energy-corrected milk (ECM), and body weight (BW) as 3 feed efficiency–related traits across lactation in 3 dairy cattle breeds (Holstein, Nordic Red, and Jersey). The analyses were based on weekly records of DMI, ECM, and BW per cow across lactation for 842 primiparous Holstein cows, 746 primiparous Nordic Red cows, and 378 primiparous Jersey cows. A random regression model was applied to estimate variance components and genetic parameters for DMI, ECM, and BW in each lactation week within each breed. Phenotypic means of DMI, ECM, and BW observations across lactation showed to be in very similar patterns between breeds, whereas breed differences lay in the average level of DMI, ECM, and BW. Generally, for all studied breeds, the heritability for DMI ranged from 0.2 to 0.4 across lactation and was in a range similar to the heritability for ECM. The heritability for BW ranged from 0.4 to 0.6 across lactation, higher than the heritability for DMI or ECM. Among the studied breeds, the heritability estimates for DMI shared a very similar range between breeds, whereas the heritability estimates for ECM tended to be different between breeds. For BW, the heritability estimates also tended to follow a similar range between breeds. Among the studied traits, the genetic variance and heritability for DMI varied across lactation, and the genetic correlations between DMI at different lactation stages were less than unity, indicating a genetic heterogeneity of feed intake across lactation in dairy cattle. In contrast, BW was the most genetically consistent trait across lactation, where BW among all lactation weeks was highly correlated. Genetic correlations between DMI, ECM, and BW changed across lactation, especially in early lactation. Energy-corrected milk had a low genetic correlation with both DMI and BW at the beginning of lactation, whereas ECM was highly correlated with DMI in mid and late lactation. Based on our results, genetic heterogeneity of DMI, ECM, and BW across lactation generally was observed in all studied dairy breeds, especially for DMI, which should be carefully considered for the recording strategy of these traits. The genetic correlations between DMI, ECM, and BW changed across lactation and followed similar patterns between breeds.     

Implementing a genomic rotational crossbreeding scheme to promote local dairy cattle breeds—A simulation study

In dairy cattle breeding, there is a clear trend toward the use of only a few high-yielding breeds. One main reason is that efficient breeding programs require a certain population size. Since some numerically small breeds are well known for their functional traits, they might be an interesting crossing partner for high-yielding breeds with the aim to utilize heterosis. This simulation study investigated the transition period of a small cattle population for the implementation of genomic selection and rotational crossbreeding with a high-yielding breed. Real SNP chip genotype data from the numerically small red dairy breed Angler and the high-yielding breed Holstein Friesian were used to simulate the base generations, from which rotational crossbreeding was conducted for 10 generations. A polygenic trait with many quantitative trait loci with additive and directional dominance effects was simulated. Different selection methods for Angler sires (purebred performance, crossbred performance, and weighted purebred-crossbred performance) and different sizes and structures of the reference population (Angler, crossbred animals, and Angler plus crossbred animals) were considered. The results showed that the implementation of a genomic rotational crossbreeding scheme is an appealing option to promote the numerically small Angler breed. The growing reference population consisting of Angler and crossbred individuals maximized the genetic gain for Angler and the performance level for the crossbred individuals. Selection for purebred performance, crossbred performance, or a weighted combination of both hardly affected the results, and differences between selection scenarios were observed only in the long term with decreasing purebred-crossbred correlations.     

Consequences of selection for milk yield from a geneticist's viewpoint

The annual genetic trend for milk yield of Holsteins in the United States has accelerated with time and had means of 37 kg during the 1960s, 79 kg during the 1970s, 102 kg during the 1980s, and 116 kg from 1990 to 1996. Selection programs of the dairy cattle breeding firms in the United States have become more selective and effective with time, and selection goals continue to place major emphasis on yield traits, which clearly impact profitability of dairying. Traits other than yield are also included in selection goals of the industry. Type traits, especially those related to udder conformation, body size, and angularity have been included in selection programs and have altered the appearance and physiological functions of Holstein cows. Selection programs have continued to increase the body size of Holsteins despite mounting evidence that smaller cows have advantages for survival and efficiency. Favorable emphasis on cows that appear sharper might result in cows that are more prone to metabolic problems. The high intensity of current selection in the United States has brought about a rapid increase in genetic relationships among animals. Increased relationships will inevitably result in undesirable levels of inbreeding in the commercial cow population unless dairy producers turn to crossbreeding.