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.     

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.     

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.     

Novel strategies to minimize progeny inbreeding while maximizing genetic gain using genomic information

In this study, 3 strategies for controlling progeny inbreeding in mating plans were compared. The strategies used information from pedigree inbreeding coefficients, genomic relationships, or shared runs of homozygosity. The strategies were compared for the reduction in genetic gain and progeny inbreeding that would be expected from selected matings, and for the decrease of homozygosity of deleterious recessive alleles. Using real pedigree, genotype [43,115 single nucleotide polymorphism (SNP) markers], and estimated breeding value data from Holstein cattle, mating plans were derived for herds of 300 cows with 20 sires available for mating, replicated 50 times. Each of the 300 individuals allocated as dams were matched to 1 of 20 sires to maximize genetic merit minus the penalty for estimated progeny inbreeding, and given the restriction that the sire could not be mated to more than 10% of the cows. The strategy that used a genomic relationship matrix (GRM) was the most effective in reducing average progeny inbreeding; this strategy also resulted in fewer homozygous SNP out of 1,000 low-frequency SNP compared with the strategy using pedigree information. In the future, large numbers of cattle may be genotyped for low-density SNP panels. A GRM constructed using 3,123 SNP produced results similar to a GRM constructed using the full 43,115 SNP. These results demonstrate that using GRM information, a 1% reduction in progeny inbreeding (valued at around $5 per cow) can be made with very little compromise in the overall breeding objective. These results and the availability of low-cost, low-density genotyping make it attractive to apply mating plans that use genomic information in commercial dairy herds.     

Rates of inbreeding and genetic diversity in Canadian Holstein and Jersey cattle

The accumulation of inbreeding and the loss of genetic diversity is a potential problem in the modern dairy cattle breeds. Therefore, the purpose of this study was to analyze the pedigrees of Canadian Holstein and Jersey cattle to estimate the past and current rates of inbreeding and genetic diversity, and to identify the main causes of diversity loss. Completeness and depth of the pedigrees were good for both breeds. For Holsteins, the average rates of inbreeding per generation showed a decreasing trend in recent years when compared with the 1990s. The estimated current effective population size was about 115 for Holsteins and is not expected to significantly change in the near future if generation intervals stay at current value, as rates of increase in inbreeding and coancestry showed decreasing trends. For Jerseys, the estimated effective population size was about 55 and it is expected to decrease in the near future due to the observed increasing rates of coancestry and inbreeding. Ancestors with the highest marginal genetic contributions to the gene pool in current years and with the highest contributions to inbreeding were identified. The 2 most heavily used and represented ancestors in the Holstein pedigree (i.e., Round Oak Rag Apple Elevation and his son Hanoverhill Starbuck), accounted for 30% of inbreeding. Analyses revealed that the most important cause of genetic diversity loss in both breeds was genetic drift accumulated over nonfounder generations, which occurred due to small effective population size. Therefore, a need exists in both breeds, particularly in Jerseys, for managing selection and mating decisions to control future coancestry and inbreeding, which would lead to better handling of the effective population size.     

Mating allocations in Holstein combining genomic information and linear programming optimization at the herd level

In this study, we explored mating allocation in Holstein using genomic information for 24,333 Holstein females born in Denmark, Finland, and Sweden. We used 2 data sets of bulls: the top 50 genotyped bulls and the top 25 polled genotyped bulls on the Nordic total merit scale. We used linear programming to optimize economic scores within each herd, considering genetic level, genetic relationship, semen cost, the economic impact of genetic defects, polledness, and β-casein. We found that it was possible to reduce genetic relationships and eliminate expression of genetic defects with minimal effect on the genetic level in total merit index. Compared with maximizing only Nordic total merit index, the relative frequency of polled offspring increased from 13.5 to 22.5%, and that of offspring homozygous for β-casein (A2A2) from 66.7 to 75.0% in one generation, without any substantial negative impact on other comparison criteria. Using only semen from polled bulls, which might become necessary if dehorning is banned, considerably reduced the genetic level. We also found that animals carrying the polled allele were less likely to be homozygous for β-casein (A2A2) and more likely to be carriers of the genetic defect HH1. Hence, adding economic value to a monogenic trait in the economic score used for mating allocation sometimes negatively affected another monogenetic trait. We recommend that the comparison criteria used in this study be monitored in a modern genomic mating program.     

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.     

Identification of functional candidate variants and genes for feed efficiency in Holstein and Jersey cattle breeds using RNA-sequencing

The identification of functional genetic variants and associated candidate genes linked to feed efficiency may help improve selection for feed efficiency in dairy cattle, providing economic and environmental benefits for the dairy industry. This study used RNA-sequencing data obtained from liver tissue from 9 Holstein cows [n = 5 low residual feed intake (RFI), n = 4 high RFI] and 10 Jersey cows (n = 5 low RFI, n = 5 high RFI), which were selected from a single population of 200 animals. Using RNA-sequencing, 3 analyses were performed to identify: (1) variants within low or high RFI Holstein cattle; (2) variants within low or high RFI Jersey cattle; and (3) variants within low or high RFI groups, which are common across both Holstein and Jersey cattle breeds. From each analysis, all variants were filtered for moderate, modifier, or high functional effect, and co-localized quantitative trait loci (QTL) classes, enriched biological processes, and co-localized genes related to these variants, were identified. The overlapping of the resulting genes co-localized with functional SNP from each analysis in both breeds for low or high RFI groups were compared. For the first two analyses, the total number of candidate genes associated with moderate, modifier, or high functional effect variants fixed within low or high RFI groups were 2,810 and 3,390 for Holstein and Jersey breeds, respectively. The major QTL classes co-localized with these variants included milk and reproduction QTL for the Holstein breed, and milk, production, and reproduction QTL for the Jersey breed. For the third analysis, the common variants across both Holstein and Jersey breeds, uniquely fixed within low or high RFI groups were identified, revealing a total of 86,209 and 111,126 functional variants in low and high RFI groups, respectively. Across all 3 analyses for low and high RFI cattle, 12 and 31 co-localized genes were overlapping, respectively. Among the overlapping genes across breeds, 9 were commonly detected in both the low and high RFI groups (INSRR, CSK, DYNC1H1, GAB1, KAT2B, RXRA, SHC1, TRRAP, PIK3CB), which are known to play a key role in the regulation of biological processes that have high metabolic demand and are related to cell growth and regeneration, metabolism, and immune function. The genes identified and their associated functional variants may serve as candidate genetic markers and can be implemented into breeding programs to help improve the selection for feed efficiency in dairy cattle.     

Characterization of the DGAT1 K232A and variable number of tandem repeat polymorphisms in French dairy cattle

A quantitative trait locus (QTL) underlying different milk production traits has been identified with a high significance threshold value in the genomic region containing the acylCoA:diacylglycerol acyltransferase (DGAT1) gene, in the 3 main French dairy cattle breeds: French Holstein, Normande, and Montbéliarde. Previous studies have confirmed that the K232A polymorphism in DGAT1 is responsible for a major QTL underlying several milk production traits in Holstein dairy cattle and several other bovine breeds. In this study, we estimate the frequency of the 2 alternative alleles, K and A, of the K232A polymorphism in French Holstein, Normande, and Montbéliarde breeds. Although the K allele segregates in French Holstein and Normande breeds with a similar effect on production traits, the existence of additional mutations contributing to the observed QTL effect is strongly suggested in both breeds by the existence of sires heterozygous at the QTL but homozygous at the K232A polymorphism. One allele at a variable number of tandem repeats (VNTR) locus in the 5′ noncoding region of DGAT1 has been recently proposed as a putative causative variant. In our study, this marker was found to present a high mutation rate of 0.8% per gamete and per generation, making the allele diversity observed compatible with that expected under neutrality. Moreover, among the sires homozygous at the K232A polymorphism, no allele at the VNTR can fully explain their QTL status. Finally, no allele at the VNTR was found to be significantly associated with the fat percentage variation in the 3 breeds simultaneously after correction for the effect of the K232A polymorphism. Therefore, our results suggest the existence of at least one other causative polymorphism not yet described. Because the A allele is nearly fixed in the Montbéliarde breed, this breed represents an interesting model to identify and confirm other mutations that have a strong effect on milk production traits.     

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.     

Characterization of semen type prevalence and allocation in Holstein and Jersey females in the United States

Our objective was to characterize semen type prevalence and allocation to inseminate US Holstein and Jersey females by year, parity, service number, and herd size. A secondary objective was to identify the prevalence of beef breed sires selected to create beef × Holstein and beef × Jersey crossbred calves. The final data set included 8,244,653 total inseminations of 4,880,752 Holstein females across 9,155 herds, and 435,267 total inseminations of 266,058 Jersey females across 2,759 herds from October 2019 to July 2021. This data set represents approximately 42 and 27% of the total dairy cows and heifers, respectively, across approximately 40% of the total licensed dairy herds in the continental United States. Holstein and Jersey females were inseminated with 1 of 4 semen types: (1) beef, (2) conventional, (3) sexed, or (4) other dairy. The top 4 beef breeds used to produce beef × Holstein and beef × Jersey crossbred calves, respectively, were Angus (55.1 and 39.1%), Limousin (13.9, and 23.5%), Simmental (11.7 and 20.5%), and Crossbreed Beef (11.3 and 4.8%). From 2019 to 2021, the use of sexed semen to inseminate Holstein and Jersey females increased from 11.0 and 24.5% to 17.7 and 32.1%, respectively, and the use of beef semen to inseminate Holstein and Jersey females increased from 18.2 and 11.4% to 26.1 and 21.2%, respectively. The use of beef semen to inseminate Holstein and Jersey females increased with increasing parity and service number, whereas the use of sexed semen decreased with increasing parity and service number supporting that farmers used sexed semen more aggressively in higher fertility and younger females with greater genetic merit. Overall, the increase in sexed and beef semen inseminations was driven primarily by larger herds. In conclusion, sexed and beef semen inseminations in US Holstein and Jersey females increased from 2019 to 2021 and was allocated differentially based on parity and service number. This increase was driven primarily by larger dairy herds possibly due to differences in reproductive performance and economies of scale.     

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.     

Ranking sires using genetic selection indices based on financial investment methods versus lifetime net merit

Current USDA selection indices such as lifetime net merit (NM$) estimate lifetime profit differences, which are accurately approximated by a linear combination of 13 traits. In these indices, every animal gets credit for 2.78 lactations of the traits expressed per lactation, such as fat and protein, independent of its productive life (PL). This formulation may over- or underestimate the net revenue from traits expressed per lactation depending on PL. The objectives were to develop 2 genetic selection indices using financial investment methods to account for differences in PL and to compare them with the 2017 NM$ for marketed Holstein sires. Selection among animals with different PL is an example of investment in mutually exclusive projects that have unequal duration. Financial investment theory says that such projects are best compared with the annualized net present value (ANPV) method when replacement occurs with technologically equal assets. However, genetic progress implies that future available replacement animals are technologically improved assets. Asset replacement theory with improved assets results in an annualized value including genetic opportunity cost (AVOC) for each animal. We developed the ANPV and AVOC and compared these with the NM$ for 1,500 marketed Holstein sires from the December 2017 genetic evaluation. The lowest Pearson correlation coefficient was 0.980 between AVOC and NM$, whereas the highest was 0.999 between ANPV and NM$ among the 1,500 sires. Correlations for the top 300 sires were lower. Although we found high correlations between indices, the 95th and 5th percentiles of individual rank changes between AVOC and NM$ were +131 and ?163 positions, respectively, whereas these changes between ANPV and NM$ were +27 and ?45 positions, respectively. The relative emphasis of PL in the AVOC index was half of the relative emphasis in NM$. These results show that applying financial investment methods to value differences in genetic merit of animals changes their rankings compared with the NM$ formulation. Rank changes were meaningful enough that the new indices warrant consideration for use in practice.     

Selection and mating considering expected inbreeding of future progeny

Animals most related or least related to current members of their breed were revealed by calculating the expected inbreeding of their future progeny. A sample of potential mates was chosen by randomly selecting 600 females from a recent birth year (1995). Relationships among the sample were computed by the tabular method. Relationships of other animals to the sample population were computed quickly from the relationships of their parents or ancestors. To-Mar Blackstar-ET and Round Oak Rag Apple Elevation were most related to the Holstein breed with expected inbreeding of 7.9 and 7.7%, respectively. Corresponding Jersey bulls were Highland Magic Duncan and Soldierboy Boomer Sooner of CJF with expected inbreeding of 10.9 and 9.5%, respectively. The highest expected inbreeding was 11.1% for Selwood Bettys Commander, 8.6% for Forest Lawn Simon Jetway, 10.1% for Dutch Mill Telestars Fayette, and 7.4% for Korncrest Pacesetter for Ayrshire, Brown Swiss, Guernsey, and Milking Shorthorn breeds, respectively. Regression on inbreeding in the genetic evaluation model removed effects of past inbreeding. Future inbreeding effects could be included for each potential mating or by adjusting breeding values for average inbreeding expected with random mating. The correlation between Holstein breeding values unadjusted and adjusted for inbreeding was 0.9976. The estimated genetic trend was 6% lower with future inbreeding included.     

Short communication: Use of young bulls in the United States

The availability of genomic evaluations since 2008 has resulted in many changes to dairy cattle breeding programs. One such change has been the increased contribution of young bulls (0.8 to 3.9 yr old) to those programs. The increased use of young bulls was investigated using pedigree data and breeding records obtained from the US national dairy database (Beltsville, MD). The adoption of genotyping was so rapid that by 2009, >90% of all Holstein artificial insemination (AI) service sires and 86% of Jersey AI service sires were genotyped, regardless of age. The percentage of sons sired by young bulls increased by 49 percentage points (10% in 2008 compared with 59% in 2012) due to the onset of genomic evaluations for Holsteins and by 46 percentage points for Jerseys (11 and 57%, respectively). When limiting these data to sons retained for breeding purposes through AI, the increase was even more dramatic, increasing approximately 80 percentage points from 2008 to 2012 for both Holsteins and Jerseys (1, 5, 28, 52, and 81% for Holsteins and 3, 4, 43, 46, and 82% for Jerseys from 2008 through 2012). From US breeding records from 2007 through 2012, 24,580,793 Holstein and 1,494,095 Jersey breedings were examined. Young bulls accounted for 28% and 25% of Holstein and Jersey breedings in 2007, respectively. These percentages increased to 51% of Holstein and 52% of Jersey breedings in 2012, representing 23- and 27-percentage-unit increases, respectively. Matings to genotyped young bulls have rapidly increased while the use of nongenotyped bulls has diminished since the onset of genomics. Mean sire age for Holstein male progeny born in 2012 was 2.7 yr younger than males born in 2006, and 1.3 yr younger for females; corresponding values for Jerseys were 2.3 and 0.9 yr. Holstein male offspring had an increase of 281 kg between 2006 and 2012, compared with 197 kg between 2000 and 2006 for parent averages (PA) for milk, an increase of 84 kg between the 2 periods. Jersey male offspring had an increase of 49 kg between the 2 periods. To demonstrate the economic impact of the differential use of young bulls, herds were grouped by the frequency of their use of young bulls, and average PTA for milk and net merit for cows that were bred in 2003 through 2012 were calculated. In 2012, herds using >75% young bulls created offspring that had a PA of +52 kg for milk and +$58 net merit compared with herds using no young bulls. Jersey herds using >75% young bulls created offspring that had a PA of +142 kg for milk and +$63 for net merit compared with herds using no young bulls. Use of young bulls has greatly reduced the generation interval and improved the rate of genetic gain since the implementation of genomic evaluations.     

Selection with inbreeding control in simulated young bull schemes for local dairy cattle breeds

Local breeds are rarely subject to modern selection techniques; however, selection programs will be required if local breeds are to remain a viable livelihood option for farmers. Selection in small populations needs to take into account accurate inbreeding control. Optimum contribution selection (OCS) is efficient in controlling inbreeding and maximizes genetic gain. The current paper investigates genetic progress in simulated dairy cattle populations from 500 to 6,000 cows undergoing young bull selection schemes with OCS compared with truncation selection (TS) at an annual inbreeding rate of 0.003. Selection is carried out for a dairy trait with a base heritability of 0.3. A young bull selection scheme was used because of its simplicity in implementation. With TS, annual genetic gain from 0.111 standard deviation units with 500 cows increases rapidly to 0.145 standard deviation units with 4,000 cows. Then, genetic gain increases more slowly up to 6,000 cows. At the same inbreeding rate, OCS produces higher genetic progress than TS. Differences in genetic gain between OCS and TS vary from to 2 to 6.3%. Genetic gain is also improved by increasing the number of years that males can be used as sires of sires. When comparing OCS versus TS at different heritabilities, we observe an advantage of OCS only at high heritability, up to 8% with heritability of 0.9. By increasing the constraint on inbreeding, the difference of genetic gain between the 2 selection methods increases in favor of OCS, and the advantage at the inbreeding rate of 0.001 per generation is 6 times more than at the inbreeding rate of 0.003. Opportunities exist for selection even in dairy cattle populations of a few hundred females. In any case, selection in local breeds will most often require specific investments in infrastructure and manpower, including systems for accurate data recording and selection skills and the presence of artificial insemination and breeders organizations. A cost-benefit analysis is therefore advisable before considering the implementation of selection schemes in local dairy cattle breeds.     

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.     

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.     

Producer breeding objectives and optimal sire selection

Information from an online survey of dairy producers was used to determine how important producers perceived three different objectives in the breeding problem. The objectives were: maximizing expected net merit of the progeny, minimizing the expected progeny inbreeding coefficient, and minimizing semen expenditure. Producers were asked to rank the three objectives and then to weight the importance of each objective relative to the others. This information was then used to determine weights to be used in a multiple-objective integer program designed to select individual mates for a herd of 76 Jersey cows with known genetic background and cow net merit. The results of the multiple-objective models show that rank and relative importance of producer objectives can affect the portfolio of sires selected. Producers whose primary objective was to maximize expected net merit had a range of average expected progeny net merit of $306 to $310, but the level of expected progeny inbreeding was from 6.99 to 10.45%, with a semen cost per conception of $35 to $41. For producers who selected minimizing progeny inbreeding as the primary goal in their breeding programs, the range of inbreeding was from 6.11 to 6.60%, with lower net merit range of $274 to $301 and semen expenditure of $30 to $37 per conception. One producer selected minimizing semen cost as the primary objective. For that producer's portfolio, the semen cost was $27 per conception and net merit was $288, with a progeny inbreeding coefficient of 10.68%. The results of this research suggest that producer information and goals have a substantial impact on the portfolio of sires selected by that producer to attain these goals.     

Use of computerized mate selection programs to control inbreeding of Holstein and Jersey cattle in the next generation

The expected role of computerized mate selection programs with regard to inbreeding and lifetime profitability of Holstein and Jersey cattle was examined using data from 25 large registered herds of each breed. Sire selection and mate allocation were carried out using linear programming with the following objectives: 1) minimum inbreeding, 2) maximum net merit subject to a fixed inbreeding threshold, and 3) maximum expected lifetime profit after adjustment for inbreeding depression. Inbreeding of actual matings was similar to inbreeding from random matings, indicating that current inbreeding avoidance programs in these herds are ineffective. Inbreeding was reduced by 1.6 and 1.9% in Holsteins and Jerseys, respectively, when a mate allocation program was applied with service sires and usage levels fixed at the actual values. Benefits of mate selection programs increased when both sire selection and mate pair allocation were considered. Maximization of mean net merit with inbreeding restricted to a fixed level (5% in Holsteins and 8% in Jerseys) led to decreases in inbreeding of 0.9 and 1.4% and increases in lifetime profit of $16.66 and $26.86 in Holsteins and Jerseys, respectively, relative to programs that ignored inbreeding. Maximization of mean expected lifetime profit after adjustment for inbreeding depression decreased inbreeding by 1.8 and 2.8% and increased lifetime profit by $37.37 and $59.77 in Holsteins and Jerseys, respectively. Inbreeding coefficients estimated with pedigree traced to 1985 were inadequate predictors of inbreeding coefficients estimated with pedigrees traced to 1960. Mate selection programs cannot function optimally unless extensive historical pedigree data are available, particularly for service sires. Computerized mate selection programs can reduce inbreeding in the next generation, which will lead to an increase in farm profitability. However, if genetic diversity is to be maintained in the long term, procedures for selecting parents of AI sires must also be considered.