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.     

Optimal Genetic Improvement for the High Producing Cow

Many 40,000-lb (18,144 kg) cows exist in today's dairy population, but herds capable of 40,000-lb averages for all cows remain to be developed. Traditional genetic improvement practices, based on consistent use of current high-ranking AI bulls selected to improve economically important traits, will remain important tools to develop high producing cows. Future breeding strategies will likely include attention to how high production is achieved and may include direct selection for increased appetite or some measure of energy balance to support high production, reproduction, and immune function. Direct selection for improved fertility, perhaps involving traits not presently used in herd management, may prove to be necessary as yields increase. Roles for evolving technologies such as marker-assisted selection, manipulation of the bovine genome, and cloning remain unclear, but will likely be incorporated into traditional progeny testing schemes. Equipment to routinely monitor physiological functions may encourage the establishment of large progeny test herds with expanded data recording capability. The expense could lead to proprietary genetic lines and private genetic evaluation systems such as exist in poultry and swine. Pedigree information will become more important in commercial herds to manage inbreeding. The dairy industry can expect to benefit from current research efforts in human genetics. However, current funding of dairy breeding research in the United States will limit the number of individuals trained in methods to implement those results in dairy cattle.     

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.     

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.     

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.     

Invited review: Beef-on-dairy—The generation of crossbred beef × dairy cattle

Because a growing proportion of the beef output in many countries originates from dairy herds, the most critical decisions about the genetic merit of most carcasses harvested are being made by dairy producers. Interest in the generation of more valuable calves from dairy females is intensifying, and the most likely vehicle is the use of appropriately selected beef bulls for mating to the dairy females. This is especially true given the growing potential to undertake more beef × dairy matings as herd metrics improve (e.g., reproductive performance) and technological advances are more widely adopted (e.g., sexed semen). Clear breed differences (among beef breeds but also compared with dairy breeds) exist for a whole plethora of performance traits, but considerable within-breed variability has also been demonstrated. Although such variability has implications for the choice of bull to mate to dairy females, the fact that dairy females themselves exhibit such genetic variability implies that “one size fits all” may not be appropriate for bull selection. Although differences in a whole series of key performance indicators have been documented between beef and beef-on-dairy animals, of particular note is the reported lower environmental hoofprint associated with beef-on-dairy production systems if the environmental overhead of the mature cow is attributed to the milk she eventually produces. Despite the known contribution of beef (i.e., both surplus calves and cull cows) to the overall gross output of most dairy herds globally, and the fact that each dairy female contributes half her genetic merit to her progeny, proxies for meat yield (i.e., veal or beef) are not directly considered in the vast majority of dairy cow breeding objectives. Breeding objectives to identify beef bulls suitable for dairy production systems are now being developed and validated, demonstrating the financial benefit of using such breeding objectives over and above a focus on dairy bulls or easy-calving, short-gestation beef bulls. When this approach is complemented by management-based decision-support tools, considerable potential exists to improve the profitability and sustainability of modern dairy production systems by exploiting beef-on-dairy breeding strategies using the most appropriate beef bulls.     

Optimization of dairy cattle breeding programs for different environments with genotype by environment interaction

Dairy cattle breeding organizations tend to sell semen to breeders operating in different environments and genotype × environment interaction may play a role. The objective of this study was to investigate optimization of dairy cattle breeding programs for 2 environments with genotype × environment interaction. Breeding strategies differed in 1) including 1 or 2 environments in the breeding goal, 2) running either 1 or 2 breeding programs, and 3) progeny testing bulls in 1 or 2 environments. Breeding strategies were evaluated on average genetic gain of both environments, which was predicted by using a pseudo-BLUP selection index model.When both environments were equally important and the genetic correlation was higher than 0.61, the highest average genetic gain was achieved with a single breeding program with progeny-testing all bulls in both environments. When the genetic correlation was lower than 0.61, it was optimal to have 2 environment-specific breeding programs progeny-testing an equal number of bulls in their own environment only. Breeding strategies differed by 2 to 12% in average genetic gain, when the genetic correlation ranged between 0.50 and 1.00. Ranking of breeding strategies, based on the highest average genetic gain, was relatively insensitive to heritability, number of progeny per bull, and the relative importance of both environments, but was very sensitive to selection intensity. With more intense selection, running 2 environment-specific breeding programs was optimal for genetic correlations up to 0.70-0.80, but this strategy was less appropriate for situations where 1 of the 2 environments had a relative importance less than 10 to 20%. Results of this study can be used as guidelines to optimize breeding programs when breeding dairy cattle for different parts of the world.     

Heritabilities and genetic correlations of body condition score and calving interval with yield, somatic cell score, and linear type traits in Brown Swiss cattle

This study aimed to estimate genetic parameters for body condition score (BCS), calving interval (CI), somatic cell score (SCS), yield, and linear type traits for the Italian Brown Swiss cattle population. A total of 32,359 records of first-parity lactating cows were collected from 2002 to 2004 in 4,885 dairy herds. The pedigree file included 96,661 animals. Multiple-trait animal models were analyzed using REML to estimate (co)variance components without repeated observations on traits. The estimated heritability was 0.15 for BCS, 0.05 for CI, and 0.06 for SCS, and ranged from 0.09 to 0.14 for test-day yield traits and from 0.07 to 0.32 for linear type traits. The genetic correlations of CI with yield and most linear type traits were positive, whereas the correlation between CI and BCS was negative (−0.35). For type traits, BCS showed, in general, a moderately negative genetic correlation except for strength, pastern, and heel height. The genetic correlation of CI or BCS with SCS was moderately low but favorable (0.19 and −0.26, respectively). The estimated correlations indicated that selection for greater yield and type traits can exert unfavorable effects on the reproductive ability of cows. To counterbalance these effects and to carry out early prediction of breeding values of bulls for fertility, inclusion of BCS in the breeding program is advisable.     

Defining a nitrogen efficiency index in Holstein cows and assessing its potential effect on the breeding program of bulls

The purposes of this study were (1) to explore the relationship between 3 milk mid-infrared predicted features including nitrogen intake (NINT), milk true protein N (MTPN), and milk urea-N yield (MUNY); (2) to integrate these 3 features into an N efficiency index (NEI) and analyses approximate genetic correlations between the NEI and 37 traits (indices) of interest; and (3) to assess the potential effect of including the NEI into breeding programs of bulls. The edited data were 1,043,171 test-day records on 342,847 cows in 1,931 herds and 143,595 test-day records on 53,660 cows in 766 herds used for estimating breeding values (EBV) and variance components, respectively. The used records were within 5 to 50 d in milk. The records were grouped into primiparous and multiparous. The genetic parameters for the included mid-infrared features and EBV of the animals included in the pedigree were estimated using a multiple-trait repeatability animal model. Then, the EBV of the NINT, MTPN, MUNY were integrated into the NEI using a selection index assuming weights based on the N partitioning. The approximate genetic correlations between the NEI and 37 traits of interest were estimated using the EBV of the selected bulls. The bulls born from 2011 to 2014 with NEI were selected and the NEI distribution of these bulls having EBV for the 8 selected traits (indices) was checked. The heritability and repeatability estimates for NINT, MTPN, and MUNY ranged from 0.09 to 0.13, and 0.37 to 0.65, respectively. The genetic and phenotypic correlations between NINT, MTPN, and MUNY ranged from ?0.31 to 0.87, and ?0.02 to 0.42, respectively. The NEI ranged from ?13.13 to 12.55 kg/d. In total, 736 bulls with reliability ≥0.50 for all included traits (NEI and 37 traits) and at least 10 daughters distributed in at least 10 herds were selected to investigate genetic aspects of the NEI. The NEI had positive genetic correlations with production yield traits (0.08–0.46), and negative genetic correlations with the investigated functional traits and indices (?0.71 to ?0.07), except for the production economic index and functional type economic index. The daughters of bulls with higher NEI had lower NINT and MUNY, and higher MTPN. Furthermore, 26% of the bulls (n = 50) with NEI born between 2011 to 2014 had higher NEI and global economic index than the average in the selected bulls. Finally, the developed NEI has the advantage of large-scale prediction and therefore has the potential for routine application in dairy cattle breeding in the future.     

Derivation of economic values for German dairy breeds by means of a bio-economic model—with special emphasis on functional traits

To assess the economic importance of breeding traits, economic values (EV) were derived for 3 German dairy cattle breeds: German Holstein (HOL), Angler (ANG), and Red and White Dual-Purpose (RDN). For that purpose, the stochastic bio-economic model SimHerd (SimHerd A/S, Viborg, Denmark) was used, which simulates the expected monetary gain in dairy herds. The EV was calculated as the alteration in average net return of the herd responding to a marginal change in the trait of interest. When deriving EV using SimHerd, economic consequences resulting from changes in the age structure of a dairy herd (i.e., structural herd effects) are considered. However, this requires the simulation of relationships between traits in the bio-economic model. To avoid double counting, the EV of a trait was corrected for effects from alterations in correlated traits using multiple regression analysis. The EV were derived for 23 traits in terms of production, conformation and workability, dairy health, calf survival, and reproduction performance. Furthermore, the relative economic importance of the breeding traits was calculated. Relative emphasis on production was between 39.9 and 44.4% in the breeds studied. Total costs per case of ketosis and metritis ranged from €167 to €196 and €173 to €182, respectively. Highest marginal EV of direct health traits were found for mastitis (€257 to €271 per case) and lameness (€270 to €310 per case). Consequently, relative emphasis on direct health traits was between 15.7 and 17.9%. The EV of reproduction performance showed largest differences among the cattle breeds. Overall relative emphasis on reproduction was 10.5% in HOL, 10.8% in ANG, and 6.5% in RDN. The relative economic importance of cow mortality ranged from 15.5 to 16.0% across the breeds. Collectively, the study showed the high economic importance of functional traits in the cattle breeds studied.     

Economic basis for the Nordic Total Merit Index

Within a group of cooperating countries, all breeding animals are judged according to the same criteria if a joint breeding goal is applied in these countries. This makes it easier for dairy farmers to compare national and foreign elite bulls and may lead to more selection across borders. However, a joint breeding goal is only an advantage if the countries share the same production environment. In this study, we investigated whether the development of a joint breeding goal for each of the major dairy cattle breeds across Denmark, Finland, and Sweden would be an advantage compared with national breeding goals. For that purpose, economic values for all breeding goal traits in the 3 countries were derived, and estimated rank correlations between bulls selected for a national breeding goal and a joint breeding goal were compared. The economic values within country were derived by means of an objective bio-economic model, and the basic situation in each of the 3 production environments was based on an average dairy cattle herd with regard to production system, production level, and management strategy. The common Nordic economic values for each trait were calculated as the average of that specific trait in each of the 3 production environments. Balanced breeding goals were obtained in all situations because the derived economic values for traits related to health, fertility, milk production, and longevity were sizeable. For both Nordic Red Dairy Cattle and Nordic Holstein, the estimated rank correlations between bulls selected for a national breeding goal and a joint breeding goal were very high. Thus, a joint breeding goal within breed is feasible for Denmark, Finland, and Sweden.     

Variants in the pregnancy-associated plasma protein-A2 gene on Bos taurus autosome 16 are associated with daughter calving ease and productive life in Holstein cattle

Reproductive disorders in dairy herds have a negative effect on farm profitability and sustainability of milk production. Given the substantial evidence of the role of the pregnancy-associated plasma protein (PAPP) gene family in the regulation of reproduction in humans and mice, its role in insulin-like growth factor metabolism, quantitative trait loci effects in the mouse, and location of a calving ease QTL on bovine chromosome 16, the PAPP-A2 gene was chosen as a candidate gene to perform an association study for reproductive health in cattle. Single nucleotide polymorphisms (SNP) were identified in coding and conserved noncoding regions of the PAPP-A2 gene in 3 dairy breeds. A total of 7 tag SNP were genotyped in 662 Holstein bulls (UCD-bulls) to perform marker trait association analysis. Three SNP (SNP 13, 15, and 16) were in strong linkage disequilibrium in Holsteins, showing significant positive associations with daughter calving ease, productive life, milk yield, and protein yield. These results were validated by genotyping SNP15 in a larger population of 992 bulls from the cooperative dairy DNA repository (CDDR-bulls). Our results demonstrate that the PAPP-A2 gene is associated with reproductive health in Holstein cattle and that the identified SNP can be used as genetic markers in dairy breeding due to their positive association with reproductive and productive traits. Functional studies need to be conducted to identify the mechanisms for the association of SNP with these traits.     

Herd manager attitudes and intentions regarding the selection of high-fertility EBV sires in Australia

Reproductive performance in dairy cattle has declined over the last 50 years as an unintended consequence of selection for high milk yield. Since the early 2000s, dairy geneticists have released successive versions of fertility estimated breeding values (EBV) to assist in reversing this trend. At the herd level, fertility EBV can help managers accelerate improvements in reproductive performance by acting as a second selection criteria when used in tandem with a breeding index. However, use of the fertility EBV in sire selection currently varies between herd managers. The aim of this study was to better understand the reasons why herd managers choose or do not choose to select high-fertility EBV sires, using the Theory of Planned Behavior (TPB) as a social research framework. Thirty-five Victorian dairy herd managers were recruited as part of a larger study investigating the daughter fertility Australian Breeding Value and interviewed using a series of questions examining TPB constructs. The interviews were recorded and transcribed using template analysis. A wide range of herd manager types were enrolled into the study, with representation from diverse systems. Out of the 35 herd managers, 27 included fertility in their list of high-priority breeding objectives. A wide variation in results was consistent with previous studies that have demonstrated marked heterogeneity in herd manager attitudes toward bull selection. Herd manager-perceived barriers to selection of sires with high daughter fertility EBV included a lack of high daughter fertility bulls with other desirable traits, a lack of trust in the fertility EBV or in the Australian EBV system, difficulty in interpreting international proofs, information overload, semen prices, low bull reliability, and difficulty in understanding bull catalogs. Not all herd managers found the process problematic, however, particularly if a breeding consultant was employed to select all or most of the sires. Herd manager-perceived barriers for choosing to select daughter fertility as a breeding objective include a lack of awareness of the EBV, a lack of interest in genetics in general, low confidence in the impact of genetic selection for fertility, and a feeling that fertility was not important for their production system. The results of this study suggest that animal geneticists and on-farm service providers need to work together to allow the opportunities arising from appropriate use of fertility EBV to be realized more broadly across the dairy industry.     

Selection of bulls for progeny testing using pedigree indices and characteristics of potential bull-dams' herds

A total of 209 bulls selected from herds in the northeastern US by Eastern AI Coop., Inc. from 1978 to 1981 were identified. The DHI data were obtained for the 145 herds from which these bulls were sampled. Also acquired were evaluations from both Modified Contemporary Comparison and animal model on these bulls and their ancestors and on cows and their sires in the bull-dam herds. From evaluation by animal model, animals appeared to have contributed information to each other effectively through relationship matrix, and thus the accuracy of cow evaluation has been improved. Bulls selected from herds of high genetic level were genetically superior to those from herds of low genetic level. However, there was no evidence that bulls from low intraherd milk variation herds were superior to those from high variation herds in the northeastern population, as was the case in Michigan herds. Parent indices were greater than bull PTA in herds of lower genetic level but less than bull PTA in herds of higher genetic level. The correlation between herd yield average and herd genetic level and that between herd yield average and intraherd yield SD were moderate but significantly different from zero. Other correlations between phenotypic and genetic measures of bull-dam herds were negligible. None of the herd characteristics showed promise in characterizing herds that were more successful in having their sampled bulls returned by AI organization after progency test.     

Potential bias in genetic evaluations from differences in variation within herds

Evidence is reviewed that indicates substantial differences among herds in variation for production traits in dairy cattle. Examples are given to illustrate the overevaluation and selection of higher proportions of individuals from more variable herds, which reduces response to selection if greater variability is not due in part to greater additive genetic variance. Differences in heritability according to herd mean and variance are examined. Potential bias is substantial in genetic evaluations of cows and may increase over generations where, if the model is realistic, evaluations of dams are used in evaluations of daughters. Possible methods of adjustment are discussed.     

Sire selection decisions and farm profitability relationships for Ontario dairy farmers.

The relationship between the relative emphasis of type and production in the sire selection decision and net farm income per cow are examined for a sample of Ontario dairy farmers. A significant positive correlation between farm profits and the genetic indices for type and production traits of selected bulls exists, but the direction of causality cannot be determined. Net farm income per cow was found to have a significant inverse association with the relative weighting between type and production in the average sire selected. In contrast, the emphasis on type relative to production was found to increase with an increase in milk yield and herd size. The results of this study show that there may be benefits to collecting the breeding, production, and economic information of selected herds. The information gathered over time would be useful for determining what factors influence breeding decisions and for determining the causality in those relationships.     

Genotype by environment interactions in fertility traits in New Zealand dairy cows

New Zealand's seasonal dairy farming system entails a condensed calving pattern with cows required to conceive within approximately 12 wk of the planned start of calving. This has resulted in strong selection for fertility through culling of nonpregnant cows and relatively strong emphasis on fertility in Breeding Worth, the national breeding objective that drives sire selection. Despite this, average herd-level fertility is highly variable across New Zealand dairy farms. We studied genotype by environment interaction in fertility-related traits, with the goal of improving selection decisions in different fertility environments. We used data from the New Zealand national dairy database, which contains records on 3,743,862 animals. Herds were classified into high-, mid-, or low-fertility categories or environments based on herd average fertility performance, and data were analyzed in 2 different ways. First, we estimated genetic parameters when the fertility trait was defined specifically for each fertility environment to determine the extent to which genetic correlations between high- and low-fertility environments differed from 1 and the extent of changes in genetic variance across environments. Second, we used simple regression to evaluate the impact of ancestral genetic merit for fertility on cow fertility phenotypes to compare the effect of changes in genetic merit on phenotypic performance between fertility environments. The genetic standard deviations of fertility-related traits were 1.5 to 3.6 times higher in low-fertility herds than in high-fertility herds, and the genetic correlations between the same fertility-related traits between the high- and low-fertility environments were moderate to high, albeit with high standard errors. The high standard errors of the correlations reflected the low heritabilities of the traits and potential problems of culling bias, particularly for traits expressed in later parities. Regression analysis revealed that the bottom 30% of herds (in terms of fertility) could achieve more than twice the benefit from selection for fertility than the top 30% of herds. Although our analyses do not support separate genetic evaluations of fertility in the different environments, they indicate that low-fertility herds could benefit more from targeted selection of sires with higher fertility estimated breeding values than from selection based solely on the multitrait national index. Conversely, high-fertility herds could focus their sire selection on traits other than fertility, provided they avoid very low fertility sires.     

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.     

Strategies for implementing genomic selection for feed efficiency in dairy cattle breeding schemes

Alternative genomic selection and traditional BLUP breeding schemes were compared for the genetic improvement of feed efficiency in simulated Norwegian Red dairy cattle populations. The change in genetic gain over time and achievable selection accuracy were studied for milk yield and residual feed intake, as a measure of feed efficiency. When including feed efficiency in genomic BLUP schemes, it was possible to achieve high selection accuracies for genomic selection, and all genomic BLUP schemes gave better genetic gain for feed efficiency than BLUP using a pedigree relationship matrix. However, introducing a second trait in the breeding goal caused a reduction in the genetic gain for milk yield. When using contracted test herds with genotyped and feed efficiency recorded cows as a reference population, adding an additional 4,000 new heifers per year to the reference population gave accuracies that were comparable to a male reference population that used progeny testing with 250 daughters per sire. When the test herd consisted of 500 or 1,000 cows, lower genetic gain was found than using progeny test records to update the reference population. It was concluded that to improve difficult to record traits, the use of contracted test herds that had additional recording (e.g., measurements required to calculate feed efficiency) is a viable option, possibly through international collaborations.