• Additive genetic, non-additive genetic and permanent environmental effects for female reproductive performance in seasonal calving dairy females

      Kelleher, Margaret M.; Buckley, Frank; Evans, R. D.; Berry, Donagh; Department of Agriculture, Food and the Marine, Ireland (Teagasc (Agriculture and Food Development Authority), Ireland, 2016-09-08)
      Excellent reproductive performance (i.e. 365-day calving interval) is paramount to herd profit in seasonal-calving dairy systems. Reproductive targets are currently not being achieved in Irish dairy herds. Furthermore, most research on the genetics of reproductive performance in dairy cattle has focused primarily on lactating cows and relatively few studies have attempted to quantify the genetic contribution to differences in reproductive performance in nulliparae. The objective of the present study was to estimate the contribution of both the additive and non-additive genetic components, as well as the permanent environmental component, to phenotypic variation in the reproductive traits in nulliparous, primiparous and multiparous seasonal-calving dairy females. Reproductive phenotypes were available on up to 202,525 dairy females. Variance components were estimated using (repeatability where appropriate) linear animal mixed models; fixed effects included in the mixed models were contemporary group, parity (where appropriate), breed proportion, inter-breed specific heterosis coefficients and inter-breed specific recombination loss coefficients. Heritability of the reproductive traits ranged from 0.004 (pregnancy rate to first service) to 0.17 (age at first service in nulliparae), while repeatability estimates for the reproductive traits in cows ranged from 0.01 (calving interval) to 0.11 (pregnant in the first 42 days of the breeding season). Breed-specific heterosis regression coefficients suggest that, relative to the parental mean, a first-cross Holstein–Jersey crossbred was almost 7 days younger at first calving, had a 9-day shorter calving interval, a 6 percentage unit greater pregnancy rate in the first 42 days of the breeding season and a 3 percentage unit greater survival rate to next lactation. Heifer calving rate traits were strongly genetically correlated with age at first calving (–0.97 to –0.66) and calving rate in the first 42 days of the calving season for first parity cows (0.77 to 0.56), but genetic correlations with other cow reproductive traits were weak and inconsistent. Calving interval was strongly genetically correlated with the majority of the cow traits; 56%, 40%, and 92% of the genetic variation in calving interval was explained by calving to the first service interval, number of services and pregnant in the first 42 days of the breeding season, respectively. Permanent environmental correlations between the reproductive performance traits were generally moderate to strong. The existence of contributions from non-additive genetic and permanent environmental effects to phenotypic differences among cows suggests the usefulness of such information to rank cows on future expected performance; this was evidenced by a stronger correlation with future reproductive performance for an individual cow index that combined additive genetic, non-additive genetic and permanent environmental effects compared to an index based solely on additive genetic effects (i.e. estimated breeding values).
    • Characterization of best linear unbiased estimates generated from national genetic evaluations of reproductive performance, survival, and milk yield in dairy cows

      Dunne, F. L.; Kelleher, Margaret M.; Walsh, S.W.; Berry, Donagh; MultiRepro project; Department of Agriculture, Food and the Marine (Elsevier, 2018-05-16)
      Genetic evaluations decompose an observed phenotype into its genetic and nongenetic components; the former are termed BLUP with the solutions for the systematic environmental effects in the statistical model termed best linear unbiased estimates (BLUE). Geneticists predominantly focus on the BLUP and rarely consider the BLUE. The objective of this study, however, was to define and quantify the association between 8 herd-level characteristics and BLUE for 6 traits in dairy herds, namely (1) age at first calving, (2) calving to first service interval (CFS), (3) number of services, (4) calving interval (CIV), (5) survival, and (6) milk yield. Phenotypic data along with the fixed and random effects solutions were generated from the Irish national multi-breed dairy cow fertility genetic evaluations on 3,445,557 cows; BLUE for individual contemporary groups were collapsed into mean herd-year estimates. Data from 5,707 spring-calving herds between the years 2007 and 2016 inclusive were retained; association analyses were undertaken using linear mixed multiple regression models. Pearson coefficient correlations were used to quantify the relationships among individual trait herd-year BLUE, and transition matrices were used to understand the dynamics of mean herd BLUE estimates over years. Based on the mean annual trends in raw, BLUP, and BLUE, it was estimated that BLUE were associated with at least two-thirds of the improvement in CIV and milk production over the past 10 yr. Milk recording herds calved heifers for the first time on average 15 d younger, had an almost 2 d longer CFS but 2.3 d shorter CIV than non-milk-recording herds. Larger herd sizes were associated with worse BLUE for both CFS and CIV. Expanding herds and herds that had the highest proportion of cows born on the farm itself, on average, calved heifers younger and had shorter CIV. By separating the raw performance of a selection of herds into their respective BLUE and BLUP, it was possible to identify herds with inferior management practices that were being compensated by superior genetics; similarly, herds were identified with superior BLUE, but because of their inferior genetic merit, were not reaching their full potential. This suggests that BLUE could have a pivotal role in a tailored decision support tool that would enable producers to focus on the most limiting factor hindering them from achieving their maximum performance.
    • Development of an index to rank dairy females on expected lifetime profit

      Kelleher, Margaret M.; Amer, P. R.; Shalloo, Laurence; Evans, R. D.; Byrne, T. J.; Buckley, Frank; Berry, Donagh (Elsevier for American Dairy Science Association, 2015-03)
      The objective of this study was to develop an index to rank dairy females on expected profit for the remainder of their lifetime, taking cognizance of both additive and nonadditive genetic merit, permanent environmental effects, and current states of the animal including the most recent calving date and cow parity. The cow own worth (COW) index is intended to be used for culling the expected least profitable females in a herd, as well as inform purchase and pricing decisions for trading of females. The framework of the COW index consisted of the profit accruing from (1) the current lactation, (2) future lactations, and (3) net replacement cost differential. The COW index was generated from estimated performance values (sum of additive genetic merit, nonadditive genetic merit, and permanent environmental effects) of traits, their respective net margin values, and transition probability matrices for month of calving, survival, and somatic cell count; the transition matrices were to account for predicted change in a cow’s state in the future. Transition matrices were generated from 3,156,109 lactation records from the Irish national database between the years 2010 and 2013. Phenotypic performance records for 162,981 cows in the year 2012 were used to validate the COW index. Genetic and permanent environmental effects (where applicable) were available for these cows from the 2011 national genetic evaluations and used to calculate the COW index and their national breeding index values (includes only additive genetic effects). Cows were stratified per quartile within herd, based on their COW index value and national breeding index value. The correlation between individual animal COW index value and national breeding index value was 0.65. Month of calving of the cow in her current lactation explained 18% of the variation in the COW index, with the parity of the cow explaining an additional 3 percentage units of the variance in the COW index. Females ranking higher on the COW index yielded more milk and milk solids and calved earlier in the calving season than their lower ranking contemporaries. The difference in phenotypic performance between the best and worst quartiles was larger for cows ranked on COW index than cows ranked on the national breeding index. The COW index is useful to rank females before culling or purchasing decisions on expected profit and is complementary to the national breeding index, which identifies the most suitable females for breeding replacements.
    • Genetic selection for hoof health traits and cow mobility scores can accelerate the rate of genetic gain in producer-scored lameness in dairy cows

      Ring, Siobhan C.; Twomey, Alan J.; Byrne, Nicky; Kelleher, Margaret M.; Pabiou, Thierry; Doherty, Michael L.; Berry, Donagh; Department of Agriculture, Food and the Marine (American Dairy Science Association, 2018-09-13)
      Cattle breeding programs that strive to reduce the animal-level incidence of lameness are often hindered by the availability of informative phenotypes. As a result, indicator traits of lameness (i.e., hoof health and morphological conformation scores) can be used to improve the accuracy of selection and subsequent genetic gain. Therefore, the objectives of the present study were to estimate the variance components for hoof health traits using various phenotypes collected from a representative sample of Irish dairy cows. Also of interest to the present study was the genetic relationship between both hoof health traits and conformation traits with producer-scored lameness. Producer-recorded lameness events and linear conformation scores from 307,657 and 117,859 Irish dairy cows, respectively, were used. Data on hoof health (i.e., overgrown sole, white line disease, and sole hemorrhage), mobility scores, and body condition scores were also available from a research study on up to 11,282 Irish commercial dairy cows. Linear mixed models were used to quantify variance components for each trait and to estimate genetic correlations among traits. The estimated genetic parameters for hoof health traits in the present study were greater (i.e., heritability range: 0.005 to 0.27) than previously reported in dairy cows. With the exception of analyses that considered hoof health traits in repeatability models, little difference in estimated variance components existed among the various hoof-health phenotypes. Results also suggest that producer-recorded lameness is correlated with both hoof health (i.e., genetic correlation up to 0.48) and cow mobility (i.e., genetic correlation = 0.64). Moreover, cows that genetically tend to have rear feet that appear more parallel when viewed from the rear are also genetically more predisposed to lameness (genetic correlation = 0.39); genetic correlations between lameness and other feet and leg type traits, as well as between lameness and frame type traits, were not different from zero. Results suggest that if the population breeding goal was to reduce lameness incidence, improve hoof health, or improve cow mobility, genetic selection for either of these traits should indirectly benefit the other traits. Results were used to quantify the genetic gains achievable for lameness when alternative phenotypes are available.
    • Genetic variability in the humoral immune response to bovine herpesvirus-1 infection in dairy cattle and genetic correlations with performance traits

      Ring, Siobhan C.; Graham, David A.; Sayers, Riona; Byrne, Nicky; Kelleher, Margaret M.; Doherty, Michael L.; Berry, Donagh; Department of Agriculture, Food and the Marine (Elsevier for American Dairy Science Association, 2018-04-26)
      Bovine herpesvirus-1 (BoHV-1) is a viral pathogen of global significance that is known to instigate several diseases in cattle, the most notable of which include infectious bovine rhinotracheitis and bovine respiratory disease. The genetic variability in the humoral immune response to BoHV-1 has, to our knowledge, not ever been quantified. Therefore, the objectives of the present study were to estimate the genetic parameters for the humoral immune response to BoHV-1 in Irish female dairy cattle, as well as to investigate the genetic relationship between the humoral immune response to BoHV-1 with milk production performance, fertility performance, and animal mortality. Information on antibody response to BoHV-1 was available to the present study from 2 BoHV-1 sero-prevalence research studies conducted between the years 2010 to 2015, inclusive; after edits, BoHV-1 antibody test results were available on a total of 7,501 female cattle from 58 dairy herds. National records of milk production (i.e., 305-d milk yield, fat yield, protein yield, and somatic cell score; n = 1,211,905 milk-recorded cows), fertility performance (i.e., calving performance, pregnancy diagnosis, and insemination data; n = 2,365,657 cows) together with animal mortality data (i.e., birth, farm movement, death, slaughter, and export events; n = 12,853,257 animals) were also available. Animal linear mixed models were used to quantify variance components for BoHV-1 as well as to estimate genetic correlations among traits. The estimated genetic parameters for the humoral immune response to BoHV-1 in the present study (i.e., heritability range: 0.09 to 0.16) were similar to estimates previously reported for clinical signs of bovine respiratory disease in dairy and beef cattle (i.e., heritability range: 0.05 to 0.11). Results from the present study suggest that breeding for resistance to BoHV-1 infection could reduce the incidence of respiratory disease in cattle while having little or no effect on genetic selection for milk yield or milk constituents (i.e., genetic correlations ranged from −0.13 to 0.17). Moreover, even though standard errors were large, results also suggest that breeding for resistance to BoHV-1 infection may indirectly improve fertility performance while also reducing the incidence of mortality in older animals (i.e., animals >182 d of age). Results can be used to inform breeding programs of potential genetic gains achievable for resistance to BoHV-1 infection in cattle.
    • How herd best linear unbiased estimates affect the progress achievable from gains in additive and nonadditive genetic merit

      Dunne, F. L.; McParland, Sinead; Kelleher, Margaret M.; Walsh, S.W.; Berry, Donagh; Science Foundation Ireland; Department of Agriculture, Food and the Marine; 16/RC/3835 (Elsevier, 2019-04-10)
      Sustainable dairy cow performance relies on coevolution in the development of breeding and management strategies. Tailoring breeding programs to herd performance metrics facilitates improved responses to breeding decisions. Although herd-level raw metrics on performance are useful, implicitly included within such statistics is the mean herd genetic merit. The objective of the present study was to quantify the expected response from selection decisions on additive and nonadditive merit by herd performance metrics independent of herd mean genetic merit. Performance traits considered in the present study were age at first calving, milk yield, calving to first service, number of services, calving interval, and survival. Herd-level best linear unbiased estimates (BLUE) for each performance trait were available on a maximum of 1,059 herds, stratified as best, average, and worst for each performance trait separately. The analyses performed included (1) the estimation of (co)variance for each trait in the 3 BLUE environments and (2) the regression of cow-level phenotypic performance on either the respective estimated breeding value (EBV) or the heterosis coefficient of the cow. A fundamental assumption of genetic evaluations is that 1 unit change in EBV equates to a 1 unit change in the respective phenotype; results from the present study, however, suggest that the realization of the change in phenotypic performance is largely dependent on the herd BLUE for that trait. Herds achieving more yield, on average, than expected from their mean genetic merit, had a 20% greater response to changes in EBV as well as 43% greater genetic standard deviation relative to herds within the worst BLUE for milk yield. Conversely, phenotypic performance in fertility traits (with the exception of calving to first service) tended to have a greater response to selection as well as a greater additive genetic standard deviation within the respective worst herd BLUE environments; this is suggested to be due to animals performing under more challenging environments leading to larger achievable gains. The attempts to exploit nonadditive genetic effects such as heterosis are often the basis of promoting cross-breeding, yet the results from the present study suggest that improvements in phenotypic performance is largely dependent on the environment. The largest gains due to heterotic effects tended to be within the most stressful (i.e., worst) BLUE environment for all traits, thus suggesting the heterosis effects can be beneficial in mitigating against poorer environments.