Genetic relationships among mastitis and alternative somatic cell count traits in the first 3 lactations of Swedish Holsteins

The objectives of this study were to estimate heritabilities of, and genetic correlations among, clinical mastitis (CM), subclinical mastitis (SCM), and alternative somatic cell count (SCC) traits in the first 3 lactations of Swedish Holstein cows, and to estimate genetic correlations for the alternative traits across lactations. Data from cows having their first calving between 2002 and 2009 were used. The alternative SCC traits were based on information on CM and monthly test-day (TD) records of SCC traits of 178,613, 116,079, and 64,474 lactations in first, second, or third parity, respectively. Sires had an average of 230, 165, or 124 daughters in the data (parities 1, 2, or 3, respectively). Subclinical mastitis was defined as the number of periods with an SCC >150,000 cell/mL and without a treatment for CM. Average TD SCC between 5 and 150 d was used as a reference trait. The alternative SCC traits analyzed were 1) presence of at least 1 TD SCC between 41,000 and 80,000 cell/mL (TD41-80), 2) at least 1 TD SCC >500,000 cells/mL, 3) standard deviation of log SCC over the lactation, 4) number of infection peaks, and 5) average days diseased per peak. The same variables in different parities were treated as distinct traits. The statistical model considered the effects of herd-year, year, month, age at calving, animal, and residual. Heritability estimates were 0.07 to 0.08 for CM, 0.12 to 0.17 for SCM, and 0.14 for SCC150. For the alternative traits, heritability estimates were 0.12 to 0.17 for standard deviation of log SCC, TD SCC >500,000 cells/mL, and average days diseased per peak, and 0.06 to 0.10 for TD41-80 and number of infection peaks. Genetic correlations between CM with SCM were 0.62 to 0.74, and correlations for these traits with the alternative SCC traits were positive and very high (0.67 to 0.82 for CM, and 0.94 to 0.99 for SCM). Trait TD41-80 was the only alternative trait that showed negative, favorable, genetic correlations with CM (-0.22 to -0.50) and SCM (-0.48 to -0.85) because it is associated with healthy cows. Genetic correlations among the alternative traits in all 3 parities were high (0.93 to 0.99, 0.92 to 0.98, and 0.78 to 0.99, respectively). The only exception was TD41-80, which showed moderate to strong negative correlations with the rest of the traits. Genetic correlations of the same trait across parities were in general positive and very high (0.83 to 0.99). In conclusion, these alternative SCC traits could be used in practical breeding programs aiming to improve udder health in dairy cattle

Integration of epidemiology into the genetic analysis of mastitis in Swedisch Holstein

Heritability of mastitis (and diseases in general) tends to be low. One possible cause is that no clear distinction can be made between resistant and nonresistant animals, because healthy animals include animals that have not been exposed to pathogens and resistant animals. To account for this, we quantified the prevalence of clinical mastitis (CM) and subclinical mastitis (SCM) in 2,069 Swedish Holstein herds as a measure of exposure. Herd prevalence averaged 26.5% for SCM and 6.4% for CM; 61% of the first lactations of 177,309 cows were classified as having at least one case of SCM and 10% as having CM. In a reaction norm approach, heritability of (S)CM was quantified as a function of herd prevalence of (S)CM. The best-fitting model was a second-order polynomial of first-lactation cow SCM as a function of herd prevalence SCM, and a first-order (linear) polynomial of first-lactation cow CM as a function of CM herd prevalence. Heritability for SCM ranged from 0.069 to 0.105 and for CM from 0.016 to 0.032. For both, we found no clear effect of herd prevalence on their heritability. Genetic correlations within traits across herd prevalences were all greater than 0.92. Whether relationships among prevalence, exposure, disease, and genetics were as expected is a matter of discussion, but reaction norm analyses may be a valuable tool for epidemiological genetics

Statistical tools to select for robustness and mil quality

This work was part of the EU RobustMilk project. In this work package, we have focused on two aspects of robustness, micro- and macro-environmental sensitivity and applied these to somatic cell count (SCC), one aspect of milk quality. We showed that it is possible to combine both categorical and continuous descriptions of the environment in one analysis of genotype by environment interaction. We also developed a method to estimate genetic variation in residual variance and applied it to both simulated and a large field data set of dairy cattle. We showed that it is possible to estimate genetic variation in both micro- and macro-environmental sensitivity in the same data, but that there is a need for good data structure. In a dairy cattle example, this would mean at least 100 bulls with at least 100 daughters each. We also developed methods for improved genetic evaluation of SCC. We estimated genetic variance for some alternative SCC traits, both in an experimental herd data and in field data. Most of them were highly correlated with subclinical mastitis (>0.9) and clinical mastitis (0.7 to 0.8), and were also highly correlated with each other. We studied whether the fact that animals in different herds are differentially exposed to mastitis pathogens could be a reason for the low heritabilities for mastitis, but did not find strong evidence for that. We also created a new model to estimate breeding values not only for the probability of getting mastitis but also for recovering from it. In a progeny-testing situation, this approach resulted in accuracies of 0.75 and 0.4 for these two traits, respectively, which means that it is possible to also select for cows that recover more quickly if they get mastitis

Objetivos de seleção para sistemas de produção de gado de corte em pasto: ponderadores econômicos Economic values for breeding goal traits for Brazilian beef cattle production

Foram desenvolvidos objetivos de seleção para gado de corte criado nas condições de produção típicas do Brasil Central. As características consideradas foram: número de bezerros desmamados por vaca/ano (NBD), peso da carcaça (PC), peso à desmama (PD) e consumo de alimento. Foram adotados dois sistemas de produção, um que considerava somente a cria e outro, o ciclo completo (cria, recria e engorda). No primeiro, as receitas foram a venda de bezerros à desmama, novilhas excedentes e vacas de descarte. No segundo, a receita foi a venda das novilhas excedentes, vacas de descarte e novilhos para o abate. Em ambas as situações, o lucro (USD/vaca/ano) foi estimado pela diferença entre receita e despesa. Os valores econômicos estimados foram expressos em dólar por unidade de mudança na característica, calculados na base vaca/ano. O valor econômico foi calculado avaliando-se a alteração ocorrida no lucro quando a característica era incrementada de uma unidade, permanecendo as demais inalteradas. A característica que apresentou maior valor bruto do ponderador econômico foi o NBD, seguida pelo consumo, PC e PD. Quando se considerou o valor econômico, em unidades de desvio-padrão genético-aditivo, a ordem de importância foi consumo, PC, NBD e PD.<br>Breeding objectives were developed for beef cattle production under typical economic and environmental conditions of central Brazil. The traits considered were: calves weaned per cow/year (NCW), weaning weight (WW), carcass weight (CW) and food intake. In the study, two systems were examined, a cow-calf system (surplus calves sold after weaning) and a cow-calf enterprise (in which surplus calves are raised for slaughter). In the first, income is from the sale of male calves and surplus heifers after weaning and of culled cows. In the second, the income is from the sale of steers, surplus heifers and culled cows. For both situations, the profit (US$/cow/year) was estimated by the difference between revenue and costs. The economical values (EV) were calculated as the change in profit resulting from a unit change in each trait, as other traits remained unchanged. The trait with greatest economic value was NCW, followed by food intake, CW and WW. The order of importance when values were in additive genetic standard deviation units were feed intake, CW, NCW and WW