Frequencies of allele groups HLA-A, HLA-B and HLA-DRB1 in a population from the northwestern region of São Paulo State, Brazil.

The aim of this study was to estimate the HLA-A, HLA-B and HLA-DRB1 allele groups frequencies in a population of 1559 volunteer bone marrow donors from the northwestern region of São Paulo State grouped according to ethnicity. An additional objective was to compare the allele frequencies of the current study with data published for other Brazilian populations. The allele groups were characterized by the PCR-rSSO method using Luminex(®) technology. Twenty HLA-A, 32 HLA-B and 13 HLA-DRB1 allele groups were identified. The most common allele groups in European descent and mixed African and European descent samples were HLA-A*02, HLA-B*35 and HLA-DRB1*13, while HLA-A*02, HLA-B*35 and HLA-DRB1*11 were more common in African descent samples. The HLA-A*23, HLA-A*36, HLA-B*58 and HLA-B*81 allele groups were more common in sample from African descent than European descent, and the HLA-DRB1*08 was more common in mixed African and European descent than in European descent. Allele group frequencies were compared with samples from other Brazilian regions. The HLA-A*30 and HLA-A*23 were more common in this study than in the populations of Rio Grande do Sul and Paraná; and the HLA-A*01, HLA-B*18, HLA-B*57 and HLA-DRB1*11 were more common in this study than in the population of Piauí. The least frequent allele groups were HLA-A*31, HLA-B*15, HLA-B*40 and HLA-DRB1*08 for the population of Piauí, HLA-A*01 and HLA-A*11 for Parana, HLA-A*02 and -A*03 for Rio Grande do Sul and HLA-DRB1*04 for Paraná, Rio Grande do Sul and Piauí. These data provide an overview on the knowledge on HLA diversity in the population of the northwestern region of São Paulo State and show that the genes of this system are useful to distinguish different ethnic groups.

Somatic cell score genetic parameter estimates of dairy cattle in Portugal using fractional polynomials.

Milk somatic cell count is an indicator trait for mastitis resistance. Genetic parameters for somatic cell score in the Portuguese Holstein-Friesian population were estimated by modeling the pattern of genetic correlation over the first 3 lactations (days in milk) with a random regression model. Data records from the first 3 lactations were from the national database of the Portuguese Holstein Association herds. Heritability estimates ranged from 0.05 at the beginning of the lactation for the 3 lactations, to 0.07 at the end of the lactation period for the first and third lactations, to 0.09 for the second lactation. This increase in the heritability values was due to an increase in the genetic variance and a decrease in the residual variances. Genetic correlations evaluated for monthly time points were high (0.65 to 0.99) for all 3 lactations, whereas phenotypic correlations were much less than the genetic correlations (0.13 to 0.62).

Prediction of daily and lactation yields of milk, fat, and protein using an autoregressive repeatability test day model.

We evaluated the accuracy of an autoregressive multiple-lactation test day (ATD) model to predict missing test day yields of milk, fat, and protein to obtain cumulative 305-d records for cows with incomplete or in-progress lactations. The data consisted of more than one million observations of daily yields on test days in the first 3 lactations of over 75,000 Portuguese Holstein cows. Differences between actual (estimates from complete lactations using the test interval method) and ATD-predicted 305-d yields were negligible and smaller than those predicted by the test interval method. The ATD procedure tended to slightly underestimate cumulative lactation yields, whereas the test interval method substantially overestimated them. Smaller differences obtained by the ATD procedure resulted in less biased estimates of lactation yield, which also implies greater accuracy. As expected, the correlations between actual and predicted lactation yields increased with the number of test days from 0.831 to 0.997. Average correlations (by parity) between actual and ATD-predicted yields ranged from 0.977 to 0.984. Correlations between actual test day yields and corresponding predicted yields exceeded 0.5 for up to 7 time-intervals from the last test day yield used to predict cumulative yield of projected lactations. These correlations indicate the good predictive ability of the ATD method. From a producer's viewpoint, these advantages underwrite management because most on-farm selection decisions are based on the producing abilities of cows. Implementation of ATD methodology does not require special computing capability and is easily transferable to the farm level.