Construction and characterization of a large insert porcine YAC library

The recent construction of genetic linkage maps of the porcine genome (Rohrer et al. 1994, 1996; Ellegren et al. 1994; Archibald et al. 1995) allows the assignment of loci affecting heritable traits of economic importance (ETLs; Lander and Botstein 1989) to specific chromosomal segments. Markers can thus be identified that may be useful in marker-assisted selection (MAS) to increase the frequency of favorable allele(s) in resource populations (reviewed in Soller 1994). In addition, mapping of these loci creates the opportunity to identify gene(s) influencing a trait, through positional cloning or positional cnadidate gene approaches (Grootscholten et al. 1991). A positional cloning strategy requires the construction of contigs that physically span large sections of chromosomes. In the human and mouse systems, contig construction has depended on the availability of multiple YAC libraries that provide depth of coverage to minimize the impact of chimeric and deleted clones inherent in these libraries. A single porcine genomic YAC library has been reported (Leeb et al. 1995), but contains only one genome coverage, which limits the ability to make large contigs. We report the construction of a porcine YAC library, with approximately 5.5-fold coverage of the genome and a low rate of chimerism, that provides an additional resource for contig construction and positional cloning

Supplementation with omega-3 polyunsaturated fatty acids and effects on reproductive performance of sows

In studies of both humans and farm animals, the inclusion of omega-3 polyunsaturated fatty acids in the diet have been shown to have beneficial effects on many physiological processes including reproduction. The aim of this study was to examine the effects of supplementary omega-3 on sow reproductive performance and piglet survival. Salmon oil (1 %) was fed to sows throughout gestation and lactation as a source of omega-3 and sows were followed through their subsequent parity when returned to a commercial gestation and lactation diet. It was hypothesised that sows fed omega-3 would show improved piglet survivability (+2 %) and an increased litter size (one extra piglet born alive per litter) in the second experimental period compared with a soya oil supplemented control. Supplementation of 1 % salmon oil across one parity increased the body weight of sows at weaning (p = 0.01) and these sows maintained on average 4 kg ± 2.3 more over the lactation period than soya oil supplemented controls. Sows that were followed across a second un-supplemented reproductive period were heavier at farrowing (p < 0.01) and weaning (p < 0.05), had a higher condition score at farrowing and tended to have a higher condition score (p = 0.063) and back fat at weaning (p = 0.073) when they had received salmon oil in the previous reproductive cycle. However, salmon oil increased pre-weaning mortality by 2.4 % in the first reproductive period (p < 0.05) and significantly reduced litter weight at birth (ca 600 g; p < 0.05). Pre-weaning mortality was reduced by 3.4 % in the second experimental period when supplementation of both salmon oil and the soya oil control had ceased (p < 0.001). This effect tended to be greater for sows previously supplemented with omega-3. There was no effect on litter size, or the number of piglets born alive. Supplementation of 1 % salmon oil improved sow body weight at weaning and increased maternal stores across a second, un-supplemented reproductive cycle perhaps through effects on maternal nutrient partitioning. The increased mortality in the first experimental period and reduced mortality (across both treatment groups) when returned to a commercial diet suggests a negative effect of omega 3 fatty acid supplementation on piglet survival when fed throughout gestation and lactation

Logistic regression to estimate the welfare of broiler breeders in relation to environmental and behavioral variables Regressão logística para estimativa do bem-estar de matrizes pesadas em função de variáveis comportamentais e ambientais

The increasing demand of consumer markets for the welfare of birds in poultry house has motivated many scientific researches to monitor and classify the welfare according to the production environment. Given the complexity between the birds and the environment of the aviary, the correct interpretation of the conduct becomes an important way to estimate the welfare of these birds. This study obtained multiple logistic regression models with capacity of estimating the welfare of broiler breeders in relation to the environment of the aviaries and behaviors expressed by the birds. In the experiment, were observed several behaviors expressed by breeders housed in a climatic chamber under controlled temperatures and three different ammonia concentrations from the air monitored daily. From the analysis of the data it was obtained two logistic regression models, of which the first model uses a value of ammonia concentration measured by unit and the second model uses a binary value to classify the ammonia concentration that is assigned by a person through his olfactory perception. The analysis showed that both models classified the broiler breeder's welfare successfully.<br>As crescentes demandas e exigências dos mercados consumidores pelo bem-estar das aves nos aviários têm motivado diversas pesquisas científicas a monitorar e a classificar o bem-estar em função do ambiente de criação. Diante da complexidade com que as aves interagem com o ambiente do aviário, a correta interpretação dos comportamentos torna-se uma importante maneira para estimar o bem-estar dessas aves. Este trabalho criou modelos de regressão logística múltipla capazes de estimar o bem-estar de matrizes pesadas em função do ambiente do aviário e dos comportamentos expressos pelas aves. No experimento, foram observados diversos comportamentos expressos por matrizes pesadas alojadas em câmara climática sob três temperaturas controladas e diferentes concentrações de amônia do ar monitoradas diariamente. A partir da análise dos dados, foram obtidos dois modelos de regressão logística, dos quais, o primeiro modelo utiliza um valor de concentração de amônia medida por equipamento, e o segundo modelo utiliza um valor binário para classificar a concentração de amônia, que é atribuída por uma pessoa através da sua percepção olfativa. As análises dos modelos mostraram que ambos classificaram satisfatoriamente o bem-estar