Scale dependency and functional response in moose habitat selection

Habitat selection can be influenced by the distribution of the habitat types in the landscape as well as net gain in visiting patches of resources, causing individual variation in habitat selection. Moreover, the hypothesis of functional response in habitat selection predicts that the degree of selection of a resource depends on its relative availability. We used radio-telemetry data from individual moose on an island off the coast of northern Norway to evaluate whether the selection of habitat types at the landscape scale differed from the choice of habitat types within the home range, and investigated the functional response in habitat selection by relating individual habitat selection to home range characteristics. At the landscape scale, moose selected for habitat types that provided both good forage and cover, with small differences between sex and age groups. At the home range scale, all individuals selected habitat types that were associated with cover and low human impact. Habitat selection was not modified by local moose density, but was related to home range size at both spatial scales. Larger home ranges contained larger proportions of non-preferred habitat types compared to smaller home ranges. At the home range scale, the selection for a habitat type decreased with its relative availability, indicating a functional response in habitat selection. This suggests that habitat selection is modified by home range size, which influences the availability of habitat types and shapes individual habitat selection patterns. Our results support previous suggestions that analyses of habitat or resource selection should follow a multi-scale approach. Both the relative availability of habitat types as well as individual variation in home range size should be accounted for in order to disentangle the complex mechanisms that contribute to shape patterns of resource selection in animals.     

Persistence of accuracy of genome-wide breeding values over generations when including a polygenic effect

Background

When estimating marker effects in genomic selection, estimates of marker effects may simply act as a proxy for pedigree, i.e. their effect may partially be attributed to their association with superior parents and not be linked to any causative QTL. Hence, these markers mainly explain polygenic effects rather than QTL effects. However, if a polygenic effect is included in a Bayesian model, it is expected that the estimated effect of these markers will be more persistent over generations without having to re-estimate the marker effects every generation and will result in increased accuracy and reduced bias.

Methods

Genomic selection using the Bayesian method, ''BayesB'' was evaluated for different marker densities when a polygenic effect is included (GWpEBV) and not included (GWEBV) in the model. Linkage disequilibrium and a mutation drift balance were obtained by simulating a population with a Ne of 100 over 1,000 generations.

Results

Accuracy of selection was slightly higher for the model including a polygenic effect than for the model not including a polygenic effect whatever the marker density. The accuracy decreased in later generations, and this reduction was stronger for lower marker densities. However, no significant difference in accuracy was observed between the two models. The linear regression of TBV on GWEBV and GWpEBV was used as a measure of bias. The regression coefficient was more stable over generations when a polygenic effect was included in the model, and was always between 0.98 and 1.00 for the highest marker density. The regression coefficient decreased more quickly with decreasing marker density.

Conclusions

Including a polygenic effect had no impact on the selection accuracy, but showed reduced bias, which is especially important when estimates of genome-wide markers are used to estimate breeding values over more than one generation.     

Moose body mass variation revisited: disentangling effects of environmental conditions and genetics

Large-scale geographical variation in phenotypic traits within species is often correlated to local environmental conditions and population density. Such phenotypic variation has recently been shown to also be influenced by genetic structuring of populations. In ungulates, large-scale geographical variation in phenotypic traits, such as body mass, has been related to environmental conditions and population density, but little is known about the genetic influences. Research on the genetic structure of moose suggests two distinct genetic lineages in Norway, structured along a north-south gradient. This corresponds with many environmental gradients, thus genetic structuring provides an additional factor affecting geographical phenotypic variation in Norwegian moose. We investigated if genetic structure explained geographical variation in body mass in Norwegian moose while accounting for environmental conditions, age and sex, and if it captured some of the variance in body mass that previously was attributed to environmental factors. Genetic structuring of moose was the most important variable in explaining the geographic variation in body mass within age and sex classes. Several environmental variables also had strong explanatory power, related to habitat diversity, environmental seasonality and winter harshness. The results suggest that environmental conditions, landscape characteristics, and genetic structure should be evaluated together when explaining large-scale patterns in phenotypic characters or life history traits. However, to better understand the role of genetic and environmental effects on phenotypic traits in moose, an extended individual-based study of variation in fitness-related characters is needed, preferably in an area of convergence between different genetic lineages.     

The Gene Encoding the Catalytic Subunit Cα of cAMP-Dependent Protein Kinase (Locus PRKACA) Localizes to Human Chromosome Region 19p13.1

We have determined the chromosomal localization of the gene for the catalytic subunit Cα of cAMP-dependent protein kinase (locus PRKACA) to human chromosome 19 using polymerase chain reaction (PCR) and Southern blot analysis of two different somatic cell hybrid mapping panels. In addition, PCR analysis of a chromosome 19 mapping panel revealed the presence of a human Cα-specific amplification product only in cell lines containing the region 19p13.1 to 19q12. Finally, two-color fluorescencein situhybridization to metaphase chromosomes using the human Cα cDNA and human chromosome 19 inter-Alu-PCR product as probes localized the human Cα gene to chromosome region 19p13.1.     

Phagocytosis of bacteria by human leukocytes measured by flow cytometry

A new method has been developed for the evaluation of the phagocytic activity of human leukocytes using fluorescently labeled bacteria and flow cytometry. By simultaneous measurement of cellular light scatter and fluorescence, extracellular bacteria, phagocytes, and nonphagocytes could be discriminated and quantified. All leukocytes assumed to be capable of phagocytosis were phagocytosing, and about 90% of these cells were polymorphonuclear neutrophilic granulocytes. Within 15 min 85% of the bacteria were phagocytosed and each phagocyte contained an average of 15-20 bacteria. The phagocytic capacity of the leukocytes from healthy individuals showed minor interindividual and day-to-day variations. This method facilitates a rapid and accurate in vitro evaluation of the phagocytic activity of human leukocytes.     

Does nociceptin play a role in pain disorders in man?

Nociceptin-immunoreactive cellbodies were detected in the human trigeminal ganglion, while no such fibers were identified in the temporal artery or in dermal tissue from the neck region. In four healthy subjects receiving nociceptin into the temporal muscle in an open labeled design no pain was detected. In 10 healthy subjects who received 200pmol of nociceptin into tender non-dominant trapezius muscles in a placebo-controlled, randomized, balanced, and double-blinded design local tenderness increased (P=0.025) while no pain was noted. Thus, the action of nociceptin should be searched for in the trigeminal ganglion and/or in the central nervous system (CNS).