Patterns of genetic variation at micro-geographic scales: results from a multi-species multi-locus project in the Italian Alps and management implication

Using sequence variation at the mitochondrial control region (D-loop) and allele frequencies at ten microsatellite nuclear markers, we analyzed patterns of genetic variation in five mammals species in the Autonomous Province of Trento (Italy): chamois (Rupicapra rupicapra), roe deer (Capreolus capreolus), red deer (Cervus elaphus), European brown hare (Lepus europaeus) and mountain hare (Lepus timidus). All these game species are presently widespread throughout the Province; however, they suffered a strong size reduction in the last century as a result of a remarkable transformation in land use and over-exploitation. Subsequent, uncontrolled restocking have probably also affected the native populations and their genetic composition. For all five species, at least four different samples were considered, each consisting of about 25 specimens, collected from populations separated by geographic distances of between 20 and 100 kilometers. Genetic divergence can be observed even at this micro-geographic scale. The relationship between the patterns of genetic variation, the ecological characteristics of the different species, and the estimated levels of anthropogenic impact in the sampling areas, is discussed. A13 TBA Mike Bruford University of Cardiff, UK A14 The use of cDNA microarrays for studying local adaptation in natural animal populations Carlos Largiadèr(1), T Giger(1), PJR Day(2) Laurent Excoffier(1) 1 University of Bern, Switzerland 2 Centre for Integrated Genomic Medical Research, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK The cDNA microarray technology has been emerging as a powerful tool to monitor gene expression of thousands of genes simultaneously. The technology has been indeed developed as a search tool for candidate genes rather than to investigate the evolutionary significance of gene expression diversity itself. In particular, individual gene expression diversity has been so far considered as a nuisance parameter that has often been ignored, for instance by pooling RNA-samples of several individuals. However, the fundamental unit of the evolutionary process is the individual. Any selection process acting on levels of gene expression is thus fuelled by inter-individual differences, which are therefore of central importance for studying local adaptation. We shall discuss how to take into account gene expression variability at the level of individuals in experimental design and in statistical analyses in general, showing that already existing statistical methodologies can be adapted to analyze cDNA microarray data. These methodologies will be applied to the particular case of investigating possible genetic determinants of local adaptation in freshwater fish populations of brown trout (Salmo trutta).