Giorgio Bertorelle

Research Interests
My research interests are in the broad field of population genetics. Empirically, I'm maily interested in the structure of human populations and in the analysis of animal species for conservation or management purposes. Theoretically, I try to understand how the large amount of information provided by modern molecular techniques can be used to infer population processes
The genetic structure of human populations
The analysis of genetic diversity within and between populations can be very useful to understand several aspects of our evolutionary history. In this context, my principal interests concern Italian and European populations, and in particular:
  • The relationship between genetic and linguistic differentiation
  • The patterns of geographic distribution of the genetic variability
  • The origin of strong genetic divergence observed in some populations
  • The demographic expansions
  • The admixture processes
  • The divergence processes
Conservation and managment of animal species
 The analysis of genetic markers provides important information when the conservation and/or the management of an animal species are concerned. At the moment, I'm involved in several projects of these type regarding the following species:
  • Roe deer (Capreolus capreolus)
  • Fallow deer (Dama dama and Dama mesopotamica)
  • Red deer (Cervus elephus)
  • Chamois (Rupicapra rupicapra)
  • Brown hare (Lepus europeaus)
  • Mountain hare (Lepus timidus)
  • Wild boar (Sus scofa)
  • Hermann's Tortoise (Testudo hermanni)
Molecular markers and population inferences
Compared to classical protein markers, DNA data contain much information on the evolutionary relationships between alleles. All this additional information, however, is often negletted in population genetics, since most of the methods were developed to analyse allele frequencies. In this context, I am interested in new methods to infer population processes which explicitly use the molecular information provided by DNA markers. These methods includes:
  • The analysis of spatial autocorrelation between DNA sequences
  • The analysis of the distribution of pairwise differences and its validation
  • The analysis of admixture proportions based on coalescent times
  • The analysis of population differentiation when the data consist of band sharing coefficient between fingerprinting patterns
  • The estimate of allele ages