Conservation genetics, population genetics, molecular ecology, molecular evolution, statistical genetics

Short description of the research team

Thematic fields of interest/research areas:Conservation genetics, population genetics, molecular ecology, molecular evolution, statistical genetics

Manager/head of the team: Giorgio Bertorelle (associate professor)

Team members: Silvia Fuselli (assistant professor), Andrea Benazzo (bioinformatics technician), Alex Panziera (PhD student), Luca Cornetti (PhD student), Rita Tonin (undergraduate student).


Research infrastructures

  • High performance Computing System composed of 80 processors
  • Access at large CINECA computing resources
  • Library with free access to scientific journals
  • Molecular laboratory for small typing projects (PCR, RT-PCR, etc.)
  • Collaborations with genomic centres


Contacts: Giorgio Bertorelle


Prerequisites of the trainee researcher:

Level of education: PhD

Research experience: At least intermediate level in population genetics

Required working language: Italian, English or French


Further useful information:

- The University of Ferrara, founded in 1391, consists of 12 Departments, with around

17.000 students enrolled. The Department of Life Sciences and biotechnology has an academic staff of around 60 scientists and a total number of post-doc fellows and PhD students of around 50 units. Different research groups implement projects in many different topics, such as environmental analyses and restoration, human population genetics, behavioural ecology, genetics, evolution, plant biochemistry and physiology.

- The population, conservation and evolutionary genetics group (, which includes also the team led by Guido Barbujani, has extensive experience in statistical methods applied to the analysis of genetic variation data. Data from several animal species have been analysed to understand the processes that  shaped the genetic variation patterns (e.g., domestication, climatic changes, adaptation, human activities and species management,  etc.).

- We extensively use statistical methods and computer simulations to infer population parameters, compare alternative models, analyse the performances of different methods, and predict pattern of genetic variation under different natural and artificial scenarios. Funding has been obtained from different agencies, including the European Union, the Italian Ministry for Research and Education, wildlife protection agencies, and National Parks.

- Some recent publications:

Hoban, S., Gaggiotti, O., Consortium, C., & Bertorelle, G. (2013). Sample Planning Optimization Tool for conservation and population Genetics (SPOTG): a software for choosing the appropriate number of markers and samples. Methods in Ecology and Evolution, 4(3), 299–303.

Marino, I., Benazzo, A., Agostini, C., Mezzavilla, M., Hoban, S. M., Patarnello, T., … Bertorelle, G. (2013). Evidence for past and present hybridization in three Antarctic icefish species provides new perspectives on an evolutionary radiation. Molecular Ecology, 22(20), 5148–61.

Perez, M., Livoreil, B., Mantovani, S., Boisselier, M.-C., Crestanello, B., Abdelkrim, J., … Bertorelle, G. (2013). Genetic Variation and Population Structure in the Endangered Hermann’s Tortoise: The Roles of Geography and Human-Mediated Processes. Journal of Heredity, 1–12. doi:10.1093/jhered/est071

Hoban, S. M., Gaggiotti, O. E., & Bertorelle, G. (2013). The number of markers and samples needed for detecting bottlenecks under realistic scenarios, with and without recovery: a simulation-based study. Molecular Ecology, 22(13), 3444–50.

Hoban, S. M., Mezzavilla, M., Gaggiotti, O. E., Benazzo, A., van Oosterhout, C., & Bertorelle, G. (2013). High variance in reproductive success generates a false signature of a genetic bottleneck in populations of constant size: a simulation study. BMC Bioinformatics, 14(1), 309.

Maisano Delser P, Fuselli S. Human loci involved in drug biotransformation: worldwide genetic variation, population structure, and pharmacogenetic implications. Hum Genet. 2013 Jan 26


Hoban, S., Bertorelle, G., & Gaggiotti, O. E. (2011). Computer simulations: tools for population and evolutionary genetics. Nature Reviews Genetics, 13(2), 110–22.

Bertorelle, G., Benazzo, a, & Mona, S. (2010). ABC as a flexible framework to estimate demography over space and time: some cons, many pros. Molecular ecology, 19(13), 2609–25.