Section: New Results

Applications in biotechnology and health

Participants : David James Sherman, Pascal Durrens [correspondant] , Florian Lajus, Xavier Calcas.

Using Magnome 's Magus system and YAGA software, we have successfully realized a full annotation and analysis of several groups of related genomes:

• Seven new genomes, provided to the Génolevures Consortium by the CEA–Génoscope (Évry), including two distant genomes from the Saccharomycetales were annotated using previously published Génolevures genomes.

• Twelve wine starter yeasts linked to fermentation efficiency.

• Five pathogenic (to human) and non pathogenic Nakaseomycetes.

• Two oleaginous strains with applications in biofuels.

Winemaking yeasts. In collaboration with partners in the ISVV, Bordeaux, we have assembled and analyzed 12 wine starter yeasts, with the goal of understanding genetic determinants of performance in wine fermentation. Analysis included identification of strain-specific gains and losses of genes linked both to niche specificity and to performance in industrial applications (article in prep.). A further combined analysis with 50 natural and industrial strains showed a pattern of introgression concentrated in industrial strains (article in prep.).

Oleaginous yeasts. In collaboration with Prof Jean-Marc Nicaud's lab at the INRA Grignon, we developed the first functional genome-scale metabolic model of Yarrowia lipolytica, an oleaginous yeast studied experimentally for its role as a food contaminant and its use in bioremediation and cell factory applications.

Using Magnome 's Pantograph method (see section 5.2 ) we produced an accurate functional model for Y. lipolytica, MODEL1111190000 in BioModels (http://biomodels.net/ ), that has been qualitatively validated against gene knockouts. This model has been enriched by Anna Zhukova with ontology terms from ChEBI and GO.

Pathogenic yeasts. A further group of five species, comprised of pathogenic and nonpathogenic species, was analyzed with the goal of identifying virulence determinants [39] . By choosing species that are highly related but which differ in the particular traits that are targeted, in this case pathogenicity, we are able to focus of the few hundred genes related to the trait [16] . The approximately 40,000 new genes from these studies were classified into existing Génolevures families as well as branch-specific families.