Fungi have an essential role in terrestrial ecosystems. Some degrade dead plant biomass, these are saprophytic species that play a major role in the carbon cycle. Others live in association with plants, they are mycorrhizal and endophytic species for those that establish symbioses or pathogenic species for parasites. Because of their very active secondary metabolisms, fungi offer important biotechnological perspectives in many fields (food, medical, fuel production, etc.), which are at the origin of the major sequencing projects launched over the last decade. One of these emblematic projects is the “1000 Fungal Genomes Project” of the US Department of Energy.
The in silico exploitation of these genomic sequences has made it possible to establish very complete gene directories. Although indispensable, these genomic repertoires are not sufficient to explain the different trophic strategies of fungi. The objective of integrative bioinformatics is to associate (integrate) these gene repertoires with the multitude of functional information that emerges from the application of “omics” experimental methods: transcriptomics, proteomics, but also metabolomics, epigenomics, etc. Given their very heterogeneous nature, the processing of these functional data and their integration into a unified “biological system” type representation is an ambitious challenge. Fungal models are of obvious interest in this respect, due to i) the diversity of their lifestyles, ii) the availability of a large number of genomic sequences and iii) the knowledge of model species, which can be manipulated in the laboratory and on which the hypotheses resulting from integrative models can be tested.
Our work aims at providing methodologies for multi-dimensional analyses that allow us to make the best use of these heterogeneous data.