A pipeline to challenge cross-comparisons of multi-omics data

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Date(s) - 09/03/2016
11 h 00 min - 12 h 00 min

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Wood decay fungi play a critical role in the decomposition of plant biomass and carbon cycling on earth. To do so, these fungi produce and secrete a plethora of enzymes able to degrade the three main polymers in plant cell walls : cellulose, hemicellulose and lignin. The order Polyporales (Agaricomycetes, Basidiomycetes), contains a large number of wood decayers that are being studied for numerous biotechnological applications related to their capacity to degrade plant cell walls.
The laboratory Biodiversité et Biotechnologie Fongiques, INRA-AMU, studies the mechanisms of enzymatic degradation of plant cell walls by wood decayers. The diversity of these mechanisms is assessed through the comparative analysis of fungal strains collected in different geo-climatic areas and maintained in the CIRM-CF collection (https://www6.inra.fr/cirm/Champignons-Filamenteux). Recently, the group has initiated a genome sequencing program for 40 Polyporales strains from the collection, in collaboration with the Joint Genome Institute (USA).
A first study aims at comparing the enzymatic machineries of three Pycnoporus species that show different abilities to grow on plant substrates despite the presence in their genome of similar repertoires of genes coding for plant cell wall degrading enzymes. The functional diversity between the three species is analyzed by combined transcriptomics and secretomics in order to identify groups of enzymes expressed for deconstruction of the complex plant biomass.
Therefore, we have developed a workflow, Applied Biomass Conversion Design for the Fungal Green Technology (ABCDEFGT), to simplify the analysis and interpretation of combined transcriptomic and secretomic data. The workflow is made of the customised R scripts combined with self organising maps for grouping the genes, weighted gene correlation network analysis package for building clusters of the genes, and DESeq2 for differential gene expression analysis. The workflow; 1) produces simple graphic outputs of genome-wide transcription for comparisons; 2) enables the selection of genes based on clustering and statistics; and 3) facilitates the integration of secretomic data.
The workflow was first tested to study the early response of one of the fungal strains to various carbon sources. We then performed inter-species comparisons using RNASeq data from the three strains grown in the same conditions. The retrieved genes showed the common or specific genes strongly regulated on these substrates. The next challenge will be to enlarge the comparative analysis to more strains that cover the taxon Polyporales.

Olivier CHABROL
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