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UID:1118@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20160309T110000
DTEND;TZID=Europe/Paris:20160309T120000
DTSTAMP:20160223T100000Z
URL:https://www.i2m.univ-amu.fr/evenements/a-pipeline-to-challenge-cross-c
 omparisons-of-multi-omics-data/
SUMMARY: (...): A pipeline to challenge cross-comparisons of multi-omics da
 ta
DESCRIPTION:: 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 Po
 lyporales (Agaricomycetes\, Basidiomycetes)\, contains a large number of w
 ood decayers that are being studied for numerous biotechnological applicat
 ions related to their capacity to degrade plant cell walls. The laboratory
  Biodiversité et Biotechnologie Fongiques\, INRA-AMU\, studies the mechan
 isms of enzymatic degradation of plant cell walls by wood decayers. The di
 versity of these mechanisms is assessed through the comparative analysis o
 f fungal strains collected in different geo-climatic areas and maintained 
 in the CIRM-CF collection (https://www6.inra.fr/cirm/Champignons-Filamente
 ux). 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 mach
 ineries of three Pycnoporus species that show different abilities to grow 
 on plant substrates despite the presence in their genome of similar repert
 oires of genes coding for plant cell wall degrading enzymes. The functiona
 l diversity between the three species is analyzed by combined transcriptom
 ics and secretomics in order to identify groups of enzymes expressed for d
 econstruction of the complex plant biomass.Therefore\, we have developed a
  workflow\, Applied Biomass Conversion Design for the Fungal Green Technol
 ogy (ABCDEFGT)\, to simplify the analysis and interpretation of combined t
 ranscriptomic and secretomic data. The workflow is made of the customised 
 R scripts combined with self organising maps for grouping the genes\, weig
 hted gene correlation network analysis package for building clusters of th
 e genes\, and DESeq2 for differential gene expression analysis. The workfl
 ow\; 1) produces simple graphic outputs of genome-wide transcription for c
 omparisons\; 2) enables the selection of genes based on clustering and sta
 tistics\; and 3) facilitates the integration of secretomic data.The workfl
 ow was first tested to study the early response of one of the fungal strai
 ns 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 a
 nalysis to more strains that cover the taxon Polyporales.
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