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CHERCHEUSE
INSERM
​CRCN

Permanent researcher

CONTACTS

00 33 (0)5 62 74 45 30
EQUIPE 4 : METABOLISME DU FER: DE LA REGULATION A LA THERAPIE 
TEAM 4 :  IRON METABOLISM:FROM REGULATION TO THERAPY ​

Carreer Path

  • Initially trained in computer science (ENSEIRB engineering school, Bordeaux), I did my phD (2002-2006) about the automatic reliable identification of gene structures in eukaryotic genomes (Exogean) under the supervision of Hugues Roest Crollius (Institut de Biology de l’Ecole Normale Supérieure, Paris) and Franck Delaplace (Université d’Evry).
  • I then moved (2006-2015) to the Centre for Genomic Regulation (CRG) in Barcelona, Spain, to work on the international ENCyclopedia Of DNA Element (ENCODE) project as a postdoctoral researcher. Within the ENCODE transcriptomic sub-project led by Thomas Gingeras and Roderic Guigó, I coordinated the analyses of genome-wide transcriptomic data (RNA-seq, CAGE, RNA-PET) produced for the first time in a very exhaustive way (many cell lines, RNA fractions and cell compartments). I also coordinated the mouseENCODE transcriptomic analysis efforts and developped the ChimPipe program to identify all types of chimeric RNAs from RNA-seq data.
  • In 2015,  I moved back to France (Toulouse, Agreenskills+ fellowship) to coordinate the bioinformatics analyses of the INRA French Animal Genome ENCODE project (FR-AgENCODE, RNA-seq, ATAC-seq and HiC data from 4 species) together with Sylvain Foissac.
  • I am now interested in the robust automatic identification of enhancer-gene relationships in the genomes and how it can help understanding complex human genetic diseases.​ In 2019 I was recruited as an INSERM permanent researcher (CRCN) to lead this project at the Digestive Health Research Institute (IRSD), Toulouse.

expertise

INTEGRATIVE ANALYSIS OF HIGH-THROUGHPUT FUNCTIONAL GENOMIC DATA
ALGORITHM AND PROGRAMMING

RESEARCH/PROJECT
The robust automatic identification of regulatory relationships in the genomes, and how it can help understanding complex genetic diseases.
​My project is organized in two parts:
  • the robust automatic identification of regulatory relationships genome-wide (focusing first on enhancer-gene relationships). After an evaluation of state-of-the-art methods on several gold-standard datasets, I will define the best approach that also relies in a minimal set of assays
  • the focus on complex genetic diseases studied in the lab such as hemochromatosis and Parkinson’s disease: after identifying important regulatory relationships in cell types related to these diseases, I will integrate them with genetic data to identify new variants, regulators, genes and pathways involved in the diseases.

SCIENTIFIC PRODUCTION 

 A selection of my publications:
  • Eché C, Iampietro C, Birbes C, Dréau A, Kuchly C, Di Franco A, Klopp C, Faraut T, Djebali S, Castinel A, Zytnicki M. A Bos taurus sequencing methods benchmark for assembly, haplotyping, and variant calling. Scientific Data. 2023 Jun 8;10(1):369.
  • ​Hoellinger H, Mestre C, Aschard H, Le Goff W, Foissac S, Faraut T, Djebali S, 2023, Enhancer/gene relationships: need for more reliable genome-wide reference sets, Frontiers in Bioinformatics, 24(3):1092853
  • Jehl F, Muret K, Bernard M, Boutin M, Lagoutte L, Désert C, Dehais P, Esquerré D, Acloque H, Giuffra E, Djebali S, Foissac S, Derrien T, Pitel F, Zerjal T, Klopp C, Lagarrigue S, 2020, An integrative atlas of chicken long non-coding genes and their  google annotations across 25 tissues, Scientific Reports, 20(1):1-17
  • Breschi A, Muñoz-Aguirre M, Wucher V, Davis CA, Garrido-Martı́n D, Djebali S, Gillis J, Pervouchine DD, Vlasova A, Dobin A, Zaleski C, Drenkow J, Danyko C, Scavelli A, Reverter F, Snyder MP, Gingeras TR and Guigó R, 2020, A limited set of transcriptional programs define major cell types, Genome Research, 30(7):1047-1059
  • Foissac S*, Djebali S*, Munyard K, Vialaneix N, Rau A, Muret K, Esquerré D, Zytnicki M, Derrien T, Bardou P, Blanc F et al. Multi-species annotation of transcriptome and chromatin structure in domesticated animals. BMC biology. 2019 Dec;17(1):1-25.
  • Rodríguez-Martín B, Palumbo E, Marco-Sola S, Griebel T, Ribeca P, Alonso G, Rastrojo A, Aguado B, Guigó R, Djebali S. ChimPipe: accurate detection of fusion genes and transcription-induced chimeras from RNA-seq data. BMC genomics. 2017 Dec;18(1):7.
  • Breschi A, Djebali S, Gillis J, Pervouchine DD, Dobin A, Davis CA, Gingeras TR, Guigó R. Gene-specific patterns of expression variation across organs and species. Genome biology. 2016 Dec 1;17(1):151.
  • Pervouchine DD*, Djebali S*, Breschi A*, Davis CA, Barja PP, Dobin A, Tanzer A, Lagarde J, Zaleski C, See LH, Fastuca M. et al, Enhanced transcriptome maps from multiple mouse tissues reveal evolutionary constraint in gene expression. Nature communications. 2015 Jan 13;6:5903.
  • Djebali S*, Davis CA*, Merkel A, Dobin A, Lassmann T, Mortazavi A, Tanzer A, Lagarde J, Lin W, Schlesinger F, Xue C et al. Landscape of transcription in human cells. Nature. 2012 Sep;489(7414):101-8.
  • Djebali S*, Lagarde J*, Kapranov P*, Lacroix V*, Borel C, Mudge JM, Howald C, Foissac S, Ucla C, Chrast J, Ribeca P et al. Evidence for transcript networks composed of chimeric RNAs in human cells. PLoS One. 2012;7(1).
  • Djebali S*, Kapranov P*, Foissac S*, Lagarde J*, Reymond A*, Ucla C, Wyss C, Drenkow J, Dumais E, Murray RR, Lin C et al. Efficient targeted transcript discovery via array-based normalization of RACE libraries. Nature methods. 2008 Jul;5(7):629.
  • Djebali S, Delaplace F, Crollius HR. Exogean: a framework for annotating protein-coding genes in eukaryotic genomic DNA. Genome Biology. 2006 Aug 1;7(S1):S7.
  • Jervis BW, Smaglo L, Djebali S. The rapid classification of brain conditions using neural networks. Conference paper -DERA/IEE Workshop Intelligent Sensor Processing, 2001