• Understanding biological complexity, from genotype to phenotype, with interdisciplinary approaches.
  • Understanding biological complexity, from genotype to phenotype, with interdisciplinary approaches.
  • Understanding biological complexity, from genotype to phenotype, with interdisciplinary approaches.

Bioinformatics and genomics of molecular networks

This research axis aims at deciphering the functional organization of the genome, defining the functional role of non coding transcripts, analyzing the molecular interactions at the DNA, RNA or protein level, developing new strategies to integrate heterogeneous information.


Genetics and genomics of multifactorial diseases

This research axis aims at identifying genes and mechanisms underlying the complex phenotypes in multifactorial diseases such as haematological malignancies, sepsis, malaria, and cardiomyopathies.


TAGC Members are actively involved in education and propose various theoretical and practical courses related to molecular biology, genetics, genomics, bioinformatics, statistics and informatics.

Attendees range from BSc, MSc, and PhD students to postdoctoral fellows and researchers.

Next Generation Sequencing Facility - TGML

The Transcriptomic and Genomic Marseille-Luminy (TGML) platform is involved in transcriptomic and genomic data production and analysis since 2001.

TAGC is part of Centuri

The Turing Centre for Living Systems (CENTURI) is an interdisciplinary project located in Marseille (France). CENTURI aims at developing an integrated interdisciplinary community, to decipher the complexity of biological systems through the understanding of how biological function emerges from the organization and dynamics of living systems.

Bioinformatics Resources and Biological Platforms

The TAGC members develop and deploy bioinformatics tools, databases and workflows ranging from next generations sequencing data analysis to network analysis.

The TAGC also own platforms for molecular biology, cell culture imaging and animals breeding.

Our goal

Understanding biological complexity, from genotype to phenotype, with interdisciplinary approaches.


17 Oct 2019

EXTERNAL SEMINAR - El Cherif Ibrahim - Institut de Neuroscience de la Timone (INT)

Title: "Transcriptional signature of the major depressive episode"

Place & date: Campus of Luminy. TAGC, Seminar room TPR2-Bloc 5. Thursday, October 17th at 11h00.


 The major depressive episode (MDE) affects nearly 15% of people worldwide. Its pathophysiology is still not completely understood but it involves systemic mechanisms and not just brain-restricted defects. So far, no biomarker of MDE has been validated and more than a third of patients do not respond to several lines of antidepressant treatment. We and others made the assumption that peripheral blood contain specific information about MDE dynamics, at the level of RNA expression, including small noncoding RNAs. Our aim is therefore to identify blood transcriptional signatures that distinguish MDE patients from controls and hopefully predict antidepressant response.

 Key Publications:

1: Apazoglou K, Farley S, Gorgievski V, Belzeaux R, Lopez JP, Grenier J, Ibrahim EC, El Khoury MA, Tse YC, Mongredien R, Barbé A, de Macedo CEA, Jaworski W,Bochereau A, Orrico A, Isingrini E, Guinaudie C, Mikasova L, Louis F, Gautron S,Groc L, Massaad C, Yildirim F, Vialou V, Dumas S, Marti F, Mechawar N, Morice E, Wong TP, Caboche J, Turecki G, Giros B, Tzavara ET. Antidepressive effects of targeting ELK-1 signal transduction. Nat Med. 2018 May;24(5):591-597. doi: 10.1038/s41591-018-0011-0. Epub 2018 May 7. PubMed PMID: 29736027.

 2: Consoloni JL, Ibrahim EC, Lefebvre MN, Zendjidjian X, Olié E, Mazzola-Pomietto P, Desmidt T, Samalin L, Llorca PM, Abbar M, Lopez-Castroman J, Haffen E, Baumstarck K, Naudin J, Azorin JM, El-Hage W, Courtet P, Belzeaux R. Serotonin transporter gene expression predicts the worsening of suicidal ideation and suicide attempts along a long-term follow-up of a Major Depressive Episode. Eur Neuropsychopharmacol. 2018 Mar;28(3):401-414. doi:10.1016/j.euroneuro.2017.12.015. Epub 2017 Dec 27. PubMed PMID: 29287766.

 3: Ibrahim EC, Guillemot V, Comte M, Tenenhaus A, Zendjidjian XY, Cancel A, Belzeaux R, Sauvanaud F, Blin O, Frouin V, Fakra E. Modeling a linkage between blood transcriptional expression and activity in brain regions to infer the phenotype of schizophrenia patients. NPJ Schizophr. 2017 Sep 7;3(1):25. doi: 10.1038/s41537-017-0027-3. PubMed PMID: 28883405; PubMed Central PMCID: PMC5589880.

 4: Hervé M, Bergon A, Le Guisquet AM, Leman S, Consoloni JL, Fernandez-Nunez N, Lefebvre MN, El-Hage W, Belzeaux R, Belzung C, Ibrahim EC. Translational Identification of Transcriptional Signatures of Major Depression and Antidepressant Response. Front Mol Neurosci. 2017 Aug 8;10:248. doi: 10.3389/fnmol.2017.00248. eCollection 2017. PubMed PMID: 28848385; PubMed Central PMCID: PMC5550836.

 5: Belzeaux R, Lin CW, Ding Y, Bergon A, Ibrahim EC, Turecki G, Tseng G, Sibille E. Predisposition to treatment response in major depressive episode: A peripheral blood gene coexpression network analysis. J Psychiatr Res. 2016 Oct;81:119-26. doi: 10.1016/j.jpsychires.2016.07.009. Epub 2016 Jul 9. PubMed PMID: 27438688.

 6: Belzeaux R, Bergon A, Jeanjean V, Loriod B, Formisano-Tréziny C, Verrier L, Loundou A, Baumstarck-Barrau K, Boyer L, Gall V, Gabert J, Nguyen C, Azorin JM, Naudin J, Ibrahim EC. Responder and nonresponder patients exhibit different peripheral transcriptional signatures during major depressive episode. Transl Psychiatry. 2012 Nov 13;2:e185. doi: 10.1038/tp.2012.112. PubMed PMID: 23149449; PubMed Central PMCID: PMC3565773.

18 Oct 2019

Internal Seminar - Julien Colle

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