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PRODUCT
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Our laboratory study cell fate decisions from a systems biology perspective, i.e. by aiming to understand their transitions from the reorganization of complex regulatory wires defining their biological state.

Marco A. Mendoza and his team; Genoscope 2023

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From big-data functional genomics to the reconstruction of  regulatory programs at the basis of biological systems

With the democratization of the sequencing technologies, the major challenge of the present genomics era does not reside anymore in data acquisition, but rather in having computational solutions for interrogating billions of data points from several datasets in a comparative manner such that their embedded information might provide means to describe biological systems. In fact, over the world large collaborative projects like the ENCODE, modENCODE, the International Human Epigenome Consortium (IHEC) and others provide the scientific community with impressive amounts of data describing the genomic binding of a large collection of transcription factors and/or histone modifications, thereby establishing largest catalogs of genomic interactions in the human genome and other model organisms. Furthermore, several laboratories perform currently functional genomics studies in defined model systems and cover a large number of molecular targets, such that the number of genomics data linked to functions increases exponentially in the public repositories. Nevertheless, while such public repositories represent an important source of information; the absence of datasets’ quality information and the lack of computational resources for exploring their content in a comparative manner make them unexplored/underexploited reservoirs of knowledge.

Over years, our team addressed these questions by the development of a universal quality control strategy for ChIP-seq and related datasets (Mendoza-Parra et al; NAR 2013), which has been applied to certify > 80 000 public datasets and more recently by the release of a user-friendly online resource for ultrafast retrieval, visualization, and comparative analysis of tens of thousands of genomics datasets to gain new functional insight from global or focused multidimensional data integration.

 

Our ambition for the coming years is focused on compiling the important number of datasets retrieved in the public domain into reconstructed gene regulatory networks per cell/tissue systems studied by the scientific community. At term we aim to provide a comprehensive view of the gene regulatory wires defining each of the cell/tissue types in an organism, thus representing a landmark catalog for the future therapeutic developments in regenerative medicine.

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1,986 human public ChIP-seq datasets targeting the histone modification H3K27ac were compared by computing pairwise similarity indices (Tanimoto) and classified with the t-SNE strategy. This analysis was further correlated with their related cell/tissue origin. A detailed view of two of the t-SNE–identified clusters (219 datasets: LNCaP and MCF7/cancer–related cell lines) displaying their similarity indexes in a heat map square matrix is illustrated in (D).

Blum et al; Life Science Alliance, Dec 2019

Decorticating the Spatio-temporal gene regulatory programs implicated on nervous tissue formation

Spatio-temporally organized cell fate transitions govern the genesis of multicellular organisms and alterations from this body plan can generate pathologies. One such process is neurogenesis, a highly complex process implicating a variety of regulatory signals, which, in a multicellular organization context (~100 billion neurons interconnected by several trillion of interconnections), gives rise to one of the most complex organs retrieved in higher organisms: the brain.

the recent advances in induced pluripotent stem cell (iPSC) technology and in 3-dimensional cerebral organoid culturing procedures - able to reconstitute brain structures in vitro - provide new avenues for studying nervous tissue formation. Specifically, it provides means to follow cell specialization in a spatio-temporal context, thus representing an optimal model for studying organogenesis from a systems biology perspective.

Our ambition is to combine 3-dimensional cerebral organoid culturing strategies with modern functional genomic readouts allowing to reconstitute the gene regulatory programs participating in tissue morpho-space architecture.

A systems biology view of cerebral organoids progression. (A) Master regulators predicted by TETRAMER from transcriptomes (Luo C. et al; Cell Reports 2016) assessed during 60 days of H9 hES-derived cerebral organoid cultures (EB, embryoid bodies). In (B), the relevance of major TFs predicted in (A) is highlighted through their association to cells/tissues (blue boxes). The identification of a few TFs associated with non-neuroectodermal tissues reveals the previously noted presence of undesired cell fate processes in cerebral organoid cultures.

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Cholley et al; Nat Sys Bio & App, Aug 2018

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ABOUT

n° Citations: 2247; h-index: 18; i10-index: 26 (Nov. 2023)

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non-peer-reviewed articles

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  • Marco Antonio Mendoza, 2001, Les Phytases : Structure, Caractérisation et Applications, www.123bio.net/revues/

Publications

FEATURED

Software

TETRAMER

qcComparator

POLYPHEMUS

NGS-QC Generator

MeDiChISeq

MULTILAYER

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Epimetheus

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qcChromStater

LOGIQA

Networks

RXRa-RARg regulome
Mendoza-Parra et al; Mol. Sys. Biol. 2011
BJ fibroblast stepwise tumorigenesis transformation
Malysheva et al; Genome Medicine. 2016
Master regulatory networks 
MEFs to iPS cells reprogramming
TETRAMER
tumorigenic transformation driven by conditioned medium from senescent cells
TETRAMER
retinoids action on neuronal/endodermal cell fate acquisiton
Mendoza-Parra et al; Genome Research. 2016
B-lymphoma to primary macrophage transdifferentiation 
TETRAMER
CONTACT

Open positions

we are always interested in working with scientists sensitive to the topics we drive in the lab. Interested master or PhD candidate applicants as well as postdoctoral scientists could directly contact us:
Current open positions:
- PhD student position.
-EU-funded engineer position in Bioinformatics (Single-cell transcriptomic).
DEMO
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