Strategic Research

Gene Function and Evolution lab (GFE)

Our main focus is to understand the role played by RNA molecules in protein networks. Characterizing protein-RNA associations is key to unravel the complexity and functionality of mammalian genomes and could open up therapeutic avenues for the treatment of a broad range of neurodegenerative disorders.  Our research focuses on associations of coding/non-coding RNAs with proteins involved in i) transcriptional and translational regulation (e.g., X-chromosome inactivation) and ii) neurodegenerative diseases (examples include Parkinson's a-synuclein, Alzheimer's disease amyloid protein APP, TDP-43 and FUS).  We aim to discover the involvement of RNA molecules in regulatory networks controlling protein production. More specifically, we are interested in discovering and understanding mechanisms whose alteration lead to aberrant accumulation of proteins.  We have recently observed that interaction between proteins and their cognate mRNAs (autogenous associations) induce feedback loops that are crucial in protein homeostasis.

Main projects

  • 1.

    Functional and dysfunctional ribonucleoprotein networks

    An unexpectedly large number of proteins are able to interact with RNA, but the partners of many RNA-binding proteins are largely uncharacterized. We intergrate in silico predictions with experimental data unravelling two major types of protein–RNA interactions, with positively correlated patterns related to cell cycle control and negatively correlated patterns related to survival, growth and differentiation. Our analysis sheds light on the role of RNA-binding proteins in regulating proliferation and differentiation processes, and we provide a data exploration tool to study cancer and neurodegenerative diseases.

  • 2.

    Protein-RNA granules and Neurodegeneration

    Mutations in a growing list of RNA binding proteins including TDP43, FUS, TAF15, EWS, ataxin2, hnRNPA1 and B2 are associated with inherited forms of amyotrophic lateral sclerosis (ALS/FTD) and Frontotemporal dementia. These diseases share features suggesting that they may have a common underlying pathogenic mechanism. First, these proteins all possess low complexity/intrinsically disordered “prion”-like domains. Second, a common neuropathological hallmark of these forms of ALS/FTD is the accumulation of the mutant RBP in the nucleus and/or cytoplasm of neurons in the brain and spinal cord of ALS/FTD patients. In our work, we proposed a model in which low-complexity (LC) domains of FUS drive its physiologically reversible assembly into membrane-free, liquid droplet and hydrogel-like structures.

  • 3.

    Transcription Factors Networks

    The ENCODE project is a massive data-collection effort set out to understand the function of the human genome. The collection comprises many types of genomic data, including the localization of transcription factors onto DNA. Transcription factors are proteins that bind to specific patterns of DNA (recognition motifs) to control how genes are turned on or off. The way this function is achieved is still unknown. In order to gain insights into this mechanism, we worked on ENCODE data to study how transcription factors interact together with specific DNA regions. We found that the association of multiple transcription factors (network) is a fundamental feature to explain their localization onto DNA. We developed a method to assess where a transcription factor will localize in the genome. The PAnDA method can be used to predict the ability of human transcription factors to localize onto DNA.



Bioinformatics expertise:

Group Leader:

Gian G. Tartaglia

Bioinformatics services offered

  • Prediction of protein-RNA interactions (catRAPID)

  • Calculation of protein solubility (ccSOL)

  • Analysis of protein data (cleverMachine)

  • Analysis of DNA/RNA data (SeAMoTe)