Objective
Recent genomics analyses have facilitated the discovery of a novel major class of stable transcripts, now called long non-coding RNAs (lncRNAs). A growing number of analyses have implicated lncRNAs in the regulation of gene expression, dosage compensation and imprinting, and there is increasing evidence suggesting the involvement of lncRNAs in various diseases such as cancer. Despite recent advances, however, the role of the large majority of lncRNAs remains unknown and there is current debate on what fraction of lncRNAs may just represent transcriptional noise. Moreover, despite a growing number of lncRNAs catalogues for diverse model species, we lack a proper understanding of how these molecules evolve across genomes. Evolutionary analyses of protein-coding genes have proved tremendously useful in elucidating functional relationships and in understanding how the processes in which they are involved are shaped during evolution. Similar insights may be expected from a proper evolutionary characterization of lncRNAs, although the lack of proper tools and basic knowledge of underlying evolutionary mechanisms are a sizable challenge. Here, I propose to combine state-of-the-art computational and sequencing techniques in order to elucidate what evolutionary mechanisms are shaping this enigmatic component of eukaryotic genomes.The first goal is to enable large-scale phylogenomic analyses of lncRNAs by developing, for these molecules, methodologies that are now standard in the evolutionary analysis of protein-coding genes. The second goal is to explore, at high levels of resolution, the evolutionary dynamics of lncRNAs across selected eukaryotic groups for which novel genome-wide data will be produced experimentally using recently developed sequencing techniques that enable obtaining genome-wide footprints of RNA secondary structure. Finally, this dataset will be used to test the impact on lncRNAs evolution of processes known to be important in protein-coding genes.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesevolutionary biology
- medical and health sciencesclinical medicineoncology
- natural sciencesbiological sciencesgeneticsRNA
- natural sciencesbiological sciencesgeneticsgenomes
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Call for proposal
ERC-2012-StG_20111109
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Funding Scheme
ERC-SG - ERC Starting GrantHost institution
08003 Barcelona
Spain