Project description
Long non-coding RNAs: associating function with sequence
The discovery of long non-coding RNA (lncRNA) genes has revolutionised genome science and prompted scientists to rethink junk DNA. Emerging evidence indicates that lncRNAs are involved in development and disease and should therefore be studied in more detail. The EU-funded RNADOMAIN project will investigate how lncRNA function is encoded in primary RNA sequence. Through a high-throughput computational approach, researchers will identify and associate lncRNA domains with localisation and biological function. Moreover, machine learning algorithms will help predict new lncRNA functional domains and shed light on the role of these newly discovered molecules in health and disease.
Objective
From junk DNA to genomic dark matter, the road to understanding RNAs that do not encode for proteins has been full of surprises. Compared to 19,000 protein-coding genes, recent estimates point that our genome contains between 25,000 and 100,000 long noncoding RNA (lncRNA) genes. Far from being inert, some lncRNAs are involved in development and disease, particularly, cancer. It has also been shown that the function of a lncRNA can be associated with its localisation in subcellular compartments. Nevertheless, to experimentally characterize and validate interesting lncRNAs is an arduous task. Computational approaches based on machine learning could be designed to complement and scale-up such efforts. Based on recent experimental discoveries, it has been proposed that lncRNAs are separable into functional domains, and that these domains are intimately related to transposable elements and repeats. Nevertheless, how functions are encoded in primary RNA sequence is a fundamental unsolved problem. I propose to develop the first high-throughput computational approach to map lncRNA domains across metazoan genomes. Domains will be first identified according to statistical evidence supported by current biological insights. Putative domains will be queried against state-of-the-art databases on lncRNA function, localisation, and disease. Machine learning algorithms will then be employed to predict new functional domains, and new mechanistic insights will be offered for promising candidates. Lastly, the obtained maps will be stored and disseminated in a database, that will be regularly updated and readily accessible for the research community. This will be a foundational resource to finally shed light on the role of lncRNAs, their regulation and involvement in disease.
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. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences databases
- natural sciences biological sciences genetics RNA
- natural sciences computer and information sciences artificial intelligence machine learning
- natural sciences biological sciences genetics genomes
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2019
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
4 Dublin
Ireland
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.