PhD project

Supervisor: Monika Gullerova

DNA damage, especially double-strand breaks (DSBs), is a major threat to genomic stability and cell survival. The DNA damage response (DDR) is a complex network of signalling and repair pathways that coordinate the detection and resolution of DNA lesions. Recent studies have revealed that RNA plays an important role in DDR, both as a regulator and as a substrate. RNA modifications, such as m6A and m5C, can affect the expression and function of DNA repair proteins, as well as the formation and resolution of DNA:RNA hybrids at DSB sites. However, the mechanisms and consequences of RNA modifications in DDR are still poorly understood.

In this project, we propose to use nanopore sequencing, a novel technology that can directly detect base modifications in native RNA molecules, to study the dynamics and functions of RNA modifications in DDR. Nanopore sequencing measures the changes in ionic current as nucleic acids pass through a nanopore, which are sensitive to the presence of modified bases. We will combine nanopore sequencing with machine learning, a branch of artificial intelligence that can learn from data and make predictions, to develop a robust and accurate method for RNA modification detection and quantification. We will also use synthetic modified RNA molecules, which are artificially produced RNA molecules with known modifications, to train and validate our method.

We will apply our method to study the changes of RNA modifications at DSBs in different stages of DDR, such as damage induction, repair initiation, repair completion and recovery. We will also identify novel RNA modifications that are involved in DDR, such as N1-methyladenosine (m1A) and 7-methylguanosine (m7G), which have been reported to regulate long non-coding RNAs (lncRNAs) in cancer. We will investigate the potential application of our method in cancer research, as aberrant RNA modifications may contribute to tumorigenesis and therapy resistance. Our project will advance the understanding of RNA biology in DDR, and will provide a powerful tool for RNA modification analysis with high commercial potential.

Publications:

• Bader AS et al., BJC, 2020
• Jimeno S et al., Front in Mol Biosc., 2021
• Wang Y et al., Nature Biotechnology, 2021
• Cusenza VY et al., Front. Oncol., 2023
• Blanco S et al.,  Mol Cancer., 2021