This project aims to understand how changes in our genetic code can disrupt the way cells control and use messenger RNA (mRNA)—the molecule that carries instructions from DNA to make proteins. In cells, mRNA does not act alone: it forms complexes with proteins called mRNPs (messenger ribonucleoprotein particles). These mRNPs are essential for regulating how genes are expressed. When they malfunction, it can lead to serious diseases, including neurodegenerative disorders like Amyotrophic Lateral Sclerosis (ALS).
Until now, researchers have struggled to study how genetic variation affects mRNPs because most available data come from a few standard cancer cell lines, which do not represent the cell types relevant to brain diseases. Recent technological advances, however, now make it possible to model these effects more accurately. Large public datasets describing protein–RNA interactions, improved experimental methods for mapping molecular contacts, and powerful new machine learning approaches have opened up new opportunities to explore mRNP biology in disease-relevant cells.
In this project, the student will build advanced computational models that link RNA sequences to their biological functions. These models will be trained using a combination of genomic, transcriptomic, and protein interaction data. Once developed, they will be used to predict how rare genetic variants—found in large-scale datasets such as Genomics England, Project MinE, and ANSWER-ALS—may alter mRNP formation and gene regulation. The goal is to connect these molecular disruptions to disease outcomes and changes in gene expression in neurodegenerative conditions.
The work will combine computational biology, artificial intelligence, and in collaboration with other lab members, experimental validation. Predictions from the models will be tested in neuronal cells derived from stem cells to confirm their real-world effects. Ultimately, this research will shed light on how genetic mutations contribute to disorders like ALS and could point toward new therapeutic strategies.