Project No. 2421

STANDARD PROJECT

Primary Supervisor

Prof Adam Eyre-Walker – University of Sussex

Co-Supervisor(s)

Dr Marta Farré Belmonte- University of Kent

Dr Frances Pearl- University of Sussex

Summary

Mutations are the ultimate source of all genetic variation.

The mutation rate is known to vary across the human genome at a variety of different scales, from variation between adjacent sites, to variation between whole chromosomes. This variation is observed both in the germline, generating heritable genetic differences, including those that cause a variety of human diseases, and in the soma, which can cause cancer. Despite its importance this variation remains poorly characterised and understood. This project will address a number of different questions. In the first part of the project we will quantify the extent to which the mutation rate varies at different scales in both the germline and soma. To what extent are the patterns of mutation correlated between different tissues and life stages? In the second part of the project we will attempt to understand why the mutation rate varies and develop a predictive model using artificial intelligence techniques. In the third part of the prohect we will investigate one particular mutational mechanism in which one mutational event leads to multiple mutational events at the same nucleotide site. The project will give us insighst into one of the most fundamental processes in genetics and help us understand how genetic variation is generated and how cancer mutations are produced.

The project will involve the analysis of DNA sequence data and will give the student training in bioinformatics, big data and statistical analysis. Students with some experience of bioinformatics are particularly encouraged to apply. The project will be supervised by Prof. Adam Eyre-Walker and Dr. Frances Pearl at the University of Sussex, and Dr. Marta Farré-Belmonte at the University of Kent, leaders in the field of molecular evolution and computational biology.