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Understanding and predicting disease-associated mutations in dynamic and disordered regions of proteins

  • Full or part time
  • Application Deadline
    Friday, December 13, 2019
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

About This PhD Project

Project Description

Applications are invited from outstanding candidates to join the MRC Human Genetics Unit (HGU), part of the Institute of Genetics and Molecular Medicine (IGMM) at the University of Edinburgh. Candidates should hold at least an upper second-class degree in a relevant subject and comply with English language requirements (see application page).

Understanding how human genetic variation translates into observable phenotypic differences is one of the most important questions in all of biology and medicine. Most human genetic disorders are caused by mutations in protein-coding regions of DNA that affect the way proteins are made. While humans exhibit extensive protein sequence variation, most of it has little or no phenotypic effect. Therefore, the ability to distinguish damaging mutations from the large majority of benign variants is tremendously important for disease diagnosis, treatment and prevention.

The vast majority of previous research into the molecular mechanisms underlying pathogenic missense mutations has focused on well-folded proteins with structures that can be determined using X-ray crystallography. While this has provided tremendous insight, the highly dynamic and intrinsically disordered regions of the human proteome have been largely ignored. Such regions are present in most human proteins, and are being increasingly recognised for their important biological roles and their strong association with human genetic disease. Thus their consideration is crucial for fully understanding genotype-to-phenotype relationships.

This project will build on the considerable expertise of the Marsh lab at the MRC Human Genetics Unit in studying protein dynamics, interactions, intrinsic disorder, and disease mutations. The student will perform a series of systematic computational analyses, investigating how the dynamics, disorder, aggregation propensity, phase separation, post-translational modifications and interactions are related to patterns of genetic variation observed in the human population, in cancer, and in evolution. These analyses will utilise a variety of bioinformatics and molecular modelling approaches, and incorporate diverse proteomic and genomic datasets. Ultimately, the goal will be to identify features of dynamic and disordered proteins that can be integrated with machine-learning strategies in order to improve the accuracy of computational phenotype predictions, and can help directly in the diagnosis of genetic disorders. Moreover, as part of this project, the student will also work closely with our clinical geneticist collaborators in order to help understand and explain recently identified mutations.

For details on how to apply, please visit:


Bergendahl LT, Gerasimavicius L, Miles J, Macdonald L, Wells JN, Welburn JPI & Marsh JA (2019) The role of protein complexes in human genetic disease. Protein Science 28:1400-1411

Abrusán G & Marsh JA (2019) Ligand binding site structure shapes allosteric signal transduction and the evolution of allostery in protein complexes. Molecular Biology & Evolution 36:1711-1727

Williamson KA, Hall HN, et al (2019) Recurrent heterozygous PAX6 missense variants cause severe bilateral microphthalmia via predictable effects on DNA-protein interaction. Genetics in Medicine (in press)

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