NPIF Rutherford Fellowship

Lead Research Organisation: MRC Laboratory of Molecular Biology
Department Name: UNLISTED

Abstract

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Technical Summary

During replication, DNA is unwound to expose single strands as a template for DNA synthesis. However, the propensity of single stranded DNA to form secondary structures poses a challenge to the smooth progression of the replication fork. Certain sequences are particularly prone to secondary structure formation, for instance G quadruplexes (G4) and triple helix forming DNA (H-DNA). Accumulating evidence suggests these structures form readily during replication in vertebrate cells, but are actively countered by a complex network of enzymes. Over 700,000 sites in the human genome are capable of G4 formation, so these structures pose challenges to replication forks potentially as frequently as naturally occurring DNA damage. Moreover, failure to maintain processive replication at secondary structures is associated with both genetic and epigenetic instability. However, the full range factors that promote secondary structure resolution during vertebrate replication is not known, and the in vivo coordination of existing enzymes and the forms of secondary structures upon which they act is also poorly understood. This project will investigate this area using a combination of RNAseq in mutants of known factors, and which have had secondary structures artificially inserted, as well as techniques that identify the location of R-loops (DNA-RNA hybrid triple helixes that may be formed in association with other secondary structures) to provide a comprehensive view of how these challenging DNA replication impediments occur and how they are handled. This will be ultimately important for understanding the circumstances under which structure-forming DNA sequences contribute to human pathology, for example in inherited syndromes, such as Werner or Bloom syndrome, or in cancer, in which replication stress may lead to widespread dysregulation of gene expression.

People

ORCID iD

Publications

10 25 50
 
Title Mogrify v2 
Description I developed a novel computational algorithm, that integrates data from various sources, to make deterministic prediction of transcription factors, which when upregulated, can reprogram any given source cell type to a target cell type of interest. This method is one of a kind, and is capable of taking as input all modern high-throughput transcriptomics data. Further, I developed, as part of the grant, a method to integrate public knowledge of protein-protein interactions and gene regulatory network interactions to make predictions of the master regulators. 
Type Of Material Computer model/algorithm 
Year Produced 2019 
Provided To Others? No  
Impact A private company Mogrify was started, and the method was licensed to the company.