PhD Studentship: Mathematical modelling DNA replication dynamics: does Polymerase δ initiate replication on the leading strand?

University of Sussex - Genome Stability/Genetics

Deadline: 12th January 2017

A Ph.D. studentship (42 months) is available from September 2017 in the group of Prof. Tony Carr, Genome Damage and Stability Centre, School of Life Sciences.

DNA replication uses 3 polymerases: Polε, Polδ, Polα. Polε synthesises the leading strand continuously. Polδ synthesises the lagging strand discontinuously. Polα initiates each replication event, synthesising ~2% of DNA. Prof. Carr recently developed a deep-sequencing method (Pu-Seq) to map polymerase usage across whole genomes (Keszthelyi 2015), generating large datasets reflecting ensemble replication dynamics. Pu-Seq exploits mutated Polε, Polδ or Polα enzymes that leave unique rNMP “tracers” in those DNA strands synthesised by a mutated enzyme. Deep sequencing identifies these tracers, mapping them onto the reference genome. The datasets inform on the ensemble use of each polymerase on the Watson and Crick strands at each genomic locus, providing information on: replication initiation, fork movement, replication timing, fork arrest and, potentially, restart (Daigaku 2015: Miyabe 2015).

Each double-stranded locus should be replicated with a ~50:48:2 (Polε:Polδ:Polα) ratio. However, we observed small but significant fluctuations for Polδ usage (+2-4%) correlating to sites of DNA replication initiation. We proposed that this reflects the detailed enzymology of leading strand initiation in vivo (Daigaku, 2015). This proposal recently received support from in vitro replication studies. Enzyme usage exhibits additional asymmetry across the chromosomes, potentially reflecting known biological phenomenon (i.e. replication/transcription clashes) and/or identifying new biological processes (i.e. heterochromatin-replication interactions). However, it is unclear how much the observed variation reflects biology and how much reflects sampling/data acquisition uncertainties. Since astronomers routinely model complex systems and apply statistical methods to large datasets, we are currently joining these disciplines to explore extracting maximum insight from Pu-Seq datasets.

The proposed student will work between biologists (GDSC-LifeSci) and mathematicians (MPS). They will generate data relating to replication dynamics and use (and further advance/refine) replication models (probabilistic and deterministic) and data simulation software to validate hypotheses. The aim is to exploit Pu-Seq datasets to identify and understand the mechanisms that control DNA replication dynamics.

This School funded position, which covers fees and a stipend at standard RCUK rates, is open to Home/EU applicants who should hold or expect to obtain a first or upper second class honours degree (or equivalent) in relevant subject. Candidates for whom English is not their first language will require an IELTS score of 6.5 overall, with not less than 6.0 in any section. It is envisaged that either a biologist with a keen interest in mathematical modelling, or a mathematician with a keen interest in biology would be appointed.

Please submit a formal application using our online application system at http://www.sussex.ac.uk/study/pg/applying/, including a CV, statement of interest and names of two academic referees.

On the application system use Programme of Study – Ph.D. Genome Stability. Contact Alice Caryer (a.caryer@sussex.ac.uk) with queries.

Please make sure you include the project title and Supervisor’s name with your statement of interest on the application form.

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Type / Role:

PhD

Location(s):

South East England