Dissecting the ageing transcription factor network to set a rational basis for age-intervention strategies

On a cellular level, ageing appears to be a largely epigenetic phenomenon that can be manipulated by pluripotency induction. Transdifferentiation and iPS technologies are forms of transcription factor (TF)-mediated cell reprogramming. This is achieved by the overexpression of a set of key TFs in a given cell type to induce reprogramming into another cell type. Direct reprogramming has so far only been used to generate “healthy young” cells from other young cell types. What would be most exciting is to transform a given cell type from an “aged” to a “healthy young” state.

To uncover TFs and chromatin state changes that drive ageing in different cell types and whether this is conserved across species, we are creating a molecular atlas (RNAseq, ATACseq) comprised of dozens of mammalian cell types from both young and aged subjects. By pinpointing and analysing age-related changes to the TF network the project will reveal if there are TFs or TF families that drive ageing across different cell types or if ageing is a largely cell type specific process. Ultimately by pinpointing and targeting what makes cells age, we want to find ways to “reprogramme” aged cells back towards working more efficiently, like young cells do, without a need for pluripotency induction. In collaboration with wet lab scientists, hypotheses derived from the candidate’s analyses will be tested using in vitro and in vivo cell models.

The diverse background of researchers within the Nefzger group, will provide the candidate with access to state of the art training in the area of computational biology.

Eligibility
To be eligible, you must meet the entry requirements for a higher degree by research.

How to apply
To be considered for this scholarship, please email the following documents to Dr Christian Nefzger ([Email Address Removed])

- Cover letter
- CV
- Academic transcript/s
- Any other documents you would like to receive

Please note the following: Submitting the above documents does not constitute a full application for admission into The University of Queensland's PhD program. If you are selected as the preferred applicant, you will then be invited to submit a full application for admission. You can familiarise yourself with the documents required for this process on the Graduate School's website.

Selection criteria
The ideal candidate has some demonstrated background in computational bioinformatics and as such is comfortable writing code in languages such as R, Matlab, Perl, or Python.