Research

My research interests and a summary of the projects I have participated in

My research involves the development and use of computational approaches and spans a wide range of topics covering the biology of ageing, population genomics and ancient DNA studies, evolution of gene expression, and cheminformatics. However, I have the deepest interest revolves around the molecular mechanisms and evolution of ageing and ageing-related diseases.

Ageing is broadly defined as a time-dependent functional decline in physiological integrity and increased susceptibility to pathologies1. Although it is associated with functional decline, it is almost universal2. Similarly, both the lifespan and ageing trajectories are very diverse across species3, yet the genes and pathways modulating lifespan in model organisms are deeply conserved4. Overall, I am interested in understanding the molecular and evolutionary mechanisms contributing to the ageing phenotype and health-related consequences.


Previous Research

Anti-ageing interventions

The lifespan of model organisms can be modulated through genetic, environmental, or pharmacological interventions. Moreover, some of the lifespan modulators also prevent age-related decline in health. Motivated by these previous studies, I have worked on a systems-level drug repurposing strategy to discover drugs that can target ageing-related gene expression changes8.

I have also contributed to another study aiming to find drugs that can specifically target ageing-related genes, utilizing interactome and biological pathways9. As part of this work, we re-discovered one of the hits we found in the previous study10, tanespimycin, and experimentally validated its effect on lifespan. In a review article11, we have summarised the available computational studies and the future directions in this area.

Gene expression reversals in the ageing human brain

During my MSc degree I worked on comparative analysis of the age-related gene expression changes during postnatal development (0-20 years of age) and ageing (20+). I specifically asked if the direction of gene expression change with age is the same before and after the completion of development (age:20), or if the reversals are common. Through a meta-analysis approach that relies on consistent changes across multiple gene expression datasets, I found 25 genes with an ‘up-down’ pattern. Moreover, overall reversal trend was associated with neuronal and synaptic functions. Our results suggested that the reversal pattern was not explained by the extension of synaptic pruning or changes in cellular compositions but may represent loss of cellular identity driven by stochastic damage accumulation.


Other studies

  • Investigation of mutation accumulation theory of ageing, analysing the changes in gene expression with age in multiple mammalian species & tissues Publication
  • Transposable element landscape in Drosophila populations selected for longevity Publication
  • Investigation of gene flow events during the Neolithic transition in West Eurasia through ancient DNA analysis Publication
  • Neanderthal Introgression in Western Asia Publication
  • Demographic investigation of first farmers in Anatolia, through ancient DNA analysis Publication
  • Characterisation of the reactions associated with multi-reaction enzymes in the Enzyme Classification (EC) System Publication

You can find my up-to-date publication list in Google Scholar.


  1. López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M. & Kroemer, G. The hallmarks of aging. Cell 153, 1194–1217 (2013).↩︎

  2. Flatt, T. & Partridge, L. Horizons in the evolution of aging. BMC Biol. 16, 93 (2018).↩︎

  3. Jones, O. R. et al. Diversity of ageing across the tree of life. Nature 505, 169–173 (2014).↩︎

  4. Fontana, L., Partridge, L. & Longo, V. D. Extending healthy life span–from yeast to humans. Science 328, 321–326 (2010).↩︎

    1. Somel, M., Khaitovich, P., Bahn, S., Pääbo, S. & Lachmann, M. Gene expression becomes heterogeneous with age. Curr. Biol. 16, R359–60 (2006). b) Bahar, R. et al. Increased cell-to-cell variation in gene expression in ageing mouse heart. Nature 441, 1011–1014 (2006)
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  5. Kedlian, V. R., Donertas, H. M. & Thornton, J. M. The widespread increase in inter-individual variability of gene expression in the human brain with age. Aging (2019) doi:10.18632/aging.101912↩︎

  6. Işıldak, U., Somel, M., Thornton, J. M. & Dönertaş, H. M. Gene expression heterogeneity during brain development and aging: temporal changes and functional consequences. bioRxiv 595249 (2019) doi:10.1101/595249↩︎

  7. Dönertaş, H. M., Fuentealba Valenzuela, M., Partridge, L. & Thornton, J. M. Gene expression-based drug repurposing to target aging. Aging Cell 17, e12819 (2018).↩︎

  8. Fuentealba, M. et al. Using the drug-protein interactome to identify anti-ageing compounds for humans. PLoS Comput. Biol. 15, e1006639 (2019).↩︎

  9. Dönertaş, H. M., Fuentealba Valenzuela, M., Partridge, L. & Thornton, J. M. Gene expression-based drug repurposing to target aging. Aging Cell 17, e12819 (2018).↩︎

  10. Dönertaş, H. M., Fuentealba, M., Partridge, L. & Thornton, J. M. Identifying Potential Ageing-Modulating Drugs In Silico. Trends Endocrinol. Metab. 30, 118–131 (2019)↩︎