Job Detail

Ref. 2016-12

DNA replication, the duplication of a cell’s genetic material, ensures the maintenance of the genetic information and is the basis of biological inheritance. In eukaryotic cells, DNA replication initiates at multiple locations in the genome, known as origins of replication, and continues from there in both directions, thereby creating replication forks.

This project aims at developing a stochastic hybrid model of DNA replication that incorporates spatial information on origin locations and protein mobility dynamics. The ultimate goal is to understand the relationship between 3D structure and DNA replication. The model will be tailored for the case of fission yeast using recent experimental data and will be simulated in a high-performance computing setup.

The research will be conducted in collaboration between the Automatic Control Laboratory of ETH Zurich and IBM Research – Zurich. More specifically, the project will involve:

• Adapting an existing model of protein mobility [1, 2] for the case of fission yeast nucleus and model origin locations in 3D using experimental data.


• Integrating the origin location and existing DNA replication models [3] to enable stochastic initiation of origin firing when activation factors diffuse and bind onto the origins.


• Simulating the resulting integrated model to test various hypotheses, for example different kinetic parameters of the activation factors or different relative positioning of the origins.


• Examining whether and how relative origin positioning affects replication timing and how the process is affected by the dynamics of activation factors.

IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent, flexible working arrangements enable both women and men to strike the desired balance between their professional development and their personal lives.

Contact

For more information please contact J. Lygeros and M. Rapsomaniki.

References

[1] E. Cinquemani, V. Roukos, Z. Lygerou, and L. Lygeros,
“Numerical analysis of FRAP experiments for DNA replication and repair,” in IEEE Conference on Decision and Control, Cancun, Mexico, December 9-11, 2008.
[2] M. Rapsomaniki, E. Cinquemani, N. Giakoumakis, P. Kotsantis, J. Lygeros, and Z. Lygerou,
“Inference of protein kinetics by stochastic modeling and simulation of fuorescence recovery after photobleaching experiments,” Bioinformatics31(3) 355-362, 2015.
[3] J. Lygeros, K. Koutroumpas, S. Dimopoulos, I. Legouras, P. Kouretas, C. Heichinger, P. Nurse, and Z. Lygerou,
“Stochastic hybrid modeling of DNA replication across a complete genome,” Proceedings of the National Academy of Sciences of the U.S.A., vol. 105, pp. 12295-12300, August 2008.