About the Project
Understanding evolutionary processes requires an interplay between wet-lab experiment and computational simulation . This project will use model systems for both to explore the interplay of evolutionary processes (primarily mutation) and the spatial environment.
EvoSim is a custom-written piece of software, developed by members of the supervisory team . It is capable of simulating evolution for large populations (>1 million) of individuals over long time periods (>5 million iterations). EvoSim uses a simplified model for computational efficiency, but incorporates many aspects of real biological evolution. It is a highly simplified system in which 64-bit digital organisms are modelled within a 1D or 2D RGB-colour based environment. Fitness depends on this environment. The organisms: have a coding and non-coding genome; can breed sexually or asexually; can move on breeding in 2D simulations; can mutate; can form different species; and have a limited or unlimited lifespan. The environment can be static or dynamic, and if the latter, can have variable rates of change. The system has a large number of variables, allowing the impact of each to be assessed; for example, the impact of rate of mutation on fitness, and the effect rate of environmental change has on the evolutionary patterns observed.
However, computational simulation results require truthing in wet-lab experiments. The organisms simulated in EvoSim bear similarity to microbes, which can also be evolved experimentally . We have used such approaches to look at basic mechanisms of evolution, in particular the relationship of mutation and the environment . This project will groundtruth the results of EvoSim simulations through complementary wet-lab work. Like EvoSim digital organisms, these can be studied over realistic time spans, and in large populations, both in spatial environments (agar plates) and non-spatial environments (shaken broth)This project will use the bacterium Escherichia coli and yeast Saccharomyces cerevisiae to test qualitative and quantitative predictions from EvoSim
This interdisciplinary combination of in-silico and lab-based study of evolution, can provide new insights into how evolution works. The consilience between complementary approaches will hone in on the driving forces behind different evolutionary patterns. This represents a unique opportunity for applicants interested in both computational biology approaches and labwork, and will allow the student to both write software in C++ and train in wet-lab techniques: a combination which will lend itself to multiple future career paths.
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