Honours research projects currently available
The Computational Evolutionary Genetics laboratory is interested in enquiries from any potential Honours students for projects in research areas described on these pages. For further details, please contact the lab head (click the "personnel" link on the left for contact details).
The following projects require computer programming. If you do not have programming experience, you will be taught to program using FORTRAN, a powerful and flexible language (the oldest, and still best, high-level programming language for quantitative applications).
Evolution Across Fitness Valleys
Two genes may interact such that individually they reduce fitness but jointly they increase fitness. This produces a metaphorical "fitness valley" because a population evolving by single-mutation steps would have to travel through the low-fitness, single-mutant state in order to reach the high-fitness, double-mutant state. There are several ways in which such fitness valleys may be crossed. The fixation of the first, deleterious mutation may occur by chance (genetic drift). Alternatively, double mutants may arise spontaneously, or be produced by recombination, and then spread to fixation. How populations actually cross fitness valleys is an important question in evolutionary biology. For this project, the student will build a population genetics model to simulate the evolution of a population across a fitness valley. This model will be used to study how populations cross fitness valleys under different conditions, and the results will be compared to theoretical predictions from HIV-1.
The Population Genetics of Altruism
The observation that in some social groups (e.g., honey bees) some individuals forfeit their own reproduction and instead help raise others' offspring, a form of altruism, was recognised by Darwin as a special challenge to his theory of evolution by natural selection. But, not until the 1960s did the evolutionary biologist Bill Hamilton formalise a solution to this paradox. Hamilton reasoned that altruism will evolve if the cost (c) to an individual, in terms of fitness, of an altruistic act is less than the benefit (b) to the receiver of the act discounted by the genetic relatedness of the two individuals (r); i.e. if c < rb. Recently, this argument has been questioned because the necessary conditions are seemingly rare. One condition, however, is common. This is where dispersal from a natal territory, permitting independent breeding, is constrained by ecological factors, such as a limited number of breeding territories. Under this scenario, the condition for c < rb may be met if a subordinate, non-breeding individual does not disperse, thereby foregoing reproduction, and instead helps its parents raise their offspring. Although this ecological-constraints model has been used to explain "helpers at the nest" in birds since the 1980s, the population genetics underlying it have never been modeled. This project involves building a spatially explicit population genetics model of altruism to determine whether, and under which specific conditions, a mutation for altruism will spread to fixation.
Students interested in these projects should contact me by the end of October in order to apply for a Science and Industry Endowment Fund $5000 scholarship.
References
DA SILVA, J., M. COETZER, R. NEDELLEC, C. PASTORE and D. E. MOSIER, 2010 Fitness epistasis and constraints on adaptation in a human immunodeficiency virus type 1 protein region. Genetics 185: 293-303.
HAMILTON, W. D., 1964 The genetical evolution of social behaviour. I and II. J. Theor. Biol. 7: 1-52.
KREBS, J. R., and N. B. DAVIES, 1997 Behavioural ecology : an evolutionary approach. Blackwell Science, Cambridge, Mass.
MARSHALL, J. A. R., 2011 Group selection and kin selection: formally equivalent approaches. Trends in Ecology & Evolution 26: 325-332.
WEINREICH, D. M., and L. CHAO, 2005 Rapid evolutionary escape by large populations from local fitness peaks is likely in nature. Evolution 59: 1175-1182.
