A Genomic Perspective on Social Selection, Natural Selection and Random Genetic Drift

Project: Research council

Project Details


The Darwinian idea of 'survival of the fittest' is central to our understanding of the diversity of life on this planet. However, if only the fittest survive and reproduce, then why do we see so much variation among individuals in traits that are tied to fitness? This problem is especially striking in social systems where cooperating individuals perform some sort of costly act that helps others. Cooperative behaviour therefore has important effects on the fitness of individuals and those that they interact with (often their relatives). Furthermore, cooperating individuals run the risk of invasion by disruptive cheaters that reap the benefits of cooperative behaviours, but do not pay their fair share of the cost. In such situations, we would expect the 'best' strategy to emerge: either cheating or cooperating. Surprisingly, however, studies of natural populations often reveal variation in the degree to which individuals appear to cooperate and cheat. If either cheating or cooperating is the better strategy, then why is there variation along a cooperator-cheater continuum? To better understand this problem, we believe that it is important to not only describe the nature of the variation that is actually present in populations, but also the genes that generate this variation and the processes shaping their variation. This is because, although evolutionary theory may suggest the best strategy, the genetic changes required may not be possible. For example, some strategies may not exist because any gains may be offset by other fitness costs. Alternatively, cooperative traits may be expressed rarely, or there may be limited opportunities to cheat, and as a result the action of Darwinian selection may simply be too inefficient to mould variation to achieve the optimal or favoured strategy. We propose to address this fundamental question using a simple system for the study of cooperative behaviour, the soil dwelling social amoeba Dictyostelium discoideum. Under favourable conditions, D. discoideum amoebae exist as single celled individuals that grow and divide by feeding on bacteria. Upon starvation, however, up to 100,000 amoebae aggregate and cooperate to make a multicellular fruiting body consisting of hardy spores supported by dead stalk cells. Stalk cells thus sacrifice themselves to help the dispersal of spores. Such sacrifices can be favoured because they typically help relatives, but when non-relatives interact, the sacrifices of an individual may help non-relatives. Crucially, like other systems, we have discovered that D. discoideum show enormous diversity in a wide array of traits, including the degree to which different individuals cooperate, thus providing us with a simple system to investigate why such variation exists. To achieve this goal, we will employ a novel combination of approaches in D. discoideum that allow the genetics and evolution of cooperative behaviour and other traits to be analysed with great power. We will use a large panel of naturally occurring strains to identify natural variation in genes that account for the diversity in the traits we observe. We will characterize the types of genes that produce natural diversity in social traits and ask whether those genes also affect other types of non-social traits, which could suggest that they are constrained or shaped by non-social processes. We will be able to determine the types of evolutionary processes that appear to be responsible for the maintenance or persistence of variation in populations. Finally, we will integrate these results with models of evolution to develop a better theoretical understanding of how genetic diversity is maintained and evolutionary outcomes constrained. This work will therefore lead to a fundamental advance in our understanding of the types of variation underlying phenotypic diversity in natural populations and the evolutionary processes shaping that variation.
Effective start/end date1/09/1531/12/18


  • Biotechnology and Biological Sciences Research Council