Bilateral BBSRC-FAPESP: A genome wide view of the evolutionary processes shaping genetic variation in natural populations

Lead Research Organisation: University of Bath
Department Name: Biology and Biochemistry


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.

Technical Summary

Explaining why so much natural genetic variation exists in fitness related traits is a fundamental problem in evolutionary genetics. Many competing explanations have been proposed, but cleanly distinguishing between them experimentally has been challenging. For example, we find surprisingly high genetic variation in key fitness related social behaviour traits across a huge diversity of taxa, despite a general expectation that variation will be removed by selection. To understand the processes shaping such variation we will employ a novel combination of approaches to dissect the genetics and evolution of social and non-social traits using the social amoeba D. discoideum (Dd). The Dd system provides a uniquely powerful model to dissect the processes shaping genetic diversity in a natural microbial population, while providing critical insights into how the genomes of more complex species are shaped by evolution. Specifically, we will employ a powerful integration of computational, genomic and experimental approaches to: 1) identify and characterize genes that produce natural diversity in social and non-social traits, 2) experimentally validate the causal role of natural genetic variants using cutting edge molecular techniques, 3) test whether the same genes affect both social and non-social traits, suggesting that they are constrained and their joint evolution is shaped by pleiotropy, and 4) determine the evolutionary processes that have shaped variation in this system. Together, these objectives will lead to fundamental advances in our understanding of the types of variation underlying phenotypic diversity in natural populations and the evolutionary processes shaping that variation. It will also provide significant long-term benefits to the research community through the establishment of a core reference panel, opening entirely new avenues of investigation into the genetic basis of any trait, and thus ensuring the legacy of this project.

Planned Impact

1. Beneficiaries:
Academic community: This project targets a central question in evolutionary genetics: the evolution and maintenance of variation within natural populations. The academic community of geneticists and evolutionary biologists will be primary beneficiaries. However, the interdisciplinary nature of the work means it will build unifying concepts, drawing together developmental biology, evolutionary biology and genetics. Furthermore, this work will provide a rich dataset and important resource that can be used in future work by researchers across research areas. These researchers can use these same strains in other studies, taking advantage of the genomic and phenotypic data we will have produced and made public, and increasing the long-term impact of this study.

Enhancing International Collaboration: Our Pathways to Impact will strengthen UK science by strengthening collaborative links with the Brazilian partners in São Paulo. This link will enhance the connection between UK funded science through RCUK and the state of São Paulo through FAPESP. FAPESP has worked together with our British institutions to foster collaborations, including the seed funding that launched the collaboration between Wolf and de Brito, The addition of more groups to this collaboration will increase its value..

General Public: The evolution and maintenance of variation within natural populations fascinates the general public. Moreover, our study focus, cooperation and cheating, captures the attention of the general public. Our work has been highlighted by the popular media and used extensively in outreach programmes in the past, and we expect that understanding the evolutionary processes shaping these sorts of behaviours in natural populations should continue to generate interest with this wider audience.

2. Implementation:
Dissemination: To reach the academic beneficiaries we will submit our results to high impact journals and ensure they are made open access. We will also work with our local media offices to maximize exposure in the popular press and continue our regular attendance at national and international scientific meetings and workshops

Research training: We will train the PDRAs and technician in cutting edge molecular genetic and quantitative skills such as maximum likelihood mixed modelling, computer simulation, analytical modelling and data manipulation. The technician will be trained in experimental design and management of large projects.

Advanced training resources:
A) Evolutionary computational genetics course: We will generate impact and added value through educational resources in evolutionary population genetics. To achieve this goal, we will deliver a three day short course at the University of Bath targeted at evolutionary biologists. The course will include computer lab components focused on analysis and simulation approaches. We will also deliver an expanded version of this course to contribute to the development of the academic community in Brazil, where research in evolutionary population and quantitative genetics is an emerging discipline. This will maximize the value of the RCUK-FAPESP joint funding by providing direct impact in both research communities. Our long term goal is to establish this course in the state of São Paulo, providing high calibre training to arguably the largest concentration of evolutionary geneticists in a developing economy.

B) Online resources: To maintain the long-term impact of these educational resources, we will package them as an online course, with the content coordinated with video and printable resources.

Community outreach: We will work with the University of Bath, University of Manchester, and Federal University of São Carlos to provide outputs to the general media. To improve our outreach the PDRAs will participate in the Royal Society Communication Skills and Media Skills Training courses (which are combined into a two day residential co


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Madgwick PG (2018) Strategic investment explains patterns of cooperation and cheating in a microbe. in Proceedings of the National Academy of Sciences of the United States of America

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Wolf JB (2016) Evolutionary genetics of maternal effects. in Evolution; international journal of organic evolution

Description We have found that the microbes we study are able to strategically vary their contributions to cooperation in response to differences in their relatedness to the other individuals they interact with. This has important implications for our understanding of the patterns of genetic variation we observe in natural populations as it suggests that there is a single optimal strategy that all strains of the microbe should use when interacting with others. As a result, we expect natural selection to remove variation and reinforce this single optimal approach to cooperation.

We have also examined patterns of variation at the genes underlying social interactions and we indeed see clear signs that these genes primarily experience 'purifying' selection to remove deleterious variation. We further found that, because social interactions only occur every few generations, the genes that are used in social interactions tend to harbour more mutational variation than other genes. This reflects the fact that the action of purifying selection is somewhat ineffective because each round of selection during the social phase is diluted by many generations of mutation during the non-social phase of the organisms life cycle.
Exploitation Route Our work has implications for how we view social interactions in simple organisms. By showing that microbes are able to invoke strategies that balance the costs and benefits of cooperation our work suggests that behaviour may be more facultative and strategic than we may have thought. Our finding that variation at the genes underlying social interactions is likely a result of the inefficiency of purifying selection implies that much of the variation that we have previously documented is likely non-adaptive and simply reflects the inability of natural selection to shape behaviours that are only expressed occasionally.
Sectors Environment