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

Lead Research Organisation: University of Manchester
Department Name: School of Health Sciences


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 course).


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Description Dawkins' fabled cooperative gene discovered in microbes
Geneticists from the Universities of Manchester and Bath are celebrating the discovery of the elusive 'greenbeard gene' that helps explain why organisms are more likely to cooperate with some individuals than others

The renowned evolutionary biologist Richard Dawkins coined the term "greenbeard gene" in his 1976 best seller The Selfish Gene.

The greenbeard is a special type of gene that, said Dawkins, could solve the conundrum of how organisms identify and direct selfless behaviour to towards other selfless individuals.

The existence of greenbeard genes once seemed improbable, but work published in Nature Communications by the team of geneticists has identified a gene that causes a whole range of 'beard colours' in a social microbe.

The microbes - 'slime moulds' - live as single celled organisms, but clump together to form a slug like creature when they run out of food. The newly formed slug can move to help them find new sources of food, but this depends on successful cooperation.

With funding from the Wellcome Trust, NERC and the BBSRC the research team found that slime mould cells are able to decide who they collaborate with. By sequencing their genomes, they discovered that partnership choices are based on a greenbeard gene.

The gene encodes a molecule that sits on the surface of a slime mould cell, and is able to bind to the same molecule in another slime mould cell.

Greenbeard genes stand out because they harbour enormous diversity, with most slime mould strains having a unique version of the gene.

The team discovered that individuals prefer to partner with those that have similar versions of the gene, and the slugs formed with preferred partners do better than those with non-preferred partners.

This demonstrates, according to the team, that there is a whole range 'beard colours' that function to identify compatible partners for cooperation.

Prof Chris Thompson, who led the work in the School of Medical Sciences at The University of Manchester, said: "Most organisms are social, including microbes. But some individuals are altruistic towards certain individuals and not others. Our discovery of a greenbeard gene goes some way to explaining partner specific cooperative behaviour in slime moulds. And what is especially exciting is the sheer diversity of this gene with every slime mould having its own colour of greenbeard."

He added: "It is certainly more difficult to explain how this might work in humans and other animals.
"But ants, for example, are thought to identify each other socially by using a greenbeard pheromone so it's not beyond the realms of possibility that humans may possess something which works along similar lines".

Professor Jason Wolf, from the Milner Centre for Evolution at the University of Bath, said: "Dawkins's original greenbeard idea seemed fanciful because it was difficult to imagine a scenario where a region of the genome could have all of the necessary properties. Therefore it was really surprising to indentify such a region, and downright astonishing to find that it harboured such a huge array of 'beard colours' that would allow individuals to be very discerning about with whom to cooperate."
Exploitation Route This is a conceptual leap as it illustrates the likelihood that genes of this nature will exists in other systems
Sectors Education,Pharmaceuticals and Medical Biotechnology

Title next generation sequencing of Dictyostelium natural isolates 
Description collection of natural isolates that have been sequenced 
Type Of Material Biological samples 
Year Produced 2016 
Provided To Others? Yes  
Impact none yet 
Title Natural strain sequence database 
Description Whole genome sequence from up to 1000 starins 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
Impact publication of one paper in current biology, and papers to be submitted 
Description Baylor college of medicine 
Organisation Baylor College of Medicine
Department Department of Molecular and Human Genetics
Country United States 
Sector Academic/University 
PI Contribution Provision of materials
Collaborator Contribution Advice and expertise on next generation sequencing and bioinformatics
Impact Publications, training
Description Brazil partnership 
Organisation Federal University of Sao Carlos
Country Brazil 
Sector Academic/University 
PI Contribution Partnership with Brazilian groups (Sao Paulo) who are sequencing geographically distant species. We have provided the strains for gDNA preparation
Collaborator Contribution Expertise in long read assembly
Impact Multidisciplinary - computational biology and molecular genetics
Start Year 2015
Description Studies of social behaviour 
Organisation University of Bath
Country United Kingdom 
Sector Academic/University 
PI Contribution We provided Dictyostelium expertise and socio-biology expertise
Collaborator Contribution They have provided mathematical and theoretical ideas to our socio-biological research
Impact Publication PMID: 19631539 Dissemination: Guardian article, BBC Three Counties Radio interview NERC Project grant NE/H020322/1 awarded July 2010 Publication PMID: 20546090
Start Year 2006
Description genetics of socio biology 
Organisation Baylor College of Medicine
Country United States 
Sector Hospitals 
PI Contribution We instigated the project during my time at Baylor College of medicine. The experimental design, conclusions and manuscript preparation were all contributed to by us
Collaborator Contribution New ideas and research directions
Impact PMID: 18272966
Description Why am I similar to slime mould? 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Children felt Developmental Biology was interesting from feedback received

Feedback that wanted to do another lab visit next year
Year(s) Of Engagement Activity 2014