Bilateral BBSRC-FAPESP: A genome wide view of the evolutionary processes shaping genetic variation in natural populations
Lead Research Organisation:
University College London
Department Name: Genetics Evolution and Environment
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
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 to 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).
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 to 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).
People |
ORCID iD |
| Christopher Thompson (Principal Investigator) |
Publications
Gruenheit N
(2021)
Mutant resources for functional genomics in Dictyostelium discoideum using REMI-seq technology.
in BMC biology
Gruenheit N
(2017)
A polychromatic 'greenbeard' locus determines patterns of cooperation in a social amoeba.
in Nature communications
Gruenheit N
(2018)
Cell Cycle Heterogeneity Can Generate Robust Cell Type Proportioning.
in Developmental cell
Cocorocchio M
(2018)
Curcumin and derivatives function through protein phosphatase 2A and presenilin orthologues in Dictyostelium discoideum.
in Disease models & mechanisms
Belcher LJ
(2022)
Developmental constraints enforce altruism and avert the tragedy of the commons in a social microbe.
in Proceedings of the National Academy of Sciences of the United States of America
Baines RP
(2021)
Dictyostelium discoideum: An Alternative Nonanimal Model for Developmental Toxicity Testing.
in Toxicological sciences : an official journal of the Society of Toxicology
Aloum L
(2019)
Coenzyme A and protein CoAlation levels are regulated in response to oxidative stress and during morphogenesis in Dictyostelium discoideum.
in Biochemical and biophysical research communications
| Description | This proposal aimed to understand the forces that shape the genes underlying social traits through the use of a unique combination of modelling, experimentation and next generation sequencing to. To date, we have published three outputs (Gruenheit et al, Nature Comm., 2017; Madgwick et al, PNAS, 2018; de Oliveira et al Nature Comm. 2019) and are about to submit three more papers that arose from work carried out in this project. Genome sequencing: during the course of this grant we were able to sequence the genomes of almost 576 D. discoideum strains. We developed a sequencing 'pipeline' which allowed large numbers of strains to be prepared for storage and for gDNA preparation. Strains were first sequenced in a 96 format by Illumina 75 bp paired end sequencing. If strains in this set were too divergent to allow mapping of sequence data to the reference genome (which is how we previously accomplished other genome assemblies), gDNA was then subjected to long read sequencing. This hybrid approach facilitates de novo genome assembly without reliance on the reference genome, using the long-read data as a scaffold to link together the shorter reads. This second set of sequencing was done in coordination with our FAPESP funded partner in Sao Carlos, Brazil. The sequencing work completed under this project has resulted in resources that will be ultimately be exploited by the research community (genome data and strain collection), whilst the genome data has already been crucial to determine signatures of molecular evolution. The sheer number of strains analysed has afforded unprecedented power of analysis and has allowed us to draw novel conclusions. High throughput phenotyping: We have also developed high throughput methodology to measure variation in phenotypes associated with social behaviour in a large number of strains. Firstly, we generated FACS based protocols that allowed the degree to which strains recognise and segregate from one another to be quantified in large numbers of single fruiting bodies. Secondly, we were able to develop highly quantitative methods to assess the contribution of different strains to the sporehead in chimera. Again, using FACS based methodology, we were able to mazimise the number of strain pairings, and even precisely investigate the effects of mixing strains at different input frequencies. Together, these approaches have been pivotal as they have provided key insights into how genome evolution has been impacted by key traits associated with social behaviour (changes in gene expression, segregation and spore formation). Finally, the high throughput phenotyping and genotyping has led to surprising observations about the nature of social interaction, which have led to a step change the way we think about how cooperation is maintained in general. We are now poised to capitalise and extend this published work through the approaches illustrated in the our new BBSRC proposal. Published findings associated with this project: Gruenheit N, Parkinson K, Stewart B, Howie JA, Wolf JB & Thompson CRL (2017) A polychromatic 'greenbeard' locus determines patterns of cooperation in a social amoeba Nature Communications, vol8:14171. doi: 10.1038/ncomms14171. This work focused on understanding variation in social traits associated with the composition of aggregations, with a goal of identifying genomic loci that explain natural variation. Using the genome sequence data and phenotypic data on patterns of segregation from chimeric aggregations generated under this project, we demonstrated that a locus ('Tgr') of a social amoeba represents a polychromatic greenbeard (which is a tag that can recognise and preferentially direct cooperation towards other tag carriers). Patterns of natural Tgr locus sequence polymorphisms predict partner-specific patterns of cooperation by underlying variation in partner-specific protein-protein binding strength and recognition specificity. Finally, Tgr locus polymorphisms increase fitness because they help avoid potential costs of cooperating with incompatible partners. These results suggest that a polychromatic greenbeard can provide a key mechanism for the evolutionary maintenance of cooperation. Madgwick PG, Stewart B, Belcher LJ, Thompson CRL and Wolf JB (2018) Strategic investment explains patterns of cooperation and cheating in a microbe PNAS, 115 (21) E4823-E4832 This work was aimed at understanding the nature of phenotypic variation in cooperative behaviour shown by natural strains in interactions with other strains. We derived a theoretical model (the "Collective Investment" game) to generate quantitative predictions for patterns of cooperation in response to group composition. We then tested these predictions by experimentally manipulating relatedness (genotype frequencies) in mixed cooperative aggregations of D.discoideum . Measurements of stalk investment by natural strains correspond to the predicted patterns of relatedness-dependent strategic investment, wherein investment by a strain increases with its relatedness to the group. These findings demonstrate 5 that simple organisms like are not restricted to being "cheaters" or "cooperators" but instead measure their relatedness to their group and strategically modulate their investment into cooperation accordingly. Consequently, all individuals will sometimes appear to cooperate and sometimes cheat due to the dynamics of strategic investing. D. discoideum JL de Oliveira, AC Morales, B Stewart, N Gruenheit, J Engelmoer, S Battom Brown, RA de Brito, LD Hurst, AO Urrutia, CRL Thompson, JB Wolf (2019) The Red King process explains molecular evolution of social genes in a microbe Nature Communications, doi.org/10.1038/s41467-019-11237-2 Here we addressed the impact of social behaviour on signatures of selection on social and nonsocial genes. We analysed the genome-wide impact of social interactions using genome sequences from a subset of 67 Dictyostelium discoideum strains sequenced under this project. We find that social genes tend to exhibit enhanced polymorphism and accelerated evolution. However, these patterns are not consistent with conflict driven processes, but instead reflect relaxed purifying selection. This pattern is most likely explained by the conditional nature of social interactions, whereby selection on genes expressed only in social interactions is diluted by generations of inactivity. This dilution of selection by inactivity enhances the role of drift, leading to increased polymorphism and accelerated evolution, which we call the Red King process. Unpublished findings in submission: Processes shaping synonymous codon use in an extremely AT-biased genome This work furthers our objective of understanding processes shaping variation in the genome. Using the genome sequence data generate by this project in conjunction with the reference genome we addressed whether deviations from equal synonymous codon usage reflect selection to optimize expression or simply 'background' processes shaping nucleotide composition. Because D. discoideum is such a highly AT-biased eukaryotic genome, it allowed us to disentangle these effects by modelling the expected distributions of synonymous codons under mutation-drift balance (estimated from our sequence data). We find that mutation bias explains a striking 88% of variation in codon usage bias. However, after accounting for this effect we identified 'preferred' codons shaped by selection, whose usage increases with expression levels and among genes evolving under stronger selective constraints. Optimization of expression seems to be addressed mostly (but weakly) by shaping levels of transcript stability. This pattern suggests a role of selection to counterpoise the strong mutational bias. Amino acid composition is influenced by evolutionary processes shaping genomic and metabolic features in a microbe Natural selection shapes the sequence of amino acids in proteins to optimize protein function in the face of constraints (e.g., relative costs or availability of different amino acids, transcription efficiency, translation speed etc). These adaptive processes interact with random background processes (mutation and random drift) to yield the observed patterns of amino acid use we observe in the genome. Understanding the relative importance of these adaptive and non-adaptive factors can provide important insights into the composition of proteins. However, in many systems it can be difficult to disentangle their influence. Here we exploit the extremely biased nucleotide composition of the D. discoideum genome to reveal the relative importance of these factors. We find that mutational bias is the largest driver of amino acid composition, but once accounted for, we uncover the underlying influence of metabolic costs. The impact of mutational bias declines rapidly with the level of gene expression, presumably reflecting the increased importance of protein optimization (with amino acid composition depending on the distinct peculiarities of individual proteins), while the importance of cost minimization increases. These findings highlight the importance of including contextual information on the study of protein evolution, rather than viewing a protein as an isolated entity. The not-so-tragic commons in a microbe We extended our work on understanding patterns of cooperation across different social conditions by characterising how collective levels of cooperation change in response to declining relatedness in groups. We find that groups suffer from the tragedy of the commons when they do not contain any strain with high relatedness to the group, which closely matches the predictions from our theoretical analysis of the scenario. However, we also find that there are genetic constraints that prevent strains from showing optimal social behaviour, which diminishes the degree to which they suffer from the worst possible tragedy of the commons. |
| Exploitation Route | These finding represent a new way of looking at the stabilisation of cooperation |
| Sectors | Education,Environment,Healthcare |
| URL | https://thethompsonlab.wordpress.com |
| Title | Dictyostelium strains and plasmids |
| Description | Dictyostelium strains and plasmids which will be used to study P2X receptor function |
| Type Of Material | Biological samples |
| Year Produced | 2011 |
| Provided To Others? | Yes |
| Impact | New ways to think about P2X receptor regulataion |
| 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 functional genomics, next generation sequencing, ChIP-seq, and bioinformatics, mutation analysis |
| 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 |