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Bilateral BBSRC-FAPESP: The genetic architecture and evolution of pleiotropy associated with evolutionary changes in developmental trajectories

Reference	BB/L002604/1
Principal Investigator / Supervisor	Professor Jason Wolf
Co-Investigators / Co-Supervisors	Professor John Hunt, Professor Andrew Ward
Institution	University of Bath
Department	Biology and Biochemistry
Funding type	Research
Value (£)	476,160
Status	Completed
Type	Research Grant
Start date	13/01/2014
End date	12/01/2017
Duration	36 months

Abstract

Individuals are composed of suites of traits that arise from a common genome through shared developmental processes that together determine their fitness. This is particularly true for the complex multidimensional traits found in higher organisms, where trait expression is determined by factors acting across the hierarchy of development. Consequently, fundamental to our understanding of the genetic basis and evolution of complex traits is the concept of pleiotropy, where a single gene affects the expression of multiple traits. Although patterns of pleiotropy have important genetic and evolutionary implications, we have a limited understanding of the genomic basis and evolution of pleiotropic effects. We propose to fundamentally advance our understanding of pleiotropy using an experimental system in which multivariate selection has been used to reshape patterns of growth and development in mice. By focusing on developmental traits we will also further our understanding of the relationship between the traits produced by the developmental system (e.g., adult morphology). To achieve our goals we will apply cutting edge computational tools to a powerful experimental population created by intercrossing mouse strains with highly divergent ontogenies. Using these tools we will map molecular variation to multidimensional phenotypic variation to achieve the following objectives. 1) Characterize the patterns of pleiotropic effects associated with evolutionary changes in ontogeny 2) Examine whether there are constraints on patterns of pleiotropic effects 3) Determine the role that context-dependent pleiotropic effects played in shaping patterns of multivariate evolution 4) Examine the contribution of maternal effects to the evolution of growth trajectories and patterns of pleiotropy, 5) Understand how ontogenetic changes impact patterns of pleiotropy among adult traits, 6) Determine the contribution of genomic imprinting to patterns of pleiotropy.

Summary

Understanding how the genome makes the traits we observe in individuals (i.e., their 'phenotype') is perhaps the most fundamental problem in biology. Achieving such an understanding has been challenging because there are many pathways from the genome to the traits we observe, and those traits themselves can be complex and 'multidimensional', being made up of suites of traits that are tied together through the shared process of development controlled by a shared genome. The shared genomic and developmental bases generally contribute to associations between traits, where the expression of one trait is correlated to the expression of other traits. Such associations between traits play a major role in evolutionary processes because they make the evolutionary fate of one trait tied to the fate of other traits. Furthermore, the success of an individual (i.e., their 'Darwinian fitness') is a product of all of their traits, operating in concert, and hence natural selection can favour particular combinations of traits and thereby shape the relationship between traits. We propose to examine the genetic basis and evolution of these associations between traits by studying populations of mice that have evolved differences in their patterns of growth in response to artificial selection (selective breeding for different growth patterns). The eight populations we are focusing on were generated by four different patterns of artificial selection that altered their rate of growth early and late in postnatal development. This resulted in a series of growth patterns that are novel and the relationship between early and late growth is different to the pattern seen in the starting generation. To understand how selection has changed the relationship between growth traits, and how these changes in development, in turn, alter the nature of variation seen at the endpoint of development in adult traits, we will mix the genomes of populations from these eight selection lines. Using this mixed population, we will ask 'how having inherited regions of the genome from these evolutionarily divergent populations allowed patterns of growth to become 'reshaped' by selection?'. We will look at the overall patterns of how these genomic regions 'map' to phenotypes (i.e., how they influence the overall pattern of traits expressed by individuals) as well as complex interactions between regions of the genome that together determine the pattern of growth and patterns of variation in complex adult phenotypes. We will also ask 'what role have changes in maternal traits played in altering patterns of growth in their offspring?'. We already know that something has changed in the way that mothers influence the growth of their offspring, but we do not know whether changes in these maternal influences led to evolutionary changes in the direction favoured by selection or whether they contributed 'maladaptive' changes opposing the direction favoured by selection. We will integrate all of the information we accumulate on how genomes build the traits we observe to develop a better understanding of how evolution proceeds at the molecular level, and how these genetic changes allowed selection to reshape patterns of growth and development. We will then link these developmental changes to the patterns of variation produced as the output of development in adults to understand how shifting growth patterns impacts the patterns of genetic variation that are produced as the output of the developmental process.

Impact Summary

1. Beneficiaries: Academic: Because the proposed research is targeted at a core question in genetics and evolutionary biology one of the primary stakeholders is the academic community of geneticists and evolutionary biologists. The project also includes core concepts related to animal development and epigenetics and therefore can contribute to the building of unifying concepts in developmental biology and evolutionary genetics. Agricultural: The founding principles of the proposed research originally emerged from selective breeding programs for plant and animal improvement. This community remains interested in the general questions we are working on and will, therefore, benefit from the results of our research. Enhancing International Collaboration: This project will strengthen UK science by developing collaborative research with the Brazilian co-investigator, through the FAPESP joint funding, and the American Project Partner. It will also help further strengthen ties to the developing research community in Brazil through the Pathways to Impact activities. General Public: How selection leads to evolutionary change is of interested to the general public and our research could provide interesting new insights to this problem. 2. Implementation: Dissemination: To reach academic beneficiaries outside our field we will submit a synthetic review on genetic constraints in multivariate evolution, focused on selective breeding programs, to a high profile journal in agricultural genetics (e.g., Crop Science, Animal Genetics). Research training: We will train the PDRAs and RA in cutting edge quantitative skills such as maximum likelihood mixed modelling, computer simulation, analytical modelling and data manipulation. The RA will be trained in experimental design and management of large projects. Advanced training resources: A) Evolutionary quantitative and population genetics course: We will generate impact and added value through educational resources in quantitativeand population genetics. To achieve this goal, we will deliver a three day short course at the University of Bath targeted at evolutionary biologists and quantitative geneticists. 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 and quantitative genetics is an emerging discipline. To achieve this goal, we are coordinating with Prof R. de Brito from the Federal University of São Carlos. São Carlos is home to two major units of the Brazilian Agricultural Research Corporation, and we will work with these units to bring the impact to the agricultural research community in Brazil. B) Agricultural genetics: The resources from the short course will be the basis of a training module aimed at agricultural researchers. We will engage with the Royal Agricultural Society of England to disseminate these materials and training resources. Concepts will be focused on cutting edge ideas in quantitative genetics. Most notably will be the theory on how traits respond to selection for multiple objectives and how genetic architecture interacts with the selection regime to produce observed changes in target traits. This will directly connect the conceptual basis for the project to the end user community using these approaches for economic improvement. This impact will also work towards the basic problems of food security and animal welfare. C) 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 to provide outputs to the general media. To improve our outreach the PDRA will participate in the BBSRC Media Training course and the Royal Society Communication Skills Course.

Committee	Research Committee C (Genes, development and STEM approaches to biology)
Research Topics	Systems Biology
Research Priority	X – Research Priority information not available
Research Initiative	BBSRC-Brazil (FAPESP) joint funding of research [2010-2015]
Funding Scheme	X – not Funded via a specific Funding Scheme

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