Genomic approaches to inference of population history and multispecies community assembly

Relationships between species, and between populations within species, have long been likened to branches in a tree - Darwin's own notes include a well-known example. Since the development of DNA sequencing, methods have been developed that allow reconstruction of historical relationships among populations from sequence. Understanding of historical relationships among populations (which includes both the splitting of ancestral populations into daughter populations, and dispersal of individuals between populations) is important in many areas of biology, including where and when our own species evolved. In conservation biology, reconstruction of population history allows us to identify where species are likely to have their greatest genetic diversity (so we know where to concentrate conservation efforts), which populations are connected by migration (and so may support each other) and which are isolated (and so at higher risk of extinction). More generally, inferring population relationships is also essential if we want to correctly understand how populations are responding to natural selection.

Population history is usually inferred using data for only a small number of genes (usually 5 or less), sampled in lots of individuals. A major reason for this has been the difficulty in getting sequence data for more genes, and a belief that sampling of many individuals is necessary to understand what is going on. Recent major advances have changed this view. First, there has been a quantum leap in availability of sequence data through development of new "nextgen" sequencing technologies, able to generate data for thousands of genes across the genome of any species. Second, advances in coalescent theory show that it is much better to sample many genes in a small number of individuals than vice versa (the common practice). This is exciting because it means we can work even with rare animals for which sampling of many individuals is unwelcome or impossible. However, the sheer size of genomic datasets makes it difficult or impossible to analyse them with available methods. A major aim of this project is the development of better tools for inference of population history from genomic datasets, which will be made available on the web for all to use.

We will then apply our new tools to real data for two natural insect communities (European oak galls and eastern Australian figs), each of which comprises herbivores and their parasitoid wasp natural enemies. By comparing population histories across species in each community, we will test whether herbivores and parasitoids spread together through space and time, or joined their communities over a range of timescales. This is a major area of current research in ecology that matters because long associations between species commonly result in strong ecological dependence, and disruptions of such interactions (for example through human-imposed habitat change) can be very hard to restore. We will also test the more specific hypothesis that herbivores can escape their natural enemies for a while, and so enjoy a measure of 'enemy-free time'. We choose these in part because of their importance as model systems in the study of multispecies interactions, and in part because an aspect of the genetics of all the insect species involved (presence of a single set of chromosomes in males) makes it particularly easy to generate and analyse genomic datasets for them. And while this example focuses on a biodiversity-related issue, the methods we will develop can be applied equally to more applied associations, such as those between humankind and their parasites.

Ability to extract information from small numbers of individuals provides enormous potential to make better use of existing samples, or minimise impact on rare species. These opportunities will be discussed with stakeholders at 3 supported workshops through the project, and communicated to school teachers in a supported SSERC summer school.

Broader applications of our research: Our research will improve the ways in which genetic information can be used to reveal history of, and dispersal between, populations of any organism. These properties of populations are usually difficult or impossible to measure directly, but knowledge of them is important outside academic science in two general sorts of application. By improving accuracy in estimation of population properties, we hope to contribute to both. Furthermore, the methods we develop will allow accurate inference of population history from much smaller numbers of individuals, facilitating work on rare species or on taxa that are expensive or difficult to collect.

Our impact strategy centers on communicating the relative merits of a population genomic approach to stakeholders (via workshops and a website linked through to our software) and to the general public (via a SSERC summer school for secondary school teachers, taught by the PI).

1. Interacting with stakeholders. Sampling using genomes for small numbers of individuals has potential benefits in a wide range of fields, including conservation genetics (Edinburgh Zoo, Royal Botanic Garden Edinburgh, Scottish Natural Heritage, English Nature, RSPB), management of crop populations (DEFRA, Scottish Agricultural College, Science Advice for Scottish Agriculture - SASA), and understanding of invasive species (SASA, DEFRA). While the aims of our proposal are driven by advances in technology and scientific advance, the questions these agencies need to answer should also influence the way we explore and report population genomic research. We will therefore organise 3 supported workshops in Edinburgh during the lifetime of the project.

Workshops 1 and 2, will involve a focus group of 10 representatives from Scottish institutions representing the stakeholder spectrum. Workshop 1 will communicate the potential of the approach, and provide materials for the representatives to take back to their institutions to invite feedback. This will be discussed by the same group at the second meeting. Wherever possible, requirements specific to stakeholder needs will be incorporated into the inference methods we develop, maximising their relevance to a diversity of end users. We will discuss how best to communicate essential elements of population genomics to stakeholders via a website linked to software outputs of the project. This resource will be developed with the outreach expertise of Edinburgh Beltane Beacons for Public Engagement project.

Workshop 3, at completion of the project, will invite 20 representatives from a broader range of national stakeholder groups. We will present our findings and (using feedback from the focus group) outline how the tools we develop can be usefully applied. Feedback from the meeting will be used in design and content of the web site interface. We hope in this way to maximize impact on policy.

2. Public outreach via schools. The most effective way to reach school children is by inspiring their teachers to bring contemporary science into the classroom.We will communicate the excitement and potential of genomics research to school teachers in Scotland via a supported summer school. The SSERC (Scottish Schools Education Research Centre) runs summer schools that provide CPD (continuing professional development) for teachers. They are advising on ongoing development of a new schools Curriculum for Excellence, which includes a section on 'Topical Science in Scotland and beyond'. We propose to work with SSERC to design a supported summer school module on genomics to be taught by the PI and Co-I's. With SSERC, we will design a powerpoint teaching session resource (available at the website described in 1.) designed for advanced higher/A level school teaching.

We will engage with the public and other stakeholders via science outreach activities at Edinburgh University (Doors Open Day, Edinburgh International Science Festival) each year.