Selection Footprints and Mapping

Lead Research Organisation: University of Edinburgh
Department Name: UNLISTED

Abstract

The research funded by this grant explores a relatively new approach to gene mapping. The selection (or hitchhiking) mapping approach exploits the fact that genetic diversity will be reduced near a gene under strong selection, due to statistical associations that develop along a chromosome. The recent increase in availability of genetic diversity data, due to technical improvements and reductions in cost of genome-wide sequencing, have made such techniques feasible. So far, this approach has primarily been applied to human data sets, with the goal of understanding the selective processes that have acted on the human genome over the course of evolution. An important issue is that while there has been a large effort applied to data generation and analysis (including the publication of some controversial conclusions regarding human evolution), the power and limitations of this approach have not been seriously addressed by researchers. The importance of our work is that it focuses on genes for which there is strong historical evidence of selection, allowing us to characterize the diversity patterns generated by selection. In most wild species and humans, this would not be possible since it is rare that a gene or genetic region is definitely known to have been under selection. However, in domesticated species, where the selection pressure has been strong and often on well-defined traits, there are more opportunities for implementation of this approach to identify genes related to the domestication process. This research has examined the diversity patterns at neutral markers in the region of three cattle genes with strong evidence of selection as well as for simulated genotypic data, generated under specific selection regimes.

Publications

10 25 50
 
Description The major finding was that the regression method developed in the project was able to detect the positive selection near the selected genes and furthermore was able to detect new putative QTL. However the regression methodology proved relatively sensitive to the variability of the markers in the dataset. The greatest power of detection of the selection footprint was shown to be when the favoured allele had reached high frequency and had moved beyond intermediate frequencies.
Exploitation Route In evolutionary studies and, in livestock, understanding the functional consequences of domestication, and recent natural and artificial selection.
Sectors Agriculture, Food and Drink

 
Description The development of new software to identify segments of DNA that can be used directly for genetic improvement or the removal of deleterious effects by breeding organisations.
First Year Of Impact 2013
Sector Agriculture, Food and Drink
Impact Types Societal,Economic

 
Description Membership of Drafting Group for UK Country Report on Farm Animal Genetic Resources, 2002
Geographic Reach National 
Policy Influence Type Membership of a guideline committee
Impact UK Country Report on Farm Animal Genetic Resources 2002. This was the first time this policy area was addressed and formed an international report to FAO.
URL https://www.gov.uk/government/publications/uk-country-report-on-farm-animal-genetic-resources-2002
 
Description INIA 
Organisation National Institute for Agricultural and Food Research and Technology
Country Spain 
Sector Public 
PI Contribution Training, design and interpretation of studies, writing papers for journals
Collaborator Contribution Personnel, funding for personnel, scientific discussion, writing papers.
Impact Scientific papers. New PhDs and trained post-docs in Spain.
Start Year 2008
 
Description Norwegian University of Life Sciences (NMBU), Aas, Norway 
Organisation Norwegian University of Life Sciences (NMBU)
Country Norway 
Sector Academic/University 
PI Contribution Supervised and lectured to postgraduate students. Provided intellectual input into science proposals, ongoing projects and outputs, including research papers.
Collaborator Contribution Facilities, students, intellectual stimulation, new project ideas, data, and other academic outputs such as scientific papers.
Impact Joint scientific papers. Joint scientific projects (UoE/NMBU).
 
Description University of Leon 
Organisation University of Leon
Country Spain 
Sector Academic/University 
PI Contribution Training, design and interpretation of studies.
Collaborator Contribution Personel. Funding for personnel.
Impact Training, papers, new PhDs.
Start Year 2008