Domestic animals as a model to understand the relationship between deleterious mutations, demography and disease (360G-Wellcome-210119_Z_18_Z)

£80,175

Most mutations have mildly to strongly harmful effects. In extreme cases, where populations experience acute demographic and selection processes, deleterious mutations implicated in both infectious and genetic disease can accumulate in the genome to impose a significant burden (a measure known as mutational load). Domestic animals provide such an extreme case because of their complex evolutionary history, marked by bottlenecks, population expansions and relaxed selection. They are thus an ideal model to investigate how different mechanisms contribute to mutational load. Recent relaxed selection (e.g. via antibiotics and vaccination) and dramatic population expansion likely increased disease transmission and the frequency of deleterious genetic variations throughout the genome, including in immune genes. Investigating these processes in domestic animals is therefore critical for human health because these species are a major source of zoonotic diseases (e.g. bird/swine flu). Using simulations, ancient and modern genomes, and transfection experiments, this project will: 1) develop computational methods to disentangle contributions from different mechanisms, such as population bottlenecks and positive or relaxed selection, towards increases in mutational load; 2) generate preliminary data and establish laboratory techniques to test the hypothesis that recent relaxed selection has had an impact on the immune capabilities of domestic animals.

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Grant Details

Amount Awarded 80175
Applicant Surname Frantz
Approval Committee Science Seeds Advisory Panel
Award Date 2017-12-04T00:00:00+00:00
Financial Year 2017/18
Grant Programme: Title Seed Award in Science
Internal ID 210119/Z/18/Z
Lead Applicant Dr Laurent Frantz
Partnership Value 80175
Planned Dates: End Date 2021-02-15T00:00:00+00:00
Planned Dates: Start Date 2018-08-19T00:00:00+00:00
Recipient Org: Country United Kingdom
Region Greater London