Genomics-informed conservation of endangered bird species in zoos

Speak, Samuel Andrew (2024) Genomics-informed conservation of endangered bird species in zoos. Doctoral thesis, University of East Anglia.

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Abstract

Globally, the biodiversity crisis threatens ~28% of species with extinction according to the Red List of the International Union for the Conservation of Nature (IUCN). Captive breeding programmes can act as insurance populations against extinction and to preserve genetic diversity. However, due to their small size, the survival of these populations is threatened by inbreeding depression resulting from high genetic load. I developed the LoadLift pipeline to assess the genetic load of individuals. LoadLift utilises Combined Annotation-Dependent Depletion (CADD) scores from model species to assess the impact of mutations and estimate the genetic load within ultraconserved elements (UCEs). Six pink pigeons (Nesoenas mayeri) were analysed with LoadLift and in silico crossings, to identify optimal mate pairings expected to show the least inbreeding depression. The CADD scores of three model species (humans, pigs and chickens) were highly comparable, giving confidence that the LoadLift approach can be applied across vertebrates. However, CADD scores cannot be summed as they represent a rank value of the predicted impact of a mutation relative to all other mutations within the genome. Hence, I converted CADD scores to selection coefficients (s) that were simulated in SLiM by aligning the rank scores of both CADD and s. LoadLift was also used to assess the genetic load of the whooping crane (Grus americana), which revealed that this species possesses a greater realised load than masked load, which is consistent with extensive inbreeding during the population bottleneck. I also compared the methods of LoadLift and SNPeff, showing good correspondence in their classifications of deleterious mutations. LoadLift enables captive-breeding managers to maintain long-term viable populations and reduce inbreeding depression. LoadLift can also be applied to assist reintroduction programmes in identifying optimal candidates to provide genetic rescue, thereby maximising the potential of ex situ populations for species conservation and restoration.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Science > School of Environmental Sciences
Depositing User:	Chris White
Date Deposited:	19 Mar 2025 09:26
Last Modified:	19 Mar 2025 09:26
URI:	https://ueaeprints.uea.ac.uk/id/eprint/98792
DOI:

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