Leveraging genomic load estimates to optimize captive breeding programmes

dc.contributor.authorJensen, Evelyn L.
dc.contributor.authorGray, Rachel
dc.contributor.authorMiller, Joshua M.
dc.date.accessioned2025-05-20T21:34:28Z
dc.date.available2025-05-20T21:34:28Z
dc.date.issued2024
dc.description.abstractRapid biodiversity loss threatens many species with extinction. Captive populations of species of conservation concern (such as those housed in zoos and dedicated breeding centres) act as an insurance should wild populations go extinct or need supplemental individuals to boost populations. Limited resources mean that captive populations are almost always small and started from few founding individuals. As a result, captive populations require careful management to minimize negative genetic impacts, with decisions about which individuals to breed together often guided by the principle of minimizing relatedness. Typically this strategy aims to retain 90% of genetic diversity over 200 years (Soulé et al., Zoo Biology, 1986, 5, 101), but it has a weakness in that it does not directly manage for genetic load. In this issue of MolecularEcology Resources, Speak et al. (Molecular Ecology Resources, 2024, e13967) present a novel proof-of-concept study for taking this next step and incorporating estimates of individual genetic load into the planning of captive breeding, using an approach that is likely to be widely applicable to many captive populations.
dc.identifier.citationJensen, E. L., Gray, R., & Miller, J. M. (2024). Leveraging genomic load estimates to optimize captive breeding programmes. Molecular Ecology Resources, 24, e14007. https://doi.org/10.1111/1755-0998.14007
dc.identifier.doihttps://doi.org/10.1111/1755-0998.14007
dc.identifier.urihttps://hdl.handle.net/20.500.14078/3912
dc.language.isoen
dc.rightsAttribution (CC BY)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCADD
dc.subjectcaptive breeding
dc.subjectconservation
dc.subjectgenetic load
dc.subjectultraconserved elements
dc.titleLeveraging genomic load estimates to optimize captive breeding programmesen
dc.typeArticle

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