Distinguishing the victim from the threat: SNP‐based methods reveal the extent of introgressive hybridization between wildcats and domestic cats in Scotland and inform future in situ and ex situ management options for species restoration - NMS Research Repository
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Distinguishing the victim from the threat: SNP‐based methods reveal the extent of introgressive hybridization between wildcats and domestic cats in Scotland and inform future in situ and ex situ management options for species restoration

Abstract

The degree of introgressive hybridization between the Scottish wildcat and domestic cat has long been suspected to be advanced. Here, we use a 35‐SNP‐marker test, designed to assess hybridization between wildcat and domestic cat populations in Scotland, to assess a database of 295 wild‐living and captive cat samples, and test the assumptions of the test using 3,097 SNP markers generated independently in a subset of the data using ddRAD. We discovered that despite increased genetic resolution provided by these methods, wild‐living cats in Scotland show a complete genetic continuum or hybrid swarm structure when judged against reference data. The historical population of wildcats, although hybridized, clearly groups at one end of this continuum, as does the captive population of wildcats. The interpretation of pelage scores against nuclear genetic data continues to be problematic. This is probably because of a breakdown in linkage equilibrium between wildcat pelage genes as the two populations have become increasingly mixed, meaning that pelage score or SNP score alone is poor diagnostic predictors of hybrid status. Until better tools become available, both should be used jointly, where possible, when making management decisions about individual cats. We recommend that the conservation community in Scotland must now define clearly what measures are to be used to diagnose a wildcat in the wild in Scotland, if future conservation action is to be effective.

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216820Distinguishing20the20victim20from20threat.pdf
29 Oct 2019
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