Abstract
Zoo populations of threatened species are a valuable resource for the
restoration of wild populations. However, their small effective
population size poses a risk to long-term viability, especially in
species with high genetic load. Recent bioinformatic developments can
identify harmful genetic variants in genome data. Here, we advance this
approach, analysing the genetic load in the threatened pink pigeon(Nesoenas mayeri) . We lift-over the mutation-impact scores that
had been calculated for the chicken (Gallus gallus ) to estimate
the genetic load in six pink pigeons. Additionally, we performin-silico crossings to predict the genetic load and realised load
of potential offspring. We thus identify the optimal mate pairs that are
theoretically expected to reproduce offspring with the least inbreeding
depression. We use computer simulations to show how genomics-informed
conservation can reduce the genetic load and maintain genome-wide
diversity, arguing this will become instrumental in maintaining the
long-term viability of zoo populations.