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 perform in-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.