Discussion
We conducted a proof-of-concept study to evaluate the utility of genomics-informed conservation for the management of captive populations in zoos. Our aim was to examine whether we could use genomic data to reduce the level of inbreeding depression and genetic load, thereby increasing both the short- and long-term population viability. We developed a novel bioinformatics pipeline to estimate the genetic load using CADD sores calculated for a model species (the chicken). We piloted our bioinformatics pipeline on the genomes of six pink pigeons from the captive-bred population from two UK zoos (Jersey Zoo and Bristol Zoo). We quantified realised load in hypothetical offspring by crossing these six individuals, showing that inbreeding depression may be reduced in the captive pink pigeon population. We furthermore found that UCEs possess the most severely deleterious mutations with highest CADD scores, and that mutations in UCEs occur at a lower SNP density and frequency compared to polymorphisms in the flanking regions. These observations are consistent with purifying selection.
Substantial genetic drift and inbreeding in zoo populations reduces long-term viability. Since the early 1970s, conservation biologists have used pedigrees and neutral genetic markers to assess and minimise inbreeding . However, genetic load cannot be effectively measured or managed using this approach because neither markers nor pedigrees contain information about the segregation of deleterious mutations. Furthermore, pedigree data does not capture the possible relatedness between founder individuals. This can be especially problematic in populations that experienced a bottleneck before being sampled.
We showed our bioinformatics pipeline can identify optimal crosses that produce offspring with on average 7.4% lower realised load than random crosses. These offspring are expected to show less inbreeding depression. This reduction in realised load was modest because after nearly 10 generations in captivity, all pink pigeon individuals are relatively related. Crosses between closely related individuals have been minimised in the captive management of this species by exchanging pigeons between different zoos. However, this means that all individuals are similarly related. More substantial gains can be made in reducing the realised load using genomics-informed breeding in zoo populations with individuals that are less closely related. Genomics-informed breeding will be especially efficient in reducing inbreeding depression in captive populations founded by many individuals, fewer generations in captivity, non-bottlenecked species, and species with a large ancestral population size . These are all scenarios of populations that are likely to possess a high genetic load of segregating deleterious mutations not yet purged ,with considerable differences between individuals.
We do not know how CADD scores translate in fitness effects, and hence, we cannot calculate the exact benefits of genomics-informed breeding for survival rates. If a population carries a realised load of one lethal equivalent (LE), a reduction of 7.4% in realised load results in an increase of survival rate from 36.8% to 39.6%. This is a 7.7% relative increase. With a higher realise load of 2 LEs, the survival rate improves from 13.5% to 15.7%, which amounts to a relative increase of nearly 16%. More generally, reducing the realised load is likely to reduce inbreeding depression and increase fitness .
Our simulations indicate that the genetic load and realised load can be reduced by the “Minimised load regime” and the “Minimised load and relatedness regime”. This resulted in a substantial increase in fitness compared to the “Random mating regime”, and the “Minimised relatedness regime”. Although the “Minimised load regime” resulted in a substantial loss in nucleotide diversity, this was avoided by reducing relatedness in the “Minimised load and relatedness regime”. Theoretically, this regime is the optimal approach to maximise the long-term viability of captive populations, both in terms of reduced genetic load and increased adaptive potential.
To conclude, CADD scores for model species can be successfully lifted over to provide an initial assessment of the genetic load from whole genome sequence data of non-model species. Optimal mate pairs can be identified to reduce the realised load and inbreeding depression in the offspring generation. Computer simulations show that genomics-informed breeding can reduce the genetic load and realised load, and this can be accomplished without significantly reducing nucleotide diversity in the population. Genomics-informed management can increase the long-term viability of captive populations and help to select the optimal individuals for reintroduction and genetic rescue programs.