Introduction
More than 28% of the 150,388 species on the Red List of the International Union for Conservation of Nature (IUCN) are threatened with extinction . A relatively small subset of these species are kept as “insurance populations” in zoos . However, given their often-small effective population size, the long-term viability of captive-bred populations is not guaranteed, and many show signs of inbreeding depression . Deleterious mutations create harmful genetic variants in the genome, collectively known as genetic load . High genetic load can compromise population viability and recovery potential of species, especially if they experienced a recent population size decline . In declining populations, the impact of genetic load on fitness is not immediately apparent. It can take many generations before the harmful effects of mutations become expressed in homozygous loci . Consequently, the long-term viability of many zoo populations could be at risk, despite individuals and populations thriving now.
In the past 50 years, conservation geneticists have focused on maintaining genetic variation as genome-wide diversity generally correlates positively with fitness and adaptive potential , but see . Recently, the Group on Earth Observations Biodiversity Observation Network (GEO BON) developed Essential Biodiversity Variables (EBVs) to assess spatiotemporal variation in biodiversity, and proposed four genetic EBVs: genetic diversity, genetic differentiation, inbreeding, and effective population size (N e) . Notably, risks posed by genetic load are generally not considered a conservation priority . This may be an oversight. However, recent advances in genomics and bioinformatics could change that.
Leveraging the extensive genomic research on human and model animals enables us to estimate the potential fitness impact of mutations in species of conservation concern . The fitness impact of deleterious alleles can be estimated by the Combined Annotation-Dependent Depletion (CADD) framework . Initially developed in humans , CADD has been successfully applied to other model organisms, including mouse , pig , and chicken . CADD ranks genetic variants such as single nucleotide polymorphisms (SNPs) and insertions and deletions (indels) throughout the genome. This analysis integrates surrounding sequence context, gene model annotation, evolutionary constraints (e.g., GERP scores), epigenetic measurements, and functional predictions into CADD scores. CADD was employed to investigate conserved elements into the chicken Combined Annotation-Dependent Depletion (chCADD) , and has helped identify regions within the chicken genome associated with known genetic disorders reported in the Online Mendelian Inheritance in Animals (OMIA). Therefore, by identifying deleterious alleles, CADD can estimate the genetic load within an individual’s genome.
Presently, we cannot translate the impact scores of mutations such as CADD into fitness effects. Nevertheless, we can calculate CADD scores for all deleterious mutations present in an individual’s genome and compare this proxy of the genetic load between individuals. Similarly, we can estimate the proportion of genetic load expressed as realised load, and the proportion whose fitness effects remains masked as an inbreeding load or masked load . The realised load comprises the genetic load that reduces fitness when the harmful effect of the mutations come to light. Inbreeding increases the realised load because more deleterious mutations become fully expressed as homozygous. By minimising realised load, conservation managers can reduce inbreeding depression. This could be particularly useful in captive-bred populations where breeding pairs can be manipulated to improve the fitness of offspring.
Considerable amount of genetic variation codes for polygenic or quantitative traits. Mutations that affect the value of a quantitative trait (e.g., body size) can be harmful of beneficial depending on whether it brings the trait value closer to the optimum. In contrast, unconditionally deleterious mutations are harmful irrespective of genetic background or environmental conditions. Mutations in ultraconserved elements (UCEs) are likely to be unconditionally deleterious , thereby contributing substantially to the genetic load. UCEs are areas of the genome phylogenetically conserved across diverged taxa . Their high level of sequence conservation is thought to be maintained by strong purifying selection . Some polymorphisms in UCEs are associated with genetic diseases or phenotypic traits , with UCEs being linked to enhancers in early development in both mammals and flies . Given their high level of phylogenetic conservation, comparative genomic approaches can be used to obtain a proxy of the genetic load, building on the knowledge of model organisms and humans. Studying UCEs in reference genomes allows for between-species comparisons of the proxies of genetic load, realised load and masked load. Additionally, analysis of genetic load at UCEs shows promise for captive breeding and conservation management of zoo populations.
Here, we conduct a proof-of-concept study to demonstrate the utility of genomics-informed breeding in the conservation management of captive populations. We quantify the genetic load of six pink pigeon individuals using chCADD scores assigned to single nucleotide variants in the UCEs derived from the chicken genome. We show that genetic load components can be estimated using CADD scores calculated on a phylogenetic closely related species and cross-mapped to the annotation of the pink pigeon, our focal species. We also calculate realised load and genetic load of potential future offspring of all possible crosses. Finally, we employ computer simulations to demonstrate the potential of genomics-informed conservation, showing how it can help to reduce inbreeding depression and maximise the long-term viability of zoo populations.