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.