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.