Genomics-informed captive breeding can reduce inbreeding depression and the genetic load in zoo populations

What Can Genome Sequence Data Reveal About Population Viability?

Biologists have long sought to understand the impacts of deleterious genetic variation on fitness and population viability. However, our understanding of these effects in the wild is incomplete, in part due to the rarity of sufficient genetic and demographic data needed to measure their impact. The genomics revolution is promising a potential solution by predicting the effects of deleterious genetic variants (genetic load) bioinformatically from genome sequences alone bypassing the need for costly demographic data. After a historical perspective on the theoretical and empirical basis of our understanding of the dynamics and fitness effects of deleterious genetic variation, we evaluate the potential for these new genomic measures of genetic load to predict population viability. We argue that current genomic analyses alone cannot reliably predict the effects of deleterious genetic variation on population growth, because these depend on demographic, ecological and genetic parameters that need more than just genome sequence data to be measured. Thus, while purely genomic analyses of genetic load promise to improve our understanding of the composition of the genetic load, they are currently of little use for evaluating population viability. Demographic data and ecological context remain crucial to our understanding of the consequences of deleterious genetic variation for population fitness. However, when combined with such demographic and ecological data, genomic information can offer important insights into genetic variation and inbreeding that are crucial for conservation decision making.

Sonification of Genomic Data to Represent Genetic Load in Zoo Populations

Maintaining a diverse gene pool is important in the captive management of zoo populations, especially in endangered species such as the pink pigeon (Nesoenas mayeri). However, due to the limited number of breeding individuals and relaxed natural selection, the loss of variation and accumulation of harmful variants is inevitable. Inbreeding results in a loss of fitness (i.e., inbreeding depression), principally because related parents are more likely to transmit a copy of the same recessive deleterious genetic variant to their offspring. Genomics-informed captive breeding can manage harmful variants by artificial selection, reducing the genetic load by avoiding the inheritance of two copies of the same harmful variant. To explain this concept in an interactive way to zoo visitors, we developed a sonification game to represent the fitness impacts of harmful variants by detuning notes in a familiar musical melody (i.e., Beethoven's Für Elise). Conceptually, zoo visitors play a game aiming to create the most optimal pink pigeon offspring in terms of inbreeding depression. They select virtual crosses between pink pigeon individuals and listen for the detuning of the melody, which represents the realised load of the resultant offspring. Here we present the sonification algorithm and the results of an online survey to see whether participants could identify the most and least optimal offspring from three potential pink pigeon offspring. Of our 98 respondents, 85 (86.7%) correctly identified the least optimal offspring, 73 (74.5%) correctly identified the most optimal, and 62 (63.3%) identified both the most and least optimal offspring using only the sonification.

Leveraging genomic load estimates to optimize captive breeding programmes

Rapid biodiversity loss threatens many species with extinction. Captive populations of species of conservation concern (such as those housed in zoos and dedicated breeding centres) act as an insurance should wild populations go extinct or need supplemental individuals to boost populations. Limited resources mean that captive populations are almost always small and started from few founding individuals. As a result, captive populations require careful management to minimize negative genetic impacts, with decisions about which individuals to breed together often guided by the principle of minimizing relatedness. Typically this strategy aims to retain 90% of genetic diversity over 200 years (Soulé et al., Zoo Biology, 1986, 5, 101), but it has a weakness in that it does not directly manage for genetic load. In this issue of Molecular Ecology Resources, Speak et al. (Molecular Ecology Resources, 2024, e13967) present a novel proof-of-concept study for taking this next step and incorporating estimates of individual genetic load into the planning of captive breeding, using an approach that is likely to be widely applicable to many captive populations.