Sonification of Genomic Data to Represent Genetic Load in Zoo Populations

Author:

Martin Edward J.1ORCID,Speak Samuel A.234,Urban Lara567ORCID,Morales Hernán E.8,van Oosterhout Cock2ORCID

Affiliation:

1. Institute of Ecology and Evolution, School of Biological Sciences University of Edinburgh Edinburgh UK

2. School of Environmental Sciences University of East Anglia, Norwich Research Park Norwich UK

3. Natural History Museum London UK

4. North of England Zoological Society Chester Zoo Chester UK

5. Helmholtz AI Helmholtz Zentrum Muenchen Neuherberg Germany

6. Helmholtz Pioneer Campus Helmholtz Zentrum Muenchen Munich Germany

7. School of Life Sciences Technical University of Munich Freising Germany

8. Center for Evolutionary Hologenomics, Globe Institute, Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark

Abstract

ABSTRACTMaintaining 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.

Publisher

Wiley

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