Related Experiment Video
Updated: Dec 29, 2025

Quantifying Fitness Costs in Transgenic Aedes aegypti Mosquitoes
Published on: September 15, 2023
Genomic-Based Optimum Contribution in Conservation and Genetic Improvement Programs with Antagonistic Fitness and
Enrique Sánchez-Molano1, Ricardo Pong-Wong1, Georgios Banos2
1Division of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh Edinburgh, UK.
Abstract:
Animal selection for genetic improvement of productivity may lead to an increase in inbreeding through the use of techniques that enhance the reproductive capability of selected animals. Therefore, breeding strategies aim to balance maintaining genetic variability and acceptable fitness levels with increasing productivity. The present study demonstrates the effectiveness of genomic-based optimum contribution strategies at addressing this objective when fitness and productivity are genetically antagonistic traits. Strategies are evaluated in directional selection (increasing productivity) or conservation (maintaining fitness) scenarios. In the former case, substantial rates of genetic gain can be achieved while greatly constraining the rate of increase in inbreeding. Under a conservation approach, inbreeding depression can be effectively halted while also achieving a modest rate of genetic gain for productivity. Furthermore, the use of optimum contribution strategies when combined with a simple non-random mating scheme (minimum kinship method) showed an additional delay in the increase of inbreeding in the short term. In conclusion, genomic-based optimum contribution methods can be effectively used to control inbreeding and inbreeding depression, and still allow genetic gain for productivity traits even when fitness and productivity are antagonistically correlated.
More Related Videos
Related Concept Videos
Inclusive Fitness
Limits to Natural Selection
Genetics of Speciation
Mutation, Gene Flow, and Genetic Drift
Plant Breeding and Biotechnology
What is Population Genetics?

