Objectives, criteria and methods for using molecular genetic data in priority setting for conservation of animal genetic resources
Boettcher, Paul J. | Tixier-Boichard, M. | Toro, M. A. | Simianer, H. | Eding, H. | Gandini, G. | Joost, S. | García, D. | Colli, L. | Ajmone-Marsan, P. | Boettcher, Paul J. [0000-0003-2030-1313]
The genetic diversity of the world's livestock populations is decreasing, both within and across breeds. A wide variety of factors has contributed to the loss, replacement or genetic dilution of many local breeds. Genetic variability within the more common commercial breeds has been greatly decreased by selectively intense breeding programmes. Conservation of livestock genetic variability is thus important, especially when considering possible future changes in production environments. The world has more than 7500 livestock breeds and conservation of all of them is not feasible. Therefore, prioritization is needed. The objective of this article is to review the state of the art in approaches for prioritization of breeds for conservation, particularly those approaches that consider molecular genetic information, and to identify any shortcomings that may restrict their application. The Weitzman method was among the first and most well-known approaches for utilization of molecular genetic information in conservation prioritization. This approach balances diversity and extinction probability to yield an objective measure of conservation potential. However, this approach was designed for decision making across species and measures diversity as distinctiveness. For livestock, prioritization will most commonly be performed among breeds within species, so alternatives that measure diversity as co-ancestry (i.e. also within-breed variability) have been proposed. Although these methods are technically sound, their application has generally been limited to research studies; most existing conservation programmes have effectively primarily based decisions on extinction risk. The development of user-friendly software incorporating these approaches may increase their rate of utilization. © 2010 International Society for Animal Genetics.
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