Optimising the Use of Cryopreserved Genetic Resources for the Selection and Conservation of Animal Populations

Abstract

Genetic diversity is essential for the sustainability and adaptability of populations, and is thus a central pillar of the agro-ecological transition. However, within a population, it is inevitable that some amount of genetic variability is lost, and efforts must be made to limit this as much as possible. A valuable tool in this endeavour could be the use of cryopreserved genetic resources in cryobanks, which could assist in the management of various animal populations in the contexts of both selection and conservation. We performed simulations that revealed that the most appropriate use of ex situ genetic resources depends on characteristics of the target population and its management objectives. For populations under conservation, the aim is to maintain genetic diversity, which was best achieved by the regular use of cryopreserved genetic resources at each generation. For populations under selection, instead, the concern is the addition of additive genetic variability, which benefited from the use of cryopreserved collections over only a few generations based primarily on the genetic values of donors. The use of cryopreserved semen had a beneficial effect when breeding objectives were changed. In both cases, the use of cryopreserved individuals in animal populations requires a large amount of reproductive material: for breeds under selection because the number of offspring is high, and for breeds under conservation because the frozen semen is used repeatedly over a long period. The use of cryopreserved material appears to be an effective means of managing the genetic variability of an animal population, either by slowing down the erosion of variability or by helping to redirect a selection objective. However, care must be taken with populations under selection to limit the disadvantages associated with the reintroduction of old genetic material, in particular the gap in breeding values for traits of interest. Finally, our study highlights the need for a sufficiently large stock of cryopreserved material in collections (e.g., number of doses, straws) to ensure the most efficient use.

Keywords: animal populations; ex situ conservation; gene bank; genetic diversity; simulations.

FIGURE 1

Breeding steps of simulations. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 2

Breeding steps for the burn‐in phase for populations under selection or conservation. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 3

Number of offspring of cryopreserved individuals across generations in the conservation programs. The x‐axis corresponds to the genealogical rank of individuals in relation to their ancestors from the ex situ collections (i.e., rank 1 for children, rank 2 for grandchildren, rank 3 for great‐grandchildren, etc.). The random mating scenario (rm) is represented in black and the scenario which maximises the genetic diversity (max_GD) is represented in blue. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 4

Evolution of average kinship across generations within populations in the conservation scenarios. The solid and dashed lines represent results without and with the use of ex situ collections, respectively. The random mating scenario (rm) is represented in black and the scenario which maximises the genetic diversity (max_GD) is represented in blue. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 5

Measurements of genetic diversity for scenarios of conservation populations. In black, scenario with random mating (rm). In blue, scenario maximising genetic diversity (max_GD). Each dot represents one replicate. Delta_Het: The difference in heterozygosity between generations 20 and 35; Delta_Kinship: The difference in kinship between generations 20 and 35; Genetic_Distance: Nei's genetic distance between generations 20 and 35; Mean_Delta_Freq: The difference in allelic frequencies between generations 20 and 35; NB_rare_SNP_enriched: The number of SNPs with a MAF lower than 0.05 in generation 20 whose frequency increased in generation 35. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 6

Number of offspring of cryopreserved individuals across generations in the different management programmes of selected population. The x‐axis corresponds to the genealogical rank of individuals in relation to their ancestors from the ex situ collections (i.e., rank 1 for children, rank 2 for grandchildren, rank 3 for great‐grandchildren, etc.). The scenario which maximise genetic gain (max_BV) is represented in red and the scenario which maximises genetic gain under a constraint of genetic diverisy (OCS) is represented in green. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 7

Evolution over time of the average genetic value of populations for the two traits of interest in the different scenarios, with and without the use of cryopreserved collections. The solid and dashed lines represent results without and with the use of ex situ collections, respectively. The scenario which maximises genetic gain (max_BV) is represented in red and the scenario which maximises genetic gain under a constraint of genetic diversity (OCS) is represented in green. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 8

Evolution over time of the average additive genetic variance of populations for the two traits in the different scenarios, with and without the use of cryopreserved collections. The solid and dashed lines represent results without and with the use of ex situ collections, respectively. The scenario which maximises genetic gain (max_BV) is represented in red and the scenario which maximises genetic gain under a constraint of genetic diversity (OCS) is represented in green. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 9

Evolution of average kinship across generations within populations in the different scenarios of selected population. The solid and dashed lines represent results without and with the use of ex situ collections, respectively. The scenario which maximise genetic gain (max_BV) is represented in red and the scenario which maximises genetic gain under a constraint of genetic diverisy (OCS) is represented in green. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 10

Measurements of genetic diversity for scenarios which maximise genetic gain (max_BV). In blue, none: Scenario with no change in the weighting of the two traits; in green, moderate: Weighting of both traits increased to 0.5; in red, strong: Complete inversion of weights between the two traits. Delta_Het: The difference in heterozygosity between generations 20 and 35; Delta_Kinship: The difference in kinship between generations 20 and 35; Genetic_Distance: Nei's genetic distance between generations 20 and 35; Mean_Delta_Freq: The difference in allelic frequencies between generations 20 and 35; NB_rare_SNP_enriched: The number of SNPs with a MAF lower than 0.05 in generation 20 whose frequency increased in generation 35. [Colour figure can be viewed at wileyonlinelibrary.com]

FIGURE 11

Measurements of genetic diversity for scenarios which maximises genetic gain under a constraint of genetic diverisy (OCS). In blue, none: Scenario with no change in the weighting of the two traits; in green, moderate: Weighting of both traits increased to 0.5; in red, strong: Complete inversion of weights between the two traits. Delta_Het: The difference in heterozygosity between generations 20 and 35; Delta_Kinship: The difference in kinship between generations 20 and 35; Genetic_Distance: Nei's genetic distance between generations 20 and 35; Mean_Delta_Freq: The difference in allelic frequencies between generations 20 and 35; NB_rare_SNP_enriched: The number of SNPs with a MAF lower than 0.05 in generation 20 whose frequency increased in generation 35. [Colour figure can be viewed at wileyonlinelibrary.com]