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Comparative evaluation of potential indicators and temporal sampling protocols for monitoring genetic erosion.

Hoban S, Arntzen JA, Bruford MW, Godoy JA, Rus Hoelzel A, Segelbacher G, Vilà C, Bertorelle G - Evol Appl (2014)

Bottom Line: The type and severity of demographic decline strongly affected power, while the number and arrangement of temporal samples had small effect.Power increased substantially with more samples or markers, and we observe that power of 2500 SNPs was nearly equivalent to 250 microsatellites, a result of theoretical and practical interest.Our results suggest high potential for using historic collections in monitoring programs, and demonstrate the need to monitor genetic as well as other levels of biodiversity.

View Article: PubMed Central - PubMed

Affiliation: National Institute for Mathematical and Biological Synthesis (NIMBioS), University of Tennessee Knoxville, TN, USA ; Department of Life Science, Università di Ferrara Ferrara, Italy.

ABSTRACT
Genetic biodiversity contributes to individual fitness, species' evolutionary potential, and ecosystem stability. Temporal monitoring of the genetic status and trends of wild populations' genetic diversity can provide vital data to inform policy decisions and management actions. However, there is a lack of knowledge regarding which genetic metrics, temporal sampling protocols, and genetic markers are sufficiently sensitive and robust, on conservation-relevant timescales. Here, we tested six genetic metrics and various sampling protocols (number and arrangement of temporal samples) for monitoring genetic erosion following demographic decline. To do so, we utilized individual-based simulations featuring an array of different initial population sizes, types and severity of demographic decline, and DNA markers [single nucleotide polymorphisms (SNPs) and microsatellites] as well as decline followed by recovery. Number of alleles markedly outperformed other indicators across all situations. The type and severity of demographic decline strongly affected power, while the number and arrangement of temporal samples had small effect. Sampling 50 individuals at as few as two time points with 20 microsatellites performed well (good power), and could detect genetic erosion while 80-90% of diversity remained. This sampling and genotyping effort should often be affordable. Power increased substantially with more samples or markers, and we observe that power of 2500 SNPs was nearly equivalent to 250 microsatellites, a result of theoretical and practical interest. Our results suggest high potential for using historic collections in monitoring programs, and demonstrate the need to monitor genetic as well as other levels of biodiversity.

No MeSH data available.


Related in: MedlinePlus

Genetic response (y-axis) to 99% exponential population decline, measured at 20 loci, in 50 individuals, over generations (x-axis). Error bars represent standard deviation. Linear regression of the indicator is shown with a red line. Gray line is value at generation one.
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fig01: Genetic response (y-axis) to 99% exponential population decline, measured at 20 loci, in 50 individuals, over generations (x-axis). Error bars represent standard deviation. Linear regression of the indicator is shown with a red line. Gray line is value at generation one.

Mentions: The simulated populations showed realistic numbers of alleles (mean 5.21 for N = 2000, 11.62 for N = 10 000) and heterozygosity (0.66 for N = 2000, 0.85 for N = 10 000). Theoretical expectations for heterozygosity for a population of Ne = 2000 is 0.667 (Hedrick 2011), and for number of alleles is 4.81 under the Kimura and Ohta (1975) approximation. Expected number of alleles for Ne = 10 000 is approximately 10.5 based on coalescent simulations (Hoban et al. 2013c). As expected, genetic indicators generally decreased following population decline in all situations (Figs1 and 2), but the degree of genetic loss, the time lag, and the ability to detect it, varied among the indicators tested and among the types of decline.


Comparative evaluation of potential indicators and temporal sampling protocols for monitoring genetic erosion.

Hoban S, Arntzen JA, Bruford MW, Godoy JA, Rus Hoelzel A, Segelbacher G, Vilà C, Bertorelle G - Evol Appl (2014)

Genetic response (y-axis) to 99% exponential population decline, measured at 20 loci, in 50 individuals, over generations (x-axis). Error bars represent standard deviation. Linear regression of the indicator is shown with a red line. Gray line is value at generation one.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4231590&req=5

fig01: Genetic response (y-axis) to 99% exponential population decline, measured at 20 loci, in 50 individuals, over generations (x-axis). Error bars represent standard deviation. Linear regression of the indicator is shown with a red line. Gray line is value at generation one.
Mentions: The simulated populations showed realistic numbers of alleles (mean 5.21 for N = 2000, 11.62 for N = 10 000) and heterozygosity (0.66 for N = 2000, 0.85 for N = 10 000). Theoretical expectations for heterozygosity for a population of Ne = 2000 is 0.667 (Hedrick 2011), and for number of alleles is 4.81 under the Kimura and Ohta (1975) approximation. Expected number of alleles for Ne = 10 000 is approximately 10.5 based on coalescent simulations (Hoban et al. 2013c). As expected, genetic indicators generally decreased following population decline in all situations (Figs1 and 2), but the degree of genetic loss, the time lag, and the ability to detect it, varied among the indicators tested and among the types of decline.

Bottom Line: The type and severity of demographic decline strongly affected power, while the number and arrangement of temporal samples had small effect.Power increased substantially with more samples or markers, and we observe that power of 2500 SNPs was nearly equivalent to 250 microsatellites, a result of theoretical and practical interest.Our results suggest high potential for using historic collections in monitoring programs, and demonstrate the need to monitor genetic as well as other levels of biodiversity.

View Article: PubMed Central - PubMed

Affiliation: National Institute for Mathematical and Biological Synthesis (NIMBioS), University of Tennessee Knoxville, TN, USA ; Department of Life Science, Università di Ferrara Ferrara, Italy.

ABSTRACT
Genetic biodiversity contributes to individual fitness, species' evolutionary potential, and ecosystem stability. Temporal monitoring of the genetic status and trends of wild populations' genetic diversity can provide vital data to inform policy decisions and management actions. However, there is a lack of knowledge regarding which genetic metrics, temporal sampling protocols, and genetic markers are sufficiently sensitive and robust, on conservation-relevant timescales. Here, we tested six genetic metrics and various sampling protocols (number and arrangement of temporal samples) for monitoring genetic erosion following demographic decline. To do so, we utilized individual-based simulations featuring an array of different initial population sizes, types and severity of demographic decline, and DNA markers [single nucleotide polymorphisms (SNPs) and microsatellites] as well as decline followed by recovery. Number of alleles markedly outperformed other indicators across all situations. The type and severity of demographic decline strongly affected power, while the number and arrangement of temporal samples had small effect. Sampling 50 individuals at as few as two time points with 20 microsatellites performed well (good power), and could detect genetic erosion while 80-90% of diversity remained. This sampling and genotyping effort should often be affordable. Power increased substantially with more samples or markers, and we observe that power of 2500 SNPs was nearly equivalent to 250 microsatellites, a result of theoretical and practical interest. Our results suggest high potential for using historic collections in monitoring programs, and demonstrate the need to monitor genetic as well as other levels of biodiversity.

No MeSH data available.


Related in: MedlinePlus