Journal article
Conservation Genetics Resources, 2019
APA
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Leroy, G., Gicquel, E., Boettcher, P., Besbes, B., Furre, S., Fernández, J., … Baumung, R. (2019). Coancestry rate’s estimate of effective population size for genetic variability monitoring. Conservation Genetics Resources.
Chicago/Turabian
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Leroy, G., E. Gicquel, P. Boettcher, B. Besbes, S. Furre, Jesús Fernández, C. Danchin-Burge, N. Alnahhas, and R. Baumung. “Coancestry Rate’s Estimate of Effective Population Size for Genetic Variability Monitoring.” Conservation Genetics Resources (2019).
MLA
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Leroy, G., et al. “Coancestry Rate’s Estimate of Effective Population Size for Genetic Variability Monitoring.” Conservation Genetics Resources, 2019.
BibTeX Click to copy
@article{g2019a,
title = {Coancestry rate’s estimate of effective population size for genetic variability monitoring},
year = {2019},
journal = {Conservation Genetics Resources},
author = {Leroy, G. and Gicquel, E. and Boettcher, P. and Besbes, B. and Furre, S. and Fernández, Jesús and Danchin-Burge, C. and Alnahhas, N. and Baumung, R.}
}
Different methods and formulae have been suggested to estimate effective population size based on pedigree data. These methods vary in their sensitivity to various sources of bias related to heterogenous pedigree knowledge or pedigree structure. We propose here to adapt a pre-existing method estimating coancestry rate for the specific purpose of monitoring genetic variability within livestock and captive populations. Coancestry rate is computed by averaging coancestries between pairs of individuals corrected by their equivalent numbers of generations, while restricting pedigree information to a maximum number of generations. Simulation demonstrated that restricting the number of generations allows a much clearer observation of the impact of recent events on genetic variability. Restricting the number of generations for the calculation of coancestry also has less bias related to incomplete pedigree, although it may overestimate effective population size due to non-independence in family sizes across generations. This strategy was tested on the Norwegian Nordland Lyngen horse, the Colblood Trotter horse, the French Avranchin sheep, and Bresse chicken, illustrating the applications of the approach for the monitoring of genetic variability.