Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon
International audience AbstractBackgroundBreeding companies may want to maximize the rate of genetic gain from their breeding program within a limited budget. In salmon breeding programs, full-sibs of selection candidates are subjected to performance tests for traits that cannot be recorded on selec...
Published in: | Genetics Selection Evolution |
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ftccsdartic:oai:HAL:hal-02281236v1 2023-05-15T15:32:59+02:00 Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon Janssen, Kasper Saatkamp, Helmut W. Calus, Mario P. L. Komen, Hans 2019-12 https://hal.archives-ouvertes.fr/hal-02281236 https://hal.archives-ouvertes.fr/hal-02281236/document https://hal.archives-ouvertes.fr/hal-02281236/file/12711_2019_Article_491.pdf https://doi.org/10.1186/s12711-019-0491-5 en eng HAL CCSD BioMed Central info:eu-repo/semantics/altIdentifier/doi/10.1186/s12711-019-0491-5 hal-02281236 https://hal.archives-ouvertes.fr/hal-02281236 https://hal.archives-ouvertes.fr/hal-02281236/document https://hal.archives-ouvertes.fr/hal-02281236/file/12711_2019_Article_491.pdf doi:10.1186/s12711-019-0491-5 info:eu-repo/semantics/OpenAccess ISSN: 0999-193X EISSN: 1297-9686 Genetics Selection Evolution https://hal.archives-ouvertes.fr/hal-02281236 Genetics Selection Evolution, BioMed Central, 2019, 51 (1), pp.49. ⟨10.1186/s12711-019-0491-5⟩ [SDV]Life Sciences [q-bio] info:eu-repo/semantics/article Journal articles 2019 ftccsdartic https://doi.org/10.1186/s12711-019-0491-5 2021-02-20T23:57:09Z International audience AbstractBackgroundBreeding companies may want to maximize the rate of genetic gain from their breeding program within a limited budget. In salmon breeding programs, full-sibs of selection candidates are subjected to performance tests for traits that cannot be recorded on selection candidates. While marginal gains in the aggregate genotype from phenotyping and genotyping more full-sibs per candidate decrease, costs increase linearly, which suggests that there is an optimum in the allocation of the budget among these activities. Here, we studied how allocation of the fixed budget to numbers of phenotyped and genotyped test individuals in performance tests can be optimized.MethodsGain in the aggregate genotype was a function of the numbers of full-sibs of selection candidates that were (1) phenotyped in a challenge test for sea lice resistance (2) phenotyped in a slaughter test (3) genotyped in the challenge test, and (4) genotyped in the slaughter test. Each of these activities was subject to budget constraints. Using a grid search, we optimized allocation of the budget among activities to maximize gain in the aggregate genotype. We performed sensitivity analyses on the maximum gain in the aggregate genotype and on the relative allocation of the budget among activities at the optimum.ResultsMaximum gain in the aggregate genotype was €386/ton per generation. The response surface for gain in the aggregate genotype was rather flat around the optimum, but it curved strongly near the extremes. Maximum gain was sensitive to the size of the budget and the relative emphasis on breeding goal traits, but less sensitive to the accuracy of genomic prediction and costs of phenotyping and genotyping. The relative allocation of budget among activities at the optimum was sensitive to costs of phenotyping and genotyping and the relative emphasis on breeding goal traits, but was less sensitive to the accuracy of genomic prediction and the size of the budget.ConclusionsThere is an optimum allocation of ... Article in Journal/Newspaper Atlantic salmon Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Slaughter ENVELOPE(-85.633,-85.633,-78.617,-78.617) Genetics Selection Evolution 51 1 |
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Open Polar |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
op_collection_id |
ftccsdartic |
language |
English |
topic |
[SDV]Life Sciences [q-bio] |
spellingShingle |
[SDV]Life Sciences [q-bio] Janssen, Kasper Saatkamp, Helmut W. Calus, Mario P. L. Komen, Hans Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon |
topic_facet |
[SDV]Life Sciences [q-bio] |
description |
International audience AbstractBackgroundBreeding companies may want to maximize the rate of genetic gain from their breeding program within a limited budget. In salmon breeding programs, full-sibs of selection candidates are subjected to performance tests for traits that cannot be recorded on selection candidates. While marginal gains in the aggregate genotype from phenotyping and genotyping more full-sibs per candidate decrease, costs increase linearly, which suggests that there is an optimum in the allocation of the budget among these activities. Here, we studied how allocation of the fixed budget to numbers of phenotyped and genotyped test individuals in performance tests can be optimized.MethodsGain in the aggregate genotype was a function of the numbers of full-sibs of selection candidates that were (1) phenotyped in a challenge test for sea lice resistance (2) phenotyped in a slaughter test (3) genotyped in the challenge test, and (4) genotyped in the slaughter test. Each of these activities was subject to budget constraints. Using a grid search, we optimized allocation of the budget among activities to maximize gain in the aggregate genotype. We performed sensitivity analyses on the maximum gain in the aggregate genotype and on the relative allocation of the budget among activities at the optimum.ResultsMaximum gain in the aggregate genotype was €386/ton per generation. The response surface for gain in the aggregate genotype was rather flat around the optimum, but it curved strongly near the extremes. Maximum gain was sensitive to the size of the budget and the relative emphasis on breeding goal traits, but less sensitive to the accuracy of genomic prediction and costs of phenotyping and genotyping. The relative allocation of budget among activities at the optimum was sensitive to costs of phenotyping and genotyping and the relative emphasis on breeding goal traits, but was less sensitive to the accuracy of genomic prediction and the size of the budget.ConclusionsThere is an optimum allocation of ... |
format |
Article in Journal/Newspaper |
author |
Janssen, Kasper Saatkamp, Helmut W. Calus, Mario P. L. Komen, Hans |
author_facet |
Janssen, Kasper Saatkamp, Helmut W. Calus, Mario P. L. Komen, Hans |
author_sort |
Janssen, Kasper |
title |
Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon |
title_short |
Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon |
title_full |
Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon |
title_fullStr |
Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon |
title_full_unstemmed |
Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon |
title_sort |
economic optimization of full-sib test group size and genotyping effort in a breeding program for atlantic salmon |
publisher |
HAL CCSD |
publishDate |
2019 |
url |
https://hal.archives-ouvertes.fr/hal-02281236 https://hal.archives-ouvertes.fr/hal-02281236/document https://hal.archives-ouvertes.fr/hal-02281236/file/12711_2019_Article_491.pdf https://doi.org/10.1186/s12711-019-0491-5 |
long_lat |
ENVELOPE(-85.633,-85.633,-78.617,-78.617) |
geographic |
Slaughter |
geographic_facet |
Slaughter |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_source |
ISSN: 0999-193X EISSN: 1297-9686 Genetics Selection Evolution https://hal.archives-ouvertes.fr/hal-02281236 Genetics Selection Evolution, BioMed Central, 2019, 51 (1), pp.49. ⟨10.1186/s12711-019-0491-5⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1186/s12711-019-0491-5 hal-02281236 https://hal.archives-ouvertes.fr/hal-02281236 https://hal.archives-ouvertes.fr/hal-02281236/document https://hal.archives-ouvertes.fr/hal-02281236/file/12711_2019_Article_491.pdf doi:10.1186/s12711-019-0491-5 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1186/s12711-019-0491-5 |
container_title |
Genetics Selection Evolution |
container_volume |
51 |
container_issue |
1 |
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1766363456999522304 |