Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon
BACKGROUND: Breeding 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 margin...
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ftpubmed:oai:pubmedcentral.nih.gov:6724325 2023-05-15T15:33:01+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 2019-09-03 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724325/ http://www.ncbi.nlm.nih.gov/pubmed/31481013 https://doi.org/10.1186/s12711-019-0491-5 en eng BioMed Central http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724325/ http://www.ncbi.nlm.nih.gov/pubmed/31481013 http://dx.doi.org/10.1186/s12711-019-0491-5 © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. CC0 PDM CC-BY Research Article Text 2019 ftpubmed https://doi.org/10.1186/s12711-019-0491-5 2019-09-15T00:25:11Z BACKGROUND: Breeding 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. METHODS: Gain 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. RESULTS: Maximum 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. CONCLUSIONS: There is an optimum allocation of budget to the numbers of ... Text Atlantic salmon PubMed Central (PMC) Slaughter ENVELOPE(-85.633,-85.633,-78.617,-78.617) Genetics Selection Evolution 51 1 |
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Research Article |
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Research Article 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 |
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Research Article |
description |
BACKGROUND: Breeding 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. METHODS: Gain 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. RESULTS: Maximum 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. CONCLUSIONS: There is an optimum allocation of budget to the numbers of ... |
format |
Text |
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 |
BioMed Central |
publishDate |
2019 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724325/ http://www.ncbi.nlm.nih.gov/pubmed/31481013 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_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724325/ http://www.ncbi.nlm.nih.gov/pubmed/31481013 http://dx.doi.org/10.1186/s12711-019-0491-5 |
op_rights |
© The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
op_rightsnorm |
CC0 PDM CC-BY |
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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1766363490066366464 |