The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar)
International audience AbstractSea lice infestations caused by Caligus rogercresseyi are a main concern to the salmon farming industry due to associated economic losses. Resistance to this parasite was shown to have low to moderate genetic variation and its genetic architecture was suggested to be p...
Published in: | Genetics Selection Evolution |
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Online Access: | https://hal.archives-ouvertes.fr/hal-01479144 https://hal.archives-ouvertes.fr/hal-01479144/document https://hal.archives-ouvertes.fr/hal-01479144/file/12711_2017_Article_291.pdf https://doi.org/10.1186/s12711-017-0291-8 |
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ftccsdartic:oai:HAL:hal-01479144v1 2023-05-15T15:31:35+02:00 The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar) Correa, Katharina Bangera, Rama Figueroa, René Lhorente, Jean P. Yáñez, José M. 2017-12 https://hal.archives-ouvertes.fr/hal-01479144 https://hal.archives-ouvertes.fr/hal-01479144/document https://hal.archives-ouvertes.fr/hal-01479144/file/12711_2017_Article_291.pdf https://doi.org/10.1186/s12711-017-0291-8 en eng HAL CCSD BioMed Central info:eu-repo/semantics/altIdentifier/doi/10.1186/s12711-017-0291-8 hal-01479144 https://hal.archives-ouvertes.fr/hal-01479144 https://hal.archives-ouvertes.fr/hal-01479144/document https://hal.archives-ouvertes.fr/hal-01479144/file/12711_2017_Article_291.pdf doi:10.1186/s12711-017-0291-8 info:eu-repo/semantics/OpenAccess ISSN: 0999-193X EISSN: 1297-9686 Genetics Selection Evolution https://hal.archives-ouvertes.fr/hal-01479144 Genetics Selection Evolution, BioMed Central, 2017, 49 (1), pp.15. ⟨10.1186/s12711-017-0291-8⟩ [SDV]Life Sciences [q-bio] info:eu-repo/semantics/article Journal articles 2017 ftccsdartic https://doi.org/10.1186/s12711-017-0291-8 2021-02-21T01:23:10Z International audience AbstractSea lice infestations caused by Caligus rogercresseyi are a main concern to the salmon farming industry due to associated economic losses. Resistance to this parasite was shown to have low to moderate genetic variation and its genetic architecture was suggested to be polygenic. The aim of this study was to compare accuracies of breeding value predictions obtained with pedigree-based best linear unbiased prediction (P-BLUP) methodology against different genomic prediction approaches: genomic BLUP (G-BLUP), Bayesian Lasso, and Bayes C. To achieve this, 2404 individuals from 118 families were measured for C. rogercresseyi count after a challenge and genotyped using 37 K single nucleotide polymorphisms. Accuracies were assessed using fivefold cross-validation and SNP densities of 0.5, 1, 5, 10, 25 and 37 K. Accuracy of genomic predictions increased with increasing SNP density and was higher than pedigree-based BLUP predictions by up to 22%. Both Bayesian and G-BLUP methods can predict breeding values with higher accuracies than pedigree-based BLUP, however, G-BLUP may be the preferred method because of reduced computation time and ease of implementation. A relatively low marker density (i.e. 10 K) is sufficient for maximal increase in accuracy when using G-BLUP or Bayesian methods for genomic prediction of C. rogercresseyi resistance in Atlantic salmon. Article in Journal/Newspaper Atlantic salmon Salmo salar Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Genetics Selection Evolution 49 1 |
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Open Polar |
collection |
Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
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ftccsdartic |
language |
English |
topic |
[SDV]Life Sciences [q-bio] |
spellingShingle |
[SDV]Life Sciences [q-bio] Correa, Katharina Bangera, Rama Figueroa, René Lhorente, Jean P. Yáñez, José M. The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar) |
topic_facet |
[SDV]Life Sciences [q-bio] |
description |
International audience AbstractSea lice infestations caused by Caligus rogercresseyi are a main concern to the salmon farming industry due to associated economic losses. Resistance to this parasite was shown to have low to moderate genetic variation and its genetic architecture was suggested to be polygenic. The aim of this study was to compare accuracies of breeding value predictions obtained with pedigree-based best linear unbiased prediction (P-BLUP) methodology against different genomic prediction approaches: genomic BLUP (G-BLUP), Bayesian Lasso, and Bayes C. To achieve this, 2404 individuals from 118 families were measured for C. rogercresseyi count after a challenge and genotyped using 37 K single nucleotide polymorphisms. Accuracies were assessed using fivefold cross-validation and SNP densities of 0.5, 1, 5, 10, 25 and 37 K. Accuracy of genomic predictions increased with increasing SNP density and was higher than pedigree-based BLUP predictions by up to 22%. Both Bayesian and G-BLUP methods can predict breeding values with higher accuracies than pedigree-based BLUP, however, G-BLUP may be the preferred method because of reduced computation time and ease of implementation. A relatively low marker density (i.e. 10 K) is sufficient for maximal increase in accuracy when using G-BLUP or Bayesian methods for genomic prediction of C. rogercresseyi resistance in Atlantic salmon. |
format |
Article in Journal/Newspaper |
author |
Correa, Katharina Bangera, Rama Figueroa, René Lhorente, Jean P. Yáñez, José M. |
author_facet |
Correa, Katharina Bangera, Rama Figueroa, René Lhorente, Jean P. Yáñez, José M. |
author_sort |
Correa, Katharina |
title |
The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar) |
title_short |
The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar) |
title_full |
The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar) |
title_fullStr |
The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar) |
title_full_unstemmed |
The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar) |
title_sort |
use of genomic information increases the accuracy of breeding value predictions for sea louse (caligus rogercresseyi) resistance in atlantic salmon (salmo salar) |
publisher |
HAL CCSD |
publishDate |
2017 |
url |
https://hal.archives-ouvertes.fr/hal-01479144 https://hal.archives-ouvertes.fr/hal-01479144/document https://hal.archives-ouvertes.fr/hal-01479144/file/12711_2017_Article_291.pdf https://doi.org/10.1186/s12711-017-0291-8 |
genre |
Atlantic salmon Salmo salar |
genre_facet |
Atlantic salmon Salmo salar |
op_source |
ISSN: 0999-193X EISSN: 1297-9686 Genetics Selection Evolution https://hal.archives-ouvertes.fr/hal-01479144 Genetics Selection Evolution, BioMed Central, 2017, 49 (1), pp.15. ⟨10.1186/s12711-017-0291-8⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1186/s12711-017-0291-8 hal-01479144 https://hal.archives-ouvertes.fr/hal-01479144 https://hal.archives-ouvertes.fr/hal-01479144/document https://hal.archives-ouvertes.fr/hal-01479144/file/12711_2017_Article_291.pdf doi:10.1186/s12711-017-0291-8 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1186/s12711-017-0291-8 |
container_title |
Genetics Selection Evolution |
container_volume |
49 |
container_issue |
1 |
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1766362103474552832 |