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Genetic architecture and genomic selection of female reproduction traits in rainbow trout

BACKGROUND: Rainbow trout is a significant fish farming species under temperate climates. Female reproduction traits play an important role in the economy of breeding companies with the sale of fertilized eggs. The objectives of this study are threefold: to estimate the genetic parameters of female...

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Autores principales: D’Ambrosio, J., Morvezen, R., Brard-Fudulea, S., Bestin, A., Acin Perez, A., Guéméné, D., Poncet, C., Haffray, P., Dupont-Nivet, M., Phocas, F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430828/
https://www.ncbi.nlm.nih.gov/pubmed/32795250
http://dx.doi.org/10.1186/s12864-020-06955-7
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author D’Ambrosio, J.
Morvezen, R.
Brard-Fudulea, S.
Bestin, A.
Acin Perez, A.
Guéméné, D.
Poncet, C.
Haffray, P.
Dupont-Nivet, M.
Phocas, F.
author_facet D’Ambrosio, J.
Morvezen, R.
Brard-Fudulea, S.
Bestin, A.
Acin Perez, A.
Guéméné, D.
Poncet, C.
Haffray, P.
Dupont-Nivet, M.
Phocas, F.
author_sort D’Ambrosio, J.
collection PubMed
description BACKGROUND: Rainbow trout is a significant fish farming species under temperate climates. Female reproduction traits play an important role in the economy of breeding companies with the sale of fertilized eggs. The objectives of this study are threefold: to estimate the genetic parameters of female reproduction traits, to determine the genetic architecture of these traits by the identification of quantitative trait loci (QTL), and to assess the expected efficiency of a pedigree-based selection (BLUP) or genomic selection for these traits. RESULTS: A pedigreed population of 1343 trout were genotyped for 57,000 SNP markers and phenotyped for seven traits at 2 years of age: spawning date, female body weight before and after spawning, the spawn weight and the egg number of the spawn, the egg average weight and average diameter. Genetic parameters were estimated in multi-trait linear animal models. Heritability estimates were moderate, varying from 0.27 to 0.44. The female body weight was not genetically correlated to any of the reproduction traits. Spawn weight showed strong and favourable genetic correlation with the number of eggs in the spawn and individual egg size traits, but the egg number was uncorrelated to the egg size traits. The genome-wide association studies showed that all traits were very polygenic since less than 10% of the genetic variance was explained by the cumulative effects of the QTLs: for any trait, only 2 to 4 QTLs were detected that explained in-between 1 and 3% of the genetic variance. Genomic selection based on a reference population of only one thousand individuals related to candidates would improve the efficiency of BLUP selection from 16 to 37% depending on traits. CONCLUSIONS: Our genetic parameter estimates made unlikely the hypothesis that selection for growth could induce any indirect improvement for female reproduction traits. It is thus important to consider direct selection for spawn weight for improving egg production traits in rainbow trout breeding programs. Due to the low proportion of genetic variance explained by the few QTLs detected for each reproduction traits, marker assisted selection cannot be effective. However genomic selection would allow significant gains of accuracy compared to pedigree-based selection.
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spelling pubmed-74308282020-08-18 Genetic architecture and genomic selection of female reproduction traits in rainbow trout D’Ambrosio, J. Morvezen, R. Brard-Fudulea, S. Bestin, A. Acin Perez, A. Guéméné, D. Poncet, C. Haffray, P. Dupont-Nivet, M. Phocas, F. BMC Genomics Research Article BACKGROUND: Rainbow trout is a significant fish farming species under temperate climates. Female reproduction traits play an important role in the economy of breeding companies with the sale of fertilized eggs. The objectives of this study are threefold: to estimate the genetic parameters of female reproduction traits, to determine the genetic architecture of these traits by the identification of quantitative trait loci (QTL), and to assess the expected efficiency of a pedigree-based selection (BLUP) or genomic selection for these traits. RESULTS: A pedigreed population of 1343 trout were genotyped for 57,000 SNP markers and phenotyped for seven traits at 2 years of age: spawning date, female body weight before and after spawning, the spawn weight and the egg number of the spawn, the egg average weight and average diameter. Genetic parameters were estimated in multi-trait linear animal models. Heritability estimates were moderate, varying from 0.27 to 0.44. The female body weight was not genetically correlated to any of the reproduction traits. Spawn weight showed strong and favourable genetic correlation with the number of eggs in the spawn and individual egg size traits, but the egg number was uncorrelated to the egg size traits. The genome-wide association studies showed that all traits were very polygenic since less than 10% of the genetic variance was explained by the cumulative effects of the QTLs: for any trait, only 2 to 4 QTLs were detected that explained in-between 1 and 3% of the genetic variance. Genomic selection based on a reference population of only one thousand individuals related to candidates would improve the efficiency of BLUP selection from 16 to 37% depending on traits. CONCLUSIONS: Our genetic parameter estimates made unlikely the hypothesis that selection for growth could induce any indirect improvement for female reproduction traits. It is thus important to consider direct selection for spawn weight for improving egg production traits in rainbow trout breeding programs. Due to the low proportion of genetic variance explained by the few QTLs detected for each reproduction traits, marker assisted selection cannot be effective. However genomic selection would allow significant gains of accuracy compared to pedigree-based selection. BioMed Central 2020-08-14 /pmc/articles/PMC7430828/ /pubmed/32795250 http://dx.doi.org/10.1186/s12864-020-06955-7 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research Article
D’Ambrosio, J.
Morvezen, R.
Brard-Fudulea, S.
Bestin, A.
Acin Perez, A.
Guéméné, D.
Poncet, C.
Haffray, P.
Dupont-Nivet, M.
Phocas, F.
Genetic architecture and genomic selection of female reproduction traits in rainbow trout
title Genetic architecture and genomic selection of female reproduction traits in rainbow trout
title_full Genetic architecture and genomic selection of female reproduction traits in rainbow trout
title_fullStr Genetic architecture and genomic selection of female reproduction traits in rainbow trout
title_full_unstemmed Genetic architecture and genomic selection of female reproduction traits in rainbow trout
title_short Genetic architecture and genomic selection of female reproduction traits in rainbow trout
title_sort genetic architecture and genomic selection of female reproduction traits in rainbow trout
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430828/
https://www.ncbi.nlm.nih.gov/pubmed/32795250
http://dx.doi.org/10.1186/s12864-020-06955-7
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