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Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions

BACKGROUND: Optimal contributions selection (OCS) provides animal breeders with a framework for maximising genetic gain for a predefined rate of inbreeding. Simulation studies have indicated that the source of the selective advantage of OCS is derived from breeding decisions being more closely align...

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Autores principales: Howard, David M., Pong-Wong, Ricardo, Knap, Pieter W., Kremer, Valentin D., Woolliams, John A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5946451/
https://www.ncbi.nlm.nih.gov/pubmed/29747576
http://dx.doi.org/10.1186/s12711-018-0392-z
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author Howard, David M.
Pong-Wong, Ricardo
Knap, Pieter W.
Kremer, Valentin D.
Woolliams, John A.
author_facet Howard, David M.
Pong-Wong, Ricardo
Knap, Pieter W.
Kremer, Valentin D.
Woolliams, John A.
author_sort Howard, David M.
collection PubMed
description BACKGROUND: Optimal contributions selection (OCS) provides animal breeders with a framework for maximising genetic gain for a predefined rate of inbreeding. Simulation studies have indicated that the source of the selective advantage of OCS is derived from breeding decisions being more closely aligned with estimates of Mendelian sampling terms ([Formula: see text] ) of selection candidates, rather than estimated breeding values (EBV). This study represents the first attempt to assess the source of the selective advantage provided by OCS using a commercial pig population and by testing three hypotheses: (1) OCS places more emphasis on [Formula: see text] compared to EBV for determining which animals were selected as parents, (2) OCS places more emphasis on [Formula: see text] compared to EBV for determining which of those parents were selected to make a long-term genetic contribution (r), and (3) OCS places more emphasis on [Formula: see text] compared to EBV for determining the magnitude of r. The population studied also provided an opportunity to investigate the convergence of r over time. RESULTS: Selection intensity limited the number of males available for analysis, but females provided some evidence that the selective advantage derived from applying an OCS algorithm resulted from greater weighting being placed on [Formula: see text] during the process of decision-making. Male r were found to converge initially at a faster rate than female r, with approximately 90% convergence achieved within seven generations across both sexes. CONCLUSIONS: This study of commercial data provides some support to results from theoretical and simulation studies that the source of selective advantage from OCS comes from [Formula: see text] . The implication that genomic selection (GS) improves estimation of [Formula: see text] should allow for even greater genetic gains for a predefined rate of inbreeding, once the synergistic benefits of combining OCS and GS are realised. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12711-018-0392-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-59464512018-05-14 Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions Howard, David M. Pong-Wong, Ricardo Knap, Pieter W. Kremer, Valentin D. Woolliams, John A. Genet Sel Evol Research Article BACKGROUND: Optimal contributions selection (OCS) provides animal breeders with a framework for maximising genetic gain for a predefined rate of inbreeding. Simulation studies have indicated that the source of the selective advantage of OCS is derived from breeding decisions being more closely aligned with estimates of Mendelian sampling terms ([Formula: see text] ) of selection candidates, rather than estimated breeding values (EBV). This study represents the first attempt to assess the source of the selective advantage provided by OCS using a commercial pig population and by testing three hypotheses: (1) OCS places more emphasis on [Formula: see text] compared to EBV for determining which animals were selected as parents, (2) OCS places more emphasis on [Formula: see text] compared to EBV for determining which of those parents were selected to make a long-term genetic contribution (r), and (3) OCS places more emphasis on [Formula: see text] compared to EBV for determining the magnitude of r. The population studied also provided an opportunity to investigate the convergence of r over time. RESULTS: Selection intensity limited the number of males available for analysis, but females provided some evidence that the selective advantage derived from applying an OCS algorithm resulted from greater weighting being placed on [Formula: see text] during the process of decision-making. Male r were found to converge initially at a faster rate than female r, with approximately 90% convergence achieved within seven generations across both sexes. CONCLUSIONS: This study of commercial data provides some support to results from theoretical and simulation studies that the source of selective advantage from OCS comes from [Formula: see text] . The implication that genomic selection (GS) improves estimation of [Formula: see text] should allow for even greater genetic gains for a predefined rate of inbreeding, once the synergistic benefits of combining OCS and GS are realised. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12711-018-0392-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-05-10 /pmc/articles/PMC5946451/ /pubmed/29747576 http://dx.doi.org/10.1186/s12711-018-0392-z Text en © The Author(s) 2018 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.
spellingShingle Research Article
Howard, David M.
Pong-Wong, Ricardo
Knap, Pieter W.
Kremer, Valentin D.
Woolliams, John A.
Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions
title Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions
title_full Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions
title_fullStr Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions
title_full_unstemmed Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions
title_short Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions
title_sort selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5946451/
https://www.ncbi.nlm.nih.gov/pubmed/29747576
http://dx.doi.org/10.1186/s12711-018-0392-z
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