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Estimates of genetic trend for single-step genomic evaluations

BACKGROUND: A common measure employed to evaluate the efficacy of livestock improvement schemes is the genetic trend, which is calculated as the means of predicted breeding values for animals born in successive time periods. This implies that different cohorts refer to the same base population. For...

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Autores principales: Meyer, Karin, Tier, Bruce, Swan, Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091173/
https://www.ncbi.nlm.nih.gov/pubmed/30075705
http://dx.doi.org/10.1186/s12711-018-0410-1
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author Meyer, Karin
Tier, Bruce
Swan, Andrew
author_facet Meyer, Karin
Tier, Bruce
Swan, Andrew
author_sort Meyer, Karin
collection PubMed
description BACKGROUND: A common measure employed to evaluate the efficacy of livestock improvement schemes is the genetic trend, which is calculated as the means of predicted breeding values for animals born in successive time periods. This implies that different cohorts refer to the same base population. For genetic evaluation schemes integrating genomic information with records for all animals, genotyped or not, this is often not the case: expected means for pedigree founders are zero whereas values for genotyped animals are expected to sum to zero at the (mean) time corresponding to the frequencies that are used to center marker allele counts when calculating genomic relationships. METHODS: The paper examines estimates of genetic trends from single-step genomic evaluations. After a review of methods which propose to align pedigree-based and genomic relationship matrices, simulation is used to illustrate the effects of alignments and choice of assumed gene frequencies on trajectories of genetic trends. RESULTS: The results show that methods available to alleviate differences between the founder populations implied by the two types of relationship matrices perform well; in particular, the meta-founder approach is advantageous. An application to data from routine genetic evaluation of Australian sheep is shown, confirming their effectiveness for practical data. CONCLUSIONS: Aligning pedigree and genomic relationship matrices for single step genetic evaluation for populations under selection is essential. Fitting meta-founders is an effective and simple method to avoid distortion of estimates of genetic trends.
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spelling pubmed-60911732018-08-20 Estimates of genetic trend for single-step genomic evaluations Meyer, Karin Tier, Bruce Swan, Andrew Genet Sel Evol Research Article BACKGROUND: A common measure employed to evaluate the efficacy of livestock improvement schemes is the genetic trend, which is calculated as the means of predicted breeding values for animals born in successive time periods. This implies that different cohorts refer to the same base population. For genetic evaluation schemes integrating genomic information with records for all animals, genotyped or not, this is often not the case: expected means for pedigree founders are zero whereas values for genotyped animals are expected to sum to zero at the (mean) time corresponding to the frequencies that are used to center marker allele counts when calculating genomic relationships. METHODS: The paper examines estimates of genetic trends from single-step genomic evaluations. After a review of methods which propose to align pedigree-based and genomic relationship matrices, simulation is used to illustrate the effects of alignments and choice of assumed gene frequencies on trajectories of genetic trends. RESULTS: The results show that methods available to alleviate differences between the founder populations implied by the two types of relationship matrices perform well; in particular, the meta-founder approach is advantageous. An application to data from routine genetic evaluation of Australian sheep is shown, confirming their effectiveness for practical data. CONCLUSIONS: Aligning pedigree and genomic relationship matrices for single step genetic evaluation for populations under selection is essential. Fitting meta-founders is an effective and simple method to avoid distortion of estimates of genetic trends. BioMed Central 2018-08-03 /pmc/articles/PMC6091173/ /pubmed/30075705 http://dx.doi.org/10.1186/s12711-018-0410-1 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
Meyer, Karin
Tier, Bruce
Swan, Andrew
Estimates of genetic trend for single-step genomic evaluations
title Estimates of genetic trend for single-step genomic evaluations
title_full Estimates of genetic trend for single-step genomic evaluations
title_fullStr Estimates of genetic trend for single-step genomic evaluations
title_full_unstemmed Estimates of genetic trend for single-step genomic evaluations
title_short Estimates of genetic trend for single-step genomic evaluations
title_sort estimates of genetic trend for single-step genomic evaluations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091173/
https://www.ncbi.nlm.nih.gov/pubmed/30075705
http://dx.doi.org/10.1186/s12711-018-0410-1
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