Estimates of genetic trend for single-step genomic evaluations

Title
Estimates of genetic trend for single-step genomic evaluations
Publication Date
2018
Author(s)
Meyer, Karin
( author )
OrcID: https://orcid.org/0000-0003-2663-9059
Email: kmeyer@une.edu.au
UNE Id une-id:kmeyer
Tier, Bruce
Swan, Andrew
( author )
OrcID: https://orcid.org/0000-0001-8048-3169
Email: aswan@une.edu.au
UNE Id une-id:aswan
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
BioMed Central Ltd
Place of publication
United Kingdom
DOI
10.1186/s12711-018-0410-1
UNE publication id
une:-chute-20180828-093106
une:-chute-20180828-093106
Abstract
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.
Link
Citation
Genetics Selection Evolution, v.50, p. 1-11
ISSN
1297-9686
0999-193X
Start page
1
End page
11
Rights
Attribution 4.0 International

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