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Title: Approximated prediction of genomic selection accuracy when reference and candidate populations are related
Contributor(s): Elsen, Jean-Michel (author)
Publication Date: 2016
Open Access: Yes
DOI: 10.1186/s12711-016-0183-3Open Access Link
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Abstract: Background: Genomic selection is still to be evaluated and optimized in many species. Mathematical modeling of selection schemes prior to their implementation is a classical and useful tool for that purpose. These models include formalization of a number of entities including the precision of the estimated breeding value. To model genomic selection schemes, equations that predict this reliability as a function of factors such as the size of the reference population, its diversity, its genetic distance from the group of selection candidates genotyped, number of markers and strength of linkage disequilibrium are needed. The present paper aims at exploring new approximations of this reliability. Results: Two alternative approximations are proposed for the estimation of the reliability of genomic estimated breeding values (GEBV) in the case of non-independence between candidate and reference populations. Both were derived from the Taylor series heuristic approach suggested by Goddard in 2009. A numerical exploration of their properties showed that the series were not equivalent in terms of convergence to the exact reliability, that the approximations may overestimate the precision of GEBV and that they converged towards their theoretical expectations. Formulae derived for these approximations were simple to handle in the case of independent markers. A few parameters that describe the markers' genotypic variability (allele frequencies, linkage disequilibrium) can be estimated from genomic data corresponding to the population of interest or after making assumptions about their distribution. When markers are not in linkage equilibrium, replacing the real number of markers and QTL by the 'effective number of independent loci', as proposed earlier is a practical solution. In this paper, we considered an alternative, i.e. an 'equivalent number of independent loci' which would give a GEBV reliability for unrelated individuals by considering a sub-set of independent markers that is identical to the reliability obtained by considering the full set of markers. Conclusions This paper is a further step towards the development of deterministic models that describe breeding plans based on the use of genomic information. Such deterministic models carry low computational burden, which allows design optimization through intensive numerical exploration.
Publication Type: Journal Article
Source of Publication: Genetics Selection Evolution, v.48, p. 1-19
Publisher: BioMed Central Ltd
Place of Publication: United Kingdom
ISSN: 1297-9686
Field of Research (FoR) 2008: 070201 Animal Breeding
Field of Research (FoR) 2020: 300305 Animal reproduction and breeding
Socio-Economic Objective (SEO) 2008: 830311 Sheep - Wool
830310 Sheep - Meat
Socio-Economic Objective (SEO) 2020: 100413 Sheep for wool
100412 Sheep for meat
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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