Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/28969
Title: Effect of selection and selective genotyping for creation of reference on bias and accuracy of genomic prediction
Contributor(s): Gowane, Gopal R (author); Lee, Sang Hong  (author); Clark, Sam  (author)orcid ; Moghaddar, Nasir  (author)orcid ; Al-Mamun, Hawlader A (author); van der Werf, Julius H J  (author)orcid 
Publication Date: 2019
Open Access: Yes
DOI: 10.1111/jbg.12420
Handle Link: https://hdl.handle.net/1959.11/28969
Abstract: Reference populations for genomic selection usually involve selected individuals, which may result in biased prediction of estimated genomic breeding values (GEBV). In a simulation study, bias and accuracy of GEBV were explored for various genetic models with individuals selectively genotyped in a typical nucleus breeding program. We compared the performance of three existing methods, that is, Best Linear Unbiased Prediction of breeding values using pedigree-based relationships (PBLUP), genomic relationships for genotyped animals only (GBLUP) and a Single-Step approach (SSGBLUP) using both. For a scenario with no-selection and random mating (RR), prediction was unbiased. However, lower accuracy and bias were observed for scenarios with selection and random mating (SR) or selection and positive assortative mating (SA). As expected, bias disappeared when all individuals were genotyped and used in GBLUP. SSGBLUP showed higher accuracy compared to GBLUP, and bias of prediction was negligible with SR. However, PBLUP and SSGBLUP still showed bias in SA due to high inbreeding. SSGBLUP and PBLUP were unbiased provided that inbreeding was accounted for in the relationship matrices. Selective genotyping based on extreme phenotypic contrasts increased the prediction accuracy, but prediction was biased when using GBLUP. SSGBLUP could correct the biasedness while gaining higher accuracy than GBLUP. In a typical animal breeding program, where it is too expensive to genotype all animals, it would be appropriate to genotype phenotypically contrasting selection candidates and use a Single-Step approach to obtain accurate and unbiased prediction of GEBV.
Publication Type: Journal Article
Source of Publication: Journal of Animal Breeding and Genetics, 136(5), p. 390-407
Publisher: Wiley-Blackwell Verlag GmbH
Place of Publication: Germany
ISSN: 1439-0388
0931-2668
Field of Research (FoR) 2008: 070201 Animal Breeding
060412 Quantitative Genetics (incl. Disease and Trait Mapping Genetics)
060408 Genomics
Field of Research (FoR) 2020: 300305 Animal reproduction and breeding
310506 Gene mapping
310509 Genomics
Socio-Economic Objective (SEO) 2008: 830399 Livestock Raising not elsewhere classified
Socio-Economic Objective (SEO) 2020: undefined
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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