Literature DB >> 34799109

Invited review: Unknown-parent groups and metafounders in single-step genomic BLUP.

Yutaka Masuda1, Paul M VanRaden2, Shogo Tsuruta3, Daniela A L Lourenco3, Ignacy Misztal3.   

Abstract

Single-step genomic BLUP (ssGBLUP) is a method for genomic prediction that integrates matrices of pedigree (A) and genomic (G) relationships into a single unified additive relationship matrix whose inverse is incorporated into a set of mixed model equations (MME) to compute genomic predictions. Pedigree information in dairy cattle is often incomplete. Missing pedigree potentially causes biases and inflation in genomic estimated breeding values (GEBV) obtained with ssGBLUP. Three major issues are associated with missing pedigree in ssGBLUP, namely biased predictions by selection, missing inbreeding in pedigree relationships, and incompatibility between G and A in level and scale. These issues can be solved using a proper model for unknown-parent groups (UPG). The theory behind the use of UPG is well established for pedigree BLUP, but not for ssGBLUP. This study reviews the development of the UPG model in pedigree BLUP, the properties of UPG models in ssGBLUP, and the effect of UPG on genetic trends and genomic predictions. Similarities and differences between UPG and metafounder (MF) models, a generalized UPG model, are also reviewed. A UPG model (QP) derived using a transformation of the MME has a good convergence behavior. However, with insufficient data, the QP model may yield biased genetic trends and may underestimate UPG. The QP model can be altered by removing the genomic relationships linking GEBV and UPG effects from MME. This altered QP model exhibits less bias in genetic trends and less inflation in genomic predictions than the QP model, especially with large data sets. Recently, a new model, which encapsulates the UPG equations into the pedigree relationships for genotyped animals, was proposed in simulated purebred populations. The MF model is a comprehensive solution to the missing pedigree issue. This model can be a choice for multibreed or crossbred evaluations if the data set allows the estimation of a reasonable relationship matrix for MF. Missing pedigree influences genetic trends, but its effect on the predictability of genetic merit for genotyped animals should be negligible when many proven bulls are genotyped. The SNP effects can be back-solved using GEBV from older genotyped animals, and these predicted SNP effects can be used to calculate GEBV for young-genotyped animals with missing parents. The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Entities:  

Keywords:  bias; genomic selection; pedigree; relationship matrix; single-step evaluation

Mesh:

Year:  2021        PMID: 34799109     DOI: 10.3168/jds.2021-20293

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  2 in total

1.  Accounting for population structure in genomic predictions of Eucalyptus globulus.

Authors:  Andrew N Callister; Matias Bermann; Stephen Elms; Ben P Bradshaw; Daniela Lourenco; Jeremy T Brawner
Journal:  G3 (Bethesda)       Date:  2022-08-25       Impact factor: 3.542

2.  International single-step SNPBLUP beef cattle evaluations for Limousin weaning weight.

Authors:  Renzo Bonifazi; Mario P L Calus; Jan Ten Napel; Roel F Veerkamp; Alexis Michenet; Simone Savoia; Andrew Cromie; Jérémie Vandenplas
Journal:  Genet Sel Evol       Date:  2022-09-04       Impact factor: 5.100

  2 in total

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