Prediction of the reliability of genomic breeding values for crossbred performance

Genetics, Selection, Evolution : GSE
Jeremie VandenplasM P L Calus

Abstract

In crossbreeding programs, various genomic prediction models have been proposed for using phenotypic records of crossbred animals to increase the selection response for crossbred performance in purebred animals. A possible model is a model that assumes identical single nucleotide polymorphism (SNP) effects for the crossbred performance trait across breeds (ASGM). Another model is a genomic model that assumes breed-specific effects of SNP alleles (BSAM) for crossbred performance. The aim of this study was to derive and validate equations for predicting the reliability of estimated genomic breeding values for crossbred performance in both these models. Prediction equations were derived for situations when all (phenotyping and) genotyping data have already been collected, i.e. based on the genetic evaluation model, and for situations when all genotyping data are not yet available, i.e. when designing breeding programs. When all genotyping data are available, prediction equations are based on selection index theory. Without availability of all genotyping data, prediction equations are based on population parameters (e.g., heritability of the traits involved, genetic correlation between purebred and crossbred performance, effective ...Continue Reading

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Citations

Oct 25, 2017·Genetics, Selection, Evolution : GSE·Claudia A SevillanoMario P L Calus
Apr 9, 2020·Journal of Animal Science·Ignacy MisztalAndres Legarra
May 28, 2019·Frontiers in Genetics·Claudia A SevillanoMario P L Calus
Jul 17, 2020·Frontiers in Genetics·Joana StockRobin Wellmann
Oct 12, 2020·Journal of Animal Breeding and Genetics = Zeitschrift Für Tierzüchtung Und Züchtungsbiologie·Jovana Marjanovic, Mario P L Calus
Nov 8, 2020·Genetics, Selection, Evolution : GSE·Yvonne C J WientjesMario P L Calus

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Methods Mentioned

BETA
genotyping

Software Mentioned

calc
grm
BSAM
QMSim
mathop
ASGM

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