Literature DB >> 27065256

Application of single-step genomic evaluation for crossbred performance in pig.

T Xiang, B Nielsen, G Su, A Legarra, O F Christensen.   

Abstract

Crossbreding is predominant and intensively used in commercial meat production systems, especially in poultry and swine. Genomic evaluation has been successfully applied for breeding within purebreds but also offers opportunities of selecting purebreds for crossbred performance by combining information from purebreds with information from crossbreds. However, it generally requires that all relevant animals are genotyped, which is costly and presently does not seem to be feasible in practice. Recently, a novel single-step BLUP method for genomic evaluation of both purebred and crossbred performance has been developed that can incorporate marker genotypes into a traditional animal model. This new method has not been validated in real data sets. In this study, we applied this single-step method to analyze data for the maternal trait of total number of piglets born in Danish Landrace, Yorkshire, and two-way crossbred pigs in different scenarios. The genetic correlation between purebred and crossbred performances was investigated first, and then the impact of (crossbred) genomic information on prediction reliability for crossbred performance was explored. The results confirm the existence of a moderate genetic correlation, and it was seen that the standard errors on the estimates were reduced when including genomic information. Models with marker information, especially crossbred genomic information, improved model-based reliabilities for crossbred performance of purebred boars and also improved the predictive ability for crossbred animals and, to some extent, reduced the bias of prediction. We conclude that the new single-step BLUP method is a good tool in the genetic evaluation for crossbred performance in purebred animals.

Entities:  

Mesh:

Year:  2016        PMID: 27065256     DOI: 10.2527/jas.2015-9930

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  15 in total

1.  Genomic selection in American mink (Neovison vison) using a SSGBLUP model for size and quality traits graded on live mink.

Authors:  Trine M Villumsen; Guosheng Su; Bernt Guldbrandtsen; Torben Asp; Mogens S Lund
Journal:  J Anim Sci       Date:  2021-01-08       Impact factor: 3.159

2.  Including crossbred pigs in the genomic relationship matrix through utilization of both linkage disequilibrium and linkage analysis.

Authors:  M W Iversen; Ø Nordbø; E Gjerlaug-Enger; E Grindflek; M S Lopes; T H E Meuwissen
Journal:  J Anim Sci       Date:  2017-12       Impact factor: 3.159

3.  Genomic predictions in purebreds with a multibreed genomic relationship matrix1.

Authors:  Yvette Steyn; Daniela A L Lourenco; Ignacy Misztal
Journal:  J Anim Sci       Date:  2019-11-04       Impact factor: 3.159

4.  Genomic Prediction Methods Accounting for Nonadditive Genetic Effects.

Authors:  Luis Varona; Andres Legarra; Miguel A Toro; Zulma G Vitezica
Journal:  Methods Mol Biol       Date:  2022

5.  Genomic evaluation for a three-way crossbreeding system considering breed-of-origin of alleles.

Authors:  Claudia A Sevillano; Jeremie Vandenplas; John W M Bastiaansen; Rob Bergsma; Mario P L Calus
Journal:  Genet Sel Evol       Date:  2017-10-23       Impact factor: 4.297

6.  Efficient genetic value prediction using incomplete omics data.

Authors:  Matthias Westhues; Claas Heuer; Georg Thaller; Rohan Fernando; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2019-01-17       Impact factor: 5.699

7.  Genetic parameters and purebred-crossbred genetic correlations for growth, meat quality, and carcass traits in pigs.

Authors:  Hadi Esfandyari; Dinesh Thekkoot; Robert Kemp; Graham Plastow; Jack Dekkers
Journal:  J Anim Sci       Date:  2020-12-01       Impact factor: 3.159

8.  Genomic evaluation by including dominance effects and inbreeding depression for purebred and crossbred performance with an application in pigs.

Authors:  Tao Xiang; Ole Fredslund Christensen; Zulma Gladis Vitezica; Andres Legarra
Journal:  Genet Sel Evol       Date:  2016-11-25       Impact factor: 4.297

9.  Genomic selection for crossbred performance accounting for breed-specific effects.

Authors:  Marcos S Lopes; Henk Bovenhuis; André M Hidalgo; Johan A M van Arendonk; Egbert F Knol; John W M Bastiaansen
Journal:  Genet Sel Evol       Date:  2017-06-26       Impact factor: 4.297

10.  Balanced selection on purebred and crossbred performance increases gain in crossbreds.

Authors:  Hadi Esfandyari; Peer Berg; Anders Christian Sørensen
Journal:  Genet Sel Evol       Date:  2018-03-22       Impact factor: 4.297

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.