Literature DB >> 28464109

Technical note: Genomic evaluation for crossbred performance in a single-step approach with metafounders.

T Xiang, O F Christensen, A Legarra.   

Abstract

A single-step genomic BLUP method (ssGBLUP) has been successfully developed and applied for purebred and crossbred performance in pigs. However, it requires phasing the genotypes and inferring the breed origin of alleles in crossbred animals, which is somewhat inconvenient. Recently, a new concept of metafounders that considers the relationship within and across base populations was developed. With this concept of metafounders, regular methods to build and invert the pedigree relationships matrix can be used with only minor modifications and, moreover, genomic relationships and pedigree-based relationships are automatically compatible in the ssGBLUP. In this study, data for the total number of piglets born in Danish Landrace, Yorkshire, and 2-way crossbred pigs and models for purebred and crossbred performance were revisited by use of ssGBLUP with 2 metafounders. Genetic variances and genetic correlations between purebred and crossbred performances were first reestimated. Then, model-based reliabilities of purebred boars for their crossbred performance and predictive abilities for crossbred animals were compared in different scenarios. Results in this study were compared to those in a previous study with identical data but with models that required known breed origin of crossbred genotypes. Results show that relationships for base individuals within Landrace and within Yorkshire are similar and that the ancestor populations for Landrace and Yorkshire are related. In terms of model-based reliabilities and predictive abilities, ssGBLUP with metafounders performs at least as well as the single-step method requiring phasing at a lower complexity.

Entities:  

Mesh:

Year:  2017        PMID: 28464109     DOI: 10.2527/jas.2016.1155

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


  14 in total

1.  Genomic prediction for crossbred performance using metafounders.

Authors:  Elizabeth M van Grevenhof; Jérémie Vandenplas; Mario P L Calus
Journal:  J Anim Sci       Date:  2019-02-01       Impact factor: 3.159

2.  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

3.  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

4.  Genomic prediction using a reference population of multiple pure breeds and admixed individuals.

Authors:  Emre Karaman; Guosheng Su; Iola Croue; Mogens S Lund
Journal:  Genet Sel Evol       Date:  2021-05-31       Impact factor: 4.297

5.  Single-step genomic evaluation of Russian dairy cattle using internal and external information.

Authors:  Andrei A Kudinov; Esa A Mäntysaari; Timo J Pitkänen; Ekaterina I Saksa; Gert P Aamand; Pekka Uimari; Ismo Strandén
Journal:  J Anim Breed Genet       Date:  2021-11-28       Impact factor: 3.271

6.  Crossbred evaluations using single-step genomic BLUP and algorithm for proven and young with different sources of data1.

Authors:  Ivan Pocrnic; Daniela A L Lourenco; Ching-Yi Chen; William O Herring; Ignacy Misztal
Journal:  J Anim Sci       Date:  2019-04-03       Impact factor: 3.159

7.  Purebred and Crossbred Genomic Evaluation and Mate Allocation Strategies To Exploit Dominance in Pig Crossbreeding Schemes.

Authors:  David González-Diéguez; Llibertat Tusell; Alban Bouquet; Andres Legarra; Zulma G Vitezica
Journal:  G3 (Bethesda)       Date:  2020-08-05       Impact factor: 3.154

Review 8.  Non-additive Effects in Genomic Selection.

Authors:  Luis Varona; Andres Legarra; Miguel A Toro; Zulma G Vitezica
Journal:  Front Genet       Date:  2018-03-06       Impact factor: 4.599

9.  Estimates of genetic trend for single-step genomic evaluations.

Authors:  Karin Meyer; Bruce Tier; Andrew Swan
Journal:  Genet Sel Evol       Date:  2018-08-03       Impact factor: 4.297

10.  Bias and accuracy of dairy sheep evaluations using BLUP and SSGBLUP with metafounders and unknown parent groups.

Authors:  Fernando L Macedo; Ole F Christensen; Jean-Michel Astruc; Ignacio Aguilar; Yutaka Masuda; Andrés Legarra
Journal:  Genet Sel Evol       Date:  2020-08-12       Impact factor: 4.297

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.