Literature DB >> 27040784

Short communication: Improving accuracy of predicting breeding values in Brazilian Holstein population by adding data from Nordic and French Holstein populations.

X Li1, M S Lund2, Q Zhang3, C N Costa4, V Ducrocq5, G Su6.   

Abstract

The present study investigated the improvement of prediction reliabilities for 3 production traits in Brazilian Holsteins that had no genotype information by adding information from Nordic and French Holstein bulls that had genotypes. The estimated across-country genetic correlations (ranging from 0.604 to 0.726) indicated that an important genotype by environment interaction exists between Brazilian and Nordic (or Nordic and French) populations. Prediction reliabilities for Brazilian genotyped bulls were greatly increased by including data of Nordic and French bulls, and a 2-trait single-step genomic BLUP performed much better than the corresponding pedigree-based BLUP. However, only a minor improvement in prediction reliabilities was observed in nongenotyped Brazilian cows. The results indicate that although there is a large genotype by environment interaction, inclusion of a foreign reference population can improve accuracy of genetic evaluation for the Brazilian Holstein population. However, a Brazilian reference population is necessary to obtain a more accurate genomic evaluation.
Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BLUP; Holstein population; genotype by environment interaction; single-step genomic BLUP

Mesh:

Year:  2016        PMID: 27040784     DOI: 10.3168/jds.2015-10609

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


  4 in total

1.  The superiority of multi-trait models with genotype-by-environment interactions in a limited number of environments for genomic prediction in pigs.

Authors:  Hailiang Song; Qin Zhang; Xiangdong Ding
Journal:  J Anim Sci Biotechnol       Date:  2020-08-19

2.  Using imputation-based whole-genome sequencing data to improve the accuracy of genomic prediction for combined populations in pigs.

Authors:  Hailiang Song; Shaopan Ye; Yifan Jiang; Zhe Zhang; Qin Zhang; Xiangdong Ding
Journal:  Genet Sel Evol       Date:  2019-10-21       Impact factor: 4.297

3.  The theory on and software simulating large-scale genomic data for genotype-by-environment interactions.

Authors:  Xiujin Li; Hailiang Song; Zhe Zhang; Yunmao Huang; Qin Zhang; Xiangdong Ding
Journal:  BMC Genomics       Date:  2021-12-05       Impact factor: 3.969

Review 4.  Genomic Selection and Use of Molecular Tools in Breeding Programs for Indigenous and Crossbred Cattle in Developing Countries: Current Status and Future Prospects.

Authors:  Raphael Mrode; Julie M K Ojango; A M Okeyo; Joram M Mwacharo
Journal:  Front Genet       Date:  2019-01-09       Impact factor: 4.599

  4 in total

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