Literature DB >> 26523557

Should we use the single nucleotide polymorphism linked to in genomic evaluation of French trotter?

S Brard, A Ricard.   

Abstract

An A/C mutation responsible for the ability to pace in horses was recently discovered in the gene. It has also been proven that allele C has a negative effect on trotters' performances. However, in French trotters (FT), the frequency of allele A is only 77% due to an unexpected positive effect of allele C in late-career FT performances. Here we set out to ascertain whether the genotype at SNP (linked to ) should be used to compute EBV for FT. We used the genotypes of 630 horses, with 41,711 SNP retained. The pedigree comprised 5,699 horses. Qualification status (trotters need to complete a 2,000-m race within a limited time to begin their career) and earnings at different ages were precorrected for fixed effects and evaluated with a multitrait model. Estimated breeding values were computed with and without the genotype at SNP as a fixed effect in the model. The analyses were performed using pedigree only via BLUP and using the genotypes via genomic BLUP (GBLUP). The genotype at SNP was removed from the file of genotypes when already taken into account as a fixed effect. Alternatively, 3 groups of 100 candidates were used for validation. Validations were also performed on 50 random-clustered groups of 126 candidates and compared against the results of the 3 disjoint sets. For performances on which has a minor effect, the coefficients of correlation were not improved when the genotype at SNP was a fixed effect in the model (earnings at 3 and 4 yr). However, for traits proven strongly related to , the accuracy of evaluation was improved, increasing +0.17 for earnings at 2 yr, +0.04 for earnings at 5 yr and older, and +0.09 for qualification status (with the GBLUP method). For all traits, the bias was reduced when the SNP linked to was a fixed effect in the model. This work finds a clear rationale for using the genotype at for this multitrait evaluation. Genomic selection seemed to achieve better results than classic selection.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 26523557     DOI: 10.2527/jas.2015-9224

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


  1 in total

1.  GWAS by GBLUP: Single and Multimarker EMMAX and Bayes Factors, with an Example in Detection of a Major Gene for Horse Gait.

Authors:  Andres Legarra; Anne Ricard; Luis Varona
Journal:  G3 (Bethesda)       Date:  2018-07-02       Impact factor: 3.154

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.