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Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection

Authors :
Taiana Lopes Rangel Miranda
Marcos Deon Vilela de Resende
Camila Ferreira Azevedo
Andrei Caíque Pires Nunes
Elizabete Keiko Takahashi
Guilherme Ferreira Simiqueli
Fabyano Fonseca e Silva
Rodrigo Silva Alves
TAIANA LOPES RANGEL MIRANDA, UFV
MARCOS DEON VILELA DE RESENDE, CNPCa
CAMILA FERREIRA AZEVEDO, UFV
ANDREI CAÍQUE PIRES NUNES, UNIVERSIDADE FEDERAL DO SUL DA BAHIA
ELIZABETE KEIKO TAKAHASHI, CELULOSE NIPO-BRASILEIRA S.A
GUILHERME FERREIRA SIMIQUELI, UFV
FABYANO FONSECA E SILVA, UFV
RODRIGO SILVA ALVES, UFLA.
Source :
Scientia Agricola, Volume: 79, Issue: 6, Article number: e20210074, Published: 01 NOV 2021, Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice), Empresa Brasileira de Pesquisa Agropecuária (Embrapa), instacron:EMBRAPA, Scientia Agricola, Vol 79, Iss 6 (2021), Scientia Agricola v.79 n.6 2022, Scientia Agrícola, Universidade de São Paulo (USP), instacron:USP
Publication Year :
2022
Publisher :
FapUNIFESP (SciELO), 2022.

Abstract

The Fisher?s infinitesimal model is traditionally used in quantitative genetics and genomic selection, and it attributes most genetic variance to additive variance. Recently, the dominance maximization model was proposed and it prioritizes the dominance variance based on alternative parameterizations. In this model, the additive effects at the locus level are introduced into the model after the dominance variance is maximized. In this study, the new parameterizations of additive and dominance effects on quantitative genetics and genomic selection were evaluated and compared with the parameterizations traditionally applied using the genomic best linear unbiased prediction method. As the parametric relative magnitude of the additive and dominance effects vary with allelic frequencies of populations, we considered different minor allele frequencies to compare the relative magnitudes. We also proposed and evaluated two indices that combine the additive and dominance variances estimated by both models. The dominance maximization model, along with the two indices, offers alternatives to improve the estimates of additive and dominance variances and their respective proportions and can be successfully used in genetic evaluation. Made available in DSpace on 2022-01-19T16:00:25Z (GMT). No. of bitstreams: 1 evaluation-of-a-new-additive.pdf: 725842 bytes, checksum: 2c26fbbce6a08e566a87f91bb64eca59 (MD5) Previous issue date: 2022

Details

ISSN :
1678992X
Volume :
79
Database :
OpenAIRE
Journal :
Scientia Agricola
Accession number :
edsair.doi.dedup.....1644b57eb9b0243e303726df72076538