Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1080149
Research center of Embrapa/Collection: Embrapa Recursos Genéticos e Biotecnologia - Artigo em periódico indexado (ALICE)
Date Issued: 2017
Type of Material: Artigo em periódico indexado (ALICE)
Authors: MÜLLER, B. S. F.
NEVES, L. G.
ALMEIDA FILHO, J. E. de
RESENDE JUNIOR, M. F. R.
MUÑOZ, P. R.
SANTOS, P. E. T. dos
PALUDZYSZYN FILHO, E.
KIRST, M.
GRATTAPAGLIA, D.
Additional Information: BÁRBARA S. F. MÜLLER, UNB; LEANDRO G. NEVES, RAPID GENOMICS LLC, USA; JANEO E. DE ALMEIDA FILHO, UNIVERSITY OF FLORIDA, USA; MÁRCIO F. R. RESENDE JÚNIRO, RAPID GENOMICS LLC, USA; PATRICIO R. MUÑOZ, UNIVERSITY OF FLORIDA, USA; PAULO EDUARDO TELLES DOS SANTOS, CNPF; ESTEFANO PALUDZYSZYN FILHO, CNPF; MATIAS KIRST, UNIVERSITY OF FLORIDA, USA; DARIO GRATTAPAGLIA, Cenargen.
Title: Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus.
Publisher: BMC Genomics, v. 18, article 524, 2017. 17 p.
Language: pt_BR
Keywords: Genomic selection
GWAS
Seleção genômica
SNP genotyping
Espécie exótica
Description: Background: The advent of high-throughput genotyping technologies coupled to genomic prediction methods established a new paradigm to integrate genomics and breeding. We carried out whole-genome prediction and contrasted it to a genome-wide association study (GWAS) for growth traits in breeding populations of Eucalyptus benthamii (n =505) and Eucalyptus pellita (n =732). Both species are of increasing commercial interest for the development of germplasm adapted to environmental stresses. Results: Predictive ability reached 0.16 in E. benthamii and 0.44 in E. pellita for diameter growth. Predictive abilities using either Genomic BLUP or different Bayesian methods were similar, suggesting that growth adequately fits the infinitesimal model. Genomic prediction models using ~5000?10,000 SNPs provided predictive abilities equivalent to using all 13,787 and 19,506 SNPs genotyped in the E. benthamii and E. pellita populations, respectively. No difference was detected in predictive ability when different sets of SNPs were utilized, based on position (equidistantly genome-wide, inside genes, linkage disequilibrium pruned or on single chromosomes), as long as the total number of SNPs used was above ~5000. Predictive abilities obtained by removing relatedness between training and validation sets fell near zero for E. benthamii and were halved for E. pellita. These results corroborate the current view that relatedness is the main driver of genomic prediction, although some short-range historical linkage disequilibrium (LD) was likely captured for E. pellita. A GWAS identified only one significant association for volume growth in E. pellita, illustrating the fact that while genome-wide regression is able to account for large proportions of the heritability, very little or none of it is captured into significant associations using GWAS in breeding populations of the size evaluated in this study. Conclusions: This study provides further experimental data supporting positive prospects of using genome-wide data to capture large proportions of trait heritability and predict growth traits in trees with accuracies equal or better than those attainable by phenotypic selection. Additionally, our results document the superiority of the whole-genome regression approach in accounting for large proportions of the heritability of complex traits such as growth in contrast to the limited value of the local GWAS approach toward breeding applications in forest trees.
Thesagro: Eucalipto
Melhoramento genético vegetal
NAL Thesaurus: Eucalyptus benthamii
Eucalyptus pellita
genetic relationships
marker-assisted selection
plant breeding
Data Created: 2017-11-20
Appears in Collections:Artigo em periódico indexado (CENARGEN)

Files in This Item:
File Description SizeFormat 
s1286401739202.pdf1,74 MBAdobe PDFThumbnail
View/Open

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace