Genomic variance estimates: With or without disequilibrium covariances?
J Anim Breed Genet
; 134(3): 232-241, 2017 Jun.
Article
em En
| MEDLINE
| ID: mdl-28508483
ABSTRACT
Whole-genome regression methods are often used for estimating genomic heritability the proportion of phenotypic variance that can be explained by regression on marker genotypes. Recently, there has been an intensive debate on whether and how to account for the contribution of linkage disequilibrium (LD) to genomic variance. Here, we investigate two different methods for genomic variance estimation that differ in their ability to account for LD. By analysing flowering time in a data set on 1,057 fully sequenced Arabidopsis lines with strong evidence for diversifying selection, we observed a large contribution of covariances between quantitative trait loci (QTL) to the genomic variance. The classical estimate of genomic variance that ignores covariances underestimated the genomic variance in the data. The second method accounts for LD explicitly and leads to genomic variance estimates that when added to error variance estimates match the sample variance of phenotypes. This method also allows estimating the covariance between sets of markers when partitioning the genome into subunits. Large covariance estimates between the five Arabidopsis chromosomes indicated that the population structure in the data led to strong LD also between physically unlinked QTL. By consecutively removing population structure from the phenotypic variance using principal component analysis, we show how population structure affects the magnitude of LD contribution and the genomic variance estimates obtained with the two methods.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Variação Genética
/
Desequilíbrio de Ligação
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Arabidopsis
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Genômica
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Locos de Características Quantitativas
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
J Anim Breed Genet
Assunto da revista:
GENETICA
/
MEDICINA VETERINARIA
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Alemanha