Impact of the size of the reference population and kinship degree on low density genotyping strategies for genotype imputation in layer chickens
Résumé
The main goal of selection is to choose breeders of the next generation among a set of
selection candidates. In genomic selection, the choice of breeders rests on the use of information on
DNA polymorphisms, in particular SNP, in addition of performance measures. Since 2013, a
commercial high density genotyping chip (600,000 markers) for chicken allowed the
implementation of genomic selection in layer and broiler breeding. However, genotyping costs with
this chip still remain high for a routine use on a large number of selection candidates. Consequently,
it is interesting to develop, at a lower cost, low density genotyping chips. To do so, a set of SNP
markers has to be selected to enable an imputation (prediction) of missing genotypes on a high
density chip (HD chip). This imputation enables to predict missing genotypes of all selection
candidates from high density genotyping of a reference population with phenotypes.
In this perspective, according to the reference population, various simulation studies were
conducted to choose the best strategy for low density genotyping of laying hen lines. Two different
low density genotyping chips of 10K SNP were designed according to two methodologies: a choice
of SNP depending on a clustering based on linkage disequilibrium threshold or a choice of SNP at
regular intervals (kb) along each chromosome. Imputation accuracy was assessed as the mean
correlation between true and imputed genotypes. Focusing on populationnal factors that can
influence imputation accuracy, it is shown that imputation accuracy improves with an increase in
the size of the reference population. By decreasing the kinship degree between reference and
candidate population, it is seen that imputation accuracy decreases. Most importantly, results show
that a key point in getting good imputations is to have the direct parents in the reference population.
Finally, all different genotyping strategies focused on population factors show that linkage
disequilibrium methodology enables to get better results of imputation than with equidistant
methodology.
Format : Poster
Loading...