10.5061/DRYAD.JB17N
Rabier, Charles-Elie
University of Toulouse
Barre, Philippe P.
Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères
Asp, Torben T.
Aarhus University
Charmet, Gilles G.
Genetics, Diversity and Ecophysiology of Cereals
Mangin, Brigitte B.
University of Toulouse
Data from: On the accuracy of genomic selection
Dryad
dataset
2017
Lolium perenne L.
plant growth rate
Genomic selection
2017-05-12T00:00:00Z
2017-05-12T00:00:00Z
en
https://doi.org/10.1371/journal.pone.0156086
3055774 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Genomic selection is focused on prediction of breeding values of selection
candidates by means of high density of markers. It relies on the
assumption that all quantitative trait loci (QTLs) tend to be in strong
linkage disequilibrium (LD) with at least one marker. In this context, we
present theoretical results regarding the accuracy of genomic selection,
i.e., the correlation between predicted and true breeding values.
Typically, for individuals (so-called test individuals), breeding values
are predicted by means of markers, using marker effects estimated by
fitting a ridge regression model to a set of training individuals. We
present a theoretical expression for the accuracy; this expression is
suitable for any configurations of LD between QTLs and markers. We also
introduce a new accuracy proxy that is free of the QTL parameters and
easily computable; it outperforms the proxies suggested in the literature,
in particular, those based on an estimated effective number of independent
loci (Me). The theoretical formula, the new proxy, and existing proxies
were compared for simulated data, and the results point to the validity of
our approach. The calculations were also illustrated on a new perennial
ryegrass set (367 individuals) genotyped for 24,957 single nucleotide
polymorphisms (SNPs). In this case, most of the proxies studied yielded
similar results because of the lack of markers for coverage of the entire
genome (2.7 Gb).
Data_files_Lolium_perenne_Rabier_et_al_2015_PLOS_ONEThe .zip file inclosed
two files: Phenotypic_data_RGA_PBarre_12112015 with the Plant growth rate
of 405 genotypes of perennial ryegrass and
Genotypic_data_RGA_PBarre_12112015 with the genotypic data (SNP scoring 0,
1, 2 and the average per marker for missing data) of the same 405
genotypes.Data_files_Lolium_perenne_Rabier_etal_2015.zip