New accuracy estimators for genomic selection with application in a cassava (Manihot esculenta) breeding program.
Genomic selection is the main force driving applied breeding programs and accuracy is the main measure for evaluating its efficiency. The traditional estimator (TE) of experimental accuracy is not fully adequate. This study proposes and evaluates the performance and efficiency of two new accuracy estimators, called regularized estimator (RE) and hybrid estimator (HE), which were applied to a practical cassava breeding program and also to simulated data. The simulation study considered two individual narrow sense heritability levels and two genetic architectures for traits. TE, RE, and HE were compared under four validation procedures: without validation (WV), independent validation, ten-fold validation through jacknife allowing different markers, and with the same markers selected in each cycle. RE presented accuracies closer to the parametric ones and less biased and more precise ones than TE. HE proved to be very effective in the WV procedure. The estimators were applied to five traits evaluated in a cassava experiment, including 358 clones genotyped for 390 SNPs. Accuracies ranged from 0.67 to 1.12 with TE and from 0.22 to 0.51 with RE. These results indicated that TE overestimated the accuracy and led to one accuracy estimate (1.12) higher than one, which is outside of the parameter space. Use of RE turned the accuracy into the parameter space. Cassava breeding programs can be more realistically implemented using the new estimators proposed in this study, providing less risky practical inferences.
Departamento de Estatística, Universidade Federal de Viçosa, Viçosa, MG, Brasil camila.azevedo@ufv.br.
C F
CF
Azevedo
Departamento de Estatística, Universidade Federal de Viçosa, Viçosa, MG, Brasil.|Embrapa Floresta, Colombo, PR, Brasil.
M D V
MD
Resende
Departamento de Zootecnia, Universidade Federal de Viçosa, Viçosa, MG, Brasil.
F F
FF
Silva
Departamento de Biologia Geral, Universidade Federal de Viçosa, Viçosa, MG, Brasil.
J M S
JM
Viana
Departamento de Biologia Geral, Universidade Federal de Viçosa, Viçosa, MG, Brasil.
M S F
MS
Valente
RAPiD Genomics, Florida Innovation Hub, Gainesville, FL, USA.
M F R
MF
Resende
Embrapa Mandioca e Fruticultura, Cruz das Almas, BA, Brasil.
E J
EJ
Oliveira
D001947:Breeding; D018745:Genome, Plant; D023281:Genomics / Q000379:methods*; D040582:Inheritance Patterns / Q000235:genetics; D002365:Manihot / Q000235:genetics*; D019655:Quantitative Trait, Heritable; D012641:Selection, Genetic