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The impact of information
quantity and strength of relationship between training set
and validation set on accuracy of genomic estimated breeding
values
M. Saatchi*, S. R.
Miraei-Ashtiani, A. Nejati Javaremi, M. Moradi-Shahrebabak
and H. Mehrabani-Yeghaneh
Department of Animal Science, University College of
Agriculture and Natural Resource, University of Tehran,
Karaj, Iran.
*Corresponding author. E-mail:
saatchi.mahdi@gmail.com.
Tel: +989121915461. Fax: +982612246752.
Accepted
20 August, 2009 |
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Recent
advances in genomic selection are a revolution in animal
breeding. A genome consisting 10 chromosomes each with 100
cM in length with 100 equally spaced markers (1 cM) were
simulated. After 50 generations of random mating in a finite
population (Ne = 100) in order to create
sufficient linkage disequilibrium, population was expanded
to two different population sizes of 500 and 1000. This
structure was conserved until generation 59. Only females of
generations 51 to 58 had phenotypic records and were
included in the training set. The generation 59 was assumed
as juveniles without any phenotypic records (validation
set). Two measures of heritability (h2 = 0.1 and
h2 = 0.5) were considered. Each simulation was
replicated 10 times and results were averaged across
replications. The results showed that using individuals of
more recent generations in training set led to higher
accuracy of genomic estimated breeding values (GEBVs) than
individuals from more distant generations. However, increase
in the amount of phenotypic records in training set even
from individuals of older generations will increase accuracy
of GEBVs. Number of phenotypic records in training set was
shown to have important role in accuracy of GEBVs especially
for low heritability traits.
Key
words:
Genomic selection, GEBVs, training set, validation set,
generation distance. |
