Issue |
Genet. Sel. Evol.
Volume 36, Number 1, January-February 2004
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|
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Page(s) | 29 - 48 | |
DOI | https://doi.org/10.1051/gse:2003049 |
DOI: 10.1051/gse:2003049
The effect of using approximate gametic variance covariance matrices on marker assisted selection by BLUP
Liviu R. Totira, Rohan L. Fernandoa, b, Jack C.M. Dekkersa, b, Soledad A. Fernándezc and Bernt Guldbrandtsenda Department of Animal Science, Iowa State University, Ames, IA 50011, USA
b Lawrence H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, IA 50011, USA
c Department of Statistics, The Ohio State University, Columbus, OH 43210, USA
d Danish Institute of Animal Science, Foulum, Denmark
(Received 19 September 2002; accepted 13 May 2003)
Abstract
Under additive inheritance, the Henderson mixed model equations (HMME)
provide an efficient approach to obtaining genetic evaluations by marker
assisted best linear unbiased prediction (MABLUP) given pedigree
relationships, trait and marker data. For large pedigrees with many
missing markers, however, it is not feasible to calculate the exact
gametic variance covariance matrix required to construct HMME. The
objective of this study was to investigate the consequences of using
approximate gametic variance covariance matrices on response to
selection by MABLUP. Two methods were used to generate approximate
variance covariance matrices. The first method (Method A) completely
discards the marker information for individuals with an unknown linkage
phase between two flanking markers. The second method (Method B) makes
use of the marker information at only the most polymorphic marker
locus for individuals with an unknown linkage phase. Data sets were
simulated with and without missing marker data for flanking markers
with 2, 4, 6, 8 or 12 alleles. Several missing marker data patterns
were considered. The genetic variability explained by marked
quantitative trait loci (MQTL) was modeled with one or two MQTL of
equal effect. Response to selection by MABLUP using Method A or Method
B were compared with that obtained by MABLUP using the exact genetic
variance covariance matrix, which was estimated using 15 000 samples
from the conditional distribution of genotypic values given the
observed marker data. For the simulated conditions, the superiority of
MABLUP over BLUP based only on pedigree relationships and trait data
varied between
and
for Method A, between
and
for Method B, and between
and
for the exact
method. The relative performance of the methods under investigation
was not affected by the number of MQTL in the model.
Key words: marker assisted selection / BLUP / gametic variance covariance matrix
Correspondence and reprints: ltotir@iastate.edu
© INRA, EDP Sciences 2004