February 10, 2004, Lauren McIntyre, Ohio State Statistics Seminar
Genetics, Genomics and Genetical Genomics: Analysis of Partial
Diallel Designs
Lauren McIntyre
Purdue University
Abstract
Classic quantitative Genetics uses breeding designs to assist in
inferences about mechanisms of genetic variation. The diallel, and
partial diallel is a tool to understanding the nature of phenotypic
variation. The generalization of the partial diallel analysis for a
problem in wheat breeding, led to the ability to use this design in
a genomic context. Microarray technology permits an examination of
genetic variation at the level of mRNA abundance. Utilizing a
partial diallel design, we present a quantitative description of
variation in mRNA abundance in terms of GCA (general combining
ability, or additive variance) and SCA (specific combining ability,
primarily dominance variance). We test whether features significant
for GCA and SCA are randomly distributed across chromosomes, and use
a nonparametric approach to demonstrate that the magnitude of the
variation is not random for GCA. We find that there is an excess of
significant features for SCA on the X chromosome relative to the
autosomes, and a paucity of features significant for GCA on the X
relative to the autosomes. The overall magnitude of the effects for
GCA on the X tends to be lower than on the autosomes, and is
contributed by rare alleles of larger effect. This non-random
patterning of genetic variation in gene expression data with respect
to chromosomal context suggests the action of selection.