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predict that false discovery rates (FDRs) would range between 0.05% and 3.00%,
based on dCHIP and gcRMA analyses (data not shown). Convincingly, we we able
to observe 24 essential genes and 17 embryo sac expressed genes at a fold change
range between 1.28 and 1.6. Moreover, our data on homology of candidate genes
to expressed sequence tags (ESTs) from monocot embryo sacs will facilitate careful
manual omission of false-positive findings. The usefulness of this approach is also
demonstrated by the observation that 84% of the essential genes and genes vali-
dated for embryo sac expression (n = 51) present in our datasets exhibited homol-
ogy to the monocot embryo sac ESTs. Therefore, our practical strategy of using
a low fold change cut-off probably helped in identifying low-abundance signals,
which would otherwise be ignored or handled in an ad hoc manner.
In contrast to the embryo sac datasets, we applied a more stringent twofold
higher expression as a baseline for comparison of the mutant sporophyte with
the wild type. This is because we had large amounts of sporophytic cells available
for comparison. In all, 527 genes were identified as candidate genes for gain of
sporophytic expression in coa and spl mutant ovules. Because the transcriptome
identified by three independent statistical methods and the resultant overlaps
were rather different in size for both the gametophytic and sporophytic datasets,
we report all the data across the three methods. This approach is validated by the
fact that candidate genes found using only one statistical method can indeed be
embryo sac expressed. Furthermore, only 8% of the validated genes (n = 51) were
consistently identified by all three methods, demonstrating the need for indepen-
dent statistical treatments. In short, our data analyses demonstrate the usefulness
of employing different statistical treatments for microarray data.
Another practical consideration following our data analyses was the very lim-
ited overlap between coa and spl datasets. Although both mutants are genetically
and phenotypically similar, the overlap is only 35 genes between the embryo sac
datasets and 13 genes between the sporophytic datasets. In light of the valida-
tion in expression for 12 genes from the coa dataset, which were not identified
from the spl dataset, we suggest that the limited overlap is not merely due to
experimental errors. It is likely that the embryo sac transcriptome is substantial
(several thousands of genes [2]), and two independent experiments identified dif-
ferent subsets of the same transcriptome. This is apparent from our validation of
expression for several genes, which were exclusively found in only one microarray
dataset. In terms of the sporophytic gene expression, we have shown that three
sporophytic genes initially identified only in the spl microarray dataset were in-
deed over-expressed in coa tissues (discussed below). In short, despite the limited
overlap between datasets, both the embryo sac and sporophytic datasets will be
very useful in elucidating embryo sac development and its control of sporophytic
gene expression.
