Biology Reference
In-Depth Information
(B)
AT2G28810
AT3G60490
AT3G61850
AT1G64620
AT1G07640
AT4G00940
AT5G53980
AT5G60200
AT2G34710
AT5G60690
MIR399B
MIR168A
FIGURE 20.3
Gene regulatory network of the root vascular tissue. (A) The gene regulatory network generated through yeast one-hybrid analyses.
(B) Modeling strength of interactions using Bayesian inference based on the effect of mutations in upstream regulators on expression of downstream
targets. (Adapted from
[11]
.)
done by performing quantitative PCR on the transcripts of
target genes in the background of insertional mutants for the
upstream regulators. In Arabidopsis there is a low rate of
return on standard reverse genetics screens, which has been
attributed to a large amount of functional redundancy. In the
stele-specific gene regulatory network therewere many cases
of promoters being bound by more than one upstream regu-
lator. A potential reason for the observed high level of func-
tional redundancy was that transcription factors played
redundant roles in binding promoters. However, in over 60%
of the tested cases there was a reproducible change in
expression of the downstream gene in the presence of
a mutated upstream factor
[11]
. This suggested that the
reported redundancy is more likely to be a function of the
topology of the regulatory networks rather than the fact that
multiple transcription factors bind to the same promoter. The
direction of change in transcript level (up- or downregulated)
of the downstream target enabled the relationship to be
designated as that of either an activator or a repressor. In
addition to specifying the type of interaction, this analysis
quantified the extent of transcriptional change, which was
used to formulate a model that specified which regulators
played the most important roles in controlling downstream
expression (
Figure 20.3
B)
[11]
.
