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the shoot apex, indicating that spatiotemporal patterns of
gene expression in the shoot meristem have more
complexity than previously anticipated. It will be impor-
tant to extend this data set with more markers, which can
be chosen from the existing digital expression atlas, to
obtain a more complete picture of the shoot tran-
scriptome. One important addition to the current system
will be to find ways to extend this analysis from the
inflorescence meristem to the vegetative meristem, which
is deeply buried in leaves and therefore relatively inac-
cessible. Furthermore, it will be important to include
differentiating cells in shoot organs in the gene expression
maps. Only then will it be possible to compare shoot and
root transcriptomes with equal sensitivity and accurately
define genes as being root- or shoot-specific.
More recently, in line with the intertwined nature of shoot
development, multiple connections between the various
subnetworks have emerged through analysis of the target
genes of some of the key transcription factors. A genome-
wide identification of WUS response genes and WUS-
binding sites indicated that WUS mainly represses
transcripts within its expression domain in the RZ, and
indicated that among these repressed genes are positive
regulators for auxin signaling and negative regulators for
cytokinin signaling
[60]
. While this study reveals that WUS
likely acts through many target genes, the limited overlap
between WUS-binding sites and WUS-dependent expres-
sion indicates that caution is needed in attempts to identify
target genes of factors that act in very few cells.
Modeling Regulatory Networks in the Shoot
The many connections between regulatory subnetworks in
shoot development that have either been identified by
genetics or assumed from target gene lists indicate that the
control of shoot development is complex. In addition, the
processes that control shoot development operate at
different levels. For example, diffusible peptide signals are
coupled to transcriptional responses in different regions;
auxin transport, biosynthesis and perception are regulated
in distinct zones and must be considered in multicellular
context; and growth that is controlled by gene regulatory
networks leads to morphological changes that can subse-
quently influence signal flow and gene regulation. For these
reasons, a formal representation of our knowledge on
regulatory networks in the shoot and the use of computer
simulations to study network properties is necessary.
Without such analysis, it is not possible to understand the
morphogenetic properties of the system.
An example of the insights that modeling can offer
comes from attempts to understand the observed self-
organization of WUS expression after laser ablations
[61]
.
By implementing a reaction
Coupled Gene Regulatory Networks
in the Shoot
The intertwined nature of shoot development has also been
advantageous. The repetitive nature of development allows
initially subtle developmental distortions to be amplified.
This has facilitated the identification of numerous genes
which specifically affect shoot development (for recent
reviews see
[37
40]
). Traditionally, these pathways were
studied in relative isolation, leading to the description of
major subnetworks. Although the separation of the shoot
gene regulatory network has several characterizations, for
the purpose of this chapter it is sufficient to define four
major subnetworks. First,
e
the WUSCHEL (WUS)
e
CLAVATA3 (CLV3) feedback loop controls the size of the
stem cell domain by positive regulation of WUS tran-
scription factor-expressing organizing cells in the RZ on
CLV3-signal peptide-expressing stem cells, and repression
of WUS expression by CLV3 action (
Figure 20.1
)
[41
43]
.
Second, the CZ and PZ express the SHOOT MER-
ISTEMLESS (STM) transcription factor, which maintains
a mutual repression loop between STM family members
and the AS1 transcription factor specific to organ primordia
(
Figure 20. 1
)
[44,45]
. Third, a PIN
e
diffusion model on an
extracted cell template of the shoot apex, it was shown that
local activation of WUS yielded a central WUS domain that
was able to regenerate
[62]
. The CLV
e
auxin network regu-
lates auxin flow such that it converges on organ initiation
points (
Figure 20.1
)
[46
e
WUS loop was
modeled to explain how the WUS-expressing organizer
cells and the CLV3-expressing stem cells maintain each
other
[63]
. In addition, alternative feedback loops between
WUS expression and cytokinin signaling were modeled and
compared to experiment, supporting the hypothesis that the
WUS domain can be established in a stable zone through
which cells are traversing when cytokinin signaling influ-
ences WUS levels, cytokinin response regulators and the
CLV pathway
[59]
. Collectively, these models increasingly
pinpoint the function of feedback motifs in the regulation of
dynamic expression domains.
Insightful modeling has also been performed on the
PIN
e
adaxial
specific transcription factor network operates through
mutual inhibition and miRNA control to establish polar
domains on organ primordia and maintain stem cells
(
Figure 20.1
)
[49
48]
Fourth, an abaxial
e
e
55]
.
The genetic studies that identified the components of
the shoot regulatory network indicated early on that
connections between the various subnetworks exist. One
example is the discovery that the plant hormone cytokinin
is not only an important player in the STM pathway
[56,57]
, but at the same time the cytokinin response is
repressed by WUSCHEL
[58]
. In addition, cytokinins
suppress CLV1 levels as well as cytokinin sensitivity
[59]
.
e
auxin network that is associated with the patterned
e
