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First published online 13 December 2006
doi: 10.1242/dev.02746
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1 Max Planck Institute for Developmental Biology, Spemanstrasse 37-39, D-72076
Tübingen, Germany.
2 Department of Molecular Biology, Spemanstrasse 37-39, D-72076 Tübingen,
Germany.
Author for correspondence (e-mail:
ingrid.lohmann{at}tuebingen.mpg.de)
Accepted 1 November 2006
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SUMMARY |
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SUMMARY
INTRODUCTION
MATERIALS AND METHODS
RESULTS
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Key words: Drosophila, Deformed, Morphogenesis, Realizators, Microarray, Hox downstream target genes
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INTRODUCTION |
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MATERIALS AND METHODS
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;
Mann and Morata, 2000;
McGinnis and Krumlauf, 1992).
In Drosophila, Hox genes are expressed in defined domains along the
AP axis, and their activity assigns distinct morphologies to the various body
segments (McGinnis and Krumlauf,
1992). In addition, Hox genes are very often expressed in
overlapping domains and crossregulate each other
(McGinnis and Krumlauf, 1992;
Miller et al., 2001).
Consequently, loss of function of one Hox gene frequently leads to the ectopic
expression of neighboring Hox genes, which is one of the reasons for the
drastic homeotic transformations of body segments initially identified by Ed
Lewis (Lewis, 1978).
Therefore, only a subset of Hox functions can be identified in
loss-of-function mutants.
Hox genes code for transcription factors with a highly conserved
DNA-binding domain, the homeodomain
(McGinnis et al., 1984;
Scott and Weiner, 1984), and
it has been postulated that Hox proteins direct morphogenesis by regulating
appropriate sets of downstream genes in a segment-specific manner
(Graba et al., 1997;
Hombria and Lovegrove, 2003).
Although a wide range of strategies has been used to identify Hox downstream
genes (Graba et al., 1997;
Hombria and Lovegrove, 2003;
Pradel and White, 1998), our
knowledge of their nature is still limited. Initial attempts have focused on
in vitro studies or on heterologous systems; however, Hox proteins acquire
DNA-binding specificity mostly through interactions with various co-factors in
vivo (Ebner et al., 2005;
Gebelein et al., 2004;
Mahaffey, 2005;
Mann, 1995;
Mann and Affolter, 1998).
Therefore, most known Hox downstream genes have been identified by candidate
gene approaches based on expression patterns or similar mutant phenotypes
(Pearson et al., 2005),
highlighting the power of in vivo strategies to identify Hox target genes.
This notion is further supported by recent successful approaches combining
loss- or gain-of-function alleles of Hox genes and microarray experiments to
identify Hox downstream genes on a larger scale
(Cobb and Duboule, 2005;
Hedlund et al., 2004;
Lei et al., 2005;
Williams et al., 2005). Still,
most previous efforts were biased toward the identification of direct Hox
target genes, and, while knowledge of direct Hox targets is a prerequisite to
understanding how Hox proteins acquire DNA-binding specificity in vivo, we
need to know the entire Hox-dependent regulatory network with all its tiers of
regulatory interactions to understand how Hox proteins control morphogenesis
on a cellular level.
Most of the known Hox downstream genes code either for transcription
factors or for signaling molecules
(Hombria and Lovegrove, 2003;
Pearson et al., 2005). These
two classes represent the top tiers of regulatory cascades and are able to
coordinate many downstream events. Hence, they are not informative for
elucidating the role of Hox proteins in the specification of morphological
properties on a cellular level per se. To this end, the functional analysis of
the so-called realizators, which directly influence the morphology by
regulating cytodifferentiation processes
(Garcia-Bellido, 1975;
Pradel and White, 1998), is
required. Unfortunately, even though the concept of realizators was postulated
more than 30 years ago, so far very few Hox realizator genes have been
identified and studied mechanistically
(Bello et al., 2003;
Lohmann et al., 2002). One
well-studied example of a realizator gene in Drosophila is the
apoptosis-inducing gene reaper (rpr), which is expressed in
the maxillary segment in Drosophila embryos and is directly
controlled by the Hox protein Deformed (Dfd)
(Lohmann et al., 2002). In
addition, the Dfd-dependent expression of rpr and, consequently, the
activation of apoptosis was shown to be necessary and sufficient for the
maintenance of the boundary between the maxillary and mandibular segments of
the embryonic head (Lohmann et al.,
2002). This is one of the few examples demonstrating how a Hox
protein can execute, via a single realizator gene, one specific aspect of
segmental morphology on the cellular level. To understand and mechanistically
link the many remaining Hox functions with morphogenetic outputs, we need to
quantitatively identify Hox downstream genes. Functional analysis of this set
will then allow us to elucidate all tiers of interactions within the
Hox-regulatory network, and to establish links between Hox genes and
realizator genes. This seems fundamental for a complete understanding of the
role of Hox genes in development and evolution.
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MATERIALS AND METHODS |
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),
UAS-Abd-A from A. M. Michelson
(Michelson, 1994) and
UAS-hepact. from M. Mlodzik
(Weber et al., 2000). For
trans-heterozygous mutants the following alleles were used:
Dfdr11 and Dfdw21 from W. McGinnis;
Scr1, Scr4, Abd-BM2,
wgl-12 and wgl-17 from the Bloomington
Stock Center; and Abd-BM5 from C. Nüsslein-Volhard
(Tübingen Drosophila Stock Collection). Dfd mutant
embryos for BrdU staining were
Dfdw21/TM3Sb[twi::GFP] crossed to
Dfdr11/TM3Sb[twi::GFP] and homozygous
Dfd mutants (Dfdw21/Dfdr11)
were identified by absence of GFP signal.
Plasmids
cDNAs were from the Drosophila Genomics Resource Center:
CG5080 (LD34147), CG7447 (LD16414), disco
(GH27656), Dll (LP01770), ImpL2 (SD07266), gt
(RE29225), sage (RE59356), skl (RE14076), spz
(SD07354), LysE (LP07339), CG8193 (GH07976), CG3097
(RE43153), Mp20 (RE55741), CG17052 (LD43683), Ance
(LD11258), Hsp23 (LD06759), sn (RH62992), mas
(LP06006), pav (RE22456), wrapper (GH03113), wg
(RE02607) and W (AT13267). prd cDNA was from W. McGinnis,
Eip63E cDNA and predicted Dfd response elements tested by EMSA were
PCR amplified, cloned and sequenced. Expression plasmids for Dfd and Ubx were
obtained from W. McGinnis and S. Carroll, respectively.
Histology and scanning electron microscopy
In situ hybridization and immunochemistry were performed as described
(Bergson and McGinnis, 1990;
Tautz and Pfeifle, 1989), and
BrdU labeling and scanning electron microscopy were done as described
(Dolbeare and Selden, 1994;
Lohmann et al., 2002). Hox
protein expression was measured by the fluorescent intensity of a standardized
area of individual nuclei using the Zeiss LSM 510 META confocal microscope.
Twenty nuclei of four independent embryos were analyzed for each expression
domain and genotype. Antibodies were: anti-Dfd, W. McGinnis; anti-Scr,
anti-Antp, anti-Abd-B and anti-wg, Developmental Studies Hybridoma Bank (Iowa,
University), anti-Ubx, R. White (Cambridge); anti-Abd-A, I. W. Duncan
(Washington, University); anti-GFP, Torrey Pines Biolabs (Houston); anti-BrdU,
Roche; anti-mouse AlexaFluor 488, anti-guinea pig AlexaFluor 488 and
anti-rabbit AlexaFluor 488, Molecular Probes.
Microarray experiments
Microarray hybridizations were carried out as described
(Schmid et al., 2003) in
biological triplicates with RNA from pools of stage 11 or stage 12 embryos.
Raw data were quantile normalized and expression estimates were calculated
using gcRMA (Wu et al., 2004)
implemented in R. Statistical testing for differential expression was carried
out using LogitT (Lemon et al.,
2003). Microarray data discussed here have been deposited with
ArrayExpress database at the EBI
(http://www.ebi.ac.uk/arrayexpress-old/;
Accession number E-MEXP-879). For analysis of gene ontology categories, GO
lists from FlyBase were used. Genes were sorted using a combination of
molecular and biological GO terms. Genes containing the following description
in their GO annotations were classified as realizators: apoptosis, cell death,
cell adhesion, cell shape, cell cycle, mitosis, cell proliferation,
cytoskeleton, proteolysis, peptidolysis, cytoskeleton, structural constituent
of larval cuticle or peritrophic membrane.
Quantitative real-time PCR
Quantitative real-time PCR (qRT-PCR) was carried out in triplicates from
RNA of pooled tissue as described (Schmid
et al., 2003) using SYBR-green QPCR Master Mix (Invitrogen).
Expression of ß-Tubulin was used for crossexperiment
normalization. Primer and probe sequences are available upon request.
Bioinformatics
For cluster identification the Cis-Analyst algorithm
(Berman et al., 2004) was used
with a Position-Frequency-Matrix (PFM) based on DNaseI footprint data
(Bergman et al., 2005) and
consensus sequences from the literature. The PFM shown in Fig. S1B in the
supplementary material was generated by PATSER. To define enhancer parameters,
such as length of enhancer, number of Dfd-binding sites per enhancer, distance
between binding sites, known Dfd-dependent enhancers were analyzed. The
parameters identified, as shown in Fig. S1B in the supplementary material,
were used to predict clusters of Dfd-binding sites in the regulatory regions
of selected genes in Drosophila melanogaster. To this end, intergenic
and intronic sequences of D. melanogaster were aligned to a multiple
sequence file, sorted and separated to segment-files, which included
annotation information. The PATSER program used these segment-files as a
template to generate P-values for each Dfd-binding site identified
according to the PFM. Using this binding site information, clusters of
Dfd-binding sites were predicted using the standalone version of
cis-Analyst-helper. To validate this approach statistically and to optimize
the parameters chosen, Dfd downstream genes identified in the microarray
experiment were used. The logic of this approach is based on the assumption
that direct Dfd target genes should be enriched among the Dfd downstream genes
identified in the microarray experiment when compared with randomly selected
genes. To identify Dfd clusters in other Drosophila species (D.
simulans, D. yakuba, D. erecta, D. pseudoobscura), a NCBI BLAST search
was performed. To consider clusters as being conserved, the following
conservation criteria had to be fulfilled: (1) conservation of the enhancer in
at least two other Drosophila species; (2) the length of the
homologues enhancer had to be 
50% of the enhancer length identified in
D. melanogaster; (3) conservation of at least two Dfd-binding sites
within the conserved enhancer elements; and (4) conserved enhancers with less
then 50% of length conservation but more then two Dfd-binding sites conserved
were treated as minor hits. Conserved enhancers were ranked according to the
following parameters: (1) evolutionary distance of Drosophila
species; (2) overall sequence similarity of conserved enhancers; (3) numbers
of binding sites present in conserved clusters; and (4) degree of variation in
enhancer length. Binding site matches for other transcription factors located
in the Hox response elements were identified by using rVISTA, Transfac and
Jasper databases.
Electrophoretic mobility shift assays
Electrophoretic mobility shift assays (EMSAs) were performed as described
(Lohmann et al., 2002).
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RESULTS |
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MATERIALS AND METHODS
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)
(Fig. 1A; for endogenous
expression of Hox proteins see Fig.
1E). The Hox genes labial (lab) and
proboscipedia (pb) were not included, as a similar study has
been performed for lab (Leemans
et al., 2001), and as pb mutant embryos do not exhibit
any obvious defects (Wakimoto et al.,
1984). We opted to use overexpression instead of a
loss-of-function experiments for several reasons. First, the analysis of Hox
mutants is complicated by the extensive crossregulatory interactions of Hox
genes (Gould et al., 1997;
Miller et al., 2001); loss of
expression of one Hox gene often results in ectopic expression of other Hox
genes, thereby obscuring the effects on downstream genes. Another important
limitation of a loss-of-function approach in conjunction with microarray
analysis is sensitivity; due to the small expression domains of many Hox genes
(McGinnis and Krumlauf, 1992;
Pearson et al., 2005), locally
restricted differences in gene expression caused by Hox mutations will be
diluted in RNA isolated from whole embryos, and therefore many downstream
genes might not be detected. Isolation of cells expressing individual Hox
genes by cell sorting (Wang et al.,
2006) could provide a means to circumvent this problem; however,
the required reporter genes that are expressed in specific Hox domains,
although independent from Hox gene activity, currently do not exist.
Conversely, although ectopic expression of one Hox gene affects the expression
of other Hox genes, their ubiquitous overexpression should allow us to even
detect genes whose expression is only weakly, or locally, affected, because
the Hox expression domains are expanded manyfold and consequently their
transcriptional output is amplified. To achieve ubiquitous Hox overexpression
in the desired stages of development, we used an armadillo
(arm)-GAL4 driver line (Sanson et
al., 1996), which confers ubiquitous expression starting at stage
10, as judged from analyzing GFP activity in embryos carrying an additional
UAS-2xEGFP transgene (Fig.
1A). Previous studies have shown that ubiquitous overexpression of
Hox genes in UAS fly strains, which were also used in our study, is sufficient
to induce ectopic differentiation of Hox-dependent structures without
affecting the development of early embryonic stages in an unspecific manner
(Li et al., 1999). Thus, a
substantial part of Hox downstream genes seem to be responsive to Hox
signaling even at ectopic locations and should be detectable by microarray
analysis.
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For the microarray experiment, total RNA from arm::lacZ
(control), arm::Dfd, arm::Scr, arm::Antp,
arm::Ubx, arm::abd-A and arm::Abd-B
embryos collected separately at the different stages was prepared and
hybridized in biological triplicates to Affymetrix Drosophila Genome
1 arrays, which contains probe sets interrogating more than 13,500 genes. A
combination of per-gene (Lemon et al.,
2003) and common variance (>1.5-fold change) filtering was used
to identify 1508 Hox responsive genes (Table S1, Table S2, Table S3, Table S4,
Table S5 and Table S6 in the supplementary material). This list contained six
of the 18 genes previously shown to be under Hox control during stages 11 and
12 (Fig. 2A), and in situ
hybridizations for three of these transcripts confirmed the microarray results
(Fig. 2A). The fact that we
were only able to recover one-third of the known Hox targets can be explained
by a number of differences between our experimental setup and the ones used
before, such as detection method
(Capovilla et al., 2001;
Mahaffey et al., 1993), timing
and level of overexpression (Feinstein et
al., 1995), and use of mutants instead of overexpression
(Mahaffey et al., 1993;
Ryoo and Mann, 1999). Based on
this observation, it is conceivable that the actual number of all Hox
downstream genes is two- to threefold the number we have discovered in our
study, which is still significantly lower than previously suggested
(Liang and Biggin, 1998). The
microarray data also showed that anterior Hox genes were repressed by those
normally expressed more posteriorly (data not shown), a crossregulatory
interaction known as posterior suppression
(Miller et al., 2001). Again,
we could confirm the microarray data by performing antibody stainings for all
Hox proteins on embryos ubiquitously misexpressing either Dfd or Abd-B
(Fig. 2B).
Verification of Hox downstream genes identified in the microarray analysis
To verify differential expression of the newly identified genes at the
cellular level, we carried out in situ hybridization on embryos misexpressing
the various Hox genes (Fig. 3;
see Fig. S1 in the supplementary material). Twenty-four of the 25 randomly
selected genes that showed a specific in situ signal behaved as observed in
the microarray experiment. In addition, for a selected subset of seven genes
Hox-dependent regulation could also be shown in Hox mutants
(Fig. 3), demonstrating the
power of the initial microarray experiment. For example, three transcripts
found to be induced by Dfd in the microarray experiment were sickle
(skl), a known apoptosis activator
(Wing et al., 2002),
CG5080, a gene putatively involved in cytoskeletal regulation
(Jasper et al., 2001), and
CG7447, a gene of unknown function. In situ analysis confirmed strong and
ectopic induction of all three genes in response to Dfd misexpression
(Fig. 3B,F,J), and showed that
their expression in the maxillary segment was lost in Dfd mutants
(Fig. 3D,H,L). Similarly, mRNA
levels of salivary gland-expressed bHLH (sage), a
transcription factor gene exclusively expressed in the salivary gland
primordium (Chandrasekaran and Beckendorf,
2003), were increased in response to ectopic Scr activity
(Fig. 3N). By contrast,
sage expression was abolished in Scr mutants
(Fig. 3P), consistent with Scr
being a master regulator of salivary gland morphogenesis
(Panzer et al., 1992). Among
the genes that were induced by Abd-B were Ecdysone-inducible gene L2
(ImpL2), putatively involved in cell adhesion
(Garbe et al., 1993), and
spätzle (spz), which encodes a Toll receptor ligand
involved in embryonic axis specification
(DeLotto et al., 2001). Again,
we observed strong ectopic expression of ImpL2 and spz in
arm::Abd-B embryos (Fig.
3R,V), whereas expression in the posterior end was lost in
Abd-B mutants (Fig.
3T,X). In summary, in situ hybridization with probes for 24
randomly selected genes (Fig.
3; see Fig. S1 in the supplementary material) not only confirmed
the microarray results, but also demonstrated that many of the identified Hox
downstream genes responded in a converse manner in the respective Hox
mutants.
Direct versus indirect Hox downstream genes
To understand the logic of Hox-dependent morphogenesis, it is important to
place the newly identified downstream genes within the underlying regulatory
hierarchy. To this end, we developed a bioinformatics tool to detect direct
Hox target genes, based on the identification of evolutionarily conserved
clusters of Hox consensus binding sites in the genome (see Materials and
methods and Fig. S2 in the supplementary material for detail). Using this
approach, we were able to identify a large number of putative direct targets
of Dfd. From the 240 genes found to be significantly regulated by Dfd, 75 had
clusters of Dfd-binding sites (31% of all identified Dfd responsive genes),
which was significantly more than expected by chance (P<0.001). In
addition, 46 of these clusters were well conserved in at least two other
Drosophila species (19% of all identified Dfd responsive genes) (see
Tables S7 and S8 in the supplementary material). Most of the predicted Dfd
response elements also contained binding sites for other transcription factors
(data not shown), a known prerequisite for functional enhancer elements
(Berman et al., 2004). We
randomly selected six of the 75 predicted Dfd response elements and performed
EMSA to test whether Dfd protein could bind to these elements. All enhancer
elements tested were bound by Dfd in vitro
(Fig. 4), whereas Ubx, a Hox
protein specifying trunk identity, was not able to interact with these
enhancers (see Fig. S2C in the supplementary material). In addition,
competition experiments showed that Dfd specifically bound some, but not all,
of the predicted Dfd-binding sites in these enhancers
(Fig. 4A-D), demonstrating that
the simple presence of a consensus binding site is not sufficient for Dfd
binding in the context of these enhancers in vitro and/or that some of the
predicted sites are not functional in vivo. Based on our results with Dfd, it
seems likely that about 20 to 30% of the identified downstream genes are
direct Hox targets. In sum, the combination of microarray analysis with
bioinformatics approaches will allow us in the future to not only identify
direct Hox target genes, but also to construct complete Hox-regulatory
networks.
Specificity of Hox-dependent regulation
To assess the specificity of Hox gene regulation, the 1508 responsive genes
were classified according to the number of Hox proteins that influenced their
expression and the influence of the developmental stage. Remarkably, most
downstream genes (1039, 68.9%) were affected by only a single Hox protein,
with Abd-A having a very high proportion of unique response genes (two-thirds
of its downstream genes were unique), whereas the fraction of unique response
genes was smaller (18 to 36%) for the other Hox genes
(Fig. 5A). The use of various
statistical cut-offs showed that this result is not an artifact of arbitrary
thresholding (data not shown). In addition, we were able to confirm the
specificity of the Hox response by analyzing the expression of some of the
unique downstream genes by in situ hybridizations in embryos misexpressing any
of the Hox genes (see Fig. S3 in the supplementary material). About one-third
of the identified downstream genes (449, 29.8%) were affected by several Hox
proteins, and only 20 genes (1, 3%) responded to all Hox proteins,
representing the classes of regional and common downstream genes, respectively
(Fig. 5A). Even when we
excluded the Abd-A experiment, which was performed slightly differently from
the rest of the set and therefore could interfere with this type of analysis,
the result did not change: 63% of the genes were uniquely regulated by only
one Hox protein, 34.5% of the genes by some and 2.5% by all Hox proteins
(Fig. 5A). Remarkably, among
the predicted direct Dfd target genes the distribution of unique and regional
Hox downstream genes was similar to their distribution among all identified
Hox downstream genes (Fig. 5B).
Taken together, these results indicate that the specific effects of Hox
proteins on morphology are largely mediated by regulatory interactions with
uniquely regulated downstream genes, and that despite the very similar
DNA-binding sequences for all Hox proteins observed in vitro
(Ekker et al., 1994), the
overlap of commonly regulated genes in vivo is relatively small.
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; Mahaffey,
2005; Merabet et al.,
2005). To confirm stagespecific regulation of Hox downstream genes
on a cellular level, we performed in situ hybridizations for some of the
differentially expressed genes (Fig.
5D), and indeed found that most of these genes were Hox responsive
primarily at one of the two stages (Fig.
5D).
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Since the realizator gene concept was postulated almost 30 years ago
(Garcia-Bellido, 1975), but
only a few such genes have previously been identified as Hox downstream genes
in Drosophila, we decided to study this class of Hox response genes
in more detail. Among the realizators, the largest subgroup comprises genes
involved in proteolytic processes, followed by genes with cytoskeleton
functions, a diverse group containing cuticle, chorion and peritrophic
membrane genes, cell cycle or cell proliferation genes, apoptosis or cell
death genes and cell adhesion genes (Fig.
6B). Genes within realizator subclasses are often coordinately
regulated: most apoptotic (7/8) and cell cycle or proliferation genes (18/21)
were activated, whereas almost all cell adhesion genes (12/14) and the
majority of genes involved in proteolytic processes (56/75) were repressed by
Hox proteins (Fig. 6C).
Re-analyzing data from a more restricted microarray study, a similar trend can
be identified for lab, another Hox gene
(Leemans et al., 2001): one
apoptotic gene and six cell cycle or cell proliferation genes were activated,
whereas three cell adhesion genes were all repressed by lab. This
suggests that a variety of cellular processes need to be regulated in a
coordinated fashion in every segment in order to realize common aspects of
segmental morphology. Support for this notion also comes from a previous
analysis in Drosophila, showing that two Hox proteins, Dfd and Abd-B,
locally activate the apoptosis gene rpr and thus the apoptotic
machinery at segment boundaries for their maintenance
(Lohmann et al., 2002).
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).
Another example for a strong correlation of differences in morphology and the
differential regulation of shared downstream genes is the Scr-Abd-A pair. In
this case, opposite regulation was found for 58% (n=55) of the
targets shared by Scr and Abd-A, in line with the very different morphologies
specified by these two Hox proteins (Fig.
6D). Again, two selected examples, pipe and
PH4
SG2, both activated by Scr and repressed by Abd-A
(see Table S2 and Table S5 in the supplementary material), are known to be
expressed exclusively in the Scr-specified salivary glands at stages 11 and 12
(Abrams and Andrew, 2002;
Zhu et al., 2005).
Interestingly, it has been shown only recently that pipe,
differentially regulated by Dfd and Abd-A, and PAPS synthetase,
differentially regulated by Scr and Dfd in our microarray analysis, are both
necessary for the production of sulfated macromolecules in the salivary glands
of Drosophila embryos (Zhu et
al., 2005). Thus, it seems that the diversification of segments is
achieved, on the one hand, through the regulation of unique downstream genes,
and, on the other hand, through the differential regulation of shared
downstream genes.
A framework for the morphogenesis of the maxillary segment
To analyze the morphogenetic function of Hox responsive genes in more
detail, we focused on the potential role of several newly identified Dfd
downstream genes during the development of the maxillary segment. It has long
been known that Dfd is expressed in the maxillary and mandibular segments, and
is necessary for the morphological specializations (mouth hooks, cirri,
ventral organ) of these head segments
(McGinnis et al., 1990).
However, only a single cellular event necessary for the morphogenesis of the
maxillary segment and under the control of Dfd has been explained
mechanistically so far: the maintenance of the boundary between the maxillary
and mandibular segments, which is dependent on Dfd-mediated activation of
rpr expression in the anterior part of the maxillary segment
(Lohmann et al., 2002).
Consistently, rpr was found among the activated Dfd downstream genes
in our microarray analysis (see Table S1 in the supplementary material).
Another prominent feature of Dfd mutants is the displacement of
maxillary and mandibular segments to a more dorsal position, caused by the
accumulation of supernumerary cells at the ventral side of both segments,
which had been observed almost 20 years ago
(Fig. 7B)
(Regulski et al., 1987). There
are two alternative explanations for this defect: loss of cell death and/or
overactivation of cell proliferation. Consistent with the former explanation,
we observed reduced local expression of the apoptosis activator skl
(Fig. 7K,P), one of the newly
identified genes activated by Dfd, and a concurrent reduction in the number of
apoptotic cells at the ventral side of the maxillary segment in Dfd
mutants (data not shown) (Lohmann et al.,
2002). Additionally, we were able to show that cell proliferation
at the ventral region of the maxillary segment is increased in Dfd
mutant embryos by performing BrdU labeling experiments
(Fig. 7E,J). This might be
attributed to the de-repression of two genes identified as repressed by Dfd in
this study (see Table S1 in the supplementary material): Ecdysone-induced
protein 63E (Eip63E), encoding a cyclin-dependent protein kinase
(Stowers et al., 2000), and
wingless (wg), encoding a signaling molecule known to play a
role in cell proliferation (Giraldez and
Cohen, 2003). In line with a role of these genes in shaping the
maxillary segment, we found that both genes are ectopically expressed in the
dorsal part of the maxillary segment in Dfd mutants
(Fig. 7Q,R). Although the
function of Eip63E during the morphogenesis of the maxillary segment
could not be analyzed due to the lack of mutants, we could confirm that
wg mutants have reduced gnathal lobes
(Fig. 7D)
(Rusch and Kaufman, 2000),
suggesting an important role of wg in the regulation of cell
proliferation in the maxillary segment. The third notable defect of
Dfd mutants is the loss of the maxillary cirri primordium
(Regulski et al., 1987).
paired (prd), one of the transcription factor genes
identified in our screen (see Table S1 in the supplementary material), is
known to be important for development of cirri and the maxillary ventral organ
(Vanario-Alonso et al., 1995).
Because late prd expression is completely under the control of Dfd
(Fig. 7N,S), we conclude that
some aspects of ventral maxillary identity are specified by Dfd via
prd regulation. Finally, we analyzed Dfd-dependent regulation of cell
shape changes, because cells at ventral positions of wild-type maxillary
segments are round (Fig. 7G),
whereas in Dfd mutants many appeared elongated
(Fig. 7H). The JNK pathway has
been implicated in cell shape changes in Drosophila, for example
during embryonic dorsal closure and adult thorax closure
(Harden, 2002;
Xia and Karin, 2004) and
because we had identified several genes responsive to the JNK pathway
(Jasper et al., 2001)
[Ras-related protein (Rala), Angiotensin converting
enzyme (Ance) and CG5080] (see Table S1 in the
supplementary material) as Dfd downstream genes, we tested the contribution of
the JNK pathway to the cell shape phenotype of Dfd mutants. After
ubiquitous activation of the JNK pathway by overexpressing a constitutively
active form of Hemipterous (Weber et al.,
2000) using the arm-GAL4 driver, we observed elongated
cells in the maxillary segment (Fig.
7I), as well as in other parts of the embryo (data not shown). As
we could confirm for one of the JNK-responsive Dfd downstream genes,
CG5080, implicated in the regulation of cytoskeletal dynamics
(Jasper et al., 2001), strong
upregulation by Dfd (Fig. 7T),
we conclude that the JNK pathway plays a major role in organizing cell shapes
in the maxillary segment.
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). Until
now much effort has gone into elucidating the nature and function of all three
hierarchical levels, with a substantial amount of knowledge having accumulated
at the activator and selector level. It is now well established that a genetic
cascade comprising maternal and various classes of segmentation genes regulate
the temporal and spatial expression of a unique combination of Hox genes in
different segments, which subsequently specifies the identities of individual
segments (McGinnis and Krumlauf,
1992; St Johnston and
Nusslein-Volhard, 1992). Additionally, the discovery that Hox
proteins act as transcriptional regulators established the general view that
each segment will enter a specific morphogenetic program and develop unique
shape and function depending on Hox downstream genes, in particular the
realizator genes. Although the question of Hox downstream gene identity and
function is not a novel problem, and although a considerable amount of
progress has been made in recent years, our knowledge of their nature and
function is still far from complete, especially with regard to the realizator
genes in the sense of Garcia-Bellido.
|
;
Pearson et al., 2005;
Pradel and White, 1998). This
was puzzling, as the primary function of Hox proteins is to specify the
morphology of different segments, thus one would have expected to find a bias
toward realizators. Moreover, this finding established the view that most of
the cellular responses mediated by Hox proteins, including realizator
functions, are indirectly influenced through the action of intermediate
regulatory molecules. Our analysis of Hox downstream genes in
Drosophila, which was designed to allow for a quantitative
identification of Hox-regulatory networks (including most realizator genes),
revealed that a major group of genes responsive to Hox input did indeed code
for realizators. Therefore, our results constitute the first experimental
support of the concept postulated by Garcia-Bellido more than three decades
ago. We could furthermore show that a substantial part of the Hox output is
directly transferred to the realizator level, suggesting that intermediate
regulators might play a smaller role than previously thought. One possible
explanation why so few Hox realizators had been identified before is that most
realizators will be required for general functions in many cells.
Consequently, mutations in realizator genes are likely to result either in
early embryonic lethality or in pleiotropic effects, making it difficult to
correlate their phenotypes to those found in Hox mutants. In addition, it
seems likely that realizators act redundantly or have very subtle effects,
making their identification in forward genetic screens extremely difficult.
Similarly, individual mutations in all known guidance factors for border cell
migration in Drosophila produce either no, or only mild, defects and
thus they could be identified only by expression profiling studies
(Wang et al., 2006). In this
study we have quantitatively identified Hox realizator genes by a comparative
microarray analysis, which now can serve as a resource to study the mechanisms
of segmental morphogenesis. Focusing on the differentiation of the maxillary
segment, we were able to functionally correlate all major morphological
defects observed in Dfd mutants with newly identified Dfd downstream
genes, many of which code for realizators, demonstrating the validity of this
approach.
|
; Carr and Biggin,
1999; Ekker et al.,
1994; Walter and Biggin,
1996), whereas many of the identified Hox downstream genes are
uniquely regulated by only a single Hox protein. This contrast may be
explained by our observation that the majority of genes are primarily
regulated at only one of the two stages, implicating that Hox proteins
excessively interact with the regulatory environment in which they are
embedded. Support for the notion that co-factor interactions have a major
impact on Hox output also comes from a recent study, which has provided direct
evidence that Hox proteins gain the ability to regulate their target genes in
a context-specific manner by interaction with known cell- and/or
tissue-specific transcription factors in vivo
(Gebelein et al., 2004). In
addition, this study also suggests that a large number of transcription
factors might function as Hox co-factors, which could dictate the outcome of
Hox gene action. Along these lines, we found that ubiquitous overexpression of
Hox proteins never caused ubiquitous activation of downstream genes, but that
ectopic expression was always locally restricted, suggesting that regional
transcription factors are essential for Hox output. This is also reflected in
our finding that conserved clusters of Hox binding sites in the regulatory
regions of direct targets frequently contain binding sites for unrelated
transcription factors. Taken together, these results support the hypothesis
put forward by Michael Akam in 1998, that "we should think of the Hox
genes with their short and relatively non-specific target sequences, as
cofactors that modify the actions of other more specific transcription
factors, rather than proteins in need of cofactors themselvess"
(Akam, 1998).
Supplementary material
Supplementary material for this article is available at
http://dev.biologists.org/cgi/content/full/134/2/381/DC1
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ACKNOWLEDGMENTS |
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Footnotes |
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REFERENCES |
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TOP
SUMMARY
INTRODUCTION
MATERIALS AND METHODS
RESULTS
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