Molecular Plant Advance Access published April 18, 2013
Molecular Plant
LETTER TO THE EDITOR
TARGET: A Transient Transformation System
for Genome-Wide Transcription Factor Target
Discovery
measured in the presence or absence of the translation inhibitor cycloheximide (CHX), allowing for the distinction of direct
and indirect target genes of the TF under study (Supplementary
Data). pBeaconRFP_GR–ABI3 was used to transfect protoplasts
prepared from the roots of Arabidopsis seedlings, where ABI3,
known largely for its role in seed development, has also been
shown to be involved in development (Brady et al., 2003).
As a first test of the TARGET system, the expression of
known direct ABI3 targets PER1 and CRU3 was assayed by
qPCR. Compared to control gene expression, both PER1 and
CRU3 showed significant induction of transcript levels upon
DEX treatment in the ABI3–GR-transfected protoplasts in
the presence of CHX (Figure 1B and 1C, and Supplementary
Data). PER1 and CRU3 expression in protoplasts transformed
with an empty vector control showed no significant induction
by DEX treatment (Figure 1B and 1C). Significant induction
of CRU3 expression could only be measured when CHX was
present, indicating that the effects of CHX may in some cases
facilitate ABI3 function. Enhancement of ABA signaling
output by protein synthesis inhibitors that could explain this
phenomenon has been noted before by independent studies
(Reeves et al., 2011). For the transcriptomic analysis, using ATH1
Genome Array chips, a two-way analysis of variance (ANOVA)
was performed, followed by a Tukey post hoc test to identify
genes whose expression is differentially regulated in response
to DEX treatment in the absence or presence of CHX (p < 0.05,
fold change >1.5; Supplementary Data). Genes found to be
significantly regulated by DEX treatment in the empty vector
control were omitted from further analysis. This analysis yielded
a total of 668 unique genes whose expression was affected by
DEX-induced nuclear localization of ABI3, 227 regulated genes
without CHX, and 458 regulated genes with CHX (microarray
results were validated by qPCR; Supplementary Data). There
was just a 17-gene overlap with and without CHX, reiterating
that (as was seen for CRU3 in preliminary qPCR analysis) there
are many genes whose response to GR–ABI3 was facilitated by
the presence of the protein synthesis inhibitor CHX. The 210
genes regulated only in the absence of CHX were categorized
© The Author 2013. Published by the Molecular Plant Shanghai Editorial
Office in association with Oxford University Press on behalf of CSPB and
IPPE, SIBS, CAS.
doi: 10.1093/mp/sst010
Received 6 December 2012; accepted 13 January 2013
Downloaded from http://mplant.oxfordjournals.org/ by guest on April 24, 2013
Dear Editor,
Determining the fundamental structure of gene regulatory
networks (GRN) is a major challenge of systems biology. In
particular, inferring GRN structure from comprehensive gene
expression and transcription factor (TF)–promoter interaction data sets has become an increasingly sought-after aim in
both fundamental and agronomical research in plant biology
(Bonneau et al., 2007; Ruffel et al., 2010). A crucial step for the
assessment of GRN is the identification of the direct TF-target
genes. Transgenic plant lines expressing tagged versions of the
TF-of-interest can be used together with transcriptomic and
DNA-binding analyses to obtain high-confidence lists of direct
targets (e.g. Mönke et al., 2012). However, the generation of
such transgenics can be a limiting factor, especially in largescale studies or in non-model species. Transient transformation of protoplasts is therefore often employed for the study
of TF–promoter interactions, using co-expression of effector
constructs with a TF-of-interest and reporter constructs with a
promoter-of-interest. We have developed a rapid technique to
study the genome-wide effects of TF activation in protoplasts
that uses transient expression of a glucocorticoid receptor
(GR)-tagged TF. We demonstrate here that this system can be
used to rapidly retrieve information on direct target genes in
less than 2 weeks’ time. As a proof-of-principle candidate, we
used the well-studied TF, ABSCICIC ACID INSENSITIVE 3 (ABI3;
Koornneef et al., 1989; Mönke et al., 2012) and established
the de novo identification of the abscisic acid response element (ABRE) and a majority of the previously classified direct
targets. We have named this technique TARGET, for Transient
Assay Reporting Genome-wide Effects of Transcription factors.
Technically, plant protoplasts are transfected with a plasmid
(pBeaconRFP_GR) that expresses the TF-of-interest fused to GR,
which allows the controlled entry of the chimeric GR–TF into
the nucleus by addition of the GR–ligand dexamethasone (DEX;
Schena and Yamamoto, 1988). In addition, the vector contains a separate expression cassette with a positive fluorescent
selection marker (red fluorescent protein; RFP) which enables
fluorescence-activated cell sorting (FACS) of successfully transformed protoplasts (Figure 1A; Bargmann and Birnbaum, 2009).
This purification step allows reliable qPCR or transcriptomic
analysis of multiple independent transfections, which would
otherwise be hampered by the presence of a population of
untransformed cells that varies from experiment to experiment.
Lastly, the effect of target gene induction by DEX treatment is
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Letter to the Editor
as putative indirect targets of ABI3, whereas the 458 genes
regulated in the presence of CHX (186 induced and 272 repressed
genes) were designated as putative direct targets of ABI3.
The list of 186 putative direct up-regulated genes was highly
significantly enriched for genes previously identified as direct
targets of ABI3 in whole-plant studies (Ze = 54.3), as well as
targets of the maize homolog VIVIPAROUS1 (Ze = 20.8) and coregulator ABI5 (Ze = 20.9) (Figure 1D and 1E, and Supplementary
Data; Suzuki et al., 2003; Reeves et al., 2011; Mönke et al., 2012).
These significant intersections indicate that the activation of
ABI3 in protoplasts reflects the effects attributed to this transcriptional regulator in in planta studies. The list also showed a
significant overrepresentation of GO-terms, including response
to ABA, response to water deprivation, lipid storage, and embryo
development (no significant overlap or enrichments were found
in the lists of indirect targets or direct down-regulated targets;
Supplementary Data). Furthermore, promoter analysis of the
50 most strongly induced direct up-regulated genes found significant enrichment of previously identified ABRE-like elements
and the RY-repeat motif (Figure 1E and Supplementary Data).
De novo searches for recurring motifs within these promoters
(using two independent algorithms, MEME and MotifSampler)
yielded the recovery of the CACGTGKC ABRE (Figure 1F and
Supplementary Data). These results show the TARGET system
can be used successfully to investigate TF function in protoplasts with significance to whole plants.
One advantage of the TARGET system lies in the speed at
which identification of genome-wide TF targets can be performed. A candidate TF can now be scrutinized for its target
genes in a genome in a matter of weeks rather than the months
required for the generation of stable transgenic plant lines. The
TARGET transient transformation system can also be used purely
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Figure 1. The TARGET System for Rapid TF-Target Identification in Plant Protoplasts.
(A) The pBeaconRFP_GR vector contains a red fluorescent protein (RFP) positive selection cassette and a Gateway recombination cassette that is
in frame with the rat glucocorticoid receptor (GR) fusion protein. The plasmid is used to transfect protoplast suspensions, followed by treatment
with dexamethasone and/or cycloheximide and cell sorting of successful transformants for transcriptomic analysis.
(B, C) qPCR quantification of PER1 and CRU3 transcript levels in protoplasts transformed with pBeaconRFP_GR-ABI3 or an empty vector control and
treated with DEX and/or CHX. Averages ± SEM are presented. ns, not significant; * p < 0.05; *** p < 0.001. t-test DEX treatment n = 3.
(D) The intersection of 186 genes identified by TARGET (blue) as directly up-regulated by ABI3 and genes identified by previous studies as direct
up-regulated targets of ABI3 (98 genes; yellow), up-regulated targets of VP1 (51 genes; green), and ABI5 (59 genes; red).
(E) Network model of putative ABI3 (white triangle) connections to its direct up-regulated target genes via the RY-repeat motif (red square;
CATGCA) and through interaction with ABRE binding factors (ABFs; purple triangle) and ABRE (dark blue square; ACGTGKC) or the more degenerate G-box (blue square; CACGTG) and bZIP core (light-blue square; ACGTG) elements. Target genes (circles) are sized according to their strength of
induction and colored according to the overlap in (D).
(F) Weight matrix representation of the ABRE-like (CACGTGKC) motif retrieved by the MotifSampler and MEME algorithms from the 1 kb upstream
of the transcription start sites of the top 50 direct up-regulated ABI3 targets, Ze = 7.19 and Ze = 7.11, respectively. See Supplementary Data.
Letter to the Editor
SUPPLEMENTARY DATA
Supplementary Data are available at Molecular Plant Online.
FUNDING
This work was supported by EMBO (ALTF-185–2010 to I.E.), NIH
(NRSA-GM095273 to A.M.C., NHI-RO1-GM078270 to K.D.B.,
NIH-RO1-GM032877 to G.C.), NSF 2010 (NSF MCB-0929338 to
G.C.), ANR (NitroNet: ANR 11 PDOC 020 01 to G.K.), and the
CNRS (PEPS Bio math Info 2012–2013: SuperRegNet to G.K.).
No conflict of interest declared.
Bastiaan O.R. Bargmanna, Amy MarshallColona, Idan Efronia, Sandrine Ruffela,b,
Kenneth D. Birnbauma, Gloria M. Coruzzia,1 and
Gabriel Krouka,b,1
a Center for Genomics and Systems Biology, Department of Biology, New
York University, New York, NY 10003, USA
b Biochimie et Physiologie Moléculaire des Plantes, UMR 5004 CNRS/
INRA/SupAgro-M/UM2, Institut de Biologie Intégrative des Plantes-Claude
Grignon, Montpellier, France
1
To whom correspondence should be addressed. G.K. E-mail krouk@
supagro.inra.fr, gkrouk@gmail.com, tel. +0(33)499612518. G.M.C. E-mail
gloria.coruzzi@nyu.edu.
REFERENCES
Bargmann, B.O., and Birnbaum, K.D. (2009). Positive fluorescent
selection permits precise, rapid, and in-depth overexpression
analysis in plant protoplasts. Plant Physiol. 149, 1231–1239.
Bonneau, R., Facciotti, M.T., Reiss, D.J., Schmid, A.K., Pan, M.,
Kaur, A., Thorsson, V., Shannon, P., Johnson, M.H., Bare, J.C.,
et al. (2007). A predictive model for transcriptional control of
physiology in a free living cell. Cell. 131, 1354–1365.
Brady, S.M., Sarkar, S.F., Bonetta, D., and McCourt, P. (2003). The
ABSCISIC ACID INSENSITIVE 3 (ABI3) gene is modulated by
farnesylation and is involved in auxin signaling and lateral root
development in Arabidopsis. Plant J. Cell Mol. Biol. 34, 67–75.
Koornneef, M., Hanhart, C.J., Hilhorst, H.W., and Karssen, C.M.
(1989). In vivo Inhibition of seed development and reserve protein accumulation in recombinants of abscisic acid biosynthesis and responsiveness mutants in Arabidopsis thaliana. Plant
Physiol. 90, 463–469.
Mönke, G., Seifert, M., Keilwagen, J., Mohr, M., Grosse, I., Hahnel,
U., Junker, A., Weisshaar, B., Conrad, U., Baumlein, H., and
Altschmied, L. (2012). Toward the identification and regulation
of the Arabidopsis thaliana ABI3 regulon. Nucleic Acids Res. 40,
8240–8254.
Reeves, W.M., Lynch, T.J., Mobin, R., and Finkelstein, R.R. (2011).
Direct targets of the transcription factors ABA-Insensitive(ABI)4
and ABI5 reveal synergistic action by ABI4 and several bZIP ABA
response factors. Plant Mol. Biol. 75, 347–363.
Ruffel, S., Krouk, G., and Coruzzi, G.M. (2010). A systems view of
responses to nutritional cues in Arabidopsis: toward a paradigm shift for predictive network modeling. Plant Physiol.
152, 445–452.
Schena, M., and Yamamoto, K.R. (1988). Mammalian glucocorticoid receptor derivatives enhance transcription in yeast.
Science. 241, 965–967.
Sheen, J. (2001). Signal transduction in maize and Arabidopsis
mesophyll protoplasts. Plant Physiol. 127, 1466–1475.
Suzuki, M., Ketterling, M.G., Li, Q.B., and McCarty, D.R. (2003).
Viviparous1 alters global gene expression patterns through regulation of abscisic acid signaling. Plant Physiol. 132, 1664–1677.
Downloaded from http://mplant.oxfordjournals.org/ by guest on April 24, 2013
as a verification of specific TF-target interactions by qPCR, much
as yeast one-hybrid (Y1H) assays are often used, but now in the
context of endogenous gene activation in plant cells rather
than promoter binding in a yeast strain. The TARGET approach
brings the convenience of microbiological systems like Y1H to
the genome-wide transcriptomic capabilities of in planta studies. Another advantage of the use of protoplast transformation
in the TARGET system is that it can be done in a wide range of
species where the generation of transgenic plant lines is either
impossible or problematic and more time-consuming (Sheen,
2001). The TARGET system combined with RNA sequencing can
enable rapid and systematic assessment of TF function in numerous plant species, such as in important crop model species.
This system is not a replacement for in-depth studies using
transcriptional and chromatin immuno-precipitation (ChIP)
analyses in transgenic plants. Rather, TARGET is rapid tool
for GRN investigations that may have uses in particular circumstances. There are considerations associated with the
use of this system. On its own, a genome-wide analysis will
yield results that contain false-positives and false-negatives.
Identification of direct regulated genes by TARGET is therefore
not unequivocal; additional assays for direct TF-target interaction (e.g. ChIP, Y1H, gel shift assays) are required for definitive
identification of TF targets. The functionality of the chimeric
GR–TF is not tested in this system, other than by the substance
of the results. CHX treatment by itself may have effects on
transcription that influence the DEX effect on certain direct
target genes. Lastly, the cellular dissociation procedure itself
may induce gene expression responses that could conceal the
effects of TF activation. We therefore envisage two ways of
using the TARGET system: either in combination with other
techniques to get high-confidence target lists for a particular
TF or as a high-throughput analysis of numerous TFs in a given
GRN to get a broad view of putative interactions.
Overall, the results presented here demonstrate that TARGET
represents a novel and rapid transient system for TF investigation that can be used to help map GRN. Important indications of
TF operation, such as direct target genes, biological function by
GO-term associations, and cis-regulatory elements involved in its
action can be obtained in a rapid and straightforward manner.
The proof-of-principle analysis with ABI3 offers a new dataset
of transcripts affected by this TF, adding to our understanding of
the downstream significance of this central regulator.
The pBeaconRFP_GR vector will be made available through
the VIB website (http://gateway.psb.ugent.be/).
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