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Transcriptome analysis of germinating maize kernels exposed to smoke-water
and the active compound KAR1
BMC Plant Biology 2010, 10:236 doi:10.1186/1471-2229-10-236
Vilmos Soos (soosv@mail.mgki.hu)
Endre Sebestyen (sebestyene@mail.mgki.hu)
Angela Juhasz (juhasza@mail.mgki.hu)
Marnie Light (melight@gmail.com)
Ladislav Kohout (kohout@uochb.cas.cz)
Gabriella Szalai (szalaig@mail.mgki.hu)
Julia Tandori (tandorij@mail.mgki.hu)
Johannes van Staden (VanStadenJ@ukzn.ac.za)
Ervin Balazs (balazs@mail.mgki.hu)
ISSN 1471-2229
Article type Research article
Submission date 7 April 2010
Acceptance date 2 November 2010
Publication date 2 November 2010
Article URL http://www.biomedcentral.com/1471-2229/10/236
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1
Transcriptome analysis of germinating maize kernels
exposed to smoke-water and the active compound KAR1

Vilmos Soós1§, Endre Sebestyén1§, Angéla Juhász1, Marnie E. Light2, Ladislav Kohout3,
Gabriella Szalai4, Júlia Tandori4, Johannes Van Staden2, Ervin Balázs1§*
1 Department of Applied Genomics, Agricultural Research Institute of the Hungarian
Academy of Sciences, H-2462 Martonvásár, Brunszvik u. 2, Hungary
2 Research Centre for Plant Growth and Development, School of Biological and Conservation
Sciences, University of KwaZulu-Natal Pietermaritzburg, Private Bag X01, Scottsville 3209,
South Africa
3
Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech
Republic, v.v.i., Flemingovo nám. 2, 166 10 Prague 6, Czech Republic
4 Department of Plant Physiology, Agricultural Research Institute of the Hungarian Academy
of Sciences, H-2462 Martonvásár, Brunszvik u. 2, Hungary
§
These authors contributed equally to this work
* Corresponding author
Email addresses:
VS: soosv@mail.mgki.hu
ES: sebestyene@mail.mgki.hu
AJ: juhasza@mail.mgki.hu
MEL: melight@gmail.com
LK: kohout@uochb.cas.cz
GS: szalaig@mail.mgki.hu
JT: tandorij@mail.mgki.hu
JvS: vanstadenj@ukzn.ac.za
EB: balazs@mail.mgki.hu

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Abstract

Background
Smoke released from burning vegetation functions as an important environmental signal
promoting the germination of many plant species following a fire. It not only promotes the
germination of species from fire-prone habitats, but several species from non-fire-prone areas
also respond, including some crops. The germination stimulatory activity can largely be
attributed to the presence of a highly active butenolide compound, 3-methyl-2H-furo[2,3-
c]pyran-2-one (referred to as karrikin 1 or KAR1), that has previously been isolated from
plant-derived smoke. Several hypotheses have arisen regarding the molecular background of
smoke and KAR1 action.

Results
In this paper we demonstrate that although smoke-water and KAR1 treatment of maize kernels
result in a similar physiological response, the gene expression and the protein ubiquitination
patterns are quite different. Treatment with smoke-water enhanced the ubiquitination of
proteins and activated protein-degradation-related genes. This effect was completely absent
from KAR1-treated kernels, in which a specific aquaporin gene was distinctly upregulated.

Conclusions
Our findings indicate that the array of bioactive compounds present in smoke-water form an
environmental signal that may act together in germination stimulation. It is highly possible
that the smoke/KAR1 ‘signal’ is perceived by a receptor that is shared with the signal
transduction system implied in perceiving environmental cues (especially stresses and light),
or some kind of specialized receptor exists in fire-prone plant species which diverged from a
more general one present in a common ancestor, and also found in non fire-prone plants
allowing for a somewhat weaker but still significant response. Besides their obvious use in
agricultural practices, smoke and KAR1 can be used in studies to gain further insight into the
transcriptional changes during germination.

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Background

Smoke released by natural fires is a major environmental cue in fire-prone habitats and a wide
range of species show enhanced germination responses after exposure to aerosol smoke or
smoke-water. In addition, several species from non-fire prone regions, and some major crops
respond to various smoke treatments. Smoke can also positively affect the post-germination
stage resulting in increased seedling vigour [1]. Efforts to identify the active compound from
smoke-water resulted in the characterization of 3-methyl-2H-furo[2,3-c]pyran-2-one using
achenes of Lactuca sativa cv. Grand Rapids [2] or the seeds of Conostylis aculeata and
Stylidium affine [3] as germination test systems. This butenolide-type compound promotes
germination over a very wide range of concentrations, from 10-4 M down to 10-9 M, spanning
five orders of magnitude [4], and the action of smoke in promoting the germination of seeds
of many species is mainly attributed to the presence of this compound in smoke. Currently, at
least five analogues of KAR1 (referred as KAR2-KAR6 [5]) can be found in smoke and some
of these are likely to contribute to the overall germination promoting activity of smoke
extracts. In addition, it was shown that ‘dual regulatory’ cues exist in the smoke which can
either have promoting or inhibitory effects on germination [6, 7]. The suspicion that
inhibitory constituents are also present in the smoke was confirmed recently when a related
butenolide, 3,4,5-trimethylfuran-2(5H)-one, was characterized from smoke showing an
inhibitory effect on germination [8]. The study revealed that the action of the compound is
concentration dependent and significantly reduces the effect of KAR1 (promoter) when lettuce
achenes were treated simultaneously, irrespective of the KAR1 concentrations applied.
There is currently little knowledge on the molecular background of smoke- and KAR1-
stimulated germination and the observed increase in seedling vigour. The studies published to
date have typically been physiological in nature, investigating similarities between the effects
of smoke and other plant growth regulators, such as gibberellins and strigolactones. Deeper
insight into the molecular background of smoke action has been published more recently [1,
9, 10]. We reported that the application of smoke-water to maize kernels yielded seedlings
with higher vigour and resulted in the induction of stress-related changes in the global
transcriptome of young seedlings [1]. Thus, it appears that the ‘hardening’ effect of smoke is
similar to that caused by abscisic acid (ABA). The chain of events in the transcriptome during
imbibition, and the genes orchestrating the effect of smoke and KAR1 are still elusive.
However, the identification of the active component in smoke (i.e. KAR1) presents enhanced

4
opportunities for elucidating the mode of action of this compound in the absence of artefacts
and confounding influences caused by the additional compounds in smoke.
It is well established that the application of smoke and KAR1 breaks seed dormancy
and yields earlier testa rupture and overall higher germination rate, although these responses
can vary between species. Thus, smoke and KAR1 treatments have the potential to improve
not only the germination percentage but also the seedling vigour of many species. Regarding
maize, this effect is more pronounced as smoke and KAR1 treatment results in a massive
increase in post-germination growth and seedling vigour [1, 11]. On the other hand, smoke
and KAR1 positively affects the germination rate of maize, as determined by a general
germination test, and slightly enhances the water uptake and imbibition of the kernels in the
pre-germinative stage [1, 11]. Other reports suggest that smoke and KAR1 affect initial water
uptake in tomato [12] and water homeostasis during germination in Eragrostis tef [13].
Our previous microarray study on smoke-exposed maize seedlings showed that smoke
treatment results in a distinct, although not robust, change in the gene expression pattern. The
aim of the present study was to gain a deeper insight into the molecular background of how
smoke and KAR1 exert their effects on seed germination during imbibition, prior to testa
rupture. To elucidate the action of smoke-water and KAR1 in the early imbibition stages of
maize germination, we recorded the changes in the total transcriptome in the first 24 h in a
time-course microarray experiment. Here, we present a detailed comparative analysis of the
changes in gene expression that take place in maize embryos after exposure to smoke-water
and KAR1. The present work substantially extends our current knowledge of transcriptional
regulation by smoke and KAR1 exposure and will provide valuable insight into which aspects
of smoke- and KAR1-induced germination and increased seedling vigour should be the focus
of further studies.

Results

Germination characteristics of smoke-water and KAR1-treated kernels

Application of smoke-water and the active compound KAR1 slightly, but significantly,
increased the germination rate of the treated kernels after 10 d, when water imbibed kernels
were used as controls (Fig. 1). The time course of testa rupture was similar in all conditions
applied, however, the first appearance of radicles/coleoptiles was after about 24 h in the

5
treated samples. The actual germination percentage was higher in the smoke- and KAR1-
exposed kernels from 5 d onwards, and beyond 10 d, no further testa rupture was observed.
For experimental design reasons, we assumed that the effect of both cues on the
germination is equivalent, regarding their apparent physiological effect on germination
parameters. Considering the presence of inhibitory compound(s) in smoke, the concentration
of which may be the limiting factor for the germination activity of smoke-water, the most
suitable range for which germination promotion by smoke occurred was determined, and we
found that the dilutions used in previous reports (1:1000 and 1:2000) worked well in our
experiments. We also determined the concentration of KAR1 and 3,4,5-trimethylfuran-2(5H)-
one in our smoke-water batches. The concentration of the KAR1 in crude smoke-water was
4.0818 x 10-6 M ± 3.6% (0.004 µM in the diluted smoke-water), whereas the concentration of
the inhibitory compound was 1.3 x 10-2 M ± 5.8% in the undiluted smoke-water. The 3,4,5-
trimethylfuran-2(5H)-one concentration was much higher in the crude smoke than the
reported 10 µM limit, which is highly inhibitory to germination [8]. Therefore, to achieve a
positive germination response we used the 1:1000 dilution of the smoke-water, a
concentration applied in previous studies [1, 6, 7].
Taking into account that KAR1 is active over a very wide concentration range, the
concentration of the inhibitory compound is the limiting factor in terms of germination
responsivity and there is no information about the physiological effects of other (supposedly)
active butenolide compounds (the karrikins) present in the smoke. Therefore, we tested the
typical and widely used 0.1 µM and 0.01 µM concentrations of KAR1 and 0.1 µM was chosen
for the microarray experiment. However, due to the possibility of other potentially active
compounds in smoke our primary interest was to assess smoke-water and KAR1 responsive
genes and not to compare the two treatments (we could not assume that the molecular basis of
smoke and KAR1 action is the same).

Transcriptome analysis of smoke-water and KAR1-treated germinating kernels

In a previous study, we performed microarray analysis of smoke-water-induced
germinating maize kernels (young seedlings) which had just entered phase III of germination
characterised by rapid and pronounced water uptake [1]. In this study, to begin elucidating the
molecular basis of smoke and KAR1 action during imbibition, before testa rupture, a detailed
temporal analysis of gene expression under smoke and KAR1 exposure was conducted using
microarrays. As the germination time course shows, the germination of maize is not perfectly

6
synchronous, and the radicles/coleoptiles first appeared in the treated samples. We assumed
that in the first 24 h of imbibition, before the first observation of testa rupture, the kernels are
more homogenous in terms of developmental stage than later, and we chose early time points
to collect the samples. Beyond 24 h, it is difficult, due to the increasing radicle emergence, to
sample imbibed kernels in the same developmental stage. To further reduce the effect of
differences in the germination stages, we used 90 embryos at every time point (15 embryos of
six independent treatments). Embryos excised from kernels of the Mv255 maize strain treated
with smoke-water (1:1000 dilution) and KAR1 (0.1 µM) solutions for 1.5, 3, 6, 9, 12 and 24 h
were used for the experiment. We also investigated the changes in the transcription profile of
embryos which were smoke-treated for 3 and 6 h, after a 3 h delay. In this experiment, control
and smoke-treated samples were compared to samples which were imbibed in water for 3 h
and then exposed to smoke-water for an additional 3 and 6 h. For the whole time-course
experiment 68 independent microarray slides were used. The microarray data presented here
have been deposited in the GEO database (http://www.ncbi.nlm.ni.gov/geo) under accession
number GSE17484. Throughout the course of the experiments, only a narrow subset of genes
were affected at all time points by the treatment. Fig. 2 shows the expression pattern of 21
selected genes whose expression changed in all experiments with fold-change ≥ 2, with
corrected p-values < 0.1 in at least two experiments (Additional File 1). Additional File 2
shows the expression patterns of all genes at all time points and comparisons which showed a
fold-change ≥ 4 and a corrected p-value < 0.1 in at least one experiment. The full list of the
genes with fold-change ≥ 2, their annotation and p-values in the different treatments and time
points are available online as Additional Files. Genes with corrected p-value < 0.1 (regarded
as significantly differentially expressed) are at the top of the list, separated with a red line.
The list of smoke-responsive genes (Fig. 2; Additional Files 2 and 3) shows a
significant overlap with our previous transcriptome data obtained from young smoke-treated
maize seedlings 24 and 48 h after imbibition [1]. A sulfiredoxin-like protein gene
(MZ00020514) and a LRR receptor kinase-like gene (MZ0000704) were upregulated, while
the transcript abundance of calcineurin 9B-like gene (CBL9; MZ00043714) and an unknown
gene (MZ00019598) with a tetratricopeptide repeat (TTR) sharply declined. In smoke-treated
seeds, the most obvious changes were observed in the expression of the ubiquitin activating
enzyme 1 (UBE1, MZ00041434) which was upregulated after 6 and 12 h.
To differentiate between imbibition/germination and the smoke-specific response, we
compared the transcriptome of kernels imbibed in water for 3 h and additionally treated with
smoke-water for 3 or 6 h with control ones in an independent experiment (Fig. 2; Additional

7
Files 2 and 4). This design allowed us to partially filter imbibition specific genes and narrow
down the potential list of smoke specific genes. Interestingly, nearly the same expression
pattern was obtained as in the time course study, with the overwhelming expression of UBE1,
and surprisingly, the upregulation of the CBL9, TTR and two unknown genes (MZ00033282
and MZ00039431) which were downregulated in the time course experiment. The putative
methylcrotonyl-CoA carboxylase (MZ00022757) showed unique and concerted upregulation
when smoke was applied in delay.
KAR1 treatment yielded a completely different gene expression pattern in comparison
to smoke-treated samples (Fig. 2, and 3; Additional File 2, 5 and 6). A senescence-associated
protein-related gene (MZ00020646) was upregulated at all time points, except at 9 h, where a
sharp decline in the expression was observed. A putative plastidic phosphate translocator-like
protein 1 (MZ00025182) and a glycosyltransferase domain-containing gene (MZ00039357)
was also constantly upregulated. The most notable gene, however, which was upregulated
during the whole course of the experiment is a tonoplast intrinsic protein (TIP3.1), a member
of the aquaporin family. Analysis of the microarray data obtained from comparison of the
KAR1- and smoke-treated samples showed that the master genes TIP3.1 (MZ00024641),
senescence-associated protein-related gene (MZ00020646) and S-adenosylmethionine-
dependent methyltransferase (MZ00029766), which proved to be KAR1-responsive, were
downregulated at almost all time points in smoke-treated plants (Fig. 2 ; Additional Files 2
and 6). This latter gene functions in the flavonoid biosynthesis process and both smoke and
KAR1 responsive gene lists were enriched in transcripts related to the phenylpropanoid
pathway, although different gene sets were affected (Additional File 2). Smoke treatment
induced the expression of anthranilate phosphoribosyltransferase (MZ00024875), flavanone
3-beta-hydroxylase (MZ00044256), flavonol glucosyltransferase (MZ00021805), flavonoid
3'-hydroxylase (MZ00021482) and CYP71D (MZ00029737), while the CYP81E1/D8 gene
(MZ00004877) was downregulated. After KAR1 treatment, the transcript abundance of
cinnamoyl-CoA reductase (MZ00036789), cinnamic acid 4-hydroxylase (MZ00036045) and
anthranilate phosphoribosyltransferase (MZ00047824) were altered.

Validation of microarray data by real-time quantitative RT-PCR

To validate the microarray results, the differential expression for selected genes was
corroborated using qRT-PCR. Fourteen genes from various functional categories and
displaying diverse expression profiles were chosen from among all differentially regulated

8
genes. Despite the relatively high false discovery rate (FDR) in some cases (i.e. ~25% in 24 h
smoke experiment and ~30% in 1.5 h and 3 h experiments, which were excluded from further
analysis, or a moderate ~11% in the delayed experiments), the expression pattern observed in
the microarray experiments was consistent with the genes analysed by real-time PCR (Fig.
4A). The linear regression analysis showed a significant correlation between the two data sets,
with R2 = 0.74082. In addition, the expression response (fold change) of the selected key
genes to smoke and KAR1 treatments showed little variation in the three independent
experiments (Fig. 4B).

Gene Ontology analysis

A stringent false discovery rate correction was applied to p-values when individual
fold changes were studied but not when genes were studied in functional groups [14]. Genes
up- or downregulated by ≥ 2-fold and with a corrected p-value < 0.2, due to smoke-water or
KAR1 treatment, were associated with different Gene Ontology (GO) terms. Fig. 5 shows the
most highly represented GO terms and their raw p-values. For the entire Gene Ontology list
and raw p-values, see Additional Files 7 and 8. The most pronounced GO terms following
smoke-water or KAR1 treatment were quite similar, contrary to the fundamental differences in
the up- and downregulated gene lists. The presence of stress-related genes were robust and
extensive among the responses. A number of GO terms involved in cold, salt, heat, osmotic,
fungus and other stress responses, light response (‘response to low light intensity’, ‘response
to light stimulus’, ‘response to blue light’, ‘shade avoidance’) and ABA and brassinosteroid-
responsiveness were enriched in both gene lists. Genes related to the phenylpropanoid
metabolism and flavonoid biosynthesis were also represented in high number. As expected,
genes related to ubiquitin-dependent protein catabolic process were abundant. Regarding
hormone-related signatures, genes involved in the ABA stimulus were more prevalent,
although auxin-mediated signalling pathway and brassinosteroid-related genes were also
overrepresented. Gibberellin-related terms, however, were less frequent on the list. Growth
and development related terms – ‘seed germination’, ‘unidimensional cell growth’,
‘embryonic development ending in seed dormancy’ were also abundant in both lists.

Physiological response of germinating maize kernels to smoke-water and KAR1-
treatment

9
Experiments were carried out to determine the effect of smoke-water and KAR1 on the
germination characteristics and growth parameters (root and coleoptile length) of 5-day-old
maize seedlings and the potential interplay between smoke-water, KAR1 and aquaporin
inhibitors (Fig. 6). The kernels responded more explicitly to the different treatments so here
we discuss the effect of smoke, KAR1 and different inhibitors on growth parameters only.
Smoke-water, applied as a 1:1000 (v/v) aqueous dilution of crude smoke extract,
yielded significantly longer coleoptiles and roots compared to the control (Mann-Whitney +
Shapiro tests, p < 10-10). Treatment of maize kernels with the 0.1 µM solution of KAR1
resulted in a very similar frequency distribution of coleoptile/root sizes as observed in smoke-
treated kernels.
To support the findings of microarray data, and of TIP3.1 aquaporin playing a crucial
role in KAR1 action, we conducted germination tests on KAR1-treated maize kernels (Fig. 6).
It was previously reported that KAR1 can alleviate the negative effect of aquaporin inhibitors
like mercury chloride (HgCl2) and zinc chloride (ZnCl2) in tomato seedlings, indicating the
possible involvement of aquaporins in KAR1 action [12]. We applied two known aquaporin
inhibitors [15], HgCl2 and silver nitrate (AgNO3), on maize seedlings to determine the
involvement of aquaporins in KAR1 action. Both treatments resulted in a reduction of the
growth parameters of the seedlings, and the AgNO3 proved to be a stronger inhibitor (Mann-
Whitney test, p < 10-10; Additional File 9). Treatment of the seedlings with a combination of
KAR1, AgNO3 and HgCl2 showed an alleviation of the adverse effect of the AgNO3 and
HgCl2, whereas simultaneous treatment with both smoke-water and AgNO3 or HgCl2 show no
such reduction in the effect of AgNO3 and HgCl2 inhibition (Additional File 9). This effect of
the KAR1 in combination with AgNO3 was demonstrated by the frequency distribution of the
seedling shoot/root size which was not significantly different from the KAR1-treated plants
(Fig. 6; also see Additional File 9). Based on the assumption that AgNO3 treatment might
interfere with ethylene perception, we also examined whether the KAR1-related transcriptome
overlaps with ethylene-related gene expression patterns (genes regulated by endogenous basal
level of ethylene and ethylene treatment in wild-type, ethylene insensitive mutant etr1-1 and
the ethylene-constitutive mutant ctr1-1Arabidopsis plants [16]) and GO terms related to
ethylene signalling or ethylene stimulus appeared in the list. Genes encoding almost every
protein in the ethylene signal transduction pathway in Arabidopsis have also been found in
maize previously, and ethylene signaling components also have similar biochemical functions
[17]. The microarray data obtained from KAR1-treated plants showed no similarity with
ethylene-related transcriptomes and no significant amount of GO terms related to these

10
biological processes occurred in any of the gene lists (see Additional Files 7 or 8), suggesting
that KAR1-treated seedlings may overcome the adverse effect of the silver ions not because of
the involvement of ethylene-related events.
Microarray data indicated the possible involvement of ubiquitin-mediated protein
degradation in smoke action. To further elucidate the findings revealed by the transcriptome
data, the level of ubiquitinated proteins were examined using an anti-ubiquitin antibody. To
demonstrate that smoke-water exposure has an effect on the ubiquitination process, we blotted
the protein samples extracted from maize embryos after 3, 4.5, 6, and 7.5 h of smoke-water
(1:1000 dilution) or KAR1 (0.1 µM) treatment onto PVDF membrane and treated it with
antibodies raised against polyubiquitin (Fig. 7). Comparing these samples with controls, and
samples treated similarly with KAR1, it was apparent that smoke-treatment, and not KAR1,
enhanced the ubiquitination of the proteins dramatically after 6 h. At 3 and 4.5 h, the level of
ubiquitination was similarly low in both treatments, and at 7.5 h all the samples showed an
increase in signal intensity, although in the smoke-treated samples the ubiquitinated proteins
were more prevalent, suggesting that the smoke treatment resulted in accelerated
ubiquitination. The proteins extracted from control and treated samples of the time course
shared similar patterns, at least within the limits of SDS-PAGE and Coomassie staining
techniques.

Discussion

Over the past few years, the physiological effects of smoke and KAR1 treatments on
seed germination have been investigated extensively, but only a few studies have discussed
the deeper implications of smoke and KAR1 action [1, 9, 10]. This is the first report in which
the effects of smoke and KAR1, during the first 24 h of imbibition, are assessed with respect
to the molecular background of the phenomena. In agreement with previous investigations
[11, 1], our results show that smoke and KAR1 can accelerate germination, although their
effect on seedling vigour is more pronounced.
The total transcriptome analysis revealed substantial differences in smoke- and KAR1-
induced gene expression. The smoke-responsive gene list showed similarities with the
transcriptome data obtained from young smoke-treated maize seedlings 24 and 48 h after
imbibition [1]. The study revealed that 24 h after smoke-water treatment, the transcript
abundance of sulfiredoxin-like protein (MZ00020514), the LRR receptor-like kinase

11
(MZ00000704) and the UBE1 (MZ00041434) were the highest (with log fold change 4.79,
4.65 and 4.32, corrected p-value < 0.05, respectively), while the tetratricopeptide repeat
containing protein (MZ00030105) was downregulated (log fold change -2.14, corrected p-
value < 0.05) in the young seedlings, confirming that these genes could be the master genes in
smoke action.
Smoke activated the ubiquitination-related UBE1 gene which catalyzes the first step in
the ubiquitination reaction that targets proteins for degradation via the proteasome. Ubiquitin-
mediated proteolysis plays a pivotal role in hormone synthesis, hormonal signalling cascades,
plant developmental processes and stress responses (for review see [18]). There are many
reports suggesting that ubiquitin-mediated proteolysis may also act upstream of the hormonal
signalling cascades by regulating hormone biosynthesis, transport and perception and it is
well established that hormonal cross-talk can occur at the level of proteolysis.
Smoke-water treatment yielded the formation of high molecular mass ubiquitin
conjugates before the ubiquitination signal or degron appeared in the control and KAR1-
treated kernels. The observed levels of ubiquitin conjugates, detected by immunoblotting
using anti-ubiquitin antibodies, suggest an intense involvement of the ubiquitin-mediated
proteolytic pathway during smoke-induced germination. It was previously shown that protein
ubiquitination, and the subsequent protein degradation, is a key feature during seed
germination [19]. In line with the expression data, the abundance of the UBE1 transcript
reflects the functional activity of the enzyme. Presumably, application of smoke-water
accelerates protein turnover and affects the assignment of proteins to be degraded by
proteasomes and this eventually leads to the enhanced germination and seedling growth.
Although the E2 and the more diverse E3 ligases are well characterized, the exact regulation
of the E1 enzyme is poorly understood. Two ubiquitin activating enzyme clones from tobacco
were induced after biotic stresses and stress hormones supporting the idea that the ubiquitin-
proteasome system is activated as a stress response [20].
Smoke-water treatment resulted in the upregulation of other stress and developmental
responsive genes. Plant peroxiredoxins (2-Cys-Prxs) are subject to substrate-mediated
inactivation reversed by the smoke-induced sulfiredoxin, which suggests that the 2-Cys-Prx
redox status and sulfiredoxin are part of a signalling mechanism participating in plant
responses to oxidative stress [21]. Leucine rich repeats containing receptor-like kinases (LRR)
comprise a large gene family which play important roles in plant growth and development as
well as hormone and stress responses. The CBL9 calcium sensor, of which the expression was
downregulated by smoke treatment, desensitizes ABA effects in seed germination since CBL9

12
functions as a negative regulator of ABA response in both seed germination and gene
expression regulation in vegetative tissues [22]. Interestingly, CBL9 was upregulated when
smoke was applied for 3 and 6 h after a 3 h delay. This unique expression pattern might be
attributed to the partially-imbibed state of the seeds before smoke-water application which
could result in a reduced uptake of the smoke compounds, or suggests that their expression is
imbibition dependent.
KAR1 application resulted in the distinctive expression of TIP3.1 aquaporin. Plant
aquaporins facilitate the transcellular movement of water and, in some cases, also the flux of
small neutral solutes across a cellular membrane. It was shown that TIP expression is highly
tissue specific and can be altered by hormones, especially ABA [23]. However, the function
of each individual TIP isoform and the integrated function of TIPs under various
physiological conditions remain elusive. One member of the TIP subfamily, the TIP1.1
showed increased expression in cold-stressed cotton cotyledons, suggesting a role in plant
defence against environmental stresses by providing a suitable water balance under stress
conditions [24]. The inhibition of water transport by gold and silver compounds [15, 25] and
mercury chloride have been reported in isolated vesicles from higher plants as well as in the
intact root system [25]. However, ethylene perception can also be blocked by silver ions [26]
and the interaction between the ethylene signal transduction and KAR1 cannot be ruled out.
The similar trend, however, that was observed with mercury-KAR1 interaction shows that the
TIP3.1 aquaporin plays an important role in KAR1 action, as previously suggested [12].
Furthermore, the KAR1-related transcriptome showed no similarity to ethylene-related
transcriptomes [27] and no significant amount of GO terms related to ethylene occurred in
any of the gene lists.
Contrary to the obvious differences in the primary action and in the lists of smoke- and
KAR1-responsive genes, the treated kernels showed very similar germination responses after
5 d, with seemingly similar growth parameters. Furthermore, the genes can be classified into
quite similar functional categories. It should be noted that due to the complexity of biological
data-mining situations, in its current state, the analysis of large gene lists with the current gene
set enrichment tools is still more of an exploratory data-mining procedure rather than a pure
and exact statistical solution. The best analytical conclusions are made with the aid of the
investigator's bio-knowledge, integrated annotation databases, computing algorithms and the
enrichment p-values derived from statistical methods [28]. In our study, the occurrence of
stress-related genes were robust and are extensive among the responses, especially cold, heat
and biotic stresses, although the p-values calculated showed less significant results. Salt,

13
osmotic and other stress-related terms were also abundant, as observed in the early post-
germinative phase of smoke-treated maize seedlings [1] or in smoke-treated achenes of Grand
Rapids lettuce [9]. Genes involved in the light response were also predominant in both lists
suggesting a presumptive involvement of light signalling in smoke action. This assumption is
in accordance with the finding that smoke and KAR1 can replace the light requirement of the
germination of Lactuca sativa cv. Grand Rapids achenes [6]. KAR1-stimulation of
Arabidopsis germination is light-dependent and reversible by far-red light exposure,
suggesting a possible involvement of light signalling in KAR1 action [10]. However, it can be
considered that the over-representation of stress- and light-response-related terms in the GO
lists may indicate that the active constituents are perceived and the signal is mediated in a
similar way as environmental stress signals and therefore general stress-related pathway
integrators could play a crucial role in smoke and KAR1 action. The CBL9 is a good example
of this type of signal integrator, since it mediates the cross-talk between hormones and its
expression is affected by stress [22]. Given the diversity of LRR kinases and more than 700
F-box proteins present in the Arabidopsis genome, it is especially intriguing to consider the
extensive possibilities for small-ligand-based signal perception mediated by these potential
receptors and signal transduction pathways [29]. These pathways are also the source of the
immense complexity of plant biochemicals, meaning that a host of additional ‘growth
regulators’ might lie undiscovered [30]. The remarkable occurrence of phenylpropanoid
pathway related genes for both treatments may suggest the importance of flavonoids in the
smoke and KAR1 action. Apart from their function in the Rhizobium-legume and in different
plant-soil pathogen interactions, flavonoids have been implicated in the modulation of
developmental processes as diverse as auxin transport, pollen germination, root hair growth,
allelopathic responses and in systemic acquired resistance [31]. The induction of several key
enzymes of the phenylpropanoid pathway raises the question whether KAR1 and other active
compounds are metabolized in plants forming a so far unknown class of growth regulators
[4].
The obvious differences between the smoke- and KAR1-responsive gene lists clearly
indicates the interaction of other germination-active cues in the smoke which together form
the physiological response towards smoke treatment. In addition to the KAR1 used in this
study, at least five other active butenolides are known to be present in smoke [5, 10] and other
active compounds are suspected to exist [4, 7]. It was previously reported that smoke-water
has a ‘dual regulatory’ effect on germination, since high concentrations of smoke-water were
shown to inhibit germination, whereas lower concentrations had a promotory effect [7]. The

14
assumption that inhibitory cues may also be present in the smoke was recently supported by
the isolation of a related butenolide, 3,4,5-trimethylfuran-2(5H)-one, that results in an
inhibitory effect on the germination of lettuce achenes [8]. Considering the assumption that
the smoke effect (and the effect of the active promoter compound) is modulated by the
presence of the inhibitory and other promoter compound(s) (e.g. KAR2-KAR6), we applied
typical smoke-water and KAR1 concentrations which are regarded as equivalent in terms of
their observed physiological activity. KAR1 is equally and uniformly active over a wide
concentration range between 10-4-10-9 M [4]. Smoke-water (a standard batch used in our
laboratories) was used in diluted form between 1:10 – 1:2000, with the higher concentrations
having an inhibitory effect [7], and the most widely used effective dilutions being between
1:500 – 1: 2000 in our previous studies. We showed that the undiluted form contains the
inhibitory compound in high concentration and by dilution of the smoke-water the inhibitory
effect can be diminished. The effect of smoke-water, however, depends on the production of
the smoke-water and also depends on the species used for the germination assay. In the
present study, our results showed that the concentrations used previously in germination
studies are not equivalent in terms of the expression pattern induced. Our results, together
with earlier findings, clearly indicate that the array of compounds present in the smoke results
in distinctly different effects on the gene expression in germinating maize kernels in
comparison to that observed with the treatment of KAR1 alone. This is to be expected
considering the number of active compounds found in smoke and smoke-water. The presence
of more potentially active compounds in smoke, the concentration-dependent activity of the
inhibitory compound, and their possible interactions implies that no two batches of smoke can
be regarded as exactly the same, or the presence of the active compounds should be monitored
in parallel. However, it should be noted that the list of potential smoke-responsive genes
shows a considerable overlap with the expression pattern of embryos in the early post-
germinative stage treated with a completely different batch (batch No. “1”) of smoke-water
[1]. We cannot necessarily draw the conclusion that different smoke batches have the same
effect on the expression pattern, as this would require a more detailed investigation.
The positive and negative germination cues represent a diverse suite of chemical
signals provided by the environment to signal germination. These compounds may fine-tune
the germination response, and it may be possible that together they would compose a distinct
signal required by fire-prone species to accurately locate their germination niche. It is of great
interest that the tri-substituted but-2-enolide ring is a common structural feature of these
butenolide compounds. The molecular basis of the effect of smoke may be related to the

15
diverse binding affinity of the active compounds to the proposed receptor and the consequent
effects exerted on the changes of gene expression patterns. Conducting in-depth molecular
biology studies on the interaction of these compounds will definitely add a further dimension
to the emerging picture on the effect of smoke on seed germination in fire-prone
environments.

Conclusions

In conclusion, accelerated protein degradation or induction of the TIP3.1 aquaporin
are key features of smoke and KAR1 action. Considering all the knowledge accumulated to
date in terms of smoke action we can assume that these physiological events represent only
the ‘tip of the iceberg’ and these can be regarded as the executers of smoke and KAR1 action.
As far as the nature of smoke and KAR1 perception is concerned, it is highly possible that the
smoke ‘signal’ is perceived by a receptor that is shared with the signal transduction system
implied in perceiving environmental cues (especially stresses and light), or some kind of
specialized receptor exists in fire-prone plant species which diverged from a more general one
present in a common ancestor, and also found in the non fire-prone plants allowing for a
somewhat weaker but still significant response. These major integrators of environmental
signals, stress and hormone responses, could be potential targets for future research.

Methods

Plant Material, growth conditions and germination tests

For the germination tests, microarray studies and western blotting experiments, kernels
(seeds) of Zea mays L. Mv255 strain were used. The kernels were stored in refrigerators at
4°C in paper bags until use. Decontamination was done in 3% sodium hypochlorite containing
Tween 20 and 70% EtOH (10 min each). In the germination time course tests, each treatment
consisted of four independent experiments with three biological replicates (30 kernels in
each). The kernels were placed in 90 mm Petri dishes on tissue paper moistened with water
(control), 1:1000 or 1:2000 (v/v) dilution of smoke-water, 0.1 or 0.01 µM KAR1, and allowed
to germinate in a controlled environmental chamber (25°C, 80% RH, and 100 µmol m-2 s-1
light intensity). Germinated kernels (kernels with visible roots and coleoptile) were scored

16
every day at the same time for 10 d. In the vigour tests, each treatment consisted of two
independent experiments with two biological replicates (30 kernels in each). Batches of
kernels were submerged for 1 h into 20 mL water (control), 1:1000 (v/v) dilution of smoke-
water, 0.1 µM KAR1, 30 µM AgNO3 and their combinations (smoke-water+AgNO3,
KAR1+AgNO3) at the same concentrations. Thereafter, the kernels were placed and incubated
for 5 d under the same temperature and light regime as described earlier. For statistical
analysis, the Mann-Whitney U-test was applied with the R 2.9.0 software [33] and p < 0.05
values were regarded as significant.

Preparation and GC-MS analysis of smoke-water

The smoke-water (batch No. “2”) was prepared from burnt Themeda triandra Forssk.
(Poaceae), according to the method outlined in Baxter et al. [32]. The butenolide, 3-methyl-
2H-furo[2,3-c]pyran-2-one (KAR1), was synthesised from pyromeconic acid according to
Flematti et al. [33]. The inhibitory compound was synthesized according to Light et al. [8].
The GC–MS analysis of KAR1 and the inhibitory compound content of smoke-water was
carried out with slight modifications using a Shimadzu Model GCMS-QP2010 system
(Shimadzu) fitted with an SP-2380 capillary column (30 m · 0.25 mm I.D., df = 0.20 lm;
Supelco/Sigma–Aldrich) according to Flematti et al. [5] and Light et al. [8], respectively.
Peaks were identified according to the retention times and mass spectra of standards.

RNA isolation

For RNA isolation from control, smoke- (1:1000) or KAR1-treated (0.1 µM) kernels,
identical conditions were applied as for the vigour tests and embryos were harvested 1.5, 3, 6,
9, 12, 24 and 27 h after placing them in the Petri dishes. At 24 h, only the kernels with no
testa rupture were selected for further experiments. In an additional experiment, control and
smoke-treated samples were compared to samples which were imbibed in water for 3 h and
then exposed to smoke-water for an additional 3 or 6 h. Individual kernels (15) from each of
six independent biological replicates were chosen and then the embryo axes (without
scutellum) were excised with a scalpel and frozen immediately in liquid nitrogen in batches.
Total RNA was isolated using TRIzol reagent (Invitrogen) and cleaned up with RNeasy Plant
Mini Kit (Qiagen). The RNA Integrity Number (RIN) of the samples was determined using
the Agilent BioAnalyzer. Only samples with a RIN ≥ 8 were considered for further analysis.

17

Microarray platform, labelling, hybridization and image acquisition

The microarray study was performed according to Soós et al. [1] with a few
modifications. The experimental design was generally based on the instructions of
Kendziorski et al. [35] and Dobbin et al. [36]. The RNA samples of six parallel and
independent experiments (each containing 15 kernels) were used and an equal amount of the
aaRNA samples (see later) were pooled (RNA of 90 individual embryos in total) from the six
experiments. Three technical replicates were applied at each time point for the microarray
analysis. Microarray slides with ~46K features were manufactured by the University of
Arizona Maize Array Project (www.maizearray.org). The detailed array annotation,
composition and the experimental procedures followed in this work can be found at the
Internet site. In brief, 400 ng total RNA was amplified and aminoallyl-UTP was incorporated
using TargetAmp Kit (Epicentre) and the resulting aaRNA was labelled with Cy3 and Cy5
(Amersham). The dye-labelled probes were then cleaned up (Qiagen), mixed with the
corresponding samples, concentrated, resuspended in the hybridization solution and incubated
at 42°C overnight in a hybridization oven. Finally, the slides were washed with different
concentrations of SSC at room temperature.
The detailed description of the various hybridizations is the following: All the samples
from control experiments were compared to samples from smoke-treated experiments with 3
technical replicates, totalling 21 microarray slides. The samples from control experiments
were also compared to samples from KAR1-treated experiment with 3 technical replicates,
totalling 18 microarray slides. The samples from KAR1-treated experiments were compared to
samples from smoke-treated experiments with 3 technical replicates (except in the case of the
3 h samples, where only 2 technical replicates were used), totalling an additional 17 slides.
Finally, 3 and 6 h control samples were compared to the 3 and 6h delayed samples, and also 3
and 6 h smoke-treated samples were compared to the 3 and 6h delayed samples with 3
technical replicates, totalling 12 slides.
Scanning was performed using an Amersham Typhoon Trio+ with default settings.
The detection of signal intensities and the grid adjustment were accomplished with
ArrayVision v8.0 (Amersham). The intensity value of each spot and background region,
multiplied by its area was used as signal intensity for further analysis.

Microarray data normalization and analysis

18

Raw intensity data were imported into the R2.9.0 [34], after pre-processing it with
custom made Perl scripts. Further analysis was carried out using the LIMMA [37] package of
BIOCONDUCTOR [38]. Background correction was done using the normexp method [39].
Normalization of data within arrays was done using the loess method [40]. To normalize the
data between arrays the quantile method was used [41]. The microarray data for each gene
were fitted to a simple control versus treatment linear model at each time point/comparison,
and statistics were generated using the lmFit and eBayes functions [42] of the LIMMA
package. The p-values were adjusted for multiple testing using the method of Benjamini and
Hochberg [43]. Genes with fold-change ≥ 2 and a corrected p-value < 0.1 were considered as
differentially expressed. The microarray data presented here have been deposited in the GEO
database (http://www.ncbi.nlm.ni.gov/geo; accession number GSE17484). The dataset
contains the expression data obtained from kernels exposed to smoke for 27 h which is not
discussed here.

Gene Ontology analysis

For Gene Ontology analysis, less stringent conditions (corrected p-value < 0.2) were
applied as for the expression analysis [14]. Based on the available chip annotation supplied by
the University of Arizona Maize Array Project (www.maizearray.org), the genes were
assigned into the available Gene Ontology categories [44], and the significant over-
representation of particular categories in the combined up- and downregulated gene sets were
determined. For the analysis we used the GeneMerge software [45], which uses the
hypergeometric distribution for obtaining the rank scores for the overrepresentation of the
studied gene sets (the upregulated genes) compared to the population gene sets (the full set of
maize genes). We also modified the GeneMerge script, to reduce the large number of IO
operations and the running time of a given analysis.

Real-time PCR

The DNase I (Qiagen) treated mRNA samples (200 ng) extracted from three
independent biological replicates (15 kernels each) were reverse transcribed with SuperScript
III reverse transcriptase (Invitrogen). Real-time PCR was performed with Applied Biosystems
7500 using SYBR Green detection chemistry (Applied Biosystems) and gene-specific

19
primers. Real-time PCR data were obtained from three independent experiments (not the
same used for microarray analysis), and the reactions were performed in quadruplicate. Prior
to the real-time PCR experiment, the applicability of the maize actin (AY103587) endogenous
control was checked and we found that its expression in the embryo was unstable during the
first 6 h of the imbibition. Based on our microarray data and the recommended reference gene
list of Czechowski et al. [46], we used a putative RNA-binding protein gene (Accession no.:
BT040552) as an internal control. The relative ratio of threshold cycle (Ct) values between
the endogenous control and the specific gene were calculated for each sample. The validation
procedure was performed with the same experimental design (all time points and treatments)
as for microarray analysis using the following genes (Operon oligo identifiers are in
brackets): UBE1 (MZ00041434), cytochrome P450 (MZ00022704), CBL9 (MZ00043714),
unknown (MZ00039967), LRR receptor-like kinase (MZ00000704), RING3 protein
(MZ00007049), ZmTIP3-1 (MZ00024641), TTR-containing gene (TTR; MZ00019598),
sulfiredoxin (MZ00020514), CYP81E1/D8 (MZ00004877), cinnamic acid 4-hydroxylase
(MZ00036045), YHVR-like protein (MZ00041687), S-adenosylmethionine-dependent
methyltransferase/ methyltransferase (UbiE/COQ5; MZ00029766) and ubiquitin-conjugating
enzyme (UCE2; MZ00041882).

Protein extraction and immunoblotting analysis

Kernels of maize strain Mv255 were raised under the same conditions as described
above for RNA extraction. For protein isolation, embryo axes (without scutellum) from
control, smoke-water (1:1000) and KAR1-treated (0.1 µM) samples were harvested after 3,
4.5, 6 and 7.5 h of treatment from three biological replicates. Fifteen embryos from each
replicate were collected and ground to a fine powder in a mortar with liquid nitrogen. Each
sample was resuspended in 500 µL extraction buffer (containing 2% (v/v) SDS, 5% (v/v)
glycerol, and 2.5% (v/v) mercaptoethanol in 50 mM Tris-HCl, pH 6.8) with protease inhibitor
cocktail (Sigma). The suspensions were thoroughly vortexed, then boiled for 10 min and
centrifuged at 14000 g for 15 min. Total protein quantification was carried out following the
Bradford's procedure.
From each experimental condition, 5 µg of protein was separated using SDS-PAGE on
12% acrylamide gels. Protein molecular weight standards in the range of 6.5-205 kDa
(Amersham) were used as standards. The gels were then stained with Coomassie Brilliant
Blue G-250 (BioRad) or the proteins were blotted onto low-fluorescent Hybond-LFP PVDF

20
membranes (Amersham). The blotted membranes were blocked with 5% BSA/TBS-T for 1 h
at room temperature, and probed overnight with Ub(6C1) mouse anti-ubiquitin antibody
(Santa Cruz) in 1:2000 dilution. The immune complexes were detected using Cy3-labeled
goat-anti-mouse IgG antibody in 1:4000 dilution (ECL Plex System, Amersham) and images
were captured with Amersham Typhoon Trio+ scanner.

Authors’ contributions

VS designed the experiments, conducted the germination tests, the microarray
experiments, the immunoblot analysis and wrote the paper, ES designed the experiments,
analysed the germination tests and microarray data and wrote the paper, AJ designed the
experiments, analysed the germination tests and microarray data and wrote the paper, MEL
isolated the compounds and wrote the paper, GS and JT carried out the GC-MS
measurements, LK synthesised the compounds, JVS assisted in experimental design and
wrote the paper, EB designed the experiments, analysed the data and wrote the paper. All
authors read and approved the manuscript.

Acknowledgements

This work was supported by the Generation Challenge Programme (GCP), the
Hungarian-South African Intergovernmental S&T Cooperation Programme, the Hungarian
Scientific Research Fund (OTKA F16066) and the National Research Foundation, Pretoria,
South Africa and the IOCB project Z4 055 0506, Czech Republic. VS and AJ were granted
Bólyai Scholarship.

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Figures

Figure 1 Effect of smoke and KAR1 on the germination time course of maize kernels
Each treatment consisted of four independent experiments with three biological replicates
(n=30). The kernels were treated with water (control), 1:1000 or 1:2000 (v/v) dilution of
smoke-water, and 0.1 or 0.01 µM KAR1. Germinated kernels were scored every day for 10 d.
Error bars represent standard error (SE) of the mean germination percentage.

Figure 2 Hierarchical clustering of data from the microarray analysis of gene
expression in smoke- and KAR1-treated germinating maize kernels
The data represents control vs. smoke, control vs. KAR1, control vs. smoke-treated for 3 h
after a 3 h delay, control vs. smoke-treated for 6 h after a 3 h delay, and KAR1 vs. smoke
comparisons. Samples with similar patterns of expression of the genes studied cluster
together, as indicated by the dendrogram. The hierarchical clustering of the 21 genes that
seemed to be the most relevant in all experiments is illustrated (expression changed in all
experiments with fold-change ≥ 2, and at least in one experiments the corrected p-values <
0.1). Yellow indicates up-, and blue indicates downregulation.

25
Figure 3 Principal component analysis of the genes distinctly differentially expressed
between smoke and KAR1 treatments
Biplot representation of the principal component analysis. The figure shows the 199 genes at
1.5 h, 3 h, 6 h, 9 h, 12 h and 24 h that were distinctly differentially expressed (fold-change ≥ 4
and a corrected p-value < 0.1) in at least one experiment. All of the genes were plotted with
respect to the first and second principal components and they are represented with a light gray
text. The originally observed variables are plotted as red (smoke- related) and blue (KAR1-
related) responsive arrows. The arrows represent the association of the measured variables
(fold-change) with the samples in the visualization: the length and location are proportional to
the variable loadings on the two first principal components. The analysis suggests that much
of the variability and difference between the two gene sets can be attributed to the two
different treatments (smoke and KAR1). Also see Additional File 10.

Figure 4 Validation of microarray results via quantitative real-time PCR
A, Quantitative real-time PCR analysis was performed for 14 genes under the same conditions
and design used for microarray analysis. Real-time PCR data were obtained from three
independent experiments with similar results, and four amplification reactions. Microarray
data (least-square means) were plotted against data from qRT-PCR and fitted into a linear
regression. Both x- and y-axes are shown in log2 scale.
B, The biological variation of the expression (assessed by quantitative real-time PCR
analysis) of 8 selected master genes are shown. Experimental design is as for Fig. 5A. Error
bars represent standard deviation. Asterisks indicate significant difference (p < 0.05) from the
control samples (statistical analysis was assessed by a t-test).

Figure 5 The list of GO terms overrepresented in the group of genes up- and
downregulated (fold change ≥ 2 and corrected p-value < 0.2)
Data obtained from 1.5 h, 3 h and 24 h smoke-water treated samples are not included on the
map. The frequency of each GO term was calculated [42] and multiplied by 100 to make the
plotting easier on the heat map. Light colours indicate low representation; blue/deep blue
colours show overrepresentation. Red squares: raw p-value < 0.05; orange squares: raw p-
value of 0.05 – 0.1; yellow squares: raw p-value 0.1 – 0.2.

Figure 6 Effect of smoke, KAR1, AgNO3 and their combinations on the seedling vigour
of 5-d-old maize seedlings

26
A, Typical phenotypes of the treated kernels.
B, Frequency distribution of two growth variables (coleoptile and root length in mm) in
control, smoke (1:1000 dilution), KAR1 (0.1 µM), AgNO3 (10 µM), smoke+AgNO3,
KAR1+AgNO3. The data were grouped into bins as presented on the graph. For statistical
analysis (see Additional File 9), the Mann-Whitney U-test was applied (R 2.9.0.) and p < 0.05
was regarded as significant (n = 120).

Figure 7 SDS-PAGE and immunoblotting analysis
Maize kernels were germinated in water (c, control) or were treated with smoke (s, 1:1000
dilution) or KAR1 (KAR1, 0.1 µM) for 3, 4.5, 6 and 7.5 h and proteins were extracted from
the embryos (n = 15). The experiments were repeated three times with similar results.
Molecular masses (kDa) of standard proteins are indicated on the left. A, Immunoblotting
analysis with anti-ubiquitin antibody. B, Protein pattern obtained by SDS-PAGE and
Coomassie Blue staining.



Additional Files

Additional File 1. The fold change and corrected p-values of the 21 selected smoke and
KAR1 responsive genes at all experiments and time points.

Additional File 2. Hierarchical clustering of data from the microarray analysis of gene
expression in smoke- and KAR1-treated germinating maize kernels. The data represents
control vs. smoke, control vs. KAR1, control vs. smoke-treated for 3 h after a 3 h delay,
control vs. smoke-treated for 6 h delay after a 3 h delay, and KAR1 vs. smoke comparisons.
Samples with similar patterns of expression of the genes studied cluster together, as indicated
by the dendrogram. The hierarchical clustering of 212 genes that were distinctly differentially
expressed (fold-change ≥ 4 and a corrected p-value < 0.1 in at least one experiment) is
illustrated. Yellow indicates up-, blue indicates downregulation.

Additional File 3. The full list of the genes that were differentially expressed at any time
point after smoke exposure. Annotations and p-values are indicated. Genes with corrected p-

27
value < 0.1 (regarded as significantly differentially expressed) are at the top of the list,
separated with a red line.

Additional File 4. The full list of the genes that were differentially expressed at any time
point when smoke-water was applied for 3 and 6 h after a 3 h delay. Annotations and p-values
are indicated. Genes with corrected p-value < 0.1 (regarded as significantly differentially
expressed) are at the top of the list, separated with a red line.

Additional File 5. The full list of the genes that were differentially expressed at any time
point after KAR1 exposure. Annotations and p-values are indicated. Genes with corrected p-
value < 0.1 (regarded as significantly differentially expressed) are at the top of the list,
separated with a red line.

Additional File 6. The full list of the genes that were differentially expressed at any time
point in the KAR1 vs. smoke comparison. Annotations and p-values are indicated. Genes with
corrected p-value < 0.1 (regarded as significantly differentially expressed) are at the top of the
list, separated with a red line.

Additional File 7. List of GO terms related to smoke action.

Additional File 8. List of GO terms related to KAR1 action.

Additional File 9. Statistical analysis of the germination experiments. For statistical analysis,
the Mann-Whitney U-test was applied with the R 2.9.0 software and p < 0.05 values were
regarded as significant (n = 120). Only kernels with both roots and coleoptile were regarded
as germinated.

Additional File 10. Details of the principal component analysis of the KAR1 and smoke
treatments on 199 differentially expressed genes at each time point.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

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