Download A Comprehensive Gene Expression Analysis Toward the

Plant Cell Physiol. 45(9): 1280–1289 (2004)
JSPP © 2004
A Comprehensive Gene Expression Analysis Toward the Understanding of
Growth and Differentiation of Tobacco BY-2 Cells
Ken Matsuoka 1, 3, Taku Demura 1, Ivan Galis 1, Tatsuya Horiguchi 1, Mami Sasaki 1, Gen Tashiro 1 and
Hiroo Fukuda 1, 2
1
2
Plant Science Center, RIKEN (Institute of Physical and Chemical Research), 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
Graduate School of Science, University of Tokyo, Tokyo, 113-0033 Japan
;
To understand how plant cell changes gene expression
during cell division and after termination of cell division,
we analyzed the change of gene expression during the
growth of tobacco BY-2 cell lines using a cDNA microarray, which contained about 9,200 expression sequence tag
fragments and corresponded to about 7,000 genes. We
found that log phase cells predominantly expressed DNA/
chromosome duplication gene homologs. In addition, many
genes for basic transcription and translation machineries,
as well as proteasomal genes, were up-regulated at the log
phase. About half of the kinesin homolog genes, but not
myosin homolog genes, were predominantly expressed at
the dividing phase as well. In contrast, stationary phase
cells expressed genes for many receptor kinases, signal
transduction machineries and transcription factors. Several hundreds of genes showed differential expression after
incubation of stationary phase cells with medium containing either salicylic acid or abscisic acid. These findings suggested that BY-2 cells at the stationary phase express genes
for perceiving extracellular signals.
Keywords: BY-2 — Expression sequence tag — Gene expression — Microarray — Nicotiana tabacum — Tobacco.
Abbreviations: EST, expression sequence tag; AFLP, amplified
fragment length polymorphism; LED, localized expression domain;
SNARE, N-ethylmaleimide-sensitive factor adaptor protein receptor.
The nucleotide sequences reported in this paper have been submitted to the DDBJ under accession numbers BP128309-BP137498.
Introduction
Shapes of plant organs are determined by the assembly of
rigid cells, which are surrounded by tough cell walls. One of
the clear differences between plants and animals is that plants
have limited cell division parts in their bodies. These parts are
located predominantly in immature tissues, whereas many differentiated animal organs have proliferating cells. Typical
zones of cell division in plants are apical meristems and the
cambium. One of the characteristic events in the meristem is
the duplication of the genome. Therefore, many plant
3
homologs of yeast or animal cell division genes are expected to
be expressed predominantly in this tissue (Baurle and Laux
2003). However, the mechanism of cytokinesis in plants differs
completely from that of both animals and fungi (Criqui and
Genschik 2002). Thus, many genes involved in plant cytokinesis cannot be predicted from the comparison of genomic data of
plants and other organisms.
To date, several plant-specific genes for cytokinesis have
been found using biochemical and genetic approaches. These
include specific kinesins (Asada and Yasuhara 2004), N-ethylmaleimide-sensitive factor adaptor protein receptors (SNAREs)
(Surpin and Raikhel 2004), dynamin homologs (Bednarek and
Falbel 2002), protein kinases (Asada and Yasuhara 2004) and
microtubule-binding proteins (Sonobe et al. 2004). Since cytokinesis in the plant is a complex process with many different
events (Bednarek and Falbel 2002), genes that we know to be
involved will go far beyond those involved in this process.
Therefore, an alternative approach, such as mass analysis of
gene expression, is necessary to find such genes. One of the
mass analyses for characterizing such genes was undertaken
using cDNA-amplified fragment length polymorphism (AFLP)
techniques, and several hundred genes regulated by the cell
cycle were found using this technique (Breyne et al. 2002).
Many cell cycle-related proteins, including cell cycle regulators, are regulated by their turnover, and in this case, cell cycle
regulation at the mRNA level is not always necessary (Dewitte
and Murray 2003). Thus, the characterization of genes that are
up-regulated throughout the cell division could also be involved
in cell division. Recently, an elegant approach was reported for
classifying genes that are predominantly expressed in different
types of cells in the Arabidopsis root apex (Birnbaum et al.
2003). A similar characterization of genes was undertaken on
lateral root initiation using a hormone-induction system of Arabidopsis (Himanen et al. 2004). However, these methods cannot distinguish genes that are involved in general cell division
from those required for root development. Therefore, they need
to be combined with an alternative approach to point out the
genes that are actually involved in plant cell division. Tobacco
BY-2 cells are the most frequently used plant cells that show
very rapid growth (Nagata 2004). At the growth phase, almost
all cells are in the dividing phase, with little G0 phase. As such,
many events of plant cytokinesis have been analyzed using this
Corresponding author: E-mail, [email protected]; Fax, +81-45-503-9573.
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Gene expression during the growth of BY-2 cells
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cell line for understanding the molecular events of plant proliferation.
No large-scale cDNA or genomic information on tobacco
was found in public databases when we started this work. Thus,
we started to make a set of expression sequence tags (ESTs)
from this cell line (http://mrg.psc.riken.go.jp/strc/index.htm).
Using the EST clones, we pursued a microarray analysis for
characterizing gene expression during the growth of BY-2 cells.
Here, we report the characterization of differences in gene
expression at different growth phases. We discuss novel candidates for plant cell division-related genes and discuss a possibility that stationary grown cells change the pattern of gene
expression to receive extracellular signals.
Results and discussion
Fig. 1 Growth of BY-2 cells, fractionation timing and cell division
frequency. (A) A typical growth curve of tobacco BY-2 cells and the
timing of sample collection. Closed arrowheads indicate the time
points for the preparation of the EST library. Open arrowheads indicate
the time points used for the microarray analysis. (B) Images of DAPIstained cells at different growth phases. Note that the cells at the log
phase were smaller than cells at other phases. (C) Mitotic index at different growth phases.
cell line (chapters found in reference Nagata et al. 2004).
Therefore, this cell is one of the best models for understanding
plant cell division. The final step of cell division in plant cells,
cytokinesis, involves many events related to endomembrane
trafficking (Surpin and Raikhel 2004 and references contained
therein). A great deal of information on protein transport in the
secretory pathway in plants has been collected using this cell
line as a model (Matsuoka 2004, Tse et al. 2004). As such
information accumulates, there is an advantage in using this
EST contents
We prepared cDNAs from lag, log and stationary phases
of tobacco BY-2 cells (Fig. 1). Lag phase cells were collected
9 h after subculture, at which time no increase in cell volume
was observed. However, some of the cells had already entered
the mitotic cycle. We chose cells cultured for 61 h as log phase
cells for the preparation of the cDNA library. At this point, and
up to 96 h after the start of subculture, the mitotic index (percentage of cells in mitosis) was about 10% under our culture
conditions. Thereafter, although the cell volume increased up to
120 h, the mitotic index decreased. After 7 d (around 168 h), no
cell division was observed (Fig. 1). Thus, we chose 7-day-old
cells as stationary phase cells. We analyzed the sequence of
9,696 clones from one side, the average read-length of which
was about 0.5 kb. We estimated the insert size of the cDNAs
after PCR amplification to be about 1 kb.
Of the cDNAs, 9,190 showed a clear sequence that formed
7,976 clusters. The information of the EST sequence and the
result of the BLASTX search can be found at our website (http:
//mrg.psc.riken.go.jp/strc/index.htm). These ESTs are available
from RIKEN Bio-Resource Center (http://www.brc.riken.jp/
lab/epd/catalog/n_tabacum.html). To estimate the distribution
of the putative functions of these cDNA clusters, we assigned
putative functions of 1,000 randomly selected clusters on the
base of BLASTX searches (Fig. 2). About 40% of clusters were
significantly similar [an expected value (E-value) < 1.0 E-4] to
at least one protein sequence found in the public databases.
Because many non-coding mRNAs were found in both Arabidopsis and mouse full-length cDNAs (Yamada et al. 2003,
Hayashizaki and Kanamori 2004), some clones without homology could correspond to such mRNAs in tobacco cells. The
composition and ratios of the functional classified genes for the
ESTs were similar to Arabidopsis genome/unigene information (Yamada et al. 2003). There are several genome-wide analyses of BY-2 genes for characterizing different responses.
These include cDNA-AFLP analyses on the cell cycle and the
methyl-jasmonate response (Breyne et al. 2002, Goossens et al.
2003). Only 110 cDNA-AFLP sequences from the cell cycle
Fig. 2 Gene distribution of tobacco BY-2 ESTs. Possible proteins that could be encoded by the BY-2 ESTs were analyzed with a BLASTX search. The left graph shows the percentage of
genes that showed homology to genes with known or predicted functions, for unknown proteins and no homology to known genes. The right graph shows the distribution of genes among
the EST-encoded genes with known or predicted functions.
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Gene expression during the growth of BY-2 cells
Gene expression during the growth of BY-2 cells
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analysis showed an identity to 68 genes in our ESTs after the
BLAST search (E < –10). The low identity frequency could be
derived from the fact that both our EST and the cDNA-AFLP
sequences cover only part of the mRNA sequence.
Quantitative BY-2 cDNA microarray
A total of 9,216 cDNA inserts were amplified by PCR
from the EST plasmids and spotted on glass slides, as
described (Demura et al. 2002). The Cy5-labeled cDNA population was prepared from the mRNA fraction prepared from
lag-, log- and stationary-grown tobacco BY-2 cells. Hybridization was carried out after mixing the labeled cDNAs with Cy3labeled oligonucleotides, which could hybridize the amplified
vector part in the PCR products. Signals of both Cy3 and Cy5
fluorescence were recorded and quantified. The level of expression was then calculated (Supplementary Table 1).
Before the microarray data was analyzed in depth, we analyzed whether the intensities of the microarray signal were correlated with the level of mRNA. For this purpose, we chose six
different genes with different expression levels and patterns
from the microarray data. The expression patterns of these
genes were analyzed by quantitative reverse transcription
(QRT)–PCR. The pattern of expression analyzed by the two
different methods was quite similar, regardless of the level of
expression (data not shown). Based on this observation, we
concluded that our microarray data were quantitative among
the wide range of expression levels.
Expression patterns and levels
We processed a triplication of the microarray data to identify genes that showed significant differences in expression. We
found 1,948 spots that showed two-thirds or lower levels of
expression at one stage than another, the differences of which
were statistically significant (P < 0.05). Because about 10% of
the log phase cells were in the M phase (Fig. 1), we chose this
criterion based on the following assumption. If we assume that
10% of the cells showed a six-fold higher expression than other
growth phase cells, and assume the other 90% showed no difference, then the ratio of the expression levels of other growth
phases to this phase could be calculated as two-thirds [1/(6 * 0.1
+ 1 * 0.9) = 2/3].
Among them, 1,072 genes that showed significant homology to known genes were listed and grouped. After testing several clustering and grouping methods, we found a simple
method using the difference of average value gave reasonable
grouping. These listed genes were classified into seven groups
based on the expression pattern (Fig. 3 and Supplementary
Table 2). Group A genes showed the highest expression at the
lag phase and the expression level did not change significantly
during the growth of the cell. Group B contained genes with a
high level of expression at the lag and log phases compared
with the stationary phase. Group C was categorized with the
highest expression at the log phase compared with the other
two phases. Group D contained the lowest expression at the lag
Fig. 3 Seven groups obtained from the classification of differentially
expressed genes.
phase, the level of which was higher and comparable in both
the log and stationary phases. Group E genes had the lowest
expression at the lag phase and the expression increased during
the growth of the cells. Genes that showed the lowest expression at the log phase were classified as group F. The final
group, G, showed lower expression at both the lag and log
phases than at the stationary phase. Genes that were not classified into these groups were not used for further analysis.
We then compared whether genes classified into a group
had a relationship with genes that were shown to be regulated
during the cell cycle by comparing data obtained with a cDNAAFLP analysis (Breyne et al. 2002). Among 68 EST clones that
could be found in the list of cDNA-AFLP data, 30 genes were
present in the above list. Of these, 14 were classified in group
B, 10 in group C and the rest in other groups. This implies that
many genes that showed differential expression during cell
cycle progression were found in groups B and C. We concluded
that the above classification represented classes of genes that
could be linked to cellular events.
We next considered whether some classes of genes
showed higher expression levels than others. After classifying
the genes, we calculated the average signal intensities of each
gene involved with a particular function and compared it with
the average of whole data or the average of the entire annotated gene data. We found that histones, ribosomal proteins and
molecular chaperones were expressed at high levels. In these
cases, the average level of expression was 10- to 60-fold higher
than median values. Of the above three, the expression of
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Gene expression during the growth of BY-2 cells
Fig. 4 Group and gene class relationship. The numbers in parentheses indicate the number of genes that showed a difference (before slash) and
total numbers of genes on array (after slash). Classified shows the percentage of genes from the total that were found in each group.
molecular chaperones did not change significantly at all growth
phases, whereas the other two showed a decrease in expression
at the stationary phase.
Growth-phase dependence of the activation of genes for a particular function
Because we noticed that the level of expression of histones and ribosomal proteins decreased at the stationary phase,
we analyzed whether some classes of genes were selectively
found in the groups. After listing all annotated functions of
genes belonging to each group, we found that some functional
classes of genes showed a relationship with the expression pattern (Fig. 4, Supplementary Table 3). Most genes that were
homologs of cell cycle regulator genes were found in the A, B
or C group. DNA and chromosome duplication are the major
events during cell cycle progression. Genes involved in these
steps were predominantly found in group B, which is a group
that showed a higher expression at the lag and log phases. The
same patterns were found in genes for basic transcription and
translation machineries. This indicates that proliferating cells
require higher transcription and translation activities than nonproliferating cells.
The other class of cellular machinery that shows a predominantly group B pattern is the microtubule/kinesin system,
which is a cytoskeletal system known to transport organelles
and other macromolecules. In this case, approximately 60% of
the genes classified in this category were found in group B or
C, and none were found in the other groups. In contrast, the
actin/myosin system was not predominantly up-regulated at the
log phase.
Several kinesins and microtubule-binding proteins are
known to be involved in cell division in plants (Lloyd and Chan
2004). MAP65, which is a 65 kDa microtubule binding protein
found in mitotic BY-2 cells (McCutcheon et al. 2001), was
found in group B. Many kinesin-like proteins that show higher
expression at the log phase are unique to plants. Thus, tobacco
homologs of some of these, especially those that show the
expression pattern classified as group C, might be involved in
plant cytokinesis.
Another class of genes that showed high expression during cell division was the genes for ubiquitin and proteasome.
This observation is consistent with previous findings that many
cell cycle regulators are degraded by proteasomes in eukaryotes, which include plants (Vierstra 2003, Murray 2004). As
described above, many protein synthesis genes were also activated at the growth phase. These findings imply that, in dividing
cells, many proteins turn over relatively quickly compared with
non-dividing phase cells. Many genes for ATP-independent
proteases, including classical proteases, were found in groups
B and C, many of which might be involved in events related to
cytokinesis. Several others were found in group G, which
suggests that protein degradation and/or processing are also
induced at the stationary phase. One of the possible triggers for
stopping cell division is starvation of nutrients such as phosphate (Sano et al. 1999). Under such starvation conditions,
autophagic degradation is activated in BY-2 cells (Moriyasu
and Ohsumi 1996). Therefore, some might be involved in the
autophagic process.
Lipid metabolism genes showed a similar pattern of
expression to the ATP-independent proteases. Cell division is
Gene expression during the growth of BY-2 cells
the duplication process of the cells and requires a net increase
in membranes and organelles. Thus, lipid synthesis-related
genes grouped into B and C might be the genes required for
this process during cell division. Lipid synthesis-related genes
in group G might not only represent the increase in membranes
during cell expansion, but also be related to the differentiation
of the cells for sensing environmental signals (see below). In
this view, it is interesting to note that both the phosphoinositide and sphingolipid metabolism genes were up-regulated
at the stationary phase, whereas fatty acid and phosphoglycerolipid metabolism genes were not. Among the five genes for
phosphatidylinositol kinases in our ESTs, three were found in
group G and the other two showed slightly higher expression at
the stationary than log phase. Likewise, two genes were found
in both groups E and G among six genes that might be involved
in sphingolipid metabolism. Because the sphingolipid-sterolrich microdomains in the plasma membrane are known to be
enriched transmembrane protein kinases, and are thought to be
the site for signal perception (Lai 2003), activation of sphingolipid synthesis at the stationary phase might relate to the differentiation of the cells for detecting environmental signals.
Both membranes and the cell wall are determinants of
plant cell morphology and organization. Therefore, genes
related to cell wall synthesis can be induced at cell growth and
expansion phases. As shown in Fig. 4, most genes related to
cell wall synthesis were found in groups C, D and G. This
expression pattern is consistent with the fact that no cell expansion takes place during the lag phase.
Genes that showed apparently higher expression at the stationary phases (group G) were transmembrane protein kinases
and transcription factors for the regulation of gene expression.
Over 25% of the genes for transmembrane protein kinases and
about 15% of genes related to transcription regulation were
found in group G. In addition, over 10% of non-receptor
kinases, many of which could be involved in the signal transduction process, were also found in group G. This pattern of
gene expression suggests that cells that reach the stationary
phase differentiate in response to extracellular signals. Indeed,
BY-2 cells at the log phase have little ability to respond exogenously to added brassinosteroids, whereas stationary phase
cells can respond to these phytohormones (Miyazawa et al.
2003). This finding clearly correlates with our findings that a
gene for EST number 6278, which encodes a tobacco homolog
of brassinosteroid receptor BRI1, was activated about 2.7-fold
at the stationary phase compared with both the lag and log
phases. Likewise, a cytokinin-induced gene, CIG1 (Kimura et
al. 2001), was greatly up-regulated (about 12-fold) at the stationary phase. BY-2 cells do not require any cytokinins in the
medium for cell growth because of their high content of cytokinins (Roef and Van Onckelen 2004). Thus, endogenous cytokinin might activate the expression of this gene at the stationary
phase.
The other classes of genes that were mainly activated at
stationary phases were genes for channels and transporters.
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Among 97 channel/transporter genes on our array, 19 genes
(about 20%) were found in group G. This suggests that stationary phase cells activate the transport of nutrients from the
extracellular space and increase the intermembrane transport of
small molecules, which include secondary metabolites.
Change in organelle activities from the view of global gene
expression
Stationary phase cells increase the cell volume (Fig. 1B)
by increasing the vacuole volume. As such, it is interesting to
note that all vacuolar water channels, and a vacuolar pyrophosphatase, both of which are major membrane proteins of the tonoplast (Maeshima 2001), were found in groups F and G.
Therefore, cell expansion at the stationary phase, with a concomitant increase in the vacuolar volume, is regulated at least
in part at the transcription level in the BY-2 cells as in the case
of other plant systems (Maeshima 2001). However, genes that
might be located in many tubular vacuoles found in log phase
cells (Kumagai et al. 2004) cannot be assigned to our microarray analysis, possibly due to a lower abundance of water channels and pyrophosphatases in the tonoplast of such vacuoles.
Not only vacuolar genes that were activated at the stationary phase, but also some other organelle-related genes, seemed
to be controlled during cell growth. About 30% of the mitochondrial genes were found to be either group B or C. This
observation suggests that the mitochondria are quite active in
the log phase. This is actually the case, because BY-2 cells are
known to contain high levels of ubiquinone, which is a cofactor for the mitochondrial respiration system (Ikeda et al. 1974).
The other organelle system that changes expression during the cell growth of BY-2 is the endomembrane system (Matsuoka 2004). We analyzed whether genes for the secretory
machinery were differentially regulated during growth of BY-2
cells. Among the 73 genes related to the transport machinery of
the secretory pathway, 25 showed differential expression at different phases of cell growth. Because SNARE proteins are
known to be major determinants for the fusion of transport vesicles to organelles, it is expected that such classes of genes
would be differentially regulated during cell growth (Surpin
and Raikhel 2004). There were 12 SNARE genes spotted on
our microarray. Two of these, 3294 and 8344, which are
homologs of Arabidopsis Knolle and NPSN11, respectively,
were found in group C. This observation, in other words high
expression at the log phase, is consistent with previous observations that both of these Arabidopsis SNAREs are known to
be involved in cell plate formation (Surpin and Raikhel 2004).
EST number 7544, which encodes a homolog of the Arabidopsis SNARE protein AtSYP32, also showed up-regulation of
expression at the log and stationary phases. Other SNAREs
showed no clear differential expression.
Comparison with Arabidopsis root-expressed genes
The expression pattern of BY-2 genes was compared with
that of genes expressed in Arabidopsis root apex (Birnbaum et
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Gene expression during the growth of BY-2 cells
al. 2003). We first identified the closest homolog of the Arabidopsis gene for each BY-2 EST that showed differential expression (Supplementary Table 2). Almost all BY-2 ESTs that can
encode proteins with significant homology to known gene
products had at least one homolog gene in Arabidopsis. Using
Arabidopsis homolog data, we compared whether the tobacco
genes classified into each group (Fig. 3) correlated with the
localized expression domain (LED) of Arabidopsis genes
(Birnbaum et al. 2003), which were classified based on gene
expression in the roots (Fig. 5). The most pronounced relationship of the groups and LED was the relationship of LED 8 and
group B. In this case, over 30% of group B gene homologs
were found in LED 8. About 15% of group C gene homologs
were also found in LED 8. These observations clearly indicated that log phase BY-2 cells, which are active in cell division, show similar gene expression to (root) meristematic cells.
Likewise, close to 20% of group A gene homologs were also
found in LED 8, most of which were related to chromosomal
replication. Another class of common genes in these groups
and LED 8 were ribosomal proteins and histones, along with
several DNA replication-related genes including DNA methylase and nucleolin, cell cycle regulator genes such as Ran GAP
and cytokinesis-related genes, including Knolle.
Fig. 5 Comparison of the groups of genes found in this study and
genes found in LEDs that were temporally and spatially regulated in
Arabidopsis roots.
Eighteen genes of unknown function were common in
LED 8 and group B (Table 1). Because cell division-related
genes were found predominantly in groups B and C, it is likely
Table 1 Comparison of group B genes and two independent Arabidopsis root
tip microarray data to determine possible genes involved in plant cell division
BY-2 EST
No.
Arabidopsis
homolog
LED 8
(Birnbaum et al. 2003)
Cluster 2
(Himanen et al. 2004)
726
1583
2906
3837
6310
1279
1583
1596
2049
2480
2561
2854
3461
4126
4225
4629
4652
4760
4777
3712
4401
At2g18220
At2g40360
At1g06190
At3g02220
At5g16750
At1g26840
At2g45860
At4g39630
At5g13960
At1g52930
At1g16070
At2g25830
At2g20490
At5g39600
At3g25940
At1g22270
At3g07230
At5g37010
At2g14880
At5g43700
At1g30070
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
Only genes whose function could not be predicted by a database search were listed. Numbers of BY-2 ESTs and the closest Arabidopsis homolog for the protein coded by the BY2 ESTs are shown. + indicates the presence of the genes in the corresponding dataset.
Gene expression during the growth of BY-2 cells
Fig. 6 Overlapping of abscisic acid, salicylic acid and hormone-free
regulated genes. The number of genes in each group is indicated in
each area. ABA, abscisic acid; SA, salicylic acid; HF, hormone free.
that that most of these common genes with unknown function(s) that could not be predicted by the homology search are
involved in cell division in plants. We also compared group B
genes with Arabidopsis genes that were activated during the
formation of lateral roots (Himanen et al. 2004). Among the
group B genes, 17 were found in cluster 2 of the lateral root
dataset. Among them, seven encoded a protein of unknown
function (Table 1). In the case of the comparison of LED 8 and
cluster 2, 29 unknown genes were found commonly, five of
which were also found in group B (Table 1). In total, 21
unknown genes were highlighted as candidate genes that are
involved in plant cell division.
Response of stationary phase cells to different phytohormones
As previously described, our microarray analysis indicated
that stationary-grown cells express many homologs of genes
for perceiving extracellular signals. We tested whether stationary phase cells could respond to different phytohormones. We
chose salicylic acid (SA) and abscisic acid (ABA) because SA
is known to induce defense-related genes in many plants, and
ABA causes cell cycle arrest in BY-2 cells at the G1 phase
(Swiatek et al. 2002). Stationary-grown cells were washed with
a medium without phytohormones and incubated with medium
that contained either SA, ABA or no phytohormones. After
24 h, cells were harvested and their gene expression monitored
with the microarray analysis. Genes that showed two-fold or
greater changes relative to stationary phase cells in both of the
duplicated experiments were selected, and the overlapping of
genes common or unique to these three conditions was classified (Fig. 6, Supplementary Table 4). In total, 705 genes
showed differential expression with at least one of the three
treatments relative to the stationary phase. The number of
genes suppressed was higher than the number induced in all
three conditions, and this difference was mainly the result of
the difference in gene numbers that were commonly changed
under these conditions: 33 genes were up-regulated under all
three conditions, whereas 124 genes were down-regulated at
the same time. This suggests that many genes that were active
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in the stationary phase were suppressed upon changing to a
fresh medium.
Among the conditions tested, medium containing ABA
caused the most significant changes in gene expression. About
100 genes were either up- or down-regulated specifically by
this hormone (Fig. 6). This implies that stopping the cell cycle
at the G1 phase with this phytohormone might depend on the
massive change in gene expression. The proportion of ABAinduced genes that showed homology to known genes (36%)
was similar to that of the whole EST. In contrast, more than
50% of the SA-induced genes have homology to known genes.
Among these genes, five (978, 5890, 6758, 7429 and 8847)
correspond to genes involved in defense responses. These
observations indicated that stationary-grown BY-2 cells can
respond differentially to different signal molecules that had
been applied extracellularly and support the possibility that
BY-2 cells at the stationary phase express genes for responding
to extracellular signals.
Conclusion and prospective
We analyzed global changes in gene expression in tobacco
BY-2 cells during growth and confirmed that almost all genes
related to cell division were highly expressed at the log phase.
In addition, our data suggested that kinesins are the major players of molecular motors that precipitate events during cell cycle
progression in plants. We also found that many genes that
showed elevated expression at the log phase have homologs
that are expressed predominantly in dividing cells of Arabidopsis roots. Using such knowledge, we could identify 21 novel
genes that are candidates to be involved in plant cell division.
The next challenge from this mass analysis is to confirm experimentally that these genes are actually involved in the division
of plant cells.
Our analyses revealed that BY-2 cells that reach the stationary phase express many genes that are likely to be involved
in sensing extracellular signals. Gene homologs for the transmission of these signals were also induced upon reaching the
stationary phase. Our analyses also showed that stationary
phase cells can respond to phytohormones and modulate the
expression of several hundred genes. These findings suggest
that stationary-grown BY-2 cells will be a possible excellent
system to analyze the molecular mechanism of extracellular
signal reception and transduction. Future analyses of phytohormones other than ABA and SA, or other extracellular stimuli
such as salts and elicitors, at the stationary phase of BY-2 cells
might reveal various new aspects of plant signal transduction.
Our tobacco BY-2 microarray will provide a novel rapid
method for analyzing genes downstream of the regulatory
genes. As the generation of transgenic BY-2 cells is rapid (less
than 3 weeks to obtain transgenic calli on plates) compared
with generating transgenic plants, overexpression of the candidates for regulator genes is not time consuming, and analyses
of downstream genes using transgenic BY-2 cells could be easily undertaken using our microarray system.
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Gene expression during the growth of BY-2 cells
Materials and methods
Acknowledgments
Tobacco BY-2 cells were grown as described (Matsuoka and
Nakamura 1991). Lag, log and stationary phase cells were collected by
vacuum filtration using a filter paper attached to a Buchner funnel.
They were then frozen with liquid nitrogen and stored at –80°C before
use. For the treatment with different phytohormones, stationary-grown
cells were washed five times with 5 vol of medium without phytohormones, then inoculated into a medium containing either 40 µM SA,
20 µM ABA or no phytohormones and cultured for 24 h before the
cells were harvested.
A cDNA library was prepared from lag, log and stationary phase
cells, which were mixed, normalized and cloned as described (Demura
et al. 2002). Plasmids were prepared and sequenced using M13
forward primers to generate ESTs. For the preparation of DNAs for the
microarray, inserts of EST clones were amplified by PCR using standard M13 forward and reverse primers, and purified as described
(Demura et al. 2002). For the microarray experiments, total RNA was
extracted from frozen tobacco cells using TRIzol reagent (Invitrogen,
Tokyo, Japan). Poly(A)-rich RNA was prepared from total RNA
using a GenElute mRNA Miniprep Kit (Sigma). The detailed
protocol is described at our website: (http://mrg.psc.riken.go.jp/strc/
mRNA%20prep.htm).
For the RT–PCR, first strand cDNA was prepared with the
Superscript II reverse transcription system using total RNA, which was
prepared as described. QRT–PCR was carried out using Light Cycler
(Roche), essentially as described in the manufacturer’s instructions
using appropriate primers.
The microarray was designed and prepared as described (Demura
et al. 2002). Microarray hybridization was carried out using a Cy5labeled probe prepared from the poly(A)-rich RNA essentially as
described (Demura et al. 2002), but with a slight modification: during
the hybridization we included Cy3-labeled oligonucleotides against the
vector sequences (TGTAAACGACGGCCAGTGAATTGTAATAC and
CAGGAAACAGCTATGACCATGATTACGCCA). After hybridization,
both Cy3 and Cy5 signals were collected as described (Demura et al.
2002). After removing data for genes that showed no Cy5 or Cy3 signals, the ratio of the intensities of Cy5 and Cy3 fluorescence was used
as the signal intensity. Because each slide contained duplicated spots
for each gene, we calculated the ratio of signals of each spot, and
genes that showed less than a three-fold difference on two spots. This
was used for the analysis. After calculating the average of the signals
of genes that remained in the list for analysis, the averages of the
hybridization intensities were normalized using the median value. The
median-normalized Cy5/Cy3 values were used for the comparison of
each time point.
After triplication of the experiments, genes that showed significant differences from the whole genes were selected. The criteria for
this selection were that the ratios at two growth phase levels were
lower than two-thirds, and P < 0.05 (Student’s t-test) of the whole ratio
data. Patterns of gene expression of the selected genes were grouped
based on the following criteria. If the difference of the level of expression in two growth phases was smaller than one-third of the maximum
expression, the two were not considered significantly different. If the
number of genes in each pattern was less than 20, these were not considered as a group. Homologs of EST-encoded proteins were searched
using the BLASTX program against a non-redundant data set found in
the public databases.
We thank Y. Yahara for DNA sequencing, T. Narisawa and M.
Shimizu for the amplification and purification of EST inserts.
Supplementary Material
Supplementary material mentioned in the article is available to
online subscribers at the journal website www.pcp.oupjournals.org.
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(Received June 1, 2004; Accepted July 7, 2004)