Abstract Elucidating the regulatory mechanisms of

plant organ formation is an important component of

plant developmental biology and will be useful for

crop improvement applications. Plant organ forma-

tion, or organogenesis, occurs when a group of pri-

mordial cells differentiates into an organ, through a

well-orchestrated series of events, with a given shape,

structure and function. Research over the past two

decades has elucidated the molecular mechanisms of

organ identity and dorsalventral axis determinations.

However, little is known about the molecular mech-

anisms underlying the successive processes. To de-

velop an effective approach for studying organ

formation at the molecular level, we generated organ-

specific gene expression profiles (GEPs) reflecting

early development in rice stamen. In this study, we

demonstrated that the GEPs are highly correlated

with early stamen development, suggesting that this

analysis is useful for dissecting stamen development

regulation. Based on the molecular and morphological

correlation, we found that over 26 genes, that were

preferentially up-regulated during early stamen

development, may participate in stamen development

regulation. In addition, we found that differentially

expressed genes during early stamen development are

clustered into two clades, suggesting that stamen

development may comprise of two distinct phases of

pattern formation and cellular differentiation. More-

over, the organ-specific quantitative changes in gene

expression levels may play a critical role for regulat-

ing plant organ formation.

Keywords Rice Æ Organ formation Æ Early stamen

development Æ Organ-specific gene expression

profiling Æ Microarray analysis

AbbreviationsaRNA antisense RNA

cDNA complementary DNA

DEPC diethyl pyrocarbonate

dUTP deoxyuridine triphosphate

EMS EXCESS MICROSPOROCYTES

ESTs expression sequence tags

EXS EXTRA SPOROGENOUS CELLS

FIL FILAMENTOUS FLOWER

LLS LETHAL LEAF SPOT

LPA linear polyacrylamide

msca1 male sterile converted anther1

NZZ NOZZLE

OsMADS7 rice MADS-box protein 7

Xiao-Chun Lu, Hua-Qin Gong contributed equally to this work.

Electronic Supplementary Material Supplementary materialis available for this article at http://www.dx.doi.org/10.1007/s11103-006-0054-3

X.-C. Lu Æ H.-Q. Gong Æ M.-L. Huang Æ S.-L. Bai ÆX. Mao Æ S.-G. Li Æ L. Wei Æ J.-S. Yuwen Æ Z.-H. Xu ÆS.-N. BaiPKU-Yale Joint Research Center of Agricultural and PlantMolecular Biology, National Key Laboratory of ProteinEngineering and Plant Gene Engineering, College of LifeSciences, Peking Unviersity, Beijing 100871, China

Y.-B. He Æ Z. GengDepartment of Probability and Statistics, School ofMathematical Sciences, Peking University, Beijing 100871,China

S.-N. Bai (&)National Plant Gene Research Center (Beijing),Beijing 100871, Chinae-mail: shunongb@pku.edu.cn

Plant Mol Biol (2006) 61:845–861

DOI 10.1007/s11103-006-0054-3

123

Molecular analysis of early rice stamen developmentusing organ-specific gene expression profiling

Xiao-Chun Lu Æ Hua-Qin Gong Æ Mo-Li Huang ÆSu-Lan Bai Æ Yang-Bo He Æ Xizeng Mao ÆZhi Geng Æ Song-Gang Li Æ Liping Wei ÆJie-Shuai Yuwen Æ Zhi-Hong Xu Æ Shu-Nong Bai

Received: 25 July 2005 / Accepted: 27 March 2006� Springer Science+Business Media B.V. 2006

PCR polymerase chain reaction

PHD plant homeodomain

RNA ribosome nucleic acid

RT reverse transcription

SPL SPOROCYTELESS

TPD TAPETUM DETERMINANT

Introduction

One of the most remarkable breakthroughs in plant

developmental biology was the discovery of a genetic

mechanism that determines floral organ identity (the

ABC model; Coen and Meyerowitz 1991). Since the

ABC model was first proposed, researchers have

strived to understand how a primordium (a group of

undifferentiated cells) can elaborate its predetermined

identity into a characteristic shape, structure and

function (Koltunow et al. 1990; Goldberg et al. 1993).

This process, known as organ formation, is a natural

consequence of organ identity determination in plant

organ development. Studying this phenomenon is

beneficial economically, because properly elaborated

reproductive organs such as grains and cereals com-

prise some of the most important plant food products.

However, aside from the identification of genes in-

volved in dorsalventral axis determination (Waites

and Hudsog 1995; McConnell and Barton 1998; Sawa

et al. 1999), little progress has been made in dissecting

the molecular mechanisms underlying organ

formation.

From morphological observations, plant research-

ers have proposed that a primordium undergoes a

series of differentiating events before an organ is

formed. These events include the three-dimensional

axes determination (dorsal–ventral, basal–distal and

medio-lateral; for review see Poethig 1997), tissue

differentiation (including epidermal, ground and vas-

cular tissues) and cellular differentiation (such as

sporogenous cells in anthers or ovules, and photo-

synthetic cells in leaves). The developmental fate or

pattern is determined at an early primordium stage

(Sussex 1955a, b; Sachs 1969). Thus, analysis of the

molecular events governing early primordial devel-

opment will likely reveal regulatory mechanisms

underlying organ formation.

To date, however, no direct molecular analysis of

early primordia development has been reported. In

recent years, two major approaches have been used to

study the regulatory mechanism of organ formation:

(1) searching for downstream targets of the genes that

determine organ identity (Sablowski and Meyerowitz

1998; Zik and Irish 2003; Bey et al. 2004) and (2)

screening of mutants with aberrant organ shape or

structure phenotypes (Freeling 1992; Tsukaya 2003;

Sanders et al. 1999; Sorensen et al. 2002). In the case of

stamen development, large-scale mutant screens have

revealed only three Arabidopsis genes (SPL/NZZ,

EMS/EXS, TPD) and one maize mutant (msca1) that

affect early stamen development from stages 1 through

7 (Sanders et al. 1999; Sorensen et al. 2002; Schieft-

haler et al. 1999; Yang et al. 1999; Canales et al. 2002;

Zhao et al. 2002; Yang et al. 2003; Chaubal et al.

2003). This dearth of identified targets suggests that the

molecular events underlying organ formation may be

too complicated to be properly analyzed by conven-

tional genetic approaches.

To address this issue, researchers are exploring new

analysis techniques. Wellmer and colleagues (2004)

used floral mutant GEPs to decipher stamen develop-

ment regulation. These authors identified over 1,000

genes with altered expression levels in mutant flowers

lacking stamen. Coen et al. (2004) proposed new con-

ceptual and experimental approaches to the problem.

These authors described organ formation using four

regional parameters. Coupled with mechanistic mod-

eling, these parameters captured interactions among

regional identities and regionalizing and polarizing

morphogens. This approach was able to associate gene

expression patterns with shape changes.

Recent technical advances such as microarrays,

RNA linear amplification and laser capture microdis-

section have provided powerful tools for analyzing gene

expression changes of micro-samples directly. We per-

formed microarray analysis on early stamen develop-

ment in rice, a model plant of great agronomy

importance with complete genome information. Cellu-

lar differentiation, and particularly in sporogenous

cells, has been the greatest focus in research of stamen

development. It remains unclear, however, how the

ground tissue, where the sporogenous cells are initiated,

differentiates from a group of buckled founder cells in

the floral meristem. Therefore, we believe that a

molecular analysis of the developmental processes of

the entire stamen primordia will provide important

information for the future study of rice stamen devel-

opment. For these studies, we dissected the entire sta-

men primordia for analysis, and demonstrated that the

gene expression changes are highly correlated with the

morphogenetic processes of early stamen development.

Thus, this is a useful approach to comprehending sta-

men development regulation. Based on the molecular

and morphological correlation, we found that over 26

genes, that were preferentially up-regulated during

early stamen development, may participate in stamen

846 Plant Mol Biol (2006) 61:845–861

123

development regulation. In addition, we found that the

GEPs reflecting primordium initiation to completion of

meiosis cluster into two clades, suggesting that this

developmental period may contain two molecularly

distinguishable phases. Also, we found that the organ-

specific quantitative changes may be crucial for organ

formation. Furthermore, in situ analysis of OsMADS7

expression addressed how the microsporogenous cells

are initiated from somatic cells.

Materials and methods

Plant materials

Seeds from the rice strain Zhonghua 15 (Oryza stativa

L. indica) were kindly provided by Dr. Yongbiao Xue

at the Institute of Genetics and Developmental Biol-

ogy, Chinese Academy of Sciences. The seedlings were

grown in a tray filled with soil at 25�C and a 9 h day/

15 h night cycle regime. One-month-old seedlings were

transplanted into plastic pots and cultivated until usage.

Sample collection and morphological observation

Samples for morphological observation were collected

from young panicles 2 mm to 6 cm in length. Semi-thin

cross sections and scanning electronic microscopy

(SEM) were conducted according to the procedures

described in Liang et al. (2003) and Bai et al. (2004).

Stamens at stages 2, 3, 5 and 7 were identified using

established morphological traits (see Results), and

collected with pretreated dissecting needles under a

dissecting microscope (Olympus SZX12, Japan). The

primordia of the 3rd leaf were collected under the

dissecting microscope from seeds soaked for 3 d at

25�C. Differentiated leaf samples were collected from

the 3rd leaf when it had just fully expended. All tools

used in the sample collection were treated with 0.1%

DEPC, and the dissected samples were immediately

moved to the Trizol extraction buffer (Promega,

USA). To maximally synchronize the samples at indi-

vidual stages, we collected stamen samples from 3 to 6

florets that shared the greatest identical morphologies.

RNA isolation and amplification

Stamen and leaf primordia at various stages were

homogenized in the Trizol reaction buffer with Micro

Tissue Grinders (Kimble Knontes, USA). Total RNA

was isolated according the manufacturer’s protocol

except that before adding chloroform, 5 lg LPA was

added into 60 ll extract solution as a RNA carrier.

We amplified mRNA from the total RNA according

to methods of Baugh et al. (2001) with the following

modifications: after the second cDNA strand was syn-

thesized, the double strand cDNA was purified with

Microcon YM-100 (Millipore, USA). After in vitro

transcription with a T7 ampliscribe kit (Epicentre,

USA) for 4 h at 42�C, the antisense RNA (aRNA) was

purified with a Genelute mammalian total RNA mini-

prep kit (Sigma, USA) according to the manufacturer’s

protocol. The quality of amplified aRNA was examined

by electrophoresis on a 1% agarose gel (Figure S1).

To minimize the possible negative effects upon the

microarray analysis generated by the variation of

individual organ primordium, we designed a ‘‘pool

strategy’’. That is in one sample collection, we col-

lected stamen primordia at same developmental stages

from 3 to 6 florets for one RNA isolation and ampli-

fication. For each sample, we repeated at least 4 col-

lections (that means 4 independently prepared aRNA).

Then we pooled the independently prepared aRNA for

labeling. In this way, we ensure our samples with rea-

sonable biological replications.

Experimental design for microarrays

To obtain maximum repeats with minimal cDNA

chips, we adopted the Loop Design principle devel-

oped by Kerr and Churchill (2001), shown in Fig. 1.

With this experimental design, we equally divided the

pooled aRNA of each sample into two parts, and la-

beled with Cy3 or Cy5, respectively. Since each labeled

sample will be used to hybridize with 2 different sam-

ples, every pooled aRNA from each sample actually

was used 4 times. In this way, we ensured the technique

replication to minimize the possible negative effects

generated in the hybridization procedures.

2

3

45

6

1

Fig. 1 Loop design of the microarray experiments. Numbers 1–4represent stamen samples at stages 2, 3, 5 and 7, designated assamples 1–4 respectively; Numbers 5 and 6 represent primordiaof the third leaves and the expanded third leaves. Arrowsindicate pairs of hybridized samples. Arrowheads indicatessample labeled with Cy3; and arrowend represents sampleslabeled with Cy5

Plant Mol Biol (2006) 61:845–861 847

123

This procedure is utilized in 2-channel microarray

experiments, and requires that each sample is hybrid-

ized to each of two different samples in two different

dye orientations. This procedure is also known as

blocking, and results in half of the variance per esti-

mate, because each sample occurs twice. The Loop

Design reduces the overall cost of the experiment

because fewer chips are required. However, if one chip

performs poorly, then the variability (and thus bio-

logical information) is compounded. Care must be

taken to produce high quality hybridizations when

using this approach.

cDNA microarrays

The cDNA chips were prepared by UniGene

(www.chinagenenet.com, China), containing 10,367

expression sequence tags (ESTs). Among these ESTs,

10,254 represented uni-sequences that we randomly

selected and sequenced from a shoot apex cDNA li-

brary. The library was constructed with mixture of

shoot apexes that had just initiated into reproductive

growth, with panicles ranging from 1 mm to 10 cm.

The remaining 113 ESTs were control genes. We

examined the EST distributions in rice chromosomes

to ensure adequate representation of the rice genome

on our chip. Figure S2 shows that our selected ESTs

were evenly distributed among the chromosomes,

suggesting that the ESTs used herein were represen-

tative of the rice genome, at least in terms of chro-

mosome localization. We would like to note that

although some genes involved in organ formation and

meiosis such as OsMADS7 and HOP1 have been in-

cluded in this array, the homologs of other genes

known to be necessary for stamen development, such

as AP3, SPL, and EMS1, were unfortunately not in-

cluded. This has made it difficult for us to verify the

GEP results.

Chip hybridization

Amplified aRNA from the six samples was examined

with a spectrophotometer (Thermo Spectronic Ele-

mental Hek IOS, USA) to ensure equal quantity and

quality (Table S1). Sample labeling with Cy3-dUTP or

Cy5-dUTP and chip hybridizations were performed

according to the protocol developed by BioStar in

UniGene (www.chinagenenet.com).

The hybridized arrays were scanned with ScanArray

4000 (Packard Biochip technologies, Inc. USA) at the

laser intensity and photomultiplier tube voltage setting,

providing the best dynamic range for each chip. In the

two channels, the ratio of the mean signal intensities

was ~1, and the percentage of spots with saturated

pixels was 0–0.25%. Image segmentation and spot local

background quantification was performed with the

analysis software GenePickPro 3.0 (Axon Instruments,

Inc. USA). We have made the array data publicly

available at the online RStGEP Database (http://

www.cbi.pku.edu.cn/database/baisn/page/indexlu.htm,

IV-A).

As mentioned above, the high quality hybridization

is critical to the validation of the microarray data. To

test the reproducibility and the quality of the chip

hybridizations, we set up duplications with the same

pairs of samples. An almost identical number of down-

and up-regulated ESTs of the duplication suggested a

satisfactory reproducibility of the hybridization proce-

dure (Table S2). The high correlation coefficient

(0.935) between the two set of data evidenced a high

quality of the hybridization, suggesting that the

microarray data was valid.

Data processing

To obtain reliable and useful information from the

microarray experiments, we conducted following data

analyses:

Normalization

To minimize the variation generated during the

hybridization process, the raw data of signal intensity

generated by the scanner were normalized with

Rowless (www.jax.org/staff/churchill/labsite/software/

anova/rmaanova). Figure S3 shows a satisfactory

distribution pattern after normalization (for complete

data see RStGEP Database IV-B). In addition, the

similarity of the distribution patterns before and after

normalization suggested that the data obtained from

the chip hybridizations are reliable.

Determination of differentially expressed genes

Although the log2-transformed ratio of signal intensity,

generally a two-fold cutoff, is widely used for analyzing

the change of gene expression level between various

samples, an analysis of variance (ANOVA) model was

strongly recommended to distinguish gene-specific ef-

fects from other effects generated by arrays and dyes,

especially for the Loop Design (Kerr and Churchill

2001). Thus we adopted the ANOVA model to eval-

uate gene expression levels using the R-MAANOVA

program (www.jax.org/staff/churchill/labsite/software/

anova/rmaanova). To ensure that our gene expression

848 Plant Mol Biol (2006) 61:845–861

123

data would be comparable with the widely used ‘‘two-

fold cutoff’’, we used a two-fold cutoff as a reference

point to choose the proper P value to set as the sig-

nificant level. Figure S4 shows that the number of dif-

ferentially expressed genes sorted out at pE5 as defined

by the F-test is closest to that obtained using a two-fold

cutoff. We therefore defined genes with expression

values below pE5 as differentially expressed genes.

With this standard, 7,225 out of 10,254 ESTs were de-

fined as being differentially expressed among the six

samples (RStGEP Database IV-D). As each EST has 6

specific expression values correspondently to the 6

samples, respectively, after the data processing with the

R-MAAMOVA program, we can use the expression

values for the additional analyses described below.

Preferential distribution of the differentially-expressed

ESTs among organs

To determine the biological significance of the differ-

entially expressed ESTs among the samples, we ana-

lyzed their preferential organ distributions. We first

defined ESTs differentially expressed between the four

stamen samples, and the two leaf samples, designated

the ‘‘O’’ set; those differentially expressed only among

the four stamen samples as the ‘‘St’’ set; and those dif-

ferentially expressed between the two leaf samples as

the ‘‘L’’ set (Figure S5). We then labeled these ESTs

with O, St or L in an Excel table, and easily identified

ESTs falling within two or more different sets, resulting

a number of subsets named 137, 1449, 1656, 2095, 176

and 1712 (Figure 2; RStGEP Database IV-D).

Gene ontology analysis

To sort out genes for further functional investigation,

we carried out gene ontology analysis with the infor-

mation provided in www.geneontology.org.

Clustering

The expression values of ESTs in the O and St sets

(with 6 and 4 samples, respectively) were used as inputs

for the clustering analyses using the self-organizing

map (SOM) feature in Spotfire (www.tigr.org). The

clustering data were presented selectively as Figure 3.

Full data see (RStGEP Database IV-E).

KOBAS analysis

To determine the biological significance of the clus-

tering pattern, we used KOBAS (Mao et al. 2005) to

identify statistically significant pathways in the two

clades of ESTs, clade 1 (samples 1 and 2) versus clade 2

(samples 3 and 4) (RStGEP Database IV E) based on

v2 test and KEGG v35 data, with the default cutoffs

(rank 5 and evalue 10)5) suggested in the original

article.

Verification of gene expression pattern

of selected genes

To validate the expression patterns revealed by the

microarray analyses, we conducted RT-PCR to detect

selected genes using the samples prepared for the

microarrays. We selected genes for validation accord-

ing to two criteria: first, the genes representing various

expression patterns revealed in the clustering analysis

(122 genes, Table S3); second, the genes having fold-

change higher than 6 (88 genes Table S4). Total RNA

was isolated using the procedure described above, and

the mRNA population was reverse-transcribed using

the ThermoScript RT-PCR system (Invitrogen, USA).

Primers employed in the RT-PCR are listed in Tables

S3 and S4.

To further investigate the expression patterns at a

cellular level, we conducted in situ hybridizations on

Fig. 2 Preferential organ distributions of differentially expressedESTs. The total number of ESTs that were differentiallyexpressed in the O set was 6912 (represented by the largecircle), of which 1712 were only differentially expressed betweenthe two organ types (area filled with yellow). The total number ofESTs differentially expressed in the St set were 3242 (repre-sented by the circle on the left), of which 137 were not includedin the O set (area filled with light green). The total ESTsdifferentially expressed in the L set were 3927 (represented bythe circle on the right), of which 176 were not included in the Oset (area filled with light blue). The definitions of the areaslabeled 1449, 1656 and 2095 are explained in the text

Plant Mol Biol (2006) 61:845–861 849

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Fig. 3 Representative clusters revealed from the clusteringanalysis. Of the 12 clusters revealed from the clustering analysisof the O set with the 6 samples, 35% of ESTs gave clusteringpatterns in which the sample 1, 3 and 5 were paired with samples 2,4 and 6, respectively (A); 30.7% of ESTs gave clustering patterns inwhich the sample 1 and 3 were paried with samples 2 and 4,respectively (B); and 21.6% of ESTs gave clustering patterns inwhich the samples 1 and 2 were clustered together (C). The

remaining ESTs did not give clustering patterns that correlatedwith morphogenetic events (D). Of the 12 clusters revealed fromthe clustering analysis of the St set with the 4 stamen samples,84.8% of ESTs gave clustering patterns in which the sample 1 and 3were paired with samples 2 and 4, respectively (E); whereas 3.2%of ESTs gave a clustering pattern in which only samples 1 and 2were clustered together (F). The remaining ESTs did not giveclustering patterns that correlated with morphogenetic events (G)

850 Plant Mol Biol (2006) 61:845–861

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selected genes. The procedure used for the in situ

hybridization was described previously (Bai et al.

2004). Primer sequences used for generating the probes

are listed in Table S5.

Results

Morphological analysis of early development

in rice stamen

Rice stamen morphogenesis has been observed using

various methods (Raghavan 1988; Nonomura et al.

2003). However, a systematic developmental morpho-

logical description of the stamen for studying organ

formation is not available. To collect samples at the

proper developmental stages, we compiled a morpho-

logical description of rice stamen early development,

from the primordium initiation to the completion of

meiosis. Using criteria similar to those used to describe

Arabidopsis stamen development (Sanders et al. 1999),

we divided the development process into seven stages

occurring prior to the pollen release from the tetrads

(Fig. 4A–N). At stage 1, the cross-section of the sta-

men primordia is rounded and no cellular differentia-

tion is observed under the epidermis (Fig. 4A and F).

Subsequently, the overall form of the stamen primor-

dia changes dramatically into a trapezoid-shape, which

is defined as stage 2. The cells at the four trapezoid

corners, beneath the epidermis, are distinguishable

from adjacent cells by their enlarged sizes. These are

defined as the archesporial initials (Fig. 4B, G and O).

Stage 3 is defined by a basic radial pattern of the rice

stamen, which is characterized by the differentiation of

all three major stamen tissues, e.g., epidermal, pro-

vascular and ground tissues. It is worth noting that at

Fig. 4 Morphological observations and morphological criteriafor sample collection. The rice developmental process prior totetrad separation was divided into 7 stages as indicated by thecross sections (A–E, K, M), and SEM (F–J, L, N) of respectiveimages from stage 1–7. Panels O–R show stamens at stages 2, 3, 5and 7, respectively. These stamen samples were used for isolatingRNA for microarrays and were designated samples 1–4,respectively. A detailed morphological description of each

developmental stage is given in Table S6. Ar: archesporium; C:Callus; Ca: carpel; E: epidermis; En: endothecium; le: lemma; Lo:lodicule; MC meiotic cells; ML: middle layer; MMC: microsporemother cells; pa: palea; PPC: primary parietal cells; Sp:sporogenous cells; SPC: second parietal cells; St: stamen; T:tapetum; Tds: tetrads; v: vascular tissue. Bars: 20 lm (A–E, K,M); 65 lm (F–J, L, N) and 135 lm (O–R)

Plant Mol Biol (2006) 61:845–861 851

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this stage, the ground tissue has undergone preliminary

differentiation into intermediate, sporogenous, and

primary parietal cells (Fig. 4C, H and P). Stage 4 is

initiated when the parietal cells divide into two layers

(Fig. 4D and I). Stage 5 occurs when the parietal cells

divide into three layers (Fig. 4E, J and Q). Stage 6 is

defined as the completion of differentiation of all ma-

jor cell types, including sporogenous (differentiated

into meiotic cells at this stage), parietal, particulularly

the tapetum, and vascular cells (Fig. 4K and L). For

convenience, stage 7 includes the entire meiotic pro-

cess to the formation of tetrads (Fig. 4M, N and R). In

addition to cellular differentiation of the stamen in the

cross section, correlated changes in the length of the

stamen and to the shape of the carpel were also used to

confirm stage distinction (Table S6).

Based on the above morphological criteria and

respective biological significance, we collected stamens

at stages 2, 3, 5 and 7 under a dissecting microscope.

We used these stamen specimens subsequently for

microarray analysis (Fig. 4O–R). We also collected the

third leaf at its primordial stage from absorbing seeds,

and at its just-expanded stage from young seedlings

(RStGEP Database II-B) for comparison.

Changes of GEP are correlated with the early

development of rice stamen

We needed to correlate molecular changes with the

early stamen morphology, in order to apply our GEP

approach. To obtain reliable data with minimal

microarray hybridization, we used a Loop Design

(Kerr and Churchill 2001) to examine the GEPs of

early rice stamen development (Fig. 1), used a ‘‘pool

strategy’’ to prepare samples, and used F-test statistics

with a set P-value of pE5 to define differentially ex-

pressed genes (Figure S4) after standard hybridization

and data processing. With this standard, 7225 ex-

pressed sequence tags (ESTs) out of 10,254 were de-

fined as differentially expressed among the 6 samples

(RStGEP Database IV-D), and the numbers of these

ESTs between sample-pairs were well correlated with

their biological relationships (Table S7).

Differentially expressed ESTs are distributed

in an organ-preferential manner

To determine whether the changes reflected in the

GEPs are correlated with various organ development

schemas, we analyzed whether the differentially ex-

pressed ESTs were preferentially distributed between

the stamen and leaf. Those that we identified among

the four stamen samples were defined as set St,

representing genes differentially expressed during sta-

men development. Those that we found by comparing

the two leaf samples were defined as set L, represent-

ing genes differentially expressed during the leaf

development. Those that were determined from com-

parisons between the four stamen and the two leaf

samples were defined as set O, representing genes

differentially expressed during development of the two

different organs, including those found in the St and L

sets (Figure S5). In all, there are 3242 ESTs identified

in the St set (approximately 44.88% of the total 7225

differentially expressed ESTs), 3927 ESTs in the L set

(approximately 54.35%), and 6912 ESTs in the O set

(RStGEP Database IV-D).

Similar differentiation events may occur in different

organs, including cell elongation and vascular tissue

differentiation. Thus, some ESTs in the St set may also

be found in the L set. Labeling the differentially ex-

pressed ESTs identified 1656 (approximately 22.92%

of the total 7225 differentially expressed ESTs) in both

the St and L sets (Fig. 2), suggesting that these 1656

gene representatives are involved in differentiation

events shared by the stamen and leaf during develop-

ment (RStGEP Database IV-D). Meanwhile, 1712

ESTs (approximately 23.7% of the total 7225 differ-

entially expressed ESTs) in the O set did not occur in

either the St or L sets, suggesting that these ESTs

(subset 1712) represent genes only differentially ex-

pressed between the two types of organs, not among

the tested stages of either organ (RStGEP Database

IV-D). The ESTs in subsets 1449 and 2095 should be

those only expressed differentially during stamen and

leaf development, respectively. Notably, 137 ESTs in

the St set, and 176 ESTs in the L set were not included

in the O set. According to the principle of defining the

St, L and O sets (Figure S5), the ESTs in the 137 and

176 subsets should have exclusive correlation with

stamen and leaf development, respectively.

To verify the biological significance of the prefer-

ential organ distribution of the differentially ex-

pressed ESTs, we checked the correlations among the

genes with known functionalities and distributions.

Because little information is available on genes ex-

pressed specifically in early stamen development, we

focused on determining whether genes involved in

photosynthesis were preferentially expressed in the

leaf samples. We found that photosynthesis genes

such as pyruvate kinase (AK070512), Rieske Fe–S

precursor protein (AF527709), ribulose-5-phosphate-

3-epimerase (AK066306) and an antenna protein of

PSII (AK061295) were all highly expressed in the

leaf samples (RStGEP Database IV-D), suggesting

that the organ-preferentially distributed ESTs may

852 Plant Mol Biol (2006) 61:845–861

123

contain useful molecular information about organ

formation.

Genes annotated in 7 GO categories have

organ-preferential distributions

To further establish the correlation between the GEP

changes and organ development from a functional as-

pect, we conducted GO analyses of the differentially

expressed genes revealed in our experiments. We

found that among the 5576 differentially expressed

annotated genes, 21.59% (1204) could be classified into

12 of the 15 GO categories, and the genes in each GO

category were differentially distributed among the 6

subsets described in Fig. 2 (Table 1).

Genes representing a particular GO category that

were distributed in subset 1449 or 2095 (Fig. 2), may

suggest a preferential involvement of this GO category

in the development of either stamen or leaf. We first

calculated a ratio of total GO gene numbers in subset

2095 versus those in 1449 (1.81). Then we calculated

ratios of gene numbers in the two subsets of each GO

category, and found that the value of the ratios of the

gene numbers between the subsets 2095 and 1449 in

GO categories antioxidant (2.73), enzyme regulator

(2.43), signal transducer (1.93) and protein transport

(1.92) were higher than that of the total GO gene

number (1.81). Whereas, the value of the gene number

ratios between subsets 2,095 and 1,449 in the categories

of translation regulator (1.12), chaperone regulators

(1.53) and ligand binding proteins (1.69) were lower

than that of the total GO gene number (1.81). With this

criterion, the GO categories of enzyme, motor activity,

obsolete molecular function and transcription regula-

tor seem to be equally important to stamen and leaf

development.

Since GO offers a broad-spectrum qualitative anal-

ysis of gene functions, each GO category contains

many biochemical reactions. Thus, it is difficult to

indicate exact correlations among the GO categories

and organ development. However, it is known that

biochemical reactions such as oxidoreduction and sig-

nal transduction are active in leaves, and the afore-

mentioned organ-preferential distributions of the GO

categories support a correlation between GEP changes

and organ development.

ESTs differentially expressed in early stamen

development are clustered into two clades

To determine whether a correlation exists between the

observed GEP alterations and early stamen develop-

ment, we conducted a cluster analysis of the O and St

sets of ESTs. The data shows that the clustering anal-

ysis can clearly separate stamen development ESTs

from those in leaf development (RStGEP Database

IV-E, Table S8). This demonstrates that the clustering

analysis can establish correlations between GEP

changes and organ development. With this method, we

analyzed the cluster patterns among the four stages of

stamen development, and found that in the O set,

65.8% of the ESTs fell within a clustering pattern, in

which the differentially expressed ESTs of samples 1

and 2 were grouped as one clade, apart from samples 3

and 4, which were grouped separately (Fig. 3A, and B;

Table S8; RStGEP Database IV-E). In the St set, such

Table 1 Preferential distribution of genes annotated to GO categories in various subsets

GO categories Subsets of preferential distribution of differentially expressed genes Ratio 2095/1449

137 (23)* 1449 (216) 1656 (284) 1712 (279) 2095 (391) 176 (20) 1.45 (1.81)

1.1 antioxidant 2 11 22 20 30 0 2.731.2 ligand binding 15 151 169 187 256 14 1.691.3 enzyme 18 186 254 254 350 18 1.881.4 enzyme regulator 3 21 23 30 51 1 2.431.5 chaperone 0 1 0 1 1 0 –1.6 chaperone regulator 2 15 17 16 23 0 1.531.7 molecular function unknown – – – – – – –1.8 motor activity 0 8 4 13 15 0 1.881.9 nutrientresevior activity – – – – – – –1.10 obsolete molecular function 9 103 117 134 186 10 1.811.11 signal transducer 8 74 102 110 143 6 1.931.12 structural molecule activity – – – – – – –1.13 transcription regulator 3 76 94 96 139 7 1.831.14 translation regulator 1 25 24 19 28 1 1.121.15 transport 11 97 111 131 186 11 1.92

* The number of genes annotated to GO categories within the respective subsets. The total number in the same column is higher thanthe number in the brackets because the same gene may be assigned into different categories according to GO analysis

Plant Mol Biol (2006) 61:845–861 853

123

a correlation was more pronounced, as 84.8% of the St

ESTs fell within the cluster pattern (Fig. 3E, and F;

Table S9; RStGEP Database IV-E).

These results were unexpected, when one considers

only the morphological changes among the 4 devel-

opmental stages, because the morphology of the sta-

mens at stage 5 (sample 3; Fig. 4E) differ greatly from

that at stage 7 (sample 4; Fig. 4M), than those at stage

3 (sample 2; Fig. 4C). However, if one carefully

examines the morphological changes from a develop-

mental perspective, it is easy to conclude that the most

distinguishing developmental event before stage 3 is

the establishment of a radial pattern (Fig. 4). After

stage 3, although there are significant morphological

differences, the most distinguishing characteristic of

the subsequent stages is the further differentiation of

cells whose fates were set during the radial patterning.

Taking this analysis in consideration, it is apparent that

the two-clade clustering pattern exhibited by the GEPs

is closely correlated with radial patterning and associ-

ated cell differentiation.

The genes clustered into the two clades are functionally

correlated with the early stamen development

To further demonstrate that the two-clade pattern of

GEP during early stamen development is biologically

meaningful, we conducted a pathway analysis using

KOBAS (Mao et al. 2005). The rationale of the anal-

ysis is that although little information is available about

genes involved in the early stamen development, some

metabolic changes are closely related to the stamen

development, such as carbohydrate and protein accu-

mulation and callose synthesis and deposition. If the

genes involved in these pathways fall into the two-

clade pattern and are consistent with the trends of the

known metabolic changes, this consistency will dem-

onstrate that from the perspective of metabolic chan-

ges the GEP is closely correlated with stamen

development, and the genes differentially expressed

may play some functional roles in the early stamen

development.

From the total 2748 ESTs that fall into the two-clade

pattern during the early stamen development, we as-

signed 180 ESTs (representing 76 genes) with up-reg-

ulated expression from clade 1 to clade 2 into 37

pathways, and 118 ESTs (representing 90 genes) with

down-regulated expression into 20 pathways (Table

S10). Among these pathways, sixteen in the up-regu-

lated category and three in the down-regulated cate-

gory contain more than three annotated genes

(Table 2). Some of the same genes were assigned into

two or more functionally related pathways, e.g. genes

assigned into aminoacyl-tRNA biosysnthesis were also

assigned into the valine, leucine and isoleucine bio-

synthesis pathways.

Table 2 Pathways correlated with the early stamen development identified with KOBAS

No Pathways No. of annotated Genes (ESTs) Putative functions*

Up-regulated from clade 1 to 21 Aminoacyl-tRNA biosynthesis [ot00970] 15 (19) Protein synthesis2 Blood group glycolipid biosynthesis-lactoseries [ot00601] 6 (6) –3 Blood group glycolipid biosynthesis-neolactoseries [ot00602] 6 (6), same to No 2 –4 Butanoate metabolism [ot00650] 7 (12) –5 C5-Branched dibasic acid metabolism [ot00660] 7 (12), same to No 4 –6 Fructose and mannose metabolism [ot00051] 10 (16)* Energy7 Ganglioside biosynthesis [ot00604] 6 (6), same to No 3 –8 Globoside metabolism [ot00603] 6 (6), same to No 3 –9 Glycerophospholipid metabolism [ot00564] 3 (4) –10 Glycosylphosphatidylinositol(GPI)-anchor biosynthesis [ot00000] 6 (6), same to No 3 –11 High-mannose typeN-glycan biosynthesis [ot00513] 6 (6), same to No 3 Callose synthesis12 N-Glycan biosynthesis [ot00510] 11 (12), among them 6 (6)

are same to No 3Callose synthesis

13 O-Glycan biosynthesis [ot00512] 6 (6), same to No 3 Callose synthesis14 Protein export [ot03060] 6 (7) Protein synthesis15 Streptomycin biosynthesis [ot00521] 4 (5) –16 Valine, leucine and isoleucine biosynthesis [ot00290] 10 (17), all be annotated to

other pathways alsoProtein synthesis

Down-regulated from clade 1 to 21 Carbon fixation [ot00710] 12 (17) –2 Cysteine metabolism [ot00272] 7 (7), some are annotated

to other pathways–

3 Ribosome [ot03010] 58 (63) –

* Putative functions related to stamen development

854 Plant Mol Biol (2006) 61:845–861

123

Is there any correlation between the pathways

identified with KOBAS and early stamen develop-

ment? One of the most unique characteristics during

early stamen development is a significant increase of

callose deposition before meiosis. Since callose is a

glycan with particular structure, the increase of glycan

biosynthesis revealed by KOBAS may reflect the in-

crease of callose deposition during stamen develop-

ment. However, since cell wall differentiation also

requires glycan synthesis, we compared the GEPs

during stamen and leaf development to distinguish a

correlation of the glycan synthesis with callose or cell

wall differentiation. Figure 5 shows that genes assigned

into the glycon biosynthesis pathway are significantly

up-regulated during stamen development, especially

between clades 1 and 2 (Fig. 5A). In contrast, during

leaf development, the expression levels of these genes

are clearly down-regulated. These expression patterns

suggest that the glycan synthesis pathway change

reflects callose synthesis and deposition during stamen

development. We found similar expression patterns in

the fructose and mannose metabolism pathways

(Fig. 5B). Since fructose is involved in energy metab-

olism, the specific increase of fructose and mannose

metabolism is consistent with the energy requirement

during early stamen development. Figure 5C–E show

that pathways related to protein biosynthesis and

export are also significantly increased in early stamen

development.

We did not detect significant differences in any

down-regulated pathways between the stamen and leaf

samples. The aforementioned characteristics of the

up-regulated pathways, however, demonstrated that the

two-clade pattern of the GEP is correlated functionally

with the known metabolic characteristics of early sta-

men development. In addition, we found that butanoate

metabolism is also significantly increased during early

stamen development (Fig. 5F). Little is known about

the function of butanoate during stamen development.

However, the increase that we observed for this

Fig. 5 The expression patterns of ESTs assigned to six pathwaysidentified with KOBAS. The Y axes represent the expressionlevels of ESTs from the microarray data (Table S10). X1-6represent samples 1–6, respectively, in which samples 1–4 werestamen samples collected from the 4 developmental stages, andsamples 5 and 6 were leaf samples from 2 developmental stages.The 6 panels represent expression patterns of ESTs associated

with six pathways, which may be correlated with early stamendevelopment as identified with KOBAS. These pathways are N-Glycan biosynthesis [ot00510] (A), Fructose and mannosemetabolism [ot00051] (B), Valine, leucine and isoleucinebiosynthesis [ot00290] (C), Aminoacyl-tRNA biosynthesis[ot00970] (D), Protein export [ot03060] (E), and Butanoatemetabolism [ot00650] (F)

Plant Mol Biol (2006) 61:845–861 855

123

pathway is consistent with the GENEVESTIGATOR,

in which butanoate metabolism homolog genes are

highly expressed during Arabidopsis stamen develop-

ment (Zimmermann et al. 2004).

Identification of genes potentially involved in the

regulation of early stamen development

The analyses presented herein demonstrated that the

changes of organ-specific GEPs are correlated with the

early stamen development. Regardless the discovery of

the novel two-clade pattern of the GEP during early

stamen development, such a correlation suggests that

these genes may play some roles in early stamen devel-

opment. In other words, we can select candidates for

further functional investigation to dissect the early sta-

men development regulation based on these GEP data.

To sort out important genes from the overwhelming

population provided by microarray analysis, we con-

ducted RT-PCR analysis to verify the gene expression

patterns and ensure hybridization reliability for further

experiments.

Approximately 85% differential expression revealed

by GEP can be verified by RT-PCR

Two different criteria were adopted to choose genes

for RT-PCR verification. One criterion included genes

exhibiting typical expression patterns in the cluster

analysis (120, Table S3), another included those with

fold changes greater than 6 among the 6 samples (249

in total and 86 were employed for detection, Table S4).

Among the 206 selected candidate genes, we examined

the expression levels of 168 by semi-quantitative RT-

PCR. Of these, the expression patterns of 143 genes

were consistent with our microarray data findings

(Table S11). Thus, in our scale of sampling, approxi-

mately 85% of the validated microarray data were

verified with RT-PCR examination, suggesting that it is

technically possible to select candidate genes for fur-

ther functional investigation based on the GEP data.

Twenty-six genes are potentially involved in the

regulation of early stamen development

Since the functions of only three Arabidopsis genes

and one maize gene have been identified as being

regulatory for early stamen development (Schiefthaler

et al. 1999; Yang et al. 1999; Canales et al. 2002; Zhao

et al. 2002; Yang et al. 2003; Chaubal et al. 2003), we

needed to seek more like genes. From the 143 verified

genes with diversified expression patterns, we found

that 26 were highly expressed during early stamen

development, compared to the leaf samples (Table 3).

Although some of the RT-PCR results did not per-

fectly match the expression levels from the microarray

data, possibly due to experimental variations, both

methods reveals their preferential expression patterns

during early stamen development. Some genes were

preferentially down-regulated in stamen. Among the

26 genes, AK066916, which is annotated as sporula-

tion-specific protein 15 (http://cdna01.dna.affrc.go.jp/

cDNA/), and U78891 (OsMADS7), according to the

expression pattern described below, are likely to be

involved in regulating stamen development, suggesting

that these 26 genes may serve as valuable candidates

for further functional investigation, although many of

them have no identified functions in early stamen

development.

In situ hybridization of selected genes revealed a

correlation between OsMADS7 expression and

differentiations of sporogenous and tapetum cells

To further explore the temporal and spatial expression

patterns of the RT-PCR verified genes, we conducted

in situ hybridizations on five genes. Of these, three

were highly expressed in the stamen samples

(AK073684, AK069222, U78891), one was highly

expressed in the primordial samples in both the stamen

and the leaf (AF098752), and one was highly expressed

in the expanded leaf (AK067730) (Table S11). Figure 6

shows that AF098752 (a FIL homolog) was detectable

at the ventral sides of the palea and lemma (Fig. 6A,

pointed by arrowheads), just as its Arabidopsis homo-

log expresses at the ventral sides of leaves and floral

organs. Additionally, this gene was detectable at the

early stamen primordia, which are the descendant cells

of the achesporium (Fig. 6A and B) and the ovule

primordium (Fig. 6C). Consistent with the RT-PCR

and microarray data (Table 3, RStGEP Database IV-

D), AK073684 (a PHD finger-related protein; Fig. 6D

and E) and AK069222 (a putative protein; Fig. 6G and

I) have distinguishable expression levels, above the

background, at early stamen primordia and descendant

cells of achesprium, respectively. It is noteworthy that

AK069222 is also expressed in the early ovule pri-

mordium (Fig. 6I). Consistent with the RT-PCR

results (RStGEP Database IV-D), AK067730, which

encodes a rice LLS1 protein, was expressed in the

descendant cells of the achesporium after stage 5, but

not in the earlier stages (Fig. 6J–L), which is consistent

with the finding that this protein is present in non-

photosynthetic tissues (Yang et al. 2004). It is worth

noting that the two genes AK073684 and AK067730

are selected from those with the two-clade pattern.

856 Plant Mol Biol (2006) 61:845–861

123

Table 3 Genes preferentially up-regulated during early stamen development

GenBank No Array ID Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6

AB004461 r0556b06 0.122064 0.1054132 0.1380501 0.0962446 -0.09758 -0.37423

AK064973 r0138e02 0.090389 0.096902 0.139614 0.1351279 -0.262947 -0.234179

AK065897 r0347a12 0.0688992 0.1490016 0.0879587 0.0654087 -0.111882 -0.274658

AK069222 r0145a03 0.1621576 0.0923443 0.1236342 0.0904952 -0.279795 -0.300926

AK073124 r0465d08 0.1163682 0.1282448 0.0887543 0.0527518 -0.198886 -0.177791

AK073684 r0560b03 0.0652047 0.1089589 0.0929353 0.0844711 -0.125643 -0.142112

AK071997 r0226h03 0.0732904 0.0884164 0.0598586 0.0989692 -0.155913 -0.129313

AK103514 r0175b10 0.0793683 0.0634113 0.0993797 0.1135085 -0.120394 -0.223888

U78891 r0008e03 0.1783616 0.1894809 0.1728628 0.1112617 -0.238172 -0.353131

X82036 r0097e04 0.1348808 0.1367709 0.1581003 0.0514765 -0.244188 -0.258812

AK063381 r0123a05 0.1398065 0.1185951 0.0940494 0.0385837 -0.21737 -0.23111

AK065367 r0342f05 -0.009082 0.0018312 0.1451698 0.2017272 -0.131876 -0.227663

AK066916 r0490g10 0.0333618 0.0369421 0.0710182 0.3065932 -0.08919 -0.361169

AK071939 r0096e12 0.0674889 0.1592845 0.0493941 0.0166285 -0.00341 -0.316312

AK073282 r0468g01 0.0439644 0.0902678 0.2082536 0.0549938 -0.106962 -0.285402

AK101994 r0123d06 0.0526801 0.0360982 0.1741343 0.1950057 -0.251626 -0.297329

AK102192 r0198f06 0.1102905 0.0736636 0.0475835 0.1418128 -0.014909 -0.270336

AK102525 r0130e08 0.0348176 0.1285981 0.0829138 0.0025989 -0.101585 -0.285367

AK102637 r0174a07 0.0989186 0.1170736 0.0761569 0.060445 -0.027765 -0.3172

AK109536 r0093d04 0.07437 0.0361171 0.1778646 0.0571404 -0.154173 -0.244162

AK109777 r0149a04 0.1227695 0.1657696 0.1101029 0.0407966 -0.022119 -0.454178

AK061599 r0515f07 0.0959044 0.1329597 0.1295044 0.039832 -0.184657 -0.203221

AK106279 r0588d04 0.1238701 0.0896508 0.1351793 0.1123415 -0.18507 -0.284336

AF210816 r0521b09 0.15055 0.079712 0.099786 0.047426 -0.15896 -0.28401

AK070863 r0589c06 0.057398 -0.05423 -0.01852 0.272162 -0.07623 -0.33161

BP432938 r0144f10 0.1283623 0.1220721 0.0888772 0.049107 -0.191089 -0.122963

R L P S1 Sample 1-6:

Gene expression

values after

processed by

maanova

Right most column:

semi-quantitative

RT-PCR results

R: root

S: stem

L: leaf

P: panicle

S1-6:

Sample 1-6

S2 S3 S4 S5 S6S

GenBank No Gene AnnotationAB004461 Oryza sativa mRNA for DNA polymerase alpha catalytic subunitAK064973 putative kinesin like protein AAK065897 tesmin/TSO1-like CXC domain-containing protein similar to CXC domain containing TSO1-like protein 1

(SOL1)AK069222 hypothetical proteinAK073124 calcium-binding EF hand family protein similar to EH-domain containing protein 1AK073684 PHD finger protein-related contains low similarity to PHD-finger domain proteinsAK071997 transcriptional factor B3 family protein / auxin-responsive factorAK103514 SMC2-like condensin, putative (SMC2) (TITAN3) very strong similarity to SMC2-like condensin (TITAN3)U78891 Oryza sativa MADS box protein (OsMADS7)X82036 cyclin 2AK063381 kinesin motor protein-relatedAK065367 Systemin receptor SR160 precursor (EC 2.7.1.37) (Brassinosteroid LRR receptor kinase)AK066916 Sporulation-specific protein 15AK071939 Oryza sativa Roc3 mRNA for GL2-type homeodomain proteinAK073282 calmodulin-binding family protein low similarity to SF16 proteinAK101994 ubiquitin carboxyl-terminal hydrolase family proteinAK102192 beta-galactosidase, putative / lactase, putative similar to beta-galactosidase precursorAK102525 calmodulin-binding family protein, probable SF16 proteinAK102637 hypothetical proteinAK109536 WD-40 repeat family protein contains 6 WD-40 repeats; similar to Fzr1AK109777 long-chain-fatty-acid–CoA ligase / long-chain acyl-CoA synthetase nearly identical to acyl CoA synthetase

(MF45P)AK061599 hypothetical proteinAK106279 chromosome-associated kinesin, putative microtubule-associated motor KIF4AF210816 probable kinesinAK070863 hypothetical proteinBP432938 dehydration-stress inducible protein 1

Plant Mol Biol (2006) 61:845–861 857

123

Their increased expressions from stage 2 to stage 5

detected by the in situ hybridization (Fig. 6D vs. E and

J vs. K) further validated the correlation of the gene

expression patterns to the developmental phases.

The most interesting expression patterns were

exhibited by U78891 (OsMADS7). This gene is

detectable only in the stamen samples in the micro-

arrays and RT-PCRs (RStGEP Database IV-D,

Table 3). The in situ hybridizations demonstrate such

an expression pattern although this gene was also

detected in the early development of integuments

(Fig. 6Q and V). Regardless the broader expression

pattern, this gene is closely correlated with sporoge-

nous and tapetum cell differentiation (Fig. 6M–P and

R–U). Before stage 2, the expression of OsMADS7 is

detectable in all cells throughout the stamen primordia

Fig. 6 Detection of expression patterns of selected genesverified by RT-PCR using in situ hybridization. A–C: Expressionpattern of the gene encoding a rice FIL homolog (AF098752) inan early floral bud (A), stage 5 stamens (B) and an ovuleprimordium (C), showing that the hybridization signals were highin the ventral sides of lemma and palea (hybridization signalsabove the background are designated by arrowheads), the stage 2stamen primordia, the descendent cells of archesporia in thestage 5 stamen and the ovule primordia. D, E: Expressionpattern of the gene encoding a rice PHD finger protein-relatedprotein (AK073684), showing that the hybridization signals weremarkedly above the background level in the stage 2 stamen (D)and the sporogenous cells in a stage 5 stamen (E). G–I:Expression pattern of the gene encoding a putative protein(AK069222), showing that the hybridization signals were clearlyabove the background level in the stage 2 stamen (G), thearchesporia descendent cells in stage 5 stamen (H) and ovuleprimordia (I). J–L: Expression pattern of the gene encoding arice LLS1 protein (AK067730), showing that the hybridizationsignals were not detectable in the stage 2 stamen and other floralparts (J), but were detectable in the sporogenous cells of thestage 5 stamen (K), tetrads and tapetum cells (L). M–V:

Expression pattern of the genes encoding OsMADS7(U78891), showing that the hybridization signals were firstdetectable in the primordial cells of lemma and palea, stamensand carpel (M). Subsequently, the signals were strongestthroughout the stage 1 and 2 stamen primordia (N, O). Whenthe stamen reached stage 3, the signals had converged into thefour corners where the archesporial cells are divided intosporogenous cells and parietal cells (see Fig. 1 and Table S6).During stages 4–6, the signals were further converged into twospecific cell types, taptum and sporocytes (R–T). When microsp-ores released from the tetrads and taptum degenerated, only lowsignals were detected (U). Note that OsMADS7 was alsodetectable in primordia of the outer integument (Q). Thisexpression was gradually down-regulated as the ovule differen-tiated (V). F: hybridization with sense probe as a negativecontrol. Ar: archesporium; Ca: carpel; E: epidermis; En:endothecium; In: integument; ii: inner integument; le: lemma;MC meiotic cells; ML: middle layer; MMC: microspore mothercells; oi: outer integument; ov: ovule; ow: ovary wall; pa: palea;Sp: sporogenous cells; SPC: second parietal cells; St: stamen; T:tapetum; Tds: tetrads; v: vascular tissue. Bars: 20 lm

858 Plant Mol Biol (2006) 61:845–861

123

(Fig. 6N and O). At stage 3, the expression of

OsMADS7 was confined to the four corners of the

primordia (Fig. 6P). Along with the parietal cells

dividing from stages 4 to 6, the expression of

OsMADS7 disappeared initially from the endothecium

layer (Fig. 6R and S), then from the middle layer

(Fig. 6T) and was finally expressed only in the tapetum

and microspore mother cells (Fig. 6T). The expression

of OsMADS7 was significantly reduced after meiosis

(Fig. 6U). This dynamic pattern of OsMADS7

expression has not been reported before.

Clearly, the in situ hybridizations validated the or-

gan-biased expression patterns revealed initially by the

microarray and RT-PCR analyses. This demonstrates

that organ-specific GEPs can be used to identify genes

potentially involved in stamen development. In addi-

tion, this analysis revealed some novel expression

patterns of the detected genes, especially OsMADS7,

in stamen development.

Discussion

To elucidate the molecular regulatory mechanisms

underlying organ formation processes, it is necessary to

use new molecule detection technologies. In this study

we demonstrated that the organ-specific GEP is closely

correlated with the early morphological development

of rice stamen. Since we validated our microarray data

with the RT-PCRs and in situ hybridizations, the or-

gan-specific GEP was proved to be a useful approach

to comprehend complex molecular events underlying

stamen development. From these examinations, we

identified 26 genes with significantly high mRNA

abundance during early stamen development. Al-

though none of the genes have been associated directly

with stamen development, this finding substantially

expands the current spectrum of stamen development-

related genes, and provides valuable candidates for

future functional investigations.

We also identified two intriguing expression char-

acteristics exhibited during early stamen development.

Namely, we found that the early stamen GEP data

cluster neatly into two clades, which are closely cor-

related with the two developmental events: radial

patterning and cellular differentiation. Although

researchers previously identified various important

developmental events, such as the establishment of the

three-dimensional axes (Poethig 1997), cellular differ-

entiation is a major criterion in describing the mor-

phogenetic process of a lateral organ. Our findings

suggest that the entire GEP is not simply correlated

with cellular differentiation, but also with broader

developmental events.

A second noteworthy characteristic emerging from

this study is that the majority of genes exhibited

quantitative changes in their expression levels, rather

than absolute ‘‘on’’ or ‘‘off’’, in different organ types or

different stages of stamen development. For example,

among the 26 genes highly expressed in stamen listed in

Table 3, only OsMADS7 is not detectable in the leaf

samples. This finding suggests that organ-specific

quantitative changes, rather than organ-specific induc-

tion in gene expression, may play critical roles in reg-

ulating plant organ formation. It is well established that

lateral organs initiated from shoot apical meristems are

essentially metamorphotic leaves (Coen and Carpenter

1993). These organs share similar developmental pro-

cedures in their early stages, including axis determina-

tion, and the establishment of the three basic tissues,

e.g., epidermal, ground and vascular tissues. It is logical

to hypothesize that the differentiation of various pri-

mordial-derived organs arises from the progressive fine-

tuning of gene expression levels, particularly during the

early stages of axis determination and radial patterning.

The expression patterns of selected genes detected

by in situ hybridization seem to support the above

perspective. As shown in the Fig. 6, the three genes up-

regulated in early stamen development expressed in all

cells of stamen primordia prior to stage 2, then differed

along the differentiation of cell types. These dynamic

gene expression changes, together with the observed

cell differentiation, may be examples of fine-tuning.

In this study, we encountered a novel expression

pattern of OsMADS7. This gene was determined to be

involved in establishing flowering time (Kang et al.

1997). In our study, we found that its expression pat-

tern is closely correlated with the differentiation of

sporogenous and tapetum cells. Plant cells committed

to meiosis (sporogenous cells) differ from animal germ

cells, in that they arise from undifferentiated somatic

cells. Little is known about how the sporogenous cells

are differentiated. Taking the differentiation of the

microsporogenous cells as an example, is the cell fate

committed to meiosis immediately determined after

the archisporial divides? Or is the cell fate gradually

determined along with cell-cell communication during

cellular differentiation? Clearly, further functional

analysis of genes such as OsMADS7 and others re-

vealed by GEP will provide a promising alternative

solution.

Acknowledgements We thank Da Luo (Inst. Plant Physiol andEco, CAS) for his initiative effort in preparing the rice cDNAmicroarray; Zhi-Yong Han (UniGene) and his team in

Plant Mol Biol (2006) 61:845–861 859

123

manufacturing of the microarray and carrying out the microarrayexperiment. We thank Hong Ma (Penn State Univ.)for his sug-gestion in our experimental design; Hong-Wei Xue (Inst. PlantPhysiol and Eco, CAS), Jing-Chu Luo (PKU) and peoples in ZhiGeng’s and Song-Gang Li’s lab for their help in data analysis. Wealso thank Qing-Zhong Xue (Zhejiang Univ.) for his help inproviding us rice plants; Sodmergen, Li-Yun Xu, Shi-Yi Hu(PKU) and Hui Zhang (Beijing Forest Univ.) for their technicalhelp in rice morphological analysis. We specially thank BobGoldberg, Brandon Le (UCLA) and Li-Geng Ma (Natl. Inst.Biol. Sci.) for their help in critical reading of the manuscript. Thisresearch was supported by grants from MST (G19990116,2002AA2Z1001, 2003CB715906, J00-A-005), NSFC (30070361),MOE (99002) to SNB.

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