Transcriptional responses to drought stress in root and leafof chickpea seedling

Xiansheng Wang • Ying Liu • Yuying Jia • Hanyan Gu •

Hongyu Ma • Tian Yu • Hua Zhang • Quanjia Chen •

Lin Ma • Aixing Gu • Jusong Zhang • Shubing Shi • Hao Ma

Received: 7 October 2011 / Accepted: 16 April 2012 / Published online: 6 May 2012

� Springer Science+Business Media B.V. 2012

Abstract Chickpea (Cicer arietinum L.) is an important

pulse crop grown mainly in the arid and semi-arid regions

of the world. Due to its taxonomic proximity with the

model legume Medicago truncatula and its ability to grow

in arid soil, chickpea has its unique advantage to under-

stand how plant responds to drought stress. In this study, an

oligonucleotide microarray was used for analyzing the

transcriptomic profiles of unigenes in leaf and root of

chickpea seedling under drought stress, respectively.

Microarray data showed that 4,815 differentially expressed

unigenes were either C2-fold up- or B0.5-fold down-reg-

ulated in at least one of the five time points during drought

stress. 2,623 and 3,969 unigenes were time-dependent

differentially expressed in root and leaf, respectively. 110

pathways in two tissues were found to respond to drought

stress. Compared to control, 88 and 52 unigenes were

expressed only in drought-stressed root and leaf,

respectively, while nine unigenes were expressed in both

the tissues. 1,922 function-unknown unigenes were found

to be remarkably regulated by drought stress. The expres-

sion profiles of these time-dependent differentially

expressed unigenes were useful in furthering our knowl-

edge of molecular mechanism of plant in response to

drought stress.

Keywords Chickpea � Oligonucleotide microarray �Drought � Transcriptional response � Root � Leaf

Introduction

Among abiotic environmental stresses, drought is one of

the common adverse environmental conditions that have

adverse effects on the growth of plants and the productivity

of crops. Plants have adapted to respond to this stress at

molecular and cellular levels as well as at physiological

and biochemical levels, enhancing them to survive. To

date, a large number of drought-induced genes in various

plants have been identified, and their expression profiles in

response to drought stress also have been revealed. And the

products of some of these identified genes have been

confirmed to function in drought tolerance or in signal

transduction pathway [1–6]. Identification of drought-

induced genes in various plants and revealing their

expression profiles in response to drought stress have been

not only of great interest for understanding their underlying

molecular mechanisms in drought tolerance but also of

great benefit to the breeding of drought-tolerant crops.

Chickpea is the third most important pulse crop in the

world just behind dry bean (Phaseolus vulgaris L.) and

field pea (Pisum sativum L.), and its cultivation area has

been more than million hectares/year since 2006 year [7].

Xiansheng Wang and Ying Liu contributed equally to this work.

Electronic supplementary material The online version of thisarticle (doi:10.1007/s11033-012-1662-4) contains supplementarymaterial, which is available to authorized users.

X. Wang � Y. Jia � H. Gu � H. Ma � T. Yu � H. Ma (&)

State Key Laboratory of Crop Genetics and Germplasm

Enhancement, Nanjing Agricultural University, Nanjing 210095,

Jiangsu, China

e-mail: Lq-ncsi@njau.edu.cn

Y. Liu

College of Agriculture, Hebei University of Engineering, Hebei

056038, China

H. Zhang � Q. Chen � L. Ma � A. Gu � J. Zhang � S. Shi (&)

Key Laboratory of Agriculture Biotechnology, Xinjiang

Agricultural University, Urumqi 830052, Xinjiang, China

e-mail: 691467566@qq.com

123

Mol Biol Rep (2012) 39:8147–8158

DOI 10.1007/s11033-012-1662-4

Chickpea is an annual, self-pollinating, diploid (2n = 2x =

16) plant with a short life cycle of 3–5 months. It has a

small genome size of 740 Mbp that is only 1.5 times larger

than that of Medicago truncatula. Due to its taxonomic

proximity with the model legume M. truncatula and its

ability to grow in the arid and semi-arid regions, chickpea

has been found rich in tolerance genes for a range of abiotic

stresses such as drought, high salinity and cold, etc. and has

been suggested as a model legume crop in study of crop

agronomic responses to various stresses [8]. A lot of genes

differentially expressed in response to drought stress in

chickpea have been identified, and their expressions in

response to drought stress have been analyzed. For exam-

ple, Romo et al. [9] reported that one gene encoding lipid

transfer protein (CapLTP) and two genes encoding late

embryogenesis abundant (CapLEA-1 and CapLEA-2) were

induced by water stress. Boominathan et al. [10] identified

101 dehydration-inducible transcripts in chickpea by

repetitive rounds of cDNA subtraction. Mantri et al. [11]

employed a 768-featured boutique microarray to compare

the genes expressed by chickpea in response to drought,

cold, high salinity and the fungal pathogen Ascochyta ra-

biei and identified 46, 54, 266 and 51 differentially

expressed transcripts, respectively. Molina et al. found that

a total of 7,532 UniTags were more than 2.7-fold differ-

entially expressed and 880 were regulated more than 8-fold

in chickpea root upon drought stress. By means of con-

structing two cDNA libraries using the PEG-treated and -

nontreated seedling leaves of chickpea [12], Gao et al. [13]

have identified 36 up-regulated and 56 down-regulated

genes in response to drought stress. Following the intro-

duction of DNA microarray technology, massive changes

in gene regulation in various plants can be assayed in a

high-throughput manner [14]. DNA microarray analysis for

the identification and characterization of large numbers of

genes has been becoming one of the most powerful tools

for dissecting environmental and developmental responses

in plants. To date, some initial cDNA microarrays (or

macroarray) have been utilized in study of drought toler-

ance of chickpea [10, 11, 15–18]. However, since their

cDNA microarray scales were all very small (no more than

1,000 cDNA), even a part of their ESTs coming from

grasspea and lentil, these researches’ information quantity

and accuracy were very limited. Further more, there were

no researches investigating gene expression profiles in root

and leaf of chickpea at the same time to date [10, 11, 15,

16]. Therefore, the transcriptional profiling of genes dif-

ferentially expressed in root and leaf of chickpea in

response to drought stress has not been completely

unveiled yet. In order to globally understand the molecular

mechanism of chickpea in drought tolerance, it is necessary

to detect the differential expressions of a variety of genes in

chickpea in response to drought stress on a larger scale

DNA microarray. To October of 2009, 34,177 ESTs of

chickpea were available in the NCBI EST database (http://

www.ncbi.nlm.nih.gov/dbEST/dbEST_summary.html), and

this offered the condition for constructing a larger scale

DNA microarray.

In this work, we constructed a 6,164 oligonucleotide

spotted microarray from 36,301 ESTs and 283 nucleotide

sequences of chickpea. And this microarray was further

employed to investigate the transcriptomic profiles of

unigenes expressed in leaf and root of chickpea seedling

under drought stress, respectively. Our results will provide

insights into the expression profiles of the time-dependent

differentially expressed unigenes in root and leaf of

chickpea seedling under drought stress, and make a sig-

nificant contribution to the understanding of the molecular

mechanisms developed by the plant against drought stress.

Materials and methods

Plant growth and stress treatments

Seeds from a drought-tolerant chickpea cultivar Xj-209

were germinated in quartz sand in a growth chamber with a

day/night cycle of 14/10 h at 28/20 �C, as described by

Gao et al. [13]. When grown for 10 days, the seedlings

were carefully transferred to one-off cups with water. 24 h

later, the seedlings were separated into two groups: one

group was exposed to 60 mM PEG 4000 as drought

treatment, and the other was harvested immediately as

control (0 h).

RNA isolation and preparation of fluorescent dye-

labeled cDNA

For drought treated group, roots and leaves of chickpea

seedlings were harvested separately at 0.5, 1.5, 6, 12, and

24 h during drought stress treatment, frozen in liquid

nitrogen, and kept at -80 �C until use. Total RNA was

extracted using Trizol reagent (Invitrogen, Carlsbad, CA,

USA) and purified with RNeasy mini spin column Kit

(Qiagen, Valencia, CA, USA) according to the manufac-

turer’s instructions. Residual genomic DNA was digested

by RNasefree DNase I (Takara). cDNA was synthesized,

linearly amplified and labeled using the cRNA Amplifica-

tion and Labeling Kit (CapitalBio). In brief, total RNA was

reverse transcribed with Cbcscript reverse transcriptase and

T7 oligo dT primer. 2nd-strand cDNA was synthesized by

DNA polymerase. The double-stranded cDNA was in vitro

transcribed into cRNA and purified by Nucleospin RNA

Clean-up kit (Macherey-Nagel, Germany). The resulting

cRNA was reverse transcribed by MMLV and purified with

PCR Nucleospin Extract II kit (Macherey-Nagel,

8148 Mol Biol Rep (2012) 39:8147–8158

123

Germany). After reverse transcription, the cDNA was

labeled by Cy5-dCTP or Cy3-dCTP (GE Healthcare, USA)

with klenow enzyme at 37 �C for 60 min. The labeled

cDNA was purified with PCR Nucleospin Extract II kit

(Macherey-Nagel, Germany).

EST collection and annotation

All the ESTs and nucleotide sequences of chickpea in

GenBank (to October of 2009) were downloaded. Vector

sequences were screened against UniVec database (http://

www.ncbi.nlm.nih.gov/VecScreen/VecScreen.html). The

resulting high quality sequences ([100 bp) were then

assembled using Phrap software (http://www.phrap.org/).

Default settings were used except 40 bp minimum overlap

and 99 % identity [19]. Assembled contigs and singletons

(called clusters) were manually revised by Consed software

(http://www.phrap.org/) [20]. All clusters were compared

with the NCBI nucleotide (nt) and non-redundant protein

(nr) databases by BLASTN (E-values B1 9 10-10) and

BLASTX (E-values B1 9 10-5), respectively. The stan-

dards of exact choice of the most related entry in each

group of alignments depended not only on the best hit

values but also on the information of matched sequences in

detail. All assembled sequences having the same annota-

tion were further clustered into a unigene. In total, 6,164

unigenes were used in designing the oligonucleotide

microarray. For each unigene, oligonucleotides were

designed using the Agilent eArray Ver. 4.5 with the length

of 60 bases.

Based on Gene Ontology (GO) classification, all unig-

enes of chickpea were analyzed for their functional char-

acteristics under drought stressed and controlled conditions.

Using the single-directional best hit (SBH) method as

recommended by the KEGG Automatic Annotation Server

(KAAS) [21] for sets of ESTs allowed us to assign unigene

pathway annotations.

Microarray hybridizations and data analysis

Chickpea oligonucleotide microarray containing 6,164

chickpea oligonucleotide probes (supplementary Table 1)

was used. The gene expression profiles in root and leaf

after 0.5, 1.5, 6, 12, and 24 h drought stress and the cor-

responding non-stressed controls (0 h) were investigated

by microarray analysis.

Each test sample was Cy5-labeled and the reference

samples Cy3 labeled. The arrays were hybridized at 42 �C

for 12–16 h in BioMixer II (CapitalBio). After hybridiza-

tion, the slides were washed with 29 SSC plus 0.2 % SDS at

42 �C for 5 min, with 0.29 SSC for 5 min at room temper-

ature and spin-dried. Hybridized microarray slides were

scanned with a LuxScan 10 K/A scanner (CapitalBio). Spot

intensities were quantified using GenePix Pro 4.0 image

analysis software (Axon Instruments). Data with signal

intensity more than 1,200 were accepted as the standard for

gene expression. Unigenes up- or down-regulated greater

than a 2-fold or less than 0.5-fold ratio value (Cy5 intensity/

Cy3 intensity) were taken as differentially expressed.

Microarray expression data were MIAME compliant and

have been deposited in a MIAME compliant database (GEO

accession number GSE25705).

To point out the time course in the expression data, a

further evaluation was based on clustering the time-

dependent expression profiles of these significantly differ-

entially expressed unigenes with an expression-level

alteration criterion of ratio value(n time point)/ratio value(n-1

time point) C 2 or ratio value(n time point)/ratio value(n-1 time

point) B 0.5 at n time point (0.5, 1.5, 12, and 24 h) during

drought stress, via self organizing maps (SOM) module of

the Multiexperiment Viewer ver. 4.2 software (MeV,

www.tm4.org).

Two independent biological replicates for each time

point of two tissues were used to hybridize. The processes

of labeling, hybridization, washing, and scanning were

carried out at Beijing National Biochip Research and

Engineering Center, China.

Quantitative real-time PCR and data analysis

To validate the array data, the expressions of 10 genes

(Contig_1885: proline dehydrogenase; Contig_3134:

lipoxygenase LOXN3; Contig_2853: peroxidase1B; Con-

tig_5876: nitrate transporter; Contig_3259: homocysteine

S-methyltransferase; Contig_1500: Photosystem I reaction

center subunit N, chloroplast precursor; Contig_2780: beta-

amylase; Contig_2823: glycine-rich protein 1; Con-

tig_2895: glutathione peroxidase 1; Contig_1672: alanine:

glyoxylate aminotransferase) were confirmed by qPCR

with the same RNA samples used for microarray hybrid-

ization. The primers used for qPCR are listed in supple-

mentary Table 2.

The cDNA from the total RNA samples, which were

used for the microarrays at different time points (0, 0.5,

1.5, 6, 12, and 24 h) during PEG-treatment, was synthe-

sized with M-MLV Reverse Transcriptase (Invitrogen),

respectively. qPCR was performed using SYBR premix EX

Taq (TaKaRa Biotech, Dalian, China) in the Bio-RAD

iCycler iQ5 Machine. The actin gene (GenBank accession

no. AJ012685) was assigned for control. All reactions were

performed in triplicate. Expressed ratio was calculated

using the Livak method [22]:

Expressed ratio ¼ 2�DDCT

where DDCT is the sum of: [CT(gene) - CT(actin)](Drought

stressed) - [CT(gene) - CT(actin)](Unstressed).

Mol Biol Rep (2012) 39:8147–8158 8149

123

For statistics, an analysis of variance (ANOVA) of the

data was performed, and a least significant difference

(LSD) test with a confidence interval of 95 % was used to

compare the means.

Results

Characterization of EST sequences

To capture the genes induced by drought stress in chickpea

as many as possible, not only all the 34,177 EST sequences

of chickpea in GenBank [supplementary Text 1, including

our previously submitted 5,097 ESTs (GenBank accession

no. FE668437–FE673533)] but also 283 nucleotide

sequences (supplementary Text 2) were downloaded in

October, 2009. After removing vector sequences and lower

quality sequences, 36,301 ESTs (including our recently

submitted 2,124 ESTs, GenBank accession no. HS107522–

HS109645) resulted in the identification of 11,042 unig-

enes (7,770 singletons and 3,372 clusters). All unigenes

were compared with the NCBI nucleotide (nt) and non-

redundant protein (nr) databases by BLASTN (E-values

B1 9 10-10) and BLASTX (E-values B1 9 10-5),

respectively. The standards of exact choice of the most

related entry in each group of alignments depended not

only on the best hit values but also on the information of

matched sequences in detail. In the case of the unigenes

corresponded to different regions of the same gene, we kept

the unigene with the longest sequence. The unigenes hav-

ing annotation of non-plant genes were also taken out.

Consequently, a total of 6,164 unigenes were obtained. The

entire data, including all annotative attributes, are shown in

supplementary Table 3. In this data, only 3,680 unigenes

had specific function, while the others 2,484 unigenes

showed similarities to proteins with function completely

unknown or even having no homology.

The 6,164 unigenes were further analyzed by the GO

assignments [23]. As a result, 4,674 unigenes (15,296 GO

terms) were classified into three broad categories, namely,

biological processes, cellular components and molecular

functions (Fig. 1). The detailed GO assignment results are

listed in supplementary Table 4.

Overall features of the drought stress-responsive

expression profiles

To identify the differential expression of the genes induced

by drought stress in root and leaf of chickpea seedling at

different time points, an oligonucleotide microarray con-

taining 6,164 unigenes was fabricated. RNA samples from

the roots and leaves collected at 0.5, 1.5, 6, 12, and 24 h

during drought treatment, as well as from that of the

untreated sample at 0 h, were used for microarray

hybridization, respectively.

The biological significance of transcriptional profiling

can be revealed by grouping of differentially expressed

genes. In this study, of 6,164 unigenes, there were 247

unexpressed at all six time points in root, while 320 were

unexpressed in leaf. Nine unigenes were found to be

unexpressed in both the tissues (Fig. 2; supplementary

Table 5). Further, among the 6,155 expressed unigenes,

only 4,815 were detected to be differentially expressed

with expression ratio of C2-fold up- or B0.5-fold down-

regulation at one or more time points; among these dif-

ferentially expressed unigenes, 3,315 and 4,059 unigenes

were differentially expressed at least one time point in root

and leaf, respectively, while there were 2,559 differentially

Fig. 1 The GO categories of

4,674 unigenes. The genes were

functionally categorized

according to the Gene Ontology

Consortium and two levels of

the assignment results were

plotted here. In this ontology,

‘‘biological process’’, ‘‘cellular

component’’ and ‘‘molecular

function’’ are categorized

independently

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123

expressed in both the tissues (Fig. 3A; supplementary

Table 6). Under the stricter criterion (expression ratio of

C5-fold up- or B0.2-fold down-regulation), only 1,957

differentially expressed unigenes were identified at one or

more time points. Among them, 1,003 and 1,480 unigenes

were identified in at least one time point in root and leaf,

respectively, while there were 526 differentially expressed

in both the tissues (Fig. 3B; supplementary Table 7).

Changes in number of the unigenes differentially

expressed in root and leaf of chickpea seedling over stress

time are shown in Fig. 4 and supplementary Table 8. These

diagrams provided an important overview showing the

distribution of number of differentially expressed unigenes

under different criteria into shared and tissue-specific

responses. In the present study, whether under the lower or

stricter criterion, the amount of the unigenes differentially

expressed in leaf was first increased and then decreased

over stress time, with the maximum occurring at 12 h,

while the number of the unigenes differentially expressed

in root showed the pattern of ‘‘increase–decrease–

increase’’, with the maximum occurring at 24 h (Fig. 4A,

B; supplementary Tables 8, 9). The change in number of

the unigenes differentially expressed in both leaf and root

over time exhibited the same pattern as that in leaf.

Compared to the root, the leaf was characterized by a

relative larger number of differentially expressed unigenes

at all the investigated time points except at 0.5 and 6 h

under the lower criterion (Fig. 4A, B; supplementary

Tables 8, 9). Furthermore, whether in root or in leaf, the

amount of the up-regulated differentially expressed unig-

enes were always less than that of the corresponding down-

regulated ones at all the investigated time points except at

1.5 h in both the tissues and at 6 h in root under the stricter

criterion. This situation also occurred in the unigenes dif-

ferentially expressed in both the tissues (Fig. 4A, B; sup-

plementary Table 8, 9). Additionally, a lot of differentially

expressed unigenes were found to be always up- or down-

regulated in one tissue or in both the tissues at all the

investigated time points (Fig. 4C; supplementary

Table 10), implying that these unigenes constantly play

important roles in response to drought stress in root and

leaf of chickpea seedling. It was noticeable that the number

of these unigenes differentially expressed in leaf were

much smaller than that in root under both the criteria

(Fig. 4C), different from the results in Fig. 4A, B; more-

over, whether in root or in leaf, the amount of these up-

regulated differentially expressed unigenes were always

less than that of the corresponding down-regulated ones.

Under the lower criterion, 10 differentially expressed

unigenes were found to be always up-regulated during

drought stress in both the tissues (Fig. 4C; supplementary

Table 10). Of them, only two had specific function anno-

tation. These two unigenes encoded Calcineurin B-like

(CBL) interacting protein kinase (CIPK) (Contig_2886)

and early light inducible protein (ELIP) (Contig_7860),

respectively. One of the three important families of Ca2?

sensor proteins is referred to as CBL proteins. CBLs have

been identified to specifically target a group of sucrose

non-fermenting-related serine/threonine kinases (SnRK3),

named CBL-interacting protein kinases (CIPK), to mediate

the sensed calcium signal [24]. A role for ELIP in resis-

tance to drought stress is indicated by several studies.

Expression of an ELIP-like gene in Craterostigma plant-

agineum, a plant that can survive and recover from extreme

dryness, is influenced by abscisic acid, light levels and

drought. Constitutive expression of the ELIP gene in He-

lianthus annuus confers drought tolerance [25, 26]. And

two ELIP genes in gametophytes of the moss Tortula ru-

ralis were found to be up-regulated in response to

Fig. 2 The numbers of unexpressed unigenes at all six time points in

root and leaf

Fig. 3 Venn diagram analysis

of numbers of differentially

expressed unigenes in root and

leaf of chickpea. A Expression

ratio of C2-fold up- or B0.5-

fold down-regulation and

B expression ratio of C5-fold

up- or B0.2-fold down-

regulation

Mol Biol Rep (2012) 39:8147–8158 8151

123

desiccation, salt, high light, and rehydration stresses [27].

Contrarily, up to 69 differentially expressed unigenes were

found maintaining down-regulation in both the tissues

during drought stress (Fig. 4C; supplementary Table 10).

Of them, only less than 50 % (29 of 69) unigenes had

unknown function annotation.

Whereas under the stricter criterion, only one differen-

tially expressed unigene (Contig_3686) was found to be

always down-regulated during drought stress in both the

tissues, while there was no unigene showing up-regulation.

Time course analysis of differentially expressed

unigenes induced by drought stress using SOM

In this study, 2,623 and 3,969 unigenes were time-depen-

dent differentially expressed in root and leaf, respectively.

To examine their changes in gene expression, the 2,623 and

3,969 differentially expressed unigenes were divided into

16 typical profiles via SOM clustering (Figs. 5, 6). The

complete list of the 2,623 and 3,969 unigenes are shown in

supplementary Tables 11 and 12.

For root (Fig. 5), the 2,623 differentially expressed

unigens were merged into three major groups: up-

regulated (R1, R9, R11, R12, and R13), down-regulated

(R2, R3, R5, R6, R7, R8, and R10) and fluctuating (R4,

R14, R15, and R16). In the up-regulated group, the signal

intensity of the unigenes in R1 was continuously increased

during the investigated period, with a rapid increase per-

iod at 0.5–6 h; the unigenes in R9 and R13 had a rapidly

increasing trend in signal intensity at 0–6 h followed by

slight decreasing; and the signal intensity of the unigenes

in R11 and R12 was maintained unchanged at early stage

and increased thereafter, with a rapidly increasing period

at mid-stage. In the down-regulated group, the signal

intensity of the unigenes in R2, R7, and R8 was gradually

decreased at 0–6 h and maintained unchanged thereafter;

the unigenes in R3 and R6 had a similar decreasing trend

in signal intensity after 0.5 h; the unigene expression in

R5 was first decreased rapidly, and then increased at

0.5–1.5 h and maintained unchanged at 1.5–24 h; the

unigenes in R10 were maintained almost unchanged in

signal intensity at 0–6 h, and then rapidly decreased at

6–12 h and rapidly increased at 12–24 h. It was notable,

in the fluctuating group, that the signal intensity of the

unigenes in R14 showed an expression pattern completely

contrary to that in R16.

Fig. 4 Changes in number of differentially expressed unigenes in

root and leaf at investigation time points. A Expression ratio of C2-

fold up- or B0.5-fold down-regulation. B Expression ratio of C5-fold

up- or B0.2-fold down-regulation. C Unigenes differentially

expressed in both root and leaf at all five time points

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For leaf (Fig. 6), the 3,969 differentially expressed

unigenes were merged into three major groups: up-regu-

lated (L2, L3, L5, L6, and L12), down-regulated (L1, L8,

L13, L14, and L15) and fluctuating (L4, L7, L9, L10, L11,

and L16). In the up-regulated group, the unigenes in L3 and

L6 had a similar expression trend, whereas L2 and L5 had

a similar expression trend; the unigenes in L12 showed a

rapidly increasing expression in signal intensity at

0.5–1.5 h and a gradually decreasing expression thereafter.

In the down-regulated group, the unigene expression in L1,

L8, and L13 had a similar decreasing pattern; the signal

intensity for the unigenes in L14 was maintained unchan-

ged for 0.5 h and then gradually decreased; in the case of

the unigenes in L15, slight fluctuating in signal intensity

was observed. In the fluctuating group, L4, L7, and L16

showed the strongest fluctuation in unigene expression

while L10 had the slightest fluctuation.

Pathways in response to drought stress in root and leaf

To examine the changes of pathways in response to

drought stress, the 6,164 differentially expressed unigenes

of chickpea were annotated in KAAS. As a result, 113

pathways were obtained. These pathways can be classified

into six groups based on their expression profiles in root

and leaf (supplementary Table 13). In group I, 89 pathways

with up- and down-regulated unigenes were involved in

both the tissues. Among them, 75.3 % belonged to

metabolism pathways including amino acid metabolism,

carbohydrate metabolism, energy metabolism and lipid

metabolism. In group II, 11 pathways with up-regulated

unigenes were involved in both root and leaf. Contrarily,

six pathways with down-regulated unigenes were involved

in both root and leaf and classified into group III. Three

pathways with down-regulated unigenes and one pathway

with up-regulated ones were involved only in leaf and

classified into group IV and group V, respectively (sup-

plementary Table 13). In addition, three pathways with no

significantly differentially expressed unigenes either in root

or leaf were classified into group VI.

Unigenes unique and shared in root and leaf in response

to drought stress

In this work, compared to the control, total 88 unigenes

were found to be expressed only in drought-stressed root.

Of them, only 18 unigenes were found to be unique for

root, and the rest were also expressed in leaf (supplemen-

tary Table 14). Total 52 unigenes were found to be

expressed only in drought-stressed leaf. Among them, only

Fig. 5 Clustering of expression profiles in root via SOMs. The 16

SOM clusters shown represent typical profiles within the 2,363

unigenes differentially expressed in root during drought stress

treatment. Each cluster (R1–R16, the number of unigenes included

is indicated) is represented by the red centroid (average expression

profile). (Color figure online)

Mol Biol Rep (2012) 39:8147–8158 8153

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13 unigenes were unique for leaf, and the rest were also

expressed in root (supplementary Table 15). Nine unigenes

were found to be expressed only in both the stressed tissues

(supplementary Table 16).

Quantitative real time PCR analysis

To confirm the microarray results, we selected 10 unigenes

that showed significant up- or down-regulation during

drought stress, and analyzed their differential expressions

by qPCR with the same RNA samples used for the

microarray experiment. As shown in Fig. 7, some genes

displayed significant higher fold-induction at certain time

point in the microarray analysis, such as Contig_1672 at 12

and 24 h in root. On the contrary, some genes displayed

significant higher fold-induction at certain time point in the

qPCR analysis, such as Contig_5876 at 6 h in leaf. These

differences probably reflected the different dynamic range

of microarray compared to qPCR analysis. Though these

differences existed, however, the qPCR results and

microarray data showed similar expression kinetic patterns

(up- or down-regulation) for all the unigenes tested, indi-

cating the strong reliability of the microarray data. In

addition, the qPCR results of CarNAC1 (Contig_3143) and

CarNAC3 (Contig_795) in our previous research were also

in agreement with those of the microarray analysis in this

study [28, 29].

Discussion

The advent of microarrays has enabled the screening of

thousands of genes in parallel to assist in candidate gene

identification. Ideally, one would like to scan the entire

genome of a particular plant to obtain a more complete

picture of transcriptional changes in response to various

stresses. However, the whole genome sequences are not

available for chickpea to date, leading to a dependence on

collections of ESTs assembled from random cDNA

libraries [11]. In this study, to construct an oligonucleotide

microarray, we collected all ESTs and nucleotide sequen-

ces of chickpea in GenBank (to October 2009). This col-

lection contained important ESTs of chickpea related to

physiological acclimation and adaptation to biotic or abi-

otic stresses, such as 592 ESTs from chickpea infected by

Ascochyta rabiei [30, 31], 6,273 related to immune-

response of chickpea to Fusarium oxysporum [32], 24,419

related to salinity and drought stresses [15, 33]. Especially,

this collection included 7,221 ESTs from two cDNA

libraries constructed using the PEG-treated and -nontreated

Fig. 6 Clustering of expression profiles in leaf via SOMs. The 16

SOM clusters shown represent typical profiles within the 3,969

unigenes differentially expressed in leaf during drought stress

treatment. Each cluster (L1–L16, the number of unigenes included

is indicated) is represented by the red centroid (average expression

profile). (Color figure online)

8154 Mol Biol Rep (2012) 39:8147–8158

123

seedling leaves of chickpea by our research group [13]. As

we expected, most genes, which have been identified to

relate to drought stress by other researchers, were also

observed in our result. Moreover, their up- or down-regu-

lated expression patterns in this study were similar to those

in other researchers’ investigations in response to drought

stress. For example, the expression of two genes encoding

ribosomal protein S2 and fructose-1,6-bisphosphatase in

leaf in this study (Contig_2767, Contig_9775) showed the

same down-regulation pattern with that by Romo et al. [9]

Fig. 7 Real-time quantitative PCR and microarray analyses of

expression of ten unigens (Contig_1885: proline dehydrogenase;

Contig_3134: lipoxygenase LOXN3; Contig_2853: peroxidase1B;

Contig_5876: nitrate transporter; Contig_3259: homocysteine S-

methyltransferase; Contig_1500: Photosystem I reaction center sub-

unit N, chloroplast precursor; Contig_2780: beta-amylase; Con-

tig_2823: glycine-rich protein 1; Contig_2895: glutathione peroxidase

1; Contig_1672: alanine: glyoxylate aminotransferase). Different

characters (a–d for qPCR, A–C for microarray) on the top of a column

indicate significant (P B 0.05) differences among different time

points of drought stress, while the asterisk indicates significant

(P B 0.05) difference between qPCR and microarray under the same

time of drought stress

Mol Biol Rep (2012) 39:8147–8158 8155

123

(DY475051, DY475548). In the case of up-regulation, two

LEA protein unigenes in this study (Contig_3383 and

Contig_1170) showed the same expression pattern with

that by Romo et al. [9] (CapLEA-1 and CapLEA-2); and a

similar result for a CBL-interacting protein kinase unigene

(Contig_1755) was also observed in the results of this study

and Tripathi et al. [34].

Although several researches have studied the gene

transcription of chickpea under drought stress via micro-

array technique [10, 11, 15, 16], there were no researches

investigating gene expression profiles in root and leaf of

chickpea seedling at the same time. In this work, compared

to the control, 88 unigenes were found to be expressed only

in drought-stressed root; of them, 18 unigenes were found

to be unique for root (supplementary Table 14). 52 unig-

enes were found to be expressed only in drought-stressed

leaf; among them, 13 unigenes were unique for leaf (sup-

plementary Table 15). Only nine unigenes were found to

be expressed in both the stressed tissues (supplementary

Table 16). Three pathways with down-regulated unigenes

and one pathway with up-regulated ones were found to be

involved only in leaf (supplementary Table 13). Addi-

tionally, a number of differentially expressed unigenes

showed obvious differences in drought stress-responsive

time points, expression intensity and up- or down-regula-

tion between both the tissues (supplementary Tables 11,

12). Therefore, we expect that all the differences in tran-

scriptomic profiles between root and leaf of chickpea

seedling in the present study will enhance our under-

standing of the diversity of responses to drought stress

among plant organs, and more importantly, will benefit the

investigation of mechanism of drought tolerance in

chickpea.

In this study, the number of differentially expressed

unigenes in chickpea root was almost always less than that

in leaf at each investigation time point (Fig. 4A, B; sup-

plementary Tables 8, 9), indicating that the biological

processes involved in drought tolerance in chickpea leaf

was more extensive and active than these in root. In

addition, there were only nine unigenes with expression

ratio of C50-fold up-regulation in root, while 44 unigenes

in leaf (supplementary Tables 8, 9). It is noteworthy that

the highest fold of the up-regulated unigenes in root

(Contig 5431: unknown [G. max], 64.87-fold up-regulation

at 24 h) was much lower than that in leaf (Contig 1183:

PREDICTED: similar to Os12g0187800 [Vitis vinifera],

1048.80-fold up-regulation at 1.5 h). Os12g0187800 is a

conserved hypothetical protein identified in rice [35]. This

is the first evidence that Os12g0187800 may play an

important role in plant drought tolerance, but more detailed

expression, localization and functional analyses are

needed.

In the present study, 4,815 unigenes and 110 pathways

significantly responded to drought stress. Some of them

could be used as candidates for further study of drought

tolerance. As far as we know, some unigenes in chickpea

and other plants or crops have been extensively investi-

gated by previous researchers, such as genes encoding LEA

proteins, water channel proteins, various transcription

factors (DREB, AREB, MYC, MYB, bZIP, and NAC,

etc.), protein kinases, protein phosphatases, sugars (ga-

lactinol, and trehalose, etc.), amino acids (proline, methi-

onine, and glycine, etc.), pathogenesis related proteins, and

so on [3, 36–38]. However, many unigenes (such as genes

encoding germin-like protein [39] and F-box protein [40])

and pathways (such as ‘‘Stilbenoid, diarylheptanoid and

gingerol biosynthesis’’ [PATH: ko00945]) that responded

to drought stress in chickpea were still poorly investigated.

To select the genes and pathways that are candidates for

drought tolerance, we should focus on the genes that were

particularly high up- or down-regulated in response to

drought stress and the pathways they involved in. Supple-

mentary Table 17 listed 183 unigenes that were particu-

larly up- or down-regulated (C50-fold) in root or leaf under

drought stress. Of the 183 unigenes, 110 had specific

function annotation. The proteins encoded by these unig-

enes included ten transcription factors (9.1 % of 110

unigenes), nine LEA proteins (8.2 % of 110 unigenes), six

heat shock proteins (5.5 % of 110 unigenes), five trans-

porters (4.6 % of 110 unigenes), and so on. It is noteworthy

that all genes encoding the heat shock proteins and LEA

proteins showed to be up-regulated in leaf at 1.5–24 h of

drought stress. Supplementary Table 18 showed the 17

pathways in which the 183 unigenes involved. These

results would be helpful for researchers in the study of

chickpea drought tolerance.

Through long-term evolution and adaptation to extreme

conditions, chickpea has been found to be rich in resistance

genes for a range of abiotic stresses, including drought,

cold and high salinity [41]. Our study showed that a high

proportion (1,922 unigenes, 39.92 %) of differentially

expressed unigenes had no function annotation or function

unknown. It is also noteworthy that many of these unigenes

showed remarkable expression changes in response to

drought stress, especially with some having a rapid

increasing or decreasing expression. We daringly specu-

lated that some of these differentially expressed unigenes

might be specific for chickpea and play very important

roles in response to drought stress. Therefore, it is possible

to identify some drought responsive genes unique to

chickpea. Further analysis of the functions and expression

controlling mechanism of these genes in chickpea would

not only supply the opportunity of isolation and identifi-

cation of novel genes, but also enhance our further

8156 Mol Biol Rep (2012) 39:8147–8158

123

understanding of specific mechanism of drought tolerance

in chickpea.

Acknowledgments We gratefully acknowledge the partial financial

support from the projects supported by the National Natural Science

Foundation of China (30960201, 30960206, 30860152 and

31160306), from the project supported by the Xinjiang Science and

Technology Department of China (200991254), from the projects

supported by the National Science and Technology Ministry

(2006BAD09A04, 2006BAD09A08), from the project supported by

the National Science Foundation for Postdoctoral Scientists of China

(20080431107), from the project supported by the Jiangsu Science

Foundation of Postdoctoral Scientists of China (0801048B) for this

research.

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