Transcript profiling identifies novel transcripts with ...

Transcript profiling identifies novel transcripts with unknown functions as primary response components to osmotic stress in wheat (Triticum aestivum L.) Bharti Garg, Swati Puranik, Shrilekha Misra, Bhumi Nath Tripathi & Manoj Prasad Plant Cell, Tissue and Organ Culture (PCTOC) Journal of Plant Biotechnology ISSN 0167-6857 Plant Cell Tiss Organ Cult DOI 10.1007/s11240-012-0254-2

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Author's personal copy Plant Cell Tiss Organ Cult DOI 10.1007/s11240-012-0254-2

ORIGINAL PAPER

Transcript profiling identifies novel transcripts with unknown functions as primary response components to osmotic stress in wheat (Triticum aestivum L.) Bharti Garg • Swati Puranik • Shrilekha Misra Bhumi Nath Tripathi • Manoj Prasad

•

Received: 31 July 2012 / Accepted: 3 November 2012 Ó Springer Science+Business Media Dordrecht 2012

Abstract Osmotic stress induced by dehydration and salinity, is among the major abiotic stresses that adversely impacts crop productivity and plants often display cultivardependent response against osmotic imbalance. To better understand the molecular mechanisms underlying differential responses to dehydration, transcriptome changes of two contrasting wheat (Triticum aestivum L.) cultivars were evaluated in plants grown under unfavorable osmotic conditions. A total of 107 non-redundant transcripts were identified. Of these, most had unknown functions (31; *30 %) signifying the existence of putative stress-specific genes in wheat, reported here for the first time. Upon comparing with previous transcriptomic studies, 43 (40 %) of the osmotically-responsive transcripts were found not to be documented. These new transcripts may therefore signify unexplored gene sources for specific responses towards short-term osmotic stress in wheat. Through

Electronic supplementary material The online version of this article (doi:10.1007/s11240-012-0254-2) contains supplementary material, which is available to authorized users. B. Garg S. Misra B. N. Tripathi Department of Bioscience and Biotechnology, Banasthali University, Banasthali 304022, Rajasthan, India S. Puranik Department of Biotechnology, Faculty of Science, Jamia Hamdard, New Delhi 110062, India B. N. Tripathi Department of Botany, Guru Ghasidas University, Bilaspur 495009, Chhattisgarh, India M. Prasad (&) National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, JNU Campus, New Delhi 110067, India e-mail: [email protected]

macroarray analysis, 69 (*64 %) transcripts were found to be differentially expressed (C3-fold) and expression of 14 transcripts (with known or unknown functions) was further confirmed by quantitative real time PCR. Expression analysis of the seven unknown transcripts also revealed their tissue- and stress-specific regulation. Comparative in silico mapping of these 107 wheat transcripts against available mapping data for rice (40; *37 %), maize (34; *32 %), and sorghum (33; *31 %) revealed presence of wheat orthologous sequences in these cereal crops. This study provides an interesting account on several novel genes, besides those with known functions, which may regulate stress response dynamics and thus, may be used as potential candidates to improve stress adaptability through genetic and molecular studies. Keywords Wheat Triticum aestivum Osmotic stress Suppression Subtractive Hybridization (SSH) Quantitative real time PCR (qRT-PCR) Polyethylene glycol (PEG) Unknown novel transcripts

Introduction One of the most severe agricultural limitations posing a serious threat to crops, including widely cultivated hexaploid wheat (Triticum aestivum), is the improper soil water uptake (Gill et al. 2004). Consequently, water limitation initiates an alteration in plant metabolism, osmotic and ionic imbalances and reduced endogenous water potential causing physiological dehydration in the cell (Bartels and Sunkar 2005). Wheat cultivars, however, show great variability in their responses to water stress, specifically dehydration, corresponding to the ability of cultivar to counterbalance the stress and subsequent induction of

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Author's personal copy Plant Cell Tiss Organ Cult

stress tolerance. The molecular mechanism underlying this variability in stress responses of wheat cultivars in context with osmotic adjustment under dehydration stress is believed to be associated with differential expression of stress resistant genes (Puranik et al. 2011). Therefore, understanding of the molecular machinery enabling dehydration tolerance in wheat requires isolation and characterization of osmotic stress-inducible genes, including tolerance-associated genes and their products in selected wheat cultivars. Previously, numerous dehydration stressresponsive transcripts, mainly those involved in cellular protection and regulation (e.g. kinases, transcription factors), were identified by microarray-based profiling in wheat roots (Mohammadi et al. 2007). Nevertheless, identification and characterization of several stress-regulated candidate genes in two Indian bread wheat cultivars with contrasting dehydration-tolerance characters have been still unexplored. Hence, development of osmotic adaptability in wheat could be achieved by identification and functional characterization of dehydration tolerance genes to maintain sustainable wheat production. Therefore, we aimed to explore the transcriptomic alterations during osmotic imbalance-induced dehydration stress, in two contrasting bread wheat cultivars having differential dehydration stress tolerance. By employing Suppression Subtractive Hybridization (SSH) approach, we have isolated 107 unique transcripts with varied expression in these cultivars and validated their expression patterns by macroarray, quantitative real-time PCR (qRT-PCR) and northern blot analysis. The present study describes the relevance of some genes with indefinable molecular identity that can further be used as candidate genes for genetic modification of stress adaptation of the test plant and other crops.

Materials and methods Plant material and stress treatments Seeds of twenty-eight Indian bread wheat (T. aestivum L.) cultivars were obtained from G.B. Pant University of Agriculture and Technology, Uttrakhand, India. After a preliminary screening, two cultivars, namely cv. C306 and cv. HI1544 were identified as highly dehydration tolerant and sensitive, respectively (Garg et al. 2012). Seeds of these two cultivars were allowed to germinate, sown in 9 cm3 pots containing composite soil (peat compost to vermiculite at 3:1 ratio) and grown in a plant growth chamber (PGC-6L; Percival Scientific Inc., USA) at 28 ± 1 °C day/23 ± 1 °C night/70 ± 5 % relative humidity with a photoperiod of 14 h and a photosynthetic photon flux density of 500 lmol m-2 s-1 (Lata et al. 2010). For construction of the SSH library and expression

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analysis, ten-days-old seedlings of both the cultivars were treated with 20 % polyethylene glycol (PEG6000) for 1, 3, 6, 12 and 24 h following Lata et al. (2010). Treatments for other abiotic stress including salinity, ABA and cold were done following the procedures given by Puranik et al. (2011). After treatment, seedlings were harvested and separated into roots and shoots depending on the experimental requirement, frozen immediately in liquid nitrogen and stored at -80 °C for RNA isolation. Construction of an SSH library Total RNA was isolated from the seedlings by TRIzol reagent (Sigma Aldrich, USA) according to manufacturer’s instructions. mRNA was purified by mRNA isolation kit (Roche Applied Science, USA). A forward cDNA subtraction library was constructed using 2 lg mRNA from cv. C306 as tester and cv. HI1544 as driver by CLONTECH PCR-select cDNA subtraction kit (CLONTECH Laboratories, Palo Alto, CA). The subtracted PCR products were cloned in T/A cloning vector (Promega, USA) and the recombinant clones were sequenced using ABI Sequencer (Version 3770) by universal M13 forward primer. Sequence analysis and in silico comparative mapping Vector and adaptor sequences were removed by VECSCREEN (www.ncbi.nlm.nih.gov/VecScreen/VecScreen. html) at NCBI. Homology search and annotation were completed by BLASTx/BLASTn algorithms (http:// blast.ncbi.nlm.nih.gov/Blast.cgi). Transcripts longer than 100 nucleotides and showing E-value less than 1e-05 were considered as significant. Functional classification was carried out using the Gene Ontology annotation tool at TAIR (www.arabidopsis.org). Further, BLASTn search tool (http://www.gramene.org/ and http://www.phytozome. net/) was employed to compare the obtained sequences with those of rice, maize and sorghum by setting minimum 75 % identity and 85 % query length coverage as standard cut-off (Gupta et al. 2012). Predicted proteins for the unknown genes were analyzed comprehensively using different tools, for example, their molecular weight, theoretical pI and hydropathicity index was computed using ProtParam (http://web.expasy.org/protparam/; Gasteiger et al. 2005). The presence of conserved domains was predicted using Pfam (http://pfam.sanger.ac.uk/; Finn et al. 2010), SMART (Simple Modular Architecture Research Tool; http:// smart.embl-heidelberg.de/; Letunic et al. 2012) or InterProScan (http://www.ebi.ac.uk/Tools/pfa/iprscan/). Two online programs WOLF-POSRT (http://wolfpsort.org/; Horton et al. 2007) and ProtComp v. 9.0 from Softberry Inc. (http://linux1.softberry.com/berry.phtml?topic=prot comppl&group=programs&subgroup=proloc) were utilized


to predict the sub-cellular localization of the proteins. Prediction of trans-membrane helices in the sequences was done using TMHMM Server v.2.0 (http://www.cbs.dtu.dk/ services/TMHMM/; Moller et al. 2001) and HMMTOP v. 2.0 (http://www.enzim.hu/hmmtop/index.php; Tusna´dy and Simon 2001). In silico mapping onto rice chromosomes was performed using the Gramene database (www.gramene.org) and previously published literature by taking E-value lower than 1e-04 and more than 100 nucleotide long as cut-off criteria. Screening of differentially regulated transcripts by macroarray and expression analysis Differentially expressed transcripts were isolated by macroarray hybridization with radiolabeled cDNA probes from dehydration stressed cv. C306 and cv. HI1544 samples, according to Boominathan et al. (2004) with some modifications. Wheat Actin (Accession No. BAD23897; Table 1) amplicon was used as an internal control while Neomycin phosphotransferase (NPTII) gene of vector pCAMBIA 1305.1 was spotted as a negative control. The normalized intensity was subjected to fold-change calculation. Expression analysis by qRT-PCR was done according to Jayaraman et al. (2008), and relative amount of the transcript accumulated for each gene normalized to actin control was analyzed using 2-DDCt method (Livak and Schmittgen 2001). The PCR efficiency which is dependent on the assay, performance of the master mix and quality of sample, was calculated as: Efficiency = 10 (-1/ slope) - 1 (3.6 C slope C 3.1) by the software itself (Applied Biosystems). The primers were designed from the non-conserved regions of the selected transcripts using the

Primer Express Version 3.0 software (Table 1). Northern hybridization was performed as given in Sambrook and Russell (2001). The PCR-amplified fragments of cDNA clones were labelled with a32P dCTP using high prime DNA labeling kit (Roche, USA) and the probes were purified using G-50 Sephadex column (GE Healthcare, USA). Labeled probe was added to hybridization buffer and incubated at 60 oC for 16–18 h. Blots were scanned in a Phosphor-imager (Typhoon-9210, GE Healthcare, USA) and quantified using Quantity One software (Bio-Rad, USA). The experiments were performed using three different RNA extractions with each experiment being conducted in three technical replicates.

Results and discussion Identification and classification of osmotic stress-associated genes Cellular response to treatments such as that to polyethylene glycol 6000 (PEG-6000), involves a rapid osmotic shock and the relative potential of different wheat cultivars to tolerate dehydration stress associated therewith could in part indicate the adaptability at physiological and biochemical levels (Lata and Prasad 2012). To identify the genes associated with osmotic stress-induced dehydration, total 1,000 recombinant plasmids were randomly sequenced. After single pass sequencing and eliminating the redundant clones, 107 unique transcripts were obtained, submitted to GenBank (Accession No. JK546454JK546560) and grouped into 12 functional categories (Supplementary Table S1). Among them, the largest

Table 1 Primers used for quantitative real time PCR analysis S. No.

Primer ID

GeneBank Acc. No

Forward sequence (50 –30 )/reverse sequence (50 –30 )

1

WRKY 17

JK546463

GACCAAGCGGCTCAACGAT/ GGTGCATATGCTAGCTTG

2

Proline oxidase

JK546467

AGAAGCGACGGAGTTAGAAGTTGT/ CCCGGACCTGCCCGGGCG

3 4

MADS-box RING-FINGER protein

JK546496 JK546506

GCCGAGGTACTAAGGAGTCAATAATT/ GAAAGCATGGTTATAGAAT CCGCAGCAGCGTTATCTACA/ GAGGTGCTTCTCTGCAGCCG

5

F-box gene

JK546511

CCTACTTGCCTACCCCACTGAA/ CACTATCGACTTGCATGCTTC

6

RNA helicase

JK546512

CTGACCCGCCGATGGA/ AACATACGCTTGTTTTAAT

7

ABA-responsive gene

JK546530

CGATGATGAACTCCACTCA/ ATGATATAGTTCCAAAGG

8

Unknown

JK546491

TCGCTCTCCGCCTATGCT/ GAGTGATGAATATGTAAGA

9

Unknown

JK546505

AAAGCAACAGGCTGTAAGCA/ TGTCGTCACCGCTCAAGTAG

10

Unknown

JK546528

ATCTGAACAACAAGCAACACCAA/ GCCACACACACACGCATAGGC

11

Unknown

JK546542

GAAGTTGTGTTTGATAATA/ GAAAAGAACACTAAGAGA

12

Unknown

JK546498

AGGTGTAAGCCCACCCCA/ ATACGGGGATGGAGCGAC

13

Unknown

JK546455

GGGCGATGGAACCAATGAT/ CTCCATTCCTCTTGATACCA

14

Unknown

JK546482

ACATGCTATCTGGAGT/ ATGATGCCTCCGAGCTTGT

15

Actin

BAD23897

CCCAAAGGCCAACAGAGAGAA/ GCCTGGATTGCGACATACATT

123


category contained transcripts with hypothetical or unknown function or with no similarities to previously sequenced genes (31; 28.9 %), indicating the presence of putative novel stress-specific genes in wheat (Fig. 1a). A detailed domain analysis of their predicted proteins was performed along with the prediction of their sub-cellular localization (Supplementary Table S2). Many of them contained various conserved domains, which may be utilized for their functional annotation in the future. This was followed by genes involved in the transcription/translation processes (15; 14 %) and metabolism-related transcripts (11; 10 %). The remaining transcripts had diverse functions in biotic and abiotic stress response, development, photosynthesis, signaling and transport (Supplementary Table S1). These findings are comparable to similar investigations performed on other crop plants during various abiotic stresses (Eisen et al. 1998; Lokko et al. 2007; Guan et al. 2010; Yang et al. 2011; Liu et al. 2012a). The identified clones present an initial overview of the transcriptional response of two distinct wheat cultivars during early hours of PEG-mediated osmotic stress. Assessing differentially expressed genes by macroarray and qRT PCR analysis The macroarray data revealed that out of the 107 transcripts, 69 (64.5 %; 63 up- and 6 down-regulated) produced C3-fold change in intensity. Of these, 61 transcripts in cv. C306 and only 8 in cv. HI1544 were differentially regulated (Supplementary Table S3). Further, in the tolerant cv. C306, all the transcripts were induced while in cv. HI1544, only 2 were induced and 6 were repressed (Supplementary Table S3). Interestingly, of the 61 upregulated transcripts in cv. C306, 26 (*43 %) belonged to unknown/ unclassified function indicating the presence of several putative novel and unexploited genes, which may be involved in water stress adaptability. Further, in the tolerant cv. C306 activation of cellular response machinery seems to occur more rapidly than in cv. HI1544. These findings clearly suggest that even during the initial period of PEG-induced dehydration, transcript response of these two cultivars is quite discrete from each other. A broad outline of the comparative expression profile of these differentially expressed transcripts was obtained by hierarchical clustering of their expression pattern in tolerant cv. C306 relative to cv. HI1544 (Mare et al. 2004; Mehta et al. 2005). Based on distance of correlation, the transcripts were clustered into 11 groups with each cluster containing various numbers of genes (Fig. 1b, c). Of these, cluster 2 (14 transcripts), cluster 9 (11 transcripts), and cluster 11 (19 transcripts) appeared to be expressed preferentially in the tolerant cv. C306 but were either downregulated or had a basal expression in cv. HI1544 (Fig. 1b,

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Fig. 1 Functional classification and clustering of non-redundant 107 c differentially expressed wheat transcripts. a Unique transcripts were grouped into 12 functional categories. b SOTA clustering generated by hierarchical clustering analyses of transcripts based on their pattern in tolerant cv. C306 in comparison to cv. HI1544. Cluster 2, 9 and 11 are boxed. c Expression profile of SOTA clusters. The expression profile of each individual gene in cluster is denoted by a lighter line and the mean expression profile is depicted by bold line. d Classification of transcripts belonging to cluster 2, 9 and 11 based on their putative functions

c). Interestingly, most of the transcripts in these clusters represented genes with unknown function (Supplementary Table S1; Fig. 1d). Further, detailed comparative analysis with the outcomes of transcriptome analysis in response to dehydration stress using available databases in wheat, rice, barley, maize, Arabidopsis thaliana and other systems revealed that 64 (60 %) transcripts shared homology with previously reported genes with known functions (Supplementary Table S3). However, to the best of our knowledge, the remaining 43 (40 %) up-regulated transcripts were not reported in transcript profiling of dehydration stress in other species, thus they may highlight early osmoticallyregulated stress-specific responses in wheat. Validation of differentially expressed transcripts in response to dehydration To authenticate the macroarray data, we performed qRTPCR for quantifying the relative transcript accumulation of 14 transcripts that had shown at least three fold inductions in macroarray. The qRT-PCR efficiency for all the reactions was between the acceptable range of 90–110 %, and all transcripts displayed an expected differential expression pattern at various time points in cv. C306 and HI1544 (Fig. 2a–n; Supplementary Table S4). Of the 14 transcripts, 7 represent members of some well-characterized stressassociated genes like WRKY17, Proline oxidase, F-box protein, MADS box, Ring finger-like protein, ATP dependent RNA helicase and ABA responsive gene. Although rest of the transcripts had no annotated functions in the database, their expression patterns may associate them as novel stress-responsive genes in wheat. Their direct or indirect relationship with the differential dehydration stress response has been discussed below. Response of transcripts of known functions A crucial part of stress response involves transcriptional regulation of stress-responsive gene expression and control of their temporal and spatial expression patterns. Four transcripts related to transcription regulation (WRKY17, MADS-box, Ring finger protein) and RNA metabolism (RNA helicase) showed a general induction by PEGinduced dehydration stress, with varying level of


(A)

10.28%

(B) 9.34%

28.9%

6.54%

14.0% 4.6

16 Genes

14 Genes

1Gene

11 Gene

33 Genes

1Gene

1Gene

1Gene

1Gene

8Gene

19 Gene

9 11

8.41% Photosynthesis Transcription/post trancription Cell cycle and DNA processing Sigalling Protein degradation Unknown/hypothetical

9

(C)

11

1.86% 1.86% 4.67% 6.54% 2.80% Metabolism Abiotic/Biotic stress Translation / post translation Trasporter House keeping Cell structure and development

CLUSTER 2 7.1%

Unknown 9.0%

Metabolism

Signalling

7.1%

9.0 %

7%

Photosynthesis

36.3%

Cell structure and development Housekeeping

7.1% 57.1% 7.1%

18.1%

Transcription/post transcription Translation/post translation

7.1%

2

CLUSTER 9 Unknown

9.0 %

9.0% 9.0%

Signalling Transcription/post transcription Translation/post traslation Transport Biotic/abiotic stress

CLUSTER 11 Unknown 15.7%

Metabolism 31.5%

5.2%

Photosynthesis Cell structure and development

15.7%

15.7% 15.7%

2

(D)

Transcription/post transcription Biotic/abiotic stress

123


expression at different time points between the two cultivars (Fig. 2a–d). Their specific upregulation in the tolerant cv. C306 suggests that its regulatory machinery is more effective than cv. HI1544. This may be crucial for dehydration adaptation due to strong and prolonged control of downstream stress-responsive gene expression in the tolerant cultivar. Different members of these well-known gene families have been previously reported to be involved in various types of abiotic stresses to activate plant defense mechanism (Mare et al. 2004; Zhang et al. 2005, 2007; Linder 2006; Owttrim 2006; Stone et al. 2006; Tardif et al. 2007; ). The cell responds to stress by synthesizing various osmoprotectants like proline and free proline levels have been found to increase under water deficit stress in wheat (Nayyar 2003; Zhu et al. 2005). Down-regulation of genes encoding proline oxidase (proline degradation enzyme) has been well documented to play an important role in stress tolerance (Shinozaki and Yamaguchi-Shinozaki 2000). However, in our study, the transcript abundance of a gene encoding this enzyme increased until 12 h of stress treatment in cv. C306 but remained near equal to that of unstressed plants in cv. HI1544 (Fig. 2e). It may be possible that during hyperosmotic stress, the state of water imbalance also leads to some kind of nutrient and energy deprivation. During such conditions, proline oxidase may start degradation of the readily available cellular proline to generate energy source (ATP) and also to produce reactive oxygen species in this process (Pandhare et al. 2009; Liu et al. 2012b; Natarajan et al. 2012). These ROS may signal the process of intrinsic apoptosis intended for removal of damaged cells or tissues, thereby promoting a competent survival during stressful conditions in the tolerant cultivar. The closest ortholog of this transcript encoded a barley proline dehydrogenase and was identified from a normalized subtracted barley full-length cDNA library during Aluminium stress (Matsumoto et al. 2011). Another stress-responsive cellular phenomenon is degradation or refolding stress-damaged proteins using proteases and chaperons. A transcript encoding an F-box protein was found to be continuously expressed in cv. C306, while in cv. HI1544 the mRNA accumulation decreased at later stages of stress (Fig. 2f). Its expression in the tolerant cv. may help to re-build the regular protein conformations thereby maintaining cellular homeostasis, as also reported previously (Jain and Chattopadhyay 2010). Another group of typical stress-responsive genes are the ABA-responsive genes which help to safeguard the plant by regulating stomatal closure. In this study, an ABA-responsive transcript was induced up to four fold during later stress durations in cv. C306, in contrast to cv. HI1544 where its expression level remained below two folds at all the time points (Fig. 2g). In several previous studies, stress tolerance was found to

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Fig. 2 qRT-PCR analysis of differentially expressed transcripts with c known and unknown functions in response to PEG-induced osmotic stress in tolerant cv. C306 and sensitive cv. HI1544. Expression patterns of aWRKY17, bMADS-box, cRing-finger, dRNA helicase, eProline oxidase, fF-box, gABA responsive gene, hUnknown (JK546491), iUnknown JK546455, jUnknown JK546482, kUnknown JK546505, lUnknown JK546528, mUnknown JK546498, and nUnknown JK546542. Bars indicate the standard error (±SE) calculated from three independent experiments

increase in desiccated Craterostigma plantagineum calli, salt-stressed tobacco cells, and wheat calli after pretreatment with ABA (Singh et al. 1987; Bartels et al. 1990; Dallaire et al. 1994). The result indicates that this transcript may have a pivotal role in osmotic stress response by integrating the ABA stress signaling pathway. Response of transcripts of unknown functions qRT-PCR analysis of transcripts with unknown function showed variation in their transcript abundance of changed osmotic conditions (Fig. 2h–n). The transcripts JK546491, JK546455, JK546482 and JK5464505 gradually upregulated (C4-fold) until 6 h later up-surging again at 24 h in cv. C306 but did not considerably accumulate in the sensitive cultivar (Fig. 2h–k). The expression pattern was similar for JK546528 and JK546498 showing higher transcript accumulation (C6fold) during 12–24 h of dehydration stress in cv. C306, while marginally expressing (up to 2-fold) in the sensitive cultivar (Fig. 2l, m). The mRNA of JK546542 gradually accumulated to[7-fold at 6 h in cv. C306, reducing continuously thereafter reaching near the basal level (Fig. 2n). Although the exact reason for such an expression pattern remains unclear at this stage of investigation, their specific accumulation signifies them as putative novel genes, which may govern superior stress adaptation in the tolerant wheat cultivar through unexplored pathways. Analysis of temporal and tissue-dependent expression of unknown genes Further, we checked the accumulation of unknown transcripts in a time and tissue-dependent manner during PEG-induced dehydration stress in cv. C306 by northern blot analysis (Fig. 3a–i). All transcripts were found to be upregulated by dehydration stress, though with varying mRNA accumulation patterns. The transcripts JK546455 and JK546491 were upregulated (C3-fold) during stress in both roots and shoots (Fig. 3a, b). The mRNAs of JK546505, JK546542 and JK546482 were more abundant in the roots inducing C2-fold as early as 1 h and maintaining high expression even until 12 h of dehydration treatment, but maintained minimal expression in shoot tissues (Fig. 3c–e). Hence, these transcripts probably represent root-specific dehydration-inducible genes, which may function in stress perception and


6 4 2 0 6

12

24

Time post stress (hours)

HI1544

12 8 4 0 C

1

6

2 1.5 1 0.5 0

1

6

12

24


8

PROLINE (JK546467) C306

HI1544

6 4 2 0 C

1

Relative mRNA expression


HI1544

4 3 2 1 0

C

1

6

12

24


20

2 C

1

24

2 0 C

1

C306

HI1544

5 0 1

6

12

24


6

12

24


C306

HI1544

6 4 2 0 C

1

6

12

24


(J)

F-BOX GENE (JK546511) 14 12 10 8 6 4 2 0

C306

C

HI1544

1

C306

16

HI1544

8 4 0 1

6

12


(M)

12

24

C306

5

HI1544

4 3 2 1 0 C

1

6

12

24


UNKNOWN (JK546528) C306

8

HI1544

6 4 2 0

C

1

6

12

24


(L) UNKNOWN (JK546542)

12

C

6


(K) UNKNOWN (JK546498)

24

(I)

UNKNOWN (JK546505) 8

12

UNKNOWN (JK546455)

10

C

6


(F)

15


4



HI1544

6

0

4

(H)

UNKNOWN (JK546482) C306

12

UNKNOWN (JK546491)

(G) 8

6

(E)

ABA RESPONSIVE GENE (JK546530) C306

6


(D)

5

HI1544

(C) Relative mRNA expression



HI1544

C

C306

8

(B)

RNA HELICASE (JK546512) C306

24


(A)

2.5

12


1

C306


C

16


HI1544

RING-FINGER PROTEIN (JK546506)

MADS-BOX (JK5546496)

24


C306



WRKY17 (JK546463) 8

8

C306

HI1544

6 4 2 0

C

1

6

12

24


(N)

123


1h

Fold expression

C

6h 12h 24h

Root Shoot

Root

4 3 2 1 0

Shoot

C

6h 12h 24h

1h

Root 0

6 12 24

1

Shoot

Fold expression

JK546491

JK546455

0

Time post stress (h)

Shoot

C

4 2

1h

6h 12h 24h

Root

0 0

1

6

12 24

Shoot


Root Shoot

Fold expresion

6h 12h 24h

Shoot

2 1 0 0

1

6

12 24

(D) JK546528

JK546482

1h

Root

3


(C)

C

Fold expression

Shoot

12 24

JK546542 Root

6

Root

5 4 3 2 1 0

Shoot

C

1h

6h 12h 24h

Root 0

1

6 12 24

Shoot

Fold expression

Root

Fold expression

6h 12h 24h

6

(B)

JK546505

1h

1

Shoot


(A)

C

Root

4 3 2 1 0


Root

3 2 1 0 0

1

Shoot

6

12 24


(E)

(F)

C Root Shoot

1h

6h 12h 24h

Fold expression

JK546498 Root

5 4 3 2 1 0 0

1

Shoot

6 12 24

Actin

rRNA

C 1h 6h 12h 24h

C 1h 6h 12h 24h

Root

Root

Shoot

Shoot


(G)

(H)

(I)

Fig. 3 a–i Temporal expression profiling of seven transcripts encoding genes while unknown function in root and shoot tissues of tolerant cv. C306 in response to PEG-induced dehydration stress by northern hybridization. The relative fold expression is shown adjacent

to each blot. h–i Actin blot shows positive control while rRNA gel is shown as loading control. Bars indicate the standard error (±SE) calculated from three independent experiments

transduction. On the other hand, transcripts JK546528 and JK546498 showed preferential expression in shoot tissues with the former one showing up to three fold expression from 1 to 12 h, while the latter expressing C4-fold during 6–24 h (Fig. 3f, g). As the shoot-specific expression was very low in comparison to roots, this possibly indicates that the stressinducible function of these transcripts is restricted to the roots. Thus, these genes encoding unknown function proteins positively regulate stress-response and could hold the possibility of major candidates for improving dehydration tolerance through targeted tissue-specific expression.

expression patterns were checked under high salinity, cold, exogenous ABA and water in the tolerant cultivar. This analysis showed differential transcript accumulation in response to all stresses in a time-dependent manner (Fig. 4a– g, Supplementary Table S5). The expression of five transcripts (JK546505, JK546498, JK546528, JK546455 and JK546482) was strongly induced by salinity and ABA at least at one time point, while cold stress highly upregulated JK546505, JK546528 and JK546455. Although these transcripts had unknown functions in the database, it is reasonably possible that they may be part of an ABA-dependent signal transduction pathway and may determine cellular osmotic conditions in response to various abiotic stresses. Thus, it would be interesting to study their differential stressspecific transcript accumulation. Similar observations have also been reported previously (Baisakh et al. 2008; Puranik et al. 2011).

Differential regulation of transcripts of unknown functions in response to various abiotic stresses To address whether other abiotic stresses also regulate any of these dehydration-inducible unknown transcripts, their

123

Author's personal copy JK54646505

8

D

6

S

4

A

2

C

0

W

C

1

6

24




Plant Cell Tiss Organ Cult JK546498

14 12 10 8 6 4 2 0

D S A C

C

1

JK546528 D

15

S

12 9

A

6

C

3

W

0

C

1

6

24


D 12

S

8

A

4

C

0

W C

1

6



D S A C W 1

24


(D)

JK546482

C

W

JK546455

16

(C) 14 12 10 8 6 4 2 0

24

(B) Relative mRNA expression


(A) 18

6


6

24

JK546491

20

D S

15

A

10

C

5

W

0 C



1

6

24


JK546542

16

D 12

S

8

A

4

C W

0 C

1

6

24


(G) Fig. 4 a–g qRT-PCR analysis of transcripts with unknown functions showing their regulation in response to various abiotic stresses in cv. C306. The relative mRNA expression for each transcript was calculated

in d, PEG-induced dehydration; S salt, A ABA, C cold and W water relative to its expression in unstressed conditions. Bars indicate the standard error (±SE) calculated from three independent experiments

In silico comparative mapping of wheat transcripts onto genomes of other cereals

(Supplementary Table S6). Maximum sequence homology was observed with rice (40; *37 %), followed by maize (34; *32 %) and sorghum (33; *31 %) suggesting the presence of wheat orthologous sequences in the individual cereals. The highest percentage (37 %) of identified wheat orthologous sequences in rice genome sequences is understandable, since both are C3 crops and do not belong to the Panicoideae subfamily of maize and sorghum. Interestingly, orthologous sequences of several important dehydration-responsive genes namely Proline oxidase, ABC transporter, Catalase1, Serine/threonine protein

Previous studies have shown the utility of in silico comparative mapping in studying evolutionary relationships and for transmitting information from one species to another (Feuillet and Keller 2002; Guyot et al. 2004; La Rota and Sorrells 2004). The 107 non-redundant differentially expressed transcripts were physically mapped onto chromosomes (chr.) of sorghum, maize and rice; whose genomes have been completely sequenced

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kinase, etc. were found to localize on different rice, sorghum and maize chromosomes. For instance, an aquaporin PIP 1–5 (JK546480) of T. aestivum was mapped on rice chr. 2, sorghum chr. 4 and maize chr. 4 while PIP 2-6 (JK546531) on rice chr. 2, sorghum chr. 6 and maize chr. 2 (Supplementary Table S6). Additionally, 50 wheat transcripts (*47 %) were mapped onto the 12 rice chromosomes and maximum (9; 18 %) orthologues were found to be located onto rice chr. 1 (Supplementary Table S7). Therefore, this information can be useful for crossspecies gene cloning and development of functional molecular markers to be used in crop improvement programs. In conclusion, the present study helps us to identify and specify some novel components regulating the molecular basis of differential dehydration tolerance of two wheat cultivars. Despite being a well-studied crop for several years, wheat has an excellent repository of yet to be characterized stress-associated genes brought out through this work. This valuable information can be exploited for improvement and stabilization of wheat yield during adverse environmental conditions. Further, the wheat transcripts identified in this study may constitute a helpful resource for development of functional markers with potential implications in wheat breeding programs. We are currently characterizing some of these novel transcripts as a prelude to determine their function which, accompanied by the acquisition of the wheat genome sequence, could eventually help to generate crop varieties with superior stress-tolerance by biotechnological intervention. Acknowledgments We are thankful to Vice-Chancellor of the Banasthali University and Head, Department of Biotechnology, Jamia Hamdard, New Delhi, India for providing necessary facilities. Ms Swati Puranik acknowledges the award of Senior Research Fellowship from the Council of Scientific and Industrial Research, New Delhi.

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