and could be representing rust specific WRKY genes. The obtained results will bestow insight into the functional characterization of WrKY transcription factors respon-sive to leaf rust pathogenesis that can be used as candidate genes in molecular breeding programs to improve biotic stress tolerance in wheat.
AbbreviationseSTs expressed sequence tagsGeO Gene expression omnibusGraVY Grand average of hydropathicityIWGSC International wheat genome sequencing
consortiumMeGa Molecular evolutionary genetic analysisnCBI national Centre for Biotechnology InformationnlS nuclear localization signalsSaGe Serial analysis of gene expressionSOliD Sequencing by oligonucleotide ligation and
regulation of gene expression in plants in retort to diverse environmental and biotic agents occurs mostly through transcriptional control requiring the involvement of sev-eral transcription factors (TFs) (eulgem et al. 2000). TFs are proteins that either activate or repress the process of transcription of target genes by binding to specific Dna
Abstract WrKY, a plant-specific transcription fac-tor family, has important roles in pathogen defense, abi-otic cues and phytohormone signaling, yet little is known about their roles and molecular mechanism of function in response to rust diseases in wheat. We identified 100 TaW-rKY sequences using wheat expressed Sequence Tag database of which 22 WRKY sequences were novel. Iden-tified proteins were characterized based on their zinc fin-ger motifs and phylogenetic analysis clustered them into six clades consisting of class IIc and class III WrKY pro-teins. Functional annotation revealed major functions in metabolic and cellular processes in control plants; whereas response to stimuli, signaling and defense in pathogen inoculated plants, their major molecular function being binding to Dna. Tag-based expression analysis of the iden-tified genes revealed differential expression between mock and Puccinia triticina inoculated wheat near isogenic lines. Gene expression was also performed with six rust-related microarray experiments at Gene expression Omnibus data-base. TaWRKY10, 15, 17 and 56 were common in both tag-based and microarray-based differential expression analysis
Communicated by S. Hohmann.
Electronic supplementary material The online version of this article (doi:10.1007/s00438-014-0890-9) contains supplementary material, which is available to authorized users.
l. Satapathy · D. Singh · P. ranjan · D. Kumar · M. Kumar · K. Mukhopadhyay (*) Department of Bio-engineering, Birla Institute of Technology, Mesra, ranchi 835215, Indiae-mail: [email protected]
K. V. Prabhu Department of Genetics, Indian agriculture research Institute, new Delhi 110012, India
sequences. Besides the leaf rust resistant (R) genes, TFs like WrKY, MYB and naC might also help plants to encounter pathogen attack and overcome abiotic stresses (Ulker and Somssich 2004; rushton et al. 2010). The WrKY TFs modulate spatio-temporal expression of the downstream target genes during pathogen infection in response to pathogen encoded protective signal molecules, the elicitors, as well as defense signaling molecules like abscisic acid, Jasmonic acid and Salicylic acid (eulgem and Somssich 2007). The different WRKY genes con-trol various physiological processes at the convergence of biotic and abiotic stress response pathways and, therefore, exploring their underlying mechanism of action might shed light on the cross talks between different stresses (atkinson and Urwin 2012).
The WrKY TFs are one of the 10 largest TF superfami-lies of higher plants that belong to the zinc-finger motif containing WrKY-GCM1 superfamily (Babu et al. 2006). They contain a ~60 amino acids Dna-binding region, des-ignated as WrKY domain, comprising of the conserved WrKYGQK heptapeptide and a zinc-finger motif. Based on the number of WrKY domains and type of zinc-finger motif, WrKY TFs have been classified into three classes (rushton et al. 2010). Class I WrKY proteins have two WrKY domains and a C2H2-type zinc-finger motif (C–X4–5–C–X22–23–H–X1–H), where only the C-terminal WrKY domain is active in Dna binding. Class II proteins contain single WrKY domain and similar zinc-finger motif like class I. The class II WrKY TFs are further divided into five subgroups ‘a–e’ based on variation in additional amino acid motifs present outside the WrKY domain. The class III WrKY TFs also carry single WrKY domain but differs from classes I and II in its altered C2HC type of zinc-finger motif (C–X7–C–X23–H–X–C) (eulgem et al. 2000; Ulker and Somssich 2004). Minor variants of the WrKYGQK signature motif like WrKYGKK and WrKYGeK, are also rarely found (Xie et al. 2005). WrKY proteins exhibit high binding affinity towards a Dna sequence, the W-box, (C/T)TGaC(T/C), although alternative binding sites are also reported (rushton et al. 2010). The conserved Cys and His residues of the zinc-finger motif are essentially involved in zinc dependent Dna-binding activity (Pandey and Somssich 2009).
The WrKY family has been extensively studied in Arabidopsis where more than 74 members were identified; many of them are associated to defense systems (Dong et al. 2003; Kalde et al. 2003; eulgem and Somssich 2007). about 109 WrKY TFs have been reported in rice (rama-moorthy et al. 2008), mostly concerned with responses to various phytohormones, abiotic and biotic stresses includ-ing those caused by blight and blast pathogens (rama-moorthy et al. 2008; ryu et al. 2006). WrKY TFs have also been studied extensively in barley (Mangelsen et al.
2008), maize (Wei et al. 2012), Brachypodium (Tripathi et al. 2012), creosote bush (Zou et al. 2004), soybean (Zhou et al. 2008), banana (Shekhawat et al. 2011), pepper (Dang et al. 2013) and few lower plants like ferns, mosses and green algae (rushton et al. 2010).
Bread wheat (Triticum aestivum l.) is an important cereal crop, that provides one-fifth of food calories and pro-teins to the world population (http://www.faostat.fao.org) and its demand is expected to rise by 60 % in the devel-oping countries by 2050 (rosegrant and agcaoili 2010). Simultaneously, climate change induced rise in tempera-ture, drought and biotic threats are estimated to abate wheat production by 29 % (Braun et al. 2010). The large allohexaploid (2n = 6x = 42) genome of ~16.94 Gb con-sisting of three homoeologous a, B and D genomes that originated from related progenitor species, provide sig-nificant challenges for molecular and functional genom-ics-based improvement of wheat (Choulet et al. 2010). Moreover, recent polyploidization, high proportion of transposable elements and repetitive Dna along with absence of completely sequenced genome, also limit cor-rect assembling, mapping and functional annotation of closely related sequences (Dubcovsky and Dvorak 2007). Therefore, genomics-based improvement of wheat is trail-ing to other major cereal crops like maize and rice (Bevan and Uauy 2013). The rust diseases often jeopardize wheat production worldwide (McIntosh and Pretorius 2011), of them leaf (brown) rust, caused by the obligate biotrophic fungus Puccinia triticina eriks. is of widespread occur-rence accounting ~10 % yield loss annually (eversmeyer and Kramer 2000; Dean et al. 2012). Various elite lines of wheat were developed by introgression and pyramiding of several R-genes, identified in wheat and its related wild species, for durable rust resistance. These R-genes are gen-erally involved in pathogen recognition and programmed death of infected cells through hypersensitive response (Hr) that leads to complete or near-complete resistance. However, any mutation in R-genes might affect ability of the plant to recognize the pathogen, thus change orienta-tion of the plant from resistant to susceptible (Poland et al. 2009). also, mutagenic variations in the pathogen genome, prolific sporulation and efficient dissemination of the spores result in frequent breakdown of cultivar resistance (Park and Wellings 2011).
The biology of WrKY TFs and its mechanism of action has been a subject of intense research for years; however, functional analysis of these TFs in an important crop like wheat is rare (Wu et al. 2008). recent reports mentioned the identification and expression patterns of various WrKY TFs in wheat against Fusarium induced biotic stress and different phytohormones (Wu et al. 2008; Proietti et al. 2010; Bahrini et al. 2011; niu et al. 2012 and Zhu et al. 2013). In our lab, expression analysis of a TaWrKY1b was
carried out which showed 146 fold induction of the gene in resistant plants but only 12-fold induction of the gene in susceptible plants during leaf rust infection as compared to mock inoculated controls (Kumar et al. 2014). Inspite of different ongoing studies, the role of WrKY TFs in leaf rust infection is not yet established and reported. How-ever, it is predicted that wheat might contain much more WrKY TFs than rice, maize or Arabidopsis due to its large genome size, but most are yet to be disclosed (Zhu et al. 2013). Since only a low (5x) coverage of wheat genome sequence is available at present (Brenchley et al. 2012; http://www.wheatgenome.org) a quicker and complemen-tary approach to identify wheat genes is through expressed sequence tags (eST) analysis (Manickavelu et al. 2012; Olga et al. 2014) Therefore, the present study was initiated with the objective for transcriptome-wide identification of WrKY TFs in wheat and their comprehensive functional exploration with respect to the rust diseases in general and leaf rust in particular.
Materials and methods
In silico data mining of WrKY TFs and phylogenetic analysis
all available WrKY protein sequences of Oryza sativa (both japonica and indica), Sorghum bicolor, Hordeum vulgare, Zea mays, Brachypodium distachyon and Sac-charum officinalis were downloaded from Gramineae (Mochida et al. 2011) and GraSSIUS (Yilmaz et al. 2009) transcription factor databases. The retrieved sequences were searched for similarity with wheat eSTs using TBlaSTn at nCBI (http://www.ncbi.nlm.nih.gov) with an e-value cutoff of 10 (Zhu et al. 2013; niu et al. 2012; Xiaoming et al. 2014). The non redundant eSTs were selected, translated in silico using GenSCan (http://genes.mit.edu/GenSCan.html) and only the sequences containing conserved WrKY domains were opted for fur-ther characterization. BlaSTn was performed with their respective nucleic acid sequences to check for novelty. The WrKY protein sequences were aligned using ClC Genom-ics Workbench 6.5 (ClC bio, aarhus n, Denmark). a pipe-line describing the strategies used in this study for identifi-cation and functional characterization of the novel WrKY TFs is provided in Supplementary Fig. S1. Phylogenetic analysis of newly identified WrKY proteins in wheat was performed to study their evolutionary relationship with known Arabidopsis, Oryza sativa japonica, Brachypodium distachyon, Physcomitrella patens and Mucor circinel-loides based on multiple sequence alignments (MSa) and neighbor joining method using Molecular evolutionary Genetic analysis (MeGa5) software (Tamura et al. 2011).
Bootstrap analysis of 1,000 replicates was performed to provide confidence estimates for the tree topologies.
In silico characterization of identified WrKY TFs in wheat
The theoretical pI and molecular weight (Bjellqvist et al. 1994) was determined using expasy Server (http://us.expasy.org/tools/pi_tool.html), whereas, the grand aver-age of hydropathicity (GraVY) and aliphatic index was analyzed using Prot Param (Gasteiger et al. 2005). Kinase specific phosphorylation sites (Blom et al. 1999) and N-glycosylation potential sites (Gupta et al. 2004) were predicted by netPhos 2.0 Server (http://www.cbs.dtu.dk) and netnGlyc 1.0 Server (http://www.cbs.dtu.dk), respec-tively. Secondary structure for the novel TaWrKY proteins were predicted using ClC Genomics Workbench 6.5 and PSIPreD (Buchan et al. 2013). Motif scan (Marchler-Bauer et al. 2011) was used to determine different catalytic domains. additional conserved motifs outside the WrKY domain were identified using Multiple eM for Motif elici-tation (MeMe) version 4.9 (Bailey et al. 2009). The limits of minimum width, maximum width and maximum num-ber of motifs were specified as 6, 50 and 20, respectively, with any number of repetitions (Puranik et al. 2013). Trans-membrane helices and nuclear localization signals (nlS) present in the newly identified complete WrKY sequences were predicted using HMMTOP software (Garg et al. 2013) and nlStradamus (nguyen et al. 2009), respectively. Subcellular localization of these sequences was predicted using Wolf PSOrT software (Horton et al. 2007; Jia et al. 2013). Cutoff value of 0.6 and viterbi algorithm was used to determine the position and their corresponding amino acid sequences of the nlS.
rna isolation, SaGe library preparation and next generation sequencing
a pair of wheat near isogenic lines (nIls): HD2329 (a leaf rust susceptible phenotype) and HD2329 + Lr28 [resistant (nest Immune 0-0;) were used. The Lr28 gene was derived from Aegilops speltoides (Tauschii) and is effective against all pathotypes of the pathogen in India. Puccinia triticina pathotype 77-5, the most predominant and devastating leaf rust pathogen in all parts of the Indian subcontinent, was selected as the experimental pathogen (Bipinraj et al. 2011). The pathogen inoculum was prepared by mixing urediniospores of P. triticina pathotype 77-5 and talcum powder (ratio 1:1) and applied gently on leaves of the nIl pairs. Both plant types were also mock inoculated with only talcum powder and used as control. after inoculation plants were placed under high humidity of >90 % for 24 hpi in the dark to facilitate infection. Then the pots were transferred to the normal growth chamber [22 °C, day time;
14 °C, night time, relative humidity (80 %)] at national Phytotron Facility, Indian agriculture research Institute, new Delhi. leaf tissues from 15 seedlings, each of mock and pathogen inoculated nIls were taken at 24 h post inoc-ulation (hpi) and stored in liquid nitrogen. Total rna was isolated from leaf samples using TrI reaGenT (Molec-ular research Center, Inc., USa) as per manufacturer’s instruction. The rna isolation time-point was based on earlier studies on development of infection structures (Hu and rijkenberg 1998) and activation of resistant signaling genes (Coram et al. 2008; Singh et al. 2012). The integrity of the isolated rnas was confirmed using agilent Bioana-lyser 2100. Four serial analysis of gene expression (SaGe) libraries were prepared from the isolated rnas [coded as: (i) S-M: HD2329 mock inoculated, (ii) S-PI: HD2329 pathogen inoculated, (iii) r-M: HD2329 + Lr28 mock inoculated and (iv) r-PI: HD2329 + Lr28 pathogen inocu-lated] using SOliD–SaGe kit (applied Biosystems, Ca, USa) following the recommended protocol and sequenced using sequencing by oligonucleotide ligation and detection (SOliD) technique at Bay Zoltán Foundation of applied research, Institute of Plant Genomics, Human Biotech-nology and Bioenergy, Zagreb, Hungary. The sequences have been submitted to nCBI Sra061917 (BioSam-ple accession as SaMM01820702, SaMM01820703, SaMM01820704 and SaMM01820705).
Functional annotation of identified WrKY sequences
The identified WrKY TFs in wheat in the present study were mapped to the SOliD–SaGe reads of wheat tran-script assembly prepared earlier in our laboratory using mock and Puccinia triticina inoculated nIls (Singh et al. 2012). Mapping was carried out using the reference assem-bly function of ClC Genomics Workbench 6.5 considering the default parameters for short reads (Mismatch cost: 2; Insertion cost: 3; Deletion cost: 3 and Global alignment). Consensus sequences were extracted from each of the source SOliD–SaGe libraries and BlaSTn was per-formed with wheat eSTs. eST hits with minimum e-value and maximum identity in all four libraries were down-loaded and redundant eSTs were eliminated. Gene ontol-ogy (GO) of the identified eSTs was performed to cat-egorize them in terms of Biological processes, Molecular functions and Cellular components using Blast2GO (B2G) software (Conesa and Gotz 2008).
expression analysis of identified WrKY TFs in wheat under biotic stress
expression values for all the identified WrKY TFs in wheat were extracted from the four SOliD–SaGe data-set using ClC Genomics Workbench 6.5. The read counts
were determined and imported into Cytoscape software (Smoot et al. 2011) where differentially expressed tran-scripts were represented in the form of different nodes based on up- or down-regulation. The differential expres-sion of the identified WrKY transcripts among the wheat nIls in response to leaf rust pathogenesis was determined with log2 transformed values and represented through heat map, scatter plot and cluster analysis.
The expression patterns of the wheat WrKY genes were further investigated using Genevestigator software (Hruz et al. 2008). Six independent rust-related microarray-based experimental data were downloaded from nCBI-GeO (national Centre for Biotechnology Information—Gene expression Omnibus; http://www.ncbi.nlm.nih.gov/geo/) and uploaded onto the sample set. The experiment IDs included GSe6227, GSe9915, GSe31753, GSe31756, GSe31761 and GSe32151. all the identified WrKY genes obtained in the present study were uploaded in the gene selection panel. expression data were hierarchically clustered based on euclidean distance in sample with log2 transformed values.
Chromosomal localization
The newly identified 22 wheat WrKY sequences were mapped onto chromosomes of wheat from International Wheat Genome Sequencing Consortium (IWGSC), Sor-ghum, Brachypodium and rice whose genomes have been completely sequenced using Plant ensembl database by selecting e-value 10 as the cutoff criteria (Kersey et al. 2014). Synteny of wheat WRKY genes was also performed using wheat zapper tool and visualized using Circos online tool (alnemer et al. 2013).
Results
In silico identification of WrKY TFs in wheat and phylogenetic analysis
To obtain a robust dataset of wheat WrKY TFs, the redundant eSTs were removed and the presence of con-served WrKY domain was examined following the pipe-line mentioned in Supplementary Fig. S1. We were able to identify a total of 470 protein sequences (80 of rice, 94 of Brachypodium distachyon, four of Hordeum vulgare, 103 of Sorghum bicolor, 142 of Zea mays and 47 of Sac-charum officinalis) containing WrKY domains that were orthologous in wheat. BlaSTn with these 470 sequences to wheat eSTs provided 100 eSTs with WrKY domains. each of these wheat WRKY genes, identified in the present study, was assigned a unique identifier from TaWRKY 1 to 100 (Supplementary Table S1). Forty five of these 100
WrKY sequences matched with >95 % identity to previ-ously known wheat WRKY genes (TaWrKY1–45, Supple-mentary Table S1). The remaining 55 WrKY sequences had either no match with any known WrKY sequences in wheat or had a matching identity of <95 % with small query coverage. These 55 eSTs were deemed as novel WrKY sequences for wheat. Sequence analysis of the deduced TaWrKY novel sequences revealed 22 of them encoded for complete WrKY proteins with the Dna-binding region consisting of both WrKY domain and zinc-finger motif (TaWrKY46–67, Supplementary Table S1). Of the remain-ing 33 sequences, 17 sequences (TaWrKY68–84; Sup-plementary Table S1) were devoid of either the initiation or the termination codon; whereas, 16 sequences (TaW-rKY85–100; Supplementary Table S1) lacked the zinc-fin-ger motif. This suggests that about one-third of the identi-fied TaWRKY genes have become nonfunctional in wheat, which may be due to genome rearrangements associated with transposon activity, a phenomenon largely observed in wheat (Dubcovsky and Dvorak 2007). These 33 pseudo-genes, being incomplete, were excluded for further analy-sis in the present study. Therefore, only the complete 67 WrKY sequences, consisting of the 45 previously known and 22 newly identified, were considered for elaborate analysis.
Multiple sequence alignment of the 67 full length TaW-rKY proteins showed that most of them shared the highly conserved WrKYGQK domain; however, a few unusual domains were also observed (Supplementary Fig. S2, Supplementary Table S1). It was noted that all identified WrKY TF proteins in wheat consisted of a single WrKY domain signifying their affiliation to either class II or class III. The zinc-finger motifs were either C2H2 type (class II WrKY) or C2HC type (class III WrKY). Most mono-cotyledons, have only one WrKY domain, a phenomenon that demarcates the divergence of monocots from dicots, where class I WrKY proteins are mostly present (Tripathi et al. 2012). Though a few class I WrKY proteins with two WrKY domains had been identified in rice (ryu et al. 2006), Brachypodium (Tripathi et al. 2012) and wheat (Zhu et al. 2013). a phylogenetic tree constructed from the MSa of these 67 TaWrKY TF protein sequences classified them into six major clades, each in turn being composed of sev-eral members (Supplementary Fig. S3). Class IIc had the highest number of 30 members, followed by 13 in class IIIa, 12 in class IId, 6 in class IIIb, 5 in class IIa and 1 in class IIe. The high bootstrap values at most branch points indicate statistical significance of the phylogenetic tree and reflect derivation of possible homologous proteins with similar functions from common ancestors (Puranik et al. 2013).
To understand the evolutionary significance of wheat WrKY TF proteins, a comprehensive phylogenetic tree
was reconstructed from the 67 TaWrKY proteins along with 57 Brachypodium distachyon, 51 Arabidopsis thali-ana, 73 Oryza sativa japonica, 33 Physcomitrella patens and 3 Mucor circinelloides published WrKY sequences downloaded from nCBI (Fig. 1). The inclusion of moss and Mucor WrKY TF proteins restricted computing errors in branch length over long evolutionary periods (Tripathi et al. 2012). Primitive organisms, studied till date, mostly have class I WrKY proteins. Though in the present study, all moss WrKY TF proteins were classified into class IIb, IIc, IId and IIIa. The similarity between the n-terminal WrKY domains of class I and the class IIc WrKY pro-teins also suggests the probable evolution of the later from the class I WrKY proteins. The phylogenetic tree con-sisted of seven major clades. The clade IIc was the larg-est with 102 sequences followed by 55 sequences in class IIIa, 37 sequences in class IId, 34 sequences in class IIIb, 27 sequences in class IIb, 13 sequences in class IIa, eight sequences in class IIe and two sequences in classI. Mucor WrKY sequences formed a separate group comprising of the three Mucor WrKY protein sequences only. although the phylogenetic tree showed some divergences, as mem-bers of certain classes of TaWrKY TF proteins were found in separate clades. Such variation may be due to gene dupli-cation or recombination resulting in events like domain rearrangements. Similar divergences in phylogram were also reported for ZmWrKY proteins in maize (Wei et al. 2012). In similar studies, phylogenetic analysis divided 86 Brachypodium distachyon and 136 Zea mays WrKY TF sequences into eight and nine subgroups, respectively (Tripathi et al. 2012; Wei et al. 2012). It is noteworthy to mention that monocots have developed a large number of WrKY TFs than dicots probably because of positive selec-tion pressure during evolution for being exposed more to biotic and abiotic stresses. Of the completely sequenced monocot genomes, maize has 136, rice 78, Brachypodium 86 WrKY TFs compared to 71 in Arabidopsis thaliana and 83 in Solanum lycopersicum (Huang et al. 2012). although wheat genome is not yet completely sequenced, still we could identify 100 WrKY TFs from the transcriptome in the present study.
Characterization of novel wheat WrKY proteins
The 22 complete TaWrKY TFs were translated in sil-ico into all six possible coding frames. The signature WrKYGQK domain was found in 15 WrKY TF proteins (TaWrKY46–48, 50–51, 53, 57–59, 61 and 63–67) (Sup-plementary Table S1). Other unusual WrKY domains consisting of WKKYGQK was present in two WrKY TF proteins (TaWrKY49, -52); WrKYGKK was found in four WrKY TF proteins (TaWrKY54–56 and 60) and WrKYGeK was present in one WrKY TF protein
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(WrKY62). Based on the type of zinc-finger motif, 15 WrKY TF proteins consisted of C2H2 type zinc-finger motif (WrKY46–49, 51–57, 59–61 and 66) and, there-fore, belong to class II WrKY family. Further classifica-tion of these class II WrKY TF proteins revealed 11 of them (TaWrKY46, -49, 51–57, -60, -66) belong to class
IIc (C–X4–C–X22–23–HXH) and four (TaWrKY47–48, -59 and -61) belong to class IId (C–X5–C–X23–HXH). Class IIa (C–X5–C–X23–HXH), IIb (C–X5–C–X23–HXH) and IIe (C–X8–C–X22–HXH) were absent among these 22 TaW-rKY TF proteins. Seven WrKY proteins (TaWrKY50, -58, 62–65, and -67) contained C2HC type zinc-finger
Arabidopsis thaliana
Oryza sativa japonica
Brachypodium distachyon
Physcometrilla patens
Mucor circinelloides
Triticum aestivum
Fig. 1 Phylogenetic relationship of 67 TaWrKY proteins in wheat and their evolutionary relationship with 57 Brachypodium distachyon, 51 Arabidopsis, 73 Oryza sativa japonica, 33 Physcomitrella patens and 3 Mucor circinelloides published sequences
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motif and, therefore, belong to class III WrKY family. Further sub-grouping of these class III proteins resulted into five TaWrKY TF proteins (TaWrKY 58, 63–65, and 67) to class IIIa (C–X7–C–X23–HXC) and two TaW-rKY TF proteins to class IIIb (C–X6–9–C–X23–28–HXC) (Zhu et al. 2013).
N-glycosylation occurs in asparagine amino acid resi-dues present in asn/Xaa-Ser/Thr stretches where Xaa can be any amino acid except proline. This consensus tripeptide is referred as N-glycosylation sequon. any potential cross-ing the threshold of 0.5 represent a predicted glycosylated site. Glycosylated sites were present in all 22 novel WrKY TF proteins (Table 1). N-phosphorylation occurs in serine, threonine and tyrosine residues that affects a multitude of cellular signaling processes. any potential crossing the threshold of 0.5 represent a predicted phosphorylated site. Serine, tyrosine and threonine phosphorylated sites was present in 14 (49, -50, -52, -54, -55, -56, -58, -59, -60, -62, -63, -64, -65 and -67) TaWrKY TF proteins (Table 1).
The instability index is an estimator of protein stability in test tube. This technique assigns a weight value of insta-bility that can be used to determine an instability index.
Proteins with instability index values less than 40 are pre-dicted as stable and values above 40 indicate instability of proteins. The instability index of WrKY proteins ranged from 36.23 to 58.64 in the present study. It was found that TaWrKY 57 and -67 were only stable proteins and the rest 20 TaWrKY proteins were unstable (Supplementary Table S2). The aliphatic index (aI) occupied by aliphatic side chains (a, V, I and l) is considered as a positive fac-tor and is defined as the relative volume of a protein for the increase of thermal stability of globular proteins. aliphatic index, which is an indicator for increase in thermostabil-ity of globular proteins, was found to be high in all novel proteins (Supplementary Table S2), indicating that WrKY domains are stable at wide ranges of temperature. aliphatic index of WrKY proteins ranged from 37.88 to 76.6. TaW-rKY53 had the highest aliphatic index which indicates its thermal stability and flexible nature.
Gene annotation of the 22 WRKY genes, performed using OrF finder, revealed five TaWRKY genes (TaWRKY 4, - 8, -51, -57, -59, -60) possess protein coding regions in the reverse frame (Table 1). The longest protein consisted of 278 amino acids (TaWrKY63), the shortest protein
Table 1 Characterization of 22 novel TaWrKY TF proteins
had 122 amino acids (TaWrKY59 and TaWrKY66) and the average length of the deduced proteins was 193 amino acids. The GraVY value of WrKY proteins ranged from −1.180 to −0.175 indicating their hydrophilic nature. GraVY values normally range from ±2 where the positive values indicate hydrophobic nature of proteins and negative values indicate hydrophilic nature of proteins.
The various catalytic domains present in the 22 novel TaWrKY proteins were predicted using Motif scan (Sup-plementary Table S3). The WrKY domain, found on all the identified TaWrKY proteins, plays an important role in regulation of various physiological processes includ-ing biotic and abiotic stress. Several other domains like amidation (receptor recognition and signal transduction), Cyclic aMP phosphorylation (regulates glycogen, sugar and lipid metabolism in cell), Casein kinase2 phospho-rylation (phosphorylates acidic proteins such as casein), Myristolysation (membrane targeting and signal transduc-tion in plants in responses to environmental stress), ala-nine rich domain (stability to tertiary structure), Threonine rich domain (ligand-binding domain into the extracellular space), BrCa2 (defense gene transcription during plant immune responses), Protein kinase C (signal transduc-tion cascade), plant zinc cluster domain (associated with WrKY), methyl CpG binding site (regulation of devel-opmental processes) were found to be differentially pre-sent in these novel proteins. Besides the above mentioned domains, N-glycosylation, serine rich domain, histidine rich domain, octapeptide repeat, ascorbate cytosolic per-oxidase, glycine rich and tyrosine kinase were also present in some of the identified proteins. Secondary structure of the WrKY protein sequences showing alpha helix and beta sheets was also predicted using ClC Genomics Workbench 6.5 and PSIPreD (Supplementary Table S4; Supplemen-tary Fig. S4).
Identification of conserved motifs, transmembrane helices and subcellular localization
The 22 newly identified TaWrKY TF protein sequences were uploaded to MeMe analysis tool and 20 conserved motifs were identified (Supplementary Table S5). Motif 1 comprised of the WrKY domain that was present in all the newly identified TaWrKY sequences. Motif 2 was shared by 20 TaWrKY protein sequences except TaWrKY50 and 62. It was further noted that the class IIc proteins were comprised of motif 1, 2, 4, 6, 7, 8, 10, 11, 13, 14, 15, 16, 17 and 20; class IId shared motif 1, 2, 3, 4, 11 and 18; class IIIa proteins shared motif 1, 2, 4, 5, 6, 9, 12 and 16 whereas class IIIb shared motif 1 and 19 only. Such vari-ation of motif sequences among the TaWrKY TF proteins show their functional diversification in relation to different aspects of biological processes they regulate. The sites and
signature amino acid sequence composition of the identi-fied 20 conserved motifs is illustrated in Supplementary Fig. S5 and S6, respectively.
Transmembrane helices play an important role in study of membrane associated proteins especially with respect to cell signaling, energy transduction and transport. Such transmembrane helix was found only in TaWrKY67 pro-tein. Subcellular localization was predicted for all 22 newly identified WrKY TF protein sequences in wheat using WolF PSOrT program (Supplementary Table S6). TaWrKY49 and 52 were present in mitochondria whereas TaWrKY53, 54, 55 and 64 were localized in cytoplasm. The remaining 16 TaWrKY proteins were localized in the nucleus. nuclear localization signal (nlS) was found in nine (TaWrKY47–48, 53, 57–59, 61, 63–65) out of 22 TaWrKY proteins using nlStradamus software. These proteins are supposed to be transported by the import machinery of the cell (Supplementary Table S7).
Functional annotation of WRKY genes
after filtering the low quality sequences, adapter sequences and ambiguous nucleotides, the numbers of reads in S-M, S-PI, r-M and r-PI libraries were 12,247,862, 12,924,486, 6,780,611 and 6,227,541, respectively, and the average length of the sequences was found to be 28.4–29.5 nucleo-tide. The identified WrKY sequences when mapped with the wheat SOliD–SaGe transcript assembly and searched for consensus sequences with wheat eSTs using BlaSTn, we found 63, 81, 62 and 36 WrKY sequences provided BlaST hits from S-M, S-PI, r-M and r-PI libraries, respectively. GO terms were assigned for biological process (Fig. 2a), molecular function (Fig. 2b) and cellular compo-nent (Fig. 2c) to each of these sequences. The biological process category in S-M library category comprised of cel-lular nitrogen compound metabolic process and rna meta-bolic process; whereas S-PI library consisted of biological regulation, immune system process, response to stimulus, signaling, metabolic process, defense response, rna meta-bolic process, and cellular processes. This observation spec-ifies a shift in functions of the WrKY proteins in suscepti-ble wheat plants due to pathogenesis. The biological process category in r-M library consisted of genes with roles in stress response, rna metabolic process, cellular process, response to stimuli; whereas in r-PI library, genes having specific roles in metabolic processes, cellular processes and biogenesis were determined. In all the four libraries, molecular function consisted of genes with roles in Dna binding, transcription factor activity and protein binding. Cellular component consisted of TaWRKY genes distributed in plastid, membrane enclosed lumen and macromolecular complex in S-M library; whereas they were found to be dis-tributed in nucleus and plastid in the rest three libraries.
Mol Genet Genomics
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SOliD–SaGe data-based expression analysis of identified WrKY TFs in wheat under leaf rust stress
Sequence sizes of tags of SOliD–SaGe libraries before and after conversion to.clc format and summary of trimming
of tag sequences using ClC Genomics Workbench is men-tioned in Supplementary Table S8. To identify the differ-entially expressed TaWRKY genes in response to leaf rust pathogenesis, the identified WRKY genes were mapped to the reads from the four SOliD–SaGe libraries using
Fig. 2 Functional assignment of identified WRKY genes from different SaGe libraries based on GO categorization. Predicted role of WRKY genes provided in bar graph format. a Biological process; b molecular function; c cellular component
RNA metabolic process nucleic acid metabolic process
cellular macromolecule metabolic process nucleobase-containing compound metabolic process
macromolecule metabolic process biological_process metabolic process
primary metabolic process cellular nitrogen compound metabolic process
nitrogen compound metabolic process cellular metabolic process
cellular process response to stress
response to stimulus response to biotic stimulus
transport establishment of localization
localization
0 1 2 3 4 5 6 20 30 40 50 60
Number of sequences
S-M S-PI R-M R-PI
DNA binding
sequence-specific DNA binding transcription factor activity
ClC Genomics Workbench 6.5. The number of times each WrKY gene is represented in a particular library served as an index for estimation of their relative abundance (Supple-mentary Table S9). Pathogen infection highly up-regulated TaWRKY 27, 34, 56, 60 and 67 in the susceptible plants, TaWRKY3, 8, 18 and 44 in resistant plants; whereas TaW-RKY 20, 42 and 43 in both nIls. The highly down-regulated genes included TaWRKY3, 4, 37, 44 and 61 in the suscepti-ble plants and TaWRKY13, 25, 28 and 49 in both nIls. The up- and down-regulated genes were depicted in the form of different nodes using Cytoscape software (Fig. 3a–d). red and green colors indicated up- and down-regulated genes, respectively, in pairwise experiments involving S-M vs. S-PI, r-M vs. r-PI, S-M vs. r-M and S-PI vs. r-PI librar-ies. Size of the nodes indicated up- and down-regulation of the identified WRKY genes; larger the node size, higher was the up-regulation of the selected WRKY gene and vice versa.
Tag-based transcriptomics is an extension of SaGe in conjunction with next generation sequencing technologies, where the full length mrnas are not sequenced. Instead, tags of 27 bp are extracted from each transcript, sequenced and counted to measure the abundance of each transcript. To identify the expression of a represented gene by a given tag, the tags are often compared to a virtual library of tags that would have been extracted from an annotated genome or a set of eSTs (Supplementary file 2, Supplementary file 3, Supplementary file 4 and Supplementary file 5). Pair-wise experiments were conducted between the libraries using differentially expressed reads with log2 transformed values to obtain hierarchical feature clustering and were displayed as heat map (Fig. 4). The log2 transformed val-ues were particularly chosen since it equally treats differ-ential up-regulation and down-regulation and has a contin-uous mapping space. a total of differentially expressed 23
Fig. 3 Comparision of SaGe reads in four libraries using Cytoscape software. Red and green colors indicated up- and down-regulated genes, respectively, in pairwise experiments involving a S-M vs.
S-PI; b r-M vs. r-PI; c S-M vs. r-M; d S-PI vs. r-PI during leaf rust induced biotic stress. The particular WRKY gene involved is shown within the square (color figure online)
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tags could be extracted and their corresponding TaWRKY genes were determined. In case of susceptible nIls due to pathogen infection, maximum level of expression was observed in TaWRKY13, 18, 29, 34, 40 and 65; minimum level of expression was observed in TaWRKY10, 12, 15, 16, 20 and 21. Whereas, in resistant nIls due to patho-gen infection maximum level of expression was observed in TaWRKY 34 only; minimum level of expression was observed in TaWRKY10, 12, 17, 20, 21, 25, 29, 53, 65 and 66. It was found that two WRKY genes, TaWRKY56 and 60 represented the same tag (Supplementary Table S10). This might be due to the presence of conserved region between the two genes.
Tags, based on their differential expression pat-terns, were also clustered in each experiment (Fig. 5). Five clusters representing different TaWRKY genes were obtained; each cluster denotes the dynamic level of differential expression. The two WRKY genes, TaW-RKY56 and 60 were also clustered together in cluster-2 (Fig. 5b). Quantitative comparison of the differentially expressed TaWRKY genes during infection of wheat nIls was performed using two dimensional scatter plots showing Pearson correlation coefficients between the SaGe libraries (Fig. 6). Pearson correlation coefficients were 0.6, 0.52 and 0.42 for S-M vs. S-PI, r-M vs. r-PI and S-PI vs. r-PI libraries respectively. among all the three experiments, highest differences in expression of
TaWrKY genes between two libraries were in r-PI vs. S-PI. This suggests that the wheat nIls employ differ-ent sets of WrKY genes to counter leaf rust pathogen mediated infection. Volcano plot, another type of scatter plot, was constructed by plotting the negative log of the p value on the y-axis (usually base 10) where the x-axis is the log of the fold changes between the two condi-tions that changes in both directions (up and down) and appear equidistant from the center (Fig. 7, Supplemen-tary file 6). Data points with low p-values, indicating high significance, appeared towards the top of the plot. experiments between S-M vs. S-PI showed, TaWRKY15, 64 and 66 to have the lowest p-value and appeared towards the top of the plot (Fig. 7a). TaWRKY 10, 20 and 66 had low p-values and were hence present towards the top of the plot in the experiment r-M vs. r-PI (Fig. 7b). TaWRKY 10, 16 and 65 possessed lowest p-value and were, therefore, present at the top of plot in the experi-ment between S-PI vs. r-PI (Fig. 7c). Hence expression levels of these genes were considered to be statistically significant.
Microarray-based expression analysis of TaWRKY genes using GeO database
Microarray helps in rapid understanding of the patterns of gene expression. GeO and array express provide impor-tant information resources for gene discovery and func-tional characterization (Wei et al. 2012). Gene expression was performed for 14 TaWRKY genes whose probe set matched with the six rust-related experiments available at GeO database and the results were represented as heat map that was obtained through Genevestigator (Supplementary Fig. S7) (Meskauskiene et al. 2013; Hruz et al. 2008). The sample tool in conditional search toolset helps in visualiza-tion of gene expression across arrays from a pre-selected set of experiments through heat map. The details regarding the wheat lines used in the experiments, pathogens used and expression pattern of TaWrKY genes in the respective experiments have been cited in Table 2.
Chromosomal localisation of wheat WRKY genes
The orthologs from 22 wheat TaWRKY genes were mapped to Brachypodium, rice and Sorghum genomes and their corresponding chromosomal locations were pre-dicted (Supplementary Fig. S8, Supplementary Table S11, Supplementary Table S12). The genome sizes of grass family vary panoramically from 272 Mbp in Brachypo-dium to 400 Mbp in rice to 730 Mbp in Sorghum. Of the 22 novel TaWRKY genes identified in the present study, none were found to be located on wheat chromosome 1a, 1D, 2a, 2D, 3a, 3D, 4B, 6B, 6D, 7B and 7D; rice
Fig. 4 Heat map representation of differentially expressed TaWRKY genes from wheat nIls showing major changes in gene expression in SaGe libraries corresponding to S-PI, S-M, r-PI and r-M. Changes in expression levels are displayed from red (down-regulated) to pur-ple (up-regulated) as shown in the color gradient at the bottom right corner (color figure online)
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chromosomes 3, 10 and 11; Sorghum chromosomes 4 and 5. This information can be useful for cross species gene cloning and development of functional molecular markers for molecular breeding programs.
Discussion
Characterization and evolution of WrKY proteins in bread wheat
Fig. 5 Clustering of tags based on changes in expression pattern into 5 clusters (a–e)
Fig. 6 Quantitative comparison of differentially expressed TaWRKY genes during infection of wheat nIls using two dimensional scatter plots a S-M vs. S-PI; b r-M vs. r-PI; c S-PI vs. r-PI. WRKY genes with equal expression values are on the diagonal identity line, with higher expression values further away from the origin. Points below
the identity line represent WRKY genes with higher expression from the library plotted on x-axis and points above the diagonal represent WRKY genes with higher expression from the library plotted on the y-axis. Further away the point is from the diagonal, the larger is its difference in expression between the two libraries
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WrKY TFs play a pivotal role in regulating defense in plants. Some act as negative regulators whereas others act as positive regulators of plant defense by associating with distinct regu-latory complexes. apart from pathogen defense, WrKY TFs are involved in regulation of several physiochemical processes hence controlling the expression of an array of genes in biotic and abiotic stress conditions. Presently research on WrKY TFs of wheat with regard to leaf rust pathogenesis is very scanty. Fifteen WrKY TFs of wheat have been isolated; their expression profiling were studied and were classified on the basis of the corresponding orthologous sequence of rice by Wu et al. (2008). Forty-three putative TaWRKY genes have been identified and classified by niu et al. (2012) which included two multiple stress induced genes TaWRKY2 and 19. among the 43 TaWRKY genes, 26 TaWRKY genes encoded complete WrKY domain. Out of these 26 genes, 6 proteins belonged to class I each containing 2 WrKY domains. Thirteen WrKY proteins had C2H2 zinc fingers and were classified as class
II member. Whereas, seven WrKY proteins had C2HC zinc finger and comprised of class III family. Similarly, Zhu et al. (2013) identified a set of 115 wheat WRKY genes using pro-tein sequences of Arabidopsis and rice. among these 115 WRKY genes, 23 TaWRKY genes contained WrKY domain but lacked zinc-finger motif and were not included for fur-ther study. Out of the remaining 92 genes, 34 sequences included start and stop codons and constituted complete cod-ing sequences. The other 58 TaWrKY sequences, represent-ing partial coding sequences, were also included in their study. In the present study the partial coding 33 sequences were not considered for detail analysis and were discarded. among the 67 sequences, 22 TaWrKY sequences were considered as novel since they had no match with the sequences previously identified by Zhu et al. (2013). This may be due to better data mining of WrKY TFs using all protein sequences of Oryza sativa (both japonica and indica), Sorghum bicolor, Hordeum vulgare, Zea mays, Brachypodium distachyon and Saccharum
Fig. 7 Volcano plot of differentially expressed transcripts from wheat nIls a S-M vs. S-PI; b r-M vs. r-PI; c S-PI vs. r-PI. Plot-ting points resulted in two regions of interest in the plot: points found towards the top of the plot that are far to either the left- or the right-
hand side and represent values that display large magnitude fold changes as well as high statistical significance (hence being towards the top)
Mol Genet Genomics
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Tabl
e 2
Mic
roar
ray
base
d ex
pres
sion
ana
lysi
s of
TaW
RK
Y g
enes
iden
tified
usi
ng G
eO
dat
abas
e
Ge
O e
xper
imen
t ID
Whe
at li
nes
used
Path
ogen
use
de
xpre
ssio
n pa
ttern
of
TaW
RK
Y g
enes
GSe
6227
nIl
s of
Jup
atec
o w
ith a
nd
with
out L
r34
gene
Tha
tche
r ru
st a
nd m
ock
inoc
ulat
ion
P. tr
itic
ana
TaW
RK
Y56
sho
wed
hig
h ex
pres
sion
inte
nsity
in J
upat
eco_
lr3
4 (s
usce
ptib
le),
moc
k in
ocul
ated
bas
al a
nd
dist
al le
af e
xper
imen
ts a
nd T
aWR
KY
76 s
how
ed h
igh
inte
nsity
in c
ase
of b
asal
leav
es o
f su
scep
tible
pl
ants
. Dif
fere
ntia
l exp
ress
ion
was
not
dis
tinct
ly s
een
in T
aWR
KY
4, -
10, -
96, -
39 a
nd -
35
GSe
9915
Tha
tche
r m
ock
inoc
ulat
ed
Tha
tche
r- L
r1 a
nd 3
4 pa
thog
en in
ocul
ated
P. tr
itic
ana
TaW
RK
Y15
and
76
show
ed h
igh
expr
essi
on in
tens
ity in
Tha
tche
r m
ock
inoc
ulat
ed a
nd th
eir
expr
essi
on
inte
nsity
red
uced
in T
hatc
her-
Lr3
4 pa
thog
en in
ocul
ated
. TaW
RK
Y56
in (
Tha
tche
r m
ock
vs P
. tri
tici
na
inoc
ulat
ed a
nd T
hatc
her-
Lr1
exp
ress
ion
leve
l was
hig
h an
d ex
pres
sion
red
uced
in c
ase
of T
hatc
her-
Lr3
4 in
ocul
ated
with
P. t
riti
cina
. Dif
fere
ntia
l exp
ress
ion
was
not
dis
tinct
ly s
een
in T
aWR
KY
4, -
10, -
96, -
39
and
-35
GSe
3175
3W
heat
Yr5
isol
ines
trea
ted
with
P.s
. tri
tici
PST
-100
ov
er a
tim
e co
urse
of
6,
12, 2
4 an
d 48
h;
P.s.
trit
ici P
ST-1
00Ta
WR
KY
56 w
as s
een
to h
ave
high
est s
igna
l int
ensi
ty in
sus
cept
ible
var
iety
inoc
ulat
ed 6
h p
ost i
nocu
latio
n an
d in
res
t of
the
expe
rim
enta
l con
ditio
ns i.
e. in
moc
k an
d pa
thog
en in
ocul
ated
in b
oth
susc
eptib
le a
nd
resi
stan
t one
the
expr
essi
on w
as d
own-
regu
late
d. e
xpre
ssio
n w
as a
lso
obse
rved
in T
aWR
KY
15, -
17, -
76
and
-81.
Dif
fere
ntia
l exp
ress
ion
was
not
dis
tinct
ly s
een
in T
aWR
KY
4, -
10, -
96, -
39 a
nd -
35
GSe
3175
6W
heat
Yr3
9 an
d Y
r39
(alp
owa)
gen
otyp
esP.
s. tr
itic
i PST
-78
In s
usce
ptib
le-
path
ogen
inoc
ulat
ed 1
2 an
d 24
h, T
aWR
KY
15, -
17, -
76 w
ere
up-r
egul
ated
whe
reas
in
susc
eptib
le-p
atho
gen
inoc
ulat
ed 4
8 h
post
inoc
ulat
ion,
exp
ress
ion
leve
l was
see
n to
be
dow
n-re
gula
ted.
In
pat
hoge
n in
ocul
ated
in r
esis
tant
Yr3
9, d
iffe
rent
ial e
xpre
ssio
n w
as o
bser
ved
in T
aWR
KY
15, -
17, a
nd
-76.
Dif
fere
ntia
l exp
ress
ion
was
not
dis
tinct
ly s
een
in T
aWR
KY
4, -
10, -
96, -
39 a
nd -
35
GSe
3176
1A
voce
t6/Y
r1av
irul
ent a
nd v
irul
ent w
heat
yel
-lo
w r
ust (
Puc
cini
a st
riif
orm
is
f.sp.
trit
ici)
TaW
RK
Y15
, -17
exh
ibite
d di
ffer
entia
l exp
ress
ion.
Dif
fere
ntia
l exp
ress
ion
was
not
dis
tinct
ly s
een
in T
aW-
RK
Y4,
-10
, -96
, -39
and
-35
GSe
3215
1Si
x in
depe
nden
t lr1
tr
ansg
enic
line
s sa
mpl
ed
befo
re in
ocul
atio
n (0
h)
and
at 6
and
24
h
avir
ulen
t P. t
riti
cina
rac
e C
CD
SD
iffe
rent
ial e
xpre
ssio
n w
as o
bser
ved
in T
aWR
KY
15, -
17, a
nd -
95 i.
e. u
p-re
gula
ted
in p
atho
gen
inoc
ulat
ed
in r
esis
tant
var
iety
6 h
pos
t ino
cula
tion
and
dow
n-re
gula
ted
in r
est e
xper
imen
tal c
ondi
tions
of
the
expe
ri-
men
t. D
iffe
rent
ial e
xpre
ssio
n w
as n
ot d
istin
ctly
see
n in
TaW
RK
Y4,
-10
, -96
, -39
and
-35
Mol Genet Genomics
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officinalis available at Gramineae (Mochida et al. 2011) and GraSSIUS (Yilmaz et al. 2009) databases.
In a recent study, Okay et al. (2014) identified and charac-terized 160 TaWrKY proteins based on sequence similarity, motif varieties, and evolutionary relationship. They obtained 187 TaWrKY proteins initially by retrieving the 111 amino acid sequences already found in Plant Transcription Fac-tor Database, Peking University and 76 sequences found in GenBank. Twenty-seven TaWrKY sequences were com-mon to both and, therefore, the total amino acid sequences were filtered to 160. BlaST was performed for the 22 novel WrKY sequences obtained in this study with the identified 160 TaWrKY proteins mentioned by Okay et al. 2014. none of the sequences identified in the present study matched with the 160 TaWrKY proteins. Hence, the 22 TaWrKY proteins were novel and not identified before. TaWrKY proteins iden-tified by niu et al. (2012), Zhu et al. (2013) and Okay et al. (2014) belonged to class I, class II and class III WrKY. The identified proteins in the present study signified their affilia-tion to only class II and class III WrKY. Phylogenetic analy-sis revealed the orthologous and co-orthologous WRKY genes in wheat providing insight into their relationship with other plants. Okay et al. (2014) aligned 160 TaWrKY sequences and identified 13 different WrKY motifs (WrKYGQK, WrKYGeK, WrKYGQe, WlKYGQK, WrKYGKK, lrKYGPK, WrnYGQn, WKKYGQK, WrKDGQK, WSKYGQK, WTKYGQK, GrKYGeK and WMKYGQK). In our study, WKKYGQK, WrKYGKK, WrKYGeK motifs were found to be present apart from WrKYGQK motif. The WrKY TFs are abundant in plants, with 74 mem-bers identified in Arabidopsis and 109 members in rice. It can be assumed that wheat contains much more WrKY members than rice and Arabidopsis due to its large genome size. Iden-tification of all WRKY genes in bread wheat genome will be delayed till the complete genome sequences are obtained.
expression profiling of TaWRKY genes
The WrKY TF family is known to regulate a range of bio-logical processes, with their most well-characterized roles in plant defense response. TaWRKY45 is involved in the defense response to Fusarium attack, and it appears to play a posi-tive role in the resistance to Fusarium head blight (Bahrini et al. 2011). This gene may also regulate expression of genes related to various disease resistance and stress response path-ways in wheat. Thus over-expression of TaWRKY45 confers enhanced resistance towards Fusarium graminearum (Bah-rini et al. 2011). TaWRKY53 has been identified and charac-terized recently as a gene that is differentially up-regulated during wheat resistance response to the aphid, Diuraphis noxia (Botha et al. 2010). In vitro analysis of the gene dem-onstrated the ability of TaWRKY78 to bind to a region of the wPr4e promoter thus regulating PR4 genes and suggesting
their role in plant defense (Proietti et al. 2010). WrKY pro-teins are associated with regulation of biotic and abiotic stress responses; but how they respond to cereal rust pathogens has never been explored at the molecular level. Full length cDna of TaWrKY1B was obtained from a wheat cultivar HD2329 derivative containing leaf rust resistance gene Lr28 by Kumar et al. (2014). Infection with a virulent race of leaf rust fungus resulted in 146 fold induction of the gene in resistant plants, but only 12 fold in the susceptible plants as compared to mock inoculated controls. In the present tag-based expression study, experiments were conducted between S-M vs S-PI; r-M vs r-PI and S-PI vs r-PI. In S-M vs S-PI, TaWRKY10, 12, 16, 21 and 59 were found to be down-regulated as evident from their negative fold change values. Meanwhile, TaWRKY5, 14, 17, 29, 34, 55, 64 and 66 were up-regulated as evident from their positive fold change values. Similarly TaWRKY15, 34, 59 and 64 were up-regulated; TaWRKY29 and 55 were down-regulated in experiment conducted between r-M and r-PI library. TaWRKY15, 16, 41 and 59 were up-regulated; TaW-RKY12, 13, 17, 18, 29, 40, 53, 55, 56, 60, 64, 65 and 66 were down-regulated in the experiment conducted between S-PI and r-PI library. TaWRKY10, 15, 17 and 56 were identified to be common in both tag-based and microarray-based differ-ential expression analysis and could be representing rust spe-cific WRKY genes. a comprehensive gene expression analy-sis revealed differential expression of wheat WrKY TFs in response to leaf rust pathogenesis. Microarray-based data mining also supplemented their putative functions in response to rust diseases. The expression analysis depicted in this study provides a skeleton framework for future functional studies including construction of transgenic plants (liu et al. 2014).
In this study using transcriptomic approach we have predicted WrKY TF proteins that regulate gene expres-sion in response to leaf rust disease and other develop-mental functions in wheat which has not been reported or studied before. In the absence of complete wheat genomic resources and limited information available through ran-dom published studies and sequences available at Tran-scription Factor Databases, in silico data mining of tran-scriptomic data would represent an effective approach to identify WRKY genes and their putative functions. even though detection of all WRKY genes and their complete sequences was a limitation, we were able to get differ-entially expressed WRKY genes indicating their role in leaf rust. GO annotation of these identified WRKY genes reveal their possible biological and molecular roles which is essential to know for the plant’s high value as a cereal crop and its varied adaptability. The underlying molecu-lar mechanism of function of most WRKY genes in wheat remain poorly understood and has become a scientific hotspot for extensive exploration in recent years. Func-tional and bioinformatics-based exploration of wheat WRKY genes and their chromosomal localization in related
Mol Genet Genomics
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monocots might provide subsets of candidate target genes to improve agronomic traits related to biotic stress tol-erance and will also contribute for similar research in other TFs in wheat and other monocots of agricultural significance.
Availability Sequence read archives: Sra061917 under BioSample accessions for four SOliD–SaGe libraries: SaMn01820702, SaMn01820703, SaMn01820704 and SaMn01820705.
Acknowledgments This work was supported by Depart-ment of Biotechnology, Government of India (Grant no. BT/Pr6037/aGr/02/308/05), BTISnet SubDIC (BT/BI/04/065/04), Department of agriculture, Government of Jharkhand (5/B.K.V/Misc/12/2001) and Coe-TeQIP-II (Grant no. nPIU/TeQIP II/FIn/31/158). l. S. is grateful to Department of Science and Technology-InSPIre (Fellowship/2011/318) and D. K. to Council of Scientific and Industrial research [9/554 (0026) 2010-eMr-I] for Ph. D. fellowships.
Conflict of interest authors declare no conflicts of interest.
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