Identification of transcription factors in tomato ...

South African Journal of Botany 106 (2016) 165–173

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Identification of transcription factors in tomato, potentially related to early blight resistance at invasion in host tissue, using microarray expression profiling Priti Upadhyay a,b,c,⁎, Showkat Hussain Ganie a, Ashutosh Rai b, Major Singh b, Brajesh Sinha c a b c

University of Delhi, North Campus, Delhi, India Indian Institute of Vegetable Research Varanasi, Uttar Pradesh, India Banaras Hindu University Varanasi, Uttar Pradesh, India

a r t i c l e

i n f o

Article history: Received 23 October 2015 Received in revised form 8 May 2016 Accepted 1 July 2016 Available online 20 July 2016 Edited by Z-H Chen Keywords: Tomato Early blight Affymetrix Microarray Resistance Transcription factor

a b s t r a c t Tomato early blight is an important threat due to its capacity to reduce the production in all major tomato producing areas. Molecular mechanisms underlying resistance to the causal organism are not well known. Therefore, we aimed to study tomato – Alternaria solani system to search the transcription factors and pathways which, are responsible for resistance to this fungi using, affymetrix gene chip for tomato. three hundred ninety five transcription factors were found to be differentially expressed at 24 h after inoculation with A. solani in the resistant genotype, EC-520,061, of tomato. Also, Zinc Finger Proteins, Ribosomal binding unit S4 and Auxin responsive transcription factors were found to play significant role in resistance. Their expression has enhanced the pathogenesis related proteins and also other proteins as well, which, have direct role in stopping the penetration of mycelia in host plant. © 2016 SAAB. Published by Elsevier B.V. All rights reserved.

1. Introduction Early blight (EB) of tomato caused by Alternaria solani, a fungi, is economically the most important disease of tomatoes in USA, Australia, Israel, UK and India where, significant reductions in yield (35 to 78%) have been observed (Datar and Mayee, 1981; Jones et al., 1993). Whereas survey reports confirm that no resistant genotype for EB has been found yet, in different screening experiments few genotypes belonging to S. hybrochaites and S. arcanum have shown moderate to high resistance; however (Chaerani et al., 2007; Upadhyay et al., 2009). Tomato accessions possessing resistance to this microbe mostly belong to wild types for example, S. arcanum, S. peruvianum, S. neorickii and S. chilense. Accessions of S. habrochaites were found to possess both, susceptibility and resistance to EB. Lines resulting from crosses of tomato with these wild species do not have satisfying crop qualities. EB disease control is therefore, mainly attempted with chemical protective agents. However, such agents do not always prevent the infestation of fruits thus, severe losses can still occur. Moreover, longterm effects of these chemicals e.g. fungicides on humans are still

⁎ Corresponding author at: University of Delhi, North Campus, Delhi, India. E-mail address: [email protected] (P. Upadhyay).

http://dx.doi.org/10.1016/j.sajb.2016.07.001 0254-6299/© 2016 SAAB. Published by Elsevier B.V. All rights reserved.

unknown though, they may contribute toward medicament resistance; with life-threatening consequences. Further, these fungicides may cause mutations by reprogramming normal genes or permanently silencing them, the effects may therefore, last for several generations (Weinhold, 2006). EB resistance is a quantitatively governed genetic trait (Foolad et al., 2002), thereby making selection more difficult; compared to qualitative traits (Moody et al., 2003; Brown and Caligari, 2011). In order to understand genetic control of EB resistance and to facilitate its introgression in tomato, molecular markers and QTL analysis have been carried out. With discoveries of new technologies, researches in this field have progressed with the use of functional genomics tools to ascertain the mechanism of resistance to EB. Searching and determining the function of a set of resistance genes, helps us understand the pathways leading to the resistant reaction in a host plant. Transcription factor (TF) is a molecule that controls the activity of a gene by determining whether the gene is up or down regulated. TFs control when, where, and how efficiently, RNA polymerases function and the proteins get translated from these transcribed RNAs. There are reports of genome-wide identification and phylogenetic analyses of the AP2/ERF TFs in plant genomes including Arabidopsis, rice, soybean, grapevine and tomato (Nakano et al., 2006; Zhang et al., 2008; Licausi et al., 2010; Sharma et al., 2010). Plants try to defend themselves against a wide array of microbes, this interaction may, or may not be

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P. Upadhyay et al. / South African Journal of Botany 106 (2016) 165–173

pathogenic. The activation of defense responses in plants is initiated by, host recognition of primary pathogen-derived elicitors (Yang et al., 1997; Kim et al., 2002). Recognition of pathogen elicitors by plant cell receptors, activates signal transduction pathways which may involve: protein phosphorylation, ion fluxes, reactive oxygen species (ROS), secondary endogenous signals and the expression of TFs, and defense genes (Yang et al., 1997; Park et al., 2005). Responses of plants against microbes are regulated by multiple signaling pathways with, a significant overlap between gene expressions. The present study was aimed to see the transcription factors differentially expressed in resistant tomato accession at early stage of A. solani infection and observe the role of various TFs, in susceptible and resistant accessions. 2. Materials and Methods 2.1. Plant material Plant materials utilized for this study were variety CO-3 and the accession EC-520,061, as susceptible and resistant respectively. The basis of this categorisation was the performance of the above mentioned genotypes against A. solani, during a screening experiment conducted earlier (Upadhyay et al., 2009). Seeds of the variety and the accession were provided by Indian Institute of Vegetable Research, Varanasi, Uttar Pradesh, India. The plants were grown, in pots, in a growth chamber under temperature–controlled condition (25 °C). 2.1.1. Inoculum Inoculum utilized for implanting the host (tomato) plants consisted of the Varanasi isolate of A. solani that, was isolated from tomato leaves showing EB symptoms. The culture was propagated on Potato Dextrose Agar (PDA) in 90-mm petri dishes. These dishes were incubated at 25 °C under a cool-white fluorescent diurnal light with a 12 h photoperiod for 15 d. After fifteen days, culture was scraped and macerated together with sterile pestle and mortar. Although the culture was free from conidia, thickening of conidiogenous hyphae and chlamydospore like structures were observed. Before the formation of these structures, cultures did not possess their usual aggressiveness and the potential for implantation. One and half month old tomato plants were implanted by spraying a suspension solution, 157 cfuml−1 spore load, of A. solani; under control condition. The implanted plants, in pots, were kept at 28 °C and more than 95% humidity, to create proper epiphytotic conditions. Plants sprayed with sterile distilled water were treated as control. After 24 hai of implantation of plants with A. solani when, leaves were not curled and the only symptom detected was - initial appearance of black spots, leaves were sampled for RNA isolation. Control samples were also collected for RNA isolation and immediately stored in liquid nitrogen at − 80 °C. While germination of spores start and reaches its maximum level between 6 and 12 h of inoculation, interaction with plant cells begin at the stage when penetration starts. This stage is very important as it indicates the time when the spores of A. solani start penetrating the leaf tissue (Dita et al., 2007) besides, it is one of the earliest cellular stages where, changes in the host tissues start in response to the fungi. 2.1.2. Microarray Experiment RNA isolation was done using TRIZOL reagent (Invitrogen, Carlsbad, CA) according to manufacturer's instructions. The RNA was quantified using Nanodrop spectrophotometer and its quality was checked on 1% agarose gel containing formaldehyde. Double stranded cDNA synthesis, in vitro transcription to synthesize biotin labeled cRNA, purification and fragmentation of cRNA, and hybridization of arrays were performed according to Affymetrix technical manual. The Affymetrix GeneChip, Tomato Genome Array, contains 10,038 probe sets representing about 4600 unigenes. Hybridized

chips were washed, stained and scanned using, GeneChip scanner to generate the CEL files. These CEL files were imported into GeneSpring GX v12 (Agilent Technologies). Signal intensities were recorded for all probe sets. The data has been deposited at NCBI (http://www.ncbi.nlm.nih.gov), with, an accession number - GSE71428. Signal intensities were normalized using, Robust Multi-array Average (RMA) algorithm (Irizarry et al., 2003). The Principal Component Analysis (PCA), GeneSpring GX 10.1, established the close location of all three biological replicates. A high correlation coefficient was observed among the three replicated samples indicating, less genetic background noise. It shows that the molecular fluctuations inherent in samples that cause random switching of genes on and off are very less (Hana and Weissman, 2011). To correct the variability in the normalized expression values, probe sets with coefficient of variation b 50% were retained while, rest were discarded. 2.1.3. Functional annotation of the differentially expressed probe sets Tables of significant transcripts were generated at p values b0.05 and fold change (FC) values N 2.0. For annotation of transcripts an annotated probe file was referred, that, was generated at Cornell University, USA: (ted.bti.cornell.edu/TFGD/array/Affy_probe_annotation.xls) and NCBI website. Among those significantly differentially expressed transcripts, we selected the transcripts, which functions as regulators of transcription. 2.2. Screening of TFs from microarray data Tomato TFs analyzed in this experiment have been described in the TF database (http://planttfdb.cbi.pku.edu.cn/). According to the annotation of Affymetrix genome microarray, we screened for TF genes that were differentially induced or repressed after A. solani implantation in CO-3 and EC-520,061 with, a FC value N 2.0 and a P-value b 0.05(Suppl Table 1). The results have been shown as a (http://bioinformatics.psb. ugent.be/webtools/Venn/ website). Further probe filtering for TF genes that were significantly induced by A. solani or constitutively expressed in the resistant accession, RHT was performed with the FC tool in GeneSpring - GX 11.5. 2.2.1. Quantitative Real Time PCR validation Total RNA was extracted from leaves of the two genotypes: CO-3 and EC-520,061 after 24 h of implantation, in three biological replications. First strand cDNA for each sample was synthesized using, SuperscriptTMIII first-strand synthesis system for RT- PCR (Invitrogen, Carlsbad, CA, USA), following manufacturer's instructions. Primers for quantitative real-time RT-PCR were designed using, web based primer designing tool from IDT (http://eu.idtdna.com/Scitools/Applications/ Primerquest/default.aspx). The sequences of all primers are enlisted in Table 1. Quantitative real time PCR was performed in three biological replications using, SYBR Green (Qiagen, USA) fluorescence dye and, analyzed by iQ-SYBR Green Supermix (Bio-Rad, CA, USA) according to the manufacturer's protocols on iQ5 thermo cycler (Bio-Rad, CA, USA) with, iQ5Optical System Software version 2.0 (Bio-Rad, CA, USA). To normalize the target gene expression, differences between the CT of the target gene and the CT of Actin (constitutive control) for the respective template were calculated (ΔCT value). To calculate FCs in gene expression, the ΔCT value was calculated as follows: ΔCT = CT (target gene)–CT (constitutive control gene). Relative transcript levels were calculated as: 1000 × 2–ΔCT. 3. Results 3.1. Potential regulator genes associate with EB resistance For understanding the mechanism behind host responses to A. solani, in the resistant and susceptible genotypes EC-520,061 and


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Table 1 Primers used in Quantitative PCR study for pathogen responsive transcripts in tomato. S. No.

Description

Primer Sequence

Start

Stop

Length

Tm

GC%

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

ZAP St Forward Primer ZAP St Reverse Primer ZPT2–13 Forward Primer ZPT2–13 Reverse Primer ZFP Forward Primer ZFP Reverse Primer TAF15b Forward Primer TAF15b Reverse Primer ERF-3 Forward Primer ERF-3 Reverse Primer Cyt K Forward Primer Cyt K Reverse Primer

GAGGCTCTTACATCACCAAGAT (Sense) CTGGACAAAGGGTAAGCGAT (AntiSense) GGCCATCGAACGAGTCATAAA (Sense) ACCTAAAGCCTGACCCATAGA (AntiSense) ATATACGGCTCCACCTCCTAA (Sense) CTGCTTCTACGCTTCCTCTAATAA (AntiSense) CAGTGGCCTTGGAGCATAAA (Sense) GCTGCAGAAGGATCTTCGTATG (AntiSense) GGGTACACTGAACACCACAA (Sense) GGTAGAGTGCAGGACTGTAAATC (AntiSense) CGGATTACAGAGCCAAACTATCT (Sense) TAACCATGAGTGCCCATCAC (AntiSense)

98 178 227 335 182 250 135 202 189 263 772 852

120 198 248 355 203 274 155 224 203 286 795 872

22 20 21 21 21 24 20 22 20 23 23 20

62 62 62 62 62 62 63 63 62 62 62 62

45.5 50.0 47.6 47.6 47.6 41.7 50.0 50.0 50.0 47.8 43.5 50.0

CO-3, we analyzed the expression profiles of transcripts represented on the Affymetrix Tomato Genome Array Gene Chip. Leaves were sampled for RNA isolation after 24 h of implantation of plants with A. solani. This stage is very important as it indicates the time when the mycelia of A. solani start penetrating the leaf tissue (Dita et al., 2007) besides, it is one of the earliest cellular stages where, changes in the host tissues start in response to the fungi (Isaac, 1991). Genes showing at least 2FC were considered as differentially expressed. The results confirmed that 8.88% of the transcripts belonged to molecular function category. Fig. 1 (pie chart) shows its graphical representation. The chip hybridization percentage was observed to be: 85.33, 86.50, 54.43 and 74.66, for EB susceptible control chip, EB susceptible treated chip, EB resistant control chip and EB resistant treated chip; respectively. Total numbers of up and down regulated transcripts in case of susceptible genotype were 3478 and 2663, respectively. Similarly, numbers of up and down regulated transcripts in resistant genotype were 3442 and 2695, respectively. We tried to elucidate the expression pattern and functions of transcription factors in this host – microbe interaction model i.e. tomato A. solani. The chips were therefore re-analyzed and, we found 395 transcripts of the molecular function category. (Supp Table 1). Of the 395 transcripts, we synthesized the primers of six transcripts for qRT validation (Table 1). A total of ten transcripts (Table 2) which showed significant up or down regulation in both resistant and susceptible genotypes are taken for co-expression analysis and schematically presented in Fig. 2. Since this stage is a start of the biochemical changes

in the plant cell against the pathogen thus, we have observed that all regulated transcription factors were significantly expressed in the resistant genotype where as, their expressions in the susceptible genotype, varies. Of the 395 transcription factors/ regulator transcripts, numbers of significantly up regulated and down regulated transcripts in the resistant genotype were 102 and 36, respectively. In case of the susceptible genotype, the numbers of significantly up regulated transcripts were 22 while, 36 down regulated transcripts were recorded. In both, resistant and susceptible genotypes, five common up regulated transcripts were observed; as well. A Venn diagram was also prepared and the result is being pictorially presented as Fig. 3 (http://bioinformatics.psb.ugent.be/webtools/Venn/ website). The diagram shows 134 transcripts from resistant and 51 transcripts from susceptible genotype to be differentially expressed at the given time stage (24 hai) of tomato - A. solani interaction. However, only four transcripts were commonly expressed in both the genotypes (resistant and susceptible). 3.1.1. Validation of selected transcripts with qPCR To independently confirm the results of microarray analyses, we performed quantitative real-time reverse transcriptase, PCR (qPCR), on A. solani implanted plants in three separate biological experiments, at 24 h post implantation. Results from qPCR (Fig. 4), confirmed the differential expression revealed by the microarray data, for all selected genes that were tested. Since the expression profiles of many genes

Fig. 1. Pie chart showing the fraction (%) of entities belonging to different sub categories of molecular function.

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Table 2 Co expression analysis of significantly up and down regulated transcripts with their FC values in both, resistant and susceptible genotypes of tomato. S.N.

Probe ID

TF

FC_Resistant

FC_Susceptible

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Les.5467.1.S1_at|101261864 LesAffx.62334.1.S1_at|101261116 Les.5114.1.S1_at|100736521 Les.88.1.S1_at |544196 LesAffx.12514.1.S1_at|101249431 Les.3575.1.S1_at|544042 LesAffx.735.1.S1_at|101268787 LesAffx.60966.2.S1_at|100037497 Les.3502.1.S1_at|543684 LesAffx.22100.1.S1_at|101259859

Growth-regulating factor 2-like Transcription factor bHLH135-like TCP transcription factor 17 Dem protein Homeobox-leucine zipper protein ATHB-52-like Pti5 Probable WRKY transcription factor 33-like GRAS1 protein Auxin-regulated dual specificity cytosolic kinase Heat stress transcription factor A-4b-like

−2.03 −3.17 −2.17 −2.76 −4.55 4.55 2.10 2.62 10.16 6.49

−5.16 −3.27 −2.45 −2.23 −2.01 4.72 3.34 3.33 3.24 2.48

obtained by qPCR and microarray analysis were in accordance, this array platform was found to be suitable for a high-throughput genome-wide analysis. This study of interaction between tomato and A. solani at early stage mainly focuses on the role of transcription factors and their expression in resistant and susceptible genotypes, and reveals quite good variability in their expression levels. 4. Discussion A resistance response of tomato during its interaction with A. solani is a quantitatively governed trait that depends upon external, internal and genetic factors. Additionally, the stages of interaction also play a vital role as responses such as: secretion of antibiotics and enzymes to degrade the fungal mycelia and, starting of necrosis to stop the growth of hyphae in the host tissue etc., must be perceived at a very early stage. Thus, we have selected the 24hai stage for our studies since, it is the early stage of tomato – A. solani interaction; for microarray expression profiling. Several families of TFs have been reported to be involved in plant defense against pathogens. (Desveaux et al., 2005; Wang et al., 2015). The Ethylene Responsive Transcription factor belongs to the largest family TF families i. e. AP2/ ERF. These ERFs interact with the GCC box (GCCGCC) promoter to alter the expression of genes either positively of negatively (Solano et al., 1998; Zhang et al., 2015). Our study revealed quite a high level of expression of ERF-3 (29.44), in the resistant genotype, its expression in the susceptible genotype is not significant; however. Moffat et al. (2012) have reported that, ERF5 and ERF6 played important role in defense against Botrytis cinerea through their significant expression in Arabidopsis. ERFs are involved in signaling pathways and defense against necrotrophic pathogens is generally mediated

through signaling. So we can conclude that they is a role of this TF for resistance against the A. solani (a necrotrophic pathogen) in EC520,061. In susceptible accession CO-3, its expression in not significant. As mentioned above ERF bind to GCC box, which is promoter for many Jasmonic Acids, and pathogenesis related proteins that have a direct role in resistance or susceptibility. Thus there is more binding of ERF-3 to GCC box in EC-520,061 as compared to CO-3 and consequently, the GCC box will promote more Jasmonic acids and PR proteins in EC520,061 to impart resistance (Brown et al., 2003) & vice-versa for the susceptibility of CO-3. Some members of ERF transcription factors work as enhancer for GCC box (Ohme-Takagi and Shinshi, 1995) and some as repressor (Fujimoto et al., 2000; Kazan, 2006). But the mechanism, which we can predict here that ERF-3 has worked as enhancer as expression of transcript for pathogenesis, related protein PR-1 has been increased (Upadhyay et al. 2014) in resistant accession while it has no significant role in susceptibility. It has been seen that Pti4, a transcription factor of ERF family has a positive role in enhancing the resistance for P. syringae (Gu et al., 2002). This study suggested that phosphorylation of the Pti4 protein by the Pto kinase enhanced the ability of Pti4 to activate expression of GCC-box PR genes in tomato and thus impart resistant against P. syringae. In this study, also the same mechanism may act behind the resistant reaction. In the present study we report that, six ERFs have induced expression which may be a reason for high resistance level of EC-520,061 i.e. resistant accession against A. solani. This result is in accordance to the results found by Velivelli et al. (2015). The workers observed significant expression of ERF-3 in mycorrhized potato plantlets, challenged with Pseudomonas. Moreover, Velivelli et al. (2015) found the same pattern of expression when they co-inoculated potato plantlets with Pseudomonas and R. solani. The role of ERF transcription factors has

Fig. 2. Bar graph showing co-expressed transcripts inresistant and susceptible genotypes of tomato interacting with A. solani (24 h after inoculation).


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Fig. 3. Venn diagram of differentially expressed transcripts having changes more tahn 2 folds.

been established and it reveals that when pathogen attacks a plant it gives a signal to activate ERF which further mediates the expression of other defense related proteins. Major role of ERF proteins is in post- translational control as observed by Oñate-Sánchez and Singh (2002). It has been observed that plants expressing Pti4 (which is activated by ERF as a consequence of pathogen interaction with plant) showed significant resistance for virulent fungal. This interaction resulted in the induction of the SAdependent PR genes PR1, PR2, PR5, and GST1 (Gu et al., 2002). Upadhyay et al. (2014) has shown that PR proteins have a role for resistance in EC520,061 as they have significantly up regulated. The Fig. 5 below has shown the clear picture how different stresses stimulate ERF transcription factor and its role in enhancing the expression of other intermediates, which finally provide resistance to the plant for concerned stress.

Zinc finger transcription factors or ZF-TFs, are transcription factors composed of a zinc finger-binding domain and any of a variety of TF effector-domains that, exert their modulatory effect in the vicinity of any sequence to which the protein domain binds (Gommans et al., 2005). It has role in defense response which has been revealed by numerous studies (Oh et al., 2005; Gupta et al., 2012). In our study, it has been observed that at 24 h after implantation, i.e. at penetration of host tissue by the mycelium (Dita et al., 2007), two zinc finger proteins (ZFP): ZFP 12, ZF-2 were found significantly up regulated. Fold change values in resistant accession was 6.2 for Zinc finger protein ZAT12 and for ZF-2 it was 6.7. These domains have ability to bind zinc ions and that's why they have been named as such (Ponting et al., 1996). There is an evidence that zinc finger transcription factor is involved in plantpathogen interaction involves from cotton (Gossypium hirsutum)

Fig. 4. Bar graph showing qRT PCR expression patterns of six transcription factors in tomato genotypes after 24 h of inoculation.

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Fig. 5. Outline of some of the stress responses and/or signals linked to ERF transcription factors; Adopted from Singh et al. (2002).

GhZFP1 (Guo et al., 2009) with enhanced salt tolerance. The possible mechanism is not yet known but assumptions have been made that these accelerate the regulatory protein that might be transferred from the nucleus to the cytoplasm and facilitate the formation of higher

order complexes by interacting with these regulators and carry the complex into the nucleus to activate regulatory pathways under stress. This study also showed that zinc finger proteins have been found to be involved in the synthesis of salicylic acids and peroxidases (Davletova

Fig. 6. Pictorial presentation of lysosome pathway.


et al., 2005) and role of these entities are already established in the disease resistance/ tolerance in plants (Seevers et al., 1971; Almagro et al., 2009). There are reports that this TF has positive involvement for resistance in the rice against bacterial leaf blight through a JAdependent defense pathway (卿邓汉 et al., 2012). Here also it can be assumed that accession with high expression of ZFPs i.e. EC-520,061 show resistance and other CO-3 will be susceptible. Kang et al. (2005) have studied these TFs and found that these have been involved in protein- protein interaction and generate hypersensitive responses. The hypersensitive response generated due to these TFs may cause necrosis and hindrance in the penetration and proliferation of the fungal mycelia in host tissue and thus, create tolerance. There is need to further study for more confirmed conclusion. During any stress condition, cell metabolism is accelerated and, transcription and translational activities increase. The ribosomal protein, S4, plays an important role in translational accuracy (Piepersberwg et al., 1980; Anthony and Liebman, 1995). In the present case, ribosomal protein S4, was observed to be significantly up regulated with FC value 9.2 in the implanted resistant accession EC-520,061 and in susceptible accession it has insignificant value. Another 50S ribosomal protein L2 is significantly up regulated in resistant accession with FC value 7.2 while it is insignificantly expressed in susceptible. Hence it may be inferred that S4 and L2 plays role in resistance of EC-520,061 and has no role in susceptibility in CO-3. We putatively assume that a regulatory network is involved in EC-520,061 its defense response against A. solani since, translation of many proteins start along with fungal implantation in comparison to the normal healthy state, while it has insignificant expression in susceptible accession CO-3 (Rawat et al., 2012; Nagaraj et al., 2015). In a study of genome-wide investigation of Soybean using sRNA-seq, degradome-seq and transcriptome-Seq, it has been revealed that ribosomal protein S4 gene was down regulated suggesting that its interaction with other target transcripts plays a key role in SMV infection during Soybean mosaic virus Infection (Chen et al., 2016). In

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our study, it has up regulation and its efficiency in transcription of other defense related genes, might resulted in resistance reaction of EC-520,061. MYELO BLAST (MYB) transcription factor family has many TFs, among which MYB 30 is well known for its role in plant defense response. It is a positive regulator of horizontal resistance (HR) to bacteria (Froidure et al., 2010). Recently it has been revealed that MYB30 is ubiquitinated and degraded by MYB30 –interacting E-3 ligase 1, when the pathogen is absent (Marino et al., 2013). In the present study on tomato - A. solani interaction, six MYB transcription factors were found significantly up regulated (FC values: 10.97, 8.7, 8.1, 5.5, 5.2 and 3.5) {please see Suppl Table 1} and four were insignificantly expressed in the resistant accession EC-520,061. Its expression is not significant in the susceptible line CO-3. There are evidences, which show that MYB Transcription Factor Induces resistance against fungal pathogen in plant. One such example of this is enhanced resistance against leaf blights in maize by induced by MYB Transcription Factor. Biosynthesis of 3-deoxyanthocyanidins requires a MYB transcription factor. Induced expression of MYB TFs cause the acceleration of 3-Deoxyanthocyanidins and consequently resistance in maize for leaf blight. (Ibraheem et al., 2015). Some MYB transcription factors have been shown to play an important role in salicylic acid (SA) biogenesis. The study of Seo and Park (2010) has shown that SA biosynthesis was elevated in the activation tagging myb96-1d line, and the endogenous concentration of SA was seven fold higher in the activation-tagging myb96-1d line. The salicylic acid has a defined role in pathogen resistance (Dennis et al., 1996; Durner et al., 1997). Other TF like MADS transcription factors were also observed, showing significantly down expression in the resistant genotype. Basically MADS transcription factor is known to be involved in growth related activities for example regulation of flower development, regulation of circadian rhythm, response to temperature stimulus and

Fig. 7. Schematic presentation of major steps of Apoptosis pathway involved in expression of defense related genes.

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vernalization response (Salathia et al., 2006; Pajoro et al., 2014). Since it is mostly insignificantly down regulated in both susceptible and resistant accession, it may be concluded that it has no major role to play here. Since there are chains of reactions for showing resistance response, the higher level of fold change shows, the increase in their activity and consequently formation of more ingredients of resistance. These TFs are mainly involved in different RNA metabolism and other defense signaling pathways. As the present study is focused mainly on the role of transcription factors in EB resistance in tomato, we tried to find out the pathways in which these participate, using web based tool of KEGG pathways database (www.genome.jp/kegg/). Many interesting pathways were found among which, is the Lysosome pathway. The molecule homeobox-leucine zipper protein ATHB-40-like (LesAffx.51158.1.S1_at, FC − 3.5 in resistant treated genotype) was identified as Cathepsins which, is involved in lysosome pathway (Fig. 6). Another entity identified was, cysteine proteinase 3-like (Les.4217.1.S1_at FC 5.9 in resistant treated genotype), has involvement in apoptosis of cells (Fig. 7). Lysosome has role in autophagy, while apoptosis is programmed cell death. Both pathways are very important during any stress whether, biotic or abiotic. Autophagy is an evolutionary conserved pathway of vacuolar degradation of cytoplasmic constituents (Khan and Hemalatha, 2015). It has been seen that autophagy can play dual roles of “Prosurvival” and “Prodeath” during pathogen infection in plants (Janawad et al., 2012). The pathogens infecting plants can be categorized as biotrophic and nectrotrophic pathogens. Nectrotrophic pathogens kill the host cells while, biotrophs rely on the host for survival. It has been reported that nectrotrophic fungal pathogen, Botrytis cinerea, infects Arabidopsis and accelerates autophagy (Bi et al., 2014). Contrarily, in a study on human glioma cell lines and parvovirus H-1, it has been observed that, lysosomal pathway is not directly related to the viral entry process instead, it results from a dramatic down regulation of cytosolic cysteine cathepsin inhibitors which, sensitize the cells to otherwise, non-lethal cathepsin release (Di Piazza et al., 2007). In conclusion, it can be presumed that, the identified TFs play a crucial role in imparting resistance to the tomato cultivar EC-520,061. These TFs can potentially activate or repress genes through cis-acting sequences that, respond to A. solani. ERF transcription factor family, ribosomal protein TF family and Zinc finger transcription factors which might have role in resistance Our study provides information on the regulatory genes and the pathways involved in tomato– A. solani pathosystem which, will help the researchers and breeders to develop new genetic tools, by coupling genome-wide approaches with reverse-genetic approaches, for breeding early blight resistant tomato. Further, this study has given basic information to understand the role of specific TFs which, should be further investigated by determining the complete network of genes that are altered in specific, gain- or loss-of-functional mutants. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.sajb.2016.07.001. Acknowledgement This research was a part of the project “NPTC-Functional Genomics Project (Code: 3013)” at Indian Institute of Vegetable Research, Varanasi, India. Priti Upadhyay was financially supported with UGC research fellowship by Banaras Hindu University, Varanasi, India. References Almagro, L., Gómez Ros, L.V., Belchi-Navarro, S., Bru, R., Ros Barceló, A., Pedreño, M.A., 2009. Class III peroxidases in plant defense reactions. Journal of Experimental Botany 60, 377–390. Anthony, R.A., Liebman, S.W., 1995. Alterations in ribosomal protein RPS28 can diversely affect translational accuracy in Saccharomyces cerevisiae. Genetics 140, 1247–1258.

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