The Plant Journal (2016) 86, 35–49

doi: 10.1111/tpj.13149

Elucidation of defense-related signaling responses to spot blotch infection in bread wheat (Triticum aestivum L.) Ranabir Sahu1, Murali Sharaff1, Maitree Pradhan1, Avinash Sethi1, Tirthankar Bandyopadhyay1, Vinod K. Mishra2, Ramesh Chand3, Apurba K. Chowdhury4, Arun K. Joshi2,5 and Shree P. Pandey1,* 1 Department of Biological Sciences, Indian Institute of Science Education and Research – Kolkata, Mohanpur Campus, Mohanpur 741246, West Bengal, India, 2 Department of Genetics and Plant Breeding, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 22105, India, 3 Department of Plant Pathology, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 22105, India, 4 Uttar Banga Krishi Viswavidyalaya, Cooch Behar, Varanasi 736165, West Bengal, India, and 5 The International Maize and Wheat Improvement Center (CIMMYT) South Asia Office, Singh Durbar Plaza Marg, Kathmandu, Nepal Received 11 September 2015; revised 13 February 2016; accepted 15 February 2016; published online 1 March 2016. *For correspondence (e-mail [email protected]).

SUMMARY Spot blotch disease, caused by Bipolaris sorokiniana, is an important threat to wheat, causing an annual loss of ~17%. Under epidemic conditions, these losses may be 100%, yet the molecular responses of wheat to spot blotch remain almost uncharacterized. Moreover, defense-related phytohormone signaling genes have been poorly characterized in wheat. Here, we have identified 18 central components of salicylic acid (SA), jasmonic acid (JA), ethylene (ET), and enhanced disease susceptibility 1 (EDS1) signaling pathways as well as the genes of the phenylpropanoid pathway in wheat. In time-course experiments, we characterized the reprogramming of expression of these pathways in two contrasting genotypes: Yangmai #6 (resistant to spot blotch) and Sonalika (susceptible to spot blotch). We further evaluated the performance of a population of recombinant inbred lines (RILs) by crossing Yangmai#6 and Sonalika (parents) and subsequent selfing to F10 under field conditions in trials at multiple locations. We characterized the reprogramming of defense-related signaling in these RILs as a consequence of spot blotch attack. During resistance to spot blotch attack, wheat strongly elicits SA signaling (SA biogenesis as well as the NPR1-dependent signaling pathway), along with WRKY33 transcription factor, followed by an enhanced expression of phenylpropanoid pathway genes. These may lead to accumulation of phenolics-based defense metabolites that may render resistance against spot blotch. JA signaling may synergistically contribute to the resistance. Failure to elicit SA (and possibly JA) signaling may lead to susceptibility against spot blotch infection in wheat. Keywords: Triticum aestivum, spot blotch, salicylic acid, wheat, Bipolaris sorokiniana, plant defense, gene annotation, phytohormone signaling, phenolic acids, recombinant inbred line.

INTRODUCTION Wheat domestication was one of the pivotal factors in shaping modern human civilization (Marcussen et al., 2014). As agriculture evolved, polyploid wheat varieties took a central stage in cultivation. Grown across the globe in >215 million hectares, wheat forms a critical ‘staff of life’ as it is food for 2.5 billion people in 89 countries of the world. Wheat ranks first as source of protein and second as source of calories in low- and middle-income countries. Accounting for a global trade worth of US$50 billion each © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd

year, wheat’s current global output amount to >680 million tones (Curtis and Halford, 2014). By 2050, the demand for wheat across the world is expected to increase by >60%; whereas 30% reduction in wheat output is forecasted if current varieties and practices are followed (Wheat CRP annual report 2013: http://repository.cimmyt.org/xmlui/bitstream/handle/10883/4016/99544.pdf). Further, agro-ecological habitats of wheat invite several abiotic and biotic stresses. One of the most important threats to wheat in 35

36 Ranabir Sahu et al. warm humid regions of the world is the spot blotch disease, caused by Bipolaris sorokiniana (Dubin and Rajaram, 1996; Arseniuk, 2013). B. sorokiniana, a hemibiotrophic fungal pathogen, is a critical threat to wheat in the warm and humid climates where temperatures remain above 15°C during the coolest month of the cropping season (Saari and Prescott, 1975; Saari, 1998). Average yield loss due to spot blotch is estimated to be ~17% (Saari, 1998); under epidemic situation losses as high as 100% have been encountered (Duveiller and Garcia Altamirano, 2000). Although spot blotch disease may originate from soil and air, infected seeds are considered the most important source of dissemination of the pathogen (Pandey et al., 2005). A positive correlation between chlorophyll content and resistance to spot blotch at higher temperature is suggested (Rosyara et al., 2009). Similarly, the ‘stay green’ trait in wheat that delays the senescence has been linked to spot blotch resistance (Joshi et al., 2007). Although few QTLs have been associated with resistance to spot blotch in wheat (Joshi et al., 2004; Sharma et al., 2007; Kumar et al., 2009, 2010), the molecular basis for the defenses and signaling pathways that underlie the interaction of B. sorokiniana with the resistant or susceptible wheat host remains unknown. Phytohormones act as signal molecules that are essential for regulation of plant development, growth, reproduction and defense. Jasmonic acid (JA), salicylic acid (SA) and ethylene (ET) play important roles in regulation of plant’s immune responses (Pieterse et al., 2012). The network that regulates effective plant responses depend profoundly on the action of these phytohormones, which often interact synergistically and/or antagonistically to fine tune defenses against pathogens (Pandey et al., 2010; Pieterse et al., 2012). Compelling evidence for their key roles have primarily come from studies in model systems such as Arabidopsis (Dodds and Rathjen, 2010; Pieterse et al., 2012), whereas their overall role when crop plants are infected by pathogen under field conditions remains understudied. Moreover, the genes involved in biogenesis and signaling of SA, JA or ET in wheat are still largely not annotated and the identity of the signaling pathways recruited against the attack of B. sorokiniana in wheat indeed remains completely unknown. In a recent study, transcriptomic and metabolite profiling of wheat during septoria blotch infection revealed both a biphasic interaction of pathogen with plant immunity and changes in gene expression for JA biosynthesis as well as enhanced SA accumulation during necrotrophic phase on infection, thus reinforcing the hypothesis of involvement of these phytohormones in wheat defense responses (Rudd et al., 2015). During biotic stresses, the elicitation of phytohormone signaling is often coupled with or followed by reprogramming of plant metabolism to recruit metabolites that may

be defensive in nature (Santino et al., 2013). The phenylpropanoid pathway forms one of the important components of metabolism reprogrammed during pathogen attack (Dixon et al., 2002). Phenolic acids, which function as antimicrobial, anti-herbivory compounds and antioxidants, have an important role in plant defense (Dixon and Paiva, 1995; Wuyts et al., 2006). The production of phenolic compounds at the site of infection results in pathogen inhibition. Phenylalanine ammonia lyase (PAL) is a key enzyme in the phenylpropanoid biosynthesis pathway, whose expression is reprogrammed as a result of pathogen infection, as well as in response to defense-related phytohormones such as SA, JA, ET and methyl-jasmonate (Wang et al., 2002; Dempsey et al., 2011; Santino et al., 2013). Two PAL genes, Wpalt1 and 2, were reported in wheat; expression of Wpalt1 was tissue specific, and was induced in leaves of a wheat line resistant to the Puccinia graminis f. sp. Tritici (Li et al., 2001), indicating a role in defense response of wheat. It is believed that SA signaling provides plant resistance to biotrophic pathogens, whereas necrotrophic resistance is controlled by JA- and ET-signaling pathways (Pieterse et al., 2009). Shikimate pathway-derived chorismate mostly initiates the synthesis of pathogen-induced SA (Dempsey et al., 2011); alternate sources may also be deployed (Chen et al., 2009). JA is synthesized from a-linolenic acid, which is further oxygenated by lipoxygenases (LOX) to produce13(s)-hydroperoxy linolenic acid (13-HPOT), which is catalyzed by allene oxide synthase (AOS) and allene oxide cyclase (AOC) to produce JA (Vick and Zimmerman, 1984). ET is derived from methionine, which in the first step is converted to S-adenosyl methionine (AdoMet) by AdoMet synthetase. AdoMet is further catalyzed to 1-amminocyclopropane-1-carboxylic acid (ACC) by ACC synthase (ACS). ACC is oxidized by ACC oxidase (ACO) to produce ET. The identification, annotation and characterization of genes of these families in wheat during the attack of spot blotch attack remain totally absent. In this study, we have annotated key genes of signaling and defense-related pathways in wheat using an integrative biology approach. Furthermore, we present a set of experiments on the molecular characterization of the spot blotch–wheat interaction from the perspective of defense signaling. Here, we have characterized the temporal dynamics of gene expression in ‘resistant’ and ‘susceptible’ wheat genotypes during spot blotch infection. We have attempted to decipher the reprogramming of expression of SA, JA, ET, enhanced disease susceptibility 1 (EDS1) and phenylpropanoid pathway genes within 24 h after infection, followed by extensive metabolite characterization of SA and several other phenolic acids in a population of recombinant inbred lines (RIL) to understand possible signaling mechanisms during wheat–spot blotch interaction.

© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

Spot blotch-induced defense signaling in bread wheat 37 whereas the hyphae spread to new cells within 24 hpi (Figure 1). Therefore, it may be safely hypothesized that the signaling events involved in early stages of pathogenesis may happen within the first 24 hpi. The pathogen colonizes the host tissue by 24 hpi; hyphae produce conidiophores that emerge out of the host, giving rise to a succession of conidia by 4 days (Figure 1). In order to study molecular responses of wheat host to B. sorokiniana

RESULTS Interaction of B. sorokiniana and wheat B. sorokiniana is an opportunistic wheat fungal pathogen that can survive as a saprophyte (necrotroph) and reproduce asexually (Acharya et al., 2011). The conidia are able to fully germinate within 4 hours post infection (hpi) on the host, followed by appressoria formation (8 hpi),

Figure 1. Interaction of B. sorokiniana with wheat. (a) Summary of disease cycle of B. sorokiniana on wheat. (b) Fully grown fungal culture on potato dextrose agar medium. Bipolar germination of spores that invade the host through stomata is shown in (c1) and (c2). Development of conidiophores and conidia leading to sporulation on flag leaves of susceptible host are visible in (d1–d3). Necrotic lesions showing restricted pathogen development on the resistant genotype (Yangmai #6; e1 and e2) and typical disease symptoms on flag leaves of susceptible genotype (Sonalika; f1–f4), where the spots merge to form blotches by 7 dpi are illustrated.

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© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

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38 Ranabir Sahu et al. pathogen, we used two contrasting genotypes, Yangmai #6, a highly resistant, and Sonalika, a highly susceptible cultivar (Eisa et al., 2013; Kumar et al., 2013). Under continuous moisture and average temperatures above 18°C, pathogenic spots were visible on the leaf surface by 4 days post inoculation (dpi) that progressed to form blotches by 7 dpi on the susceptible cultivar, Sonalika (Figure 1). Conversely, the spread of pathogen across the host tissue was severely restricted in the resistant genotype (Yangmai #6), which produced only pinpointed curtailed spots (Figure 1). Identification of signaling and defense-related genes of wheat We identified 18 key signaling and defense-related genes of SA [ICS1, NPR1-3 (an NPR1-like gene), PR1.1 and PR3], JA [MYC2, LOX2, AOS, OPR3, and PDF2.2], ET (ACS6 and ACO4), EDS [EDS1, PAD4 and FMO1], and the phenylpropanoid (PAL1, PAL2 and PAL3) pathways as well as the homolog of the WRKY33 transcription factor (Table S1 and Figures S1–S3). Pairwise alignments of nucleotide sequences of most of the wheat genes, to the corresponding Arabidopsis baits, showed 16–98% coverage with 64– 75% similarity (Figure S4). The identity scores varied between 36–79% and 58–100% coverage were recorded when wheat and Arabidopsis peptides were compared (Table S2 and Figure S4). Predicted FMO1 peptide contained the characteristic FMO-like domain (Figure S3) and showed 37% identity with 98% coverage; however fulllength coding DNA sequences (CDS) of wheat FMO1 showed little identity to the corresponding Arabidopsis nucleotide sequence. Similarly, the peptide sequence of PAD4 contained the characteristic lipase 3 domain and showed maximum identity of 36% (at 84% coverage) with Arabidopsis PAD4 peptide sequences; however no significant identity was noticed in the nucleotide sequences of the two species. Transcriptional reprogramming of phytohormone signaling and phenylpropanoid pathway during spot blotch attack in wheat Salicylic acid, jasmonic acid, ethylene, and EDS1 are the four major signaling pathways associated with plant defenses against phytopathogens (Pieterse et al., 2009). In order to understand which of these may be recruited in defenses against spot blotch in wheat, we studied the changes in accumulation of transcripts of genes of these signaling pathways in time-course experiments in the two genotypes [Yangmai #6 (resistant to spot blotch) and Sonalika (susceptible) respectively; Figures 2 and S5 and Table S3]. Both genotypes showed contrasting expression patterns in all the analyzed genes of SA pathway [the ICS1 (central component of SA biogenesis), NPR1-like master regulator, and the two PR genes that served as markers for pathogenesis], which specifically were elicited only in

resistant genotype upon spot blotch infection (Figure 2). All the genes of SA signaling were clearly up regulated as soon as 8 hpi in the resistant Yangmai #6 (repeated measures ANOVA; Fisher’s LSD; P ≤ 0.05; Table S3). A three-fold induction in the expression of ICS1 and NPR1like transcripts were visible within 8 hpi (Figure 2). Similarly, an 8–15-fold elicitation of PR transcripts was clearly evident at 48 hpi (Figure 2). In contrast with Yangmai #6, no significant elicitation was recorded in the expression of most of the SA pathway genes in the susceptible Sonalika (Figure 2 and Table S3). Studying the elicitation dynamics of MYC2 transcription factor [that regulates the expression of LOX2 (Pozo et al., 2008)], LOX2 (catalyzes the first committed step of JA biosynthesis), AOS, OPR3 (JA biogenesis genes) and PDF2.2 [marker of JA pathway (Kazan and Manners, 2008)] indicated that JA signaling may be modulated upon spot blotch attack to help plants confer resistance (Figure 2; repeated measures ANOVA; Fisher’s LSD; P ≤ 0.05; Table S3). A three-fold elicitation in the MYC2 transcript was evident. This corroborated with ~7-fold elicitation in levels of LOX2 and 3–5-fold elevation in transcript levels of AOS2 and OPR3 genes within 12 hpi in Yangmai #6 (Figure 2). A >5-fold increase in transcript abundance of PDF2.2 in the resistant cultivar further confirmed the elicitation of JA signaling during spot blotch attack (Figure 2). Interestingly, some alterations in OPR3 and PDF2.2 transcript levels were also seen after 24 hpi in Sonalika (Figure 2). ACS6 and ACO4 are the two important components of ET biogenesis (Figure 2). Transcripts of ACS6 were >4-fold elicited whereas ACO4 were >2-fold increased within 12 hpi in Yangmai #6. Interestingly, both the genes were similarly elicited (four- and two-fold respectively, over 0 hpi controls) in the Sonalika but their elicitation was delayed to 24 hpi (Figure 2). During pathogen attack, EDS1 and PAD4 form a complex to elicit defense signaling in Arabidopsis (Feys et al., 2001; Pandey et al., 2010); FMO1 is a positive regulator of the EDS1-signaling pathway [(Bartsch et al., 2006); (Figure S5)]. A 3-fold) only in Yangmai #6 during 4–48 hpi (Figure 2). Expression of PAL1 was also enhanced in 12–24 hpi, whereas PAL2 increased between 12 and 48 hpi in Yangmai #6 (Figure 2). We evaluated the dynamics of change in expression of the wheat homolog to the Arabidopsis WRKY33 that regulates plant defense to necrotrophic pathogens in Arabidopsis (Zheng et al., 2006; Birkenbihl et al., 2012). A clear elicitation was noticed for WRKY33 transcripts at 8–12 hpi in Yangmai #6 that was significantly higher from the accumulation levels in Sonalika (Figure 2; repeated measures ANOVA; Fisher’s LSD; P ≤ 0.05; Table S3). Accumulation dynamics of SA show its elicitation specifically in resistant genotype Next, we evaluated the accumulation dynamics of SA in the Yangmai#6 and Sonalika in time-course experiments. As an additional control, we also evaluated the accumulation of SA in a third genotype, CIANO T79 [CIANO T79 is universally susceptible to spot blotch in all environments evaluated until now across the world (Duveiller and Garcia Altamirano, 2000)]. Significant increase in SA levels was recorded in Yangmai #6 rapidly within 8 hpi (ANOVA, P ≤ 0.05; Figure 3 and Table S4) that increased by threefold in 12–24 hpi (Table S4; ANOVA, P ≤ 0.01; Figure 3). Conversely, no significant changes in SA levels were recorded in either of the susceptible genotypes, Sonalika or CIANO T79 (Figure 3 and Table S4). Metabolomic reprogramming of phenolics during spot blotch infection in wheat Transcriptional reprogramming of PALs (Figure 2) indicated recruitment of phenylpropanoid pathway-based metabolites by wheat during defense against spot blotch infection. To confirm this hypothesis, we next investigated how the accumulation patterns of both, total free and bound phenolics changed in resistant (Yangmai #6) as compared with the susceptible (Sonalika and CIANO T79) genotypes in time-course studies (Figures 3 and S6 and Table S4). Significant increases in both the total free phenolics as well as the total bound phenolics were clearly observed in Yangmai #6 by 12–24 hpi (ANOVA P ≤ 0.01; Figure 3). No changes were noticed in either Sonalika or CIANO T79, the two widely accepted susceptible genotypes. Of the nine free phenolics-based metabolites studied, chlorogenic acid was found to be most abundant; highly significant increases in chlorogenic acid levels were recorded 24 hpi in Yangmai #6 as compared with both the susceptible cultivars (Table S4; ANOVA P ≤ 0.01; Figure 3). Similarly, syringic acid and 4-hydroxybenzoic acid showed 1.8- and 2-fold increases at 24 hpi of spot blotch infection in the resistant genotype, in comparison with the susceptible strain

(Table S4; ANOVA P ≤ 0.01; Figure 3). Also, significant changes in caffeic acid levels were recorded by 12 hpi in Yangmai #6 in comparison with susceptible genotypes (Table S4; Figure 3; ANOVA P ≤ 0.001). Minor increase in vanillic acid accumulation was seen in the resistant cultivar, whereas no significant differences were noticed amongst Yangmai #6 and Sonalika or Sonalika and CIANO T79 genotypes in gallic acid accumulation (Figure S6). Performance of RILs confirms that resistance to spot blotch depends on SA and induced defenses Results from the contrasting genotypes indicated that elicitation of SA and phenolic acids may be involved in resistance of wheat against spot blotch disease. To further corroborate this hypothesis, we studied the RILs of Yangmai #6 9 Sonalika in three geographical locations for their disease harboring ability and other traits (methods). Timecourse experiments were further conducted in field conditions and samples were collected at 0, 8, 12 and 24 hpi for all the lines, including the parents and CIANO T79. The area under the disease progress curve (AUDPC) of RILs varied between 143–598 [Banaras Hindu University (BHU), Varanasi], 367–1274 [Uttar Banga Krishi Viswavidyalaya (UBKV), Cooch Behar] and 740–1537 [Rajendra Agriculture University (RAU), Pusa] (Table S5). At three field sites, the AUDPC of the susceptible (Sonalika) and the resistant (Yangmai #6) parents were 486,160 (BHU), 1274, 459 (UBKV) and 1319, 1031(RAU) respectively (Figure 4; Table S5). AUDPC of the susceptible CIANO T79 was 460 (BHU), 1259 (UBKV) and 1486 (RAU). In order to compare the performance of genotypes across the three centers, they were ranked (increasing ranks correspond to increasing susceptibility) and hierarchically clustered (Figure 4b). Upon k-means clustering, four distinct clusters were observed. It was evident that the population of RILs generated variability in resistance of plants against spot blotch infection, which could be grouped into four reaction types: highly resistant, moderately resistant, moderately susceptible and highly susceptible (Figure 4; genotypes listed in Table S6). Furthermore, 11 RILs (13, 24, 30, 32, 38, 39, 47, 52, 60, 113 and 116) largely showed resistance to spot blotch at all the three locations (Table S6 and Figure 4b). In order to gain insights into how the fitness parameters relate to resistance levels of the RILs, we also recorded the thousand kernel weight (TKW), plot yield and days to heading (DH) of RILs at three sites (Table S5). Taken together, these data on the performance of RILs would be helpful in selecting breeding material and planning future crop improvement initiatives for developing cultivars with high disease resistance as well as higher fitness parameters. We further characterized the pattern of elicitation of SA and phenolics-based metabolites in the RILs during the time of infection of Bipolaris in field conditions at BHU,

© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

Spot blotch-induced defense signaling in bread wheat 41 Figure 3. Elucidation of temporal accumulation of salicylic acid (SA) and phenolic acids in resistant (Yangmai #6) and two susceptible (Sonalika and CIANO T79) wheat genotypes during spot blotch infection. Values are expressed as mean
SD (ANOVA with Fisher’s LSD; comparisons between genotypes are presented; significantly different from the susceptible CIANO T79 at *P ≤ 0 .05, **P ≤ 0 .01, ***P ≤ 0.001 at respective time points).

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Varanasi (Figures 5 and 6 and Tables S7 and S8). We used a set of 16 RILs with a mix of reaction type to spot blotch infection: six lines (13, 24, 30, 38, 39 and 116) were resistant at all the three test locations. We incorporated another six lines (17, 18, 49, 51 64 and 73) that were resistant at two centers, whereas two lines (25 and 34), which were susceptible at test locations. We also included two lines (33 and 42), whose reaction type was variable at test locations (Figure 5 and Table S7). Elicitation of SA and phenolics was noticed at 12–24 hpi (Figures 5 and 6). A cluster of eight high SA accumulating genotypes, similar to the levels in

Yangmai #6, was obtained. All these eight lines (including Yangmai #6) were highly resistant to spot blotch infection. RILs 116, 17 and 49 (which were highly resistant to spot blotch) clustered with line 42, which was either susceptible or moderately resistant at test locations (one of the variable genotypes). Very low levels of SA (4.11 lg g1 FW) was recorded at time 0 in line 42, which elicited a nine-fold increase after 12 h of spot blotch infection (Table S7). Conversely, line 33 clustered with the susceptible genotypes, as the SA levels were comparable with Sonalika and CIANO T79 susceptible genotypes (Figure 5 and Table S7).

© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

42 Ranabir Sahu et al.

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Figure 4. Field evaluation of a wheat RIL population of cross ‘Yangmai #6 9 Sonalika’ at three sites of India. (a) Box plot showing distribution of AUDPC at all the three sites. (b) Heat map shows the hierarchical clustering of ranked AUDPC of RILs and parents at all the three sites [higher rank (red color on the heat map) designates susceptibility]. (c) k-means clustering of wheat genotypes at the three sites on AUDPC. Four groups were designated as highly susceptible (red), moderately susceptible (green), moderately resistant (blue) and highly resistant (black). RAU, Rajendra Agriculture University, Pusa; BHU, Banaras Hindu University, Varanasi; UBKV, Uttar Banga Krishi Viswavidyalaya, Cooch Behar.

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Similar to their SA accumulation patterns, four RILs (17, 24, 38 and 64) showed maximum elicitation of phenolicsbased compounds (Figure 6). Increase in accumulation of phenolic acids was clearly visible at 12 and 24 hpi in RILs (Figure 6). The elicitation of SA and disease progression/ AUDPC was indeed strongly negatively correlated (r = 0.57; P ≤ 0.05; Figure 7a). Similarly, total free phenolics showed strongly negative correlations to disease progression (r = 0.53; P ≤ 0.05; Figure 7b). Correlation of RILs for AUDPC and SA, as well as AUDPC and phenolics content {total free phenolics, as well as syringic acid [r = 0.62; P ≤ 0.05; Figure 7c], chlorogenic acid [r = 0.60; P ≤ 0.05; Figure 7d], and caffeic acid [r = 0.53; P ≤ 0.05; Figure 7e]} showed a strong dichotomy; lines that depicted low AUDPC (resistant) were high in elicited SA and phenolics contents (within 12–24 hpi) and vice versa (Figure 7a–e). DISCUSSION In order to defend themselves, plants recruit a network of signaling molecules that changes concentration to mediate a range of adaptive responses during biotic stresses

(Pieterse et al., 2009). The identity and functions of such signaling network in wheat remain unknown during spot blotch infection. In this investigation, we have annotated genes of the defense-related signaling network of wheat belonging to SA, JA, EDS1, ET and phenylpropanoid pathways. We identified 18 key genes and elucidated dynamics of their expression during the spot blotch infection process. Integrating gene expression data with metabolite data and field studies, and based on the details accomplished in other species [such as Arabidopsis; (Panstruga et al., 2009)], we propose a ‘physiology model’ for effective induced resistance against spot blotch in wheat (Figure 7f). During spot blotch infection, expression of WRKY33 is reprogrammed. Further, expressions of SA biogenesis genes are induced to elicit an accumulation of SA. This may lead to the recruitment of NPR1-dependent signaling pathway, followed by phenylpropanoid pathway, ultimately conferring resistance (Figure 7f). Inadequate induction of these components of the pathway resulted in susceptibility, as noticed in Sonalika and CIANO T79.

© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

Spot blotch-induced defense signaling in bread wheat 43 4 11 18 25 32 39 46 53 60 67 Reaction

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Figure 5. Accumulation dynamics of salicylic acid (SA) (lg g1 FW) in wheat RILs of the cross ‘Yangmai #6 9 Sonalika’ upon spot blotch infection. Patterns of accumulation of SA in parental and susceptible genotypes were reproducible. Upper cluster contained all the lines that were highly resistant (HR) to spot blotch as well as accumulated high SA levels after infection. Lines in the middle cluster were low in basal levels of SA, as well as failed to elicit SA accumulation after infection. These lines were largely susceptible (S) or only resistant (MR) to spot blotch. The third cluster contained genotypes that although had low levels of SA similar to susceptible control genotypes, but were able to elicit SA after 12–24 hpi, and largely displayed a resistant reaction type against spot blotch infection.

Salicylic acid forms an integral component of pathogenactivated defense signaling network in plants (Pieterse et al., 2009). Most of the current understanding of SA signaling comes from studies in model organisms such as Arabidopsis and tobacco (Lu et al., 2009; Pieterse et al., 2009; Dodds and Rathjen, 2010) but its role in wheat remains understudied. SA is believed to be essential for pathogen recognition and establishment of local and systemic resistance in plants (Lu et al., 2009). It induces pattern recognition receptors (PRR) and promotes defenses in Arabidopsis (Tateda et al., 2014). Increased levels of SA have also been associated with induction of systemic acquired resistance (SAR) and coordinated activation of PRs (Tsuda et al., 2008). Plants impaired in SA signaling do

not show PR-gene activation. The NPR1 protein acts as transducer of SA signaling as it is a co-activator of expression of PR genes (Dong et al., 2004). Taken together, our data on contrasting resistant and susceptible genotypes as well on RILs indicated that spot blotch-induced SA accumulation formed the central component of resistance in wheat. Highly increased SA levels might elicit NPR1 expression, which activated the PR-gene expression and further downstream defense responses. Accumulation of phenolic compounds including chlorogenic acid, syringic acid, 4-hydroxybenzoic acid and caffeic acid, may form a crucial component of defense response against spot blotch in wheat. SA is believed to modulate defense responses against biotrophic pathogens. Conversely, JA and ET are believed to be involved in plant defenses against necrotrophs. Infection of B. sorokiniana to wheat comprises of an initial biotrophic phase that allows the pathogen to colonize the host and establish. Once the pathogen has colonized the plant cells, it multiplies and spreads from older to newer leaves as a necrotroph (Attard et al., 2010). Elicitation of genes of JA biosynthesis and signaling, as evident in this study, corroborate with such a lifestyle of pathogen. JA signaling may be recruited in wheat to complement resistance elicited by SA during initial infection cycles. The next step in investigation will to decipher the mechanistic role of JA and to understand the how SA and JA signaling pathways interact. Defense-related phytohormone signaling is strongly modulated by WRKY transcription factors (Pandey and Somssich, 2009). Of this family, WRKY33 of Arabidopsis is a key transcription factor that regulates several aspects of defense signaling when plants are attacked by necrotrophic fungi (Zheng et al., 2006). WRKY33 may regulate ‘antagonistic interaction’ between JA and SA pathways, mediating defense responses of Arabidopsis against the virulent bacterial and fungal pathogens (Zheng et al., 2006). It also modulates several components of SA-, JAand ET-signaling pathways as well as elicitation of a defense-related secondary metabolism (Birkenbihl et al., 2012). It further modulates the JA-dependent signaling responses at later stages of infection against necrotrophic fungal attack in Arabidopsis (Birkenbihl et al., 2012). Here, we observed that WRKY33 expression was selectively reprogrammed in wheat lines that were resistant to spot blotch. It may be hypothesized that reprogramming of expression of WRKY33 in wheat (genotype resistant to spot blotch) may modulate such interplay between SA and JA signaling. This warrants further investigation. Defense-related signaling forms the central nerve of adaptive responses in plants (Pieterse et al., 2009; Dodds and Rathjen, 2010), yet the identification of crucial genes of defense signaling in wheat remains a limiting factor.

© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

44 Ranabir Sahu et al.

1200

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Figure 6. Dynamics of accumulation of phenolic acids (lg g1 FW) in the wheat RILs of ‘Yangmai #6 9 Sonalika’ at various time intervals upon spot blotch infection. (a) Total free phenolic content, (b) 4-hydroxybenzoic acid, (c) syringic acid, (d) chlorogenic acid, (e) caffeic acid, (f) vanillic acid, (g) gallic acid, (h) total bound phenolic content, (i) ferulic acid, and (j) p-coumaric acid.

© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

Spot blotch-induced defense signaling in bread wheat 45

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Induced Plant Defense

Figure 7. Logarithmic regression of inverse correlation of AUDPC with: (a) salicylic acid (SA); (b) free total phenolic content (FTPC); (c) syringic acid (SYA); (d) chlorogenic acid (CLA); and (e) caffeic acid (CA) contents at 12–24 hpi. Pearson correlation coefficient (r) at significance levels of P ≤ 0.05 or P ≤ 0.01 (t-statistics approximation) are indicated. (f) A model for elicitation of defense response in wheat rendering resistance against spot blotch infection.

Wheat forms the ‘critical staff of life’ for billions of people across the globe. But, spot blotch is posing an important emerging challenge to wheat cultivation, especially in the densely populated south Asia. Our investigation not only identified 18 critical genes belonging to five defense-

related signaling pathways, it offers insights into spot blotch–wheat interaction. Genes analyzed here can be used directly to develop effective resistance strategies in breeding programs. Genotypes with high phytohormone inducibility after spot blotch attack can serve as sources of

© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

46 Ranabir Sahu et al. resistance. Biotechnological and genetic manipulation of signaling genes discussed here may be another strategy for generating plants resistant to spot blotch infection. Our study demonstrates an integrative biology approach that combines comparative genomics, bioinformatics, molecular biology, analytical chemistry, plant pathology and field experimentations in developing models for effective induced resistance in crop plants against pathogen attack.

Sampling of plant material To explore whether spot blotch disease elicits changes in phytohormone signaling and phenylpropanoid pathway in wheat, timecourse experiments were conducted in two contrasting (resistant and susceptible) wheat cultivars in controlled (polyhouse) conditions as described earlier. Flag leaves (150–200 mg) were collected after inoculation of B. sorokiniana. Eight biological replicates, at six time points (0, 4, 8, 12, 24 and 48 hpi) were harvested in liquid nitrogen and stored at 80°C until further use for gene expression studies and evaluation of SA and phenolic acids.

EXPERIMENTAL PROCEDURE

Analysis of gene expression by quantitative real-time PCR

Identification and annotation of phytohormone signaling gene families in T. aestivum

Total RNA was extracted using the Trizol method following the manufacturer’s instructions (Ambion, Life Technologies, Carlsbad, CA, USA), and reverse-transcribed with the help of Superscript first-strand cDNA synthesis kit (Life Technologies) and oligo-dT primers following the manufacturer’s protocol (Life Technologies). SYBR Green assays were developed using ‘power SYBR green’ kit (Life Technologies) and gene-specific primers (Table S9). All the gene-specific primers were designed with the help of Primer Expressâ Software Version 3.0 (Applied Biosystems, Foster City, CA, USA; http://www.appliedbiosystems.com). cDNA templates corresponding to 40 ng total RNA before reverse-transcription were used in all the quantitative real-time PCR (qPCR) assays and Tubulin served as the endogenous control (Exposito-Rodriguez et al., 2008). The delta-delta CT (DDCT) method was used for analysis of data (Pandey et al., 2010). Expression levels in plants corresponding to time point 0 hpi (controls) were set to 1 (as reference) and relative expressions of genes at various time points were determined. Three or four biological replicates (randomly selected from eight described above) were used and qPCR was repeated twice.

An integrative bioinformatics approach deployed to isolate genes of defense-related phytohormone signaling is summarized in Figure S1. Using the gene sequences of A. thaliana [at NCBI (http://www.ncbi.nlm.nih.gov/) and TAIR (http://Arabidopsis.org/)] as reference, homologs of phytohormone signaling pathway genes were mined in T. aestivum EST databases at NCBI (http://www.ncbi.nlm.nih.gov/dbEST/; accessed October 2012) and JCVI (http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/ gimain.pl?gudb=wheat) with the help of BLASTN search (Evalue < 1 e4; Figure S1). These EST tags were concatenated and assembled into the contigs. To retrieve full-length CDS, contigs were later mapped on T. aestivum high-confidence (HCS) chromosome arm-assigned gene models and genome sequences (version v2.2) (Mayer et al., 2014) available at IWGSC repository (http://www.wheatgenome.org/). The complete open reading frame was confirmed by using ORF finder (http:// www.ncbi.nlm.nih.gov/projects/gorf/). The Pfam (http://pfam.sanger.ac.uk/) database was used to analyze the characteristic domains in the predicted sequences. Finally, the identity and annotation of all the predicted homologs were confirmed by comparing the domain distribution and alignment of full-length CDS and peptide sequences with corresponding sequences of the Arabidopsis genes (Figures S2–S4 and Table S2). The MYC2 homolog was confirmed using the genome database (Brenchley et al., 2012).

Plant material and creation of artificial epiphytotic condition Two contrasting lines, Sonalika (susceptible) and Yangmai #6 (resistant to spot blotch infection) were evaluated in the glass house conditions in pots at two locations, the Indian Institute of Science Education and Research, Kolkata, and Institute of Agricultural Sciences, BHU, Varanasi, India. The growing conditions were maintained as following: temperature of 22–26°C, relative humidity of 73–75% and a 16 h photoperiod. Fertilizer was applied to supplement nitrogen, phosphorus and potassium (NPK) in a proportion of 120:60:40. The 87 RILs developed from the cross of Yangmai #6 and Sonalika, and selfed to F10 generation (Kumar et al., 2009), were used in the subsequent field experiments. Inoculation of pathogen was done at the growth stage (GS) 59 (Zadoks et al., 1974) when the flag leaf had fully emerged. A pure culture of B. sorokiniana was maintained on potato dextrose agar (PDA) medium (Chand et al., 2003). B. sorokiniana spores were multiplied on sorghum grain (Goel et al., 2006) and the pathogen was uniformly spray-inoculated at a concentration of 106 spore ml1 of water. Spot blotch symptoms appeared by 4 dpi.

Salicylic acid and metabolite analysis Estimation of salicylic acid and phenolic acids was done by the UPLC-DAD method (Verberne et al., 2002). Six to eight biological replicates of flag leaves (150–200 mg), from each of the time points detailed above, were collected from wheat after inoculation with B. sorokiniana. Fresh leaves were crushed in liquid nitrogen and extracted in 1 ml of 90% methanol and supernatants were dried at 40°C for 80 min followed by adding 250 ll of 5% trichloroacetic acid and mixture was mixed by vortexing. Partitioning with 800 ll extraction buffer (ethyl acetate:cyclohexane, 1:1) resulted in the separation of two layers in which upper organic phase was collected for SA estimation. The organic phase was dried in a speed-vac concentrator (LABCONCO, Kansas City, MO, USA) at 40°C for 20 min. As it may have been difficult to correctly integrate SA peak from the extract of some sample due to low milliabsorbance unit concentrations (mAU), 50 lg ml1 of standard SA was spiked with the dried extract. This amount was used to normalize SA levels across the samples after integrating the total peak area after spiking. Furthermore, 1 ml of UPLC eluent was added to the dry sample. After centrifugation, filtered (0.22 lm membrane filter) supernatants were transferred to a clean vial for analysis by UPLC. Total phenolic contents were determined with the Folin–Ciocalteu’s assay (Kofalvi and Nassuth, 1995). Flag leaf samples were pulverized with liquid nitrogen and extracted with 1 ml of 70% methanol. After centrifugation, the process was repeated and supernatants were combined. A 100 ll aliquot of supernatant was mixed with 0.5 ml of 2 N Folin–Ciocalteu’s reagent (Sigma, Mumbai, India) followed by 2.5 ml of 20% sodium carbonate. Sodium

© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

Spot blotch-induced defense signaling in bread wheat 47 carbonate was introduced 2 min after but 8 min before adding Folin–Ciocalteu’s reagent. The solutions were incubated at room temperature for 30 min and absorbance was measured at 765 nm in a spectrophotometer (UV-1800, Shimadzu, Kyoto, Japan). Total phenolic contents in the extracts were determined from standard curve prepared with gallic acid. For UPLC-based analysis, phenolic acids were extracted as in a previously described method (Li et al., 2008) in both free and bound form. Briefly, ground flag leaves (100–150 mg) were extracted with 70% methanol and supernatants were used for free phenolic acid contents, where pellets were analyzed for bound phenolic acid contents after hydrolysis. Estimation of individual phenolic acids (gallic acid, 4-hydroxybenzoic acid, syringic acid, vanillic acid, p-coumaric acid, chlorogenic acid, caffeic acid, sinapic acid and ferulic acid) was investigated using UPLC-DAD method using C18 column. Water and acetonitrile (80:20 v/v) with 0.1% formic acid (pH 3.0) was used as mobile phase at the flow rate of 0.3 ml min1 where column was maintained at 40°C. The DAD (the detector) was set at four multiple wavelengths (275, 285, 310 and 320 nm) for UPLC analysis.

Evaluation of disease severity and plant performance under field conditions A recombinant inbred population was generated by crossing Yangmai #6 and Sonalika lines and used in identifying QTL/genetic factors for resistance to spot blotch (Kumar et al., 2009). The 87 ‘single seed descent’ F10 RILs, along with their parents as well as universal susceptible genotypes (CIANO T79), were subjected to field trials in the three locations: (i) BHU, Varanasi (25.2°N and 83.0°E), (ii) RAU, Pusa (25.6°N and 83.4°E), and (iii) UBKV, Cooch Behar (26.2°N and 89.2°E). The lines were evaluated in an alphalattice design with three replicates where a 2 M single row was assigned for each line. Row-to-row and plant-to-plant distance was 25 and 5 cm, respectively. Fertilizers (NPK) were applied according to recommended agronomic practices (120:60:40) for which phosphorus and potassium were applied at the time of sowing in full dose. Urea, the source of nitrogen, was applied, half at the time of sowing, whereas remaining one-fourth of each was used after 25 and 45 days of sowing, respectively. Furthermore, RILs were categorized into four groups as per their reaction types by k-means clustering using an R statistical package version 3.2.0. The four groups were designated as: (i) highly resistant (HR), (ii) moderately resistant (MR), (iii) moderately susceptible, (MS), and (iv) highly susceptible (HS) as described earlier (Joshi et al., 2004).

Assessment of disease Spot blotch was assessed at three different growth stages: GS 63 (beginning of anthesis to half complete), GS 69 (anthesis complete) and GS 77 (late milking) (Zadoks et al., 1974) using a double digit (DD, 00–99) scale (Saari and Prescott, 1975). The first digit (D1) indicates vertical disease progress on the plant and the second digit (D2) indicates severity, measured in diseased leaf area. The DS percentage for each score was based on the following formula, % severity = (D1/9) 9 (D2/9) 9 100 (Duveiller et al., 2005). AUDPC was calculated using the percent severity estimations corresponding to the disease rating (Joshi and Chand, 2002; Joshi et al., 2004): AUDPC ¼

n X ½fðYi þ Yiþ1 =2g  ðtiþ1  ti  i1

where Yi = disease level at time ti, (ti+1  ti) = days between two disease scores, n = number of readings.

Associated fitness parameters In addition to disease severity, plot yield (amount of harvested crop per crop area), DH and thousand kernel weights (weight of 1000 gains) were also recorded to evaluate plant performance.

Statistical analysis Statistical analyses were performed using the ‘stat’ package in R statistical environment (https://www.r-project.org/). For gene expression studies, repeated measure two-way ANOVA with Fisher’s LSD at P ≤ 0.05 (log2 scale) was used to evaluate transcript changes before and after infection (time-course study), as well as between genotypes at a given time point (Table S3). For metabolite studies, one-way ANOVA with Fisher’s LSD P ≤ 0.05 was used to evaluate differences between genotypes (Table S4).

ACKNOWLEDGEMENTS We thank Ravi Singh for help with experiments and analysis, Harshata Pal for phenolic acid standards, and Rajiv Kumar (RAU, Pusa) for help with field trials at RAU Pusa, respectively. The authors thank the WHEAT Competitive Grants Initiative, CIMMYT and the CGIAR (A4031.09.10) and MPG-India partner program of Max Planck Society and Indo-German Center for Science and Technology, Department of Science and Technology (India) for financial support. RS thanks University Grant Commission (UGC) for providing research fellowship. The suggestions given by Pawan Kumar Singh and Ravi P. Singh, CIMMYT, Mexico are gratefully acknowledged.

SUPPORTING INFORMATION Additional Supporting Information may be found in the online version of this article. Figure S1. Schematic summary of an integrative genomics approach to identify key defense-related signaling genes in bread wheat. Figure S2. Coding sequences of the 18 key signaling and defense related genes in wheat. Figure S3. Organization of characteristic domains in the 18 key signaling and defense related genes. Figure S4. Pairwise alignment of (a) nucleotide and (b) protein sequences of T. aestivum genes to the corresponding A. thaliana baits. Figure S5. Evaluation of expression of components of EDS1 signaling pathway genes during spot blotch infection of susceptible (Sonalika) and resistant (Yangmai #6) wheat genotypes. Figure S6. Accumulation of gallic acids in resistant (Yangmai #6) and two susceptible (Sonalika and CIANO T79) wheat genotypes during spot blotch infection. Table S1 Genomic coordinates of the phytohormone signaling and phenylpropanoid pathway genes in T. aestivum. Table S2 Statistics of pairwise alignments of the phytohormone signaling genes of T. aestivum (Ta) and A. thaliana (At). Table S3 Statistical analysis (repeated measure two-way ANOVA; Fisher’s LSD) of transcript accumulation during spot blotch infection on resistant (Yangmai #6) and susceptible (Sonalika) wheat genotypes over a period of 48 hpi. Table S4 Statistical analysis (one-way ANOVA; Fisher’s LSD) of accumulation of SA and phenolic acids during spot blotch infection on resistant (Yangmai #6) and susceptible (Sonalika) wheat genotypes in comparison to CIANO T79 wheat genotype (significant difference at P ≤ 0.05).

© 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd, The Plant Journal, (2016), 86, 35–49

48 Ranabir Sahu et al. Table S5 Area under disease progressive curve (AUDPC), thousand kernel weight (TKW), days to heading (DH) and plot yield of wheat genotypes at three centers. Table S6 Four distinct clusters according to their reaction types across the three centers: HR, highly resistant; MR, moderately resistant; MS, moderately susceptible; and HS, highly susceptible. Table S7 Salicylic acid content (lg g1 FW) in RILs during spot blotch infection. Table S8 Accumulation of phenolic acid (lg g1 FW) in RILs during spot blotch infection. Table S9 List of primers for qPCR analysis.

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