Introduction

Rice (Oryza sativa L.) is one of the most important staple food crops for more than one half of the world’s population. Productivity of the crop is affected by damage caused by insect pests/pathogens. The Asian rice gall midge, Orseolia oryzae (Wood Mason), is one of the important rice pests causing an annual yield loss to the tune of about US$80 million in India (Bentur et al. 2003). Development of rice cultivars with resistance to the pest is the desirable approach to mitigate this loss. However, adaptation of pest populations and evolution of virulent biotypes is the cause of concern. Hence, identification and characterization of resistance genes in rice are essential to the development of durable resistance against the pest.

Plants posses an array of defense arsenal against pathogens and insect pests. While plant defense against pathogens generally involves salicylic acid (SA)-mediated response resulting in expression of hypersensitive reaction (HR), defense against insects involves jasmonic acid (JA)-mediated response (Thaler et al. 2012). Often these two pathways act antagonistically. Genotype-specific variations in defense in the same plant species against specific race/biotype of the pest are also reported. Such diversity is the result of co-evolution and negate the counter-defense strategies of the invading organisms (Xu et al. 2013).

The rice gall midge interaction is genetically well-characterized. Until now, 11 R genes have been identified from different rice varieties and mapped on to different chromosomes (Yasala et al. 2012). None of these genes is effective against all the seven gall midge biotypes reported in India (Vijaya Lakshmi et al. 2006). Incompatibility between the host and the gall midge, i.e., plant resistance is manifested in two distinct ways, i.e., with or without the expression of hypersensitive reaction (HR+ or HR− types), wherein the HR+ type results in tissue necrosis at the feeding site, while HR− type response is without tissue necrosis (Bentur and Kalode 1996). Conversely, compatible interaction or plant susceptibility occurs when virulent maggots successfully establish in the plant to complete the life cycle to emerge as adults. Of the known R genes, only Gm1 and Gm8 confer HR− type resistance (Bentur et al. 2003). The indica rice cultivar Aganni, carrying gall midge resistance gene Gm8, has a wide range of resistance across gall midge biotypes. This gene has been tagged and mapped within 0.43-Mb region on chromosome 8 of rice between the flanking SSR markers RM22685 and RM22709 (Sama et al. 2012).

In our earlier studies on the molecular basis of rice-gall midge interactions, we have analyzed differentially expressed genes in the rice variety Suraksha (possessing gall midge resistance gene Gm11) expressing HR+ type of resistance, using suppressive subtraction hybridization (SSH) cDNA library (Rawat et al. 2013). Defense mechanism in this cultivar showed similarity with that observed in rice against pathogens. In contrast, microarray analysis of resistance mechanism in the rice variety Kavya carrying Gm1 gene (with HR− type of resistance) revealed the resistance to be a novel type (Rawat et al. 2012a). Using both SSH and microarray approaches compatible interactions were also studied in gall midge-susceptible rice TN1 (with no R gene) and also in Kavya (with Gm1 gene) and Suraksha (with Gm11 gene) challenged with the virulent biotype of the gall midge (Rawat et al. 2012b). These studies revealed up-regulation of genes involved in primary metabolism, nutrient relocation, cell organization, DNA synthesis, and down-regulation of genes involved in defense, secondary metabolism, and signaling. This study also identified few putative ‘susceptibility genes’. In this paper we have examined the molecular basis of resistance in another rice variety Aganni, carrying Gm8 – a gene conferring HR− type of resistance—and show that pathways involved here are not similar to those described earlier.

Materials and methods

Plant material for suppressive subtraction hybridization (SSH) cDNA library construction

Rice variety Aganni carrying gall midge resistance gene Gm8 with HR− type of resistance was used for SSH cDNA library construction. Aganni seeds were germinated and grown in plastic trays (60 × 30 × 30 cm) with fertilizer-enriched rice soil under standard conditions. Each tray had 12 lines of 20 plants each. When plants were 15-day-old, one of the trays was exposed to gall midge biotype 4 (GMB4) adults (50 females and 10 males). Another tray was used as the control where the plants were not exposed to the insects. Two days after insect release, both the trays were transferred to a high humidity chamber (>90 % RH) for two days (for egg incubation and maggot establishment in infested plants). Plants were sampled at five different time points 24, 48, 72, 96, and 120 hours after infestation (hai). Plants from the uninfested trays were also sampled at the same time point.

Plant material for gene validation

Two sets of plants – test lines with contrasting phenotypes, − were used for validation of shortlisted genes for real-time PCR. The two contrasting parents—gall midge-susceptible TN1 and gall midge-resistant Aganni formed the first set. Two pre-NILs (near isogenic lines) designated as susceptible 34S and resistant 74R selected from the 426 F10 recurrent inbred lines (RILs) from the cross TN1 X Aganni with over 93 % genetic similarity as assessed with 320 Simple Sequence Repeats (SSR) markers formed the second set of plants (data not shown). Seeds of the test lines were germinated and grown in plastic trays (60 × 30 × 30 cm) with fertilizer-enriched rice soil under standard conditions. Plants were grown, infested with GMB1, and sampled as mentioned earlier (Rawat et al. 2013). Plants from the uninfested trays were also sampled at the same time point.

RNA extraction

The sampled plants were cut at the base, dissected under stereo binocular microscope to remove live and dead maggots from the infested plants. Uninfested plants were also similarly dissected out despite the fact there would be no maggots in these tissues. The meristematic tissue (region ~1 cm from the base) was cut and preserved in RNALater (Qiagen, Germany). Later, the tissues were crushed in liquid N2 and total RNA was isolated using TRIzol (Invitrogen, USA) according to the manufacturer’s protocol. Equal amounts of total RNA were pooled from all the time intervals, for both the sets of plants, separately. Total RNA 700 μg from uninfested and 350 μg from infested plants was used for mRNA isolation by magnetic separation after annealing to 5′-biotinylated oligodT primer and subsequently immobilized on streptavidin-linked paramagnetic beads, as described earlier (Mishra et al. 2005).

Driver preparation

First-strand cDNA was synthesized, using Superscript III reverse transcriptase (Invitrogen, USA) along with 5′-biotinylated anchored oligodT [T(18) VN] primer, from 5 μg of mRNA isolated from the control plants, according to the manufacturer’s protocol. Subsequent purification of the cDNA was performed by hydrolyzing the mRNA by alkaline treatment (30 min at 55 °C in 0.1 N NaOH) followed by removal of excess oligodT primers according to Mishra et al. (2005).

Suppressive subtraction hybridization (SSH)

Five-fold excess of 5′-biotinylated first-strand cDNA populations, from the control plants (driver) were mixed with one microgram of mRNA (tester) from the infested Aganni variety. The samples were kept for hybridization for 4 h at 68 °C in 50 μl RNase-free hybridization buffer (10 mM Tris–HCl pH 7.5, 0.5 M KCl, and 5 mM EDTA) in a silanized eppendorf tube. SSH library was prepared as per Rawat et al. (2012b). Double-strand cDNA was synthesized using the sequence abundant, normalized, and enriched, differentially up-regulated, subtracted mRNA. The double-stranded cDNA was uni-directionally ligated to lambda-ZAP vector, in vitro packaged and allowed to infect XL1-Blue MRF E. coli cells according to the manufacturer’s instructions using a UNI-ZAP XR cDNA library construction kit (Stratagene, USA).

Screening for recombinant clones

The recombinant clones were stored temporarily at −20 °C after transferring into 96-well format storage plates containing 200 μl of SM buffer (100 mM NaCl, 8 mM MgSO4.7H2O, 50 mM Tris–HCl pH 7, 0.04 % gelatin) supplemented with 5 % DMSO and 0.5 % chloroform. The cDNA clones were PCR amplified with 100 ng of universal M13 forward and reverse primers and recombinant phages having insert sizes of ≥200 bp were selected and re-arrayed into new storage plates. PCR was performed using 1 μl of phage suspension as template in 100 μl of PCR reaction volume (1X PCR buffer, 200 μM dNTPs and 5U Taq polymerase) for 30 cycles with following PCR conditions, 94 °C for 1 min, 55 °C for 1 min and 72 °C for 2 min. The PCR products were purified using StrataPrep 96 PCR purification kit (Stratagene, USA) to remove un-incorporated primers and nucleotides. Next, the purified PCR products were dried and sent for sequencing (Macrogen, South Korea).

Data processing

The obtained sequence data for each clone were processed using MacVector (MacVector Inc, USA, version 11.1.2) suite of programs to trim out vector sequences. The inbuilt Phred and Phrap program of MacVector was used to assemble the sequences into contigs.

Data analysis

Homology search was performed using BlastN and BlastX (http://www.ncbi.nlm.nih.gov/BLAST/ version 2.2.29) to search for homologous sequences in the non-redundant nucleotide and protein databases, respectively. Selected clones were manually annotated using the information from the highest scoring matches returned by both the analyses. Functional classification of the ESTs was performed using Gene Ontology (http://www.ricearray.org/analysis/GO/). Further ESTs were assigned to the main metabolic pathways using Kyoto Encylopedia of Genes and Genomes (http://www.ricearray.org/analysis/KO/). All the processed sequences have been submitted to the GenBank.

Primer designing and real-time PCR validation of differentially expressed genes

Primer pairs were designed using Primer3 software tool (http://frodo.wi.mit.edu/) or Primer Express Software (Applied Biosystems) from the genes shortlisted, from those that were sequenced, for validation of expression using quantitative real-time PCR (qPCR). The primers were designed so as to amplify a 60–150-bp product (Table 1).

Table 1 Sequence information of primers used for the real-time PCR of the shortlisted ESTs from the SSH cDNA library of Aganni
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In all, 27 candidate genes were validated via real-time reverse transcription PCR with four sets of samples derived from the test lines (TN1, Aganni, 74R line, and 34S line). Real-time PCR was conducted using cDNA prepared from RNA sampled from independent infestations at two time points viz., 24 and 120 hours after infestation (hai). Three micrograms of RNA was used for first-strand cDNA synthesis using the SuperScript III RT (Invitrogen, USA) following the manufacturer’s guidelines. Real-time-PCR was performed using Applied Biosystems 7500 Real Time PCR System with the SYBR green chemistry (Applied Biosystems, USA) according to the manufacturer’s instructions. Rice ubiquitin gene, OsUbq (GenBank accession no. AK059694), was used as the endogenous control. Real-time PCR reaction volume of 20 μl contained 10 μl SYBR green PCR master mix (Applied Biosystems, USA), 500 nM each of forward and reverse primers and 20 ng of the cDNA. To calculate mean relative expression levels, cDNAs from three independent biological samples in two technical replications each were used. PCR was initiated with a pre-incubation at 50 °C for 2 min and denaturation at 95 °C for 10 min followed by 40 cycles of denaturation at 95 °C for 15 s and annealing and extension at 60 °C for 1 min. A melt curve analysis was done to determine the specificity of the reaction. After normalization, quantity of each mRNA was calculated from the threshold points located in the log-linear range. The data from different PCR runs or cDNA samples were compared by using mean CT values of the biological replicates that was normalized to the mean of CT values of the endogenous control gene. The relative standard curve method was used for the quantification of mRNA levels and displayed as relative expression values (REV). Expression ratios were calculated using the 2−∆∆Ct method (Livak and Schmittgen 2001). The data were analyzed using the 7500 Sequence Detection Software (Applied Biosystems, USA) with default baseline and threshold. Mean values were compared pairwise between the time points within treatments with Tukey’s HSD test and P < 0.05 was considered as level of significance (SAS Institute Inc., version 4.3, Cary, USA). Data was presented as Relative Expression Values.

Results

Structure of SSH cDNA library

In all, 3000 clones from the Aganni library were picked and PCR amplified using M13 forward and reverse primers and sequenced. Of these, 2,800 ESTs were further considered for sequence assembly after removing low-quality sequences or those with very small inserts (<50 bp) or those clones without any inserts. The high-quality ESTs were assembled into contigs using MacVector program. These high-quality sequences had an average read length of 450 bp. Of these, 258 sequences were singletons whereas rest of the sequences assembled into 190 contigs (Table 2 and Electronic supplementary material (ESM) Table S1). All the 1,405 unique ESTs have been submitted to the EST database of GenBank (http://www.ncbi.nlm.nih.gov/dbEST) (GenBank ID: JZ546410–JZ547814). This library was used to elucidate transcriptional changes and identify transcripts that showed differential responses in rice variety Aganni triggered by the infestation with the rice gall midge biotype 4 (GMB4).

Table 2 A comparative analysis of SSH cDNA libraries developed form three rice varieties to highlight differential gene expression following gall midge infestation
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Sequencing and data analysis

Based on BlastX and BlastN homology searches of the 387 non-redundant sequences of the Aganni library, 282 (73 %) clones were homologous to genes with known function, 60 (15 %) clones were homologous to genes with unknown function and named as hypothetical proteins. Of the rest, 15 (4 %) clones did not match any known sequences in the rice database, but had matched sequences reported from other crops such as wheat, maize, mustard, and also from other species such as green algae and bacteria whereas 30 (8 %) clones did not show any hit with sequences in the NCBI database (Fig. 1, Table 2).

Fig. 1
figure 1

Distribution of ESTs (based on sequence homology) in the SSH cDNA library prepared for rice variety Aganni challenged with GMB4

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Gene ontology-based functional annotation

Based on gene ontology (GO) annotation, EST sequences were grouped into three categories, viz., biological process, molecular function, and cellular component. However, some ESTs were annotated in two or all the three categories. Among the ESTs under biological process, large number of ESTs pertained to biosynthetic process and translation and protein turnover (Fig. 2a). Under molecular function category, ESTs related to enzyme activity, ion binding followed by DNA binding and transferase activity were abundant (Fig. 2b). In the case of cellular component, high number of ESTs was found in membrane and intracellular group (Fig. 2c). A comparative view of the data with respect to earlier reports on Suraksha (Rawat et al. 2013) and TN1 (Rawat et al. 2012b) EST libraries is presented in supplementary figures (ESM Fig. 1A, B, C). It is evident from the data that the Aganni library had unique features, i.e., nine sub-categories, under biological process 13 sub-categories under molecular function and 13 sub-categories under cellular component that were uniquely represented in the Aganni library.

Fig. 2
figure 2

Distribution of ESTs from Aganni SSH cDNA library based on the functional classification, into the three principal Gene Ontology (GO) categories: a biological process, b molecular function, c cellular component. Values represent the number of ESTs found under each sub-category under the three main GO categories

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ESTs classified based on function

To obtain better understanding of the putative functions of the ESTs, these were further classified into 12 different groups, within each gene ontology categories. Four groups of ESTs namely transport, translation and protein turnover, metabolic process, and biosynthetic process were found to be in a majority in the Aganni library (Table 3). In all, 57 ESTs were present in transport group that code for monodehydroascorbatereductase, amino acid transporter, and related transporter family proteins (ESM Table S2). In translation and protein turnover group, 70 ESTs coding for peptidylprolylcis/trans isomerase, calcium/calmodulin-dependent protein kinases, and heat shock protein were present (ESM Table S3). In the metabolic process group, 42 ESTs coding for serine hydroxymethyltransferase, acyl-CoA, erythronate-4-phosphate dehydrogenase, glutamine synthetase, cysteine synthase, and others were high in number (ESM Table S4). In the biosynthetic process group, 31 ESTs coding for ketol-acid reductoisomerase, conserved peptide U ORF-containing transcript were present (ESM Table S5).

Table 3 Relative abundance of ESTs under different functional groups detected in three SSH cDNA libraries
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ESTs in another set of four groups relating to transcription and modification, defense related, signal transduction, and DNA structure, synthesis, and cell organization were also abundant in the Aganni library. In the transcription group ESTs coding for NAC domain-containing protein, WW domain-containing protein and auxin-responsive protein were present (ESM Table S6). In the defense related group, ESTs coding for abscisic stress-ripening, pathogenesis-related Bet v I family protein and plasminogen activator inhibitor (ESM Table S7) were present. In the signal transduction group 14 ESTs were present. These ESTs code for COP9 signalosome complex subunit 5b, protease inhibitor, and histidine-containing phosphotransferase protein (ESM Table S8). In the DNA structure, synthesis, and cell organization, group ESTs coding for FACT complex subunit SPT16, ABC transporter, ATP-binding protein were present (ESM Table S9). The third set of four groups such as cell wall metabolism, cell redox, primary metabolism, and homoiothermy had relatively lower number of ESTs in Aganni. In the cell wall metabolism group, eight ESTs related to phox domain-containing protein and MLO domain-containing protein were present (ESM Table S10). In Cell redox group, 19 ESTs coding for peroxidase precursor and glyceraldehyde 3 phosphate dehydrogenase were present (ESM Table S11). In primary metabolism group, nine ESTs coding for aspartic proteinase, transporter family protein (ESM Table S12) were present. In homoiothermy group eight ESTs related to AP2 domain-containing protein and membrane associated DUF588 domain-containing protein were present (ESM Table S13). Significantly, no EST was detected under cell signaling and secondary metabolism groups.

Chromosomal distribution of ESTs

The ESTs identified as being up-regulated during the rice gall midge infestation and whose homology was determined by using BlastN against the rice annotation database (TIGR) and Gramene database were mapped (in silico) to the rice chromosomes. Highest number of ESTs from the Aganni library mapped to chromosome 3 followed by those mapping to chromosome 1, 5, 4, 2, and 12, each consisting of 56, 47, 32, 31, 26, and 21 ESTs, respectively. In contrast, less than 20 ESTs mapped on to the remaining chromosomes 6, 7, 9, 10, and 11; while only 15 ESTs mapped to chromosome 8.

Validation of candidate gall midge resistance genes through real-time reverse transcription PCR (rtPCR)

Relative expression of 27 ESTs, picked from the above library, in response to rice gall midge infestation was studied in real-time expression in TN1, Aganni, 34S, and 74R rice lines at various time points after gall midge infestation (Table 1). The basis of selecting these genes has been their reported role in plant stress management based on recent literature (ESM Table S14).

Genes induced in Aganni and 74R

Eight of the ESTs were found significantly up-regulated in both Aganni and 74R at 24 hai when compared with their respective uninfested plants (Table 4). These were (1) abscisic stress-ripening-ASR (contig 374), (2) NAC domain (contig 368), (3) peptidylprolylcis/trans isomerase- PPI (contig 425), (4) glutamine synthetase- GS (contig 478), (5) serine hydroxymethyltransferase- SHMT (contig 358), (6) WW domain-containing protein (contig 415), (7) OsAPx1—cytosolic ascorbate peroxidase encoding gene 1–8 (contig 399), (8) plasminogen activator inhibitor- PAI (contig 456). Expression of these genes decreased at 120 hai (Fig. 3a, b). Only one EST, (9) pathogenesis-related Bet v I family was induced (contig 458, Table 4) in Aganni and 74R at 120 hai. However, there was no induction observed at 24 hai (Fig. 4a, b).

Table 4 Relative expression values for the selected ESTs at 24 and 120 in Aganni and 74R upon infestation by GMB1 compared with respective uninfested controls
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Fig. 3
figure 3

Relative expression profiles of 8 ESTs induced in Aganni and 74R (≥2-fold) when compared with the respective uninfested control a at 24 hai and b at 120 hai. Error bars represent mean ± S.D. Light bars represent Aganni-GMB1 and dark bars 74R-GMB1 incompatible interactions, respectively

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Fig. 4
figure 4

Relative expression profile of one EST induced in Aganni and 74R (≥2-fold) when compared with the respective uninfested control a at 24 hai and b at 120 hai. Error bars represent mean ± S.D. Light bars represent Aganni-GMB1 and dark bars 74R-GMB1 incompatible interactions, respectively

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Genes induced only in 74R

Five ESTs were induced only in 74R at 24 hai. These were (1) erythronate-4-phosphate dehydrogenase-EDPP (contig 401, 3.05-fold), (2) cysteine synthase-CS (GenBank ID: JZ546692, 2.96-fold), (3) acyl-CoA synthetase (GenBank ID: JZ547652, 2.76-fold), (4) aspartic proteinase (AP) oryzasin-1 (contig 451, 2.55-fold) and (5) OsAPx2 - Cytosolic Ascorbate Peroxidase encoding gene 4,5,6,8 (contig 404, 2-fold) (Fig. 5a, b). Another five ESTs viz., (1) leucine-rich repeat (LRR) family protein (GenBank ID: JZ546538, 3.58-fold), (2) amino acid transporter (contig 497, 3.38-fold), (3) Phox domain-containing protein (contig 461, 2.30-fold), (4) heat shock protein-HSP (GenBank ID: JZ547665, 2.28-fold) and (5) COP9 signalosome complex subunit 5b (GenBank ID: JZ546688, 2.10-fold) (Fig. 6a, b) were induced at 120 hai.

Fig. 5
figure 5

Relative expression profiles of 5 ESTs induced only in 74R (≥2-fold) when compared with the respective uninfested control a at 24 hai and b at 120 hai. Error bars represent mean ± S.D. Light bars represent Aganni-GMB1 and dark bars 74R-GMB1 incompatible interactions, respectively

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Fig. 6
figure 6

Relative expression profiles of another five ESTs induced only in 74R (≥2-fold) when compared with the respective uninfested control a at 24 hai and b at 120 hai. Error bars represent mean ± S.D. Light bars represent Aganni-GMB1 and dark bars 74R-GMB1 incompatible interactions, respectively

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Genes induced inTN1 and 34S

One EST, i.e., peptidyl prolylcis/trans isomerase (contig 425), registered 2.07- and 2.33-fold increase, respectively, in transcription levels in TN1 and 34S line at 24 hai, when compared with the respective uninfested plants (Table 5). Another three ESTs were found to be induced only in 34S line at 24 hai viz., abscisic stress-ripening (contig 374, 2.62-fold), aspartic proteinase oryzasin-1 (contig 451, 2.04-fold) and erythronate-4-phosphate dehydrogenase (contig 401, 2.03-fold) (Fig. 7a, b). None of EST was found up-regulated at 120 hai in this set of plants.

Table 5 Relative expression values for the selected ESTs at 24 and 120 in TN1 and 34S upon infestation by GMB1 compared with respective uninfested controls
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Fig. 7
figure 7

Relative expression profiles of 4 ESTs induced in TN1 and in 34S (≥2-fold) when compared with the respective uninfested control a at 24 hai and b at 120 hai. Error bars represent mean ± S.D. Light bars represent TN1-GMB1 and dark bars 34S-GMB1 compatible interactions, respectively

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Genes with low level of induction

In addition to the 19 genes listed above, remaining eight genes registered low level of induction (≤2.0-fold) in the genotypes tested (ESM Fig. 2A, B).

Discussion

Plants have evolved diverse defense mechanisms to protect themselves from various biotic stresses. They have the ability to detect invading pathogen/insect and respond with inducible defenses by producing toxic chemicals and invoking deliberate cell death—apoptosis. Generally, defense against the biotrophic pathogens and some phloem feeding insects is associated with the SA pathway (Hua 2009) and that against the necrotrophic pathogens and leaf-feeding insects with JA pathway (Turner et al. 2002). Pathogenesis-related (PR) genes are associated with plant defense against both pathogens and insects along with initiation of signal transduction processes related to induction of systemic acquired resistance (SAR) (Van Loon 1997). Since the interactions between plant and invading pathogen/insect are dynamic and constantly subjected to coevolving selection pressures, several alternative defense pathways are involved in the same plant species against same or similar group of organisms. This is evident from the fact that multiple R genes, often representing multiple pathways and present in the same host (Ellis and Jones 2003), are effective against the same pathogen/insect, e.g., over 60 genes are reported in rice conferring resistance against blast (Magnaporthe oryzae) (Chen et al. 2005), over 38 genes against bacterial blight (Xanthomonas oryzae pv oryzae) (Natrajkumar et al. 2012), over 27 genes against the brown planthopper, Nilaparvata lugens (Huang et al. 2013; Fujita et al. 2013), and 11 genes against the gall midge (Yasala et al. 2012). Despite the knowledge that these gall midge resistance genes confer a varying spectrum of resistance, against the seven known biotypes of the pest, and differ in expression of HR, the commonality, or diversity in terms of pathway(s) involved in the manifestation of resistance is yet to be elucidated.

Our recent studies involving gene cloning and characterization (Sama et al. 2014) or through analysis of differential gene expression profiles of genes identified through SSH cDNA libraries (Rawat et al. 2012b; Rawat et al. 2013) or microarrays (Rawat et al. 2012a) have revealed diversity in defense pathways triggered by some of the key R genes of rice involved in conferring resistance to gall midge. A comparative analysis of SSH cDNA libraries developed for the rice variety Suraksha (with Gm11 gene conferring HR+ type resistance), TN1 with no gall midge resistance genes and Aganni (with Gm8) (Table 2) revealed relatively lower percentage (73 %) of genes with known function in Aganni as compared with that in Suraksha (83 %) or TN1 (84 %). As observed in the case of Suraksha, Aganni too had a higher percentage of ESTs that mapped on to chromosome 3. But Aganni library revealed highest percentage (6.7 %) of ESTs with no homologies to sequences in the NCBI database. Gene ontology and functional annotation (Table 3) revealed highest proportion of ESTs under translation and protein turnover group in all of them. However, cell signaling and secondary metabolism related ESTs were conspicuously absent in Aganni library. Understandably, defense related ESTs were more abundant in Aganni and Suraksha as compared with those in TN1 library. Significantly, ESTs related to catabolic process and homoiothermy were present only in the Aganni library. In view of a large number of distinct ESTs under several subgroups of all the three categories of GO annotation (ESM Fig. 1A, B, C), Aganni library was unique compared with other genotypes TN1 and Suraksha studied earlier (Rawat et al. 2012b; Rawat et al. 2013).

Recent paradigm shift in gene-for-gene hypothesis of plant defense (Stuart 2015) elaborates four phases of defense. Basal immunity is primarily directed at evading host un-adapted pathogens and triggered by pathogen associated molecular patterns (PAMPs). However, the first line of defense against host-adapted pathogens is mediated by effector triggered immunity (ETI). The main class of genes in pathogen elicitor recognition is nucleotide-binding site leucine-rich repeat (NBS-LRR) (Marone et al. 2013). This immunity is race specific. The diversity of plant defense against a wide range of pathogens and their races, also insects and their biotypes, is reflected in presence of hundreds of such genes in any plant genome, as exemplified in rice above. Generally the plant LRR protein coding R genes are race specific and also associated with hypersensitive response mediated induced resistance (Belkhadir et al. 2004). There have been several recent studies elaborating on structure based specificity among such genes. The NBS-LRR proteins are large, abundant proteins involved in the plant defense through detection of diverse pathogens, including bacteria, viruses, fungi, nematodes, insects, and oomycetes (McHale et al. 2006). NBS-LRR proteins are classified into two sub groups. The first subgroup consists of proteins that have a distinct N-terminal region (TIR domain) that resembles the cytoplasmic domains of the Drosophila protein Toll and the mammalian interleukin-1 receptor protein. The proteins of the second subgroup lack this region but may have a leucine zipper or coiled coil-domain in the N-terminal region (Pan et al. 2000). NBS and TIR domains have a conserved signaling function but LRR domain is involved in the pathogen recognition by either direct interaction with avr protein or indirectly by binding to the protein complex between avr protein and other host proteins (Kobe and Diesenhofer 1995). Rice genome has 653 NBS-LRR genes (Marone et al. 2013). Rice blast resistance genes Pi50, Pi-ta, Pi9, and Pi54 encode NBS-LRR proteins (Su et al. 2015; Bryan et al. 2000; Qu et al. 2006; Ramkumar et al. 2011). Three of the bacterial blight (BB) resistance genes, Xa1, Xa21, and Xa26 are also members of the NBS-LRR family (Hu et al. 2015; Sun et al. 2004). Two of the brown planthopper resistance genes Bph14 and Bph26 encode coiled coil-nucleotide binding leucine-rich repeat (CC-NB-LRR) protein (Du et al. 2009; Tamura et al. 2014). Seven nucleotide binding (NB) and/or LRR genes are reported in the rice genome segments with gall midge resistance genes Gm2, gm3, Gm4, Gm6, Gm7, and Gm11 (Yasala et al. 2012) all conferring HR+ type resistance. Of these genes, NB-ARC and NBS-LRR have been functionally validated, respectively, as the candidate gene for gm3 and Gm4 (Sama et al. 2014; Divya et al. 2015). In the present study one of the LRR genes (LOC_Os11g42660) was found up-regulated in incompatible interaction (Fig. 6b), though it is not located on chromosome 8 to which the Gm8 gene has been mapped (Sama et al. 2012). LRR genes require trans-partners to be effective and several heat shock proteins (HSP) act as such trans-partners (Belkhadir et al. 2004). Heat shock proteins (HSP) belong to a multigenic family and are known to function as chaperones, which assists protein folding in response to environmental stress (Sarkar et al. 2013; Mayer and Bukau 2005). HSP 70 family plays an important role in protecting the rice plants from heat stress (Jung et al. 2013). Genome wide interactions of HSPs in rice revealed Hsp70s to be involved in CHO metabolism, innate immunity, and photosystem II repair (Wang et al. 2014). Heat shock proteins play a central role in the early sensing of H2O2 in plants (Miller and Mittler 2006) and complement the action of NBS-LRR protein (Kadota and Shirasu 2012), e.g., in Arabidopis (Hubert et al. 2003) tobacco (Liu et al. 2004); and potato (Lu et al. 2003). In our earlier study, a HSP gene (LOC_Os03g16860) was noted to be up-regulated in Suraksha at 120 hai (Rawat et al. 2013). At present, another HSP (LOC_ Os12g32986) gene was induced following gall midge infestation (Fig. 6b).

Recognition of invading pathogen by LRR gene is immediately followed by ion flux in the target cells triggering production of reactive oxygen species (ROS), such as hydrogen peroxide, superoxide radical, and singlet oxygen, often leading to expression of hypersensitive reaction (HR). HR results in death of host cells invaded by pathogen/insect. One of the genes, likely to be involved in calcium dependent oxidative burst, CAMK_CAMK_like.7—CAMK was not found induced in this study (ESM Fig. 2A, B). Reactive oxygen species (ROS) /oxidation reduction can be activated during the course of normal aerobic metabolism or when plant is exposed to a variety of stress conditions. A Phox domain-containing protein coding gene was involved in ROS production in Arabidopis (Torres et al. 2002). A gene of this family was also found up-regulated in our study (Fig. 6b). However, ascorbate peroxidases play a major role in H2O2 scavenging to prevent the plant from ROS damage (Zou et al. 2005). Two cytosolic APX isoforms (OsAPX1 and OsAPX2) have been characterized for their role in rice plant defense. OsAPX1/2 knockdown plants (AP1/2s) exhibited enhanced accumulation of H2O2 (Ribeiro et al. 2012). In the present study OsAPx1—Cytosolic Ascorbate Peroxidase encoding gene 1–8 and OsAPx2—Peroxidase encoding gene 4, 5, 6, 8 were upregulated (Fig. 5a, b) suggesting that ROI scavenging enzymes successfully prevented ROS damage in Aganni and prevented HR. Rice genotypes resistant to gall midge display diversity in HR expression. Those genotypes that express HR showed higher expression of LRR, HSP, and PR genes (Rawat et al. 2013); while in Kavya with Gm1 gene that did not express HR, these genes were not up-regulated (Rawat et al. 2012b). Hence, it is of interest to note that Aganni with Gm8 gene did show enhanced expression of LRR, HSP, and PR genes but did not express HR. We associate this with enhanced activity of two of the three genes tested relating to ROS scavenging activity viz., OsAPx1 and OsAPx2. However, the third gene, MDHAR (monodehyroxiascorbate reductase) did not show enhanced levels of activity (ESM Fig. 2A, B). MDHAR is a key enzyme in the oxidative stress in the plants. This enzyme involved in the ascorbate recycling in the ascorbate-glutathione cycle is important in plants against abiotic stresses (Do et al. 2014). TaMDHAR gene is reported to be involved in the resistance of wheat against diseases by regulating the ROS level. The knock down of this gene resulted in higher accumulation of H2O2 and lower APX activity (Feng et al. 2014). Yet another mechanism has been noted in rice line RP2068-18-3-5 carrying the recessive gm3 gene and expressing HR-mediated resistance (Agarrwal et al. unpublished). Following gall midge infestation in this rice, there is enhanced expression of ascorbate peroxidase coding genes which mainly scavenge H2O2. However, HR in this rice is likely to be induced by singlet oxygen (Agarrwal et al. unpublished) produced by photosystem II when energy is transferred from excited chlorophyll to oxygen (Krieger-Liszkay 2005).

Once the first line of defense accomplishes the mortality of invading batch of pathogens, plant defense involves triggering of systemic acquired resistance (SAR). In systemic acquired resistance (SAR), the signal is transmitted from the infected tissue into the whole plant for induction of overall defense gene expression (Ryals et al. 1994). This step involves triggering of several transcription factors (TF) that induce genes involved in plant hormone metabolism, cell signaling, pathogenesis-related protein production and subsequently those involved in primary metabolism. At least two of the five TF genes covered in this study (NAC domain-containing protein 67, WW domain-containing protein) showed rapid induction following insect attack (Fig. 3a). In plant genomes, approximately 7 % of the coding sequences consist of transcriptional factors which proves the complexity of transcriptional regulation (Udvardi et al. 2007). NAC domain-containing proteins respond to pathogen infection (Ren et al. 2000; Selth et al. 2005; Xie et al. 1999) and to abiotic stresses (Hegedus et al. 2003; Tran et al. 2004). There are about 75 NAC domain-containing TFs in rice (Kikuchi et al. 2000). NAC19 gene in rice was strongly induced by rice blast fungus infection and after extraneous application of methyl-jasmonate and ABA (Lin et al. 2007). NAC domain-containing protein is one of the regulators in ABA pathway which leads to the up-regulation of this gene. Several classes of NAC transcriptional factors regulate the secondary cell wall formation in rice (Yoshida et al. 2013). A mutant gene CFL impairs cuticle development in rice. The wild type of this gene codes for WW domain-containing protein (Wu et al. 2011). More recently, WW domain-containing proteins were shown to regulate virus replication by acting as cell-intrinsic restriction factor (CIRF) in tomato (Barajas et al. 2015). One of the genes covered in this study, identified as TF under GO category, CIGR—chitin-inducible gibberellin-responsive protein (LOC_OS01g65900) has been identified as the candidate gene ph1 affecting plant height and closely linked to sd1 gene (Kovi et al. 2011). However, this TF did not get induced in the present study (ESM Fig. 2A) though it was implicated in compatible interaction earlier in TN1 (before Rawat et al. 2012b). Likewise, auxin-responsive Aux/IAA gene family member (Rawat et al. 2012a) and bZIP transcription factor domain-containing protein gene did not respond to insect infestation in Aganni. The basic leucine zipper (bZIP) domain-containing transcription factors (TFs) function as key regulators of cellular growth and differentiation in eukaryotic organisms. Till now 19 bZIP TFs have been characterized in rice. One of such TF has been associated in compatible interaction with blast fungus (Tang et al. 2015).

Genes involved in plant hormone metabolism and covered in the present studies were those coding for abscisic stress ripening (ASR) protein, COP9 signalosome complex subunit 5b (CSN5B), Aminocyclopropane-1-carboxylate oxidase 1and Enoyl-CoA hydratase/isomerase. While roles of salicylic acid and jasmonic acid in conferring plant resistance against two distinct guilds of pests are known, role of other hormones either in inducing or modulating these pathways is now being reported. ABA-related gene induces susceptibility in rice against Xanthomonas oryzae and Magnaporthe oryzae by down-regulating the SA-mediated pathway (Xu et al. 2013; Jiang et al. 2010). Rawat et al. (2012b) also reported that ABA related genes like HAV22 protein are involved in susceptibility against gall midge infestation. This ABA-related gene also triggered ROS production in cells. In Arabidopis two genes (AtrbohD and AtrbohF) are reported to be associated in ROS production in response to ABA and mutant of these genes showed reduced ROS production and cell death in response to pathogen infection (Kwak et al. 2003). CSN5B in Arabidopis is involved in regulatory role of Abscisic acid (Wang et al. 2013). Aminocyclopropane-1-carboxylate oxidase 1 gene involved in ethylene production has been implicated in cucumber for aphid resistance (Liang et al. 2015). Enoyl-CoA hydratase/isomerase family protein is reported to be involved in JA biosynthesis in coffee after leaf miner attack (Cardoso et al. 2014). However, these genes did not show increased activity in Aganni in this study.

Two genes coding PR proteins were induced following gall midge infestation. Many PR genes were up-regulated in resistant variety IR28 against false smut disease in rice (Han et al. 2015). Earlier studies had shown a dramatic 40-fold increase in transcript levels of PR10α in Suraksha with Gm11 gene following infestation (Rawat et al. 2010; Rawat et al. 2013). In contrast, in Kavya with Gm1 gene no such up-regulation of any PR gene was seen (Rawat et al. 2012a). In this study, pathogenesis-related Bet v1 family protein, also member of PR10 family, showed up-regulation in Aganni and 74R line at late hours (Fig. 4). The plasminogen activator inhibitor (PAI) 1, another PR gene induced in Aganni at 24 hai (Fig. 3a), codes for a serine protease inhibitor and belongs to family 7 of PR proteins which are well-known in plant defense against insect pests (Lawrence and Koundal 2002). Expression of PR proteins has been considered as the marker of SAR induction.

Final step towards enhanced systemic resistance has been the modulation of host metabolism towards a possible shift in C/N ratio to favor the host. However, there are reports of C/N shift towards N in wheat during compatible interaction with the Hessian fly (Zhu et al. 2008). This shift probably favors the insect. However, in our study, focusing on an incompatible interaction, a higher number of genes involved in amino acid metabolism were found to be up-regulated (i.e., Serine hy-droxymethyltransferase, Glutamine synthetase—catalytic domain-containing protein, Aspartic proteinase oryzasin-1 precursor, Cysteine synthase—putative and Amino acid transporters) were found to be upregulated (Figs. 3a and 5a) as opposed to genes encoding proteins involved in carbon metabolism (i.e., Erythronate-4-phosphatedehydrogenase and Acyl-CoA synthetase protein involved in CHO and lipid metabolism, respectively) (Fig. 5a).

Four of the genes validated in the study (Abscisic stress-ripening—putative, Erythonate-4-phosphate-dehydrogenase, Aspartic proteinase oryzasin-1 precursor, and peptidylprolylcis/trans isomerase) were up-regulated during both compatible (Fig. 7) and incompatible (Figs. 3 and 4) interaction in Aganni. The last-mentioned gene is reported to be involved in pH homeostasis in cells (Bissoli et al. 2012). It is likely that these genes respond to stress in general and prepare the plant for suitable response based on quantum and nature of stress. Likewise, ten of the genes showed >2-fold induction in 74R line but threshold level was low (≤2-fold) in the parent Aganni (Figs. 5 and 6). This could be possible if residual genome of the susceptible parent carried certain positively acting gene elements that would have been kept under check in the resistant parent. Alternatively, these genes could have been induced either early or later and missed detection with two time points (24 and 120 hai) of sampling. Such instances have also been reported in rice (Raorane et al. 2015) with reference to yield under drought related QTLs. However, more studies need to be carried out to understand the phenomenon.

Conclusions

SSH cDNA library was generated from the infested and uninfested Aganni meristematic stem tissues to identify key genes involved in the resistance pathway. Our results suggested involvement of NBS-LRR, PR, heat shock protein, and NAC domain protein coding genes, earlier observed to confer HR+ resistance in Suraksha. In addition, two genes viz., OsAPx1 and OsAPx2 (ROI—scavenging-enzyme) were found to be up-regulated in Aganni suggesting their possible role in the suppression of HR. Further, resistance pathway in Aganni did not share features observed in Kavya conferring HR− resistance. We suggest that Aganni has a deviant form of inducible, salicylic acid (SA)-mediated, resistance but without HR.