Plants, in particular cereal food crops play a major role in survival of human beings. Unlike animals, plants are sessile and hence, cannot escape stressful conditions, that originate from the abiotic stresses (drought, salinity, metal, and submergence), which may lead to the loss in yield and nutritional value (Rizhsky et al., 2002, 2004; Mittler, 2006; Mittler and Blumwald, 2010; Atkinson and Urwin, 2012). Each abiotic stressors affects the plants at different levels, heat stress reduces the yield of the plants and drought affects its growth (Rizhsky et al., 2002, 2004; Mittler, 2006; Acquaah, 2007; Thakur et al., 2010; Prasad et al., 2011; Vile et al., 2012). The effect of an individual stressor on the plant may modulate its susceptibility to the concurrently combined multiple stresses. Previous studies have shown that water deficit or avoidance to salinity, may increase the susceptibility of plant to biotic stress (Siddiqui, 1980; Xu et al., 2008). Plants are highly developed from all the surrounding defense responses by acclimatizing to CAbS (Mickelbart et al., 2015). The exertion of combined stresses triggers the activation of several ion channels leading to the accumulation of hormonal changes, which in turn increases the production of reactive oxygen species (ROS). ROS acts as signaling molecules and are also expected to cause cellular damages (Mittler, 2002; Apel and Hirt, 2004; Kissoudis et al., 2014). Upon exposure to stress conditions, non-specific signals are transduced, which in turn generate physiological, molecular and metabolic responses that eventually alters the stress tolerance (Rizhsky et al., 2004; Koussevitzky et al., 2008; Atkinson et al., 2013; Iyer et al., 2013; Prasch and Sonnewald, 2013; Rasmussen et al., 2013; Lata et al., 2015; Ramegowda and Senthil-kumar, 2015). Thus, the overall effect of a stress combination may be entirely different from the individual stresses, which makes it appropriate to analyze the effect of a combination of stress by subjecting them to a CAbS (Mittler, 2006; Atkinson and Urwin, 2012; Prasch and Sonnewald, 2013). How plants distinguish the CAbS leading to gene regulation is far from clear. Global agricultural production will face abounding challenges over the coming decades, mainly due to climate change. It will be a tough task for the farmers to increase the production under adverse climatic conditions, where combination of stresses will play a dominant role (Munns and Tester, 2008; FAO, 2009; Zhao and Running, 2010; Peters et al., 2011; Shanker and Venkateswarlu, 2011; Kissoudis et al., 2014). So understanding the molecular responses to these combined stresses in crop plants are unconditionally needed for the future food security. Apart to literary survey, huge amount of transcriptomic data are available in the field of abiotic stress biology. Comparison of the transcriptomic data of plants exposed to the individual and combined stresses is expected to reveal the importance of the molecular cross-talks specific to a particular stress or CAbS. The available transcriptomic information can thus be utilized to understand responses of plants to the combined stress (Ma et al., 2007; Narsai et al., 2013a). Easily accessible meta-analysis data are vital for this direction. Arabidopsis thaliana and O. sativa subjected to bacterial and water deficit stresses resulted in a number of commonly regulated stress-responsive genes by meta- analysis of microarray data (Shaik and Ramakrishna, 2013, 2014). To our knowledge, this is the first time an effort was made to compare the transcriptomic data of rice plants for understanding the molecular mechanisms involved in specific and CAbS responses. Herein, the comprehensive meta-analysis was performed on rice transcriptome datasets selected from 8 freely accessible abiotic stress experiments to identify commonly regulated genes. We predicted that 30 AbS responsive genes were expressed across the CAbS. In addition, similar computational analysis of these genes confirmed their expression pattern observed in the microarray. This analysis led to the identification of unique and combined sets of AbS genes for further characterization toward outlining their functional role of AbS signaling in rice.

The overall frame work from data mining followed by grouping and analyzing the CAbS responsive genes of this transcriptomic study is illustrated in framework Figure 1.

Individual and combined abiotic stressors, such as drought, salinity, metal, and submergence in water, adversely affect plant growth and yield (Rizhsky et al., 2002, 2004; Mittler, 2006; Mittler and Blumwald, 2010; Atkinson and Urwin, 2012). Plant's response to the continuous exposure of CAbS conditions are more complex that are mostly influenced by diverse and antagonistic signaling pathways, which may interact and/or impede each other (Suzuki et al., 2005; Mittler and Blumwald, 2010). Meta - analysis is a way of combining the results of all the studies. It has been used to identify the genes commonly expressed under different stress conditions in recent studies (Chang et al., 2013; Shaik and Ramakrishna, 2013, 2014; Ramu et al., 2016). Here we report the transcriptomic data of O. sativa for eight different abiotic stresses processed using INMEX and the heatmap was derived based on the expression values of the stress responsive genes. Based on this heatmap and physical map data, 30 commonly expressed AbS responsive genes were identified and subjected to Rice DB to have an insight on the developmental tissue-specific expression of genes. Further these AbS responsive genes were chosen for expression profiling under CAbS. Public microarray hybridization of Rice DB expression values showed developmental tissue-specific expression patterns of 28 genes out of 30 AbS responsive genes based on the available transcriptomic data. The plants are affected by stress under different developmental tissues (Jin et al., 2013; Narsai et al., 2013b) and thus a large set of transcriptomic data are available to study the expression analysis leading to a better understanding of different molecular mechanisms regulating AbS (Liu, 2015). Hence these 28 genes which showed differential expression pattern in the 41 different developmental tissues showed a higher expression level of AbS responsive genes from multiple tissue and their expression during the individual or combined stresses. Thus, suggesting their multiple roles in diverse molecular and physiological activities. This data could be exploited for selecting candidate genes showing distinct expression pattern for explaining their functional roles. It highlighted the meta-analysis of genes expressed in different developmental tissues. We outlined information on co-regulation among genes under AbS conditions (Narsai et al., 2013b). By identifying each protein family involved in the stress response, the molecular mechanism of the plant stress response can be predicted. These results support the phase-specific expression of AbS responsive genes and are presumed to get expressed only during reserve deposition phase of plant tissues and seed development. This expression profiling data would facilitate the combinatorial usage of candidate genes in the transcriptional regulation of AbS related protein synthesis. Further, this supplementary data also serves as a base for conducting overexpression studies of potential genes in various plant tissues in order to increase the AbS responsive protein content in rice.

Physical mapping of 30 AbS responsive genes on the 12 chromosomes of O. sativa showed, that a maximum number of AbS responsive genes were present on chromosomes 5 (6 genes; ~20%) and 2 (4 genes; ~13.33%) and these physical regions contains higher accumulation of gene clusters at both upper and lower end of the arms. A minimum number of genes were present on chromosome 3, 7, 9, (3 genes; ~10% each) and 1, 4, 11, 12, (2 genes each; ~6.66% each) and a minimum of 1 gene each (~3.33%) were present on chromosomes 6, 8, and 10. It speculates lower accumulation of genes as demonstrated by Muthamilarasan et al. (2014a). It revealed the AbS responsive genes distribution of chromosomes among the genome.

Comparative mapping of AbS responsive proteins on rice, sorghum, foxtail millet and maize databases were performed to understand the orthologous connections between the grass species genomes. Rice AbS genes showed maximum synteny with maize and foxtail millet genes (~70%), followed by sorghum (~67%), however, higher percentage of orthology was expected between rice, maize and foxtail millet owing to their extensive synteny at gene level. Rice AbS responsive genes were found to be more homologous to maize and foxtail millet highlights its close evolutionary relationships while the decrease in synteny with sorghum due to the increase in genetic distance across the phylogeny (Bennetzen et al., 2012; Zhang et al., 2012). This pattern of decreasing synteny was also observed in the comparative mapping of NAC TFs (Puranik et al., 2013), WD40 genes (Mishra et al., 2014), C₂H₂ zinc fingers (Muthamilarasan et al., 2014a), MYB TFs (Muthamilarasan et al., 2014b), AP2/ERFs (Lata et al., 2014) and 14-3-3 proteins (Kumar et al., 2015). This comparative map data would assist in understanding the evolutionary process of AbS responsive genes among the Poaceae members.

The present report predicted certain key CAbS genes like MATH (TRAF homology)-BTB and NAC domains. MATH-BTB domain genes were found in large number at O. sativa and Arabidopsis (Gingerich et al., 2007), that are reported to be involved in expansion and diversification events in monocots and dicots (Gingerich et al., 2007). MATH-BTB domain are responsible to activate the ubiquitination that plays a candid role in the development, homeostasis, physiology, hormonal balance, cell cycle, circardian rhythms, photomorphogenesis, ecological adaptation, disease resistance, and abiotic stress tolerance (Drought and salinity) (Zapata et al., 2007; Qi et al., 2009; Zhao et al., 2013; Kushwaha et al., 2016). NAC domains (TFs) on other hand are commonly induced by CAbS that acts potential candidates to produce plants with improved CAbS tolerance (Wu et al., 2009; Shao et al., 2015). But many the time this overexpression study may lead to negative effects in rice and Arabidosis transgenic plants such as lower yield, late flowering, sensitive to ABA signaling and dwarfing (Nakashima et al., 2007; Hao et al., 2011; Liu et al., 2011; Lu et al., 2012; Mao et al., 2012). Therefore, to gain first insight into the key players and their potential functions of rice CAbS genes during stress response and development, we have explored publically available microarray data for rice. Further, this would also enable the researchers to select and validate the candidate genes from rice.

Commonly shared genes, their respective protein cross talks, and functional association revealed the complexity of abiotic stresses based on seed protein neighborhoods and the configuration of its nodes, connecting edges from the genes that were differentially expressed in abiotic stress studies. AbS encoding proteins and their properties revealed huge difference in the length, isoelectric point, molecular weight, instability index, aliphatic index and GRAVY values of these proteins.

The emerging advancement in physiology and computational approaches has paved way to understand the role of AbS responsive genes in molecular cross talks. Gene regulation has been studied well in all the major food crops and tree species. No such study on CAbS genes has been conducted in O. sativa, for exploring C3 photosynthesis and AbS tolerance mechanisms. Seemingly the importance of these crop and abiotic stress genes, the current study uses well-known computational approaches to detect and describe AbS responsive genes. The identified genes were used for the construction of physical map, gene ontology annotation, comparative mapping, molecular interaction, and subcellular localization predictions. In toting, in silico expression profiling of rice AbS responsive (genes) transcriptomic data was performed to understand the expression pattern of these genes in different developmental tissues. These in silico expression analysis of 30 novel AbS responsive genes showed regulatory functions under combined stress conditions. The present study we hypothesize CAbS responsible proteins may activate various downstream gene(s), (yet to be characterized), which lead to the accumulation of osmolytes such as proline, lysine, glycine, betaine, sucrose, fructose, myo-inosital, and mannitol (these osmolytes plays important role in AbS tolerance and avoidance mechanisms) to improve the oxidative stress by scavenging chemically active ROS molecules and consequently provide CAbS endurance by altering the molecular and physiological process of the plant.

The in silico expression analysis infers role of CAbS in ABA dependent/ independent manner and affects regulation of ROS quenching responsible genes. Though further studies are needed to establish the exact mechanism of action of the CAbS key players in plant under diverse AbS's. In addition to the advanced technologies such as RNA-seq needs completely sequenced models are prerequisite to generate high quality transcriptomic data for understanding the regulatory mechanism of CAbS. Further validation of the current study using crops such as A. thaliana, Setaria italica and O. sativa is speculated to throw more light in depicting the function of key genes in the development of CAbS tolerance.

MR and PM conceived and designed the experiments. PM, SRK, and RP performed the experiments. PM analyzed the results and wrote the manuscript. MR approved the final version of the manuscript.