Genome-wide identification and expression analysis of sucrose nonfermenting-1-related protein kinase (SnRK) genes in Triticum aestivum in response to abiotic stress

The SnRK gene family is a key regulator that plays an important role in plant stress response by phosphorylating the target protein to regulate subsequent signaling pathways. This study was aimed to perform a genome-wide analysis of the SnRK gene family in wheat and the expression profiling of SnRKs in response to abiotic stresses. An in silico analysis identified 174 SnRK genes, which were then categorized into three subgroups (SnRK1/2/3) on the basis of phylogenetic analyses and domain types. The gene intron–exon structure and protein-motif composition of SnRKs were similar within each subgroup but different amongst the groups. Gene duplication and synteny between the wheat and Arabidopsis genomes was also investigated in order to get insight into the evolutionary aspects of the TaSnRK family genes. The result of cis-acting element analysis showed that there were abundant stress- and hormone-related cis-elements in the promoter regions of 129 SnRK genes. Furthermore, quantitative real-time PCR data revealed that heat, salt and drought treatments enhanced TaSnRK2.11 expression, suggesting that it might be a candidate gene for abiotic stress tolerance. We also identified eight microRNAs targeting 16 TaSnRK genes which are playing important role across abiotic stresses and regulation in different pathways. These findings will aid in the functional characterization of TaSnRK genes for further research.


Genome-wide identification and expression analysis of sucrose nonfermenting-1-related protein kinase (SnRK) genes in Triticum aestivum in response to abiotic stress Shefali Mishra, Pradeep Sharma * , Rajender Singh, Ratan Tiwari & Gyanendra Pratap Singh
The SnRK gene family is a key regulator that plays an important role in plant stress response by phosphorylating the target protein to regulate subsequent signaling pathways. This study was aimed to perform a genome-wide analysis of the SnRK gene family in wheat and the expression profiling of SnRKs in response to abiotic stresses. An in silico analysis identified 174 SnRK genes, which were then categorized into three subgroups (SnRK1/2/3) on the basis of phylogenetic analyses and domain types. The gene intron-exon structure and protein-motif composition of SnRKs were similar within each subgroup but different amongst the groups. Gene duplication and synteny between the wheat and Arabidopsis genomes was also investigated in order to get insight into the evolutionary aspects of the TaSnRK family genes. The result of cis-acting element analysis showed that there were abundant stress-and hormone-related cis-elements in the promoter regions of 129 SnRK genes. Furthermore, quantitative real-time PCR data revealed that heat, salt and drought treatments enhanced TaSnRK2.11 expression, suggesting that it might be a candidate gene for abiotic stress tolerance. We also identified eight microRNAs targeting 16 TaSnRK genes which are playing important role across abiotic stresses and regulation in different pathways. These findings will aid in the functional characterization of TaSnRK genes for further research.
Bread wheat (T. aestivum L.) is a major cereal crop and an important source of carbohydrates and protein in the human diet, accounting for 20% of daily calorie consumption. The most significant economic feature is grain yield, which is influenced by a variety of biotic and abiotic stressors. By 2050, it is expected that the demand for wheat will increase by 60% 1 . Plants use a variety of molecular defence mechanisms to deal with abiotic stresses such as salt, drought, and heat. Plants respond to environmental stresses in two ways: gene expression regulation and protein modification 2 . Protein kinase-mediated phosphorylation and dephosphorylation are important in protein modification 3 . SnRKs (Sucrose nonfermenting 1 (SNF1)-related protein kinases) are a group of protein kinase genes that have a role in a variety of physiological activities 4 . Based on their sequence similarities and gene architectures, plant SnRKs may be split into three subfamilies: SnRK1, SnRK2, and SnRK3 4,5 . The SnRK1 subfamily has a highly conserved N-terminal protein kinase (Pkinase) domain, which is similar to SNF1 in yeast and AMPKs in mammals 6 . The SnRK2 and SnRK3 subfamilies are unique to plants, and both show more variability than the SnRK1 subfamily members in terms of plant diversity. A conserved P kinase domain and a C-terminal variable adjusting domain are found in members of the SnRK2 family 7 . SnRK3, known as CIPK (CBL-interacting protein kinases), also has conserved N-terminal protein kinase domains and NAF domains, as well as PPI domains at the C-terminus 8,9 . Plant cells respond to starvation and metabolic stress through the SnRK1 family of genes. Catalytic components of heterotrimeric complexes, SnRK1 kinases interact with two additional subunits 10 . SnRK1 was shown to be involved in the stimulation of sucrose synthase expression and had a key function in carbohydrate metabolism control in S. tuberosum 11 . Low energy stress (e.g., darkness and hypoxia) may also cause SnRK1 nuclear Phylogenetic analysis of SnRK genes family. To study the evolutionary relationships among SnRK proteins and their classification, we performed unrooted phylogenetic tree analysis using the full-length amino acid sequences of 174 SnRKs genes of T. aestivum, 38 of A. thaliana and 50 of O. sativa (Fig. 1). The clustering of 38 AtSnRKs into three groups was reported earlier 3 . Based on the phylogenetic analysis and domains presence, 174 TaSnRKs were also divided into three groups in this study. Of these, 14 proteins in the TaSnRK1 subfamily have Pkinase (PF00069 of Pfam), UBA (PF00627), and KA1 (PF02149) domains, whereas 65 proteins in the TaSnRK2 subfamily have Pkinase domains with strong resemblance to AtSnRK2 subfamily, and 95 proteins in the SnRK3 subfamily have Pkinase and NAF (PF03822) domain (Fig. 1).

Motif composition and gene structural analysis of the SnRK gene family in T. aestivum. MEME
analysis showed that 10 conserved motifs were identified in TaSnRK proteins ( Fig. 2A). The conserved motif 's sequence and length details have been listed in Supplementary Table S1. The conserved Pkinase domain including the pattern 1, 2, 3, 5, 6 was discovered in all TaSnRK genes in this investigation ( Supplementary Fig. 1). Furthermore, TaSnRK genes from the same subfamily have comparable pattern compositions, but TaSnRK genes from different subfamilies have varied motif compositions. TaSnRK1 subfamily genes have 9 motif (motifs 1, 2, 3, 4, 5, 6, 7, 8 and 10) while TaSnRK2 subfamily genes had either motifs 1, 2, 4, 6, 8 or motifs 1, 2, 3, 4, 5 and 10. TaSnRK3 subfamily genes had 10 motifs while a few of them do not have any motif ( Fig. 2A). In conclusion, the comparable gene architectures and conserved motif compositions of SnRK genes within the same subfamily substantially support the phylogenetic analysis based subfamily classifications.
The exon-intron structure of TaSnRK genes showed that the TaSnRK1 subfamily genes have more than 10 exons, while the TaSnRK2 subfamily genes have 2-34 exons followed by TaSnRK3 subfamily which have 1-33 exons (Fig. 2B). Notably, 14 genes are intron-less. In addition, the TaSnRK3 family is divided into two subgroups. The genes in SnRK3 subgroup 1 had more than 10 exons, while the genes in subgroup 2 had less than four exons. www.nature.com/scientificreports/

Analysis of chromosomal location and orthologous genes in T. aestivum. The chromosomal dis-
tribution of all TaSnRK genes across the genome was investigated which provides useful information on the genomic regions (Fig. 3). The A sub-genome had 56 TaSnRK genes, comprising 2 genes from TaSnRK1 subfamily, 21 genes from TaSnRK2 subfamily, and 33 genes from TaSnRK3 subfamily, whereas the B sub-genome had 61 genes, comprising 8 genes from TaSnRK1 subfamily, 21 of TaSnRK2 subfamily, and 32 of TaSnRK3 subfamily. However, 4 genes of TaSnRK1 subfamily, 23 genes of TaSnRK2 subfamily, and 30 genes of TaSnRK3 subfamily were found on the D sub-genome ( Supplementary Fig. S2A). These findings suggested that TaSnRK genes were distributed randomly throughout the A, B, and D chromosomes ( Supplementary Fig. S2B).
In this study, 57 orthologous pairings were identified between T. aestivum and H. valgare, while 166 between T. aestivum and A. thaliana. However, 53 orthologous genes were found within wheat species for instance between T. aestivum and T. urartu, while 102 orthologous genes between T. aestivum and Ae. dicoccoides and 63 between T. aestivum and Ae. tauschii (Supplementary Table S3).
We identified 11 segmental events across different chromosomes and 2 tandom duplication occurrences in the same chromosome using the BLAST and MCScanX techniques. The findings revealed that gene duplication may have produced some TaSnRK genes, and that segmental duplication events were important in the growth of TaSnRK genes in the wheat genome. We also looked into the frequency of tandem duplication occurrences. There were 45 TaSnRK gene pairs found in this area all of which were strongly related. (Supplementary Table S4). However, the identities of these were > 80%, indicating that they were included into tandem duplication occurrences.
We looked at the duplication events of the TaSnRK gene in the wheat genome since gene duplication has a big impact on the emergence of new functionalities and gene families. In addition, 55 gene pairs were found to be duplicated as shown in Fig. 4.
Furthermore, the synteny of SnRK gene pairs between T. aestivum genome and A. thaliana genome was performed. The result showed that 166 SnRK genes of T. aestivum exhibiting syntenic relationship with AtSnRK genes (Fig. 5 and Supplementary Table S3), suggesting that these genes might have contributed to the evolution of TaSnRK gene family. K s values, K a values, K a /K s ratios and divergence time of paralogous and orthologous on SnRK family genes were estimated to assess the evolutionary constraints undertaking (Supplementary Table S4). The K a /K s ratios of the majority of segmentally duplicated TaSnRK gene pairs were < 1, the mean values of TaS-nRK3 gene pairs (K a /K s = 0.30) and TaSnRK2 (K a /K s = 0.35) were lower than TaSnRK1 (K a /K s = 0.41). Furthermore, segmental gene divergence time spans from 18.76 to 34.97 Mya. These findings showed that the TaSnRK gene family may have been subjected to significant purifying selection during evolution.
Promoter analysis. PlantCARE was used to look at cis-elements (1.5 kb upstream from ATG) in order to better understand the function and regulatory processes of TaSnRK genes. We found 129 out of 174 TaSnRK genes had cis-elements ( Supplementary Fig. S3, Supplementary Table S5). MyB, ABRE, and LTRE cis-elements were found to be involved in drought, ABA, and low-temperature responses. Auxin (9.77%), MeJA (51.72%), and Gibberallin (11.49%) cis-elements were found in phytohormones. It was also shown that most genes have many cis-element types. In addition, the TaSnRK1 (30.50) family had more cis-elements than the TaSnRK2 (19.29) or TaSnRK3 (23.81) families (Supplementary Table S5). Finally, the cis-elements study revealed that most TaSnRK genes can respond to a variety of environmental challenges, and that distinct subfamily genes can be regulated in various ways.
MicroRNAs targeting TaSnRK. The role of miRNAs in controlling the expression of TaSnRK genes have been investigated using the psRNATarget server. We predicted 16 TaSnRK genes as possible targets for eight different miRNAs (Table 2). Tae-miR319 implicated in the regulation of seven TaSnRK genes (TaSnRK3.33,

Functional annotation of Hub genes and interacting network analysis.
Based on their involvement in a biological and cellular process, we studied the function of potential hub genes. String database contains a collection of predicted and experimentally confirmed protein-protein interactions in wheat and other species. However, wheat SnRK found in string database is linked to them as well as numerous metabolic and regulatory processes. SnRK were defined based on the interaction observed. TaSnRK2.48 is included in the first, which serves as the network's (Fig. 6). Here, the cluster is directly linked to TaSnRK3 subfamily (TaSnRK3.7, TaSnRK 3.14, TaSnRK  www.nature.com/scientificreports/     The expression patterns of TaSnRK family genes in wheat tissues under abiotic stresses were evaluated (Fig. 7B). A total of 16 genes with high expression levels in all studied tissues under abiotic stresses (log 2 -based values > 5) were assigned to sub-group1. SnRK3.40, for example, was shown to be highly expressed in all vegetative organs, with log 2 -based average values. In sub-group2, the expression levels of 55 TaSnRK genes were significantly lower across all detected tissues (log 2 -based values > 2). In sub-group3, 103 TaSnRK genes were involved with the lowest expression levels in diverse tissues at various stages. Meanwhile, sub-group1 had one TaSnRK1, 6 TaSnRK2 genes and 9 TaSnRK3 genes; Sub-group2 had 8 TaSnRK1, 21 TaSnRK2, and 26 TaSnRK3 genes and Sub-group3 had 5 TaSnRK1, 38 TaSnRK2, and 69 TaSnRK3 genes (Fig. 7A). The expression pattern of TaSnRK genes was nonetheless studied using drought, salinity and heat stresses 26 . The expression levels of TaSnRK genes have been significantly changed under various abiotic stresses (Fig. 7B). TaSnRK3.17 and TaS-nRK3. 18, for example, were highly stimulated by all treatments, whereas TaSnRK3. 15 and TaSnRK3.16 responded to dehydration by increasing their levels of expression. But, TaSnRK 3.37, TaSnRK3.45, and TaSnRK3. 46 have demonstrated high expression levels in response to heat and drought stress (Fig. 7B). These results demonstrated that TaSnRKs have a large variety of patterns of expression and that even genes within the same subfamily had different patterns of expression.

Validation of TaSnRK for abiotic stresses using qRT-PCR.
Members of the SnRK family serve critical roles in plant abiotic stress response. In plants, however, the specific mechanism underpinning SnRK function is not fully understood. The expression analysis of SnRK2s and SnRK3s in leaf tissue was identified by qRT-PCR following different stress treatments at different time intervals. This was to study the function of TaSnRK2 and TaSnRK3 genes in responding to salt, heat, and drought stress (Fig. 8).

Discussion
This study identified 174 TaSnRK genes in the T. aestivum genome, which were classified as TaSnRK1, TaSnRK2, or TaSnRK 3 based on their subfamily classification. The TaSnRK gene family was carefully searched, including evolutionary linkages, protein patterns, gene architectures, gene duplication, distributions of chromosomal, and the promoter cis-elements. This research progresses towards the future functionality of SnRK genes in order to improve abiotic stress adaption of plant. SnRK genes were already reported in A. thaliana 4 , O. sativa 27 , B. distachyon 28 , and E. grandis 29 having 39, 48, 44, and 34, respectively. The number of TaSnRK genes in the genome of T. aestivum is substantially higher than in diploid plants. There were 14 TaSnRK1 genes, 65 TaSnRK2 genes , and 95 TaSnRK3 genes were discovered and classified into three subfamilies. According to more detailed description, T. aestivum and other species have similar member proportions for each subfamily. T. aestivum is a naturally occurring amphidiploid evolved from T. urartu (AA), A. speltoides (BB), and A. tauschii (DD). There were 56, 61, and 57 TaSnRK genes discovered in the A, B, and D sub-genomes, respectively demonstrating that SnRK genes had a similar functional role in progenitor species.
Although the conserved domains of the SnRK subfamily genes differ, the N-terminal protein kinase domain is retained. It has been discovered that SnRK3 subfamily genes interact with CBLs in a calcium-dependent manner due to the NAF domain. Furthermore, the NAF domain identifies a set of heterologous kinases that CBL calcium sensor protein targets and participate in a range of signalling cascades 8 . According to this study, distinct www.nature.com/scientificreports/ TaSnRKs subfamily genes shared different types of conserved domains. This might imply that the TaSnRK genes family is functionally diverse based on the domains contained. In the AtSnRK and TaSnRK genes, certain subfamily genes showed substantial structural exon-intron divergences and gene length differences. In genes with fewer introns, increased expression in plants has been previously reported 30,31 . A compact gene structure with few introns has enabled rapid activation and responsiveness to different environmental conditions 31 . However, when the transcriptome data used in this study was combined, we found no evidence that TaSnRK gene with fewer introns had shown higher expression levels than the other TaSnRKs genes.
According to accumulating data, gene activity was often linked to discrepancies in the promoter region 32 . In gene promoter regions, cis-elements played a major role in controlling gene expression during development and environmental changes 33,34 . TaSnRKs had several cis-elements, including growth hormones, MyB, ABRE, and LTR according to promoter analysis in this investigation. Most gene promoters contained at least one of these components, demonstrating that many TaSnRKs were capable of responding to a variety of abiotic stresses while  www.nature.com/scientificreports/ also promoting growth. When gene expression profiles from TaSnRKs with MyB and ABRE cis-elements were merged under drought stress, TaSnRKs with MyB and ABRE cis-elements increased by an average of 6.3-fold, but TaSnRKs without cis-elements only increased by 3.5-fold. As a result, cis-elements analysis can help with gene function studies, particularly gene expression patterns under different stress conditions. TaSnRK gene expression levels were analysed using transcriptome data in different tissues and organs of T. aestivum 26 . The research results showed that expression patterns of these genes are divided into three categories (Fig. 7). In this study, it we found that subgroup-2 TaSnRKs contain fewer cis-elements than TaSnRKs in subgroups-1 and -3 in their promoters. Every gene in subgroup-1 has an average of 5.08 Auxin, 13.55 MeJA, and 8.47 ABRE, 1.69 MYB, 3.38 LTR compared with each gene in subgroup3 and averages of 2.05 in Auxin, 11.08 of MeJA, 1.43 of Gibberellins and 6.67 ABRE, 1.43 MYB, 0.61 LTR, each gene in subgroup 2 with a total of 0.35 Auxin, 9.12 MeJA, 4.56 Gibberellin, 3.50 ABRE, 1.40 MYB, 0.35 LTRE. These data showed that TaSnRK activity is linked to promoter region differences.
The roles and functions of several TaSnRKs in response to different abiotic stresses were also determined. Drought stress findings showed that ABA production and A. thaliana signals in response to drought were orthologous to AtSnRK2.3 39 and imply that TaSnRK2.11 and AtSnRK2.3 play the same role in response to drought stress. The extreme expression changes in T. aestivum against effects of drought, salt, thermal stress and ABA induction were reported in TaSnRK2. 8,TaSnRK2.12,TaSnRK3.11,TaSnRK2.16,TaSnRK3.23 and TaSnRK3.83 whereas its orthologs, AtSnRK2.2, could also respond to osmotic stress and ABA induction in A. thaliana. This shows that under different conditions the TaSnRK2.11 gene may be activated substantially.
Previous research has shown that ABA-independent regulation of SnRKs occurs in terrestrial plants, such as Arabidopsis SnRK2.1, SnRK 2.4, SnRK 2.5, SnRK 2.9, and SnRK 2.10, which are activated by osmotic stress following an ABA-independent pathway 7 . Arabidopsis ABA-independent SnRKs control stress related gene/ transcripts under hyperosmotic conditions, complementing the action of ABA-dependent SnRK2s function 35 . As reported in other plants, ABA-independent SnRK2s in wheat also showed sensitive reaction to osmotic stress. Specific responses to low nitrogen or sulfur deprivation 36 , however, appear to be initiated in an ABA-independent manner, as in other plants. These findings support the hypothesis that the plant-specific SnRK2 subfamily is important in stress response signalling both in Arabidopsis and wheat. These pathways are not solely responsible for energy-saving decisions, but they do resulting complex remodelling of cell metabolism, as evidenced by the interactions with DNA repair and maintenance pathways and TOR in Arabidopsis 37 network as indicated by STRING studies. The fact that a single stress induces the expression of a large number of SnRK2 genes implies that there is a significant compensating impact or pleiotropy within this family in wheat. It is well known that most stresses result in oxidative damage 38,39 . The third SnRK subfamily, the other hand, played an important role in response to osmotic, salt, and heat stresses, because it consists of proteins kinases interacting with calcineurin B-like calcium binding domains 7 which are mostly involved in drought and salt resistance, being the SOS (salt overly sensitive) mechanism being the best-known 40 .
The findings of this study provide a thorough description of the SnRK gene family in T. aestivum. It helps us to better understand the biological role of specific TaSnRK genes in T. aestivum. The study presented just a fundamental characterisation of the TaSnRK genes and a comprehensive functional validation would be required to hold the importance of the SnRK family.

Conclusions
SnRK genes are involved in a variety of signalling pathways, including responses to biotic and abiotic stresses. In this study, SnRK gene family has been intensively investigated in wheat. A total of 174 TaSnRK genes were discovered and categorized into three subgroups based on motif composition and gene structural similarity within each subfamily. Phylogenetic analyses of SnRK genes in A. thaliana and O. sativa can also be used to derive the evolutionary characteristics of the TaSnRK genes. Furthermore, the TaSnRK family's microRNA targeting, cis-acting elements, and gene expressions were investigated in order to better understanding the biological role of TaSnRK genes in T. aestivum.

Materials and methods
Identification and characterization of SnRKs. Protein sequences of SnRKs identified in related plant species were obtained from the Phytozome database (http:// www. phyto zome. net/) and the Rice Annotation Project (RAP) (https:// rapdb. dna. affrc. go. jp/). BLASTP searches were performed against the bread wheat protein sequences (ftp:/ftp.ensemblgenomes.org/pub/plants/release-51/fasta/triticum aestivum/pep/) using an e-value cut-off of 0.0001 and bit-score > 100. Potential SnRK candidates were discovered using the methods described above. Following the removal of duplicate results, the final sequences were checked for the existence of SnRK related domains using HMMscan (https:// www. ebi. ac. uk/ Tools/ hmmer/ search/ hmmsc an), the SMART database (http:// smart. embl-heide lberg. de/) 41  www.nature.com/scientificreports/ Motif composition and gene structural analysis of the SnRK gene family in T. aestivum. The Multiple Expectation Maximization for Motif Elicitation (MEME) online tool 46 (http:// meme. sdsc. edu/ meme/ itro. html) was used to find conserved motifs in TaSnRK proteins with the following parameters: The number of repetitions is unlimited, the maximum number of motifs is ten, and the ideal motif length is six to one hundred residues. The exon-intron structures of TaSnRK family genes were analysed using the Gene Structure Display Server online application (GSDS v.2.0: http:// gsds. cbi. pku. edu. ch) based on the gff3 data file 47 .

Analysis of chromosomal location and orthologous genes in T. aestivum.
Using MapChart version 3.0 48 , the chromosomal coordinates of all TaSnRK genes were mapped to 21 chromosomes of the wheat genome based on physical location from the Plant ensemble database. All T. aestivum gene sequences were aligned using BLASTP with an e value of 1e −10 to find gene duplication. The pattern of duplicated SnRK were classified as segmental, tandem duplications using MCScanX with default parameters 49 . A tandem duplication is defined as a chromosomal area of less than 200 kb that contains two or more genes 50 . TBtools were used to exhibit synteny relationships of the orthologous SnRK genes between T. aestivum and A. thaliana, the syntenic analysis maps and synonymous (Ks) and non-synonymous (Ka) substitution of each duplicated TaSnRK gene 51 .

cis-Elements in promoter regions of TaSnRKs.
The wheat genome database was used to extract upstream sequences (1500 bp) from the start codon of each TaSnRK gene, which were subsequently utilised for cis-element distributions in promoter regions using PlantCARE software (http:// bioin forma tics. psb. ugent. be/ webto ols/ plant care/ html/) 52 .

Prediction of MIR genes targeting TaSnRK.
The TaSnRK gene transcript sequences were obtained from the wheat genome database. The psRNATarget service was used to examine the matured miRNA sequences 53,54 and the TaSnRK transcript sequences with default settings 55,56 .
Analysis of protein-protein interactions. The STRING v1054 databases were used to identify proteinprotein functional interactions. SnRK protein sequences were uploaded to the STRING 57 application, and the database was searched with A. thaliana as the reference organism. All identified interaction partners were gathered and searched against the A. thaliana genome using blast software at e-value 1−e10.
Using Cytoscape 58 , the one best-hit for each gene was selected for the creation of a PPI network. Finally, the top hub gene from the interaction network was predicted using Cytoscape's cytoHubba plugin (Cytoscape Consortium 2016).
RNA-seq derived gene expression profiling. The value of TPM (transcripts per million) for each TaS-nRK was obtained from the expVIP database (http:// www. wheat-expre ssion. com/). Clustvis (https:// biit. cs. ut. ee/ clust vis/) was used to create heatmaps 59 . Plant material and growth conditions. In this experiment, seeds of bread wheat genotypes (C-306, WL-711, RAJ3765, HS240, Kharchia 65, and HD2687) were procured from Germplasm Unit, ICAR-Indian Institute of Wheat and Barley Research, Karnal, India. Seeds were sterilised with 1% sodium hypochloride for 10 min and then rinsed with distilled water three times and germinated in petri plates at 22 °C under controlled conditions. Seedlings were moved to a culture bottle filled with full-strength Hoagland's solution after 5 days of germination and allowed to grow for seven days. Each genotype was seeded in two sets of three biological replications. For drought stress, two contrasting wheat genotypes, C306-drought tolerant and WL711, drought susceptible were used. After 14 days of growth in Hoagland's solution, one set of seedlings was given osmotic shock using 25% (v/v) polyethylene glycol (PEG) 6000 for 24 h, while untreated used as control 60 . Leaf samples from control and stressed seedlings were harvested at above mentioned time intervals for expression analysis. For heat stress, two contrasting wheat genotypes were chosen: RAJ3765-heat resistant and HS240-heat sensitive. These plants were kept at 42 °C for 3 h (at Basal), followed by at 37 °C for 3 h (at Normal), and finally at 42 °C for 3 h (at Acquired). At the time interval stated above, leaf samples from the basal and acquired stress levels were collected. Kharchia 65-salt resistant and HD2687-salt sensitive wheat genotypes were utilised to study salt stress. Two week old seedlings of both genotypes were subjected to 150 mM NaCl treatment. The leaf samples were collected 12 h and 24 h after the treatment. All obtained samples were wrapped in foil and immediately frozen in liquid nitrogen at − 80 °C for total RNA isolation.
RNA isolation and real time PCR analysis. RNA was extracted using TRIzol Reagent according to the manufacturer's instructions. To get DNA-free RNA, the extracted RNA was treated with DNase I (NEB, USA). The first strand cDNA synthesized from 1 g of total RNA by using Superscript-III reverse transcriptase (Invitrogen, USA). The cDNA was diluted to 1:2 for real-time qRT-PCR analysis, and 1.5 µL of the diluted cDNA was utilised as a template in a 20 µL reaction volume according to the manufacturer's instructions. Real time quantitative RT-PCR analysis was carried out by using the BIO-RAD CFX96 using SYBR Green (Bio-Rad). The endogenous control β-actin was used to standardise the expression data 61 . Using the 2 −ΔΔCt method, the expression was measured as a relative fold change 62 . The error bars show the standard deviation of the three biological replicates' expression. www.nature.com/scientificreports/