Review epigenetic literature for salt stress effects

Uncovering Differentially Methylated Regions (DMRs) in a Salt-Tolerant Rice Variety under Stress: One Step towards New Regulatory Regions for Enhanced Salt Tolerance

We analyzed genome wide DNA methylation of a salt-tolerant rice variety under salinity and identified a set of differentially methylated regions (DMRs) between control and stress samples using high-throughput sequencing of DNA immunoprecipitated with the 5-methylcytosine antibody (MeDIP-Seq). The examination of DNA methylation pattern at DMRs regions revealed a general tendency for demethylation events in stress samples as compared to control. In addition, DMRs appear to influence the expression of genes located in their vicinity.

Following our previous studies [13] we have furthered investigated the patterns of DNA methylation in 'Pokkali', a rice variety that simultaneously shows a great capacity to tolerate salinity stress and to rapidly shape DNA methylation levels when exposed to salinity.

The percentage of uniquely mapped reads was considerably higher on the non-immunoprecipitated sample (approximately 50%) contrasting with approximately 25% for the immunoprecipitated samples (Table 1). Regarding the genome coverage, approximately 7.5% of cytosines were covered by at least one uniquely mapped read (Table 1).

The analysis of differential methylation based on MeDIP-Seq data, using the MEDIPS program, as mentioned in the methods section, enabled the identification of 53 DMRs between control and salt stress samples. The DMRs that were close to each other (less than 500 bp) were merged originating 22 DMRs (ranging from 100 to 1000 bp) (Table 2). Although all methylation contexts were present (CG, CHG, and CHH), in DMR2 the methylation was mainly in the CHH context, while in DMR15 the CHG context was predominant.

The DMRs were analyzed according to their position relative to the nearest gene, and more than 70% of the DMRs were in close proximity to genes (less than 2 kbp away) (Figure 2A). Furthermore, over 75% of the DMRs identified were associated with transposable elements and repetitive sequences (Figure 2B).

The functional annotation of genes flanking or overlapping salt-induced DMRs was performed using Blast2GO [35] and multilevel pie charts were generated for the three main classes: cellular component, biological process, and molecular function (Figure S4).

Advances in understanding salt tolerance in rice

Methylation of cytosine bases is one of the well-known processes regulating the gene expression epigenetically under different stresses in plants (Boyko and Kovalchuk 2011). However, the role of alterations in DNA methylation status of rice under salinity stress is poorly explored. Effects of salinity on DNA methylation patterns in four rice genotypes with varying salt tolerance levels have been studied using methylation-sensitive amplification polymorphism (MSAP) technique (Karan et al. 2012). It has been postulated that expression patterns of selected MSAP loci are influenced by cytosine alterations found in the UTRs and exons of such loci, indicating the probable significance of gene body methylation in regulating gene expression under salinity stress. Further, it is also reported that stressed roots are relatively more methylated than the shoots of all the four genotypes, suggesting that different levels of epigenetic responses exist in the root and shoot system during salt stress. Feng et al. (2012) have evaluated DNA methylation patterns of salinity-stressed salt-tolerant and salt-susceptible rice genotypes through methylation-sensitive molecular markers. They showed that hypermethylation was displayed by tolerant rice genotypes, whereas sensitive genotypes showed demethylation, further indicating the possible regulatory role of DNA methylation in conditioning the tolerance to high salinity. Further, the study proposes that DNA methylation changes and the salinity tolerance are inherited to several selfed generations in parallel, implicating the acquisition of transgenerational stress tolerance.

In an attempt to quantify the global DNA methylation under salt stress in salt-tolerant Pokkali, it was found that this genotype showed more rapid demethylation than the salt-sensitive IR29, which may be attributed to the increased demethylase expression in Pokkali under salinity (Ferreira et al. 2015). From this study, it is deduced that the changes in methylation and demethylation are regulated in a complex manner varying with genotypes and tissue type. Our group recently found that methylation status in the promoters of osa-miR393a-TIR1 (Transport Inhibitor Response1) module of two contrasting rice genotypes (FL478 and IR29) was associated with the transcript abundance of this module under salinity stress (Ganie et al. 2016).

Thus, epigenetic changes in different tissues of contrasting rice genotypes may be an essential alternative regulatory mechanism for responding to salinity stress but requires more in-depth exploration to determine its definite role in salinity tolerance.

This is a review paper.

Salt Tolerant and Sensitive Rice Varieties Display Differential Methylome Flexibility under Salt Stress

Global DNA methylation was quantified using the 5-methylcytosine (5mC) antibody and an ELISA-based technique

The salt-tolerant rice variety Pokkali was remarkable in its ability to quickly relax DNA methylation in response to salt stress. In spite of the same tendency for reduction of global methylation under salinity, in the salt-sensitive rice variety IR29 such reduction was not statistically supported. In 'Pokkali', the salt stress-induced demethylation may be linked to active demethylation due to increased expression of DNA demethylases under salt stress. In 'IR29', the induction of both DNA demethylases and methyltransferases may explain the lower plasticity of DNA methylation.

The salt tolerant 'Pokkali' showed a remarkable ability to alter DNA methylation levels with a 70% decline of total DNA methylation upon salt stress. In 'Nipponbare' and 'FL478' the methylation loss was about 54% and 43%, respectively. In contrast, in the salt susceptible 'IR29', the methylation loss under salinity was only 14%, with no-statistical significance (Fig 1A).

This paper is interesting in that it looked at global methylation levels, not specific cytosines.

Salt stress induced variation in DNA methylation pattern and its influence on gene expression in contrasting rice genotypes

Methylation sensitive amplification polymorphism (MSAP) technique was used to assess the effect of salt stress on extent and patterns of DNA methylation in four genotypes of rice differing in the degree of salinity tolerance.

Overall, the amount of DNA methylation was more in shoot compared to root

cytosine methylation changes under salinity as well as gene expression varied with genotypes and tissue types irrespective of the level of salinity tolerance of rice genotypes.

In shoot, salinity stress decreased the percentage of total methylated bands in IR29 (from 59.3% to 51.7%) and Geumgangbyeo (from 48.6% to 34.5%) but increased in Nipponbare (from 46.4% to 57.6%) and Pokkali (from 57.2% to 65.3%). However, in root, the number of fully methylated bands was reduced under salt stress compared with the control in all the four rice genotypes but it was more pronounced in Nipponbare (Table 1B). Interestingly, a general trend of higher level of fully methylated and hemimethylated bands was observed in shoot than root under both control and salinity stress in all four genotypes of rice.

One of the demethylated gene, Os11g23900 (P8) in the shoot of Nipponbare, showed 6-8 fold increase expression in shoot of Bengal, and Pokkali but was downregulated in IR29, while remain unchanged in Nipponbare, Nonabokra, and Geumgangbyeo under salinity (Figure 2A).

Comparative analysis of DNA methylation changes in two rice genotypes under salt stress and subsequent recovery

The rice introgression line IL177-103 and its recurrent parent IR64, which show contrasting salt stress tolerance, were used to characterize DNA methylation changes under salt stress and subsequent recovery using methylation-sensitive amplified polymorphism (MSAP) analysis.

The MSAP results showed that less than 10.5% of detected DNA methylation sites were genotype specific, in line with their similar genetic background.

Salt-induced DNA methylation changes in both genotypes were mostly detected in roots

Bisulphite sequencing reveals dynamic DNA methylation under desiccation and salinity stresses in rice cultivars

Stress treated seedlings were harvested, snap frozen in liquid nitrogen and stored at -80 C till further use.

we analyzed role of DNA methylation under desiccation and salinity stresses in three (IR64, stress-sensitive; Nagina 22, drought-tolerant and Pokkali, salinity-tolerant) rice cultivars via bisulphite sequencing.

Methylation in CG context within gene body and methylation in CHH context in distal promoter regions were positively correlated with gene expression. Hypomethylation in Nagina 22 and hypermethylation in Pokkali in response to desiccation and salinity stresses, respectively, were correlated with higher expression of few abiotic stress response related genes.

DMR-DEGs harboring differentially methylated cytosines due to DNA polymorphisms between the sensitive and tolerant cultivars in their promoter regions and/or coding regions were identified, suggesting the role of epialleles in abiotic stress responses.

Correlation between DNA methylation and gene expression was determined by plotting methylation density of genes expressed at different levels in each sample. Based on FPKM values, genes expressed at very low (<1 FPKM), low (>1-5 FPKM), moderate (>5-25 FPKM) and high (>25 FPKM) levels were categorized. Methylation density in gene body, gene ends and flanking regions was estimated for these sets of genes expressed at varying levels. The correlation between differential methylation and differential gene expression (>2 fold-change with <0.05 q-value) under desiccation/salinity stress as compared to control condition within same cultivar was analyzed by estimating methylation level differences in different sequence contexts within gene body and 2 kb flanking regions.

We generated about (76-86 million) high-quality 90-bp long paired-end reads with >30x sequencing depth for each sample. A total of about 46-55 million uniquely mapped reads covered ~88% of the rice genome and 81.5-82.8% of total cytosine residues in each sample analyzed (Table S1).

Average methylation level of mCs in CG context (85.45-90.37%) was much higher than CHG (66.41-70.15%) and CHH (39.76-45.69%) contexts (Fig. 1B; Fig. S1).

we compared methylation levels between stress treated and control samples for each cultivar. Interestingly, methylation levels showed most variations in CHH context followed by CHG context in response to desiccation and salinity stresses in Nagina 22 and Pokkali, respectively (Fig. 1B).

increased methylation level in Pokkali under salinity stress were observed in both the sequence contexts.

methylation levels in CG context were marginally lower under desiccation stress in Nagina 22 and under salinity stress in Pokkali.

The control and stress treated sample(s) of the same cultivar clustered together, suggesting that methylome divergence among the cultivars is much higher than the methylation changes in response to abiotic stress within a cultivar (Fig. 1C).

pericentromeric and centromeric regions harboring high density of transposable elements (TEs) were found to be extensively methylated in CG and CHG contexts in control and stress treated samples (Fig. 1D). In contrast, higher fraction of mCs in CHH context was detected in gene rich regions under control and stress conditions in all the cultivars (Fig. 1D), suggesting an important role of CHH context DNA methylation in abiotic stress response.

The methylation density at gene ends representing transcription start site (TSS) and transcription termination site (TTS) was lower as compared to their body and flanking regions in all the sequence contexts.

Likewise, methylation density difference between control and salinity stress conditions in IR64 and Pokkali cultivars was analyzed. Higher methylation density in IR64 and lower methylation density in Pokkali were observed in all the sequence contexts under salinity stress in both protein coding genes and TEs (Fig. 2C, D; Fig. S3B).

Interestingly, we observed a positive correlation between DNA methylation in CHH context in distal flanking regions (-500 to -2000 bp) and gene expression in control (Fig. S4) and stress treated samples (Fig. 3). In contrast, an antagonistic correlation between CG and CHG contexts DNA methylation in all other genic regions and gene expression was observed.

Likewise, we analyzed DMRs under salinity stress in IR64 and Pokkali. A total of 2511 and 3580 DMRs representing 2002 and 2834 genes were detected in IR64 and Pokkali, respectively, under salinity stress. Majority of DMRs were detected in CHH context followed by CG and CHG contexts in IR64 and Pokkali cultivars (Fig. 4E, F).

This suggests that CHH context hypermethylation may be involved in salinity stress response in rice.

In Pokkali, GO terms related to abiotic stress response, including response to salt stress in the hypermethylated genes (Fig. S5).These results suggest that hypomethylation under desiccation stress in Nagina 22 and hypermethylation under salinity stress in Pokkali may be important to elicit stress tolerance in these cultivars.

This suggests that methylation dynamics in CHH context guided by de novo methylation and demethylation may be important during stress response within a cultivar. However, methylation differences detected in CG context between cultivars may be due to diversification of DNA methylomes during selection/domestication in different rice cultivars.

To understand the role of DNA methylation in response to salinity stress, we analyzed differential expression of DMR-associated genes in different sequence contexts and gene regions in IR64 and Pokkali. A total of 34 and 74 DMR associated DEGs under salinity stress were detected in IR64 and Pokkali, respectively (Fig. 6A, B). Most (86.1-88.57%) of the DMR-DEGs under salinity stress showed differential methylation in CHH context in both the cultivars (Fig. 6C, D). About (77.94-87.1%) of the DMR-associated genes in CHH context showed higher expression under salinity stress in both the cultivars and most of these genes harbored DMRs in their flanking regions (82.3-83.87%).

In IR64, CHH context hypermethylation in promoter (55.5%), gene body (80%) and downstream regions (69.2%) was correlated with higher gene expression under salinity stress (Fig. 6C). However, correlation of CHH context hypermethylation in promoter (94.7%), gene body (80%) and downstream (91.7%) regions with higher gene expression was found to be more significant in Pokkali (Fig. 6D). In addition, the number of genes showing correlation was much higher (~3 times) in Pokkali as compared to IR64. These results suggest that hypermethylation in CHH context may be associated with salinity stress response in Pokkali.

Further, we analyzed correlation of differential methylation with differential gene expression in the sets of genes involved in abiotic stress response. In IR64, four genes exhibited CHH context hypermethylation and higher expression under salinity stress (Fig. 6E). In Pokkali, a total of five genes involved in abiotic stress response showed hypermethylation in CHH context and higher gene expression under salinity stress (Fig. 6F).

Next, we analyzed overlap of DMR-associated DEGs in the sensitive and tolerant rice cultivars underdesiccation and salinity stresses. Likewise, about 74-78% of the DMR-associated DEGs were specific under salinity stress in IR64 and Pokkali (Fig. 7).

Divergent DNA methylation patterns associated with gene expression in rice cultivars with contrasting drought and salinity stress response

We report DNA methylation patterns and their influence on transcription in three rice (Oryza sativa) cultivars (IR64, stress-sensitive; Nagina 22, drought-tolerant; Pokkali, salinity-tolerant) via an integrated analysis of whole genome bisulphite sequencing and RNA sequencing.

Overall, methylation levels were significantly different in the three rice cultivars. Numerous differentially methylated regions (DMRs) among different cultivars were identified and many of which were associated with differential expression of genes important for abiotic stress response.

The average methylation levels was also highest in CG context (87-88%) followed by CHG (67-68%) and CHH (41-43%) contexts (Supplementary Fig. S1).

The comparison of DNA methylation levels with density of genes and transposable elements (TEs) revealed a positive correlation with the density of TEs and negative correlation with gene density.

For CG, largest number of mCs were located within gene body in rice cultivars. However, the frequency of mCs in CHG and CHH contexts were considerably higher in the upstream and downstream regions as compared to the gene body.

For identification of DMRs, we calculated methylation levels in 100-bp bins. A total of 64,212 DMRs between N22 and IR64 (N22/IR64) and 35,723 DMRs between Pokkali and IR64 (PK/IR64) could be identified (q-value<0.01, Fisher's exact test followed by SLIM correction) (Fig. 3a).

The DMRs were found more likely to be located near (2-kb upstream and downstream) the genes (42-45%), but not so often within the gene body (16-18%) (Supplementary Fig. S6). Overall, the DMRs present within/near protein-coding genes presented the major fraction (57-62%) of total DMRs. The genes with DMRs within their body and 2-kb flanking sequences were regarded as DMR-associated genes. A large number of protein-coding rice genes were identified as DMR-associated genes in N22/IR64 (57.9%) and PK/IR64 (38.5%).

Gene ontology (GO) analysis revealed that genes involved in diverse biological processes, such as metabolic processes, response to stress, signal transduction, translation and epigenetic regulation of gene expression were differentially methylated among rice cultivars (Supplementary Fig. S7). Notably, a large fraction of these genes were found to be associated with response to abiotic stress.

We determined the transcript abundance of all the rice genes in IR64, N22 and Pokkali cultivars using RNA-seq approach (Supplementary Table S2). The transcripts showing at least two-fold change with P-value less than 0.05 were identified as differentially expressed genes (DEGs). A total of 5172 (2620 upregulated and 2552 downregulated) and 3226 (1202 upregulated and 2024 downregulated) rice transcripts were found to be differentially expressed in N22/IR64 and PK/IR64, respectively (Fig. 4a, Supplementary Table S3).

The genes involved in various cellular processes, including metabolic processes, amino acid metabolism, cell wall components, response to abiotic stimulus (osmotic stress, salt stress and water stress), defense response, photosynthesis, transcription and signal transduction were well represented among the differentially expressed genes (Supplementary Table S3).

To examine influence of DNA methylation on expression of neighbouring genes, we assessed the relationship between DMRs and transcript abundance on a genome-wide scale. A total of about 39% (2010) and 30% (966) of the DEGs in N22/IR64 and PK/IR64, respectively, were found to be associated with DMRs. We found that differential expression of DMR-associated genes was dependent on the direction of change in methylation status (Fig. 5a). In general, the genes proximal to hypermethylated DMRs exhibited lower levels of transcript abundance (downregulation) relative to entire gene set. The genes proximal to hypomethylated DMRs displayed similar or moderately higher levels of transcript abundance (upregulation) compared to all genes.

The GO analysis of DMR-associated genes in both N22/IR64 and PK/IR64 revealed a significant enrichment of genes that participate in stress response (Fig. 6b,c).

Long-term somatic memory of salinity unveiled from physiological, biochemical and epigenetic responses in two contrasting rice genotypes

The BRS Ligeirinho (ssp indica - sensitive) and BRS Bojuru (ssp. japonica - tolerant) genotypes, known to exhibit different salinity response patterns (Benitez et al. 2010), were used to perform the experiment.

in all conditions higher Na/K values were found in roots, as compared with leaves.

To quantify the expression levels of genes involved in DNA methylation (DRM, MET and CMT) and demethylation (ROS and DML) in rice leaves under different salinity conditions, an analysis using RT-qPCR was performed. In general, we can observe distinct expression patterns in genotypes, with an increase in the expression value of most genes in the sensitive genotype (Fig. 5A) after recovery

Global DNA methylation levels were estimated as percentages of methylated cytosines in the samples, relative to the methylated positive control. The global levels of DNA methylation for leaves of BRS Ligeirinho were only significantly altered for the condition SR, with an increase of more than 40% at 48-h of stress, whereas no significant change was observed in recovery. In contrast to the sensitive genotype, high variation was observed for the tolerant genotype BRS Bojuru, with a reduction in the global levels of methylation in SV+R and SV conditions at 48-h of stress. For recovery, there was a reduction in all saline stress conditions, with the lowest levels being reached in plants exposed to stress only at reproductive stage (below 20% methylation).

In the stress period, the highest negative correlations were for the DML3b (-0.98), ROS1d (-0.97), MET1-1 (-0.96) and DRM2 (-0.92) genes, with only ROS1c and DML3a presenting positive correlation values. However, at the moment of recovery, there was an inverse response, with only DNMT2, ROS1c and ROS1d showing negative correlation with DNA methylation levels, and DML3a, MET1-1 and DRM1b showing the highest correlation values, 0.92, 0.86 and 0.87, respectively.

The R2R3-type MYB gene OsMYB91 has a function in coordinating plant growth and salt stress tolerance in rice

Here, the function of OsMYB91, an R2R3-type MYB transcription factor of rice was explored. OsMYB91 was induced by abiotic stress, especially by salt stress. Analysis of chromatin structure of the gene revealed that salt stress led to rapid removal of DNA methylation from the promoter region and rapid changes of histone modifications in the locus. Plants over-expressing OsMYB91 showed reduced plant growth and accumulation of endogenous ABA under control conditions. Under salt stress, the over-expression plants showed enhanced tolerance

To determine whether the expression of OsMYB91 was regulated by DNA methylation and histone modification, two week-old rice seedlings were treated with 100 uM 5-azacytidine (5-Aza, inhibitors of DNA methylation) and 3 mM NaBu (inhibitors of histone deacetylase) for two days. The results showed that OsMYB91 was highly induced by the treatments, and the induction tendency was similar to that of NaCl treatment (Fig. 2, Fig. 1), indicating that DNA demethylation and histone acetylation were involved in the activation of OsMYB91 gene.

Bisulfite sequencing analysis revealed a significantly decrease of cytosine methylation of CG (cytosine and guanine) dinucleotides on the promoter region 12 h after salt stress (Fig. 2C). These results indicated that in control conditions, the expression of OsMYB91 was repressed by CG methylation and H3K27me3 and that salt stress induction of the gene was mediated by DNA demethylation and rapid removal of H3K27me3 and increased H3K4me3 and H3K9ac.