Peanut drought-resistances
The plantation acreage of peanuts in the Northeastern provinces of China has been constantly increasing during recent years. To evaluate the performances of our current peanut germplasms under drought and to search for suitable research materials for peanut drought biology, we examined twenty-three representative commercial peanut varieties for their drought-resistances. After 24 h of simulated drought stress, all tested varieties had exhibited differential relative fresh-weight (FW), wilting-index (WI), leaf water-loss and conductivity (Table S1). And the level of drought-resistance was represented by a calculated “the membership function” (described as in the “materials and methods”). By this approach, the most drought-resistant varieties were NH5 and HY22 with ratings of 0.884 and 0.833 respectively. The least drought-resistant varieties were FH18 and NH16 with ratings of 0.304 and 0.288, ~ 36% of NH5 (Fig. 1). Showing synchronized paces of plant development, FH18 and NH5 were chosen as drought sensitive and drought-resistant peanut varieties for further analysis.
Analysis of Drought Stress Responses
Since FH18 (sensitive type) and NH5 (resistant type) seedlings showed vigorous growth during the 4th -leaf stage (Fig. 1), these seedlings were examined for phenotypic changes after being subjected to continuous simulated drought stresses. First, leaves of both varieties had exhibited an obvious wilting phenotype when the drought treatment prolonged but to a severer extent in FH18 than NH5 (Fig. 2). For example, FH18 leaves started drooping at DT1 (4 h), while no obvious change was observed in NH5 leaves at the same time-point. Furthermore, at DT2 (8 h), FH18 leaves significantly wilted but NH5 leaves only partially wilted (Fig. 2), indicating that NH5 could preserve a higher leaf water content than FH18 under drought conditions.
Stomata are important gateways for plants to control carbon and water exchange between leaves and the atmosphere. Based on the above observations, different stomatal-closure patterns should be identified between FH18 and NH5 during the time-course of drought treatments. As expected, the stomata of both peanut varieties remained open at 0 h of drought stress (Fig. 3). NH5 showed stomatal closure at DT1 but not in FH18 (Fig. 3). For DT2 and DT3, the stomata in both peanut varieties were all closed (Fig. 3). These results suggested that drought- induced quick stomatal closure in NH5 leaves compared to FH18 leaves, which might contribute to a relatively slower water-loss and a higher leaf water content as displayed by NH5 in Fig. 2.
Relative conductivity (REC) is an index which can be used to reflect the ability of osmotic adjustment to stresses in the plasma membrane. Under drought conditions, the lower the REC value correlates with the better abilities of adjusting osmotic balance and thus stronger drought tolerance. As shown in the Fig. 4a, the REC values of NH5 were lower than those of FH18 at DT1 and DT2 time points (relative REC increase compared with CK: 1.81% for NH5 and 7.36% for FH18 at DT1; 5.85% for NH5 and 16.36% for FH18 at DT2) (P < 0.01). These data indicated better osmotic adjustment ability in NH5 than in FH18.
Reduced glutathione (GSH) is one of the most effective scavengers for reactive oxygen species (ROS). Next, the GSH contents in FH18 and NH5 were determined (Fig. 4B). Under the control conditions, there was no significant difference in the GSH content between these two peanut varieties. As the process of drought treatment progressed, the GSH content in both peanuts showed an increase trend but to different extent. Compared with the CK group, DT1, DT2 and DT3 of NH5 increased by 0.15 mol/g, 0.37 mol/g and 1.4 mol/g respectively, while DT1, DT2 and DT3 of FH18 increased by 0.15 mol/g, 0.26 mol/g and 0.52 mol/g respectively (P < 0.01). These results showed that stressed NH5 contained more GSH and therefore stronger ROS scavenging capabilities than FH18.
Transcriptome sequencing and assembly
Transcriptomes from the FH18 and NH5 seedlings which were stressed to different levels were sequenced using Illumina 2000, and totally twenty-four transcriptome libraries were constructed (three library repeats for each variety at every time-point). After removing the low-mass readings, 177.69 Gb of clean data were obtained. The clean data for each sample reached 5.90 Gb and the percentage of Q30 bases was 94.62% or more. The “Clean Reads” of each sample were sequenced with the designated reference genome, and the alignment efficiency ranged from 94.47% to 97.49%. Based on comparisons, alternative splicing prediction analysis, gene structure optimization analysis and discovery of new genes were carried out, and 6,940 new genes were discovered (Table S1).
Expression Analysis of Differential Genes
Gene expression patterns could be significantly affected by drought stresses. Therefore, differentially expressed genes (DEGs) were extracted according to their differential expression levels in different samples. Then functional annotation and enrichment analysis were carried out with these identified DEGs. DEGs at DT1, DT2 and DT3 of FH18 were identified as 7,989 (up-regulated 3,709/ down-regulated 4,280), 9,386 (up-regulated 4,052/down-regulated 5,334) and 11,218 (up-regulated 4,881/down-regulated 6,337), respectively. In contrast, 4,497 (up-regulated 2,448/down-regulated 2,049) DT1, 5,780 (up-regulated 2,673/down-regulated 3,107) DT2 and 5,762 (up-regulated 2,585/down-regulated 3,177) DT3 DEGs for NH5 were identified. It was obvious that at each time point DEGs of FH18 significantly outnumbered those of NH5, for example almost twice of NH5 DEGs at DT3. This difference indicated that drought stresses would induce more volatile transcriptomic dynamics in FH18 than in NH5. From another aspect, NH5 seemed to be able to maintain a stabler transcriptome under drought conditions. Furthermore, when carefully examined, the number of down-regulated FH18 DEGs was ~ 30% more than up-regulated DEGs at both DT2 and DT3. For NH5 DEGs, the ratios were ~ 15% at DT2 and ~ 20% at DT3. These results suggested that drought stresses within 24 h tended to exert more of a down-regulation impact on peanut transcriptomes. Also the comparatively lesser extent of down-regulation in NH5 transcriptomes than FH18 might reflect and confirm previous physiological characterizations of NH5 as drought-resistant and FH18 as drought-sensitive. Next, cluster analysis was carried out with identified differential genes (Fig. 5b).
Functional Annotation of DEGs
Next, functional annotation was carried out for DEGs (refer to Table S2 for statistical numbers of genes annotated in each differential gene set). In order to determine subordinate categories of the responsive genes, we used GO classification for the DEGs in FH18 and NH5 respectively. And the matched DEGs were divided into three functional categories: biological processes, molecular functions and cell components (Fig. 6a and b). In the category of biological processes, the most abundant genes belonged to metabolic processes and cellular processes. In the category of cell components, the number of genes in cell parts and cells was the highest. In the category of molecular function, DEGs mainly belonged to binding and catalytic activity subgroups. In order to identify active biological pathways enriched with DEGs in both peanut varieties, KEGG pathway database was used (Figure S1). The results of KEGG enrichment analysis were shown in the following Figure with the first twenty top-ranking pathways by smallest significant Q values (Fig. 6C and D). Although FH18 and NH5 had shared similar pathway-enrichment results, the number of enriched genes and the expression levels of enriched genes were quite different (Table S3 and S4). The enriched-pathways included GSH-related glutathione metabolism, glycolysis, glyoxylic acid and dicarboxylic acid ester metabolism associated with pyruvic acid. Pathways of corneal and wax anabolism, fatty acid degradation related to stratum corneum, carbon fixation, photosynthesis-antenna protein, photosynthesis, degradation of amino acids valine, leucine and isoleucine, and porphyrin and chlorophyll metabolism were also enriched. In addition, several pathways were only enriched in the drought-resistant variety NH5, including alanine metabolism, sulfur metabolism, sphingolipid metabolism, phenylpropane biosynthesis, isoquinoline alkaloid biosynthesis and biosynthesis of tropane, piperidine and pyridine alkaloid.
Peanut Drought Resistant- Related Genes and Pathways
In order to explore the drought-resistance mechanism of peanut, we examined transcriptional changes of potential drought-resistance genes in FH18 and NH5 with drought treatments. It was found that genes related to ABA and SA signal-transduction were significantly up-regulated, specifically sixteen ABF genes and twenty-two TGA (TGACG motif-binding factor) genes (Table S5). Compared with FH18 transcriptomes, some genes were differentially expressed only in NH5. These NH5-specific DEGs could be categorized into various biological pathways. Among them, fourteen genes were identified as ROS-scavenging genes (Table S5), which belonged to glutathione metabolism and proline metabolism respectively. Thirty-three osmotic-potential-regulating genes (Table S5) were subordinate to the metabolism of arginine, proline, sucrose and starch. In addition, fourteen cell wall sclerosis-related genes and fourteen cutin and wax metabolism genes were also enriched from NH5 transcriptomes, which were believed to be able to affect water loss (Table S5). Another set of genes involved in peanut defense- responses showed much higher expression levels in NH5 than in FH18. On the other hand, FH18-specific differential genes were also identified, however their expression patterns indicated that these genes were suppressed by drought treatments. Furthermore, another 126 DEGs genes were identified to enrich in main drought-responsive metabolic pathways (Table S5) such as sphingolipid metabolism, photosynthesis, pyruvate metabolism, fatty acid degradation and tricarboxylic acid cycle. In conclusion, a diagram of interactions of above-described enriched-pathways was drawn and shown as in Fig. 7.
Real-time qPCR Validation
In order to validate the accuracy of transcriptome data sets, the real-time qPCR technology was applied to analyze transcriptional levels ten genes which were randomly selected from drought-resistant-related pathways. The relative expression levels of genes were measured and calculated with ARAH1 as the internal reference gene. These ten genes were: pyruvate dehydrogenase; glutamate synthetase, agmatine deiminase isoenzyme X2, PXG, trehalose 6-phosphate synthase/phosphatase, inositol oxygenase 2, glutathione S-transferase, cinnamyl alcohol dehydrogenase, glycerol kinase and enoyl-CoA hydratase. RT-PCR results confirmed that the transcription changes of these ten genes were comparable with the fold-changes gained from our transcriptome analysis (Fig. 8).