In recent years, the plantation acreage of peanuts in the northeastern provinces of China has constantly increased. To evaluate the performance of the current peanut germplasms in drought conditions and to search for suitable research materials for the study of peanut drought biology, we examined 23 representative commercial peanut varieties for their drought tolerance. After 24 h of simulated drought stress, all tested3 varieties exhibited differenced in relative fresh weight (FW), wilting index (WI), leaf water loss, and conductivity (Table S1). The level of drought-tolerance was represented by a calculated “membership function” (as described in the “materials and methods”). Using this approach, the most drought-tolerant varieties were NH5 and HY22, with ratings of 0.884 and 0.833, respectively. The least drought-tolerant varieties were FH18 and NH16 with ratings of 0.304 and 0.288, ~36% of NH5 (Fig. 1). Therefore, FH18 and NH5 were chosen as drought-sensitive and drought-tolerant peanut varieties for further analysis also because their development paces synchronized with each other.
Analysis of peanut drought-responses
Since both FH18 (sensitive type) and NH5 (tolerant type) seedlings showed vigorous growth during the 4th-leaf stage (Fig. 1), seedlings at this stage were examined for phenotypic changes caused by continuous simulated drought-stresses. First, leaves from both varieties had exhibited obvious wilting when the drought treatment prolonged. However, FH18 leaves wilted to a severer extent than those of NH5 (Fig. 2). For example, FH18 leaves started drooping at DT1 (4 h), while no obvious change could be observed in NH5 leaves at the same time. At DT2 (8 h), FH18 leaves significantly wilted but NH5 leaves only partially wilted (Fig. 2). These observations indicated that NH5 could preserve higher leaf water-contents under drought conditions than FH18.
Stomata are vital gateways for plants to control carbon and water exchange between the leaf surface and the atmosphere. Based on the above observations, it was expected that different stomatal closure patterns would be identified between FH18 and NH5 during the different drought treatment time-periods. As expected, the stomata of both peanut varieties remained open at 0 h of drought stress (Fig. 3). NH5, but not FH18, showed stomatal closure at DT1 (Fig. 3). At DT2 and DT3, the stomata in both peanut varieties were all closed (Fig. 3). These results suggest that drought conditions induced a quick stomatal closure in NH5 leaves but not in the FH18 leaves, which may have contributed to the observed slower water loss and higher leaf water content in NH5 compared to FH18 (Fig. 2).
Relative conductivity (REC) is an index which is used to reflect the osmotic-adjustment in the plasma membrane to stresses. Under drought conditions, a lower REC value correlates with an increased ability to adjust the osmotic balance. This allows for a higher drought tolerance. As shown in Fig. 4a, the REC values of NH5 were lower than those of FH18 at DT1 and DT2 (relative REC increased compared with CK: 1.81% in NH5 and 7.36% in FH18 at DT1; 5.85% in NH5 and 16.36% in FH18 at DT2) (P < 0.01). These data suggested that NH5 preserved better plasma membrane osmotic adjustment ability than FH18.
Reduced glutathione (GSH) is one of the most effective scavengers for reactive oxygen species (ROS). The GSH contents in FH18 and NH5 samples were determined (Fig. 4B). Under control conditions, there was no significant difference in GSH content between the two peanut varieties. As the drought treatments progressed, the GSH content increased in both peanut varieties but the magnitude of these increases differed. Compared with the CK group, the GSH content in NH5 at DT1, DT2, and DT3 increased by 0.15 mol/g, 0.37 mol/g and 1.4 mol/g respectively, while in FH18 at DT1, DT2, and DT3 it increased by 0.15 mol/g, 0.26 mol/g and 0.52 mol/g, respectively (P < 0.01), about 40% of that of NH5 at DT3. These results showed that drought stresses induced higher GSH contents in NH5 and therefore NH5 contained stronger ROS scavenging capabilities than FH18.
Transcriptome sequencing and assembly
Transcriptomes from the FH18 and NH5 seedlings, which underwent different levels of stress, were sequenced using Illumina 2000, and a total of 24 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 for each sample were aligned with the designated reference genome, and the alignment efficiency ranged from 94.47% to 97.49%. Based on comparisons, alternative splicing prediction analysis, and gene structure optimization analysis, 6,940 new genes were discovered (Table S2).
Drought stresses can induce significant changes in gene expression patterns. Therefore, differentially expressed genes (DEGs) among our sequenced samples were extracted according to their differential expression levels. Then, functional annotation and enrichment analysis were carried out with these identified DEGs. DEGs for FH18 at DT1, DT2 and DT3 were respectively 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). In contrast, DEGs for NH5 were 4,497 (up-regulated 2,448/down-regulated 2,049) at DT1, 5,780 (up-regulated 2,673/down-regulated 3,107) at DT2 and 5,762 (up-regulated 2,585/down-regulated 3,177) at DT3. It was obvious that at each time point DEGs for FH18 significantly out-numbered those for NH5. For example, the number of FH18 DEGs at DT3 was 11,218 almost twice of NH5 DEGs. These DEGs-number differences illustrated that drought stresses could induce more dynamic transcriptomic changes in the FH18 genome than in the NH5 genome. In another word, NH5 seemed to be able to maintain more stable transcriptomes under drought conditions. Furthermore, the number of down-regulated FH18 DEGs was ~30 % more than the number of up-regulated DEGs at both DT2 and DT3. As of NH5 DEGs, these ratios were ~15 % at DT2 and ~20 % at DT3. These results suggested that drought- stresses within 24 h exerted more down-regulatory impacts on peanut transcriptomes. In addition, this drought-induced down-regulatory impact on transcriptomes appeared to be relatively minor for NH5 than for FH18. Taken together, the differences in DEGs between NH5 and FH18 provided a justified reflection of different molecular basis underlying NH5 drought-tolerant and FH18 drought-sensitive phenotypes. Last, cluster analysis was carried out with identified differential genes (Fig. 5b).
Functional annotation of DEGs
Functional annotation was carried out for identified DEGs (refer to Table S3 for statistical numbers of genes annotated in each differential gene set). GO classification was respectively applied to DEGs in FH18 and NH5. The matched DEGs were divided into three functional categories: biological processes, molecular functions, and cell components (Fig. 6a and 6b). 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, the KEGG pathway database was searched (Fig S1). The results of the KEGG enrichment analysis are shown in Fig. 6c and 6d with the first 20 top-ranking pathways indicated by the smallest significant Q values. Although FH18 and NH5 shared similar pathway enrichment patterns, the number of enriched genes and the expression levels of enriched genes were quite different (Table S4 and S5). 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 the stratum corneum; carbon fixation; photosynthesis-antenna protein; photosynthesis; degradation of valine, leucine, and isoleucine amino acids; and the porphyrin and chlorophyll metabolisms were also enriched. In addition, several pathways were only enriched in the drought-tolerant variety, NH5: alanine metabolism; sulfur metabolism; sphingolipid metabolism; phenylpropane biosynthesis; isoquinoline alkaloid biosynthesis; and the biosynthesis of tropane, piperidine, and a pyridine alkaloid.
Peanut drought tolerance-related genes and pathways
In order to explore the drought-tolerance mechanism in peanut, we examined transcriptional changes of potential drought-tolerance genes in FH18 and NH5. We found that genes related to ABA and SA signal-transduction were significantly up-regulated, including sixteen ABF genes and twenty-two TGA (TGACG motif-binding factor) genes (Table S6). 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 S7) belonging to glutathione metabolism and proline metabolism. Thirty-three osmotic-potential-regulating genes (Table S7) were under the metabolism of arginine, proline, sucrose and starch. Fourteen cell wall sclerosis-related genes and fourteen cutin and wax metabolism genes were also enriched from NH5 transcriptomes which were suspected to affect water loss (Table S7). 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 were found to be enriched in the main drought-responsive metabolic pathways (Table S7) such as the sphingolipid metabolism, photosynthesis, the pyruvate metabolism, fatty acid degradation, and the tricarboxylic acid cycle. A diagram of the interactions of the above-described enriched-pathways is shown in Fig. 7.
Real-time qPCR validation
In order to validate the transcriptome data sets, the real-time qPCR technology was applied to analyze transcriptional levels of ten genes which were randomly selected from drought-tolerance-related pathways. The relative expression levels of genes were measured and calculated using ARAH1 as the internal reference gene. These ten genes included: 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. The RT-PCR results confirmed that the transcription changes of these 10 genes were comparable with the fold-changes observed in our transcriptome analysis (Fig. 8).