Chinese cork oak (Quercus variabilis) is a widely distributed and highly valuable deciduous broadleaf tree from both ecological and economic perspectives. Seeds of this species are recalcitrant, i.e., sensitive to desiccation, which affects their storage and long-term preservation of germplasm. However, little is known about the underlying molecular mechanism of desiccation sensitivity of Q. variabilis seeds. In this study, the seeds were desiccated with silica gel for certain days as different treatments from 0 (Control) to 15 days (T15) with a gradient of 1 day. According to the seed germination percentage, four key stages (Control, T2, T4, and T11) were found. Then the transcriptomic profiles of these four stages were compared. A total of 4,405, 4,441, and 5,907 differentially expressed genes (DEGs) were identified in T2 vs. Control, T4 vs. Control, and T11 vs. Control, respectively. Among them, 2,219 DEGs were overlapped in the three comparison groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these DEGs were enriched into 124 pathways, such as “Plant hormone signal transduction” and “Glycerophospholipid metabolism”. DEGs related to hormone biosynthesis and signal transduction (ZEP, YUC, PYR, ABI5, ERF1B, etc.), stress response proteins (LEA D-29, HSP70, etc.), and phospholipase D (PLD1) were detected during desiccation. These genes and their interactions may determine the desiccation sensitivity of seeds. In addition, group specific DEGs were also identified in T2 vs. Control (PP2C62, UNE12, etc.), T4 vs. Control (WRKY1-like, WAK10, etc.), and T11 vs. Control (IBH1, bZIP44, etc.), respectively. Finally, a possible work model was proposed to show the molecular regulation mechanism of desiccation sensitivity in Q. variabilis seeds. This is the first report on the molecular regulation mechanism of desiccation sensitivity of Q. variabilis seeds using RNA-Seq. The findings could make a great contribution to seed storage and long-term conservation of recalcitrant seeds in the future.
Quercus mongolica is a multipurpose forest species of high economic value that also plays an important role in the maintenance and protection of its environment. Consistent with the wide geographical distribution of Q. mongolica, differences in the growth and physiological traits of populations of different provenances have been identified. In this study, the molecular basis for these differences was investigated by examining the growth, physiological traits, and gene expression of Q. mongolica seedlings from six provenances in northern China. The results showed that there were significant differences in growth and physiological traits, except for the ground diameter (p < 0.05), and identified abscisic acid (ABA), indole-3-acetic acid (IAA), and soluble sugar contents as important physiological traits that distinguish Q. mongolica of different provenances. The transcriptome analysis showed that the largest difference in the total number of differentially expressed genes (DEGs) was between trees from Jilin and Shandong (6918), and the smallest difference was between trees from Heilongjiang and Liaoning (1325). The DEGs were concentrated mainly in the Gene Ontology entries of metabolic process, catalytic activity, and cell, and in the Kyoto Encyclopedia of Genes and Genomes metabolic pathways of carbohydrate metabolism, biosynthesis of other secondary metabolites, signal transduction, and environmental adaptation. These assignments indicated that Q. mongolica populations of different provenances adapt to changes in climate and environment by regulating important physiological, biochemical, and metabolic processes. A weighted gene co-expression network analysis revealed highly significant correlations of the darkmagenta, grey60, turquoise, and plum1 modules with ABA content, IAA content, soluble sugar content, and soluble protein content, respectively. The co-expression network also indicated key roles for genes related to the stress response (SDH, WAK5, APA1), metabolic processes (UGT76A2, HTH, At5g42100, PEX11C), signal transduction (INPS1, HSD1), and chloroplast biosynthesis (CAB13, PTAC16, PNSB5). Functional annotation of these core genes implies that Q. mongolica can adapt to different environments by regulating photosynthesis, plant hormone signal transduction, the stress response, and other key physiological and biochemical processes. Our results provide insight into the adaptability of plants to different environments.
Quercus mongolica, a common tree species for building and landscaping in northern China, has great commercial and ecological value. The seedlings of Q. mongolica grow poorly and develop chlorosis when introduced from high-altitude mountains to low-altitude plains. Effective cultivation measures are key to improving the quality of seedlings. To investigate the complex responses of Q. mongolica to different cultivation measures, we compared the adaptability of 3-year-old Q. mongolica seedlings to pruning (P), irrigation (W), and fertilization [F (nitro compound fertilizer with 16N-16P-16K)]. Physiological measurements and transcriptome sequencing were performed on leaves collected under the P treatments (control, cutting, removal of all lateral branches, and removal of base branches to one-third of seedling height), the W treatments (0, 1, 2, 3, 4, or 5 times in sequence), and the F treatments (0, 2, 4, and 6 g/plant). Analyses of the physiological data showed that P was more effective than W or F for activating intracellular antioxidant systems. By contrast, W and F were more beneficial than P for inducing the accumulation of soluble sugar. OPLS-DA identified superoxide dismutase, malondialdehyde, and peroxidase as critical physiological indices for the three cultivation measures. Transcriptome analyses revealed 1,012 differentially expressed genes (DEGs) in the P treatment, 1,035 DEGs in the W treatment, and 1,175 DEGs in the F treatment; these DEGs were mainly enriched in Gene Ontology terms related to the stress response and signal transduction. Weighted gene coexpression network analyses indicated that specific gene modules were significantly correlated with MDA (one module) and soluble sugar (four modules). Functional annotation of the hub genes differentially expressed in MDA and soluble sugar-related modules revealed that Q. mongolica responded and adapted to different cultivation measures by altering signal transduction, hormone levels, reactive oxygen species, metabolism, and transcription factors. The hub genes HOP3, CIPK11, WRKY22, and BHLH35 in the coexpression networks may played a central role in responses to the cultivation practices. These results reveal the mechanism behind the response of Q. mongolica to different cultivation measures at the physiological and molecular levels and provide insight into the response of plants to cultivation measures.
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