| With an increasing number of accessible sequenced plant genome data, it is more convenient to explore gene function using systems biology approaches, which commonly integrates large-scale genomics analysis and experimental verification. In this study, we attempted to elucidate the molecular mechanisms of dark-induced leaf senescence by systems biology approach in Arabidopsis. We also developed a maize transcriptomic data analysis platform, and hope it can provide support for functional gene’s research.Leaf senescence is essential for plant growth and survival. It can be caused by various environmental cues, such as drought, darkness, pathogen and many endogenous hormones, which including ethylene, jasmonic acid, salicylic acid, abscisic acid etc. As a simulation model of the natural aging, dark-induced leaf senescence model has been applied in numbers of studies. However, the regulatory mechanism is not well understood. JASMONATE ZIM-domain (JAZ) proteins were discovered as repressors of jasmonate signaling and degraded through the SCFCOI1-dependent26S proteasome pathway in response to jasmonoyl-isoleucine (JA-Ile). In this study, we mainly focused on the role of JAZs regulating the dark-induced leaf senescence. Based on data mining of transcription profiles and mutant phenotypes screening of JAZ family genes under darkness, we found that the mutation of JAZ7led to severe leaf senescence by dark-treatment. The yellowing process and chlorophyll degradation were speeded up and more H2O2was accumulated in jaz7mutant under darkness. Then we applied a transgenic approach to further validate the results. We found that JAZ7complementary line (35S::JAZ7/jaz7) showed similar phenotype with wild-type while the senescence was delayed in JAZ7over-expression line (35S::JAZ7/WT). These results provided solid evidence for our conclusion. In addition, a recover phenotype was discovered in the jaz7×coil double mutant plants, which exhibited relatively delayed leaf senescence. Acts as a regulatory hub within the JA signaling pathway, MYC2has been confirmed interacting with JAZ7. The jaz4×myc2double mutant also display a recover phenotype compared to jaz7. These results implied that JAZ7involved in the COI1-JAZ7-MYC2signal transduction during dark-induced leaf senescence in jaz7mutant. Furthermore, proteomics (LC-MS/MS) and transcriptomics (microarray) analysis were conducted to elucidate the possible molecular mechanism underlying JAZ7negatively regulating dark-induced leaf senescence. Some genes were identified as targets of MYC2, and some biological processes were significantly different between wt and jaz7under dark-treatment both in translation and transcription levels, such as light reaction of photosynthesis, ubiquitin dependent protein degradation process, redox, jasmonate and ethylene stimulus, defense, hydrogen peroxide, etc. Our study indicates that JAZ7may play a critical role in regulating dark-induced leaf senescence in Arabidopsis.The second work was building a maize transcriptomics data analysis platform. With the rapid development of high-throughput technology, more and more scientists use the expression profile or high-throughput sequencing technology to study maize transcriptome. Numbers of transcriptomics data are available for maize, these data can provide valuable insights and improve maize study if integrate and analyze these data in a novel and comprehensive way. In addition to next generation sequencing data of conventional maize varieties, there are also some other of mixed genome species. How to analysis these data with a more effective method and then mining the gene function, is one of the difficulties for analysts. For better data mining of maize transcriptomics data, we built an analysis platform that will provide an analysis pipeline for transcrptomics data by high-throughput sequencing and visualization of results. Moreover, the platform can offer a series of services for data mining, such as maize gene network analysis, a graphical display of pathway, a cis-element significance analysis toolbox and other general tools in the database. We hope it will improve the accuracy and robustness of maize transcriptome data analysis, especially high-throughput sequencing data. In this study, we also explored an analysis method for transcriptomics data of mixed genome species, which proved to be an effective approach. We hope it can provide a revelation for other same sequencing data.Following the systems biology approach, we have explored molecular mechanism of dark-inducted leaf senescence. In addition, another project was built a maize transcriptomics data analysis platform. By the two parts work, we hope to offer a referential thinking for the subsequent studies of functional genes and the in-depth analysis of omics data. |
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