A transcriptome analysis using RNA-seq to investigate the tolerance of the cabbage (Brassica oleracea var. capitata L.) to high temperature and waterlogging stresses

• Main Authors: Chih-Liang Hung, 洪志良
• Other Authors: 許輔
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/54647787871605189173

博士 === 國立臺灣大學 === 園藝暨景觀學系 === 104 === Waterlogging at high temperature is a major stress after typhoon to the cabbage production during summer in Taiwan. This stress brings in serious physiological disorder and results in yield loss in cabbage. However, the molecular mechanisms of the physiological disorders under waterlogging stress at high temperature remain unclear. This thesis aims to identify how the waterlogging stress at high temperature (HWS) influences the cabbage transcriptome and to discover the gene sets which contribute to the tolerance of HWS in cabbage. First, RNA-seq was used to investigate the whole transcriptome of eight-week-old cabbage ‘Shia Feng No. 1’ treated with or without waterlogging both at 25 or 35°C. Log2 fold change value in selected 2,040 genes was used to discriminate differentially expressed genes (DEGs). By hierarchical clustering, WRKY-induced up-regulation of ACC oxidase 1 was specifically found in HWS treatment, which to be one of the key factors that caused decreased stress tolerance in cabbage ‘Shia Feng No.1’. According to gene ontology (GO) enrichment analysis, the enriched GO terms in heat treatment were close to HWS treatment; however, there were still unique GO terms enriching in each treatment. To further understand the co-functional networks in cabbages exposed to stress, AraNet v2 was used to predict co-expression network modules of HWS-treated cabbages. In the 7 predicted co-expression modules, the down-regulation of two modules related to ABA signaling and tolerance to osmotic stress in plants may provide the evidence about the HWS intolerance in cabbage. Next, next generation sequencing was employed to compare the transcriptome of stress-tolerant cultivar ‘228’ and stress–intolerant cultivar ‘Fuyudori’ under HWS, which were used to find HWS-influenced metabolic pathways and gene sets. Stress treatment was performed in growth chamber at 35°C for 24 h, and sampling was performed at 0, 6, 12, and 24 h after treatment. A time-course RNA-seq analysis was performed and combined two different bioinformatic methods, primary co-expression measure with hierarchical clustering and weighted correlation network analysis (WGCNA), for analyzing the transcriptome data. 256 most significantly changed genes were identified and 13 coexpression modules associate to HWS were constructed. Finally, comparative analysis showed HWS tolerance highly linked to phenolic biosynthesis in ‘228’, and uncontrollable water deprivation may be one of the key factors to cause HWS-affected in ‘Fuyudori’. These data show how HWS influences the metabolic and regulatory pathways in cabbages. Several stress tolerance-specific gene modules were linked to the accumulation of secondary metabolites, transduction of ABA signaling, and up-regulation of heat stress factors and heat shock proteins. These may provide cabbage a flexible strategy tolerant to cope with HWS by offering appropriate metabolic adaptability under the dramatically changing environment.