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BMC Plant Biol. 2015 Feb 12;15:43. doi: 10.1186/s12870-015-0433-5.

Global analysis of the Gossypium hirsutum L. Transcriptome during leaf senescence by RNA-Seq.



Leaf senescence is an important developmental programmed degeneration process that dramatically affects crop quality and yield. The regulation of senescence is highly complex. Although senescence regulatory genes have been well characterized in model species such as Arabidopsis and rice, there is little information on the control of this process in cotton. Here, the senescence process in cotton (Gossypium hirsutum L.) leaves was investigated over a time course including young leaf, mature leaf and leaf samples from different senescence stages using RNA-Seq.


Of 24,846 genes detected by mapping the tags to Gossypium genomes, 3,624 genes were identified as differentially expressed during leaf senescence. There was some overlap between the genes identified here and senescence-associated genes previously identified in other species. Most of the genes related to photosynthesis, chlorophyll metabolism and carbon fixation were downregulated; whereas those for plant hormone signal transduction were upregulated. Quantitative real-time PCR was used to evaluate the results of RNA-Seq for gene expression profiles. Furthermore, 519 differentially expressed transcription factors were identified, notably WRKY, bHLH and C3H. In addition, 960 genes involved in the metabolism and regulation of eight hormones were identified, of which many genes involved in the abscisic acid, brassinosteroid, jasmonic acid, salicylic acid and ethylene pathways were upregulated, indicating that these hormone-related genes might play crucial roles in cotton leaf development and senescence. However, most auxin, cytokinin and gibberellin pathway-related genes were downregulated, suggesting that these three hormones may act as negative regulators of senescence.


This is the first high-resolution, multiple time-course, genome-wide comprehensive analysis of gene expression in cotton. These data are the most comprehensive dataset currently available for cotton leaf senescence, and will serve as a useful resource for unraveling the functions of many specific genes involved in cotton leaf development and senescence.

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