RNA-seq Reveals Complicated Transcriptomic Responses to Drought Stress in a Nonmodel Tropic Plant, Bombax ceiba L.
High-throughput transcriptome provides an unbiased approach for understanding the genetic basis and gene functions in response to different conditions. Here we sequenced RNA-seq libraries derived from a Bombax ceiba L. system under a controlled experiment. As a known medicinal and ornamental plant, B. ceiba grows mainly in hot-dry monsoon rainforests in Southeast Asia and Australia. Due to the specific growth environment, it has evolved a unique system that enables a physiologic response to drought stress. To date, few studies have characterized the genome-wide features of drought endurance in B. ceiba. In this study, we first attempted to characterize and identify the most differentially expressed genes and associated functional pathways under drought treatment and normal condition. Using RNA-seq technology, we generated the first transcriptome of B. ceiba and identified 59 differentially expressed genes with greater than 1,000-fold changes under two conditions. The set of upregulated genes implicates interplay among various pathways: plants growth, ubiquitin-mediated proteolysis, polysaccharides hydrolyzation, oxidative phosphorylation and photosynthesis, etc. In contrast, genes associated with stem growth, cell division, fruit ripening senescence, disease resistance, and proline synthesis are repressed. Notably, key genes of high RPKM levels in drought are AUX1, JAZ, and psbS, which are known to regulate the growth of plants, the resistance against abiotic stress, and the photosynthesis process. Furthermore, 16,656 microsatellite markers and 3,071 single-nucleotide polymorphisms (SNPs) were predicted by in silico methods. The identification and functional annotation of differentially expressed genes, microsatellites, and SNPs represent a major step forward and would serve as a valuable resource for understanding the complexity underlying drought endurance and adaptation in B. ceiba.
Zhou, Z; Ma, H; Lin, K; Zhao, Y; Chen, Y; Xiong, Z; Wang, L; Tian, B
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