Dataset Information

Transcriptomic profiling of abiotic responses to drought, salt, ABA and SA in Phyllostachys edulis

ABSTRACT: Moso bamboo (Phyllostachys edulis (Carrière) J. Houz.), ) is one of the most importantessential economic bamboo species in China. However, the woods quality and yield of bamboo shoots were significantly threatened by diverse environmental conditions. significantly threaten the quality of wood and yield of bamboo shoots. In this study, to explore the molecular mechanism of abiotic stress response, we report the RNA-seq analyses of mosoMoso bamboo treated with drought, salt, SA and ABA at three -time courses. A total of 224.4 Gb clean data were generate in to explore the molecular mechanism of the abiotic stress response. The full-length transcriptome sequencing of these four treatments generated a total of 224.4 Gb data after quality trimming, and approximately 5.83Gban average of 6.615 Gb clean data were per sample was generated in per sample. The comparative analyses of the generated transcriptome data in this study will provide a valuable resource for identifying regulatory genes and potential pathways involved in various abiotic stresses in mosoMoso bamboo.

ORGANISM(S): Phyllostachys edulis

PROVIDER: GSE169067 | GEO | 2021/10/01

REPOSITORIES: GEO

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Project description:Purpose:Bamboo shoots rapidly lose water and accumulate lignin when stored under room temperature, while low temperature conditioning (LTC, 4℃) can alleviate lignification and reduce weightlessness rate. However, few transcriptional response and profiling datasets are available to explore the LTC mechanism of bamboo shoots.The goal of this study is to provides insights into the regulation of Lei bamboo (Phyllostachys violascens) shoots during postharvest cold storage by transcriptome analysis. Methods:Total RNA was extracted using RNAiso Plus (Takara, Japan) according to the protocol, and after quality testing, was used for library construction and transcriptome sequencing by Illumina Novaseq™ 6000. The quality-controlled reads were aligned to the Phyllostachys edulis reference genome (http://gigadb.org/dataset/100498). The edgeR program25 was used for differential expression analyses. Results: After raw data filtering, a high clean data rate from each sample was achieved, and the assessment result for the clean data by FastQC all demonstrated that our sequencing data was of high quality, full representativeness and validity. Compared with CK, a total of 7,452 DEGs were identified during LT storage. The Pearson’s correlation coefficient (r) and principle component analysis (PCA) results all suggested a high correlation among all samples. The above results suggest an effective LT treatment of postharvest bamboo shoots and a high-quality bioinformatics analysis of our RNA-seq results. Conclusions: Our study represents the first detailed analysis of Lei bamboo (Phyllostachys violascens) shoots during postharvest cold storage transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. We conclude that RNA-seq based transcriptome characterization would reveal the essence of ripening and senescence of fruits and vegetables.

Dataset Information

Transcriptomic profiling of abiotic responses to drought, salt, ABA and SA in Phyllostachys edulis

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