Dataset Information

ABSTRACT: Phyllostachys violascens leaf

PROVIDER: PRJNA510221 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	SRR8325809_1.fastq.gz	Fastqsanger.gz
	SRR8325809_2.fastq.gz	Fastqsanger.gz

Items per page:

1 - 2 of 2

Similar Datasets

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

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets