Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

RNA-seq transcriptomic profiling of crassulacean acid metabolism pathway in Dendrobium catenatum.

Long-Hai Zou | Xiao Wan | Hua Deng | Bao-Qiang Zheng | Bai-Jun Li | Yan Wang
Scientific data | 2018

The regulation of crassulacean acid metabolism (CAM) pathway has recently become a topic of intensive research and has been explored in terms of several aspects, including phylogenetics, genomics, and transcriptomics. Orchidaceae, which contains approximately 9,000 CAM species, is one of the largest lineages using this special photosynthetic pathway. However, no comprehensive transcriptomic profiling focused on CAM regulation in orchid species had previously been performed. In this report, we present two Illumina RNA-seq datasets, including a total of 24 mature leaf samples with 844.4 million reads, from Dendrobium catenatum (Orchidaceae), a facultative CAM species. The first dataset was generated from a time-course experiment based on the typical CAM phases in a diel. The second was derived from an experiment on drought stress and stress removal. A series of quality assessments were conducted to verify the reliability of the datasets. These transcriptomic profiling datasets will be useful to explore and understand the essence of CAM regulation.

Pubmed ID: 30422119

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


GenBank (tool)

RRID:SCR_002760

NIH genetic sequence database that provides annotated collection of all publicly available DNA sequences for almost 280 000 formally described species (Jan 2014) .These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using web-based BankIt or standalone Sequin programs, and GenBank staff assigns accession numbers upon data receipt. It is part of International Nucleotide Sequence Database Collaboration and daily data exchange with European Nucleotide Archive (ENA) and DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through NCBI Entrez retrieval system, which integrates data from major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of GenBank database are available by FTP.

View all literature mentions

Illumina (tool)

RRID:SCR_010233

American company incorporated that develops, manufactures and markets integrated systems for the analysis of genetic variation and biological function. Provides a line of products and services that serve the sequencing, genotyping and gene expression and proteomics markets. Its headquarters are located in San Diego, California.

View all literature mentions

FastQC (tool)

RRID:SCR_014583

Quality control software that perform checks on raw sequence data coming from high throughput sequencing pipelines. This software also provides a modular set of analyses which can give a quick impression of the quality of the data prior to further analysis.

View all literature mentions

MultiQC (tool)

RRID:SCR_014982

Data aggregate that compiles results from bioinformatics analyses across multiple samples into a single report. It is written in Python.

View all literature mentions