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RNA-seq03:21

RNA-seq

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RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
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Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
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Rice Expression Database (RED): An integrated RNA-Seq-derived gene expression database for rice.

Lin Xia1, Dong Zou2, Jian Sang1

  • 1CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.

Journal of Genetics and Genomics = Yi Chuan Xue Bao
|May 23, 2017
PubMed
Summary
This summary is machine-generated.

The Rice Expression Database (RED) offers comprehensive RNA-Seq data for rice, aiding in gene function discovery and understanding complex traits. This resource supports plant research by providing gene expression profiles and co-expression networks.

Keywords:
Co-expression networkExpression profilesHousekeeping geneRice expression databaseTissue-specific gene

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Area of Science:

  • Plant Biology
  • Bioinformatics
  • Genomics

Background:

  • Rice is a crucial global food source and a model organism in plant science.
  • Understanding rice gene expression is vital for improving crop traits and agricultural practices.

Purpose of the Study:

  • To introduce the Rice Expression Database (RED), an integrated resource for rice gene expression profiles.
  • To provide a comprehensive platform for analyzing RNA-Seq data in rice.

Main Methods:

  • Compilation of 284 high-quality RNA-Seq experiments.
  • Integration of extensive gene expression profiles across diverse rice growth stages and treatments.
  • Development of user-friendly web interfaces for data querying, browsing, and visualization.

Main Results:

  • RED hosts a large collection of RNA-Seq data, covering various biological conditions.
  • Identification of potential housekeeping and tissue-specific genes in rice.
  • Dynamic construction of gene co-expression networks based on the integrated data.

Conclusions:

  • RED serves as a valuable core resource for the plant research community.
  • The database facilitates the characterization of rice gene functions and biological processes.
  • RED aids in understanding the genetic mechanisms underlying complex agronomic traits in rice.