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Rice Reference Genes: redefining reference genes in rice by mining RNA-seq datasets.

Xin Liu1,2, Siyuan Tang1,2, Yingbo Gao1,2

  • 1Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College of Yangzhou University, 48 East WenHui Rd, Yangzhou, Jiangsu 225009, China.

Plant & Cell Physiology
|November 23, 2024
PubMed
Summary

Selecting appropriate reference genes is vital for accurate gene expression analysis using reverse transcription quantitative real-time PCR (RT-qPCR). The new Rice Reference Genes (RRG) tool simplifies this selection process for rice researchers.

Keywords:
RNA-seq datasetsRT-qPCRreference genericeweb tool

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Area of Science:

  • Molecular Biology
  • Plant Science
  • Bioinformatics

Background:

  • Reverse transcription quantitative real-time PCR (RT-qPCR) is a standard method for gene expression analysis.
  • Accurate gene expression data relies on the selection of suitable reference genes.
  • Identifying optimal reference genes for specific rice tissues and stress conditions presents a significant challenge.

Purpose of the Study:

  • To introduce the Rice Reference Genes (RRG) tool for selecting reference genes in rice.
  • To provide a user-friendly platform for researchers to identify reliable reference genes across diverse experimental conditions.
  • To validate the accuracy and reliability of reference genes identified using the RRG tool.

Main Methods:

  • Utilized 4404 rice-derived RNA-seq datasets covering five tissue types and seven stress conditions.
  • Employed the RRG web-based tool to identify candidate reference genes in rice under salt and drought stress.
  • Validated candidate reference genes against conventionally used reference genes.

Main Results:

  • The RRG tool successfully identified candidate reference genes for rice leaves, roots, and seedlings under stress.
  • Validation confirmed the accuracy and reliability of the identified candidate reference genes.
  • The RRG tool demonstrated user-friendliness for efficient reference gene selection.

Conclusions:

  • The RRG tool is a valuable resource for rice researchers needing to select optimal reference genes.
  • The tool enhances the accuracy and reliability of gene expression studies in rice under various conditions.
  • The RRG tool simplifies the process of reference gene selection, even for users with limited experience.