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Gene expression analysis by RT-qPCR (Reverse-Transcription quantitative PCR) is extensively used in many fields of biological research, including responses to abiotic and biotic stresses. Compared with conventional methods like southern blot or fluorescence in situ hybridization, RT-qPCR is more practical in gene expression analysis for its high sensitivity, specificity and broad dynamic range even with limited amounts of RNA samples.

Regardless of its numerous advantages, RT-qPCR requires appropriate normalization strategies to ensure reliable gene expression measurement. The normalization by Internal Control Genes (ICGs) is the most popular one. An ideal internal control gene should be expressed at a relatively constant level among samples from different conditions, and should not be affected by different experimental treatments.

ICG is a wiki-based knowledgebase of internal control genes (or reference genes) for RT-qPCR data normalization in a variety of species, including human, plants, animals, fungi, and bacteria. Based on community curation, ICG harnesses collective intelligence to integrate a comprehensive collection of internal control genes curated from a large volume of literature and provides appropriate internal control genes corresponding to specific experimental conditions for both model and non-model organisms.


Purpose & Aims

To establish a community-based system to curate RT-qPCR internal control genes across different tissues and different experimental conditions for both model organisms and non-model organisms.
To provide up-to-date, comprehensive, and professional information on internal control genes for molecular biologists to customize their RT-qPCR experiments.

What is curation?

In life sciences, curation or Biocuration involves the translation and integration of information relevant to biology into a database or resource that enables integration of the scientific literature as well as large datasets. Accurate and comprehensive representation of biological knowledge, as well as easy access to the data for working scientists and a basis for computational analysis, are primary goals of Biocuration.

What are expert curation and community curation

Traditionally, biological knowledge has been aggregated through expert curation, conducted manually by dedicated experts. However, with the burgeoning volume of biological data and contrastingly the small number of expert curators, expert curation becomes more and more laborious and time-consuming, increasingly lagging behind knowledge creation. Accordingly, community curation—harnessing community intelligence for knowledge curation, bears great promise in dealing with the flood of biological knowledge.

What kind of curation strategy does ICG use?

ICG features community-based curation, exploiting the full potential of the scientific community for collaborative curation of internal control genes. In addition, ICG invites field experts and authors of publications to get involved in curation.

How to Join?

ICG allows free to view and search but only users registered in our volunteer team can add and edit content.
To join the volunteer team, please email the ICG Team at haolili(AT) to tell us your research background, preferred login name, real name, institute/university, etc., and we will set up an account for you.
Please also share these resources with anyone who might be of interest.

How to Contribute?

You can join us and make contributions based on your expertise to create a more comprehensive encyclopedia of internal control genes for RT-qPCR normalization.

If you are a molecular biologist with experience in RT-qPCR experiments, please feel free to share your valuable knowledge in ICG portal.
If you are a teacher/investigator, community curation of internal control genes in ICG can be incorporated as student assignments, where contribution can be quantified as a score.
If you are a student, you can work as a volunteer, e.g., data collection, content formatting.
If you are a journal publisher, please consider community curation as a recommended post-publication when any "Selection of Internal Control Genes / Reference genes" - related paper is accepted by the journal.

How to Cite?

Biologists are always welcome to apply the data and information from ICG in their own research projects. The ICG knowledgebase has been published in Nucleic Acids Research. To cite us, please refer to the following publication:

ICG: a wiki-driven knowledgebase of internal control genes for RT-qPCR normalization. Nucleic Acids Res 2018. 46(D1),D121-D126. [PMID:29036693]


ICG is supported by the following grants:

National Key Research & Development Program of China [2017YFC0907502];
Special Investigation on Science and Technology Basic Resources of the MOST [2019FY100102];
Strategic Priority Research Program of the Chinese Academy of Sciences [XDA19050302, XDB38030200, XDB38030400];
The Youth Innovation Promotion Association of Chinese Academy of Science [2018134];
National Key Research & Development Program of China [2018YFC0309805];
International Partnership Program of the Chinese Academy of Sciences [153F11KYSB20160008];
Genomics Data Center Construction of Chinese Academy of Sciences [WX145XQ07-04];
National Natural Science Foundation of China [32030021, 31871328];
Open Biodiversity and Health Big Data Programme of IUBS. Funding for open access charge: Special Investigation on Science and Technology Basic Resources


We thank a large number of curators and users for sharing their valuable knowledge, editing entries, sending suggestions and reporting bugs.