Literature DB >> 29134774

Identifying suitable reference genes for developing and injured mouse CNS tissues.

Dongchao Xu1, Ajuan Liu1, Xuan Wang1, Ming Zhang2, Zunyi Zhang1, Zhou Tan1, Mengsheng Qiu1,3.   

Abstract

Accurate quantification of gene expression is fundamental for understanding the molecular, genetic and functional bases of tissue development and diseases. Quantitative real-time PCR (qPCR) is now the most widely used method of quantifying gene expression due to its simplicity, specificity, sensitivity, and wide quantification range. The use of appropriate reference genes to ensure accurate normalization is crucial for the correct quantification of gene expression from the early development, maturation, aging to injury processes in the central nervous system (CNS). In this study, we have determined the expression profiles of 12 candidate housekeeping genes (ACTB, CYC1, HMBS, GAPDH, HPRT1, RPL13A, YWHAZ, PPIA, RPLP0, TFRC, GUS, and 18S rRNA) in developing mouse brain and spinal cord. Throughout development, there was a significant degree of fluctuations in their expression levels, indicating the importance and complexity of finding appropriate reference genes. Three software including BestKeeper, geNorm and NormFinder were used to evaluate the stability of potential reference genes. GUS was the most stable gene and GUS/YWHAZ were the most stable reference gene pair across different developmental stages in different CNS regions, whereas HPRT1 and GAPDH were the most variable genes and thus inappropriate to use as reference genes. Therefore, our results identified GUS and YWHAZ as the best combination of two reference genes for expression data normalization in CNS developmental studies.
© 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 39-50, 2018. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  CNS; development; injury; reference genes; stability

Mesh:

Year:  2017        PMID: 29134774     DOI: 10.1002/dneu.22558

Source DB:  PubMed          Journal:  Dev Neurobiol        ISSN: 1932-8451            Impact factor:   3.964


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