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β2-Microglobulin is an appropriate reference gene for RT-PCR-based gene expression analysis of hematopoietic stem cells

Real-time reverse transcription polymerase chain reaction (RT-PCR) is regarded as one of the most useful and powerful tools for characterizing hematopoietic stem cells (HSCs), because samples of extremely small cell numbers can be analyzed. The expression levels determined by RT-PCR are based on rel...

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Detalles Bibliográficos
Autores principales: Matsuzaki, Yu, Umemoto, Terumasa, Tanaka, Yuji, Okano, Teruo, Yamato, Masayuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japanese Society for Regenerative Medicine 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6581808/
https://www.ncbi.nlm.nih.gov/pubmed/31245448
http://dx.doi.org/10.1016/j.reth.2015.04.003
Descripción
Sumario:Real-time reverse transcription polymerase chain reaction (RT-PCR) is regarded as one of the most useful and powerful tools for characterizing hematopoietic stem cells (HSCs), because samples of extremely small cell numbers can be analyzed. The expression levels determined by RT-PCR are based on relative quantification; therefore, the selection of an appropriate reference gene with a relatively stable expression level under most conditions is crucial. Here, we determined that beta2-microglobulin (B2m) is an appropriate reference gene for analyzing mouse HSCs by a novel method using single-cell RT-PCR. Clonally sorted HSCs were subjected to RT reactions with exogenous RNA fragments and then to real-time PCR. Next, the relative gene expression levels of 4 well-known housekeeping genes were quantified in each single cell sample based on the threshold cycle of exogenous RNA. The analysis revealed that B2m expression was reproducibly detected in almost all HSCs and that B2m had the most stable expression level among the compared genes, even after the cells had been cultured under various conditions. Thus, our results indicate that B2m can reliably be used as a reference gene for the relative quantification of expression levels in HSCs across various conditions. Furthermore, our work proposes a novel method for the selection of appropriate reference genes.