Housekeeping gene stability influences the quantification of osteogenic markers during stem cell differentiation to the osteogenic lineage
- PMID: 20396946
- PMCID: PMC2873986
- DOI: 10.1007/s10616-010-9265-1
Housekeeping gene stability influences the quantification of osteogenic markers during stem cell differentiation to the osteogenic lineage
Abstract
Real-time reverse transcription PCR (RT-qPCR) relies on a housekeeping or normalizer gene whose expression remains constant throughout the experiment. RT-qPCR is commonly used for characterization of human bone marrow mesenchymal stem cells (hBMSCs). However, to the best of our knowledge, there are no studies validating the expression stability of the genes used as normalizers during hBMSCs differentiation. This work aimed to study the stability of the housekeeping genes beta-actin, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and ribosomal protein L13A (RPL13A) during the osteogenic differentiation of hBMSCs. Their stability was evaluated via RT-qPCR in 14 and 20 day differentiation assays to the osteogenic lineage. Different normalization strategies were evaluated to quantify the osteogenic markers collagen type I, bone sialoprotein and osteonectin. Cell differentiation was confirmed via alizarin red staining. The results demonstrated up-regulation of beta-actin with maximum fold changes (MFC) of 4.38. GAPDH and RPL13A were not regulated by osteogenic media after 14 days and presented average fold changes lower than 2 in 20 day cultures. RPL13A (MFC < 2) had a greater stability when normalizing as a function of culture time compared with GAPDH (MFC </= 2.2), which resulted in expression patterns of the osteogenic markers more consistent with the observed differentiation process. The results suggest that beta-actin regulation could be associated with the morphological changes characteristic of hBMSCs osteogenic differentiation, and provide evidence for the superior performance of RPL13A as a normalizer gene in osteogenic differentiation studies of hBMSCs. This work highlights the importance of validating the normalizer genes used for stem cells characterization via RT-qPCR.
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