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Optimizations for identifying reference genes in bone and cartilage bioengineering.

Fei Xiong1, Xiangyun Cheng2, Chao Zhang2

  • 1Department of Sports Medicine, Wuxi 9th People's Hospital affiliated to Soochow University, Wuxi, Jiangsu, China.

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|March 18, 2021
PubMed
Summary

Selecting appropriate reference genes for quantitative real-time PCR (RT-qPCR) is crucial for accurate gene expression analysis. This study found that the minimum Vn/n+1 scheme is superior for tissue samples like skeletal muscle and adipose tissue, ensuring reliable results.

Keywords:
BioengineeringChondrogenesisOsteogenesisRT-qPCRReference gene set

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Area of Science:

  • Biotechnology
  • Molecular Biology
  • Bioengineering

Background:

  • Quantitative real-time polymerase chain reaction (RT-qPCR) is a key method for gene expression analysis.
  • Inappropriate reference gene selection can lead to inaccurate results and misinterpretations.
  • Optimal reference gene selection guidelines, like the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE), are still debated.

Purpose of the Study:

  • To identify the most feasible reference gene identification schemes for bone and cartilage bioengineering.
  • To investigate reference gene selection in rat bone mesenchymal stem cells (rBMSCs), skeletal muscle, and adipose tissue undergoing specific inductions.
  • To ensure stable and accurate gene expression interpretation in bone and cartilage bioengineering.

Main Methods:

  • Analysis of stability and pairwise variance of eight candidate reference genes using the geNorm algorithm.
  • Comparison of different normalization schemes (V0.15, Vmin, V0.20, Opt3) across different tissue types.
  • Evaluation of the impact of selection schemes on target gene normalization and expression levels.

Main Results:

  • In rBMSCs, the V0.15 and Vmin schemes had no significant effect on target gene normalization.
  • For skeletal muscle and adipose tissue, different normalization schemes significantly impacted target gene normalization.
  • The Vmin scheme demonstrated a superior mode for generating accurate gene expression results in specific tissue types.

Conclusions:

  • The proposed Vn/n+1 cut-off value of 0.15 should be used cautiously, especially with certain tissue types.
  • For cell-based experiments (e.g., rBMSCs), a Vn/n+1 under 0.15 is sufficient for RT-qPCR.
  • For skeletal muscle and adipose tissue, the minimum Vn/n+1 scheme is recommended for accurate gene expression analysis.