Background <p>Normalization of data obtained from RT-qPCR studies is important for accurate interpretation of the results. The two most common methods of normalization that are used are the reference gene method or an algorithm-only approach, such as NORMA-Gene. Here, we assessed the impact of normalization using reference genes or the NORMA-Gene method on the expression results of five target genes that are related to oxidative stress (<i>CAT</i>, <i>GPX1</i>, <i>GPX3</i>,<i> PRDX1</i>, and <i>SOD1</i>) in the liver of sheep that had been exposed to three dietary treatments.</p> Results <p>The reference genes selected as the most stable across samples for normalization were <i>HPRT1</i>, <i>HSP90AA1</i>, and <i>B2M</i>. Interpretation of the effect of the treatment on the expression of <i>GPX3</i> differed significantly between the methods of normalization. NORMA-Gene was better at reducing the variance in the expression of the target genes than was any of the other normalization methods.</p> Conclusions <p>We demonstrated that NORMA-Gene can provide a more reliable normalization method that requires less resources than the use of reference genes for studies on gene expression in livestock.</p>

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A comparison of normalization methods for the expression of genes associated with oxidative stress in the liver of sheep

  • Sarah Babington,
  • Luoyang Ding,
  • Alan J. Tilbrook,
  • Shane K. Maloney,
  • Dominique Blache

摘要

Background

Normalization of data obtained from RT-qPCR studies is important for accurate interpretation of the results. The two most common methods of normalization that are used are the reference gene method or an algorithm-only approach, such as NORMA-Gene. Here, we assessed the impact of normalization using reference genes or the NORMA-Gene method on the expression results of five target genes that are related to oxidative stress (CAT, GPX1, GPX3, PRDX1, and SOD1) in the liver of sheep that had been exposed to three dietary treatments.

Results

The reference genes selected as the most stable across samples for normalization were HPRT1, HSP90AA1, and B2M. Interpretation of the effect of the treatment on the expression of GPX3 differed significantly between the methods of normalization. NORMA-Gene was better at reducing the variance in the expression of the target genes than was any of the other normalization methods.

Conclusions

We demonstrated that NORMA-Gene can provide a more reliable normalization method that requires less resources than the use of reference genes for studies on gene expression in livestock.