Evaluation of candidate reference genes for quantitative real-time PCR analysis in a male rat model of dietary iron deficiency

Author:

Fiddler Joanna L.ORCID,Clarke Stephen L.

Abstract

Abstract Background Quantitative real-time polymerase chain reaction (qPCR) is a reliable and efficient method for quantitation of gene expression. Due to the increased use of qPCR in examining nutrient-gene interactions, it is important to examine, develop, and utilize standardized approaches for data analyses and interpretation. A common method used to normalize expression data involves the use of reference genes (RG) to determine relative mRNA abundance. When calculating the relative abundance, the selection of RG can influence experimental results and has the potential to skew data interpretation. Although common RG may be used for normalization, often little consideration is given to the suitability of RG selection for an experimental condition or between various tissue or cell types. In the current study, we examined the stability of gene expression using BestKeeper, comparative delta quantitation cycle, NormFinder, and RefFinder in a variety of tissues obtained from iron-deficient and pair-fed iron-replete rats to determine the optimal selection among ten candidate RG. Results Our results suggest that several commonly used RG (e.g., Actb and Gapdh) exhibit less stability compared to other candidate RG (e.g., Rpl19 and Rps29) in both iron-deficient and iron-replete pair-fed conditions. For all evaluated RG, Tfrc expression significantly increased in iron-deficient animal livers compared to the iron-replete pair-fed controls; however, the relative induction varied nearly 4-fold between the most suitable (Rpl19) and least suitable (Gapdh) RG. Conclusion These results indicate the selection and use of RG should be empirically determined and RG selection may vary across experimental conditions and biological tissues.

Funder

national institutes of health

national institute of food and agriculture

Publisher

Springer Science and Business Media LLC

Subject

Genetics,Endocrinology, Diabetes and Metabolism

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3