Busato Sebastiano, Mezzetti Matteo, Logan Paul, Aguilera Nicolas, Bionaz Massimo
Department of Animal and Rangeland Sciences, Oregon State University, Corvallis, OR 97331, United States of America.
Istituto di Zootecnica, Facoltà di Agraria, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy.
Gene. 2019;721S:100003. doi: 10.1016/j.gene.2018.100003. Epub 2018 Dec 23.
Reverse-Transcription quantitative PCR (RT-qPCR) provides a valuable tool to study gene expression with exquisite sensitivity. To retain its inferential power, user-introduced technical variability must be reduced and accounted for. Selecting a set of stably expressed internal control genes (ICG), validated for each experimental condition/sample set, is widely accepted as a reliable way to normalize RT-qPCR data and account for said variability. Despite significant efforts in establishing standardized and resource-efficient normalization approaches, numerous recent reports have underlined deficiencies in the state of RT-qPCR normalization. Livestock science has benefitted tremendously from the use of RT-qPCR; however, the issue of lack of proper normalization likely affects this discipline as well. We thus decided to determine whether this is true, and to which extent. We conducted an in-depth analysis of all (225) RT-qPCR articles published in the six most prominent livestock journals in the field from 2013 to 2017. A quantitative scale was constructed, and values were assigned to each article based on the number of ICG used, the use of a publicly available algorithm to assess the reliability of ICG, and the reporting of pertinent information related to ICG (ranges from 0 = total noncompliance - to 100 = total compliance). Out of the surveyed group, only 10.7% of the publications obtained a score of 100, while the largest group (n = 158) was represented by articles that scored 0. Subdividing articles based on whether an algorithm to validate ICG was used (YAL) or not (NAL) revealed the use of a larger number of ICG to normalize RT-qPCR in the YAL group compared to NAL (1.4-fold more, 95% C.I.: 1.11-1.84) and was closer to the "gold standard" of three ICG. Using an algorithm also increased the diversity of ICG and significantly reduced the use of RNA18S, whose suitability as ICG has been thoroughly debated. These remarkably low normalization standards are likely to generate questionable results that can severely hinder the advance of transcriptomic studies in livestock science and related fields.
逆转录定量聚合酶链反应（RT-qPCR）为研究基因表达提供了一种具有极高灵敏度的宝贵工具。为保持其推断能力，必须减少并考虑用户引入的技术变异性。选择一组针对每个实验条件/样本集进行验证的稳定表达的内参基因（ICG），被广泛认为是对RT-qPCR数据进行标准化并考虑上述变异性的可靠方法。尽管在建立标准化且资源高效的标准化方法方面付出了巨大努力，但最近的大量报告强调了RT-qPCR标准化现状的不足之处。畜牧科学从RT-qPCR的使用中受益匪浅；然而，缺乏适当标准化的问题可能也影响了这一学科。因此，我们决定确定情况是否如此，以及影响程度如何。我们对2013年至2017年该领域六本最著名的畜牧期刊上发表的所有（225篇）RT-qPCR文章进行了深入分析。构建了一个定量量表，并根据使用的ICG数量、使用公开可用算法评估ICG的可靠性以及与ICG相关的相关信息报告情况（范围从0 = 完全不遵守到100 = 完全遵守）为每篇文章赋值。在被调查的组中，只有10.7%的出版物得分100，而得分0的文章占最大组（n = 158）。根据是否使用验证ICG的算法（YAL）对文章进行细分，结果显示与未使用算法的组（NAL）相比，使用算法的组（YAL）在RT-qPCR标准化中使用的ICG数量更多（多1.4倍，95%置信区间：1.11 - 1.84），并且更接近三个ICG的“黄金标准”。使用算法还增加了ICG的多样性，并显著减少了RNA18S的使用，其作为ICG的适用性一直存在激烈争论。这些极低的标准化标准很可能产生有问题的结果，可能严重阻碍畜牧科学及相关领域转录组学研究的进展。
