Identification of novel reference genes based on MeSH categories.
Identification of novel reference genes based on MeSH categories.
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DOI：
10.1371/journal.pone.0093341
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Cetin-Atalay R
中科院分区：
文献类型：
--
作者：
Ersahin T;Carkacioglu L;Can T;Konu O;Atalay V;Cetin-Atalay R
进行转录组实验以通过mRNA表达分析评估蛋白质丰度。基因的表达水平根据实验条件和细胞反应而变化。转录组数据必须是多样的，但在稳定表达的基因，即使它们是从不同的实验室在相同的生物背景下产生的。在这项研究中，9090个微阵列样本分组到381个NCBI-GEO数据集的表达模式进行了研究，以确定新的候选参考基因使用随机化和受试者工作特征（ROC）曲线。分析表明，细胞类型特异性参考基因组显示出比所有组织的联合组更小的变异性。因此，组成型和稳定表达的起源特异性新参考基因集基于它们在所有GEO数据集中的变异系数和出现百分比来鉴定，所述GEO数据集使用医学主题词（MeSH）分类。大量MeSH分组参考基因列表作为新的组织特异性参考基因列表呈现。通过RT-qPCR比较这些组中最常见的17种基因在8种肝细胞癌、5种乳腺癌和3种结肠癌细胞中的表达，以验证组织特异性。事实上，常用的管家基因GAPDH、肌动蛋白和EEF 2具有组织特异性变异，而几个核糖体基因是体外表达最稳定的基因。我们的研究结果证实，两个或两个以上的参考基因应结合使用，从微阵列或下一代测序研究获得的大规模数据的差异表达分析。因此，上下文依赖的参考基因集，如本研究中所提出的，需要从不同的技术背景的表达数据的标准化。
Transcriptome experiments are performed to assess protein abundance through mRNA expression analysis. Expression levels of genes vary depending on the experimental conditions and the cell response. Transcriptome data must be diverse and yet comparable in reference to stably expressed genes, even if they are generated from different experiments on the same biological context from various laboratories. In this study, expression patterns of 9090 microarray samples grouped into 381 NCBI-GEO datasets were investigated to identify novel candidate reference genes using randomizations and Receiver Operating Characteristic (ROC) curves. The analysis demonstrated that cell type specific reference gene sets display less variability than a united set for all tissues. Therefore, constitutively and stably expressed, origin specific novel reference gene sets were identified based on their coefficient of variation and percentage of occurrence in all GEO datasets, which were classified using Medical Subject Headings (MeSH). A large number of MeSH grouped reference gene lists are presented as novel tissue specific reference gene lists. The most commonly observed 17 genes in these sets were compared for their expression in 8 hepatocellular, 5 breast and 3 colon carcinoma cells by RT-qPCR to verify tissue specificity. Indeed, commonly used housekeeping genes GAPDH, Actin and EEF2 had tissue specific variations, whereas several ribosomal genes were among the most stably expressed genes in vitro. Our results confirm that two or more reference genes should be used in combination for differential expression analysis of large-scale data obtained from microarray or next generation sequencing studies. Therefore context dependent reference gene sets, as presented in this study, are required for normalization of expression data from diverse technological backgrounds.
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影响因子：
3.7
作者：
de Jonge HJ;Fehrmann RS;de Bont ES;Hofstra RM;Gerbens F;Kamps WA;de Vries EG;van der Zee AG;te Meerman GJ;ter Elst A
通讯作者：
ter Elst A
影响因子：
2.7
作者：
Dheda, K;Huggett, JF;Zumla, A
通讯作者：
Zumla, A
影响因子：
--
作者：
Jung M;Ramankulov A;Roigas J;Johannsen M;Ringsdorf M;Kristiansen G;Jung K
通讯作者：
Jung K
影响因子：
3
作者：
Risso D;Schwartz K;Sherlock G;Dudoit S
通讯作者：
Dudoit S
影响因子：
3.8
作者：
OEFINGER, PE;BRONSON, DL;DREESMAN, GR
通讯作者：
DREESMAN, GR