大鼠毒理基因组学研究揭示了不同微阵列平台间的分析一致性。

Rat toxicogenomic study reveals analytical consistency across microarray platforms.

作者信息

Guo Lei, Lobenhofer Edward K, Wang Charles, Shippy Richard, Harris Stephen C, Zhang Lu, Mei Nan, Chen Tao, Herman Damir, Goodsaid Federico M, Hurban Patrick, Phillips Kenneth L, Xu Jun, Deng Xutao, Sun Yongming Andrew, Tong Weida, Dragan Yvonne P, Shi Leming

机构信息

National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arkansas 72079, USA.

出版信息

Nat Biotechnol. 2006 Sep;24(9):1162-9. doi: 10.1038/nbt1238.

DOI:10.1038/nbt1238

PMID:17061323

Abstract

To validate and extend the findings of the MicroArray Quality Control (MAQC) project, a biologically relevant toxicogenomics data set was generated using 36 RNA samples from rats treated with three chemicals (aristolochic acid, riddelliine and comfrey) and each sample was hybridized to four microarray platforms. The MAQC project assessed concordance in intersite and cross-platform comparisons and the impact of gene selection methods on the reproducibility of profiling data in terms of differentially expressed genes using distinct reference RNA samples. The real-world toxicogenomic data set reported here showed high concordance in intersite and cross-platform comparisons. Further, gene lists generated by fold-change ranking were more reproducible than those obtained by t-test P value or Significance Analysis of Microarrays. Finally, gene lists generated by fold-change ranking with a nonstringent P-value cutoff showed increased consistency in Gene Ontology terms and pathways, and hence the biological impact of chemical exposure could be reliably deduced from all platforms analyzed.

摘要

为了验证和扩展微阵列质量控制（MAQC）项目的研究结果，我们使用来自用三种化学物质（马兜铃酸、里德灵碱和紫草科植物）处理的大鼠的36个RNA样本生成了一个具有生物学相关性的毒理基因组学数据集，并且每个样本都与四个微阵列平台进行杂交。MAQC项目评估了不同实验室间和跨平台比较的一致性，以及基因选择方法对使用不同参考RNA样本的差异表达基因的谱数据再现性的影响。这里报告的实际毒理基因组学数据集在不同实验室间和跨平台比较中显示出高度一致性。此外，通过倍数变化排名生成的基因列表比通过t检验P值或微阵列显著性分析获得的基因列表更具可重复性。最后，通过具有宽松P值截止值的倍数变化排名生成的基因列表在基因本体论术语和通路中显示出更高的一致性，因此可以从所有分析平台可靠地推断化学暴露的生物学影响。