Instituto de Microbiología Bioquímica, Consejo Superior de Investigaciones Científicas (CSIC)/Universidad de Salamanca, Edificio Departamental, Campus Miguel de Unamuno, 37007-Salamanca, Spain.
BMC Bioinformatics. 2010 Mar 17;11:136. doi: 10.1186/1471-2105-11-136.
DNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale. Expression microarrays (EMA) contain probes for annotated open reading frames (ORF) and are widely used for the analysis of differential gene expression. By contrast, tiling microarrays (TMA) have a much higher probe density and provide unbiased genome-wide coverage. The purpose of this study was to develop a protocol to exploit the high resolution of TMAs for quantitative measurement of DNA strand-specific differential expression of annotated and non-annotated transcripts.
We extensively filtered probes present in Affymetrix Genechip Yeast Genome 2.0 expression and GeneChip S. pombe 1.0FR tiling microarrays to generate custom Chip Description Files (CDF) in order to compare their efficiency. We experimentally tested the potential of our approach by measuring the differential expression of 4904 genes in the yeast Schizosaccharomyces pombe growing under conditions of oxidative stress. The results showed a Pearson correlation coefficient of 0.943 between both platforms, indicating that TMAs are as reliable as EMAs for quantitative expression analysis. A significant advantage of TMAs over EMAs is the possibility of detecting non-annotated transcripts generated only under specific physiological conditions. To take full advantage of this property, we have used a target-labelling protocol that preserves the original polarity of the transcripts and, therefore, allows the strand-specific differential expression of non-annotated transcripts to be determined. By using a segmentation algorithm prior to generating the corresponding custom CDFs, we identified and quantitatively measured the expression of 510 transcripts longer than 180 nucleotides and not overlapping previously annotated ORFs that were differentially expressed at least 2-fold under oxidative stress.
We show that the information derived from TMA hybridization can be processed simultaneously for high-resolution qualitative and quantitative analysis of the differential expression of well-characterized genes and of previously non-annotated and antisense transcripts. The consistency of the performance of TMA, their genome-wide coverage and adaptability to updated genome annotations, and the possibility of measuring strand-specific differential expression makes them a tool of choice for the analysis of gene expression in any organism for which TMA platforms are available.
DNA 微阵列技术允许在全基因组范围内分析基因组结构和动态。表达微阵列（EMA）包含注释开放阅读框（ORF）的探针，广泛用于差异基因表达分析。相比之下，平铺微阵列（TMA）具有更高的探针密度，并提供无偏的全基因组覆盖。本研究的目的是开发一种方案，利用 TMA 的高分辨率对注释和非注释转录物的 DNA 链特异性差异表达进行定量测量。
我们广泛筛选了 Affymetrix Genechip Yeast Genome 2.0 表达和 GeneChip S. pombe 1.0FR 平铺微阵列中存在的探针，以生成定制的芯片描述文件（CDF），以比较它们的效率。我们通过测量酵母酿酒酵母在氧化应激条件下生长的 4904 个基因的差异表达来实验测试我们方法的潜力。结果显示，两种平台之间的 Pearson 相关系数为 0.943，表明 TMA 与 EMA 一样可用于定量表达分析。TMA 相对于 EMA 的一个显著优势是能够检测仅在特定生理条件下产生的非注释转录物。为了充分利用这一特性，我们使用了一种目标标记方案，该方案保留了转录物的原始极性，因此可以确定非注释转录物的链特异性差异表达。在生成相应的定制 CDF 之前使用分段算法，我们鉴定并定量测量了长度大于 180 个核苷酸且不与先前注释的 ORF 重叠的 510 个转录本的表达，这些转录本在氧化应激下的差异表达至少为 2 倍。
我们表明，从 TMA 杂交获得的信息可以同时用于对经过充分研究的基因以及先前未注释和反义转录物的差异表达进行高分辨率定性和定量分析。TMA 的性能一致性、其全基因组覆盖范围以及对更新的基因组注释的适应性，以及测量链特异性差异表达的可能性，使它们成为分析任何具有 TMA 平台的生物体中基因表达的首选工具。
