Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays.
Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays.
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DOI：
10.1186/1471-2164-7-59
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发表时间：
2006-03-21
期刊：
影响因子：
4.4
通讯作者：
Samaha, Raymond R
中科院分区：
文献类型：
--
作者：
Wang, Yulei;Barbacioru, Catalin;Hyland, Fiona;Xiao, Wenming;Hunkapiller, Kathryn L;Blake, Julie;Chan, Frances;Gonzalez, Carolyn;Zhang, Lu;Samaha, Raymond R
DNA微阵列正迅速成为基于发现的基因组和生物医学研究的基本工具。然而，由于存在不同的技术和非标准的数据分析和解释方法，微阵列结果的可靠性受到挑战。在缺乏用于基因表达测量的“金标准”/“参考方法”的情况下，评估和比较各种微阵列平台的性能的研究常常产生主观和矛盾的结论。为了解决这个问题，我们进行了一个大规模的基于TaqMan®基因表达测定的实时PCR实验，并使用该数据集作为参考，以评估两个代表性的商业微阵列平台的性能。在这项研究中，我们分析了三种人体组织的基因表达谱：脑，肺，肝和一个通用的人类参考样本（UHR）使用两个代表性的商业长寡核苷酸微阵列平台：（1）应用生物系统人类基因组调查微阵列（基于单色检测）;（2）安捷伦全人类基因组寡核苷酸微阵列（基于双色检测）。选择由两种微阵列平台代表的并且跨越基因表达水平的宽动态范围的1，375个基因用于基于TaqMan®基因表达测定的实时PCR验证。对于每个平台，根据每个制造商的标准方案对相同的总RNA样品进行四次技术重复。对于Agilent阵列，使用Cy 5掺入脑/肺/肝RNA和Cy 3掺入UHR RNA（通用参考）进行比较杂交。使用基于TaqMan® Gene Expression Assay的实时PCR数据集作为参考集，评价两个微阵列平台的性能，重点关注以下标准：（1）检测表达的灵敏度和准确度;（2）在成对组织中以及在所有组织中测定的基因表达谱中与实时PCR数据的倍数变化相关性;（3）差异表达检测的敏感性和准确性。我们的研究提供了一个最大的“参考”数据集的基因表达测量使用TaqMan®基因表达测定基于实时PCR技术。该数据集使我们能够使用替代基因表达技术来评估不同微阵列平台的性能。我们的结论是，微阵列确实是非常宝贵的发现工具，具有可接受的可靠性，全基因组基因表达筛选，虽然在基因表达的假定变化的验证仍然是可取的。我们的研究还描述了微阵列的局限性;理解这些局限性将使研究人员能够以更谨慎和适当的方式更有效地评估微阵列结果。
DNA microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan® Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial microarray platforms. In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR) using two representative commercial long-oligonucleotide microarray platforms: (1) Applied Biosystems Human Genome Survey Microarrays (based on single-color detection); (2) Agilent Whole Human Genome Oligo Microarrays (based on two-color detection). 1,375 genes represented by both microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan® Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference). Using the TaqMan® Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two microarray platforms was evaluated focusing on the following criteria: (1) Sensitivity and accuracy in detection of expression; (2) Fold change correlation with real-time PCR data in pair-wise tissues as well as in gene expression profiles determined across all tissues; (3) Sensitivity and accuracy in detection of differential expression. Our study provides one of the largest "reference" data set of gene expression measurements using TaqMan® Gene Expression Assay based real-time PCR technology. This data set allowed us to use an alternative gene expression technology to evaluate the performance of different microarray platforms. We conclude that microarrays are indeed invaluable discovery tools with acceptable reliability for genome-wide gene expression screening, though validation of putative changes in gene expression remains advisable. Our study also characterizes the limitations of microarrays; understanding these limitations will enable researchers to more effectively evaluate microarray results in a more cautious and appropriate manner.