Fu Xing, Fu Ning, Guo Song, Yan Zheng, Xu Ying, Hu Hao, Menzel Corinna, Chen Wei, Li Yixue, Zeng Rong, Khaitovich Philipp
Key lab of Systems Biology, Shanghai Institutes for Biological Sciences, China Academy of Sciences, Shanghai, 200031, PR China.
BMC Genomics. 2009 Apr 16;10:161. doi: 10.1186/1471-2164-10-161.
Microarrays revolutionized biological research by enabling gene expression comparisons on a transcriptome-wide scale. Microarrays, however, do not estimate absolute expression level accurately. At present, high throughput sequencing is emerging as an alternative methodology for transcriptome studies. Although free of many limitations imposed by microarray design, its potential to estimate absolute transcript levels is unknown.
In this study, we evaluate relative accuracy of microarrays and transcriptome sequencing (RNA-Seq) using third methodology: proteomics. We find that RNA-Seq provides a better estimate of absolute expression levels.
Our result shows that in terms of overall technical performance, RNA-Seq is the technique of choice for studies that require accurate estimation of absolute transcript levels.
微阵列技术通过在全转录组范围内进行基因表达比较,彻底改变了生物学研究。然而,微阵列技术无法准确估计绝对表达水平。目前,高通量测序正作为转录组研究的一种替代方法而兴起。尽管它没有微阵列设计所带来的许多限制,但其估计绝对转录水平的潜力尚不清楚。
在本研究中,我们使用第三种方法——蛋白质组学,评估了微阵列技术和转录组测序(RNA测序)的相对准确性。我们发现RNA测序能更好地估计绝对表达水平。
我们的结果表明,就整体技术性能而言,RNA测序是需要准确估计绝对转录水平的研究的首选技术。