3' tag digital gene expression profiling of human brain and universal reference RNA using Illumina Genome Analyzer.

3' tag digital gene expression profiling of human brain and universal reference RNA using Illumina Genome Analyzer.
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DOI:
10.1186/1471-2164-10-531
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发表时间:
2009-11-16
期刊:
影响因子:
4.4
通讯作者:
Kocher JP
Kocher JP
中科院分区:
生物学2区
文献类型:
--
作者:
Asmann YW;Klee EW;Thompson EA;Perez EA;Middha S;Oberg AL;Therneau TM;Smith DI;Poland GA;Wieben ED;Kocher JP

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大规模平行测序有可能取代微阵列作为转录组分析的方法。目前有两种方案:全长RNA测序(RNA-SEQ)和3‘-标签数字基因表达(DGE)。在这项初步工作中,我们使用来自微阵列质量控制联盟(MAQC)的两个参考RNA样本来评估3‘DGE方法。使用多次运行的脑RNA样本,我们证明了3‘DGE的转录谱在同一实验室甚至不同实验室构建的文库的技术和生物复制之间以及Illumina的两代基因组分析仪之间具有高度的重复性。大约65%的序列阅读定位于线粒体基因、核糖体RNA和规范转录本。比较了脑RNA和通用人类参考RNA的表达谱,表明DGE也是高度定量的,与实时定量PCR差异表达具有很好的相关性。此外,使用目前的测序化学和图像处理软件的3‘DGE测序的一个通道具有更宽的转录组图谱的动态范围,并且能够检测到通常低于微阵列检测阈值的低表达基因。采用大规模平行测序的3‘Tag DGE图谱技术实现了转录组图谱的高灵敏度和重复性。尽管与RNA-SEQ相比,它缺乏检测选择性剪接事件的能力,但它更实惠,在检测丰度较低的转录本方面明显优于微阵列(Affymetrix)。
Massive parallel sequencing has the potential to replace microarrays as the method for transcriptome profiling. Currently there are two protocols: full-length RNA sequencing (RNA-SEQ) and 3'-tag digital gene expression (DGE). In this preliminary effort, we evaluated the 3' DGE approach using two reference RNA samples from the MicroArray Quality Control Consortium (MAQC). Using Brain RNA sample from multiple runs, we demonstrated that the transcript profiles from 3' DGE were highly reproducible between technical and biological replicates from libraries constructed by the same lab and even by different labs, and between two generations of Illumina's Genome Analyzers. Approximately 65% of all sequence reads mapped to mitochondrial genes, ribosomal RNAs, and canonical transcripts. The expression profiles of brain RNA and universal human reference RNA were compared which demonstrated that DGE was also highly quantitative with excellent correlation of differential expression with quantitative real-time PCR. Furthermore, one lane of 3' DGE sequencing, using the current sequencing chemistry and image processing software, had wider dynamic range for transcriptome profiling and was able to detect lower expressed genes which are normally below the detection threshold of microarrays. 3' tag DGE profiling with massive parallel sequencing achieved high sensitivity and reproducibility for transcriptome profiling. Although it lacks the ability of detecting alternative splicing events compared to RNA-SEQ, it is much more affordable and clearly out-performed microarrays (Affymetrix) in detecting lower abundant transcripts.
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