Ernst-Moritz-Arndt-University Greifswald, Institute for Microbiology and Interfaculty Institute for Genetics and Functional Genomics, F.-L.-Jahn-Strasse 15, Greifswald, Germany.
Curr Opin Biotechnol. 2011 Feb;22(1):32-41. doi: 10.1016/j.copbio.2010.10.003. Epub 2010 Nov 10.
Genomic tiling array transcriptomics and RNA-seq are two powerful and rapidly developing approaches for unbiased transcriptome analysis. Providing comprehensive identification and quantification of transcripts with an unprecedented resolution, they are leading to major breakthroughs in systems biology. Here we review each step of the analysis from library preparation to the interpretation of the data, with particular attention paid to the possible sources of artifacts. Methodological requirements and statistical frameworks are often similar in both the approaches despite differences in the nature of the data. Tiling array analysis does not require rRNA depletion and benefits from a more mature computational workflow, whereas RNA-Seq has a clear lead in terms of background noise and dynamic range with a considerable potential for evolution with the improvements of sequencing technologies. Being independent of prior sequence knowledge, RNA-seq will boost metatranscriptomics and evolutionary transcriptomics applications.
基因组平铺阵列转录组学和 RNA-seq 是两种强大且快速发展的无偏转录组分析方法。它们以空前的分辨率提供了对转录本的全面鉴定和定量，为系统生物学带来了重大突破。在这里，我们回顾了从文库制备到数据分析解释的分析的每一个步骤，特别关注可能的伪影来源。尽管数据的性质不同，但这两种方法在分析过程中的方法要求和统计框架通常是相似的。平铺阵列分析不需要 rRNA 耗尽，并且受益于更成熟的计算工作流程，而 RNA-seq 在背景噪声和动态范围方面具有明显的优势，并且随着测序技术的改进，具有相当大的进化潜力。由于不依赖于先前的序列知识，RNA-seq 将推动宏转录组学和进化转录组学的应用。
