Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Tanner Stokes, Haoning Howard Cen, Philipp Kapranov, Iain J Gallagher, Andrew A. Pitsillides, Claude-Henry Volmar, William E Kraus, James D. Johnson, Stuart M. Phillips, Claes Wahlestedt, James A. Timmons
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引用次数: 5

Abstract

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data—to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.

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临床和实验生物学研究的转录组学:挂在序列上
人类基因组测序为转化医学提供了动力,促进了转录组范围的分子诊断、途径生物学和药物重新定位。最初,微阵列被用于研究大量转录组;但现在短读RNA测序(RNA-seq)占主导地位。定位为一种卓越的技术,这使得发现新的转录本成为常规,大多数RNA-seq分析实际上是基于已知的转录组建模的。RNA-seq方法的局限性已经出现,而阵列的设计和应用的分析策略已经成熟。提供了这些技术之间的公平比较,突出了现代阵列比RNA-seq具有的优势。阵列技术可以更准确地定量组织复制中组成表达的蛋白质编码基因,并且更可靠地研究低表达基因。阵列显示,长链非编码rna (lncRNA)既不稀疏,也不低于蛋白质编码基因的表达。用RNA-seq观察到的组成性表达基因的异质性覆盖,破坏了途径分析的有效性和可重复性。驱动这些观察的因素,其中许多与长读或单细胞测序有关。正如本文所提出的,需要重新认识大量转录组学方法,包括更广泛地使用现代高密度阵列数据,以紧急修改现有的解剖RNA参考图谱,并协助更准确地研究lncRNAs。
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