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Advancing RNA-Seq analysis

Nature Biotechnology volume 28, pages 421–423 (2010)Cite this article

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New methods for analyzing RNA-Seq data enable de novo reconstruction of the transcriptome.

Sequencing of RNA has long been recognized as an efficient method for gene discovery1 and remains the gold standard for annotation of both coding and noncoding genes2. Compared with earlier methods, massively parallel sequencing of RNA (RNA-Seq)3 has vastly increased the throughput of RNA sequencing and allowed global measurement of transcript abundance. Two reports in this issue introduce approaches for RNA-Seq analysis that capture genome-wide transcription and splicing in unprecedented detail. Trapnell et al.4 describe a software package, Cufflinks, for simultaneous discovery of transcripts and quantification of expression levels and apply it to study gene expression and splicing during the differentiation of mouse myoblast cells. Taking a similar approach, Guttman et al.5 use software called Scripture to reannotate the transcriptomes of three mouse cell lines, defining complete gene models for hundreds of new large intergenic noncoding RNAs (lincRNAs)6.

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Figure 1: Strategies for reconstructing transcripts from RNA-Seq reads.

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Authors and Affiliations

  1. Brian J. Haas and Michael C. Zody are at the Broad Institute, Cambridge, Massachusetts, USA.,

    Brian J Haas & Michael C Zody

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  1. Brian J Haas
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  2. Michael C Zody
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Correspondence to Brian J Haas or Michael C Zody.

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Haas, B., Zody, M. Advancing RNA-Seq analysis. Nat Biotechnol 28, 421–423 (2010). https://doi.org/10.1038/nbt0510-421

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