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Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

Nature Biotechnology volume 28, pages 511–515 (2010)Cite this article

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Abstract

High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery and abundance estimation1,2,3. However, this would require algorithms that are not restricted by prior gene annotations and that account for alternative transcription and splicing. Here we introduce such algorithms in an open-source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed >430 million paired 75-bp RNA-Seq reads from a mouse myoblast cell line over a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Over the time series, 330 genes showed complete switches in the dominant transcription start site (TSS) or splice isoform, and we observed more subtle shifts in 1,304 other genes. These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.

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Figure 1: Overview of Cufflinks.
Figure 2: Distinction of transcriptional and post-transcriptional regulatory effects on overall transcript output.
Figure 3: Excluding isoforms discovered by Cufflinks from the transcript abundance estimation affects the abundance estimates of known isoforms, in some cases by orders of magnitude.
Figure 4: Robustness of assembly and abundance estimation as a function of expression level and depth of sequencing.

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Acknowledgements

This work was supported in part by the US National Institutes of Health (NIH) grants R01-LM006845 and ENCODE U54-HG004576, as well as the Beckman Foundation, the Bren Foundation, the Moore Foundation (Cell Center Program) and the Miller Research Institute. We thank I. Antosechken and L. Schaeffer of the Caltech Jacobs Genome Center for DNA sequencing, and D. Trout, B. King and H. Amrhein for data pipeline and database design, operation and display. We are grateful to R. K. Bradley, K. Datchev, I. Hallgrímsdóttir, J. Landolin, B. Langmead, A. Roberts, M. Schatz and D. Sturgill for helpful discussions.

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Authors and Affiliations

  1. Department of Computer Science, University of Maryland, College Park, Maryland, USA

    Cole Trapnell & Steven L Salzberg

  2. Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA

    Cole Trapnell, Geo Pertea & Steven L Salzberg

  3. Department of Mathematics, University of California, Berkeley, California, USA

    Cole Trapnell & Lior Pachter

  4. Division of Biology and Beckman Institute, California Institute of Technology, Pasadena, California, USA

    Brian A Williams, Ali Mortazavi, Gordon Kwan & Barbara J Wold

  5. Genome Sciences Center, Washington University in St. Louis, St. Louis, Missouri, USA

    Marijke J van Baren

  6. Department of Molecular and Cell Biology, University of California, Berkeley, California, USA

    Lior Pachter

  7. Department of Computer Science, University of California, Berkeley, California, USA

    Lior Pachter

Authors
  1. Cole Trapnell
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Contributions

C.T. and L.P. developed the mathematics and statistics and designed the algorithms; B.A.W. and G.K. performed the RNA-Seq and B.A.W. designed and executed experimental validations; C.T. implemented Cufflinks and Cuffdiff; G.P. implemented Cuffcompare; M.J.v.B. and A.M. tested the software; C.T., G.P. and A.M. performed the analysis; L.P., A.M. and B.J.W. conceived the project; C.T., L.P., A.M., B. J.W. and S.L.S. wrote the manuscript.

Corresponding author

Correspondence to Lior Pachter.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Tables 1–3, Supplementary Figs. 1–11 and Supplementary Methods (PDF 2058 kb)

Supplementary Table 4

Genes with complex isoform expression dynamics in C2C12 myogenesis (XLS 80 kb)

Supplementary Data (ZIP 5773 kb)

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Trapnell, C., Williams, B., Pertea, G. et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28, 511–515 (2010). https://doi.org/10.1038/nbt.1621

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