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Analysis and design of RNA sequencing experiments for identifying isoform regulation

Nature Methods volume 7, pages 1009–1015 (2010)Cite this article

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Abstract

Through alternative splicing, most human genes express multiple isoforms that often differ in function. To infer isoform regulation from high-throughput sequencing of cDNA fragments (RNA-seq), we developed the mixture-of-isoforms (MISO) model, a statistical model that estimates expression of alternatively spliced exons and isoforms and assesses confidence in these estimates. Incorporation of mRNA fragment length distribution in paired-end RNA-seq greatly improved estimation of alternative-splicing levels. MISO also detects differentially regulated exons or isoforms. Application of MISO implicated the RNA splicing factor hnRNP H1 in the regulation of alternative cleavage and polyadenylation, a role that was supported by UV cross-linking–immunoprecipitation sequencing (CLIP-seq) analysis in human cells. Our results provide a probabilistic framework for RNA-seq analysis, give functional insights into pre-mRNA processing and yield guidelines for the optimal design of RNA-seq experiments for studies of gene and isoform expression.

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Figure 1: More accurate inference of splicing levels using MISO.
Figure 2: MISO CIs for Ψ values and qRT-PCR validation.
Figure 3: Bayes factor analysis of hnRNP H regulation of exon splicing.
Figure 4: Bayes factor analysis implicates hnRNP H in alternative cleavage and polyadenylation.
Figure 5: Improved estimation of isoform abundance using paired-end reads.

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Acknowledgements

We thank C. Wilusz (Colorado State University) for the gift of the CUGBP1-knockdown and control C2C12 cells; R. Darnell for advice regarding CLIP-seq protocols; S. Abou Elela, V. Butty, R. Nutiu and G. Schroth for sharing RNA-seq data; and J. Ernst, D. Gresham, M. Guttman, F. Jäkel, E. Jonas, F. Markowetz, D. Roy, R. Sandberg, T. Velho, X. Xiao and members of the Burge lab for insightful discussions and comments on the manuscript. This work was supported by grants from the US National Science Foundation (E.M.A.) and the US National Institutes of Health (E.M.A. and C.B.B.).

Author information

Authors and Affiliations

  1. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, USA

    Yarden Katz

  2. Department of Biology, MIT, Cambridge, Massachusetts, USA

    Yarden Katz, Eric T Wang & Christopher B Burge

  3. Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts, USA

    Eric T Wang

  4. Department of Statistics and FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, USA

    Edoardo M Airoldi

  5. Department of Biological Engineering, MIT, Cambridge, Massachusetts, USA

    Christopher B Burge

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  1. Yarden Katz
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Contributions

Y.K., development of MISO model and software, analyses involving MISO, writing of main text and methods; E.T.W., hnRNP H CLIP-seq experiments and associated computational analyses, CUGBP1 knockdown RNA-seq experiments and associated computational analyses; E.M.A., development of model and statistical analysis, writing of methods; C.B.B., development of MISO model, contributions to computational analyses, writing of main text.

Corresponding authors

Correspondence to Edoardo M Airoldi or Christopher B Burge.

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The authors declare no competing financial interests.

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Supplementary Figures 1–12, Supplementary Tables 1 and 2, Supplementary Note (PDF 1935 kb)

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Katz, Y., Wang, E., Airoldi, E. et al. Analysis and design of RNA sequencing experiments for identifying isoform regulation. Nat Methods 7, 1009–1015 (2010). https://doi.org/10.1038/nmeth.1528

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