Letter | Published:

Extensive transcriptional heterogeneity revealed by isoform profiling

Nature volume 497, pages 127131 (02 May 2013) | Download Citation

Abstract

Transcript function is determined by sequence elements arranged on an individual RNA molecule. Variation in transcripts can affect messenger RNA stability, localization and translation1, or produce truncated proteins that differ in localization2 or function3. Given the existence of overlapping, variable transcript isoforms, determining the functional impact of the transcriptome requires identification of full-length transcripts, rather than just the genomic regions that are transcribed4,5. Here, by jointly determining both transcript ends for millions of RNA molecules, we reveal an extensive layer of isoform diversity previously hidden among overlapping RNA molecules. Variation in transcript boundaries seems to be the rule rather than the exception, even within a single population of yeast cells. Over 26 major transcript isoforms per protein-coding gene were expressed in yeast. Hundreds of short coding RNAs and truncated versions of proteins are concomitantly encoded by alternative transcript isoforms, increasing protein diversity. In addition, approximately 70% of genes express alternative isoforms that vary in post-transcriptional regulatory elements, and tandem genes frequently produce overlapping or even bicistronic transcripts. This extensive transcript diversity is generated by a relatively simple eukaryotic genome with limited splicing, and within a genetically homogeneous population of cells. Our findings have implications for genome compaction, evolution and phenotypic diversity between single cells. These data also indicate that isoform diversity as well as RNA abundance should be considered when assessing the functional repertoire of genomes.

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Primary accessions

Gene Expression Omnibus

Data deposits

The data reported in this paper have been deposited in GEO under accession number GSE39128 and are also accessible at http://steinmetzlab.embl.de/TIFSeq.

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Acknowledgements

We thank R. Aiyar for help in editing and refining the manuscript. We thank W. Huber, C. Zhu, A. I. Järvelin, S. Clauder-Münster, J. Zaugg, S. Adjalley, G. Lin and the members of the Steinmetz laboratory for helpful discussions and critical comments on the manuscript. We thank V. N. Gladyshev and C. Pineau for sharing published data. This study was technically supported by the EMBL Genomics Core Facility. This study was financially supported by the National Institutes of Health (to L.M.S.). V.P. was supported by an EMBO fellowship.

Author information

Author notes

    • Vicent Pelechano
    •  & Wu Wei

    These authors contributed equally to this work.

Affiliations

  1. Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69117 Heidelberg, Germany

    • Vicent Pelechano
    • , Wu Wei
    •  & Lars M. Steinmetz
  2. Stanford Genome Technology Center, Stanford University, Palo Alto, California 94304, USA

    • Wu Wei
    •  & Lars M. Steinmetz

Authors

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Contributions

W.W., V.P. and L.M.S. conceived the project. V.P. developed the TIF-Seq method and performed experiments. W.W. and V.P. performed the analysis. V.P., W.W. and L.M.S. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Lars M. Steinmetz.

Supplementary information

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    Supplementary Information

    This file contains Supplementary Figures 1-24, Supplementary Methods, a Supplementary Discussion, Supplementary Tables 1-5, legends for the Supplementary Data (see separate file) and Supplementary References.

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    Supplementary Data

    This zipped file contains Supplementary Data files 1-10 – see Supplementary Information for full legends. Supplementary Data 10 was updated on 4 July 2013 to correct a misannotation.

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DOI

https://doi.org/10.1038/nature12121

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