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Extensive transcriptional heterogeneity revealed by isoform profiling


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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Figure 1: Genome-wide measurement of transcript isoform diversity using TIF-Seq.
Figure 2: Extensive isoform diversity revealed among overlapping RNA populations, both at the genomic and single-gene level.
Figure 3: Transcript isoforms with varying regulatory elements and independent short coding RNAs.
Figure 4: Alternative transcript isoforms increase coding diversity.

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The data reported in this paper have been deposited in GEO under accession number GSE39128 and are also accessible at


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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.

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Authors and Affiliations



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.

Corresponding author

Correspondence to Lars M. Steinmetz.

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The authors declare no competing financial interests.

Supplementary information

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. (PDF 2848 kb)

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. (ZIP 15418 kb)

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Pelechano, V., Wei, W. & Steinmetz, L. Extensive transcriptional heterogeneity revealed by isoform profiling. Nature 497, 127–131 (2013).

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