Genome-wide pervasive transcription has been reported in many eukaryotic organisms1,2,3,4,5,6,7, revealing a highly interleaved transcriptome organization that involves hundreds of previously unknown non-coding RNAs8. These recently identified transcripts either exist stably in cells (stable unannotated transcripts, SUTs) or are rapidly degraded by the RNA surveillance pathway (cryptic unstable transcripts, CUTs). One characteristic of pervasive transcription is the extensive overlap of SUTs and CUTs with previously annotated features, which prompts questions regarding how these transcripts are generated, and whether they exert function9. Single-gene studies have shown that transcription of SUTs and CUTs can be functional, through mechanisms involving the generated RNAs10,11 or their generation itself12,13,14. So far, a complete transcriptome architecture including SUTs and CUTs has not been described in any organism. Knowledge about the position and genome-wide arrangement of these transcripts will be instrumental in understanding their function8,15. Here we provide a comprehensive analysis of these transcripts in the context of multiple conditions, a mutant of the exosome machinery and different strain backgrounds of Saccharomyces cerevisiae. We show that both SUTs and CUTs display distinct patterns of distribution at specific locations. Most of the newly identified transcripts initiate from nucleosome-free regions (NFRs) associated with the promoters of other transcripts (mostly protein-coding genes), or from NFRs at the 3′ ends of protein-coding genes. Likewise, about half of all coding transcripts initiate from NFRs associated with promoters of other transcripts. These data change our view of how a genome is transcribed, indicating that bidirectionality is an inherent feature of promoters. Such an arrangement of divergent and overlapping transcripts may provide a mechanism for local spreading of regulatory signals—that is, coupling the transcriptional regulation of neighbouring genes by means of transcriptional interference or histone modification.
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We thank A. Akhtar, A. Ladurner, S. Blandin, R. Aiyar, E. Mancera and E. Fritsch for comments on the manuscript, J. Toedling for discussion and for the template of the website, C. Girardot for data submission to ArrayExpress, N. Proudfoot for access to experimental equipment, and the contributors to the Bioconductor (http://www.bioconductor.org) and R (http://www.r-project.org) projects for their software. This work was supported by grants to L.M.S. from the National Institutes of Health and Deutsche Forschungsgemeinschaft, by a SystemsX fellowship to E.G., by a Roche fellowship to J.C. and by grants to F.S. from SNF and NCCR Frontiers in Genetics.
Author Contributions L.M.S., Z.X. and W.W. designed the research; Z.X. and W.W. annotated the transcripts with the help of J.G. and F.P.; W.W. and Z.X. performed analysis of the transcripts with the help of J.G.; F.P. and S.C.-M. performed the array hybridizations; J.C. E.G. and F.S. provided samples for the rrp6Δ mutant, and designed and performed validation polymerase chain reaction with reverse transcription and 5′ RACE experiments; L.M.S., J.G., F.S. and W.H. supervised the research; and L.M.S., Z.X., W.W., J.G. and W.H. wrote the manuscript.
Supplementary Table 3: Transcript boundaries for ORF-Ts, SUTs and CUTs
Supplementary Table 5: Primers used in this study, RT-PCR and 5 RACE results
Supplementary Table 6: List of SUTs with at least 2 fold increase in rrp6Δ vs. WT.
Supplementary Table 11: Transcripts initiating from shared NFRs
Supplementary Table 12: List of 19 examples like GAL80-SUR7
Supplementary Table 13: Expression level of transcript pairs containing SUTs