4.6 Article

Nuclear RNA Sequencing of the Mouse Erythroid Cell Transcriptome

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PLOS ONE
卷 7, 期 11, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0049274

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资金

  1. Medical Research Council
  2. Biotechnology and Biological Sciences Research Council, UK
  3. Natural Sciences and Engineering Research Council of Canada
  4. EMBO
  5. Ontario Graduate Scholarship
  6. National Human Genome Research Institute
  7. National Institutes of Health, Bethesda, MD, USA
  8. MRC [G0800036] Funding Source: UKRI
  9. Medical Research Council [G0800036] Funding Source: researchfish

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In addition to protein coding genes a substantial proportion of mammalian genomes are transcribed. However, most transcriptome studies investigate steady-state mRNA levels, ignoring a considerable fraction of the transcribed genome. In addition, steady-state mRNA levels are influenced by both transcriptional and posttranscriptional mechanisms, and thus do not provide a clear picture of transcriptional output. Here, using deep sequencing of nuclear RNAs (nucRNA-Seq) in parallel with chromatin immunoprecipitation sequencing (ChIP-Seq) of active RNA polymerase II, we compared the nuclear transcriptome of mouse anemic spleen erythroid cells with polymerase occupancy on a genome-wide scale. We demonstrate that unspliced transcripts quantified by nucRNA-seq correlate with primary transcript frequencies measured by RNA FISH, but differ from steady-state mRNA levels measured by poly(A)-enriched RNA-seq. Highly expressed protein coding genes showed good correlation between RNAPII occupancy and transcriptional output; however, genome-wide we observed a poor correlation between transcriptional output and RNAPII association. This poor correlation is due to intergenic regions associated with RNAPII which correspond with transcription factor bound regulatory regions and a group of stable, nuclear-retained long non-coding transcripts. In conclusion, sequencing the nuclear transcriptome provides an opportunity to investigate the transcriptional landscape in a given cell type through quantification of unspliced primary transcripts and the identification of nuclear-retained long non-coding RNAs.

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