Nuclear RNA sequencing of the mouse erythroid cell transcriptome

• Published in: PloS one 2012-11, Vol.7 (11), p.e49274-e49274
• Main Authors: Mitchell, Jennifer A, Clay, Ieuan, Umlauf, David, Chen, Chih-Yu, Moir, Catherine A, Eskiw, Christopher H, Schoenfelder, Stefan, Chakalova, Lyubomira, Nagano, Takashi, Fraser, Peter
• Format: Article
• Language: English
• Subjects: Animals; Biology; Chromatin; Chromatin Immunoprecipitation; Comparative analysis; Correlation; Correlation analysis; Deoxyribonucleic acid; DNA; DNA-directed RNA polymerase; Erythroid cells; Erythroid Cells - metabolism; Gene expression; Gene Expression Regulation; Gene Library; Gene loci; Gene sequencing; Genes; Genomes; Genomics; High-Throughput Nucleotide Sequencing; Immunoprecipitation; Laboratories; Messenger RNA; Mice; Poly(A); Post-transcription; Protein Binding; Regulatory sequences; Regulatory Sequences, Nucleic Acid; Reproducibility of Results; Ribonucleic acid; RNA; RNA polymerase; RNA polymerase II; RNA Polymerase II - genetics; RNA Polymerase II - metabolism; RNA sequencing; RNA, Long Noncoding - genetics; RNA, Long Noncoding - metabolism; RNA, Nuclear - genetics; Sequence Analysis, RNA; Spleen; Steady state; Stem cells; Studies; Transcription (Genetics); Transcription, Genetic; Transcriptome
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0049274

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.