Project description:To test the role of Mpe1 in transcription termination we inserted a mini-auxin induced degron (mAID) at the C-terminal end of the endogenous MPE1 locus in the yeast Saccharomyces cerevisiae. We treated Mpe1-mAID cells (JRY101) or wild type cells (WT, YMK728) with 1 mM auxin for 30 minutes and labeled the nascent RNA with 4-thiouracil (4tU) for 6 minutes. The nascent RNA fraction was prepared by biotinylating the 4tU-labeled RNA followed purification with streptavidin beads. Nascent and total RNA fractions were depleted of ribosomal RNA and strand-specific libraries prepared. Libraries were single-end sequenced using an Ilummina HiSeq 4000 instrument.
Project description:We have generated single-nucleotide resolution, nascent transcription profiles from HeLa cells by developing Native Elongation Transcript sequencing technology for mammalian chromatin (mNET-seq). Our extensive data sets provide a substantial resource to study mammalian nascent transcript profiles. We reveal unanticipated phosphorylation states for RNA polymerase II C-terminal domain (Pol II CTD) at both gene ends. We also observe that following 5’ splice site cleavage by the spliceosome, upstream exon transcripts are tethered to Pol II CTD phosphorylated on the serine 5 position (S5P) which is accumulated over downstream exons. We further show that depletion of termination factors substantially reduces Pol II pausing at gene ends leading to termination defects. Remarkably termination factors play an additional promoter role by restricting non-productive RNA synthesis and redistributing Pol II CTD S2P to promoters. These data demonstrate that CTD phosphorylation is more dynamic and variably distributed across mammalian transcription units than previously envisaged. To monitor nascent RNA within the mammalian Pol II complex, and its association with different CTD phosphorylation states, we employed mNET-seq methodology on HeLa cells, complemented with direct sequencing of chromatin-bound RNA (ChrRNA-seq). mNET-seq was preformed using the antibodies 8WG16, CMA602, CMA603 and CMA601, which are specific for unphosphorylated CTD, Ser2 phosphorylation, Ser5 phosphorylation and all CTD isoforms, respectively. In another experiment, to evaluate the effect of transcription termination factors in nascent RNA production by Pol II, mNET-seq and complemented with ChrRNA-seq was preformed on HeLa cells transfected with siRNA against PTBP1, CPSF73, CstF64+CstF64tau or Xrn2, and the gene profiles were compared with profiles from HeLa transfected with siRNA for Luciferase generated by the same protocol.
Project description:mRNAs are generally assumed to be loaded instantly with ribosomes upon entry into the cytoplasm. To measure ribosome density on nascent mRNA, we developed nascent Ribo-Seq (nRibo-Seq) by combining Ribo-Seq with progressive 4-thiouridine labelling. In mouse macrophages, we experimentally determined, for the first time, the lag between the appearance of nascent RNA and its association with ribosomes, which was calculated to be 20 - 22 min for bulk mRNA, and approximated the time it takes for mRNAs to be fully loaded with ribosomes to be 41 - 44 min. Notably, ribosomal loading time is adapted to gene function as rapid loading was observed with highly regulated genes. The lag and ribosomal loading time correlate positively with ORF size and mRNA half-life, and negatively with tRNA adaptation index. Similar results were obtained in mouse embryonic stem cells, where the lag in ribosome loading was even more pronounced with 35 - 38 min. We validated our measurements after stimulation of macrophages with lipopolysaccharide, where the lag between cytoplasmic and translated mRNA leads to uncoupling between input and ribosome-protected fragments. Uncoupling is stronger for mRNAs with long ORFs or half-lives, a finding we also confirmed at the level of protein production by nascent chain proteomics. As a consequence of the lag in ribosome loading, ribosome density measurements are distorted when performed under conditions where mRNA levels are far from steady state expression, and transcriptional changes affect ribosome density in a passive way. This study uncovers an unexpected and considerable lag in ribosome loading, and provides guidelines for the interpretation of Ribo-Seq data taking passive effects on ribosome density into account.