Unknown,Transcriptomics,Genomics,Proteomics

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RNA-DNA DIFFERENCES IN NASCENT RNA

ABSTRACT: RNA sequences are expected to be identical to their corresponding DNA sequences. Advances in technologies have enabled deep sequencing of nucleic acids that uncovered exceptions to the one-to-one relationship between DNA and RNA sequences. Previously in human cells, post-transcriptional RNA editing was the only known mechanism that changes RNA sequences from the underlying DNA sequences. Here, we sequenced nascent RNA and found all 12 types of RNA-DNA differences. Using various experimental analyses, we validated this finding. Our results showed that sequences of nascent RNAs within 40 nucleotides of the exit channel of RNA polymerase II already differ from the corresponding DNA sequences. These RNA-DNA differences are mediated by RNA processing steps closely coupled with transcription and not by known deaminase-mediated RNA editing mechanisms nor during NTP incorporation by Pol II. This finding identifies sequence substitution as part of co-transcriptional RNA processing. We sequenced nascent RNA using global run-on sequencing, GRO-seq from human B-cells from two individuals and a variant of the GRO-seq procedure, known as precision run-on sequencing, PRO-seq. The RNAs are prepared after a short run-on assay performed with isolated nuclei in the presence of Br-UTP. The isolated RNAs are base hydrolyzed to ~100 nucleotides and affinity purified with anti-BrU beads three times at each successive step of preparing the RNAs for orientation-specific sequencing using Illumina technology. The 5M-bM-^@M-^Y ~half of each sequence represents nascent RNA made in the cell and the 3M-bM-^@M-^Y ~half represents sequences made in vitro during the run-on reaction. The precision variation, PRO-seq, incorporates one or at most a few biotin-labeled nucleoside triphosphates during the run-on, and sequencing from the 3M-bM-^@M-^Y end of this affinity purified, nascent RNA maps the cellular location of engaged polymerases with near single nucleotide precision. We obtained ~ 100 million 100-nucleotide uniquely mapped GRO-seq reads from B-cells of two individuals. For one subject, we also carried out pGRO-seq and obtained 60 million uniquely mapped reads. In addition, we sequenced ~135 million uniquely mapped RNA-seq reads, and the corresponding DNA of the two individuals to 30X and 60X coverage. Additionally, we isolated and sequenced nascent RNA with an alternate method described by Wuarin and Schibler (1994) in order to compare chromatin-bound RNA to the very nascent RNA from PRO-seq. We obtained ~190 million uniquely mapped reads from chormatin-bound RNA-seq.

ORGANISM(S): Homo sapiens

SUBMITTER: Isabel Wang

PROVIDER: E-GEOD-39878 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

RNA-DNA differences are generated in human cells within seconds after RNA exits polymerase II.

Wang Isabel X IX Core Leighton J LJ Kwak Hojoong H Brady Lauren L Bruzel Alan A McDaniel Lee L Richards Allison L AL Wu Ming M Grunseich Christopher C Lis John T JT Cheung Vivian G VG

Cell reports 20140220 5

RNA sequences are expected to be identical to their corresponding DNA sequences. Here, we found all 12 types of RNA-DNA sequence differences (RDDs) in nascent RNA. Our results show that RDDs begin to occur in RNA chains ~55 nt from the RNA polymerase II (Pol II) active site. These RDDs occur so soon after transcription that they are incompatible with known deaminase-mediated RNA-editing mechanisms. Moreover, the 55 nt delay in appearance indicates that they do not arise during RNA synthesis by P ...[more]

PMID: 24561252

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Project description:We developed native elongating transcript sequencing (NET-seq, Churchman and Weissman Nature 2011, PMID: 21248844) combined with RNase footprinting of nascent transcripts (RNET-seq) to visualize translocation dynamics and nascent transcript errors in paused RNA polymerases in E. coli. We employed RNET-seq to the wild-type (WT) E. coli strain and to an isogenic strain deficient in genes for GreA and GreB (ΔgreAB). Gre factors and their eukaryotic analog TFIIS rescue backtracked complexes of RNAP. Briefly, the cells were rapidly lysed via spheroplasting, and the transcribing RNAPs were released from the genomic DNA by digestion with DNase I. Any ribosomes involved in co-transcriptional translation were separated from RNAP by digestion with RNase A. All RNAPs including those associated with the fragmented double-stranded DNAs and their 5’-truncated nascent RNAs were immobilized on Ni2+-NTA beads through the hexa-histidine-tagged β’ subunit and then extensively washed with a high-salt buffer. The 5’ ends of the transcripts in ECs were trimmed with RNase T1/V1 to leave a minimal length of RNA protected by RNAP. The RNases were subsequently removed by further washing of the beads. Elution with imidazole generated ECs carrying ~6-30 nt long transcripts. The nascent RNAs isolated from the ΔgreAB strain were longer than those from the WT strain and peaked at 18 nt versus 16 nt suggesting an enrichment of backtracked ECs, which is expected to occur in the absence of Gre-dependent 3’ RNA cleavage. The RNET-seq method involves trimming of excess nascent RNA from the 5’ ends leaving only the nascent RNA that is protected by RNAP. A previous in vitro study showed that an RNAP forming an EC protects different lengths of the 3’-proximal transcript from trimming by RNases A and T1 depending on the EC translocation state. Post-translocated, pre-translocated, and backtracked complexes protect 14-nt, 15-nt and >15-nt segments of the RNA, respectively. Because the very 3’ end of the RNA is extruded to a narrow pore within front of the enzyme during backtracking, the extruded RNA remains inaccessible to RNases increasing in length as backtracking increases. Thus, paused RNAP in either the pre- and post-translocated states as well as in different backtracked distances were monitored over the entire genome. The unique properties of our RNET-seq approach provided an opportunity to dissect the core mechanisms of different types of pausing in living cells.

Project description:Transcript abundance results from the balance between transcription and mRNA decay, and varies pervasively in humans. We have examined the effect of DNA variation on mRNA half-life differences by conducting a genome-wide survey of mRNA stability in seven human HapMap lymphoblastoid cell lines (LCLs). We determined the mRNA half-life for each gene from the ratio of 4-thio-uridine (4sU)-labeled nascent RNAs to total RNAs. 5,145 (46%) of 11,132 analyzed genes showed inter-individual mRNA half-life differences at a false discovery rate, FDR<0.05. As previously reported, we found transcription to be the main factor influencing transcript abundance. Although mRNA half-life explained only ~6% of transcript abundance on average, it explained ~16% for the subset of genes (~10%) showing inter-individual mRNA half-life differences (P<0.001). We confirmed previously reported correlations of mRNA half-life with transcript length, 3M-bM-^@M-^Y-UTR length, and number of exon-junctions per kb of transcript. The number of miRNA targets in 3M-bM-^@M-^Y-UTRs was negatively correlated with half-life (P=2.2M-CM-^W10-16), a new observation that is consistent with the role of miRNA in inducing mRNA degradation. Notably, coding GC and GC3 content showed positive correlations with mRNA half-life in genes with inter-individual mRNA half-life differences, implying a role of mRNA stability in shaping synonymous codon usage bias. Consistently, G or C alleles of coding SNPs were found associated with longer mRNA half-life (P=0.021). As expected, we also found that nonsense SNPs were associated with shorter mRNA half-life (P=0.009). Our results strongly suggest that inter-individual mRNA stability differences are widespread and affected by DNA sequence and composition variation. A total of 7 HapMap LCLs were used to measure mRNA half-life. Total RNAs and the 4sU-labeled-newly synthesized RNAs (nascent RNAs) were isolated from the same cell culture and were assayed simultaneously with human Exon array. For 3 LCLs, we included 3 biological replicates (i.e., independent cell cultures) and for 1 LCL we also included technical duplicates. mRNA half-life was calculated from the ratio of nascent RNAs/total RNAs. We used ANOVA to test inter-individual difference of mRNA half-life between 3 subjects who have biological replicates and technical duplicates. We examined the Spearman rank correlation of mRNA half-life with a number of gene features, including transcript length, intron length, 5'-UTR length and folding energy, 3'-UTR length and folding energy, microRNA target sites, GC and GC3 contents, etc. We also performed linear regression to test the effects of specific type of sequence variants (nonsense SNPs, SNPs within miRNA target sites, and coding synonymous and nonsynonymous SNPs) on mRNA half-life across 3 subjects that have whole genome sequencing data available (1000 genome project June 2011 release).

Dataset Information

RNA-DNA DIFFERENCES IN NASCENT RNA

Publications

RNA-DNA differences are generated in human cells within seconds after RNA exits polymerase II.

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