Nascent RNA and Poly(A) RNA Seq from S2 cells [RNA-seq]
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA480280 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7500640.fastq.gz | Fastqsanger.gz | |||
| SRR7500641.fastq.gz | Fastqsanger.gz | |||
| SRR7500642.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 3 of 3 |
Similar Datasets
Project description:Nascent RNA and Poly(A) RNA Seq from S2 cells UPF1 is an ATP-driven RNA helicase required for efficient nonsense mediated mRNA decay in eukaryotes. Although it is currently understood that UPF1 primarily acts on the 3’UTR of translating mRNAs in the cytoplasm, our data indicates that this is a highly dynamic protein that is rapidly shuttling between nucleus and cytoplasm in Drosophila. Additionally, ChIP-seq analysis in different cell types demonstrates genome-wide association of UPF1 with nascent RNAs at most of the active Pol II transcription sites, and at some specific Pol III genes. Notably, intron recognition appears to interfere with association and translocation of UPF1 on nascent transcripts. Cells depleted of UPF1 show defects in nuclear processes such as mRNA export and transcription site retention. These data, thus redefine UPF1 as a global player in mRNA based processes in the nucleus as well as the cytoplasm.
2019-04-01 | GSE116807 | GEO
Project description:METTL16 belong to methyltransferase like (METTL) family and possesses the ability to deposit N6-methyladenosine (m6A) in mRNA. We have conducted m6A-seq with poly(A) RNAs isolated from the whole HEK293T cells upon METTL16 knockdown to identify the transcripts with hypo m6A peaks after METTL16 knockdown, and also conducted RIP-seq with HEK293T cells to determine the METTL16-bound transcripts. However, we found that the transcripts with hypo m6A peaks upon METTL16 knockdown only account for a small proportion of METTL16-bound transcripts. We suppose one of the possibility reasons might be due to spatiotemporal installation of m6A. To support our hypothesis, we performed additional m6A seq with nascent RNA and nuclear poly(A) RNA isolated from HEK293T cells with METTL16 knockdown.
2021-10-28 | GSE156795 | GEO
Project description:Determine METTL16-mediated spatiotemoral installation of m6A via MeRIP-seq (m6A-seq) with nascent RNA and nuclear poly(A) RNA
| PRJNA659037 | ENA
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.
2021-06-22 | PXD026828 | Pride
Project description:To determine the prevalence of cotranscriptional splicing in Drosophila, we sequenced nascent RNA transcripts from Drosophila S2 cells as well as from Drosophila heads. 87% of introns assayed manifest more than 50% cotranscriptional splicing. The remaining 13% are cotranscriptionally spliced poorly, or slowly, with ~3% being almost completely retained in nascent pre-mRNA. Although individual introns showed slight but statistically significant differences in splicing efficiency, similar global levels of splicing were seen from both sources. Importantly, introns with low cotranscriptional splicing efficiencies are present in the same primary transcript with efficiently spliced introns, indicating that splicing is intron-specific. The analysis also indicates that cotranscriptional splicing is less efficient for first introns, longer introns and introns annotated as alternative. FinallyFinally, S2 cells expressing the slow RpII215C4 mutant manifest substantially less intron retention than wild-type S2 cells. Examination of Total pA and Nascent RNA from 2 different cell populations and isolated fly heads.
2011-12-01 | E-GEOD-32950 | biostudies-arrayexpress
Project description:RNA-Seq in Drosophila melanogaster S2 cells
| PRJNA606761 | ENA
Project description:RNA-Seq procedure was used for analysis of expression in S2 cells.
2020-12-31 | GSE145320 | GEO
Project description: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.
2014-02-21 | E-GEOD-39878 | biostudies-arrayexpress
Project description:Over the past decade, genome-wide assays have underscored the broad sweep of circadian gene expression. A substantial fraction of the transcriptome undergoes oscillations in many organisms and tissues, which governs the many biochemical, physiological and behavioral functions under circadian control. Based predominantly on the transcription feedback loops important for core circadian timekeeping, it is commonly assumed that this widespread mRNA cycling reflects circadian transcriptional cycling. To address this issue, we directly measured dynamic changes in mouse liver transcription using Nascent-Seq. Many genes are rhythmically transcribed over the 24h day, which include precursors of several non-coding RNAs as well as the expected set of core clock genes. Surprisingly however, nascent RNA rhythms overlap poorly with mRNA abundance rhythms assayed by RNA-seq. This is because most mouse liver genes with rhythmic mRNA expression manifest poor transcriptional rhythms, indicating a prominent role of post-transcriptional regulation in setting mRNA cycling amplitude. To gain further insight into circadian transcriptional regulation, we also characterized the rhythmic transcription of liver genes targeted by the transcription factors CLOCK and BMAL1; they directly target other core clock genes and sit at the top of the molecular circadian clock hierarchy in mammals. CLK:BMAL1 rhythmically bind at the same discrete phase of the circadian cycle to all target genes, which not surprisingly have a much higher percentage of rhythmic transcription than the genome as a whole. However, there is a surprisingly heterogeneous set of cycling transcription phases of direct target genes, which even include core clock genes. This indicates a disconnect between rhythmic DNA binding and the peak of transcription, which is likely due to other transcription factors that collaborate with CLK:BMAL1. In summary, the application of Nascent-Seq to a mammalian tissue provides surprising insights into the rhythmic control of gene expression and should have broad applications beyond the analysis of circadian rhythms. Mouse liver nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina GAII (Nascent-Seq); Mouse liver mRNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (RNA-Seq); CLK and BMAL1 DNA binding profile in the mouse liver at ZT8, sequenced along an Input sample using GAII (ChIP-Seq); Mouse liver strand-specific nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (Strand-specific Nascent-Seq); Supplementary file NascentSeq_Mouse_Liver_NormalizedGeneSignal.txt represents Nascent RNA abundance (reads per base pair) for each sample.
2012-11-10 | E-GEOD-36872 | biostudies-arrayexpress