Effect of 4sU labeling concentrations on quantification bias in nucleotide conversion RNA-seq data
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE229504 | GEO | 2024/02/06
REPOSITORIES: GEO
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Project description:To investigate the effect of labeling durations on quantification bias in nucleotide conversion RNA-seq, we labeled NIH cells with 4sU. We then measured 4sU dropout in 4sU samples compared to 4sU naive samples.
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Project description:RNA synthesis and decay rates determine the steady-state levels of cellular RNAs. Metabolic tagging of newly transcribed RNA by 4-thiouridine (4sU) can reveal the relative contributions of RNA synthesis and decay rates. The kinetics of RNA processing, however, so far remained unresolved. Here, we show that ultra-short 4sU-tagging not only provides snap-shot pictures of eukaryotic gene expression but, when combined with progressive 4sU-tagging and RNA-seq, reveals global RNA processing kinetics at nucleotide resolution. Using this method, we identified classes of rapidly and slowly spliced/degraded introns. Interestingly, each class of splicing kinetics was characterized by a distinct association with intron length, gene length and splice site strength. For a large group of introns, we also observed long lasting retention in the primary transcript, but efficient secondary splicing or degradation at later time points. Finally, we show that processing of most, but not all small nucleolar (sno)RNA-containing introns is remarkably inefficient with the majority of introns being spliced and degraded rather than processed into mature snoRNAs. In summary, our study yields unparalleled insights into the kinetics of RNA processing and provides the tools to study molecular mechanisms of RNA processing and their contribution to the regulation of gene expression. 4sU-tagging was performed in human DG75 B-cells by adding 500 uM 4sU to cell culture medium for 5, 10, 15, 20 or 60 min. Following isolation of total cellular RNA, this was separated into nascent and untagged, pre-existing RNA. Nascent RNA as well as total and untagged RNA from 60 min 4sU-tagging were subjected to SOLiD sequencing (SOLiD II) obtaining 35 nt reads.
2012-04-25 | E-GEOD-31653 | biostudies-arrayexpress
Project description:RNA synthesis and decay rates determine the steady-state levels of cellular RNAs. Metabolic tagging of newly transcribed RNA by 4-thiouridine (4sU) can reveal the relative contributions of RNA synthesis and decay rates. The kinetics of RNA processing, however, so far remained unresolved. Here, we show that ultra-short 4sU-tagging not only provides snap-shot pictures of eukaryotic gene expression but, when combined with progressive 4sU-tagging and RNA-seq, reveals global RNA processing kinetics at nucleotide resolution. Using this method, we identified classes of rapidly and slowly spliced/degraded introns. Interestingly, each class of splicing kinetics was characterized by a distinct association with intron length, gene length and splice site strength. For a large group of introns, we also observed long lasting retention in the primary transcript, but efficient secondary splicing or degradation at later time points. Finally, we show that processing of most, but not all small nucleolar (sno)RNA-containing introns is remarkably inefficient with the majority of introns being spliced and degraded rather than processed into mature snoRNAs. In summary, our study yields unparalleled insights into the kinetics of RNA processing and provides the tools to study molecular mechanisms of RNA processing and their contribution to the regulation of gene expression.
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Project description:RNA metabolic labeling using 4-thiouridine (s4U) can be used to capture the dynamics of RNA synthesis and decay. The power of this approach is dependent on appropriate quantification of labeled and unlabeled sequencing reads, which can be compromised by the apparent loss of s4U-labeled reads in a process we refer to as dropout. Here we show that s4U-containing transcripts can be selectively lost when RNA samples are handled under sub-optimal conditions, but that this loss can be minimized using an optimized protocol. We demonstrate a second cause of dropout in nucleotiderecoding and RNA sequencing (NR-seq) experiments that is computational and downstream of library preparation. NR-seq experiments involve chemically converting s4U from a uridine analog to a cytidine analog and the apparent T-to-C mutations are then used to identify the populations of newly synthesized RNA. We show that high levels of T-to-C mutations can prevent read alignment with some computational pipelines, but that this bias can be overcome using improved alignment pipelines. Importantly, kinetic parameter estimates are affected by dropout independent of the NR chemistry employed, and all chemistries are practically indistinguishable in bulk, short-read RNA-seq experiments. Dropout is an avoidable problem that can be identified by including unlabeled controls, and mitigated through improved sample handing and read alignment that together improve the robustness and reproducibiltiy of NR-seq experiments.
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Project description:Genomes are pervasively transcribed leading to stable and unstable transcripts that define functional regions of genomes and contribute to cellular phenotypes. Defining comprehensive nascent transcriptomes is pivotal to understand gene regulation, disease processes, and the impact of extracellular signals on cells. However, currently employed methods are laborious, technically challenging and costly. We developed single-nucleotide resolution 4sU-sequencing (SNU-Seq), involving pulse labelling, biotinylation and direct isolation of nascent transcripts. Artificial poly-(A)-tailing of the 3’ most nucleotide of nascent transcripts ensures oligo-d(T) primer-based library preparation and sequencing using commercial 3’ RNA-Seq kits. We show that SNU-Seq is a cost-effective new method generating even read profiles across transcription units. We used SNU-Seq to identify transcription elongation parameters, to map usage of polyadenylation (PAS) sites and novel enhancers. Remarkably, 4sU labelled nascent RNA accumulates short ~100nt transcripts that map to the 5’ end of genes. We show that isolation of these short nascent RNA and sequencing the 5’ and 3’ ends using size-selected SNU-Seq (ssSNU-Seq) provides highly sensitive annotations of mapped and novel TSSs, promoter-proximal pause/termination sites. Thus, SNU-seq and ssSNU-seq combined yield comprehensive transcriptomics data at low cost with high spatial and temporal resolution.
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Project description:Noncoding variants play a central role in the genetics of complex traits, but we still lack a full description of the main molecular pathways through which they act. Here we used molecular data to quantify the contribution of cis-acting genetic effects at each major stage of gene regulation from chromatin to proteins, within a population sample of Yoruba lymphoblastoid cell lines (LCLs). We performed 4sU metabolic labeled transcripts in 65 YRI LCLs to identify genetic variants that affect transcription rates. As expected, we found an important contribution of genetic variation via chromatin, contributing â¼65% of eQTLs (expression Quantitative Trait Loci). The remaining eQTLs, which are not asso- ciated with chromatin-level variation, are highly enriched in transcribed regions, and hence may affect expression through co- or post-transcriptional processes. International HapMap lymphoblastoid cell lines (LCLs) derived from YRI (Yoruba in Ibadan, Nigeria); We adapted the 4sU labelling method from (PMID 21516085). Briefly, cell cultures were grown to log phase in volumes sufficient to yield about 300 ng of 4sU-labeled RNA. Cells were incubated with 4sU for the required length of time (0, 30, or 60 minutes), then washed, pelleted, and frozen. Total RNA was extracted, and 4sU-labeled RNA was separated from total RNA using a bead-based biotin-streptavidin purification protocol. We sequenced metabolic labeled transcripts in 65 YRI LCLs 30 minutes and 60 minutes after incubation.
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Project description:Swiss murine embryonic fibroblasts (NIH-3T3) were infected with wild-type Smith strain mouse cytomegalovirus (MCMV) at a multiplicity of infection (MOI) of 10. Sequencing libraries were prepared using the 4sU-seq protocol (Dölken et al., RNA 2008 and Rutkowski et al.) from the indicated time points of infection as described in Rutkowski, A.J. et al, Nat. Commun (2015)
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