Single-cell nascent transcription is sparse and heterogeneous, revealing cellular plasticity [pro-seq]
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1168888 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR30885239_1.fastq.gz | Fastqsanger.gz | |||
| SRR30885239_2.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 2 of 2 |
Similar Datasets
Project description:Single-cell nascent transcription is sparse and heterogeneous, revealing cellular plasticity [EU_seq]
| PRJNA1168886 | ENA
Project description:Single-cell nascent transcription is sparse and heterogeneous, revealing cellular plasticity [single_cell]
| PRJNA1168887 | ENA
Project description:Single-cell nascent RNA sequencing is essential for understanding how a genome drives cell diversity. We developed scFLUENT-seq, a single-cell method that captures genome-wide transcription with brief metabolic labeling. Our analysis shows that only 3~6% of the genome is transcribed per cell in a 10-minute window, compared to over 80% in bulk, revealing significant variability in how individual cells interpret the genome. Notably, substantial transcription occurs in intergenic regions, particularly in heterochromatin, with high stochasticity. Moreover, promoter-associated antisense and genic sense transcription rarely co-occur in the same cell. Distal intergenic transcription correlates poorly with gene activity but links to increased genome-wide transcriptional diversity, which marks cellular plasticity and may precede cell-state shifts. Furthermore, mRNA synthesis and decay are uncoupled at the single-cell level, unlike intergenic ncRNA, suggesting specialized mechanisms counteracting stochastic noncoding production. In summary, scFLUENT-seq captures the full transcriptional spectrum, revealing the heterogeneity and regulatory complexity underlying cellular plasticity.
2024-10-09 | GSE278776 | GEO
Project description:Single-cell nascent RNA sequencing is essential for understanding how a genome drives cell diversity. We developed scFLUENT-seq, a single-cell method that captures genome-wide transcription with brief metabolic labeling. Our analysis shows that only 3~6% of the genome is transcribed per cell in a 10-minute window, compared to over 80% in bulk, revealing significant variability in how individual cells interpret the genome. Notably, substantial transcription occurs in intergenic regions, particularly in heterochromatin, with high stochasticity. Moreover, promoter-associated antisense and genic sense transcription rarely co-occur in the same cell. Distal intergenic transcription correlates poorly with gene activity but links to increased genome-wide transcriptional diversity, which marks cellular plasticity and may precede cell-state shifts. Furthermore, mRNA synthesis and decay are uncoupled at the single-cell level, unlike intergenic ncRNA, suggesting specialized mechanisms counteracting stochastic noncoding production. In summary, scFLUENT-seq captures the full transcriptional spectrum, revealing the heterogeneity and regulatory complexity underlying cellular plasticity.
2024-10-09 | GSE278777 | GEO
Project description:Single-cell nascent RNA sequencing is essential for understanding how a genome drives cell diversity. We developed scFLUENT-seq, a single-cell method that captures genome-wide transcription with brief metabolic labeling. Our analysis shows that only 3~6% of the genome is transcribed per cell in a 10-minute window, compared to over 80% in bulk, revealing significant variability in how individual cells interpret the genome. Notably, substantial transcription occurs in intergenic regions, particularly in heterochromatin, with high stochasticity. Moreover, promoter-associated antisense and genic sense transcription rarely co-occur in the same cell. Distal intergenic transcription correlates poorly with gene activity but links to increased genome-wide transcriptional diversity, which marks cellular plasticity and may precede cell-state shifts. Furthermore, mRNA synthesis and decay are uncoupled at the single-cell level, unlike intergenic ncRNA, suggesting specialized mechanisms counteracting stochastic noncoding production. In summary, scFLUENT-seq captures the full transcriptional spectrum, revealing the heterogeneity and regulatory complexity underlying cellular plasticity.
2024-10-09 | GSE278775 | GEO
Project description:Revealing nascent RNA processing dynamics with nano-COP
| PRJNA645078 | ENA
Project description:Collateral Responses to Classical Cytotoxic Chemotherapies are Heterogeneous and Sensitivities are Sparse
| PRJNA700876 | ENA
Project description:miRNAs are key post-transcriptional regulators of gene expression. However, it is still poorly understood how miRNAs themselves are regulated, mainly due to the sparse annotation of miRNA transcription start sites (TSSs). Here, we developed a novel method for identifying active miRNA TSSs from nascent transcriptomes generated by nuclear run-on sequencing. With the least data requirement, our method demonstrated better performance than existing methods. Moreover, it provided ways not only to recognize miRNA TSSs but also to quantify primary miRNA expression in one experiment, which is very useful for revealing miRNAs directly regulated by the regulator(s) of interest.
2017-04-20 | GSE97143 | GEO
Project description:During maturation, eukaryotic precursor RNAs undergo processing events including intron splicing, 3’-end cleavage, and polyadenylation. Here, we describe nanopore analysis of CO-transcriptional Processing (nano-COP), a method for probing the timing and patterns of RNA processing. An extension of native elongating transcript sequencing (NET-seq), which quantifies transcription genome-wide through short-read sequencing of nascent RNA 3’ ends, nano-COP uses long-read nascent RNA sequencing to observe global patterns of RNA processing. First, nascent RNA is stringently purified through a combination of 4-thiouridine metabolic labeling and cellular fractionation. In contrast to cDNA or short-read–based approaches relying on reverse transcription or amplification, the sample is sequenced directly through nanopores to reveal the native context of nascent RNA. nano-COP identifies both active transcription sites and splice isoforms of single RNA molecules during synthesis, providing insight into patterns of intron removal and the physical coupling between transcription and splicing. The nano-COP protocol yields data within 3 days.
2021-01-06 | GSE154079 | GEO
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