Cell-cycle dynamics of nascent transcription and mature RNA accumulation are concordant in normal fibroblasts
RNA-seq (gene expression) · human · 18 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 18 samples: 7 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Cell-cycle dynamics of nascent transcription and mature RNA accumulation are concordant in normal fibroblastsbioRxiv : the preprint server for biology · 2025
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE305617_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1306672 and SRA study SRP609226. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 18 samples.
How we read this: 7 replicated groups read from 18 sample titles; they account for 18 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM9180582 Nuclear run-on RNA, G1 population of BJ-Fucci cells, Rep1 Nuclear run-on RNA, G1 …
- GSM9180583 Nuclear run-on RNA, late S/G2/M population of BJ-Fucci cells, Rep1 Nuclear run-on RNA, lat…
- GSM9180584 Nuclear run-on RNA, early G1 population of BJ-Fucci cells, Rep1 Nuclear run-on RNA, ear…
- GSM9180585 Nuclear run-on RNA, G1 population of BJ-Fucci cells, Rep2 Nuclear run-on RNA, G1 …
- GSM9180586 Nuclear run-on RNA, late S/G2/M population of BJ-Fucci cells, Rep2 Nuclear run-on RNA, lat…
- GSM9180587 Nuclear run-on RNA, early G1 population of BJ-Fucci cells, Rep2 Nuclear run-on RNA, ear…
- GSM9180600 Poly A RNA, G1 population of BJ-Fucci cells, Rep1 Poly A RNA, G1 populati…
- GSM9180601 Poly A RNA, late S/G2/M population of BJ-Fucci cells, Rep1 Poly A RNA, late S/G2/M…
- GSM9180602 Poly A RNA, early G1 population of BJ-Fucci cells, Rep1 Poly A RNA, early G1 po…
- GSM9180603 Poly A RNA, early S population of BJ-Fucci cells, Rep1 Poly A RNA, early S pop…
- GSM9180604 Poly A RNA, G1 population of BJ-Fucci cells, Rep2 Poly A RNA, G1 populati…
- GSM9180605 Poly A RNA, late S/G2/M population of BJ-Fucci cells, Rep2 Poly A RNA, late S/G2/M…
- GSM9180606 Poly A RNA, early G1 population of BJ-Fucci cells, Rep2 Poly A RNA, early G1 po…
- GSM9180607 Poly A RNA, early S population of BJ-Fucci cells, Rep2 Poly A RNA, early S pop…
- GSM9180608 Poly A RNA, G1 population of BJ-Fucci cells, Rep3 Poly A RNA, G1 populati…
- GSM9180609 Poly A RNA, late S/G2/M population of BJ-Fucci cells, Rep3 Poly A RNA, late S/G2/M…
- GSM9180610 Poly A RNA, early G1 population of BJ-Fucci cells, Rep3 Poly A RNA, early G1 po…
- GSM9180611 Poly A RNA, early S population of BJ-Fucci cells, Rep3 Poly A RNA, early S pop…
- GSE297242 Effect of lactate accumulation on translation and transcription in MDA-MB-231 breast cancer cells 12 samples shares transcription, accumulation
- GSE245175 Neuroblastoma heterogeneity and plasticity over disease progression are rooted in the dynamics of an early sympathetic transcriptional trajectory 79 samples shares transcription, dynamics
- GSE182605 Integrative gene regulatory analysis reveals transcriptional mechanisms required in mature human hepatocytes and during in vitro hepatocyte differentiation 35 samples shares transcription, mature
- GSE325391 Unique transcriptional profiles of adult human immature neurons in healthy aging, Alzheimer’s disease, and cognitive resilience 27 samples shares transcription, mature
- GSE331144 Transcriptional and spatial profiling of fibroblasts from human lungs highlights CTHRC1+ cells as fibrogenic signaling hubs in fibrosis 9 samples shares transcription, fibroblasts
- GSE281556 Lysosomal sequestration of PARP inhibitors drives heterogeneous accumulation in ovarian cancer to increase efficacy 204 samples shares accumulation
- GSE337533 A Single-Cell Atlas of Transcriptional and Immunoglobulin Repertoire Evolution in Early B Cell Development 66 samples shares transcription
- GSE287976 Single-Cell Omics Analysis of Human Basophils Reveals Two Transcriptionally Distinct Populations 12 samples shares transcription
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.