mRNA juxtacap sequences govern mRNA translation and stability
RNA-seq (gene expression) · human · 40 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
- 40 samples: 20 conditions, mostly in duplicateGroups 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
- Decoding m(6)Am by simultaneous transcription-start mapping and methylation quantificationbioRxiv : 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 GSE188510_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 PRJNA779102 and SRA study SRP345324. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 40 samples.
How we read this: 20 replicated groups read from 40 sample titles; they account for 40 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.
- GSM5684315 WT 5' SLAM-seq 0 h rep1 WT 5' SLAM-seq 0 h
- GSM5684316 WT 5' SLAM-seq 2 h rep1 WT 5' SLAM-seq 2 h
- GSM5684317 WT 5' SLAM-seq 6 h rep1 WT 5' SLAM-seq 6 h
- GSM5684318 WT 5' SLAM-seq 12 h rep1 WT 5' SLAM-seq 12 h
- GSM5684319 PCIF1 KO 5' SLAM-seq 0 h rep1 PCIF1 KO 5' SLAM-seq 0 h
- GSM5684320 PCIF1 KO 5' SLAM-seq 2 h rep1 PCIF1 KO 5' SLAM-seq 2 h
- GSM5684321 PCIF1 KO 5' SLAM-seq 6 h rep1 PCIF1 KO 5' SLAM-seq 6 h
- GSM5684322 PCIF1 KO 5' SLAM-seq 12 h rep1 PCIF1 KO 5' SLAM-seq 12…
- GSM5684323 WT 5' SLAM-seq 0 h rep2 WT 5' SLAM-seq 0 h
- GSM5684324 WT 5' SLAM-seq 2 h rep2 WT 5' SLAM-seq 2 h
- GSM5684325 WT 5' SLAM-seq 6 h rep2 WT 5' SLAM-seq 6 h
- GSM5684326 WT 5' SLAM-seq 12 h rep2 WT 5' SLAM-seq 12 h
- GSM5684327 PCIF1 KO 5' SLAM-seq 0 h rep2 PCIF1 KO 5' SLAM-seq 0 h
- GSM5684328 PCIF1 KO 5' SLAM-seq 2 h rep2 PCIF1 KO 5' SLAM-seq 2 h
- GSM5684329 PCIF1 KO 5' SLAM-seq 6 h rep2 PCIF1 KO 5' SLAM-seq 6 h
- GSM5684330 PCIF1 KO 5' SLAM-seq 12 h rep2 PCIF1 KO 5' SLAM-seq 12…
- GSM5684331 WT input rep1 WT input
- GSM5684332 WT polysome fraction 1 rep1 WT polysome fraction 1
- GSM5684333 WT polysome fraction 2 rep1 WT polysome fraction 2
- GSM5684334 WT polysome fraction 3 rep1 WT polysome fraction 3
- GSM5684335 WT polysome fraction 4 rep1 WT polysome fraction 4
- GSM5684336 WT polysome fraction 5 rep1 WT polysome fraction 5
- GSM5684337 PCIF1 KO input rep1 PCIF1 KO input
- GSM5684338 PCIF1 KO polysome fraction 1 rep1 PCIF1 KO polysome fract…
- GSM5684339 PCIF1 KO polysome fraction 2 rep1 PCIF1 KO polysome fract…
- GSM5684340 PCIF1 KO polysome fraction 3 rep1 PCIF1 KO polysome fract…
- GSM5684341 PCIF1 KO polysome fraction 4 rep1 PCIF1 KO polysome fract…
- GSM5684342 PCIF1 KO polysome fraction 5 rep1 PCIF1 KO polysome fract…
- GSM5684343 WT input rep2 WT input
- GSM5684344 WT polysome fraction 1 rep2 WT polysome fraction 1
- GSM5684345 WT polysome fraction 2 rep2 WT polysome fraction 2
- GSM5684346 WT polysome fraction 3 rep2 WT polysome fraction 3
- GSM5684347 WT polysome fraction 4 rep2 WT polysome fraction 4
- GSM5684348 WT polysome fraction 5 rep2 WT polysome fraction 5
- GSM5684349 PCIF1 KO input rep2 PCIF1 KO input
- GSM5684350 PCIF1 KO polysome fraction 1 rep2 PCIF1 KO polysome fract…
- GSM5684351 PCIF1 KO polysome fraction 2 rep2 PCIF1 KO polysome fract…
- GSM5684352 PCIF1 KO polysome fraction 3 rep2 PCIF1 KO polysome fract…
- GSM5684353 PCIF1 KO polysome fraction 4 rep2 PCIF1 KO polysome fract…
- GSM5684354 PCIF1 KO polysome fraction 5 rep2 PCIF1 KO polysome fract…
- GSE325326 Codon-dependent regulation of mRNA translation and stability by ZC3H7A and ZC3H7B RNA-binding proteins 24 samples shares translation, stability, mrna
- GSE297337 Codon-dependent regulation of mRNA translation and stability by ZC3H7A and ZC3H7B RNA-binding proteins [Ribo-seq] 15 samples shares translation, stability, mrna
- GSE298022 JNK activation dynamics drive distinct gene expression patterns over time mediated by mRNA stability 45 samples shares stability, mrna
- GSE248571 m6A sites in the coding region trigger translation-dependent mRNA decay (RNA-seq) 32 samples shares translation, mrna
- GSE289390 pTα enhances mRNA translation and potentiates CAR T cells for solid tumor eradication [bulk RNA-seq] 25 samples shares translation, mrna
- GSE273217 m6A sites in the coding region trigger translation-dependent mRNA decay (SLAM-seq) 18 samples shares translation, mrna
- GSE266017 Effect of DHX29 depletion on mRNA stability in HEK293T cells 18 samples shares stability, mrna
- GSE313691 Translational Downregulation of 5’ TOP mRNAs During T Cell Exhaustion [RNA-Seq] 12 samples shares translation, mrna
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.