Suppression of ERK signalling promotes pluripotent epiblast in the human blastocyst [RNA-seq I]
RNA-seq (gene expression) · human · 134 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
- 134 samples: 8 conditions, mostly with about 40 replicates eachGroups 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
- Suppression of ERK signalling promotes pluripotent epiblast in the human blastocystNature communications · 2025
Read the full summary ↓
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 GSE239843_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 PRJNA1001047 and SRA study SRP452661. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 133 samples.
How we read this: 8 replicated groups read from 134 sample titles; they account for 133 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.
- GSM7675221 Human_DMSO_1_1 Human_DMSO_1
- GSM7675222 Human_DMSO_1_2 Human_DMSO_1
- GSM7675223 Human_DMSO_1_3 Human_DMSO_1
- GSM7675224 Human_DMSO_1_4 Human_DMSO_1
- GSM7675225 Human_DMSO_1_5 Human_DMSO_1
- GSM7675226 Human_DMSO_1_6 Human_DMSO_1
- GSM7675227 Human_DMSO_1_7 Human_DMSO_1
- GSM7675228 Human_DMSO_1_8 Human_DMSO_1
- GSM7675229 Human_DMSO_1_9 Human_DMSO_1
- GSM7675230 Human_DMSO_1_10 Human_DMSO_1
- GSM7675231 Human_DMSO_1_11 Human_DMSO_1
- GSM7675232 Human_DMSO_1_12 Human_DMSO_1
- GSM7675233 Human_DMSO_1_13 Human_DMSO_1
- GSM7675234 Human_DMSO_1_14 Human_DMSO_1
- GSM7675235 Human_DMSO_1_15 Human_DMSO_1
- GSM7675236 Human_DMSO_1_16 Human_DMSO_1
- GSM7675237 Human_DMSO_1_17 Human_DMSO_1
- GSM7675238 Human_DMSO_1_18 Human_DMSO_1
- GSM7675239 Human_DMSO_2_1 Human_DMSO_2
- GSM7675240 Human_DMSO_2_2 Human_DMSO_2
- GSM7675241 Human_DMSO_2_3 Human_DMSO_2
- GSM7675242 Human_DMSO_2_4 Human_DMSO_2
- GSM7675243 Human_DMSO_2_5 Human_DMSO_2
- GSM7675244 Human_DMSO_2_6 Human_DMSO_2
- GSM7675245 Human_DMSO_2_7 Human_DMSO_2
- GSM7675246 Human_DMSO_2_8 Human_DMSO_2
- GSM7675247 Human_DMSO_2_9 Human_DMSO_2
- GSM7675248 Human_DMSO_2_10 Human_DMSO_2
- GSM7675249 Human_DMSO_2_11 Human_DMSO_2
- GSM7675250 Human_Ulix_1_1 Human_Ulix_1
- GSM7675251 Human_Ulix_1_2 Human_Ulix_1
- GSM7675252 Human_Ulix_1_3 Human_Ulix_1
- GSM7675253 Human_Ulix_1_4 Human_Ulix_1
- GSM7675254 Human_Ulix_1_5 Human_Ulix_1
- GSM7675255 Human_Ulix_1_6 Human_Ulix_1
- GSM7675256 Human_Ulix_1_7 Human_Ulix_1
- GSM7675257 Human_Ulix_1_8 Human_Ulix_1
- GSM7675258 Human_Ulix_2_1
- GSM7675259 Human_DMSO_3_1 Human_DMSO_3
- GSM7675260 Human_DMSO_3_2 Human_DMSO_3
+ 94 more — browse all 134 samples with per-sample file links →
- GSE235092 Pre-existing skin-resident CD8 and γδ T cell circuits mediate immune response in Merkel cell carcinoma and Predict immunotherapy efficacy [bulkRNA-seq] 85 samples shares erk, rna-seq
- GSE326661 Reprogramming engineered autologous T cells to overcome resistance in Merkel cell carcinoma [scRNA-seq] 22 samples shares erk, rna-seq
- GSE312098 Overcoming ADC resistance in advanced colorectal cancer by dual targeting of TROP2 and PERK to suppress Wnt/β-catenin signaling [TROP2+GSK RNA-Seq] 12 samples shares erk, rna-seq
- GSE300083 The Lysine Demethylase Kdm4C is an Oncogenic Driver and Regulates ERK Activity in KRAS Mutant Pancreatic Ductal Adenocarcinoma [RNA-Seq] 12 samples shares erk, rna-seq
- GSE224698 Gene expression profiles of human dermal fibroblasts and human pluripotent stem cells analyzed by bulk RNA-seq 69 samples shares pluripotent, rna-seq
- GSE255982 Persistent epigenome anomalies in induced pluripotent stem cells from late-onset sporadic Alzheimer’s disease cases [RNA-seq] 52 samples shares pluripotent, rna-seq
- GSE274217 METTL3-dependent m6A RNA methylation represses transposable elements derived enhancers to suppress naïve pluripotency in human pluripotent stem cells [RNA-Seq] 28 samples shares pluripotent, rna-seq
- GSE269571 Generation of Stable Chambered Cardioids from human Pluripotent Stem Cells [bulk RNA-seq] 24 samples shares pluripotent, rna-seq
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.