Histone chaperon ASF1B recruits distinct epigenetic factors in regulation of histone variant H3.3 during the fetal and adult erythropoiesis.
RNA-seq (gene expression) · mouse · 54 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
- Mus musculus (mouse)
- Samples
- 54 samples: 18 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
- ASF1B promotes erythropoiesis by regulating the establishment and enrichment of H3.3 nucleosomesNucleic acids research · 2026
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 GSE215076_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 PRJNA888362 and SRA study SRP401612. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 54 samples.
How we read this: 18 replicated groups read from 54 sample titles; they account for 54 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.
- GSM6620815 WTS0 population-Rep1 WTS0 population
- GSM6620816 WTS0 population-Rep2 WTS0 population
- GSM6620817 WTS0 population-Rep3 WTS0 population
- GSM6620818 WTS1 population-Rep1 WTS1 population
- GSM6620819 WTS1 population-Rep2 WTS1 population
- GSM6620820 WTS1 population-Rep3 WTS1 population
- GSM6620821 WTS2 population-Rep1 WTS2 population
- GSM6620822 WTS2 population-Rep2 WTS2 population
- GSM6620823 WTS2 population-Rep3 WTS2 population
- GSM6620824 WTS3 population-Rep1 WTS3 population
- GSM6620825 WTS3 population-Rep2 WTS3 population
- GSM6620826 WTS3 population-Rep3 WTS3 population
- GSM6620827 WTS45 population-Rep1 WTS45 population
- GSM6620828 WTS45 population-Rep2 WTS45 population
- GSM6620829 WTS45 population-Rep3 WTS45 population
- GSM6620830 KOS0 population-Rep1 KOS0 population
- GSM6620831 KOS0 population-Rep2 KOS0 population
- GSM6620832 KOS0 population-Rep3 KOS0 population
- GSM6620833 KOS1 population-Rep1 KOS1 population
- GSM6620834 KOS1 population-Rep2 KOS1 population
- GSM6620835 KOS1 population-Rep3 KOS1 population
- GSM6620836 KOS2 population-Rep1 KOS2 population
- GSM6620837 KOS2 population-Rep2 KOS2 population
- GSM6620838 KOS2 population-Rep3 KOS2 population
- GSM6620839 KOS3 population-Rep1 KOS3 population
- GSM6620840 KOS3 population-Rep2 KOS3 population
- GSM6620841 KOS3 population-Rep3 KOS3 population
- GSM6620842 KOS45 population-Rep1 KOS45 population
- GSM6620843 KOS45 population-Rep2 KOS45 population
- GSM6620844 KOS45 population-Rep3 KOS45 population
- GSM6620845 WT E1 population-Rep1 WT E1 population
- GSM6620846 WT E1 population-Rep2 WT E1 population
- GSM6620847 WT E1 population-Rep3 WT E1 population
- GSM6620848 WT E2 population-Rep1 WT E2 population
- GSM6620849 WT E2 population-Rep2 WT E2 population
- GSM6620850 WT E2 population-Rep3 WT E2 population
- GSM6620851 WT E3 population-Rep1 WT E3 population
- GSM6620852 WT E3 population-Rep2 WT E3 population
- GSM6620853 WT E3 population-Rep3 WT E3 population
- GSM6620854 WT E4 population-Rep1 WT E4 population
+ 14 more — browse all 54 samples with per-sample file links →
- GSE276628 Reciprocal genetic screens identify epigenetics factors controlling epidermal cell activation. [RNAseq_MiniBulk] 41 samples shares epigenetic, factors
- GSE276632 Reciprocal genetic screens identify epigenetics factors controlling epidermal cell activation. 262 samples shares epigenetic, factors
- GSE157232 The CD8+ T cell tolerance checkpoint triggers a transcriptionally and epigenetically distinct differentiation state defined by protein translation defects 30 samples shares epigenetic, distinct
- GSE308116 Epigenetic modification, as a distinctive therapeutic molecule for Parkinson’s disease gene therapy. 17 samples shares epigenetic, distinct
- GSE283727 Histone 3 lysine 36 methylation shapes an epigenetic landscape in intestinal stem cell to orchestrate lipid metabolism and prevent cell senescence [CUT&Tag] 12 samples shares epigenetic, histone
- GSE241770 ACSS2 mediates an epigenetic pathway to regulate maternal Beta-cell adaptation and progression of gestational diabetes (scRNA-Seq) 7899 samples shares epigenetic
- GSE222745 Enhanced activities of OCT4 and SOX2 facilitates epigenetic reprogramming by modulating cell cycle [scRNA-Seq] 422 samples shares epigenetic
- GSE280168 The spatial zonation of the placental vasculature is specified by epigenetic mechanisms 383 samples shares epigenetic
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.