mRNA-Engineered CRISPR-Cas Epigenetic Editors Enable Durable and Efficient Gene Silencing in Vivo [RNA-seq]
RNA-seq (gene expression) · mouse · 66 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
- 66 samples: 66 samples, each with a distinct title — no replicated groupsGroups 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
- mRNA-engineered CRISPR-Cas epigenetic editors enable durable and efficient gene silencing in vivoInnovation (Cambridge (Mass.)) · 2026
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 GSE299303_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 PRJNA1273879 and SRA study SRP591210. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 66 sample titles: 66 distinct titles with little repetition. 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.
- GSM9036858 Mouse liver, Vehicle_1, Day 30, rep 1
- GSM9036859 Mouse liver, Vehicle_2, Day 30, rep 2
- GSM9036860 Mouse liver, Vehicle_3, Day 30, rep 3
- GSM9036861 Mouse liver, Vehicle_4, Day 90, rep 1
- GSM9036862 Mouse liver, Vehicle_5, Day 90, rep 2
- GSM9036863 Mouse liver, Vehicle_6, Day 90, rep 3
- GSM9036864 Mouse liver, SF01_EE_1, Day 30, rep 1
- GSM9036865 Mouse liver, SF01_EE_2, Day 30, rep 2
- GSM9036866 Mouse liver, SF01_EE_3, Day 30, rep 3
- GSM9036867 Mouse liver, SF01_EE_4, Day 30, rep 4
- GSM9036868 Mouse liver, SF01_EE_5, Day 30, rep 5
- GSM9036869 Mouse liver, SF01_EE_6, Day 30, rep 6
- GSM9036870 Mouse liver, SF01_EE_7, Day 90, rep 1
- GSM9036871 Mouse liver, SF01_EE_8, Day 90, rep 2
- GSM9036872 Mouse liver, SF01_EE_9, Day 90, rep 3
- GSM9036873 Mouse liver, SF01_EE_10, Day 90, rep 4
- GSM9036874 Mouse liver, SF01_EE_11, Day 90, rep 5
- GSM9036875 Mouse liver, SF01_EE_12, Day 90, rep 6
- GSM9036876 Mouse liver, Sp_EE_1, Day 30, rep 1
- GSM9036877 Mouse liver, Sp_EE_2, Day 30, rep 2
- GSM9036878 Mouse liver, Sp_EE_3, Day 30, rep 3
- GSM9036879 Mouse liver, Sp_EE_4, Day 30, rep 4
- GSM9036880 Mouse liver, Sp_EE_5, Day 30, rep 5
- GSM9036881 Mouse liver, Sp_EE_6, Day 30, rep 6
- GSM9036882 Mouse liver, Sp_EE_7, Day 90, rep 1
- GSM9036883 Mouse liver, Sp_EE_8, Day 90, rep 2
- GSM9036884 Mouse liver, Sp_EE_9, Day 90, rep 3
- GSM9036885 Mouse liver, Sp_EE_10, Day 90, rep 4
- GSM9036886 Mouse liver, Sp_EE_11, Day 90, rep 5
- GSM9036887 Mouse liver, Sp_EE_12, Day 90, rep 6
- GSM9036888 Mouse liver, Sp_EE_13, Day 120, rep 1
- GSM9036889 Mouse liver, Sp_EE_14, Day 120, rep 2
- GSM9036890 Mouse liver, Sp_EE_15, Day 120, rep 3
- GSM9036891 Mouse liver, Sp_EE_16, Day 120, rep 4
- GSM9036892 Mouse liver, Sp_EE_17, Day 120, rep 5
- GSM9036893 Mouse liver, Sp_EE_18, Day 120, rep 6
- GSM9036894 Mouse liver, Sp_573_EE_1, Day 30, rep 1
- GSM9036895 Mouse liver, Sp_573_EE_2, Day 30, rep 2
- GSM9036896 Mouse liver, Sp_573_EE_3, Day 30, rep 3
- GSM9036897 Mouse liver, Sp_573_EE_4, Day 30, rep 4
+ 26 more — browse all 66 samples with per-sample file links →
- GSE243942 Spatio-temporal X-linked gene reactivation in the mouse germline reveals site-specific retention of epigenetic silencing [RNA-seq] 125 samples shares epigenetic, silencing, rna-seq
- GSE241770 ACSS2 mediates an epigenetic pathway to regulate maternal Beta-cell adaptation and progression of gestational diabetes (scRNA-Seq) 7899 samples shares epigenetic, rna-seq
- GSE276155 RBBP5 is an epigenetic regulator of mammalian hepatic 12h oscillator [RNA-seq] 96 samples shares epigenetic, rna-seq
- GSE309564 IFNg shapes macrophage inflammatory responses by STAT1 isoform-specific epigenetic and transcriptional mechanisms [RNA-Seq] 72 samples shares epigenetic, rna-seq
- GSE289641 Noncanonical PRC2 chromatin association reveals a key role of EZHIP in intergenerational epigenetic memory transition [RNA-Seq] 68 samples shares epigenetic, rna-seq
- GSE270509 In vivo CRISPR screen reveals interplay of epigenetic regulators underlies kinetics of hepatobiliary reprogramming [RNA-Seq] 27 samples shares epigenetic, rna-seq
- GSE300014 The CARM1 Epigenetic Enzyme Inhibits Cross-presenting Dendritic Cell Function in Cancer Immunity [RNA-seq] 26 samples shares epigenetic, rna-seq
- GSE246799 Epigenetic recording of stimulation history reveals BLIMP1-BACH2 balance in determining memory B cell fate upon recall challenge (RNA-Seq) 24 samples shares epigenetic, 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.