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Development of an Optimized Epigenetic Silencer to Transcriptionally Inactivate Viral DNA in Chronic Hepatitis B [RNAseq]

GSE318225 Homo sapiens (human) RNA-seq (gene expression) 218 samples Submitted 2026/06/28 Platform GPL30173Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 218 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
218 samples: 56 conditions, mostly with about 4 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.
Summary (written by the submitters)
Approved chronic hepatitis B (CHB) therapies rarely result in functional cure, as they fail to permanently silence all transcriptionally active hepatitis B virus (HBV) DNA. CRMA-1001 employs an optimized epigenetic silencer that represses viral transcription through targeted deposition of DNA methylation on episomal and integrated HBV DNAs.
Read the full summary ↓
In HBV mouse models, a single dose of CRMA-1001 produced >3 log10 reductions in viral biomarkers, which correlated with de novo methylation of HBV DNA. Three doses resulted in up to 90% of animals with undetectable hepatitis B surface antigen (HBsAg) and HBV DNA by 6 months post-treatment. In non-human primates, CRMA-1001 induced transient liver transaminase elevations only at the highest dose tested. Expression and DNA methylation profiling revealed no detectable unintended targets in the human genome. These findings support the initiation of clinical development of CRMA-1001 as a finite treatment course with the potential for functional cure in individuals living with CHB.
This dataset
Open GSE318225 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE318225_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1416938 and SRA study SRP672283. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
56 conditions, mostly with about 4 replicates each
RNAseq, PHH Donor1, Untreated, ×4 RNAseq, PHH Donor1, CRMA-1001 1.0 µg/mL, ×4 RNAseq, PHH Donor1, CRMA-1001 0.5 µg/mL, ×4 RNAseq, PHH Donor1, EE7000 mRNAOnly, ×4 RNAseq, PHH Donor1, HBV-CRISPRi, ×4 RNAseq, PHH Donor1, Mock-treatment, ×4 RNAseq, PHH Donor1, PCSK9-EE7000, ×4 RNAseq, PHH Donor2, CRMA-1001 0.5 µg/mL, ×4 +48 more

Supports a between-group comparison across 218 samples.

How we read this: 56 replicated groups read from 218 sample titles; they account for 218 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.

Samples in this study

+ 178 more — browse all 218 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.