← BioTransfer GEO Dataset Finder
GEO series

Modified loop2 epegRNA improve prime editing efficiency.

GSE274737 Homo sapiens (human) RNA-seq (gene expression) 1159 samples Submitted 2025/11/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 1159 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
1159 samples: 142 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
Loop engineering improves prime editing efficiencyMolecular therapy. Nucleic acids · 2025
Summary (written by the submitters)
Prime editor (PE) has wide application prospects in disease treatment due to its diversity of editing outcomes. However, the editing efficiency of PE still needs to be further improved for therapeutic applications. Here, we increase the probability of hybridization of the pegRNA primer binding site (PBS) to single-stranded DNA flap by adding additional PBS sequence and reverse transcription template (RTT) to the loop region of pegRNA.
Read the full summary ↓
The selection of loop and the design of loop length are optimized. The resulting modified loop2 epegRNA (ML-epegRNA) showed higher prime editing efficiency than that of the epegRNA in HEK293T cells. In addition, we used ML-epegRNA for PE editing of multiple editing types in multiple cell lines, and the results showed a general improvement in editing efficiency. Overall, the ML-epegRNA expands the capabilities of genome editing tools.
Published in
Loop engineering improves prime editing efficiency
Li B, Lu Z, Zhou T et al. · Molecular therapy. Nucleic acids 2025 · PMID 41341749 · doi:10.1016/j.omtn.2025.102764
This dataset
Open GSE274737 in finder → Find more human 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 GSE274737_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 PRJNA1143215. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41341749) ↗
Study design
142 conditions, mostly in duplicate
HEK293T cell, EMX1, G5T, loop2-25-22-7-M, PE2, ×5 HEK293T cell, EMX1, G5T, loop2-13-18-5-M, PE2, ×4 HEK293T cell, EMX1, G5T, loop2-25-22-7, PE2, ×3 HEK293T cell, VEGFA, A3C, tetraloop-34-20-7, … ×3 HEK293T cell, VEGFA, A3C, tetraloop-34-20-7-M… ×3 HEK293T cell, VEGFA, A3C, tetraloop-34-22-7, … ×3 HEK293T cell, VEGFA, A3C, tetraloop-34-31-7, … ×3 HEK293T cell, VEGFA, A3C, loop2-34-20-7, PE2, ×3 +192 more

Supports a between-group comparison across 342 samples.

How we read this: 142 replicated groups read from the first 400 of 1159 sample titles; they account for 342 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

+ 1119 more — browse all 1159 samples with per-sample file links →

Datasets on a similar topic

Search all human datasets in GEO →

Share this dataset

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.