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Single Alkyl Phosphonate Modification of the siRNA Backbone in the Seed Region Enhances Specificity and Therapeutic Profile

GSE285764 Homo sapiens (human) RNA-seq (gene expression) 110 samples Submitted 2025/01/15 Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 110 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
110 samples: 101 distinct titles, 9 of them repeatedGroups 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
Single alkyl phosphonate modification of the siRNA backbone in the seed region enhances specificity and therapeutic profileNucleic acids research · 2025
Summary (written by the submitters)
We evaluated the effect of alkyl phosphonate linkages in enhancing the specificity and therapeutic profile of siRNA when incorporated into the seed region. Modified siRNAs with a single alkyl phosphonate linkage demonstrated improved specificity, particularly when positioned at the internucleotide linkage between positions 6 and 7 from the 5'-end of the guide strand.
Read the full summary ↓
These modifications maintained robust on-target activity both in vitro and in vivo while significantly reducing off-target effects, as shown by differential gene expression analysis. Additionally, we observed enhanced safety in mice, as evidenced by reduced ALT/AST elevation and the absence of histopathological changes.
Published in
Single alkyl phosphonate modification of the siRNA backbone in the seed region enhances specificity and therapeutic profile
Nikan M, Li Q, Tanowitz M et al. · Nucleic acids research 2025 · PMID 40737088 · doi:10.1093/nar/gkaf692
This dataset
Open GSE285764 in finder → Find more 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 GSE285764_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 PRJNA1205781 and SRA study SRP555014. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40737088) ↗
Study design
101 distinct titles, 9 of them repeated
ACTN1_1744547_repAtx1_0.200000uM_A5_tech ×2 ACTN1_1788297_repAtx1_0.200000uM_C5_tech ×2 ACTN1_1788300_repAtx1_0.200000uM_E5_tech ×2 ACTN1_1744547_repAtx1_1.000000uM_A3_tech ×2 ACTN1_1788297_repAtx1_1.000000uM_C3_tech ×2 ACTN1_1788300_repAtx1_1.000000uM_E3_tech ×2 ACTN1_1744547_repAtx1_5.000000uM_A1_tech ×2 ACTN1_1788297_repAtx1_5.000000uM_C1_tech ×2 +1 more

How we read this: Read from 110 sample titles: 101 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.

Samples in this study

+ 70 more — browse all 110 samples with per-sample file links →

Datasets on a similar topic

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