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Quantum Molecular Resonance attenuates an oxidative stress-induced chimeric transcriptome program in human retinal pigment epithelial cells, preserving RNA structural fidelity

GSE328981 Homo sapiens (human) RNA-seq (gene expression) 108 samples Submitted 2026/06/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 108 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
108 samples: 108 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.
Summary (written by the submitters)
Chimeric and fusion-like transcripts are increasingly recognized as dynamic, non-genomic responses to acute environmental stress. Elevated reactive oxygen species (ROS) compromise RNA Polymerase II (RNAPII) termination and splicing fidelity, generating a potentially proteotoxic burden of structurally aberrant RNAs. However, robust quantification of these stress-induced chimeras in non-tumor perturbation models remains technically challenging.
Read the full summary ↓
We profiled the structural fidelity of the transcriptome across a large-scale RNA-seq cohort (n=72 samples) centered on Quantum Molecular Resonance (QMR) therapy and oxidative stress (H2O2 400 µM) in ARPE-19 human retinal pigment epithelial cells, across four treatment groups (Control, QMR Rescue, Secretome, QMR+Secretome Rescue) at 8h, 24h, and 72h post-challenge. Using a stringently uniform bioinformatic pipeline (CLC Genomics Workbench v25.0.3, Detect and Refine Fusion Genes v1.6; hg38/Ensembl v113), chimeric events were stratified into three escalating confidence tiers: Tier 1 (PASS), Tier 2 (PASS + in-frame CDS), and Tier 3 (high-confidence: PASS + in-frame + spanning reads > 0). Ubiquitous background chimeras constitutively expressed across all conditions (e.g., NBPF14--NOTCH2, FBXL5--ENSG00000305512, RAB27A--PIGBOS1) were explicitly identified and partitioned from the dynamic, treatment-responsive fraction. Oxidative stress significantly exacerbated the global Chimeric Burden at 72 hours, with mean aggregate read support surging to 575.5 (SD 55.1) in the Control-OX group. QMR Rescue and QMR+Secretome treatment profoundly attenuated this structural derailment (525.5 ± 139.3 and 449.0 ± 33.9, respectively). A robust 25-event QMR-Rescued Signature was derived, mapping OX-induced chimeras to four discrete biological modules: (I) Lipid/Steroidogenic pathway integrity (CTDNEP1--ENSG00000262526, HSD17B7P2--HSD17B7); (II) Extracellular matrix structural integrity (COL7A1--UCN2, COP1-DT--PAPPA2); (III) Nuclear architecture and mitochondrial coupling (COX17--POPDC2); and (IV) Zinc-finger transcriptional networks (ZNF721--ABCA11P, ZNF782--ZNF510). Top events were orthogonally validated by Arriba and STAR-Fusion (93.3% concordance, 14/15 events), and physically confirmed by junction-spanning RT-qPCR and Sanger sequencing. These findings unveil structural transcriptomic fidelity as a third, unprecedented hierarchical layer of QMR-mediated cellular protection—complementing previously described lncRNA-mediated abundance regulation and miRNA-mediated stability control—and establish a rigorous analytical framework for non-oncological chimeric RNA profiling.
This dataset
Open GSE328981 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 GSE328981_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 PRJNA1457319 and SRA study SRP694492. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
108 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 108 sample titles: 108 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

+ 68 more — browse all 108 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.