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Adverse outcome pathways of ionizing radiation investigated with multi-omics and benchmark dose modeling

GSE260589 Homo sapiens (human) RNA-seq (gene expression) 278 samples Submitted 2025/02/28 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 278 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
278 samples: 56 conditions, mostly with about 5 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)
Background/Issue and Objectives: Health risks from chronic low dose radiation exposures encountered in environmental and occupational settings are uncertain. A key aspect to understanding health risks is precise and accurate modelling of the dose-response relationship. Benchmark dose (BMD) modeling is an approach used in chemical hazard assessments to identify the dose at which a pre-defined (e.g., 10%) change relative to background occurs.
Read the full summary ↓
Herein, this method is being explored for radiation hazard assessments along with Adverse Outcome Pathways (AOPs), a knowledge framework of causally linked chains of key events (KEs) from a molecular initiating event to an adverse outcome (AO). Design/Method/Description: Blood was drawn from human participants (6 females and 8 males), and lymphocytes were isolated, cultured and X-irradiated at a lower dose-rate (LDR: 0.05 Gy/minute) and higher dose-rate (HDR: 1 Gy/minute) across nine different doses (0, 0.05, 0.10 0.25, 0.5, 1, 2, 4 and 6 Gy). Transcriptomic and proteomic changes were then assessed 24 hours post-exposure. Concurrently, cell membrane integrity and cellular ATP level were also measured, which are markers of radiation injuries. BMD values were then derived for each endpoint and pathways enriched in omics data were compared with Kes in an existing AOP to leukemia (www.aopwiki.org/aop/432). Conclusions/Impacts/Outcomes/Implications/Next Steps: By using AOPs as an organizational framework and BMD modeling for dose-response analysis, it provides a pragmatic platform to analyse complex data for radiation hazard assessment. Future work will entail in-depth analysis of the responses specific to LDR and HDR and effects of confounding factors on BMD values.
This dataset
Open GSE260589 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 GSE260589_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 PRJNA1082296 and SRA study SRP492610. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
56 conditions, mostly with about 5 replicates each
Donor B-HD ×5 Donor B-LD ×5 Donor C-HD ×5 Donor C-LD ×5 Donor D-HD ×5 Donor D-LD ×5 Donor E-HD ×5 Donor E-LD ×5 +75 more

Supports a between-group comparison across 251 samples.

How we read this: 56 replicated groups read from 278 sample titles; they account for 251 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

+ 238 more — browse all 278 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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