GEO series

Multi-omics analysis in primary T cells elucidates mechanisms behind disease associated genetic loci [RNA-seq]

GSE282511 Homo sapiens (human) RNA-seq (gene expression) 128 samples Submitted 2024/12/18 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 128 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: 128 samples: 79 × Primary T-cell, Patient vs 38 × Primary T-cell, HealthyGroups 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: Multi-omics analysis in primary T cells elucidates mechanisms behind disease-associated genetic lociGenome biology · 2025

Summary (written by the submitters)

Background: Genome wide association studies (GWAS) have uncovered the genetic basis behind many diseases and conditions. However, most of these genetic loci affect regulatory regions, making the interpretation challenging. Chromatin conformation has a fundamental role in gene regulation and is frequently used to associate potential target genes to regulatory regions.

Read the full summary ↓

However, previous studies mostly used small sample sizes and immortalized cell lines instead of primary cells. Results: Here we present the most extensive dataset of chromatin conformation with matching gene expression and chromatin accessibility from primary CD4+ and CD8+ T cells to date, isolated from psoriatic arthritis patients and healthy controls. We generated 108 Hi-C libraries (49 billion reads), 128 RNA-seq libraries and 126 ATAC-seq libraries. These data enhance our understanding of the mechanisms by which GWAS variants impact gene regulation, revealing how genetic variation alters chromatin accessibility and structure in primary cells at an unprecedented scale. We refine the mapping of GWAS loci to implicated regulatory elements, such as CTCF binding sites and other enhancer elements, aiding gene assignment. We uncover BCL2L11 as the probable causal gene within the rheumatoid arthritis (RA) locus rs13396472, despite the GWAS variants’ intronic positioning relative to ACOXL, and we identify mechanisms involving SESN3 dysregulation in the RA locus rs4409785. Conclusions: Given these genes’ significant role in T cell development and maturation, our work deepens our comprehension of autoimmune disease pathogenesis, suggesting potential treatment targets. In addition, our dataset provides a valuable resource for the investigation of immune mediated diseases and gene regulatory mechanisms.

Published in

Multi-omics analysis in primary T cells elucidates mechanisms behind disease-associated genetic loci

Shi C, Zhao D, Butler J et al. · Genome biology 2025 · PMID 39930543 · doi:10.1186/s13059-025-03492-y

This dataset

Open GSE282511 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 GSE282511_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 PRJNA1185164 and SRA study SRP544674. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39930543) ↗

Study design

79 × Primary T-cell, Patient vs 38 × Primary T-cell, Healthy

Supports a case/control comparison: 90 samples read as cases, 38 as controls.

How we read this: 2 replicated groups read from 128 sample titles; they account for 117 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

GSM8644845 Primary T-cell, Healthy 1 Primary T-cell, Healthy
GSM8644846 Primary T-cell, Healthy 2 Primary T-cell, Healthy
GSM8644847 Primary T-cell, Healthy 3 Primary T-cell, Healthy
GSM8644848 Primary T-cell, Healthy 4 Primary T-cell, Healthy
GSM8644849 Primary T-cell, Healthy 5 Primary T-cell, Healthy
GSM8644850 Primary T-cell, Healthy 6 Primary T-cell, Healthy
GSM8644851 Primary T-cell, Healthy 7 Primary T-cell, Healthy
GSM8644852 Primary T-cell, Healthy 8 Primary T-cell, Healthy
GSM8644853 Primary T-cell, Healthy 9 Primary T-cell, Healthy
GSM8644854 Primary T-cell, Healthy 10 Primary T-cell, Healthy
GSM8644855 Primary T-cell, Healthy 11 Primary T-cell, Healthy
GSM8644856 Primary T-cell, Healthy 12 Primary T-cell, Healthy
GSM8644857 Primary T-cell, Healthy 13 Primary T-cell, Healthy
GSM8644858 Primary T-cell, Healthy 14 Primary T-cell, Healthy
GSM8644859 Primary T-cell, Healthy 15 Primary T-cell, Healthy
GSM8644860 Primary T-cell, Healthy 16 Primary T-cell, Healthy
GSM8644861 Primary T-cell, Healthy 17 Primary T-cell, Healthy
GSM8644862 Primary T-cell, Healthy 18 Primary T-cell, Healthy
GSM8644863 Primary T-cell, Healthy 19 Primary T-cell, Healthy
GSM8644864 Primary T-cell, Healthy 20 Primary T-cell, Healthy
GSM8644865 Primary T-cell, Healthy 21 Primary T-cell, Healthy
GSM8644866 Primary T-cell, Healthy 22 Primary T-cell, Healthy
GSM8644867 Primary T-cell, Healthy 23 Primary T-cell, Healthy
GSM8644868 Primary T-cell, Healthy 24 Primary T-cell, Healthy
GSM8644869 Primary T-cell, Healthy 25 Primary T-cell, Healthy
GSM8644870 Primary T-cell, Healthy 26 Primary T-cell, Healthy
GSM8644871 Primary T-cell, Healthy 27 Primary T-cell, Healthy
GSM8644872 Primary T-cell, Healthy 28 Primary T-cell, Healthy
GSM8644873 Primary T-cell, Healthy 29 Primary T-cell, Healthy
GSM8644874 Primary T-cell, Healthy 30 Primary T-cell, Healthy
GSM8644875 Primary T-cell, Healthy 31 Primary T-cell, Healthy
GSM8644876 Primary T-cell, Healthy 32 Primary T-cell, Healthy
GSM8644877 Primary T-cell, Healthy 33 Primary T-cell, Healthy
GSM8644878 Primary T-cell, Healthy 34 Primary T-cell, Healthy
GSM8644879 Primary T-cell, Healthy 35 Primary T-cell, Healthy
GSM8644880 Primary T-cell, Healthy 36 Primary T-cell, Healthy
GSM8644881 Primary T-cell, Healthy 37 Primary T-cell, Healthy
GSM8644882 Primary T-cell, Healthy 38 Primary T-cell, Healthy
GSM8644883 Primary T-cell, Patient 1 Primary T-cell, Patient
GSM8644884 Primary T-cell, Patient 2 Primary T-cell, Patient

+ 88 more — browse all 128 samples with per-sample file links →

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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.