GEO series

Killer cell immunoglobulin-like receptors delineate distinct phenotypes and functions in human γδ T cells [ATAC]

GSE301798 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 14 samples Submitted 2026/03/24 Platform GPL34281

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 14 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Homo sapiens (human)
Samples: 14 samples
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: Killer-cell immunoglobulin-like receptors define a potent effector program in human γδ T cellsJCI insight · 2026

Summary (written by the submitters)

Killer cell immunoglobulin-like receptors (KIRs) are a diverse family of HLA class I-specific receptors that shape immune responses, primarily through NK cells. Beyond NK cells, subsets of T cells, notably γδ T cells, express KIRs, but their roles remain unclear. Here, we demonstrate that KIR⁺γδ T cells are significantly more abundant in CMV-seropositive healthy adults, particularly within the Vδ2⁻ subset.

Read the full summary ↓

These cells exhibit a TEMRA phenotype, are predominantly CD16⁺CD57⁺, hallmarks of a highly differentiated state, and express multiple NK cell-associated receptors. KIR+γδ T cells display enhanced cytotoxic potential, with higher levels of granzyme B and perforin than their KIR- counterparts. Using Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and transcriptional analyses, we show that KIR- and KIR+ γδ T cells reveal distinct molecular signatures, with KIR+γδ T cells transcriptionally and epigenetically aligning with terminally differentiated effector memory T cells, while KIR- cells retain a naïve-like phenotype. These findings suggest that CMV infection drives the differentiation of γδ T cells into potent, KIR-expressing cytotoxic effectors. This adaptive mechanism may bolster immune defense while maintaining self-tolerance, highlighting a previously unappreciated role for KIRs in shaping γδ T cell immunity.

Published in

Killer-cell immunoglobulin-like receptors define a potent effector program in human γδ T cells

Razmi M, Almasi Y, Larrivée M et al. · JCI insight 2026 · PMID 42044172 · doi:10.1172/jci.insight.201160

This dataset

Open GSE301798 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE301798_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1287582 and SRA study SRP599125. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42044172) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 14 more — browse all 14 samples with per-sample file links →

Datasets on a similar topic

GSE237807 Multi-omics analysis of FOXO3 pioneer factor activity reveals distinct networks in proliferating and DNA damage induced senescent cells [ATAC-Seq] 42 samples shares atac, distinct
GSE274113 Transcription factor networks disproportionately enrich for heritability of blood cell phenotypes [10x ATAC + GEX Multiome] 42 samples shares atac, phenotypes
GSE319130 Multi-omic analysis reveals molecular subtypes with distinct immunological phenotypes in SLE [RNA-Seq] 804 samples shares phenotypes, distinct
GSE310672 Progesterone receptors drive advanced breast cancer phenotypes including circulating tumor- and stem-like cell expansion in the context of ESR1 mutation [RNA-seq] 48 samples shares phenotypes, receptors
GSE291386 Chromatin accessibility profiling of HSPC-derived erythroblast differentiation [ATAC-seq] 165 samples shares atac
GSE289805 Histone H4 lysine 20 tri-methylation safeguards breast cancer lineage fidelity and unfolded protein response [ChIP-seq/ATAC-seq] 126 samples shares atac
GSE252382 ATACseq of TNBC cell lines treated with EZH2i (tazemetostat) and/or AKTi (ipatasertib) 84 samples shares atac
GSE270684 The EZH2 and EZH1 inhibitor valemetostat derepresses p16INK4a to induce early endomitotic exit in megakaryocytes [scATAC-Seq] 66 samples shares atac

Search all human ChIP / ATAC / CUT&Tag 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.