GEO series

Selective infection and loss of PRDM1+ LN Tfh cells in uncontrolled HIV infection precludes formation of Tfh reservoirs under ART

GSE313072 Homo sapiens (human) Single-cell RNA-seq 420 samples Submitted 2025/12/16 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 420 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 420 samples: 105 × DOGMAseq, ATAC, Sample vs 105 × DOGMAseq, GEX, Sample vs 105 × DOGMAseq, ADT, Sample vs 85 × DOGMAseq, HTO, SampleGroups 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)

The multifaceted and long-lived nature of HIV-1 reservoirs has proven to be a formidable obstacle in the development of a therapeutic cure of HIV-1. One of the major dimensions of the HIV-1 reservoir is its prevalence and persistence in tissue environments, including in lymph nodes (LN). Within LN, T follicular helper (Tfh) cells are widely considered as the dominant sub-reservoir in viremic people with HIV (PWH).

Read the full summary ↓

However, whether Tfh cells survive to establish a reservoir in PWH undergoing suppressive antiretroviral therapy (ART) has remained controversial. To address these issues, we deeply phenotyped over 500,000 cells and identified over 2,000 HIV-1 infected cells by employing single-cell multiomics on LN from PWH during viremia and suppressed on ART. While we detected HIV-1 infected Tfh cells, the majority of infected cells during viremia and ART had non-follicular phenotypes and were instead heterogeneously distributed between various CD4+ T-cell subsets. Within-subset comparisons of HIV+ and HIV- cells revealed heightened activation signatures and altered cell cycle states during viremia, but largely similar features during ART. Furthermore, the comparison between viremia and ART in PWH highlighted a noncanonical Tfh subset - defined by high locus accessibility and transcription of PRDM1 - that is selectively depleted during viremia, recovers after ART, and is highly susceptible to infection in vitro. Our work suggests a revised direction for the HIV-1 cure field where a mandate of any comprehensive strategy will be to address the high proportional burden of non-follicular cells towards the HIV reservoir.

This dataset

Open GSE313072 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 GSE313072_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1374234. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

105 × DOGMAseq, ATAC, Sample vs 105 × DOGMAseq, GEX, Sample vs 105 × DOGMAseq, ADT, Sample vs 85 × DOGMAseq, HTO, Sample

Supports a between-group comparison across 400 samples.

How we read this: 4 replicated groups read from the first 400 of 420 sample titles; they account for 400 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

GSM9360078 DOGMAseq, ATAC, Sample 1 DOGMAseq, ATAC, Sample
GSM9360079 DOGMAseq, ATAC, Sample 2 DOGMAseq, ATAC, Sample
GSM9360080 DOGMAseq, ATAC, Sample 3 DOGMAseq, ATAC, Sample
GSM9360081 DOGMAseq, ATAC, Sample 4 DOGMAseq, ATAC, Sample
GSM9360082 DOGMAseq, ATAC, Sample 5 DOGMAseq, ATAC, Sample
GSM9360083 DOGMAseq, ATAC, Sample 6 DOGMAseq, ATAC, Sample
GSM9360084 DOGMAseq, ATAC, Sample 7 DOGMAseq, ATAC, Sample
GSM9360085 DOGMAseq, ATAC, Sample 8 DOGMAseq, ATAC, Sample
GSM9360086 DOGMAseq, ATAC, Sample 9 DOGMAseq, ATAC, Sample
GSM9360087 DOGMAseq, ATAC, Sample 10 DOGMAseq, ATAC, Sample
GSM9360088 DOGMAseq, ATAC, Sample 11 DOGMAseq, ATAC, Sample
GSM9360089 DOGMAseq, ATAC, Sample 12 DOGMAseq, ATAC, Sample
GSM9360090 DOGMAseq, ATAC, Sample 13 DOGMAseq, ATAC, Sample
GSM9360091 DOGMAseq, ATAC, Sample 14 DOGMAseq, ATAC, Sample
GSM9360092 DOGMAseq, ATAC, Sample 15 DOGMAseq, ATAC, Sample
GSM9360093 DOGMAseq, ATAC, Sample 16 DOGMAseq, ATAC, Sample
GSM9360094 DOGMAseq, ATAC, Sample 17 DOGMAseq, ATAC, Sample
GSM9360095 DOGMAseq, ATAC, Sample 18 DOGMAseq, ATAC, Sample
GSM9360096 DOGMAseq, ATAC, Sample 19 DOGMAseq, ATAC, Sample
GSM9360097 DOGMAseq, ATAC, Sample 20 DOGMAseq, ATAC, Sample
GSM9360098 DOGMAseq, ATAC, Sample 21 DOGMAseq, ATAC, Sample
GSM9360099 DOGMAseq, ATAC, Sample 22 DOGMAseq, ATAC, Sample
GSM9360100 DOGMAseq, ATAC, Sample 23 DOGMAseq, ATAC, Sample
GSM9360101 DOGMAseq, ATAC, Sample 24 DOGMAseq, ATAC, Sample
GSM9360102 DOGMAseq, ATAC, Sample 25 DOGMAseq, ATAC, Sample
GSM9360103 DOGMAseq, ATAC, Sample 26 DOGMAseq, ATAC, Sample
GSM9360104 DOGMAseq, ATAC, Sample 27 DOGMAseq, ATAC, Sample
GSM9360105 DOGMAseq, ATAC, Sample 28 DOGMAseq, ATAC, Sample
GSM9360106 DOGMAseq, ATAC, Sample 29 DOGMAseq, ATAC, Sample
GSM9360107 DOGMAseq, ATAC, Sample 30 DOGMAseq, ATAC, Sample
GSM9360108 DOGMAseq, ATAC, Sample 31 DOGMAseq, ATAC, Sample
GSM9360109 DOGMAseq, ATAC, Sample 32 DOGMAseq, ATAC, Sample
GSM9360110 DOGMAseq, ATAC, Sample 33 DOGMAseq, ATAC, Sample
GSM9360111 DOGMAseq, ATAC, Sample 34 DOGMAseq, ATAC, Sample
GSM9360112 DOGMAseq, ATAC, Sample 35 DOGMAseq, ATAC, Sample
GSM9360113 DOGMAseq, ATAC, Sample 36 DOGMAseq, ATAC, Sample
GSM9360114 DOGMAseq, ATAC, Sample 37 DOGMAseq, ATAC, Sample
GSM9360115 DOGMAseq, ATAC, Sample 38 DOGMAseq, ATAC, Sample
GSM9360116 DOGMAseq, ATAC, Sample 39 DOGMAseq, ATAC, Sample
GSM9360117 DOGMAseq, ATAC, Sample 40 DOGMAseq, ATAC, Sample

+ 380 more — browse all 420 samples with per-sample file links →

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