GEO series

RNA sequencing of naïve, activated and HIV-1 infected CD4+ T cells

GSE328010 Homo sapiens (human) RNA-seq (gene expression) 9 samples Submitted 2026/04/14 Platform GPL16791

At a glance

RNA-seq (gene expression) · human · 9 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: 9 samples: 9 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)

CD4+ T cells play a major role in immune function regulation. Naive CD4+ T cells undergo major transcriptional changes upon activation through simultaneous engagement of the T-cell receptor and co-stimulatory molecules (anti-CD3/anti-CD28). Activated CD4+ T cells are the preferential target of HIV-1. Both T cell activation and HIV-1 infection modulate the expression and splicing of multiple genes.

Read the full summary ↓

This study characterizes the transcriptome of naive, activated, and activated-HIV-1 infected CD4+ T cells from 3 healthy donors using bulk RNA-Seq, with validation of gene expression and alternative splicing by RT-qPCR and RT-PCR respectively.

This dataset

Open GSE328010 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 GSE328010_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 PRJNA1453501 and SRA study SRP691796. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

9 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 3 samples read as cases, 3 as controls.

How we read this: Read from 9 sample titles: 9 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

GSM9670305 Naive CD4+ T cells, donor D, biological replicate 1
GSM9670306 Naive CD4+ T cells, donor E, biological replicate 2
GSM9670307 Naive CD4+ T cells, donor F, biological replicate 3
GSM9670308 Activated CD4+ T cells, donor D, biological replicate 1
GSM9670309 Activated CD4+ T cells, donor E, biological replicate 2
GSM9670310 Activated CD4+ T cells, donor F, biological replicate 3
GSM9670311 Activated HIV-1 infected CD4+ T cells, donor D, biological replicate 1
GSM9670312 Activated HIV-1 infected CD4+ T cells, donor E, biological replicate 2
GSM9670313 Activated HIV-1 infected CD4+ T cells, donor F, biological replicate 3

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GSE342431 Transcriptomic effects of combined AZD4573 and SMAP-2 treatment in resting and anti-CD3/CD28-activated primary human CD4+ T cells 12 samples shares cd4, activated
GSE299348 Single-cell epigenetic, transcriptional, protein, and TCR states of HIV-1-infected cells in gut 117 samples shares hiv-1, infected
GSE313059 Single cell multiomic analysis of the impact of Delta-9-tetrahydrocannabinol on HIV infected CD4 T cells 16 samples shares cd4, infected

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.