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Regulation of CD45 isoforms during human effector and memory CD8 T cell differentiation: Implications for T cell nomenclature

GSE284430 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2026/07/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 21 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
21 samples: 7 conditions, mostly in triplicateGroups 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)
This study shows a detailed analysis of the expression of CD45 isoforms on virus specific CD8 T cells after YFV vaccination (YFV-17D) longitudinally starting at two weeks after infection going out to over 10 years. As expected, effector CD8 T cells at day 14 express CD45RO but interestingly within 4-6 weeks all of the virus specific CD8 T cells become CD45RA and then remain CD45 RA for > 10yrs.
Read the full summary ↓
The journey for these YFV specific CD8 T cells goes from naïve (CD45RA+ CCR7+) to effector/EM (CD45RO+ CCR7-) to TEMRA (CD45RA+ CCR7-) to TSCM (CD45RA+ CCR7+). These YFV specific CD8 T cells rarely acquire the canonical Tcm phenotype (CD45RO+ CCR7+). The few CM cell found in the YFV CD8 T cell response are effector cells in the first 11 days of the infection and their numbers become almost undetectable in subsequent samples. We found that CD8 T cells returned to expressing a mixture of CD45 isoforms similar but not identical to those found in naive T cells. CD45RA expression correlated closely with reduced expression of the splicing mediator hnRNP LL. This CD45RO to RA switch happens around one month post-infection and coincides with clearance of YFV, so we hypothesized that antigen may be playing a role in which CD45 isoform is expressed by the virus specific CD8 T cells. We addressed this issue by ex vivo analysis and provide evidence that this switch is indeed regulated by antigen. Sorted CD45RO positive YFV specific effector CD8 T cells re-express CD45RA when cultured ex vivo in the absence of antigen. We then show that SARS-CoV-2 spike specific CD8 T cells undergo the same CD45RA to RO to RA transition in vivo in a longitudinal analysis of a cohort of COVID-19 patients receiving the SARS-CoV-2 mRNA vaccine. These studies have important implications for T cell nomenclature and in particular for defining human memory CD8 T cell subsets. The re-expression of CD45RA in CD8 T cells likely explains the large number of TEMRA and absence of CM CD8 T cells. However, comparison to CD4 populations suggests that these findings are only applicable to CD8 T cells.
This dataset
Open GSE284430 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 GSE284430_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 PRJNA1199001 and SRA study SRP551855. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly in triplicate
naive CD4 dono ×3 CM CD4 dono ×3 EM CD4 dono ×3 naive CD8 dono ×3 EM CD8 dono ×3 EM (mid RA) CD8 dono ×3 EMRA CD8 dono ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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
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