GEO series

Next Generation Sequencing Facilitates Quantitative Analysis of wild typeHDAC1 and HDAC1_S434A Transcriptomes with or without PKA inhibitor H89 treatment

GSE284216 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/03/12 Platform GPL20301

At a glance

RNA-seq (gene expression) · human · 12 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: 12 samples: 3 × Mut_control vs 3 × Mut_treat vs 3 × WT_control vs 3 × WT_treatGroups 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: PKA plays a conserved role in regulating gene expression and metabolic adaptation by phosphorylating Rpd3/HDAC1Nature communications · 2025

Summary (written by the submitters)

Cells need to reprogram their metabolism to adapt to extracellular nutrient changes. The histone acetyltransferase SAGA (Spt-Ada-Gcn5-acetyltransferase) complex has been reported to acetylate its subunit Ada3 and form homo-dimers to enhance its ability to acetylate nucleosomes and facilitate metabolic gene transcription. How cells transduce extracellular nutrient changes to SAGA structure and function changes remains unclear.

Read the full summary ↓

Here, we found that SAGA is deacetylated by Rpd3L complex and uncovered how its deacetylase activity is repressed by nutrient sensor protein kinase A (PKA). When sucrose is used as the sole carbon source, PKA catalytic subunit Tpk2 is activated, which phosphorylates Rpd3L catalytic subunit Rpd3 at serine 50 and serine 354 to inhibit its ability to deacetylate Ada3. Moreover, Tpk2 phosphorylates Rpd3L subunit Ash1 at serine 149 and serine 388, which specifically reduces the interaction between Rpd3L and SAGA. By phosphorylating both Rpd3 and Ash1, Tpk2 inhibits Rpd3L-mediated Ada3 deacetylation, which promotes SAGA dimerization, nucleosome acetylation and transcription of genes involved in sucrose utilization and tricarboxylate (TCA) cycle, resulting in metabolic shift from glycolysis to TCA cycle. Most importantly, PKA phosphorylates HDAC1, the Rpd3 homolog in mammals to repress its deacetylase activity and promote TCA cycle gene transcription. Blocking PKA-catalyzed HDAC1 phosphorylation reduced TCA cycle and impaired cell growth. Our work hence reveals a conserved role of PKA in regulating Rpd3/HDAC1 and metabolism adaptation and provides a potential target for future cancer treatment.

Published in

PKA plays a conserved role in regulating gene expression and metabolic adaptation by phosphorylating Rpd3/HDAC1

Dai W, Yu Q, Ma R et al. · Nature communications 2025 · PMID 40301306 · doi:10.1038/s41467-025-59064-y

This dataset

Open GSE284216 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 GSE284216_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 PRJNA1198008 and SRA study SRP551305. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40301306) ↗

Study design

3 × Mut_control vs 3 × Mut_treat vs 3 × WT_control vs 3 × WT_treat

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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

GSM8679828 Mut_control_rep1 Mut_control
GSM8679829 Mut_control_rep2 Mut_control
GSM8679830 Mut_control_rep3 Mut_control
GSM8679831 Mut_treat_rep1 Mut_treat
GSM8679832 Mut_treat_rep2 Mut_treat
GSM8679833 Mut_treat_rep3 Mut_treat
GSM8679834 WT_control_rep1 WT_control
GSM8679835 WT_control_rep2 WT_control
GSM8679836 WT_control_rep3 WT_control
GSM8679837 WT_treat_rep1 WT_treat
GSM8679838 WT_treat_rep2 WT_treat
GSM8679839 WT_treat_rep3 WT_treat

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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.