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The 24-Hour Time Course of Integrated Molecular Responses to Resistance Exercise in Human Skeletal Muscle Implicates MYC as a Hypertrophic Regulator

GSE252357 Homo sapiens (human) RNA-seq (gene expression) 61 samples Submitted 2024/04/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 61 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
61 samples: 61 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.
Paper
The 24-Hour Time Course of Integrated Molecular Responses to Resistance Exercise in Human Skeletal Muscle Implicates MYC as a Hypertrophic Regulator That is Sufficient for GrowthbioRxiv : the preprint server for biology · 2024
Summary (written by the submitters)
Molecular control of recovery after exercise in muscle is temporally dynamic. A time course of biopsies around resistance exercise (RE) combined with -omics is necessary to better comprehend the molecular choreography of skeletal muscle adaptation in humans. We collected vastus lateralis biopsies before and 30 minutes, 3-, 8-, and 24 hours after acute RE.
Read the full summary ↓
RNA-sequencing defined the transcriptome and a time-point matched biopsy only group were controls. DNA methylomics and computational approaches complimented the transcriptome data. Moreover, we tested whether cyclic transient overexpression of transcription factor MYC for 4 weeks were sufficient to induce skeletal muscle hypertrophy in female mice.
Published in
The 24-Hour Time Course of Integrated Molecular Responses to Resistance Exercise in Human Skeletal Muscle Implicates MYC as a Hypertrophic Regulator That is Sufficient for Growth
Edman S, Jones RG 3rd, Jannig PR et al. · bioRxiv : the preprint server for biology 2024 · PMID 38586026 · doi:10.1101/2024.03.26.586857
This dataset
Open GSE252357 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 GSE252357_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 PRJNA1060283 and SRA study SRP480933. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38586026) ↗
Study design
61 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 61 sample titles: 61 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

+ 21 more — browse all 61 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq 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.