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Molecular signatures underlying heterogeneous hypertrophy responsiveness to resistance training in older men and women: a within-subject design

GSE277819 Homo sapiens (human) RNA-seq (gene expression) 81 samples Submitted 2025/08/27 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 81 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
81 samples: 27 × A vs 27 × BD vs 27 × BEGroups 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
Molecular signatures underlying heterogenous hypertrophy responsiveness to resistance training in older men and women: a within-subject designJournal of applied physiology (Bethesda, Md. : 1985) · 2025
Summary (written by the submitters)
We showed higher resistance training (RT) volume (4-sets) offsets muscle hypertrophy non-responsiveness to single-set RT (1-set), while enhancing hypertrophic response among responders. Here, we investigated molecular traits underpinning RT-related hypertrophic variability via targeted (ribosome density and biogenesis) and untargeted approaches (RNAseq gene-ontology (GO) and Pathway-Level Information ExtractoR [PLIER]).
Read the full summary ↓
Twenty-seven older (693 years) participants in the parental trial had one leg randomly allocated to 1-set and the contralateral leg allocated to 4-sets of RT for 10-wk, 2x/week. Pre- and postintervention, participants underwent magnetic resonance imaging (MRI) and muscle biopsies. We selected participants based on quadriceps muscle cross-sectional area (qCSA) changes and used the MRI typical error (2xTE=3.27%) to allocate those in distinct hypertrophy phenotype: low-responders: blunted hypertrophy, regardless of RT-volume; medium-responders: hypertrophy only following the higher RT-volume; and high-responders: hypertrophy following both RT-volume. The qCSA was higher for 4-sets compared with 1-set for medium- and high-responders only. Higher RT-volume, regardless of responsiveness groups, was followed by increased Frizzled-1 protein expression. RNAseq showed that high-responder’s robust hypertrophy was followed by up-regulation of pathways linked with protein turnover metabolism, RT-related metabolic response, and with protein-folding biological processes. Hypertrophy in medium-responders was marked by down-regulation of pathways linked with muscle catabolism (Proteasome and Spliceosome), modulations on distinct RT-related metabolic response, and biological processes associated with hormone- and steroid-related pathways. Low-responders, on the other hand, did not show measurable changes in any molecular pathways, regardless of RT volume manipulation. Overall, these finding reveal differential molecular signatures across the spectrum of RT responsiveness among older individuals.
Published in
Molecular signatures underlying heterogenous hypertrophy responsiveness to resistance training in older men and women: a within-subject design
Lixandrao ME, Bamman M, Lavin KM et al. · Journal of applied physiology (Bethesda, Md. : 1985) 2025 · PMID 40839394 · doi:10.1152/japplphysiol.00052.2025
This dataset
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.

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 GSE277819_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1164267 and SRA study SRP534285. Searching any of these in the dataset finder brings you back here.

Study design
27 × A vs 27 × BD vs 27 × BE

Supports a between-group comparison across 81 samples.

How we read this: 3 replicated groups read from 81 sample titles; they account for 81 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

+ 41 more — browse all 81 samples with per-sample file links →

Datasets on a similar topic

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