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Skeletal muscle reprogramming of metabolic, ribosomal and developmental pathways contributes to Roux-en-Y gastric bypass-induced adaptation in women

GSE341455 Homo sapiens (human) RNA-seq (gene expression) 70 samples Submitted 2026/07/31 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 70 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
70 samples: 70 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)
Background: Understanding how skeletal muscle responds to weight loss is crucial for developing targeted strategies to manage obesity and promote sustained improvement in metabolic health. Here, we investigated the molecular mechanisms underlying skeletal muscle reprogramming of gene expression and metabolic activity following Roux-en-Y gastric bypass (RYGB).
Read the full summary ↓
Methods: Forty-one women were studied before and one year after RYGB surgery. We leveraged multi-omics (DNA methylomics and transcriptomics) and machine learning approaches to complement muscle metabolic analyses and clinical data to identify mechanisms underlying RYGB-induced muscle metabolic reprogramming. Findings: RYGB markedly decreased body weight and fat mass and improved metabolic health. Integrative analysis of vastus lateralis muscle identified 8233 genes with differentially methylated regions and 2173 differentially expressed genes post-RYGB surgery, of which 1197 genes were both differentially methylated and differentially expressed. Promoter hypomethylation was associated with the enhanced expression of transcription factors involved in skeletal muscle development and ribosomal subunits. In contrast, expression of genes encoding mitochondrial proteins decreased despite increases in mitochondrial content and enhanced mitochondrial function in skeletal muscle post-RYGB. Pre-operative muscle OXPHOS capacity, and expression of skeletal muscle hypertrophy and differentiation genes MYOC and EHMT2 were associated with weight loss success. Interpretation: RYGB improves systemic metabolic health and induces sustained skeletal muscle bioenergetic reprogramming characterised by enhanced expression of genes involved in myogenesis and protein translation, but decreased expression of genes involved in mitochondrial metabolism, which may reflect improved mitochondrial quality and function. These findings advance our understanding of skeletal muscle metabolic responses to weight loss and of individual variability in metabolic phenotypes.
This dataset
Open GSE341455 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 GSE341455_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 PRJNA1502799 and SRA study SRP721537. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
70 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 70 sample titles: 70 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

+ 30 more — browse all 70 samples with per-sample file links →

Datasets on a similar topic

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.