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A multi-omics census reveals miRNA miR-let-7 as instigator of paternal mitochondrial dysfunction and in epigenetic heredity of intergenerational metabolic decline [F0_Liv_eWAT_RNAseq]

GSE280273 Mus musculus (mouse) Single-cell RNA-seq 36 samples Submitted 2025/01/15 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 36 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
36 samples: 36 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)
We describe that diet-induced obesity and weight loss development in male mice causes reversible abnormalities in glucose and lipid metabolism, serum metabolomes, and adipose tissue and liver gene expression and causes specific, but reversible, reductions in activity of genes controlling mitochondrial energy dissipation in white adipose tissue.
Read the full summary ↓
When mating obese mice with isogenic lean females, we observed highly concordant reductions in mitochondrial gene expression and translation in offspring that resemble those observed in obese fathers. When mapping small RNA responses across somatic and gametic cell types and between generations, we saw that obesity and weight loss reversible affected miRNA abundance, and observed several miR-let7 isoforms induced in obese adipose tissues of the paternal (F0) and offspring (F1) generation, as well as in sperm of F0 mice. Mechanistically, when overexpressing miR-let-7 in primary adipocytes, we found it to silence DICER1, a key rheostat required for adipose tissue adaptation in obesity as evidenced by functional deficiency in mitochondrial functioon following DICER1 loss. Upon ectopic delivery of miR-let7d/e levels into fertilized oocytes by microinjection, we elicited glucose intolerance and impairments in adipose mitochondrial gene expression in mice sired from miRNA-injected embryos, thus phenocopying key aspects of paternal obesity itself. When performing single-cell RNA-Seq in embryos, we found that miR-let7d/e delivery impaired mitochondrial gene expression, suggesting altered energy metabolism following sperm-mediated changes in zygotic miRNA pools. When studying miRNA alterations in human gametes, we found that lifestyle-induced weight loss downregulated MIR-LET7D/E in semen from human subjects, suggesting similar roles for human miR-let7d/e in gametic epigenomes and embryogenesis.
This dataset
Open GSE280273 in finder → Find more mouse 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 GSE280273_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1177507 and SRA study SRP540713. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
36 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 36 sample titles: 36 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
Datasets on a similar topic

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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.