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Brain-Derived CCN3 Is An Osteoanabolic Hormone That Sustains Bone in Lactating Females [pituitary gland]

GSE248880 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2024/09/03 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 16 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
Mus musculus (mouse)
Samples
16 samples
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
A maternal brain hormone that builds boneNature · 2024
Summary (written by the submitters)
During lactation, mothers initiate cycles of bone formation followed by significant bone loss to meet the high calcium (Ca2+) demand by progeny. While estrogen functions typically as an anabolic driver of bone remodeling, this sex steroid is absent in postpartum females. Here, we report that a brain-derived secreted from neurons of the arcuate nucleus (ARC) fills this void and functions as a potent osteogenic factor to promote bone mass in lactating females.
Read the full summary ↓
We previously reported an extraordinarily sex-specific high bone mass phenotype in female mice that persists with aging and is central in origin after eliminating estrogen receptor alpha signaling in ARCKISS1 neurons. Parabiosis and bone transplant studies established that a humoral factor in mutant females accounts for this unusual skeletal phenotype. High bone mass in mutant females could be traced back to the skeletal stem cell (SSC) level, reflected by their increased frequency and osteochondrogenic potential. Based on ex-vivo, in vivo, and in vitro assays, one protein emerged as the most promising secreted pro-osteogenic factor from the ARC, acting in mice and human SSCs at low concentrations (<nM) independent of age and sex. The role of this brain-derived factor in bone formation was confirmed by in vivo gain and loss of function studies. Unexpectedly, in wild-type females, a transient spike of this protein appears in ARCKISS1 neurons coincident with lactation when bone remodeling and high calcium demand intensify in estrogen-depleted mothers. Our findings establish a potentially new therapeutic anabolic bone hormone that functions in a novel female-specific brain-bone axis to ensure mammalian species survival.
Published in
A maternal brain hormone that builds bone
Babey ME, Krause WC, Chen K et al. · Nature 2024 · PMID 38987585 · doi:10.1038/s41586-024-07634-3
This dataset
Open GSE248880 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 GSE248880_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 PRJNA1046372 and SRA study SRP474797. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38987585) ↗
Samples in this study

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+ 16 more — browse all 16 samples with per-sample file links →

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