GEO series

Generation of human hypothalamic appetite-regulating neurons and tanycytes from stem cells

GSE271235 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2026/05/29 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 21 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: 21 samples: 21 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)

The balance between energy intake and expenditure is controlled by the hypothalamus, a small brain region composed of several subregionalised nuclei with high neuronal diversity which are key to controlling appetite and food intake through response to circulating hormones and metabolic. However, the cellular and functional characteristics of this highly specialised neural region has been studied mainly in animal models due to a lack of access to human experimental counterparts.

Read the full summary ↓

Here, we fine-tuned the differentiation of human pluripotent stem cells toward hypothalamic nuclei, including the arcuate nucleus (ARC), ventromedial hypothalamus (VMH) and paraventricular nucleus (PVN), and we identified key subtype-specific progenitor markers of hypothalamic subregions. We show that the timing for addition and withdrawal of bone morphogenic protein (BMP) was essential for controlling sub-regional specification of tuberal hypothalamic progenitors along the anterior-posterior axis, balancing VMH versus ARC fates. A particular population of SHH-/NKX2.1+/RAX+/FGF10+/TBX3high posterior tuberal progenitors was identified as the source for generation of ARC-associated agouti-related peptide (AGRP) neurons and tanycytes whilst anterior tuberal SHH+/NKX2.1+/RAX+/TBX3low progenitors generated VMH phenotypes including NR5A1 neurons. Upon maturation in 2D, 3D and in vivo, ARC-patterned progenitors gave rise to multiple key appetite-regulating cell types including AGRP, prepronociceptin (PNOC), growth hormone-releasing hormone (GHRH), thyrotropin-releasing hormone (TRH) and pro-opiomelanocortin (POMC) neurons and characteristic tanycyte glial cells. Differentiated ARC cultures showed high transcriptomic similarity to the human ARC and displayed evidence of functionality by AGRP secretion and responsiveness to leptin and fibroblast growth factor 1 (FGF1). In summary, our work provides new insights into the developmental lineages underlying human hypothalamic subregional specification and enables access to highly characterized human hypothalamic ARC cultures, which will provide novel opportunities for investigating the cellular and molecular pathways triggered by obesity-associated genetic variants and appetite-regulating drugs and peptides.

This dataset

Open GSE271235 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 GSE271235_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 PRJNA1130498 and SRA study SRP517396. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

21 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 21 sample titles: 21 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

GSM8372005 RC17 cells, ARC, day 16, RNA (D4) + HTO (D703), scRNA-seq
GSM8372006 RC17 cells, ARC, day 25_50_70, RNA (D1) + HTO (D701), snRNA-seq
GSM8372007 RC17 cells, ARC, day 25_50_70, RNA (E1) + HTO (D702), snRNA-seq
GSM8372008 RC17 cells, ARC, day 25_50_70, RNA (F1) + HTO (D703), snRNA-seq
GSM8372009 RC17 cells, ARC, day 25_50_70, RNA (G1) + HTO (D704), snRNA-seq
GSM8372010 RC17 cells, ARC, day 25_50_70, RNA (H1) + HTO (D705), snRNA-seq
GSM8372011 RC17 cells, ARC, day 25_50_70, RNA (C2) + HTO (D706), snRNA-seq
GSM8372012 RC17 cells, ARC, day 25_50_70, RNA (D2) + HTO (D707), snRNA-seq
GSM8372013 RC17 cells, ARC, day 25_50_70, RNA (E2) + HTO (D708), snRNA-seq
GSM8372014 RC17 cells, ARC, day 25_50_70, RNA (F2) + HTO (D709), snRNA-seq
GSM8372015 RC17 cells, ARC, day 25_50_70, RNA (G2) + HTO (D710), snRNA-seq
GSM8372016 RC17 cells, ARC, day 25_50_70, RNA (H2) + HTO (D711), snRNA-seq
GSM8372017 RC17 cells, ARC, day 70, RNA (A6) + HTO (D701), snRNA-seq
GSM8372018 RC17 cells, ARC, day 70, RNA (A7) + HTO (D702), snRNA-seq
GSM8372019 RC17 cells, ARC, day 70, RNA (A9) + HTO (D703), snRNA-seq
GSM8372020 RC17 cells, ARC, day 70, RNA (A11) + HTO (D704), snRNA-seq
GSM8372021 RC17 cells, ARC, day 70, RNA (B5) + HTO (D705), snRNA-seq
GSM8372022 RC17 cells, ARC, day 70, RNA (B6) + HTO (D706), snRNA-seq
GSM8372023 RC17 cells, ARC, day 70, RNA (B7) + HTO (D707), snRNA-seq
GSM8372024 RC17 cells, ARC, day 70, RNA (B8) + HTO (D708), snRNA-seq
GSM8372025 RC17 cells, ARC, day 70, RNA (B10) + HTO (D709), snRNA-seq

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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.