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Rapid Human Oogonia-like Cell Specification via Combinatorial Transcription Factor-Directed Differentiation [RNA-seq]

GSE273465 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2024/07/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 28 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
28 samples: 28 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 generation of germline cell types from human induced pluripotent stem cells (hiPSCs) represents a key milestone toward in vitro gametogenesis, which has the potential to transform reproductive modeling and medicine. Methods to recapitulate advanced germline cell specification in vitro have relied on extensive, long term culture methods, the most notable of which is a four-month culture protocol employing xenogeneic reconstituted ovaries with mouse embryonic ovarian somatic cells.
Read the full summary ↓
Recently, transcription factor (TF)-based methods have demonstrated the feasibility of exogenous factor expression to directly differentiate hiPSCs into cell types of interest, including various ovarian cell types. The protocols leveraged in these studies, however, utilize more local methods of factor selection, such as basic differential gene expression analysis, and lower-throughput screening strategies via iterative testing of a small set of TFs. In this work, we integrate our recently-described graph theory pipeline and highly-parallelized screening protocols to globally identify and screen 46 oogenesis-regulating TFs for their role in human germline formation. We identify ZNF281, LHX8, SOHLH1, ZGLP1, and ANHX whose combinatorial overexpression drives DDX4+ induced oogonia-like cell (iOLC) formation from hiPSCs. In contrast to previous methods, our protocol employs a simple four-day, feeder-free monolayer culture condition. We additionally demonstrate a method of post-isolation, feeder-free expansion of DDX4+ iOLCs that shows retained cell identity in vitro. We additionally identify DLX5, HHEX, and FIGLA whose individual overexpression enhances hPGCLC formation from hiPSCs. We characterize these TF-based iOLCs and hPGCLCs via gene and protein expression analyses and demonstrate their broad similarity to in vivo and in vitro-derived oogonia and primordial germ cells. Together, these results identify new regulatory factors that enhance in vitro human germ cell specification and further establish unique computational and experimental tools for human in vitro oogenesis research.
This dataset
Open GSE273465 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 GSE273465_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 PRJNA1141981 and SRA study SRP523099. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
28 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 28 sample titles: 28 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.