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JAX Study 1- RNA-seq of male KOLF2.2J hiPSC-derived trophoblast cell lines homozygous null for seven different transcription factors

GSE288288 Homo sapiens (human) RNA-seq (gene expression) 90 samples Submitted 2025/01/30 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 90 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
90 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.
Summary (written by the submitters)
This study aims to phenotype iPSC-derived trophoblast lines that contain homozygous null alleles for transcription factors expressed within the extra-embryonic lineage, with a focus on differentiation toward either primitive syncytium or extra-embryonic mesenchymal cells, depending on the TF being analyzed. Null alleles were generated using three distinct genetic engineering approaches: full protein coding region deletion (KO), critical exon deletion (CE), and insertion of a premature termination codon with frameshift (PTC+1).
Read the full summary ↓
RNA-seq data was generated after 6 days of initiating differentiation from iPSCs. The study included the homozygous null alleles for the following transcription factors: GRHL1, POU2F3, EPAS1, FOSB, GCM1, PPARG, and ISL1. Notably, the hypoxia-inducible factor EPAS1 was evaluated under both 20% oxygen and 3% (~ level present at peri-implantation) oxygen concentrations. This analysis provided insight into the differences between the various CRISPR-Cas9-based approaches and the impact of loss of function for these transcription factors in trophoblast lineage differentiation.
This dataset
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.

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 GSE288288_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJEB83081 and SRA study ERP166747. Searching any of these in the dataset finder brings you back here.

Samples in this study

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