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Hepatocytes demarcated by EphB2 contribute to the progression of non-alcoholic steatohepatitis

GSE189600 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 21 samples Submitted 2023/02/08 Platform GPL24247Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 21 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
21 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)
Current therapeutic strategies for treating non-alcoholic steatohepatitis (NASH) have failed to alleviate liver fibrosis, which is a devastating feature leading to hepatic dysfunction. Here, we integrated single-nucleus transcriptomics and epigenomics to characterize all major liver cell types during NASH development in mice and humans.
Read the full summary ↓
The bifurcation of hepatocyte trajectory with NASH progression was conserved between mouse and human. At the non-alcoholic fatty liver (NAFL) stage, hepatocytes exhibited metabolic adaptation, whereas at the NASH stage, a subset of hepatocytes was enriched for the signatures of cell adhesion and migration, which was mainly demarcated by receptor tyrosine kinase EphB2. EphB2, acting as a downstream effector of Notch signaling in hepatocytes, was sufficient to induce cell-autonomously inflammation. Knockdown of Ephb2 in hepatocytes ameliorated inflammation and fibrosis in NASH. Thus, EphB2 expressing hepatocytes contribute to NASH progression and may serve as a potential therapeutic target.
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 GSE189600_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA783863 and SRA study SRP348024. Searching any of these in the dataset finder brings you back here.

Samples in this study

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