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Integrated transcriptomic and epigenomic analysis demonstrates apple mango leaf extract induced maturation and functional activation of BMDCs

GSE292962 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2025/04/30 Platform GPL24247Platform GPL17021

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 10 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: Mus musculus (mouse)
Samples: 10 samples: 3 × RNA-seq, DMSO0.04%, vs 3 × RNA-seq, AMLE400ug/ml, vs 2 × ATAC-seq, DMSO0.04%, vs 2 × ATAC-seq, AMLE400ug/ml,Groups 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 apple mango (Mangifera indica L.) is primarily consumed for its fruit, and the other components of the plant, including the leaves, are often discarded as agricultural by-products. This study investigated the immunomodulatory properties of apple mango leaf extract (AMLE) using transcriptomic and chromatin accessibility analyses, focusing on gene regulation and signaling pathways in bone marrow-derived dendritic cells (BMDCs).

Read the full summary ↓

Weighted gene co-expression network analysis (WGCNA) revealed two inversely regulated gene network modules. The upregulated module following AMLE treatment included pathways essential for dendritic cell (DC) activation, while the downregulated module was enriched in cell cycle and metabolic pathways. Assay for Transposase Accessible Chromatin with Sequencing (ATAC-seq) analysis revealed increased promoter accessibility in AMLE-treated BMDCs, suggesting increased transcriptional activity. By integrating RNA-seq and ATAC-seq data, we identified 33 commonly regulated genes, with 25 upregulated genes forming a protein-protein interaction network centered on IL1b. These genes were associated with pathways related to cytokine signaling, T cell differentiation and extracellular matrix interactions. AMLE treatment enhanced DC chemotaxis, antigen presentation and promoted T cell differentiation signaling. Specifically, flow cytometric analysis shows that AMLE increased the expression of major histocompatibility complex class II (MHCII) and the co-stimulatory molecules CD40 and CD80, leading to BMDC maturation and expansion of the CD11c+MHCIIhi and CD11c+CD11blo subsets. These findings suggest that AMLE induces potent maturation responses through multiple pathways within DC subpopulations. By elucidating the transcriptional and epigenetic effects of AMLE on BMDCs, this study contributes to a broader understanding of plant-derived compounds in immune modulation.

This dataset

Open GSE292962 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE292962_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1242255 and SRA study SRP573425. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × RNA-seq, DMSO0.04%, vs 3 × RNA-seq, AMLE400ug/ml, vs 2 × ATAC-seq, DMSO0.04%, vs 2 × ATAC-seq, AMLE400ug/ml,

Supports a between-group comparison across 10 samples.

How we read this: 4 replicated groups read from 10 sample titles; they account for 10 of them. 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

GSM8871068 RNA-seq, DMSO0.04%, rep1 RNA-seq, DMSO0.04%,
GSM8871069 RNA-seq, DMSO0.04%, rep2 RNA-seq, DMSO0.04%,
GSM8871070 RNA-seq, DMSO0.04%, rep3 RNA-seq, DMSO0.04%,
GSM8871071 RNA-seq, AMLE400ug/ml, rep1 RNA-seq, AMLE400ug/ml,
GSM8871072 RNA-seq, AMLE400ug/ml, rep2 RNA-seq, AMLE400ug/ml,
GSM8871073 RNA-seq, AMLE400ug/ml, rep3 RNA-seq, AMLE400ug/ml,
GSM8871074 ATAC-seq, DMSO0.04%, rep1 ATAC-seq, DMSO0.04%,
GSM8871075 ATAC-seq, DMSO0.04%, rep2 ATAC-seq, DMSO0.04%,
GSM8871076 ATAC-seq, AMLE400ug/ml, rep1 ATAC-seq, AMLE400ug/ml,
GSM8871077 ATAC-seq, AMLE400ug/ml, rep2 ATAC-seq, AMLE400ug/ml,

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