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Functional investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatment [ATAC-seq]

GSE224530 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 32 samples Submitted 2024/04/10 Platform GPL24676Platform GPL20301
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 32 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
32 samples: 11 conditions, mostly in duplicateGroups 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.
Paper
Investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatmentNature communications · 2024
Summary (written by the submitters)
Although acute lymphoblastic leukemia (ALL) is the most prevalent childhood cancer, there is limited understanding of the contribution of inherited genetic variation on inter-individual differences in chemotherapy response, and defining genetic factors impacting therapy failure can help better predict response and identify drug resistance mechanisms.
Read the full summary ↓
Using inherited noncoding variants associated with chemotherapeutic drug resistance and/or treatment outcome, we mapped these variants to ALL cis-regulatory elements and investigated their gene regulatory potential and genomic connectivity using massively parallel reporter assays and promoter capture Hi-C, respectively. We identified 53 variants with reproducible allele-specific effects on transcription and high-confidence gene targets. Subsequent functional interrogation of the top variant (rs1247117) determined that it disrupted a PU.1 consensus motif and PU.1 binding affinity. Importantly, deletion of the genomic interval containing rs1247117 sensitized ALL cells to vincristine. Together, these data demonstrate that noncoding regulatory variation associated with diverse pharmacological traits harbor significant effects on allele-specific transcriptional activity and impact sensitivity to chemotherapeutic agents in ALL.
Published in
Investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatment
Bhattarai KR, Mobley RJ, Barnett KR et al. · Nature communications 2024 · PMID 38693155 · doi:10.1038/s41467-024-48124-4
This dataset
Open GSE224530 in finder → Find more human 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 GSE224530_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 PRJNA931605 and SRA study SRP420997. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38693155) ↗
Study design
11 conditions, mostly in duplicate
ATAC_NALM6_parental ×3 ATAC_NALM6_rs1247117_AtoG_clone1 ×3 ATAC_NALM6_rs1247117_AtoG_clone2 ×3 ATAC_P12 ×2 ATAC_MOLT16 ×2 ATAC_CEM ×2 ATAC_Loucy ×2 ATAC_DND41 ×2 +10 more

Supports a between-group comparison across 25 samples.

How we read this: 11 replicated groups read from 32 sample titles; they account for 25 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
Datasets on a similar topic

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