Controlling for DNA dosage with whole-genome sequencing improves ATAC-seq peak calling
Abstract
ATAC-seq is a powerful method for mapping chromatin accessibility and identifying cis-regulatory elements (CREs) across cell types. We reveal that ATAC-seq peak calling is compromised by local biases in DNA dosage, arising from copy number variations but also from DNA replication timing. As part of the FANTOM consortium’s efforts, we propose enhancing the model-based analysis of ChIP-seq pipeline by integrating whole-genome sequencing (WGS) data, analogous to input controls in ChIP-seq analyses. This adjustment increases both the number and width of ATAC peaks, with improved proximity to transcription start sites. These ATAC peaks exhibit canonical CRE epigenetic marks and are enriched for trait- and disease-associated genetic variants. Furthermore, the number of peaks called with WGS enhances the correlation with gene expression levels compared to peaks called without WGS control. Collectively, these results demonstrate that integrating WGS as a control significantly enhances the accuracy of ATAC-seq peak calling. Critically, even low-depth WGS data suffice to improve peak calling, making this approach cost effective and scalable. We implemented this method as an open-source Nextflow pipeline for accessibility and reproducibility. By challenging the assumption of uniform genomic visibility, our approach also holds broad implications for other DNA sequencing-based technologies.
Related
- ogMapper improves speed and memory for short-sequencing read mapping using a novel guided sparse genome index
- Whole-genome sequencing and comparative genomic analysis of Plenodomus biglobosus
- Protocol for genome-wide differential methylation using long-read DNA sequencing in the cortex of a mouse model of Alzheimer's disease.
- BioSIFTR: functional inference from shallow shotgun sequencing using biome-specific genome catalogues benchmarked in gut microbiomes
- IndelQuant: A Workflow for Cost-Efficient Amplicon Sequencing Analysis of Genome-Edited Chickens
BibTeX
@article{vroland2026controlling,
title = {{Controlling for DNA dosage with whole-genome sequencing improves ATAC-seq peak calling}},
author = {Christophe Vroland and Mohammad Salma and Artemy Zhigulev and Pelin Sahlen and Eric Soler and Laurent Bréhélin and Charles-Henri Lecellier},
journal = {NAR Genomics and Bioinformatics},
year = {2026},
month = oct,
doi = {10.1093/nargab/lqag119},
url = {https://hal.science/hal-05843241v1},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Controlling for DNA dosage with whole-genome sequencing improves ATAC-seq peak calling
AU - Christophe Vroland
AU - Mohammad Salma
AU - Artemy Zhigulev
AU - Pelin Sahlen
AU - Eric Soler
AU - Laurent Bréhélin
AU - Charles-Henri Lecellier
PY - 2026
DA - 2026/10/09
JO - NAR Genomics and Bioinformatics
DO - 10.1093/nargab/lqag119
UR - https://hal.science/hal-05843241v1
AB - ATAC-seq is a powerful method for mapping chromatin accessibility and identifying cis-regulatory elements (CREs) across cell types. We reveal that ATAC-seq peak calling is compromised by local biases in DNA dosage, arising from copy number variations but also from DNA replication timing. As part of the FANTOM consortium’s efforts, we propose enhancing the model-based analysis of ChIP-seq pipeline by integrating whole-genome sequencing (WGS) data, analogous to input controls in ChIP-seq analyses. This adjustment increases both the number and width of ATAC peaks, with improved proximity to transcription start sites. These ATAC peaks exhibit canonical CRE epigenetic marks and are enriched for trait- and disease-associated genetic variants. Furthermore, the number of peaks called with WGS enhances the correlation with gene expression levels compared to peaks called without WGS control. Collectively, these results demonstrate that integrating WGS as a control significantly enhances the accuracy of ATAC-seq peak calling. Critically, even low-depth WGS data suffice to improve peak calling, making this approach cost effective and scalable. We implemented this method as an open-source Nextflow pipeline for accessibility and reproducibility. By challenging the assumption of uniform genomic visibility, our approach also holds broad implications for other DNA sequencing-based technologies.
SN - 2631-9268
ER -