用全基因组测序校正 DNA 剂量可改善 ATAC-seq peak calling
Controlling for DNA dosage with whole-genome sequencing improves ATAC-seq peak calling
FANTOM 联盟的研究提出，把全基因组测序（WGS）数据作为对照整合进基于模型的 ChIP-seq 分析流程（MACS），以校正拷贝数变异和 DNA 复制时序带来的局部 DNA 剂量偏倚，从而改善 ATAC-seq 的 peak calling。加入 WGS 对照后，检出的 ATAC peak 数量和宽度均增加，与转录起始位点的距离更近，带有典型 cis 调控元件（CRE）的表观标记，并富集性状与疾病相关遗传变异。与基因表达水平的相关性也优于不加 WGS 对照的 peak。
来源：NAR Genomics and Bioinformatics · doi.org
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.