Abstract
BackgroundChromatin dysregulation is associated with developmental disorders and cancer. Numerous methods for measuring genome-wide chromatin accessibility have been developed in the genomic era to interrogate the function of chromatin regulators. A recent technique which has gained widespread use due to speed and low input requirements with native chromatin is the Assay for Transposase-Accessible Chromatin, or ATAC-seq. Biologists have since used this method to compare chromatin accessibility between two cellular conditions. However, approaches for calculating differential accessibility can yield conflicting results, and little emphasis is placed on choice of normalization method during differential ATAC-seq analysis, especially when global chromatin alterations might be expected.ResultsUsing an in vivo ATAC-seq data set generated in our recent report, we observed differences in chromatin accessibility patterns depending on the data normalization method used to calculate differential accessibility. This observation was further verified on published ATAC-seq data from yeast. We propose a generalized workflow for differential accessibility analysis using ATAC-seq data. We further show this workflow identifies sites of differential chromatin accessibility that correlate with gene expression and is sensitive to differential analysis using negative controls.ConclusionsWe argue that researchers should systematically compare multiple normalization methods before continuing with differential accessibility analysis. ATAC-seq users should be aware of the interpretations of potential bias within experimental data and the assumptions of the normalization method implemented.
Highlights
Genome-wide quantitative sequencing methods for measuring genomic features have been recently developed to address various biological questions previously limited to locus-level interrogation
Comparison of 8 analytical approaches to calculate Assay for Transposase-Accessible Chromatin (ATAC)‐seq differential accessibility To determine if choice of ATAC-seq differentially accessible (DA) analysis method influences experimental results, we compared 8 different DA approaches (Table 1) using the published tools MACS2, DiffBind, csaw, voom, limma, edgeR, and DESeq2 [27,28,29,30,31,32,33]
We present data indicating that ATAC-seq is sensitive to bias when comparing chromatin accessibility across multiple conditions
Summary
Adapter-ligated genomic regions, which are typically nucleosome-depleted and euchromatic, can be enriched for sequencing This technique provides a similar readout as DNase I hypersensitivity (DNase-seq) and formaldehyde-assisted isolation of regulatory elements (FAIRE-seq), which measure accessible chromatin regions, and it is an orthogonal assay to Micrococcal nuclease digestion (MNase-seq), which measures nucleosome-occupied regions [9, 10]. ATAC-seq offers many benefits over comparable assays including a lower input material requirement, shorter assay time, in situ library preparation, and further protocol adaptation to fresh-frozen tissue [11]. These advantages have permitted precise in vivo regulatory genomic assays on small populations of sorted cells [12,13,14,15,16,17]. Approaches for calculating differential accessibility can yield conflicting results, and little emphasis is placed on choice of normalization method during differential ATAC-seq analysis, especially when global chromatin alterations might be expected
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