Lineage-Resolved Enhancer and Promoter Usage during a Time Course of Embryogenesis.

Enhancers are essential drivers of cell states, yet the relationship between accessibility, regulatory activity, and in vivo lineage commitment during embryogenesis remains poorly understood. Here, we measure chromatin accessibility in isolated neural and mesodermal lineages across a time course of Drosophila embryogenesis. Promoters, including tissue-specific genes, are often constitutively open, even in contexts where the gene is not expressed. In contrast, the majority of distal elements have dynamic, tissue-specific accessibility. Enhancer priming appears rarely within a lineage, perhaps reflecting the speed of Drosophila embryogenesis. However, many tissue-specific enhancers are accessible in other lineages early on and become progressively closed as embryogenesis proceeds. We demonstrate the usefulness of this tissue- and time-resolved resource to definitively identify single-cell clusters, to uncover predictive motifs, and to identify many regulators of tissue development. For one such predicted neural regulator, l(3)neo38, we generate a loss-of-function mutant and uncover an essential role for neuromuscular junction and brain development.

Reproducible inference of transcription factor footprints in ATAC-seq and DNase-seq datasets using protocol-specific bias modeling.

BACKGROUND: DNase-seq and ATAC-seq are broadly used methods to assay open chromatin regions genome-wide. The single nucleotide resolution of DNase-seq has been further exploited to infer transcription factor binding sites (TFBSs) in regulatory regions through footprinting. Recent studies have demonstrated the sequence bias of DNase I and its adverse effects on footprinting efficiency. However, footprinting and the impact of sequence bias have not been extensively studied for ATAC-seq. RESULTS: Here, we undertake a systematic comparison of the two methods and show that a modification to the ATAC-seq protocol increases its yield and its agreement with DNase-seq data from the same cell line. We demonstrate that the two methods have distinct sequence biases and correct for these protocol-specific biases when performing footprinting. Despite the differences in footprint shapes, the locations of the inferred footprints in ATAC-seq and DNase-seq are largely concordant. However, the protocol-specific sequence biases in conjunction with the sequence content of TFBSs impact the discrimination of footprint from the background, which leads to one method outperforming the other for some TFs. Finally, we address the depth required for reproducible identification of open chromatin regions and TF footprints. CONCLUSIONS: We demonstrate that the impact of bias correction on footprinting performance is greater for DNase-seq than for ATAC-seq and that DNase-seq footprinting leads to better performance. It is possible to infer concordant footprints by using replicates, highlighting the importance of reproducibility assessment. The results presented here provide an overview of the advantages and limitations of footprinting analyses using ATAC-seq and DNase-seq.