A temporal single cell atlas of dynamic chromatin accessibility during mammalian lung maturation

Mammalian lung maturation involves intricate cellular differentiation and structural remodeling, yet the underlying epigenetic dynamics remain poorly characterized at single-cell resolution. Here we present HTL-ATAC-seq, an ultra-high throughput, ligation-based single cell ATAC-seq approach. Applying HTL-ATAC-seq to mouse lung tissue across 15 continuous postnatal time points, we constructed a temporal chromatin accessibility atlas from 1,185,619 nuclei, capturing dynamic changes in the regulome during lung maturation. We identified 129 distinct cell subclusters and 713,987 candidate chromatin regulatory elements (cCREs). Temporal analysis revealed three distinct cellular maturation stages and 12 distinct dynamic chromatin accessibility patterns, reflecting the coordinated transition from structural morphogenesis to immune maturation. We uncovered distinct cCRE-transcription factor binding patterns between alveolar type 1 (AT1) and 2 (AT2) cells and identified a novel Sprr1a enhancer specifically active in AT1 cells. Finally, we identified time- and cell type-specific cCREs linked to lung disease susceptibility. This comprehensive resource provides insights into the epigenetic mechanisms underlying lung maturation and disease risk. Data File Descriptions all_cCREs.csvA table containing information on all candidate cis-Regulatory Elements (cCREs).Each row corresponds to one cCRE, and columns indicate chromatin accessibility across different cell types and time points. cell_meta_ann.csvCell-level metadata table.Each row represents one cell (cell/barcode), and columns include sample ID, cell type annotation, quality control metrics, and low-dimensional embedding coordinates (UMAP/TSNE), etc. celltype_modify.csvA modified version and mapping table of cell type annotations, used to standardize cell type names for downstream analyses. Epi_AT1_sub.rdsAn RDS file storing a Seurat object that contains only AT1-related cells, including the accessibility matrix, dimensionality reduction results, and clustering information, for dedicated analysis of AT1 cell subpopulations. Epi_AT2_sub.rdsAn RDS file storing a Seurat object that contains only AT2-related cells, including the accessibility matrix, dimensionality reduction results, and clustering information, for dedicated analysis of AT2 cell subpopulations. epi_sub.rdsA Seurat object of the full epithelial cell subset.It includes accessibility matrices, dimensionality reduction and clustering results, and epithelial cell type annotations for all epithelial-related cells. NMF_modules.csvMapping between modules and gene sets obtained from Non-negative Matrix Factorization (NMF). pseudoObj_cells.rdsBecause the full accessibility matrix of all cells exceeds the data size that R can efficiently handle, a manually constructed pseudo-Seurat object for all cells was created without storing the accessibility matrix.This object is intended to facilitate downstream visualization using Seurat. pseudoObj_peaks.rdsBecause the full accessibility matrix of all cells exceeds the data size that R can efficiently handle, a manually constructed pseudo-Seurat object for all cCREs was created without storing the accessibility matrix.This object is intended to facilitate downstream analyses and visualizations such as CoveragePlot.