The activity of early-life gene regulatory elements is hijacked in aging through pervasive AP-1–linked chromatin opening
Creators: name: Naval Sanchez, Marina
name: Patrick, Ralph
name: Nefzger, Christian M
Publisher: name: figshare
Year: 2024
Subjects: classificationCode: 310204
subject: Genomics and transcriptomics
classificationCode: 310201
subject: Bioinformatic methods development
classificationCode: 310206
subject: Sequence analysis

description: This page contains code and associated data files for reproducing analyses and figures in the paper "The activity of early-life gene regulatory elements is hijacked in aging through pervasive AP-1–linked chromatin opening" by Patrick and Naval-Sanchez et al. The code in many cases will be reliant on data in zipped subfolders - make sure any referenced folders have been downloaded and unzipped. The scripts for generating different analyses/figures in the paper can be found as follows:Peak calling and generation of an open-chromatin atlas.The in-house step-by-step scripts to generate the "460K universal ATAC-seq peak set" across 23 murine cell types and two ageing conditions, 2 months and 22-24 months, can be found in the folder ATAC-seq_peak_universe.ATAC-seq and RNA-seq PCAATAC-seq PCA analyses (Figures 1C and S2D) are in ATACseq_PCA_analysis.R and RNA-seq PCA (Figure 1D) analyses are in RNAseq_PCA.R.ATAC-seq Differential Accessible Analyses can be redone using the script Universal_DARS_cell_type.RMarker heatmapThe heatmap of marker expression and correlation analysis (Figure S2A) - cell_type_marker_heatmap.R.DAR scATAC-seq validationsThe evaluation of HSC DARs in HSC scATAC-seq (Figures 1E-G and S2E-F) is in the scATACseq/HSCs folder in HSC_DAR_comparisons.R. The evaluation in neuron DARs in frontal cortex scRNA-seq (Figures S2G-I) is in neuron_scATAC-seq_validation.R.ATAC-seq DAR featuresThe analysis of DAR features in Figures 2A-C, 2I-J and S2A-D are in ATACseq_DAR_features.R.The plotting of Jaccard coefficients representing the number of overlapping DARs among different cell types as presented in Figure S3E-J can be reproduced using Supplementary_Figure3_E_F.R and the FS3 folder.Peak:gene linkage analysisThe script for running the peak:gene linkage analysis is in gene_peak_correlations_corrected_bg.R. The script for generating summaries of the linkage features and overlap with DORCs in mouse skin (Figures S4A-D) is peak_gene_tss_downstream_analysis.R. The script for evaluating the overlap of neuron linkages with mouse cortex Hi-C data (Figure S4E) is Neuron_links_HiC_validation.R. The script for evaluating the overlap of muscle stem cell links with corresponding Hi-C data (Figure S4F) is muscle_stem_cell_HiC_validation.R. The script for evaluating the overlap of DAR-linked genes and DEGs (Figure 3C-E) is linked_genes_DAR_DEG_overlaps.R. The script for evaluating the peak:gene expression analyses (Figures 3F, 3B and S4J) are in dar_linked_gene_expression_analysis.R.STRING DEG analysisThe script for running the comparison of STRING networks in DAR-linked vs non-DAR-linked DEGs (Figure S4H) is string_DEG_analysis.R.GO term analyses in DAR-linked genesThe script for generating the GO term tests underlying Figures 3G-H and S4K-N is in linked_genes_go_analysis.R.Mouse 460K universal peak set classification in 7 global peak categories and average LFC accessibility changes across cell types.The script for generating the Figure 4B is in Figure4B_log2FC_accessiblity_pie_regions.R and the data required in the Figure4B folder.Prioritisation and plotting the AP-1/CTCF/Cell identity codeScripts Figures4G_5G_heatmaps.R, Associating_motif2TFGE.R, Associationg_motif2TF2GE_human_fetal.R together with the data folders Figure4G_5G_heatmaps, prioritisation_cell_type_specific_motifs and human_data_TF_prioritization contain the scripts and information to reproduce the analysis to prioritise cell-type specific TFs based on motif enrichment results and gene expression. They also contain the scripts to visualise the AP-1/CTCF/Cell-type log fold change enrichment compared with genomic background across general peak categories. These scripts reproduce the heatmaps in Figure 4G and 5G.Plotting AP-1/CTCF/Cell-type specific Gene ExpressionScript Figure5G_boxplot_gene_expression and its corresponding folder can be used to reproduce Gene expression box plots (Figure 5G). That is gene expression Log Fold Change differences (median of TFs across cell types) relative to young cells for genes linked to each of the three TF groups, namely, AP-1, CTC and Cell-type specific.<br>Human maturation 17 cell types motif enrichment heatmapThe scripts for generating the human maturation 17 cell type heatmap (Figure 4H) are in scATACseq/Human_17_cell_types.Human neuron analysisThe scripts for analysis of the human neuron single-cell multiome data (Figure S6C) are in scATACseq/Neurons.Human pituitary gland analysisThe scripts for analysis of the human pituitary gland single-cell multiome data (Figures 4I, 4J and S6D-I) are in scATACseq/Pituitary_gland.Mouse keratinocyte maturationThe script for comparing keratinocyte age-DARs in keratinocyte maturation scATAC-seq (Figure S6P) are in scATACseq/Keratinocytes.Mouse kidney EC maturationThe script for comparing kidney EC age-DARs in kidney EC maturation scATAC-seq (Figure S6Q) is in scATACseq/Kidney.Top globally redistributed factor analysisScript for analysis of top globally redistributed factors is global_redistribution_scoring.R. Script for differential expression analysis of top redistributed factors (e.g. Figure S8F) is redistribution_differential_expression_analysis.RCUT&amp;RUNThe CUT&amp;RUN analyses presented in Figures 5G, S7 and S5 are in the scripts cut_and_run_CTCF_stable_peaks.R (Figure S5), cut_and_run_validation.R (Figure S7), cut_and_run_keratinocyte_comparisons.R (Figure 5) and cut_and_run_DAR_Tcell_comparisons.R (Figure S7).GO term analyses for genes linked to stress/stimulus DARsScripts for performing the GO analyses of genes linked to Fosl2 overexpression or stress-associated DARs (Figures 6L-M) are in MEF_DAR_linkages.R, stress_DAR_linkages.R and MEF_stress_plot_GO_terms.R.<br>