We developed an allele-specific assay for transposase-accessible chromatin with high-throughput sequencing (ATAC–seq) to genotype and profile active regulatory DNA across the genome. Using a mouse hybrid F1 system, we found that monoallelic DNA accessibility across autosomes was pervasive, developmentally programmed and composed of several patterns. Genetically determined accessibility was enriched at distal enhancers, but random monoallelically accessible (RAMA) elements were enriched at promoters and may act as gatekeepers of monoallelic mRNA expression. Allelic choice at RAMA elements was stable across cell generations and bookmarked through mitosis. RAMA elements in neural progenitor cells were biallelically accessible in embryonic stem cells but premarked with bivalent histone modifications; one allele was silenced during differentiation. Quantitative analysis indicated that allelic choice at the majority of RAMA elements is consistent with a stochastic process; however, up to 30% of RAMA elements may deviate from the expected pattern, suggesting a regulated or counting mechanism.
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We thank J. Dekker for sharing Hi-C data before publication and for feedback, and J. Pritchard, A. Urban and members of our laboratories for advice. This work was supported by the US National Institutes of Health (NIH; P50-HG007735 to H.Y.C. and W.J.G.). The Heard labratory is “Equipe labellisée par la Ligue Nationale Contre le Cancer” and is supported by a European Research Council (ERC) Advanced Investigator Award; Labex DEEP (ANR-11-LBX-0044) part of the IDEX Idex PSL (ANR-10-IDEX-0001-02 PSL).
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Integrated supplementary information
Supplementary Figure 1 Evaluation of allelically informative accessible regions and monoallelic sites.
(a) Comparison of allelic read assignment for technical replicates, biological replicates and different clones. Pearson’s correlation coefficients were calculated from allelic counts for the 129 and Cast alleles. (b) Comparison of two statistical methods for evaluating allelic bias based on the binomial distribution and permutation method. Cumulative curves for P value (adjusted by the Benjamini–Hochberg procedure) from the X chromosome and chromosome 5 are shown in red and blue, respectively. The permutation method was compared to the exact binomial test. The right panel is a zoomed-out view of the left panel. The difference between the dark and light curves shows that the permutation method is more stringent on the autosomes, but more sensitive on the X chromosome. (c) Scatterplot showing the number of usable reads versus the number of allelically informative accessible regions. The number of allelically informative regions is close to stable when the number of usable sequencing reads is more than 40 million. The number of allelically informative accessible regions in ESCs is lower than for NPC clones with the same number of usable reads (red points). Blue points show downsampled data from a highly sequenced line (NPC XY14). (d) Scatterplot of TSS enrichment score versus the number of allelically informative accessible regions. There is no significant correlation between them (r = –0.186, P = 0.461). Red indicates the two ESC lines. (e) Simulation to determine the number of reads needed to identify monoallelic peaks in NPCs. 6–100 million usable reads were randomly sampled from a deeply sequenced NPC clone (NPC XY14). The number of monoallelically accessible regions dramatically increases up to 40 million reads where it plateaus. (f) Number of monoallelic peaks identified by ATAC–seq on the Cast X chromosome, 129 X chromosome, Cast autosomes and 129 autosomes in each cell line analyzed.
Supplementary Figure 2 Examples of genome-specific monoallelic regulatory elements and chromHMM annotation of accessible sites.
(a) Example of a 129-specific site located at the Mpp7 gene promoter on chromosome 18. 129 reads are shown in pink, and Cast reads are shown in blue. (b) Example of a Cast-specific site located at the AK043958 gene promoter on chromosome 4. 129 reads are shown in pink, and Cast reads are shown in blue. The peak to the left is biallelic, as indicated by pile-up of 129 (pink) and Cast (blue) reads, while the peak on the right is Cast specific. (c) Proportion of 129-specific, Cast-specific and RAMA elements located at distal elements (>2 kb from a TSS), promoter elements of expressed genes and promoter elements of unexpressed genes (<2 kb from a TSS). For each set of elements, control sets are size matched and matched for peak enrichment. (d) Chromatin states identified by chromHMM using available histone modification ChIP–seq data in NPCs. Enrichment for the histone modifications labeled on the x axis is represented in blue. Interpretations of each state are labeled on the right. (e) Allelically accessible regions (accessible regions for which ten clones have sufficient allelically informative information after removing CNV regions) show the same distribution of chromatin states as all accessible regions across the genome in NPCs.
Supplementary Figure 3 Genome-specific monoallelic sites and RAMA elements are stable across passages and during mitosis.
(a–c) Scatterplots showing the d score for Cast- and 129-specific monoallelically accessible regions in PX + 10 versus PX + 0 for NPC XX2, XX4 and XY14. (d) Distribution of changes in d score (max d score – min d score) across passages PX + 0, PX + 5, and PX + 10 for NPC clones XX2, XX4 and XY14. As a control, the changes in d score are compared to three replicates from a single clone at the same passage (NPC XX 1). (e) Distribution of changes in d score (max d score – min d score) across passages PX + 0, PX + 5, and PX + 10 for NPC clones XX2, XX4 and XY14 for genome-specific monoallelic elements. (f) Tracks showing an example RAMA element at the promoter of RME gene Fam149a across passages in NPC XX 4. 129 reads are shown in magenta, and Cast reads are shown in blue. (g) Scatterplot showing the number of reads under all ATAC–seq peaks in mitotic and asynchronous NPCs (XX 1). All peaks are shown in black, and RAMA elements are shown in red.
(a) Cumulative plot of the log2 (RPKM) values from RNA–seq data for RME genes with promoter RAMA elements (green) and RME genes with a non-RAMA element in the TSS region (yellow). (b) Cumulative plot showing the peak enrichment score for promoter RAMA elements located at RME genes (dark green) and non-RME genes (light green). (c) RT–PCR followed by Sanger sequencing for RME gene Bag3 in NPC lines XY7-10. Colored circles indicate the allelic status of the promoter ATAC–seq peak in that line. Red boxes outline the informative SNP at each locus. (d) Tracks showing allele-specific ATAC–seq at the noncoding RNA Vaultrc5, which is not detected by allelic RNA–seq due to poly(A) selection. 129 reads are shown in pink, and Cast reads are shown in blue. (e) Tracks showing allele-specific ATAC–seq at the noncoding RNA Mir34b, which is not detected by allelic RNA–seq due to poly(A) selection. 129 reads are shown in pink, and Cast reads are shown in blue. (f) Permutation of RNA–seq d score versus d score of all accessible elements within 2–10 kb of RME genes. Matched with Figure 4h, left. (g) Permutation of RNA–seq d score of nearest gene versus d score of distal RAMA elements. Matched with Figure 4h, left. (h) Density plot showing the correlation coefficient for distal RAMA elements and RNA–seq d score of the nearest gene compared to permutated values. (i) Density plot showing the correlation coefficient for ATAC–seq d score of accessible element and RNA–seq d score of the nearest gene for promoter and distal genetic MA separately. (j) Tracks showing allele-specific ATAC–seq at the Arc locus. The Arc promoter element is RAMA, while the upstream enhancer is biallelically accessible. 129 reads are shown in pink, and Cast reads are shown in blue.
Supplementary Figure 5 Chromatin signature of RAMA elements during differentiation from ESCs to NPCs.
(a) Histone modification signal from ESC ChIP–seq data at promoter RAMA elements that are accessible in ESCs. (b) Histone modification signal from NPC ChIP–seq data at promoter RAMA elements that are accessible in ESCs. (c) Histone modification signal from ESC ChIP–seq data at distal RAMA elements that are not accessible in ESCs. (d) Histone modification signal from NPC ChIP–seq data at distal RAMA elements that are not accessible in ESCs. (e) Histone modification signal from ESC ChIP–seq data at distal RAMA elements that are accessible in ESCs. (f) Histone modification signal from NPC ChIP–seq data at distal RAMA elements that are accessible in ESCs. (g) Chromatin states identified by chromHMM using histone modification ChIP–seq data from ESCs. Enrichment for histone modifications labeled on the x axis is represented in blue. Interpretations of each state are labeled on the right. (h) Chromatin states identified by chromHMM using Pol II and PRC complex ChIP–seq data from ESCs. Enrichment for transcription factors labeled on the x axis is represented in blue. Interpretations of each state are labeled on the right. (i) ChIP–qPCR for H3K4me3 and H3K9me3 at six RAMA promoters in XX1 ESCs.
(a) Distribution of Pact (n accessible alleles/n total alleles) for promoter-distal (blue) and promoter-proximal (black) RAMA elements. (b) Distribution of P value by likelihood test for all RAMA elements. (c) Example RAMA site at the promoter of Mettl24 that has fewer monoallelic (1) clones than expected based on its Pact of 0.81. (d) Allelic ATAC–seq signal in 16 clones at the RAMA promoter element at Pde7b (related to Fig. 6h). Pink, 129 monoallelic; blue, Cast monoallelic; gray, biallelically accessible; black, not accessible; white, masked in CNV region. (d) Allelic ATAC–seq signal in 16 clones at the RAMA promoter element at Slc27a6 (related to Fig. 6i). Pink, 129 monoallelic; blue, Cast monoallelic; gray, biallelically accessible; black, not accessible; white, masked in CNV region.
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Xu, J., Carter, A., Gendrel, AV. et al. Landscape of monoallelic DNA accessibility in mouse embryonic stem cells and neural progenitor cells. Nat Genet 49, 377–386 (2017). https://doi.org/10.1038/ng.3769
BMC Ecology and Evolution (2022)
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