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. 2015 Feb 19;518(7539):331-6.
doi: 10.1038/nature14222.

Chromatin Architecture Reorganization During Stem Cell Differentiation

Free PMC article

Chromatin Architecture Reorganization During Stem Cell Differentiation

Jesse R Dixon et al. Nature. .
Free PMC article


Higher-order chromatin structure is emerging as an important regulator of gene expression. Although dynamic chromatin structures have been identified in the genome, the full scope of chromatin dynamics during mammalian development and lineage specification remains to be determined. By mapping genome-wide chromatin interactions in human embryonic stem (ES) cells and four human ES-cell-derived lineages, we uncover extensive chromatin reorganization during lineage specification. We observe that although self-associating chromatin domains are stable during differentiation, chromatin interactions both within and between domains change in a striking manner, altering 36% of active and inactive chromosomal compartments throughout the genome. By integrating chromatin interaction maps with haplotype-resolved epigenome and transcriptome data sets, we find widespread allelic bias in gene expression correlated with allele-biased chromatin states of linked promoters and distal enhancers. Our results therefore provide a global view of chromatin dynamics and a resource for studying long-range control of gene expression in distinct human cell lineages.


Figure 1
Figure 1. Dynamic reorganization of chromatin structure during differentiation of hESCs
a, First principle component (PC1) values and Hi-C interaction heat maps in H1 ES cells and H1-derived lineages. PC1 values are used to determine the A/B compartment status of a given region, where positive PC1 values represent “A” compartment regions (blue), and negative values represent “B” compartment regions (yellow). Dashed lines indicate TAD boundaries in ESCs. b, K-means clustering (k=20) of PC1 values for 40kb regions of the genome that change A/B compartment status in at least one lineage. c, K-means clustering of PC1 values surrounding TAD boundaries. d, Distribution of fold-change in gene expression for genes that change compartment status (“A to B” or “B to A”) or that remain the same (“stable”) upon differentiation. e, Genome browser of two genes where one (OTX2) shows concordant expression and PC1 values while a second (TMEM260) does not.
Figure 2
Figure 2. Domain-wide alterations in chromatin interaction frequency and chromatin state
a, Chromatin interaction heat maps in H1 lineages and IMR90 fibroblasts. Also shown are domain calls in ES cells and the directionality index (DI) in each lineage. b, Changes in interaction frequency between ES and MSC. Regions with higher interaction frequency in ES are shown in blue, while regions with higher interaction frequency in MSC are shown in yellow. TADs having a concerted increase or decrease in intra-domain interaction frequency are labeled yellow or blue, respectively, with the fraction of the domain showing increased or decreased interaction frequency listed. Domains that do not show a concerted change are shown in gray. c, Boxplots of Pearson correlations coefficients between interaction frequency changes and chromatin mark changes across TADs. d, Classification accuracy of the Random Forest model in predicting whether a bin increases or decreases in interaction frequency, tested on 10 randomly selected subsets of Hi-C data. Accuracy was also checked using actual data (blue), circularized permutation (green) and a random permutation (yellow) of the data. As expected, randomly permuting the data yields 50% accuracy. Accuracy was also assessed considering the top 30, 40, 50%, or all predictions based on vote frequency difference (error bars show the standard deviation of accuracies from the 10 randomly selected data subsets). e, Ranked chromatin features shown according to importance in classification (mean decrease of Gini index).
Figure 3
Figure 3. Haplotype-resolved chromatin organization in H1 lineages
a, Variants per megabase for all (green), phased (orange) and unphased variants (purple) along chromosome 1. The inset zooms in on a ∼1Mb region, where the presence of a variant at each base is indicated by a value of 1. b, Genome browser shots of allele specific chromatin features and strand-specific mRNA-sequencing. c, Genome browser shot of PC1 values along chromosome 2 for the p1 and p2 allele. d, Allele specific compartment A/B patterns and mRNA-seq surrounding the imprinted ZDBF2 gene. e, Boxplots of the difference between alleles of PC1 values. Regions with imprinted genes (p=0.003) and allelic genes (p=0.002) have more variable PC1 values (KS-test). f. Similar to e, but for regions with differential allelic chromatin activity (the number of allelic biased variants per 200kb bin). Regions in the top 0.1% of differential allelic activities (orange) show greater differences in PC1 values compared other regions. (p=1.6e-08 and p=0.0015, respectively, KS-test).
Figure 4
Figure 4. Allelic biases in gene expression in H1 lineages
a, Proportion of genes with detectable allelic expression with statistically significant allelic bias. b, Density plot of the absolute value of the fold change in expression (log2) between alleles. c, Heat map showing k-means (k=20) clustering of the allelic expression ratios (log2) at genes with constitutively testable expression. d, Genome browser shot of variable allelic expression of the PARP9 gene. e, Fraction of imprinted genes among allele-biased genes and other genes. (p=4.4e-5, Fisher exact test). f, Fraction of allele-biased genes that are known imprinted genes. g, Cumulative density plot of distances from variants to the nearest allele-specific gene. Allele specific variants are defined using histone acetylation, H3K9me3, H3K27me3, DNaseI HS, and H3K4me3 (p<2.2e-16, KS-test). h, Number of allele-biased genes showing consistent allele specific chromatin states in their promoter regions. Active variants are defined by H3K4me3, DNaseI HS, or histone acetylation. Inactive promoter variants are defined by DNA methylation and H3K9me3/27me3. i, Genome browser shot of mRNA-seq and chromatin features surrounding the TDG gene.
Figure 5
Figure 5. Allele biases at enhancers in H1 lineages
a, Enrichment of acetylation (top row), DHS (middle) and DNA-methylation (bottom) at enhancers defined as allelic by acetylation (left column), DHS (middle), or DNA-methylation (right). The active allele is in blue, inactive allele in red. b, The distance between allelic genes and enhancers as defined by allelic histone acetylation (purple) compared with randomly selected enhancers (grey). Random enhancers were selected to match the read coverage of allele-biased enhancers. c, Number of allele specific genes linked to concordantly biased allele specific enhancers. Genes linked by “long-range enhancers” are defined using Hi-C interaction frequencies, while “short-range enhancers” are defined as any enhancer less than 20kb from a genes transcription start site. d, Boxplots of the Pearson correlation coefficients between allelic gene-enhancer pairs defined by acetylation (left) or DNaseI (right). Gene-enhancer pairs are grouped into strongly interacting (top 30%), weakly interacting (bottom 30%), and intermediately interacting pairs (others) based on Hi-C interaction frequency (p-values using Welch's t-test). e, Normalized 4C-seq interaction frequencies near the HAPLN1 gene. The 4C-seq bait region is in an allele-biased enhancer near the 3′ end of the EDIL3 gene. Specific interactions called by the LOWESS regression model are shown in black as “bait interacting regions (BIRs).” f, Allele-biased expression of the two alleles of the HAPLN1 gene, histone acetylation levels at the nearby interacting allele-biased enhancer, and allele resolved 4C-seq data (4C-seq p-value from T-test, n=2 for p1 allele, n=2 for p2 allele).

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