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. 2016 Dec 15;167(7):1734-1749.e22.
doi: 10.1016/j.cell.2016.11.033.

Disease Model of GATA4 Mutation Reveals Transcription Factor Cooperativity in Human Cardiogenesis

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Free PMC article

Disease Model of GATA4 Mutation Reveals Transcription Factor Cooperativity in Human Cardiogenesis

Yen-Sin Ang et al. Cell. .
Free PMC article

Abstract

Mutation of highly conserved residues in transcription factors may affect protein-protein or protein-DNA interactions, leading to gene network dysregulation and human disease. Human mutations in GATA4, a cardiogenic transcription factor, cause cardiac septal defects and cardiomyopathy. Here, iPS-derived cardiomyocytes from subjects with a heterozygous GATA4-G296S missense mutation showed impaired contractility, calcium handling, and metabolic activity. In human cardiomyocytes, GATA4 broadly co-occupied cardiac enhancers with TBX5, another transcription factor that causes septal defects when mutated. The GATA4-G296S mutation disrupted TBX5 recruitment, particularly to cardiac super-enhancers, concomitant with dysregulation of genes related to the phenotypic abnormalities, including cardiac septation. Conversely, the GATA4-G296S mutation led to failure of GATA4 and TBX5-mediated repression at non-cardiac genes and enhanced open chromatin states at endothelial/endocardial promoters. These results reveal how disease-causing missense mutations can disrupt transcriptional cooperativity, leading to aberrant chromatin states and cellular dysfunction, including those related to morphogenetic defects.

Keywords: GATA4; TBX5; birth defect; cardiomyopathy; congenital heart defects; disease modeling; epigenetics; gene regulation; heart development; systems biology.

Figures

Figure 1
Figure 1. Pluripotent GATA4 iPS Cells and Differentiation to CMs
(A) Top, GATA4 pedigree. Numbers in circles (females) and squares (males) are de-identified patient labels. Bolded border denotes CRISPR-corrected iPS line. WT, wildtype familial control. G296S, red, GATA4 mutants. cmy. cardiomyopathy. ASD, atrial septal defect. VSD, ventricular septal defect. AVSD, atrioventricular septal defect. PS, pulmonary valve stenosis. Bottom, schematic of GATA4 protein domains. TAD, transactivation domain. ZF, zinc-finger domain. NLS, nuclear localization signal. (B) Still frames from transthoracic apical four-chamber view echocardiograms from a normal child and GATA4 G296S subject. Arrow indicates dense trabeculation in the right ventricle (RV). Right atrium, RA. Left ventricle, LV. Left atrium, LA. (C) CRISPR-correction strategy. (D) Sequence chromatograms show c.886G>A, G296S mutation in G296S 4, WT6 and CRISPR-corrected iWT4. (E) Calcium flux measurements of hiPS-derived CM show expected responses to indicated agonists. (F) Electron micrograph of representative iPS-derived CM. See also Figure S1.
Figure 2
Figure 2. GATA4 G296S CMs Have Impaired Cardiac Function
(A) FACS analysis of cTnT+ CMs from representative WT and G296S differentiation after lactate purification. (B) CMs micropatterned in arrays of single cells (top) and immunostained for αActinin or F-actin (bottom). (C) Contractile measurements on micro-patterns. % of single-CM responding to 1 Hz pacing in WT and G296S (left). Traction force microscopy measurements of force production as a function of cell movement of CMs responding to 1Hz pacing (right). All measurements were done in triplicate with CM generated independently from two patient lines. Data for patient 4 are shown. (D) Action potential measurements of WT and G296S CM. Overshoot potential (OSP) indicates highest membrane potential reached. Data shown are mean ± SEM from 2 WT and 2 G296S lines. *, p<0.05 (Mann-Whitney test). (E) Calcium flux measurement on microclusters. F/F0 (Max), peak amplitude relative to baseline fluorescence between action potentials. Data shown are mean ± SEM from 2 WT and 2 G296S lines. *, p<0.05 (t test). (F) Calcium flux measurement on patterned microtissues. CMs patterned on hydrogels of 10kPa-stiffness; 1-mm-long lines (left) and calcium flux measured as F/F0 (center). Rates of rise and fall (right) between action potentials. Data are mean ± SEM. *, p<0.05 (t test). (G) Percentage of CMs of individual sarcomeric classes observed by α-Actinin staining. Class IV represents the most disarrayed sarcomeric organizations. n= >150 CMs. (H) Mitochondria staining intensity of single-CM micropatterns (top). Mitotracker red intensity relative to cell area was quantified (bottom). Data shown are mean ± SEM from 2 G296S lines. **, p<0.005 (t test). (I) Seahorse measurements of glycolytic functions. Isogenic CM data are mean ± SEM. **, p<0.005, ***, p<0.0005 (t test). See also Figure S2.
Figure 3
Figure 3. Transcriptome Aberrations in G296S CPCs and CMs
(A) Heatmap shows hierarchical clustering of Spearman correlation scores for all differentiation time course samples based on RNA-seq profiles. Red, GATA4 mutants. Score of 1 (yellow) denotes perfect correlation. (B) Human fetal tissue prediction matrix for all differentiation time course samples based on RNA-seq profiles. Red, GATA4 mutants. Score of 1 (green) denotes highest similarity. (C). GSEA (top) and heatmap (bottom) shows downregulation of SHH signaling response genes in G296S CPCs. NES, normalized enrichment score. Values are row-scaled to show relative expression. Blue and red are low and high levels respectively. (D–F) Heatmap shows hierarchical clustering of differentially expressed genes in CPCs (D), D15-CMs (E) or D32-CMs (F). Values are row-scaled to show relative expression. Blue and red are low and high levels respectively. Representative down- (blue box) and up-regulated (red box) genes are listed. (D′–F′) GO analyses of down- (blue box) and up-regulated (red box) genes in CPCs (D′), D15-CMs (E′) or D32-CMs (F′). Significance shown as −Log10 Bonferroni p-value after multiple hypothesis correction. See also Figure S3.
Figure 4
Figure 4. Chromatin Accessibility Aberrations in G296S CPCs
(A) GSEA analyses of genesets for cardiac (top) and endothelial/endocardial (bottom) development. NES, normalized enrichment score. FDR, false discovery rate. Positive and negative NES indicate higher and lower expression in iWT respectively. (B) IGV browser tracks at chr14:23693015-24168059 show normalized ATAC-seq signal from WT (black) and G296S (red) matches normalized signal from ENCODE-DHS (blue) (grey regions). (C) Heatmap of normalized read counts from ENCODE DHSs, H3K4me3, H3K27me3 (D5CPC) around ATAC-seq loci identified in iWT CPCs. White and blue are low and high signal intensity, respectively. (D) Pie-chart shows gene-body, upstream, downstream distribution (top) and coding and non-coding gene distribution (bottom) of 14532 iWT ATAC-seq loci. (E) IGV browser tracks at TBX5 (top) and SOX17 (bottom) loci show decreased and increased (grey regions) ATAC-seq signal between WT (black) and G296S (red). Y-axis shows reads/million/25 bp. Blue track, normalized GATA4 ChIP-seq signal in WT1 CMs. (F) Metagenes plot of iWT (black) and G296S (red) normalized ATAC-seq signal ± 5 kb around the TSS of genesets for cardiac (top) and endothelial (bottom) development. (G) Known consensus motifs enriched in ATAC-seq loci up-regulated in G296S CPC. (H) GO analyses of down- (blue box) and up-regulated (red box) ATAC-seq loci after generic loci were filtered out using a fibroblast DHS dataset. Nearest gene to a peak was defined within a 100kb window. Significance shown as −Log10 Bonferroni p-value after multiple hypothesis correction. (I) FPKM values of select, differentially expressed NOTCH and NFAT target genes in iWT and G296S CPCs or CMs. Data are mean ± SEM. *, FDR<0.05.
Figure 5
Figure 5. TF Mis-Localizations in G296S CMs
(A) IGV browser tracks of indicated ChIP-seq signals at known GATA4 target loci (NPPA, NPPB) in WT CM. Grey boxes, significant peaks identified by MACS2. Y-axis shows reads/million/25 bp. (B) Metagenes plot of normalized ChIP-seq signals for indicated factors at 2428 G4T5 co-bound sites (±5kb) identified in WT CM. (C) Normalized GATA4 (left) or TBX5 (right) signal at sites that are G4T5 co-bound versus single TF bound. Boxplot and whiskers show mean, 25th and 75th percentile followed by 5th and 95th percentile. ****, p<0.00005, (Kolmogorov-Smirnov test). (D) Known consensus motifs enriched in 2428 G4T5 co-bound sites in WT CM. (E) Venn diagram shows changes in GATA4, TBX5 or G4T5 bound sites between WT and G296S CMs. Number of sites lost in WT (L), gained in G296S (E) and unchanged (U) are shown (top row). Legend for metagenes of relative (G296S/WT) ChIP-seq occupancy at sites that are L (blue line), U (green) or E (red) (top row, far-right). 2nd to 4th rows show relative changes in GATA4, TBX5, and H3K27ac occupancy at these L, U or E sites. (F) FPKM values of genes mapped ± 20 kb of 1186 G4T5L sites in iWT and G296S cells at 3 differentiated stages. Boxplot and whiskers show mean, 25th and 75th percentile followed by 5th and 95th percentile. *, p<0.05, **, p<0.005, ***, p<0.0005, (Wilcoxon signed-rank test). (G) Gap distances between GATA4 and TBX5 motifs within G4T5U vs.G4T5L sites on the same (blue) or different (red) DNA strand. Boxplot and whiskers show mean, 25th and 75th percentile followed by 5th and 95th percentile. *, p<0.05 (Fisher’s exact test). (H) Bar graph showing number of sites with ≥1 GATA4-TBX5 motif pairs (left) and number of motif pairs on same or different DNA strands (right) within G4T5U vs. G4T5L sites. *, p<0.05, ****, p<0.00005 (Fisher’s exact test). (I) GO analyses of 1186 G4T5L sites. Significance shown as −Log10 Bonferroni p-value after multiple hypothesis correction. (J) Heatmap shows hierarchical clustering of 414 putative G4T5 target genes in D15-CMs/D32-CMs and changes to GATA4 and TBX5 binding. RNA-seq expression is row-scaled to show relative expression (left). ChIP-seq shows relative (Log2FC) GATA4, TBX5 occupancy (right). One ChIP-seq peak with the largest fold difference was selected for each gene. Rows between GATA4 and TBX5 are approximately matched. Blue and red are low and high levels respectively. (K) Heatmap shows clustering of 82 endothelial genes and changes to GATA4 and TBX5 binding within endothelial TADs. RNA-seq (left) and ChIP-seq (right) show relative (Log2FC) gene expressions and GATA4, TBX5 occupancy (right). Blue and red are down- and up-regulation respectively. Rows between RNAseq and ChIPseq results are approximately matched. See also Figure S4 and S5.
Figure 6
Figure 6. Aberrant Cardiac SE Regulation in G296S CMs
(A) Distribution of MED1 ChIP-seq signal across 5,040 putative enhancers in WT CM. 213 SEs show highest MED1 intensity. Representative genes within 20 kb are labeled. (B) IGV browser tracks of ChIP-seq signals at MYH6 and MYH7 loci show 47 kb SE element. A 1.3 kb STAU2 TE also shown. Y-axis shows reads/million/25 bp. (C) Enhancer length (left) and nearest (20 kb) gene expression (right) of TEs vs. SEs. Boxplot and whiskers show mean, 25th and 75th percentile followed by 5th and 95th percentile. ****, p<0.00005 (t test). (D) Metagenes plot of normalized ChIP-seq signals at 4827 TE and 213 SE identified in WT CMs. (E) Known consensus motifs enriched at constituent enhancers within SE elements in WT CM. (F) GO analyses of 213 SE elements. Significance shown as −Log10 Bonferroni p-value after multiple hypothesis correction. (G) Distribution of MED1 ChIP-seq signal in G296S CMs. 172 SEs show highest MED1 intensity. Representative genes within 20 kb are labeled. (H) Venn diagram (top) shows changes in MED1-bound SE elements between WT (black circle) and G296S (red). Number of sites lost in WT (L), gained in G296S (E) or unchanged (U) are shown. (I) Metagenes plot of normalized GATA4 and TBX5 ChIP-seq signal within SE that are L, U or E in WT (black line) and G296S (red) CM. (J) Example genes within 20 kb of the SE elements that are L, U or E in G296S CMs. (K) FPKM values of genes mapped ± 20 kb around SEs in iWT and G296S cells at 3 differentiated stages. Boxplot and whiskers show mean, 25th and 75th percentile followed by 5th and 95th percentile. *, p<0.05, ***, p<0.0005, ****, p<0.00005 (Wilcoxon signed-rank test). (L) Sub-network extracted from global network diagram analyzed by TDA shows enrichment for genes regulated by SE regions and co-bound by GATA4-TBX5. Red and blue colors represent high and low enrichment respectively. Blue colors in GATA4-siRNA expression network show down-regulation of this SE-regulated geneset upon GATA4 knockdown. See also Figure S6 and S7.
Figure 7
Figure 7. GATA4-TBX5 GRN Revealed Hubs Centered on PI3K Signaling
(A) GATA4-controlled GRN. Nodes are genes that are differentially expressed or G4T5 co-bound or have MED-1 SE elements. Edges are physical or functional interactions between nodes as extracted from STRING. Yellow, top-20 hubs with the most direct neighbors. Hubs are grouped into 5 subnetworks (pink circle). (B) Sub-network plot of extracted top-20 hubs named by gene symbol. Number of edges from entire GRN shown beside each node. Blue or red are gene expressions down- or up-regulated, respectively. Diamond, square, or circle represents genes that gained, lost or were unchanged for G4T5 binding. Bolded border represents genes with SE elements. (C) Relative change in force generation between iWT (black) and G296S (red) CMs after inhibition (circle) or activation (triangle) of PI3K signaling. Traction force microscopy (TFM) measurements of CMs responding accurately to 1 Hz pacing. Data are mean ± SEM, *, p<0.05, **, p<0.005, ***, p<0.0005 (Mann-Whitney test). (D) Beat rate measurements between iWT (black) and G296S (red) CMs after inhibition (circle) or activation (triangle) of PI3K signaling. TFM measurements of CMs responding accurately to 1Hz pacing. Data are mean ± SEM, *, p<0.05, **, p<0.005, ***, p<0.0005 (Mann-Whitney test). (E) Proposed model. Top, cardiac gene loci in WT are open and permissive to G4T5 binding at MED1-bound SE elements, which activates transcription; G4T5 and HDAC2 repress aberrant endothelial gene transcription. Bottom, transcriptional and epigenetic consequences of GATA4 G296S. Cardiac gene loci have reduced open chromatin and TBX5 binding to SE elements which reduces transcription; aberrantly open chromatin is depleted of GATA4-HDAC2 but enriched for TBX5, along with motifs for ETS factors resulting in failure to silence endothelial gene transcription and other sites involved in septal development not depicted. See also Figure S7.

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