Broad H3K4me3 is associated with increased transcription elongation and enhancer activity at tumor suppressor genes

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1 Broad H3K4me3 is associated with increased transcription elongation and enhancer activity at tumor suppressor genes Kaifu Chen 1,2,3,4,5,10, Zhong Chen 6,10, Dayong Wu 6, Lili Zhang 7, Xueqiu Lin 1,2,8, Jianzhong Su 1,2, Benjamin Rodriguez 1,2, Yuanxin Xi 1,2, Zheng Xia 1,2, Xi Chen 2, Xiaobing Shi 9, Qianben Wang 6,11, Wei Li 1,2,11 1 Division of Biostatistics, Dan L. Duncan Cancer Center and 2 Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA. 3 Institute for Academic Medicine, and 4 Center for Cardiovascular Regeneration, Department of Cardiovascular Sciences, The Methodist Hospital Research Institute, Houston, TX 77030, USA. 5 Weill Cornell Medical College, Cornell University, New York, NY 10065, USA. 6 Department of Molecular Virology, Immunology and Medical Genetics and the Comprehensive Cancer Center, The Ohio State University College of Medicine, Columbus, OH, USA. 7 Ocular Surface Center, Cullen Eye Institute, Department of Ophthalmology, Baylor College of Medicine, Houston, TX Department of Bioinformatics, School of Life sciences and Technology, Tongji University, Shanghai 20092, China. 9 Department of Molecular Carcinogenesis and Center for Cancer Epigenetics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. 10 These authors contributed equally to this work. 11 These authors jointly directed this work. Correspondence should be addressed to Q.W. (qianben.wang@osumc.edu) or W.L. (WL1@bcm.edu). 1

2 Supplementary Figure 1. Average density plots of H3K4me3 ChIP-Seq signal and genomic input background at genes associated with broad, sharp, or randomly selected H3K4me3 peaks. The total numbers of H3K4me3 and input reads mapped to the whole genome were normalized to be the same. The right panel is a zoom out view of the left panel. The three plots for input signals closely overlap with each other. 2

3 Supplementary Figure 2. Tumor suppressors (left) and oncogenes (right) are equally enriched in the KEGG Pathways In Cancer (hsa05200). As a control, they are not enriched in housekeeping genes. Enrichment P value was calculated based on Fisher's exact test. 3

4 Supplementary Figure 3. Boxplot to indicate H3K4me3 width at tumor suppressors, oncogenes, or other genes in each single pathway (left 2 panels) or a pool of 186 pathways (right panel). Pathway genes were downloaded from the GSEA website ( Number of genes is indicated on the top of each boxplot. 4

5 Supplementary Figure 4. Boxplot of H3K4me3 peak integrated intensity (top left), associated gene expression (top right), peak height, and peak width. Subsets of broad and sharp peaks with similar integrated intensity were used for the plots. 5

6 Supplementary Figure 5. Annotated TSS (a) and CAGE read density (b) at genes associated with broad, sharp and random H3K4me3 peaks. All genes were scaled to 40 kb long. The right panel is a zoom out view of the left panel. A Wilcoxon test P value for gene body CAGE read density between genes associated with broad and sharp H3K4me3 is indicated in the right panel of (b). CAGE reads density is normalized to gene expression level determined from RNA-Seq data. 6

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8 Supplementary Figure 6. Most promoter epigenetic marks coincide with broad H3K4me3 in human CD4+ T cells. Average density of epigenetic marks at genes associated with broad, sharp and random H3K4me3 peaks. All genes were scaled to 40 kb long. 8

9 Supplementary Figure 7. Some chromatin marks show weak and complicated enrichment patterns. (a) Heatmaps for average density of each epigenetic mark on genes associated with broad, sharp and random H3K4me3 peaks. (b) Average density plot of each epigenetic mark. 9

10 Supplementary Figure 8. Spearman correlation coefficients of ChIP-Seq read densities between H3K4me3 and other chromatin marks at genes associated with broad H3K4me3. 10

11 Supplementary Figure 9. Pol II pausing index plotted against H3K4me3 width in 12 ENCODE cell types that has ChIP-Seq data for both H3K4me3 and Pol II. Cell name and Spearman correlation coefficient was indicated on top of each plot. 11

12 Supplementary Figure 10. Sharp and random control H3K4me3 peaks have little overlap with enhancers in human CD4+ T cells. (a) Venn diagrams showing the overlap between genes associated with super enhancers and genes associated with sharp (left) or control (right) H3K4me3 peaks. (b) The distribution of H3K4me3 peaks (left), typical enhancers (middle), and super enhancers (right) flanking TSS at genes associated with sharp and control H3K4me3 peaks. 12

13 Supplementary Figure 11. Enrichment levels of housekeeping genes, oncogenes, and tumor suppressors (columns) in genes associated with broad H3K4me3 only, both broad H3K4me3 and super enhancers, and super enhancers only. 61 cell types or tissues (rows) that has both H3K4me3 and super enhancer data were plotted. Color scale indicates enrichment level calculated by Fisher's Exact Test. 13

14 Supplementary Figure 12. Broad H3K4me3 at tumor suppressors is conserved across normal samples in the Roadmap Epigenomics Project. (a) Heatmap for H3K4me3 peak widths of 8,143 promoters (rows) across 153 Roadmap normals samples (columns). Promoters were further divided into 9 groups (A-I) based on the conservation level of H3K4me3 peak width (% samples with H3K4me3 peak longer than 4kb) from high to low. (b) The enrichment levels of 9 promoter groups, as indicated in (a), in tumor suppressors, oncogenes, and housekeeping genes. Enrichment P value was calculated based on Fisher's exact test. (c) Venn diagram for the comparison between 500 most conserved broad H3K4me3 peaks defined from the ENCODE and Roadmap projects. 14

15 Supplementary Figure 13. Widespread shortening of broad H3K4me3. All genes with average H3K4me3 width wider than 4 kb in ENCODE normal or cancer samples were analyzed. (a) Numbers of broad H3K4me3 peaks that are shortened, lengthened, or stable between 63 cancer and 105 normal samples or through 1,000 mock comparisons. (b) Enrichment levels of the 3 gene groups from (a) in housekeeping genes, oncogenes, tumor suppressors, and KEGG pathways in cancer. Heatmap of the H3K4me3 peak widths (c) or expression levels (d) at each gene (row) in each sample (column). The same 3 groups of genes with broad H3K4me3 peaks shortening, lengthening, or stable as indicated in (a) were plotted. Genes were ranked in the same order in the two heatmaps. A boxplot was plotted at the right side of each heatmap to show quantitative difference between cancer and normal samples. * P<1x10-15 by Wilcoxon test, NS represent P>

16 Supplementary Figure 14. Shortening of broad H3K4me3 peaks in a T cell cancer model. (a) Heatmaps for H3K4me3 density flanking TSS in CD4+ T cells (left 2 panels) and the Jurkat (right 2 panels) cells. In each panel, each row represents a 10kb region flanking TSS. (b) Gene expression levels in CD4+ T cells and Jurkat cells. Genes were ranked as in (a). (c) Pol II pausing index at genes with broad H3K4me3 shortening in Jurkat cell relative to normal T cell (top) or all other genes (bottom). Wilcoxon test P value for difference in Pausing index between the two cell types was indicated on top of boxplot. (d) Snapshots of H3K4me3 shortening in two tumor suppressors KLF6 (top) and CYLD (bottom). 16

17 Supplementary Figure 15. Shortening of broad H3K4me3 peaks in a breast cancer model. (a) Heatmaps for H3K4me3 density flanking TSS in HMEC normal breast epithelial cells (left 2 panels) and MCF7 cancer cells (right two panels). In each panel, each row represents a 10kb region flanking TSS. (b) Gene expression levels in HMEC and MCF7 cells. Genes were ranked as in (a). (c) Snapshots of H3K4me3 shortening in two tumor suppressors KLF6 (top) and PTPN14 (bottom). 17

18 Supplementary Figure 16. Shortening of broad H3K4me3 peaks in liver tumors. (a) Enrichment P values (y-axis) of tumor suppressors in different promoter groups (symbols along the curves) ranked by H3k4me3 peaks from wide to narrow. Each promoter group contains 500 genes. The left most promoter group contains the broad H3K4me3 peaks. Enrichment P value was calculated using Fisher's exact test. (b) Snapshots of broad H3K4me3 shortening in two tumor suppressors FBP1 (top) and MAOB (bottom). (c) Heatmaps for H3K4me3 density flanking TSS in liver normal tissues (left 2 panels) and liver tumors (right 2 panels). In each panel, each row represents a 10kb region flanking TSS. (d) Gene expression levels in liver normal tissues and liver tumors. Genes were ranked as in (c). 18

19 Supplementary Figure 17. The pipeline for defining tumor suppressor candidate in a given tissue type. 19

20 Supplementary Figure 18. Functional characterization of putative novel tumor suppressors defined by conserved broad H3K4me3. (a, c) A549 cells were seeded at 5x10 4 cells/well in 6-well plates. sirnas targeting putative tumor suppressor genes or randomly selected genes with comparable expression were transfected. After 4 days, the numbers of living cells were measured by direct cell counting. P values for cell number difference were calculated based one tail T test compared to sicontrol, ** P< 0.01, * P<0.05. P value for expression difference was calculated based Wilcoxon test. (b) Candidate tumor suppressors with conserved broad H3K4me3 and 10 randomly selected genes with sharp H3K4me3 have comparable gene expression. 20

21 Supplementary Figure 19. Nucleosomes positions are fuzzier in broad than in sharp H3K4me3 peaks. H3K4me3 ChIP-Seq was conducted following MNase digestion of normal lung (top 2 panels) and normal liver (bottom 2 panels) tissues. Average reads density was then calculated around TSSs associated with broad (red) or sharp (blue) H3K4me3 peaks. 21

22 Supplementary Figure 20. The Spearman method, but not the Pearson method, indicates significant correlation between H3K4me3 width and gene expression level. A very recent report indicates that broad H3K4me3 domains are linked to cell identity and function in normal cells 1. The authors calculated Pearson correlation coefficient between H3K4me3 breadth quantile (ranging from 0% to 100%) and gene expression FPKM value (ranging from 10-3 to 10 4 ), but observed no correlation based on this calculation. Using 22

23 the same method, we successfully reproduced similar results from the same ChIP-seq raw data (a and c). However, Pearson correlation is a method for measuring linear correlation and thus is not appropriate in this situation, since the H3K4me3 breadth quantile and gene expression FPKM value are not in a strong linear relationship (a and c). In contrast, we used the appropriate non-parametric rank-based Spearman correlation coefficient for the relationship analysis between H3K4me3 breadth and gene expression. Using Spearman method on the same ChIP-seq raw data, we surprisingly observed clear correlation between H3K4me3 breadth and gene expression (b and d). To further elucidate that the Pearson method cannot detect nonlinear correlation, we performed a simulation study, in which we know the ground truth. We used both Pearson and Spearman methods to check the relationship between a vector A=(2 1, 2 2, 2 3,..., ) and its rank transformation B = (1, 2, 3,..., 1000). Since A and B are essentially the same data, their correlation should be calculated as 1 by the correct method. As expected, Spearman method gave coefficient of 1, whereas the Pearson method gave coefficient of 0 between A and B (e and f). Together, we conclude that H3K4me3 breadth has good correlation with gene expression and the lack of correlation in the earlier report is largely due to the inappropriate statistical method. 23

24 Supplementary Figure 21. H3K4me3 ChIP-Seq peak height plotted relative to peak width in CD4+ cell. Each panel is plotted using peaks called based on a specific merging distance cutoff, as indicated on top. 24

25 Supplementary Figure 22. Tumor suppressor enrichment P value for each H3K4me3 peak group (dot in each panel). In each panel, genes bearing H3K4me3 peak in promoter were ranked based on H3K4me3 peak width and divided in to groups each contain 500 genes. Each panel is plotted using peaks called based on a specific extending distance, as indicated on top. Enrichment P value was calculated based on Fisher's exact test. 25

26 Supplementary Figure 23. Peak height plotted relative to peak width based on simulated H3K4me3 ChIP-Seq reads. Combing three negative binomial models (top left) allows us to reproduce the pattern observed in real H3K4me3 ChIP-Seq data, in which the highest peaks have no overlap with widest peaks. However, in data simulated based on each single model (top right, bottom left, and bottom right), there are considerable overlap between highest and widest peaks. Parameters in each single negative binomial model were indicated on top of associated panel. 26

27 Supplementary Figure 24. Percentage of tumor suppressors in different number of top genes ranked based on H3K4me3 breadth. Supplementary Table 1. A list of public data sets used in this study. Supplementary Table 2. Number of genes assigned with broad H3K4me3 in each sample. Supplementary Table 3. H3K4me3 width at each gene in each sample from ENCODE and Roadmap Epigenome. Supplementary Table 4. Broad H3K4me3 peaks at tumor suppressors that are shortened, lengthened, or stable between 105 normal and 63 cancer samples. Supplementary References 1. Benayoun, B.A. et al. H3K4me3 breadth is linked to cell identity and transcriptional consistency. Cell 158, (2014). 27