ZBTB33 binds unmethylated regions of the genome associated with actively expressed genes
© Blattler et al.; licensee BioMed Central Ltd. 2013
Received: 18 March 2013
Accepted: 16 April 2013
Published: 21 May 2013
DNA methylation and repressive histone modifications cooperate to silence promoters. One mechanism by which regions of methylated DNA could acquire repressive histone modifications is via methyl DNA-binding transcription factors. The zinc finger protein ZBTB33 (also known as Kaiso) has been shown in vitro to bind preferentially to methylated DNA and to interact with the SMRT/NCoR histone deacetylase complexes. We have performed bioinformatic analyses of Kaiso ChIP-seq and DNA methylation datasets to test a model whereby binding of Kaiso to methylated CpGs leads to loss of acetylated histones at target promoters.
Our results suggest that, contrary to expectations, Kaiso does not bind to methylated DNA in vivo but instead binds to highly active promoters that are marked with high levels of acetylated histones. In addition, our studies suggest that DNA methylation and nucleosome occupancy patterns restrict access of Kaiso to potential binding sites and influence cell type-specific binding.
We propose a new model for the genome-wide binding and function of Kaiso whereby Kaiso binds to unmethylated regulatory regions and contributes to the active state of target promoters.
KeywordsDNA methylation Zinc finger proteins Histone modifications Transcription factor binding Epigenetics Transcriptional regulation
Genes are epigenetically regulated by a combination of histone modifications and methylation of CpG dinucleotides near their promoters [1, 2]. Promoters that have high levels of DNA methylation always show low activity whereas the relationship of histone methylation and promoter activity differs depending on exactly which residue is methylated. For example, trimethylation of lysine 4 of histone H3 (H3K4me3) correlates with high promoter activity whereas trimethylation of lysine 9 or lysine 27 of histone H3 (H3K9me3 or H3K27me3) correlates with low promoter activity. Recent studies have demonstrated distinct spatial relationships of these two repressive histone modifications with regions of methylated DNA [3, 4]. These analyses entailed chromatin immunoprecipitation using antibodies that recognize specific histone modifications followed by bisulfite sequencing of the ChIP DNA (BisChIP-seq). One study showed that H3K27me3 can sometimes be associated with methylated promoters but that the H3K27me3-marked regions are repressed independently of the level of DNA methylation . A similar study by Brinkman et al.  found that H3K27me3 and DNA methylation are compatible except at CpG-rich promoters where the two marks are mutually exclusive, supporting a previous study by Komashko et al. . The studies of Komashko et al. also showed a very low overlap of the sets of promoters having high levels of H3K9me3 versus high levels of DNA methylation. From their BisChIP-seq results, Brinkman et al. suggest that H3K9me3 has a high degree of overlap with regions of methylated DNA. However, the majority of H3K9me3 sites in the genome are not at promoter regions and, unfortunately, their analyses did not distinguish the DNA methylation status of promoter versus non-promoter H3K9me3 sites. In summary, although the spatial relationship of these repressive histone methylations has been described, it is not yet clear if DNA methylation and H3K27me3 or H3K9me3 cooperate to repress promoter regions.
A model has been proposed in which Kaiso binds to methylated DNA in a promoter region, recruits components of the NCoR histone deacetylase complex, and represses transcription (Figure 1B). This model is based in part on analysis of the MTA2 promoter. Yoon et al.  showed that Kaiso can bind in vitro to a methylated version of the sequence GGCGCGCGAGTCTTTGGGGCGCG, which is found within the CpG island promoter of the MTA2 gene. Using primers specific for methylated DNA, they also showed that this sequence is methylated in HeLa cells and they performed ChIP experiments to show that Kaiso binds this site before, but not after, cells are treated with 5aza-dC, a drug which reduces DNA methylation levels. They show that Kaiso interacts with the NCoR complex and demonstrate that Kaiso fused to the GAL4 DNA binding domain can repress transcription of a luciferase reporter containing a GAL4 binding site. Finally, they show that treating cells with siRNAs to Kaiso, 5aza-dC or the HDAC inhibitor TSA can increase MTA2 RNA. Taken together, they proposed a model in which Kaiso binds to the methylated MTA2 promoter and represses transcription by reducing levels of acetylated histones near the start site. We wished to test this model on a genome-wide scale and therefore have analyzed Kaiso binding in normal and cancer human cell lines, performed motif analyses of the in vivo binding sites, and investigated the relationship between Kaiso binding, DNA methylation, modified histones, and gene expression levels. Our results suggest that, in contrast to in vitro studies, in cells Kaiso binds to highly active, unmethylated promoters.
Identification and characterization of Kaiso-binding sites
Sequencing and peak metrics for ENCODE Kaiso ChIP-seq datasets
Unique reads, Rep1
Sole-Search peaks, Rep1
Median peak tag height Rep1
Unique reads, Rep2
Sole-Search peaks, Rep2
Median peak tag height, Rep2
40% overlap (reciprocal overlap)
Unique reads, merged Reps
Sole-Search peaks, merged Reps
Median peak tag height, merged
Median peak tag height
Testing a model of Kaiso-mediated transcriptional repression
As described above, Kaiso has been shown to bind to methylated DNA and has been suggested to function as a transcriptional repressor via recruitment of HDACs via interaction with the NCoR and SMRT complexes [8, 10, 15–18]. If true, this could provide a mechanistic explanation for a link between promoter methylation and transcriptional repression. However, these studies were performed in vitro and/or focused on small sets of genes. To test this model on a genome-wide scale, we have examined the location of Kaiso binding sites asking the following questions: 1) Are Kaiso binding sites located in promoter regions? 2) What is the epigenetic status of the regulatory regions bound by Kaiso? and 3) what is the DNA methylation status of Kaiso binding sites?
Motif analysis of Kaiso binding sites
KaisoHC GM12878 (1,648 sites)
KaisoHC+Pol2HC GM12878 (1,270 sites)
KaisoHC-No Pol2HC GM12878 (378 sites)
KaisoHC K562 (3,082 sites)
Characterization of Kaiso binding sites in cancer cells
The analyses of Kaiso binding sites described above were performed using GM12878 cells, which is an EBV immortalized normal lymphoblastoid cell line. Because Kaiso binds to promoter regions, it is possible that the lack of correlation between Kaiso binding and DNA methylation is simply due to the fact that most CpG island promoters are hypomethylated in normal cells. In contrast, in cancer cells although the majority of the genome is hypomethylated, many promoters become hypermethylated. Thus, it is possible that there are more methylated TCTCGCGAGA motifs in cancer cells, providing a platform for Kaiso to bind to methylated DNA. To determine if Kaiso binds to methylated DNA in a cancer cell, we analyzed Kaiso binding sites in the myeloid leukemia cell line, K562. Kaiso was determined to be similarly expressed in GM12878 and K562 by Western blot and by RNA-seq data (see Methods). We first identified a set of Kaiso binding sites that were present in both replicates of the K562 Kaiso ChIP-seq datasets. The number of these sites was much higher than the number of GM12878 Kaiso binding sites and therefore we performed further inspection of the K562 peaks. We noted that a much lower percentage of the K562 Kaiso peaks contained the Kaiso motif than did the GM12878 peaks (12% versus 43%), suggesting that the K562 peak set may contain a large number of false positive peaks. K562 cells are cancer cells and have a number of highly-amplified genomic regions. Although our peak-calling program has features that remove many of the false positive peaks due to genomic amplifications [11, 12], we observed that a large number of peaks from K562 cells were in the amplified regions. We removed these amplified regions from our analyses and the peak set was reduced to approximately 3,082 peaks, approximately 30% of which contained a TCTCGCGAGA motif (Additional file 5). This adjusted peak set was used for all downstream analyses as the high-confidence Kaiso peaks in K562. Additional file 6 contains the genomic coordinates of the amplified regions in K562 and the Kaiso peaks before and after removal of these amplified regions.
To determine if Kaiso binds to methylated promoters in K562 cells, we selected the set of Kaiso peaks that contained a CGCG motif and determined the methylation percentage of each of the CpG dinucleotides. In this case, we used RRBS data for DNA methylation analysis because WGBS data is not available for K562 cells. The genomic coverage is lower in the K562 data than in the GM12878 data; the number of CpGs with 3× coverage or greater in the K562 RRBS dataset is 1 million, compared to 45.6 million in the GM12878 methylation data for which we could use a combination of WGBS and RRBS. Therefore, with a 3× coverage cut-off, we could only analyze 1,069 CGCG motifs in the K562 Kaiso peaks. Of these, 28 peaks contained medium levels of DNA methylation and only two peaks contained high levels of methylation (Figure 5C); a snapshot of the chromosomal region containing the highest methylated CGCG motif (63% methylated) is shown in Additional file 7.
Cell type-specific binding of Kaiso
The purpose of this study was to test the previously proposed model that Kaiso functions as a DNA methylation-dependent transcriptional repressor that causes local depletion of acetylated histones near its binding sites. In our studies, we bioinformatically analyzed genome-wide binding of Kaiso in normal and cancer cells, examined the epigenetic profiles of Kaiso-bound promoters, and determined the percentage of DNA methylation of CpGs bound by Kaiso. Although the analyses presented in this study focused on only two cell lines, we have also examined the relationship between Kaiso binding sites, Pol2, and histone modifications in HCT116, A549, and SK-N-SH cells (see Table 1 for the number of high- confidence Kaiso peaks analyzed in each dataset). In each cell type, Kaiso is associated with active promoters (unpublished data). In addition, we performed whole genome bisulfite sequencing of HCT116 and found that Kaiso binding sites are not methylated; specifically, out of 3,051 CGCG motifs within the high-confidence HCT116 Kaiso-binding sites, 3,036 (99.5%) had methylation levels less than 20% (unpublished data). Thus, results from all tested cell lines are similar but do not support the previously proposed model. Specifically, we find that Kaiso does not bind to methylated DNA and that it is associated with highly acetylated, actively transcribed promoters. Our results are consistent with those presented in Factorbook , an online repository that hosts analyses of ENCODE transcription factor ChIP-seq data. However, due to the large scale of that project, individualized analyses were not performed for each factor. For example, the Factorbook analysis of motifs found in Kaiso binding sites included only the top 500 peaks and did not specifically search for the non-methylated motif to which Kaiso has been shown to bind in vitro. Another difference is that Factorbook uses the ENCODE IDR peak sets which, as we describe above, do not represent the same peaks as our high confidence peaks that are found in both ChIP-seq replicates for a given cell type. In addition, our studies included a thorough analysis of cell type-specific binding patterns, motifs, and nucleosome occupancy of Kaiso sites. Finally, Factorbook did not include an analysis of DNA methylation, which is the central theme of our study.
Several different groups have used in vitro gel shift assays to demonstrate that Kaiso binds to the motif TCTCGCGAGA when both CpGs in the motif are methylated [7–10, 26]. In addition, Bartels et al. performed an unbiased in vitro screen for methyl DNA-binding proteins and identified Kaiso using mass spectrometry analysis of the proteins captured in the screen . Also, a recent study has solved the structure of Kaiso bound to methylated DNA . Clearly, Kaiso does bind to methylated DNA in vitro. However, the vast majority of in vivo Kaiso binding sites have very low levels of DNA methylation. Visual inspection of the rare sites that have high DNA methylation revealed that Kaiso has the ability to bind methylated DNA in vivo, but that the Kaiso peaks at those sites are among the lowest enriched binding sites. In fact, a plot of peak score versus percent DNA methylation clearly shows that the strongest Kaiso sites have very low levels of DNA methylation (Additional file 9). These data do not support the in vitro studies that indicate that Kaiso prefers to bind to the TCTCGCGAGA motif when both CpG dinucleotides are fully methylated. However, we note that we used Bowtie to align the sequenced tags to the human genome and used Sole-Search [11, 12] to call peaks. It was possible that this combination of alignment and peak-calling resulted in a loss of the set of highly methylated Kaiso binding sites. To ensure that our method of alignment and peak identification had not biased our results, we reanalyzed the Kaiso ChIP-seq data using LONUT, a new alignment tool which takes into account both unique and non-unique tags (manuscript submitted) and used BELT  to call peaks. Also, to eliminate the possibility that we are missing a set of Kaiso peaks that are highly methylated, but are not as robust or not as reproducible as the peaks called using Sole-Search, we relaxed our stringency and called peaks on the merged Kaiso ChIP-seq datasets for each cell type (thus not requiring that each peak be identified in both replicates). We identified many thousands of Kaiso binding sites in GM12878 and K562 cells, most of which were very small and found in only one of the two replicates. We found that most of the Kaiso binding sites identified using this method again had low levels of DNA methylation (Additional file 10). In fact, only 12 of the 8,069 Kaiso peaks identified by LONUT in GM12878 had greater than 50% DNA methylation. Visual inspection of these 12 sites revealed two peaks on the X chromosome (red arrows, Additional file 10A) within the CpG island promoters of the PHF8 and PRDX4 genes (the other 10 sites had low Kaiso peaks and/or were not reproducible between the two biological replicates). A central CGCG motif was found to be 73% methylated in PHF8 and 55% methylated in PRDX4. However, upon further characterization of these promoters, they were discovered to be expressed, and have high levels of active histone modifications surrounding the promoter (Additional file 10B, PHF8 shown). For both promoters, the methylated CGCG motif identified was discovered to be just outside the borders of the Sole-Search-called peaks and therefore was not analyzed in Figure 5. In general, the combination of LONUT and BELT results in the assignment of larger genomic regions to peaks than does the combination of Bowtie and Sole-Search; as a result the new analysis included some new CGCG motifs in the final dataset. However, these CGCG motifs were not highly methylated and the ones that had modest methylation were on the edges of the peak and unlikely to contribute to Kaiso binding.
Binding of transcription factors in the context of chromatin is influenced by many factors. For example, recent ChIP-seq analyses have revealed that not all binding sites contain the ‘expected’ motif that was derived from in vitro binding studies [30, 31]. In addition, the epigenetic profile of a promoter region can influence binding, with repressive histone marks and nucleosome occupancy limiting access of transcription factors to their binding sites [32–34]. Taken in this context, we believe that although Kaiso may ‘prefer’ to bind to methylated DNA, this is not an option in the context of chromatin. Under conditions in which the CpGs in a promoter are highly methylated, the entire promoter region is often densely wrapped around nucleosomes and in a repressive heterochromatic state. The absence of a nucleosome-free region prevents access of transcription factors to the promoter region and hence prevents access of Kaiso to its methylated motif. Being denied access to the preferred methylated motif, Kaiso instead binds to the same motif in its unmethylated state. It is interesting to note that this disconnect between in vitro and in vivo binding to a methylated motif has been seen by others. Bartels et al. identified RBP-J as a strong binder of methylated DNA in vitro. However, they cannot find evidence that this factor binds to methylated DNA in vivo . Other zinc finger proteins have been implicated in binding methylated DNA. Quenneville et al.  showed that a portion of ZFP57 consisting of two zinc fingers can bind to a methylated TGCCGC motif in vitro and they used bisulfite analysis of ChIP DNA to show that ZFP57 can bind to the methylated allele of three imprinted mouse genes. However, the DNA methylation status of the other 11,000 ZFP57 ChIP-seq peaks was not analyzed and therefore the significance of these three sites in the context of the biological function of ZFP57 is not clear. Spruijt et al.  used quantitative mass spectrometry to identify proteins that bind to methylated DNA in vitro, identifying the zinc finger factors KLF2, KLF4, and KLF5 as methyl DNA binding proteins. They report that approximately 18% of the KLF4- binding sites in mouse ES cells show high levels of DNA methylation when using a 100 bp window centered on the peak. However, when the analysis is restricted to the binding motif, the DNA methylation levels dropped significantly. Therefore, it is not clear if KLF4 actually binds to methylated DNA in the context of chromatin.
While we were able to identify a small number of methylated promoters to which Kaiso binds, these genes are enriched for active histone modifications and are expressed. The CpG methylated sites were found to be located away from the center of the Kaiso peak and they do not contain the full TCTCGCGAGA motif. Therefore, it is unclear as to whether these sites are relevant to Kaiso binding or to promoter activity. At this point, we cannot rule out that there are methylated TCTCGCGAGA motifs bound by Kaiso in certain cells under certain growth conditions. As noted above, a previous study has reported that Kaiso binds to a methylated MTA2 promoter region in HeLa cells . Unfortunately, we do not have Kaiso ChIP data for HeLa cells and there is no available DNA methylation data from HeLa cells for the precise region of the MTA2 promoter that corresponds to the reported Kaiso binding site. However, in HeLa cells the MTA2 promoter has marks of open chromatin and is bound by Pol2; furthermore, the MTA2 transcript is expressed in HeLa cells (Additional file 11). Therefore, if Kaiso does bind at the MTA2 promoter in HeLa cells, it does not silence transcription. We have examined the relationship of Kaiso binding and MTA2 expression in six other cell types. We find that Kaiso binds to the MTA2 promoter in K562, A459, and SK-N-SH cells, and in all of these cell lines the MTA2 promoter has acetylated histones. Another study  suggested that Kaiso binds to and represses the CDKN2A, HIC1, and MGMT promoters in a methylation-dependent manner in HCT116 cells. However, ChIP-seq data indicates that in HCT116 cells Kaiso does not bind within the genomic regions of these promoters. A recent study  claims that Kaiso binds the cyclin D1 CpG island promoter via a ‘KBS motif’, TCCTGCNA, 69 bp upstream of the transcription start site and functions to repress expression of the cyclin D1 gene in HCT116 and MCF7 cells. They show that the methylation of three adjacent CpG dinucleotides helps to stabilize Kaiso’s interaction with sequences containing the cyclin D1 promoter using in vitro assays, and that Kaiso binds the region by ChIP. However, ENCODE ChIP-seq data from HCT116 shows that Kaiso is not enriched at the cyclin D1 promoter and RRBS data shows that the region encompassing the KBS motif 69 bp upstream of the transcription start site is unmethylated in both HCT116 and MCF7. The gene is also bound by Pol2 and acetylated histones, and is expressed in both cell lines. Thus, it is hard to find a clear relationship between Kaiso binding and repression of any gene in any cell line. In fact, by comparison of the expression levels of the genes bound by Kaiso in both GM12878 and K562 versus the expression of the genes whose promoters are bound by Kaiso in a cell type-specific manner, we find a positive correlation between Kaiso- binding and gene expression (Figure 12).
Although many promoters are bound by Kaiso in multiple cell types, we did observe cell type-specific binding. While we do not yet fully understand what specifies cell type-specific binding of Kaiso, it appears that in some cases increased DNA methylation and compact chromatin structure may prevent Kaiso from binding in a particular cell type. Our studies also suggest that interaction with other transcription factors can influence cell type-specific binding of Kaiso. Motif analysis indicated that most cell type-specific Kaiso binding sites did not contain the TCTCGCGAGA motif, suggesting that Kaiso may be recruited to these sites in a manner distinct from direct binding to its motif. To test this hypothesis we performed a motif analysis and found motifs for GATA and CTCF family members in the K562-specific Kaiso peaks and for ETS and Runt family members in the GM12878-specific Kaiso peaks. These results suggested that Kaiso might co-localize with these specific factors in GM12878 or K562 cells. ChIP-seq data from the ENCODE project confirmed the validity of these bioinformatic predictions; we found CTCF, GATA1, and GATA2 to be highly-enriched at K562-unique Kaiso binding sites, and RUNX3 and PU.1 to be highly enriched at GM12878-unique Kaiso binding sites. We note that a previous study has shown that Kaiso can interact with CTCF . Taken together with our genome-wide analyses, we suggest that CTCF may help to recruit Kaiso to certain locations in the genome. Physical interaction studies of Kaiso and GATA factors have not been performed; therefore, further work is necessary to determine the significance of these co-localizations. We note that a previous study suggested that Kaiso can interact with ZNF131 . However, the ZNF131 motif was not identified in any of our unbiased motif analyses. We performed a direct search for the ZNF131 motif allowing up to two mismatches, and found that only 24 of 603 GM-specific peaks that lack a Kaiso motif and only 38 of 1855 K56-specific peaks that lack a Kaiso motif contained a match to the ZNF131 motif. There is no ChIP-seq data for ZNF131, but based on motif analyses, it may not play an important role in recruiting Kaiso to the genome. Our results also indicate that nucleosome occupancy plays a role in dictating Kaiso’s cell type-specific binding between GM12878 and K562 (Figure 11). Specifically, binding sites unique to K562 cells show reduced nucleosome occupancy relative to the same genomic loci in GM12878 cells. However, in GM12878 cells, it appears that the positioning of nucleosomes plays a lesser role in differential Kaiso binding between the two cell types.
In summary, and in contrast to prediction, all of our analyses suggest that there is a strong positive relationship between the binding of Kaiso, the absence of DNA methylation, the presence of active marks on a promoter, and RNA expression levels. Thus, Kaiso does not appear to play a major role in creating a repressive promoter structure. Rather, our studies suggest that instead of recruiting repressive proteins such as HDACs, Kaiso may recruit positively-acting transcription factors. Future studies are needed to more precisely define the mechanism by which Kaiso contributes to the overall expression level of its target genes. Importantly, our findings establish a clear disconnect between in vitro studies and in vivo studies. Rather than DNA methylation of a small motif, the chromatin landscape, along with the cooperation of Kaiso with other factors, dictates Kaiso binding patterns. We suggest that the fact that Kaiso may prefer a methylated motif is not relevant to in vivo function because the methylated Kaiso motifs are not accessible for binding. A recent study has highlighted the fact that two-thirds of the members of the large family of KRAB domain-containing zinc finger proteins contain a specific argenine-histidine linker sequence between the C2H2 zinc finger domains that may allow recognition of methylated cytosines . Future studies may successfully identify a transcription factor that can bind to a methylated motif in the context of chromatin and contribute to gene silencing.
ChIP-seq peak calling and analysis
Two replicate Bowtie-mapped ChIP-seq datasets were downloaded for GM12878, K562, A549, HepG2, HCT116, and SK-N-SH from the UCSC browser. All Kaiso ChIP-seq experiments were carried out in the Myers Lab using Santa Cruz Biotechnology antibody sc-23871. The antibody has been validated to be specific to Kaiso as required by ENCODE standards , using Western blot analysis and mass spectrometry. We note that the antibody validation document shows that the levels of Kaiso in GM12878 and K562 are similar. The Kaiso (ZBTB33) antibody validation document from the ENCODE consortium can be found at http://genome-preview.ucsc.edu/cgi-bin/hgEncodeVocab?term=%22ZBTB33%22. Peaks were called for each replicate in each cell type using Sole-Search [11, 12]. The parameters used in the Sole-Search program for all Kaiso datasets were as follows: a permutation of 5, fragment length of 150, alpha value of 0.0010, an FDR of 0.0010, and a peak merge distance of 0. To determine the reproducibility between the two replicates for the Kaiso datasets (and to compare Kaiso peaks with other ChIP-seq datasets), the called peak files for each replicate were compared using the overlap analysis tool in Sole-Search [11, 12]. A file containing the genomic locations of all CpG islands were downloaded from the UCSC genome browser. To determine the location of Kaiso peaks (and the location of the Pol2 top-ranked peaks versus the Pol2 peaks excluded from analysis) relative to transcription start sites, the location analysis tool of Sole-Search was used. The epigenetic profiles of the Kaiso binding sites were analyzed using tag density plots that were created using Hypergeometric Optimization of Motif EnRichment software (HOMER, http://biowhat.ucsd.edu/homer/index.html) . All histone modification and transcription factor ChIP-seq datasets used in comparison to Kaiso peaks were downloaded from the UCSC genome browser.
DNA methylation analysis
To determine the DNA methylation status of the genomic regions corresponding to Kaiso peaks, a BigBed file for GM12878 WGBS data was downloaded from the UCSC genome browser and was converted to BED format using the BigBedtoBed script available at http://hgdownload.soe.ucsc.edu/admin/exe/macOSX.i386/. HOMER  was then used to plot the percent methylation across Kaiso peak regions using the annotatePeaks.pl script and the ‘-ratio’ option, comparing peak files to tag directories created using the ‘-mCpGbed’ option. The resulting output files were used to create histograms plotting the average percent methylation in 500bp regions surrounding the center of Kaiso peaks using a bin size of 10bp. To identify an enriched motif within Kaiso-binding sites, a motif analysis was performed using HOMER to identify strings of nucleotide sequences that are enriched within Kaiso peaks. The findMotifsGenome.pl command was run in HOMER using hg19 as the reference genome. To limit the motif analysis to regions pulled down by ChIP, the analysis was limited to sequences contained within each peak using the ‘-size given’ option. For some analyses, we centered Kaiso peaks on the methylated motif using the annotatePeaks.pl script and the -center option in HOMER. To determine the methylation status of individual CGCG motifs contained with peaks, the genomic coordinates of each motif was compared to WGBS and/or RRBS data, and a beta value was assigned to each CpG within the motif. For GM12878 methylation analyses, WGBS and RRBS data was combined to achieve higher genomic coverage; for K562 analyses, only RRBS data was available. Only bases with a minimum 3× sequencing coverage were used in methylation analyses.
where n is the number of mapped reads localized within exons, N is the total number of uniquely mapped reads in the experiment, and L is the length of gene body summing from all union exons in base pairs. We note that Kaiso had an RPKM value of 0.004081966 in GM12878 and 0.004755255 in K562, and ranked within the top 40% of expressed genes in both cell types. To verify the difference among groups of peaks (K562-unique, common, GM12878-unique), the Mann-Whitney rank test was applied.
Hypergeometric Optimization of Motif EnRichment
Reads per kilobase per million reads
Reduced representation bisulfite sequencing
Whole genome bisulfite sequencing.
All ChIP-seq and RNA-seq data was produced as part of the ENCODE consortium, and is available at (http://genome.ucsc.edu); all data used in this study is past the nine month moratorium. This work was supported in part by 1U54HG004558 as a component of the ENCODE project and by P30CA014089 from the National Cancer Institute; AB was supported in part by a pre-doctoral training fellowship from the National Human Genome Research Institute of the National Institutes of Health under grant number F3100HG6114.
- Jones PA: Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet. 2012, 13: 484-492. 10.1038/nrg3230.View ArticlePubMed
- Li G, Reinberg D: Chromatin higher-order structures and gene regulation. Curr Opin Genet Dev. 2011, 21: 175-186. 10.1016/j.gde.2011.01.022.PubMed CentralView ArticlePubMed
- Statham AL, Robinson MD, Song JZ, Coolen MW, Stirzaker C, Clark SJ: Bisulfite sequencing of chromatin immunoprecipitated DNA (BisChIP-seq) directly informs methylation status of histone-modified DNA. Genome Res. 2012, 22: 1120-1127. 10.1101/gr.132076.111.PubMed CentralView ArticlePubMed
- Brinkman AB, Gu H, Bartels SJJ, Zhang Y, Matarese F, Simmer F, Marks H, Bock C, Gnirke A, Meissner A, Stunnenberg HG: Sequential ChIP-bisulfite sequencing enables direct genome-scale investigation of chromatin and DNA methylation cross-talk. Genome Res. 2012, 22: 1128-1138. 10.1101/gr.133728.111.PubMed CentralView ArticlePubMed
- Komashko VM, Farnham PJ: 5-azacytidine treatment reorganizes genomic histone modification patterns. Epigenetics. 2010, 5: 229-240. 10.4161/epi.5.3.11409.View ArticlePubMed
- Dunham I, Kundaje A, Aldred SF, Collins PJ, Davis CA, Doyle F, Epstein CB, Frietze S, Harrow J, Kaul R, Khatun J, Lajoie BR, Landt SG, Lee B-K, Pauli F, Rosenbloom KR, Sabo P, Safi A, Sanyal A, Shoresh N, Simon JM, Song L, Trinklein ND, Altshuler RC, Birney E, Brown JB, Cheng C, Djebali S, Dong X, Dunham I: An integrated encyclopedia of DNA elements in the human genome. Nature. 2012, 489: 57-74. 10.1038/nature11247.View Article
- Filion GJP, Zhenilo S, Salozhin S, Yamada D, Prokhortchouk E, Defossez P-A: A family of human zinc finger proteins that bind methylated DNA and repress transcription. Mol Cell Biol. 2006, 26: 169-181. 10.1128/MCB.26.1.169-181.2006.PubMed CentralView ArticlePubMed
- Prokhortchouk A, Hendrich B, Jørgensen H, Ruzov A, Wilm M, Georgiev G, Bird A, Prokhortchouk E: The p120 catenin partner Kaiso is a DNA methylation-dependent transcriptional repressor. Genes Dev. 2001, 15: 1613-1618. 10.1101/gad.198501.PubMed CentralView ArticlePubMed
- Daniel JM, Spring CM, Crawford HC, Reynolds AB, Baig A: The p120(ctn)-binding partner Kaiso is a bi-modal DNA-binding protein that recognizes both a sequence-specific consensus and methylated CpG dinucleotides. Nucleic Acids Res. 2002, 30: 2911-2919. 10.1093/nar/gkf398.PubMed CentralView ArticlePubMed
- Yoon H-G, Chan DW, Reynolds AB, Qin J, Wong J: N-CoR mediates DNA methylation-dependent repression through a methyl CpG-binding protein Kaiso. Mol Cell. 2003, 12: 723-734. 10.1016/j.molcel.2003.08.008.View ArticlePubMed
- Blahnik KR, Dou L, O’geen H, McPhillips T, Xu X, Cao AR, Iyengar S, Nicolet CM, Ludäscher B, Korf I, Farnham PJ: Sole-Search: an integrated analysis program for peak detection and functional annotation using ChIP-seq data. Nucleic Acids Res. 2010, 38: e13-10.1093/nar/gkp1012.PubMed CentralView ArticlePubMed
- Blahnik KR, Dou L, Echipare L, Iyengar S, O’geen H, Sanchez E, Zhao Y, Marra MA, Hirst M, Costello JF, Korf I, Farnham PJ: Characterization of the contradictory chromatin signatures at the 3′ exons of zinc finger genes. PLoS One. 2011, 6: e17121-10.1371/journal.pone.0017121.PubMed CentralView ArticlePubMed
- Landt SG, Marinov GK, Kundaje A, Kheradpour P, Pauli F, Batzoglou S, Bernstein BE, Bickel P, Brown JB, Cayting P, Chen Y, DeSalvo G, Epstein C, Fisher-Aylor KI, Euskirchen G, Gerstein M, Gertz J, Hartemink AJ, Hoffman MM, Iyer VR, Jung YL, Karmakar S, Kellis M, Kharchenko PV, Li Q, Liu T, Liu XS, Ma L, Milosavljevic A, Myers RM: ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res. 2012, 22: 1813-1831. 10.1101/gr.136184.111.PubMed CentralView ArticlePubMed
- Li Q, Brown JB, Huang H, Bickel PJ: Measuring reproducibility of high-throughput experiments. The Annals of Applied Statistics. 2011, 5: 1752-1779. 10.1214/11-AOAS466.View Article
- Lopes EC, Valls E, Figueroa ME, Mazur A, Meng F-G, Chiosis G, Laird PW, Schreiber-Agus N, Greally JM, Prokhortchouk E, Melnick A: Kaiso contributes to DNA methylation-dependent silencing of tumor suppressor genes in colon cancer cell lines. Cancer Res. 2008, 68: 7258-7263. 10.1158/0008-5472.CAN-08-0344.View ArticlePubMed
- Donaldson NS, Nordgaard CL, Pierre CC, Kelly KF, Robinson SC, Swystun L, Henriquez R, Graham M, Daniel JM: Kaiso regulates Znf131-mediated transcriptional activation. Exp Cell Res. 2010, 316: 1692-1705. 10.1016/j.yexcr.2010.03.011.View ArticlePubMed
- Kelly KF, Otchere AA, Graham M, Daniel JM: Nuclear import of the BTB/POZ transcriptional regulator Kaiso. J Cell Sci. 2004, 117: 6143-6152. 10.1242/jcs.01541.View ArticlePubMed
- Raghav SK, Waszak SM, Krier I, Gubelmann C, Isakova A, Mikkelsen TS, Deplancke B: Integrative genomics identifies the corepressor SMRT as a gatekeeper of adipogenesis through the transcription factors C/EBPβ and KAISO. Mol Cell. 2012, 46: 335-350. 10.1016/j.molcel.2012.03.017.View ArticlePubMed
- Li G, Ruan X, Auerbach RK, Sandhu KS, Zheng M, Wang P, Poh HM, Goh Y, Lim J, Zhang J, Sim HS, Peh SQ, Mulawadi FH, Ong CT, Orlov YL, Hong S, Zhang Z, Landt S, Raha D, Euskirchen G, Wei C-L, Ge W, Wang H, Davis C, Fisher-Aylor KI, Mortazavi A, Gerstein M, Gingeras T, Wold B, Sun Y: Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation. Cell. 2012, 148: 84-98. 10.1016/j.cell.2011.12.014.PubMed CentralView ArticlePubMed
- Lee B-K, Iyer VR: Genome-wide studies of CCCTC-binding factor (CTCF) and cohesin provide insight into chromatin structure and regulation. J Biol Chem. 2012, 287: 30906-30913. 10.1074/jbc.R111.324962.PubMed CentralView ArticlePubMed
- Kelly TK, Liu Y, Lay FD, Liang G, Berman BP, Jones PA: Genome-wide mapping of nucleosome positioning and DNA methylation within individual DNA molecules. Genome Res. 2012, 22: 2497-2506. 10.1101/gr.143008.112.PubMed CentralView ArticlePubMed
- Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK: Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010, 38: 576-589. 10.1016/j.molcel.2010.05.004.PubMed CentralView ArticlePubMed
- Ruzov A, Savitskaya E, Hackett JA, Reddington JP, Prokhortchouk A, Madej MJ, Chekanov N, Li M, Dunican DS, Prokhortchouk E, Pennings S, Meehan RR: The non-methylated DNA-binding function of Kaiso is not required in early Xenopus laevis development. Development. 2009, 136: 729-738. 10.1242/dev.025569.PubMed CentralView ArticlePubMed
- Defossez PA: The human enhancer blocker CTC-binding factor interacts with the transcription factor Kaiso. J Biol Chem. 2005, 280: 43017-43023. 10.1074/jbc.M510802200.View ArticlePubMed
- Wang J, Zhuang J, Iyer S, Lin X, Whitfield TW, Greven MC, Pierce BG, Dong X, Kundaje A, Cheng Y, Rando OJ, Birney E, Myers RM, Noble WS, Snyder M, Weng Z: Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors. Genome Res. 2012, 22: 1798-1812. 10.1101/gr.139105.112.PubMed CentralView ArticlePubMed
- Buck-Koehntop BA, Martinez-Yamout MA, Dyson HJ, Wright PE: Kaiso uses all three zinc fingers and adjacent sequence motifs for high affinity binding to sequence-specific and methyl-CpG DNA targets. FEBS Lett. 2012, 586: 734-739. 10.1016/j.febslet.2012.01.045.PubMed CentralView ArticlePubMed
- Bartels SJJ, Spruijt CG, Brinkman AB, Jansen PWTC, Vermeulen M, Stunnenberg HG: A SILAC-based screen for Methyl-CpG binding proteins identifies RBP-J as a DNA methylation and sequence-specific binding protein. PLoS One. 2011, 6: e25884-10.1371/journal.pone.0025884.PubMed CentralView ArticlePubMed
- Buck-Koehntop BA, Stanfield RL, Ekiert DC, Martinez-Yamout MA, Dyson HJ, Wilson IA, Wright PE: Molecular basis for recognition of methylated and specific DNA sequences by the zinc finger protein Kaiso. Proc Natl Acad Sci USA. 2012, 109: 15229-15234. 10.1073/pnas.1213726109.PubMed CentralView ArticlePubMed
- Lan X, Bonneville R, Apostolos J, Wu W, Jin VX: W-ChIPeaks: a comprehensive web application tool for processing ChIP-chip and ChIP-seq data. Bioinformatics. 2011, 27: 428-430. 10.1093/bioinformatics/btq669.PubMed CentralView ArticlePubMed
- Rabinovich A, Jin VX, Rabinovich R, Xu X, Farnham PJ: E2F in vivo binding specificity: comparison of consensus versus nonconsensus binding sites. Genome Res. 2008, 18: 1763-1777. 10.1101/gr.080622.108.PubMed CentralView ArticlePubMed
- Farnham PJ: Insights from genomic profiling of transcription factors. Nat Rev Genet. 2009, 10: 605-616. 10.1038/nrg2636.PubMed CentralView ArticlePubMed
- Thurman RE, Rynes E, Humbert R, Vierstra J, Maurano MT, Haugen E, Sheffield NC, Stergachis AB, Wang H, Vernot B, Garg K, John S, Sandstrom R, Bates D, Boatman L, Canfield TK, Diegel M, Dunn D, Ebersol AK, Frum T, Giste E, Johnson AK, Johnson EM, Kutyavin T, Lajoie B, Lee B-K, Lee K, London D, Lotakis D, Neph S: The accessible chromatin landscape of the human genome. Nature. 2012, 489: 75-82. 10.1038/nature11232.PubMed CentralView ArticlePubMed
- Gaffney DJ, McVicker G, Pai AA, Fondufe-Mittendorf YN, Lewellen N, Michelini K, Widom J, Gilad Y, Pritchard JK: Controls of nucleosome positioning in the human genome. PLoS Genet. 2012, 8: e1003036-10.1371/journal.pgen.1003036.PubMed CentralView ArticlePubMed
- Li B, Carey M, Workman JL: The role of chromatin during transcription. Cell. 2007, 128: 707-719. 10.1016/j.cell.2007.01.015.View ArticlePubMed
- Quenneville S, Verde G, Corsinotti A, Kapopoulou A, Jakobsson J, Offner S, Baglivo I, Pedone PV, Grimaldi G, Riccio A, Trono D: In embryonic stem cells, ZFP57/KAP1 recognize a methylated hexanucleotide to affect chromatin and DNA methylation of imprinting control regions. Mol Cell. 2011, 44: 361-372. 10.1016/j.molcel.2011.08.032.PubMed CentralView ArticlePubMed
- Spruijt CG, Gnerlich F, Smits AH, Pfaffeneder T, Jansen PWTC, Bauer C, Münzel M, Wagner M, Müller M, Khan F, Eberl HC, Mensinga A, Brinkman AB, Lephikov K, Müller U, Walter J, Boelens R, van Ingen H, Leonhardt H, Carell T, Vermeulen M: Dynamic readers for 5-(hydroxy)methylcytosine and its oxidized derivatives. Cell. 2013, 152: 1146-1159. 10.1016/j.cell.2013.02.004.View ArticlePubMed
- Donaldson NS, Pierre CC, Anstey MI, Robinson SC, Weerawardane SM, Daniel JM: Kaiso represses the cell cycle gene cyclin D1 via sequence-specific and methyl-CpG-dependent mechanisms. PLoS One. 2012, 7: e50398-10.1371/journal.pone.0050398.PubMed CentralView ArticlePubMed
- Liu Y, Zhang X, Blumenthal RM, Cheng X: A common mode of recognition for methylated CpG. Trends Biochem Sci. 2013, 38: 177-183. 10.1016/j.tibs.2012.12.005.PubMed CentralView ArticlePubMed
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