The TCF7L2 transcription factor has been linked to a variety of human diseases such as type 2 diabetes and cancer [3
]. To investigate the mechanisms by which this site-specific DNA binding transcriptional regulator can impact on such diverse diseases, we performed ChIP-seq analysis for TCF7L2 in 6 different human cell lines, identifying more than 116,000 non-redundant binding sites, with only 1,864 sites being common to all 6 cell types. Several striking discoveries that came from our ChIP-seq analysis of the 6 different cell lines are: i) TCF7L2 has multiple binding sites near each target gene; ii) TCF7L2 has developed cell type-specific mechanisms for regulating a set of approximately 14,000 genes; iii) TCF7L2 binds to more than 40% of the active enhancers in each of the 6 cancer cell lines; and iv) TCF7L2 functions as repressor when recruited to the genome via tethering by the master regulator GATA3.
By analysis of the TCF7L2 ChIP-seq datasets from 6 different human cancer cell lines, we identified 116,270 TCF7L2 binding sites, with each cell type having approximately 25,000 to 50,000 TCF7L2 peaks. We note that another group has examined TCF7L2 binding in human HCT116 cells [12
], identifying only 1,095 binding sites. It is not clear why Zhao and colleagues [12
] identified such smaller numbers of TCF7L2 binding sites in HCT116 cells, but it is not likely due to the antibody specificity (the antibodies used in both studies give similar patterns on western blots). It is more likely that the 30-fold difference in peak number is due to the ChIP protocol. Zhao et al
] used protein A agarose beads, whereas we used magnetic protein A/G beads; we have found that protein A agarose beads produce low signals in many ChIP assays (unpublished data). Interestingly, the 116,270 TCF7L2 binding sites that we identified correspond to only 14,193 genes, with each target gene having an average of 8.2 TCF7L2 binding sites. Many of these binding sites are cell type-specific, as exemplified by the fact that there are only three to four TCF7L2 binding sites per target gene in any one cell type (Figure ).
Cell type-specific binding patterns suggest that TCF7L2 binds cooperatively to the genome along with cell type-specific factors. For example, the AP1 (activator protein 1) motif is enriched in the sets of HCT116-specific and MCF7-specific TCF7L2 binding sites. Interestingly, TCF7L2 has previously been shown to physically interact with JUN (which is one of the heterodimeric components of AP1) and it has been suggested that the JUN and TCF7L2 interaction is a molecular mechanism that integrates the activation of the TCF and CTNNB1 pathway by the JNK (Jun N-terminal kinase) pathway [36
]. Although ChIP-seq data for AP1 components is not available for HCT116 or MCF7 cells, there are 7,400 genomic locations that are bound by TCF7L2 in HCT116 cells that are also bound by JUN in HeLa cells [11
]; it is likely that a much larger number of co-localizing regions would be identified if the datasets were from the same cell type. Our detailed bioinformatic analysis of the HepG2-specific TCF7L2 peaks suggested that HNF4α and FOXA2 might be binding partners of TCF7L2 in this cell type. A previous study had shown that FOXA2 and HNF4α colocalize at a subset of sites in mouse liver [37
], but that study did not examine the relationship of these sites with TCF7L2 binding. Therefore, we experimentally validated our bioinformatic prediction by comparing ChIP-seq data for all three factors. We found that greater than 50% of the TCF7L2 HepG2-specific binding sites are also bound by the liver transcription factors HNF4α and FOXA2, suggesting that this trio of factors cooperate in gene regulation. Based on the identification of motifs for all three factors in the TCF7L2 peaks, we suggest that TCF7L2, HNF4α, and FOXA2 all bind directly to the DNA, perhaps with the liver-specific factors helping to stabilize TCF7L2 genomic binding to particular enhancer regions in HepG2 cells. HNF4α and FOXA2 have been shown to be critical determinants of hepatocyte identity; Hnf4α plus Foxa1, Foxa2, or Foxa3 can convert mouse embryonic and adult fibroblasts into cells that closely resemble hepatocytes in vitro
]. The induced hepatocyte-like cells had multiple hepatocyte-specific features and reconstituted damaged hepatic tissues after transplantation. Future studies should address a potential role of TCF7L2 in hepatocyte identity.
Bioinformatic analysis of the MCF7-specific TCF7L2 sites revealed that the GATA3 motif was highly enriched and experimental analysis of MCF7 GATA3 ChIP-seq data showed that nearly one-half of the MCF7-specific TCF7L2 binding sites co-localize with GATA3. Interestingly, we found that the TCF7L2 motif was not enriched in the regions bound by both TCF7L2 and GATA3. These results suggested that perhaps GATA3 binds directly to the DNA at these sites and tethers TCF7L2 to the genome at the MCF7-specific TCF7L2 binding sites Accordingly, we showed that depletion of GATA3 reduced recruitment of TCF7L2 to a subset of genomic sites. We also demonstrated that TCF7L2 functions mainly as a repressor when tethered to the genome via GATA3. At some genes, TCF7L2 cooperatively represses genes with GATA3 but at other genes TCF7L2 antagonizes GATA3-mediated activation (Figure ).
Figure 8 Two modes of TCF7L2-mediated transcriptional repression of GATA3 target genes. (a) GATA3 tethers TCF7L2 to the genome and both factors cooperate to repress target genes. (b) GATA3 tethers TCF7L2 to the genome with TCF7L2 antagonizing GATA3-mediated transcriptional (more ...)
Specification of cell phenotypes is achieved by sets of master transcriptional regulators that activate the genes specific for one cell fate while repressing genes that specify other cell fates. The GATA factors, which include six site-specific DNA binding proteins that bind to the sequence (A/T)GATA(A/G), are master regulators that govern cell differentiation [39
]. For example, GATA1-3 have been linked to the specification of different hematopoietic cell fates and GATA4-6 are involved in differentiation of cardiac and lung tissues. Also, GATA3 is the most highly enriched transcription factor in the mammary epithelium, has been shown to be necessary for mammary cell differentiation, and is specifically required to maintain the luminal cell fate [43
]. Studies of human breast cancers have shown that GATA3 is expressed in early stage, well-differentiated tumors but not in advanced invasive cancers. In addition, GATA3 expression is correlated with longer disease-free survival and evidence suggests that it can prevent or reverse the epithelial to mesenchymal transition that is characteristic of cancer metastasis [45
]. Our studies show that TCF7L2 cooperates with the master regulator GATA3 to repress transcription in the well-differentiated MCF7 breast cancer cell line and suggest that a TCF7L2-GATA3 complex may be a critical regulator of breast cell differentiation.
Our finding that TCF7L2 co-localizes and cooperates in gene regulation with a GATA factor in MCF7 breast cancer cells is similar to a recent study of TCF7L2 in hematopoietic cells. Trompouki et al
] showed that in hematopoietic cells, TCF7L2 co-occupies sites with GATA1 and GATA2, which are master regulators of blood cell differentiation. Both the TCF7L2 motif and the GATA motif were found at the co-bound sites (suggesting adjacent binding of the two factors, not tethering) and TCF7L2 functioned as a transcriptional activator at those sites. In contrast, our studies indicate that co-localization of TCF7L2 with GATA3 in MCF7 cells is not due to adjacent binding but rather TCF7L2 is tethered to the genome by interaction with GATA3 binding to a GATA motif and that this tethering results in transcriptional repression. A study of Drosophila
TCF binding to the Ugt36Bc
upstream region indicated that TCF represses transcription of the Ugt36Bc
gene by binding to non-traditional TCF motifs [46
]. Interestingly, the three Ugt36Bc
TCF sites (AGAAAT, AGATAA, AGATAA) are almost identical to the GATA3 motif. Blauwkamp et al
] suggest that the sequence to which TCF binds has an important function in determining whether a gene will be activated or repressed. Their studies did not address whether TCF bound directly to the GATA-like motifs. However, based on our studies, it would be worthwhile to investigate a possible genomic tethering mechanism of TCF by GATA factors in Drosophila