A growing body of evidence suggests that changes to the coding regions of transcription factors play a much larger role in the evolution of developmental gene regulatory networks than originally imagined. Just as cis-regulatory changes make use of modular binding site composition and tissue-specific modules to avoid pleiotropy, transcription factor coding regions also predominantly evolve in ways that limit the context of functional effects. Here, we review the recent works that have led to this unexpected change in the field of Evolution and Development (Evo-Devo) and consider the implications these studies have had on our understanding of the evolution of developmental processes.The form that an animal takes during development is directed by gene regulatory networks (GRNs). Developmental GRNs interpret maternally deposited molecules and externally supplied signals to direct cell-fate decisions, which ultimately leads to the arrangements of organs and tissues in the organism. Genetically encoded modifications to these networks have generated the wide range of metazoan diversity that exists today. Most studies of GRN evolution focus on changes to  The interaction between a transcription factor and a specific binding site within a CRM allow for positive or negative influence on expression of a target gene. Because these networks instruct the specification of a particular cell type or structure, changes to these networks result in the evolution of animal morphology.Gene regulatory networks (GRNs) explain the gene expression states that direct a cell to establish a particular fate . In devecis regulatory modules have historically been considered the dominant source of GRN evolution, and this idea continues to be supported by new data in the genomics era (reviewed in [cis regulatory sequences [There has been much debate surrounding the mechanisms by which GRNs evolve. Changes to iewed in –4). Whiliewed in –8). In riewed in  and compequences . Additioequences .On the other hand, several lines of evidence suggest that transcription factors are incredibly well conserved over evolutionary time. The first indication of this comes from the now famous examples from the Hox transcription factor cluster. These transcription factors are conserved in both sequence and function, patterning the body axis of organisms as disparate as insects and vertebrates , 13. MorEven prior to this breadth of experimental evidence in support of CRM change as the primary driver of GRN evolution, some theorized that this would be the case . The logMore recently, it has been argued that transcription factors also have the capacity to be modular, and consequently could contribute to developmental GRN evolution more significantly than originally considered , 24. TheThe basic biochemical function of a transcription factor is twofold: (i) to recognize and bind a short, specific piece of DNA within a regulatory region, and (ii) to recruit or bind other proteins relevant to transcriptional regulation, such as other transcription factors, chromatin remodeling proteins, and general RNA polymerase machinery. The first function, DNA binding, directs the transcription factor to its target loci. The second allows the factor to elicit changes in transcriptional levels by influencing the stability of the transcriptional apparatus or the chromatin state. Combined, these functions enable transcription factors to influence gene expression. At the structural level, transcription factor proteins contain discrete domains for exerting these functions, known as DNA-binding domains and protein-protein interaction domains. Some have more than one of each, and others may perform both functions via a single domain. Because transcription factors have such functional units, which may individually acquire mutations and be lost or gained over time, they are modular just as CRMs are and, thus, have opportunities to evolve in ways that minimize pleiotropy.In general, DNA binding domains are extremely well-conserved, but the rest of the protein readily diverges between homologs. For example, the aforementioned Hox genes were discovered on the basis of highly conserved homeobox DNA-binding domains . Yet, McHere, we will first discuss the mechanisms that can lead to an increase in transcription factor functional diversity and then consider ways that these functions can also evolve context dependence. Both sets of mechanisms allow transcription factor change to be modular, and importantly, multiple mechanisms can be combined to reduce evolutionary constraint even more. This is depicted in Figure Many transcription factor families arose at the base of the metazoan lineage (reviewed in ) and manDrosophila Myb in functional-equivalence assays, but A and C-Myb cannot [in vivo[New transcription factor homologs are created in two ways. When species diverge from a common ancestor, each initially is endowed with the same collection of transcription factors, which generates orthologs. Following the split, each set will acquire mutations. Until a novel regulatory mechanism is devised, the orthologous proteins must execute the same tasks in each species as they did in the common ancestor. This means that orthologous transcription factors are under a great amount of constraint and are therefore thought to remain thoroughly conserved. Conversely, paralogs, transcription factors generated by gene duplication events, are much more free to evolve Figure A  (reviewed ). In C.  domains , 43. As  domains ).Radiation of the supnrs is not an isolated example. Other transcription factor families also exhibit lineage-specific expansions, and so this is thought to be an important source of gene regulatory change (reviewed in ). Zinc fConversely, a different zinc-finger subfamily, the Krüppel-Associated-Box (KRAB-ZNF), radiated dramatically in tetrapod vertebrate lineages, while only one paralog, Prdm9, exists in invertebrates . Many ofAnother mechanism for increasing modularity within transcription factor repertoires is exon shuffling. Exon shuffling allows for the creation of new genes by piecing together existing functional domains Figure A. This mPerhaps the most unexpected source of transcription factor adaptability is modular DNA-binding. This is surprising partly because functional-equivalence studies implied conserved DNA specificity of both orthologous , 18, 56 Initial studies that made use of protein-binding microarrays unearthed a few surprising findings. First, many transcription factors’ binding preferences are best described by multiple position weight matrices rather than the one matrix –68. ThesA recent study of yeast C2H2 zinc finger paralogs also found modular differences in DNA-binding . These pOrthologous transcription factors are under greater evolutionary constraint; therefore, until recently it was uncertain whether this type of modularity would extend to these genes. In addition to the differences in Fox paralog families described above, Nakagawa and colleagues also observed that different orthologs of yeast Fox3 exhibit substantial DNA binding diversity . Some reStrongylocentrotus purpuratus) and a sea star (Patiria miniata) evolved differences in their secondary binding abilities. Interestingly this secondary motif is also different compared to what has been reported for the vertebrate ortholog of Tbr, Eomesodermin [Recent work demonstrates that while metazoan developmental transcription factors may not diverge as dramatically as yeast orthologs, they do seem capable of exploiting modular divergence mechanisms used by paralogs . In thissodermin . Howeversodermin . The mecsodermin , 76, 77.sodermin , 79. Chain vivo, but in many cases have distinct developmental tasks. Notably, in the case of Hedgehog-responsive genes used during Drosophila development, low-affinity, non-canonical alternative Cisites cannot be replaced by canonical, higher affinity sites as this results in a switch from activation to repression [Drosophila muscle development; all have the same primary motif and therefore would not be able to confer different myoblast identities without these unique secondary motifs [in vivo functionality just as primary sites do. Because primary and secondary sites have distinct functions, the effects of changing binding to one type of site are less pleiotropic than changing binding to a solitary binding site. Importantly, since alternative binding sites can be gained and lost without affecting a conserved site [Several studies have demonstrated that these secondary and other non-canonical alternative binding sites are not only functional pression , 81. As y motifs . Thus, sved site –74, thesPax6 expression is controlled by the affinity of the Prep1 binding sites within its enhancer [Pax6 expression to begin too early. Heterochrony, or shifts in the rate or timing of developmental processes, is an important source of morphological differences between species . MoIn addition to having modular structure and function, transcription factors can also evolve reduced pleiotropy by limiting the spatiotemporal context of their functions. As mentioned previously, temporal control is crucial to the faithful execution of developmental programs, and shifts in timing can alter development and lead to the evolution of morphological changes. Thus limiting a transcription factor’s action to a particular developmental period is important to the process. Likewise, control of the transcription factor’s spatial domain is important for developmental processes. GRNs typically make use of combinatorial logic; thus, addition or subtraction of a constituent transcription factor results in alterations to where the GRN is active. Such changes can modify development and resulting morphology. Therefore, mechanisms are in place to ensure not only that transcription factors are expressed and active in particular developmental contexts, but also to allow the many processes they participate in to be uncoupled and evolve independently. The most well-known, and probably also the most common, mechanism for limiting and altering spatiotemporal contexts is by control of transcription factor expression through CRMs. HerDsx gene, but the C-terminus of each form is sex-specific due to the retention of exon 4 in the female version, and 5 and 6 in the male version [Alternative splicing can evolve to produce lineage-specific variants of transcription factors in a modular way from the existing structural composition. This is thought to be particularly useful in the evolution of developmental GRNs because different variants can be limited to a particular tissue or developmental stage (reviewed in ). This m version . Interes version . These eTranscription factors do not influence gene expression on their own, but do so as regulatory complexes mediated by interactions between the constituent transcription factors and cofactors. These interactions tend to be context-dependent; a particular protein-protein interaction will only be relevant when both interacting partners are present. The composition of a transcription factor complex is also guided by the types of binding sites present in the CRM, and so many transcription factors participate in multiple non-identical complexes and are able to form interactions with more than one other protein. Therefore, changes to such interactions are predicted to be minimally pleiotropic.Ftz’s expression domain via CRM evolution was important, but so were changes to the protein coding region. These changes resulted in the loss of an ancestral interaction peptide motif, YPWM, which is required for interaction with Exdand homeotic function, and gain of a new LXXLL motif, which created an interaction with Ftz-F1. The latter confers most segmentation function, although the N terminal arm of the homeodomain also participates. More recently, it was shown that this is not a simple case of drastic changes in a particular lineage. Rather, the YPWM homeotic potential motif evolved into stronger and weaker variants of the ancestral sequence throughout the arthropod clade [A well-known example critical to arthropod evolution is Ftz, which acquired novel cofactor interactions that changed the function of this transcription factor from homeotic to pair-rule segmentation factor . This ocod clade . While YNewly evolved interaction motifs are also able to change the magnitude of an existing function. Throughout bilaterians, the transcription factor Engrailed (En) interacts with a co-repressor Groucho (Gro), usually through a well-conserved motif , 93. HowImportantly, changes to protein-protein interactions can occur without major disruptions of the existing protein-protein interaction domain. Brayer and colleagues discovered that an important new interaction evolved between Hoxa11 and Foxo1a in placental mammals without actually changing the ancestral binding interface . These gThese case studies highlight the previously underappreciated versatility of transcription factor coding region changes, in addition to offering a mechanism for limiting the context of the evolved transcription factor’s function. Furthermore, they reveal that mutations to transcription factors can accomplish some of the same advantageous functions of CRMs, such as the ability to tweak target gene transcriptional output. Finally, they demonstrate that there are many ways to alter a transcription factor without abolishing ancestral function, such as through changing protein conformation as opposed to the sequence of the functional domain.Post-translational modifications are a common way to increase protein functional diversity. They are of particular interest to those seeking to understand how transcription factors may evolve while avoiding pleiotropy because they are known to regulate the location, longevity, and activity of proteins. They can also allow for alternate protein structure and enhance or prevent protein-protein interactions and DNA-binding . ThMoreover, new modification sites evolve rapidly. A comprehensive bioinformatics screen identified over two-hundred ubiquitylation sites that arose in the human lineage since it split from other primates . A similDll, which also results in repression of limb formation. They demonstrated that phosphorylation of CK2 sites in crustaceans interferes with the ability of Ubx to repress Dll, and as a result more appendages form in crustaceans compared to insects. The molecular consequence of phosphorylating these sites is unknown, but there are precedents for phosphorylation affecting DNA-binding of Hox proteins and also their protein-protein interactions [It is unsurprising then that recent work has found compelling connections between novel post-translational modification sites within transcription factors and the evolution of new features. For example, Ubx, a Hox transcription factor, is expressed in the limb primordia of both insects and crustaceans. Thus, alteration of the Ubx protein explains differences in appendage number between different groups of arthropods rather than CRM level changes . Taghli-ractions , 107.Another interesting example entails evolution of pregnancy in mammals, due in part to changes in phosphorylation of Cebpβ . This woTranscription factor coding changes are becoming a theoretically more accepted source of GRN evolution, but there are still only a few studies documenting specific changes and tying those to developmental novelties. Many of the studies we have discussed in this review suggest interesting ways GRN evolution can occur via transcription factor change, but further study is still required in order to understand the full mechanism. As these experimental examples continue to increase, we will be able to decipher what impact these changes have on the wiring of their GRNs and how this might differ from CRM mutations. The original logic supporting CRM mutations over transcription factor changes would suggest that the former are ideally suited to alter the expression of a particular gene and potentially also its downstream targets within a tissue or cell-type, while changes to transcription factors will have broader effects, changing the regulation of large sets of target genes across the organism. The experimental evidence described here points to incremental and modular transcription factor mutations being favored by evolution, and latent motifs and abilities becoming more pronounced or reduced over time. Thus, in many ways, transcription factors evolve in ways that are very reminiscent of CRM evolution in that both use modularity to circumvent pleiotropy. However, it is important to realize that their effects on the surrounding GRNs are potentially not equal. Each type of change may be more ideal for driving different types of GRN changes and developing different types of novelty. More information about both types of change is required to tease out this discrepancy. On the other hand, several recent works suggest that CRM and transcription factor mutations may generally operate together , 110. Ad


The functions of the TAF subunits of mammalian TFIID in physiological processes remain poorly characterised. In this study, we describe a novel function of TAFs in directing genomic occupancy of a transcriptional activator. Using liver-specific inactivation in mice, we show that the TAF4 subunit of TFIID is required for post-natal hepatocyte maturation. TAF4 promotes pre-initiation complex (PIC) formation at post-natal expressed liver function genes and down-regulates a subset of embryonic expressed genes by increased RNA polymerase II pausing. The TAF4–TAF12 heterodimer interacts directly with HNF4A and in vivo TAF4 is necessary to maintain HNF4A-directed embryonic gene expression at post-natal stages and promotes HNF4A occupancy of functional cis-regulatory elements adjacent to the transcription start sites of post-natal expressed genes. Stable HNF4A occupancy of these regulatory elements requires TAF4-dependent PIC formation highlighting that these are mutually dependent events. Local promoter-proximal HNF4A–TFIID interactions therefore act as instructive signals for post-natal hepatocyte differentiation.DOI:http://dx.doi.org/10.7554/eLife.03613.001 To decode the information contained within a gene, a number of processes need to occur. For example, the DNA sequence that makes up the gene needs to be copied to make a molecule of RNA, which is then translated to build the corresponding protein. The first steps in the manufacture of RNA involve a structure called a ‘pre-initiation complex’ moving an enzyme called RNA polymerase II to the start of the gene that needs to be copied.The pre-initiation complex is made up of many types of protein, including a set of proteins called TAFs. However, the way that these proteins work in mammals is not well understood. There are good reasons for this: proteins are often studied by seeing what happens when the protein is removed, but many TAFs are so important that removing them is lethal.Alpern et al. have now studied the function of TAF4 by removing this protein from mouse liver cells. This causes severe hypoglycemia . Moreover, it seems as if these cells start dying before they become fully mature. In liver cells lacking TAF4, some 1408 genes that are normally turned on just after birth are not properly switched on; these genes are necessary for the metabolic functions of the liver. Furthermore, 776 genes that are normally turned off after birth continue to be expressed. It seems that the absence of TAF4 sometimes disrupts the formation of the pre-initiation complex, which would slow down the production of RNA. However, it can also have the opposite effect by increasing the activity of RNA polymerase II, hence making too many copies of RNA from some genes.Alpern et al. also find that TAF4 is needed to allow a protein called HNF4A, which is important in the development of the liver and in controlling metabolism, to interact with over 7000 important DNA sequences. Mutations in HNF4A are responsible for a syndrome known as Maturity Onset of Diabetes in the Young. The next stage in this work will be to explore if these mutations influence the interaction between HNF4A and TAF4, and if they do, whether these changes contribute to this form of diabetes.DOI:http://dx.doi.org/10.7554/eLife.03613.002 TFIID plays a critical role in RNA polymerase II (Pol II) pre-initiation complex (PIC) formation. The TATA-box binding protein (TBP) and 13–14 TBP-associated factors (TAFs) assemble to form TFIID from an association between the ‘core complex’ comprising the TAF4–TAF12 and TAF6–TAF9 histone-fold heterodimers together with TAF5 and a second module comprising TBP, TAF1, TAF2, and TAF7 . The TAFExtensive genetic analysis of TAFs has been performed in yeast , but theDespite these studies, the role of TAFs in physiological processes in vivo remains largely unknown and the molecular basis of their action is poorly characterised. In this study, we show that TAF4 is essential for activation of the post-natal hepatocyte gene expression programme. The TAF4–TAF12 heterodimer interacts with the nuclear receptor HNF4A to promote its binding to conserved and functional cis-regulatory elements located close to the transcription start sites of liver function genes. The stable binding of HNF4A to these elements is thus dependent on concomitant pre-initiation complex formation. These results reveal that HNF4A interaction with the basal transcription machinery controls not only PIC formation but also the occupation of its cognate regulatory elements.Immunofluorescence revealed TAF4 expression in P12 wild-type (WT) hepatocytes, mesenchymal tissues, endothelial and smooth muscle cells around the hepatic veins and arteries, and cholangiocytes lining the bile ducts . TAF4 anTaf4a gene were crossed with animals expressing Cre recombinase under the control of the albumin (Alb) promoter to inactivate Taf4 in post-partum murine hepatocytes (Taf4aaf4−/−hep). TAF4 expression is lost from hepatocytes by P12 . Taf4ahep−/− animals are of normal weight and size at birth, show retarded growth by P12, begin to die between P12 and P14, and all are dead by P21  were repressed as were the bile acid secretion and re-uptake components Abcb1a and Abcg5/8, respectively  and FXR (Nr1h4), but also by repression of Cyp8b1. In Cyp8b1−/− mice, Cyp7a1 expression is up-regulated due to loss of cholic acid, a primary bile acid produced by CYP8B1 , Gck, the rate-limiting enzyme of glucose metabolism, Pcx, several glucose inter-conversion enzymes , and Aqp7/Aqp9, important for glycerol supply and hepatic gluconeogenesis. Reduced expression of the components of all epithelial junction types: tight junctions , adherent junctions , desmosomes , and gap junctions (Gjb1/2) supports the observed disruption of the hepatic epithelium and loss of the blood–bile barrier in the TAF4 mutant animals.Many glycolysis/gluconeogenesis and fatty acid oxidation genes were repressed such as the glucose transporter GLUT2  and acyl-CoA-synthetase (Acsl3) that activates long chain fatty acids were also up-regulated. Activated FAs are shuttled across the mitochondrial membrane via carnitine palmitoyltransferase-1 that has three isoforms: liver, muscle, and brain. Expression of liver Cpt1a was unchanged, but the muscle Cpt1b isoform was overexpressed.Several genes involved in glucose and lipid metabolism were up-regulated in teatosis . The braWe compared our RNA-seq data with a multi-stage analysis of gene expression in developing liver . From thDlk1, Meg3, Dio3, Plagl1, Peg3, Peg10, Igf2as, Airn, Igf2r, Malat1, Neat1, and Grb10) were up-regulated in mutant liver. These genes regulate fetal growth and are post-natal repressed. Expression of these genes is a hallmark of immature tissue, showing that TAF4 is required for normal post-natal hepatoblast maturation.Interestingly, several imprinted genes , trimethylated lysine 4 of histone H3 (H3K4me3), and CTCF to monitor PIC formation and chromatin organisation.We performed ChIP-seq from wild-type and Taf4ahep−/− liver –TAF12(29–161), containing their histone fold regions that form a soluble heterodimer in hia coli , with fuhia coli , while oTAF4 inactivation in early post-natal hepatocytes led to defective liver organisation and function resulting in death of the animals by P15. Three major features characterise this phenotype: defective bile duct formation, disorganised hepatocyte epithelium with loss of cell junctions and blood–bile barrier, lack of post-natal gene activation and consequent metabolic abnormalities. Many of these features, indicative of retarded hepatocyte maturation, can be explained by TAF4 acting as a cofactor for HNF4A, an idea that is supported by functional and biochemical data.Several features of the TAF4 knockout are observed when HNF4A is inactivated during hepatoblast development, such as disorganisation of the hepatocyte epithelium and liver architecture, loss of cell junctions, and glycogen accumulation . While tAlb-Cre transgene) TAF4 inactivation is complete by P12 resulting in the loss of HNF4A binding to regulatory elements of at least 296 genes. Consequently, we observe a more severe general loss of liver metabolic functions with many relevant genes amongst these 296 requiring TAF4–HNF4A cooperation. While loss of HNF4A in adults has little effect on the expression of other nuclear receptors such as FXR, PXR, and LXR that play important functions in liver, their expression is strongly diminished in the Taf4ahep−/− liver also contributing to the more severe phenotype.HNF4A is required for post-natal expression of many liver metabolic function genes . For exaTwo different situations can thus be defined. At many, but not all, genes activated by HNF4A pre-natally in the presence of TAF4, subsequent TAF4 inactivation leads to diminished PIC formation, but has little effect on HNF4A occupancy of their regulatory elements that persists at post-natal stages. In contrast, TAF4 is required to stably recruit HNF4A to regulatory elements and for PIC formation at post-natal activated genes as both processes are disrupted upon TAF4 inactivation.Our data also define for the first time the full scope of HNF4A in maintaining the integrity of the hepatocyte epithelium acquired during embryogenesis and in activation of the post-natal gene expression programme. In previous studies not all of these functions were observed due to the inappropriate timing of HNF4A inactivation that was either too early or too late to reveal them. While loss of HNF4A function accounts for many aspects of the TAF4 phenotype, we do not exclude that TAF4 may act as a cofactor for other transcription factors, for example RPBJ-NCID involved in bile duct morphogenesis.In addition to the above functional data, biochemical data also support the idea that TAF4 acts as a cofactor for HNF4A. Epitope-tagged HNF4A can precipitate TFIID . We alsoTaf10hep−/− animals die at P35–P38. Upon TAF10 inactivation, recruitment of TBP and TAFs to many promoters is lost but PIC formation was not affected suggesting that transcription persists in the absence of TBP/TFIID. In contrast, we show that TBP  is recruited to promoters of expressed genes, and its recruitment and PIC formation are diminished to comparable extents. Moreover, TAF3 promoter occupancy at expressed genes is less affected. While loss of TFIID integrity compromises TBP occupancy and PIC formation, interaction with H3K4me3 acts to stabilise TAF3 recruitment independently of TBP. We therefore find no evidence for PIC formation and gene expression in the absence of TBP and TAF3 recruitment in the TAF4 mutant hepatocytes.Given the essential role of TAF4 in TFIID core assembly, the lack of TAF4b to compensate for its absence, and the reduced TBP-TAF co-precipitation, it is likely that TFIID integrity is disrupted in mutant hepatocytes, with the residual TBP-TAF co-precipitation reflecting the presence of intact TFIID in the cell types where TAF4 remains expressed. A similar conclusion was drawn when TAF10 that is also essential for TFIID integrity was inactivated in adult liver . TAF10 iTAF4 regulates hepatocyte gene expression by controlling HNF4A occupancy, PIC formation, and Pol II pausing. Expression of subset of embryonic genes is up-regulated in the absence of TAF4 due to decreased Pol II pausing, although it is also possible that changes in RNA stability may also contribute to the observed increase in mRNA abundance. Why TAF4 regulates pausing at this set of genes remains to be determined, although we note that they are enriched in short intron-less genes. Also it has been previously described that TAF7 has a negative effect on CDK9 and BRD4 activity . PerhapsWe show that TAF4 is essential for activation of the post-natal hepatocyte gene expression programme acting as a cofactor for HNF4A. Previous models proposed that activators bind their cognate sites and promote PIC formation via interactions with TAFs. We show in vivo that HNF4A stably occupies a set of functional sites only when accompanied by concomitant TAF4-dependent PIC formation showing that these are mutually dependent events . Many reTaf4alox/lox animals were crossed with Albumin-Cre (Alb-Cre) transgenic mice .Library preparation and mRNA sequencing were performed as previously described . The res2, 60 mM KCl) and treated with MNase  at 37°C for 10 min. The reaction was stopped by addition of EDTA to a final concentration of 20 mM. Chromatin was incubated with 0.3% SDS (5 min on ice) and with 1% Triton X-100 (5 min on ice) and centrifuged at 14,000 rpm. ChIP was performed overnight with 50 μg of chromatin and 5 μg of the following antibodies: anti-Pol II (sc-9001 X), anti-TFIIB (sc-225 X), anti-TFIIE (sc-6935 X), anti-HNF4A (sc-8987 X), anti-CDK9 (sc-8338 X), anti-HNF6 (sc-13050 X), anti-CEBPA (sc-9314 X), anti-FOXA2 (sc-6554 X) from Santa Cruz , anti-TBP (ab28175) from Abcam (Cambridge UK), anti-CTCF (07–729) and anti-H3K4me3 (04–745) from Millipore , anti-TAF3 . ChIP-seq libraries were prepared as previously described and sequenced on the Illumina Hi-seq2500 as single-end 36-base reads (http://bips.u-strasbg.fr/seqminer/) (http://www.r-project.org/) and visualized using ggplot2 package. Genomic region annotation was performed with either seqMINER or GREAT (http://bejerano.stanford.edu/great/public/html/). Overlap between HNF4A-binding sites that are enhanced or depleted in TAF4-mutant liver and CRMs was performed by intersecting the corresponding genomic coordinates.For ChIP-seq, mouse livers, freshly isolated or snap frozen in liquid nitrogen, were homogenized by douncing and fixed with 1% PFA for 10 min and fixing was stopped by adding glycine at a final concentration of 0.125 M. Alternatively, for TAF3 and for TBP ChIP-seq, chromatin was fragmented by MNase I digestion as follows. Fixed nuclei were resuspended in equal volume of MNase buffer   and R  and DTT. Nuclei were washed twice in cold hypotonic buffer followed by centrifugation  and lysed in 50 mM Tris–HCl, pH 7.5, 450 mM NaCl, 0.5% NP40, 5% glycerol for 2 hr on 4°C with constant rotation. Detection was performed using the same antibodies as for ChIP or previously described in house antibodies against TBP and TAFs  following the standard procedures.Livers were fixed at 4°C for 16 hr in 4% paraformaldehyde in phosphate-buffered saline (PBS), washed overnight in PBS, and embedded in paraffin. For immunofluorescence 10 µm sections were treated in a microwave oven in citrate buffer pH 6.0 for 15 min at 150 W. Staining was performed with primary anti-TAF4 (sc-136093) and anti-HNF4A (sc-6556) from Santa Cruz, Claudin3 (ab15102) and TBP (ab51841) from Abcam, Sox9 (AB5535) from Chemicon, anti-aSMA (M0851) from DAKO, TJP1 from Invitrogen  (339100), KI67 from Novocastra  (NCL-KI67P). Nuclei were counterstained with Hoechst. For histological analysis, sections were stained with Hematoxylin and Eosin, Red Oil O, and E. coli BL21 cells were transformed with respective vectors and colonies were used to grow 15 ml cultures at 37°C till the OD600 = 0.4. Protein expression was induced by IPTG and cultures were grown at 25°C overnight. Cells were resuspended in 1.5 ml of lysis buffer  and sonicated. After the centrifugation, the supernatants were incubated with TALON resin for two hours at 4°C with the permanent agitation. The resin was washed twice with 1 ml of ice-cold lysis buffer and resuspended in 25 µl of Laemmli buffer. Samples were analysed by SDS-PAGE with subsequent Coomassie brilliant blue staining.Full length HNF4A and its indicated deletion mutants, the histone-fold containing fragments of human TAF4 (805–1083) and (832–966) and TAF12 (29–161), were cloned into the His-Tag vector pEA-tH and/or the native pCS vector . E. coliTotal RNA was extracted with the RNeasy Mini Kit  following the manufacturer's instructions and treated with RNase-free DNase (Fermentas). RNA (3 μg) was reverse transcribed by using a Maxima Kit . The final product was then diluted 10 times and 2 μl were mixed with forward and reverse primers  and 5 μl of SYBR Green master mix (Qiagen). The real-time PCR reaction was performed by using the LightCycler 1.5 system (Roche). Each cDNA sample was tested at least in triplicate. review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  and 3 reviewers, one of whom is a member of our Board of Reviewing Editors.Thank you for sending your work entitled “TAF4 directs HNF4A promoter occupancy to induce post-natal hepatocyte differentiation” for consideration at The following individuals responsible for the peer review of your submission have agreed to reveal their identity: Michael R Green (Reviewing editor), Robert Roeder (one of the two other reviewers).The Reviewing editor and the other reviewers discussed their comments before we reached this decision, and the Reviewing editor has assembled the following comments to help you prepare a revised submission.This manuscript elaborates a specific TAF4 requirement for liver development and functions that reflects a major contribution to the HNF4a-mediated genomic program. By using a liver-specific TAF4 mutant mouse line, the authors observed several severe liver failures in P12 to P21 mice that led to lethality. RNA-seq analysis suggest that a subset of liver functional genes are deregulated in TAF4 mutant mice. Using genome-wide ChIP-seq assays, the authors further show that TAF4 inactivation diminishes PIC formation and attenuates HNF4a occupancy on a subset of post-natally expressed genes in liver. Finally, in a biochemical analysis the authors show a direct interaction between HNF4a and the TAF4/TAF12 dimer that may explain the impaired HNF4a occupancy of its targets in TAF4 mutant mice.Overall, the results presented in this manuscript provide substantial evidence for the physiological functions of a TAF subunit that is specifically required for HNF4a-controlled gene expression related to liver function. Although previous studies have shown a TAF10 subunit requirement for liver function and TAF coactivator functions in cell-based assays, the current manuscript provides significant new evidence for physiological TAF coactivator functions by showing, first, a TAF4 function in the genome-wide occupancy of a TAF4-interacting activator and, second, a mechanism involving direct interactions.However, the three reviewers have a number of specific concerns and the authors are encouraged to address as many of these as possible with experimentation and/or textual revisions as appropriate.Major specific comments:1) The main conclusion that Taf4 is a cofactor for Hnf4a during liver maturation is not supported by the data provided in this paper. Although the authors show that the Taf4-Taf12 heterodimer interacts with Hnf4a when the recombinant proteins are expressed in E. coli, these data do not support a physiological interaction of these two proteins during liver maturation. Additionally, due to the fact that Hnf4a has been previously shown to directly interact with TBP , and the2) Another explanation for the altered genomic binding locations of Hnf4a in Taf4 depleted livers may be that the loss of Taf4 results in altered genomic locations of other Hnf4a cofactors. Several other cofactors have been identified for Hnf4a, including CBP/p300. It would add to the breadth of the paper, and allow for a more succinct conclusion to be made about the disrupted genomic binding of Hnf4a in the Taf4-/- livers, if analysis was performed to determine whether or not CBP/p300 or other Hnf4a cofactors are lost at Hnf4a binding locations when Taf4 is conditionally ablated.3) In 4) In 5) In 6) In 7) The authors should discuss how a GTF (TAF4) recruits a sequence-specific DNA binding protein (HNF4A). The more general model is that the sequence-specific DNA binding protein recruits the GTF. Likewise, the authors should discuss what might be the basis of occupancy of HNF4A at new sites in the absence of TAF4.8) In 9) In 10) The authors conclude that down-regulation is due to defective PIC formation, while up-regulation of many genes reflects decreased pausing and increased elongating Pol II and CDK9 recruitment. Do the authors have any ideas as to how TAF4 can act in such a dual fashion and the basis by which TAF4 behaves so differently at down and up regulated genes?11) 12) The TAF3 results, although interesting, don't really connect well with the major conclusions of this study, which are TAF4, HNF4A and liver development. This reviewer at least found these to be a distraction. The authors might consider removing these experiments or at least de-emphasizing them by for example moving them to supplemental. 1) The main conclusion that Taf4 is a cofactor for Hnf4a during liver maturation is not supported by the data provided in this paper. Although the authors show that the Taf4-Taf12 heterodimer interacts with Hnf4a when the recombinant proteins are expressed in E. coli, these data do not support a physiological interaction of these two proteins during liver maturation. Additionally, due to the fact that Hnf4a has been previously shown to directly interact with TBP , and the data in this paper show that TBP does not interact with the TFIID complex properly when Taf4 is conditionally knocked out, and TBP is obsolete from the majority of its genomic binding locations in the Taf4 depleted livers, it seems appropriate for the authors to conclude that the mis-localization of Hnf4a at its genomic binding sites in the Taf4 depleted livers results from a secondary effect (improper TFIID assembly which results in a loss of TBP at Hnf4a target genes).The referees raise several points here and we have included some additional data that reinforce the idea that HNF4A-TAF4-TAF12 interactions are also likely to contribute to HNF4A localisation and PIC formation.Firstly, we agree with the referees that the HNF4-TBP interaction may be involved in HNF4A localisation and PIC formation. This is why we illustrated this in our summary model  Another explanation for the altered genomic binding locations of Hnf4a in Taf4 depleted livers may be that the loss of Taf4 results in altered genomic locations of other Hnf4a cofactors. Several other cofactors have been identified for Hnf4a, including CBP/p300. It would add to the breadth of the paper, and allow for a more succinct conclusion to be made about the disrupted genomic binding of Hnf4a in the Taf4-/- livers, if analysis was performed to determine whether or not CBP/p300 or other Hnf4a cofactors are lost at Hnf4a binding locations when Taf4 is conditionally ablated.Based on the suggestion of the referees, we have attempted to perform anti-p300 ChIP-qPCR experiments, but we saw little enrichment even at HNF4A-occupied sites where public ChIPseq data shows that p300 should be present. While this is probably a technical issue that would take some time to resolve, we would like to stress however that in the original manuscript, we showed that Cebpa, Foxa2 and Hnf6 were all depleted along with Hnf4a at CRMs . As it is the activators that recruit the co-activators rather than the co-activators that recruit the activators, it would seem highly unlikely that changes in p300 recruitment are the principal cause of the lost HNF4Aa binding. In addition, our new data showing that TAF4-TAF12 interacts with the HNF4a LBD reinforce the idea that a specific interaction with HNF4A is the important one.3) In, the authors observed a reduction of TSS-bound Pol II (paused) in the up-regulated gene subset. The explanation offered is that TAF4 inactivation increases the recruitment of CDK9 , leading in turn to release of paused Pol II and increased gene expression. However, it also is noted that PIC formation is diminished on those genes . Could the authors provide a possible mechanism for reduced PIC formation leading to enhance CDK9 recruitment and Pol II release?For the moment, we do not have a specific mechanism that would explain this. As it is likely that TFIID integrity is compromised, perhaps the presence of TAF4 or other TAFs at these promoters that is lost in the mutant, has a negative effect on CDK9 recruitment. It has been previously described by the Singer lab that TAF7 has a negative effect on CDK9 and BRD4 activity. Perhaps defective recruitment of TAF7 at these genes due to compromised TFIID integrity would explain the augmented CDK9 recruitment and an increase in its kinase activity would account for the enhanced elongation. We did not discuss this as we have no ChIP-grade TAF7 antibody that allows us to test the idea. Also enhanced elongation is not a general effect, but is limited to a sub-set of genes. We originally investigated whether these promoters had some common feature , but so far we have not identified any common feature of this subset of promoters. We have included a discussion of this in the revised version.4) In, the authors show increased Pol II occupancy for a few up-regulated genes  In, it is noted that TAF4 inactivation globally diminishes the occupancies of TBP, TFIIB, TFIIE and H3K4Me3, but has less effect on TAF3 binding. Is this observed variation in TAF3 binding due to an alternative chromatin fragmentation method used for TAF3 ChIP or is there something unique about TAF3 relative to TFIID-specific TAFs? Was any other TAF analyzed?In fact TAF3 was the not only protein that we analysed by MNaseI digestion. TBP was also analysed in this way. We have corrected the Materials and methods section to clarify this point as it was not correctly described in the original version. The classic sonication method does not work with our anti-TAF3 antibody and this is why MNaseI was used, while for TBP, ChIP is much more efficient with MNaseI than sonication. Thus, it is not the chromatin fragmentation method that accounts for the lesser effect seen with TAF3. We rather propose that the high affinity of TAF3 for H3K4me3, a unique feature of TAF3 relative to other TAFs, accounts for the observed data.6) In, an analysis of HNF4a-enriched sites should be added as well.We have added this additional analysis requested by the referees (7) The authors should discuss how a GTF (TAF4) recruits a sequence-specific DNA binding protein (HNF4A). The more general model is that the sequence-specific DNA binding protein recruits the GTF. Likewise, the authors should discuss what might be the basis of occupancy of HNF4A at new sites in the absence of TAF4.In the Discussion section of the paper, we tried to emphasize that PIC formation and HNF4A binding are mutually dependent events. Our data are consistent with a model where stable binding of HNF4A to TSS proximal CRMs requires interaction with TFIID and PIC formation. Mutual interactions between HNF4A and TFIID stabilise both PIC formation and CRM occupancy, without PIC formation HNF4A does not stably bind to its binding sites. In our data we showed that a majority of sites occupied in absence of TAF4 are not normally occupied either during embryogenesis or in adult liver. As mentioned above, sites enriched in the TAF4 mutant have no specific location although a small number are associated with upregulated genes. This small set perhaps corresponds to sites that are occupied during embryogenesis and normally lost in neonatal liver, but not in the mutant. The vast majority of sites are however not in this category. It is more likely that there is a more general disorganisation of the chromatin landscape in the mutant liver and that this allows accessibility to sites that are not accessible to HNF4A.8) In, what is the criterion used  for association between HNF4A and a gene?In 9) Inthe authors need to explain in the Results section how paused pol II downstream of the transcription start-site is distinguished from the pol II of the PIC.We do not understand exactly what the referees are referring to here. It is now well established that ‘paused’ Pol II accumulates around 50 nucleotides downstream of the TSS at a large number of promoters. This is what is visualized in the ChIP-seq experiments.10) The authors conclude that down-regulation is due to defective PIC formation, while up-regulation of many genes reflects decreased pausing and increased elongating Pol II and CDK9 recruitment. Do the authors have any ideas as to how TAF4 can act in such a dual fashion and the basis by which TAF4 behaves so differently at down and up regulated genes?This is related to comments 3 and 7. Please see discussion in reply to these comments.11). Have the authors performed a similar experiment measuring CDK9 recruitment for up-regulated genes?I presume that the referees are referring to ‘down-regulated’ genes, as up-regulated genes were already shown in the original manuscript. Yes, we had performed these experiments and there is no enhanced CDK9 recruitment at down-regulated genes. We have now included one example in 12) The TAF3 results, although interesting, don't really connect well with the major conclusions of this study, which are TAF4, HNF4A and liver development. This reviewer at least found these to be a distraction. The authors might consider removing these experiments or at least de-emphasizing them by for example moving them to supplemental.We fully agree with the comment of the referees: the TAF3 data are interesting but not central to the story. We have therefore moved these data into the supplemental section, new


Ets2 and Elk3, are themselves regulated by SCC-SC super-enhancers suggesting a cooperative feed-forward loop. Malignant progression requires these genes, whose knockdown severely impairs tumor growth and prohibits progression from benign papillomas to SCCs. ETS2-deficiency disrupts the SCC-SC super-enhancer landscape and downstream cancer genes while ETS2-overactivation in epidermal-SCs induces hyperproliferation and SCC super-enhancer-associated genes Fos, Junb and Klf5. Together, our findings unearth an essential regulatory network required for the SCC-SC chromatin landscape and unveil its importance in malignant progression.Tumor-initiating stem cells (SCs) exhibit distinct patterns of transcription factors and gene expression compared to healthy counterparts. Here, we show that dramatic shifts in large open-chromatin domain (super-enhancer) landscapes underlie these differences and reflect tumor microenvironment. By in vivo super-enhancer and transcriptional profiling, we uncover a dynamic cancer-specific epigenetic network selectively enriched for binding motifs of a transcription factor cohort expressed in squamous cell carcinoma SCs (SCC-SCs). Many of their genes, including DOI:http://dx.doi.org/10.7554/eLife.10870.001 Many cancers contain a mixture of different types of cells. Of these, cells known as cancer stem cells can form new tumours and drive the growth and spread of the cancer around the body. A central question is how cancer stem cells differ from healthy adult stem cells. Recent evidence suggests that, in addition to having genetic mutations, cancer stem cells live in a very different environment to other cells within the tumour. This 'microenvironment'also has a major impact on how these cells behave compared to normal stem cells. Together, the genetic and environmental differences profoundly change the way genes are expressed in the cancer cells.In 2013, a group of researchers identified regions of DNA called super-enhancers. These regions are long stretches of DNA that proteins called transcription factors can interact with to coordinate the expression of nearby genes to alter the production of certain proteins. Super-enhancers contain several transcription factor-binding sites that are close to each other with the different sites being associated with transcription factors that are only active in specific types of cells. Furthermore, super-enhancers are often self-regulatory, meaning that the binding of transcription factors to a super-enhancer can lead to an increase in the expression of the genes that encode the same transcription factors.Yang, Schramek et al. have now identified the super-enhancers in a skin cancer called squamous cell carcinoma and showed that they differ dramatically from the super-enhancers of normal skin stem cells. Their experiments show that the active super-enhancers in cancer stem cells are associated with a very different set of genes that are highly and often specifically expressed in cancer stem cells. In the cancer stem cells, a transcription factor called ETS2 binds to the super-enhancers and reprograms the expression of genes to promote the development of cancer. Yang, Schramek et al. also show that over-active ETS2 is a major driver of squamous cell carcinoma. Furthermore, ETS2 also increases the expression of genes that cause inflammation and promote the growth of cancers.Yang, Schramek et al.’s findings reveal a new regulatory network that governs the expression of genes involved in cancer. Furthermore, the experiments show that high levels of ETS2 are linked with poor outcomes for patients with head and neck squamous cell carcinoma, which is one of the most life-threatening cancers world-wide. In the future, these findings might lead to the development of new therapies to treat these cancers.DOI:http://dx.doi.org/10.7554/eLife.10870.002 Stem cells (SCs) have the capacity to self-renew and to generate and repair tissues. Advances in genome technologies provide the means to not only comprehensively analyze transcriptional profiles of SCs but also map their epigenetic landscape on a global level. Studies on cultured embryonic stem cells (ESCs) have shown that a special set of large open-chromatin domains, so-called super-enhancers (SEs), control expression of genes important to ESC behavior . Like tyStudies on a variety of tissue cell lines have shown that another key feature of SEs is a high density of sequence motifs for cell stage-specific transcription factors (TFs). This allows for their cooperative binding, thereby rendering SE-regulated genes particularly sensitive to the key TF cohort. Moreover, the genes encoding lineage-specific TFs often themselves harbor SEs resulting in a stable feed-forward loop to fuel and maintain the lineage .Mice devote much of their tissue-generating energy to making hair follicles (HFs), each of which possesses a compartment of multipotent SCs that fuel HF regeneration and hair growth. Additionally, hair regeneration is governed by cyclical bouts of SC activity where HFs are either at rest (telogen) or actively regenerating (anagen). The ability to purify large quantities of SCs directly from their native microenvironment (‘niche’) makes the HF one of the few systems where in vivo chromatin dynamics can be studied in an adult tissue SC population. Such studies on purified HF-SCs show that although their TFs are largely distinct from those of ESCs, many of the basic features of SEs are displayed by HF-SCs in their native tissue niche .Studies on SC populations isolated from adult tissues have also yielded new insights into SE dynamics. Notably, most of the master regulators of HF-SCs bind within smaller chromatin domains (<3 kb) of SEs termed ‘epicenters’, which are also enriched for Mediator and for H3K27ac . AdditioPerhaps, most intriguing is that even though HF-SCs still possess stemness outside their native niche, for example in culture or in wound-repair, they change their SE landscape dramatically. Mechanistically, this plasticity of remodeling can be traced to a dramatic reduction of HF-SC TFs, resulting in a decommissioning of most in vivo SEs with a new set of SEs gained in vitro . In a reCancer can be viewed as a disease of lost cell identity. The cellular origin of tumor-initiating, so-called ‘cancer SCs’ may be a result of arresting SC maturation or of dedifferentiation of a progenitor lineage, endowing the incipient tumor cell with the potential to self-renew and fuel the cancer. Although largely limited to studies on self-renewing cancer cell lines in vitro and their normal whole tissue (e.g. MCF7 breast cancer cell line and mammary epithelium), increasing evidence underscores the importance of SEs in cancers .Recent studies suggest that the transcriptional profile and behavior of tumor-initiating SCs are highly sensitive to their tumor-microenvironment, which is markedly distinct from that of their normal counterparts . This maHere, we specifically test this hypothesis, focusing on skin squamous cell carcinoma (SCC), which is one of the most common and rapidly rising cancers world-wide . More brHras, Kras or Rras2  (G12V in combination with loss of TGFβ receptor II (TGFβRII) results in invasive SCCs, which can metastasize  encoding a key transmembrane receptor for TGFβ signaling, and infected them with a non-integrating adenovirus expressing a Cre-GFP recombinase. After fluorescence-activated cell sorting (FACS), purified cells were then stably transduced with an integrating retrovirus expressing HRasG12V  . HRasG12astasize . We therNude mice, they efficiently formed SCC tumors, typified by hyperproliferation, pyknotic nuclei, a discontinuous basement membrane and signs of invasion into the surrounding stroma  (43%) and distal elements, considered enhancers (57%) . A smallWhen compared to the SEs of HF-SCs , that ishighα6highβ1high SCC-SC population, we assigned SE-associated genes on the basis of 1) their proximity to an SCC-SC SE; 2) their active transcription in SCC-SCs; and 3) their strict correlation between expression pattern and the presence of their putative SE not only in SCC-SCs but also in HF-SCs and transit-amplifying progeny.Enhancers control adjacent genes by looping to their promoters, with most of these interactions occurring within <50 kb . More thMyc, and also genes associated with SCCs, for example Cd44  of SE-associated genes were higher than those of TE-associated genes , in agreMyc was particularly interesting, in that human MYC has been shown to be associated with an SE in a variety of cultured cancer cell lines  analysis categorized SE-associated genes in SCC-SCs as wound-responsive, stress-responsive, TF binding, kinase targets or actin binding, according to molecular function and biological process . Myc wasll lines . In addi and Gsr . Many of and Gsr . These fNext, we sought to identify the key TFs involved in regulating the SE landscape in SCC-SCs. An unbiased motif analysis of SCC-SC SEs revealed a distinct set of putative TF binding sites that were largely non-overlapping with those found in the SEs of HF-SCs and TACs  Figure . ETS wasFos, Junb, Nfe2l2), three KLF motif genes , two ETS motif genes , and Hoxb7  progenitors and quiescent HF-SCs, and was only transcribed at low levels in proliferative progenitors during the growth phase of the hair cycle. By contrast,  nuclear  and 3B.1Elk3 mRNA and protein levels by >70%  control shRNAs, each njection . Moreovenjection . By contnjection .Ets2 gene was more broadly and abundantly transcribed in progenitors, unlike Elk3. Based on these data, it was equally important to examine the consequences of Ets2 loss of function on SCC tumorigenesis. To do so, we selected two powerful hairpins, which knocked down Ets2 transcription and protein production by >65%  ETS2 protein was only seen in SCCs and not in normal progenitors, the  by >65% . Importaent mice . Of addiEts2 #649 or #985, tumor growth was markedly reduced relative to control virus  and then injected subcutaneously into host recipient mice, the Ets2_mut refractory to shRNA knockdown rescued the effects of Ets2-shRNA. As shown in Overall, the impeding effects on SCC tumor growth and morphology were seen irrespective of whether we knocked down ts2-cDNA . When SCPreviously, we showed that for HF-SCs, sustained levels of SOX9 were critical for the binding of other HF-SC TFs to SE epicenters . Given tIf ETS factors function in SE dynamics, then elevating the levels of active ETS factors in normal skin progenitors might be expected to induce some of the phenotypic consequences of SCC progression, including hyperproliferation and the expression of other SCC-TFs or SCC genes that are regulated by SEs. To test this hypothesis, we engineered a phosphomimetic T72D version of ETS2, thus bypassing the need for HRas/MAPK to make this modification . Since EWith these controls, we then proceeded to inject the high titer lentivirus into the amniotic sacs of E9.5 K14-rtTA mouse embryos in utero. As previously shown, this strategy selectively and efficiently transduces the single layer of surface epithelial progenitors of the embryo, particularly within the head region . Within In vivo mice in which overexpression of wild-type ETS2 was induced in the skin epithelium did not exhibit overt phenotypic perturbations, and by immunofluorescence, epidermal differentiation appeared normal . By contNotably, T72D-ETS2 activated epithelium was also typified by expression of AP1 factors FOS and JUNB, as well as ELK3 . IntriguEts2 knockout mice, whose epidermal homeostasis appeared normal , Cxcl2 (>50X), and Elk3 (4X) ranked among the most differentially expressed.While our findings thus far underscored the importance of SEs and ETS proteins, it was also important to test the functional relevance of SE dynamics. To do so, we first determined the transcriptional consequences of selectively inducing constitutively active ETS2 in the skin epithelium of postnatal mice. Interestingly, T72D-ETS2 not only generated SCC-like hyperproliferation and invaginations, but also induced and/or up-regulated many genes which we had found to be strongly expressed in SCCs . Among t+Sca1+ basal progenitors from the skin epidermis of our mice at 4 weeks after ETS induction, and then subjected these and control epidermal cells to ChiP-seq analysis for the SE mark H3K27ac. Remarkably, 46% of the SEs found in SCC-SCs overlapped with those of T72D-ETS overexpressing skin epidermis with a genome-wide Pearson Correlation Coefficient of 0.72 -mediated repression, typified by a trimethylation mark at this same residue. In this regard, it was intriguing that a small number of genes, including genitors , but thegenitors . Correspgenitors .10.7554/Cxcl1 and Cxcl2 locus, as the encoded Cxcl1 and Cxcl2 cytokines can act in paracrine fashion to recruit neutrophils and activate angiogenesis, features which promote tumor progression   . Upon an8 (IL-8) . Taken tSCCs are the most common cancers world-wide, occurring most frequently on the skin and affecting millions of people each year. Being visible, skin SCCs are typically treated early and mortality is low. However, SCCs can also arise in the lung, breast, esophagus, cervix, and head and neck, where they are associated with high risk of metastasis and drug resistance. Understanding the molecular complexities that underlie the tumor-initiating SCs within SCC cancers is therefore of paramount importance in developing new and improved diagnostic and therapeutic tools to establish new treatments.Like HF-SCs and EpiSCs from which SCC-SCs can derive , SCC-SCsWe profiled the SEs of SCC-SCs and compared them to their wild-type counterparts in order to gain a better understanding of the epigenetic rewiring that might be associated with SCC transcription. Since the chromatin landscape in general, and SEs in particular, are highly sensitive to their microenvironment , it was In previous studies on SCs in which chromatin landscapes regulated by master regulators have been mapped, ChIP-seq analysis of the known master TFs has preceded subsequent SE analysis. Thus, with cultured ESCs, ChIP-seq for the established pluripotency regulators SOX2, OCT4, NANOG, and KLF4, was already available when ensuing SE analyses revealed that the pluripotency factors bind within these open chromatin domains . SimilarFor SCC-SCs, global ChIP-seq chromatin mapping in vivohas not been performed, due to the relative paucity of tumor tissue relative to normal skin. Moreover, the abundance of keratin and resilience of the epidermal plasma membrane poses technical hurdles for newer ATAC-seq methods which can be performed with fewer cell numbers and allow TF mapping for some cell types . CompounTo approach the problem, we identified the TFs whose expression is upregulated in SCC-SCs and which display putative TF binding sites within the epicenters of dense H3K27ac peaks of the majority of SCC-SC-specific SEs. As learned from analyses of ESCs and HF-SCs, an additional frequent, albeit not absolute, feature of SC master regulators is that their genes are often regulated by SEs themselves, thereby establishing a feed-forward loop for maintaining the SC state . By SE pElk3 and Ets2 with SEs, begged for functional studies. Indeed, our analyses provide compelling evidence that these factors drive hyperproliferation and SCC progression. Our added finding that high ELK3 and ETS2 expression correlates with poor prognosis in human SCCs fuels the importance of this family of proteins in these cancers.Several lines of evidence suggest that our strategy was successful. First and foremost was the finding that SOX binding sites were present in >70% of all SCC-SC SEs, a feature predicted from SOX2’s functional role in SCCs . AdditioFos, Junb and Klf5 are associated with SCC-SC SEs which contain AP1, ETS and KLF binding motifs, these findings underscore the physiological relevance of these factors not only in SCC oncogenesis but also in orchestrating the chromatin dynamics of SCC-SCs.The role of ETS proteins is particularly intriguing given that their levels matter not only in tumorigenesis but also in maintaining SCC-SC master regulators. Thus when ETS2 was reduced in SCC-SCs, KLF5 and SOX2 were also absent from the resulting cellular masses, and when constitutively active ETS2 was induced in normal epidermis of juvenile mice, the epidermis acquired marked features of hyperproliferation and invasion, accompanied by upregulation/induction of FOS, JUNB and KLF5 and a shift in SE dynamics from one of normal skin progenitors to one of malignant transformation. When coupled with the fact that Our results are particularly intriguing in that phosphorylation of ETS2 is known to be regulated by Ras/MAPK signaling . Indeed,Given the well-established links between AP1 family members, Ras/MAPK and cancer , the preFos, Junb, Ets2, and Elk3, but also Myc, Src, Mapk6, Map2k2, Cd44, and Tgfa. Also present on this list are HMGA2, RUNX1 and FOXG1, which are critical TFs for self-renewal of SCC-SCs and other cancer models  were used for the purification of HF SCs. Female CD1 mice transgenic for krt14-H2B-GFP  were use2 floxed  mice to Tgfbr2 floxed were cultured on 3T3-S2 feeder layer in 0.05 mM Ca++ E-media supplemented with 15% serum . The cBioPortal for Cancer Genomics developed and maintained by the Computational Biology Center at Memorial Sloan-Kettering Cancer Center was used to mine the publicly available TCGA dataset on HNSCC  in Nude mice. Tumor size was measured every three days and calculated using the formula 4/3π × L/2 × W/2 × D/2.For allograft transplantation, 1.0 × 10Tumors were dissected from mice, and normal skin, blood vessels and connective tissue were removed. Tumor tissues were minced and treated with 0.25% collagenase  in HBSS  for 20 min at 37°C with shaking. After washing with cold PBS, the tissues were treated with 0.25% trypsin for 10 min at 37°C, and then were washed with PBS containing 5% of fetal bovine serum (FBS). The cell suspensions were filtered through 70-μm and 45-μm strainers. Isolation of HF-SCs and Epi-SCs from adult mice back skins was done as previously described , Briefly7 cells were used and for nano-ChIP-seq, 1~2 × 105 cells were used. Cells were sorted by FACS. Sorted cells were cross-linked in fresh 1% (wt/vol) formaldehyde solution for 10 min at room temperature followed by adding one-tenth volume of 2.5 M Glycine to quench formaldehyde. Cells were rinsed twice with PBS, flash frozen in liquid nitrogen and stored at -80°C prior to use. Cells were resuspended and lysed in lysis buffers. To solublilize and shear cross-linked DNAs, lysates were subjected to a Bioruptor Sonicator  according to a 30X regimen of 30 s sonication followed by 60 s rest. The resulting whole-cell extract was incubated overnight at 4°C with Dynabeads Protein G magnetic beads  which had been pre-incubated with anti-H3K27ac  antibody. After ChIP, samples were washed with low salt, high salt, LiCl and Tris-EDTA buffer for 10 min. Bound complexes were eluted and crosslinking was reversed by overnight incubation at 65°C. Whole cell extract DAN was also treated for crosslink reversal.Immunoprecipitations were performed on FACS-sorted populations from tumors and nano-ChIP-seq was done as described. For eacGTATCCGGATGTNNNNNNNNN-3’, Primer 2: 5′-GACATGTATCCGGATGT-3′). After BciVI digestion, the ChIP DNA was ligated with Illumina adapters and amplified, and fragment sizes between 200-700bp were selected by electrophoresis. The DNA was gel-purified and sequencing was performed on the Illumina HiSEq 2500 Sequencer following manufacturer protocols. ChIP-seq reads were aligned to them mouse genome  using Bowtie aligner  in the ligation step. A subsequent PCR step with 25 amplification cycles added the additional Solexa linker sequence to the fragments to prepare them for annealing to the Genome analyzer flow cell. After amplification, a narrow range of fragment sizes between 150–300 bp was selected by separation on a 2% agarose gel and the DNA was gel-purified and diluted to 10 nM for loading on the flow cell. Nano-ChIP-seq was carried out similarly, except that ChIP DNA was primed with Sequenase enzyme using the primer 1 that contains universal sequence, the BciVI restriction site and random 9-mer and then amplified using primer 2 that contains universal sequence , anti-myc antibody (Abcam) and normal rabbit IgG  were used. The purified ChIP DNAs were mixed with indicated primers and SYBR green PCR Master Mix (Sigma), and qRT-PCR was performed on an Applied Biosystems 7900HT Fast Real-Time PCR system. The following primer sequences were used (5’ to 3’):Cxcl1/2 SE_epicenter forward: CAACATGCCTAGCCCGTGAGTC,Cxcl1/2 SE_epicenter reverse: GTGCCCTGTTTCACAGATAGAGGCElk3 SE_epicenter forward: CGTCCATTCTCTCCCCTTTTCTAGC,Elk3 SE_epicenter reverse: CATGATTGGCAGTGGAGTATCGAGCEts2 SE_epicenter forward: CAATGGCTTGGAGATCCCCGAC,Ets2 SE_epicenter reverse: CAGGGTCACCAGTGAGTCACAGFam49b SE_epicenter forward: CCACGGAACCTGAGAATGAAGCC,Fam49b SE_epicenter reverse: GCTTCAACTGACTGAACTCCCAGGIl1a/b SE_epicenter forward:, CAGAGGGTGGCACAGGATAGACAG,Il1a/b SE_epicenter reverse: CAGTGTCCTGCCCAGTCATCTGPthlh SE_epicenter forward:, CTGAGCTACACCCTTCCACTTCAC,Pthlh SE_epicenter reverse: GTCTTCATTCCTCTGAGCCAATGTGCNegative control region forward: CATGCAAGCATCACCAACAAAGTA,Negative control region reverse: CCATGGAACTGGGACCTTCTTCFACS-isolated cells and cultured cells were directly lysed into TRIzol LS . Total RNA was purified using the Direct-zol RNA MiniPrep kit  per manufacturer’s instructions. For RNA-Seq, quality of the RNA for sequencing was determined using an Agilent 2100 Bioanalyzer; all samples used had RNA integrity numbers >9. Library preparation using the Illumina TrueSeq mRNA sample preparation kit was performed at the Weill Cornell Medical College Genomic Core facility , and RNAs were single-end sequenced on Illumina HiSeq 2000 machines. Alignment of reads was done using Tophat with the mm9 build of the mouse genome. Transcript assembly and differential expression was determined using Cufflinks with Refseq mRNAs to guide assembly . AnalysimPpib2 forward: GTGAGCGCTTCCCAGATGAGA,mPpib2 reverse: TGCCGGAGTCGACAATGATGmHprt forward: GATCAGTCAACGGGGGACATAAA,mHprt reverse: CTTGCGCTCATCTTAGGCTTTGTmGapdh forward: GTCGTGGAGTCTACTGGTGTCTTCAC,mGapdh reverse: GTTGTCATATTTCTCGTGGTTCACACCCmEts2 forward: GACGGGGGATGGATGGGAGTTCAAG,mEts2 reverse: AGCCCAGCAAGTTCTGCAGGTCACAmElk3 forward: TCCTCACGCGGTAGAGATCAG,mElk3 reverse: GTGGAGGTACTCGTTGCGGmCxcr2 forward: TGTTCTGCTACGGGTTCACACTG,mCxcr2 reverse: GCGGCGCTCACAGGTCTCmCxcl1 forward: CCACACTCAAGAATGGTCGC,mCxcl1 reverse: TCTCCGTTACTTGGGGACACmCxcl2 forward: CGGTCAAAAAGTTTGCCTTG,mCxcl2 reverse: TCCAGGTCAGTTAGCCTTGCFor immunofluorescence microscopy of tumor sections, dissected tumors were fixed with 1% PFA in PBS for 1 hr at 4°C, washed with PBS, incubated with 30% sucrose overnight at 4°C, and embedded in OCT . For telogen, anagen and phosphomimic Ets2 (T72D) overexpressed skin, tissues were harvested and embedded in OCT. Cryosections were cut at a thickness of 10 μm on a Leica cryostat and mounted on SuperFrost Plus slides (VWR). Sections were blocked for 1 hr in blocking buffer . Primary antibodies were diluted in blocking buffer and incubated at 4°C overnight. The following primary antibodies were used: ETS2 , Phospho-ETS2 pThr72 , ELK3 , KLF5 , SOX2 , Phospho-NFkB p65 pSer276 , FOS , Integrin β4 , GFP , pSmad2 , CD34 , K6 , K5 , K10 , Laminin5 , CXCR2 , Loricrin , CD31 , and Ki67 . After washing with PBS, sections were treated for 1 hr at room temperature with secondary antibodies conjugated with Alexa 488, RRX, or Alexa 647 (Life Technologies). Slides were washed, counterstained with 4’6’-diamidino-2-phenilindole (DAPI), and mounted in Prolong Gold (Life Technologies). Images were acquired with an Axio Observer.Z1 epifluorescence microscope equipped with a Hamamatsu ORCA-ER camera , and with an ApoTome.2  slider that reduces the light scatter in the fluorescent samples, using 20X objective, controlled by Zen software (Carl Zeiss). Z stacks were projected and RGB images were assembled using ImageJ. Panels were labelled in Adobe Illustrator CS5.Immunohistochemistry was performed as previously described . BrieflyTo generate the phosphomimic Ets2 (T72D) expression construct, Ets2 cDNA was PCR amplified and 72 threonine residue was mutated to glutamate by site-directed mutagenesis. Final PCR product was nserted into the LV-TRE-PGK-H2BmRFP1 construct. The resulting LV-TRE-mycEts2(T72D)-PGK-H2BmRFP was used for in utero injections.5 cells per well and incubated with viruses in the presence of polybrene (20 μg/ml) for 30 min, and then plates were spun at 1100 g for 30 min at 37°C in a Thermo IEC CL40R centrifuge. Infected cells were selected with puromycin. For in vivo lentiviral transduction, viral supernatant was filtered (0.45-μm filter) and concentrated by ultracentrifugation. Final viral particle was resuspended in viral resuspension buffer  and 1 or 0.5 μl was in utero injected into E9.5 embryos.Production of VSV-G pseudotyped lentivirus was performed by calcium phosphate transfection of 293FT cells (Invitrogen) with pLKO.1 and helper plasmids pMD2.G and psPAX2 . Viral supernatant was collected 46 hr after transfection and filtered through a 0.45-μm filter. For lentiviral infections in culture, cells were plated in 6-well plate at 1.0 × 10For knockdown experiments, we used clones from the Broad Institute’s Mission TRC mouse library. We tested the knockdown efficiency of 5–10 independent shRNAs for each gene and used the following clones and target sequence:Ets2 , Elk3 , Cxcr2 .The scramble shRNA , Data were analyzed and statistics performed using unpaired two-tailed Student’s t-test in Prism6 . Significant differences between two groups were noted by asterisks or actual p values. Quantification data were presented in mean value ± SEM or in box and whisker plots with the dimensions of the box encompassing the 25th–75th percentile, the horizontal bar representing the median, and the error bars representing minimum and maximum values.ChIPseq and RNAseq databases were deposited in GEO (Accession #GSE72147). review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see eLife. Your manuscript has been reviewed by two experts in the field and by a member of the Board of Reviewing Editors (BRE). We have appended the detailed reviews for you at the bottom of this letter.Thank you for submitting your study titled, "ETS family of transcriptional regulators drive chromatin dynamic and malignancies in squamous cell carcinomas" for consideration by eLife.As you can see, the reviewers and the BRE member find the study of interest to the journal and are in agreement that the initial profiling of HF-SC's and SCC-SC's for histone modifications are interesting. However, the reviewers unanimously agree that the lack of genome-wide data testing whether the identified transcription factors are actually acting by regulating super enhancers under growth and malignancy conditions has lessened their enthusiasm for the manuscript. We would be interested in a revised study if you have performed these control experiments and have the genome-wide data and the analyses available so that they can be included in a revised manuscript. In this case we, would be happy to consider such a revised manuscript. Otherwise, we feel that the requested studies will take much longer than allowed for a revised submission at Reviewer #1:Recently super enhancers have been revealed as critical cis-regulatory elements to maintain cell fate as well as to determine cell lineages. A role of super enhancers in cancer cells has not been well characterized. In this work, Yang and colleagues using squamous cell carcinoma (SCC) to interrogate a role of super enhancers in cancer cells. Overall this is an interesting paper with identification of ETS transcript factor family in SCC, which is subject to the regulation by super enhancers. Furthermore, the ETS TF associated super enhancer is highly correlated with development of SCC and is more specific for SCC but not to their "normal" counterpart HF-SCs. This ETS binding super enhancer also induced a positive forward loop of CXCL1/2 with their corresponding receptors, reflecting a feature of tumor microenvironment. Their method of prospecting for genes involved in various disease states using SE's and binding motifs could prove very useful. All these are novel findings. However, their conclusions on the relevance of SE's still require direct evidence.Major concern:Given the fact that super enhancers are so implied throughout the paper, and indeed even in the title, I find it odd that the chromatin landscape isn't examined even once after any of their treatments. Aside from the initial profiling of HF-SC's and SCC-SC's, neither histone modifications nor occupancy of TFs reported as SE regulators are ever explored. This could have been done after ELK3, ETS2, or CXCR2 knockdown, but instead they rely very heavily on the very tenuous assumption that because they have binding sites, and their genes are regulated by SE's, that any effects of their treatments must directly involve SE's. Given the pleiotropic effects any of these targets could have, relying solely on phenotypic outcome to imply a specific mechanism of action seems odd.Reviewer #2:Cxcl1 and Cxcl2. Currently, the relationship between supper-enhancer dynamics and ETS family proteins is uncertain.In this manuscript, the authors did a comparison study on super-enhancers in squamous cell carcinoma stem cells and hair follicles stem cells. Based on the bioinformatics analysis on the H3K27ac ChIP-seq data and RNA-seq data, they identified both known and new cancer stem cell specific transcription factors under the super-enhancers. They functionally studied ETS family factors by both knocking down and ORF rescue experiments, and the ETS family factors played significant roles in driving squamous cell carcinoma stem cells. However, there is a lack of solid biological evidence that the ETS factors are actually regulating super-enhancers and that feedback on super-enhancers regulates other factors like Major concerns:1) The authors performed H3K27ac ChIP-seq analysis on SCC-SC in comparison with the one in HF-SC, and identified cancer stem cell specific SEs and SEs associating genes. To better understand the specificity of super-enhancers in cancer stem cells, the authors should include one more SCC sample control.Elk3 and Ets2 in tumorigenesis by knocking down and cDNA rescue, which cannot address the initial question. A correct experiment is Elk3 ChIP-seq and Ets3 ChIP-seq. Since the authors also appealed that they cannot perform ChIP-seq on these two factors due to the limitation of cancer tissues, they should change this sentence.2) In subheading “SE-associated ETS TFs constitute cancer vulnerabilities within SCCs”, the authors wrote: "Our ChIP-seq analyses showed that genes encoding both ELK3 and ETS2 were governed by super-enhancers. Given that both of these TFs are known to bind to ETS sequence motifs, we wondered whether they might both participate in governing super-enhancer dynamics." But, the follow up experiments are all on the functional study of 3) The subtitle "Testing the physiological significance of super-enhancer dynamics in SCCs" was over-claimed, please change it accordingly to the data.Elk3 transcription was knocked down by >90%, while in 4) In paragraph two of the subsection “SE-associated ETS TFs constitute cancer vulnerabilities within SCCs”, the authors claimed Ets2 transcription was knocked down by 80-90%, while, in 5) Similarly, in the fourth paragraph of the aforementioned section, the authors claimed Elk3 and Ets2 participate in governing super-enhancer dynamics, but turned out to test the functional significance of them. I would suggest changing the first two sentences to focus more on their function.6) In "SE-associated ETS TFs constitute cancer vulnerabilities within SCC", the authors started from the purpose to explore whether eLife. It should be noted that the existence of a binding motif does not necessarily indicate the binding of a transcription factor. The regulation of the recruitment of transcription factors has been shown by many studies.7) The title of the paper concludes that ETS family transcriptional regulators drive chromatin dynamics. However, in the paper, due to the difficulties to profile global chromatin states by ChIP-seq, no direct proof can be found to fully support this conclusion. Without direct evidence to support the major conclusion of the paper it is not of sufficient impact for  Reviewer #1:Major concern:Given the fact that super enhancers are so implied throughout the paper, and indeed even in the title, I find it odd that the chromatin landscape isn't examined even once after any of their treatments. Aside from the initial profiling of HF-SC's and SCC-SC's, neither histone modifications nor occupancy of TFs reported as SE regulators are ever explored. This could have been done after ELK3, ETS2, or CXCR2 knockdown, but instead they rely very heavily on the very tenuous assumption that because they have binding sites, and their genes are regulated by SE's, that any effects of their treatments must directly involve SE's. Given the pleiotropic effects any of these targets could have, relying solely on phenotypic outcome to imply a specific mechanism of action seems odd.We agree with the reviewer and have addressed histone modification as well as TF occupancy. Most significantly, we carried out in vivo RNA-seq and H3K27ac ChiP-seq experiments on purified skin basal epidermal control progenitors and progenitors following Doxy-induction of skin epidermis to induce a phosphomimetic super-activated form of ETS2, which normally requires oncogenic HRas-MAP kinase for this threonine phosphorylation. Not only does the epidermis transform into an SCC-like state, but at the transcriptional level, many of the genes upregulated in SCC-SCs are now elevated in the ETS skin progenitors. At the level of chromatin landscaping, this not only includes the SE-regulated genes, but in fact these genes now acquire the chromatin remodeling and super-enhancer acquisition that we observed in SCC-SCs. Finally, although the numbers of cells required for ETS ChIP-seq are still prohibitive, as are the numbers of cells for ETS2 knock-down tumors, we were successful in carrying out ETS2 ChiP-qPCR with a number of SE-regulated genes from these cells purified in vivo.Cxcl1, Cxcl2 and Elk3 ranked among the highest upregulated genes, analogous to what we had seen in SCCs  The authors performed H3K27ac ChIP-seq analysis on SCC-SC in comparison with the one in HF-SC, and identified cancer stem cell specific SEs and SEs associating genes. To better understand the specificity of super-enhancers in cancer stem cells, the authors should include one more SCC sample control.did perform the CHIP-seq experiments and the analysis in two completely independent experiments. Moreover, every duplicate was a pool of several tumors, which was necessary as we had to FACS-purify 20 million (!) cancer stem cells for a single CHIP experiment. Importantly, the duplicates showed a robust Pearson correlation coefficient of genome-wide read densities of r>0.89  In subheading “SE-associated ETS TFs constitute cancer vulnerabilities within SCCs”, the authors wrote: "Our ChIP-seq analyses showed that genes encoding both ELK3 and ETS2 were governed by super-enhancers. Given that both of these TFs are known to bind to ETS sequence motifs, we wondered whether they might both participate in governing super-enhancer dynamics." But, the follow up experiments are all on the functional study of Elk3 and Ets2 in tumorigenesis by knocking down and cDNA rescue, which cannot address the initial question. A correct experiment is Elk3 ChIP-seq and Ets3 ChIP-seq. Since the authors also appealed that they cannot perform ChIP-seq on these two factors due to the limitation of cancer tissues, they should change this sentence.Cxcl1/2, Ets2 and Il1b  The subtitle "Testing the physiological significance of super-enhancer dynamics in SCCs" was over-claimed, please change it accordingly to the data.We changed this subheading to “Testing the physiological significance of ETS2 in super-enhancer dynamics” as we now have provided functional data showing that ETS2 is required for maintenance and in sufficient to induce CSC-SE in otherwise normal skin epithelium.4) In paragraph two of the subsection “SE-associated ETS TFs constitute cancer vulnerabilities within SCCs”, the authors claimed Elk3 transcription was knocked down by >90%, while in We apologize and have changed it to >70% in the text, although we also now add very nice Western blots to show efficiency.5) Similarly, in the fourth paragraph of the aforementioned section, the authors claimed Ets2 transcription was knocked down by 80-90%, while, in We apologize and have changed it to >65% in the text, although we add nice Western Blots to show the efficiency.6) In "SE-associated ETS TFs constitute cancer vulnerabilities within SCC", the authors started from the purpose to explore whether Elk3 and Ets2 participate in governing super-enhancer dynamics, but turned out to test the functional significance of them. I would suggest changing the first two sentences to focus more on their function.We completely agree and have removed the second sentence: “Given that both of these TFs are known to bind to ETS sequence motifs, we wondered whether they might both participate in governing super-enhancer dynamics. To test this possibility,” and changed it to: “To test their functional relevance, we began by focusing on ELK3…”.7) The title of the paper concludes that ETS family transcriptional regulators drive chromatin dynamics. However, in the paper, due to the difficulties to profile global chromatin states by ChIP-seq, no direct proof can be found to fully support this conclusion. Without direct evidence to support the major conclusion of the paper it is not of sufficient impact for eLife. It should be noted that the existence of a binding motif does not necessarily indicate the binding of a transcription factor. The regulation of the recruitment of transcription factors has been shown by many studies.We have now added genetic proof that ETS2 indeed regulates global chromatin dynamics in CSC and would like to refer the reviewer to the new To further validate our ETS2 overexpression model, we now also added data showing that expression of phosphomimetic constitutive-active ETS2 but not wild-type ETS2 induces hyperproliferation and marked epidermal thickening and invaginations. In addition we also added data showing that constitutive-active ETS2 also increased CD11b+ inflammatory cell recruitment  – anothe