Investigating the Role of the ETS Transcription Factor ELK1 in Stem Cell Transcription

Investigating the role of the ETS transcription factor ELK1 in stem cell transcription

A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Biology, Medicine and Health

2017 Ian E. Prise Division of Molecular & Cellular Function School of Biological Sciences

I. Table of Contents II. List of Figures ...... 5 III. Abstract ...... 7 IV. Declaration ...... 8 V. Copyright Statement ...... 8 VI. Experimental Contributions ...... 9 VII. Acknowledgments ...... 10 1. Introduction ...... 12 1.I Pluripotency ...... 12 1.II Chromatin ...... 13 1.II.A Histones ...... 14 1.III Transcription ...... 15 1.III.A Transcriptional activation ...... 15 1.III.B Transcriptional repression ...... 17 1.III.C Polycomb repression complexes ...... 20 1.IV The mitogen activated protein kinase pathways...... 24 1.IV.A Response to different stimuli ...... 24 1.V The ETS transcription factor family...... 25 1.VI ELK1...... 26 1.VI.A Structure of ELK1 ...... 26 1.VI.B Relationship to other ETS proteins ...... 29 1.VI.C Biological processes involving ELK1 ...... 30 2. Project aims...... 32 3. Materials and Methods ...... 35 3.I Lab techniques ...... 35 3.I.A Cell Culture ...... 35 3.I.B Retinoic acid treatment ...... 35 3.I.C Mesoderm Differentiation ...... 36 3.I.D Neural Progenitor Cell Differentiation...... 36 3.I.E IL-6 Cell stimulation ...... 36 3.I.F shRNA treatment ...... 36 3.I.G siRNA transfection ...... 36 3.I.H Crosslinking and lysing cells ...... 37 3.I.I Chromatin Immunoprecipitation ...... 37 3.I.J Co-Immunoprecipitation ...... 38 3.I.K RNA purification ...... 38 3.I.L PCR (siELK1, MIM and NPC treatments) ...... 38 3.I.M RT-PCR (shELK1 and RA treatments) ...... 39 3.I.N Rapid immunoprecipitation of endogenous proteins ...... 39 3.I.O Western Blot Analysis ...... 40 3.II Bioinformatic analysis ...... 40 3.II.A ChIP-seq analysis...... 40 3.II.B RNA-seq analysis ...... 41 3.II.C Peak Intersections ...... 41 3.II.D Tag Density Graphs ...... 41

3.II.E Motif Analysis ...... 41 3.II.F Graphics ...... 42 3.II.G Accession numbers ...... 42 3.II.H Primer Design ...... 42 3.II.I Statistical Analysis ...... 42 3.III Materials ...... 42 3.III.A siRNAs ...... 42 3.III.B PCR Primers ...... 42 3.III.C ChIP Solutions ...... 46 3.III.D Western Blot Solutions ...... 48 3.III.E Antibodies ...... 48 4. Results ...... 50 4.I ELK1 binding regions can be divided into different modules ...... 50 4.I.A Genomic distribution of ELK1 modules ...... 50 4.I.B ELK1 loci with low ERK2 enrichment correlate with high PRC2 enrichment ...... 52 4.I.C ELK1 loci with high SUZ12 enrichment correlate with low enrichment of active histone modifications ...... 54 4.I.D ELK1 loci with high SUZ12 enrichment correlate with genes enriched for developmental GO terms ...... 56 4.I.E An ELK1+SUZ12 binding module is H1-hESC specific ...... 58 4.I.F ELK1 loci with low GABPA enrichment correlate with high PRC2 enrichment ...... 60 4.I.G Conclusion Part1 ...... 65 4.II ELK1 does not interact with PRC2 ...... 67 4.II.A An ELK1+RBBP7 interaction is detectable with RIME ...... 67 4.II.B An ELK1+PRC2 interaction is not detectable with Co-Immunoprecipitation ...... 70 4.II.C Conclusion Part 2 ...... 72 4.III ELK1 is not necessary to recruit SUZ12 to developmental genes ...... 75 4.III.A Retinoic Acid does not change PRC2 binding ...... 75 4.III.B ELK1 depletion does not decrease SUZ12 and H3K27me3 binding ...... 81 4.III.C Conclusion Part 3 ...... 85 4.IV The role of ELK1 in pluripotency and differentiation ...... 86 4.IV.A Mesoderm induction produces Brachyury/T expressing cells ...... 86 4.IV.B The role of ELK1 in mesoderm and neural differentiation ...... 88 4.IV.C The role of ELK1 in pluripotency ...... 92 4.IV.D Conclusion Part 4 ...... 95 4.V Genome-wide investigation of ETS transcription factor binding sites ...... 96 4.V.A ChIP-seq of ELK1 and ETV1 ...... 96 4.V.B Verification of ELK1+SRF co-binding ...... 106 4.V.C SRF depletion reduces ELK1 binding ...... 116 4.V.D Conclusion Part 5 ...... 120 5. Summary ...... 121 5.I ELK1 does not recruit PRC2 ...... 121 5.II The role of ELK1 in maintaining pluripotency and differentiation...... 122 5.III Investigating ELK1 co-factors ...... 123

6. Discussion ...... 125 6.I SUZ12 recruitment ...... 125 6.II STAT binding overlaps with ELK1 binding ...... 106 6.II.A The relationship of ELK1 and STAT ...... 126 6.III Establishing an ETS-switch ...... 128 6.IV The role of ELK1 in pluripotency ...... 129 7. Citations ...... 131

Word Count: 31670

II. List of Figures Figure 1: Initiation of gene transcription by RNAPII...... 17 Figure 2: PRC2 deposits methylation onto histone H3...... 23 Figure 3: The structure of ELK1 isoforms...... 26 Figure 4: Overview of small molecule involved in hESC differentiation...... 33

Figure 5: Genomic distribution of transcription factor binding loci...... 51 Figure 6: ELK1 has a binding module enriched for ERK2 and enriched for active histone marks ...... 53 Figure 7: ELK1 has a binding module enriched for PRC2 and enriched for repressive histone marks ...... 55 Figure 8: Gene ontologies for ELK1 binding loci partitioned by overlap with SUZ12 binding loci...... 57 Figure 9: ELK1 peaks unique to hESC are enriched for PRC2……………………………………………...... 59 Figure 10: ELK1 peaks are enriched for PRC2 and active histone marks...... 61 Figure 11: Genomic distribution of GABPA binding loci...... 62

Figure 12: ELK1 peaks are enriched for PRC2 and active histone marks GABPA (Top 30%)...... 64 Figure 13: Binding profiles surrounding ELK1+SUZ12 peaks...... 66 Figure 14: Co-Immunoprecipitation assay of ELK1 and SUZ12 interacting proteins...... 68 Figure 15: RIME analysis of the ELK1 interactome ...... 70 Figure 16: Co-Immunoprecipitation assay of ELK1 and SUZ12 interacting proteins ...... 71 Figure 17: Model of recruitment of RBBP7 by ELK1 ...... 73 Figure 18: RBBP7 does not co-occupy SIN3A binding sites...... 74 Figure 19: ELK1-bound genes are upregulated during RA treatment...... 76 Figure 20: ELK1, SUZ12 and H3K27me3 antibodies are specific...... 78 Figure 21: RA treatment has no effect on the binding of ELK1, SUZ12 and H3K27me3...... 79 Figure 22: H3K27ac modification increases near in RA-induced genes...... 80

Figure 23: shELK1 treatment decreases NANOG and OCT4 expression ...... 81 Figure 24: ELK1, SUZ12 and H3K27me3 antibodies are specific in shELK1 treat cells...... 82 Figure 25: ELK1 knockdown does not affect SUZ12 binding ...... 83 Figure 26: Expression of ELK1-bound genes following ELK1 depletion ...... 84 Figure 27: Pluripotency and differentiation factor expression in H1-hESC upon MIM treatment ...... 87 Figure 28: The role of ELK1 in gene expression driving mesoderm differentiation...... 89 Figure 29: The role of ELK1 in gene expression driving neural differentiation...... 91 Figure 30: siELK1 treatment does not decrease pluripotency markers...... 93 Figure 31: Effect of long term ELK1 depletion on pluripotency and lineage marker expression ...... 94 Figure 32: Model of ELK1 as a repressive factor...... 97

Figure 33: Western blot of and expression ETV1 in H1-hESC and mesoderm cells...... 98 Figure 34: ELK1 ChIP-seq peak counts………………………...... 99 Figure 35: Motifs in ELK1 ChIP-seq peaks...... 101 Figure 36: ETV1 ChIP-seq has low fold enrichment...... 103

Figure 37: Top ETV1 ChIP-seq Peaks by Fold Enrichment...... 104 Figure 38: Motifs in ETV1 ChIP-seq peaks...... 105 Figure 39: STAT Motifs are present in ETS ChIP-seq peaks...... 107

Figure 40: ELK1 ChIP-seq peaks overlapping with STATs...... 108

Figure 41: STAT3 binding is not increased by IL-6 in H1-hESC...... 109 Figure 42: ChIP-qPCR of regions not bound by ELK1 and SRF...... 111 Figure 43: ChIP-qPCR of regions bound by ELK1 and not SRF in H1-hESC and mesoderm...... 112 Figure 44: ChIP-qPCR of regions bound by ELK1 in H1-hESC and mesoderm……...... 113 Figure 45: ChIP-qPCR of regions with higher ELK1 and SRF binding in mesoderm...... 114

Figure 46: ChIP-qPCR of regions with higher ELK1 and SRF binding in mesoderm...... 115 Figure 47: The effect of SRF and ELK1 depletion on SRF and ELK1 binding...... 116 Figure 48: SRF depletion reduces ELK1 binding...... 118 Figure 49: ELK1 depletion increases SRF binding...... 119 Figure 50: ELK1 and STAT3 regulation in Naïve cells and hESC...... 127 Figure 51: Effect of long term ETV1 depletion on pluripotency expression...... 128

III. Abstract The University of Manchester Ian Prise Investigating the role of the ETS transcription factor ELK1 in stem cell transcription

ELK1 is a member of the E-twenty-six transcription factor family which is known to be both an activator and a repressor of transcription and is able to toggle between the two modes. Even in a single cell line, ELK1 can act as both an activator and repressor in response to a single stimulus, such as epidermal growth factor stimulation. To answer this apparent paradox, ELK1 binding can be parsed into distinct binding modules, with a distinct biological function, and these binding modules may explain ELK1’s dual roles.

A recent study performed in human embryonic stem cells (hESC) suggested that ELK1 exists in an active module which co-localises with SRF, and a repressive module co-localizing with members of Polycomb repressive complex 2 (PRC2) on loci near to developmental genes. The PRC2 complex has shown to have repressive roles in pluripotent stem cells, however, the regulation and recruitment of PRC2 remains a mystery. Elucidating the possible relationship between ELK1 and the PRC2 complex may further explain the pathways that govern PRC2 recruitment and shed light on the role of ELK1 as a repressor.

To investigate an ELK1-PRC2 interaction, we first scanned the ELK1 protein interactome using the rapid immunoprecipitation and mass spectrometry of endogenous proteins (RIME) protocol. Subsequently, we investigated the co-binding of ELK1 and PRC2, and its effect on the regulation of gene transcription during ELK1 depletion and differentiation. We did not detect any interaction between ELK1 and PRC2 using these protocols, although we saw an increase in transcription of the developmental gene SIX1 upon ELK1 depletion, hinting at a PRC2-independent repressive role for ELK1. We next investigated the role of ELK1 in pluripotency and both early mesoderm and neural differentiation. Although we did not uncover a central role for ELK1 in these processes, concurring with the in vitro studies, we find that ELK1 depletion increased the expression of genes in both mesoderm and neural differentiation, pointing to the role of ELK1 as a repressor.

We finally revisit the interaction between ELK1 and SRF in the context of mesoderm differentiation. We uncovered ELK1 and SRF co-binding near many genes. We see a decrease in ELK1 binding in both hESC and mesoderm upon SRF depletion, affirming the role of SRF as a recruiter of ELK1.

IV. Declaration No portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning;

V. Copyright Statement i. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and s/he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes. ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made. iii. The ownership of certain Copyright, patents, designs, trademarks and other intellectual property (the “Intellectual Property”) and any reproductions of copyright works in the thesis, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions. iv. Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=24420), in any relevant Thesis restriction declarations deposited in the University Library, The University Library’s regulations (see http://www.library.manchester.ac.uk/about/regulations/) and in The University’s policy on Presentation of Theses

VI. Experimental Contributions I would like to thank Claire Morrisroe, Andy Hayes, Ian Donaldson, Ronan O’Cualain, Stacey Warwood and Stacey Holden of the University of Manchester Core Facilities who performed the mass spectrometry, ChIP sequencing and Fluidigm experiments.

VII. Acknowledgments Having established that a myriad of people were tremendously helpful and supportive during this experience, I next sought to acknowledge them:

Gerkle “Gerick Lee” Lee – This is mostly your fault

Shauneth, Iiiitalooo – To a Job well done

Lil’ Baby Joe, Giulia, Pari, Alan, Pablito, Karolito, Mezida – May you one day find the library

C-bone, T-bone, Teoh-bone – Ye who eateth of the mango rind Is quick and nimble of the mind

Nick, Vick, Ry, Bri, Nad, Drew, Teachout, Big Alpha and all Seattle Folk – To long held friends who are overseas: save me a seat at Sarducci’s

Y-lynn, Rajat, Zi Ying and the Singapore Improve Company – 西安辣椒面松散的舌头

Prof. Ng, Winston, Paul, Zongling, Karren and all members of Sharrocks and Ng Labs – Boundless thanks for your guidance and help

Grumpy – 七八月的南瓜皮老心不老

Elisita – ピペットと心は団結しなければなりません。

技法自体が不十分で、精神だけでは不十分です

The Andrew Sharrocks – Who knows most says least. Ta

The Northern Prises – “To wear the kilt is my delight. It is not wrong I know it's right.”

Colin Prise – Las sábanas suaves hacen mentes agudas

Madre and Papa Prise – At your knees I learned to ski and cycle, Play piano and the drums And now my thanks to Diana and Michael Now this giant project is done And though I lack the genes to be a medic It’s not your fault, it’s epigenetic

Meg Fleming – “I asked her for one hair from her golden head. She gave me three”

Infinite thanks to everyone

VIII. List of Abbreviations BRE B recognition element ChIP Chromatin immunoprecipitation Co-IP Co-immunoprecipitation DMEM Dulbecco's modified Eagle's medium DNA Deoxyribonucleic acid EED Embryonic ectoderm development protein ELK1 ETS-like transcription factor 1 ERK Extracellular signal-regulated kinases ETS E-twenty six protein family ETV1 ETS translocation variant 1 EZH2 Enhancer of Zeste 2 protein FGF Fibroblast growth factor GABPA GA-binding protein alpha GTF General transcription factor HDAC Histone de-acetylation hESC Human embryonic stem cell INR Initiator element JNK c-Jun N-terminal kinases MAPK Mitogen-activated protein kinase MIM Mesoderm induction media mRNA Messenger ribonucleic acid MRTF Myocardin-related transcription factor NIM Neural induction media NPC Neural progenitor cell PBS Phosphate buffered saline PRC1 Polycomb repressive complex 1 PRC2 Polycomb repressive complex 2 qPCR Quantitative polymerase chain reaction RA Retinoic acid RBBP7 Retinoblastoma-binding protein 7 RIME Rapid immunoprecipitation and mass spectrometry of endogenous proteins RNA Ribonucleic acid RNAPII RNA polymerase II ROCK Rho-associated protein kinase RT-qPCR Reverse transcription quantitative polymerase chain reaction shRNA Short hairpin RNA siRNA Small interfering RNA SRE Serum response element SRF Serum response factor STAT Signal transducer and activator of transcription SUMO Small ubiquitin-like modifier SUZ12 Suppressor of Zeste 12 protein TCF Ternary complex factor TF Transcription factor TSS Transcription start site

1. Introduction 1.I Pluripotency Human embryonic stem cells (hESCs) are derived from the epiblast of the human embryo (Thomson et al., 2007). They are pluripotent, meaning that they are able differentiate into the three early lineages, which go on to contribute to every tissue in the adult body

(Odorico et al., 2001). And importantly, they are able to self-renew in vitro, allowing for the study of self-renewal and the early stages of human development (Amit et al., 2000; Odorico et al., 2001). Over the last decade, advances in cell culture have led to the culture of a large array of more mature human cells and organoids- heterogeneous, self-organized, in vitro tissue (Lancaster & Knoblich, 2014). Combined with the induction of pluripotency in mature tissues, or induced pluripotent stem cells, creating the potential to use tissue from a patient to create syngeneic cells, these tissues will have a myriad of therapeutic uses, including disease modelling, pharmaceutical testing and potentially transplantation of lab-grown tissue

(Fatehullah et al., 2016; Lancaster & Knoblich, 2014; Y. Sun & Ding, 2017; Takahashi et al.,

2007; Yamanaka & Blau, 2010).

Two of the defining features of hESCs, their ability to remain undifferentiated and to self-renew, are maintained by a central transcription program, consisting of, OCT4, SOX2 and

NANOG, which is sustained by external signals and creates a positive feedback loop (Boyer et al., 2005; Kashyap et al., 2009). In addition, NANOG, SOX2 and OCT4 are able to control the transcription of other transcription factors (TFs) in the pluripotency network (Kashyap et al.,

2009). In fact, forced expression of OCT4 and SOX2 alone is able to induce pluripotency in human fibroblasts, suggesting that OCT4 and SOX2 are able to establish expression of the pluripotency network (Huangfu et al., 2008).

The pluripotency network is subject to regulation from external factors. Pluripotency has been shown to be activated in response to external factors, with the activation of the WNT,

NOTCH, NF-κB, AKT and FGF/ERK (discussed further in section 1.IV) signalling being necessary

12 to maintain pluripotency, self-renewal and cell survival (Androutsellis-Theotokis et al., 2006;

Armstrong et al., 2006; J. Li et al., 2007; Pera & Tam, 2010; Sato et al., 2004; Vallier et al.,

2005). Additionally NANOG and SOX2 activity has been shown to be regulated by FGF signalling and NANOG has been shown to be directly regulated by TGF-β/SMAD signalling, again demonstrating the connection of extrinsic factors to pluripotency maintenance (Mansukhani et al., 2005; Xu et al., 2008; P. Yu et al., 2011). They play an important part in maintaining self- renewal and controlling differentiation, repressing the transcription of lineage specific factors, on one hand, while also playing an active role in differentiation (Gagliardi et al., 2013; Kashyap et al., 2009; Lee et al., 2006a; Zheng Wang et al., 2012). The maintenance of pluripotency and process of differentiation can therefore be studied as an epigenetic phenomenon, with both pluripotency markers and lineage specific factors contributing to chromatin structure and accessibility (Dixon et al., 2015; Kaestner, 2015; Loh et al., 2016; Lu Wang et al., 2017; Xie et al., 2013; Ziller et al., 2014).

1.II Chromatin The genome, the entirety of heritable information, is encoded in DNA in all non-virus organisms. DNA consists of two strands comprised of 4 different nucleotides (guanine, cytosine, adenine and thymine), braced by a phosphate-deoxyribose backbone, and twisted into a double helix structure. The Human Genome Project estimated the human genome at

3.08x109 bp in length. However, only about 1.2% of the human genome contains exons, regions that code for proteins (International Human Genome Sequencing Consortium, 2004). A recent screen across 15 human cell lines revealed that 74.7% of the human genome is transcribed into primary RNA, but never translated into protein (Djebali et al., 2012).

The human genome is packaged into a DNA-protein complex called chromatin. DNA is wrapped around histones, protein complexes comprised of H2A, H2B, H3 and H4 histone proteins which are organized in an octamer. This DNA-histone package is a nucleosome, ~147

13 bp of DNA wrapped around the histone octamer. These nucleosomes are organized into higher order structures, with the assistance of H1 histones (reviewed in Richmond & Davey, 2003).

Eukaryotic chromatin exists in three forms, euchromatin, loosely packed chromatin; heterochromatin, tightly packed chromatin; and centromeric chromatin, a subset of heterochromatin responsible for attachment to the kinetochore during replication (Sullivan &

Karpen, 2004). Euchromatin comprises ~93.5% of the human genome and contains roughly

20,000-25,000 protein coding genes and at least another 55,000 non protein coding RNAs

(Esteller, 2011; International Human Genome Sequencing Consortium, 2004).

1.II.A Histones The expression of genes is regulated in part by modification of histones. In order for the transcriptional machinery to have access to the DNA, the DNA must be loosened from the nucleosomes. Histones can be regulated by modification, the addition and subtraction of chemical groups, such as acetyls, methyls, phosphates, and ubiquitin to effect a tightening and loosening of DNA around the histone core (Yuan, 2012). Many of these histone modifications are thus associated with either an increase in active transcription or and an increase in transcriptional repression.

Modification to effect these changes is performed by a variety of enzymes; histone methyltransferases (HMTs) and histone demethylases (HDMs) which, respectively, add and remove methyl groups, and histone acetyl transferases (HATs) and histone deacetylases

(HDACs), which, respectively, add and remove acetyl groups. In addition, ligases and kinases add ubiquitin and phosphate groups. Generally, acetylation is associated with active gene expression whilst deacetylation is associated with repression, however the effects of other modifications, such as methylation do not have as clear an association with specific transcriptional states (Struhl, 1998). Histone modification is a dynamic process, with acetylation turning over in under 15 minutes and methylation turning over during the course

14 of a few days. This allows acetylation to be utilized for rapid processes, like gene expression, and methylation to be utilized for slower processes, such as epigenetic inheritance and cell differentiation (Barth & Imhof, 2010). In addition to modifications of the histone, there are classes of enzymes which are able to add, eject and move histones along the DNA, or exchange histone variants with differing affinity for DNA, which will again tighten or loosen the chromatin, thus allowing or denying access to the DNA, for processes like transcription (Gaume

& Torres-Padilla, 2016; Peterson & Workman, 2000; Shain & Pollack, 2013).

1.III Transcription Transcription is the process by which the genetic information stored in DNA is transcribed into RNA, which may be exported from the nucleus as mRNA and translated into protein, or modified to create a variety of non-coding RNA.

1.III.A Transcriptional activation Transcription is an enzymatic process in which a DNA sequence is copied into RNA polymers. This process is catalysed by RNA polymerases (RNAPs). Eukaryotic RNA polymerases are split into three classes: RNAPI, which transcribes ribosomal RNA, RNAPIII, which transcribes transfer RNA, and RNAPII is involved in the transcription of many classes of small RNAs and mRNA, which is later translated into protein (Jonkers & Lis, 2015; Moss, 2004; White, 2011). As

RNAPII involved in the transcription of mRNA, its recruitment is well studied and involves a myriad of transcription factors, co-activators, general transcription factors (GTFs) and the mediators, which are ultimately assemble at promoter region, just upstream of the transcription start site (TSS). This complex of factors orient RNAPII, allow DNA accessibility and initiate transcription with the phosphorylation of the serine 5 of the carboxy-terminal domain of RNAPII, which begins the process of RNA polymerization or elongation (Jonkers & Lis, 2015).

Before the general transcription machinery is recruited a sequence-specific transcription factor may bind to a regulatory region. Sequence-specific transcription factors are able to recognize short stretch of DNA in regions that regulate the expression of genes (Fig. 1A). They

15 can be controlled at all levels - transcription, translation and activation - and are thus important the control of gene transcription. They can recruit the transcription machinery and, in the case of so-called pioneer factors, open condensed chromatin (Fig. 1B) (Arvey et al.,

2012; B. Li et al., 2007; Magnani et al., 2011; Weirauch et al., 2014). The pioneer transcription factor may bind to a large array of proteins collectively known as mediators, which are involved in recruiting and stabilizing the general transcription machinery (Fig. 1C) (Allen &

Taatjes, 2015; Poss et al., 2013).

The general transcription machinery initiate the process of transcription and include many classes of general transcription factors (Fig. 1D). For instance, TFIIB, which is able to bind to BREs and TFIID, which includes the TATA-box binding factor, can bind the TATA box and the

TAF1/2 subunits which can associate with the INR, all of which recruit, stabilize and dictate the orientation of the RNAPII complex (Fig. 1E+F) (Deng et al., 2005; Dynlacht et al., 1991;

Lagrange et al., 1998; Lim et al., 2004; Purnell et al., 1994; Sainsbury et al., 2015). Other members, TFIIH and TFIIE, open the DNA, allowing for elongation (Grünberg et al., 2012;

Holstege et al., 1996). And yet another member, TFIIF are able to recruit RNAPII (Langelier et al., 2001). Finally, P-TEFb is able to phosphorylate the serine 2 of the carboxy-terminal domain of RNAPII, and elongation can begin (Fig. 1G) (Chao & Price, 2001; Moon et al., 2005).

C B G Mediator complex D Chromatin General transcription modifiers factors

RNAPII

Sequence specific transcription factor A E F

Figure 1: Initiation of gene transcription by RNAPII Model of the recruitment of the transcription machinery, showing A) the binding of a sequence specific transcription factor, which may be near to the promoter or farther away, in regulatory regions classically called enhancers. B) These factors may go on to recruit chromatin modifiers, which can make the DNA more accessible. C) Next, the mediator family of complexes connect, recruit and stabilize the interaction of transcription factors. D) The general transcription machinery which recruit and orient RNAPII. For instance E) TFIID may additionally associate with DNA elements, TATA box and BREs, roughly 40 bp upstream of the TSS or F) the INR, which straddles the TSS. G) Finally RNAPII is phosphorylated by P-TEFb and can initiate RNA elongation.

1.III.B Transcriptional repression There is a large diversity of repression mechanisms, acting at many steps during the process of activation. Repressors can work either directly, inhibiting the protein-protein or

DNA-protein interactions required to complete transcription, or indirectly, regulating activator turnover or disrupting the cellular localization of TFs (reviewed in Gaston & Jayaraman, 2003 and Rojo, 2001). In addition, repression can occur on specific genes or repression can occur more globally, for instance, in response to environmental stress (Chen et al., 2003).

Controlling activator turnover can occur by flagging an activator for degradation. For instance, the repressor SRB10 can phosphorylate the activator GCN4, flagging it for ubiquitination and, ultimately, repressing GCN4-activated transcription (Chi et al., 2001). In addition to indirect repression, such as tagging the proteins for degradation with ubiquitin,

AEBP1 is able to directly cleave the TF AP2, causing repression (Lyons et al., 2006).

Repressors are also able to modify the cellular localization of activators. For instance, the repressor IκB binds to the activator NF-κB, blocking the nuclear localization signal and disrupting its translocation to the nucleus (Verma et al., 1995). Additionally, KEAP1 chaperones

NRF2 out of the nucleus, once NRF2 has activated transcription, thus repressing gene expression (Sun et al., 2007).

Inhibition of activator interaction with DNA occurs in two ways. Firstly, a repressor can compete directly with an activator for a region of the DNA. For instance, the repressor

Engrailed is able to bind to the same homeobox binding motif as the activator FTZ, thereby inhibiting transcription (Jaynes & Farrell, 1988). Secondly, repressors are able to bind to TFs in order to inhibit their activation. In an example of mutual repression, glucocorticoid receptor is able to bind to JUN and FOS, which comprise the AP1 dimer, mutually inhibiting the DNA binding of both AP1 and glucocorticoid receptor (Yang-Yen et al., 1990).

Finally, many activators require co-activators to initiate transcription. Many repressors can disrupt this interaction to inhibit transcription. For instance, the MHC class II transactivator is able to competitively bind to NF-AT with the CBP/p300 complex, the co-activator of NF-AT, repressing expression of IL-4 (Sisk et al., 2000).

The C-terminal domain of RNA polymerase II (RNAP II) is dephosphorylated upon initiation and phosphorylated upon elongation (Dahmus, 1996). SRB10 phosphorylates the C- terminal domain during initiation, this rendering RNAP II unable to initiate elongation

(Hengartner et al., 1998). Additionally, the CTD is glycosylated upon initiation and is de- glycosylated upon elongation (Kelly et al., 1993). The mSin3a repressor complex is able to recruit O-GlcNAc transferase, which in turn, glycosylates RNAP II, causing deactivation (Yang, et al., 2002).

The basal machinery can be inhibited in many ways. First, TBP is the GTF responsible for recognizing and binding the TATA box in the promoter region. The TATA box-TBP interaction can be disrupted to cause repression. For instance, Even-skipped competitively binds in the same region as TBP, disrupting the TBP-DNA interaction, causing repression (Li &

Manley 1998). Next, TBP can be repressed by direct binding by a repressor, as is the case with

Mot1 (Darst et al., 2001). Finally, the interaction between the GTFs can be disrupted, as is the case with NC2, which inhibits the interaction between the GTFs TFIIA and TFIIB, causing repression (Zhao, 1995).

Chromatin confirmation also plays a role in repression. As described earlier, chromatin can be modified to a more or less open conformation. This is achieved by the modification of histones. While there are a large variety of histone modifications, generally speaking, acetylation is associated with gene expression whilst deacetylation is associated with repression (Struhl, 1998). In addition to histone modification, DNA can be methylated, a process known to cause repression. Methylation takes place on CpG groups, cytosine and guanine dinucleotides. Methylation can act as a repressor by directly blocking transcription, changing the chromatin conformation, or recruiting HDACs (reviewed in Gaston & Jayaraman

2003). As methylation is often maintained on both strands, this type of repression is heritable

(Bird, 2002).

Many of the proteins that modify chromatin function in a complex. The multi-protein nature of such complexes serves to illustrate the multistep nature of chromatin remodelling.

For instance, the NuRD complex consists of histone binding proteins RBBP7/RbAp46 and

RBBP4/RbAp48; MBD3, a CpG domain binding protein with DNA methylation capabilities;

MTA2, which promotes the assembly of the complex; and HDAC1 and HDAC2, which catalyse the actual deacetylation (Reese et al., 2007; Yi Zhang et al., 1999). This complex is a good example of how multiple proteins work together to allow for histone deacetylation and DNA

19 methylation. These complexes can be recruited by transcription factors which bind to specific

DNA elements, adding gene-specific control of transcription. For instance, the factor PARP recruits NuRD to sites of DNA damage in response to UV radiation, locally repressing transcription (Chou et al., 2010).

1.III.C Polycomb repression complexes

The Polycomb group proteins (PcG) are a class of genes capable of silencing genes via chromatin remodelling. The PcG were originally described in Drosophila, as silencers of the

HOX genes (Duncan, 1982). They were shown to contribute to long-term, heritable control of gene expression. However, studies demonstrating that PcG can be activated during development and the dynamic interplay between PcG and RNAPII demonstrate a more dynamic regulation of biological processes (reviewed in Schuettengruber & Cavalli 2009;

Brookes et al. 2012).

PcG proteins assemble into complexes, the Polycomb repression complexes (PRC). Two

PRCs have been described in mammals. PRC2 binding is associated with the H3K27me3 repressive histone mark, whilst PRC1 binding is associated with the H2AK119ub1 repressive histone mark (Wang et al. 2004; Cao & Zhang 2004b).

PRC1 is comprised of RING1A or RING1B, E3 ubiquitin ligases, and BMI1, both of which are necessary for the PRC1 ubiquitinase function (Buchwald et al., 2006; Cao et al., 2005). In addition, the histone-binding proteins, CBX2, CBX4, CBX6, CBX7, and CBX8 have been shown to assist in PRC1 binding to H3K27me3 (Vincenz & Kerppola, 2008). Additionally, RYBP has been shown to stimulate the ubiquitinase ability of PRC1 (Gao et al., 2012).

PRC2 in humans is comprised of the core components EED, EZH2 and SUZ12 (Fig. 2A).

The EED-EZH2 complex is necessary to trimethylate lysine 27 on H3, with EZH2 specifically carrying out the HMT activity (Czermin et al., 2002; Müller et al., 2002). Additionally, SUZ12

20 has been demonstrated to be necessary for the gene silencing and methylation function of the

EED-EZH2 complex (Cao & Zhang, 2004a). In addition to these core components, other proteins have been shown to improve or alter the function of the PRC2. The DNA-binding protein AEBP2 has been shown to improve the enzymatic activity of the PRC2 (Cao & Zhang,

2004a). JARID2 is essential for binding of the PRC2 to the target genes (Fig 2B) (Pasini et al.,

2010). Meanwhile, EZH1, a homolog of EZH2, has been shown to function in a similar, but not wholly redundant manner to EZH2, suggesting different variations of the PRC2 with different epigenetic programs (Shen et al., 2008). Finally, the histone-binding proteins RBBP7 and RBBP4 are associated with the PRC2 (Kuzmichev et al., 2002).

The PRCs have also been shown to be involved in cell differentiation, a more dynamic process. The PRCs play an integral role in maintaining ESCs pluripotency, as evidenced by a series of PRC2 component knockdowns, which resulted in differentiation (Boyer et al. 2006;

Pasini et al. 2007). In both of these studies, the deletion of PRC2 components was accompanied by a loss of H3K27me3 markings. Additionally, many of the repressed sites encoded differentiation genes, suggesting that PRC2 plays a role in repressing differentiation.

PRC2 component knockdowns or inhibition result in failed differentiation, unscheduled expression of development genes, cell death and low levels of Ser 5-RNAPII, or poised RNA polymerase (Landeira et al., 2010; Pasini et al., 2010; Pasini et al., 2007; Y. Yu et al., 2017). In addition to PRC2, the deletion of PRC1 components, such as RING1 and RYBP, leads to abnormal differentiation (Gao et al., 2012; Román-Trufero et al., 2009)

PRCs were originally described in the context of stable, heritable epigenetic modification

(Beuchle et al., 2001). Though there is still speculation on the exact mechanisms, PRC1 has been shown to remain bound to replicated DNA during replication, passing on the same epigenetic information (Francis et al., 2009). In addition, there is evidence that EZH2 can recruit DNA methyltransferases, contributing to heritable DNA modification (Viré et al., 2006).

One of the hallmarks of Polycomb modification is the bivalent state, in which histones are simultaneously modified to be in an active (H3K4me3) and inactive (H3K27me3) state. In this way, the genes are primed for either the repression or activation of development genes.

When the cell is in a non-differentiated state, many TFs with CG-rich promoter regions will have both modifications, and subsequently be expressed at very low levels. However, upon differentiation, the TSSs of these TFs will exhibit one histone modification or the other

(Bernstein et al., 2006). The PRC2 is bound to 78% of bivalent promoters and Ring1B, a member of the PRC1, occupied 94 % of PRC2 binding sites, consistent the recruitment of PRC1 to H3K27me3 modification sites. Finally, PRC1-containing bivalent sites in ESCs tended to be enriched for genes which are fully repressed and genes that regulate development compared to non-PRC1 containing sites (Ku et al., 2008; Vincenz & Kerppola, 2008).

PRCs are preferentially recruited to sites called Polycomb response elements (PREs) in

Drosophila (Müller & Kassis, 2006). However, there exists no clear consensus sequence for these sites. Whilst there exists indirect evidence suggesting TF recruitment of PRCs – TF consensus sequences found near PRC binding sites, a reduction of PRC binding upon OCT4 and

SOX2 deletion, and overlap of TF binding sites with PRC binding sites – as of yet, only RUNX1 has been shown to directly interact with PRC1 subunits (Göke et al., 2013; Ku et al., 2008; Lee et al., 2006b; M. Yu et al., 2012). PRC2 has been shown to directly interact with Xist, a ncRNA, deletion of which abolishes PRC2 methylation ability, suggesting ncRNA-mediated recruitment of PRCs (Zhao et al. 2008). In addition, the different components of the PRCs have been shown to localize to distinct chromatin regions in embryonic stem cells, suggesting that the components themselves have some part in directing recruitment (Vincenz & Kerppola, 2008).

A EZH2 EED

SUZ12 H3K27me3

GENE

B C

Figure 2: PRC2 deposits methylation onto H3 A model of the Polycomb repressive complex 2 (PRC2) including A) the core components SUZ12, EED and EZH2, the component responsible for the deposition of the repressive H3K27me3 histone modification B) the DNA biding components, AEBP2 and JARID2, C) the histone associating components RBBP4 and RBBP7.

With a lack of known recruiters and a known genomic consensus sequence, the best guess at the recruitment of the PRC2 complex was that it is recruited by the PRC1 histone modification, DNA CpG methylation or is directed in some manner by lncRNAs. However, recent studies have shown that the PRC2 complex interacts with a large number of RNA transcripts and shows that PRC2 localizes near areas of low transcription, but does not localize near areas of no transcription, which suggests that gene transcription, though at low levels, is one of the main mechanisms of PRC2 localization, and that PRC2 is perhaps ejected from areas of high expression (Beltran et al., 2016; Berrozpe et al., 2017). Presumably, as the PRC2 complex maintains cell-type specific gene expression, there is a mechanism by which cell-type specific genes are silenced.

Recently, it has been shown that whilst the PRC2 complex binds near lowly expressed genes, highly expressed genes and genes with no expression have no PRC2 binding. Taken together with mutual antagonism between PRC2 and RNAPII and PRC2 attraction to chromatin and RNA (Beltran et al., 2016; Tee et al., 2014), this suggests that the PRC2 functions to silence

23 genes that might be necessary eventually for a cellular process (such as differentiation), but are not necessary in the current cell state in which it is operating.

1.IV The mitogen activated protein kinase pathways The ERK, JNK and p38 mitogen activated protein kinase (MAPK) pathways control a large variety of cellular processes. These pathways function on the MAPK pathway model, in which small receptor-related GTPases activate, via phosphorylation, a series of MAP kinases, which ultimately activate nuclear transcription factors. In this way, an external stimulus, such as the presence of growth factor, can be converted to a cellular response: the activation or repression of target genes. The ERK pathway is activated by growth factors and mitogens, and is thus involved in differentiation and cell proliferation, whilst the JNK and p38 pathways are activated in response to cytokines and stress signals, and subsequently control apoptosis, inflammation and development (reviewed in Qi & Elion 2005). The MAPK pathway also plays a central role in maintaining the expression of adhesion and survival genes, promoting self- renewal in hESC by the FGF2-stimulated phosphorylation of MEK/ERK (Eiselleova et al., 2009; J.

Li et al., 2007). Also, FGF2 may have some role in lineage specification, as suggested by multiphasic FGF expression during differentiation, tissue specific knockdown effects and the role of FGF in maintaining NANOG, which is an endoderm lineage marker, and inhibitor of nueroectoderm specification, in addition to being a pluripotency marker (Lanner & Rossant,

2010; J. Rao & Greber, 2017; Zheng Wang et al., 2012).

1.IV.A Response to different stimuli Even though multiple MAPK pathways converge on the same transcription factors, such as GATAs, AP-1 and ETS factors, different stimuli elicit different responses (Karin, 1995;

Katsumura et al. 2016; Nerlov et al., 2000; Selvaraj et al., 2015; Tenhunen et al., 2004; Yang &

Sharrocks, 2005). For instance, the SUMO ligase PIASxα is differentially activated in response to either the ERK or the p38 pathways. Its activation by the ERK pathway results in deSUMOylation, the removal of the small ubitiquin-like modifier (SUMO), from the

24 transcription factor ELK1, resulting in the dissociation of HDAC2 from the ELK1-bound FOS promoter. On the other hand, p38 activation of PIASxα protects against deSUMOylation of

ELK1 and HDAC2 dissociation (Yang & Sharrocks, 2005). Additionally, recognition of different docking domains by kinase isoforms in each pathway may allow for differential activation

(Sharrocks et al., 2000; Whitmarsh, 2007). Thus the interactions between and within MAPK pathways, TFs can attain a high level of activation variability and specificity.

1.V The ETS transcription factor family The E-twenty six (ETS) transcription factor family are all phosphorylated by the MAPK pathways. They share a conserved DNA binding domain, the ETS domain which is their defining feature. This structure, a helix-turn-helix, shows a high level of conservation across members of the family and recognizes a specific 8 nucleotide sequence centred on a GGAA motif (Wei et al. 2010). There is not complete redundancy amongst ETS factors, as evidenced by the fact that knockouts in mice do produce phenotypes (Bartel et al., 2000). However, how ETS factors obtain specificity while sharing a similar binding motif is one of the central questions of the ETS factors.

ETS TFs regulate genes by interaction with co-regulators. In this way, ETS proteins can increase their specificity of action (reviewed in Sharrocks, 2001). For instance, the ternary complex factor (TCF) class of ETS proteins associates with the SRF, increasing their affinity to

DNA (Shore & Sharrocks, 1994). Additionally, ETS1 binds cooperatively with USF1, enhancing

DNA binding and transcriptional activation (Sieweke et al, 1998). Similarly ETS1 is recruited by

PAX5 to the mb-1 promoter, again promoting transcription by releasing ETS1 auto-inhibition

(Fitzsimmons et al., 1996; Fitzsimmons et al., 2009). Additionally, ETV6 has been shown to dimerize, and ERG is shown to heterodimerize, suggesting that ETS proteins may even be able to interact with each other. By interacting with other co-factors, ETS factors could achieve specificity (Carrère et al., 1998; Green et al., 2010).

1.VI ELK1 ELK1 is a member of the TCF subset of the ETS transcription factor family. TCFs, which also include ELK3/NET and ELK4/SAP1 are defined by their ability to create ternary complexes on the serum response element (SRE) in a promoter region, with their binding partner, serum response factor (SRF). To this end, the TCF proteins, with the notable exception of the ELK1 splice variant ΔELK1, have a conserved SRF binding element between their N-terminal ETS DNA binding region and their C-terminal MAPK activation region (Reviewed in Buchwalter et al.

2004).

1.VI.A Structure of ELK1

Figure 3: The structure of ELK1 isoforms The structure of full length ELK1 short ELK1 and ΔELK. A) ETS=E-Twenty Six DNA binding domain, B) S= SRF interaction domain (the B-box), C) R= Repression or SUMOylation domain, D) D and F= MAPK interaction domains, E) TA= transcriptional activation domain. Additionally shown are a A) SIN3A interaction domain and D+E) p300 interaction domain. Adapted from Buchwalter et al., 2004; Q.-J. Li et al., 2003; Yang et al., 2001.

As previously described, the ETS domain is the defining feature of the ETS protein family.

The ETS-domain is the primarily used to bind to the DNA. For ELK1, the ETS domain preferentially recognizes the CCGGAAGT motif (Fig. 3A) (Boros et al., 2009). In addition to its

DNA binding function, the ETS domain in ELK1 has been shown to associate the mSin3A HDAC

26 complex, contributing to repression (Yang et al. 2001). Additionally, in non-phosphorylated

ELK1, the TAD domain interacts more freely with the ETS domain, constituting the inactive conformation (Yang et al. 1999).

The SRF binding domain (the B-box) is the defining region of the TCF subgroup of the

ETS family, which includes ELK1 (Fig. 3B). The ELK1 SRF binding domain binds to the SRF, which in turn, binds to the SRE on the DNA (Shore & Sharrocks, 1994). The preferred SRE consensus sequence is CC(A/T)6GG. There exists a flexible tether region between the ETS region and the

SRE, allowing for variability in distances between the ETS and SRE regions (Treisman et al.,

1992).

It is important to note that, while the SRF is the defining the feature of TCF proteins, such as ELK1, TCF proteins are able to bind to genes that lack SRE regions and do not always need SRF to activate (Boros et al., 2009; Yamazaki et al., 2003). Additionally, a truncated form of ELK1, ΔELK1, has been described, lacking the SRF binding domain. It is therefore unable to bind to SRF, altering the binding specificity (Rao & Reddy, 1993).

The serum response factor increases the affinity of ELK1 to DNA on the FOS promoter

(Janknecht & Nordheim, 1992). In addition to binding ELK1, it has been shown to interact with

GATA4, GATA6, NKX2.5 and the myocardia factors MRTFA and MRTFB (Esnault et al., 2014;

Miano, 2003), whilst SRF is known to improve ELK1 binding to the DNA on the FOS promoter, it is unknown whether ELK1 recruits or is recruited by SRF, and whether this is necessarily true for other binding regions. Additionally, as the TCF family and the MRTF family of TFs binding to

SRF in response to different stimuli, and occupy different loci This suggests that the TCFs and

MRTFs separately associate with SRF at mutually exclusive loci (Esnault et al., 2014; Gualdrini et al., 2016; Zhigao Wang et al., 2004).

ELK1 contains two interaction sites for MAPK proteins, D and F. In ELK1, the D-domain, upstream from the C-domain, is the docking site for MAPKs. Directly downstream of the C- domain, is the F-domain, defined by the FXFP docking motif. This is also capable of docking ERK

MAPKs. However, the FXFP docking site directs S383 phosphorylation sites, whilst the D- domain directs MAPK phosphorylation of the other sites (Fantz et al., 2001) (Fig. 3D).

The repression domain of ELK1 contains ΦKXE motifs, the sites of SUMO addition.

SUMOylated ELK1 can function as a repressor by recruiting HDAC2 (Fig. 3C) (Yang et al. 2003;

Yang & Sharrocks 2004). SUMO can act as both a deactivator, rendering ELK1 unable to act as an activator, or a direct repressor, facilitating the recruitment of co-repressor proteins. In addition to the role of SUMO as an activation inhibitor, SUMO can act as a direct repressor, recruiting HDAC2 (Yang et al. 2003; Yang & Sharrocks 2004). Finally, modification with SUMO has been shown to reduce nuclear shuttling of ELK1, suppressing the differentiation of neuronal cells normally facilitated by ELK1 (Salinas et al., 2004).

The C domain contains the T353, T363, T368, S383 and S389 MAPK phosphorylation sites (Fig. 3E) (Marais et al., 1993). ELK1 is phosphorylated by all three MAPK subgroups, ERK,

JNK, and p38 (Selvaraj et al., 2015). This domain is included in the domain interacting with the co-activator p300 (Q.-J. Li et al., 2003). Recently, Mylona et al demonstrated that ELK1 has different classes of phosphorylation sites, with sites more accessible to ERK phosphorylated rapidly, which are necessary for an initial transcription burst, and sites less accessible to ERK phosphorylated more slowly, which dampen transcription (Mylona et al., 2016). This suggests that the phosphorylation of ELK1 regulates transcription, independent of phosphatases.

1.VI.A.i ELK1 as an activator The phosphorylation of ELK1 increases not only the affinity for DNA, but allows for the recruitment of co-activators, such as CBP/p300 (Li et al. 2003; Yang et al. 1999). In addition, the phosphorylation of ELK1 induces the formation of the ternary complex (Gille et al., 1995).

Finally, phosphorylation of ELK1 via the ERK pathway causes deSUMOylation, thus de- repressing ELK1 (Yang et al., 2003). Though non-phosphorylated ELK1 is able to recruit CBP to the SRE, suggesting constituent binding by the activating complex, but transcription is only activated by phosphorylation (Nissen et al., 2001).

While ELK1 has 8 phosphorylation sites, S383 and S389 are thought to be especially critical for transcriptional activation, as ablation of these sites completely abolished transcription (Cruzalegui et al., 1999; Yang & Sharrocks 2006a).

1.VI.B Relationship to other ETS proteins In many cell types the three human TCFs, ELK1, ELK4 and ELK3, are expressed at relatively equivalent levels (Price et al., 1995). The lack of a serious phenotype upon ELK1 ablation suggests that the presence of ELK1-like transcription factors gives functionally redundancy. This has been shown to be the case in thymus cells, preadipocytes, and B- lymphocytes where ELK1 and ELK4 were shown to be functionally redundant (Clarkson et al.,

1999; Costello et al., 2010; Fitzsimmons et al., 1996). Finally, ELK3 and ELK4 were shown to be functionally equivalent to ELK1 as repressors, playing an opposing role to myocardin in smooth muscle cells (Wang et al. 2004).

In addition, ELK1 exhibits different binding modes. ELK1 has been shown to bind in a

“unique” and a “redundant” fashion (Odrowaz & Sharrocks, 2012a). That is to say, ELK1 has one binding mode in which ELK1 binds to unique regions and one mode in which ELK1 binds to other ETS protein bound regions. The unique binding mode has many distinct characteristics. It has binding region more broadly spread around the TSS, as opposed to a tight peak around the

TSS characteristic of the redundant sites. Many unique sites show an enrichment of both SRF and AP-1 consensus sequences. Finally, the genes directly regulated by ELK1 were divided in to

8 clusters by a k-means clustering. Four of the clusters (2, 4, 7 and 8) were then analysed. Two of the clusters (2, 4) showed both significantly more unique regions and downregulation upon

ELK1 depletion. The other two clusters (7, 8) showed significantly more redundantly bound regions and an upregulation upon ELK1 depletion. GO enrichment of the clusters uncovered a set of genes regulated by ELK1 that control migration (Odrowaz & Sharrocks, 2012b). This suggests that ELK1 has at least two distinct binding loci: unique and shared with other ETS factors. This also suggests that the different binding modes of ELK1 may regulate distinct cellular processes. Control over sets of genes which regulate distinct cellular processes has been demonstrated before. ELK1-mediated gene repression has been demonstrated in smooth muscle cells and ELK1-mediated gene activation has been suggested in neuronal cells (Cesari et al., 2004; Salinas et al., 2004; Zhigao Wang et al., 2004). Again, displaying two different modes of ELK1-mediated gene regulation. While some ELK1 binding patterns have been described - preferential ELK1 consensus sequence, occurrence of nearby SRF and AP-1 binding regions - the mechanisms surrounding the patterns, the pathways that contribute to them, and indeed the role of ELK1 in a variety of cellular processes has yet to be elucidated.

1.VI.C Biological processes involving ELK1 ELK1 is highly expressed in neuronal cells (Price et al., 1995). Additionally, the only clear of effect Elk-1 deletion in mice thus far is inhibition of neuron gene transcription (Cesari et al., 2004). Activation of the MAPK pathways and ELK1 specifically has been shown in response to learning (Cammarota et al., 2000; Selcher, 1999). While the exact mechanism remains unclear, phosphorylation of ELK1 plays a role in neuronal differentiation and dendrite formation, as in this scenario ELK1 plays a role both as a TF and also interacts with cytoskeletal proteins (Robison et al., 1998). Again, the nuclear-cytoplasmic shuttling of ELK1 appears to have some importance in both neuron survival and differentiation, but the full role of ELK1 in the cytoplasm has yet to be elucidated (reviewed in Besnard et al. 2011).

Perhaps demonstrating the varied and cell specific nature of ERK signalling, ELK1 has also been shown to activate differentiation in many cell lines. For example, in human haemopoetic cells, ELK1 acted as a differentiation enhancer by transcribing induced myeloid

30 leukaemia cell differentiation protein (MCL1), which, in turn, promotes viability during differentiation (Townsend et al. 1998; Townsend et al. 1999). In PC12 neuronal cells, ELK1 induces differentiation, however, as discussed earlier, sELK1, a truncated isoform lacking the

NES region, antagonizes ELK1 (Vanhoutte et al., 2001; Vossler et al., 1997). Finally, ELK1 and

ELK4 work synergistically to induce differentiation of preadipocytes by expression of early growth response protein 1 (EGR1), highlighting a possible interaction between ETS factors

(Clarkson et al., 1999).

ELK1 has also been shown to repress differentiation. The zinc finger protein, kruppel-like factor 4 (KLF4) and ELK1 can repress differentiation in smooth muscle cells by cooperatively recruiting HDAC2 and HDAC5 (Yoshida et al., 2008).

Ablation of ELK1 in XaXa cells (female human pluripotent stem cells with two active X chromosomes) resulted in significantly lower differentiation and higher expression of pluripotency factors, whilst overexpression of ELK1 in XaXi cells (female hESCs with one inactivated X chromosome) resulted in an increase in differentiation (Bruck et al., 2013).

2. Project aims ELK1 is known to be both an activator and a repressor and is able to toggle between the two modes (Yang & Sharrocks, 2006b). Even in a single cell line, ELK1 can act as both an activator and repressor in response to a single stimulus, such as epidermal growth factor (EGF) stimulation or FGF2 containing culture (Göke et al., 2013; Odrowaz & Sharrocks, 2012a; Yang &

Sharrocks, 2006a). To answer this apparent paradox, a 2012 study has shown that ELK1 can be parsed into distinct binding modules, with a distinct biological function, and that that these binding modules may explain ELK1’s dual roles (Odrowaz & Sharrocks, 2012a). These findings demonstrate that ELK1 can act as a repressor or an activator in different contexts, the description of which may provide an insight into how ELK1 mediates different biological functions. In addition, PRC2 has been shown to be an repressor of transcription and gatekeeper to pluripotency (Y. Yu et al., 2017). However, their exact regulation and recruitment mechanism remains a mystery (discussed in section 1.III.C).

H1-hESC and H1-hESC derivative cells may be a useful model to parse different modules of ELK1 binding and gene regulation, because H1-hESC cells and all three early derivatives of

H1-hESC are grown in media containing FGF2, which stimulate the ERK2 pathway (Lanner &

Rossant, 2010). The use of FGF2 in pluripotency and differentiation cell culture summarized in

Fig. 4.

hESC FGF2

(Primed) Mesendo.//Meso./Endo. Molecules Mesendo.//Meso./Endo.

FGF2 FGF2 BMP4i TGF-β RA BMP4 TGFβi Mesendoderm

WNT3

Ectoderm Endoderm Mesoderm

Figure 4: Overview of small molecule involved in hESC differentiation Model of differentiation into three early lineages from hESC, noting the small molecules involved in the culture of each lineage. Black arrows indicated differentiation. Circular line indicates self-renewal. Adapted from Borowiak et al., 2009; Chu et al., 2016; D’Amour et al., 2005; Grossman et al., 2017; Hu et al., 2010; Laflamme et al., 2007; X.-J. Li et al., 2005; Loh et al., 2016; Oldershaw et al., 2010; Pankratz et al., 2007; Perrier et al., 2004; Reubinof et al. , 2000; Roy et al., 2006; Takeuchi, Nakatsuji, & Suemori, 2014; Lisheng Wang et al., 2010; Lu Wang et al., 2017; S.-C. Zhang et al., 2001.

Additionally, in a 2013 study done in H1-hESC, ELK1 had been suggested to exist in an active module, co-localizing with ERK2 and a repressive module, co-localizing with members of

PRC2, which have been shown to have a repressive chromatin remodelling function (Göke et al., 2013). The PRC2 is shown to have repressive roles in ESCs, however, their exact regulation and recruitment remains a mystery (Brookes et al., 2012; Lee et al., 2006b). Elucidating the possible relationship between ELK1 and the PRC2 complex may further explain the pathways that govern pluripotency and shed light on the role of ELK1 as a repressor. One possible avenue to describe relationship between ELK1 and the PRCs is the rapid immunoprecipitation and mass spectrometry of endogenous proteins (RIME) protocol. The RIME protocol is a method of immunoprecipitation of crosslinked proteins to identify binding partners using mass

33 spectrometry (Mohammed et al., 2013). Though a previous study has demonstrated a direct

TF-PRC1 interaction, the protein complex purification was performed with GST-tagged targets, the benefit of the RIME protocol is the direct, unbiased measurement of unmodified protein- protein interactions (M. Yu et al., 2012).

Exploring the relationship between ELK1 and the PRC2 complex may further explain the pathways that govern pluripotency, provide an example of PRC recruitment and shed light on the role of ELK1 as a repressor.

Therefore, in this study we will investigate:

1. Potential ELK1-bound genes and regions of interest, using ChIP-seq data to determine candidates for an in vitro study of ELK1-mediated PRC2 repression

2. Potential ELK1 co-factors utilizing rapid immunoprecipitation and mass spectrometry of endogenous proteins (RIME) and co-immunoprecipitation

3. The recruitment of the PRC2 complex by ELK1, and regulation of developmental genes in pluripotent stem cells by ELK1

4. The genome-wide interplay of ELK1 and another ETS transcription factor, ETV1 during differentiation

5. The nature of ELK1 and SRF co-binding during early mesoderm differentiation

3. Materials and Methods 3.I Lab techniques 3.I.A Cell Culture H1-hESC cells (Wicell) were cultured in mTeSR1™ (StemCell Technologies). Plates were coated with Matrigel (Corning) at 37oC for 1 hour before passage. To passage the cells, the cells were coated with a thin coat of ReLeSR™ (StemCell Technologies) and incubated at 37oC for 5 minutes.

For shELK1 treatment, conditioned H1 media was used, containing DMEM/F12

(Invitrogen), 20% (v/v) KnockOut serum replacement (Thermo Fisher Scientific), 1 mM L- glutamine (Gibco), 1% (v/v) nonessential amino acids (Gibco), 0.1 mM 2-mercaptoethanol

(Gibco), and 4 ng/ml basic fibroblast growth factor (Invitrogen). This media was conditioned with CF1 mouse fibroblasts (MTI-GlobalStem) for 24 hr. Media was then vacuum filtered (0.22

µM), and an additional 8 ng/ml of basic fibroblast growth factor (Invitrogen) was supplemented to conditioned medium before usage. To passage the cells, the cells were coated with a thin coat of Dispase (StemCell Technologies) and incubated at 37oC for 5 minutes.

MCF10A cells were cultured in DMEM/F-12 nutrient mixture (Life Technologies), 10

µg/ml insulin (Sigma), 100 ng/ml cholera toxin (Sigma), 0.5 µg/ml hydrocortisone (Sigma), 20 ng/ml EGF (Sigma) and 5% (v/v) horse serum (Biosera). To passage the cells, the cells were coated with a thin coat of trypsin (Gibco) and incubated at 37oC for 5 minutes.

3.I.B Retinoic acid treatment Cells were dissociated with TrypLE™ Express and seeded at a density of 5x105 per cm2 in mTeSR1™ supplemented with 10 µM Y-27632. After 24 hours, cells were grown in in mTeSR1™ supplemented with 5 µM Retinoic acid (RA) (sigma) for up to 96 hours.

3.I.C Mesoderm Differentiation Cells were treated with ROCK inhibitor and dissociated with TrypLE™ Express, as described in section 3.I.B. Seeded at a density of 5x105 per cm2 in mTeSR1™ supplemented with 10 µM Y-27632. After 24 hours, cells were grown in STEMdiff™ Mesoderm Induction

Medium (StemCell Technologies) for an additional 3 days.

3.I.D Neural Progenitor Cell Differentiation Cells were treated with ROCK inhibitor and dissociated with TrypLE™ Express, as described in section 3.I.B. Cells were seeded at a density of 2x105 per cm2 in mTeSR1™ supplemented with 10 µM Y-27632. After 24 hours, cells were grown in STEMdiff™ Neural

Induction Medium (StemCell Technologies) for an additional 5 days.

3.I.E IL-6 Cell stimulation Cells were treated with ROCK inhibitor and dissociated with TrypLE™ Express, as described in section 3.I.B. Cells were then cultured in mTeSR1™ for 96 hours. After 96 hours, the cells were stimulated with 100 ng/mL of IL-6 (Thermo Fisher Scientific, PHC0066) for timepoints ranging from 0-60 minutes, the cells were collected in RIPA buffer or harvested for

ChIP see Crosslinking and lysing cells.

3.I.F shRNA treatment Cells were treated with ROCK inhibitor and dissociated with TrypLE™ Express, as described in section 3.I.B. 5x105 cells were treated with 7.5 µL of TransIT®-LT1 (Mirus) plus

2.5µg of shRNA plasmid prepared in 250 µL of OptiMEM. shELK1 plasmid was a pSuper plasmid containing the shRNA hairpin for ELK1: GCCAGAAGTTCGTCTACAA (Göke et al., 2013) An empty pSuper plasmid was used as a control.

3.I.G siRNA transfection Cells were treated with ROCK inhibitor and dissociated with TrypLE™ Express, as described in section 3.I.B. Express and seeded at a concentration of 5x105 per cm2 in mTeSR1™ supplemented with 10 µM Y-27632. Each 5x105 cells was treated with 7.5 µL Lipofectamine

RNAiMAX reagent (Thermo Fisher Scientific) and 2.5 µL of siRNA (20 µM stock concentration), prepared in 150 µL Opti-MEM (Gibco). Cells were treated with siRNA every 48 hours.

3.I.H Crosslinking and lysing cells Cells were incubated at room temperature with 1% (v/v) formaldehyde (Sigma), for 10 minutes. The crosslinking reaction was then quenched with 0.125 M glycine for 5 minutes.

Cells were washed with ice cold 1x PBS. 3x106 cells were then harvested in FA cell lysis buffer, rotated for 10 minutes at 4oC, and the nuclei pelleted at 13.1krpm at 4oC for 5 minutes and the supernatant discarded. Cells were resuspended in FA Cell Lysis Buffer, rotated for 10 minutes at 4oC, pelleted at 13.1krpm at 4oC for 5 minutes and the supernatant discarded. Nuclei were then resuspended in 1% SDS solution, rotated for 10 minutes at 4oC and the chromatin pelleted at 13.1krpm at 4oC for 5 minutes and the supernatant discarded. Chromatin was then suspended in 0.1% SDS solution, rotated for 10 minutes at 4oC, pelleted at 13.1krpm at 4oC for

5 minutes and the supernatant discarded. Chromatin was then resuspended in 0.1% SDS solution and sonicated to produce chromatin fragments of 100-500 bp.

3.I.I Chromatin Immunoprecipitation 3x106 cells were seeded per immunoprecipitation (IP). For 3x106 cells seeded, 12.5 µl of Dynabeads® Protein G (Thermo Fisher Scientific) and 1.25 µg of antibodies were conjugated at RT for 2 hours, after which, conjugated beads were washed with 0.1% SDS buffer. The lysate was then rotated with conjugated beads overnight at 4oC. The next day, beads were washed sequentially with 0.1% SDS solution, high salt wash, NP40/LiCl wash and TE. The beads were then resuspended in ChIP elution buffer and shaken at 690C at 1000 rpm for 1 hour. This supernatant was then transferred to a new tube, treated with 1:50 Proteinase K (Roche) and shaken at 550C at 600 rpm for 1 hour. For siELK1 and MIM treatment, DNA was then further purified using the QIAquick PCR purification kit (Qiagen).

For shELK1 and RA treatment, the eluted DNA was mixed with equal volume of phenol- chloroform (Thermo Fisher Scientific). The aqueous layer was isolated following centrifuging,

37 for 10 minutes at 13.1krpm at 4oC, and mixed 1:1 with isopropanol and frozen at -80oC for 30 minutes. The solution was then spun at 13.1krpm at 4oC for 20 minutes and the supernatant discarded. The pellet was then washed with 70% ethanol and spun two more times. It was then air-dried for 24 hours. And 100 µl of H20 was added.

3.I.J Co-Immunoprecipitation 3x106 cells were seeded per IP. For 3x106 cells seeded, 10 µl of Dynabeads® Protein G

(Thermo Fisher Scientific) and 1 µg of antibodies were conjugated at RT for 2 hours, after which, conjugated beads were washed with 0.1% SDS buffer. The lysate was then rotated with conjugated beads overnight at 4oC. The next day, beads were washed with 3x with 0.1% SDS solution. The beads were then resuspended in 0.1% SDS solution and boiled at 99oC before western blotting.

3.I.K RNA purification RNA was purified with an RNeasy Kit (Qiagen) using the manufacturer’s protocol.

3.I.L PCR (siELK1, MIM and NPC treatments) Component Amount SybrGreen (Qiagen) 5 µl One-Step RT Reagent for RT-PCR (or H20 for ChIP- 0.1 µl qPCR) (Qiagen) H20 2.84 µl Primer (50 µM) 0.06 µl ChIP sample or RNA sample (diluted to 20ng/ µl) 2 µl A PCR reaction was then run with the following settings:

50 oC 30 min (only for RT-PCR), 95 oC 15 min, then [95oC 20 sec., 57oC 30 sec., 72oC 30 sec.] x 50 cycles, melt curve 72-95oC

Data was collected with the RotorGene Q cycler (Qiagen) and RotorGene R3000 cycler

(Corbett) and analysed with the RotorGene software (Qiagen)

ChIP samples in section 4.V.B were analysed with the BioMark HD System (Fludigim) used as per the manufacturer’s instructions. The 14 cycle Specific Target Amplification was used

38 for pre-amplification of the ChIP product and Exonuclease I treatment was used to remove unincorporated primers. BioMark Data Analysis (Fluidigm) was used for data analysis.

3.I.M RT-PCR (shELK1 and RA treatments) Cells were collected into 350 µl of RNAzol (Sigma) and spun at 13.1 krpm at 4oC for 20 minutes and the supernatant discarded. The aqueous layer was then mixed 1:1 with isopropanol and frozen at -80oC for 30 minutes. The solution was then spun at 13.1 krpm at

4oC for 20 minutes and the supernatant discarded. The pellet was then washed with 70% ethanol and spun two more times. It was then air-dried for 24 hours.

The following reaction was then performed with the 2-step RT-PCR kit (Thermo Fisher

Scientific)

1. 500 µg of RNA was diluted in 8µl of water. 1µl 10x DNAase buffer, and 1 µl DNase 2. 37oC for 30 min 3. Add 1 µl Oligo dT and 1 µl dNTP 4. 65oC 5 min, place on ice for 2 min 5. Add 4 µl 5x FS buffer, 2 µl DTT, 1 µl RNaseOUT and 1 µl SuperScript2 8. 42oC 50 min, 70oC 15min 9. Add 80 µl DEPC treated water Component Amount Power SybrGreen (Thermo Fisher Scientific) 5 µl Primers (10 µM) 0.4 µl HiRox 0.2 µl

H20 2.6 µl cDNA from the above reaction, or purified ChIP DNA 2 µl

A PCR reaction was then run with the following settings:

50 oC 30 min (only for RT-PCR), 95 oC 20 min [95oC 20 sec., 55oC 30 sec., 72oC 30 sec.] x 40 cycles, melt curve 72-95oC

Data was collected with the ViiA 7 (Thermo Fisher Scientific) and analysed with Viia7

V1.2 software (Thermo Fisher Scientific)

3.I.N Rapid immunoprecipitation of endogenous proteins 16 x 106 MCF10A cells were seeded for Rapid immunoprecipitation and mass spectrometry of endogenous proteins (RIME) (Mohammed et al., 2013). Cells were incubated

39 at room temperature 1X PBS containing 100 µM DMA (Sigma) for 20 minutes. Cells were next incubated at room temperature in 1X PBS containing 11% (v/v) ultrapure formaldehyde

(Polysciences), for 10 minutes. The crosslinking reaction was then quenched with 0.125 M glycine for 5 minutes. Cells were then harvested and incubated with antibody-bound

Dynabeads overnight as previously described. See Co-IP

For RIME, beads were washed three times with RIPA buffer and additional three times with 100mM ammonium bicarbonate (AMBIC). Cells were then suspended in 10 µl of 100 µM

AMBIC containing 100 μg/ml trypsin (Promega) and incubated overnight with trypsin at 37oC.

Lysate was eluted into a separate 1.5 mL tube and beads were washed with 10 µl of 100 µM

AMBIC, which was added to the digested lysate.

Raw data were analysed using Thermo Xcalibur (Thermo Fisher Scientific), the peptides were then analysed using Scaffold4 (Proteome Software).

3.I.O Western Blot Analysis For most Western blot analysis, cells were harvested in RIPA buffer by scraping on ice.

Cell lysates were then centrifuged at 13.1krpm at 4oC for 2 minutes. The supernatant was then measured using a Bradford Protein Assay. 1 µL of sample was added to 1 mL of Coomassie

Brilliant Blue (Thermo Fisher Scientific) and measured against BSA standards ranging from 0.2 mg/mL to 2 mg/mL. Approximately 20 µg of protein was used for each well. 1x SDS loading buffer was added to the lysate, which was then boiled at 99oC for 10 minutes. Proteins were resolved on the 12% gel in 1x SDS running buffer, and transferred to a nitrocellulose membrane using transfer buffer. Finally, cells were incubated with primary and secondary antibodies, diluted 1:500-2000 and 1:10000, respectively, in Licor Odyssey Buffer and imaged on the Odyssey Imaging System (Licor biosciences).

3.II Bioinformatic analysis 3.II.A ChIP-seq analysis Reads were mapped using Bowtie2 (v2.2.9) with default settings (Langmead &

Salzberg, 2012). Bowtie2 output was then sorted, compressed and unaligned reads removed

40 using samtools (v0.1.18), using the settings -Shu -F4, which removed unmapped reads (H. Li et al., 2009). Finally, peaks were called with MACS2, using the default settings (Yong Zhang et al.,

2008).

3.II.B RNA-seq analysis Reads were then aligned to the RefSeq genome (hg19/GRCh37) using STAR (v2.5.3).

Reads were then sorted, compressed and unaligned reads removed using samtools, using the settings -Shu -F4, which removed unmapped reads. Processed reads were then compared using the Cuffdiff function of Cufflinks (v2.2.1) (Trapnell et al., 2013).

3.II.C Peak Intersections After MACS2 peak calling, narrowPeak files were intersected with the intersectBed tool in bedtools (v2.21) (Quinlan & Hall, 2010), using the -f 0.1 and -r settings, creating a reciprocal overlap of 10%.

3.II.D Tag Density Graphs Mapped, sorted and compressed ChIP-seq files were converted to BED files using the bamtobed tool in bedtools. BED files were converted to tag directories using the makeTagDirectory.pl tool in HOMER (v4.8.3) (Heinz et al., 2010). Finally, ChIP-peaks were annotated using annotatePeaks.pl tool in HOMER, using the settings -size -2500, 2500 -hist 25 - norm 0, which created a tag density profile with a 25 bp bin, averaged to tag count in all tag directories, 2500 bp on either side of the peak centre.

3.II.E Motif Analysis Overrepresented motifs were identified using the findMotifGenome.pl tool in HOMER using the settings -size 200. Homer creates matched genomic background regions with GC% content.

3.II.F Graphics PCR plots were prepared using Prism7 (GraphPad). Western blots were imaged with the Odyssey Imaging System (Licor) and processed and quantified with ImageJ. ChIP-seq experiments were visualized with the IGV genome browser.

3.II.G Accession numbers For the H1-hESC, ChIP-seq data can be accessed using the following accession numbers from the European Nucleotide Archive: ELK1 (ERP002417), EZH2 (ERP001833), SUZ12

(SRR400428), and ERK2 (ERS226580). All other data was downloaded from the ENCODE or

Epigenomic Roadmap databases.

3.II.H Primer Design Primers were designed using either Primer3Plus (primer3plus.com) or the IDT RT-PCR primer design tool (https://www.idtdna.com) and were checked with the in-silico PCR tool from UCSC (https://genome.ucsc.edu/cgi-bin/hgPcr). The primers were designed to give a single product of 80-300 bp

3.II.I Statistical Analysis For both ChIP-qPCR and RT-qPCR, we assumed a two-tailed normal distribution, and we performed a Student’s t-test to calculate statistical significance, setting a p-value threshold at 0.05. The data was presented as the arithmetic mean +/- standard error of the mean.

3.III Materials 3.III.A siRNAs Gene Supplier ELK1 Dharmacon (L-003885-00) ETV1 Dharmacon (L-003801-00) SRF Dharmacon (L-009800-00) Non-targeting control Dharmacon (D-001206-13)

3.III.B PCR Primers 3.III.B.i RT-PCR Name Forward (5’ to 3’) ADS Numbers (Alternate Name Reverse (5’ to 3’) ACTB CATCCACGAAACTACCTTCAACTC 5450

ATACTCCTGCTTGCTGATCCA 5451 B2M TCGCGCTACTCTCTCTTTCT 5286 TCTCTGCTGGATGACGTGAG 5287 BTG2 TTGTTTTTCTGCTGGGCTTT 6262 TGCCCATATAAGGGAAGCAC 6263 ELK1 TCAGGGTAGGACACAAACTTG 6089 CGCAAGAACAAGACCAACATG 6090 ETV1 TCCCTCCATCGCAGTCCATA 5552 (ER71) GGAAAGCTTTGGCTGGCCG 5553 FAM32A CTCAAAAAGGGGTTGGGTTT 6260 TGCCCTTCGATTCCTATCTG 6261 FOXC1 AGTAGCTGTCAAATGGCCTTC 6038 TGCCTTGATGGGTTCCTTTAG 6039 FOXG1 TGGGACCTACTCCCTCAACC 5980 TCCCGTCGTAAAACTTGGCA 5981 FOXJ3 CCATCAGACCTTGAAACTGTG 3743 CAACACATACAGCACCATCC 3744 GAPDH ACAGTCAGCCGCATCTTCTT 2184 TTGATTTTGGAGGGATCTCG 2185 GSC GAGAACCTCTTCCAGGAGAC 4565 CCTTCCTCTTCCCTCTTCTC 4566 HAND2 GCTACATCGCCTACCTCATG 6032 CTGCTCACTGTGCTTTTCAAG 6033 KLF4 TACCAAGAGCTCATGCCACC 4800 GGTGTGCCTTGAGATGGGAA 4801 LHX2 AAGTTCAGGCGCAACCTCTT 5978 AAGACGGACGTCACAGTTGG 5979 LINC1412 GAGGCTTAAGGTCTTCAGCG 4948 GGACGGCTTTTCGGGAAAC 4949 MEIS1 CATCTTTCCCAAAGTAGCCA 2450 GTTCCTTGACTTACTGCTCG 2451 MIXL1 TTCCATTGGTCTGCATCCCT 5290 AGAGACGGGGTAGAGTGACT 5291 MSX2 GGATGTGGTAAAGGGCGTG 6034 CGGTCAAGTCGGAAAATTCAG 6035 MYC CCTCCTCGTCGCAGTAGAAA 4988 GCTGCTTAGACGCTGGATTT 4989 NANOG ATAACCTTGGCTGCCGTCTC 4794 AGCCTCCCAATCCCAAACAA 4795 OCT4 CCTTCGCAAGCCCTCATTTC 4792 (POU5F1) TAGCCAGGTCCGAGGATCAA 4793 PITX2 CAGCGGACTCACTTTACCAG 6036 GACGATTCTTGAACCAAACCC 6037 PODXL CCAAAACACCTTCTCCCACTG 6010 GATCAATTTCTCATCCGAAGCG 6011 SOX1 GGACCGCACGGAATTTGAAC 5300 GGATCAGGGACCTGTCACAC 5301 SOX17 GGACCGCACGGAATTTGAAC 5300 GGATCAGGGACCTGTCACAC 5301 SOX2 ATGGACAGTTACGCGCACAT 4796 CGAGCTGGTCATGGAGTTGT 4797 T ACCCAGTTCATAGCGGTGAC 5292 (BRACYURY) CCATTGGGAGTACCCAGGTT 5293 TBX3 TGGGATCAGTTTCACAAGCG 6030 TTTATCCAGCCCAGAACATCTC 6031

TERT AGAGTGTCTGGAGCAAGTTG 6085 GATGAAGCGGAGTCTGGAC 6086 WNT3 (WNT3B) GACTTCGGCGTGTTAGTGTC 5294 TGTGGTCCAGGATAGTCGTG 5293 ZFP42 GTAGTGCTCACAGTCCAGC 6087 CTTTGCCCGTTTCTTCAGTTG 6088

3.III.B.ii ChIP-qPCR Name Forward (5’ to 3’) ADS Number Reverse (5’ to 3’) ANGPTL2 ATGGAGTGTGGGTCCTCAAG 6220 AGTTCCTCCTCAGGGAGGTC 6219 ARC AGCACAGTGCCATCAGGAG 6203 GGAGGCAGAAGGGACCTC 6204 BTG2 CTAACCTGGAACCAGCCAAA 6213 ATCCGTCCCTATCTCCCATC 6214 CFL1 AGGACAAGAGACTCGAGGGG 6189 GTAGCCCCAGCCAAGCTAAA 6188 CFOS GAGCCCGTGACGTTTACACT 1680 TTGAAGCCCGAGAACATCAT 1681 CYR61 CCGAAGCTAGATGACGGAGT 6254 TTGCCAAGAATCGAGGTTTC 6255 EGFL6 ACACATAGCCCAGCCATGA 6217 GGGCTCAAGATTGCCAAATA 6218 EGR1 GACCCGGAAATGCCATATAA 6199 TATCGGGCCACTCCAAATAA 6200 EGR1_2kb AAGTGATCCTCCAGCCTCCT 6135 AAGTGGGTGAATCGCTTGAG 6134 EGR1_TTS AGAGCTCCATTCTTGCCCAT 4769 TAGGTTCTTTTGGGCCCAGT 4768 EGR2 AATTCCGGTTCTCTGGGACT 6197 GCTCGGTTTCTTTCCGAAGT 6198 EGR2_Intron CAGTCTGTGGGCCTCAATTT 6001 CCGCTCACATAGGTCCATTT 6000 EGR3 CCCCTTCTCCTTCTCGATTT 6252 GGGTTCCGTTCTTCTTTCCT 6253 HCN2 ACCTTCGAGCACCAGTCTTG 6242 CTCGTGGGGGAGGTTTCTA 6243 IER2 CTAATATGGGCAACCGGAAG 6215 CCGCTGACTTCCACAACTAA 6216 IRF3 TGGGTAACAGACCCAAAAGC 6221 ACGCTCAATTTGCATGTGAC 6222 ITE1 GTTTGGTTTCCACGGTGA 5666 GCCAAATATGGGCAGAGC 5667 JUNB CAGATCTCCAGGGTTGGATG 6201 GGCAGAATCGGTCCTTGTAT 6202 LIMA1 GAGGGAGAGGGGAAGAGAGA 6240 AGAGCTGGGTTTGCCTTTCT 6241

MAP3K14 CCTACGCCAACCAATGAGAC 6211 ACATCGTCCGGAAATAGTGC 6212 MAP3K14_STAT AGCTGCGTTCTCGAGGTTAC 6246 GAAGTCAGTGGCAGGGAGTG 6247 MAPK4 CCAAGCCAGGTCTGCTTATC 6225 CATGACATTCCCAGGTTGTG 6226 MAPK4_STAT CTGGGGAATGGAGAAAAACA 6248 TTGGCTCAGGCTTAAAGATTTC 6249 MCL1 AGACCCCGACTCCTTACTGG 6244 CGCCCTAAAACCGTGATAAA 6245 NDUFS5 CCATTGTCCCCCAAACATAG 6229 TCGCCAAGTGAAGATCAGTG 6230 NR3C2 CCACAGTCCAGCAACAGCTA 6231 CCCACTACTCTGCCCTCAGA 6196 PTGES3L GGGCCGCTATCTTTAGATCC 6236 AAGGATGAAGCTGTCCCAGA 6237 RPL24 CCTCCCCAATATCCTTCGAT 6232 AGCTGTCAGGGAAAACGAGA 6233 SIRT6 CTCAGACGCGCTCACCTC 6238 AACGCGGTTCCTCCTTCTT 6239 SPARCL1 TGTGTCCCTGCAGACTTCAC 6209 TTGTCCTCAGAAAAGCAGCA 6210 STK35 GGCTGGAGTTACTGCCACTG 6234 GGTAGAAGGGATTGGCTGAA 6235 TADA3 TGGCAAAGGTGACAAGAAGG 6207 CACCTAGGGCTGTCTCGGTA 6208 TCF7 AGTAAGCGGGGTCAGGAGTT 6227 GAGAGAGACGTCGGACAAGC 6228 VDAC3 CCACAGTCCCCTTTTATGGA 6205 ATCTGGAGTCTTCCGGTTCA 6206

3.III.B.iii RT-PCR (shELK1 and RA treatment) Name Forward (5’ to 3’) Reverse (5’ to 3’) GAPDH ACATCGCTCAGACACCATG TGTAGTTGAGGTCAATGAAGGG ELK1_1 CGCAAGAACAAGACCAACATG TCAGGGTAGGACACAAACTTG ELK1_2 CTGCTTCCTACGCATACATTG GGATGGAAACTGGAAGGAGAG NANOG CCTATGCCTGTGATTTGTGGG TTTGGGACTGGTGGAAGAATC OCT4/POU5F1 AGAACATGTGTAAGCTGCGG GTTGCCTCTCACTCGGTTC MYC TTCGGGTAGTGGAAAACCAG AGTAGAAATACGGCTGCACC SOX2 AGAAGGATAAGTACACGCTGC TCCAGCCGTTCATGTGC BMP4 GCACTGGTCTTGAGTATCCTG TGCTGAGGTTAAAGAGGAAACG MEIS2 TCCACAAATCTCGCTGACC GTCTAAACCATCCCCTTGCTC MSX2 CGGTCAAGTCGGAAAATTCAG GGATGTGGTAAAGGGCGTG OLIG3 ATTTCCCGCCTAAAGCCTC CCTCAGGTACATCTCATCCATG ONECUT2 AGTAAACTCAAATCTGGCAGGG TGTTTGGTTCTTGCTCTTTGC PAX7 GAGGATGAAGCGGACAAGAA TCAGTGGGAGGTCAGGTT POU3F2 AAAGTAACTGTCAAATGCGCG GCTGTAGTGGTTAGACGCTG SIX1 GCATCAGCTCCAAGACTCTC ATTTACAAGTGTCCCTAGTCGC ZFHX3 TGAAGATGTTGAAGGACCCAG AAGGAGATGCGTTTGGAGG

3.III.B.iv ChIP-qPCR (shELK1 and RA treatment) Name Forward (5’ to 3’) Reverse (5’ to 3’) Location (UCSC hg19) Neg.Reg.3 CTGGTGTGGAGATTCCAGCCAAA GTGGGAGGAACATGCTTCGGAAC chr6:31140806 +31140978 ABLIM2 GGCTTGCTCAGAAACACTCC ATCCTTCCTGAGTCCCCACT chr4:7962305 +7962491 BMP4 CATCGGGGAGACAAGCTAGA GAGGAAGGAAGATGCGAGAA chr14:54423394 +54423549 MSX2 TCTGCAGTCTCTCTCCAGCTC AGAGGGGAGGGCTGGATCT chr5:174160162 +174160248 MEIS2 AGTAGGTGTTGGCAGGTTGG CTATGGCCACCACGACTTC chr15:37392548 +37392661 SIX1 GGAGGTAGGGAGTGGGTGAG CATTGATTTGTGCGGAGTTG chr14:61116466 +61116564 ZFHX3 CCTAGGTAGGTGGCAACTGG CGAGTCTTGGCTGAACTTCC chr16:73081496 +73081592 PAX7 CCTGGTCTCCGGGTTCTG ACAAACACTCCAACCCCAAG chr1:18957748 +18957838 POU3F2 TCGCAAAAGAGGTACCTTGG CTAGGCTGTCTGGGCCTTC chr6:99290321 +99290403 OLIG3 TTCCTAGAGGCGAGCTGAAG GTAGGCAGGAATCGAGTGGA chr6:137810307 +137810430 ONECUT2 ACTGACACTCCCTGGAGCAG AAGTCCAGACGCCGAGAGT chr18:55097822 +55097917 ZIC1 AGTCCTACACGCATCCCAGT CAAGCCGAGAGCCAAGAG chr3:147130428 +147130527

3.III.B.v Nucleosome ChIP-qPCR (shELK1, siELK1 and RA treatments) Name Forward (5’ to 3’) Reverse (5’ to 3’) Location (UCSC hg19) ACTB CAAAGGCGAGGCTCTGTG CCGAAAGTTGCCTTTTATGG chr7:5570187+5570304 B2M GGGTTTCCGTTTTCTCGAAT GCCCCAGAGATGCTAAGTGA chr15:45003314+45003401 BMP4 GGCTGTGTGCAGAACTGTGT GGGGTCTACCTCAGGGTCAT chr14:54424065+54424190 EGR1 GCCCTAGGGTGCAGGATG GGGAGGACCCGGAGTGAC chr5:137800982+137801051 EGR2 CACTCCGTTCATCTGGTCAA GTTTTGTGCACCAGCTGTCT chr10:64575628+64575743 GAPDH TGAGCAGTCCGGTGTCACTA ACGACTGAGATGGGGAATTG chr12:6643165+6643316 MEIS2 AGGGAAAGAAGCCGATGAAT CTGCTCGCTGCTTGATGAT chr15:37391494+37391563 MSX2 CTCTGGGCACAGAATTTGCT GCCGAAAAGTCAGAGGAAGA chr5:174161875+174161988 NANOG TTAGTGCTGGAACCCCACTC GCTTTTTCCCTCTGGCTCTT chr12:7940954+7941112 OLIG3 TGCTTGCGTGTAAACTGTGG CTCTTTTCCTCGTGGTCTGC chr6:137808924+137809012 ONECUT2 CGGCCATGAACAACCTCTAC GACCGTAGTTGGGCAGACTC chr18:55103562+55103699 OTX2 CAGCCTCATGGGAGGTTAGA GAAGGGTGAAGACTGCAAGG chr14:57276881+57276991 PAX7 GCGTCCTTCCTAAACATCCA AAAAACACAGGAGCGGGTCT chr1:18958899+18959021 POU3F2 CACTCTATCGCTTCCCAAGG CTGCGTCTAGAGCCCACTTT chr6:99290598+99290741 SIX1 CCGGTTCTTAAACCAGTTGC AAGGAGAAGTCGAGGGGTGT chr14:61115383+61115514 SOX17 GAATGGACGCTCGGTATGTT GAGACTCGAAAAGCCGTCTG chr8:55370164+55370256 SOX2 TACAGCATGATGCAGGACCA TCATGTAGGTCTGCGAGCTG chr3:181430659+181430800 T GGCTCTCACCATCTGGAAAA AGCGAGGAGGACACTTCTCA chr6:166582062+166582162 ZFHX3 CTTTTCCTCGGGCACAATAA GGGGATGTGATGGTTTTCAC chr16:73083218+73083371 ZIC1 CCAAAGGAAAGAGCTGAGGA AAGCCTCCTCAATCCCAAAT chr3:147129301+147129421 3.III.C ChIP Solutions FA Cell Lysis Buffer 10 mM Tris-HCl, pH 8.0 0.25% (v/v) Triton-X100 10 mM EDTA

0.1 M NaCl H20 Before cell lysis, buffer was chilled on ice and supplemented with 1:100 cOmplete™ protease inhibitor (Sigma)

1% SDS Solution 50 mM HEPES-KOH, pH 7.5 150 mM NaCl 2 mM EDTA 1% (v/v) Triton-X100 0.1% (w/v) Na-DOC 1% (w/v) SDS H20 Before nuclear lysis, buffer was chilled on ice and supplemented with 1:100 cOmplete™ protease inhibitor (Sigma)

0.1% SDS Solution 50 mM HEPES-KOH, pH 7.5 150 mM NaCl 2 mM EDTA 1% (v/v) Triton-X100 0.1% (v/v) Na-DOC 0.1% (w/v) SDS H20 Before washes or sonication, buffer was chilled on ice and supplemented with 1:100 cOmplete™ protease inhibitor (Sigma)

High Salt Wash 50 mM HEPES-KOH, pH 7.5 500 mM NaCl 2 mM EDTA 1% (v/v) Triton-X100 0.1% (w/v) Na-DOC 0.1% (w/v) SDS H20

ChIP Elution 50 mM Tris-HCl, pH 7.4 10 mM EDTA 1% (w/v) SDS H20

NP40/LiCl Wash 10 mM Tris-HCl, pH 8.0 0.25 M LiCl 1 mM EDTA 0.5% (v/v) NP-40 0.1% (w/v) Na-DOC H20

TE 10 mM Tris-HCl pH 8.0 1 mM EDTA

3.III.D Western Blot Solutions 12% (v/v) Gel Lower Buffer (1.5 M Tris-HCL, 0.4% (w/v) SDS) 12% (v/v) Bis/Acrylamide

H20 TEMED APS

7% (v/v) Gel (Stacking Gel) Upper Buffer (0.5 M Tris-HCL, 0.4% (w/v) SDS) 7% (v/v) Bis/Acrylamide H20 TEMED APS

RIPA buffer 150 mM NaCl 50 mM Tris, pH 8.0 1.0% (v/v) IGEPAL® CA-630 1 mM EDTA H20

Transfer Buffer 1x Towbin Buffer Methanol H20

SDS Running Buffer (10x) 250 mM Tris 1.9 M Glycine 0.1% (w/v) SDS

5x SDS Loading Buffer 210 mM Tris-HCL, pH 6.8 235 mM SDS 21.6% (v/v) Glycerol 0.002% (w/v) Bromophenol Blue 10% (v/v) β-Mercaptoethanol

3.III.E Antibodies Antibody Supplier ELK1 Abcam (ab32106) ER81/ETV1 Abcam (ab81086) ERK1/2 Cell Signalling Technology (9102) EZH2 Cell Signalling Technology (3147) H3K27me3 (siELK1 ChIP) Diagenode (C15410069) H3K27me3 (shELK1 and RA ChIP) Active Motif (61017) NANOG Abcam (ab21624) OCT4 Abcam (ab19857) phELK1 Cell Signalling Technology (9186) phERK1/2 Cell Signalling Technology (9106) phSTAT3 Cell Signalling Technology (9145)

RBBP7/RPBP46 (Blotting) Santa Cruz (sc-8272) RBBP7/RPBP46 (Immunoprecipitation) Abcam (ab3535) SOX2 Abcam (ab97959) SRF (Blotting) Novus Biologicals (NBP1-51976) SRF (Immunoprecipitation) Cell Signalling Technology (5147) SSEA4 Abcam (ab16287) STAT3 (Blotting) Cell Signalling Technology (4904) STAT3 (Immunoprecipitation) Abcam (ab5073) SUZ12 Active Motif (39357) T/Brachyury R&D Systems (AF2085) TRA1-60 Abcam (ab16288) TUBULIN Sigma (T9026) Rabbit IgG Millipore (12-370)

Secondary Antibody IRDye 800CW Mouse Licor Biosciences (926-32210) IRDye 800CW Goat Licor Biosciences (926-32214) IRDye 680LT Rabbit Licor Biosciences (926-68023)

4. Results 4.I ELK1 binding regions can be divided into different modules Göke et al. demonstrated that ELK1 occupies two distinct sets of genomic loci in H1- hESC, one of which co-localized with members of the PRCs and lacked ERK2 co-localization, and suggested that these modules may have biological significance (Göke et al., 2013).

Therefore, to establish a pool of candidate genes of further interest in exploring an ELK1-PRC2 interaction, we re-analysed some of the ChIP-seq data and partitioned the H1-hESC ELK1 peaks by a variety of means.

4.I.A Genomic distribution of ELK1 modules The previous analysis of ELK1 binding was centred on TSSs. However, we chose to reanalyse the ELK1 binding loci, including all of the peaks. We first intersected the ELK1 H1- hESC ChIP-seq dataset with binding peaks of ERK2, SUZ12, and GABPA, another ETS TF (Fig. 5).

We then separated the ELK1 and ERK2 ChIP-seq peaks into ELK1-ERK2, ELK1+ERK2 and ERK2-

ELK1 modules, which are, respectively, ELK1 peaks not overlapping with ERK2 peaks, shared

ELK1 and ERK2 peaks and ERK2 peaks not overlapping with ELK1 (Fig. 5B). We see that the

ELK1+ERK2 module has a greater percentage of peaks proximal (within 1000 bp) to the TSS relative to the ELK1-ERK2 module.

We next intersected ELK1 and SUZ12 ChIP-seq peaks into ELK1-SUZ12, ELK1+SUZ12 and

SUZ12-ELK1 modules, which are, respectively, ELK1 peaks not overlapping with SUZ12 peaks, shared ELK1 and SUZ12 peaks and SUZ12 peaks not overlapping with ELK1 (Fig. 5C). We see reciprocal results to the ELK1 and ERK2 modules, i.e. the ELK1+SUZ12 module have more proportionally more peaks distal (more than 1000 bp) to the TSS relative to the ELK1-SUZ12 module.

Additionally, ETS proteins are known to overlap binding sites. To establish if PRC2 co- localization was unique to ELK1, we intersected ELK1 and GABPA, another ETS protein with an available H1-hESC dataset. We separate ELK1 and GABPA ChIP-seq peaks into ELK1-GABPA,

ELK1+GABPA and GABPA-ELK1 modules, which are, respectively, ELK1 peaks not overlapping with GABPA peaks, shared ELK1 and GABPA peaks and GABPA peaks not overlapping with ELK1

(Fig. 5D). A larger portion of peaks in the ELK1+GABPA modules were proximal (within 1000 bp) to the TSS relative to the ELK1-GAPBA modules.

A ELK1

Total=818 Legend Legend Legend B C Legend D Legend Legend ELK1-ERK2 ELK1-SUZ12 ELK1-GABPA Legend Legend Legend Legend Legend Legend Legend Legend Legend Total=667 Total=710<-10001Legend bp Total=573Legend LegendLegend -10000 to -1001 bp Legend Legend ELK1+ERK2 ELK1+SUZ12 ELK1+GABPA -1000 to 0 bp Legend Legend 1 to 1000 bp Legend Legend 1001 to 10000 bp Legend Legend Total=151 Total=108>10001Legend bp Total=245Legend Legend Legend Legend Legend ERK2-ELK1 SUZ12-ELK1 GABPA-ELK1 Legend Legend Legend Legend Legend Legend Legend Legend Legend Total=3103 Total=1858Legend Total=14194Legend Legend ERK2 SUZ12 GABPA

Total=3257 Total=1965 Total=14439 <-10001 bp -10000 to -1001 bp ELK1+ERK2 -1000 to 0 bp 1 to 1000 bp 1001 to 10000 bp Total=151 >10001 bp

Figure 5. Genomic distribution of transcription factor binding loci The genomic distribution of binding loci of A) ELK1 alone and ELK1 intersected with B) ERK2 C) SUZ12 and D) GABPA. The distance is measured from the centre of the binding peaks to the nearest TSS (0 bp).

4.I.B ELK1 loci with low ERK2 enrichment correlate with high PRC2 enrichment Having shown the relative binding distance of ELK1 to the TSS, we wanted to examine the relative binding of additional transcription factors and the presence of histone modifications in different ELK1 modules. We therefore created a tag density profile of ELK1 and ERK2 ChIP-seq peaks separated into ELK1-ERK2, ELK1+ERK2 and ERK2-ELK1 modules using a ChIP-seq data from a variety of transcription factors and histone modifications in H1-hESC

(Fig. 6). As expected, ERK2 binding was enriched in the ELK1+ERK2 module relative to ELK1-

ERK2 and, further enriched in the ERK2-ELK1 module relative to both the ELK1+ERK2 and ELK1-

ELK1 modules. We saw enrichment in SRF binding in both the ELK1+ERK2 module, relative to the ERK2-ELK1 module, and further enrichment of SRF in the ELK1-ERK2 module, relative to

ELK1+ERK2 and ERK2-ELK1. However, in the ELK1-ERK2 module we also saw binding enrichment of SUZ12 and EZH2, elements of the PRC2 complex. Additionally, the ELK1-ERK2 regions were enriched with H3K27me3, suggesting a repressive transcription state. Likewise, the histone marks suggestive of active transcription, H3K4me3, H3K9ac and H3K27ac, were less enriched in ELK1-ERK2 regions. We also note that the ELK1-ERK2 and ELK1+ERK2 peaks have a dip in the histone modifications, which the ERK2-ELK1 peaks, this points to the role of

ELK1 as a DNA-bound transcription factor, as opposed to ERK2, a kinase, which doesn’t have a clear binding footprint. From this initial ELK1 binding region partition, we can see that the

ELK1-ERK2 module has lower enrichment of active histones and higher enrichment of PRC2 complex than that of ELK1+ERK2. This suggests that ELK1 has a repressive module, which lacks the association with ERK2. In addition, the ELK1-ERK2 modules has a higher enrichment of SRF, suggesting that within the ELK1 binding region, there may be an SRF module, separate from the PRC2 module.

ELK1-ERK2 ELK1-ERK2 ELK1-ERK2 H3K9ac SUZ12 120 80 100 H3K27ac EZH2

y y ELK1 80

i i 60 H3K4me3 H3K27me3

n n SRF 60

e 60 e 40

a a 20

T 20 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 ELK1+ERK2 ELK1+ERK2 ELK1+ERK2 H3K9ac SUZ12 120 80 ELK1 100 H3K27ac y EZH2

y y 80

t SRF i

i i 60

s s H3K4me3

n H3K27me3

n 60

e e 60 40

a a 20 T 20

T 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 ERK2-ELK1 ERK2-ELK1 ERK2-ELK1 H3K9ac SUZ12 120 80 ELK1 100 H3K27ac EZH2

t t 80

i i 60 SRF

s s H3K4me3 H3K27me3

n n 60

60 40 e

a a 20

T T 20

T 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3

ELK1-ERK2 ELK1+ERK2 ERK2-ELK1 60 60 60

s 40 s 40 40

g 20 g 20 20

T 0 0 0 ERK2 ERK2 ERK2

Figure 6: ELK1 has a binding module enriched for ERK2 and enriched for active histone marks. Transcription factor binding profiles for ELK1 binding loci in H1- hESC partitioned by overlap with ERK2 peaks. Histograms represent 5000 bp centred on ELK1 or ERK2 peaks.

4.I.C ELK1 loci with high SUZ12 enrichment correlate with low enrichment of active histone modifications Given the enrichment of SUZ12 binding on ELK1-bound regions, which suggested a potential mechanism of ELK1-mediated repression and PRC2 recruitment, and the potential for a separate SRF enriched module, we decided ELK1 and SUZ12 regions merited further analysis.

We thus sought to create a tag density profile of ELK1 and SUZ12 ChIP-seq peaks separated into ELK1-SUZ12, ELK1+SUZ12 and SUZ12-ELK1 modules using a ChIP-seq data from a variety of transcription factors and histone modifications in H1-hESC (Fig. 7). The ELK1+SUZ12 binding loci were enriched for SUZ12, H3K27me3 and EZH2 relative to ELK1-SUZ12 binding loci.

Likewise, the histone marks suggestive of active transcription, H3K4me3, H3K9ac and H3K27ac, were less enriched in ELK1+SUZ12 regions, relative to ELK1-SUZ12.

As expected, SUZ12, H3K27me3 and EZH2 are less enriched in in ELK1-SUZ12. In the

ELK1-SUZ12 binding loci, there was an enrichment of ELK1 and SRF binding. Taken with the enrichment of histone marks suggestive of active transcription, H3K4me3, H3K9ac and

H3K27ac in the ELK1-SUZ12 regions, these data point to an active ELK1+SRF module, distinct from a repressive ELK1+SUZ12 module.

Again, we note that the shapes of the tag density profiles. ELK1+/-SUZ12 modules and have a dip in the histone modifications, which the SUZ12-ELK1 peaks lack. The EZH2 tag density profiles in all modules appear as flat plateaus in the ELK1 containing modules, perhaps pointing to PRC2 propagation (Margueron et al., 2009). Additionally, note that SUZ12 has a binding profile that centres on the ELK1 peak, which makes it the ideal candidate for following up a potential interaction.

ELK1-SUZ12 ELK1-SUZ12 ELK1-SUZ12 H3K9ac SUZ12 120 80 ELK1 100 H3K27ac EZH2

t t 80

i 60 SRF i

s H3K27me3

s s H3K4me3

n n 60

e 60 40 e

a 20 a

T T 20 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 ELK1+SUZ12 ELK1+SUZ12 ELK1+SUZ12 H3K9ac SUZ12 120 80 ELK1 100 H3K27ac EZH2

y y 80

i 60 i

s SRF H3K27me3

s s H3K4me3

n n 60

e 60 40 e

a 20 a

T T 20 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 SUZ12-ELK1 SUZ12-ELK1 SUZ12-ELK1 H3K9ac SUZ12 120 80 ELK1 100 H3K27ac EZH2

t t 80

i 60 SRF i

s s H3K4me3 H3K27me3

n n 60

e 60 40 e

a 20 a

T T 20 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3

Figure 7: ELK1 has a binding module enriched for PRC2 and enriched for repressive histone marks. Transcription factor binding profiles for ELK1 binding loci in H1-hESC partitioned by overlap with SUZ12 peaks. Histograms represent 5000 bp centred on ELK1 or SUZ12 peaks.

4.I.D ELK1 loci with high SUZ12 enrichment correlate with genes enriched for developmental GO terms Having established a method of partitioning ELK1 peaks to enrich ELK1+SUZ12 peaks, we next sought to establish if the genes associated with these peaks had potential biological relevance. To address this, we first assigned genes to binding loci, with HOMER (Heinz et al.,

2010), using the nearest TSS model. We next analysed the biological process gene ontologies

(GO) of genes linked to partitioned ELK1 binding loci using DAVID (Huang et al., 2008, 2009).

We found that ELK1 binding loci overlapping with SUZ12 binding loci were enriched for terms relating to development (Fig. 8A). These loci are also enriched for EZH2 binding and the

H3K27me3 modification (Fig. 7), a functional indication of PRC2-mediated repression, suggesting that an ELK+SUZ12 module might be involved developmental gene repression.

Conversely, ELK1 binding loci not overlapping with SUZ12 binding loci were not enriched for developmental processes and were instead correlated with metabolic and biosynthetic processes (Fig. 8B). As PRCs are known to functionally repress key developmental genes, this result was expected (Lee et al., 2006b). However, an ELK1-mediated mechanism of PRC repression would be novel.

Figure 8. Gene ontologies for ELK1 binding loci partitioned by overlap with SUZ12 binding loci.

Top 10 DAVID biological function gene ontology terms, sorted by -log10 p-value, of ELK1 binding loci A) overlapped with SUZ12 binding loci B) not overlapped with SUZ12 binding loci.

4.I.E An ELK1+SUZ12 binding module is H1-hESC specific The ELK1+SUZ12 regions are associated with developmental genes, which may suggest a function unique to hESC. This could have also suggest that the ELK1+SUZ12 binding module was hESC specific. To determine this, we overlapped ELK1 ChIP-seq data from K562 and

MCF10A cells with that of hESC (ELK1 HESC +/- K562 and ELK1 HESC +/- MCF10A, respectively)

(Fig. 9).

For both cells lines, the hESC unique peaks (ELK1 HESC-K562 and ELK1 HESC-MCF10A) were enriched for SUZ12, EZH2 and H3K27me3 binding. The shared peaks (ELK1 HESC+K562 and ELK1 HESC+MCF10A) were enriched for SRF. In all cases, there was no difference in

H3K27ac, H3K9ac and H3K4me3 histone modification levels, suggesting that the H1-hESC specific peaks are likely associated with a mixture of active and repressed genes. These data may suggest two binding modules: An ELK1+SUZ12 repressive or primed chromatin state unique to hESC and an ELK1+SRF active chromatin region, general to many cell types.

A ELK1 HESC-MCF10A ELK1 HESC-MCF10A ELK1 HESC-MCF10A H3K9ac SUZ12 120 80 ELK1 100 H3K27ac EZH2

t 80

i 60 SRF i

s s H3K4me3 H3K27me3

n n 60

e e 60 40

a 20

T T 20

T 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 ELK1 HESC+MCF10A ELK1 HESC+MCF10A ELK1 HESC+MCF10A H3K9ac SUZ12 120 80 ELK1 100 H3K27ac EZH2

y y 80

t i 60 SRF i H3K27me3

s H3K4me3

n 60

e e 40

60 D

D 40

a 20 T 20

T 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 B ELK1 HESC-K562 ELK1 HESC-K562 ELK1 HESC-K562 H3K9ac 120 80 100 SUZ12 ELK1 H3K27ac

y 80

t EZH2

i 60

s H3K4me3

n SRF 60 n H3K27me3

e e 40

60 D

D 40

a a 20

T 20

T 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 ELK1 HESC+K562 ELK1 HESC+K562 ELK1 HESC+K562 SUZ12 100 H3K9ac 120 80 ELK1 EZH2

y H3K27ac

y 80

i i 60 SRF s H3K27me3

n 60 H3K4me3

e 60 e 40 D

20 T 20

T 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3

Figure 9: ELK1 peaks unique to hESC are enriched for PRC2 Transcription factor binding profiles for ELK1 binding loci in H1-hESC partitioned by A) overlap with ELK1 peaks in MCF10A B) overlap with ELK1 peaks in K562 Histograms represent 5000 bp centred on an ELK1 peaks.

4.I.F ELK1 loci with low GABPA enrichment correlate with high PRC2 enrichment Having shown that an ELK1+SUZ12 interaction maybe cell-type specific, we next sought to examine whether it was ELK1 specific or shared binding regions with another ETS protein. We therefore created a tag density profile of ELK1 and GABPA, as a representative of the ETS TF family. We separated ELK1 and GABPA ChIP-seq peaks into ELK1-GABPA,

ELK1+GABPA and GAPBA-ELK1 modules (Fig. 10). As expected the ELK1-GABPA and

ELK1+GABPA were equivalently enriched for ELK1 and both were more enriched relative to

GABPA-ELK1. Likewise, SRF was enriched in ELK1-GABPA, relative to ELK1+GABPA and further enriched relative to GABPA-ELK1. The ELK1-GABPA and ELK1+GABPA peaks also were enriched for SUZ12, EZH2 and H3K27me3 levels, relative to GABPA-ELK1 peaks. However, ELK1-GABPA and ELK1+GABPA peaks showed an increase in H3K27ac, H3K9ac and H3K4me3 binding, relative to GABPA-ELK1 peaks. This could be due to the large amount of GABPA-ELK1 peaks as compared to ELK1+GABPA and ELK1-GABPA peaks, which may include many low fold- enrichment GABPA peaks, as evidenced by the lower average tag density for GABPA in in

GABPA-ELK1 than ELK1+GABPA. In addition, the distribution of GABPA peaks were a lot more evenly distributed than the distribution of ELK1 peaks, which were more proximal (within 1000 bp) to the TSS. (Fig. 11). We therefore sought to establish a set of GABPA peaks that were distributed more similarly to ELK1, we partitioned the GABPA dataset by decile (sorted by p- value), and at 30% the dataset was not further enriched for TSS proximal peaks (Fig. 11A).

ELK1-GABPA ELK1-GABPA ELK1-GABPA H3K9ac SUZ12 120 80 100 ELK1 H3K27ac EZH2

y y 80

i i 60

s s SRF H3K4me3 H3K27me3

n 60

e e 60 40

a a 20

T 20

T 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 ELK1+GABPA ELK1+GABPA ELK1+GABPAELK1 H3K9ac SUZ12 120 80 100 H3K27ac EZH2

y SRF y

t 80

i 60 i H3K27me3

s s H3K4me3

n n 60

e 60 40 e

a 20 a

T T 20 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 GABPA-ELK1 GABPA-ELK1 GABPA-ELK1 H3K9ac SUZ12 120 80 ELK1 100 H3K27ac EZH2

y y 80

SRF i

i i 60

s H3K27me3

s s H3K4me3

n n 60

e e 60 40

a a 20

T T 20 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3

ELK1-GABPA ELK1+GABPA GABPA-ELK1 60 60 60

y y

t t

i i

s s 40 s 40 40

n n

e e

D D

g g 20 g 20 20

a a

T T 0 0 0 GABPA GABPA GABPA

Figure 10: ELK1 peaks are enriched for PRC2 and active histone marks Transcription factor binding profiles for ELK1 binding loci in H1-hESC partitioned by overlap with GABPA peaks. Histograms represent 5000 bp centred on an ELK1 or GABPA peak.

Legend Legend A GABPA (Top 20%) B ELK1 Legend Legend Legend Total=2888 LegendTotal=818 Legend Legend Legend GABPA (Top 30%) ELK1-GABPA(Top 30%) Legend Legend Legend Legend Legend Legend<-10001 bp Legend Legend Total=4332 Total=672 Legend-10000 to -1001 bp LegendELK1+ERK2 Legend ELK1+GABPA(TopLegend 30%) -1000 to 0 bp GABPA (Top 40%) Legend Legend 1 to 1000 bp Legend Legend 1001 to 10000 bp Legend LegendTotal=151 Legend>10001 bp Total=5776 Total=146 Legend Legend Legend GABPA (Top 50%) GABPA(Top 30%)-ELK1 Legend Legend Legend Legend Legend Legend Legend Total=7220 LegendTotal=4186 Legend Legend GABPA GABPA (Top 30%) Legend Legend Legend Total=14439 Total=4332 Legend

Figure 11: Genomic distribution of GABPA binding loci A) The genomic distribution of binding loci of GABPA peaks partitioned between the top 50%-20% of peaks, sorted by p-value. B) The genomic distribution of binding loci of ELK1 peaks intersected with the top 30% of GABPA peaks, sorted by p-value. The distance is measured from the centre of the binding peaks to the nearest TSS (0 bp).

We then reanalysed the GABPA data using only to top 30% of GAPBA peaks (sorted by p- value). Again, overlapping the ELK1 and new set of GABPA peaks, a larger portion of peaks in the ELK1+GABPA modules were proximal (within 1000 bp) to the TSS relative to the ELK1-

GAPBA modules (Fig. 11B).

Reanalysing the tag densities using only the top 30% of GAPBA peaks (sorted by p- value), we can first see an increase in the average of tag density of GABPA, relative to the total

GABPA peaks (Fig. 10, Fig. 12). Again, as expected the ELK1-GABPA and ELK1+GABPA were equivalently enriched for ELK1 and both were more enriched relative to GABPA-ELK1. Likewise,

SRF was enriched in ELK1-GABPA, relative to ELK1+GABPA and further enriched relative to

GABPA-ELK1. The ELK1-GABPA and ELK1+GABPA peaks also were enriched for SUZ12, EZH2 and H3K27me3 levels, relative to GABPA-ELK1 peaks. Additionally, we can see a lower SUZ12,

EZH2 and H3K27me3 in ELK1-GABPA, relative to ELK1+GABPA and GABPA-ELK1. Finally, we see that histone marks suggestive of active transcription, H3K4me3, H3K9ac and K3K27ac, were less enriched in ELK1-GABPA modules, relative to both ELK1+GABPA and GABPA-ELK1 modules.

Taken together, we see that, relative to GABPA-ELK1 and ELK1+GABPA binding modules,

ELK1-GABPA binding module has a greater enrichment of SRF, which is to be expected, but supports the veracity of these data. Additionally, SUZ12, EZH2 and H3K27me3 are enriched in an ELK1-GABPA binding module, which suggest unique co-localization with ELK1, relative to

GABPA (a fellow ETS factor). We therefore conclude that studying PRC2 interaction with ELK1 in hESC would be an appropriate model. Additionally, the presence of both SUZ12 and SRF in the ELK1-GABPA binding module, suggest a set of ELK1-unique regions that may be further divided into active and repressive modules.

ELK1-GABPA ELK1+GABPA GABPA-ELK1 100 100 100

e e 50 50 50

T 0 0 0 GABPA GABPA GABPA

ELK1-GABPA ELK1-GABPA ELK1-GABPA H3K9ac 120 80 100 SUZ12 ELK1 H3K27ac EZH2

y y 80

i i 60

s s SRF H3K4me3 H3K27me3

n n 60

e e 60 40

a a 20

T T 20 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 ELK1+GABPA ELK1+GABPA ELK1+GABPAELK1 H3K9ac SUZ12 120 80 100 H3K27ac EZH2

SRF y

t t 80

i 60 i H3K27me3

s s H3K4me3

n n 60

e 60 40 e

a 20 a

T T 20 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3 GABPA-ELK1 GABPA-ELK1 GABPA-ELK1 H3K9ac SUZ12 120 80 ELK1 100 H3K27ac EZH2

y y 80

t t SRF

i i 60

s H3K27me3

s s H3K4me3

n n 60

e 60 e 40

a a 20

T T 20 0 0 0 ELK1 SRF H3K9ac H3K27ac H3K4me3 SUZ12 EZH2 H3K27me3

Figure 12: ELK1 peaks are enriched for PRC2 and active histone marks GABPA (Top 30%) Transcription factor binding profiles for ELK1 binding loci in H1-hESC partitioned by overlap with the top 30% peaks GABPA peaks, sorted by p-value. Histograms represent 5000 bp centred on an ELK1 or GABPA peak.

4.I.G Conclusion Part1 To establish a pool of candidate genes of further interest in exploring an ELK1-PRC2 interaction, we partitioned ELK1 peaks in H1-hESC by potential co-factors. In line with previous analysis we show that ELK1 binding loci in H1-hESC can be divided into modules which overlap with ERK2 (ELK1+ERK2) and those that do not (ELK1-ERK2), with the ELK1-ERK2 modules more enriched for members of the PRC2 repressive complex (Fig. 6). Next, we demonstrate that partitioning ELK1 peaks by PRC2 occupancy, again gives us two modules, an ELK1+SUZ12 module, enriched for the PRC2 complex and the H3K27me3 repressive histone modification, and an ELK1-SUZ12 modules, enriched for active histone marks and SRF (Fig. 7). Further we demonstrate that an ELK1+SUZ12 module is enriched for peaks near development genes (Fig.

8).

Additionally, we demonstrate the enrichment of the PRC2 is specific to ELK1 binding loci, compared to GABPA, another ETS TF, in H1-hESC, suggesting that the PRC2 interaction may be unique to ELK1 (Fig. 10,12). Finally, we find that PRC2 is enriched on H1-hESC specific ELK1 peaks, relative to other cell types, suggesting that an ELK1+PRC2 interaction may be H1-hESC specific (Fig. 9). Taken together with the genomic distributions, which suggest that the

ELK1+SUZ12 module is generally farther away from TSSs (Fig. 5), we can describe two ELK1 binding modules in H1-hESC, an ELK1-SUZ12 binding module, containing SRF and active histone marks, more proximal to TSSs (Fig. 13A+B), and a ELK1+SUZ12 binding modules, containing the

PRC2 complex and the H3K27me3 repressive histone mark (Fig. 13B+C).

A ELK1+SUZ12 Tag Densities 120 ELK1 SRF SUZ12

s EZH2

D H3K27me3

g a H3K9ac

T H3K27ac H3K4me3 -2500 -1500 -500 500 1500 2500 Distance (bp) B H3K4me3 H3K27me3

ELK1

EZH2 EZH2 SUZ12 EZH2 EZH2 2 0bp <-500 bp -250 bp 250 bp >500 bp

ELK1-SUZ12 Tag Densities C 120 ELK1 SRF SUZ12

s EZH2

D H3K27me3

g a H3K9ac

T H3K27ac H3K4me3 -2500 -1500 -500 500 1500 2500 Distance (bp)

D H3K27ac H3K4me3 H3K9ac ELK1

SRF

0 bp -750 bp -250 bp 250 bp 750 bp

Figure 13: Binding profiles surrounding ELK1+SUZ12 peaks A) Tag density plot and B) hypothetical model of binding around ELK1 C) Number of ELK1+SUZ12 peaks surrounding TSS sites. C) Tag density plot and D) hypothetical model of binding around ELK1.

4.II ELK1 does not interact with PRC2 4.II.A An ELK1+RBBP7 interaction is detectable with RIME Having shown co-localization of ELK1 and the PRC2 complex, we decided to investigate whether an interaction between ELK1 and the PRC2 complex was detectable biochemically.

Initially, we attempted a Co-IP of ELK1 in MCF10A, which were readily available and expressed

ELK1 and SUZ12 at levels detectable with western blot (Fig. 14). We detected SRF, but could not detect SUZ12 (Fig. 14A). We also carried out the reciprocal experiment and immunoprecipitated SUZ12. We detected EZH2, a known SUZ12 co-factor, but not ELK1 (Fig.

14B). We next attempted a RIME (Rapid Immunoprecipitation and Mass Spectrometry of

Endogenous Proteins) assay in MCF10A cells, which would allow us an unbiased identification of proteins associated with ELK1. Briefly, formaldehyde crosslinked chromatin was sheared, immunoprecipitated with ELK1 antibody and trypsinised and analysed with mass spectrometry

(Mohammed et al., 2013). We set a cut-off at least 2 peptides in at least 2 ELK1 IP samples.

Whilst, neither SUZ12 nor EZH2 were pulled down with ELK1, we did detect RBBP7 (Fig. 15), a histone-binding protein associated with both the PRC2 and HDAC complexes, which ELK1 had been known previously to interact with (Kuzmichev et al., 2002; Y Zhang et al., 1998). Whilst

ELK1 is clearly on the chromatin, as evidenced by the presence of histones, we did not pick up

SRF, SIN3A or P300, known ELK1 co-factors. Taken together with the low number of ELK1 peptides detected with RIME, this may suggest that this technique lacks the sensitivity to detect weak or infrequent interactions. Additionally, the detection of high numbers of ribosomal proteins and elongation factors, both involved in translation, could suggest regions of active transcription, closely followed by translation (Fig. 15B). However, the abundance of integrins, membrane-bound proteins suggest a high level of background for the pulldown of a nuclear transcription factor.

70- ELK1

100- SUZ12

55- SRF

1 2 3

100- SUZ12

70- ELK1

100- EZH2

1 2 3

Figure 14: Co-Immunoprecipitation assay of ELK1 and SUZ12 interacting proteins A) ELK1, SUZ12 and SRF western blots following ELK1 Immunoprecipitation in MCF10A. B) SUZ12, ELK1 and EZH2 western blots following SUZ12 Immunoprecipitation in MCF10A. FT = 50% of the IP flow through. Blots are representative of 2 independent experiments. Dotted lines represent the excision of empty lanes.

4.II.B An ELK1+PRC2 interaction is not detectable with Co-Immunoprecipitation We next sought to verify the interaction of ELK1 and RBBP7 and determine if there was a measurable interaction of ELK1 and the PRC2 complex in H1-hESC cells. We therefore immunoprecipitated ELK1 and blotted for potential co-factors. We detected SRF, but could detect neither EZH2 nor RBBP7 (Fig. 16A). We also carried out the reciprocal experiment and immunoprecipitated SUZ12. We detected EZH2 and RBBP7, both previously known members of the PRC2, but not ELK1 (Fig 16B). These data suggest that the ELK1 has no detectable interaction the PRC2 and we were unable to verify the interaction of ELK1 and RBBP7 in H1- hESC.

70- ELK1

100- EZH2 70- SRF 55-

55- RBBP7

1 2 3 4 5

100- SUZ12

70- ELK1

100- EZH2

55- RBBP7

1 2 3 4 5

Figure 16: Co-Immunoprecipitation assay of ELK1 and SUZ12 interacting proteins A) ELK1, EZH2, SRF and RBBP7 western blots following ELK1 Immunoprecipitation in H1-hESC. B) SUZ12, ELK1, EZH2 and RBBP7 western blots following SUZ12 Immunoprecipitation in H1-hESC. FT = 10% of the IP flow through. Blots are representative of 2 independent experiments.

4.II.C Conclusion Part 2 We established that there was a subset of ELK1 loci that are enriched for PRC2 binding, suggesting perhaps a co-regulatory interaction in which ELK1 recruits PRC2 to chromatin regulating developmental genes in H1-hESC. We therefore attempted to investigate the ELK1 interactome using RIME. We did not detect any PRC2 core components, though we did detect

RBBP7, a histone binding protein (Fig. 15A). However, we did not detect SRF, SIN3A or P300, known ELK1 co-factors, so the efficacy of this experiment is uncertain. We further determined that there was likely no direct interaction between ELK1 and PRC2 using co- immunoprecipitation (Fig. 16), we next tested whether there was a possible indirect interaction between ELK1 and the PRC2.

The large presence of integrins, eukaryotic translation factors and ribosomal proteins, suggest that pulldown or wash was inefficient, carrying over cytosolic proteins to the mass spectrometer (Fig. 15B). Or, perhaps the mass spectrometer met a saturation point, in which amount of background proteins outweighed the detection of ELK1 and its co-factors.

One potential mechanism by which ELK1 could recruit PRC2 is by RBBP7, which is involved in both the mSIN3A, a known repressive co-factor of ELK1, and the NURD HDAC complexes (Fig. 17)(Allen et al., 2013). Unfortunately, while RBBP7 is detectable with immunoprecipitation, RBBP7 is not detectable with ChIP-PCR near SIN3A or SUZ12 sites (Fig.

18). Thus we did not follow-up RBBP7 any further in this study.

A HDAC complex

SIN3A? RBBP7

H3K27ac? Active? ELK1 GENE

B PRC2

HDAC complex

RBBP7 H3K27me3

ELK1 GENE

Figure 17: Model of recruitment of RBBP7 by ELK1 Hypothetical recruitment of RBBP7 and an HDAC complex from ChIP-seq analysis and RIME data. A) ELK1 recruiting RBBP7 which subsequently B) recruits PRC2

55- RBBP7

1 2 3 4 5 B ChIP-qPCR of SIN3A and RBBP7 0.15

 SIN3A

t 0.10 u  RBBP7

I  IgG % 0.05

0.00 S 1 2 1 B c c S R R E u u T O T N N N T F G G I U _ _ - C E E J 1 3 1 X X R I H G S F E Z

SIN3A loci SUZ12 loci -ve control

Figure 18: RBBP7 does not co-occupy SIN3A binding sites. A) RBPP7 blot of RBBP7 Immunoprecipitation B) ChIP-qPCR of SIN3A and RBBP7 in H1-hESC cells at the indicated loci. “SIN3A loci” were enriched for SIN3A in H1-hESC ChIP-seq reads and “SUZ12 loci” were enriched for SUZ12 in H1-hESC ChIP-seq reads in the UCSC browser. Binding presented as % Input. Blot is representative of 3 independent experiments. FT = 5% of the IP flow through.

4.III ELK1 is not necessary to recruit SUZ12 to developmental genes 4.III.A Retinoic Acid does not change PRC2 binding Having shown that ELK1+SUZ12 peaks were enriched in development genes, we decided to find a set of genes that were induced upon differentiation (Fig. 8A). We hypothesised that the regulatory regions of these genes would switch from repressed (i.e. PRC2-bound) to active, and thus we would expect ELK1 and/or SUZ12 binding to change during differentiation. We chose to use retinoic acid (RA), a potent initiator of hESC differentiation, as demonstrated by the decrease in canonical pluripotency factors OCT4, SOX2 and MYC (Fig. 19A). Using the nearest TSS-association model in HOMER, we identified a set of ELK1+SUZ12-bound genes whose expression increased upon 48-96 hours of treatment with RA (Fig. 19B+C).

A RT-qPCR of Pluripotency Factors 2.0

i s 1.5 s * e * *

r p * +DMSO x 1.0

E +RA (48 hrs)

i t 0.5 a +RA (96 hrs)

R 0.0

H C G 4 2 D Y O T X P M N C O A A O S B G N RT-qPCR of ELK1-bound genes 30

n *

s *

e 20

x * +DMSO

e * * +RA (48 hrs) v 10

a l +RA (96 hrs)

R 0 H 4 2 1 3 D P T IX X P M U S H B C F A E Z G N C O RT-qPCR of ELK1-bound genes RT-qPCR of ELK1-bound genes 100 400

n * n

o o *

i * i

s 80 * * s 300 s s *

e * e

r r +DMSO +DMSO

p 60

x * x 200

+RA (48 hrs) +RA (48 hrs)

e 40 e

t t 100 +RA (96 hrs) +RA (96 hrs)

l 20 l

R 0 0 H 2 3 7 2 2 D X IG X F IS P S A 3 E M L P U A O O M G P

Figure 19: ELK1-bound genes are upregulated during RA treatment RT-qPCR of A) pluripotency markers B) and C) ELK1-bound genes upon 48 and 96 hours of RA treatment. Gene expression normalized to “+DMSO” and GAPDH expression. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments. Significance is calculated comparing “+RA (48 hours)” and “+DMSO” or “+RA (96 hours)” and “+DMSO”. * = p-value < 0.05.

Having identified a set of ELK1-bound genes where expression changes upon RA-induced differentiation, we used ChIP-qPCR to determine if ELK1 binding changes on the loci near these regions during differentiation. Additionally, we performed ChIP-qPCR on SUZ12, because the binding profile of SUZ12 more closely resembled ELK1, with peaks centred most densely on

ELK1 peaks, as opposed to EZH2 which had a more evenly distributed binding profile. (Fig. 7).

Finally, we performed ChIP-qPCR on H3K27me3, a repressive histone modification deposited by PRC2. We first demonstrated that the ELK1, SUZ12 and H3K27me3 antibodies were able to

IP chromatin in a specific manner, with a set of regions which has low enrichment compared to the IgG control (negative regions) and a set of regions which has high enrichment compared to the IgG control (positive regions) (Fig. 20)

A ELK1 ChIP-qPCR ELK1 ChIP-qPCR 3 20

15  ELK1 +DMSO  ELK1 +DMSO

2 t

p p  IgG +DMSO  IgG +DMSO

n n 10

 ELK1 +RA

% 1 %  ELK1 +RA 5  IgG +RA  IgG +RA

0 0 2 3 2 1 g H IM e D R R L R P G G B g A E E A e G N Negative controls ELK1-bound regions B SUZ12 ChIP-qPCR SUZ12 ChIP-qPCR SUZ12 ChIP-qPCR 3 33

 SUZ12 +DMSO SUZ12 +DMSO  SUZ12 +DMSO

t 2 t 2 2

p p  IgG +DMSO  IgG +DMSO  IgG +DMSO

 SUZ12 +RA %  SUZ12 +RA

% %  SUZ12 +RA 1 11  IgG +RA  IgG +RA  IgG +RA

0 00 2 3 1 2 3 H 1 g H M g D R IMF e D R I e P G L3 P G L R U R A E B g A E OB g A e G A e G N P N H3K27me3 ChIP-qPCR C H3K27me3 ChIP-qPCR 1.5 1.5

t 1.0 t 1.0  H3K27me3 +DMSO

u u  H3K27me3 +DMSO

p p  IgG +DMSO

I  IgG +DMSO

 H3K27me3 +RA

% % 0.5 0.5  H3K27me3 +RA  IgG +RA  IgG +RA

0.0 0.0 2 H 1 2 F D R X 3 P G O U A E S O G P

Figure 20: ELK1, SUZ12 and H3K27me3 antibodies are specific ChIP-qPCR of ELK1-binding sites using ELK1 antibodies after 96 hours of DMSO or RA treatment. B) ChIP-qPCR of ELK1-binding sites using SUZ12 antibodies after 96 hours of RA treatment. C) ChIP-qPCR of nucleosomes near ELK1-binding sites using H3K27me3 antibodies after 96 hours of RA treatment. Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments.

A ELK1 ChIP-qPCR 0.8

0.6

t u +DMSO

n 0.4

I +RA

% 0.2

0.0 2 4 2 2 3 2 7 2 1 3 T X F X IM P IS X IG 3 I X L M E S L U A S H B M C P U F B M O E O Z A N P O B SUZ12 ChIP-qPCR 3

t 2

u +DMSO

I +RA

% 1

0 H 4 2 2 3 2 7 2 1 3 D P IS X IG T X F IX X P M E S L U A 3 S H A B M C P U F M O E O Z G N P O C H3K27me3 ChIP-qPCR 3

t 2

n +DMSO

% 1 +RA

0 H 4 2 2 3 2 7 2 1 3 D P IS X IG T X F IX X P M E S L U A 3 S H A B M C P U F M O E O Z G N P O

Figure 21: RA treatment has no effect on the binding of ELK1, SUZ12 and H3K27me3 A) ChIP-qPCR of ELK1-binding sites using ELK1 after 96 hours of RA treatment B) ChIP-qPCR of ELK1-binding sites using SUZ12 after 96 hours of RA treatment C) ChIP- qPCR of nucleosomes near ELK1-binding sites using H3K27me3 after 96 hours of RA treatment . Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments.

Next we analysed the binding of ELK1, SUZ12 and the presence of H3K27me3 following

RA-induced differentiation. During RA-induced differentiation we only saw decreases in ELK1 binding near SIX1 and ZFHX3 (Fig. 21A), but did not see any change in the binding of SUZ12 on

ELK1 regions and H3K27me3 level on nearby nucleosomes (Fig. 21B+C). However, we did see a general increase in levels of H3K27ac modification on the nucleosomes near genes which were

RA-inducible, consistent with the regulatory regions of activated genes (Fig. 22). We also tested nucleosomes near ABLIM2 and GAPDH - regions not bound by ELK1 - and EGR1, which has a promoter bound by ELK1 (Fig. 22). Our controls remained the same in both conditions, supporting the validity of the increase in RA-inducible genes. We would assume that the increase of H3K27ac modification would be accompanied by a decrease in H3K27me3 modification, suggesting that either different nucleosomes are modified in response to gene activation, or the change in H3K27me3 is so small, relative to the change in H3K27ac, that is does not create a change detectable in ChIP-qPCR.

H3K27ac ChIP-qPCR 0.8

0.6

u +DMSO

n 0.4

I +RA % 0.2

0.0 2 H 1 4 2 2 3 2 7 2 1 3 T X F X IM D R P IS X IG 3 I X L P G M E S L U A S H A E B M C P U F B M O E O Z A G N P O Controls RA-inducible genes

Figure 22: H3K27ac binding in RA-treated cells ChIP-qPCR of H3K27ac on nucleosomes near ELK1-binding sites after 96 hours of RA treatment. Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 2 independent experiments.

4.III.B ELK1 depletion does not decrease SUZ12 and H3K27me3 binding Having established a set of ELK1-bound regions associated with RA-inducible genes, we next sought determine if SUZ12 binding was affected by depletion of ELK1 binding on these regions. To examine this we used ChIP-qPCR to measure ELK1 and SUZ12 binding in H1-hESC with shELK1 depletion for 4 days. The ELK1 depletion reduced the amount of ELK1 protein and

RNA and reduced levels of and the level of ELK1 binding to chromatin (Fig. 23 and Fig. 25A).

Protein Quantification

70- s 1.5 ELK1 n e t 1.0 +Empty

I Plasmid

e 0.5 v +shELK1

HDAC1 t

a 55- l 0.0

R 1 1 C K A L D E H B RT-qPCR of Pluripotency Factors 2.0

s 1.5

p * * * * x 1.0

E +Plasmid

v i +shELK1 t 0.5

R 0.0 1 2 4 2 B M H _ C G T 2 D K 1 Y O T X C B P L K M N C O A A E L A O S G E N Controls ELK1 Pluripotency Markers

Figure 23: shELK1 treatment decreases NANOG and OCT4 expression A) Western blot analysis and protein quantification of ELK1 and HDAC1 expression in H1-hESC with after 96 hours of shELK1 treatment. B) RT-qPCR of ELK1 and pluripotency markers after 96 hours of shELK1 KD. Gene expression normalized to “+Plasmid” and GAPDH expression. RT-qPCR values are the average of 5 independent experiment, with the exception of MYC and B2M, which are the average of 3 independent experiments. Blots are representative of 2 independent experiments. * = p-value < 0.05.

Again we demonstrated that the ELK1 and SUZ12 antibodies were able to IP chromatin in a specific manner now in shELK1 treated cells, with a set of regions which has low enrichment compared to the IgG control (negative controls) and a set of regions which has high enrichment compared to the IgG control (positive controls) (Fig. 24)

A ELK1 ChIP-qPCR ELK1 ChIP-qPCR 1.5 8

t 1.0 t  ELK1 +Plasmid

u u  ELK1 +Plasmid

p p  IgG +shELK1

n n 4

I I  IgG +Plasmid

% %  ELK1 +shELK1 0.5  ELK1 +shELK1 2  IgG +Plasmid  IgG +shELK1

0.0 0 2 3 2 1 g H IM e D R R L R P G G B g A E E A e G N Negative controls ELK1-bound regions B SUZ12 ChIP-qPCR SUZ12 ChIP-qPCR 5 5

4 4  SUZ12 +Plasmid

t t  SUZ12 +Plasmid

u u 3 3 IgG +Plasmid

p 

n n  IgG +Plasmid

2 2  SUZ12 +shELK1

% %  SUZ12 +shELK1  IgG +shELK1 1 1  IgG +shELK1

0 0 2 3 1 2 g H F IM e D R 3 L R P G U B g A E O A e G P N Figure 24: ELK1, SUZ12 and H3K27me3 antibodies are specific in shELK1 treat cells ChIP-qPCR of ELK1-binding sites using A) ELK1 and B) SUZ12 antibody after 96 hours of shELK1 treatment. Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments.

A ELK1 ChIP-qPCR 0.4

0.3

n 0.2 +Plasmid

% +shELK1 0.1

0.0 2 4 2 2 3 2 7 2 1 3 T X F X IM P IS X IG 3 I X L M E S L U A S H B M C P U F B M O E O Z A N P O B SUZ12 ChIP-qPCR 5

u 3 +Plasmid

I 2 +shELK1

0 H 4 2 2 3 2 7 2 1 3 D P IS X IG T X F IX X P M E S L U A 3 S H A B M C P U F M O E O Z G N P C O H3K27me3 ChIP-qPCR 1.5

t 1.0

u +siNT

I +siELK1 % 0.5

0.0 H 1 2 2 1 3 D R X T IX X P G S U S H A E M C F E Z G N O Figure 25: ELK1 knockdown does not affect SUZ12 binding A) ChIP-qPCR of ELK1-binding sites using ELK1 after 96 hours of shELK1 treatment B) ChIP-qPCR of ELK1-binding sites using SUZ12 after 96 hours of shELK1 treatment C) ChIP-qPCR of nucleosomes near ELK1-binding sites using H3K27me3 after 96 hours of siELK1 treatment . Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments.

Though we saw reduction of ELK1 binding as detected with ChIP-qPCR, SUZ12 binding was not reduced at ELK1-binding loci upon ELK1 depletion using shELK1 treatment (Fig. 25B).

Additionally, the H3K27me3 level was reduced on ZFHX3 upon siELK1 treatment, however,

H3K27me3 levels were unchanged on nucleosomes nearby to ELK1 loci (Fig. 25C). However,

ZFHX3 expression did not increase upon shELK1 treatment, suggesting, in this case of ZFHX3, the depletion of ELK1 alone is not sufficient to stimulate transcription (Figs. 25B, 26).

In addition to, we saw a significant change in the expression SIX1, but only slight increases in other genes upon ELK1 depletion (Fig. 26). The increase in gene expression upon

ELK1 depletion was lower than the increase of gene expression upon RA-treatment.

A RT-qPCR of ELK1-bound genes 4

o i * s 3

x 2 +Plasmid

v +shELK1

i t 1

R 0 H 4 2 2 3 2 7 2 1 3 D P IS X IG T X F IX X P M E S L U A 3 S H B M C P U F A M O E O Z G N P O Figure 26: Expression of ELK1-bound genes following ELK1 depletion RT-qPCR of ELK1-bound genes after 96 hours of shELK1 KD. Gene expression normalized to “+Plasmid” and GAPDH expression. Values are the average of 5 independent experiments, with the exception of ONECUT2 and POU3F2 which are the average of 4 independent experiments. Significance is calculated comparing “+Plasmid” and “+shELK1”. * = p-value < 0.05.

4.III.C Conclusion Part 3 We identified a set of potential regulatory regions with ELK1 and SUZ12 binding nearby genes that increase upon RA treat in H1-hESC (Fig. 19). However, with the exception of the decrease of ELK1 binding near SIX1 and ZFHX3, we did not see a general decrease of SUZ12 binding or H3K27me3 enrichment nearby any of the genes we tested during RA-induced differentiation (Fig. 21). We also depleted ELK1 to determine if SUZ12 binding was affected by depletion of ELK1 binding. However, we did not see a decrease of SUZ12 binding or the

H3K27me3 modification upon ELK1 depletion (Fig. 21), suggesting that ELK1 is not necessary for SUZ12 recruitment. However, we do see significant change in the expression SIX1, and slight increases in other genes upon ELK1 depletion (Fig. 26). There may be a slight repressive role for ELK1 in the case of SIX1 regulation, but this does not appear to involve SUZ12/PRC2 repression.

We also see a decrease in ELK1 binding near ZFHX3 upon RA treatment, however this was not accompanied by a change in SUZ12 binding or H3K27me3 binding (Fig. 21). However,

ZFHX3 expression did not increase upon ELK1 depletion, suggesting, in this case of ZFHX3, the depletion of ELK1 alone is not sufficient to stimulate transcription (Fig. 26).

4.IV The role of ELK1 in pluripotency and differentiation 4.IV.A Mesoderm induction produces Brachyury/T expressing cells To further investigate the potential role of ELK1 in the repression or activation of genes expressed in differentiation, we chose to deplete ELK1 during mesoderm differentiation. We chose mesoderm because it is takes a short time to differentiate and is therefore compatible with a siRNA depletion approach. Additionally, there are many mesoderm epigenetic datasets from the NIH Roadmap Epigenomics Mapping Consortium. While the gene expression controls

B2M and GAPDH and the protein loading control TUBB remained equal in both conditions, the cells expressed T/Brachyury upon 72 hours of treatment with Mesoderm Induction Media

(MIM) (Fig. 27B+C) and displayed a decrease in the pluripotency markers, SSEA4, NANOG,

SOX2 and OCT4 (Fig. 27A+C). In addition, we saw no increase in SOX17, an early endoderm marker, suggesting that this was mesoderm, as opposed to mesendoderm lineage (Fig. 27A).

Taken together, the increase in the expression of T/Brachyury and the decrease in expression of pluripotency factors suggest that this protocol produces early mesoderm cells.

A RT-qPCR of Pluripotency Factors C 2.0 70-

o ELK1

i s 1.5 s * *

e r 55- H1-HESC p OCT4 x 1.0 E Mesoderm

v i 40- t 0.5 SOX2

R 0.0 40- NANOG M H 7 G 4 2 D 1 O T B P X C O N O A S A G N 55- SSEA4 B RT-qPCR of T 2000

o i * 55- s 1500 T

p H1-HESC 40- x 1000

e Mesoderm

i t 500 TUB a 55-

R 0 T Figure 27: Pluripotency and differentiation factor expression in H1-hESC upon MIM treatment RT-qPCR measuring the expression of A) pluripotency markers B) T after 72 of growth in MIM C) ELK1, TUB, SSEA4, OCT4, SOX2, NANOG and T/Brachyury blots in H1-hESC cells grown in MIM for 72 hours. Gene expression normalized to “MTESR”. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments. Blots are representative of at least 3 independent experiments. * = p-value < 0.05.

4.IV.B The role of ELK1 in mesoderm and neural differentiation We next tested a set of ELK1-bound genes whose expression increases upon mesoderm differentiation, to see if the depletion of ELK1 had an effect on their expression. Briefly, cells were treated with siRNA 24 hours before the initiation of mesoderm differentiation and retreated with siRNA 24 hours after the initiation of mesoderm differentiation. We see that

ELK1 expression decreases upon treatment with siELK1 in both H1-hESC and mesoderm (Fig.

28A). Additionally, we see a decrease in the expression of the pluripotency factors NANOG,

OCT4 and SOX2, suggesting mesoderm differentiation (Fig. 28A). Upon depletion of ELK1 during mesoderm differentiation, FOXC1 and HAND2 increased approximately 2-fold above their normal increase (Fig. 28B). However, ELK1 depletion alone did not initiate any increase in the expression of other differentiation genes or affect the expression pluripotency markers

(Fig. 28A+B). Additionally, we tested a set of genes with no nearby ELK1-binding sites.

Amongst those genes, GSC and WNT3B, increased upon 98 hours of siELK1 treatment, suggesting perhaps secondary effects of an ELK1 depletion (Fig. 28C).

A RT-qPCR of Pluripotency Factors 3

s *

e 2 * r * * H1-hESC +siNT p x * * H1-hESC +siELK1 E * *

e * Mesoderm +siNT

v 1

t Mesoderm +siELK1

R 0

M 1 G 4 2 2 K O T X B L N C O E A O S B N RT-qPCR of ELK1-bound genes 4

o *

s 3 s e * *

r H1-hESC +siNT

x 2 * H1-hESC +siELK1 E * * * e * Mesoderm +siNT v i * * * t 1 Mesoderm +siELK1

R 0

M 1 2 2 2 3 2 C D X X X B X N S IT B O A M P T F H C RT-qPCR of non-ELK1-bound Mesoderm markers 3 *

o i s * *

e 2 * r * * H1-hESC + siNT

p x H1-hESC + siELK1

E * *

e Mesoderm + siNT

v 1

i t Mesoderm + siELK1

R 0

M C 1 T B 2 S L 3 B G IX T M N W Figure 28: The role of ELK1 in gene expression driving mesoderm differentiation RT-qPCR measuring the expression of A) Pluripotency markers and ELK1 B) ELK1- bound genes after 98 hours of growth in MIM and KD with siELK1. Gene expression normalized to “MTESR +siNT” in Fig. 27A and “MIM +siNT” in Fig 27B. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments. * = p-value < 0.05.

Though we did not detect a clear role for ELK1 in mesoderm differentiation, it could be the case that ELK1 may play an important role in the differentiation down a different lineage.

We therefore tested the role of ELK1 in neural differentiation by treating H1-hESC for 5 days with Neural Induction Media (NIM), forming neural progenitor cells (NPCs). Briefly, cells were treated with siRNA 24 hours before the initiation of neural differentiation and retreated with siRNA 24 and 72 hours after the initiation of neural differentiation. We see a large decrease in

ELK1 expression in both H1-hESC and NPCs with siELK1 treatment (Fig. 29A). We also see the decrease of the expression of the pluripotency markers NANOG and OCT4 during neural differentiation and the moderate increase of the pluripotency gene SOX2, which is retained during neural differentiation (Fig. 29A). These changes along with an increase in LHX2 (Fig.

29B), a neural lineage marker, suggest that these the neural differentiation protocol works.

The expression of the NANOG, OCT4 and SOX2 were not significantly affected by siELK1 treatment (Fig. 29A). However, the expression of BTG2 increased with siELK1 depletion in both conditions, and SOX1 showed small increases with ELK1 depletion, though its expression decreases during neural differentiation, suggesting a potential repressive role for ELK1 (Fig.

29B). MEIS1 displayed a large increase in expression upon ELK1 depletion after neural differentiation, but not in untreated H1-hESC, again suggesting a repressive role for ELK1 (Fig.

29B). Finally, LHX2 displayed a decrease in expression upon ELK1 depletion after neural differentiation, but not in untreated H1-hESC (Fig. 29C). Though ELK1 does not directly bind near LHX2 in H1-hESC, perhaps it is recruited during neural differentiation or a TF activated by

ELK1 is necessary for the activation of LHX2. As a whole, this suggests ELK1 is not necessary for early mesoderm or neuronal differentiation, though it may play a repressive role a few of the genes tested. In addition, the decrease of LHX2 and the increase of MEIS1 in response to ELK1 depletion, genes which are expressed in different regions in the developing mouse vomeronasal organ and cerebellar anlage, suggest that perhaps long term depletion of ELK1

90 could channel differentiating cells into different neural lineages (Chang & Parrilla, 2016;

Morales & Hatten, 2006).

A RT-qPCR of Pluripotency Genes 2.0

i H1-hESC +siNT

s 1.5

e H1-hESC +siELK1

x 1.0 NPC +siNT

v NPC +siELK1

i t 0.5

R 0.0

H 1 G 4 2 D K O T X P L N C O A E A O S G N B C RT-qPCR of ELK1-bound RT-qPCR of non-ELK1-bound Differentiation Genes Differentiation Genes 4 4

s 3 s 3

s s H1-hESC +siNT

x x H1-hESC +siELK1 2 2

e e NPC +siNT

t 1 t 1

l l NPC +siELK1

R 0 0

B 2 1 1 1 2 T G IS X G X C T E O X H A B O L M S F

Figure 29: The role of ELK1 in gene expression driving neural differentiation RT-qPCR measuring the expression of A) Pluripotency markers and ELK1 B) ELK1- bound genes and C) non-ELK1 bound genes after 5 days of growth in NIM and KD with siELK1. Gene expression normalized to “MTESR +siNT” in Fig. 29A and “MIM +siNT” in Fig. 29B. Graphs represent the arithmetic mean +/- S.E.M. of 2 independent experiments.

4.IV.C The role of ELK1 in pluripotency Whilst performing ELK1 depletions in differentiation, using siELK1, we observed no change in pluripotency factors, contrary a previous report suggesting a necessary role for ELK1 in hESC pluripotency, and the observation of pluripotency marker reduction in shELK1 treatment (Göke et al.) (Fig. 23B, Fig. 28A and Fig. 29A). We therefore tested whether the siRNA depletion of ELK1 affected pluripotency markers. Briefly, cells were treated with siRNA on the day of cell plating and retreated with siRNA 48 hours after plating the cells. There was no change on the RNA or protein level of a variety of pluripotency factors following ELK1 depletion for 4 days (Fig. 30). We sought to determine whether a long term depletion of ELK1 had any effect on pluripotency. We therefore knocked down ELK1 for 7 days and tested the expression of canonical pluripotency factors and various early lineage factors, to establish whether ELK1 depletion stimulated differentiation or pluripotency loss. Briefly, cells were treated with siRNA on the day of cell plating and retreated with siRNA 48 and 96 hours after plating the cells. Upon 7 days of treatment with siELK1, we again saw a significant decrease in

ELK1 expression, but no significant change in either pluripotency factors or any of the lineage markers (Fig. 31). This suggests that ELK1 has no obvious role in maintaining pluripotency.

A B

70- ELK1 55- OCT4

55- TUBB 40- NANOG

Protein Quantification 35-

s 1.5 40- n * SOX2

e t 1.0 n +siNT 35-

e 0.5 v +siELK1

a l 0.0

R B 1 B K U L T E C RT-qPCR of Pluripotency Factors 2.0

s 1.5

r *

x 1.0 E +siNT

i t 0.5 +siELK1

R 0.0 H 1 4 C 4 L 2 T 2 K F G T X X 4 D L Y O R P P L M N C D O E F A E K A O O S T Z G N P

Figure 30: siELK1 treatment does not decrease pluripotency markers A) Western blot and protein quantification of ELK1 B) Western blots for TUBB, OCT4, NANOG and SOX2 expression in H1-hESC after 96 hours of siELK1 treatment C) RT- qPCR measuring the expression of pluripotency markers. Blots are representative of 3 independent experiments. Gene expression normalized to “+siNT.” Values are the average of 3 independent experiments. Significance is calculated comparing “+siNT” and “+siELK1”. * = p-value < 0.05.

A RT-qPCR of Pluripotency Factors 2.5

s 2.0

p 1.5 *

+siNT

e 1.0

t +siELK1

l 0.5

R 0.0

H 1 4 C G 1 2 3 D K F Y O F X X P L L 5 O B E K M N U S T A A O G N P B RT-qPCR of Lineage Markers 2.0

s 1.5

p +siNT

x 1.0

E +siELK1

i t 0.5

R 0.0

M 3 S 2 T 7 2 J E D 1 B X M N X O O A O F E H S

rm e d rm rm rm o e e e d d d d n o o o e s d t s e n c e E E M M

Figure 31: Effect of long term ELK1 depletion on pluripotency and lineage marker expression RT-qPCR measuring the expression of A) ELK1 and pluripotency markers and B) lineage markers after 7 days of siRNA treatment. Gene expression normalized to “+siNT.” Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments. * = p-value < 0.05.

4.IV.D Conclusion Part 4 Having shown that ELK1 did not recruit PRC2, we next tested the hypothesis that ELK1 was independently recruited to areas of SUZ12 binding during differentiation and played a contributing, but independent role in gene expression. We therefore performed ELK1 depletion during both mesodermal and neural differentiation. In both cases we found that

ELK1 depletion did not affect the expression or change in expression of pluripotency factors either before or after differentiation (Fig. 28A and Fig. 29A). We additionally, found that ELK1 depletion did not affect the expression of pluripotency factors, over a long term knockdown

(Fig. 30 and Fig. 31). We did see that ELK1 depletion increased the expression of BTG2 and

MEIS1 in neural differentiation (Fig. 29B) and FOXC1 and HAND2 in mesoderm differentiation

(Fig. 28B). This suggests that ELK1 may have a repressive role in the regulation of these genes.

To further investigate this, we therefore sought to reaffirm previously known ELK1 peaks in

H1-hESC and uncover binding regions in mesoderm, using ChIP-seq to analyse ELK1 binding genome-wide.

4.V Genome-wide investigation of ETS transcription factor binding sites 4.V.A ChIP-seq of ELK1 and ETV1 Having determined that ELK1 was not necessary for the expression of differentiation genes, but in fact may be repressing some of them, we sought to explore mechanisms by which ELK1 might be acting. One mechanism may be physically inhibiting the binding of other, transcription-activating ETS factors, or recruiting co-repressors (Fig. 32). We therefore set out to test for either of these possibilities and chose to perform ChIP-seq on ELK1 and another ETS protein in both H1-hESC and mesoderm. Boros et al. demonstrate that ELK1-bound promoters are bound by other ETS factors, suggesting that the same may be true in H1-hESC and mesoderm, and the exchange may provide mechanisms to follow-up on (Boros et al., 2009).

We chose ETV1 because 1) its expression remains high at the mRNA level, relative to many other ETS-proteins during mesoderm differentiation (Fig. 33A), 2) using our mesoderm differentiation protocol, we found the protein level of ETV1 appeared to increase (Fig. 33B), 3) it is an activator of gene transcription (Papoutsopoulou & Janknecht, 2000), and would thus be a potential active counterpart to ELK1-based repression. We thus performed ChIP-seq on ETV1 and ELK1 in cells grown in pluripotency media and cells differentiated to mesoderm for 72 hours.

ETS? Repressive Co-factors?

H3K27me3

Pluripotent cell ELK1 GENE ETS Motif?

B Activating Co-factors?

Activation? Differentiated cell ETS? GENE ETS Motif?

Figure 32: Model of ELK1 as a repressive factor Hypothetical exchange mechanism involving the recruitment of another ETS factor to an ELK1 repressive binding site. A) ELK1 and potential repressive co-factors repress the expression of a gene in a pluripotent cell state. B) A new ETS protein binds to the region, perhaps recruiting co-factors and activating gene expression in a differentiated cell state.

Figure 33: Western blot of and expression ETV1 in H1-hESC and Mesoderm cells A) Normalized FPKM and H1/Mesoderm fold change (FC) in log2 of ELK1 and ETV1 and other ETS factors in mRNA-seq data for H1-hESC and Mesoderm (data from the Epigenomics Roadmap Consortium). B) ETV1 and TUB blots in hESC cells grown in MTESR, to maintain pluripotency or grown in MIM, to promote mesoderm differentiation for 72 hours. Blots are representative of at least 3 independent experiments. There were 2 RNA-seq datasets for each condition. .

4.V.A.i Analysis of the ELK1 ChIP-seq peaks Likewise, the ELK1 ChIP-seq, while reasonably successful in mesoderm, with ~10% of peaks with a fold enrichment of over 7. This was lower than the H1 (GIS) dataset, with 47.5% of the peaks in this dataset, with a fold enrichment of over 7. Finally, we saw very few high fold enrichment (FE > 4) peaks in H1-hESC, suggesting perhaps a poor ChIP-seq dataset (Fig. 34A).

However, we also see that roughly 36%, 43.9% and 42.7%, respectively, of the H1-hESC, mesoderm and H1 (GIS) peaks, contain any known ETS motifs in HOMER (Fig. 34A). We therefore decided to analyse the quality of the ChIP-seq datasets in a different way. We analysed the datasets for enrichments of known binding motifs in HOMER. We report the ETS motif with the highest enrichment. Though we see comparable amount of ETS motifs in both

ELK1 datasets (ETV2 motifs were found 26% in mesoderm and 20% in H1-hESC peaks) this was roughly half of ETS enrichment in the ELK1 H1 (GIS) dataset (FLI (ETS TF) motifs were found in roughly 46% of the peaks) (Fig. 35). Additionally, we analysed all three datasets for SRF, which has been reported to be enriched up to 54% in an ELK1 dataset (Odrowaz & Sharrocks, 2012a).

When we analysed the dataset, both mesoderm and H1 (GIS) had an SRF motif in 13% and 15% of the peaks, respectively (Fig. 35 B,C), which is comparable to the 17% SRF enrichment seen in a 2014 TCF ChIP-seq dataset analysis (Esnault et al., 2014). The H1-hESC dataset netted only 6

SRF motifs (Fig. 35A), underscoring a potentially poor ChIP-seq dataset, suggesting too low a

ChIP signal for the peaks to be called in MACS2. Looking in the IGV viewer, we do in fact see many genes, which are bound at a low level, but did not necessarily get called in MACS2. In either case, we validated the ChIP-seq results with Fluidigm rather than a bioinformatics approach (discussed in section 4.V.C).

Figure 34: ELK1 ChIP-seq peak counts Counts of narrow peaks from MACS2 analysis on ELK1 ChIP-seq overlaps of H1-hESC (replicates 1 and 2 merged), mesoderm (replicates 1 and 2 merged) and H1 (GIS), the H1-hESC ELK1 ChIP dataset from Göke et al. Overlaps are further specified by those peaks containing ETS motifs, a fold enrichment of 4 over input and a fold enrichment of 7 over input.

100

Figure 35: Motifs in ELK1 ChIP-seq peaks Top ETS and SRF motifs in the A) ELK1 in H1-hESC B) ELK1 in Mesoderm and C) ELK1 in H1-hESC (Göke et. al, 2013) ChIP-seq datasets sorted by log P-value. D) Visualization of top motifs by JAPSAR.

101

4.V.A.ii Analysis of the ETV1 ChIP-seq We next attempted a ChIP-seq of ETV1 in H1-hESC and mesoderm, to contrast with ELK1 binding regions. We first attempted an immunoprecipitation of ETV1 and the pulldown was successful (Fig. 36A). We again analysed the datasets for enrichments of known binding motifs in HOMER. We report the ETS motif with the highest enrichment. We do see comparable amount of ETS motifs in both ELK1 datasets (ELF5 motifs were found 14.3% in mesoderm and

20% in H1-hESC peaks) and only 1 SRF motif in the ETV1 mesoderm dataset (Fig. 36). This would suggest detectable ETV1 peaks. However, upon calling peaks with MACS2 we found low fold-enrichment above the input for even the top peaks, no high fold-enrichment (FE>4) ETV1 peaks in H1-hESC and only two high fold-enrichment (FE>4) ETV1 peaks in mesoderm (Fig.

36B+C). Having called no highly enriched peaks with MACS2, we next attempted to pick out binding peaks visually. Spot checking large stretched of gene rich regions, we still don’t see any clear highly enriched ETV1 binding sites (Fig. 37). We therefore could not further analyse the

ETV1 ChIP-seq results.

102

Figure 36: ETV1 ChIP-seq has low fold enrichment A) Western blot of ETV1 Immunoprecipitation. The top 10 MACS2 ChIP-seq peaks for ETV1 in B) H1-hESC C) Mesoderm cells sorted by fold enrichment, relative to input. FT = 6.67% of the IP flow through. Each chart represents the 1st of 2 replicates.

103

Figure 37: Top ETV1 ChIP-seq Peaks by Fold Enrichment ETV1 ChIP-seq in H1-hESC and Mesoderm, visualized in IGV at gene-rich regions of chr1 and 2. Genome visualization represents the 1st of 2 replicates. The red box highlights the chromosomal coordinates of the genome view.

104

Figure 38: Motifs in ETV1 ChIP-seq peaks Top ETS and SRF motif in the A) ETV1 in H1-hESC B) ETV1 in Mesoderm ChIP-seq datasets sorted by log P-value. C) Visualization of top motifs by JAPSAR.

105

4.V.B STAT binding overlaps with ELK1 binding In addition to the enrichment of ETS and SRF motifs in the ELK1 ChIP-seq dataset and

ETS motifs in the ETV1 ChIP-seq dataset, STAT motifs showed up in both our ETV1 and ELK1

ChIP-seq dataset (Fig. 39). This could be an artefact of the similarity of the STAT and ETS motifs, though looking at the peaks in the genome browser, we can also see that many of the

ELK1 peaks are bound by one or more of the STAT TFs in one or more of the cell lines (Fig.

40A).

106

Figure 39: STAT Motifs are present in ETS ChIP-seq peaks Top STAT and ETS motifs in the A) ELK1 in H1-hESC B) ELK1 in Mesoderm and C) ELK1 in H1-hESC (Göke et. al, 2013) ChIP-seq datasets sorted by log P-value. D) Visualization of top motifs by JAPSAR.

107

Figure 40: ELK1 ChIP-seq peaks overlapping with STATs A) ELK1, STAT1 and STAT3 ChIP-seq peaks visualized in IGV in MCF10A, HELA and H1- hESC. B) Normalized FPKM and H1/Mesoderm fold change (FC) in log2 of mRNA-seq of H1-hESC and Mesoderm cells. Genome visualization represents the 1st of 2 replicates for ELK1. STAT1 and STAT3 ChIP-seq data from ENCODE. Cell lines are indicated after TF names. RNA-seq data from the Epigenomics Roadmap Consortium. STAT4 was not significantly expressed. There were 2 datasets for each condition.

108

To establish potential co-binding of STAT and ELK1, we next attempted to ChIP STAT3 in both H1-hESC and mesoderm cells, because STAT3 had the highest expression in both cell lines (Fig. 40B). However, though STAT3 was detectable with an IP, albeit at a low level (Fig

41A), we were ultimately unable to find any ELK1 binding regions to which it also bound.

Suspecting that STAT3 would need to localize to the nucleus to be detectable with ChIP, we stimulated H1-hESC with IL-6. However, still no STAT3 binding was detectable with IL-6 treatment (Fig 41B). Therefore, we did not investigate STAT further in this study.

100- STAT3

1 2 3 4 5 B STAT3 ChIP-qPCR 0.010

0.008  STAT3

t  IgG u 0.006

 STAT3 +IL-6 0.004

%  IgG +IL-6 0.002

0.000 S 1 2 B T T O R R N A A F G G T T c U S S E E J _ _ 4 4 1 K K 3 P P A A M M Figure 41: STAT3 binding is not increased by IL-6 in H1-hESCcells A) Western blot analysis of STAT3 Immunoprecipitation. B) ChIP-qPCR of STAT3 in H1-hESC cells stimulated with IL-6 for 30 minutes. Blot and ChIP-qPCR are representative of 1 experiment.

109

4.V.C Verification of ELK1+SRF co-binding Using the ChIP-seq data from ELK1 in both the H1-hESC and mesoderm datasets, we designed primers for ELK1 peaks with high binding in at least one ChIP-seq dataset, which we then went on to verify with ChIP-PCR, using the Biomark HD Fluidigm system.

Firstly, all of the regions tested were bound by ELK1 in at least one condition, in the

ChIP-qPCR. First we tested three regions on which ELK1 and SRF was expected not to be bound, as negative controls to check for non-specific binding, all three of these, were confirmed to be negative for ELK1 and SRF binding (Fig. 42). Next, we tested 10 ELK1 regions that were bound in roughly equally measure in both H1-hESC and mesoderm in the ChIP-seq data, these were confirmed to be roughly equivalently bound in the ChIP-qPCR data (Fig. 44).

Next, we tested three regions that were positive for ELK1 and negative for SRF, all three of these were confirmed (Fig. 43). Finally, we tested 15 regions in which ELK1 appeared to increase in the mesoderm condition. Out of these, 4 were confirmed to display an increased level of ELK1 binding, along with an increase in SRF (Fig. 45). One of these, a region near

MAPK4, had decreased ELK1 and SRF binding in mesoderm (Fig. 46A). The final 10 regions showed binding by both ELK1 and SRF in both conditions, but either had no change between conditions, or the trend varied between replicates (Fig. 46B). Taken together these data, demonstrate that there are regions in which ELK1 and SRF binding increase upon mesoderm differentiation. It could be the case that either ELK1 or SRF recruits its cofactor during differentiation. In addition, there are many regions in which the ELK1 or SRF increase or remain bound at equal levels during differentiation, and it could be that ELK1 or SRF is necessary for maintaining the binding levels of its co-factor during differentiation, making these equally useful peaks to follow up on.

110

B ChIP-qPCR of ELK1 and SRF ELK1 H1 0.05 ELK1 Meso. 0.04

t SRF H1 u 0.03

I SRF Meso. 0.02

% 0.01 IgG H1 0.00 IgG Meso. n b H k D ro 2 P t _ A in 1 _ G 2 R R G G E E

Figure 42: ChIP-qPCR of regions not bound by ELK1 and SRF A) H1-hESC and SRF and ELK1 ChIP-seq and mesoderm ELK1 ChIP-seq peaks visualized in IGV. B) Fluidigm ChIP-qPCR of ELK1, SRF and rabbit IgG in H1-hESC and mesoderm. Genome visualization represents the 1st of 2 replicates for ELK1. SRF ChIP-seq data from ENCODE. Cell lines are indicated after TF names. Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments.

111

B ChIP-qPCR of ELK1 and SRF ELK1 H1 0.05 ELK1 Meso. 0.04

t SRF H1 u 0.03

I SRF Meso. 0.02

% 0.01 IgG H1 0.00 IgG Meso. 2 6 5 N T 3 R K C I T H S S

Figure 43: ChIP-qPCR of regions bound by ELK1 and not SRF in H1-hESC and mesoderm A) H1-hESC and SRF and ELK1 ChIP-seq and mesoderm ELK1 ChIP-seq peaks visualized in IGV. B) Fluidigm ChIP-qPCR of ELK1, SRF and rabbit IgG in H1-hESC and mesoderm. Genome visualization represents the 1st of 2 replicates for ELK1. SRF ChIP-seq data from ENCODE. Cell lines are indicated after TF names. Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments.

112

B ChIP-qPCR of ELK1 and SRF ELK1 H1 0.15 ELK1 Meso. SRF H1 t 0.10

n SRF Meso.

% 0.05 IgG H1

0.00 IgG Meso. 6 A 2 3 4 L 2 R F 1 F 3 E R K G M I I 3 E A P F A M ChIP-qPCR of ELK1 and SRF ELK1 H1 0.05 ELK1 Meso. 0.04 t SRF H1 u 0.03

I SRF Meso. 0.02

% 0.01 IgG H1 0.00 IgG Meso. 3 1 2 3 1 1 R A 4 A K G IM 1 D N E L 0 A W C T IN L

Figure 44: ChIP-qPCR of regions bound by ELK1 in H1-hESC and mesoderm A) H1-hESC and SRF and ELK1 ChIP-seq and mesoderm ELK1 ChIP-seq peaks visualized in IGV. B) Fluidigm ChIP-qPCR of ELK1, SRF and rabbit IgG in H1-hESC and mesoderm. Genome visualization represents the 1st of 2 replicates for ELK1. SRF ChIP-seq data from ENCODE. Cell lines are indicated after TF names. Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments.

113

B ChIP-qPCR of ELK1 and SRF ELK1 H1 0.05 ELK1 Meso. 0.04 *

t SRF H1 u 0.03

I SRF Meso. * 0.02 * * *

% 0.01 IgG H1 0.00 IgG Meso. 2 2 1 3 L G A C T T 4 A P B R D G N V N A

Figure 45: ChIP-qPCR of regions with higher ELK1 and SRF binding in mesoderm A) H1-hESC and SRF and ELK1 ChIP-seq and mesoderm ELK1 ChIP-seq peaks visualized in IGV. B) Fluidigm ChIP-qPCR of ELK1, SRF and rabbit IgG in H1-hESC and mesoderm. Genome visualization represents the 1st of 2 replicates for ELK1. SRF ChIP-seq data from ENCODE. Cell lines are indicated after TF names. Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments. * = p > 0.5.

114

A ChIP-qPCR of ELK1 and SRF ELK1 H1 0.05 ELK1 Meso. 0.04

t SRF H1 u 0.03

I SRF Meso. 0.02

% 0.01 IgG H1 0.00 IgG Meso. 4 K P A B M ChIP-qPCR of ELK1 and SRF ELK1 H1 0.05 * ELK1 Meso. 0.04 *

t SRF H1 u 0.03

I SRF Meso. 0.02

% 0.01 IgG H1 0.00 IgG Meso. C S 1 2 1 R O 6 R L A F R G C c Y E C M

ChIP-qPCR of ELK1 and SRF ELK1 H1 0.05 * ELK1 Meso. 0.04

t SRF H1 u 0.03

I SRF Meso. 0.02

% 0.01 IgG H1 0.00 IgG Meso. L L 5 4 7 C 3 S 2 F R S F L C A E U P T P G D R S T N P

Figure 46: ChIP-qPCR of regions with higher ELK1 and SRF binding in mesoderm A) Fluidigm ChIP-qPCR of ELK1, SRF and rabbit IgG measuring binding near MAPK and B) on a variety of regions in H1-hESC and mesoderm. Cell lines are indicated after TF names. Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments. * = p > 0.5.

115

4.V.D SRF depletion reduces ELK1 binding Having established a pool of regions which are bound by ELK1 and/or SRF in both H1- hESC and mesoderm, we further investigated the relationship of ELK1 and SRF in gene co- regulation. By knocking down either ELK1 or SRF, on which binding loci ELK1 recruits SRF or vice versa. Having four regions in which ELK1 and SRF both increase during differentiation, and

15 regions in which either ELK1 or SRF increase, and the other remains bound and equivalent levels, we performed ELK1 and SRF depletion to determine the order of recruitment.

We then performed a ChIP-qPCR analysis of our previously tested ELK1-bound regions to determine the binding of ELK1 and SRF with both siELK1 and siSRF treatments in both H1-hESC and mesoderm. In the case of the siSRF treatment, SRF binding and ELK1 binding were both reduced, as demonstrated in binding loci near EGR1, EGR2 and SPARCL (Fig. 47A-C), whilst the negative region remained unbound in all conditions (Fig. 47D). This pattern was detected in

19/19 of the regions tested H1-hESC (Fig. 48A+B) and 16/19 of the regions tested in mesoderm

(Fig. 48C+D).

In the case of siELK1 treatment, ELK1 binding was reduced, as demonstrated in binding loci near EGR1, EGR2 and SPARCL (Fig. 47A-C), whilst the negative region remained unbound in all conditions (Fig. 47D). However, SRF binding was increased upon ELK1 binding. This pattern was detected in 16/19 of the regions tested H1-hESC (Fig. 49A+B) and 14/19 of the regions tested in mesoderm (Fig. 49C+D). Neither of these binding changes affected the non-bound regions, suggesting these binding changes aren’t due a general increase or decrease in binding.

116

+siNT +siNT

+siSRF +siSRF

+siELK1 +siELK1 A +siNT +siNT EGR1 in H1-hESC EGR1 in Mesoderm 0.25 0.25 +siSRF +siSRF 0.20 * 0.20

t t *

u u * * +siNT+siELK1 +siNT+siELK1

p p 0.15 0.15 *

n n *

I I

* 0.10 0.10 * +siSRF+siNT +siSRF+siNT

% % 0.05 0.05 +siELK1 0.00 0.00 +siELK1+siSRF +siSRF T F 1 T F 1 T F 1 T F 1 T F 1 T F 1 +siNT B iN R K iN R K iN R K iN R +siNT+siELK1K iN R K iN R K +siELK1 s iS L s iS L s iS L s iS EGR2L s iniS MesodermL s iS L + s iE EGR2+ s in H1-hESCiE + s iE + s iE + s iE + s iE 0.10 + s + s + s 0.10 + s + s + s + + + + +siSRF + + +siSRF * 0.08

0.08 t t *

 ELK1  SRF  IgG u  ELK1  SRF  IgG u +siELK1 +siELK1 p 0.06 +siNT p 0.06 +siNT

n n * * I

* 0.04 0.04 +siNT * % * +siNT +siSRF % +siSRF 0.02 0.02 +siSRF 0.00 0.00 +siELK1+siSRF +siELK1 T F 1 T F 1 T F 1 T F 1 T F 1 T F 1 N R K N R K N R K iN R +siELK1K iN R K iN R K +siELK1 C i S L i S L i S L s iS +siNTL s iS L s iS L +siNT s i E s i E s i E + s iE + s iE + s iE + s i SPARCL+ s ini H1-hESC+ s i + s SPARCL+ ins Mesoderm+ s 0.05 + s + s + s 0.05 + + + + + + +siSRF +siSRF 0.04 * 0.04 t  ELK1  SRF  IgG t  ELK1  SRF  IgG

u u +siELK1+siNT +siNT+siELK1

p 0.03 p 0.03

0.02 0.02 *+siNT+siSRF +siSRF+siNT

% % 0.01 0.01 0.00 0.00 +siSRF+siELK1 +siELK1+siSRF T F 1 T F 1 T F 1 T F 1 T F 1 T F 1 K K K N R +siELK1K N R K N R K +siELK1 D iN R iN R iN R i +siNTL i L i L +siNT s iS L s iS L s iS L s iS s iS s iS + s EGR1_2KbiE + s iinE H1-hESC+ s iE + s EGR1_2KbiE + s iniE Mesoderm+ s iE + s + s + s + s + s + s 0.05 + + + 0.05 + +siSRF + + +siSRF 0.04 0.04

t  ELK1  SRF  IgG t  ELK1  SRF  IgG

u u +siELK1 +siELK1

p 0.03 p 0.03

0.02 0.02 +siNT +siNT

% 0.01 % 0.01 0.00 0.00 +siSRF +siSRF T F 1 T F 1 T F 1 T F 1 T F 1 T F 1 iN R K iN R K iN R K iN R +siELK1K iN R K iN R K +siELK1 s iS L s iS L s iS L s iS L s iS L s iS L + s iE + s iE + s iE + s iE + s iE + s iE + s + s + s + s + s + s + + + + + +  ELK1  SRF  IgG  ELK1  SRF  IgG

Figure 47: The effect of SRF and ELK1 depletion on SRF and ELK1 binding ChIP-qPCR of ELK1 (yellow bars), SRF (blue bars) and rabbit IgG (grey bars) on ELK1-bound regions near A) EGR1 B) EGR2 C) SPARCL or D) a negative region 2Kb upstream of EGR1, after 96 hours of siNT, siSRF or siELK1 treatment in H1-hESC or mesoderm. Binding presented as % Input. Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments. * = p-value < 0.05.

117

A B C D SRF in H1-hESC ELK1 in H1-hESC SRF in Mesoderm ELK1 in Mesoderm ANGPTL2 0.0027 ANGPTL20.0022 0.0021 ANGPTL20.0013 0.0047 ANGPTL20.0026 0.0060 0.0035 ARC 0.0084 0.0061ARC 0.0077 0.0037ARC 0.0057 0.0039ARC 0.0072 0.0055 BTG2 0.0236 0.0126BTG2 0.0085 0.0048BTG2 0.0116 0.0076BTG2 0.0060 0.0049 CFOS 0.0376 0.0225CFOS* 0.0262 0.0162CFOS* 0.0220 0.0172CFOS 0.0155 0.0182 CYR61 0.0085 CYR610.0046 0.0042 0.0024CYR61 0.0073 CYR610.0053 0.0052 0.0038 EGFL6 0.0437 EGFL60.0234 * 0.0065 0.0036EGFL6 0.0180 EGFL60.0057 * 0.0058 0.0025 EGR1 0.1055 0.0625EGR1* 0.0564 0.0304EGR1* 0.0645 0.0411EGR1 0.0392 0.0292 EGR2 0.0432 0.0305EGR2 0.0146 0.0063EGR2 0.0291 0.0180EGR2 0.0093 0.0072 EGR3 0.0241 0.0103EGR3* 0.0136 0.0044EGR3 0.0180 0.0069EGR3* 0.0098 0.0047 IER2 0.0239 0.0164IER2 0.0422 0.0210IER2* 0.0131 0.0117IER2 0.0236 0.0204 IRF3 0.0410 0.0266IRF3* 0.0523 0.0324IRF3* 0.0251 0.0236IRF3 0.0326 0.0340 MAP3K14 0.0643 MAP3K140.0362 * 0.0532 MAP3K140.0260 0.0366 MAP3K140.0216 0.0350 0.0220 * MAPK4 0.0155 MAPK40.0071 0.0076 MAPK40.0026 0.0071 MAPK40.0033 0.0046 0.0027 MCL1 0.0194 0.0132MCL1 0.0122 0.0056MCL1 0.0140 0.0104MCL1 0.0085 0.0056 NR3C2 0.0158 NR3C20.0085 0.0070 NR3C20.0036 0.0087 NR3C20.0065 0.0052 0.0040 NR4A1 0.0082 NR4A10.0051 0.0078 NR4A10.0034 0.0068 NR4A10.0069 0.0092 0.0097 SPARCL 0.0329 SPARCL0.0149 * 0.0107 SPARCL0.0044 0.0216 SPARCL0.0135 0.0090 0.0068 0.0100 0.0051 0.0079 0.0027TCF7 0.0079 0.0043TCF7 0.0066 0.0042

- TCF7 TCF7 -

e 0.0109e 0.0050 0.0081 0.0049

e VDAC3 0.0068e VDAC30.0044 0.0046 VDAC30.0018 VDAC3*

r r EGR1_2kb 0.0011 EGR1_2kb0.0023 0.0011 0.0010

e EGR1_2kb 0.0013 EGR1_2kb0.0015 0.0017 0.0011 e

g EGR2_intron 0.0031g EGR2_intron0.0026 0.0032EGR2_intron0.0015 0.0027EGR2_intron0.0020 0.0026 0.0013

n GAPDH 0.0021n GAPDH0.0025 0.0041 0.0030

n GAPDH 0.0029n GAPDH0.0027 0.0032 0.0030

T F T F T F T F iN R iN R iN R iN R s iS s iS s iS s iS + s + s + s + s + + + + % Input % Input % Input % Input

2 4 6

1 2 3

5 0

2 4

0 0 0

0 1

0 0

. . .

. .

0 0 0

0 0

Figure 48: SRF depletion reduces ELK1 binding. Heatmaps displaying ChIP-qPCR of A) SRF and B) ELK1 in +siNT and +siSRF treated H1-hESC and C) SRF and D) ELK1 in +siNT and +siSRF treated mesoderm. Binding presented as % Input. Cell values represent the arithmetic mean of 3 independent experiments. -ve regions = regions negative for ELK1 binding. * = p-value < 0.05.

118

A B C D ELK1 in H1-hESC SRF in H1-hESC ELK1 in Mesoderm SRF in Mesoderm ANGPTL2 0.0021 ANGPTL20.0020 0.0027 ANGPTL20.0036 0.0060 ANGPTL20.0025 0.0047 0.0046 ARC 0.0077 0.0046ARC 0.0084 0.0175ARC 0.0072 0.0028ARC 0.0057 0.0093 BTG2 0.0085 0.0037BTG2 0.0236 0.0458BTG2* 0.0060 0.0029BTG2* 0.0116 0.0199 CFOS 0.0262 0.0156CFOS* 0.0376 0.0717CFOS* 0.0155 0.0138CFOS 0.0220 0.0436 * CYR61 0.0042 CYR610.0051 0.0085 CYR610.0207 * 0.0052 CYR610.0045 0.0073 0.0130 EGFL6 0.0065 EGFL60.0052 0.0437 EGFL60.0607 * 0.0058 EGFL60.0050 0.0180 0.0253 EGR1 0.0564 0.0230EGR1* 0.1055 0.1250EGR1* 0.0392 0.0164EGR1* 0.0645 0.0861 * EGR2 0.0146 0.0081EGR2 0.0432 0.0788EGR2* 0.0093 0.0037EGR2* 0.0291 0.0366 EGR3 0.0136 0.0073EGR3 0.0241 0.0388EGR3 0.0098 0.0042EGR3* 0.0180 0.0171 IER2 0.0422 0.0234IER2* 0.0239 0.0530IER2* 0.0236 0.0116IER2* 0.0131 0.0210 IRF3 0.0523 0.0360IRF3* 0.0410 0.0789IRF3* 0.0326 0.0209IRF3* 0.0251 0.0363 MAP3K14 0.0532 MAP3K140.0269 * 0.0643 MAP3K140.0707 0.0350 MAP3K140.0153 * 0.0366 0.0414 MAPK4 0.0076 MAPK40.0031 0.0155 MAPK40.0158 0.0046 MAPK40.0020 0.0071 0.0065 MCL1 0.0122 0.0058MCL1 0.0194 0.0341MCL1 0.0085 0.0051MCL1 0.0140 0.0207 NR3C2 0.0070 NR3C20.0054 0.0158 NR3C20.0175 0.0052 NR3C20.0030 0.0087 0.0076 NR4A1 0.0078 NR4A10.0006 0.0082 NR4A10.0129 0.0092 NR4A10.0062 0.0068 0.0116 SPARCL 0.0107 SPARCL0.0056 0.0329 SPARCL0.0372 0.0090 SPARCL0.0046 * 0.0216 0.0217 TCF7 0.0079 0.0028TCF7 0.0100 0.0095TCF7 0.0066 0.0025TCF7 0.0079 0.0050

- -

- - *

v v

e e

e VDAC3 0.0046e VDAC30.0037 0.0068 VDAC30.0068 0.0081 VDAC30.0034 * 0.0109 0.0075

r r

r EGR1_2kb 0.0017r 0.0009 0.0013 EGR1_2kb0.0012 0.0011 EGR1_2kb0.0007 0.0011 0.0009

e e e EGR1_2kb

g g

g EGR2_intron 0.0032g EGR2_intron0.0024 0.0031EGR2_intron0.0020 0.0026EGR2_intron0.0013 0.0027 0.0032

i i

o o

n n

n GAPDH 0.0032n GAPDH0.0024 0.0029 GAPDH0.0013 0.0041 GAPDH0.0036 0.0021 0.0041

s s

s T 1 T 1 T 1 T 1 iN K iN K iN K iN K s L s L s L s L + iE + iE + iE + iE s s s s + + + + % Input % Input % Input % Input

1 2

4 2

2 4

5 0

0 0

0 1

. .

0 0

Figure 49: ELK1 depletion increases SRF binding. Heatmaps displaying ChIP-qPCR of A) ELK1 and B) SRF in +siNT and +siELK1 treated H1-hESC and C) ELK1 and D) SRF in +siNT and +siELK1 treated mesoderm. Binding presented as % Input. Cell values represent the arithmetic mean of 3 independent experiments. -ve regions = regions negative for ELK1 binding. * = p-value < 0.05.

119

4.V.E Conclusion Part 5 Having shown that ELK1 may have had a repressive function in differentiation (discussed in section 4.IV.B) we next sought to determine if there was an ELK1-ETS factor binding switch during differentiation, and performed a ChIP-seq on ELK1 and ETV1 in both H1-hESC and mesoderm cells. Whilst the ETV1 ChIP-seq was unsuccessful (discussed in section 4.V.A.ii), we were able to call ELK1 peaks in H1-hESC and mesoderm cells. We followed up the ChIP-seq with a ChIP-qPCR of ELK1 and its known co-factor SRF using Fluidigm. We found loci of ELK1 and SRF binding in H1-hESC and mesoderm (Figs. 42-46). Moreover, the similar binding trends of ELK1 and SRF in many loci during mesoderm differentiation suggest a cooperative relationship.

Having established a pool of regions which are bound by ELK1 and/or SRF in both H1- hESC and mesoderm, we performed a ChIP-qPCR analysis of our previously tested ELK1-bound regions to determine the binding of ELK1 and SRF with both siELK1 and siSRF treatments in both H1-hESC and mesoderm.

In the case of the siSRF treatment, SRF binding and ELK1 binding were both reduced, as demonstrated in binding loci near EGR1, EGR2 and SPARCL (Fig. 47), whilst the negative region remained unbound in all conditions. The reduction of ELK1 binding upon the depletion of SRF, suggests that SRF improves the recruitment of and perhaps even directly recruits ELK1 (Fig.

48). This corroborates a study by Esnault et al. showing SRF bound on the chromatin before the recruitment of either MRTFs or TCFs (Esnault et al., 2014).

However, SRF binding increased upon ELK1 depletion (Fig. 49), which is suggestive at least of ELK1/TCF redundancy, and may further suggest a model by which an SRF co-factor, perhaps another TCF or MRTF, bind in the absence of ELK1 and increase the affinity of SRF for

DNA.

120

5. Summary 5.I ELK1 does not recruit PRC2 To establish a pool of candidate genes of further interest in exploring an ELK1-PRC2 interaction, we partitioned ELK1 peaks in H1-hESC by potential co-factors. We demonstrate that partitioning ELK1 peaks by PRC2 occupancy, again gives us two modules, an ELK1+SUZ12 module, enriched for the PRC2 complex and the H3K27me3 repressive histone modification, and an ELK1-SUZ12 modules, enriched for active histone marks and SRF (Fig. 7). We additionally demonstrate that an ELK1+SUZ12 module is enriched for peaks near development genes (Fig. 8).

We also found the enrichment of the PRC2 is specific to ELK1 binding loci, compared to

GABPA, another ETS TF, suggesting that the PRC2 interaction might be unique to ELK1 (Fig. 12).

Finally, we find that PRC2 is enriched on H1-hESC specific ELK1 peaks, relative to other cell types, suggesting that an ELK1+PRC2 interaction may be H1-hESC specific (Fig. 9). Taken together, these data suggested that investigating the recruitment of PRC2 by ELK1 was appropriate to study in H1-hESC, we therefore investigated a direct interaction between ELK1 and PRC2.

Having established that there was a subset of ELK1 loci that are enriched for PRC2 binding, suggesting perhaps a co-regulatory interaction between ELK1 and PRC2, we attempted to investigate the ELK1 interactome using RIME. We did not detect any PRC2 core components using RIME, and did not detect any interaction using co-immunoprecipitation and determined that there was no detectable direct interaction with ELK1 and PRC2 (Fig. 16). We therefore tested whether there was a possible indirect interaction between ELK1 and the

PRC2.

Using the binding regions from the ELK1+SUZ12 binding module (Fig. 13A+B), we identified a set of nearby genes that increase upon RA treat in H1-hESC (Fig. 19B+C). However,

121 with the exception of the decrease of ELK1 binding near SIX1 and ZFHX3, we did not see a general decrease of ELK1, nor a decrease in SUZ12 binding or H3K27me3 enrichment nearby any of the genes we tested during differentiation (Fig. 21). We also depleted ELK1 to determine if SUZ12 binding was affected by depletion of ELK1 binding. However, we did not see a decrease of SUZ12 binding or the H3K27me3 modification upon ELK1 depletion (Fig. 25), suggesting that ELK1 is not necessary for SUZ12 recruitment.

We do see a decrease in ELK1 binding near ZFHX3 upon RA treatment, however this was not accompanied by a change in SUZ12 binding or H3K27me3 binding (Fig. 21). However,

ZFHX3 expression did not increase upon ELK1 depletion, suggesting, in this case of ZFHX3, the depletion of ELK1 alone is not sufficient to stimulate transcription (Figs. 26). Additionally, we do see significant change in the expression SIX1 upon ELK1 depletion (Fig. 26). There may be a slight repressive role for ELK1 in the case of SIX1 regulation, but this does not appear to involve

SUZ12/PRC2 repression. Taken together, we therefore conclude that ELK1 does not recruit the

PRC2 complex, but may still have a repressive function.

5.II The role of ELK1 in maintaining pluripotency and differentiation Göke et al. also suggest that ELK1 is necessary for the maintenance of pluripotency repressing differentiation genes (Göke et al., 2013). While our re-analysis of the ChIP-seq data suggested a similar conclusion, depletion of ELK1 with siELK1 did not have an effect on pluripotency. ELK1 depletion had an effect on a few genes in both mesoderm and neural differentiation, but again, we did not see a general effect. We also saw a decrease in NANOG and OCT4 expression with ELK1 depletion with shELK1. However, we didn’t see a decrease in other pluripotency factors nor a change in most differentiation factors. Taken together with a mouse knockdown study, these data suggest that ELK1 doesn’t have a crucial role in pluripotency or development (Cesari et al., 2004). Further, we depleted ELK1 using siRNA during both mesodermal and neural differentiation. In both cases we found that ELK1 did not

122 affect the expression or change in expression of pluripotency factors either before or after differentiation (Fig. 28A and Fig. 29A). We additionally, found that ELK1 depletion using siRNA did not affect the expression of pluripotency factors, over a long term knockdown (Fig. 30 and

Fig. 31)

We did see that ELK1 depletion increased the expression of BTG2 and MEIS1 in neural differentiation (Fig. 29B) and FOXC1 and HAND2 in mesoderm differentiation (Fig. 28B). This suggests that ELK1 may have a repressive role in the regulation of these genes, though we don’t see a general inhibition or activation of pluripotency or differentiation factors, making any role for ELK1 in differentiation unclear.

5.III Investigating ELK1 co-factors Having seen a potential influence on transcription of genes in differentiation with ELK1, we attempted to ChIP ELK1 and ETV1 to potentially uncover an interaction between two ETS proteins potentially suggesting a specific remit for each TF. However, the ETV1 ChIP-seq was unsuccessful.

We then went on to revisit a potential active role for ELK1 and SRF in differentiation, we therefore sought to perform ChIP-qPCR on ELK1 and known co-factor SRF in H1-hESC and mesoderm. Having established a pool of regions which are bound by ELK1 and/or SRF in both

H1-hESC and mesoderm (Fig. 42-46), we performed a ChIP-qPCR analysis of our previously tested ELK1-bound regions to determine the binding of ELK1 and SRF with both siELK1 and siSRF treatments in both H1-hESC and mesoderm. In the case of the siSRF treatment, SRF binding and ELK1 binding were both reduced (Fig. 48), suggesting that SRF improves the recruitment of and perhaps even directly recruits ELK1.

However, upon ELK1 depletion, we see an increase in SRF binding on many regions (Fig.

49), which may suggest a model by which an SRF co-factor, perhaps another TCF (pointing again to TCF binding/functional redundancy) or MRTF, bind in the absence of ELK1 and

123 increase the affinity of SRF for DNA. An alternate explanation for increase SRF pulldown, could be an increased exposure of the SRF epitope after ELK1 depletion. Though the SRF epitope

(near residue 375) is not near the MADS box, the TCF interaction domain of SRF, a lack of ELK1 could perhaps induce conformational changes (Posern & Treisman, 2006).

In any case, further work will need to be done to establish the co-factors of ELK1 and

SRF in each condition, and the impact of ELK1 and SRF depletion on gene expression. Further studies will likely follow-up the effect on gene expression of ELK1 and SRF depletion during mesoderm differentiation. It may be also be useful to revisit H1-hESC and mesoderm ChIP-seq data, and perform ChIP-qPCR experiments for histones and other ELK1 or SRF co-factors to further flesh out the mechanisms of gene expression.

124

6. Discussion 6.I SUZ12 recruitment One of our initial aims was to determine if ELK1 was able to recruit the PRC2 complex.

ELK1 and two members of the PRC2 complex (EZH2 and SUZ12) co-localized. Demonstrating

PRC2 recruitment by a transcription factor, in this case ELK1, would have been a novel finding.

We did not find a direct interaction between ELK1 and PRC2, nor did we find that ELK1 depletion affects the deposition of methylation on H3K27, the enzymatic product of PRC2. We therefore could conclude that ELK1 is not involved in the recruitment or localization of PRC2.

With a lack of known recruiters or a known genomic consensus sequence, the best guess at the recruitment of the PRC2 complex was that it was recruited by the PRC1 histone modification, DNA CpG methylation or was directed in some manner by lncRNAs (Brockdorff,

2013; Cooper et al., 2014; Gupta et al., 2010; Kotake et al., 2011; Ku et al., 2008; Mendenhall et al., 2010; Pasini et al., 2010; Riising et al., 2014; J. Zhao et al., 2008). However, recent studies have shown that the PRC2 complex interacts with a large number of RNA transcripts, which suggests that gene transcription is one of the main traits of PRC2 localization, and that

PRC2 is perhaps ejected from areas of high expression (Beltran et al., 2016; Berrozpe et al.,

2017). Presumably, as the PRC2 complex maintains cell-type specific gene expression, there is a mechanism by which cell-type specific genes are silenced. This apparent specificity may be more a response to gene activation- and potentially epigenetic states, such as histone modification and DNA methylation- rather than direct recruitment to a specific region of DNA by a repressor.

125

6.II The relationship of ELK1 and STAT Though we could not detect STAT3 with ChIP-qPCR in this study (Fig. 41B), with more time, it might be interesting to determine if any STAT TF binds on or near any other ELK1 binding sites and to identify an appropriate signal to stimulate the chromatin binding of STAT.

With the loci of interest determined, we could then go on to investigate if ELK1 recruits or antagonizes recruitment of STAT or vice versa. A useful model to study this interaction may be the transition from naïve or ground-state stem cells require. This model is supported by a shift from FGF2-supplemented media, which is required for the maintenance of hESC, to media containing LIF and MEKi, which is required for the maintenance of naïve or ground-state stem cells (Fig. 50). As we would be testing a model in which ETS protein and STATs either co- associate or compete for binding regions, this shift in signalling from FGF2 to LIF signalling, may suggest ETS and STAT TFs fulfil the same role in two different cell contexts.

126

Figure 50: ELK1 and STAT3 regulation in Naïve cells and hESC A hypothetical model of ERK1 and STAT3 regulation in A) Naïve/Ground- State/Epiblast cells, whose culture includes combinations of FGFR, BRAF and MAPK inhibitors, and B) hESC cells, whose culture includes FGF2 and does not require JAK/STAT activation. Red lines indicate small molecule inhibition. Black lines indication activation. Dotted line indicated dispensability. Adapted from Chan et al., 2013; Gafni et al., 2015; Guo et al., 2016; Hu et al. , 2009; Schnerch et al., 2010; Takashima et al., 2015; Ware et al., 2014, Dahéron et al., 2004.

127

6.III Establishing an ETS-switch Theoretically, differential ETS-binding could be a combination of differing expression levels of ETS-factors and their co-factors and differing response to stimulation. Similar work has been done in this vein, in the context of haematopoiesis and ETS proteins (Reviewed in

Ciau-Uitz et al., 2013). Theoretically, a study in two or more cells states with a large difference in ETS co-factor expression levels and/or external stimulation (receptors/growth factors), could net interesting results to better understand ETS specificity. We attempted such a study, but our ChIP-seq of ETV1 was unsuccessful. Additionally, the depletion of ELK1 and ETV1 did not decrease expression of pluripotency factors (Fig. 30A, Fig. 51). Therefore, it may be more useful to study ETS factors that are known to be peri-implantation or embryonic lethal or exhibit a large change in expression during differentiation (Fig. 33A) (Bartel et al., 2000).

Recently, Kedage et al. report that ERG, another ETS factors, associates with the PRC2 complex, an association which is abrogated by phosphorylation (Kedage et al., 2017). The ERG binding region that associates with the PRC2 is not shared with ELK1, so this specific interaction is likely not generalizable to the ETS factor family. This report may both suggest that areas of ELK1 and PRC2 co-localization may in fact be an ELK1 partial occupancy site, with a different ETS factor, which does associate with PRC2, occupying the same site at in other conditions or at other times.

n RT-qPCR of Pluripotency Factors

o i 2.0

e r 1.5 * +siNT

x 1.0 E +siETV1

v 0.5

a l 0.0

R H 1 4 C G 1 2 D V F Y O F X P T L 5 O E K M N U S A A O G N P Figure 51: Effect of long term ETV1 depletion on pluripotency expression RT-qPCR measuring the expression of ETV1 and pluripotency after 7 days of siRNA treatment. Gene expression normalized to “+siNT.” Graphs represent the arithmetic mean +/- S.E.M. of 3 independent experiments. * = p-value < 0.05.

128

6.IV The role of ELK1 in pluripotency One of our initial aims was to determine whether or not ELK1 had a repressive role in developmental genes in pluripotent stem cells. To determine this we depleted ELK1 with two different RNAi methods, shELK1 and siELK1.

We saw a decrease in OCT4 and NANOG after 4 days of shELK1 treatment (Fig. 23B).

However, we didn’t see a decrease in any pluripotency factors in the siRNA treatment, at day 4 or at day 7 of treatment (Figs. 30C, Fig. 31A). This could be due to a few factors. One factor that may explain the difference in phenotypes could be the knockout efficiency, or off-target effects. Though we did not repeat the rescue experiment, Göke et al. performed a rescue after knockdown with this shELK1 construct. This suggests that effects of shELK1 treatment on pluripotency aren’t due to off-target effects. After 4 days of shELK1, ELK1 mRNA decreased by

79.5% or 83% (as measured by two different ELK1 RT-qPCR primers) (Fig. 23B). However, the protein knockout was only 47% (Fig. 23A). We do however see a decrease in ELK1 binding in shELK1 treatment, suggesting that, even such a modest protein decrease was measurable with

ChIP (Fig 25A). Conversely, after 4 days of siELK1 treatment, ELK1 mRNA decreased by 60%, which is less than that of shELK1 depletion. However, ELK1 protein levels decreased by 92%

(Fig. 30A+C). In both case, knockdown did result in some detectable changes in gene expression and binding levels, therefore we’re inclined to believe that knockdown is not the source of this discrepancy.

A second factor could be cell culture conditions. Whilst H1-hESC cells cultured in both feeder-cultured media (used for shELK1 treatment) and mTeSR1™ (used for siRNA treatment) express many of the canonical pluripotency factors, stem cells are known to exist as a heterogeneous population (Graf & Stadtfeld, 2008; Habibi & Stunnenberg, 2017; Schnerch et al., 2010; Torres-Padilla & Chambers, 2014). This is apparently borne out by the lower TRA-1-

60 and TRA-1-81 levels in feeder-cultured media compared to mTeSR1™ cultured cells

129

(Hannoun et al., 2010). It could be the case therefore that the two populations are not at the same state of pluripotency or at a state more or less perturbable by ELK1 depletion.

Finally, as ELK1 knockdown is not lethal, and only has limited effects in a mouse knockout (Cesari et al., 2004). We suggest that the interpretation of ELK1 alone as essentially dispensable for pluripotency is likely the correct interpretation. And whilst we do see difference in gene expression during differentiation with siELK1 treatment, it would require further testing to determine whether these differences ultimately affect long-term differentiation or tissue specification.

130

7. Citations Allen, B. L., & Taatjes, D. J. (2015). The Mediator complex: a central integrator of transcription. Nature Reviews Molecular Cell Biology, 16(3), 155–166. https://doi.org/10.1038/nrm3951

Allen, H. F., Wade, P. A., & Kutateladze, T. G. (2013). The NuRD architecture. Cellular and Molecular Life Sciences, 70(19), 3513–3524. https://doi.org/10.1007/s00018-012-1256-2

Amit, M., Carpenter, M. K., Inokuma, M. S., Chiu, C.-P., Harris, C. P., Waknitz, M. A., … Thomson, J. A. (2000). Clonally Derived Human Embryonic Stem Cell Lines Maintain Pluripotency and Proliferative Potential for Prolonged Periods of Culture. Developmental Biology, 227(2), 271–278. https://doi.org/10.1006/dbio.2000.9912

Androutsellis-Theotokis, A., Leker, R. R., Soldner, F., Hoeppner, D. J., Ravin, R., Poser, S. W., … McKay, R. D. G. (2006). Notch signalling regulates stem cell numbers in vitro and in vivo. Nature, 442(7104), 823–826. https://doi.org/10.1038/nature04940

Armstrong, L., Hughes, O., Yung, S., Hyslop, L., Stewart, R., Wappler, I., … Lako, M. (2006). The role of PI3K/AKT, MAPK/ERK and NFκβ signalling in the maintenance of human embryonic stem cell pluripotency and viability highlighted by transcriptional profiling and functional analysis. Human Molecular Genetics, 15(11), 1894–1913. https://doi.org/10.1093/hmg/ddl112

Arvey, A., Agius, P., Noble, W., & Leslie, C. (2012). Sequence and chromatin determinants of cell-type–specific transcription factor binding. Genome Research, 22(9), 1723–1734. https://doi.org/10.1101/gr.127712.111

Bartel, F. O., Higuchi, T., & Spyropoulos, D. D. (2000). Mouse models in the study of the Ets family of transcription factors. Oncogene, 19(55), 6443–6454. https://doi.org/10.1038/sj.onc.1204038

Barth, T. K., & Imhof, A. (2010). Fast signals and slow marks: the dynamics of histone modifications. Trends in Biochemical Sciences, 35(11), 618–26. https://doi.org/10.1016/j.tibs.2010.05.006

Beltran, M., Yates, C. M., Skalska, L., Dawson, M., Reis, F. P., Viiri, K., … Jenner, R. G. (2016). The interaction of PRC2 with RNA or chromatin s mutually antagonistic. Genome Research, 26(7), 896–907. https://doi.org/10.1101/gr.197632.115

Berrozpe, G., Bryant, G. O., Warpinski, K., Spagna, D., Narayan, S., Shah, S., & Ptashne, M. (2017). Polycomb Responds to Low Levels of Transcription. Cell Rep, 20(4), 785–793. https://doi.org/10.1016/j.celrep.2017.06.076

Besnard, A., Galan-Rodriguez, B., Vanhoutte, P., & Caboche, J. (2011). Elk-1 a transcription factor with multiple facets in the brain. Frontiers in Neuroscience, 5(March), 35. https://doi.org/10.3389/fnins.2011.00035

Beuchle, D., Struhl, G., & Müller, J. (2001). Polycomb group proteins and heritable silencing of Drosophila Hox genes. Development (Cambridge, England), 128(6), 993–1004.

Bird, A. (2002). DNA methylation patterns and epigenetic memory. Genes & Development, 16(1), 6–21. https://doi.org/10.1101/gad.947102

Boros, J., O’Donnell, A., Donaldson, I. J., Kasza, A., Zeef, L., & Sharrocks, A. D. (2009). Overlapping promoter targeting by Elk-1 and other divergent ETS-domain transcription

131

factor family members. Nucleic Acids Research, 37(22), 7368–80. https://doi.org/10.1093/nar/gkp804

Borowiak, M., Maehr, R., Chen, S., Chen, A. E., Tang, W., Fox, J. L., … Melton, D. A. (2009). Small Molecules Efficiently Direct Endodermal Differentiation of Mouse and Human Embryonic Stem Cells. Cell Stem Cell, 4(4), 348–358. https://doi.org/10.1016/j.stem.2009.01.014

Boyer, L. A., Tong, I. L., Cole, M. F., Johnstone, S. E., Levine, S. S., Zucker, J. P., … Young, R. A. (2005). Core transcriptional regulatory circuitry in human embryonic stem cells. Cell, 122(6), 947–956. https://doi.org/10.1016/j.cell.2005.08.020

Brockdorff, N. (2013). Noncoding RNA and Polycomb recruitment. RNA, 19(4), 429–42. https://doi.org/10.1261/rna.037598.112

Brookes, E., de Santiago, I., Hebenstreit, D., Morris, K. J., Carroll, T., Xie, S. Q., … Pombo, A. (2012). Polycomb associates genome-wide with a specific RNA polymerase II variant, and regulates metabolic genes in ESCs. Cell Stem Cell, 10(2), 157–70. https://doi.org/10.1016/j.stem.2011.12.017

Bruck, T., Yanuka, O., & Benvenisty, N. (2013). Human pluripotent stem cells with distinct X inactivation status show molecular and cellular differences controlled by the X-Linked ELK-1 gene. Cell Reports, 4(2), 262–70. https://doi.org/10.1016/j.celrep.2013.06.026

Buchwald, G., van der Stoop, P., Weichenrieder, O., Perrakis, A., van Lohuizen, M., & Sixma, T. K. (2006). Structure and E3-ligase activity of the Ring-Ring complex of polycomb proteins Bmi1 and Ring1b. The EMBO Journal, 25(11), 2465–74. https://doi.org/10.1038/sj.emboj.7601144

Buchwalter, G., Gross, C., & Wasylyk, B. (2004). Ets ternary complex transcription factors. Gene, 324, 1–14. https://doi.org/10.1016/j.gene.2003.09.028

Cammarota, M., Bevilaqua, L. R., Ardenghi, P., Paratcha, G., Levi de Stein, M., Izquierdo, I., & Medina, J. H. (2000). Learning-associated activation of nuclear MAPK, CREB and Elk-1, along with Fos production, in the rat hippocampus after a one-trial avoidance learning: abolition by NMDA receptor blockade. Brain Research. Molecular Brain Research, 76(1), 36–46.

Cao, R., Tsukada, Y.-I., & Zhang, Y. (2005). Role of Bmi-1 and Ring1A in H2A ubiquitylation and Hox gene silencing. Molecular Cell, 20(6), 845–54. https://doi.org/10.1016/j.molcel.2005.12.002

Cao, R., & Zhang, Y. (2004a). SUZ12 Is Required for Both the Histone Methyltransferase Activity and the Silencing Function of the EED-EZH2 Complex. Molecular Cell, 15, 57–67.

Cao, R., & Zhang, Y. (2004b). The functions of E(Z)/EZH2-mediated methylation of lysine 27 in histone H3. Current Opinion in Genetics & Development, 14(2), 155–64. https://doi.org/10.1016/j.gde.2004.02.001

Carrère, S., Verger, A., Flourens, A., Stehelin, D., & Duterque-Coquillaud, M. (1998). Erg proteins, transcription factors of the Ets family, form homo, heterodimers and ternary complexes via two distinct domains. Oncogene, 16(25), 3261–8. https://doi.org/10.1038/sj.onc.1201868

Cesari, F., Brecht, S., Vintersten, K., Vuong, L. G., Hofmann, M., Klingel, K., … Nordheim, A. (2004). Mice Deficient for the Ets Transcription Factor Elk-1 Show Normal Immune

132

Responses and Mildly Impaired Neuronal Gene Activation. Molecular and Cellular Biology, 24(1), 294–305. https://doi.org/10.1128/MCB.24.1.294-305.2004

Cesari, F., Rennekampff, V., Vintersten, K., Vuong, L. G., & Seibler, J. (2004). Elk-1 Knock-Out Mice Engineered by Flp Recombinase-Mediated Cassette Exchange, 92, 87–92. https://doi.org/10.1002/gene.20003

Chan, Y. S., Göke, J., Ng, J. H., Lu, X., Gonzales, K. A. U., Tan, C. P., … Ng, H. H. (2013). Induction of a human pluripotent state with distinct regulatory circuitry that resembles preimplantation epiblast. Cell Stem Cell, 13(6), 663–675. https://doi.org/10.1016/j.stem.2013.11.015

Chang, I., & Parrilla, M. (2016). Expression patterns of homeobox genes in the mouse vomeronasal organ at postnatal stages. Gene Expression Patterns, 21(2), 69–80. https://doi.org/10.1016/j.gep.2016.08.001

Chao, S. H., & Price, D. H. (2001). Flavopiridol Inactivates P-TEFb and Blocks Most RNA Polymerase II Transcription in Vivo. Journal of Biological Chemistry, 276(34), 31793– 31799. https://doi.org/10.1074/jbc.M102306200

Chen, D., Toone, W. M., Mata, J., Lyne, R., Burns, G., Kivinen, K., … Jones, N. (2003). Global Transcriptional Responses of Fission Yeast to Environmental Stress. Molecular Biology of the Cell, 14(January), 214–229. https://doi.org/10.1091/mbc.E02

Chi, Y., Huddleston, M. J., Zhang, X., Young, R. a, Annan, R. S., Carr, S. a, & Deshaies, R. J. (2001). Negative regulation of Gcn4 and Msn2 transcription factors by Srb10 cyclin- dependent kinase. Genes & Development, 15(9), 1078–92. https://doi.org/10.1101/gad.867501

Chou, D. M., Adamson, B., Dephoure, N. E., Tan, X., Nottke, A. C., Hurov, K. E., … Elledge, S. J. (2010). A chromatin localization screen reveals poly (ADP ribose)-regulated recruitment of the repressive polycomb and NuRD complexes to sites of DNA damage. Proceedings of the National Academy of Sciences of the United States of America, 107(43), 18475–80. https://doi.org/10.1073/pnas.1012946107

Chu, L.-F., Leng, N., Zhang, J., Hou, Z., Mamott, D., Vereide, D. T., … Thomson, J. A. (2016). Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm. Genome Biology, 17(1), 173. https://doi.org/10.1186/s13059- 016-1033-x

Ciau-Uitz, A., Wang, L., Patient, R., & Liu, F. (2013). ETS transcription factors in hematopoietic stem cell development. Blood Cells, Molecules, and Diseases, 51(4), 248–255. https://doi.org/10.1016/j.bcmd.2013.07.010

Clarkson, R. W., Shang, C. a, Levitt, L. K., Howard, T., & Waters, M. J. (1999). Ternary complex factors Elk-1 and Sap-1a mediate growth hormone-induced transcription of egr-1 (early growth response factor-1) in 3T3-F442A preadipocytes. Molecular Endocrinology, 13(4), 619–31.

Cooper, S., Dienstbier, M., Hassan, R., Schermelleh, L., Sharif, J., Blackledge, N. P., … Brockdorff, N. (2014). Targeting Polycomb to Pericentric Heterochromatin in Embryonic Stem Cells Reveals a Role for H2AK119u1 in PRC2 Recruitment. Cell Reports, 7(5), 1456– 1470. https://doi.org/10.1016/j.celrep.2014.04.012

Costello, P., Nicolas, R., Willoughby, J., Wasylyk, B., Nordheim, A., & Treisman, R. (2010).

133

Ternary complex factors SAP-1 and Elk-1, but not net, are functionally equivalent in thymocyte development. Journal of Immunology (Baltimore, Md. : 1950), 185(2), 1082– 92. https://doi.org/10.4049/jimmunol.1000472

Cruzalegui, F. H., Cano, E., & Treisman, R. (1999). ERK activation induces phosphorylation of Elk-1 at multiple S/T-P motifs to high stoichiometry. Oncogene, 18(56), 7948–57. https://doi.org/10.1038/sj.onc.1203362

Czermin, B., Melfi, R., McCabe, D., Seitz, V., Imhof, A., & Pirrotta, V. (2002). Drosophila enhancer of Zeste/ESC complexes have a histone H3 methyltransferase activity that marks chromosomal Polycomb sites. Cell, 111(2), 185–96.

D’Amour, K. A., Agulnick, A. D., Eliazer, S., Kelly, O. G., Kroon, E., & Baetge, E. E. (2005). Efficient differentiation of human embryonic stem cells to definitive endoderm. Nature Biotechnology, 23(12), 1534–1541. https://doi.org/10.1038/nbt1163

Dahéron, L., Opitz, S. L., Zaehres, H., Lensch, W. M., Andrews, P. W., Itskovitz-Eldor, J., & Daley, G. Q. (2004). LIF/STAT3 Signaling Fails to Maintain Self-Renewal of Human Embryonic Stem Cells. Stem Cells, 22(5), 770–778. https://doi.org/10.1634/stemcells.22-5-770

Dahmus, M. E. (1996). Reversible Phosphorylation of the C-terminal Domain of RNA Polymerase II. Journal of Biological Chemistry, 271, 19009–19012. https://doi.org/10.1074/jbc.271.32.19009

Darst, R. P., Wang, D., & Auble, D. T. (2001). MOT1-catalyzed TBP-DNA disruption: uncoupling DNA conformational change and role of upstream DNA. The EMBO Journal, 20(8), 2028– 40. https://doi.org/10.1093/emboj/20.8.2028

Deng, W., Roberts, S. G. E., Deng, W., & Roberts, S. G. E. (2005). A core promoter element downstream of the TATA box that is recognized by TFIIB service A core promoter element downstream of the TATA box that is recognized by TFIIB, 2418–2423. https://doi.org/10.1101/gad.342405

Dixon, J. R., Jung, I., Selvaraj, S., Shen, Y., Antosiewicz-Bourget, J. E., Lee, A. Y., … Ren, B. (2015). Chromatin architecture reorganization during stem cell differentiation. Nature, 518(7539), 331–336. https://doi.org/10.1038/nature14222

Djebali, S., Davis, C. a., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., … Gingeras, T. R. (2012). Landscape of transcription in human cells. Nature, 489(7414), 101–108. https://doi.org/10.1038/nature11233

Duncan, I. M. (1982). Polycomblike: a gene that appears to be required for the normal expression of the bithorax and antennapedia gene complexes of Drosophila melanogaster. Genetics, 102(1), 49–70.

Dynlacht, B. D., Hoey, T., & Tjian, R. (1991). Isolation of coactivators associates with the TATA- binding protein that mediate transcriptional activation. Cell, 66, 563–576.

Eiselleova, L., Matulka, K., Kriz, V., Kunova, M., Schmidtova, Z., Neradil, J., … Dvorak, P. (2009). A complex role for FGF-2 in self-renewal, survival, and adhesion of human embryonic stem cells. Stem Cells, 27(8), 1847–1857. https://doi.org/10.1002/stem.128

Esnault, C., Stewart, A., Gualdrini, F., East, P., Horswell, S., Matthews, N., & Treisman, R. (2014). Rho-actin signaling to the MRTF coactivators dominates the immediate transcriptional response to serum in fibroblasts. Genes & Development, 28(9), 943–58.

134

https://doi.org/10.1101/gad.239327.114

Esteller, M. (2011). Non-coding RNAs in human disease. Nature Reviews. Genetics, 12(12), 861–74. https://doi.org/10.1038/nrg3074

Fantz, D. a, Jacobs, D., Glossip, D., & Kornfeld, K. (2001). Docking sites on substrate proteins direct extracellular signal-regulated kinase to phosphorylate specific residues. The Journal of Biological Chemistry, 276(29), 27256–65. https://doi.org/10.1074/jbc.M102512200

Fatehullah, A., Tan, S. H., & Barker, N. (2016). Organoids as an in vitro model of human development and disease. Nature Cell Biology, 18(3), 246–254. https://doi.org/10.1038/ncb3312

Fitzsimmons, D., Hodsdon, W., Wheat, W., Maira, S. M., Wasylyk, B., & Hagman, J. (1996). Pax- 5 (BSAP) recruits Ets proto-oncogene family proteins to form functional ternary complexes on a B-cell-specific promoter. Genes & Development, 10(17), 2198–2211. https://doi.org/10.1101/gad.10.17.2198

Fitzsimmons, D., Lukin, K., Lutz, R., Garvie, C. W., Wolberger, C., & Hagman, J. (2009). Highly Cooperative Recruitment of Ets-1 and Release of Autoinhibition by Pax5. Journal of Molecular Biology, 392(2), 452–464. https://doi.org/10.1016/j.jmb.2009.07.028

Francis, N. J., Follmer, N. E., Simon, M. D., Aghia, G., & Butler, J. D. (2009). Polycomb proteins remain bound to chromatin and DNA during DNA replication in vitro. Cell, 137(1), 110–22. https://doi.org/10.1016/j.cell.2009.02.017

Gafni, O., Weinberger, L., Mansour, A. A., Manor, Y. S., Chomsky, E., Ben-Yosef, D., … Hanna, J. H. (2015). Derivation of novel human ground state naive pluripotent stem cells. Nature, 520(7549), 710–710. https://doi.org/10.1038/nature14370

Gagliardi, A., Mullin, N. P., Ying Tan, Z., Colby, D., Kousa, A. I., Halbritter, F., … Chambers, I. (2013). A direct physical interaction between Nanog and Sox2 regulates embryonic stem cell self-renewal. The EMBO Journal, 32(16), 2231–2247. https://doi.org/10.1038/emboj.2013.161

Gao, Z., Zhang, J., Bonasio, R., Strino, F., Sawai, A., Parisi, F., … Reinberg, D. (2012). PCGF homologs, CBX proteins, and RYBP define functionally distinct PRC1 family complexes. Molecular Cell, 45(3), 344–56. https://doi.org/10.1016/j.molcel.2012.01.002

Gaston, K., & Jayaraman, P.-S. (2003). Transcriptional repression in eukaryotes: repressors and repression mechanisms. Cellular and Molecular Life Sciences (CMLS), 60(4), 721–741. https://doi.org/10.1007/s00018-003-2260-3

Gaume, X., & Torres-Padilla, M. E. (2016). Regulation of reprogramming and cellular plasticity through histone exchange and histone variant incorporation. Cold Spring Harbor Symposia on Quantitative Biology, 80, 165–175. https://doi.org/10.1101/sqb.2015.80.027458

Gille, H., Kortenjann, M., Thomae, O., Moomaw, C., Slaughterl, C., Cobb, M. H., & Shaw, P. E. (1995). ERK phosphorylation potentiates Elk-1-mediated ternary complex formation and transactivation. The EMBO Journal, 14(5), 951–962.

Göke, J., Chan, Y., Yan, J., Vingron, M., & Ng, H.-H. (2013). Genome-wide kinase-chromatin interactions reveal the regulatory network of ERK signaling in human embryonic stem cells. Molecular Cell, 50(6), 844–55. https://doi.org/10.1016/j.molcel.2013.04.030

135

Graf, T., & Stadtfeld, M. (2008). Heterogeneity of Embryonic and Adult Stem Cells. Cell Stem Cell, 3(5), 480–483. https://doi.org/10.1016/j.stem.2008.10.007

Green, S. M., Coyne, H. J., McIntosh, L. P., & Graves, B. J. (2010). DNA binding by the ETS protein TEL (ETV6) is regulated by autoinhibition and self-association. Journal of Biological Chemistry, 285(24), 18496–18504. https://doi.org/10.1074/jbc.M109.096958

Grossman, S. R., Zhang, X., Wang, L., Engreitz, J., Melnikov, A., Rogov, P., … Lander, E. S. (2017). Systematic dissection of genomic features determining transcription factor binding and enhancer function. Proceedings of the National Academy of Sciences, 201621150. https://doi.org/10.1073/pnas.1621150114

Grünberg, S., Warfield, L., & Hahn, S. (2012). Architecture of the RNA polymerase II preinitiation complex and mechanism of ATP-dependent promoter opening. Nature Structural & Molecular Biology, 19(8), 788–796. https://doi.org/10.1038/nsmb.2334

Gualdrini, F., Esnault, C., Horswell, S., Stewart, A., Matthews, N., & Treisman, R. (2016). SRF Co- factors Control the Balance between Cell Proliferation and Contractility. Molecular Cell, 64(6), 1048–1061. https://doi.org/10.1016/j.molcel.2016.10.016

Guo, G., Von Meyenn, F., Santos, F., Chen, Y., Reik, W., Bertone, P., … Nichols, J. (2016). Naive Pluripotent Stem Cells Derived Directly from Isolated Cells of the Human Inner Cell Mass. Stem Cell Reports, 6(4), 437–446. https://doi.org/10.1016/j.stemcr.2016.02.005

Gupta, R. a, Shah, N., Wang, K. C., Kim, J., Horlings, H. M., David, J., … Chang, H. Y. (2010). Long noncoding RNA HONTAIR reprograms chromatin state to promote cancer metastasis. Nature, 464(7291), 1071–1076. https://doi.org/10.1038/nature08975.Long

Gupta, R. a, Shah, N., Wang, K. C., Kim, J., Horlings, H. M., Wong, D. J., … Chang, H. Y. (2010). Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature, 464(7291), 1071–6. https://doi.org/10.1038/nature08975

Habibi, E., & Stunnenberg, H. G. (2017). Transcriptional and epigenetic control in mouse pluripotency: lessons from in vivo and in vitro studies. Current Opinion in Genetics & Development, 46, 114–122. https://doi.org/10.1016/j.gde.2017.07.005

Hannoun, Z., Fletcher, J., Greenhough, S., Medine, C., Samuel, K., Sharma, R., … Hay, D. C. (2010). The comparison between conditioned media and serum-free media in human embryonic stem cell culture and differentiation. Cellular Reprogramming, 12(2), 133–140. https://doi.org/10.1089/cell.2009.0099

Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., … Glass, C. K. (2010). Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Molecular Cell, 38(4), 576–89. https://doi.org/10.1016/j.molcel.2010.05.004

Hengartner, C. J., Myer, V. E., Liao, S. M., Wilson, C. J., Koh, S. S., & Young, R. a. (1998). Temporal regulation of RNA polymerase II by Srb10 and Kin28 cyclin-dependent kinases. Molecular Cell, 2(1), 43–53.

Holstege, F. C., van der Vliet, P. C., & Timmers, H. T. (1996). Opening of an RNA polymerase II promoter occurs in two distinct steps and requires the basal transcription factors IIE and IIH. The EMBO Journal, 15(7), 1666–1677.

Hu, B.-Y., Du, Z.-W., Li, X.-J., Ayala, M., & Zhang, S.-C. (2009). Human oligodendrocytes from

136

embryonic stem cells: conserved SHH signaling networks and divergent FGF effects. Development, 136(9), 1443–1452. https://doi.org/10.1242/dev.029447

Hu, B.-Y., Weick, J. P., Yu, J., Ma, L.-X., Zhang, X.-Q., Thomson, J. A., & Zhang, S.-C. (2010). Neural differentiation of human induced pluripotent stem cells follows developmental principles but with variable potency. Proceedings of the National Academy of Sciences, 107(9), 4335–4340. https://doi.org/10.1073/pnas.0910012107

Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2008). Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protocols, 4(1), 44–57.

Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009). Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Research, 37(1), 1–13. https://doi.org/10.1093/nar/gkn923

Huangfu, D., Osafune, K., Maehr, R., Guo, W., Eijkelenboom, A., Chen, S., … Melton, D. A. (2008). Induction of pluripotent stem cells from primary human fibroblasts with only Oct4 and Sox2. Nature Biotechnology, 26(11), 1269–1275. https://doi.org/10.1038/nbt.1502

International Human Genome Sequencing Consortium, & IHGSC. (2004). Finishing the euchromatic sequence of the human genome. Nature, 431(7011), 931–45. https://doi.org/10.1038/nature03001

Janknecht, R., & Nordheim, A. (1992). Elk-1 protein domains required for direct and SRF- assisted DNA-binding. Nucleic Acids Research, 20(13), 3317–3324. https://doi.org/10.1093/nar/20.13.3317

Jaynes, J. B., & Farrell, P. H. O. (1988). Activation and repression of transcription by homoeodomain- containing proteins that bind a common site. Nature, 336(6201), 744– 749. https://doi.org/10.1038/336744a0.Activation

Jonkers, I., & Lis, J. T. (2015). Getting up to speed with transcription elongation by RNA polymerase II. Nature Reviews Molecular Cell Biology, 16(3), 167–177. https://doi.org/10.1038/nrm3953

Kaestner, K. H. (2015). An epigenomic road map for endoderm development. Cell Stem Cell, 16(4), 343–344. https://doi.org/10.1016/j.stem.2015.03.006

Karin, M. (1995). The regulation of AP-1 activity by mitogen-activated protein kinases. Journal of Biological Chemistry, 270(July), 16483–16486.

Kashyap, V., Rezende, N. C., Scotland, K. B., Shaffer, S. M., Persson, J. L., Gudas, L. J., & Mongan, N. P. (2009). Regulation of Stem Cell Pluripotency and Differentiation Involves a Mutual Regulatory Circuit of the Nanog, OCT4, and SOX2 Pluripotency Transcription Factors With Polycomb Repressive Complexes and Stem Cell microRNAs. Stem Cells and Development, 18(7), 1093–1108. https://doi.org/10.1089/scd.2009.0113

Katsumura, K. R., Ong, I. M., DeVilbiss, A. W., Sanalkumar, R., & Bresnick, E. H. (2016). GATA Factor-Dependent Positive-Feedback Circuit in Acute Myeloid Leukemia Cells. Cell Reports, 16(9), 2428–2441. https://doi.org/10.1016/j.celrep.2016.07.058

Kedage, V., Strittmatter, B. G., Dausinas, P. B., & Hollenhorst, P. C. (2017). Phosphorylation of the oncogenic transcription factor ERG in prostate cells dissociates polycomb repressive complex 2 allowing target gene activation. Journal of Biological Chemistry, jbc.M117.796458. https://doi.org/10.1074/jbc.M117.796458

137

Kelly, W. G., Dahmuss, M. E., & Hartll, G. W. (1993). RNA Polymerase I1 Is a Glycoprotein, 268(14), 10416–10424.

Kotake, Y., Nakagawa, T., Kitagawa, K., Suzuki, S., Liu, N., Kitagawa, M., & Xiong, Y. (2011). Long non-coding RNA ANRIL is required for the PRC2 recruitment to and silencing of p15INK4B tumor suppressor gene. Oncogene, 30(16), 1956–1962. https://doi.org/10.1038/onc.2010.568

Ku, M., Koche, R. P., Rheinbay, E., Mendenhall, E. M., Endoh, M., Mikkelsen, T. S., … Bernstein, B. E. (2008). Genomewide analysis of PRC1 and PRC2 occupancy identifies two classes of bivalent domains. PLoS Genetics, 4(10), e1000242. https://doi.org/10.1371/journal.pgen.1000242

Kuzmichev, A., Nishioka, K., Erdjument-Bromage, H., Tempst, P., & Reinberg, D. (2002). Histone methyltransferase activity associated with a human multiprotein complex containing the Enhancer of Zeste protein. Genes & Development, 16(22), 2893–905. https://doi.org/10.1101/gad.1035902

Laflamme, M. A., Chen, K. Y., Naumova, A. V, Muskheli, V., Fugate, J. A., Dupras, S. K., … Murry, C. E. (2007). Cardiomyocytes derived from human embryonic stem cells in pro-survival factors enhance function of infarcted rat hearts. Nature Biotechnology, 25(9), 1015–1024. https://doi.org/10.1038/nbt1327

Lagrange, T., Kapanidis, A. N., Tang, H., Reinberg, D., & Ebright, R. H. (1998). New core promoter element in RNA polymerase II-dependent transcription: Sequence specific DNA binding by transcription factor IIB. Genes \& Dev, 12, 34–44.

Lancaster, M. A., & Knoblich, J. A. (2014). Organogenesis in a dish: Modeling development and disease using organoid technologies. Science, 345(6194), 1247125–1247125. https://doi.org/10.1126/science.1247125

Landeira, D., Sauer, S., Poot, R., Dvorkina, M., Mazzarella, L., Jørgensen, H. F., … Fisher, A. G. (2010). Jarid2 is a PRC2 component in embryonic stem cells required for multi-lineage differentiation and recruitment of PRC1 and RNA Polymerase II to developmental regulators. Nature Cell Biology, 12(6), 618–24. https://doi.org/10.1038/ncb2065

Langelier, M. F., Forget, D., Rojas, A., Porlier, Y., Burton, Z. F., & Coulombe, B. (2001). Structural and Functional Interactions of Transcription Factor (TF) IIA with TFIIE and TFIIF in Transcription Initiation by RNA Polymerase II. Journal of Biological Chemistry, 276(42), 38652–38657. https://doi.org/10.1074/jbc.M106422200

Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods, 9(4), 357–9. https://doi.org/10.1038/nmeth.1923

Lanner, F., & Rossant, J. (2010). The role of FGF/Erk signaling in pluripotent cells. Development, 137(20), 3351–3360. https://doi.org/10.1242/dev.050146

Lee, T. I., Jenner, R. G., Boyer, L. A., Guenther, M. G., Levine, S. S., Kumar, R. M., … Young, R. A. (2006a). Control of Developmental Regulators by Polycomb in Human Embryonic Stem Cells. Cell, 125(2), 301–313. https://doi.org/10.1016/j.cell.2006.02.043

Lee, T. I., Jenner, R. G., Boyer, L. a, Guenther, M. G., Levine, S. S., Kumar, R. M., … Young, R. a. (2006b). Control of developmental regulators by Polycomb in human embryonic stem cells. Cell, 125(2), 301–13. https://doi.org/10.1016/j.cell.2006.02.043

138

Li, B., Carey, M., & Workman, J. L. (2007). The Role of Chromatin during Transcription. Cell, 128(4), 707–719. https://doi.org/10.1016/j.cell.2007.01.015

Li, C., & Manley, J. L. (1998). Even-skipped Represses Transcription by Binding TATA Binding Protein and Blocking the TFIID-TATA Box Interaction Even-skipped Represses Transcription by Binding TATA Binding Protein and Blocking the TFIID-TATA Box Interaction, 18(7).

Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., … Durbin, R. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25(16), 2078–2079. https://doi.org/10.1093/bioinformatics/btp352

Li, J., Wang, G., Wang, C., Zhao, Y., Zhang, H., Tan, Z., … Deng, H. (2007). MEK/ERK signaling contributes to the maintenance of human embryonic stem cell self-renewal. Differentiation, 75(4), 299–307. https://doi.org/10.1111/j.1432-0436.2006.00143.x

Li, Q.-J., Yang, S.-H., Maeda, Y., Sladek, F. M., Sharrocks, A. D., & Martins-Green, M. (2003). MAP kinase phosphorylation-dependent activation of Elk-1 leads to activation of the coactivator p300. The EMBO Journal, 22(2), 281–91. https://doi.org/10.1093/emboj/cdg028

Li, X.-J., Du, Z.-W., Zarnowska, E. D., Pankratz, M., Hansen, L. O., Pearce, R. A., & Zhang, S.-C. (2005). Specification of motoneurons from human embryonic stem cells. Nature Biotechnology, 23(2), 215–221. https://doi.org/10.1038/nbt1063

Lim, C. Y., Santoso, B., Boulay, T., Dong, E., Ohler, U., & Kadonaga, J. T. (2004). The MTE , a new core promoter element for transcription by RNA polymerase II. Genes and Development, 32, 1606–1617. https://doi.org/10.1101/gad.1193404.interactions

Loh, K. M., Chen, A., Koh, P. W., Deng, T. Z., Sinha, R., Tsai, J. M., … Weissman, I. L. (2016). Mapping the Pairwise Choices Leading from Pluripotency to Human Bone, Heart, and Other Mesoderm Cell Types. Cell, 166(2), 451–467. https://doi.org/10.1016/j.cell.2016.06.011

Lyons, P. J., Mattatall, N. R., & Ro, H. (2006). Modeling and Functional Analysis of AEBP1 , a Transcriptional Repressor, 1083(December 2005), 1069–1083. https://doi.org/10.1002/prot

Magnani, L., Eeckhoute, J., & Lupien, M. (2011). Pioneer factors: Directing transcriptional regulators within the chromatin environment. Trends in Genetics, 27(11), 465–474. https://doi.org/10.1016/j.tig.2011.07.002

Mansukhani, A., Ambrosetti, D., Holmes, G., Cornivelli, L., & Basilico, C. (2005). Sox2 induction by FGF and FGFR2 activating mutations inhibits Wnt signaling and osteoblast differentiation. Journal of Cell Biology, 168(7), 1065–1076. https://doi.org/10.1083/jcb.200409182

Marais, R., Wynne, J., & Treisman, R. (1993). The SRF Accessory Protein Elk-l Contains a Growth Factor-Regulated Transcriptional Activation Domain. Cell, 73(April), 391–393.

Margueron, R., Justin, N., Ohno, K., Sharpe, M. L., Son, J., Drury III, W. J., … Gamblin, S. J. (2009). Role of the polycomb protein EED in the propagation of repressive histone marks. Nature, 461(7265), 762–767. https://doi.org/10.1038/nature08398

Mendenhall, E. M., Koche, R. P., Truong, T., Zhou, V. W., Issac, B., Chi, A. S., … Bernstein, B. E. (2010). GC-rich sequence elements recruit PRC2 in mammalian ES cells. PLoS Genetics,

139

6(12), 1–10. https://doi.org/10.1371/journal.pgen.1001244

Miano, J. M. (2003). Serum response factor: toggling between disparate programs of gene expression. Journal of Molecular and Cellular Cardiology, 35(6), 577–593. https://doi.org/10.1016/S0022-2828(03)00110-X

Mohammed, H., D’Santos, C., Serandour, A. a, Ali, H. R., Brown, G. D., Atkins, A., … Carroll, J. S. (2013). Endogenous purification reveals GREB1 as a key estrogen receptor regulatory factor. Cell Reports, 3(2), 342–9. https://doi.org/10.1016/j.celrep.2013.01.010

Moon, K. J., Mochizuki, K., Zhou, M., Jeong, H. S., Brady, J. N., & Ozato, K. (2005). The bromodomain protein Brd4 is a positive regulatory component of P-TEFb and stimulates RNA polymerase II-dependent transcription. Molecular Cell, 19(4), 523–534. https://doi.org/10.1016/j.molcel.2005.06.027

Morales, D., & Hatten, M. E. (2006). Molecular markers of neuronal progenitors in the embryonic cerebellar anlage. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 26(47), 12226–12236. https://doi.org/10.1523/JNEUROSCI.3493-06.2006

Moss, T. (2004). At the crossroads of growth control; making ribosomal RNA. Current Opinion in Genetics & Development, 14(2), 210–217. https://doi.org/10.1016/j.gde.2004.02.005

Müller, J., Hart, C. M., Francis, N. J., Vargas, M. L., Sengupta, A., Wild, B., … Simon, J. a. (2002). Histone methyltransferase activity of a Drosophila Polycomb group repressor complex. Cell, 111(2), 197–208.

Müller, J., & Kassis, J. a. (2006). Polycomb response elements and targeting of Polycomb group proteins in Drosophila. Current Opinion in Genetics & Development, 16(5), 476–84. https://doi.org/10.1016/j.gde.2006.08.005

Mylona, A., Theillet, F.-X., Foster, C., Cheng, T. M., Miralles, F., Bates, P. A., … Treisman, R. (2016). Opposing effects of Elk-1 multisite phosphorylation shape its response to ERK activation. Science, 354(6309), 233–237. https://doi.org/10.1126/science.aad1872

Nerlov, C., Querfurth, E., Kulessa, H., & Graf, T. (2000). GATA-1 interacts with the myeloid PU.1 transcription factor and represses PU.1-dependent transcription. Blood, 95(8), 2543–51.

Nissen, L. J., Gelly, J. C., & Hipskind, R. a. (2001). Induction-independent recruitment of CREB- binding protein to the c-fos serum response element through interactions between the bromodomain and Elk-1. The Journal of Biological Chemistry, 276(7), 5213–21. https://doi.org/10.1074/jbc.M007824200

Odorico, J. S., Kaufman, D. S., & Thomson, J. A. (2001). Multilineage Differentiation from Human Embryonic Stem Cell Lines. Stem Cells, 19(3), 193–204. https://doi.org/10.1634/stemcells.19-3-193

Odrowaz, Z., & Sharrocks, A. D. (2012a). ELK1 uses different DNA binding modes to regulate functionally distinct classes of target genes. PLoS Genetics, 8(5), e1002694. https://doi.org/10.1371/journal.pgen.1002694

Odrowaz, Z., & Sharrocks, A. D. (2012b). The ETS Transcription Factors ELK1 and GABPA Regulate Different Gene Networks to Control MCF10A Breast Epithelial Cell Migration. PloS One, 7(12), 1–9. https://doi.org/10.1371/journal.pone.0049892

140

Oldershaw, R. A., Baxter, M. A., Lowe, E. T., Bates, N., Grady, L. M., Soncin, F., … Kimber, S. J. (2010). Directed differentiation of human embryonic stem cells toward chondrocytes. Nature Biotechnology, 28(11), 1187–1194. https://doi.org/10.1038/nbt.1683

Pankratz, M. T., Li, X.-J., LaVaute, T. M., Lyons, E. A., Chen, X., & Zhang, S.-C. (2007). Directed Neural Differentiation of Human Embryonic Stem Cells via an Obligated Primitive Anterior Stage. Stem Cells, 25(6), 1511–1520. https://doi.org/10.1634/stemcells.2006-0707

Papoutsopoulou, S., & Janknecht, R. (2000). Phosphorylation of ETS transcription factor ER81 in a complex with its coactivators CREB-binding protein and p300. Molecular and Cellular Biology, 20(19), 7300–7310. https://doi.org/10.1128/MCB.20.19.7300-7310.2000

Pasini, D., Bracken, A. P., Hansen, J. B., Capillo, M., & Helin, K. (2007). The polycomb group protein Suz12 is required for embryonic stem cell differentiation. Molecular and Cellular Biology, 27(10), 3769–79. https://doi.org/10.1128/MCB.01432-06

Pasini, D., Cloos, P. a C., Walfridsson, J., Olsson, L., Bukowski, J.-P., Johansen, J. V, … Helin, K. (2010). JARID2 regulates binding of the Polycomb repressive complex 2 to target genes in ES cells. Nature, 464(7286), 306–10. https://doi.org/10.1038/nature08788

Pera, M. F., & Tam, P. P. L. (2010). Extrinsic regulation of pluripotent stem cells. Nature, 465(7299), 713–720. https://doi.org/10.1038/nature09228

Perrier, A. L., Tabar, V., Barberi, T., Rubio, M. E., Bruses, J., Topf, N., … Studer, L. (2004). Derivation of midbrain dopamine neurons from human embryonic stem cells. Proceedings of the National Academy of Sciences, 101(34), 12543–12548. https://doi.org/10.1073/pnas.0404700101

Peterson, C. L., & Workman, J. L. (2000). Promoter targeting and chromatin remodeling by the SWI/SNF complex. Current Opinion in Genetics & Development, 10(2), 187–192. https://doi.org/10.1016/S0959-437X(00)00068-X

Posern, G., & Treisman, R. (2006). Actin’ together: serum response factor, its cofactors and the link to signal transduction. Trends in Cell Biology, 16(11), 588–596. https://doi.org/10.1016/j.tcb.2006.09.008

Poss, Z. C., Ebmeier, C. C., & Taatjes, D. J. (2013). The Mediator complex and transcription regulation. Critical Reviews in Biochemistry and Molecular Biology, 48(6), 575–608. https://doi.org/10.3109/10409238.2013.840259

Price, M. A., Rogers, A. E., & Treisman, R. (1995). Comparative analysis of the ternary complex factors. The EMBO Journal, 14(11), 2589–2601.

Purnell, B. A., Emanuel, P. A., & Gilmour, D. S. (1994). TFIID sequence recognition of the initiator and sequences farther downstream in Drosophila class II genes. Genes and Development, 8(7), 830–842. https://doi.org/10.1101/gad.8.7.830

Qi, M., & Elion, E. a. (2005). MAP kinase pathways. Journal of Cell Science, 118(Pt 16), 3569–72. https://doi.org/10.1242/jcs.02470

Quinlan, A. R., & Hall, I. M. (2010). BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics (Oxford, England), 26(6), 841–2. https://doi.org/10.1093/bioinformatics/btq033

Rao, J., & Greber, B. (2017). Concise Review: Signaling Control of Early Fate Decisions Around

141

the Human Pluripotent Stem Cell State. STEM CELLS, 35(2), 277–283. https://doi.org/10.1002/stem.2527

Rao, V. N., & Reddy, E. S. P. (1993). ∆elk-1, a Variant of Elk-1 , Fails to Interact with the Serum Response Factor and Binds to DNA with Modulated Specificity. Cancer Cell, 53(January), 215–220.

Reese, K. J., Lin, S., Verona, R. I., Schultz, R. M., & Bartolomei, M. S. (2007). Maintenance of paternal methylation and repression of the imprinted H19 gene requires MBD3. PLoS Genetics, 3(8), e137. https://doi.org/10.1371/journal.pgen.0030137

Reubinoff, B. E., Pera, M. F., Fong, C. Y., Trounson, A., & Bongso, A. (2000). Embryonic stem cell lines from human blastocysts: somatic differentiation in vitro. Nature Biotechnol., 18(4), 399–404.

Richmond, T. J., & Davey, C. a. (2003). The structure of DNA in the nucleosome core. Nature, 423(6936), 145–50. https://doi.org/10.1038/nature01595

Riising, E. M., Comet, I., Leblanc, B., Wu, X., Johansen, J. V., & Helin, K. (2014). Gene silencing triggers polycomb repressive complex 2 recruitment to CpG Islands genome wide. Molecular Cell, 55(3), 347–360. https://doi.org/10.1016/j.molcel.2014.06.005

Robinson, M. J., Stippec, S. a, Goldsmith, E., White, M. a, & Cobb, M. H. (1998). A constitutively active and nuclear form of the MAP kinase ERK2 is sufficient for neurite outgrowth and cell transformation. Current Biology : CB, 8(21), 1141–50.

Rojo, F. (2001). Mechanisms of transcriptional repression. Current Opinion in Microbiology, 4, 145–151.

Román-Trufero, M., Méndez-Gómez, H. R., Pérez, C., Hijikata, A., Fujimura, Y., Endo, T., … Vidal, M. (2009). Maintenance of undifferentiated state and self-renewal of embryonic neural stem cells by Polycomb protein Ring1B. Stem Cells (Dayton, Ohio), 27(7), 1559–70. https://doi.org/10.1002/stem.82

Roy, N. S., Cleren, C., Singh, S. K., Yang, L., Beal, M. F., & Goldman, S. A. (2006). Functional engraftment of human ES cell–derived dopaminergic neurons enriched by coculture with telomerase-immortalized midbrain astrocytes. Nature Medicine, 12(11), 1259–1268. https://doi.org/10.1038/nm1495

Sainsbury, S., Bernecky, C., & Cramer, P. (2015). Structural basis of transcription initiation by RNA polymerase II. Nature Reviews Molecular Cell Biology, 16(3), 129–143. https://doi.org/10.1038/nrm3952

Salinas, S., Briançon-Marjollet, A., Bossis, G., Lopez, M., Piechaczyk, M., Jariel-Encontre, I., … Hipskind, R. a. (2004). SUMOylation regulates nucleo-cytoplasmic shuttling of Elk-1. The Journal of Cell Biology, 165(6), 767–73. https://doi.org/10.1083/jcb.200310136

Sato, N., Meijer, L., Skaltsounis, L., Greengard, P., & Brivanlou, A. H. (2004). Maintenance of pluripotency in human and mouse embryonic stem cells through activation of Wnt signaling by a pharmacological GSK-3-specific inhibitor. Nature Medicine, 10(1), 55–63. https://doi.org/10.1038/nm979

Schnerch, A., Cerdan, C., & Bhatia, M. (2010). Distinguishing between mouse and human pluripotent stem cell regulation: The best laid plans of mice and men. Stem Cells, 28(3), 419–430. https://doi.org/10.1002/stem.298

142

Schuettengruber, B., & Cavalli, G. (2009). Recruitment of polycomb group complexes and their role in the dynamic regulation of cell fate choice. Development (Cambridge, England), 136(21), 3531–42. https://doi.org/10.1242/dev.033902

Selcher, J. C. (1999). A Necessity for MAP Kinase Activation in Mammalian Spatial Learning. Learning & Memory, 6(5), 478–490. https://doi.org/10.1101/lm.6.5.478

Selvaraj, N., Kedage, V., & Hollenhorst, P. C. (2015). Comparison of MAPK specificity across the ETS transcription factor family identifies a high-affinity ERK interaction required for ERG function in prostate cells. Cell Communication and Signaling : CCS, 13(1), 12. https://doi.org/10.1186/s12964-015-0089-7

Shain, A. H., & Pollack, J. R. (2013). The Spectrum of SWI/SNF Mutations, Ubiquitous in Human Cancers. PLoS ONE, 8(1). https://doi.org/10.1371/journal.pone.0055119

Sharrocks, A. D. (2001). The ETS-domain transcription factor family. Nature Reviews. Molecular Cell Biology, 2(11), 827–37. https://doi.org/10.1038/35099076

Sharrocks, A. D., Yang, S. H., & Galanis, A. (2000). Docking domains and substrate-specificity determination for MAP kinases. Trends in Biochemical Sciences, 25(9), 448–53.

Shen, X., Liu, Y., Hsu, Y.-J., Fujiwara, Y., Kim, J., Mao, X., … Orkin, S. H. (2008). EZH1 mediates methylation on histone H3 lysine 27 and complements EZH2 in maintaining stem cell identity and executing pluripotency. Molecular Cell, 32(4), 491–502. https://doi.org/10.1016/j.molcel.2008.10.016

Shore, P., & Sharrocks, A. D. (1994). The transcription factors Elk-1 and serum response factor interact by direct protein-protein contacts mediated by a short region of Elk-1. Molecular and Cellular Biology, 14(5), 3283–3291. https://doi.org/10.1128/MCB.14.5.3283

Sieweke, M. H., Tekotte, H., Jarosch, U., & Graf, T. (1998). Cooperative interaction of ets-1 with USF-1 required for HIV-1 enhancer activity in T cells. The EMBO Journal, 17(6), 1728–39. https://doi.org/10.1093/emboj/17.6.1728

Sisk, T. J., Gourley, T., Roys, S., & Chang, C. H. (2000). MHC class II transactivator inhibits IL-4 gene transcription by competing with NF-AT to bind the coactivator CREB binding protein (CBP)/p300. Journal of Immunology (Baltimore, Md. : 1950), 165(5), 2511–7.

Struhl, K. (1998). Histone acetylation and transcriptional regulatory mechanisms. Genes & Development, 12, 599–606.

Sullivan, B. a, & Karpen, G. H. (2004). Centromeric chromatin exhibits a histone modification pattern that is distinct from both euchromatin and heterochromatin. Nature Structural & Molecular Biology, 11(11), 1076–83. https://doi.org/10.1038/nsmb845

Sun, Y., & Ding, Q. (2017). Genome engineering of stem cell organoids for disease modeling. Protein and Cell, 8(5), 315–327. https://doi.org/10.1007/s13238-016-0368-0

Sun, Z., Zhang, S., Chan, J. Y., & Zhang, D. D. (2007). Keap1 controls postinduction repression of the Nrf2-mediated antioxidant response by escorting nuclear export of Nrf2. Molecular and Cellular Biology, 27(18), 6334–49. https://doi.org/10.1128/MCB.00630-07

Takahashi, K., Tanabe, K., Ohnuki, M., Narita, M., Ichisaka, T., Tomoda, K., & Yamanaka, S. (2007). Induction of Pluripotent Stem Cells from Adult Human Fibroblasts by Defined Factors. Cell, 131(5), 861–872. https://doi.org/10.1016/j.cell.2007.11.019

143

Takashima, Y., Guo, G., Loos, R., Nichols, J., Ficz, G., Krueger, F., … Smith, A. (2015). Resetting Transcription Factor Control Circuitry toward Ground-State Pluripotency in Human. Cell, 162(2), 452–453. https://doi.org/10.1016/j.cell.2015.06.052

Takeuchi, H., Nakatsuji, N., & Suemori, H. (2014). Endodermal differentiation of human pluripotent stem cells to insulin-producing cells in 3D culture. Scientific Reports, 4, 1–9. https://doi.org/10.1038/srep04488

Tee, W.-W., Shen, S. S., Oksuz, O., Narendra, V., & Reinberg, D. (2014). Erk1/2 Activity Promotes Chromatin Features and RNAPII Phosphorylation at Developmental Promoters in Mouse ESCs. Cell, 156(4), 678–690. https://doi.org/10.1016/j.cell.2014.01.009

Tenhunen, O., Sármán, B., Kerkelä, R., Szokodi, I., Papp, L., Tóth, M., & Ruskoaho, H. (2004). Mitogen-activated protein kinases p38 and ERK 1/2 mediate the wall stress-induced activation of GATA-4 binding in adult heart. Journal of Biological Chemistry, 279(23), 24852–24860. https://doi.org/10.1074/jbc.M314317200

Thomson, J. A., Itskovitz-eldor, J., Shapiro, S. S., Waknitz, M. A., Swiergiel, J. J., Marshall, V. S., & Jones, J. M. (2007). Embryonic Stem Cell Lines Derived from Human Blastocysts. Science, 1145(1998), 1145–1148. https://doi.org/10.1126/science.282.5391.1145

Torres-Padilla, M.-E., & Chambers, I. (2014). Transcription factor heterogeneity in pluripotent stem cells: a stochastic advantage. Development, 141(11), 2173–2181. https://doi.org/10.1242/dev.102624

Townsend, K. J., Trusty, J. L., Traupman, M. A., Eastman, A., & Craig, R. W. (1998). Expression of the antiapoptotic MCL1 gene product is regulated by a mitogen activated protein kinase- mediated pathway triggered through microtubule disruption and protein kinase C. Oncogene, 17(10), 1223–34. https://doi.org/10.1038/sj.onc.1202035

Townsend, K. J., Zhou, P., Qian, L., Bieszczad, C. K., Lowrey, C. H., Yen, A., & Craig, R. W. (1999). Regulation of MCL1 through a Serum Response Factor/Elk-1-mediated Mechanism Links Expression of a Viability-promoting Member of the BCL2 Family to the Induction of Hematopoietic Cell Differentiation. Journal of Biological Chemistry, 274(3), 1801–1813. https://doi.org/10.1074/jbc.274.3.1801

Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D. R., … Pachter, L. (2013). Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature Protocols, 7(3), 562–578. https://doi.org/10.1038/nprot.2012.016.Differential

Treisman, R., Marais, R., & Wynne, J. (1992). Spatial flexibility in ternary complexes between SRF and its accessory proteins. The EMBO Journal, 11(12), 4631–40.

Vallier, L., Alexander, M., & Pedersen, R. a. (2005). Activin/Nodal and FGF pathways cooperate to maintain pluripotency of human embryonic stem cells. Journal of Cell Science, 118(Pt 19), 4495–509. https://doi.org/10.1242/jcs.02553

Vanhoutte, P., Nissen, J. L., Brugg, B., Gaspera, B. D., Besson, M. J., Hipskind, R. a, & Caboche, J. (2001). Opposing roles of Elk-1 and its brain-specific isoform, short Elk-1, in nerve growth factor-induced PC12 differentiation. The Journal of Biological Chemistry, 276(7), 5189–96. https://doi.org/10.1074/jbc.M006678200

Verma, I. M., Stevenson, J. K., Schwarz, E. M., Van Antwerp, D., & Miyamoto, S. (1995). Rel/NF- kappa B/I kappa B family: intimate tales of association and dissociation. Genes &

144

Development, 9(22), 2723–2735. https://doi.org/10.1101/gad.9.22.2723

Vincenz, C., & Kerppola, T. K. (2008). Different polycomb group CBX family proteins associate with distinct regions of chromatin using nonhomologous protein sequences. Proceedings of the National Academy of Sciences of the United States of America, 105(43), 16572–7. https://doi.org/10.1073/pnas.0805317105

Viré, E., Brenner, C., Deplus, R., Blanchon, L., Fraga, M., Didelot, C., … Fuks, F. (2006). The Polycomb group protein EZH2 directly controls DNA methylation. Nature, 439(7078), 871–4. https://doi.org/10.1038/nature04431

Vossler, M. R., Yao, H., York, R. D., Pan, M. G., Rim, C. S., & Stork, P. J. (1997). cAMP activates MAP kinase and Elk-1 through a B-Raf- and Rap1-dependent pathway. Cell, 89(1), 73–82.

Wang, H., Wang, L., Erdjument-Bromage, H., Vidal, M., Tempst, P., Jones, R. S., & Zhang, Y. (2004). Role of histone H2A ubiquitination in Polycomb silencing. Nature, 431(7010), 873–878.

Wang, L., Li, L., Menendez, P., Cerdan, C., Bhatia, M., & Dc, W. (2010). Human embryonic stem cells maintained in the absence of mouse embryonic fibroblasts or conditioned media are capable of hematopoietic development Human embryonic stem cells maintained in the absence of mouse embryonic fibroblasts or conditioned media are . Development, 105(12), 4598–4603. https://doi.org/10.1182/blood-2004-10-4065

Wang, L., Xu, X., Cao, Y., Li, Z., Cheng, H., Zhu, G., … Chen, Y.-G. (2017). Activin/Smad2-induced Histone H3 Lys-27 Trimethylation (H3K27me3) Reduction Is Crucial to Initiate Mesendoderm Differentiation of Human Embryonic Stem Cells. Journal of Biological Chemistry, 292(4), 1339–1350. https://doi.org/10.1074/jbc.M116.766949

Wang, Z., Oron, E., Nelson, B., Razis, S., & Ivanova, N. (2012). Distinct lineage specification roles for NANOG, OCT4, and SOX2 in human embryonic stem cells. Cell Stem Cell, 10(4), 440– 454. https://doi.org/10.1016/j.stem.2012.02.016

Wang, Z., Wang, D., Hockemeyer, D., Mcanally, J., Nordheim, A., & Olson, E. N. (2004). Myocardin and ternary complex factors compete for SRF to control smooth muscle gene expression. Nature, 428(March), 185–189. https://doi.org/10.1038/nature02331.1.

Ware, C. B., Nelson, A. M., Mecham, B., Hesson, J., Zhou, W., Jonlin, E. C., … Ruohola-Baker, H. (2014). Derivation of naive human embryonic stem cells. Proceedings of the National Academy of Sciences, 111(12), 4484–4489. https://doi.org/10.1073/pnas.1319738111

Wei, G.-H., Badis, G., Berger, M. F., Kivioja, T., Palin, K., Enge, M., … Taipale, J. (2010). Genome- wide analysis of ETS-family DNA-binding in vitro and in vivo. The EMBO Journal, 29(13), 2147–60. https://doi.org/10.1038/emboj.2010.106

Weirauch, M. T., Yang, A., Albu, M., Cote, A. G., Montenegro-Montero, A., Drewe, P., … Hughes, T. R. (2014). Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity. Cell, 158(6), 1431–1443. https://doi.org/10.1016/j.cell.2014.08.009

White, R. J. (2011). Transcription by RNA polymerase III: more complex than we thought. Nature Reviews Genetics, 12(7), 459–463. https://doi.org/10.1038/nrg3001

Whitmarsh, A. J. (2007). Regulation of gene transcription by mitogen-activated protein kinase signaling pathways. Biochimica et Biophysica Acta, 1773(8), 1285–98. https://doi.org/10.1016/j.bbamcr.2006.11.011

145

Xie, W., Schultz, M. D., Lister, R., Hou, Z., Rajagopal, N., Ray, P., … Ren, B. (2013). Epigenomic analysis of multilineage differentiation of human embryonic stem cells. Cell, 153(5), 1134–48. https://doi.org/10.1016/j.cell.2013.04.022

Xu, R. H., Sampsell-Barron, T. L., Gu, F., Root, S., Peck, R. M., Pan, G., … Thomson, J. A. (2008). NANOG Is a Direct Target of TGFβ/Activin-Mediated SMAD Signaling in Human ESCs. Cell Stem Cell, 3(2), 196–206. https://doi.org/10.1016/j.stem.2008.07.001

Yamanaka, S., & Blau, H. M. (2010). Nuclear reprogramming to a pluripotent state by three approaches. Nature, 465(7299), 704–12. https://doi.org/10.1038/nature09229

Yamazaki, Y., Kubota, H., Nozaki, M., & Nagata, K. (2003). Transcriptional regulation of the cytosolic chaperonin theta subunit gene, Cctq, by Ets domain transcription factors Elk-1, Sap-1a, and Net in the absence of serum response factor. The Journal of Biological Chemistry, 278(33), 30642–51. https://doi.org/10.1074/jbc.M212242200

Yang-Yen, H. F., Chambard, J. C., Sun, Y. L., Smeal, T., Schmidt, T. J., Drouin, J., & Karin, M. (1990). Transcriptional interference between c-Jun and the glucocorticoid receptor: mutual inhibition of DNA binding due to direct protein-protein interaction. Cell, 62(6), 1205–15.

Yang, S.-H., Jaffray, E., Hay, R. T., & Sharrocks, A. D. (2003). Dynamic Interplay of the SUMO and ERK Pathways in Regulating Elk-1 Transcriptional Activity. Molecular Cell, 12, 63–74.

Yang, S.-H., & Sharrocks, A. D. (2004). SUMO Promotes HDAC-Mediated Transcriptional Repression, 13, 611–617.

Yang, S.-H., & Sharrocks, A. D. (2005). PIASx acts as an Elk-1 coactivator by facilitating derepression. The EMBO Journal, 24(12), 2161–2171. https://doi.org/10.1038/sj.emboj.7600690

Yang, S.-H., & Sharrocks, A. D. (2006a). Convergence of the SUMO and MAPK pathways on the ETS-domain transcription factor Elk-1. Biochemical Society Symposium, 73, 121–129.

Yang, S.-H., & Sharrocks, A. D. (2006b). PIASxalpha differentially regulates the amplitudes of transcriptional responses following activation of the ERK and p38 MAPK pathways. Molecular Cell, 22(4), 477–87. https://doi.org/10.1016/j.molcel.2006.03.037

Yang, S. H., Shore, P., Willingham, N., Lakey, J. H., & Sharrocks, A. D. (1999). The mechanism of phosphorylation-inducible activation of the ETS-domain transcription factor Elk-1. The EMBO Journal, 18(20), 5666–74. https://doi.org/10.1093/emboj/18.20.5666

Yang, S. H., Vickers, E., Brehm, A., Kouzarides, T., & Sharrocks, A. D. (2001). Temporal recruitment of the mSin3A-histone deacetylase corepressor complex to the ETS domain transcription factor Elk-1. Molecular and Cellular Biology, 21(8), 2802–14. https://doi.org/10.1128/MCB.21.8.2802-2814.2001

Yang, X., Zhang, F., & Kudlow, J. E. (2002). Recruitment of O-GlcNAc transferase to promoters by corepressor mSin3A: coupling protein O-GlcNAcylation to transcriptional repression. Cell, 110(1), 69–80.

Yoshida, T., Gan, Q., & Owens, G. K. (2008). Kruppel-like factor 4, Elk-1, and histone deacetylases cooperatively suppress smooth muscle cell differentiation markers in response to oxidized phospholipids. American Journal of Physiology. Cell Physiology, 295(5), C1175-82. https://doi.org/10.1152/ajpcell.00288.2008

146

Yu, M., Mazor, T., Huang, H., Huang, H.-T., Kathrein, K. L., Woo, A. J., … Cantor, A. B. (2012). Direct recruitment of polycomb repressive complex 1 to chromatin by core binding transcription factors. Molecular Cell, 45(3), 330–43. https://doi.org/10.1016/j.molcel.2011.11.032

Yu, P., Pan, G., Yu, J., & Thomson, J. A. (2011). FGF2 sustains NANOG and switches the outcome of BMP4-induced human embryonic stem cell differentiation. Cell Stem Cell, 8(3), 326– 334. https://doi.org/10.1016/j.stem.2011.01.001

Yu, Y., Deng, P., Yu, B., Szymanski, J. M., Aghaloo, T., Hong, C., & Wang, C.-Y. (2017). Inhibition of EZH2 Promotes Human Embryonic Stem Cell Differentiation into Mesoderm by Reducing H3K27me3. Stem Cell Reports, 8(0), 326–334. https://doi.org/10.1016/j.stemcr.2017.07.016

Yuan, G.-C. (2012). Linking genome to epigenome. Wiley Interdisciplinary Reviews. Systems Biology and Medicine, 4(June). https://doi.org/10.1002/wsbm.1165

Zhang, S.-C., Wernig, M., Duncan, I. D., Brüstle, O., & Thomson, J. A. (2001). In vitro differentiation of transplantable neural precursors from human embryonic stem cells. Nature Biotechnology, 19(12), 1129–1133. https://doi.org/10.1038/nbt1201-1129

Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., … Liu, X. S. (2008). Model-based analysis of ChIP-Seq (MACS). Genome Biology, 9(9), R137. https://doi.org/10.1186/gb-2008-9-9-r137

Zhang, Y., Ng, H., Erdjument-Bromage, H., Tempst, P., Bird, A., & Reinberg, D. (1999). Analysis of the NuRD subunits reveals a histone deacetylase core complex and a connection with DNA methylation. Genes & …, 13, 1924–1935.

Zhang, Y., Sun, Z. W., Iratni, R., Erdjument-Bromage, H., Tempst, P., Hampsey, M., & Reinberg, D. (1998). SAP30, a novel protein conserved between human and yeast, is a component of a histone deacetylase complex. Molecular Cell, 1(7), 1021–31.

Zhao, J., Sun, B. K., Erwin, J. a, Song, J.-J., & Lee, J. T. (2008). Polycomb proteins targeted by a short repeat RNA to the mouse X chromosome. Science (New York, N.Y.), 322(5902), 750– 6. https://doi.org/10.1126/science.1163045

Zhao, Y. (1995). TATA-binding Protein Residues Implicated in a Functional Interplay between Negative Cofactor NC2 (Dr1) and General Factors TFIIA and TFIIB. Journal of Biological Chemistry, 270(18), 10976–10981. https://doi.org/10.1074/jbc.270.18.10976

Ziller, M. J., Edri, R., Yaffe, Y., Donaghey, J., Pop, R., Mallard, W., … Meissner, A. (2014). Dissecting neural differentiation regulatory networks through epigenetic footprinting. Nature, 518(7539), 355–359. https://doi.org/10.1038/nature13990

147