Carcinogenesis is a complex process tightly regulated at multiple levels by post-translational modifications. Epigenetics plays a major role in cancer development, all stable changes to the gene expression process that are not a result of a direct change in the DNA code are described as epigenetics. Epigenetic processes are regulated by post-translational modifications including ubiquitination which can directly affect either histones or transcription factors or may target their co-factors and interacting partners exerting an indirect effect. Deubiquitination of these target proteins is equally important and alterations in this pathway can also lead to cancer development, progression and metastasis. Only the correct, unaltered balance between ubiquitination and deubiquitination ensures healthy cellular homeostasis. In this review we focus on the role of deubiquitinating (DUB) enzymes in various aspects of epigenetics including the regulation of transcription factors, histone modifications, DNA damage repair pathways and cell cycle regulation. We discuss the impact of those processes on tumourigenesis and potential therapeutic applications of DUBs for cancer treatment. Ubiquitination is one of the most important post-translation modifications (PTMs) responsible for regulating the stability and activity of modified proteins. For the ubiquitin molecule to be attached to its target protein it initially has to be activated by an E1 enzyme during an ATP-dependent reaction, which is followed by conjugation of ubiquitin by an E2 class enzyme allowing E3 ubiquitin ligase to ubiquitinate target proteins directly or indirectly , MD, MD9], MAll stable, long-term alterations to the transcriptional potential of the cells that are not caused by direct changes to the DNA sequence itself and can be passed to daughter cells are referred to as epigenetics. These changes include DNA methylation, histone modifications and alterations to the activity of repressors and transcription factors. All of these processes result in altered transcriptome and affect cellular growth, survival and homeostasis; as such epigenetics play a crucial role in cancer development and progression . DUBs caGene expression is controlled by transcription factors that directly bind to DNA. Transcription factors act in complexes with other proteins and DUBs can affect their activity by deubiquitinating transcription factors directly or by targeting their binding partners and altering the stoichiometry of the complex. Usp12 activity towards the androgen receptor (AR) is an example of direct transcription factor deubiquitination . SimilarSometimes it is not clear if DUBs control transcription factors via direct deubiquitination or if their regulation of the transcriptome is more via effects exerted on histones that cause a signalling cascade affecting the transcription factors. This is the case for Usp10, it was initially reported to directly regulate p53 and AR by deubiquitinating them and acting as a co-activator . HoweverP53 is a crucial tumour suppressor acting as a transcription factor responsible for regulating the expression of multiple genes associated with stress responses, cellular survival, growth and homeostasis , 28], , . P53 canSome DUBs can control p53 stability independently of their enzymatic activity. One such example is OTUB1 which can inhibit UbcH5. UbcH5 is an MDM2 cognate ubiquitin-conjugating enzyme (E2), as a result of its inhibition p53 ubiquitination is abrogated leading to its increased stability and activity , 33]. T. T33]. Tregs) from asthma patients, however the role of this interaction in carcinogenesis still remains to be established.GATA3 serves as another example of a transcription factor regulated by deubiquitination. GATA3 is a master regulator of T helper cells (Th2) cell differentiation and function; it controls early T cell development and is one of only 3 genes mutated in over 10% of breast cancers as it plays a key role in mammary gland development , 36]. R. R36]. RBoth canonical and non-canonical Wnt signalling pathways are also regulated by deubiquitination. Recent reports identified proteasome associated DUB Usp14 as an oncogene and a positive regulator of Wnt signalling via deubiquitination of Dishevelled (Dvl) . DepletiAn additional level of control of transcriptional activity mediated by the nuclear receptors is provided by the SAGA (Spt-Ada-Gcn5-acetyl 1 transferase) histone acetyltransferase (HAT) complex. In addition to HAT activity, SAGA has deubiquitinating activity, which is required for the transcriptional activity of nuclear receptors with Usp22 being the active DUB subunit of SAGA that removes ubiquitin from the histones H2A and H2B . As SAGAMono-ubiquitination of histone H2A is one of the key histone modifications, it is associated with transcriptional repression by the polycomb group proteins and maintenance of the genome integrity. H2A is mono-ubiquitinated at K119 and it is estimated that between five and fifteen percent of the H2A fraction is mono-ubiquitinated at any one time compared to only one percent of H2B. As previously discussed, Usp10 can deubiqutinate the mono-ubiquitinated H2A.Z variant of H2A which results in increased AR activity . HoweverHistone ubiquitination plays a vital role in both DNA damage response and repair pathways Table . IncreasUbiquitination of both H2A and H2B is equally important for maintaining cellular homeostasis and there are DUBs that specifically target histone H2B, including Usp49  and Usp4Some DUBs are not as specific and have the ability to deubiquitinate both histones H2A and H2B, for example the closely related family of DUBs comprising Usp1, Usp12 and Usp46. All three DUBs require Uaf-1 (WDR48) for their enzymatic activity  and addiIn normal cells most genes have an epigenetically stable transcriptional status. However, some genes are an exception to this rule as their sole purpose is to be responsive to the outside stimuli including growth factors and cellular contact. Those genes are most susceptible to epigenetic changes and their expression is rapidly affected by them. Dysregulation of epigenetics might result in altered expression of these genes leading to cellular transformation and malignancy. As a result, impact of DUBs on cell cycle regulation and DNA damage repair pathways deserves specific attention. The human genome is continuously challenged by both endogenous and exogenous insults potentially damaging the DNA which can result in various types of damage including double and single strand breaks, oxidative lesions and pyrimidine dimers. Cells have developed multiple ways to counteract and repair the DNA damage known as the DNA damage response pathways. These responses can be divided into two main groups; cell-cycle checkpoint activation and DNA repair. Both of these mechanisms are tightly controlled by chromatin remodelling and epigenetics.As discussed in previous sections multiple DUBs affect cell cycle indirectly by regulating transcription factors that control cell cycle progression, including the AR and p53, and by modulating histones. However, some DUBs regulate cell cycle in a much more direct fashion. DUBs can regulate cell cycle progression by controlling the G2/M checkpoint. Specifically both Usp50 and UbpM contribute towards this process. Usp50, even though it is catalytically inactive, plays a role in cell cycle progression. It associates with Hsp90 and controls Wee1 stability via an Hsp90-dependent mechanism. Usp50 consequently functions as a negative regulator of the G2/M checkpoint . UbpM reUsp1 knock-out mice are genetically unstable and hypersensitive to DNA damage ..Usp1 knoin vivo. This process is tightly controlled by Usp28 which is necessary to stabilise Chk2 and 53BP1 in response to DNA damage and is required for DNA damage induced apoptosis , , . This pog agents . Multiplg agents . This reg agents . The autg agents .Usp7 is one of the most extensively researched DUBs due to its role in regulating multiple key proteins including p53, MDM2, PTEN, FOXO, the polycomb complex and histones . During Discoveries over recent years clearly indicate that ubiquitination and deubiquitination regulate cellular homeostasis and as a result deregulation of these processes can promote cancer development and progression. DUBs can affect carcinogenesis through multiple cellular pathways with epigenetics being the main example. Deubiquitination of histones, transcription factors and their co-factors plays a major role in regulating epigenetics by DUBs. As a result DUBs could be valuable therapeutic targets in oncology. Although this field is still relatively novel, recent advances indicate that targeting DUBs could be an efficient strategy. Novel inhibitors aimed at both Usp1 and Usp7 have been shown to re-sensitise cells to known therapeutic agents and to have a therapeutic effect when used independently in both the cellular setting and in some xenograft models. DUBs might present a challenge for compound design as their active domains are often conserved and many of them are Cys-dependent making targeting more complex. Recently, Usp1 inhibitors have been discovered which inhibit Usp1 by targeting its interaction with Uaf-1, a protein binding partner required for Usp1's enzymatic activity, rather than by targeting the active domain directly. This is a very exciting direction which could offer a solution to DUB inhibitors design providing both specificity and decreased toxicity. Multiple DUBs rely on binding to other proteins for their activity and stability and many of those interacting partners are WD40 proteins just like Uaf-1 Table , it does


The histone acetyltransferase (HAT) Mof is essential for mouse embryonic stem cell (mESC) pluripotency and early development. Mof is the enzymatic subunit of two different HAT complexes, MSL and NSL. The individual contribution of MSL and NSL to transcription regulation in mESCs is not well understood. Our genome-wide analysis show that i) MSL and NSL bind to specific and common sets of expressed genes, ii) NSL binds exclusively at promoters, iii) while MSL binds in gene bodies. Nsl1 regulates proliferation and cellular homeostasis of mESCs. MSL is the main HAT acetylating H4K16 in mESCs, is enriched at many mESC-specific and bivalent genes. MSL is important to keep a subset of bivalent genes silent in mESCs, while developmental genes require MSL for expression during differentiation. Thus, NSL and MSL HAT complexes differentially regulate specific sets of expressed genes in mESCs and during differentiation.DOI:http://dx.doi.org/10.7554/eLife.02104.001 Embryonic stem cells are special cells that have the ability to become many different types of cells, such as skin, muscle, or neuronal cells. This process is called differentiation. They can also undergo a process called self-renewal to produce more embryonic stem cells. These processes are controlled by a complex network of enzymes, and the production of these enzymes depends on various genes within the organism being expressed as proteins.The DNA that holds the genetic information inside cells spends most of its time wrapped around proteins called histones: this allows the DNA molecules—which can be up to several metres long in some species—to fit inside the cell nucleus; it also protects the DNA molecules, which are quite fragile, from damage. Enzymes that attach chemical groups called acetyl groups to histones have a central role in controlling the self-renewal and differentiation of embryonic stem cells.Mof is an enzyme that attaches an acetyl group to a specific position in a particular histone. It is a subunit within two larger protein complexes that were originally identified in flies: the male-specific lethal (MSL) complex, which is only found in male flies, and the non-specific lethal (NSL) complex, which is found in both male and female flies. These complexes have been widely studied in flies, and the role of the Mof enzyme is also reasonably well understood in mammals. However, the roles of the MSL and NSL protein complexes in mammals are not fully understood.Ravens et al. have now used a combination of a technique called ChIP-seq (which can identify binding sites anywhere in the genome) and genetic ‘knock down’ experiments to explore the roles of these two complexes in mouse embryonic stem cells and neuronal progenitor cells.There is some overlap between the genes that the complexes act on. However, NSL acts on some genes than MSL does not act on, and vice versa. NSL mostly acts on genes that have ‘housekeeping’ functions and are expressed in many different cell types. MSL binds more to genes that are specific to embryonic stem cells, and acts on genes required for the development of neuronal progenitor cells. This means that NSL regulates the growth of embryonic stem cells, whereas MSL controls their development and differentiation.DOI:http://dx.doi.org/10.7554/eLife.02104.002 Pluripotent mouse embryonic stem cells (mESCs) have the ability to self-renew or to differentiate into all cell types. Specific transcription factors like Oct4, Sox2, and Nanog form a core transcriptional network, which is required for the maintenance of mESC pluripotency . ChromatN-acetyltransferase (GNAT) family (i.e. Gcn5 and p300) and the Moz-Ybf2/Sas3-Sas2-Tip60 (MYST) family  (reviewed in Drosophila (d) and mammals: the male-specific lethal (MSL) and the non-specific lethal (NSL) complexes  leads to early embryonic lethality as Mof−/− embryos fail to develop beyond the expanded blastocyst stage and die at implantation  MSL complex is composed of the subunits MSL1, MSL2, MSL3, and MOF , while tTo better understand the role of MSL and NSL in gene regulation and their individual contribution in epigenetic changes in mESCs, we have analysed these two Mof-containing complexes by chromatin immunoprecipitation coupled with high throughput sequencing (ChIP-seq) and by shRNA knockdown (KD) experiments in mESCs. The obtained genome-wide binding maps show that MSL and NSL locate to a large number of expressed genes and each complex has a distinct binding profile at promoters or gene bodies. Our combined ChIP-seq and KD data indicate that MSL and NSL have a combinatorial effect on a given set of genes, whereas some specific loci are only MSL- or only NSL-dependent. Our data indicate that NSL binds exclusively at promoters, while MSL binds more in gene bodies. We show that in mESCs NSL regulates cell growth whereas MSL is the main HAT complex acetylating histone H4K16. MSL is present at mESC-specific genes. Moreover, MSL binds to and regulates developmental genes in mESCs and during differentiation. Altogether our data demonstrate that MSL and NSL complexes are present at expressed genes in mESCs, but that MSL is essential for regulation of key mESC-specific and bivalent developmental genes.To understand the global role of the two Mof-containing complexes in chromatin remodelling and how this regulates genes linked to self-renewal, proliferation, and/or differentiation, we set out to analyse the genome-wide binding of MSL and NSL in mESCs. To this end, we raised antibodies targeting Msl1 or Nsl1, which are specific subunits of the MSL or NSL complexes, respectively, and are known to play a role in the assembly and the regulation of these complexes . The speTo characterize the genome-wide role of MSL and NSL complexes, we carried out ChIP-seq analysis in mESCs using the above-characterized anti-Msl1 and anti-Nsl1 antibodies. The obtained binding maps of Msl1 and Nsl1 in mESCs were then compared at the UCSC genome browser to publicly available ChIP-seq data for Mof, H4K16 acetylation (H4K16ac), RNA Polymerase II (Pol II), and DNAse hypersensitive sites (DHS). At a representative genomic locus, Nsl1 peaks were detected at the TSSs of four expressed genes, where they co-localized with Mof, Pol II and DHSs, whereas Msl1 binding peaks were usually broader and together with H4K16ac downstream of Pol II peaks . As prevUsing MACS14 algorithm  we deter−160)  . This in−160) . In cont−160) . Moreove−160) , and aft−160) . As onlyTo understand the genome-wide binding of MSL and NSL, we compared by k-means clustering either Msl1, or Nsl1 binding profiles with that of Mof and the presence of H4K16ac at 30,300 ENSEMBL transcription start sites (TSSs). In good agreement with our results showing that in mESCs Msl1 and Nsl1 incorporate in the endogenous MSL or NSL complexes, respectively, genome-wide Mof binding overlaps with that of Msl1 and Nsl1 around most of the TSSs, which are also H4K16ac positive .Interestingly, at promoters, MSL and NSL complexes have distinct binding profiles. Nsl1 and Mof show a sharp binding peak centred at the TSSs, while the average Msl1 binding profile is similar to H4K16ac (see below) and extends downstream from the TSSs in the GB regions . MoreoveTo assess the relationship between Msl1 and Nsl1 binding and gene expression in mESCs, we took advantage of available RNA-seq data  and compTo determine whether the binding strength of Msl1 or Nsl1 correlates with gene expression, we compared Msl1 and Nsl1 enrichment around TSSs with gene expression data from the corresponding bound genes. Msl1- or Nsl1-positive genes were divided into five categories according to their expression levels . As a coDrosophila and mammals  at mESC-specific genes. Available RNA-seq data of mESCs  allowed To validate these bioinformatics analyses, all Msl1- and/or Nsl1-bound genes were divided into three categories : Msl1- aMof results in lethality at embryonic day 3.5 and Mof also affects mESCs pluripotency  mESCs  mESCs  to overcO) mESCs . Howeverntenance . Severalntenance   under control and Msl1 KD conditions . BivalenIn this study, we analysed two Mof-containing complexes, MSL and NSL to understand their transcription regulation function in mESCs. The proteomic characterization of the mMsl1-, or mNsl1-containing complexes indicated that the subunit composition of the mMSL and the mNSL complexes is identical to human complexes . ImportaThis observation is important for our study as it indicates that the ChIP binding profiles obtained with either anti-Msl1 or anti-Nsl1 antibodies represent the behaviour of the corresponding endogenous Mof-containing MSL, or NSL HAT complexes. Furthermore, our findings are consistent with previous observations, which suggested that Msl1 and Nsl1 directly interact with Mof in their respective complexes, to stabilize the assembly of these complexes and to regulate their HAT activity .Drosophila  or gene bodies (MSL). MSL and NSL have overlapping and distinct roles in transcriptional regulation in mESCs. NSL binds mostly to genes with housekeeping functions and mediates mESC proliferation suggesting that NSL is important for the cellular homeostasis of mESCs. MSL is the main acetyltransferase complex acetylating H4K16. Moreover, MSL binds to mESC-specific genes, which are de-regulated in 2) in DMEM (4.5 g/l glucose) w-Glutamax-I, 15% foetal calf serum ESC-tested, leukemia inhibiting factor (5 μg) (Sigma), 50 mM ß-Mercaptoethanol , penicillin/streptomycin (Invitrogen), 200 mM L-glutamine (Invitrogen), and non-essential amino acids . To work under feeder-free conditions cells were treated with 1 mg/ml Collagenase (GIBCO) and 2 mg/ml Dispase (GIBCO) and cultivated for one passage without feeder cells on 0.1% gelatine (Sigma) coated plates. Experiments were conducted at passage 26–29. Mouse embryonic fibroblasts (3T3 ATCC) were cultivated in DMEM (4.5 g/l glucose), 10% newborn calf serum and gentamycin (Invitrogen).Wild-type male mESCs (E14.wt) were cultivated on 0.1% gelatine  and CD1 feeder cells  w-Glutamax-I, 10% foetal calf serum ESC-tested, 50 mM ß-Mercaptoethanol (Invitrogen), penicillin/streptomycin (Invitrogen), 200 mM L-glutamine (Invitrogen), and non-essential amino acids on bacteriological Petri dishes  to start differentiation. After 4 days retinoic acid (5 μm) (Sigma) was added to induce NPC formation. Experiments were conducted 8 days after differentiation.For NPC generation, we followed the protocol of E. coli (BL21). For primer sequences see Polyclonal anti-Msl1 (3208) and anti-Nsl1 (3130) antibodies were generated by immunization of rabbits with the N-terminal (3-210 amino acids) region of mouse Msl1 or C-terminal region (762-1037 amino acids) of mouse Nsl1. The fragment was amplified and cloned in pET28b  vector to express proteins in 2) and 100 mM KCl and afterwards with IP buffer containing 250 mM KCl. Proteins were eluted from protein A Sepharose beads 150 μl of 0.1 M Glycine pH 2.6. Elutions were neutralized by adding 50 μl of 2 M Tris pH 8.5.Nuclear extracts were prepared from 30 P15 plates of mESCs with 80% confluency as described in Mus musculus protein sequence database containing 16,604 entries (from the Swissprot 2013-04-03 release). In all searches, cysteine residues were considered to be fully carboxyamidomethylated  and methionine considered to be oxidized . Proteins were considered as specific in a given IP data set if they were absent or 10-fold minimum enriched as compared to a MOCK IP, performed on the same protein input by using a non-specific antibody targeting yeast TAF90. Relative protein abundance for each protein in either the anti-Msl1, or the anti-Nsl1 IPs was estimated by the calculation of a Normalized Spectral Abundance Factor (NSAF)  . NSAF va2, 150 mM KCl, and 5% Glycerol was used. 250 μl calibration mix containing Dextran Blue (2 MDa) and Biorad calibration kit (ref 151-1901) with marker sizes of 670 kDa, 158 kDa, 44 kDa, 17 kDa, and 1.35 kDa were injected at 0.3 μl/min. 500 μl of mESC nuclear extract containing 1 mg protein was injected and run at 0.3 μl/min. 40 fractions were collected and analysed by western blot. For western blot the anti-Mof  antibody was used.For gel filtration a Superose 6 (10/300) column pre-equilibrated in 25 mM Tris pH 7.9, 1 mM DTT, 5 mM MgClChIP was carried out as described previously with slight modifications . At 80% Mus musculus genome assembly (NCBI37/mm9) from NCBI was used for the sequence alignment by the software Bowtie (0.12.7) (www.ncbi.nlm.nih.gov/geo/) in our analysis: Input (GSM798320)  for Msl1 and the NEBNext protocol  for Nsl1. Libraries were validated with the Agilent Bioanalyzer. Single reads run sequencing was conducted with the HiSeq 2000. Image analysis and base calling were done with the Illumina pipeline (1.8.2). The July 2007 (0.12.7) . All anaM798320) , RNA PolM798320) , H4K16acM798320) , and MofM798320) . Fastq fM798320) . DHS wer−5, no shifting model was built and the shift size was defined as 200. The annotation was based on the ENSEMBL 67 database (mm9). Peaks were annotated to genomic features  using the software HOMER (4.2)   with defTo calculate the Msl1, Nsl1, or Pol II enrichment at a given gene either the peak tag density of the nearest peak to the TSS (in a region of +2 kb), was obtained through MACS14  or the tDensity profiles around the TSS and GB were obtained through seqMINER . For theTo verify the statistical significance of the obtained Msl1- or Nsl1-bound gene groups in Gene expression levels are based on the ENSEMBL 67 database (mm9). Raw data of mESCs and NPCs were taken from Gene Expression Omnibus (GSE34473) and processed using the software tools TopHat  and HTSe6 mESCs selection with puromycin (2 μg /ml) (InvivoGen) was started. Experiments were conducted 5 days after viral transfection. KD efficiency was tested at RNA levels through reverse transcriptase (RT)-qPCR  of the TRC2 library. For Ns1 KD the TRCN0000241466 shRNA clone and for Msl1 KD the TRCN0000241378 shRNA clone was used. Double KD of Msl1 and Nsl1 was conducted with equal amount of the TRCN0000241466 and TRCN0000241378 shRNA clones. For control the shRNA non-target control (Product No. SHC002) was applied. Production of lentiviral particles as well as infection of mESCs was conducted according to the manufacturer's protocol. 3 days after viral transfection of 2 × 10qPCR see  and at p2, 10 mM KCl, 0.5 mM DTT, 100 mM Natrium Butyrate, and 0.2 M HCl for 30 min on ice, centrifuged and dialysed first against 0.1 M acidic acid and then against water. Samples were analysed by western blot for histone modifications using the anti-H4K16ac , anti-H4K5ac , anti-H4K8ac , and anti-H3  antibody.Histones were prepared from mESCs by lysing cells in 10 mM HEPES, pH 7.5, 1.5 mM MgCl5 mESCs on 0.1% gelatine coated per 6-well plates in triplicates. mESCs were counted in triplicates using Neubauer cell counting chambers at indicated time points. mESCs were split every second day to 1 × 105 mESCs/6-well.Cell growth analyses was started 6 days after lentiviral infection by plating 1 × 105 mESCs were dissolved in 1 ml PBS (0.1% NaCitrate and 0.1% TritonX 100). Propidium iodide (50 μg/ml) was added and after 4 hr incubation on ice cells were analysed by the FACS calibur. Data were analysed using the CellQuest software.7 days after lentiviral infection 5 × 10Cell death was examined using the APOPercentage apoptosis assay  following the manufacturer's instructions. As a positive control apoptosis was induced with 10 mM hydrogen peroxide for 8 hr in sh control cells. Absorbance was read at 550 nm and normalized to the blank control (without cells).Experiments were designed with three independent biological replicas. Biotinylated cDNA targets were prepared, starting from 150 ng of total RNA, using the Ambion WT Expression Kit (Cat 4411974), and the Affymetrix GeneChip WT Terminal Labelling Kit (Cat 900671) according to Affymetrix recommendations. Following fragmentation and end-labeling, 3 μg of cDNAs were hybridized on GeneChip Mouse Gene 2.0 ST arrays  for whole-transcript expression profiles. Washed and stained chips were scanned with the GeneChip Scanner 3000 7 G (Affymetrix) at a resolution of 0.7 μm. Obtained raw data (.CEL intensity files) were processed with Affymetrix Expression Console software version 1.1 to calculate probe set signal intensities using Robust Multi-array Average (RMA) algorithms with default settings.To select the DE genes, we used the fold change rank ordering statistics (FCROS) method . In the www.ncbi.nlm.nih.gov/geo/) under the accession numbers: GSE53797 and GSE56646.Msl1 and Nsl1 ChIP-seq data sets as well as gene expression profiles of sh control, sh Msl1 and sh Nsl1 mESCs are deposited at Gene Expression Omnibus ( review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  in a timely manner we would be happy to consider a revised version.1) Genetic mutation of Mof has a lethal phenotype in mice and ES cells. The authors apply depletion of Msl1 and Nsl1 but do not seem to provide data on how these affect stem cell behaviour. Self-renewal and differentiation potential need to be analysed carefully. Also if lethality is caused by loss of either complexes  then changes in gene expression could be due to cell death. This needs to be carefully considered and discussed. Alternatively, does combined Msl1 and Nsl1 depletion recapitulate the Mof mutation?2) In 3) The authors conclude that there is no free Nsl1 and Msl1 protein as all would associate in Mof complexes. I wonder if the data allows this conclusion. To make this point the authors would need to demonstrate that their measurements would in principle allow detecting 10% free Msl1 or Nsl1 protein. To conclude from “Msl1 or Nsl1, incorporate in their respective complexes with similar abundance as does Mof” is too vague to make this point.4) The overlap between MSL/NSL and bivalent genes appears not very significant (5) Acetylation of other residues than H4K16ac is suggested (Discussion) as a redundant mechanism. It is not clear how to reconcile this speculation fits with the Mof phenotype. 1) Genetic mutation of Mof has a lethal phenotype in mice and ES cells. The authors apply depletion of Msl1 and Nsl1 but do not seem to provide data on how these affect stem cell behavior. Self-renewal and differentiation potential need to be analysed carefully. Also if lethality is caused by loss of either complexes  then changes in gene expression could be due to cell death. This needs to be carefully considered and discussed. Alternatively, does combined Msl1 and Nsl1 depletion recapitulate the Mof mutation?As required we have included following experiments in our revised manuscript to address the reviewers’ first points:a) To analyse whether Msl1 and Nsl1 play a role in maintenance of ESC pluripotency, we have conducted single Msl1 (shMsl1), or Nsl1 (shNsl1) or combined of Msl1 and Nsl1 (shMsl1/Nsl1) knockdowns (KDs) in mESCs see new . First wb) Note, however, that we do not observe detectable changes in Oct4 new  and alkac) Since we observed MSL binding at developmental bivalent genes , which aIn conclusion, we show that Nsl1 regulates proliferation and cellular homeostasis of mESCs. Knockdown of Msl1 leads to a global loss of histone H4K16ac indicating that MSL is the main HAT acetylating H4K16 in mESCs. MSL is enriched at many mESC-specific genes, but also at bivalent domains. Interestingly, MSL is important to keep a subset of bivalent genes silent in pluripotent ESCs, while the same genes require MSL for expression during differentiation. In agreement, during neuronal differentiation MSL is essential for the regulation of key developmental genes.2) InH4K16as shows peaks (right most H4K16ac peak) where neither Nsl1 nor Msl1 are enriched. This indicates that other complexes also act. A Mof chromatin IP would be useful to see if H4K16ac overlaps with Mof as would be expected.By using the commercially available anti-MOF antibody batches we obtained only very low enrichment values by ChIP-qPCR at defined genomic loci ), which are then used for sequencing. Thus, extensive fragmentation might result in disruption, or at least partial disruption, of large chromatin-bound complexes, resulting in ChIP-seq signal loss of proteins not directly associated with the chromatin. If Mof would be closer to the DNA than Msl1, or Nsl1, respectively, in MSL or NSL complexes at certain loci, the sole detection of Mof could be explained by the suggestion of Straub et al (2013).Thus, as suggested we included the published Mof ChIP-seq results  in our analyses see new . Figure Importantly however, our new These new results are now described in the Results section.3) The authors conclude that there is no free Nsl1 and Msl1 protein as all would associate in Mof complexes. I wonder if the data allows this conclusion. To make this point the authors would need to demonstrate that their measurements would in principle allow detecting 10% free Msl1 or Nsl1 protein. To conclude from “Msl1 or Nsl1, incorporate in their respective complexes with similar abundance as does Mof” is too vague to make this point.We apologize if our conclusion obtained from our mass spec results  were notBriefly, the development of non-gel-based, “shotgun” proteomic techniques such as Multidimensional Protein Identification (MudPIT) has provided powerful tools for studying large-scale protein characterization in complex biological systems. As during enzymatic digestions of protein mixtures for proteomic analyses large proteins contribute more peptide/spectra than small ones, a normalized spectral abundance factor (NSAF) was defined to account for the effect of protein length on spectral count for comparing protein abundance in the different samples , MethodsIn addition, as required we further addressed the reviewers’ concern and performed a gel filtration (GF) experiment using nuclear extracts prepared from mouse ESCs as described by the new We think that we have now convincingly demonstrated  that Msl1 or Nsl1 are exclusively present in their respective HAT complexes, in which Mof is present with similar abundance (with a close to 1:1 subunit ratio) than either Msl1, or Nsl1.4) The overlap between MSL / NSL and bivalent genes appears not very significant . The large majority of Msl1 and Nsl1 bound genes are not H3K27me3. Throughout the manuscript genes are categorized but statistical testing seems to be not performed. Rigorous statistical tests and control groups need be included to establish meaningful correlations.The overlap between MSL and NSL with bivalent sites is now included in our revised manuscript in 5) Acetylation of other residues than H4K16ac is suggested (Discussion) as a redundant mechanism. It is not clear how to reconcile this speculation fits with the Mof phenotype.We agree with the reviewers that our speculation did not fit with the Mof phenotype. Therefore, as required we have now deleted the original


The initiation of flowering is an important developmental transition as it marks the beginning of the reproductive phase in plants. The MADS-box transcription factors (TFs) FLOWERING LOCUS C (FLC) and SHORT VEGETATIVE PHASE (SVP) form a complex to repress the expression of genes that initiate flowering in Arabidopsis. Both TFs play a central role in the regulatory network by conferring seasonal patterns of flowering. However, their interdependence and biological relevance when acting as a complex have not been extensively studied.We characterized the effects of both TFs individually and as a complex on flowering initiation using transcriptome profiling and DNA-binding occupancy. We find four major clusters regulating transcriptional responses, and that DNA binding scenarios are highly affected by the presence of the cognate partner. Remarkably, we identify genes whose regulation depends exclusively on simultaneous action of both proteins, thus distinguishing between the specificity of the SVP:FLC complex and that of each TF acting individually. The downstream targets of the SVP:FLC complex include a higher proportion of genes regulating floral induction, whereas those bound by either TF independently are biased towards floral development. Many genes involved in gibberellin-related processes are bound by the SVP:FLC complex, suggesting that direct regulation of gibberellin metabolism by FLC and SVP contributes to their effects on flowering.The regulatory codes controlled by SVP and FLC were deciphered at the genome-wide level revealing substantial flexibility based on dependent and independent DNA binding that may contribute to variation and robustness in the regulation of flowering.The online version of this article (doi:10.1186/s13059-015-0597-1) contains supplementary material, which is available to authorized users. Identifying the individual binding sites of TFs and their precise modes of regulation enables definition of such networks. The genome-wide binding sites of several TFs involved in flowering-time control and floral development were described based on the results of chromatin immunoprecipitation (ChIP) focused on single TFs [Arabidopsis thaliana.Developmental programs of multicellular organisms require the establishment of defined temporal and spatial patterns of gene expression. In higher plants, the initiation of flowering is the first step in reproductive development, and is controlled by a complex regulatory network that converges on the transcription of a small number of floral integrator genes ,2. This ngle TFs -10. Howengle TFs ,11,12. HA. thaliana genome and these were classified into 58 families [Over 2,000 TFs are encoded in the families , many offamilies . MADS dofamilies -18 and dfamilies ,19-23 infamilies . AccordiFLC represses flowering but its mRNA level is reduced by exposure to winter cold , allowing flowering to proceed [SVP mRNA reappears shortly after in floral primordia, allowing this TF to participate in flower development [Two members of the MADS-box family, FLC and SVP, enhance the flowering response to seasonal cues by repressing flowering under non-inductive conditions. These functions were defined by genetic analysis that placed FLC in the autonomous and vernalisation pathways ,18. FLC  proceed ,18. Simi proceed ,26. SVP elopment ,28. The elopment ,29,30.FLOWERING LOCUS T (FT) and SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1) [FT is expressed in the leaves during floral induction, the major site of action for SOC1 is in the shoot apical meristem. FLC acts in both organs to repress expression of these genes and delay flowering [FLC or SVP lead to early flowering and increased levels of FT and SOC1 mRNAs [SVP and FLC have partially redundant functions during floral repression [The inhibition of flowering caused by FLC and SVP is, at least in part, due to repression of the floral integrator genes 1 (SOC1) ,30. Whillowering ,31. Similowering . MutatioC1 mRNAs ,16,18. Npression ,33.FT and SOC1 [A. thaliana MADS-box proteins also reported, among others, APETALA1 (AP1), SOC1, and SEPALLATA 3 (SEP3) as components of the SVP interactome [Consistent with their shared activity in repressing flowering and the capacity of many other MADS-box TFs to form transcriptional complexes, SVP and FLC proteins directly interact ,33. In aand SOC1 ,9,31,34.and SOC1 ,27,35,36and SOC1 ,29. Furteractome ,27,37.vice versa has the potential to identify bona fide dependencies and to elucidate how both factors act in a combinatorial fashion to regulate transcription.The activities of SVP and FLC were studied by ChIP PCR on individual target genes, and their genome-wide binding maps were characterized separately by ChIP followed by sequencing (ChIP-seq) or ChIP-on-chip approaches ,4,9. Thisvp mutant. Our study shows that the formation of the FLC:SVP complex substantially influences occupancy of each factor at specific binding sites. The findings demonstrate that complex formation is indeed essential for DNA binding to a subset of genes, leading to the identification of novel cis-regulatory elements that may contribute to the recruitment of the complex. The distinct spatial roles of SVP and FLC are emphasised by the marked differences in observed gene expression profiles between leaves and apices. Thus, by describing the genome-wide effects of two MADS-box proteins capable of forming a multimeric complex we show how their interactions generate diverse patterns of co-regulation.Here, we studied the combinatorial activity of the TFs FLC and SVP at a genome-wide level by combining ChIP-seq and transcriptome gene expression profiling on experiments performed on different genetic backgrounds and tissues. Through this comprehensive approach we identified direct targets of SVP in the presence and absence of its partner FLC. Reciprocally, FLC ChIP-seq was performed in wild-type and the FT and SOC1 in the leaves and apices, respectively [SVP and FLC under SDs. All plants carried a functional FRIGIDA (FRI) allele to ensure high levels of FLC transcription [SVP FLC FRI (WT) and differentially expressed genes (DEGs) were selected for subsequent analysis  [svp and flc mutants [FLC was found to have a direct role in leaf development [TCP genes were also overrepresented among direct targets of other MADS-box proteins such as SEP3 and AP1 [Unlike clusters A and A’, the expression patterns of clusters B and D and B’ and D’ were similar in both leaves and apices. Expression of genes in clusters B and B’ was greatly affected in the double mutant while much less in single mutants Figure E, suggesLIA-like  and TEOS9 (TCP9) . Leaf sh mutants ,44, and  and AP1 ,20,45.GIBBERELLIN 20 OXIDASE 2 (GA20OX2), which encodes an enzyme involved in gibberellin (GA) biosynthesis and was recently shown to be repressed by SVP at the shoot apex [GA20OX2 independently of SVP , compensatory (clusters B and B’) or additive (clusters C and C’) modes of co-regulation.The extent to which FLC:SVP regulates gene expression was then addressed. Clusters D (62 genes) and D’ (6 genes) exhibited negative interaction coefficients for FLC:SVP, indicating that FLC and SVP act in the same pathway and consistent with the proteins acting in a heterodimer to regulate the expression of these genes. We propose that their regulation could depend on the protein complex Figure  and 8. SJASMONATE ZIM-domain (JAZ) genes , which contribute to the jasmonate signalling pathway [DARK INDUCIBLE 10 (DIN10), also known as RAFFINOSE SYNTHASE, which encodes a glycosyl hydrolase associated with cold response, as well as light and sucrose stimulus. In Arabidopsis, DIN10 transcript levels respond to cold treatments predicted to reduce FLC expression [DIN10 mRNA by independent real-time quantitative PCR (qRT-PCR) in leaves of svp, flc and svp flc mutants  and pSVP:SVP:GFP svp-41 flc-3 FRI (hereafter SVP in flc-3)  and svp-41 FLC FRI backgrounds (FLC in svp-41). Each ChIP-seq was done in triplicate. Irreproducible discovery rate (IDR) analysis was performed and only the peaks that were reproducible at an IDR ≤ 0.05 were selected for further processing  antibody in the genotypes flc-3 mutant 264 peaks were called for SVP:GFP and annotated to 303 genes . Thus, overall the presence of FLC increased the number of SVP:GFP targets, but targets only bound in the absence of FLC were also detected. Binding to the flowering-related genes SEP3, SOC1 and SCHLAFMUTZE (SMZ), which were previously shown to be targets of SVP [TEMPRANILLO 1 (TEM1), CONSTANS-LIKE 1 (COL1) and CONSTANS-LIKE 4 (COL4) were exclusively bound in WT when both TFs were present. As described for other MADS-box TFs [In WT, SVP:GFP binding was detected at 523 unique genomic regions that were assigned to 773 neighbouring genes (peaks reside 3 kb upstream of the transcription start site or 1 kb downstream of the transcription end site) Figure . On the s Figure . Among ts of SVP ,11,12, d-box TFs ,20, bindsvp-41 mutant . As for SVP, FLC peaks were mainly located in promoter regions in both genotypes  were also bound by FLC in svp-41 (22% of the FLC targets in svp-41). Therefore, when FLC and SVP bind independently, about 20 to 30% of their target genes are shared. The presence of these common targets ; peaks only identified in WT, that is, when both TFs were present (2TF); and peaks only identified in the mutant (1TF) Figure B. Of 144de novo motif discovery using MEME [6GG, although variations in the distribution of A and T nucleotides in the A/T stretch or its length have been described [6GG motif was found to be the most enriched in all genotypes, whether FLC or SVP and 1TF, 2TF or UB data were used  was found in UB or 2TF peaks but not in the 1TF set  was detected that is exclusively present adjacent to sites at which SVP binds in genotypes where it can form a complex with FLC.To gain further insight into the biological roles of FLC and SVP acting as a complex or individually, the genes targeted by these TFs in WT and mutant backgrounds were analysed. First, genes bound in WT but not in mutant genotypes were selected. The genes present in either 2TF group were bound by FLC or SVP only in WT, and therefore were combined in one set that contained 643 genes. This set was referred to as complex-enriched genes, because it was expected to contain all the genes bound by the complex, but might also contain some genes bound in WT by only one of the TFs. A more stringently selected set of genes bound by the complex is represented by those present in both 2TF groups. This set contained 67 genes that after stringent individual inspection was reduced to 45, and these were referred to as complex-exclusive genes.SEP3, SHATTERPROOF 2 (SHP2/AGL5), APETALA3 (AP3), SOC1 and SVP  encodes a MADS-box TF that was described as a target of SVP and FLC in previous studies [These gene lists were analysed according to their functional annotation  and Gene SHP2/AGL, APETALAP Figure . In cont SHP2/AGL, APETALA SHP2/AGL, APETALA studies . Our dat SHP2/AGL, APETALA studies . The ChI studies ,9.FigureTaken together, our functional analyses suggest that individually FLC and SVP, probably coupled with other TFs, predominantly control flower development, whereas the FLC:SVP heterodimer acts as a major regulator of flowering time.The correlation between DEGs and direct targets obtained by ChIP-seq was then assessed to determine how many of the transcriptional changes are due to direct binding of FLC and SVP. The DEGs in leaves and apices were combined and compared with the list of target genes obtained from seedlings in the ChIP-seq experiments. This global analysis showed that 15 to 20% of DEGs in all the mutants were direct targets of FLC or SVP Figure . FurtherTEMPRANILLO (TEM) genes encode TFs that delay flowering by directly repressing FT and reducing GA levels [. TEM1 directly binds to and represses transcription of paralogues encoding GIBBERELLIN 3-OXIDASE, GA3OX1 and GA3OX2, an enzyme required for biosynthesis of bioactive GAs [TEM1 and TEM2 were among the direct targets of FLC and SVP and TEM1 was in the complex-exclusive set  encodes an AP2-type TF that promotes expression of the GA catabolic enzyme GIBBERELLIN 2-OXIDASE 7 (GA2OX7) [DDF1 was associated with a complex-exclusive peak , a homologue of GA2OX7, was also present in the complex-exclusive list  carrying a T-DNA insertion in the first exon  . DDF1 wak Figure  and 26 at Figure . Regulatbidopsis . The com8 Figure . FLC ands Figure . Strikins Figure , a phenoe GA2OX8 . In agrese to GA , is alsosvp mutant due to deregulation of GA20OX2 expression, which is indirectly repressed by SVP [Previously, higher levels of bioactive GA were detected in the d by SVP , and FLCd by SVP . Here weArabidopsis MADS-box TFs FLC and SVP interact to form a complex and each represses the transition from vegetative growth to flowering. Here we studied their functional interdependency at the genome-wide level. Transcript profiling and ChIP-seq studies were performed in WT plants in which both TFs are active as well as in mutants lacking activity of one or both TFs. The landscape of binding sites and regulated genes differed dramatically when both factors were active compared with when they functioned individually. Strikingly, a subset of binding sites that is recognized by each factor only when the other is present identified genes that are regulated specifically by the FLC:SVP complex. Genes involved in flowering time or environmental responses were enriched among those recognized by the complex whereas genes with developmental functions during flower development were over represented among those recognized by the TFs acting individually. Our study demonstrates at the genome-wide level how the functions of these plant MADS-box TFs with pivotal roles in reproductive development are influenced by their cognate partners.The A. thaliana [FLC transcription. Mutation of FLC or SVP is sufficient to cause much earlier flowering under inductive LDs, while double mutants exhibit extreme early flowering even under non-inductive SDs. The genetic data demonstrate that although these TFs interact to form a complex, each protein must retain a function in the absence of the other. MADS-box TFs interact with other TFs of the same class to form higher order complexes [SVP and FLC contribute to several endogenous and environmental pathways that govern floral induction in thaliana . Their mthaliana ,33. SVP omplexes , so indiomplexes ,35,59,65omplexes .FLC have an effect on vegetative phase change reflected in leaf heteroblasty [svp mutants. However, mutations in SVP do increase GA levels leading to changes in chlorophyll accumulation in leaves and to leaf petiole elongation [flc mutants nevertheless included flowering-time genes such as SOC1. SVP has defined functions in flower development in part by interacting with other MADS proteins involved in this process [To define the contribution of FLC or SVP acting individually, genome-wide transcriptome analysis of the WT and single and double mutants in apices and leaves was carried out. Both genes are expressed in these tissues and influence flowering when expressed in either region ,32. As eroblasty , whereas process ,65 and sInterestingly, a set of leaf and apex genes that are bound specifically by the FLC:SVP complex in seedlings was identified Figures . ExpressGenome-wide identification of binding sites for FLC and SVP revealed that 15 to 25% of the transcript changes were caused by direct regulation and that SVP and FLC act almost exclusively as repressors , the te [et al.  and alig [et al.  and 223  [et al. ,9 was lecis-elements  [-2 s-1 under both conditions. The mutant lines described here are: svp-41 [flc-3 [svp-41 flc-3, din10 (SAIL-54-G03), and ga2ox8 . svp-41, flc-3 and svp-41flc-3 were crossed with Col FRI-Sf2 to obtain an active FRI background. Plants used for ChIP experiments are described below in the 'The WT Col FRI) . The def: svp-41 , flc-3 [1 [flc-3 , svp-41 SVP FLC FRI, SVP flc-3 FRI, svp-41 FLC FRI and svp-41 flc-3 FRI genotypes were grown for 2 weeks under SD conditions or 2 weeks under SDs and then transferred for 2 days under LDs. Leaf and apex tissue was harvested at Zeitgeber 8 (ZT8). Total RNA from three biological replicates was isolated with an RNAeasy extraction kit  and probed to an AGRONOMICS1 Tiling array [2 expression values using the ‘lmFit’ function in the limma package in R: Sgytr = GYTgyt + Rr + εgytr, where S is log2 expression value, GYT is genotype:condition:tissue interaction, and R and ε are the random factors: R is biological replicate and ε is the residual. The ‘ebayes’ function in the limma package was used for variance shrinkage in calculation of the P-values and the Storey’s q-values were calculated from the P-values using the ‘qvalue’ function in the qvalue package. Heat maps were generated by CLUSTER3.0 [Seedlings from ng array . Probe sng array  using thUSTER3.0  using unUSTER3.0 . The sigUSTER3.0 ,41.PP2A (At1g13320) and UBC21 (At5g25760) as house-keeping genes. The sequences of the primers used to quantify the expression are listed in Additional file Total RNA was isolated from leaf or apex tissues using an RNAeasy extraction kit (Qiagen) and treated with RNAse-free DNase  to remove residual genomic DNA. Total RNA (1 μg) was used for reverse transcription . Transcript levels were quantified by quantitative PCR in a LightCycler 480 instrument  using svp-41 mutant, SVP::SVP:GFP svp-41 [SVP::SVP:GFP svp-41 flc-3 FRI and SVP::SVP:GFP svp-41 FLC FRI. Both lines were compared with the control line, in our case 35S::GFP. Polyclonal antibody (5 μl) against GFP from Abcam (Ab290) was used to immunoprecipitate chromatin . For ChIPs on FLC we used the genotypes Col FRI and svp-41 FRI and these were compared to the control svp-41 flc-3 FRI. In this case, 2 μl of FLC antiserum was used (kindly provided by Chris Helliway) [et al. [SEP3 [For ChIP experiments plants were grown under SDs for 2 weeks and above-ground tissue was collected at ZT8. Three biological replicates were performed for all the ChIP assays. For ChIP on SVP we used the line expressing SVP fused to GFP under its own promoter in the P svp-41 , and cro [et al.  with minA. thaliana genome (TAIR10) using Bowtie [P-value cutoff of 1e-3, followed by IDR analysis [P ≤ 0.05 (Hotelling’s T2 test). P-values were adjusted for multiple comparison using Benjamini-Hochberg correction [svp-41 and flc-3 mutants as opposed to the WT were tentatively classified as complex-dependent. The plots and heat maps in Figures We followed recommended guidelines in the analysis of ChIP-seq data for quality control, read mapping, normalization, peak-calling, assessment of reproducibility among biological replicates, and post-processing of peaks . Low-quag Bowtie  version g Bowtie  with a Panalysis . Duplicaanalysis . Peaks aanalysis . Only MAanalysis . Analysianalysis . Proximaanalysis , withoutrrection . Genes tSignificant GO terms were identified using the Functional Annotation Tool from DAVID Bioinformatics resources ,94.cis-elements. We used MEME [de novo motif identification. MEME parameters were set to find the 10 most significant motifs with length between 5 and 20 nucleotides. TOMTOM [For each ChIP experiment we first generated three subsets of peaks (and associated sequences): peak regions in (the experiments with) both genotypes (UB), peaks present only for the WT genotype (2TF), and peaks present only for the respective mutant genotype (1TF). ChIP regions for all six scenarios  were screened for enriched sed MEME  with ‘zo. TOMTOM  . MOODS was used to re-screen ChIP and random regions. Average numbers of sequences with CArG-box and G-box as well as standard deviation in random sets were calculated to generate Z-scores for each motif for each of the six scenarios. Z-scores above 3 were considered as significant.To confirm enrichment of cis-elements of both categories.To check whether CArG-boxes and G-boxes preferentially occur within a specific distance range in any of the six scenarios, we searched for all occurrences of CArG-boxes and G-boxes and calculated the distances between nearest Plant protein extracts of 2-week-old SD grown plants dissected for apices and leaves at ZT8 were prepared in extraction buffer  and a total of 30 μg of plant protein extract was used for immunoblots. Western analysis was performed with anti-rabbit-RGA antibody (AGRISERA), and immunoblots were incubated with SuperSignal Femto West Substrate (Thermo Fisher Scientific) and detected with a LAS-4000 Mini-image analyzer (Fujifilm).Microarray data have been deposited with the NCBI Gene Expression Omnibus (GEO) under accession number GSE57416. ChIP-seq data have been deposited under accession number GSE54881.