An international conference on Transposable Elements (TEs) was held 21–24 April 2012 in Saint Malo, France. Organized by the French Transposition Community  and the French Society of Genetics (SFG), the conference’s goal was to bring together researchers from around the world who study transposition in diverse organisms using multiple experimental approaches. The meeting drew more than 217 attendees and most contributed through poster presentations (117), invited talks and short talks selected from poster abstracts . The talks were organized into four scientific sessions, focused on: impact of TEs on genomes, control of transposition, evolution of TEs and mechanisms of transposition. Here, we present highlights from the talks given during the platform sessions. The conference was sponsored by Alliance pour les sciences de la vie et de la santé (Aviesan), Centre national de la recherche scientifique (CNRS), Institut national de la santé et de la recherche médicale (INSERM), Institut de recherche pour le développement (IRD), Institut national de la recherche agronomique (INRA), Université de Perpignan, Université de Rennes 1, Région Bretagne and Mobile DNA.Jean-Marc DeragonAbdelkader Ainouche, Mireille Bétermier, Mick Chandler, Richard Cordaux, Gaël Cristofari, Jean-Marc Deragon, Pascale Lesage, Didier Mazel, Olivier Panaud, Hadi Quesneville, Chantal Vaury, Cristina Vieira and Clémentine Vitte Jef Boeke , set the tone and gave a very good example of what studying TEs can lead to these days. First, he explained how massive sequencing could be used to understand in great detail basic aspects of retrotransposon behavior. Using deep sequencing of yeast Ty1-flanking sequence amplicons, he was able to reveal not only that the majority of Ty1 insertions were associated with the 5′ regions of RNA polymerase III transcribed genes, but also that an exquisitely specific relation exists between Ty1 insertion sites and nucleosomal DNA segments at specific positions on the nucleosome lateral surface. The use of massive sequencing technologies was essential to observe this specific relation and led to the conclusion that a dynamic process such as nucleosome remodeling is likely involved in Ty1 integration. Next, he illustrated the power of deep sequencing to carry out screens of human genomes for retrotransposon insertion polymorphisms (RIPs) and found that frequencies of individual presence/absence alleles vary dramatically and could be used to characterize specific human populations. Finally, he argued that understanding TEs is essential to generate a completely synthetic yeast genome lacking all destabilizing elements. In the long term, yeasts containing such a synthetic genome could be used to evaluate the impact on genome evolution and fitness of reintroducing different types of TEs. Genome-wide approaches have been enthusiastically adopted by many participants and adapted to study the impact of TEs on genome and gene expression to better understand the control of TEs, their evolution and their mechanism of transposition.Transposable elements (TEs) are truly fascinating biological entities. This is, of course, the opinion of all ICTE 2012 participants who met last April in Saint Malo, France, for what turned out to be a very exciting congress. A major evolution in the field since the ICTE 2008 edition is the routine use by many research groups of next-generation sequencing methods. This technological revolution has not only allowed significant progress in our fundamental understanding of TE biology, but has also revealed more than ever the importance of TE research to better understand genome evolution and to decipher the complexity of gene expression networks. The keynote lecture of the meeting, given by Henry Levin  described a novel approach to identify the function of eukaryotic genes based upon dense maps of transposon integration. As a proof of concept, he generated a large library of transposon Hermes insertions in Schizosaccharomyces pombe. Cells with insertions in genes important for growth become depleted in the culture. Deep sequencing of insertion sites reveals which insertions cannot be tolerated under a specific growth condition, determining which genes are required for cells to grow in defined medium.Genome-wide TEs analysis in plants and animals shows that TEs are a major and extremely active component of eukaryotic genomes, constituting up to 90% of the nuclear DNA in some species (for example bread wheat). Their insertion and deletion activities are affected by factors such as chromatin structure, recombination rate, and gene density. Mark Batzer  the opportunity to analyze polymorphisms related to these three active elements. This revealed 7,380 polymorphic mobile element insertions. Experimental validation showed that while the small Alu1 element (300 bp) has a low false detection rate (5%), a higher error rate is found for the several kilobase long L1 and SVA elements , a feature that may be due to the use of short reads and low genome coverage. Characterization of mobile subfamilies through analysis of target site duplication length distributions revealed that the AluYa5 subfamily accounts for the vast majority of Alu variation and is therefore the main driver of human Alu insertion.TEs contribute to genomic variation between individuals in populations. In human, while most retroelements are remnants of ancient transposition events and are no longer capable of active retrotransposition, a fraction remains active and contributes to variation between individuals. These elements belong almost exclusively to the Alu, LINE-1 (L1), and SVA families of non-long terminal repeat (LTR) retrotransposons. The 1000 genome project, the goal of which is to provide a comprehensive resource on human genetic variation through sequencing genomes from different populations, offered Moaine Elbaidouri  developed a new bioinformatic procedure for mining and clustering of LTR retrotransposons that allows comprehensive comparative genome-wide study of the impact of retrotransposition on genome structure in the plant kingdom. Regardless of the size of the plant genome, only a few families have undergone recent transposition. Moreover, difference in genome size is correlated with the extent of the burst of the most recent active families. This also suggests that most ancient TE insertions have been eliminated, confirming that differentiation of the non-genic compartment of plant genomes occurs through a very fast turnover of TE-related sequences.The growth of genomic data made available by next-generation sequencing (NGS) technologies has opened new perspectives for studying TE evolutionary dynamics across many lineages through comparative studies. This necessitates robust methods for TE identification and most importantly their classification from sequenced genomes. Philippe Glaser  introduced an original transposition mechanism observed in Streptococcus insertion sequence (IS) TEs. After excision, the TE circles are infectious as they can be transmitted from one cell to another during conjugation. Interestingly, the integration is specifically targeted into the promoter region of genes, limiting the impact of this TE on the genome.Aurélien Doucet  discussed about the identification of an unconventional mechanism for the human LINE-1 ORF2 translation. Using biochemical and cellular approaches as well as the L1 retrotransposition assay, developed in the laboratory of John Moran, he described the translation of ORF2, located downstream of ORF1 in the L1 bicistronic transcript, likely occurring by termination/re-initiation. This mechanism seems specific to the bicistronic context. Deletion of the inter-ORF spacer or substitution of the first ORF still lead to ORF2p expression; indicating that there is likely no specific sequence upstream of ORF2 to allow its translation.Helen Rowe  showed that endogenous retroviruses (ERVs) are transcriptional landmines whose KAP1-mediated control is essential to preserve transcriptional networks at the heart of embryonic stem (ES) cell pluripotency. Regulation of retroelements is, therefore, critical not just to prevent retrotransposition, but more broadly to safeguard the timely activation of genes through development.TEs are also responsible for a large proportion of visible mutations and possibly a substantial proportion of advantageous mutations. Many TEs are located within or near genes and have been shown to play important roles in gene regulation and function. Matthias Zytnicki  noted that for some TE families, small regions that seem to be over-represented in the genome might contain putative transcription start sites (TSSs). This could imply that some specific TE fragments may have been positively selected by the host genome. He showed that active transposable copies influence host gene transcription and that TSSs of TEs have been exaptated to provide new gene structures.Eugenio Butelli  gave a spectacular example of the impact of LTR retrotransposons in the occurrence of blood oranges. Following characterization of the ruby gene - which encodes the conserved domain of the Myb regulators of anthocyanin biosynthesis - from the Sicilian Moro blood orange, the authors found that this gene is expressed in the fruit of several blood oranges but not in that of the common blond oranges. The difference in expression was shown to be driven by insertion of a copia-like LTR retrotransposon in the 5′ untranslated region (UTR) of the gene of the blood orange. The 3′ LTR of the retrotransposon contributes a transcription initiation site that is not present in blond oranges. This creates a chimeric LTR/gene transcript, which leads to gene expression. Interestingly, both complete element and solo LTR forms of the element, which are found in different Sicilian blood orange varieties, can induce gene expression. Finally, analysis of ruby in an ancient Chinese blood orange variety of non-Sicilian origin revealed the insertion of a different LTR retrotransposon in its 5′ UTR. This insertion is in inverse orientation and the retrotransposon does not bring a transcription start site through its LTR. The observation of two independent LTR retrotransposon insertions inducing the expression of the ruby gene through different mechanisms is particularly striking.As advantageous mutations, TEs have been involved in the domestication of several crop species. (ChIP-seq) approach, Guillaume Bourque  showed that, in mammals, some repeats have a strong association with transcription factors. To investigate the presence of TE-based transcriptional regulatory networks, the authors analyzed whether TE-embedded sites are associated with genes regulated by the protein, which are binding these sites. Through a simultaneous analysis of protein occupancy and expression data, they revealed that different TE families have contributed to a significant fraction of binding sites in both human and mouse. Although orthologous genes had the same regulation pattern in both human and mouse, the type of involved binding sites were different, revealing that TEs have contributed in rewiring gene expression network in mammals.TEs are also clearly involved in building host gene regulation. Through a chromatin immunoprecipitation followed by massive DNA sequencing Rita Rebollo  analyzed insertionally polymorphic sites for three retrotransposons  at specific loci in two mouse embryonic stem cell lines and investigated the chromatin state around the full and empty sites using ChIP-seq analysis. While IAP elements induce H3K9me3 heterochromatic marks in flanking genomic DNA, such heterochromatin is not induced by LINEs and only by a minority of polymorphic ETn/MusD copies. Only one case of transcriptional silencing via IAP-induced heterochromatin was identified. DNA methylation analysis showed no difference between full and empty sites for IAP, but revealed that MusD induces DNA methylation at short distances (within 1.5 kb). On the other hand, when the two LTRs of a given element are compared, the LTR located the closest to the gene is not methylated, whereas the other is, suggesting that genes can also influence MusD methylation. While influence can be seen in both directions (retrotransposon to gene or gene to retrotransposon), many cases of equilibrium exist. The role of insulator protein is proposed as a wall to prevent spreading between genes and retrotransposons.Beyond being potential mutagenic agents, TEs are sometimes co-opted for functional roles in eukaryotic genomes. Recent results indicate their central role in epigenetic control of gene expression. In the mouse, retrotransposons are often located in repressed regions and are thought to induce heterochromatin formation and its spread. However, direct evidence for TE-induced local heterochromatin in mammals is surprisingly scarce. To examine this phenomenon, Prescott Deininger  created a novel cassette-based recombination assay system allowing evaluation of a broad range of potential Alu-related sequence factors. Replacing one of the Alu elements with sequences having different percentage and distribution of mismatches demonstrates a strong dependence on sequence identity, as well as distribution. With perfectly matched Alu elements, the system detects only Alu/Alu non-allelic homologous recombination (NAHR) events. However, as mismatch is increased, deletions caused by non-homologous end joining (NHEJ) become dominant. Surprisingly, at moderate levels of mismatch, both NAHR and NHEJ recombination are suppressed, suggesting a complicated local interference between DNA repair pathways.TEs are tightly regulated to prevent potential damage they might cause to the host genome if their activity is too high. A variety of regulatory systems has been selected by the cell to counteract the mutagenic effects of TEs. A given TE uses a set of mechanisms to control its activity at several levels. These may vary in detail, even between TEs that are phylogenetically related or between different tissues within an organism. Control of transposition activity can involve autoregulatory circuits or interactions with cellular factors. It can occur at different stages of transposition such as transcription, translation, transport, intracellular formation of nucleoprotein structures and efficiency/selectivity of their integration into the cell genome. TE activity can also be silenced by different epigenetic regulation mechanisms: at the transcriptional level via DNA methylation and/or histone modifications, and/or at post-transcriptional level via small RNAs. The talks in the ‘Control of transposition’ session revealed the ever-expanding diversity of mechanisms that control transposition activity. Each talk focused on different TE models (ranging from LTR and non-LTR retrotransposons to DNA transposons) and in several organisms .Saccharomyces cerevisiae is activated by environmental stresses through host-cell signaling pathways and produces Ty1 sense and antisense RNAs. Pascale Lesage  reported that Ty1 transcription increases in response to a severe deficiency in intracellular ATP and ADP levels. The Tye7 transcription factor originally identified as an activator of Ty1-adjacent gene transcription, is induced in response to ATP/ADP depletion, inhibits Ty1 antisense transcription and activates Ty1 mRNA transcription. Tye7 probably represses Ty1 antisense RNA synthesis, directly. These findings highlight a new level of control of Ty1 mobility by environmental stress conditions, since Ty1 antisense RNAs play an important role in regulating Ty1 at both the transcriptional and post-transcriptional stages.The transcription of the Ty1 LTR retrotransposon of Joan Curcio  described the use of selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) analysis to resolve the secondary structure of in vitro-transcribed Ty1 RNA (nucleotide 1–380) that is necessary for packaging and initiation of translation and reverse transcription. This structure predicts the existence of a pseudoknot separating the RNA into two well-organized domains. Mutational analysis suggests that the pseudoknot is a determinant of Ty1 RNA packaging and retrotransposition, which may delineate functional as well as structural domains in Ty1 RNA. J. Curcio also characterized several cellular factors required for the formation of retrosomes, microscopically distinct foci where retrotransposon-encoded RNA and proteins localize, inside the yeast cell. Although these cofactors are not necessary for Ty1 RNA and Gag protein expression or VLP formation, Ty1 cDNA is strongly reduced in their absence, suggesting that retrosome formation may be a required step in the production of replication-competent VLPs.LTR retrotransposon RNA within virus-like particles (VLPs) serves as the genome, as the template for translation of Gag and Pol proteins, and for reverse transcription. An important issue concerns the partition of RNA among these three functions. Geraldine Servant  showed that the DNA-repair endonuclease complex ERCC1-XPF, which specifically recognizes and cleaves 3′ flap structures, and core proteins of the nucleotide excision repair (NER) pathway, such as the XPD helicase and the lesion-binding protein, XPC, limit L1 retrotransposition. One hypothesis is that the NER pathway recognizes an L1 insertion intermediate as damage, disturbing the helical structure of the DNA, and recruits ERCC1-XPF to inhibit subsequent insertion. These data point to a new function for NER in the maintenance of the human genome integrity by controlling L1 proliferation.The L1 non-LTR retrotransposon is the most abundant and active mobile element in the human genome. About 34% of the human genome is a consequence of L1 element activity. Moreover, L1 has been shown to cause genetic disorders and tumorigenic diseases by local genomic destabilization. Two talks focused on how mammalian cells have adopted several strategies to restrict L1 mobility and potentially deleterious consequences of its uncontrolled retrotransposition. L1 replication by target-primed reverse transcription of its RNA generates a 3' flap intermediate at the insertion site, resulting from the elongation of the L1 cDNA. Gerald Schumann  showed that A3C-mediated L1 restriction requires both an intact dimerization site and a functional RNA-binding pocket domain of the protein. He found that L1 ORF1p and A3C are located in the same fraction after density gradient centrifugation of L1 ribonucleoprotein particles (RNPs). Co-immunoprecipitation experiments confirmed a direct interaction of L1 ORF1p and A3C. L1 element amplification protocol (LEAP) assays using L1 RNPs from HeLa cells indicated that overexpression of A3C reduces the L1 reverse transcription rate by approximately 50%, consistent with the observed inhibition of L1 retrotransposition by 40 to 60%. He proposed that A3C-mediated L1 restriction occurs via a cytidine deaminase-independent mechanism, based on an L1 mRNA-bridged interaction with L1 ORF1p, which inhibits the processivity of L1 reverse transcriptase (RT).Human APOBEC3 (A3-A to A3-G) cytidine deaminase proteins also contribute to intracellular defense against retroelements and inhibit L1 retrotransposition. However, genomic L1 retrotransposition events that occurred in the presence of L1-inhibiting A3 proteins are devoid of expected G-to-A hypermutations in L1 DNA, suggesting a deaminase-independent mechanism that restricts L1. Mike Cowley  reported how imprinted retrogenes located within introns can control the choice of host-genes mRNA polyadenylation (poly(A)) sites. Transcription of the expressed retrogene correlates with host gene transcripts using poly(A) sites upstream of the retrogene insertion, whereas the silenced retrogene allele is associated with the use of downstream poly(A) sites. He proposed that intronic imprinted retrogenes might inflict alternative poly(A) sites on the host gene, possibly through a transcriptional interference mechanism, which may impact on the protein-coding capacity of the host gene. These intronic retrogenes also provide some of the first experimental examples of epigenetic marks influencing alternative polyadenylation.Retrogenes arise by L1-mediated retrotransposition of genomic DNA and are potentially imprinted . Constance Ciaudo  reported that L1 elements are regulated during mouse ES cell differentiation. L1 elements are strongly upregulated in RNA interference (RNAi) mutants at both mRNA and protein levels, and their copy number increases in Dicer mutants indicating an active retrotransposition. She demonstrated that Dicer is involved in regulation of L1 promoter activity. Using deep sequencing approaches, she reported the identification of small RNAs derived from young active L1 elements. These small RNAs are produced via RNA degradation pathways and are loaded into Argonaute complexes. She proposes that these small RNAs could be primal RNA involved in the epigenetic regulation of L1 elements.Finally, Drosophila melanogaster, its differences with somatic lineages and its potential impact in the progeny.Over the last decade, mechanisms of epigenetic regulation controlling TE activity have been extensively analyzed with numerous models species. Three talks focused on the silencing exerted on TEs in the germ line of Yikang S. Rong  reported that Drosophila telomeric retroposons are an excellent system to study interactions between host and TEs. When analyzing their targeting to chromosome ends, he showed that these elements are under multiple modes of host regulation: in the germline, expression from the elements is suppressed by Piwi-interacting RNAs involved in the so-called piRNA pathway while in the soma, cell cycle-specific regulation limits their expression to a narrow window of the S-phase. Furthermore, the retrotransposon machinery forms large spherical structures encapsulating multiple chromosome ends suggesting an important role in telomere maintenance for the host.Kirsten-Andre Senti  used tissue-specific RNAi to separately and specifically knockdown several piRNA pathway components in the Drosophila soma and germline. RNA sequencing (RNA seq) was then performed from ovary samples and from early embryos. This systematic analysis showed that the Drosophila piRNA pathway prevents access of TEs to the next generation, provides an annotation of the active elements repressed by the piRNA pathway, and will serve as a starting point to understand the complexity of the piRNA pathway at the transition between the female gonad and the next generation.Drosophila against the deleterious effect of TE in the germline, Emilie Brasset  reported the identification of a small window during cyst mitosis in the ovary, when Piwi expression is impaired. In these germinal cells, piRNA silencing is less efficient, offering a short period during which TEs can escape from host restraint and expand.Although the piRNA pathway protects Stéphane Ronsseray , in collaboration with the group of Christophe Antoniewski , reported a case of stable paramutation, which takes place in the Drosophila female germline. This paramutation was discovered using a homology-dependent silencing induced by P-element-derived transgenes and provides a genetic model for transgenerational repression of TEs.A paramutation is an interaction between two alleles of a locus, through which one allele induces a heritable modification of the other allele without modifying the DNA sequence. The group of Thierry Lagrange  reported that ARGONAUTE4 binds 24-nt siRNAs and interacts with several RdDM components through evolutionarily conserved GW-rich motifs, called AGO hooks. Functional analysis of NERD, a novel AGO hook protein, demonstrated that Arabidopsis harbors a second siRNA-dependent DNA methylation pathway that targets a subset of loci, including non-annotated intergenic regions and TEs. The NERD pathway differs from RdDM by relying on 21-nt siRNAs and silencing-related factors so far implicated in post-transcriptional gene silencing (PTGS), including RNA-dependent RNA polymerase1/6 and ARGONAUTE2. Their results uncover a conserved chromatin-based RNA silencing pathway encompassing both PTGS and transcriptional gene silencing (TGS) components in plants that targets transposable elements.In plants, the RNA-directed DNA methylation (RdDM) pathway triggers DNA methylation and gene silencing at repeated loci by 24-nt small interfering RNAs (siRNAs). TE evolution is strongly coupled to evolution of their host genomes. The session ‘Evolution of transposable elements’ included issues regarding features of host genomes related to TEs, the evolution of TE sequences, the way TEs have been horizontally transferred between organisms, and how TE evolution drives host evolution.Brandon Gaut  showed that, in plants, methylation of genes flanking TEs is negatively correlated with their expression. TE silencing by methylation appears to be the cause of this phenomenon and, as such, methylation is a trade-off that benefits a plant by reducing TE activity but has the potential negative effect of perturbing gene expression. The implication of TE methylation on methylation of flanking genes was investigated by contrasting gene expression between orthologs that do or do not differ in the presence of a nearby (flanking) TE. The negative correlation between flanking methylation and gene expression appears to be a general feature of plant genomes, as demonstrated in grass (Poaceae) species. However, the strength of this correlation appears to vary between plant genomes, perhaps due to species differences in epigenetic response or strength of selection associated with that response. Interaction between TEs, methylation and gene expression likely plays a critical role in shaping the evolution of plant genome size and structure across angiosperms. Despite the fact that the mechanism that causes suppression of gene expression is unknown, it is possible that heterochromatic markers extend beyond the borders of some TEs to affect gene expression.TEs very often behave as deleterious elements, and it is expected that selection will lead to their elimination from genomes. Although epigenetic mechanisms, such as DNA methylation, maintain a control over TE activity, it is less clear how epigenetic control of TEs may affect nearby genomic regions. Harmit Malik , in the context of an evolutionary arms race between host and viral genomes. Interaction between poxvirus K3L and the host protein kinase R (PKR) was used as a model system for studying host proteins challenged by viral mimicry. Poxviral K3L mimics the conserved substrate of PKR . PKR has evolved under intense episodes of positive selection in primates, allowing it to evade antagonism by K3L. Thus, vaccinia K3L cannot defeat human PKR. In an experimental evolution system, vaccinia viruses rapidly acquired higher fitness via recurrent K3L gene amplifications to defeat PKR. These expansions also facilitated the gain of an adaptive amino acid substitution in K3L to defeat PKR. Poxviral ‘gene-accordions’ explains how poxviruses can rapidly adapt to defeat different host defenses despite low mutation rates.Another type of interaction between host genomes and mobile genetic elements was illustrated by Aurélie Kapusta  presented data on how bats may maintain relatively small genomes with high rates of DNA loss that counteracts TE invasions. While no activity has been reported in other mammals, vesper bats show recent waves of DNA transposon activity and therefore offer an unprecedented opportunity to study DNA transposon dynamics, regulation and genomic impact in one of the most extraordinarily species-rich group of mammals. Bats may keep their genomes slim thanks to a balance between moderate TE activity and high rate of DNA loss (via medium-size or large deletions). Intense genome contraction throughout bat evolution supports the idea that flight imposes a constraint on genome size.Claudia Carareto  presented data on TEs from Drosophila melanogaster and D. simulans supporting the hypothesis of horizontal transfer between these two species. The full-length Bari and 412 copies in D. melanogaster appeared to be exclusively derived from D. simulans suggesting either that D. melanogaster did not inherit active copies from a common ancestor, or could have lost them early during its diversification. Bari and 412 appeared to have been reintroduced into D. melanogaster before the expansion of both species out of Africa , when D. melanogaster and D. simulans were in sympatry in mainland Africa. Species of the genus Zaprionus and of the melanogaster subgroup share the same age of origin and diversification in tropical Africa. The use of phylogenetic networks can resolve relationships among low diversity sequences, and can be used to infer the origin of multiple copies from a unique sequence, revealing relationships between ancestral and derived sequences.Horizontal transfer of TEs between different species has often been reported and recent developments in sequencing technologies now allow us to test different hypotheses of gene transfer on an unprecedented scale. Jean-Michel Drezen  discussed an illustration of this type of system. Functionally, bracovirus particles are gene transfer agents produced in the ovaries of parasitoid wasps. They are injected into the parasitized butterfly host and they ensure the production of virulence proteins by the host, altering its immune defenses. The DNA molecules packaged in the particles are produced from a proviral form integrated in the wasp genome, which constitutes a large target (≈1 megabase) for TE insertions. Remnants of retroelements and large DNA transposons  were identified in the Cotesia congregata bracovirus (CcBV) genome. DNA circles packaged in the particles were recently shown to integrate into lepidopteran host DNA and analysis of a wasp genome revealed that reintegration of circles back into wasp DNA can also occur. Thus, bracovirus circles can navigate between genomes of different insect orders and are potential vehicles for genetic exchanges between genomes including TE transmission. Since several lepidopteran genomes have recently become available, it is now possible to evaluate the extent of bracovirus contribution to TE horizontal transfers between Hymenoptera and Lepidoptera.The way TEs are horizontally transmitted between species is still a matter of discussion. Genome comparisons involving different interacting partners could give us indications on the way TEs are transferred. Richard Cordaux , bacterial genomes usually experience high sequence turnover and short TE retention times, obscuring ancient TE evolutionary patterns. The genomes of six Wolbachia bacterial endosymbionts revealed the presence of numerous IS copies. IS account for >14% of Wolbachia wVulC genome, one of the highest IS genomic coverages reported in prokaryotes to date. Several processes may explain TE abundance in Wolbachia, including recent activity, along with recurrent invasions through horizontal transfers and gene conversion. Remarkably, 60 to 100% of IS within each Wolbachia genome are non-functional that is, have undergone or are undergoing decay. This can be explained by the particular lifestyle of Wolbachia endosymbionts, which exhibit reduced effective population sizes, relative to free-living bacteria, leading to relaxed efficiency of selection and enhanced genetic drift. The outcome for IS is fast fixation followed by slow removal via small deletions. This contrasts with free-living bacteria in which efficient negative selection leads to fast removal of IS. Non-functional IS constitute an unusual bacterial IS genomic fossil record providing direct empirical evidence for a long-term IS evolutionary dynamics following successive periods of intense transposition activity. Identification of an important IS genomic fossil record in Wolbachia demonstrates that IS are not always of recent origin, contrary to the conventional view of TE evolution in prokaryote genomes.The evolution of TEs can be very different depending on the host genomes. As reported by Drosophila. Pierre Capy  presented an analysis of class II elements (DNA) indicating that most of the internal deletions that were identified in these TEs occurred between short regions (from 2 to 11 bp) exhibiting microhomologies. One hypothesis is that these internal deletions are due to errors in DNA double-strand break repair after excision of the TEs. It is tempting to propose that this system may be at the origin of miniature inverted-repeat transposable element (MITE) elements.TE evolution and decay has also been documented in other genomes such as those of Drosophila, the class I (RNA) HeT-A telomeric retrotransposons was reported by Elena Casacuberta . Her results showed a 28-nucleotide sequence in the 3′ UTR region to be the most conserved sequence of the element within and among closely related species. This short sequence has been named HeT-A_pi1 since pairs of sense and antisense piRNA sequences have been detected in piRNA libraries of D. melanogaster. The high degree of conservation found in the piRNA target HeT-A_pi1 sequence suggests an important function of this sequence in the co-evolution of this TE and the Drosophila genome.Analysis of other elements from Eric Meyer  for Paramecium tetraurelia mating type determination, one of the oldest known cases of ‘transgenerational epigenetic inheritance’. Mating type O is determined during development of the somatic macronucleus by the excision of the promoter of the mtA gene, which encodes a mating type E-specific transmembrane protein. Maternal inheritance of mating types is mediated by the scan RNA (scnRNA) pathway, a piRNA-like class of small RNAs required to eliminate TEs during macronuclear development. These RNAs target any sequence absent from the maternal macronucleus (through a process known as ‘genome scanning’) and assure their elimination. In the sibling species Paramecium septaurelia, mtA is also an E-specific protein and maternal inheritance of mating types is also due to a maternally inherited alternative rearrangement of the genome. However, the O type is determined by a deletion of part of mtB, encoding a transcription factor required for mtA expression, rather than by deletion of the mtA promoter. These examples illustrate the flexibility with which the scnRNA pathway is naturally used to maintain an essential phenotypic polymorphism in populations of genetically identical cells.Small RNAs may play important functions in gene regulation in many other organisms. This was illustrated by Astrid Engel  reported the reconstruction of the consensus sequence of two ancient extinct L1 subfamilies from primate genomes (40 and 25 million years old) and demonstrated that they were both retrotranspositionally active and can support the retrotransposition of old and young Alu subfamilies at different levels of efficiency. The use of different cell lines showed that cellular factors significantly affect L1 retrotransposition efficiency of the older L1 element and that these factors have likely had a significant effect on L1 element evolution.Long-term TE evolution can readily be reconstructed in mammals thanks to many degraded copies constituting genomic fossil records of past TE proliferations. Mojca Tajnik  reported that Alu exonization contributes to transcriptome diversity via alternative splicing. By using quantitative UV-crosslinking and immunoprecipitation (iCLIP) and RNA seq methods, the heterogenous nuclear ribonucleoprotein C1/C2 (hnRNP C) was identified as a silencer of antisense Alu element exonization. The mechanism of silencing was studied through competition of hnRNP C and the core splicing factor U2AF65 for binding on polypyrimidine tracts, using reporter minigene assays with introduced single-nucleotide substitutions and disease-related mutations in polypyrimidine tracts. This study revealed a new mechanism for maintaining transcriptome integrity via repression of the cryptic Alu exons.Also in primates, The session on transposition mechanisms included talks, which addressed cellular control of transposon integration, transposase oligomerization and the control of transposition, mechanisms of reverse transcription and retrotransposition and transposase domestication and genome dynamics.Vincent Parissi  presented studies on the integration of human immunodeficiency virus (HIV) and prototype foamy virus (PFV) retroviruses. He described the effect of nucleosome positioning in vitro on concerted (double end) integration using purified components. HIV integration into stable nucleosomal regions was reduced, but this inhibition was partially alleviated by the ATP-dependent chromatin-remodeling complex SWI/SNF known to interact with the retroviral integrase IN. This is consistent with high throughput sequencing studies indicating that HIV integration is enriched in nucleosome-poor regions. On the other hand, integration of PFV was shown to be significantly less sensitive than HIV to the presence of stable nucleosomes. This pattern is consistent with the DNA bending  required for PFV integration but not for that of HIV.Bernard Hallet , for the bacterial Tn4430 transposon, a member of the Tn3 family whose transposase, like retroviral IN, belongs to the DDE superfamily. Tn4430 transposes using a replicative cointegration mechanism and its insertion appears tightly coupled to target DNA replication. Slowing down the target replication fork results in preferential upstream insertions. Moreover, Tn4430 transposase binds with high affinity to artificial DNA forks in vitro and uses these as a specific target for joining the transposon ends. The data suggest a ‘replication fork hijacking’ mechanism whereby Tn4430 would recruit the cellular replication machinery by jumping into replication intermediates.Control of integration was also addressed by Bao Ton-Hoang , who showed that the single strand DNA insertion sequence, IS608, which uses tyrosine rather than DDE chemistry for transposition, is excised from and inserts preferentially into the lagging strand template of both plasmid and chromosomal replication forks. Its transposase, TnpA, also localizes to blocked replication forks in vivo and preferentially binds branched DNA structures in vitro, such as forks, D-loops and Holliday junctions, suggesting a mechanism for assuring transposition activity at the fork.The theme was also taken up by Ronald Chalmers  described a model explaining overproduction inhibition (OPI), a phenomenon observed for several eukaryotic transposons where high levels of transposase result in a reduction in transposition activity. Using the human mariner TE, Hsmar1, he provided strong biochemical support for a model in which the key controlling element is a transposase dimer, which first binds a single transposon end via one of the component monomers before using the second to bind the other end to form an active transpososome. OPI is proposed to arise from occupation of each end of the transposon by a transposase dimer, preventing formation of the transpososome. The model was rigorously tested using computer simulations. It can be used to explain the strong tendency for TEs to undergo decay in eukaryotes.Two presentations addressed the role of transposase oligomerization in regulating transposition. Fred Dyda  presented a set of crystallographic structures of the transposase of another eukaryotic TE, Hermes belonging to the hAT family. He identified an octomeric unit in which four dimers are intertwined via their C-terminal domains. This was found to have limited activity in vitro. However, the structure predicts that removal of an α-helix should destroy the interface holding the octomer together and result in the formation of transposase dimers. It was observed that such deletions render the transposase hyperactive in vitro. Although the exact details remain to be elucidated, it seems probable that the ‘closed’ octomeric form may represent a downregulated transposase species.Thomas Eickbush  presented the results of studies of R2 non-LTR retrotransposons. These elements integrate in a sequence-specific way into 28S RNA genes by target-primed reverse transcription (TPRT). R2 RNA, the transposition intermediate, is processed from a 28S/R2 cotranscript by a self-cleaving ribozyme located at the 5' R2 RNA end. Eickbush has now shown that this activity is present in all R2 elements from Drosophila to hydra. The position of cleavage varies from organism to organism and determines insertion site selectivity. When cleavage occurs within the 28S RNA moiety, subsequent insertion into a 28S DNA target is precise - presumably due to base pairing between the 28S gene and the remaining 28S RNA sequence attached to the R2 transcript. For those organisms in which cleavage occurs at the exact R2-28S RNA junction, insertion shows addition of non-templated nucleotides. Eickbush also localized by mutagenesis the RNA binding domain of the R2 protein in a region upstream of the reverse transcriptase domain conserved in other non-LTR retrotransposons and in telomerase.A third theme of this session was the mechanism(s) involved in reverse transcription and retrotransposition. Clement Monot  has developed a direct reverse transcriptase assay with native L1 RNP for studying the initiation of reverse transcription. Using this system, he defined the preferential rules of L1 reverse transcription initiation. He showed that efficient priming can be achieved with as little as four matching nucleotides at the primer 3' end, but also that the L1 RNP can tolerate terminal mismatches if compensated by an increased number of upstream matching nucleotides. Based on these data, he proposed that the terminal bases of the primer act as a specific snap and the upstream ones as a weaker ‘velcro strap’ allowing efficient and flexible retrotransposition into imperfect AT-rich regions as observed in mammalian genomes.In contrast to R2, mammalian LINEs, such as L1, do not integrate in a specific locus. Most L1 insertions occur in the highly frequent A/TTTT motif. However, individual sites are often degenerate and contain much longer stretches of AT-rich sequences. The L1 machinery is a ribonucleoprotein particle (RNP), which contains an additional RNA-binding protein, ORF1p, encoded by the L1 element. Alan Schulman  described in vivo studies with the BARE LTR-retrotransposons. These elements produce several RNA populations: one that is capped, polyadenylated, and translated but cannot be reverse transcribed; another that is not capped or polyadenylated, but packaged into virus-like particles (VLPs) and reverse transcribed; and a third which is capped, polyadenylated and spliced to produce high amounts of Gag, the capsid protein that forms the VLPs. The relative amount of the spliced and unspliced forms varies from tissue to tissue. These data highlight a unique situation among the retroelements where distinct RNA pools are committed to translation (with or without splicing) or reverse transcription depending on post-transcriptional processing.Bao Ton-Hoang  presented evidence that an IS608-related tyrosine transposase has evolved to manage repeated extragenic palindromes (REP) sequences which are present in many bacteria in very high copy number and are involved in genome structure and gene expression. In Escherichia coli, only a single copy of the gene, tnpAREP, is present. It is located in an identical position in all strains. Phylogenetic evidence suggested that the gene arrived early in the radiation of E.coli and was later lost in some of the present clades. Purified TnpAREP protein exhibited catalytic activity. It is capable of sequence-specific cleavage and strand transfer of REP sequences. This would provide one of the first examples of transposase domestication in a prokaryote.The final theme of the session centered around transposase domestication and genome dynamics. Transib. Nancy Craig  presented a functional analysis of the Transib transposase and demonstrated that, like V(D)J recombination, Transib transposition passes through an intermediate involving formation of a DNA hairpin on the flanking DNA.Perhaps one of the most important examples of transposase domestication is that of the RAG proteins involved in generating V(D)J diversity. The RAG ancestor is thought to resemble the transposase of Martin Gellert , who presented data confirming that the ‘signal end’ complex within which the recombination reactions occur includes RAG1, RAG2, HMGB1 in a 2:2:1 stoichiometry. He also provided structural information from electron microscopy EM studies. This indicated a parallel anchor-shaped RAG1/2 complex with approximately 2-fold symmetry in which RAG2 is located at the head of anchor, RAG1 N-terminus at the ‘shank’ end, along with DNA chains beyond nonamers. Functional experiments showed that there is autoinhibition by interaction of RAG1 and RAG2 C-termini and that autoinhibition can be alleviated by binding a histone H3 tail peptide containing trimethylated lysine 4 (H3K4me3) and known to bind the PHD domain of RAG2 and to target it to recombinationally active loci. This is possibly the first known case where chromatin tethering activates an enzyme.The V(D)J system was addressed by Alexander Vogt , Vienna, Austria), described Tpb2p, a domesticated piggyBac-like transposase essential for the excision of internal eliminated sequences (IESs), an obligatory genome rearrangement in the Tetrahymena life cycle. The enzyme introduces a 4-bp staggered cleavage at an IES boundary in vitro. Mutagenesis of the boundary sequence revealed a crucial role for positions 2 and 3 after the cut (in vitro and in vivo). In addition, IES-specific heterochromatin seems to control cleavage site accuracy through a possible interaction between Tpb2p and H3K9me3. Thus both boundary sequences and heterochromatin interactions are probably involved in specifying precise IES excision.Ciliates have recently provided a novel illustration of the role played by domesticated transposases in developmentally programmed genome rearrangements. Mireille Bétermier  presented the analysis of a genome-wide set of IESs identified in Paramecium by high-throughput sequencing of DNA extracted from cells depleted in PiggyMac, the Tpb2p homolog responsible for IES excision in this ciliate. A vast majority of Paramecium IESs (93%) are shorter than 150 bp. Among the longest IESs, recognizable fragments of Tc1-like transposons were identified, indicating that PiggyMac excises DNA sequences unrelated to piggyBac. Again, this raises the question of how the domesticated transposase is targeted to its cleavage sites. The size distribution of Paramecium IESs exhibits a 10.2-bp periodicity that coincides with the helical phase of DNA. This may reflect DNA bending constraints on assembly of the IES excision complex. Evidence was presented for a requirement for Ku70/Ku80 before DNA cleavage, which would possibly favor the precise repair of IES excision sites by the NHEJ pathway.The tradition of a large international meeting on Transposable Elements will continue in 2014, in the USA. The venue and dates will be announced soon.Bp: base pair; ChIP-seq: chromatin immunoprecipitation followed by massive DNA sequencing; ERV: endogenous retroviruses; ES cell: embryonic stem cell; iCLIP: UV-crosslinking and immunoprecipitation; IES: internal eliminated sequence; IS: insertion sequence; LEAP: L1 element amplification protocol; L1: LINE-1; LTR: long terminal repeat; ORF: open reading frame; MITE: miniature inverted-repeat transposable element; NAHR: non-allelic homologous recombination; NER: nucleotide excision repair; NGS: next-generation sequencing; OPI: overproduction inhibition; piRNA: Piwi-interacting RNAs; PTGS: post-transcriptional gene silencing; RdDM: RNA-directed DNA methylation; REP: repeated extragenic palindromes; RIP: retrotransposon insertion polymorphism; RNP: ribonucleoprotein; RNAi: RNA interference; RNA seq: RNA sequencing; RT: reverse transcriptase; scnRNA: scan RNA; SHAPE: selective 2′-hydroxyl acylation analyzed by primer extension; siRNA: small interfering RNA; TAP: tandem affinity purification; TPRT: target-primed reverse transcription; TE: transposable element TGS, transcriptional gene silencing; TSS: transcription start site; UTR: untranslated region; VLP: virus-like particle.The authors declare that they have no competing interests.J-MD wrote Introduction and keynote lecture. OP, HQ and ClV wrote Session 1: Impact on genomes, PL and ChV wrote Session 2: Control of transposition, AA, RC and CrV wrote Session 3: Evolution of transposable elements, MB, MC and GC wrote Session 4: Mechanisms of transposition. All authors read and approved the final manuscript.Work in the laboratory of M. Bétermier is supported by intramural funding from Centre National de la Recherche Scientifique (CNRS) and by the Agence National de la Recherche (ANR) (grants ANR BLAN08-3-310945 ‘ParaDice’ and ANR 2010-BLAN-1603 ‘GENOMAC’). Work in the laboratory of M. Chandler is supported by intramural Centre National de la Recherche Scientifique (CNRS) funding and by ANR grant MOBIGEN. Work in the laboratory of G. Cristofari is supported by grants from the Institut National de la Santé et de la Recherche Médicale (INSERM) and the Institut National du Cancer , and the European Research Council . Work in the laboratory of P. Lesage is supported by intramural CNRS and INSERM funding. Work in the laboratory of C. Vieira is supported by the ANR Genemobile and the Institut Universitaire de France. Work in the laboratory of C. Vaury is supported by grants from INSERM, CNRS, the Université d’Auvergne and Région Auvergne.


The carbohydrate response element binding protein (ChREBP), a basic helix-loop-helix/leucine zipper transcription factor, plays a critical role in the control of lipogenesis in the liver. To identify the direct targets of ChREBP on a genome-wide scale and provide more insight into the mechanism by which ChREBP regulates glucose-responsive gene expression, we performed chromatin immunoprecipitation-sequencing and gene expression analysis. We identified 1153 ChREBP binding sites and 783 target genes using the chromatin from HepG2, a human hepatocellular carcinoma cell line. A motif search revealed a refined consensus sequence (CABGTG-nnCnG-nGnSTG) to better represent critical elements of a functional ChREBP binding sequence. Gene ontology analysis shows that ChREBP target genes are particularly associated with lipid, fatty acid and steroid metabolism. In addition, other functional gene clusters related to transport, development and cell motility are significantly enriched. Gene set enrichment analysis reveals that ChREBP target genes are highly correlated with genes regulated by high glucose, providing a functional relevance to the genome-wide binding study. Furthermore, we have demonstrated that ChREBP may function as a transcriptional repressor as well as an activator. Glucose is a vital energy nutrient that provides carbon for biosynthetic reactions and ATP for energy. Most organisms have evolved diverse and sophisticated mechanisms for sensing glucose and using it efficiently, including mechanisms for glucose-dependent regulation of gene transcription. In mammals, the molecular basis of glucose-regulated gene transcription was revealed by the discovery and characterization of the carbohydrate response element binding protein , which is a glucose-responsive transcription factor ob/ob mice alleviates obesity and corrects hepatic steatosis ChREBP is a basic helix-loop-helix leucine zipper transcription factor, mediating glucose-regulated gene transcription. Upon activation by glucose, ChREBP, whose expression is most prominent in the liver, translocates from the cytosol into the nucleus To fully understand the molecular basis of glucose-regulated gene transcription mediated by ChREBP, it is essential to identify ChREBP target genes and their roles. It is known that ChREBP regulates various enzymes involved in glycolysis and lipogenesis such as pyruvate kinase, liver and RBC (PKLR), acetyl-CoA carboxylase and fatty acid synthase (FASN) To identify the complete repertoire of ChREBP target genes, we treated HepG2 cells with 25 mM glucose for 8 h. This experimental condition was determined by time course experiments that measured the expression level changes of known ChREBP target genes in response to 25 mM glucose . FollowiChREBP binding sites and their associated genes were identified using PeakFinder ChREBP binding sites of representative ChREBP target genes, PKLR CACGTG, PWM score = 1) and the extended E-boxes , were identified in the ChREBP binding sites with strong enrichment . ChBM1 consists of a perfect E-box and an imperfect E-box separated by 5 nt (CABGTG-nnCnG-nGnSTG), resembling the ChoRE consensus sequence (CAYGNG-n5-CNCRTG) p<0.0001), ChBM1-derived sequence (CACGTG GCCGG CGCGTG) was found to be present in 39.3%  of the 1153 peaks. The second motif, termed as ChREBP binding motif 2  is present in 1152 peaks . Sequence-wise, ChBM2 significantly differs from known ChREBP binding sites. Therefore, rather than being a direct binding site for ChREBP, ChBM2 may represent binding sites for ChREBP–associated proteins. TOMTOM analysis, which compares a novel motif with known DNA-binding motifs in TRANSFAC motif database p = 1.2e−04, false-discovery rate (FDR) = 0.042].To search for enriched motifs in the peaks from the ChIP-seq dataset, we used the motif finding program W-ChIPMotifs richment . Two novrichment . The firbona fide binding sites of ChREBP, we performed electrophoretic mobility shift assay (EMSA). HEK293 cells were transfected with expression vectors of ChREBP and heterodimer partner Mlx and nuclear extracts were prepared. Nuclear extracts were incubated with a radiolabeled oligonucleotide containing ChBM1 or ChBM2 sequence , supporting the central role of ChREBP in lipid metabolism. Further investigation of ChREBP target genes involved in this pathway identified the key enzymes of gluconeogenic pathway, such as phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase catalytic subunit (G6Pase). This result indicates that ChREBP may work as a dual regulator of lipogenesis and gluconeogenesis, which have a reciprocal relationship in response to glucose . The comparison of expression profiles between no- and high-glucose conditions revealed that expression levels of 1822 genes were significantly changed by high glucose.p = 1.5e−11). Thus, the distinct possibility exists that the ChIP-seq identified sites correspond to functional sites of ChREBP action.To compare the list of ChREBP target genes from the ChIP-seq dataset with the gene expression profiling dataset, the expression profiling dataset was rank-ordered by fold change such that the most highly up-regulated genes under the high glucose condition were at the top of the ranked list . InteresTo further validate the relationship between ChREBP binding and glucose-dependent gene regulation, the expression levels of several genes including PKLR, TXNIP, sterol regulatory element binding protein-1c (SREBP-1c), diacylglycerol O-acyltransferase homolog 2 (DGAT2), pyruvate dehydrogenase kinase isozyme 2, INHBE, PEPCK, and solute carrier family 6 member 9 (SLC6A9) were determined by reverse transcription/quantitative real-time PCR (qRT-PCR). The binding of ChREBP to these genes was already confirmed by ChIP-qPCR  and S2. The aim of the present study was to identify the direct targets of ChREBP on a genome-wide scale and to understand the underlying mechanism of glucose-responsive gene regulation by ChREBP. ChIP-seq analysis revealed that ChREBP binds to 1153 sites across the genome, 45% of which are located in potential gene regulatory regions including proximal/distal promoters, 5′ UTRs, and the first/second introns of known genes. In addition, the present study showed that the majority of the ChREBP binding sites identified by the ChIP-seq analysis are functionally important in mediating glucose-responsive gene expression with ChREBP acting as either an activator or a repressor.As mentioned above, 45% of ChREBP binding sites are closely associated with TSSs, yet the rest are remotely associated with TSSs. Previous genome-wide localization analysis of other transcription factors such as Foxa2, ERα, Myc, and PPARγ/RXR also revealed that transcription factor binding sites can be localized to regions other than the 5′-proximal promoter regions, such as far upstream sequences, introns, and 3′ region of the gene CAYGNG-n5-CNCRTG by analyzing functional ChoRE sequences from seven different genes. According to the authors, the heterotetramer formation between ChREBP/Mlx heterodimers is essential to stabilize their binding to the tandem E box-like sites (two imperfect CACGTG motifs) in ChoRE. In addition, the stringent spacing between E boxes within ChoRE is critical for the transcriptional response to glucose CABGTG-nnCnG-nGnSTG), similar to the ChoRE consensus sequence, was predicted from ChREBP binding sites identified in the present study. When ChREBP binding sites were scanned with ChBM1 for further refinement of the consensus sequence using a more stringent cut-off (p<0.0001), a new ChBM1-derived sequence (CACGTG GCCGG CGCGTG) was acquired as a consensus sequence, which is present in 39.3%  of the 1153 peaks. The overall structure of this ChBM1-derived sequence is precisely matched to that of ChoRE consensus sequence, but with more details.ChREBP forms a heterodimer with Mlx to bind to ChoRE. Ma and colleagues GGGGNRGGGSAGGGRGN), one of the major binding motifs, significantly differs from known ChREBP binding sites and no direct ChREBP binding to ChBM2 was observed in EMSA (ChBM2 ( in EMSA . This map = 1.5e−11). Although many ChREBP target genes were upregulated as expected given the known role of ChREBP in activating glycolytic and lipogenic genes, especially in the liver in vivo evidence that ChREBP may play a repressive role in glucose responsive transcription.Gene set enrichment analysis using the modified KS test revealed a high degree of correlation between ChREBP binding and ChREBP-dependent gene expression when HepG2 cells are subjected to high glucose conditions  293 cells were obtained from the American Type Culture Collection  and maintained in 25 mM glucose Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 100 U/ml penicillin/streptomycin. For ChIP-seq and gene expression profiling, HepG2 cells (passage 8–10) were cultured in 2.7 mM glucose DMEM with 10% FBS for 16 h and then cultured in 0, 2.7, or 25 mM glucose medium for an additional 8 h.To obtain nuclear extracts for gel shift assays, HEK293 cells were transfected in 100 mm plates using Lipofectamine (Invitrogen) according to the manufacturer's directions. Ten µg each of expression plasmids of ChREBP and Mlx were cotransfected. Nuclear extracts were prepared from cells 48 h post-transfection using the ‘nuclear cell extract’ protocol in the Nuclear Extract kit from ActiveMotif (Carlsbad. CA).7 cells) previously cultured in 2.7 mM or 25 mM glucose for 8 h were cross-linked with 1% formaldehyde for 30 min at 37°C. The cross-linking time was optimized using two parameters: average size of DNA after shearing and analysis of the immunoprecipitation efficiency by PCR. Cross-linking was stopped by the addition of glycine to a final concentration of 0.125 M. The cells were washed three times with ice-cold phosphate-buffered saline and kept on ice for 10 min in 25 mM HEPES (pH 7.8), 1.5 mM MgCl2, 10 mM KCl, 0.1% Nonidet P-40, 1 mM dithiothreitol, 0.5 mM phenylmethylsulfonyl fluoride, and protease inhibitor cocktail . Nuclei were collected and resuspended in sonication buffer for 30 min on ice and sonicated on ice to an average length of 200 bp using a tissue lyser set at 50% amplitude. After sonication, the chromatin solution (500 µg) was incubated with Dynabeads protein A  and 5 µg of rabbit anti-ChREBP  or 5 µg of rabbit normal IgG  at 4°C overnight. Antibody-bound complexes were obtained and DNA fragments extricated from these complexes were purified using a QIAquick PCR Purification Kit . The purified ChIPed DNA samples were analyzed by qPCR using an Applied Biosystems Prism 7900HT sequence detection system  and SYBR-Green chemistry as described ChIP assays were performed as previously described For ChIP-seq library construction, ChIPed DNA was end-repaired, ligated to adaptors, and amplified. Amplified fragments of about 300 bp (with adaptors) were gel purified from 2% agarose and used for sequencing on GAII  according to the manufacturer's instructions. Sequence reads were mapped to the human reference genome using MAQ http://david.abcc.ncifcrf.gov/) All ChREBP binding sites were assigned to nearest genes based on the Homo sapiens NCBI Build 36.1 genome assembly . GO analysis for ChREBP target genes was conducted using the NIH Database for Annotation, Visualization, and Integrated Discovery  was combined with 5–10 µg of nuclear extract from HEK293 cells in 75 mM of KCl, 7.5% (v/v) of glycerol, 20 mM of HEPES (pH 7.4), 0.1% (v/v) of Nonidet P-40, and 2 mM of dithiothreitol. The nonspecific competitors, 2 µg of poly dI-dC (Amersham Biosciences) and 20 pM of nonspecific antisense oligonucleotide were added in each binding reaction. Following incubation with the labeled probe for 30 min on ice, samples were subjected to electrophoresis on a 4.5% nondenaturing polyacrylamide gel. For reactions with antibodies, nuclear extract was preincubated with antibody for 30 min on ice before addition of the probe. For competition assays, a 10- or 50-molar excess of various unlabeled competitor DNAs was added to the reaction mixture prior to the addition of the probe. Results were visualized by autoradiography.in vitro transcription using the Illumina total prep RNA amplification kit  according to the manufacturer's instructions. Biotinylated cRNAs were then hybridized to an Illumina HumanHT-12 BeadChip. Microarray data were normalized and assessed for differential expression using the LIMMA component (Linear Models for Microarray Data) of the Bioconductor package http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi) under accession number GSE22074.Total RNA from HepG2 cells was prepared using a Qiagen RNeasy Kit. Total RNA from six biological replicates under 0 or 25 mM glucose conditions were then amplified into cRNA and biotinylated by The ChIP-seq data were compared with expression microarray data using a KS plot, which is a modified method of gene set enrichment analysis (GSEA) 5′-GGUAU AUCCA GUAUG UGAAU U-3′; antisense, 5-UUCAC AUACU GGAUA UACCU U-3′) was purchased from Genolution . Briefly, 1×105 cells, 20 nM of RNAi medium, and 20 nmol of each ChREBP siRNA or scrambled RNA incubated in serum reduced OPTI-MEM for 10 min and were plated in 12-well plates. The cells were cultured in 2.7 mM glucose DMEM for 40 h and then cultured in 25 mM glucose medium for an additional 8 h. The cells were lysed and total RNA was extracted.HepG2 cells were transfected with siRNAs using RNAiMAX according to the manufacturer's directions (Invitrogen). A scrambled siRNA  was purchased from invitrogen and a siRNA for human ChREBP . Two micrograms of total RNA was treated with RNase-free DNase (Roche) and reverse transcribed using SuperScript II (Invitrogen) and random hexamers. Gene-specific primers were designed using Primer Express Software  and validated by analysis of template titration and dissociation curves. Primer sequences are provided in Figure S1Determination of the optimal condition for ChREBP activation in HepG2 cells. HepG2 cells were cultured in 2.7 mM glucose DMEM for 16 h and then cultured in high (25 mM) glucose medium for an indicated time. Total RNA was extracted and the PKLR and FAS gene expression was determined by qRT-PCR. Expression levels were normalized to expression of cyclophilin. Values represent the mean of triplicate samples ± S.D.(TIF)Click here for additional data file.Figure S2Validation of ChIP-seq binding sites by single gene ChIP-qPCR. ChIP-qPCR was performed on ChREBP-enriched chromatin prepared from high glucose-treated HepG2 cells. All randomly selected sites were validated by single gene ChIP-qPCR. Positive control region (PKLR) and negative controls  were included.(TIF)Click here for additional data file.Table S1The peak location and the nearest gene list. The nearest genes to the ChREBP binding peaks are listed.(PDF)Click here for additional data file.Table S2Functional annotation clustering of the ChREBP ChIP-seq dataset. To reduce redundancy, the newly developed functional annotation clustering report groups and displays similar annotations together to make the biology clearer and more focused for reading when compared to a traditional chart report. For annotation clustering, we used GOTERM_BP_ALL, GOTERM_MF_ALL, PANTHER_BP_ALL, and PANTHER_MF_ALL.(PDF)Click here for additional data file.Table S3Primer sequences for the measurement of human DNA or RNA using an ABI Prism 7900HT system. All primers are listed in the 5′ to 3′ orientation.(PDF)Click here for additional data file.


FLC expression by vernalization (extended cold) has become a model for understanding polycomb-associated epigenetic regulation in plants. Antisense and sense non-coding RNAs have been respectively implicated in initiation and maintenance of FLC repression by vernalization. We show that the promoter and first exon of the FLC gene are sufficient to initiate repression during vernalization; this initial repression of FLC does not require antisense transcription. Long-term maintenance of FLC repression requires additional regions of the gene body, including those encoding sense non-coding transcripts.The repression of Arabidopsis  FLC gene is a repressor of flowering that confers a requirement for vernalization  to promote flowering in spring FLC encodes a MADS box protein that binds to and represses expression of the floral promoting genes FT and SOC1FLC by a plant homeodomain-polycomb repressive complex 2 (PHD-PRC2) mechanism FLC locus. Detailed studies of the timing of changes in FLC mRNA expression and H3K27me3 levels showed that transcription of FLC is repressed and H3K27me3 increases at a region around the transcription start site during the cold FLC transcription FLC expression and reduced repression of FLC after vernalization FLC locus is important in down-regulating its expression pre- and post-vernalization. Experiments to define the parts of the FLC gene mediating the different phases of the vernalization response showed that the promoter and first exon are sufficient to confer repression of a reporter gene during vernalization, but maintenance of repression after return to warm conditions requires the first intron in addition to the promoter and exon 1 FLC gene fragment including approximately 1.8 kb of FLC intron 1 and the remainder of the 3′ end of the gene recruits PRC2 and H3K27me3 in the absence of transcription FLC repression after vernalization.The Arabidopsis HOTAIR, which targets PRC2 to the HoxD locus, and is associated with HoxD silencing in humans FLC locus have been identified. The COOLAIR antisense transcripts originate from a promoter adjacent to the FLC 3′ untranslated region and consist of two classes, terminating at proximal or distal sites  originating from a region within the first intron of FLCCOLDAIR transcript has been shown to interact with PRC2 and its abundance also increases during vernalization. Reduction of COLDAIR transcript levels by RNAi showed that it is not required for the initial repression of FLC but is required for subsequent maintenance of repression.A complex array of non-coding RNAs is transcribed from eukaryotic genomes, the majority of which are of unknown function. Some long non-coding RNAs (lncRNAs) associate with and target protein complexes to regulate gene expression al sites Figure 1COOLAIR antisense transcripts in the initial vernalization-induced repression of FLC and the results of reporter gene studies we used FLC insertion mutants to test the role of these transcripts in FLC repression.As there are apparent contradictions in the proposed role of the FLC promoter and first intron are required for the stable vernalization-mediated down-regulation of a reporter gene we tested the effect of a Ds insertion of approximately 6 kb (flc-20) that separates these regions in the endogenous FLC gene FLC 5′ unspliced transcript as an approximation of transcription rate flc-20 mutant that was not maintained after plants were returned to warm conditions  in both C24 and flc-20 at the end of cold, but this increase is not maintained in flc-20 after return to warm temperatures .As the flc-20 mutant together with previous data from FLC reporter constructs raised the question of whether antisense transcription from the COOLAIR promoter is a requirement for vernalization-induced repression of FLC. To test this we carried out further experiments with T-DNA insertions close to the 3′ end of the FLC gene that disrupt the distal (SALK_092716) or both proximal and distal (SALK_140021) antisense transcripts , with the exception of regions 3′ of the SALK_092716 insertion which had high H3K27me3 under all conditions as seen previously for non-transcribed parts of FLCThe data from the COOLAIR transcripts is not an essential component of vernalization-induced repression of FLC. The observations presented here for these SALK lines are in agreement with previous results showing that sequences consisting of the promoter, exon 1 and intron 1 but not the COOLAIR promoter, are sufficient to confer stable repression on a reporter gene COOLAIR lncRNAs may play a redundant role in regulating FLC expression, our data shows that they are not required for the vernalization response.These data show that the production of COLDAIR lncRNA acting to maintain repression of FLC by recruiting the PRC2 machinery COLDAIR transcript and all show maintenance of repression after vernalization.Our data are consistent with the FLC, we measured 5′ unspliced FLC transcripts in the swn7clf28 double mutant and in the vin3-4 mutant. CLF and SWN encode histone methyl transferases components of PRC2; loss of function of these genes leads to a genome-wide loss of H3K27me3 swn7clf28 plants have increased 5′ unspliced FLC transcript in non-vernalized plants and show a similar fold-repression as ColFRI during 4 weeks of cold exposure  and crossed with ColFRI, a Col line with an active FRI allele FRI allele activates expression of FLC. PCR was used to identify F2 plants in which the active FRI allele and the T-DNA insertions were homozygous. The flc-20 mutant contains a modified Ds element inserted in the first intron of FLCSalk insertion mutants were obtained from the Arabidopsis Stock Center . Primers used are listed in Table S1. PCR were reactions carried out in quadruplicate, quantified using a standard curve of diluted cDNA and normalized to At4g26410 RNA was extracted using Qiagen Plant RNeasy Mini columns with an on-column DNase treatment according to the manufacturer's protocol. cDNA was synthesized using Superscript III (Invitrogen), primed with oligo dT  or with gene specific primers for the Table S1.Chromatin immunoprecipitation was carried out and amplicons for ChIP-qPCR are as described Figure S1H3K27me3 ChIP qPCR across FLC in C24 and flc-20. ChIP qPCR for amplicons 1–12 flc-20 plants grown for 12 long days (12LD), 12 long days followed by 4 weeks at 4°C (12+4V) or 12 long days, 4 weeks at 4°C followed by 2 long days (12LD+4V+2LD).(TIF)Click here for additional data file.Figure S2H3K27me3 ChIP qPCR across FLC in ColFRI, SALK_092716, SALK_140021 and SALK_131491. ChIP qPCR for amplicons 1–12  in ColFRI, SALK_092716, SALK_140021 and SALK_131491 plants grown for 12 long days (12LD), 12 long days followed by 4 weeks at 4°C (12+4V), 12 long days, 4 weeks at 4°C followed by 2 long days (12LD+4V+2LD) or 12 long days, 4 weeks at 4°C followed by 5 long days (12LD+4V+5LD).(TIF)Click here for additional data file.Table S1Oligonucleotide sequences.(XLS)Click here for additional data file.


Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF) partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks.In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2) were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM). A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes.We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study) and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes) and targeted TFs (25% of common TFs). The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells.Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to further study the underlying mechanisms in breast cancer cells or other human diseases. Global level profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years, from hybridization with spotted or tiling microarray (ChIP-chip) -4, to SAEstrogen-mediated gene regulation is such a challenging question that it may require powerful genome-wide profiling tools like ChIP-based technologies. In breast cancer cells, ERα can mediate genomic transcription regulation with nuclear initiated steroid signalling and non-genomic activation of various protein kinase cascades . In the Tamoxifen is one of selective ER modulators (SERMs) and is widely used to block ERα function for breast cancer treatment ; howeverIn this study, we collected three public available ChIP-based datasets--ChIP-chip, ChIP-PET and ChIP-seq for ERα binding sites in breast cancer MCF7 cells upon estrogen exposure, which also include RNA polymerase II (Pol-II) binding sites in these cells since the binding of Pol-II could provide direct information of potential transcription activation. We then applied computational approaches to investigate the hierarchical regulatory information for ERα regulation in MCF7 cells. We have been able to construct hierarchical regulatory networks with target hubs and have established the regulatory pathways between TFs and genes. We also have applied ChIP-seq technology to systematically compare the estrogen-mediated regulatory information between MCF7 and MCF7-T cells.It is well recognized that the transcription is driven by Pol-II and the general transcriptional machinery; therefore, it is likely that the genes (or promoters) bound by ERα may not be transcribed without Pol-II binding. As such, we need to use the whole-genome-wide binding peaks information combining ERα with Pol-II antibodies.Methods section. The number of ChIP peaks from ChIP-seq is 12,516 for ERα and 13,261 for Pol-II upon E2-treated compared to the vehicle control, the number from ChIP-PET is 14,703 for ERα and 13,133 for Pol-II, the number from ChIP-chip is 10,409 for ERα and 11,455 for Pol-II . Our results showed that 18% for ChIP-seq, 44% for ChIP-PET, 45% for ChIP-chip of Pol-II binding peaks are located within Promoter regions  of a known transcription start site (5'TSS)  are common between ChIP-seq and ChIP-chip Figure  while 18de novo motif discovery approach (ChIPMotifs) [One possible scenario to explain why the majority of ERα direct targets are not activated or repressed is that they may lack certain binding TF partners serving as helpers for ERα to co-regulate these genes. Thus we applied the PMotifs) ,35 develPMotifs)  and JASPPMotifs)  databasede novo ChIPMotifs first ab initio identify motifs at a set of relatively short sequences (~300 - 500 bp), then find possible matched TFs from the TRANSFAC database after obtaining significant motifs, therefore, this might miss some co-TFs if they locate outside 500 bp distance from ERα. But if we used longer sequences, that might lose the specificity for the identified motifs such as missing identifying ERE. Regardless, we chose to include these three co-TFs  in our further analysis. These TFs' Seq-LOGOs in ChIP-seq data, ChIP-chip data and ChIP-PET data were shown in Figure In this study, for each ChIP-based dataset, we selected the top 2000 peaks with high scores (enrichments) as the input data for ChIPMotifs. After running ChIPMotifs, ERE, PAX6, PITX2 and RORA were identified in ChIP-seq data; ERE, PITX2, RORA and GATA2 were identified in ChIP-chip data; RORA, PAX6, PITX2 and ERE were identified in ChIP-PET data  direct binding to ERE (estrogen response element); b) indirect binding, through which it binds to other TF partners which bind to DNA; and c) co-occurrent binding, where both ERα and other TF partners bind to their own specific DNA motifs . Furthermore, for the transcriptional regulatory network (as a part of gene regulatory network), only transcription factors were used for the network construction . ERα binding peaks associated with those normal TFs were further scanned by Hub TF  PWMs to determine if there is any connection between a Hub TF and a normal TF. A shuffling test was performed to test the reliability of each connection of the network. The resulted regulatory networks were thus constructed and topologically visualized using Cytoscape [Methods section and Figure In order to understand how the regulatory network responds to E2 treatment in three ChIP-based technologies, we here integrated the ChIP data with the time series of E2 induced gene expression data. In order to determine if a gene is differentially expressed, we used the difference of expression levels between time point 12 hr and 0 hr, positive value as up-regulated and negative value as down-regulated. Thus all genes in the networks were differentially expressed and with ERα and PolII binding ChIP-peaks  and FOXA1 were known TF partners of ERα. After integrating the TF-DNA interactions data with 1,513 genes (see Methods section), a total of 5 paths were clearly diverging for these genes . A final combined regulatory pathway map obtained from three ChIP data showed that genes were traversing the 3 splits are shown with (a) corresponding to the split at 0 hr, (b) corresponding to the split at 3 hr and (c) corresponding to the split at 6 hr . We further revealed a new estrogen-mediated up-regulated path requiring a TF partner PITX2, and the function of this set of genes is associated with ribonucleoprotein complex (p = 6.7 × 10-8), mRNA metabolic process (p = 1 × 10-10), mRNA processing (p = 4.9 × 10-10) and chromosome (p = 5.5 × 10-7). Our analysis also showed other paths with less significant genes: Lyase activity with a p-value of 6.9 × 10-3 , response to virus with a p-value of 4.3 × 10-3. We also found that the TF FOS, CEBP, FOXA1 and PITX2 are related to the up-regulated genes, while FOXA1 was shown up in both up and down-regulated genes. The gene lists of five paths were shown in Additional file We next applied DREM program to model, analyze, and visualize dynamic gene regulatory functions . The mapr Figure . The patr Figure . Our finex p = 6. × 10-8, Methods section). Around 22 million reads were obtained for Pol-II control data, and 19 million reads in Pol-II E2-treated data. For ERα antibody, the number is 14 million for control data and 16 million for E2-treated data  common genes Figure  between We next applied the same computational analytical approach to examine the ERα regulated network in MCF7-T cells. We started with training the top 2000 ERα binding peaks with high scores (enrichments) by the ChIPMotifs, a total of 7 TFs were identified, including ERE, PAX6, PITX2, RORA, XBP1, PPARG and PPARA Figure . Of themThe ERα associated transcriptional regulatory network in MCF7-T cells was then constructed and visualized as shown in Figure In this study, we applied computational approaches to analyze and integrate three ChIP-based datasets and one time-series gene expression data to investigate the dynamic regulatory information for ERα in estrogen-dependent breast cancer MCF7 cells. Our studies not only compared the results of three ChIP-based protocols, but also have inferred the regulatory network and pathway for E2 induced MCF7 cells. Moreover, we used the same approach to compare the difference between MCF7 and MCF7-T cells.Our comprehensive analysis of the estrogen-mediated regulatory network in MCF7 indicated that the three ChIP-based technologies have similar peak distribution patterns for the same antibody. However, for different antibody (ERα and Pol-II), the binding preference is totally different. Pol-II tends to binding to the promoter region, while ERα has no specific preference.Our analysis Figure  also shoWe also compared the regulatory network in MCF7 constructed by our approach with another method--ReMoDiscovery . We usedp-values. Figure In Figure Since a totally different technology is used for ChIP-chip data, in order to reduce the inconsistency caused by the technology itself, we further examined only ChIP-seq and ChIP-PET data to reproduce the network Figure . We founThe hierarchical regulatory network analysis with DREM and Cytoscape revealed that RORA could be a potential ERα partner, which is consistent to other reports  showing In MCF7-T cells, we found very small proportion (21.2%) of differential expressed genes overlapped with MCF7 cells (ChIP-seq dataset) with both ERα and Pol-II binding peaks. In addition, the number of common TFs of the network between MCF7-T and MCF7 cells is only 25%. Moreover, we also found two TFs with opposite expression trend between MCF7 and MCF7-T cells, in which MSX2 is up-regulated in MCF7-T cells and down-regulated in MCF7 cells, whereas ESR1 (ERα) is down-regulated in MCF7-T cells. We also identified 3 new Hub TFs in MCF7-T cells which were not found in MCF7 cells. This indicates that ERα may be no longer the most important transcription factor, other transcriptional regulators and signalling pathways may play important role in tamoxifen resistant MCF7 cells. Our comparative analysis also suggests that the ERα associated regulatory network in MCF7-T cells is rewired upon E2 induced.We have performed additional experiments using both RT-qPCR and ChIP-qPCR to validate randomly select eight ER regulated binding loci in MCF7-T cell, and the result demonstrated that the predicted ER regulated binding loci with differential gene expression after E2 treatment were validated as shown in Additional file p-value. The result was shown in Additional file We further compared the E2 induced gene functions to specify the difference between MCF7 and MCF7-T cell line. We selected the genes that were differentially expressed and with ERα and PolII binding site. These genes were performed by GO function by the DAVID program  and the In summary, we analyzed hierarchical regulatory networks for estrogen-dependent regulation in MCF7 and MCF7-T cells. We systematically compared different ChIP-based technologies as well as different breast cancer cells. Our results revealed extended hierarchal regulatory networks with new target hubs in breast cancer cells. Our computational analytical approach may also provide a framework for dissecting transcriptional regulatory networks in response to breast cancer and other human diseases.Methods section "ERα regulatory network analysis") is used to test the reliability of each connection of the network. The resulted regulatory network is visualized by Cytoscape and the pathway is analyzed by DREM. In this study, a given TF is ERα.Our computational analytical approach Figure  started For MCF7 cells, the ChIP-chip data is from Carroll's paper , ChIP-seThe time-series E2-induced gene expression data in MCF7 cells for all three ChIP-based datasets was obtained from Carroll et al. 2006 . The dat-7 mol/L 4-hydroxytamoxifen. Prior to all experiments, MCF7-T cells were cultured in hormone-free medium for 1 week to deplete any residual OHT, and then MCF7-T cells were cultured in hormone-free basal medium  for three days. MCF7-T cells were treated with E2 (108 mol/L) for 3 hours.ChIP-seq of E2-induced MCF7-T cells were maintained in a hormone-free medium  supplemented with 107 cells were crosslinked with 1% formaldehyde for 10 min, at which point 0.125 M glycine was used to stop the crosslinking. In brief, after crosslinking, cells were treated by lysis buffers and sonicated to fragment the chromatin to a size range of 200 bp-1 kb. Chromatin fragments were then immunoprecipitated with 10 ug of antibody/magnetic beads. The antibodies against Pol-II and ERα were purchased from Santa Cruz Biotechnology . After immunoprecipitation, washing, and elution, ChIP DNA was purified by phenol:chloroform:isoamyl alcohol and solubilized in 70 μl of water. Then Illumina library was constructed and sequenced with Illumina/Solexa Genome Analyzer . Briefly, the ChIP DNA sample was run in 12% PAGE and the 100-300 bp DNA fraction was excised and eluted from the gel slice overnight at 4°C in 300 μl of elution buffer -7.5 M ammonium acetate) and was purified using a QIAquick purification kit . The library was constructed using Illumina genomic DNA prep kit by following its protocol , clusters were generated on the Illumina cluster station , and the sequence was run on Illumina 1G Analyzer following the manufacturer's instructions . The unique mapped ChIP-seq datasets  for MCF7-T cells are available from GEO database (accession number: GSE26083) or from our webpage http://motif.bmi.ohio-state.edu/ERNetwork/.5 × 10http://www.R-project.org . Total RNA (2 μg) was reverse transcribed to cDNA with oligo-dT . Quantitative RT-PCR was performed by using SYBR Green dye chemistry (Applied Biosystems) on a 7500 Real-time PCR system apparatus (Applied Biosystems). Gene Expression was measured by the ΔΔCt method using To confirm candidate ERα target genes determined by ChIP-seq, PCR primers targeting a region within 200 bp of the predicted ERE were used to measure the enrichment of this sequence in anti-ERa-immunoprecipitated samples by quantitative PCR with SYBR Green-based detection method (Applied Biosystems). Quantitative values measured by a standard curve  of input DNA amplified with the same primer set. Results are presented as the mean of triplicates with standard derivation.p-value of each overlapped number, and assumed that the human genome number is 30,000 .j ≤ n), the occurrence frequency of every nucleotide (A or T or C or G) was calculated by counting the number in m sequences (equation 1).Suppose there are m sequences, and the sequence length is n. For each column j, Si ≤ 4) and column j(1 ≤ j ≤ n), the PWM can be calculated:Hence, the PWM is represented as a 4*n matrix. For row i(1 ≤ Where p(i) is the background frequency of nucleotide i. For Human genome, p(i = A) = p(T) = 30% and p(i = C) = p(G) = 20%, approximately.For the case that the number sample is small, the equation 1 needed to be replaced asThen, the significant PWMs were mapped to TransFac  databaseTo construct the regulatory network, the PWM was used to scan the peak region of each gene. To make the result more reliable, we use stringent threshold  to determine the underlying TF binding site. The PWM score and core score is calculated as follows:Given a sequence with the same length (column number n) of PWM, we can first calculate the sequence score:w is the score at row i which the nucleotide is the same as the given sequence at column j.Where Then, the minimum and maximum score of PWM can be calculated as:The PWM score for the given sequence is shown in equation 7Our program ChIPMotifs will give the length (k) and start (k1) and end (k2) position of Core region in a PWM. The given sequence will be scanned (n-k+1) times (move forward one position each time) to find a maximum Core score. For the dth time, the sequence score can be represented as:For equation 5 and 6, only the boundary of j was changed from 1-n to k1- k2. The Core score for the dth time isAnd the Core score for the given sequence isIf there is Motif for ERα and Hub TFs for certain gene, a connection between the Hub TF (include ERα) and the gene was made. We further facilitated these relationships by visualizing an estrogen regulatory network with Cytoscape  softwareTo test the significance of the network proposed in this study, a statistical strategy (permutation) was used to determine the probability of each edge of the network under random circumstances. Since the TF binding site region is composed of specific sequences, and only by scanning the sequence region using PWM, we get the network edges. Hence, we shuffled the sequence of each peak region for 1000 times, and to see how many times a specific TF binding site is hit by the scanning process. The ratio (times hit by scanning divide by 1000) of each edge was calculated. The number with low value was considered high statistical significance (we used 0.2 as a cutoff to include as more connection as possible while keeping the relationship reliable).The up/down-regulated genes were grouped into several classes (sub up/down-regulated classes). For each group, the common gene functions were identified from GO database with p-value represented for the significance. Then, we used the PWMs of the 6 TFs  to identify all possible binding sites in all genes with peaks. Thus we established the relationship between Hub TFs and grouped genes. A DREM diverging score less than 0.1 was used as a significant score threshold for TF-grouped gene relationship.FG, HKH, PYH, JW, YM, JP, THMH and VXJ conceived and designed the study. VXJ and FG performed the computational analysis and HKH, PYH and JW performed MCF7-T experiments and RT-, ChIP-qPCR validations. VXJ, FG, JP and THMH drafted the manuscript. All authors provided comments on the paper and read and approved the final manuscript.Table S1. A distribution of locations of Pol-II and ERα binding sites relative to Human HG18 RefSeq Genes three ChIP-based datasets in MCF7 cell line.Click here for fileFigure S1. A plot of the distribution of identified ERα and Pol-II binding loci relative to a known gene's TSS. A) Definition of different regions of a gene. B) The histogram of the distribution of peak location. A big portion of Pol-II bind in promoter regions (2 kb around TSS); A small portion of ERα binding loci are located in promoter region. These observations confirm that the majority of ERα binding loci are outside of proximal promoter regions in which it is consistent with the results from other studies.Click here for fileFigure S2. Three major binding models for ERα regulated gene expression. A) direct binding to ERE (estrogen response element); B) indirect binding, through which it binds to other TF partners which bind to DNA; C) co-occurrent binding, where both ERα and other TF partners bind to their own specific DNA motifs.Click here for fileFigure S3. The Regulatory network for E2 treated MCF7 cell line of three different ChIP-based datasets. A) The Regulatory network for E2 treated MCF7 cell line from ChIP-seq dataset. B) The Regulatory network for E2 treated MCF7 cell line from ChIP-PET dataset. C) The Regulatory network for E2 treated MCF7 cell line from ChIP-chip dataset.Click here for fileTable S2. The list of common TFs among all three regulatory networks.Click here for fileFigure S4. Regulatory pathway analysis from three ChIP-based dataset. Figure S4 (I). Regulatory pathway analysis from ChIP-seq dataset. A) The time series gene expression data of E2 induced genes superimposed with the regulatory pathway map produced by DREM using the gene expression profile as well as ERα binding sites and PolII binding sites. The bright green nodes indicate split points where the sets of expression of genes diverge. B) Paths out of splits are annotated with TFs determined by DREM to be associated with the genes assigned to the path at a score <0.1. The GO annotations for the genes in 5 of the paths are shown at the right with their p-values. C) The genes traversing the 3 splits are shown with (a) corresponding to the split at 0-hr, (b) corresponding to the split at 3-hr and (c) corresponding to the split at 6-hr. Figure S4 (II). Regulatory pathway analysis from ChIP-PET dataset. A) The time series gene expression data of E2 induced genes superimposed with the regulatory pathway map produced by DREM using the gene expression profile as well as ERα binding sites and PolII binding sites. The bright green nodes indicate split points where the sets of expression of genes diverge. B) Paths out of splits are annotated with TFs determined by DREM to be associated with the genes assigned to the path at a score <0.1. The GO annotations for the genes in 5 of the paths are shown at the right with their p-values. C) The genes traversing the 3 splits are shown with (a) corresponding to the split at 0-hr, (b) corresponding to the split at 3-hr and (c) corresponding to the split at 6-hr. Figure S4 (III). Regulatory pathway analysis from ChIP-chip dataset. A) The time series gene expression data of E2 induced genes superimposed with the regulatory pathway map produced by DREM using the gene expression profile as well as ERα binding sites and PolII binding sites. The bright green nodes indicate split points where the sets of expression of genes diverge. B) Paths out of splits are annotated with TFs determined by DREM to be associated with the genes assigned to the path at a score <0.1. The GO annotations for the genes in 5 of the paths are shown at the right with their p-values. C) The genes traversing the 3 splits are shown with (a) corresponding to the split at 0-hr, (b) corresponding to the split at 3-hr and (c) corresponding to the split at 6-hr.Click here for fileTable S3. A. The five paths for ERα regulated genes identified by DREM analysis in ChIP-seq data. B. The five paths for ERα regulated genes identified by DREM analysis in ChIP-PET data. C. The five paths for ERα regulated genes identified by DREM analysis in ChIP-chip data.Click here for fileTable S4. A. The transcription factors identified in ChIP-seq with predicted binding motifs. B. The transcription factors identified in ChIP-PET with predicted binding motifs. C. The transcription factors identified in MCF7 with predicted binding motifs.Click here for fileTable S5. Transcription factor network identified by ReMoDiscovery.Click here for fileFigure S5. Validation of the regulatory network of MCF7-T cell line. 8 TFs were selected from MCF7-T network. All the TFs were found with ERα binding peaks. (A) mRNA levels derived from RT-qPCR of 8 ERα regulated target genes were shown under E2  stimulation in MCF7-T cells. GAPDH was as internal control. Mean ± SD (n = 3). (B) Validations of predicted ERα-binding regions for 8 binding loci by ChIP-qPCR. Control and E2-treated MCF7-T cells were subjected to ChIP-qPCR with ERα antibody. Mean ± SD (n = 3).Click here for fileFigure S6. A comparison of GO functions between MCF7 and MCF7-T cells using genes from ChIP-seq technology. (A) GO functions of MCF7 cells. (B) GO functions of MCF7-T cells. (C) the GO function of two cells in the same figure.Click here for fileTable S6. A list of genes used for GO function analysis for MCF7 and MCF7-T ChIP-seq data.Click here for fileTable S7. Gene expression data of MCF7-T cells.Click here for fileTable S8. Fisher exact test of the significance of overlapped genes in Figures Click here for file