Transposable elements (TEs) contribute to the large amount of repetitive sequences in mammalian genomes and have been linked to species-specific genome innovations by rewiring regulatory circuitries. However, organisms need to restrict TE activity to ensure genome integrity, especially in germline cells to protect the transmission of genetic information to the next generation. This review features our current understandings of mammalian PIWI-interacting RNAs (piRNAs) and their role in TE regulation in spermatogenesis. Here we discuss functional implication and explore additional molecular mechanisms that inhibit transposon activity and altogether illustrate the paradoxical arms race between genome evolution and stability. Transposable elements can be activated during germ cell maturation, potentially leading to genome instability and rewiring of the genetic circuitry. In this review, the authors discuss how the piRNA machinery suppresses these elements to ensure accurate spermatogenesis. A subfraction of these repeats are mobile elements, also termed transposable elements (TEs), that play crucial roles in driving genome evolution by fueling the development of new genes, introducing novel immune strategies such as V(D)J recombination, and rewiring gene regulatory circuitries2. However, such plasticity comes at the price of causing potential deleterious effects as a result of uncontrolled retrotransposition and therefore requires a tight handling of TEs by their host cells3. This is especially important in cells contributing to the germline, to ensure the integrity of the genome that is passed on to the next generation. To this effect, an additional layer of retrotransposon control has evolved in the metazoan germline that is based on small RNA-mediated recognition of TE transcripts called the piRNA pathway.Repetitive sequences make up a large proportion of mammalian genomes, with up to two thirds of the human genome being repeat-derived4. A requirement for the successful retrotransposition of a TE is active cell divisions5. Hence, the burden is heavier during male germ cell development in mammals, which is marked by continuous waves of spermatogenesis throughout the life span, compared to female germ cells of which a defined number arrests in meiosis I during embryonic development and only matures after the onset of sexual maturity6.Active retrotransposition is more frequent in germ cells since the epigenetic reprogramming that primes these cells for totipotency also results in the derepression of TEsIn this review, we will discuss the role of PIWI-interacting RNAs (piRNAs) throughout mammalian, mostly mouse, spermatogenesis and their interplay with transposable elements and briefly touch on additional silencing mechanisms controlling the activity of transposable elements.7 9. Male PGCs remain mitotically arrested until postnatal day 2 (P2), during which time de novo DNA methylation and the establishment of paternal imprints takes place10. This process is mediated by the de novo DNA methyltransferases DNMT3A and DNMT3B as well as their catalytically inactive interaction partner DNMT3L11. DNMT3L is essential for spermatogenesis by guiding de novo DNA methylation and binding to unmethylated histone H3 lysine 4 tails12.Gametogenesis is a complex process that starts as early as embryonic day 7.5 (E7.5) with the emergence of primordial germ cells (PGCs) that migrate to and populate the genital ridges at E10.5–E11.57 Fig. . Migrato7 Fig. 7. PGCs a13. After several rounds of mitotic divisions from P2 onwards, the first meiosis is initiated in a synchronous manner around P10. As cells progress through spermatogenesis, they move away from the basement membrane toward the lumen of seminiferous tubules and enter pre-leptotene/leptotene, zygotene, pachytene, and diplotene stages on P10, 12, 14, and 17, respectively13. Prophase of meiosis I is unique in that it promotes transfer of genetic information between the parental genomes via crossovers. To allow meiotic crossovers, homologous chromosomes synapse during the zygotene stage and form bivalents14. This is mediated by DNA double-strand breaks (DSBs) that are specifically induced by SPO1115 and enable homologous recombination (HR) between non-sister chromatids of homologous chromosomes. Crossovers are essential for proper chromosome synapsis and occur in hotspots across mammalian genomes, directed by PRDM918. Failures in de novo DNA methylation have been shown to cause mislocalization of crossovers resulting in spermatogenic arrest at the pachytene stage19. When reaching the diplotene stage of prophase I, homologous chromosomes begin to separate but are still attached to each other, thereby forming the characteristic structures called chiasmata. Eventually, bivalents are arranged on the metaphase plate and homologous chromosomes are separated to opposite poles followed by cytokinesis ending the first meiotic division.Male PGCs resume cell division shortly after birth and give rise to type-A spermatogonia, which are found on the basement membrane of seminiferous tubules. These cells have self-renewing potential but also produce type-B spermatogonia, which can enter meiosis and become spermatocytes20. The latter is achieved via genome-wide replacement of histones with transition proteins at first, followed by protamines, which results in up to a 20 times more condensed structure due to the basic character of these proteins21. To allow the transition, a loose chromatin structure is adopted and mediated in part by the incorporation of various testis-specific histone variants, which leads to a global transcriptional activation including TEs24. Histone replacement, however, was shown to be incomplete with some genomic regions retaining their histones including epigenetic modifications to potentially prime these regions for early transcription after fertilization27.The second meiotic division follows promptly and generates the first set of round spermatids to be found at P20. Round spermatids then undergo a complex differentiation program called spermiogenesis, during which they form sperm-specific structures such as the acrosome and flagellum and undergo nuclear compactionThe different waves of epigenetic reprogramming and global remodeling of the genome allow repetitive elements to become transcriptionally active in the male germline at several developmental time points. To prevent these repetitive elements from causing genome instability, additional control mechanisms are required during spermatogenesis.30. Each PIWI protein exhibits a unique expression profile throughout spermatogenesis  family: MILI, MIWI, and MIWI2, all of which are essential for spermatogenesis and male fertilitysis Fig.  and asso44. Once in the cytoplasm, piRNA precursors associate with the RNA helicase MOV10L1, whose ATP-dependent unwinding activity is essential for piRNA biogenesis as illustrated by the increase in piRNA precursor transcripts and almost complete lack of mature piRNAs in MOV10L1 knockouts, or catalytically defective mutants46. MOV10L1 is believed to fuel piRNA precursors into the biogenesis pathway by facilitating the interaction with PLD6 (MITOPLD), the endonuclease that generates the 5′ end of primary piRNAs48. Intermediate fragments with a 5′ uridine (1U) are preferentially bound by PIWI proteins and thereby stabilized, leading to the strong 1U bias that is characteristic for primary piRNAs49. PIWI-bound piRNA intermediates then undergo 3′ end processing, which most likely involves exonucleolytic shortening by a 3′–5′ trimmer that has not been identified in mammals yet. The process is facilitated by Tdrkh, a Tudor and KH domain-containing protein, whose absence causes the accumulation of 31–37 nucleotide (nt) long intermediates50. The final length of piRNAs during 3′ end maturation is determined by the footprint of their associated PIWI protein, which protects the 3′ end from further trimming51. This generates size-specific piRNA populations for the different PIWI proteins with a mean length of 26 nt for MILI-, 28 nt for MIWI2-, and 30 nt for MIWI-bound piRNAs53. Mature 3′ ends are then 2′-O methylated by the RNA methyltransferase HENMT1 resulting in increased stability and binding to the PAZ domain of their PIWI protein54.Besides their association with different PIWI proteins, piRNAs are further distinguished based on their biogenesis. The biogenesis of primary piRNAs begins with the transcription of a single-stranded piRNA precursor molecule by RNA polymerase II (Pol II) from defined genomic locations termed piRNA clusters Fig. . piRNA p53. This 10A bias has long been thought to originate from complementarity to the 5′ uridine of primary piRNAs. However, base pairing at the first position is not necessary for efficient cleavage by Argonaute proteins55 and it appears that mammalian PIWI proteins rather have a preference for adenine at the t1 position that is not determined by base pairing56. Secondary piRNAs in turn can then fuel the production of the initiating primary piRNAs, thereby completing the ping-pong cycle. In the mouse, secondary piRNA production is driven by the slicer activity of MILI and most ping-pong cycles rely on homotypic MILI:MILI interactions with occasional heterotypic MILI:MIWI2 associations57. These heterotypic ping-pong interactions are however not reciprocal and the loading of MIWI2 with secondary piRNA is entirely dependent on MILI53. The disengagement of MIWI from the ping-pong cycle was shown to be due to active repression of the ping-pong cycle by RNF17, a Tudor family member, in meiotic cells. RNF17 knockout demonstrated that MILI:MIWI ping-pong interactions can occur in vivo, but result in spermatogenic arrest due to ping-pong-initiated piRNA responses against protein-coding genes58.Primary piRNAs can then guide the PIWI-mediated cleavage of antisense transcripts between nucleotide 10 and 11 to produce secondary piRNAs, a process known as the ping-pong cycle. Secondary piRNAs therefore have a defining 10 nt 5′ overlap with the primary piRNA that mediated the cleavage and often have adenine at their tenth position (10A)59.In addition to the primary and secondary piRNA biogenesis pathways, a separate mechanism termed “inchworming” fuels the production of MIWI2-associated piRNAs. Inchworming is initiated by MILI-loaded piRNAs that direct slicing of a target transcript. Instead of giving rise to only one conventional secondary piRNA, multiple evenly spaced, 37 nt long piRNA intermediates are formed in 5′–3′ direction from the initial cleavage product. These intermediates can associate with both MILI and MIWI2 and are trimmed at their 3′ ends to the typical length of 26 and 28 nt, respectively. Inchworm piRNAs do not have the characteristic 10 nt overlap of secondary piRNAs but display a strong 1U bias59.MILI-associated piRNAs that initiate inchworming are in sense orientation to L1 elements and therefore lead to the production of large amounts of antisense inchworm piRNAs in contrast to the piRNAs produced in the ping-pong cycle. Thus, inchworming presents an amplification mechanism for antisense piRNAs that can silence L1 elements on the transcriptional or post-transcriptional level by associating with either MIWI2 or MILI, respectively61. In contrast, MIWI2 is only expressed during a short period of time, starting at E14.5 until shortly after birth with protein levels being undetectable by P461. This expression window largely coincides with mitotic arrest of PGCs and de novo DNA methylation. Knockout of either MILI or MIWI2 leads to upregulation of TEs resulting in a spermatogenic arrest; however, not during the time of their joint expression, but only several days and cell divisions later in early pachytene spermatocytes62. piRNAs expressed during this period are termed pre-pachytene piRNAs and are characterized by a high occurrence of TEs in sense orientation, suggesting that most primary pre-pachytene piRNAs derive directly from TE transcripts53. These piRNAs associate with MILI and drive the production of secondary piRNAs through recognition of antisense transcripts, which then associate with either MILI or MIWI2. This amplification method results in fine-tuning of the piRNA population and specific enrichment of those piRNAs that target the most active TEs.MILI is the first PIWI protein to be expressed during development, starting at E13.5 in PGCs with a dynamic expression profile up until the round spermatid stage63. Translocation of MIWI2 into the nucleus is however dependent on its association with piRNAs and therefore on the slicer activity of MILI that is necessary to load MIWI2 with secondary piRNAs53. In contrast, the slicer activity of MIWI2 itself is dispensable for spermatogenesis, as catalytically inactive MIWI2 mutants show normal fertility and only modest upregulation of TEs57. This strongly suggests that MIWI2’s essential function during spermatogenesis defers from post-transcriptional gene silencing (PTGS) of TE transcripts in the cytoplasm and is rather related to its nuclear function. Indeed, MIWI2 is required for the establishment of de novo DNA methylation over TEs acting upstream of DNMT3L in PGCs53  and intracisternal particle A (IAPs)) correspond to evolutionary young elements that also become activated as a result of MILI knockout and consequently unloaded MIWI264. MIWI2 is believed to use antisense piRNAs as guides to detect nascent TE transcripts in the nucleus and recruits not only the de novo DNA methylation machinery65, but also histone methyltransferase to establish a repressive chromatin landscape especially across LINE1 elements66. Interestingly, preferential targeting of LINE1 elements by MIWI2 was also observed for DNA methylation. While loss of MIWI2 results in demethylation and derepression of mostly LINE1 elements, MILI deficiency causes DNA methylation defects across a wider range of TE families, including both LINE1 and LTR elements. This suggests that MILI can induce DNA methylation in a MIWI2-independent manner, however the underlying mechanisms are unknown68. In contrast to these observations, a recent report showed greater disruption of DNA remethylation upon loss of Miwi2 compared to Mili, suggesting a MILI-independent piRNA biogenesis pathway in fetal male gonads69.60. This repressive histone mark, however, displays a dynamic pattern during spermatogenesis and completely disappears at the pachytene stage  map uniquely to the genome, thereby allowing unambiguous identification of piRNA clusters32. Pachytene piRNA clusters can be either uni- or bidirectionally transcribed. Although there is a fewer number of bidirectional clusters annotated in the genome, they contribute to the majority of pachytene piRNAs  from the promoter of a pachytene piRNA cluster resulted in a reduction but not complete depletion of piRNA precursor transcript levels and processed pachytene piRNAs75. This suggests that what directs piRNA precursors into the biogenesis pathway is more likely to be an RNA-based recognition signal and could involve the formation of G-quadruplex structures45. Similar to the observations in fetal gonocytes63, the piRNA pathway components involved in the processing and function of pachytene piRNAs also show distinct localization patterns to cytoplasmic nuage structures termed chromatoid bodies in mid-to-late meiotic spermatocytes and haploid spermatids77.As the first wave of spermatocytes reaches the pachytene stage of meiosis, the transcription of the third PIWI family member MIWI starts together with a new class of piRNAs termed pachytene piRNAs32, that is in fact lower than the genome average78, thereby calling their importance in the regulation of TEs into question. However, it has been demonstrated that MIWI’s slicer activity is necessary for the accurate silencing of LINE1 elements in spermatocytes79. Nevertheless, the functional division between repeat-targeting and non-repeat-associated pachytene piRNAs still remains unclear.In contrast to pre-pachytene piRNAs, pachytene piRNAs have a surprisingly low repeat content (<20%)80. A similar scenario is possible for new TE insertions, which has led to the suggestion that piRNA clusters may serve as “genomic sinks” to capture active TEs81. However, in contrast to observations in Drosophila that show higher TE insertion rates into piRNA clusters82, no such bias has been described in mammals so far. It is therefore still unclear how the pachytene piRNA system adapts to newly invading repetitive elements and how quickly a new piRNA response can be installed.Pachytene piRNA clusters have been shown to produce novel artificial piRNA sequences upon introduction of transgenic sequences29. These late stages of spermatogenesis are associated with major epigenetic changes and various functions have been implicated for non-repeat-related pachytene piRNAs. For example, the transitioning from histone- to protamine-bound DNA in round spermatids requires open and accessible chromatin, which leads to a genome-wide loosening of transcriptional control and the expression of spurious transcripts including many long non-coding RNAs (lncRNAs)83. Pachytene piRNAs have been shown to be essential in targeting many of these mRNA and lncRNAs to regulate their expression via PTGS84 , a perfect match between nucleotides 2–11 with a maximum of four mismatches between nucleotides 12–21 was detected. In support of this model, the observed male sterility phenotype of this mouse was explained by silencing of the germline-specific gene Dpy19L2 by one of the ectopically expressed human piRNAs. Double transgenic mice, expressing human piRNAs as well as the human Dpy19L2 gene that does not contain a target site for human piRNAs, were indeed fertile and able to produce offspring86.Recent work cloning a human piRNA cluster into the mouse and identifying mRNAs that are targeted by human ectopic piRNAs, shed light on the target specificity of this mechanism87. Further functional implications for MIWI were made that are independent of associated piRNAs. In that case, MIWI binds to and stabilizes spermiogenic mRNAs that are stored for translation at later time points when transcription has been switched off44.During later stages of spermatogenesis in elongating spermatids, pachytene piRNAs were shown to direct the elimination of mRNAs. This was independent of the slicer activity of MIWI but required interaction with the deadenylase CAF1 to induce deadenylation and subsequent degradation of mRNAs88. Studies have shown that conditional knockout of MILI after birth, therefore avoiding adverse phenotypes from MILI’s prenatal role, has no impact on the establishment of meiotic silencing across the X and Y chromosomes89. Interestingly, while piRNA clusters are absent from the X chromosome in the mouse, profiling of the piRNA repertoire in marmoset identified several piRNA cluster on the X chromosome, suggesting that these regions may escape meiotic silencing81.Interestingly, one meiotic process, which has not been directly linked with piRNAs so far, is the meiotic silencing of unsynapsed chromosomes (MSUC). This mechanism is essential for meiosis, conserved across mammals, and results in transcriptional silencing of any chromosomes that are unpaired at the pachytene stage. One of the best studied examples for this is the meiotic silencing of the sex chromosomes in male germ cells due to their largely unpaired nature92.Periods of global epigenetic remodeling present TEs with an opportunity to become activated and retrotranspose, generating the need for the piRNA pathway in the male germline. Epigenetic reprogramming, however, is not unique to the male germline but also an essential process in female gametogenesis as well as preimplantation development in mouse embryos. Yet, the piRNA pathway is dispensable both in mouse oocytes as well as early embryos despite frequent upregulation of TEs93. In addition to PIWIL3, recent studies also found PIWIL1 expressed in both bovine oocytes and human fetal ovaries and suggest a role for piRNAs in the female germline of other mammals95. A possible compensation for the loss of PIWIL3 in the Muridae family is the expression of an oocyte-specific Dicer isoform (DicerO) originating from a retrotransposon insertion. This insertion drives the expression of a shortened Dicer variant that is more efficient in processing double-stranded RNA into endogenous siRNAs96. In general, it has been shown that oogenesis is far more dependent on Dicer and other small RNA biogenesis factors97. However, small RNAs, such as microRNAs, appear to function unperturbed throughout spermatogenesis. They are also not required for oogenesis and are in fact drastically downregulated during oocyte maturation, potentially to avoid competing effects between microRNA and endo-siRNA binding to AGO proteins99.A possible explanation for the independence of the female germline in mice could be the lack of the fourth PIWI family member that exists in other mammals. PIWIL3 is found across eutherian mammals but is missing in the Muridae family comprising mice and rats. While its function remains largely elusive, it might hold some female germline-specific function as indicated by its exclusive expression in bovine oocytes92. While some studies have implicated low levels of piRNA expression in embryonic stem cells (ESCs)100, their presence does not appear to be crucial. However, it has been shown that ESCs and early embryos show high levels of repeat activation and while the activation of repetitive elements is often part of the developmental program and helps to orchestrate gene expression, a more sophisticated fine-tuned system is required to ensure proper regulation104. TE silencing in early embryos mostly relies on transcriptional gene silencing mediated by H3K9me3 instead of DNA methylation107. One mechanism to specifically target transcriptional gene silencing to TEs is based on the large family of Cys2-His2 zinc finger (C2H2-ZF) proteins that form the largest family of transcription factors in both the mouse and human genome108. DNA binding is mediated via the use of up to several dozen C2H2-ZF domains in a combinatorial manner and results in large binding motifs. These proteins are often coupled to effector domains, the most common being the Krüppel-associated box (KRAB), and upon binding are called KRAB-ZFPs in mice or KZNFs in humans109. KRAB-ZFPs mediate transcriptional silencing by interacting with the corepressor protein KAP1 , which serves as a scaffold domain to recruit chromatin modifiers like the histone lysine-methyl transferase SETDB1110.Apart from germ cell development, early embryonic development is another developmental window during which the regulation of transposable elements is vital for proper cell differentiation111. Indeed, an elegant study using transchromosomic mouse ESCs that carry one human chromosome was able to identify two human KZNFs that are necessary to repress two retrotransposon families that emerged relatively recently during human genome evolution112. Over time, repressed TEs will accumulate a sufficient number of mutations to render them inactive, making the KRAB-ZFP involvement in their recognition obsolete, which is reflected by the large number of KRAB-ZFP pseudogenes in the genome111. To date, only a few KRAB-ZFPs have been linked to a specific repeat element and their highly species-specific activities prohibit to draw conclusions from other model organisms. Assigning specific functions to KRAB-ZFPs in different species will remain challenging but the recent advance in identifying binding motifs and genomic target sites for numerous mouse and human KRAB-ZFPs will help to shed light onto this matter116. The KRAB-KAP1 pathway is an elegant example of co-adaptation between host genomes and their specific repeat content, which is dependent on gene duplication and mutation and therefore relatively slow. This could give highly active TEs the opportunity to cause major genomic damage until adaptation occurs. Our current understanding on how this adaptation is driven or directed is still very limited.KRAB-ZFPs are rapidly evolving and can be correlated to the emergence of species-specific TEsin vitro models to study this pathway. Recently published protocols for the differentiation of ESCs into PGCs or further into sperm118 might allow the study of mammalian piRNAs in more detail. As of to date, most studies rely on the use of mouse knockout models and candidate genes are often chosen based on their described function in other organisms, such as Drosophila. However, piRNA pathway components identified in Drosophila are not always conserved in mammals, such as the rhino-deadlock-cutoff complex119, therefore making the mechanistic comparisons from insect to mammalian systems challenging. Without knowing the exact piRNA biogenesis pathway, other aspects such as identifying the signal that directs piRNA precursors to be processed, similar to piRNA trigger sequences in Drosophila75, remain a challenge.Many parts and factors of the piRNA biogenesis pathway in mammals still remain unknown due to the lack of easy-to-use While silencing of TEs in the germline is the unifying function of piRNAs observed across all animals, piRNAs have evolved and adapted additional functions in mammalian spermatogenesis. This includes the establishment of proper DNA methylation including paternal imprints as well as regulating meiotic crossovers by defining the chromatin state. Furthermore, piRNAs have recently been shown to be essential for proper spermatogenesis by controlling and orchestrating the transcriptional program via the regulation of spermatogenic mRNAs on both transcriptional and post-transcriptional levels.


Bacillus subtilis has seven ECF σ factors including σX and σM that transcribe their own structural genes. Here, we report that glucose addition to the medium induced sigX and sigM transcription independent of their anti-σ factors. This induction was dependent on an intracellular acetyl-CoA pool. Transposon mutagenesis searching for the mutants showing no induction of sigX and sigM revealed that the cshA gene encoding DEAD-box RNA helicase is required for gene induction. Global analysis of the acetylome in B. subtilis showed CshA has two acetylated lysine residues. We found that in a cshA mutant with acetylation-abolishing K to R exchange mutations, glucose induction of sigX and sigM was abolished and that glucose addition stimulated acetylation of CshA in the wild type strain. Thus, we present a model wherein glucose addition results in a larger acetyl-CoA pool, probably leading to increased levels of acetylated CshA. CshA is known to associate with RNA polymerase (RNAP), and thus RNAP with acetylated CshA could stimulate the autoregulation of sigX and sigM. This is a unique model showing a functional link between nutritional signals and the basal transcription machinery.Extracytoplasmic function (ECF) σ factors have roles related to cell envelope and/or cell membrane functions, in addition to other cellular functions. Without cell-surface stresses, ECF σ factors are sequestered by the cognate anti-σ factor, leading to inactivation and the resultant repression of regulons due to the inhibition of transcription of their own genes.  The varfamilies . ECF σ ffamilies . In Bacie genome . In manyectively . As a reectively . The σX peptides . In the et known . The σM ene bcrC .B. subtilis is well-understood for σW and includes specific proteolysis of its cognate anti-σ factor (sigM)  . In addiregulons . For exapression . A mutat regulon . Transpoump gene .sigX and sigM regulation. Protein lysine acetylation is a well-conserved protein modification in both eukaryotes and prokaryotes  containing appropriate antibiotics at 37°C overnight. The cells were scraped from the plate and suspended in the sporulation medium. The suspension was inoculated into 50 ml sporulation medium (with or without glucose) without antibiotics in a 200-ml flask. Klett value was adjusted around 10 units. The flask was gently shaken (110 reciprocation/min) at 37°C. Cell growth was monitored using Klett colorimeter .The plasmids used in this study are listed in Supplementary Table bkdB::Pxyl-cshA unit was constructed using PCR  cells as described previously . To clarify which σ factors other than σA are responsible for GI, we introduced several mutations in the genes encoding σ factors and examined expression of the promoter for yjbC fused to lacZ. The typical cell growth in the sporulation medium with or without 2% glucose is shown . In a double mutant of sigX and sigM, GI was completely lost, while in the sigB and sigW mutants, GI was still observed . Similar results were obtained using an spx-lacZ fusion . This induction was very sensitive to low concentrations of glucose, 0.05% for sigX and 0.1% for sigM. In B. subtilis the ccpA gene has been known to play a major role in glucose-dependent gene induction and repression . This demonstrated that CcpA is not involved in GI.To examine this possibility, we tested the expression of two genes in glucose-containing medium. As expected, pression . Thus, tsigX and sigM has been shown to be downregulated by their respective anti-σ factors . As shown in these panels, GI was observed in both mutants, indicating no involvement of anti-σ factors in GI of two σ-regulated genes. Among the seven ECF σ genes, only these two genes were subject to GI  are located on the SP-β prophage region in the chromosome  and sunS (Sublancin glycosyltransferase) genes are activated by the transition regulator Abh, whose transcription requires σX in addition to σM, although σM has a minor role . This indicates that glucose addition induces sigX, leading to enhanced transcription of abh and the operon containing sunA. Recently, glucose addition was shown to enhance Sublancin resistance in LB medium . Moreover, between the core promoter regions of sigX and sigM there is no common nucleotide sequence except for the -35 and -10 elements for σX-RNAP and σM-RNAP. Thus, the similar levels of GI in all constructs suggested no involvement of some unknown trans-acting factors in GI.We determined a minimum promoter region responsible for GI in sigX and sigM expression. Thus, three carbon sources were added, and we examined the expression levels of both sig genes. Glycerol or pyruvate addition induced gene expression to some extent, while succinate did not . We note that the effects of pyruvate were modest. Glycerol and pyruvate have been shown to be incorporated into the glycolysis pathway and succinate is not . We observed slow growth and poor cell mass of the mutants as previously reported . Among many candidates of the Tn mutagenesis, only additional four mutations negatively affected GI of both sigX and sigM genes (data not shown). Two carried a disruption of a gene of which function was not yet identified (ylxR and yqfO) and the rests were ptsH and gcp mutants. Probably in the ptsH mutant efficient glucose transport would be inhibited, leading to abolishment of GI. The detailed analysis of these mutants will be reported elsewhere.To further gain insights into the mechanism of GI, we performed transposon mutagenesis for GI-deficient mutants by using a transposon delivery vector, pMarA . Mutantshelicase . TranspocshA is shown in Supplementary Figure cshA seems to be a monocistronic operon with its own promoter and terminator -ddlA-murF . Xylose addition to the culture with glucose also rescued GI of these strains, demonstrating that the cshA gene is responsible for GI. We noted that xylose addition did not have any effect on GI in the control strain with sigX-lacZ nor sigM-lacZ (data not shown).We created a xylose-inducible bkdB using PCR . Xylose addition to the culture with or without glucose caused expression of His-CshA, and the two protein fractions containing His-CshA from the two time points (T0 and T2), were purified by Ni-affinity column . A global analysis of the acetylome in B. subtilis revealed that CshA was acetylated at K244 and K296 . A similar result was reproducibly observed from independent culture (data not shown).We added His-tag to the CshA protein encoded by the cassette at and K296 . Thus, wsigX and sigM due to the inhibition of RNase Y activity through acetylated CshA-dependent mechanism, leading to the longer half-life of mRNAs of sigX and sigM. Otherwise RNase Y may regulate sigX and sigM indirectly. Indeed, sigM expression was enhanced in an RNase Y-depleted mutant, rny, according to the three analyses . With respect to sigM, we observed enhancement of sigM-lacZ expression especially in the log phase as expected . Moreover, GI of sigM was also clearly observed. These results demonstrated that CshA would act on expression of sigX and sigM independent of influence to RNase Y due to interaction of CshA with RNA degradosome.CshA has been known to be involved in RNA degradosome containing endoribonuclease RNase Y . RNase Yanalyses . To examcshA cassette system . In the strain with CshA bearing two K–R substitutions, basal expression was recovered to that of wild type CshA, whereas GI was completely abolished. In the strain with CshA bearing two K–Q substitutions, basal expression was not recovered, whereas GI was observed. These results strongly suggested that acetylation of two lysine residues in CshA is required for GI of sigX and sigM. Moreover, the results also indicated that basal expression and GI of sigX and sigM were mutually distinguishable in a genetic context. We note that the strains bearing wild type and mutant CshA proteins did not grow in culture with 2% glucose in the presence of xylose, and the extent of the resistance against glucose changed in the strains bearing sigX-lacZ and sigM-lacZ due to unknown reasons (data not shown). Thus, different glucose concentrations were used for the experiments for sigX-lacZ and sigM-lacZ.K–R and K–Q mutations have been shown to mimic non-acetylation and acetylation states, respectively . Hence, B. subtilis RNAP reported that half of the RNAP pool was associated with CshA , because stress-responsive sigma factor homologs of σB in B. subtilis and σS in E. coli are lacking in C. crescentus. Metabolic stress such as carbon-starvation induced ECF σ factor σT perhaps in an anti-σ factor dependent manner in this bacterium (sigX and sigM genes independent of their anti-σ factors, probably through a CshA-dependent functional modification of RNAP. This is the first report for GI of ECF σ genes to our knowledge. The addition of glucose to the medium affects σX- and σM-dependent cellular functions, such as Sublancin production and Spx overproduction.Extracytoplasmic function σ factor genes have been shown to be induced mainly by cell envelope and cell membrane stresses through a mechanism involving anti-σ factor embedded in the cell membrane. As an exception, acterium . Our stusigX and sigM. Our model shown in Figure 9 encompasses all of the experimental data: involvement of pdhC, the different effects of carbon sources on GI, the effects of non-acetylation mimicking mutations, and the enhancement of CshA acetylation by glucose, yet some key elements in this model remain unknown. It is of interest whether CshA is acetylated before it binds to RNAP or if acetylation of CshA stimulates RNAP-binding of CshA. In addition, there are several outstanding questions, for example, what enzyme acetylates CshA, or how σX/M replaces σA in the RNAP holoenzyme, during GI. According to an analysis of the RNAP holoenzyme, the core RNAP with no σ factor was barely detected (X/M for σA is a likely event. Generally, competition between housekeeping σA and alternative σ factors for the core RNAP is favorable for σA-binding due to the higher affinity of σA for RNAP (RNA polymerase with acetylated CshA may somehow stimulate the autoregulatory loop of detected . Thus, rfor RNAP . To chanfor RNAP . For exafor RNAP . This deB. subtilis, but with respect to transcription factors, a link between acetylation and a functional change has only been elucidated in very rare cases (Thousands of protein acetylation sites have been reported in re cases . GeneralsigX and sigM, GI was observed in rny-depleted mutant. This indicates that the mechanism of CshA-dependent GI does not occur via mRNA metabolism by RNase Y. Moreover, CshA is required for ribosome biogenesis, and thus CshA has a role in translation (sigX and sigM by CshA cannot be completely excluded. However, it is difficult to speculate how the changes in ribosome biogenesis caused by the cshA depletion results in the specific regulation of sigX and sigM expression. Thus, we favored the model shown in Figure 9, although further experiments will be required to prove the model.CshA has been characterized as a multi-functional protein and required for growth in low temperatures . CshA exnslation . A possiMO and KA designed research, performed experiments and analyzed results. MO wrote the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Some studies have already described how the chromatin structure, through histone modifications, varies from a developmental stage to another in a few unicellular parasites. While H3K4me3 profiles remain relatively constant, H3K27 trimethylation and bivalent methylation show strong variation. Inhibitors (A366 and GSK343) of H3K27 histone methyltransferase activity in S. mansoni efficiently blocked miracidium to sporocyst transition indicating that H3K27 trimethylation is required for life cycle progression. As S. mansoni is a multicellular parasite that significantly affects both the health and economy of endemic areas, a better understanding of fluke developmental processes within the definitive host will likely highlight novel disease control strategies. Towards this goal, we also studied H4K20me1 in female cercariae and adults. In particular, we found that bivalent trimethylation of H3K4 and H3K27 at the transcription start site of genes is a landmark of the cercarial stage. In cercariae, H3K27me3 presence and strong enrichment in H4K20me1 over long regions (10–100 kb) is associated with development related genes. Here, we provide a broad overview of the chromatin structure of a metazoan parasite throughout its most important lifecycle stages. The five developmental stages studied here present distinct chromatin structures, indicating that histone methylation plays an important role during development. Hence, components of the histone methylation (and demethylation) machinery may provide suitable Schistosomiasis control targets.Epigenetic mechanisms and chromatin structure play an important role in development. Their impact is therefore expected to be strong in parasites with complex life cycles and multiple, strikingly different, developmental stages,  Schistosoma mansoni is a parasitic flatworm and causative agent of intestinal schistosomiasis, a neglected tropical disease affecting 67 million people worldwide. The parasite has a complex life cycle involving two consecutive obligate hosts  and two transitions between these hosts as free-swimming larvae. Here, we show that the chromatin structure of five different developmental stages is characterized by specific changes in chemical modifications of histones, basic proteins that are closely associated with DNA . These modifications occur around protein coding genes as well as within repetitive genomic elements. A functional role for histone methylation during schistosome development was elucidated by the use of epi-drugs targeting G9a/GLP and EZH2 histone methyltransferase orthologs in S. mansoni. Our results indicate that histone methylation plays an important role during schistosome development and suggest that the enzymes responsible for maintaining these chromatin modifications are suitable targets for anti-schistosomal drugs. Plasmodium falciparum), leishmaniasis (Leishmania spp.), cryptosporidiosis (Cryptosporidium spp.), Chagas disease (Trypanosoma cruzi) and schistosomiasis  [i.e. any change in chromatin structure [P. falciparum), a similar approach has yet to be taken for a multicellular human endoparasite [Parasites often display complex life cycles that involve several hosts and multiple, phenotypically distinct, developmental stages. This is the case for many human endoparasites, which cause deadly diseases including malaria (ponicum) . Severalponicum) –7. In thtructure . A betteSchistosoma mansoni.If developmental epigenetic changes are detectable in multicellular parasites, they can either reflect global changes in epialleles or changes in the relative number of cells with different chromatin structures within the individual. This is similar to a situation in which epialleles are investigated in a population, and we will therefore use epiallele frequencies as a proxy for chromatin structure profiles. Here, we define “epiallele” as a variation of the same genetic locus that differs in their chromatin structure but not in their DNA sequence or genomic position. Epiallele frequencies represented along DNA sequences will be referred to hereafter as chromatin landscapes. Average profiles over genetic units such as genes will be called chromatin profiles or signatures. The present work investigated how epialleles in the chromatin landscape change during the development of the human parasite S. mansoni is a parasitic platyhelminth (flatworm) responsible for intestinal schistosomiasis (or bilharzia), a neglected tropical disease present in Africa, Caribbean, Middle East, Brazil, Venezuela and Suriname [Fig 1). Eggs released via the feces of the definitive vertebrate host give rise to a free-swimming miracidium larva, by contact with freshwater. Miracidia seek out an intermediate host, a freshwater snail of the Biomphalaria genus [Fig 1). This phenotypic variability has also been found to respond to different environmental stresses , where  quality , interme quality , and def quality , and dru quality ,). In a  quality . We obse quality . TranscrSchistosoma life cycle is characterized by two waves of H3K27 methylation/demethylation around the transcription start site (TSS) of genes; one wave with a maximum of H3K27 trimethylation in Sp1 and another wave of H3K27 trimethylation in adults. Furthermore, bivalent H3K4me3 and H3K27me3 methylation (at the same locus) starts in sporocysts and continues until the adult stage, with the highest frequency observed at transcription start sites in cercariae. The distinct chromatin profile over the life cycle indicate that histone methylation plays an important role during development and we have demonstrated that inhibitors of histone methyltransferase orthologs in S. mansoni arrests miracidium to sporocyst transition. As Picard et al. [i.e. presence of a peak or a stronger peak in cercariae, when compared to adults). Also, we discovered ‘ranges’ spanning 10 to 100 kb, where either H3K27me3 frequency, H4K20me1 frequency, or both, were much stronger  in female cercariae, 98.6% of the time. A gene ontology overrepresentation analysis showed that these ranges with enrichments in H4K20me1  comprise many genes related to development and regulation of transcription.In the present study, we investigate how the chromatin signature changes over the major developmental stages of the parasite: miracidia, primary sporocysts (Sp1), cercariae, schistosomula and adults, and whether other marks might be essential for the human-infecting cercariae to allow their development into adults upon skin penetration. We show here that the frequency of histone methylation marks starts at low levels in miracidia and increases progressively until the adult stage, where sexual reproduction occurs. We also found that the d et al.  has prevMinistère de l’Agriculture et de la Pêche and French Ministère de l’Éducation Nationale de la Recherche et de la Technologie provided permit A66040 to our laboratory for experiments on animals and certificate for animal experimentation  for the experimenters. All mouse procedures leading to the isolation of miracidia and transformation into sporocysts performed at Aberystwyth University (AU) adhered to the United Kingdom Home Office Animals (Scientific Procedures) Act of 1986 (project license PPL 40/3700) as well as the European Union Animals Directive 2010/63/EU and were approved by AU’s Animal Welfare and Ethical Review Body (AWERB).Housing, feeding and animal care at Perpignan followed the national ethical standards established in the writ of 1 February 2013 (NOR: AGRG1238753A) setting the conditions for approval, planning and operation of establishments, breeders and suppliers of animals used for scientific purposes and controls. The French Schistosoma mansoni strain (SmBre) originally sampled in Recife, Brazil, in the 1960s, provided to our laboratory in 1975 by Pr. Y. Golvan (Faculté de Médecine de Paris—Saint Antoine). It has since then been maintained in its sympatric intermediate host strain BgBre of the mollusk Biomphalaria glabrata  and Mus musculus (SWISS) as definitive vertebrate host. The mollusk strain has albinism from genetic origin, but it does not have any impact on the experimental design. At Aberystwyth University, a Puerto Rican strain (NMRI) of S. mansoni was used throughout the study and maintained between M. musculus  and B. glabrata  hosts.SmBre strain were freshly obtained from eggs extracted from the liver of infected mice. Livers were ground by pestle and mortar and eggs were isolated by sequential filtration with sieves. Isolated eggs were transferred into freshwater and exposed to bright light to stimulate egg hatching. Hatched miracidia were collected by pipetting and frozen in liquid nitrogen after removing as much water as possible.Miracidia from the BgBre snails were infected using 10 miracidia per snail. Mollusks were screened for infection a month later, and cercariae shed by each positive B. glabrata were genotyped with sex markers [ markers , 20. Sevin vitro transformation of miracidia. Miracidia were collected for this purpose from freshly hatched eggs extracted from infected hamster livers and placed into wells of a sterile 24-well cell culture cluster  containing 15 mL of sterile Chernin's balanced salt solution (CBSS) supplemented with 2X antibiotics (Penicillin-Streptomycin Sigma P4458). Miracidia were cultured at 26°C without light condition for 48h to induce sporocysts transformation. Transformed primary sporocysts (Sp1) were then carefully transferred into a 15-mL sterile tube and centrifuged at 2000 g and 25°C for 10min. Supernatant was discarded and Sp1 were stored at -80°C until further use. Miracidia used for drug co-culture experiments were processed independently, as described below (histone methyltransferase inhibitors study). Data for cercariae and adult worms were obtained from (i) mixed sex infections or (ii) by monomiracidial infection of BgBre snails [Sporocysts used for chromatin immunoprecipitation followed by sequencing (ChIP-Seq) were obtained through e snails  and anale snails . Worms fS. mansoni was used throughout the study and maintained between M. musculus (HsdOla:MF1) and B. glabrata  for 1 hour and used to percutaneously infect M. musculus (200 cercariae/mouse) [Homo sapiens G9a/GLP and EZH2 histone methyltransferases (HMTs) were obtained from the Structural Genomics Consortium (http://www.thesgc.org), solubilized in DMSO and subsequently diluted to the correct concentration with CBSS. A 500 μL sample of the relevant drug solution was then added to the treatment wells to give a final concentration of 200 μM , 20 μM  10μM , 2 μM  and 0.4 μM  respectively [post hoc analysis with Tukey’s multiple comparison test was performed to infer statistical significance. A miracidium was considered to have fully transformed if all ciliated plates had been shed, and partially transformed if some plates were still attached. Representative images were subsequently acquired at low power (10X objective).A Puerto Rican strain (NMRI) of d hybrid  hosts). e/mouse) . At sevee/mouse) . Followiectively , 24–27. S. mansoni in Cosseau et al. [http://ihpe.univ-perp.fr/methods/methods/native_chip_sm_3.htm).We performed native chromatin immunoprecipitation followed by sequencing (ChIP-Seq) for all developmental stages as described for u et al.   are in S. mansoni [For each sample, we used a control without antibody to assess nonspecific background (bound fraction) and input (unbound fraction). Inputs were used for normalization in all subsequent bioinformatics analyses. Antibodies were carefully tested for specificity as described , had bee mansoni  and werehttp://gqinnovationcenter.com/index.aspx). Briefly, fragmented DNA was quantified using a 2100 Bioanalyzer (Agilent Technologies). Libraries were generated robotically with 10 ng of fragmented DNA (range 100–300 bp) using the Kapa HTP Library Preparation Kit (Kapa Biosystems) as per the manufacturer’s recommendations, except that adapters and PCR primers were diluted 100-fold . The size selection step was carried out after the PCR step, and the number of PCR cycles was increased by 6. Adapters and PCR primers were purchased from Integrated DNA Technologies and size selection was performed on a Pippin Prep instrument (SAGE Biosciences Inc). Libraries were quantified using the Quant-iT Pico-Green dsDNA Assay Kit (Life Technologies) and the Kapa Illumina GA with Revised Primers-SYBR Fast Universal kit (D-Mark). Average size fragment was determined using a LabChip GX (PerkinElmer) instrument. Cluster formation on the flow cell was performed using the cBot instrument (Illumina) with four indexed libraries per lane. Sequencing, in the form of 50-cycle single-end reads, was performed on a HiSeq 2000/2500 (Illumina) running HCS software version 2.2.38. Demultiplexed FASTQ files were generated by allowing up to one mismatch in the index.Cercariae, schistosomula and adult stages were sequenced as single-end 50-bp reads on an Illumina HiSeq 2500 at McGill University and Génome Québec Innovation Centre (http://bioinfo.univ-perp.fr [https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). All samples had a minimum average read quality score of 30 over 95% of their length, and no further cleaning steps were performed.All data processing was performed on a local GALAXY instance (-perp.fr ). Read qS. mansoni reference genome v5 [Sequences were aligned to the enome v5  with Bowenome v5  using paenome v5  (samtoolenome v5  (parametenome v5 .S. mansoni. We used chromstaR (v1.2.0) for peak detection and comparative analysis, using epialleles that chromstaR detected in all replicates of a given developmental stage [i.e. each replicate for each developmental stage) and (2) we performed a multivariate HMM over the combined ChIP-seq samples. BAM files from each parasite stage were processed under the combinatorial mode, with a false discovery rate (FDR) cutoff of 0.05 and bin size of 150. We used the input as negative controls for comparative analyses. Transcriptional start sites (TSS) of genes were defined as 3 bp (one base pair upstream and downstream of the +1 transcription site) based on the genome annotation file v.5 downloadable from ftp://ftp.sanger.ac.uk/pub/pathogens/Schistosoma/mansoni/genome/GFF/. A simplified BED file with TSS and transcription end sites (TES) was generated for contigs assembled at chromosome level. Chromosome names were changed to Chr1—ChrW (S1 File). Average histone modification profiles were generated over 8,000 bp windows . Knowing that histone modifications have crucial roles in the regulation of gene expression, we tested the genome-wide coverage (i.e. the percentage of the genome that is covered by the chromatin state) of each histone mark over the genome and at TSS. In the following, chromatin profiles were generated for fragments over several base pairs (bp) in length. Operationally analytical units of different lengths: ‘bins’ (shortest fragment unit of 150 bp), ‘segments’ (consecutive bins that are in the respective state) and ‘regions’ .We started our analyses by characterizing the genome-wide chromatin landscape in five developmental stages of al stage . Chromstal stage . Chromstvice versa). We performed this step for each histone mark separately (univariate) and together (multivariate). The use of a clonal population of cercariae and corresponding adults allowed genotype (and sex)-dependent differences. As each mark has a different distribution, we tested different parameters to assess the best specificity and sensitivity for each histone modification. We noticed after visual inspection that there were two main types of chromatin differences . One type was smaller, spanning 0.3-10kb (segments with no gap) and another type was larger spanning 10–100 kb ; we, therefore, defined two sets of parameters to specifically look for these ‘peaks’ (Table 2) and 'ranges' (Table 3). All differences identified by chromstaR were visually inspected in IGV [S. mansoni v5 annotation [We also used chromstaR  to find d in IGV  and thennotation  and an anotation . We decihttp://pantherdb.org/geneListAnalysis.do) and GO-slim analyses of molecular functions, biological pathways and protein class under default parameters. We built annotated gene lists depending on the different type of chromatin structure enrichment we saw (i.e. which mark(s) were enriched at a given position) and the type of differences  in which they were found. When chromstaR detected a gene in both ‘peaks’ and ‘ranges’ (some of these regions were overlapping), we only considered it in the list of ‘ranges’.List of annotated genes with differential chromatin structure between cercariae and adults were tested for statistical overrepresentation in gene ontology (GO) terms using Panther v12 (http://methdb.univ-perp.fr/cgi/download_dump.cgi?file_name=RepBasePerpignanSma52.fasta), a collection of 3,145 consensus repeat sequences [Fastq reads of ChIP-Seq for each stage of the parasite were aligned to the S. mansoni “repeatome” . First, we analyzed the correlation between all samples to understand how the distribution of both histone marks, spanning the entire genome, changed over all developmental stages. H3K4me3 showed a similar profile between all stages , with over 60% of peak positions being conserved throughout all stages . H3K27me3 peaks display a much weaker correlation (0–25% of the peaks conserved between stages) and a very different profile , suggesting that this repressive mark is stage-specific. Genome-wide frequency analyses revealed that the presence of both histone marks followed a wave pattern throughout the life cycle. Simultaneous presence of two histone modifications (H3K4me3 and H3K27me3), occur in 5.8%-35.2% of S. mansoni genome from miracidia to adult worms. Genome-wide, H3K27me3 accumulates in Sp1 and adult stages, and is relatively low during miracidia, cercariae and schistosomula stages . When not associated with another mark that we have studied, H3K4me3 is stable throughout the life cycle and only slightly increases during the Sp1 and schistosomula stages . Bivalent marks  occur in Sp1, cercariae and adults, but were at the highest level at the cercarial stage. The pattern of active H3K4me3 and repressive H3K27me3 is different over the whole genome and showed some specificity when focused at the TSS . Throughout the schistosome life cycle, two sharp increases in H3K4me3 at the TSS can be seen (peaking during Sp1 and schistosomula). Similarly, H3K27me3 at the TSS also displays two peaks found in both Sp1 and adult stages. Bivalent marks at the TSS are at their maximum during the cercarial stage .We calculated the genome-wide coverage of trimethylation of histone 3 at lysine 4 (H3K4me3) and at lysine 27 (H3K27me3) in five developmental stages of Fig 3). In free-swimming miracidia, we detected the presence of H3K4me3 over 36.8% of TSS and H3K27me3 over 2.2% of TSS. H3K4me3 segments cover 11,834 kb of the genome and starts around the TSS and do not spread more than 3,000 bp downstream of the TSS (Table 3). When the miracidium loses its ciliated surface to become a Sp1, H3K4me3 increases to be present at 38.7% of TSS. H3K27me3 also increases to be present over 15.5% of TSS . Also, we observed that bivalent methylation starts in Sp1  spanning -2000 bp to +500 bp in 1.78% of the TSS .Next, we looked at how histone marks were distributed around the transcription start sites (TSS) of genes . After the cercaria to schistosomula transformation, H3K4me3 reaches coverage levels of 41.81% at TSS. Also, a strong loss of H3K27me3 is observed with only 2.93% of TSS covered, and no bivalent state observed around TSS .The transition to cercariae is characterized by a notable increase in bivalent marks (H3K4me3 and H3K27me3), occurring at 32.7% of all TSS (-500 to +1000 bp). In cercariae, H3K4me3 covers 9,990 kb of the genome (5.22% of TSS), starting around 500 bp upstream of TSS. For the broad H3K27me3, 32,756 kb of the genome are covered (5.54% of TSS), slightly upstream of the gene body, and decreases while the bivalency increases around TSS . H3K27me3 covers 133,653 kb and the coverage at TSS increases 4-fold inside the definitive host in comparison to the previous stage (from 2.93% in schistosomula to 14.38% in adults). The active H3K4me3 mark covers 10,493 kb (24.1% of TSS) and starts around 500 bp upstream while the repressive HK27me3 mark decreases. The bivalent methylation in adult worm (-500 to +1000 bp) reaches 10% of coverage at TSS (Table 4).In adults, 60 days post-infection, a notable increase in trimethylation of H3K27 is observed  and the environment can be easily controlled. Specifically, we used drugs targeting H. sapiens G9a/GLP (A366) and EZH2 (GSK343) H3K27 methyltransferases to assess the ability of these epidrugs to block transformation efficiency . In the presence of both drugs, the miracidium to sporocyst transformation efficiency was significantly reduced when compared to the DMSO controls, even at concentrations as low as 0.4 μM. In DMSO controls, 64% of miracidia fully transformed into sporocysts while exposure to 0.4 μM and 2 μM of A366 significantly reduced transformation efficiency to 28% and 24%, respectively (p<0.005). Additionally, for GSK343, there was a dose-dependent decrease in transformation efficiency, as there was a significant difference (p<0.005) in transformation efficiencies between the 0.4 μM (21% fully transformed) and 2 μM (17% fully transformed) cultures . These results suggest that changes in H3K27me3  are essential for life cycle progression in S. mansoni.Since our chromatin landscape studies had identified trimethylation of H3K27 as a histone modification that undergoes major modifications during the life cycle, we wondered if histone modification would be cause or consequence of stage to stage progression. We reasoned that if pharmacological inhibition of this modification results in blocking the life cycle then histone modifications are cause of the developmental plasticity. We decided to test this hypothesis at the miracidium to sporocyst transition where the increase in H3K27 trimethylation is most pronounced , characterized by the presence/absence in one stage and its absence in another, or when the enrichment in one condition is significantly more intense in one stage . To target the gender that has the highest impact on host morbidity (driven by parasite egg production), we focused our generation of ChIP-Seq data on female and maximized the signal for this analysis .To gain further insights into chromatin modifications in the transition that is of principal medical interest,  embryos . KnowingS2 File for a detailed identification of all these regions). In 14% of the cases (169), two or more marks displayed a different profile . Details about the distribution of the differential enrichment are in Table 5. The most striking feature is that the vast majority of the differences for all three marks occur with a peak or stronger peak in cercariae. 82% of the differences involving H3K4me3, 96% of the differences in H3K27me3 and 92% of the differences in H4K20 are characterized by new peaks or peaks that are stronger in cercariae. These differentially enriched regions are preferentially located within annotated genes or transcripts [Using chromstaR, we investigated 6,182 peaks  for H3K4me3, 22,562  for H3K27me3 and 20,468  for H4K20me1, to spot significant differences between female cercariae and female adults. We identified a total of 1,195 peaks (< 10 kb) where at least one histone mark showed a differential enrichment between cercariae and adults . We adjusted chromstaR parameters to specifically detect these wide regions. We found 851 of them (from 10 to 100 kb long) in cercariae, and only 15 of them in adults. In cercariae, 488 were enriched in H4K20me1, 186 in H3K27me3 and 177 in both. These ranges contained at least one gene, with the exception of regions enriched in both H3K27me3 and H4K20me1 (Table 6). Genomic coordinates of these regions are available in S3 File and gene lists present in these regions can be consulted in S4 File.While performing visual inspection to validate the differentially enriched regions identified by chromstaR, we observed wide ranges (from 10 to 100 kb long) with a differential chromatin structure (see Table 7). We separated genes found in peaks from the ones found in ranges. When chromstaR found the same gene in both peak and range region, we excluded it from the peak. There was no overrepresentation in adults at all. This was not surprising due to the relatively low number of enriched regions in adults, when compared to cercariae. In peaks identified in female cercariae, we only found overrepresentation of GO terms associated with regulation of transcription to contain the repressive H3K27me3 mark. In ranges, we found that the presence of H4K20me1 is strikingly associated with developmental functions such as homeobox transcription factors, regulation of transcription, and the NOTCH pathway.We were curious to know if genes present in differentially enriched chromatin regions would present specific molecular or biological functions. To investigate this matter, we performed gene ontology overrepresentation tests. To make our analysis as precise as possible, we tested different gene lists depending on the chromatin structure present at the differentially enriched regions . Stages can be segregated by histone methylation on repeats alone. However, for miracidia and Sp1, in contrast to histone modifications in the TSS, histone methylation at repeats is very similar. This indicates that modification of histone methylation in TSS in miracidia to Sp1 is very specific.The repeatome of Here, we describe for the first time the dynamic nature of two histone modifications throughout the five major developmental stages of a multicellular human pathogen. There are clear distinctions in the histone modification pattern between the stages, and interestingly, we observe that both studied marks follow a cyclic distribution throughout the parasite’s life cycle.S. mansoni cercariae and adults that this mark was also preferentially distributed around TSS of genes, similarly to what is found in other metazoans [Fig 2D), but when we focus on TSS only, we see a strong decrease of solely H3K4me3 in cercariae . In this stage, most TSS have bivalent methylation and transcription is probably poised there. This fits the low transcription level in this developmental stage [In the literature, H3K4me3 is known to be associated with promoters and transcription start sites of transcriptionally competent genes of vertebrates and invertebrates –44. Thisetazoans . We can al stage .i.e. genomic regions that become heterochromatic in certain cells, tissues, or depending on the developmental processes), which impedes transcription [S. mansoni, the genome-wide distribution of this mark broadly fluctuates throughout development, with two peaks occurring at the Sp1 and the adult stages. In contrast, this mark is globally very low in miracidia and schistosomula. In cercariae, the mark co-localizes with H3K4me3 . In zebrafish, fruit flies and mice, the removal of H3K27me3 plays an important role in key developmental stages, tissue regeneration and cell differentiation [S. mansoni for transition from cercariae to schistosomula. In the case of primary sporocysts, in which cells multiply at a high rate to produce hundreds of secondary sporocysts and then mature in cercariae, the addition of H3K27me3 to H3K4me3 at TSS probably promotes cell growth without differentiation [Vasa-like  that are required for proliferation and expansion of neoblasts, putative polo kinase (Smp_009600) that is probably activating mitosis, and fibroblast growth factor receptor-encoding genes  that are potentially required for cell cycle and DNA repair machinery [H3K27me3 is generally described as a mark associated with facultative heterochromatin . On the other hand, cercariae are a product of asexual multiplication within secondary sporocysts (Sp2). It is possible that, in S. mansoni, bivalent histone marks are only involved in asexual multiplication. It would be interesting to see if this bivalency in cercariae is conserved in other Schistosoma species. Miracidia actually have the lowest amount of bivalent marks  throughout the whole lifecycle suggesting a more euchromatic situation in general. We have previously demonstrated that histone deacetylation inhibitors can reversibly inhibit miracidia to sporocyst transition, suggesting that heterochromatisation is important during this step [S. mansoni genome assembly. This would suggest that A366 exerts its activity via promiscuous inhibition of other schistosome HMTs (responsible for H3K27me3 or other modifications) [The presence of the ive mark –52,54. Wive mark . Throughive mark –56, we iive mark . With thhis step . Here, whis step ,60. In bcations) , 62. Nevi.e. without confounding potentially sex-specific effects) and because females play a crucial role in morbidity of the mammal host, through egg production. A possible caveat of our experiment is that we obtained female adults from single sex, clonal infection. Hence, the females we collected are not fully mature, and the chromatin structure we observe will not show any specific chromatin changes corresponding to sexual maturation. Also, for both cercariae and adults, we used a very limited number of genotypes due to clonal infections. In total, we had two female genotypes (one was done in replicate). The objective was to have a better, clearer signal and to see how the chromatin structure from a single genotype would evolve from one developmental stage to another. As the Schistosoma SmBre strain that we used has a very low genetic diversity, and we previously observed very low epigenetic difference between these two genotypes [S. mansoni genome due to its high repetitive DNA content (where no sequence reads are mapped) and, therefore, peak calling parameters needed to be adjusted. The number of differential peaks is relatively high in H3K4me3  but much lower for H3K27me3  and H4K20me1 . These differences are mainly characterized by the presence of a peak or a stronger peak in cercariae and its absence or reduced size in adults . These changes occur mostly around the transcription start sites of genes, hinting at a possible effect on gene regulation. No specific pathway was found, but there is an over-representation of genes involved in regulation of transcription and DNA binding in regions with increased H3K27me3 in cercariae. The presence of this repressive mark in genes involved in transcription control fits our previous observation regarding the poised transcriptional state in cercariae. We then looked at the ranges (10 to 100 kb long), which were differentially enriched in H3K27me3, H4K20me1, or both. Once again, most of the enrichments occur in cercariae . Ranges with differential enrichment in cercariae of H4K20me1 alone or combined with H3K27me3 present an overrepresentation of genes involved in regulation of transcription and developmental processes. We also highlighted the presence of the Notch signaling pathway in regions differentially enriched in H4K20me1 in cercariae. Notch signaling is a very well conserved metabolic path in metazoans, involved in embryonic development, cell lineage and tissue regeneration [We wanted to better characterize the chromatin structural changes between cercariae and adults, as this transition is fundamental in the epidemiology of the parasite, and a better understanding could lead to the discovery of new therapeutic targets. Our laboratory has previously demonstrated that in male cercariae H3K27 trimethylation around TSS is much stronger than in female cercariae and that there are pronounced changes in H3K27me3 associated with transition into adult males . For thienotypes , we belienotypes ), quiescenotypes , is assoenotypes  and playenotypes ,66. As wneration . Interesneration  and alsoTable 7), but we can assume that different mechanisms could be associated with these differential chromatin structures. For example, genes marked with one of the two chromatin mark combinations could be activated faster than the other upon penetration of the cercariae in the host. We found little information regarding the co-localization of H4K20me1 and H3K27me3 over such ranges, only that in Drosophila it was involved in early embryo development [Schistosoma. The presence of ranges with differential enrichment was previously described with H3K27me3 in mouse embryonic fibroblast and associated with gene-poor and transposable element rich regions [There are not many differences between the overrepresented gene ontology terms in ranges of H4K20me1 only or associated with H3K27me3  H3K4me3 and (B) H3K27me3.Aligned read count over all annotated TSS in the chromosome level assembled  Every line corresponds to an individual TSS, different colors denote differential stability of the mark during the 5 life cycle stages. Greyscale for RPKM.(TIF)Click here for additional data file.S2 FigDifferences in these regions for both marks, identified by chromstaR, are within the dotted lines.(JPEG)Click here for additional data file.S1 FileChromosome names were changed to Chr1-W.(BED)Click here for additional data file.S2 File(XLSX)Click here for additional data file.S3 File(ZIP)Click here for additional data file.S4 File(ZIP)Click here for additional data file.


The mammalian circadian clock relies on the transcription factor CLOCK:BMAL1 to coordinate the rhythmic expression of 15% of the transcriptome and control the daily regulation of biological functions. The recent characterization of CLOCK:BMAL1 cistrome revealed that although CLOCK:BMAL1 binds synchronously to all of its target genes, its transcriptional output is highly heterogeneous. By performing a meta-analysis of several independent genome-wide datasets, we found that the binding of other transcription factors at CLOCK:BMAL1 enhancers likely contribute to the heterogeneity of CLOCK:BMAL1 transcriptional output. While CLOCK:BMAL1 rhythmic DNA binding promotes rhythmic nucleosome removal, it is not sufficient to generate transcriptionally active enhancers as assessed by H3K27ac signal, RNA Polymerase II recruitment, and eRNA expression. Instead, the transcriptional activity of CLOCK:BMAL1 enhancers appears to rely on the activity of ubiquitously expressed transcription factors, and not tissue-specific transcription factors, recruited at nearby binding sites. The contribution of other transcription factors is exemplified by how fasting, which effects several transcription factors but not CLOCK:BMAL1, either decreases or increases the amplitude of many rhythmically expressed CLOCK:BMAL1 target genes. Together, our analysis suggests that CLOCK:BMAL1 promotes a transcriptionally permissive chromatin landscape that primes its target genes for transcription activation rather than directly activating transcription, and provides a new framework to explain how environmental or pathological conditions can reprogram the rhythmic expression of clock-controlled genes. Circadian clocks in mammals rely on the heterodimeric transcription factor CLOCK:BMAL1 to drive rhythmic gene expression and allow biological functions to perform best at the most appropriate time of the day. Investigation of the mechanisms by which CLOCK:BMAL1 regulates its target genes transcription has led to the paradoxical observation that while CLOCK:BMAL1 DNA binding is rhythmic and occurs during the day for all target genes, its transcriptional output is highly heterogeneous. To address this issue, we analyzed independent genome-wide datasets and found that CLOCK:BMAL1 DNA binding during the day is associated with a reorganization of the chromatin that is favorable to transcription activation for all target genes. However, this diurnal CLOCK:BMAL1 DNA binding and chromatin remodeling is not sufficient to promote a transcriptionally active enhancer, therefore suggesting that CLOCK:BMAL1 cooperates with other factors to control the transcription of most of its target genes. This hypothesis is supported by our finding that ubiquitous transcription factors, but not tissue-specific transcription factors, are differentially recruited at CLOCK:BMAL1 enhancers. Altogether, our data highlight the critical role of transcription factors recruited at CLOCK:BMAL1 enhancers in regulating transcription, and present a new mechanistic framework to understand how changes in the environment can reprogram circadian transcriptional programs. Period , Cryptochrome (Cry1 and Cry2), Rev-erb (Rev-erbα and Rev-erbβ) and Ror . Upon expression and maturation, PERs and CRYs form a repressive complex that rhythmically inhibits CLOCK:BMAL1-mediated transcription first on-DNA and then off-DNA . Fo. FoBmal1et genes .Clock, Bmal1 and several direct rhythmic target genes  are unaffected by fasting, some other targets exhibit a significantly altered gene expression profile  while other targets exhibit an increased amplitude of expression   . Remarkaondition . Becauseondition  57]..Clock, BBased on the mechanisms by which CLOCK:BMAL1 regulates the expression of several core clock genes, it is commonly assumed that the rhythmic binding of CLOCK:BMAL1 to DNA is necessary and sufficient to drive the rhythmic transcription of its target genes. However, the recent characterization of CLOCK and BMAL1 cistromes in the mouse liver revealed that CLOCK:BMAL1 target gene transcription is highly heterogeneous, thereby suggesting that CLOCK:BMAL1 regulation of clock-controlled gene expression relies on more complex mechanisms than those underlying core clock gene rhythmic transcription , 28–30. Neurospora (WCC for White Collar Complex) and Drosophila (CLK:CYC heterodimer) are based largely on how they regulate the expression of the core clock genes frequency (in Neurospora), and period and timeless (in Drosophila) [The current models describing the regulation of rhythmic gene expression by circadian clocks in other eukaryotes are also based on how core clock components regulate their own transcription via transcriptional feedback loops. For example, the mechanisms underlying transcriptional regulation by CLOCK:BMAL1 orthologs in sophila) , 58–60. sophila) , 62, andsophila) –67.etc.), they would be transcriptionally inactive and require the binding of other transcription-associated factors needed to trigger H3K27ac and rhythmic transcription.The recent characterization of many transcription factor cistromes revealed that the number of transcription factor DNA binding sites often exceeds the number of anticipated target genes, suggesting that many of these DNA binding sites are non-functional , 69. AltBmal1-/- mice, we propose that a major function of CLOCK:BMAL1 is to facilitate the recruitment of both positive and negative transcription factors to drive the rhythmic transcription of clock-controlled genes . Although the mechanisms underlying of this cooperation between CLOCK:BMAL1 and other transcription factors are still unknown, nucleosome-mediated cooperation between transcription factors is not unprecedented [Investigation of the transcription factors that are recruited at CLOCK:BMAL1 enhancers revealed a surprising difference between u-TFs and ts-TFs. In particular, ts-TFs are recruited at similar levels between expressed and non-expressed CLOCK:BMAL1 target genes, suggesting that they do not significantly contribute to the heterogeneity of CLOCK:BMAL1 transcriptional output. Because ts-TFs are known to establish tissue-specific enhancers and enable the binding of u-TFs in a tissue-specific manner –75, it icedented –82, and This cooperation between CLOCK:BMAL1 and other TFs may explain why a large fraction of CLOCK:BMAL1 target genes are not expressed: u-TF recruitment is not sufficient to activate CLOCK:BMAL1 enhancers and promote transcription. In support of this idea, CLOCK:BMAL1 enhancers targeting non-expressed target genes are enriched for the NF-κB transcription factor motif, which is known to mediate transcriptional response to immune and inflammatory responses . BecauseTranscription regulation in higher eukaryotes relies on the activity of multiple enhancers , 89. It It was recently proposed that altering the environmental conditions can reprogram circadian transcriptional programs .In conclusion, our data indicate that the mechanisms by which CLOCK:BMAL1 regulates the transcription of core clock genes do not apply to clock-controlled genes, and suggest that the primary function of CLOCK:BMAL1 is to regulate the chromatin landscape at its enhancers to facilitate the binding of other transcription factors. Our results therefore highlight the emerging role of other transcription factors in regulating the ~15% of genes that are rhythmically expressed in a given mammalian tissue, and suggests that clock-controlled gene expression relies more on the interplay between the circadian clock and other signaling pathways. Given that the majority of CLOCK:BMAL1 target genes are either arrhythmically or not expressed under standard conditions, our data also suggest that these non-oscillating genes may become rhythmically expressed under other environmental and/or pathological conditions, and thus expand the total number of genes under circadian control to more than 50% in mammals . FinallyUnless notified below, publically available datasets used in this paper were downloaded from the NCBI or EBI websites in either sra or fastq formats  Rhythmic transcription in phase with CLOCK:BMAL1 binding (peak of transcription between ZT02 and ZT12), 205 CLOCK:BMAL1 peaks,(ii) Rhythmic transcription out-of-phase with CLOCK:BMAL1 binding (peak of transcription between ZT12 and ZT02), 124 CLOCK:BMAL1 peaks,(iii) Arrhythmic transcription, 654 CLOCK:BMAL1 peaks . Note that to decrease the number of false positive in the list of arrhythmically expressed genes, we removed genes that exhibit arrhythmic nascent RNA expression, but exhibit rhythmic mRNA expression  Not transcribed (average reads/bp between the 12 sample < 1), 291 CLOCK:BMAL1 peaks.The remaining peaks, which were not analyzed in this study, were categorized as:(v) Post-transcriptional cyclers, 262 CLOCK:BMAL1 peaks. These peaks target genes with an arrhythmic Nascent-Seq signal, but rhythmic RNA-Seq signal .(vi) Low expression levels, 588 CLOCK:BMAL1 peaks. These CLOCK:BMAL1 peaks target genes with Nascent-Seq and/or RNA-Seq signals that are below threshold for the analysis of rhythmic expression, but above the threshold of 1 read/bp set to define the “not-expressed” CLOCK:BMAL1 target genes. These thresholds were defined in Menet et al., 2012 .(vii) No signal value, 334 CLOCK:BMAL1 peaks. These peaks were assigned to a target gene , but no information was found in the Nascent-Seq or RNA-Seq. Several of these peaks target genes encoding for a non-coding RNA, as well as genes with alternative gene symbol.The list of the 3217 CLOCK:BMAL1 peaks parsed into the different transcriptional output categories is provided in ChIP-Seq, MNase-Seq and GRO-Seq signal was retrieved from bam files containing uniquely mapped reads (and duplicated reads removed) at CLOCK:BMAL1 enhancers using custom-made scripts . SpecifiCLOCK:BMAL1 peak center ± 250 bp for transcription factors, CBP, p300 and Pol II,CLOCK:BMAL1 peak center ± 1kb for histone modifications,CLOCK:BMAL1 peak center ± 500 bp for eRNA,CLOCK:BMAL1 peak center ± 75bp for nucleosome signal,and normalized to the sequencing depth. Differences in the window size were calculated based on the width of the ChIP-Seq signal at CLOCK:BMAL1 DNA binding sites . Because we aimed at assessing the role of CLOCK:BMAL1 in removing a nucleosome at its DNA binding site, we chose a narrower window size of 150bp see . All anaEnhancers lying into CLOCK:BMAL1 target gene loci (-10kb from the transcription start site to +1kb from the transcription termination site) were identified using a public mouse liver DNAse-Seq dataset (see above)  and bedt(i) In-phase transcription cyclers: 1548 DHS peaks,(ii) Out-of-phase transcription cyclers: 1189 DHS peaks,(iii) Arrhythmically expressed target genes, 5830 DHS peaks,(iv) Not expressed target genes, 991 DHS peaks.H3K27ac and Pol II ChIP-Seq signals, as well as GRO-Seq (eRNA) signal, were retrieved at those DHS sites (as well as those overlapping with a CLOCK:BMAL1 peak) using the DHS peak coordinate and normalized to 100,000,000 reads. Signal was then normalized to the coordinate length (in bp) to obtain the signal displayed as reads/bp per 100,000,000 reads. The coordinates used were, for the same reason as above for CLOCK:BMAL1 DNA binding sites:H3K27ac ChIP-Seq: DHS genomic coordinate center ± 1 kb,Pol II ChIP-Seq: DHS “real” genomic coordinates,GRO-Seq : DHS genomic coordinate center ± 500 bp.Because our analysis revealed the existence of small but significant overall variations of H3K27ac and Pol II ChIP-Seq signal between time points see , we furtMotif analysis was performed at CLOCK:BMAL1 enhancers  for each of the transcriptional categories using the findsMotifGenome.pl script from the HOMER suite. Parameters were as the following: -size given–len8. The resulting table was sorted by the q-value and a q-value less than 0.05 was considered significant. Percent enrichment (percent of target sequences with motifs / percent of background sequences with motif) was then calculated for motifs found to be significant in at least one of the CLOCK:BMAL1 transcriptional output category. Results of the motif analysis are provided as To determine the variance of each TF DNA binding  between the four CLOCK:BMAL1 transcriptional output categories, we computed a TF DNA binding “variability index” based on the analysis performed in To determine if the results described in this paper are specific to CLOCK:BMAL1, we also performed an analysis on genes not targeted by CLOCK:BMAL1, but exhibiting similar profiles of expression to the 4 CLOCK:BMAL1 transcriptional output categories . To this end, 125 genes were randomly selected for each of the 4 groups, using criteria similar to those used to define CLOCK:BMAL1 transcriptional output (see above). Levels of expression for each group were not significantly different to those of CLOCK:BMAL1 target genes . Nucleosome signal, H3K27ac ChIP-Seq signal, Pol II ChIP-Seq signal, eRNA expression, tissue specific and ubiquitous transcription factor ChIP-Seq signal were all calculated as described above for CLOCK:BMAL1 target genes. Statistical analysis was also performed similarly to CLOCK:BMAL1 transcriptional output.Pro 12.0.1. SAS Institute Inc., Cary, NC, 1989–2007. Differences in sequencing signal, represented in the boxplot graphs, were analyzed for statistical enrichment using the nonparametric Kruskal-Wallis test. Rhythmic analysis of nucleosome signal and ChIP-Seq signal was performed using a Fourier analysis Click here for additional data file.S2 Figvs. DD) impact BMAL1 rhythmic DNA binding phase and signal. A. Correlation between BMAL1 ChIP-Seq signal in LD and DD for each of the 4 CLOCK:BMAL1 transcriptional output categories ; rhythmic out-of-phase ; arrhythmic ; and non expressed  target genes). Peaks targeting core clock genes are depicted with an open circle. B. Correlation between the phase of BMAL1 DNA binding in LD and DD for each of the 4 CLOCK:BMAL1 transcriptional output categories. C. Correlation between the phase of BMAL1 DNA binding in LD and DD for all 3217 CLOCK:BMAL1 ChIP-Seq peaks from the Koike et al., 2012 dataset  or constant darkness  were compared to determine if the lighting conditions (LD aset see . ChIP-Se(TIF)Click here for additional data file.S3 FigA. Analysis of BMAL1 ChIP-Seq signal from Koike et al. (2012) at CLOCK:BMAL1 peaks targeting rhythmically transcribed genes (RG), arrhythmically transcribed genes (AR) or not transcribed genes (NE). Peaks targeting rhythmic targets are binned in 5 groups of equal size for either all peaks , or those targeting non-core clock genes only . Data are represented as boxplots for each group and time points, and the thick line displays CLOCK:BMAL1 DNA binding rhythm based on the median of ChIP-Seq signal. Statistical analysis was performed by Kruskal-Wallis non-parametric test, and pair-wise post-hoc analyses are displayed for each of the six time points using color-coding of the p-values. B. Phases of nascent RNA expression of rhythmically transcribed CLOCK:BMAL1 target genes are displayed for either all rhythmic target genes , or only non-core clock rhythmic target genes . Nascent RNA expression was retrieved from Menet et al., 2012. C. Analysis of CLOCK ChIP-Seq signal from Koike et al. (2012) at CLOCK:BMAL1 peaks was performed as for BMAL1 ChIP-Seq signal in A. D. Nascent RNA expression of rhythmically transcribed CLOCK:BMAL1 is displayed for either all rhythmic targets (groups RG1 to RG5), or for non-core clock target genes (groups RG1’ to RG5’), as well was for arrhythmically transcribed target genes (AR), or non-expressed target genes (NE). Groups with different letters are significantly different .(TIF)Click here for additional data file.S4 FigPer1, Per2, Cry2, Dbp, Rev-erbα, and Rev-erbβ; circles filled in red), extended core clock genes , to those targeting clock-controlled genes . CLOCK:BMAL1 peaks targeting arrhythmically transcribed genes (circles filled in black) and non expressed genes (circles filled in grey) are shown for comparison. C. Correlation between the phase of BMAL1 (top) or CLOCK (bottom) DNA binding and the phase of transcription of rhythmically transcribed CLOCK:BMAL1 target genes in the mouse liver. D. Correlation between BMAL1 ChIP-Seq signal and nascent RNA expression levels of CLOCK:BMAL1 target genes in the mouse liver, parsed based on the transcriptional output of CLOCK:BMAL1 target genes.A. Correlation between BMAL1 and CLOCK ChIP-Seq signal at CLOCK:BMAL1 ChIP-Seq peaks in the mouse liver from Koike et al., 2012 datasets, parsed based on the transcriptional output of CLOCK:BMAL1 target genes . B. Correlation between BMAL1 (top) and CLOCK (bottom) ChIP-Seq signal and the phase of nascent RNA expression of rhythmic CLOCK:BMAL1 target genes in the mouse liver . The dash lines depict the cut-offs used to partition the in-phase cyclers  to the out-of-phase cyclers . Distinction is made between CLOCK:BMAL1 peaks targeting core clock genes ((TIF)Click here for additional data file.S5 FigPer1, Per2, Cry2, Dbp, Rev-erbα, and Rev-erbβ); Bottom table: CLOCK:BMAL1 target genes without core clock genes  and other associated clock genes . Yellow boxes indicate the location of clock genes within the table. The distribution of the number of CLOCK:BMAL1 ChIP-Seq peaks per gene is also displayed as a pie chart for all CLOCK:BMAL1 peaks. Groups with different letters are significantly different (Fischer's exact test (two-sided test); p < 0.05). B, C. BMAL1 (B) and CLOCK (C) ChIP-Seq signal at CLOCK:BMAL1 ChIP-Seq peaks  is displayed for each of CLOCK:BMAL1 transcriptional output category. In this analysis, ChIP-Seq signal at CLOCK:BMAL1 peaks targeting the same gene was summed up (see panel A for the number of genes with multiple peaks for each category). Groups with different letters are significantly different . D. Nascent RNA expression of CLOCK:BMAL1 target genes parsed based on CLOCK:BMAL1 target gene transcription, for all CLOCK:BMAL1 targets (left), target genes without core clock genes (middle), and target genes without core clock genes and other associated clock genes . Groups with different letters are significantly different .A. The number of CLOCK:BMAL1 target genes is displayed based on the number of CLOCK:BMAL1 ChIP-Seq peaks for each of the 4 categories of CLOCK:BMAL1 transcriptional output . Top table: all CLOCK:BMAL1 target genes; Middle table: target genes without core clock genes ((TIF)Click here for additional data file.S6 FigLeft) Circadian rhythm of BMAL1 and CLOCK ChIP-Seq signal in the mouse liver at CLOCK:BMAL1 DNA binding sites for each of the 4 CLOCK:BMAL1 transcriptional output groups. (Right) Distribution of BMAL1 and CLOCK ChIP-Seq signal for each of the 4 CLOCK:BMAL1 transcriptional output groups at the time of maximal DNA binding (CT04 for BMAL1 and CT08 for CLOCK). B. (Left) Circadian rhythm of PER1, PER2, CRY1, and CRY2 ChIP-Seq signal in the mouse liver at CLOCK:BMAL1 DNA binding sites for each of the 4 CLOCK:BMAL1 transcriptional output groups. (Right) Distribution of PER1, PER2, CRY1, and CRY2 ChIP-Seq signal for each of the 4 CLOCK:BMAL1 transcriptional output group at the time of maximal DNA binding Click here for additional data file.S7 FigCry2, Dbp, Rev-erbα, and Rev-erbβ for the Rinφ group, and of the peaks targeting Per1 and Per2 for the Ro/φ group. E: maximal and minimal nucleosome signal from the 6-time points rhythms for each of the CLOCK:BMAL1 transcriptional output groups. Groups with different letters are significantly different .A-D: Nucleosome signal was retrieved from mouse liver MNase-Seq datasets , which consists of 6 time points each separated by 4 hours with n = 4 mice for each time point. Each graph displays a 6-time points rhythm of nucleosome signal at CLOCK:BMAL1 binding sites , displayed as the average ± s.e.m. of the signal (n = 4) calculated for each mouse and for each transcriptional output category: (A) Rhythmic-in-phase ; (B) Rhythmic out-of-phase ; (C) arrhythmic ; (D) non expressed  target genes). The phase of rhythm  is indicated in the bottom right. Each rhythm is double-plotted for better visualization. For both Rinφ and Ro/φ groups, the nucleosome rhythm is calculated at all CLOCK:BMAL1 peaks targeting rhythmic target genes (left), or only at peaks targeting rhythmic non core clock genes Click here for additional data file.S8 FigLeft; blue background) or at non-CLOCK:BMAL1 enhancers located in CLOCK:BMAL1 target genes  for each of the 4 CLOCK:BMAL1 transcriptional output groups: rhythmic-in-phase ; rhythmic out-of-phase ; arrhythmic ; and non expressed  target genes. Datasets were retrieved from Koike et al., 2012 (top) or Vollmers et al., 2012 (bottom) and re-analyzed Click here for additional data file.S9 FigEnrichment for transcription factor DNA binding motifs  at CLOCK:BMAL1 DNA binding sites for each of the four CLOCK:BMAL1 transcriptional output categories: rhythmic-in-phase ; rhythmic out-of-phase ; arrhythmic ; and non expressed  target genes. Enrichment is reported as the ratio between the calculated enrichment over the calculated background. * q < 0.05 (Benjamini-Hochberg procedure). Motif enrichment is shown for: CLOCK:BMAL1 (A); tissue-specific transcription factors (B); as well as ubiquitous transcription factors for which the motif is enriched for all 4 output groups (C) or specific group(s) (D).(TIF)Click here for additional data file.S10 FigMouse liver ChIP-Seq signal of tissue-specific transcription factors (A), ubiquitous transcription factors , and transcriptional co-activators / RNA Polymerase II at ZT10 (D) at CLOCK:BMAL1 DNA binding sites (peak center ± 250bp) for each of the transcriptional output categories. ChIP-Seq signal is represented for each output group based on its distribution (every decile). Groups with different letters are significantly different .(TIF)Click here for additional data file.S11 Fig Nucleosome signal at TF ChIP-Seq peaks harboring a CLOCK:BMAL1 peak (blue), or at the top 10,000 TF ChIP-Seq peaks that do not harbor a CLOCK:BMAL1 peak (green).  Nucleosome signal at TF ChIP-Seq peaks harboring a CLOCK:BMAL1 peak, and parsed based on CLOCK:BMAL1 transcriptional output: Rhythmic-in-phase , Rhythmic out-of-phase , arrhythmic , and non expressed .Nucleosome signal at four TF DNA binding sites was retrieved from mouse liver MNase-Seq datasets , which consists of 6 time points each separated by 4 hours with n = 4 mice for each time point. MNase-Seq data are displayed for two tissue-specific TFs: FOXA2 (A) and HNF6 (B), and two ubiquitous TFs: REV-ERBα (C) and ERα (D). Nucleosome signal was calculated at TF peak center ± 75 bp for each peak and at each TF ChIP-Seq peak coordinate, and is displayed as the average ± s.e.m of the signal (n = 4) calculated for each mouse. Each rhythm is double-plotted for better visualization. (TIF)Click here for additional data file.S12 Figad libitum, and that exhibit under fasting condition a decrease in the rhythm amplitude (first column), no change (second column) or an increase in the rhythm amplitude (third column). Mouse liver mRNA expression is also displayed for CLOCK:BMAL1 target genes that are arrhythmically expressed in the liver of mice fed ad libitum, and that exhibit rhythmic expression under fasting condition.Rhythm of mRNA expression in the liver of mice fed ad libitum (blue) or fasted for at least 22 hours (orange). Data were retrieved from a public dataset . Mouse liver mRNA expression is displayed for CLOCK:BMAL1 target genes that are rhythmically expressed in the liver of mice fed (TIF)Click here for additional data file.S13 FigClock and Bmal1 (A), and some CLOCK:BMAL1 target genes that are rhythmic under both normal chow and high fat diet (B); normal chow only (C); and high fat diet only (D).A-D. Six-time point rhythm of liver mRNA expression in mice fed with normal chow (black) or high fat diet (blue). Values were retrieved from a public dataset  and corr(TIF)Click here for additional data file.S14 FigAnalysis of a random set of genes not targeted by CLOCK:BMAL1 and transcribed similarly to the 4 CLOCK:BMAL1 transcriptional output groups (n = 125 genes for each group) was performed to determine the extent to which the findings reported in the manuscript are specific to CLOCK:BMAL1. The same criteria as those used for the characterization of CLOCK:BMAL1 transcriptional output were used, and groups are thus similarly referred as Rhythmic-in-phase , Rhythmic out-of-phase , arrhythmic , and non expressed . Cis-regulatory regions targeting the randomly selected control genes are defined as DNase I hypersensitive sites (DHS) located within -10kb of the TSS to +1kb of the TTS (similarly to what was done for CLOCK:BMAL1 target genes). Analysis of these DHS suggests that many of our findings are specific to CLOCK:BMAL1 A. Heatmap displaying nascent RNA expression of the random set of genes and parsed based on the transcriptional output. Nascent-Seq signal was ordered based on the phase of nascent RNA oscillations for the in-phase and out-of-phase transcriptional cyclers. Ordering of arrhythmically transcribed genes is based on the peak time of maximal expression; the lack of a distinctive 24-hr rhythm profile of nascent RNA expression over the 48-hr time-scale is indicative of arrhythmic transcription. NE genes are not displayed due to the lack of expression. B. Average nascent RNA expression level for the 4 control groups. C-D. BMAL1 (C) and CLOCK (D) ChIP-Seq signal at DNase I hypersensitive sites (DHS) targeting the randomly selected control genes. ChIP-Seq signal for CLOCK:BMAL1 target genes is provided for comparison. E. Nucleosome rhythm at DHS targeting the randomly selected control genes (similar to (TIF)Click here for additional data file.S15 FigLif and Bottom: Adc), and exhibiting significant CTCF ChIP-Seq signal. Arrows with question marks indicate a potential CTCF-mediated long-range chromatin interaction that would enable CLOCK:BMAL1 to regulate the rhythmic transcription of genes located more than 50kb away from its enhancer.Visualization file of ChIP-Seq signal at two CLOCK:BMAL1 enhancers (yellow boxes) targeting non expressed genes (Top: (TIF)Click here for additional data file.S1 TableThis table contains the list of the 3217 CLOCK:BMAL1 peaks that was used in this study, along with their genomic localization (mm10 version), their target gene, and their parsing into specific transcriptional output categories.(TXT)Click here for additional data file.S2 TableOutcome of the motif analysis performed by the HOMER software at CLOCK:BMAL1 DNA binding sites parsed based on their transcriptional output.(XLSX)Click here for additional data file.S3 TableThis table contains the ChIP-Seq signal for several TFs at the 1,274 CLOCK:BMAL1 peaks that were assigned to a CLOCK:BMAL1 transcriptional output category used in this study.(XLSX)Click here for additional data file.S4 TableThe genomic coordinates of these control genes correspond to -10kb from the TSS to +1kb from the TTS (mm10 version). The table also contains the genomic location of the top 40,000 DNase hypersensitive sites (given size) located within these control genes (-10kb from the TSS to +1kb from the TTS), and that were used in our analysis.(XLSX)Click here for additional data file.