PCNA generally loads onto the genome before Pol δ. Once assembled, the holoenzyme has a relatively short lifetime on the genome, implying multiple Pol δ binding events may be needed to synthesize an Okazaki fragment. During disassembly, Pol δ dissociation generally precedes PCNA unloading. We also find that Pol δ p125, the catalytic subunit of the holoenzyme, is maintained at a constant cellular level, indicating an active mechanism for control of Pol δ levels in vivo. Collectively, our studies reveal that Pol δ holoenzyme assembly and disassembly follow a predominant pathway in vivo; however, alternate pathways are observed.Human DNA polymerase delta (Pol δ) forms a holoenzyme complex with the DNA sliding clamp proliferating cell nuclear antigen (PCNA) to perform its essential roles in genome replication. Here, we utilize live-cell single-molecule tracking to monitor Pol δ holoenzyme interaction with the genome in real time. We find holoenzyme assembly and disassembly  in vivo are highly dynamic and ordered. They find that assembly and disassembly of the Pol δ holoenzyme complex follow a predominant pathway in vivo, with alternate pathways also observed.Drosopoulos et al. report human Pol δ holoenzyme assembly and disassembly on the genome   The eukaryotic genome is replicated primarily by an ensemble of three B-family DNA polymerases, namely, Pol α, Pol δ, and Pol ε . Pol α, in vitro  . PCNA te complex .in vitro  allow for direct observation of individual protein molecules in vivo in real time in individual cells  was generated where the 19.5-kDa SNAP protein tag was fused to the N terminus of the catalytic p125 subunit of human Pol δ . Similareal time .SNAP-Pol δ and Halo-PCNA proteins were co-expressed under the control of doxycycline-inducible promoters from constructs stably integrated into LOX cells, a human melanoma cell line . Initialin vivo, we performed live-cell two-color SMT. LOX cells co-expressing tagged and fluorescently labeled Pol δ and PCNA were imaged using HILO  illumination  fluIn vitro biochemical studies have shown that PCNA interaction with PIP-box-containing proteins could be disrupted by T2 amino alcohol (T2AA), a non-peptide small-molecule competitive inhibitor  then binds to the loaded PCNA ring to form the holoenzyme complex. To establish if this is indeed how the holoenzyme assembles aneously , top. Ananeously . The majaneously , bottom.aneously . After daneously . We founin vivo.The interaction of PCNA with Pol δ greatly stimulates processive DNA synthesis by the polymerase by enhancing stable binding of the enzyme to DNA. However, it is unknown whether polymerase activity affects the stability of the bound PCNA-Pol δ holoenzyme complex. To examine the effect of polymerase activity on binding dynamics, we generated a catalytically inactive SNAP-Pol δ mutant (SNAP-Pol δ Dead), where the DNA synthesis and 3′–5′ exonuclease activities were inactivated . This muDual-color SMT of LOX cells co-expressing SNAP-Pol δ Dead and Halo-PCNA  and S4 r1, represented tracks that had a relatively “short” residence time, typically 2 s or less. The T1 population comprises most of the tracks, 84%–96% of the total depending on the tagged protein  for both SNAP-Pol δ and Halo-PCNA when Halo-PCNA was co-expressed with Pol δ Dead versus Pol δ WT. PCNA residence time of the stable population increased from 20 s to 43.9 s  to 16% (Pol δ Dead)   and S3. Lagging strand copying is a primary function of Pol δ. Because it occurs in a discontinuous manner involving cycles of Pol δ binding synthesis dissociation , Pol δ iin vivo investigations reveal key aspects of Pol δ chromatin binding behavior, Pol δ-PCNA holoenzyme assembly/disassembly pathways, and Pol δ p125 catalytic subunit protein regulation.Pol δ performs essential roles in genome integrity maintenance, including serving as the main polymerase tasked with lagging strand DNA synthesis during genomic replication. Using stably expressed fluorescently tagged Pol δ and PCNA, we used SMT to study the dynamics of Pol δ interaction with chromatin and PCNA in real time in living human cells. Our Pol δ was tracked in our experiments by a SNAP-tagged p125 catalytic subunit. Uncomplexed, free p125 is essentially unable to stably bind primed DNA templates, even in the presence of PCNA , and PolEscherichia coli replisome by Pol III (Bacillus subtilis replisome by Pol C (In vitro data suggest fast equilibrium kinetics between the formation and disassembly of the human Pol δ replicative complex on DNA templates (in vitro estimates indicate that complete Okazaki fragments (100–250 nt) could be synthesized by human Pol δ4 in 1–2.5 s, based on a kpol (polymerization rate constant) of 87–108 nt sec−1 (pol = ~20 nt sec−1) (in vivo average chromatin residence times we observe for the short (T1) and long binding (T2) populations of Pol δ , suggesting that the polymerase is constantly scanning the genome for target replication sites. These interactions may be indicative of the polymerase searching for a primer-template-bound PCNA ring. Alternatively, these short-lived binding events may represent fast polymerase turnover similar to the rapid concentration-dependent exchange seen within the  Pol III  and in tby Pol C . In vitremplates . Howevernt sec−1  or by Pot sec−1)  in 5–12 of Pol δ . Alternaof Pol δ . In addiof Pol δ . Accordiof Pol δ .in vitro examination of the individual steps of Pol δ loading and PCNA loading/unloading in isolation. This has led to models where the holoenzyme is constructed on a primed DNA template by the stepwise, ordered addition of PCNA (by the RFC clamp loader) followed by Pol δ (Current understanding of human Pol δ holoenzyme assembly and disassembly dynamics has been largely based on by Pol δ . By infeIn vivo PCNA binding dynamics have been examined by fluorescence recovery after photobleaching (FRAP)  , althougunloaded .in vitro , are 350 and 106 nt, respectively . Transfer of materials may require a material transfer agreement (MTA) to be signed.Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Carl Schildkraut , 20mM HEPES, 100 I.U./mL Penicillin, and 100 μg/mL Streptomycin (Corning)). The line was authenticated by short tandem repeat (STR) profiling.LOX human  melanoma cells  were groDoxycycline-inducible lentiviral plasmids used to express N-terminally Halo tagged PCNA, N-terminally SNAP tagged Pol δ (WT), and N-terminally SNAP tagged Pol δ Dead proteins were generated as follows. The inducible expression lentiviral vector pInducer10 , a gift Stable LOX cell lines inducibly expressing Halo-PCNA and SNAP-Pol δ proteins were generated by lentiviral transduction. Cells were first infected with lentiviral particles containing pIND-Halo-PCNA and single cell clonal colonies were selected in 400μg/mL Geneticin (G418). To generate dual expression cell lines co-expressing Halo-PCNA and SNAP-Pol δ WT or SNAP-Pol δ Dead, we infected an individual clone of Halo-PCNA expressing LOX cells with lentiviral particles containing pIND-SNAP-Pol δ WT or pIND-SNAP-Pol δ Dead. Single cell clonal colonies of Halo-PCNA-expressing cells stably transduced with SNAP-Pol δ particles were then selected with 400μg/mL Geneticin and 4μg/mL blasticidin. Halo-PCNA and SNAP-Pol δ proteins were expressed in stable lines by induction with 1μg/ml Doxycycline.2 and stored at −80°C. For SDS-PAGE, pellets were thawed on ice and lysed by resuspending in Laemmli Buffer  to a final concentration of 106 cells ml−1. Lysates were denatured (5min/100°C) and passed through a 25-gauge needle (5x) then spun for 2 min at full speed in a microfuge. Aliquots of lysate corresponding to 105 cells were resolved on 4%–15% gradient SDS-PAGE gels (BioRad), proteins transferred to nitrocellulose membrane and blocked in PBS with 5% Blotting-grade Blocker (BioRad) and 0.1%Tween-20. Membranes were then incubated with primary antibodies diluted in PBS with 5% Blotting-grade Blocker. Primary antibodies used were: anti-human DNA Pol δ p125 , anti-human PCNA , anti-SNAP tag , anti-Halo tag , anti-α-Tubulin , and anti-actin . Following incubation with primary antibodies membranes were washed with PBS + 0.1% Tween 20. Membranes were then incubated with fluorescently labeled Goat Anti-Mouse IRDye 680LT (Li-Cor) and Goat Anti-Rabbit IRDye 800CW (Li-Cor) secondary antibodies then washed in PBS + 0.1% Tween 20. Immunoblots were then imaged on an Odyssey Lc Infrared scanner (Li-Cor). Band intensities were quantified using ImageStudio software (Li-Cor).Cells were harvested by trypsinization, suspended in complete RPMI, washed with PBS, then pelleted and flash frozen in liquid N5 cells) stably expressing Halo-PCNA and SNAP-Pol δ, or SNAP-Pol δ Dead were plated in selective media on 35 mm MatTek imaging dishes. 24 hours prior to imaging 1 μg/ml Doxycycline was added to the cells and incubated at 37°C. Immediately prior to imaging, cells were incubated at 37°C with 0.4nM JF549-HTL (Janelia Labs) and 10nm SNAP-Cell 647-SiR (New England Biolabs) for a total of 15 and 60 minutes, respectively. Cells were then washed 3 times with 1x PBS, replaced with complete RPMI and further incubated for 30 minutes at 37°C to remove unincorporated dye. Cells were then washed 2 times with 1x PBS and placed in L-15 imaging media (Life technologies) + 10% FBS for imaging. For T2AA treatment, LOX cells co-expressing Halo-PCNA and SNAP-Pol δ were treated for 4 hours immediately prior to labeling with 20μM T2AA, labeled as above in the presence of 20mM T2AA, then two-color imaged in the presence of 20μM T2AA.Two days prior to imaging, cells  and 640nm  lasers for JF549-HTL and SNAP-Cell 647-SiR imaging respectively. Time-lapse two dimensional images of single molecules were acquired with a customized inverted Nikon Eclipse Ti microscope with a 150x oil-immersion objective lens . Sequential dual color images of live cell nuclei were acquired for ~22 minutes using 500ms exposures on an EMCCD camera  with a 512 × 512 pixel field of view  and a high speed filter wheel (~169ms dead time) that continuously alternated between the SNAP-Cell 647-SiR (labeled SNAP-Pol δ and SNAP-Pol δ Dead) and JF549-HTL  channels. The effective time resolution for each channel using such a system was 0.75Hz.All imaging sessions were carried out with asynchronous cultures at room temperature. Only cells displaying a punctate nuclear distribution pattern of PCNA, identifying them as S phase cells , were im2/sec and allowing for 5 s gaps in trajectories due to blinking or missed localizations. A 2D projection map displaying the x,y positions of binding events for PCNA and Pol δ was generated using the average localizations of PSFs from individual binding trajectories of Halo-PCNA, SNAP-Pol δ, and SNAP-Pol δ Dead binding events over 22 minutes of imaging. Nuclear Halo-PCNA, SNAP-Pol δ, and SNAP-Pol δ Dead tracks were identified based on the boundaries from 2D projection maps of binding events. Nuclear boundaries were confirmed via 2D projections of the summed nuclear Halo-PCNA fluorescent signal after 22 minutes of imaging and confirmed using bright field imaging. Tracks that fell outside of the nucleus were excluded. Photobleach rates for single fluorescent dyes were then determined for each background-subtracted movie based upon the exponential decay of the global fluorescence signal of genomic bound Halo-PCNA, SNAP-Pol δ, and SNAP-Pol δ Dead. The average photobleach rates for JF549-HTL dye and the SNAP-Cell 647-SiR dye were 166.8 s and 99.3 s, respectively.Time-lapse movies of acquired images were de-interlaced to separate the two imaging channels and processed to subtract background in ImageJ using a rolling ball radius of 50 pixels. Background subtracted movies of separate imaging channels were subjected to Multi-Target Tracking (MTT) to resolve the trajectories of individual molecules  using a Custom MATLAB scripts were used to identify SNAP-Pol δ WT/Dead genomic binding events lasting at > 1.34 s that temporally colocalized within 47nm of a Halo-PCNA molecule. The binding order was defined from co-localized Halo-PCNA and SNAP-Pol δ WT/ Dead tracks as follows. The “arrival” point was determined by the frame at which either SNAP-Pol δ WT/Dead or Halo-PCNA first appeared in a colocalized track. The “departure” point was the frame where signals disappeared. SNAP-Pol δ WT/Dead arrival and departure times , and S1 Genomic binding residence time was determined by plotting a survival curve  of the track-lengths of nuclear bound Halo-PCNA, SNAP-Pol δ, and SNAP-Pol δ Dead in each cell. Single and double-exponential models were then fitted to these 1-CDF plots to determine the residence times. In general, fitting of the 1-CDF curves predominantly showed two populations of residences times consisting of both long-lived stable (> 1.7 s) and short-lived unstable (< 1.7 s) genomic binding events. A previous study examining chromatin binding of Sox2 found that unstable (residence time < 1 s) and stable (residence time > 1 s) binding arose from non-specific and specific interactions with the genome, respectively .1 population) and stable (T2 population) residence times, and proportions of molecules participating in unstable and stable residence events were conducted by taking the global residence time and the proportion of molecules participating in these residence events for each cell. A two-sample Kruskal-Wallis test was used to determine pairwise significance.Global comparisons of both unstable  as it was raster scanned across the expanded 2D projection map of the nucleus. Contiguous octagon windows centered on an individual pixel containing at least 3 SNAP-Pol δ WT/Dead binding events were defined and labeled as hubs. A two-sample Kruskal-Wallis test was used to determine pairwise significance.The total number of hubs per cell were then normalized to the total number of SNAP-Pol δ WT/Dead binding events per cell. This normalized amount of hubs were then multiplied to produce the number of SNAP-Pol δ hubs formed per 1,000 binding events  for each cell. Overall significance was determined with a two-sample Kruskal-Wallis test to determine pairwise significance.To quantify binding latency times in hubs, tracks of binding events in individual hubs were further analyzed to determine the time periods between single SNAP-Pol δ binding events. 1-CDF survival plots of all SNAP-Pol δ latency times in hubs accumulated from 59 cells (Pol δ WT) and 13 cells (Pol δ Dead) were fit with a single, double, and triple exponential decay model. In general, fitting of the 1-CDF curves predominantly showed three populations of latency times consisting of short (~6–10 s), intermediate (~23–27 s) and long (~160–230 s) time periods. Overall significance was determined using a two-sided Student’s t test.Statistical details of experiments can be found in the figure legends. Statistical tests were performed using built-in scripts in MATLAB v 2014b . Two-sample Kruskal-Wallis test and two-sided Student’s t test were used to determine pairwise comparisons.https://doi.org/10.17632/c62m7cm88v.1. The custom MATLAB-based SMT Analysis code generated during this study is available at https://github.com/Coleman-Laboratory/SMT-Data-and-code.Annotated Halo-PCNA and SNAP-PolD (WT/Dead) molecular localization, binding trajectory, residence time, and binding hub datasets generated during this study are available at MendeleyData. Video S1Video S2Video S3Video S4Supplemental figures


S. cerevisiae, the levels of transcription through a noncoding region, IRT2, located upstream in the promoter of the inducer of meiosis, IME1, regulate opposing chromatin and transcription states. At low levels, the act of IRT2 transcription promotes histone exchange, delivering acetylated histone H3 lysine 56 to chromatin locally. The subsequent open chromatin state directs transcription factor recruitment and induces downstream transcription to repress the IME1 promoter and meiotic entry. Conversely, increasing transcription turns IRT2 into a repressor by promoting transcription-coupled chromatin assembly. The two opposing functions of IRT2 transcription shape a regulatory circuit, which ensures a robust cell-type-specific control of IME1 expression and yeast meiosis. Our data illustrate how intergenic transcription levels are key to controlling local chromatin state, gene expression, and cell fate outcomes.Transcription through noncoding regions of the genome is pervasive. How these transcription events regulate gene expression remains poorly understood. Here, we report that, in   •IRT2 regulate opposing local transcription statesTranscription levels of the lncRNA •IRT2 promote H3K56ac, chromatin disassembly, and TF recruitmentLow levels of •IRT2 levels promote chromatin assembly and transcriptional repressionIncreasing •IRT2 transcription shapes the regulatory circuit for cell-type-specific control of yeast meiosis IRT2 can have opposing effects on local gene transcription, thereby controlling entry into yeast meiosis. Low levels of IRT2 promote H3K56ac, chromatin disassembly, transcription factor recruitment, and, thus, transcriptional activation. Increasing levels promote chromatin assembly and, consequently, transcriptional repression.Moretto et al. demonstrate that transcription levels of a lncRNA named  Transcription in intergenic regions of the genome is widespread. The noncoding RNAs emanating from these transcription events embody a large fraction of the transcriptome . ParticuNoncoding transcription occurs near protein coding genes in promoter regions or at the 3′ ends of genes where they produce sense or antisense lncRNA transcripts . NoncodiNoncoding transcription events can repress and activate gene transcription. Examples from yeasts have demonstrated that transcription through promoters of protein coding genes exerts gene repression . At thesIME1 , at which nutrient and mating-type signals integrate (IME1 transcription is only induced in cells expressing both mating-type loci (MATa and MATα) under starvation conditions.Two lncRNAs are transcribed in the promoter of the Inducer of Meiosis 1 gene, IME1 . This maIME1 . In diplIME1 . The IMEntegrate . These sIME1 expression is mediated by the transcription of two lncRNAs in the IME1 promoter (MATa or MATα), typically haploid cells, transcription of a lncRNA named IME1 regulating transcript 1 (IRT1) represses the IME1 promoter to prevent meiotic entry  represses the transcriptional activator of IRT1, RME1, enabling IME1 induction and, thus, meiotic entry  is expressed to moderate levels in various genetic backgrounds  enter meiosis in yeast. Our data illustrate how noncoding transcription levels are key to controlling local chromatin state, gene expression, and cell fate outcomes.Here, we report the surprising finding of a dual function for transcription of the more upstream lncRNA in the IME1 promoter. To examine this, we determined IRT1 and IRT2 expression levels and mapped the transcription start sites (TSSs) and polyadenylation sites  of both transcripts in cells harboring a single mating type (MATa) and both mating types (MATa/α) in the sporulation-proficient SK1 strain background. As expected, MATa/α diploid cells entering meiosis synchronously induced IME1 expression rapidly and displayed strong induction of IRT2, whereas IRT1 levels remained relatively low (IRT2 TES while multiple TSSs spread over ∼215 base pairs (bp) were detected, matching the slight smear observed on the northern blot for the IRT2 transcript (MATa) cells, IRT1 expression was higher than in MATa/α cells, and IME1 expression was repressed  , demonstrating that IRT2 is also expressed in this cell type  C. SurpriTa cells B, lane 6ell type D. To cappression A. Strikinduction D. Since lability .IRT2 is required for IRT1 induction, we created deletions in the IRT2 TSS cluster, Δirt2(−188) and Δirt2(−246), while keeping the Rme1 binding sites intact (irt2(−188) and Δirt2(−246) cells, IRT1 expression decreased; IME1 levels increased; and, as expected, IRT2 expression was not detectable. Both IRT2 mutants also displayed reduced association of Rme1 to the IRT1 promoter  did not alter IRT1 and IME1 expression (IRT1 (irt1-T) showed wild-type (WT)-like Rme1 recruitment and displayed no additional reduction in Rme1 binding when combined with Δirt2(−246), indicating that transcription through IRT1 is not required for inducing IRT1 expression , which impairs Ime1 function (IRT1 expression was detected in the absence of IRT2 transcription (IRT2 by deleting the Ume6 repressor binding site (u6bsΔ) in the IRT2 promoter, which decouples IRT2 expression from IME1 activation  led to earlier IRT1 transcription and earlier Rme1 recruitment (u6bsΔ rescued the IRT1 expression defect observed when Ime1 function was impaired (ime1-T), but not when IRT2 transcription was terminated earlier (irt2-T)  activator and β-estradiol inducer  site without the need to activate LexA-ER with β-estradiol  in cells harboring Gal4-ER (no β-estradiol)  J. In thely, IRT1 J. Taken IRT1, undergo a lethal type of meiosis (IRT2-mediated activation of IRT1 in preventing haploid cells from entering meiosis. We found that in irt2 mutants Δirt2(−246) and irt2-T, a large fraction of cells displayed high levels of IME1 expression (more than 30 mRNA copies per cell) (irt2 mutants Δirt2(−188), Δirt2(−246), and irt2-T also displayed reduced viability, possibly due to entering meiosis (MATa/a), mimicking mating-type repression of IME1 expression. Approximately 30% to 40% of MATa/a diploid cells for each irt2 mutant underwent at least one meiotic division , histone acetylation (GCN5 and RTT109), and histone chaperone function (ASF1) were identified (RTT109 and ASF1. Rtt109 is the sole histone acetyltransferase that acetylates histone H3 lysine 56 (H3K56ac) in yeast, whereas Asf1 is involved directly in chromatin assembly and acts as a chaperone for Rtt109-directed H3K56ac  were affected in rtt109Δ cells during starvation  site. Whereas IRT2 was clearly expressed in lexO(−10) rtt109Δ cells, IRT1 expression was still compromised, suggesting that Rtt109 acts in concert with IRT2 transcription in inducing IRT1  rtt109Δ cells, suggesting that the IRT2 RNA by itself has little function in IRT2-mediated activation of IRT1  allele and measured the effect on IRT1 activation. IRT1 expression in the irt2-T rtt109Δ double mutant was affected to a degree comparable to that of the single mutants , but not when IRT2 was repressed during exponential growth (YPD) or when RTT109 was deleted . Galactose induction had no effect on IME1 expression under these conditions, which excludes the possibility that the effects were due to changes in IME1 promoter activity  sequence repeats near the IRT2 TSS (lexOn(+96), +96 bp from the Ume6 binding site) and measured IRT2 and IRT1 levels together with nucleosome positioning (IRT2 levels as well as Pol II binding increased with the number of integrated lexOn(+96) repeats  compared to when the locus was repressed (YPD)  F and S6Fmitantly F and S6FIRT2 transcription direct H3K56ac to chromatin, which, in turn, promotes the recruitment of Rme1 and activation of IRT1 transcription. Conversely, increasing levels of IRT2 transcription set in place a well-positioned nucleosome that likely interferes with Rme1 recruitment and, consequently, represses IRT1 transcription  by replacing the endogenous promoter with the CUP1 promoter (pCUP-IRT2) . These data show that increasing IRT2 transcription levels suppresses IRT1-mediated repression of the IME1 promoter, allowing these cells to enter meiosis. Conversely, low levels of IRT2 are required for activating IRT1 transcription and preventing meiotic entry (Our observation that UP-IRT2) G. Under ivisions . Approxiic entry G.IRT2 transcription activates IRT1 expression, whereas higher levels of IRT2 transcription repress IRT1 expression in a dose-dependent manner. IRT1 transcription levels are also linked to the levels of Rme1, which vary greatly between cells expressing a single mating type (MATa or MATα) and cells expressing opposite mating types (MATa/α), and between MATa/α cells of different genetic backgrounds  and diploid (MATa/α) cell type, respectively, which resulted in the repression or activation of Ime1 expression  and the inability for haploid (MATa or MATα) cells to enter meiosis. Importantly, the absence of IRT2 transcription or the presence of only activating low levels of IRT2 abrogated the bimodal relationship between Rme1 and Ime1 expression levels .Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Folkert van Werven  yeast extract, 2.0% (w/v) bacto tryptone, 1.0% (w/v) potassium acetate, 50 mM potassium phthalate) grown for about 16 h, subsequently centrifuged, washed with sterile miliQ water, centrifuged again, re-suspended at OD600 = 1.8 in sporulation medium (SPO) (0.3% (w/v) potassium acetate and 0.02% (w/v) raffinose)) and incubated at 30°C. For IRT1 or IME1 expression with slow kinetics. In short, cells were grown till saturation for 24h in YPD then diluted in YPD aiming to reach OD600 = 6 after 16h, several samples were taken from that point till 24h, subsequently cells were washed, and transferred to SPO.All experiments were performed at 30°C in a shaker incubator at 300rpm. A protocol for rapid induction of eviously . In shor600 = 0.4) in pre-sporulation medium and grown for another 16h. Cultures were then split and treated with β-estradiol (25nM) or ethanol (mock) for 1h, transferred to SPO (OD600 = 1.8), and incubated up till 3h in the presence of β-estradiol (15 nM) or ethanol.For the lexO/LexA-ER experiments described in pGAL-IRT2/GAL4-ER experiment described in 600 = 0.4) in pre-sporulation medium and grown for another 16h. Subsequently samples were taken for the indicated time points.For the and 600 = 0.9. Cells were then arrested in G1 with α factor (5 μg/ml) for 2h, subsequently split to YP plus 2% galactose and YPR both containing α factor (5 μg/ml).For measuring histone exchange rates described in RPB3-FLAG allele was generated through a one-step C-terminal tagging procedure of RPB3 with a FLAG tag cassette which contains three copies of the FLAG epitope (gift Jesper Svejstrup). MATa/a diploid strains were generated by replacing the MATα locus in MATa/α diploids with a plasmid linearized by EcoRI digestion harboring the MATa fragment with URA3 or TRP1 selectable markers  , gift from Valerie Borde). Genetic crosses were used to generate the histone H3K56A and H3K56R mutants in the absence of the wild-type histone H3 covering plasmid. The plasmids for generating strains with LexA operator (lexO) sequences and LexA fused to the estrogen receptor domain and activation domain (LexA-ER-HA-B112) were described previously  (IRT2 locus position +96 or −10 bp from the Ume6 binding site. A plasmid expressing LexA-ER-HA-B112 from the GPD1 promoter was linearized with SfiI restriction enzyme and integrated at the TRP1 locus. The strains used for the histone H3 exchange assay described in HHT2-Myc (histone Myc-H3) and untagged HHF2 (histone H4) under control of their endogenous promoters. In addition this stain also harbored a plasmid (YIplac211 pGAL1-10 HHF1 FLAG-HHT1) integrated at the URA3 locus with HHT1 FLAG tagged (histone FLAG-H3) and untagged HHF1 (histone H4) under control of the GAL1-10 promoter . The irtstrategy . In shorc-Avitag . To exciouchoux) . After eHF1,pDM9 , gift frin Ünal)   . A diffepromoter . To geneeviously . PlasmidA table of oligonucleotides used in this study is available in DAPI staining was used to monitor meiotic divisions throughout time courses. Cells were fixed in 80% (v/v) ethanol, pelleted by centrifugation and re-suspended in 100 mM phosphate buffer (pH 7) with 1 μg/ml 4′,6-diamidino-2-phenylindole (DAPI). Cells were then sonicated for a few seconds and left in the dark at room temperature for at least 5 min. The proportion of cells containing one, two, three or four (meiosis I + II) DAPI masses were counted using a fluorescence microscope.HMR locus, which showed no binding for Rme1. For HMR locus, which showed no binding for Rpb3.Chromatin immunoprecipitation (ChIP) experiments were performed as described previously . Cells wIRT2 locus was determined by quantifying the abundance of mononucleosomal DNA using a MNase digestion protocol that was described previously (600 units of cells were crosslinked for 25 min at 30°C with 1% (v/v) formaldehyde. Reaction was quenched with the addition of glycine to 125 mM. Subsequently, cells were re-suspended in 20 mL of buffer Z  plus β-mercaptoethanol (10mM) and treated with 250 μg of T100 Zymolyase for 60 min. Next, cells were re-suspended in 1 mL NP buffer , 0.075% (w/v) Tergitol solution-type NP-40 detergent (NP-40), 50 mM NaCl, 10 mM Tris-HCl pH 7.4, 5 mM MgCl2, 1 mM CaCl2), vortexed for 10 s, and 100 μL of extract was treated with 0.2 μL of MNase  for 30 min at 37°C, the reaction was quenched with 10 mM EDTA, and reverse crosslinked overnight in 1% SDS-TE and 4 units per ml of proteinase K (NEB). Samples were treated with RNase A and purified DNA fragments were separated by gel electrophoresis before gel purification of the mono-nucleosome bands. MNase treated and input samples were quantified by qPCR on a 7500 FAST Real-Time PCR machine (Life Technologies) using Platinum SYBR mix (Thermofisher). The signals were normalized using primers directed against a telomere locus. The scanning primer pairs covering the IRT2 locus and downstream region used for the analysis are available in Nucleosome positioning at the eviously . In shorNorthern blots were performed as described previously . In shorAt least 5 μg of total RNA was treated with DNase and purified on column (Macherey-Nagel). At least 500 ng of purified total RNA was used as input for the KAPA mRNA Hyper Prep kit . Libraries were prepared according to manufacturer’s instructions. After bead based clean up, libraries were sequenced on an Illumina HiSeq 2500 to an equivalent of 75 bases single-end reads, at a depth of approximately 20 million reads per library.+ RNA/mRNAs, together with in vitro spike-ins, were fragmented for 3 min at 70°C using a Zinc-based alkaline fragmentation reagent . RNAs were cleaned up using RNeasy MinElute Cleanup Kits  to enrich for 200-300 nt fragments. These fragments were dephosphorylated with 30 units of recombinant shrimp alkaline phosphatase  for 1 h at 37°C with RNasin Plus, the phosphatase was heat inactivated and the RNA was extracted with Acid Phenol:chloroform: Isoamyl alcohol (125:24:1) and precipitated at −20°C overnight in ethanol with 0.3M sodium acetate and 1 μL linear acrylamide . RNA was then subjected to a decapping reaction with 2 units of Cap-Clip acid pyrophosphatase  and with RNasin Plus. RNAs were then extracted using acid Phenol:chloroform:isoamyl alcohol (125:24:1) and precipitated in ethanol. Some RNA from a SPO (starvation) 0 h time point was set apart without the decapping reaction as a non-decapping control. Subsequently, the RNA was mixed with 10 μM of custom 5′ adaptor (CACTCTrGrArGrCrArArUrArCrC) and the ligation reaction was done using T4 RNA ligase 1  and with RNasin Plus. The ligation reaction was cleaned up with the RNeasy MinElute Cleanup Kit and RNAs were mixed with 2.5 μM random hexamers  and RNasin Plus, denatured at 65°C for 5 min and cooled on ice. Reverse transcription reactions were carried out using SuperScript IV reverse transcriptase  at 23°C for 10 min, 50°C for 10 min, 80°C for 10 min and held at 4°C. The RNA templates were degraded by incubating reactions with 5 units of RNase H  and 1.0 μL of RNase cocktail enzyme mix . DNA products were purified using 1.8x volume of HighPrep PCR beads . Purified products were subjected to second strand synthesis using 0.3 μM of second strand biotinylated primer (GCAC/iBiodT/GCACTCTGAGCAATACC) and the KAPA Hi-Fi hot start ready mix . The second strand reaction was carried out at 95°C for 3 min, 98°C for 15 s, 50°C for 2 min, 65°C for 15 min and held at 4°C. Double stranded product (dsDNA) was purified with 1.8x volume HighPrep PCR beads and concentration was quantified using the Qubit dsDNA HS assay kit . At least 1 ng of dsDNA was then used as input for the KAPA Hyper Prep Kit  and ligated to KAPA single indexed adapters Set A  or Set B . Samples were processed according to manufacturer’s instructions with one exception: just prior to the library amplification step, samples were bound to MyOne Streptavidin C1 Dynabeads  to capture biotinylated dsDNA. Library amplification was done on the biotinylated dsDNA fraction bound to the beads. Depending on the input amounts, 15 PCR cycles were used to generate libraries. Amplified libraries were quantified by Qubit, and adaptor-dimers were removed by electrophoresing libraries on Novex 6% TBE gels  at 120 V for 1 h, and excising the smear above ∼150 bp. Gel slices containing libraries were shredded by centrifugation at 13000 g for 3 min. Gel shreds were re-suspended in 500 μL crush and soak buffer  and incubated at 65°C for 2 h on a thermomixer . Subsequently, the buffer was transferred into a Costar SpinX column  with two 1 cm glass pre-filters . Columns were centrifuged at 13000 g for 1 min. DNA libraries in the flowthrough were precipitated at −20°C overnight in ethanol with 0.3 M sodium acetate and 1 μL linear acrylamide . Purified libraries were further quantified and inspected on a Tapestation (Agilent Technologies) and sequenced on an Illumina HiSeq 2500 to an equivalent of 75 bases single-end reads, at a depth of approximately 20 million reads per library.The TSS sequencing approach was adapted and modified from previously published protocols  Arriber Malabat. At leasThe TES sequencing approach was adapted and modified from previously published protocols  Ng et a. From thThe nascent RNA sequencing procedure was adapted as described in . Briefly, about one liter of yeast culture was spin down at the harvest time point and pellet snap frozen in liquid nitrogen. Cell pellets were then grinded in fine powder using a cryo-mill instrument with the instrument maintained cooled with liquid nitrogen. All the powder was re-suspended in about 12 to 15 mL of lysis buffer  and lysate subjected to DNase I treatment (1200 U per sample) for 20 min. Lysate was then clarified through two rounds of centrifugation at about 20 000 g for 10 min at 4C. Anti-FLAG immunoprecipitation was performed using 750 μL of anti-FLAG M2 agarose beads per sample and for 2.5 h at 4C on a rotating wheel. Beads were then washed 5 times using 10 mL of cold wash buffer  for 5 min at 4C. Beads were then cleaned using a Pierce column and two rounds of elution were performed using FLAG peptide (450 μL 10 mg/ml Sigma FLAG peptide) for 30 min at 4C. Elution was then subjected to a phenol:Chloroform extraction and RNA precipitated overnight in ethanol containing 0.3 M Na acetate. RNAs were then resuspended in Nuclease free water, quantified by Qbit RNA high sensitivity assay kit  and analyzed by Bioanalyser (Agilent technologies).At least 500 ng of purified RNA was treated with DNase and purified on column (Macherey-Nagel). Then, about 100 ng of purified total RNA was used as the inputs for the KAPA RNA hyperPrep kit . Libraries were prepared according to manufacturer’s instructions. After bead based clean up, libraries were sequenced on an Illumina HiSeq 4000 to an equivalent of 75 bases single-end reads, at a depth of approximately 50 million reads per library.S. cerevisiae SK1 genome assembly from Keeney lab (http://cbio.mskcc.org/public/SK1_MvO/) (For RNA-seq data (including nascent RNA-seq), adaptor trimming was performed with cutadapt (version 1.9.1) with parameters “-a AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC–minimum-length=20.” STAR (version 2.5.2) with parameters “–alignIntronMin 3–alignIntronMax 5000” was used to perform the read mapping to the K1_MvO/) . AlignmeK1_MvO/)   . AlignmeK1_MvO/) .For the TSS transcript sequencing data, the custom 5′ adaptor sequence specific to the protocol was removed by re-running cutadapt with the parameters “-g CACTCTGAGCAATACC -O 16–minimum-length=20,” and only the reads containing the adaptor sequence were used for further analysis. STAR (version 2.5.2) with parameters “–alignIntronMin 2–alignIntronMax 1”  was used to align TSS-seq reads to the SK1 genome assembly (plus three spike-in sequences) . The alignments with mapping quality of > = 10 were kept for further analysis. Alignments from forward strand and reverse strand were separated by using “samtools view -b -f 0x10” and “samtools view -b -F 0x10.” The 5′-most nucleotide of aligned reads were extracted to generate the genome-wide tracks of TSSs. The BedGraph tracks were normalized by the number of usable reads in each library.For the TES transcript sequencing data, Adaptor trimming was performed with cutadapt (version 1.9.1) with parameters “-a AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC–minimum-length=20.”STAR (version 2.5.2) with parameters “–alignIntronMin 2–alignIntronMax 1” as for the 5′ end sequencing part, and alignments with mapping quality of > = 10 were kept for further analysis. The reads kept were those with soft-clipping at the 3′ end (size of soft-clipping part ≤ 10) and with at least two consecutive non-templated as in the soft-clipping part. Insertions/deletions were also not allowed. Alignments from forward strand and reverse strand were separated by using “samtools view -b -f 0x10” and “samtools view -b -F 0x10.” The 3′-most nucleotide of aligned reads were extracted to generate the genome-wide tracks of TESs. The BedGraph tracks were normalized by the number of usable reads in each library.IME1 (AF594) and ACT1 (Cy5) as an internal control. Cells were imaged using a 100x oil objective, NA 1.4, on a Nikon TI-E imaging system (Nikon). DIC, DAPI, AF594 (IME1), Cy5 (ACT1) images were collected every 0.3 micron (20 stacks) using an ORCA-FLASH 4.0 camera (Hamamatsu) and NIS-element software (Nikon). ImageJ software was used to make maximum intensity Z projections of the images . StarSearch software  was used to quantify transcripts in single cells. Comparable thresholds were used to count RNA foci in single cells. Only cells positive for the internal control ACT1 were used for IME1 analysis. At least a total n = 150 cells were counted for each experiment.The single molecule RNA FISH was performed as described previously . In shorWestern blots were performed as previously described . ProteinIRT1. After 0 or 14 days in SPO cells were diluted to OD600 = 1 in sterile water, and serial dilutions (5-fold) were spotted onto YPD agar plates. Cells were incubated at 30°C for 2 days before imaging.Cells were grown using the protocol for rapid induction of IME1 expression by IRT1 and IRT2, we developed a mathematical model. We incorporated new observations described in this manuscript, into the model described previously , followed by a Fisher LSD test. Fisher’s LSD test confer more power to the test, compared to performing multiple Student’s t tests, in that t tests compute the pooled standard deviations from only the two groups being compared, while the Fisher’s LSD test computes the pooled standard deviations from all the groups while assuming that all population have similar standard deviation.


In addition to the transposition module, Tn3 members often carry additional passenger genes , and three were previously known to carry a toxin-antitoxin (TA) system often associated with plasmid maintenance; however, the role of TA systems within the Tn3 family is unknown. The genetic context of TA systems in Tn3 members suggests that they may play a regulatory role in ensuring stable invasion of these Tns during transposition.Transposable elements (TEs) are important in genetic diversification due to their recombination properties and their ability to promote horizontal gene transfer. Over the last decades, much effort has been made to understand TE transposition mechanisms and their impact on prokaryotic genomes. For example, the Tn 3 family is arguably one of the most widespread transposon families. Members carry a large range of passenger genes incorporated into their structures. Family members undergo replicative transposition using a DDE transposase to generate a cointegrate structure which is then resolved by site-specific recombination between specific DNA sequences (res) on each of the two Tn copies in the cointegrate. These sites also carry promoters controlling expression of the recombinase and transposase. We report here that a number of Tn3 members encode a type II toxin-antitoxin (TA) system, typically composed of a stable toxin and a labile antitoxin that binds the toxin and inhibits its lethal activity. This system serves to improve plasmid maintenance in a bacterial population and, until recently, was believed to be associated with bacterial persistence. At least six different TA gene pairs are associated with various Tn3 members. Our data suggest that several independent acquisition events have occurred. In contrast to most Tn3 family passenger genes, which are generally located away from the transposition module, the TA gene pairs abut the res site upstream of the resolvase genes. Although their role when part of Tn3 family transposons is unclear, this finding suggests a potential role for the embedded TA in stabilizing the associated transposon with the possibility that TA expression is coupled to expression of transposase and resolvase during the transposition process itself.Much of the diversity of prokaryotic genomes is contributed by the tightly controlled recombination activity of transposons (Tns). The Tn However, they are highly diverse in the range of passenger genes that they carry  site lies between tnpS and tnpT. Examples of these architectures are shown in res includes a number of short DNA subsequences which are recognized and bound by the cognate resolvases. These are different for different resolvase systems and called res (for resolution site), IRS , IRS  or irs (ion site ), or rstnpS tnpT )  system belonging to the type II TA class ., 16.XantTA class .3-related transposon, Tn6231, from the non-self-transmissible plasmid pR28  also ca3 family transposons had been noted previously  and made use of an in-house script which searches for tnpA, tnpR, and TA genes located in proximity to each other  to search complete bacterial genomes in the RefSeq database at NCBI. Of 190 Tn3 family transposons for which relatively complete sequence data  were available, 39 carry TA systems  and tnpI (Tn5401 and TnBth4) genes  genes . Illustr3 transposons by comparison of the TA protein sequences with the Pfam database using hmmscan from the HMMER suite  and Tn3000 , while 6 members of 5 different toxin families  were found distributed in the other subgroups . There are 7 different toxin-antitoxin pairs: ParE-ParD (14 instances), ParE-PhD (2 instances), PIN_3-RHH_6 (13 instances), Gp49-HTH_37 (7 instances), PIN-Phd (1 instance), PIN-AbrB (1 instance), and HEPN-MNT (1 instance).We examined the diversity of the TA modules associated with TnER suite . CandidaER suite . In totaER suite . All of ER suite , while PER suite . The maj3 family transposons, five members of the Tn3000 subgroup (tnpR> tnpA> (where the arrowheads point in the direction of transcription)  , 28. A s3 subgroup, Tn5401 and TnBth4, both with the configuration tnpI> tnpA>, carried a different TA system, a ParE toxin (Pfam: PF05016) and a ParD antitoxin, which appears to lack the DNA-binding domain. Among the TA gene pairs found in members of the Tn3000 transposon subgroup, a majority of toxins are of the ParE (Pfam: PF05016) type while the potential antitoxins have no Pfam match. Results from HHpred indicate that these are antitoxins have an RHH fold similar to that of the classical ParD antitoxin (PDB accession no. 4Q2U_C). It should be noted that this subgroup of Tns (Tn5501 and its derivatives) are highly related and differ mainly by the passenger genes they carry. With the exception of Tn5501.12 (discussed below), all Tn5501 derivatives have identical or nearly identical toxin and antitoxin protein sequences. They were all identified from the nonredundant NCBI nucleotide database using Tn5501 as query sequence. Interestingly, a single member of the Tn4651 subgroup, TnTsp1, also encodes a nearly identical ParE -ParD (2 amino acid substitutions) TA pair.Two additional members of the Tn3-associated toxins assigned to the same Pfam group, along with the seed sequences used to build the Pfam hidden Markov model (HMM) (tnpA and/or resolvase genes), it is likely that it was first acquired by a transposon that subsequently diverged. Alternatively, for transposons which are generally not related  but which harbor TA modules that are similar at the DNA level, it is likely that the TA module was acquired by recombination with another transposon. Tn3 toxins sharing their most common ancestor with non-Tn3 toxins are likely to have been acquired independently. The different TA modules identified and the Tn3 family members in which they are found are described below.A relevant question is whether these TA modules  were acqel (HMM) . If toxiparE toxin genes in our collection; 14 are paired with a parD antitoxin gene and two are paired with a phd/yefM antitoxin gene , Tn3 (two examples), and Tn4651 (one example), suggesting that the parD-parE operon has been acquired three independent times in this collection  TnBth4 and Tn5401; and (3) TnSpu1 and TnAbapMCR4.3. Notice that TnTspu1 is a recombinant since the DNA sequence similarity is limited to the TA module. (B) Transposons encoding the PIN_3 toxin. The dot plot suggests that all transposons except TnHdN1.1 share sequence similarity over the TA module, thereby suggesting two independent acquisition events of the PIN_3/RHH module. (C) Transposons encoding the Gp49 toxin. Seven TA modules are composed of a Gp49 toxin and an HTH antitoxin. The dot plot indicates that this TA module has been recruited on 3 occasions: (1) by the Tn3000 subgroup transposons TnDsu1, TnPupPGH1, Tn4662a, Tn4662a.1, and Tn5501.12; (2) by TnPosp1 (Tn4651 subgroup); and (3) by TnSku1 (Tn5393 subgroup). (D) The two transposons encoding the PIN toxin do not share any sequence similarity, suggesting that the TA module was recruited independently on two occasions. Download FIG S1, PDF file, 1.4 MB.Pairwise DNA sequence alignment visualization by dot plot. For all transposons with a toxin classified in the same family, the DNA segments that included the transposase gene (large mauve square), the resolvase gene , and the TA module were compared. For visualization purposes, the size of the TA module was magnified 150-fold. (A) Pairwise comparison of 16 transposons encoding a ParE toxin. The dot plot suggests three independent acquisitions of the TA module, corresponding to (1) TnCopyright © 2020 Lima-Mendez et al.2020Lima-Mendez et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the parE-parD module located in TnTsp1 (Tn4651 subfamily) is identical at the protein level and nearly identical at DNA level (95%) with the 10 parE-parD modules of the set of Tn5501 derivatives  as indicated by the phylogenetic analysis  in the Tn3 subgroup . Interestingly, although TnHdN1.1 does not share significant sequence similarity at the nucleotide level with the Tn3 subgroup Tns featuring the same TA module, at the protein level both toxin and antitoxin from TnHdN1.1 share ∼80% sequence identity with those in the Tn3 subgroup (HdN1.1 acquired the TA module via recombination (The PIN_3 toxin domain is represented 13 times (8 unique sequences) in our collection. This domain is associated with an RH_6 antitoxin. Twelve Tns having this module are in the Tnsubgroup . Phylogebination .Seven TA modules are composed of a Gp49 toxin and an HTH antitoxin. Phylogenetic analyses suggest that this TA module has been recruited on three occasions .3000 subgroup transposons TnDsu1, TnPupPGH1, Tn4662a, Tn4662a.1, and Tn5501.12. Tn5501.12 is the only relative of Tn5501 to have this TA module. Sequence comparisons suggest that Tn5501.12 resulted from exchange of the entire left end of transposon Tn5501 with a transposon very similar to Tn4662a (res site I containing the dinucleotide (in red) at which recombination takes place during the cointegrate resolution step of transposition , whose toxin does not share a recent ancestor with those of the Tn3000 group or with the TnPosp1 toxin  carries a Phd/YefM antitoxin and TnPsy42 has an AbrB/MazE antitoxin.There are two transposons in the set with a PIN toxin, which appear phylogenetically distant , suggestSod9 (Tn21 subgroup), located in the Shewanella oneidensis MR-1 megaplasmid, includes an HEPN (higher eukaryotes and prokaryote nucleotide-binding)-type toxin and an MNT  antitoxin as identified by their similarity to another toxin and antitoxin pair (HHpred hit PDB identifier 5YEP) encoded in the chromosome of the same strain , although single examples are observed in the Tn4651 (TnPosp1_p), Tn21 (TnSod9), and Tn163 (Tn5393.1) subgroups.Additional indications of independent TA acquisitions are evidenced by Tnres site. They are positioned very close to the res sites .In most cases, the TA gene pairs are embedded within the transposition module comprising transposase and resolvase genes and the es sites . This isnsposons . Indeed,3-associated TA gene pairs are located directly upstream of the resolvase genes (tnpR or tnpI) (HdN1.1 (tnpS and transposase genes (Sku1 (not shown), the TA genes are located downstream of and transcribed toward tnpR, and in the third, a partial transposon copy, TnAmu2_p (not shown), there is a short open reading frame (ORF) of unknown function between the divergently transcribed antitoxin and tnpR genes.In the majority of cases –37, the –or tnpI) . There a  are shown in green, transposition genes are in purple, and toxin-antitoxin genes are in orange. The toxin-antitoxin pair and resolvase types are indicated at the right of each transposon together with the Tn3 subgroup to which they belong. Download FIG S2, PDF file, 0.03 MB.Different types of transposase, resolvase, and TA gene arrangements. This figure illustrates the different types of gene arrangements in members of the TnCopyright © 2020 Lima-Mendez et al.2020Lima-Mendez et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 3, which has been examined in detail, transposase and resolvase gene expression is controlled by promoters found within the res site located between the two divergent genes , and RSAT tools  . This analysis resulted in identification of 27 potential res sites .10.1128/mBio.00452-20.4TABLE S2res sites of TA-carrying transposons. Column 1, TA-carrying transposon names and accession numbers; column 2, Tn3 subgroup; columns 3, 5, and 7, nucleotide within res at which res sites I, II, and III start ; columns 4, 6, and 8, DNA sequence of res sites I, II, and III; uppercase indicates the motif, and lowercase letters indicate nucleotides that are not part of the motif. Download Table S2, DOCX file, 0.02 MB.Predicted Copyright © 2020 Lima-Mendez et al.2020Lima-Mendez et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the res (irs) site of the tnpI-carrying Tn5401 , we identified and analyzed 190 Tn3 family transposons  innsposons , and TnHxin tree , the mosfor HEPN . At pres3 family transposons, the TA genes are located at an unusual position within the transposon. They are close to the DNA resolution site   , and mors site I , a DNA sientated , the TA on e.g., . A similres site. For TnSku1, the TA genes are located downstream of and expressed toward tnpR, while in the partial copy, TnAmu2_p, there is a short ORF between the divergently transcribed antitoxin and tnpR genes. This does not appear to be related to the 3-component toxin-antitoxin-chaperone (TAC) systems  promoters that must occur during the transposition process  synthesis, transitorily promoting transposition as the transposon invades a new host. Subsequent repression by newly synthesized TnpR would reduce transposition activity, reinstalling homeostasis once the transposon has been established, a process similar to zygotic induction  over and above that provided by the endogenous TA regulation system. If the transposon is on a molecule  that is unable to replicate vegetatively in the new host, expression of the TA module without transposition to a stable replicon would lead to loss of the transposon and consequent cell death, whereas cells in which transposition had occurred would survive and give rise to a new population in which all cells would contain the Tn. This might be seen as a “take me or die” mechanism, a notion which could be explored experimentally.Expression of the TA module from the in silico analyses and need to be addressed experimentally. These include whether the TA genes include their own promoters and whether expression is controlled by TA-associated promoter elements or by the resident promoters embedded in the res sites. Finally, it is an open question whether resolvase binding to res represses TA expression either from proximal TA promoters or from res-embedded promoters.Clearly, there remain a number of important questions about the control of TA gene expression that arise from our 3 transposases and resolvases were retrieved from the ISfinder database . ORF prediction was performed with Prodigal 2.6.1 . TA gene pairs were evaluated in greater detail by comparisons with the Pfam 32.0 database  using hmhttp://tree.bio.ed.ac.uk/software/figtree) and edited with Inkscape 0.92.4 (http://www.inkscape.org).TnpA protein sequences retrieved from our manually curated data set were aligned with MAFFT 7.309 , and theTo reconstruct the phylogeny of the toxins, we built a nonredundant toxin set, by removing duplicated sequences. Following the classification of the toxin sequences by comparison with the Pfam database, we downloaded the seed protein sequences for each of the PFAM entries that matched the toxins. Protein sequence alignment of the toxins with the corresponding PFAM seed sequences and phylogenetic reconstruction followed the same procedure described above for TnpA proteins.Transposons were compared all-against-all using blastn. For transposons having a toxin from the same family, all pairwise sequence similarities between the DNA segments comprising the transposase gene, the resolvase, and the TA were visualized as dot plots using flexidot version 1.06  with 10


RAB37 promoter by a comparative analysis of promoter activities of RAB37 in humans, mice, and pigs. Two of the transcription factors bound to and co-regulated RAB37 promoter in each species. SNPs were further screened in pig RAB37 gene by population genomics in pig populations from both China and Europe. Three SNPs were identified in second CpG island upstream of core promoter of RAB37. These SNP variations led to at least 5 haplotypes, representing 5 multiple alleles of RAB37 in pig population. Distribution of these alleles in different genetic background of breeds showed a role of artificial selection for the variations of these multiple alleles. Of them, RAB37-c acquired the highest ability to activate gene expression in comparison with the other promoters, thus enhanced autophagy efficiently. These findings provide better understanding of transcription activation of RAB37 and artificial selection via RAB37 for autophagy regulation.Detecting selection signatures in genomes that relates to transcription regulation has been challenges in genetic analysis. Here, we report a set of transcription factors EBF1, E2F1 and EGR2 for transcription activation of  Macroautophagy (hereafter autophagy) is an evolutionarily conserved process of catabolism, in which intracellular unwanted components and organelles are sequestered by double-membrane vesicle and delivered to the lysosome for degradation and recycling. Autophagy pathways usually degrade cytoplasmic components, and yet selective nuclear autophagy (nucleophagy) has been observed in eukaryotic cells Autophagy occurs when cells encounter different forms of stress in various physiological and pathological conditions, including nutrient deprivation and hypoxia. A range of signaling activated phagophore induction process, which were involved in a set of ATGs proteins  RAB37 was associated with metastasis RAB37, as a small GTPase, plays important roles in several cellular processes through intracellular membrane traffic. RAB37 can regulate insulin secretion in β-cells RAB37 remain elusive. To further explore transcription activation of RAB37, in this study, we comparatively analyzed promoter activities of RAB37 in humans, mice, and pigs, investigated transcription factors and their binding abilities to the promoters of RAB37 genes in these species, screened polymorphism in pig RAB37 gene, and identified RAB37 alleles in pig populations worldwide. Further roles of these RAB37 alleles in autophagy were analyzed. These results highlight the importance of transcription activation of RAB37 in autophagy.As the core machinery of autophagy, the complex ATG5-ATG12-ATG16L1 was essential for LC3B lipidation and thus promoted autophagosome membrane biogenesis Anti-LC3B (Cat# 3868) was purchased from Cell Signalling Technology, Danvers, MA, USA. Anti-p62 (SQSTM1) (Cat# 18420-1-AP) was from Proteintech Group, Rosemont, IL, USA. Anti-FLAG antibody (Cat# F3165) was from Sigma-Aldrich, St Louis, MO, USA. Goat anti-rabbit IgG (H+L), horseradish peroxidase (HRP) conjugated antibody (Cat# 31460), goat anti-mouse IgG (H+L), HRP conjugated antibody (Cat# 31430), and TRITC-conjugated ImmunoPure goat anti-rabbit IgG (H+L) (A16071) were obtained from Invitrogen, Carlsbad, USA. DAPI (Cat# C1002) was purchased from Beyotime Institute of Biotechnology . EBSS (Cat# SH30029.02) was from HyClone, Logan, USA.RAB37 (ENSSSCT00025032574.1) promoter were amplified from pig genomic DNA, and cloned into pGL3-basic  vector digested by XhoΙ and HindⅢ. Full-length EBF1 (ENSSSCT00000040359.2) and EGR2 (ENSSSCT00025106300.1) of pig were cloned into pcDNA3.0 using HindⅢ/XhoΙ and HindⅢ/EcoRΙ double digestion to generate pCMV-pig-EBF1 and pCMV-pig-EGR2. Site-directed mutagenesis for the EBF1 and EGR2 binding sites were performed using the primers described in Eight deletion fragments of the pig RAB37 containing relevant alleles were cloned into pGL3-basic vector (digested by XhoΙ and HindⅢ) to generate pGL3-RAB37 . These promoter fragments were cloned into RAB37-FLAG and RAB37-GFP Four different promoter fragments of pig RAB37 promoters. MethPrimer software (www.urogene.org) was used to predict the CpG islands in promoter with island size > 100, observed/expected ratios > 0.6, and GC percent > 50.0. JASPAR database (jaspar.genereg.net/) was used to search sequences and logos of transcription factors.Genomatix database (www.genomatix.de) was used to predict transcription factors in RAB37 promoter regions by polymerase chain reaction and primers described in Sus scrofa 11.1 using Ensembl and corresponding SNP position of the sequences was determined in the region of chr12: 6493414-6494172. Positions on the chromosome of SNP variations were at nt 6493746 (SNP1), nt 6493872 (SNP2), and nt 6493991 (SNP3). SNP sites were blasted against available SNP data in the Ensembl databases. SNP frequencies were calculated based on these data.Genomic DNA samples from Meishan, Xihuzhou large white and Tongcheng pigs were used to amplify the COS-7, 293T and CHO cells were obtained from China Center for Type Culture Collection. COS-7 and 293T cells were cultured in DMEM  with 10% FBS . CHO cells were cultured in MEM  with 10% FBS.Dual-luciferase reporter assays were performed according to our previous protocols Western blots were performed following our previous protocols Immunofluorescence analysis was performed according to our previous study P value < 0.05 was considered to be statistically significant.The data were presented as the means ± standard deviation from at least three independent experiments. One-way analysis of variance was tested for comparisons among more than two groups. Statistics analysis was performed using GraphPad Prism 7 software package . For all analyses, RAB37, we analyzed potential transcription factors to activate RAB37 transcription in pig. CpG island and transcription factors were first predicted. An EBF1 binding site (-35 bp to -23 bp) and an E2F1 binding site (-27 bp to -9 bp) were detected in a CpG island in the potential promoter in pig , while another transcription factor was also essential for transcription activation of the RAB37 gene  were higher than that of wild-type pGL3-RAB37-a in CHO cells  for RAB37 genes was acquired in these species. These data suggest that these transcription factors regulate RAB37 via transcription factor-associated evolution in RAB37 promoter for maintaining cellular homeostasis. These transcription factors can also directly regulate transcription of autophagy genes. For example, E2F1 can bind to the promoter regions of autophagy genes LC3B, ATG1, and DRAM to activate transcription of these genes, thus enhanced autophagy ATG12, ATG16L2, ATG9B, ULK3, SQSTM1 and RAB37RAB37. These two modes of regulation probably exert roles synergistically, which is important for maintaining cellular homeostasis upon different forms of stress. Further studies are needed to clarify this mechanism.In addition to EBF1, co-regulation of transcription factors EGR2 and E2F1 differentially evolved for RAB37 promoter, in addition to transcription factors EBF1 and EGR2 selected to activate RAB37 promoter in the pig lineage. Three SNPs are located in second CpG island upstream of core promoter of RAB37, which could affect binding of EBF1 and EGR2 to RAB37 promoter by mediating spatial structure of transcription complex. These SNP variations resulted in at least 5 haplotypes, representing 5 alleles of RAB37. Of them, RAB37-c acquired the highest ability to activate expression in comparison with the other promoters, thus enhanced autophagy efficiently. A large scale of population genome analysis from both China and Europe demonstrated that artificial selection led to RAB37 multiple alleles in pig population , acquired 100% frequency of the allele RAB37-c. Considering a high female fecundity in Jiangquhai pigs and Meishan pigs, the allele RAB37-c could be artificially selected for autophagy regulation. Further analysis to illuminate the molecular mechanism will help in genetics and breeding practice in pigs.Long-term artificial selection of female fecundity and meat production has changed gene expression pattern in pig breeding n Figure . Both ChRAB37 in humans, mice and pigs. Transcription factors and their binding abilities to the promoters were determined. SNPs in the pig RAB37 gene were screened and multiple alleles of RAB37 in pig populations from both China and Europe were identified. Population genomics showed a role of artificial selection in variations of these alleles. Furthermore, roles of RAB37 alleles in autophagy regulation were confirmed. These findings provided a better understanding of transcription activation of RAB37 and suggested RAB37 as a potential gene for artificial selection of autophagy regulation in pig breeding practice.In this study, we performed a comparative analysis of promoter activities and related transcription factors of Supplementary figures and tables.Click here for additional data file.


A new study demonstrates that the disordered N-terminal domain of DNMT3A1 binds PRC1-catalyzed H2AK119ub, targeting DNA methylation to bivalent promoters in mouse brain cortical cells. Methylation around bivalent genes is critical for mouse postnatal development, and could be equally important in other cell types and in disease. It is added de novo by DNA methyltransferases 3A, 3B and 3C (DNMT3A/B/C) and maintained across cell divisions by DNMT11. Dnmt3a is essential for postnatal development: knockout mice are runted and die at ~4 weeks of age2. In humans, DNMT3A mutations are associated with paragangliomas3, microcephalic dwarfism4 and cancer5. There are two distinct isoforms of DNMT3A: DNMT3A1 and DNMT3A2  is an important epigenetic modification associated with gene expression levels during development, in aging and in disease  DNMT3A2 . Both co DNMT3A2 . Little Dnmt3a the authors generated isoform-specific knockout mice and found that, whilst Dnmt3a2-/- mice had no altered phenotype, Dnmt3a1-/- mice were similar to Dnmt3a-/- knockouts8. Because they found that Dnmt3a1 is predominantly expressed in the brain, and indeed re-expression in the brain could partially rescue the knockout phenotype, they focused here for mechanistic experiments.To understand the difference between the two isoforms of 10. Thus, the authors show that DNMT3A1 flanks the promoters of genes that are important for neuronal development. The authors also detected DNMT3A1 binding at enhancer elements, but we do not yet know what role it plays here. Enhancers and bivalent domains are enriched for 5-hydroxymethylcytosine (5hmC)12, generated through oxidation of 5mC. 5hmC also accumulates in neurons, more so than in many other somatic cell types13, so perhaps DNMT3A1 also plays a role in the accumulation of this poorly understood epigenetic modification.Isoform-specific chromatin immunoprecipitation and sequencing (ChIP-seq) of DNMT3A1 in the cerebral cortex revealed enrichment flanking bivalent neurodevelopmental gene promoters, which was dependent on the disordered N-terminal domain . Bivalency is the co-occurrence of histone modifications associated with gene activation (H3K4me3) and repression (H3K27me3 and H2AK119ub) across the same region. It is characteristic of promoters regulating developmental genes that are not expressed at high levels but are poised for activation upon stimulation; for example, following activation of a signaling pathway that induces differentiation8. Contrarily, RNA-seq of sorted neuronal nuclei revealed both up- and down-regulation of genes in response to Dnmt3a1 knockout, and only a weak correlation between hypomethylation and differential gene expression. The different transcriptional changes in the cortex (a heterogeneous tissue) and sorted neuronal cells is intriguing and warrants further investigation – does Dnmt3a1 function differently in glia? Promoter methylation is traditionally thought to be gene repressive, but methylation at the flanks of bivalent domains could also activate gene expression if it is important to constrain polycomb activity and thus the distribution of repressive histone modifications14. Loss of DNMT3A1 would also presumably result in loss of 5hmC, which could also have a regulatory role.DNMT3A1 depletion resulted in hypomethylation around bound genes in cells from the cerebral cortex of knockout mice, and RNA sequencing (RNA-seq) experiments largely revealed downregulation of bivalent neurodevelopmental genes relative to wild type controlsIn vitro nucleosome pulldown assays confirmed that the N-terminal domain interacts with H2AK119ub, and this interaction was abrogated upon mutation of the UBR. A similar domain was described by Weinberg et al.15 who demonstrated that, in mesenchymal stem-like cells (MSCs), DNMT3A1 is capable of binding H2AK119ub at bivalent genes via the N-terminal disordered region. Intriguingly they only observed this when the PWWP domain of DNMT3A was mutated, as it is in some diseases5. Moreover, they show that this binding is dependent on H2AK119ub, catalyzed by polycomb repressive complex 1 (PRC1), but independent of PRC2 and H3K27me315.Next, the authors asked how the N-terminal domain of DNMT3A1 confers binding to bivalent domains. Computational analysis identified a putative ubiquitin binding region (UBR) within a predicted alpha-helix at amino acids 189-206. 15 are certainly a good place to begin looking for regulatory PTMs. Differential isoform usage is another route by which cells could govern DNMT3A activity – DNMT3A2 is the dominant isoform in embryonic stem cells and Gu, Hao et al. show that it is also expressed in bone marrow, spleen, testis and thymus. DNMT3A1 is the predominant isoform in the brain, kidneys and liver8. Perhaps, then, targeting of DNMT3A to bivalent domains is not desirable in certain tissues, such as pluripotent cells, and it would be interesting to understand whether the lack of this binding activity is important for transcriptional programs and/or pluripotency. Indeed, aberrant binding of DNMT3A to H2AK119ub in contexts where the PWWP domain is mutated, such as in paragangliomas and microcephalic dwarfism4, could be a mechanism that drives pathologies.Together these works suggest that DNMT3A1 can be targeted by different molecular mechanisms in different contexts. Likely in some cell types targeting through the PWWP and ADD domains is dominant. In other contexts, including in neurons and in certain diseases, binding via the N-terminal domain is more common . It willet al.8 in this issue together with the recent publication by Weinberg et al.15 identify an exciting molecular cross talk between PRC1, H2AK119ub and DNMT3A1 that is dependent on a novel UBR in the N-terminal disordered domain. This isoform, and specifically the N-terminal domain, is critical for neurodevelopmental gene expression and mouse postnatal development. Targeting of DNMT3A1 in different cell types is an interesting area of future research that may be of (patho)physiological importance.Overall, the study by Gu, Hao