However, the essential transcription factor for gene expression of HOTAIRM1 is still unknown.Long noncoding RNA HOX antisense intergenic RNA myeloid 1 (HOTAIRM1) has been characterized as a critical factor in allHOTAIRM1. Co-expression of PU.1 led to the transactivation of the regulatory region of HOTAIRM1 in a reporter assay. Detailed analysis showed that two PU.1 motifs, which were located around +1100 bp downstream of the transcriptional start site of the HOTAIRM1 promoter, were responsible for the PU.1-dependent transactivation. The induction of HOTAIRM1 by ATRA was dependent on PU.1, and ectopic expression of PU.1 significantly up-regulated HOTAIRM1. Furthermore, low HOTAIRM1 expression was observed in APL cells, which was attributed to the reduced PU.1 expression rather than the repression by PML-RARα via the direct binding.Chromatin immunoprecipitation (ChIP) assays revealed that PU.1 constitutively bound to the regulatory region of HOTAIRM1 during granulocytic differentiation. The reduced PU.1 expression, rather than PML-RARα itself, results in the low expression of HOTAIRM1 in APL cells. Our findings enrich the knowledge on the regulation of lncRNAs and the underlying mechanisms of the abnormal expression of lncRNAs involved in APL.PU.1 directly activates the expression of HOTAIRM1 through binding to the regulatory region of The online version of this article (doi:10.1186/s13045-016-0274-1) contains supplementary material, which is available to authorized users. Recently, it has become increasingly clear that long noncoding RNAs (lncRNAs) function as a class of versatile regulators through interaction with DNA, RNA, and proteins to modulate gene expression –3. ExtenHOXA1 and HOXA2 genes. Functional studies have revealed that HOTAIRM1 is essential for myeloid differentiation. HOTAIRM1 knockdown impairs all-trans retinoic acid (ATRA)-driven granulocytic differentiation and attenuates the expression of differentiation-related genes including ITGAM, CD18, HOXA1, and HOXA4 [HOX antisense intergenic RNA myeloid 1 (HOTAIRM1) is a myeloid-specific lncRNA, which is transcribed between the nd HOXA4 . A recennd HOXA4 . In addind HOXA4 . DespiteTranscription factor PU.1 is a master regulator in the control of myeloid differentiation –13. PU.1HOTAIRM1 in vivo and transactivated this region, which was mainly mediated through two PU.1 motifs around +1100 bp downstream to the transcription start site (TSS). Furthermore, PU.1 knockdown down-regulated HOTAIRM1 and PU.1 overexpression increased HOTAIRM1. Finally, we revealed that the reduced PU.1 expression was responsible for the low HOTAIRM1 expression in APL cells.In this study, using chromatin immunoprecipitation (ChIP) and luciferase reporter assays, we found that PU.1 bound to the regulatory region of It has been shown that HOTAIRM1 is up-regulated in APL cells upon exposure to ATRA and plays a critical role in myeloid differentiation . Since HHOTAIRM1, which can be defined using binding profiles of H3K4me3 and H3K27Ac. Due to the myeloid-specific expression of HOTAIRM1, we chose CD14+ monocytes (a myeloid lineage) for the analysis. We utilized the chromatin immunoprecipitation (ChIP)-seq data generated by the ENCODE Project Consortium [http://genome.ucsc.edu) [HOTAIRM1 and this region was used in the following experiment and analysis. We then investigated the significantly enriched transcription factor binding sites within this regulatory region of HOTAIRM1 using Matinspector [HOTAIRM1.To search for the newly synthesized regulatory factors involved in the up-regulation of HOTAIRM1, we first identified the regulatory region responsible for the transcriptional regulation of nsortium . The bincsc.edu) . As shownspector . InteresHOTAIRM1 through the PU.1 binding sites identified above, we employed the luciferase reporter assay in HEK-293T cells, which lack endogenous PU.1. We cloned a 1370 bp fragment of the regulatory region of HOTAIRM1 spanning from −134 to +1237 into a luciferase reporter plasmid, which was designated as pGL3-HOTAIRM1 , another effective agent used in APL therapy, on HOTAIRM1 expression. We found that ATO had almost no effect on the expression levels of HOTAIRM1 and PU.1  Fig. . To valiHOTAIRM1 using ChIP-qPCR assays. As shown in Fig. HOTAIRM1 in NB4 cells, indicating that PML-RARα did not directly bind to the HOTAIRM1 promoter to repress its expression. The luciferase reporter assay also showed that PML-RARα had minimal impact on the promoter activity of HOTAIRM1   Fig. . To supp16) Fig. . This alTaken together, the data suggested that low HOTAIRM1 expression in APL cells was attributed to the reduced PU.1 expression rather than repression by PML-RARα via the direct binding.HOTAIRM1 was not a direct ATRA-responsive gene, and the observed up-regulation of HOTAIRM1 induced by ATRA was a secondary event that was dependent on the expression of PU.1 activated by ATRA.Recently, extensive studies have been carried out to understand the functions of lncRNAs, but fewer studies have focused on the regulation of lncRNAs. In this study, we reveal that the transcription factor PU.1 controls the expression of the lncRNA HOTAIRM1, which acts as a critical noncoding regulator in ATRA-induced granulocytic differentiation of APL cells. On the one hand, we showed that HOTAIRM1 to transactivate the promoter activity of HOTAIRM1 and identified the two PU.1 motifs responsible for the PU.1-dependent transactivation. These findings enrich our knowledge on the regulation of lncRNAs and the underlying mechanisms of the abnormal expression of lncRNAs involved in APL.On the other hand, we observed low HOTAIRM1 expression in APL cells and revealed that low expression was attributed to the reduced PU.1 expression, rather than the direct binding and repression of PML-RARα. To support these observations, we provided the evidence that PU.1 constitutively bound to the regulatory region of HOTAIRM1 as a novel target of PU.1. This finding implicates that there still exist unidentified PU.1 targets that are essential for myeloid differentiation. To date, most of the known PU.1 direct target genes participating in myeloid differentiation belong to protein-coding genes [HOTAIRM1, there are perhaps hundreds of lncRNA candidates potentially under the transcriptional control of PU.1, among which some are likely correlated with or necessary for myeloid differentiation. Systematic approaches like ChIP-seq and RNA-seq would be a powerful tool to globally identify these PU.1 candidate targets. In addition, we also identified the direct binding site of PU.1 at the +1100 downstream of the TSS of the HOTAIRM1 promoter. It is worth mentioning that it was possible that the −122 region might also have a partial impact on the promoter activity of HOTAIRM1, although we focused on the +1067/+1123 locus in the luciferase reporter assay , HCK, PSMB10, and IRF1 [HOTAIRM1. Instead, we found that the dysregulated expression level of HOTAIRM1 was due to the inhibition of PU.1, which suggested the PML-RARα-suppressive effect on HOTAIRM1 was indirect. Also, this explains the noticeably low level of HOTAIRM1 in APL and suggests that the indirect suppression by PML-RARα can also be potent. Considering the indispensable role of HOTAIRM1 in myeloid differentiation [HOTIARM1 contributes to the differentiation block in APL, which provides an additional mechanism for leukemogenesis in APL.Finally, our work revealed the mechanism underlying the dysregulation of HOTAIRM1 in APL cells. PML-RARα is a critical factor required for the initiation and development of APL. At the transcriptional level, PML-RARα represses genes indispensable for normal granulocytic differentiation through multiple ways. First, PML-RARα interferes with the retinoid acid receptor α (RARα) signaling. As a potent transcriptional repressor, PML-RARα directly binds to the retinoic acid response elements (RAREs), recruiting co-repressor proteins such as DAXX, NcoR, and HDAC1 or methylating enzymes such as DNMT1 and DNMT3A, thereby leading to transcriptional repression . Second,and IRF1 . Our stuntiation , our worHOTAIRM1 as a novel PU.1-targeted gene and PU.1 mediates the myeloid-specific expression of HOTAIRM1. PU.1-dependent transactivation of HOTAIRM1 relies on the two PU.1 motifs at the +1100 region of the HOTAIRM1 promoter. The inhibition of PU.1 by PML-RARα contributes to the low HOTAIRM1 level in APL cells, which allows us to understand further how the oncofusion protein PML-RARα blocks myeloid cells at the promyelocytic stage during the development of APL.In conclusion, we identify the lncRNA 2 incubator. All-trans retinoic acid  was added to NB4 or U937 cells at a final concentration of 1 μM.HEK-293T cells were cultured in DMEM  containing 10 % fetal bovine serum , and NB4, HL60, and U937 cells were cultured in RPMI 1640 (Gibco) supplemented with 10 % fetal bovine serum. Cells were maintained at 37 °C in a 5 % COTotal RNA was extracted using an RNeasy Mini Kit  according to the manufacturer’s directions. Reverse transcription was performed using the SuperScript III Reverse Transcriptase . Real-time PCR was performed using the SYBR Green real-time PCR Master Mix  in the Vii7 Real-Time PCR System . All primers for quantitative reverse transcription-PCR (qRT-PCR) are listed in Additional file HOTAIRM1 was amplified using NB4 genomic DNA and then cloned to a pGL3-basic luciferase reporter vector . The PU.1-coding sequence was amplified using NB4 cDNA and then cloned to the MigR1 vector (Addgene).The regulatory region of Chromatin immunoprecipitation (ChIP) was performed according to the Affymetrix protocol as previously described . The folLuciferase assays were conducted in HEK-293T cells as previously described . Dual-luThe siRNA oligos were transiently transfected to NB4 cells using Nucleofector Kit V  according to the manufacturer’s instructions. PU.1-targeting siRNA oligos matching the sequences: CACUCAAGGCUCUUUGCUU (siPU.1 #1) and GAUGUUACAGGCGUGCAAA (siPU.1 #2), and a negative control siRNA (AGCGUGUAGCUAGCAGAGG), were used. After transfection for 24 h, cells were harvested for qRT-PCR.The MigR1 vector (Addgene) was used to transduce NB4 cells for PU.1 overexpression. The preparation of retroviruses and transduction was done as previously described . BrieflyThe transcriptome data was provided by Tomasson et al.  (GSE1035


Salmonella enterica spp. have been shown to invade and colonize neoplastic tissues where it retards the growth of many tumors. This offers the possibility to use the bacteria as a vehicle for the tumor specific delivery of therapeutic molecules. Specificity of such delivery is solely depending on promoter sequences that control the production of a target molecule. We have established the functional structure of bacterial promoters that are transcriptionally active exclusively in tumor tissues after systemic application. We observed that the specific transcriptional activation is accomplished by a combination of a weak basal promoter and a strong FNR binding site. This represents a minimal set of control elements required for such activation. In natural promoters, additional DNA remodeling elements are found that alter the level of transcription quantitatively. Inefficiency of the basal promoter ensures the absence of transcription outside tumors. As a proof of concept, we compiled an artificial promoter sequence from individual motifs representing FNR and basal promoter and showed specific activation in a tumor microenvironment. Our results open possibilities for the generation of promoters with an adjusted level of expression of target proteins in particular for applications in bacterial tumor therapy.Systemically applied  Clostridia spp. that are able to grow exclusively in necrotic tumor areas without oxygen supply, facultative anaerobes like Salmonella enterica spp. have been shown to target tumors and spread throughout the entire neoplastic tissue.Cancer is one of the most frequent cause of death and its incidence is rising . This reSalmonella would be perfect candidates to be used as such transporters. However, the normal target organs of Salmonella, spleen and liver, are also colonized in tumor bearing hosts. Thus, to prevent the destruction of these healthy tissues the expression of the therapeutic agent must be exclusively restricted to the tumor mass.Besides their inherent anti-cancer effect, these bacteria offer the possibility to act as transport vehicles for therapeutic agents. Such molecules are usually toxic and should exclusively be expressed directly in the tumor. On the other hand, to be most effective, sufficient concentrations of such therapeutic molecules should be reached throughout the entire cancerous tissue. Facultative anaerobic bacteria like S. Typhimurium several DNA fragments containing promoters that specifically respond to the physiological conditions of cancerous tissue . Therefore, TSPs should contain basal promoter structures like -10 and -35 elements as a prerequisite for gene transcription.The strategy employed here is illustrated in rategies . Based oBasalPTSP = 0.92. In the NP set the frequency is BasalPNP = 0.27. For HMM, the values are BasalPTSP = 0.83 and BasalPNP = 0.43, respectively. It is clear, that the specificity of predictions by the kernel method is much higher than by HMM. Thus, the kernel method was assumed to be more reliable and results obtained by it considered further. To identify exact positions of TATA-box and Inr element, program BROM [The kernel method identified basal promoters in 12 out of 13 TSPs giving a frequency of Tumor specific transcriptional activation is apparently achieved by features encoded in the DNA sequence of TSP promoters. Such features could be, for example, transcription factor binding motifs or specific conformations of the DNA. Therefore, it was hypothesized that TSP promoters should contain a motif or motifs that either activate transcription exclusively in tumors and/or suppress basal promoter activity in tissues other than tumors such that the observed specificity of transcription would be achieved.The remainder of this subsection will be organized as follows: i) identification of known DNA motifs, ii) identification of novel DNA motifs, iii) identification of other possible features of the promoters and finally iv) combinatorial analysis of identified motifs and other features.Recognition of known transcription factor binding motifs on DNA is usually carried out with the help of position weight matrixes (PWMs) that are collected in databases like DPInteract , TRANSFAPotential binding motifs were identified using all three databases. Thresholds for each PWM were varied to maximize the discrimination between TSP and NP as described in Methods. Following this strategy, motifs for a number of prokaryotic  and eukaryotic  transcription factors were identified as specific for the TSP dataset. Top scoring motifs are shown in Along with library based searches, programs for DNA motif detection exist that do not require databases of PWMs. Such programs evaluate the statistical occurrence of DNA motifs and usually do not differentiate between pro- and eukaryotic genomes. Several programs were applied to our data and the resulting PWMs were examined for specificity to the TSP set as above. Only a few programs identified specific motifs, namely: 6 motifs by Meme , 2 by DMATTSP = 0.512, ATNP = 0.468) and can be specifically characterized by the presence of AT-rich regions , but not in the set of NP (A8NP = 0.47). This feature may represent a general transcriptional activity of the promoters not connected to tumor activation and therefore may represent a general promoter feature.Features like nucleotide composition are also known to affect gene expression. It was found that TSP promoters are in general AT-rich , cloned and confirmed by sequencing. Results of the analysis by flow cytometry are presented in The promoter model identified above consists of three regulatory DNA elements and according to the literature all of them may regulate transcription both positively and negatively –23. To tFrom this analysis it became clear that the motif for transcription factor NagC is not functional. Mutation of this motif did not change differential tumor specific expression. On the other hand, modification of the FNR motif completely disrupted transcription . The same effect was found for the TATA-box . Deletion in the TGIF motif reduced transcription to approx. 75% of the level of the original promoter . Mutations at insignificant positions in motifs FNR and NagC (clone P1.6) did not influence specificity of transcription, but led to increase in expression in tumors by approximately 60% . ChangesSalmonella yielded the same results  set. A randomly selected region of 100bp from this fragment was used as template. The idea here was to create a minimal set of promoters comprising all discovered functional elements for FNR and TSS including their consensus sequences from the literature. This should confirm the validity of the proposed principle and the functionality of each element.Inr element (P2.4) and another one was complemented by an additional FNR consensus sequence (P2.5).Five promoters were constructed by implanting the FNR motif together with basal promoter elements into the template. We denote these as round 2 promoters "P2." . The third set of promoters showed even an increased level of expression under aerobic in vitro conditions. In vivo expression of such promoters was still restricted to the cancerous tissue  staining between necrotic and viable tumor zones  as identified by the BROM program . So for and thrA , for NP From another side, the overall score revealed by the kernel method  of the TThe deviation from the well known assumption that promoters should mainly respond to anaerobic conditions, known as Warburg effect, is interesting. Promoters of group A in Salmonella are not evolutionary selected for the microenvironment of a solid tumor. Rather, the tumor mimics natural habitats of the bacteria. Hypoxia and anoxia, as can be found in the central necrotic or its neighboring regions, was a first apparent suggestion by us and others. Such conditions might not prevail in systemic organs but are most likely excessive in the large intestine. This idea was only partly confirmed. Apparently, the tumor microenvironment represents a highly complex environment for which a natural equivalent cannot be envisioned yet. It will be important to unravel such conditions further as it may provide new targets for therapy by bacteria or other means.Obviously, promoters of Procedures involving animals and their care were fully in compliance with the German Animal Welfare Act  and with the permission number 33.9.42502-04-050/09 of LAVES (Niedersaechsisches Landesamt fur Verbraucherschutz und Lebensmittelsicherheit).To construct plasmids that contain fragments of the original library inserts , oligonu5 CT26 colon carcinoma cells (ATCC CRL-2638). When tumors reached volumes of approximately 200 mm3, mice were infected intravenously with 5x106 bacteria  in 100 μl PBS. One, three, and five days after infection, mice were sacrificed by exposure to CO2, respective tissues were removed and homogenized in 2 ml PBS. The homogenates were diluted 1:10  or 1:100 (tumors) in 0.1% TritonX-100/PBS containing 2 mM EDTA, filtered through a 30 μm CellTrics filter  and sorted. Samples were analyzed via two color flow cytometry on a FACSAria or LSRII, respectively  and plated on LB plates containing 50 μg/ml ampicillin to allow normalization. No plasmid loss was confirmed via plating on ampicillin. The two color flow cytometry is a method that allows to discriminate GFP expressing bacteria from autofluorescent cellular debris since GFP expressing Salmonella have a substantially lower orange/green emission ratio [Salmonella from larger particles by setting an appropriate scatter gate. For more detailed information see [Eight weeks old female BALB/c mice were purchased from Janvier (France) and subcutaneously injected with 5x10on ratio . Additio2, supplemented with the appropriate antibiotics, 100 μM MgSO4, 40 μg/ml histidine, 40 μg/ml phenylalanine, 40 μg/ml tryptophane, 40 μg/ml tyrosine, 10 μg/ml para-aminobenzoic acid, 10 μg/ml 2,3-dihydroxybenzoate and 0.2% glucose. The salt concentration was decreased to 0.05% NaCl and the pH was adjusted to 5.5 (IM) or to 7.4 (MM). From the 4 ml liquid cultures (i) 200 μl were used to start two new cultures of 20 ml LB medium each. One was grown under aerobic and the other under anaerobic conditions. Before 1:100 inoculation of the 15 ml liquid cultures for condition (ii), the cultured bacterial cells were washed twice in PBS and adjusted to OD600 of 1.0. Cultures were analyzed at different time points by flow cytometry and parallel by OD600 measurements or plating to allow normalization. Data presented were derived from 3 hrs  or 4 hrs (aerobic/anaerobic) cultures, respectively.Respective bacterial strains were streaked out from glycerol stocks onto LB agar plates containing the appropriate antibiotics. After overnight growth at 37°C, the cultures were used to inoculate (i) 4 ml LB medium with antibiotics and grown at 37°C overnight with shaking at 180 rpm or (ii) 15 ml of induction medium (IM) and minimal medium (MM). Both are M9 medium based  without Salmonella genome into fragments following the same length distribution as in the TSP set, resulting in 7682 sequences. Negative promoters (NP) are DNA fragments from the Salmonella genome that are proved not to initiate any transcription either in tumors or spleen [Datasets of promoter sequences were compiled on the basis of our previous research. According to that, tumor specific promoters (TSP) are 13 promoters from class 1, 115 negative promoters (NP) are from class 5 and lowTSPs are 12 promoters from class 2 . LowTSP Promoter nomenclature will be as follows. Promoters from  will be ElementNameTSP and for negative promoters as ElementNameNP. Recognition was performed for a range of values for each parameter required by a method and those values that maximize the ratio ElementNameTSP/ElementNameNP were selected as optimal, provided that the boundary conditions are met (i.e. ElementNameTSP ≥0.75 and ElementNameNP≤0.50). The higher the ratio the more specific is an element to the promoters.Parameters of the methods for recognition of basal promoters, regulatory motifs and other elements were selected such that they maximize discrimination between tumor specific promoters and negative promoters. As boundary condition, it was set that at least 75% (10 out of 13) of TSPs must have a minimum of one recognized element and at most 50% of NPs may contain such an element. We will denote a portion of TSPs that have an element as 8), one mismatch is allowed. To identify exact positions of TATA-box and Inr element program BROM [This principle was applied for recognition of basal promoters using Kernel  and HMM ram BROM  was applram BROM . Due to S1 FigValues are normalized numbers of promoters in a set containing at least one motif. P–values are calculated as a binomial probability to observe the actual number of promoters with a motif in the TSP set compared to RP set.(DOC)Click here for additional data file.S2 FigDNA motifs for FNR are shown in yellow, NagC in light brown, TGIF in green, TATA-box and Inr element in grey. Mutated nucleotides are shown in red.(DOC)Click here for additional data file.S3 FigDNA motifs for FNR are shown in yellow, -35 and -10 elements are in grey. Nucleotides introduced into the template sequence are in capital and marked red.(DOC)Click here for additional data file.S1 Table(DOC)Click here for additional data file.S2 TableEach module consists of two or more elements indicated by "+". P–values are calculated as a binomial probability to observe the actual number of promoters with a module in the TSP set compared to RP set.(DOC)Click here for additional data file.S1 Text(DOC)Click here for additional data file.


YRA1 intron-less constructs and analyzed its effect on gene expression and genome integrity. We found that YRA1 overexpression induces DNA damage and leads to a transcription-associated hyperrecombination phenotype that is mediated by RNA:DNA hybrids. In addition, it confers a genome-wide replication retardation as seen by reduced BrdU incorporation and accumulation of the Rrm3 helicase. In addition, YRA1 overexpression causes a cell senescence-like phenotype and telomere shortening. ChIP-chip analysis shows that overexpressed Yra1 is loaded to transcribed chromatin along the genome and to Y’ telomeric regions, where Rrm3 is also accumulated, suggesting an impairment of telomere replication. Our work not only demonstrates that a proper stoichiometry of the Yra1 mRNA binding and export factor is required to maintain genome integrity and telomere homeostasis, but suggests that the cellular imbalance between transcribed RNA and specific RNA-binding factors may become a major cause of genome instability mediated by co-transcriptional replication impairment.Yra1 is an essential nuclear factor of the evolutionarily conserved family of hnRNP-like export factors that when overexpressed impairs mRNA export and cell growth. To investigate further the relevance of proper Yra1 stoichiometry in the cell, we overexpressed Yra1 by transforming yeast cells with  Saccharomyces cerevisiae. The cellular levels of Yra1 are tightly auto-regulated by splicing of an unusual intron in its pre-mRNA, removal of which causes Yra1 overexpression that results in a dominant-negative growth defect and mRNA export defect. We wondered whether or not YRA1 overexpression has an effect on genome integrity that could explain the loss of cell viability. Our analyses reveal that YRA1 overexpression causes DNA damage, confers a hyperrecombination phenotype that depends on transcription and that is mediated by RNA:DNA hybrids. YRA1 overexpression also leads to a cell senescence-like phenotype and telomere shortening. We show by ChIP-chip analysis that Yra1 binds to active chromatin and Y’ telomeric regions when it is overexpressed, in agreement with a possible role of this mRNP factor in the maintenance of telomere integrity. Our data indicate that YRA1 overexpression correlates with replication impairment as inferred by the reduction of BrdU incorporation and the increase of Rrm3 recruitment, a helicase involved in replication fork progression, at transcribed genes and Y’ regions. We conclude that the stoichiometry of specific RNA-binding factors such as Yra1 at telomeres is critical for genome integrity and for preventing transcription-replication conflicts.Yra1 is an essential nuclear RNA-binding protein that plays a role in mRNA export in  Messenger RNA (mRNA) is coated by RNA-binding proteins (RBPs) forming large messenger ribonucleoprotein particles (mRNPs). Many mRNA processing factors that participate in 5′-end capping, splicing, 3′-end processing, and polyadenylation are loaded co-transcriptionally to the pre-mRNA through interactions with the carboxy-terminal domain (CTD) of the RNA polymerase II (RNAPII) ,2. Co-trCo-transcriptional mRNP biogenesis has also been shown to be necessary for the maintenance of genome integrity. The correct formation of an mRNP particle has been proposed to prevent nascent pre-mRNA molecules from physical entanglement with DNA during transcription and the formation of R loops that would hinder transcription elongation and constitutes a block for replication fork progression . One of Yra1 is an essential nuclear RNA-binding protein that belongs to the evolutionarily conserved REF family of hnRNP-like export factors . It contYRA1 is one of the 5% of yeast genes that undergo splicing, containing an unusual intron in size and branch-point sequences, and its expression is negatively auto-regulated by splicing of its unusual intron . Hi. HiYRA1 1 intron . Interest defect  41] [38 [38YRA1 t defect  43]. Im. ImYRA1 t defect ,45;46];;YRA1 is t defect . ConsequYRA1 overexpression in yeast. We show that YRA1 overexpression causes DNA damage and a transcription-associated-hyperrecombination phenotype mediated by RNA:DNA hybrids. Interestingly, overexpression leads to a cell senescence-like phenotype and telomere shortening. Indeed, Yra1 binds to telomeres and its overexpression increases its occupancy and that of the Rrm3 DNA helicase at the Y’ telomeric regions, as determined by ChIP-chip analyses, and impairs replication, as determined by BrdU incorporation. The genome-wide occupancy of Rrm3 reveals a DNA replication impairment that can explain the genome instability phenotype observed. Our data suggest that stoichiometric amounts of Yra1 are critical for the maintenance of genome integrity, preventing the formation of aberrant co-transcriptional structures that may cause replication impairment.Here we examined the effect of YRA1 could interfere with these functions. For this purpose, we cloned the YRA1 gene (YRA1) and a cDNA copy of YRA1 (YRA1Δi) under the control of the Tet-off promoter, which is repressed upon doxycycline addition, and under the strong GAL1 promoter. YRA1 overexpression is achieved when expression is driven from YRA1Δi constructs, in agreement with previous reports (tet:YRA1Δi transformants an increase in YRA1 mRNA levels could be observed in medium without doxycycline (ON condition) and this effect was exacerbated in GAL::YRA1Δi cells grown in galactose-containing medium. To gain insight into the molecular basis of the growth inhibition phenotype associated with YRA1 over-expression we investigated whether this effect was increased in the absence of factors involved in the maintenance of genome integrity such as recombination factors, DNA-damage checkpoint proteins, DNA helicases and other factors involved in DNA metabolism  and recombination  mutants when YRA1Δi was expressed in 2% galactose-containing medium  that are transcribed from the LEU2 promoter, but they differ in the length of the transcribed intervening sequence  . T. TYRA1 g HA-YRA1 . However-YRA1Δi) . Since tYRA1 overexpression confers an increase in transcription-associated recombination (TAR), we wondered whether this was dependent on the nascent mRNA and whether was mediated by R loops. We first used the GL-Rib+ and GL-ribm repeat recombination systems that contains an active (Rib+) and inactive (ribm) hammerhead ribozyme, respectively , to, to35], nome see  S5 Fig)YRA1 over in ORFs  and peak in ORFs . This prYRA1 intron (YRA1 gene . Fo. FoS. ceMicroarray expression data were normalized by RMA (robust microarray average) and statistically analyzed by LIMMA , comparing the mutant expression profile with its isogenic wild-type strain. The genes showing at least a 1.5-fold expression change with a P-value < 0.01 with a false discovery rate (FDR) corrections were considered as significantly altered.ChIP–chip data were analyzed using the Tiling Array suite (TAS) software from Affymetrix. For each probe position, TAS produces the signal and the change P-value, taking into account the probes localized within a given band-width around the inspected probe. Protein chromosomal distribution was then analyzed by detecting binding clusters, which were defined as ranges within the chromosome respecting the following conditions: estimated signal (IP/SUP-binding ratio) positive in the whole range, P-value < 0.01, minimum run of 100 bp, and maximum gap of 250 bp.http://genome.ucsc.edu/). Distribution of binding sites along genes was carried out as previously described [The results were visualized with the UCSC Genome Browser, developed and maintained by the Genome Bioinformatics Group  Effect of YRA1 overexpression together with or without SUB2 overexpression. Ten-fold serial dilutions of WT cells transformed with either GAL::YRA1Δi, GAL::SUB2 or GAL::YRA1Δi and GAL::SUB2 constructs and plated on minimal selective medium with 2% galactose  and different amounts of glucose (Glu). Photographs were taken after 3 days of growth at 30°C. (B) Recombination analysis of the plasmid-borne recombination systems LY in WT cells transformed with either tet:YRA1, tet:YRA1Δi, tet::SUB2 or tet::SUB2 and tet::YRA1Δi constructs. Gray boxes represent LEU2 repeats. Arrows indicate the transcripts produced.((PDF)Click here for additional data file.S2 FigWestern blot analysis of cells transformed with HA-YRA1, HA-YRA1ΔI and HA-YRA1ΔRBDΔi constructs is plotted.(PDF)Click here for additional data file.S3 Fighpr1Δ mutant was included as positive control. Experiments were performed in 2% galactose to allow expression of the direct repeats.The (PDF)Click here for additional data file.S4 FigYRA1 deletion complemented with the YRA1 gene (YRA1), the mutant allele yra1-1, the complete cDNA (YRA1Δi) or the cDNA lacking the RBD domain (YRA1ΔRBDΔi) were grown in SC-Ura or SC-Trp medium. Three different transformants of each strain were analyzed by Southern blot. Sub-telomeric and telomeric fragments are visualized using a telomeric-specific probe (Y’ probe). Other details as in Strains carrying (PDF)Click here for additional data file.S5 Fig2 ratio values for the significant ChIP-chip clusters is plotted. The X-axis shows chromosomal coordinates in kb. Positions of centromeres are indicated as open circles.A representation of each chromosome with the signal log(PDF)Click here for additional data file.S6 FigA) Venn diagrams showing the overlap between genes sets with significant Yra1 binding in the different ChIP-chip experiments. (B) Yra1 cluster distribution at ARSs, centromeres, introns, ncRNA, transposable elements, RNAPIII genes, snoRNA/snRNA and telomeres under wild-type (HA-YRA1) and overexpression (HA-YRA1Δi) conditions.((PDF)Click here for additional data file.S7 Fig(A) RT-qPCR analysis of transcription levels of W303-1A (WT) cells expressing HA-YRA1 and HA-YRA1Δi constructs, treated or not with actinomycin D (ActD) for 2 hours. (B) ChIP and qPCR analysis in specific genomic regions of Yra1 in the same strains and conditions as in (A). Average and SD of three independent experiments are shown. Asterisks indicate statistically significant differences between the indicated conditions, according to Student's t-tests .(PDF)Click here for additional data file.S8 Fig(PDF)Click here for additional data file.S9 FigCells were synchronized in G1 with α-factor and released at 30°C.(PDF)Click here for additional data file.S10 FigOther details as in (PDF)Click here for additional data file.S11 Fig2 ratio values for the significant Rrm3 binding clusters is plotted. The X-axis shows chromosomal coordinates in kb. Centromeres are indicated as open circles.A representation of each chromosome with the signal log(PDF)Click here for additional data file.S12 FigA) Venn diagrams showing the overlap between genes with significant Rrm3 binding in the different ChIP-chip experiments. (B) Venn diagrams showing the overlap between genes with significant Yra1 and Rrm3 binding in different ChIP-chip experiments. (C) Rrm3 cluster distribution at ARSs, centromeres, introns, ncRNA, transponible elements, RNAPIII genes, snoRNA/snRNA and telomeres under wild-type (GAL::YRA1) and Overexpression (GAL::YRA1Δi) conditions.((PDF)Click here for additional data file.S1 TableGAL::YRA1Δi).Top genes whose expression levels are up-regulated and down-regulated in YRA1-overexpressing cells ((PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.


Here, we evaluated the role of an Ikaros binding site within its major lympho-myeloid promoter. We identified an Ikaros/Ets binding site within a promoter sub-region that was highly conserved in mouse and human. Deletion of this binding site increased the percentage of the reporter-expressing mouse lines, indicating that its loss provided a more permissive chromatin environment. However, once transcription was established, the lack of this site decreased transcriptional activity. These findings implicate a dual role for Ikaros/Ets1 binding on Ikzf1 expression that is exerted at least through its promoter.Ikaros DNA binding factor plays critical roles in lymphocyte development. Changes in Ikaros expression levels during lymphopoiesis are controlled by redundant but also unique regulatory elements of its locus that are critical for this developmental process. We have recently shown that Ikaros binds its own locus in thymocytes  A number of stage and lineage specific nuclear regulators govern proper development of blood and immune systems. The Ikaros family of Kruppel-type zinc (Zn)-finger DNA-binding proteins are critical regulators for lymphocyte differentiation and homeostasis –3. They During early hemo-lymphopoiesis, Ikaros is first expressed in the hematopoietic stem cell (HSC) at low levels and then up-regulated in the downstream lymphoid-primed multi-potent progenitor, LMPP ,13, a maIKZF1 locus that cause reduction of IKAROS activity are highly associated with development of acute lymphoblastic leukemias in humans  andhttp://www.rsat.eu).Putative transcription factor binding motif search was performed using TRANSFAC and RSAT programs (A cluster of five Ikaros binding motifs in the conserved sub-region 1 was deleted using Quick-change site-directed mutagenesis XL kit (Stratagene) from B-p-GFP construct. The priFlow cytometry was performed using fluorescent antibodies from BD Bioscences, Caltag or eBiosciences specific to the following surface antigens: B220 (RA3-6B2), CD4 (RM4-5), CD8α (53–6.7), TCRβ (H57-597), Mac-1 (M1/70), Gr-1 (RB6-8C5). Antibody-stained cells were analyzed using FACScan, FACS Calibur, FACSCanto flow cytometers (BD). Data analysis was performed using FlowJo software .http://www.physics.csbsju.edu/stats/contingency_NROW_NCOLUMN_form.html). Significance was determined if p< 0.05.The statistic significance for GFP-expression between the B-p-GFP lines and BΔIK-p-GFP lines was tested using chi-square analysis that was performed using software at  in un-translated exons 1a and 1b regions, a promoter element (p) just up-stream of the first translated exon 2, seven translated exons (2 to 8), and six lympho-myeloid specific enhancers , E, F, H, I) on the locus (Ikzf1 locus .,30.Ikzf1Additional analyses of these binding sites revealed that the Ikaros binding site in the promoter-B region  spanned the un-translated exon 1b and overlapped with one of the mouse-human conserved sub-regions  in the promoter-B region . In contin vivo.Cross-species conserved regions often contain regulatory elements. Thus, the Ikaros binding site in the promoter-B region overlapping with the conserved sub-region 1 was further examined for its role in auto-regulation Ikzf1 has shown that this promoter region is also enriched for an Ets1 binding in a B cell line    30]. Th. ThIkzf1p<10−3).The parental promoter-only construct B-p-GFP was highly susceptible to the transcriptionally restrictive chromatin environment and only three out of twenty-seven transgene-positive mice showed more than 1% of GFP expression in peripheral blood leukocytes (PBL) that contain B cells, T cells and myeloid cells as previously described . In contNonetheless, expression in PBL was variegated to an even greater level compared to the expressing founders generated by the parental reporter despite the greater number of expressing founders generated by the BΔIK-p-GFP, which was shown by a lower average GFP expression among expressing lines  of reporter expression, which is a measure for transcription rate, was evaluated for GFP-expressing founder lines. Two out of three parental B-p-GFP lines were available for this analysis with eighteen BΔIK-p-GFP lines . AlthougThe promoter B is active from the HSC and progenitors to B cells, myeloid cells, and pre-T cells; however, it does not support reporter expression past pre-T cell stages without the T cell specific enhancers-D or-H. Therefore, the parental B-p-GFP shows the expression profile; “high B/low T/intermediate myeloid” in PBL in all three lines ,30 Fig . These rIkzf1 expression past pre-T cell stages. This site is also likely to provide more stable reporter expression in B cells and myeloid lineages as seen in overall decrease in the percentage of GFP+ cells in each cell type of the BΔIK-p-GFP lines tested.In the six GFP-expressing BΔIK-p-GFP lines tested, four lines maintained the expression profile of the parental B-p-GFP reporter line “high B/low T/intermediate myeloid” and two lines showed GFP expression predominantly in B cells . This inIkzf1 provides a better understanding on molecular mechanisms that control proper expression of Ikzf1 during lymphocyte development. Here, we investigated the function of the Ikaros/Ets1 binding site in Ikzf1 promoter region using transgenic fluorescent reporter mice. We have provided evidence that the Ikaros/Ets1 binding site tested have a dual role in controlling reporter expression. Given Ikaros and Ets1 are both expressed in B lineages and T lineages from progenitor stages (http://www.immgen.org) [Ikzf1 expression at least through its promoter region. Elucidating Ikaros and Ets1 occupancies in different lymphoid cell types remain elusive to understand their stage specific roles.Changes in Ikaros expression correlate with its critical roles at various stages of lymphopoiesis. Characterizing cis-regulatory elements on gen.org) , currentIkaros/Ets1 on one hand may recruit factors promoting restrictive chromatin. Given the parental promoter-only B-p-GFP construct was highly susceptible to a repressive chromatin environment, it revealed de-repression of the GFP reporter upon the deletion of the Ikaros/Ets1 binding site resulting in a greater number of GFP-expressing lines. The parental transgene may be expressed only when the negative effect of Ikaros and/or Ets1 is overcome in a permissive chromatin environment.In contrast, Ikaros/Ets1 may recruit factors to positively regulate transcription once the locus becomes accessible. Since transcription is regulated in a stochastic manner at the single cell level , Ikaros/+ cells among all the mice, or when similarly expressed parental and mutant lines were compared. Therefore, probability of expression and transcription rate may be independently regulated, and the Ikaros/Ets1 binding in the promoter may not affect transcription rate.Due to the limited number of available GFP-expressing parental lines, it was not conclusive whether the lack of the site affected transcription rate of reporter expression. Nonetheless, there was no trend between the MFI and frequencies of the GFPIkzf1 expression in T-lineages requires additional positive regulation by enhancers-D or-H.The repressive effect of the Ikaros/Ets1 binding site is likely to be counteracted by activities of stage and cell type specific cis-elements and trans-factors. However, inactivation of the reporter in mature T cells was not due to the repressive effect; rather Ikzf1 regulation. Once Ikaros expression is established in lymphoid progenitors, Ikaros may play a positive role to further up-regulate its expression at lymphoid precursor stagesIn the HSC, Ikaros may play a negative role in order to maintain its expression low in this stage. In order to overcome the repressive or poised state and move into a downstream lymphoid pathway, additional factors such as E2A, a critical regulator for the proper differentiation of the LMPP , may be Ikzf1 expression during lymphocyte differentiation. This will aid manipulation of Ikaros expression levels in normal and malignant lymphoid lineages to facilitate lymphoid differentiation or suppress malignant transformation for future clinical applications.Further investigation on the roles of cis-elements and trans-factors including E2A, Ets1 and Ikaros will provide insights on transcriptional networks underlining


Escherichia coli sRNA RyhB. We not only validate a majority of known RyhB targets using the Ribo-seq approach, but also discover many novel ones. We further confirm regulation of a selection of known and novel targets using targeted reporter assays. By mutating nucleotides in the mRNA of a newly discovered target, we demonstrate direct regulation of this target by RyhB. Moreover, we show that Ribo-seq distinguishes between mRNAs regulated at the level of RNA stability and those regulated at the level of translation. Thus, Ribo-seq represents a powerful approach for genome-scale identification of sRNA targets.Bacteria express large numbers of non-coding, regulatory RNAs known as ‘small RNAs’ (sRNAs). sRNAs typically regulate expression of multiple target messenger RNAs (mRNAs) through base-pairing interactions. sRNA:mRNA base-pairing often results in altered mRNA stability and/or altered translation initiation. Computational identification of sRNA targets is challenging due to the requirement for only short regions of base-pairing that can accommodate mismatches. Experimental approaches have been applied to identify sRNA targets on a genomic scale, but these focus only on those targets regulated at the level of mRNA stability. Here, we utilize ribosome profiling (Ribo-seq) to experimentally identify regulatory targets of the  RNAs represent a major class of regulatory molecule in bacteria. ‘Small RNAs’ (sRNAs) are typically non-coding RNAs, 50–150 nt in length  (shiA and cirA (strated) ,7. The mstrated) ,7. Understrated) . The majand cirA ,10.Computational prediction of targets is an important problem for diverse classes of regulatory RNAs, and has been most extensively applied to metazoan microRNAs . For bacin vivo  products were electroporated into AMD054 containing pKD46, to replace ryhB with thyA, yielding JXW026. The pair of oligonucleotides JW5707 and JW5708 contained the ryhB mutation for strain JXW029. The pair of oligonucleotides JW5367 and JW5368 contained the ryhB mutation for strain JXW028. Each of these pairs, together with JW4986 and JW4887 were used to amplify PCR products containing ryhB mutations and flanking sequences, using a colony of MG1655 as template, with SOEing PCR . The rne131 allele has been described previously (ryhB (ΔryhB::cat) and araB (ΔaraB::kan) deletions was described previously -encoding helper plasmid pCP20, as described  or fumB (−77 to +24) was amplified using JW5066 and JW5116 (ynfF) or JW5079 and JW5119 (fumB). The two PCR products were fused using SOEing . To construct pJXW034–42, the entire 5′ UTR of each gene (as indicated in Supplementary Table S1) was amplified using the oligonucleotides listed in Supplementary Table S2, fused to a constitutive promoter, and cloned between the SphI and HindIII restriction sites of pAMD-BA-lacZ, using the In-Fusion kit (Clontech).All eviously  using thSphI and NheI sites of pAMD033   , using tfepB translational fusion pJXW043 was constructed using PCR products made with oligonucleotides JW5084 and JW5712, JW5085 and JW5711, with a colony of MG1655 as template, using SOEing PCR . The mutated cirA translational fusion pJXW042 was constructed similarly, using oligonucleotides JW5102, JW5382, JW5103 and JW5381.The mutated Eing PCR . The resE.coli culture, and grown at 37°C to an OD600 of ≈0.5. Arabinose was added to 0.1%, 10 min before harvesting the cells, to induce the transcription of RyhB. Two minutes prior to harvesting, chloramphenicol was added to a final concentration of 100 μg/ml. Cells were harvested by rapid filtration by using a 500 ml 0.45 μm PES filter system (Celltreat). Cells were flash frozen in liquid nitrogen together with 0.65 ml lysis buffer  as described previously .600 of 0.3–0.6. β-galactosidase assays were performed as previously described (− (MG1655 ΔlacZ ΔryhB) sample was assigned a value of 100. All other samples were normalized relative to this value. All assay values are the mean of three independent experiments.Overnight cultures were inoculated in 3 ml M9 medium with 0.4% fructose and 30 μg/ml chloramphenicol, and grown to an ODescribed . Three iOur new methodology for prediction of sRNA binding sites on a target mRNA is described by the following series of computations:in vivo in dynamic equilibrium among a population of structures, we used the Sfold program  of RNA:RNA interaction, we specifically focused on regions of the sRNA that are predicted to be single-stranded with high probabilities . For eactructure . Since hGT-disruption is the target disruption energy, which represents the free energy cost to unpair the target's intramolecular base pairs at the site of hybridization. To calculate ΔGT_disruption, we adopted the simplifying assumption that sRNA binding results in a local structural alteration at the site of hybridization, but not longer-range effects on overall target secondary structure. Here, we defined local structural alteration as the breakage of only those target intramolecular base pairs that are required to permit formation of the sRNA:target duplex predicted by the RNAhybrid program. Specifically, ΔGT_disruption was calculated as the energy difference between ΔGT_before, the free energy of the original target mRNA structure, and ΔGT_after, the free energy of the new locally altered structure (ΔGT_disruption = ΔGT_before− ΔGT_after). We calculated ΔGT_before by the average energy of the original 1000 structures predicted by Sfold, and ΔGT_after by the average energy of all of the 1000 locally altered structures.Given a region with hybrid conformation predicted by RNAhybrid, we further performed structure-based computation for several energetic parameters to model the hybridization process. ΔGS-disruption is the disruption energy for the sRNA, which represents the free energy cost to unpair the RNA's intramolecular base pairs at the site of hybridization. Using 1000 structures predicted by Sfold for the sRNA, ΔGS-disruption was computed by the same approach described above for computing ΔGT_disruption. Using 1000 structures predicted by Sfold for the sRNA, ΔGhybrid is the free energy gain from the hybridization, i.e. the stability of the complete hybrid as computed by the RNAhybrid program. The total energy change of the hybridization is ΔGtotal = ΔGinitiation + ΔGhybrid − (ΔGT-disruption + ΔGS-disruption), where the initiation energy ΔGinitiation = 4.1 kcal/mol , and one negative control  and a ryhB gene deletion derivative of MG1655 ΔlacZ (RyhB−). Since in E. coli, RyhB is expressed in iron-limiting conditions  were expressed at a substantially lower level in the RyhB+ strain than in the RyhB− strain  were expressed at a significantly higher level in the RyhB+ strain than in the RyhB− strain . Surprisingly, one of the fusions for a putative RyhB-activated gene, ugpB, showed significantly lower expression in the RyhB+ strain than in the RyhB− strain . Only one of these fusions, eptB-lacZ, showed significantly higher expression in the RyhB+ strain than in the RyhB− strain , suggesting there are few false negatives in the set of RyhB-activated genes identified by Ribo-seq using a cut-off of two-fold.We next analyzed expression of translational n Figure . Among tn Figure , suggestlacZ fusion constructs described above include the corresponding promoter for the putative RyhB-regulated gene. Hence, it is possible that effects of RyhB on expression of the lacZ fusions could be due to altered levels of transcription initiation. To rule out this possibility, we selected eight of the RyhB-regulated genes and constructed reporter plasmids in which a constitutive promoter . All of these fusions were expressed at a substantially lower or higher level in the RyhB+ strain than in the RyhB− strain , consistent with the activity of longer reporter fusions . As for all other putative RyhB-repressed genes tested, expression of fumB-lacZ and ynfF-lacZ was substantially lower in the RyhB+ strain than in the RyhB− strain .The promoter  was fuse operons ,56, cons operons  to the rkatG-lacZ by RyhB  were predicted from Ribo-seq data to be regulated predominantly at the level of translation. The fourth (dhaK) was predicted to be regulated predominantly at the level of mRNA stability. We compared expression of lacZ for each fusion in RyhB+ and RyhB− strains. Consistent with the Ribo-seq data, expression of the dhaK transcriptional lacZ fusion was significantly repressed by RyhB, whereas repression of the fepB fusion by RyhB was significantly lower than for the translational fusion . To determine whether this is a genuine site of RyhB base-pairing, we introduced a mutation in the fepB mRNA that is predicted to disrupt fepB-RyhB pairing  alone or in combination . However, combining mutant RyhB and mutant fepB-lacZ resulted in β-galactosidase activity similar to that of fully wild-type cells , consistent with an earlier report . TransiB Figure ,52, but are high .We identified a substantially higher ratio of false positives for genes that were predicted by Ribo-seq to be activated by RyhB. We believe this bias simply reflects the fact that most RyhB-regulated genes are repressed Table . In contThe major theoretical advantage of Ribo-seq over other transcription profiling is the ability to identify regulation at the level of translation. We identified many putative translational targets of RyhB, including examples of both positive and negative regulation Figure . We succdmsA, ynfF, nagT, and fumB, also encode proteins that contain iron-sulfur clusters or are part of a complex that contains iron-sulfur clusters (nrfA and katG, encode heme-binding proteins (dhaK and dhaM, which both encode subunits of dihydroxyacetone kinase.The primary function of RyhB is in the iron-sparing response: RyhB represses expression of non-essential genes that encode iron-associated proteins. Of the 27 novel RyhB-repressed genes we identified using Ribo-seq, 13 are known to encode iron-bound proteins. In particular, genes encoding every subunit of the iron-sulfur cluster-containing NapABCGH periplasmic nitrate reductase were observed to be down-regulated by RyhB, largely at the level of mRNA stability (Table clusters –67. Two proteins ,68. ThusyncE, has a well-established association with iron utilization, although cpdA function has been tentatively linked to iron (yncE is repressed by Fur, the iron-sensing transcription factor (fepB, which encodes a ferric enterobactin transporter, is repressed by both Fur and RyhB. Hence, the impact of iron starvation on iron uptake by ferric enterobactin is unclear, since fepB would be simultaneously relieved of Fur repression and repressed by RyhB.Only one RyhB-activated gene,  to iron . yncE isn factor , and hasn factor ,70. ThusfepB by RyhB is due to base-pairing around the S-D sequence and start codon, similar to regulation of other RyhB target genes (katG occurs through a novel regulatory mechanism. katG is repressed by RyhB (Figure katG ORF, downstream of the eighth codon (Figure katG coding sequence. There are described examples of sRNAs that regulate by base-pairing with mRNA coding sequence, far from the translational start (katG is translationally repressed by RyhB (Table katG through a novel mechanism that involves base-pairing with the katG coding sequence and alteration of long-range intramolecular base-pairing in target RNA secondary structure.In addition to identifying physiological functions of RyhB, our data also provide insight into mechanisms of RyhB-mediated regulation. For example, our data indicate that translational repression of et genes ,71. In cB Figure , but maxn Figure . This sual start ,72,73. HsRNA target recognition is known to be associated with low sRNA and mRNA secondary structure ,13, the Importantly, use of data from comprehensive experimental approaches such as Ribo-seq still requires downstream computational analysis and prediction. Specifically, Ribo-Seq can identify the target mRNAs but not the precise site of sRNA:target hybridization. Hence, sRNA target prediction algorithms could be combined with Ribo-seq data sets. This will greatly facilitate target site prediction, since the predictions will be focused on one mRNA rather than the whole transcriptome.Our work highlights the value of Ribo-seq for identifying sRNA targets, especially for genes regulated at the level of translation. Ribo-seq can be easily adaptable to the studies of other sRNAs, including those in other bacteria species, making comprehensive, genome-scale investigation of sRNA targets experimentally accessible. Ribo-seq analysis of sRNA targets promises to be valuable for refining the ‘rules’ of sRNA target recognition.


The transition of RNA polymerase II (Pol II) from transcription initiation into productive elongation in eukaryotic cells is regulated by the P-TEFb kinase, which phosphorylates the C-terminal domain of paused Pol II at promoter-proximal regions. Our recent study found that P-TEFb (in an inhibited state bound to the 7SK snRNP complex) interacts with the KAP1/TRIM28 transcriptional regulator, and that KAP1 and the 7SK snRNP co-occupy most gene promoters containing paused Pol II. Here we provide a detailed experimental description and analysis of the ChIP-seq datasets that have been deposited into Gene Expression Omnibus (GEO): GS72622, so that independent groups can replicate and expand upon these findings. We propose these datasets would provide valuable information for researchers studying mechanisms of transcriptional regulation including Pol II pausing and pause release. Excess trypsin/PBS was aspirated and the cell pellet was resuspended to a density of 1 × 107 cells/mL in PBS. Methanol-free formaldehyde (16% stock) was added dropwise to a 0.5% final concentration and gently nutated at room temperature for 10 min. To ensure that no cell clumps formed, the cell suspension was pipetted up and down throughout several times during the crosslinking step. Crosslinking was quenched through the dropwise addition of glycine to a final concentration of 0.125 M and gently nutated at room temperature for 10 min. The crosslinked cell suspension was then spun down at 800 g at 4 °C for 5 min. The cell pellet was washed twice (spun down at 1000 g at 4 °C for 5 min) in cold PBS to eliminate excess formaldehyde and glycine.Low passage (< 5) HCT116 cells were grown in T150 cm7 cells/mL and dounce homogenized (10 strokes) in a 1 mL dounce homogenizer using a loose pestle (Wheaton). The cell suspension was then nutated at 4 °C for 30 min and spun down at 1000 g at 4 °C for 10 min. These combined steps are to separate cytosolic components from the nucleus. The supernatant (cytosol) was discarded and the pellet (nuclei) was resuspended in cold Szak's RIPA buffer  to a final density of 2.5 × 107 cells/mL and dounce homogenized (10 strokes) in a 1 mL dounce homogenizer using a tight pestle (Wheaton). The nuclear lysate was then transferred to thin-walled 1.5 mL TPX tubes (Diagenode) for a final volume of 250 μL per tube . Samples were then sonicated until DNA was fragmented to an average distribution of about 200–300 bp using a water bath Bioruptor (Diagenode) for a total of 45 cycles (30 s on and 30 s off). To further ensure sonication efficiency, we allowed a 20 min cool-down of the water bath after every 20 cycles. To verify that DNA was fragmented to the appropriate size (200–300 bp average distribution), a fraction of lysate was reverse crosslinked, the DNA was purified and run on a 1.5% agarose gel stained with ethidium bromide alongside a 100 bp ladder at 5 V/cm.The cell pellet was then resuspended in cold Farnham lysis buffer  (PIPES) pH 8.0, 85 mM KCl, 1 mM PMSF, 1 × EDTA-free protease inhibitor, 0.5% NP-40) to a final cell density of 1 × 102.37 cell nuclei for Pol II, H3K4me3, H3K4me1, and H3K27ac; and 5.0 × 107 cell nuclei for KAP1, Cdk9, Hexim1, and Larp7. Unbound nuclear lysate was discarded and beads were washed twice with the following cold buffers:1.RIPA buffer (see above),2.Low salt buffer ,3.High salt buffer ,4.LiCl buffer ,5.1 × Tris–HCl EDTA buffer (TE).Dynabeads Protein G  (70 μL of slurry per ChIP) were equilibrated with RIPA buffer. 4 μg of each antibody diluted in 500 μL of RIPA  at 65 °C for 30 min, with intermittent vortexing. Protein-DNA complexes were decrosslinked using decrosslinking buffer  at 60 °C for 4 h. DNA was then purified using the Zymo ChIP DNA Clean and Concentrator Kit (Zymo Research).After washing, complexes were eluted off the beads using elution buffer (1% SDS and 100 mM NaHCO2.4NFKBIA promoter (a Pol II paused gene) prior to library preparation and sequencing. The non-Pol II paused gene GREB1 was used as a negative control NFKBIA promoter-proximal region (but not at the GREB1 negative control gene), we submitted our samples for high-throughput sequencing.All ChIP DNA samples were quantified for concentration using the Qubit® 2.0 Fluorometer (Thermo Fisher Scientific). A small fraction of input and ChIP DNA was used to test for enrichment at the 2.57 total reads of 50 nt, depending on the sample. For each sample, ~ 70–80% of unique reads mapped to the human genome (GRCh37/hg19).10–20 ng DNA (Input or ChIP from Point 2.3) were submitted to the McDermott Center Sequencing Core at UT Southwestern Medical Center for library preparation and high-throughput sequencing using the NextSeq500 (Illumina). Samples were end repaired, 3′-end adenylated and barcoded with multiplex adapters (Applied Biosystems). After purification with Ampure XP beads (Beckman Coulter), samples were PCR amplified for 15 cycles, size selected with Ampure XP beads, and quantified on the Agilent 2100 BioAnalyzer. Emulsion PCR was then performed and beads enriched on the EZ-Bead system. Each sample yielded 2.5–5.0 × 1033.1All scripting was performed using Python 2.7.6. All ChIP-seq binding events were loaded into a custom MySQL database to allow for efficient comparisons of multiple factors' binding loci. Fastq files obtained from the sequencing core were first checked for quality using Fastqc, and then trimmed of any adapters, barcodes, and low-quality sequences using the Fastx toolkit . For map3.2B and –SPMR flags set to generate signal pileup tracks in bedGraph format on a per million reads basis. This allows for direct comparison between individual tracks, regardless of any differences in the sequencing depth. The bedgraph files were converted to BigWig files using a custom script based on the University of California at Santa Cruz (UCSC) tool ‘bedGraphToBigWig’. The pileup tracks (.BigWig files) were visualized using Integrative Genomics Viewer (IGV) MACS2 was run in the callpeak mode with the –3.3hist flag was set with a parameter of 50 bp bins and the –ghist flag was also set to generate a density matrix. After density matrixes were generated they were fed into Cluster 3.0 to generate a .cdt file. A custom script was then used to rank the resulting .cdt file in order of decreasing density. We took the Pol II matrix and sorted it by decreasing total density and then clustered all other ChIP-seq matrices to the same sort order as Pol II. The resulting .cdt matrices were then fed into Java TreeView 3.0 HOMER 3.4hist flag was set using 50 bp bins for all metagene profiles. Plots were centered on the TSS and extending the indicated window (e.g. ± 1 kb (− size 2000)).HOMER 3.5ftp://ftp.sra.ebi.ac.uk/vol1/fastq/) and then aligned using Bowtie v1.1.2 allowing for up to two mismatches (− n 2) resulting in a sam output file (− S). Sam files were then converted into sorted bam using Samtools v1.3 and further converted into strand specific genome coverages using bedtools (genomeCoverageBed). Entire documented analysis and parameters can be found on our Github .We analyzed the nascent RNA-sequencing data (GRO-seq) generated by the Espinosa laboratory in the HCT116 cell line 3.6Larp7 (constitutively bound to the 3′ of 7SK RNA), Hexim1 (7SK RNA-binding protein that tethers P-TEFb to the 7SK snRNP), and Cdk9 (the kinase subunit of P-TEFb) To characterize the genome-wide distribution of the 7SK snRNP, we employed an unbiased ChIP-seq approach to localize the individual components: To identify KAP1 and 7SK snRNP target genes we searched for KAP1, Hexim1, Larp7, and Cdk9 narrow peaks (as defined by MACS) at promoter-proximal regions of genes listed in the UCSC RefSeq database . For the occupancy analysis, we defined a broader promoter-proximal region window than others have used (− 250 to + 1000 bp from the TSS). These thresholds were selected because we found 13,048 genes having a Pol II summit using a narrow window (− 250 to + 250 bp from the TSS) and 4268 additional genes containing a Pol II summit, in addition to an H3K4me3 peak, at + 250 to + 1000 bp from the TSS A. It is KAP1-7SK snRNP early Elongation Complex), we first searched for Pol II summit locations in the broad promoter-proximal region (− 250 to + 1000 bp from TSS) and analyzed for co-occupancy of all KAP1-7SK snRNP components within a window of − 250 to + 250 bp from the Pol II summit (narrow peak as determined by MACS)  B. This fby MACS) B and C. by MACS) C.3.7− 16 (machine zero), as calculated using a hypergeometric density distribution. In addition, we found paused Pol II at the promoter-proximal region of genes (n = 551) devoid of KAP1-7SK snRNP, indicating significant de-enrichment of genes having paused Pol II but no (or very low levels) KAP1-7SK snRNP at these sites . Together, this indicates that Pol II and the KAP1-7SK snRNP significantly co-localize at promoter-proximal regions.We found that the majority of KAP1 and components of the 7SK snRNP complex mapped to promoter and promoter-proximal regions of most genes containing paused Pol II 3.8Drosophila) used in the experimental approaches, number of genes being averaged depending on the species analyzed, and/or mean signal densities. Higher resolution approaches like GRO-seq Given the high frequency of Pol II and KAP1-7SK snRNP co-occupancy at promoter-proximal regions, we generated metagene plots to define their average relative proximity to the TSS. The Pol II metagene reveals that the average pause site occurs at about + 100 bp from the TSS A and B, Interestingly, the metagene profiles for components of the KAP1-7SK snRNP complex peaked downstream of the Pol II pause site, mirroring the active chromatin signatures H3K4me3 and H3K27Ac C, indica3.9To define the relationship between Pol II pausing, KAP1-7SK snRNP deposition at promoter-proximal regions and transcriptional levels, we re-analyzed the nascent RNA-sequencing data (GRO-seq) generated by the Espinosa laboratory 4We described here an experimental approach to determine the occupancy of KAP1, the 7SK snRNP and Pol II in the human genome. Using this collection of ChIP-seq datasets we demonstrated that the transcriptional regulator KAP1 and the 7SK snRNP complex co-occupy (with high frequency) promoter-proximal regions containing paused Pol II. We propose that this collection will provide valuable information for researchers studying mechanisms of transcriptional regulation, particularly Pol II pausing and pause release. Certainly, future experimental and computational approaches are needed to further define if KAP1 recruits the 7SK snRNP to most promoter-proximal regions containing paused Pol II and whether the KAP1-7SK snRNP complex regulates pause release genome-wide. Our main work has closely examined annotated transcripts but not divergent transcripts or non-coding RNAs. Thus, it remains to be elucidated whether these unique non-coding RNA species are also targeted by KAP1 and the 7SK snRNP or whether they have unique regulatory strategies. Moreover, given that enhancers play an important role in controlling gene activation from promoters and because the 7SK snRNP appears to be recruited to these genomic sites The authors declare that there are no conflicts of interests.


Manuscript provides insights into the biology of long-lived plants, different from Arabidopsis, tomato or grass species that are widely studied. In the European larch the diplotene stage lasts approximately 5 months and it is possible to divide it into several substages and to observe each of them in details. The diplotene stage is a period of intensive microsporocyte growth associated with the synthesis and accumulation of different RNA and proteins. Larch microsporocytes display changes in chromatin morphology during this stage, alternating between 4 short stages of chromatin condensation (contraction) and 5 longer diffusion (relaxation) stages. The occurrence of a diplotene diffusion stage has been observed in many plant species. Interestingly, they have also been observed during spermiogenesis and oogenesis in animals. The aim of this study was to examine whether chromatin relaxation during the diplotene is accompanied by the synthesis and maturation of mRNA. The results reveal a correlation between the diffusion and chromatin decondensation, transcriptional activity. We also found decreasing amount of poly(A) mRNA synthesis in the consecutive diffusion stages. During the early diffusion stages, mRNA is intensively synthesized. In the nuclei large amounts of RNA polymerase II, and high levels of snRNPs were observed. In the late diffusion stages, the synthesized mRNA is not directly subjected to translation but it is stored in the nucleus, and later transported to the cytoplasm and translated. In the last diffusion stage, the level of poly(A) RNA is low, but that of splicing factors is still high. It appears that the mRNA synthesized in early stages is used during the diplotene stage and is not transmitted to dyad and tetrads. In contrast, splicing factors accumulate and are most likely transmitted to the dyad and tetrads, where they are used after the resumption of intense transcription. Similar meiotic process were observed during oogenesis in animals. This indicates the existence of an evolutionarily conserved mechanism of chromatin-based regulation of gene expression during meiotic prophase I. L. leptolepis microsporocytes have shown that chromosomes undergo several gradual and major organisational changes during the diplotene stage [Meiosis is an important step in sexual reproduction. It is a specialised cell division that generates four haploid cells from a diploid parent cell after a single round of DNA replication and two consecutive rounds of nuclear division. In the first nuclear division, homologous chromosomes segregate, and in the second division, sister chromatids segregate. Accurate chromosome segregation during meiosis is essential for haploid gamete formation . The mosne stage . Interesne stage –19.According to the proposed model , chromosLarix decidua Mill. anthers were collected from the same tree in successive meiotic prophase stages of the diplotene stage from November until March at weekly intervals. Anthers were fixed in 4% paraformaldehyde in phosphate-buffered saline (PBS), pH 7.2, for 12 h and squashed to obtain free meiocytes. Meiotic protoplasts were isolated from these cells [in situ hybridization (FISH).The study was carried out in the botanical garden of our home Faculty Biology and Environmental Protection of Nicolaus Copernicus University, no specific additional permissions were required. To maintain consistent experimental conditions, se cells  and wereFor transmission electron microscopy analyses, cells were fixed in 4% paraformaldehyde and 0.25% GA in Pipes buffer overnight at room temperature, dehydrated in alcohol and embedded in LR Gold resin . The resultant material was sectioned using a Leica Ultracut UCT Ultramicrotome, and the sections were placed on nickel-formvar-coated grids.in situ hybridization methods because when in situ hybridization was applied first, the subsequent levels of immunofluorescence signals were very weak. In the double immunofluorescence labeling experiments with bromouridine and polymerase II RNA labeling, BrU labeling always preceded RNA pol II labeling because the secondary anti-mouse IgM antibody used to detect the anti-RNA pol II primary antibody can react with both the IgM and IgG primary antibodies, whereas the anti-mouse IgG antibody does not react with the primary IgM antibody and only binds the primary IgG antibody.Several double-labeling immunofluorescence-FISH reactions (bromouridine (BrU): poly(A) RNA; m3G snRNA: U2 snRNA) and double immunofluorescent labeling (bromouridine (BrU): RNA polymerase II) were performed as described below. In the double-labeling immunofluorescence-FISH reactions, the immunocytochemical methods always preceded the Immunodetection of bromouridine incorporation prior to FISH or immunofluorescence staining in double-labeling reactions. Bromouridine incorporation was accomplished according to the method , with a For the hybridization assays, the probes were resuspended in hybridization buffer  at a concentration of 50 pmol/ml, and hybridization was performed overnight at 37°C. The following antisense DNA oligonucleotides were used in the reactions of the detection of poly (A) RNA and U2 snRNA: poly(A) RNA—5′ Alexa 594 T(T)29 3′, U2 snRNA—5′ Alexa 594 ATATTAAACTGATAAGAA CAGATACTACACTTG 3′ , ITS1a—5′ Cy3 TCTTGCAAATCAACAGCCAC 3′, ITS1b—5′ Cy3 ATTATAGCAAGAGCATAACAAGCACAC 3′. The following sense DNA oligonucleotides were used in the control reactions: 5′ Alexa 594 A(A)29 3′, 5′ Alexa 594 CAAGTGTAGTATCTGTTCTTATCAGTTTAATAT 3′, 5′ Cy3 GTCGTGTT GATTTGCAAGA 3′, 5′ Cy3 GTGTGCTTGTTATGCTCTTGCTATAAT 3′ .Immunofluorescence methods for double-labeling reactions. Assays involving the m3G cap–anti-m3G antibody  were performed as . RNA polAfter fixation in Carnoy’s solution , anthers were washed in 95% ethanol and incubated with 1 N HCl at 60°C for 10 minutes. Next, the anthers were washed with water and incubated in Schiff’s reagent for 1 h at room temperature in the dark, followed by rinsing in bisulfite solution  in 3 washes of 5 min each and thorough rinsing with water. Then, smears were prepared on 2.5% gelatin-coated slides and frozen on dry ice. The slides were finally dehydrated in a 70%, 96% and 100% alcohol series for 2 min each, followed by mounting with Euparal  under coverslips.For in situ detection of structures containing DNA at the ultrastructural level, immunolabeling with monoclonal mouse IgM anti-DNA antibodies  and anti-mouse IgM secondary antibodies with 10 and 20 nm gold particles  were used. Grids were then rinsed and contrasted (1% phosphotungstic acid and 2.5% uranyl acetate).in situ hybridization. Each reaction step was performed using consistent temperatures, incubation times and concentrations of probes and primary and secondary antibodies. A total of 35 cells from each stage were analyzed following 3 different preparations. Three-dimensional optical sections were acquired with a 0,5-μm step interval. For all antigens and developmental stages, the obtained data were corrected for background autofluorescence, as determined by negative control signal intensities. The Lucia General software , was used for image processing and analysis which is compatible with the images collected in the Nikon PCM 2000 confocal microscope and Nikon C1 confocal microscope as well as other microscopes manufactured by Nikon. The Kruskal–Wallis ANOVA test was applied to test for differences between multiple samples .Image analysis of the larch microsporocyte protoplasts was performed after immunofluorescence staining with antibodies against m3G snRNA and RNA Pol II and after For colocalization analysis before measurement we perform the proper controls, including specimens labeled with each probe alone as well as an unstained autofluorescence standard. At the beginning of the measurements we performed software correction of bleed-through before proceeding with colocalization analysis. We calculated the % of fluorescence intensity in the “newly formed RNA” channel covered by the colocalization area.The results were registered with Nikon C1, Nikon PCM 2000, Leica SP8 confocal microscopes using lasers emitting light at a wavelengths of 405, 488, 543, 561 and 594 nm. For Nikon confocal microscopes a 60X  Plan Apochromat DIC H oil immersion lens were used. Images were collected collected sequentially in the green (Alexa 488 fluorescence) and red (TRIC or Alexa 594) channels. To minimize bleed-through between fluorescence channels, we employed low laser power (3–10% of maximum power) and single-channel collection. For bleed-through analysis and control experiments, Lucia G software was used . For Leica confocal microscope an optimized pinhole, long exposure time (400 kHZ) and 60X  Plan Apochromat DIC H oil immersion lens were used. Images were collected sequentially in the blue (DAPI), in the green (Alexa 488 fluorescence) and red  channels. To minimize bleed-through between fluorescence channels, we employed low laser power (0.4–5% of maximum power) and single-channel collection. For bleed-through analysis and control experiments, Leica SP8 software was used.Control reactions. Control treatments consisting of incubations without the primary antibody were performed for the in situ hybridizations and immunofluorescence assays. For the in situ hybridization, high-resolution and fluorescence analyses, sense-labeled probes and ribonuclease-treated samples were used as additional controls. For the detection of new transcripts, a control reaction was performed in the protoplasts without incubation with bromouridine. All control reactions either produced negative results or results that were very weak compared with the standard reactions  and after paraformaldehyde or Carnoy’s fixation. Strong chromatin condensation during the pachytene stage was followed by chromatin diffusion at the beginning of the diplotene stage, but we also observed 4 transient stages in which chromatin was more compact (contraction stages) that alternated with 4longer diffuse stages, although of various lengths (The diplotene stage in European larch microsporocytes begins in November and continues until March. We collected flower buds weekly (22 harvests) and obtained protoplasts. We prepared the cells and stained the DNA to measure the cell and nuclei volume. Our analysis indicates that 70–95% of the cells collected from one harvest were similar in size and chromatin morphology. The characteristic changes in chromatin morphology and cell size were accompanied by changes in the localisation and amount of several factors. These data allowed us to distinguish between 14 stages in the diplotene stage. We observed similar changes in cell size and morphology of the chromatin  lengths –4 Figs.. lengths  and conf lengths , which o lengths .. Ultras lengths . In turn lengths  and DAPI lengths –4 Figs., lengths .in vivo studies (unpublished data). Therefore, our findings are representative of plasticity rather than an artefact of the procedures.During the 5-month-long diplotene stage, microsporocytes extensively grew, and their volume gradually increased. In the middle of the diplotene stage, the cells were 2-foldlarger, and by the end of diplotene, they were 3-fold larger than at the beginning of the diplotene stage. Cell growth was associated with nuclear volume increases . At the We examined whether the changes in cell and nuclear volume and in chromatin morphology were associated with changes in microsporocyte transcriptional activity. Using the BrU incorporation technique, we examined the distribution patterns and level of newly formed transcripts in diplotene larch microsporocytes. Long incubations of cells with BrU  allowed us to visualise newly formed transcripts at the site of synthesis and their transportation into the cytoplasm. The results revealed that there was a correlation between chromatin morphology and RNA synthesis. In cells in which chromatin was organised into fibres, labelling of the newly formed transcript was much higher, and we observed signal in the nucleus and cytoplasm . ParticuWe examined whether the high transcription level was associated with mRNA synthesis. Through double labelling of newly formed transcripts, we analysed RNA polymerase II distribution, which is responsible for the synthesis of protein-encoding transcripts and most splicing snRNAs, in periods of high and low transcriptional activity. During the periods of high transcriptional activity , RNA polWe also performed double labelling to examine the correlation between the distribution and levels of newly formed transcripts and poly-adenylated RNA (poly(A) RNA) . InteresWe analysed the percentage of newly formed transcripts that were poly(A) RNAs. We performed double labelling with FISH immunofluorescence and measured the colocalisation of new transcripts with poly(A) RNA in the nucleus . We obseWe also examined RNA polymerase II levels associated with elongation (elongation form—Pol II O) and initiation of transcription (Pol II A) . During These data indicate that mRNA is intensively synthesised, mainly during the early diplotene stages when RNA polymerase II levels are high. We investigated the level of uridine-rich small nuclear RNAs involved in splicing. Previous studies have shown that snRNPs undergo cyclic synthesis during early prophase . We analThe levels of mature snRNA and U2 snRNA underwent large fluctuations during the diplotene stage . SimilarIn contrast to mature snRNA, the level of U2 snRNA considerably increased in the second half of diplotene. We observed a biphasic increase in the U2 snRNA level: the first stage occurred at the beginning of the fourth diffusion stage, and the second and largest increase occurred at the end of the fourth diffusion stage. In the last diffusion stage, U2 snRNA decreased compared to that of the previous stage, although it remained high . During All control reactions produced negative results or very weak results compared to the standard reactions ..Prophase of the first meiotic division is a period of dynamic chromosome behaviour . After cLarix leptolepis has revealed profound changes in chromosome organisation, including four well documented diffuse substages: schisonema, pre-diffuse diplotene, mid-diffuse diplotene and post-diffuse diplotene [Research on chromatin morphology at this stage in iplotene . The preOur recent research has shown that the diplotene stage is the most transcriptionally active stage of prophase I. However, the level of newly formed transcripts during this long diplotene stage, which lasts approximately 5 months, fluctuates. We identified 5 periods of intense transcription separated by short periods of transcriptional silence. The periods of intense transcription in larch microsporocytes positively correlated with periods of chromatin decondensation, whereas during the chromatin contraction stages, transcription levels decreased. During insect spermatogenesis, the diffuse stage is associated with an intense and long period of cellular growth and important transcriptional activity ,30. FurtOur research revealed that the highest level of newly formed transcripts occurred during the 4th diffuse stage. At this stage, the chromatin consists of numerous fibres. Such chromatin organisation resembles the lampbrush chromosome (LBC). LBCs are found in the oocyte germinal vesicle of many vertebrate and invertebrate animals . ImmenseLarch microsporocyte growth likely requires extensive protein synthesis. We determined the level of mRNA synthesis by analysing the levels of poly(A) RNA, RNA polymerase II (which is responsible for poly(A) RNA synthesis; ,35) and These results were confirmed by the high content of hyperphosphorylated RNA polymerase II, which is responsible for pre-mRNA elongation, and the high level of snRNAs that are involved in transcript maturation. During the third period, a particularly high level of ribosomal RNA synthesis occurs in the nucleolus, which corresponds to an increase in cytoplasmic rRNA contents ,28, reflH. orientalis microspores and Brassica napus [Danio rerio embryos, in which snRNAs are present in CBs at the 4-cell stage, which occurs 1 hour after fertilisation, and before zygotic genome activation at the 512-cell stage, which occurs approximately 2.75 hours after fertilisation [Interestingly, despite the low levels of newly formed mRNAs, snRNAs were maintained at high levels, particularly during the mid- and late diplotene stages. Larch microsporocytes likely accumulate and store snRNAs during late diplotene that will later be transmitted to the dyad cells during cell division  . The larca napus –48. The lisation .The accumulation of snRNAs in diplotene microsporocytes may also be related to the maturation of these molecules. snRNP complex biogenesis (except for U6 snRNPs) is a complex process involving a specific sequence of events in the nucleus and cytoplasm. Following RNA polymerase II transcription, the original U snRNA transcripts are transported to the cytoplasm where they bind to Sm proteins, and the 5′-cap undergoes hypermethylation ,50–52.snBy comparing changes in mature snRNA (m3G snRNAs with a hypermethylated 5′-cap structure) and U2 snRNA levels, considered here as total snRNAs, we found that their levels are quite different from each other. Total mature snRNA transcripts were maintained at a relatively constant level in the second half of diplotene, but total U2 snRNAs gradually increased. There was also a clear difference in their distribution. At the end of the diplotene stage, mature snRNA transcripts primarily localised to the cytoplasmin globular clusters. Similar structures known as cytoplasmic bodies are rich in snRNPs, and they have been observed in larch microsporocytes during premeiotic interphase and early prophase .Xenopus oocytes have suggested that CBs also function as “supervisors” that control the correct assembly of a complex that exports snRNA to the cytoplasm and is composed of the CRM1 export receptor, CBC cap-binding complex and PHAX adapter [These structures most likely serve as a platform for snRNP complex assembly. The portion of U2 snRNA that did not colocalise with m3G snRNA primarily localised to the nucleoplasm, particularly in the large and numerous CBs present during this period. This lack of colocalisation suggests that the U2 snRNAs are in their immature form. The accumulation of immature U2 snRNAs in larch microsporocyte CBs may be associated with early snRNP biogenesis. Smith and Lawrence  previous adapter . DiploteOur research shows that the diplotene stage in plants is a highly metabolically active stage. Our results contradict the view that the diffusion stage in larch cells is a resting period caused by low temperatures –4. DurinS1 Fig1—Chromatin in the form of small irregular patches, consisting of low density material; dense chromatin present in only a few small spots. 2—Irregular patches of very dense chromatin; low-density chromatin was present only on the edge of patches. 3—Large patches of closely packed chromatin; dense chromatin was primarily localised in the centre of each patch, and the less dense portion localised to the patch periphery. 4—Large, elongated patches of chromatin surrounded by spaces of low chromatin content; dense chromatin primarily localised to the centre of each patch, and low-density chromatin localised to the edge of patches and penetrated into the free spaces in a fibrous form.(TIF)Click here for additional data file.S2 Fig5–2nd contraction stage—small compact patches of dense chromatin are separated by large spaces of low chromatin content; small amounts of less dense chromatin are visible on the edge of the patches. 6–3rd diffuse stage—large, elongated patches primarily consisting of low-density chromatin. 7–3rd contraction stage—irregular, compact chromatin patches primarily consisting of dense chromatin.(TIF)Click here for additional data file.S3 Fig8—During the first step of the 4th diffuse stage, chromatin was visible in the form of small, regular, closely spaced patches, composed primarily of low-density fibrils. 9—At the second step of the 4th diffuse stage, much larger chromatin patches were observed, composed of delicate fibrils. 10–During the third step of the 4th diffuse stage, chromatin was present in the form of large, regular patches separated by regions with low chromatin content. Within patches, dense chromatin localised to the centre of the patch and was surrounded by delicate chromatin fibrils. 11—A fourth step of the 4th diffuse stage—chromatin is present in the form of large, elongated patches.(TIF)Click here for additional data file.S4 Fig12–4th contraction stage—chromatin arranged in numerous, small, dense patches.13—a first step of the 5th diffuse stage—chromatin in the form of large, elongated, closely spaced patches consisting primarily of low-density chromatin. 14—a second step of the 5th diffuse stage—chromatin arranged in the form of large, irregular patches separated by spaces with low chromatin content. Within patches, dense chromatin localised to the centre of the patch surrounded by delicate chromatin fibres.(TIF)Click here for additional data file.S5 FigA—protoplasts without BrU incubation and treated with anti-BrU primary antibody and secondary antibody; B—hybridisation with sense oligo d(A) probe, C—merge. Control reaction of double labelling of newly formed transcripts and pol II RNA. D—protoplasts without BrU incubation and treated with anti-BrU primary antibody and secondary antibody; E—immunolocalisation reaction in the absence of pol II RNA-specific primary antibody (H5); F—merge. Control reaction of the double labelling reaction of m3G snRNA and U2 snRNA. G—immunolocalisation reaction in the absence of the m3G cap-specific primary antibody; H—hybridisation with the U2 snRNA sense probe; I—merge. Bars—10 μm.(TIF)Click here for additional data file.