With the rise of resistance to chemical acaricides, alternative methods in tick control are warranted. Gene manipulation has been successful in controlling mosquitoes and mosquito-borne diseases and is now looked upon as a candidate method to control ticks and tick-borne pathogens. Our previous study has identified the ferritin-derived promoter from the H. longicornis tick was characterized in silico, and the core promoter sequences and some of its important components were identified. Several truncations of the promoter region were created and inserted to a reporter plasmid to determine the important components for its activity. The activities of the truncated promoters on the Ixodes scapularis tick cell line (ISE6) were measured via a dual luciferase assay using experimental and control reporter genes. To induce the promoter’s activity, transfected ISE6 cells were exposed to ferrous sulfate. The 639 nucleotides truncated promoter showed the highest activity on ISE6 cells when exposed to 1 mM ferrous sulfate.Here, the In this study, we characterized an iron-inducible tick promoter that could be a valuable tool in the development of a gene-manipulation system to control ticks and tick-borne pathogens.The online version of this article (10.1186/s13071-019-3574-9) contains supplementary material, which is available to authorized users. Next to mosquitoes, ticks are considered to be the most important vectors of pathogens that cause human diseases . At presHaemaphysalis longicornis is a hard tick that can be found in East Asia and Australia and that has recently attracted much attention because of reports of infestation with this species in several states in the USA  nucleotide was the estimated TSS among the sequences  for the 2848 nucleotide (nt) whole promoter, HlFer1 (F1) for the 821 nt promoter, HlFer1 (F2) for the 638 nt promoter, HlFer1 (F3) for the 450 nt promoter, and HlFer1 (F4) for the 185 nt promoter  and IRP may have resulted in the depressed activity of the HlFer1 promoter. Therefore, different concentrations of ferrous sulfate were used in the media to liberate the IRP from the IRE for translation induction. A dose-dependent luciferase activity for the different truncated promoters up to 1 mM ferrous sulfate was observed. With 2 mM ferrous sulfate, decreased activity was observed at the HlFer1 (F1), HlFer1 (F2), and HlFer1 (F3) truncates  possessed the highest luciferase activity in all of the ferrous iron-enriched media, followed by the HlFer1 (F1) and HlFer1 (F3) truncates, except at a 2 mM ferrous sulfate concentration, wherein HlFer1 (F3) has a slightly higher activity than HlFer1 (F1). The HlFer1 (F0) and HlFer1 (F4) sequences exhibited the lowest relative luciferase activity, and their relative luciferase activity did not differ significantly  being the smallest truncated promoter and still exhibited activity could be the core promoter region, while the HlFer1 (F2) showed optimal promoter activity in the presence of 1 mM ferrous sulfate  = 540.83, P < 0.0001).Promoter-replacing expression vectors were constructed based on a pmirGLO plasmid vector with the phosphoglycerate kinase (PGK) promoter as the original promoter. The PGK promoter was replaced by truncated HlFer1 (F2) promoter activity under fluorescence microscopy to show the activity of this truncated promoter. The previously constructed pmirGLO-HlAct pro-Venus and pmirGLO-HlFer1(F2)-Venus, wherein the PGK promoter and luciferase gene were replaced by the HlFer1(F2) promoter and the Venus gene, respectively, in the pmirGLO plasmid were evaluated. The mentioned vectors were transfected to ISE6 cells, and then the cells were enriched with 1 mM ferrous sulfate. The fluorescence of Venus was observed under fluorescence microscopy at day 4 after ferrous sulfate enrichment. The fluorescence microscopy test showed that the addition of 1 mM ferrous sulfate resulted in the increased fluorescence intensity of pmirGLO-HlFer1(F2)-Venus transfected cells; however, the addition of 1 mM ferrous sulfate did not affect the intensity of pmirGLO-HlAct pro-Venus transfected cells. No apparent difference in intensity was observed between pmirGLO-HlAct pro-Venus and pmirGLO-HlFer1(F2)-Venus transfected ISE6 cells -Venus resulted in expression of the Venus protein in ISE6 cells  was utilized to evaluate the core promoter sequence of the different candidates in the HlFer1 promoter sequences since the activity of HlAct and HlFer1 promoter has already been established in this tick cell line [A dual reporter assay, such as the dual luciferase reporter assay, has been commonly used in cell lines to evaluate promoter activity , 28, 29.nis tick  as the pell line .HlFer1 promoter was tested for activity in our previous study, it showed depressed or no transcriptional activity [HlFer1 mRNA, which interacts with the IRP that hinders the protein translation. On a previous study, an increasing HlFer1 protein expression was observed during blood-feeding despite no difference in the expression of HlFer1 mRNA expression. It was then hypothesized that the increasing expression was due to the liberation of IRP from IRE due to the increased iron in the tick blood meal [Ixodes ticks [Haemaphysalis and Ixodes ticks, as well as Ixodes cells are all regulated by iron concentration. Therefore, ferrous sulfate enrichment on HlFer1 promoter transfected ISE6 cells was utilized to determine whether it would result in luciferase activity due to liberation of the IRP and eventually, protein translation. A dose-dependent increase in activity was observed to peak in 1 mM ferrous sulfate-enriched media. The lower luciferase activity with 2 mM ferrous sulfate could be attributed to the possible increased cell mortality at the increased ferrous concentration, as was observed in our previous study [HlFer1 (F2) promoter showed the highest activity, followed by HlFer1 (F1), HlFer1 (F3), HlFer1 (F4), and HlFer1 (F0), with HlFer1 (F4) and HlFer1 (F0) not differing significantly, thus strengthening our hypothesis that the HlFer1 (F4) promoter is the core promoter region. Since we consider this region to be the core promoter region, its activity could also be considered the basal activity of the promoter region [HlFer1 (F3) and HlFer1 (F2) promoter regions could indicate that these extended regions contain the enhancers or positive regulatory elements. The decrease in the activity of the HlFer1 (F1) and especially the HlFer1 (F0) region could indicate that these regions contain the silencers or negative regulatory elements. This is consistent with human cell lines, in which the − 350 to − 40 nt region showed enhanced transcriptional activity, while the region further upstream, especially -500 to -1000 nt, showed a decline in transcriptional activity [Rhipicephalus microplus showed a 17-fold higher promoter activity when compared with the 1191 nt originally cloned promoter. Meanwhile, a three-fold increase was observed when the − 1005 to − 495 sequences were deleted from the EF1-α promoter of the same tick species, indicating the presence of repressive elements in the upstream sequences of the promoters [Although the activity . This coood meal . The sames ticks . In our es ticks . It coulus study . With 1 r region . The incactivity . This isVenus gene-expression vectors (pmirGLO/HlAct-Venus and pmirGLO/HlFer1(F2)-Venus) were constructed. More intense Venus fluorescence within transfected cells of the ferrous sulfate-enriched ISE6 cells was detected in pmirGLO-HlFer1 (F2)-Venus transfected groups as compared to those without ferrous sulfate enrichment. Meanwhile, no difference in the ferrous sulfate-enrichment and non-enrichment was observed on pmirGLO-HlAct pro-Venus transfected cells. It would then be of interest to know if this Fer1 promoter sequence could also be found in I. scapularis and would exhibit same or higher activity. Nonetheless, we believed that the HlFer1 promoter sequence maintained its promoter activity. These results also demonstrate the iron inducibility of the activity of the ferritin derived promoter.To further confirm the activity of the gene-expression vectors in ISE6 cells, Trichomonas vaginalis [Precise spatial and temporal gene-expression and gene-modification control is necessary in the study of several gene functions. An inducible system of gene expression has been a valuable tool in the conduct of such study . The useaginalis , 34. Ticaginalis , 36. We Additional file 1: Table S1. Oligonucletiode primer sequences used for construction of the plasmids. Table S2. Relative luciferase activity of the different HlFer1 promoter truncates in ISE6 cells exposed to different concentrations of ferrous sulfate.


CD69 promoter, there are four conserved noncoding regions (CNS1-4) upstream of the CD69 promoter. Furthermore, we proposed that CNS2 is the main enhancer of CD69 transcription. In the present study, we mapped the transcription factor (TF) binding sites (TFBS) from ChIP-seq databases within CNS2. Through luciferase reporter assays, we defined a ~60 bp sequence that acts as the minimum enhancer core of mouse CNS2, which includes the Oct1 TFBS. This enhancer core establishes cooperative interactions with the 3′ and 5′ flanking regions, which contain RUNX1 BS. In agreement with the luciferase reporter data, the inhibition of RUNX1 and Oct1 TF expression by siRNA suggests that they synergistically enhance endogenous CD69 gene transcription. In summary, we describe an enhancer core containing RUNX1 and Oct1 BS that is important for the activity of the most potent CD69 gene transcription enhancer.The immune regulatory receptor CD69 is expressed upon activation in all types of leukocytes and is strongly regulated at the transcriptional level. We previously described that, in addition to the  CNS) with DNase I hypersensitivity. Cis-regulatory elements contain binding sites for trans-acting transcription factors (TFBSs) and serve as centers of epigenetic changes [In mammals, 95% of the genome is noncoding, and 40% of the noncoding region plays a role in transcription regulation . In comb changes ,3. TheseCD69 promoters are able to direct transcription in resting cells, as well as to increase CD69 transcription in stimulated cells [CD69 is a leukocyte activation marker that plays an important role in the regulation of immune responses ,6,7,8. Ced cells . This ined cells ,30,31.CD69 promoter, another five cis-regulatory regions: A non-conserved hypersensitivity site (HS) located within the first intron of the CD69 gene and four conserved noncoding regions (CNS1-4) upstream of the CD69 promoter [CNS2 and CNS4 had constitutive and inducible enhancer activity in reporter assays, with CNS2 being the region with the highest inducible enhancer capacity [CNS2 is the main enhancer of CD69 promoter transcription in vivo [CNS2 according to updated ChIP-seq data; and, based on their distribution, we divided them into five different regions. Then, we determined the enhancer activity of CNS2 and identified its location through luciferase reporter assays. With this approach, we found a minimum enhancer core of ~60 bp that includes an Oct1 (POU2F1) BS. This core functionally interacts with adjacent regions at the 5′ end, which contains RUNX1 BSs, and at the 3′ end, which contains SRF BSs, via a cooperative modular model that leads to CD69 promoter induced enhancement of transcription. Moreover, we assessed the roles of Oct1 and RUNX1 in the transcriptional regulation of the endogenous CD69 gene by siRNA. In agreement with the luciferase reporter data, the gene silencing results also indicate synergistic cooperation between these TFs to enhance CD69 transcription.We previously described the existence of, in addition to the promoter ,33. In mcapacity ,33. Furt in vivo  based onCNS2 is a potent enhancer of mouse CD69 promoter transcription and defines an enhancer core that acts together with flanking cis-interacting TFs through a cooperative modular model to increase CD69 promoter induced enhancement of transcription.In summary, our work strengths support indicating that CNS2.Data-mining, identification and mapping of conserved TFBSs within  The CNS2 sequences of several mammal species were downloaded and analyzed for the presence of conserved TFBSs, as previously described [® software  to create a comprehensive map of the TFBSs contained within CNS2.escribed . Transcrescribed  and bothescribed   was cloned into BglII and HindIII restriction enzyme (RE) cloning sites of the commercial luciferase vector pGL3 basic  (pPr plasmid). Then, the CNS2 region  was cloned into KpnI and XhoI RE sites, with the introduction of an EcoRI site by KpnI for further cloning (pPr2 plasmid). Modified CNS2 constructs containing different regions or specific TFBSs were generated by PCR amplification of pPr2 employing custom primers  were transfected with 1 µg of modified firefly luciferase plasmid (purified with the Plasmid Maxi Kit from Qiagen 12163) plus 20 ng of pRL-TK  to standardize the luciferase activity independent of the efficiency of transfection between samples) using Effectene (Qiagen 301425) following the manufacturer’s protocol. After transfection, the cells were cultured at 37°C with 5% CO2 for 24 h and were then stimulated with 10 ng/mL PMA and 500 ng/mL Ionomycin for an additional 24 h. Forty-eight hours after transfection, cells were lysed with passive lysis buffer , and luciferase activity (firefly/renilla) was measured with a dual luciferase kit  using the Orion II microplate luminometer .Design of dicer substrate small interfering RNA (DsiRNA). All DsiRNAs described were synthetized by IDT . Three DsiRNAs were designed for each gene to be silenced in addition to two additional DsiRNAs and a negative control targeting NC1. The genome reference used for DsiRNA design was mm10. DsiRNA transfection and CD69 characterization. Mouse EL-4 T cells (105) were transfected with a 1 µM pool of three DsiRNAs against POU2F1 (Oct1) or RUNX1 in a 1:1:1 ratio or a negative control DsiRNA against NC1. RNA of transfected cells were extracted, and a qPCR was performed to assess mRNA levels of RUNX1 and POU2F1 (Oct1).2 for 16 h and then stimulated or not with 10 ng/mL PMA and 500 ng/mL ionomycin for an additional 6 h. Twenty-two hours after transfection, CD69 surface expression was measured by flow cytometry as follows: cells were washed twice in cold 1X PBS and stained for 30 min at 4 °C with 0.5 µg of an α-mCD69/PE-Cy7 monoclonal antibody . Samples were acquired with a FACSCanto  flow cytometer, and data were analyzed using FlowJo software. The percentage of inhibition of CD69 expression with respect to its expression in the NC-1 control was represented using GraphPad Prism 7 .Transfected cells were cultured in a 96-well plate at 37 °C with 5% COData representation and statistical analysis. Luciferase assay and flow cytometry data were plotted with GraphPad Prism 7. Significant differences between multiple conditions were tested with a nonparametric one-way ANOVA test performed with GraphPad Prism 7.CNSs of the CD69 gene, we proposed that CNS2 is the putative main enhancer based on the enrichment of chromatin accessibility, modifications and bound TF [CD69 3′untranslated region, intron 1, promoter, CNS1, CNS2 and CNS4 and in the murine 3′untranslated region, promoter, CNS1 and CNS2 have a higher density of TFBSs (TFBSs per 100 bp) than the rest of noncoding sequence within the CD69 locus. Thus, the 3′untranslated region, promoter, CNS1 and CNS2 of both species contain numerous TFBSs, which suggests that they may play a particularly important role in the transcriptional regulation of the CD69 promoter. In agreement with our previous observations, mouse CNS2 also shows a higher total number of TFBSs compared to the other regulatory regions within CD69 locus.In a previous data-mining study of the regulatory features of the bound TF . Given tCNS2 into different subregions based on the presence of TFBSs conserved between 6 mammal species and tested their contribution to the enhancer capacity of CNS2. However, that characterization left undefined regions where bound TFs have subsequently been identified and could play a relevant role. Moreover, considering that some regulatory mechanisms may have diverted during evolution and that, consequently, some important TFBS might not be conserved, in the present work, we subdivided the mouse CNS2 into five regions based on the abovementioned updated ChIP-seq data, taking into account all bound TFs, as well as those bound to sites that are not conserved between six mammal species  to enhance transcription from the mouse CD69 promoter with those of different CNS2 fragments: I+II+III, II+III and I+II . As shown in CD69 promoter upon PMA/ionomycin activation, while those of regions I, IV and V have a more modest contribution.Then, we assessed the contribution of the different regions to mouse While region III contains three overlapping BSs, region II has two separate subregions with TFBSs: One with an Oct1 BS and another with GATA+MyoD TFBSs. We further assessed the contribution of the individual regions I, II and III, as well as the subregions of region II separately or in combination with the region I or III, but keeping, within the tested fragment, the original sequence with the endogenous TFBSs distribution. CD69 transcription. Furthermore, the combination of this sequence with region I  had a transcriptional enhancing capacity as high as half of that of region I-III and similar to that of regions I and II together  significantly increases the inducible enhancer activity in a similar manner as region II (Prom+II), while the ~65 bp sequence containing GATA+MyoD TFBSs (Prom+GATA+MyoD) did not significantly increase the inducible enhancer activity. These results suggest that the subregion that contains the Oct1 TFBS constitutes the most relevant regulatory feature of region II. Moreover, considering that regions I and III alone do not show enhancing activity, these data indicate that the ~60 bp sequence containing the Oct1 TFBS is the shortest sequence identified within regions I+II+III that has transcriptional enhancer activity, likely acting as the enhancer core of together B. Althoutogether B, it is CD69 transcriptional regulation. To do so, we silenced them individually or in combination using siRNA in the mouse T cell line EL-4 and analyzed the effect of silencing on surface CD69 protein in unstimulated cells or cells activated with PMA/Ion. Under both conditions, inhibition of RUNX1 and Oct1 individually resulted in a CD69 expression reduction of ~40%, and the joint inhibition of both TFs did not further reduce CD69 expression  on CD69 promoter transcriptional regulation. Using ChIP-seq data, we mapped the TFBS within CNS2 and used the TFBS distribution to define different regions. Then, we tested the effect of these regions on transcription induced by the CD69 promoter in response to PMA/ionomycin activation in luciferase reporter assays. In this way, we defined a minimal sequence with intrinsic enhancer capacity that contained a conserved Oct1 BS that could further enhance transcription if it was accompanied by either a 3′ flanking region containing a conserved SRF BS or a 5′ flanking region containing conserved RUNX1, GABPA and Elk-1 TFBSs and could enhance transcription to even higher levels in the presence of both of them. These results suggest cooperation between these TFs. We further tested the effect of Oct1 and RUNX1 silencing on CD69 protein expression. It these experiments, the observed synergy seemed even more striking because the effect of each TF depended on the presence of the other.In this work, we deepened the understanding of the enhancer function of mouse conserved noncoding sequence 2 (CNSs, CNS2 had the most potent enhancer activity on CD69 transcription. In the present work, the mapping of TFBSs on the CD69 locus showed that several of the TFs that have been shown to bind to CNS2 also bind the promoter region, which suggests their importance in the transcriptional regulation of CD69. Despite the fact that there are fewer data available for the TFs bound to the mouse CD69 locus than to the human CD69 locus, similar to humans, mouse CNS2 is also the region with the highest enrichment of TFBSs. Occupancy by specific TF has been described to be a predictor of enhancer activity of a given region [CNS2 as a transcriptional enhancer of CD69.In previous studies, we observed that among the different n region . Thus, tCNS2 regions are in agreement with our previous work, in which the regions with the highest enhancer capacity comprises regions I, II and III, described in the current study [per se, it could increase that of Oct1 BS. This could be explained by an interaction of TFBSs in region I with the transcriptional machinery that bounds to the region containing the Oct1 BS. Altogether, these data suggest a cooperative modular model of transcription factors that synergistically enhances transcription. Cooperation between transcription factors may occur based on their physical association, a mechanism frequently described for enhancer sequences that affect the transcriptional behavior of several immune system genes [The present results regarding the enhancer capacity of nt study . In the em genes ,40,41.+ T cell differentiation [+ effector T cells as a switchable stabilizer of the repressed and inducible state [Although Oct1 has been widely studied as a regulator of transcription in many cell types ,43, its ntiation  and memontiation , orchestle state , acting le state .CNS2, many enhancers are located far from their target genes, but are able to specifically communicate with distal promoters over large distances [As is the case for istances ,55,56 thistances ,58. Thusistances ,60.CD69 gene. Silencing of these TFs separately in the mouse EL-4 T cell line reduced CD69 expression as much as their joint silencing, suggesting that they can enhance CD69 expression, but only if the other TF is also present. This result suggests a mode of action that is completely synergic. Given the predominant enhancer role of CNS2 in CD69 transcription and, within it, of the Oct1 TFBS, and its observed cooperation with region I, we believe that these results might reflect, to some extent, the role of Oct1 and RUNX1 acting on the BSs described in regions I and II of CNS2. However, we cannot rule out that they might also be influenced by the action of these TFs on other BSs within the CD69 locus. The ChIP-seq databases show two RUNX1 BS found in CD69 promoter sequence. However, since these regions have a much more modest enhancing capacity, we propose that the main enhancer effect of RUNX1 is through the BS in CNS2. Future experiments using ChIP, TF silencing and TFBS mutagenesis might shed more light on the role of the studied TF in CD69 transcription in the genomic context.Because of the lack of a genomic context in reporter plasmids, luciferase assay data do not reflect the effects of chromosome topology on transcription. However, the luciferase assay can still be used as a predictor of the regulatory capacity of elements that can be further characterized in a more physiologic context. With that aim, we tested the effects of RUNX1 and Oct1 silencing on the expression of the endogenous CNS2 as an essential enhancer of mouse CD69 promoter transcription. Despite the need for further studies on the role of CNS2 in the genomic context, to our knowledge, no detailed studies on the composition and function of regulatory elements within this enhancer have been published. Our work is, therefore, a step forward in understanding how CNS2 regulates CD69 expression.In summary, our results strengthen evidence of the role of


Cebpa encodes a transcription factor (TF) that plays an instructive role in the development of multiple myeloid lineages. The expression of Cebpa itself is finely modulated, as Cebpa is expressed at high and intermediate levels in neutrophils and macrophages respectively and downregulated in non-myeloid lineages. The cis-regulatory logic underlying the lineage-specific modulation of Cebpa’s expression level is yet to be fully characterized. Previously, we had identified 6 new cis-regulatory modules (CRMs) in a 78kb region surrounding Cebpa. We had also inferred the TFs that regulate each CRM by fitting a sequence-based thermodynamic model to a comprehensive reporter activity dataset. Here, we report the cis-regulatory logic of Cebpa CRMs at the resolution of individual binding sites. We tested the binding sites and functional roles of inferred TFs by designing and constructing mutated CRMs and comparing theoretical predictions of their activity against empirical measurements in a myeloid cell line. The enhancers were confirmed to be activated by combinations of PU.1, C/EBP family TFs, Egr1, and Gfi1 as predicted by the model. We show that silencers repress the activity of the proximal promoter in a dominant manner in G1ME cells, which are derived from the red-blood cell lineage. Dominant repression in G1ME cells can be traced to binding sites for GATA and Myb, a motif shared by all of the silencers. Finally, we demonstrate that GATA and Myb act redundantly to silence the proximal promoter. These results indicate that dominant repression is a novel mechanism for resolving hematopoietic lineages. Furthermore, Cebpa has a fail-safe cis-regulatory architecture, featuring several functionally similar CRMs, each of which contains redundant binding sites for multiple TFs. Lastly, by experimentally demonstrating the predictive ability of our sequence-based thermodynamic model, this work highlights the utility of this computational approach for understanding mammalian gene regulation. CCAAT/Enhancer binding protein, α (Cebpa) encodes a TF that is necessary for neutrophil development [Cebpa is expressed in hematopoietic stem cells, granulocyte-monocyte progenitors (GMPs), neutrophils, and macrophages . Altn levels . Correspectively . Cebpa iopically .cis regulation of Cebpa during hematopoiesis is poorly understood. C/EBPα, C/EBPβ, and C/EBPδ are known to activate Cebpa by binding to its proximal promoter [Cebpa is regulated in 32Dcl3 myeloid cells by PU.1, other Ets TFs, SCL, Gata2, Myb, and C/EBPα, which bind to an enhancer located 37kb downstream of the gene [Cebpa is also regulated by multiple CRMs. More importantly, it is not understood how the regulatory contributions of these and other TFs modulate Cebpa’s gene expression during differentiation. In this study, we decode the regulatory logic of seven cis-regulatory elements (CRMs) of Cebpa at binding-site resolution during myeloid differentiation.Despite its essential and pleiotropic functions, the promoter . Recentlpromoter . Cebpa ithe gene , 12. It the gene , Cebpa iCebpa’s regulatory logic illustrate the general challenge of decoding gene regulation of complex mammalian loci. The challenge arises from the complexity of gene regulation—genes may be regulated by multiple CRMs [The deficits in our understanding of ple CRMs , 14 and ple CRMs –20. The a priori knowledge of the identities or the regulatory roles, activation or repression, of the TFs regulating a CRM. The TFs regulating a CRM and their regulatory roles are inferred in silico by testing many alternative models, each realizing a potential regulatory scheme, against quantitative reporter data. The composition of the best fitting model then implies the regulatory roles of the TFs most congruent with the observed patterns of CRM- and cell-type-specific reporter activity. It is worth noting that this procedure not only produces a description of the TFs, their roles, and their binding sites, but also yields predictive models of CRM function.We have developed a computational approach to solve the problem of mapping multiple TF inputs to transcriptional output and decoding regulatory logic . We utilCebpa in order to comprehensively decode its regulation [Cebpa transcription start site (TSS). Four CRMs, including one encompassing the +37kb enhancer identified by Guo et al. [Cebpa. The remaining CRMs, appeared to behave as silencers and repressed the activity of the proximal Cebpa promoter in a dominant fashion.We previously applied our approach to gulation  during mgulation , which agulation , 8. We io et al. , acted aCebpa locus and suggested a novel mechanism of lineage resolution [Cebpa is necessary for the specification and maintenance of non-myeloid cell fates [Cebpa promoter by distal silencers in non-myeloid lineages therefore might be a mechanism for resolving lineages. These inferences must however be regarded as predictions since they are yet to be verified experimentally.Our computational analysis inferred a comprehensive map of the regulation of the solution . The enhll fates , 17, 35.Cebpa CRMs. We predicted the effect of mutations to one or more binding sites by simulating the regulation of mutated DNA in the model. The predictions were experimentally tested by synthesizing mutated CRMs and assaying their activity and by comparing against publicly available ChIP datasets. The regulatory logic of enhancers was investigated in PUER cells, representing the myeloid lineage where Cebpa is expressed robustly. The function and regulation of silencers was investigated in G1ME cells [Gata1−/− mice and represent the red-blood cell lineage by virtue of being blocked at the megakaryocyte-erythrocyte progenitor (MEP) stage.Here we rigorously test the predictions of our computational models to determine the regulatory logic of ME cells , which aSpi1−/− cells, expressing conditionally activable PU.1 protein, which can be differentiated into macrophages or neutrophils by PU.1 activation . PUER cells were differentiated into macrophages by adding 200nM 4-hydroxy-tamoxifen . Cells were differentiated into neutrophils by replacing IL3 with 10ng/ml Granulocyte Colony Stimulating Factor  and inducing with 100nM OHT after 48 hours. Gata1-deficient megakaryocyte-erythrocyte (G1ME) cells were routinely maintained in complete α-MEM Glutamax  supplemented with 20% FBS and 20ng/ml TPO .We utilized n PUER; , 8, 33)., 33.Spi1luc2 Luciferase reporter vector . The proximal promoter was introduced into the multiple cloning site (MCS) of pGL4.10luc2 between XhoI and HindIII sites. The distal CRMs were inserted between BamHI and SalI sites downstream of the SV40 late poly(A) signal. CRM sequences are provided in Putative CRMs were cloned into a pGL4.10luc2  following the manufacturer’s instructions. The following PCR cycling conditions were used: initial denaturation of 30s at 98C, 30 cycles of 30s at 98C, 30s at 60C, and 60s at 72C, and a final extension for 10 minutes at 72C. Primers included 40bp of sequence homologous to pGL4.10μg total plasmid DNA in SF buffer , using program CM134 and incubated for 24 hours prior to luminescence measurement. G1ME cells were transfected with 4.52μg total plasmid DNA in P3 buffer , using program CM134 and incubated for 6 hours before luminescence measurement. After incubation, Firefly and Renilla luminescence were measured using the Dual-Glo Luciferase activity kit  and the DTX 880 Multimode Detector (Beckman Coulter) according to manufacturer’s instructions. Transfections were performed in at least 10 replicates. Raw luminescence data from PUER and G1ME cells are provided in PUER or G1ME cells were transfected with a reporter vector and Renilla control vector  in a 1:200 ratio using a 4D-Nucleofector (Lonza). PUER cells were transfected with 2.26β, of the line y = βx, where y is Firefly luminescence and x is the Renilla luminescence. Briefly, β was estimated by minimizing the loss functionxi and yi are individual replicates of Renilla and Firefly luminescence measurements, c = 4.7, and S is an estimate of the scale of the residuals. The argument of Tukey’s function is the orthogonal distance of the point  from the regression line. Tukey’s function is bounded for large values of t, which limits the contribution of outliers to the loss function and ensures that the slope estimate is robust to outliers. The value of S was estimated by solving the equationκ = 0.05 and χ(t) is Tukey’s loss function with c = 1.56. The minimization problems were solved by the sequential least-squares quadratic programming (SLSQP) algorithm of the NLOPTR package of R, with parameters xtol_rel and maxeval set to 10−7 and 1000 respectively.Well-to-well transfection efficiency variation was controlled for by normalizing Firefly luminescence against Renilla luminescence. Robust errors-in-variables (EIV) regression, implemented according to the method of Zamar , was useR package BOOT. 999 replicates were subsampled using the ordinary simulation and the function boot.ci was used determine confidence intervals using the basic bootstrap method.95% confidence intervals were estimated by bootstrapping using the et al. [α, C/EBPδ, Egr1, Gfi1, Myb, PU.1, Jun, Myc, Ets1, Ikaros, and Fli1, that are expressed in PUER cells [et al. [15 = 32, 768 alternative models realizing all possible combinations of roles. The alternative models were fit to reporter activity measurements from 46 putative CRMs from the Cebpa, Egr1, and Egr2 regions in uninduced and 24 hour IL3 and GCSF induced conditions. Hierarchical clustering was used to identify 8 models with highly consistent regulatory schemes from the 20 lowest scoring model realizations. The model utilized in this work, 81762, was representative of the low scoring models and it’s output was highly correlated with the measured reporter activity (r2 = 0.91). It is worth noting that the same model, that is the same set of TF-related parameters, was able to correctly simulate the regulation of 46 diverse CRMs in three conditions simultaneously.We briefly describe the specific model used here to identify binding sites and make predictions. For details, see Bertolino et al. . The modER cells , 21 and in silico with the aid of our sequence-based model of transcription [luc2 using Gibson assembly as described above. Mutant CRM sequences are provided in Mutations to predicted TF binding sites were designed cription . A mutancription  of the cCebpa expression relative to Hprt was computed as Cebpa and Hprt respectively. The following primers were used:Total RNA was extracted using MagJet RNA kit , and reverse transcribed using the High Capacity cDNA Transcription kit  following the manufacturer’s instructions. Real-Time PCR was performed using the Ssofast Evagreen Supermix  in a C1000 Thermal Cycler with CFX384 Real-Time System (BioRad) using the following cycling conditions: initial denaturation of 30s at 95C followed by 40 cycles of 5s at 95C and 5s at 60C. Cebpa_fwd: ACTTTCCGCGGAGCTGAGCebpa_rev: ATTTTTGCTCCCCCTACTCGHprt_fwd: ACCTCTCGAAGTGTTGGATAHprt_rev: CAACAACAAACTTGTCTGGAThe data are provided in PUER cells were preincubated with Rat anti-mouse CD16/CD32 antibody  to reduce nonspecific binding. Cells were stained with (Phycoerythrin)-CF594-conjugated anti-F4/80  or Biotin-conjugated anti-Gr-1  monoclonal antibodies from BD Biosciences. Gr-1 primary incubation was followed by incubation with Allophycocyanin-conjugated Streptavidin . Stained cells were analyzed on a BDFACSymphony flow cytometer (BD Biosciences). Data were analyzed using FlowJo . Positive fraction was estimated using FlowJo’s SE Dymax method.6 cells were lysed in RIPA buffer (Fisher Scientific) and the lysates were size-separated by 12% SDS-PAGE. Proteins were transferred to an Immobilon-FL PVDF membrane (Sigma-Aldrich). The membrane was incubated with the REVERT total protein stain (Licor) and imaged in the 700nm channel of a Licor Odyssey Fc near-infrared imaging system. Subsequently the membrane was incubated with a Rabbit anti-mouse C/EBPα (D56F10) monoclonal antibody  and an IRDYE 800CW Donkey anti-rabbit secondary antibody . The membrane was imaged in the 800nm channel to detect C/EBPα. The data were analyzed using Image Studio (LI-COR) and the total fluorescence in each band was measured and summed. Total C/EBPα fluorescence was normalized against the total fluorescence in the total protein stain.5 × 10Cebpa expression during the differentiation of PUER cells into macrophages and neutrophils. PUER cells are IL3-dependent hematopoietic progenitors derived from Spi1−/− mice and carry a transgene encoding a PU.1-Estrogen receptor fusion protein [We characterized the time course of  protein . Uninduc protein ). For neCebpa gene expression relative to Hprt or Gapdh using RT-RTPCR in uninduced PUER cells and at four time points during a 7-day course of differentiation in IL3 and GCSF conditions . Cebpa expression increases 70% during the 48 hour pretreatment with GCSF, and another 40% after the first 24 hours of GCSF+OHT treatment. Thereafter, the expression level declines gradually over time to revert to pre-OHT levels at day 7. In contrast, the expression level remains relatively constant after OHT treatment in IL3 conditions. C/EBPα protein displays the same expression pattern as the mRNA , overlapped with a known enhancer located 37kb downstream of the Cebpa TSS [cis-regulatory logic of these newly identified enhancers, we validated their activity in PUER cells using a statistically robust procedure for measuring reporter activity that we have developed recently  regression [In our method, we utilize linear regression to determine the normalized activity as the slope of the best fit line , and hengression , 42 instgression . FurtherCebpa proximal promoter alone (Cebpa(0)) or in combination with one of the distal CRMs (Cebpa(X), where X is the CRM number. The comparison of the CRM-bearing reporter with Cebpa(0) allows us to discriminate enhancing or silencing CRMs from neutral ones. Reporter activity was assayed in uninduced conditions and 24 hours after the addition of OHT in either IL3 or GCSF conditions, when the difference in Cebpa expression between the two treatments is the largest  is the strongest enhancer in uninduced conditions, upregulating activity ∼6-fold relative to Cebpa(0). Cebpa(7)’s enhancing effect is moderated somewhat to 3-fold and 4.5-fold in induced IL3 and GCSF conditions respectively. Cebpa(14) has a qualitatively similar activity pattern as Cebpa(7), providing the greatest activation, ∼2.5-fold, in uninduced conditions. Cebpa(16) and Cebpa(18), in contrast, have the greatest activity in induced conditions. Cebpa(16) upregulates the proximal promoter 4.1-fold in induced GCSF conditions compared to ∼2-fold in uninduced conditions. Similarly, Cebpa(18) provides the greatest upregulation of ∼2.5-fold in induced GCSF conditions.All four enhancers upregulated the activity of the promoter robustly and also exhibited cell-type specific patterns of activity . Cebpa(7Cebpa(7) upregulates activity ∼6-fold instead of ∼4-fold as observed previously. These differences likely stem from two sources. First, we used the pGL4 vector backbone instead of pGL3 since the former has many fewer predicted binding sites for mammalian TFs, minimizing confounding effects from spurious TF binding. Secondly, we measured luminescence in 10 replicates and analyzed the data with robust EIV regression. Both of these modifications should result in more accurate estimates of reporter activity than before.Although these activity patterns are largely consistent with our previous measurements , some qucis-regulatory logic by mutating binding sites predicted by sequence-based models of gene regulation [et al. [Having rigorously validated the novel enhancers, we next decoded their gulation . We prov [et al.  for impl [et al. . The mod [et al. , 24, tha [et al. , 44, 45,Besides predicting the activity from sequence when the regulating TFs are known, this modeling framework can also be used to learn which TFs regulate a particular CRM and whether they act as activators or repressors. This is achieved by constructing an ensemble of models realizing all possible combinations of the regulatory roles of a set of candidate TFs and identifying which model realization best fits the empirical reporter activity data . WhetherCebpa CRM regulation at binding-site resolution  over Cebpa(0) results from activation provided by C/EBP family TFs and Gfi1, which bind 2 and 3 sites respectively (Cebpa(7m1), which lacks C/EBP sites and is predicted to have half the activity of Cebpa(7) in uninduced conditions when simulated in our model (Cebpa(7m1) and assayed its activity in both uninduced and induced conditions in PUER cells. We compare fold-change relative to the proximal promoter, Cebpa(0), since the absolute scale of the reporter data used to fit the model in Bertolino et al. [Cebpa(7) by C/EBP family TFs  data also suggested that Gfi1 or other as yet unidentified sites are functional since the C/EBP sites did not account for the entirety of Cebpa(7) activity. We tested the contribution of Gfi1 sites to the residual activity of Cebpa(7m1) by designing a second mutant, Cebpa(7m2), lacking all Gfi1 and C/EBP binding sites (Cebpa(7m2) completely lacked activity in the uninduced condition (Cebpa(7m1), so that Cebpa(7m2)’s activity was three-fold lower than that of the wildtype CRM  suggests that as yet unknown TFs also contribute to the activity of Cebpa(7).The ng sites . Simulatondition . We obsetype CRM . This reCebpa(14) is activated exclusively by Egr1, which binds the CRM at two predicted sites (Cebpa(14) (Cebpa(14m1), which lacks both Egr1 sites. Simulation of Cebpa(14m1) predicted a reversion of activity to the level of the proximal promoter (Cebpa(14).We had inferred that ed sites . Consistebpa(14)  matches promoter . Experimpromoter , demonstCebpa(16) utilizes 4 activator binding sites, 3 for PU.1 and 1 for C/EBP family TFs (Cebpa(16) in induced conditions (Cebpa(16m1), was predicted to lack enhancing activity in induced conditions, while being expressed at the same level as wildtype in uninduced conditions (Cebpa(16m1) behaved as predicted, with an activity nearly half of Cebpa(16) and indistinguishable from that of the proximal promoter in induced IL3 conditions (Cebpa(16m1) was statistically indistinguishable from that of the wildtype enhancer. The activity of Cebpa(16m1) was also ∼43% lower than that of Cebpa(16) in the induced GCSF condition, although residual upregulation relative to the proximal promoter likely implies that the C/EBP site is also functional.The model for enhancer mily TFs . Activatnditions , when thnditions . Experimnditions . There wCebpa(18) is a PU.1-responsive enhancer with additional activator binding sites for Ets1, Myc, and Gfi1   encompasses the +37kb Cebpa enhancer previously identified by Guo et al. [et al. [We had inferred that Fig F in . Cebpa is 201bp longer than the +37kb enhancer, we next investigated whether the extra sequences had any function or not. As a first step, we simulated the +37kb enhancer in our model. The model predicted that the activity of the +37kb enhancer is 7- and 4.5-fold higher than that of Cebpa(18) in the uninduced and induced IL3 conditions respectively (Cebpa(18) in both uninduced and induced IL3 conditions ’s activity. The model had inferred five active repressor sites in Cebpa(18), Fli1, Elf1, GATA, Myb, and Ebf1 (Cebpa(18), lying in the extra 201bp of sequence. Of the two TFs, Myb is more likely to mediate the repressive effects since Ebf1 is not expressed in myeloid cells [Cebpa(18m1), with the model. The model predicted that Cebpa(18m1) has a much higher level of activity that is indistinguishable from that of the +37kb enhancer (Cebpa(18m1)’s activity was derepressed relative to Cebpa(18) and indistinguishable from that of the +37kb enhancer , and Cebpa(16). PU.1 peaks were detected in Cebpa(16) and Cebpa(18). Gfi1, Myb, and Egr1 bind to Cebpa(7), Cebpa(18), and the proximal promoter respectively. We were unable to verify just one prediction, the binding of Egr1 to Cebpa(14), with the available datasets. This discrepancy could be a result of cell-type specific binding of Egr1 since the ChIP data in question (GSM881139) are from Dendritic cells [Having validated the binding sites predicted by the model, we checked in publicly available genome-wide TF binding datasets whether the predicted TFs bind to Fig M in . C/EBP pic cells  and not cis-regulatory logic of four Cebpa enhancers at the resolution of individual binding sites. In all cases, the model’s predictions were borne out by experiment. The identified TFs and their sites are likely the most important regulators of Cebpa during macrophage-neutrophil differentiation since they account for most of the CRM activity. The investigated TFs do not however account for all of the CRM activity, suggesting that other TFs not represented in the model also perhaps regulate Cebpa. The overall picture that emerges is that C/EBP family TFs, Gfi1, and Egr1 support Cebpa’s expression in uninduced or progenitor conditions by binding to Cebpa(7) and Cebpa(14). Activation in induced conditions is provided via Cebpa(16) and Cebpa(18) by increased PU.1 activation and a loss of Myb repression.To summarize, we have decoded the Cebpa promoter, reduced the activity of the construct to levels lower than that of the promoter alone [Drosophila [Cebpa(9), Cebpa(11), Cebpa(23), and Cebpa(24), lie 9–40kb away from the Cebpa TSS (Cebpa(11) and Cebpa(24) in G1ME cells  checking whether the silencers do, in fact, exert dominant repression in a non-myeloid cell type, and 2) determining whether the silencing is attributable to the predicted repressors.Cebpa in a myeloid background.Before testing the activity of the silencers in a non-myeloid cell type, we measured their activity in PUER cells using the statistically rigorous methodology we developed for analyzing reporter data. In PUER cells, all of the silencers were either neutral or had weak enhancing activity Fig H in . This reCebpa(11) and Cebpa(24) in G1ME cells , Cebpa(11), Cebpa(24) in addition to the promoter had ∼3-fold lower activity compared to the promoter alone  (Cebpa(9m1), Cebpa(11m1), and Cebpa(24m1)—lacking binding sites for both TFs (Cebpa(11m1) carried additional mutations in an Ebf1 site but was functionally equivalent to a GATA/Myb mutant since Ebf1 is not expressed in the red-blood cell lineage  and Cebpa(11m1), their activity was indistinguishable from that of Cebpa(0)  . We syntboth TFs . Cebpa. AsCebpa(0) . This imCebpa proximal promoter. We considered three hypotheses and tested them by mutating GATA and Myb sites individually in Cebpa(11)  and Cebpa(11m3), which carry impaired GATA or Myb sites respectively. Both of the constructs carrying only one functional repressor site were able to silence the proximal promoter (Cebpa(11m2) is lower than that of Cebpa(11), which could be interpreted to imply an activating role for GATA. However, if GATA were an activator, one would expect a loss of repression in Cebpa(11m3), which has a functional GATA site. Since this is not the case, we favor the explanation that perhaps, even though Myb is a more potent repressor, GATA competes with Myb and limits the overall repression to that achieved by GATA alone. This would help explain why the activities of Cebpa(11m3)Cebpa(11) are indistinguishable. The maintenance of repression in the single mutants supports the hypothesis that GATA and Myb are capable of repressing the promoter individually and act redundantly.Next, we investigated how GATA and Myb jointly repress the activity of the ebpa(11) . First, r Bicoid , 59. We promoter . The expCebpa proximal promoter in a dominant manner. Dominant repression only occurs in the red-blood cell lineage and the CRMs do not silence the proximal promoter in myeloid cells. Lastly, the silencing activity is attributable to a regulatory motif shared by all three silencers—GATA and Myb sites that act redundantly.In summary, we have shown that three of four putative silencers are capable of attenuating the activity of the Cebpa at the resolution of individual binding sites. In the process of doing so, we have also verified the predictive ability of a thermodynamic model of mammalian gene regulation that we developed recently [Drosophila gene regulation [even-skipped, as the focus of most of the work. Our model is closely related to its Drosophila counterparts, incorporating just one additional mechanism, long-distance dominant repression, lacking in the latter. The ability of models with shared mechanisms of gene regulation to predict reporter activity in these divergent species supports the view that the rules of transcriptional regulation are universal.We have comprehensively analyzed the regulation of 7 CRMs neighboring recently . It is wgulation , 60–64, Cebpa expression in non-myeloid lineages. The hypothesis predicts that the silencers of Cebpa would have much lower activity in the myeloid lineage, where the gene is expressed, than in non-myeloid ones, where it is not expressed. When we assayed the activity of the silencers in PUER cells, which belong to the myeloid lineage, we found they they acted as enhancers or neutral elements  (Cebpa(18)   and CebpFig F in  are actifor Egr1  unique tCebpa enhancers and silencers is that of a distributed and specialized control scheme Click here for additional data file.S1 FileCRM sequences are provided in the FASTA format.(TXT)Click here for additional data file.S1 DatasetCebpa (CebpaCq), Gapdh (GAPDHCq), and Hprt (HprtCq) are provided. Column 1: time in hours. Column 2: replicate number. Column 3: cytokine treatment. Column 4: whether cells were treated with OHT or not .Threshold cycle values of (CSV)Click here for additional data file.S2 DatasetLuc/Ren are luminescence measurements from each well. Construct indicates the CRM/promoter being assayed, where “0” is promoter by itself. OHT is true or false for induced or uninduced conditions respectively. The “note” column indicates whether the construct is wildtype and, if not, which sites were mutated.(CSV)Click here for additional data file.S3 DatasetLuc/Ren are luminescence measurements from each well. Construct indicates the CRM/promoter being assayed, where “0” is promoter by itself. OHT is true or false for induced or uninduced conditions respectively. The “note” column indicates whether the construct is wildtype and, if not, which sites were mutated.(CSV)Click here for additional data file.


HOMER1) was detected as a candidate gene. The aim of this work was to further verify the candidate gene by sequencing the gene and find the significantly associated mutation. Then we preliminarily analyzed the effect of the significant SNP on intronic promoter activity. This research provided a reference for further investigation of the pathogenesis of PSL.In our previous genome-wide association study (GWAS) on the piglet splay leg (PSL) syndrome, the homer scaffolding protein 1 . The G allele of rs325197091 (A > G) may create a new binding site of transcription factor aryl hydrocarbon receptor nuclear translocator (ARNT) and could enhance HOMER1 intronic promoter activity.We investigated the 19 SNPs on HOMER1 gene was associated with the PSL, and the rs325197091 could influence HOMER1 intronic promoter activity in vitro.The online version of this article (10.1186/s12863-018-0701-0) contains supplementary material, which is available to authorized users. HOMER1 gene (Sscrofa 10.2) [HOMER1 codes a scaffold protein and always concentrated in post-synaptic structures as well as combined with metabolic glutamate [HOMER1 was found expressed in neuromuscular junction, muscle development system and vertical sacroplasmic reticulum vesicles in human and mouse skeletal muscles [HOMER1 can intact with Ca2+ related channel signal molecules such as IP3R, RYR, TRPC, and NFAT [2+/calcineurin signaling pathway is important for myotube formation, and HOMER1 may influence the skeletal muscle function via Ca2+ [HOMER1 gene were reported in Ensemble. HOMER1–201 (ENSSSCT00000057415.1) has high homology among different species. There are nine exons that are exon 1, exon 5 to exon 12 encoded in HOMER1–201. Its translation initiation code resides on the exon 1. Other four transcripts are predicted transcript. However, HOMER1–205 (ENSSSCT00000062712.1) is associated with the skeletal muscle contraction, the development of skeletal muscle fibers, and the regulation of Ca2+ channel activity predicted suggested by GO analysis. Eight exons, which are from exon 5 to exon 12, are encoded in the HOMER1–205. Besides, the first 110 bp encoded in HOMER1–205 are not belonging to the coding area in other four transcripts. The translation initiation code of HOMER1–205 resides on exon 5 but the location of its 5’UTR and promoter are not clear. In this research, we aimed to characterize the polymorphism of HOMER1 gene including the promoters of HOMER1–201 and HOMER1–205 for identifying the significant-associated mutation of PSL.Piglet splay leg (PSL) syndrome is one of the complex genetic defects in newborn piglets . It coulfa 10.2) . HOMER1 lutamate . HOMER1  muscles , 6. HOMEand NFAT –10. In avia Ca2+ . Twelve DNA for 183 animals, including 110 normal pigs and 73 PSL pigs from Tianzhong stock Corporation , which came from the 185 animals described in our previous study [2 at 37 °C.The porcine kidney cells (PK15) and the human kidney cells (293 T) were obtain from China Center for Type Culture Collection (CCTCC) and cultured using DMEM medium with high glucose  supplemented with 10% FBS  in a humidified atmosphere of 5% COOne primer was designed and the PK15 cDNA was used to amplify the sequence of exon 5 different from other transcripts in intron 4. The forward primer resided in intron 4 while the reverse primer resided in exon 6. The primer pairs used are as follows: HM-205 T former: 5′- GTCAAGTTTGAAAGTAAGTTTCCCT -3′; reverse: 5′- AGTATTTGCCCGGCTATCGG -3′; 18srRNA former: 5′- GAGACGGTGGGACAGCG -3′; reverse: 5′- GCCCTCGGTCGAGTTGTC -3′.http://www.fruitfly.org/seq_tools/promoter.html) was used to analyze the promoter regions in 3000 bp upstream the exon 1 and exon 5. JASPAR (http://jaspar.genereg.net/) were used to predict the transcription factor binding on the SNPs sites.Bioinformatics website Neural Network Scan Service  based on the genomic sequence of the porcine HOMER1 gene (ENSSSCG00000014113) referring to Sscorfa11.1 assembly to amplify all exons and partial adjacent introns . 2 μl of siRNA, 0.2 μg of reconstructed plasmids were co-transfected into the cells using Lipofetamine 2000™ reagent for 4 h–6 h. Then the transfection mixtures were drew out, and the complete DMEM medium was added in each well. After 24 h, the enzymatic activity of luciferase was measured by PerkinElmer 2030 Multilabel Reader (PerkinElmer).Western blotting was performed as our previously described . 10–12% p value < 0.05 was considered as statistically significant.All experiments were performed independently three times, and data were presented as the means ± standard (SEM). Data were analyzed by two-tailed Student’s t-tests with SPSS version 16.0 . A HOMER1 mRNA according to the sequence of HOMER1–205. One primer was designed and PK15 cDNA was used to amplify the sequence of exon 5 different from other transcripts in intron 4 including the ATG of HOMER1–205 which was the first three bases of exon 5 . One SNP (rs331422651) resided in exon 5. One significant splicing mutation (rs344145865), resided in the intron 11 near the splicing site. Two significant SNPs (rs711466420 and rs709236548) were found in exon 12 belonged to the 3’UTR in HOMER1–201. Besides rs333077091 and rs709236548, other significant SNPs were in Hardy-Weinberg equilibrium  and HP2 (P < 0.01) were significantly different between the PSL and normal pigs. HP1 contained the mutant type of rs339135425, rs325197091 and rs322755731 while HP2 contained the wild.rs339135425, rs344370846, rs335396960, rs325197091, rs342088137, rs332280474 and rs322755731, those 7 significant SNPs in intron 4 composed the block1 which had five haplotypes (D’ = 1.00) .P < 0.05)  was significantly higher than the fragment H2W (− 276 bp to + 154 bp) (http://jaspar.genereg.net/)  when the ARNT in lower expression while the H3W (GATC) containing the allele A was no obvious changed  and HP2 (AGCGCCG) were two haplotypes associated with the PSL. The rs339135425, rs325197091 and rs322755731 were the different SNPs between those two haplotypes. In the meanwhile, rs325197091 was the most significant SNP and resided behind one of the predicted promoter regions in intron 4. So we suggest that rs325197091 may regulate the intronic promoter activity and then affect the expression of HOMER1–205.P < 0.001). Hence, an independent promoter was suggested in the − 663~ − 276 bp. In addition, the promoter activity of the − 663~ − 276 bp containing the rs339135425 and rs325197091 mutant alleles was significantly higher than of the wild type (P < 0.05).Therefore, a series of truncated intronic promoter luciferase reporter vectors were constructed and identified. The promoter activity of -663~ + 154 bp upstream was significantly higher than − 276~ + 154 bp (P < 0.01) by interfering ARNT while of the wild type was not significantly changed. Thus the mutation of rs325197091 might enhance the HOMER1–205 expression through binding ARNT in vitro. ARNT is the beta subtype of hypoxia-inducible factor (HIF-1), belonging to the basic-Helix-Loop-Helix (bHLH) – PSA (Per-Amt-Sim) family of proteins involved in cell differentiation and glycolysis which is highly expresses in skeletal muscle tissue. It can interact with HIF-1α and participates in solution and other physiological or biochemical pathways [HOMER1 in PSL.ARNT was the transcription factor predicted binding on rs325197091. The promoter activity of − 663~ + 154 bp mutant type was reduced Primers for gene Polymorphism detection. A table of all the primers’ sequences, Tm, and product size using for detecting polymorphisms in Additional file 2:Primers for vector construction. A table of all the primers’ sequence, Tm and the lengths of fragments inserted using for vector construction, as well as the vectors’ name. The italics are the protect base, and the double marked are the enzyme locus. (DOCX 16 kb)Additional file 3:HOMER1 gene intronic promoter predicted by Neural Network Promoter Prediction. A table of all the promoter elements’ locations and sequences resided on the region upstream the exon 5 of HOMER1–205 transcript predicted by Neural Network Promoter Prediction. The ATG of HOMER1–205 was assigned as + 1. (DOCX 16 kb)Pig Additional file 4:HOMER1 gene promoter at 5′ end region by Neural Network Promoter. A table of all the promoter elements’ locations and sequences resided on the region upstream the exon 1 of HOMER1–201 predicted by Neural Network Promoter Prediction. The ATG of HOMER1–201 was assigned as + 1. (DOCX 16 kb)Prediction of pig Additional file 5:P-value associated with the PSL. (DOCX 16 kb)The frequencies of haplotypes of Block1. A table of all the haplotypes’ frequencies in block and the Additional file 6:Transcription factors binding on the allele of rs325197091 predicted by JASPAR. A table of all the predicted transcription factors’ names and target sequences binding on the wild or mutant allele of rs325197091. (DOCX 16 kb)


Trypanosoma brucei is highly unusual: virtually all genes are co-transcribed from multigene transcription units, with mRNAs generated by linked trans-splicing and polyadenylation, and transcription initiation sites display no conserved promoter motifs. Here, we describe the genome-wide distribution of R-loops in wild type mammal-infective T. brucei and in mutants lacking RNase H1, revealing both conserved and diverged functions. Conserved localization was found at centromeres, rRNA genes and retrotransposon-associated genes. RNA Pol II transcription initiation sites also displayed R-loops, suggesting a broadly conserved role despite the lack of promoter conservation or transcription initiation regulation. However, the most abundant sites of R-loop enrichment were within the regions between coding sequences of the multigene transcription units, where the hybrids coincide with sites of polyadenylation and nucleosome-depletion. Thus, instead of functioning in transcription termination the most widespread localization of R-loops in T. brucei suggests a novel correlation with pre-mRNA processing. Finally, we find little evidence for correlation between R-loop localization and mapped sites of DNA replication initiation.R-loops are stable RNA–DNA hybrids that have been implicated in transcription initiation and termination, as well as in telomere maintenance, chromatin formation, and genome replication and instability. RNA Polymerase (Pol) II transcription in the protozoan parasite  One example of trans R-loop formation is seen during the prokaryotic CRISPR-cas defence system  in T. brucei is transcribed from a small number (∼200) of multigene transcription units, with little evidence for functional grouping within the units  FBS  and 1% (v/v) penicillin-streptomycin solution (Gibco) at 37°C and 5% CO2. Heterozygous (–/+) and homozygous (–/–) Tbrh1 knockout cell lines were generated using two constructs containing cassettes of either blasticidin or neomycin resistance genes between α-β tubulin and actin intergenic regions, flanked by sequences homologous to the 5′ and 3′ UTRs of TbRH1, essentially as described in . Homologous flanking regions were PCR-amplified using the following primers: 5′ UTR CGACGGGATCCTTGCCTTACCCGTGTTTT and CGACGTCTAGACCTTTTCTTTCCCATGGAC, 3′ UTR CGACGCCCGGGAGGTGTGTATGGGAATGA and CGACGCTCGAGGCACCACCCAGTATAGAAA.All cell lines used were BSF 8 cells were grown to log phase before fixing in 1% formaldehyde for 5 min whilst shaking at room temperature, before 1 ml of 10× glycine buffer was added directly to the cells to stop fixation. Cells were then pelleted, re-suspended in Glycine Stop-Fix Solution and shaken at room temperature for 5 min. Cells were next lysed, according to the manufacturer's protocol, allowing chromatin to be extracted and digested for 5 min with Enzymatic Shearing Cocktail at 37°C to produce ∼200 bp fragments. IP was performed overnight at 4°C with 4.5 ng of S9.6 antibody (Kerafast). For DRIP-qPCR analysis each replicate chromatin sample was divided in two, allowing parallel IP reactions to be performed, one of which was subjected to Escherichia coli RNase HI treatment, essentially as described in (DRIP was performed using a ChIP-IT Enzymatic Express kit (Active Motif). Briefly, ∼2 × 10ribed in .https://github.com/FelixKrueger/TrimGalore) under default settings before alignment to a ‘hybrid’ reference genome consisting of the TRUE-927 v5.1 core chromosome assembly, plus sequences of 14 Lister 427 VSG ES and 5 mVSG ES (Library preparation was performed using a TruSeq ChIP Library Preparation Kit (Illumina) and fragments of 300 bp, including adaptors, were selected with Agencourt AMPure XP (Beckman Coulter). Sequencing was performed with an Illumina NextSeq 500 platform. Reads were trimmed using TrimGalore  and cDNA was generated with the SuperScript™ First-Strand Synthesis System  using random hexamers. In both cases 21 μl qPCR reactions were set up with 10 μl SYBR™ Select master mix (Applied Biosciences™), 350 nM each primer and 1 μl diluted DRIP/cDNA sample. qPCR was run with the 7500 Real Time PCR system (Applied Biosystems®) as follows: 10 min at 95°C, 40 cycles of 95°C for 15 s and 60°C for 1 min. Relative mRNA fold-change between WT and Tbrh1–/– samples was calculated with the 2–ΔΔCt method ((input-IP).In the case of DRIP-qPCR, DRIP samples were prepared as for DRIP-seq above. For RT-qPCR, RNA extracts were made with 1 × 10t method . For DRIhttps://htseq.readthedocs.io/en/release_0.10.0/count.html]. Counts were normalized between samples using the regularized log expression method as implemented in DESeq2 , and poly(A) selection and library preparation was performed using the TruSeq Stranded Total RNA kit (Illumina). 75 bp paired-end reads were generated using an Illumina NextSeq 500 platform. After trimming with Trim Galore, reads were aligned to a ‘hybrid’ reference genome . Alignment was carried out using Hisat2   and readn DESeq2  and normT. brucei hybrid genome. The results of whole genome analysis were converted into bigwig format and skew was plotted over regions of interest with deepTools analysis software.GC and AT skew were calculated as (G-C)/(G+C) and (A-T)/(A+T), respectively. Skew was calculated either in 11 bp windows  or in 100 bp windows across the Saccharomyces cerevisiae , allowing comparison of the mapping profiles. TbRH1 mutants were generated by two rounds of allele replacement, with the resulting Tbrh1–/– null cells found to be viable and to grow in culture at the same rate as WT BSF cells .RNA–DNA hybrid immunoprecipitation (DRIP), either on cross-linked or ‘naked’ DNA, has been used in a number of organisms, with some experimental variations based on treatment of the nucleic acid components, the mode of genome fragmentation and whether the recovered nucleic acid was analysed by sequencing, microarray hybridization or qPCR . Here, wrevisiae ,28,86,87es pombe  and Arabthaliana . To provi genome . To compT. brucei genome revealed very widespread coverage  was performed in parallel with the IP reactions , we, weT. brs Figure ; this dis Figure  further s Figure , since momosomes . DRIP-seomosomes  in both s Figure , indicats Figure –C. To ens Figure . EcRHI ts Figure . In addi R-loops ,86. Very. brucei  and compr Figure .T. brucei protein-coding genes can also be transcribed by RNA Pol I, including procyclin and VSG. DRIP-seq enrichment was notably greater in each of these loci than in the rRNA , while DRIP-seq patterns at the procyclin loci and metacyclic (m) VSG expression sites, both of which display gene expression repression in this life cycle stage . Why DRIP-seq signal was observed across the procyclin loci  genes in /– cells , with thT. cruzi ,97. MembT. cruzi  and planT. cruzi , RHS locT. cruzi .Tbrh1–/– cells most pronounced in inter-CDS regions  and a very limited effect on gene expression, since RNA-seq comparing WT and Tbrh1–/– cells found only five genes with clearly changed abundance, three of which were VSGs , this slight increase may not be the result of increased R-loops at the coding region. Indeed, plotting of DRIP signal over genes that appeared to have intra-CDS DRIP-seq enrichment and those that do not, showed little difference in DRIP profile, indicating intra-CDS R-loops are weakly enriched compared to those at the flanking sites  in both WT and Tbrh1–/– cells  tract Figure , suggests Figure . Heatmaps Figure , though nylation ,98, as ss Figure . Visualis Figure , suggests Figure . In conts Figure .n, 110), and therefore proximal to the transcription start sites, and all others , which are distal to the transcription start site and internal to the PTU. In both cases a pattern of DRIP-seq enrichment was revealed  mRNAs  mRNAs . The neathaliana . Intra-Ced genes . In T. b unknown . Given tn Figure .trans-splicing of multigene precursor RNA  tail is guided by a polypyrimidine tract and AG sequence upstream of ORFs that predominantly dictate splicing  tracts was also identified is less clear, since such a feature has not been linked with trans-splicing or polyadenylation in PTUs. These data reveal a previously undescribed association between R-loops and mRNA processing. In yeast and humans, mapping of R-loops shows their abundance and density to be lower in intron-rich genes compared with genes lacking introns, at least in part because recruitment of the splicing machinery suppresses R-loop formation   , the epirminate) ,112 do nT. brucei R-loops with initiation of multigenic transcription, the DRIP-seq data provides less compelling evidence for a role in termination, since signal enrichment at the ends of PTUs, such as within convergent SSRs, is less pronounced. In addition, where peaks are seen at such sites they frequently localize to tRNAs. The limited enrichment we describe contrasts with the strong localization of R-loops at gene termination sites in other eukaryotes  in RNA Pol II transcription termination telomeric R-loops might contribute to kinetoplastid biology, such as the expression or stability of telomere-proximal genes, has been little explored.Repeat sequences are well-established loci for the accumulation of R-loops, and several examples of this association are seen in karyotes ,120 and karyotes ; as the karyotes ? Third,  hybrids . However hybrids ,122, andfication  or cell fication , despitefication ,126. Fin. brucei  and Leisishmania  has revehttp://tritrypdb.org/tritrypdb/) in an upcoming release.Sequences used in the mapping have been deposited in thean European Nucleotide Archive (accession number PRJEB21868). DRIPseq analysis will be hosted at TriTrypDB (Supplementary DataClick here for additional data file.


FSHR gene that interact with transcription factors to regulate FSHR transcription. In this study, DNA sequencing was used to identify SNPs in the FSHR promoter sequence in both Dongxiang and Suken chickens. To detect the activity of the chicken FSHR gene promoter, we analysed the characteristics of the sequence and constructed three deletion vectors. We confirmed that the region (−18/−544) was the core promoter. Furthermore, five polymorphisms, including a 200‐bp indel at −869, C−1684T, C−1608T, G−368A and T−238A, were detected in both the Dongxiang and Suken chickens. The age at first egg (AFE) for different genotype of −869 indel in Suken chicken was significantly different (p < 0.01). For SNP C−1684T in Dongxiang chickens, the CC genotype had higher egg number at 43 weeks of age (E43) than that of the TC genotype (p < 0.05). For SNP C−1684T in Suken chickens, the TC genotype had higher AFE than that of the CC genotype (p < 0.05). For SNP C−1608T in Suken chickens, the CC genotype had higher AFE than that of the TC genotype (p < 0.05). For SNP G−368A in Suken chickens, the AG genotype had higher AFE than that of the GG genotype (p < 0.05).Egg production is an important economic trait in poultry, and it is of great significance to study the key genes and functional SNPs that affect egg laying performance. Follicle‐stimulating hormone (FSH) plays an important physiological role in the reproductive performance of humans and animals by binding to its receptor (FSHR). Studies have shown that there are many transcriptional regulatory elements in the 5′ flanking region of the  Mice developed follicular dysplasia after FSHR gene knockout in granulosa cells  and Suken chickens (n = 434) from Jiangsu Xincao Farm. The chicken was bred in cages (one chicken per cage) with the same feeding and management conditions. We recorded the age at first egg (AFE) and egg number at 43 weeks of age (E43) of every chicken.The chicken populations used for the experiment were Dongxiang  from chicken wings and stored it at −20°C. The DNA was extracted by a conventional phenol–chloroform extraction method , 10 pmol of upstream and downstream primers and 100 ng of chicken genomic DNA. The following reaction conditions were used: 95°C pre‐denaturation for 5 min, 95°C denaturation for 30 s, X°C , including two TATA‐boxes (TBP binding site), three CAAT‐boxes (C/EBP binding sites), a GC‐box (SP1 binding site) and two E‐boxes (USF1/2 binding sites). In addition, several transcription factor binding sites were enriched in the chicken FSHR proximal promoter sequence, including AP1, SF1, YY1, GATA, FKHD, SP1 and CREB  was defined as +1. The constructed plasmids were identified by double digests . In contrast, no significant difference was observed between pFSHR‐1479, pFSHR‐812 and pGL3‐basic (p > 0.05).PCR product electrophoresis is shown in Figure 3.4FSHR, including ApaI, MboI, NdeI and SspI, respectively. The four single nucleotide polymorphisms and the 200‐bp indel mutation were detected by PCR‐RFLP  (Table p < 0.01). The AFEs of the SNP C−1684T and C−1608T genotypes were also significantly different  in Spodoptera litura‐221 (Spli‐221) cells increased the promoter activity 5.57‐fold, while mutation of the C/EBP CRE abolished the binding of the C/EBP with the CRE  were predicted in the chicken FSHR gene promoter with Genomatix software, including AP1, GATA, SF1, YY1, as well as others. It is noteworthy that the transcription factors E2F, Smad3 and ETS were involved in the transcriptional regulation of the FSHR gene in previous reports , pFSHR‐812 (−830/−18) and pFSHR‐544 (−562/−18). The activity of pFSHR‐544 was significantly higher than that of pFSHR‐basic, pFSHR‐1479 and pFSHR‐812. There is no significant difference in the activity between pFSHR‐1479 and pFSHR‐812 and the pFSHR‐basic. The above studies suggested that the region (−18/−562) contains some positive cis‐regulatory elements, whereas the region  contains some negative transcription factor binding sites.Researchers have identified that the region  was the core promoter of the porcine FSHR gene. It has been widely reported that mutations in the FSHR gene have a genetic effect on reproductive traits in humans and other animals , whereas the SNP A227G is significantly associated with age at first egg stage (p < 0.05)  or age at first egg (AFE).In conclusion, in this study, we identified the core promoter region of the chicken None of the authors have any conflict of interest to declare.Debing Yu and Yinglin Lu designed the experiment. Xiaopeng Li, Xiaofan Liu, Xiaolei Xie and Kun Wang completed the experiment. Xiaopeng Li wrote and revised the paper.


In this study, Eaton et al. examine the validity of the allosteric and torpedo models of transcription termination on protein-coding genes. Using several genomic and molecular assays, the authors propose a model that combines both allosteric/torpedo mechanisms, in which PP1-dependent slowing down of polymerases over termination regions facilitates their pursuit/capture by XRN2 following poly(A) signal processing. The allosteric and torpedo models have been used for 30 yr to explain how transcription terminates on protein-coding genes. The former invokes termination via conformational changes in the transcription complex and the latter proposes that degradation of the downstream product of poly(A) signal (PAS) processing is important. Here, we describe a single mechanism incorporating features of both models. We show that termination is completely abolished by rapid elimination of CPSF73, which causes very extensive transcriptional readthrough genome-wide. This is because CPSF73 functions upstream of modifications to the elongation complex and provides an entry site for the XRN2 torpedo. Rapid depletion of XRN2 enriches these events that we show are underpinned by protein phosphatase 1 (PP1) activity, the inhibition of which extends readthrough in the absence of XRN2. Our results suggest a combined allosteric/torpedo mechanism, in which PP1-dependent slowing down of polymerases over termination regions facilitates their pursuit/capture by XRN2 following PAS processing. Termination by RNA polymerase II (Pol II) completes the transcription cycle. It serves to recycle Pol II for new rounds of initiation and prevents interference with the transcription of neighboring genes. On protein-coding genes, transcriptional termination is mechanistically connected with 3′ end formation, which involves cleavage and polyadenylation (CPA) . For CPAThe allosteric (or antiterminator) model proposes that transcription of the PAS induces a change in the elongation complex that renders it prone to termination . This miThe torpedo model proposes that the Pol II-associated product of PAS cleavage is degraded by a 5′ → 3′ exonuclease leading to termination . EvidencC. elegans, where XRN2 depletion causes termination defects on only a subset of genes . These slowed-down polymerases pile up beyond the PAS, and their presence, is enriched by rapid depletion of XRN2. Strikingly, longer readthrough can be induced in the absence of XRN2 by inhibiting or depleting protein phosphatase 1 (PP1), identifying a mechanistic basis for the pause. We propose that allosteric events facilitate the pursuit of Pol II and its termination by XRN2 constituting a unified allosteric/torpedo mechanism for transcriptional termination on human protein-coding genes.E. coli-derived DHFR degron caused more extended readthrough of selected genes, implying a comparatively more important role for its activities in termination. The DHFR degron requires ∼10 h for depletion, whereas XRN2-AID could be depleted faster, so we tagged CPSF73 with an AID to better-compare CPSF73 and XRN2 functions , causes a general termination defect on protein-coding genes . In the unctions . AID deppression .CPSF73-AID cells or the same cells treated with dox and then auxin. Chromatin-associated RNA was sequenced because it is highly enriched in the nascent transcripts that we wished to study. Rapid depletion of CPSF73 caused very obvious and widespread transcriptional readthrough as shown by the chromosome snapshot in MAP2K4 and YTHDC2) further detail this effect where readthrough is for hundreds of kilobases , and more reminiscent of that observed on some genes upon cell stress or viral infection . The extensive nature of the CPSF73 readthrough also highlights transcriptional interference in cis. ERRFL1 reduces the expression of the convergent PARK7 gene. Finally, CPSF73 depletion did not affect integrator-dependent snRNA gene termination demonstrating the specificity of these effects . We conclude that functions of CPSF73 are indispensable for Pol II termination on protein-coding genes.A termination defect in the absence of CPSF73 is not unexpected; however, the effect here is much greater than previously observed using RNAi  before treatment or not with auxin to remove XRN2. Chromatin-associated and nucleoplasmic RNA was isolated as we anticipated that termination products might be released from chromatin. To check the validity of this approach, quantitative reverse transcription and PCR (qRT-PCR) was performed to detect a PROMPT transcript upstream of RBM39, which is a well-characterized exosome substrate. This was strongly stabilized by exosome depletion, validating siRNA function, with the effect largest in the nucleoplasmic fraction .A reasonable explanation for this difference is XRN2-independent termination that still requires CPSF73 . This meMYC and TRIB1 were two exceptions that showed an additional nucleoplasmic increase, which may indicate some XRN2-independent termination on those genes. However, these examples were still less sensitive to exosome loss than the RBM39 PROMPT control. In our view, these data do not provide convincing evidence for efficient termination in the absence of XRN2.3′ flanking RNA derived from six protein-coding genes was then analyzed B. As expMORF4L2 gene to include an XRN-resistant RNA (xrRNA). Isolated from West Nile virus, the xrRNA forms a structure that impairs 5′ → 3′ exonucleases and can be used to probe the directionality of RNA decay . We performed this gene editing in our recently described DIS3-AID cells in which the major catalytic subunit of the exosome, DIS3, can be rapidly depleted by auxin .These findings imply that degradation of 3′ flanking RNA is commonly unidirectional. To probe this more sensitively, we used CRISPR–Cas9 to edit the NA decay . MORF4L2by auxin . Total Rnsertion D. SimilaMORF4L2 in XRN2-AID cells to inhibit 5′ → 3′ degradation generally. RNA was isolated from XRN2-AID cells modified or unmodified at MORF4L2 following treatment or not with auxin. qRT-PCR analysis of readthrough transcription showed that RNA between the PAS and xrRNA was stabilized only when XRN2 was depleted as expected  downstream from expected E. SimilaMORF4L2 in xrRNA-modified and unmodified XRN2-AID cells without depletion of XRN2 .Data so far show that CPSF73 loss causes runaway readthrough, which is much less extensive when XRN2 is depleted. This difference is not due to efficient XRN2-independent mechanisms or other 5′ → 3′ exonucleases, active when XRN2 is eliminated. We therefore hypothesized that Pol II accumulating beyond the PAS when XRN2 is eliminated is slowed rather than terminated and that this is why readthrough is shorter than in the absence of CPSF73. To interrogate this, we performed Pol II ChIP on el genes A. Auxin ACTB and MYC in CPSF73-AID and XRN2-AID cells grown with or without auxin and observed its expected enrichment beyond the PAS in control samples (We next assayed whether the difference in Pol II behavior caused by XRN2 vs CPSF73 depletion is associated with any changes in its modification status. The CTD of the largest Pol II subunit is heavily modified during the transcription cycle . Thr4p i samples B. XRN2 lRBM3 was modified with (δRZ[WT/MT]) in CPSF73-AID and XRN2-AID cells and was chosen as an alternative to MORF4L2 . The RZ was inserted just downstream from where termination normally occurs and loss of XRN2 induces some transcription beyond the insertion site . If, in the absence of XRN2, the ultimate position of Pol II occupancy defines an auxiliary termination site, then most Pol II should transcribe the RZ when XRN2 is depleted. If instead most Pol II accumulates upstream of the RZ when XRN2 is eliminated only a fraction will transcribe beyond it. CPSF73-AID cells act as a control because its depletion induces profound readthrough beyond the RZ insertion site .Reduced Pol II occupancy beyond the PAS is usually interpreted as consequential of transcriptional termination. Our data argue that XRN2 depletion enriches polymerases that can neither elongate well nor terminate. We designed an experiment to test this more directly using a hepatitis δ ribozyme that cleaves very efficiently and can be inactivated by a single mutation (δRZ[WT/MT]) . RZ cleaCPSF73-AID cells and unmodified CPSF73-AID cells treated or not with auxin . As expected, the 3′ cleavage product cannot be degraded as its accumulation is similar in δRZ[MT] and δRZ[WT] scenarios.qRT-PCR was performed to look at readthrough in δRZ[WT/MT]-modified th auxin A. In unmXRN2-AID cells, δRZ[MT]-modification of RMB3 gives a similar result to unmodified XRN2-AID cells in that XRN2 depletion leads to stabilization of 3′ flanking region RNA .In gion RNA B. For thACTB and MYC in XRN2-AID cells treated with auxin, the selective PP1 inhibitor, tautomycetin  confirmed that PP1 depletion enhances readthrough when XRN2 is eliminated. An additional protein phosphatase inhibitor, Calyculin A, was used to further confirm the protein phosphatase effect on extended ACTB readthrough . The combined interpretation of this ChIP and qRT-PCR is that PP1 is important for Pol II slowing after the PAS and for its efficient capture and termination by XRN2.Mass spectrometry identified PP1α and β isoforms as components of the 3′ end processing complex . We therID cells C. We theID cells D. DepletNLS-RNASEH1). Because the requisite puromycin-resistance marker had been used in CPS73-AID cells (to introduce TIR1), dox-inducible NLS-RNASEH1 was integrated into our previously described CPSF73-DHFR cell line  GapmeR-induced cleavage , perhaps because their RNAs undergo 3′ end cleavage by RNaseP/Z  transfected with control or ETF1 GapmeRs  promotes Thr4p with PP1 activity playing an important role in slowing Pol II down to facilitate its capture by XRN2. The allosteric events most likely aid XRN2 rather than acting as a separate or mutually exclusive termination pathway because cleavage of primary transcripts promotes termination in the absence of CPSF73 and outside of a PAS context. Consequently, we propose that the long-standing allosteric and torpedo models for transcriptional termination can be unified into a single mechanism with XRN2 likely providing the termination activity E.MYC and TRIB1) cases. However, 3′-flanking transcripts were always much more sensitive to XRN2 loss than to exosome depletion and remained largely chromatin-associated under all circumstances. While there may be inefficient or stochastic XRN2-independent termination, it does not seem to be linked by a common mechanism. We do not rule out XRN2-independent termination that evades our detection or that occurs on certain genes, but our subsequent finding that PP1 inhibition causes longer readthrough when XRN2 is depleted argues against efficient alternatives.This conclusion followed from our failure to detect efficient/general XRN2-independent termination, although we did observe some evidence for this in two  in termination is to provide an end for XRN2, otherwise alternative cleavage would not function in its absence. It also demonstrates that CPSF73-dependent changes occurring beyond the PAS facilitate termination  rather than directly contributing. This is consistent with the ability for XRN2 to promote termination in vitro in the absence of other factors . This exHCT116 cells were cultured in DMEM (high glucose) containing penicillin/streptomycin and 10% FBS at 37°C. DNA transfections were done with Jetprime (polyplus) and RNAi with Lipofectamine RNAiMAX (Life Technologies) following the manufacturers’ guidelines. Two siRNA transfections were used: the second 24 h after the first and RNA isolation 48 h after that. PP1 RNAi was performed using a single siRNA transfection with RNA isolated 72 h later. GapmeRs were transfected at 10 nM in 24-well or 100-mm dishes for RNA and ChIP experiments, respectively. This was done using 1.5 or 10 μL of Lipofectamine RNAiMAX in a final combined volume of 50 or 500 μL of OptiMEM (Life Technologies). Dox was used at 1 μg/mL, auxin was used at 500 μM, tautomycetin was used at 500 nM, PlaB was used at 1 nM, and calyculin A was used at 5 nM. TMP was used at 20 μM and withdrawn for 12 h to deplete CPSF73-DHFR.XRN2-AID and CPSF73-eDHFR cell lines are previously described (NLS-RNASEH1 was synthesized by Integrated DNA Technologies and cloned into pMK243 (Addgene 72835) digested with MluI and BglII. This plasmid was transfected with AAVS1 T2 CRISPR plasmid (Addgene 72833), and colonies were selected in 1 μg/mL puromycin. The CPSF73-AID cell line was made by generating plasmids containing a 5′ homology arm – AID – P2A – HYG/NEO – SV40 PAS – 3′ homology arm. We have published the sequences of each of these elements  flanked with homology arms. Positive clones were selected by growth in 0.5 μM ouabain. Insertions were confirmed by Sanger sequencing.The escribed . NLS-RNAelements . These, election . gRNA seThe following antibodies were used: CPSF73 (Bethyl Laboratories A301-090A), Tubulin (Abcam Ab7921), HA (Roche 3F10), Thr4p (Active Motif 6D7), EXOSC10 (Santa Cruz Biotechnology Sc-374595-X), PP1α (Bethyl Laboratories A300-904A), PP1β (Bethyl Laboratories A300-905A), and RNA Pol II (MBL Technologies CMA601 and Abcam 8WG16). Note that CMA601 was discontinued during our study and used in RNA was isolated using tri-reagent and, following DNase treatment, 1 μg was reverse transcribed  with random hexamers. cDNA was diluted to 50 μL in water and 1 μL was used per qPCR, performed with LUNA qPCR reagent (New England Biolabs) in a Qiagen Rotorgene instrument.2, 0.5% NP40); this was underlayered with HLB + 10% sucrose and spun at 500×g for 5 min. Nuclei were resuspended in 100 μL of NUN1 buffer  and then topped up with 1 mL of NUN2 . After incubation for 10 min on ice with mixing every 2–3 min, samples were spun at 13,000 rpm for 10 min. Chromatin pellets were resuspended in 500 μL of Tri-reagent and RNA was isolated with Trizol as above. Nucleoplsamic RNA was extracted from the supernatant by phenol chloroform and ethanol precipitation.A six-well dish of cells was lysed in in HLB  and then with auxin/EtOH (3 h). Nuclear RNA-seq was performed following treatment with dox (18 h) and then auxin/EtOH (3 h). Five-hundred nanograms was rRNA depleted using the Ribozero kit, and libraries were prepared with the tru-seq stranded kit and sequenced on an illumina Hi-seq 2500. Data processing steps are described in the A semi-confluent 100-mm dish of cells was cross-linked in 1% fomaldehyde for 10 min before quenching in 125 mM glycine. Cells were pelleted and resuspended in 350 μL RIPA buffer  before sonication in a Bioruptor for 30 sec on and 30 sec off 10 times on high. Cross-linked chromatin was divided into two: Half was incubated with 40 μL of sheep antimouse/sheep antirat Dynabeads (Life Technologies) preincubated with 3 μg of Pol II/Thr4p antibody for 2 h at 4°C, and the other half with beads incubated without antibody. Following rotation for 3 h at 4°C, beads were washed twice in RIPA buffer, three times in ChIP wash buffer , and twice in RIPA buffer (ChIP wash washes were not used for Thr4p). DNA was eluted in 0.1 M NaHCO3/1% SDS with rotation for 30 min at room temperature. Eluate was added to 30 μL of 5 M NaCl and cross-links were reversed overnight at 70°C. DNA was purified by phenol chloroform extraction and ethanol precipitation and resuspended in 50 μL of water. One microliter was used per qPCR.XRN2-AID cells (GSE109003); chromatin and nuclear RNA-seq of CPSF73-AID cells (GSE137727); CPSF73 RNAi chromatin RNA-seq (GSE60358).RNA-seq and mNET-seq of Supplemental Material.All DNA sequences are provided in the