Drosophila provides a model for understanding how chromatin organization can modulate coordinate gene regulation. Male Drosophila increase the transcript levels of genes on the single male X approximately two-fold to equal the gene expression in females, which have two X-chromosomes. Dosage compensation is mediated by the Male-Specific Lethal (MSL) histone acetyltransferase complex. Five core components of the MSL complex were identified by genetic screens for genes that are specifically required for male viability and are dispensable for females. However, because dosage compensation must interface with the general transcriptional machinery, it is likely that identifying additional regulators that are not strictly male-specific will be key to understanding the process at a mechanistic level. Such regulators would not have been recovered from previous male-specific lethal screening strategies. Therefore, we have performed a cell culture-based, genome-wide RNAi screen to search for factors required for MSL targeting or function. Here we focus on the discovery of proteins that function to promote MSL complex recruitment to “chromatin entry sites,” which are proposed to be the initial sites of MSL targeting. We find that components of the NSL  complex, and a previously unstudied zinc-finger protein, facilitate MSL targeting and display a striking enrichment at MSL entry sites. Identification of these factors provides new insight into how MSL complex establishes the specialized hyperactive chromatin required for dosage compensation in Drosophila.Sex chromosome dosage compensation in  Drosophila melanogaster is a chromatin-modifying complex that specifically regulates a large number of genes. The MSL complex targets active genes on the single male X chromosome to upregulate their output to match both female X chromosomes. How the MSL complex specifically targets the X chromosome and upregulates active genes is only partially understood. In order to increase our understanding of gene regulation at a mechanistic level, we performed a genome-wide genetic screen in male cells to identify factors that facilitate MSL targeting and function. Our results identify two chromatin-associated protein complexes and a new candidate DNA binding protein as key factors in MSL–based regulation. We also provide an extensive list of additional candidate genes to be examined in future studies.Gene regulation is essential to all living things. For example, levels of gene expression in individual cells must be fine-tuned during development and in response to changing environmental conditions. Genes are regulated by DNA binding proteins and by factors that influence DNA packaging into chromatin. The MSL complex in  Drosophila provides a model for understanding how a large number of diversely regulated genes along the length of a single chromosome can be targeted for coordinate regulation. In Drosophila, the transcript levels of genes along the length of the single male X-chromosome are upregulated approximately two-fold, a process mediated by the MSL  histone acetyltransferase complex X-chromosome dosage compensation in male While significant progress has been made towards understanding how MSL complex is targeted and functions, much remains to be understood. For example, since MREs are less than two-fold enriched on the X-chromosome Seminal genetic screens identified five core components of the MSL complex by isolating genes that were specifically required for male viability Therefore, we designed a cell-based reporter system that specifically monitors MSL function at chromatin entry sites, and conducted a genome-wide RNAi screen to identify genes required to regulate this reporter. We identified the NSL roX2 gene (370 bp); 2) Firefly luciferase reporter gene; 3) MSL complex binding site for roX2 (DNase I Hypersensitivity Site: 280 bp). The system is based on a similar one that functions as a male-specific MSL-dependent reporter in vivoDrosophila RNAi Screening Center (DRSC) that contains approximately 21,000 dsRNAs was screened in duplicate (www.flyrnai.org). To eliminate off-target effects, secondary screens were conducted using a set of validation RNAi constructs in addition to rescreening the original constructs.In order to identify genes that regulate MSL complex recruitment or function, we performed a genome-wide RNAi screen using an MSL-dependent cell-based reporter system for which we previously reported functionality roX2 promoter and specific CES used in the genome-wide screen; 3) We then used known functional information about the genes to narrow the list to those that have potential direct activating roles; 4) We determined whether new proteins affect MSL complex recruitment at endogenous sites without altering transcription of MSL complex components; 5) We performed genome-wide localization analysis to determine whether new proteins are enriched at CES loci.In addition to direct regulators of MSL complex recruitment or function, several additional types of genes could be identified by our RNAi screen. Therefore, we used the following steps to identify potential direct activators of MSL complex targeting: 1) To reduce the number of non-specific regulators of luciferase gene transcription and protein stability that were identified, we calculated the ratio of activity from our MSL-dependent Firefly luciferase reporter to a heterologous Renilla luciferase reporter. 2) We used multiple MSL-dependent reporters to further narrow the list of genes to those that function independently of the As briefly described above, we first normalized the MSL-dependent Firefly luciferase reporter activity to an MSL-independent reporter including the Renilla luciferase gene that can be independently assayed using a different substrate. This dual Firefly/Renilla approach also controls for technical variation in transfection efficiencies among wells and differences in cell number caused by altered viability after RNAi treatments. We used a Renilla construct that was regulated by an Actin promoter as previously described msl2 RNAi) and two negative control (GFP RNAi) constructs, that were previously validated. After confirming that at least a 5-fold dynamic range was observed in the expected activity of positive and negative controls on each plate, the Firefly/Renilla ratios of the two plates were averaged and screening hits were identified relative to the median Firefly/Renilla ratio for each plate  Ribosomal protein genes that are identified by many RNAi screens (41 genes); 2) Genes with a large number of predicted RNAi off targets using 17 bp as an overlap cutoff Class 1 (18 genes): General transcriptional regulators that activate our reporter; 2) Class 2 (6 genes): Proteins that have potential sequence-specific DNA binding activity and activate our reporter; 3) Class 3 (7 genes): General transcriptional regulators that repress our reporter; 4) Class 4 (3 genes): Proteins that have potential sequence-specific DNA binding activity and repress our reporter; 5) Class 5 (7 genes): Proteins that regulate RNA metabolism ; 6) Class 6 (26 genes): Proteins that are previously unstudied and/or have functions unrelated to transcription or RNA metabolism. The remaining genes are known MSL complex components. Members of each of these classes could directly modulate MSL recruitment or activity or indirectly effect MSL complex by altering complex levels.To narrow our list of candidate genes, we classified genes into categories based on their activity in our assay and previously determined functional information about the gene products as follows : 1) ClasDue to the large number of genes identified, we focused on potential direct regulators of MSL complex recruitment or function that had known roles in transcriptional regulation or potential DNA binding domains (Classes 1–4). This analysis identified 34 potential transcriptional regulators. We validated the activity of these candidate genes using our MSL-dependent reporter assay in a more accurate 96-well format . OverallroX gene transcription in vivoroX1 CES In addition to identifying all core components of MSL complex as activators of our reporter system , we idenThe transcription of MSL complex components could be modulated and thus indirectly affect its function. Therefore, we selected candidates and examined whether they function directly to recruit MSL complex to CES loci using several approaches: 1) Determine whether RNAi against candidate genes affects recruitment of MSL complex to endogenous CES; 2) Define whether RNAi knockdown of candidates alters transcription of MSL complex components; 3) Examine the recruitment of candidate proteins to CES loci. We hypothesized that direct regulators of MSL complex recruitment will be recruited to CES loci and alter MSL complex recruitment but not transcription of MSL complex components. Using these approaches, we examined the function of three factors: 1) the NSL complex; 2) the PAF complex; and 3) CG1832.We selected NSL complex for further study because six of its components  were identified in our screen and NSL and MSL complexes share the MOF catalytic component. NSL1 is one of the structural components of NSL complex that directly contacts MOF using a similar protein-protein interaction surface as MSL1 S. cerevisiae SAGA complex component Ubp8 Drosophila) We also examined the PAF transcription complex that associates with RNAP II across gene bodies to promote transcription elongation in vivo.The previously-unstudied CG1832 zinc finger protein was chosen for further study because it was identified three independent times using different double-stranded RNA constructs and exhibits a very strong reporter activation phenotype. Furthermore, unlike other potential DNA binding proteins, CG1832 RNAi does not decrease cell viability significantly and was not identified by other RNAi screens. Similarly, loss of MSL complex components does not significantly alter cell viability although it causes male-specific lethality in flies. The CG1832 protein has a glutamine rich N-terminus and a seven zinc finger domain at its C-terminus. Because each finger is likely to recognize three bases in vivo  of the MSL2 core component in male SL2 cells. We found that both NSL1 and CG1832 RNAi knockdowns significantly reduce MSL2 recruitment to several CES loci in vivo . Next, win vivo .roX1 is not expressed at significant levels in SL2 cells roX2 RNA levels as expected because roX2 is activated by MSL complex, but little effect on the mRNA levels of other MSL complex components. Also, NSL1 and CG1832 RNAi treatments do not affect mRNA splicing of MLE as reported for the Znf72D zinc finger protein (data not shown) To examine whether NSL1 and CG1832 RNAi treatments disrupt MSL complex recruitment due to regulation of MSL complex component mRNA levels, we assayed these by qRT-PCR . roX1 iswww.modENCODE.org). Therefore, we analyzed the enrichment of these proteins at CES loci compared with other sites that contain MRE sequences. Results indicate that there is a broad enrichment of NSL complex components within a 10 kb region surrounding CES compared to additional genomic loci on the X and autosomes that contain MREs  or on more laborious assays for MSL occupancy. Many of the regulators that we have identified are likely to have additional functions in both male and female flies and therefore could not have been recovered from classical male-specific lethal genetic screens. In addition to direct regulators of MSL complex recruitment, it is possible that transcriptional regulators identified from our screening approach could function indirectly to regulate transcription of MSL complex components themselves. Therefore, we used chromatin immunoprecipitation and existing modEncode data to demonstrate that two factors, the NSL complex and CG1832, are likely to have local roles in MSL complex recruitment to CES. Moreover, CG1832 is a strong candidate to recruit MSL complex directly to CES due to its strong enrichment at MRE sequences.Using a novel cell-based RNAi screening approach, we have identified new candidate regulators of MSL complex function. The screen took advantage of the ∼five fold regulation of a Interestingly, we identified a previously unstudied function of the highly-conserved NSL complex at CES loci. NSL and MSL complex share the MOF histone acetyltransferase as their catalytic component S. cerevisiae SAGA complex component Ubp8 Many additional activators were identified from our RNAi screening approach including all components of the PAF transcription complex that associates with RNAP II across gene bodies to promote transcription elongation and polyadenylation roX CES loci In addition to identifying activators of MSL-dependent reporter activity, we identified several repressors including NURF301, a known repressor of MSL complex function at the Our most exciting new candidate is CG1832, a previously unstudied zinc-finger protein that is strongly and precisely enriched at MRE sequences within CES and facilitates MSL complex recruitment to these sites. This protein has seven zinc-fingers at its C-terminus that could potentially bind DNA and a glutamine-rich N-terminus that may interact with MSL complex. Therefore, future analyses will focus on the exciting possibility that CG1832 functions as a previously unknown link between MSL complex and MRE sequences.In summary, our novel screening approach identified two regulators that facilitate MSL complex recruitment at CES: NSL complex and CG1832. Furthermore, our genetic screen provides an extensive dataset of additional candidate genes that may facilitate MSL targeting and function. We expect that future genetic, genomic, and biochemical approaches will define new mechanisms by which many of these candidate genes modulate coordinate gene regulation.www.flyrnai.org) A genome-wide RNAi screen was performed in duplicate using the version 2 RNAi libraries generated by the Drosophila RNAi Screening Center . All RNAi treatments were conducted for 5 days in SL2 cells as previously described mRNA analysis and qRT-PCR was performed after the following RNAi treatments: 1) DRSC03718 to target CG1832; 2) DRSC15625 to target NSL1 (CG4699); and 3) DRSC27502 to target PAF1  was used at a 1∶10,000 dilution, and the histone H3 antibody (Abcam) was used at a 1∶1000 dilution.Western blotting was conducted as previously described using standard protocols www.flyrnai.org): 1) DRSC03718 to target CG1832; 2) DRSC15625 to target NSL1 (CG4699); and 3) DRSC27502 to target PAF1 (atms). To assure reproducibility, large scale RNAi experiments were performed in which 225 ug of each dsRNA was added to a T225 flask containing 45 mls of SL2 cells. An additional CG1832 RNAi construct (DRSC 29935) was also tested with similar results (data not shown).Chromatin immunoprecipitation from SL2 cells was conducted as described previously Three independent chromatin preparations were performed for each experiment and qPCR was performed on input and IP samples using primers that are specific for MSL target genes and CES loci. Primer sequences were previously described www.illumina.com). To obtain sufficient starting material, three IPs were pooled and concentrated using Qiagen MinElute columns such that 15 ng of starting material were obtained prior to library preparation. Libraries from matching input samples were also prepared for each chromatin preparation. Each enzyme reaction was followed by purification using AMPure XP Beads (Agilent). The fragmented DNA was 3′ end repaired and 5′ phosphorylated using End-it Kit (Epicentre). A 3′ adenosine was added using Klenow Fragment (3′→5′ exo) (NEB). The annealed adapters were ligated in a 1∶50 dilution of the 10 mM stock using T4 DNA Ligase Quick Ligase Kit (Enzymatics). The libraries were PCR amplified using Phusion high fidelity polymerase (NEB) for 15 cycles. The libraries were then size selected on a 2% agarose gel using the E-Gel system (Invitrogen) selecting a range from 200 bp to 500 bp followed by concentration on a MinElute Column (Qiagen). Sequencing was performed on the Illumina GaIIx platform.Duplicate ChIP-seq libraries from independent chromatin preparations were generated using a protocol adapted from the Illumina ChIP-seq sample preparation guide as follows Replicate #1 CG1832 IP: 27820142 raw reads, 19210177 aligned reads (69.1%)Replicate #2 input: 22498098 raw reads, 13510882 aligned reads (60.1%)Replicate #2 CG1832 IP: 28231400 raw reads, 15194724 aligned reads (53.8%)Pearson R value for CG1832 ChIP-seq replicates, 1 kb bins: 0.95Reads aligned with more than one mismatch, and reads that did not align uniquely were discarded. Peaks were called in each ChIP-seq sample using the SPP software package with an FDR threshold of 0.05 The average enrichment profiles of proteins around the MREs (+/−5 kb) are shown in www.modencode.org). Data analysis was performed in R statistical programming environment (http://www.r-project.org). For the visualization of the heatmap  are publicly accessible online through the modENCODE project  qRT-PCR was used to assay the expression levels of all MSL complex components present in SL2 cells. roX2 levels are decreased likely because targeting of MSL complex to the roX2 CES locus is altered by the RNAi treatments as expected. Expression levels of other MSL complex components are unchanged. All data were normalized to the control RNAi treatment and are the average of two replicates. B) Effective RNAi treatments were validated by qRT-PCR and the results shown are the average of two replicates.(TIF)Click here for additional data file.Figure S2Western blots for CG1832 RNAi treatment and antibody validation. A) Westerns on whole cell and nuclear extracts indicate that CG1832 is a nuclear protein and the CG1832 RNAi treatment reduces CG1832 protein levels. The arrow indicates the location of the CG1832 protein (60 kDa) and tubulin was used as a loading control. B) Nuclear extraction was performed on protein samples from SL2  and Kc  cells followed by Western blotting. The histone H3 antibody was used as a loading control. Levels of CG1832 are similar in males and females.(TIF)Click here for additional data file.Figure S3Validation of CG1832 antibody by ChIP at CES loci. qPCR was performed on CG1832 ChIP samples before and after CG1832 RNAi treatment. Three independent CES loci were assayed and CG1832 RNAi strongly reduced the levels of CG1832 protein on chromatin at all three loci. An average of two independent experiments is shown.(TIF)Click here for additional data file.Figure S4Immunostaining of polytene chromosomes. Polytene staining using the CG1832 antibody (red) in male (A) and female (B) larvae. Co-staining was performed with an anti-MSL3 antibody (green). Co-localization of the two proteins is shown in yellow.(TIF)Click here for additional data file.Table S1Initial candidates identified from a genome-wide RNAi screen to identify novel regulators of dosage compensation.(XLSX)Click here for additional data file.Table S2Final candidates identified from a genome-wide RNAi screen. Candidates are color-coded and divided into functional categories described at the bottom of the table.(PDF)Click here for additional data file.


We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when transcription factors and RNA polymerase interact by means of three-body interactions. Overall, we show that versatility of transcriptional activation is brought about by nonlinearities of transcriptional response functions and interactions between transcription factors, RNA polymerase and DNA. Combinatorial regulation of gene expression involves different receptor ligands, signaling pathway crosstalk, and different transcription factors. Such a combinatorial regulation can give rise to both synergistic activation responses E. coli cyclic AMP receptor protein (CRP) Cooperative activation exhibiting greater-than-additive effects can involve different species of transcription factors or several transcription factor molecules of the same type, as illustrated in As mentioned above, a greater-than-additive response to cooperative stimulation may also be found when several transcription factor molecules of the same type are bound at different promoter sites. In addition to the aforementioned experiments by Joung et al., in a separate study Note that a plentitude of experimental studies have been conducted that report cooperative activation in general, and in particular greater-than-additive effects. The aforementioned examples represent only a few such studies. Since greater-than-additive responses have been frequently highlighted in the literature, it is important to consider the mechanisms leading to such responses and to support the plausibility of those mechanisms by means of quantitative models. In fact, it has been argued that greater-than-additive effects are caused by at least two different mechanisms Of particular interest are DNA states where RNA polymerase is bound at the promoter, thereby initiating transcription. The cumulative probability obtained from all these states provides a general measure for gene expression and in particular for transcription initiation Statistical approaches have the benefit of allowing us to derive mathematical expressions for transcription rates without introducing levels of complexity that are not well understood and go beyond the identification of transcription factors and transcription factor binding sites. In particular, analytical expressions for transcription rates can be obtained with predictive power and in doing so can guide the design of experimental studies. However, there is still a demand for the characterization of the key features of thermostatistical models of cooperative transcriptional activation. The reason for this is that by definition the models are defined on multi-dimensional state spaces, which is a key challenge to a rigorous and systematic analysis  In previous studies, focus has primarily been on the binding probabilities of transcription factors, while a statistical treatment of the binding of the RNA polymerase has been neglected We will present a general statistical model for cooperative activation by means of an arbitrary number of transcription factors below Section . The derSuch re-entrant phenomena, in turn, are well known in physics Let us consider Our objective is to determine the probability  to  see  and has Eq. (4) is nonlinear with respect to the energy shifts A more concise description of the DNA state probabilities The probability Our next objective is to study gene expression regulated by two transcription factors using the statistical approach outlined above. We refer to the two transcription factors as The probability hown see  that theWe define the differenceTranscription factor concentrations are varying. In this case We compare different (mutant) promoters under the same type of stimulation . In this case, In general, the difference measure ysis see  domains At low concentrations of transcription factors, i.e., for As mentioned above, Eq. (4) is nonlinear with respect to the energy shifts The situation changes when ure  see . First nand  see . The criLet us close our considerations on the impacts of nonlinearities of the thermostatistical transcriptional machinery. To this end, we examine gene expression involving relatively small transcription rates. In Ref. onse see . In partThe energy shifts Note that for see also , case 7bE. coli cyclic AMP receptor protein (CRP) As mentioned in the introduction and illustrated in onse see  again. NAs summarized in Having illustrated the applicability of the thermostatistical approach to experimental data, we would like to point out that the aforementioned model-based interpretations are of speculative nature. First, the experiments by Joung et al. and Lee et al. have not been designed to test the thermostatistical model discussed here. Second, as mentioned in the introduction, it is challenge to estimate parameters of thermostatistical models of transcription initiation. The data available in the studies by Joung et al. and Lee et al. do not allow us to determine parameter estimation errors or to conduct model validation methods.less than the sum of the binding probability induced by single activation (less-than-additive effect), see Section ‘Low transcription factor concentrations and weak activators’. We also discussed several scenarios in which the binding probability under combined activation is larger than the sum of the binding probabilities induces by individual activations (greater-than-additive effect). These scenarios typically involve large doses of transcription factors . In order to illustrate the cross-over from less-than-additive to greater-than-additive responses when activator concentrations We showed that for low concentrations of transcription factors the RNAP binding probability induced by combined stimulation with both factors is In short, we put First, we focus on the role of energy shifts ose  see . There aIn the aforementioned discussion we focused on the role of the nonlinearities of the thermostatistical transcriptional machinery. Next, we shift our focus to the three-body interaction between RNA polymerase and the transcription factors bound at the two promoter binding sites. Accordingly, we put tion see  shows thIn closing these considerations, let us point out the importance of the dashed line shown in As mentioned in the introduction, Joung et al. We have derived a statistical model describing the combinatorial impact of multiple transcription factors on the RNAP binding probabilities and gene expression rates. We computed the probability of RNAP being bound to the promoter by calculating the sum of the probabilities of all DNA states form see (29)whereWe focused on studying promoters regulated by two transcription factors. We found that in this case the binding probability First of all, we addressed the issue that in general, at low transcription factor concentrations only less-than-additive effects can be observed. Second, if three-body interactions between RNAP and the two transcription factors are negligibly small  can induce a change from a greater-than-additive response to a less-than-additive response.Text S1Provides the following information: In Section 1 a rigorous mathematical derivation of the thermostatistical model (7) for multiple transcription factors is given. In Section 2 the model is compared with the thermostatistical model for transcription initiation proposed by Shea and Ackers. Section 3 provides mathematical details of the thermostatistical model for two activators. In Section 4 a proof is given that the thermostatistical modeling approach predicts that gene expression regulated by two activators is a monotonically increasing function of the activator concentrations. Section 5 provides various mathematical proofs necessary to show under which conditions less-than-additive and greater-than-additive effects are predicted by the thermostatistical two activator model for transcription initiation.(PDF)Click here for additional data file.


Drosophila the mode of limb suppression by the central  and posterior class  Hox proteins. Results highlight that Hox-mediated limb suppression relies on distinct modes of DNA binding and a distinct use of TALE cofactors. Control of common functions by divergent Hox proteins, at least in the case studied, relies on evolving novel molecular properties. Thus, changes in protein sequences not only provide the driving force for functional specialization of Hox paralogue proteins, but also provide means to perform common ancient functions in distinct ways.The emergence following gene duplication of a large repertoire of Hox paralogue proteins underlies the importance taken by Hox proteins in controlling animal body plans in development and evolution. Sequence divergence of paralogous proteins accounts for functional specialization, promoting axial morphological diversification in bilaterian animals. Yet functionally specialized paralogous Hox proteins also continue performing ancient common functions. In this study, we investigate how highly divergent Hox proteins perform an identical function. This was achieved by comparing in  Animal body plan diversity is controlled by transcription factors that select within each cell of a multi-cellular organism the set of genes to be expressed, eventually allowing distinct fate to emerge according to spatial coordinates. Transcription factors can be grouped based on their DNA binding domains in a few classes that likely arise from a common ancestral protein. This raises the question of how, within each class, transcription factors have gained specific function, and while doing so how they still continue performing ancient functions. Hox proteins, which play key roles in diversifying animal morphology, have largely been used to unravel the mechanisms underlying functional diversification of transcription factors. Here we use this family of transcription factors to investigate how common functions are achieved by divergent transcription factors. Results suggest that changes in protein sequences not only provide the driving force for defining novel and specific functions, but also provide means to perform common ancient functions in distinct ways. Hox genes encode homeodomain (HD) containing transcription factors widely used for diversifying animal body plans in development and evolution Sequence conservation/divergence within the HD allows grouping paralogue proteins in three classes Drosophila Hox paralogue proteins in specifying tritocerebral commissure in the embryonic brain Yet, in addition to having specialized biological functions, distinct Hox paralogue proteins also perform common  functions. A striking example is provided by the functional equivalence of most Drosophila the mode of action of central and posterior class Hox proteins, which display the most extreme divergence within Hox paralogues We aimed at addressing this so far poorly investigated issue by comparing in Drosophila harbors limbs exclusively in the thorax and not in the abdomen. This morphological distinction relies on the regulation of the limb-promoting gene Distalless (Dll), expressed in the thoracic limb primordia, but not in the abdomen. Thoracic specific expression of Dll relies on abdominal repression by Ubx and AbdA in the anterior abdomen (segments A1-A7) and by AbdB in the posterior abdomen (segments A8-9) Dll expression was shown to be mediated by multiple enhancers. This includes two enhancers in the 5′ and a distant one in the 3′ of the gene Dll repression by Ubx and AbdA Dll, which allows addressing how posterior and central class Hox proteins perform similar functions.To assess molecularly how divergent Hox proteins as Ubx/AbdA and AbdB can perform identical functions, we focused on limb suppression. As all insects, Dll expression -Gal4 driver, see material and methods), that both accurately reproduce Dll expression  and AbdBr in segment A9 AbdB gene, DMX activity is de-repressed in abdominal segments A1–A7, but not in A8 and A9 , in the posterior abdomen. Dll activation in thoracic segments precludes a loss of function approach. The question was addressed in gain of function experiments, making use of DMX enhancers mutated either on the Slp or on the En binding sites Next we investigated the contribution of En and Slp proteins for AbdB-mediated DMX repression. The requirement of En and Slp for proper We concluded, as previously shown for Ubx/AbdA, that AbdB-mediated repression of DMX occurs in anterior and posterior compartment cells and uses the En and Slp co-repressors.Dll repression, we first examined the distribution of Exd. Consistent with previous reports Dll , we re-examined the effect associated to mutations spanning the DMX-R  by exploring if any of these result in distinct effects in anterior abdominal segments, where repression is mediated by Ubx/AbdA, and posterior abdominal segments where repression is mediated by AbdB. This was achieved by quantifying the level of derepression associated to each mutation, focusing on segments A1 and A8, as representatives of anterior and posterior abdominal segments respectively. Dll repression. Since Hth levels decrease dramatically in the posterior abdomen, we asked if AbdB itself mediates this down regulation. We found that depleting the AbdBm (m3AbdB) or AbdBm and r proteins (Df(P9)) results in increasing the level of Hth to a level similar to the anterior abdomen and thorax region, from segment A4 and including segments A8 and A9 respectively  do not alter AbdB potential to repress DME activity  results in a strong reduction of the AbdB repressive potential  resulted in a complete loss of repressive activity, demonstrating the essential character of AbdB DNA binding for proper Dll repression . KK fails to properly repress DME, with a loss of 60% of its repressive potential (CEN). CEN has a very weak repressive potential, even lower than that of AbdBKK , establishes a contribution of the HD N-terminal arm and residues immediately C-terminal to the HD, and reveals a strict requirement for AbdB DNA binding.Dll repression. To address if the conclusion also holds true for central Hox proteins, we investigated the requirement of position 50 within helix 3 of the Ubx HD for proper DME repression. Mutation of position 50 of the HD was previously shown to be essential for Ubx binding to DMX-R H3) showed that it still represses DME, with a limited loss (30%) of repressive potential. ), which significantly restored repressive potential  instead of 68% for Ubx HX,UAAbdB(HD);  and UbxHX,UAAbdB(HD+Cter) use an AbdB like mode of repression, by investigating if DNA binding is critical for the activity of these chimeras. Mutations of position 51 of the HD within the context of these two chimeras were generated, and the resulting chimeras were assayed for DME repression. Results showed that UbxHX,UAAbdB(HDH3) and UbxHX,UAAbdB(HDH3+Cter) are fully deficient in DME repression . As we bdB(HD); . These rpression , indicatDll, we have investigated how highly divergent central (Ubx/AbdA) and posterior (AbdB) Hox proteins perform an identical function. The comparison of Dll regulatory cis requirements, use of cofactors, and requirements in Hox protein intrinsic domains demonstrate distinct modes of Dll regulation, highlighting usage of distinct molecular strategies by divergent Hox proteins to achieve common biological functions  results in de-repression all abdominal segments including in A8 and A9 in vitro EMSA's on DMX-R showing a competition effect of Hth and Hht/En/Exd complexes on AbdB binding, and by de-repression of Dll in posterior segments A8 and A9 following increased levels of Hth expression. Functional antagonism between AbdB and the TALE cofactors Exd and Hth is further demonstrated in the specification of several AbdB-dependent specific features, including the posterior spiracle and the suppression of ventral denticle belts Beyond dispensability, the absence of Exd and Hth in the embryo may be required for proper AbdB function. This view is supported by our Drosophila, some aspect of Hox protein function do not require Exd, including the function of the central Hox protein Ubx in specifying haltere development Our results also provide additional support for developmental functions performed independently by Hox proteins and their usual cofactors Exd and Hth. In Dll enhancer on its own, while binding by Ubx or AbdA requires the assistance of the Exd and Hth cofactors.Although generally conserved, the mode of HD/DNA contacts significantly varies between anterior/central and posterior paralogue groups Dll regulation by Ubx and AbdA Dll repression in abdominal segments needs to accommodate the repression by different molecular complexes. This relies on the plastic usage of the same Dll cis sequences in the anterior and posterior abdomen. First, Hox binding sites may accommodate binding by Hox proteins displaying significantly divergent mode of DNA binding, as shown by the use of Hox1 and Hox2 binding site for Ubx/AbdA and AbdB DNA binding. Second, the same cis sequence binds distinct proteins, as shown for the initially labeled “Exd binding site” that also mediates AbdB binding to DMX-R. The current mode of Dll cis sequence usage may reflect the evolutionary history of Dll repression: Dll repression may have initially been achieved by AbdB, and have later been extended to repression by Ubx/AbdA by the acquisition/cooptation of Exd and Hth binding sites, enabling Ubx and AbdA to bind the enhancer, despite having a HD not optimized for efficient binding to the Dll gene.Taken together with previous data on The following stocks were used for the study: UAS-Ubx::HA Transgenic flies were generated using P-element germline transformation either in yw flies AbdB variants and AbdB/Ubx chimeras were generated using the SOE method, starting form UbxIa and AbdBm cDNAs, and cloned into pUAST vector . Primers were as follows:AbdB variants:5′ AAAAGAATTCATGCAGCAGCACCATCTGCA; 5′ CGGCGGTTCTACGTGGTTGAGCTCAAAA)AbdB m AbdB TG AbdB EWTG S AbdB KKABdB CEN AbdB H3a AbdB H3b AbdB terAbdB CHXUA and AbdBm were used as templates):Ubx/AbdB chimeras AbdB HD amplification Ubx N-Ter amplification Ubx C-Ter amplification (HXUA(AbdB H3) template used for AbdB HD amplification was AbdB H3b.For Ubx HXUA (AbdB HD+Cter) and Ubx HXUA (AbdB HDH3+Cter), the procedure was similar using the AbdB HDCter 3′ (5′ TTCTTCTTGAGTGTCGCGGTCCGGCTCTTCGTC) instead of (5′ GATCGCCTGTGAGTTCTTCTT).For Ubx Hth and Dll Digoxigenin RNA-labelled probes were generated by in vitro transcription from plasmid containing hth and Dll cDNA. RNA in situ hybridization were performed according to standard methods.P insertions were genetically mapped. For each variant, two lines were crossed with the prd-Gal4 and arm-Gal4 driver at 22, 25, or 29°C. Collected embryos were stained with anti-Ubx , anti-AbdB or anti-HA tag  to select the conditions (line and temperature) that result in expression levels similar (+/−15%) to Ubx and AbdB wild-type levels in A1 and A8, respectively Df P9 (BX-C mutant) embryos.Embryo collections and immunostaining of embryos were performed according to standard procedures. Quantification of DME repression was achieved following anti-β-galactosidase immunostainings  by using the same DME-lacZ insertion. The levels of DME enhancer repression were estimated by quantifying the surface reduction in T2 of the DME-positive cell cluster by using the AxioVision LE4.5 measurement tool. Quantification was done on five individual experiments for each genotype. In case of de-repression observed in DMX binding sites mutants, the area of de-repressed β-gal was measured in A1 and A8 in at least 10 embryo's. The average was taken and compared to levels of DMX-lacZ de-repression levels observed in A1 and A8 segments in in vitro transcription/translation system (Promega). The following double stranded oligos (only one strand is specified) spanning the Dll repressive sequences were used:AbdB variants and AbdB/Ubx chimeras generated as described above were cloned into pcDNA3  for protein synthesis. Exd and Hth were full-length, and En protein was lacking the 60 N-terminal amino acids. AbdB and AbdB with HD mutations were cloned in pCDNA3 vector and sequence verified. Proteins were produced with the TNT (T7)-coupled DMX-R containing Slp, Hox1, Exd, En, Hth and Hox2 binding sites:GACAATATTTGGGAAATTAAATCATTCCCGCGGACAGTTTTATAGTGCTTTGGGAAATTAAATCATTCCCGCGGACAGTTTTATAGTGCDIIRL: containing Hox1, Exd, En,and Hth and Hox2 binding sites: TTTGGGAAATTAAATCATTCCCGCGGACAGTDIIR containing Hox1, Exd, En,and Hth binding sites: Mutations in Hox1, Hox2, Exd and Hth were previously described  and are:ATTAAAA to GCCCGAAHox1: TTTATAG to GGGCTAGHox2: TCATAAA to GGATAAAExd: ACAGGG to CCGGGGHth: Figure S1Dll expression. A) Embryos stained for the Dll transcript (red), showing expression in the thoracic and head segments. B) prd-Gal-4 driven anterior ectopic expression of AbdBm (green) results in Dll (red) repression in thoracic segment T2 and head segment (arrowhead).Ectopic expression of AbdBm represses thoracic (TIF)Click here for additional data file.Figure S2m3), displaying posterior Exd accumulation till A8. B) Embryos co-stained for Exd (red) and Ubx (green). Ectopic Ubx expression was driven in every other segments by prd-Gal4. While AbdB ectopic expression  Embryos co-stained for Exd (red) and AbdB (green). Arrowheads highlight segments A3 and A8. Upper panels: wild type embryo, decrease of Exd expression is seen from segment A3 and reaches very low levels in A8; Lower panels: embryo lacking AbdB m isoform (AbdB(TIF)Click here for additional data file.Figure S3Dll cis sequences. A) EMSA of AbdB on DIIRL  and DIIRL mutants for binding sites Hox1, Hox2, Hox 1+2 and Exd. B)Quantification of AbdB binding in EMSA to DIIRL wild type and mutated using the lowest AbdB quantity. Single mutations in Hox1, Hox2 and Exd similarly reduces the efficiency of AbdB binding to DMX-R, while combined mutation of Hox1 and Hox2 results in stronger decrease in DNA binding. C) EMSA on DMX-R  with AbdB, En, Exd, Hth, Exd+En, Exd+Hth, Hth+En and Exd+Hth+En identifying AbdB-DNA and Exd-Hth-En-DNA complexes.Binding site requirements for AbdB binding to (TIF)Click here for additional data file.Figure S4exd) or Hth (DIIRHth) binding sites. Note that the Exd-mediated release of inhibitory effect seen for full length Hth is lost with the truncated Hth HM protein, and that mutation of the Exd binding site affect the formation of AbdB/DNA complexes.Requirements for Hth/Exd inhibition of AbdB binding to DIIR. EMSA of AbdB on DIIR with various combinations of AbdB, Exd, Hth and truncated HM (HD less) form of Hth, or on DIIR mutated in the Exd (DIIR(TIF)Click here for additional data file.Figure S5Df P9). Except for the DMX(Hox1S) and DMX binding sites, no difference in derepression was observed between A1 and A8.Quantifications of DMX-R sequence requirements for repression in A1 and A8. A) Schematic representation of DMX-R mutations analysed. DMX lacZ reporter transgenic lines, transcription factor binding site  allocation, and name of DMX-R mutant enhancers are from (TIF)Click here for additional data file.Figure S6Illustrations of DMX-R sequence requirements for repression in A1 and A8. Embryos bearing DMX-R lacZ reporter transgenes mutated in one or multiple binding sites were stained for β-gal. Note that for some of these mutations, a significant variability was observed see  and is n(TIF)Click here for additional data file.Figure S7hth transcript (red). B) prd-Gal-4 driven ectopic expression of AbdBm (green) results in hth (red) repression. Right and left panel shows early (germ band extended) and late (germ band retracted) embryos.AbdBm represses the transcription of Hth. A) Embryos stained for the (TIF)Click here for additional data file.Figure S8Lack (or low level) of AbdA repressive function on Hth expression. Embryos bearing the DME reporter co-stained for β-gal (green) and Hth (red).(TIF)Click here for additional data file.Figure S9Increasing Hth expression levels in the posterior abdomen allows posterior derepression of DMX in A8 and A9 segments. Embryo bearing the DMX reporter co-stained for β-gal (red) and Hth (green) ubiquitously driven by arm-Gal4. Note that only moderate posterior accumulation of Hth could be reached in posterior abdominal segments. Arrows point to derepression in A8 and A9 segments.(TIF)Click here for additional data file.Figure S10Protein sequence requirements for AbdB-mediated DME repression. Thoracic centered magnifications of embryo bearing the DME reporter co-stained for β-gal (red) and AbdB variants (green) driven by prd-Gal4. Levels of repressive activity of different AbdB murtations on DME were evaluated by defining the ratio of β-gal staining in T2 and T3 . Quantifications are shown in (TIF)Click here for additional data file.Figure S11H3 or Ubx/AbdB chimeras (green) driven by prd-Gal4. Levels of UbxH3 or Ubx/AbdB chimeras repressive activity on DME was evaluated by defining the ratio of β-gal staining in T2 and T3 . Illustrations for wild type AbdB is given in HX,UA in Ubx/AbdB chimera protein sequence requirements for DME repression. Thoracic centered magnifications of embryo bearing the DME reporter co-stained for β-gal (red) and Ubx(TIF)Click here for additional data file.


Brachypodium distachyon, Oryza sativa ssp. japonica, Sorghum bicolor, Zea mays) and four dicots  reveals the structural organization of the core promoter in relation to the TATA-box as well as with respect to other CPEs. The distribution of known CPE motifs with respect to transcription start site (TSS) exhibited positional conservation within monocots and dicots with slight differences across all eight genomes. Further, a more refined subset of annotated genes based on orthologs of the model monocot (O. sativa ssp. japonica) and dicot  genomes supported the positional distribution of these thirteen known CPEs. DNA free energy profiles provided evidence that the structural properties of promoter regions are distinctly different from that of the non-regulatory genome sequence. It also showed that monocot core promoters have lower DNA free energy than dicot core promoters. The comparison of monocot and dicot promoter sequences highlights both the similarities and differences in the core promoter architecture irrespective of the species-specific nucleotide bias. This study will be useful for future work related to genome annotation projects and can inspire research efforts aimed to better understand regulatory mechanisms of transcription.Transcription initiation, essential to gene expression regulation, involves recruitment of basal transcription factors to the core promoter elements (CPEs). The distribution of currently known CPEs across plant genomes is largely unknown. This is the first large scale genome-wide report on the computational prediction of CPEs across eight plant genomes to help better understand the transcription initiation complex assembly. The distribution of thirteen known CPEs across four monocots ( Despite numerous technological advances in biological and computational sciences in the post- genome era, our basic understanding of gene regulatory mechanisms remains primitive. Currently, the fundamental need to understand RNA polymerase II (polII) mediated transcription initiation is well recognized for developing system level understanding of the condition-specific gene regulatory networks (GRNs). It is now well known that the TATA-box motif, once thought to be necessary for formation of polII pre-initiation complex (PIC) assembly, only accounts for a small fraction of the expressed genome Saccharomyces cerevisiae, Drosophila melanogaster, and mammals, several other CPEs have been identified in TATA and TATA-less promoters that include the initiator (Inr) element located at or surrounding the TSS which is recognized by TAF1 and TAF2 subunits of the TFIID complex Promoter regions can be categorized into two classes: core  and extended . The core promoter is the primary docking site of polII PIC and directs basal transcription D. melanogasterCaenorhabditis elegansRattus norvegicusMus musculusHomo sapiensVery little is known about the cis-regulatory elements of transcription control in plants. In the past decade, considerable work has focused on model animal species like in silico prediction is still in its early stage. Though the number of computational motif discovery methods has significantly increased in last two decades Due to the complexity, diversity and inherent degenerate nature of regulatory motifs within promoters, the prediction of cis-regulatory elements is quite challenging and We performed a genome-wide prediction of known CPEs in eight plant species spanning both monocots and dicots, by developing a systematic and unbiased high-throughput methodology using PWMs, DNA free energy profiles, and homology to significantly reduce the false positive rate of motif discovery. The CPE profiles were compared to see the similarities and differences in promoter sequence architecture within and across monocots and dicots.Core promoter regions are generally reported within a tight window of TSS±50bases www.gramene.org]. These eight plant genomes included four monocots (Brachypodium distachyon (Bdi), Oryza sativa ssp. japonica (Osa), Sorghum bicolor (Sbi), Zea mays (Zma)) and four dicots , Populus trichocarpa (Ptr), Vitis vinifera (Vvi), Glycine max (Gma)). For each genome, only the transcripts annotated with a 5′ untranslated region (5′UTR) and high quality filtered gene-set (after discarding transposable elements) were used for CPEs predictions   for four monocots  and four dicots . To see cross-species conservation of CPEs based on orthologs, A.thaliana and O.sativa ssp japonica orthologous protein coding genes with sequence identity ≥50% with their respective dicots  and monocots  were selected for orthologous conservation study. 9225 and 7958 orthologous protein coding genes for Ath and Osa were selected for this study. The ortholog dataset was retrieved from Gramene biomart The core promoter sequences [TSS±500] of protein coding genes with known 5′UTR information were extracted from the Gramene core databases (version 34b) [Drosophila melanogaster were extracted from Eukaryotic promoter database [http://epd.vital-it.ch/] The promoter sequences for DNA free energy profiles of the promoter regions and randomly generated background sequences as negative control related to eight plant genomes were constructed using PromPredict – an algorithm based on GC content of the genome as well as difference in the GC content of the promoter region and the genomic sequence flanking the promoter region Arabidopsis thaliana as a dicot model and Oryza sativa ssp. japonica as a monocot model were selected as mentioned before. It provided an additional approach to increase the confidence in putative CPEs predictions made based on the positional conservation.For positional conservation, we analyzed the promoters for which 5′UTR information was available for all eight genomes. For orthologous conservation, Search Tool for Occurrences of Regulatory Motifs (STORM) was used to identify motifs based on predefined PWMs in silico according to the real nucleotide composition of the genomes in our data set. It established motif's positional signal detection base-line threshold. The range in which foreground CPE abundance was at least 1.5 standard deviations higher than the background CPE abundance was considered as a candidate binding site region. Further, overlaying of individual species frequency distribution profiles within monocots and dicots provided positional conservation of the binding site region across species. Overlaying of frequency distribution profiles based on A. thaliana orthologous gene promoters among dicots and O. sativa japonica orthologous gene promoters among monocots provided further confidence in cross species conservation of CPEs. Based on these approaches, the consensus range for each CPE was determined independently in the monocots and dicots.We generated and tested several background models specifically derived from corresponding real genomic sequences from non-regulatory regions as well as a pseudo random background model designed from a large set of sequences that had been generated artificially For each genome, a list of each core promoter element's putative distribution range was determined based on the qualitative and quantitative measures as mentioned earlier. Custom perl scripts were used to determine the specific core element present in each promoter sequence of the genome. The set of core elements found to be present in a particular promoter sequence defined that promoter's combinatorial module. Though, with this approach one combinatorial module per promoter was obtained, however often a combinatorial module was found to be present in more than one promoter. Therefore, only the set of unique combinatorial modules was analyzed. To further determine prevalent CPEs contributing to the majority of the combinatorial modules, this dataset was partitioned with respect to the presence and absence of the TATA-box.A. thaliana protein coding genes in TATA, TATA-less, and CPE-less categories were analyzed for gene ontology functional enrichment by using BiNGO Figure S1The distribution of the number of transcripts with respect to 5′UTR length across dicots and monocots. The panel A shows the distribution of 5′ UTR length in four dicots: Arabidopsis thaliana (Ath - solid navy blue), Glycine max (Gma-solid dark blue), Populus trichocarpa (Ptr –solid blue sapphire), and Vitis vinifera (Vvi -solid blue green). The panel B shows the distribution of 5′UTR length in four monocots: Brachypodium distachyon (Bdi-solid bronze yellow), Oryza sativa ssp. japonica (Osa-solid red), Sorghum bicolor (Sbi-solid bronze), and Zea mays (Zma -solid purple). X-axis shows bins of 5′ UTR length, where each bin is 10 base-pair long. Y-axis shows the number of transcripts.(TIF)Click here for additional data file.Figure S2The GC content distribution across dicots and monocots. X-axis shows the percentage GC across eight genomes whereas Y –axis shows the number of transcripts. GC percentage in monocots and dicots showed the demarcation of GC content distribution between dicots and monocots.(TIF)Click here for additional data file.Figure S3Arabidopsis thaliana).The distribution of all known core promoter elements in dicot model , Inr (dark-grey), GC-box (black), CCAAT-box (purple), DPE (dark-green), BREu (brown), BREd (sky-blue), DCE-S1 (yellowish-green), XCPE1 (blue), TATA-box (red), MED-1 (light-grey), and Y-patch (green).(TIF)Click here for additional data file.Figure S4Oryza sativa ssp. japonica).The distribution of all known core promoter elements in monocot model , Inr (dark-grey), GC-box (black), CCAAT-box (purple), DPE (dark-green), BREu (brown), BREd (sky-blue), DCE-S1 (yellowish-green), XCPE1 (blue), TATA-Box (red), MED-1 (light-grey), and Y-patch (green).(TIF)Click here for additional data file.Figure S5Drosophila melanogaster.The distribution of selected known core promoter elements in  Genome-wide motif distribution profiles of core elements – TATA-box (solid red), Inr (solid blue), MTE (solid black), and DPE (solid green) in D. melanogaster genome showing positional conservation of these CPEs with respect to TSS. X-axis shows  promoter region that is binned into 20 base-pair bins, where each bin is represented by the bin-center. Y-axis shows the frequency distribution of the elements along the promoter with respect to TSS.(TIF)Click here for additional data file.Table S1Genomic information of the eight plant species from Gramene.(XLSX)Click here for additional data file.Table S2Brief information on core promoter elements with sequence logo of the respective position weight matrix.(XLSX)Click here for additional data file.Table S3Position weight matrix specific score threshold cut off for each core promoter element for eight plant species.(XLSX)Click here for additional data file.Table S4Putative binding site distribution of the core promoter elements relative to transcription start sites based on positional and orthologous gene conservation across species.(XLSX)Click here for additional data file.Table S5Percentage distribution of the core promoter elements in eight plant genomes.(XLSX)Click here for additional data file.Table S6CPE combinatorial modules selected based on the positional distribution range across dicots.(XLSX)Click here for additional data file.Table S7CPE combinatorial modules selected based on the positional distribution range across monocots.(XLSX)Click here for additional data file.Table S8Prevalence of core promoter elements in combinatorial CPE modules in TATA(+) and TATA(−) promoter genes.(XLSX)Click here for additional data file.Table S9Functional annotation based on gene ontology molecular function enrichment of TATA, TATAless and Coreless genes.(XLSX)Click here for additional data file.Table S10Functional annotation based on gene ontology biological process enrichment of TATA, TATAless and Coreless genes.(XLSX)Click here for additional data file.


In vitro experiments using knockout mice have shown that Msi1 and its isoform Musashi2 (Msi2) keep NS/PCs in an undifferentiated and proliferative state. Msi1 is expressed not only in NS/PCs, but also in other somatic stem cells and in tumours. Based on previous findings, Msi1 is likely to be a key regulator for maintaining the characteristics of self-renewing stem cells. However, the mechanisms regulating Msi1 expression are not yet clear.The specific genetic regulation of neural primordial cell determination is of great interest in stem cell biology. The Musashi1 (Msi1) protein, which belongs to an evolutionarily conserved family of RNA-binding proteins, is a marker for neural stem/progenitor cells (NS/PCs) in the embryonic and post-natal central nervous system (CNS). Msi1 regulates the translation of its downstream targets, including Msi1 transcription, we inserted the fusion gene ffLuc, comprised of the fluorescent Venus protein and firefly Luciferase, at the translation initiation site of the mouse Msi1 gene locus contained in a 184-kb bacterial artificial chromosome (BAC). Fluorescence and Luciferase activity, reflecting the Msi1 transcriptional activity, were observed in a stable BAC-carrying embryonic stem cell line when it was induced toward neural lineage differentiation by retinoic acid treatment. When neuronal differentiation was induced in embryoid body (EB)-derived neurosphere cells, reporter signals were detected in Msi1-positive NSCs and GFAP-positive astrocytes, but not in MAP2-positive neurons. By introducing deletions into the BAC reporter gene and conducting further reporter experiments using a minimized enhancer region, we identified a region, "D5E2," that is responsible for Msi1 transcription in NS/PCs.To identify the DNA region affecting Msi1 transcription in NS/PCs is located in the sixth intron of the Msi1 gene. The 595-bp D5E2 intronic enhancer can transactivate Msi1 gene expression with cell-type specificity markedly similar to the endogenous Msi1 expression patterns.A regulatory element for  Neural stem cells (NSCs) are one of the most important research targets in developmental neurobiology, and are attracting attention in strategies for central nervous system (CNS) regeneration -6. NSCs Drosophila . The data represent the mean ±SEM of three independent experiments. The data were subjected to non-repeated-measures ANOVA tests, and p values were calculated by Bonferroni multiple comparison tests. *p < 0.05: P1 to D5E2-P1, D5E2 reverse-P1.Click here for fileFigure S6. Candidate transcription-factor binding sites in D5E2. Sequence comparisons of the Msi1 enhancer D5E2 sites between human, dog, mouse and rat species; three potential SOX and four potential AP-2 highly conserved binding sites were identified (searched results are from the JASPAR CORE database).Click here for file


We found that zebrafish angptl4 is transcribed in multiple tissues including the liver, pancreatic islet, and intestinal epithelium, which is similar to its mammalian homologs. Zebrafish angptl4 is also specifically suppressed in the intestinal epithelium upon colonization with a microbiota. In vivo transgenic reporter assays identified discrete tissue-specific regulatory modules within angptl4 intron 3 sufficient to drive expression in the liver, pancreatic islet β-cells, or intestinal enterocytes. Comparative sequence analyses and heterologous functional assays of angptl4 intron 3 sequences from 12 teleost fish species revealed differential evolution of the islet and intestinal regulatory modules. High-resolution functional mapping and site-directed mutagenesis defined the minimal set of regulatory sequences required for intestinal activity. Strikingly, the microbiota suppressed the transcriptional activity of the intestine-specific regulatory module similar to the endogenous angptl4 gene. These results suggest that the microbiota might regulate host intestinal Angptl4 protein expression and peripheral fat storage by suppressing the activity of an intestine-specific transcriptional enhancer. This study provides a useful paradigm for understanding how microbial signals interact with tissue-specific regulatory networks to control the activity and evolution of host gene transcription.The intestinal microbiota enhances dietary energy harvest leading to increased fat storage in adipose tissues. This effect is caused in part by the microbial suppression of intestinal epithelial expression of a circulating inhibitor of lipoprotein lipase called Angiopoietin-like 4 (Angptl4/Fiaf). To define the  Angptl4 gene, which encodes a secreted inhibitor of fat storage. Although Angptl4 is expressed in multiple tissues, microbial suppression occurs only in the intestine. To determine how microbes control fat storage, we must elucidate the mechanisms underlying intestine-specific and microbial regulation of Angptl4 expression. Here, we take advantage of the unique features of the zebrafish model to define the regulatory DNA sequences controlling angptl4 expression. Our results reveal that different DNA regulatory regions within the angptl4 gene mediate expression of angptl4 in the intestine and other tissues. By assessing the evolution of angptl4 regulatory regions and subjecting them to structure-function analyses, we identify discrete DNA sequences that are required for intestinal expression. Strikingly, microbes suppress the activity of the intestine-specific regulatory region similar to the endogenous angptl4 gene. Therefore, intestinal microbes might regulate angptl4 production by suppressing the signaling pathway interpreted by an intestine-specific transcriptional regulatory region. Our results provide new mechanistic insights into how intestinal microbes might influence fat storage and contribute to the development of obesity.Recent studies have revealed that the community of microorganisms residing in the intestine regulates fat storage. Microbes evoke this response in part by suppressing expression of the  The vertebrate intestine harbors a dense community of microorganisms (gut microbiota) that exerts a profound influence on distinct aspects of host physiology Angiopoietin-like 4  Angptl4 expression is restricted to the intestinal epithelium and is not observed in other tissues that express Angptl4, such as liver and adipose tissue. This restricted suppression leads to a significant increase in LPL activity and fat storage in adipose tissue of animals colonized with a microbiota, which is an effect abolished in mice lacking Angptl4Angptl4 as a key host factor mediating the microbial regulation of host energy balance and have raised considerable interest in defining the mechanisms underlying the tissue-specific and microbial regulation of Angptl4 expression. The importance of understanding mechanisms regulating Angptl4 production is further underscored by reports suggesting that human ANGPTL4 functions as an important determinant of plasma TG levels The ability of the microbiota to modify host nutrient metabolism and energy balance is a prominent theme in host-microbe commensalism in the intestine. Recent mechanistic insights into this process have been provided by comparisons between mice reared in the absence of microbes (germ-free or GF) to those colonized with members of the normal microbiota, as well as high-throughput DNA sequencing analysis of the metabolic potential of gut microbial genomes. These approaches have shown that the gut microbiota contributes biochemical activities not encoded in the host genome that enhance digestion of dietary nutrients Angptl4 expression is subject to complex cell type-specific regulation but the underlying mechanisms remain unclear. Angptl4 mRNA in humans and rodents is expressed in multiple tissues, including adipose tissue, liver, intestinal epithelium, pancreatic islets, and cardiac and skeletal muscle trans- and cis-regulatory mechanisms controlling Angptl4 transcription have been provided by analyses in non-intestinal tissues. Members of the peroxisome proliferator-activated receptor (PPAR) family of nuclear receptors  have been identified as activators of Angptl4 expression in adipose tissue, liver Angptl4 intron 3 has been shown to directly bind different PPAR family members in adipose tissue, liver Angptl4 transcription is induced under hypoxic conditions in several non-intestinal cell types by hypoxia-inducible factor 1α (HIF1α) trans- and cis-regulatory factors in controlling Angptl4 transcription in these cell types, yet the mechanisms underlying the transcription of Angptl4 in other tissues, such as the intestine and pancreatic islet, remain unknown. Moreover, the cis/trans-regulatory mechanisms underlying microbial suppression of Angptl4 transcription in the intestinal epithelium remain undefined.Previous studies have revealed that mammalian Danio rerio) provides unique opportunities to study the transcriptional regulatory programs mediating tissue-specific and the microbial control of vertebrate gene expression. Robust transgenesis methods using the Tol2 transposon system Angptl4Angptl4 homolog, and the mechanisms underlying the tissue-specific and microbial regulation of its expression, have not been previously described.The zebrafish  that mediate intestinal and islet expression. Using this information, we reveal that the intestine-specific CRM also responds to microbial stimuli to suppress angptl4 expression. These results provide novel insights into how vertebrates might control the tissue-specific transcription of Angptl4 and constitute an important advance towards understanding how commensal gut microbes regulate gene expression and energy balance in their vertebrate hosts.These features position the zebrafish as a powerful model for assaying the regulatory potential of DNA involved in mediating cell-specific and microbe-responsive transcriptional events. Previous studies of DNA regulatory potential in the zebrafish system have focused primarily on developmental genes in situ hybridization (WISH) to identify the tissues in which angptl4 is transcribed during zebrafish development. We found that zebrafish angptl4 mRNA is expressed ubiquitously in 1 dpf embryos , stickleback (Gasterosteus aculeatus), fugu (Takifugu rubripes), and tetraodon (Tetraodon nigroviridis)] approximately 230–307 million years ago angptl4 loci from four teleost fishes  and three mammals . Alignment of teleost and mammalian genomic sequences did not detect regions of primary sequence conservation within angptl4 non-coding regions , suggesting that these alignment methods are not sufficiently sensitive to detect existing non-coding conservation angptl4 (Angptl4 loci (angptl4 loci both contain 7 conserved exons as well as a concentration of conserved non-coding sequences directly upstream of exon 1 and in intron 3 (angptl4 transcription may be evolutionarily conserved.Previous studies have indicated that conservation in non-coding genomic DNA sequence across vertebrate lineages can be a reliable predictor of  angptl4  and mammtl4 loci  and searintron 3 . Similarangptl4 transcription start site (TSS) for the ability to transcribe a reporter in the intestine, liver, and islet. We first employed 5′ rapid amplification of cDNA ends (5′RACE) to determine the location of the TSS (angptl4 locus (data not shown), we found no evidence of alternative promoters farther upstream of the defined TSS. Using Tol2 transposon transgenesis, we assayed the regulatory potential of genomic DNA upstream of the zebrafish angptl4 TSS, including the 5′ untranslated region (UTR)  , to drivon (UTR) . Robust on (UTR) . Howeverntestine  or isletrd intron of zebrafish angptl4 for transcriptional regulatory potential. We cloned full-length zebrafish angptl4 intron 3  into a Tol2 transposon reporter vector upstream of a minimal mouse Fos promoter (Mmu.Fos) driving transcription of a GFP or tdTomato reporter. Importantly, the minimal Fos promoter alone is relatively inactive in most tissues and is not sufficient to drive transcription of detectable levels of GFP in the intestine, islet, or liver Tg(in3-Mmu.Fos:GFP) transgene disclosed that full-length in3 is sufficient to confer reporter expression in multiple tissues including the liver, muscle, intestine ) In vivo imaging of 6 dpf progeny from intercrosses of s892Tg(ins:CFP-NTR) and Tg(in3.2-Mmu.Fos:tdTomato) adults revealed strong co-localization of CFP and tdTomato (Tg(in3.4-Mmu.Fos:GFP) transgene revealed that GFP driven by the in3.4 module co-localizes with 4E8-positive absorptive enterocytes  specifically in insulin-producing β-cells within the islet  and 9 other members of order Cypriniformes (angptl4 intron 3 orthologous to zebrafish in3.2 (Ol in3.2) failed to drive reporter expression in either the intestine or islet  D. aequipinnatus, C. auratus, C. carpio, P. conchonius). These results reveal differential evolutionary dynamics of the angptl4 intestinal and islet modules and support the hypothesis that high sequence conservation is required for tissue-specific transcription.We used comparative genome sequence analysis from 12 teleost fishes and heterologous cription . Howeverequences . We therniformes . Becauseniformes  and S6. or islet . Notablyor islet . HoweverIn silico prediction of transcription factor binding sites in this critical region identified putative binding sites for multiple transcription factors known to be active in pancreatic islets such as Myc Guided by our conservation analyses, we next sought to map the boundaries of critical regulatory regions in the zebrafish in3.3 islet and in3.4 intestinal CRMs by creating and testing truncations of these modules. Each truncation construct was injected into embryos and analyzed at 6–7 dpf for mosaic expression in the islet or intestine. These analyses defined a 164 bp region sufficient to confer islet expression in3.17;  includinangptl4 intron 3 required for intestinal and islet transcription.A distinct 116 bp region (in3.12) was found to be sufficient to confer intestinal expression . Notablyangptl4. Ten base-pair substitutions were tiled across the region corresponding to in3.11 within the context of the entire in3.4 module, and assayed for competency to drive intestinal transcription  to generate a higher-resolution understanding of the functional DNA motifs required for enterocyte-specific transcription of cription . This ancription . DNA adjcription  by localcription . Specifi species . This re species  that repAngptl4 transcript specifically in the intestinal epithelium, which is thought to lead to increased peripheral fat storage cis-regulatory module within intron 3 could impart this environmental response in the zebrafish. Our previous comparisons of 6 dpf GF zebrafish to age-matched ex-GF zebrafish colonized since 3 dpf with a normal microbiota  indicated that the presence of a microbiota results in reduced angptl4 transcript levels angptl4 mRNA in the intestinal epithelium in 6 dpf CONVD zebrafish compared to age-matched GF controls  zebrafish to 6 dpf under GF or CONVD conditions and assayed transcript levels for both GFP reporter and endogenous angptl4 using qRT-PCR. Consistent with our WISH results, endogenous angptl4 transcript levels were significantly and reproducibly reduced in CONVD compared to GF animals , harboring the in3.2 reporter which includes the in3.4 module . This finding suggests that the tissue-specific pattern of Angptl4 expression may have been conserved in the last common ancestor of mammalian and teleost lineages and might have important functional consequences on vertebrate physiology.Transcriptional regulation is a key determinant of gene function in the context of animal development and physiology. Recent biochemical and genetic studies in mouse and humans have identified Angptl4 as a critical hormonal regulator of TG-rich lipoprotein metabolism, angiogenesis, and tumor cell survival and metastasis. An improved understanding of the mechanisms controlling Angptl4 activity levels could therefore lead to new approaches for controlling multiple pathophysiologic processes. Although we have a working understanding of Angptl4's post-translational functions, our current knowledge of the mechanisms underlying angptl4 in distinct tissues might be governed by independent cis-regulatory mechanisms. This modular design could have important implications for Angptl4 evolution and function. First, tissue-specific CRMs could have allowed independent evolution of CRM sequence structure. Consistent with this notion, we observed evidence of differential evolution of the islet and intestinal modules within teleost fish lineages . This result suggests either that regulatory information governing islet and intestinal expression of murine Angptl4 is not located within intron 3 or that compensatory cis/trans mutations render murine intron 3 sequences non-functional in the zebrafish. We suspect that rules governing CRM function and evolution are dependent on the distinct nature of the organism, the specific module, and the signals that the module integrates. It therefore remains an intriguing question as to what extent lessons learned from developmental gene regulation are applicable to the evolution of CRMs controlling expression of genes like Angptl4 that function in homeostatic physiology or in response to environmental factors like the microbiota Previous studies of CRM evolution in vertebrates and invertebrates have focused primarily on enhancers regulating expression of genes involved in development Analyses of Drosophila genomes have elegantly shown that CRM “discovery power scales with the divergence time and number of species compared” Angptl4 transcript levels in the epithelium of the small intestine but not in liver or WAT Angptl4 transcript levels were due to alterations in Angptl4 transcription or mRNA turnover. Furthermore, the molecular basis of the intestinal specificity of this response remained unknown. Our results reveal that zebrafish angptl4 transcript levels are also reduced in the intestinal epithelium in the presence of a microbiota, suggesting that the microbial regulation of angptl4 transcript levels might be an evolutionarily ancient feature of host-microbe commensalism in the vertebrate intestine. Our observation that transcript levels from the in3.4 reporter and the endogenous angptl4 gene respond similarly to microbial colonization strongly suggests that the microbiota regulates angptl4 expression, at least in part, by reducing the transcriptional activity of this enterocyte-specific enhancer module. These results indicate that enterocyte-specific and microbial control of angptl4 transcription is conferred through a shared intronic enhancer.The intestinal microbiota has been identified as an important environmental factor that contributes to host energy storage and obesity, and our results provide critical new insights into how this might be achieved. Previous studies in gnotobiotic mice have shown that the intestinal microbiota regulates fat storage in part by suppressing trans-factors, (ii) subverting the expression or activity of activating trans-factors, and/or (iii) inducing expression or activity of repressive trans-factors that function through this module. To distinguish between these models, it will be useful to identify the microbial activity and host transcription factors that regulate angptl4 transcription in the intestinal epithelium. We previously reported that colonization of GF zebrafish with a microbiota harvested from conventionally raised zebrafish or mice resulted in similar suppression of angptl4 transcript levels in the digestive tract angptl4 transcription is expressed by the ‘native’ zebrafish microbiota and in the ‘non-native’ and compositionally distinct mouse gut microbiota. Previous studies have identified individual microbial species sufficient to regulate angptl4 expression in gnotobiotic zebrafish angptl4 homologs and other host genes.Future investigation will be required to determine whether microbial regulation of in3.4 activity is achieved by (i) reducing the accessibility of this chromatin region to activating angptl4 tissue-specific transcription and/or microbial suppression. Because sequence-specific transcription factors typically recognize 6–12 bp motifs C. elegans GATA family member elt-2 has been implicated in mediating intestinal epithelial cell immune responses angptl4. PPAR family members have been identified as key regulators of mammalian Angptl4 expression in adipocytes and hepatocytes through PPAR responsive elements located in the 5′ portion of human ANGPTL4 intron 3 angptl4 locus contains multiple predicted PPRE sites, including several in both the 5′ and 3′ portion of intron 3 angptl4 intron 3 that display the highest sequence homology to the defined human ANGPTL4 intron 3 PPRE mapped outside of minimal regions for either intestinal or islet expression within the 5′ liver module (data not shown). The location of these PPREs in the 5′ region of zebrafish angptl4 intron 3, combined with the fact that the PPREs discovered in human ANGPTL4 are also located in the 5′ portion of intron 3, suggests that the predicted PPREs within the 3′ islet and intestine CRMs of zebrafish angptl4 could represent novel elements for which functional equivalents have not been identified in mammals.In this study, we define two minimal regions within the in3.4 CRM that harbor regulatory activity in the intestine and are also conserved within the Danio lineage . Predictangptl4, databases of predicted TFBSs are incomplete and commonly produce both false-positive and false-negative predictions. Moreover, critical regions identified by SDM might reflect sequences that alter nucleosome positioning or histone modification patterns rather than binding sites for sequence-specific transcription factors. Therefore, we anticipate that unbiased methods for transcription factor discovery will provide the most rigorous approach to an improved understanding of this cis/trans system. The structure-function analysis of the zebrafish in3.4 intestinal enhancer module reported here was designed to identify sequences critical for intestinal activity. It will therefore be interesting to determine whether exogenous microbial inputs are interpreted through the same or distinct motifs within this CRM and how the endogenous trans-acting factors mediating microbial and intestinal regulatory inputs interact to determine transcriptional output.Although these predicted factors represent candidates for controlling intestine-specific regulation of s892Tg(ins:CFP-NTR)All experiments using zebrafish were performed in wild-type TL or Homo sapiens, Hs) ANGPTL4 and zebrafish Angptl4  were acquired through NCBI or Ensembl and aligned using MUSCLE with default settings in silico predictions in silico translated using ExPASy http://mobyle.pasteur.fr/cgi-bin/portal.py. A distance matrix was computed using Phylip 3.67 , and trees were built using the neighbor-joining method. Bootstrap analysis was performed from 1000 replicates. PHYLIP software and the maximum likelihood probability model Protein sequences from top BlastP hits to human (Angptl4 locus from Homo sapiens (GRCh37:19:8419011:8449257:1), Mus musculus (NCBIM37:17:33900702:33928520:−1), Canis familiaris (BROADD2:20:55933601:55958821:1), Danio rerio (Zv9:2:23312551:23337293), Oryzias latipes (MEDAKA1:17:6095931:6120384:1), Takifugu rubripes (FUGU4:scaffold_212:367815:391593:1), and Tetraodon nigroviridis (TETRAODON8:15:3989265:4012887:1) were acquired through Ensembl. 10 kb was chosen as a cutoff because of proximity to neighboring gene loci. Genomic DNA sequence encompassing the angptl4 locus from Danio albolineatus was generously provided by David Parichy . For species without available genomic sequence, angptl4 intron 3 regions were PCR amplified from the relevant genomic DNA using a high-fidelity Taq polymerase  and the primers listed in angptl4 homolog in Ictalurus punctatus (CK419825) was used to design primers targeting exon 3 and exon 4 for PCR amplification of the full-length intron 3. For Cypriniformes species, ESTs EG548328 (Rutilus rutilus), DT085020 , GH715226 , and AM929131 (Carassius auratus) were aligned and used to design primers targeting highly conserved regions in angptl4 exon 3 and exon 4, which we predicted would function for multiple Cypriniformes species. These primers were used to amplify, clone, and sequence the full-length intron 3 from Cyprinus carpio and Chromobotia macracanthus. Alignment of Cc, Cm, and Dr revealed 100% conservation at the extreme 5′ end of the in3.2 module. We used a forward primer targeting in3.2 in combination with a reverse primer targeting exon 4 for cloning of the remaining Cyprinidae species. The bacterial artificial chromosome golwb118_K01 containing the angptl4 locus from Oryzias latipes was provided by Hiroyo Kaneko . Carassius auratus, Puntius conchonius, Cyprinus carpio, Devario aequipinnatus, and Chromobotia macracanthus genomic DNA was extracted from the fins of two individuals acquired from commercial suppliers. Genomic DNA from Ictalurus punctatus and Danio species  from one individual were generously provided by Zhanjiang Liu  and David Parichy , respectively. Novel angptl4 intron 3 sequences generated in this study were deposited in GenBank with accession numbers JN606312–JN606321. Intronic sequences were aligned in mVISTA using LAGAN Genomic DNA sequences encompassing 10 kb upstream, including, and 10 kb downstream of the Ol in.3) or intestine-negative  sequences for islet-positive or intestine-positive MEME motifs, respectively. TOMTOM DNA sequences were queried for predicted transcription factor binding sites deposited in TRANSFAC In situ hybridization was performed in whole zebrafish as described angptl4 were generated by digesting plasmid fj89c07 in pBK-CMV (NCBI Accession XM_686956) with NotI (sense) or BamHI (anti-sense), and transcribed in vitro using T3  or T7 RNA polymerase . Sense riboprobes were used in each experiment as a negative control.Total RNA was extracted from groups of 6 dpf whole zebrafish larvae from 6 dpf zebrafish  using TRIzol Reagent (Invitrogen) or the Qiagen RNeasy (Qiagen) kit using manufacturer's protocol. qRT-PCR was performed as described angptl4 locus were analyzed using UCSC and Ensembl genome browsers. Total RNA was extracted from adult zebrafish intestines and subjected to 5′RACE using the FirstChoice RLM-RACE kit (Ambion), according to the manufacturer's specifications (see angptl4 locus.ESTs at the zebrafish E. coli (Invitrogen). The bacterial artificial chromosome C177A22 containing the zebrafish angptl4 locus was used as the template for all zebrafish angptl4 promoter and intronic PCR amplification and cloning. Mouse BAC , Medaka BAC (golwb118_K01), and sequenced pCR2.1 clones  containing intronic regions orthologous to zebrafish in3.2 from each species were used as source material for cloning in heterologous reporter assays. The plasmid pT2cfosGW Fos minimal promoter and angptl4 5′ upstream regions were PCR amplified and directionally cloned into pT2cfosGW using XhoI and BamHI restriction sites. This step removed both the original Fos promoter and the upstream Gateway site. Of note, we observed significant levels of reporter expression in muscle tissue upon removal of the Gateway cloning site  using the single BglII site located downstream of SV40polyA. A vector (Tg(in3.4-Mmu.Fos:GFP)) containing the angptl4 intronic module in3.4 was used as the source vector for site-directed mutagenesis. To create site-directed substitutions, 50 bp complementary primers containing two 20 bp regions complementary to in3.4, separated by a 10 bp substitution block, were used in circular PCR followed by DpnI treatment to digest methylated parent plasmid. A ClaI restriction site was incorporated into the 10 bp region in order to screen for mutant bacterial colonies. Selection of nucleotide exchange was generally A–C and G–T, except in cases that would create a site amenable to DamI methylation. All plasmids were verified by Sanger dideoxy terminator sequencing. All primers used are listed in All PCR reactions used for cloning were performed with high-fidelity DNA polymerase  and TOP10 chemically competent Co-injections of Tol2 plasmid and transposase mRNA were performed as described Staining of fixed and sectioned 6 dpf zebrafish was performed exactly as described 2). Cells were gently lysed in 10 ml cold RSB plus 0.075% NP-40 and nuclei pelleted at 500× G at 4°C for 10 minutes. Nuclei were incubated with various concentrations of Dnase I  for 10 minutes at 37°C. Reactions were stopped by adding an equal volume of 2× Lysis Buffer  and incubated overnight at 37°C. Digested DNA was extracted using phenol/cholorform/isoamyl alcohol (Fisher), precipitated with ethanol and sodium acetate, and quantified using a fluorimeter . Quantitative PCR was performed as described above using primers listed in Three intestines were dissected from adult zebrafish at 1 year post-fertilization, splayed, and washed extensively with 1× PBS. Intestines were incubated for 15 minutes on ice in 5 ml of Dissociation Reagent 1 , then transferred to Dissociation Reagent 2  and shaken at 25°C until epithelial layers were sufficiently sloughed. Epithelial cells were collected, washed in 1× PBS, and re-suspended in 500 microliters of RSB , catfish , medaka , tetraodon , fugu , xenopus , chicken , mouse , human , dog , pig , and cow . All nodes are significant (>700/1000 bootstrap replicates) except those marked with an asterisk (*). Phylogenic relationships inferred through Maximum Likelihood yield similar branching with differences only in the positions of the nodes separating Xt Angptl3 and Angptl4 and Gg Angptl3 and Angptl4 from mammals (data not shown). Scale bar indicates phylogenetic distance, in number of amino acid substitutions per site. See Phylogeny of Angptl4 and Angptl3 proteins from multiple vertebrate species. Distance phylogram of Angiopoietin-like 3 and 4 from zebrafish ((TIF)Click here for additional data file.Figure S2in silico predicted fibrinogen domain. Black downward arrows designate the exon 2/3 boundary in human, black upward arrows designate the exon2/3 boundary in zebrafish. White downward arrows designate the exon 3/exon 4 boundary in human, white upward arrows designate the exon 3/exon 4 boundary in zebrafish. The black asterisk marks the position of the human E40K variant Alignment of Angptl4 proteins from multiple vertebrate species. (A) Multiple sequence alignment of Angptl4 proteins from representative vertebrate species. Amino acids highlighted in black represent identical residues in at least 50% of species, whereas amino acids highlighted in grey represent biochemically similar residues. The green line denotes the cleavage recognition sequence (TIF)Click here for additional data file.Figure S3angptl4 transcription start site drives expression in the liver but not in the intestine or islet. (A) The zebrafish angptl4 locus and positions of promoter regions assayed in 0–7 dpf transgenic zebrafish are annotated to scale. (B) 5′ RACE and EST data (not shown) establish a single transcription start site directly upstream of exon 1. The positions of the TATA box, transcription start site, and translation start site are annotated.  Non-coding DNA −5.2 kb and −1 kb upstream of the translation start site drives expression in the liver in 6 dpf mosaic animals. Note that the −5.2 kb fragment includes a region −4.9 kb upstream from the TSS that shares extensive homology with medaka ) and −1 kb transgenes (Tg(-1angptl4:GFP)). Scale bars = 50 µm. (G) Fluorescence intensity in mosaic animals is quantified Click here for additional data file.Figure S4angptl4 in3.4 intestinal module exhibits hallmarks of a classical enhancer. (A) Dr in3.4 was cloned in an inverted orientation (in3.4(ds-iv)) downstream of GFP driven by −1 kb of the angptl4 promoter (Tg(-1angptl4:GFP:in3.4inv)). Mosaic and stable intestinal expression patterns are indistinguishable from those when in3.4 is upstream of the Fos minimal promoter (see angptl4 promoter (see The zebrafish oter see . The whioter see . (B) The(TIF)Click here for additional data file.Figure S5angptl4 in3.3 modules. Sequence alignment (MUSCLE) of in3.3 regions from 12 teleost species.Multiple-species sequence alignment of teleost (PDF)Click here for additional data file.Figure S6angptl4 in3.4 modules. Sequence alignment (MUSCLE) of in3.4 regions from 12 teleost species. Asterisks mark 5 individual bp changes that are differentially conserved in intestine-positive modules versus intestine-negative modules within the critical region defined by truncation mapping and SDM.Multiple-species sequence alignment of teleost (PDF)Click here for additional data file.Figure S7angptl4. Quantitative RT-PCR of angptl4 and tdT in dissected digestive tracts from 6 dpf GF and CONVD Tg(in3.2-Mmu.Fos:tdT) animals. GF and CONVD animals were derived from the same Tg(in3.2-Mmu.Fos:tdT) stable line. tdT and angptl4 mRNA were normalized to 18S rRNA levels and are shown as fold difference compared to GF controls averaged across 3 experimental replicates ± SEM . Asterisks denote P-value<.05 from unpaired T-test between GF and CONVD conditions for each gene. Note that module in3.2 includes the intestinal module in3.4 Click here for additional data file.Table S1Angiopoietin-like protein sequences used for inferring phylogenic relationships.(TXT)Click here for additional data file.Table S2Primer sequences used in this study.(XLS)Click here for additional data file.Table S3Allele designations for stable lines created in this study.(XLS)Click here for additional data file.Text S1Angptl4.Text describing the comparative sequence analysis that reveals the zebrafish genome encodes a single ortholog of mammalian (DOC)Click here for additional data file.