Streptomyces coelicolor. Recent study revealed that NdgR is one of the regulatory targets of SigR, an oxidative stress response sigma factor, suggesting that the NdgR plays an important physiological role in response to environmental stresses. Although the regulatory functions of NdgR were partly characterized, determination of its regulon is required for better understanding of the transcriptional regulatory network related with the oxidative stress response.NdgR is an IclR-type transcription factor that regulates leucine biosynthesis and other metabolic pathways in ndgR is induced by SigR under the thiol oxidation, and that an ndgR mutant strain is sensitive to the thiol oxidizing agent, diamide. Through the expression test of NdgR and the target genes for NdgR under diamide treatment, regulatory motifs were suggested. Interestingly, NdgR constitutes two regulatory motifs, coherent and incoherent feed-forward loops (FFL), in order to control its regulon under the diamide treatment. Using the regulatory motifs, NdgR regulates cysteine biosynthesis in response to thiol oxidative stress, enabling cells to maintain sulfur assimilation with homeostasis under stress conditions.We determined genome-wide binding loci of NdgR by using chromatin immunoprecipitation coupled with sequencing (ChIP-seq) and explored its physiological roles. The ChIP-seq profiles revealed 19 direct binding loci with a 15-bp imperfect palindromic motif, including 34 genes in their transcription units. Most genes in branched-chain amino acid and cysteine biosynthesis pathways were involved in the NdgR regulon. We proved that S. coelicolor.Our analysis revealed that NdgR is a global transcriptional regulator involved in the regulation of branched-chain amino acids biosynthesis and sulphur assimilation. The identification of the NdgR regulon broadens our knowledge regarding complex regulatory networks governing amino acid biosynthesis in the context of stress responses in  Streptomycetes are abundant and ubiquitous soil bacteria that are prolific producers of more than two-thirds of natural antibiotics used in the pharmaceutical industry. They have complex regulatory systems for morphological differentiation in response to environmental or nutritional conditions. Genome sequences of this genus also support the existence of complex regulatory networks for sensing and signal transduction to adapt to such conditions -3.S. coelicolor is the most thoroughly studied model organism among this genus that produces antibiotics, including the red-pigmented tripyrrole undecylprodigiosin (Red), the lipopeptide calcium-dependent antibiotic (CDA), and the deep blue-pigmented polyketide actinorhodin (Act). Its genome size has been revealed as 8,667,507 bp, encoding 965 proteins (12.3%) predicted to have regulatory functions, including sigma factors, two-component regulatory systems, and many transcription factor families such as LysR, LacI, ROK, GntR, TetR, IclR, AraC, AsnC, and MerR [E. coli, reflecting its differential regulatory networks under changing stress environments.For instance, proteins 2.3% predMembers of the IclR family of transcriptional regulatory proteins are composed of approximately 250 amino acid residues . The IclS. coelicolor, 16 genes are annotated as members of the IclR family of regulators [ndgR is highly conserved among Streptomyces species as well as other actinomycetes such as Mycobacterium and Corynebacterium [leuCD, which encodes isopropylmalate dehydratase, and have been identified as its transcriptional regulator. In addition, the last step of methionine biosynthesis has been identified as a regulatory target of NdgR [ndgR orthologs in other bacteria has also been revealed. For example, AreB in Streptomyces clavuligerus controls the biosynthesis of leucine and secondary metabolites [Corynebacterium glutamicum, LtbR has been characterized as a regulator involved in leucine and tryptophan biosynthesis [In gulators . Among tacterium ,16. NdgRabolites . In Coryynthesis .ndgR [Meanwhile, it was revealed that SigR, an oxidative stress response sigma factor, binds to the upstream region of ndgR . SigR isndgR . This inStreptomyces [S. coelicolor harboring a 6× myc-tagged NdgR that was successfully utilized for the immunoprecipitation of NdgR-DNA complexes. This experiment revealed that NdgR regulates not only leuCD but also most of genes involved in leucine biosynthesis in S. coelicolor. Despite the previous studies, the DNA-binding locations of NdgR under physiologically relevant conditions have not been described at a high resolution, and on a genome-wide scale. Here, we further investigate the NdgR regulon in vivo using chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and further explore the responses of the NdgR regulatory network to thiol oxidative stress. We also discuss the regulatory roles of NdgR in S. coelicolor.Previously, we developed a versatile PCR-based tandem epitope tagging tool for the identification of direct binding targets of DNA-binding proteins of ptomyces . Using tin vitro by DNA-binding experiments [in vivo analysis of direct interaction between NdgR and its cognate DNA has not been described. To study the binding characteristics of NdgR to the S. coelicolor chromosome, we exploited a ChIP-seq method that has been used for genome-wide determination of in vivo binding locations of regulatory proteins. We constructed a 6× myc-tagged NdgR strain using homologous recombination for the immunoprecipitation (IP) using a specific anti-c-myc antibody [S. coelicolor genome (NC_003888). Using the MACS program, 19 NdgR-binding loci were detected with stringent cut-off conditions  . Meanwhile, the peak summits of 4 genes  were located to intragenic regions. With these criteria, we identified 34 genes in the NdgR regulon , ilvD (SCO3345), ilvB (SCO5512), leuB (SCO5522), and ndgR-leuC intergenic region (SCO5552-SCO5553) were previously annotated as direct regulatory targets of NdgR by in vitro experiments such as electrophoretic mobility shift assay and DNA affinity capture assay [scbR (SCO6264), which is a gene directly regulated by NdgR [in vivo and in vitro experimental conditions. In addition, we observed low levels of NdgR binding at the promoters of metH (SCO1657) and leuA (SCO5559) relative to the other binding peaks. Taken together, these results show that binding locations of NdgR were successfully detected in vivo.Five genes, re assay ,16. The  by NdgR , was notAlthough the putative DNA-binding motifs of NdgR and its orthologs were previously predicted using the known binding sequences of other IclR-type regulators in different strains -18, cleain vitro experiments such as electrophoretic mobility shift assay and DNA affinity capture assay [metF, ilvB, ilvD, leuB, and the intergenic region between NdgR and leuCD. The putative motif from genome-wide prediction using FIMO was found in the promoters of known targets, metH and leuA. This result further supports that their low intensity in ChIP-seq profiles represents the subtle differences between in vivo and in vitro experimental conditions.We identified the putative binding motif from previously known targets of NdgR as revealed by re assay ,16. Thisftp://ftp.sanger.ac.uk/pub/S_coelicolor/classwise.txt) , β-isopropylmalate dehydratase , and β-isopropylmalate dehydrogenase (LeuB). Despite the scattered locations of those genes along the chromosome, NdgR directly bound their upstream regions. Interestingly, the NdgR mutant (BG11) exhibited methionine auxotrophy, but not leucine auxotrophy [NdgR directly regulates eight genes in the biosynthetic pathways of branched chain amino acids (BCAAs) Figure A. For inxotrophy . Notwithxotrophy -27.FigurcysA, cysM, cysN, cysD, cysC, cysH and cysI) that are involved in sulfur-assimilation metabolism , cysD (SCO6098), and cysC (SCO6099), participate in 3′-phosphoadenylyl sulfate (PAPS) formation from sulfate. PAPS reductase encoded by cysH (SCO6100) converts PAPS to sulfite. The serial reactions are followed by two pathways that result in thiosulfate production by a thiosulfate sulfurtransferase and sulfide production by a sulfite reductase encoded by cysA (SCO4164) and cysI (SCO6102), respectively. The two metabolites (thiosulfate and sulfide) are sulfur donors for the sulfur assimilation into O-acetyl-L-serine by cysteine synthase encoded by cysM (SCO2910) [Next, we observed that NdgR directly bound the upstream region of three transcription units including seven genes  ,31.cysG (SCO1553). Siroheme is a prosthetic group that participates in six-electron reduction reactions catalyzed by both sulfite and nitrite reductases. CysG converts uroporphyrinogen III, which is a precursor of heme and cobalamin (vitamin B12), to siroheme using multifunctional activities such as SAM-dependent methylase, dehydrogenase and ferrochelatase [thiL (SCO5562) and moeB (SCO5178), respectively. In addition, phosphomethylpyrimidine kinase encoded by thiD (SCO5563) in the polyamine biosynthesis category is likely involved in thiamine metabolism.Moreover, NdgR bound to the promoter region of putative siroheme synthase encoded by helatase . BiosyntS. clavuligerus, AreB, an ortholog of NdgR, bound to the upstream region of the pathway-specific regulator of clavulanic acid and cephamycin C, and the areB deletion mutant increased their production. Moreover, the ndgR mutant showed overproduction of actinorhodin in our experimental conditions [ndgR and its ortholog [In nditions . Interesortholog ,17, nonendgR as one of the targets of the oxidative stress response sigma factor SigR [ndgR by SigR in response to thiol oxidative stress. NdgR was transiently induced by diamide treatment in the presence of SigR  and complemented mutant (BG13) spores were spotted on the R5- agar plates containing 0.6 mM diamide, BG11 cells were found to be sensitive to diamide even in the complex media . This result is likely due to the fact that 70% of total fatty acids in the membrane are branched-chain fatty acids, which are synthesized from the precursors derived from BCAA degradation [The role of BCAAs in response to stress conditions has not been completely elucidated in bacteria; however, ovis BCG . In planovis BCG -36. It hovis BCG . Isovaleradation .cysIHCDN, cysM, and cysA are significantly increased by SigB under osmotic and oxidative stresses [Sulfur-related reactions are well known as anti-oxidation reactions in actinomycetes ,20,28. EcysI in cysIHCDN operon, cysA and cysM in cysteine biosynthesis, and ndgR. First, we confirmed that the transcriptional level of ndgR is induced by diamide. All of the target genes were also induced by diamide regardless of the presence of ndgR. This result indicates that other transcription factors related to oxidative stress could also exist for the regulation of them. Next, we observed two regulatory modes based on the measurement of expression levels affected by NdgR under diamide treatment. cysA and cysI were induced by NdgR regardless of diamide. Meanwhile, cysM seems to be hardly expressed without diamide treatment regardless of the presence of ndgR. Although NdgR may bind to the promoter of cysM in absence of diamide treatment, the expression level may not be decreased because cysM is not expressed originally. However, NdgR repressed the expression of cysM in the presence of diamide; thus, the role of NdgR as a dual regulator was confirmed.The members of the IclR family of regulators have been demonstrated to be activators, repressors, and dual-role proteins in many cases . HowevercysI and cysA is controlled by C1-FFL with OR-gates, cells can maintain sulfur assimilation activity after the signal is OFF. Meanwhile, an I1-FFL is a regulatory pattern in which an activator (D) controls a target gene (T) and also activates a repressor (N) of that target gene. This motif is a pulse generator and a response accelerator [We further explored the physiological roles of these two regulatory modes by NdgR using network motif theory . The twoelerator . In addielerator . CysM haS. coelicolor to maintain homeostasis in stress conditions.We revealed that NdgR controls sulfur assimilation into the cysteine biosynthesis pathway through two regulatory modes. Using C1-FFL with OR-gate, NdgR can initiate a reduction in sulfate immediately in response to the stress and stably protect assimilation systems against transient loss of signal. At the final step, NdgR acts as a memory of stress intensity by using the I1-FFL motif. Thus, it mediates a continual temporal comparison between the present and past levels of stresses. During the stress condition, the memory is adjusted to the new level of stress intensity, and cysteine synthesis by CysM returns to its basal level. Thus, this modulation prevents excess synthesis of cysteine, which is energetically wasteful and avoids potential osmotic imbalances. Using these regulatory modes, NdgR likely provides an advantage for S. coelicolor using ChIP-seq and revealed its physiological role under oxidative stress conditions. In our growth condition, we found that NdgR directly regulates 34 genes that are involved in the synthesis of BCAAs and cysteine using 19 regulatory binding sites. We confirmed that SigR, an oxidative stress response sigma factor, induces NdgR in response to thiol oxidative stress induced by diamide treatment. Interestingly, this implied physiological roles of the NdgR regulon in S. coelicolor. Degradation of BCAAs is known to produce major CoA precursors of branched-chain fatty acids, which are the major components of bacterial cell membranes; thus, their production enhances the robustness of the cell. Furthermore, BCAAs can serve as an alternative electron transport donor for energy production under various stress conditions, similarly to that which occurs in plants. Because the induction of biosynthesis of BCAA under stress conditions has also been reported in other bacteria, the exact roles of BCAAs in stress conditions require further investigation. In addition, many BCAA biosynthesis genes require sulfur-containing cofactors such as thiamine and iron-sulfur clusters, which are vulnerable to thiol oxidative stress; these cofactors can be replenished by sulfur-related pathways such as cysteine biosynthesis, which is also regulated by NdgR. Furthermore, cysteine is one of the precursors of mycothiol, a major redox buffer in S. coelicolor that helps maintain redox balance in the cell. The cysteine biosynthesis pathway is regulated by NdgR under thiol oxidative stress using coherent and incoherent FFL, which enables cells to adapt to the environmental conditions by maintaining homeostasis. This study provides a deeper understanding the mechanisms by which NdgR regulates amino acid biosynthesis in response to stress in S. coelicolor. In addition, this model system shows a possibility such that revealing the global regulatory network of transcription factors using ChIP-seq technique will enable in depth understanding of their physiological roles in S. coelicolor.We identified genome-wide binding sites of NdgR in S. coelicolor A3 (2) M145 and E. coli K-12 MG1655 and its derivatives. For the ChIP experiments, strain expressing 6× myc-tagged NdgR constructed previously [2HPO4, 0.02% MgSO4 · 7H2O, 0.001% FeSO4 · 7H2O, 2.2% agar, 0.05% L-asparagine, and 1% N-acetylglucosamine. For sensitivity testing and gene expression analysis, spores of S. coelicolor A3(2) M145 and an ndgR knockout strain, previously constructed using PCR targeting method [2SO4, 1.01% MgCl2 · 6H2O, 1% glucose, 0.01% Difco casamino acids, 0.2% trace element solution composed of 0.004% ZnCl2, 0.02% FeCl3 · 6H2O, 0.001% CuCl2 · 2H2O, 0.001% MnCl2 · 4H2O, 0.001% mg Na2B4O7 · 10H2O, 0.001% mg (NH4)6Mo7O24 · 4H2O in 1 l of deionized water, 0.5% yeast extract, 0.57% TES buffer, and 0.7% (v/v) 1 N NaOH in 1 l of distilled water.All strains used are eviously  was growg method ,16,40, wChIP experiments were performed as described previously . Cells hS. coelicolor reference genome (GenBank: NC_003888) with CLC Genomics Workbench 6.5. The alignment BAM file was analyzed using MACS v1.4 to detect read-enriched regions in the genome [10 , and fold-enrichment greater than 3. For conserved motif searches, nucleotide sequences (400 bp) centered on each peak were extracted and submitted to the MEME software suite [Illumina reads were aligned to the e genome . Enrichere suite . The parndgR disruption mutant (BG11) and ndgR complemented mutant (BG13) were obtained using a PCR-targeting mutagenesis protocol as described previously [6, 105, 104, 103, and 102) were spotted on R5- agar containing 0.6 mM diamide or 0 mM diamide (control) and incubated for 5 days at 30°C.The eviously ,16,40. FTotal RNA extraction was performed with the RNeasy Mini Kit (Qiagen) according to the manufacturer’s instructions. Sample aliquots were obtained after 30 min of incubation with or without 0.6 mM diamide at the exponential phase (OD600 ~ 0.5). RNA was reverse transcribed into first-strand cDNA using SuperScript™ III Reverse Transcriptase (Invitrogen). qPCR was performed using a CFX96 real-time system . All samples were measured in triplicate. Gene expression level was normalized by using housekeeping gene (SCO5820) as internal control.All raw sequence data files have been deposited to Gene Expression Omnibus through accession number GSE59010.


P. chrysogenum. In recent years, the multisubunit protein complex velvet has been identified as one of the key regulators of fungal secondary metabolism and development. However, until recently, only a little has been known about how velvet mediates regulation at the molecular level. To address this issue, we performed ChIP-seq (chromatin immunoprecipitation in combination with next-generation sequencing) on and follow-up analysis of PcVelA, the core component of the velvet complex in P. chrysogenum. We demonstrate direct involvement of velvet in transcriptional control and present the putative methyltransferase PcLlmA as a new downstream factor and interaction partner of PcVelA.Filamentous fungi are of major interest for biotechnological and pharmaceutical applications. This is due mainly to their ability to produce a wide variety of secondary metabolites, many of which are relevant as antibiotics. One of the most prominent examples is penicillin, a β-lactam antibiotic that is produced on the industrial scale by fermentation of  Penicillium chrysogenum is the sole industrial producer of the β-lactam antibiotic penicillin, which is the most commonly used drug for treating bacterial infections. In P. chrysogenum and other filamentous fungi, secondary metabolism and morphogenesis are controlled by the highly conserved multisubunit velvet complex. Here we present the first chromatin immunoprecipitation next-generation sequencing (ChIP-seq) analysis of a fungal velvet protein, providing experimental evidence that a velvet homologue in P. chrysogenum (PcVelA) acts as a direct transcriptional regulator at the DNA level in addition to functioning as a regulator at the protein level in P. chrysogenum, which was previously described. We identified many target genes that are related to processes known to be dependent on PcVelA, e.g., secondary metabolism as well as asexual and sexual development. We also identified seven PcVelA target genes that encode putative methyltransferases. Yeast two-hybrid and bimolecular fluorescence complementation analyses showed that one of the putative methyltransferases, PcLlmA, directly interacts with PcVelA. Furthermore, functional characterization of PcLlmA demonstrated that this protein is involved in the regulation of conidiosporogenesis, pellet formation, and hyphal morphology, all traits with major biotechnological relevance.IMPORTANCE Filamentous fungi are of major interest for biotechnological and pharmaceutical applications. This is due mainly to their ability to produce a wide variety of secondary metabolites, many of which are relevant as antibiotics. One of the most prominent examples is penicillin, a β-lactam antibiotic that is produced on the industrial scale by fermentation of P. chrysogenum. In recent years, the multisubunit protein complex velvet has been identified as one of the key regulators of fungal secondary metabolism and development. However, until recently, only a little has been known about how velvet mediates regulation at the molecular level. To address this issue, we performed ChIP-seq (chromatin immunoprecipitation in combination with next-generation sequencing) on and follow-up analysis of PcVelA, the core component of the velvet complex in P. chrysogenum. We demonstrate direct involvement of velvet in transcriptional control and present the putative methyltransferase PcLlmA as a new downstream factor and interaction partner of PcVelA. Penicillium chrysogenum, which was first described in 1928 , was first described as a light-dependent regulator in Aspergillus nidulans  reduces penicillin production and causes light-independent formation of conidiospores. Moreover, the deletion results in dichotomous branching of hyphae and increases pellet formation in shaking cultures -dependent methyltransferase (MTase) LaeA (loss of aflRexpression A), which acts as a global regulator of secondary metabolism and development in various euascomycetes  . Supportt manner . The firpsulatum . By chroectively . This fiectively , demonstAlthough extensive efforts were made to decipher the molecular mechanisms that control velvet protein-mediated regulation in various fungi, these mechanisms remain poorly understood. Therefore, the aim of this work was to shed light onto PcVelA regulatory functions on a genome-wide scale by using ChIP combined with next-generation sequencing (ChIP-seq). Follow-up analyses were designed to further elucidate PcVelA DNA-binding properties on a molecular level and to enable functional characterization of new PcVelA downstream factors.velA under the control of its native promoter sequence and under conditions scheduled for ChIP. As only minimal amounts of the PcvelA transcript were detected in the wild-type P2niaD18 and ΔPcku70-FRT2 strains  Plasmid pPcVelA-EGFP, harboring a Pgpd::PcvelA::egfp fusion construct, was used for ectopic integration into the ΔPcvelA strain, a marker-free PcvelA deletion strain. (C) PCR analysis confirmed integration of Pgpd::PcvelA::egfp. Binding positions of primers PcvelA_f and egfp_r are indicated as arrows in panel B. (D) Presence of the epitope-tagged protein PcVelA-EGFP in crude protein extract from strain PcVelA-ChIP was confirmed using SDS-PAGE and Western blot analysis. (E) Fluorescence microscopy confirmed the nuclear localization of PcVelA-EGFP in the PcVelA-ChIP strain. Strains were grown on solid medium for 48 h. Scale bar = 10 µm. Download Figure S1, TIF file, 8.9 MB.Construction of PcVelA-ChIP strains. (A) Northern blot analysis revealed low expression of PcCopyright © 2016 Becker et al.2016Becker et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the P. chrysogenum, Saccharomycescerevisiae, and higher eukaryotes, which revealed overlaps of 10 to 50% between TF occupancy and the expression of neighboring genes  were regarded as overlapping. Doing so, we identified 592 sites that were specifically bound by PcVelA in both biological replicates see , but theng genes –25.10.1128/mSphere.00149-16.7Data Set S1 Data Set S1, XLSX file, 0.3 MB.Complete data set from bioinformatics analysis of PcVelA ChIP-seq data. Download Copyright © 2016 Becker et al.2016Becker et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the In order to validate the biological significance of our data set and to rule out bias from the bioinformatics analysis, the PcVelA-specific enrichment of four selected target regions that were identified in the ChIP-seq analyses was confirmed using quantitative ChIP-PCR. Target regions were selected to cover a range of PcVelA binding sites, from high-affinity to midaffinity sites, as deduced from the ChIP-seq data. The enrichment of the target region was calculated as the ratio of the region of interest to the level of a control region showing no PcVelA-specific enrichment in ChIP DNA relative to this ratio in the input DNA. A randomly selected region that showed no specific enrichment in the ChIP-seq data was used as a control (NC). Data from the ChIP-PCR analysis were compared to peak values obtained in the bioinformatics analysis. These values represent the average number of sequence tags found within a peak region after normalization to a total of 10 million mapped tags. The ChIP-PCR results were consistent with the peak values, confirming the specific enrichment of all tested PcVelA target regions .10.1128/mSphere.00149-16.2Figure S2 Figure S2, TIF file, 0.6 MB.Validation of PcVelA ChIP-seq data. ChIP-PCR analysis was performed to analyze the enrichment of selected PcVelA target regions in ChIP DNA compared to input DNA. Enrichment was calculated as the ratio of the region of interest to a control region showing no PcVelA-specific enrichment in ChIP-seq experiments. Another region showing no PcVelA-specific enrichment in ChIP-seq analysis is shown as a control (NC). ChIP-PCR ratios (gray bars) are shown in comparison to the corresponding peak values, as obtained from bioinformatics analysis (black bars). Values for ChIP-PCR are the mean scores from three biological replicates; averages ± standard deviations are indicated. Peak regions are named according to neighboring genes see . DownloaCopyright © 2016 Becker et al.2016Becker et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the velA deletion strain to those in the corresponding ΔPcku70 wild-type strain (con-6 (Pc16g03240), flbC (Pc12g12190), flbD (Pc13g03170), artA (Pc18g03940), and brlA (Pc23g00400), all of which are related to different developmental steps of conidiation (treA or ath1 (Pc16g11870), which encodes an α,α-trehalose glucohydrolase, Pc16g06690, which encodes a precursor of the spore wall fungal hydrophobin DewA, and Pc13g09910, which encodes a late-embryogenesis-abundant (LEA) domain protein , which encodes a TF with a basic helix-loop-helix domain. Notably, StuA not only regulates penicillin biosynthesis in P. chrysogenum , revealing that the protein directly controls the expression of 24 TFs, which in turn might be involved in transcriptional control on a second hierarchical level  fungi database did not reveal any significant matches, comparison to the JASPAR CORE (2014) vertebrate database revealed some interesting similarities to other motifs. As shown in H. capsulatum (A. nidulans VosA (We used the MEME (Multiple Expression Motifs [EM] for Motif Elicitation) platform to perform cVelA.M1 , that wapsulatum  as well ans VosA .10.1128/mSphere.00149-16.3Figure S3 P values, and E values are indicated. The size of each letter is proportional to the frequency of each nucleotide at this position within the consensus sequence. Motifs are centered on common central nucleotides. Download Figure S3, TIF file, 6.6 MB.Comparison of PcVelA.M1 to the JASPAR CORE databases. The PcVelA.M1 motif sequence was submitted to TOMTOM , using dCopyright © 2016 Becker et al.2016Becker et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the S-transferase (GST)-tagged version of the PcVelA N-terminal region from amino acids 1 to 256 (PcVelA1–256), which was purified from Escherichia coli, and 50-nt DNA sequences (PcLlmA_2 and PcLlmA_4) derived from a region within the PcllmA upstream sequence  using a glutathione sequence . Both ole  and protein-DNA complexes (→) are indicated. Download Figure S4, TIF file, 0.7 MB.EMSA using full-length PcVelA. EMSAs were performed using 50-nt radiolabeled double-stranded oligonucleotide probes  derived from the PcCopyright © 2016 Becker et al.2016Becker et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the velA expression, and the ΔPcvelA strain with levels in wild-type P2niaD18. As a reference for normalization, we used amplification of a fragment of the 18S rRNA. All strains were grown under the same conditions as for ChIP-seq sample preparation. As shown in llmA (Pc21g02240), PcllmB (Pc18g01840), Pc21g12700, and Pc22g01170. Pc18g06010 showed PcVelA-dependent expression in qRT-PCR but not in microarray analysis , which have previously been described as velvet-associated proteins . Bec. Bec6). analysis . Next, t Pc21g022, PcllmB proteins . In geneproteins , 44. Theproteins , 45, 46.milarity . Howevermilarity , 44, 46.10.1128/mSphere.00149-16.5Figure S5 A. nidulans LlmF, VipC, and VapB. Alignments were visualized using Jalview according to the ClustalX color scheme . The secondary-structure model of PcLlmA was generated using the I-TASSER server  Alignment of amino acid sequences revealed a high degree of conservation between PcLlmA, PcLlmB, and PcLaeA as well as R server  and is iR server , 45 are R server  server. Copyright © 2016 Becker et al.2016Becker et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the llmA as a direct target gene of PcVelA and because the SAM-binding domains of PcLlmA and other velvet-associated MTases were highly conserved  approach. Briefly, diploid yeast strains that synthesize both the bait and the prey proteins were spotted on selective media that lacked adenine and histidine (in order to select for ADE2 and HIS3) and that were supplemented with X-α-Gal . Only those interactions that could be verified based on both reporter systems (growth on selective media and blue color) were considered positive. Interestingly, PcLlmA interacted with PcVelA but not with the other velvet components, i.e., PcVelB, PcVelC, PcVosA, or the putative MTase PcLaeA  (eyfp fragments encoding either the N or the C terminus of the yellow fluorescent protein (YFP), and strains harboring both constructs were analyzed using fluorescence microscopy. As a control, we investigated strains that generated only split enhanced YFPs (EYFPs) and strains producing one split EYFP together with either EYFP-PcVelA or PcLlmA-EYFP. As shown in velA-eyfp and PcllmA-eyfp fusion constructs showed clear EYFP signals, while no fluorescence was detectable in control strains  . Genes e strains . DAPI , defined by the consensus sequence AACCTTGGAA, which was present in 46.5% of all PcVelA peak regions (P ≤ 0.001). The sequence shows strong similarity to the DNA-binding motif sequence described for the Ryp2/Ryp3 heterodimer (GAACCATGGT)   as well CCATGGT) . Interesin vitro . Howeverin vitro  showed tin vitro .llmA affected conidiosporogenesis, pellet formation, hyphal morphology, and germination characteristics, deletion of the gene resulted in phenotypic changes only within the context of conidiospore germination. Interestingly, the observed changes in asexual sporulation are not dependent on BrlA or PcVelA, as expression of the corresponding genes is not effected in the PcllmA deletion and overexpression strains. As part of the functional characterization of PcLlmA, Y2H and BiFC analysis revealed direct interaction between PcVelA and PcLlmA at the protein level. This interaction seemed to be restricted to PcVelA, as no interactions between PcLlmA and other components of the velvet complex were detected. This observation is consistent with the results of previous Y2H analyses which found that the interaction between the putative MTase PcLaeA and components of the velvet complex was mediated solely by PcVelA  served as a host for heterologous overexpression of PcVelA-GST   , TOMTOM te.org/) , and thete.org/) .1–256. Fifty-nucleotide double-stranded oligonucleotides . For shift experiments, 3.5- to 7.0-fmol (~50 to 100 cps) samples of radiolabeled oligonucleotides were incubated with various protein concentrations in the presence of 2 µl binding buffer  and 1 µg poly(dI-dC)-poly(dI-dC)  in a total volume of 20 µl for 20 min at room temperature. Samples were run on 5% polyacrylamide gels at 4°C in 190 mM glycine, 27 mM Tris-HCl, pH 8.5.Gel shift assays were performed using oligonucleotides derived from ChIP-enriched regions and purified GST-PcVelAE. coli was performed as described earlier .For analysis of pellet formation, P. chrysogenum strains were grown on solid CCM, and incubation under light or dark conditions was performed for 120 h at 27°C.Sporulation assays were performed as described previously  with somSRP067220.Raw sequencing data from ChIP-seq experiments are available from the NCBI SRA database under accession number


Nipped-B-Like (NIPBL) gene, and milder cases often have missense or in-frame deletion mutations in genes encoding subunits of the cohesin complex. Cohesin mediates sister chromatid cohesion to facilitate accurate chromosome segregation, and NIPBL is required for cohesin to bind to chromosomes. Individuals with CdLS, however, do not display overt cohesion or segregation defects. Rather, studies in human cells and model organisms indicate that modest decreases in NIPBL and cohesin activity alter the transcription of many genes that regulate growth and development. Sister chromatid cohesion factors, including the Nipped-B ortholog of NIPBL, are also critical for gene expression and development in Drosophila melanogaster. Here we describe how a modest reduction in Nipped-B activity alters growth and neurological function in Drosophila. These studies reveal that Nipped-B heterozygous mutant Drosophila show reduced growth, learning, and memory, and altered circadian rhythms. Importantly, the growth deficits are not caused by changes in systemic growth controls, but reductions in cell number and size attributable in part to reduced expression of myc (diminutive) and other growth control genes. The learning, memory and circadian deficits are accompanied by morphological abnormalities in brain structure. These studies confirm that Drosophila Nipped-B mutants provide a useful model for understanding CdLS, and provide new insights into the origins of birth defects.Individuals with Cornelia de Lange Syndrome (CdLS) display diverse developmental deficits, including slow growth, multiple limb and organ abnormalities, and intellectual disabilities. Severely-affected individuals most often have dominant loss-of-function mutations in the  Nipped-B gene, which is equivalent to the NIPBL gene, show characteristics similar to individuals with CdLS. These include reduced growth, learning, memory, and altered circadian rhythms. These studies thus indicate that Drosophila Nipped-B mutants are a valuable system for investigating the causes of the CdLS birth defects, and developing potential treatments. They also reveal that the slow growth in Drosophila Nipped-B mutants is not caused by disruption of systemic hormonal growth controls, and that the learning and memory deficits may reflect changes in brain structure.Cornelia de Lange Syndrome (CdLS) alters many aspects of growth and development. CdLS is caused by mutations in genes encoding proteins that ensure that chromosomes are distributed equally when a cell divides. These include genes that encode components of the cohesin complex, and Nipped-B-Like (NIPBL) that puts cohesin onto chromosomes. Individuals with CdLS have only modest reductions in the activities of these genes and do not show changes in chromosome distribution. Instead, they show differences in the expression many genes that control development. Animal models of CdLS will be useful for studies aimed at understanding how development is altered, and testing methods for treating CdLS. We find that Drosophila with one mutant copy of the  The ring-like cohesin complex consisting of the Smc1, Smc3, Stromalin (SA) and Rad21 proteins is required for sister chromatid cohesion and accurate chromosome segregation. Cohesin is loaded on to chromosomes by the kollerin complex, consisting of the NIPBL adherin (Nipped-B in Drosophila) and Mau-2 proteins, and is removed from chromosomes by the releasin complex containing the Wapl and Pds5 proteins . Adherinc-myc, display high transcriptional pausing. In addition to direct control of active gene transcription, evidence from Drosophila shows that cohesin indirectly controls epigenetic silencing of homeotic genes by Polycomb complexes via sequestration of the PRC1 Polycomb complex at active genes and limiting the amount available for silencing  were outcrossed to wild-type Oregon R males for all experiments, generating GFP negative progeny that are heteroallelic across the genome. Control and mutant crosses were always performed at the same time, and used the same batch of food.For growth and nutrition studies, flies were cultured on cornmeal, yeast and molasses media in agar  at 25°. Nipped-B407 was chosen for detailed analysis in growth experiments because it has been shown to be rescued by Nipped-B cDNA transgenes, providing evidence that Nipped-B407 is the only essential gene mutation in the chromosome 75]. Brieribed in .Sleep and circadian rhythm tests were performed and analyzed as described ,77. AdulBrains from 2–4 day old adults were dissected in PBS, fixed, and stained as described ,76. AntiMechanical stress tests (bang sensitivity) and heat shock assays were performed as described ,80. OverS1 FigNipped-B in centromere-proximal heterochromatin on chromosome 2R, with extensive repeat sequences, including many natural transposable elements . The Nipped-B gene displays histone H3 lysine 9 trimethylation (H3K9me3) and HP1 occupancy typically associated with heterochromatin. The homozygous Nipped-B407 genomic sequence shows that nucleotide 579,589 (release 5 April 2006 coordinates) in the second to last exon matches the reference genome , while the RNA sequence from Nipped-B407 / Oregon R wing discs does not, with all aligned reads showing C in the minus strand (G in plus strand). This is a silent mutation in the wobble position of a Thr codon that does not change the amino acid sequence. Thus most of the RNA is not produced by Nipped-B407, suggesting that is essentially a null allele. No mutations were found in the Nipped-B407 coding sequences by genomic sequencing. RNA-seq sequence coverage shown in Nipped-B407 is likely a chromosomal rearrangement  that is hidden by the repetitive sequence nature of the surrounding environment.The top diagram shows the location of (TIF)Click here for additional data file.S2 FigNipped-B407 homozygous 2nd instar larvae (orange), and for the minus strand RNA-seq coverage for P57B / Oregon R wing discs (black) and Nipped-B407 / Oregon R wing discs (blue). The mathematical difference between the P57B and Nipped-B407 log2 RNA-seq coverage (ΔP57B-Nipped-B407) is shown in the bottom track (green) to visually compare the transcript patterns in P57B and Nipped-B407. This subtraction, which calculates fold-differences, reveals that there are no significant changes in coverage across the gene between the P57B control and Nipped-B mutant wing discs, indicating that there are no changes in the transcription start sites, termination sites or splicing. The middle panel shows the 5’ end of the gene, where there is substantial alternative splicing, to show that the splicing pattern is not detectably altered. The bottom panel shows the log2 RNA-seq bedgraphs (combined plus and minus strand transcription) for the entire region surrounding Nipped-B, indicating that transcription of the genes neighboring Nipped-B are not altered by the Nipped-B407 mutation. Combined with the sequence comparison in Nipped-B RNA in Nipped-B407 / Oregon R wing discs is from the wild-type allele.The top shows the sequence coverage (log2 bedgraph) for the minus strand genome sequence of (TIF)Click here for additional data file.S3 FigThe top panel is a boxplot of the wing blade areas of females of the indicated genotypes, and the bottom panel gives the p values for the indicated comparisons (t test).(TIF)Click here for additional data file.S4 Figwiso31, Nipped-B291.1, and Nipped-B407 flies. The numbers of flies in each genotype are described in  Average double plotted actograms for (TIF)Click here for additional data file.S5 FigNipped-B mutant and control males (A1) and females (B1) recorded in 12 hour L/D cycles (15 to 16 flies of each genotype and sex for over six days). The activity of both male and female Nipped-B mutants is comparable to that of wild-type controls, suggesting that they are not hyperactive.  Sleep profiles for males (A2) and females (B2) with standard error bars. These patterns were analyzed in more detail in  Average activity patterns of (TIF)Click here for additional data file.S1 TableThe spreadsheet tabs give the expression values for active genes  (EXPRESSED), the active genes that decrease in expression with a p value ≤ 0.05 (DOWN), the functional gene ontology analysis ,82 of th(XLSX)Click here for additional data file.


Bradyrhizobium japonicum USDA 110, the nitrogen-fixing symbiont of soybean, and developed algorithms to map TSSs and promoters.Differential RNA-sequencing (dRNA-seq) is indispensable for determination of primary transcriptomes. However, using dRNA-seq data to map transcriptional start sites (TSSs) and promoters genome-wide is a bioinformatics challenge. We performed dRNA-seq of de novo algorithm to identify promoter motifs upstream of mapped TSSs, which is publicly available, and found motifs mainly used in symbiosis (similar to RpoN-dependent promoters) or under both conditions (similar to RpoD-dependent promoters). Mapped TSSs and putative promoters, proteomic evidence and updated gene annotation were combined into an annotation file.A specialized machine learning procedure for TSS recognition allowed us to map 15,923 TSSs: 14,360 in free-living bacteria, 4329 in symbiosis with soybean and 2766 in both conditions. Further, we provide proteomic evidence for 4090 proteins, among them 107 proteins corresponding to new genes and 178 proteins with N-termini different from the existing annotation . Guided by proteomics evidence, previously identified TSSs and TSSs experimentally validated here, we assign a score threshold to flag 14 % of the mapped TSSs as a class of lower confidence. However, this class of lower confidence contains valid TSSs of low-abundant transcripts. Moreover, we developed a B. japonicum represent a valuable resource for future systems biology studies and for detailed analyses of individual non-coding transcripts and ORFs. Our data will also provide new insights into bacterial gene regulation during the agriculturally important symbiosis between rhizobia and legumes.The genome-wide TSS and promoter maps along with the extended genome annotation of The online version of this article (doi:10.1186/s12864-016-2602-9) contains supplementary material, which is available to authorized users. Bradyrhizobium japonicum USDA 110, a symbiont of the soybean plant Glycine max  [https://github.com/mimakaev/promoter_mapper]. All other datasets supporting the conclusions of this article are included within the article and its Additional files.The RNA-seq data set supporting the conclusions of this article is available in the [NCBI’s Gene Expression Omnibus] repository [GEO Series accession number GSE69059 and SE69059] . The pro


Saccharomyces cerevisiae. Quantitative sequence-to-affinity models were built from high-throughput in vivo RNA binding protein (RBP) binding data for 15 yeast RBPs. Integration of these models with genome-wide mRNA expression data allowed us to estimate protein-level RBP regulatory activity for individual segregants from a genetic cross between two yeast strains. Treating these activities as a quantitative trait, we mapped trans-acting loci  that act via posttranscriptional regulation of transcript stability. We predicted and experimentally confirmed that a coding polymorphism at the IRA2 locus modulates Puf4p activity. Our results also indicate that Puf3p activity is modulated by distinct loci, depending on whether it acts via the 5′ or the 3′ untranslated region of its target mRNAs. Together, our results validate a general strategy for dissecting the connectivity between posttranscriptional regulators and their upstream signaling pathways.Understanding how genomic variation influences phenotypic variation through the molecular networks of the cell is one of the central challenges of biology. Transcriptional regulation has received much attention, but equally important is the posttranscriptional regulation of mRNA stability. Here we applied a systems genetics approach to dissect posttranscriptional regulatory networks in the budding yeast  Howevercis-regulatory elements in the 3′ untranslated region (UTR), examples also exist of stability regulation through the 5′ UTR of the transcripts, such as an upstream open reading frame (ORF) that can inhibit ribosomal scanning and promote mRNA decay  homology domain family. The regulatory activities of these factors typically change in opposite directions in response to changes in nutrient conditions, suggesting regulation by a single genetic locus. However, we found that the activity of these two PUF proteins are linked to distinct genetic loci. We mapped distinct aQTLs depending on whether Puf3p acts via binding to the 5′ or to the 3′ UTR of its target mRNAs. We also performed experiments to determine the effect of allelic variation at the IRA2 locus on Puf4p posttranscriptional activity. We found that the activity of Puf4p depends on the allele at the IRA2 locus in the BY but not the RM strain background. It is likely that other polymorphisms in RM make expression of Puf4p targets less sensitive to Puf4p activity.Our analysis yielded causal aQTL relationships for a number of RBPs, including PUF4::KanMX cassette was amplified from the relevant Mata strain from the Saccharomyces cerevisiae Genome deletion collection (sequence-www.stanford.edu/group/yeast_deletion_project/deletions3.html) and used to transform BY4716 (lys2Δ0)MATα  and YLK807 (lys2Δ0 ura3Δ0 IRA2RM)MATa . G418 -resistant cells were selected and the site of integration confirmed by polymerase chain reaction (PCR). For RM1-11a (leu2Δ0 ura3Δ0 hoMATa ::KanMX) and YLK810 leu2Δ0 ura3Δ0 hoMata ::KanMX IRA2BY), the KanMX at the ho locus was replaced with the NatMX cassette by transformation with p4339 cut with EcoRI .The th of this reaction mix was used as template for RT-PCR using 1 × iQSYBR Green Supermix . All reactions were carried out in triplicate using a StepOnePlus machine  and the data analyzed using AB software. Three technical replicates were carried out for each strain .Yeast were grown under standard laboratory conditions to early log phase in yeast extract peptone dextrose (YPD) and harvested by centrifugation. Total RNA was extracted using the Master Pure YeastRNA Purification Kit  and 2.5 ng was used to generate cDNA with the iScript cDNA Synthesis Kit . 1/20RRS1 were determined, using THI6 as a reference  in each column (i.e. IP experiment). Let X. As illustrated in Figure S1, we then defined th quantile,th element in the vector x. This transformation reduces the effect of outliers.For our motif analysis, we took logN) of sequence (S) of mRNA of gene (g) by an RBP (ϕ) is given as follows:S is defined as the sum of the relative affinities of a sliding window of length b indicates the nucleotide identity of the base at the coordinate S. The aforementioned formula assumes that the contribution to the binding free energy at each position within the binding site is independent. The set of w’s thus represent the PSAM of RBP (ϕ).To model for RBP-mRNA binding occupancy, we used a biophysical model similar to that presented by Figure S2. To detect the motifs, we used the MatrixREDUCE program from the REDUCE Suite package (bussemakerlab.org/software/REDUCE) to perform a genome-wide fit of a PSAM to the rank-quantile log2-ratios of RBP binding data. MatrixREDUCE builds a multiple linear regression model originally developed by  the best nucleotide element was given value equal to 1 and unacceptable nucleotides  were given a very small number close to zero. The optimization step aims to find the optimal weight matrix by minimizing an error function:ϕ, e, and g label RBP, IP experiment replicate, and gene, respectively. Here, Z represents the rank-quantile transformed binding data for training set. The training set was obtained by randomly selecting 50% of the data from each transformed IP experiment. The motif seed finding step and subsequent optimization step of the PSAM are both performed on the training set. Once the optimization step converges for this PSAM, the residues of Z are then used for the next seed finding and optimization iteration. The intercept C represents the genome-wide basal expression level when no preferred motif is present on the sequence. The slope F reflects a combination of the activity of the RBP under the media conditions in which binding was assayed, and the efficiency of the protocol for the particular technical replicate. We split every column of the binding data randomly into two sets of equal sized training and test sets and ran MatrixREDUCE on the training set of all experimental replicates of an RBP simultaneously (using command line option -mf). For every RBP, we searched for binding motifs on the whole mRNAs, 5′ UTRs, ORFs and 3′ UTRs sequences separately. For Idh1p, Nrd1p, Tdh3p, and Vts1p, we also ran the software without the -mf argument because for all of these factors one of the experimental duplicates was missing more than 40% of the data points. We obtained the Saccharomyces cerevisiae UTR sequences RNA-seq data . For all RBPs, we searched for PSAMs of length 1−10 iteratively with a p-value cut-off of 0.001.The MatrixREDUCE algorithm consists of two steps: seed motif finding and PSAM optimization. The seed finding step seeks to identify within the set of all possible nucleotides of a specified length, the one whose occurrence best correlates with the binding signal. The motif size is allowed to vary from to 1 to 10 nucleotides in our analysis. Once the optimal motif was identified, it was used as a seed for the optimization procedure. For an optimal motif of length i.e., the remaining 50% of each IP experiment). We extended the flanking sides at most one nucleotide position  to the flanks of the PSAM) and ran the OptimizePSAM software from the same package using the PSAM with added columns on the sides as seed. We continued adding columns to the sides of the PSAM until no nucleotide’s weight at the added side flanks was less than 0.1. In the case of Nrd1p PSAM optimization we neglected this criterion where the matrix element for G nucleotide at position 8 was equal to 1 × 10−7. Further flank addition and optimization of this PSAM resulted in optimization divergence after several rounds. At the end of each optimization cycle, we validated the newly extended PSAM by calculating the Pearson t-value and Spearman p-value on the test set. After this step, we ran OptimizePSAM using the full data on the PSAMs passed validation steps.We calculated the affinity scores of the discovered PSAMs using the AffinityProfile software from the REDUCE Suite package. We then calculated the Pearson t-value and Spearman p-value for the correlation of the affinity scores to the test data set. We further tried to capture low-specificity flanking sequences for PSAMs that passed a validation step on the test set  enrichment analysis .To perform the GO enrichment analysis, we used packages To further validate novel motifs, we correlated the affinity scores of the 25 factors to expression data from 173 different stress conditions. The stress conditions include heat shock, exposure to oxidative or reductive chemical agents, nutrients or amino acid starvation, and changes in osmolarity. We performed least-squares multiple linear regression of the genome-wide mRNA expression levels of each condition to the affinity scores of all of the selected RBP/region combination and compared the t-values of the regression coefficients among different conditions.trans-acting polymorphisms on mRNA expression via the activity of transcription factors is independent of the effect due to allelic variation in cis-regulatory sequences. Because this study focused on the trans-acting genetic variation, and also to simplify the analysis, all affinity scores were calculated based on the transcript sequences of S288c, a strain isogenic to BY. We performed genome-wide multiple regression on the 25 RBP/region combinations of every segregant mRNA expression log2-ratios to infer segregant-specific activity levels of the RBPs.g for segregant s relative to the reference. Here, the regression coefficient ϕ for segregant s, whereas g of the BY strain for the factor under consideration, as mentioned previously.From the RBP motif discovery analysis we obtained 25 independent RBP/region combinations. As in i.e., segregants) while preserving the genotype data to get LOD score thresholds at 1% false discovery rate (FDR) level. We obtained this threshold for each RBP/region combination separately.Significant aQTL regions were discovered by splitting the multiple regression coefficient between BY and RM at every marker and testing for the significance of the difference between the distributions of the two groups of coefficients using the composite interval mapping (CIM) method for maximum resolution . CIM usetrans-acting factors and not dominated by a single-gene eQTL, we repeated the analysis after eliminating 3 groups of genes: (i) genes that encode RBPs; (ii) genes fully or partly located within 10 kb of aQTL markers; and (iii) genes whose expression variation maps to a marker 20 kb of aQTL markers, and scoring an affinity of at least 50% of the maximum for the RBP under consideration . To find the latter group, we carried out eQTL analysis using the expression of each gene as a trait and calculated LOD score for every marker using CIM method. We combined these three groups of genes and removed them from the affinity and expression data sets for each RBP separately. This way, the activity calculation for each factor was not affected by elimination of unrelated genes.To confirm that the detected aQTL regions for the RBPs are modulated by Protein−protein interaction data were downloaded from (thebiogrid.org) for yeast, April 2012. We used it to detect any known genetic or physical interactions with the genes located in aQTL regions.IRA2 alleles were swapped between the BY and RM strains. We label the strain carrying the RM allele of IRA2 in the BY background as (RM@IRA2) and the strain carrying the BY allele of IRA2 in the RM background as (BY@IRA2). The reference sample used for the gene expression measurements was pooled parental mRNA (BY and RM). To obtain the net effect of the IRA2 allele replacement on the genome-wide mRNA levels (IRA2 strain as an example):IRA2 was replaced by the BY allele in the RM background and carried out multiple regression analysis. To capture the effect of the IRA2 allele swap between the two backgrounds, we subtracted the regression coefficients between the two cases for all the 25 combinations. We then permuted the two y vectors for all genes 1000 times independently to calculate the statistical significance threshold at 1% FDR level  and THI6 (control). Because of the inverse relation between mRNA level and CT, we subtracted the test value from the control value. We performed a least-squares fit of the following linear model to estimate the effect of IRA2, and PUF4 on the mRNA level of RRS1, as well as the genetic interaction between IRA2 allelic status and PUF4 deletion:x = 1 when the IRA2 allele is RM, or the PUF4 gene is deleted, respectively, and x = 0 otherwise. We fit the model separately for two subsets that were selected based on the background strain BY or RM.For each of the three technical replicates of the eight strains, we calculated the difference in CFor motif discovery, we used RNA immunoaffinity purification data that included a total of 132 IP experiments for 45 RBPs from Figure S2. We used the MatrixREDUCE program from the REDUCE Suite software package, which takes as inputs the nucleotide sequences and RBP binding log2-ratios for all mRNAs. To reduce the effect of outliers, we applied a quantile-based transformation to the binding data . To define RNA sequences, we used the annotation from  and only selected those validated using the remaining 50% of the data. We further optimized these PSAMs by adding flanking sequence (up to one nucleotide on either side) to capture low-specificity bases not identified during the training step. A final optimization step using the complete data set yielded PSAMs for 20 of 45 RBPs (see Table S1 and Table S5).After the training step, using a random sample of 50% of the data, we calculated the affinity scores using the derived position-specific affinity matrices  separately. We also required that each PSAM was most correlated with binding for each factor (IP data). Five of the 20 PSAMs we discovered  did not pass this specificity test .Regulation of mRNA stability typically is carried out through protein interactions via the 3′ UTR . This was expected because Bfr1p associates with cytoplasmic mRNP complexes containing Scp160p , is predictive for binding in the ORF. Gbp2p is involved in mRNA export from the nucleus to the cytoplasm. The motif HGGUGW  previously reported for this protein  tail formation control and export of mRNA from nucleus to cytoplasm . The motif we obtained for Pin4p looks similar to the motif reported by  binding protein that is essential for stability of many mRNAs . We also performed GO analysis on the in vitro affinity scores using the Wilcoxon-Mann-Whitney test .Our method detected novel binding specificities for three RBPs for which previous motif finding attempts had failed. To corroborate these finding, we analyzed the correlation of PSAM-based affinity scores with differential mRNA expression data across 173 different stress conditions . GO analysis based on the mRNA affinity scores for Scp160p showed an association with the nitrogen compound metabolic process category .Sik1p (Nop56p) is a component of the box C/D snoRNP complexes that direct 2′-O-methylation of pre-rRNA during its maturation. Our detected motif for Sik1p is enriched in both 5′ UTRs and ORFs of mRNAs. We observed positive correlation of ORF affinity scores with differential expression during YPD stationary phase growth and after heat shock (see Table S2). It could be that Sik1p has a direct or indirect role in rRNA methylation regulation under heat shock and that could explain why we observed positive correlation for the heat shock conditions. GO analysis showed significant association with ribosome and rRNA-related categories .Tdh3p encodes glyceraldehyde-3-phosphate dehydrogenase, which is required during gluconeogenesis and is essential for yeast cells to grow on noncarbohydrate sources such as ethanol and glycerol .glycerol . The afftrans-acting loci controlling the activity of RBPs that influence mRNA expression levels through posttranscriptional control of their half-lives . Khd1p, Msl5p, Pub1p, Puf2p, Puf3p, Puf4p, and the putative regulator YLL032C.We combined segregant-specific genome-wide mRNA expression profiles with prior information about the posttranscriptional regulatory network to infer differential RBP activity levels in each of 108 haploid segregants from a genetic cross between a lab (BY) and a wild (RM) strain . Figure y scores . Multiply scores  to map aPuf3p and Puf4p differ with respect to the length of the gap between the UGUA and AUA submotifs (cf. The binding specificities of tifs cf. . As a cotifs cf. . The samtifs cf. .Puf3p and Puf4p activity levels respond oppositely when cells are exposed to different sugar sources (−16). By contrast, inferred Puf3p and Puf4p activity levels do not correlate across the segregants from the BY-RM cross  in the RM strain is a glutamine (Q) in S288c. Pop7p is the subunit of both RNase MRP and nuclear RNase P; RNase mitochondrial RNA processing cleaves pre-rRNA, whereas nuclear RNase P cleaves tRNA precursors to generate mature 5′ ends and facilitates turnover of nuclear RNAs .The aQTL LOD score profile for e 5′ UTR . Messeng RM@IRA2  correlatIRA2 allele replacement did not correlate with affinity scored on the ORF or 5′ UTR. This finding suggests that a polymorphism that is genetically linked to but outside IRA2 is responsible for modulation Puf4p activity as it acts via the 5′ UTR. Possible causal genes are REX4 and BRX1, both of which have putative roles in pre-rRNA possessing and ribosome assembly. Puf4p is known to interact with mRNAs encoding nucleolar rRNA-processing factors (REX4 contains three coding single-nucleotide polymorphisms between the RM and S288c strains: the asparagine (N) at position 34, phenylalanine (F) at position 155, and lysine (K) at position 248 in RM are lysine (K), leucine (L), and arginine (R) in S288c, respectively. There is a single noncoding polymorphism at position 243 within the coding region of BRX1; the thymine in RM is cytosine in S288c.The expression response to Khd1p, Msl5p, Pub1p, Puf2p, and YLL032C) are also linked to the IRA2 locus. Using the IRA2 allele replacement data again to test these aQTL associations, we found that only the affinity of Puf2p via the 5′ UTR  was significantly correlated with differential mRNA expression. Even though we found the linkage to IRA2 locus and significant correlation between IRA2 allele replacement data and the affinity score of Puf2p, no evidence has been reported for a connection between them in the literature thus far.The activities of five other RBPs . When active, Puf4p destabilizes its target mRNAs through interaction mostly via 3′ UTR of its targets . Performing the regression on the four strains with BY background, we obtained an excellent fit (R2 = 0.96), with a significant negative effect of allele replacement to RM@IRA2 , a significant positive effect of PUF4 deletion , and a significant positive interaction between these two predictors . The signs of the regression terms are all consistent with our aQTL-based findings and the known role of PUF4 as a destabilizer of mRNA transcripts . Most approaches either impose a threshold to filter RBPs binding data or use gene expression data in combination with mRNA half-lives to identify stability motifs associated with RBPs. Measuring mRNA half-lives requires transcription arrest, which can interfere with the post-transcriptional control of mRNAs under study . Experimental follow up will be required to rule out this possibility and further validate our new findings.The PSAMs discovered for 12 RBPs agree with previously reported consensus motifs in other studies. In addition, we discovered three novel motifs for Taken together, our findings highlight the importance of posttranscriptional regulation that reflects in the mRNA stability by RBPs. Our approach is not yeast-specific and can be applied to other organisms.


S. cerevisiae. Cmr1 occupancy correlates with the Pol II occupancy genome-wide, indicating that it is recruited to coding sequences in a transcription-dependent manner. Cmr1-enriched genes include Gcn4 targets and ribosomal protein genes. Furthermore, our results show that Cmr1 recruitment to coding sequences is stimulated by Pol II CTD kinase, Kin28, and the histone deacetylases, Rpd3 and Hos2. Finally, our genome-wide analyses implicate Cmr1 in regulating Pol II occupancy at transcribed coding sequences. However, it is dispensable for maintaining co-transcriptional histone occupancy and histone modification (acetylation and methylation). Collectively, our results show that Cmr1 facilitates transcription by directly engaging with transcribed coding regions.Cmr1 (changed mutation rate 1) is a largely uncharacterized nuclear protein that has recently emerged in several global genetic interaction and protein localization studies. It clusters with proteins involved in DNA damage and replication stress response, suggesting a role in maintaining genome integrity. Under conditions of proteasome inhibition or replication stress, this protein localizes to distinct sub-nuclear foci termed as intranuclear quality control (INQ) compartments, which sequester proteins for their subsequent degradation. Interestingly, it also interacts with histones, chromatin remodelers and modifiers, as well as with proteins involved in transcription including subunits of RNA Pol I and Pol III, but not with those of Pol II. It is not known whether Cmr1 plays a role in regulating transcription of Pol II target genes. Here, we show that Cmr1 is recruited to the coding regions of transcribed genes of  S. cerevisiae protein Ydl156w/Cmr1 (changed mutation rate 1) is a putative WD40 domain containing protein , 27GAL1 cription . In contondition . Howevered cells . Therefo2 ratio ChIP/input) of the probes present within the transcription start site (TSS), and the transcription end site (TES) of a given gene. Consistent with our results above (ARG1 (0.91 log2 ratio) and HIS4 (0.85 log2 ratio), and low in the ORFs of PMA1 (0.07 log2 ratio) and ADH1 (-0.05 log2 ratio)  ChIP-chip analysis using Agilent 4x44K arrays under amino acid starvation condition (+SM). For each gene, the average Cmr1 and Pol II occupancies were determined by averaging the signal intensities  . Moreove2 ratio) . Metagen2 ratio) . In cont2 ratio) . These rgcn4Δ strain treated with SM, which induces transcription of Gcn4 target genes. In WT cells, 94 Gcn4-targets genes exhibited average Pol II occupancies greater than the log2 ratio of 1.0 (strongly transcribed). Metagene comprised of these 94 genes revealed lower Cmr1 occupancy in gcn4Δ than that seen in the WT cells  strain, in which the Kin28 activity can be rapidly inhibited by treating cells with an ATP analog NA-PP1 [kin28as/bur2Δ double mutant.Having determined that Cmr1 localizes to the coding regions of transcribed genes, we next investigated the mechanism by which it is recruited. We first focused on evaluating the role of elongating Pol II on Cmr1 recruitment. The C-terminal domain (CTD) of Rpb1, the largest subunit of Pol II, is phosphorylated at Ser5 residue by the TFIIH associated kinase Kin28 , 32. Thig NA-PP1 , 18. In g NA-PP1 . To undegcn4Δ cells, at the ARG1 5’ and 3’ ORFs in both kin28as and kin28as/bur2Δ mutants  at the 5’ ends of transcribed genes, whereas Ctk1 has a major role in phosphorylating Ser2 at 3’ ends [bur1as allele were treated with ATP-analog 3MB-PP1 to inactivate Bur1 kinase activity. Such treatment led to an expected reduction in Ser2P at the 5’ ARG1 ORF in the bur1as mutant and a substantial reduction at both 5’ and 3’ ORFs in bur1as/ctk1Δ cells . Collectively, our results indicate that Ser5 phosphorylation by Kin28, but not of Ser2 by Bur1 and Ctk1, stimulates Cmr1 recruitment to the ARG1 coding sequences.To directly test the last conclusion, we examined Cmr1 occupancy in Ser2 kinase mutants,  3’ ends . Strainst shown, ). While,as/ctk1Δ . Howevere mutant . As suche mutant  and founARG1 coding region was unaffected in set1Δ and set2Δ mutants  complexes [gcn5Δ/esa1ts) and WT cells was observed in the ARG1 ORF  mutants. Both Hos2-Set3 and Rpd3 HDACs are recruited via phosphorylated Pol II CTD , 43, rec strains . Interes3Δ/hos2Δ , suggest mutants . These rARG1 and HIS4 in WT and cmr1Δ cells. While H3 occupancies at the 5’ and 3’ ORFs of ARG1 and HIS4 decreased upon induction  was observed in the ARG1 ORF upon induction in WT cells  (data not shown) levels were analyzed in WT and cmr1Δ. Overall, these results indicate that while Cmr1 interacts with histones, it may not regulate their occupancy or modifications that are generally associated with transcription activation.These conclusions were further supported by analyzing the level of histone modifications, by immunoblotting, in whole-cell extracts prepared from the WT and and K23)  or methycmr1Δ mutant under amino acid starvation conditions, genome-wide. Average gene Rpb3 occupancy profile for the 500 most-affected genes (Cmr1-affected), among transcribing genes (Rpb3 log2 ratio > 0.5), is shown in cmr1Δ elicits greatest Pol II reduction downstream of the TSS at these genes, suggesting that Cmr1 may regulate transcription at the elongation step. This group of genes included 77 gcn4-regulated  and 50 ribosomal protein genes   occupancy in a x 10−14) . Pol II equences . These requences  showing ARG1 and HIS4 at different time points during their induction by SM. As expected, in the WT cells, Pol II occupancy gradually increased both at the TATA and 3’ ORF of ARG1 upon SM treatment and exhibited the maximum recruitment between the 10 and 20 minutes time points , a greater reduction in Pol II binding was observed at the 3’ end of ARG1, suggesting that Cmr1 plays a role in the elongation phase of transcription. Since ARG1 is a relatively short gene (1263 base pairs), we examined Rpb3 occupancy at HIS4, which has a longer coding region (2400 base pairs). At the HIS4 5’ ORF, Pol II occupancy in cmr1Δ was similar to that observed in the WT cells at all of the time-points examined  with 2% galactose  and repressed by adding 4% glucose (Glu). Rpb3 occupancy at the GAL1 TATA, 5’ and 3’ ORFs is shown.(EPS)Click here for additional data file.S2 Figgcn4Δ, kin28as and kin28as/bur2Δ cells were treated with an ATP-analog NA-PP1 to inactivate Kin28 activity, and the occupancy of the Pol II CTD phosphorylated at Ser5 (Ser5P) was determined at the ARG1 TATA, 5’ ORF and 3’ ORF by ChIP. B) The WT, gcn4Δ, bur1as and bur1as/ctk1Δ cells were treated with an ATP-analog 3MB-PP1 to inactivate Bur1, and Rpb3 occupancy at the ARG1 5’ and 3’ ORFs was determined by ChIP.A) The WT, (EPS)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


CBP plays an important role in embryonic development and cell differentiation and mutations in CBP can lead to various diseases in humans. In addition, CBP and the related p300 protein have successfully been used to predict enhancers in both humans and flies when they occur with monomethylation of histone H3 on lysine 4 (H3K4me1).CREB-binding protein  chromatin, where they correlate with binding of the Pho repressive complex. Interestingly, we find that CBP also binds to most insulators in the genome. At a subset of these, CBP may regulate insulating activity, measured as the ability to prevent repressive H3K27 methylation from spreading into adjacent chromatin.Here, we compare CBP chromatin immunoprecipitation sequencing data from We conclude that CBP could be involved in a much wider range of functions than has previously been appreciated, including Polycomb repression and insulator activity. In addition, we discuss the possibility that a common role for CBP at all functional elements may be to regulate interactions between distant chromosomal regions and speculate that CBP is controlling higher order chromatin organization.The online version of this article (doi:10.1186/s13072-015-0042-4) contains supplementary material, which is available to authorized users. Drosophila, there is only one CBP ortholog and it is called nejire, dCBP, CBP/p300, or CBP. CBP and p300 interact with multiple transcription factors and are thus associated with regulatory DNA sequences [CREB-binding protein (CBP) is a transcriptional co-activator that is conserved in metazoans. In mammals, CBP shares functions with the paralogous adenovirus E1A binding protein p300. In equences . Loss ofequences . CBP actequences . Recent equences .Drosophila embryos suggest that CBP is targeted preferentially by some transcription factors in the genome [KB) [Drosophila ovarian follicle cells and Kc cells [Today, over 400 interaction partners have been described for CBP including proteins from all major transcription factor families. Many CBP binding sites are localized in sites known as HOT sites which are regions in the genome that bind multiple transcription factors . CBP boue genome . In earle genome . Early some [KB) . This suome [KB) , 11. It ome [KB) . Other home [KB) , 14; theome [KB)  and H3K5Kc cells , 16.In humans, CBP/p300 binding regions that are outside of genes often overlap with H3K4me1 and are a signature of transcriptional enhancers . The genAlthough CBP occupancy generally correlates with active genes, silent genomic regions with Polycomb-mediated H3K27me3 prevent histone acetylation but do not inhibit CBP binding . StudiesThough most CBP binding sites in the genome are at promoters and enhances, not all genomic positions bound by CBP are promoters or enhancers. In this paper, we have investigated the full range of CBP bound regions to determine if CBP is involved in any additional processes that have yet to be identified. Our main objective was to classify the local chromatin environments where CBP is found. We also wanted to identify both the proteins and histone modifications that potentially interact with CBP and may modulate CBP activity and recruitment to chromatin. We found that CBP binding sites can be classified into Polycomb repressed regions, inactive enhancers, active enhancers, active promoters and insulators. At some insulators, we discovered that CBP functions to prevent repressive H3K27 methylation from spreading into active genes. Our results also suggest that CBP has a role in chromatin opening, DNA replication and chromosomal interactions.Drosophila melanogaster S2 cell-line genome. Based on these data, 2477 high-confidence binding sites of CBP were defined. We also used proteins and histone modifications mapped by modENCODE [Using our previously characterized C-terminal CBP antibody , we mappodENCODE  in theseTo find out where the CBP regions of the nine classes are located in the genome, we mapped their positions in relation to the following gene features: promoters, exons, introns and intergenic regions. Classes V and VI CBP binding sites map to promoters of genes that tend to be highly expressed Fig. c, d. We Since CBP is commonly used as a marker for enhancers, we compared the CBP binding classes to H3K4me1 regions and to enhancers that were experimentally identified by self-transcribing active regulatory region sequencing (STARR-seq) in S2 cells , 26. We We next looked at the differences between these four active enhancer classes and found that Classes VII, VIII and IX were bound by different combinations of factors  and active enhancers . We were also interested in exploring the features of the other classes. Surprisingly, we find that Class I is highly enriched in Polycomb factors such as Polycomb (Pc), Enhancer of zeste (Ez), Pho, Scm-related gene containing four mbt domains (dSfmbt), Sex combs extra (dRing), Polycomb-like (Pcl), Posterior sex combs (Psc), and Trx Fig. g and 2b.p < 0.05) with the enrichment levels of Pho and dSfmbt (members of the Pho repressive complex) but not with any PRC1 or PRC2 components, indicating that CBP might interact with the Pho repressive complex. Of all of the classes, the strongest CBP sites in the genome are found in Class I . Within Class I binding sites, the enrichment levels of CBP correlate  and plotted the average methylation 10 kb up and downstream. Regions were oriented so that the highest level of H3K27me3 was to the right of the Class IV site. Interestingly, the Class IV CBP sites with high levels of acetylation appear to block the spread of H3K27me3, whereas Class IV sites with low levels of acetylation do not appear to have this capacity . We therefore propose that CBP plays an important role in insulator function and suggest that the HAT activity of CBP regulates insulating activity in some instances.We note that Class V, and to some degree Class VI, are enriched in insulator proteins  and minichromosome maintenance 2 (Mcm2) were found in all classes except Class II. This was confirmed by overlapping CBP regions with defined regions of Orc2 and Mcm2 binding Fig. a. CBP isTaken together, our results show that CBP is bound at genomic sites with a wide range of functions. A common feature of these functional elements is that they physically interact with other chromosomal regions. For example, promoters, enhancers and insulators interact via loop formations that are functionally important , 38, whiOur study shows that CBP is found at active promoters and enhancers as previously demonstrated , 17. In To conduct PCA analysis, a matrix was generated with CBP bound regions as observations and the amount of binding of different proteins in CBP bound regions as variables. To calculate the amount of binding of different proteins at CBP sites, the top three consecutive binding values for each protein within 150 bp of the CBP peak centre was averaged. The genomic mean was used if three binding values were not available. All computations were done in log2 scale. PCA was applied to the data after unit variance scaling. Hierarchical clustering was then applied on the first four significant components of PCA, to define clusters of CBP bound regions. Ward clustering was used to calculate tree distances. Nine classes of CBP bound regions were defined in the hierarchical cluster tree.Flybase annotation Release 5.32  was usedDrosophila S2 cells as well as H3K27ac and expression in different developmental stages) was obtained from modMine (http://intermine.modencode.org/). Two additional proteins, Trx and M1BP , that were not used in the classification, were included in the heatmap  and ChIP B  for 10 min at 4 °C followed by resuspension in Sonication buffer  to a final concentration of 5–10 × 107 cells/ml. Nuclei were sonicated for 15 min using a Bioruptor (Diagenode), rotated for 10 min followed by centrifugation for 10 min at 13,000 rpm at 4 °C.7 cells.A mix of Protein A and G Dynabeads (Invitrogen) blocked with only BSA (Sigma Aldrich) for ChIP-sequencing or BSA (1 mg/ml) and salmon sperm DNA (1 mg/ml) for ChIP-qPCR were mixed with indicated antibodies. Beads and antibodies were incubated for at least 2 h followed by the addition of 0.5–1 × 10Chromatin and antibody bead complexes were formed during at least 2 h followed by 5 min washes with sonication buffer , WashA , WashB  and TE.Beads were resuspended in Elution buffer  in a new tube. Cross-linking was reversed at 68 °C for at least 4 h and proteins removed by Proteinase K. DNA was purified with phenol–chloroform, ethanol precipitated and finally resuspended in 200 µl 0.1 × TE.Chromatin immunoprecipitation samples were analyzed by qPCR or sequenced at the Uppsala Genome Center. 2 µl of DNA was used as template for qPCR, which was run in duplicates using 300 nM primers and EvaGreen (Solis BioDyne) on a CFX96 Real-Time system (BioRad). Average Cq was calculated for each ChIP sample and compared to input. To account for the background of each individual ChIP, normalization was made to two intergenic sites devoid of known histone modifications and chromatin factors. ChIP values were further normalized to the total amount of histone H3.Ten ChIP samples were pooled and used for SOLiD (TM) ChIP-Seq Library preparation, size selection (100–150 bp + adapters 90 bp) and sequenced using SOLiD4 50 bp fragment run.D. melanogaster genome (release 5) and only those with unique map sites were retained. A log2-ratio was calculated between the IP and the input samples read densities. After median smoothing with 100 bp windows, high-confidence binding sites were identified as described in [CBP ChIP-seq reads were mapped to the ribed in . In brieTwo affinity purified antibodies raised against CBP, one in guinea-pig , 49 and 6 cells/ml of S2 cells were centrifuged and dissolved in FCS free media. 30 µM of CBP inhibitor (C646) or control drug (CM37) in DMSO was added to the cells for 30 min before ChIP.2 × 10


SiARDP is a DREB-type transcription factor from foxtail millet. SiARDP is involved in ABA-dependent signal pathways under the control of SiARDP and plays a positive role in plant responses to drought stress. cis-elements in promoter regions. The upstream transcription factors that regulate the transcription of DREB transcription factors have not been clearly defined, although the function of DREB transcription factors in abiotic stress is known. In this study, an abscisic acid (ABA)-responsive DREB-binding protein gene (SiARDP) was cloned from foxtail millet . The transcript level of SiARDP increased not only after drought, high salt, and low temperature stresses, but also after an ABA treatment in foxtail millet seedlings. Two ABA-responsive elements  exist in the promoter of SiARDP. Further analyses showed that two ABA-responsive element binding (AREB)-type transcription factors, SiAREB1 and SiAREB2, could physically bind to the ABRE core element in vitro and in vivo. The constitutive expression of SiARDP in Arabidopsis thaliana enhanced drought and salt tolerance during seed germination and seedling development, and overexpression of SiARDP in foxtail millet improved drought tolerance. The expression levels of target genes of SiARDP were upregulated in transgenic Arabidopsis and foxtail millet. These results reveal that SiARDP, one of the target genes of SiAREB, is involved in ABA-dependent signal pathways and plays a critical role in the abiotic stress response in plants.The DREB (dehydration-responsive element binding)-type transcription factors regulate the expression of stress-inducible genes by binding the DRE/CRT  The growth of plants and productivity of crops are limited by environmental stresses, such as drought, high salinity, soils, and low temperatures. To respond and adapt to these stresses, a large number of specific genes are induced, such as molecular chaperones, osmotic adjustment proteins  and othecis-elements in the ABA-responsive gene promoter region (Abscisic acid (ABA)-responsive element binding (AREB) transcription factors are members of the group A subfamily of the bZIP transcription factor family and play a key role in ABA-responsive abiotic stress , ZmDREB1A from maize (Zea mays), and PgDREB2A from sorghum, have been identified , in which the negative regulatory region was deleted, could improve drought tolerance and activate the expression of the target genes in transgenic Arabidopsis /ethylene-responsive factor (ERF) proteins constitute a transcription factor family, and there are 145 ERF/AP2 members in promoter . Since tDBF1, CBF4, and OsDREB1F , an ancient crop in China, provides rich nutrient elements and has excellent drought tolerance  were germinated on moist gauze for 24h at 28°C, and then grown in pots filled with nutrient soil and vermiculite mixed 1:1 (v/v) under a 16 h:8h (light:dark cycle) at 28°C and 60% relative humidity for 2 weeks. Then, the soil and vermiculite attached to the seedling roots were washed away. The seedlings were fixed in plastic foam, transferred to 1/3 Hoagland solution and grown hydroponically at 26°C for 3 d. They were then subjected to various treatments. During culture, the Hoagland solution was changed every day, and an aeration system was used. For salt, dehydration, and ABA treatments, the seedling roots were immersed separately in 1/3 Hoagland solution containing 100mM NaCl, 20% PEG-6000 and 10 μM ABA, respectively, and kept for the time indicated. For the cold treatment, 17-day-old seedlings grown in soil were maintained at 4°C for the time indicated. Meanwhile, seedlings cultured in 1/3 Hoagland solution without treatment for the corresponding times indicated were used as controls.Seeds of foxtail millet . The bait strains were screened on synthetic defined (SD) medium lacking uracil and containing different concentrations of Aureobasidin A (AbA).The foxtail millet cDNA library was constructed following the protocol of the Matchmaker™ Gold Yeast One-Hybrid Library Screening System .SiARDP, SiAREB1 and SiAREB2 were cloned into pGADT7-AD at the NdeI and XhoI sites as prey vectors. They were transformed into bait strains and grown on SD medium lacking leucine and containing 800ng ml−1 AbA for 3 d at 30°C.Total RNA was isolated using TRIzol reagent . After digestion with RNase-free DNase I , ~2 μg of total RNA was used for reverse transcription by M-MLV Reverse Transcriptase .T method was used to calculate the expression levels of relevant genes.Reverse transcription polymerase chain reaction (RT-PCR) was performed using 2 × Taq PCR StarMix with Loading Dye . PCR conditions were 95°C for 3min, followed by 24 cycles of 95°C for 30 s, 60°C for 30 s, 72°C for 30 s, and 72°C for 5min. Quantitative RT-PCR (qRT-PCR) assays were performed with a LightCycler 480 II real-time PCR detection system  using the UltraSYBR Mixture . The PCR conditions were 95°C for 10min, followed by 40 cycles of 95°C for 15 s, and 57°C or 60°C for 1min. The ΔΔCSiARDP, SiAREB1 and SiAREB2 without the stop codons were inserted into a modified pUC-GFP plasmid. The AT-hook motif nuclear-localized protein 22 gene, AHL22 (BR000358), without the stop codon, was cloned into a modified pUC-RFP plasmid as the positive control. The primers used are shown in Supplementary Table S2 at JXB online. The genes were driven by the cauliflower mosaic virus (CaMV) 35S promoter. Each plasmid (20 μg) was transformed into millet protoplasts. After culturing for 16 to 20h, fluorescence was observed under a confocal laser microscope (Leica HQ).The full-length sequences of 2, 5mM KCl, and 2mM MES at pH 5.7) and cultured in the dark at 26°C for 16h.Seeds of foxtail millet were germinated in pots filled with nutrient soil and vermiculite mixed 1:1 (v/v) under 12 h:12h (light:dark) conditions at 26°C for 3 d, and then were moved to the dark for another 4–6 d. Tissues from the stems and leaves were used. A bundle of foxtail millet plants was cut into 0.5–1mm wide strips. Protoplast isolation and transfection were carried out according to the procedure described by SiARDP, SiAREB1, and SiAREB2 were inserted into the pBD-GAL4 plasmid  at the EcoRI and SalI sites under the control of the yeast alcohol dehydrogenase 1 (ADH1) promoter. The pBD-GAL4 plasmid was used as the negative control and the pGAL4 vector as the positive control. These plasmids were independently transformed into the yeast YRG-2 strain. These transformed yeast cells were grown on SD medium lacking threonine, or lacking threonine and histidine, for 3 d at 30°C.The open reading frames of SiARDP was cloned into the pET-28a vector, which contained a Flag tag, at the NdeI and XhoI sites, while SiAREB1 and SiAREB2 were inserted into the NdeI and XhoI sites of the modified pGEX-TEV vector containing a GST tag. These fusion proteins were expressed in Escherichia coli (BL21) and purified using nickel NTA  and Glutathione Sepharose 4B , respectively. Oligonucleotides and their reverse complementary oligonucleotides, which were labelled with biotin, were synthesized. These sequences are shown in ® Chemiluminescent EMSA Kit .SiARDP was amplified by RT-PCR and inserted into the modified binary vector pS1300 at the HindIII and SpeI sites, and was driven by the CaMV 35S promoter. The plasmid was transformed into Arabidopsis Col-0 by the vacuum infiltration method  ubiquitin promoter, and the vector was introduced into Agrobacterium tumefaciens strain LBA4404. The transformation was performed according to the method reported by −1 hygromycin for 4 weeks. The transgenic plants were examined by PCR for the presence of hygromycin phosphotransferase II and by western blotting. Two independent lines of the T2 generation were chosen for further analysis. The expression levels of SiARDP in the transgenic millet were determined by qRT-PCR.Arabidopsis were used for the phenotypic analysis. For the high salinity treatment, seeds of WT and transgenic Arabidopsis were sown on the MS medium containing 0, 100, 150, and 175mM NaCl for 8 d at 22°C, and then the fresh/dry weights of the WT and transgenic Arabidopsis were measured. Additionally, 35-day-old seedlings from WT and transgenic Arabidopsis grown on MS medium were transplanted on MS medium containing 0, 150, 200, and 250mM NaCl for 4 d at 22°C.Approximately 70 seeds from the wild-type (WT) and each selected line of the T3 generation of transgenic Arabidopsis were sown on MS medium containing 0, 200, and 300mM mannitol for 8 d at 22°C, and then the fresh/dry weights of the WT and transgenic Arabidopsis were measured. To test drought tolerance, 30 seeds each from WT and transgenic Arabidopsis were grown on MS medium for 1 week and transferred to pots filled with soil and vermiculite  for an additional 2 weeks at 22°C and 60% relative humidity. Water was withheld for 14 d as the control condition. The survival rate was counted 5 d after rewatering. Approximately 48 seeds from WT and transgenic millet were germinated on moist gauze for 24h at 28°C and then transferred into pots filled with soil and vermiculite  for an additional 2 weeks under conditions of 28°C day:25°C night. Two-week-old seedlings were not watered for 14 d, and then were rewatered and grown under normal conditions for 5 d. The survival rate was calculated.For the dehydration treatment, ~70 seeds from WT and transgenic Relative electrolyte leakage rates and proline contents were measured as described by The survival rate, fresh/dry weights, relative electrolyte leakage rate, and proline content data were subjected to Student’s t-test analyses using GraphPad Prism 5. All of the experiments were repeated three times.Arabidopsis and transgenic Arabidopsis were used to examine the expression levels of Rd29A, Rd29B, Rd17, and MT2A by qRT-PCR. The primers are shown in Supplementary Table S2 at JXB online.Total RNA of non-transgenic Supplementary Table S1 at JXB online). The primers are shown in Supplementary Table S2 at JXB online.Total RNA was isolated from non-transgenic millet and transgenic millet, and was used to examine the expression levels of stress-relevant genes  according to the instructions of the manufacturer. The anti-GFP antibody  was used. To calculate the enrichment, the CT values were normalized against the input CT, where ΔCT = CT (sample) − CT (input). The primer sequences are listed in Supplementary Table S2 at JXB online.Approximately one million foxtail millet protoplasts were transfected with rd29A promoter, which contains a DRE core sequence (ACCGAC) at its centre, was cloned into pAbAi as a bait plasmid. A triplicate 16-bp mutant DNA fragment in which the DRE core sequence ACCGAC was substituted with AAAAAA was used as a negative control. The bait plasmid and control were independently transformed into yeast. These transformed yeast cells could grow on media lacking uracil but could not grow on media containing 800ng ml−1 Aureobasidin A (AbA) (data not shown). Thus, the concentration of 800ng ml−1 AbA was chosen as a screening criterion, and more than 2.0×106 yeast transformants from a library prepared using 2-h and 6-h dehydrated foxtail millet were screened. A millet cDNA encoding a protein with a highly conserved ERF/AP2 DNA-binding domain and two nuclear localization signals  was cloned. The yeast one-hybrid assay was conducted again to confirm the results. The cDNA was cloned into the yeast expression vector pGADT7-AD. The recombinant plasmid was separately transformed into the bait and mutant bait strains. The transformed bait yeast cells grew on medium lacking leucine and containing 800ng ml−1 AbA, but the transformed mutant bait yeast cells did not , indicating that the transcription factor belonged to the DREB2 family. It was named SiARDP.To isolate cDNAs encoding DRE binding proteins from foxtail millet, the one-hybrid library screening system was used. A triplicate 16-bp DNA fragment (ATACTACCGACATGAG) between positions −156 and −171 in the  did not . The cloE.coli. Because DREB transcription factors bind to the DRE core element ACCGAC in the rd29A promoter  of each time point were calculated. The results showed that the expression of SiARDP increased during drought, low temperature, and high salinity treatments. SiARDP expression was also induced by ABA treatment. The transcript level of SiARDP was obviously induced after 3h of ABA treatment and reached its highest level at 12h. The amount of SiARDP showed a significant decrease after the 24-h treatment . These results indicate that SiARDP may activate the expression levels of the drought stress-relevant genes through direct binding to the DRE core element in their promoter regions.We chose 13 stress-relevant genes from foxtail millet to analyse the function of nditions . Additiol millet . There wSiARDP in foxtail millet, we analysed the promoter of SiARDP and found two ABRE motifs . The AREB/ABF subfamily binds to the ABRE core sequence, and SiARDP might be regulated by AREB-type transcription factors in foxtail millet. We found six putative AREB-type genes in foxtail millet. Among these genes, two multiple stress-inducible genes, named SiAREB1 and SiAREB2, were chosen for further research. SiAREB1 encoded a protein of 357 amino acids, and SiAREB2 encoded a protein of 280 amino acids. Both proteins had a basic leucine zipper (bZIP) domain. SiAREB1 harbours three N-terminal and one C-terminal conserved domains, and SiAREB2 has two N-terminal and one C-terminal conserved domains.To further study the stress signal transduction pathway mediated by SiAREB1 and SiAREB2 were induced by dehydration, high salinity, and ABA treatments, but they were not affected by cold stress . Both SiAREB1 and SiAREB2 were highly expressed in leaf tissue . A subcellular localization assay showed that both SiAREB1 and SiAREB2 fused to GFP were located in the nucleus of the foxtail millet protoplast . These results suggest that SiAREB1 and SiAREB2 are AREB-type transcription factors associated with abiotic stress in foxtail millet.The expression levels of otoplast –L. The aSiAREB1 and SiAREB2 are involved in the regulation of SiARDP, a yeast one-hybrid assay was performed. Two bait sequences were inserted into a bait plasmid. One has three 17-bp sequences containing ABER1 (ACGTGTC) and another has three 17-bp sequences containing ABRE2 (ACGTGGC). Both sequences were in the SiARDP promoter. Meanwhile, mutant bait constructs containing AAAAAAA as a substitute for ABRE1 and ABRE2 core elements were also created. The bait strains and mutant bait strains grew on media lacking uracil, but did not grow on media containing 800ng ml−1 AbA (data not shown). SiAREB1 and SiAREB2 were independently inserted into the expression vector pGADT7-AD. Then, the two vectors were transformed separately into the bait strains or mutant bait strains. The bait yeast cells transformed with pGADT7-SiAREB1 or pGADT7-SiAREB2 grew on media lacking leucine and containing 800ng ml−1 AbA, but the transformed mutant bait yeast cells did not (To examine whether  did not .rd29A promoter was used as probe 1 (P1) (SiARDP was used as probe 2 (P2). The sequence that contained ABRE2 and that contained ABRE1 in the SiARDP promoter were used as probe 3 (P3) and probe 4 (P4), respectively (SiAREB1 and SiAREB2 were expressed as glutathione S-transferase (GST) fusion proteins in E. coli. We examined whether SiAREB1 and SiAREB2 could bind to these probes. Both SiAREB1 and SiAREB2 had the ability to bind to P2 and P3 but not P4  . The seqectively . Full-let not P4 . Both SiSiARDP in vivo, a transient ChIP-qPCR was performed on WT foxtail millet protoplasts. A sequence analysis showed that two ABRE elements, A1 and A2, existed in a 1-kb region upstream of the translation start site . In addition, three genes, SiARDP, SiAREB1, and SiAREB2, exhibited the same tissue-specific expression patterns in foxtail millet . The co-expression of these three genes in the same tissues at the same time indicated that SiAREB1 and SiAREB2 may be involved in the regulation of SiARDP. These results suggest that SiARDP is a member of two abiotic stress signal transduction pathways. One is the ABA-dependent signal pathway for drought and salt stress regulated by SiAREB1 and SiAREB2, and the other appears to be an ABA-independent pathway for low temperature stress regulated by other transcription factors  in transgenic Arabidopsis  and the National Science Foundation of China (grant No. J1103520).This work was supported by the