Kd) and maximum binding capacity (Bmax) of 16 high affinity DNA and RNA aptamers. The Kd values of the high affinity DNA aptamers were compared to those derived from colorimetric ELONA performed in parallel. Additionally, Electrophoretic Mobility Shift Assays (EMSA) were used to confirm the binding of representative PCBP-2-specific RNA aptamers in solution. We propose this ELONA-(RT)qPCR approach as a general strategy for aptamer characterization, with a broad applicability in biotechnology and biomedicine.Improvements in Systematic Evolution of Ligands by EXponential enrichment (SELEX) technology and DNA sequencing methods have led to the identification of a large number of active nucleic acid molecules after any aptamer selection experiment. As a result, the search for the fittest aptamers has become a laborious and time-consuming task. Herein, we present an optimized approach for the label-free characterization of DNA and RNA aptamers in parallel. The developed method consists in an Enzyme-Linked OligoNucleotide Assay (ELONA) coupled to either real-time quantitative PCR  or reverse transcription qPCR , which allows the detection of aptamer-target interactions in the high femtomolar range. We have applied this methodology to the affinity analysis of DNA and RNA aptamers selected against the poly(C)-binding protein 2 (PCBP-2). In addition, we have used ELONA-(RT)qPCR to quantify the dissociation constant ( Aptamers are single-stranded (ss) DNA or RNA molecules that can bind with high affinity and specificity to a desired target molecule . They arNext generation sequencing (NGS) of DNA is currently replacing the traditional methods based on the analysis of clonal sequences, which provides a significant information increase on the selected pools of aptamers ,6. ConseKd) and its maximum binding capacity (Bmax). Over the last two decades, several methods have been used to characterize the binding affinity of aptamers, all of them showing merits and limitations. Among them, colorimetric or fluorescence-based techniques, Electrophoretic Mobility Shift Assays (EMSA), or those depending on additional biophysical principles  are the preferred methodologies [A considerable number of individual aptamer candidates (from dozens to even hundreds) must be functionally screened for their binding affinity and specificity against the cognate target. The quantitative measurement of the aptamer–target binding reaction is often calculated by means of the dissociation constant of the aptamer qPCR were applied to the characterization of nucleic acid populations obtained after 10 rounds of DNA and RNA aptamer selection performed in parallel against poly(C)-binding protein 2 (PCBP-2) . PCBP-2 2+-coated polystyrene plates (Target PCBP-2 was expressed as a fusion protein with a polyhistidine (6xHis) tag at its N-terminal end, thus allowing its immobilization onto Cue plates , as welle plates  at 37 °Ce plates . The nucleotide composition of DNA and RNA selected aptamers , showed 2, higher than 0.99) was achieved for both DNA and RNA templates. The minimum quantity of template DNA and RNA detected was in the attomolar range: 6.25 × 10−18 mol of DNA  and 1.80 × 10−17 mol of RNA (Ct = 24.13). Then, using these calibration curves, the amount of aptamer bound to PCBP-2 after the partition step of the last SELEX round was quantified by interpolating the average Ct value obtained in the ELONA-(RT)qPCR experiments. The possibility that shorter PCR or RT-PCR products could have resulted from skipping some of the ACTG or ACUG repeats of such template molecules was discarded by analysing the amplification products by gel electrophoresis (Before setting up the ELONA-(RT)qPCR methodology for the affinity assay and further characterization of aptamers, qPCR and RTqPCR calibration curves were constructed, using SYBR green as a fluorophore and the template molecules, D-ACTG and R-ACUG, respectively . They were chosen as non-biased templates to represent the whole set of DNA or RNA aptamer molecules selected in our work, regardless of their sequence composition. As shown in phoresis .2+-coated polystyrene plates, further incubated with 10 pmol of each individual DNA or RNA aptamer (The interest in developing ELONA-(RT)qPCR methodology was twofold. First, it was used to assay, in a 96-well format, the affinity and specificity of the individual selected aptamers. With that purpose, a fixed amount of PCBP-2 (10 pmol), or the same amount of bovine serum albumin , was immobilized onto Cu aptamer . Such a  aptamer . Among t aptamer . Kd and Bmax, of those individual DNA and RNA aptamers showing the highest affinity in the previous assay. Hence, 16 aptamers were chosen among those that revealed a high binding capability and specificity for PCBP-2: 05DS10-01, 05DS10-02, 05DS10-05, 05DS10-12, 05DS10-18, 05DS10-21, 05DS10-22, and 05DS10-26 (DNA aptamers); 05RS10-04, 05RS10-09, 05RS10-11, 05RS10-18, 05RS10-19, 05RS10-30, 05RS10-32, and 05RS10-34 (RNA aptamers). The experiments involved the immobilization of 10 pmol of PCBP-2 to a Cu2+-coated polystyrene plate and its incubation with a titration of each aptamer qPCR assays was to quantify the binding constants, 2 values in the range of 0.92–0.99) in all cases, from which the values of Kd and Bmax were computed. In parallel, the molecules used as negative controls (D-ACTG and R-ACUG) and the initial populations (D-M1-40 and R-M1-40) could only be adjusted to a linear regression model, thus revealing unspecific binding to PCBP-2. All the assayed aptamers showed Kd values in the nanomolar range: From 8.4 to 89.9 nM for DNA aptamers and from 24.1 to 276.5 nM for RNA aptamers. In turn, the Bmax values were in the range of 4.9 × 10−5 to 2.0 × 10−5 pmol (DNA) and 1.7 × 10−5 to 1.2 × 10−4 pmol (RNA). Thus, the highest affinity for PCBP-2 was achieved by a DNA aptamer , while the fittest RNA aptamer showed an affinity three times smaller . Regarding the maximum binding capacity, the DNA selection process produced the best aptamer , almost two times higher than the RNA aptamer endowed with the maximum PCBP-2 binding .The affinity curves obtained using the ELONA-(RT)qPCR approach  showed tWe investigated whether the qPCR and RTqPCR calibration curves used could differ when some of these DNA or RNA aptamer sequences were amplified instead of the D-ACTG and R-ACUG templates. The obtained calibration curves for the different DNA and RNA templates overlapped along a linear range of six orders of magnitude . This reThe predicted secondary structure of the 16 aptamers was calculated using Mfold software  for DNA Kd values of high affinity DNA aptamers. The obtained Kd values of the digoxigenin-labelled version of the eight DNA aptamers previously analysed using ELONA-qPCR ranged from 9.9 to 109.5 nM , and PCBP-2 was titrated (concentration range of 0.1 to 27.1 nM). The results  showed aAmong the diverse set of molecules involved in the regulation of post-transcriptional pathways, poly(C)-binding proteins (PCBPs) are of special interest due to their role in translation initiation of some viral RNAs . In partIn this work, ssDNA and RNA aptamers against PCBP-2 were selected in parallel, using identical experimental conditions and selection pressures . The lacTherefore, the in vitro DNA and RNA selection processes performed exemplify the need for an experimental approach that allows the screening of the binding affinity and specificity of the selected aptamers, beyond their individual sequences or secondary structures. Assays that effectively quantify aptamer-target interactions include colorimetric ELONA , flow cyThe ELONA-(RT)qPCR methodology here developed allowed us to assay 52 individual DNA and RNA aptamers selected against PCBP-2, as well as to further analyse the 16 fittest ones, avoiding the need for either target/aptamer labelling or secondary recognition reaction. Additionally, (RT)qPCR amplification (using SYBR green as the fluorophore instead of specific fluorescent probes) provided sensitive detection of both DNA and RNA aptamers  solution structure of each assayed aptamer. In turn, the RTqPCR-based method developed here allows the screening and analysis of a number of RNA aptamers in parallel, avoiding the need for RNA labelling. Furthermore, the binding of representative in vitro selected RNA aptamers to PCBP-2 in solution was confirmed by EMSA , fast (the complete protocol lasts less than 4 h), and cost effective  analysis of individual aptamers. The  studies ,42,43).  by EMSA . We haveE. coli BL21(DE3) cells transformed with a plasmid expressing 6 × His-PCBP-2 [2PO4, 500 mM NaCl, 20 mM imidazole, 5 mM DTT) as described [s-PCBP-2  grown atescribed . Cell de2, and 100 mM HEPES pH 7.4) and immobilized onto 25 µL Ni-NTA agarose beads  following the manufacturer’s guidelines. Such complexes were used as the selection matrix for the SELEX processes. The designed ssDNA library, termed M1-40, contained a pool of 76 nucleotides (nt)-long oligonucleotides showing a central randomized region of 40 nt flanked by two conserved, 18 nt-long primer-binding sequences: 5′-GCGGATCCAGACTGGTGT(N40)GCCCTAAAGACAAGCTTC-3′. This synthetic random DNA library and the DNA primers used for nucleic acid amplifications were purchased (HPLC-purified) from IBA Lifesciences.For each SELEX round , 50 pmol13 molecules) of M1-40 were amplified by PCR using the forward primer, M1-F (5′-GCGGATCCAGACTGGTGT-3′), and the reverse, 5′-phosphorylated primer M1-R-5′P (5′-GAAGCTTGTCTTTAGGGC-3′). Four cycles of PCR reaction  were performed in a final volume of 1 mL, with 200 µM each dNTP and 0.05 U/µL Expand High Fidelity Polymerase (Roche) [The starting material for the in vitro selection consisted in, roughly, 10 copies of each molecule present in the original M1-40 population. To prepare it, 80 pmol  . The rev14 molecules) of the prepared ssDNA population, resuspended in 90 µL of SB, denatured at 95 °C for 10 min, and renatured at 37 °C for 10 min. The folded ssDNA pool was added to 90 µL of selection matrix (Ni-NTA agarose beads bound to PCBP-2) and incubated at 37 °C for 30 min. In the partition step, unbound ssDNA was removed from the selection matrix by centrifugation at 16,000 g for 2 min and washing twice with 250 µL of SB. Then, ssDNA–PCBP-2–bead complexes were resuspended in 90 µL of Milli-Q water, and ssDNA was denatured and eluted by heating at 95 °C for 5 min. The amplification of eluted ssDNA to start the next SELEX round was performed using 5 to 20 cycles (adjusted in each SELEX round depending on the amount of ssDNA recovered) of assymetric PCR using a 100-fold excess of the forward primer, M1-F, with respect to the reverse primer, M1-R-5′P. The PCR reaction  containing up to 1 pmol of template was performed in a final volume of 50 µL, with 200 µM each dNTP and 0.05 U/µL Expand High Fidelity Polymerase. The residual presence of the reverse DNA strand was removed by enzymatic digestion using λ exonuclease as described above. To foster the isolation of high affinity aptamers, the stringency of the SELEX process was increased by reducing the amount of ssDNA bound to the selection matrix  from 800 pmol (round 1) to 80 pmol (rounds 2 to 10), as well as by doubling the number of washing steps every two rounds. A counter-selection step (using Ni-NTA agarose beads without any bound protein) was introduced before the first round to discard aptamers that could have been selected against the inert matrix. The complete SELEX method consisted of 10 amplification-selection rounds.The first SELEX round was carried out using 800 pmol  of M1-40 were PCR amplified using the primer, M2-F  and M1-R, in a 1 mL reaction with 4 cycles. Milli-Q water treated with DEPC was used in all the processes involving RNA. Thereafter, the amplified product was in vitro transcribed (IVT) by T7 RNA polymerase . The resulting RNA pool was purified by ethanol precipitation. As in the case of ssDNA aptamers, the first SELEX round was performed using 800 pmol of RNA population renatured in 90 µL of SB. After incubation with 90 µL of selection matrix at 37 °C for 30 min, the unbound RNA was removed by centrifugation and washing. RNA–PCBP-2–beads complexes were resuspended and RNA was eluted as detailed above. The recovered aptamers were retro-transcribed and amplified by one-step RT-PCR  using M2-F and M1-R in a total volume of 100 µL , followed by in vitro transcription of 2 µg of the amplified DNA pool. Other experimental variables were the same as those described for the ssDNA process.In turn, for the selection of RNA aptamers, 80 pmol  and following standard protocols.The individual aptamers present at the last round of DNA or RNA SELEX processes were cloned. With that aim, the products of the PCR-amplified DNA (or RT-PCR-amplified RNA) were cloned using the TOPO TA cloning PCR II Kit (ThermoFisher) and the recombinant plasmids were used to transform One Shot Mach1-T1 (ThermoFisher) competent −12 to 6.25 × 10−18 mol in DNA and 1.8 × 10−11 to 1.8 × 10−17 mol in RNA.All reactions were carried out in a StepOnePlus Real-Time PCR System (ThermoFisher): qPCRs were performed using KAPA SYBR FAST qPCR Master Mix , whereas RTqPCRs were carried out with SuperScript™ III Platinum™ One-Step qRT-PCR Kit (ThermoFisher). Both kits contained SYBR Green I dye (Sigma). The final volume of all the reactions was 10 µL, containing 4.7 µL of the DNA or RNA template. For the construction of the calibration curves, serial dilutions of the template molecules of D-ACTG and R-ACUG  were useTM 96-Well High Binding Standard ELISA microplate (ThermoFisher) while three additional wells were used to attach the same amount of BSA as a control of the specificity  were interpolated within the corresponding, previously constructed calibration curve (ELONA-(RT)qPCR experiments were performed by attaching 10 pmol of PCBP-2 to three contiguous wells of a Greiner Bio-Onecificity . The proon curve  to quant2+-coated, high capacity 96-well plate and it was incubated (in triplicate) with eight increasing concentrations  of each individual aptamer. Therefore, four different aptamers could be assayed in parallel in a single plate  were interpolated within the previously constructed calibration curves qPCR. For that, PCBP-2 (10 pmol) was attached to each of the 96 wells of a Cule plate . All thele plate  were denn curves  to quant10GCCCTAAAGACAAGCTTC-3′) and R-ACUG (5′-GGGGCGGAUCCAGACUGGUGU(ACUG)10GCCCUAAAGACAAGCUUC-3′), respectively. Additionally, the initial random population of D-M1-40 GCCCUAAAGACAAGCUUC-3′) was also used as a reference. All the affinity curves obtained were adjusted to alternative binding models using GraphPad Prism software, and those showing higher R2 values were selected to calculate the corresponding Kd and Bmax parameters for each individual DNA or RNA aptamer.In parallel, two molecules were designed and assayed as negative controls in the ELONA-(RT)qPCR experiments, whose sequences contained 10 repeats of either ACTG (ssDNA aptamers) or ACUG (RNA aptamers) tetranucleotides in their central regions. They were termed D-ACTG (5′-GCGGATCCAGACTGGTGT(ACTG)2+-coated, high capacity 96-well plate  was attached to a Cull plate  and it w2, 50 mM DTT, 0.5 mM rNTPs  at 37 °C for 2 h. Transcripts were uniformly labelled using α32P-CTP (500 Ci/mmol) and RNA was separated from non-incorporated isotope using G-25  spin columns. Labelled RNA was extracted with phenol-chloroform, ethanol precipitated, and resuspended in TE to a concentration of 0.04 pmol/µL. RNA integrity was examined in 6% acrylamide 7 M urea denaturing gel electrophoresis, as described [w/v) βME). Increasing amounts of protein (0.1 to 27.1 nM) were incubated with a fixed concentration of 32P-labelled RNA  for 20 min at room temperature, as described [32P-labelled RNA and retarded aptamer–PCBP-2 complexes were detected by autoradiography  of dried gels.RNA aptamer synthesis was performed by in vitro transcription using T7 RNA polymerase. With that purpose, the dsDNA template version of the RNA aptamers (0.5 µg/µL) was transcribed in 40 mM Tris-HCl pH 7.9, 6 mM MgClescribed . Next, aescribed . FollowiKd and Bmax, in a label-free and cost-effective format. Therefore, we envisage the ELONA-(RT)qPCR approach as a general strategy for aptamer characterization, with a broad applicability in the field of aptamer-based biosensors useful in biotechnology and biomedicine.Here, we report the development and characterization of the first described DNA and RNA aptamers against the protein, PCBP-2. From a technological point of view, we demonstrated the usefulness and general applicability of the ELONA-(RT)qPCR approach for the functional analysis of DNA and, noticeably, RNA aptamers. This methodology allows the quantification of their kinetic constants,


Traditionally, cancer is viewed as a disease driven by genetic mutations and/or epigenetic and transcriptional dysregulation. While these are undoubtedly important drivers, many recent studies highlight the disconnect between the proteome and the genome or transcriptome. At least in part, this disconnect arises as a result of dysregulated RNA metabolism which underpins the altered proteomic landscape observed. Thus, it is important to understand the basic mechanisms governing post-transcriptional control and how these processes can be co-opted to drive cancer cell phenotypes. In some cases, groups of mRNAs that encode protein involved in specific oncogenic processes can be co-regulated at multiple processing levels in order to turn on entire biochemical pathways. Indeed, the RNA regulon model was postulated as a means to understand how cells coordinately regulate transcripts encoding proteins in the same biochemical pathways. In this review, we describe some of the basic mRNA processes that are dysregulated in cancer and the biological impact this has on the cell. This dysregulation can affect networks of RNAs simultaneously thereby underpinning the oncogenic phenotypes observed. High-throughput studies revealed that the transcriptome does not always predict the proteome , highligThis complexity gives rise to the question: How does the cell coordinate metabolism and regulation of mRNAs encoding proteins in the same biological process so that the proteins can be coordinately produced? In answer to this question, Keene and colleagues proposed the RNA regulon model , where mRNA regulons are inherently dynamic, and enable cells to adapt to environmental stresses and cues in a rapid and effective manner. Operation and control of regulons are mediated through targeting RBPs which act as nodes or center-points for these networks. Factors that modulate the localization or activity of these RBPs or that modify the USER codes (such as RNA methylation) ultimately influence the activity of a given regulon. A key control step is the interaction between specific RBPs and their cognate USER codes in the groups of RNAs to be regulated. Here, we suggest the possibility some transcripts may require a two-tier system of USER codes which allow their correct channeling to the appropriate machinery. Here, we provide examples of single and multi-tier systems as a launch point for this notion.Havoc ensues when RNA regulons become dysregulated contributing to a variety of diseases including cancer. Dysregulation of regulons can occur because of dysregulation of RBPs or mutation in the USER codes. Consistent with this, RBPs involved in all levels of mRNA metabolism were found dysregulated or mutated in cancers . Further7G) cap on RNAs to recruit these to the translation machinery, thereby increasing the number of polysomes per transcript, i.e., their translation efficiency. Over time it has become clear that eIF4E regulates the translation of only a subset of capped transcripts (Odc1) and Myc mRNAs but not that of Gapdh or Cyclin D1 , Fth1 (Ferritin heavy chain) translation but not β-Actin or Gapdh  USER code system, as described below.eIF4E is traditionally defined as a factor key to global translation initiation. eIF4E binds the 5′-methyl-7-guanosine  in the 3′UTR required for export of its target transcripts is one of the best understood eIF4E USER codes. The 4ESE is defined by its secondary structure comprised of paired stem loops as determined by nuclease mapping experiments, and is necessary for export. For instance, Z is not , 2006. AZ is not . Other sZ is not , but furs Figure .Biochemical studies of the eIF4E-mRNA export complex elucidated the mechanisms by which the 4ESE directs mRNAs to this level of control . Here, tHas3  mRNA, similarly reduced invasion and metastatic potential indicating that the HA pathway is critical for these eIF4E-driven activities . In this case, the cap or ribavirin analogs prevent association of eIF4E with Importin 8, correlating with reduced nuclear entry of eIF4E, reduced mRNA export and reduced oncogenic activity. Interestingly, Importin 8 also provides evidence of a feedback mechanism whereby eIF4E promotes the export of Importin 8 mRNAs to increase production of this protein and thus its own nuclear entry , and the I-shaped structures (ISS) from Maize necrotic spot and Melon necrotic spot viruses  provides another example of a protein which turns out to function beyond its traditional roles. SRSR3 associates with the spliceosome and was thought to act in the splicing of all intron-containing RNAs . HoweverNanog, Sox2, Kif4, and Myc, and their levels were downregulated in SRSF3-depleted cells  is required. More studies into the minimal domains required to imbue SRSF3 sensitivity are important to understand how this USER code enables recruitment of different complexes to act in splicing, export and/or stability Figure .Nanog, Sox2, Kif4, and Myc are SRSF3 targets (PRC2), Ezh2, and Epop , and the transcriptional targets of FOXM1 including Cdc25B  and PLK1  to control cell cycle progression and proliferation. Depletion of SRSF3 in cancer cells induced G2/M arrest, growth inhibition and apoptosis, while SRSF3 overexpression in rodent fibroblasts induced cell transformation and tumor formation and growth in nude mice , VIM  and TRIO , and increases the stability of SDC4 , TNC (extracellular matrix protein which interacts with SDC4 and is involved in regulation of cell adhesion) and CTTN . Overexpression of VIM and RAC1 can overcome UNR depletion and fully restore colony growth of melanoma cells . In this way, RBPs can act in multiple steps in RNA metabolism by virtue of their function as defined by the recognition of specific RNA binding motifs. In this way, RBPs may be much broader actors in RNA metabolism thereby facilitating the wiring of RNA regulons in the cell. Further, given the RNA world theory, while it has been posited that RNA regulons can recapitulate transcriptional programs, perhaps it is possible that RNA regulons came first. Interestingly, analysis of ancestral stem cells revealed that RBPs are more evolutionarily conserved than transcription factors suggesting that RNA regulons have played a key role in animal stem cell biology for millions of years, even playing roles in sponges and premetazoans . Indeed,All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Ebola virus (EBOV) is a negative-strand RNA virus with significant public health importance. Currently, no therapeutics are available for Ebola, which imposes an urgent need for a better understanding of EBOV biology. Here we dissected the virus-host interplay between EBOV and host RNA-binding proteins. We identified novel EBOV host factors, including Staufen1, which interacts with multiple viral factors and is required for efficient viral RNA synthesis. Ebola virus (EBOV) genome and mRNAs contain long, structured regions that could hijack host RNA-binding proteins to facilitate infection. We performed RNA affinity chromatography coupled with mass spectrometry to identify host proteins that bind to EBOV RNAs and identified four high-confidence proviral host factors, including Staufen1 (STAU1), which specifically binds both 3′ and 5′ extracistronic regions of the EBOV genome. We confirmed that EBOV infection rate and production of infectious particles were significantly reduced in STAU1-depleted cells. STAU1 was recruited to sites of EBOV RNA synthesis upon infection and enhanced viral RNA synthesis. Furthermore, STAU1 interacts with EBOV nucleoprotein (NP), virion protein 30 (VP30), and VP35; the latter two bridge the viral polymerase to the NP-coated genome, forming the viral ribonucleoprotein (RNP) complex. Our data indicate that STAU1 plays a critical role in EBOV replication by coordinating interactions between the viral genome and RNA synthesis machinery. Ebola virus (EBOV) has caused multiple human outbreaks, notably the 2013–2016 catastrophic epidemic in West Africa which led to more than 11,000 fatalities 1–. At presFiloviridae in the order Mononegavirales  that interact with the long and highly structured EBOV RNAs, we used RNA affinity chromatography combined with mass spectrometry (RAC-MS) and analyzed the functional effects of candidate EBOV RBPs on viral infection. We focused on Staufen1 (STAU1), which preferentially associates with both 3′ and 5′ extracistronic regions of EBOV genomic RNA, as an important EBOV proviral host factor. We demonstrated that STAU1 enhances EBOV RNA synthesis and that STAU1 is recruited to EBOV inclusion bodies during viral infection. Unexpectedly, we also revealed that endogenous STAU1 associates with multiple components of the EBOV RNP. Our observations suggest STAU1 is a cellular constituent of EBOV inclusion bodies that is actively engaged in the process of EBOV RNA synthesis.cis-acting elements to hijack cellular factors that facilitate viral infection. To begin testing this hypothesis, we performed an RNA affinity chromatography combined with mass spectrometry (RAC-MS) screen to identify host proteins interacting with selected EBOV RNA regions  EBOV genome 5′ trailer. (B) EBOV genome 3′ extracistronic region. (C) EBOV VP24 mRNA 5′ UTR. (D) EBOV NP mRNA 5′ UTR. Download Copyright © 2018 Fang et al.2018Fang et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mBio.01771-18.10DATA SET S1Data Set S1, XLSX file, 0.0 MB.Summary of host RNA-binding proteins (RBPs) identified by RAC-MS. Results from two independent RAC-MS experiments are shown. Download Copyright © 2018 Fang et al.2018Fang et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mBio.01771-18.2FIG S2FIG S2, TIF file, 26.5 MB.Scatter plots of a repeat experiment showing that host RBPs associate with EBOV RNA identified by RAC-MS. Thirty protein candidates selected in the main article were further analyzed by two additional criteria in order to identify proteins that interact with EBOV RNA. We arbitrarily defined the ratio of normalized total spectra (NTS) for a given EBOV RNA construct to that of the reference RNA construct as enrichment factor 1. Likewise, the ratio of NTS of a particular EBOV RNA construct to the average NTS of all RNA constructs was arbitrarily defined as enrichment factor 2. Identified proteins with an enrichment factor 1 or 2 of >2 were compared across two independent experiments. Proteins that met the criteria described above in both experiments are shown in blue. Download Copyright © 2018 Fang et al.2018Fang et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the We used multiple criteria to classify proteins identified by quantitative MS. The first criterion excluded proteins that nonspecifically bound to the matrix. After ruling out nonspecific interactors, we identified 30 host RBPs shared in both experiments . We then37–We next asked whether the 14 hits identified by RAC-MS affect EBOV infection of HuH-7 cells. We performed small interfering RNA (siRNA)-mediated depletion of each target protein, followed by infection with a replication-competent recombinant EBOV expressing enhanced green fluorescent protein (eGFP) (EBOV-eGFP) , and mea10.1128/mBio.01771-18.3FIG S3P < 0.05; **, P < 0.005; ***, P < 0.0005. Download FIG S3, TIF file, 15.3 MB.Effects of siRNA transfection on cell numbers in the mini-siRNA screen. Cell numbers for siRNAs were normalized to the value for the nonsilencing control (NSC). Values are means and standard errors of the means. Values that are significantly different are indicated by asterisks as follows: *, Copyright © 2018 Fang et al.2018Fang et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the in vitro.We next focused on the role of the double-stranded RNA-binding protein STAU1, because it has not been previously implicated as an EBOV host factor, but it has been reported to play important roles for other RNA viruses –48. Firs–10.1128/mBio.01771-18.4FIG S4FIG S4, TIF file, 9.5 MB.RNA immunoprecipitation of EBOV minigenome RNA with STAU1-Flag. 293T cells were transfected with the EBOV minigenome plasmid, a T7 RNA polymerase expression plasmid, and either vector or STAU1-Flag expression plasmid. RNA-IP was performed with Flag antibody, and 18S rRNA/EBOV minigenome RNAs were quantified by RT-qPCR. For each RNA, the negative control (IP from vector-transfected cells) is normalized to one. The results of two independent experiments are shown. Download Copyright © 2018 Fang et al.2018Fang et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the To confirm the importance of STAU1 for EBOV infection, we characterized the growth kinetics of EBOV-eGFP in STAU1-depleted HuH-7 cells in both one-step (MOI of 3 PFU per cell) and multistep (MOI of 0.01 PFU per cell) infection assays. We performed siRNA-mediated depletion of STAU1 in HuH-7 cells, followed by infection of EBOV-eGFP, and determined the yield of infectious particles secreted into cell supernatants by plaque assay. We also analyzed the kinetics of STAU1 depletion by individual siRNAs. For the one-step growth curve experiment, the yield of infectious particles in STAU1-depleted cells was significantly lower at days 1 and 2 postinfection than in cells transfected with NSC siRNA, indicating that STAU1 knockdown significantly slows the kinetics of EBOV infection . For theGiven that STAU1 was identified as a putative EBOV RBP, we hypothesized that it may be in close proximity to EBOV inclusion bodies where EBOV RNA synthesis takes place . To deteIn mock-infected HuH-7 cells, STAU1 was observed to localize diffusely in the cytoplasm, which is consistent with previous reports describing STAU1 localization to the rough endoplasmic reticulum  50). At. At50). We next sought to determine whether STAU1 is important for the formation of EBOV inclusion bodies. Analysis of the quantity of EBOV inclusion bodies revealed no differences in STAU1-depleted cells compared to control cells  and B, s10.1128/mBio.01771-18.5FIG S5t test under each condition compared to the values for controls. The means and standard errors of means are shown. (C) A representative Z-stack analysis of an inset in panel A with 4× magnification of the merged image. Images on the bottom and right side depict the Z-axis. Bar = 20 μm. Download FIG S5, TIF file, 91.2 MB.STAU1 is dispensable for EBOV inclusion body formation. HuH-7 cells were transfected with 10 nM STAU1 siRNA or nonsilencing control siRNA (NSC) 48 hours prior to infection with EBOV at an MOI of 3 PFU per cell. At 24 hours postinfection, cells were fixed and immunostained with anti-STAU1 (red) and anti-eVP35 (green) antibodies for confocal microscopy. Nuclei were visualized by Hoechst staining. (A) Representative fields are shown from two independent experiments with duplicate wells. The number and area of EBOV inclusion bodies per cell were measured in a total of 639 cells. In each experiment, the number and area of EBOV inclusion bodies in STAU1-depleted cells were normalized to the value for the NSC control (set at 100%). (B) Percent EBOV inclusion body count/area per cell was analyzed using unpaired, two-tailed Copyright © 2018 Fang et al.2018Fang et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the bona fide 3′ and 5′ extracistronic regions of the EBOV genome required for EBOV RNA synthesis. Viral proteins  are supplied by cotransfection of expression plasmids, and a Renilla luciferase (Rluc) expression plasmid is included to normalize for transfection efficiency. The resulting Fluc signal normalized against control Rluc signal is taken as a measure of the activity of EBOV RNA synthesis, which reflects a combination of both genome replication and transcription. We depleted or overexpressed STAU1 in 293T cells and transfected the minigenome system plasmids 48 h later. We observed that cells overexpressing STAU1  assays. 293T cells were cotransfected with plasmids expressing recombinant Flag-tagged STAU1 and either hemagglutinin (HA)-tagged VP35 (HA-VP35) , lane 4 Due to the relatively low signal of VP35 in STAU1 Flag IP samples, we performed a reverse co-IP to confirm the interaction between these proteins. 293T cells were transfected with a plasmid expressing HA-VP35, and anti-HA IPs were performed in the presence or absence of RNase treatment. We observed endogenous STAU1 to co-IP with HA-VP35 . Additio10.1128/mBio.01771-18.6FIG S6FIG S6, TIF file, 49.6 MB.Interaction of STAU1 with EBOV VP35 and VP30. (A) 293T cells were transfected with equal amount of HA-tagged wild-type VP35 (VP35wt-HA), N-terminal domain of VP35 (VP35-N), or C-terminal domain of VP35 (VP35-C) expression plasmids. Forty-eight hours after transfection, cell lysates were harvested for the HA-IP experiments. Representative Western blot analysis from three independent HA-IP experiments is shown. (B) Coimmunoprecipitation of STAU1 with VP30-Flag. 293T cells were transfected with vector or VP30-Flag, and lysates with or without RNase treatment were harvested for IP using Flag antibody. The Western blot shows input and IP samples probed with Flag, STAU1, and PKR antibodies. Representative Western blot analysis from two independent experiments is shown. Download Copyright © 2018 Fang et al.2018Fang et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the We also probed for two cellular proteins that have been previously linked to VP35 and/or STAU1. In contrast to a previous study , we did Together, our results show that STAU1 is able to interact with both VP35 and NP. Although each of these three proteins is capable of RNA binding, co-IP was resistant to RNase treatment, suggesting that RNA was not required for the interaction. Importantly, associations between STAU1 and either VP35 or NP were not altered when both proteins are coexpressed, which has been shown to result in formation of NP/VP35 helical structures that contain cellular RNA and resemble viral nucelocapsids . This reWe further investigated the potential for colocalization of endogenous STAU1 and EBOV VP35/NP by immunofluorescence analysis. Specifically, we asked whether expression of NP, VP35, or both proteins is sufficient to recruit endogenous STAU1 to cytosolic granular structures formed by these proteins. First, consistent with previous studies , 55, 56,Our results imply a possible ternary complex between STAU1, NP, and VP35 proteins. In addition, on the basis of our RAC data, we hypothesized that EBOV minigenome RNA, which harbors 3′ and 5′ extracistronic regions of the EBOV genome, would cofractionate with STAU1 together with NP and VP35 in sucrose density gradient centrifugation. To investigate the possibility that STAU1 can form a complex with EBOV RNP components, we cotransfected 293T cells with plasmids expressing EBOV NP, VP35, and the T7 promoter-driven EBOV minigenome with or without T7 polymerase expression plasmid. After 48 h, cytoplasmic lysates were harvested and separated on 20 to 60% sucrose density gradients. We fractionated the gradients and analyzed the distribution of target proteins and RNA in gradient fractions.Consistent with our previous findings, STAU1 primarily cosedimented with NP and VP35 in low-density fractions . Importa10.1128/mBio.01771-18.7FIG S7FIG S7, TIF file, 91.5 MB.Repeat experiment showing STAU1 and EBOV RNP components  cofractionate in sucrose gradient. 293T cells were cotransfected with plasmids encoding NP, VP35, and EBOV minigenome plasmid with (A) and without (B) a T7 RNA polymerase expression plasmid. Forty-eight hours posttransfection, cell lysates were separated in a 20 to 60% sucrose gradient. Twenty-four fractions were collected and analyzed for protein and RNA levels by Western blotting and qRT-PCR, respectively. Relative quantities of protein and RNA in each fraction were normalized against the total quantity in all fractions. Download Copyright © 2018 Fang et al.2018Fang et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mBio.01771-18.8FIG S8FIG S8, TIF file, 0.4 MB.Depiction of model showing hypothetical interactions between STAU1 and EBOV proteins at the 3′ and 5′ extracistronic regions of the viral genome. Download Copyright © 2018 Fang et al.2018Fang et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the trans-acting factors in the presence of NP. Related to our finding that STAU1 preferentially binds to 3′ and 5′ extracistronic regions of the EBOV genome in vitro, we propose a model in which STAU1 is involved in the early formation of EBOV RNA synthesis machinery on the 3′ extracistronic region of the EBOV genome, and likewise, in the termination and release of EBOV RNA synthesis machinery on the 5′ extracistronic region  was previously identified as a VP35 interactor as well as an EBOV polymerase suppressor  markers  were previously found to localize on discrete, compact granules within EBOV inclusion bodies . In contGiven the correlation between the level of STAU1 expression and EBOV minigenome activity, it is of interest to pinpoint the molecular event(s) STAU1 regulates during EBOV RNA synthesis. For nonsegmented, negative-sense RNA viruses, the first step of viral RNA synthesis is primary transcription in order to generate sufficient levels of viral proteins. When a supply of NP has been synthesized, genome replication and secondary transcription are allowed to commence, leading to the production of encapsidated antigenomes and progeny genomes as well as naked mRNAs . Attempttrans-acting protein Tat, which binds to the transactivation-responsive element (TAR) in the HIV genome, in the context of viral infection  revealed another interesting cellular player, PKR. Although PKR is well-known for its antiviral function by sensing viral RNA and phosphorylating the host translation initiation factor eIF2α , it has nfection , 74. Intnfection , 75, 76.nfection , 54, oneIn conclusion, we identified STAU1 as the first host factor reported to interact with multiple EBOV RNP components, highlighting the significance of this RBP for the EBOV life cycle. These interactions together with redistribution of STAU1 to EBOV inclusion bodies and to NP-induced inclusion bodies link STAU1 to EBOV RNA synthesis, for which we speculate that STAU1 facilitates both the initiation and termination steps. It will be of interest to clarify the exact molecular events occurring during initiation and termination of EBOV RNA synthesis and how STAU1 may participate in these processes. Our study contributes to knowledge of the role of host factors in EBOV RNA synthesis and provides a novel cellular target for the development of possible therapeutic interventions to combat EBOV infection.2. EBOV strain Mayinga and Mayinga expressing green fluorescent protein (GFP) , penicillin (100 U/ml), streptomycin (100 μg/ml), nonessential amino acids, and plasmocin (2.5 μg/ml). Vero-E6 cells were maintained in minimum essential medium supplemented with 10% FBS, 1% sodium pyruvate, and 0.1% gentamicin sulfate. All cells were grown at 37°C and 5% COin (GFP)  were proThe pCI-neo-STAU155R-FLAG plasmid was a gift from Lynne Maquat (University of Rochester). Plasmids pCEZ-NP, pCEZ-VP35, pCEZ-VP30, pCEZ-L, and pCAGGS-T7 were kindly provided by Yoshihiro Kawaoka (University of Wisconsin). The EBOV minigenome system was kindly provided by Elke Mühlberger (Boston University). The pcDNA5-eVP35-HA plasmid and deletion variants were constructed by introducing a C-terminal hemagglutinin (HA) epitope tag by PCR amplification and cloning into pcDNA5/FRT/TO using KpnI and NotI. The pRL-TK plasmid was purchased from Promega. The pCAGGS-eNP-flag plasmid was a gift from Daniel Engel (University of Virginia).Antibody 6C5 for VP35 was purchased from Kerafast. Anti-NP antibody was purchased from IBT Bioservices. Anti-STAU1 (EPR7966) and anti-HA tag (16B12) antibodies were purchased from Abcam. Antitubulin antibody (B-5-1-2) was purchased from Invitrogen. All small interfering RNAs (siRNAs) were purchased from Qiagen -activated Sepharose matrices. Eluted proteins were subjected to either quantitative mass spectrometry or Western blot analysis. For proteins identified by MS, the abundance of each protein is indicated by normalized total spectral counts. We calculated the average abundance of identified proteins in eluate from each RNA construct and normalized it to that from the matrix, which we termed RNA/matrix ratio. From duplicate RAC-MS experiments, we classified host RNA-binding proteins (RBPs) in each sample as proteins with RNA/matrix ratios of >2. To identify RBPs preferentially bound to EBOV RNA, we introduced two enrichment factor criteria to exclude proteins bound nonspecifically to all RNAs. We defined enrichment factor 1 as the ratio of the protein abundance in eluate from a particular EBOV RNA to that from the DDX39B reference RNA. Similarly, we defined enrichment factor 2 as the ratio of the protein abundance in eluate from a particular EBOV RNA to the mean of all RNAs tested. Proteins specifically bound to EBOV RNA were selected with at least one enrichment factor larger than 2.RNA affinity chromatography combined with mass spectrometry (RAC-MS) experiments were performed as described previously . Briefly3) were seeded into 96-well plates and transfected the next day with 10 nM siRNA using Lipofectamine RNAiMAX. Cells were transferred to BSL-4 and 48 h later were infected with EBOV expressing enhanced GFP (EBOV-eGFP) at an MOI of 1 PFU per cell. At 72 h postinfection (hpi), the cells were fixed with formalin and removed from BSL-4 conditions. Nuclei were visualized by Hoechst staining. Rates of infected cells were determined by measuring GFP-positive cells using an Opera Phenix high-content imager. Representative images of fixed and stained monolayers were taken using a wide-field fluorescence microscope (Olympus).HuH-7 cells (5 × 104) were seeded in 24-well plates and transfected with siRNA the next day as described above. Twenty-four hours later, cells were maintained under BSL-2 conditions for Western blot analysis or transferred into BSL-4 facilities for infection. Forty-eight hours after transfection, cells were infected with EBOV-eGFP at an MOI of 3 or 0.01 for 1 h. Infection of the cells was followed by removal of the inoculum, washing the cells with phosphate-buffered saline (PBS) three times, and adding fresh medium containing 2% FBS to the cells. Aliquots of supernatant were harvested every 24 h for virus titration.HuH-7 cells (3 × 104) were seeded in 24-well plates and transfected the next day with siRNA at a final concentration of 10 nM per well using Lipofectamine RNAiMAX 48 h prior to minigenome transfection. For STAU1 overexpression, 6 × 104 293T cells were seeded in 24-well plates and transfected the next day with 500 ng of pCI-neo-STAU155R-FLAG or 500 ng of a control pCI plasmid using Lipofectamine 2000 24 h prior to minigenome transfection. Experiments involving the EBOV minigenome were performed essentially as previously described (293T cells (3 × 10escribed . Conflueescribed  and harv5) seeded in 100-mm dishes were transfected the next day with 14 μg total plasmid(s) using Lipofectamine 2000. Forty-eight hours posttransfection, cells were lysed in radioimmunoprecipitation assay (RIPA) buffer containing protease inhibitors. Anti-HA or anti-Flag M2 agarose beads were blocked in NT2 buffer  with bovine serum albumin (BSA) (0.5 mg/ml) for 30 min. One milligram of cell lysate with or without RNase treatment  was added to agarose beads and incubated overnight at 4°C with rotation. After four washes with NT2 buffer, proteins were eluted in sample buffer and analyzed by Western blotting. In RNA immunoprecipitation (RNA-IP) experiments, RNA was eluted from IP reaction mixtures using TRIzol-LS and analyzed by reverse transcription-quantitative PCR (RT-qPCR) using primers that specifically recognize EBOV trailer.293T cells  for 15 mins, permeabilized with 0.5% Triton X-100 for 10 min, and incubated in blocking solution  for 1 h at room temperature (RT). Primary antibodies were incubated for 2 h at RT or overnight at 4°C. After the cells were washed with PBST (PBS containing 0.1% Tween 20), secondary antibodies and Hoechst stain were added, and cells were incubated for 1 h at RT followed by washes with PBST. Monolayers were fixed by formalin and removed from BSL-4 following SOP. To neutralize formalin, monolayers were treated with 0.1 M glycine for 10 min at room temperature, mounted in ProLong Gold antifade reagent and analyzed by laser scanning confocal microscopy using an Olympus FV1000 confocal microscope with a 60× immersion oil lens. The number and area of EBOV inclusion bodies were quantified using Image J software.5) grown on six-well glass bottom plates were transfected with a total of 2.5 μg of plasmid(s) in different combinations: NP-flag only, VP35 only, and NP-flag and VP35 (4:1). At 24 h posttransfection, cells were fixed, permeabilized, and incubated with different combinations of antibodies. After the final wash with PBST, cells were mounted and analyzed by wide-field fluorescence microscopy (Olympus) using an Olympus IX71 microscope with a 60× immersion oil lens.HuH-7 cells (3 × 107) grown in 100-mm dishes were transfected with plasmids expressing EBOV NP (5.6 μg), VP35 (1.4 μg), and T7 polymerase (3.5 μg) with or without the T7 promoter-driven EBOV minigenome plasmid (3.5 μg). After 48 h, cells were harvested and homogenized in 2 ml lysis buffer . Sequential centrifugations at 700 × g and 1,000 × g for 5 min were performed, and the resulting supernatants were layered onto continuous 20 to 60% sucrose gradients in 10 mM HEPES (pH 7.5) and 1 mM MgCl2 and centrifuged at 31,000 × g for 2.5 h in a SW40 rotor (Beckman). Fractions were collected from top to bottom, and protein and RNA were collected from each fraction for quantification by Western blotting and RT-qPCR, respectively.Cell fractionation on sucrose gradients was adapted from previous studies , 65. 293Details regarding number of replicates and type of statistical test can be found in figure legends. Statistical analyses were performed using GraphPad Prism version 5.01.


Abiotic and biotic stresses severely affect the growth and reproduction of plants and crops. Determining the critical molecular mechanisms and cellular processes in response to stresses will provide biological insight for addressing both climate change and food crises. RNA sequencing (RNA-Seq) is a revolutionary tool that has been used extensively in plant stress research. However, no existing large-scale RNA-Seq database has been designed to provide information on the stress-specific differentially expressed transcripts that occur across diverse plant species and various stresses.We have constructed a comprehensive database, the plant stress RNA-Seq nexus (PSRN), which includes 12 plant species, 26 plant-stress RNA-Seq datasets, and 937 samples. All samples are assigned to 133 stress-specific subsets, which are constructed into 254 subset pairs, a comparison between selected two subsets, for stress-specific differentially expressed transcript identification.http://syslab5.nchu.edu.tw/PSRN.PSRN is an open resource for intuitive data exploration, providing expression profiles of coding-transcript/lncRNA and identifying which transcripts are differentially expressed between different stress-specific subsets, in order to support researchers generating new biological insights and hypotheses in molecular breeding or evolution. PSRN is freely available at The online version of this article (10.1186/s12864-018-5367-5) contains supplementary material, which is available to authorized users. Drought, salinity, heat, cold, chilling, freezing, nutrient, high light intensity, ozone   is a revplant stress RNA-Seq nexus (PSRN), that achieves the following unprecedented features: (i) large-scale and comprehensive data archives and analyses, including coding-transcript profiling and lncRNA profiling, (ii) phenotype-oriented data organization and searching, and (iii) the visualization of expression profiles, as well as differential expression. PSRN was developed with the goal of collecting, processing, analyzing and visualizing publicly available plant RNA-Seq data. Figure http://syslab5.nchu.edu.tw/PSRN.In this study, we constructed the first large-scale plant stress RNA-Seq database, the Arabidopsis thaliana and Oryza sativa were obtained from plant non-coding RNA database (PNRD) [http://www.genome.jp/tools/kaas/) [The annotation for the RNA-Seq datasets regarding plant stress was collected from NCBI GEO , and RNAe (PNRD)  for the e (PNRD)  using the (PNRD) , versions/kaas/)  was useds/kaas/)  of each 2 scale with an added pseudo-count and performed a t-test between two subsets without overlapping samples. To take the type-I error rate into account, we simultaneously used the Benjamini-Hochberg procedure [P-value < 0.01).To estimate the expression profile of each sample, Bowtie , versionrocedure  to calcuArabidopsis thaliana and Oryza sativa data. We selected coding transcripts and lncRNAs with a relatively high expression variance (standard deviation > 0.3 and (standard deviation/mean) > 0.5) within a subset and then calculated Pearson’s correlation coefficient between every pair of selected coding RNA and lncRNA expression profiles for a given subset pair. To assess the significance of these connections, the Pearson’s correlation coefficient was transferred into the P-value and the significant correlations  between protein-coding RNAs and lncRNAs were collected for network construction. Cytoscape [To investigate the potential stress-specific biological functions of lncRNAs in plant cells, we constructed protein-coding RNA and lncRNA coexpression networks from ytoscape  was usedArabidopsis thaliana, Chlamydomonas reinhardtii, Glycine max, Manihot esculenta, Oryza sativa indica, Oryza sativa Japonica, Panicum virgatum, Populus tremuloides, Solanum lycopersicum, Sorghum bicolor, Triticum aestivum, and Vitis vinifera, which contain 26 RNA-Seq datasets and 937 samples. All samples were classified and assigned to 133 stress-specific subsets, which were constructed into 254 subset pairs to describe stress-specific differentially expressed (DE) transcripts from a systematic RNA-Seq analysis. Considering the variants exiting in different analyses, we just compared the expression profile in the same database. We have also checked the consistency between PSRN and the individual analysis in each paper. According to the information of individual papers, we used transcript ID or gene name to find the corresponding expression profile. Most of them displayed similar patterns between PSRN and the individual analyses in different papers.The PSRN database includes 12 plant species: (i)DE coding transcripts: Given a subset pair, PSRN constructs a heat map to visualize the expression profiles of all DE protein-coding transcripts, sorted by the significance level  between two subsets. The interface displays the rank, the P-value, the FDR, the average expression values in the subset, the transcript ID and the homology annotation for each transcript, such as KEGG and RefSeq annotations. Whenever user clicks transcript ID, the PSRN will show details of its expression in all subsets across all datasets belonging to the same species. In this panel, users can filter DE transcripts based on their P-value or FDR threshold and choose to present the sorted transcripts according to whether they are up- or downregulated. Additionally, the search function on the expression profiles allows users to investigate all transcripts associated with the given transcript ID, KEGG Orthology number/Name, or RefSeq annotation, and an autocomplete function provides suggestions for search field as the user types, quickly searching and displaying partially matched terms. The search function also allows users to investigate the expression profiles of multiple genes at one time. To do so, users simply type their transcript IDs, KEGG Orthology numbers/Names, or RefSeq annotations, and separate them by comma.(ii)DE lncRNAs: The DE lncRNAs tab panel is only provided for Arabidopsis thaliana and Oryza sativa (both in indica group and japonica group). All functions of this panel are similar to the DE coding transcript panel but visualize the expression profiles of DE lncRNAs sorted by the P-value.(iii)Protein-coding RNA-lncRNA coexpression network: As shown in Fig. Arabidopsis thaliana and Oryza sativa groups.PSRN provides a user-friendly web interface that integrates large-scale stress-specific RNA-Seq datasets of plants. Three main functional units, analysis, tutorial, and download, were included in PSRN. The tutorial unit provides brief instructions about how to use PSRN. From the download unit, users can retrieve all the differential expression analysis results of all datasets in PSRN. Here, we describe the analysis unit, which is the main function unit of the PSRN database. As shown in Fig. Arabidopsis thaliana as examples.(i)Arabidopsis [Arabidopsis, AtGOLS1 and AtGOLS12 were induced by drought and high-salinity stresses; in contrast, AtGOLS3 was induced by cold stress only [In the analysis results for the GSE54680 dataset, the top 5 significant upregulated transcripts in 10 °C subset are AT3G50970.1 , AT4G14690.1 , AT1G09350.1 , AT5G52310.1 , and AT1G20440.1  Arabidopsis, the HAB1 gene has three alternatively spliced isoforms: HAB1.1 (AT1G72770.1), HAB1.2 (AT1G72770.2), and HAB1.3 (AT1G72770.3). HAB1.1 interacts with the Open Stomata 1 (OST1), inhibiting its kinase activity, which switches the ABA signaling off. In contrast, HAB1.2 encodes a nonfunctional truncated protein, thereby keeping the ABA signaling on. Thus, accurate regulation of the HAB1.1 to HAB1.2 ratio is important for the fine-tuning of ABA signaling and plant adaptation to stress. An RNA-binding motif (RBM)-containing protein RBM 25 is known as a critical key regulator of HAB1 isoforms through its binding to the last intron of HAB1 pre-mRNA in Arabidopsis [In the analysis results for the GSE66737 dataset, we used the HAB1 gene, a group A protein phosphatase 2C (PP2C), to demonstrate the biological importance of the level of expression of isoforms provided in PSRN  the new plant stress RNA-Seq datasets and the reference transcriptomes collection, data curation, and KEGG and Refseq annotations, (2) performing the expression profile analysis pipeline of RNA-Seq datasets. The DESeq will be performed in this update, and the results of both t-test and DESeq will be reported in the database.In this study, we collected, processed, analyzed and visualized all publicly available plant stress RNA-Seq data from NCBI GEO and SRA to construct the PSRN database. Although a few databases have previously been developed for plant stress, PSRN is the first comprehensive database using RNA-Seq data to obtain complete transcriptome profiles and differentially expressed protein-coding transcripts and lncRNAs for various plant species and stress types. Moreover, the systematic and user-friendly web interface can assist researchers in accessing the information efficiently. We hope that PSRN may provide a new resource that can facilitate biologists gaining better biological insights into plant responses to stress with a high resolution of transcript isoforms levels.Additional file 1:Table S1. The list of 133 subsets in 26 datasets of PSRN. (XLSX 15 kb)Additional file 2:Table S2. The stress treatment information and web link of subset pairs in PSRN. (XLSX 37 kb)


Extending the literature on culture and the personal or interpersonal construction of choices, this research investigates consequences of an ingroup member’s vicarious decision for the entire group and the mechanism behind cultural variation. In Study 1, Japanese people showed, compared to Germans, greater acceptance of vicarious choice and evaluated the ingroup member who had chosen on their behalf more positively. Using mediation analyses and priming methods, Studies 2 and 3 identified rejection avoidance to partly explain culturally diverse reactions to vicarious choices. These findings suggest that the mechanism behind cultural differences in choice is related to variation in strength of the motivation to maintain social approval. In this research, drawing on the literature on culture and choice, we examine cultural differences in reactions to a group member’s vicarious choice in Germans and Japanese. Based on previous work suggesting that East Asians are more motivated than Westerners to avoid rejection by group members , we hypoThe self has been featured as being independent and separate from other people in Western cultures such as in Germany, whereas it has been featured as being interdependent and connected with others in East Asian cultures such as in Japan . AgainstCultures promote different implicit frameworks of normative behavior, called models of agency . North AMirroring these divergent models of agency, previous research has illustrated sociocultural variation in emphases on personal and interpersonal aspects in choice. Research identified cultural differences in whether choice is considered individual, personal decision-making or whether multiple people can be involved in a more interpersonally constructed form of choice . People Although evidence is limited, the consequence of the denial of choice also differs across cultures. For instance, in In this research, we pay attention to situations in which someone else decides on behalf of a group, for example, when selecting or saying something on the others’ behalf, and thereby restricts the others in their expression of personal preferences and ideas. Studies have examined how choices made by ingroup  or outgroup  choosers on behalf of the individual affect this individual’s performance and judgments . HoweverWhile negative reactions to the denial of freedom are associated with independence of the self , a positTo explore the underlying mechanism of a cultural difference in the response to vicarious choice, we focus on how being afraid of social rejection leads to avoidant behavior. People care deeply about social rejection, as they want to connect with other people in their own group. The need to belong has been shown to play a significant role across cultures . PreviouHowever, the literature also suggests cultural differences in the significance of the strategy to avoid rejection in order to live a good life. The concern for others’ appraisals might lead individuals across cultures to feel a threat of rejection from the group they belong to, particularly in situations in which all group members form a mutual commitment relationship and can observe individuals’ behavior. Choosing based on one’s inner attributes while ignoring the social context or failing to incorporate others’ preferences could be seen as incongruent to social standards and thus potentially elicit rejection by the other group members. However, as structural factors in Japan promote the prevention of social rejection more strongly than structural factors in Germany, Japanese people might respond more positively to vicarious choice by ingroup members, while Germans would be more likely to risk rejection and claim personal choice. We hypothesized, accordingly, that the cultural differences in reactions can be partly explained by variation in levels of rejection avoidance.The present research conducted three studies among German (representing a Western culture) and Japanese (representing an East Asian culture) participants to explore cultural differences in responses to vicarious choice. We hypothesized that Germans would be more likely than Japanese to demand choice as a reaction to vicarious choice and evaluate the chooser more negatively, whereas Japanese would be more likely than Germans to accept vicarious choices and evaluate the chooser more positively. Following Study 1, which tests the cultural differences, Studies 2 and 3 hypothesized that Japanese would be higher in rejection avoidance than Germans and that higher rejection avoidance would lead people to accept vicarious choice and demand less personal choice.Given that rejection avoidance reflects a concern for social disapproval, the impact on responses to vicarious choice would be clearly demonstrated in a group situation such as when people are working in a team. Thus, we developed a set of group scenarios that one group member first chooses and proposes a collective behavior without asking and considering individual preferences and opinions. Little is known about cultural differences in reactions to vicarious choice in a group setting, as previous findings that the consequences of vicarious choice depend on culture are mainly based on the examinations at the dyadic level  and 99 German adults  were recruited through an online crowdsourcing service in each country . The participants were paid according to local standards. We determined the sample size by referring to ds = 0.33–0.61). We estimated that the sample size was 99 for each culture, assuming the effect size (d) as 0.4 and a value for desired power as 0.80.One hundred and ten Japanese  to 7 (very likely), respectively. In the following analyses, we created an index for acceptance and an index for choice demand over all three scenarios. However, the results were the same when we analyzed them separately.For each scenario, participants indicated on three items how likely they would be to accept the vicarious choice  and on two items how likely they would be to demand personal choice  on Likert-type scales ranging from 1 (likable and sociable) and negatively strongly disagree, 7 = strongly agree). Moreover, participants indicated their agreement to the statement “a situation like this occurs frequently” on a 7-point scale  for each scenario.Furthermore, participants indicated how positively , Japanese participants  indicated that such situations are frequent daily life situations more than German participants  = 3.86, p < 0.001, d = 0.53, 95% CI = ). However, as we were interested in consequences of vicarious choice situations independent of how frequent such situations occur, we controlled for this variable in the following analysesIf vicarious choices are, as expected, more positively connoted in Japan as compared to Germany, it would be natural if vicarious choice situations were more frequent occurrences in Japan than in Germany. Indeed, across scenarios  and demand personal choice  in all three scenarios and conducted ANCOVAs to investigate cultural differences. As predicted, Japanese participants  were significantly more likely than German participants  to accept the choices on their behalf: F = 24.03, p < 0.001, M = 4.91, SD = 1.18) were significantly more likely than Japanese participants  to demand personal choice: F = 57.74, p < 0.001, We calculated participants’ likeliness to accept the vicarious choice  and negatively  the participants would evaluate the ingroup member who had chosen for the entire group across scenarios and compared German and Japanese respondents. As predicted, Japanese evaluated the chooser as more likable and sociable  and less egoistic and dominant  than Germans did . Culture also predicted rejection avoidance tendencies significantly, b = 0.77, SE = 0.12, t(430) = 6.53, p < 0.001, 95% CI = . Importantly, individual rejection avoidance tendencies in turn affected reactions to vicarious choice b = 0.36, SE = 0.04, t(430) = 8.82, p < 0.001, 95% CI =  and the predictive power of culture was significantly reduced to b = 0.65, SE = 0.11, t(430) = 6.23, p < 0.001, 95% CI =  when we controlled for rejection avoidance. Bootstrap analyses revealed a significant indirect effect : 95% CI . Hence, the cultural difference in acceptance of vicarious choice was partially mediated by individual variation in rejection avoidance  = −11.24, p < 0.001, 95% CI = . When we entered rejection avoidance simultaneously to an analysis of regression, the effect of culture was significantly reduced, b = −0.99, SE = 0.10, t(430) = −9.50, p < 0.001, 95% CI =  and rejection avoidance predicted choice demand, b = −0.21, SE = 0.04, t(430) = −5.05, p < 0.001, 95% CI = . The indirect effect was significant ; suggesting that the cultural difference in choice demand was partially mediated by rejection avoidance  = 82.22, p < 0.001; model 2: R2 = 0.283, F = 56.20, p < 0.001], the variance explained by these models did not differ significantly  and the interaction term was not significant . The effect of rejection avoidance was significant in both samples , suggesting that if someone has a strong tendency to avoid rejection, this person is likely to accept vicarious choice regardless of his/her cultural background. When we performed this analysis with choice demand as dependent variable, both models were significant . We found a significant change in R2 = 0.016, F = 9.84, p = 0.002 and the interaction term was significant . However, quite the contrary to the assumption that rejection avoidance plays a crucial role in Japan but not in Germany, the effect of rejection avoidance was stronger in the German sample  than in the Japanese sample . This indicates that in Germany, people with strong tendencies to avoid rejection would rather not demand personal choice, compared to people with weaker rejection avoidance tendencies. In Japan, people would be unlikely to demand personal choice, regardless of their rejection avoidance tendencies.As an alternative possibility, based on the claim that rejection avoidance is more connected to structural factors in Japan than in Germany, the association between rejection avoidance and responses to vicarious choices could be evident in the Japanese sample, but not in the German sample. We tested this possibility by comparing two regression models, one that includes culture and rejection avoidance to predict acceptance of vicarious choice (model 1) and one that includes also the interaction of culture and rejection avoidance (model 2). Although both models were significant  or personal choice demand . Gender was thus not included in the following analyses. Accordingly, data from 81 participants in the social rejection condition (43 Germans and 38 Japanese) and 91 participants in the control condition (49 Germans and 42 Japanese) were analyzed. Based on past research showing a main effect of manipulated social rejection (ds = 0.35 and 0.45 in d = 0.67 in d = 0.50), set the desired power to 0.80, and estimated that the sample size was 63 for each condition.We recruited 105 German and 87 Japanese students. However, because some participants failed to report a situation in which they were strongly rejected, the final sample consisted of 92 German  and demand personal choice  over the scenarios. We ran two ANOVAs to test whether culture and priming condition had an influence on acceptance and choice demand, respectively. Regarding acceptance, Japanese students  were significantly more likely than German students  to accept the choices on their behalf, F = 6.42, p = 0.012, M = 4.10, SD = 0.86) were more likely to accept the ingroup member’s choice than the control group [M = 3.80, SD = 0.94, F = 4.60, p = 0.033, F = 1.13, p = 0.289. Similarly, German students  were more likely to demand personal choice than Japanese students [M = 3.79, SD = 0.98, F = 34.81, p < 0.001, M = 4.02, SD = 0.98) were less likely to demand personal choice than the control group [M = 4.41, SD = 0.99, F = 7.45, p = 0.007, F = 0.76, p = 0.385. The results are illustrated in As in Studies 1 and 2, we calculated participants’ likeliness to accept vicarious choice , our findings can be generalized only to everyday choice situations and not to more consequential choices. It is possible that Japanese people are more likely to demand personal choice if the decision is important to them, or alternatively, that increased importance makes them even more likely to reflect upon social approval and accept choices on their behalf. Similarly, more consequential decisions might lead Germans to incorporate the social context more strongly or to be even more likely to decide merely based upon their own preferences. Indeed, previous research suggested that the importance of a decision is a relevant factor to consider . FurtherDespite providing insights into the mechanism behind culturally diverse reactions to vicarious choice, rejection avoidance tendencies cannot fully explain sociocultural differences. Additional testing for mediators, such as self-esteem , self-moAnother future research direction could be to examine more automatic and unconscious responses to vicarious choice and to investigate its neural mechanism. For instance, given that the dorsal anterior cingulate cortex (dACC) plays a crucial role in the detection of a behavioral conflict, previous research found that cognitive dissonance, particularly conflict evoked by difficult choice, is linked to strong activation of dACC . If WestFinally, it is important to explore whether cultural differences in reaction to vicarious choice mediated by rejection avoidance can be observed even in children. Given that To conclude, the present research adds to previous evidence on culture and choice by showing that responses to vicarious choice differ across cultures. It also provided the first evidence that the cultural influence on responses to vicarious choice can be explained by cultural differences in rejection avoidance. This evidence for the mechanism that underlies responses to vicarious choice has implications for fields such as marketing and politics particularly in the globalizing world today where people with different cultural backgrounds are urged to work together as a group. Also, the present research presents interesting questions, which should be addressed in future research. We believe that additional insight provided by further investigations suggested in the present research will enhance our understanding of cultural mechanisms behind responses to vicarious choice.The study was reviewed and approved by the Experimental Research Ethics Committee at the Graduate School of Humanities, Kobe University. Participants provided written informed consent at the beginning of the study. All responses were confidential.CE and KI designed the research. CE and KI performed the research. CE analyzed the data. CE and KI wrote the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest.


The trinucleotide repeat expansion disorders (TREDs) constitute of a group of >40 hereditary neurodegenerative human diseases associated with abnormal expansion of repeated sequences, such as CAG repeats. The pathogenic factor is a transcribed RNA or protein whose function in the cell is compromised. The disorders are progressive and incurable. Consequently, many ongoing studies are oriented at developing therapies. We have analyzed crystal structures of RNA containing CAG repeats in complex with synthetic cyclic mismatch-binding ligands (CMBLs). The models show well-defined interactions between the molecules in which the CMBLs mimic nucleobases as they form pseudo-canonical base pairs with adenosine residues and engage in extensive stacking interactions with neighboring nucleotides. The binding of ligands is associated with major structural changes of the CAG repeats, which is consistent with results of biochemical studies. The results constitute an early characterization of the first lead compounds in the search for therapy against TREDs. The crystallographic data indicate how the compounds could be further refined in future biomedical studies. Microsatellites or short tandem repeats (STR) are highly abundant sequences scattered throughout the human genome . The maiThe pathogenesis of TREDs depends on where the repeated sequences are localized in the gene . When exRepeat expansion disorders are progressive and incurable, and they are the subject of many ongoing studies to develop therapies targeting the toxic RNAs and proteins . Diversein vitro and in vivo observations relevant to the biomedical aspects of TREDs.In recent years, we have solved the crystal structures of all four CNG repeats . This alSubsequently, we have designed a group of small molecules to target noncanonical base-pairs in RNA or mismatches in DNA . The ligHere, we report the structural and biochemical studies of CMBLs in complexes with the CAG repeats. These first crystal structures of RNA repeats with small ligands show major structural changes, as the ligands recognize the noncanonical A-A pairs. The observed induced fit would be difficult to foresee, yet the structures should be insightful for chemists attempting to develop molecules to target RNA.3-C)AGC were synthesized according to published protocols . All pictures were drawn using PyMOL  data were collected at the wavelength 0.9756 Å corresponding to the selenium absorption edge. The data were integrated and scaled using the program suite XDS with XDSAPP or xdsgui interface ,38. Datang PyMOL . Atomic 2 and (GCAGCAGC)2 (5 μM) with or without CMBL3a (20 μM) were carried out in a buffer containing 10 mM sodium cacodylate pH 7.0, 100 mM NaCl and 2% DMSO. Measurements were performed using SHIMADZU UV-2550 UV/Vis spectrometer linked to a Peltier temperature controller. The absorbance of the sample was monitored at 260 nm from 2°C to 85°C with a heating rate of 1°C/min. The melting point for a given experiment was calculated using the median method. RNA oligonucleotides were purchased from Gene Design Inc.Thermal denaturation profiles of (UCAACAGUUGA)2EDTA, pH 7.0. The GCAGCAGC oligomer was prepared in nine different concentrations in the range 10−5 to 10−6 M. The concentrations of single strand oligomers were calculated from a high-temperature (>80°C) absorbance and single strand extinction coefficients approximated by the nearest-neighbor model. For the thermodynamics study of RNA-ligand complexes, the appropriate CMBL molecule was added to the RNA duplex in a 4:1 molar ratio. The UV absorption versus temperature was measured at 260 nm at the heating rate of 1°C/min in the range 5°C – 95°C. The melting curves were analyzed and the thermodynamic parameters calculated using MeltWin 3.5. The enthalpy (ΔH), entropy (ΔS) and free energy (ΔG37), for 37°C, were calculated by two methods: fitting the experimental and theoretical melting curves and linear correlation of the melting temperature 1/TM and concentration of RNA (log CT). Melting point (TM) was calculated at the RNA concentration of 10−4 M.Detailed UV thermal melting studies were performed according to Pasternak and Wengel (2010) on a JASCO V-650 spectrometer equipped with a thermo-programmer . The UV 9–518 RU, (CCG)9–882 RU, (CGG)9–482 RU and (CUG)9–503 RU. CMBL3a ligand in 1 mM DMSO was diluted in 10 mM HEPES, 150 mM NaCl, 3.0 mM EDTA, pH 7.4 and 0.005% (v/v) Surfactant P20 such that the final ligand solution contained 5% DMSO. Sensorgrams were obtained in the 0.1–0.5 μM ligand concentration range, 60 μl/min flow rate, 30 min of contact time and 120 s of dissociation time. All sensorgrams were corrected by reference subtraction of blank flow cell response and buffer injection response.SPR single cycle kinetics assay were performed using Biacore T200 platform. RNA oligomers were immobilized on the Series S sensor chip SA surface using avidin-biotin coupling in 10 mM HEPES and 150 mM NaCl, pH 7.4. 5′-Biotinylated oligonucleotides (Gene Design Inc.) were diluted to 0.2 μM concentration in 10 mM HEPES and 500 mM NaCl and injected with contact time of 840 s and flow rate of 5 μl/min to reach the response of around 500 RU (Response Unit). Blank immobilization was performed in the flow cell 1 to permit reference subtraction. The amount of immobilized RNA was as follows: (CAG)9 (2.5 μM) with variable concentration of CMBL3a  were measured at ambient temperature in 10 mM sodium cacodylate pH 7.0 and 100 mM NaCl. The apparent dissociation constant (Kd) of (CAG)9-CMBL3a complex was calculated by fitting the data to the 1:2 binding isotherm. RNA oligonucleotides were purchased from Gene Design Inc.Circular dichroism measurements were carried out using J-725 CD spectropolarimeter (JASCO). CD titration spectra of (CAG)N-acyl-amino groups and additional constituents: in CMBL3a it is a E-alkene, in CMBL3b it is an Z-alkene, and in CMBL4 it is an aminoalkyl moiety. Each ligand was cocrystallized with a GCAGCAGC RNA oligomer, giving crystals suitable for X-ray diffraction experiments.Three cyclic bis-naphthyridines (CMBLs) were used in this study: CMBL3a, CMBL3b and CMBL4 Figure . In each2-CMBL3a, one structure of (GCAGCAGC)2-CMBL3b and one (GCAGCAGC)2-CMBL4 complex have been analyzed ed Table . ElectroIn all of the models, two CMBL molecules are bound to each RNA duplex. The ligands are located inside the RNA helix and mimic nucleobases. One ligand interacts simultaneously with two adenosine residues located on opposite RNA strands Figure , C. Eachexo-amino group of A and the imine group of the naphthyridine ring  Figure , C. The endo conformation of the 3A ribose 2–CMBL complexes showed an increase in thermal stability compared to the unliganded RNA 9 (9 (9 (9 (The surface plasmon resonance (SPR) assay of CMBL3a binding was performed on (CNG)r (CAG)9 . No SPR CAG)9 (9  and (CCG)9  spectra of (CAG)n Figure , B. BaseThe presented results are part of our search for compounds that would interact specifically with the pathogenesis-related RNA repeats. The described complexes of the cyclic bis-naphthyridines with CAG repeats are the first crystal structures of this type. The models show details of the ligand binding, local and nonlocal effects on the RNA structure and interactions with the solvent, which should be useful for developing therapeutics against TREDs. The structural results are supported by biochemical data.via one weak N1···H-C2 H-bond, and the large purine rings are accommodated by shifting them towards the major groove of the helix 9 oligomer, providing additional evidence of structural rearrangements, even though the spectroscopic measurements and crystallography were performed under different experimental conditions.The rearrangements around the adenosine residues are reflected by changes of the helix backbone conformation. The backbone torsion angles are changed, one adenosine of each pair has the ribose ring in the C2′-in silico approaches. Nevertheless, the UV-melting experiments indicate that the rearrangement caused by the ligand is thermodynamically favorable. The melting temperature of the RNA–ligand complex is consistently higher than for the sole RNA molecule, suggesting that stability is increased by the formation of adenosine-CMBL pairs. Removing the C–G pairs from the helix could relieve geometric constrains and allow optimal stacking interactions of the remaining nucleobases with the naphthyridine rings.The flipping out of G and C residues is unexpected since the G–C pairs have been a constant feature in all the structures of the CNG repeats and are expected to be a major stabilizing factor in the duplex. Such extensive structural rearrangements would be difficult to predict by via ring stacking  the aromatic rings of the ligands and their potential for stacking interactions, (ii) the ring edges and their potential to form H-bonds with the nucleobases and (iii) the linkers between the rings.via a water molecule (Figure via the shorter linker to make a ligand that would target two A–A pairs simultaneously. The crystal structures show the liganded adenosines come into direct contact as the C and G residues are looped out of the helix. A ligand that would stabilize such a state should be more specific than two ligands acting separately. One of approaches toward this strategy has been reported recently (CMBL ligands make extensive stacking interactions within the RNA duplex; each naphthyridine moiety is inserted between two nucleobases. Much of the binding energy certainly comes from aromatic stacking, but such interactions are nonspecific. The base-pairing contacts are much more selective. The inner edge of the naphthyridine ring has the potential for three H-bonds: the two imine groups and one amine, evenly spaced, form an array of two acceptors and a donor Figure . Two of e Figure . A possirecently . In the Atomic coordinates and structure factors for the reported crystal structures have been deposited with the Protein Data bank under accession numbers 6QIQ, 6QIR, 6QIS, 6QIT, 6QIV.gkz832_Supplemental_FileClick here for additional data file.


The widespread applications of substituted diketopyrrolopyrroles (DPPs) call for the development of efficient methods for their modular assembly. Herein, we present a π‐expansion strategy for polyaromatic hydrocarbons (PAHs) by C−H activation in a sustainable fashion. Thus, twofold C−H/N‐H activations were accomplished by versatile ruthenium(II)carboxylate catalysis, providing step‐economical access to diversely decorated fluorogenic DPPs that was merged with late‐stage palladium‐catalyzed C−H arylation on the thus‐assembled DPP motif. PAHs: Double C−H/N−H activation by ruthenium(II) catalysis enabled the assembly of π‐expanded diketopyrrolopyrroles with unique spectroscopic features (see scheme). N‐Alkylation leads to DPPs with improved solubilities, the properties of which can be fine‐tuned by the incorporation of different aromatic motifs.Since their first synthesis,DPP derivatives with a highly decorated periphery as well as DPP‐based polymers are usually obtained through conventional condensation reactionsDuring the past decade, C−H activation has been identified as a transformative platform for various small molecule derivatizations through alkyne annulations.1 a with alkyne 2 a , with o‐xylene being superior. Control experiments confirmed the essential role of carboxylate‐assisted ruthenium(II) catalysis (entries 10–11). The particularly challenging character of the twofold C−H/N−H activation was reflected by palladium and iridium catalysts failing short in delivering the desired product 3 aa (entries 13 and 14). Likewise {Cp*RhIII}‐catalysis was significantly less effective than the cost‐effective ruthenium(II) manifold (entries 15 and 16).We initiated our studies by probing various reaction conditions for the envisioned double C−H/N−H activation of diketopyrrolopyrrole 1 a with a variety of aryl‐substituted alkynes 2 /6–311+G+SMD(o‐Xylene) level of theory  of 2.02 eV. Our computed absorption spectrum is in good qualitative agreement with the experimental data.To investigate further the electronic structure of the DPPs 3 am in terms of the introduction of two aryl motifs7 was realized by palladium‐catalyzed twofold C−H arylations. It is noteworthy that the C−H activation‐based incorporation of two aromatic moieties drastically shifted both the absorption and the emission maxima into the NIR region, which was mirrored by the green color of PAH 7.Finally, we became attracted by further late‐stage functionalization of PAH In summary, we have devised an enabling strategy for the assembly of π‐extended DPPs. Thus, ruthenium(II)‐catalyzed double C−H/N−H activation allowed for the synthesis of novel, diversely‐decorated DPP derivatives in a step‐economical manner. The novel DPPs were fully characterized, including spectroscopy, XRD and DFT computation. The twofold alkyne annulation was furthermore merged with C−H arylations of the thus obtained π‐extended PAHs to furnish DPPs with absorption and emission maxima shifted into the NIR region. Our findings should prove invaluable for applications to optoelectronics, material sciences and live cell imaging.The authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.