High-throughput sequencing (HTS) provides a powerful solution for the genome-wide identification of RNA-editing sites. However, it remains a great challenge to distinguish RNA-editing sites from genetic variants and technical artifacts caused by sequencing or read-mapping errors.Here we present RES-Scanner, a flexible and efficient software package that detects and annotates RNA-editing sites using matching RNA-seq and DNA-seq data from the same individuals or samples. RES-Scanner allows the use of both raw HTS reads and pre-aligned reads in BAM format as inputs. When inputs are HTS reads, RES-Scanner can invoke the BWA mapper to align reads to the reference genome automatically. To rigorously identify potential false positives resulting from genetic variants, we have equipped RES-Scanner with sophisticated statistical models to infer the reliability of homozygous genotypes called from DNA-seq data. These models are applicable to samples from either single individuals or a pool of multiple individuals if the ploidy information is known. In addition, RES-Scanner implements statistical tests to distinguish genuine RNA-editing sites from sequencing errors, and provides a series of sophisticated filtering options to remove false positives resulting from mapping errors. Finally, RES-Scanner can improve the completeness and accuracy of editing site identification when the data of multiple samples are available.de novo RNA-editing site identification and annotation for any species with matching RNA-seq and DNA-seq data. The package is freely available.RES-Scanner, as a software package written in the Perl programming language, provides a comprehensive solution that addresses read mapping, homozygous genotype calling, The online version of this article (doi:10.1186/s13742-016-0143-4) contains supplementary material, which is available to authorized users. Caenorhabditis elegans [Drosophila melanogaster [RNA editing is a post-transcriptional-processing mechanism, which alters RNA sequences by insertion, deletion or modification of specific nucleotides so that the information in the mature RNA differs from that defined in the genome , 2. In m elegans  and Drosnogaster  and is anogaster , 14.de novo identification of RNA-editing sites in non-model species.High-throughput RNA sequencing has enabled genome-wide identification of RNA-editing sites in any species. However, distinguishing RNA-editing events from genetic variants and technical artifacts caused by sequencing or read-mapping errors is still a challenge –18. MuchREDItools was the first published software package for genome-wide RNA-editing site identification. It uses pre-aligned HTS reads in BAM format as inputs and implements a variety of filters to remove potential false positives . Howeverde novo RNA-editing site identification and annotation for any species with matching RNA-seq and DNA-seq data.Here we introduce RES-Scanner (RES: RNA-editing site), a flexible and efficient software package written in the Perl programming language, which has been developed for genome-wide identification and annotation of RNA-editing sites. RES-Scanner is designed to address HTS read mapping, homozygous genotype calling, and Acromyrmex echinatior [The prototype of RES-Scanner was developed during our previous study of RNA editomes in the leaf-cutting ant hinatior . To facihinatior .Fig. 1OvC. elegans [While the inputs for RES-Scanner are single/paired-end reads in FASTQ format, RES-Scanner can invoke BWA, an effective and accurate short-read aligner , to map  elegans  and ant  elegans . However elegans , TopHat2 elegans , GSNAP [ elegans , and HIS elegans . Thus, uIn the next step, RES-Scanner only keeps those reads with unique alignment and with no suboptimal hits using Perl scripts, and discards potential PCR duplications  except for the one with the highest mapping quality according to the ‘rmdup’ function of SAMtools . Given tPrevious studies usually distinguished candidate RNA-editing events from genome-encoded variants based on frequency of the alternative allele  present in the DNA-seq data, followed by selection of an arbitrary threshold , 25, 29.RES-Scanner introduces a statistical model based on a Bayesian method (Bayesian model) to infer the genotype of each genomic site on the reference genome . This stRES-Scanner also provides two additional methods to estimate the reliability of a homozygous genotype: one is based on a binomial distribution model  and the other is based on the read depth and the frequency of the alternative allele (Frequency model) present in the DNA-seq data  of this site must be ≥ 5 %. Bases on RNA reads with a Phred quality score below 30 are discarded, restricting the upper limit of sequencing error for an RNA base to < 0.1 % for any candidate editing site. Users can modify the quality score cutoff according to their dataset. These candidate editing sites are then subjected to genotype analysis as described above, and only the sites showing robust homozygosity in genomic DNA are kept. RES-Scanner also allows users to supply a list of potential SNPs derived from other analyses or databases of the target species, and exclude candidate editing sites that overlap these SNPs. Candidate sites that show multiple editing types are also discarded as these positions may be associated with higher probabilities of mapping error.To avoid potential false positives resulting from misalignment of reads onto very similar paralogous regions, RES-Scanner invokes BLAT , a BLASTIn addition to these basic filters, and to avoid potential false positives resulting from mis-mapping of reads at splice junctions, RES-Scanner requires a candidate editing site to be supported by at least one RNA read in the middle of its length (e.g. from positions 23 to 68 of a 90-bp read), and discards intronic candidate sites that occur within six bases of a splice site. RES-Scanner also removes sites in homopolymer runs of five or more base pairs (e.g. AAAAA), given that homopolymers have higher rates of sequencing error . FinallyTo further eliminate false positives due to sequencing errors, RES-Scanner performs statistical tests for all the candidate editing sites based on the binomial distribution B , where pOwing to the stringent filtering criteria of RES-Scanner in identifying RNA-editing sites for a single sample, a number of true positives may be missed due to their low editing level, insufficient sequencing depth or failure to satisfy other requirements. These editing sites can, however, be retrieved by RES-Scanner if multiple samples across individuals or tissues are available. RES-Scanner first combines all editing sites identified in each sample to obtain a comprehensive map of potentially editable positions in the genome of the target species. These positions are homozygous for DNA, located in unique genomic regions, not close to any splice sites and RNA-edited in at least one of the multiple samples. RES-Scanner then retrieves missed editing sites in each sample in these editable positions using the more liberal criteria of at least one RNA read supporting editing and an FDR below a user-chosen cutoff . DNA data from multiple samples are also helpful in improving the accuracy of calling homozygous genomic sites. RES-Scanner will discard any editing site for which the genomic DNA is not homozygous in any one of the multiple DNA samples.RES-Scanner can annotate the identified RNA-editing sites with a variety of genomic features, such as exon, intron, coding sequence (CDS), 5‘-untranslated region (5‘-UTR), 3‘-UTR and repeat, if the position files of these genomic features are provided   and the r = 0.90 and p < 10−15; Additional file For the ant dataset, we ran RES-Scanner with default parameters, except for setting the ploidy to eight for the Bayesian model to determine homozygous genomic sites due to the special genetic background of the ant samples  for det, represeWe next tested the performance of the three models  on homozygous genotype calling and RNA-editing site identification based on the data of sample L363 from Li et al. . In geneFor the human dataset, we performed a comprehensive comparison of the results from RES-Scanner with those generated by Ramaswami et al. , REDItooTaken together, these results indicate that RES-Scanner provides high accuracy in genome-wide RNA-editing site identification using matching DNA-seq and RNA-seq data, and it is capable of working on organisms with simple genomes like ants and complex genomes like humans.We first compared the overall runtime of RES-Scanner to REDItools and GIREMI in processing the human GM12878 dataset from pre-aligned reads to final editing sites. It is not surprising that GIREMI runs much faster than RES-Scanner  on non-diploid samples from non-model species using the leaf-cutting ant dataset from Li et al. , in whicFinally, RES-Scanner can provide an integrated, end-to-end solution that works from raw sequencing reads to final editing sites, greatly reducing the risk of incompatibility between read alignment outputs and the downstream editing site identification pipeline. RES-Scanner can automatically annotate identified RNA-editing sites with genomic features and deduce codon and amino acid changes after RNA editing, providing useful information for downstream analysis. Furthermore, the final result file output by RES-Scanner has integrated DNA and RNA information from all samples for each editing site, greatly facilitating downstream comparative analysis between different samples. Thus, we believe that RES-Scanner is also superior to other existing software packages in terms of ease of use.It is equipped with rigorous statistical models  to infer the reliability of homozygous genotypes derived from DNA-seq data. This approach is different from traditional SNP calling, which is aimed at ensuring the reliability of genetic polymorphism rather than homozygosity.With these statistical models, RES-Scanner is capable of calling homozygous genotypes reliably from samples with any ploidy number, including samples from a pool of multiple individuals. This feature is especially useful because many species - or the target tissues of a species - are small in size and, in practice, pooling of multiple individuals is usually required to obtain enough biomass for sequencing.RES-Scanner implements binomial tests to rigorously distinguish RNA-editing sites from sequencing errors by assigning a p-value to each RNA-editing candidate.RES-Scanner provides a complete pipeline from raw sequencing reads to final editing sites, which should be especially valuable to users who have limited experience in bioinformatics or are working with non-model species with no prior knowledge of the optimal mapping strategy.Compared with existing packages, RES-Scanner provides four novel features:The application of our package to the leaf-cutting ant and GM12878 human datasets demonstrates that RES-Scanner provides high accuracy in identifying RNA-editing sites using matching DNA-seq and RNA-seq data. It should be noted that RES-Scanner is not species-specific: it is applicable to genome-wide identification of RNA-editing sites in any species with matching RNA-seq and DNA-seq data.A detailed user manual for RES-Scanner is available in Additional file Project name: RES-ScannerProject home page: https://github.com/ZhangLabSZ/RES-ScannerOperating systems: Linux/Mac OS XProgramming language: PerlRequirements: See Additional file License: GPL v3Restrictions to use by non-academics: NoneFDR, false discovery rate; HTS, high-throughput sequencing; MI, mutual information; SNP, single-nucleotide polymorphism; SNV, single-nucleotide variant


Circular RNAs (circRNAs), a kind of covalently closed RNA molecule, were used to be considered a type of by-products of mis-splicing events and were discovered sporadically due to the technological limits in the early years. With the great technological progress such as high-throughput next-generation sequencing, numerous circRNAs have recently been detected in many species. CircRNAs were expressed in a spatio-temporally specific manner, suggesting their regulatory functional potentials were overlooked previously. Intriguingly, some circRNAs were indeed found with critical physiological functions in certain circumstances. CircRNAs have a more stable molecular structure that can resist to exoribonuclease comparing to those linear ones, and their molecular functions include microRNA sponge, regulatory roles in transcription, mRNA traps that compete with linear splicing, templates for translation and possibly other presently unknown roles. Here, we review the discovery and characterization of circRNAs, the origination and formation mechanism, the physiological functions and the molecular roles, along with the methods for detection of circRNAs. We further look into the future and propose key questions to be answered for these magical RNA molecules. CircRNA is a member of the non-coding RNA kingdom. Unlike the traditionally known RNA species, sequence of circRNA is not arranged in a normal order relative to the genomic context but arrays in a scrambled manner, in which the 3′ downstream sequences are joined to the 5′ upstream sequences, resulting in a covalent-closed circular molecule without free terminals, resemble that of plasmids.DCC gene in the human cell line  , a circular RNA, which contained dozens of microRNA-7 (miR-7) binding sites, could resist the microRNA (miRNA)-mediated endocleavage pathway and acted as a competing endogenous molecule in gene expression regulation  circRNA could also function as a decoy to absorb miR-138 , the functions of circRNAs may depend on the features of their sequences and structures. Recent studies had revealed that the antisense transcript of cerebellar degeneration-related protein 1  had half-lives of less than 20 h  tail) are absent in these transcripts. Because of the absence of free terminals, these molecules can easily antagonize the hydrolysis by various cellular exoribonucleases. Jeck et al. proved that the half-lives of four circular RNAs exceeded 48 h, whereas the linear transcripts of corresponding parent genes  and usually considered to be by-products of splicing in the past a few years. For example, the abundances of circRNA derived from the n Dixon, . Benefitn Dixon, . It shoun Dixon, .Sry gene are the main transcripts in embryonic brains on Days 11–19, whereas linear molecules become more ample in postnatal brains, wherein circRNAs can even be absent  in length  and some are originated from lncRNAs  in inverted orientation within the introns flanking the joined exons are indispensable cis- elements, and they are reported contributing to the circularization of RNA , a splicing factor, is thought to promote its own circRNA biogenesis from the second exon in Drosophila and humans  protein, an RNA binding protein containing KH domain and also an alternative splicing factor, was found to be correlate well with the circRNAs dynamic change during EMT, wherein, QKI protein recognizes the QKI binding motifs within the introns adjacent to the joined exons of circRNAs to promote the circRNAs biogenesis  retained in the nucleus can act as activators of parent gene by interacting with Pol II machinery  linear RNA. Further study demonstrated that this specific fmn mutant mice exhibited an incomplete penetrant renal agenesis phenotype, suggesting that the unproductive circRNA could have important physiological roles in regulating developmental process . It is assumed that backsplice produces circular RNA and corresponding truncated linear transcript Fig. . AlthougNCX1) in transfected cells. The size of the truncated protein was consistent with the predicted molecular weight (MW) of approximately 70 kDa, and also exhibited Na/Ca exchange activity  is another artifact in circRNA detection using RT-PCR. Therefore, more accurate methods are required to confirm the positive results, such as using the same out-facing primer pair for the genomic DNA as a control when PCR was carried out. There are optional ways to improve the accuracy in identifying circRNA, such as enriching circRNA by degrading linear RNA with exonuclease—RNase R or tobacco acid pyrophosphatase combined with 5′-phosphate-dependent exonuclease  with dynamic expression changes were supposed to be involved in the circRNA biogenesis, such as QKI protein (Conn et al., The biogenesis mechanism of circRNAs is under intensive investigation recently. Multiple lines of evidence supported the hypothesis that complementary-sequence-mediated exon circularization could be a broad source of circRNA production (Jeck et al., CDR1as, can be negatively regulated by miR-671 through Ago2-mediated endocleavage pathway (Hansen et al., Moreover, future studies should take into consideration of circRNA degradation or turn-over, since both degradation and biogenesis of circRNA determine their temporal-spatial specific accumulation, and contribute to their biological function in certain circumstances. However, it is almost totally unknown in this important aspect for circRNAs, though a conformed evidence has shown that a circRNA, With the continuous decrease of sequencing cost, RNA-seq become the most prevalent method for identification of circRNAs. Although a few bioinformatic algorithms such as MapSplice (Wang et al., Lastly, future studies should also attach some importance to circRNA-involved regulatory network, which would help us comprehensively understand the formation, biological and physiological function, and degradation of circRNAs. To sum up, circRNA, acting as a new transcriptome regulation player, is attracting an increasing number of researchers to this emerging field.


The substitution of 2′-fluoro for 2′-hydroxyl moieties in RNA substantially improves the stability of RNA. RNA stability is a major issue in RNA research and applications involving RNA. We report that the RNA polymerase from the marine cyanophage Syn5 has an intrinsic low discrimination against the incorporation of 2′-fluoro dNMPs during transcription elongation. The presence of both magnesium and manganese ions at high concentrations further reduce this discrimination without decreasing the efficiency of incorporation. We have constructed a Syn5 RNA polymerase in which tyrosine 564 is replaced with phenylalanine (Y564F) that further decreases the discrimination against 2′-fluoro-dNTPs during RNA synthesis. Sequence elements in DNA templates that affect the yield of RNA and incorporation of 2′-fluoro-dNMPs by Syn5 RNA polymerase have been identified. These properties result in a longer survival time of 2′-F RNAs  rference –8.The most common 2′-F substitutions used in RNAs are 2′-F-dCMP and 2′-F-dUMP. RNAs containing these substitutions are resistant to RNase A, the most common RNase contaminant, which recognizes the 2′-OH of pyrimidines for cleavage . 2′-F RNin vitro transcription. These advantages include product-3′-homogeneity, high processivity, flexible initiating nucleotide and tolerance to salt  was from Epicentre. DNA Clean & Concentrator™-5 kit was from ZYMO Research. RNaseOUT™ recombinant ribonuclease inhibitor was from Invitrogen. NTPs were from USB and 2′-F-dNTPs were from Trilink.Oligonucleotides were obtained from Integrated DNA Technology . DNA purification kits and Ni-NTA resin were from Qiagen. Preparative Superdex 200 for gel filtration was from GE Healthcare. Restriction endonucleases, T4 DNA ligase, VentE. coli cells harboring this vector grow significantly faster than those carrying the original plasmid and contain higher levels of overproduced protein . Y564F and Y574F mutations were introduced into the Syn5 RNA polymerase gene in the Syn5 RNAP-NP-pET24 vector by polymerase-chain-reaction mutagenesis.We have modified the original expression vector ,16 to imE. coli BL21(DE3) cells containing the plasmid Syn5 RNAP-NP-pET24 were grown in 2 L of LB medium containing 50 μg/ml kanamycin at 37°C until they reached an OD600 of 1.2. The gene for Syn5 RNA polymerase was induced by the addition of 0.5 mM IPTG at 25°C and incubation was continued for 4–8 h. The cells were harvested, resuspended in 50 mM sodium phosphate, pH 8.0, 100 mM NaCl, and lysed by three cycles of freeze-thaw in the presence of 0.5 mg/ml lysozyme. Solid NaCl was added to the lysed cells to a final concentration of 2 M and then the cleared lysate was collected after centrifugation. 5 ml Ni-NTA agarose was added to the clear lysate and gently mixed at 4°C overnight. The resin was loaded and collected in a column and washed with 60 ml of Wash Buffer . Syn5 RNA polymerase was eluted from the column using 30 ml Elution Buffer . Eluted protein was concentrated to 1 ml using an Amicon Ultra-15 Centrifugal Filter Units (Millipore). The concentrated sample was loaded directly onto a 200 ml preparative Superdex 200 column. The gel filtration buffer contained 20 mM Tris-HCl pH 7.5, 2 M NaCl, 0.5 mM DTT and 0.5 mM EDTA. Fractions were analyzed on SDS-PAGE gels and those fractions that contained homogenous Syn5 RNAP were pooled. The pooled fractions were concentrated by Amicon Ultra-15 Centrifugal Filter followed by dialysis against Dilution Buffer  and stored at −20°C. Dilutions for enzyme assays were carried out using Dilution Buffer. The yield of Syn5 RNA polymerase following this procedure was greater than 20 mg protein per gram of wet cells, with the majority of the soluble Syn5 RNA polymerase (>80%) retained in the flow-through and wash fractions of the Ni-NTA step. Repetition of this procedure using the flow-through fraction of the Ni-NTA column generates similar amounts of purified protein. Syn5 RNA polymerase mutants Y564F and Y574F were purified following the same procedure resulting in a similar yield.The purification procedure was modified from that previously described . E. coliT1: GGTATTGGGCACCCGTAAGGAGAACCTTAA GGTTTAACTTTAAGACCCTTAAGTGT2: GCCATTGGGCACCCGTAAGGGAGAGAGCAT CGCTTGGTGCAGATCGGGACT3 : GCCATTGGGCACCCGTAACAGAGAATAGTT TAAATTAGAATCTTAGCTTTGGGTGCTAATGGTGGAGTTAAAGACTTTTTCTCTGACCAT4: GGTATTGGGCACCCGTAAGGAGAAGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT5: GGTATTGGGCACCCGTAAGGGGAAGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT6: GGTATTGGGCACCCGTAAGAAGAAGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT7: GGTATTGGGCACCCGTAAAGAGAAGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT8: GGTATTGGGCACCCGTAAGCAGAAGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT9: GGTATTGGGCACCCGTAAGGAAAAGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT10: GGTATTGGGCACCCGTAAGGATTTGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT11: GGTATTGGGCACCCGTAAGGACCCGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT12: GGTATTGGGCACCCGTAAGGAGAAAAAGAA GGTTTAACTTTAAGACCCTTAAGTGT13: GGTATTGGGCACCCGTAAGGAGAAGCGGAA GGTTTAACTTTAAGACCCTTAAGTGT14: GGTATTGGGCACCCGTAAGGAGAATTTGAA GGTTTAACTTTAAGACCCTTAAGTGT15: GGTATTGGGCACCCGTAAGGAGAACCCGAA GGTTTAACTTTAAGACCCTTAAGTGT16: GGTATTGGGCACCCGTAAGGAGAAGAAAAA GGTTTAACTTTAAGACCCTTAAGTGT17: GGTATTGGGCACCCGTAAGGAGAAGAATTT GGTTTAACTTTAAGACCCTTAAGTGT18: GGTATTGGGCACCCGTAAGGAGAAGAACCC GGTTTAACTTTAAGACCCTTAAGTGT19: GGTATTGGGCACCCGTAAGGAGTAGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT20: GGTATTGGGCACCCGTAAGGAGTAGTAGAA GGTTTAACTTTAAGACCCTTAAGTGT21: GGTATTGGGCACCCGTAAGGAGTTGAAGAA GGTTTAACTTTAAGACCCTTAAGTGT22: GGTATTGGGCACCCGTAAGCAGAACCTTAA GGTTTAACTTTAAGACCCTTAAGTGT23: GGTATTGGGCACCCGTAACAGGAACCTTAA GGTTTAACTTTAAGACCCTTAAGTGT24: GGTTAATACGACTCACTATAGGAGAACCTTAAGGTTTAACTTTAAGACCCTTAAGTGT25: GGTTAATACGACTCACTATAGGGGAACCTTAAGGTTTAACTTTAAGACCCTTAAGTGT26: GGTTAATACGACTCACTATAGCAGAACCTTAAGGTTTAACTTTAAGACCCTTAAGTGT27: GGTTAATACGACTCACTATACAGGAACCTTAAGGTTTAACTTTAAGACCCTTAAGTGT28: GGTTAATACGACTCACTATAGGAGAAGAAGAAGGTTTAACTTTAAGACCCTTAAGTGT29: TCCATTGGGCACCCGTAAGCAGGGAGGACG ATGCGGGCCTTCGTTTGTTTCGTCCACAGACGACTCGCCCGAT32: GGTATTGGGCACCCGTAAUGAGAACCTTAA GGTTTAACTTTAAGACCCTTAAGTGT33: ATTGGGCACCCGTAAGGGAGGACGATGCGGGCCTTCGTTTGTTTCGTCCACAGACGACTCGCCCGADNA templates were constructed by annealing the complementary synthesized oligonucleotides listed below. Only the non-template strands are shown, listed 5′-3′, with the promoters shown in bold and the nucleotides corresponding to residues 1–12 of the RNA products underlined.ATTGGGCACCCGTAAGGG-3′) inserted between the BamHI and XbaI sites  prior to use in transcription assays.Plasmid pUC19 with a single Syn5 promoter and three guanosine residues  contained 40 mM Tris-HCl pH 8.0, 2 mM spermidine, 20 mM DTT, 20 mM MgCl2 , 4 mM of each of the 4 rNTPs , 1.5 U/μl RNaseOUTTM recombinant ribonuclease inhibitor, 0.006 U/μl E. coli inorganic pyrophosphatase, DNA template  or 20 nM linearized 2700 bp plasmid (∼35 ng/μl) and RNA polymerase  from Epicentre). Reaction mixtures were incubated at 37°C for 4 h . Samples . We speculated that since cyanophage Syn5 is likely more ancient evolutionarily than bacteriophage T7, its enzymes may have more relaxed specificity for substrates. We initially examined the ability of wild-type Syn5 RNA polymerase to incorporate 2′-F-dNMPs into RNA. Syn5 RNA polymerase exhibits dramatically different abilities to incorporate each of the four different 2′-F-dNMPs into three different DNA templates that encode a 37 nt RNA, a 32 nt RNA and a tRNA Figure . In geneTo further test our hypothesis, we constructed another template (T4) that is the same as T1 except that C7C8U9U10 (numbers represent the position of the nucleotide in RNA counting from the 5′-end) was replaced by G7A8A9G10. We examined the ability of Syn5 RNA polymerase to initiate transcription on this template in the presence of 2′-F-dNTPs Figure . TemplatWhen comparing T1 and T4 as templates for run-off transcription with Syn5 RNA polymerase, it is clear that not only the incorporation of 2′-F-dCMP and 2′-F-dUMP, but also the overall yield of transcripts in the absence of any analogs, are dramatically different. When C7C8U9U10 in T1 is replaced by G7A8A9G10 in T4, the yield increases 10-fold Figure . In follThe template region corresponding to nts 1–3 in the RNA is critical for transcription efficiency by T7 RNA polymerase . When seFor template sequences corresponding to the regions 4–6 and 7–9 of the transcript, we found that a consecutive stretch of three A's or U's in either of these regions of the transcript is very inhibitory to Syn5 RNA polymerase Figure . PreviouThe plasmid template we used in our previous work (T30) was derived from plasmid pUC19 and encodes for an RNA transcript that starts with GGGUCUAGA . Based oWe have previously shown that transcription by Syn5 RNA polymerase that starts with U is very inefficient using 0.2 mM UTP . IncreasReplacement of C7C8U9U10 by G7A8A9G10 increases the yield of transcripts produced by Syn5 RNA polymerase by a factor of 10 . On this template, 2′-F-dCTP and 2′-F-dUTP inhibit the amount of transcripts produced by T7 RNA polymerase, at least by a factor of 10  are not transcribed efficiently by Syn5 RNA polymerase in the presence of 2′-F-dCTP and 2′-F-dUTP using the standard conditions described above. We varied reaction conditions in order to optimize transcription on these templates. Manganese ions decrease the substrate discrimination for many polymerases . T7 RNA 0–2.5 mM , 10-foldith Mg2+ . A mixtuessfully ,24 to pressfully . Presuma2+ is 100 times the concentration found in E. coli, the natural host for bacteriophage T7  in the presence of a high concentration of Mgr Figure . For exar Figure , lane 7,r Figure , lane 8.r Figure . We analWe examined the ability of the two altered Syn5 RNA polymerases to synthesize transcripts containing 2′-F-dCMP and 2′-F-dUMP. Syn5-Y574F RNA polymerase behaves similar to wild-type Syn5 RNA polymerase with regard to the ability to incorporate 2′-F-dCMP and 2′-F-dUMP , wild-type Syn5 RNA polymerase efficiently incorporates 2′-F-dCMP and 2′-F-dUMP Figure , lane 142+ alone; II. wild-type Syn5 RNA polymerase with a mixture of Mg2+ and Mn2+; and III. Syn5-Y564F RNA polymerase with Mg2+ alone) for their efficiency in transcribing different templates . With Mg2+, Mn2+ and wild-type Syn5 RNA polymerase, all four rNMPs can be substituted with 2′-F-dNMPs at a yield of ∼0.1 μg/μl reaction. The use of wild-type Syn5 RNA polymerase with just Mg2+ ions is effective only when the small RNA product has no U and one C in the first nine nucleotides of the transcript  with 2′-F-dCMP and 2′-F-dUMP substitutions as it does for wild-type enzyme  with 2′-F-dCMP and 2′-F-dUMP substitutions is significantly improved compared to that with Mg2+ only .We tested the effect of Mne Figure  at all cFinally we compared the Syn5-Y564F RNA polymerase to T7-Y639F RNA polymerase, the standard tool for synthesis of 2′-F RNA (2′-F DNA), with various initial sequences in the template (Figure Supplementary Data are available at NAR Online.


Escherichia coli (E. coli) host for protein synthesis, had remained enigmatic, due to the absence of structural information about Qβ replicase. In the last five years, the crystal structures of the core Qβ replicase, consisting of the β-subunit, EF-Tu and Ts, and those of the core Qβ replicase representing RNA polymerization, have been reported. Recently, the structure of Qβ replicase comprising the β-subunit, EF-Tu, EF-Ts and the N-terminal half of S1, which is capable of initiating Qβ RNA replication, has also been reported. In this review, based on the structures of Qβ replicase, we describe our current understanding of the alternative functions of the host translational elongation factors and ribosomal protein S1 in Qβ replicase as replication factors, beyond their established functions in protein synthesis.Qβ replicase is a unique RNA polymerase complex, comprising Qβ virus-encoded RNA-dependent RNA polymerase  and three host-derived factors: translational elongation factor (EF) -Tu, EF-Ts and ribosomal protein S1. For almost fifty years, since the isolation of Qβ replicase, there have been several unsolved, important questions about the mechanism of RNA polymerization by Qβ replicase. Especially, the detailed functions of the host factors, EF-Tu, EF-Ts, and S1, in Qβ replicase, which are all essential in the  Escherichia coli (E. coli) and replicates by transcribing its genomic RNA with Qβ replicase ,6766,67]-subunit a,c. ThisN-terminal half of S1, containing OB1-3, is sufficient for the efficient release of the product RNA from the template RNA in a single stranded form at the terminal stage [N-terminal half of S1 is mobile and would be capable of pivotal rotation, using the α helix between OB2 and OB3 as a swing arm. Therefore, the OB3 domain in S1 also acts as a termination factor, by binding to the growing RNA and preventing the template and growing RNAs from forming double stranded RNA (Recent biochemical studies also suggested that the al stage . The OB3nded RNA c. At preN-terminal OB-fold domains [N-terminal half of S1 is required and sufficient for the initiation of mRNA translation [Taken together, S1 in Qβ replicase can act as a replication initiation factor as well as a termination factor. In ribosomes, S1 is anchored onto the 30S ribosome via its two  domains ,20, and Replication and transcription of viral RNA in host cells rely on the host-derived factors, although the catalytic subunits, RdRps, for RNA synthesis are derived from the viral RNA. In some RNA viruses from eubacteria, plant and animal origins, the viral RdRps form a complex with the host-derived translational factors . The RdRIn this review, we have described recent reports leading toward an understanding of RNA polymerization by Qβ replicase. In particular, the alternative functions of the host translation factors in Qβ replicase, beyond their functions in protein synthesis, were presented based on the recent crystallographic analysis of Qβ replicase as well as biochemical studies.N-terminal half of S1 also revealed that S1 is anchored to the β-subunit of the core Qβ replicase via its two N-terminal OB-folds, while the third, mobile OB-fold is important for the recognition of Qβ RNA, the efficient initiation of Qβ RNA, and termination (N-terminal two OB-folds, and the third OB-fold is required for translation initiation. Structural studies of the core Qβ replicase representing RNA polymerization revealed that domains 2 and 3 of EF-Tu are important for the separation of the double strand RNA between the template and growing RNAs, for efficient and processive RNA polymerization . Togethemination c. S1 intE. coli. Thus, E. coli would not be tolerant to mutations in the functional domains of these translation factors. Qβ virus might have evolved to employ a smart strategy to recruit these essential host factors and utilize their functionally important domains for its propagation in the host cells.The translational elongation factors EF-Tu and EF-Ts and the ribosomal protein S1 are all essential for protein synthesis in Alternatively, these translational factors might have been original cofactors required for RNA replication, and the modern translational apparatus might have borrowed these replication factors for protein synthesis ,75. Tran


This process can generate long non-coding RNAs (lncRNAs), one of the most diverse classes of cellular transcripts, which have demonstrated multifunctional roles in fundamental biological processes, including embryonic pluripotency, differentiation and development. Antisense lncRNAs have been shown to control nearly every level of gene regulation—pretranscriptional, transcriptional and posttranscriptional—through DNA–RNA, RNA–RNA or protein–RNA interactions. This review is centered on functional studies of antisense lncRNA-mediated regulation of neighboring gene expression. Specifically, it addresses how these transcripts interact with other biological molecules, nucleic acids and proteins, to regulate gene expression through chromatin remodeling at the pretranscriptional level and modulation of transcriptional and post-transcriptional processes by altering the sense mRNA structure or the cellular compartmental distribution, either in the nucleus or the cytoplasm.Antisense transcription, considered until recently as transcriptional noise, is a very common phenomenon in human and eukaryotic transcriptomes, operating in two ways based on whether the antisense RNA acts in  Additioant loci . Within ant loci ,4. Moreoi.e., pretranscriptional, transcriptional or posttranscriptional.The focus of this article is centered on functional studies of antisense lncRNA-mediated regulation of neighboring gene expression in mammals, especially humans, with particular emphasis on the interaction mechanisms and types of regulation, cis or in trans. In cis, the antisense RNA interacts with a gene transcribed from the same DNA region, whereas in trans, the interaction is with genes located at distant loci or even at other chromosomes [Antisense transcription is defined as transcription from the opposite strand of a protein-coding gene or a sense strand-derived RNA . It is aomosomes ,14.Cis antisense transcription can be further categorized according to the proximity between the sense and antisense partners in the genome . ncRNAs include several types of RNA, exemplified by transfer RNAs (tRNAs), ribosomal RNAs (rRNAs) and small nuclear RNAs (snRNAs), with very well defined function in many cellular processes ,19,20,21 et al. identified lncRNAs derived from excised introns, flanked at both ends by intronic small nucleolar RNA sequences (sno-lncRNAs), which are specifically expressed in pluripotent cells. The most abundant sno-lncRNAs, from chromosomal region 15q11–q13, interacted with alternative splicing regulator FOX2 (feminizing locus on X) conferring changes in FOX2-dependent splicing, with a limited cis effect on the 15q11–q13 locus, [Although most lncRNAs share similarities with mRNAs regarding transcript processing, the 5' cap structure and 3' poly(A) tail, recently identified lncRNAs highlighted alternative processing mechanisms, for example capping by small nucleolar RNAs (snoRNAs) at both ends or forming circular RNA structures. Classes of lncRNAs that lack a poly(A) tail include: eRNAs (enhancer RNAs); sno-lncRNAs (snoRNA-related lncRNAs); circRNAs (circular RNAs); and ciRNAs (circular intronic RNAs) . Yin et 3 locus, . Moreove3 locus, . Another3 locus, ,29, or d3 locus, . circRNA3 locus, ,29. On t3 locus, .The recent research emphasis on lncRNAs has demonstrated multifunctional roles in fundamental biological processes, including embryonic pluripotency, differentiation and development ,32. DysrMEG3) lncRNA has also been correlated with gliomas, but in contrast to H19, the MEG3 levels are markedly decreased in gliomas, while its overexpression inhibits cell proliferation and promotes apoptosis in vitro [The H19 lncRNA has been characterized as an oncogene in hepatocellular and bladder carcinoma, as well as in colon and breast cancer. More recently, increased H19 levels have been found to be associated with high grade gliomas, and H19 depletion inhibits the invasion of glioma cells ,42. The in vitro ,44.According to a study using full-length cDNA datasets from human and mouse, lncRNAs may originate from various genomic positions, but predominantly from the vicinity of protein-coding genes. This suggests that transcription of certain lncRNAs may depend on the same promoter regions as the nearby protein-coding genes .Bioinformatics analysis is indicative of structural conformations of lncRNAs that may be biologically relevant. For example, the function of the MEG3 and SRA1 lncRNAs, as a tumor suppressor and a hormone receptor coactivator, respectively, is apparently maintained through interactions between distinct secondary structural elements ,46.Compared with coding transcripts, most antisense lncRNAs are expressed at 10-fold lower levels on average, and their expression in different tissues and cell types has generally been found to be more cell type specific ,32. A biAntisense lncRNAs are functionally very diverse ,39. TheyAntisense lncRNAs have been found to act at nearly every level of gene regulation ,31,55: pcis and by bridging epigenetic effectors and regulatory complexes at specific genomic loci [Thousands of lncRNAs have emerged as key molecular players in epigenetic processes through their association with chromatin modifiers . Specifimic loci .de novo DNA methylation, the Polycomb repressive complex PRC2, which elicits histone H3 lysine 27 trimethylation (H3K27me3), or G9a/GLP methyltransferases targeting histone H3 lysine 9 (H3K9), which correlate with transcriptional repression [Sequence complementarity can establish complex configurations, such as RNA–DNA duplexes and triplexes. These direct RNA–DNA A interacpression ,46,57.There is currently limited evidence for widespread direct interactions between lncRNAs and DNA through the formation of RNA:DNA hybrids or triplex structures that are based on sequence complementarity . HoweverRASSF1 gene locus, maps upstream of the RASSF1C isoform and overlaps most of the of RASSF1 isoforms. This transcript is expressed in several cell lines and tissues, and its interaction with genomic DNA, forming an RNA/DNA hybrid, leads to downregulation of the sense gene at the pretranscriptional level. ANRASSF1 recruits PRC2 to the RASSF1A promoter, then PRC2 induces the accumulation of the repressive mark H3K27me3, which confers a specific reduction in the RASSF1A transcriptional activity. Current research has not detected any effect of ANRASSF1 on the expression of the RASSF1C isoform, which is under the control of a different promoter, or the levels of H3K27me3 and PRC2 recruitment at the RASSF1C promoter and at the promoters of neighboring genes in the RASSF1 locus, demonstrating the selectivity of its regulatory mechanism [RASSF1A  is one of eight different transcripts generated by alternative splicing/alternative promoter usage. It encodes a protein similar to the RAS effector proteins, with multiple modulatory functions at apoptotic and cell cycle checkpoint pathways. Additionally, its inactivation is implicated in the development of many human cancers . ANRASSFechanism .rRNA genes by recruiting chromatin-modifying enzymes to the rDNA promoter. It requires for its function a heterogeneous population of 150–300-nucleotide RNA, termed pRNA (promoter-associated RNA), in an activity that coordinates several macromolecular complexes to modify histones and methylate DNA [rRNA genes, are non-coding RNAs in sense or antisense orientation that are complementary to the rDNA promoter, with numerous potential functions, including promoter-targeted RNA-induced transcriptional gene regulation via de novo CpG methylation of rRNA genes [Chromatin remodeling complex NoRC silences a subset of late DNA . pRNA trNA genes ,61.Specifically, these non-coding RNAs interact with complementary sequences within the rDNA promoter forming a RNA–DNA–DNA triplex  that is ANRIL (antisense non-coding RNA in the INK4 locus) spans a region of 126.3 kb and is transcribed in the antisense orientation of the INK4b-ARF-INK4a gene cluster, which plays a central role in cell cycle inhibition, senescence and stress-induced apoptosis [INK4b-ARF-INK4a locus is located on the human chromosome 9p21 and encodes three tumor-suppressor proteins, p15INK4b, p14ARF and p16INK4a [ANRIL overlaps with the two exons of p15INK4b and maintains the silencing state of this gene. The 5' end of the ANRIL first exon is located −300 bp upstream of the transcription start site (TSS) of the p14ARF gene, suggesting that these two genes may share a bidirectional promoter [ANRIL was shown to be involved in epigenetic regulation of the INK4b-ARF-INK4A locus by recruiting Polycomb repressive complex-1 (PRC1) and -2 (PRC2) to form heterochromatin surrounding the INK4b-ARF-INK4a locus, leading to repression of gene expression [ANRIL expression is regulated by ATM-E2F1 signaling, and alteration in its structure and/or expression mediates the susceptibility to a variety of chronic diseases and cancer predisposition [poptosis . This anpoptosis ,78,79. Tp16INK4a ,80. The promoter ,63. ANRIpression . The naspression ,62,76. Aposition ,82.Sense RNA and antisense lncRNA transcripts can hybridize and form RNA duplexes B by virt et al. found that an antisense lncRNA transcribed from the opposite strand of the mouse Uchl1  gene in a head-to-head orientation can activate polysomes for increased translation of Uchl1 under certain stress conditions [Uchl1 gene, including the AUG codon, through RNA–RNA interactions between the sense and antisense transcripts , with 104 nucleotides of full complementarity to exon 6 of the human BACE1 mRNA, which regulates protein expression of the sense gene in the brain of an AD mouse model [Beta-secretase 1 or β-site amyloid precursor protein cleaving enzyme 1 (BACE1) is a protease that participates in the sequential cleavage of amyloid precursor protein, a crucial enzyme in Alzheimer’s disease (AD) pathophysiology. Faghihise model . The BACse model . The chase model ,66.PTEN is a tumor-suppressor gene in chromosome 10q23 that is mutated in a large number of human cancers [trans through an intricate mechanism involving a pseudogene, known as PTENpg1, located in 9p23, and a non-coding RNA antisense to this pseudogene, which is termed PTENpg1as [ cancers  and is pTENpg1as .PTEN promoter and functions as an epigenetic modulator by the recruitment of DNMT3a and enhancer of zeste. On the other hand, PTENpg1as beta forms an RNA–RNA duplex with the PTENpg1 transcript, altering the subcellular distribution and increasing PTENpg1 RNA stability. This enhances the miRNA sponge-like properties of PTENpg1 and, ultimately, its capacity to posttranscriptionally regulate PTEN [The PTENpg1 sense RNA lacks a poly(A) tail, and its stability and export to the cytoplasm is facilitated by interactions with PTENpg1as. There are three PTENpg1as variants: alpha, beta and unspliced. Alpha and beta are spliced, polyadenylated isoforms found predominately in the cytoplasm, whereas the unspliced isoform is exclusively found in the nucleus . PTENpg1ate PTEN ,67.lncRNAs are mainly associated with proteins due to the possession of distinct protein-binding domains. Such complexes may have an impact on transcription, acting as key regulators of gene expression. lncRNAs can function as molecular decoys, with sponge-like properties, taking away proteins from a specific location or recruiting proteins to activate or inhibit processes involved at any level of gene regulation. Miscellaneous RNA–protein interactions can support the assembly of protein complexes (scaffold), which link the factors together in order to generate brand new functions that may impact the process of transcription ,68, eithcis and exerts transcriptional repression on the entire X chromosome through DNA and histone methylation, global histone hypoacetylation and the Polycomb repressive complex, PRC2 [cis along the X chromosome [In mammals, X inactivation avoids the dosage differences of X-linked genes between males and females, as one of the two copies of the X chromosome present in female cells is inactivated by Xist . This geex, PRC2 . This lnromosome ,70.apolipoprotein A1 (APOA1), a gene with a specific role in lipid metabolism, expresses a long non-coding antisense transcript, APOA1-AS, which modulates the expression of not only APOA1, but also multiple neighboring genes, in vitro and in vivo, acting as a modular scaffold and negative transcriptional regulator. This antisense transcript has two exons and spans two neighboring genes, APOA1 and SIK3 . APOA1-AS acts via recruitment of H3K27me3 marks along the promoter regions of APOA1, APOA4 and APOC3, facilitating the interaction of the histone-modifying enzymes, LSD1 and SUZ12, and the PRC2 complex [Recent studies have found that  complex .GLI1 (glioma-associated oncogene 1) encodes a transcription factor that is a marker of Hedgehog signaling activation, and its increased expression is associated with a wide variety of human cancers [GLI1 gene and tail-to-tail with the INHBE gene. Its gene repressive effects via H3K27me3 appear to be more pronounced on the GLI1 than the INHBE gene [An additional antisense lncRNA with a scaffold-type regulatory impact is GLI1AS, which generates repressive chromatin marks at its locus, acting as an epigenetic modifier that negatively regulates the expression of neighboring genes . Among t cancers . GLI1AS HBE gene .The accumulated evidence suggests that the complexity of organisms is associated with an intricate network of gene regulatory processes. Consequent to a better understanding of these mechanisms and their molecular contexts is the growing research focus in this direction.Long non-coding RNAs with an antisense orientation toward known protein-coding genes are demonstrated to significantly contribute to the repertoire of regulatory mechanisms that are used by mammalian cells to modulate gene expression. These may depend on base pair complementarity or on their ability to bind to proteins, thereby serving as platforms and/or adaptors for diverse DNA–RNA, RNA–RNA or RNA–protein interactions.Admittedly, our understanding of the mechanistic details of the biological function of antisense long non-coding RNAs is still in the early stages, yet it is clear that they can act at nearly all levels of gene regulation, including transcription, mRNA processing and translation.


In the Funding section, the grant from National Science and Technology Major Project (2013ZX10002008) is omitted.The correct funding statement should read:This work was supported in part by grants from UNC UCRF innovation grant, from NIH: UNC SPORE grants; AI076142, AA018009 (LS), and UNC Lineberger Comprehensive Cancer Center and UNC Infectious Disease Pathogenesis Postdoctoral Training Grants (MTB); from Chinese MOST 2009CB522507, MOH 2012ZX10004503-007 (LZ) and from National Science and Technology Major Project 2013ZX10002008. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


The extent, regulation and enzymatic basis of RNA editing by cytidine deamination are incompletely understood. Here we show that transcripts of hundreds of genes undergo site-specific C>U RNA editing in macrophages during M1 polarization and in monocytes in response to hypoxia and interferons. This editing alters the amino acid sequences for scores of proteins, including many that are involved in pathogenesis of viral diseases. APOBEC3A, which is known to deaminate cytidines of single-stranded DNA and to inhibit viruses and retrotransposons, mediates this RNA editing. Amino acid residues of APOBEC3A that are known to be required for its DNA deamination and anti-retrotransposition activities were also found to affect its RNA deamination activity. Our study demonstrates the cellular RNA editing activity of a member of the APOBEC3 family of innate restriction factors and expands the understanding of C>U RNA editing in mammals. Aberrant RNA editing is linked to a range of neuropsychiatric and chronic diseases. Here Sharma et al. show that APOBEC3A can function as an RNA editing protein in response to physiological stimuli, significantly expanding our understanding of RNA editing and the role this may play in diseases. RNA editing is a co- or posttranscriptional process that alters transcript sequences without any change in the encoding DNA sequenceAPOBEC genes . APOBEC3 proteins can deaminate cytidines in single-stranded (ss) DNA, and although the APOBEC proteins bind RNAAPOB) mRNA as its physiological targetRNA-dependent ADAR1, ADAR2 and ADAR3 adenosine deaminases, and APOBEC1 cytidine deaminase (CDA) are the only known RNA-editing enzymes in mammals. RNA sequencing studies suggest that A>I RNA editing affects hundreds of thousands of sites, although most of A>I RNA edits occur at a low level and in non-coding intronic and untranslated regions, especially in the context of specific sequences such as Alu elements23SDHB) gene in normal peripheral blood mononuclear cells (PBMCs) of humansSDHB encodes the iron-sulfur subunit of mitochondrial respiratory complex II, which also participates in oxygen sensing and response1213SDH genes are associated with both hereditary and non-hereditary paraganglioma and pheochromocytoma, renal carcinoma and gastrointestinal stromal tumours2) enhances the C>U editing of SDHB RNA at c.136 in monocytes, with an editing level of ∼18% observed for monocyte-enriched PBMCs (MEPs) after 48 h of hypoxiaSDHB may therefore represent a hypoxia-adaptive mechanism that may have implications for the pathogenesis of chronic inflammatory diseases.We have previously observed C>U editing of cytidine at c.136 (NCBI reference sequence NM_003000), which generates a nonsense codon (R46X), in ∼6% of transcripts of the succinate dehydrogenase B , we analyse their whole transcriptome RNA sequences. We show that transcripts of hundreds of genes including those implicated in viral pathogenesis and Alzheimer's disease are targets of editing in monocytes and macrophages. Such editing is regulated by oxygen, interferons (IFNs) and also during macrophage polarization. Most importantly, we demonstrate that APOBEC3A, which belongs to the APOBEC3 family of CDAs, is an RNA-editing enzyme. These findings significantly expand our understanding of C>U RNA editing and open new avenues of inquiry on the role of SDHB c.136C>U RNA editing observed in monocytes. We therefore examined whether IFNs induce SDHB c.136C>U RNA editing. As shown in the left panel of −1) or IFNγ (200 U ml−1) for 24 h induced SDHB c.136C>U RNA editing in MEPs, both in normoxia and hypoxia under 1% O2 . The editing level in normoxic or hypoxic MEPs was increased ∼6-fold by IFN1 and ∼3-fold by IFNγ, suggesting that the induction of RNA editing with IFN1 was higher than with IFNγ . An additive effect of IFNs and hypoxia on SDHB c.136C>U RNA editing was observed and this was confirmed in an independent experiment in which matched MEPs of seven individuals were cultured under normoxia or hypoxia with 0, 300 or 1,500 U ml−1 IFN1 for 24 h. Editing level in cells treated with both hypoxia and IFN1 was higher than in cells treated with only hypoxia or IFN1 .Similar to hypoxia, an IFN-rich microenvironment is another factor that monocytes are exposed to during inflammation. IFNs also upregulate expression of APOBEC3 CDAsSDHB c.136C>U RNA editing in basal unpolarized (M0), M1 and M2 macrophages. M0 cells were derived in vitro from CD14+ peripheral blood monocytes and matched M1 and M2 macrophages were generated from the M0 cells by treatment with IFNγ and lipopolysaccharides (LPS) and interleukin-4, respectively. The SDHB RNA editing was found to be absent in M0 macrophages but occurred at an average level of ∼27% in M1 cells (IFNγ is an inducer of M1 (pro-inflammatory) polarization of macrophages, which are derived from monocyte precursors. We therefore examined and compared SDHB in MEPs, we performed RNA sequencing of matched normoxic and hypoxic MEPs of three healthy individuals. We also examined whole transcriptome RNA sequencing data obtained by Beyer et al.in vitro from peripheral blood monocytes of three individuals, to determine whether M1 macrophage polarization differentially affects editing of other RNAs besides SDHB. Such comparison of whole transcriptomes of paired samples to identify RNA editing is less likely to falsely identify sequencing and mapping artefacts or genome sequence variations as RNA-editing events.To investigate whether hypoxia affects editing of RNAs other than q-value of <0.05 and a higher intra-group mean variation level of ⩾5%. The type of RNA editing at a genome position was surmised from the base variation and the gene-coding chromosome strand at the position. The candidate RNA-editing sites were filtered to remove probable false positives. Filtering criteria included identification of the site with a separate read-mapping software and location of the site within a known RefSeq gene  and 25 (12%) of the 206 C>U sites for which editing was upregulated by hypoxia. In normoxic MEPs, the levels were <1% and <5%, respectively, for 162 (79%) and 202 (98%) of the 206 sites . AverageCG sequence motif (edited site underlined), with CAUC and its CACC, CCUC, CUUC and UAUC 1-nucleotide (nt) variants present for ∼79% and 85% of the editing sites of MEPs and macrophages, respectively  than the sum of those with IFN1 (mean=10.8%) or hypoxia (mean=14.5%) alone. Editing levels did not significantly differ between hypoxia and IFN1 treatments . Sanger sequencing of PCR-amplified genomic DNA fragments of hypoxia- and IFN1-treated MEPs did not reveal C>T nucleotide variation at the editing site for any of the 23 genes that were examined (Thirty-three non-synonymous C>U RNA-editing sites (in 33 genes) that were identified in the analysis of RNA sequencing data  were choSDHB  was alsoSDHB ; the ediexamined .TMEM131, 95%; SDHB, 90%; PCGF3, 90%; NBN, 84%; and RNH1, 83%). In lymphocytes, RNA editing was seen for only two of the 34 genes , suggesting that most of the differential C>U RNA editing in MEPs occurred in the monocytes.MEPs contain both monocytes and lymphocytes. To determine the RNA-editing levels of the 31 experimentally validated genes in these individual cell types, Sanger sequencing of RT–PCR products of monocyte and lymphocyte isolates  of hypoxSDHB  and SIN3A , the effect of hypoxia-induced C>U RNA editing on protein level was examined by immunoblotting assays of whole-cell lysates of monocytes isolated from normoxic or hypoxic MEPs of three donors in a separate experiment. As shown in SDHB and SIN3A RNA levels by an average of 4.7- and 1.6-fold in these three CD14+ monocyte samples, as tested by quantitative RT–PCR . Although this reduction could be at the transcriptional level, it could also be a result of posttranscriptional processes such as nonsense-mediated decay and microRNA targeting of the transcripts because of the sequence change resulting from their editing.For two of the transcripts for which the editing results in a nonsense codon change, SDHB c.136C>U RNA editing in monocytes and macrophages. CDA and the seven APOBEC3 genes were identified as expressed in RNA sequencing data of MEPs and only CDA expression was upregulated by hypoxia  were upregulated in M1 compared with M2 macrophages, with APOBEC3A upregulation being the highest (∼67-fold), whereas AID and APOBEC1, 2 and 3H were not expressed in macrophages  was associated with  hypoxia . Expressrophages . Upregulnormoxia . ExaminaSDHB c.136C>U RNA editing, we evaluated RNA sequencing data in the Cancer Genome Atlas (TCGA) for three randomly chosen cancers, primary head and neck squamous cell carcinoma, lung adenocarcinoma and secondary skin cutaneous melanoma. As tumours contain immune cells and can have hypoxic regions, we hypothesized that some degree of SDHB c.136C>U variation may be noticeable in the RNA sequences of the TCGA samples. Somatic SDHB c.136C>T mutation has not been identified in any TCGA sample for these cancers  at c.136, but at no other site, in 30.2%, 26.4% and 9.6% of 298 primary head and neck squamous cell carcinoma, 220 lung adenocarcinoma and 187 secondary skin cutaneous melanoma cases that were examined, respectively . Comparison of gene expression between the editing-positive and -negative samples showed that APOBEC3A was the only CDA gene whose expression was upregulated in the editing-positive samples in all three cancers. Consistent differential expression of common hypoxia- or monocyte/macrophage-associated genes across all three cancers between editing-negative and -positive samples was not seen  but not IFN1 (600 U ml−1) mildly enhanced this editing . Sanger sequencing of PCR-amplified genomic DNA fragments of transfectants did not reveal C>T nucleotide variation at the editing site for any of the 23 genes that were examined . To test whether RNA editing and retrotransposition-suppressing functions of APOBEC3A are linked, we tested the effect of mutations on SDHB RNA in vitro, an SDHB ORF RNA of ∼1.1 kb with an artificial sequence at its 5′-end was incubated with whole-cell lysates of 293T transfectants. Editing of the RNA at c.136 was quantified by allele-specific RT–PCR with a 5′-primer that was specific to the artificial sequence and using the same 3′-primers as describedAPOBEC3A but not a control transfectant induced C>U editing of the exogenous SDHB RNA at c.136 in a time- and dose-dependent manner, and this activity was not seen with the heat-inactivated lysate  too was deaminated at c.136 by the recombinant APOBEC3A protein. However, cytidine deamination of the ssDNA was also observed at other positions (c.117 and c.132); the deaminated residue at both positions occurs in a TC sequence context  and ITGB2 (CD18), which encode an integrin that is exploited by various viruses for cell entryUBE2J1, which targets major histocompatibility complex class I heavy chains for endoplasmic reticulum-associated degradation, a pathway used by cytomegalovirusesVIM encodes vimentin with which various viruses physically interact for their survivalXPO1, which encodes a cargo protein that plays a role in exporting the unspliced HIV-1 RNAAP2A1, which encodes a subunit of clathrin-associated adaptor complex 2 that is involved in infectious entry of various virusesSIN3A, which encodes a transcriptional co-repressor that is incorporated in HIV-1 virions as SIN3A-HDAC1 complex that contributes to efficient reverse transcription in host cellsNon-synonymously C>U RNA-edited genes identified in this study may represent factors that mediate the anti-viral and -retrotransposition function of APOBEC3A. Several of the edited genes have already been associated with viral pathogenesis. Examples include C or its 1-nt. variant motifs that are flanked by palindromic sequences. It thus appears that previous studies failed to observe the RNA-editing activity of APOBEC3A, which is known to bind RNAAPOBEC3A is believed to deaminate foreign but not host genomic DNA in primary cells, and previous studies have demonstrated the deamination activity of the enzyme against ssDNA but not RNA26in vivo. How hypoxia activates C>U RNA editing is currently unknown. Although upregulation of APOBEC3A expression may underlie the activation of C>U RNA editing by IFNsAPOBEC3A expression in MEPs is downregulated by hypoxia  in 1 or 2 ml per well of 6- or 12-well standard tissue culture plates under 5% CO2 in RPMI-1640 medium (Mediatech) with 10% FBS, and 100 U ml−1 penicillin and 100 μg ml−1 streptomycin (Mediatech). Monocytes and lymphocytes were isolated from MEPs based on light scattering and binding of a phycoerythrin-conjugated mouse anti-CD14 antibody  by flow cytometry on a FACS Aria II instrument with FACS Diva 6.0 software . PBMCs of anonymous platelet donors were isolated from peripheral blood in Trima Accel leukoreduction system chambers  after thrombocytapheresis, in accordance with a protocol approved by the institutional review board of Roswell Park Cancer Institute. A density gradient centrifugation method using polysucrose-containing Lymphocyte Separation Medium  was used for PBMC isolation. MEPs were prepared from PBMCs using the well-established cold aggregation methodonocytes . Inductis per ml .6 ml−1 with 50 ng ml−1 recombinant human macrophage colony stimulating factor , 1 × GlutaMAX-I (Life Technologies) and 1 mM sodium pyruvate (Mediatech) to generate M0 macrophages. M0 macrophages were also similarly generated from fresh monocytes isolated from PBMCs by the Percoll-based method. For M1 or M2 macrophage polarization, M0 cells were treated for 2 days with 20 ng ml−1 recombinant human IFNγ (Life Technologies) and 100 ng ml−1Escherichia coli LPS , or 20 ng ml−1 recombinant human interleukin 4 (Life Technologies), respectively. RNA was isolated from cells using the Total RNA Purification Kit from Norgen Biotek .CD14+ monocytes isolated from PBMCs by magnetic sorting and stored frozen in RPMI-1640 with 36% v/v FBS and 10% v/v dimethyl sulfoxide were thawed and cultured for a week at a density of 0.25 × 102, 5% CO2 and 94% N2 in an Xvivo System . Human IFNγ and ‘universal' type I IFN, a hybrid of amino-terminal IFNα-2 and carboxy-terminal IFNα-1, produced in E. coli were obtained from PBL Assay Science  and used at 200 and 300–1,500 U ml−1, respectively. Unless noted otherwise, hypoxia and/or IFN treatments were for 24 h. Differential viability of MEPs after 1-day culture in normoxia versus hypoxia was not observed as evaluated by Trypan blue stain. Transfected 293T cells were subjected to hypoxia and/or IFN treatment 24 h after transfection.For hypoxia, cells were cultured under 1% OIndexed sequencing libraries were generated from RNA, isolated using TRIzol and without DNAse treatment, as per methods and reagents provided with the TruSeq Stranded Total RNA Sample Prep Kit with Ribo-Zero ribosomal RNA reduction chemistry . PCR for library generation employed ten cycles. Electrophoresis of the libraries on Bioanalyzer 2100 instrument  showed highest peaks at 220–240 bp. Paired-end multiplexed sequencing of libraries (three per flow cell lane) to generate reads of 101 b was performed on HiSeq 2000 instrument with TruSeq SBS and PE Cluster v3 Kits (Illumina). CASAVA 1.8.2 software (Illumina) was used for base-calling and de-multiplexing, to obtain the raw RNA sequencing reads for further analyses. RNA sequencing of all six samples of this study was performed in one batch.http://www.ncbi.nlm.nih.gov/sites/books/NBK158900/).Paired-end, 101-b read sequence data generated using TruSeq RNA Sample Preparation Kit on Illumina HiSeq 2000 for paired M1 and M2 macrophages derived from CD14+ monocytes of three donorswww.bioinformatics.babraham.ac.uk/projects/fastqc/). Trimmomatic 0.32 (www.usadellab.org/cms/?page=trimmomatic) was used to trim 12 b from the 5′-end and remove adapter sequences and poor-quality bases from the reads. The Trimmomatic call was invoked with ‘HEADCROP:12 ILLUMINACLIP: TruSeq3-PE-2.fa:2:30:10:6:TRUE LEADING:5 TRAILING:5 SLIDINGWINDOW:4:15 MINLEN:30', to satisfy these criteria, in the following order : (1) remove 12 b from the 5′-end of all reads because of base bias at these positions; (2) remove read segments that matched sequences of adapters and primers used for sequencing library preparation (the TruSeq3-PE-2.fa file provided with Trimmomatic was used); (3) remove leading/trailing bases with Phred33 base quality score <5; (4) using a sliding window of four bases, remove the most 5′-base if the average Phred33 base quality score of the four bases was <15; and (5) completely discard trimmed reads with <30 remaining bases. Pair-mates of a fraction of raw reads were lost following this read processing with Trimmomatic. Processed read data thus had both paired and unpaired reads  in the Illumina iGenomes UCSC hg19 data. The tophat2 command was used with the transcriptome and bowtie2 genome indexes, and the following argument values specified: mate-inner-dist=−50, mate-std-dev=40, max-multihits=1, read-mismatches=3, read-edit-dist=3, no-novel-juncs . The nature of genomic regions that the reads mapped to was assessed using RSeQC. Mapping statistics are provided in Processed reads, both paired and unpaired, were also mapped to the UCSC hg19 human genome assembly with the TopHat2 2.0.10 alignergenome.sph.umich.edu/wiki/BamUtil), pileups were produced from the mapping data (BAM files) with mpileup in SAMtools 0.1.19 (www.htslib.org), with computation of base alignment quality disabled (B), ‘anomalous' reads permitted (A), maximum depth (d) set at 80,000, and aligner-reported read mapping quality (Q) >0 and Phred33 base quality score (q) >19 required.After clipping overlaps of read pair-mates with clipOverlap utility in bamUtil 1.0.10 (www.ncbi.nlm.nih.gov/refseq), or mapped to either exons of >1 RefSeq genes on both chromosome strands, or mapped to only introns of >1 RefSeq genes on both chromosome strands were excluded. Annotation data (BED files) for RefSeq gene introns and exons for the UCSC hg19 genome assembly were obtained on 21 March 2014, using UCSC Genome Browser (genome.ucsc.edu). The inverted β-binomial (IBB) test for multiple paired count dataq-values were calculated from IBB test P-values using the q-value function in the q-value Bioconductor package with these argument values specified: pi0.method=bootstrap, robust. Sites that were further considered had q-value <0.05 and >2-fold difference in either direction for editing level between test and control samples  in analysis of Subread subjunc-aligned RNA-sequencing data, as well as an IBB test P-value <0.05 and >2-fold difference in analysis of TopHat2-aligned RNA-sequencing data. Sites were then filtered if either of their 5′-and 3′-, 29-b-long, flanking genomic sequences, respectively, with either the reference or variant base at the 3′-and 5′-end aligned perfectly with the genome at another location; blat 35 (genome.ucsc.edu) was used for this purpose. Finally, for filtering based on sequencing read strand bias, sites were filtered out if in the Subread subjunc-aligned data the variant base was called from a total across all six samples of more than nine forward RNA sequencing reads but no reverse read, or vice versa, or if the number of forward and reverse reads were significantly different for either the test or control samples . Numbers of sites that were left after and filtered by different steps of the analysis described here are noted in Paired comparison of pileups for the three pairs, from three different human donors, of normoxic and hypoxic MEP, or M2 and M1 macrophage samples was performed to identify genome sites with differential RNA editing in MEPs under hypoxia (test samples) compared with normoxia (control samples), or in M1 macrophages (test) compared with M2 macrophages (control). Python 2.7, R 3.0 and shell scripts were used for the analysis. Sites considered for analysis satisfied all of the following criteria regarding the A/T/G/C base-calling reads that covered them: (1) ⩾20 calls  in both samples of ⩾1 pair and ⩾5 calls in all 6 samples; (2) ⩾50% of calls for the reference human genome base in all test or all control samples; (3) ⩾2 variant (other than the reference base) but identical base calls in ⩾2 test or ⩾2 control samples, with ⩾1 such calls in all test or all control samples, and ≤5 base calls for a different variant in all 6 samples; and, (4) ⩾95% reads with a base call for either the reference or variant nucleotide in all 6 samples . Variation or editing level for sites was calculated as the ratio of variant base-calling- to the sum of variant and reference base-calling-read counts. Sites were then filtered by editing level, requiring: (1) ⩾2.5% in ⩾2 test or ⩾2 control samples; (2) mean ⩾5% for test or control samples; and (3) range/mean ⩾2 across all 6 samples (to reduce subsequent multiple testing). Variant sites with known maximum population prevalence >20% for identical sequence polymorphism , or sites that did not map to a known RefSeq gene (www.openbioinformatics.org/annovar) and ljb23_metalr (22 February 2014), popfreq_max (21 August 2013), RefSeq-based refGene (13 November 2013) and dbSNP 138-based snp138 (13 December 2013) ANNOVAR databases were used to annotate sites with information such as gene features they are located in, frequencies of known C/T genomic DNA polymorphism and effects on amino acid coding. Coding genomic strand sequences flanking the editing sites were extracted from the whole-genome FASTA file for the UCSC hg19 genome assembly (obtained from Illumina iGenomes) with the getfasta utility in bedtools 2.17.0 (github.com/arq5x/bedtools) and these sequences were analysed as transcript RNA sequences. Palindromic sequence context of editing sites was manually examined. RNA folding was predicted with ViennaRNA package 2.1.6 (www.tbi.univie.ac.at/RNA). These annotations are provided in weblogo.threeplusone.com). Gene-set enrichment analyses for biological function, molecular process and PANTHER pathway ontologies were performed with PANTHER 9.0 (www.pantherdb.org/panther). Enrichment of a gene set with at least two genes for an ontology term, in comparison with the reference database for 21,804 genes, was assessed by binomial test and an FDR <5%, calculated from P-values by the Benjamini–Hochberg method, was considered significant.ANNOVAR tool . RNA and whole-exome sequencing data mapped to the hg19 genome assembly (BAM files) were obtained from Cancer Genomics Hub  during February and March, and October 2014, respectively.SDHB gene is coded on the minus chromosome strand). Otherwise, C>U editing level was estimated as the ratio of G to the sum of A and G calls. Information on C/T single-nucleotide polymorphisms in SDHB protein coding sequence was obtained from dbSNP (build 37).Pileups were generated as described above. Editing was deemed indeterminable for a sample if <99% of mapped reads had a base call other than A or G, or there were <200 calls with none for A, or there were <100 calls with only one for A  for normalization with the trimmed mean of APOBEC3A, APOBEC3G, CDA and SDHB cDNAs, with sequences matching NCBI RefSeq sequences NM_145699.2, NM_021822.1, NM_001785.1 and NM_003000.2, respectively, for the generation of C-terminal Myc-DDK-tagged APOBEC3A and untagged APOBEC3G, CDA and SDHB proteins were obtained from OriGene . An inducible bacterial expression construct for APOBEC3A with a C-terminal His6-tag in the pET21 vector was obtained from Dr Jinwoo Ahn . Site-directed mutagenesis of APOBEC3A constructs  vector (Life Technologies) plasmid was used for control transfectants. The pRL-SV40 plasmid for SV40 promoter-driven expression of Renilla luciferase was obtained from Addgene . A LINE-1 plasmidLINE-1 element bearing a CMV promoter-driven firefly luciferase cassette in its 3′-untranslated region was obtained from Dr Judith Levin .Sequence-verified plasmid constructs in pCMV6 vector for cytomegalovirus (CMV) promoter-driven expression of human 293T cells were transfected with plasmid DNA using the liposomal X-tremeGENE 9 DNA reagent  or jetPRIME  reagents as per guidelines provided by the reagent manufacturer. Transfection efficiency with both reagents was 60%–80% as assessed by fluorescent microscopy of cells transfected with the pLemiR plasmid DNA (Open Biosystems) for expression of a red fluorescent protein. Cells were harvested 2 days after transfection.6 cells per ml in 1 ml medium per well of six-well plates were transfected with 100 nM of negative control  or either or equimolar mix of two human APOBEC3A siRNAs  using Lipofectamine RNAiMAX (Life Technologies) as per guidelines supplied by the manufacturer. IFNγ and LPS were added with 1 ml medium to each well, to induce M1 polarization, and cells were harvested a day later.A day before induction of M1 polarization, M0 macrophages at a density of 1 × 10LINE-1 element from a plasmid DNA to the genome is measured in this assay. 293T cells at ∼50% confluence in 12-well tissue culture plates were co-transfected with 0.75 μg of the LINE-1 plasmid, 0.5 μg of pcDNA 3.1(+) or an APOBEC3A expression plasmid, 0.25 μg of pcDNA 3.1(+) and 1 ng of pRL-SV40 plasmid (per well). Transfectants were lysed after 2 days for measurement of their firefly and Renilla luciferase activities using Dual-Luciferase Reporter Assay System . Retrotransposition was quantified as the ratio of firefly and Renilla luciferase activities.Briefly, firefly luciferase expression conditional to the retrotransposition of a human R DNA polymerases  was used in PCR to generate products for Sanger sequencing. For quantitative PCR to assess ACTB, APOBEC3A, APOBEC3B, CDA, SDHB, SIN3A and B2M gene expression, reactions using FastStart Taq DNA polymerase and SYBR Green I dye were performed on a LightCycler 480 System (Roche). Quantification cycle (Cq) values were calculated by the instrument software using the maximum second derivative method and the mean Cq value of duplicate or triplicate PCR reactions was used for analysis. TaqMan Gene Expression Assays from Life Technologies with identification numbers Hs00234140_m1, Hs00171149_m1, Hs00233627_m1 and Hs00267207_m1, or prepared in houseCCL2, CCL19, FCER2, MRC1 and ACTB with PCR performed on a 7900HT instrument (Life Technologies) and Cq values determined with automatic baseline and threshold detection by SDS 2.4 software (Life Technologies).RNA was reverse transcribed with random DNA hexamers and/or oligo-dT primers using material and methods provided with the Transcriptor First Strand cDNA Synthesis (Roche) or High Capacity cDNA Reverse Transcription (Life Technologies) kits. PCR typically employed 35 cycles of amplification and an annealing temperature of 60 °C. PCR oligonucleotide primers  are listed in SDHB c.136C>U RNA-editing level obtained with it against those obtained with allele-specific RT–PCR (Sequencing primers (Integrated DNA Technologies) are listed in c RT–PCR .Whole-cell lysates were prepared using M-PER reagent  with 1 × Halt protease and phosphatase inhibitor cocktail (Thermo Fisher). Reducing and denaturing polyacrylamide gel electrophoresis of 20 μg proteins in Laemmli buffer system was performed on pre-cast, 4%–15% gradient polyacrylamide gels . Proteins were then transferred to polyvinylidene difluoride membrane with a pore-size of 0.2 μm for 7 min at 1.3 A in a Bio-Rad Trans-Blot Turbo apparatus. Membranes were incubated in Tris-buffered 0.15 M NaCl of pH 7.5 with 0.05% v/v TWEEN 20  and 5% w/v dried, non-fat, cow milk  with antibodies at dilutions recommended by their manufacturers. Rabbit polyclonal anti-APOBEC3A  in 10 mM Tris (pH 8.0), 50 mM NaCl, 1 mM dithiothreitol (DTT) and 1 mM EDTA in a volume of 50 μl. The reaction was stopped by adding 40 μg proteinase K (Life Technologies) and incubating it for 20 min at 65 °C. Ten microlitres of 1 N NaOH was added to the reaction, which was then incubated at 37 °C for 15 min. After adding 10 μl of 1 N HCl, the reaction (10 μl) was electrophoresed on a 10% denaturing polyacrylamide gel. Typhoon 9400 Imager  was used to scan the gel in fluorescence mode.The deamination assay described by Byeon E. coli (EMD Millipore) transformed with a bacterial expression construct for C-His6-tagged APOBEC3A and grown in Luria broth at 37 °C were induced for expression of the recombinant protein with 0.3 mM isopropyl β-D-1-thiogalactopyranoside and cultured overnight at 18 °C. Harvested cells were lysed with a French pressure cell  and Ni-NTA His.Bind Resin (EMD Millipore) was used as per manufacturer's instructions to purify APOBEC3A protein from the lysates by affinity chromatography. Isolated protein was concentrated using an Amicon Ultra-4 Centrifugal Filter Unit with Ultracel-3 membrane . The concentrated protein was stored in 25 mM Tris (pH 8.0) with 50 mM NaCl, 1 mM DTT, 5% v/v glycerol and 0.02% w/v sodium azide. Staining with Coomassie blue of protein preparation electrophoresed on a denaturing polyacrylamide gel indicated that it had APOBEC3A at >90% purity.Rosetta 2(DE3)pLysS 4-(2-hydroxyethyl)-1-piperazine-ethane-sulfonic acid , 100 mM KCl, 25 mM NaCl, 1.5 mM MgCl2, 1 mM DTT and 0.5x Halt protease and phosphatase inhibitor cocktail, and stored with 10% v/v glycerol at −80 °C. SDHB ORF RNA of ∼1.1 kb was generated by in vitro transcription of XhoI enzyme-linearized plasmid DNA using reagents and methods provided with the MEGAscript T7 Transcription Kit (Life Technologies). SDHB RNA isolated from the transcription reaction was treated with DNAse I (Thermo Fisher) and its integrity verified by electrophoresis on an agarose gel. For in vitro SDHB RNA-editing assay, transfectant cell lysate (2–8 μl containing 21–84 μg protein) was incubated at 37 °C for 4–11 h with 50 pg (125 amole) of SDHB RNA in a buffer containing 0.02 U μl−1 RNAse inhibitor , 100 mM KCl, 10 mM HEPES (pH 7.4), 1 mM DTT and 1 mM EDTA in a total volume of 50 μl. In vitro assays with purified APOBEC3A contained 5–10 μM APOBEC3A, 50 pg SDHB full-length RNA or single-stranded SDHB DNA (c.37-c.156), 10 mM Tris (pH 8.0), 50 mM KCl and 10 or 100 nM ZnCl2 with or without 10 mM 1,10-phenanthroline (Sigma Aldrich). The reactions were incubated for 2 h at 37 °C. RNA was purified from the reactions containing transfectant lysates or purified APOBEC3A using TRIzol (Life Technologies) as per the manufacturer's instructions. The c.136C>U editing of the exogenous RNA was assessed by allele-specific RT–PCR as described previouslySDHB RNA. For Sanger sequencing to assess a 619-b segment of the RNA that spanned exons 1 to 5, the cDNA was amplified with primers with sequences 5′- GGTCCTCAGTGGATGTAGGC -3′ and 5′- TGGACTGCAGATACTGCTGCT -3′. For reactions with SDHB DNA as substrate, 4 μl of the reaction was directly used in PCR of volume 20 μl with primers with sequences 5′- TTGCCGGCCACAACCCTT -3′ and 5′- AGCCTTGTCTGGGTCCCATC -3′ to amplify the substrate for Sanger sequencing by the forward primer.Whole-cell lysates of 293T transfectants were prepared using lysis buffer containing 0.2% Surfact-Amps NP-40 (Thermo Fisher), 30 mM SDHB gene expression and c.136C>U RNA editing was quantified by RT–PCRB.E.B. designed the study with contributions from S.K.P and S.S. S.S. generated the expression constructs for mutant APOBEC3A and performed the experiments with 293T transfectants and APOBEC3A protein, and. S.K.P. analysed RNA sequencing data and editing sites, and created figures for the manuscript. B.E.B. quantified results of Sanger sequencing and analysed palindromic sequences and RNA folding. S.K.P. and E.D.K. performed the experiments with macrophages. S.M.E. and P.D.G. prepared purified APOBEC3A proteins. R.T.T., B.E.B. and S.S. performed all other experiments. B.E.B., S.K.P. and S.S. wrote the manuscript. S.S. and S.K.P. contributed equally to the study.Accession codes: RNA Sequencing data of MEPs were deposited in NCBI Sequence Read Archive (SRA) with accession number SRP040806.How to cite this article: Sharma, S. et al. APOBEC3A cytidine deaminase induces RNA editing in monocytes and macrophages. Nat. Commun. 6:6881 doi: 10.1038/ncomms7881 (2015).Supplementary Figures 1-9 and Supplementary Tables 1-10Characteristics of sites identified as differentially RNA-edited under hypoxia or M1 macrophage polarization in analyses of RNA sequencing data


Eubacterium rectale is a member of the recently-discovered Type III class of TA systems, defined by a protein toxin suppressed by direct interaction with a structured RNA antitoxin. Here, we present the crystal structure of the CptIN protein–RNA complex to 2.2 Å resolution. The structure reveals a new heterotetrameric quaternary organization for the Type III TA class, and the RNA antitoxin bears a novel structural feature of an extended A-twist motif within the pseudoknot fold. The retention of a conserved ribonuclease active site as well as traits normally associated with TA systems, such as plasmid maintenance, implicates a wider functional role for Type III TA systems. We present evidence for the co-variation of the Type III component pair, highlighting a distinctive evolutionary process in which an enzyme and its substrate co-evolve.Genes encoding toxin–antitoxin (TA) systems are near ubiquitous in bacterial genomes and they play key roles in important aspects of bacterial physiology, including genomic stability, formation of persister cells under antibiotic stress, and resistance to phage infection. The CptIN locus from  Bacterial toxin–antitoxin (TA) systems were discovered nearly 30 years ago in studies of plasmid stabilization during cell division ,2. GenesRecent advances in sequencing technology and the associated exponential increase in available genomic data have enabled large-scale bioinformatic surveys of TA loci, aimed both at finding locations of known families and discovering new TA families within the many open reading frames (ORFs) of unknown function ,8. As ittoxINPa, was discovered on a cryptic plasmid of Pectobacterium atrosepticum strain SCRI1039. A gene on this plasmid encoded a homologue of a known phage resistance protein, and this provided strong protection from some bacteriophages while also being extremely toxic to the cell (Pa and ToxIPa (for Toxin Inhibitor). Structural studies of toxINPa revealed that the ToxNPa ribonuclease cleaved the repetitive ToxIPa RNA into individual 36 base pseudoknot repeats, and then assembled with these catalytic products into a heterohexameric, triangular complex that inhibits the toxin  can also mediate phage resistance  based on sequence similarity of their toxin components . While isistance .It has also become increasingly clear that RNA species play a pivotal role in controlling gene expression in bacteria . Since tEubacterium rectale (CptINEr) as the first representative of the CptIN family. CptINEr forms a dramatically different complex from that of the previously described ToxIN systems, exhibiting a unique oligomeric structure. We demonstrate that, while CptIEr retains the pseudoknot core previously observed in other Type III antitoxins, the extended length of the RNA leads to the formation of unique tertiary features. However, the overall principles of toxin inhibition are shared between the CptIN and ToxIN families. The present study reveals the structural diversity that can exist in these loci and highlights the remarkable case in which an enzyme co-evolves with its cognate substrate.Here, we present the first structural investigation of a member of the CptIN family of Type III TA systems. Many Type III TA systems are plasmid-encoded  but we dEr was cloned into pTYB1 (NEB) using primers TRB273 and TRB274 (Table Er gene was cloned into pACYC184 (Escherichia coli ER2566 (NEB) by electroporation. For native protein expression a 500 ml culture in 2×TY media was inoculated with an overnight culture of the expression strain at a 1:100 dilution and was grown at 37°C to OD600 0.8. The cells were then shifted to 18°C, expression of CptINEr was induced with a final concentration of 1 mM IPTG, and expression was continued for 16 h. Expression of the SeMet derivative was performed using a supplemented minimal medium, as described , yielding one sharp peak identified as the CptINEr complex. The protein–RNA complex was then concentrated to ∼5 mg.ml−1 and used in crystallization trials.The ORF encoding CptNpACYC184  along wiescribed . The cel2, 100 mM CH3CO2Na, 20% v/v 2-propanol, pH 4.8. Data collection was performed on the I-02 beamline at the Diamond Light Source synchrotron facility , with a single crystal of the native complex diffracting to 2.2 Å and two crystals of the SeMet derivative, both of which diffracted to 3.0 Å .Initial crystallization trials were carried out in 96-well tray sitting drops of 200 nl of protein mixed with 200 nl of precipitant in a vapour diffusion system with 200 μl of the precipitant in a reservoir, using the Classics, JCSG+ and Protein Complex commercial screens (Qiagen). Hits were optimized using 24-well tray hanging drops of 1 μl of protein mixed with 1 μl of precipitant with 500 μl of precipitant in the reservoir. The best diffracting crystals for both the native and the SeMet derivative were from a condition containing 200 mM CaCl REFMAC5  against AMIGOS II  was usedEr repeat, or a mutated repeat, were constructed using a strategy described previously  were isomorphous, and, following phasing through SAD, the final structure was solved to a resolution of 2.2 Å  monomers each complexed with a single CptIEr RNA repeat of 45 nt. Examination of the symmetry units  reveals that each protein–RNA heterodimer formed a self-closing, heterotetrameric ring-shaped complex with a heterodimer from the neighbouring asymmetric unit  regions S1 and S2, with two loops L1 and L2, with L1 being extremely short (one base), and a much longer L2 loop , at the same time forming some unique intra-chain hydrogen bonds  also rotates around S1 in a clockwise manner  for nucleotides A27–A29. No examples of nucleotide stretches with similar torsional angles  that also interacted with the minor groove of a double helix were found in any previously described RNA structure. This suggests that the counter-clockwise A-minor twist is a novel motif.In contrast to L2b, L2a (A27–A29) is a counter-clockwise twist of 3 nt with its own unique set of polar interactions Figure ; this diEr were tested for antitoxicity against CptNEr  share a common locus organization and 35–44% sequence identity between their toxin components. Expression of any of the three CptN toxins was sufficient to cause a dramatic drop in viable count, and this was restored by co-overexpression of the cognate CptI antitoxin , and the coordinating tyrosine (Tyr104) approaches from below the plane of the base as depicted, instead of above, as in the ToxN structures. This positioning also stabilizes the entry of the RNA by stacking with G44, as described above. The combined evidence from the structures of, now, three active sites in complex with their RNA products suggest a catalytic mechanism that is similar to that seen in Ribonuclease A  of the c search .Er structure solved here forms a heterotetrameric complex  overall implies a high degree of malleability when nucleating the secondary structure around it. The three Type III families seen appear to therefore represent three energetically favourable ‘solutions’ to forming this protein–RNA complex. The lack of cross-reactivity between even extremely similar antitoxin RNAs (Figure This particular structure also raises some interesting questions regarding the evolution of the Type III TA systems. The conservation of the cage of residues in the active site shows the importance of this core to the toxic function of the system, but the low primary sequence identity (<15% between CptNs Figure  show thaE. coli, the fact that such structural diversity is seen, even with the integrity of the TA functionality being so critical, hints at the importance of these loci in bacterial physiology.Functionally, there are still many mysteries surrounding TA systems. The plasmid stabilization shows the selfish nature of these loci, independent of host context. While no phage resistance was seen in the experiments conducted in


Nrd1 and Nab3 are essential sequence-specific yeast RNA binding proteins that function as a heterodimer in the processing and degradation of diverse classes of RNAs. These proteins also regulate several mRNA coding genes; however, it remains unclear exactly what percentage of the mRNA component of the transcriptome these proteins control. To address this question, we used the pyCRAC software package developed in our laboratory to analyze CRAC and PAR-CLIP data for Nrd1-Nab3-RNA interactions.We generated high-resolution maps of Nrd1-Nab3-RNA interactions, from which we have uncovered hundreds of new Nrd1-Nab3 mRNA targets, representing between 20 and 30% of protein-coding transcripts. Although Nrd1 and Nab3 showed a preference for binding near 5′ ends of relatively short transcripts, they bound transcripts throughout coding sequences and 3′ UTRs. Moreover, our data for Nrd1-Nab3 binding to 3′ UTRs was consistent with a role for these proteins in the termination of transcription. Our data also support a tight integration of Nrd1-Nab3 with the nutrient response pathway. Finally, we provide experimental evidence for some of our predictions, using northern blot and RT-PCR assays.Collectively, our data support the notion that Nrd1 and Nab3 function is tightly integrated with the nutrient response and indicate a role for these proteins in the regulation of many mRNA coding genes. Further, we provide evidence to support the hypothesis that Nrd1-Nab3 represents a failsafe termination mechanism in instances of readthrough transcription. To better understand the function of RNA binding proteins, it is important to identify their RNA substrates and the sites of interaction. This helps to better predict their function and lead to the design of more focused functional analyses. Only recently, the development of cross-linking and immunoprecipitation (CLIP) and related techniques has made it possible to identify direct protein-RNA interactions solution -5. To issolution ,4, and isolution . We havesolution . The comsolution ,5,7. Thisolution -11. We hNrd1 and Nab3 are essential sequence-specific yeast RNA binding proteins that function as a heterodimer in processing and degradation of diverse classes of RNAs -19. TranRecent high-throughput studies have indicated Nrd1 and Nab3 frequently UV cross-link to mRNAs ,24,29 anPrevious genetic and biochemical studies have identified a number of short Nrd1 and Nab3 RNA binding motifs  ,18,24,29Two high-throughput protein-RNA cross-linking studies on Nrd1 and Nab3 in yeast have recently been described using PAR-CLIP ,29 and tWe next searched for overrepresented sequences in Nrd1 and Nab3 read contigs Figure  and onlyTLC1) as a Nrd1-Nab3 target [RPR1), the signal recognition particle RNA (SCR1) and ICR1. Collectively, our analyses uncovered over a thousand mRNAs that could be regulated by Nrd1 and Nab3.Figure 3 target ,36. OtheTo refine our analyses, we generated genome-wide coverage plots for cross-linked Nrd1 and Nab3 motifs and compared them to the distribution of the motifs present in the genome Figure .PCF11, URA8 and NRD1 . We speculate that Nrd1 and Nab3 can regulate mRNA metabolism at many levels.Both Nrd1 and Nab3 are co-transcriptionally recruited to the Pol II CTD. Chromatin immunoprecipitation (ChIP) experiments have indicated a preference for Nrd1-Nab3 binding near the 5′ ends of protein coding genes ,28,37. B Figures  and 5A [P-value <0.02) and genes involved in cellular transport activities such as nitrogen compounds . These included genes involved in ergosterol biosynthesis , nucleoporins , several nucleoside and amino acid permeases .Gene Ontology term analyses on this list of transcripts also revealed a significant enrichment of enzymes with oxidoreductase activity  [AIM44, CDC47/MCM7, DIP5, ERG24, EMI2, FCY2, FRE1, GPM2, IRA2, MIG2, MYO1, TIR2, TEX1, YOR352W and YGR269W[Regulation of many genes involved in nucleotide biosynthesis is dictated by nucleotide availability and involves selection of alternative TSSs (d ADE12) -45. Whend YGR269W,39  or opposite strand (RPS2). This arrangement of termination sites is reminiscent of the region downstream of RPL9B  where cross-linked Nrd1 and/or Nab3 motifs mapped to 3′ UTRs ) [A role for Nrd1-Nab3-dependent 3′ end processing of mRNA has also been described: the ded RNAs . Our anan Figure A and we x Figure B. Severa (XUTs)) , raisingnrd1-102 temperature-sensitive mutant showed a higher mitochondrial DNA content and was synthetically lethal with an AIM37 deletion, a gene involved in mitochondrial inheritance [P-value 0.011). These include those encoding the mitochondrial DNA binding protein (ILV5), the nuclear pore associated protein  and several mitochondrial ribosomal proteins . Notably, cells lacking AIM4 show similar defects in mitochondrial biogenesis as an aim37Δ strain [The Corden laboratory recently demonstrated a role for Nrd1 in mitochondrial DNA maintenance . An nrd1eritance ,47. Remaotein ILV, the nucCollectively, the data suggest that Nrd1 and Nab3 play an important role in mitochondrial function and development.SNR13 gene through the TSR31 gene  [All Gene Transfer Format (GTF) annotation and genomic sequence files were obtained from ENSEMBL. Genomic coordinates for annotated CUTs, SUTs, TSSs, polyadenylation sites and UTRs were obtained from the se (SGD) ,38-41. TS. cerevisiae genome (version EF2.59) using novoalign version 2.07 [Nrd1, Nab3 and Pol II (Rpb2) PAR-CLIP datasets were downloaded from the Gene Expression Omnibus (GEO) database . The fastx_toolkit  was usedion 2.07  and onlySaccharomyces Genome Database (SGD) [PyReadCounters was used to calculate overlap between aligned cDNAs and yeast genomic features. To simplify the analyses, we excluded intron-containing mRNAs. UTR coordinates were obtained from the se (SGD) ,52. The The pyCalculateFDRs script uses a modified version of a FDR algorithm implemented in Pyicos . For a dThe motif analyses were performed using the pyMotif tool from the pyCRAC suite. To indicate overrepresentation of a k-mer sequence in the experimental data, pyMotif calculates Z-scores for each k-mer, defined as the number of standard deviations by which an actual k-mer count minus the k-mer count from random data exceeds zero. K-mers were extracted from contigs that mapped sense or anti-sense to yeast genomic features. Repetitive sequences in reads or clusters were only counted once to remove biases towards homopolymeric sequences. Bedtools was used to extract motifs that overlap with genomic features such as exons and UTRs and plots were generated using Gnuplot. The EMBOSS tool fuzznuc was used to extract genomic coordinates for all possible Nrd1 and Nab3 binding and the output files were converted to the GTF format.PyBinCollector was used to generate the coverage plots. To normalize the gene lengths, the tool divided the gene sequences over an equal number of bins. For each read, cluster (and their mutations), it calculated the number of nucleotides that map to each bin (referred to as nucleotide densities). To plot the distribution of T-C mutations over the 4 nucleotide Nrd1-Nab3 RNA binding motifs, we added 50 nucleotides up- and downstream of genomic coordinates for each identified motif, and divided these into 104 bins, yielding one nucleotide per bin and the motif start at bin 51. We then calculated the number of T-C substitutions that map to each bin and divided the number by the total number of Ts in each bin, yielding T-C substitution percentages. To plot the distribution of cross-linked motifs around TSSs, we included 500 nucleotides up- and downstream of the start sites and divided these into 1,001 bins, yielding one nucleotide per bin. To generate the heat maps shown in Figures GAL::3HA strains were performed as previously described [GAL::3HA-nrd1/GAL::3HA-nab3), 10 (GAL::3HA-nrd1) or 12 hours (GAL::3HA-nab3). Total RNA extraction was performed as previously described [Western blot analyses and genetic depletion of Nrd1-Nab3 using escribed . Brieflyescribed . NortherPPM2 transcript (NM_00118395) where no significant cross-linking of Nrd1 and Nab3 was detected. For the end-point RT-PCR reactions, 100 ng of total RNA was reverse transcribed using Superscript III at 50°C according to the manufacturers instructions  and 2 μM of IPP1 reverse primer. The PCR included 200 nM of forward primers. Thermal cycling conditions were 35 cycles of: 95°C for 30 s, 60°C for 30 s and then 72°C for 1 minute.The oligonucleotide primers used for the RT-PCR analyses are listed in Table S3 in Additional file ChIP: Chromatin immunoprecipitation; CLIP: Cross-linking and immunoprecipitation; CPF: Cleavage and polyadenylation; CRAC: Cross-linking and cDNA analysis; CTD: Carboxy-terminal domain; CUT: Cryptic unstable transcript; FDR: False discovery rate; GTF: Gene Transfer Format; PCR: Polymerase chain reaction; Pol: RNA polymerase; qRT-PCR: Quantitative RT-PCR; snoRNA: Small nucleolar RNA; snRNA: Small nuclear RNA; SUT: Stable unannotated transcript; TSS: Transcription start site; UTR: Untranslated region; XUT: Xrn1-sensitive unstable transcript.The authors declare that they have no competing interests.SW implemented pyCRAC in Galaxy, RDH performed the qRT-PCR experiments, GK aided in the development pyBarcodeFilter and pyMotif. SG conceived and performed the experimental and computational procedures and developed the pyCRAC tools. SW, RDH, GK and SG wrote the paper. All authors read and approved the final manuscript for publication.Table S2. Transcripts that contained cross-linked Nrd1-Nab3 motifs in 3′ UTRs. Table S3. Oligonucleotides used in this study.PyMotif identified previously described Nrd1-Nab3 RNA binding motifs. Shown are overrepresented 4- to 6-mers (k-mers) and corresponding Z-scores that were isolated from the Nrd1  and Nab3  intervals with an FDR value of <0.01. Previously identified Nrd1 and Nab3 motifs are highlighted in red and blue, respectively. Click here for file Analysis of T-C mutations found in the PAR-CLIP data near Nab3 and Nrd1 RNA binding motifs. (C) Analysis of deletions found in the Nab3 CRAC data around the Nab3 motifs [ and Nrd1  (A) motifs identified in the genome. To calculate T-C conversion percentages, the number of T-C substitutions was divided by the total number of Ts at each position. The asterisks indicate the positions in the motif where most frequently T-C substitutions were found in the Nrd1-Nab3 motifs.Mutations are enriched in and around Nrd1 and Nab3 RNA binding motifs. 3 motifs . pyBinCoClick here for file