We found that the establishment of editing and variation in editing levels across Drosophila species are largely explained and predicted by cis-regulatory elements. Furthermore, editing events that arose early in the species tree tend to be more highly edited in clusters and enriched in slowly-evolved neuronal genes, thus suggesting that the main role of RNA editing is for fine-tuning neurological functions. While nonsynonymous editing events have been long recognized as playing a functional role, in addition to nonsynonymous editing sites, a large fraction of 3’UTR editing sites is evolutionarily constrained, highly edited, and thus likely functional. We find that these 3’UTR editing events can alter mRNA stability and affect miRNA binding and thus highlight the functional roles of noncoding RNA editing. Our work, through evolutionary analyses of RNA editing in Drosophila, uncovers novel insights of RNA editing regulation as well as its functions in both coding and non-coding regions.Adenosine-to-inosine RNA editing diversifies the transcriptome and promotes functional diversity, particularly in the brain. A plethora of editing sites has been recently identified; however, how they are selected and regulated and which are functionally important are largely unknown. Here we show the  Drosophila genus as model organisms, we analyze the evolution of A-to-I RNA editing to identify a large fraction of both coding and non-coding editing events that are under evolutionary constraint and therefore likely functionally important. We find that non-coding editing events in the 3’UTRs of genes could affect miRNA binding and are associated with a decrease in gene expression levels.Many important modifications are made to RNA to fine-tune genomic information. One type, Adenosine-to-Inosine (A-to-I) RNA editing, changes certain adenosines to inosines and is essential for the neurological well-being of many animals. Although RNA editing occurs at thousands of sites across the genomes of various animals, the functions of nearly all editing events–particularly those in non-coding regions–have not been studied, and what determines whether particular adenosines across the genome are edited has not been fully explored. Here, using the  Drosophila, the knockout of ADAR leads to severe neurological defects such as locomotion impairment, heat sensitive-paralysis, and age-dependent tremors [Adenosine-to-inosine (A-to-I) RNA editing converts adenosine to inosine in RNA, which is then read by the cellular machinery as guanosine (G) –3. This  tremors .Drosophila, a significant fraction of editing events are located in coding regions, and many are likely to be beneficial [The widespread presence of A-to-I editing at thousands to millions of sites in various organisms, from flies to humans, has been recently revealed e.g. ,12–18). –18. 12–1neficial –24.Drosophila genus and find that a surprisingly large fraction of both types are under selective pressure and therefore likely functionally important. Furthermore, we examine the potential functions of editing events in 3’ UTRs using a fly with catalytically inactive ADAR.While these studies have highlighted the potential functions of coding editing events, little is known about noncoding events. Few instances of noncoding RNA editing functions have been found: For example, RNA editing in the intron of mammalian ADAR2 alters splicing and thus truncates the protein . In thisDrosophila, this only represents a small fraction of the adenosines in the genome, and why particular adenosines are edited is not fully explored. Our analysis of the evolution of RNA editing gives us an opportunity to study how the evolution of RNA editing substrates alters editing. By making incremental changes to editing substrates, evolution has conducted a natural experiment allowing us to test the effects of various changes on RNA editing. Therefore, we can examine the characteristics of editing substrates. dsRNA is a well-known requirement for A-to-I RNA editing [Drosophila genus.Although there are thousands of editing events in  editing –28; we r editing ,30. Furt editing . HoweverDrosophila genus to use for our analyses. Although we and others have recently identified a large number of RNA editing sites in D. melanogaster (D.mel) [D.mel and identify additional editing sites unique in other Drosophila species, we applied our previously developed methods [Drosophila species (S1 Table). We identified 627 novel exonic editing sites, including 545 novel ones edited in non-D.mel species only (S2 Table). We combined this list with three other sets of sites identified in D.mel [D.mel ADAR null mutant [S1C Fig). We removed the false positive sites to obtain 2,380 exonic editing sites (counting orthologous sites only once) (S2 Table). These sites are located in 909 genes, preferentially in coding regions and 3’UTRs. 56% alter amino acid coding .We first assembled a master list of editing sites in the  (D.mel) ,13,16, iD.mel and 5 other Drosophila species that spanned a range of evolutionary distances from D.mel and had well assembled genomes and deeper RNA-seq coverage . To accurately measure editing levels in the RNA-seq data, only sites covered by ≥20 or 50 reads (medium or high stringency) were included, which leads to an average of 95 or 127 reads per editing site, respectively. While RNA-seq has been used to quantify RNA editing [S4 Table). We obtained ~2,400 reads per editing site per sample . Editing levels are highly consistent between biological replicates  and with the RNA-seq quantification when sufficient RNA-seq reads are available . Finally, we combined the RNA-seq and mmPCR-seq datasets to obtain a more comprehensive and accurate RNA editing level measurement .We next used publicly available RNA-seq data, supplemented with our targeted sequencing assay covering ~600 editing sites, to measure the editing levels of the 2,380 exonic editing sites in  editing , its ina editing  to quantS2E Fig) and, separately, eight D.mel strains , we found that there was a clear positive correlation between editing level divergence and species divergence time . Furthermore, the editing level divergence tree recapitulates the topology of the phylogenetic tree . These observations suggest that editing level evolution is generally neutral.When we compared editing levels between all pairs of the six species . To evaluate the effect of ADAR motif changes on editing level variation, we first deduced the ADAR motif weight matrix and used it to calculate motif scores for each of the 16 possible nucleotide triplets  in the “anchor” species but absent (≤1.5% level) in the other species under comparison to the control “Presence/Presence” sites, which were edited (≥10%) in both species. With D.mel as an example anchor species, we found that ~25% of Presence/Absence sites had higher motif scores in D.mel, while only 8% of them had higher motif scores in the other, non-edited species, indicating an excess of better ADAR motifs in the “anchor” species  . Strikingly, <1% of the “Presence/Presence” control sites had motif differences between species, although many of the sites were edited at different levels between two species. We observed similar results when performing the same analyses using the other 5 species as the anchor . Therefore, ADAR motif preference plays an important role to determine whether a site is edited rather than how much a site is edited.ADAR’s preferred sequence motif, in particular the triplet containing nucleotides immediately adjacent to the edited adenosine , is esseFig 2B. This observation is also supported by our recent analyses of secondary structure changes within D.mel strains [To examine the effect of secondary structure on editing level variation, we used a computational pipeline we previously developed  to predi strains .Drosophila species, we dissected the dsRNA structures into 8 structural features and examined their roles separately . Using the set of Presence/Absence editing sites and its control set of Presence/Presence sites described above, we observed that Presence/Absence of RNA editing best correlated with free energy, stem length, and number of paired bases . This suggests that the stability and length of the RNA duplex play an important role for editing.To systematically evaluate how secondary structure changes contribute to editing variation across Materials and Methods). The difference in the prediction accuracy before and after permuting the predictor variable is used as an importance measure . For both scenarios, structural features such as folding energy, base-pairing, and stem length were important. While motif score and maximum bulge size were important in determining the presence or absence of editing, they were less informative for explaining editing level variation. Thus, our observations suggest that both motif and structural features determine whether ADAR can bind and edit a substrate, while changes in structural features contribute to editing level variation. It was previously shown that mutations in the ADAR motif can increase or decrease editing levels in vitro [in vivo, perhaps because such tuning allows for greater flexibility.While we showed that both motif and dsRNA structure changes are associated with editing changes, their relative importance is unknown. To study how these two regulatory elements work together, we determined the relative importance of the features for the establishment of editing in Presence/Absence sites and the variation in editing levels observed in Presence/Presence sites. We used random forests, a machine learning technique , to predin vitro . But ourcis-regulatory elements to editing divergence, we examined how well these features could be combined together to predict changes in editing using random forests [cis-elements to editing divergence. In particular, given the editing levels in D.mel, we predicted the editing levels of orthologous sites in other species. The predictive accuracy of the model with motif and structural features are substantially higher than those of the model without these features . Therefore, a large portion of the editing level divergence across species can be accounted for by changes in cis regulation. Taken together, our cis regulatory element analyses reveal the structural landscape of editing and demonstrate how cis regulatory element changes lead to editing changes.To estimate the contribution of  forests . The difD.mel editing site . We found that evolutionarily long-lived (older) editing sites have higher editing levels than younger sites , suggesting that the older sites with higher editing levels might be optimized for ADAR binding and editing. We observed similar results when using the other Drosophila species as the anchor . Our observation that older sites are much more likely to be clustered with other nearby editing sites  further supports the idea that the sequences around older editing events can be edited at multiple positions and thus might be optimized for editing. Additionally, we found that the correlation of editing levels between species for old editing sites is higher than that for young editing sites , suggesting that older sites are under stronger purifying selection. Furthermore, we examined the functional enrichment of genes containing the younger and older editing sites. We observed no significant enrichment for genes containing the younger editing sites. However, the older sites gradually became enriched in genes with functions that are mostly neuron-related , the ratio of the nonsynonymous site substitution rate (Ka) to the synonymous site substitution rate (Ks) [S8A Fig). This pattern persists when comparing genes with and without editing sites within the same functional categories . Furthermore, the number of nonsynonymous editing sites per gene is negatively correlated with the evolution rate of edited genes . In contrast, no significant correlation was observed for genes with intronic editing sites . Consistent with the findings above, we found that younger sites reside in genes evolving at a rate similar to the rest of the genome, while older editing sites tend to be in slowly evolved genes . Additionally, neuronal genes evolved more slowly . Taken together, these results suggest that individual editing events arise in genes of diverse functions and are subsequently selected to remain in slowly evolved genes, particularly with neuronal functions.To determine whether editing tended to affect slowly or quickly evolving genes, we also examined the evolution rate of edited versus unedited genes. We only analyzed RNA editing sites identified from ta alone ,13, in oate (Ks) . We founD.mel editing sites based on whether they resulted in nonsynonymous, synonymous, or 3’UTR editing (5’UTR sites were not examined because only a few were available) and examined their evolution with respect to both editing levels and surrounding DNA sequences. First, we examined the editing levels of the eight D.mel strains. The editing levels of nonsynonymous sites are least variable, suggesting the strongest selective pressure. Unexpectedly, the editing levels of the 3’UTR sites are much less variable than those of the synonymous sites, indicating the presence of purifying selection around the 3’UTR sites . We observed a similar pattern between species, except that the editing levels of 3’UTR sites were more variable, probably because of the increased sequence divergence rate in noncoding regions between species . Second, we examined the conservation levels of DNA sequences surrounding editing sites. We used RNA editing sites identified from D.mel RNA-seq data alone [S9D Fig). This is likely due to the evolutionary constraint in maintaining the dsRNA structure for many nonsynonymous and 3’UTR sites. Additionally, we observed higher editing levels of nonsynonymous and 3’UTR sites . These data suggest that a large number of nonsynonymous and 3’UTR, but not synonymous, sites are functionally important.We next separated exonic ta alone ,13, in oS2 Table). By examining the conservation of the regions spanning the editing sites and the more distal flanking regions, we categorized each editing site as highly constrained, moderately constrained, or unconstrained . We found 514 highly constrained and 466 moderately constrained sites (S2 Table). As expected, the surrounding DNA sequences of evolutionarily older sites tended to be highly or moderately constrained . In addition, the highly constrained nonsynonymous and 3’UTR sites had the highest editing levels, and the moderately constrained sites had higher editing levels than the unconstrained ones , further supporting the functional importance of highly and moderately constrained sites. If one assumes that lowly edited (<1.5%) events are functionally neutral and uses the fraction of lowly edited sites in highly or moderately constrained regions as a baseline, one can roughly estimate that 14.2%  of nonsynonymous editing events and 12.0%  of 3’UTR editing events are in highly or moderately constrained regions and therefore likely functionally important. For synonymous events, the difference is not significant .  This further supports the idea that a fraction of nonsynonymous and 3’UTR editing events are likely functionally important.Our observations prompted us to identify sites that were under evolutionary constraint and thus more likely to be functional . This effect was more dramatic in genes that were edited in more than one site in the 3’UTR (p = 0.004) . Additionally, we found that the expression levels of genes with high 3’UTR editing levels or constrained 3’UTR sites increased more than those of genes with low editing levels or unconstrained sites, respectively . Thus, 3’UTR editing is associated with changes in gene expression, and this further supports the functional importance of 3’UTR editing.While nonsynonymous amino acid changes affect protein sequence, the function of 3’UTR editing is unclear and under studied. 3’UTR regions often play a regulatory role in gene expression . Therefo4 (S1 Table). Because RNA editing is co-transcriptional [Fig 5E). On the contrary, 3’UTR editing sites have very similar editing levels in nascent RNA and polyA+ mRNA . This suggests that, among other possibilities, the edited 3’UTR transcripts may be degraded post-transcriptionally, thus lowering the editing levels in the mature polyA+ mRNA. Further experiments are needed to provide direct evidence for this hypothesis.The association of the presence of 3’UTR editing and decrease in gene expression prompted us to hypothesize that RNA editing in the 3’UTR may lead to mRNA degradation. To test this, we compared editing levels from nascent RNA-seq to those from polyA+ RNA-seq in publicly available data2 Fold change >0.2 or <-0.2, 14 genes in total). We only used miRNAs that are co-expressed in fly male head samples for target prediction. We identified two editing events that create binding sites for miR-282-5p and miR-1017-3p; in both cases, the host genes have increased gene expression levels in the EA mutant compared to the WT flies . Therefore, RNA editing in the 3’UTR may affect miRNA binding, thus at least partially explaining the gene expression.We further explored the possible roles of miRNAs in regulating gene expression via differential binding to edited and unedited 3’UTRs ,41. We eDrosophila genus. We used changes in both RNA primary sequence and secondary structure to predict differences in editing level between species. This highlights the importance of local cis-regulatory changes in the evolution of individual RNA editing events, consistent with the findings of recent studies of RNA editing variation across more closely related Drosophila [cis regulatory architecture of RNA editing and demonstrated how these features can be used to explain and predict the occurrence of an editing event as well as differences of RNA editing across species. For example, unexpectedly, we found that the ADAR binding motif is a feature that is a lot more important to determine whether a site can be edited compared to what level a site is edited . Our work lays a foundation for future work towards a cis regulatory code of RNA editing.In this work, we examined the birth, death, and persistence of editing events as well as the quantitative changes of editing levels during ~60 million years of evolution in the osophila ,30, and In addition, our data suggests that RNA editing is selected to be enriched in slowly evolved neuronal genes. While neuronal genes evolve slowly, the nervous system acquires high complexity at least partially through the means of RNA editing. Thus, RNA editing, rather than nucleotide substitution at the genomic DNA level, may be the preferred evolutionary means of fine-tuning neuronal functions.Drosophila RNA editing evolution was published [Drosophila genus and found that editing events conserved in at least two members of a gene family were enriched in genes with neurological functions and in regions subject to purifying selection. These conserved editing events tended to cause amino acid changes, which is consistent with the idea that nonsynonymous editing events are more likely functionally important. This is echoed by our analyses that employ a targeted deep sequencing method to achieve much more accurate measurements of RNA editing levels. We both find that highly conserved editing events tend to be nonsynonymous, in neurological genes, and in regions or genes with a lower substitution rate.While this manuscript was under preparation, another study on ublished . Yu and In addition to examining coding events, our work delves further into the often ignored non-coding RNA editing events. We found that 3’UTR editing is evolutionarily constrained at the DNA level and highly conserved at the RNA level. This is surprising to us given that the non-coding 3’UTRs are generally not evolutionarily conserved compared to coding regions. While the nonsynonymous editing events may have a more obvious function because of their ability to alter amino acid sequences, our work suggests that many 3’UTR sites are under negative selection. Thus, we identify a large fraction of both nonsynonymous and 3’UTR editing events that are likely functionally important. Our list of candidate functional sites will be valuable for further identification and characterization of truly functional, individual editing sites among the large number of sites that have been recently identified e.g. ,12–14).–14.12–14in vivo suggests a new role for RNA editing in the regulation of RNA expression levels. We also pinpoint examples of 3’UTR editing sites that alter miRNA binding, thus affecting gene expression. Our findings would add another element to the array of tools by which RNA editing could fine-tune gene function in complex neurological systems. Further experimental work needs to be done to establish whether 3’UTR editing causes gene expression changes, and to explore the mechanism of action. In sum, our analyses provide strong evidence for a set of functional RNA editing sites and indicate an association between 3’UTR editing and mRNA regulation.Our work further provides evidence of potential functions of 3’UTR editing events. Our finding that 3’UTR editing is associated with mRNA degradation S11 Fig), so caution should be exercised when using editing level alone as a proxy for fitness or negative selection. The approaches used in this study can be applied to identify functionally important editing events in other species, such as the primates where RNA editing is a lot more abundant particularly in non-coding regions [By comparative evolutionary analyses, we found that nonsynonymous and 3’UTR sites are edited at high levels and located in highly or moderately constrained genomic regions. These data suggest that nonsynonymous and 3UTR edited sites are functionally important. However, it should be noted that little is known about the dominance of post-editing phenotypes, and editing divergence is only moderately correlated with the editing level ( regions .Drosophila species from the NCBI Sequence Read Archive (SRA) (http://www.ncbi.nlm.nih.gov/sra) and modENCODE project (http://www.modencode.org/). We obtained the Anopheles gambiae whole body RNA-seq data from NCBI SRA. A list of datasets is shown in S1 Table. We obtained D.mel yellow white (yw) strain nascent RNA-seq, ADAR null mutant nascent RNA-seq, yw genomic DNA-seq, ADAR wild type and null mutant RNA-seq from NCBI SRA .We obtained RNA-seq data for 13 We adopted a pipeline that can accurately map RNA-seq reads to the genome . In brieD.eug, D.tak, D.fic, D.ele, D.kik, and D.bip), the sequences were aligned using Lastz with the following parameters: H = 2000, Y = 3400, L = 4000, K = 2200, O = 400, and E = 30 [The LiftOver tool was used to convert genomic positions between different species. Since LiftOver does not provide strand information between two species , we obtained the strand information between different species using pairwise alignment data from UCSC genome browser. For the 6 species without genome alignments available on the UCSC genome browser . RNA variants were called separately for each species as described above. Shared RNA variants that are present in any of the species pairs were obtained using various frequency cutoffs. As expected, the majority of the resulting RNA variants are A-to-G mismatches, indicative of A-to-I editing . To achieve a high accuracy in editing site calling without a substantial reduction in sensitivity, we chose a frequency cutoff such that the fraction of variants that were A-to-G was at least 80% [S2 Table).We have recently developed a cross-species transcriptome comparison method that accurately identifies exonic RNA editing events . We modieast 80% . In totaD.mel wild type strain and from the Adar null mutant that eliminates RNA editing . We then removed the sites we found to be false positives to obtain 2,380 exonic editing sites.We next combined this list with three other lists ,13,16. WD.mel editing site list [We note that we did not include a recently published ite list  because  All stocks were grown on standard molasses media (Stanford fly media center). Ten whole bodies were collected from adult flies (eclosion + ~5 days) for each sample. The ADAR E374A mutant (“Adar EA”) contains 2 point mutations: C1725T (synonymous) and A1733C (leading to the E374A mutation), was produced using CRISPR reagents described in [y sc background, backcrossed to white Canton-S (CS) for 7 generations. For the RNAseq, stocks were grown at 18°C, and heads were collected from 3 day old male adult flies.A list of all species and strains used for mmPCR-seq are listed in ribed in , and is Total RNA was extracted with the RNeasy Kit (Qiagen). After DNase I treatment, 3 ug of total RNA was used to synthesize the cDNA using iScript™ Advanced cDNA Synthesis Kit (Bio-Rad). cDNA was purified with MinElute PCR Purification Kit (Qiagen).For the ADAR EA mutant RNAseq, total RNA was extracted using RNAdvance magnetic beads (Agencourt), treated using TURBO DNase (Thermo Fisher Scientific), depleted of ribosomal RNA , and treD.mel using RNA-seq data for primer design. Using the D.mel genome, we designed 48 pools of 12 to 15-plex multiplex PCR primers [D.ana, D.pse, and D.vir, we also designed additional multiplex primers, which covered 192, 211, and 232 editing loci, respectively, that could not be amplified using the primers designed for D.mel. All primer sequences are listed in S4 Table.We used a microfluidic multiplex PCR and sequencing method  to quant primers , which cWe next loaded cDNAs and primer pools into the 48.48 Access Array IFC (Fluidigm) and performed target amplification as previously described . PCR proWe used the FASTX Toolkit  to demultiplex the raw reads. We used Tophat  to alignFor editing level quantification, sites covered by ≥50 mmPCR-seq reads were used.D.mel. For the non-D.mel species, because of the presence of the mismatches between some of the D.mel primers and templates, we expected that the amplification efficiency of different loci would be variable; in addition, some loci could not be amplified. As expected, we found a higher variability in coverage of various loci in non-D.mel data . Since we are only comparing the ratios of two alleles of the same amplicon, we expect that the amplification efficiency difference should not affect the accuracy of editing level measurement. Both the high reproducibility of biological replicates  of highly edited sites (≥50%). The motif weight matrices are very similar across species so we used the average motif weight matrix for analysis. Motif scores of each of the 16 possible nucleotide triplets were calculated by FIMO  and thenD.mel as an anchor species, we found 492 Presence/Absence sites. 90% of the Presence/Absence sites had statistically significant higher editing levels in D.mel . And 99% of the absence sites had similar editing level to the typical A-to-G sequencing error rate, indicating no evidence of editing.To maximize the number of sites used for “Presence/Absence” site analysis, we combined the male and female whole body data. For an editing site to be considered as absence, we required that the observed A-to-G frequency was less than 1.5% in all datasets with editing level measurements for the site. For an editing site to be considered as presence, we required that the A-to-G frequency was at least 10% in at least one dataset. To estimate if an absent site has evidence of editing, we examined if the editing level of this site was significantly higher than the typical A-to-G sequencing error rate (1%)  based onDrosophila species. To predict distal, intronic ECSs, we predicted conserved ECSs located in intronic regions. We smoothed phastCons scores using a sliding window of 51 bp [D.mel, the species in which they were identified, we used only the proximal ECSs for our cross-species evolutionary analyses. Both the intronic and proximal ECSs were used for comparisons within the D.mel population.We used the proximal and distal ECS prediction pipelines previously described . Brieflyof 51 bp . We seleWe used our ECS predictions for two types of analyses to examine how differences in various features of orthologous sites are related to differences in editing level. First, we examined changes of editing in two scenarios. In the “Presence/Absence” scenario, we examined features of sites that were edited (≥10%) in an “anchor” species and unedited (≤1.5%) in another species. As a control, comparisons were also made in the “Presence/Presence” scenario, in which both the anchor and other species were edited (≥10%). Sites with predicted ECSs that passed the filter in the anchor species were used. (The ECS was not required to pass the filter in the other species since it may or may not be present.) Secondly, we predicted the editing level in a second species, given the editing level in the first species. In this analysis, sites with ECS predictions that passed the filter in at least one of the two species were used.We dissected the dsRNA structures into 8 structural features . To determine the free energy of the dsRNA stem, we joined the editing stem with the complementary region stem by a 100 base linker of adenosines and ran the RNA secondary structure prediction program fold from the RNAStructure package.The relationship between editing changes and the ADAR motif and 8 structural features was modeled using random forests  (R packaR2) = 1 –(the mean squared error of the editing level prediction / the variance in editing levels).To predict whether a site is edited (“Presence/Absence”), classification trees were used.  are made to classify items (ie: sites).) To predict the editing level changes (“Presence/Presence”), regression trees, which are decision tree models that use continuous values, were used. The relative importance of the features  was calculated by randomly permuting each feature, taking the average difference between the accuracy of predictions using the permuted data and the accuracy using the non-permuted data, and then dividing by their standard deviation . The perD.mel without motif and structural features, there was only one feature, so only one was sampled at each split .For predicting the editing level in one species using the editing level in To calculate the conservation levels of DNA sequences surrounding the editing sites, we used a 30 bp sliding window size because the editing stem regions are usually 30–50 bp long . For nonTo categorize each editing site as highly constrained, moderately constrained or unconstrained, we examined the conservation of the region spanning the editing sites  and the more distal flanking region . We first defined sites with high conservations (average PhastCons score > 0.9) for both S_region and F_region as highly constrained sites. For the remaining sites, we defined sites with a statistically significant higher conservation in the S_region compared to the F_region to be moderately constrained sites, and the ones with similar or lower conservation of S_regions as unconstrained sites. The significance was determined using two-sample Kolmogorov-Smirnov test .D.mel RNA-seq datasets, including 30 RNA-seq datasets from 30 developmental stages spanning the whole life cycle and 29 tissue-specific RNA-seq datasets in various tissues dissected from various stages (http://www.modencode.org/). For each dataset, we calculate editing levels for editing sites covered by ≥20 reads. For each site, the maximal editing level across all samples was used as the representative editing level of a site.We obtained a total of 59 D.mel editing event using a combination of the male and female whole body data. We used 5 fly species  and 1 mosquito species (Anopheles gambiae) representing 6 time points compared to D.mel. We posited that editing events rarely independently originate from different lineages so the age of each D.mel editing site was based on the most distantly related species in which sites were also edited (parsimony principle).We defined the age of each To determine if a site is edited, we required the editing level to be ≥2% in at least one dataset. With this cutoff, 89% of the editing sites have significantly higher editing levels than the typical A-to-G sequencing error rate (1%)   term analysis was done using DAVID . P-valueThe ω values of each gene were obtained from Larracuente and colleagues . In brieRNA sequencing libraries of the Adar EA mutant and wild type control were produced using the KAPA RNA-Seq Kit (Kapa Biosystems). Libraries were sequenced on an Illumina NextSeq 500 Sequencer using paired-end 75-bp cycles. Reads were mapped using TopHat  and DESeWe obtained nascent and polyA RNA-seq data for yw male head samples from a recent study . Reads wD.mel miRNAs. miRNAs were obtained from miRBase database Release 20. Male head miRNA expression data was from GSM322543. Only miRNAs expressed in male heads  were used for analysis.We used the TargetScan algorithm  to prediS1 FigA) The pipeline for exonic editing identification by the cross-species transcriptome comparison method. (B) Relationship between the proportion of detected mismatches that are A-to-G and the minimum editing level . The colors indicate the minimum editing levels. Each colored, vertical line represents the RNA variants shared by one pair of species. Dotted line indicates an 80% A-to-G fraction cutoff. (C) The false discovery rate (FDR) of exonic RNA editing site identification for the 4 specified studies. The D.mel Adar-/- mutant RNA-seq data were used to estimate FDRs. The numbers of editing sites are indicated above the bars. (D) Distribution of exonic sites in various genic regions. CDS sites are categorized by functional consequence into three groups: nonsynonymous, synonymous, and stoploss changes. (E) The density of exonic sites in various genic regions.((PDF)Click here for additional data file.S2 FigA) The read number (gray bar) and mapping rate (red dot) of each sample. (B) The coverage of editing sites for each sample. (C) Correlations between editing levels of biological or technical replicates. Sites present in all samples for each species were used for this analysis. All samples are biological replicates except the ones indicated with *. (D) Comparison of editing levels measured by mmPCR-seq and RNA-seq. Both the RNA-seq and mmPCR-seq data are from ~5 day adult whole body samples. A minimum number of 20 and 50 reads is required for sites measured with RNA-seq and mmPCR-seq data, respectively. (E) Pairwise comparison of editing levels between species. The Spearman’s rho values are indicated in red. Female whole body data is shown. (F) Comparison of editing levels measured by mmPCR-seq in eight D.mel strains. Spearman’s rho values are indicated in red.((PDF)Click here for additional data file.S3 FigThe FPKMs (fragments per kilobase of exon per million fragments mapped) of ADAR and tubulin are shown. The error bars indicate the differences between male and female gene expression levels. The triangles indicate the ADAR expression levels normalized by the tubulin expression levels.(PDF)Click here for additional data file.S4 FigDrosophila species.Nucleotide composition in the position immediately upstream (left) and downstream (right) of editing sites in six (PDF)Click here for additional data file.S5 FigA) The difference in motif score for editing sites that are edited (≥10%) in one species but not edited (≤1.5%) in the other species under comparison (green), compared to the control in which sites are edited (≥10%) in both species (purple). (B) The difference in free energy, number of paired bases and stem length between sites that are edited (≥10%) in one species but not edited (≤1.5%) in the other species under comparison (green), compared to the control in which sites are edited (≥10%) in both species (purple). The D.mel-D.sim comparisons are not shown because there are fewer than 10 editing sites with ECS predictions that are edited ≥10% in D.sim and not edited in D.mel. D. pse and D. vir are not shown because, for every species pair, fewer than 10 editing sites with ECS predictions are edited ≥10% in them and not edited in the other species under comparison. *: p ≤ 0.05, **: p ≤ 0.01, ***: p ≤ 0.001 (one-tailed Mann-Whitney U test).((PDF)Click here for additional data file.S6 FigD.mel as the “anchor,” please see Fig 3.)Left of each panel: Depiction of the species and age groups analyzed; numbers above the branches denote the numbers of editing sites in each age group. The anchor species is in bold. Right of each panel: Boxplots of the editing levels in the anchor species for the editing sites in each age group. Spearman’s ρ is indicated. (For the plots using (PDF)Click here for additional data file.S7 FigD.mel subgroup ; old sites: sites edited in all Drosophila species analyzed. Both Pearson and Spearman correlation coefficients are shown.Young sites: shared only in (PDF)Click here for additional data file.S8 FigA) The comparison of evolution rate between genes with nonsynonymous sites, genes with synonymous sites only, and unedited genes. Since editing preferentially occurs in neural tissues, to avoid potential bias, we used genes expressed in heads as a control. (B-C) The relationship between ω of edited genes and the normalized number of nonsynonymous editing sites per gene between D.mel–D.yak (B) or D.mel–D.ana (C). Spearman's ρ is indicated. (D) The relationship between the number of intronic editing sites per gene and omega. The number of intronic editing sites is normalized by the number of adenosines in the intron. (E) The comparison of evolution rate between neuronal genes and all fly protein coding genes. We defined genes with neuron-related GO terms to be neuronal genes. P-values were calculated using the Mann-Whitney U test.((PDF)Click here for additional data file.S9 FigA) The pairwise comparisons of editing level differences between D.mel strains for nonsynonymous, synonymous, and 3’UTR sites. To minimize the effect of different distributions of editing levels in the three categories, sites edited at ≥20% in one or both strains in the pairwise comparisons were used. P-value was calculated using Paired-sample Wilcoxon test. (B-C) The pair-wise comparisons of normalized (B) or unnormalized (C) average editing level difference across species. Male whole body data was shown. All sites with at least 20 reads are included. Sites edited at ≥20% in one or both strains in the pairwise comparisons were used. P-value was calculated using the Paired-sample Wilcoxon test. (D) Conservation of DNA sequences surrounding ECSs. Left: the PhastCons score distributions for the 60 bp regions flanking the corresponding sites in ECSs that are paired with the editing sites. The results were plotted separately for nonsynonymous, synonymous and 3’UTR editing sites using a 30 bp window size. We only analyzed D.mel proximal ECSs, in order to avoid potential bias of using evolutionarily conserved intronic ECSs. Since ECSs located in different genic regions likely have different evolution rates, for nonsynonymous and synonymous editing sites, we only examined ECSs located in CDS regions; for 3’UTR editing sites, we only examined ECSs located in 3’UTR regions. Regions that are significantly different  from the site paired with editing site  are colored gray. Right: normalized conservation score, i.e. the D statistic of the flanking regions of edited loci relative to the region with the highest conservation score.((PDF)Click here for additional data file.S10 FigFig 3A. Right: The distribution of highly (red), moderately constrained (yellow), or unconstrained (blue) sites in each age group.Left: Depiction of the species and age groups analyzed as in (PDF)Click here for additional data file.S11 FigD.mel–editing level, the other species) / . Spearman's ρ is indicated.Editing conservation is defined as 1 − Absolute value Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S8 Table(XLSX)Click here for additional data file.


All sequencing experiments and most functional genomics screens rely on the generation of libraries to comprehensively capture pools of targeted sequences. In the past decade especially, driven by the progress in the field of massively parallel sequencing, numerous studies have comprehensively assessed the impact of particular manipulations on library complexity and quality, and characterized the activities and specificities of several key enzymes used in library construction. Fortunately, careful protocol design and reagent choice can substantially mitigate many of these biases, and enable reliable representation of sequences in libraries. This review aims to guide the reader through the vast expanse of literature on the subject to promote informed library generation, independent of the application. Next generation sequencing technologies have undeniably changed the scientific landscape in biology. The fast-paced methodological progress driving many of the developments in the field has not only been the result of exceptional advances in sequencing chemistry, detection systems and data-processing or analysis methods , but alsIn addition to libraries for sequencing purposes, many proteome-wide functional assays, for instance assessing protein interactions ,3, proteMany researchers can (and do) resort to the use of commercial kits to capture the desired nucleic acid species into a workable library of molecules. While there are numerous suppliers for sequencing library construction, and the resulting libraries are often of reasonable quality for standard sequencing experiments (e.g. transcriptome sequencing), it is generally acknowledged that these conventional procedures allow little room to tailor the library toward the specific needs of the researcher, especially when the research question calls for a non-standard approach. Additionally, there is always a lag between the description of a new method and its commercialization.The goal of this review is to provide an in-depth yet application-independent overview of current and state-of-the-art technical developments in the field, guiding the reader through the vast expanse of tools that can be used to turn a pool of nucleic acids into a library that can be sequenced or assayed using other means. We here summarized the principal insights in this fast-paced discipline, expanding on newly published studies and aspects not covered in previous reviews .+-RNA transcripts, but can extend to in vitro-transcribed (IVT) RNA, various types of non-coding RNAs, ribosome footprints, tRNAs, crosslinked RNA or modified RNA. For each of these subsets, dedicated protocols . The starting point in RNA procedures are mostly total RNA or poly(A)rotocols  or commeRibosomal RNA (rRNA) makes up more than 80–90% of the total RNA pool of all cells . In mostHEG1 and DUX mRNAs , as was recently assessed by sequencing of IVT-arrayed cDNA libraries (+ selection will only recover the 3′ portion of the transcript.Poly(A)-tailed RNA selection via hybridization capture using oligo(dT)-coupled beads (or variations on this theme) has been very powerful to extract protein-coding mRNA transcripts from the total RNA pool, passively depleting it from rRNA and immature or incompletely processed heterogeneous nuclear RNA . The mosUX mRNAs , althougocessing . Additioocessing , bacteriocessing ,30,31. FNA genes . Many ofibraries . Finally+ selection -selection, correlated the most with total RNA data  and RiboMinus (Thermo Fisher)) is a popular alternative compatible with the recovery of poly(A)-negative RNA, as it offsets many of the disadvantages of poly(A)-selection. However, remaining contaminating rRNA is also of concern, to a variable extent but generally more so than in poly(A)election ,32,33. Aelection ,26. Of telection . For mRNRNA data . EnzymatRNA data ,36, evenRNA data   that will dictate which approach is the most appropriate. However, it is important to note that none of these strategies are compatible with the minute amounts of RNA extracted from a single cell. Instead, current single-cell RNA-seq library construction methods almost exclusively rely on direct oligo(dT)-based priming  of extracted RNA to simultaneously deplete ribosomal species and prime the mRNA for reverse transcription cription . In one cription .Fragmentation is a requirement for most sequencing libraries, as uniform sizing of molecules is important for optimal performance of most ‘second-generation’ sequencing instruments. This is not only due to restrictions in read length, but also because amplification (both in solution and solid-phase) favors smaller fragments over longer ones. In addition to the observation that RNA hydrolysis is more straightforward and less prone to sequence bias than DNA fragmentation, it can mitigate some of the biases that can be introduced during the conversion to cDNA by RTs (see below). As such, RNA fragmentation reduces random priming bias during cDNA synthesis, likely by limiting secondary structure formation, and enables a more equal coverage of the 5′ and 3′ transcript ends .2+ or Mg2+, is sufficient for efficient hydrolysis , single-stranded RNA (ssRNA) can also be cleaved by modulating the salt and RNA concentration . HoweverRNA requires conversion to DNA for most applications, whether it is for cloning or for sequencing. Direct sequencing of RNA has been reported  and is s−6–10−8 for DNA polymerases (switching mechanism at the 5′ end of the RNA template) method, in which the dC tail preferentially appended by RT is used for hybridization with an oligo(G)-containing primer for second strand synthesis , remains thermostable and processive, and was shown to be completely compatible with RNA-seq, leading to nearly identical coverage and expression profiles as an established RT  polymerase, the most often used tailing enzyme in these approaches, is however significantly affected by terminal stemloop structures , the standard approach relies on either oligo(dT) or random primers. Homopolymer stretches, mostly poly(A), can be added to substrates without poly(A)-tail to enable oligo(dT) priming . The Escructures ,95 and tructures  of the sructures ,97, and ructures , the metin silico  primers after fragmentation) with specific sequences . These tails reportedly only modestly influence priming ,100,101,template .How sensitive are these methods for the generation of single-cell libraries? As alluded to above, the greatest strength of oligo(dT)-based priming is its ability to combine ribodepletion and priming of mRNA for reverse transcription in a single step, which is why this strategy has become by far the most widespread starting point for single-cell transcriptome library synthesis . The HuaA popular alternative to oligo(dT) or (tagged) random primers is the ligation of adaptors at the RNA level prior to cDNA synthesis. Crucially, this method preserves the directionality of RNA molecules and is thus a stranded approach, provided that the necessary end groups are protected. Combined with an rRNA-masking oligo, RNA ligation can also be used in a single-cell setup .2, three-carbon or six-carbon spacers) for the 5′ ligation reaction. The trRnl2 does tend to deadenylate the App-adaptors and to subsequently adenylate the substrate RNA molecule, leading to substrate concatamers and circles; the K227Q point mutant lacks this activity, leading to less side products   Figure . To avoiAlternatively, the 5′ adaptor can be ligated to the first strand cDNA after degradation of the RNA strand, for instance through alkaline treatment  or RNaseBoth 3′ and 5′ end RNA (or ssDNA) ligation biases are significant and have been extensively documented, mostly in the context of small RNA sequencing ,114–117.Alternatively, to avoid the biases associated with 5′ end ligation by Rnl1, 3′ adaptor-ligated products  can be reverse transcribed as per usual, but then circularized by a pre-adenylated ssDNA ligase (‘CircLigase’) and PCR amplified Figure . This CiRNA ligation can be a challenge when substrate RNA molecules are modified at their 5′ or 3′ ends. Under the right conditions, 2′-O-methyl groups are not an issue for trRnl2 . In contE. coli RNase H digestion, which creates nicks in the RNA strand of the RNA–DNA duplex after first-strand synthesis, E. coli DNA pol I, which can use these nicked sites as primer for 5′→3′ DNA synthesis while displacing and degrading the RNA in the same direction through its 5′→3′ activity, and E. coli DNA ligase, which ligates the nicks. Overhangs are degraded through the 5′→3′ and 3′→5′ nuclease activities of the DNA pol I, leaving blunt ended DNA.Second strand synthesis is generally performed using the very efficient and versatile classical Gubler and Hoffman method , or one-Although this classical Gubler and Hoffman second strand synthesis method is not intrinsically strand specific, the polarity of transcripts can be retained by replacing dTTP with dUTP in the second strand synthesis reaction. The introduction of uracil blocks high-fidelity amplification of the second strand in the PCR step , and comIf specific sequences are incorporated prior to second strand synthesis, for instance through RNA ligation or SMART-type template switching, double-stranded DNA (dsDNA) can be generated from the single-stranded cDNA through PCR amplification. This approach is sensitive and suitable for second strand generation in single-cell setups ,48,106.In many applications, DNA is the starting point of the library synthesis. This can be genomic DNA, immunoprecipitated DNA such as in ChIP (chromatin immunoprecipitation) or MeDIP (methylated DNA immunoprecipitation), targeted sequence captured DNA or any other method where a specific subset of sequences requires library synthesis. Alternatively, existing DNA collections such as the human ORFeome  can alsoDNA fragmentation is required for short-read sequencing library construction when starting from molecules longer the required platform range. Additionally, fragmentation is also an intrinsic part of fragment library generation for expression or protein–protein interaction screening. Compared to RNA, the double-stranded configuration and lower reactivity of the deoxyribose in DNA makes it more difficult to hydrolyze. Hence, one generally resorts to physical shearing methods using sonication, nebulization or acoustic shearing; or to enzymatic methods.With sonication or nebulization, the size range tends to be wide and difficult to adapt, resulting in low yields; sample heating in the process may additionally lead to DNA damage and strand dissociation . The CovEarly reports (from 2006) employing DNase I digestion to randomly fragment DNA described the method as essentially bias-free ,134. TheRandom priming of DNA material has been done as well . While s2+ to induce double-strand breaks after uracil doping . Y-shaped adaptors have the added advantage that molecules in the library are tagged with a different adaptor sequence on the 5′ and 3′ end  is mostly used for this purpose . Generald Figure . For seqd Figure . A variaUracil-containing adaptors have been useful in various other alternative approaches for DNA adaptor ligation. The DLAF (directly ligate adaptors to first-strand cDNA) method for ligation of adaptors to ssDNA (e.g. first-strand cDNA) uses double-stranded ‘splint’ adaptors containing single-stranded overhangs of five to six random nucleotides for hybridization-based ligation with T4 DNA ligase . As the The ligation-based schemes with the Y-shaped or hairpin adaptors mentioned above are efficient, and the formation of side products is strongly reduced. Nevertheless, the procedure requires much sample-handling and is incompatible with very limited inputs (e.g. DNA from single cells). In contrast, the clever ‘tagmentation’ approach, which uses an engineered hyperactive Tn5 transposase for simultaneous DNA fragmentation and tag (or adaptor) insertion, is fast and suited for low input amounts . A generMore difficult input sample types require adapted protocols. Highly degraded DNA, especially from ancient or FFPE samples, has a higher proportion of ssDNA and the input material is often only available in trace amounts. Single-strand compatible methods include the Swift Biosciences approach of sequential ligation as outlined above , but taihttp://dx.doi.org/10.1101/165449), which has a mutated uracil-binding pocket to avoid stalling at uracils. Second, bisulfite treatment can also result in the loss of cytosine bases and subsequent DNA breakage at the resulting abasic sites, consequently inducing DNA fragmentation (http://dx.doi.org/10.1101/165449).Analyzing the methylation status of the genome requires the construction of libraries of methylated DNA. The golden standard for genome-wide profiling of 5′-methylcytosines (5mC), the most established DNA methylation mark, relies on chemical treatment of  DNA with bisulfite . Bisulfientation . As thishttp://dx.doi.org/10.1101/165449) and requires relatively high input amounts. In addition, it necessitates adaptor synthesis with full cytosine-to-5′-methylcytosine replacement in order to avoid uracil conversion of the adaptor (http://dx.doi.org/10.1101/165449) and have pushed the starting material limit down to the nanogram and even single-cell .Although the above whole-genome bisulfite sequencing methods allow for full genome-scanning of methylation status, only a fraction of the genome is generally  methylated, and it can be more efficient and cost-effective to focus on methylome-relevant regions instead of whole genomes. One strategy involves the digestion of genomic DNA with methylation-insensitive restriction enzymes that recognize CG-rich sites, such as CCGG in the case of MspI, thereby enabling enrichment of regions with high CpG content. Combined with bisulfite treatment of digested and size-selected fragments, such reduced bisulfite representation sequencing (RRBS) allows the monitoring of a reproducible subset of CpG islands in genomes ,167. EnrAlternatives to bisulfite-based strategies focus on pulldown of methylome-relevant regions using methyl-binding domains ,173 or 5et al. systematically compared polymerase performance for sequencing library amplification over a range of different contexts, revealing considerable differences in fidelity, yield, sequence-sensitivity and processivity between the 23 polymerases tested  limit the breadth of applications of such amplification-free methods. The Turner lab demonstrated the superiority of PCR-free sequencing library construction using simple ligation of Y-shaped adaptors that contain all the necessary sequences required for Illumina sequencing, in the sequencing of extremely AT- or GC-rich bacterial genomes . Similarin vitro transcription of DNA molecules encoding a T7 promotor, a system routinely used for microarray sample preparation linear amplification methods to amplify the material while minimizing artifacts. Because of the exponential aspect of PCR, errors quickly propagate and biases are exacerbated; this cumulative effect is less extreme for linear methods relying on the T7 RNA polymerase or strand-displacing enzymes such as the BstI or ϕ29 polymerases. The bacteriophage T7 RNA polymerase methods rely on paration ,189 ; a feature exploited intensely in the context of C0t analysis  to estimate size, complexity and repetitiveness of genomes before sequencing became the norm , however, enabled simple and robust digestion of double-stranded abundant species (http://doi.org/10.1101/241349).Historically, these issues have been addressed in several ways; repetitive sequences, which are often hypermethylated ,215, havthe norm ,221. As the norm ,223. All species    . Similarag-seq’) . Consideag-seq’) ,241.Aside from barcoding individual samples, another relatively recent development involves the tagging of individual molecules in single samples through the incorporation of degenerate regions in adaptors or PCR primers before PCR. Such molecular tags  have been tremendously useful to differentiate identical molecules originating from the same PCR template (PCR duplicates), and those that were present at the onset of the library preparation . SequencAs a final note, for libraries of amplicons intended for Illumina sequencing, it may be convenient to introduce sequences of varying lengths just upstream of the first amplicon bases to be sequenced. Illumina platforms strongly rely on the equality of base distributions in the first few cycles for phasing and cluster calling; the sequencing of libraries where the first position is the same in all clusters on the flow cell is therefore very inefficient  Figure . This isMost molecular manipulations during library preparation introduce some form of bias, resulting in a skewed representation of the original molecules. This can affect accurate quantification, lead to false results, or mask potentially interesting patterns. The nature, source and impact of these library preparation biases in various settings has been subjected to intense research in the past decade, and steadily, strategies to address some of these issues are emerging. As such, TGIRTs and the reverse RTX are showing promise in replacing the inherently more error-prone retroviral RTs, and the benefits of internal randomization of adaptors during RNA ligation have become clear. For DNA amplification, the KAPA HiFi enzyme still tops the charts when it comes to PCR, and with careful PCR cycle number monitoring and the incorporation of MTs, PCR-related data distortions can be attenuated. Linear amplification methods such as MDA and MALBAC are being increasingly used, especially in single-cell setups. The implementation of nucleases such as the DSN or Cas9 for library normalization opens up the prospect of capturing rare molecules in complex samples. These valuable insights should help the researcher to make informed choices when it comes to library generation.While protocols or enzymes of some commercial kits are generally updated with time, these adaptations often lag behind current knowledge; customizing the library preparation is almost always a better option and generally leads to libraries of superior quality. With continuous effort, it is expected that better enzymes or even simple protocol changes will continue to improve such procedures, enabling more accurate systematic assessment of genome, transcriptome and proteome function.


Organelle genomes are among the most sequenced kinds of chromosome. This is largely because they are small and widely used in molecular studies, but also because next-generation sequencing technologies made sequencing easier, faster, and cheaper. However, studies of organelle RNA have not kept pace with those of DNA, despite huge amounts of freely available eukaryotic RNA-sequencing (RNA-seq) data. Little is known about organelle transcription in nonmodel species, and most of the available eukaryotic RNA-seq data have not been mined for organelle transcripts. Here, we use publicly available RNA-seq experiments to investigate organelle transcription in 30 diverse plastid-bearing protists with varying organelle genomic architectures. Mapping RNA-seq data to organelle genomes revealed pervasive, genome-wide transcription, regardless of the taxonomic grouping, gene organization, or noncoding content. For every species analyzed, transcripts covered ≥85% of the mitochondrial and/or plastid genomes , indicating that most of the organelle DNA—coding and noncoding—is transcriptionally active. These results follow earlier studies of model species showing that organellar transcription is coupled and ubiquitous across the genome, requiring significant downstream processing of polycistronic transcripts. Our findings suggest that noncoding organelle DNA can be transcriptionally active, raising questions about the underlying function of these transcripts and underscoring the utility of publicly available RNA-seq data for recovering complete genome sequences. If pervasive transcription is also found in bigger organelle genomes (>105 kb) and across a broader range of eukaryotes, this could indicate that noncoding organelle RNAs are regulating fundamental processes within eukaryotic cells. Mitochondrial and plastid DNAs (mtDNA and ptDNAs) are among the most sequenced and best-studied types of chromosome . This isNext-generation sequencing (NGS) technologies, ballooning genetic databanks, and new bioinformatics tools have made it easier, faster, and cheaper to sequence, assemble, and analyze organelle transcriptomes . The Nati.e., transcription of the entire organelle genome, including coding and noncoding regions . Our explorations reveal pervasive, genome-wide organelle transcription among disparate plastid-bearing protists and highlight the potential of freely available RNA-seq data for organelle research.https://www.ncbi.nlm.nih.gov/sra) and the organelle DNAs from the Organelle Genome Resources section of NCBI (https://www.ncbi.nlm.nih.gov/genome/organelle/) or GenBank (https://www.ncbi.nlm.nih.gov/genbank/). See Supplemental Material, Table S1 for detailed information on the RNA-seq and organelle genome data we downloaded, including accession numbers, sequencing technologies, read counts, organelle DNA features, and the strains used for genome sequencing and RNA-seq.By scanning the SRA (using NCBI’s Taxonomy Browser), we identified 30 plastid-bearing species for which there are complete mitochondrial and/or plastid genome sequences and abundant RNA-seq data. We downloaded the RNA-seq reads from the SRA (We mapped the RNA-seq reads to the corresponding organelle genomes using Bowtie 2  implemenhttps://www.ncbi.nlm.nih.gov/sra/) and their respective accession numbers are listed in Table S1. Figure S1 depicts transcription maps for all 30 species analyzed.The datasets analyzed in this study are available in the SRA database  plastids . The organelle genomic architectures of these species vary in structure , size (5.8–105 kb), gene repertoire , gene arrangement , and coding content  . We made sure that the RNA-seq and corresponding organelle genome data always came from the same species, but, in a few instances, they were from different strains of the same species (Table S1). It should be stressed that most of the RNA-seq experiments we sourced were generated under stress-related conditions and often using very different protocols (Table S1). But these caveats did not seem to impede the mapping experiments.After an exhaustive search of GenBank and the SRA, we identified 30 plastid-bearing protists for which there were abundant RNA-seq data as well as complete mtDNA and/or ptDNA sequences with lengths of ∼100 kb or smaller. We did not include larger organelle DNAs because we wanted to reconstruct entire organelle genomes from the transcript data alone and assumed that it would be easier to do so using RNA from small to moderately sized organelle genomes. Moreover, organelle DNAs >100 kb are typically repeat rich , making plastids  as well i.e., mtDNA vs. ptDNA), or underlying genomic architecture . Not only was the overall read coverage high across the various mitochondrial and plastid genomes (85–100%), but the mean read depth (reads/nt), with few exceptions, was consistently high, ranging from 5 to >23,000 (bona fide organelle-derived transcripts (see below), these findings suggest that transcription is pervasive, spanning most or all of the organelle genome, including noncoding regions, in a diversity of plastid-bearing protists.Indeed, for each of the species and genomes we explored, the raw RNA-seq reads covered the entire or nearly entire organelle DNA, regardless of taxonomic grouping, organelle type  it extended into and encompassed the entire mitochondrial telomeres, as has been observed for linear mtDNAs from other lineages , red algae , dinoflagellate algae , and diatom algae , as well as in both compact and moderately bloated mtDNAs (57–90% coding) .The RNA-seq data of the circular-mapping mtDNAs from the green alga  regions . Full tre.g., Toxoplasma gondii) , 98% of which was represented at the RNA level . Overall, these data, alongside previous experiments   and thatNA level . The seceriments , show thNannochloropsis oceanica is a model candidate for harvesting biofuels and, thus, the currently available RNA-seq experiments for this species are aimed at better understanding its growth and lipid production, and maximizing its economic potential , suggesting that the libraries used for the cDNA sequencing were depauperate in organelle-derived transcripts. This could be because RNA-seq libraries are often filtered for polyadenylated transcripts (mRNA) and in some lineages organelle RNA can become unstable upon polyadenylation . There is also a danger of confusing the transcripts of nuclear mitochondrial-like sequences and nuclear plastid-like sequences for genuine organelle RNA, but this is less of an issue for protists than it is for animals and land plants  is that mitochondrial and plastid genomes are pervasively transcribed . This ismusculus . Some hamusculus . HoweverSymbiodinium minutum mtDNA (∼327 kb) (Chlamydomonas reinhardtii ptDNA (∼204 kb), and other bloated organelle DNAs  organelle genomes, such as land plant mtDNAs (lle DNAs  and not lle DNAs , but nond plants ] or moreThe primary goal of this study was to show that entire organelle genome sequences from diverse plastid-containing species can be reconstructed from publicly available RNA-seq datasets within the SRA, as has been previously argued . On thiswww.g3journal.org/lookup/suppl/doi:10.1534/g3.117.300290/-/DC1.Supplemental material is available online at Click here for additional data file.Click here for additional data file.


Recent advances in sequencing technologies led to the identification of a plethora of different genes and several hundreds of amino acid recoding edited positions. Changes in editing rates of some of these positions were associated with diseases such as atherosclerosis, myopathy, epilepsy, major depression disorder, schizophrenia and other mental disorders as well as cancer and brain tumors. This review article summarizes our current knowledge on that front and presents glycine receptor C-to-U RNA editing as a first example of disease-associated increased RNA editing that includes assessment of disease mechanisms of the corresponding gene product in an animal model. The conversion of genetic information from the DNA to the protein level includes the transcription of a given gene into RNA and its subsequent translation. Protein expression is tightly regulated at each step, and depends on the presence and activity of a bulk of proteins, which in most cases are themselves regulated by further proteins, hormones, metabolites or other modulators. Thus, any cell may generate nearly infinite expression profiles being able e.g., to differentiate in a tissue-dependent manner during development or to adapt to changes in environmental conditions. The variability of a genome is further increased by posttranscriptional modifications that change the genetic information during expression and lead to alternative variants of a given protein. Posttranscriptional modifications may occur at each step of gene expression and are carried out by evolutionarily conserved mechanisms. Commonly known posttranscriptional modifications are the splicing events in the nucleus, RNA editing and the specific insertion of a selenocysteine instead of a cysteine during translation. This review article focuses on RNA editing of nuclear transcripts in higher eukaryotes, its mechanisms, systemic relevance and association with development and disease.Trypanosoma where the mRNA of the mitochondrial gene coding for cox-2 was found to differ from its expected sequence in terms of four missing uridines at the 5′ end in comparison to the respective DNA sequence , which is dependent on the APOBEC  gene family and auxiliary proteins. Enzymatic deamination of adenosine yields inosine (A-to-I) and is dependent on the ADAR (“adenosine deaminase acting on RNA”) enzyme gene family. U-to-C and G-to-A RNA editing may also occur due to amination of the respective bases  were identified in the mammalian genome with ADAR1 being the first one  and the more distally located cysteine residues C451 and C516 (human ADAR2). Unlike APOBEC, members of the ADAR family are able to catalyze deamination without the aid of additional auxiliary proteins . Furthermore, there are some important indications that ADAR-mediated RNA editing modulates the efficiency of RNAi pathways including the generation of microRNAs (miRNAs) and the processing of small interfering RNAs (siRNAs)  within the transmembrane domain 6 of human Kv1.1 ; Bransteitter et al., APOBEC gene family. Thanks to the pioneer work of Harold C. Smith, the role of APOBEC-1 and auxiliary proteins in pre-mRNA editing of apolipoprotein B (ApoB) was elucidated in great detail  promoters rather than being a cytosine deaminase  belong to the ligand-gated ion channel gene superfamily and are glycine-gated chloride channels which were involved in TLE, inflammatory pain sensitization, autism spectrum disorder and glioblastoma  that require investigation at the functional level; some of which may turn out to be the master regulatory targets of the editing machinery and disease-promoting cellular programs. Thus, we are just at begining of a new era of research that will ultimately need to identify functional changes of gene products due to amino acid recoding RNA editing and identify molecular key players that are masters and hence could signal upstream of, and regulate RNA processing machines. Furthermore, using animal models, in depth characterization of the functional consequences at both molecular and cellular levels are required to identify mechanisms that are responsible for the diverse phenotypes and disease symptomatology. The fact that there is an increasing number of patients with unknown cause of disease further underscores the need for characterization of causes and effects of epitranscriptional pathophysiological deviation from normal RNA processing, hopefully providing a future good starting point for the development of novel, genuine, therapeutic concepts.RNA editing is an evolutionarily conserved process that has several advantages over gene mutation. Like alternative RNA splicing, the extent of RNA editing may be regulated, resulting in increased genomic variance. Furthermore, mRNA variability can be regulated whereas gene mutations are permanent. It seems as if there is reasonable evidence supporting altered RNA processing in a wide range of disease, including paroxysmal and neoplastic disorders of the brain, neuromuscular disease, as well as lung and liver disease and breast cancer. The examples discussed in this review article actually point to a critical role of deviation from normal RNA processing/editing in disease ontology and/or the epitranscriptomics of disease. However, there are several hundreds more amino acid recoding RNA editing events in many different gene products including gene regulatory transcripts (see All authors contributed to writing the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Saccharomyces cerevisiae rapidly switches between two alternative pre-rRNA processing pathways depending on the environmental conditions. Our findings reveal a new level of complexity in the regulation of ribosome biogenesis.Most microorganisms are exposed to the constantly and often rapidly changing environment. As such they evolved mechanisms to balance their metabolism and energy expenditure with the resources available to them. When re-sources become scarce or conditions turn out to be unfavourable for growth, cells reduce their metabolism and energy usage to survive. One of the major energy consuming processes in the cell is ribosome biogenesis. Unsurprisingly, cells encountering adverse conditions immediately shut down production of new ribosomes. It is well established that nutrient depletion leads to a rapid repression of transcription of the genes encoding ribosomal proteins, ribosome biogenesis factors as well as ribosomal RNA (rRNA). However, if pre-rRNA processing and ribosome assembly are regulated post-transcriptionally remains largely unclear. We have recently uncovered that the yeast  The process of ribosome synthesis is conserved from prokaryotes to eukaryotes. It starts by the transcription of a large pre-rRNA that is subsequently processed into mature rRNAs and assembled with ribosomal proteins into the ribosomal subunits. During the processing, the pre-rRNA is cleaved at several positions, trimmed by exonucleases and covalently modified at a number of sites. The making of ribosomes in eukaryotes requires a coordinated action of all three RNA polymerases, dozens of small nucleolar RNAs (snoRNAs) and hundreds of proteins - accessory ribosome biogenesis factors and ~80 ribosomal proteins. It was estimated that in a fast growing yeast cell up to 60% of all transcription represents transcription of the ribosomal RNA (rRNA) by RNA polymerase I. In addition, transcription of the ribosomal protein genes accounts for 50% of the RNA polymerase II activity. Furthermore, the RNA polymerase III synthesises the 5S rRNA. The Tor complex 1 (TORC1) pathway controls the activity of all three RNA polymerases in concordance with the nutrient availability. When nutrients are abundant, the Tor1 kinase is active and promotes high levels of transcription. A depletion of nutrients leads to inactivation of TORC1 and cessation of the transcription of rDNA and ribosomal protein genes.in vivo pulse-chase experiments, indicating that the A3-pathway is not productive. The Northern blot analyses showed that the pre-rRNA processing and assembly of both ribosomal subunits is stalled after the first cleavages. While in favourable conditions the 20S and 27S-A2 pre-rRNA (produced by a cleavage at the site A2) are rapidly matured into ribosomal subunits, the 23S pre-rRNA is not further processed and the synthesis of the small ribosomal subunit seems to be stalled at this step. Similarly, the 27S-A3 is only quickly converted to 27S-B pre-rRNA and the processing also stalls at this point and no new large ribosomal subunits are produced .We recently observed that nutrient depletion leads to a striking change in the pre-rRNA processing pattern. We showed that yeast switches promptly between the two alternative ribosome biogenesis pathways in response to nutrients availability and certain environmental stresses. We named the two alternative pre-rRNA processing pathways after the specific cleavage site that distinguishes them as A2-pathway and A3-pathway, respectively. Under favourable growth conditions, the pre-rRNA is cleaved at the site A2 to split the large precursor into 20S and 27S-A2 pre-rRNAs (A2-pathway). In contrast, under unfavourable growth conditions, the pre-rRNA is cleaved at the site A3 yielding the 23S and 27S-A3 pre-rRNAs (A3-pathway). In agreement with previous observations, the transcription of rDNA also decreases. However, we found that the synthesis of pre-rRNA, while strongly reduced, continues for days but the produced pre-rRNA is cleaved differently. We estimate that the rDNA transcription is reduced to ~2% after the depletion of glucose. This still represents a significant amount of transcription, as rDNA is very highly transcribed - each active rDNA unit can be transcribed simultaneously by 50- 100 RNA polymerases I and there are 75-100 active rDNA units in yeast. Significantly, we could not detect any new ribosomes being made in our Interestingly, the existence of the 23S pre-rRNA was reported two decades ago but its functional relevance remained highly controversial. As the 23S is readily detectable in the yeast strains with mutations affecting ribosome biogenesis, it has been mostly dismissed as a product of aberrant processing. Our results show that it is a physiologically relevant intermediate produced under unfavourable conditions. The meaning of the 23S appearance in the mutant strains needs to be critically re-evaluated as it might represent a general stress response to defects in ribosome biogenesis rather than a direct consequence of the particular mutation in the yeast strain.The nutrients availability and stress sensing in yeast is mediated by the four kinases Tor1, PKA, Snf1 and Pho85 via their signalling cascades. We found that the switch between the alternative pre-rRNA processing pathways is controlled by the Tor1 kinase, or more specifically the TORC1. Inactivation of TORC1 by rapamycin caused a rapid switch from A2- to A3-pathway. The TORC1 signalling pathway has two major branches, one controlled by the Sch9 kinase  and the other controlled by the Tap42 kinase. The Sch9 kinase regulates all three RNA polymerases, directly controlling the synthesis of the pre-rRNA and mRNAs for ribosomal proteins and ribosome biogenesis factors (RiBi genes). Surprisingly, we discovered that both Sch9 and Tap42 functions are dispensable for the switch in pre-rRNA processing, indicating that TORC1 has another so far unrecognized or unidentified effector regulating directly the pre-rRNA processing. We therefore looked at the casein kinase 2 (CK2), which is a component of the early pre-ribosomes. Importantly, the CK2 kinase is also a component of the CURI complex consisting of CK2, Utp22, Rrp7 and Ifh1. Whereas the Utp22 and Rrp7 are essential bona-fide ribosome biogenesis factors, the Ifh1 is a transcriptional coactivator required for the efficient transcription of ribosomal protein genes. Therefore, the CURI complex was therefore proposed to link ribosome biogenesis with the expression of ribosomal proteins. Thus CK2 represents are good candidate for direct regulation of the pre-rRNA processing. We showed that inhibition of the CK2 activity resulted in a fast switch from A2- to A3-pathway. Interestingly, small amounts of 27S-A2 pre-rRNA (produced by the A2-pathway) were still detectable at the initial time point after CK2 inhibition indicating that CK2 kinase activity is required also for the further downstream processing of the 27S-A2 precursor. Our proteomic analyses of pre-ribosomes identified a number of proteins with changes in the phosphorylation at various sites, including potential CK2 target sites. Further investigation of the identified candidates is needed to gain insight into the link between TORC1 and CK2.Our observations raise many important questions regarding the underlying mechanism of the switch. Can the switch in the pre-rRNA processing be explained without the need to invoke a new target of TORC1? The transcription of rDNA and expression of ribosomal proteins are reduced strongly after nutrient depletion. Is it the smaller number of RNA polymerases I or their speed with which they are passing through rDNA together with the changed availability of ribosomal proteins that affect co-transcriptional folding of the pre-rRNA to physically block the processing at the A2 site? We addressed these possibilities by several experiments. First, we showed that the switch in processing occurs regardless whether the rDNA is transcribed by RNA polymerase I or II. Second, acute sequestering of the catalytic subunit of RNA polymerase I by the anchor-away technique, which effectively reduced the number of available RNA polymerases I, did not elicit the switch from A2 to A3 pathway. Third, using the strain with RNA polymerase I insensitive to rapamycin we showed that sustained transcription of rDNA does not prevent switch to A3 pathway. We also showed that the content of ribosomal proteins in the pre-ribosomes produced by the A3-pathway is not changed or even increased compared to A2-pathway pre-ribosomes. This demonstrates that a general lack of ribosomal proteins after reduction of their expression is also unlikely the cause of the change in the pre-rRNA processing. All these observations together with the rapidity of the switch point to a direct control of the pre-rRNA processing. Nevertheless, it is not clear if there is indeed just one target protein that is fully responsible for the regulation of the cleavage site choice. Pre-ribosomes are immensely dynamic and complex machines. It is plausible that subtle rearrangements of the pre-ribosomes, driven by post-translational protein modifications, affect the choice of the cleavage site.Finally, what is the advantage for yeast to switch to a non-productive pre-rRNA processing? One explanation could be an evolutionary advantage increasing the competitive fitness of the organism. A complete abolishment of rDNA transcription causes dissolution of the nucleoli, the ribosome factories, with ribosome biogenesis factors diffusing away. Restarting the ribosome production with an "empty factory" will take significantly longer than with a factory still running at minimal level. In nature, even a small delay can lose the battle with other faster species.Our findings reveal a new mode of regulation of ribosome biogenesis. Intriguingly, different cleavage sites can also be used in the human pre-rRNA processing. Whether a mechanism similar to yeast is conserved and used by cells depending on their proliferation status remains to be seen. As a dysregulated ribosome biogenesis is observed in many cancers, a better understanding of its regulation might have far reaching implications also for human health.


Reoviridae family with segmented double-stranded RNA genomes achieve this challenging task by forming RNA networks of segments prior to their recruitment into the assembling capsid albeit direct evidence is still lacking. Here, we investigated the capability of virus recovery by preformed complexes of ten RNA segments of H Virus (EHDV), a Reoviridae member, by transcribing exact T7 cDNA copies of genomic RNA segments in a single in vitro reaction followed by transfection of mammalian cells. The data obtained was further confirmed by RNA complexes generated from Bluetongue virus, another family member. Formation of RNA complexes was demonstrated by sucrose gradient ultracentrifugation, and RNA-RNA interactions inherent to the formation of the RNA complexes were demonstrated by electrophoretic mobility shift assay. Further, we showed that disruption of RNA complex formation inhibits virus recovery, confirming that recruitment of complete RNA networks is essential for packaging and consequently, virus recovery. This efficient reverse genetics system will allow further understanding of evolutionary relationships of Reoviridae members and may also contribute to development of antiviral molecules.Viruses with segmented RNA genomes must package the correct number of segments for synthesis of infectious virus particles. Recent studies suggest that the members of the  Reoviridae family) are vectored to particular vertebrate species  by arthropods  replicating in both insect and mammalian hosts. The two most common orbiviruses are Bluetongue virus (BTV) and virus (EHDV), each with multiple serotypes. Both BTV and EHDV are transmitted from animal to animal by the same Culicoides vectors (gnats) and are responsible for considerable economic losses to international livestock industries [Orbiviruses  double-stranded RNA (dsRNA) segments, the majority of which encode only a single protein product. The outer capsid is composed of two major proteins, VP2 and VP5, which surround the inner capsid or viral core formed by two other major proteins, VP7 and VP3 as well as the transcription complex of three minor proteins VP1, VP4 and VP6 that are closely associated with the viral genomic dsRNA segments [in vitro packaging of the ten ssRNA segments of BTV follows a selective and sequential order, which requires specific RNA-RNA interactions and complex formation. These data implied that a preassembled network of RNA segments in vivo may be necessary prior to genomic RNA packaging of BTV and related Orbiviruses [in vitro transcripts. Subsequently, ten RNA transcripts were synthesized in a single reaction to allow formation of supramolecular complexes of RNA segments and tested their infectivity in mammalian cells. The underlying RNA-RNA interactions, visualized by native gel electrophoresis, were further fractionated to separate complete RNA complexes from incomplete RNA complexes and free RNAs by sucrose gradient ultracentrifugation. Altogether, our data indicated that ssRNA segments undergo a cascade of RNA interactions required for complex formation and follow the proposed order of genome packaging for BTV, a closely related orbivirus. This RG system will also facilitate further studies on the reassortment with other serotypes or other species of the genus and to identify the regions likely to possess sorting and packaging signals.Recent studies have reported that the iviruses , 7. In tin vitro co-transcription products of the EHDV-7 segments showed that ssRNA bands were synthesized in correct sizes similar to the authentic transcripts derived from wild type (WT) viral core  are infectious, confluent BSR monolayers were transfected first with S1, S4, and S9  along with S3 (VP3), S5 (NS1) and S8 (NS2) as reported previously [in vitro co-synthesized transcript mixture is highly efficient.Emerging data on RNA assortment and packaging studies of segmented RNA viruses indicate that supramolecular RNA complexes are likely to form by specific RNA-RNA interactions, allowing selection of viral RNA segments during or prior to genome packaging and encapsidation -13. To ie Figure . Howevereviously , 16 and Although the above data demonstrates that the mixture of co-transcribed RNA segments is infectious, it was necessary to prove that a mixture of individually synthesized and purified segments is also infectious in BSR cells as reported for other orbiviruses , 17-20. NdeI restriction site (T to A mutation at position nt416) and a mutant virus was successfully recovered with the S10 mutant together with the S1-S9 wild type transcripts. No changes could be detected in the dsRNA profile of the mutant S10 when compared with that of the WT virus , which was further confirmed by sequencing (data not shown). The successful recovery of virus particles from transfection of individual RNA segments confirmed the ability of the RNA transcripts to generate viable virus, albeit with a lower number of virus plaques compared with the co-synthesized transcripts at an approximately equal amount of transfected RNA segments.To ensure that the rescued virus was not from contaminating WT EHDV-7, a silent mutation in the S10 open reading frame (ORF) was introduced to abolish the s Figure . RT-PCR in-vitro co-synthesized RNA transcripts yielded viral plaques that started to appear at 48hpt, and 100% CPE at 96hpt  were detectable mainly in two fractions at the middle of the gradient, fractions #6 and #7 Figure . ComplexThe infectivity of the fractionated RNA complexes was also tested by transfection of BSR cells as described. Typical viral plaques were recovered from fractions #6 and #7 while few or no virus plaques developed from the rest of the fractions Figure . These rThe sucrose gradient data indicated that the ssRNA complexes are formed in stages. Further our previous data also demonstrated that BTV ssRNA segments interact with each other in a highly specific manner which is probably necessary for forming a network of ssRNA molecules prior to packaging . To deteIn the combinations of three RNA segment interaction assays, distinct RNA complexes were detected when S5 or S6 was included in the reaction with segments S7, S8 and S10  were mixed in a single transcription reaction Figure .via RNA-RNA interactions and that the infectious complexes were sufficiently stable to tolerate isolation by sucrose gradient centrifugation. It was therefore imperative to confirm that disruption of RNA complexes would affect the virus recovery. To validate this, the 10 ssRNA transcripts were co-synthesized and products were divided into two aliquots. While one aliquot was subjected to heat treatment followed by flash cooling as described in Materials and Methods, the other was kept as control. BSR cells were then transfected with both aliquots and incubated for plaque formation. Results showed that the heated RNA products generated a markedly reduced number of plaques when compared to the untreated control  upon transfection of cells. Virus recovery was achieved not only at a higher number but were also detected earlier than that of the individually synthesized ssRNAs. These results highlighted that the key factor for the successful recovery of infectious viruses was due to ssRNA complexes allowing specific RNA-RNA interactions prior to transfection as suggested previously , 7, 24. Intersegment interaction of all BTV segments is important in orbivirus genome sorting and packaging as earlier proposed in the cell-free assembly assay system  and confSeparation of 10 ssRNA complexes of EHDV-7 and BTV-1 from the incomplete RNA complexes provided further evidence that higher order RNA complexes are formed through specific RNA-RNA interactions. Such events must occur prior to RNA complex assembly. The isolation of smaller complexes corresponding to small and medium size class of RNA segments has also supported our previous findings that BTV RNA complex are formed through a coordinated interactions of RNA starting from forming the smaller complex of smaller segments and recruits the next size classes , 7.in vitro assembly of the BTV capsid, it was demonstrated that ssRNA copies of all 10 genomic segments were needed to generate an infectious viral core and that in absence of certain segments ssRNAs were not packaged [Using a unique packaged , 24. It packaged , 26. In packaged  and simipackaged , 27, 28.The successful recovery of viable virus using approaches we introduced here has proven the likelihood of the hypothesis that RNA segments make RNA contacts for correct genome organization, and suggests that a similar pathway linked to RNA-RNA interactions and complex formation occurs between related orbiviruses.Reoviridae and opened up an opportunity to investigate evolutionary relationship between different members of orbivirus species.Understanding how orbivirus organizes its multiple genetic material into one compact complex of RNA ready for another round of virus life cycle either for encapsidation or gene expression is fundamental for an effective control of this economically important virus. Broader studies on RNA-RNA interactions of segmented viruses can also be used to effectively inhibit network formation through designer oligonucleotides, siRNA or virus delivery system and thereby virus multiplication. This study has also established an improved and facile RG system for 2.BSR cells, a BHK 21 clone derivative of baby hamster kidney cells (American Type Culture Collection) were grown in Dulbecco modified Eagle medium supplemented with 5% fetal calf serum (FCS), penicillin, streptomycin and amphotericin B at 35°C with 5% COBluetongue virus serotype 1 (BTV-1) South African reference strain and Epizootic hemorrhagic disease virus serotype 7 (EHDV-7) (CSIRO 775 strain) were plaque purified and amplified in BSR cell line. Virus stocks were maintained by infecting BSR cells at multiplicity of infection (MOI) of 0.1 and harvested at 100% cytopathic effect (CPE).NdeI restriction site was generated by overlapping polymerase chain reaction (PCR) through site-directed mutagenesis and treated with DpnI to digest the parental plasmid [Full-length cDNA copies of each genomic segment of EHDV-7 flanked by T7 promoter and restriction enzymes were synthesized using the full-length amplification of cDNAs (FLAC) methodas described  with som plasmid . Complet plasmid .S-adenosylmethionine, 6 mM dithiothreitol, 9 mM MgCl2, 0.5U/μl RNasin Plus (Promega) [For synthesis of EHDV and BTV co-transcripts, exact cDNA copies of EHDV-7 or BTV-1 genome segments S1-S10 were used as templates in one single transcription reaction using mMESSAGE mMACHINE T7 Ultra Kit (Ambion) according to manufacturer's procedures. For generation of transcripts expressing the proteins necessary for primary replication, S1, S3, S4, S6, S8 and S9 plasmids were co-transcribed to facilitate the synthesis of VP1, VP3, VP4, VP6, NS1 and NS2, respectively in the transfected cells. For synthesis of RNA transcripts from viral core, EHDV cores were purified according to the modified methods described previously , 31. BriPromega) . Both tr5) and incubated for 16-18 h followed by a second round of transfection with ~1.5 μg of 10ssRNA co-transcripts or authentic viral transcripts and overlaid with 0.8% agarose gel in DMEM with 1% FCS. The cells were further incubated for up to 72 h and observed for virus plaque formation. To confirm virus recovery, plaques from the reverse genetics were picked and amplified and genomic dsRNAs were extracted, and analysed on a 10% native PAGEFor the reverse genetics system, ~1 μg of the co-synthesized RNA products  were transfected directly onto a 90% confluent cells  for 3 h at 37°C followed by RNase free DNase 1 treatment. Immediately after, the reaction mixture was loaded on a 15% to 65% continuous sucrose gradient for 90 min at 200,000 ×gat 4 °C, using a TLS55 rotor. Fractions were collected from the top and used for the second transfection of BSR cells pre-transfected with  transcripts for recovery of viable virus. The fractionated complexes were analyzed on a 1% denaturing agarose gel electrophoresis in MOPS buffer and formaldehyde to check the integrity of transcription.For RNA complex formation,150 ng linearized plasmid of each segments were co-transcribed (S1-S10) in a buffer containing 40mM Tris, pH7.5; 10mM MgCl2; 20mM NaCl2, 3mM spermidine, 50mM DTT; 5mM each rNTPs; 10U RNase inhibitor and 40U of T7 RNA polymerase (Thermo Scientific) for 3 h at 37°C followed by RNase free DNase 1 treatment. Immediately after DNase treatment, detection of RNA complexes was done by electrophoretic mobility shift assay (EMSA). Electrophoresis gel was run for 180 min at 150 V in TBM buffer  and stained with 0.01% (w/v) ethidium bromide. The integrity of transcribed RNA was checked routinely by denaturing gel electrophoresis.For RNA-RNA interactions of EHDV RNA segments, 150 ng linearized plasmid of each segments (S5-S10) were transcribed either in pairs or combinations of multiple segments. RNA transcription was carried out in a buffer containing 40mM Tris, pH7.5; 10mM MgClEHDV RNA segments were allowed to form a complex by co-transcription of S1-S10 as described. Immediately after DNase treatment, an aliquot was collected and heat treated at 70°C for 1.5 minutes and flash cooled on ice. Another aliquot was treated by standard phenol chloroform extraction and purified RNAs were suspended in RNase free water before heating at 70°C for 1.5 minutes and flash cooled. Both aliquots were used for the second transfection of BSR for recovery of viable virus. The integrity of transcribed RNA was checked by denaturing gel electrophoresis.


Such a possibility may be considered a remote prospect by majority of virologists because of the prevailing perspective that positive strand RNA viruses do not need to synthesize DNA to complete their life cycle neither do they have any reverse transcriptase to generate a complementary DNA. Since there seems to be no chance of reverse transcription , it becomes easy to infer that a DNA stage (i) does not exist and (ii) is not functionally important. We argue that these inferences are not true. The current paradigm is that DNA transcribed from the RNA of these viruses does not exist in the host genome; and it requires a robust evidence of POSTRAITE to refute this generally held belief. In this paper we will demonstrate that such affirmation already exists.Scientific literature is filled with papers that don't even consider the possibility of RNA to DNA synthesis in these viruses and their host genome integration. But we propose that there is a genuine likelihood despite the absence of reverse transcriptase and integrase in their genomes. In order to give a scientific basis to this apparently radical proposition, we need to establish atleast one obligatory and one supportive postulate viz. (i) experimental evidence of a positive strand RNA viral genome (devoid of reverse transcriptase and integrase) integration into host genome (obligatory) and (ii) speculation of possible function/s such an integration may serve the virus (supportive). If, there is evidence of the virus antigens being found in the nuclei of the host cells, our proposition may imbibe further strength. The mechanism of host genome integration, in principle, can be true with many other diseases where the viral genome has sequence based similarities to certain regions of the host genome. This conceptual model is coherent and may pave way to deciphering mechanisms of many complex viral diseases (in addition to Zika virus mediated brain defects). But for such a mechanism to be true, POSTRAITE needs to be a biological verity. Establishing the likelihood of such a biological reality is the basic aim of the present paper and can be achieved by finding satisfactory answers for the above mentioned obligatory and supporting postulates.Aedes mosquito genomes) by Suzuki et al.  have not been reported to reverse transcribe into cDNA. As an example of Zika virus, an RNA polymerase on the NS5 subunit of the Zika virus polyprotein has been indicated for viral genome replication (RNA-dependent-RNA polymerase activity), without the involvement of reverse transcriptase (Godoy et al., i et al. . Their fi et al. . This inIn an interesting study, Klenerman et al.  reportedRNAs are relatively unstable molecules; for that reason the genomes of RNA viruses are susceptible to various host cell mechanisms aimed at exonucleolytic mRNA decay/destruction (Moon et al., Though the complete lifecycle of positive strand RNA viruses is thought to be exclusively cytoplasmic, their presence in the host cell nuclei have, nevertheless, been documented (Buckley and Gould, Though the supposition of positive strand RNA virus genome integration to host genome is currently considered improbable but this phenomenon is, nevertheless, a reality and has already been reported. This concept has a lot of information to offer from safety concerns of RNA based gene therapies to viral etiology of previously thought non-infectious diseases. The etiobiology of neurodegenerative disease may further be understood under this umbrella (Li et al., MF and AK: conceived the idea, wrote the manuscript, and revised the manuscript; HS, VP, and PK: wrote and revised the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.