Formalin-fixed and paraffin-embedded (FFPE) blocks held in clinical laboratories are an invaluable resource for clinical research, especially in the era of personalized medicine. It is important to accurately quantitate gene expression with degraded and small amounts of total RNA from FFPE materials.High concordance in transcript quantifications were shown between FF and FFPE samples using the same kit. The gene expression using the TaKaRa kit showed a difference with other kits, which may be due to the different principle of rRNA depletion or the amount of input total RNA. For seriously degraded RNA from FFPE samples, libraries could be constructed with as low as 50 ng of total RNA, although there was residual rRNA in the libraries. Data analysis with HISAT demonstrated that the unique mapping ratio, percentage of exons in unique mapping reads and number of detected genes decreased along with the decreasing quality of input RNA.The method of RNA library construction with rRNA depletion can be used for clinical FFPE samples. For degraded and low-input RNA samples, it is still possible to obtain repeatable RNA expression profiling but with a low unique mapping ratio and high residual rRNA. With the development of massive parallel sequencing, RNA-Seq has become an useful tool for transcriptome analysis, as well as for the identification of novel transcripts, SNPs, gene fusion and alternative splicing events . FormaliRNA-seq requires the enrichment of mature mRNAs, or the depletion of highly abundant ribosomal RNAs (rRNAs) from total RNA before sequencing. RNAs from FFPE materials are usually degraded to small sizes without the 3′poly (A) tail; moreover, recent studies suggest that certain functionally important mRNAs are non-poly (A) RNAs . TherefoFor RNA-seq of FFPE samples, rRNA depletion from total RNA is the optimal solution. Nucleic acids extracted from FFPE blocks are fragmented and chemically modified, making them controversial to use in molecular diagnosis. rRNA depletion protocols could keep as much information as possible from the total RNA. There are several rRNA depletion protocols. The first method that is commonly used hybridizes the rRNA to a DNA probe and degrades the rRNA: DNA hybrids using RNase H. In the second method, rRNA is captured by complementary DNAs, which are coupled to paramagnetic beads, and the mixture is removed from the reaction . SeveralIn this study, we compared four FFPE RNA library preparation kits  based on two principles of rRNA depletion, with degraded RNA from FFPE samples and paired FF samples as starting materials Fig. . Takara 2+. And then, 1st strand and 2nd strand cDNA was synthesized successively, of which 2nd strand cDNA was marked by dUTP. The dAMP was then added to the 3′-end of dscDNA fragments, and 3′-dTMP adapters are ligated to 3′-dAMP library fragments. After fragment separation, PCR amplification was performed on the final library.KAPA kit has been validated for library construction from 25 ng to 1 μg of total RNA. This kit using Oligo Hybridization and rRNA Depletion eliminated the effect of ribosomal RNA on library. The rRNA duplexed to DNA oligos was digested by RNase H treatment. Before the cDNA synthesis, hybridization oligos were removed from the sample by DNase I digestion. The rRNA-depleted RNA is eluted and fragmented to the desired size using high temperature in the presence of Mg + RNA. So we used the first few steps of Vaths™ Total RNA-seq (H/M/R) Library Prep Kit protocol to get the poly(A) + RNA. The removal of ribosomal RNA from both Vazyme and QIAGEN kits was similar to KAPA kit.Vazyme kit is mainly applicable to the total RNA of human, mouse and rat with a starting value of 0.1–1 μg, and also applicable to the construction of the library for the degradation of RNA samples of the above species. QIAGEN Kit need 1–100 ng enriched, poly(A)In addition, we evaluated the effect of bioanalysis tools on the total mapping rate, unique mapping rate, exon percentage and number of detected genes using FF samples and FFPE samples. HISAT  allows scientists to align reads to a genome, assemble transcripts, compute the abundance of these transcripts in each sample and compare experiments to identify differentially expressed genes and transcripts . STAR  = 0.96 for the TaKaRa kit, R (FF vs FFPE) = 0.97 for the Vazyme and QIAGEN kits, R (FF vs FFPE) = 0.98 for the KAPA kit). In addition, we compared the consistency of FF (or FFPE) samples between different kits. The consistency among the KAPA, Vazyme and QIAGEN kits was higher than that of the four kits. Among the four kits, KAPA and QIAGEN showed the highest consistency, not only for FF samples (R (KAPA vs. QIAGEN) = 0.97) but also for FFPE samples (R (KAPA vs. QIAGEN) = 0.96). The gene expression using the TaKaRa kit showed a difference with the other kits, especially in the FFPE sample (R (TaKaRa vs. KAPA) = 0.61, R (TaKaRa vs. Vazyme) = 0.77, R (TaKaRa vs. QIAGEN) = 0.66.), which might due to the different principle of rRNA depletion or the amount of input total RNA. The similar results were got from the test of samples 13, 14 and 15, showing in Additional file RNA-seq is an established platform for quantifying gene expression using high-quality RNA. To evaluate the gene expression performance of the FF and FFPE samples across the four kits, we compared the consistency of transcript quantification from matched pairs of FF and FFPE samples using the same kit Figure . The resTo clarify the difference between the TaKaRa kit and any one of the other three kits in FFPE samples and FF samples, we chose the differential transcripts, which had more than a 50-fold difference. There were a total of 37 differential transcripts in the FF sample and 58 differential transcripts in the FFPE sample  of most FFPE samples was so poor that it was not sensitive enough to evaluate the quality of RNA from degraded FFPE samples. Here, we used the reference of DV200%, the percentage of RNA fragments > 200 nucleotides, to assess FFPE RNA quality. We tested the two kits with 15 different qualities of FFPE RNA samples . The reproducibility performance of five low-quality clinical samples was shown in Table RNA-seq of clinical FFPE samples could provide more important and reliable information for discovery and validation of biomarkers. Previous research , 18 and The difference in the principle of rRNA depletion could still result in a difference in library yield, residual rRNA, the percent of exons in unique mapping reads and transcript quantification. The KAPA kit, QIAGEN kit and Vazyme kit used the same principle of rRNA depletion, so a high concordance of transcript quantification was shown among the three kits. These three kits removed rRNA from total RNA before cDNA synthesis, using a rRNA probe to combine rRNA and then digesting rRNA by RNase H and removing the rRNA probe by DNase I. The library of the TaKaRa kit showed a difference with higher yield, residual rRNA, exon percentage and the number of detected genes, using a lower RNA input compared to the other three kits, which might result from the unique method of rRNA depletion. The workflow used in the TaKaRa kit takes advantage of a novel technology allowing removal of ribosomal cDNA (cDNA fragments originating from rRNA molecules) after cDNA synthesis using probes specific to mammalian rRNA. The specificity and number of probes could have an effect on the rRNA depletion efficiency, especially in low-quality RNA of FFPE samples, so there was higher residual rRNA in the TaKaRa library. In our results, we found that there were 9 transcripts  that had very high expression (FPKM was more than 1000) in the TaKaRa libraries, while their FPKM were very low in the other kits. These transcripts included mitochondrially encoded 16S RNA, mitochondrially encoded 12S RNA, small nucleolar RNA, the 5S ribosomal pseudogene, and 5S ribosomal 9, all of which were noncoding RNAs. These transcripts detected in the TaKaRa libraries were due to low efficiency of rRNA depletion. For the same reason, we only obtained fewer clean data with the TaKaRa kit compared to the KAPA kit when using poor-quality RNA to construct libraries. The shortcoming of high residual rRNA would waste sequencing reads and increase the cost of RNA-seq.On the other hand, the strategy of rRNA depletion after cDNA synthesis made the TaKaRa kit especially well-suited for working with very small quantities of total RNA. A similar strategy was adopted not only by TaKaRa kit but also by the Nugen kit . We trieThe concordance between FF and FFPE samples is excellent for any of four RNA-seq library kits. Therefore, FFPE could be used for the RNA-seq profiling with the methods of rRNA removal from total RNA. The difference between TaKaRa and the other three kits for FF and FFPE samples might be due to the different principle of rRNA removal or different input of total RNA. Both the KAPA and TaKaRa kits allowed low total RNA input and consistent transcript quantification was obtained between the lowest input and a higher input. When the quality of input total RNA was high, in which the DV 200% was more than 30%, both the KAPA and TaKaRa kits performed well. When the DV 200% of degraded RNA was less than 30%, lower quality data with lower unique mapping and lower exon percentage or failure of library construction will be evident. The TaKaRa RNA-seq library kits could be used for RNA-seq library construction of low-quality and low-quantity FFPE samples. Although the rRNA residual is a little higher, it could detect more transcripts and showed good reproducibility with low-quality and low-quantity FFPE samples.2 in air atmosphere, and culture media RPMI 1640  contained 10% fetal bovine serum (FBS) . About 1 × 107 cells were treated with 10% neutral formalin for 1 h and then the fixed cells were collected by centrifugation of 3000 rpm for 10 min . The cells were suspended with 0.5 ml 1xPBS and then was added into 2% agarose gel. The mixture was cooled and solidified into block. The GM12878 cell block was processed according to standard formalin-fixed and paraffin-embedded (FFPE) methods [GM12878 cell line, which was originated from human B-lymphoblastoid cells and now often used as control sample in NGS, was obtained from Cobioer Biological Technology  and cultured using the recommended culture conditions. Briefly, GM12878 was incubated at 37 °C in an incubator  with 5% COThere were 5 FF clinical samples sample 1 to 5) and 22 FFPE samples (sample 6 to 27). FFPE sample 13, 14 and 15 were samples from native external quality assessment. All the 24 clinical samples  were collected from the Cancer Hospital Chinese Academy of Medical Sciences & Peking Union Medical College. FFPE tissue slides were examined by expert pathologists including a minimum of 20% cancer cells. All these cancer samples from patients who signed the informed consent forms and were allowed to be used in other researches , and three 5um-sections of the FFPE samples were used to extract total RNA using AllPrep DNA/RNA FFPE Kit , both according to the manufacturer’s recommendations. We could get enough RNAs from above samples just following the detailed user guide of the kits.The final RNA concentration was typically measured by Qubit RNA HS assay kit . The integrity of RNA was determined by the RNA integrity number (RIN) and DV200 (percentage of RNA fragments greater than 200 nt) with Eukaryote total RNA pico 6000 Assay of the 2100 Bioanalyzer (Agilent).We used four RNA library Preparation kits including TaKaRa™ SMARTer® Stranded Total RNA-Seq Kit v2 , KAPA Stranded RNA-Seq Kit with RiboErase (HMR) , Vaths™ Total RNA-seq (H/M/R) Library Prep Kit for illumina  and Qiagen™ Stranded Total RNA Lib Kit  kits.We constructed libraries strictly according to the user guide of each kit and libraries prepared with the above four kits were sequenced using 150-bp paired-end runs on Illumina NGS systems (HiSeq® 2500 and Xten) after quantification by the Qubit dsDNA Assay Kit and determination of fragment length by the Agilent 2100 Bioanalyzer with the DNA 1000 Kit.Raw data (raw reads) of fastq format were firstly processed through in-house scripts. In this step, raw reads, Q20, Q30 and GC content were calculated. Then, Trimmomatic v0.36  was usedAdditional file 1: Figure S1. The quality of the RNA samples from GM12878 fresh cells and paired FFPE sample. Figure S2. The quality of the RNA samples from the fifteen clinical samples. Table S1. Comparison of four RNA library preparation kits for FFPE samples. Table S2. The consistency of transcript quantification of four RNA library preparation kits with FFPE samples. Table S3. The list of differentially expressed transcripts between TaKaRa and other three kits. Table S4. Comparison of mapping data using HISAT and STAR in FF and FFPE samples. Table S5. Clinical information of samples


RNA editing is a co/posttranscriptional modification mechanism that increases the diversity of transcripts, with potential functional consequences. The advent of next-generation sequencing technologies has enabled the identification of RNA edits at unprecedented throughput and resolution. However, our knowledge of RNA editing in swine is still limited.Here, we utilized RES-Scanner to identify RNA editing sites in the brain, subcutaneous fat, heart, liver, muscle, lung and ovary in three 180-day-old Large White gilts based on matched strand-specific RNA sequencing and whole-genome resequencing datasets. In total, we identified 74863 editing sites, and 92.1% of these sites caused adenosine-to-guanosine (A-to-G) conversion. Most A-to-G sites were located in noncoding regions and generally had low editing levels. In total, 151 A-to-G sites were detected in coding regions (CDS), including 94 sites that could lead to nonsynonymous amino acid changes. We provide further evidence supporting a previous observation that pig transcriptomes are highly editable at PRE-1 elements. The number of A-to-G editing sites ranged from 4155 (muscle) to 25001 (brain) across the seven tissues. The expression levels of the ADAR enzymes could explain some but not all of this variation across tissues. The functional analysis of the genes with tissue-specific editing sites in each tissue revealed that RNA editing might play important roles in tissue function. Specifically, more pathways showed significant enrichment in the fat and liver than in other tissues, while no pathway was enriched in the muscle.This study identified a total of 74863 nonredundant RNA editing sites in seven tissues and revealed the potential importance of RNA editing in tissue function. Our findings largely extend the porcine editome and enhance our understanding of RNA editing in swine.The online version of this article (10.1186/s40104-019-0326-9) contains supplementary material, which is available to authorized users. After qualification by an Agilent 2100 Bioanalyzer and real-time PCR, each library preparation was sequenced on an Illumina HiSeq platform by the Novogene Bioinformatics Technology Cooperation , and 150 bp paired-end reads were generated.Muscle DNA was extracted from the three pigs mentioned above and used to construct three DNA libraries . All downstream analyses were based on high-quality filtered data.Sus scrofa 10.2.87 was downloaded from Ensembl (ftp://ftp.ensembl.org/pub/release-87/fasta/sus_scrofa/dna/). The genomic feature position files and Sus_scrofa.dbSNP145.gtf were prepared using custom scripts on the basis of Sus_scrofa.Sscrofa10.2.87.gtf (ftp://ftp.ensembl.org/pub/release-87/gtf/sus_scrofa/) and Sus_scrofa.vcf (ftp://ftp.ensembl.org/pub/release-87/variation/vcf/sus_scrofa/) following the RES-Scanner user manual.The detection of RNA editing sites was conducted using RES-Scanner . ParametA candidate RNA editing site must meet the following conditions: 1) the genomic site is homozygous with a Bayesian probability exceeding 0.95 and is supported by at least 10 reads; 2) at least three RNA reads differ from the genomic genotype; 3) the site has an editing level ≥ 0.05 and must be supported by at least one RNA read in the middle of its length; 4) the binomial test false discovery rate (FDR) of this site must be < 0.05; and 5) the site is not located within homopolymeric regions of five or more residues and within six intronic bases of a splice site. All thresholds used for the identification of the RNA editing sites were the default parameters of RES-Scanner.In total, 64 editing sites randomly selected from all sites identified in Brain3 were used to assess the reliability of RES-Scanner. RNA isolated from Brain3 was used for reverse transcription by a PrimeScript™ RT Reagent Kit  according to the manufacturer’s instructions. DNA was extracted from Muscle3. The primers were designed by the National Center for Biotechnology Information (NCBI) Primer–BLAST and synthesized by Thermo Fisher Scientific Inc.  to amplify appropriate fragments for Sanger sequencing . Then, HTseq [To quantify the porcine gene expression level, Tophat2  was appln, HTseq  was usedn, HTseq , was calq-value < 0.05 were considered significantly enriched.We used the clusterProfiler package  to conduSus scrofa reference genome. A summary of the deep sequencing process is provided in Table To accurately detect the candidate RNA editing sites at the transcriptome-wide level in swine, strand-specific poly(A)-positive RNA sequencing and matched DNA sequencing were performed using seven tissues from three pigs. After quality trimming, on average, 74.8 million reads were generated from each sample, with an average mapping rate of 85.6%. Approximately 88.1% of the 1338 million pass-filter reads obtained from the DNA sequencing were successfully aligned to the To fully utilize our sequencing data, the possible RNA editing events were detected with RES-Scanner, which requires matched RNA-seq and DNA-seq data to rule out genomic single nucleotide variants and automatically separates the plus-strand alignments from the minus-strand alignments for the strand-specific RNA-seq libraries to identify the correct genomic loci of origin. Using this method, in total, 163315 RNA editing events at 74863 sites were detected within our datasets , including 68934 A-to-G editing sites  sites were covered by at least one EST sequence, and 45243 (60.4%) sites were found in at least one RNA edited EST clone. The validation rates significantly varied across the different RNA editing types as follows: 63.7% (43901/68934) of the A-to-G editing sites were supported by at least one RNA edited EST sequence, while less than 43% of the RNA editing sites were validated for each of the 11 non-A-to-G types (range from 14.9% to 42.5%)  as follows: more editing sites were detected on SSC1, SSC6 and SSC13 than on the other SSCs . Then, we ranked the chromosomes according to the difference between the normalized chromosome length  and observed RNA editing sites. The top four chromosomes were SSC6, SSCX, SSC1 and SSC11. Given the large number of RNA editing sites, we were able to determine whether there was a sequence preference in the vicinity of the detected A-to-G sites. Consistent with the known attributes of ADAR substrates, the nucleotide immediately upstream of the editing site showed significantly depleted G, while the downstream nucleotide favored G  and DARNED (https://darned.ucc.ie/) databases. Using 50 bp flanking regions of the porcine RNA editing sites, BLAST analyses were performed against 50 bp flanking regions of the human sites. The sites supported by the ESTs with e-values < 0.001, identity > 85% and alignment length > 50 bp were considered conserved editing sites [In this study, 12 types of RNA editing were detected, including all possible base substitutions as follows: A-to-G, A-to-C, A-to-T, C-to-A, C-to-G, C-to-T, G-to-A, G-to-C, G-to-T, T-to-A, T-to-C and T-to-G  predictget mRNA . The topget mRNA  demonstrpulation . This fiWhile concentrating on the distribution of A-to-G sites within a gene model, we found that 92.8% of the 5420 protein-coding genes undergoing RNA editing were edited in only one genic region Fig. c. While The number of A-to-G sites greatly varied across tissues and pigs Fig. a. Accordq-value = 9.07 × 10−5), “lipid modification” in the fat , “cardiac muscle cell differentiation” in the heart , “carboxylic acid catabolic process” in the liver , “vesicle organization” in the lung , “actomyosin structure organization” in the muscle , and “cell cycle G2/M phase transition” in the ovary . The top 5 GO terms of each tissue according to the q-values are displayed in Additional file q-value = 4.33 × 10−2), “AMPK signaling pathway” in the fat , and “fatty acid metabolism”  in the liver. Specifically, more pathways were enriched in the fat and liver than in the other tissues, while no pathway was enriched in the muscle. Similar results were obtained even after excluding the tissue-specific expressed genes  and the global RNA editing level  at the sample level. This analysis revealed a strong and statistically significant correlation between both the number of editing sites  and the global level of editing  with the expression of ADAR1 . Then, by repeating this analysis at the tissue group level, statistically significant correlations were found only for ADAR1   . A certaConsistent with previous studies in primates , 6, 40, GRIK2, I/V in COPA, I/V in KCNA1, T/A in ACOT4, R/G in GRIA2, I/V, I/M and N/S in HTR2C and R/G in GRIA3 have been identified in pigs in other studies [GRIK2 are considered important for regulating calcium permeability [COPA, I/V editing was detected in the current seven tissues, and its hypoediting is associated with hepatocellular carcinoma pathogenesis in humans [KCNA1 via RNA editing affects the action potential shape, signal propagation and the firing pattern by accelerating the KCNA1 channel recovering from inactivation [ACOT4 was also found to be edited in fat, but the function of its editing is unknown. The R/G recoding in GRIA2 and GRIA3 leads to faster desensitization recovery [HTR2C can reduce the efficacy of the interaction between receptors and their G protein [In our research, the intergenic regions contained the largest number of RNA editing sites, which is different from humans, where intronic editing sites are the most common. A possible explanation for the difference is that the porcine genome annotation is of poor quality compared with the human annotation, and many unannotated genes are present (25322 pig genes vs 63305 human genes in Ensembl release 87). However, the abundance of RNA editing within the intronic and intergenic regions is unexpected because our RNA-seq libraries were purified using oligo(dT) beads to enrich polyadenylated mRNAs that had undergone splicing. This finding could be partially attributed to intron retention . Moreove studies . The threability . For COPn humans . The I/Vtivation . Consistrecovery . The RNA protein . In addiAlthough obvious variation was observed across the editing profiles of the samples, the intrapopulation variability in the editing levels is lower than that across tissues, suggesting a similarity to gene expression regulation . By compADAR1 and ADAR2 were highly expressed in the brain and lung, and ADAR3 was exclusively expressed in the brain [ADARs, the tendency to change did not perfectly align. This observation shows that the editing enzymes play an important role in RNA editing regulation but cannot explain all modification.The ADAR enzymes have been shown to be essential for normal life and development in mice , 9. Conshe brain , 14. AltThis study identified 74863 RNA editing sites using matched RNA and DNA sequencing data and revealed the comprehensive profile of RNA editing in pigs. We also provide further evidence supporting a previous observation that pig transcriptomes are highly editable in PRE-1 SINE elements. Furthermore, the functional analysis of the genes with tissue-specific editing sites in each tissue revealed the potentially functional importance of RNA editing in porcine tissue regulation. Our study largely extends the list of RNA editing sites in swine and provides deeper insight into the characteristics of the pig editome.Additional file 1:Figure S1. Overview of the experimental design. Figure S2. Results of the Sanger sequencing validation of all 64 selected editing sites. For each candidate editing site (indicated by genome coordinates and red arrow), raw chromatograms of sequences derived from cDNA and matched DNA samples are shown. Unverified sites are marked with an asterisk. Figure S3. Distribution of RNA editing types in repetitive sequences. Figure S4. Distribution of A-to-G sites across major repeat families. Figure S5. Overlap of RNA editing sites among the three samples of each tissue. Figure S6. Dot plot of the top five enriched GO biological process terms in each tissue. Dot color indicates statistical significance of the enrichment ; dot size represents the fraction of genes annotated to each term. Figure S7. Dot plot of the enriched KEGG pathways after removing the tissue-specific expressed genes. Dot color indicates the statistical significance of the enrichment ; dot size represents the fraction of genes annotated to each term. Figure S8. RNA editing vs expression of ADARs in all samples. a) We correlated the number of A-to-G sites and ADAR1 expression levels in all samples (n = 21). b) We correlated the number of A-to-G sites and ADAR2 expression levels in all samples (n = 21). c) and d) We calculated the correlations between the overall RNA editing levels and the expression values of ADAR1 and ADAR2 in all samples (n = 21). Correlation coefficients (r) and P-values are shown in each graph. Figure S9. RNA editing vs the expression of ADARs in tissue groups. a) We correlated the number of A-to-G sites and ADAR1 expression levels in all tissue groups (n = 7). b) We correlated the number of A-to-G sites and ADAR2 expression levels in all tissue groups (n = 7). c) and d) We calculated the correlations between the overall RNA editing levels and the expression values of ADAR1 and ADAR2 in tissue groups (n = 7). Correlation coefficients (r) and P-values are displayed in each graph. (PDF 87057 kb)Additional file 2:Table S1. Primers used in the Sanger sequencing. (XLSX 135 kb)Additional file 3:Table S2. RNA editing sites identified in this study. (XLSX 6798 kb)Additional file 4:Table S3. Clustering of A-to-G sites in each sample. (XLSX 9 kb)Additional file 5:Table S4. Conserved A-to-G editing sites between pigs and humans. (XLSX 25 kb)Additional file 6:Table S5. Top 20 miRNAs according to the number of edited targets. (XLSX 9 kb)Additional file 7:Table S6. A-to-G sites resulting in amino acid changes. (XLSX 13 kb)Additional file 8Table S7. RNA editing sites shared by the seven examined tissues. (XLSX 27 kb)Additional file 9Table S8. Statistics of the tissue-specific A-to-G editing sites. (XLSX 9 kb)


The RNA exosome fulfills important functions in the processing and degradation of numerous RNAs species. However, the mechanisms of recruitment to its various nuclear substrates are poorly understood. Using Epstein-Barr virus mRNAs as a model, we have discovered a novel function for the splicing factor SRSF3 in the quality control of nuclear mRNAs. We have found that viral mRNAs generated from intronless genes are particularly unstable due to their degradation by the nuclear RNA exosome. This effect is counteracted by the viral RNA-binding protein EB2 which stabilizes these mRNAs in the nucleus and stimulates both their export to the cytoplasm and their translation. In the absence of EB2, SRSF3 participates in the destabilization of these viral RNAs by interacting with both the RNA exosome and its adaptor complex NEXT. Taken together, our results provide direct evidence for a connection between the splicing machinery and mRNA decay mediated by the RNA exosome. Our results suggest that SRSF3 aids the nuclear RNA exosome and the NEXT complex in the recognition and degradation of certain mRNAs. The adequately processed mRNPs are then competent for their export to the cytoplasm where they will be translated3. All these processes are intimately linked: 5′-end capping, splicing and 3′-end maturation occur co-transcriptionally due to the important role played by the carboxy-terminal domain (CTD) of RNA polymerase II’s (RNAP-II) largest subunit5. However, mRNA processing is error-prone and improperly matured mRNPs have to be degraded in order to avoid the synthesis of nonfunctional proteins. While the synthesis of the mRNPs progresses, surveillance mechanisms that detect malformed mRNPs are also operating. Aberrant mRNPs6 that fail to pass the quality control steps are retained in the nucleus and degraded by different ribonucleases. In human cells, two major degradation pathways are responsible for mRNA decay of defective transcripts in the nucleus: (i) the 5′-3′ exoribonuclease XRN2, together with the decapping factor DCP2, and (ii) the RNA exosome8.In eukaryotic cells, functional mRNA expression is a multi-step process in which the DNA-encoded message is transcribed into a pre-mRNA molecule that undergoes numerous modifications such as 5′-end capping, splicing, 3′-end cleavage and polyadenylation, together with the assembly of diverse factors required for the formation of a messenger ribonucleoprotein particle (mRNP)10. This complex recognizes and degrades improperly-formed RNAs in the nucleus11. To exert its function, the nuclear RNA exosome uses cofactors that directly stimulate its enzymatic activity and serve as adaptors for its many substrates12. Several proteins or complexes have recently been identified for their capacity to recruit the nuclear RNA exosome onto its target RNAs. In the yeast system for which several exosome-associated adaptors have been characterized, it appears that the nuclear RNA exosome depends largely on the activities of the TRAMP (Trf4p/5p-Air1p/2p-Mtr4p polyadenylation) complex19. However, in human, at least three distinct RNA exosome adaptors have recently been identified. All critically depends on the RNA helicase hMTR4: the hTRAMP complex, which is homologous to the yeast complex and localizes in the nucleolus22, the PAXT (poly(A) tail exosome targeting) complex formed by hMTR4-ZFC3H1 and the NEXT (nuclear exosome targeting) complex which is not conserved in yeast and localizes in the nucleoplasm25. The RBM7 protein, a putative pre-mRNA splicing factor, and the ZCCHC8 (zinc finger CCHC domain-containing protein 8) protein form the NEXT complex. Interestingly, ZCCHC8 has also been shown to interact with the cap-binding complex (CBC) and several members of the SR protein family21, and one study has reported that, in vitro, RBM7 interacts with the splicing factor 3b subunit 2 (SAP145) and the SRSF3 protein26. The interaction between SRSF3 and RBM7 was also found by a proteomic approach27. This suggests that the cap-binding complex and the spliceosome are involved in the recruitment of the RNA exosome to its target RNAs via their interaction with the NEXT complex. Moreover, it was recently demonstrated that the recruitment of the RNA exosome by CBC promotes the degradation of promoter upstream transcripts (PROMPTs)27. The role of the spliceosome in mRNA decay is also suspected because an interaction has been found between hMTR4 and hRRP6 and several components of the spliceosomal U4/U6.U5 tri-snRNP complex28. However, a direct functional link between the splicing reaction and the mRNA decay machinery is lacking.The RNA exosome complex, first described in yeast, is conserved in all eukaryotic cells. In human cells, it is composed of a core of nine subunits which serves as a binding platform for two active ribonucleases - hRRP6 and hDIS3/hRRP44 - that have 3′-5′ RNA exonuclease and endonuclease activities29. EBV persists in an infected host for life by establishing a latent infection in memory B cells30. Following cell differentiation, viral reactivation into the productive cycle leads to the production of progeny viruses that spread to new cells and hosts31. For these two phases of the viral life cycle different viral gene expression programs are used. During latency, a small subset of EBV genes is expressed that allows maintenance of the viral genome and induction of cell proliferation and differentiation in the absence of viral production. Genes expressed during this phase have the same structure as cellular genes. By contrast, during the productive cycle, the structure of a majority of the viral genes expressed during this phase differs from that of cellular genes because most of the viral genes are intronless. This characteristic may represent an handicap for the viral mRNAs in terms of cytoplasmic accumulation and translation efficiency since it is now well documented that pre-mRNA splicing efficiently increases both mRNA export and translation33. However, EBV - like all herpesviruses - encodes a protein called EB2  whose role is to increase the cytoplasmic accumulation and translation of viral mRNAs expressed from intronless genes38. EB2 is an RNA-binding protein (RBP)39 essential for virus replication40 that shuttles between the nucleus and the cytoplasm42. It has been reported to facilitate the nuclear export of viral mRNAs expressed from intronless genes by interacting with the cellular ALYREF and TAP-NXF1/p15 proteins that promote cellular mRNA export42. Thus, EB2 may serve as a bridge between viral RNAs and the cellular export complex (TREX), which is recruited to the 5´-end of cellular RNAs as a result of splicing43. In this model, EB2, like homologous proteins from other herpesviruses, compensates for the absence of splicing of the viral mRNAs expressed from intronless genes, by recruiting the TREX complex. Accordingly, EB2 is dispensable for mRNAs expressed from intron-containing genes. In addition, EB2 is able to inhibit the splicing reaction44 and modify the splicing pattern of specific cellular mRNAs45. The interaction observed between EB2 and SR proteins like SRSF1 (ASF/SF2), SRSF3 (SRp20) and SRSF7 (9G8) is probably involved both in the modifications of specific cellular genes splicing and in the increase in nuclear mRNA export of viral mRNA expressed from intronless genes48. Interestingly, EB2, like its homologous protein ORF57 from Kaposi’s sarcoma-associated herpesvirus, has also been suggested to be involved in increasing mRNA stability. However, the mechanisms involved are not yet understood50.Epstein-Barr virus (EBV), a ubiquitous human herpes virus, is the causative agent of infectious mononucleosis and is also associated with various cancers observed in immuno-competent individuals  as well as in immuno-deficient patients (lymphoma and post-transplant lympho-proliferative diseases)In the present study, we show that in addition to its well-documented role in mRNA export and translation, the viral RNA-binding protein EB2 is also involved in mRNA stability control. In the absence of EB2, its target mRNAs - produced from intronless genes - are rapidly degraded by the nuclear RNA exosome. We have identified the splicing factor SRSF3 as being responsible for the destabilization of these viral mRNAs. Our data reveal, for the first time, that SRSF3 associates with both the NEXT complex and the RNA exosome to induce degradation of mRNAs in the nucleus. The viral protein EB2 appears to interfere with this processus, thus rescuing viral mRNAs from degradation. Our findings reveal an important novel function of the SR protein SRSF3, in the recognition and degradation of some mRNAs.49. To explore this further, cytoplasmic and nuclear RNAs were purified from HEK293EBV∆BMLF1 cells40 which contain a recombinant virus defective for the expression of EB2. The relative amounts of several viral mRNAs whose cytoplasmic accumulation was known to be dependent on EB2  or not (BMRF1) was then measured, by RT-PCR  tail. In the cell nucleus, these determinants interact respectively with the cap-binding complex (CBC) and the nuclear poly(A)-binding protein (PABPN1) to protect the transcripts from exoribonucleases and to promote the export of the mRNAs. To initiate mRNA decay, either one of these two structures must be compromised or the mRNA must be cleaved by endonucleolytic attack. Two main pathways have been described for the degradation of nuclear mRNAs: either the 5′cap structure is removed by the decapping enzyme DCP2 thus allowing the mRNA body to be degraded in the 5′-3′ direction by the XRN2 exoribonuclease or the 3′ poly(A) tail is attacked by a large exonuclease complex known as the RNA exosomeing Fig. . Interesing Fig. . Down-reing Fig. . Taken tBy contrast, when the 5′-3′ decay pathway was down-regulated by siRNAs directed against either DCP2 or XRN2 proteins or both, the stability of the RLuc reporter mRNA was not significally altered compared to what was observed in the case of down-regulation of the RNA exosome pathway Fig. . Thus, nEBV∆BMLF1 cell line, by transfection of a siRNA specifically directed against hRRP40  could also affect the EB2-dependent nuclear accumulation of specific viral mRNAs as well as viral production. For this, expression of the nuclear RNA exosome was down-regulated in the HEK293P40 Fig. . 48 h afP40 Fig. . By contP40 Fig.  as alreated Fig. . However47 and interestingly, we recently found that SRSF3 (SRp20) depletion results in an increase in the cytoplasmic accumulation of EB2’s target mRNAs47. This suggests that EB2 functions by antagonizing SRSF3 and that the splicing factor SRSF3 might affect mRNA stability. To investigate this possibility, the pTRE2-BDLF1 reporter plasmid was transfected into HeLa cells previously depleted of SRSF3 by siRNA treatment  within the same pathway, the Renilla luciferase and BDLF1 reporter plasmids were transfected into HeLa cells from which the RNA exosome (hRRP40 or hRRP46 core components) or/and SRSF3 were depleted Fig. . The nucin vivo, each Flag-tagged subunit of the RNA exosome expressed in HeLa cells was immunoprecipitated, and co-purification of SRSF3 was assessed by western blotting. hRRP6, one of the ribonucleases associated with the core RNA exosome, was used as a positive control. These analyses revealed that SRSF3 was co-immunoprecipitated with each subunit of the RNA exosome  the RNA exosome core subunit hRRP40, (ii) the SRSF3 protein, (iii) the NEXT complex subunits RBM7 and ZCCHC8, or (iv) the RNA helicase hMTR4.27. As shown previously, RT-qPCR analyses revealed that the level of RLuc and BDLF1 mRNAs increased upon depletion of hRRP40 and SRSF3  and SRSF7 (9G8), was down-regulated and the level of the NEXT complex components assessed by western blot Fig. . SRSF3 wIn this study, we demonstrate that some mRNAs synthesized from intronless genes - which is the case for most herpesviruses mRNAs produced during the viral productive cycle - are unstable and are degraded in the nucleus. We also show that the splicing factor SRSF3 is involved in the nuclear destabilization of these intronless mRNAs by the RNA exosome. The RNA exosome complex is recruited onto the target mRNAs by the NEXT complex associated with SRSF3 via its RBM7 component. In addition, SRSF3 appears to play an important role in the stabilization of the NEXT complex. The interaction between the NEXT complex, the RNA exosome and the SRSF3 protein suggests that the mRNA degradation machinery is co-transcriptionally recruited onto the mRNA.54. In the case of EBV, viral mRNAs synthesized from intronless genes, not only accumulate in the cytoplasm but are also stabilized in the cell nucleus. However, it is surprising to observe that the BDLF1 mRNA accumulates in the cytoplasm, although its nuclear half-life is over 7 hours. In effect, it should not be expected to stay in the nucleus for such a long period if it is efficiently exported by EB2. This suggests that EB2 has only a minor role in mRNA export and that its major function is to stabilize its target mRNAs. It has been shown that some RNA molecules can spend hours in the nucleus before being exported to the cytoplasm. mRNA nuclear retention can effectively buffer the burst of mRNA transcription which could induce temporal fluctuations in the level of cytoplasmic mRNA55. Since, in our assay, the BDLF1 gene is under the control of a very strong promoter, we can hypothesize that the high level of BDLF1 mRNA produced may be retained in the nucleus and protected from nuclear degradation when EB2 is expressed.Herpesvirus mRNAs synthesized from intronless genes, inefficiently accumulate in the cytoplasm in the absence of a specific viral protein47, hence preventing the nuclear RNA exosome’s access to the mRNAs that are then protected from the degradation machinery. However, overexpression of EB2 does not appear to inhibit the interaction between SRSF3 and the NEXT complex suggesting that EB2 and RBM7 do not interact with the same domain of SRSF3. Another way in which EB2 could interfere with RNA exosome recruitment, could be by changing the ability of the SRSF3/NEXT complex loaded onto the mRNA, to interact with the RNA exosome. Concomitantly, the interaction between EB2 and the TAP-NXF1/p15 complex favors mRNAs export from the nucleus42 and their translation in the cytoplasm52.Based on our findings, we propose a novel model for the coupling between pre-mRNA splicing and nuclear RNA quality control revealed by our study on the function of the EBV protein EB2 Fig. . In the et al. showing that the nuclear poly(A)-binding protein and the exosome are also implicated in the nuclear degradation of intronless RNAs56.Interestingly, our present work demonstrating the implication of specific components of the spliceosome (i. e. SRSF3) and the RNA exosome in the nuclear degradation of intronless RNAs extends a previous work from Bresson 22 is associated with the NEXT, PAXT and hTRAMP complexes. However, the antibody used in our assays to detect hMTR4 is not very efficient and only detects hMTR4 expressed at a high level. The level of remaining hMTR4, following SRSF3 depletion, is probably insufficient to be detected by the antibody. Nevertheless, the modification of the protein level of the different components of the NEXT complex observed when SRSF3 is depleted, argues in favor of the formation of a stable complex between SRSF3 and NEXT and comforts the hypothesis that SRSF3 plays an important role in RNA exosome activity. In addition, the recently published results of independent proteomics analysis27 demonstrating that RBM7, ZCCHC8, hMTR4 and SRSF3 co-purify, completely support our conclusion that SRSF3 interacts with the NEXT complex and not only with RBM7, outside of the NEXT context.As discussed above, our work provides evidence of an interaction between SRSF3 and the NEXT complex. In this context, it is noteworthy that depletion of SRSF3 induces a concomitant depletion of all three components of the NEXT complex - RBM7, ZCCHC8 and hMTR4. Similarly, depletion of MTR4 correlates with a depletion of both RBM7 and ZCCHC8. Taken together, these observations suggest that SRSF3 contributes to the stabilization of the NEXT complex, hence also increasing the stability of its components. However, from our results, it would appear that the depletion of hMTR4 is complete when SRSF3 is downregulated. This is surprising since only a fraction of the hMTR4 protein pool is expected to be associated with the NEXT complex. In effect, in human cells, the hMTR4 RNA helicase which is required for all activities of the nuclear RNA exosome58. mRNA expression is the result of a coupling between transcription by RNA polymerase II and pre-mRNA processing reactions such as 5′-end capping, splicing, 3′-end maturation and mRNP formation. All these events can affect the localization, translation and degradation of the mRNA. Recent data have shown that the 5′cap of the mRNA associated with the cap-binding complex (CBC) is a type of hub that mediates key events in the life of the mRNA60. Indeed, as recently demonstrated, the CBC is very important both for the recruitment of the mRNA export machinery and the recruitment of the RNA exosome through the NEXT complex61, suggesting a direct link between mRNA 5′-end capping and nuclear RNA surveillance. Interestingly, it has also been shown that the CBC is necessary, although not sufficient, for co-transcriptional spliceosome assembly in yeast62. This demonstration of an essential link between the CBC and spliceosome assembly indicates that 5′-end capping couples transcription to pre-mRNA splicing and probably also to mRNA decay via recruitment of the RNA exosome by specific splicing factors. Our results support a direct coupling between the splicing and the mRNA degradation machineries. Thus, in addition to the recruitment of NEXT by the CBC complex, there appears to be an alternative mode of recruitment of the nuclear RNA exosome involving specific spliceosome components.In the cell nucleus, several types of coding and non-coding RNAs are synthesized and processed. To ensure the survival of cells, only functional competent RNAs must be produced. All the aberrant and inproperly processed transcripts have to be recognized and degraded by RNA quality control mechanisms47. For pTRE2-BDLF1, the EBV BDLF1 CDS was amplified by PCR and cloned into the BamHI and XbaI sites of the pTRE2 expression plasmid (Clontech). The pTet-On vector was supplied by Clontech (Tet-Off and Tet-On gene expression systems). Individual Flag-tagged RNA exosome components, hTRAMP and NEXT subunits were a generous gift from Drs Frederick W. Alt and Torben Heick Jensen63. All plasmid sequences are available upon request.pCMV-Renilla Luciferase, pCMV-HA-SRSF3, pCMV-EB1, pCI-Flag-EB2 and pCMV-BDLF1 have been described elsewhereEBV∆BMLF1 cells40 were maintained in DMEM supplemented with 10% FBS, penicillin-streptomycin and hygromycin B (100 µg/ml). Raji cells were maintained in RPMI supplemented with 10% FBS and penicillin-streptomycin. 48 h prior to DNA transfection, siRNAs were transfected using INTERFERin transfecting reagent (Polyplus-transfection) at 20 nM final concentration, following the manufacturer’s instructions  and penicillin-streptomycin. HEK293EBV∆BMLF1 cells were transfected with pCMV-EB1 in order to activate the viral productive cycle. Cell supernatants were harvested 48 h post-transfection and filtered through a 0.45 -µm pore size filter. Raji cells (1 × 105) were incubated with 1 ml of cell supernatant for 6–8 h at 37 °C in a 24-well plate. Cells were then washed, re-suspended in 1 ml of RPMI supplemented with 10% FBS and penicillin-streptomycin and incubated for an additional 72 h at 37 °C. GFP-expressing Raji cells were quantified by FACS analysis.HEK293HeLa cells were transfected in 60 mm dishes with the pTet-On vector and the pTRE2-BDLF1 plasmid. 24 h after transfection, 1 μg/ml of doxycycline (Sigma-Aldrich) was added to repress transcription. Cells were then harvested at the time points indicated in individual experiments. Actinomycin D treatment of HeLa cells was performed using 5 μg/ml of actinomycin D (Sigma-Aldrich).36 and reverse-transcribed using the qScript cDNA Synthesis Kit (Quanta BioSciences). Standard PCRs were performed using GoTaq DNA polymerase (Promega) and the PCR-amplified fragments analyzed on 2% agarose gels. All PCR reactions were made using several dilutions of the RT products in order to insure that the RT-PCR results were in the linear range of the PCR reaction. We used ß-actin mRNA and U6 snRNA as internal controls. qPCRs were performed using FastStart Universal SYBR Green Master (Rox) (Roche) on an Applied Biosystems 7000 thermocycler. Cycling conditions were 5 min at 95 °C and 45 cycles of 15 s at 95 °C, 30 s at 60 °C on a 96-well thermoblock. This program was followed by melting curve analysis in order to verify the specificity of the PCR products. PCR results were normalized with the parallel amplification of GAPDH mRNA. The various set of primers used in the study are listed in Table Nuclear and cytoplasmic RNAs extraction were performed as previously described2), containing 0.5% Triton X-100 and protease inhibitors (Roche). Cells were gently lysed by sonication and centrifuged  at 4 °C. Supernatants were incubated with 2 μg of a mouse anti‐Flag M2 antibody  or 2 μg of a mouse anti‐HA antibody  overnight at 4 °C, 10 r.p.m. rotation. Protein-antibody complexes were recovered with 40 μl of Protein G Sepharose 4 Fast Flow beads  during 2 h at 4 °C, 10 r.p.m. and recovered complexes were washed extensively with RSB100/0.5% Triton X-100 buffer. RNase treatment was performed by adding 2 μl of RNase A (10 mg/ml) to the incubation mixture where indicated. Immunopurified proteins were then resuspended in SDS‐loading buffer and analysed by western blotting.48 h after transfection, cells from a 100 mm plate were washed in PBS (Life Technologies) and collected in 0.5 ml of RSB100 buffer , containing 0.5% Triton X-100, protease inhibitors (Roche) and RNasin (Promega). Extracts obtained after centrifugation were incubated with 2 μg of a mouse anti‐HA antibody  overnight at 4 °C. PureProteome ProteinA/G Mix Magnetic Beads (Merck Millipore) were mixed and coated with PBS + 10% BSA, supplemented with tRNA and RNasin overnight. After re-equilibration with RSB100 buffer, the beads were added to the lysate for 2 h at 4 °C before extensive washing in RSB100 buffer containing 0.5% Triton X-100 and 0.05% NP-40. Half of the immunoprecipitates were analyzed by Western blotting. The other half were treated 15 min at 55 °C with proteinase K (0.5 mg/ml) and SDS (0.1%), and the RNAs were recovered by phenol/chloroforme extraction and ethanol precipitation.RIPs were carried out from uncrosslinked extracts. Briefly, 1064, rabbit polyclonal anti-EB2 (1:500)40, mouse monoclonal anti-gp350 (1:500)65, rabbit polyclonal anti-Flag , rabbit polyclonal anti-HA , mouse monoclonal anti-SRSF1 , mouse monoclonal anti-SRSF3 , rabbit polyclonal anti-SRSF7 , rabbit polyclonal anti-XRN2 , rabbit polyclonal anti-DCP2 , mouse polyclonal anti-hDIS3 , rabbit polyclonal anti-hRRP40, anti-hRRP46 and anti-hRRP6 , human anti-hMTR4 , rabbit polyclonal anti-ZCCHC8  or rabbit polyclonal anti-RBM7 .Cell lysates were prepared in RSB100/0.5% Triton X-100 and protease inhibitors (Roche) buffer and quantified by Bradford assay. Equivalent amounts of each sample were resolved by SDS-PAGE and analysed by western blotting using the following antibodies: mouse anti-Tubulin , mouse monoclonal anti-EB1 t-test was used to evaluate the statistical difference between samples and significance was evaluated with P-values as follows: * P < 0.05; ** P < 0.01; *** P < 0.001.All results are expressed as means ± standard deviations of experiments independently repeated at least three times. Unpaired Student’s Supplementary Information


Given the ability of RNA-seq to reveal active regions of the genome, detection of RNA-seq SNPs can prove valuable in understanding the phenotypic diversity between populations. Thus, we present a novel computational workflow named VAP  that takes advantage of multiple RNA-seq splice aware aligners to call SNPs in non-human models using RNA-seq data only. We applied VAP to RNA-seq from a highly inbred chicken line and achieved high accuracy when compared with the matching whole genome sequencing (WGS) data. Over 65% of WGS coding variants were identified from RNA-seq. Further, our results discovered SNPs resulting from post transcriptional modifications, such as RNA editing, which may reveal potentially functional variation that would have otherwise been missed in genomic data. Even with the limitation in detecting variants in expressed regions only, our method proves to be a reliable alternative for SNP identification using RNA-seq data. The source code and user manuals are available at  Detection of single nucleotide polymorphisms (SNPs) is an important step in understanding the relationship between genotype and phenotype. The insights achieved with next generation sequencing (NGS) technologies provide an unbiased view of the entire genome, exome or transcriptome at a reasonable cost . Most meRNA-seq is applicable to numerous research studies, such as the quantification of gene expression levels, detection of alternative splicing, allele-specific expression, gene fusions or RNA editing . WorkfloDue to these limitations, we designed a workflow, called VAP , to reliably identify SNPs in RNA-seq in non-human models. VAP takes into consideration current state-of-the-art RNA-seq mapping, variant calling algorithms and the GATK best practices recommended by the Broad Institute , Our worhttps://broadinstitute.github.io/picard/). The SNP calling step uses the GATK toolkit for splitting “N” cigar reads (i.e. splice junction reads), base quality score recalibration and variant detection using the GATK HaplotypeCaller [(Het) is calculated by Heti = aai/ ti; where i is the nucleotide base pair, aai is the alternate read depth at the location i, and ti is the total number of reads at location i. After filtering, the variants were annotated using the ANNOVAR [https://modupeore.github.io/VAP/.peCaller . Lastly, ANNOVAR  and VEP  ANNOVAR  softwareWe obtained RNA-seq and whole genome sequencing (WGS) data for highly inbred Fayoumi chickens from previously published works. For RNA-seq, a total of 117 million 75bp pair-end reads were generated from the brain and liver of 2 chicken embryos at day 12  . Both saGallus gallus 5.0 genome (from Axiom server) using the Axiom Analysis Suite Software (version 3.0.1) following the software’s Best Practices Workflow using recommended settings for agricultural animals. The final results were exported, including a raw VCF of all the genotype calls and a txt file of all variants with > = 97% call rate. The txt file was utilized to filter low quality variants from the raw VCF.Samples were genotyped individually and included 96 samples from two purebred (24 samples) and one crossbred (72 samples) commercial broiler populations. Standard management and husbandry procedures were followed, as approved by the Animal Care and Use Committee (AACUC #(27) 03-12-14R). The samples were genotyped with the ThermoFisher Axiom Chicken Genotyping Array (the Gene Expression Omnibus Accession code GSE131764) . The rawGallus gallus Build 5.0 reference genome and the mapping files were converted to BAM using SAMtools (v 1.4.1). The BAM files were processed, and variants were called using Picard tools (v 2.13.2) and GATK (v 3.8-0-ge9d806836) through the VAP pipeline. We used ANNOVAR (v 2017Jul16) and VEP (v 91) to annotate variants on the basis of gene model from RefSeq, Ensembl and the UCSC Genome Browser. We retained SNPs found with all three mapping tools and those that fulfilled the filtering criteria in SNPs / (verifiedSNPs + novelSNPs).RNA-seq samples were mapped with the three RNA-seq mapping tools; TopHat2 (v 2.1.1), HiSAT2 (v 2.1.0) and STAR (v 2.5.2b) 2-pass method using default parameters to the NCBI Gallus gallus Build 5.0 reference genome. Variant calling was performed using Picard and GATK HaplotypeCaller, following the recommendations proposed by Van der Auwera et al [We mapped the WGS data with BWA-mem (v 0.7.16a-r1181)  using dera et al  and Yiyura et al . SimilarTo determine the accuracy of detecting a true variant from RNA-seq using our VAP workflow, we calculated the specificity and sensitivity of the verified RNA-seq SNPs. Because we are using transcriptome data, we theoretically should only be able to detect SNPs at sites expressed in our data. Sensitivity analysis will evaluate the accuracy of our pipeline to correctly detect known SNPs using RNA-seq, and specificity analysis will assess how likely a SNP is detected by RNA-seq compared to WGS. To do this, we further characterized our verified RNA-seq SNPs as “true-verified” and “non-verified” SNPs. A true-verified SNP (TS) is a SNP with the same corresponding dbSNP and/or WGS data, and a non-verified SNP (NS) is where the genotype does not match the dbSNP/WGS data. Also, SNPs not detected in RNA-seq but found in WGS and validated using dbSNP are called “DNA-verified” SNPs (DS). Sensitivity is calculated as the number of TS divided by the number of TS plus the number of PS (i.e. Sensitivity = TS / (TS + NS)). While specificity is estimated as the number of TS divided by the number of TS plus the number of DS (i.e. Specificity = TS / (TS + DS)) ,9.Variants in expressed regions were identified by gene quantification analysis using StringTie v1.3.3  on the TVAP uses a multi-aligner concept to call SNPs confidently. The application of multiple aligners reduces false discovery rates significantly, as shown in the eSNV-detect pipeline ,27. HoweOur method identified 514,729 SNPs from all 3 aligners before filtering, which assures reduction of false positives calls . After fVAF ≥ 0.99, and heterozygous with VAF < 0.99. We found 264,790 (93.6%) and 18,008 (6.4%) SNPs were classified as homozygous alternate and heterozygous, respectively. Most of the predicted SNPs were homozygous to the non-reference allele, confirming high level of inbreeding in Fayoumi [The 282,798 SNPs called, were grouped based on their variant allele frequencies (VAF). VAFs were calculated by dividing the number of reads supporting the variant allele by the total number of reads obtained. SNPs were grouped as homozygous to the alternative allele with  Fayoumi ,30.A high proportion of SNPs detected in RNA-seq data are true variants. The sensitivity of SNP calls are similar for both heterozygous and homozygous sites . With thThirteen percent of the RNA-seq SNPs were predicted to be within protein-coding regions while >1% of the WGS SNPs were in coding regions when annotated against both the NCBI and ENSEMBL gene database for chicken; the remaining SNPs were found in non-coding or regulatory regions . Due to To calculate specificity of our VAP methodology, we focused on variants in coding regions to allow for fair comparison between RNA-seq and WGS data. Approximately 66% of the coding variants identified by WGS were discovered using RNA-seq alone . Given tWe then compared the RNA-seq SNPs in expressed genes (having FPKM > 0.1), and the specificity increased from 66% to over 82% . This shin silico verification of our RNA-seq SNPs.Given the high accuracy of genotyping arrays for SNP discovery, we compared our initially verified RNA-seq SNPs with the genotyped chromosomes identified in the 600k chicken genotyping panel (i.e. the autosomes (GGA1–33). A low percentage (10%) of our RNA-seq SNPs overlap with the 600k SNPs , which iAs mentioned before, our RNA-seq SNPs were notably contributed from transitions which may be attributed to mRNA editing. Further classifications of the RNA-seq SNPs detected in exons reveal 34% of the exonic SNPs verified by dbSNP were not identified in our WGS data. The majority of the RNA SNPs were not found in WGS because of the mapping and filtering parameters as shown in CYFIP2, GRIA2 and COG3 previously validated by Frésand et al. in chicken embryos [RNA editing is the most prevalent form of post-transcriptional maturation processes that contributes to transcriptome diversity. It involves the modification of specific nucleotides in the RNA sequence without altering its template DNA ,32. From embryos   can increase the coverage thereby facilitate variant discovery in regions of interest that would have otherwise been missed. Our study demonstrates that variants calling from RNA-seq experiments can tremendously benefit from an increased number of reads increasing the coverage of genomic regions especially for whole genome analysis; nevertheless even our small sample size allowed for reliable calling of variants and enriching for variants in exonic regions.Despite the limitations of calling genomic variants from RNA-seq data, our work shows high sensitivity and specificity in SNP calls from RNA-seq data. SNP calling from RNA-seq will not replace WGS or exome-sequencing (WES) approaches but rather offers a suitable alternative to either approaches and might complement or be used to validate SNPs detected from either WGS or WES. Overall, we present a valuable methodology that provides an avenue to analyze genomic SNPs from RNA-seq data alone.


Alterations in RNA metabolism play an important role in Amyotrophic Lateral Sclerosis (ALS) pathogenesis. The literature has described, so far, a small number of long non coding RNAs (lncRNAs) associated to ALS demonstrating that how there is still much to do to identify and understand their role in ALS. This class of RNAs may offer numerous starting points for new investigations about pathogenic mechanism involved in ALS disease. In this review, we have collected all the presented data about lncRNAs and ALS to offer an overview about this class of non-coding RNAs and their possible role in ALS disease. ApproxiHexanucleotide repeat expansion in C9ORF72 produces dipeptide repeat proteins (DPRs), in particular polyGly-Argn(GR) and polyPro-Arg (PR) , that diMoreover, important ALS genes, such as SOD1 have been described deregulated at mRNAs level ,14. In fIn fact, there are various examples of RBP involved in ALS pathogenesis, such as hnRNPA2B1, MATR3, TAF15 and TIA1 .d-amino acid oxidase (DAO) that reduces d-serine metabolism [Heterogenous Nuclear Ribonucleoprotein A2B1 (hnRNPA2B1) already associated with neurodegeneration . Its funtabolism .Also, mutations in Matrin 3 (MATR3) have been associated to ALS and its RNA binding domains are homologous to those found in the heterogeneous nuclear ribonucleoproteins (HNRNPs) . MATR3 bTATA-Box Binding Protein Associated Factor 15 (TAF15) binds to the 3′UTR of select mRNAs, thus this implies a role in RNA stability . Wild-tyMutation in T-cell restricted intracellular antigen-1 gene (TIA1) was identified as a cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) . TIA1 isAlso, given the deregulations associated to non coding RNAs  in ALS, these seem to have an implication in ALS disease, even if the available data are still few and do not describe the possible mechanisms in relation to the pathogenesis ,7. In th2Thanks to the Encyclopedia of DNA Elements  Project , which l2.1The complexity of ALS disease is due to the numerous different cellular features, one of those are the “paraspeckles”, nuclear bodies formed by a set of specialized proteins and RNAs, such as the lncRNA Nuclear-Enriched Abundant Transcript 1_2 (NEAT1_2T) , that waInterestingly, also FUS is an integral component of paraspeckles  that sig2.2Single-stranded low-copy-number ncRNA transcripts have also been associated to FUS/TLS (Fused in sarcoma/translocated in liposarcoma). FUS is a multifunctional protein component of the heterogeneous nuclear ribonucleoprotein (hnRNP) complex and it is implicated in cellular processes that include regulation of gene expression, maintenance of genomic integrity and mRNA/microRNA processing . Defects3Natural antisense RNA transcripts are lncRNAs that are transcribed from the opposite strand (OS) of protein-coding genes or a sense strand-derived mRNA ,41, and cis or in trans. In cis, the antisense RNA interacts with a gene transcribed from the same DNA region, whereas in trans, the interaction is with genes located at distant loci or even at other chromosomes [There are well documented examples of antisense-induced chromatin modifications, suggesting that lncRNA-AS guided gene silencing could well have broader significance . Sequencomosomes .Another mechanism, regarding antisense transcript-mediated gene regulation, is based on the predicted nuclear sense-antisense RNA duplex formation, which results in the modulation of sense mRNA expression. Antisense RNA may bind to the sense RNA, masking the splice sites and thereby changing the balances between splice variants , or antiLncRNA-AS can also function as molecular decoys, with sponge-like properties, taking away proteins from a specific location or recruiting proteins to activate or inhibit processes involved at any level of gene regulation . AntisenIn a paper recently published by our group, a strong deregulation of lncRNAs has emerged in Peripheral Blood Mononuclear Cells (PBMCs) from sporadic ALS patients compared to healthy controls. Interestingly, the most represented gene biotype associated with the disease was lncRNA-AS . Moreove3.1Ataxin 2 (ATXN2) is a coding gene recently linked to ALS by the association between the length of ATXN2 repeat expansion and risk of ALS . ATXN2 p3.2(GGG GCC)n hexanucleotide expansion within the first intron of the C9orf72 gene is the most common genetic cause of both ALS and Fronto-Temporal Dementia (FTD), causing up to 40% of familial ALS and 25% of familial FTD . Health Different works have demonstrated that the expression of hexanucleotide RNA is extremely toxic to adult Drosophila neurons, resulting in dramatically shortened lifespan . AlthougA recent work studied the toxicity of sense and antisense C9orf72 RNA in Drosophila . In orde4Recently, different massive transcriptome profiles have been published in different tissues of ALS patients and matched controls showing and important deregulation in expressed genes ,73 and iSo, far, only one paper reported a transcriptome sequencing in peripheral blood mononuclear cells (PBMCs) from ALS patients . PBMCs u5in vitro differentiation system generating MNs from embryonic stem cells. Moreover, by using mutant mouse MNs carrying ALS-associated FUS alleles (P517L), specific lncRNAs affected by this mutation have been pointed out and comparative analysis with human MNs derived in vitro from induced pluripotent stem cells have indicated that candidate lncRNAs are conserved between mouse and human [The long non-coding transcriptome of mouse motor neurons (MNs) has been identified and characterized by taking advantage of an nd human . A subgrnd human , such asnd human  and werend human . In accond human , specifind human .6In this review we have reported the published data about the lncRNAs described associated to ALS even if the vision is still confused. What about the lncRNAs regulation on ALS linked genes? Up-regulation of SOD1 mRNAs in ALS patients, that the is a still unknown, may be related to any lncRNAs effect? FUS mutation may be linked to defects in development by lncRNAs expression?As we know, ALS disease is still without any cure, in particular seems to be very important a medical approach at the first stage of the disease. A pharmacological approach on RNA that are deregulated at the early phase of ALS, such asNEAT1_2T, may be an interesting target. Moreover, the next step about lncRNAs is to understand wicth are the targets of their regulation, starting from the most deregulated lncRNAs founded in ALS patients by, for example, RNA pull-down experiments. This allows us to understand the gene expression regulation to hypothesize lncRNAs as a potential value in anti-ALS therapy. Considering that lncRNAs can be both positive and negative regulators of the transcription, they could be targeted using different approaches. RNAi mediated gene silencing provides a direct approach to selectively inhibit target molecules by means different agents like siRNA , shRNAs (short hairpin RNAs), and miRNAs. AntagoNATs, ASOs that target antisense lncRNA, could be employed to up-regulate specific mRNAs/proteins by silencing the corresponding antisense lncRNA. Moreover, we could also block the molecular interactions of lncRNAs with their interacting protein partners by small molecule inhibitors that mask the binding sites on their interactors.Finally, the available data may also open to use lncRNAs as biomarkers, future studies on asymptomatic patients will be fundamental to identify possible deregulated lncRNAs before the onset of symptoms for a preventive future treatment.The published data has brought the light on the importance of lncRNAs and mRNAs regulation, but, on the other hand, is evident how still much to do to identify and understand the lncRNAs role in ALS that may offer numerous starting points for new investigations about pathogenic mechanism involved in ALS disease.None.


E. coli 16S rRNA 7-methylguanosine and pseudouridine modifications, and a 7-methylguanosine modification that confers aminoglycoside resistance to some pathological E. coli strains.The ribosome small subunit is expressed in all living cells. It performs numerous essential functions during translation, including formation of the initiation complex and proofreading of base-pairs between mRNA codons and tRNA anticodons. The core constituent of the small ribosomal subunit is a ~1.5 kb RNA strand in prokaryotes (16S rRNA) and a homologous ~1.8 kb RNA strand in eukaryotes (18S rRNA). Traditional sequencing-by-synthesis (SBS) of rRNA genes or rRNA cDNA copies has achieved wide use as a ‘molecular chronometer’ for phylogenetic studies, and as a tool for identifying infectious organisms in the clinic. However, epigenetic modifications on rRNA are erased by SBS methods. Here we describe direct MinION nanopore sequencing of individual, full-length 16S rRNA absent reverse transcription or amplification. As little as 5 picograms (~10 attomole) of purified E. coli 16S rRNA was detected in 4.5 micrograms of total human RNA. Nanopore ionic current traces that deviated from canonical patterns revealed conserved  Nanopore-based native RNA strand sequencing is conceptually similar to nanopore DNA sequencing . An applOther PCR-free RNA sequencing technologies (often referred to as direct RNA sequencing because the RNA is present during sequencing) have been implemented using SBS combined with optical readout of fluorophore-labelled DNA nucleotides ,9. They Nanopore RNA sequencing was first implemented by Oxford Nanopore Technologies (ONT) for mRNA using adapters designed to capture polyadenylated RNA strands. We reasFig 1A and S1A Fig). This overhang included the Shine-Dalgarno sequence [sequence , which tsequence . Next, asequence .E. coli 16S rRNA strand through a nanopore in the MinION array. The read begins with an ionic current pattern characteristic of the ONT RNA sequencing adapter strand followed by the 16S rRNA adapter strand. The 16S rRNA is then processed through the nanopore one base at a time in the 3′ to 5′ direction. The ionic current features are typical of long nucleic acid polymers processed through a nanopore [nanopore ,18.E. coli strain MRE600 using a single flow cell produced 219,917 reads over 24 hours that aligned to the reference sequence (16S rRNA rrnD gene) . This represents 94.6% of the total MinION read output for that experiment. Median read length was 1349 bases. We identified 142,295 reads that had sequence coverage within twenty-five nucleotides of the 16S rRNA 5′-end and within fifty nucleotides of the 3′-end.Sequencing of purified 16S rRNA from S2 Fig). The median read identity for 16S rRNA was 81.6% compared to 87.1% for Enolase 2 (S1 Table). Close examination of 16S rRNA reads revealed frequent deletion errors in G-rich regions, which are abundant in non-coding structural RNAs . This is observed as drops in coverage when unsmoothed read coverage is plotted across the E. coli 16S rRNA reference . Other sequencing errors may represent true single nucleotide variants (SNVs) from the 16S rRNA reference sequence used for alignment. E. coli strains typically have seven 16S rRNA gene copies, with some of the gene copies differing by as much as 1.1%. Modified nucleotides could also alter ionic current from canonical nucleotides [E. coli 16S rRNA contains 11 known nucleotide modifications [We calculated percent read identities for nanopore experiments using 16S rRNA and Enolase 2 RNA  . Five of these correlated with variants in the reference sequence relative to the other 16S rRNA gene copies in E. coli MRE600. For example, at position 79 the reference is adenine (A79), whereas the other six E. coli MRE600 16S rRNA gene copies are guanosine, in agreement with the majority of nanopore reads.As a diagnostic for detecting SNVs and nucleotide modifications, we scanned for bases that were reproducibly mis-called when individual 16S rRNA MinION reads were aligned to the d of 0.3 , we deteFig 2A and Fig 2B). This residue is located in a conserved region of the 16S rRNA 530 loop, near the A-site in the ribosome [One of the highest probability deviations from reference was at G527 , which was systematically mis-called by the nanopore as a C  16S rRNA nanopore reads with reads for an E. coli strain . As predicted, a canonical guanosine base at position 527 in the mutant strain eliminated the reproducible base-call error seen in the wild type E. coli strain at that position .As a test, we compared rain see  that lacFig 2C).As a further direct test, we compared ionic current signatures caused by G527 versus m7G527 by aligning traces at kmers bearing those bases. We found a reproducible decrease in ionic current for m7G527 compared to canonical G527, as anticipated  consistent with N7 methylation of G1405. We then compared 16S rRNA sequence reads for this strain (RmtB+) with reads from the parent E. coli strain (BL21) without the plasmid , as was observed at position 527. In this region, N4,2′-O-dimethylcytosine (position 1402) and 5-methylcytosine (position 1407) may also contribute to an aberrant ionic current, which could account for the sequence mis-calls proximal to those bases in the parent strain ( right panel).To this end, we engineered an S5 Fig). This mis-called position had the highest probability variant in our marginCaller analysis  bearing a canonical uridine at position 516  consistent with the hypothesis.Nanopore detection of epigenetic RNA modifications is not limited to m7G. While examining base mis-calls proximal to G527, we also noted a systematic miscall at U516  . These were chosen to give a range of 16S rRNA sequence similarities to E. coli . The 16S rRNA adapter sequence was altered slightly for each microbe to accommodate minor sequence differences at the 3′ end  to 96.9% for long reads (>1000 bases) .Another important feature of native nanopore 16S rRNA reads is that they are predominantly full-length. It has been established that more complete 16S rRNA sequences allow for improved taxonomic classification . To test end see . We binnTable 1, S7 Table). When using the SILVA database, both the specificity and sensitivity for 16S rRNA reads were 97% at the family level, 95% at the genus level, and 83% at the species level. We observed better performance for the curated GRD database, with both specificity and sensitivity of 99% at the family level, 94% at the genus level, and 93% at the species level.We next assessed the utility of MinION 16S rRNA reads for microbial classification by aligning 1000+ base 16S rRNA MinION reads against two ribosomal RNA reference sequence databases, SILVA (release 128) and GRD . SILVA iE. coli total RNA preparation with and without enrichment. We observed that enrichment increased the number of reads that aligned to 16S E. coli rRNA sequence >5-fold relative to the library without enrichment .Our early sequencing experiments required purifying 16S rRNA, which would be prohibitively slow for most practical applications. Therefore, we devised an enrichment strategy that permits selective preparation of 16S rRNA from total bacterial RNA. This involved adding a desthiobiotin to the 16S rRNA adapter. The adapter was hybridized to 16S rRNA in a mixture, and then bound to streptavidin-conjugated magnetic beads. This allowed washing and removal of non-specific RNA in approximately one hour. 16S rRNA with associated adapter could be displaced from the beads with excess biotin, and the library preparation was then performed as usual see . To testE. coli 16S rRNA into 4.5 μg total RNA from human embryonic kidney cells (HEK 293T) and prepared sequencing libraries . The lowest mass (5 pg) approximates the amount of 16S rRNA from 300 E. coli cells [This suggested that 16S rRNA could be selectively sequenced from a human total RNA background. To test this, we titered 5 pg to 500 ng of li cells . 4.5 μg E. coli 16S rRNA reads and E. coli 16S rRNA concentrations over a 100,000-fold sample range . Because nanopore data are collected in real-time, we examined how rapidly E. coli 16S rRNA was detected in these MinION runs. We extracted acquisition times for all reads that aligned to E. coli 16S rRNA . At concentrations ≥5ng, we found that the first 16S rRNA read occurred within ~20 seconds of the start of sequencing. This means that some 16S rRNA strands were immediately captured and processed by the MinION upon initiation of the sequencing run. At lower input amounts (<5 ng), we detected E. coli 16S rRNA strands in less than one hour.We observed a linear correlation between E. coli 16S rRNA. Further development of the sequencing adapter design will be necessary to capture the variability in 16S rRNA 3′ ends. This is a prerequisite for applying our selective 16S rRNA sequencing method to a metagenomic sample. A targeted approach similar to the one described here could also be applied to eurkaryotic ribosomal 18S rRNA and other rRNAs. Some nanopore RNA sequencing applications (e.g. strain-level taxonomic identification or detection of splice sites in transcript isoforms) will require better base-call accuracy than achieved in this study. These improvements seem likely based on prior evidence for MinION DNA sequencing where base call accuracies increased from 66% in 2014 [In summary, we have shown that full length 16S rRNA can be sequenced in its native form using nanopore technology. Additionally, we have demonstrated that nanopore sequencing is sensitive to 7-methyl-guanosine and pseudouridine modifications in  in 2014  to 92% i in 2014 . Future  in 2014 –36. WithE. coli strains BW25113 JW3718Δ and BW25113 JW2171Δ , deficient for 16S rRNA modifying enzymes RsmG and RsuA respectively, were purchased from the Keio Knockout collection [E. coli strains K12 MG1655, RsmGΔ, RsuAΔ and S. enterica strain LT2 were grown in LB media (supplemented with 50 μg/ml kanamycin for RsmGΔ and RsuAΔ) at 37°C to an A600 = 0.8–1.0. Cells were harvested by centrifugation and total RNA was extracted with Trizol (Thermo Fisher) following the manufacturer’s recommended protocol. All total RNA samples were treated with DNase I (NEB) (2U/10 ug RNA) in the manufacturer's recommended buffer at 37°C for 15 minutes. Following the DNase I reaction, RNA was extracted by acid phenol/chloroform extraction  and two rounds of chloroform extraction. RNA was precipitated with sodium acetate (pH 5.2) and ethanol. RNA was resuspended in nuclease-free water and stored at -80°C. For experiments where human RNA was used as a background, total RNA was extracted from 107 HEK 293T cells following the same steps.E. coli strain MRE600 16S rRNA was isolated from sucrose-gradient purified 30S subunits. Vibrio cholerae strain A1552 and Methanococcus maripaludis strain S2 16S rRNAs were isolated by gel purification from total RNA. 50–100 μg total RNA (DNase I treated) was heated to 95°C for 3 minutes in 7M urea/1xTE loading buffer and run on a 4% acrylamide/7M urea/TBE gel for 2.5 hours at 28W. Gel bands corresponding to 16S rRNA were cut from the gel. 16S rRNA was electroeluted into Maxi-size D-tube dialyzers  in 1X TBE for 2 hours at 100V. RNA was precipitated with sodium acetate and ethanol overnight at -20°C. RNA was pelleted washed once with 80% ethanol. Recovered RNA was resuspended in nuclease free water and quantitated using a Nanodrop spectrophotometer.S1A Fig), with the sequence 5′-CCTAAGAGCAAGAAGAAGCCTAAGGAGGTGATCCAACCGC-3′. The top strand, which is directly ligated to the 16S rRNA, used the sequence 5′-pGGCTTCTTCTTGCTCTTAGGTAGTAGGTTC-3′ . For V. cholerae and M. maripaludis, the 3′ terminal 20-nt of the bottom strand were slightly changed to yield adapters with perfectly complementary to their respective 16S rRNA 3′ ends. This resulted in the strands 5′-CCTAAGAGCAAGAAGAAGCCTAAGGAGGTGATCCAGCGCC-3′ and 5′-CCTAAGAGCAAGAAGAAGCCAGGAGGTGATCCAGCCGCAG-3′, respectively. To make a 16S rRNA adapter, top and the bottom strands were hybridized at 10 μM each in a buffer containing 10 mM Tris-HCl (pH 8.0), 1 mM EDTA, and 50 mM NaCl. The mixtures were heated to 75°C for 1 minute before being slowly cooled to room temperature in a thermocycler. We confirmed the adapter hybridizes and ligates to E. coli str. MRE600 16S rRNA 3′ end by a gel electrophoresis-based assay with a 6-FAM-labeled version of the top strand . For experiments where 16S rRNA was enriched from a total RNA background, a desthiobiotin was added to the 5′ terminus of the bottom strand. All adapter oligonucleotides were synthesized by IDT.The 16S rRNA adapter was designed as a double-stranded DNA oligo. The bottom 40-nt strand has one 20-nucleotide region complementary to the 3’ end of the 16S RNA, and a second 20-nt region complementary to the top strand  were added to a 15 μL reaction in 1x Quick Ligase buffer with 3000U T4 DNA ligase (New England Biolabs). The reaction was incubated at room temperature for 10 minutes. These reactions were cleaned up using 1.8x volume of RNAclean XP beads (Beckman Coulter), washed once with 80% ethanol and resuspended in 20 μl nuclease-free water. The RNA sequencing adapter (Oxford Nanopore Technologies) was ligated to the RNA library following manufacturer recommended protocol.Sequencing libraries of purified 16S rRNA for E. coli strains K-12 MG1655, BL21 DE3 pLys, BL21 DE3 pLys pLM1-RmtB+, BL21 DE3 pLys pLM1-RmtBΔ, RsmGΔ, RsuAΔ, and S. enterica strain LT2. 16S rRNA-enriched sequencing libraries were essentially prepared as described for purified 16S rRNA with the following exceptions: 15 pmol of 5′ desthiobiotinylated 16S rRNA adapter was added to 4.5–5 μg total RNA in 10 μL buffer containing 10 mM Tris-HCl pH 8, 1 mM EDTA and 50 mM NaCl. The mixture was heated to 50°C for 1 minute and slowly cooled to room temperature in a thermocycler (~10 minutes). The mixture was then incubated at room temperature for 20 minutes with 100 μL MyOne C1 magnetic streptavidin beads (Thermo Fisher) in 10 mM Tris-HCl (pH 8), 1 mM EDTA, 500 mM NaCl, and 0.025% NP-40 (Buffer A). The beads were washed once with an equal volume of Buffer A and once with an equal volume of buffer containing 10 mM Tris-HCl (pH 8), 1 mM EDTA, 150 mM NaCl (Buffer B). To elute 16S rRNA-enriched RNA, 20 μl Buffer B amended with 50 μM biotin was incubated with the beads at 37°C for 30 minutes. The hybridized 16S rRNA adapter was then ligated by bringing the mixture to 40 μL 1x Quick Ligase buffer (New England Biolabs) and adding 3000U of T4 DNA ligase (New England Biolabs). The rest of the library preparation was performed the same as described for purified 16S rRNA sequencing libraries.Enrichment-based 16S sequencing libraries were prepared for RmtB gene was purchased as a synthetic gBlock from IDT with the sequence from GenBank accession EU213261.1. pET-32a+ (EMD Millipore) and RmtB gBlock were digested with XhoI and NdeI. Digested plasmid and gBlock were ligated with T4 DNA ligase (NEB) to create plasmid pLM1-RmtB+. To create RmtB null plasmid, pLM1-RmtBΔ, XhoI and NdeI digested pET-32a+ was end repaired and ligated. Plasmids were transformed into E. coli DH5a cells (NEB) and confirmed by Sanger sequencing. Confirmed clones for pLM1-RmtB+ and pLM1-RmtBΔ were transformed into E. coli BL21 DE3 pLysS cells to create expression strains. To methylate G1405 in 16S rRNA, E. coli BL21 DE3 pLys pLM1-RmtB+ cells were cultured in 150 ml LB at 37°C with Ampicillin (100 ug/ml) until OD600 ~ 0.4. Cultures were diluted into 1 L in pre-warmed LB media with Ampicillin (100 ug/ml), and plasmid expression was induced with 1 mM IPTG. Cultures were grown at 37°C to an OD600 ~ 0.4. Cells were then pelleted and resuspended in 30 ml of 25 mM Tris-HCl (pH 7.5), 100 mM NH4Cl, 15 mM MgCl2, 5 mM β-mercaptoethanol. Cells were harvested for RNA purification or flash frozen in liquid nitrogen and stored at -80°C.The E. coli 16S rRNA was carried out essentially as described previously . Approximately 10 pmol 16S rRNA or RNA extracted from 70S ribosomes was resuspended in 20 μl 0.5 M Tris-HCl (pH 8.2). Selective reduction of m7G was performed by adding 5 μl freshly made 0.5 M sodium borohydride solution. The reaction was incubated on ice in the dark for 30 minutes. The reaction was ended by the addition of 10 μl 3 M sodium acetate (pH 5.2) and precipitated with ethanol. Pellets were washed once with 80% ethanol. RNA was pelleted by centrifugation and resuspended in 20 μl 1 M aniline/glacial acetic acid solution (1:1.5) (pH 4.5). RNA cleavage proceeded by incubating the reaction at 60°C for 10 minutes in the dark. The reaction was ended by the addition of 20 μl 0.5 M Tris-HCl (pH 8.2), and the RNA was isolated by extracting with phenol/chloroform/isoamyl alcohol. RNA was precipitated from the aqueous phase, pelleted and washed with 80% ethanol. RNA pellets were resuspended in 2.5 μl nuclease free water. Primer extension to determine the site of m7G-specific cleavage was carried out as described (Merryman and Noller 1998). To detect G527 methylation, the primer 5′-CGTGCGCTTTACGCCCA-3′ was used.Chemical probing for 7-methylguanosine in MinION sequencing of 16S rRNA libraries was performed using MinKNOW version 1.1.30. The flow cells used were FLO-MIN106 SpotON version. ONT’s Metrichor base-calling software  takes this raw signal and produces base-called FASTQ sequence in the 5′ to 3′ order after reads are reversed. During the course of these experiments, ONT made a new local base-caller available, named Albacore. We performed base-calling for the sequencing runs using Albacore v1.0.1, and performed all alignment-based analyses with the newer sequence data.FastQ sequences were extracted using poretools v0.6  and thenE. coli strains that were sequenced on the MinION. We used the software with its default settings. We chose graphmap [We used nanoraw v0.4.2  to visuagraphmap  as the ain silico and aligned using marginAlign v0.1 [Binning reads by length , we randomly sampled 10,000 reads from at least 15,000 reads per bin for each microbe. These reads were then mixed ign v0.1 . A read Long RNA reads (>1000 bases) collected independently for each of the four microbes were searched against two large microbial databases, SILVA and GRD. We aligSensitivity—Ratio of true positives over the sum of true positives and false negatives. For example, for E. coli this would be the ratio of the number of reads correctly classified as E. coli over the total number of reads from E. coli data that were classified (as anything).Specificity—Ratio of true negatives over the sum of true negatives and false positives. For example, for E. coli this would be the ratio of the total number of reads correctly classified as non-E. coli over the total number of reads from non-E. coli data that were classified.S1 Fig(a) Schematic of oligonucleotide adapter hybridized to the 3′ end of 16S rRNA. The adapter bottom (splint) strand can hybridize 20 nt to the conserved Shine-Dalgarno sequence on the 16S rRNA 3′ end. The adapter top strand can hybridize 20 nt to the 5′ end of the adapter bottom strand as shown. The 3′ terminal hydroxyl of the 16S rRNA and the 5′ terminal phosphate of the adapter top strand can be covalently joined by T4 DNA ligase. The broken line indicates an unshown ssDNA 3′ overhang, which is necessary for ligating the ONT sequencing adapter (see (b) Denaturing acrylamide gel analysis of a ligation reaction demonstrating the 16S adapter hybridizes and ligates to E. coli 16S rRNA 3′ ends. The left panel shows the unstained gel image. The lower band is a fluorescent, 3′-6-FAM-labeled version of adapter top strand. Lanes 1–3 show pre-ligation reaction samples for: Lane 1) RNA adapter ligation positive control with a polyA-specific adapter containing a 3′ terminal oligo dT10 overhang (replaces 16S-specific overhang) and the 6-FAM labeled top strand. A synthetic 288mer polyA RNA is used as the control substrate. Lane 2) 6-FAM-labeled 16S rRNA-specific adapter and purified 16S rRNA from E. coli. Lane 3) ligation negative control with adapter present, E. coli 16S rRNA, but without T4 DNA ligase. Lanes 4–6 show post-ligation reaction samples for: Lane 4) RNA adapter ligation positive control with polyA RNA 288mer. Lane 5) 16S rRNA reaction with 6-FAM labeled 16S rRNA-specific adapter. Lane 6) ligation negative control. The size-shifted fluorescent top strand indicates ligation to the 16S rRNA 3′ end (Open arrow). The right image is the same gel stained with SybrGold. Position of the 16S rRNA is indicated by open arrows.pter see . (b) Den(PNG)Click here for additional data file.S2 Figa) Identity vs. read length for Enolase 2. The intensity of blue shading represents the density of the data distribution. The black dots at the edge of the distributions represent regions where there are only a few data points. (b) Identity vs. read length for 16S E. coli rRNA. The blue shading and black dots are as in panel (a). (c) Coverage across reference for Enolase 2 calibration strand. (d) Coverage across reference for 16S E. coli rRNA. (e) Alignment of 100,000+ Enolase 2 reads to the reference sequence.Alignments were performed using marginAlign . ((PDF)Click here for additional data file.S3 FigThis matrix was determined using marginAlign EM. The matrix shows low rates of C-to-G and G-to-C substitutions, relative to the other substitutions. The color scheme is fitted on a log scale, and the substitution values are on an absolute scale.(PDF)Click here for additional data file.S4 Fig(a) Canonical m7G527 is present in wild-type E. coli and absent in the RsmG deficient E. coli strain. Sodium borohydride/aniline cleavage was used to assess the presence or absence of m7G527 in 16S rRNA from wild-type E. coli str. MRE600 or RsmG deficient (mutant) E. coli str. BW25113 JW3718Δ. Sequencing lanes 1–4 are labeled for A, C, G, and U of the RNA sequence. The respective lanes are reactions containing the complementary ddNTP to the RNA sequence. Wild-type 16S rRNA from E. coli str. MRE600 is used as the template. Lanes 6 and 8: sodium borohydride/aniline treatment (labeled +) of 16S rRNA from wild type E. coli and 16S rRNA from RsmG mutant E. coli, respectively. Strand cleavage, which is dependent on the presence of m7G, should result in an primer extension stop at C528, 1-nt preceding G527 (position 527 is marked by an asterisk). Lane 5 and 7: untreated 16S rRNA for wild type and mutant 16S rRNA. Primer extension products were run on denaturing 6% acrylamide gel, and imaged using a phosphorimager. A spontaneous RT stop appears at m7G527 in all lanes where wild-type 16S rRNA was used as the template, which has been observed previously. (b) RmtB confers a kanamycin resistance phenotype consistent with G1405 N7-methylation in 16S rRNA from an engineered E. coli strain. Serial dilutions from 10−2 to 10−6 (Left to Right) of E. coli BL21 DE3 pLysS strains transformed with pLM1-RmtB and negative control pLM1-RmtBΔ were spotted on LB agar plates. The pLM1 plasmids use pET32a as the backbone, which contains an ampicillin resistance gene. The RmtB gene is under the control of a lactose inducible T7 promoter. Plates are supplemented with: 100 μg/ml Ampicillin (top), 100 μg/ml Ampicillin + 200 μg/ml Kanamycin + 1% glucose (middle), 100 μg/ml Ampicillin + 200 μg/ml Kanamycin + 1 mM IPTG (bottom). Apparent leaky expression of the pLM-RmtB vector leads to some cell survival, even under non-inducing conditions and in the presence of glucose. RmtB is known to confer high-level resistance to kanamycin.(PNG)Click here for additional data file.S5 Fig(a) Comparison of aligned reads from strands containing putative pseudouridine versus strands bearing canonical uridine at position 516. Reads are aligned to the E. coli MRE600 rrnD 16S rRNA reference sequence. Shown are twenty-five 16S rRNA reads from separate sequencing runs for E. coli str. MRE600 (wild type), which bears a pseudouridine at U516 (Ψ516) and an RsuA deficient strain (RsuAΔ mutant), which has a canonical U at position 516. Green shading indicates the position of U516 (shown as a T in the reference gene sequence). (b) Aligned ionic current traces from approximately thirty 16S rRNA reads covering position U516 from wild-type E. coli and RsuAΔ mutan strain. Pseudouridylation site, U516, is shown in large font. The sequence is shown 3′-to-5′ because ionic current signal is 3′-to-5′. Numbering uses standard E. coli 16S rRNA numbering.(PNG)Click here for additional data file.S1 TableError models were estimated using marginAlign . Statistics were generated using marginStats.(DOCX)Click here for additional data file.S2 TableE. coli 16S rRNA (right).Over and Under represented 5-mers comparison for Enolase 2 (left) and  5-mers were counted and compared for RNA read data and their respective reference sequences. LogFC represents log fold-change.(DOCX)Click here for additional data file.S3 TableMRE600 reference sequence for rrnD 16S rRNA.(DOCX)Click here for additional data file.S4 TableMRE600 reference sequence for rrnD 16S rRNA.(DOCX)Click here for additional data file.S5 TableMRE600 reference sequence for rrnD 16S rRNA.(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 Table(DOCX)Click here for additional data file.


Solitary adrenal metastasis from colorectal cancer is rare. Adrenal metastasis is usually detected with synchronous multiple metastases in other organs and is, therefore, considered to be unsuitable for surgical resection. The long-term outcomes of patients with solitary adrenal metastasectomy from colorectal cancer have been reported; however, the survival advantage has not been established. We herein report two cases of curative adrenal resection in patients with solitary adrenal metastasis from colorectal cancer who achieved long-term survival of > 9 years without recurrence after surgical resection.The first case involved a 71-year-old man who underwent abdominoperineal rectal resection for rectal cancer. Preoperative CT revealed a mass in the right adrenal, which was growing after surgery. After chemotherapy the adrenal mass decreased in size, and adrenalectomy was performed at 8 months after the first surgery. A pathological examination confirmed metastasis from rectal cancer. The patient received adjuvant chemotherapy and is currently alive without recurrence at 9 years after the adrenalectomy. The second case involved a 53-year-old man who underwent sigmoidectomy for sigmoid colon cancer. Four years later, lobectomy was performed for isolated lung metastasis. Twenty months later, PET-CT revealed solitary metastasis in the left adrenal gland and adrenalectomy was performed. A histopathological examination revealed metastatic adenocarcinoma of sigmoid cancer. Postoperative chemotherapy was administered after adrenalectomy and the patient is currently alive and apparently disease-free at more than 9 years after undergoing adrenal metastasectomy.Curative resection for solitary adrenal metastasis from colorectal cancer may be beneficial for survival. Metastasis to the adrenal gland is a relatively frequent autopsy finding in cancer patients. Adrenal metastasis from colorectal cancer (CRC) is not rare; however, it usually occurs in patients with multiple synchronous metastases in the terminal stage of cancer. Solitary and clinically curable adrenal metastasis from CRC is extremely unusual. In cases involving pulmonary or liver metastases from CRC, successful resection procedures have a clear survival benefit  –4; howevA 71-year-old man who presented with anemia was diagnosed with rectal cancer with a synchronous adrenal metastasis. His serum level of carcinoembryonic antigen (CEA) was 529.8 ng/ml; and other laboratory data showed no abnormalities. Preoperative abdominal computed tomography (CT) revealed a mass in the right adrenal gland of 4.3 × 3.2 cm in size . Preoperative laboratory analyses, including the serum level of CEA (0.8 ng/ml), showed no abnormalities. After surgery, chemotherapy with 5-fluorouracil and folinic acid followed by tegafur uracil were administered. At 46 months after the operation, the patient’s CEA level increased to 13.9 ng/ml and positron emission tomography (PET)-CT showed an abnormal uptake in the upper lobe of left lung, and left upper lobectomy was performed. The pathological examination revealed metastatic adenocarcinoma from the previously resected sigmoid colon cancer. Oral adjuvant chemotherapy with tegafur uracil and calcium folinate was administered after lobectomy. Although the patient’s serum CEA level normalized after surgery, it increased to 23.3 ng/ml at 20 months after lobectomy, and PET-CT revealed a left adrenal metastasis , the survival of the high-risk sub-group (three or more prognostic factors) wihtin the curable group was as poor as that of the non-curable group. A review of reports concerning adrenal metastasis showed that patients with suspected adrenal metastasis should be considered candidates for adrenalectomy when: (1) control of extra-adrenal disease can be accomplished; (2) metastasis is isolated to the adrenal gland(s), adrenal imaging is highly suggestive of metastasis, or the patient has a biopsy-proven adrenal malignancy; (d) metastasis to the adrenal gland is confirmed by a recent imaging study; and (e) the patient’s performance status warrants an aggressive approach [The performance of metastasectomy for common cancer types has substantially increased . It is gapproach . In the Based on our cases and previous reports, curative resection of adrenal metastasis from CRC might lead to a good prognosis –35.These cases suggested that curative resection may be effective for adrenal metastasis from CRC. The further accumulation of similar cases will be needed to confirm these findings.