Transcription regulation in metazoans often involves promoter-proximal pausing of RNA polymerase (Pol) II, which requires the 4-subunit negative elongation factor (NELF). Here we discern the functional architecture of human NELF through X-ray crystallography, protein crosslinking, biochemical assays, and RNA crosslinking in cells. We identify a NELF core subcomplex formed by conserved regions in subunits NELF-A and NELF-C, and resolve its crystal structure. The NELF-AC subcomplex binds single-stranded nucleic acids in vitro, and NELF-C associates with RNA in vivo. A positively charged face of NELF-AC is involved in RNA binding, whereas the opposite face of the NELF-AC subcomplex binds NELF-B. NELF-B is predicted to form a HEAT repeat fold, also binds RNA in vivo, and anchors the subunit NELF-E, which is confirmed to bind RNA in vivo. These results reveal the three-dimensional architecture and three RNA-binding faces of NELF.DOI:http://dx.doi.org/10.7554/eLife.14981.001 Transcription of eukaryotic protein-coding genes by RNA polymerase II (Pol II) is not only regulated during the initiation phase  but alsoPromoter-proximal pausing requires the DRB sensitivity-inducing factor (DSIF), a heterodimer of subunits Spt4 and Spt5 . DSIF bi1S2P3T4S5P6S7) that are variably phosphorylated during the transcription cycle , explaining the stability of the complex in 2 M sodium chloride (not shown).Both NELF-A regions interact extensively with NELF-C through hydrophobic and polar contacts. Two invariant tryptophan side chains (W24 and W89) on the NELF-A N-terminal domain insert into largely conserved hydrophobic pockets of NELF-C , 2C. TheDrosophila melanogaster are compared, which share 55% identity for NELF-A and 50% identity for NELF-C. Intriguingly, NELF-A and -C homologs are present in some worms such as the filiarial nematode Loa loa  forms extensive crosslinks within itself and with the C-terminal region (438–519). The C-terminal region also crosslinks considerably with itself. The middle region (291–438) forms intrasubunit crosslinks within but not outside of the module, suggesting that it may act as a hinge between the N- and C- terminal regions.We next used the program I-TASSER to generate homology based models of NELF-B . I-TASSENELF-B crosslinks with NELF-AC via its N- and C- terminal regions. The crosslinks primarily map to a single face of NELF-AC . Two NELWith respect to crosslinks between NELF-E and NELF-C, two lysines in the non-crystallized N-terminal region of NELF-C (K66 and K125) form several crosslinks with NELF-E, including its RRM domain. Regions of NELF-C in the vicinity of helices 18’ and 19’, which are also responsible for some of the detected crosslinks between NELF-B and -C, crosslink with the NELF-E N-terminal region and the RRM , 4A. No Our crosslinking data suggest the 3D topology for the entire NELF complex. The NELF-AC subcomplex interacts with NELF-B primarily through contacts made by NELF-C and the N-terminal region of NELF-B. The opposite face of NELF-AC remains solvent exposed in the complex. NELF-B with its predicted heat repeats forms a cradle around the N-terminal region of NELF-E, tethering the RRM domain to the rest of the complex. Taken together, NELF is a modular, flexible, multivalent complex with many interaction faces for both nucleic acids and protein partners.Dictyostelium , demonstrating that regions of NELF outside of the NELF-E RRM associate with RNA. To further investigate NELF’s RRM domain-independent RNA-binding behavior, a patch mutated variant of NELF-C  was used to replace the WT NELF-C protein in the WT, ∆RRM, and ABC complexes  were overexpressed in insect cells and purified . BindingThe human immunodeficiency virus (HIV)-1 transactivation response (TAR) element is a hairpin shaped RNA produced +59 nucleotides after Pol II initiates transcription from the HIV-1 long terminal repeat of the integrated HIV-1 virus  Figure . The TARIt is known that the NELF-E subunit binds RNA in vitro and in vivo . Our bioWe found that a NELF-E antibody immunoprecipitated the entire NELF complex, as determined by mass spectrometry analysis and Western blotting, in an apparently stoichiometric fashion, allowing us to assess RNA binding by each subunit . Bands cDeciphering the mechanism of promoter-proximal Pol II pausing is essential for understanding gene regulation and requires structural information of Pol II elongation complexes bound by DSIF, NELF, and P-TEFb. To this end, structures of the involved multi-protein components are required. Structural information is available for Pol II elongation complexes , DSIF K, and P-TFrom our structural, biochemical and in vivo data, we propose an architectural model for the NELF complex. In the complex, NELF-AC binds to the N-terminal region of NELF-B. The N-terminal region of NELF-E is sandwiched in between the N- and C- termini of NELF-B, anchoring the flexible NELF-E RRM domain to the rest of the complex. Strong RNA binding by the NELF-E RRM may initially recruit NELF to RNA and secondary binding events by NELF-B and NELF-C may further stabilize the complex on nucleic acid. Future structural studies are required to determine the nucleic acid binding surfaces of NELF-B and to determine how RNA snakes from the NELF-E RRM through the rest of the complex . It is aDrosophila Pol II  . The NELWe note that nucleic acid binding alone may explain recruitment of NELF to certain genes and its association with promoter-proximal regions, but is insufficient to explain Pol II pausing, which additionally requires a change in the elongation behavior of Pol II. This may involve a conformational switch in the polymerase that may be triggered or stabilized by NELF binding to the Pol II surface. Analysis of this intricate mechanism awaits structural studies of functional complexes comprising Pol II, DSIF, NELF and additional factors. The results reported here provide an important step towards this goal.NdeI and XhoI or NdeI and BamHI restriction sites, respectively, resulting in N-terminally His6-tagged NELF-A (6–188) and untagged NELF-C (183–590). Synthetic oligonucleotides were purchased from Thermo Fisher Scientific and Sigma Genosys.The borders of NELF-A and NELF-C within the NELF-AC subcomplex were determined by limited proteolysis of human full-length NELF-AC complex followed by Edman sequencing. Human NELF-A (Q9H3P2) and NELF-C (Q8IXH7) were amplified from codon optimized DNA (Mr. Gene) and cloned into pET28a and pET21b vectors, between E. coli BL21 CodonPlus (DE3) RIL cells (Stratagene). Cells were grown in LB medium at 37°C until OD600 ~0.6 and cooled on ice for 30 min. Protein expression was induced by the addition of 1 mM IPTG. After induction, cells were grown for an additional 16 hr at 18°C. All purification steps were performed at 4°C. Cells were resupsended and lysed in buffer A . The lysate was applied to Ni-NTA agarose (Qiagen) beads and washed extensively with buffer A containing 20 and 40 mM imidazole. Protein was eluted from the beads with buffer A containing 200 mM imidazole. The eluted protein was mixed with 1 U thrombin/mg protein (Sigma) and dialyzed against buffer B  for 16 hr at 4°C. The protein was applied to Ni-NTA beads equilibrated in buffer B to remove uncleaved protein. The Ni-NTA flow through was applied to an anion exchange column  equilibrated in buffer B. Protein was eluted via a salt gradient from 100 mM to 1 M NaCl in buffer B. The protein was further purified by size exclusion chromatography with the use of a Superose 6 10/300 column  equilibrated in buffer B. Peak fractions were pooled and concentrated by centrifugation in Amicon Ultra 4 ml concentrators (10 kDa MWCO) (Millipore) to 12 mg/ml. Protein concentration was determined by absorbance at 280 nm using protein-specific parameters. Protein was aliquoted, flash frozen, and stored at -80°C.Plasmids encoding NELF-A (6–188) and NELF-C (183–590) were co-transformed into E. coli B834 (DE3) cells. For protein expression, cells were grown in SelenoMet Medium (AthenES) supplemented with 40 µg/ml L-selenomethionine (SeMet). Selenomethionine-labeled protein was purified as above.For production of selenomethionine-labeled protein, NELF-AC (6–188 and 183–590) plasmids were co-transformed into Native and selenomethionine-labeled NELF-AC crystals were grown by hanging-drop vapor diffusion and were obtained by mixing 1 µl NELF-AC protein (12 mg/ml) with 1 µl reservoir solution containing 14–14.5% (w/v) PEG 3350 and 200 mM sodium malonate pH 6.8–7.0. Tetrahedral NELF-AC crystals grew within 3–5 days. Crystals were cryo-protected in mother liquor containing 25% (w/v) glucose, and flash frozen in liquid nitrogen.Diffraction data for native crystals were collected under cryo conditions (100 K) in 0.1° increments at beamline X06DA of the Swiss Light Source in Villigen (Switzerland) using a wavelength of 1.0000 Å and a Pilatus 2M-F detector . Raw datWT and mutant NELF-AC proteins were expressed and purified as described above. For the final size exclusion step, the column was equilibrated in buffer C . Peak fractions were pooled, concentrated by centrifugation to 30 mg/ml, aliquoted, flash frozen, and stored at −80°C.c-fos gene (bps 87–96 downstream of the TSS eLife. Your revised article has been favorably evaluated by Kevin Struhl (Senior editor) and a Reviewing editor. The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:Thank you for resubmitting your work entitled "Architecture and RNA binding of the human Negative Elongation Factor" for further consideration at In the revised version of Vos et al. the authors do a nice job of clarifying the manuscript and addressing reviewer concerns. Overall, the manuscript is now acceptable for publication. The presentation of a basic structural model for NELF is highly useful for the field, as is the discovery of multiple, low-affinity RNA binding sites across the surface of the NELF complex. This work will clearly provide a nice framework for extending our mechanistic understanding of NELF activity and will stimulate considerable follow-up.However, there is one remaining issue we would like the authors to remedy: the language about the specificity of RNA binding by NELF-AC is stronger than warranted by the data presented. NELF-AC does appear to bind RNA comprised of 60% GC more strongly than 40% GC or TAR RNA, but the nature of such selectivity is not addressed . Thus, there is concern over definitive statements such as "the strength of binding and preference for RNA or DNA are sequence-dependent".When one talks of specificity in an RNA-binding protein, one often is referring to a specific motif or sequence context  that is recognized by specific interactions. That is not at all the case in this work. For this reason, we request that the authors modify their language in subsection “NELF-AC binds single-stranded nucleic acids” and elsewhere to better match the limited data presented. Rather than their data 'indicating' specificity, rather it 'suggests' specificity, or they 'provide some evidence for selectivity'. If the authors can tone down this language to better reflect the data presented, we will be happy to accept this work. The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Note: The authors should make their title more broadly accessible.- Use of acronyms (like NELF) is discouraged. NELF should be described as the Negative Elongation Factor- The authors should note that they are working with human NELF proteins(further information is below)We have altered the title of the manuscript to make it more accessible to the community. The Abstract, Introduction, and Materials and methods section have been modified to make it clear that the work described in this manuscript was conducted with human NELF proteins.Summary:NELF complex plays a critical role in RNA polymerase II pausing, which has been shown to be important in transcriptional regulation of many genes in various organisms. The structure of NELF complex, which has been elusive for a long time, is crucial of mechanistic understanding of its function in Pol II pausing. In their paper, Patrick Cramer and his colleagues have solved the crystal structure of NELF-A/C subcomplex, and modeled NELF-B and -E based on the cross-linking data. Interestingly, in addition to the predominant RNA interaction of NELF complex via the RRM domain of NELF-E subunit, they identified a region of NELF-A/C complex that associates with RNA (and ssDNA) both in vitro and in vivo. Information provided in this manuscript is a first step for a detailed mechanistic study of NELF's role in Pol II pausing and its regulation.While the study provides novel insights into the assembly structure of the NELF complex, there are several limitations (listed below), that should be addressed prior to publication.Additionally, the reviewers noted that there is limited explanation of figures in the main text, and strongly recommend that the authors endeavor to describe the experiments and figures in more detail so that a reader needn't access supplemental methods in order to understand what has been done.We thank the referees for their insightful comments and suggestions. The suggestions have led to a much improved manuscript. We present several new experiments in the manuscript including crosslinking-mass spectrometric analysis with the full-length (FL) NELF tetramer produced in insect cells, RNA binding experiments with the FL NELF tetramer, and in vivo experiments after NELF-B overexpression. Our conclusions could be expanded with the new data. Additional information concerning the figures has been added to the text and figure legends to make things clearer for the reader. We have addressed the points raised by the reviewers.Essential revisions:1) The authors identified novel RNA binding sites in NELF-C, but it is unclear whether this interaction actually occurs in the context of tetramer  It was unclear to the reviewers whether the authors were arguing for sequence specificity in the RNA binding of NELF-C . HoweverSince this RNA binding region of NELF-C is a main novel aspect of the manuscript, the authors should clarify this section. If they believe there is any specificity to the RNA ligands bound, they must expand their biochemical analysis of NELF-AC binding to nucleic acids. For example, For example, in subsection “NELF-AC binds single-stranded nucleic acids” "both the strength of binding and the preference for RNA or DNA are sequence-dependent." In this concluding sentence of the paragraph, the authors should add "protein" before "sequence" or substitute "protein residue-dependent" to make it clear that they are referring to the protein having regions that are specific for RNA binding and not that the protein binds specific RNAs.Drosophila and human NELF-E RRM  in vitro. To expand upon these findings, we tested whether the stem loop of the HIV-1 TAR RNA associates with NELF through regions outside of the RRM. Indeed, we find that NELF associates with the TAR stem loop in the absence of NELF-E. From our data, it appears that NELF-B in complex with a fragment of -E modestly associates with the RNA. In contrast, NELF-AC does not associate with the TAR RNA, further suggesting that its ability to associate with RNA is sequence-dependent.We apologize for the lack of clarity in this section. Indeed, we observe that NELF-AC prefers to bind certain RNA sequences. We have added evidence to confirm this point. Use of another random 25 nt RNA/DNA sequence resulted in no detectable binding by the NELF-AC complex. This data has now been incorporated as panel 5B. Further, the HIV-1 TAR RNA was previously shown to be a preferred substrate for the JunB and c-Fos and determined binding constants that are similar to those obtained with the 60% GC random sequence. That we observe interactions with these sequences in vitro does not mean that NELF-AC associates with these sequences in vivo. We only interpret these data to mean that NELF-AC has a propensity to associate with sequences associated with the JunB or c-Fos. We have moved these figures to the supplementary material.We made sure the conclusions reflect correctly what is observed. We had performed binding experiments with substrates that correspond to pausing sequences of 3) The data supporting an interaction of NELF-C with RNA in cells is not very strong. First, the bands for NELF-C/D are not well separated from NELF-B, making it totally possible that they are in fact detecting NELF-B interactions with RNA rather than NELF-C. This is a serious caveat. Further, I am concerned that the signals shown don't appear to depend much on UV irradiation  and are thus difficult to separate by SDS-PAGE. Unfortunately, we are limited in the number of available technologies for detecting protein•RNA interactions in vivo. PAR-CLIP is well suited but is limited by the availablility of good antibodies to immunoprecipitate (IP) specific complexes or proteins. We attempted to IP NELF-C specifically, but the IP failed with several different antibodies. We also tried to IP NELF-B specifically, but this also failed. We performed PAR-CLIP in several cell lines with the NELF-E IP . In K562 and HeLa cells, low abundance of the NELF complex and other RNA binding contaminants, respectively, stymied our attempts to orthogonally test whether we could detect a signal for NELF-B/C.Therefore, to determine whether NELF-B could contribute to the radiolabeled signal, we performed in vitro binding experiments with NELF-B and found that it indeed associates with RNA (see point 1). This indicates that in our IP from Jurkat cells, the signal we detect can be attributed to either NELF-B or NELF-C or both. We have noted this in the text.We also performed overexpression experiments in 293FT cells with NELF-B and detect a signal for NELF-B. Further, we have observed that 293FT cells show less signal after UV exposure than Jurkat cells. UV irradiation enhances the RNA crosslinking to proteins but the efficiency of crosslinking might differ for each cell line. It is possible that Jurkat cells possess more RNA bound NELF than 293FT, resulting in a more intense signal after UV irradiation. Taken together, we hope the reviewers appreciate the technical limitations of investigating RNA binding to NELF subunits in vivo, and agree that we show convincingly that NELF-B and -C bind RNA in cells, but certainly there is in vivo RNA binding outside of NELF-E.4) The authors should provide a final model of the NELF architecture with and without RNA. The authors may also consider performing protein-protein cross linking as in  in the pWe have provided a model of NELF architecture with and without RNA as In the revised version of Vos et al. the authors do a nice job of clarifying the manuscript and addressing reviewer concerns. Overall, the manuscript is now acceptable for publication. The presentation of a basic structural model for NELF is highly useful for the field, as is the discovery of multiple, low-affinity RNA binding sites across the surface of the NELF complex. This work will clearly provide a nice framework for extending our mechanistic understanding of NELF activity and will stimulate considerable follow-up.However, there is one remaining issue we would like the authors to remedy: the language about the specificity of RNA binding by NELF-AC is stronger than warranted by the data presented. NELF-AC does appear to bind RNA comprised of 60% GC more strongly than 40% GC or TAR RNA, but the nature of such selectivity is not addressed . Thus, there is concern over definitive statements such as "the strength of binding and preference for RNA or DNA are sequence-dependent".When one talks of specificity in an RNA-binding protein, one often is referring to a specific motif or sequence context  that is recognized by specific interactions. That is not at all the case in this work. For this reason, we request that the authors modify their language in subsection “NELF-AC binds single-stranded nucleic acids” and elsewhere to better match the limited data presented. Rather than their data 'indicating' specificity, rather it 'suggests' specificity, or they 'provide some evidence for selectivity'. If the authors can tone down this language to better reflect the data presented, we will be happy to accept this work.We thank you for your positive and kind remarks. We agree that to define the specificity of RNA binding by NELF-AC further experiments must be conducted. We have thus adapted the language in the manuscript to be less definitive and better reflect the data presently available.


In the AJCC, hepatic artery station (No.12a) lymph node (LN) metastasis is classified as distant metastasis, whereas in the Japanese guidelines, this classified is regional metastasis. This study aimed to evaluate whether it is appropriate to reclassify No.12a LN metastasis as distant metastasis in consideration of survival outcome.There is a discrepancy between the American Joint Committee on Cancer (AJCC) guidelines , but was similar to that of patients with LN involvement in the D2 lymphadenectomy region (P > 0.05). No.12a LN metastasis was shown to significantly influence survival outcome in univariate analysis, but was not identified as a significant independent predictor in multivariate analysis. In logistic multivariate regression analysis, T stage, N stage, and station No.3, 5, and 6 LN metastasis were independent predictors of No.12a LN involvement.Among the 247 patients with gastric cancer who underwent No.12 LN harvest, 45 (18.2%) were positive for No.12a LN metastasis. No.12a LN metastasis was significantly associated with poor clinicopathological features, advanced tumor stage, and poor overall survival. The 5-year survival rate of patients with No.12a LN metastasis was significantly better than that of patients with distant metastasis (It is inappropriate to reclassify No.12a LN metastasis as distant metastasis. We propose that this be considered as regional metastasis and be included in the extent of D2 lymphadenectomy to improve survival outcomes in patients with gastric cancer. Howevc cancer  considerc cancer –10 agreeThe study was approved by the Institutional Review Board of the 1st Affiliated Hospital of Sun Yat-Sen University and informed consent was obtained according to institutional regulations. Written informed consent for further clinical research was given by participants for their clinical records to be used when patients were admitted to hospital.Data obtained from patients with gastric cancer who underwent gastrectomy plus D2 or greater lymphadenectomy between January 1996 and December 2006 at the 1st affiliated hospital of Sun Yat-sen University were retrospectively analyzed. Patients who received neoadjuvant chemotherapy or chemoradiotherapy were excluded. The D2 lymphadenectomy region was determined according to the 6th edition AJCC gastric cancer guidelines and included the LNs along the left gastric artery (station No.7), the front of the common hepatic artery (station No.8a), the celiac axis (station No.9), the splenic hilum (station No.10), the splenic artery (station No.11), and the proper hepatic artery (station No.12a).th edition of the AJCC gastric cancer guidelines.The clinicopathological features analyzed included age, sex, tumor size, histological tumor type, gross tumor type, tumor location, and cancer embryonic antigen (CEA) level. The histological type was defined as well or poorly differentiated. Poorly differentiated types included poorly differentiated adenoma, mucinous gastric cancer, signet ring cell cancer, and undifferentiated adenoma. The postoperative pathological stage was reclassified according to the 7　 Follow-up was conducted every 3–6 months for the first 3 years and once a year thereafter. Patients underwent regular blood tests including a tumor biomarker assessment, endoscopic examination, abdominal computed tomography or ultrasonography, and chest radiography or thoracic computed tomography. The last follow-up date was in December 2013. The mean follow-up time was 41.28 ± 34.84 months.The chi-square test was used to compare differences in the categorical data. Survival was compared using the log-rank test, and survival curves were generated using the Kaplan-Meier method. The Life-table was used to calculate survival time. Univariate and multivariate analyses were conducted using the Cox proportional hazards regression model and forward logistic regression. Logistic regression analysis was used to determine factors associated with No.12a LN metastasis. A P-value <0.05 was considered statistically significant. All data were analyzed using the Statistical Package for Social Sciences .A total of 811 cases were eligible for study inclusion. Among the 247 patients with gastric cancer who underwent No.12 LN harvest, 45 (18.2%) were positive for No.12a LN metastasis. The mean number of No.12a LN metastases was 1.71 ± 1.84 (range: 1–11). To investigate the clinical significance of No.12a LN metastasis, clinicopathological characteristics were compared between cases with or without No.12a LN metastasis. Patients with No.12a LN metastasis had a large tumor size, a poor tumor histological and gross type, an abnormally high CEA level, deep tumor invasion, and extensive LN involvement .Univariate logistic regression analysis revealed that tumor diameter, histological type, gross classification, T stage, N stage, and CEA level were associated with No.12a LN metastasis . In addiA comparison of survival between patients with or without No.12a LN metastasis revealed that those with No.12a LN metastasis had a significantly poorer survival outcome , Fig. 1ath edition of the AJCC guidelines for gastric cancer describes No.12a LN metastasis as distant metastasis, we compared the survival outcome between patients with No.12a LN metastasis and those with distant metastasis. Among the 45 patients with No.12a LN metastasis, 8 had distant metastasis. Interestingly, survival was significantly different between patients with TNM stage I–III No.12a LN metastasis and those with distant metastasis (including the 8 patients with No.12a LN metastasis). Distant metastasis was associated with a significantly worse overall survival than was No.12a LN metastasis among patients with stage I–III disease -defined D2 lymphadenectomy region, although survival was poorer in cases of No.12a LN metastasis than in those of distant metastasis. No.12a LN metastasis in the current study was associated with poor malignant tumor behavior and advanced tumor stage. Moreover, No.12a LN metastasis was associated with poor overall survival in patients with gastric cancer. Although the LNs along the bile duct (12b) and portal vein (12p) are excluded from the extent of regular D2 lymphadenectomy, these results support the notion that the No.12a LN metastasis should be considered as regional LN metastasis.Lee et al  reportedLimitations of the current study include its retrospective design. Therefore, this study could not address the likelihood of station No. 12a nodal metastasis in patients deemed candidates for D2 dissection. A prospective randomized controlled study is needed in the future.In conclusion, the survival outcome of patients with No.12a LN metastasis is similar to that of patients with LN involvement in the D2 lymphadenectomy region and worse than those of patients with distant metastasis, suggesting that the No.12a LN should be included in the definition of the D2 lymphadenectomy region in the gastric cancer guidelines.


Y. pestis RyhB in the absence of Hfq. Expectedly, the transcript levels of both RyhB1 and RyhB2 increase only after inactivating PNPase, which confirms the importance of PNPase in sRNA degradation. By contrast, the signal of RyhB becomes barely perceptible after inactivating of RNase III, which may be explained by the increase in PNPase levels resulting from the exemption of pnp mRNA from RNase III processing. No significant changes are observed in RyhB stability after deletion of either the PNPase-binding domain of RNase E or rhlB. Therefore, PNPase acts as a major enzyme of RyhB degradation independent of PNPase-containing RNase E and RhlB assembly in the absence of Hfq.The RNA chaperone Hfq in bacteria stabilizes sRNAs by protecting them from the attack of ribonucleases. Upon release from Hfq, sRNAs are preferably degraded by PNPase. PNPase usually forms multienzyme ribonucleolytic complexes with endoribonuclease E and/or RNA helicase RhlB to facilitate the degradation of the structured RNA. However, whether PNPase activity on Hfq-free sRNAs is associated with the assembly of RNase E or RhlB has yet to be determined. Here we examined the roles of the main endoribonucleases, exoribonucleases, and ancillary RNA-modifying enzymes in the degradation of  Escherichia coli. RNase E and polynucleotide phosphorylase (PNPase) are two major components of the RNA degradation process [Small regulatory RNAs (sRNAs) function as posttranscriptional regulators by altering translation or stability of the target mRNA, which increases their applicability in different physiological processes in bacteria . The RNA process , 8. RNas process –11. Hfq  process , 12. PNP process , 14. Rec process –17. A tr process . RNA hel process . However E. coli [ rho sequences in E. coli [ S. typhimurium [ Yersinia pestis, which indicates that they may serve as important functions during Y. pestis pathogenesis. The stability of RyhB1 and RyhB2 is differentially Hfq-dependent in Y. pestis grown under nutrient-limiting conditions [ hfq mutant strains that lack various RNases or ancillary enzymes and monitors the expression level and degradation speeds of RyhB to investigate the effect of these enzymes on the degradation of Hfq-free RyhB.The well-characterized sRNA RyhB was used as a model sRNA for this study. RyhB is an Hfq-binding sRNA that maintains iron homeostasis in bacteria , 21. Bes E. coli . Two Ryh E. coli  have alshimurium . RyhB1 anditions . This st Y. pestis strain 201, a newly established biovar, the Microtus [λ-Red homologous recombination. RNase E is essential for viability in bacteria, but deleting the C-terminal half (CTH) of this enzyme is not lethal [ E. coli RNase E) [rne910. Bacteria were grown to midexponential phase (A620 ≈ 1.0) in BHI medium at 26°C. Iron depletion was induced by adding 100 μM 2′,2′-dipyridyl (DIP) for 20 min. Antibiotics were added when needed at the following concentrations: 34 μg/mL chloramphenicol, 50 μg/mL kanamycin, 100 μg/mL ampicillin, 20 μg/mL gentamicin, and 20 μg/mL streptomycin.All strains are derivatives ofMicrotus .  Table t lethal . The CTHRNase E)  was dele Y. pestis using TRIzol Reagent (Invitrogen). Northern blotting analysis was performed by using a DIG Northern Starter Kit (Roche) according to the manufacturer's protocol described by Beckmann et al. [μg) were denatured at 70°C for 5 min, separated on 6% polyacrylamide-7M urea gel, and transferred onto Hybond N+ membranes (GE) via electroblotting. The membranes were UV-crosslinked and prehybridized for 1 hr, and 3′-end DIG-labeled RNA oligonucleotides were added. The membranes were then hybridized overnight at 68°C in a DIG Easy Hyb. RNA was immunologically detected and scanned according to the instructions. Multiple exposures to X-ray film were taken to achieve the desired signal strength.Pure bacterial cultures were mixed with RNAprotect Bacteria Reagent (Qiagen) to minimize RNA degradation. The total RNA was then extracted fromn et al. . RNA samμg/mL rifampicin for RNA half-life determination. Culture samples were collected at 0, 5, 10, 20, 30, and 60 min and were subject to RNA extraction and Northern blotting. Films were scanned and RNA band intensity was measured using Quantity One software. The intensities were plotted and RNA half-lives were calculated using the slope from each plot.Bacteria grown to exponential phase were treated with 250  Y. pestis strains grown to exponential growth phase (OD620 = 1.2) in BHI by using Trizol Reagent (Invitrogen). DNA contaminants were removed by using DNA-free Kit (Ambion), and the cDNA was converted by using random hexamer primers with the Superscript II system (Invitrogen). Real-time PCR was performed in duplicate for each RNA preparation by using the LightCycler system (Roche) with an appropriate dilution of cDNA as a template. Negative controls without reverse transcriptase enzyme were included in all experiments. Relative quantitative analysis across different cDNA templates was performed by using LightCycler 480 software (Bio-Rad) with the 16S rDNA as the normalized gene.Total RNA was isolated from differentBHI was selected as the growth medium for bacterial culture because some mutants that were constructed in this study experienced a slow growth upon inoculation into TMH medium, which pose a challenge to our experiments. hfq mutants that lacked major RNases or ancillary RNA-modifying enzymes to validate the influence of endoribonucleases, exoribonucleases, and ancillary RNA-modifying enzymes on RyhB regulation in Y. pestis without Hfq (rng), RNase II (rnb), or polyA polymerase (pcnB). In contrast, RyhB was rarely detected in the double mutants that lacked Hfq and RNase III (rnc).The expressions of RyhB1 and RyhB2 were monitored in multiplehout Hfq . The exp rne (910-1221aa), rng, pnp, and rnb genes were deleted from the double deletion mutant that lacked Hfq and RNase III to determine which RNases account for the degradation of RyhB1 and RyhB2, respectively  than in bacterial cells that were grown in minimal media . The half-lives of both RyhB1 and RyhB2 exceeded 60 min in a WT strain that was grown exponentially in BHI medium (data not shown), which indicated that the nutrition conditions would influence the stability of Y. pestis RyhB in the absence of Hfq.RyhB1 was rapidly degraded, but RyhB2 retained its stability in the absence ofH medium . In Y. palf-life . Althoug hfq-pnp double mutant were investigated to verify the effects of PNPase on the degradation of Hfq-free RyhB ( hfq-pnp double mutant rather than in the hfq single mutant, which confirmed the role of PNPase in the degradation of Hfq-free RyhB. The rnc deletion mutation produced insignificant effects on the stability of RyhB with half-lives of 20.2 min and 49.3 min ( hfq-rne910 double mutant remains unclear. The half-lives of RyhB dramatically reduced to 3.8 min and 6.5 min in the hfq-rnc double mutant, whereas the deletion of the pnp gene increased the half-life of RyhB to >30 min (The half-lives of RyhB in theree RyhB . The sta49.3 min . However >30 min . Therefo rne gene in the encoding of RNase E is lethal, an rne mutant without PNP-binding domain was constructed in this study to produce an RNase E protein that was unassociated with PNPase.PNPase usually forms multienzyme ribonucleolytic complexes with RNase E and/or RNA helicase RhlB during the degradation of the structured RNA , 32. RNa rne and rhlB had a > 7 min half-life in the hfq-rnc mutant, but its stability was substantially lower than that upon PNPase inactivation (The Northern blotting analysis revealed that the mutation oftivation . Therefo


OPRM1 and NAT1, and detecting no effect of rs1045642 (3435C>T) in ABCB1 (MDR1) on polysomal loading while supporting previous results showing increased mRNA turnover of the 3435T allele. Use of high-throughput sequencing of complete transcript profiles (RNA-Seq) in three LCLs revealed significant differences in polysomal loading of individual RNA classes and isoforms. Correlated polysomal distribution between protein-coding and non-coding RNAs suggests interactions between them. Allele-selective polysome recruitment revealed strong genetic influence for multiple RNAs, attributable either to differential expression of RNA isoforms or to differential loading onto polysomes, the latter defining a direct genetic effect on translation. Genes identified by different allelic RNA ratios between cytosol and polysomes were enriched with published expression quantitative trait loci (eQTLs) affecting RNA functions, and associations with clinical phenotypes. Polysomal RNA-Seq combined with allelic ratio analysis provides a powerful approach to study polysomal RNA recruitment and regulatory variants affecting protein translation.mRNA translation into proteins is highly regulated, but the role of mRNA isoforms, noncoding RNAs (ncRNAs), and genetic variants remains poorly understood. mRNA levels on polysomes have been shown to correlate well with expressed protein levels, pointing to polysomal loading as a critical factor. To study regulation and genetic factors of protein translation we measured levels and allelic ratios of mRNAs and ncRNAs (including microRNAs) in lymphoblast cell lines (LCL) and in polysomal fractions. We first used targeted assays to measure polysomal loading of mRNA alleles, confirming reported genetic effects on translation of  ProtWhereas loading of protein-coding mRNAs onto translating polysomes has been studied extensively, less is known about other classes of RNAs, including antisense and pseudogene RNAs, long (intergenic) noncoding RNAs (l(i)ncRNAs), and short RNAs such as microRNAs . TherefoA second focus of this study was to develop an approach for detecting genetic variants altering polysomal RNA loading. The human genome contains numerous variants affecting transcription  and RNA A novel approach used here is to measure differential polysome loading of RNAs and their isoforms, coupled with allele-specific measurements, to assess the impact of genetic variation on translation. Differences in the allelic RNA ratios between cytosolic and polysomal extracts reveal the presence of regulatory factors that determine polysomal loading. The vast majority of genes present multiple RNA isoforms with different 3′ and 5′ UTRs and alternative splicing events, or undergoing RNA editing. To resolve these processes we employed full transcriptome sequencing (RNA-Seq) in LCLs to measure differential loading of all RNAs and their isoforms onto translating ribosomes. RNA-Seq further provides estimates of allelic ratios at heterozygous SNPs , revealiOPRM1  and NAT1*10 (rs1057126)) [ABCB1  was also included to test two proposed alternative mechanisms of post-transcriptional regulation. The synonymous SNP 3435C>T (rs1045642) had been shown to alter mRNA stability [3435T reduces translation [To test the utility of allelic RNA ratio analysis comparing total cellular to polysomal RNAs, we first employed a targeted gene approach investigating the effects on polysomal loading exerted by regulatory variants known to alter translation 057126)) , 24. ABCtability , while a) , 24. AHere we report exploratory study analyzing the entire cellular transcriptome in comparison to the translatome (RNAs on polysomes). We also present a new approach to discover regulatory polymorphisms affecting translation, by measuring changes in allelic RNA ratios upon loading onto translating polysomes.OPRM1, NAT1, and ABCB1 mRNAs across polysomal fractions  and from polysomal fractions , convertractions , consistOPRM1 coding region with either the 118A or the 118G allele were transfected into CHO cells. As the OPRM1 118G allele had been shown to reduce both the overall OPRM1 RNA expression and translational efficiency relative to the 118A allele, measured by luciferase assays [A/G ratios from cytoplasmic lysates to the polysomal fractions, reflecting preferential loading of 118A. Accordingly, the normalized allelic mRNA ratios for 118A/G was 1.3 in cytoplasmic lysate , while allelic A/G ratios increased to 1.5–1.6-fold in polysomes, significantly greater than the cytosolic allelic mRNA ratio   , consistpression .NAT1*10 3′ UTR SNP had been shown to enhance translation in LCLs without affecting total cytoplasmic mRNA content [*10 allele versus the *4 wild-type allele. This hypothesis was tested in LCL sample GM07341, which is heterozygous for the NAT1*4/*10 alleles. Consistent with a lack of effect of NAT1*10 on transcription and mRNA processing, the allelic mRNA ratio NAT1*4/*10 in the cytoplasmic lysate did not differ from unity  (*4/*10 mRNA ratios below unity (0.72–0.64) (n = 6 for each category), demonstrating greater ribosome loading for the minor *10 allele, accounting for enhanced protein expression [*4/*10 was already strongly reduced in the monosome fraction, suggesting a main effect on first ribosomal loading, possibly via long-range interactions between the 3′ UTR *10 allele with the 5′ UTR.NAT1 is natively expressed in LCLs at levels sufficient for analysis. The  content , suggest, n = 6) . In contpression . In cont3435C>T on mRNA expression and polysomal occupancy of ABCB1 mRNA in LCLs natively expressing ABCB1 and in HeLa cells transfected with an equal mixture of full-length ABCB1 expression plasmid with either 3435C or 3435T. Consistent with our earlier findings supporting enhanced mRNA turnover [3435T, presumably as a result of increased turnover. The allelic mRNA ratios did not significantly differ in the polysomal fractions   in total cytoplasm and remained the same throughout all gradient fractions  . In ABCBractions .These results demonstrate the utility of detecting differences in allelic mRNA ratios between cytosol and polysomes.The purpose of this exploratory study was to determine the loading of all RNA classes onto polysomes, including mRNAs and noncoding RNAs, and their isoforms and alleles. Genetic effects can be indirect, for example by altering transcription start sites, splice sites, and polyadenylation sites leading to isoforms undergoing differential loading, or by altering sequestration into other cell structures such as P-bodies.RNA-Seq was performed on cytosolic extracts and polysomal fractions (3 ribosomes or more) from three LCLs. Previous studies have measured mRNAs in the heavy fractions of the sucrose gradient eluate; however, this fraction does not contain smaller particles that sequester RNA , potentially further confounding isoform and allele distributions. For better comparison with widely available RNA-Seq profiles, we measured total RNA content in the cytosol, expecting to detect significant changes in RNAs sequestered on polysomes. As each RNA fraction was amplified (NuGen kit), and relative contributions from various RNA classes differed between cytosol and polysomes, the fraction of any given RNA species loaded onto polysomes was difficult to compare. Therefore, we focused on relative recovery of the various RNA classes and rank order of single RNAs compared to total RNA. The number of RNA-Seq reads per sample averaged ~40 million with a mean length of ~120 bases, of which ~70% aligned to annotated sequences representing mRNAs and various classes of noncoding RNAs including lncRNA and pseudogenes.The distributions of long RNA classes (>200 bases) within the cytosolic and polysomal fractions are shown in U47924.28, CTD-2369P2.2, and RP11-16E12.2 showed similar trends. Their role in translation should be further studied. In contrast, RNA encoded by MT-RNR2-like 11, which is annotated as a pseudogene but nevertheless protein-coding, was significantly lower in the polysome fraction , possibly accounting for the discrepant annotation. Polysome to cytosol ratio distributions of mRNA and ncRNAs for all tested genes are shown in While the polysome fractions contained high levels of protein-coding transcripts as expected, pseudogenes and long noncoding RNAs were also detected but at reduced relative levels compared to the cytosol . PseudogTo understand broadly the processes that govern the distribution of RNA classes, we determined similarity indices and constructed dendrograms of the three cytosolic and polysomal samples. We also sequenced short noncoding RNAs and focused our analysis on microRNAs. We observed a large number of microRNAs in the polysomal fraction, consistent with previous findings . Table 3PIN1, RHOG, H2AFX, and NAT14 ranged from 2.8 to 3.8, , while corresponding microRNAs predicted to target these genes, mir-1275, let-7a (for RHOG and NAT14), and mir-145, had ratios from 2.3 to 12. These results support the model proposed by Molotski and Soen, in which microRNA occupancy on polysomes is determined by their interaction with target mRNA [Analysis of putative targets of the top 20 microRNAs with greatest preferential loading onto polysomes revealed 167 polysome-enriched mRNAs, with polysome/cytosol ratio ranging from 2 to 5.5 . Lymphocyte antigen 6 complex, locus E (LY6E), the putative target of mir-1275 (ratio >4), showed significantly higher polysomal occupancy . Polysome/cytosol mRNA ratio of VEGFA, STIM2, CLIP2, IMMT, SLC24RG, FMR1, ABCC1, and SERPIND8, whereas FAM195A, AURKA, CTTN, ZNF280D, PPRC1, and SLC39A8 isoforms were depleted. Differences in isoform distribution are likely the result of distinct regulatory sequences. In addition, isoforms of annotated genes that do not contain open reading frames (ORFs), e.g., ZNF280D and FAM127A, were observed predominantly in cytosol, presumably lacking domains needed for polysomal loading.We then tested whether RNA isoforms, such as splice variants or RNAs with varying 3′ and 5′ UTRs, undergo differential loading. Determining mRNA isoforms from the RNA-Seq data yielded estimates of relative isoform distribution between cytosol and polysome fractions. RNA-Seq data on annotated isoforms were subjected to pairwise comparison between cytosol and polysomes, yielding 327 unique genes with major isoforms displaying different distributions  . Select Allelic differences in the cytosolic fraction result from regulatory variants altering gene expression, mRNA processing, and sequestration to cellular compartments , whereasTo identify genetic factors altering polysomal loading, we searched for mRNAs showing ≥2-fold difference in the allelic RNA ratio  between cytosolic and polysomal fractions of the same LCL sample . This apFOXK2). FOXK2, GOT2, LMO2, PMS2, NSA2 and TOB2 mRNAs displayed a higher allelic ratio on polysomes, while HSP1, IFFO2, and ITPK1 presented with a lower ratio on polysomes, as observed by RNA-Seq   for accu RNA-Seq .MGC70870, and GSTM2P1 had significant differences in allelic RNA ratios between cytosol and polysome fractions, suggesting similar processes regulating polysomal loading compared to mRNAs; possible translation into proteins should be evaluated. We also observed a few examples of robust allelic ratios deviating from unity in lncRNAs ), but the ratios did not differ between cytosol and polysome, suggesting regulation of transcription or RNA processing. Overall, our results show that subcellular RNA samples have different allelic compositions, adding to the regulatory processes arising from genetic factors.Among the pseudogenes, MTOR, POLD4, and FHIT, displayed distinct allelic ratios between the cytosol and polysomes, suggesting a role in isoform formation or polysomal loading , except for FRG1 and GEMIN4 with higher polysomal allelic ratios , with only 3 isoforms having higher allelic ratios on polysomes   for allelic mRNA expression imbalance. Measured allelic RNA ratios can reflect contributions from different RNA isoforms if the marker SNP resides in an exon shared between them. For specific isoform analysis one needs to select SNPs in an exon not shared with other isoforms. Among genes with differential polysomal loading of isoforms, 82% displayed allelic ratios ≥2 fold in either cytosol or polysome in at least one LCL, but no significant difference between the two fractions, suggesting regulatory effects on transcription or RNA processing affecting all isoforms equally, for example equal changes in turnover rates. In contrast, 18% of mRNA with substantial isoforms detectable , for example  loading . The isoc ratios . A reduc1, STAM) . The intCDCA2  = 0.19)–the regulator of chromosome structure during mitosis, mitochondrial ribosomal protein MRPL13 , and RAS oncogene family member RAB38 . eQTLs in transcripts of genes such as nuclear proteins involved in regulation of proliferation and cell cycle, such as NSA2  or ceramide synthase CERS5 , were also identified by GTEx.A finding of allelic expression imbalance (AEI) signals the presence of regulatory variants. While distinct cytosol-polysome allelic RNA ratios likely arise from regulatory variants residing in the transcribed region of a gene locus, epigenetic effects and RNA editing are also possible . As we hCRCP and IKZF3, the implicated dbGaP SNP was identical to the SNP identified by our AEI analysis, suggesting that it is the causative SNP or in high Linkage Disequilibrium (LD) with a functional variant.Overlap between polysome AEI and clinical phenotypes in the database of Genotypes and Phenotypes (dbGaP) was observed in 16 of the 37 genes . This fiWe also searched for databases with protein eQTLs (pQTLs), but these are less well developed . In one cis-acting variants affecting translation. Here, we utilize two novel approaches for detecting the effect of genetic variants in mRNA on translational activity by measuring allelic mRNA ratios. The first approach to establish a proof of principle uses targeted expression of cloned constructs for OPRM1, NAT1, and ABCB1 alleles [i.e. the translatome) in LCLs and to assess the role of genetic variants in polysomal loading.Delineating the contributions of regulatory variants on protein translation is critical for understanding a substantial proportion of unresolved genetic regulation. The overall regulation of translation is considered a main factor determining protein abundance in cell lines , and imp alleles , 24, 26,OPRM1 and NAT1 and ABCB1 as examples. Full sequencing of the transcriptome and translatome detects widespread differences in allelic ratios on translating mRNAs, providing evidence for cis-acting variants that influence translation. However, measuring allelic RNA ratios alone in short sequencing reads reduces the ability to attribute genetic effects to specific RNA isoforms, such as splicing or different transcription start site or poly-adenylation site usage, that occur before polysomal loading and yield RNA isoforms that then have different ability to load ribosomes. Importantly, determining allelic RNA ratios in polysomal fractions is less confounded by RNA isoforms present in other cellular fractions, while focusing on RNA alleles with likely functions in regulating translation. Therefore, differential allelic loading signals a cis-acting influence on translation, with likely biological consequences that remain obscured when measuring total cellular RNA content alone.Our targeted gene results support the use of measuring allelic ratios during polysomal loading as a sensitive means for detecting genetic effects on mRNA translation, such as initial and subsequent ribosome loading, with OPRM1 non-synonymous polymorphism 118A>G (N40D) had been shown to exert a dual effect on both overall mRNA expression levels and translational activity [OPRM1 118A>G cDNA alleles, the main allele A is indeed more abundant in the cytosolic fraction, while it is further significantly enriched in the heavy polysome fractions, supporting previous findings of reduced expression and translation caused by 118G. On the other hand only a small increase of the A/G ratio was observed in the monosome fractions, indicating that reduced loading of an initial ribosome onto the G allele mRNA was less robustly impaired compared to further ribosome loading. As the 118A>G SNP resides towards the 5′ region of OPRM1, we speculate that the movement of the ribosome along the mRNA strand could be impaired, resulting in lower polysome loading.The activity , while aactivity  remains NAT1*10 had been shown to increase expressed enzyme activity, compared to the wild-type (*4) which we had attributed to enhanced translational efficiency, presumably through the increased loading onto polysomes [NAT1 that NAT1*10 does promote association of the mRNA allele with polysomes. Even though the *10 SNP is located in the 3′ UTR, loading of the first ribosome was already enhanced, in contrast to the observation with OPRM1 118G. 3′-untranslated regions (3′ UTR) appear to physically interact with the 5′ UTRs via protein complexes in regulating initiation of translation [The N-acetyltransferase allele olysomes . Here wenslation , with ge3435C>T ABCB1 (rs1045642), (MDR1) has been widely shown to lower expression of the P-glycoprotein drug transporter. In LCL cells natively expressing MDR1, we confirm a lower level of expression of the 3435T allele in the cytoplasmic lysate, consistent with enhanced mRNA turnover [C>T ratios did not change in any of the polysomal fractions, which one would have expected if rare codon usage were to affect polysomal loading [3435T that leads to nonsense mediated mRNA decay or no-go-decay, and expected allelic ratio differences in polysome fractions. Further studies, such as ribosomal profiling [3435C>T underlying reduced MDR1 expression, a topic of considerable interest in predicting therapeutic drug response.The synonymous SNP turnover . However loading . This reB1 rs10452, (MDR1)rofiling  will be The RNA sequencing data provided here show relative distributions of different RNA categories and their occupancy on polysomes from three lymphoblast cell lines . Our appDifferential loading of mRNA isoforms was observed for a number of genes , Table 4Comparison of microRNAs in cytosol and polysomes showed differential association of microRNAs with polysomes suggesting distinct interaction with their target mRNAs . microRNcis-acting regulatory factors altering polysomal loading or isoform expression, having downstream effects on isoform distribution onto polysomes. In addition, genetic variants can alter cellular trafficking by multiple mechanisms, such as microRNA binding. Any of these mechanisms can result in altered allelic ratios on polysomes, requiring further study to distinguish between them.Any deviation of allelic RNA ratios from unity  reveals Transcriptome sequencing , 67 reveExtensive localization of long noncoding RNAs to polysomes was reported earlier , but meacis-eQTLs [We have surveyed GWAS databases (dbGaP) and RNA expression data (GTEx) to search for clinical associations and eQTLs in genes showing strong, differential allele-selective loading on polysomes . This anis-eQTLs . With usIKZF3 synonymous SNP rs907092 (MAF = 0.30) had been associated with primary biliary cirrhosis [CRCP SNP rs875971  with aortic root diameter alternations [IKZF3 is also associated with numerous other diseases including asthma and hay fever [LGALS17A has been associated with obesity [RAB38 in sclerosis [In a number of instances, the SNPs previously identified as eQTLs or GWAS hits were identical, supporting the notion that the SNP is causative or in high LD with a causative variant. Of particular interest are two overlapping AEI-GWAS SNPs. The irrhosis , and CRCrnations . In bothay fever , rheumatay fever , inflammay fever  and Crohay fever . As an eclerosis .Upon completion of this study, a similar approach was recently published by Battle et al., employing RNA-Seq for mRNAs, ribosomal fraction of mRNA profiling and protein analysis, to identify eQTLs in mRNA associated with ribosomes, termed rQTLs, and pQTLs . In thiscis-acting influence on protein translation for further functional studies. Our study provides a proof-of-principle that allelic effects on translation are pervasive and can be sensitively detected on polysomes, deployable on a transcriptome-wide scale using RNA-Seq to identify regulatory variants affecting translation.In conclusion, the method developed in this study provides tools to explore functional genomics of translation and examine genetic loci linked to human disease. Using different cell or tissue types with this method is likely to reveal genetic effects vital for regulatory sequences. This approach allows us to prioritize genes showing strong 2. For RNA-Seq experiments, cells were grown to 5x105 cells/mL density in T75 tissue culture flask and harvested. For transient transfections, 1.5×106 cells were seeded into 10 cm2 culture plates and after 24 hours transfected with 1 μg plasmid solution containing equal concentration of two expression plasmids carrying either allele of a regulatory variants in a target gene, along with 75 ng emGFP as an internal control, using lipofectamine 2000 reagent .Immortalized lymphoblastoid cell lines  from the Utah Residents with European ancestry (CEPH) , were puOPRM1 (CHO cells), and ABCB1 (HeLa cells) [NAT1 and ABCB1). Cell lines were selected to match previous experiments with the same plasmids. pcDNA3-OPRM1-118A [pcDNA3-OPRM1-118G variant allele using Quick Change site-directed mutagenesis kit  with primers OPRM1-SDM-G118-F, OPRM1-SDM-G118-R (OPRM1-seq-primer-118-R. Plasmid vectors expressing full length ABCB1 (MDR1) 3435C and 3435T mRNA alleles were used as described [pcDNA6.2-emGFP was used as a co-transfection control.We used either transfection of expression plasmids (a cells) ), or natRM1-118A  was usedM-G118-R . The seqescribed . pcDNA6.Cells were lysed and DNA was extracted from the nuclear pellet as described in . RNA wasDpnI (for plasmid transfections experiments only) and DNaseI treatment followed by real-time PCR quantification of ABCB1, OPRM1, NAT1, and luciferase mRNAs, using FAST-SYBR Green qRT-PCR supermix ,  and quantified using a Qubit 2 fluorometer . RNA was isolated from every fraction followed by cDNA synthesis and qRT–PCR to study the sedimentation pattern of each target mRNA. For cDNA synthesis with oligodT priming , 0.5 μg RNA was subjected to We tested allelic ratios at polymorphic sites using the primer extension method SNaPshot, , as previously described . qRT-PCR2, 0.2% NP-40, 2 mM dithiothreitol, 2 mM sodium orthovanadate, 1 mM phenylmethylsulfonyl fluoride, and 80 units/mL RNaseOUT. After 10 min incubation on ice, samples were centrifuged at 7500 x g at 4°C for 10 min to pellet the nuclei . 100 μL lysate was stored for the isolation of total cytoplasmic RNA and plasmid DNA. Genomic DNA was extracted by lysing the nuclear pellet. Equal volumes of total cytosol lysates (400 μL) were extracted for RNA analysis or subjected to sucrose gradient centrifugation as above.Three LCL lines were obtained from the Coriell Institute: LCL14, LCL19, and LCL31. Cells were treated with 0.1 mM cycloheximide for 3 min, harvested, and washed with ice-cold PBS containing 0.1 mM cycloheximide, and harvested by centrifugation at 1000 RPM. The cell pellet was resuspended in 500 μL lysis buffer containing 150 mM NaCl, 50 mM Tris-HCl pH 7.5, 10 mM KCl, 10 mM MgClRNA was isolated with Trizol reagent from the cytoplasm of the three LCLs , and from pooled polysome sucrose fractions . Two-step column purification and size separation were performed on each RNA sample. First, long RNA (>200 bases) was separated using SpinSmart RNA Purification column (Denville), and the flowthrough (<200 bases) was placed on a second column for small RNA (microRNA) separation with mirPremier microRNA isolation kit . RNA quality was evaluated on a Bioanalyzer.Cytoplasmic  and polysome derived long RNA (25 ng each) was then converted to cDNA using the NuGen Ovation RNA-Seq System V2 , which uses both random hexamers and oligo-dT to amplify all RNA sequences, while suppressing cDNA formation from ribosomal RNA by >90%. ERCC RNA  controls were spiked into RNA prior to NuGen cDNA synthesis. The NuGen Ovation RNA-Seq kit produces non-stranded cDNA ). The double-stranded cDNA derived from long RNAs was sheared to 150–200 bp fragments with a Covaris focused-ultrasonicator  and recovered by centrifuging over an YM-30 spin filter . Fragments longer than 100 bp were retained and eluted from the membrane.We generated barcoded sequencing libraries from 100 ng of sheared cDNA using the NEBNext Fast DNA Library Prep Set for Ion Torrent sequencing , as described , 71. In http://ioncommunity.lifetechnologies.com/docs/DOC-8434). Reads were initially mapped using tophat v2.11 [http://picard.sourceforge.net). Small RNA reads were aligned using miRanalyzer [RNA-Seq data were aligned using a two-step alignment approach . Data are expressed as mean±SEM.Statistical significance was expressed as p-values using the two-tailed student’s http://cran.r-project.org). Gene expression distributions of mRNA, pseudogenes, lncRNA, and microRNAs were analyzed using Chi-squared test. The analyses were performed using scripts written in R programming language [The non-parametric Mann-Whitney test (u-test) was used for statistical significance analysis of read counts of microRNA data. Pairwise analysis of microRNA sample similarity was performed using Renyi’s divergence calculated for each pair of samples. The pairwise similarity matrix was used for hierarchical clustering. Renyi’s divergence is a measure of similarity between two probability distributions. It is a generalization of the standard Kullblack-Leibler distance . To obtalanguage .S1 FigA-C. RNA was isolated from sucrose gradient fractions (0.5 mL). Low cycle (20–25 cycles) RT-PCR was performed for each target RNA and the amplicons resolved on an agarose gel. A. OPRM1 mRNA transfected into CHO cells showed more mRNA in light and intermediate than heavy polysomes. B-C. NAT1 and ABCB1 mRNAs natively expressed in LCLs and HeLa cells, respectively, both showing increased levels in heavy polysome fractions. mRNP represent cytosolic mRNA either free or bound to ribonucleotide particles. D-F. Sucrose gradient fractions (0.5 mL) were pooled to reflect cytosol, monosomes, light, intermediate and heavy polysomes .olysomes . qRT-PCR(TIF)Click here for additional data file.S2 Fig3435C>T allelic mRNA ratios were measured in transfected HeLa cells expressing ABCB1 3435C and T alleles, demonstrating a significant reduction of the 3435T allele to the same extent in all fractions. Data are representative of gradients done with extracts from 3 independent cultures . B. qRT-PCR of pooled polysome ABCB1 mRNA shows increased occupancy on heavy polysomes .ABCB1 (TIF)Click here for additional data file.S3 FigA. Comparison of distributions of polysome to cytosol ratios of RNA abundance between mRNA and noncoding genes revealed significant difference between means of the ratio frequency . B. Distribution of polysome to cytosol ratios of microRNA abundance.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableAllelic ratios were calculated with RNA-seq data of cytosol and polysome from LCLs, and 100 mRNAs and ncRNAs with highest allelic ratios in either cytosol or polysomes are listed. An allelic ratio 1.0 suggests equal expression of both alleles.(DOCX)Click here for additional data file.S3 TableFor isoforms presented in (DOCX)Click here for additional data file.


Furthermore, we have identified hm5C in total RNA from all three domains of life and in polyA-enriched RNA fractions from mammalian cells. This suggests m5C oxidation is a conserved process that could have critical regulatory functions inside cells.RNA methylation is emerging as a regulatory RNA modification that could have important roles in the control and coordination of gene transcription and protein translation. Herein, we describe an in vivo isotope-tracing methodology to demonstrate that the ribonucleoside 5-methylcytidine (m Recent studies, however, have shown that they can be dynamic and might have critical regulatory and/or signalling roles inside cells, similar to the reversible epigenetic marks on DNA and histones.methionine for 117 days.urea and used in a Vorbrüggen coupling with an acyl-protected ribose donor in the presence of a Lewis acid to yield 2′,3′,5′-tri-O-benzoyl-uridine . Treatment of 2 with tri--N-phosphoramidate furnished an intermediate N4-triazolyl species. Subsequent aminolysis with concentrated aqueous NH4OH and saponification of the benzoyl esters under Zemplén conditions yielded cytidine (3). 5-Hydroxymethyl-cytidine (4) was obtained from hydroxymethylation of 3 by adapting published procedures in a microwave-assisted formylation reaction in combination with the use of a cyclic acetal protecting group to aid purification.[3]-[6D]cytidine (6) was synthesized from [D4]thymine by using the same sequence of reactions as was used for the synthesis of 3 (Scheme 2 B).The conservation of mukaryotes and the tandards. Its presScheme 2. Thus, 2-fication. 5-[Methy5C in total RNA samples from model organisms representing the three domains of life by using a previously described methodology.[Methanocaldococcus jannaschii, the bacterium Escherichia coli and two eukaryotic model organisms, namely a plant  and a nematode (Caenorhabditis elegans). HEK293T cells and mammalian tissues[5C to hm5C as a result of downstream RNA processing, we subjected synthetic RNA 122-mers to identical RNA extraction and enzymatic digestion. No oxidation was detected in the quantitative LC-MS/MS analysis of these control samples.With the stable-isotope-labelled internal standards in hand, we examined the abundance of hmhodology. We chosen tissues were anan tissues To rule 5C in all samples studied . In these samples, the extent of C5-hydroxymethylation in polyA RNA was 40 times higher than in total RNA (Table S6.5). Currently, the function of m5C in mRNA and lncRNA is not clearly understood. However, the presence and levels of hm5C as an oxidative m5C metabolite in polyA RNA suggests that hm5C and m5C might be part of a dynamic regulatory mechanism. Further studies are needed to assess the functional roles of m5C and hm5C in RNA.We detected hm studied , thus cothaliana. This sug enzymes. Comparisg levels . This co5C oxidation in vivo and is pervasive in all three domains of life across a variety of different species. Our findings suggest the existence of dynamic m5C metabolism in RNA that might have important roles in RNA function.In summary, we have shown for the first time that 5-hydroxymethylcytosine in RNA is generated by m) is given in the Supporting Information. Synthetic procedures and full compound characterization for all compounds and 1H and 13C NMR spectra of 3, 4 and 6 can also be found in the Supporting Information.All in vivo experiments were performed under the terms of a UK Home Office licence. C57BL/6J (JAX mice strain) mice were bred and housed according to UK Home Office guidelines. Detailed information on the mouse labelling study, cell culture and subsequent RNA extraction  and purification  and antarctic phosphatase (New England Biolabs) in a Tris⋅HCl buffer (pH 8) for 12 h. A solution of SIL C, m5C and hm5C used for LC-MS/MS quantitation was added to samples before the enzymatic digestion.RNA was digested by using a mixture of Benzonase (Sigma), snake venom phosphodiesterase I (2O/MeCN (0.1 % formic acid) linear gradient.LC-MS/MS analysis was performed by using an Agilent 1290 Infinity UHPLC system coupled to an AB Sciex 6500 triple-quadrupole mass spectrometer. Chromatographic conditions typically consisted of using a Waters Acquity UPLC HSS T3 column and an H


Both were infectious in PLC/PRF/5 cells. And the fraction in the middle of the gradient (1.06g/cm3) from the cell culture supernatant,but not that from the feces, also has ORF2 protein and HEV RNA but was not infectious in PLC/PRF/5.The infectious RNA-rich fraction from the cell culture contained ORF3 protein and lipid but the corresponding fraction from feces had no lipid and little ORF3 protein. The lipid on the surface of the virus has no effect on its binding to cells but the ORF3 protein interferes with binding. The result suggests that most of the secreted ORF2 protein is not associated with HEV RNA and that hepatitis E virus produced in cell culture differs in structure from the virus found in feces in that it has a lipid envelope.The absence of a productive cell culture system hampered detailed analysis of the structure and protein composition of the hepatitis E virion. In this study, hepatitis E virus from a robust HEV cell culture system and from the feces of infected monkeys at the peak of virus excretion was purified by ultra-centrifugation. The common feature of the two samples after ultracentrifugation was that the ORF2 protein mainly remained in the top fractions. The ORF2 protein from cell culture system was glycosylated, with an apparent molecular weight of 88 kDa, and was not infectious in PLC/PRF/5 cells. The ORF2 protein in this fraction can bind to and protect HEV RNA from digestion by RNase A. The RNA-ORF2 product has a similar sedimentation coefficient to the virus from feces. The viral RNA in the cell culture supernatant was mainly in the fraction of 1.15g/cm Hepevirus in the family Hepeviridae. There are four recognized genotypes of HEV that infect humans: genotypes 1 and 2 are thought to infect humans and non-human primates exclusively, whereas genotypes 3 and 4 seem to be of porcine origin . Three milliliters of fecal suspension or culture supernatant from infected PLC/PRF/5 cells were treated with 20μg/ml of RNase A at 37°C for 1 hour and layered onto the gradient. The tubes were centrifuged at 35000 rpm at 4°C for 4 h. Seven fractions of 1 ml and seventeen fractions of 200 μl were recovered from the top. The density of each fraction was measured by refractometry.The removal of lipid: The ultracentrifugation fractions rich in HEV RNA from the two sources were incubated with 2% NP40 at 37°C for 1 h. Then, buffer containing 2% NP40 was replaced with PBS buffer. The delipidated samples were ultra-centrifuged again and the fractions were harvested as above.The removal of ORF3 protein: The delipidated samples were treated with a solution containing 0.1% (vol/vol) NP40, 0.1% (vol/vol) 2-mercaptoeththanol (2-ME) and 0.1% (wt/vol) pronase E and then was incubated at 37°C for 2 h. The above solution was replaced with PBS buffer using a centrifugal filter . The samples were ultra- centrifuged again and the RNA rich fractions were harvested as above.2 atmosphere. Then, every three days, the maintenance medium was collected and stored at -80°C until virus titrations were performed.PLC/PRF/5 cells were used to evaluate the infectivity of the gradient fractions. Monolayers of PLC/PRF/5 cells in six-well microplates were incubated with 0.1ml gradient fractions and 3ml MEM with 2% FBS. Three days after inoculation, the solution was removed and 3 ml MEM with 2% FBS was added. The culture was incubated at 35°C in a humidified 5% COPLC/PRF/5 cells grown in 12-well plates were incubated with the samples with the same content of HEV RNA. After incubation at 37°C for 8h, 24h, 48h and 72h, the cells were washed with PBS five times. Then the RNA binding to the cells was extracted and the amount was measured using RT-PCR quantification analysis, as described above.The ORF2 protein and HEV were extracted using affinity chromatography. The anti-ORF2 monoclonal antibody (the antibody was produced in NICPBP lab) was purThe anti-ORF3 monoclonal antibody (the antibody was produced in NICPBP lab and the data was unpublished) was purified and coupled to the CNBr-activated Sepharose 4B  as described previously. The gradient fraction rich in HEV RNA was incubated with 2% NP40 at 37°C for 1 h. Then the buffer containing 2% NP40 was replaced with PBS. The treated fraction samples were incubated with the coupled Sepharose 4B in PBS buffer with rotation overnight at 4°C. After the samples were loaded, five gel volumes PBS were used to remove impurities. The virus was eluted with elution buffer  in two gel volumes and then concentrated using a centrifugal filter .Immunocapture RT-PCR was used to evaluate the ability of virus from various sources to bind anti-ORF3 antibody. The samples with or without delipidation were bound to anti ORF3 MAb beads as described above and the beads were eluted with lysis buffer . RNA was detected in the eluate using real-time RT-PCR. The binding RNA percentage was calculated as the bound RNA divided by the total RNA in the original sample.The samples were resolved by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) at a 15% concentration and electrophoretically transferred onto a polvinylidene difluoride membrane (PVDF)  for analysis by western blotting. The membrane was incubated with serum from a hepatitis E patient (for ORF2 protein) or with rabbit anti-ORF3 antibody for 1 hour at room temperature. Then the membrane was incubated with alkaline phosphatase conjugated secondary antibody   and, after washing, bands were detected with BICP/NBT .Glycoprotein staining assay: The ORF2 protein extracted from the cell culture supernatant was separated by SDS-PAGE at a 15% concentration and then the gel was stained using a Glycoprotein Staining Kit .l-phenylalanine chloromethyl ketone  at 37°C.The digested samples were initially transferred to the pre-column at a flow rate of 5 μl/min with mobile phase A (0.1% formic acid). Then the peptides were separated with a linear gradient of 10–40% mobile phase B (0.1% formic acid in acetonitrile) over 60 min at 200 nl/min followed by 10 min at 85% mobile phase B. The column temperature was maintained at 35°C. Analysis of tryptic peptides was performed using a SYNAPT G2-S mass spectrometer  operating in the v-mode with a typical resolving power of at least 10,000 full-width half-maximum. The TOF analyzer was calibrated with the MS/MS fragments of [Glu1]-fibrinopeptide B from m/z of 50 to 1600. Accurate mass LC-MS and MS/MS data were collected in high-definition DDA mode. LC-MS/MS data were processed using ProteinLynx Global Server version 2.4 and the resulting peak lists were searched against the sequence of genotype 4 ORF2 protein (HEV AJ272108).The ORF2 protein captured from cell culture supernatants was separated by SDS-PAGE. Then the positive band was excised from the region of the gel corresponding to the western blot and hydrolyzed overnight with trypsin treated with N-tosyl-2 at 4°C overnight and then mixture treated with 20μg/ml RNase A  at 37°C for 1 hour and ultracentrifuged as described previously. The HEV RNA, with or without treatment with RNase A, as the RNA negative control and the ORF2 protein without HEV RNA as the protein control were also ultracentrifuged using the same protocol. The RNA and the ORF2 protein in the fractions were detected using real-time RT-PCR and ELISA.Reassembly of the captured ORF2 protein and RNA was performed according to the procedure described by Touze et al.. BrieflyTo observe the RNA content variation with the added ORF2 protein, ORF2 protein was diluted serially to 5500 ng/ml, 550 ng/ml, 55 ng/ml, and 5.5 ng/ml and was mixed with 100μg HEV RNA. Then the processing method was as described previously. The RNA was detected in the various fractions and compared with native virus.3were stained with 2% uranyl acetate and observed by electron microscopy.Electron microscopy was performed on a Hitachi H-7500 electron microscope , at 80 kV. The refolded samples banded at a density of 1.19–1.24 g/cmThe full-length HEV cDNA was reversed transcripted from genotype 4 HEV RNA and was c2, 10mM DTT, pH 7.3 in 20 μl on ice. Specific competitive inhibition EMSA was using 4 times and 8 times unlabeled HEV RNA as competitor and nonspecific competitive inhibition EMSA was using 0.2μg total PLC/PRF/5 cell RNA as competitor. The competitor non-biotin-labeled RNA was mixed well with biotin-labeled RNA and then was mixed with binding protein, the mixture was incubated in binding buffer on ice. The mixtures were analyzed on native 0.4% agarose gels using Tris-acetate-EDTA buffer. The samples were electrophoresed until the bromophenol blue dye has migrated approximately 3/4 down the length of the gel. Sandwich the gel and the soaked nylon membrane  in a clean electrophoretic transfer at 400mA for 30 minutes. Then the membrane was cross-linked using UV-light 5 min and was blocking. The membrane was incubated with streptavidin-horseradish peroxidase conjugate buffer. After washing, the labeled RNA was detected by chemiluminescence.To detect RNA-protein interactions by EMSA, the captured ORF2 protein were mixed with 5 pmol biotin-labeled RNA and incubate for 30 min in 100mM HEPES, 200mM KCl, 10mM MgClTo analyze the hepatitis E virions in the cell culture supernatant and in feces, we ultra-centrifuged the virus from the two sources and analyzed the various fractions rich in RNA or ORF2 protein.The accuracies of the ELISA for quantification of ORF2 protein and the real time RT-PCR for quantification of HEV RNA were validated. The linear ranges are shown in 3 is consistent with this containing the hepatitis E virions. Most of the detectable ORF2 protein remained at the top of the gradient; very little RNA was detected in these fractions and it seems possible that this is free capsid protein, perhaps derived from disrupted virions in the feces. A similar pattern was seen in the gradient of the virus from cell culture. However, the peak of the major band of HEV RNA was in fraction 15, with a density of 1.15 g/cm3. Again, most of the ORF2 protein remained at the top of the gradient and this may be free protein secreted from the infected cells. In addition, there was a second band of HEV RNA with a peak in fractions 5 and 6, with a density of 1.05–1.06 g/cm3.To extract and analyze the hepatitis E virion, virus preparations from the cell culture supernatant and feces with similar RNA contents were separated using sucrose density gradient ultracentrifugation (10%-60% (wt/vol)) and the gradient fractions were harvested. The ORF2 protein and HEV RNA in the fractions were analyzed using ELISA assay and real-time RT-PCR. Detection of HEV RNA in the gradient of the fecal preparation shows a single band with a peak in fraction 21. Although there was little ORF2 protein in this band, the density of 1.21 g/cmTo test whether the ultracentrifugation conditions might disrupt the hepatitis E virions, the samples from both cell culture supernatant and feces were fixed using 4% polyformaldehyde and then ultracentrifuged under the same conditions. The results did not change: the ORF2 protein and RNA distribution were the same as previously. So the structure of HEV was stable under the ultracentrifugation conditions.The ORF2 protein and RNA were distributed in different fractions following the ultracentrifugation. Culture in PLC/PRF/5 cells was used to investigate the infectivity of gradient fractions of HEV from the cell culture supernatant and feces.2 copies/ml at 27 days and 34 days post inoculation (pi) when the titer of inoculated HEV RNA was 3.4×103copies/ml and 3.4×104copies/ml, respectively. The progeny HEV titer reached 1×106 copies/ml at 43 days and 47 days. HEV continued to be released into the cell supernatant, reaching a peak at 60 days post incubation. The second band of HEV RNA from culture cell supernatant, which was at fraction 5 with a density of 1.06g/cm3, was also tested for infection and replication ability. No progeny HEV was detected in the culture cells within an observation period of two months. Because the sample from the cell culture supernatant had been treated with 20μg/ml of RNase A before ultracentrifugation, the HEV RNA at the second band was assumed to be protected from digestion of RNase A. Thus, although the HEV RNA in this fraction seemed to be protected the particles were not infectious in cell culture.The infection and replication ability of fraction 15 from the cell culture supernatant is shown in 2 copies/ml at 27 days and 34 days post inoculation (pi) and reached 1×106 copies/ml at 50 days and 53 days, when the titer of inoculated HEV RNA was 1.08×105 copies/ml and 1.08×104 copies/ml, respectively. HEV continued to be released into the cell supernatant, reaching a peak at 63 days post infection. The curve of progeny HEV titer and time post inoculation implies that virus production varied with the titer of HEV inoculated.The infection and replicative ability of fraction 21 from the sample from feces is shown in 3 whilst those from the culture supernatant were of 1.15g/cm3. After treatment of the samples with NP40 to remove lipid, the density of the particles from the cell culture supernatant changed from 1.15 g/cm3 to 1.21 g/cm3 but the density of those from feces did not change , HEV from cultured cells can hijack the host membrane to form an envelope.However, there is a difference between the viruses. HAV from cell culture system forms two RNA-rich fractions following the ultracentrifugation; a proportion of HAV hijacks the host membrane to bud from cell and the remainder is secreted without the membrane. The latter has no envelope and bands at a high density following ultracentrifugation. However, HEV virions from the cell culture supernatant formed only one band after ultracentrifugation; this was at low density and was shown to be enveloped with lipid. It seems that naked hepatitis E virions are not released from infected PLC/PRF/5 cells in detectable amounts.HAV and HEV are similar; both form naked virions that are spread via the fecal-oral route but also form enveloped particles that circulate in the plasma of the infected host . It is nInvestigation of the ability of the virions, with and without detergent treatment, to bind to cells suggests that the envelope has little effect on cell binding. However, removal of the ORF3 protein increased the cell binding ability greatly, suggesting that the ORF3 protein has a negative effect on binding. This may support the hypothesis thatthe ORF3 protein only functions to facilitate the egress the virus from the infected cells  and is nThe analysis of ORF2 by LC-MS/MS revealed that a peptide in the C-terminal 52 amino acids of the protein was present in the native ORF2 protein. This result is consistent with the study of Shiota et al.. The HEVThe analysis of ORF2 protein by western blotting revealed an apparent molecular weight of 88 kDa, similar to that produced in mammalian cells but differing from the findings of Emerson et al. and ShioBecause no efficient cell culture was available, the natural form of ORF2 protein in the HEV virion, including its length and glycosylation status, is not well known. Jameel et al., 26detecThe non-glycosylated ORF2 protein, without the C-terminal 52 amino acids, can assemble into particles with a T = 1 structure and the protein will assemble into particles with a T = 3 structure in the presence of RNA. One study  suggesteIn conclusion, the ORF2 protein and the viral RNA banded at different density following ultracentrifugation. ORF3 protein and lipid was on the surface of the virus from the cell culture supernatant but not the virus from feces. The glycosylated ORF2 protein containing the C-terminal 52 amino acids in the low density fractions of the gradient can bind to and protect the viral RNA, suggesting that this may be the protein assembled into virus produced in cell culture.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.


The cellular lifetime includes stages such as differentiation, proliferation, division, senescence and apoptosis. These stages are driven by a strictly ordered process of transcription dynamics. Molecular disruption to RNA polymerase assembly, chromatin remodelling and transcription factor binding through to RNA editing, splicing, post-transcriptional regulation and ribosome scanning can result in significant costs arising from genome instability. Cancer development is one example of when such disruption takes place. RNA silencing is a term used to describe the effects of post-transcriptional gene silencing mediated by a diverse set of small RNA molecules. Small RNAs are crucial for regulating gene expression and microguarding genome integrity. RNA silencing studies predominantly focus on small RNAs such as microRNAs, short-interfering RNAs and piwi-interacting RNAs. We describe an emerging renewal of interest in a ‘larger’ small RNA, the transfer RNA (tRNA). Precisely generated tRNA-derived small RNAs, named tRNA halves (tiRNAs) and tRNA fragments (tRFs), have been reported to be abundant with dysregulation associated with cancer. Transfection of tiRNAs inhibits protein translation by displacing eukaryotic initiation factors from messenger RNA (mRNA) and inaugurating stress granule formation. Knockdown of an overexpressed tRF inhibits cancer cell proliferation. Recovery of lacking tRFs prevents cancer metastasis. The dual oncogenic and tumour-suppressive role is typical of functional small RNAs. We review recent reports on tiRNA and tRF discovery and biogenesis, identification and analysis from next-generation sequencing data and a mechanistic animal study to demonstrate their physiological role in cancer biology. We propose tRNA-derived small RNA-mediated RNA silencing is an innate defence mechanism to prevent oncogenic translation. We expect that cancer cells are percipient to their ablated control of transcription and attempt to prevent loss of genome control through RNA silencing. Transcription is a core step in the regulation of gene expression. It is of fundamental importance in maintaining organism function and integrity. The transcription process involves a number of active and intricate molecular interactions. The inherent transcription machinery and associated cofactors are dynamically recruited to their target DNA loci in order to produce messenger RNA (mRNA) transcripts, actively expressing a gene. Interactions between DNA-binding factors and chromatin play a key role in RNA polymerase assembly, initiation, and elongation . The shoPerturbation of these molecular synergies can result in significant fitness costs arising from genome instability. These costs may lead to accelerated ageing and disease. Neoplasia is a general term used to describe the effects of uncontrolled cellular division. These division effects may be corrected by immune responses or medical intervention. Malignant neoplasia, or cancer, is associated with abnormal, immature, and uncontrolled cell growth with a potential to spread to other parts of the body. Cancer typically evades immune responses and drastic curative measures are critical. Such measures include systemic chemotherapies and wide resection surgery. There are over two hundred cell types in the human body, most with their own distinctive pathways of homeostasis. Abhorrent cell division may arise from a variety of biological errors. Many cancer types are caused by somatic mutations to the genomic DNA molecule. Single nucleotide polymorphisms can cause DNA sequence variation. This may be beneficial in terms of organism or species evolution. It may also introduce deleterious effects. For instance, the open reading frame of transcription may be altered and protein production is disordered. Concerning the ~350 of our ~20,000 genes implicated in cancer development, DNA sequence variation may be lethal . On a laThe advent of DNA microarrays and next-generation sequencing, creating a post-genomic era of cancer genome projects, has been instrumental in delineating molecular subtypes of cancer. Many subtypes are associated with discrete biological infrastructures leading to varied disease progression and treatment responses . The samSmall RNAs are a diverse set of functional, non-coding RNA molecules that are key regulators of gene expression through the process of gene silencing , 11. HisThere is great interest in small RNAs because of their role in modifying gene expression through RNA-mediated gene silencing mechanisms . RNA silAll species have adapted to survive in the face of short-term variation in extrinsic and intrinsic stresses, such as nutrition, temperature, and reproduction. Bombardment from damaging exogenous factors such as carcinogens may overwhelm stress protection responses and accelerate cellular ageing. A recent hypothesis suggests that this kind of genetic inflammation could be minimised through the activity of miRNAs in a process known as microguarding . ReportsDue to their major role in modifying gene expression, miRNAs have been the focus of many cancer studies. Molecular approaches to profile genome-wide miRNA expression, i.e., library construction and next-generation sequencing, identified other types of small RNA which could not be assigned to miRNA loci during bioinformatics analysis. Many of the sequencing reads mapped to mRNAs, ribosomal RNAs and transfer RNAs (tRNAs). This data was initially dismissed as RNA degradation. On further analysis, the non-miRNA reads were realised to be abundant with recurring sequences, implicating the existence of novel small RNA classes. These ‘new’ small RNAs may play an important role in RNA silencing, microguarding and cancer.Escherichia coli as a mechanism to antagonise bacteriophage infection, tiRNAs have been reported in numerous organisms [7G cap of mRNA [The best studied class of these new small RNAs are tRNA halves (tiRNAs). First described in rganisms , 33. Therganisms   of mRNA . These i of mRNA . Natural of mRNA . Stress  of mRNA . In most of mRNA . The fin of mRNA , 36.Fig.Ser molecule [O-methyl tRF-1001 oligonucleotide [Distinct but related to tiRNAs are the less well studied tRNA fragments (tRFs). Libraries of 17–26 nt small RNAs were constructed from prostate adenocarcinoma cells prior to next-generation sequencing. A significant number of sequences were derived from the precise processing of 5′ and 3′ ends of mature or precursor tRNAs . These dmolecule . Knockdomolecule . Reducedcleotide . The tRFcleotide .Later, tRF-5s and tRF-3s were observed to behave similarly to miRNAs in human cell lines. The tRFs had associations with Argonaute proteins, and one tRF was shown to be produced by Dicer, the enzyme responsible for cytoplasmic miRNA processing , 15. TheSince the discovery of tRFs, there have been several studies in a variety of model organisms. These studies conflict on the biogenesis of tRF-5s and tRFs-3s with some implicating Dicer and others reporting Dicer-independent pathways . SeveralTo address the contentions on tRF biogenesis and function, Kumar et al. took advantage of the deposited small RNA data to perform a meta-analysis of tRFs and provide an inference to their biology . The invwww.genome.bioch.virginia.edu/trfdb/ [Despite the fact that tRFs are more evolutionarily conserved than miRNAs, tRFs are present in similar abundance to miRNAs and display Argonaute sorting in humans, there was not a global repository for tRF sequences. This lack of consensus resulted in multiple labs working on the same tRF without realising, for example, cand45 in Cole et al. . Moreoveu/trfdb/ .It was proposed that tiRNAs and tRFs could have roles in cancer progression, similar to the role of miRNAs. As hypoxia is a major stress encountered by cancer cells, tRNA-derived small RNAs induced under hypoxic conditions may act to curb metastatic progression . This thGlu as ‘bait’, the RNA-binding protein Y box binding protein 1 (YBX1) was immunoprecipitated and identified as the trans-factor [A group of tRFs were identified by small RNA sequencing that were upregulated under hypoxia in breast cancer cells as well as non-transformed mammary epithelial cells . Highly s-factor . The mRNYBX1 is a malleable RNA-binding protein with a variety of networking partners. It is involved in key cellular pathways and inactivation leads to embryonic lethality . YBX1 isTo demonstrate the physiological significance of the hypoxia-induced tRF-YBX1 pathway, the study further used a reporter to drive the expression of luciferase under a hypoxia response promoter in mice xenografted with human breast cancer. A lentiviral system with a luciferase reporter fused to 3′-UTRs of cluster of differentiation 97 (CD97) and TIMP metallopeptidase inhibitor 3 (TIMP3), two important tRF-YBX1 targets, was used to show lower luciferase activity in YBX1 knockdowns post-injection . The lacTransfer RNA-derived small RNAs are amongst a diverse set of small RNA molecules present in bacteria to humans. These tiRNAs and tRFs can be freely generated from the transcriptome or produced by stress-induced cleavages. Non-stress-induced tRNA-derived small RNAs are thought to arise from ribonucleolytic processing of tRNAs by Dicer and RNase Z , 20. TheWe propose that tRNA-derived small RNAs are an innate tumour suppressive mechanism which is open to molecular manipulation through the use of RNA mimicry and antagonism. Some reports conflict with this idea where some tRNA-derived small RNAs promote cancer. This dual role as oncogenic and tumour suppressive is typical of functional small RNAs. It may also be evidence of the tumour evolutionary arms race for metastatic clonal selection. We previously suggested that miRNAs can buffer against potential oncogenic transcription . Researc