Tissue-derived RNA, DNA and protein samples become more and more crucial for molecular detection in clinical research, personalized and targeted cancer therapy. This study evaluated how to biobanking colorectal tissues through examining the influences of cold ischemic time and freeze-thaw cycles on RNA, DNA and protein integrity. Here, 144 pairs of tumor and normal colorectal tissues were used to investigate the impact of cold ischemic times (0-48h) on RNA, DNA and protein integrity at on ice or room temperature conditions. Additionally, 45 pairs of tissues experienced 0-9 freeze-thaw cycles, and then the RNA, DNA and protein quality were analyzed. On ice, RNA, DNA and protein from colorectal tumor and normal tissues were all stable up to 48h after surgery. At room temperature, RNA in colorectal tumor and normal tissues began to degrade at 8h and 24h, respectively. Meanwhile, the tumor tissues DNA degradation occurred at 24h after surgery at room temperature. Similarly, the protein expression level of tumor and normal tissues began to change at 24h after the surgery at room temperature. Interestingly, tissue RNA and DNA remained stable even after 9 freeze-thaw cycles, whereas the proteins levels were remarkably changed after 7 freeze-thaw cycles. This study provided a useful evidence on how to store human colorectal tissues for biobanking. Preserving the surgical colorectal tissue on ice was an effective way to prevent RNA, DNA and protein degradation. Importantly, more than 7 repeated freeze-thaw cycles were not recommended for colorectal tissues. Tissue-derived RNA, DNA and protein samples have become more essential for molecular analysis in medical research, personalized and targeted cancer therapy The importance of specimens in the translational cancer research has enhanced the foundation and development of tissue banks in lots of medical centers In clinical practice, cold ischemic time and freeze-thaw cycles have been considered as the key factors to determine the RNA, DNA and protein quality of tissues In this study, we developed a standard procedure of tissue biobanking for colorectal cancer (CRC) patients, particularly in terms of cold ischemic time and freeze-thaw cycles by examining RNA, DNA and protein integrity in various conditions. We found that the quality of RNA, DNA and protein remain stable up to 48h after surgery if tissues were stored on ice. On the contrary, RNA of tissues left at room temperature was degraded at 8h after surgery. Additionally, the tumor tissues DNA began to degrade at 24h after surgery, and the protein expression pattern in colorectal tumor and normal tissues began to change at 24h after the surgery at room temperature. Furthermore, for both tumor and normal tissues, RNA and DNA remained stable even after 9 freeze-thaw cycles, whereas the proteins expression levels were remarkably changed after 7 freeze-thaw cycles.The Tissue Bank of the Sixth Affiliated Hospital, Sun Yat-sen University, as the biggest colorectal tissue bank in Southern China, coupled with a comprehensive clinical database and follow-up system, was established in 2007. Here, 112,140 colorectal tissue samples had been collected from 6,230 patients who underwent a radical CRC surgery from January 2007. For each case, 18 fresh tissue samples would be stored at the biobank, including of 9 tumor tissues and 9 paired normal adjacent tissues. The written patients consent for tissue banking was approved before the surgery for each case.3 for bio-banking. Moreover, the normal mucosa at 5cm far away from the tumor was collected simultaneously. Half part of the tumor and the paired normal adjacent tissues were then moved to labelled cryovials, and stored in a ultra-low freezer (-80℃). Additionally, another half part of the tumor and paired normal adjacent tissue samples were incubated in the RNAlater stabilization reagents  at 4℃ overnight, and further stored in the ultra-low freezer for long-term storage. Clinical information and tissues ex-vivo ischemic time were precisely recorded for each sample.After resection, the specimens were transferred into pre-chilled cryovials and stored at on ice immediately, followed by delivering to the tissue biobank within 10 min after the surgery. Well trained research assistants were responsible for the initial gross examination. Subsequently, the tissues were then cut into pieces with the dimension of 0.5*0.5*0.5 cmIn this study, we examined the effects of different cold ischemia time  at on ice or room temperature Figure A, and frTo analyze the impact of tissue cold ischemic time on RNA, DNA and protein quality, fresh tumor and paired normal adjacent tissues were collected. For each case, the tumor and normal adjacent tissues were obtained immediately after surgical resection in the operating room. The tissue was divided into 16 pieces with equal size. Half subgroup (8 pieces) was placed at room temperature (25℃), while another half subgroup (8 pieces) was placed on ice. One piece in each subgroup was immediately immersed into liquid nitrogen, and then transferred to -80℃ for further analysis and considered as 0h. After 0.5h, 1h, 2h, 4h, 8h, 24h and 48h, one piece was taken from each subgroup to extract the RNA, DNA and protein immediately at the end of each time point. For RNA analysis, the tissues were always immersed in RNAlater stabilization reagents to prevent RNA degradation.To investigate the effect of repeated freeze-thaw times on tissue RNA, DNA and protein integrity, 45 pairs of CRC and normal tissues were tested Figure B. Each sTissue RNA extraction was performed using RNeasy Mini Kit  and RNase-Free DNAase Set  in accordance with the manufacturer's instructions. The isolated RNA was analyzed by Agilent 2100 Bioanalyzer . To assess the RNA integrity, RNA integrity numbers (RINs) were calculated by Agilent software, and RIN ≥ 7.0 was considered as high-quality and intact RNA samples from the tissues.DNA was extracted and purified using Tissue gDNA kit  and Wizard Genomic DNA Purification kit , according to the manufacturer's instructions. DNA concentration was estimated by measuring the absorbance at 260 nm. DNA integrity was determined by agarose gel electrophoresis. Equal amount of extracted DNA for each sample was loaded to 1.5% agarose gel and stained with ethidium bromide for imaging.2, 1mM EGTA, 100mM NaF, 10mM NaPPi, 10% glycerol supplemented with fresh PMSF , Na3VO4 , protease (cOmplete Tablets EDTA-free) and phosphatase (PhosSTOP) inhibitor cocktail (Roche Applied Science)]. Tumor and normal adjacent tissue lysates were serially diluted two-fold for 5 dilutions (from undiluted to 1:16 dilution) and printed on nitrocellulose-coated slides using an Aushon Biosystems arrayer  in an 11x11 format. Samples were stained with primary and secondary antibodies in an autostainer (BioGenex), probed by tyramide-based signal amplification approach and then visualized by DAB colorimetric reaction. RPPA slides were stained for 298 unique antibodies , 150mM NaCl, 1.5mM MgCles Table , which wP> 0.05), respectively. For normal tissues the mean RINs were 8.8, 8.7, 8.9, 8.2, 8.5, 8.1, 7.8 and 7.7 at 0h, 0.5h, 1h, 2h, 4h, 8h, 24h and 48h after the surgery , respectively. These results indicated that all tissue RNA with a good quality when placed at on ice. By contrast, when the tissues were processed at room temperature (25℃), the tumor tissues RNA  had no apparent effect on RNA and DNA integrity. However, proteins expression levels, including of phosphorylated proteins expression levels, were evidently changed after 7 freeze-thaw cycles. Especially, this protein expression change was obviously happened in colorectal cancer tissues.Though the purified RNA is a labile molecule and prone to degradation, the tissue RNA seems to be more stable. A study on breast samples showed that tissue RNA remained stable for up to 24h after the surgery With regard to the impact of freeze-thaw cycle on RNA integrity, our study showed that RNA remained intact even after 9 freeze-thaw cycles for both tumor and normal tissues Figure A. SimilaDNA being more stable is considered better than RNA and protein for storage. Sang et al. reported that the colorectal cancer tissues DNA was stable up to 90 minutes after extraction Histologic evaluation of frozen tissues was often used to test the integrity of proteins Previous studies reported that proteins, especially phosphorylated proteins, tend to be degraded, and thus rapid freezing < 5 minutes) was critical to keep the high protein quality in tissue samples, particularly for the protein phosphorylation status  minutes Here, we also realized that the present study had several limitations. First, we just focused on the impact of cold ischemic time and freeze-thaw cycles on tissue RNA, DNA and protein quality. Actually, there are many other factors, such as storage time, might also affect their quality. Therefore, the other factors should be addressed in future research. Another limitation was the ischemic time. At the laparoscopic surgery era Supplementary figure and tables.Click here for additional data file.


Psychrobacter sp., which is two-orders of magnitude more abundant during the day. Nighttime communities are enriched with species of Roseobacter, Halomonas, and Alteromonas encoding a greater variety of pathways for carbohydrate catabolism, further illustrating temporal patterns of energetic provisioning between different marine microbes. Dynamic diel fluctuations of microbial populations could also support the efficient trophic transfer of energy posited in coral reef food webs.On coral reefs, microorganisms are essential for recycling nutrients to primary producers through the remineralization of benthic-derived organic matter. Diel investigations of reef processes are required to holistically understand the functional roles of microbial players in these ecosystems. Here we report a metagenomic analysis characterizing microbial communities in the water column overlying 16 remote forereef sites over a diel cycle. Our results show that microbial community composition is more dissimilar between day and night samples collected from the same site than between day or night samples collected across geographically distant reefs. Diel community differentiation is largely driven by the flux of  Microbes structure biogeochemical cycles and food webs in the marine environment. Here, the authors sample coral reef-associated microbes across a 24-hour period, showing clear day–night patterns of microbial populations and thus calling for more studies to consider temporal variation in microbiomes at this scale. The water column overlying tropical coral reefs comprises a complex mixture of oligotrophic offshore waters and reef water enriched with the organic carbon and nitrogen substrates exuded by the benthic community5, which establishes the base of a robust microbial food web7. Coral reef benthic communities can directly consume bacterioplankton from the overlying water column via suspension feeding11 thereby reducing energy loss that would otherwise be respired by microbes. These top down consumption processes reduce microbial production in the water column and simultaneously enhance transfer of microbial biomass to metazoan consumers in the benthos. The mechanisms sustaining these retention processes, yet poorly understood, promote the tight recycling of materials and production of high consumer biomass observed in coral reef ecosystems12.Microorganisms comprise the majority of biomass in the oceans and their role in the decomposition of organic substrates is critical to nutrient cycling, as well as for channeling nutrients and energy to higher trophic levels14 and allochthonous inputs16. As reefs shift toward algal-dominated states microbial production increases and becomes a greater energetic sink compared to that observed in a coral dominated system18. Diel investigations on reefs are required to better understand the heterotrophic metabolisms that dominate at night, including fundamental processes influenced by microbial communities, such as reef dissolution and boundary layer anoxia21. Furthermore, the influence of rhythmic growth patterns versus predation on reef microbial community structure remains virtually unknown.A key question in reef ecology is identifying how benthic communities influence reef microbial community structure and function. Microbial biomass and community structure on reefs are linked to local conditions, such as the composition of benthic assemblages22 and meiofauna  that are active during the night23. Autochthonous copepods have been observed moving into the water column at night to feast on the planktonic communities25. Remote cameras and hydrophones have also recorded nocturnal migrations of invertebrates from the dark reef to the benthic surfaces23. To further distinguish trophic linkages between macroorganisms and microorganisms, and provide a more holistic understanding of the structure and function of coral reef communities, measurements of microbial dynamics in natural reefs over a complete diel cycle are needed.The majority of studies on coral reefs have been conducted during the day when diurnal processes predominately associated with corals and benthic algae exhibit highest rates of primary production and calcification. The hazards of apex predator feeding behaviors and of navigating boats through the reef during the night complicate the logistics of acquiring field diel measurements and nocturnal sample collections outside of controlled but artificial environments such as aquaria. Despite these challenges, few studies have shown that the dark reef  is a hotspot for microorganisms28). Our results illustrate a dramatic and consistent shift in day versus night microbial communities, which is reflected both in the taxonomic structure and the metabolic capacity encoded by the populations. This study highlights ecosystem functions on reefs that support dynamic fluctuations of diel microbial populations, capturing a key aspect of microbial ecology implicated in promoting trophic transfer of energetic resources through the microbial food web in tropical reef ecosystems.The study described here used a novel apparatus to collect diel biochemical and metagenomic samples from remote coral reefs to characterize microbial community dynamics in the water column overlying 16 forereef plots over a 24 h period. Metagenomic characterizations of environmental microbes can reveal linkages between spatial and temporal community dynamics, biogeochemical fluxes, and ecological niche partitioning  was collected from four distinct forereef sites over a 24-h period (N = 16). Benthic chambers were constructed over each reef plot (0.75 m2) to provide structure for autonomous sampling at night  from October 22 through November 6, 2013. The study site encompasses three uninhabited coral islands and one atoll: Vostok , Millennium , Starbuck , and Malden  separated by 800 km of latitudinal distance and exhibiting variance in ocean productivity and nutrient regimes between islandsght Fig. . The for32 and dominated by calcifying coral and algae33. All benthic chambers were placed on forereef sites (10 m depth) which were predominately composed of reef-building macroorganisms including scleractinian corals, crustose coralline algae (CCA) and calcified macroalgae  and pH ranged from 8.13 to 8.49 over a diel cycle. Temperature differences over the 24 h sampling period were lowest on Vostok and Millennium (0.1−0.4 °C) and highest on Malden (1 °C)  compared to offshore waters (96.3 ± 4.9 µmoles kg−1). A subset of the DOC pool characterized as humic-like fluorescent dissolved organic matter (fDOM) was also measured in higher concentrations on the forereef and did not differ between open reefs and benthic chambers at the start of incubations (p > 0.98). Both DOC and fDOM concentrations demonstrated significantly higher concentrations in the night samples across islands (p < 0.05), indicating either enhanced release or reduced consumption of organic materials during the night  Fig. . Dissolvght Fig. ; in all N = 16 sites and 48 samples). Microbial community composition differed strongly between day and night across all reef sites and islands  and among islands , emphasizing the role of island-scale variation in benthic communities  and chamber endpoint (t24) daytime communities (PERMANOVA p > 0.25) or between ambient and chamber nighttime (t12) communities (PERMANOVA p > 0.37) but both ambient and chamber diel pairwise comparisons were all significantly different , clarifying that Islands did not differ in these robust patterns. Within each benthic chamber (reef site), microbial community phylogenetic and metagenomic composition differed more between night and day than between the daytime start (t0) and end (t24) of deployments, or between daytime samples among chambers  and the night t12) is described from four distinct reef sites on each of the four islands: Vostok, Millennium, Starbuck, and Malden (2 is descPsychrobacter spp. from the Family Moraxellaceae (Gammaproteobacteria). Abundances of Moraxellaceae taxa during the day ranged from 32.8 ± 5.66% on Starbuck (mean ± s.e.m.) to 70.2 ± 3.47% on Vostok  were also enriched during the day (5.35 ± 1.03–10.3 ± 2.25). Rarer bacterial families significantly enriched during the day included Neisseriaceae (Betaproteobacteria) and Pasteurellaceae (Gammaproteobacteria) , but was depleted by nearly two orders of magnitude during the night   Fig.  and threia) Fig. . There wia) Fig. . One tax16) Fig. . In cont16) Fig. .Fig. 2Po5, minimum length of alignment of 45 bp, minimum nucleotide identity of 70%), where each read assigned a gene function was classified into Subsystem Levels 1−3 (metabolic pathways annotated into a stepwise hierarchy)34. Hierarchical cluster analysis classified the broadest metabolic designations  into two groups of predominantly daytime (14 categories) or nighttime enriched metabolism (eight categories)  Fig. . The metes) Fig. . Daytimees) Fig. . Night ces) Fig. .Fig. 3Dip-values according to Benjamini and Hochberg35. During the day, several different housekeeping gene pathways were more abundant, including DNA replication and repair, RNA processing and modification, and protein folding. Biosynthetic pathways to build plasma membranes (phospholipids), protein cofactors and Gram negative cell wall components  were all present in higher abundances during the day , as well as flagellar motility were more abundant at night. Finally, seven distinct pathways to build a cellular capsule were significantly enriched at night  that were significantly enriched between the day and night communities across all reef sites are depicted in Fig. ght Fig. .36, the English Channel37, and Monterey Bay38 all report marginal changes in community structure and gene content between day and night communities. While transcriptional activity of metabolic functions in marine bacterioplankton communities are strongly influenced by diel patterns39, significant shifts in composition are more commonly linked to seasonal changes41, spatial patterns, such as distance to land42 and oceanographic processes, such as upwelling43 and mesoscale eddies44.Marine microbes generally demonstrate similar community profiles during the day and night. Previous studies from the North Pacific Subtropical GyrePsychrobacter, dominated the day community on all reef sites (up to 70% on Vostok), but was depleted to an average of 0.5% at night  on these reefs was striking but not unexpected. For comparison, reef microbes collected between 2009 and 2016 from 22 Pacific islands were investigated for the presence of Psychrobacter. The abundances of Psychrobacter spp. were higher on the reef compared to surface and offshore waters  and Alteromonas also represented a significant proportion of the night community . The difference in diel patterns between open ocean communities and those associated with coral reef habitats reflects the potential for a benthic–pelagic coupling of the microbial food web.There were also a number of microbial taxa that were common during the night across all islands including one phylotype from the family Rhodobacteraceae (Alphaproteobacteria) that on average represented 17% of the night population and up to 33% on Starbuck. Gammaproteobacteria from the Genus Psychrobacter spp. The metabolic profile of genes encoded during the day were predominately anabolic pathways including the biosynthesis of cofactors, vitamins, cell walls, and membranes (lipids), as well as DNA replication and repair. Thus, day community metabolism reflected a strategy for cellular growth, but a limited capacity to catabolize a variety of substrates.The metabolic profile during the day was strongly influenced by the high prevalence of 18. Enriched carbohydrate pathways encoded by the night community also reflect greater availability of sugar alcohols and cycling of C1–C3 compounds that could be metabolized more favorably in low oxygen conditions47. Prior research has suggested that temporal cascades of transcriptional activity by different oceanic heterotrophs reflect a mechanism for partitioning energetic resources between members of the microbial community49. These organisms potentially respond to rhythmic metabolic fluctuations through molecular regulation that result in oscillatory patterns or circadian clocks50. Coral reef habitats create strong temporal fluxes of biochemicals including oxygen, pH, labile-dissolved organic matter, and inorganic nutrients  was enriched in day communities whereas genes encoding the Entner–Doudoroff (ED pathway) were significantly more abundant at night, suggesting alternative strategies for catabolism at night53. Temporal synchrony of certain members of the microbial community to exhibit high metabolic rates during the day that correlate with primary productivity may represent another example of such mechanisms. These fast-growing diurnal microbes are diminished at night by (1) reduced growth rates, (2) protist predation that could channel energy into the benthic food web, or (3) viral lysis coordinated to remove a large proportion of the bacterial biomass, providing both reduced activity and available energetic substrates to different members of the community.Coral reef communities appear to maximize efficient processes related to nutrient cycling; dynamic growth and removal processes foster high production in these otherwise resource-limited environmentsThe influence of predation versus rhythmic growth patterns on community structure are fundamental questions in microbial ecology that remain largely unanswered. The use of commercial autonomous samplers could provide the capacity to sample different size fractions , at finer temporal resolution  and over consecutive diel cycles. This enhanced time resolution would also provide a means to further characterize dynamics of microbial populations and help resolve the roles of predators, both phage and protists, in community shifts on diel time scales. While it is less logistically feasible to deploy larger sampling equipment on cruises, land-based field studies both on populated islands and remote regions  would provide greater geographic context to these observed diel patterns and allow for comparison across intact and degraded coral reef ecosystems. We hypothesize that the ecological functions driving these microbial fluxes will be diminished as habitats become influenced by anthropogenic perturbations. Further studies are required to better describe the retention of microbes from the water column into the benthic habitat, how this capacity serves to influence production and respiration processes in coral reef ecosystems, and to what degree this functionality is lost as habitats degrade.N = 16) over a 24-h diel cycle: between 0900–1159 on day 1 (t0), 2100−2359 on day 1 (t12), and 0900−1159 on day 2 (t24) for a total of 48 samples. On each of the four islands, samples were collected at one reef site without a benthic chamber at t12 to represent an open nighttime reef community without confinement. Time-zero samples were collected immediately after benthic chambers were deployed and therefore should be representative of the ambient reef water community. Reef water samples (1–3 l) were pumped through 0.22 µm 47 mm polyethersulfone filters  that were subsequently dried and frozen at −20 °C.Discrete water samples were collected from each reef plot . Shotgun sequence metagenomic libraries generated ~17 million reads with an average length of 225 base pairs after low-quality reads were removed using Prinseq56. More than six million significant sequence similarities to the SEED protein database were obtained  because 16S genes can be differentiated using a quantitative genetic distance as opposed to protein classifications assigned to taxa of a particular rank. Statistical analyses were completed in R using the Vegan Package57 and with JMP Pro v13 .Putative SSU rRNA gene sequences 25,316) were extracted from the shotgun libraries using GenomePeek6 were exFurther information on experimental design is available in the Supplementary InformationPeer Review FileReporting SummarySource Data


By utilizing the same methodology one can redesign the adapter in order to expand the targets to include viral mRNA and (+) sense cRNA, which are essential to the viral life cycle, or other pathogens. This approach also has the potential to identify and quantify splice variants and base modifications, which are not practically measurable with current methods.For the first time, a coding complete genome of an RNA virus has been sequenced in its original form. Previously, RNA was sequenced by the chemical degradation of radiolabeled RNA, a difficult method that produced only short sequences. Instead, RNA has usually been sequenced indirectly by copying it into cDNA, which is often amplified to dsDNA by PCR and subsequently analyzed using a variety of DNA sequencing methods. We designed an adapter to short highly conserved termini of the influenza A virus genome to target the (-) sense RNA into a protein nanopore on the Oxford Nanopore MinION sequencing platform. Utilizing this method with total RNA extracted from the allantoic fluid of influenza rA/Puerto Rico/8/1934 (H1N1) virus infected chicken eggs (EID Since then, little progress has been made on directly sequencing RNA. Instead, the elucidation of RNA sequences is typically indirect and primarily requires methods that synthesize cDNA from RNA templates. While these methods are powerful2, they suffer from limitations inherent to cDNA synthesis and amplification such as template switching3, artifactual splicing4, loss of strandedness information5, obscuring of base modifications6, and propagation of error7. In 2009, a method for RNA sequencing was developed on the Helicos Genetic Analysis System where poly(A) mRNA is sequenced by the step-wise synthesis and imaging of nucleotides labeled with an interfering but cleavable fluorescent dye8. While the input material requirements for this method are extremely low, the long workflow and short reads are limiting. Nevertheless, these approaches expose two major limitations of RNA sequencing: sequencing by synthesis and short read length. Overall, current technologies for sequencing RNA templates present difficulties in the assessment of base modifications, splice variants, and analysis of single RNA molecules.Decades ago, a method was published describing the use of base-specific chemical degradation with chromatographic and autoradiographic resolution as a way of directly sequencing short stretches of RNA11. Sequencing these viruses has played an important role in their understanding for 40 years13 including the discovery of highly conserved vRNA termini14  of influenza A virus segments18, current methods retain some of the limitations inherent to cDNA-based techniques7. A new tool for long read direct RNA sequencing could reduce these biases and greatly aid efforts to directly sequence influenza A viruses and other RNA viruses.Influenza A viruses are negative-sense segmented RNA virusesi14 Fig. . These 319. The RTA is a small dsDNA molecule  mRNA and a 5′ phosphate (Pi) that ligates to the RNA creating a DNA-RNA hybrid. The RTA also serves as a priming location for reverse transcription of the entire length of the RNA molecule, though the cDNA generated is not sequenced. The DNA-RNA hybrid is then ligated to the sequencing adapter which directs the RNA strand of the assembled library into the nanopore for sequencing19.Oxford Nanopore Technologies (ONT) recently released their direct RNA sequencing protocol. This method involves the sequential ligations of a reverse transcriptase adapter (RTA) and a sequencing adapterule Fig.  that con19 . Of the 171,135 ± 21,987 reads, 98.6 ± 1.4% mapped to the reference sequence Tables , with 10Based on available details on the RTA system, it was possible to make further modification to target other RNA species Fig. . To adap50 4.2 × 1011) preparations (pure) were sequenced via MinION. Two sequencing experiments covered 100% of the coding regions of the PB2, PB1, PA, HA, NP, NA, M, and NS vRNA segments to an average depth 8,360 and 936 respectively  virus  was sequenced via MinION. Three independent sequencing experiments each covered 100% of the coding regions of the PB2, PB1, PA, HA, NP, NA, M, and NS gene segments to an average depth of 2,789 ± 752  harvested from a genetically defined recombinant virus (rA/Puerto Rico/8/1934 (H1N1)) infected chicken eggs  virus  pure and crude virus preparations were amplified by M-RTPCRs Tables . The reas Tables . The maps Tables  with reds Tables . The rea16 amplified genome and MiSeq approach and that data was deposited in GenBank (NCBI).To demonstrate that the adapter targets a region highly conserved among influenza A viruses, we directly sequenced vRNA from four contemporary influenza A viruses: A/Florida/20/2018 (H1N1pdm09), A/Texas/50/2012 (H3N2), A/chicken Ghana/20/2015 high pathogenic avian influenza (HPAI H5N1) and A/British Columbia/1/2015 low pathogenic avian influenza (LPAI H7N9) Table . For the50 of 1.89 × 107. This is well outside the range of most original clinical samples and roughly four orders of magnitude less sensitive than M-RTPCR16.The sensitivity of the direct RNA sequencing of influenza A virus strategy was determined through serial dilution of the RNA from influenza A/Florida/20/2018 (H1N1pdm09) virus. RNA was extracted and diluted fivefold serially to generate five RNA samples with Ct values: 11.6, 14.2, 17.0, 19.6, and 22.3 Table . RNA was20 sequencing of an RNA virus genome by direct RNA sequencing. Using a method originally designed to sequence mRNA, we adapted the target sequence to bind the 3′ sequence conserved among influenza A viruses. The specificity of this adapter allowed efficient sequencing of influenza rA/Puerto Rico/8/1934 virus RNA genomic segments from RNA isolated from purified virus particles (control) or from RNA isolated from a crude extract that contains a myriad of viral and host (chicken) RNAs. Using this adapter, 98.8% of reads from the crude virus RNA preparation mapped to influenza rA/Puerto Rico/8/1934 virus, which is practically as efficient as with the purified virus RNA sample (99.3%). This performance on crude virus stocks demonstrates that the sequence-directed library preparation is a very effective method to select specific target RNA species among a population of RNAs, as the vast majority of reads were to influenza rA/Puerto Rico/8/1934 virus using 12 ribonucleotides as the target sequence.We have demonstrated, for the first time, coding completeThe utility of this adapter was demonstrated by directly sequencing RNA from crude stocks of contemporary influenza A/Florida/20/2018 (H1N1pdm09), A/Texas/50/2012 (H3N2), A/chicken Ghana/20/2015 (H5N1), and A/British Columbia/1/2015 (H7N9) viruses. The adapter was able to target the conserved 3′ termini of this diverse subset of influenza A viruses as all four were sequenced to coding complete coverage and roughly 98% consensus identity to M-RTPCR and MiSeq results. Moreover, the adapter remained efficient with these diverse viruses with >96% of reads mapping to its respective influenza A virus genome.The data shows that further modifications to the adapter could target other RNA species such as RNAs from specific pathogens and different RNA species within a particular pathogen. For example, one could compare (+) sense cRNA [replication intermediate of (−) sense vRNAs], (+) sense mRNAs, or (−) sense RNAs present during RNA virus infections (such as for influenza A viruses). The adapter sequence could be modified to target specific viral families, genera, or species by extending the target sequence and or by adding degeneracies. This is an advantage over poly(A) methods that have a reduced signal-to-noise ratio due to host mRNA. Targeting influenza A vRNA and cRNA independently may prove difficult as there is complementarity between the two conserved termini of the vRNA segments, and therefore high sequence identity between the 3′ termini of the (−) sense vRNA and (+) sense cRNA. Rather, cRNA and vRNA reads can be sorted based on their (+) and (−) polarity, respectively. Moreover, this technique is highly amenable to sequencing a variety of non-poly-adenylated RNAs from hosts and pathogens, including untranslated regions (UTRs), without biasing the sequence to the primer. This allows the examination of the UTRs in their native form, which we have done here with influenza A virus. Genomic length and quantitative sequencing of viral mRNA species, using unmodified kit components, has the potential to provide direct detection of base modifications, splice variants, and transcriptional changes. By examining (−) sense vRNA, native UTRs, (+) sense cRNA, viral mRNAs, and host mRNAs activated during an influenza infection, one could dissect the viral replication processes and observe changes at a given point in time and under different replication conditions, such as viruses used for vaccine production.19. Currently, the RNA input requirements for direct RNA sequencing are high and are not physically achievable with most original clinical samples. While we were able to successfully sequence influenza A vRNA using much less input material than is recommended by ONT, direct sequencing of serially diluted influenza A vRNA revealed that this technique is not sensitive enough for most clinical samples and roughly four orders of magnitude less sensitive than M-RTPCR based sequencing. Hence, direct RNA sequencing is currently limited to cultured viruses. Lessening the RNA input requirement of the direct RNA sequencing would take full advantage of the unbiased nature of direct RNA sequencing and allow for the detection and description of the rich diversity intrinsic to influenza and other viruses. The continuing effort to advance this technology by ONT will undoubtedly result in higher accuracy reads and greatly improved utility.The primary limitations of this technology are the high read level error rate and high input material requirements. Reducing the error rate would enable multiplexing and more accurate consensus sequence determination and is a requirement for understanding nucleotide polymorphisms and genome sub-populations, particularly in viruses such as influenza that have significant intra-host diversity and or base modifications to be identified. There are currently several bioinformatic tools for detecting DNA base modifications such as Tombo, Nanopolish, SignalAlign, and mCaller; however, RNA specific tools have yet to be released21 and propagated in 11 day-old embryonated hen eggs at 35 °C for 48 hours. Allantoic fluid was harvested from the chilled eggs and clarified at 5,400 × g, 10 minutes, 4 °C . The virus was clarified twice more by centrifugation at 15,000 × g, 5 minutes, 4 °C . Virus was pelleted by centrifugation at 39,000 × g, 3 hours at 4 °C . Virus pellets were resuspended overnight in PBS and loaded onto a 30%/55% (w/w) density sucrose gradient. The gradient was centrifuged at 90,000 × g for 14 hours at 4 °C . The virus fractions were harvested and sedimented at 131,000 × g  for 2.5 hours. The resulting virus pellet was resuspended in PBS and aliquoted for future use.Genetically defined rA/Puerto Rico/8/1934 virus was created by reverse geneticsA/Florida/20/2018 (H1N1pdm09), A/Texas/50/2012 (H3N2), and A/British Columbia/1/2015 were propagated in MDCK cells. A/chicken/Ghana/20/2015 was propagated in embryonated hen eggs and harvested as an E1/E3 passage.TM TRIzol® extraction22 according to manufacturer’s instructions with additional considerations for biosafety. The virus was inactivated by the addition of 10 volumes of TRIzol® in a Biosafely Level 2 biosafety cabinet. Influenza A/British Columbia/1/2015 (LPAI H7N9) and A/chicken Ghana/20/2015 (HPAI H5N1) viruses were inactivated by the addition of 3 volumes of TRIzol® in a Biosafely Level 3 enhanced laboratory before removal. Following inactivation, a fume hood was used for the chloroform addition and aqueous phase removal steps. RNA pellets were resuspended in 10–40 µL nuclease free water and quantified by Quant-iTTM RiboGreen® RNA Assay Kit or a QubitTM RNA Assay Kit. Due to the difficulty in acquiring sucrose-purified material, the pure controls were limited to one MiSeq run and two separate MinION experiments. RNA from influenza A/Florida/20/2018 (H1N1pdm09) virus was diluted serially and aliquoted for determining the limit of detection.Enolase II (YHR174W) mRNA is supplied in the ONT materials as the RNA calibration strand (RCS) at a concentration of 50 ng/µL. For influenza A virus samples, total RNA was isolated by Invitrogen10 overhang (Tm ~ 20 °C) to target the ligation of the RTA to mRNA, with 12 nucleotides complementary to the conserved 3′ end of Influenza A vRNA23  respectively and were combined in a 2:3 molar ratio to a total concentration of 1.4 µM. This mixture was used as a direct replacement to the RTA supplied in the protocol for influenza A vRNA samples. Though there is some disagreement regarding the segment specific degeneracies of the 12 nucleotides at the 3′ end of the genome, RTA-U12 is expected to target the segments PA, NP, M, and NS; and RTA U-12.4 is expected to target the segments PB2, PB1, HA, and NA25. For the pure, crude, and contemporary virus experiments, 10 µL of vRNA was ligated to 1 µL of RTA-U12. For the LOD experiment, which also used influenza A (H1N1pdm09) virus, 9 µL of vRNA and 0.5 µL of 50 ng/µL enolase mRNA were combined and ligated to 1 µL of RTA-U12 and 1 µL of the stock RTA.The ONT direct RNA library preparation input material requirement is 500 ng of target molecule in a 9.5 µL volume Table . For mRN26 with the FLU-MinION preset configuration to produce influenza A virus consensus sequences for comparison to MiSeq-derived consensuses. The FLU-MinION preset differs from the default FLU module settings by the following: dropping the median read Q-score filter from 30 to 0, raising the minimum read length from 125 to 150, raising the frequency threshold for insertion and deletion refinement from 0.25 to 0.75 and 0.6 to 0.75 respectively, and lowering the Smith-Waterman mismatch penalty from 5 to 3 and the gap open penalty from 10 to 6. For read-level comparisons of MinION to MiSeq, raw fastqs from both sequencing platforms were mapped with bwa-mem v.0.7.7 algorithm27 to MiSeq + IRMA derived consensus sequences as references. Bwa-mem settings were left default except for the following arguments: “-A 2” and “-B 3”. Figures and tables were created in Tableau v.10.4.3.Adapter ligated RNA was directly sequenced on the MinION nanopore sequencing using a FLO-MIN107 flowcell equipped with the R9 chemistry. The enolase sequencing experiments were operated through MinKNOW versions 1.4.2, 1.7.7, and 1.10.11; the pure sequencing experiments were operated through MinKNOW 1.7.7; the crude, contemporary virus, and LOD 1 sequencing experiments were operated through MinKNOW 1.10.11; and the LOD 2–5 sequencing experiments were operated through MinKNOW 2.1. Raw data was basecalled using Albacore 2.1.10 (released 01/26/2018), and reads were assembled using IRMAAccuracy rate = 1 − average number of insertions, deletions, and minority alleles/sum of aligned bases + number of deletions and insertions at left-adjacent (upstream or 5′ to the site) base per position per segment.Insertion rate = average number of insertions, irrespective of insertion length/sum of aligned bases + number of insertions at left-adjacent base per position per segment.Deletion rate = average number of deletions, irrespective of deletion length/sum of aligned bases + number of deletions at left-adjacent base per position per segment.Substitution rate = average number of minority bases/sum of aligned bases per position per segment.Alignment read lengths were calculated as matching + inserted bases per read (CIGAR M + I).Error rates were calculated against the aligned plurality consensus sequence as follows:16 with SuperScript III One-Step RT-PCR with Platinum Taq High Fidelity (Invitrogen). Following amplification, indexed paired-end libraries were generated from 2.5 µl of 0.2 ng/µL using the Nextera XT Sample Preparation Kit (Illumina) following the manufacturer protocol using half-volume tagmentation reactions. Libraries were purified with 0.8X AMPure XP beads  and assessed for fragment size  and quantitated using Quant-iT dsDNA High Sensitivity Assay (Invitrogen). Six pmol of pooled libraries were sequenced on the Illumina MiSeq with MiSeq v2 300 cycle kit and 5% PhiX spike-in to increase the sequence diversity. Sequence analysis was performed using IRMA26 as part of the current Illumina-based pipeline utilized by the Influenza Genomics Team at the Centers for Disease Control and Prevention.The coding complete influenza A virus genome was amplified with the RNA from all viral samples. The MRT-PCR used the Uni/Inf primer setSupplementary Figures and Table LegendsDataset 1


Drosophila, mouse, and human have shown that RNA editing can be genetically modulated, highlighting loci that quantitatively impact editing of transcripts. The potential gene expression and physiological consequences of these RNA-editing quantitative trait loci (edQTL), however, are almost entirely unknown. Here, we present analyses of RNA editing in a large domestic mammal (Bos taurus), where we use whole-genome and high-depth RNA sequencing to discover, characterize, and conduct genetic mapping studies of novel transcript edits. Using a discovery population of nine deeply sequenced cows, we identify 2413 edit sites in the mammary transcriptome, the majority of which are adenosine to inosine edits (98.6%). Most sites are predicted to reside in double-stranded secondary structures (85.1%), and quantification of the rates of editing in an additional 355 cows reveals editing is negatively correlated with gene expression in the majority of cases. Genetic analyses of RNA editing and gene expression highlight 152 cis-regulated edQTL, of which 15 appear to cosegregate with expression QTL effects. Trait association analyses in a separate population of 9989 lactating cows also shows 12 of the cis-edQTL coincide with at least one cosegregating lactation QTL. Together, these results enhance our understanding of RNA-editing dynamics in mammals, and suggest mechanistic links by which loci may impact phenotype through RNA editing mediated processes.Post-transcriptional RNA editing may regulate transcript expression and diversity in cells, with potential impacts on various aspects of physiology and environmental adaptation. A small number of recent genome-wide studies in  ADAR) family (The process of gene expression involves transcribing the information stored in DNA into messenger RNA (mRNA). In Eukaryotes, most mRNA sequences differ to those of DNA, primarily due to RNA splicing. However, the process of RNA editing can add additional diversity, whereby bases in the transcript are altered in situ by direct enzymatic modification. In metazoan cells, the most common form of RNA editing is deamination of adenosine (A) nucleotides, forming inosine (I), catalyzed by enzymes from the adenosine deaminase acting on the RNA  family .A key function of mRNA editing by ADAR1 is to prevent immune sensing of endogenous dsRNA by MDA5 . Dependicis or trans regulatory elements, or through other mechanisms such as DNA methylation, is thought to account for the majority of genetic variance in phenotypic traits . After applying further quality filtering to the variants , a total of 2413 edited sites were identified. Editing sites in lactating mammary tissue have not been previously reported in bovine studies (or any other species to our knowledge), though of the recent bovine studies examining editing in other tissues, our data set includes 121 of the 1600 sites reported by To identify candidate RNA editing sites, we performed WGS of nine animals for which high-depth RNA-seq data was also available. Animals were sequenced at an average 22-fold read depth for genomic sequence and 104 million read pairs for RNA-seq, with variants called for both DNA and RNA sequence alignments . Variants that were identified from RNA data but found to be absent from DNA data for the same animal were considered candidate sites  with the majority of sites (84.4%) contained in intronic sequences . Edits lSupplemental Figure S1 showing data for all successfully sequenced sites and animals. Importantly, edits were confirmed in at least three of the four sequenced animals for all five sites. An additional two RNA editing sites were also captured in the validation amplicons, and although not targeted for that purpose, represented sites that had also been detected using our RNA-seq-based pipeline . Following RT-PCR and sequencing of amplicons representing four of the animals used for RNA-seq-based edit discovery, five of the eight sites yielded high-quality Sanger traces. pipeline . These dADAR1 gene was approximately 1.5-fold more highly expressed than ADAR2 , but significantly enriched at positions immediately downstream . Similar patterns of upstream underrepresentation and downstream enrichment for guanosine have been reported in the literature . Visual examination of the predicted structures confirmed that the majority of candidate edited sites  are located within regions of RNA with the potential to form double-stranded helices. When only A-to-I edits were considered, a slightly higher percentage  were predicted to occur in such regions. Although some proportion of the 14.9% of sites not observed to reside in double-stranded regions could be assumed to be false-positive edit sites, these inconsistencies could arise from failure to accurately identify base-paired structures, or where the paired strand was more than 1500 base pairs from any edit sites within the gene and therefore not included within the plotted region . Images of the predicted double-stranded secondary structures are displayed in Supplemental Figure S3.Since the ADAR1 and ADAR2 enzymes target double-stranded sections of RNA , 2000, in = 1195) were predicted to base-pair with a uridine residue, in accordance with standard Watson–Crick base-pairing rules . The majority of the remaining sites were situated opposite to a cytidine residue , in agreement with previous literature  where the predicted base pair of the edit site was a guanosine, compared to other bases. These edit sites were also the least frequently observed, with only 24 observations among the 2047 within double-stranded regions. Conversely, the most stable modification is expected when the paired base is a cytidine, and a higher median Φ value was observed for these sites (15.9% of reads). Values for paired adenosine and uridine bases were intermediate, at 15.2% and 11.9% of reads edited, respectively.N = 117 after Bonferroni adjustment; Supplemental Fig. S4), with the distribution of effects showing a strong bias toward genes whose expression was negatively correlated with Φ . To assess the potential role of ADAR expression in this relationship, we also repeated this analysis after adjusting for expression of the ADAR gene. This analysis had no obvious impacts on the strength of correlation , suggesting that these impacts were unlikely to be modulated by ADAR expression per se. Although it is unknown whether editing is driving these effects, these observations highlight a potential mechanism by which RNA editing may be impacting lactation phenotypes through regulation of mRNA abundance.Given the observation of widespread editing across diverse mammary transcripts, we wondered what physiological effects might be attributable to these modifications. Since editing has previously been proposed as a mechanism to modulate gene expression through microRNA-based mechanisms , through−8). Of these 187 edQTL, 134 sites harbored the top associated variant within 500 kbp of the editing site, and could therefore be assumed to be regulated in cis. These sites mapped to a total of 89 genes, with the CD46, CSN3, ELF5, HOOK3, and HPSE genes each containing five or more associated sites. The full list of 134 sites is detailed in Supplemental Table S2. Low levels of inflation in the test statistics were observed across the 187 edQTL GWAS , indicating that the GLS models were adequately controlling for relatedness between the animals.Having defined Φ values for all animals and all curated sites, we next used these data as phenotypes for genome-wide association studies (GWAS), with the aim of discovering RNA editing QTL. These models comprised generalized least squares (GLS) models, modeling the covariance between animals using a numerator relationship matrix based on pedigree records to account for underlying population structure and relatedness between animals . Using 630,774 genotypes from the Illumina BovineHD marker panel and logit-transformed Φ-values as phenotypes, 187 of the 2413 RNA editing sites exhibited edQTL that were significant after Bonferroni adjustment for multiple testing  that mapped within the double-stranded region containing that site. HOOK3 gene.We next aimed to fine-map signals using imputed WGS data. Imputation was conducted using methods analogous to those previously described . Variant pairs were also filtered to exclude those that had fewer than five reads encompassing both sites. This yielded 70 pairs of edited bases and WGS variants, representing 49 distinct edit sites in 37 genes (where the reduced number of edits compared to pairs reflected sites that were paired with multiple variants). Association analysis revealed strong phase enrichment for the majority of pairs, with 58 of 70 significant at the Bonferroni threshold of P < 7.14 × 10−4 .Since base substitutions within double-stranded RNA transcripts could be assumed to modify the structure and stability of such molecules, we reasoned that colocated, RNA editing-associated WGS variants would make strong candidate causal variants for the observed edQTL. To investigate these relationships, edit sites that exhibited significant N = 144 pairs; where double-stranded regions were predicted as previously described). We hypothesized that WGS alleles that were complementary to the base on the opposite, paired strand would increase the substrate affinity for ADAR enzymes, thus leading to increased editing for these sites (N = 125 pairs remaining). Using a one-sided t-test to assess whether the anticipated sign of effect between edits and complementary and noncomplementary alleles was different than zero, a modest, but significant effect was observed (P = 0.012). This observation, and the allele-specific editing results described above, supports the hypothesis that the mechanism of genetic modulation of editing at least partly derives from the impact of these variants on RNA secondary structures.The second analysis focused only on pairs of edited bases and edit-associated WGS variants colocating to double-stranded structures  in the DESeq R package , along with several genes for which genetic impacts on milk composition or production have previously been published, including MARC1 , correlations of greater than 0.707 were observed between edQTL and eQTL, potentially suggesting a gene expression consequence of the observed edQTL effects. These 15 sites mapped to nine discrete genes.To test for shared regulatory architecture between the eQTL and colocated edQTL, Spearman correlations were calculated using the association escribed . This mecis-edQTL/eQTL pairs would reflect this relationship, where we could anticipate allelic effects to show antagonistic signs of effect between edQTL and eQTL. To test this, pairs of eQTL and edQTL that were significantly correlated were identified following Bonferroni adjustment , and subsequently classified as to whether the effect of the top edQTL variant had the same or opposite sign of effect to the eQTL. Given our prior hypothesis that the sign of effects would be reversed, we conducted a one-sided t-test that the mean sign of these effects was negative. This yielded a marginally significant P-value of 0.0250. This observation suggests that, at least for the loci for which eQTL/edQTL pairs are most strongly correlated , increased levels of editing lead to decreases in mRNA expression.Given the bias toward negatively correlated gene expression and editing per se (see “Relationship between RNA editing and transcript abundance” section above), we also wondered whether cis-edQTL intervals. Examining cosegregation signals using the same methods applied to analysis of eQTL data, 10 edited sites exhibited edQTL that were strongly correlated (r > 0.7) with at least one production QTL .Since edQTL might have further effects on lactation traits such as milk yield and milk component concentration phenotypes, we conducted association analysis on these phenotypes using imputed WGS genotypes and the GLS models described above. To perform association analysis of lactation traits, herd test data for 9989 cows was used to test for the presence of fat, protein, lactose, and milk yield QTL that were colocated to each of the 134 tion QTL . These e compare D. AdditiWe report the discovery of 2413 RNA editing sites in the bovine mammary transcriptome, and subsequently explore the genomic context and properties of these sites. We note strong correlations between the extent of RNA editing and the overall abundance of these transcripts, and we further report genome-wide association analyses of editing to identify genetic modulators of these effects. Association analysis of gene expression and lactation phenotypes for variants mapping to edQTL intervals reveals a number of overlapping signals at these locations, providing a potential mechanistic linkage between the editing of transcripts and mammary and lactation physiology. We discuss some of these findings in more detail, below.Alu repeat elements, where almost all adenosines are edited (The majority of editing sites discovered were A-to-I edits (2380 of 2413). This percentage (98.6%) is higher than the 80%–88% reported previously for the cattle transcriptome , but is e edited . Howevere edited , the obsPrevious work in mice  has repoThe fact that edited sites, while resembling heterozygous SNPs, will in general not approximate a 50% allelic balance, will also have impacted our ability to discover sites, given that most variant callers assume a diploid state. We chose a variant caller (FreeBayes) that should be less sensitive to allelic imbalances than other commonly applied callers such as HaplotypeCaller (GATK RNA-seq Best Practices), though it can be assumed that the results reported here likely underrepresent sites with low levels of editing.In total, 33 (1.4%) of the 2413 edited sites reported in this study were not canonical A-to-I edits. The three most common noncanonical edit types previously reported for cattle are C-to-U, G-to-A, and U-to-C , while GhnRNPK  of reduced mRNA production, and other biases relating to library preparation or sequencing  could coCSN1S1, CSN2, and CSN3 genes, as well as the antimicrobial LPO and LTF proteins. A number of other edited genes are important mediators of milk fat synthesis  encoded by the CA, GPAM ) and secH, PLIN3 ), or are[SLC37A1 , ABCG2  as a phenotype. This analysis yielded significant  editing . This hu editing , and two editing  and Drososophila , similarcis-edQTL, we identified 41 with significant cis-eQTL, 15 of which also showed strong correlation of association statistics (r > 0.707). We also assessed correlations between edQTL and colocated lactation QTL, determined in a separate population of 9989 outbred cows. Correlations greater than 0.707 were observed for A-to-I sites in the CD36, FBXW8, HOOK3, HPSE, and TLR6 genes. Two sites in the CD36 gene were correlated with colocated fat concentration and milk yield QTL, with lower correlations also observed for the lactose yield and protein concentration phenotypes. This gene encodes a component of the milk fat globule membrane, comprising a glycoprotein that is implicated in fatty acid transport  was sequenced using RNA-seq only, and used to quantify the level of editing at the sites first identified in the discovery set. The quantification animals were used to generate editing proportion phenotypes (Φ) for use in edQTL mapping.RNA sequencing was performed on mammary biopsies from all 364 animals, as reported previously . BrieflyWGS was performed for the animals in the discovery set using methods we have described previously , 2016. AVariant calling was performed on the nine discovery set animals, for both DNA and RNA alignments, using Freebayes version 1.2.0 . Reads tSupplemental Figure S7.Variants present in the RNA-called set but absent from the DNA-called set formed the initial set of potential RNA edits, yielding a set of 9520 candidate RNA editing sites. These sites were further subjected to manual evaluation to remove sites where, for example, no read coverage was available in the DNA sequence, or where alignments in the RNA sequence appeared anomalous. This resulted in a conservative subset of 4522 sites. Bases were counted at each site in the discovery set animals, and sites were excluded where fewer than two thirds of the animals had an edited read, or fewer than two thirds of animals had fewer than five reads mapping to the site. Using these criteria yielded a final set of 2413 manually appraised sites. An example region comparing DNA and RNA sequencing data for three animals is illustrated in Editing proportions for each of the 2413 verified sites were calculated for each cow in the quantification set by reporting the base composition of reads in the RNA alignments. Edit sites were allocated to genes using the Ensembl Variant Effect Predictor , requiriLocal mRNA secondary folding structure was predicted for each editing site. Within each gene, sequence was extracted for an interval that included 1.5 kbp of sequence upstream and downstream from the most 5′ and 3′ edited sites. In cases where the total sequence extracted for a gene exceeded 15 kbp, multiple, shorter sub-sequences were used.Supplemental Fig. S2). Dots were placed where at least 11 of the 15 nucleotides, centered on each pair of positions, were complementary. Diagonal lines appearing in the plots are indicative of long strands of complementary sequence, highlighting potential double-stranded regions for examination, by manual observation, for the presence of edited sites. These regions were also processed using the bifold-smp program from the RNAstructure software package . Variants with minor allele frequencies <1% were removed. As a filter for erroneous SNP assays, tests were conducted for Hardy–Weinberg equilibrium  using PLAs described above, the base composition of RNA editing sites was determined in the quantification set of animals to determine the proportions of edited reads for each animal and site Φ; . To satiy = Xβ + ɛ, where the error term (ɛ) has the conditional mean ɛ|X) = 0 and covariance Var (ɛ|X) = W, where I is the identity matrix and Each genotyped variant was fitted individually using the GLS model described in χ2 statistic was calculated, with the ratio of the observed median and the expected median (0.4549) yielding the inflation statistic for that edited site. Inflation is indicated when the value of this statistic exceeds unity.To confirm that shared ancestry was not inflating the GLS results, the statistic As part of a previous study , gene exR2< 0.95 were excluded for quality filtering purposes.To map variants at a higher resolution around identified edQTL, WGS variants were imputed into the quantification animal set using a previously described reference population of 565 animals , 2016, ccis-edQTL markers, were imputed to WGS resolution using Beagle 4 , then normalized using the variance-stabilizing transformation (VST). RNA editing was quantified using the logit function on the proportion of edited reads (Φ), with Pearson correlations and significance levels for transcript abundances calculated using R . For theTo examine the effect of RNA editing on milk production traits, milk fat, protein, and lactose phenotypes were derived for 9989 cows from measurements taken as part of standard herd-testing procedures. Milk samples were processed by LIC Testlink (Newstead) using Fourier transform infrared spectroscopy on Milkoscan FT6000 (FOSS) and Bentley FTS (Bentley) instruments. Individual phenotypic measurements for each animal were estimated using repeated measures models in ASReml-R as described in N = 6481), BovineHD (N = 62), and GeneSeek Genomic Profiler BeadChip . Five hundred and one cows had been genotyped on multiple panels. All cows were imputed to WGS resolution for the 134 edQTL intervals using Beagle 4 as described above. These genotypes were subsequently used with the milk-sample-derived phenotypes to explore QTL at each of these intervals, using the GLS model described above.These 9989 cows had previously been genotyped on several different SNP platforms: Illumina Bovine SNP50 . Candidate sites were also restricted to those appearing in at least 305 animals . Primers were then designed to amplify each candidate edit in an ∼300–400 bp amplicon.Reverse transcriptase PCR (RT-PCR) and Sanger sequencing were performed to attempt to validate the subset of candidate variants. Synthesis of cDNA was performed using total RNA template in conjunction with random hexamer primers and the standard synthesis conditions of the SuperScript III First-Strand Synthesis System (Thermofisher). Four samples were targeted for cDNA synthesis, representing four of the nine animals used for the edit-site discovery phase of the broader study.Supplemental Table S4. Generation of transcript amplicons was performed using KAPA2G Robust DNA polymerase  with the following thermocycler conditions: 3 min initial denaturation at 95°C, followed by 40 cycles of 15 sec denaturation at 95°C, 15 sec annealing at 60°C, and 30 sec extension at 72°C, followed by a final extension at 72°C for 1 min.Primer sequences can be found in Supplemental Figure S1.Amplicons were visualized by electrophoresis on a 1.2% agarose gel prior to purification using NucleoSpin Gel and PCR Clean-up kit (Macherey-Nagel) and direct sequencing using Applied Biosystems BigDye version 3.1 terminator chemistry (Life Technologies/Applied Biosystems) on the Applied Biosystems 3130xL instrument (Life Technologies/Applied Biosystems). Sequencing was performed at the University of Auckland DNA Sequencing Facility . Traces for five sites are presented in All animal experiments in this study were conducted in accordance with all rules and guidelines in the New Zealand Animal Welfare Act 1999. As the majority of data were generated as part of routine commercial activities, formal committee assessment and ethical approval (as defined by the above guidelines) were not required. Samples were obtained for the mammary tissue biopsy experiment in accordance with protocols approved by the Ruakura Animal Ethics Committee, Hamilton, New Zealand . No animals were killed for this study.Sequence (BAM) files containing the WGS and RNA-seq reads sequenced from the nine discovery set cows, have been uploaded to the NCBI sequence read archive (SRA). BioProject accession number: PRJNA446068 (SRP136662); BioSample accession numbers: SAMN08810150 to SAMN08810167.Supplemental material is available for this article.T.J.L., C.C., K.T., S.R.D., B.L.H., and M.D.L. are employees of Livestock Improvement Corporation, a commercial provider of bovine germplasm. The remaining authors declare that they have no competing interests.


Long-read nanopore sequencing by a MinION device offers the unique possibility to directly sequence native RNA. We combined an enzymatic poly-A tailing reaction with the native RNA sequencing to (i) sequence complex population of single-stranded (ss)RNA viruses in parallel, (ii) detect genome, subgenomic mRNA/mRNA simultaneously, (iii) detect a complex transcriptomic architecture without the need for assembly, (iv) enable real-time detection. Using this protocol, positive-ssRNA, negative-ssRNA, with/without a poly(A)-tail, segmented/non-segmented genomes were mixed and sequenced in parallel. Mapping of the generated sequences on the reference genomes showed 100% length recovery with up to 97% identity. This work provides a proof of principle and the validity of this strategy, opening up a wide range of applications to study RNA viruses. Therefore, novel RNA viruses, or coinfections might not be discovered by this approach.Infectious disease epidemics are primarily driven by RNA viruses  and hencWe established a rapid procedure and evaluated the feasibility of MinION for complete sequencing of multiple, single-stranded RNA (ssRNA) viruses in a single reaction to obtain complete genomes. Our approach combines (1) poly(A)-tailing using simple enzymatic reaction, (2) native RNA sequencing by MinION, and (3) real-time analysis aiming to simultaneously detect and characterize multiple RNA viruses. A mix of negative(-) and positive(+) ssRNA viruses, including Mayaro virus (MAYV), Venezuelan equine encephalitis virus (VEEV), Chikungunya virus (CHIKV), Zika virus (ZIKV), vesicular stomatitis Indiana virus (VSV), and Oropouche virus (OROV) were used in this demonstration.E. coli poly(A) polymerase (EPAP), followed by sequencing, and 3) Applying ribosomal RNA (rRNA) depletion step to host-rRNA contaminated samples, followed by poly(A)-tailing and sequencing. Then, we applied the optimized protocol on a mix of all RNA viruses.To establish an optimal procedure for real-time native RNA sequencing, we performed three experiments. 1) Sequencing two polyadenylated RNA viruses without RT, suggested by the original protocol, 2) Adding poly(A)-tail to non-polyadenylated RNA phage and ZIKVs using In the first scenario, naturally polyadenylated (+)ssRNA alphaviruses, MAYV and VEEV, genome size approximately 11.5 kb, were used. Extracted RNA  of MAYV and VEEV were pooled at approximately the same concentration (∼350 ng) and used for library preparation of the dRNA-seq protocol, following the manufacturer’s recommendations, except the RT step was skipped . The prepared library then was loaded into ONT flow cell and sequenced. The sequenced reads were mapped on the genomes and analyzed , resultiThe second scenario sought to evaluate the feasibility of using the poly(A)-tailing reaction coupled with dRNA-seq, (+)ssRNA. Bacteriophage MS2 was used first. Five hundred nanograms of 3.57 kb RNA was treated with EPAP using an optimized poly(A)-tailing reaction . Poly(A)-tailed RNA was then used as input for library preparation and sequencing in the same way as described above, resulting in a complete read of the bacteriophage genome . We thenIn the third scenario, we introduced host rRNA depletion step using a rRNA removal kit, to increase the amount of viral RNA reads. The rRNA depletion was performed before poly(A)-tailing and dRNA-seq. The ZIKV sample was used to evaluate changes in ratio of viral/host RNA. We found that introducing the depletion step resulted in a 160-fold increase in proportion of viral RNA reads/ host reads compared to the non-depleted sequencing. However, we observed high proportion of low-quality sequences compared to non-depleted scenario. We further tested the impact on rRNA depletion step on artificial mixing of 2% of bacteriophage MS2 RNA and 98% of total RNA extracted from mouse cells. The rRNA depletion kit was used for the mixture as described above. Again, the proportion of low quality reads was increased as seen in rRNA-depleted ZIKV sample . This prFinally, we applied the established procedure to sequence a pool of six RNA viruses including MAYV, VEEV, CHIKV, ZIKV, VSV, and OROV, which were each purified from supernatant of varying cell lines and RNA was extracted from purified virions . This mixed RNA viruses has diversified genomic property i.e., (+)ssRNA, (-)ssRNA, lack/presence of poly(A)-tail, segmented/non-segmented genomes . The RNAWe inspected the mapped reads based on strand-orientation and found feasibility of simultaneous detection of viral genome and its transcripts . We obseThis versatile protocol can contribute viral RNA research by (i) retaining the strand direction; this facilitates simultaneously detection of genome, subgenomic mRNA/mRNA, recombinant, complementary RNA intermediates (ii) increasing the accuracy of determining transcriptomic architecture and recombination with no need for assembly (iii) providing a fast and easy method to perform direct sequencing of any RNA virus (iv) directly sequencing of novel RNA viruses with no specific primer required, including novel ones and (v) saving on the budget see . In addiMayaro virus , OROV  and VEEV  were cultivated on Vero cells in MEM with 5%FBS and 1%PenStrep. The infection was made on 80% confluent cells with an MOI of 1 for MAYO and 0.5 for OROV. Both viruses were incubated with cells for 3 days. The viruses were then aliquoted and centrifuged according to protocol. The TRIzol LS extraction (Invitrogen) was carried out following the manufacturer’s instruction for RNA extraction with the exception of adding glycogen after separating the aqueous phase from the organic layer and interphase. Purified RNA was resuspended in 50 μl RNase-free water and stored at -70°C.g for 20 min. The cell supernatant was stored at -80°C until use and viral RNA was isolated from the supernatants. RNA was isolated using RNAzol RT (MRC) with the Direct-zol RNA miniprep kit (Zymo Research) according to manufacturer’s instructions, with one additional wash step.CHIKV  was propagated in Vero 76 cells (ATCC CRL-1587) grown in MEM-E with 10% FBS. After CPE was monitored, the cell supernatant was harvested and clarified with a low-speed centrifugation at 4,000 ×g for 10 min then the supernatants were layered on top of a 20% sucrose cushion and pelleted at 100,000 ×g for 1 h. The virus pellet was resuspended in Tris–saline, pH 7.4 and stored at -80°C. The viral pellet was subjected to a phenol-chloroform RNA extraction from TRIzol LS (Invitrogen) following manufacturer’s protocol with the exception of adding glycogen after separating the aqueous phase from the organic layer and interphase. Purified RNA was resuspended in 20 μl RNase-free water and stored at -70°C.BHK-21 cells were infected at a multiplicity of 0.1 and the culture medium was collected after 22 h. The culture media were first clarified by centrifuging at 8,000 ×Two strains of ZIKV were used for this study.(1)1Genomic RNA of ZIKV  used for method optimization was purchased from ATCC.(2)g for 20 min. The cell supernatant was stored at -80°C until use and viral RNA was isolated from the supernatants. RNA was isolated using RNAzol RT (MRC) with the Direct-zol RNA miniprep kit (Zymo Research) according to manufacturer’s instructions, with one additional wash step.ZIKV  used in pooled viruses sequencing was propagated in Vero 76 cells grown in MEME (GIBCO Laboratories) with 10% fetal bovine serum. After CPE was monitored, the cell supernatant was harvested and clarified with a low-speed centrifugation at 4,000 × 2RNA from bacteriophage MS2 (Sigma) is composed of 3569 nucleotides (Genbank no: NC_001417.2). MS2 RNA is free of host nucleic acids and proteins.RNA isolation was performed from a mouse cell line with the Direct-Zol RNA miniprep Kit (Zymo Research) as per manufacturer’s instructions. Total RNA was eluted in 50 μl nuclease free water and stored at -80°C.Host cytoplasmic and mitochondrial rRNA was depleted from the samples using Ribo-Zero Gold kit (Illumina) according to manufacturer’s instructions. Briefly, magnetic beads were washed, samples were treated with rRNA removal solution, rRNA was removed, and rRNA-depleted samples were purified.® 2.0 Fluorometer (ThermoFisher Scientific) and Nanodrop Spectrophotometer (ThermoFisher Scientific). The Qubit® assay uses a Qubit RNA BR (Broad-Range) Assay Kit (ThermoFisher Scientific).RNA was quantified using a QubitE. coli EPAP (NEB# M0276) was designed to perform in a 26 μl reaction . Purified RNA was treated with 2.5 μl 10X E. coli Poly(A) Polymerase Reaction Buffer (supplied with the enzyme), 4.5 μl ATP (10 mM) (supplied with the enzyme), and 4 μl EPAP (NEB) at 37°C for 10 min. Poly(A)-tailed RNA was then cleaned using 2.5× (by volume) AMPureXP beads (Beckman Coulter) and eluted with 11–15 μl nuclease free water (NEB), 2 min at room temperature. Cleaned Poly(A)-tailed RNA was incubated for 1 min at 70°C and immediately placed on ice to remove secondary structure. The cleaned Poly(A)-tailed RNA was used as input for dRNA-seq library preparation.To obtain high quality RNA for further preparation, extracted RNA of each virus received from a different independent lab was purified and concentrated using AMPureXP beads (Beckman Coulter) and eluted in 15 μl nuclease-free water (NEB). Purified and concentrated RNA was incubated at 70°C for 2 min and immediately placed on ice to avoid secondary structure formation. Poly(A)-tailing reaction using Direct RNA sequencing was performed using the Direct RNA Sequencing Protocol (SQK-RNA001 kit) for the MinION. Some steps of the manufacture protocol were modified. First, the ligation reaction of RNA and adaptor was extended from 10 to 15 min. At this step, control RNA (RCS) was not added. Second, the RT (50 min) step was skipped in our protocol. Third, wire-bored tips (Axygen) were used for mixing AMPureXP beads (Beckman Coulter)-RNA. RNA library was eluted and loaded onto a flow cell for sequencing. Sequencing of the RNA was performed on a single R9.4/FLO-MIN106 flow cell on a MinION Mk1B for ∼8 h.Immediately after loading the library onto a flow cell and sequencing, base-calling was started using the local-based software, Albacore version 2.3.1 (ONT) with the (–disable_filtering -q 0) command modifications from default. We first filtered out the sequenced reads below a size of 200 bases to avoid short, low-quality reads. The remaining reads were mapped to viral genomes and the host genomes using Minimap2 version 2.9  with thePRJNA493665.The sequence native RNA data of six viruses has been submitted to GenBank and is publicly available under the Bioproject number IN and TW designed and conceived the project. IN, CJ, and DU supervised the study. CJ, MT, JL, AT, JP, BK, NA, AS, DC, CC, MW, WK, RS, and NH performed viral cultivation and RNA extraction. TDW and TW optimized library preparation protocol. TW and SK conducted MinION sequencing. PJ and IN performed computational analysis. All authors participated in interpreting the results and writing the manuscript, and read and approved the final version of this manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In most organisms, ribosomal RNA (rRNA) contributes to >85% of total RNA. Thus, to obtain useful information from RNA-sequencing (RNA-seq) analyses at reasonable sequencing depth, typically, mature polyadenylated transcripts are enriched or rRNA molecules are depleted. Targeted depletion of rRNA is particularly useful when studying transcripts lacking a poly(A) tail, such as some non-coding RNAs (ncRNAs), most bacterial RNAs and partially degraded or immature transcripts. While several commercially available kits allow effective rRNA depletion, their efficiency relies on a high degree of sequence homology between oligonucleotide probes and the target RNA. This restricts the use of such kits to a limited number of organisms with conserved rRNA sequences. In this study we describe the use of biotinylated oligos and streptavidin-coated paramagnetic beads for the efficient and specific depletion of trypanosomal rRNA. Our approach reduces the levels of the most abundant rRNA transcripts to less than 5% with minimal off-target effects. By adjusting the sequence of the oligonucleotide probes, our approach can be used to deplete rRNAs or other abundant transcripts independent of species. Thus, our protocol provides a useful alternative for rRNA removal where enrichment of polyadenylated transcripts is not an option and commercial kits for rRNA are not available. Yet, the large proportion of ribosomal RNA (rRNA), comprising >85% of total RNA in most organisms, complicates detection of low abundant transcripts. To increase the sequence coverage of the transcripts of interest, highly abundant transcripts, such as rRNAs, are typically removed from the pool of total RNA prior to sequencing4.Massive parallel sequencing has become the gold standard for transcriptome analyses and has been employed in organisms as diverse as humans5, but it cannot be used if the RNA of interest is lacking a poly(A) tail. This is the case for partially degraded samples6, many short and long ncRNAs7, newly transcribed, unprocessed transcripts8 or RNA from bacteria9. To study these classes of RNA by RNA-seq, hybridization-based rRNA depletion is typically performed using one of the available kits that follow two approaches. One approach is to capture rRNA with complimentary oligos that are coupled to paramagnetic beads, followed by removal of the bound rRNA. Kits following this approach include, for example, the RiboMinus Transcriptome Isolation Kits (ThermoFisherScientific). An alternative strategy is to hybridize complementary DNA oligos to rRNA followed by degradation of the RNA:DNA hybrids using RNaseH11, e.g. NEBNext rRNA Depletion Kits (New England Biolabs). To ensure efficient rRNA depletion and minimal removal of unrelated transcripts, both approaches require a high degree of sequence homology between rRNA transcripts and DNA probes. This restricts the use of the available commercial kits to organisms with rRNA sequences matching those of the provided probes. As a consequence, no commercially available rRNA depletion kits exist for many organisms. However, even if a suitable kit does exist for the organism studied, that oligo sequences and buffer compositions are typically not disclosed poses problems to reproduce analyses if a manufacturer decides to change a kit’s composition or to terminate its production. For example, despite significant differences between human and T. brucei rRNA sequences, the RiboMinus Eukaryote Kit  has been successfully used to deplete trypanosomal rRNA13. However, following a change in the kit’s composition, the manufacturer no longer recommends the kit for the depletion of trypanosomal rRNA . Similar problems arise in case of production stops. Even though a recent study comparing three kits for the depletion of bacterial rRNA found the Ribo-Zero kit (Illumina) to exhibit the highest efficiency14, production of this kit has been discontinued as of November 2018.Generally, one of two strategies is used to remove rRNA from total RNA, enrichment of mature polyadenylated (poly(A)) mRNA or targeted depletion of rRNA. The former is based on the use of oligo(dT) primers during reverse transcription of RNA into cDNA. This approach typically reduces the levels of rRNA to less than 5%Thus, our goal was to establish a protocol for the specific depletion of rRNA molecules that would allow the generation of high-quality transcriptome analyses without the need for commercially available kits.Here, we describe an efficient and highly specific rRNA removal approach that can be easily adapted to deplete rRNA or other transcripts of any species. Using a set of only 12 biotinylated DNA oligos, we were able to reduce the levels of the most abundant rRNA transcripts to less than 5% of the total RNA with minimal off-target effects.T. brucei ribosome contains more then 50 different rRNAs15. Sequencing total RNA, we found that 28S alpha, 28S beta and 18S are the most abundant rRNA transcripts in T. brucei, contributing to 75% of the total T. brucei RNA  of biotinylated oligos. Based on the binding capacity of the beads (Dynabeads MyOne Streptavidin C1) and the size of our oligos, 1.8 mg and 3.6 mg of beads seemed ideal to capture 2 µg and 4 µg of oligos, respectively.Previously, a template-to-probe mass ratio of 1:2 has been successfully used for the depletion of bacterial rRNAAnalyzing depleted and control RNA by gel electrophoresis, we observed the most efficient rRNA depletion when 4 µg of probes were used Fig. . In addiUsing these conditions, RNA-seq analysis of the rRNA-depleted and control samples indicated that following 0 (control), 1, 2 or 3 rounds of oligo capture, rRNA  contributed to 75.6%, 77.6%, 30.4% and 4.3% of total RNA, respectively  to be significantly (padj < 0.1) different by more than 2-fold after 1, 2 and 3 rounds of oligo capture, respectively, compared to the untreated control,  tail, such as many non-protein coding transcripts and immature transcripts, eliminates the possibility of using strategies enriching for polyadenylated RNA. Instead, methods to specifically deplete rRNA are needed. Our RNA-seq data indicated that depletion of rRNA greatly improves the coverage across most genes Fig. .Figure 420, we investigated whether very long transcripts or transcripts with a short half-life were underrepresented in poly(A)-enriched RNA datasets compared to our rRNA depleted RNA-seq data. While no general correlation could be observed  data compared to our dataset (fold-change (log2) = −3.298; padj ≤ 0.1).To better understand the effects of rRNA depletion and mRNA-enrichment-based approaches on transcriptome data, we compared the transcriptome data generated in this study with previously published data generated from poly(A)-enriched RNA and RNA from which the rRNA had been removed using the RiboMinus Eukaryote Kit. We found our dataset to correlate strongly with previously published RNA-seq datasets Fig. . Yet, fo22. Such reads could be splicing intermediates or ncRNAs.Overall, we found that transcriptome data from our rRNA-depleted pool of RNA contained a higher percentage of reads aligning outside of ORFs than reads from a poly(A)-enriched RNA pool: 79.8% compared to 54.5%We describe the establishment of a highly specific and efficient approach to deplete rRNA from total RNA extracts that can be easily adapted to remove any species-specific rRNA or other abundant transcripts that may mask signal from low abundance transcripts.20.Performing a systematic RNA-seq analysis following multiple rounds of rRNA depletion, we found that 3 rounds of probe capture were necessary to reduce rRNA levels to <5%. No rRNA depletion was observed following 1 round of oligo capture. We suspect that streptavidin-coated beads have a higher binding affinity for unbound hybridization probes than for probes bound to rRNA. Thus, in the first IP we may have pulled out only unbound probes. In addition, analysis of RNA-seq data revealed a small set of transcripts that was co-depleted with rRNA. Surprisingly, the degree of co-depletion did not correlate with the degree of sequence homology between the co-depleted transcripts and the probes. Thus, we suspect that the off-target effects may be caused by non-specific binding of some transcripts to the streptavidin-coated beads. Given that the off-target depletion was reproducible, it should be possible to normalize for the observed co-depletion if necessary. In addition, the reproducibility means that the co-depletion will not affect comparative RNA-seq analyses. If a specific transcript is co-depleted at similar levels in RNA from wild type and mutant cells, the co-depletion will not affect the measurements of changes in transcript levels. Finally, we suspect that strategies employing enrichment of polyadenylated transcripts introduce biases and that differences in poly(A) tail length may affect the efficiency of poly(T)-primed reverse transcription23 or a different life cycle stage11. Comparing reads mapping to ORFs, we observed very high correlations, underscoring the reproducibility of the different methods. However, in our dataset a much higher percentage of reads mapped to regions outside of annotated ORFs. We suspect this increase to be the result of the lack of enrichment for polyadenylated mRNA and to better represent the true distribution of cellular RNA.To evaluate the robustness of our protocol, we compared the distribution of RNA-seq reads from our rRNA-depleted samples to previously published RNA-seq datasets derived from poly(A)-enriched samples. RNA-seq data from samples in which rRNA was depleted by hybridization to complementary DNA oligos and RNaseH digestion were not included in the comparison since the RNA was isolated either from a genetically manipulated cell lineT. brucei transcriptome contains several other highly abundant transcripts such as VSG-2 transcripts  or rRNAs from the gamma, delta and zeta subunits . To increase the detection of low abundance mRNA even further, our set of 12 oligos may be extended to target other highly abundant transcripts. While the need for three rounds of depletion adds to the cost of our approach, the cost per rRNA depletion is still lower than it would be with most commercially available kits. To further reduce the costs, we propose regeneration of the streptavidin-coated magnetic beads. It has been shown that the incubation of beads in water at temperatures above 70 °C destroys the biotin-streptavidin interactions without denaturing the proteins24. Alternatively, beads have been regenerated at 90% efficiency by exposure to a solution containing 25% aqueous ammonia and 25% aqueous ammonia in methanol (9:1) at 25 °C25.In this analysis we focused on the depletion of five rRNA transcripts. However, the In summary, our study shows that organism-specific design of hybridization probes can be successfully used for the depletion of abundant transcripts. We describe a protocol that allows the efficient depletion of rRNA with little off-target effects. Thus, our protocol provides a useful alternative for the depletion of rRNA where enrichment of polyadenylated transcripts is not an option and commercial kits for rRNA removal are not available.T. brucei derived from the Lister 427 bloodstream-form MITat 1.2 isolate was cultivated at 37 °C and 5% CO2 in HMI-11 medium (HMI-9 medium26 without serum plus) up to a density of 0.9 × 106 cells/ml. 45 million cells were harvested at 1,500 g and 4 °C for 10 min. The cell pellet was washed with 1× TDB . RNA isolation was performed using the NucleoSpin RNA kit  with minor changes. The cell lysis buffer was modified by adding 3.8 µl 1 M RNAse-free dithiothreitol  and 1 μl of 1:10 Ambion ERCC RNA Spike-In Mix .Wild type Selected oligonucleotides were ordered with a 5´-biotin tag and HPLC-purified from Sigma-Aldrich. Each oligo was diluted to 100 μM in nuclease-free 10 mM Tris pH 8 . The rRNA depletion mix was generated by combining equal volumes of each 100 μM oligonucleotide stock.19. All solutions were kept free from nucleases. For each hybridization reaction, 2 μg of total RNA were mixed with 10 μl of formamide , 2.5 μl of 20× SSC , 5 μl of 0.005 M EDTA pH 8 , 2.48 μl of 100 μM rRNA depletion mix  and RNAse-free water  to a total volume of 50 µl. Hybridization was performed in a Bio-Rad C1000 Touch Thermal Cycler capable of performing temperature ramps with the following program: 5 min at 80 °C, ramp down to 25 °C at intervals of 5 °C per minute. Subsequently, 2 μl of RNAse-OUT  and 50 μl of 1x SCC containing 20% formamide were added. Dynabead MyOne Streptavidin C1 beads  were prepared as recommended by the manufacturer for RNA applications and immobilization of nucleic acids. For each round of oligo capture 120 μl (1.2 mg) of magnetics beads were prepared (unless indicated otherwise). For the first round of depletion, the hybridization reaction was added to the beads, incubated at room temperature (RT) for 15 min using gentle rotation followed by bead separation on a magnetic rack (2 min). For the second and third round of depletion, the supernatant was added to a new batch of beads, incubated at RT for 15 min using gentle rotation followed by bead separation on a magnetic rack (2 min). The resulting supernatant, containing rRNA-depleted RNA, was purified using RNeasy MinElute CleanUp Kit . Depletion of rRNAs was evaluated on a 1.2% TBE-agarose gel and on an Agilent 2100 Bioanalyzer  using the RNA 6000 Nano Kit .The set-up for the hybridization reaction is based on a published protocol27. To generate strand-specific RNA-seq libraries, uracil excision and removing of the second strand was performed prior to conversion of Y-shaped adapters. Therefore, 3 μl of USER enzyme  were mixed with 16 μl of adapter-ligated DNA, 1 μl of TruSeq PCR primer cocktail (50 μM) and 20 μl of KAPA HiFi HotStart ReadyMix . USER digestion was performed at 37 °C for 15 min, followed by the published amplification protocol. Library concentrations were determined in duplicates using Qubit dsDNA HS Assay Kit  and a Qubit 2.0 Fluorometer  and quantified using the KAPA Library Quantification Kit  according to the manufacturer’s instruction. Strand-specific RNA-sequencing libraries were sequenced in paired-end mode on an Illumina NextSeq 500 sequencer (2 × 76 cycles).Synthesis of cDNA was performed using NEBNext Ultra Directional RNA Library Prep Kit for Illumina  according to the manufacturer’s instruction. The concentration of cDNA was measured using Qubit dsDNA HS Assay Kit  and a Qubit 2.0 Fluorometer . Sequencing libraries were prepared as described previously28 and the sequencing datasets were mapped to the T. brucei Lister 427 genome assembly  using BWA-mem30. The alignments were converted from SAM to BAM format, sorted and indexed using SAMtools version 1.831. Additionally, unmapped, PCR or optical duplicate, not primary aligned and supplementary aligned reads were filtered out from the alignment files (SAM flag: 3332).Adapter sequences were removed using Cutadaptet al.22. For on overview of the data analyses performed to generate the different figures see Supplementary Table The same procedure was applied for processing the poly(A) RNA-seq datasets from Hutchinson 32 in R33 and normalized to the total read counts. To determine the fraction of rRNAs in each RNA-seq experiment, rRNA read counts  were summed and their proportion of the total reads counts was calculated. Differential gene expression analyses were performed using the DESeq2 package34 from R/Bioconductor. For analyses of non-rRNA transcripts, rRNA counts were excluded and vice versa.Using BAM files, reads per gene were counted using the GenomicAlignments package13) and EBI ENA . For correlation analyses, transcripts per million were calculated for each dataset in the non-alignment-based mode with SALMON38 using the transcriptome of T. brucei Lister 427  as reference and normalized to the total number of transcripts excluding the number of rRNA transcripts.The ribo(−) kit and different poly(A) RNA-seq datasets derived from previous studies were downloaded from NCBI SRA , we extended each CDS with the median UTR length of 89 bp upstream and 400 bp downstream2. To calculate reads mapping outside of protein-coding genes, we counted all reads not mapping to CDS + UTRs or rRNA. The total number of reads mapping inside or outside of protein-coding genes was summed up and the percentages were calculated.To calculate the number of reads mapping inside of protein-coding genes, we counted the number of reads mapping to the CDS features of the official annotation using the GenomicAlignments packagemerge. The number of reads was normalized per billion mapped reads and coverage files were generated in the wiggle format using COVERnant version 0.3.0 with the subcommand ratio, as previously described39.To visualize read coverage, filtered SAM alignments from replicate sequence experiments were merged using samtools Supplementary InformationSupplementary Table 1Supplementary Table 2Supplementary Table 3Supplementary Table 4Supplementary Table 5Supplementary Table 6