Pleurotus tuoliensis is a precious edible fungus with extremely high nutritive and medicinal value. The cultivation period of P. tuoliensis is longer than those of other Pleurotus species, which is mainly due to a longer mycelium physiological maturation period (30–60 days). Currently, the molecular processes underlying physiological maturation of the mycelium remain unclear. We performed a comparative transcriptomic analysis of immature and mature mycelia using RNA-seq. De novo transcriptome assembly resulted in identification of 17,030 unigenes. 451 differentially expressed genes—including those encoding nucleoside diphosphate kinase (NDPK), glycoside hydrolase family proteins, exopolygalacturonase, and versatile peroxidases—were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that nucleotide synthesis and energy metabolism are highly active during the physiological maturation of mycelia, and genes related to these pathways were significantly upregulated in mature mycelia. NDPK is predicted to be essential for mycelia maturation. Our findings contribute to a comprehensive understanding of mycelia maturation in a commercially important fungal species. Future efforts will focus on the function of NDPK and the mechanism by which it regulates mycelia maturation.  Pleurotus tuoliensis, also known as Bailinggu, is one of the most commercially important species of edible mushrooms [P. tuoliensis was initially found in Xinjiang province [ushrooms . P. tuolprovince  and is nprovince . P. tuoliensis yield decreased year by year. In 2017, only 70,000 tons were produced, which represents a 77% decrease from 2012 (http://hz.cefa.org.cn/2019/03/18/10498.html). This decrease may be due to this fungus’ biological characteristics, such as long cultivation period, a high proportion of deformed fruiting bodies, poor uniformity of fruiting bodies, and strain degeneration [P. tuoliensis mycelia is essential for its fruiting. This maturation takes 30–60 days and is responsible for the above-mentioned long cultivation period. In this physiological maturation stage, mycelia accumulate and metabolize nutrients [P. tuoliensis cultivation more tractable and aids efforts to improve P. tuoliensis quality and yield. However, the molecular mechanisms underlying physiological maturation of P. tuoliensis mycelia remain undefined. In recent years, utrients . Cold stPleurotus eryngii [Cordyceps militaris [Ganoderma lucidum [P. tuoliensis mycelia [P. tuoliensis fruiting body formation [RNA-seq is a rapid and cost-effective technology for discovery of genes expressed in a given growth stage, especially in non-model species for which reference genome sequences are not available . Many tr eryngii , Cordyceilitaris , and Gan lucidum . This hi mycelia  as well ormation .P. tuoliensis mycelia. To identify genes and pathways that are differentially expressed during physiological mycelium maturation and explore molecular mechanisms underlying this maturation, a comparative transcriptome study on immature and mature P. tuoliensis mycelia was performed in this study. To our knowledge, no transcriptome analyses have been performed to investigate the transcriptional changes that occur during physiological maturation of P. tuoliensis (ACCC 50869) was obtained from the Agricultural Culture Collection of China. Mycelia were grown at 25 °C in plastic bottles containing 820 g of cultivation substrate  in the dark for 37 days, after which the substrate was fully covered by mycelia. We randomly selected three cultivation bottles and took the mycelia from cultivation substrate into three corresponding tubes and froze them at −80 °C until RNA extraction . The remaining plastic bottles were maintained at a temperature of 17 °C in the dark to induce physiological maturation of mycelia. After 20 days of induction, CA-asp content in mycelia were determined every two days. After CA-asp content in mycelia reached 0.9 g/L, mycelia reached physiological maturation [Mycelia total RNA was extracted using TRIzol reagent  according to the manufacturer’s protocol. The concentration, quality, and integrity of the extracted RNA samples were determined by agarose gel electrophoresis and a NanoDrop spectrophotometer . Six cDNA libraries were constructed using the Illumina TruSeq Stranded mRNA LT Library Preparation Kit  and then paired-end sequenced on an Illumina HiSeq 2000 platform by Shanghai Personal Biotechnology Co. Ltd. . https://www.bibsonomy.org/bibtex/f230a919c34360709aa298734d63dca3) and have been deposited in the National Center for Biotechnology Information (NCBI) database under the the BioProject accession PRJNA551095. Low-quality reads, duplicate sequences and adapter sequences were removed to obtain high-quality clean reads using cutadapt (https://cutadapt.readthedocs.io/en/stable/). Clean paired-end reads were assembled into contigs based on the similarity between overlapping regions using Trinity [Raw reads were assessed for quality using FastQC . The Blast2GO program [Based on sequence homology, all assembled unigenes were compared to the NCBI non-redundant protein (Nr) and Swiss-Prot databases using the BLASTX program  database at the NCBI archives (https://www.ncbi.nlm.nih.gov/geo) under accession GSE135839. To identify the differentially expressed genes, transcript abundance were first calculated by mapping clean reads to unigenes database using RSEM . DEGs wehttps://david.ncifcrf.gov/) were used to analysis DEGs for GO term and KEGG pathyway enrichment. The online analysis tool, the Database for Annotation, Visualization and Integrated Discovery  with SYBR green fluorescent dye . Amplification conditions were: 95 °C for 3 min, followed by 40 cycles of 94 °C for 3 s, 60 °C for 32 s, and 72 °C for 30 s. Each reaction was performed in triplicate using the glyceraldehyde-phosphate dehydrogenase gene (gapdh) as an internal reference. Relative gene expression levels were calculated using the 2−∆∆Ct method [We selected 12 DEGs identified by RNA-seq for validation by RT-qPCR. Total RNA from immature and mature mycelia was extracted using the same procedures as used for RNA-seq. RNA from each sample was reverse transcribed using TransScript One-Step gDNA Removal and cDNA Synthesis SuperMix . Primers for the 12 DEGs were designed in Primer 6.0 software  and are shown in t method .The cultivation substrate was fully covered by white fungal mycelia after incubation at 25 °C for 37 days in the dark. These cultivation bottles were then maintained at a temperature of 17 °C in the dark to induce mycelia maturation. The sawdust media surface was gradually covered with plump and elastic hyphae . At the We performed paired-end sequencing of six cDNA libraries . We obtained an average of 45,688,081 raw reads per library. After removing adapter sequences and low-quality reads, clean reads represented approximately 99.53% of the raw reads. Clean reads were combined into a single dataset for de novo assembly. A total of 60,330 transcripts, including sequence isoforms, were obtained. Transcripts displayed a mean length of 1897 bp. To reduce redundancy, only the longest sequence isoform within each subcomponent was selected. In total, we obtained 17,030 unigenes representing unique transcripts for further analysis . This unigene dataset displayed a total size of 21,120,061 bp, an average length of 1240 bp, and an N50 of 1891 and served as the mRNA transcriptome for mycelia . P. ostreatus, a species evolutionarily related to P. tuoliensis , which included 206 upregulated and 245 downregulated genes , we compared the normalized read counts  of the immature and mature mycelia samples. This comparative analysis revealed 451 significantly DEGs , oxalate decarboxylase OxdC (DN8634_c0_g1), pseudouridylate synthase Pus (DN2821_c0_g2), DNA repair and recombination protein RHM52 (DN3170_c0_g1), and nucleoside diphosphate kinase Ndpk (DN4800_c0_g2), demonstrating that this complex developmental program requires not only fast mycelial vegetative growth, but also more energy to accumulate nutrients and thus nurture developing fruit bodies during the reproductive stage. Versatile peroxidases (Vps) are key lignin-degrading enzymes, as they possess both manganese and lignin peroxidase activities. We observed upregulation of Vp-encoding genes  in mature mycelia, consistent with nutrient accumulation. Another important class of DEGs identified in our mature mycelia were those encoding post-modification enzymes, such as cytochrome P450 monooxygenase and methyltransferases, which are important for the synthesis of secondary metabolites. The expression of genes encoding cytochrome P450s monooxygenase Psih  and a methyltransferase (DN4644_c0_g2) were found to be significantly upregulated in mature mycelia. Finally, upregulated fruiting body protein SC3 (DN5369_c0_g1) was enriched in mature mycelia, probably indicating the initiation and formation of fruiting bodies . In this study, we also searched our DEGs for families related to carbohydrate-active enzymes (CAZymes) using the Carbohydrate Active Enzymes (CAZy) database . BLASTX Reverse transcription-quantitative PCR (RT-qPCR) was performed to verify the expression of 12 DEGs, including exopolygalacturonase ESP (DN2903_c0_g1), pseudouridine synthase PS (DN3768_c0_g2), nucleoside diphosphate kinase NDPK (DN4800_c0_g2), versatile peroxidase VP (DN8870_c0_g2), fruiting body protein SC3 (DN5369_c0_g1), cytochrome P450 monooxygenase (DN5495_c0_g1), cell cycle checkpoint control protein RAD9A (DN8865_c1_g1), α-galactosidase α-GAL (DN10455_c0_g1), carbonic anhydrase CA (DN556_c0_g1), NADPH dehydrogenase afvA (AFVA), dual specificity protein phosphatase (DUSP), and ATP-dependent DNA helicase Q4 (RECQL4). All of these DEGs showed similar expression patterns in RT-qPCR analysis as observed from RNA-seq data .P. tuoliensis fruiting body. Only mature mycelia are subjected to low temperature and light stimulation, primordia and fruiting body can be finely developed. Transcriptomic studies on mature mycelia to cold stimulation and fruiting body formation for P. tuoliensis have been performed by Fu et al.  to reveal physiological metabolic properties underlying primordia formation and fruiting body development [P. tuoliensis mycelia indicated that functional groups of differentially expressed unigenes associated with cell wall and membrane stabilization, soluble sugars, and protein biosynthesis and metabolism pathways, and calcium signaling and mitogen-activated protein kinases (MAPK) pathways play a vital role in Bailinggu’s response to cold stimulation. While transcriptomic analysis on fruiting body development identified the stage-specific and differentially expressed unigenes (DEGs) involved in morphogenesis, primary carbohydrate metabolism, cold stimulation, and blue-light response, predicting that these unigenes might help P. tuoliensis adapt to genetic and environmental factors that influence fructification. However, no transcriptome analyses have been performed to study the molecular mechanisms underlying physiological maturation of mycelia. In this study, we utilized a comparative transcriptomic approach to explore differential gene expression and molecular processes during the physiological maturation of mycelia. The physiological maturation stage of mycelia, which lasts approximately 30–60 days, is critical for the growth and development of the elopment . TranscrP. tuoliensis mycelia have undergone a physiological maturation process, their morphology does not display a huge change relative to the process of primordia formation or fruiting body development. As shown in GO and KEGG enrichment results of DEGs, DEGs were mainly enriched for nucleotide synthesis and energy metabolism functions. Which are consistent with the fast growth and nutrient accumulation that are characteristic of mycelium maturation [P. tuoliensis mycelia also revealed similar metabolism phenomenon. Metabolites enriched on pyrimidine synthesis were significantly abundant in mature P. tuoliensis mycelia, such as CMP and cytosine, which are indicative of the high demand for rapid nucleotide synthesis during physiological maturation [Our comparative transcriptome analysis identified 451 differentially expressed genes (DEGs) between immature and mature mycelia. Although the number of DEGs is small considering ~17000 unigenes, this result is reasonable. Even if turation . MetabolNeurospora crassa, Ndpk is associated with hyphal development and photomorphogenesis [Lentinus edodes mycelia, concluding that this enzyme may plays an important role in light-induced mycelial brown-film formation, an indicator of physiological mycelial maturation in L. edodes [P. tuoliensis mycelia is likely associated with physiological mycelial maturation. The specific function of Ndpk in this process is worthy of further study.Among our DEGs, the upregulation expression of NDPK is interesting. Many studies have demonstrated that NDPK regulates various biological processes and signal transduction pathways in addition to playing a fundamental role in maintaining the cellular balance of NDP and NTP ,23. In Nogenesis . Tang et. edodes . Thus, uP. tuoliensis relies on nutrients produced by decomposition of the cultivation substrate. CAZymes are involved in the hydrolysis of plant cell wall polysaccharides and play an important role in substrate degradation processes [Growth and development of rocesses . We idenrocesses . The GH rocesses . GH13 isrocesses . The funrocesses , versatirocesses , and lacrocesses . We idenFunctional enrichment analyses of our DEGs also demonstrated that oxidation-reduction activities and pathways are very active during the physiological maturation of mycelia. Cytochrome P450 monooxygenases psiH, which catalyze the biooxidation of various substrates through activation of molecular oxygen and play important roles in metabolic processes and stress responses , displayP. tuoliensis. The unigene encoding hydrophobin 2 was upregulated in primordia while downregulated in the fruiting bodies. However, they did not find unigenes that specifically expressed during the initiation of fruiting [We also observed upregulated fruiting body protein SC3 in mature mycelia, which was reported to be involved in fruiting body development of edible mushroom ,34. The fruiting .P. tuoliensis mycelia. GO and KEGG enrichment analysis demonstrated that metabolic pathways related to genetic information and energy metabolism are extremely active during the physiological maturation of mycelia. Genes related to critical oxidation-reduction processes are upregulated in mature mycelia. CAZymes involved in the hydrolysis of plant cell wall polysaccharides were differentially expressed in mature mycelia compared with immature mycelia and the differential expression of these genes may relate with substrate degradation utilization. In addition, we predict that NDPK may be an important enzyme for participating in mycelia physiological maturation. Our data enables an improved understanding of physiological maturation in P. tuoliensis mycelia, which lay an important foundation for revealing mycelia physiological maturation properties in edible mushrooms.In summary, our comparative transcriptomic analysis of immature and mature mycelia revealed gene expression differences indicative of changing metabolism during physiological mycelium maturation and identified a potential functional group of genes responsible for regulating the physiological maturation in


A novel integration of three-dimensional (3D) architectures of near-field electrospun polyvinylidene fluoride (PVDF) nano-micro fibers (NMFs) is applied to an intelligent self-powered sound-sensing element (ISSE). Using 3D architecture with greatly enhanced piezoelectric output, the sound wave energy can be harvested under a sound pressure of 120+ dB SPL of electrical signal about 0.25 V. Furthermore, the simple throat vibrations such as hum, cough and swallow with different intensity or frequency can be distinguishably detected. Finally, the developed ultrathin ISSE of near-field electrospun piezoelectric fibers has the advantage of direct—write fabrication on highly flexible substrates and low cost. The proposed technique demonstrates the advancement of existing electrospinning technologies in new practical applications of sensing purposes such as voice control, wearable electronics, implantable human wireless technology. The direct-write technique by means of NFES to produce and place piezoelectric PVDF nanofibers on working substrates is shown in As the increasing needs for the extreme integration of micro/nanodevices with versatile functionalities, the multifunctional micro/nanosystems are highly pursuit for transduction of energy in the fields of environmental, biomechanical and human–machine interfacing ,2,3,4,5.3, 2.5 mm in width). As illustrated in The NFES manufacturing process and the structure of the intelligent and self-powered sound-sensing elements (ISSE) is schematically illustrated in The optical photo of ISSE is shown in Electricity-generating performance of proposed ISSE at various sound loudness and NFES processing conditions under biomechanical human voice of hum was initially recorded and broadcasted by loudspeaker  in Furthermore, the forward and reverse connections measurements of the NFES electrospun NMFs have been validated and presented in After identifying the potential for harvesting the acoustic energy, ISSE is used to detect the vibration of throat cords. As shown in ISSE can be functionally working as a sound detector in the self-powered fashion, schematically presented in In summary, a direct-write, self-aligned and one-step fabricated sound sensing element based on PVDF fibers has been developed and functions in the self-powered manner. The ISSE realizes the functional integration of piezoelectric materials as sound detectors to capture the bio-mechanical vibration of human motion such as throat cords. This developed process enables orderly fiber-by-fiber stacking to construct 3D structures in a controllable and prescribed pattern. The distinctive in situ electrical poling and mechanical stretching in NFES process to deposit one row of 200 PVDF NMFs can create a peak output voltage of ~132 mV and a current reaching 8 nA at the optimized resistor matching of 10 MΩ. It can be demonstrated that distinguishable characteristics of nod, head shaking, cough, hum and swallow can be clearly differentiated. In addition, the musical scores of unique waveforms as played in Cannon in D are also vividly captured by the ISSE with different tones and volumes such that the voice recognition capability is demonstrated. Therefore, this 3D electrospinning nanofabrication technique has the potential in constructing 3D structures for wearable electronics as the voice control and recognition devices.


H-1,2,3-triazole derivatives PILAB 1–12 were synthesized and a pharmacological screening of these derivatives was performed to identify a possible effect on the Central Nervous System (CNS) and to explore the associated mechanisms of action. The mice received a peritoneal injection (100 µmol/kg) of each of the 12 PILAB derivatives 10 min prior to the injection of pentobarbital and the mean hypnosis times were recorded. The mean hypnosis time increased for the mice treated with PILAB 8, which was prevented when mice were administered CTOP, a µ-opioid antagonist. Locomotor and motor activities were not affected by PILAB 8. The anxiolytic effect of PILAB 8 was evaluated next in an elevated-plus maze apparatus. PILAB 8 and midazolam increased a percentage of entries and spent time in the open arms of the apparatus compared with the control group. Conversely, a decrease in the percentages of entries and time spent in the closed arms were observed. Pretreatment with naloxone, a non-specific opioid antagonist, prior to administration of PILAB 8 exhibited a reverted anxiolytic effect. PILAB 8 exhibited antinociceptive activity in the hot plate test, and reduced reactivity to formalin in the neurogenic and the inflammatory phases. These data suggest that PILAB 8 can activate µ-opioid receptors to provoke antinociceptive and anti-inflammatory effects in mice.5′-4-Alkyl/aryl-1 H-indole-2,3-dione, 1, 2 . Meanwhile, molecular modeling studies have shown the existence of π-π interactions between the triazole ring and Tyr334 in the anionic binding site of the enzyme -2′(1′H)-one with various alkynes under acidic conditions followed by the application of ultrasound irradiation as described by Silva et al. -2′(1′H)-one (1), were evaluated for hypnotic-sedative activity  was used as the mobile phase with a 150  ×  4.6-mm Eclipse Plus C18 column. The flow rate was 1 mL/min and the injection volume was 1 μL. The wavelength of detection used was 280 nm. The purities of the compounds are shown in The HPLC analysis was conducted on a Shimadzu LC20AT system . The Shimadzu Lab solutions software was used for data acquisition. Acetonitrile/methanol .The experimental protocols used in the present study were approved by the Animal Care and Use Committee of the Universidade Federal do Rio de Janeiro, Brazil (CEUA/UFRJ DFBCICB068). Briefly, male Swiss mice (25–35 g) were kept in polypropylene boxes containing sawdust and were maintained under controlled temperature (21 ± 1 °C) and humidity (60%) with a 12-h light/dark cycle (lights on at 6 a.m.). Food and water were provided PILAB compounds, azide, and triazoles were kindly donated by the Laboratório de Produtos Naturais e Transformações Químicas . Acetylsalicylic acid , morphine, flumazenil, midazolam, and diazepam  were freshly prepared in dimethyl sulfoxide  minutes prior to the experiments. Naloxone (Cristália), formaldehyde , nor-binalthophimine, naltrindole, and CTOP and pentobarbital sodium salt  were dissolved in distilled water.The The hypnotic effect of the compounds investigated was examined in a pentobarbital-induced sleep test as previously described . BrieflyPILAB 4, 6, 7, 8, 9, 11 and 12 (100 µmol/kg i.v.) into tail of the animal. PILAB 8 was also administered at increasing doses to evaluate response dose in relation to hypnosis time. To investigate the mechanisms mediating the induction of hypnosis, mice were pre-treated with an i.p. injection of: flumazenil (33 µmol/kg), a benzodiazepine antagonist [PILAB 8 (i.v.), except for CTOP (0.94 µmol/kg), a selective mu opioid receptor antagonist, which was administered 15 min prior to PILAB 8 [The time of hypnosis was further examined with the administration of vehicle and tagonist ; naloxontagonist ; nor-bintagonist . All of  PILAB 8 .PILAB 8 or morphine (25 µmol/kg).Dunham and Miya described a method for detecting motor harm in response to substances such as skeletal muscle relaxants or CNS depressants ,52. A roPILAB 8 (25 µmol/kg), or midazolam (6.14 μmol/kg) 10 min before being placed on the central platform of the maze facing an open arm. The percentage of entries into the open and closed arms, as well as the time spent in each set of arms, were counted during a 5-min test period. An LE 846 apparatus  was used which contains two open arms and two closed arms connected by a central platform. Both arms are elevated to a height of 50 cm from the floor. An animal’s position is registered by eight photoelectric cells that are arranged in each arm so that nine sectors are defined. Data were recorded with the Mazesoft-4 Software. Male Swiss mice were treated with an i.p. injection of vehicle, PILAB 8 (25 µmol/kg). The total time spent by each animal licking in the injected paw was then observed for 30 min.A formalin test was performed based on a protocol previously described for the quantitative study of antinociceptive effects . BrieflyPILAB 8 (25 µmol/kg), or morphine (25 µmol/kg). Involvement of the opioid pathway was investigated by administering naloxone (3.1 µmol/kg i.p.) 15 min prior to the administration of PILAB 8. Antinociceptive activity (AA%) was calculated using Equation (1):Central analgesic activity was evaluated in a hot plate test. Briefly, mice were placed onto a hot plate maintained at 52 ± 1 °C . The latency of their nociceptive threshold was recorded according to the time until licking or shaking of one of their paws or jumping was observed. Maximal permanence of the animals on the hot plate was 35 s to avoid damage to the paws. Animals received an i.p. injection of vehicle, p > 0.05 were considered significant.Data are expressed as the mean ± standard error of the mean (SEM) and were analyzed using one-way analysis of variance (ANOVA) followed by Dunnett’s multiple comparison test. GraphPad Prism, version 6.0 , was used to perform the statistical analyses and differences with a PILAB 8, bearing the longest alkyl chain among the tested compounds, showed the best hypnotic profile. This compound was selected for subsequent experiments, indicating that can activate µ-opioid receptors to provoke antinociceptive effect without morphine-like side effects. In addition, PILAB 8 was found to effectively reverse anxiety independent of a pain response.In conclusion, the results of the present study provide evidence that the triazole scaffold potentiates the activity of isatin ketals and an apolar substituent attached to this ring increases the effects on the CNS.


RNA sequencing has become one of the most common technology to study transcriptomes in cancer, whereas its length limits its application on alternative splicing (AS) events and novel isoforms. Firstly, we applied single molecule long-read RNA sequencing (Iso-seq) and de novo assembly with short-read RNA sequencing (RNA-seq) in both wild type (231-WT) and paclitaxel resistant type (231-PTX) of human breast cancer cell MDA-MBA-231. The two sequencing technology provide both the accurate transcript sequences and the deep transcript coverage. Then we combined shor-read and long-read RNA-seq to analyze alternative events and novel isoforms. Last but not the least, we selected BAK1 as our candidate target to verify our analysis. Our results implied that improved characterization of cancer genomic function may require the application of the single molecule long-read RNA sequencing to get the deeper and more precise view to transcriptional level. Our results imply that improved characterization of cancer genomic function may require the application of the single molecule long-read RNA sequencing to get the deeper and more precise view to transcriptional level. The complexity of transcriptions and proteins are mainly due to the numerous alternative splicing (AS) events, which is a common phenomenon in eukaryotic species3. In human, 95% genes are multi-alternatively spliced, whereas the function of every event is yet to be studied4. In terms of cancer research, previous reviews have shown that about 15,000 AS events are detected in 27 cancer types and the cancer specific AS events are correlated to differentiated cancer survival5. However, with the development of cancer processing, various number of unannotated AS events happened and formed novel transcription, which may play a critical role in cancer metastasis and drug resistance6.With the advancing technology of RNA sequencing (RNA-seq)7. Therefore, Iso-seq is widely used in constructing genome reference of different species, which further more expending its application into high-throughput sequencing with de novo genome reference when combining with RNA-seq.8.Other than short-read RNA sequencing which assembles short fragments (36–125 bp) and aligns to the reference such as GRCh38, the single molecule long-read RNA sequencing, which also called Pacbio sequencing (Iso-seq) can detect as long as thousands of base pairs (1–10 kb) and assemble as de novo transcriptome reference11. In spite of the emerging therapeutic such as immunotherapy, the chemotherapy is still the only recognized standard therapy for TNBC patients13. Thus, the potential drivers and mechanism for drug resistance is necessary to be clarified. Recently, increasing researches have remarkable founding on the function of some alternative splicing event and transcripts played a pivotal role the tumorigenesis, progression, and metastasis of cancer, as well as inducing drug resistance16.The chemotherapy resistance has been a challenging project in breast cancer, especially in triple negative breast cancer (TNBC)Here we treated one of the TNBC cell lines, MDA-MB-231 with paclitaxel to generate paclitaxel-resistant cells. Then we used both RNA sequencing and Pacbio sequencing technology to perform paclitaxel resistant cells and wide type cells. We combined two kinds of data to build a paclitaxel-resistant genomic profiling of TNBC. Next, we analyzed the AS events using Iso-seq data and verified with RNA-seq splicing junction. Moreover, we defined 390 differentiated isoforms combing both the RNA sequencing and Pacbio sequencing results and highlighted 11 novel differentiated isoforms with the common character that they can only be detected on isoforms level. At last, we verified a novel isoform of BAK1 genes.The MDA-MB-23 human triple negative breast cancer cell line from the Shanghai Cell Bank Type Culture Collection Committee  and cultured in complete growth medium as recommended by the distributor. The MDA-MB-231 paclitaxel-resistant subline 231-PTX was established by concentrations of paclitaxel (MCE) 1 mM with 12 cycles in culture medium. Each cycle lasts for 24 hours and change for normal culture medium to culture for 2 weeks.The Cell Counting Kit-8 (CCK-8) assay  was used to construct a dose-response curve to obtain half the maximal inhibitory concentration (IC50) of each compound. The IC50 was calculated using the XLFit curve fitting software . All experiments were performed three times in triplicate.Total RNA was extracted using TRIzol reagent (Invitrogen) and extracted following the manufacturer’s protocol. For RNA sequencing, the libraries were constructed using TruSeq Stranded mRNA LTSample Prep Kit . And were sequenced on the Illumina sequencing platform (HiSeqTM 2500). For Pacbio sequencing, cDNA was synthesized using a SMARTer PCR cDNA Synthesis Kit (Clontech) and SMRT bell libraries were generated using a SMRTbell Template prep kit 1.0 (Pacific).17 was used to correct the low quality data using RNA sequencing reads of the same experiment18. The corrected sequences were mapped to the NCBI Refseq genome by software GMAP19. Moreover, the corrected isoforms were collapsed by the ToFU package (http://github.com/PacificBiosciences/cDNA_primer/) with the index of identity = 85% to detruncate the redundant isoforms. Isoforms differing only at the 50 bp of the starting site were defined as redundant isoforms and only the longest version was retained.The IsoSeq software ver2.3.0 (PacBio) was applied to get the reads of interest (ROI) fragmets and Quiver software was applied for Error Correction (ICE) to generate the cluster consensus sequences. Next, the package Long-Read De Bruijn Graph Error Correction (LoRDEC)20. Then the clean reads were mapped to reference genome using hisat221. FPKM22 fragments Per kb per Million reads) value of each gene was calculated using cufflinks23, and the read counts of each gene were obtained by HTseq-count24. DEGs were identified using the DESeq package (https://github.com/olgabot/rna-seq-diff-exprn) functions estimate size factors and negative binomial distribution test. P value < 0.05 and fold change >2 or fold change <0.5 was set as the threshold for differential genes. For short-read assembly, short contigs were reassembled by Cufflinks to get the de novo assembly.Raw data (raw reads) were processed using NGS QC Toolkit25 to detect 5 types of AS events including A3SS, A5SS, ES, IR and MXE. The novel AS event was defined by MatchAnnot package (https://github.com/TomSkelly/MatchAnnot). For RNA sequencing splicing junction investigation, short reads were aligned to the Pacbio sequencing isoforms by STAR26 to detect four splice motifs including CT/AC, CT/GC, GT/AT and other non-canonical sites.After data processing, PacBio sequencing isoforms were analyzed by the software AStalavistahttp://blast.ncbi.nlm.nih.gov) with the index of coverage > = 0.85, identity > = 90 and e value < = 1e-20 to obtain the intersection of the two datasets. To create Unigene, a new genome reference, the novel isoforms to were compared to the NCBI Refseq by bowtie2  and eXpress (http://www.rna-seqblog.com/express-a-tool-for-quantification-of-rna-seq-data/) to acquire abundance of Unigene transcripts of the two samples. Then FPKM was applied for quantifying the Unigene expression. The fold change values and p value were calculated by DESeq, with threshold pf fold change >2 or <0.5 and p value < 0.05. We applied the Integrated Genomics Viewer v2.3.55 to visualize the region of BAK127.The PacBio isoforms were mapped to reference genome using MatchAnnot. The novel transcripts were defined as the coverage <50% of the annotated isoforms. The novel transcripts identification in RNA sequencing were the result of comparing de novo assembly to the reference genome using cuff compare software. Iso-seq novel isoforms were aligned with RNA-seq novel isoforms by BLAST+ package . PCR was performed to validate the novel isoforms by Q5 High-Fidelity DNA Polymerase (NEB). Primers are listed in the Supplementary Table.In order to construct a paclitaxel-resistant cell subline of MDA-MB-231 (231-PTX), we treated cells as described in Materials and Methods Fig. . The pacTo avoid the bias of preferentially detecting shorter length of isoforms, three SMRT Cells with the read length of <2 kb, 2–3 kb and >3 kb were sequenced and produced about 5000 million bases data for each cDNA sample. The base pair quality, read length and coverage of Reads-Of-Insert (ROI) of the two samples indicated that the Iso-seq data was in high quality, wide range length and adequate ROI coverage  of the RNA-seq contigs mapped to 94%  of the PacBio transcript isoforms. There were 23%  of RNA-seq contigs and 6%  of Iso-seq isoforms unique to each of the datasets due to the fake assembly of RNA-seq short reads and the failed coverage of Iso-seq isoforms to all the human genome sequences Fig. . ConsequBased on Iso-seq, we identified the number of each AS event type in 231-WT and 231-PTX . In total, we detected 48,646 AS events in Iso-seq isoforms of both 231-WT and 231-PTX samples. Among these, SE event was the most prevalent mode, which was consistent with previous research. Compared to annotated AS events in Refseq, only 11.11% of all the AS events were mapped, which illustrated that a vast viability of AS events during paclitaxel resistance process in TNBC Fig. . The conSince the RNA-seq defining AS events at a local view, we used it to evaluate the accuracy of Iso-seq results. An average of more than 90% of the Iso-seq junction positions were supported by RNA-seq short reads, which indicating high accuracy of the Iso-seq in analyzing the alternative splicing events Fig. . AnotherSince the majority of the alternative splicing events happened during the process of drug resistance were novel, there should be numerous novel isoforms emerged, whose significance are unexplored. We mapped 79,181 Iso-seq isoforms to NCBI RefSeq database, it turned out 72,602 (91.69%) isoforms in Iso-seq could be annotated and number of novel isoform was 6130 (15.07%). Next we aligned the 6,130 Iso-seq, 4,948 RNA-seq novel contigs, which was displayed in the pie chart that 2,509 Iso-seq isoforms, and 2,474 RNA-seq contigs were matched Fig. . TherefoAs the isoforms detected in Iso-seq were not fully covered the Refseq, we combined the Iso-seq isoforms and NCBI Refseq database to create a database called Unigene. The RNA short reads were mapped to Unigene for quantitative-differentiated analysis. The violin plot exhibited that the average value of log2 fold change was higher in novel isoforms than in annotated isoforms Fig. . In addiFrom the 11genes listed in Fig. et al. applied microarray technology to find the significance of AS events of TRA2A in paclitaxel resistant TNBC cells28. Johnson et al. induced high lung-metastatic TNBC cell lines and performed RNA sequencing to identify a common dysregulated splicing event in CPEB229. However, a comprehensive analysis of AS event and novel isoforms in TNBC drug resistance has not been reported yet. In this research, we applied the MDA-MB-231 paclitaxel resistant cell line to analyze their AS event character and discovered novel isoforms that were differentiated expressed in 231-PTX compared to 231-WT, which established the basis of the whole-transcriptional expression profile and shed light on the drug resistant research work to a deeper level.Numerous researches have performed sequencing on genetic level to analyze genome profile of drug resistance. Some contribution has been achieved on alternative splicing events of some gene and drug resistance in TNBC. Liu 30. Yet PacBio sequencing provided a direct and convincing approach to identify alternative RNA processing events, as its long length of reads can be clearly distinguished each AS event even the long intron retention event31. Therefore, we applied the Iso-seq technology and substantially expanded the repertoire of AS events in TNBC, which had much more number than known events, especially the IR event, with 40 times more novel event detected than the known ones.Although the major analyzing strategy of alternative splicing events is to use the short reads from next generation sequencing, it cannot be denied that it is limited to accurately define these events by short RNA-seq reads alone, especially for the IR eventset al. applied SMRT PacBio sequencing on Chinese individual HX1 to explore the Chinese genome profile specifically32. Targeted TP53 sequencing PacBio dataset and FLT3 PacBio sequencing dataset were established by Olivier et al. and Gilliland et al. for clinical use34. Our research is the first to use the PacBio sequencing on studying drug resistance in breast cancer. We focused on the novel isoforms that were not only significantly expressed but also would be missed if only performing RNA sequencing. The genes listed are worth studying their different functions between isoforms and may be the potential biomarker on drug resistance.Other than species that need Iso-seq to identify their genome, the human genome has established several comprehensive genome database, among which the most widely used is GENCODE. However, the diversity of novel isoforms in human genome in different situations makes it necessary to use Iso-seq technology to precisely discovered dramatic alterations on isoform level. Shi 35. Therefore, we adopted the common novel isoforms of the two sequencing technology to establish a new genome reference called Unigene, which was mapped by RNA-seq short reads to calculate expression and compare the expression of the two samples. We focused on the novel isoforms that were not only significantly expressed but also probably be missed if only performing RNA sequencing. The genes listed are worth studying their different functions between isoforms and may be the potential biomarker on drug resistance.Despite its long length reads, PacBio Iso-seq is currently not good enough in comparative analyses due to its low throughout. While RNA-seq has the high throughout but short length reads35. Previous studied have depicted that BAK1 played a role in tumor growth and drug sensitivity. Aarnink et al. discovered that in 69 gastric cancer patients after chemotherapy whose specimens showed good chemotherapeutic histopathological responses had higher BAK expression than those with poor responses36. However, there is few evidence about BAK1 in breast cancer. Our definition of the novel isoform, PB.4024.2 is the potential biomarker of drug resistance in TNBC.BAK1 is one of the BCL family members and functioned as a apoptosis inducing geneIn conclusion, we detected a new strategy to analyze AS events and novel isoforms and pave a new path to drug resistance research in cancer Fig. . LimitedSupplementary information


Our understanding of the expanded genetic alphabet has been growing rapidly over the last two decades, and many of these developments came more than 80 years after the original discovery of a modified guanine in tuberculosis DNA. These new understandings, leading to the field of epigenetics, have led to exciting new fundamental and applied knowledge and to the development of novel classes of drugs exploiting this new biology. The number of methyl modifications to RNA is about seven times greater than those found on DNA, and our ability to interrogate these enigmatic nucleobases has lagged significantly until recent years as an explosion in technologies and understanding has revealed the roles and regulation of RNA methylation in several fundamental and disease-associated biological processes. Here, we outline how the technology has evolved and which strategies are commonly used in the modern epitranscriptomics revolution and give a foundation in the understanding and application of the rich variety of these methods to novel biological questions. In DNA, the intensive study of modified nucleotides during the last 20 years of the epigenetics revolution has led to the understanding of the role of DNA modifications in swathes of developmental decisions and disease. The epigenetics revolution has resulted in novel drugs, including DNA methylation inhibitors, bromodomain inhibitors, and histone acetyl transferase inhibitors5.Beyond the basic genetic letters of A, G, C, and U, chemically modified nucleotides can be found in the RNA of all eukaryotes. Though originally characterised in the 1970s6. Most of these modifications  tail is centred on the metabolism of the mRNA molecule rather than the encoded information. These structures are not coded for in the DNA but are found on the vast majority of mRNA molecules and have well-established roles in message stabilisation, nuclear export, and translation initiationcations  and lack10, but in 2011, evidence that the fat mass and obesity-associated protein, FTO, was able to remove the N6 methylation from mRNA was published, linking the modification to those diseases associated with FTO14 and reigniting the interest in mRNA methylation, its detection, and its biological impacts. More recent works have linked the modification to various processes, from the fundamental such as alternative splicing16 to diseases, including cancer17.Previous works had linked internal N6-methylation of adenosine to fundamental biological processes and developmental decisions18 and pseudouridylation19. These modifications do not involve methylation but can affect the metabolism of the RNA without modifying the coding sequence.Other common epitranscriptomic marks not covered here include the editing of adenosine-to-inosine20.These developments led to the field of the “epitranscriptome”, a field of molecular biology that attempts to characterise the causes and effects of modifications to the nucleotides of mRNA that affect not the coding sequence but rather the expression characteristics of the transcript. Understanding these modifications will allow a new level of fine tuning of gene expression and has great potential in fundamental biology, medicine, biotechnology, and crop production21. Similarly, methylations or modifications to the base-pairing “Watson–Crick edge”  tails using oligoDT or by depleting ribosomal RNA through a number of available strategies25. Since mRNA constitutes only 1 to 5% of the total RNA and the other RNA species can be heavily methylated, several rounds of purification are often required for reliable, consistent data from mRNA.Detection of the type of methylation found in RNA is preceded by a number of well-established methods for the purification of RNADepending on the downstream protocol, as little as 50 ng of mRNA, as measured by spectrophotometry, may be required. The quality of the RNA is paramount to generating high-quality data and typically is measured by using agarose gel electrophoresis or microfluidic analysis such as the Agilent bioanalyzer . The subsequent characterisation and analysis of the RNA depend on the type of modification , the abu26 as the radioactive methyl group is added onto the nucleoside. Combining this simple assay with various biochemical tools enabled early identification of methyltransferase activity, the initial identification of the m6A writer complex27, and the characterisation of the properties of various enzymes. However, the use of the method is limited where sequence context is desired or in the assaying ofex vivo RNA.The earliest works on RNA methylation were carried out by incorporating radioactive isotopes into the RNA. Labelling the methyl donor, s-adenosyl-methionine, with tritium (3H) enables the measurement of methyltransferase activity by scintillation28 published their paper chromatography analysis of previously discarded RNA preparation fractions. These paper chromatography assays evolved over time into two-dimensional thin-layer chromatography (2D-TLC) capable of identifying most of the modified nucleotides present in RNA29. By separating RNA in two dimensions, the nucleotides disperse across the typically cellulose substrate according to their charge and hydrophobicity, two attributes affected by methylation. The pattern then can be imaged with ultraviolet light or by pre-labelling the RNA with radioisotopes. The numerous advances in isolation of RNA, mRNA, and individual mRNA have enabled the adaptation of this method to assay for both internal m6A10 and cap-adjacent modifications Nm and m6Am30, resulting in a sensitive, quantitative and reproducible strategy.A “fifth ribonucleotide” in yeast RNA was first reported in 1957 when Davis and Allen30.The modern methods require that the RNA be prepared in such a way that the nucleotide of interest is exposed at the 5′ end of the transcript. For example, digesting mRNA with RNAse T1 which, cutting after every guanine, exposes any nucleotide following a guanine, thereby exposing adenosines found within the canonical m6A motif to 5’ end labelling. The 5′-most nucleotide then can be labelled with a radioactive phosphate group from γ-32P-ATP. These then can be separated on 2D-TLC and the resultant spots can be imaged and quantified with autoradiography. Enzymatic decapping and dephosphorylating of the 5′ end of intact mRNA reveal the nucleotide immediately adjacent to the 5′ cap, enabling the assaying of the cap1 structure31 can be used to assay the stoichiometry (ratio of modified to unmodified nucleotide) of the methylation at a known site. Here, a 2’-ribose methylated single-stranded DNA (ssDNA) probe complementary to the target site is used to direct RNAse-H–mediated cleavage, exposing the nucleotide for subsequent 2D-TLC analysis.Where sequence information is already known, site-specific cleavage and radioactive labelling followed by ligation-assisted extraction and thin-layer chromatography (SCARLET)32. These works localised the m6A modification to the 3′ end of eukaryotic mRNA33, reported on the phenotypic abnormalities resulting from knockouts in a reverse genetics approach33, as well as pointing towards their roles in developmental decisions35.2D-TLC has been used to identify and characterise the location of various methylated nucleotides and was used in the first mapping of the locations of m6A in bovine prolactin mRNAOwing to the modest quantities of mRNA required and the preservation of stoichiometry information, recent studies continue to use 2D-TLC in combination with other methods to allow a detailed analysis of the methylation states of internal and cap-adjacent nucleotides. However, 2D-TLC–based methods are often avoided because of their use of radioisotope and sensitivity to degradation, they also require a method of revealing the modified nucleotide and thus will miss modifications outside of a known context or sequence, or where it is not possible to reliably expose only the nucleotide of interest, such as the cap2 nucleotide. 2D-TLC provides excellent stoichiometric information but provides only a general transcriptome-wide view of the methylation status and yields little insight into the sequence specificity.36.In combination with separation based on biophysical properties, mass spectrometry (MS) can identify nucleotides by the mass-to-charge ratio in comparison with known standards. In many ways, MS identification is similar in principle to the chromatography-based methods but without the need for radioisotope or specific exposure of the nucleotide of interest for labelling. The method can detect methylation on the sugar and Watson–Crick edges of the nucleotide. MS also enables the profiling of methylations found on a variety of RNA fragments, including the cap2 structures that are typically inaccessible in 2D-TLC. Enhanced by the available sequencing information, MS has been used to map the modifications to transfer RNA (tRNA)Using MS in the analysis of mRNA has been performed to aid in the measurement of Cap1 and Cap2 structures. However, a major drawback of MS-based methods is the extremely large quantities of RNA required and the need for pre-existing sequencing information for the most informative results to be generated.37.Sodium bisulphite treatment deaminate cytosine to uracil, resulting in a mutation to thymine during reverse transcription, which then is revealed in the final sequencing dataset. Methylation of the cytosine at the fifth carbon position protects cytosine from this deamination. This strategy has been widely used in the study of DNA methylation to single base-pair resolutions38. For these, a large quantity of RNA is required to be incubated at high temperatures in a buffer containing sodium bisulphite. RNA libraries then can be prepared by using a standard library preparation protocol for fragmented RNA. The identification of m5C sites then can be carried out by identifying events of cytosine conversion to thymidines in the treated sample against an untreated control or by comparison with a reference genomic dataset. Those sites that remain cytosines in the final data were protected by the methylation.Given the harsh reaction conditions, sequencing bisulphite-treated RNA was largely considered futile; however, adaptations to the protocol have enabled the use of bisulphite sequencing in a whole-transcriptome mannerThe limiting factor in bisulphite-RNA-sequencing is the initial large quantity of RNA required to compensate for the high losses caused by the bisulphite treatment; at the same time, neighbouring modifications or double-stranded regions may be resistant to bisulphite treatment, especially under the gentler treatment required to maintain the RNA integrity. At the same time, the most common modification to eukaryotic mRNA is m6A rather than m5C.40. Although these methods have been enhanced over the last 7 years, the principles have largely remained unchanged. Antibodies are available for most of the base modifications, and strategies to sequence them mostly follow the established “methylated RNA immunoprecipitation sequencing” (or “MeRIP-seq”)40.The first whole-transcriptome maps of the internal m6A methylated nucleotide were published in 201239 and MeRIP-seq40—were designed to detect N6-adenosine methylation in mRNA and long non-coding RNA but can be applied to any modification with available antibodies; following isolation of poly(A) RNA, the RNA is fragmented to 100 base-pair lengths before being immunoprecipitated with an antibody to N6-methyl adenosine (m6A). The precipitated fractions then can be sequenced with a standard RNA-sequencing approach. During the downstream bioinformatics, the fragments are aligned to the transcriptome. Regions that are enriched after immunoprecipitation are assumed to contain a methylated nucleotide.The first two methods—named m6A-seq41) or any nearby nucleotide (miCLIP42)—in order to induce detectible mutations or truncations during the downstream library preparation.Although these early methods enabled the transcript-specific identification of methylated mRNAs, they suffer from low resolution of about 100 to 200 nucleotides and require significant quantities of input RNA. Furthermore, if the antibody exhibits non-specific binding  stretch rather than a modified m6A site), false positives can be generated. To tackle some of these issues, recent methods have included ultraviolet crosslinking—with either an incorporated neighbouring photoactivatable ribonucleotide , troughs (reverse transcriptase stops), or mutations  in the sequencing data.50 or STAR51) that is able to span exon–exon reads (or using a transcriptome index) is used to align the sequencing data to a known genome.A typical bioinformatics workflow for mRNA methylation analysis begins with initial basecalling, adaptor trimming, and demultiplexing of both an untreated and an immunoprecipitated sample for each replicate. Depending on the type of library preparation strategy used, collapsing polymerase chain reaction duplicates by identifying unique molecular barcodes included on the reverse transcription primer in order to increase the accuracy of the methylation quantification may be possible. Next, an alignment tool  CIMS algorithm can be used to call these sites, whilst a truncation site can be called with the CITS algorithm. A number of software packages exist for analysis of CLIP data, such as MACS253, and these will work for RNA immunoprecipitated with antibodies to methylated nucleotides. The “peaks” generated in this way are areas of the genome that are enriched in the immunoprecipitated samples and so must contain the methylated nucleotide. If enough fragments are sequenced, locating the precise modified base is possible although this is dependent on the fragment size and sequencing depth of the employed sequencing technology.If a mutation is expected where methylation is deposited, the CLIP Tool Kit54 for the identification of sequence contexts of the methylation and functional annotation such as Gene Ontology (GO) enrichment55 in order to identify the enriched biological characteristics of genes. Other bioinformatics and experiments are likely to follow in order to understand the biological consequences of the methylation; these are beyond the scope of the present work but consist largely of methods to assay the metabolism of the RNA56.Following the association of methylation with a gene’s transcript, further bioinformatics is likely to include motif analysisWhere the methyl group is found at a location normally involved in base pairing , reverse transcriptases are unable to pair the nucleotide with its complement, resulting in a consistent “stop” or mutation during reverse transcription. These artefacts in the sequencing data may present an opportunity to detect possible methylations in publicly available datasets.57, which was able to discern tRNA modification sites from such public datasets. However, relying on reverse transcriptase dynamics can result in the loss of information about rare methylation events, methylation on rare transcripts, and stoichiometric information and thus is not so readily applicable to the analysis of mRNA.The increase in publicly available sequencing data has enabled the development of software such as HAMR58. Whilst this technology is rapidly advancing, the current lack of read depth and requirement for high computing power appear to be the major limiting factors in the more widespread adoption of this technique for analysis of the diverse mammalian transcriptomes.Given the variety of methylated nucleotides found in RNA, it is likely to be some time before a single gold standard strategy exists which allows the preservation of all of the desired characterisations, sequence, and stoichiometry information of a given modification. The most likely candidate appears to be nanopore sequencing technology, which uses changes in electrical charge to discern the nucleotides passing through a protein or graphene nanopore in substrate. Since these methods require no conversion to DNA and analyse the nucleotide by how they affect the charge passing through the substrate, nanopore sequencing is also able to distinguish modified bases from their unmodified counterparts59, understanding their clinical roles is likely to be a major feature of future research. Therefore, the development of new technologies that can quickly identify the types of modifications found in disease is likely to be paramount to the application of epitranscriptomics both to medicine and in industry.Given that methylated nucleotides can be used as biomarkers from a number of non-invasive tissuesMethylation of nucleotides confers several unique properties to RNA during the life cycle of the molecule but also to their fundamental chemistry, which in recent years has been exploited in order to detect them. Owing to the huge variety of methylated nucleotides found in RNA, the epitranscriptomics revolution has lagged behind the epigenetics revolution by some 20 years. However, study of these modifications has been rapidly evolving over the last decade because of the availability of new technology, and curiosity has been ignited by their newfound associations with economically and medically important arenas of biochemistry.In many ways, the technology remains the limiting factor. Currently, there is no single best way to detect and analyse the variety of structures associated with RNA methylation, often resulting in a need for a combinatorial approach to gain insights into their stoichiometry whilst maintaining sequence information . It is tDeeper understanding of the epitranscriptome and its consequences can only lead to a better ability to control gene expression in desirable ways. The epigenetics revolution is now leading to improved diagnostics and therapeutics for disease, and the fruits of the epitranscriptomics revolution are likely to be as exciting.2D-TLC, two-dimensional thin-layer chromatography; FTO, fat mass and obesity-associated protein; MeRIP-seq, methylated RNA immunoprecipitation sequencing; mRNA, messenger RNA; MS, mass spectrometry


All plant species are subject to disease. Plant diseases are caused by parasites, e.g. viruses, bacteria, oomycetes, parasitic plants, fungi, or nematodes. In all organisms, gene expression is tightly regulated and underpins essential functions and physiology. The coordination and regulation of both host and pathogen gene expression is essential for pathogens to infect and cause disease. One mode of gene regulation is RNA silencing. This biological process is widespread in the natural world, present in plants, animals and several pathogens. In RNA silencing, small (20–40 nucleotides) non-coding RNAs  accumulate and regulate gene expression transcriptionally or post-transcriptionally in a sequence-specific manner. Regulation of sRNA molecules provides a fast mode to alter gene activity of multiple gene transcripts. RNA silencing is an ancient mechanism that protects the most sensitive part of an organism: its genetic code. sRNA molecules emerged as regulators of plant development, growth and plant immunity. sRNA based RNA silencing functions both within and between organisms. Here we present the described sRNAs from plants and pathogens and discuss how they regulate host immunity and pathogen virulence. We speculate on how sRNA molecules can be exploited to develop disease resistant plants. Finally, the activity of sRNA molecules can be prevented by proteins that suppress RNA silencing. This counter silencing response completes the dialog between plants and pathogens controlling plant disease or resistance outcome on the RNA (controlling gene expression) and protein level. Most studied molecules that plants can recognize are peptides and proteins such as extracellular pathogen-associated molecular patterns (PAMPs) or intracellular pathogen effectors delivered into the host cells. Recognition by the plant triggers signal transduction events and this can lead to rapid defense responses that include massive transcriptional reprogramming within the plant. sRNA molecules, usually non-coding RNA molecules that are shorter than 200 nucleotide in length, can also lead to transcriptional reprogramming. sRNAs can form double-stranded RNA (dsRNA) that trigger post-transcriptional RNA silencing (PTGS) and lead to a decrease in messenger RNA level. RNA silencing is an epigenetic mechanism that initiates and sustains epigenetic changes, as do DNA methylation and histone modification. Epigenetic changes are heritable changes in gene expression that do not involve changes to the underlying DNA sequence; in other words: a change in phenotype without a change in genotype. Consequently epigenetic mechanisms provide a rapid mode to alter gene activity, e.g. when plants are exposed to parasites , DCL2 and DCL4 activity for natural antisense short interfering RNA (natsiRNA), DCL3 activity for repeat associated small interfering RNA (rasiRNA) and DCL4 activity for trans-acting small interfering RNA (tasiRNA) production  are more susceptible to the bacterium, P. syringae pv. tomato (avrRpt2), the fungus, Verticillium dahliae, and viruses, indicating that the production of sRNAs is important for immunity against multiple  pathogens  of the target genes. This evolutionary dilemma applies for miRNAs that target developmental processes, as well as for miRNAs that target immune systems. However, if host fitness is dependent upon faithful targeting of immune system genes such as R-genes, this is no easy task. Unlike most genes controlling development, R-genes are notorious for their rapid, adaptive protein evolution and in this sense, act as a moving target for their corresponding miRNAs  approach. sRNAs that arrest parasites and promote disease resistance could be applied directly to crops (Kamthan et al. sRNAs can alter plant immunity depending upon the action of their targets. Disease susceptibility can be enhanced following the accumulation of parasite or plant sRNAs that silence plant genes important for resistance Table . Eight oDMR1 or DMR6, are also regulated by sRNAs during downy mildew infection (van Damme et al. On the other hand, resistance can be enhanced when sRNA accumulate which silence plant “susceptibility” genes and/or genes that are required for pathogen virulence. Nine plant sRNAs that enhance disease resistance against pathogens and three sRNAs that enhance resistance against plant parasites have been reported Table . AlthougVerticillium dahliae (Table Silencing of viral gene transcripts by plant sRNAs proceeds inside the plant cell, however the silencing of three fungal genes by two plant miRNAs is suggested to take place in the fungus. Absence or reduction of these fungal genes affects the virulence and fitness of the fungus, ae Table .Although sRNAs that enhance disease resistance can be used directly to generate disease resistant plants (shaded box Fig. Phytophthora sojae, the causal agent of root and stem rot of soybean, were also shown to suppress RNA silencing in plants by inhibiting the biogenesis of sRNAs (Qiao et al. Although the RNA silencing mechanism was originally identified as a defence mechanism against viruses, viruses can counteract this defence mechanism by suppressing the host RNA silencing response (Burgyán and Havelda RNA silencing suppressor proteins are translocated from the parasite to the plant (Fig. In this review we focus on sRNAs that alter plant immunity. Johanna Westerdijk started her position 44 years before the genetic code and messenger RNA were described. What if Johanna could search through the genomes of the fungi in her collection and browse through all the sequenced plant genomes? Even more, what if she could gain insight into the regulation of all the sRNAs and transcripts present in both plant and the fungal genomes. Needless to say, this would allow her to gain insights into the various life styles of fungi on the molecular, genomic and epigenetic level. How different would it have been if she were able to visualize the communication between various organisms on the epigenetic level? Clarifying the “communication sources” e.g. the identification of small RNAs and how they are utilized by both the plant and the parasite to cause resistance or disease can be exploited to develop disease resistant plants in the future.


Gene expression involves multiple steps from the transcription of a mRNA in the nucleus to the production of the encoded protein in the cytoplasm. This final step occurs through a highly regulated process of mRNA translation on ribosomes that is required to maintain cell homeostasis. Alterations in the control of mRNA translation may lead to cell’s transformation, a hallmark of cancer development. Indeed, recent advances indicated that increased translation of mRNAs encoding tumor-promoting proteins may be a key mechanism of tumor resistance in several cancers. Moreover, it was found that proteins whose encoding mRNAs are translated at higher efficiencies may be effective biomarkers. Evaluation of global changes in translation efficiency in human tumors has thus the potential of better understanding what can be used as biomarkers and therapeutic targets. Investigating changes in translation efficiency in human cancer cells has been made possible through the development and use of the polyribosome profiling combined with DNA microarray or deep RNA sequencing (RNA-Seq). While helpful, the use of cancer cell lines has many limitations and it is essential to define translational changes in human tumor samples in order to properly prioritize genes implicated in cancer phenotype. We present an optimized polyribosome RNA-Seq protocol suitable for quantitative analysis of mRNA translation that occurs in human tumor samples and murine xenografts. Applying this innovative approach to human tumors, which requires a complementary bioinformatics analysis, unlocks the potential to identify key mRNA which are preferentially translated in tumor tissue compared to benign tissue as well as translational changes which occur following treatment. These technical advances will be of interest to those researching all solid tumors, opening possibilities for understanding what may be therapeutic Achilles heels’ or relevant biomarkers. Protein synthesis relies on the regulation of mRNA synthesis and degradation as well as on its translation efficiency. Upon synthesis, mRNA undergoes multiple processing steps before being exported to the cytoplasm to be either stored in untranslated form, directed to degradation or loaded onto ribosomes for conversion into proteins -3. Thus,via activation of stress-based adaptive translational mechanisms [e.g., HRI, GCN2 and PERK) is a major stress-induced event known to modulate mRNA translation during both hypoxia and nutrient deprivation towards the preferential expression of pro-survival functions [e.g., HIF1) and downstream growth factors are responsible for angiogenesis, invasion and metastasis, inducing chemoresistance [Indeed, upregulation of the translation of mRNAs encoding tumor-promoting proteins is a well-recognized mechanism of tumor progression ,5. Two ichanisms ,15. Amonunctions -9, 16-18et al. [in vivo is currently in its infancy, mainly because of limitations arising from the poor quality of isolated tumors polyribosomes.Global changes that occur in translation with the development of cancer are still not well defined and are not detectable with commonly performed DNA or RNA-Seq . Polyribet al.  found thet al. ,40, in ket al. . AlthougPolyribosomes are generally prepared by velocity sedimentation through linear sucrose density gradients of total cytoplasmic extracts. However, our initial experiments showed that this classical method is inefficient to prepare polyribosomes from tissues and tumors. Our optimized homemade protocol presented here uses an initial step of ultracentrifugation through a sucrose cushion that enriches polyribosomes , which aEstablishment of xenografts and collection of transurethral prostate samples:•25G needle syringe•Sterile PBS  •Matrigel Membrane Matrix •3M Vetbond Tissue adhesive•Hank’s Balanced Salt Solution •D-sucrose (molecular biology & density gradient) •Glycerol •Tris Hydrochloride •NaCl •2 (Magnesium chloride hexahydrate) MgCl•DL-Dithiothreitol (DTT) •Nonidet P40 substitute •Complete protease inhibitor cocktail tablets •RNAseOUT Recombinant Ribonuclease Inhibitor •Sodium deoxycholate •Bromophenol blue •Cycloheximide  •Proteinase K •Acidic phenol •Phenol:Chloroform:Isoamyl alcohol (PCI) (125:24:1) •Isopropanol •EDTA •SDS •NaOAc (Sodium Acetate Trihydrate) •Illumina TruSeq stranded mRNA sample preparation kit •Agencourt AMPure XP beads Prepare solutions in RNAse-free glassware and plastic ware .NOTE: Buffers and sucrose solutions  should be preferentially prepared the day of the experiment.•2 in sterile distilled water. Store at 4ºC until use. Before use, add 1 mM DTT, complete protease inhibitor cocktail  and 60 U/ml RNAseOUT.Buffer #1: Prepare a solution containing 20 mM Tris (pH 7.4), 150 mM NaCl, 5 mM MgCl•2, 1% Nonidet P-40 substitute in sterile distilled water. Store at 4ºC. Before use, add 1 mM DTT, 1% sodium deoxycholate, 50 µg/ml cycloheximide, complete protease inhibitor cocktail  and 60 U/ml RNAseOUT.Buffer #2: Prepare a solution containing 20 mM Tris (pH 7.4), 150 mM NaCl, 5 mM MgCl•2. Mix until complete dissolution and complete to 100 ml with sterile distilled water. Store at 4ºC until use. Before use, add 1 mM DTT, 50 µg/ml cycloheximide, complete protease inhibitor cocktail  and 8 U/ml RNAseOUT.15%, 50% and 55% sucrose solutions: Dissolve 15 g, 50 g or 55 g of sucrose  in 40 ml of sterile distilled water supplemented with 20 mM Tris (pH 7.4), 100 mM NaCl and 3 mM MgCl•2. Mix until complete dissolution and complete to 100 ml with sterile distilled water. Add a little bit of bromophenol blue in order to get a dark coloration and agitate until the solution is homogeneous. Store at 4ºC until use.60% sucrose solution: Dissolve 60 g of sucrose in 40 ml of sterile distilled water supplemented with 10% glycerol (v/v), 20 mM Tris (pH 7.4), 100 mM NaCl and 3 mM MgCl•RNA extraction buffer: Prepare a solution containing 10 mM Tris (pH 7.4), 1 mM EDTA (pH 8.0), 0.2% SDS and 0.8 mg/ml proteinase K in sterile distilled water.•c 3M, pH 5.2: Dissolve 204.12 g of sodium acetate trihydrate in 400 ml of sterile distilled water. Adjust to pH 5.2 with acetic acid. Complete to 500 ml with sterile distilled water. Sterilize by autoclaving and store at room temperature.NaOA•Preparation of DEPC-treated water: Mix 1 ml of DEPC with 1 L of water, stir overnight and then autoclave.CAUTION: DEPC causes irritation to eyes, skin and mucous membranes. It is suspected to be a carcinogen. Prepare the solution in a fume hood and wear gloves. Alternatively, DEPC-treated water is also available on the market, e.g., Invitrogen, cat. # 750023.•Dounce tissue homogenizer with teflon pestle, working volume 7 ml•Beckman SW 40 Ti rotor and swinging buckets •Tubes PA Thinwall 12 ml •ISCO Density Gradient Fractionation System with UA-6 detector •Heating blocks•Refrigerated benchtop centrifuge•Spectrophotometer (Eppendorf BioPhotometer)•HiSeq 2500 system 1.1.1.Harvest LNCaP prostate cancer cells by trypsinization then inactivate trypsin by adding media containing 10% FBS and centrifuge for 5 min at 1500 rpm at room temperature.1.2.Remove the supernatant and wash the cell pellet twice with PBS.1.3.Resuspend the cell pellet in PBS.1.4.Count the cells with a Hemocytometer to determine cell concentration.1.5.Centrifuge the cell suspension for 5 min at 1500 rpm at room temperature.1.6.6 cells/100 in a Matrigel matrix: PBS (1:1) mix.Discard the supernatant and resuspend the cell pellet at 2 10Establishment of xenografts: Our protocol for the establishment of the human prostate tumor xenografts uses procedures and conditions approved by the Laval University’s Animal Care Committee.NOTE: From this step, always keep working on ice otherwise the Matrigel matrix could start polymerize. The Matrigel matrix is previously thawed overnight at 4ºC.1.7.6-day old nude female mice. Add a drop of tissue adhesive over the injection site before pulling out the needle in order to avoid losing material. The tumor growth is monitored at least twice a week by using calipers for measuring the size of the tumors.Prepare one tube per mouse containing 250 of the cell suspension and keep them on ice. Anesthetize each mouse with isoflurane inhalant just prior injection. Carefully mix the cell suspension by up and down to prevent cells from settling and inject, with a 25G needle, 100 of the cell suspension  containing 2 ml of buffer #1.Preparation of extracts from human xenografts and tumors: Euthanasia of mice was conducted according to procedures approved by the Laval University’s Animal Care Committee.NOTE: Xenografts weight is between 0.1 and 0.8 g. Human biopsies weight is between 0.5 and 0.8 g.2.4.Homogenize the tumors on ice with 10 strokes of the pestle of the ice-cold Dounce tissue homogenizer. Put a drop of the homogenate onto a microscope slide and check for cell lysis by phase-contrast microscopy. Only nuclei are visible after a complete cell lysate.CAUTION: Keeping samples and solutions on ice throughout all manipulations is important to reduce RNAse activity. Avoid harsh homogenization which may induce destabilization of polyribosomes.2.5.Clarification of the homogenate: Centrifuge the homogenate at 12000 rpm (13500 g) for 15 min at 4°C. Transfer the supernatant into a new 15 ml Falcon tube. Adjust the volume of the supernatant to 8 ml with the buffer #2.TIP: Measure of RNA concentration with a spectrophotometer may be done to estimate the quantity of RNA obtained. One OD260 unit correspond to 40 µg/ml of RNA.NOTE: Keeping the tumors cold helps in preventing fortuitous dissociation of polyribosomes and to prevent mRNA degradation during the preparation of the extracts. For optimal polyribosome profiles results, use cycloheximide, an antibiotic that block translation elongation by stalling polyribosomes-RNA interactions.3.3.1.Priming the tubing system: Wash the tubing system with 0.1% SDS for 5 min, with DEPC-treated water for 5 min and pump air in order to dry the apparatus.3.2.Preparing the gradients: Set the gradient parameters in order to obtain a linear 15%–55% gradient of 11 ml according to the manufacturer’s instructions.Preparation of the density gradient fractionation system and sucrose gradientsTIP: During the preparation of the gradients, ensure no air bubbles are trapped inside the tubing system, since bubbles disturb the gradient formation. When the gradient formation is finished, carefully transfer the tube on ice without disturbing it.4.4.1.Prepare a 3 ml cushion of 50% sucrose in a 12 ml polycarbonate ultracentrifuge tube by pipetting the sucrose solution against the tube wall.4.2.g) at 4ºC.Load the supernatant (step 2.5) onto the 50% sucrose cushion and centrifuge for 2 h at 35000 rpm  is recommended until ready to use. To load the supernatant, place the tip of the pipette against the tube wall close to the surface of the sucrose cushion without disturbing it. Ensure all loaded tubes are equivalent weights with a maximal difference of 0.01 g. Buffer #2 can be added to the top of the gradients to balance tubes weights.4.3.Remove all the sucrose after centrifugation and resuspend the resulting translucent pellet in 1 ml of buffer #2 by pipetting up and down.NOTE: We do not recommend to vortex your extract.4.4.Incubate on ice for 30 min to complete homogenization.TIP: Mix the extract by repeated pipetting during the incubation in order to obtain a complete resuspension of the pellet.4.5.260 with a spectrophotometer.Estimate the RNA concentration of the resuspended extract by measuring the ODNOTE: Proteins as well as non-ionic detergents will also absorb UV light near 260 nm and this will result in an overestimation of RNA concentration. All UV blank determination should be done using buffer #2 as standard. At this step, only an estimation of RNA concentration is needed.4.6.260) on the top of the 15%–55% sucrose gradient (prepared at step 3.2) without disturbing the interface.Carefully load the sample  for 2 h 30 min at 4ºC.Gently place the gradients in a Beckman SW 40 Ti rotor and centrifuge the gradients at 37000 rpm  Sensitivity: 0.2 (tumor biopsies) or 0.5 (xenograft); (2) Peak separator: OFF; (3) Noise Filter: 1.5.Fractionation of polyribosomesTIP: The sensitivity of the detector can be changed depending of the quantity of sample. The less material you have, the higher sensitivity of the detector should be chosen.5.4.5.4.1.Pump the 60% sucrose solution (colored with bromophenol blue) into the tubing system until it reaches the needle.Reading the gradients:TIP: Make sure to have a few drops dripping out of the needle. This will minimize the risks of introducing air bubbles into the gradient.5.4.2.Place carefully the gradient into the tube piercer of the Automated Density Fractionation System and then pierce the tube with the needle.TIP: Be sure to not create any waves in the gradient when you install the gradient in the tube piercing system.5.4.3.Start introducing the 60% sucrose solution into the gradient, set the chart speed to 60 and start the recording program.5.5.Collect each fraction (approximately 500 ) in an individual pre-labelled Eppendorf tube while the polyribosome profile is recorded on the chart paper.NOTE: The Optical Unit of the Density Gradient Fractionation System is configured to read the absorbance at 254 nm. Alternatively, an electronic acquisition of the polyribosome profile can be obtained.5.6.At the end of each run, transfer the collected fractions on ice. At this time, either store collected fractions at−80°C or directly precipitate protein-RNA complexes as follows.NOTE: Typically, we collect 24 fractions of approximately 500 per gradient.5.7.Repeat steps 5.4 to 5.6 if there is more than one gradient to analyze.CAUTION: Clean the tubing system between each gradient by pumping SDS 0.1% (5 min) and then DEPC-treated water (5 min). Ensure all water is out of the tube before the next gradient is processed.6.6.1.Precipitate RNA-protein complexes by adding 3 volumes of pure cold ethanol to each collected fraction and incubate overnight at −20 °C.6.2.g) for 30 min at 4 °C, remove the supernatant and let the pellets air dry for 10 min.Centrifuge RNA-protein precipitates at 13000 rpm  pH 4.3–4.7.6.6.Vortex during 15 s and centrifuge at 13000 rpm (16000 × g) for 15 min at 4ºC. Transfer the aqueous phase to a new Eppendorf tube without disrupting the white middle interphase.TIP: Avoid contamination with the organic phase.6.7.g) for 15 min at 4ºC.Add 500 of PCI ) to the aqueous phase, vortex then centrifuge at 13000 rpm  for 30 min at 4ºC. Carefully aspirate the supernatant without disturbing the pellet. Wash the pellet with 500 cold EtOH 70%. Centrifuge at 13000 rpm (16000 g) for 30 min at 4ºC. Carefully aspirate the supernatant and let the pellets air dry for few minutes.Centrifuge at 13000 rpm  of RNAse free water.NOTE: Alternatively, RNAstableBiomatrica, San Diego, CA, USA) may be used during long-term storage to protect samples from degradation.7.7.1.Check RNA quality using a 2200 TapeStation system .RNA-Seq analysis: This protocol is based on that used by the Next-Generation Sequencing Platform, Genomics Center, CHU de Québec-Université Laval Research Center, Québec City, CanadaCAUTION: High quality RNA is essential for successful cDNA library. It is critical to check RNA integrity to ensure that differential RNA degradation of samples is not later mistaken for differential expression. The RNA integrity number (RIN) is used to assess RNA quality and a RIN higher of 7 is ideal for RNA-Seq analysis. RNA purity is determined by measuring the 260/280 and 260/230 ratios. Acceptable 260/280 ratio for RNA purity: > 1.8.TIP: A minimum of 500 ng of total RNA is recommended for mRNA sequencing library preparation. However, some sequencing platforms can prepare cDNA library with less amount of total RNA .7.2.7.2.1.Poly(A) RNA are isolated from total RNA using oligo-dT attached magnetic beads followed by fragmentation of mRNA. Alternatively, ribosomal RNA can be depleted from polyribosomal RNA using Ribo-Zero rRNA Removal kit .7.2.2.The fragmented mRNA is used as template for cDNA synthesis by reverse transcription with random primers. The resulting cDNA are then converted into double-stranded cDNA that are end-repaired to incorporate the specific index adaptor for multiplexing.7.2.3.The cDNA library is further purified with Agencourt AMPure XP beads and amplified by PCR.Prepare mRNA sequencing libraries using the Illumina TruSeq stranded mRNA sample preparation kit in accordance with manufacturer’s instructions.NOTE: The quality of final amplified libraries is examined with a DNA screentape D1000 on a TapeStation 2200. The quantification is done on the QBit 3.0 fluorometer  as well as by qPCR using KAPA library quantification kits. .7.3.Sequencing and analysis: RNA-Seq libraries with unique index were pooled together in equimolar ratio. The pool is then sequenced using an HiSeq 2500 system at the Next-Generation Sequencing Platform, Genomics Center, CHU de Québec-Université Laval Research Center, Québec City, Canada, and data analyzed using standardized pipeline, from sample demultiplexing, quality control and trimming to transcript quantification and different expression analysis.Figure 1 and 2, we have successfully generated high-quality polyribosome profiles prepared from human tumors grown in mice  as well as from prostate cancer specimens derived from transurethral resection of the prostate . This protocol also allows us to prepare intact polyribosome-bound mRNA which can be readily amplified and analyzed by RNA-Seq for further bioinformatics analyses as described [As shown in escribed . By multe.g., prostate) and then analyzed for differential translational changes between tumors and benign specimens with Sleuth. Sleuth will use bootstrapping results from Kallisto to error-correct and evaluate significant differential expressions through model fitting . The obtained translational variations will also be corrected for differences in the cytoplasmic level of mRNAs in order to identify translatome variations that are not due to alterations in the steady-state level of mRNAs [An important step of the identification of relevant translatome cancer data relies on an adapted bioinformatics analysis, which requires a well-developed pipeline dedicated to analyzing RNA-Seq data derived from human tumor polyribosome profiles. This includes poor quality sequence trimming, clipping of adapter sequences from the reads using softwares such as Trimmomatic. The resulting reads will be pseudo-aligned by bootstrap using Kallisto  to humanof mRNAs ,45. Bioiof mRNAs .e.g., stalling [Polyribosome RNA-Seq does not generate however direct evidence of mature proteins . In addistalling - and miRstalling -mediatedstalling -50. We svia an enrichment analysis on lists of up- and down-regulated genes (FDR < 0.05) using pathway analysis tools: the Kyoto Encyclopedia of Genes database. Prioritization for further validation and functional studies can be based on literatures, magnitude of translational changes and putative function, such as genes encoding functions relevant to tumors progression and resistance including cell cycle regulators, stress genes, DNA repair and cell survival. Standard in vitro  and in vivo  validation experiments of the identified targets should further confirm changes relevant to cancer and resistant phenotype, including proliferation, apoptosis or invasion assays, and tumor development, relevant to the putative function of the target gene. Subsequent patient validation studies will include evaluation of selected targets in the collected human tumors samples to confirm the tumor-specific nature of the candidate targets by immunohistochemistry or western blot. Further validation of the prognostic importance of these proteins may also be evaluated in accessible specific cancer microarrays.Validated corresponding genes whose mRNA translational efficiencies are significantly upregulated in tumors can be grouped in biological functional categories according to annotations from the gene ontology consortium . GeneratIn conclusion, applying polyribosomes profiling in human tumors may open possibilities for understanding what may be novel therapeutic Achilles heels’ for cancer cells or relevant biomarkers of treatment resistance. As aforementioned, the use of such an approach in prostate cancer cells has highlighted the role of YB-1 and MTA1 levels, with validation in human microarrays . HoweverThe main limitation of our technique is that the amount of tissue required exceeds that typically available from percutaneous biopsies. Further, there is inevitable exposure to body and room temperature as part of the surgical procedure, as well as cautery artifact. Nonetheless, our results with transurethral-obtained prostate chips were reproducible and suggest the technique will be easily adaptable to other tumor sites. As compared to other proteomics approaches, polyribosome profiling is costly due to the expenses of RNA-Seq which however should drop with development of new generations of RNA-Seq. Although proteomics approaches appear less time consuming, necessitating less steps than polyribosome profiling to be completed, they are limited in their ability to cover the full proteome, and therefore in their ability to assess changes on a global cellular scale. Further, protein measurements with proteomics approaches reflect both protein synthesis and degradation. The latter is a highly regulated process that precludes direct assessment of translation efficiency which depends mainly on the rate of protein synthesis. Polyribosome profiling allows direct measurement of translation efficiency, circumventing possible contributions of protein degradation which could compromize the accuracy of the data. Finally, unlike protein, RNA molecules can readily be amplified, making their measurement for identification of novel isoforms as well as for comprehensive global analysis based on limited clinical samples more feasible. Similarly, evaluation of relative differences in protein levels following the development of resistance is more difficult with proteomics approaches ,52. HoweThis protocol highlights a method to obtain polyribosomes profiles from solid tumors to facilitate global analysis of translational changes in solid tumors. Such analysis has a clear potential to advance our fundamental knowledge in cancer research. As it has previously been done with transcriptomic and proteomic data, the unique comprehensive data obtained may be translated to benefit patients through the identification of novel targets or biomarkers.Table 1.Possible problems and their troubleshooting solutions are listed in