We have studied confined nuclear migration in Caenorhabditis elegans larval P cells, which is mediated by the LINC complex to pull nuclei towards the minus ends of microtubules. Null mutations of the LINC component unc-84 lead to a temperature-dependent phenotype, suggesting a parallel pathway for P-cell nuclear migration. A forward genetic screen for enhancers of unc-84 identified cgef-1 (CDC-42 guanine nucleotide exchange factor). Knockdown of CDC-42 in the absence of the LINC complex led to a P-cell nuclear migration defect. Expression of constitutively active CDC-42 partially rescued nuclear migration in cgef-1; unc-84 double mutants, suggesting that CDC-42 functions downstream of CGEF-1. The Arp2/3 complex and non-muscle myosin II (NMY-2) were also found to function parallel to the LINC pathway. In our model, CGEF-1 activates CDC-42, which induces actin polymerization through the Arp2/3 complex to deform the nucleus during nuclear migration, and NMY-2 helps to push the nucleus through confined spaces.Successful nuclear migration through constricted spaces between cells or in the extracellular matrix relies on the ability of the nucleus to deform. Little is known about how this takes place  Highlighted Article: An actin-based pathway allows nuclei to squeeze through narrow spaces as a normal part of development in C. elegans. A system where mouse dendritic cells are imaged migrating through the extracellular matrix of explanted mouse ears has been used to find more in vivo relevance  in C. elegans (unc-84(null) mutants is morphologically distinct from normal programmed cell death and are not affected by the ced-3(n717) mutation  protein UNC-84 and the KASH  protein UNC-83 . UNC-84,essfully . This leunc-84 (emu) at 15°C (emu mutations were isolated in these screens and one was identified as a lesion in toca-1 (transducer of Cdc-42-dependent actin assembly)  . TOCA-1 ssembly) . One modssembly) .emu allele in cgef-1 that is predicted to encode a guanine nucleotide exchange factor (GEF) for CDC-42 , MIG-2 (Rac) and CDC-42  mutants were missing an average of 2.08±0.66 [mean±95% confidence interval (CI)] GABA neurons, slightly above wild type  double mutants had an average of 4.41±0.73 missing GABA neurons (P<0.00005). yc3 also enhanced the nuclear migration defect of unc-84(n369) at 20°C and at 25°C  is the molecular lesion responsible for enhancing the nuclear migration defect of unc-84, we tested whether other alleles of cgef-1 also enhance the P-cell nuclear migration defect of unc-84(n369) null mutants. cgef-1(gk261) is likely a null allele, as it is a 318 bp deletion that removes the entire third exon in cgef-1a and is predicted to result in a frame shift (cgef-1(gk261) unc-84(n369) double mutants had significant P-cell nuclear migration defects at 15°C, 20°C and 25°C compared with the single mutants (cgef-1(RNAi) significantly enhanced the nuclear migration defects of unc-84(n369)  . Thus, myc3 phenotype is due to the molecular lesion in cgef-1 and not some other mutation in the genome, we expressed cgef-1 extra-chromosomal rescue arrays in yc3, unc-84(n369) double mutants. Two fosmids that together cover the longest predicted isoforms of cgef-1 (WRM0622bA03 and WRM0625dG08) were able to rescue the nuclear migration defect in three independent lines (P<0.0005)  . TogetheC. elegans encodes at least four cgef-1 predicted isoforms  domain, as well as a pleckstrin homology (PH) domain  that spans only the cgef-1a, cgef-1c and cgef-1d isoforms was sufficient to rescue the cgef-1(yc3) unc-84 nuclear migration defect at 15°C, indicating that exons 1-11 of cgef-1b are not necessary for P-cell nuclear migration (CGEF-1 activates CDC-42 during early embryogenesis . C. elegisoforms  (Ziel et) domain . cgef-1aigration .cgef-1 functions in this process, we generated new alleles in each isoform using CRISPR-Cas9 gene editing, either as an early stop codon in the first or second exon of an isoform or as a deletion mutation that resulted in a predicted frameshift (cgef-1b(yc101) and cgef-1b(yc102), did not enhance the nuclear migration defect of unc-84(n369) at 15 or 20°C (cgef-1d(yc103) early stop codon and cgef-1d(yc104) frame-shift deletion mutations significantly enhanced the nuclear migration defect of unc-84(n369) at 15 and 20°C  and cgef-1a,c(yc110), also enhanced the nuclear migration defect of unc-84(n369) at 20°C but not at 15°C. Thus, we conclude that cgef-1b is dispensable for P-cell nuclear migration whereas cgef-1d and cgef-1a,c contribute to nuclear migration when the LINC complex is disrupted.To further determine which isoform of ameshift . Predict or 20°C . In contand 20°C . Mutatiocgef-1a,c and cgef-1d isoforms are expressed in P-cells during nuclear migration. We used previously described 5′cis-regulatory element reporter strains that drive the expression of GFP under the control of promoters for cgef-1d or cgef-1a,c  system  nuclear migration defect at both 15°C and 25°C  system . We taggigration . Howeverand 25°C , suggestcdc-42 is in the same pathway as cgef-1 by degrading CDC-42 in cgef-1, unc-84 double mutants. Degradation of CDC-42 in cgef-1(gk261), unc-84(n369) double mutant L1 larvae significantly enhanced the P-cell nuclear migration defects of the double mutant alone (cgef-1(gk261) is a predicted null, this result suggests that CGEF-1 and CDC-42 have partially independent roles, and that other RhoGTPases or GEFs may function during P-cell nuclear migration.We next tested whether nt alone . Becausecgef-1, we expressed constitutively active cdc-42, rho-1, mig-2 or ced-10 (cgef-1(yc3), unc-84(n369) double mutants. When constitutively active cdc-42(G12V) was expressed from an extrachromosomal array under the control of the P-cell-specific hlh-3 promoter, it was able to partially rescue the nuclear migration defect of cgef-1(yc3), unc-84(n369) double mutants , mig-2(G16V) or ced-10(G12V) were expressed in P cells, we did not observe rescue of nuclear migration defects in cgef-1(yc3), unc-84(n369) mutants. Instead, we observed an enhancement of P-cell nuclear migration defects when Rac family members mig-1(G16V) or ced-10(G12V) were overexpressed in cgef-1(yc3), unc-84(n369) mutants , actin networks (ARX-3 of the Arp2/3 complex) and actomyosin contractions (NMY-2) to determine their necessity for P-cell nuclear migration.unc-84(n369) nuclear migration defect at 15°C but not at 20°C (unc-84(n369) mutants. Furthermore, the degradation of PKC-3 did not significantly enhance the nuclear migration defect of unc-84(n369) (CDC-42 activates PAR-6 and PKC-3 during polarization events in early embryogenesis  and regu at 20°C . However84(n369) . A cavea84(n369) . TogetheC. elegans homolog of mammalian Arp3, is one of the seven subunits that make up the ARP2/3 complex (unc-84(n369) nuclear migration defect  gene. Degradation of NMY-2 in an unc-84(n369) background resulted in a significantly worse nuclear-migration defect than the unc-84(n369) single mutant larvae  and cgef-1(yc21) disrupt both vulval and neuronal lineages, suggesting that the defect occurs before the division of Pn cells to Pn.p and Pn.a. Additionally, in cgef-1(yc3) or cgef-1(yc21) larvae, there were always the normal number of six P cells present on each lateral side of an embryo or early L1 larva, and these P cells developed normally, narrowing as in wild type until just before nuclear migration  is(are) important during a narrow window of development in mid-L1 when P-cell nuclei migrate. P cells divide within 1 h of nuclear migration to the ventral cord to form Pn.p daughters, which develop into hypodermal and vulval cells, and Pn.a daughters, which are neuroblasts . Our enhigration . Thus, tAlthough our genetic findings implicate actin networks in nuclear migration, it is still not clear where in the cell that actin- and/or actomyosin-specific structures function to move nuclei. One possibility is that branched actin could be localized at the leading edge of the nucleus to deform it as it enters the constriction. This would be analogous to nuclei in mouse dendritic cells induced to migrate through fabricated constrictions . AlternaC. elegans P cells as a model is that the formation of cellular protrusions, often associated with cell migrations, can be genetically separated from nuclear migrations through constricted spaces. During embryonic development, hypodermal P cells extend cytoplasmic protrusions from the lateral side of the embryo; these protrusions meet at the ventral midline to cover up the endoderm during embryonic ventral enclosure  mutants remain at their lateral starting points, retract their cytoplasm into the lateral region, remain alive, and form ectopic GABA neurons and pseudovulvae in the lateral side of the animal  (yc3 and yc21 strains but not the other four sequenced strains. The SNP was predicted to cause an early stop codon in cgef-1. No other unique mutations predicted to cause stop codons were identified in the six strains.Strains carrying the 84 (emu) . We coll84 (emu) . Genomic84 (emu) . For eac84 (emu) . We focuC. elegans animals were grown on NGM plates seeded with OP50 at their specified temperatures (C. elegans strains used in this study were provided by the Caenorhabditis Genetics Center (CGC), which is funded by the National Institutes of Health Office of Research Infrastructure Programs (P40OD010440). The strains used in this study are described in eratures . Some C.in vitro, which was then injected into UD87 as described previously   was usedeviously .cgef-1 rescue experiments were from the C. elegans Fosmid Library (Source BioScience) and were amplified in bacteria using CopyControl Induction Solution  and purified using a DNA midi prep kit . Fosmid injection mixes contained 5 ng/µl of each indicated fosmid and 100 ng/µl of odr-1::gfp plasmid  as a co-CRISPR marker (zen-4 crRNA (0.6 mM), 0.21 µl target gene crRNA (0.6 mM), 1.033 µl tracr (0.17 mM), 4.39 µl Cas9 (40 µM), 0.28 µl ssODN zen-4(+) repair template (500 ng/µl) and 4 µl ssDNA repair template (500 ng/µl). The injection mix was injected into germline of temperature-sensitive zen-4(cle10) mutant young adults and screened as previously described p], an unnamed strain from Abby Dernburg  that expresses single copy TIR1 in the germline, was used for injections. Protein Cas9 and synthetic RNA were generated by Integrated DNA Technologies.An auxin-induced degron was inserted into the 5′ end of NA oligo . A dpy-1activity . The strhlh-3::2xHA::cdc-42(G12V)::unc-54 3′UTRp], the cdc-42(G12V) open reading frame was amplified from pEL298 (cdc-42 start codon. To generate plasmid pSL885 [hlh-3::2xHA::mig-2(G16V)::unc-54 3′UTRp], the mig-2(G16V) open reading frame was amplified from pEL656 (mig-2 start codon. To generate plasmid pSL886 [hlh-3::2xHA::ced-10(G12V)::unc-54 3′UTRp], the ced-10(G12V) open reading frame was amplified from pEL777 (ced-10 start codon. To generate plasmid pSL887 [hlh-3::2xHA::rho-1(G14V)::unc-54 3′UTRp], the rho-1(G14V) open reading frame was amplified from pEL1021  was used to assemble pSL884, pSL885, pSL886 and pSL887. Injection mixes containing 2 ng/µl of a plasmid encoding a constitutively active construct and 100 ng/µl of plasmid odr-1::gfp (To generate plasmid pSL884 [m pEL298  with homm pEL656  with homm pEL777  with hom pEL1021  with homr-1::gfp  as a co-unc-47::gfp]oxIs12[p transgenic worms (EG1285) were used as the wild-type control  was scored for each animal as previously described  and cloned under control of the hlh-3 promoter in pSL780  to visualize P-cell nuclei throughout development. Once animals reached the L4 stage, the number of UNC-47::GFP marked GABA neurons were quantified.Synchronized L1 animals were washed off normal NGM plates with distilled water ∼2 h before P-cell nuclear migration began. Next, the L1 larvae were transferred to NGM+auxin plates with 1 mM 3-indoleacetic acid  and kept in the dark. After P-cell nuclear migration was completed, the L1 larvae were washed off the NGM+auxin plates with M9 buffer and subsequently transferred to an NGM plate. For experiments performed at 15°C, embryos were left on the plates to develop for 29 h and then the resulting L1s were washed onto NGM+auxin plates and left to develop for 8 h before being washed off onto NGM plates without auxin to develop to the L4 stage. For experiments carried out at 20°C, embryos developed into L1s on NGM plates for 18 h and then placed on NGM with auxin plates for 7 h. For experiments performed at 25°C, embryos developed into L1s for 12 h and then placed on NGM with auxin plates for 6 h. These timings were determined by using the marker pC. elegans for imaging, three to five plates of gravid animals were bleached, and eggs were pelleted and resuspended in M9 solution for 12-16 h at room temperature on a rocker. After starvation, L1s were plated onto NGM plates seeded with OP50 and grown at room temperature for 12 h. After 12 h, L1s were washed off the plates with M9 and mounted onto 2% agarose slides with 1 mM tetramisole solution.To synchronize Images were taken on a Zeiss LSM 980 with Airyscan using 20× objective and the Zeiss Zen Blue software that was provided by the MCB light imaging microscopy core and by the National Institutes of Health.t-test was used to determine statistical significance when there was a single comparison. We used one-way ANOVA analyses with Holm-Sidak's corrections for multiple comparisons. Error bars are 95% confidence intervals.Graphs of GABA neuron counts were created by using Prism (version 9). An unpaired, two-tailed Student's Click here for additional data file.10.1242/develop.202115_sup1Supplementary informationClick here for additional data file.


RNA undergoes complex posttranscriptional processing including chemical modifications of the nucleotides. The resultant-modified nucleotides are an integral part of RNA sequences that must be considered in studying the biology of RNA and in the design of RNA therapeutics. However, the current “RNA-sequencing” methods primarily sequence complementary DNA rather than RNA itself, which means that the modifications present in RNA are not captured in the sequencing results. Emerging direct RNA-sequencing technologies, such as those offered by Oxford Nanopore, aim to address this limitation. In this study, we synthesized and used Nanopore technology to sequence RNA transcripts consisting of canonical nucleotides and 10 different modifications in various concentrations. The results show that direct RNA sequencing still has a baseline error rate of >10%, and although some modifications can be detected, many remain unidentified. Thus, there is a need to develop sequencing technologies and analysis methods that can comprehensively capture the total complexity of RNA. The RNA sequences obtained through this project are made available for benchmarking analysis methods. N6-methyladenosine (m6A), and others are complex multistep modifications, resulting in wybutosine  and a sugar-phosphate backbone. The bases and sugar of RNA undergo chemical alteration, leading to >150 modified nucleotides  methods do not sequence RNA, rather RNA is converted back to DNA and the resultant DNA is sequenced; in the reverse transcription, all modifications are lost  and the >150 modifications, it is necessary to train base-calling algorithms to establish the correspondence between the nucleotides and their corresponding current patterns. Many groups have developed methods to convert the current signals to sequence  was cloned from human fibroblast DNA into the pcDNA3.1-GFP(1–10) (Addgene cat# 70219) vector. The clone sequence was as follows:UUGAGCAUUUCAUCCGGAGUCUGGCCGCCCUGACCUUCCCCCAGCCGCCUGCAGGGGGCGCCAGAGGGCCGGAGCACGGAAAGCAGCGGAUCCUUGAUGCUGCCUUAAGUCCGGCUCAGAGGGGCGCAGCGUGGCCUGGGGUCGCUAUCUUCCCAUCCGGAACAUCUGCCCUGCUGGGGGACACUACGGGCCUUCCCUUGCCUGAGGGUAGGGUCUCAAGGUCACUUGCCCCCAGCUUGACCUGGCCGGAGUGGCUAUAGAGGACUUUGUCCCUGCAGACUGCAGCAGCAGAGAUGACACUGUCUCUGAGUGCAGAGAUGGGGGCAGGGAGCUGGGAGAGGGUUCAAGCUACUGGAACAGCUUCAGAACAACUAGGGUACUAGGAACUGCUGUGUCAGGGAGAAGGGGCUCAAGGACUCGCAGGCCUGGGAGGAGGGGCCUAGGCCAGCCAUGGGAGUUGGGUCACCUGUGUCUGAGGACUUGGUGCUGUCUGGAUUUUGCCAACCUAGGGCUGGGGUCAGCUGAUGCCCACCACGACUCCCGAGCCUCCAGGAACUGAAACCCUGUCUGCCCCCAGGGUCUGGGGAAGGAGGCUGCUGAGUAGAACCAACCCCAGGUUACCAACCCCACCUCAGCCACCCCUUGCCAGCCAAAGCAAACAGGCCCGGCCCGGCACUGGGGGUUCCUUCUCGAACCAGGAGUUCAGCCUCCCCUGACCCGCAGAAUCUUCUGAUCCCACCCGCUCCAGGAGCCAGGAAUGAGUCCCAGUCUCUCCCAGUUCUCACUGUGUGGUUUUGCCAUUCAUCUUGCUGCUGAACCACGGGUUUCUCCUCUGAAACAUCUGGGAUUUAUAACAGGGCUUAGGAAAGUGACAGCGUCUGAGCGUUCACUGUGGCCUGUCCAUUGCUAGCCCUAACAUAGGACCGCUGUGUGCCAGGGCUGUCCUCCAUGCUCAAUACACGUUAGCUUGUCACCAAACAUACCCGUGCCGCUGCUUUCCCAGUCUGAUGAGCAAAGGAACUUGAUGCUCAGAGAGGACAAGUCAUUUGCCCAAGGUCACACAGCUGGCAACUGGCAGAGCCAGGAUUCACGCCCUGGCAAUUUGACUCCAGAAUCCUAACCUUAACCCAGAAGCACGGCUUCAAGCCCCUGGAAACCACAAUACCUGUGGCAGCCAGGGGGAGGUGCUGGAAUCUCAUUUCACAUGUGGGGAGGGGGCUCCCCUGUGCUCAAGGUCACAACCAAAGAGGAAGCUGUGAUUAAAACCCAGGUCCCAUUUGCAAAGCCUCGACUUUUAGCAGGUGCAUCAUACUGUUCCCACCCCUCCCAUCCCACUUCUGUCCAGCCGCCUAGCCCCACUUUCUUUUUUUUCUUUUUUUGAGACAGUCUCCCUCUUGCUGAGGCUGGAGUGCAGUGGCGAGAUCUCGGCUCACUGUAACCUCCGCCUCCCGGGUUCAAGCGAUUCUCCUGCCUCAGCCUCCCAAGUAGCUAGGAUUACAGGCGCCCGCCACCACGCCUGGCUAACUUUUGUAUUUUUAGUAGAGAUGGGGUUUCACCAUGUUGGCCAGGCUGGUCUCAAACUCCUGACCUUAAGUGAUUCGCCCACUGUGGCCUCCCAAAGUGCUGGGAUUACAGGCGUGAGCUACCGCCCCCAGCCCCUCCCAUCCCACUUCUGUCCAGCCCCCUAGCCCUACUUUCUUUCUGGGAUCCAGGAGUCCAGAUCCCCAGCCCCCUCUCCAGAUUACAUUCAUCCAGGCACAGGAAAGGACAGGGUCAGGAAAGGAGGACUCUGGGCGGCAGCCUCCACAUUCCCCUUCCACGCUUGGCCCCCAGAAUGGAGGAGGGUGUCUGGAUUACUGGGCGAGGUGUCCUCCCUUCCUGGGGACUGUGGGGGGUGGUCAAAAGACC5)] of the 5-mers of the RNA synthesized with just the canonical nucleotides.The sequence includes 691 distinct 5-mers, about 70% 5-deoxyadenosine, 2.5 mM MgCl2, and 5 mM Tris-HCl buffer pH 8.0. The digestion mixture was incubated at 37°C for 6 h.RNA from each sample (2 µg) was hydrolyzed in a 50-µL digestion cocktail containing 8 U benzonase, 5 U calf intestinal alkaline phosphatase, 0.15 U phosphodiesterase I, 0.1 mM deferoxamine, 0.1 mM butylated hydroxytoluene, 5 ng coformycin, 50 nM internal standard [N1-methyladenosine (m1A), m/z 282 → 150, 1.2 min; m6A, m/z 282 → 150, 8.7 min; 5-hydroxymethylcytidine (hm5C), m/z 274.1 → 142.1, 0.88 min; Y, m/z 245 → 191, 0.88 min. Signal intensities for each ribonucleoside were normalized by dividing by the sum of the UV signal intensities of the 4 canonical ribonucleosides recorded with an in-line UV spectrophotometer at 260 nm.After digestion, all 9 samples were analyzed by chromatography-coupled triple-quadrupole mass spectrometry (LC-MS/MS). For each sample, 600 ng of hydrolysate was injected into each of 3 technical replicates. Using synthetic standards, HPLC retention times of RNA modifications were confirmed on a Waters Acuity BEH C18 column  coupled to an Agilent 1290 HPLC system and an Agilent 6495 triple-quadrupole mass spectrometer. The HPLC system was operated at 25°C and a flow rate of 0.3 mL/min in a gradient [Escherichia coli poly(A) polymerase, followed by Oxford Nanopore's protocol for direct RNA sequencing (SQK-RNA002). RNA samples were sequenced using an Oxford Nanopore MinION Mk1B device or a 5-cell GridION sequencer, with FLO-MIN106D flow cells . Reads were aligned to the clone sequence using minimap2 v2.17 , using tIn each sample, at each nucleotide position, we compared the RNA sequence to the corresponding sequence of the DNA sense strand, and then, we calculated the error rate as a ratio of mismatches to the total sequence reads at position (matched + mismatched). Those ratios are presented as percentages in the figures.For each sample, we also break down the errors by the 4 nucleotides in the DNA template. For each of the 4  nucleotides in the DNA, we looked for the number of mismatches in the RNA. In each sample, for each nucleotide, we determined the ratio of the number of mismatches to the total number of reads for the nucleotides and reported the ratios in percentages as A-to-X, C-to-X, G-to-X, and U-to-X where X is A, C, G, and U from Nanopore. The error rates calculated as implemented in our Python scripts are the same as those from EpiNano.To compute dwell times, reads were first resquiggled using f5c version 0.8  and principal component 1 (PC2) scores are plotted.Principal component analysis (PCA) was performed by using 7 variables  for the 45 samples . The data were normalized by using the Z-score. The PCA was calculated as the total variance explained.We also carried out a PCA with up to 5,000 randomly selected reads from each sample and the current and dwell times for the 5-mers that are most different among the modifications were used as variables. To select the variables for the PCA, for each 5-mer in our data, we performed ANOVA to identify the current signals that are most variable among the samples vs within, the top 5% of the most variable current signals were used as variables. The same analysis was used to identify the dwell times for the PCA. The variables were normalized by Z-score. The PCA was calculated as the total variance explained. For each sample, we then looked for the sites with the most modified nucleotides based on the PC1 and PC2 scores. We identified the outlier sites as those with PC scores furthest by Euclidean distance from the center of the plots; then at those locations, in each read, we looked for errors and longer dwell times to identify the most likely modified nucleotides. For the m6A, biotinylated-C, and Y samples, we only looked at the A, C, and U, respectively.Another PCA was performed for each sample with 7 variables  for each nucleotide. The data were also normalized by We synthesized a set of RNA transcripts with only canonical nucleotides and also with 10 different modified nucleotides. We then performed direct RNA sequencing using the Oxford Nanopore technology on those 2 kb RNA transcripts.O-methyladenosine (Am), 2′-O-methylcytidine (Cm), 2′-O-methylguanosine (Gm), and 2′-O-methyluridine (Um). Each of the modified nucleotides was added with its corresponding canonical nucleotide in 1:100, 1:10, 1:5, and 1:2 proportions .Some of the IVT reactions included canonical nucleotides only, others included different proportions of a modified base or sugar nucleotide and the corresponding canonical nucleotide. The modified bases consist of m1A, m6A, biotinylated cytidine, hm5C, 5-methylcytidine (m5C), Y, and the modified sugars were 2′-To verify that the modified nucleotides were incorporated into the RNA transcripts, the samples were checked by chemiluminescent assay and LC-MS/MS. The samples with biotinylated cytidine were checked by chemiluminescence using streptavidin-horseradish peroxidase. Additionally, to obtain a more accurate assessment of the modifications, 9 samples were analyzed by mass spectrometry. These include 1 sample synthesized with just canonical nucleotides and samples with m1A, m6A, hm5C, and Y at 2 concentrations . All the synthesized RNA transcripts were polyadenylated, and then sequenced using the Oxford Nanopore MinION. The base-calling was carried out using Guppy, alignment was performed with Minimap2 , and seqWe started by analyzing the 10 independently synthesized and sequenced sets of RNA with just canonical nucleotides. The samples were sequenced deeply with an average coverage of 5,563 reads  and is prone to slippage in particular when transcribing A/T homopolymers  and those from EpiNano  in the samples with and without modified bases. We found that all 6 nucleotides with modified bases have highly significantly different , the cytidines in the samples with modified cytidines  and the uridines in the Y samples. By motif analysis, we found that neighboring adenosines contributed to errors in the m6A samples but not in the m1A samples, this may allow for the 2 modifications to be distinguished. There is no such combination of features that allows us to tell apart the 3 modified cytidines. While all 6 modified bases led to significantly different dwell times in the pores, dwell time alone does not tell apart the different modifications.O-methylated sugars  at different proportions in the IVT reactions. The samples are deeply sequenced . We also carried out PCA with sequence reads to ask whether we can distinguish them. We used a similar concept in population genetic studies where individuals are grouped by populations based on their genotypes of genetic markers that have different allele frequencies across populations . We usedMaterials and Methods) and at those positions, we annotated the sequence reads with errors or longer dwell time as modified nucleotides  DNA template for IVT with 10 different modified nucleotides in a range of concentrations to generate RNA transcripts with modified bases or sugars. We also included RNA transcripts with only canonical nucleotides. The incorporation of the modified nucleotides was confirmed by chemiluminescence assay and mass spectrometry analyses. The RNAs were then sequenced on a Nanopore MinION with deep coverage, most samples having >5,000 reads. These are available for benchmarking algorithms for base-calling.We generated independently 10 sets of RNA with only canonical nucleotides for comparison with their counterparts with modified ribonucleotides. Direct RNA sequencing of the samples with only canonical nucleotides revealed that the error rate of Nanopore RNA sequencing is still >10%.Our analyses show that, while some modifications can be detected with existing algorithms such as Tombo and analysis of error patterns, we are far from sequencing RNA with all modifications. To obtain the complete sequences with all modifications, several technological advancements are needed. These include reducing the error rates to <0.1%, improving the resolution from 5-nucleotide to single-nucleotide, and developing base-callers that identify the canonical bases, known modifications, and yet-to-be discovered modifications. Given the large number of ribonucleotides per cell, even if we assume 10 pg of RNA per cell, there are >10 billion ribonucleotides in each cell, and thus, even a low error rate of 0.1% has many errors. Improvement in resolution to the single-nucleotide level will facilitate base-calling. Most probably, many modifications are transient and occur at a low level, so they are difficult to detect, and therefore, technical barriers such as poor resolution need to be improved. The biggest challenge of direct RNA sequencing is base-calling. Even if the instrument can capture current signals of a single nucleotide or uses methods such as exo-seq (RNA-sequencing technologies that provide the complete sequences with all the modifications, at affordable cost, will transform RNA biology and clinical medicine. The complete sequences will elucidate the basic aspects of RNA from splicing to stability. The sequences are crucial for the development of effective RNA-based therapeutics. The exact sequences are necessary for targeting specific RNA, replacing dysfunctional ones and in manufacturing vaccines. Development of sequencing technologies, coupled with analysis methods, is a necessary breakthrough to advance RNA biology and therapeutics.jkad200_Supplementary_DataClick here for additional data file.


Correction to: BMC Public Health (2023) 23:99310.1186/s12889-023-15803-8The original publication of this article contained an incorrect funding section. The incorrect and correct information is listed in this correction article, the original publication has been updated.IncorrectThis work was support by Science and Technology Commission Shanghai Municipality (No. 20JC1410204) for the Seroepidemiological Study of Novel Coronavirus Pneumonia in Key Populations.CorrectThis work was support by the Shanghai Municipal Health Commission [grant numbers GWV-10.1-XK18] and Science and Technology Commission Shanghai Municipality (No. 20JC1410204) for the Seroepidemiological Study of Novel Coronavirus Pneumonia in Key Populations.


Single-cell and single-population RNA sequencing (RNA-seq) is a rapidly evolving new field of intense investigation. Recent studies indicate unique transcriptomic profiles are derived based on the spatial localization of neurons within circuits and regions. Individual neuronal subtypes can have vastly different transcriptomic fingerprints, well beyond the basic excitatory neuron and inhibitory neuron designations. To study single-population gene expression profiles of spatially characterized neurons, we have developed a methodology combining laser capture microdissection (LCM), RNA purification of single populations of neurons, and subsequent library preparation for downstream applications, including RNA-seq. LCM provides the benefit of isolating single neurons characterized by morphology or via transmitter-identified and/or receptor immunoreactivity and enables spatial localization within the sample. We utilize unfixed human postmortem and mouse brain tissue that is frozen to preserve RNA quality in order to isolate the desired neurons of interest. Microisolated neurons are then pooled for RNA purification utilizing as few as 250 individual neurons from a tissue section, precluding extraneous nonspecific tissue contaminants. Library preparation is performed from picogram RNA quantities extracted from LCM-captured neurons. Single-population RNA-seq analysis demonstrates that microisolated neurons from both postmortem human and mouse brain tissues are viable for transcriptomic profiling, including differential gene expression assessment and bioinformatic pathway inquiry. For the last several decades, even prior to the development and implementation of RNA sequencing (RNA-seq) technologies, researchers have utilized various experimental protocols to query RNA expression levels of specific genes, using methods such as qPCR, microarray analysis, and chip-based technologies, which all strive to resolve the burning question, “what genes are differentially expressed?” ,5,6,7,8.In the last decade, a concerted effort has been put forth to advance RNA-seq technologies, which have several key benefits over previous transcriptomic identification and quantification technologies, including the ability to detect previously unidentified noncoding RNA (ncRNA) species, identification of sequence variations, including single nucleotide polymorphisms (SNPs) and highly homologous sequences, as well as having low to no background . There ain situ sequencing [Recently, high-precision technologies have improved enough to examine spatial transcriptomic profiles, including laser capture microdissection combined with RNA-sequencing (LCM-Seq) , spatialquencing . TechnicAnimal protocols were approved by the Nathan Kline Institute/New York University Grossman School of Medicine IACUC in accordance with NIH guidelines. In order to preserve the RNA quality and quantity for single neuron dissections, neurons from mouse and postmortem human tissue were isolated from unfixed frozen tissue. Mice were anesthetized with ketamine  and xylazine . Once mice were unresponsive to toe pinch, tails were taken to confirm genotype, and chest cavity was opened, wherein mice were checked for tumors or other malformations. Mice were perfused transcardially  with a 22-gauge catheter using 0.15 M phosphate buffer (pH 7.2) at 7.5 mL/minute (min) for ~2–3 min until the liver was completely cleared of blood. Following completion of perfusion, brains were removed from the skull and immediately flash frozen with powdered dry ice or liquid nitrogen. Once brains were frozen A,B, theyUtilizing either postmortem human E or mousTrue North boxes capable of holding 25 slides  with a small, perforated bag of desiccant were equilibrated at −80 °C, then put on dry ice. To select slides for LCM, a single slide box of stored cryocut samples was removed from weathertight totes and put on dry ice. Slides were chosen quickly and moved to 25-place True North boxes. Once completed, both slide boxes were returned to −80 °C in weathertight tote until ready to perform staining or LCM. To perform staining or LCM, the True North boxes with the selected specimens were equilibrated stepwise to room temperature (RT) as follows: closed slide boxes were quickly moved from −80 °C to −20 °C and incubated for 5 min. After 5 min equilibration at −20 °C, the slide box was quickly moved to 4 °C for 10 min, then moved to RT for 5 min without opening True North boxes with desiccant inside. Once equilibrated to RT for 5 min, boxes were opened, and slides were stained.A rapid protocol based on the Vector Labs ImmPress HRP reagent kit  was used, with the ImmPACT NovaRed chromogen employed as the peroxidase substrate . To preserve the RNA from the tissue, phosphate-buffered saline , blocking buffer , diluent buffer, and secondary antibody solutions  had 1 µL (20 U) per ml of RNase Inhibitor  added to solution immediately prior to use. Briefly, stepwise equilibration was performed, and slides were rinsed with ice-cold PBS. Blocking buffer was incubated for 5 min at RT . Blocking buffer was decanted, and primary antibody solution was added. To identify basal forebrain cholinergic neurons ,30, we u−1 min at RT [Briefly, stepwise equilibration was performed, and slides were rinsed with ice-cold PBS with optional 1 µL RNase Inhibitor added per ml of solution. Nissl stain was added  for ~30 sin at RT . Slides Samples were moved immediately following staining or equilibration to the LCM apparatus . LCM was limited to 1 h at RT to reduce RNA degradation. The ‘specimen overview’ feature  was used to generate a quick overview image using the 1.25× or 5× objective to orient tissue sections for cutting of single cells. Neurons were collected in 50 µL of ice-cold Qiazol , utilizing the 40× (N.A. 1.4) or 20× (N.A. 0.85) objective using the ‘draw and cut’ feature . Stained cell bodies were identified with a Wacom digitizer pen , outlined with the ‘point-to-point’ feature or with the ‘automated detection module’  using stained cells to identify cell bodies (outline was set at 15 pixels outside of the identified cell). Cells were outlined slightly outside of the cell body edge to allow for laser cutting line . Offset, power, aperture, speed, specimen balance, head current, and pulse frequency were adjusted as necessary to allow for thin cut line without burning adjacent tissue. If necessary, the ‘laser screw’ feature  was utilized with 1–2 steps at 3–5 µm to fully cut cells. Samples were identified by cell type, brain region, and sample number and stored at 4 °C. Once all samples from the slide were microisolated, accuracy of cutting was performed, either by counting collected cells that were fully cut or by using the ‘shape list summary’ feature . Samples were briefly spun down and moved to −80 °C until ready for RNA isolation.200 was used to estimate RNA quality [200 measures the percentage of RNA quantified that is larger than 200 base pairs.For LCM samples of 500–2000 neurons, the miRNeasy micro kit was employed . The manufacturer’s specifications were followed except for the following alterations. The optional DNase digestion step was performed with the following amendments: the RWT initial wash (B1) was performed with 700 µL per sample, not the 350 µL recommended; the RWT wash step B4 was performed with 600 µL RWT buffer; and flow through was collected at 750 µL to rewash the column (step B5). The DNase digestion was performed twice sequentially, meaning that after step B5, steps B2–B5 were repeated before continuing to original protocol. After the DNase digestion, the RPE buffer wash step was performed (step 11), not skipped as suggested by the kit specifications . Finally, for the final elution, after samples had 14 µL of RNase-free water added to column, a 1 min incubation was performed before the centrifugation step to help fully elute all RNA available on the column. Quality control was performed by bioanalysis using the 2100 Bioanalyzer system  in association with the RNA 6000 Pico kit  or the Tapestation  with the high-sensitivity RNA screen tape . This allowed for the quantification of the harvested RNA in pg/µL. For the Pico kit, any sample below ~100 pg/µL, and for the Tapestation, any sample below ~500 pg/µL, will not generate an RNA integrity number (RIN), in which case the DV quality . DV200 mThe SMARTer Stranded Total RNA-Seq kit-Pico input mammalian kit  was used according to the manufacturer’s specifications with the maximum amount of RNA utilized (or ~1 ng of RNA for larger neuron collections). Utilizing the fragmentation step was dependent on the quality of the RNA gathered. RNA derived from antibody-stained tissue was only performed with option 2 (without fragmentation). Additionally, for the newest version tested (v3), dependent on the amount and quality of RNA, PCR 1 (section B) and PCR2 (section E) were modified in terms of cycle number. For highly degraded RNA, PCR1 was 10 cycles, and PCR2 was 16 cycles, whereas for cells collected from Nissl-stained tissue, PCR1 was 10 cycles, and PCR2 was 13–14 cycles, depending on the amount of starting RNA . The Takara v3 kit  includes unique molecular identifiers for dual indexes, which can result in higher visible primer dimer concentrations see D,E.Brain preparation is critical for downstream processing of the tissue, with perfusion using phosphate buffer or PBS utilized herein. Following perfusions, mouse brains were quickly dissected and frozen to preserve RNA quality. There are several quick freeze methods that can be utilized for the preservation of brain specimens. We tested three different protocols for rapid isolation and freezing of brain tissue to preserve RNA quality. Liquid nitrogen was utilized in a glass-walled crucible to perform rapid freezing, which cooled brain dissections within seconds of isolation. However, liquid nitrogen also caused cracking of brain tissue A, likelyIsolation of frozen postmortem human tissue is often conducted by a biobank or repository. Unless a researcher has access to fresh-cut human postmortem brain tissue and an approved protocol for their brain collection, postmortem human specimens are typically delivered not perfused but frozen and blocked by the neuropathologist for the regions of interest E. Once bTo preserve tissue quality and prevent crystal formation in and on cells, a step-down equilibration step is utilized, with desiccant added to prevent moisture formation on brain sections. When performed, we found little to no condensation or crystal formation on sections. For brain regions and cell types that can be easily identified by region and morphology, Nissl staining was utilized A,B,F. AlWe utilized the miRNeasy kit  for RNA isolation, which performs well for total brain and neuronal LCM samples. Previous work in bulk tissue dissection utilizing RNA purification kits without a phenol–chloroform extraction clogged the columns, including the RNeasy kit  and the Total RNA mini kit . For LCM samples, an estimate is ~1–10 pg of RNA per neuron. Antibody staining will skew the amount of RNA toward the lower end . These include the SMARTer Stranded Total RNA-Seq kit-Pico input mammalian and the SMART-SEQ Stranded Kit . We utilized both kits per the manufacturer’s specifications and found them to work with mouse (SMARTer) and human (SMARTer and SMART) LCM-collected samples, with at least 500 mouse neurons  or DV200  from 20–200 .in vivo brain tissues that are suitable for spatial transcriptomic analysis. Several key steps within this pathway can be modulated during sample preparation to utilize this protocol for samples from colorimetric, antibody-stained tissue, or fluorescently tagged cells. We document pitfalls, caveats, and salient points to consider to successfully navigate from brain collection to RNA-seq library preparation in the context of single-population assessments. Importantly, this protocol can be utilized for mouse or human neuron purification and has been successfully employed for antibody, colorimetric, and fluorescently tagged neuron isolations by LCM. Other species have not been investigated, but the likelihood of success is high based on our assessments of optimally  and suboptimally  prepared and collected brain tissue samples. Different cell types outside the CNS  are also likely to be excellent input sources of RNA, considering the difficulty associated with neuronal isolation and the success we have demonstrated herein. Finally, we highlight some ‘tips and tricks’ that may help to troubleshoot problematic dissections or isolations.In conclusion, we detail a protocol to successfully microisolate individual adult neurons from


Self-rated health (SRH) refers to the subjective evaluation of one’s own health. Big Five personality traits including Neuroticism, Agreeableness, Openness, Conscientiousness, and Extraversion have been consistently found as significant predictors of SRH. In addition, SRH declines with age, and personality traits change with age. Thus, it is reasonable to speculate that age might moderate the associations between personality traits and SRH. The current study analyzed data from 33,256 participants with a mean age of 45.78 years old and 55.92% females. The current study found that age significantly moderates the associations between Agreeableness, Openness, and Conscientiousness and SRH after controlling for demographic covariates. The current study implies that personality traits relate to SRH differently at different ages. Thus, studies regarding the associations between personality traits and SRH must take the interactions between age and personality traits into account. Self-rated health (SRH) refers to the subjective evaluation of one’s own health. Moreover, there is a substantial amount of evidence regarding the predictive validity of this single-item measurement of health. For instance, poor SRH is associated with higher risks of chronic disease, steeper cognitive decline, higher risks of dementia, and higher mortality risk across diverse groups . Thus, iThe Big Five is one of the most used inventories that measure personality traits, which include Neuroticism, Agreeableness, Openness, Conscientiousness, and Extraversion. This relationship between Big Five personality traits and health can be found in a wide range of health outcomes, including biological and functional markers ,b, mentaBesides objective health, personality is also closely related to SRH. For instance, Neuroticism is the tendency of experiencing negative emotions, which has been consistently associated with poor SRH in cross-sectional  and longAge is also a consistent predictor of SRH given objective health decreases with age. For instance, cardiovascular disease is more prevalent at older ages compared to younger counterparts . There aTaken together, this evidence seems to suggest that personality traits and age are closely associated with SRH. Thus, one would hypothesize that age moderates the associations between personality traits and SRH. As one gets older, they tend to have worse objective health and SRH, which makes them unable to be influenced by certain personality traits. The aim of the current study is to test how age might moderate the associations between Big Five personality traits and SRH.via surveys from the original sample of UK households since 1991 when it was previously known as The British Household Panel Study . Data from Wave 3 was used because only data from Wave 3 contains personality measures. After removing participants with missing values, there were 33,256 participants remaining for further analysis with a mean age of 45.78 years old and 55.92% females.The current study extracted data from Wave 3 (collected between 2010 and 2011), Understanding Society: the UK Household Longitudinal Study (UKHLS), which has been collecting annual information https://www.understandingsociety.ac.uk/documentation/mainstage/dataset-documentation/term/personality-traits?search_api_views_fulltext=. Studies have revealed that these short Big Five measures have good internal consistency, test-retest reliability, convergent validity, and discriminant validity  to 5 (“agree strongly”). Scores were reverse-coded when appropriate. The exact set of questions used to ask participants can be found: validity .Participants responded to the question, “In general, would you say your health is…” using a 5-point scale ranging from 1 (excellent) to 5 (very poor). The reliability of this single measurement of subjective health is high e.g., . SRH scoDemographic controls included age, sex, monthly income, the highest educational qualification, and the present legal marital status. Specifically, age, and monthly income were coded as what they were (continuous), sex was coded as male vs. female, the highest educational qualification was coded as below college vs. college, and the present legal marital status was coded as single vs. married vs. divorced/separated/widowed.A hierarchical regression was used to analyze how age might moderate the link between Big Five personality traits and SRH. Specifically, demographic variables including age, sex, monthly income, the highest educational qualification, and the present legal marital status and personality traits including Neuroticism, Agreeableness, Openness, Conscientiousness, and Extraversion with age by personality traits interactions were taken into the hierarchical regression models as predictors with SRH health. Then participants were put into three groups based on their age including young (mean age −1 SD), mean-age, and older (mean age +1 SD) groups. Three multiple regressions were then conducted for each age group by taking demographics and personality traits as predictors and SRH as the predicted variable. All analyses were conducted on MATLAB 2018a.b = −0.001, p < 0.001, 95% CI ), Openness , and Conscientiousness  interactions after controlling for demographic covariates  was negatively related to SRH whereas Agreeableness , Conscientiousness  and Extraversion  were positively related to SRH among young people (mean age −1 SD). However, among mean age adults, Neuroticism  was negatively related to SRH whereas Openness  and Conscientiousness  were positively related to SRH. Finally, Neuroticism  was negatively related to SRH whereas Openness  and Conscientiousness  were positively related to SRH in older adults , middle-aged >39 and <60), and older people (>59). Similarly, analysis steps were taken but this time age was coded as categorical  rather than continuous before running the same hierarchical regression and multiple regressions. Results were still pretty similar , 6.0, and olThe aim of the current study was to test how age may moderate the link between personality traits and SRH in a large representative sample from the United Kingdom. Results from the current study showed that age significantly moderates the associations between Agreeableness, Openness, and Conscientiousness and SRH after controlling for demographic covariates. Specifically, Neuroticism was negatively related to SRH whereas Agreeableness, Conscientiousness, and Extraversion were positively related to SRH among young people. However, among mean-age and older adults, Neuroticism was negatively related to SRH whereas Openness and Conscientiousness were positively related to SRH.Neuroticism was consistently negatively associated with SRH in all age groups, which seems to be largely consistent with previous studies. A direct explanation for the negative association between Neuroticism and SRH is that neurotic individuals tend to have worse health, which can then be reflected in SRH. Moreover, Neuroticism is also associated with slower walking speed e.g., ,b and biConscientiousness was positively related to SRH in all age groups. Conscientiousness tends to be positively associated with health-promoting behaviors such as more physical activities  but negaThe current study found that Agreeableness is positively related to SRH in young people but not in young or older adults. The positive association between Agreeableness and SRH seems to be consistent with previous studies . The posFinally, Openness was only positively related to SRH in middle-aged and older adults. Indeed, recent studies have found that Openness is associated with more physical activities , better Despite the strengths of the current study including a large sample size and well-controlled socioeconomic characteristics, there are some limitations of the current study as well. First, the current study relied on a cross-sectional design, which cannot establish causality. Second, the current study was based on self-reported measures, which cannot avoid self-reporting bias. Specifically, since both personality and health are subjective evaluations, which mean that they share the method. Thus, they are not entirely independent entities and the observed relationships between them can be produced by the artifact of the method. Finally, the current study focused on participants from the United Kingdom, which may make it generate to other cultures/countries e.g., . Future Taken together, the current study found that age significantly moderates the associations between Agreeableness, Openness, and Conscientiousness and SRH after controlling for demographic covariates. Specifically, Neuroticism was negatively related to SRH whereas Agreeableness, Conscientiousness, and Extraversion were positively related to SRH among young people. However, among mean-age and older adults, Neuroticism was negatively related to SRH whereas Openness and Conscientiousness were positively related to SRH. The current study implies that personality traits relate to SRH differently at different ages. Thus, studies regarding the associations between personality traits and SRH must take the interactions between age and personality traits into account.https://www.understandingsociety.ac.uk.Publicly available datasets were analyzed in this study. This data can be found here: The studies involving human participants were reviewed and approved by the University of Essex. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.The author confirms being the sole contributor of this work and has approved it for publication.


MIB2-134aa is completely consistent with the amino acid sequence of the two domains of host gene MIB2 protein; host gene MIB2 can target TRAF6 through the two domains and inhibit the innate immune response by promoting the ubiquitination degradation of the K11-link of TRAF6, MIB2-134aa also targets TRAF6 through these same domains. Interestingly, MIB2-134aa greatly reduced the degradation of TRAF6 by its host gene MIB2. More importantly, we found that circRNA therapy of circMIB2 can significantly inhibit the colonization of Vibrio anguillarum in zebrafish, and it provides a new direction for the treatment of pathogenic diseases of fish.The mRNA therapy is widely used in the treatment of diseases due to its efficient characteristics, and the COVID-19 vaccine is the application of mRNA therapy. However, due to the instability of mRNA, mRNA vaccines often need lots of modifications to ensure its stability. Recent research shows that circRNA with stable RNA structure can encode protein, which provides a new direction for mRNA therapy. Here, we discovered a novel circRNA (circMIB2) derived from E3 ubiquitin-protein ligase MIB2 (MIB2) gene in lower vertebrate fish, which can translate into a 134 amino acid protein (MIB2-134aa) through m RNA therapy is an effective method to treat or prevent diseases based on RNA molecules and mainly includes four strategies. The first strategy is that it can target and bind target nucleic acid molecules through single-stranded antisense RNA. For example, they can regulate the splicing of precursor mRNA and induce the degradation of target mRNA through degradation mediated by RNase H or block the translation of mRNA to protein , 2. The 7G cap structure and 3’ poly (A) tail structure, circRNA is a covalently closed single-stranded RNA molecule  = 1.0 M and 37 °C by the UNAfold Web Server. According to the prediction results, the optimal cyclization site of circMIB2 was determined, and the complete linear RNA of circMIB2 (L-circMIB2) was synthesized from this cyclization site. For ligation experiments, a phosphate was in advance introduced to the 5’-position of L-circMIB2 by using T4 polynucleotide kinase (Beyotime) and T4 RNA Ligase 2 (Beyotime) . FinallyThe RNA interferences for circMIB2 are as follows: si-circMIB2-1 sequence was 5’-CACACUCCCAGCCUCACCCTT-3’. And the si-circMIB2-2 sequence was 5’-CUCCCAGCCUCACCCCUGATT-3; The scrambled control RNA sequences were 5’- GGCACACUCCCAGCCAACAAATT-3’. The RNA interference for MIB2 is as follows: si-MIB2 sequence was 5’- UGUUACAUGAACAACAAGCTT-3’. The scrambled control RNA sequences were 5’- UUCUCCGAACGUGUCACGUTT-3’.Transient transfection of cells with siRNA was performed in 24-well plates using Lipofectamine RNAiMAX (Invitrogen), and cells were transfected with DNA plasmids or synthetic circRNA were performed using Lipofectamine 3000 (Invitrogen) according to the manufacturer’s instructions. For functional analyses, the plasmid (500 ng per well) or control vector (500 ng per well), the circRNA (500 ng per well) or circ-NC (500 ng per well), and siRNA (100 nM) were transfected into cells in culture medium and then harvested for further detection.Danio rerio (4 months old) were maintained at 28 °C in tanks. Mix the synthesized circRNA and Lipofectamine 3000 (Invitrogen), and then inject the mixture into the abdominal cavity of zebrafish (10 μg). After 24 h of injection of circRNA, the experiment of V. anguillarum infection was started. The zebrafish in the control group was injected with 20 μl of normal saline intraperitoneally, and the zebrafish in the infection group was injected with 20 μl of V. anguillarum (1 × 108 CFU/ml).Zebrafish, Add the liver, spleen, kidney or gill of the above zebrafish into sterile centrifuge tubes, add sterile physiological saline and steel ball to shake and break. Then the broken tissue solution is coated on the plate, and the plate is incubated at 37 °C for 12 h.For the isolation and purification of both cytoplasmic and nuclear RNA from MSpC and MIC cells, the Cytoplasmic & Nuclear RNA Purification Kit has been used according to the manufacturer’s instructions (Norgen Biotek). The total RNA of tissue or cell samples was isolated with TRIzol Reagent (Invitrogen), and the cDNA was synthesized using the FastQuant RT Kit (Tiangen). The expression patterns of each gene were performed by using SYBR Premix Ex TaqTM (Takara). GAPDH was employed as endogenous controls for mRNA, respectively. Primer sequences are displayed in Supplementary Table Renilla luciferase plasmid, negative controls. At 48 h post-transfection, the cells were lysed for reporter activity using the dual-luciferase reporter assay system (Promega). All the luciferase activity values were achieved against the renilla luciferase control. Ratios of renilla luciferase readings to firefly luciferase readings were taken for each experiment, and triplicates were averaged.To determine the functional regulation of MIB2-134aa, cells were co-transfected the plasmid of STING, MAVS, TRIF, or TRAF6 and circMIB2 or circMIB2-ATG-mut, together with IRF3, ISRE, NF-κB, and IL-1β luciferase reporter gene plasmids, phRL-TK TM ECL (Advansta). The digital imaging was performed with a cold CCD camera.A polyclonal antibody against the MIB2-134aa protein produced by circMIB2 was obtained by inoculating rabbits (GenScript). Cellular and tissue lysates were generated by using 1 × SDS-PAGE loading buffer. Proteins were extracted from cells and measured with the BCA Protein Assay kit (Vazyme), then subjected to SDS-PAGE (8%) gel and transferred to PVDF (Millipore) membranes by semidry blotting (Bio-Rad Trans Blot Turbo System). The antibody against TRAF6 was diluted at 1:500 (Abcam); The antibody against MIB2 was diluted at 1:500 (Abcam); The antibody against MIB2-134aa was diluted at 1:200 (GenScript); anti-Flag, anti-HA, anti-Myc, and anti-Tubulin monoclonal antibody were diluted at 1:2000 (Sigma); and HRP-conjugated anti-rabbit IgG or anti-mouse IgG (Abbkine) at 1:5000. The immunoreactive proteins were detected by using WesternBright2 plate overnight and then were co-transfected with 5 μg indicated plasmids, and the specific steps were performed as described [For immunoprecipitation (IP) experiments, MSpC cells, EPC cells were seeded onto a 10-cmescribed .6A-specific antibody (Germany) in IP buffer. Then the IP RNA was reverse-transcribed to create the cDNA by SuperScript™ II Reverse Transcriptase (Invitrogen). RNA was extracted from the remaining beads, and qPCR was used to evaluate the expression levels of circMIB2.Total RNA was isolated using TRIzol reagent. Then the cleaved RNA fragments were incubated for 2 h at 4 °C with m7) transfected with YTHDF1 and YTHDF3. After 48 h transfection, the MSpC cells were used in RIP assays via the Magna RIPTM RNA-Binding Protein Immunoprecipitation Kit (Millipore) and an anti-flag antibody following the manufacturer’s protocol.RIP experiments were performed by using the Magna RIP RNA-Binding Protein Immunoprecipitation Kit (Millipore) following the manufacturer’s protocol. The RIP assay was also conducted in MSpC cells (~2.0 × 106A mutant of circMIB2 (MS2-circMIB2-m6A-mut) and circMIB2 (MS2-circMIB2) with MS2 sequence. The MS2-RNA pulldown assay was conducted in MSpC cells transfected with YTHDF1, YTHDF3, pMS2-GFP (Addgene) plasmids and MS2-circMIB2, MS2-circMIB2-m6A-mut circRNA, and the specific steps were performed as described [We first synthesized the circRNA of the mescribed .CircMIB2-134aa proteins were separated on SDS-PAGE gels, and bands were manually excised from the gel and digested with sequencing-grade trypsin (Promega). The digested proteins were analyzed using a QExactive mass spectrometer (Thermo). Fragment spectra were analyzed using the National Center for Biotechnology Information nonredundant protein database with Mascot (Matrix Science) .The RNA FISH assay was performed using Cy3-labeled circMIB2 probe (5’-Cy3-AACAGATCAGGGGTGAGGCTGGGAGTGTG-3’) and FAM-labeled MIB2 probe (5’-Cy3-CATCTCCTCGGTCAGTGATTCTA-3’). Subsequently, the Fluorescent In Situ Hybridization test kit (GENESEED) was used for detection in MSpC and MIC cells.−∆∆CT method, and comparisons between groups were analyzed by one-way analysis of variance (ANOVA) followed by Duncan’s multiple comparison tests [p < 0.05 was considered significant.Data are expressed as the mean ± SE from at least three independent triplicated experiments. Student’s t-test was used to evaluate the data. The relative gene expression data was acquired using the 2on tests . A valueSupplementary Figure LegendsSupplementary Figure 1Supplementary Figure 2Supplementary Table 1Original Data File-1Original Data File-2


RNA vaccines, including conventional messenger RNA (mRNA) vaccines, circular RNA (circRNA) vaccines, and self-amplifying RNA (saRNA) vaccines, have ushered in a promising future and revolutionized vaccine development. The success of mRNA vaccines in combating the COVID-19 pandemic caused by the SARS-CoV-2 virus that emerged in 2019 has highlighted the potential of RNA vaccines. These vaccines possess several advantages, such as high efficacy, adaptability, simplicity in antigen design, and the ability to induce both humoral and cellular immunity. They also offer rapid and cost-effective manufacturing, flexibility to target emerging or mutant pathogens and a potential approach for clearing immunotolerant microbes by targeting bacterial or parasitic survival mechanisms. The self-adjuvant effect of mRNA-lipid nanoparticle (LNP) formulations or circular RNA further enhances the potential of RNA vaccines. However, some challenges need to be addressed. These include the technology’s immaturity, high research expenses, limited duration of antibody response, mRNA instability, low efficiency of circRNA cyclization, and the production of double-stranded RNA as a side product. These factors hinder the widespread adoption and utilization of RNA vaccines, particularly in developing countries. This review provides a comprehensive overview of mRNA, circRNA, and saRNA vaccines for infectious diseases while also discussing their development, current applications, and challenges. Over the past few decades, mRNA vaccine development has achieved significant milestones since the discovery of mRNA in 1961 ,,98,97,98RNA vaccines have emerged as a highly sophisticated and effective vaccine technology, but they still face two key challenges that limit their effectiveness. Firstly, negatively charged RNA has difficulty crossing the cell membrane structure, and secondly, RNA, especially mRNA, is intrinsically unstable and susceptible to degradation by ribonucleases in the circulation. To address these challenges, drug delivery systems have been developed to shield and protect the RNA. One of the most successful RNA delivery approaches is the lipid nanoparticle (LNP), which has achieved great success during the SARS-CoV-2 pandemic. LNP is composed of four main components: an ionizable or cationic lipid to neutralize the RNA’s negative charge, a zwitterionic lipid that has minimal electrostatic interaction with blood cells’ membranes, cholesterol to stabilize the LNP’s membrane, and PEG, which affects particle size and colloidal stability (as shown in Lipid nanoparticle (LNP) is currently the most widely used drug delivery system for RNA vaccines. However, there are significant opportunities for improvement. First, thermostability remains a challenge as these vaccines require extremely low transportation and storage temperatures. Second, the inflammatory nature of LNP components can lead to undesirable side effects or even fatalities with different administration routes . Recent Extracellular vesicles (EVs) have emerged as a promising natural RNA delivery carrier due to their superior biocompatibility. These nanosized structures, enclosed by phospholipid bilayers, are released by mammalian and bacterial cells and contain proteins, lipids, and nucleic acids. EVs play a crucial role in cell-to-cell communication by delivering functional molecules. Mammalian EVs can be categorized into exosomes, microvesicles, and apoptotic bodies based on their biogenesis routes . ExosomeGenetic engineering presents a promising approach for loading RNA cargo into the lumen of extracellular vesicles (EVs). Hung et al. introduced the ‘TAMEL approach (targeted and modular EV loading approach)’ to achieve dynamic mRNA loading. This method involves fusing the RNA-binding protein MS2 bacteriophage coat protein to the surface EV-enriched protein (EEP) LAMP2b, enabling high loading efficiency. Their study revealed that smaller RNAs (500 kb) had higher loading efficiency compared to longer RNAs (~1.8 kb). Additionally, the choice of EEP significantly impacted the loading efficiency, with VSVG showing a 42-fold enrichment of cargo RNA in vesicles compared to Hspa8, which exhibited minimal enrichment . AnotherBacterial extracellular vesicles (EVs) display a diverse range of structures and compositions. Among them, outer membrane vesicles (OMVs) are shed from both Gram-negative and positive bacterial organisms c. OMVs cProtamine is a naturally occurring protein derived from salmon spermatozoa, containing a significant number of positively charged L-arginine amino acids, making it ideal for condensing and stabilizing negatively charged mRNA . StudiesMycobacterium tuberculosis’, ‘HIV’, and ‘Malaria’. To further advance the field, attention should be directed towards addressing potential issues in manufacturing and RNA delivery systems, including concerns related to the toxicity of lipid components, and the need for low-temperature storage and transportation. With continued research and investment in this thriving area, these challenges are likely to be overcome in the near future.RNA vaccines have emerged as a powerful tool in the fight against the SARS-CoV-2 pandemic, demonstrating significant advantages such as large-scale manufacturing capacity and reasonable cost, making them accessible to developing and underdeveloped countries, and creating a positive global impact. Different types of RNA, including conventional mRNA, self-amplifying mRNA, and circular RNA, offer distinct advantages and challenges. Conventional mRNA is safe for administration and easily manufactured via in vitro transcription (IVT); however, it may not always elicit the desired immune response, necessitating the use of an effective delivery system. Self-amplifying mRNA addresses this limitation by enabling sufficient antigen expression through its self-amplifying process, but the use of alphavirus elements may raise safety concerns and induce unwanted immune responses. Circular RNA shows promise due to its inherent stability, resulting in a longer RNA half-life and prolonged antigen expression without requiring a delivery system. However, its complex manufacturing process and limited RNA circulation pose challenges. Additionally, in some circumstances, RNA vaccines may be difficult to implement, as in resource-limited or low-income areas, poverty creates cost barriers for those regions using this advanced technology. RNA vaccines can be more expensive to produce and distribute if they require lyophilization or cold-chain transport to be stabilized. Despite these challenges, mRNA vaccines have achieved significant milestones not only in the SARS-CoV-2 pandemic but also in combating other pathogens, as evidenced by promising preclinical and clinical data for mRNA vaccines targeting flaviviruses, VZV, RSV, and influenza. Furthermore, ongoing efforts are directed toward developing mRNA vaccines for obstinate infectious diseases such as ‘


We also determine the NMR solution structures of RBM39’s tandem RNA recognition motifs (RRM1 and RRM2) bound to their respective RNA targets, revealing how RRM1 recognises RNA stem loops whereas RRM2 binds specifically to single-stranded N(G/U)NUUUG. Our results support a model where RRM2 selects the 3’-splice site of a poison exon and the RRM3 and RS domain stabilise the U2 snRNP at the branchpoint. Our work provides molecular insights into RBM39-dependent 3’-splice site selection and constitutes a solid basis to design alternative anti-cancer therapies.Pharmacologic depletion of RNA-binding motif 39 (RBM39) using aryl sulfonamides represents a promising anti-cancer therapy but requires high levels of the adaptor protein DCAF15. Consequently, novel approaches to deplete RBM39 in an DCAF15-independent manner are required. Here, we uncover that RBM39 autoregulates via the inclusion of a poison exon into its own pre-mRNA and identify the  RBM39 is an essential splicing factor for several cancer cells. Here, the authors described how RBM39 selects RNA at atomic level and autoregulates at the mRNA level by selecting the 3’-splice site of a poison exon. Understanding how aberrant splicing patterns drive tumorigenesis and the survival of cancer cells is crucial for the development of novel therapeutic approaches4.Alternative pre-mRNA splicing is a crucial step of gene expression that not only increases the coding capacity of the genome but also regulates the transcriptional output of genes. Consequently, non-physiological splicing patterns contribute significantly to diseases, in particular to cancer malignancy7 and is essential for the survival of many cancer cells including Acute Myeloid Leukaemia (AML) cells8. In AML, RBM39 sustains a network of RNA-binding proteins by splicing of their pre-mRNAs and ensures the correct processing of pre-mRNAs encoding Homeobox protein A9 targets11. As a consequence, anticancer drugs coined the aryl sulfonamides, that specifically induce the targeted degradation of RBM39, trigger the death of cancer cell lines derived from hematopoietic and myeloid lineages14 but also cancer stem cells15 and recently, showed exceptional responses in the treatment of high-risk neuroblastoma models17. The small molecule acts as a molecular glue between RBM39 and the DCAF15-CRL4 E3 ubiquitin ligase to induce proteasome-mediated degradation of RBM39 which in turn leads to cancer cell death20. Furthermore, the targeted degradation of RBM39 generates bona fide neoantigens and augments checkpoint immunotherapy21. However, a major caveat of this innovative approach is the dependence on DCAF15, the adaptor protein acting at the interface between the aryl sulfonamide and the E3 ubiquitin ligase activity22. Hence, the efficiency of this treatment correlates with DCAF15 expression levels. Accordingly, the control of RBM39 homoeostasis is important for cancer cell survival, and therefore the identification of alternative approaches to lower the intracellular concentration of RBM39 independently of DCAF15 could be beneficial for cancer treatment.The RNA-binding protein called RNA Binding Motif 39 (RBM39) is overexpressed in several types of cancer23  experiments suggest that RBM39 has a different RNA-binding selectivity, although the proposed sequence motifs show little overlap32. Hence, the RNA-binding specificity of RBM39 remains to be addressed experimentally.RBM39 is a ubiquitously expressed SR-like protein and is homologous to U2AF2cis-acting sequence elements in the RBM39 pre-mRNA. Furthermore, we decipher the molecular basis of RBM39-RNA recognition by its RRM1 and RRM2. Our data bring molecular insights into RBM39-dependent 3′-splice site selection by this cancer-associated splicing factor.To decipher the role of RBM39 in RNA metabolism, we combined functional and structural approaches. Our data revealed that RBM39 actively participates in splice site selection and autoregulates through a negative feedback loop by enhancing the inclusion of a poison exon in its own pre-mRNA. This splicing regulation involves all three RRM domains as well as the RS domain along with two 33 and computed meta p-values comparing both Ctrl versus KD and rescue versus KD34. Using this approach, we found 7,233 mRNAs whose steady-state levels were affected by RBM39  or RBM39 siRNAs (RBM39 KD) and rescued the RBM39 KD by co-transfecting RNAi-resistant FLAG-RBM39. The principal component analysis confirmed a strong clustering of the three biological replicates  and established direct hydrogen bonds with the backbone of the C-terminal extremity of the protein  using FLAG-tagged RBM39 or mutants where either RNA-binding by RRM1 or RRM2 or the UHM-ULM interactions of RRM3 were disrupted by point mutations  and measured the levels of co-precipitating mRNA by RT-qPCR. All bait proteins were purified with comparable efficiencies and have rich protein interactomes. Compared to a no-transfection control (NTC) condition, the RBM39-regulated mRNAs MBD1, PAPOLA and TPP1 as well as the housekeeping mRNAs GAPDH, HSP90 and TUBA1A were significantly enriched by FLAG-RBM39. However, we did not observe apparent differences between the mutant constructs, suggesting that RBM39 interacts with mRNPs in a redundant manner involving both protein–protein as well as protein–RNA contacts  which represent major hubs for the communication with splicing factors47. Interestingly, similar ILV methyl chemical shifts perturbations (CSP) of RRM12 were observed when the protein was titrated with isolated U1 snRNA SL3 or SL4  motifs that were previously isolated by CLIPSL4 Fig. . To testnce Fig. . Using i15N-labelled RRM1, we observed amide CSPs in an unusually large part of the RRM which covers β1 (RNP2), the β1−α1 loop (near A161), the β2-β3 loop (near R192), β3 (RNP2), and the β4-β5 loop (near G220) . The interactions with U105 and G106 are only mediated by stacking interactions against the aromatic rings of F156 and Y198 while A104 inserts into a cavity along β5 and interacts directly with the side chain of Q159  Fig. . On the 20) Fig. . The sol20) Fig. . The ens159 Fig. . The mai159 Fig. . There aIn order to test the functional relevance of our protein–RNA complex structures, we mutated key residues at the protein/RNA interfaces and tested the ability of mutants to rescue RBM39 KD on the three RBM39-dependent intron retention events. We designed a mutant altering RNA-binding by RRM1 on the β-sheet surface , and one mutant altering the contact from the basic residues of the loop β2-β3 . We also prepared an RBM39 mutant altering the RNA-binding interfaces of RRM2 , another altering the interaction of RRM3 with U2 snRNP  and finally a mutant combining mutations of both RRM2 and RRM3 (mRRM2&3) Fig. . All thecis-acting RNA elements responsible for RBM39-dependent splicing, we first inserted the poison exon and approximately 100 nucleotides of its flanking intronic regions into the human β-globin (HBB) gene between exons 2 and 3. In this heterologous context, the RBM39-dependency of poison exon inclusion was preserved, indicating that the cis regulatory elements are located in proximity of the poison exon and its flanking regions  and thus activates poison exon inclusion in an RBM39-independent manner. Nevertheless, RBM39 KD completely abolished poison exon inclusion suggesting that BS2 is not the primary binding site for RBM39. In agreement, the stabilisation of SLi (OPT-SLi) reduced poison exon inclusion  in the adjacent major groove NUUUG-3′ motifs. When compared to the RRMs of FUS and RBMY, which are also specific for RNA stem loopsRBM39 gene. Such a negative feedback loop mechanism is commonly observed in autoregulation of key splicing or transcription regulators54, allowing a precise control of critical gene expression regulator homoeostasis. Our experimental data reveal that the inclusion of the poison exon is controlled by two distinct mechanisms: one RBM39-dependent and one RBM39-independent.Among the RBM39-dependent cassette exons, a PTC-containing exon-inducing mRNA decay was identified in the 25. Our data also support an important role of the RS domain in stabilising the association between RBM39 and U2 snRNP. A possible explanation for the increase in baseline exon inclusion is that the mutated 3′-splice site that originates from a constitutive exon in the β-globin gene is recognised more efficiently by U2AF2 which may functionally substitute for RBM39 by recruiting U2 snRNP NUUUG-3′ consensus motif of RRM2 inferred from our structural studies, we propose that RBM39 selects the 3′-splice site using RRM2 and stabilises the U2 snRNP on the branchpoint by interacting with ULM motifs in SF3b155 via its RRM3 (UHM) domain. In principle, RBM39 could also recruit the ULM-containing proteins U2AF2 or SF1 to the 3′-splice site; however, the affinity of RBM39 for SF3b155 is at least 20-fold higher compared to these other proteinsSMN2 exon 755 or Map/Tau exon 1056. However, this cis-acting RNA element modulates poison exon splicing in an RBM39-independent manner. Upon mutation of the inhibitory stem loop that releases the 5′-splice site, we observed an increase baseline exon inclusion that was reset by RBM39 depletion  acts as a repressive element by sequestering the 5′-splice site of the poison exon. Similar structures have been previously described to regulate alternative splicing of cassette exons such as ion Fig. . Our fun22 and in high-risk glioblastomas cases16, response to aryl sulfonamides treatment correlated with high expression level of DCAF15. This observation suggests that the identification of alternative approaches triggering the degradation of RBM39 independently of DCAF15 could be beneficial for cancer treatments. By deciphering the molecular mechanisms governing the homoeostasis of RBM39, we provide important data to manipulate this negative feedback loop mechanism and to trigger the depletion of RBM39 independently of DCAF15. By pushing the splicing equilibrium towards the constitutive inclusion of the poison exon, the expression of RBM39 could be shut down, resulting in cancer cell death in a DCAF15-independent manner. The manipulation of the autoregulation mechanism using RNA therapeutics could represent a novel strategy to deplete RBM39 from cancer cells. A similar strategy was recently used to lower the level of huntingtin mRNA and develop an innovative therapeutic approach against Huntington’s disease57. The rapid expansion of the field of RNA therapeutics correcting splicing has provided innovative therapeutic strategies for inherited diseases63. In the future, it could also benefit cancer therapy.In AML2.HeLa cells were grown in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% foetal calf serum (FCS), penicillin (100 IU/ml) and streptomycin (100 μg/ml) (DMEM+/+) at 37 °C and 5% COE. coli codon optimised ORF (GeneScript) into pET26bII between the NdeI-XhoI site. RRM1 was subcloned using the sc1 and sc2 oligonucleotides; RRM2 was subcloned using the sc3 and sc4 oligonucleotides and RRM12 was subcloned using the sc1 and sc4 oligonucleotides. Mutagenesis was performed by following the quick-change protocol. Plasmids allowing the expression of protein mutants  were designed into pET26b+ and purchased (Genscript). pcDNA3.1-FLAG-GSG15-RBM39 was created by cloning codon optimised RBM39 (GeneArt) into the BamHI and NotI sites of pcDNA3.1-FLAG-GSG15 . To generate pcDNA3.1-FLAG-GSG15-RBM39-deltaRRM1 and deltaRRM2, the optimised coding sequences of RBM39 missing amino acids 153–230 (RRM1) or amino acids 250–330 (RRM2) were ordered from GeneArt, amplified using the primers dj217 and dj218 and inserted into the BamHI and NotI sites of pcDNA3.1-FLAG-GSG15. To create pcDNA3.1-FLAG-GSG15-RBM39-deltaRRM3, the coding region for RBM39 amino acids 1–445 was amplified from pcDNA3.1-FLAG-GSG15-RBM39 with dj217 and mdr835 and inserted into the BamHI and NotI sites of pcDNA3.1-FLAG-GSG15. To generate pcDNA3.1-FLAG-GSG15-deltaRS-RBM39-SV40NLS, the region encompassing amino acids 146–530 was amplified using dj798 and dj799 and inserted into the BamHI and NotI sites of pcDNA3.1-FLAG-GSG15. The point mutations to disrupt RNA-binding and UHM-ULM interactions were introduced by Quick-change mutagenesis of pcDNA3.1-FLAG-GSG15-RBM39. RRM1 was mutated using the primers mdr842 (Y198A), mdr843 (F156A), mdr866 (R192A), whereas RRM2 was mutated using mdr867 , mdr864 (Y253A) and mdr865 (F295A). RRM3 was mutated using mdr841 . The pd2-N1-RBM39-minigene was generated as follows: the region spanning exon 1 to 4 of the endogenous RBM39 gene was amplified from human fibroblast gDNA using the primers dj282 and dj283 and inserted into the SalI and NotI sites of pd2-EGFP-N1 (Clonetech). Subsequently, a cryptic splice site in intron 3 was destroyed by QuikChange mutagenesis using the primer mdr848. Pd2-N1-RBM39 deltaBS1 was generated by Quikchange mutagenesis using the primer dj779. To create the pd2-N1-RBM39-optSLi plasmid, the region spanning RBM39 exons 2 – 3 with the desired point mutations was ordered by gene synthesis and cloned into the EcoRV and Not1 sites of the pd2-EGFP-N1-RBM39 minigene. To generate the plasmids pd2-N1-RBM39-deltaBS2 and pd2-N1-RBM39-HBB-3′ss, the region spanning RBM39 exons 2 and 3 between the BstX1 and EcoRV sites containing the desired mutations was ordered by gene synthesis and cloned into the pd2-N1-RBM39 minigene. To create the RBD-only FLAG-RBM39 constructs for RNA/RNP immunoprecipitation, the RNA-binding region of RBM39 was amplified from the pcDNA3.1-FLAG-GSG15-RBM39  expression vectors using dj734 and dj735 and cloned into the BamHI and NotI sites pcDNA3.1-FLAG-GSG15. For the RRM1&2 double mutant, the regions encoding RRM1 and RRM2 were first amplified from pcDNA3.1-FLAG-GSG15-RBM39 (mutRRM1 and mutRRM2) using dj734/dj737 (RRM1) and dj736/dj735 (RRM2), and the resulting PCR fragments where then fused by a second round of PCR amplification with dj734/dj735 before cloning into the BamHI and NotI sites of pcDNA3.1-FLAG-GSG15. To create the pEBFP-c1-HBB minigene with Hind3 and Sal1 restriction sites in intron 2 to facilitate the subsequent introduction of alternative exons, the regions of HBB exon 1 to intron 2 and HBB intron 2 to exon 3 were amplified from fibroblast genomic DNA using the primers dj714, dj715, dj716 and dj717. After fusion of the two fragments by PCR with dj714 and dj717, the HBB gene was inserted into the Bgl2 and Xba1 sites of pEBFP-c1. To generate the pEBFP-c1-HBB-RBM39 WT and deltaBS1 minigene, the region containing RBM39 exon 2b was amplified from pd2-N1-RBM39 minigene WT or deltaBS1 using dj777 and dj778 and cloned into the Hind3 and Sal1 sites of the pEBFP-c1-HBB minigene. To create the pEBFP-c1-HBB RBM39 HBB 3′ss and mutBS1 plasmids, the region spanning RBM39 exon 2b with the desired point mutations was ordered by gene synthesis and cloned into the Hind3 and Sal1 sites of the pEBFP-c1-HBB minigene.Plasmids allowing the expression of RBM39 RRM1, RBM39 RRM2 and RBM39 RRM12 were prepared by subcloning the corresponding E. coli BL21 DE3. 15N and 13C uniform isotopic labelling was performed in M9 medium complemented by 1 g of 15NH4Cl and/or 2 g of 13C glucose. ILV methyl labelling was performed in M9-D2O medium in presence of 15N-labelled ammonium chloride, unlabelled glucose, 100 mg/L of alpha-ketobutyric acid  and 60 mg/L of alpha-ketoisovaleric acid . All the recombinant protein expressions were performed at 37 °C during 4 h in the presence of 1 mM IPTG. Cell lysis was performed using a microfluidizer  in buffer A  in the presence of DNAse I (10 μg/ml), lysozyme (10 μg/ml) and anti-protease tablets (Roche). The cell lysate was clarified by centrifugation  and loaded into an 5 ml HisTrap column (Cytiva) previously equilibrated in buffer A. Protein was eluted by a linear gradient of imidazole and dialysed at room temperature during 4 h in buffer B  in presence of thrombin . The resulting digest was loaded into an 5 ml HisTrap column previously equilibrated in buffer B and the flow through was collected, dialysed in buffer C . The sample was loaded on a 5 ml HiTrap SP FF column (Cytiva) and eluted with a linear gradient of buffer D . RRM2 and RRM12 were dialysed in buffer E  and were further purified by size exclusion chromatography  in buffer E. RRM1 was dialysed in buffer F  and was further purified by size exclusion chromatography in buffer F . RRM3 and mRRM3 were expressed and purified as previously described25. All the protein mutants were prepared using similar protocols than wild-type proteins. Recombinant protein purification was monitored by SDS-PAGE.Expression of RRM1, RRM2 and RRM12 were performed in 2, 6 mM of each NTP, 4 mM GMP, 2.5 μM dsDNA template and 1.7 μM T7 RNA Polymerase in a transcription buffer containing 40 mM Tris-HCl pH 8.0, 1 mM spermidine, 0.01% Triton X-100 and 5 mM DTT. 1 U/mL pyrophosphatase was added to reduce magnesium phosphate accumulation. After 4 h, the reaction was stopped by adding 100 mM EDTA pH 8.0. The mixture was then centrifuged  and filtered with 0.22 µm filter. The transcription mixture was then loaded into a preparative anion exchange column mounted on an HPLC system allowing the purification of RNA in denaturing conditions . The RNA was eluted with a gradient of salt, butanol-extracted, refolded and lyophilised. RNA production and purification were monitored by Urea-PAGE. Short RNA fragments were purchased (Horizon).The RNA U1 snRNA SL3, SL4 and RBMY aptamers were produced by T7-driven in vitro transcription using homemade T7 RNA polymerase. Transcriptions were performed using ssDNA templates (Supplementary Data HeLa cells were grown to 80% confluency in 6-well plates and transfected with 300 ng pcDNA3.1-FLAG-RBM39 constructs using Lipofectamine2000 (Invitrogen). On the following day, 40,000 HeLa cells were re-seeded in 8-well chambers (Bioswisstec AG) and fixed after 24 h with 4% PFA for 30 min. After three washes with TBS, the cells were permeabilised and blocked using 1x TBS, 0.5% (v/v) Triton-X-100, 6% BSA at room temperature for 1 h. Ms anti-FLAG M2 antibodies (Sigma) were diluted 1:200 in TBS+/+  Triton-X-100, 6% BSA) and incubated with the cells overnight at 4 °C. After 3 × 5 min washes with TBS+/+, the secondary antibody  was diluted in TBS+/+ and bound to the primary antibody at 37 °C for 1.5 h followed by incubation at room temperature for 30 min. Then, the slides were washed 5 times with 1x TBS and mounted with Vectashield HardSet mounting medium containing DAPI (Vectorlabs). Images were acquired with a non-confocal fluorescence microscope  using the Leica Application Suite software (LAS-X) or with a non-confocal Eclipse Ti-2 epifluorescence microscope (Nikon) using the NIS-Elements AR software (Ver 5.01) using a 60x/1.4 NA oil immersion lens. For printing, brightness and contrast of the pictures were linearly enhanced.2 f.c., 416.6 U/ml Cyanase (Ribosolutions Inc) and 333 μg/ml RNAse A (Sigma).120 μl Protein G Dynabeads (Life Technologies) per immunoprecipitation were washed three times with TBS supplemented with 0.05% NP-40 (IGEPAL CA-630) and incubated in 600 μl total volume of TBS-0.05% NP-40 with 15 μg of mouse anti-SmB/B’ (Y12), mouse anti-U1A , rabbit anti-RBM39 , mouse IgG , or rabbit IgG  head over tail for 1.5 h or supplemented with 1 mg/ml BSA overnight at 4 °C. The beads were subsequently washed three times with 1 ml TBS-0.05% NP-40 and resuspended in 600 μl TBS-0.05% NP-40 supplemented with 1 x Halt Protease Inhibitor Cocktail (Thermo Scientific) or 1x Halt Protease/Phosphatase Inhibitor Cocktail. For RNAse-free IP conditions TBS-0.05% NP-40 was supplemented with 1 U/ul RNAse inhibitor . For nuclease treated samples, the immunoprecipitations were supplemented with 1.5 mM MgClg. 30 µl of cleared nuclear extract per 15 μg of antibody were added to the protein G–antibody complexes and incubated for 1.5 h head of tail at 4 °C. Subsequently, the beads were washed three times with TBS-0.1% NP-40, followed by a final wash with 5 min head over tail incubation. With the final wash, the beads were transferred to new tubes, wash buffer was removed, and the beads were resuspended in 60 μl of 2× LDS‐loading buffer, boiled for 10 min at 70 °C and loaded on a 4–12% NuPAGE gel. The proteins were transferred to nitrocellulose membranes using the iBlot Gel Transfer Device (Life Technologies). Membranes were blocked with 5% non-fat dry milk in TBS supplemented 0.1% with Tween or with SeaBlock (Life Technologies) for 1 h and incubated with the primary antibodies rabbit anti-U1C , rabbit anti-RBM39 , mouse anti-U1A , mouse anti-SF3A3  overnight at 4 °C. After five washes with TBS-Tween, the membranes were incubated with donkey anti-mouse IRDye800CW  or donkey anti-rabbit IRDye800CW  in TBS-Tween-Milk for 1.5 h followed by analysis with the Odyssey Infrared Imaging System (Li-Cor).Hela nuclear extract  was thawed on ice, cleared by centrifugation for 5–10 min at 5000–10,0002 flasks and then transfected with 10 µg of the respective pcDNA3.1 expression vectors using Lipofectamine2000 according to the manufacturer’s protocol. 48 h post-transfection, the cells were harvested with trypsin/EDTA, and the pellets were shock frozen in liquid nitrogen for storage at −80 °C until use. To prepare cellular extracts, the pellets were dissolved in 5 mL Gentle Hypotonic Lysis Buffer  supplemented with 2x HALT protease inhibitor cocktail  and 0.5 U/µL RiboLock Rnase inhibitor  and incubated on ice for 10 min. After adjusting the NaCl concentration to 150 mM, the extracts were incubated for another 5 min on ice and then cleared by centrifugation at 15,000g and 4 °C for 15 min. Per IP, 100 µL FLAG-M2 matrix (200 µL of a 50% solution) were washed once with matrix preparation solution  once with 0.2 M Glycine pH 3.5 (to remove unconjugated FLAG antibodies) and again twice in matrix preparation solution. To keep protein and RNA input fractions, 50 μl of the cleared extracts were boiled with 2x LDS loading buffer and 200 μl were transferred to 1 ml TRIzol  supplemented with 0.14 M β-mercaptoethanol . Three times 1.5 mL of the extracts were then distributed to Eppendorf tubes containing FLAG-M2 matrix and incubated on a rotary wheel for 1.5 h at 4 °C. After washing the beads 5 times with HEPES NET-2 buffer , 1/5 of the beads was transferred into a separate Eppendorf tube and boiled in 2x LDS loading buffer, whereas the remaining beads were transferred to 1 ml TriZOL supplemented with 0.14 M β-mercaptoethanol. Proteins were analysed using 4–12% Bis-Tris polyacrylamide gels in MOPS buffer followed by Coomassie staining or western blot using the following antibodies: Mouse anti-FLAG M2 . RNA was isolated from TriReagent according to the manufacturer’s protocol and then reverse transcribed using the high-capacity RNA-to-cDNA kit  and analysed by RT-qPCR.For the RBM39 FLAG immunoprecipitation, HeLa cells were grown to 50% confluency in 300 cmITC experiments were performed on a VP-ITC instrument . Both partners were prepared in the NMR buffers (buffer E for RRM2 and RRM12 or buffer F for RRM1): the protein  was injected into a solution of ssRNA  by 40 injections of 6 μl every 350 s at 35 °C (for RRM12) or at 40 °C (for RRM1 and RRM12). Raw data were integrated, normalised for the molar concentration and analysed using Origin 7.0 according to a 1:1 binding model. ITC experiments performed with the mutants RRMs  were performed with a PEAQ-ITC . mRRM1.1, mRRM1.2 and mRRM2 titrations were performed in the same buffer than the wild-type proteins while the RRM3 titration were performed in Buffer G . The proteins were diluted at 300 μM in the syringe and the ligand at 30 μM in the cell. Data were analysed using the manufacturer’s software.5 cell equivalents were loaded on a 4–12% Bolt Bis-Tris protein gel and subjected to western blotting. Knockdown and rescue were analysed using rabbit anti-RBM39 , mouse anti-FLAG  and rabbit anti-Actin . RNA from each condition in triplicates was processed at the genomics core facility of the University of Bern using the Illumina TruSeq Stranded mRNA Library Prep Kit and sequenced on an Illumina HiSeq3000 platform using in 2 × 150 bp paired-end sequencing cycles. To assess the ability of RBM39 mutants to promote pre-mRNA splicing, we rescued siRNA-mediated knockdown of endogenous RBM39 by co-transfection of 300 ng RNAi-resistant pcDNA3-FLAG-RBM39 constructs using the protocol described above. To study the autoregulation of RBM39, 100 ng pd2-N1-RBM39-minigene were included in the second transfection at day 3. UPF1 knockdown experiments were performed according to the same timeline employing either 120 pmol Ctrl siRNA or 120 pmol UPF1 siRNA (5′-GAUGCAGUUCCGCUCCAUUdTdT-3′) along with 300 ng of empty pcDNA3 vector. Western blots were probed with rabbit anti-RBM39 , mouse anti-FLAG , goat anti-UPF1  and mouse anti-TUB1A2  to assess knockdown and rescue efficiencies. RNA isolated from TriReagent was Dnase treated using the Turbo DNA-free kit (Ambion) followed by reverse transcription using the high-capacity RNA-to-cDNA kit (Applied Biosystems). RT-PCR was carried out for 25 cycles using 2x KAPA Taq ready-mix (Kapa Biosystems) in 50 µl reactions containing 80 ng cDNA and 400 nM primers each, following the manufacturer’s manual. qPCR was performed using the 2x MESA Green qPCR Master Mix Plus (Eurogentec) for SYBR assays in 50 µl reactions containing 32 ng cDNA at a primer concentration of 600 nM each, according to the manufacturer’s instructions. Pipetting was performed using a Qiagility pipetting robot (Qiagen) and a Rotor-Gene 6000 Q cycler (Qiagen) was used for PCR amplification and fluorescence monitoring. Primer sequences are listed in Supplementary Data 64 and statistical significances were assessed on non-transformed ΔΔCt values using the Welch’s test65 to account for unequal variance between the conditions.HeLa cells, in 6-well plates at 80% confluency were transfected using Lipofectamine 2000 with either 120 pmol of Control siRNA (5′-AGGUAGUGUAAUCGCCUUGdTdT-3′) and 300 ng of pcDNA3.1, 60 pmol RBM 3′UTR (5′-GAGAAUUCAUCUUGAGUUAdTdT-3′), 60 pmol RBM CDS2 siRNA (5′-GGAAAGAGAUGCAAGGACAdTdT-3′) and 300 ng of pcDNA3.1, or 60 pmol RBM 3′UTR, 60 pmol RBM CDS2 siRNA and 300 ng of pcDNA3-FLAG-RBM39 using Lipofectamine 2000. 24 h post-transfection the cells were split and re-transfected the next day with 160 pmol of siRNAs and 300 ng of pcDNA3 expression constructs. The cells were expanded the next day and harvested 5 days post-transfection in Tri-Reagent for RNA extraction or RIPA Lysis and extraction buffer (Thermo Scientific) for immunoblot analysis. 1.5 × 1066. Annotation indexes were built based on Ensembl GTF files (release 84). Gene-level counts were computed with featureCounts67 program of the Subread package (version 1.4.6). Differential gene expression analysis was carried out with default options with DESeq2 version 1.6.333. The differential analyses have been carried out on two comparisons: KD vs control and rescue vs KD. A meta-analysis of p-values of the two comparisons determined the list of all significant events. Alternative exon usage was instead identified by using DEXseq35 on BAM files. Ensembl isoforms were filtered for main transcripts as classified in the APPRIS database68. Finally, intron retention was quantified with custom python scripts based on PySam package69. Briefly, a ratio between spliced and unspliced reads was calculated and the significant differences between controls, KD and rescue conditions were assessed using a modified DESeq2 run (https://github.com/Martombo/SpliceRatio).RNA-seq data have been analysed for transcriptional and isoform-level changes. Common to both analyses is the mapping to the human genome GRCh38 by means of STAR aligner version 2.5.2a43.The preparation of the U1 snRNP components and the particle assembly was performed as previously described70. Sequence-specific backbone and side chain assignments were achieved using the classical approach71. All NOE spectroscopy (NOESY) experiments were recorded with a mixing time of 80 ms to avoid spin diffusion. RNA assignment was performed using 2D 1H-1H homonuclear TOCSY and NOESY for the ssRNA target and U1 SL3. U1 SL3 was also produced 15N/13C-labelled and assigned by combining 3D HCCH-TOCSY and 3D 1H-13C HSQC NOESY. Identification of intermolecular NOEs was achieved by comparing 2D F2f 1H-1H NOESY and 2D F1fF2f 1H-1H NOESY recorded with various mixing times ranging between 60 ms to 150 ms72 for both protein–RNA complexes. For the complex RRM1-U1SL3, we also used 3D 13C- NOESY HSQC73 using RRM1 15N-13C labelled and SL3 unlabelled.All the NMR spectroscopy measurements were performed either at 308 K (for RRM2) or at 313 K (for RRM1 and RRM12) using Bruker AVIII 500 MHz, AVIII 600 MHz, AVIII 700 MHz and Avance 900 MHz spectrometers. The data were processed with Topspin3.2 (Bruker) and analysed with CARA74 in combination with structure calculations using CYANA. In addition, dihedral angle constraints were derived with TALOS+ using backbone chemical shifts as input75 and hydrogen bonds were identified based on reduced amide exchange rates in D2O. RNA intramolecular NOEs and protein–RNA intermolecular NOEs were picked manually. The resulting peak lists including intramolecular and intermolecular NOEs, the hydrogen bonds restraints and backbone dihedral angle restraints were combined to calculate the initial structures of the protein–RNA complex using the CYANA NOEASSIGN module76. The 50 lowest energy structures were refined in cartesian space using the SANDER module of AMBER2077. Analysis of the refined structures was performed using AMBER20 scripts and PROCHECK78.To solve the structures of the RNA bound states of RRM1 and RRM2, the resonance assignments of the bound proteins were used for peak picking and automatic NOE assignment in the 3D NOESY spectra using UNIO–ATNOS–CANDIDFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Movie 1Supplementary Movie 2Reporting SummarySource data