N6-methyladenosine (m6A) deposition on nascent RNAs in human cells by developing a new method MINT-Seq, which revealed that many classes of RTE RNAs, particularly intronic LINE-1s (L1s), are strongly methylated. These m6A-marked intronic L1s (MILs) are evolutionarily young, sense-oriented to hosting genes, and are bound by a dozen RNA binding proteins (RBPs) that are putative novel readers of m6A-modified RNAs, including a nuclear matrix protein SAFB. Notably, m6A positively controls the expression of both autonomous L1s and co-transcribed L1 relics, promoting L1 retrotransposition. We showed that MILs preferentially reside in long genes with critical roles in DNA damage repair and sometimes in L1 suppression per se, where they act as transcriptional “roadblocks” to impede the hosting gene expression, revealing a novel host-weakening strategy by the L1s. In counteraction, the host uses the SAFB reader complex to bind m6A-L1s to reduce their levels, and to safeguard hosting gene transcription. Remarkably, our analysis identified thousands of MILs in multiple human fetal tissues, enlisting them as a novel category of cell-type-specific regulatory elements that often compromise transcription of long genes and confer their vulnerability in neurodevelopmental disorders. We propose that this m6A-orchestrated L1–host interaction plays widespread roles in gene regulation, genome integrity, human development and diseases.The molecular basis underlying the interaction between retrotransposable elements (RTEs) and the human genome remains poorly understood. Here, we profiled  DNA methylation14 and histone methylation (e.g. H3K9me3).16 Post-transcriptional mechanisms were also involved in RTE suppression.18 Recently, DNA damage repair (DDR) and replication related factors were identified as new suppressors of L1 activity.20 However, as compared to these defense systems deployed by the hosts to suppress RTEs, it is less known as to how RTEs harness epigenetic mechanisms to benefit their own propagation, or how RTEs may exploit the vulnerability of the host genome to undermine its defense, and what the human genome uses to cope with these L1 actions.Retrotransposable elements (RTEs), consisting of Long Interspersed Elements (LINEs), Short Interspersed Element (SINEs), and endogenous retroviruses (ERVs), make up nearly half of the mammalian genomes.13 among which ~100–140 L1s are potentially capable to transpose autonomously .21 About 20 RC-L1s are particularly active, and are responsible for a majority of the ongoing L1 mobilization.22 RC-L1s transcribe ~6-kb-long RNA by autonomous promoters and fulfill a life cycle of transcription, RNA processing, translation (into ORF1p and ORF2p), trafficking back to the nucleus, and finally the new genomic insertion13 (we sometimes refer to these as live L1s in this paper). It is important to note that while RC-L1s are the primary focus of many studies, they are actually the extreme minority as compared to the total number of annotated L1s in the reference human genome.10 Most annotated L1 sequences are truncated or mutated, incapable of coding for functional ORF1p/ORF2p, and/or have lost their 5’ends including autonomous promoters.6 They are retrotranspositionally incompetent, ‘dead’ L1s that represent evolutionary relics of L1 insertions in the past but were since fixed in our genome. Less is known about the potential functions and mechanisms of these dead L1s despite their > 17% occupancy of our genome.6 Importantly, the repertoire of L1 relics is continuously expanding because the great majority of RC-L1 jumping events will create new ‘dead’ L1s at the new location.6 Thus, understanding the regulation/function of both RC-L1s and the dead L1s is crucial to unravel how L1 transposition takes place in the human genome, and how L1 mobilization and deregulation may impact human development or diseases.More than 520,000 copies of L1s exist in the human genome, with about 3000–5000 being full length,25 Studies reported that L1 insertion may disrupt protein sequences,26 can act as alternative promoters,28 or may be mis-spliced into mRNAs.29 However, there is an exceeding rarity of L1 insertion into coding regions,30 and most post-insertion L1s lose their 5’ end and autonomous promoters,22 suggesting that some other mechanisms may more widely underlie L1 impact on host gene expression. Introns harbor a large portion of the pre-existing L1s (both live and dead L1s),12 and are the major targets for de novo L1 insertion (~35%–50%)34 . Intronic L1s may be common functional contributors to altering the genome or changing gene expression, as have been implicated by several observations,36 but a mechanistic understanding of intronic L1s on host gene control is lacking.6L1 mobilization contributes to more than 100 human genetic diseases.37 Coincidentally, the nervous system also uniquely expresses a large number of long genes.39 These long genes display a particular vulnerability to deregulation in neurodevelopmental or neuropsychiatric disorders (NNDs).41 The mechanisms underlying long gene vulnerability are unclear, despite a role of DNA topological stress in their gene bodies was suggested.41 Intriguingly, increased L1 activity was often observed in the brains of NND patients, and many of L1 pathological transpositions directly landed to long gene introns.43 However, a mechanistic link between long gene control/vulnerability and the intronic L1s has not been appreciated.Human brain possesses a uniquely high somatic activity of L1s.13 RNAs in mammals are subjected to more than 100 different types of chemical modifications, which emerge as a new paradigm in transcriptome control.45 Among these, N6-methyladenosine  is the most abundant, and was found important for mRNA metabolism, stability, and translation.45 The discoveries of specific enzyme complexes that methylate (“writer”) or demethylate (“eraser”) the m6A marks, and of proteins recognizing m6A marks or m6A-marked RNA motifs (“reader”) give birth to the concept of “epitranscriptomics” or “RNA epigenetics”.47 This was coined in analogy to the well-known concept of “epigenetics” that comprises dynamic and reversible regulation of DNA and histone chemical modifications.49 Whether RNA m6A modification may play roles in L1 retrotransposition or RTE–host interaction has been underexplored.L1s need to be transcribed into RNAs before they can insert back to the host genome .6A modification in human cells. We uncovered that m6A is a unique epigenetic mark that acts to promote L1 RNA expression and retrotransposition, and we further identified new m6A-modulated RNA binding proteins (RBPs) in human cells that act to counteract such m6A benefits. Unexpectedly, our results discovered thousands of sense-oriented m6A-marked intronic L1s (MILs) as novel regulatory elements that preferentially suppress the transcription of long human genes. This epitranscriptomic mechanism lays a new foundation to understand RTE–host interaction in gene regulation and genome maintenance, with broad implications for human development and genetic diseases, such as neurodevelopmental disorders.Here we report that the RTE-derived RNA transcripts, particularly evolutionarily young L1s, are heavily marked by m6A landscape on nascent RNAs, which we refer to as m6A inscribed Nascent Transcript Sequencing (MINT-Seq) ,50 which served as the input for MINT-Seq   and LTR retrotransposons , which is significantly higher than expected  and signals of transcription , we identified 4315 m6A-methylated intronic L1s (MILs) in K562 cells , Super-MILs and MILs possess lower sequence divergence as compared to L1 consensus sequence, and they also bear longer length, suggesting that they are evolutionarily younger53 55  and nascent transcripts (TT-Seq), Super-MILs were found to be more stable than typical MILs or other L1s .While many MILs can only be detected at the nascent RNA stage, i.e., solely by MINT-Seq , L1PA2 and L1PA3 being the most methylated  in K562,62 we found little enrichment of DNA 5mC on the genomic regions coding for MILs  on the genomic regions of MILs  and/or histone H3 methylation (H3K9me3).L1s Fig. . The depaks Fig. , which iaks Fig. .67 Characteristic promoter-associated histone marks H3K4me3 and H3K27ac were deposited to RC-L1 promoters.68 Analysis of published ChIP-Seq identified no enrichment of these marks at the 5’ ends of genomic regions coding for MILs, indicating that most MIL RNAs are not independently transcribed ; whereas the signals are high on annotated human gene promoters/TSSs  use their autonomous promoters near 5’end to drive transcription of a ~6kb-long intronless RNA.29 To test the commonality of this behavior for MILs, we used a de novo transcript assembly method, Stringtie, to identify transcripts from RNA-Seq data,72 and examined the frequency of MILs being spliced into mRNA transcripts .73 While the extremely repetitive nature of L1HS precludes their full alignment by short reads sequencing, there are a few that can be detected based on unique-mappable regions in the L1 body and immediate downstream sequences.68 Breast cancer cell line MCF7 harbors one such RC-L1 in the first intron of TTC28 gene in the antisense direction 68 68 Fig. . This isted Fig. . In thisted Fig. .6A methylation of a single active L1HS-Ta in Chr22q12.1 , the category of MILs is predominantly composed of retrotranspositionally dead L1s, which are not, or are weakly, associated with conventional epigenetic/chromatin states ; 2), Super-MILs and MILs are rarely spliced to adjacent gene mRNAs, which together with the fact that their RNAs are more stable than flanking introns Fig.  suggest 2.1 Fig. , suggestata Fig. : what ar74 , its ~70% homologous paralogue SAFB, and RBM15, a nuclear adapter protein that recruits m6A methyltransferase to Xist lncRNA75 . The strong binding of m6A-MILs by these RBPs, but not by any other abundant nuclear RBPs such as hnRNPU, suggest that they may be putative novel m6A-RNA binding proteins . One known nuclear m6A reader protein, YTHDC1,44 was not included in ENCODE eCLIP-Seq datasets. Re-analysis of published iCLIP-Seq data75 showed that YTHDC1 also binds MILs  data generated by the ENCODE consortium in K562 cellsA75 Fig. . Except 622 Fig. . The str622 Fig. , and is cus Fig. . As a cocus Fig. . UV crossts Fig. , suggest63 This is also due to its uniquely strong roles in affecting L1 RNA expression and retrotransposition  complex METTL3 and METTL14 using siRNAs , can also be recognized by the anti-m6A antibody during MeRIP or MINT-Seq.89 Knockdown of PCIF1,91 the methyltransferase of m6Am, did not affect the expression levels of L1 RNAs  generally reduced levels of young L1 RNAs in both mouse and human cells  of m6A writers . There was no alteration of an inactive L1 subfamily, the L1PA2 , supporting that the L1 retrotransposition changes were specific effects. The L1 copy increase was abolished in the presence of an inhibitor of reverse transcriptase, lamivudine (3TC) , suggesting bona fide retrotransposition events. These data together indicated that the known m6A writer/reader positively promoted L1 retrotransposition, while SAFB specifically suppressed that.L1 RNA is the key intermediate for its retrotransposition. We interrogated an important question mentioned earlier Fig. : how doe2.1 Fig. , the mos L1 Fig. , in a ma6A writers can potentially affect other genes and may impact L1s indirectly. We sought to consolidate a direct role of m6A on L1 control. m6A deposits to the RRACH motif on mRNAs,101 and we found this to be consistent on L1s  of its RRACH motifs mutated to lose the “RAC”  and no amino acid difference. We hereafter investigate the causal function of m6A by comparing this m6A-mutant L1-neo reporter  to the original reporter with consensus L1HS sequence   Fig. .6A level as compared to that by Con reporter  assay showed that as compared to the Con L1HS, the Mut L1HS was less bound by SAFB  and retrotransposition (RC-L1s), which at least in part was mediated by RNA stability control. By contrast, SAFB is a host factor that counteracts such beneficial roles of m6A through directly binding m6A-L1s to decrease their abundance, consistent with its role as an L1 suppressor identified in a CRISPR screening.63Taken together, these data demonstrated that m34 We already observed that MILs tend to exist in host genes associated with DNA damage repair and response  are predominantly sense-oriented to hosting genes Fig. , are co-L1s Fig. . InteresL1s Fig. . Disruptism Fig. .Fig. 5MItranscription blocking index (TBI) to measure the transcriptional activity of hosting genes after each intronic L1 as compared to that before it  or no m6A   in two independent cell clones  in two cell clones  Fig. . KO of tnes Fig. . By contnes Fig. . KO of alls Fig. . We condion Fig. . In suppRNA Fig. . We obsenes Fig. . In thisnes Fig. . The PSM6A-L1 RNA or the DNA region, we conducted an L1 inversion experiment. We identified two cell clones in which the original Super-MIL region was inverted. This can be verified by the presence of direction-flipped TT-Seq signals from the other strand that were not seen in WT cells  with either the m6A demethylase FTO (dCasRx-FTO) or an FTO mutant with no enzymatic activity  . This unbiased analysis not only revealed reduction of the few genes mentioned earlier ,106 but also identified other DDR genes as hosts for, and were suppressed by, MILs, such as SPIDR,107ERCC6L2108 and BRIP1    genes and long genes Fig. . Inspectem Figs. . Globallem Figs. . The effem Figs. , consistem Figs. . This unon) Fig. . The redon) Fig. .ZRANB3 has a length of 336 kb, and its expression was reduced by ~60% after depletion of SAFB&B2  ,113UBE3A,114 and CTNND2 (delta2-catenin)115 ,33 in genes coding for crucial transmembrane molecules (CNTNAP4 and CTNNA2),117 and in major neurotransmitter receptor genes such as GABA receptor type-A γ3 (GABRG3) and Glutamate Receptor AMPA Type-4 (GRIA4)  Fig. . MIL-hos39) Fig. , a largeong Fig. .Fig. 7MI118 To confirm the roles of MILs/SAFB&B2 in brain cells, we generated hNPCs from induced human pluripotent stem cells (iPSCs) with a high purity, as shown by expression of marker genes NESTIN, SOX1 and SOX2 in immunofluorescence  were known to harbor high L1 activity.120 but L1 expression and function in this cell type are less explored. We conducted TT-Seq/MINT-Seq in HMC3 cells, a transformed primary cell type of embryonic human microglia,122 which identified 1607 MILs 123 (https://www.sfari.org/resource/sfari-gene/). There is a strong association between autism-associated genes and MIL-hosting genes in the fetal brain  and of histone tails .61 Our current findings demonstrated that methylation of RNAs also controls RTEs, but acts as a unique epigenetic mark to benefit L1 propagation, opposite to the suppressive roles of DNA and histone H3K9 methylation. We found that RNA m6A predominantly enriches on transcribed intronic L1s. In addition, RNA m6A prefers young L1s that are overall longer than average, and are in the same direction as the host genes, largely due to the enrichment of RRACH motifs to permit m6A deposition. Remarkably, the genes hosting intronic m6A-L1s are often associated with essential functions for cell survival . We are tempted to speculate that these genes are largely “un-silenceable” by DNA or histone methylation. As a result, many young L1s that “hide” in their introns can be co-transcribed together with the hosting genes. Interestingly, the N6-methyladenosine on DNA was also observed to exist on L1s in mouse ESCs, although its abundance is extremely low.124 Whether RNA and DNA m6A methylation on L1s crosstalk to each other in development or disease and how that mediates L1 activity or host gene expression are interesting questions for future investigation.Here, we report a remarkable enrichment of m6A orchestrates a beneficial crosstalk between the living and the dead. Only ~100 RC-L1s in human genomes possess autonomous mobility, and the large majority of annotated L1s  are transpositionally ‘dead’.12 Our current study provided two important insights: 1) RNA m6A modification represents a unique epigenetic mark harnessed by RC-L1s to self-benefit, at least in part through increasing RNA stability; 2) m6A-marked dead MILs act as transcriptional roadblocks to impede key host genes with roles in L1 suppression to indirectly support L1 transposition  generally reduced levels of the youngest/live L1 RNAs in both mouse and human cells , for both the living RC-L1 and dead MILs, SAFB/SAFB2 bind their RNAs in an m6A-enhanced manner to suppress their expression, at least in part by decreasing RNA stability; 2) for the transpositionally-dead intronic MILs, SAFB inhibits their expression and rectifies their transcription blocking effects on important host genes  that carried a comparable density of predicted motifs cannot bind SAFB well ,129 we propose that m6A may regulate higher-order L1 RNA structures to permit stronger L1–SAFB binding.From the viewpoints of the host genome, our results revealed several RNA binding proteins as previously unappreciated defense factors. L1s are parasitic genetic elements in the human genome.es Figs. ,6,7j. Noell Fig. . These r130 research on its processivity control in gene bodies, particularly in long genes, is a minimally explored area. The number of MILs  enlisted them as a large class of elements with comparable numbers in each cell type as other well-known elements such as enhancers.132 Analogous to enhancers, MILs exhibited cell type specificity, as well as computational features of being ‘typical’ or ‘Super’. Our data indicated that MILs function in suppressing DDR genes in a tissue-invariant manner but regulate neuronal/synaptic genes in a tissue-specific fashion. These findings thus add novel insights to the regulatory roles played by RTEs in host gene regulation or genome evolution.9 Moreover, we provided mechanistic evidence by TT-Seq that the roles of MILs lie in their ability to impede RNAPII transcription. Our computational attempts, i.e., by defining TBIs for intronic elements, pave way for systematically examining the intronic control of RNAPII processivity in health and disease. The exact mechanisms of MILs on blocking host gene transcription remain unclear at this stage. We observed some overlap between Super-MILs and R-loops by re-analyzing a published dataset94 (data not shown). However, future work is warranted to elucidate the complete mechanisms by which the m6A-marked intronic L1 RNAs impede host genes, which may involve R-loop formation and/or dissolving.An unexpected advance from our work is that we established MILs as a large category of overlooked regulatory elements for gene transcriptional control. Indeed, as compared to extensive studies of RNA polymerase II (RNAPII) action at the stages of transcription initiation, pause release and elongation,134 Here, our data revealed that a portion of introns, i.e., the L1s embedded therein, can be made into stable RNAs . These genes displayed length-aggravated defects in human NPCs in the absence of SAFB&B2, indicating that they are more prone to impediment by MILs  Huang lab from Texas A&M University Health Science Center Houston, and were originally purchased from ATCC. They were cultured in RPMI 1640 medium (CORNING) supplemented with 10% fetal bovine serum. HeLa, MCF7 and 293T cells were purchased from ATCC, and cultured in DMEM medium (CORNING) supplemented with 10% fetal bovine serum. HMC3 cells are immortalized primary human embryonic microglia cells, and were purchased from ATCC. They were cultured in EMEM medium supplemented with 10% FBS. hNPCs were generated by an in-house protocol (see below). Mycoplasma was examined every 6 months to a year.6A , anti-Sox1 , anti-Sox2 , anti-Nestin .Antibodies were used at the indicated dilutions as follows: anti-SAFB , anti-YTHDC1 , anti-METTL3 , anti-METTL14 , anti-GAPDH , anti-mSee Supplementary information, Table 5 cells cultured in a well of 6-well plate were transfected with 40 nM siRNA for qPCR purposes, and two rounds of transfection were often conducted to increase the efficiency of knockdown. Large culture volumes of cells during transfection can be used for RIP or other purposes. A commercial non-targeting control siRNA  was used as negative control. 48 h to 72 h after transfection, cells were harvested and subjected to RNA extraction, RIP or western blots.Transfections of siRNAs were performed mostly using Lipofectamine 2000 following the manufacturer’s instructions. RNAiMax was used for transfecting HMC3 and human NPC cells. Often, 5 × 105 293T cells cultured in 6-well plates by using Lipofectamine 3000 (Thermo Fisher) following the manufacturer’s instructions. Virus containing medium was harvested 48 h after transfection. 5 × 105 K562 cells were infected with 1 mL fresh virus medium supplemented with polybrene at a final concentration of 8 μg/mL in 6-well plates. 1 mL fresh RPMI-1640 culturing medium was added to each well 12 h after infection. Selection was performed with 1.5 μg/mL puromycin 24 h after infection and maintained for 3 days. Survived K562 cells were used for experiments, or frozen stocked, or kept cultured in normal medium supplemented with 1 μg/mL puromycin.In brief, 1.5 μg pLKO shRNA vector with scramble sequences or with sequences targeting specific target genes (purchased from sigma) together with 1 μg psPAX2 and 0.5 μg pMD2.G plasmids were co-transfected into 5 × 10137 and were cloned into pSpCas9(BB)-2A-GFP (Addgene 48138) and pSpCas9(BB)-2A-Puro (Addgene 48139) backbones, respectively. Plasmids were prepared with E.Z.N.A.® Plasmid Midi Kit (Omega). Wild-type K562 cells were electroporated with both sgRNA plasmids at 1:1 ratio using Gene Pulser Xcell™ Electroporation Systems (Biorad) following the manufacturer’s instructions. Transfected cells were recovered in the fresh RPMI medium for 1 day and selected by 1.5 μg/mL puromycin for 3 days (to select Addgene 48139 transfected cells). These cells were then sorted by FACS with a BD FACSAria II system (BD Biosciences) to select GFP+ cells (indicating Addgene 48138 transfected). Sorted cells were plated into 96-well plates at a density of 1 cell per well and expanded. The genotypes of these isogenic cell clones were validated by PCR assays. Validated cell clones with Super-MIL inversion or homozygous KO were expanded for experiments. SgRNA and primer sequences used are listed in Supplementary information, Table For intronic L1 KO in K562 cells, two sgRNAs targeting L1 flanking sequences were designed using CHOPCHOP,138 together with 1 μg psPAX2 and 0.5 μg pMD2.G plasmids were co-transfected into 5 × 105 293T cultured in a well of 6-well plate using Lipofectamine 3000 (Thermo Fisher). Virus was harvested after 48 h and used to infect K562 cells supplemented with polybrene. 1 mL fresh RPMI-1640 culturing medium as added to each well 2 h after infection. Selection was performed with 50 μg/mL G418 48 h after infection and maintained for 6 days before subsequent experiments.To generate K562 TRE-dCas9-KRAB stable line, 1.5 μg of pHAGE-TRE-dCas9-KRAB PSMA1 gene promoter, two sgRNAs targeting PSMA1 promoter sequences were designed using CHOPCHOP,137 and were cloned into lenti sgRNA(MS2)-zeo backbone .139 SgRNA sequences used are listed in Supplementary information, Table PSMA1 promoter or a non-targeting control were transfected into 293T cells together with psPAX2 and pMD2.G for lenti-virus generation (see above). Virus was harvested after 48 h and used to infect K562 TRE-dCas9-KRAB stable line supplemented with polybrene. Infected cells were selected with 400 μg/mL zeocin for 7 days and then cultured in medium supplemented with 2 μg/mL doxycycline. Three days later cells were harvested for RNA extraction and RT-qPCR quantification.To suppress 140 To make L1HS-neo-Con reporter, L1HS consensus coding sequences were cloned into L1-neo-TET backbone 141 by replacing the codon-optimized L1 sequence using Gibson assembly. To make L1HS RRACH mutation reporter (L1HS-neo-RRACH-Mut), we disrupted the “RAC” sequences in the middle of 49 RRACH motifs without affecting coding sequence or significant changing codon usage efficiency.142 This mutant L1HS sequence was fully synthesized .143 with modification. In brief, 5 million HeLa cells were transfected with siRNAs targeting desired proteins to achieve high knockdown efficiency in retrotransposition time window. 24 h later, cells were co-transfected with L1-reporter constructs (see the previous section) and a puromycin-resistant construct serving as an internal control (Addgene 48139). Two days later, transfected cells were splitted at the same ratio for each group to 6-well plates for G418 selection (400 μg/mL) or puromycin selection (2 μg/mL). To count the numbers of cell colonies with successful L1 retrotransposition, G418 selection was maintained for ~ 14 days, and cells were fixed with a fixation buffer  for 1 h with gentle shaking at room temperature. Fixed cells were washed with ddH2O and stained with 0.1% crystal violet blue for 1 h with shaking at room temperature. Stained cells were rinsed with ddH2O and images were taken with a Bio-Rad V3 imaging system. The foci in each plate/condition were counted with ImageJ with the same settings.L1 retrotransposition reporter assay was performed according to Kopera et al.® Green Supermix  following standard parameters recommended by the manufacturer. All primer sequences are shown in Supplementary information, Table Total cellular RNA was extracted with Quick-RNA Miniprep Kit  or TRIzol following the manufacturer’s instructions. Reverse transcription was performed using Superscript™ IV kit  using oligodT for MILs, mRNAs or random hexamer for 18S RNA, and U1 as specified in each experiment. SYBR-qPCR was performed using SsoAdvanced™ Universal SYBR2. Membrane was hybridized with denatured DIG-labeled RNA probe overnight at 68 °C. Strand specific DIG labeled RNA probe was generated with MEGAscript™ T7 Kit (Thermo Fisher). DNA template for probe synthesis was generated by primers specifically targeting the first 100 bp of reporter L1 region, which is shared by both L1 consensus and RRACH mutation reporter  following the manufacturer’s instructions. In brief, RNA was separated with 1.2% formaldehyde agarose gel and transferred to a positively charged nylon membrane (Roche) by capillary transfer overnight with standard 2× SSC solution. Membrane was UV crosslinked with 400 millijoule (mJ)/cm103 all of which were based on gibson cloning. FTO enzymatically-dead mutant , was PCR-amplified from a plasmid kindly provided by Dr. Chuan He lab as a gift,93 which was introduced to the backbone of pLenti-dCAS9-VP64_Blast  in the same manner as the wildtype FTO. Stable cell lines expressing dCasRx-FTO or dCasRx-FTO-mut were generated by infection with lentivirus packaged with helper constructs and were selected with blasticidin. Guide RNAs for Cas13d (or CasRx) system were designed following a published algorithm,144 and were cloned into a lentiviral backbone . Sequences of gRNAs were listed in the Supplementary information, Table pLenti-dCasRx-FTO-HA was generated by cloning the coding sequence of human FTO into the backbone of a published construct pLenti-dCAS9-VP64_Blast (Addgene #61425), but with dCas9-Vp64 replaced by dCasRx (which is from Addgene #109050),145 with modifications. Briefly, 10 millions of HeLa cells per RIP were UV-crosslinked at 254 nm (400 mJ/cm2) in 10 mL ice-cold PBS and collected by scraping. Cells were incubated in a cold lysis buffer /mL Superase-In, 1× Protease Inhibitor in PBS) at 4 °C for 25 min with rotation. Lysate was sonicated with Qsonica Q800R3 sonicator for 5 min at 25% amplitude with 10/20 s ON/OFF cycle followed by 10 U/mL Turbo DNase treatment for 15 min at 37 °C. After centrifugation, the supernatant was incubated with 2 μg Rabbit IgG or anti-YTHDC1 antibodies immobilized on 20 μl Dynabeads™ Protein G beads overnight at 4 °C. Next morning, protein G beads bound with RNA–protein complexes were washed three times with 1 mL ice-cold wash buffer , and treated with 10 U Turbo DNase for 30 min at 37 °C. After three more times of wash with wash buffer supplemented with 10 mM EDTA, beads were digested with 200 μL Proteinase K buffer  for 30 min at 65 °C. RNA was recovered by TRIzol reagent and examined by RT-qPCR.UV-RIP was performed according to Jeon and Lee146 with modifications. 1 × 108 cells were cultured in normal medium supplemented with 700 uM 4SU (Sigma T4509) for 5 min at 37 °C. These cells were immediately lysed by TRIzol (Thermo Fisher) after medium removal. Total RNA was extracted following the manufacturer’s instructions and was dissolved in the biotinylation buffer  to a concentration of 0.4 μg/μL. Biotinylation of nascent RNA was done by adding 1/4 volume of MTSEA biotin-XX  followed by rotating in dark for 2 h. RNA was extracted with phenol/chloroform  according to standard precipitation protocol. Purified RNA dissolved in the fragmentation buffer  was fragmented at 70 °C for 15 min to an average size of 100–200 nt. Fragmentation was terminated by adding 1/10 volume of 0.5 M EDTA on ice. An aliquot of fragmented total RNA was transferred into a new tube and was subjected to RNA-Seq and MeRIP-Seq if desired. Other fragmented RNA was diluted with the high-salt buffer  by at least 5 folds. 50 μL pre-balanced streptavidin C1 beads  were added and the mixture was incubated at room temperature for 30 min with rotation. The beads were washed 3 times with 700 μL high-salt buffer, twice with 700 μL TET buffer , once with 1 mL TE buffer , with 2 min rotation at room temperature for each wash. Nascent RNA was eluted twice by 150 μL fresh-made 5% beta mercaptoethanol (b-ME) with rotation for 15 mins at dark. The two elutes were combined and precipitated with iso-propanol. Eluted RNA was dissolved in 1010 μL of ice-cold IP buffer . 10 μL of dissolved nascent RNA was transferred to a new tube and was used for TT-Seq . The remaining 1000 μL will be used for m6A immunoprecipitation. m6A-spike-in mixture (see in vitro RNA transcription) was added to both input and m6A IP samples. In the meantime, anti-m6A antibody conjugated Dynabeads™ Protein G beads  were prepared by adding anti-m6A antibody to 20 μL pre-balanced beads in 1 mL IP buffer followed by incubation at room temperature for 30 min. The beads  were then washed 3 times with the IP buffer and mixed with the RNA samples for IP. The mixture of RNA and beads was incubated at 4 °C for at least 4 h with rotation. The beads were washed 3 times with ice-cold IP buffer, twice with ice-cold low-salt wash buffer , twice with ice-cold high-salt wash buffer , once with ice-cold TE buffer, with 5 min rotation at 4 °C for each wash. The same amount of ERCC-RNA spike-in  was added to both washed beads and the input RNAs. Immunoprecipitated RNAs and input RNAs were extracted by TRIzol-LS (Thermo Fisher) following the manufacturer’s instructions. Both immunoprecipitated and input RNAs were subjected to next generation sequencing library preparation, which are MINT-seq and TT-seq samples, respectively.Nascent RNA labeling and capture was performed according to Duffy et al.6A immunoprecipitation. m6A-spike-in mixture (see in vitro RNA transcription) was added to both input and IP samples. In the meantime, anti-m6A antibody conjugated Dynabeads™ Protein G beads were prepared by adding anti-m6A antibody to 20 μL pre-balanced beads in 1 mL IP buffer followed by incubation at room temperature for 30 min. The beads were washed 3 times with the IP buffer and added to the RNA samples for IP. The mixture of RNA and beads was incubated at 4 °C for at least 4 h with rotation. The beads were washed 3 times with ice-cold IP buffer, twice with ice-cold low-salt wash buffer , twice with ice-cold high-salt wash buffer , once with ice-cold TE buffer, with 5 min rotation at 4 °C for each wash. ERCC-RNA spike-in (Thermo Fisher) was added to both washed beads and the input RNAs previously prepared. Immunoprecipitated RNAs and input RNAs were extracted by TRIzol-LS following the manufacturer’s instructions. Both immunoprecipitated and input RNAs were subject to next generation sequencing library preparation, which are MeRIP-seq and RNA-seq, respectively.Fragmented total RNA (see MTS-TT-seq and MINT-seq) was diluted with ice-cold IP buffer  to a final volume of 1010 μL. 10 μL of diluted RNA was transferred to a new tube and was used for RNA-seq  and kept on ice. The remaining 1000 μL will be used for m+ RNA for sequencing, and we labeled them in the legends  mRNA Magnetic Isolation Module  and the resulting polyA RNAs were used for library making in the same way as above described. Generated libraries in this study were mostly sequenced using NextSeq 550 Sequencing System with paired-end 40nt/40nt mode following the manufacturer’s instructions.We used ribo-depleted total RNA for most of the RNA-sequencing in this paper. Only for a few cases, we used polyAProtein samples were prepared by adding 2× Laemmli sample buffer  to cell pellets followed by passing through QIA shredder . Denatured proteins were separated by 4%–15% Mini-Protean TGX SDS-PAGE gels  and transferred to PVDF membranes. Membranes were blocked with 5% milk in the TBST buffer  followed by incubation with primary antibodies at 4 °C overnight. Membranes were washed 3 times with TBST buffer and then incubated with anti-mouse/rabbit secondary antibodies conjugated to HRP (Jackson) for 30 min at room temperature. After 3 times TBST buffer wash, proteins on the PVDF membrane were detected by chemiluminescence using Clarity™ Western ECL Substrate  and a ChemiDoc™ Gel Imaging System according to manufacturer’s instructions.6A-labeled mixed RNA species with known m6A levels as spike-in controls in our MINT-seq. Twenty non-human template sequences at 200–300 bp in length were generated by PCR with T7 containing primers  to generate non-methylated RNAs or m6A-methylated RNAs, respectively. Non-methylated RNAs and m6A-methylated RNAs generated from the same group were mixed with the following ratios , which generates spike-in groups with different methylation levels . Equal amounts from the five RNA spike-in groups were combined and mixed as final m6A-spike-in RNAs.We made mN6-methyl-ATP , or biotin-11-UTP only to generate biotin-labeled m6A-RNAs or biotin-labeled RNAs. In vitro transcribed RNAs were examined by formaldehyde RNA agarose gel to verify theirpurify, size and abundance.For in vitro RNA pulldown assay in Fig. 2, and 10% glycerol). The SAFB protein was eluted in a linear gradient over 10 column volumes with buffer B (buffer A containing 1 M KCl). The elutes were examined by SDS-PAGE. The fractions that contain pure SAFB protein were combined for subsequent in vitro pulldown experiments.Briefly, the protein coding region of human SAFB was amplified from K562 cDNA  and then incubated at room temperature for 20 min. 800 μL High-salt buffer  and 50 μL pre-balanced streptavidin C1 beads were added to RNA samples. The mixtures were incubated at room temperature for 1 h and then washed 3 times with the high-salt buffer.In vitro RNA pulldown assay was performed according to a published work Tsai et al.7 K562 cells were lysed with 1 mL RIPA buffer  and then centrifuged at 12,000× for 10 min at  °C. The supernatant was added to the prepared RNA-bound C1 beads. For pulldown against recombinant proteins, protein solution was diluted with RIPA buffer for at least ten folds before added to the prepared RNA-bound C1 beads. The mixture was then incubated at 4 °C for 4 h with rotation. Beads were washed twice with RIPA buffer, twice with high salt wash buffer , with 5 min of rotation at 4 °C for each wash. Washed beads were directly boiled in sample buffer and subjected to western blots or coomassie blue staining for target protein detection.For pulldown against cell lysates, 2 ×  10To immobilize SAFB-L1 complex on streptavidin beads, we first bind biotinylated L1HS RNA to the beads. 250 ng biotin-labeled L1HS RNA (see in vitro RNA transcription) was denatured at 65 °C for 3 min, chilled on ice, diluted with 130 μL RNA structure buffer  and then incubated at room temperature for 20 min. 800 μL High-salt buffer  and 50 μL pre-balanced streptavidin C1 beads were then added to the RNA samples. After incubation at room temperature for 1 h, the RNA-beads complex was washed 3 times with the high-salt buffer, and then incubated with 2 μg recombinant SAFB proteins in RIPA buffer  at 4 °C for 4 h with rotation. Beads bound with L1HS RNA and SAFB were washed twice with RIPA buffer with 5 min of rotation at 4 °C for each wash. The immobilized L1HS-SAFB complex was then incubated with various amounts of synthesized competition RNA at 4 °C for more than 4 h with rotation. After that, beads were washed twice with RIPA buffer, twice with high salt wash buffer , with 5 min of rotation at 4 °C for each wash. Washed beads were directly boiled in sample buffer and were subjected to western blots or coomassie blue staining for target protein detection.K562 cells stably expressing shRNA targeting mRNA of SAFB were continuously cultured for 20–30 passages in full medium or supplemented with 10 μM 3TC . Genomic DNA was extracted by Quick-DNA Miniprep Kit (ZYMO research) and sheared by sonication using Qsonica Q800R3 sonicator for 5 min at 25% amplitude with 10 s/20 s ON/OFF cycle. Same amount of fragmented genomic DNA was subjected to qPCR with SsoAdvanced™ Universal SYBR® Green Supermix  to examine the relative copy number of L1HS or L1PA2.148 Human iPSCs were reprogrammed from the dermal fibroblasts from a male patient using Sendai Virus kit (CytoTune Sendai Reprogramming Kit) containing transcription factors OSKM  in human iPSC media (minus bFGF) supplemented with 10 mM SB-431542, 1 mM dorsomorphin, 3 mM CHIR 99021, 0.5 mM purmorphamine, and 10 mM ROCK inhibitor Y-27632 . On day 2, medium was replaced by N2B27 medium supplemented with the same small molecule supplements without ROCK inhibitor. N2B27 medium contains DMEM/F12: Neurobasal (1:1) supplemented with 1× Glutamax, 1× NEAA, 1× N2 and 1× B27 minus Vitamin A . On day 4, all the small molecules were withdrawn and the medium was changed to NPC medium, comprising N2B27 medium with 20 ng/mL bFGF. On day 6, EBs were attached to the cell culture dish coated with Matrigel. After 2–4 days, neural rosettes were manually isolated and dissociated into single cells. The cells were expanded in NPC medium and were passaged every 4–5 days in a 1:4–6 ratio.Human NPCs were generated from human iPSCs using a modified dual SMAD inhibitors method.Human NPCs were characterized by immunocytochemistry. Briefly, cells grown on glass coverslips were fixed with 4% paraformaldehyde and incubated in the blocking buffer  for 15 min. Cells were then incubated in primary antibodies diluted in the blocking buffer at 4 °C overnight. Appropriate secondary antibodies were used for single and double labeling. All secondary antibodies were tested for cross-reactivity and nonspecific immunoreactivity. The following primary antibodies were used, anti-SOX2 , anti-Nestin , anti-SOX1 . Bis-benzamide  was used to visualize the nuclei. Images were captured using a Zeiss Axiovision microscope with z-stack split view function.149 with parameters of –-genomeSAindexNbases 14 –outFilterMultimapNmax 10 –outFilterMismatchNmax 10. Duplicated reads were removed, and only unique aligned reads will be considered for later visualization and quantification. For gene/mRNA quantification, hg19 RefSeq gene annotation coordinates were used. HOMER toolset was used to calculate the FPKM value of individual repeat elements, based on repeat mask annotation.150 The unique aligned reads were further converted to bigwig format with a fragment length of 75 nt for visualization on IGV browser.MINT-Seq, TT-Seq, MeRIP-Seq raw data were de-multiplexed by bcl2fastq (v2.20), and quality-controlled with fastqc. All clean reads were mapped to human reference genome hg19 by STAR v2.7.0,6A spike-in sequences, see Supplementary information, Table 6A-spike-in RNAs, we first used ERCC reads to normalize the RNA-Seq reads of both the m6A IP group (MINT-Seq) and Input RNA group (TT-Seq). We used a linear regression model (MINT-Seq/TT-Seq ERCC reads) to obtain an ERCC normalization factor. The observed m6A level of one transcript will be calculated by raw m6A ratio (MINT-Seq/TT-Seq m6A spike-in reads) divided by ERCC normalization factor. Further, as the m6A levels of the spike-in m6A reads are known, we can compare the observed m6A levels of spike-in to their expected m6A levels by calculating the spearman’s correlation coefficient  (using STARv2.5.2) with the parameters of “–winAnchorMultimapNmax 100 –outFilterMultimapNmax 100” as recommended by TEtranscripts. TEtranscripts was run using stranded options (–stranded reverse and –stranded yes).Most RTE repeat quantification is based on uniquely aligned reads. We also considered multi-mapped reads to estimate m6A peak calling by using MACS2151 with the parameters of -f BAM -q 0.01 -n. We are aware that there are alternative tools to call m6A peaks,153 but MACS2 remains one of the commonly used tools and works robustly for many different m6A RNA-Seq datasets in different tissues or conditions. For MINT-Seq peak calling, we considered TT-Seq as input, and for MeRIP-Seq peak calling, we treated RNA-Seq as input. The called m6A peaks were overlapped with annotated LINE-1 elements using bedtools v2.1.0.154 We used HOMER de novo motif discovery tool (findMotifGenome.pl -rna) with MINT-Seq peaks overlapping intronic L1s as input sequences to identify potential m6A RNA motifs. Annotation of m6A peaks overlapping genomic regions was performed by the HOMER toolset. MILs (m6A-methylated intronic L1s) were identified as transcribed intronic L1s  that overlap at least one m6A peak (MINT-Seq or MeRIP-Seq). Then the methylation level of each MIL was computed by the ratio between (MINT-Seq FPKM + pseudo-count)/(TT-Seq FPKM + pseudo-count), which was ranked to generate the plot shown in Fig. 51 i.e., we find the data point that shows a slope closest to 1 in the ranked plot of m6A methylation levels , and ages of different L1 subfamilies were based on a previous publication.55This analysis is related to Supplementary information, Fig. 156 then a de novo transcript assembly tool, Stringtie72 was applied to analyze the data with these parameters (-p 64 -f 0.5 -m 200 -a 10 -j 3 -c 2 -g 200 –rf). To identify de novo transcripts that contain MILs, we overlapped the StringTie de novo assembly transcripts with K562 MILs identified from MINT-Seq datasets using bedtools . The UMI information of eCLIP reads were utilized to remove possible duplicates with ENCODE eCLIP tool: barcode_collapse_pe.py (https://www.encodeproject.org/software/barcode_collapse_pe.py/). We further extracted reads that can be aligned to genome annotated L1HS regions in hg19 reference genome, filtered these reads with clipping, insertion, and deletions (to ensure the reads are not from other L1 sub-families), and aligned the filtered reads (read2 only) to the L1HS consensus sequence with bwa-mem (default parameters). The distribution of eCLIP binding sites on L1HS were calculated with bedtools (genomeCoverageBed -strand + -3 -d).K562 ENCODE eCLIP-Seq raw datasets were downloaded from ENCODE data portal  in a specific human fetal tissue was considered an MIL. The RefSeq genes that harbor at least one MIL were used to perform functional enrichment analysis using Metascape157).The human fetal tissue MeRIP-Seq and RNA-Seq datasets were retrieved from a previous study.TBI was calculated utilizing TT-Seq reads coverage. Upstream TT-Seq signal denotes the reads coverage (FPKM) between a specific intronic L1s’ 5' end and the hosting gene TSS, while downstream TT-Seq signal denotes reads coverage (FPKM) between an intronic L1s’ 3-end and the hosting gene TES. Then TBI for each intronic L1 were calculated as the ratio between the upstream TT-Seq FPKM and the downstream TT-Seq FPKM. Only sense-oriented (relative to host gene) intronic L1s were considered when we calculated the TBI values. MIL-hosting genes were excluded from Control L1-hosting genes . For PSMA1 Super-MIL TBI calculation, the TES of PSMA1 gene were manually annotated to exclude the reads from PSMA1 gene short isoforms.63 In Liu et al.63 (K562 CRISPR screen), any genes that showed CasTLE score < 0  in their high-coverage secondary screen targeting the high-confident hits  were considered as L1 suppressor genes in our current work. Mita, et al., identified 220 inhibitory hits (Z-score > 3.0) in their RNAi screen, and all were considered as L1 suppressor genes in our current analysis. Genes associated with the Autism spectrum disorders (ASD) were obtained from the SFARI database (https://www.sfari.org/resource/sfari-gene/).MIL-hosting genes are RefSeq genes (hg19) that harbor identified MILs in their introns . The list of DDR genes was generated by combining genes included in two GO terms (cellular response to DNA damage stimulus (GO: 0006974), and DNA repair (GO: 0006281), Supplementary information, Table t-test was used to compare means between groups as indicated; P < 0.05 was considered significant, and P-values are indicated in each figure. All other statistical analyses were performed with Python script. Key software used in analysis of high-throughput sequencing data are described above.All qPCR data were analyzed with R and were presented as means ± SD as indicated. Two-tailed Student’s Supplementary Fig 1Supplementary Fig 2Supplementary Fig 3Supplementary Fig 4Supplementary Fig 5Supplementary Fig 6Supplementary Fig 7Supplementary Fig 8Supplementary Fig 9Supplementary Fig 10Supplementary Fig 11Supplementary Fig 12Table S1Table S2Table S3Table S4Table S5Table S6Table S7


Next-generation sequencing (NGS) technology has revolutionized sequence-based research. In recent years, high-throughput sequencing has become the method of choice in studying the toxicity of chemical agents through observing and measuring changes in transcript levels. Engineered nanomaterial (ENM)-toxicity has become a major field of research and has adopted microarray and newer RNA-Seq methods. Recently, nanotechnology has become a promising tool in the diagnosis and treatment of several diseases in humans. However, due to their high stability, they are likely capable of remaining in the body and environment for long periods of time. Their mechanisms of toxicity and long-lasting effects on our health is still poorly understood. This review explores the effects of three ENMs including carbon nanotubes (CNTs), quantum dots (QDs), and Ag nanoparticles (AgNPs) by cross examining publications on transcriptomic changes induced by these nanomaterials. Sequence based high-throughput technology has made it possible to observe gene expression changes and is quickly becoming the preferred choice in toxicological studies through identifying the modes of action (MOA) or the mechanisms of toxicity of certain chemicals and materials. These technologies are extremely sensitive and capable of whole-transcriptome sequencing and can quantify gene expression alterations by measuring RNA transcripts. The most accurate technique, RNA-Seq, has been around for more than a decade and can detect the slightest changes in gene expression with unprecedented accuracy . It is qENMs include a wide variety of nano-sized particles with incredibly small size ranges of 1–100 nm  that posIt has been commonly established in ENM-toxicity studies that their physiochemical properties contribute to their toxicity. The high diversity in physiochemical properties amongst ENMs has made characterizing their modes of action or identifying their individual mechanisms of toxicity in biological systems exceedingly difficult ,10. In aIn this review, we attempt to examine the toxicity of three ENMs including AgNPs, carbon nanotubes (CNTs), and QDs. AgNPs and CNTs were selected because silver is the most common nanomaterial used in products, followed closely by carbon-based nanomaterials . AdditioDNA microarray and RNA-Seq are the best methods for whole transcriptome gene expression profiling in toxicogenomic studies ,14. DNA The limitations of DNA microarray are apparent when target sequences are composed of unknown genomic sequences. This method only works by using nucleic acid probes of known sequences that are covalently bound to a slide. Therefore, microarray techniques are only as accurate as the bioinformatic data available on an organism’s genome . In compRNA-Seq is clearly the superior technique for gene expression profiling, however, DNA microarray is still valid and implemented in gene expression investigations. Due to the rapid advancements in software, RNA-Seq will eventually become more cost effective. Currently, the use of DNA microarray and RNA-Seq in evaluating ENM-toxicity is not very common, but is becoming more frequent, RNA-Seq more so than DNA microarray. Notably, DNA microarray techniques will not become obsolete anytime soon partly due to their clinical applications in disease diagnostics . Soon, RDue to the evident advantages of using RNA-Seq in identifying changes in gene expression, toxicogenomic techniques have become a useful tool for assessing risk to human health . These tCNTs are a highly versatile class of ENMs that have a variety of uses ranging from high performance batteries and touchscreens to drug delivery systems  5]. The. The5]. Previous studies have shown that exposure to CNTs can have toxic effects through the generation of oxidative stress or by inducing inflammation . MWCNT aEscherichia coli (E. coli) . As. AsGSS, p53, p21, Cyt C, Bid, Bax, and Bak; modification of signaling molecule expression related to cell survival, viability, and cytotoxicity were also observed , in cervical cancer cells (HeLa) by Yuan et al. The combined treatments increased the expression of pro-apoptotic genes like observed  74]. NG. NGp53, The study of AgNPs in human tissue is crucial to discovering the strengths/limitations of their application to human cancer. Opposed to their anti-cancer potential, recent evidence has shown that AgNPs alter genetic expression to increase susceptibility to carcinogens  76]. Ou. Ou76]. In conclusion, the use of AgNPs has greatly impacted antibacterial, antifungal, and anticancer treatment methods. This review only touches the surface of data that has been reported, but shows evidence concluding that AgNPs are effective in the alteration of gene expression among species. While its properties are promising, careful consideration is still needed in reference to their toxicity within mammalian cells. Going forward, more research is needed to understand what levels of AgNPs are safe for human consumption and ways to harness their toxicity so that they can continue to be an effective treatment against pathogenesis.Toxicogenomic techniques such as DNA microarray and RNA-seq could be valuable tools for assessing toxicity. However, RNA-seq provides more precise coverage of the transcriptome of a cell . Due to


EXOSC2 cause an apparently distinct clinical presentation that has been defined as a novel syndrome SHRF . We generated the first in vivo model of the SHRF pathogenic amino acid substitutions using budding yeast by modeling pathogenic EXOSC2 missense mutations  in the orthologous S. cerevisiae gene RRP4. The resulting rrp4 mutant cells show defects in cell growth and RNA exosome function. Consistent with altered RNA exosome function, we detect significant transcriptomic changes in both coding and noncoding RNAs in rrp4-G226D cells that model EXOSC2 p.Gly198Asp, suggesting defects in nuclear surveillance. Biochemical and genetic analyses suggest that the Rrp4 G226D variant subunit shows impaired interactions with key RNA exosome cofactors that modulate the function of the complex. These results provide the first in vivo evidence that pathogenic missense mutations present in EXOSC2 impair the function of the RNA exosome. This study also sets the stage to compare exosomopathy models to understand how defects in RNA exosome function underlie distinct pathologies.RNA exosomopathies, a growing family of diseases, are linked to missense mutations in genes encoding structural subunits of the evolutionarily conserved, 10-subunit exoribonuclease complex, the RNA exosome. This complex consists of a three-subunit cap, a six-subunit, barrel-shaped core, and a catalytic base subunit. While a number of mutations in RNA exosome genes cause pontocerebellar hypoplasia, mutations in the cap subunit gene  Saccharomyces cerevisiae in a screen for ribosomal RNA processing (rrp) mutants  . As illuAs described above, a feature of the RNA exosome is the ability to both process and degrade numerous RNA targets. The specificity for this broad set of target transcripts is achieved, at least in part, through RNA exosome cofactors that associate with the complex via interactions with multiple subunits . These cEXOSC genes encoding the structural subunits of the RNA exosome to various human pathologies, which comprise a growing family of diseases termed “RNA exosomopathies” , neurological disorders characterized by atrophy of the pons and cerebellum  (OMIM #617763)  . While S#617763) , the disEXOSC2 gene that alter conserved amino acids in this cap subunit, shown in EXOSC2 p.Gly30Val (G30V) in the amino-terminal domain of EXOSC2 , with the G198D missense mutation located within the K-homology (KH) RNA binding domain . Notably, EXOSC2 Gly30 and EXOSC3 Gly31, an amino acid that is substituted in PCH1b patients . EXOSC2 Gly198 and EXOSC3 Trp238, another amino acid that is substituted in PCH1b patients . An amino acid substitution that alters the glycine at position 30 is predicted to alter the β-turn and position the Asp31 residue away from Arg232 such that the salt bridge would be disrupted. In addition, the EXOSC2 G30V substitution introduces a valine, which is significantly larger than glycine and appears to clash with residues Asp154 and Ala191 in EXOSC4  in Rrp4 that forms a salt bridge with Arg233 in Rrp41, similar to the EXSOC2–EXOSC4 interface . Similar to the human structure, in the yeast exosome structure, the Rrp4 Gly58 residue is also predicted to be essential for the flexibility of the region, facilitating the β-turn, and thus stabilizing the Rrp4–Rrp41 interface . Similar to the EXOSC2 G30V substitution, substitution of Gly58 in Rrp4 most likely disrupts this β-turn, disrupting the salt bridge and destabilizing the Rrp4–Rrp41 interface.To explore how EXOSC2 G30V and EXOSC2 G198D variants could alter the structure of the EXOSC2 protein or the RNA exosome complex C, we modPDB 6FSZ ). Structn EXOSC4 A, suggesn EXOSC4 C, is locn EXOSC4 B, mirrorn EXOSC4 A. Rrp4 GEXOSC2 Gly198 is positioned in a dense region of the subunit, surrounded by four β sheets C. The EXSupplemental Table S3) suggest that the pathogenic amino acid substitutions have molecular consequences that could affect RNA exosome function in both humans and budding yeast.The online server mCSM-PPI2 was used to calculate the change in Gibbs free energy (ΔΔG) to predict the effect of the EXOSC2 amino acid substitutions and corresponding Rrp4 amino acid substitutions on protein–protein interactions. Consistent with observations from structural modeling, the software predicts destabilizing changes in the affinity of the protein–protein interactions for both EXOSC2 G30V  and EXOSC2 G198D . The EXOSC2 G198D substitution is also predicted to reduce protein stability (Score = 1.000 Polymorphism Phenotyping v2). These predictions are consistent with previous work showing that EXOSC2 G198D has reduced stability compared to wild-type EXOSC2 . FurtherS. cerevisiae ortholog Rrp4, G58V, and G226D . This approach ensures that the genetic background for all mutants compared to one another is identical -tagged Rrp43 core subunit from the endogenous RRP43 locus. We coexpressed Rrp4-Myc, Rrp4 G58V-Myc, or Rrp4 G226D-Myc in these RRP43-TAP cells. The Rrp43-TAP protein was immunoprecipitated and association of the Myc-tagged Rrp4 variants was assayed by immunoblotting  processing, specifically processing 7S pre-rRNA into mature 5.8S rRNA , which have documented accumulation of this rRNA precursor  of the resulting RNA-seq data produced two distinct clusters, indicating that the rrp4 mutant transcriptome is distinct from the wild-type RRP4 control (rrp4-G226D mutant cells compared to the control (P < 0.05) and 802 transcripts decreased  in rrp4-G226D cells compared to the RRP4 control , NRD1 and NAB3, encode components of the Nrd1–Nab3–Sen1(NNS) transcription termination complex (Gene Ontology (GO) analysis of the differentially expressed transcripts in tEnrichr , 2019 retEnrichr D. These  complex .CUT501, CUT770, CUT896  in rrp4-G226D cells compared to RRP4 control cells. We also validated decreased steady-state levels of several mRNAs  (P < 0.01) in rrp4-G226D cells compared to control  in solid media growth assays , U4 small nuclear RNA (snRNA), and TLC1 telomerase RNA . The EXOSC2–EXOSC4 and Rrp4–Rrp41 interfaces may be differentially impacted by the valine substitution in the two eukaryotic species which could account for the differences between budding yeast rrp4-G58V cells and homozygous EXOSC2-G30V patients. Previous studies also suggest that the RNA exosome plays an important role in tissue development and human embryonic stem cell differentiation . As CUTs and SUTs are stabilized in RNA exosome mutants and cross-link to the RNA exosome , with the most significantly decreased transcript being INO1 mRNA. Previous studies have shown that INO1 mRNA associates with the catalytic Dis3/Rrp44 subunit of the RNA exosome in budding yeast as determined by UV cross-linking and analysis of cDNA (CRAC)  mRNAs are decreased in rrp4-G226D cells and GO analysis of the decreased transcripts revealed cytoplasmic translation to be the most significantly affected biological process  . This puS3 mRNAs ; other R process D. Consist cells, . Decreasrrp4-G226D cells could result from indirect effects, reflecting cellular changes that occur when the function of the RNA exosome is compromised, leading to numerous downstream changes. Previous work in Drosophila melanogaster that used RNAi to deplete Rrp4 identified decreased levels of several transcripts encoding autophagy proteins  , which is consistent with observations in this previous study. Further studies will be required to assess whether rrp4-G226D cells have impaired autophagy as well as to determine whether these mRNA transcripts are direct targets of regulation by the RNA exosome.Many of the decreased mRNA transcripts observed in proteins . The autproteins . In our rrp4-G226D cells could be due to disrupted cofactor interactions, particularly decreased association with the essential RNA helicase Mtr4. Human structural studies have shown that MTR4/MTREX binds directly not only to MPH6/MPP6 but also to a conserved region of EXOSC2  (EXOSC2 mutations on protein stability and function.We used the cryo-EM structure (PDB 6D6R) of the human nuclear RNA exosome at 3.45 Å resolution  and the PROVEAN) , and SNAPROVEAN)  webserveS. cerevisiae strains and plasmids used in this study are listed in Supplemental Table S1. The rrp4Δ (yAV1103) and rrp40Δ (yAV1107) strains were previously described (RRP43-TAP (ACY2788) strain was obtained from Horizon Discovery Biosciences Limited and was previously described (RRP43-TAP rrp4Δ (ACY2803) strain was constructed by deletion of the genomic RRP4 ORF in the RRP43-TAP (ACY2788) strain containing a RRP4 URA3 maintenance plasmid by homologous recombination using a RRP4-UTR neoMX4 PCR product. The rrp4Δ mpp6Δ (ACY2471), rrp4Δ rrp47Δ (ACY2474), rrp4Δ rrp6Δ (ACY2478) strains and the rrp40Δ mpp6Δ (ACY2638), rrp40Δ rrp47Δ (ACY2462), rrp40Δ rrp6Δ (ACY2466) strains were constructed by deletion of the MPP6, RRP47, and RRP6 ORF in the rrp4Δ (yAV1103) and rrp40Δ (yAV1107) strains by homologous recombination using MPP6-, RRP47-, or RRP6-UTR natMX4 PCR products. The rrp4Δ mtr4Δ (ACY2536) and rrp40Δ mtr4Δ (ACY2540) strains were constructed by consecutive deletion of the genomic MTR4 ORF and RRP4 ORF or RRP40 ORF in a wild-type (W303) strain harboring a  (pAC3714) or  (pAC3713) maintenance plasmid by homologous recombination using MTR4-UTR natMX4 and RRP4-UTR or RRP40-UTRneoMX4 PCR products. Construction of RRP40-2×Myc and rrp40-2×Myc variant plasmids  was reported previously (RRP4-2×Myc LEU2 CEN6 (pAC3474) plasmid was constructed by PCR amplification of the endogenous promoter, 5′-UTR and ORF of the RRP4 gene from S. cerevisiae genomic DNA and cloning into pRS315 plasmid containing a carboxy-terminal 2×Myc tag and the ADH1 3′-UTR (rrp4-G58V-2×Myc (pAC3476) and rrp4-G226D-2×Myc (pAC3477) plasmids were generated by site-directed mutagenesis of the RRP4-2×Myc (pAC3474) plasmid using oligonucleotides containing the SHRF syndrome-linked G58V and G226D missense mutations and the QuikChange II Site-Directed Mutagenesis Kit (Agilent). The untagged RRP4/rrp4-G226D  and RRP40/rrp40-W195R  plasmids and Myc-tagged RRP4/rrp4-G226D  plasmid containing native 3′-UTRs were generated by excision of the 2×Myc-ADH1 3′-UTR from each RRP4/40-Myc LEU2 CEN6 plasmid by restriction digestion and cloning of the native RRP4 3′-UTR, RRP40 3′-UTR, or 2×Myc-RRP4 3′-UTR PCR product into the relevant plasmid using NEBuilder HiFi Assembly (New England BioLabs). The -MTR4 HIS3 CEN6 (pAC4096) plasmid was constructed by PCR amplification of the endogenous promoter, 5′-UTR, ORF, and 3′UTR of the MTR4 gene from S. cerevisiae genomic DNA and cloning into pRS313 (mtr4-F7A-F10A (pAC4099) plasmid was generated by site-directed mutagenesis of the MTR4 HIS CEN6 plasmid (pAC4096) using oligonucleotides containing the F7A and F10A missense mutations and the QuikChange II Site-Directed Mutagenesis Kit (Agilent). The MTR4-2×FLAG (pAC3719) plasmid was constructed by PCR amplification of the MTR4 promoter-5′-UTR-ORF (No Stop) and 2×FLAG-native MTR4 3′-UTR using MTR4 template plasmid (pAC2897 -ATP (PerkinElmer) using polynucleotide kinase (New England Biolabs) at 37°C for 30 min. [P32]-Labeled oligonucleotide probe was purified through a G25 microspin column , heated at 100°C for 5 min, and added to hybridization buffer. The oligonucleotide probe was hybridized to membrane in hybridization buffer at 37°C overnight. Following removal of hybridization buffer, membrane was rinsed twice in 5× SSPE; 0.1% SDS at 25°C and washed twice in 0.5× SSPE; 0.1% SDS at 37°C for 20 min each. The membrane was exposed to phosphoscreen overnight and imaged using Typhoon FLA 7000 phosphorimager .For analysis of 5.8S pre-rRNA processing—detection of 7S pre-rRNA and processing intermediates—in S. cerevisiae rrp4 and rrp40 mutant cells was isolated using TRIzol (Invitrogen) for qRT-PCR and northern blotting and MasterPure Yeast RNA Purification Kit  for RNA-seq. S. cerevisiae cells were grown in 2 mL Leu− minimal media overnight at 30°C to saturation. Cultures were diluted in 10 mL Leu− minimal media to an OD600 = 0.2 and grown for 5 h at 37°C. Cells were pelleted by centrifugation, transferred into 2 mL screw cap tubes, and stored at −80°C. To prepare total RNA using TRIzol, cells were resuspended in 1 mL TRIzol (Invitrogen) with 300 µL of glass beads. Cell samples were disrupted in a BioSpec Mini-Beadbeater 16 Cell Disrupter for 2 min at 25°C. For each sample, 100 µL of 1-bromo-3-chloropropane (BCP) was added, sample was vortexed for 15 sec, and incubated at 25°C for 2 min. The sample was centrifuged at 16,300g for 8 min at 4°C, and the upper layer was transferred to a fresh microfuge tube. RNA was precipitated with 500 µL isopropanol and sample was vortexed for 10 sec to mix. Total RNA was pelleted by centrifugation at 16,300g for 8 min at 4°C. The RNA pellet was washed with 1 mL 75% ethanol, centrifuged at 16,300g for 5 min at 4°C, and air-dried for 15 min. Total RNA was resuspended in 50 µL diethylpyrocarbonate -treated water and stored at −80°C. Total RNA was prepared using MasterPure Yeast RNA Purification Kit  according to manufacturer's protocol. Total RNA was resuspended in 50 µL DEPC-treated water and stored at −80°C.Total RNA from Supplemental Table S2. For analysis of steady-state RNA levels using quantitative PCR, three independent biological replicates of rrp4Δ (yAV1103) cells containing only RRP4 (pAC3656) or rrp4-G226D (pAC3659) and rrp40Δ (yAV1107) cells containing only RRP40 (pAC3652) or rrp40-W195R (pAC3655) were grown in 2 mL Leu− minimal media overnight at 30°C, 10 mL cultures with an OD600 = 0.2 were prepared and cells were grown at 37°C for 5 h. Total RNA was isolated from cell pellets and 1 µg of total RNA was reverse transcribed to first strand cDNA using the M-MLV Reverse Transcriptase (Invitrogen) according to manufacturer's protocol. Quantitative PCR was performed on technical triplicates of cDNA (10 ng) from three independent biological replicates using gene specific primers , QuantiTect SYBR Green PCR master mix (Qiagen) on a StepOnePlus Real-Time PCR machine . ALG9 was used as an internal control. The mean RNA levels were calculated by the ΔΔCt method  cells containing RRP4-2×Myc (pAC3474) or rrp4-G226D-2×Myc (pAC3477) as the sole copy of RRP4 grown at 37°C. Cells were grown in 2 mL Leu− minimal media overnight at 30°C, diluted to an OD600 = 0.4 in 10 mL Leu− minimal media, grown at 37°C for 5 h, and collected and stored at −80°C. Total RNA was isolated, rRNA was depleted, and stranded cDNA libraries were prepared using TruSeq Total RNA Stranded Library Prep kit (Illumina). Paired-end sequencing of the cDNA libraries was performed on a HiSeq4000 instrument (2 × 150 cycles) at Frederick National Laboratory for Cancer Research (FNLCR) at the CCR Sequencing Facility, NCI, NIH. The RRP4 samples yielded an average of 28,890,739 pass filter reads and the rrp4-G226D samples yielded an average of 34,644,683 pass filter reads, with a base call quality of 94% of bases with Q30 and above. The reads were mapped to the S. cerevisiae S288C genome assembly R64-1-1, annotated with CUTs and SUTs  in rrp4-G226D samples relative to RRP4 samples. Principal component analysis (PCA) on raw read counts was also performed using DESeq2. A volcano plot of differential gene expression data was produced in Prism 8 (Graphpad Software). Piecharts of RNA class percentages in significantly altered genes were generated in Microsoft Excel for Mac (Microsoft Corp.). Gene Ontology (GO) analysis on significantly altered genes for Biological Process category was performed using the YeastEnrichr webserver .rrp4-G226D or rrp40-W195R and RNA exosome cofactor/subunit deletion mutants, rrp4Δ mpp6Δ (ACY2471), rrp4Δ rrp47Δ (ACY2474), and rrp4Δ rrp6Δ (ACY2478) cells containing only RRP4 (pAC3656) or rrp4-G226D (pAC3659) and rrp40Δ mpp6Δ (ACY2638), rrp40Δ rrp47Δ (ACY2462), and rrp40Δ rrp6Δ (ACY2466) cells containing only RRP40 (ACY3652) or rrp40-W195R (ACY3655) were grown in 2 mL Leu− minimal media overnight at 30°C to saturation, serially diluted, and spotted on Leu− minimal media plates. The plates were incubated at 30°C and 37°C for 3 d.To test genetic interactions between rrp4-G226D or rrp40-W195R and the mtr4 mutant, mtr4-F7A-F10A, rrp4Δ mtr4Δ (ACY2536) cells containing the  (pAC3714) maintenance plasmid were transformed with RRP4 (pAC3656) or rrp4-G226D (pAC3659) LEU2 plasmid, and rrp40Δ mtr4Δ (ACY2540) cells containing the  (pAC3713) maintenance plasmid were transformed with RRP40 (pAC3652) or rrp40-W195R (pAC3655) LEU2 plasmid and selected on Ura−Leu− minimal media plates. Transformed cells containing both the URA3 maintenance plasmid and the RRP4/rrp4-G226D or RRP40/rrp40-W195R LEU2 plasmid were subsequently transformed with MTR4 (pAC4096) or mtr4-F7A-F10A (pAC4099) HIS3 plasmids and selected on Ura−Leu−His− minimal media plates. The transformed cells were then streaked onto 5-FOA Leu− His− plates to select for cells that did not contain the URA3 maintenance plasmid. The resulting rrp4Δ mtr4Δ cells containing only RRP4 or rrp4-G226D LEU2 plasmid and MTR4 or mtr4-F7A-F10A HIS3 plasmid and rrp40Δ mtr4Δ cells containing only RRP40 or rrp40-W195R LEU2 plasmid and MTR4 or mtr4-F7A-F10A HIS3 plasmid were grown in 2 mL Leu− His− minimal media overnight at 30°C to saturation, serially diluted, and spotted on Leu− His− minimal media plates. The plates were incubated at 30°C and 37°C for 3 d.To test genetic interactions between 600 = 0.2–0.3 were prepared and grown at 30°C for 5 h. Yeast cell lysates were prepared by resuspending cell pellets in 0.5–0.75 mL of IPP150 Buffer  supplemented with protease inhibitors , and 300 µL of glass beads. Cells were disrupted in a Mini-Beadbeater 16 Cell Disrupter (BioSpec) for 4–5 × 1 min at 25°C with 1 min on ice between repetitions. Crude lysate was transferred to a chilled microcentrifuge tube and remaining beads were washed with an additional 150 µL of IPP150 Buffer. Lysate was then cleared by centrifugation at 16,000g for 10 min at 4°C. Protein lysate concentration was determined by Pierce BCA Protein Assay Kit (Life Technologies). For input samples, 40 µg of cleared lysate was collected and frozen at −20°C. For coimmunoprecipitations, 1 mg of cleared lysate in 1 mL IPP150 Buffer was prepared, 15–30 µL of a 1:1 bead slurry of either Pierce Anti-c-Myc Magnetic Beads (Thermo Fisher) or IgG Sepharose 6 Fast Flow Beads  was added, and samples were incubated at 4°C overnight with mixing. After overnight incubation, beads were washed three times in 1 mL IPP150 Buffer for 15 sec each (anti-Myc beads) or 5 min each (IgG Sepharose beads). Whole cell lysate input samples (40 µg) and total bound samples in reducing sample buffer were boiled for 5 min at 100°C, resolved on 4%–20% Criterion TGX Stain-Free Precast Polyacrylamide Gels (Bio-Rad), transferred to nitrocellulose membranes (Bio-Rad) and immunoblotted. Myc-tagged Rrp4 proteins were detected with mouse anti-Myc monoclonal antibody 9B11 . TAP-tagged Rrp43 protein was detected with peroxidase anti-peroxidase (PAP) soluble complex antibody produced in rabbit . FLAG-tagged Mtr4 protein was detected with anti-DYKDDDDK (FLAG) tag rabbit monoclonal antibody D6W5B . The 3-phosphoglycerate kinase (Pgk1) protein was detected using anti-Pgk1 monoclonal antibody  as a loading control.All immunoprecipitations were performed using the same protocol. Cell samples were grown in 2 mL selective media overnight at 30°C to saturation and 10–20 mL cultures with an ODRRP43-TAP (YCR035C) cells expressing RRP4-Myc (pAC3669), rrp4-G58V-Myc (pAC3670) or rrp4-G226D-Myc (pAC3672) and RRP43-TAP rrp4Δ (ACY2803) cells expressing only RRP4-Myc (pAC3669) or rrp4-G226D-Myc (pAC3672) and immunoprecipitated Rrp43-TAP using the IgG Sepharose beads. Levels of associated Rrp4-Myc proteins with the Rrp43-TAP tagged subunit were detected by immunoblotting. To assess association of Rrp4 G226D with the Mtr4 helicase, we utilized rrp4Δ (yAV1103) cells expressing only RRP4-Myc (pAC3669) or rrp4-G226D-Myc (pAC3672) and coexpressing exogenous MTR4-FLAG (pAC3719) and immunoprecipitated Rrp4-Myc or Rrp4 G226D-Myc using anti-c-Myc beads. Levels of associated Mtr4 with the Rrp4-Myc proteins were detected by immunoblotting.To assess association of Rrp4 G226D with the RNA exosome complex, we utilized The raw RNA-seq data from this study have been submitted to the NCBI Gene Expression Omnibus (GEO) under accession GSE163106.Supplemental material is available for this article.


In the present study, we investigated the influence of sequence variation in the recognition arms of the RNA/PNAzyme complex on the RNA cleavage activity of the artificial enzymes. The base pairs closing the 3-nucleotide bulge region on both sides of the bulge as well as the neighbouring nucleobases were shown to significantly influence the RNA cleavage activity. Elongation of the RNA/PNAzyme complex was shown to be tolerated, although potentially prohibitive for catalytic turnover. The specificity of PNAzyme action was clearly demonstrated by the significantly reduced or absent cleavage activity in complexes containing mismatches. Further investigation into 2- and 4-nucleotide RNA bulges indicated that formation of 3-nucleotide bulges in the target RNA gives the optimal cleavage rates, while some potential off-target cleavage of formed 4-nucleotide bulges of select sequences should be considered.The development of Zn 2+ dimethyl-dppz PNAzymes to cleave RNA target sequences with under 20 minute half-lives is critically dependent on the bulge-closing base pairs as well as their stacking interactions with the neighbouring nucleobases.The ability of Zn A thorough understanding of the intricacies of the sequence–activity relationships in the RNA/PNAzyme complexes can shed light on various aspects of PNAzyme action, while also being critical for the effective identification of novel RNA targets and for understanding possible off-target effects. The present study takes a particular interest in the bulge-closing base pairs on both sides of the bulge, as well as the sequence and length of the shorter recognition arm of the RNA/PNAzyme complex. Moreover, in addition to the cleavage of 3-nucleotide RNA bulges, which have been studied in detail,15 we demonstrate the cleavage of 2-nucleotide RNA bulges and study the sequence-dependence in 4-nucleotide bulges.Artificial ribonucleases of various designs have been reported, including both metal-freei.e. the long recognition arm.15 In such systems, the AAA bulge is cleaved site-specifically with an approximately 1 h half-life  showed slightly lower activity. Rather strikingly, the cleavage activity suffered a major loss when the AAA bulge was closed with a UA (RNA 5/PNAzyme V) or AT base pair (RNA 4/PNAzyme IV), where the RNA cleavage half-lives were estimated to be in the 4 and 11 h range, respectively . MS anal15 the nucleobase preceding the bulge-closing base pair has been either of the two pyrimidine bases in the RNA and the complementary purine in the PNA strand. As such, it should be carefully considered in the selection of novel RNA targets in future investigations whether instead of UC or CC (pyrimidine-C), perhaps AG or GG (purine-G) sequence would be tolerated equally well in the bulge-closing region of the long recognition arm. It should be noted that the activity of more complex triplex-forming Cu2+-neocuproine PNAzymes has indeed been higher with purine–purine (AG) rather than purine-pyrimidine (AC) sequence in the RNA target in the same bulge-closing region.18The overall dependence of RNA cleavage activity on the bulge-closing base pairs (most to least favourable CG > GC > UA > AT) suggests that the strength of hydrogen bonding is key. Moreover, there seems to be an additional benefit if the pyrimidine is in the RNA and the purine in the PNA strand. Herein as well as in prior reports,25 The bulge nucleobases can point out into the solvent, fold back onto adjacent hydrophobic surfaces, or they may take part in the continuous stacking of the surrounding double strands, favouring kinking of the helix.25 As such, the bulge-closing base pair is clearly changing the structural arrangement, which is also evident in the comparison of the circular dichroism (CD) spectra of these four complexes , but the activity remained very low for all five bulge sequences  once again outperformed those with the AT and UA pairs . Interestingly, this change in the position next to the bulge-closing base pair in the short recognition arm led to a slightly lower cleavage rate. As such, the GC sequence in RNA 13 closing the bulge in the short recognition arm was favoured over GG in RNA 20. It remains unclear whether the strength of hydrogen bonding in the position next to the bulge-closing base pair is critical, or perhaps GU (purine–pyrimidine) would be tolerated equally well, hence allowing the possibility of a UA base pair in the RNA/PNAzyme complex next to the bulge-closing GT wobble.Moreover, a further change was then introduced by replacing the GT wobble with an AT bulge-closing base pair, which was then followed by a GC base pair (RNA 6/PNAzyme VII). A further decrease in the RNA cleavage rate was observed. The cleavage still took place at a single site between the second and third nucleotide in the bulge  since the complex stability will be higher. The previously studied complexes (e.g. RNA 1/PNAzyme I) consist of two recognition arms comprising 7 Watson–Crick base pairs on the one side and 1 GT wobble followed by 3 Watson–Crick base pairs on the other side. The elongated complexes studied herein contained elongated short recognition arms. The RNA 24/PNAzyme XI and RNA 25/PNAzyme XII complexes have two and four additional Watson–Crick base pairs at the RNA 3′ terminus. Elongation of the complex in the short recognition arm led to virtually the same extent of cleavage as the shorter system in the presence of equimolar PNAzyme  in the long recognition arm would likely also adversely affect turnover.While the rate of cleavage is unaffected by elongation of the short recognition arm, the length of the complex can be more critical for catalytic turnover, 15 While the latter is evidently a better target, the possibility of off-target cleavage of the former should be considered. Moreover, the rate of cleavage of 3-nucleotide bulges is greatly increased when the AAA bulge is replaced with UUA, AUA or GUA bulges .15 It is likely that the sequence of the 4-nucleotide bulges would also have a significant influence on the cleavage rate, but this sequence-dependence requires further investigation.Prior reports have indicated that the cleavage of the AAAA bulge can be several times slower than the AAA bulge.15 the preservation of the preferred 5′-U/A-3′ or A/A cleavage site was clearly important also in 4-nucleotide bulges, as the presence of uridine in the position next to the GT wobble (AAAU bulge in RNA 8) led to a slight decrease in the cleavage rate and two consecutive uridines next to the GT wobble  were even more detrimental to the cleavage rate  were cleaved more efficiently when the complex contained the CG and GC bulge-closing base pairs instead of UA and AT pairs. Thus, the bulge-closing base pair was suggested to have a critical role in defining the structural arrangement of the bulge nucleotides, while interactions involving the base pair preceding the bulge-closing base pair are also likely to be important.The bulge-closing base pair in the short recognition arm was equally influential, as the highest rates were obtained with a GT wobble, and both AT and GC Watson–Crick base pairs had a negative effect on the cleavage rate. The activity was also affected by the succeeding base pair.2+-dimethyl-dppz-PNAzymes. For rapid site-specific cleavage, the RNA targets are suggested to require the sequence 5′-Py-C-bulge-G-C-3′ , although the feasibility of the RNA sequence Pu-G (Pu = purine) instead of Py-C preceding the bulge and G-U following the bulge could also be evaluated. Variations in the rest of the sequence are likely to be tolerated. Furthermore, the RNA/PNAzyme complex can be longer than the standard 11 base pairs, albeit the catalytic turnover might be affected if either of the cleaved fragments forms more than 7 base pairs with the PNAzyme. Consequently, these structural demands must be taken into consideration in the selection of RNA target sequences for PNAzymes in future studies. Although RNA targets forming 3-nucleotide bulges are clearly more efficiently cleaved, potential off-target sequence cleavage should be considered, as the PNAzymes were shown to also cleave 4-nucleotide RNA bulges of select sequences with down to 1 h half-lives.These sequence–activity relationships shed light on the structural demands for efficient cleavage of RNA targets by the Zn15 Oligoribonucleotides RNA 26–28 were purchased purified from integrated DNA Technologies, Inc . RNA 13, 16, 24 and 25 were synthesised as previously reported.15 Concentrations of RNA sequences were determined by UV absorption at 260 nm on a Varian Cary 300 UV-Vis dual beam spectrophotometer  using extinction coefficients obtained by the nearest neighbour approximation.26All reagents and solvents used were of analytical commercial quality. RNA cleavage experiments were performed in nuclease-free water for molecular biology purchased from Sigma-Aldrich . Oligoribonucleotides RNA 1–23 were purchased from Dharmacon . RNA 1 and 13 were purchased purified. RNAs 2–12 and 14–23 were purified as previously reported.−1) was purchased from Biotage . Peptide nucleic acid monomers, Fmoc-PNA-A(Bhoc)-OH, Fmoc-PNA-G(Bhoc)-OH, Fmoc-PNA-C(Bhoc)-OH and Fmoc-PNA-T-OH, were purchased from Link Technologies Ltd . Fmoc-l-Dap(Mtt)-OH , Fmoc-l-Lys(Boc)-OH, N,N′-diisopropylcarbodiimide (DIC) and 1-[bis(dimethylamino)methylene]-1H-1,2,3-triazolopyridinium 3-oxide hexafluorophosphate (HATU) were purchased from Iris Biotech GmbH . Ethyl cyano(hydroxyimino) acetate (Oxyma) was purchased from Merck-Millipore . Acetic anhydride and 2,6-lutidine were purchased from Alfa Aesar . N-Methylpyrrolidone (NMP), dichloromethane (DCM), triisopropylsilane (TIS), piperidine and N-methylmorpholine (NMM) were purchased from Sigma-Aldrich . Trifluoroacetic acid (TFA) was purchased from Fisher Scientific . Neocuproine and 3,4-diaminobenzoic acid were purchased from Fluorochem .Rink Amide resin  were prepared as previously reported.15 The RP-HPLC purity analysis of purified PNA conjugates is available in ESI-S1.−1 sinapic acid in acetonitrile–water  containing 0.1% TFA).PNA oligomers were prepared on a Biotage Initiator+ Alstra microwave peptide synthesiser as previously reported.m/z: PNAzyme I C151H181N73O38 [M + H]+1 calculated 3625.34, observed 3625.36. PNAzyme II C162H194N80O41 [M + H]+1 calculated 3916.56, observed 3916.92. PNAzyme III C161H194N78O41 [M + H]+1 calculated 3876.56, observed 3877.13. PNAzyme IV C162H195N77O42 [M + H]+1 calculated 3891.56, observed 3891.73. PNAzyme V C162H194N80O40 [M + H]+1 calculated 3900.57, observed 3901.06. PNAzyme VI C150H180N74O37 [M + H]+1 calculated 3610.46, observed 3611.66. PNAzyme VII C150H181N71O38 [M + H]+1 calculated 3585.45, observed 3585.60. PNAzyme VIII C150H181N71O38 [M + H]+1 calculated 3585.45, observed 3585.29. PNAzyme IX C151H181N73O37 [M + H]+1 calculated 3609.46, observed 3609.30. PNAzyme X C151H182N70O39 [M + H]+1 calculated 3600.45, observed 3600.53. PNAzyme XI C173H207N87O42 [M + H]+1 calculated 4175.68, observed 4176.44. PNAzyme XII C194H234N96O49 [M + H]+1 calculated 4692.88, observed 4693.48.MALDI-MS 26 and the reported extinction coefficient for dipyridophenazine.27Concentrations of PNA conjugates were determined by UV absorption at 260 nm on a Varian Cary 300 UV-Vis dual beam spectrophotometer , using extinction coefficients obtained by the nearest neighbour approximation,15 but for clarity we requote them in ESI-S2.2+ ion binding.RNA cleavage experiments were performed and analysed as previously reported,−1 linear gradient from 0 to 80% acetonitrile in 8.6 mM TEA + 100 mM HFIP buffer over 15 min at 40 °C on Waters Xevo G2-XS QTof. Ionization mode: ESI negative. Source capillary voltage: 2 kV. Source desolvation temperature: 320 °C. Full scan with fragmentation, mass range: 400–2000 Da/0.5 s, sensitivity mode. Deconvoluted using 5 ppm tolerance. The MS spectra of the cleaved fragments are shown in ESI-S3.RNA cleavage experiments were performed as detailed above, but with a 22 hour incubation time. The cleaved fragments were then identified by LC-MS analysis of the quenched reaction aliquots as follows. HRMS spectra were collected by elution of the aliquots of RNA cleavage reactions on an Oligonucleotide BEH C18  column using a 0.4 mL min2+ ions in 10 mM phosphate buffer containing 100 mM NaCl and 0.1 mM EDTA at pH 7.0. The spectra were smoothed over 5 points. The spectra are shown in ESI-S4.†CD spectra of RNA/PNAzyme complexes were measured between 230 and 370 nm on a Jasco J-1500 CD Spectrometer using 10 mm path length cuvettes. The spectra were recorded as an average of five scans at 25 °C and normalised by subtracting the background buffer scans. The samples of RNA/PNAzyme complexes (4 μM) were analysed in the absence of ZnConceptualisation – O. L., M. M. and R. S. Formal analysis – O. L. and R. S. Funding acquisition – R. S. Investigation – O. L and K. K. with contributions from P. B., M. B. Methodology – O. L., M. M., R. S. Project administration – O. L., R. S. Resources – U. T., R. S. Supervision – M. B., U. T., R. S. Visualisation – O. L. Writing - original draft – O. L. Writing – review and editing – O. L. and R. S. with contributions from all.Since performing this work, Olivia Luige has become an employee of AstraZeneca.There are no conflicts to declare.RA-012-D1RA08319H-s001