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meCLICK-Seq, a Substrate-Hijacking and RNA Degradation Strategy for the Study of RNA Methylation

  • Sigitas Mikutis
    Sigitas Mikutis
    Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.
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    • , 
  • Muxin Gu
    Muxin Gu
    Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, U.K.
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    • , 
  • Erdem Sendinc
    Erdem Sendinc
    Boston Childrens’ Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
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    • , 
  • Madoka E. Hazemi
    Madoka E. Hazemi
    Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.
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    • , 
  • Hannah Kiely-Collins
    Hannah Kiely-Collins
    Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.
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    • , 
  • Demetrios Aspris
    Demetrios Aspris
    Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, U.K.
    The Center for the Study of Haematological Malignancies, Karaiskakio Foundation, Nicandrou Papamina Avenue, 2032 Nicosia, Cyprus
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    • , 
  • George S. Vassiliou
    George S. Vassiliou
    Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, U.K.
    The Center for the Study of Haematological Malignancies, Karaiskakio Foundation, Nicandrou Papamina Avenue, 2032 Nicosia, Cyprus
    Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Puddicombe Way, Cambridge CB2 0AW, U.K.
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    • , 
  • Yang Shi
    Yang Shi
    Boston Childrens’ Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
    Ludwig Institute for Cancer Research, Oxford University, Old Road Campus Research Build, Roosevelt Dr., Oxford OX3 7DQ, U.K.
    More by Yang Shi
    • , 
  • Konstantinos Tzelepis*
    Konstantinos Tzelepis
    Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, U.K.
    Boston Childrens’ Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
    Milner Therapeutics Institute, University of Cambridge, Puddicombe Way, Cambridge CB2 0AW, U.K.
    *E-mail: [email protected]
    More by Konstantinos Tzelepis
    Orcidhttp://orcid.org/0000-0002-4865-7648
    • , and 
  • Gonçalo J. L. Bernardes*
    Gonçalo J. L. Bernardes
    Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.
    Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Avenida Professor Egas Moniz, 1649-028 Lisboa, Portugal
    *E-mail: [email protected]
    More by Gonçalo J. L. Bernardes
    Orcidhttp://orcid.org/0000-0001-6594-8917
Cite this: ACS Cent. Sci. 2020, 6, 12, 2196–2208
Publication Date (Web):October 29, 2020
https://doi.org/10.1021/acscentsci.0c01094
Copyright © 2020 American Chemical Society
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Abstract

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The fates of RNA species in a cell are controlled by ribonucleases, which degrade them by exploiting the universal structural 2′-OH group. This phenomenon plays a key role in numerous transformative technologies, for example, RNA interference and CRISPR/Cas13-based RNA editing systems. These approaches, however, are genetic or oligomer-based and so have inherent limitations. This has led to interest in the development of small molecules capable of degrading nucleic acids in a targeted manner. Here we describe click-degraders, small molecules that can be covalently attached to RNA species through click-chemistry and can degrade them, that are akin to ribonucleases. By using these molecules, we have developed the meCLICK-Seq (methylation CLICK-degradation Sequencing) a method to identify RNA modification substrates with high resolution at intronic and intergenic regions. The method hijacks RNA methyltransferase activity to introduce an alkyne, instead of a methyl, moiety on RNA. Subsequent copper(I)-catalyzed azide–alkyne cycloaddition reaction with the click-degrader leads to RNA cleavage and degradation exploiting a mechanism used by endogenous ribonucleases. Focusing on N6-methyladenosine (m6A), meCLICK-Seq identifies methylated transcripts, determines RNA methylase specificity, and reliably maps modification sites in intronic and intergenic regions. Importantly, we show that METTL16 deposits m6A to intronic polyadenylation (IPA) sites, which suggests a potential role for METTL16 in IPA and, in turn, splicing. Unlike other methods, the readout of meCLICK-Seq is depletion, not enrichment, of modified RNA species, which allows a comprehensive and dynamic study of RNA modifications throughout the transcriptome, including regions of low abundance. The click-degraders are highly modular and so may be exploited to study any RNA modification and design new technologies that rely on RNA degradation.

Synopsis

RNA methylation controls many biological processes. We describe a small molecule-based platform to hijack RNA methylation by guided degradation for high resolution profiling of modified substrates.

Targeted cutting and degradation of RNA plays key roles in a wide array of cellular mechanisms, such as RNA turnover,(1,2) processing,(3) and innate immune responses.(4) These mechanisms are harnessed in technologies, such as RNA interference(5) and CRISPR/Cas13 systems.(6) However, these platforms are genetically encoded or oligomer-based, which limits their applicability. Small molecules that target and degrade RNA circumvent many of these limitations and expand the scope for RNA degradation approaches.(7,8) So far, their availability is limited and their platforms lack the modularity of genetically encoded approaches. Thus, a strategy that retains the modularity and scope of small-molecule targeting of RNA is highly desirable.
We have come up with a concept of click-degraders, small molecules that can be covalently attached to any RNA species by click chemistry, degrading them in a similar way to ribonucleases. To demonstrate the power of this concept, we have developed meCLICK-Seq (methylation–CLICK-degradation sequencing), a small-molecule-based transcriptome-editing platform that hijacks endogenous RNA methylation pathways(9) to induce specific cleavage and degradation of methylated RNAs (Figure 1a), and used it to carry out a transcriptome-wide sequencing of methylated RNA writer substrates to determine the specificity of m6A writer enzymes. What makes meCLICK-Seq unique among RNA modification sequencing methods is that its readout is depletion, not enrichment, of methylated RNA species, which allows reliable high-throughput sequencing in a wider range of RNA species than before. meCLICK-Seq has numerous other advantages over other available RNA sequencing methods. Unlike antibody-based methods,(2,10−12) meCLICK-Seq does not require large quantities of RNA (so is ideal for large parallel studies and for use with rare cellular populations), does not rely on availability of an antibody against a particular modification and is catalytically dependent, and so captures a dynamic picture of RNA modifications at a given time. Unlike antibody-free RNA methylation mapping methods,(13−15) meCLICK-Seq does not involve enzymatic or any other kind of RNA processing besides the regular sequencing pipelines. RNA degradation is achieved by direct treatment of cultured cells with small molecules; this avoids enzymatic biases. Importantly, the meCLICK-Seq platform is highly modular, and the click-degrader can be used with different probes to map different RNA modifications, for example, acetylation or isopentenylation, and with suitable cellular models, the approach described here can be used to study any type of RNA methylation.

Figure 1

Figure 1. meCLICK-Seq, a small molecule-based methylated RNA editing platform. (a) Proposed mechanism of action of meCLICK-Seq. (b) Conversion of PropSeMet into SeAdoYn and subsequent introduction of propargyl groups into RNA. (c) Functionalization of propargylated RNA with the click-degrader. (d) Proposed mechanism of the general base RNA degradation. (e) Copper-mediated RNA degradation.

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Despite the complex mechanism, meCLICK-Seq involves just two cell culture treatment steps. In the first step, cells are incubated with methionine surrogate PropSeMet (PSM) after 30 min of methionine starvation. Cells take up the methionine surrogate, and native methionine adenosyltransferases transform it into SeAdoYn, an S-adenosyl methionine (SAM) surrogate. RNA methyltransferases (MTases), including METTL3 and METTL16, use SeAdoYn as a cofactor, instead of SAM, which leads to the addition of propargyl, instead of methyl, groups onto RNA (Figure 1b).(16) A Cu(I)-catalyzed azide–alkyne cycloaddition (CuAAC) reaction is then carried out directly on cultured cells to tag RNA with a click-degrader, which acts as a functional artificial RNA modification that catalyzes the cleavage of RNA and leads to its degradation (Figure 1c). This in situ step prevents further RNA processing and minimizes treatment biases. The imidazole-based click-degrader has a dual mechanism. It acts as a general base that abstracts a proton from the 2′-O position on RNA that leads to cleavage, similarly to ribonucleases and other artificial nuclease mimics (Figure 1d).(17−19) It also cleaves RNA in a copper-dependent manner, which mimics several nucleic acid-cleaving natural products (Figure 1e(20)). As a result, this cleavage leads to decreased levels of methylated substrates, which can be directly quantified to provide information about the methylation status of any RNA transcript in real time.

Results and Discussion

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Click-Degraders Function through a Dual Chemical Mechanism

To demonstrate the validity of our RNA degradation strategy and to probe the chemical mechanism of click-degraders, we have carried out in vitro experiments on a synthetic RNA 11-mer functionalized with a propargyl moiety on one of its 6A positions. An unmodified 11-mer was used as a control. We went on to attach the click-degrader onto alkynylated RNA so as to observe what effect it has on RNA stability. Under optimal conditions, CuAAC RNA functionalization was complete in approximately 10 min (Figure S1a–c). Furthermore, we found that upon incubation at 37 °C, the functionalized RNA gets gradually degraded (Figure 2a). Although the kinetic profile of RNA degradation may be complex, first-order half-lives are often used as an estimate of RNA stability.(21) By using a first-order approximation, we have calculated the functionalized RNA 11-mer to have a half-life of 2.6 h (Figure S1d). Additionally, we carried out the click-degrader functionalization and degradation on two longer oligomers (Figure S2a–c). In both cases, longer oligomers got degraded more extensively than the 11-mer (Figure S1e). This might be because longer oligomers have more sites susceptible to degradation. We have also compared the effects of click-chemistry components (copper sulfate, THPTA, sodium ascorbate, and the click-degrader) on alkynylated and nonalkynylated control oligomer. Only 9% of the alkynylated click-degrader-functionalized RNA remained after 14 h of incubation, whereas almost no degradation was observed when an identical click-degrader treatment was applied to a control RNA oligomer that lacks the propargyl handle and the ability to be click-functionalized (Figure 2b). To obtain further evidence that the click-components only affect the stability of functionalized RNA, we have carried out the click-functionalization and degradation on a mixture of control and propargylated 11-mers (both at 100 μM). Again, extensive degradation was observed exclusively for the click-degrader functionalized oligomer (Figure S1f,g). These results demonstrate that only the covalently imidazole-functionalized RNA is degraded, so the observed effect is specific to modified RNA and not the result of nonspecific degradation, for example from the click-degrader, copper, and ascorbate.

Figure 2

Figure 2. Study of the chemical mechanism of click-degraders. (a) Time-dependent degradation of click-degrader 1 functionalized RNA 11-mer at 37 °C. n = 2. (b) Extent of RNA degradation after 14 h at 37 °C, pH 7.5, n = 2. (c) Extent of RNA degradation after 14 h at 37 °C, pH 3.0, n = 2. (d) Extent of RNA degradation in neutral and acidic conditions, n = 2. (e) Extent of RNA degradation after 14 h at 37 °C, pH 7.5, with PEG linkers of differing lengths. Cinitial corresponds to initial concentration; C corresponds to concentration at a specified time point. Click-degraders 1, 2, and 3 have linkers with 6, 4, and 2 PEG subunits, respectively, n = 2. Error bars represent SD.

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To gain insight into the mechanism of click-degraders, we carried out in vitro degradation reactions under conditions that suppress certain mechanisms. To investigate whether copper plays a role, we ran reactions quenched with either the copper chelator bathocuproinedisulfonic acid (BCS) or the general metal chelator ethylenediaminetetraacetic acid (EDTA). In the presence of these chelators, 68% and 79% of RNA remained intact, respectively (Figure 2b), which suggests that copper plays a key role in the degradation process. To investigate the role of our click-degrader as a general base, we carried out the reaction under acidic conditions (pH 3), in which imidazole on the click-degrader is protonated and nonbasic but intrinsic RNA stability is comparable to neutral conditions,(22) as well as under basic conditions (pH 8.5), in which the imidazole is nearly completely deprotonated. In the case of pH 3.0, 15% of functionalized RNA was retained, which is almost twice as much as under pH 7.5, whereas the nonpropargylated oligomer was not significantly affected; at pH 8.5 only 2% of functionalized RNA remained intact (Figures 2c,d and S1h). Similar trends were observed when the functionalized 11-mer was degraded at pH 3.0, 7.5, and 8.5 for 2 h (Figure S1i). Importantly, no significant RNA degradation was observed in the presence of BCS at pH 3 when both copper and general base mechanisms are blocked (Figure 2c). These findings show that both copper-dependent and general base mechanisms are relevant and sufficient to explain the chemical mechanism of our click-degrader. We were also interested whether other transition metals as well as noncoordinated copper in tandem with the click-degrader are able to facilitate degradation. To look into this, we used the minimum amount of copper–THPTA complex (100 μM) for the CuAAC reaction, followed by quenching of copper with BCS (200 μM) and the addition of other transition metals (1 mM of corresponding chloride). Interestingly, we found that Zn(II) facilitates the degradation but Fe(II) does not (Figure S1j). This result suggests that in the cellular environment, cofactors other than copper can facilitate the degradation of functionalized RNAs. In addition, we also investigated how the length of the click-degrader linker affects the efficiency of degradation. We tested three different linker lengths [6, 4, and 2 poly(ethylene glycol) (PEG) subunits] and found that the longest linker led to the most efficient degradation, possibly because it is more flexible and provides a better reach for imidazole (Figure 2e). It was difficult to isolate and test click-degraders with even longer linkers, so we used click-degrader 1 (6 PEG subunits) for downstream experiments.
To gain further insight into the mechanism of the click-degrader, we have carried out liquid chromatography–mass spectrometry (MS) and RNA gel analyses on the degradation products of the click-degrader functionalized 11-mer. The MS analysis was carried out on LCMS traces of degraded RNA products of the functionalized 11-mer. In all the degraded samples many peaks corresponding to different masses were observed, suggesting that the degradation results in the formation of many different RNA products (Figure S3a–c, Supporting Table S1). An RNA degradation reaction quenched with BCS also revealed formation of numerous RNA products, however there was a different pattern of observed peaks, suggesting that the click-degrader can cleave RNA on many different sites through the general base mechanism (Figure S3d, Supporting Table S2). The RNA gels were in agreement with LCMS results: formation of a smear was observed upon prolonged degradation, further suggesting formation of multiple RNA species (Figure S3e,f). Altogether, these results have implications for detection of 2′-O-methylated RNA species (e.g., m6Am). As the degradation can take place on many different positions, the 2′-O-Me should not protect RNA from degradation (with potential exceptions where several such modifications are nested together); thus meCLICK-Seq should be adaptable for detection of modifications such as m6Am.

Elucidation of mRNA Substrates of m6A Writers

Upregulation of RNA methylation was shown to play a pivotal role in the maintenance of cancers, including acute myeloid leukemia (AML) cells.(23,24) We thus went on to investigate whether PropSeMet treatment results in formation of propargyl groups on a human acute myeloid leukemia cell line, MOLM13, as well as a kidney cancer cell line, HEK293T, focusing on the propargyl version (Pr6A) of the RNA modification m6A, the most abundant type of mRNA methylation. Indeed, having analyzed via mass spectrometry the RNA of these cells after PropSeMet treatment, we observed formation of the propargylated adenosine on polyA-enriched RNA (Figure S4a,b). Having demonstrated that PropSeMet is a probe capable of inducing RNA propargylation, we went on to apply meCLICK-Seq to the human AML cell line MOLM-13 (Figure 3a). We used isogenic MOLM-13 cells stably transduced with conditional shRNAs against METTL3 or METTL16, both known to be m6A writers,(25,26) or scrambled shRNA as control (Figure 3b).(27) As our platform is catalysis-dependent, the loss or down-regulation of an RNA methyltransferase is predicted to eliminate degradation of its RNA substrates. Initially, we observed that the abundance of many mRNAs was reduced in clicked but not control (PropSeMet-fed but not clicked) cells, which suggests successful intracellular degradation of methylated transcripts (Figure 3c and Figure S5a). Strikingly, levels of many of these transcripts were restored in cells with either METTL3 or METT16 downregulation, which suggests that methylation of the relevant RNAs was mediated by the catalytic activity of the corresponding MTase. In particular, we identified 5441 METTL3- and 7656 METTL16-dependent mRNA substrates (Supporting Table S3). We then cross-compared our findings to results of an m6A individual-nucleotide resolution cross-linking and immunoprecipitation (miCLIP)(12) sequencing experiment carried out on MOLM-13 cells (Supporting Table S4).(28) We observed a consistent overlap for both enzymes with 69% of METTL3 and 67% of METTL16 mRNA substrates identified through meCLICK-Seq reported to contain m6A sites by miCLIP (Figure 3d and Figure S5b). Furthermore, we found that the m6A methylation of 5159 mRNAs depends on both MTases and that the majority of the identified methylated substrates are dependent on METTL16, which is in line with the fact that METTL16 is the modulator of cellular cofactor SAM and its levels (Figure S5c).(25,29) It is thus likely that many of the overlapping substrates are methylated predominantly by METTL3, whose catalytic activity in part depends on METTL16. In a similar fashion, METTL16- but not METTL3-dependent m6A-containing substrates are most likely directly methylated by METTL16. To check whether these results can be observed by independent methods, we used RT-qPCR to validate a panel of m6A-containing transcripts (Figure 3e,f and Figure S5d). Notably, this validation mirrored the results of the RNA-seq highlighting the specificity of our platform. Furthermore, to show that the click components, on their own, have little effect on the individual transcript levels, we carried out qPCR on a panel of m6A substrates using RNA extracted from starved MOLM13 cells treated with the same click conditions as PropSeMet-fed cells. We observed no significant differences in substrate abundances between treated and nontreated cells, showing that the observed effects result from the click-degrader functionalization and not the individual click components (Figure S5e). Thus, we have demonstrated that meCLICK-Seq can specifically identify the mRNA substrates of RNA MTases and the results agree closely with the results of antibody-based approaches.

Figure 3

Figure 3. meCLICK-Seq elucidates the relationship between m6A writers and methylation of mRNAs and lncRNAs. (a) meCLICK-Seq workflow. (b) Western blots demonstrate the extent of METTL3 and METTL16 depletion in conditional knock-down MOLM-13 cells treated with PropSeMet. Application of click-degrader does not significantly alter the levels of MTases. (c) Heat map showing decrease of methylated mRNA levels upon clicking and rescue of METTL3-dependent transcripts upon METTL3 depletion. (d) Overlap of m6A-containing mRNAs determined through m6A miCLIP and METTL3 mRNA substrates determined by meCLICK-Seq; significance indicated by Fisher’s exact test. (e) RT-qPCR-based meCLICK-Seq validation of a panel of genes, n = 3. (f) RT-qPCR-based meCLICK-Seq validation of a panel of genes in METTL3 depleted cells, n = 3. (g) Genome browser snapshot of NEAT1. Applying click machinery diminishes the WT but not METTL3 or METTL16 levels. p values determined with one-tailed t test. ns = not significant (p ≥ 0.05). Error bars represent SD.

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Many lncRNAs Are METTL3 or METTL16 Substrates

Another group of RNAs reported to be heavily methylated are long noncoding RNAs (lncRNAs). We therefore investigated whether our meCLICK-Seq platform could identify methylation changes on this RNA subgroup focusing again on METTL3- and METTL16-dependent m6A events.(30) For example, NEAT1 was shown to be a target of m6A demethylase ALKBH5, although the MTases that deposit the modifications were not identified.(31) Through meCLICK-Seq, we demonstrate that the methylation of NEAT1 depends on both METTL3 and METTL16 (Figure 3g). In total, we identified 689 METTL3-dependent and 889 METTL16-dependent lncRNAs, out of which 77 and 104, respectively, significantly overlapped with lncRNA substrates shown to contain m6A sites by miCLIP sequencing (Figure S5f,g and Supporting Table S5). Interestingly, we observed that the overlap between meCLICK-Seq and m6A miCLIP, albeit significant, is much smaller for lncRNAs than for mRNAs. Furthermore, meCLICK-Seq was able to identify a greater number of lncRNA substrates than m6A miCLIP, the opposite to what was observed for mRNAs, which suggests that our platform efficiently probes lncRNA methylation without antibody biases. Similar to mRNAs, the majority of lncRNAs are promiscuous m6A substrates because methylation of 562 lncRNAs (56% of total identified) appeared to be dependent on both METTL3 and METTL16 (Figure S5h). We were also able to validate a number of these findings by RT-qPCR (Figure S5i). Furthermore, to investigate whether meCLICK-Seq is able to degrade and therefore identify RNA species that contain methylation on known secondary structures, we validated using qPCR the lncRNA MALAT1 with primers designed to target the m6A-containing loop (Figure S6a).(32) We observed extensive degradation, showing that our method could indeed target methylation on secondary structures. Overall, using meCLICK-Seq, we have thus revealed m6A methylation on lncRNAs in a MTase-dependent fashion.
To provide additional evidence that PropSeMet treatment does indeed result in formation of propargylated adenosine (Pr6A) on natively m6A-containing species and to show that CuAAC click reaction can effectively take place on these sites, we carried out a biotin–streptavidin pull-down experiment. Briefly, we treated MOLM13 cells with PropSeMet and reacted the propargylated RNA with biotin-azide probe, followed by streptavidin pull-down and qPCR analysis of a panel of known m6A-containing species. As expected, these RNA species were successfully enriched after full PropSeMet–biotin treatment but not in any of the controls that omit one of the components, indicating that these RNA species were indeed labeled with PropSeMet as well as providing an additional method to validate sufficiently abundant methylated RNA species (Figure S6b). Altogether, these experiments provide further evidence that PropSeMet treatment indeed results in propargylation of mRNA.

meCLICK-Seq Reveals That m6A Is Widespread in Intronic and Intergenic Regions

Rather unexpectedly, further interrogation of our RNAseq data with the meCLICK-Seq platform revealed high-resolution peaks in intronic and intergenic regions. The majority of these peaks were highly sensitive to functionalization with the click-degrader, which indicates that these regions were indeed modified by MTases (Figure 4a). These peaks might be a result of the artificial propargyl modification interfering with RNA recycling pathways and perhaps leading to increased stability. Another interesting observation was the pronounced loss of abundance of many identified peaks in cells depleted of either METTL3 or METTL16, which implies that these MTases regulate methylation at the corresponding peaks (Figure 4b and Figure S7a–d). In total, we have found 1345 METTL3- and 9618 METTL16-dependent intronic and intergenic peaks that lost abundance upon clicking and hence had the modification (Figure 4c) with the distribution of these peaks appearing different for the two MTases (Supporting Table S6). In line with recent literature,(23,33,34) 50% of METTL3-dependent peaks were found in intergenic regions (relative to 23% for METTL16) further highlighting the involvement of METTL3 in chromatin associated or cotranscriptional pathways (Figure 4d,e). Moreover, more than 77% of METTL16-dependent peaks were located in intronic regions with 36% of those found in the first intron, unexpected for a 3′-biased method. This highlights the different roles these MTases play in mRNA modification, with METTL16 regulating the modification in many more intronic regions than METTL3. This is in line with previous reports about the cotranscriptional role of METTL3 and METTL16 in depositing m6A in introns.(25,35) meCLICK-Seq is thus the first method to capture widespread methylation in low-abundance transcriptomic regions at such high resolution and low RNA input. Unlike antibody-based intronic analysis, meCLICK-Seq does not require enrichment of nascent RNA to observe intronic methylation.

Figure 4

Figure 4. meCLICK-Seq reveals widespread m6A mark in introns and intergenic regions. (a) Intronic peaks in the first intron of FLI1. (b) Intronic peaks in the first intron of CADM1 in three isogenic cell models. Intronic peaks are abolished specifically in METTL16-KD cells. (c) Overlap between METTL3- and METTL16-dependent intronic peaks. (d) Distribution of METTL3-dependent peaks in intronic and intergenic regions. (e) Distribution of METTL16-dependent peaks in intronic and intergenic regions. (f) RT-qPCR-based validation of a panel intronic peaks, n = 3. (g) Validation of dependence of intronic peaks on RNA methylases METTL3 and METTL16, n = 3. (h) Results of m6A-RIP in cells with methylated introns removed by dual gRNA system, n = 3. (i) Results of m6A-RIP in cells with depleted METTL3, n = 3. (j) Results of m6A-RIP in cells with depleted METTL16. RASA3 peak 2 is not affected by the knock-down illustrating that the observed effect is enzyme-specific, n = 3. ns = not significant (p ≥ 0.05). Error bars represent SD.

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To further demonstrate that the peaks we found contain bona fide m6A sites, we performed motif analysis. We find that variations of the DRACH and TACAG motifs, the respective consensus sequences for METTL3 and METTL16, are dramatically overrepresented in METTL3- and METTL16-dependent peaks, respectively (Figure S8a,b).(29,36,37) We also compared the overlap between these peaks and m6A sites found in introns and exons by m6A miCLIP. A significant overlap was observed for both METTL3- and METTL16-dependent peaks, which provides further evidence that the observed peaks have m6A sites (Figure S8c,d). Furthermore, a centered distribution of distances between miCLIP sites and meCLICK-Seq peaks was observed (Figure S8e,f). We also validated some of these peaks by RT-qPCR. The results echoed the findings of RNA-seq (Figure 4f). Furthermore, we observed a decrease in the intensity of meCLICK-Seq peaks in the click group, identical to the results obtained by RNA-Seq (Figure 4g). To validate the intronic results with additional, independent methods, we derived cell lines with deletions in intronic regions that correspond to METTL3- or METTL16-dependent meCLICK-Seq peaks. This was done by using CRISPR-Cas9, with dual gRNAs targeting the flanks of selected meCLICK-Seq peaks. Using m6A-RIP-qPCR, we found that cells with introns removed via CRISPR had significantly less m6A compared to cells containing empty CRISPR-Cas9 vectors (Figure 4h). Additionally, in MOLM-13 cells with either METTL3 or METTL16 knock-down, the m6A-RIP signal was selectively decreased at peaks dependent on the relevant RNA MTase, further validating the results of meCLICK-Seq (Figure 4i,j). Combined, this shows that the meCLICK-Seq peaks contain m6A sites and hold information about MTase specificity.

meCLICK-Seq Can Determine Substrates for Other RNA Methylations

Through further interrogation of meCLICK-Seq data sets we demonstrated that the method can be used for study of different types of methylation. For this aim, we compared our findings with a published data set for 7-methyl guanosine (m7G), obtained through m7G-Seq.(38) We found a significant overlap between modified mRNAs determined by the two methods, with 378 overlapping genes (Figure S9a and Supporting Table S7). Strikingly, 82 click-sensitive intronic and intergenic peaks were found to be in vicinity of m7G-Seq-determined sites, a number significantly higher than expected from a random distribution (Figure S9b,c and Supporting Table S8). Thus, meCLICK-Seq is able to probe various types of RNA methylation.

METTL16 Is Linked to Intronic Polyadenylation Sites

To better understand the presence of intronic peaks in our analysis, we decided to investigate the connection to intronic polyadenylation (IPA) given the fact that we used polyA-enriched RNA for RNA-seq analysis. IPA has been recently reported to be widespread in cancers and to inactivate certain tumor suppressors in leukemia.(39,40) To determine whether IPA is associated with the presence of m6A, we compared the positions of meCLICK-Seq peaks to IPA sites of leukemia cells identified in a published study by 3′-Seq.(39) For additional confidence, we applied very strict parameters and only considered meCLICK-Seq peaks positioned on the exact IPA site. Strikingly, significant overlap was found between METTL16- but not METTL3-dependent peaks and the IPA sites (Figure S10a,b and Supporting Table S4). Moreover, the distribution of METTL16 peaks around the IPA sites suggested a link between the two, with a large number of the peaks overlapping or being close to the IPA sites (Figure S10c). These data suggest that METTL16 has a possible role in IPA and, in turn, splicing, and also demonstrate that meCLICK-Seq can be used to interrogate methylation of low-abundance transcripts.

Conclusions

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We have designed click-degraders, small molecules that are clicked onto RNA to induce its degradation, and by using them we developed meCLICK-Seq, a powerful small-molecule-based method for the study of diverse aspects of cellular RNA methylation, including high-confidence mapping of methylation in low abundance transcripts transcribed from introns and intergenic regions. Unlike many RNA methylation sequencing methods, meCLICK-Seq is unbiased and depends strictly on the catalytic activity of RNA MTases, such that it can determine their transcript and locus specificity. The method offers the reproducibility characteristics of small-molecule-based methods, is easy to perform, and has low RNA input requirements, which make it ideal for parallel characterization of different cell types, rare purified populations, and tissues. meCLICK-Seq is perhaps the first non-microscopic method to apply click chemistry directly on cells with a quantifiable output. Antibody-based methods provide a biased picture of methylation at any given time, whereas meCLICK-Seq reports a dynamic state of methylation in a cell. Unlike most antibody-free RNA methylation mapping methods, meCLICK-Seq does not involve complex postextraction RNA modification or processing. Furthermore, this is one of the first studies that exploit functional artificial RNA modifications for a measurable biological output.
We used meCLICK-Seq to define the transcript substrates of m6A writers METTL3 and METTL16 and their overlap. We have also demonstrated that m6A is widespread in lncRNAs and intronic and intergenic regions, where it is deposited primarily by METTL16. Furthermore, we demonstrate for the first time the prevalence of m6A modification in polyadenylated introns, which have been shown to be oncogenic contributions in cancer.(39,40)
meCLICK-Seq is highly modular, and by use of suitable models and metabolic labeling it can be adapted to study of other RNA methyltransferases and demethylases as well as other RNA modifications. With a modified workflow this method could also be adapted to investigate and characterize DNA modifications. The majority of studies of RNA methylation focus on high-abundance RNA species, whereas the role of methylation in low-abundance species is largely uncharacterized owing to a lack of molecular tools. We foresee meCLICK-Seq enabling the study of RNA modifications in previously inaccessible regions of the transcriptome. Defects in intron-related mechanisms are implicated in a wide range of pathologies,(41) and much remains to be learned about the role of noncoding RNAs in disease.(42) We expect that our click-degradation platform will facilitate both fundamental and translational discoveries about the role of RNA modifications throughout the transcriptome and, in parallel, pave the way for the development of new technologies aimed to expand the capabilities of targeted nucleic acid degradation.

Experimental Section

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In Vitro Click-Degrader Functionalization Reactions

In a standard reaction, CuSO4 (final concentration 1.0 mM), tris(3-hydroxypropyltriazolylmethyl)amine (THPTA, 3.0 mM), click-degrader (2.0 mM), and the RNA oligomer (200 μM) were added to pH 7.5 or pH 3 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES, 20 mM) or pH 8.5 TRIS (100 mM) buffer supplemented with 10 mM MgCl2 and 100 mM KCl. CuAAC was initiated by adding sodium ascorbate (NaAsc, 50 mM). The reaction mixture was then incubated at 37 °C. Reactions to generate calibration curves were quenched with EDTA (12 mM) 20 min after adding NaAsc to allow complete functionalization of the RNA oligomer. Reactions involving prequenching were quenched with EDTA (12 mM) or bathocuproinedisulfonic acid (BCS, 3 mM) 20 min after adding NaAsc. After quenching, the reaction mixtures were analyzed using LCMS. For all samples, an initial concentration was calculated from analysis of an appropriate oligomer treated under click conditions for 20 min, ensuring full functionalization of propargylated oligomers. Identities of RNA species present were determined by their mass (Figure S6–S10). For nonstandard reactions, the conditions are specified in the text.

LCMS Analysis of Oligonucleotides

Oligomers were analyzed using a Xevo G2-S TOF mass spectrometer coupled to an Acquity UPLC system using an Acquity UPLC BEH C18 1.7 μm column. The system utilizes electrospray ionization (ESI). Two mobile phases were used, 16.3 mM TEA, 400 mM HFIP in H2O and 16.3 mM TEA, 400 mM HFIP in 80:20 v/v MeCN and H2O, with a flow rate of 0.200 mL/min. Calibration curves for the RNA species were based either on A260 or intensities of specified negative m/z signals (Figure S1e–h). Intensities of integrated peaks were calculated using native modules of KNIME software platform.(43) Total mass spectra were reconstructed from the ion series using the MaxEnt algorithm preinstalled on MassLynx software (v. 4.1 from Waters) according to the manufacturer’s instructions. To obtain the negative ion series described, the oligomer peak in the chromatogram was selected for integration and further analysis.

RNA Degradation Gel Electrophoresis

In vitro RNA degradation reactions were carried out as described above. The quenched reaction mixture was mixed in 1:1 ratio with a loading buffer (95% formamide, 0.025% SDS, 0.025% bromophenol blue (BPB), 0.025% xylene cyanol FF, 0.025% ethidium bromide, 0.5 mM EDTA), heated at 70 °C for 5 min, and cooled to 0 °C. PAGE was performed on NovexTM TBE-Urea Gels, containing 15% polyacrylamide under 1× TBE buffer (89 mM Tris, 89 mM boric acid, 2 mM EDTA) at 180 V for 60 min. Gel staining was performed using SYBR Green II RNA Gel Stain (Invitrogen) in 1× TBE buffer. The stained RNA was visualized with ChemiDoc MP (Bio-Rad, United Kingdom).

Cell Culture

MOLM13 cells were cultured in RPMI1640 (Gibco) supplemented with 10% v/v FBS and 1% v/v penicillin/streptomycin/l-glutamine. 293T cells were cultured in DMEM (Gibco) supplemented with 10% v/v FBS and 1% v/v penicillin/streptomycin/l-glutamine.

Lentiviral Vector Production, Infection, and Transfection

For virus production, 293T cells were transfected with lentiviral vector pLKO.1 together with the packaging plasmids PAX2 and VSVg at a 1:1.5:0.5 ratio. Supernatant was harvested 48 and 72 h after transfection. Cells (1 × 106) and viral supernatant were mixed in 2 mL of culture medium supplemented with 8 μg mL–1 Polybrene (Millipore), followed by spinfection (60 min, 900g, 32 °C), and further incubated overnight at 37 °C. The medium was refreshed on the following day, and the transduced cells were further cultured.

Generation of Conditional Knock-down and Intronic Deletion-Containing Cells

MOLM-13 cells were transfected using Lipofectamine 2000 reagent (Invitrogen) according to the manufacturer’s instructions using pLKO-TETon-Puro lentiviral vectors expressing shRNAs against the coding sequence of human METTL3, METTL16, or a scrambled control. Twenty-four hours after spinfection, the cells were replated in fresh medium containing 1 μg mL–1 of puromycin and kept in selection medium for 7 days. Anti-METTL3 and scrambled shRNAs were induced by treating the cells with 200 ng mL–1 tetracycline for 3 days, anti-METTL16 was induced by identical treatment for 2 days.
gRNA assays were performed using dual gRNA vectors as reported previously.(44) Viral supernatants were collected 48 h after transfection. All transfections and viral collections were performed in 15 cm plates as mentioned below. For virus production, 5 μg of the above plasmids and 5 μg of psi-Eco packaging vector were transfected dropwise into the 293T cells using 47.5 μL TransIT LT1 (Mirus) and 600 μL of Opti-MEM (Invitrogen). The resulting viral supernatant was harvested, and transduction of cells was performed in 6-well plates. After transduction, transduced cells were sorted for BFP (for gRNA). The gRNA sequences are listed in Table S12.

Cellular RNA Degradation Reactions (meCLICK-Seq)

MOLM13 cells were suspended in methionine-free RPMI-1640 media (Gibco) supplemented with 10% v/v FBS and 1% v/v penicillin/streptomycin/l-glutamine at a density of 1 000 000 cells mL–1. The cells were incubated for 30 min at 37 °C followed by addition of PropSeMet at a final concentration of 150 μM. Treated cells were incubated for further 16 h at 37 °C. Aqueous solutions of premixed CuSO4 and THPTA were added at final concentrations of 100 and 300 μM, respectively, followed by the click-degrader 1 at 400 μM and NaAsc at 5 mM. Treated cells were incubated for 10 min at 37 °C and resuspended in complete RPMI-1640 medium. Afterward, the cells were again incubated at 37 °C and harvested after 5 h for RNA extraction.

m6A RNA Immunoprecipitation

Total RNA was isolated from MOLM-13 control, Δintronic, METTL3-KD, or METTL16-KD cells (two independent biological replicates for each shRNA) 8 days after doxycycline administration using the RNAeasy midi kit (Qiagen). Successively polyA enriched RNA was purified from 300 μg of total RNA using the NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs). For each immunoprecipitation reaction, 500 ng of polyA+ purified RNA was used. m6A RNA immunoprecipitation was performed using the Magna MeRIP m6A kit (Millipore) according to the manufacturer’s instructions. Immunoprecipitated RNA was analyzed via RT-qPCR.

RNA Extraction, Reverse Transcription, and RT-qPCR

Total RNA was extracted from pelleted cells using RNAeasy Mini Kit (Qiagen) according to the manufacturer’s instructions. Twenty micrograms of total RNA was enriched for polyA-containing sequences using Dynabeads mRNA purification kit (Invitrogen) according to the manufacturer’s instructions. One microgram of total RNA and all of the polyA-enriched RNA from the previous step were retrotranscribed using SuperScript Vilo Master Mix (Invitrogen) according the to manufacturer’s instructions. Levels of specific RNAs were measured using fast mode of StepOnePlus Real-Time PCR System (Applied Biosystems) and Fast SYBR Green Master Mix (Applied Biosystems) according to the manufacturer’s instructions. For reactions where total RNA was used, RNA levels were normalized to 18S subunit of the ribosome. For reactions where polyA-enriched RNA was used, RNA levels were normalized to RPL32 mRNA. These housekeeping genes were chosen as their levels fluctuated the least under various conditions tested. Primer sequences are listed below.

Statistical Analysis

General statistical analyses were carried out using a one-sided (in cases where we were interested only in a decrease of signal in the treated group) or two-sided Student’s t test at a confidence interval of 95%.

Protein Extraction and Immunoblotting

The cells were lysed in whole-cell lysis buffer (50 mM Tris-HCl, pH 8, 150 mM NaCl, 0.1% NP-40, and 1 mM EDTA) supplemented with 1 mM DTT, protease inhibitors (Sigma), and phosphatase inhibitors (Sigma). Protein quantities were estimated with Bradford assays (Bio-Rad). The protein samples were supplemented with SDS–PAGE sample buffer, and DTT was added to each sample. Protein (10–40 μg) was separated on a 4–12% Bis-Tris SDS–PAGE gel (Invitrogen) with a same amount of protein added to each track of a gel and blotted onto poly(vinylidene difluoride) membranes (Millipore). Visualization was performed using LumiGLO Chemiluminescent Substrate (KPL, 54-61-00) and X-ray film (GE Healthcare). The following antibodies were used: anti-METTL3 from Bethyl Laboratories (A301-568A), anti-METTL16 from Abcam (ab185990), anti-β-actin from Abcam (ab8227), goat anti-rabbit IgG H&L (HRP) from Abcam (ab205718).

HPLC-MS/MS Analysis of RNA

Up to 10 μg of poly(A) RNA was decapped with Cap-Clip Acid Pyrophosphatase (Cellscript) for 90 min at 37 °C, then digested with 100 U of P1 nuclease (New England Biolabs) at 37 °C overnight and dephosphorylated with 1 U of rSAP (New England Biolabs) at 37 °C for 1 h. The 100 μL samples were filtered with Millex-GV 0.22 μm filters (Millipore Sigma). Five to ten microliters from each sample was injected into the Agilent 6470 Triple Quad LC/MS instrument with Agilent Zorbax Eclipse C18 reverse phase HPLC column. The samples were run at 500 μL/min flow rate in mobile phase buffer A (water with 0.1% formic acid) and 0–20% gradient of buffer B (methanol with 0.1% formic Acid). MRM transitions were measured for adenosine (268.1 to 136.1), guanosine (284.1 to 152.1), and Pr6A (306.1 to 174.1). Standard compound for Pr6A was run on HLPC-MS/MS to optimize the HPLC method and determine retention times. For LC-MS/MS data collection and analysis, Agilent Mass Hunter LC/MS Data Acquisition, version B.08.00, and Quantitative Analysis, version B.07.01, software were used.

Biotin Pull-down Experiment

RNA was extracted from PropSeMet treated MOLM13 cells as described above. CuAAC reaction was then performed in 20 mM HEPES (pH 7.5) on 7 μg of RNA, 20 μM azide-PEG3–biotin conjugate (Sigma-Aldrich), 5 mM CuSO4, 15 mM THPTA, and 5 mM NaAsc, to a final volume of 100 μL. After initiating the reaction with NaAsc, the mixture was stirred at 37 °C for 30 min, followed by quenching of the reaction with 6 mM EDTA. Biotinylated RNA was then precipitated with EtOH and redissolved in 30 μL of nuclease-free water. Streptavidin pull-down was carried out using streptavidin beads (Invitrogen) according to the manufacturer’s instructions. RNA was then analyzed via RT-qPCR as described above with abundance of each transcript in the pulled-down RNA compared to corresponding input RNA.

Bioinformatic Analysis

Total RNA was extracted from pelleted cells using RNAeasy Mini Kit (Qiagen) according to the manufacturer’s instructions. RNaseq data from all experiments consisting of 75 bp paired-end Illumina reads were mapped to the human genome assembly GRCh38 by STAR 2.7.1b,(45) using arguments “--outSAMunmapped Within KeepPairs --outFilterIntronMotifs RemoveNoncanonicalUnannotated --chimSegmentMin 0 --chimJunctionOverhangMin 20”. BigWig files were produced by deepTools 3.3.2(46) bamCoverage using RPKM normalization. Exonic reads were removed using the intersect function in Bedtools, v2.29.0,(47) and exon regions derived from the Ensembl GRCh38, version 93. Reads on the forward strand were extracted using Samtools 1.9,(48) with “view -f 128 -F 16” and “-f 80” and merged into one file. Reads on the reverse strand were extracted using “view -f 144” and “-f 64 -F 16” and merged. Broad peaks were called by MACS2 2.1.4,(49) using WT as treatment and METTL16/METTL3 as control, with arguments “callpeak --broad --extsize = 300 --keep-dup 20 --nomodel -g hs --broad-cutoff 0.9 --max-gap 500”. Intersection of peaks between the two replicates was taken. Peaks that show reduced signals in meCLICK-Seq compared to WT were selected as the final set.
To search for motifs, DNA sequences of peaks were extracted from the GRCh38 genomic FASTA file. Motifs were discovered by MEME-chip 5.0.5(50) using parameters “-meme-nmotifs 30”. For gene quantification, exonic regions were obtained from Ensembl GRCh38, version 93. Number of reads in each exon was calculated by customized code and normalized by RPKM. To counter the 3′ bias, the level of the most 3′ exon was used as expression of the gene.
m6A sites were analyzed by first mapping Reads from the miCLIP experiments to the GRCh38 assembly using STAR 2.7.1a(45) with arguments “--outFilterMismatchNoverReadLmax 0.05 --alignIntronMax 0”. Forward and reverse genomic-coverage tracks were subsequently produced by the bamCoverage function in deepTools 3.3.2(46) with arguments “--normalizeUsing None --filterRNAstrand forward” and “--normalizeUsing None --filterRNAstrand reverse” respectively. Regions with nonzero coverage were extracted by customized codes. Sites called from 4 miCLIP runs were merged into a union set, and the ones also present in the input data were removed.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acscentsci.0c01094.

  • Putative mass spectra peaks for the 11-mer after 2 hour degradation and for the functionalized and BCS-quenched 11-mer after 14 hour degradation, detected RNA species, oligomers used for the in vitro study, list of primers and gRNAs, analysis of propargylated and non-propargylated RNA oligomers degradation by click-degrader, predicted structures of oligomers used, analyses of CTRL and Prop oligomers, analysis of mRNA and lncRNA species, examples of intronic peak snapshots, analyses of METTL3- and METTL16-dependent peaks, comparison of methylated mRNAs determined via meCLICK-Seq and m7G-Seq, analysis of MeCLICK-Seq peaks and IPA sites, mass spectra of functionalized 11-mer species, and chemical synthesis and characterization including NMR spectra (PDF)

  • METTL3 and METTL16 mRNA substrates determined via meCLICK-Seq (TXT)

  • Results of a miCLIP study of m6A in MOLM13 cells (XLSX)

  • METTL3 and METTL16 lncRNA substrates determined via meCLICK-Seq (TXT)

  • METTL13 and METTL16-dependent intronic/intergenic peaks determined via meCLICK-Seq (XLSX)

  • Methylated mRNA species determined via meCLICK-Seq with an overlap with m7G-Seq study (XLSX)

  • Intronic and intergenic click-degrader sensitive RNA peaks with an overlap with m7G-Seq study (XLSX)

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Author Information

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  • Corresponding Authors
    • Konstantinos Tzelepis - Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, U.K.; Boston Childrens’ Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, Massachusetts 02115, United States; Milner Therapeutics Institute, University of Cambridge, Puddicombe Way, Cambridge CB2 0AW, U.K.; Orcidhttp://orcid.org/0000-0002-4865-7648; Email: [email protected]
    • Gonçalo J. L. Bernardes - Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.; Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Avenida Professor Egas Moniz, 1649-028 Lisboa, Portugal; Orcidhttp://orcid.org/0000-0001-6594-8917; Email: [email protected]
  • Authors
    • Sigitas Mikutis - Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.
    • Muxin Gu - Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, U.K.
    • Erdem Sendinc - Boston Childrens’ Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
    • Madoka E. Hazemi - Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.
    • Hannah Kiely-Collins - Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.
    • Demetrios Aspris - Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, U.K.; The Center for the Study of Haematological Malignancies, Karaiskakio Foundation, Nicandrou Papamina Avenue, 2032 Nicosia, Cyprus
    • George S. Vassiliou - Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, U.K.; The Center for the Study of Haematological Malignancies, Karaiskakio Foundation, Nicandrou Papamina Avenue, 2032 Nicosia, Cyprus; Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Puddicombe Way, Cambridge CB2 0AW, U.K.
    • Yang Shi - Boston Childrens’ Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, Massachusetts 02115, United States; Ludwig Institute for Cancer Research, Oxford University, Old Road Campus Research Build, Roosevelt Dr., Oxford OX3 7DQ, U.K.
  • Notes

    The authors declare the following competing financial interest(s): S.M., K.T., and G.J.L.B. are co-inventors on a patent application that incorporates discoveries described in this manuscript. All other authors declare no conflict of interests.

Acknowledgments

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We thank UKRI (BBSRC DTP scholarships to S.M. and H.K.C) and the Jardine Foundation and Cambridge Trust (Ph.D. scholarship to M.E.H.). K.T. was funded by a Wellcome Trust Sir Henry Wellcome Fellowship (grant reference RG94424). G.S.V. is funded by a Cancer Research UK Senior Cancer Fellowship (C22324/A23015). Research in the Shi lab is supported by Ludwig Institute for Cancer Research. Y.S. is American Cancer Society Research Professor. G.J.L.B. is a Royal Society University Research Fellow (URF\R\180019) and an FCT Investigator (IF/00624/2015). We thank Dr. Vikki Cantrill for her help with the editing of this manuscript.

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    Cox, D. B. T.; Gootenberg, J. S.; Abudayyeh, O. O.; Franklin, B.; Kellner, M. J.; Joung, J.; Zhang, F. RNA editing with CRISPR-Cas13. Science 2017, 358 (6366), 1019,  DOI: 10.1126/science.aaq0180
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    6
    RNA editing with CRISPR-Cas13
    Cox, David B. T.; Gootenberg, Jonathan S.; Abudayyeh, Omar O.; Franklin, Brian; Kellner, Max J.; Joung, Julia; Zhang, Feng
    Science (Washington, DC, United States) (2017), 358 (6366), 1019-1027CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
    Nucleic acid editing holds promise for treating genetic disease, particularly at the RNA level, where disease-relevant sequences can be rescued to yield functional protein products. Type VI CRISPR-Cas systems contain the programmable single-effector RNA-guided RNase Cas13. We profiled type VI systems in order to engineer a Cas13 ortholog capable of robust knockdown and demonstrated RNA editing by using catalytically inactive Cas13 (dCas13) to direct adenosine-to-inosine deaminase activity by ADAR2 (adenosine deaminase acting on RNA type 2) to transcripts in mammalian cells. This system, referred to as RNA editing for programmable A to I replacement (REPAIR), which has no strict sequence constraints, can be used to edit full-length transcripts contg. pathogenic mutations. We further engineered this system to create a high-specificity variant and minimized the system to facilitate viral delivery. REPAIR presents a promising RNA-editing platform with broad applicability for research, therapeutics, and biotechnol.
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  7. 7
    Costales, M. G.; Matsumoto, Y.; Velagapudi, S. P.; Disney, M. D. Small Molecule Targeted Recruitment of a Nuclease to RNA. J. Am. Chem. Soc. 2018, 140 (22), 6741– 6744,  DOI: 10.1021/jacs.8b01233
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    7
    Small Molecule Targeted Recruitment of a Nuclease to RNA
    Costales, Matthew G.; Matsumoto, Yasumasa; Velagapudi, Sai Pradeep; Disney, Matthew D.
    Journal of the American Chemical Society (2018), 140 (22), 6741-6744CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
    The choreog. between RNA synthesis and degrdn. is a key determinant in biol. Engineered systems such as CRISPR have been developed to rid a cell of RNAs. Here, we show that a small mol. can recruit a nuclease to a specific transcript, triggering its destruction. A small mol. that selectively binds the oncogenic microRNA(miR)-96 hairpin precursor was appended with a short 2'-5' poly(A) oligonucleotide. The conjugate locally activated endogenous, latent RNase (RNase L), which selectively cleaved the miR-96 precursor in cancer cells in a catalytic fashion. Silencing miR-96 de-repressed pro-apoptotic FOXO1 transcription factor, triggering apoptosis in breast cancer, but not healthy breast, cells. These results demonstrate that small mols. can be programmed to selectively cleave RNA and has broad implications.
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  8. 8
    Li, Y.; Disney, M. D. Precise Small Molecule Degradation of a Noncoding RNA Identifies Cellular Binding Sites and Modulates an Oncogenic Phenotype. ACS Chem. Biol. 2018, 13 (11), 3065– 3071,  DOI: 10.1021/acschembio.8b00827
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    8
    Precise Small Molecule Degradation of a Noncoding RNA Identifies Cellular Binding Sites and Modulates an Oncogenic Phenotype
    Li, Yue; Disney, Matthew D.
    ACS Chemical Biology (2018), 13 (11), 3065-3071CODEN: ACBCCT; ISSN:1554-8929. (American Chemical Society)
    Herein, we describe the precise cellular destruction of an oncogenic noncoding RNA with a small mol.-bleomycin A5 conjugate, affording reversal of phenotype and a facile method to map the cellular binding sites of a small mol. In particular, bleomycin A5 was coupled to a small mol. that selectively binds the microRNA-96 hairpin precursor (pri-miR-96). By coupling of bleomycin A5's free amine to the RNA binder, its affinity for binding to pri-miR-96 is >100-fold stronger than to DNA and the compd. selectively cleaves pri-miR-96 in triple neg. breast cancer (TNBC) cells. Indeed, selective cleavage of pri-miR-96 enhanced expression of FOXO1 protein, a pro-apoptotic transcription factor that miR-96 silences, and triggered apoptosis in TNBC cells. No effects were obsd. in healthy breast epithelial cells. Thus, conjugation to bleomycin A5's free amine may provide programmable control over its cellular targets. Few approaches are available to define the binding sites of small mols. within cellular RNAs. Our targeted cleavage approach provides such an approach that is straightforward to implement. That is, we detd. exptl. the site cleaved within pri-miR-96 in vitro and in cells; these studies revealed that the site of cleavage is the precise site for which the small mol. cleaver was designed and in agreement with modeling. These studies demonstrate the potential of sequence-based design to provide bioactive compds. that precisely recognize and cleave RNA in cells.
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  9. 9
    Tomkuviene, M.; Clouet-d’Orval, B.; Cerniauskas, I.; Weinhold, E.; Klimasauskas, S. Programmable sequence-specific click-labeling of RNA using archaeal box C/D RNP methyltransferases. Nucleic Acids Res. 2012, 40 (14), 6765– 6773,  DOI: 10.1093/nar/gks381
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    9
    Programmable sequence-specific click-labeling of RNA using archaeal box C/D RNP methyltransferases
    Tomkuviene, Migle; Clouet-d'Orval, Beatrice; Cerniauskas, Ignas; Weinhold, Elmar; Klimasauskas, Saulius
    Nucleic Acids Research (2012), 40 (14), 6765-6773CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
    Biophys. and mechanistic investigation of RNA function requires site-specific incorporation of spectroscopic and chem. probes, which is difficult to achieve using current technologies. We have in vitro reconstituted a functional box C/D small ribonucleoprotein RNA 2'-O-methyltransferase (C/D RNP) from the thermophilic archaeon Pyrococcus abyssi and demonstrated its ability to transfer a prop-2-ynyl group from a synthetic cofactor analog to a series of preselected target sites in model tRNA and pre-mRNA mols. Target selection of the RNP was programmed by changing a dodecanucleotide guide sequence in a 64-nt C/D guide RNA leading to efficient derivatization of three out of four new targets in each RNA substrate. We also show that the transferred terminal alkyne can be further appended with a fluorophore using a bioorthogonal azide-alkyne 1,3-cycloaddn. (click) reaction. The described approach for the first time permits synthetically tunable sequence-specific labeling of RNA with single-nucleotide precision.
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  10. 10
    Meyer, K. D.; Saletore, Y.; Zumbo, P.; Elemento, O.; Mason, C. E.; Jaffrey, S. R. Comprehensive analysis of mRNA methylation reveals enrichment in 3′ UTRs and near stop codons. Cell 2012, 149 (7), 1635– 1646,  DOI: 10.1016/j.cell.2012.05.003
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    10
    Comprehensive analysis of mRNA methylation reveals enrichment in 3' UTRs and near stop codons
    Meyer, Kate D.; Saletore, Yogesh; Zumbo, Paul; Elemento, Olivier; Mason, Christopher E.; Jaffrey, Samie R.
    Cell (Cambridge, MA, United States) (2012), 149 (7), 1635-1646CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
    Methylation of the N6 position of adenosine (m6A) is a posttranscriptional modification of RNA with poorly understood prevalence and physiol. relevance. The recent discovery that FTO, an obesity risk gene, encodes an m6A demethylase implicates m6A as an important regulator of physiol. processes. Here, we present a method for transcriptome-wide m6A localization, which combines m6A-specific methylated RNA immunopptn. with next-generation sequencing (MeRIP-Seq). We use this method to identify mRNAs of 7676 mammalian genes that contain m6A, indicating that m6A is a common base modification of mRNA. The m6A modification exhibits tissue-specific regulation and is markedly increased throughout brain development. We find that m6A sites are enriched near stop codons and in 3' UTRs, and we uncover an assocn. between m6A residues and microRNA-binding sites within 3' UTRs. These findings provide a resource for identifying transcripts that are substrates for adenosine methylation and reveal insights into the epigenetic regulation of the mammalian transcriptome.
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  11. 11
    Dominissini, D.; Moshitch-Moshkovitz, S.; Schwartz, S.; Salmon-Divon, M.; Ungar, L.; Osenberg, S.; Cesarkas, K.; Jacob-Hirsch, J.; Amariglio, N.; Kupiec, M.; Sorek, R.; Rechavi, G. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 2012, 485 (7397), 201– 206,  DOI: 10.1038/nature11112
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    11
    Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq
    Dominissini, Dan; Moshitch-Moshkovitz, Sharon; Schwartz, Schraga; Salmon-Divon, Mali; Ungar, Lior; Osenberg, Sivan; Cesarkas, Karen; Jacob-Hirsch, Jasmine; Amariglio, Ninette; Kupiec, Martin; Sorek, Rotem; Rechavi, Gideon
    Nature (London, United Kingdom) (2012), 485 (7397), 201-206CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
    An extensive repertoire of modifications is known to underlie the versatile coding, structural and catalytic functions of RNA, but it remains largely uncharted territory. Although biochem. studies indicate that N6-methyladenosine (m6A) is the most prevalent internal modification in mRNA, an in-depth study of its distribution and functions has been impeded by a lack of robust anal. methods. Here, we present the human and mouse m6A modification landscape in a transcriptome-wide manner, using a novel approach, m6A-seq, based on antibody-mediated capture and massively parallel sequencing. We identify over 12,000 m6A sites characterized by a typical consensus in the transcripts of more than 7,000 human genes. Sites preferentially appear in two distinct landmarks-around stop codons and within long internal exons-and are highly conserved between human and mouse. Although most sites are well preserved across normal and cancerous tissues and in response to various stimuli, a subset of stimulus-dependent, dynamically modulated sites is identified. Silencing the m6A methyltransferase significantly affects gene expression and alternative splicing patterns, resulting in modulation of the p53 (also known as TP53) signalling pathway and apoptosis. Our findings therefore suggest that RNA decoration by m6A has a fundamental role in regulation of gene expression.
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  12. 12
    Linder, B.; Grozhik, A. V.; Olarerin-George, A. O.; Meydan, C.; Mason, C. E.; Jaffrey, S. R. Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nat. Methods 2015, 12 (8), 767– 772,  DOI: 10.1038/nmeth.3453
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    12
    Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome
    Linder, Bastian; Grozhik, Anya V.; Olarerin-George, Anthony O.; Meydan, Cem; Mason, Christopher E.; Jaffrey, Samie R.
    Nature Methods (2015), 12 (8), 767-772CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)
    N6-methyladenosine (m6A) is the most abundant modified base in eukaryotic mRNA and has been linked to diverse effects on mRNA fate. Current mapping approaches localize m6A residues to transcript regions 100-200 nt long but cannot identify precise m6A positions on a transcriptome-wide level. Here we developed m6A individual-nucleotide-resoln. crosslinking and immunopptn. (miCLIP) and used it to demonstrate that antibodies to m6A can induce specific mutational signatures at m6A residues after UV light-induced antibody-RNA crosslinking and reverse transcription. We found that these antibodies similarly induced mutational signatures at N6,2'-O-dimethyladenosine (m6Am), a modification found at the first nucleotide of certain mRNAs. Using these signatures, we mapped m6A and m6Am at single-nucleotide resoln. in human and mouse mRNA and identified small nucleolar RNAs (snoRNAs) as a new class of m6A-contg. non-coding RNAs (ncRNAs).
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  13. 13
    Zhang, Z.; Chen, L.-Q.; Zhao, Y.-L.; Yang, C.-G.; Roundtree, I. A.; Zhang, Z.; Ren, J.; Xie, W.; He, C.; Luo, G.-Z. Single-base mapping of m6A by an antibody-independent method. Sci. Adv. 2019, 5 (7), eaax0250,  DOI: 10.1126/sciadv.aax0250
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    Meyer, K. D. DART-seq: an antibody-free method for global m6A detection. Nat. Methods 2019, 16 (12), 1275– 1280,  DOI: 10.1038/s41592-019-0570-0
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    14
    DART-seq: an antibody-free method for global m6A detection
    Meyer, Kate D.
    Nature Methods (2019), 16 (12), 1275-1280CODEN: NMAEA3; ISSN:1548-7091. (Nature Research)
    N6-methyladenosine (m6A) is a widespread RNA modification that influences nearly every aspect of the mRNA lifecycle. Our understanding of m6A has been facilitated by the development of global m6A mapping methods, which use antibodies to immunoppt. methylated RNA. However, these methods have several limitations, including high input RNA requirements and cross-reactivity to other RNA modifications. Here, we present DART-seq (deamination adjacent to RNA modification targets), an antibody-free method for detecting m6A sites. In DART-seq, the cytidine deaminase APOBEC1 is fused to the m6A-binding YTH domain. APOBEC1-YTH expression in cells induces C-to-U deamination at sites adjacent to m6A residues, which are detected using std. RNA-seq. DART-seq identifies thousands of m6A sites in cells from as little as 10 ng of total RNA and can detect m6A accumulation in cells over time. Addnl., we use long-read DART-seq to gain insights into m6A distribution along the length of individual transcripts.
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  15. 15
    Wang, Y.; Xiao, Y.; Dong, S.; Yu, Q.; Jia, G. Antibody-free enzyme-assisted chemical approach for detection of N6-methyladenosine. Nat. Chem. Biol. 2020, 16 (8), 896– 903,  DOI: 10.1038/s41589-020-0525-x
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    15
    Antibody-free enzyme-assisted chemical approach for detection of N6-methyladenosine
    Wang, Ye; Xiao, Yu; Dong, Shunqing; Yu, Qiong; Jia, Guifang
    Nature Chemical Biology (2020), 16 (8), 896-903CODEN: NCBABT; ISSN:1552-4450. (Nature Research)
    The inert chem. property of RNA modification N6-methyladenosine (m6A) makes it very challenging to detect. Most m6A sequencing methods rely on m6A-antibody immunopptn. and cannot distinguish m6A and N6,2'-O-dimethyladenosine modification at the cap +1 position (cap m6Am). Although the two antibody-free methods (m6A-REF-seq/MAZTER-seq and DART-seq) have been developed recently, they are dependent on m6A sequence or cellular transfection. Here, the authors present an antibody-free, FTO-assisted chem. labeling method termed m6A-SEAL for specific m6A detection. The authors applied m6A-SEAL to profile m6A landscapes in humans and plants, which displayed the known m6A distribution features in transcriptome. By doing a comparison with all available m6A sequencing methods and specific m6A sites validation by SELECT, m6A-SEAL has good sensitivity, specificity and reliability for transcriptome-wide detection of m6A. Given its tagging ability and FTO's oxidn. property, m6A-SEAL enables many applications such as enrichment, imaging and sequencing to drive future functional studies of m6A and other modifications.
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  16. 16
    Hartstock, K.; Nilges, B. S.; Ovcharenko, A.; Cornelissen, N. V.; Püllen, N.; Lawrence-Dörner, A.-M.; Leidel, S. A.; Rentmeister, A. Enzymatic or In Vivo Installation of Propargyl Groups in Combination with Click Chemistry for the Enrichment and Detection of Methyltransferase Target Sites in RNA. Angew. Chem., Int. Ed. 2018, 57 (21), 6342– 6346,  DOI: 10.1002/anie.201800188
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    16
    Enzymatic or In Vivo Installation of Propargyl Groups in Combination with Click Chemistry for the Enrichment and Detection of Methyltransferase Target Sites in RNA
    Hartstock, Katja; Nilges, Benedikt S.; Ovcharenko, Anna; Cornelissen, Nicolas V.; Puellen, Nikolai; Lawrence-Doerner, Ann-Marie; Leidel, Sebastian A.; Rentmeister, Andrea
    Angewandte Chemie, International Edition (2018), 57 (21), 6342-6346CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)
    N6-methyladenosine (m6A) is the most abundant internal modification in eukaryotic mRNA. It is introduced by METTL3-METTL14 and tunes mRNA metab., impacting cell differentiation and development. Precise transcriptome-wide assignment of m6A sites is of utmost importance. However, m6A does not interfere with Watson-Crick base pairing, making polymerase-based detection challenging. We developed a chem. biol. approach for the precise mapping of methyltransferase (MTase) target sites based on the introduction of a bioorthogonal propargyl group in vitro and in cells. We show that propargyl groups can be introduced enzymically by wild-type METTL3-METTL14. Reverse transcription terminated up to 65 % at m6A sites after bioconjugation and purifn., hence enabling detection of METTL3-METTL14 target sites by next generation sequencing. Importantly, we implemented metabolic propargyl labeling of RNA MTase target sites in vivo based on propargyl-L-selenohomocysteine and validated different types of known rRNA methylation sites.
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    Raines, R. T. Ribonuclease A. Chem. Rev. 1998, 98 (3), 1045– 1066,  DOI: 10.1021/cr960427h
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    17
    Ribonuclease A
    Raines, Ronald T.
    Chemical Reviews (Washington, D. C.) (1998), 98 (3), 1045-1065CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
    A review with 420 refs., of the structure and function of RNase A, with emphasis on applications of recombinant DNA technol. and nucleic acid chem.
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    Cheng, L.; Abhilash, K. G.; Breslow, R. Binding and biomimetic cleavage of the RNA poly(U) by synthetic polyimidazoles. Proc. Natl. Acad. Sci. U. S. A. 2012, 109 (32), 12884,  DOI: 10.1073/pnas.1210846109
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    18
    Binding and biomimetic cleavage of the RNA poly(U) by synthetic polyimidazoles
    Cheng, Liang; Abhilash, K. G.; Breslow, Ronald
    Proceedings of the National Academy of Sciences of the United States of America (2012), 109 (32), 12884-12887, S12884/1-S12884/5CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    Four polyimidazoles were used in the binding and cleavage studies with poly(U). The two polydisperse polyvinylimidazoles were previously described by others, while the other two new polymers of polyethyleneimines were prepd. by cationic polymn. of oxazolines. The latter had imidazole units attached to each nitrogen of the polymers. They were characterized by gel permeation chromatog. and had very low polydispersities. When they were partially protonated they bound to the poly(U) and catalyzed its cleavage by a process analogous to that used by the enzyme RNase A. The kinetics of the cleavage were followed by an assay we had previously described using phosphodiesterase I from Crotalus venom after the cleavage processes. Cleavage of poly(U) with Zn2+ was also examd., with and without the polymers. A scheme is described in which these cleavages could be made sequence selective with various RNAs, particularly with important targets, such as viral RNAs.
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    Beloglazova, N. G.; Fabani, M. M.; Zenkova, M. A.; Bichenkova, E. V.; Polushin, N. N.; Sil’nikov, V. V.; Douglas, K. T.; Vlassov, V. V. Sequence-specific artificial ribonucleases. I. Bis -imidazole-containing oligonucleotide conjugates prepared using precursor-based strategy. Nucleic Acids Res. 2004, 32 (13), 3887– 3897,  DOI: 10.1093/nar/gkh702
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    19
    Sequence-specific artificial ribonucleases. I. Bis-imidazole-containing oligonucleotide conjugates prepared using precursor-based strategy
    Beloglazova, Natalia G.; Fabani, Martin M.; Zenkova, Marina A.; Bichenkova, Elena V.; Polushin, Nikolai N.; Sil'nikov, Vladimir V.; Douglas, Kenneth T.; Vlassov, Valentin V.
    Nucleic Acids Research (2004), 32 (13), 3887-3897CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
    Antisense oligonucleotide conjugates, bearing constructs with two imidazole residues, were synthesized using a precursor-based technique employing post-synthetic histamine functionalization of oligonucleotides bearing methoxyoxalamido precursors at the 5'-termini. The conjugates were assessed in terms of their cleavage activities using both biochem. assays and conformational anal. by mol. modeling. The oligonucleotide part of the conjugates was complementary to the T-arm of yeast tRNAPhe (44-60 nt) and was expected to deliver imidazole groups near the fragile sequence C61-ACA-G65 of the tRNA. The conjugates showed RNase activity at neutral pH and physiol. temp. resulting in complete cleavage of the target RNA, mainly at the C63-A64 phosphodiester bond. For some constructs, cleavage was completed within 1-2 h under optimal conditions. Mol. modeling was used to det. the preferred orientation(s) of the cleaving group(s) in the complexes of the conjugates with RNA target. Cleaving constructs bearing two imidazole residues were found to be conformationally highly flexible, adopting no preferred specific conformation. No interactions other than complementary base pairing between the conjugates and the target were found to be the factors stabilizing the active cleaving conformation(s).
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  20. 20
    Li, Z.-R.; Li, J.; Cai, W.; Lai, J. Y. H.; McKinnie, S. M. K.; Zhang, W.-P.; Moore, B. S.; Zhang, W.; Qian, P.-Y. Macrocyclic colibactin induces DNA double-strand breaks via copper-mediated oxidative cleavage. Nat. Chem. 2019, 11 (10), 880– 889,  DOI: 10.1038/s41557-019-0317-7
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    20
    Macrocyclic colibactin induces DNA double-strand breaks via copper-mediated oxidative cleavage
    Li, Zhong-Rui; Li, Jie; Cai, Wenlong; Lai, Jennifer Y. H.; McKinnie, Shaun M. K.; Zhang, Wei-Peng; Moore, Bradley S.; Zhang, Wenjun; Qian, Pei-Yuan
    Nature Chemistry (2019), 11 (10), 880-889CODEN: NCAHBB; ISSN:1755-4330. (Nature Research)
    Colibactin is an assumed human gut bacterial genotoxin, whose biosynthesis is linked to the clb genomic island that has a widespread distribution in pathogenic and commensal human enterobacteria. Colibactin-producing gut microbes promote colon tumor formation and enhance the progression of colorectal cancer via cellular senescence and death induced by DNA double-strand breaks (DSBs); however, the chem. basis that contributes to the pathogenesis at the mol. level has not been fully characterized. Here, the authors report the discovery of colibactin-645, a macrocyclic colibactin metabolite that recapitulates the previously assumed genotoxicity and cytotoxicity. Colibactin-645 shows strong DNA DSB activity in vitro and in human cell cultures via a unique copper-mediated oxidative mechanism. The authors also delineate a complete biosynthetic model for colibactin-645, which highlights a unique fate of the aminomalonate-building monomer in forming the C-terminal 5-hydroxy-4-oxazolecarboxylic acid moiety through the activities of both the polyketide synthase ClbO and the amidase ClbL. This work thus provides a mol. basis for colibactin's DNA DSB activity and facilitates further mechanistic study of colibactin-related colorectal cancer incidence and prevention.
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  21. 21
    Peterson, J. R.; Thor, S.; Kohler, L.; Kohler, P. R. A.; Metcalf, W. W.; Luthey-Schulten, Z. Genome-wide gene expression and RNA half-life measurements allow predictions of regulation and metabolic behavior in Methanosarcina acetivorans. BMC Genomics 2016, 17, 924,  DOI: 10.1186/s12864-016-3219-8
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    21
    Genome-wide gene expression and RNA half-life measurements allow predictions of regulation and metabolic behavior in Methanosarcina acetivorans
    Peterson, Joseph R.; Thor, Sheng Shee; Kohler, Lars; Kohler, Petra R. A.; Metcalf, William W.; Luthey-Schulten, Zaida
    BMC Genomics (2016), 17 (), 924/1-924/23CODEN: BGMEET; ISSN:1471-2164. (BioMed Central Ltd.)
    While a few studies on the variations in mRNA expression and half-lives measured under different growth conditions have been used to predict patterns of regulation in bacterial organisms, the extent to which this information can also play a role in defining metabolic phenotypes has yet to be examd. systematically. Here we present the first comprehensive study for a model methanogen. We use expression and half-life data for the methanogen Methanosarcina acetivorans growing on fast- and slow-growth substrates to examine the regulation of its genes. Unlike Escherichia coli where only small shifts in half-lives were obsd., we found that most mRNA have significantly longer half-lives for slow growth on acetate compared to fast growth on methanol or trimethylamine. Interestingly, half-life shifts are not uniform across functional classes of enzymes, suggesting the existence of a selective stabilization mechanism for mRNAs. Using the transcriptomics data we detd. whether transcription or degrdn. rate controls the change in transcript abundance. Degrdn. was found to control abundance for about half of the metabolic genes underscoring its role in regulating metab. Genes involved in half of the metabolic reactions were found to be differentially expressed among the substrates suggesting the existence of drastically different metabolic phenotypes that extend beyond just the methanogenesis pathways. By integrating expression data with an updated metabolic model of the organism (iST807) significant differences in pathway flux and prodn. of metabolites were predicted for the three growth substrates. This study provides the first global picture of differential expression and half-lives for a class II methanogen, as well as provides the first evidence in a single organism that drastic genome-wide shifts in RNA half-lives can be modulated by growth substrate. We detd. which genes in each metabolic pathway control the flux and classified them as regulated by transcription (e.g. transcription factor) or degrdn. (e.g. post-transcriptional modification). We found that more than half of genes in metab. were controlled by degrdn. Our results suggest that M. acetivorans employs extensive post-transcriptional regulation to optimize key metabolic steps, and more generally that degrdn. could play a much greater role in optimizing an organism's metab. than previously thought.
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  22. 22
    Oivanen, M.; Kuusela, S.; Lönnberg, H. Kinetics and Mechanisms for the Cleavage and Isomerization of the Phosphodiester Bonds of RNA by Brønsted Acids and Bases. Chem. Rev. 1998, 98 (3), 961– 990,  DOI: 10.1021/cr960425x
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    22
    Kinetics and Mechanisms for the Cleavage and Isomerization of the Phosphodiester Bonds of RNA by Bronsted Acids and Bases
    Oivanen, Mikko; Kuusela, Satu; Loennberg, Harri
    Chemical Reviews (Washington, D. C.) (1998), 98 (3), 961-990CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
    A review with 240 refs. on acid/base catalyzed cleavage and isomerization of the 3',5'-phosphodiester bonds of DNA.
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  23. 23
    Barbieri, I.; Tzelepis, K.; Pandolfini, L.; Shi, J.; Millán-Zambrano, G.; Robson, S. C.; Aspris, D.; Migliori, V.; Bannister, A. J.; Han, N.; De Braekeleer, E.; Ponstingl, H.; Hendrick, A.; Vakoc, C. R.; Vassiliou, G. S.; Kouzarides, T. Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control. Nature 2017, 552 (7683), 126– 131,  DOI: 10.1038/nature24678
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    23
    Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control
    Barbieri, Isaia; Tzelepis, Konstantinos; Pandolfini, Luca; Shi, Junwei; Millan-Zambrano, Gonzalo; Robson, Samuel C.; Aspris, Demetrios; Migliori, Valentina; Bannister, Andrew J.; Han, Namshik; De Braekeleer, Etienne; Ponstingl, Hannes; Hendrick, Alan; Vakoc, Christopher R.; Vassiliou, George S.; Kouzarides, Tony
    Nature (London, United Kingdom) (2017), 552 (7683), 126-131CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
    N6-methyladenosine (m6A) is an abundant internal RNA modification in both coding and non-coding RNAs that is catalyzed by the METTL3-METTL14 methyltransferase complex. However, the specific role of these enzymes in cancer is still largely unknown. Here we define a pathway that is specific for METTL3 and is implicated in the maintenance of a leukemic state. We identify METTL3 as an essential gene for growth of acute myeloid leukemia cells in two distinct genetic screens. Downregulation of METTL3 results in cell cycle arrest, differentiation of leukemic cells and failure to establish leukemia in immunodeficient mice. We show that METTL3, independently of METTL14, assocs. with chromatin and localizes to the transcriptional start sites of active genes. The vast majority of these genes have the CAATT-box binding protein CEBPZ present at the transcriptional start site, and this is required for recruitment of METTL3 to chromatin. Promoter-bound METTL3 induces m6A modification within the coding region of the assocd. mRNA transcript, and enhances its translation by relieving ribosome stalling. We show that genes regulated by METTL3 in this way are necessary for acute myeloid leukemia. Together, these data define METTL3 as a regulator of a chromatin-based pathway that is necessary for maintenance of the leukemic state and identify this enzyme as a potential therapeutic target for acute myeloid leukemia.
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  24. 24
    Vu, L. P.; Pickering, B. F.; Cheng, Y.; Zaccara, S.; Nguyen, D.; Minuesa, G.; Chou, T.; Chow, A.; Saletore, Y.; MacKay, M.; Schulman, J.; Famulare, C.; Patel, M.; Klimek, V. M.; Garrett-Bakelman, F. E.; Melnick, A.; Carroll, M.; Mason, C. E.; Jaffrey, S. R.; Kharas, M. G. The N6-methyladenosine m6A-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells. Nat. Med. 2017, 23 (11), 1369– 1376,  DOI: 10.1038/nm.4416
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    24
    The N6-methyladenosine (m6A)-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells
    Vu, Ly P.; Pickering, Brian F.; Cheng, Yuanming; Zaccara, Sara; Nguyen, Diu; Minuesa, Gerard; Chou, Timothy; Chow, Arthur; Saletore, Yogesh; MacKay, Matthew; Schulman, Jessica; Famulare, Christopher; Patel, Minal; Klimek, Virginia M.; Garrett-Bakelman, Francine E.; Melnick, Ari; Carroll, Martin; Mason, Christopher E.; Jaffrey, Samie R.; Kharas, Michael G.
    Nature Medicine (New York, NY, United States) (2017), 23 (11), 1369-1376CODEN: NAMEFI; ISSN:1078-8956. (Nature Research)
    N6-methyladenosine (m6A) is an abundant nucleotide modification in mRNA that is required for the differentiation of mouse embryonic stem cells. However, it remains unknown whether the m6A modification controls the differentiation of normal and/or malignant myeloid hematopoietic cells. Here we show that shRNA-mediated depletion of the m6A-forming enzyme METTL3 in human hematopoietic stem/progenitor cells (HSPCs) promotes cell differentiation, coupled with reduced cell proliferation. Conversely, overexpression of wild-type METTL3, but not of a catalytically inactive form of METTL3, inhibits cell differentiation and increases cell growth. METTL3 mRNA and protein are expressed more abundantly in acute myeloid leukemia (AML) cells than in healthy HSPCs or other types of tumor cells. Furthermore, METTL3 depletion in human myeloid leukemia cell lines induces cell differentiation and apoptosis and delays leukemia progression in recipient mice in vivo. Single-nucleotide-resoln. mapping of m6A coupled with ribosome profiling reveals that m6A promotes the translation of c-MYC, BCL2 and PTEN mRNAs in the human acute myeloid leukemia MOLM-13 cell line. Moreover, loss of METTL3 leads to increased levels of phosphorylated AKT, which contributes to the differentiation-promoting effects of METTL3 depletion. Overall, these results provide a rationale for the therapeutic targeting of METTL3 in myeloid leukemia.
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  25. 25
    Pendleton, K. E.; Chen, B.; Liu, K.; Hunter, O. V.; Xie, Y.; Tu, B. P.; Conrad, N. K. The U6 snRNA m6A Methyltransferase METTL16 Regulates SAM Synthetase Intron Retention. Cell 2017, 169 (5), 824– 835,  DOI: 10.1016/j.cell.2017.05.003
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    25
    The U6 snRNA m6A methyltransferase METTL16 regulates SAM synthetase intron retention
    Pendleton, Kathryn E.; Chen, Beibei; Liu, Kuanqing; Hunter, Olga V.; Xie, Yang; Tu, Benjamin P.; Conrad, Nicholas K.
    Cell (Cambridge, MA, United States) (2017), 169 (5), 824-835.e14CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
    Maintenance of proper levels of the Me donor S-adenosylmethionine (SAM) is crit. for a wide variety of biol. processes. We demonstrate that the N6-adenosine methyltransferase METTL16 regulates expression of human MAT2A, which encodes the SAM synthetase expressed in most cells. Upon SAM depletion by methionine starvation, cells induce MAT2A expression by enhanced splicing of a retained intron. Induction requires METTL16 and its methylation substrate, a vertebrate conserved hairpin (hp1) in the MAT2A 3' UTR. Increasing METTL16 occupancy on the MAT2A 3' UTR is sufficient to induce efficient splicing. We propose that, under SAM-limiting conditions, METTL16 occupancy on hp1 increases due to inefficient enzymic turnover, which promotes MAT2A splicing. We further show that METTL16 is the long-unknown methyltransferase for the U6 spliceosomal small nuclear RNA (snRNA). These observations suggest that the conserved U6 snRNA methyltransferase evolved an addnl. function in vertebrates to regulate SAM homeostasis.
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    Bokar, J. A.; Shambaugh, M. E.; Polayes, D.; Matera, A. G.; Rottman, F. M. Purification and cDNA cloning of the AdoMet-binding subunit of the human mRNA (N6-adenosine)-methyltransferase. RNA 1997, 3 (11), 1233– 1247
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    Purification and cDNA cloning of the AdoMet-binding subunit of the human mRNA (N6-adenosine)-methyltransferase
    Bokar, Joseph A.; Shambaugh, Mary Eileen; Polayes, Deborah; Matera, A. Gregory; Rottman, Fritz M.
    RNA (1997), 3 (11), 1233-1247CODEN: RNARFU; ISSN:1355-8382. (Cambridge University Press)
    The methylation of internal adenosine residues in eukaryotic mRNA, forming N6-methyladenosine (m6A), is catalyzed by a complex multicomponent enzyme. Previous studies suggested that m6A affects the efficiency of mRNA processing or transport, although the mechanism by which this occurs is not known. As a step toward better understanding the mechanism and function of this ubiquitous posttranscriptional modification, the authors have shown that HeLa mRNA (N6-adenosine)-methyltransferase requires at least two sep. protein factors, MT-A and MT-B, and MT-A contains the AdoMet binding site on a 70-kDa subunit (MT-A70). MT-A70 was purified by conventional chromatog. and electrophoresis, and was microsequenced. The peptide sequence was used to design a degenerate oligodeoxynucleotide that in turn was used to isolate the cDNA clone coding for MT-A70 from a HeLa cDNA library. Recombinant MT-A70 was expressed as a fusion protein in bacteria and was used to generate anti-MT-A70 antisera in rabbits. These antisera recognize MT-A70 in HeLa nuclear exts. by western blot and are capable of depleting (N6-adenosine)-methyltransferase activity from HeLa nuclear ext., confirming that MT-A70 is a crit. subunit of (N6-adenosine)-methyltransferase. Northern blot anal. reveals that MT-A70 mRNA is present in a wide variety of human tissues and may undergo alternative splicing. MT-A70 cDNA probe hybridizes to a 2.0-kilobase (kb) polyadenylated RNA isolated from HeLa cells, whereas it hybridizes to two predominant RNA species (approx. 2.0 kb and 3.0 kb) using mRNA isolated from six different human tissues. Anal. of the cDNA sequence indicates that it codes for a 580-amino acid protein with a predicted MW = 65 kDa. The predicted protein contains sequences similar to consensus methylation motifs I and II identified in prokaryotic DNA (N6-adenosine)-methyltransferases, suggesting the functional conservation of peptide motifs. MT-A70 also contains a long region of homol. to the yeast protein SPO8, which is involved in induction of sporulation by an unknown mechanism.
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    Wiederschain, D.; Wee, S.; Chen, L.; Loo, A.; Yang, G.; Huang, A.; Chen, Y.; Caponigro, G.; Yao, Y.-M.; Lengauer, C.; Sellers, W. R.; Benson, J. D. Single-vector inducible lentiviral RNAi system for oncology target validation. Cell Cycle 2009, 8 (3), 498– 504,  DOI: 10.4161/cc.8.3.7701
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    Single-vector inducible lentiviral RNAi system for oncology target validation
    Wiederschain, Dmitri; Wee, Susan; Chen, Lin; Loo, Alice; Yang, Guizhi; Huang, Alan; Chen, Yan; Caponigro, Giordano; Yao, Yung-mae; Lengauer, Christoph; Sellers, William R.; Benson, John D.
    Cell Cycle (2009), 8 (3), 498-504CODEN: CCEYAS; ISSN:1538-4101. (Landes Bioscience)
    The use of RNA interference (RNAi) has enabled loss-of-function studies in mammalian cancer cells and has hence become crit. for identifying and validating cancer drug targets. Current transient siRNA and stable shRNA systems, however, have limited utility in accurately assessing the cancer dependency due to their short-lived effects and limited in vivo utility, resp. In this study, a single-vector lentiviral, Tet-inducible shRNA system (pLKO-Tet-On) was generated to allow for the rapid generation of multiple stable cell lines with regulatable shRNA expression. We demonstrate the advantages and versatility of this system by targeting two polycomb group proteins, Bmi-1 and Mel-18, in a no. of cancer cell lines. Our data show that pLKO-Tet-On-mediated knockdown is tightly regulated by the inducer tetracycline and its deriv., doxycycline, in a concn.- and time-dependent manner. Furthermore, target gene expression is fully restored upon withdrawal of the inducing agent. An addnl., 17 distinct gene products have been targeted by inducible shRNAs with robust regulation in all cases. Importantly, we functionally validate the ability of the pLKO-Tet-On vector to reversibly silence targeted transcripts in vivo. The versatile and robust inducible lentiviral RNAi system reported herein can therefore serve as a powerful tool to rapidly reveal tumor cell dependence.
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  28. 28
    Leger, A.; Amaral, P. P.; Pandolfini, L.; Capitanchik, C.; Capraro, F.; Barbieri, I.; Migliori, V.; Luscombe, N. M.; Enright, A. J.; Tzelepis, K.; Ule, J.; Fitzgerald, T.; Birney, E.; Leonardi, T.; Kouzarides, T. RNA modifications detection by comparative Nanopore direct RNA sequencing. bioRxiv 2019, 843136, https://www.biorxiv.org/content/10.1101/843136v1.
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    Doxtader, K. A.; Wang, P.; Scarborough, A. M.; Seo, D.; Conrad, N. K.; Nam, Y. Structural Basis for Regulation of METTL16, an S-Adenosylmethionine Homeostasis Factor. Mol. Cell 2018, 71 (6), 1001– 1011,  DOI: 10.1016/j.molcel.2018.07.025
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    29
    Structural Basis for Regulation of METTL16, an S-Adenosylmethionine Homeostasis Factor
    Doxtader, Katelyn A.; Wang, Ping; Scarborough, Anna M.; Seo, Dahee; Conrad, Nicholas K.; Nam, Yunsun
    Molecular Cell (2018), 71 (6), 1001-1011.e4CODEN: MOCEFL; ISSN:1097-2765. (Elsevier Inc.)
    S-adenosylmethionine (SAM) is an essential metabolite that acts as a cofactor for most methylation events in the cell. The N6-methyladenosine (m6A) methyltransferase METTL16 controls SAM homeostasis by regulating the abundance of SAM synthetase MAT2A mRNA in response to changing intracellular SAM levels. Here we present crystal structures of METTL16 in complex with MAT2A RNA hairpins to uncover crit. mol. mechanisms underlying the regulated activity of METTL16. The METTL16-RNA complex structures reveal at. details of RNA substrates that drive productive methylation by METTL16. In addn., we identify a polypeptide loop in METTL16 near the SAM binding site with an autoregulatory role. We show that mutations that enhance or repress METTL16 activity in vitro correlate with changes in MAT2A mRNA levels in cells. Thus, we demonstrate the structural basis for the specific activity of METTL16 and further suggest the mol. mechanisms by which METTL16 efficiency is tuned to regulate SAM homeostasis.
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  30. 30
    Yang, D.; Qiao, J.; Wang, G.; Lan, Y.; Li, G.; Guo, X.; Xi, J.; Ye, D.; Zhu, S.; Chen, W.; Jia, W.; Leng, Y.; Wan, X.; Kang, J. N6-Methyladenosine modification of lincRNA 1281 is critically required for mESC differentiation potential. Nucleic Acids Res. 2018, 46 (8), 3906– 3920,  DOI: 10.1093/nar/gky130
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    30
    N6-methyladenosine modification of lincRNA 1281 is critically required for mESC differentiation potential
    Yang, Dandan; Qiao, Jing; Wang, Guiying; Lan, Yuanyuan; Li, Guoping; Guo, Xudong; Xi, Jiajie; Ye, Dan; Zhu, Songcheng; Chen, Wen; Jia, Wenwen; Leng, Ye; Wan, Xiaoping; Kang, Jiuhong
    Nucleic Acids Research (2018), 46 (8), 3906-3920CODEN: NARHAD; ISSN:1362-4962. (Oxford University Press)
    Previous studies have revealed the crit. roles of N6-methyladenosine (m6A) modification of mRNA in embryonic stem cells (ESCs), but the biol. function of m6A in large intergenic noncoding RNA (lincRNA) is unknown. Here, we showed that the internal m6A modification of linc1281 mediates a competing endogenous RNA (ceRNA) model to regulate mouse ESC (mESC) differentiation. We demonstrated that loss of linc1281 compromises mESC differentiation and that m6A is highly enriched within linc1281 transcripts. Linc1281 with RRACU m6A sequence motifs, but not an m6A-deficient mutant, restored the phenotype in linc1281-depleted mESCs. Mechanistic analyses revealed that linc1281 ensures mESC identity by sequestering pluripotency-related let-7 family microRNAs (miRNAs), and this RNA-RNA interaction is m6A dependent. Collectively, these findings elucidated the functional roles of linc1281 and its m6A modification in mESCs and identified a novel RNA regulatory mechanism, providing a basis for further exploration of broad RNA epigenetic regulatory patterns.
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  31. 31
    Zhang, J.; Guo, S.; Piao, H.-Y.; Wang, Y.; Wu, Y.; Meng, X.-Y.; Yang, D.; Zheng, Z.-C.; Zhao, Y. ALKBH5 promotes invasion and metastasis of gastric cancer by decreasing methylation of the lncRNA NEAT1. J. Physiol. Biochem. 2019, 75 (3), 379– 389,  DOI: 10.1007/s13105-019-00690-8
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    31
    ALKBH5 promotes invasion and metastasis of gastric cancer by decreasing methylation of the lncRNA NEAT1
    Zhang, Jun; Guo, Shuai; Piao, Hai-yan; Wang, Yue; Wu, Yue; Meng, Xiang-yu; Yang, Dong; Zheng, Zhi-chao; Zhao, Yan
    Journal of Physiology and Biochemistry (2019), 75 (3), 379-389CODEN: JPBIF2; ISSN:1138-7548. (Springer)
    N6-Methyladenosine (m6A) is the most common posttranscriptional modification of RNA and plays crit. roles in cancer pathogenesis. However, the biol. function of long noncoding RNA (lncRNA) methylation remains unclear. As a demethylase, ALKBH5 (alkylation repair homolog protein 5) is involved in mediating methylation reversal. The purpose of this study was to investigate lncRNA m6A modification and its role in gastric cancer (GC). Bioinformatics predicted interactions of ALKBH5 with lncRNAs. Five methods were employed to assess the function of nuclear paraspeckle assembly transcript 1 (NEAT1), including gene silencing, RT-PCR, sepn. of nuclear and cytoplasmic fractions, scrape motility assays, and transwell migration assays. Then, m6A RNA immunopptn. and immunofluorescence were used to detect methylated NEAT1 in GC cells. Rescue assays were performed to define the relationship between NEAT1 and ALKBH5. NEAT1 is a potential binding lncRNA of ALKBH5. NEAT1 was overexpressed in GC cells and tissue. Addnl. expts. confirmed that knockdown of NEAT1 significantly repressed invasion and metastasis of GC cells. ALKBH5 affected the m6A level of NEAT1. The binding of ALKBH5 and NEAT1 influences the expression of EZH2 (a subunit of the polycomb repressive complex) and thus affects GC invasion and metastasis. Our findings indicate a novel mechanism by which ALKBH5 promotes GC invasion and metastasis by demethylating the lncRNA NEAT1. They may be potential therapeutic targets for GC.
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  32. 32
    Zhou, K. I.; Parisien, M.; Dai, Q.; Liu, N.; Diatchenko, L.; Sachleben, J. R.; Pan, T. N6-Methyladenosine Modification in a Long Noncoding RNA Hairpin Predisposes Its Conformation to Protein Binding. J. Mol. Biol. 2016, 428, 822– 833,  DOI: 10.1016/j.jmb.2015.08.021
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    32
    N6-Methyladenosine Modification in a Long Noncoding RNA Hairpin Predisposes Its Conformation to Protein Binding
    Zhou, Katherine I.; Parisien, Marc; Dai, Qing; Liu, Nian; Diatchenko, Luda; Sachleben, Joseph R.; Pan, Tao
    Journal of Molecular Biology (2016), 428 (5_Part_A), 822-833CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)
    N6-Methyladenosine (m6A) is a reversible and abundant internal modification of mRNA and long noncoding RNA (lncRNA) with roles in RNA processing, transport, and stability. Although m6A does not preclude Watson-Crick base pairing, the N6-Me group alters the stability of RNA secondary structure. Since changes in RNA structure can affect diverse cellular processes, the influence of m6A on mRNA and lncRNA structure has the potential to be an important mechanism for m6A function in the cell. Indeed, an m6A site in the lncRNA metastasis assocd. lung adenocarcinoma transcript 1 (MALAT1) was recently shown to induce a local change in structure that increases the accessibility of a U5-tract for recognition and binding by heterogeneous nuclear ribonucleoprotein C (HNRNPC). This m6A-dependent regulation of protein binding through a change in RNA structure, termed "m6A-switch", affects transcriptome-wide mRNA abundance and alternative splicing. To further characterize this first example of an m6A-switch in a cellular RNA, we used NMR and Forester resonance energy transfer to demonstrate the effect of m6A on a 32-nucleotide RNA hairpin derived from the m6A-switch in MALAT1. The obsd. imino proton NMR resonances and Forester resonance energy transfer efficiencies suggest that m6A selectively destabilizes the portion of the hairpin stem where the U5-tract is located, increasing the solvent accessibility of the neighboring bases while maintaining the overall hairpin structure. The m6A-modified hairpin has a predisposed conformation that resembles the hairpin conformation in the RNA-HNRNPC complex more closely than the unmodified hairpin. The m6A-induced structural changes in the MALAT1 hairpin can serve as a model for a large family of m6A-switches that mediate the influence of m6A on cellular processes.
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  33. 33
    Huang, H.; Weng, H.; Zhou, K.; Wu, T.; Zhao, B. S.; Sun, M.; Chen, Z.; Deng, X.; Xiao, G.; Auer, F.; Klemm, L.; Wu, H.; Zuo, Z.; Qin, X.; Dong, Y.; Zhou, Y.; Qin, H.; Tao, S.; Du, J.; Liu, J.; Lu, Z.; Yin, H.; Mesquita, A.; Yuan, C. L.; Hu, Y.-C.; Sun, W.; Su, R.; Dong, L.; Shen, C.; Li, C.; Qing, Y.; Jiang, X.; Wu, X.; Sun, M.; Guan, J.-L.; Qu, L.; Wei, M.; Müschen, M.; Huang, G.; He, C.; Yang, J.; Chen, J. Histone H3 trimethylation at lysine 36 guides m6A RNA modification co-transcriptionally. Nature 2019, 567 (7748), 414– 419,  DOI: 10.1038/s41586-019-1016-7
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    33
    Histone H3 trimethylation at lysine 36 guides m6A RNA modification co-transcriptionally
    Huang, Huilin; Weng, Hengyou; Zhou, Keren; Wu, Tong; Zhao, Boxuan Simen; Sun, Mingli; Chen, Zhenhua; Deng, Xiaolan; Xiao, Gang; Auer, Franziska; Klemm, Lars; Wu, Huizhe; Zuo, Zhixiang; Qin, Xi; Dong, Yunzhu; Zhou, Yile; Qin, Hanjun; Tao, Shu; Du, Juan; Liu, Jun; Lu, Zhike; Yin, Hang; Mesquita, Ana; Yuan, Celvie L.; Hu, Yueh-Chiang; Sun, Wenju; Su, Rui; Dong, Lei; Shen, Chao; Li, Chenying; Qing, Ying; Jiang, Xi; Wu, Xiwei; Sun, Miao; Guan, Jun-Lin; Qu, Lianghu; Wei, Minjie; Muschen, Markus; Huang, Gang; He, Chuan; Yang, Jianhua; Chen, Jianjun
    Nature (London, United Kingdom) (2019), 567 (7748), 414-419CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
    DNA and histone modifications have notable effects on gene expression1. Being the most prevalent internal modification in mRNA, the N6-methyladenosine (m6A) mRNA modification is as an important post-transcriptional mechanism of gene regulation2-4 and has crucial roles in various normal and pathol. processes5-12. However, it is unclear how m6A is specifically and dynamically deposited in the transcriptome. Here we report that histone H3 trimethylation at Lys36 (H3K36me3), a marker for transcription elongation, guides m6A deposition globally. We show that m6A modifications are enriched in the vicinity of H3K36me3 peaks, and are reduced globally when cellular H3K36me3 is depleted. Mechanistically, H3K36me3 is recognized and bound directly by METTL14, a crucial component of the m6A methyltransferase complex (MTC), which in turn facilitates the binding of the m6A MTC to adjacent RNA polymerase II, thereby delivering the m6A MTC to actively transcribed nascent RNAs to deposit m6A co-transcriptionally. In mouse embryonic stem cells, phenocopying METTL14 knockdown, H3K36me3 depletion also markedly reduces m6A abundance transcriptome-wide and in pluripotency transcripts, resulting in increased cell stemness. Collectively, our studies reveal the important roles of H3K36me3 and METTL14 in detg. specific and dynamic deposition of m6A in mRNA, and uncover another layer of gene expression regulation that involves crosstalk between histone modification and RNA methylation.
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  34. 34
    Liu, J.; Dou, X.; Chen, C.; Chen, C.; Liu, C.; Xu, M. M.; Zhao, S.; Shen, B.; Gao, Y.; Han, D.; He, C. N6-methyladenosine of chromosome-associated regulatory RNA regulates chromatin state and transcription. Science 2020, 367 (6477), 580– 586,  DOI: 10.1126/science.aay6018
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    34
    N6-methyladenosine of chromosome-associated regulatory RNA regulates chromatin state and transcription
    Liu, Jun; Dou, Xiaoyang; Chen, Chuanyuan; Chen, Chuan; Liu, Chang; Xu, Meng Michelle; Zhao, Siqi; Shen, Bin; Gao, Yawei; Han, Dali; He, Chuan
    Science (Washington, DC, United States) (2020), 367 (6477), 580-586CODEN: SCIEAS; ISSN:1095-9203. (American Association for the Advancement of Science)
    N6-methyladenosine (m6A) regulates stability and translation of mRNA in various biol. processes. In this work, we show that knockout of the m6A writer Mettl3 or the nuclear reader Ythdc1 in mouse embryonic stem cells increases chromatin accessibility and activates transcription in an m6A-dependent manner. We found that METTL3 deposits m6A modifications on chromosome-assocd. regulatory RNAs (carRNAs), including promoter-assocd. RNAs, enhancer RNAs, and repeat RNAs. YTHDC1 facilitates the decay of a subset of these m6A-modified RNAs, esp. elements of the long interspersed element-1 family, through the nuclear exosome targeting-mediated nuclear degrdn. Reducing m6A methylation by METTL3 depletion or site-specific m6A demethylation of selected carRNAs elevates the levels of carRNAs and promotes open chromatin state and downstream transcription. Collectively, our results reveal that m6A on carRNAs can globally tune chromatin state and transcription.
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  35. 35
    Louloupi, A.; Ntini, E.; Conrad, T.; Ørom, U. A. V. Transient N6-Methyladenosine Transcriptome Sequencing Reveals a Regulatory Role of m6A in Splicing Efficiency. Cell Rep. 2018, 23 (12), 3429– 3437,  DOI: 10.1016/j.celrep.2018.05.077
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    35
    Transient N-6-Methyladenosine Transcriptome Sequencing Reveals a Regulatory Role of m6A in Splicing Efficiency
    Louloupi, Annita; Ntini, Evgenia; Conrad, Thomas; Oerom, Ulf Andersson Vang
    Cell Reports (2018), 23 (12), 3429-3437CODEN: CREED8; ISSN:2211-1247. (Cell Press)
    Splicing efficiency varies among transcripts, and tight control of splicing kinetics is crucial for coordinated gene expression. N-6-methyladenosine (m6A) is the most abundant RNA modification and is involved in regulation of RNA biogenesis and function. The impact of m6A on regulation of RNA splicing kinetics is unknown. Here, we provide a time-resolved high-resoln. assessment of m6A on nascent RNA transcripts and unveil its importance for the control of RNA splicing kinetics. We find that early co-transcriptional m6A deposition near splice junctions promotes fast splicing, while m6A modifications in introns are assocd. with long, slowly processed introns and alternative splicing events. In conclusion, we show that early m6A deposition specifies the fate of transcripts regarding splicing kinetics and alternative splicing.
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  36. 36
    Mendel, M.; Chen, K.-M.; Homolka, D.; Gos, P.; Pandey, R. R.; McCarthy, A. A.; Pillai, R. S. Methylation of Structured RNA by the m6A Writer METTL16 Is Essential for Mouse Embryonic Development. Mol. Cell 2018, 71 (6), 986– 1000,  DOI: 10.1016/j.molcel.2018.08.004
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    Methylation of Structured RNA by the m6A Writer METTL16 Is Essential for Mouse Embryonic Development
    Mendel, Mateusz; Chen, Kuan-Ming; Homolka, David; Gos, Pascal; Pandey, Radha Raman; McCarthy, Andrew A.; Pillai, Ramesh S.
    Molecular Cell (2018), 71 (6), 986-1000.e11CODEN: MOCEFL; ISSN:1097-2765. (Elsevier Inc.)
    Internal modification of RNAs with N6-methyladenosine (m6A) is a highly conserved means of gene expression control. While the METTL3/METTL14 heterodimer adds this mark on thousands of transcripts in a single-stranded context, the substrate requirements and physiol. roles of the second m6A writer METTL16 remain unknown. Here we describe the crystal structure of human METTL16 to reveal a methyltransferase domain furnished with an extra N-terminal module, which together form a deep-cut groove that is essential for RNA binding. When presented with a random pool of RNAs, METTL16 selects for methylation-structured RNAs where the crit. adenosine is present in a bulge. Mouse 16-cell embryos lacking Mettl16 display reduced mRNA levels of its methylation target, the SAM synthetase Mat2a. The consequence is massive transcriptome dysregulation in ∼64-cell blastocysts that are unfit for further development. This highlights the role of an m6A RNA methyltransferase in facilitating early development via regulation of SAM availability.
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  37. 37
    Shima, H.; Matsumoto, M.; Ishigami, Y.; Ebina, M.; Muto, A.; Sato, Y.; Kumagai, S.; Ochiai, K.; Suzuki, T.; Igarashi, K. S-Adenosylmethionine Synthesis Is Regulated by Selective N6-Adenosine Methylation and mRNA Degradation Involving METTL16 and YTHDC1. Cell Rep. 2017, 21 (12), 3354– 3363,  DOI: 10.1016/j.celrep.2017.11.092
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    37
    S-Adenosylmethionine Synthesis Is Regulated by Selective N6-Adenosine Methylation and mRNA Degradation Involving METTL16 and YTHDC1
    Shima, Hiroki; Matsumoto, Mitsuyo; Ishigami, Yuma; Ebina, Masayuki; Muto, Akihiko; Sato, Yuho; Kumagai, Sayaka; Ochiai, Kyoko; Suzuki, Tsutomu; Igarashi, Kazuhiko
    Cell Reports (2017), 21 (12), 3354-3363CODEN: CREED8; ISSN:2211-1247. (Cell Press)
    S-adenosylmethionine (SAM) is an important metabolite as a methyl-group donor in DNA and histone methylation, tuning regulation of gene expression. Appropriate intracellular SAM levels must be maintained, because methyltransferase reaction rates can be limited by SAM availability. In response to SAM depletion, MAT2A, which encodes a ubiquitous mammalian methionine adenosyltransferase isoenzyme, was upregulated through mRNA stabilization. SAM-depletion reduced N6-methyladenosine (m6A) in the 3' UTR of MAT2A. In vitro reactions using recombinant METTL16 revealed multiple, conserved methylation targets in the 3' UTR. Knockdown of METTL16 and the m6A reader YTHDC1 abolished SAM-responsive regulation of MAT2A. Mutations of the target adenine sites of METTL16 within the 3' UTR revealed that these m6As were redundantly required for regulation. MAT2A mRNA methylation by METTL16 is read by YTHDC1, and we suggest that this allows cells to monitor and maintain intracellular SAM levels.
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    Zhang, L.-S.; Liu, C.; Ma, H.; Dai, Q.; Sun, H.-L.; Luo, G.; Zhang, Z.; Zhang, L.; Hu, L.; Dong, X.; He, C. Transcriptome-wide Mapping of Internal N7-Methylguanosine Methylome in Mammalian mRNA. Mol. Cell 2019, 74 (6), 1304– 1316,  DOI: 10.1016/j.molcel.2019.03.036
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    Transcriptome-wide Mapping of Internal N7-Methylguanosine Methylome in Mammalian mRNA
    Zhang, Li-Sheng; Liu, Chang; Ma, Honghui; Dai, Qing; Sun, Hui-Lung; Luo, Guanzheng; Zhang, Zijie; Zhang, Linda; Hu, Lulu; Dong, Xueyang; He, Chuan
    Molecular Cell (2019), 74 (6), 1304-1316.e8CODEN: MOCEFL; ISSN:1097-2765. (Elsevier Inc.)
    N7-methylguanosine (m7G) is a pos. charged, essential modification at the 5' cap of eukaryotic mRNA, regulating mRNA export, translation, and splicing. M7G also occurs internally within tRNA and rRNA, but its existence and distribution within eukaryotic mRNA remain to be investigated. Here, we show the presence of internal m7G sites within mammalian mRNA. We then performed transcriptome-wide profiling of internal m7G methylome using m7G-MeRIP sequencing (MeRIP-seq). To map this modification at base resoln., we developed a chem.-assisted sequencing approach that selectively converts internal m7G sites into abasic sites, inducing misincorporation at these sites during reverse transcription. This base-resoln. m7G-seq enabled transcriptome-wide mapping of m7G in human tRNA and mRNA, revealing distribution features of the internal m7G methylome in human cells. We also identified METTL1 as a methyltransferase that installs a subset of m7G within mRNA and showed that internal m7G methylation could affect mRNA translation.
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    Lee, S.-H.; Singh, I.; Tisdale, S.; Abdel-Wahab, O.; Leslie, C. S.; Mayr, C. Widespread intronic polyadenylation inactivates tumour suppressor genes in leukaemia. Nature 2018, 561 (7721), 127– 131,  DOI: 10.1038/s41586-018-0465-8
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    Widespread intronic polyadenylation inactivates tumour suppressor genes in leukemia
    Lee, Shih-Han; Singh, Irtisha; Tisdale, Sarah; Abdel-Wahab, Omar; Leslie, Christina S.; Mayr, Christine
    Nature (London, United Kingdom) (2018), 561 (7721), 127-131CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
    DNA mutations are known cancer drivers. Here we investigated whether mRNA events that are upregulated in cancer can functionally mimic the outcome of genetic alterations. RNA sequencing or 3'-end sequencing techniques were applied to normal and malignant B cells from 59 patients with chronic lymphocytic leukemia (CLL)1-3. We discovered widespread upregulation of truncated mRNAs and proteins in primary CLL cells that were not generated by genetic alterations but instead occurred by intronic polyadenylation. Truncated mRNAs caused by intronic polyadenylation were recurrent (n = 330) and predominantly affected genes with tumor-suppressive functions. The truncated proteins generated by intronic polyadenylation often lack the tumor-suppressive functions of the corresponding full-length proteins (such as DICER and FOXN3), and several even acted in an oncogenic manner (such as CARD11, MGA and CHST11). In CLL, the inactivation of tumor-suppressor genes by aberrant mRNA processing is substantially more prevalent than the functional loss of such genes through genetic events. We further identified new candidate tumor-suppressor genes that are inactivated by intronic polyadenylation in leukemia and by truncating DNA mutations in solid tumors4,5. These genes are understudied in cancer, as their overall mutation rates are lower than those of well-known tumor-suppressor genes. Our findings show the need to go beyond genomic analyses in cancer diagnostics, as mRNA events that are silent at the DNA level are widespread contributors to cancer pathogenesis through the inactivation of tumor-suppressor genes.
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    Singh, I.; Lee, S.-H.; Sperling, A. S.; Samur, M. K.; Tai, Y.-T.; Fulciniti, M.; Munshi, N. C.; Mayr, C.; Leslie, C. S. Widespread intronic polyadenylation diversifies immune cell transcriptomes. Nat. Commun. 2018, 9 (1), 1716,  DOI: 10.1038/s41467-018-04112-z
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    Widespread intronic polyadenylation diversifies immune cell transcriptomes
    Singh Irtisha; Leslie Christina S; Singh Irtisha; Lee Shih-Han; Mayr Christine; Sperling Adam S; Samur Mehmet K; Tai Yu-Tzu; Fulciniti Mariateresa; Munshi Nikhil C
    Nature communications (2018), 9 (1), 1716 ISSN:.
    Alternative cleavage and polyadenylation (ApA) is known to alter untranslated region (3'UTR) length but can also recognize intronic polyadenylation (IpA) signals to generate transcripts that lose part or all of the coding region. We analyzed 46 3'-seq and RNA-seq profiles from normal human tissues, primary immune cells, and multiple myeloma (MM) samples and created an atlas of 4927 high-confidence IpA events represented in these cell types. IpA isoforms are widely expressed in immune cells, differentially used during B-cell development or in different cellular environments, and can generate truncated proteins lacking C-terminal functional domains. This can mimic ectodomain shedding through loss of transmembrane domains or alter the binding specificity of proteins with DNA-binding or protein-protein interaction domains. MM cells display a striking loss of IpA isoforms expressed in plasma cells, associated with shorter progression-free survival and impacting key genes in MM biology and response to lenalidomide.
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    Jung, H.; Lee, D.; Lee, J.; Park, D.; Kim, Y. J.; Park, W.-Y.; Hong, D.; Park, P. J.; Lee, E. Intron retention is a widespread mechanism of tumor-suppressor inactivation. Nat. Genet. 2015, 47 (11), 1242– 1248,  DOI: 10.1038/ng.3414
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    Intron retention is a widespread mechanism of tumor-suppressor inactivation
    Jung, Hyunchul; Lee, Donghoon; Lee, Jongkeun; Park, Donghyun; Kim, Yeon Jeong; Park, Woong-Yang; Hong, Dongwan; Park, Peter J.; Lee, Eunjung
    Nature Genetics (2015), 47 (11), 1242-1248CODEN: NGENEC; ISSN:1061-4036. (Nature Publishing Group)
    A substantial fraction of disease-causing mutations are pathogenic through aberrant splicing. Although genome profiling studies have identified somatic single-nucleotide variants (SNVs) in cancer, the extent to which these variants trigger abnormal splicing has not been systematically examd. Here we analyzed RNA sequencing and exome data from 1,812 patients with cancer and identified ∼900 somatic exonic SNVs that disrupt splicing. At least 163 SNVs, including 31 synonymous ones, were shown to cause intron retention or exon skipping in an allele-specific manner, with ∼70% of the SNVs occurring on the last base of exons. Notably, SNVs causing intron retention were enriched in tumor suppressors, and 97% of these SNVs generated a premature termination codon, leading to loss of function through nonsense-mediated decay or truncated protein. We also characterized the genomic features predictive of such splicing defects. Overall, this work demonstrates that intron retention is a common mechanism of tumor-suppressor inactivation.
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    Kopp, F.; Mendell, J. T. Functional Classification and Experimental Dissection of Long Noncoding RNAs. Cell 2018, 172 (3), 393– 407,  DOI: 10.1016/j.cell.2018.01.011
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    Functional classification and experimental dissection of long noncoding RNAs
    Kopp, Florian; Mendell, Joshua T.
    Cell (Cambridge, MA, United States) (2018), 172 (3), 393-407CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
    A review. Over the last decade, it has been increasingly demonstrated that the genomes of many species are pervasively transcribed, resulting in the prodn. of numerous long noncoding RNAs (lncRNAs). At the same time, it is now appreciated that many types of DNA regulatory elements, such as enhancers and promoters, regularly initiate bi-directional transcription. Thus, discerning functional noncoding transcripts from a vast transcriptome is a paramount priority, and challenge, for the lncRNA field. In this review, we aim to provide a conceptual and exptl. framework for classifying and elucidating lncRNA function. We categorize lncRNA loci into those that regulate gene expression in cis vs. those that perform functions in trans and propose an exptl. approach to dissect lncRNA activity based on these classifications. These strategies to further understand lncRNAs promise to reveal new and unanticipated biol. with great potential to advance our understanding of normal physiol. and disease.
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    Freitas, A. A. Comprehensible classification models: a position paper. SIGKDD Explor. Newsl. 2014, 15 (1), 1– 10,  DOI: 10.1145/2594473.2594475
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    Tzelepis, K.; Koike-Yusa, H.; De Braekeleer, E.; Li, Y.; Metzakopian, E.; Dovey, O. M.; Mupo, A.; Grinkevich, V.; Li, M.; Mazan, M.; Gozdecka, M.; Ohnishi, S.; Cooper, J.; Patel, M.; McKerrell, T.; Chen, B.; Domingues, A. F.; Gallipoli, P.; Teichmann, S.; Ponstingl, H.; McDermott, U.; Saez-Rodriguez, J.; Huntly, B. J. P.; Iorio, F.; Pina, C.; Vassiliou, G. S.; Yusa, K. A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia. Cell Rep. 2016, 17 (4), 1193– 1205,  DOI: 10.1016/j.celrep.2016.09.079
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    A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia
    Tzelepis, Konstantinos; Koike-Yusa, Hiroko; De Braekeleer, Etienne; Li, Yilong; Metzakopian, Emmanouil; Dovey, Oliver M.; Mupo, Annalisa; Grinkevich, Vera; Li, Meng; Mazan, Milena; Gozdecka, Malgorzata; Ohnishi, Shuhei; Cooper, Jonathan; Patel, Miten; McKerrell, Thomas; Chen, Bin; Domingues, Ana Filipa; Gallipoli, Paolo; Teichmann, Sarah; Ponstingl, Hannes; McDermott, Ultan; Saez-Rodriguez, Julio; Huntly, Brian J. P.; Iorio, Francesco; Pina, Cristina; Vassiliou, George S.; Yusa, Kosuke
    Cell Reports (2016), 17 (4), 1193-1205CODEN: CREED8; ISSN:2211-1247. (Cell Press)
    Acute myeloid leukemia (AML) is an aggressive cancer with a poor prognosis, for which mainstream treatments have not changed for decades. To identify addnl. therapeutic targets in AML, we optimize a genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screening platform and use it to identify genetic vulnerabilities in AML cells. We identify 492 AML-specific cell-essential genes, including several established therapeutic targets such as DOT1L, BCL2, and MEN1, and many other genes including clin. actionable candidates. We validate selected genes using genetic and pharmacol. inhibition, and chose KAT2A as a candidate for downstream study. KAT2A inhibition demonstrated anti-AML activity by inducing myeloid differentiation and apoptosis, and suppressed the growth of primary human AMLs of diverse genotypes while sparing normal hemopoietic stem-progenitor cells. Our results propose that KAT2A inhibition should be investigated as a therapeutic strategy in AML and provide a large no. of genetic vulnerabilities of this leukemia that can be pursued in downstream studies.
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    Dobin, A.; Davis, C. A.; Schlesinger, F.; Drenkow, J.; Zaleski, C.; Jha, S.; Batut, P.; Chaisson, M.; Gingeras, T. R. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013, 29 (1), 15– 21,  DOI: 10.1093/bioinformatics/bts635
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    STAR: ultrafast universal RNA-seq aligner
    Dobin, Alexander; Davis, Carrie A.; Schlesinger, Felix; Drenkow, Jorg; Zaleski, Chris; Jha, Sonali; Batut, Philippe; Chaisson, Mark; Gingeras, Thomas R.
    Bioinformatics (2013), 29 (1), 15-21CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
    Motivation: Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results: To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Ref. (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential max. mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per h on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addn. to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we exptl. validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy.
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    Ramírez, F.; Ryan, D. P.; Grüning, B.; Bhardwaj, V.; Kilpert, F.; Richter, A. S.; Heyne, S.; Dündar, F.; Manke, T. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 2016, 44 (W1), W160– W165,  DOI: 10.1093/nar/gkw257
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    deepTools2: a next generation web server for deep-sequencing data analysis
    Ramirez, Fidel; Ryan, Devon P.; Gruening, Bjoern; Bhardwaj, Vivek; Kilpert, Fabian; Richter, Andreas S.; Heyne, Steffen; Duendar, Friederike; Manke, Thomas
    Nucleic Acids Research (2016), 44 (W1), W160-W165CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
    We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solns. for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. DeepTools continue to be open to all users and freely available as a web service. The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available.
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    Quinlan, A. R.; Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 2010, 26 (6), 841– 842,  DOI: 10.1093/bioinformatics/btq033
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    BEDTools: a flexible suite of utilities for comparing genomic features
    Quinlan, Aaron R.; Hall, Ira M.
    Bioinformatics (2010), 26 (6), 841-842CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
    Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with std. UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets.
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    Li, H.; Handsaker, B.; Wysoker, A.; Fennell, T.; Ruan, J.; Homer, N.; Marth, G.; Abecasis, G.; Durbin, R.; Genome Project Data Processing, S. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009, 25 (16), 2078– 2079,  DOI: 10.1093/bioinformatics/btp352
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    The Sequence Alignment/Map format and SAMtools
    Li, Heng; Handsaker, Bob; Wysoker, Alec; Fennell, Tim; Ruan, Jue; Homer, Nils; Marth, Gabor; Abecasis, Goncalo; Durbin, Richard
    Bioinformatics (2009), 25 (16), 2078-2079CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
    Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against ref. sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: [email protected]
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    MEME-ChIP: motif analysis of large DNA datasets
    Machanick, Philip; Bailey, Timothy L.
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Cited By

This article is cited by 1 publications.

  1. Allen C. Zhu, Chuan He. Global Detection of RNA Methylation by Click Degradation. ACS Central Science 2020, 6 (12) , 2126-2129. https://doi.org/10.1021/acscentsci.0c01449

  • Abstract

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    Figure 1

    Figure 1. meCLICK-Seq, a small molecule-based methylated RNA editing platform. (a) Proposed mechanism of action of meCLICK-Seq. (b) Conversion of PropSeMet into SeAdoYn and subsequent introduction of propargyl groups into RNA. (c) Functionalization of propargylated RNA with the click-degrader. (d) Proposed mechanism of the general base RNA degradation. (e) Copper-mediated RNA degradation.

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    Figure 2

    Figure 2. Study of the chemical mechanism of click-degraders. (a) Time-dependent degradation of click-degrader 1 functionalized RNA 11-mer at 37 °C. n = 2. (b) Extent of RNA degradation after 14 h at 37 °C, pH 7.5, n = 2. (c) Extent of RNA degradation after 14 h at 37 °C, pH 3.0, n = 2. (d) Extent of RNA degradation in neutral and acidic conditions, n = 2. (e) Extent of RNA degradation after 14 h at 37 °C, pH 7.5, with PEG linkers of differing lengths. Cinitial corresponds to initial concentration; C corresponds to concentration at a specified time point. Click-degraders 1, 2, and 3 have linkers with 6, 4, and 2 PEG subunits, respectively, n = 2. Error bars represent SD.

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    Figure 3

    Figure 3. meCLICK-Seq elucidates the relationship between m6A writers and methylation of mRNAs and lncRNAs. (a) meCLICK-Seq workflow. (b) Western blots demonstrate the extent of METTL3 and METTL16 depletion in conditional knock-down MOLM-13 cells treated with PropSeMet. Application of click-degrader does not significantly alter the levels of MTases. (c) Heat map showing decrease of methylated mRNA levels upon clicking and rescue of METTL3-dependent transcripts upon METTL3 depletion. (d) Overlap of m6A-containing mRNAs determined through m6A miCLIP and METTL3 mRNA substrates determined by meCLICK-Seq; significance indicated by Fisher’s exact test. (e) RT-qPCR-based meCLICK-Seq validation of a panel of genes, n = 3. (f) RT-qPCR-based meCLICK-Seq validation of a panel of genes in METTL3 depleted cells, n = 3. (g) Genome browser snapshot of NEAT1. Applying click machinery diminishes the WT but not METTL3 or METTL16 levels. p values determined with one-tailed t test. ns = not significant (p ≥ 0.05). Error bars represent SD.

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    Figure 4

    Figure 4. meCLICK-Seq reveals widespread m6A mark in introns and intergenic regions. (a) Intronic peaks in the first intron of FLI1. (b) Intronic peaks in the first intron of CADM1 in three isogenic cell models. Intronic peaks are abolished specifically in METTL16-KD cells. (c) Overlap between METTL3- and METTL16-dependent intronic peaks. (d) Distribution of METTL3-dependent peaks in intronic and intergenic regions. (e) Distribution of METTL16-dependent peaks in intronic and intergenic regions. (f) RT-qPCR-based validation of a panel intronic peaks, n = 3. (g) Validation of dependence of intronic peaks on RNA methylases METTL3 and METTL16, n = 3. (h) Results of m6A-RIP in cells with methylated introns removed by dual gRNA system, n = 3. (i) Results of m6A-RIP in cells with depleted METTL3, n = 3. (j) Results of m6A-RIP in cells with depleted METTL16. RASA3 peak 2 is not affected by the knock-down illustrating that the observed effect is enzyme-specific, n = 3. ns = not significant (p ≥ 0.05). Error bars represent SD.

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      Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome
      Linder, Bastian; Grozhik, Anya V.; Olarerin-George, Anthony O.; Meydan, Cem; Mason, Christopher E.; Jaffrey, Samie R.
      Nature Methods (2015), 12 (8), 767-772CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)
      N6-methyladenosine (m6A) is the most abundant modified base in eukaryotic mRNA and has been linked to diverse effects on mRNA fate. Current mapping approaches localize m6A residues to transcript regions 100-200 nt long but cannot identify precise m6A positions on a transcriptome-wide level. Here we developed m6A individual-nucleotide-resoln. crosslinking and immunopptn. (miCLIP) and used it to demonstrate that antibodies to m6A can induce specific mutational signatures at m6A residues after UV light-induced antibody-RNA crosslinking and reverse transcription. We found that these antibodies similarly induced mutational signatures at N6,2'-O-dimethyladenosine (m6Am), a modification found at the first nucleotide of certain mRNAs. Using these signatures, we mapped m6A and m6Am at single-nucleotide resoln. in human and mouse mRNA and identified small nucleolar RNAs (snoRNAs) as a new class of m6A-contg. non-coding RNAs (ncRNAs).
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    13. 13
      Zhang, Z.; Chen, L.-Q.; Zhao, Y.-L.; Yang, C.-G.; Roundtree, I. A.; Zhang, Z.; Ren, J.; Xie, W.; He, C.; Luo, G.-Z. Single-base mapping of m6A by an antibody-independent method. Sci. Adv. 2019, 5 (7), eaax0250,  DOI: 10.1126/sciadv.aax0250
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      Meyer, K. D. DART-seq: an antibody-free method for global m6A detection. Nat. Methods 2019, 16 (12), 1275– 1280,  DOI: 10.1038/s41592-019-0570-0
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      14
      DART-seq: an antibody-free method for global m6A detection
      Meyer, Kate D.
      Nature Methods (2019), 16 (12), 1275-1280CODEN: NMAEA3; ISSN:1548-7091. (Nature Research)
      N6-methyladenosine (m6A) is a widespread RNA modification that influences nearly every aspect of the mRNA lifecycle. Our understanding of m6A has been facilitated by the development of global m6A mapping methods, which use antibodies to immunoppt. methylated RNA. However, these methods have several limitations, including high input RNA requirements and cross-reactivity to other RNA modifications. Here, we present DART-seq (deamination adjacent to RNA modification targets), an antibody-free method for detecting m6A sites. In DART-seq, the cytidine deaminase APOBEC1 is fused to the m6A-binding YTH domain. APOBEC1-YTH expression in cells induces C-to-U deamination at sites adjacent to m6A residues, which are detected using std. RNA-seq. DART-seq identifies thousands of m6A sites in cells from as little as 10 ng of total RNA and can detect m6A accumulation in cells over time. Addnl., we use long-read DART-seq to gain insights into m6A distribution along the length of individual transcripts.
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    15. 15
      Wang, Y.; Xiao, Y.; Dong, S.; Yu, Q.; Jia, G. Antibody-free enzyme-assisted chemical approach for detection of N6-methyladenosine. Nat. Chem. Biol. 2020, 16 (8), 896– 903,  DOI: 10.1038/s41589-020-0525-x
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      15
      Antibody-free enzyme-assisted chemical approach for detection of N6-methyladenosine
      Wang, Ye; Xiao, Yu; Dong, Shunqing; Yu, Qiong; Jia, Guifang
      Nature Chemical Biology (2020), 16 (8), 896-903CODEN: NCBABT; ISSN:1552-4450. (Nature Research)
      The inert chem. property of RNA modification N6-methyladenosine (m6A) makes it very challenging to detect. Most m6A sequencing methods rely on m6A-antibody immunopptn. and cannot distinguish m6A and N6,2'-O-dimethyladenosine modification at the cap +1 position (cap m6Am). Although the two antibody-free methods (m6A-REF-seq/MAZTER-seq and DART-seq) have been developed recently, they are dependent on m6A sequence or cellular transfection. Here, the authors present an antibody-free, FTO-assisted chem. labeling method termed m6A-SEAL for specific m6A detection. The authors applied m6A-SEAL to profile m6A landscapes in humans and plants, which displayed the known m6A distribution features in transcriptome. By doing a comparison with all available m6A sequencing methods and specific m6A sites validation by SELECT, m6A-SEAL has good sensitivity, specificity and reliability for transcriptome-wide detection of m6A. Given its tagging ability and FTO's oxidn. property, m6A-SEAL enables many applications such as enrichment, imaging and sequencing to drive future functional studies of m6A and other modifications.
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    16. 16
      Hartstock, K.; Nilges, B. S.; Ovcharenko, A.; Cornelissen, N. V.; Püllen, N.; Lawrence-Dörner, A.-M.; Leidel, S. A.; Rentmeister, A. Enzymatic or In Vivo Installation of Propargyl Groups in Combination with Click Chemistry for the Enrichment and Detection of Methyltransferase Target Sites in RNA. Angew. Chem., Int. Ed. 2018, 57 (21), 6342– 6346,  DOI: 10.1002/anie.201800188
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      16
      Enzymatic or In Vivo Installation of Propargyl Groups in Combination with Click Chemistry for the Enrichment and Detection of Methyltransferase Target Sites in RNA
      Hartstock, Katja; Nilges, Benedikt S.; Ovcharenko, Anna; Cornelissen, Nicolas V.; Puellen, Nikolai; Lawrence-Doerner, Ann-Marie; Leidel, Sebastian A.; Rentmeister, Andrea
      Angewandte Chemie, International Edition (2018), 57 (21), 6342-6346CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)
      N6-methyladenosine (m6A) is the most abundant internal modification in eukaryotic mRNA. It is introduced by METTL3-METTL14 and tunes mRNA metab., impacting cell differentiation and development. Precise transcriptome-wide assignment of m6A sites is of utmost importance. However, m6A does not interfere with Watson-Crick base pairing, making polymerase-based detection challenging. We developed a chem. biol. approach for the precise mapping of methyltransferase (MTase) target sites based on the introduction of a bioorthogonal propargyl group in vitro and in cells. We show that propargyl groups can be introduced enzymically by wild-type METTL3-METTL14. Reverse transcription terminated up to 65 % at m6A sites after bioconjugation and purifn., hence enabling detection of METTL3-METTL14 target sites by next generation sequencing. Importantly, we implemented metabolic propargyl labeling of RNA MTase target sites in vivo based on propargyl-L-selenohomocysteine and validated different types of known rRNA methylation sites.
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    17. 17
      Raines, R. T. Ribonuclease A. Chem. Rev. 1998, 98 (3), 1045– 1066,  DOI: 10.1021/cr960427h
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      17
      Ribonuclease A
      Raines, Ronald T.
      Chemical Reviews (Washington, D. C.) (1998), 98 (3), 1045-1065CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
      A review with 420 refs., of the structure and function of RNase A, with emphasis on applications of recombinant DNA technol. and nucleic acid chem.
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    18. 18
      Cheng, L.; Abhilash, K. G.; Breslow, R. Binding and biomimetic cleavage of the RNA poly(U) by synthetic polyimidazoles. Proc. Natl. Acad. Sci. U. S. A. 2012, 109 (32), 12884,  DOI: 10.1073/pnas.1210846109
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      18
      Binding and biomimetic cleavage of the RNA poly(U) by synthetic polyimidazoles
      Cheng, Liang; Abhilash, K. G.; Breslow, Ronald
      Proceedings of the National Academy of Sciences of the United States of America (2012), 109 (32), 12884-12887, S12884/1-S12884/5CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      Four polyimidazoles were used in the binding and cleavage studies with poly(U). The two polydisperse polyvinylimidazoles were previously described by others, while the other two new polymers of polyethyleneimines were prepd. by cationic polymn. of oxazolines. The latter had imidazole units attached to each nitrogen of the polymers. They were characterized by gel permeation chromatog. and had very low polydispersities. When they were partially protonated they bound to the poly(U) and catalyzed its cleavage by a process analogous to that used by the enzyme RNase A. The kinetics of the cleavage were followed by an assay we had previously described using phosphodiesterase I from Crotalus venom after the cleavage processes. Cleavage of poly(U) with Zn2+ was also examd., with and without the polymers. A scheme is described in which these cleavages could be made sequence selective with various RNAs, particularly with important targets, such as viral RNAs.
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    19. 19
      Beloglazova, N. G.; Fabani, M. M.; Zenkova, M. A.; Bichenkova, E. V.; Polushin, N. N.; Sil’nikov, V. V.; Douglas, K. T.; Vlassov, V. V. Sequence-specific artificial ribonucleases. I. Bis -imidazole-containing oligonucleotide conjugates prepared using precursor-based strategy. Nucleic Acids Res. 2004, 32 (13), 3887– 3897,  DOI: 10.1093/nar/gkh702
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      19
      Sequence-specific artificial ribonucleases. I. Bis-imidazole-containing oligonucleotide conjugates prepared using precursor-based strategy
      Beloglazova, Natalia G.; Fabani, Martin M.; Zenkova, Marina A.; Bichenkova, Elena V.; Polushin, Nikolai N.; Sil'nikov, Vladimir V.; Douglas, Kenneth T.; Vlassov, Valentin V.
      Nucleic Acids Research (2004), 32 (13), 3887-3897CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
      Antisense oligonucleotide conjugates, bearing constructs with two imidazole residues, were synthesized using a precursor-based technique employing post-synthetic histamine functionalization of oligonucleotides bearing methoxyoxalamido precursors at the 5'-termini. The conjugates were assessed in terms of their cleavage activities using both biochem. assays and conformational anal. by mol. modeling. The oligonucleotide part of the conjugates was complementary to the T-arm of yeast tRNAPhe (44-60 nt) and was expected to deliver imidazole groups near the fragile sequence C61-ACA-G65 of the tRNA. The conjugates showed RNase activity at neutral pH and physiol. temp. resulting in complete cleavage of the target RNA, mainly at the C63-A64 phosphodiester bond. For some constructs, cleavage was completed within 1-2 h under optimal conditions. Mol. modeling was used to det. the preferred orientation(s) of the cleaving group(s) in the complexes of the conjugates with RNA target. Cleaving constructs bearing two imidazole residues were found to be conformationally highly flexible, adopting no preferred specific conformation. No interactions other than complementary base pairing between the conjugates and the target were found to be the factors stabilizing the active cleaving conformation(s).
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    20. 20
      Li, Z.-R.; Li, J.; Cai, W.; Lai, J. Y. H.; McKinnie, S. M. K.; Zhang, W.-P.; Moore, B. S.; Zhang, W.; Qian, P.-Y. Macrocyclic colibactin induces DNA double-strand breaks via copper-mediated oxidative cleavage. Nat. Chem. 2019, 11 (10), 880– 889,  DOI: 10.1038/s41557-019-0317-7
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      20
      Macrocyclic colibactin induces DNA double-strand breaks via copper-mediated oxidative cleavage
      Li, Zhong-Rui; Li, Jie; Cai, Wenlong; Lai, Jennifer Y. H.; McKinnie, Shaun M. K.; Zhang, Wei-Peng; Moore, Bradley S.; Zhang, Wenjun; Qian, Pei-Yuan
      Nature Chemistry (2019), 11 (10), 880-889CODEN: NCAHBB; ISSN:1755-4330. (Nature Research)
      Colibactin is an assumed human gut bacterial genotoxin, whose biosynthesis is linked to the clb genomic island that has a widespread distribution in pathogenic and commensal human enterobacteria. Colibactin-producing gut microbes promote colon tumor formation and enhance the progression of colorectal cancer via cellular senescence and death induced by DNA double-strand breaks (DSBs); however, the chem. basis that contributes to the pathogenesis at the mol. level has not been fully characterized. Here, the authors report the discovery of colibactin-645, a macrocyclic colibactin metabolite that recapitulates the previously assumed genotoxicity and cytotoxicity. Colibactin-645 shows strong DNA DSB activity in vitro and in human cell cultures via a unique copper-mediated oxidative mechanism. The authors also delineate a complete biosynthetic model for colibactin-645, which highlights a unique fate of the aminomalonate-building monomer in forming the C-terminal 5-hydroxy-4-oxazolecarboxylic acid moiety through the activities of both the polyketide synthase ClbO and the amidase ClbL. This work thus provides a mol. basis for colibactin's DNA DSB activity and facilitates further mechanistic study of colibactin-related colorectal cancer incidence and prevention.
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    21. 21
      Peterson, J. R.; Thor, S.; Kohler, L.; Kohler, P. R. A.; Metcalf, W. W.; Luthey-Schulten, Z. Genome-wide gene expression and RNA half-life measurements allow predictions of regulation and metabolic behavior in Methanosarcina acetivorans. BMC Genomics 2016, 17, 924,  DOI: 10.1186/s12864-016-3219-8
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      21
      Genome-wide gene expression and RNA half-life measurements allow predictions of regulation and metabolic behavior in Methanosarcina acetivorans
      Peterson, Joseph R.; Thor, Sheng Shee; Kohler, Lars; Kohler, Petra R. A.; Metcalf, William W.; Luthey-Schulten, Zaida
      BMC Genomics (2016), 17 (), 924/1-924/23CODEN: BGMEET; ISSN:1471-2164. (BioMed Central Ltd.)
      While a few studies on the variations in mRNA expression and half-lives measured under different growth conditions have been used to predict patterns of regulation in bacterial organisms, the extent to which this information can also play a role in defining metabolic phenotypes has yet to be examd. systematically. Here we present the first comprehensive study for a model methanogen. We use expression and half-life data for the methanogen Methanosarcina acetivorans growing on fast- and slow-growth substrates to examine the regulation of its genes. Unlike Escherichia coli where only small shifts in half-lives were obsd., we found that most mRNA have significantly longer half-lives for slow growth on acetate compared to fast growth on methanol or trimethylamine. Interestingly, half-life shifts are not uniform across functional classes of enzymes, suggesting the existence of a selective stabilization mechanism for mRNAs. Using the transcriptomics data we detd. whether transcription or degrdn. rate controls the change in transcript abundance. Degrdn. was found to control abundance for about half of the metabolic genes underscoring its role in regulating metab. Genes involved in half of the metabolic reactions were found to be differentially expressed among the substrates suggesting the existence of drastically different metabolic phenotypes that extend beyond just the methanogenesis pathways. By integrating expression data with an updated metabolic model of the organism (iST807) significant differences in pathway flux and prodn. of metabolites were predicted for the three growth substrates. This study provides the first global picture of differential expression and half-lives for a class II methanogen, as well as provides the first evidence in a single organism that drastic genome-wide shifts in RNA half-lives can be modulated by growth substrate. We detd. which genes in each metabolic pathway control the flux and classified them as regulated by transcription (e.g. transcription factor) or degrdn. (e.g. post-transcriptional modification). We found that more than half of genes in metab. were controlled by degrdn. Our results suggest that M. acetivorans employs extensive post-transcriptional regulation to optimize key metabolic steps, and more generally that degrdn. could play a much greater role in optimizing an organism's metab. than previously thought.
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    22. 22
      Oivanen, M.; Kuusela, S.; Lönnberg, H. Kinetics and Mechanisms for the Cleavage and Isomerization of the Phosphodiester Bonds of RNA by Brønsted Acids and Bases. Chem. Rev. 1998, 98 (3), 961– 990,  DOI: 10.1021/cr960425x
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      22
      Kinetics and Mechanisms for the Cleavage and Isomerization of the Phosphodiester Bonds of RNA by Bronsted Acids and Bases
      Oivanen, Mikko; Kuusela, Satu; Loennberg, Harri
      Chemical Reviews (Washington, D. C.) (1998), 98 (3), 961-990CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
      A review with 240 refs. on acid/base catalyzed cleavage and isomerization of the 3',5'-phosphodiester bonds of DNA.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXis1yqu7s%253D&md5=890374fb922f9ad0d2d871d264b63c9c
    23. 23
      Barbieri, I.; Tzelepis, K.; Pandolfini, L.; Shi, J.; Millán-Zambrano, G.; Robson, S. C.; Aspris, D.; Migliori, V.; Bannister, A. J.; Han, N.; De Braekeleer, E.; Ponstingl, H.; Hendrick, A.; Vakoc, C. R.; Vassiliou, G. S.; Kouzarides, T. Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control. Nature 2017, 552 (7683), 126– 131,  DOI: 10.1038/nature24678
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      23
      Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control
      Barbieri, Isaia; Tzelepis, Konstantinos; Pandolfini, Luca; Shi, Junwei; Millan-Zambrano, Gonzalo; Robson, Samuel C.; Aspris, Demetrios; Migliori, Valentina; Bannister, Andrew J.; Han, Namshik; De Braekeleer, Etienne; Ponstingl, Hannes; Hendrick, Alan; Vakoc, Christopher R.; Vassiliou, George S.; Kouzarides, Tony
      Nature (London, United Kingdom) (2017), 552 (7683), 126-131CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
      N6-methyladenosine (m6A) is an abundant internal RNA modification in both coding and non-coding RNAs that is catalyzed by the METTL3-METTL14 methyltransferase complex. However, the specific role of these enzymes in cancer is still largely unknown. Here we define a pathway that is specific for METTL3 and is implicated in the maintenance of a leukemic state. We identify METTL3 as an essential gene for growth of acute myeloid leukemia cells in two distinct genetic screens. Downregulation of METTL3 results in cell cycle arrest, differentiation of leukemic cells and failure to establish leukemia in immunodeficient mice. We show that METTL3, independently of METTL14, assocs. with chromatin and localizes to the transcriptional start sites of active genes. The vast majority of these genes have the CAATT-box binding protein CEBPZ present at the transcriptional start site, and this is required for recruitment of METTL3 to chromatin. Promoter-bound METTL3 induces m6A modification within the coding region of the assocd. mRNA transcript, and enhances its translation by relieving ribosome stalling. We show that genes regulated by METTL3 in this way are necessary for acute myeloid leukemia. Together, these data define METTL3 as a regulator of a chromatin-based pathway that is necessary for maintenance of the leukemic state and identify this enzyme as a potential therapeutic target for acute myeloid leukemia.
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    24. 24
      Vu, L. P.; Pickering, B. F.; Cheng, Y.; Zaccara, S.; Nguyen, D.; Minuesa, G.; Chou, T.; Chow, A.; Saletore, Y.; MacKay, M.; Schulman, J.; Famulare, C.; Patel, M.; Klimek, V. M.; Garrett-Bakelman, F. E.; Melnick, A.; Carroll, M.; Mason, C. E.; Jaffrey, S. R.; Kharas, M. G. The N6-methyladenosine m6A-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells. Nat. Med. 2017, 23 (11), 1369– 1376,  DOI: 10.1038/nm.4416
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      24
      The N6-methyladenosine (m6A)-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells
      Vu, Ly P.; Pickering, Brian F.; Cheng, Yuanming; Zaccara, Sara; Nguyen, Diu; Minuesa, Gerard; Chou, Timothy; Chow, Arthur; Saletore, Yogesh; MacKay, Matthew; Schulman, Jessica; Famulare, Christopher; Patel, Minal; Klimek, Virginia M.; Garrett-Bakelman, Francine E.; Melnick, Ari; Carroll, Martin; Mason, Christopher E.; Jaffrey, Samie R.; Kharas, Michael G.
      Nature Medicine (New York, NY, United States) (2017), 23 (11), 1369-1376CODEN: NAMEFI; ISSN:1078-8956. (Nature Research)
      N6-methyladenosine (m6A) is an abundant nucleotide modification in mRNA that is required for the differentiation of mouse embryonic stem cells. However, it remains unknown whether the m6A modification controls the differentiation of normal and/or malignant myeloid hematopoietic cells. Here we show that shRNA-mediated depletion of the m6A-forming enzyme METTL3 in human hematopoietic stem/progenitor cells (HSPCs) promotes cell differentiation, coupled with reduced cell proliferation. Conversely, overexpression of wild-type METTL3, but not of a catalytically inactive form of METTL3, inhibits cell differentiation and increases cell growth. METTL3 mRNA and protein are expressed more abundantly in acute myeloid leukemia (AML) cells than in healthy HSPCs or other types of tumor cells. Furthermore, METTL3 depletion in human myeloid leukemia cell lines induces cell differentiation and apoptosis and delays leukemia progression in recipient mice in vivo. Single-nucleotide-resoln. mapping of m6A coupled with ribosome profiling reveals that m6A promotes the translation of c-MYC, BCL2 and PTEN mRNAs in the human acute myeloid leukemia MOLM-13 cell line. Moreover, loss of METTL3 leads to increased levels of phosphorylated AKT, which contributes to the differentiation-promoting effects of METTL3 depletion. Overall, these results provide a rationale for the therapeutic targeting of METTL3 in myeloid leukemia.
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    25. 25
      Pendleton, K. E.; Chen, B.; Liu, K.; Hunter, O. V.; Xie, Y.; Tu, B. P.; Conrad, N. K. The U6 snRNA m6A Methyltransferase METTL16 Regulates SAM Synthetase Intron Retention. Cell 2017, 169 (5), 824– 835,  DOI: 10.1016/j.cell.2017.05.003
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      25
      The U6 snRNA m6A methyltransferase METTL16 regulates SAM synthetase intron retention
      Pendleton, Kathryn E.; Chen, Beibei; Liu, Kuanqing; Hunter, Olga V.; Xie, Yang; Tu, Benjamin P.; Conrad, Nicholas K.
      Cell (Cambridge, MA, United States) (2017), 169 (5), 824-835.e14CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
      Maintenance of proper levels of the Me donor S-adenosylmethionine (SAM) is crit. for a wide variety of biol. processes. We demonstrate that the N6-adenosine methyltransferase METTL16 regulates expression of human MAT2A, which encodes the SAM synthetase expressed in most cells. Upon SAM depletion by methionine starvation, cells induce MAT2A expression by enhanced splicing of a retained intron. Induction requires METTL16 and its methylation substrate, a vertebrate conserved hairpin (hp1) in the MAT2A 3' UTR. Increasing METTL16 occupancy on the MAT2A 3' UTR is sufficient to induce efficient splicing. We propose that, under SAM-limiting conditions, METTL16 occupancy on hp1 increases due to inefficient enzymic turnover, which promotes MAT2A splicing. We further show that METTL16 is the long-unknown methyltransferase for the U6 spliceosomal small nuclear RNA (snRNA). These observations suggest that the conserved U6 snRNA methyltransferase evolved an addnl. function in vertebrates to regulate SAM homeostasis.
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    26. 26
      Bokar, J. A.; Shambaugh, M. E.; Polayes, D.; Matera, A. G.; Rottman, F. M. Purification and cDNA cloning of the AdoMet-binding subunit of the human mRNA (N6-adenosine)-methyltransferase. RNA 1997, 3 (11), 1233– 1247
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      Purification and cDNA cloning of the AdoMet-binding subunit of the human mRNA (N6-adenosine)-methyltransferase
      Bokar, Joseph A.; Shambaugh, Mary Eileen; Polayes, Deborah; Matera, A. Gregory; Rottman, Fritz M.
      RNA (1997), 3 (11), 1233-1247CODEN: RNARFU; ISSN:1355-8382. (Cambridge University Press)
      The methylation of internal adenosine residues in eukaryotic mRNA, forming N6-methyladenosine (m6A), is catalyzed by a complex multicomponent enzyme. Previous studies suggested that m6A affects the efficiency of mRNA processing or transport, although the mechanism by which this occurs is not known. As a step toward better understanding the mechanism and function of this ubiquitous posttranscriptional modification, the authors have shown that HeLa mRNA (N6-adenosine)-methyltransferase requires at least two sep. protein factors, MT-A and MT-B, and MT-A contains the AdoMet binding site on a 70-kDa subunit (MT-A70). MT-A70 was purified by conventional chromatog. and electrophoresis, and was microsequenced. The peptide sequence was used to design a degenerate oligodeoxynucleotide that in turn was used to isolate the cDNA clone coding for MT-A70 from a HeLa cDNA library. Recombinant MT-A70 was expressed as a fusion protein in bacteria and was used to generate anti-MT-A70 antisera in rabbits. These antisera recognize MT-A70 in HeLa nuclear exts. by western blot and are capable of depleting (N6-adenosine)-methyltransferase activity from HeLa nuclear ext., confirming that MT-A70 is a crit. subunit of (N6-adenosine)-methyltransferase. Northern blot anal. reveals that MT-A70 mRNA is present in a wide variety of human tissues and may undergo alternative splicing. MT-A70 cDNA probe hybridizes to a 2.0-kilobase (kb) polyadenylated RNA isolated from HeLa cells, whereas it hybridizes to two predominant RNA species (approx. 2.0 kb and 3.0 kb) using mRNA isolated from six different human tissues. Anal. of the cDNA sequence indicates that it codes for a 580-amino acid protein with a predicted MW = 65 kDa. The predicted protein contains sequences similar to consensus methylation motifs I and II identified in prokaryotic DNA (N6-adenosine)-methyltransferases, suggesting the functional conservation of peptide motifs. MT-A70 also contains a long region of homol. to the yeast protein SPO8, which is involved in induction of sporulation by an unknown mechanism.
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    27. 27
      Wiederschain, D.; Wee, S.; Chen, L.; Loo, A.; Yang, G.; Huang, A.; Chen, Y.; Caponigro, G.; Yao, Y.-M.; Lengauer, C.; Sellers, W. R.; Benson, J. D. Single-vector inducible lentiviral RNAi system for oncology target validation. Cell Cycle 2009, 8 (3), 498– 504,  DOI: 10.4161/cc.8.3.7701
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      Single-vector inducible lentiviral RNAi system for oncology target validation
      Wiederschain, Dmitri; Wee, Susan; Chen, Lin; Loo, Alice; Yang, Guizhi; Huang, Alan; Chen, Yan; Caponigro, Giordano; Yao, Yung-mae; Lengauer, Christoph; Sellers, William R.; Benson, John D.
      Cell Cycle (2009), 8 (3), 498-504CODEN: CCEYAS; ISSN:1538-4101. (Landes Bioscience)
      The use of RNA interference (RNAi) has enabled loss-of-function studies in mammalian cancer cells and has hence become crit. for identifying and validating cancer drug targets. Current transient siRNA and stable shRNA systems, however, have limited utility in accurately assessing the cancer dependency due to their short-lived effects and limited in vivo utility, resp. In this study, a single-vector lentiviral, Tet-inducible shRNA system (pLKO-Tet-On) was generated to allow for the rapid generation of multiple stable cell lines with regulatable shRNA expression. We demonstrate the advantages and versatility of this system by targeting two polycomb group proteins, Bmi-1 and Mel-18, in a no. of cancer cell lines. Our data show that pLKO-Tet-On-mediated knockdown is tightly regulated by the inducer tetracycline and its deriv., doxycycline, in a concn.- and time-dependent manner. Furthermore, target gene expression is fully restored upon withdrawal of the inducing agent. An addnl., 17 distinct gene products have been targeted by inducible shRNAs with robust regulation in all cases. Importantly, we functionally validate the ability of the pLKO-Tet-On vector to reversibly silence targeted transcripts in vivo. The versatile and robust inducible lentiviral RNAi system reported herein can therefore serve as a powerful tool to rapidly reveal tumor cell dependence.
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    28. 28
      Leger, A.; Amaral, P. P.; Pandolfini, L.; Capitanchik, C.; Capraro, F.; Barbieri, I.; Migliori, V.; Luscombe, N. M.; Enright, A. J.; Tzelepis, K.; Ule, J.; Fitzgerald, T.; Birney, E.; Leonardi, T.; Kouzarides, T. RNA modifications detection by comparative Nanopore direct RNA sequencing. bioRxiv 2019, 843136, https://www.biorxiv.org/content/10.1101/843136v1.
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      Doxtader, K. A.; Wang, P.; Scarborough, A. M.; Seo, D.; Conrad, N. K.; Nam, Y. Structural Basis for Regulation of METTL16, an S-Adenosylmethionine Homeostasis Factor. Mol. Cell 2018, 71 (6), 1001– 1011,  DOI: 10.1016/j.molcel.2018.07.025
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      29
      Structural Basis for Regulation of METTL16, an S-Adenosylmethionine Homeostasis Factor
      Doxtader, Katelyn A.; Wang, Ping; Scarborough, Anna M.; Seo, Dahee; Conrad, Nicholas K.; Nam, Yunsun
      Molecular Cell (2018), 71 (6), 1001-1011.e4CODEN: MOCEFL; ISSN:1097-2765. (Elsevier Inc.)
      S-adenosylmethionine (SAM) is an essential metabolite that acts as a cofactor for most methylation events in the cell. The N6-methyladenosine (m6A) methyltransferase METTL16 controls SAM homeostasis by regulating the abundance of SAM synthetase MAT2A mRNA in response to changing intracellular SAM levels. Here we present crystal structures of METTL16 in complex with MAT2A RNA hairpins to uncover crit. mol. mechanisms underlying the regulated activity of METTL16. The METTL16-RNA complex structures reveal at. details of RNA substrates that drive productive methylation by METTL16. In addn., we identify a polypeptide loop in METTL16 near the SAM binding site with an autoregulatory role. We show that mutations that enhance or repress METTL16 activity in vitro correlate with changes in MAT2A mRNA levels in cells. Thus, we demonstrate the structural basis for the specific activity of METTL16 and further suggest the mol. mechanisms by which METTL16 efficiency is tuned to regulate SAM homeostasis.
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    30. 30
      Yang, D.; Qiao, J.; Wang, G.; Lan, Y.; Li, G.; Guo, X.; Xi, J.; Ye, D.; Zhu, S.; Chen, W.; Jia, W.; Leng, Y.; Wan, X.; Kang, J. N6-Methyladenosine modification of lincRNA 1281 is critically required for mESC differentiation potential. Nucleic Acids Res. 2018, 46 (8), 3906– 3920,  DOI: 10.1093/nar/gky130
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      30
      N6-methyladenosine modification of lincRNA 1281 is critically required for mESC differentiation potential
      Yang, Dandan; Qiao, Jing; Wang, Guiying; Lan, Yuanyuan; Li, Guoping; Guo, Xudong; Xi, Jiajie; Ye, Dan; Zhu, Songcheng; Chen, Wen; Jia, Wenwen; Leng, Ye; Wan, Xiaoping; Kang, Jiuhong
      Nucleic Acids Research (2018), 46 (8), 3906-3920CODEN: NARHAD; ISSN:1362-4962. (Oxford University Press)
      Previous studies have revealed the crit. roles of N6-methyladenosine (m6A) modification of mRNA in embryonic stem cells (ESCs), but the biol. function of m6A in large intergenic noncoding RNA (lincRNA) is unknown. Here, we showed that the internal m6A modification of linc1281 mediates a competing endogenous RNA (ceRNA) model to regulate mouse ESC (mESC) differentiation. We demonstrated that loss of linc1281 compromises mESC differentiation and that m6A is highly enriched within linc1281 transcripts. Linc1281 with RRACU m6A sequence motifs, but not an m6A-deficient mutant, restored the phenotype in linc1281-depleted mESCs. Mechanistic analyses revealed that linc1281 ensures mESC identity by sequestering pluripotency-related let-7 family microRNAs (miRNAs), and this RNA-RNA interaction is m6A dependent. Collectively, these findings elucidated the functional roles of linc1281 and its m6A modification in mESCs and identified a novel RNA regulatory mechanism, providing a basis for further exploration of broad RNA epigenetic regulatory patterns.
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    31. 31
      Zhang, J.; Guo, S.; Piao, H.-Y.; Wang, Y.; Wu, Y.; Meng, X.-Y.; Yang, D.; Zheng, Z.-C.; Zhao, Y. ALKBH5 promotes invasion and metastasis of gastric cancer by decreasing methylation of the lncRNA NEAT1. J. Physiol. Biochem. 2019, 75 (3), 379– 389,  DOI: 10.1007/s13105-019-00690-8
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      31
      ALKBH5 promotes invasion and metastasis of gastric cancer by decreasing methylation of the lncRNA NEAT1
      Zhang, Jun; Guo, Shuai; Piao, Hai-yan; Wang, Yue; Wu, Yue; Meng, Xiang-yu; Yang, Dong; Zheng, Zhi-chao; Zhao, Yan
      Journal of Physiology and Biochemistry (2019), 75 (3), 379-389CODEN: JPBIF2; ISSN:1138-7548. (Springer)
      N6-Methyladenosine (m6A) is the most common posttranscriptional modification of RNA and plays crit. roles in cancer pathogenesis. However, the biol. function of long noncoding RNA (lncRNA) methylation remains unclear. As a demethylase, ALKBH5 (alkylation repair homolog protein 5) is involved in mediating methylation reversal. The purpose of this study was to investigate lncRNA m6A modification and its role in gastric cancer (GC). Bioinformatics predicted interactions of ALKBH5 with lncRNAs. Five methods were employed to assess the function of nuclear paraspeckle assembly transcript 1 (NEAT1), including gene silencing, RT-PCR, sepn. of nuclear and cytoplasmic fractions, scrape motility assays, and transwell migration assays. Then, m6A RNA immunopptn. and immunofluorescence were used to detect methylated NEAT1 in GC cells. Rescue assays were performed to define the relationship between NEAT1 and ALKBH5. NEAT1 is a potential binding lncRNA of ALKBH5. NEAT1 was overexpressed in GC cells and tissue. Addnl. expts. confirmed that knockdown of NEAT1 significantly repressed invasion and metastasis of GC cells. ALKBH5 affected the m6A level of NEAT1. The binding of ALKBH5 and NEAT1 influences the expression of EZH2 (a subunit of the polycomb repressive complex) and thus affects GC invasion and metastasis. Our findings indicate a novel mechanism by which ALKBH5 promotes GC invasion and metastasis by demethylating the lncRNA NEAT1. They may be potential therapeutic targets for GC.
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    32. 32
      Zhou, K. I.; Parisien, M.; Dai, Q.; Liu, N.; Diatchenko, L.; Sachleben, J. R.; Pan, T. N6-Methyladenosine Modification in a Long Noncoding RNA Hairpin Predisposes Its Conformation to Protein Binding. J. Mol. Biol. 2016, 428, 822– 833,  DOI: 10.1016/j.jmb.2015.08.021
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      32
      N6-Methyladenosine Modification in a Long Noncoding RNA Hairpin Predisposes Its Conformation to Protein Binding
      Zhou, Katherine I.; Parisien, Marc; Dai, Qing; Liu, Nian; Diatchenko, Luda; Sachleben, Joseph R.; Pan, Tao
      Journal of Molecular Biology (2016), 428 (5_Part_A), 822-833CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)
      N6-Methyladenosine (m6A) is a reversible and abundant internal modification of mRNA and long noncoding RNA (lncRNA) with roles in RNA processing, transport, and stability. Although m6A does not preclude Watson-Crick base pairing, the N6-Me group alters the stability of RNA secondary structure. Since changes in RNA structure can affect diverse cellular processes, the influence of m6A on mRNA and lncRNA structure has the potential to be an important mechanism for m6A function in the cell. Indeed, an m6A site in the lncRNA metastasis assocd. lung adenocarcinoma transcript 1 (MALAT1) was recently shown to induce a local change in structure that increases the accessibility of a U5-tract for recognition and binding by heterogeneous nuclear ribonucleoprotein C (HNRNPC). This m6A-dependent regulation of protein binding through a change in RNA structure, termed "m6A-switch", affects transcriptome-wide mRNA abundance and alternative splicing. To further characterize this first example of an m6A-switch in a cellular RNA, we used NMR and Forester resonance energy transfer to demonstrate the effect of m6A on a 32-nucleotide RNA hairpin derived from the m6A-switch in MALAT1. The obsd. imino proton NMR resonances and Forester resonance energy transfer efficiencies suggest that m6A selectively destabilizes the portion of the hairpin stem where the U5-tract is located, increasing the solvent accessibility of the neighboring bases while maintaining the overall hairpin structure. The m6A-modified hairpin has a predisposed conformation that resembles the hairpin conformation in the RNA-HNRNPC complex more closely than the unmodified hairpin. The m6A-induced structural changes in the MALAT1 hairpin can serve as a model for a large family of m6A-switches that mediate the influence of m6A on cellular processes.
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    33. 33
      Huang, H.; Weng, H.; Zhou, K.; Wu, T.; Zhao, B. S.; Sun, M.; Chen, Z.; Deng, X.; Xiao, G.; Auer, F.; Klemm, L.; Wu, H.; Zuo, Z.; Qin, X.; Dong, Y.; Zhou, Y.; Qin, H.; Tao, S.; Du, J.; Liu, J.; Lu, Z.; Yin, H.; Mesquita, A.; Yuan, C. L.; Hu, Y.-C.; Sun, W.; Su, R.; Dong, L.; Shen, C.; Li, C.; Qing, Y.; Jiang, X.; Wu, X.; Sun, M.; Guan, J.-L.; Qu, L.; Wei, M.; Müschen, M.; Huang, G.; He, C.; Yang, J.; Chen, J. Histone H3 trimethylation at lysine 36 guides m6A RNA modification co-transcriptionally. Nature 2019, 567 (7748), 414– 419,  DOI: 10.1038/s41586-019-1016-7
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      33
      Histone H3 trimethylation at lysine 36 guides m6A RNA modification co-transcriptionally
      Huang, Huilin; Weng, Hengyou; Zhou, Keren; Wu, Tong; Zhao, Boxuan Simen; Sun, Mingli; Chen, Zhenhua; Deng, Xiaolan; Xiao, Gang; Auer, Franziska; Klemm, Lars; Wu, Huizhe; Zuo, Zhixiang; Qin, Xi; Dong, Yunzhu; Zhou, Yile; Qin, Hanjun; Tao, Shu; Du, Juan; Liu, Jun; Lu, Zhike; Yin, Hang; Mesquita, Ana; Yuan, Celvie L.; Hu, Yueh-Chiang; Sun, Wenju; Su, Rui; Dong, Lei; Shen, Chao; Li, Chenying; Qing, Ying; Jiang, Xi; Wu, Xiwei; Sun, Miao; Guan, Jun-Lin; Qu, Lianghu; Wei, Minjie; Muschen, Markus; Huang, Gang; He, Chuan; Yang, Jianhua; Chen, Jianjun
      Nature (London, United Kingdom) (2019), 567 (7748), 414-419CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
      DNA and histone modifications have notable effects on gene expression1. Being the most prevalent internal modification in mRNA, the N6-methyladenosine (m6A) mRNA modification is as an important post-transcriptional mechanism of gene regulation2-4 and has crucial roles in various normal and pathol. processes5-12. However, it is unclear how m6A is specifically and dynamically deposited in the transcriptome. Here we report that histone H3 trimethylation at Lys36 (H3K36me3), a marker for transcription elongation, guides m6A deposition globally. We show that m6A modifications are enriched in the vicinity of H3K36me3 peaks, and are reduced globally when cellular H3K36me3 is depleted. Mechanistically, H3K36me3 is recognized and bound directly by METTL14, a crucial component of the m6A methyltransferase complex (MTC), which in turn facilitates the binding of the m6A MTC to adjacent RNA polymerase II, thereby delivering the m6A MTC to actively transcribed nascent RNAs to deposit m6A co-transcriptionally. In mouse embryonic stem cells, phenocopying METTL14 knockdown, H3K36me3 depletion also markedly reduces m6A abundance transcriptome-wide and in pluripotency transcripts, resulting in increased cell stemness. Collectively, our studies reveal the important roles of H3K36me3 and METTL14 in detg. specific and dynamic deposition of m6A in mRNA, and uncover another layer of gene expression regulation that involves crosstalk between histone modification and RNA methylation.
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    34. 34
      Liu, J.; Dou, X.; Chen, C.; Chen, C.; Liu, C.; Xu, M. M.; Zhao, S.; Shen, B.; Gao, Y.; Han, D.; He, C. N6-methyladenosine of chromosome-associated regulatory RNA regulates chromatin state and transcription. Science 2020, 367 (6477), 580– 586,  DOI: 10.1126/science.aay6018
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      34
      N6-methyladenosine of chromosome-associated regulatory RNA regulates chromatin state and transcription
      Liu, Jun; Dou, Xiaoyang; Chen, Chuanyuan; Chen, Chuan; Liu, Chang; Xu, Meng Michelle; Zhao, Siqi; Shen, Bin; Gao, Yawei; Han, Dali; He, Chuan
      Science (Washington, DC, United States) (2020), 367 (6477), 580-586CODEN: SCIEAS; ISSN:1095-9203. (American Association for the Advancement of Science)
      N6-methyladenosine (m6A) regulates stability and translation of mRNA in various biol. processes. In this work, we show that knockout of the m6A writer Mettl3 or the nuclear reader Ythdc1 in mouse embryonic stem cells increases chromatin accessibility and activates transcription in an m6A-dependent manner. We found that METTL3 deposits m6A modifications on chromosome-assocd. regulatory RNAs (carRNAs), including promoter-assocd. RNAs, enhancer RNAs, and repeat RNAs. YTHDC1 facilitates the decay of a subset of these m6A-modified RNAs, esp. elements of the long interspersed element-1 family, through the nuclear exosome targeting-mediated nuclear degrdn. Reducing m6A methylation by METTL3 depletion or site-specific m6A demethylation of selected carRNAs elevates the levels of carRNAs and promotes open chromatin state and downstream transcription. Collectively, our results reveal that m6A on carRNAs can globally tune chromatin state and transcription.
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    35. 35
      Louloupi, A.; Ntini, E.; Conrad, T.; Ørom, U. A. V. Transient N6-Methyladenosine Transcriptome Sequencing Reveals a Regulatory Role of m6A in Splicing Efficiency. Cell Rep. 2018, 23 (12), 3429– 3437,  DOI: 10.1016/j.celrep.2018.05.077
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      35
      Transient N-6-Methyladenosine Transcriptome Sequencing Reveals a Regulatory Role of m6A in Splicing Efficiency
      Louloupi, Annita; Ntini, Evgenia; Conrad, Thomas; Oerom, Ulf Andersson Vang
      Cell Reports (2018), 23 (12), 3429-3437CODEN: CREED8; ISSN:2211-1247. (Cell Press)
      Splicing efficiency varies among transcripts, and tight control of splicing kinetics is crucial for coordinated gene expression. N-6-methyladenosine (m6A) is the most abundant RNA modification and is involved in regulation of RNA biogenesis and function. The impact of m6A on regulation of RNA splicing kinetics is unknown. Here, we provide a time-resolved high-resoln. assessment of m6A on nascent RNA transcripts and unveil its importance for the control of RNA splicing kinetics. We find that early co-transcriptional m6A deposition near splice junctions promotes fast splicing, while m6A modifications in introns are assocd. with long, slowly processed introns and alternative splicing events. In conclusion, we show that early m6A deposition specifies the fate of transcripts regarding splicing kinetics and alternative splicing.
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    36. 36
      Mendel, M.; Chen, K.-M.; Homolka, D.; Gos, P.; Pandey, R. R.; McCarthy, A. A.; Pillai, R. S. Methylation of Structured RNA by the m6A Writer METTL16 Is Essential for Mouse Embryonic Development. Mol. Cell 2018, 71 (6), 986– 1000,  DOI: 10.1016/j.molcel.2018.08.004
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      Methylation of Structured RNA by the m6A Writer METTL16 Is Essential for Mouse Embryonic Development
      Mendel, Mateusz; Chen, Kuan-Ming; Homolka, David; Gos, Pascal; Pandey, Radha Raman; McCarthy, Andrew A.; Pillai, Ramesh S.
      Molecular Cell (2018), 71 (6), 986-1000.e11CODEN: MOCEFL; ISSN:1097-2765. (Elsevier Inc.)
      Internal modification of RNAs with N6-methyladenosine (m6A) is a highly conserved means of gene expression control. While the METTL3/METTL14 heterodimer adds this mark on thousands of transcripts in a single-stranded context, the substrate requirements and physiol. roles of the second m6A writer METTL16 remain unknown. Here we describe the crystal structure of human METTL16 to reveal a methyltransferase domain furnished with an extra N-terminal module, which together form a deep-cut groove that is essential for RNA binding. When presented with a random pool of RNAs, METTL16 selects for methylation-structured RNAs where the crit. adenosine is present in a bulge. Mouse 16-cell embryos lacking Mettl16 display reduced mRNA levels of its methylation target, the SAM synthetase Mat2a. The consequence is massive transcriptome dysregulation in ∼64-cell blastocysts that are unfit for further development. This highlights the role of an m6A RNA methyltransferase in facilitating early development via regulation of SAM availability.
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    37. 37
      Shima, H.; Matsumoto, M.; Ishigami, Y.; Ebina, M.; Muto, A.; Sato, Y.; Kumagai, S.; Ochiai, K.; Suzuki, T.; Igarashi, K. S-Adenosylmethionine Synthesis Is Regulated by Selective N6-Adenosine Methylation and mRNA Degradation Involving METTL16 and YTHDC1. Cell Rep. 2017, 21 (12), 3354– 3363,  DOI: 10.1016/j.celrep.2017.11.092
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      37
      S-Adenosylmethionine Synthesis Is Regulated by Selective N6-Adenosine Methylation and mRNA Degradation Involving METTL16 and YTHDC1
      Shima, Hiroki; Matsumoto, Mitsuyo; Ishigami, Yuma; Ebina, Masayuki; Muto, Akihiko; Sato, Yuho; Kumagai, Sayaka; Ochiai, Kyoko; Suzuki, Tsutomu; Igarashi, Kazuhiko
      Cell Reports (2017), 21 (12), 3354-3363CODEN: CREED8; ISSN:2211-1247. (Cell Press)
      S-adenosylmethionine (SAM) is an important metabolite as a methyl-group donor in DNA and histone methylation, tuning regulation of gene expression. Appropriate intracellular SAM levels must be maintained, because methyltransferase reaction rates can be limited by SAM availability. In response to SAM depletion, MAT2A, which encodes a ubiquitous mammalian methionine adenosyltransferase isoenzyme, was upregulated through mRNA stabilization. SAM-depletion reduced N6-methyladenosine (m6A) in the 3' UTR of MAT2A. In vitro reactions using recombinant METTL16 revealed multiple, conserved methylation targets in the 3' UTR. Knockdown of METTL16 and the m6A reader YTHDC1 abolished SAM-responsive regulation of MAT2A. Mutations of the target adenine sites of METTL16 within the 3' UTR revealed that these m6As were redundantly required for regulation. MAT2A mRNA methylation by METTL16 is read by YTHDC1, and we suggest that this allows cells to monitor and maintain intracellular SAM levels.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXitVWlsrbE&md5=95ed079e22ae359a395b3d11d58a494b
    38. 38
      Zhang, L.-S.; Liu, C.; Ma, H.; Dai, Q.; Sun, H.-L.; Luo, G.; Zhang, Z.; Zhang, L.; Hu, L.; Dong, X.; He, C. Transcriptome-wide Mapping of Internal N7-Methylguanosine Methylome in Mammalian mRNA. Mol. Cell 2019, 74 (6), 1304– 1316,  DOI: 10.1016/j.molcel.2019.03.036
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      Transcriptome-wide Mapping of Internal N7-Methylguanosine Methylome in Mammalian mRNA
      Zhang, Li-Sheng; Liu, Chang; Ma, Honghui; Dai, Qing; Sun, Hui-Lung; Luo, Guanzheng; Zhang, Zijie; Zhang, Linda; Hu, Lulu; Dong, Xueyang; He, Chuan
      Molecular Cell (2019), 74 (6), 1304-1316.e8CODEN: MOCEFL; ISSN:1097-2765. (Elsevier Inc.)
      N7-methylguanosine (m7G) is a pos. charged, essential modification at the 5' cap of eukaryotic mRNA, regulating mRNA export, translation, and splicing. M7G also occurs internally within tRNA and rRNA, but its existence and distribution within eukaryotic mRNA remain to be investigated. Here, we show the presence of internal m7G sites within mammalian mRNA. We then performed transcriptome-wide profiling of internal m7G methylome using m7G-MeRIP sequencing (MeRIP-seq). To map this modification at base resoln., we developed a chem.-assisted sequencing approach that selectively converts internal m7G sites into abasic sites, inducing misincorporation at these sites during reverse transcription. This base-resoln. m7G-seq enabled transcriptome-wide mapping of m7G in human tRNA and mRNA, revealing distribution features of the internal m7G methylome in human cells. We also identified METTL1 as a methyltransferase that installs a subset of m7G within mRNA and showed that internal m7G methylation could affect mRNA translation.
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      Lee, S.-H.; Singh, I.; Tisdale, S.; Abdel-Wahab, O.; Leslie, C. S.; Mayr, C. Widespread intronic polyadenylation inactivates tumour suppressor genes in leukaemia. Nature 2018, 561 (7721), 127– 131,  DOI: 10.1038/s41586-018-0465-8
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      Widespread intronic polyadenylation inactivates tumour suppressor genes in leukemia
      Lee, Shih-Han; Singh, Irtisha; Tisdale, Sarah; Abdel-Wahab, Omar; Leslie, Christina S.; Mayr, Christine
      Nature (London, United Kingdom) (2018), 561 (7721), 127-131CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
      DNA mutations are known cancer drivers. Here we investigated whether mRNA events that are upregulated in cancer can functionally mimic the outcome of genetic alterations. RNA sequencing or 3'-end sequencing techniques were applied to normal and malignant B cells from 59 patients with chronic lymphocytic leukemia (CLL)1-3. We discovered widespread upregulation of truncated mRNAs and proteins in primary CLL cells that were not generated by genetic alterations but instead occurred by intronic polyadenylation. Truncated mRNAs caused by intronic polyadenylation were recurrent (n = 330) and predominantly affected genes with tumor-suppressive functions. The truncated proteins generated by intronic polyadenylation often lack the tumor-suppressive functions of the corresponding full-length proteins (such as DICER and FOXN3), and several even acted in an oncogenic manner (such as CARD11, MGA and CHST11). In CLL, the inactivation of tumor-suppressor genes by aberrant mRNA processing is substantially more prevalent than the functional loss of such genes through genetic events. We further identified new candidate tumor-suppressor genes that are inactivated by intronic polyadenylation in leukemia and by truncating DNA mutations in solid tumors4,5. These genes are understudied in cancer, as their overall mutation rates are lower than those of well-known tumor-suppressor genes. Our findings show the need to go beyond genomic analyses in cancer diagnostics, as mRNA events that are silent at the DNA level are widespread contributors to cancer pathogenesis through the inactivation of tumor-suppressor genes.
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    40. 40
      Singh, I.; Lee, S.-H.; Sperling, A. S.; Samur, M. K.; Tai, Y.-T.; Fulciniti, M.; Munshi, N. C.; Mayr, C.; Leslie, C. S. Widespread intronic polyadenylation diversifies immune cell transcriptomes. Nat. Commun. 2018, 9 (1), 1716,  DOI: 10.1038/s41467-018-04112-z
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      Widespread intronic polyadenylation diversifies immune cell transcriptomes
      Singh Irtisha; Leslie Christina S; Singh Irtisha; Lee Shih-Han; Mayr Christine; Sperling Adam S; Samur Mehmet K; Tai Yu-Tzu; Fulciniti Mariateresa; Munshi Nikhil C
      Nature communications (2018), 9 (1), 1716 ISSN:.
      Alternative cleavage and polyadenylation (ApA) is known to alter untranslated region (3'UTR) length but can also recognize intronic polyadenylation (IpA) signals to generate transcripts that lose part or all of the coding region. We analyzed 46 3'-seq and RNA-seq profiles from normal human tissues, primary immune cells, and multiple myeloma (MM) samples and created an atlas of 4927 high-confidence IpA events represented in these cell types. IpA isoforms are widely expressed in immune cells, differentially used during B-cell development or in different cellular environments, and can generate truncated proteins lacking C-terminal functional domains. This can mimic ectodomain shedding through loss of transmembrane domains or alter the binding specificity of proteins with DNA-binding or protein-protein interaction domains. MM cells display a striking loss of IpA isoforms expressed in plasma cells, associated with shorter progression-free survival and impacting key genes in MM biology and response to lenalidomide.
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    41. 41
      Jung, H.; Lee, D.; Lee, J.; Park, D.; Kim, Y. J.; Park, W.-Y.; Hong, D.; Park, P. J.; Lee, E. Intron retention is a widespread mechanism of tumor-suppressor inactivation. Nat. Genet. 2015, 47 (11), 1242– 1248,  DOI: 10.1038/ng.3414
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      Intron retention is a widespread mechanism of tumor-suppressor inactivation
      Jung, Hyunchul; Lee, Donghoon; Lee, Jongkeun; Park, Donghyun; Kim, Yeon Jeong; Park, Woong-Yang; Hong, Dongwan; Park, Peter J.; Lee, Eunjung
      Nature Genetics (2015), 47 (11), 1242-1248CODEN: NGENEC; ISSN:1061-4036. (Nature Publishing Group)
      A substantial fraction of disease-causing mutations are pathogenic through aberrant splicing. Although genome profiling studies have identified somatic single-nucleotide variants (SNVs) in cancer, the extent to which these variants trigger abnormal splicing has not been systematically examd. Here we analyzed RNA sequencing and exome data from 1,812 patients with cancer and identified ∼900 somatic exonic SNVs that disrupt splicing. At least 163 SNVs, including 31 synonymous ones, were shown to cause intron retention or exon skipping in an allele-specific manner, with ∼70% of the SNVs occurring on the last base of exons. Notably, SNVs causing intron retention were enriched in tumor suppressors, and 97% of these SNVs generated a premature termination codon, leading to loss of function through nonsense-mediated decay or truncated protein. We also characterized the genomic features predictive of such splicing defects. Overall, this work demonstrates that intron retention is a common mechanism of tumor-suppressor inactivation.
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    42. 42
      Kopp, F.; Mendell, J. T. Functional Classification and Experimental Dissection of Long Noncoding RNAs. Cell 2018, 172 (3), 393– 407,  DOI: 10.1016/j.cell.2018.01.011
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      Functional classification and experimental dissection of long noncoding RNAs
      Kopp, Florian; Mendell, Joshua T.
      Cell (Cambridge, MA, United States) (2018), 172 (3), 393-407CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
      A review. Over the last decade, it has been increasingly demonstrated that the genomes of many species are pervasively transcribed, resulting in the prodn. of numerous long noncoding RNAs (lncRNAs). At the same time, it is now appreciated that many types of DNA regulatory elements, such as enhancers and promoters, regularly initiate bi-directional transcription. Thus, discerning functional noncoding transcripts from a vast transcriptome is a paramount priority, and challenge, for the lncRNA field. In this review, we aim to provide a conceptual and exptl. framework for classifying and elucidating lncRNA function. We categorize lncRNA loci into those that regulate gene expression in cis vs. those that perform functions in trans and propose an exptl. approach to dissect lncRNA activity based on these classifications. These strategies to further understand lncRNAs promise to reveal new and unanticipated biol. with great potential to advance our understanding of normal physiol. and disease.
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      Freitas, A. A. Comprehensible classification models: a position paper. SIGKDD Explor. Newsl. 2014, 15 (1), 1– 10,  DOI: 10.1145/2594473.2594475
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      Tzelepis, K.; Koike-Yusa, H.; De Braekeleer, E.; Li, Y.; Metzakopian, E.; Dovey, O. M.; Mupo, A.; Grinkevich, V.; Li, M.; Mazan, M.; Gozdecka, M.; Ohnishi, S.; Cooper, J.; Patel, M.; McKerrell, T.; Chen, B.; Domingues, A. F.; Gallipoli, P.; Teichmann, S.; Ponstingl, H.; McDermott, U.; Saez-Rodriguez, J.; Huntly, B. J. P.; Iorio, F.; Pina, C.; Vassiliou, G. S.; Yusa, K. A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia. Cell Rep. 2016, 17 (4), 1193– 1205,  DOI: 10.1016/j.celrep.2016.09.079
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      A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia
      Tzelepis, Konstantinos; Koike-Yusa, Hiroko; De Braekeleer, Etienne; Li, Yilong; Metzakopian, Emmanouil; Dovey, Oliver M.; Mupo, Annalisa; Grinkevich, Vera; Li, Meng; Mazan, Milena; Gozdecka, Malgorzata; Ohnishi, Shuhei; Cooper, Jonathan; Patel, Miten; McKerrell, Thomas; Chen, Bin; Domingues, Ana Filipa; Gallipoli, Paolo; Teichmann, Sarah; Ponstingl, Hannes; McDermott, Ultan; Saez-Rodriguez, Julio; Huntly, Brian J. P.; Iorio, Francesco; Pina, Cristina; Vassiliou, George S.; Yusa, Kosuke
      Cell Reports (2016), 17 (4), 1193-1205CODEN: CREED8; ISSN:2211-1247. (Cell Press)
      Acute myeloid leukemia (AML) is an aggressive cancer with a poor prognosis, for which mainstream treatments have not changed for decades. To identify addnl. therapeutic targets in AML, we optimize a genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screening platform and use it to identify genetic vulnerabilities in AML cells. We identify 492 AML-specific cell-essential genes, including several established therapeutic targets such as DOT1L, BCL2, and MEN1, and many other genes including clin. actionable candidates. We validate selected genes using genetic and pharmacol. inhibition, and chose KAT2A as a candidate for downstream study. KAT2A inhibition demonstrated anti-AML activity by inducing myeloid differentiation and apoptosis, and suppressed the growth of primary human AMLs of diverse genotypes while sparing normal hemopoietic stem-progenitor cells. Our results propose that KAT2A inhibition should be investigated as a therapeutic strategy in AML and provide a large no. of genetic vulnerabilities of this leukemia that can be pursued in downstream studies.
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    45. 45
      Dobin, A.; Davis, C. A.; Schlesinger, F.; Drenkow, J.; Zaleski, C.; Jha, S.; Batut, P.; Chaisson, M.; Gingeras, T. R. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013, 29 (1), 15– 21,  DOI: 10.1093/bioinformatics/bts635
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      STAR: ultrafast universal RNA-seq aligner
      Dobin, Alexander; Davis, Carrie A.; Schlesinger, Felix; Drenkow, Jorg; Zaleski, Chris; Jha, Sonali; Batut, Philippe; Chaisson, Mark; Gingeras, Thomas R.
      Bioinformatics (2013), 29 (1), 15-21CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
      Motivation: Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results: To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Ref. (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential max. mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per h on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addn. to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we exptl. validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy.
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    46. 46
      Ramírez, F.; Ryan, D. P.; Grüning, B.; Bhardwaj, V.; Kilpert, F.; Richter, A. S.; Heyne, S.; Dündar, F.; Manke, T. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 2016, 44 (W1), W160– W165,  DOI: 10.1093/nar/gkw257
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      46
      deepTools2: a next generation web server for deep-sequencing data analysis
      Ramirez, Fidel; Ryan, Devon P.; Gruening, Bjoern; Bhardwaj, Vivek; Kilpert, Fabian; Richter, Andreas S.; Heyne, Steffen; Duendar, Friederike; Manke, Thomas
      Nucleic Acids Research (2016), 44 (W1), W160-W165CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
      We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solns. for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. DeepTools continue to be open to all users and freely available as a web service. The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhtV2itrfI&md5=d4be278c28c75bdaea672a9420efef8f
    47. 47
      Quinlan, A. R.; Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 2010, 26 (6), 841– 842,  DOI: 10.1093/bioinformatics/btq033
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      BEDTools: a flexible suite of utilities for comparing genomic features
      Quinlan, Aaron R.; Hall, Ira M.
      Bioinformatics (2010), 26 (6), 841-842CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
      Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with std. UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets.
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXivFGkurc%253D&md5=508a4f647b8c205fdac8358528f3e835
    48. 48
      Li, H.; Handsaker, B.; Wysoker, A.; Fennell, T.; Ruan, J.; Homer, N.; Marth, G.; Abecasis, G.; Durbin, R.; Genome Project Data Processing, S. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009, 25 (16), 2078– 2079,  DOI: 10.1093/bioinformatics/btp352
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      48
      The Sequence Alignment/Map format and SAMtools
      Li, Heng; Handsaker, Bob; Wysoker, Alec; Fennell, Tim; Ruan, Jue; Homer, Nils; Marth, Gabor; Abecasis, Goncalo; Durbin, Richard
      Bioinformatics (2009), 25 (16), 2078-2079CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
      Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against ref. sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: [email protected]
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    49. 49
      Zhang, Y.; Liu, T.; Meyer, C. A.; Eeckhoute, J.; Johnson, D. S.; Bernstein, B. E.; Nussbaum, C.; Myers, R. M.; Brown, M.; Li, W.; Liu, X. S. Model-based Analysis of ChIP-Seq (MACS). Genome Biol. 2008, 9 (9), R137,  DOI: 10.1186/gb-2008-9-9-r137
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      Machanick, P.; Bailey, T. L. MEME-ChIP: motif analysis of large DNA datasets. Bioinformatics 2011, 27 (12), 1696– 1697,  DOI: 10.1093/bioinformatics/btr189
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      MEME-ChIP: motif analysis of large DNA datasets
      Machanick, Philip; Bailey, Timothy L.
      Bioinformatics (2011), 27 (12), 1696-1697CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
      Motivation: Advances in high-throughput sequencing have resulted in rapid growth in large, high-quality datasets including those arising from transcription factor (TF) ChIP-seq expts. While there are many existing tools for discovering TF binding site motifs in such datasets, most web-based tools cannot directly process such large datasets. Results: The MEME-ChIP web service is designed to analyze ChIP-seq peak regions'-short genomic regions surrounding declared ChIP-seq peaks'. Given a set of genomic regions, it performs (i) ab initio motif discovery, (ii) motif enrichment anal., (iii) motif visualization, (iv) binding affinity anal. and (v) motif identification. It runs two complementary motif discovery algorithms on the input data-MEME and DREME-and uses the motifs they discover in subsequent visualization, binding affinity and identification steps. MEME-ChIP also performs motif enrichment anal. using the AME algorithm, which can detect very low levels of enrichment of binding sites for TFs with known DNA-binding motifs. Importantly, unlike with the MEME web service, there is no restriction on the size or no. of uploaded sequences, allowing very large ChIP-seq datasets to be analyzed. The analyses performed by MEME-ChIP provide the user with a varied view of the binding and regulatory activity of the ChIP-ed TF, as well as the possible involvement of other DNA-binding TFs.
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  • Supporting Information

    Supporting Information

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acscentsci.0c01094.

    • Putative mass spectra peaks for the 11-mer after 2 hour degradation and for the functionalized and BCS-quenched 11-mer after 14 hour degradation, detected RNA species, oligomers used for the in vitro study, list of primers and gRNAs, analysis of propargylated and non-propargylated RNA oligomers degradation by click-degrader, predicted structures of oligomers used, analyses of CTRL and Prop oligomers, analysis of mRNA and lncRNA species, examples of intronic peak snapshots, analyses of METTL3- and METTL16-dependent peaks, comparison of methylated mRNAs determined via meCLICK-Seq and m7G-Seq, analysis of MeCLICK-Seq peaks and IPA sites, mass spectra of functionalized 11-mer species, and chemical synthesis and characterization including NMR spectra (PDF)

    • METTL3 and METTL16 mRNA substrates determined via meCLICK-Seq (TXT)

    • Results of a miCLIP study of m6A in MOLM13 cells (XLSX)

    • METTL3 and METTL16 lncRNA substrates determined via meCLICK-Seq (TXT)

    • METTL13 and METTL16-dependent intronic/intergenic peaks determined via meCLICK-Seq (XLSX)

    • Methylated mRNA species determined via meCLICK-Seq with an overlap with m7G-Seq study (XLSX)

    • Intronic and intergenic click-degrader sensitive RNA peaks with an overlap with m7G-Seq study (XLSX)


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