{"paper_id":"56c2fe70-efb2-47b4-9b67-f68ee7fe6672","body_text":"Widespread 3'UTR capped RNAs derive from G-rich regions in proximity to AGO2 binding sites | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Widespread 3'UTR capped RNAs derive from G-rich regions in proximity to AGO2 binding sites Nejc Haberman, Holly Digby, Rupert Faraway, Rebecca Cheung, Anob M. Chakrabarti, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4809688/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract The 3’ untranslated region (3’UTR) plays a crucial role in determining mRNA stability, localisation, translation and degradation. Cap analysis of gene expression (CAGE), a method for the detection of capped 5’ ends of mRNAs, additionally reveals a large number of apparently 5’ capped RNAs derived from locations within the body of the transcript, including 3’UTRs. Here we provide direct evidence that these 3’UTR-derived RNAs are indeed capped and widespread in mammalian cells. By using a combination of AGO2 enhanced individual nucleotide resolution UV crosslinking and immunoprecipitation (eiCLIP) and CAGE following siRNA treatment, we find that these 3’UTR-derived RNAs likely originate from AGO2-binding sites, and most often occur at locations with G-rich motifs bound by the RNA-binding protein UPF1. High-resolution imaging and long-read sequencing analysis validate several 3’UTR-derived RNAs, showcase their variable abundance and show that they may not co-localise with the parental mRNAs. Taken together, we provide new insights into the origin and prevalence of 3’UTR-derived RNAs, show the utility of CAGE-seq for their genome-wide detection, and provide a rich dataset for exploring new biology of a poorly understood new class of RNAs. 3’UTR CAGE capping AGO2 UPF1 3’UTR-derived RNA G-rich subcellular localisation Figures Figure 1 Figure 2 Figure 3 Figure 4 Background In all eukaryotes, mRNA molecules contain an evolutionarily conserved m7G cap (N7-methylated guanosine), which is incorporated at the 5’ end of nascent transcripts. Co-transcriptional capping is the first modification made to nascent RNA in the nucleus, which protects it from exonuclease cleavage while promoting cap-related biological functions such as pre-mRNA splicing, polyadenylation and nuclear export [ 1 ]. In addition to the co-transcriptional capping, there is also evidence for a post-transcriptional capping mechanism, in which an m7G cap is added to newly exposed 5’ ends of RNA fragments created upon endonucleolytic cleavage or decapping [ 2 – 5 ]. However, little is known about the extent and biological role of this post-transcriptional capping, and of its relation to other post-transcriptional RNA processing mechanisms. Cap analysis of gene expression and deep-sequencing (CAGE-seq) was originally designed to precisely determine transcription start site (TSS) positions by capturing and sequencing 5’ ends of capped mRNA transcripts, and it can also be used to measure gene expression [ 6 ]. However, several studies have detected the unexpected, reproducible, and so-far unexplained presence of CAGE signals (~ 10–15% of total reads) and/or an enrichment of RNA-seq reads mapping to 3’UTRs, far away from the usual TSS [ 7 – 15 ]. Previous studies have shown an absence of active promoter marks (i.e. no enrichment histone modifications or RNA polymerase II (RNAPII) occupancy) around these 3’UTR signals [ 7 , 9 , 16 ], arguing against the possibility that they are unannotated transcription start sites. Moreover, the expression of some of these capped 3’ UTRs is tissue-specific and regulated in mouse embryonic development, whilst their subcellular localization can be separated from the associated protein-coding transcript, suggesting that their generation is a regulated process [ 16 ]. In addition, specific isolated 3'UTRs have been implicated in a growing number of physiological processes, such as cell signalling or oxidative stress [ 7 , 17 , 18 ]. Moreover, several capped 3’UTRs have been reported to play important roles in regulating protein expression in trans , similar to long non-coding RNAs [ 7 , 9 , 10 ]. Truncated mRNAs and RNA decay intermediates can be subject to post-transcriptional, cytosolic capping [ 2 , 3 , 15 ] and it has been suggested that a similar mechanisms may underlie the generation of some 3’UTR CAGE signals, referred to as 3’UTR-associated RNAs (uaRNAs) [ 16 ]. To avoid potential misunderstandings we refer to these as 3’UTR-derived RNAs, as these newly generated RNAs are not known to be physically associated with 3’ UTRs. Here, we thoroughly examine the presence of these 3’UTR-derived RNAs across the transcriptome, and the molecular basis of their generation and characteristics. We perform a genome-wide identification of 3’ UTR-derived RNAs based on their capped 5’ ends, and proceed to investigate the mechanisms involved in their formation. To this end, we combine CAGE, RNA-seq and cross-linking immunoprecipitation (CLIP)-based techniques from ENCODE and FANTOM consortia. We show that 3’UTR-derived RNAs present biochemical properties similar to their 5’ capped counterparts and that they can be as abundant as the protein-coding version of the host transcript, or even more so. We reveal that the 5' ends of 3'UTR-derived RNAs are enriched in G-rich motifs and tend to form strong secondary structures, while the immediately upstream region of these 5' ends is bound by UPF1 and/or AGO2. Moreover, some of these abundant 3’ UTR-derived RNAs exhibit a markedly different subcellular localisation profile than their protein-coding counterparts. Finally we show, for the first time, that capped RNAs can also emerge following mRNA cleavage by small interfering RNAs (siRNAs). Results CAGE-seq identifies non-promoter associated capped 3'UTR-derived RNAs We and others [ 7 – 12 ] have previously reported the presence of CAGE-seq signals outside of annotated promoter regions in thousands of protein-coding genes. However, their origin or biological relevance has not been thoroughly interrogated. Here we first confirmed the prevalence of these signals in human cell lines using CAGE data provided by the ENCODE consortium. As expected, we detected a similar proportion of CAGE signals per genomic region in two different human cell lines (HeLa and K562) and showed that the CAGE signal is highly reproducible across replicates. This included the library size, number of uniquely mapped CAGE reads and distribution of the 5’ CAGE reads mapping to different genomic regions (Fig. 1 a, S1 a, b, c, d). A similar genomic distribution has also been detected by other groups before, using the same CAGE-seq protocol [ 19 ]. The relative intensities of CAGE signal detected at different genomic regions depend on the priming method for reverse transcription (oligo-dT, random hexamers, or mixtures thereof in different ratios) [ 12 ]. Oligo-dT priming quantitatively favours shorter transcripts, while the reverse is true for random priming. We subsequently verified CAGE signals within 3’UTRs are most detected when a combination of Oligo-dT and random primers is used, with the optimal inclusion ratio of 1 to 4 ratio of Oligo-dT to random primers [ 19 , 20 ] (Fig. S1 e). Notably, the same ratio was used in ENCODE CAGE samples analysed in this study. The CAGE signal is the strongest at 5'UTRs of known protein-coding genes [ 19 ] (Fig. 1 a, ~ 65% of total reads). While low-level non-promoter CAGE signal (sometimes referred to as “exon painting” [ 4 ] [ 21 ]), can be detected along the entire length of transcripts, the signal at 3’UTRs is consistently present and occurs in localised clusters, similar to CAGE signals at promoters (see Fig. S1 l for examples). We focused on the 3’UTR region, which contains a substantial proportion (~ 11%) of the total CAGE reads (Fig. 1 a), the implications of which are unknown. To identify robust CAGE signals with sufficient sensitivity, we used a 20nt window requiring at least two 5' reads overlapping from two different replicates for each cell line separately. This revealed 32,065 3’UTR CAGE clusters across all samples (Table S1 ). As expected, correlation between technical replicates was high (Pearson correlation (PC) > 0.9) for all CAGE signals, independently of genomic location (Fig. S1 g-j). Moreover, expression of the 3’UTR CAGE clusters was highly reproducible between HeLa and K562 samples (PC ~ 0.98, Fig. S1 f), suggesting biological relevance. Correlation across cell types was much higher for 3’UTR clusters than that for the 5’ UTR CAGE (PC ~ 0.79, Fig. S1 g) and CDS CAGE (PC of 0.61, Fig. S1 h) signals and comparable to intronic CAGE signal (PC ~ 0.93, Fig. S1 i). This may suggest that 3’UTR CAGE signals originate from more stable and/or less tissue specific subset of transcripts. Together these analyses show that the transcripts whose 5’ end map to 3’UTR ends of protein-coding genes are highly reproducible across cell types, and that CAGE is a robust method for their quantitative detection. 3'UTR-derived RNAs are confirmed by RNA-seq, qPCR and long-read CAGE Next, we aimed to confirm the existence of these 3’UTR capped RNAs using independent methods. First, we asked if these fragments could be identified in transcriptomic (RNA-seq) data. For this we compared the CAGE signal with the RNA-seq signal of two different cell lines. To categorise CAGE peaks we first used the paraclu [ 22 ] peak caller to identify clusters of 5’ ends of capped RNAs, and within each cluster we selected the highest signal as the dominant CAGE peak position. For comparison, we processed paired-end RNA-seq data from the same K562 and HeLa cell lines, then plotted read-starts and read-ends relative to the dominant 3’UTR CAGE peak per transcript (Fig. 1 b - in blue, and S1J). Both RNA-seq samples showed highly reproducible enrichments of read ends coinciding with dominant 3’UTR CAGE peaks. This reveals that the 3’UTR CAGE peaks are confirmed by the read-ends from reverse-stranded RNA-seq data, which suggests that the signal could be originating from post-transcriptional cleavage sites. Notably, there is also a small enrichment of RNA-seq read-starts downstream from the 3’UTR CAGE peaks, which could represent the same RNA fragments detectable by the CAGE samples (Fig. 1 b in yellow). More importantly, these findings demonstrate that 3’UTR capped fragments identified by CAGE can also be detected by other, methodologically independent, high-throughput sequencing methods such as RNA-seq. We next aimed to confirm the presence of transcripts initiating at the 3’UTR CAGE peaks by an alternative experimental approach, not dependent on RNA library creation or high-throughput sequencing. We focussed on two genes, CDKN1B/ p27kip1 (p27) and JPT2 , which contain a dominant CAGE peak located within the 3’UTR region, demonstrated with highly reproducible read coverage for CAGE and RNA-seq in both K562 and HeLa cells (see Fig. S1 m for example). Separate sets of primers were designed to quantitatively PCR-amplify ~ 150bp sequences within 300 nucleotides upstream and downstream of the 3’UTR CAGE peaks in CDKN1B and JPT2 (see Methods, Fig. S1 k). In agreement with CAGE and RNA-seq data (Fig. S1 m), RT-qPCR detected higher levels of these transcripts with the downstream primers (Fig. S1 K) than with upstream primers. A similar enrichment in RT-qPCR signal (Fig. S1 k) was observed with downstream primers in comparison to primers designed to amplify a ~ 150bp region spanning the CAGE peak in CDKN1B, suggesting an accumulation of 3’UTR fragments in comparison to full-length mRNAs. Treatment of the samples with TerminatorTM 5’-Phosphate-Dependent Exonuclease (TEX), a 5′→3′ exonuclease that digests RNA with a 5′ monophosphate, but not RNA with 5′-triphosphate, 5′-cap or 5′-hydroxyl group had no or little effect on the amount of JPT2 and CDKN1B transcripts detected with primers amplifying either side of the 3’UTR CAGE peak within these cells. This was in sharp contrast with the known uncapped 3’ fragment of SLC38A2 mRNA, previously described by Malka et al. [ 8 ], which was, as expected, sharply reduced upon TEX treatment (Fig. 1 c). These results lend further support that all the quantified transcripts, including the 3’UTR fragments, are capped. We further confirmed that 3’UTR-derived RNAs could be detected by long-read Nanopore-sequencing CAGE (Fig. 1 d). We were provided with data in cortical neuron samples by the FANTOM6 consortium for 10 genes that contain HeLa and K562 3’UTR CAGE peaks (Fig. 1 d, S1 n). In all of the 10 examples, the full length read sequencing CAGE identified reads spanning from the start of our identified CAGE 3’UTR peaks till the end of the annotated transcripts, whereas for most of these genes, reads spanning between the 5’CAGE and the 3’CAGE signal were absent (Fig. S1 n). These observations suggest that the capped 3’UTR derived RNAs originate from the full length mRNA whilst fragments upstream of the 3’CAGE may not be stable. Notable exceptions are DDX17 and GHITM but it is unclear whether these 3’CAGE upstream sequences result from alternative polyadenylation or are products from the cytosolic cleavage of the full-lenght. Capped 3’UTR-derived RNAs are evolutionarily conserved and generated post-transcriptionally We next wanted to investigate whether the 3’UTR CAGE signals originate from post-transcriptionally capped RNA fragments. First, we explored whether there is evidence of nuclear Cap Binding Complex (CBC) binding to the capped 5’ ends of 3'UTR fragments, as this protein is known to bind to 5’ ends of nascent protein-coding mRNA transcripts in the nucleus. Individual-nucleotide resolution UV crosslinking and immunoprecipitation (iCLIP) is a method that identifies protein-RNA crosslinking interactions with nucleotide resolution in a transcriptome-wide manner. We examined CBC-iCLIP data from HeLa cells, where the authors targeted nuclear cap-binding subunit CBP20 protein [ 23 ]. CBP20 is a nuclear component of cap-binding complex (CBC), which binds co-transcriptionally to the 5' cap of pre-mRNAs and interacts directly with the m7-G cap [ 24 , 25 ]. The CBP20 RNA binding data was analysed using a standard iCLIP processing pipeline, where the nucleotide preceding the cDNA-start position after PCR duplicate removal is reported as the crosslinking position (see Methods). The CBP20 crosslinking positions were then screened across all dominant 5’UTR and 3’UTR CAGE peaks per transcript. As expected, CBP20 crosslinks were enriched around the dominant 5’UTR CAGE peaks where the TSS of full-length transcripts is positioned. However, the enrichment was very weak at the non-promoter 3’UTR CAGE peaks (Fig. S2 a). This strongly indicates that the 3’UTR capped fragments identified by CAGE are not part of nuclear CBC, further suggesting that they are likely a product of an independent post-transcriptional processing pathway. To further explore whether the 3’UTR capped fragments were generated co-transcriptionally, we investigated the location of cap signals in nascent RNAs identified in global nuclear run-on sequencing experiments of 5’ capped RNAs (GRO-cap) [ 26 ]. As anticipated, strong GRO-cap signals overlapped with CAGE peaks in 5’UTRs and, to a lesser extent, with introns and upstream CDSs but were notably absent around 3’UTR CAGE peaks (Fig. S2 b). This also indicates that capping of 3’UTR fragments occurs post-transcriptionally. Additionally, we analysed capCLIP data from HeLa cells. capCLIP is a version of CLIP that targets the translation elongation factor eIF4E, a cytoplasmic protein which binds the 7-methyl-GTP moiety of the 5′-cap structure of RNAs to facilitate the efficient translation of almost all mRNAs [ 27 , 28 ]. The capCLIP data was analysed following the same methodology as CBP20-iCLIP. The enrichment of capCLIP signal at the non-promoter 3’UTR CAGE peaks was much stronger than in the CBC-iCLIP (Fig. S2 a, S2c), which demonstrates that the cap of the 3’UTR-derived RNAs is strongly bound by cytoplasmic eIF4E, but not the nuclear cap binding protein CBP20, suggesting that these RNAs are predominantly cytoplasmic. Furthermore, we investigated ribosome footprinting data [ 29 ] to interrogate whether the 3'UTR-derived RNAs, which are bound by eIF4E, are translated. However, we did not find evidence of ribosomal binding to these RNAs that suggested active translation (data not-shown). Next, we investigated the evolutionary conservation of 3’UTR-derived RNAs. Utilising UCSC conservation tracks, we computed conservation scores around 3’UTR CAGE peaks. To exclude the influence of coding regions and transcript termination sites, we specifically selected 21,831 3’UTR CAGE peaks positioned at least 150 bps away from the 3’UTR bordering region (≥ 150 bps downstream from CDS and ≥ 150 bps upstream from transcript termination). Remarkably, our findings reveal that the exact 3’UTR CAGE peaks exhibit lower conservation compared to the surrounding regions. However, the region immediately downstream of the 3’UTR CAGE peaks, corresponding to the \"body\" of 3’UTR-derived RNAs shows a notable enrichment in conservation scores, suggesting a potential functional contribution (Fig. S2 d). Altogether, these analyses confirm the presence of abundant, evolutionarily conserved, capped 3’UTR-derived non-coding RNAs that may originate from cytosolic cleavage of full-length mRNAs. 5' ends of 3'UTR-derived RNAs are enriched for G-rich motifs and strong secondary structures Next, we wanted to understand the sequence features that distinguish the CAGE peaks corresponding to co-transcriptional capping of TSS from those originating from post-transcriptional capping of 3'UTR-derived RNAs. We first explored the possibility that 3’UTR fragments might be a by-product of nuclear polyadenylation and associated endonucleolytic cleavage. If this were the case, the identified 3'UTR CAGE peaks should be preceded by enrichment of the canonical polyA signal (A[A/U]UAAA hexamers), which recruit the nuclear polyadenylation machinery. However, we only found such enrichment at the annotated 3'UTR ends, and not upstream of the 3'UTR CAGE peaks (Fig. S2 e). We observed a notable enrichment downstream of the 3’UTR CAGE peaks (Fig. S2 e - red line), which most likely corresponds to the canonical polyA site as some of the 3'UTR-derived RNAs are relatively short and their 5’ ends are close to the annotated 3'UTR ends. Next, we explored whether there were additional distinctive sequence characteristics between the two types of CAGE peaks. Consistent with previous studies [ 9 , 13 ], we detected a strong G-enrichment overlapping the 5’ end of the CAGE reads present in non-promoter regions (Fig. 2 a, S2 f), distinct from the YR dinucleotide characteristic of signals at 5’ ends of genes. More surprisingly, CAGE peaks within the 3’UTR region showed a strong increase in internal pairing probability (see Methods: Secondary structure) in comparison to CAGE peaks in other regions (Fig. 2 b, S2 g), suggesting that structural preference may be important for the generation of 3’UTR-derived RNAs. Notably, the surrounding (within 100 bps) region of CAGE peaks in 5’UTRs is more structured (light blue line in Fig. 2 b, S2 g), representing the higher GC content that is present around all 5’UTRs in vertebrates [ 30 ], with a distinctive drop at -25 bps coinciding with the canonical TATA box position. Motifs with G-rich repeats in the transcriptome can form non-canonical four-stranded structures (G4s) implicated in transcriptional regulation, mRNA processing, the regulation of translation and RNA translocation [ 31 ]. Similar to web-logo motif analyses of CAGE peaks from different mRNA regions (Fig. 2 a, S2 f), the nucleotide enrichment plot of GGG sequences showed the highest enrichment overlapping 3'UTR CAGE peaks (Fig. 2 c, S2 f). This raises the possibility that the sequence around the 3’UTR CAGE peaks may have an increased propensity to form RNA-G4 structures via the canonical G4 motif (G 3 -N 1 − 7 -G 3 -N 1 − 7 -G 3 -N 1 − 7 -G 3 ) [ 32 ]. To further explore the RNA G-quadruplexes formation profile, we integrated RNA-G-quadruplex sequencing (rG4-seq) data from HeLa cells [ 33 ] and ran G4-Hunter predictions [ 34 ] around CAGE peaks. Both the rG4-seq data (HeLa) and G4-Hunter predictions (K562) showed the highest G4s enrichment around CAGE peaks in the 3'UTR region (Fig. S2 h-l) with the highest percentage of rG4-seq hits within 3’UTRs (Fig. S2 m). Nevertheless, it is worth noting that the number of 3’CAGE sites overlapping with rG4-seq sites was relatively small (~ 3800 out of ~ 133900). In sharp contrast, 8 of the 10 gene examples with 3’UTR CAGE peaks and validated with long-read CAGE explored here (selected due to highest 3’UTR CAGE signal) contained rG4-seq clusters coinciding with 3’UTR CAGE peaks (Fig. S1 n). It is important to note that the determination of whether these sites are genuinely in the G4-folded state remains uncertain, as the rG4-seq method employs G4 stabilisers to artificially enhance G4 structures. 3’UTR CAGE sites are flanked by enriched UPF1 binding The evidence outlined so far is consistent with our hypothesis that capped 3’UTR-derived RNAs are formed post-transcriptionally. Next, we aimed to determine whether specific RNA-binding proteins (RBPs) were involved in the mechanism of their generation. To that end, we analysed publicly available enhanced CLIP (eCLIP) data for 80 different RBPs in the K562 cell line, produced by the ENCODE consortium [ 35 ]. For each RBP, we calculated normalised cross-linking enrichment compared to other RBPs around maximum CAGE peaks per annotated gene region (5’UTR, CDS, intron, 3’UTR). This identified a specific set of RBPs around CAGE peaks, with UPF1 (Up-frameshift protein 1) as the top candidate in 3’UTRs (Fig. 2 c), DDX3X (DEAD-Box Helicase 3 X-Linked) in 5’UTRs (Fig. S2 n), KHSRP (KH-type splicing regulatory protein) in introns (Fig. S2 o), and less protein specific enrichments in CDS with YBX3 (Y-Box-Binding Protein 3) as the top candidate (Fig. S2 o,p). UPF1 is involved in a variety of RNA degradation pathways [ 36 ], including Nonsense-Mediated Decay (NMD) [ 37 ] and the normal mRNA decay where stalled UPF1 at CUG and GC-rich motifs activates decay [ 38 ]. KHSRP plays a well-characterised role in pre-mRNA splicing, but has also been involved in several other aspects of RNA biology, such as mRNA decay and editing and maturation of miRNA precursors [ 39 ]. On the other hand, the YBX3 has been implicated in regulation of mRNA translation as well as stability, likely in a transcript-dependent manner [ 40 ]. As a positive control for our enrichment score approach, we noted DDX3X enrichment around 5’UTR CAGE peaks. This is consistent with known roles for DDX3X in transcription and pre-mRNA splicing through interactions with transcription factors and Spliceosomal B Complexes [ 41 ]. Interestingly, the crosslinking of UPF1 is enriched within 20 nt upstream of the 3’UTR CAGE peaks, followed by a steep depletion within ~ 10 bps downstream (Fig. 2 d). Additionally, a substantial correlation (R = 0,654) was observed between the 3’UTR CAGE signal and UPF1 binding, but not associated with gene expression or 3’UTR length (Fig. S2 q). More specifically, the degree of UPF1 binding coincides with the intensity of the 3’UTR CAGE peaks and proximity to the peaks (Fig. S2 r, s). However, transfecting K562 cells with UPF1-targeting small interfering RNAs (siRNAs) for 48 hours did not lead to changes in the enrichment of RT-qPCR signal obtained with primers targeting downstream of the 3’UTR CAGE peak in CDKN1B or JPT2 when compared to upstream-targeting primers (Fig. S2 t). Thus, it remains unclear if the precise binding position of UPF1 relative to the re-capping position may be important for the generation of the 3’UTR capped fragments, or if accumulation of UPF1 is an indirect result of the presence of other factors that contribute to the cleavage. mRNA cleavage by small interfering RNAs generates newly capped RNA fragments mRNAs can be cleaved post-transcriptionally through RNA interference (RNAi). Indeed, a common way to artificially accomplish gene silencing is to utilise siRNAs to induce endonucleolytic degradation of the target transcripts [ 42 , 43 ]. SiRNAs are usually 21–23 nt long and their sequence is antisense to their mRNA target sequence. Silencing by siRNAs is induced through the endonuclease activity of Argonaute 2 (AGO2), a subunit of the RNA-induced gene-silencing complex (RISC) in the cytoplasm [ 44 ]. We hypothesised that siRNA silencing through AGO2 cleavage could lead to cytoplasmic capping of the cleaved RNA fragments instead of degradation. To test this hypothesis, we first investigated if CAGE-seq could detect cleaved RNA fragments guided by siRNA. We analysed CAGE data from siRNA-treated samples from the FANTOM5 dataset [ 45 ], which included samples from the TC-YIK human cell line transfected with siRNAs targeting mRNAs of 28 different transcription factors (20 siRNAs designed by ThermoFisher and 8 by the study authors) and 5 non-targeting control samples, in triplicates. We detected CAGE signal at the exact position targeted by the siRNA in at least two replicates in 20 out of the 28 samples (Fig. 3 a). The strongest enrichment in CAGE signal relative to the siRNA target site was detected in the Islet-1 knockdown ( ISL1 -KD) samples, with no signal detected in control samples (Fig. 3 b,c, S3 a). More interestingly, the dominant CAGE 5' end signal was present in the middle of the siRNA target sequence (Fig. 3 e, S3 a), where the AGO2 cleavage is known to take place [ 46 , 47 ]. As expected, the TSS CAGE signal in the 5'UTR of the corresponding protein-coding gene dropped by ~ 75% compared to the control samples in all 3 replicates (Fig. 3 b,c), confirming that the silencing of the ISL1 transcript was efficient. Together these results indicate that siRNA-mediated recruitment of AGO2 can lead to the generation of post-transcriptionally capped RNA fragments following mRNA cleavage. 3'UTR CAGE peaks coincide with AGO2 and UPF1 binding sites alongside G-rich motifs Since the endonuclease activity of AGO2 facilitates mRNA cleavage guided by siRNAs, we investigated whether AGO2 binding also occurred at the endogenous 3'UTR CAGE peaks. There was no publicly available AGO2 binding data for either HeLa or K562 cells so we produced ‘enhanced individual nucleotide resolution’-CLIP (eiCLIP) [ 48 ] data for AGO2 (AGO2-eiCLIP) in HeLa cells. Our analysis revealed that 32.8% of the crosslinking positions mapped to the 3’UTR region (Fig. S3 b), with a higher binding enrichment in known microRNA (miRNA)-regulated transcripts, and with a clear miRNA-seed matching-sequence enrichment downstream of the crosslinking site (Fig. S3 c,d). Similarly to UPF1, AGO2 crosslinks were enriched immediately upstream from the 3'UTR CAGE peaks but, unlike UPF1, they were not depleted in the downstream region (Fig. 3 d, S3 e, 3 d). In animals, endogenous RNAi is mainly mediated by microRNAs (miRNAs). MiRNAs are ~ 21–23 nucleotide (nt) long RNAs that, in contrast to siRNAs, recruit the miRNA induced silencing complex (miRISC) containing AGO1-4 to mRNAs with partial sequence complementarity. As a result, miRNA action induces translational repression and/or exonucleolytic cleavage of the target mRNAs [ 42 , 43 ]. Thus, miRNA-mediated degradation of target mRNAs in animals usually involves deadenylation, decapping, and degradation by the major cytoplasmic 5’to-3’ exonucleases, rather than direct endonucleolytic cleavage by AGO2 [ 5 , 49 ]. Nevertheless, it has been demonstrated that extensive miRNA-mRNA pairing can also trigger AGO2 catalytic activity [ 50 – 52 ]. We thus hypothesised that AGO2 miRNA-guided cleavage of mRNA targets might lead to the generation of recapping fragments in a similar manner to that observed for siRNAs. To test this we first identified genomic sequences with extensive complementarity (fewer than 2 mismatches) to human miRNAs. We identified 29 such targets that mapped within 3’UTRs but there was no CAGE signal present around any of them (data not shown). In line with this, AGO2 crosslinking enrichment around 3’UTR CAGE signals was considerably weaker for AGO2 binding sites overlapping with predicted miRNA binding sites (see Methods, Fig. S3 f). Intriguingly, CRISPR/Cas9-mediated elimination of AGO2 in K562 cells did not change the enrichment in RT-qPCR signal detected for JPT2 and CDKN1B with primers downstream the 3’CAGE versus upstream primers (Fig S3 g-i). All together, our observations suggest that AGO2 binds immediately upstream of the site of cleavage that generates 3’UTR-derived RNAs independently of miRNA directed recruitment and that endogenous 3’UTR-derived RNAs are not produced as a result of AGO2 cleavage activity. Accordingly, we instead explored the binding specificity of AGO2-eiCLIP data, and performed a motif analysis using HOMER motif finder. When analysing the 15 bp flanking region around AGO2-crosslinking peaks (see Methods), one of the most prominent motifs was highly enriched in Gs (Fig. S3 j − 2nd and 3rd). Notably, this also agrees with one of the first AGO2-CLIP studies performed on mouse embryonic stem cells, where the authors showed that, without the miRNA present, AGO2 binds preferentially to G-rich motifs [ 53 ]. As we had previously demonstrated that G-rich motifs, which have the capability to form RNA-G-quadruplexes, are enriched around 3’UTR-derived RNAs, we next investigated whether AGO2 and UPF1 could be attracted to these specific G-rich motif structures independently of their location to CAGE peaks. We first aligned AGO2-eiCLIP and UPF1-eCLIP cross-linking positions relative to the 3' end of rG4-seq sites in different regions of primary transcripts. Both AGO2 and UPF1 crosslink-binding sites are much more highly enriched at rG4-seq sites in the 3’UTRs relative to 5’UTRs, introns and coding sequence although we noted that the binding of UPF1 occurred at the 3’end of the G4-seq sites and AGO2 bound immediately upstream (Fig. S3 k-n). To further explore the relationship between AGO2 and UPF1 binding concerning 3’UTR CAGE peaks and their association with G4-seq signals, we categorised the 3’UTR CAGE peaks into four classes, depending on the presence or absence of these elements. We observed that the majority of 3’UTR CAGE peaks contained both AGO2 and UPF1 binding but not G4-seq signal although, on the other hand, the majority of 3’UTR CAGE sites overlapping with G4-seq also contained AGO2/UPF1 sites (Fig. S3 o). Then we further explored the binding position of UPF1 and AGO2 relative to the 3'UTR CAGE peaks, in the presence or absence of the G4-seq site. Interestingly, both proteins exhibited a distinct shift in position influenced by the G4 motif enrichment; whilst AGO2 showed a pronounced shift to the upstream region of the 3’UTR CAGE peak in the presence of G4-seq sites, UPF1 displayed a downstream shift (Fig. S3 p-q). An important next direction for future studies will be to experimentally investigate the mechanistic implications of the overlap between sites with the ability to form RNA-G4 structures and AGO2 and UPF1 binding for the generation of the capped 3’UTR-derived RNAs. Capped 3’UTR fragments of CDKN1B and JPT2 transcripts do not co-localise with the parental mRNAs Finally, we examined the potential implications of 3’UTR-derived RNAs. Specifically, we sought to understand how 3’UTR-derived RNAs might localise either together or independently from the parental mRNAs. To test this, we designed smFISH (single molecule fluorescence in situ hybridization) probes to simultaneously image the RNA upstream and downstream of the proposed post-transcriptional cleavage and capping site in CDKN1B and JPT2 using hybridisation chain reaction RNA-fluorescence in situ hybridization (HCR-FISH 3.0) [ 54 ]. To account for technical biases in detection, we also designed probes against the coding sequence (hereafter upstream) and 3’UTR (hereafter downstream) of a control mRNA, PGAM1, which does not contain CAGE peaks in the 3’UTR and contained a similar 3’UTR length to our targets. We performed HCR-FISH in HeLa cells to determine whether putative 3’UTR-derived RNAs can be found independently of the RNA upstream of the cleavage site (Fig. 4 a, b). In the control transcript, PGAM1, we observed that 17.3% of upstream signals did not have a colocalising downstream signal and 21.3% of downstream signals did not have a colocalising upstream signal (Fig. 4 c, S4 a). However, the mRNAs that contain a 3’UTR CAGE signature were significantly more likely to show independent signals from the RNA downstream of the proposed cleavage site (CDKN1B: 53.3%, p adj. < 0.05; JPT2: 52.3%, p adj. < 0.05; Fig. 4 c). In the case of JPT2, we also observed significantly more independent signals from the upstream probes (29.3%, p adj. < 0.05; Fig. 4 c). These observations are consistent with the existence of cleaved 3’UTR fragments in the cell, and they reveal that these products may localise differently from their host transcripts. Discussion Previous studies had identified 3’UTR-derived RNAs via enrichment of RNA-seq reads-starts or CAGE signals mapping at 3’UTRs [ 7 , 16 , 18 ]. Nevertheless, most 3’UTR-derived RNAs may have remained undetected until now due to technical limitations inherent to these approaches, including reliance on fragmented-based sequencing methods and potentially biassed library preparations. Here, we provide multiple lines of evidence that complement CAGE and RNA-seq data, including RNA structural features, RBP interactions around 3’UTR CAGE signals and long-read nanopore CAGE to validate the widespread presence of capped 3’UTR-derived RNAs in human cells. We show that capped 3’UTR-derived RNAs are generated post-transcriptionally at positions characterised by the presence of G-rich motifs and specific RBP binding sites. We also demonstrate that, consistent with a functional role, capped 3’UTR-derived RNA sequences are evolutionary conserved and can localise to different subcellular regions than the parental mRNAs. The role of AGO2, UPF1 and G-rich motifs in the generation of 3'UTR-derived capped RNAs One of the key findings of our work is that siRNA action can result in the generation of capped RNAs downstream of the cleavage site (Fig. 3 a,c, S3 a). However, with the available data we could not quantify the efficiency of such capping, or identify all the factors that might be involved in the process. It is well established that AGO2 cleaves the double stranded RNA formed by the reverse complementary binding of siRNAs to their target mRNAs in the cytosol, pointing to a model in which AGO2 cleavage products can be recapped. The strong enrichment of AGO2 to a region with a modest increase in sequence conservation (Fig. S2 d) immediately upstream of the endogenous 3’UTR CAGE peaks (Fig. 3 d) suggested that AGO2 also plays a role in the generation of endogenous capped 3’UTR-derived RNAs. Endogenous RNA interference in mammalian cells is mainly mediated by miRNAs. MiRNAs drive AGO2 to their targets through partial complementarity only and thus, in contrast to siRNAs, do not trigger AGO2 catalytic activity [ 55 ]. On the contrary, miRNA action in mammals relies mostly on translational repression and/or exonucleolytic degradation of their targets through the recruitment of other protein partners [ 55 ]. This raises two interesting possibilities: (1) that the mechanism by which AGO2 is involved in the generation of endogenous 3’UTR-derived capped RNAs is different to its role in the generation of capped fragments following siRNA action. In this scenario, AGO2 role will likely be independent of its catalytic activity and possibly require the recruitment of other nucleases, or (2) that AGO2 endonucleolytic activity is also important for the generation of endogenous 3’UTR-derived capped RNAs and therefore likely independent of its role in miRNA-mediated silencing of gene expression. The latter model is supported by the finding of a stronger enrichment in AGO2 binding in 3’UTR CAGE peaks in the absence of miRNA binding sites (Fig. S3 f). We also failed to observe CAGE peaks in the vicinity of 29 mRNA targets whose genomics sequences contained miRNA target sites of extensive (< 2 mismatches) complementarity to known miRNAs. Interestingly, we found that AGO2 binds to potential RNA-G4s in 3’UTR CAGE sites (Fig. S3 h-i). Early AGO2-CLIP experiments had already identified an enrichment of a G-rich motif in sequences cross-linked to AGO2 likely in a miRNA-independent manner [ 53 ]. AGO2 binding sites neighbouring G-rich sequences may be less likely to be guided by miRNAs, as RNA-G4s can prevent miRNA binding from their target sites [ 56 ]. Thus, our analysis suggests that the role of AGO2 in the generation of capped 3’UTR-derived RNAs is independent of its role in miRNA-mediated gene silencing. This is in agreement with previous findings by Andreassi et al. [ 57 ]. Moreover, elimination of AGO2 did not affect the enrichment of JPT2 and CDKN1B RT-qPCR signals corresponding to 3’UTR-derived RNAs (S3i) further arguing against a direct role of AGO2 catalytic activity in the generation of these species. In the future, long-read CAGE analysis in models of AGO2 loss of function, possibly in conjunction with the elimination of other AGO proteins (1, 3–4) present in the cells, may help clarify the specific role of AGO2 in the global generation of capped 3’UTR-derived RNAs. Our work identified UPF1 as the RBP with the strongest binding enrichment around 3’UTR CAGE peaks and uncovered an overlapping of AGO2, UPF1 and G-rich sequences in 3’UTR CAGE sites. Interestingly, a significant overlap between UPF1 and AGO2 binding sites as well as preferential UPF1 binding to structured G-rich regions had been previously reported [ 58 ]. Whilst it is well-established that UPF1 plays an essential role in mRNA degradation [ 36 ] and binds to GC-rich motifs in 3’UTRs [ 38 ], the main trigger of UPF1-mediated mRNA decay remains unknown. It has been suggested that G-enrichment in 3’UTRs plays a vital role in triggering UPF1-mediated mRNA decay [ 38 ]. It was therefore tempting to hypothesise a causal role for UPF1 in the generation of 3’UTR-derived RNAs in connection with its role in mRNA decay [ 18 ]. Nevertheless, arguing against this possibility, siRNA-mediated downregulation of UPF1 did not change the relative amount of CDKN1B and JPT2 mRNA detected with primers targeting downstream versus upstream of the 3’CAGE peaks (Fig. S2 t). Additional experimental data will be needed to reach a more definitive conclusion, but it is is also likely that the presence of RNA-G4 sequences (or strong secondary structures) around 3’UTR CAGE causes the stalling of UPF1 as the helicase translocates in a 5’-3’ direction [ 59 ]. Our analysis also shows that the G-rich sequences around 3’UTR CAGE peaks have a strong pairing probability and thus have the potential to form G4 structures (Fig. 2 b, S2 g-l). Nevertheless, although RNA-G4s are known to form stable structures in vitro , recent studies have suggested that they may be less stable in vivo due to active unwinding by RNA helicases [ 60 , 61 ]. However, Kharel et al. (2022) [ 62 ] demonstrated that 3’UTR-G4s are dynamically regulated under cellular stress conditions and may play a role in mRNA stability for several transcripts, including the 3’UTR-G4 in the amyloid precursor protein ( APP ) mRNA. The G4 motif in the 3’UTR of APP mRNA was found to suppress overproduction of APP protein, but the underlying mechanism remained unclear [ 63 ]. Analysis of rG4-seq and CAGE data from HeLa cells showed that the 3’ end of this G4 motif in APP 3’UTR precisely coincided with a 3’UTR CAGE signal (Fig. S1 n - APP, Fig. 2 l). Moreover, long-read sequencing CAGE from cortical neuron samples, confirmed that abundant 3’UTR-derived capped RNAs are present in these samples that span from the identified 3’UTR CAGE peak to the end of the annotated APP gene (Fig. S1 n - APP). This raises the possibility that the RNA-G4 regulates APP protein through an unknown mechanism that involves the generation of 3’UTR-derived capped RNAs. Future studies will focus on investigating whether these G-rich sequences form stable G4 structures in other genes and whether they directly contribute to the formation of 3’UTR-derived RNAs. Another important open question that warrants further investigation is whether these G-rich motifs are essential for the recruitment of AGO2 and/or other proteins responsible for the generation of endogenous 3’UTR-derived RNAs. Independent localisation of capped 3’UTR fragments from the parental mRNAs . CAGE-seq, RNA-seq, RT-qPCR and long-read CAGE experiments suggested that 3'UTR-derived RNAs in CDKN1B and JPT2 are capped and highly expressed in cells. In line with these experiments, HCR-FISH showed that RNAs derived from CDKN1B and JPT2 3’UTRs can be detected at separate cytosolic locations than their parental mRNAs. In agreement with the CAGE data, higher ratio of downstream vs. upstream probes is present in CDKN1B (Fig. 4 a-c, S1 n - CDKN1B). Interestingly, some cells exhibited a pronounced perinuclear accumulation of 3’UTR-probes in CDKN1B (Fig. 4 a), whereas for the majority of the cells, the signal was dispersed throughout the cytosol. An intriguing possibility is a potential cell cycle-dependence, as observed in other aspects of CDKN1B gene expression regulation, such as mRNA translation [ 64 , 65 ]. It has been previously shown that defective CDKN1 splicing can be rectified to restore CDKN1B/p27 kip protein production and induce cell cycle arrest [ 66 , 67 ]. Likewise, the capped 3’UTR fragments of CDKN1B mRNA could regulate p27 kip protein in a cell cycle-specific manner, albeit this possibility remains to be investigated. Of note, a separate study proposed a cell-cycle function for 3’UTR fragments of NURR1 (nuclear receptor related 1 protein) mRNA which were highly expressed in proliferating neuronal cells [ 17 ]. Exploring the dynamic nature of these capped 3’UTR fragments and their potential influence on cellular functions in a manner dependent on the cell cycle remains an important area for further investigation. The different localisation of the 3’UTR-derived fragments to their full-length counterparts raises more questions on the fate and function of these RNAs. It is worth mentioning that analysis of ribosome footprinting data [ 29 ] (not-shown) failed to reveal any substantial ribosomal binding to capped 3’UTR-derived RNAs. This argues against their translation and supports a role similar to other cytosolic lncRNAs [ 68 ], as previously observed by others for specific 3’UTR-derived RNAs [ 17 , 18 , 69 ]. Nevertheless, the binding of the translation initiation factor eIF4E to these RNAs seems paradoxical. Moreover, these findings are in sharp contrast with those by Sudmant et al. who found evidence for ribosomal binding and for the existence of peptides encoded by comparable isolated 3’UTR fragments in human brain samples[ 17 , 18 , 69 ]. It is important to acknowledge that the coverage of ribo-footprinting in 3’UTRs is limited and it therefore can’t fully rule out that some of the capped, eIF4E-bound, 3’UTR-derived RNAs identified in our study are translated. This will require further investigation, possibly in a gene- and tissue-dependent manner. Methodological implications Different abundance and localisation of 3’UTR derived RNAs relative to their parental transcripts and the 5’ cleavage fragment containing protein coding sequence suggests that 3’UTR fragmented-based sequencing methods might be measuring the wrong RNA species in a significant proportion of cases. Even in the case of RNA-seq, quantitating the signal across the entire length of the uncleaved mRNA might measure a combination of protein-coding and non-coding RNA species. To increase the accuracy of quantitation of protein coding transcript levels, as well as those of 3’UTR-derived RNAs themselves, it may be necessary to develop new computational quantitation methods informed by the results of this paper, which will try to estimate the levels of protein-coding and 3’UTR fragments separately. Moreover, many new drugs which are based on siRNA targeting are already in use or under active clinical trials for treating a variety of conditions including neurological diseases [ 70 ]. Side cleavage products of the targeted mRNAs from these therapeutic drugs could be subjected to a cytoplasmic capping mechanism and result in unwanted toxic side effects. Limitations At the moment we do not have the ability to identify the full-length size of 3'UTR-derived RNAs in a high-throughput manner since the main technique that we used (CAGE-seq) is based on 5’ end sequencing. Also, CAGE-seq method has a limitation on fragment size similar to other HT-sequencing methods with a minimum fragment size of 200 bps. This can be overcome with the long-read CAGE (Fig. S1 n), but the whole data is not yet publicly available. Using only experimental datasets has limitations in coverage, organisms, cell lines and can increase the number of false positives as a result of background noise. It is for example important to note that we have limited our study to RBPs with eCLIP available, which may have prevented the identification of other important proteins involved in the cleavage and/or re-capping of 3’UTR mRNA fragments. This study is limited to human samples and, even though the sequence conservation suggests that capped 3'UTR-derived fragments may be conserved, this will need further experimental validation. New computational methods will need to be developed for these studies which are currently limited by the availability of such large datasets. Conclusions 3'UTR-derived RNAs are emerging as novel regulatory molecules, with potential implications in broad cellular processes such as cell cycle or neuronal homeostasis [ 17 , 18 , 69 ]. However, the molecular mechanisms involved in the generation of these RNA species had been largely unknown. Our study sheds new light into these mechanisms by revealing that capped 3'UTR-derived RNAs originate from sequences rich in G motifs that contain both UPF1 and AGO2 binding sites. These findings suggest a significant role for these elements in the regulatory mechanism. Overall, our findings provide the framework for further investigations where their functions will surely emerge. Declarations Acknowledgments This work was funded in part by The Wellcome Trust grants (106954/Z/15/Z) awarded to B.L., by the Medical Research Council (MRC) (MR/P023223/1 and MR/X009912/1) to A.M-S, MRC (grant number MC_UP_1102/18) to S.V, and by (215593/Z/19/Z) to J.U., Medical Research Council (MRC) Core Funding (MC-A652-5QA10), by the Imperial College Research Fellowship awarded to N.H., and by the Francis Crick Institute which receives its core funding from Cancer Research UK (CC0102), the UK Medical Research Council (CC0102), and the Wellcome Trust (CC0102), and by an institutional budget from RIKEN, MEXT (Ministry of Education, Culture, Sports, Science and Technology) and from institutional budget from the Human Technopole. We thank the Crick Advanced Light Microscopy facility, especially Donald Bell, for their support. We thank Sarvesh Nikumbh for help with the CAGEr tool and other members of Lenhard's group for helpful discussions and comments on the manuscript. We thank Ira Iosub for processing the ribosome footprinting data. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Author contributions N.H. and B.L. conceived the study. N.H. designed the experiments, analysed the data, and led the project. R.C. and A.M-S. performed and designed qPCR experiments. AGO2-eiCLIP was designed and performed by C.R.S and A.M-S. R.F. and H.D. designed and performed smFISH probe imaging supervised by J.U. Long-read CAGE examples were produced, processed and provided by C.P., K.Y., T.K., C.W.Y., M.K., H.T., P.C., and visualised by A.M.C. N.H. and A.M-S. wrote the manuscript, with contributions from A.M.C., R.F., H.D., A.M.J, S.V., C.R.S., J.U. and B.L. Declaration of interests The authors declare no competing interests. References Ramanathan, A., Robb, G.B., and Chan, S.-H. (2016). mRNA capping: biological functions and applications. Nucleic Acids Res. 44 , 7511–7526. Otsuka, Y., Kedersha, N.L., and Schoenberg, D.R. (2009). Identification of a cytoplasmic complex that adds a cap onto 5’-monophosphate RNA. Mol. Cell. Biol. 29 , 2155–2167. Mukherjee, C., Bakthavachalu, B., and Schoenberg, D.R. (2014). The cytoplasmic capping complex assembles on adapter protein nck1 bound to the proline-rich C-terminus of Mammalian capping enzyme. PLoS Biol. 12 , e1001933. Hestand, M.S., Klingenhoff, A., Scherf, M., Ariyurek, Y., Ramos, Y., van Workum, W., Suzuki, M., Werner, T., van Ommen, G.-J.B., den Dunnen, J.T., et al. (2010). Tissue-specific transcript annotation and expression profiling with complementary next-generation sequencing technologies. Nucleic Acids Res. 38 , e165. Naeli, P., Winter, T., Hackett, A.P., Alboushi, L., and Jafarnejad, S.M. (2023). The intricate balance between microRNA-induced mRNA decay and translational repression. FEBS J. 290 , 2508–2524. Murata, M., Nishiyori-Sueki, H., Kojima-Ishiyama, M., Carninci, P., Hayashizaki, Y., and Itoh, M. (2014). Detecting expressed genes using CAGE. Methods Mol. Biol. 1164 , 67–85. Kocabas, A., Duarte, T., Kumar, S., and Hynes, M.A. (2015). Widespread differential expression of coding region and 3’ UTR sequences in neurons and other tissues. Neuron 88 , 1149–1156. Malka, Y., Steiman-Shimony, A., Rosenthal, E., Argaman, L., Cohen-Daniel, L., Arbib, E., Margalit, H., Kaplan, T., and Berger, M. (2017). Post-transcriptional 3´-UTR cleavage of mRNA transcripts generates thousands of stable uncapped autonomous RNA fragments. Nat. Commun. 8 , 2029. Mercer, T.R., Dinger, M.E., Bracken, C.P., Kolle, G., Szubert, J.M., Korbie, D.J., Askarian-Amiri, M.E., Gardiner, B.B., Goodall, G.J., Grimmond, S.M., et al. (2010). Regulated post-transcriptional RNA cleavage diversifies the eukaryotic transcriptome. Genome Res. 20 , 1639–1650. Affymetrix ENCODE Transcriptome Project, and Cold Spring Harbor Laboratory ENCODE Transcriptome Project (2009). Post-transcriptional processing generates a diversity of 5’-modified long and short RNAs. Nature 457 , 1028–1032. Adiconis, X., Haber, A.L., Simmons, S.K., Levy Moonshine, A., Ji, Z., Busby, M.A., Shi, X., Jacques, J., Lancaster, M.A., Pan, J.Q., et al. (2018). Comprehensive comparative analysis of 5’-end RNA-sequencing methods. Nat. Methods 15 , 505–511. Carninci, P., Kasukawa, T., Katayama, S., Gough, J., Frith, M.C., Maeda, N., Oyama, R., Ravasi, T., Lenhard, B., Wells, C., et al. (2005). The transcriptional landscape of the mammalian genome. Science 309 , 1559–1563. Carninci, P., Sandelin, A., Lenhard, B., Katayama, S., Shimokawa, K., Ponjavic, J., Semple, C.A.M., Taylor, M.S., Engström, P.G., Frith, M.C., et al. (2006). Genome-wide analysis of mammalian promoter architecture and evolution. Nat. Genet. 38 , 626–635. Kiss, D.L., Oman, K., Bundschuh, R., and Schoenberg, D.R. (2015). Uncapped 5’ ends of mRNAs targeted by cytoplasmic capping map to the vicinity of downstream CAGE tags. FEBS Lett. 589 , 279–284. Berger, M.R., Alvarado, R., and Kiss, D.L. (2019). mRNA 5’ ends targeted by cytoplasmic recapping cluster at CAGE tags and select transcripts are alternatively spliced. FEBS Lett. 593 , 670–679. Mercer, T.R., Wilhelm, D., Dinger, M.E., Soldà, G., Korbie, D.J., Glazov, E.A., Truong, V., Schwenke, M., Simons, C., Matthaei, K.I., et al. (2011). Expression of distinct RNAs from 3’ untranslated regions. Nucleic Acids Res. 39 , 2393–2403. Ji, S., Yang, Z., Gozali, L., Kenney, T., Kocabas, A., Jinsook Park, C., and Hynes, M. (2021). Distinct expression of select and transcriptome-wide isolated 3’UTRs suggests critical roles in development and transition states. PLoS ONE 16 , e0250669. Sudmant, P.H., Lee, H., Dominguez, D., Heiman, M., and Burge, C.B. (2018). Widespread Accumulation of Ribosome-Associated Isolated 3’ UTRs in Neuronal Cell Populations of the Aging Brain. Cell Rep. 25 , 2447–2456.e4. Takahashi, H., Lassmann, T., Murata, M., and Carninci, P. (2012). 5’ end-centered expression profiling using cap-analysis gene expression and next-generation sequencing. Nat. Protoc. 7 , 542–561. Djebali, S., Davis, C.A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., Tanzer, A., Lagarde, J., Lin, W., Schlesinger, F., et al. (2012). Landscape of transcription in human cells. Nature 489 , 101–108. Kanamori-Katayama, M., Itoh, M., Kawaji, H., Lassmann, T., Katayama, S., Kojima, M., Bertin, N., Kaiho, A., Ninomiya, N., Daub, C.O., et al. (2011). Unamplified cap analysis of gene expression on a single-molecule sequencer. Genome Res. 21 , 1150–1159. Frith, M.C., Valen, E., Krogh, A., Hayashizaki, Y., Carninci, P., and Sandelin, A. (2008). A code for transcription initiation in mammalian genomes. Genome Res. 18 , 1–12. Giacometti, S., Benbahouche, N.E.H., Domanski, M., Robert, M.-C., Meola, N., Lubas, M., Bukenborg, J., Andersen, J.S., Schulze, W.M., Verheggen, C., et al. (2017). Mutually Exclusive CBC-Containing Complexes Contribute to RNA Fate. Cell Rep. 18 , 2635–2650. Izaurralde, E., Lewis, J., McGuigan, C., Jankowska, M., Darzynkiewicz, E., and Mattaj, I.W. (1994). A nuclear cap binding protein complex involved in pre-mRNA splicing. Cell 78 , 657–668. Schoenberg, D.R., and Maquat, L.E. (2009). Re-capping the message. Trends Biochem. Sci. 34 , 435–442. Core, L.J., Martins, A.L., Danko, C.G., Waters, C.T., Siepel, A., and Lis, J.T. (2014). Analysis of nascent RNA identifies a unified architecture of initiation regions at mammalian promoters and enhancers. Nat. Genet. 46 , 1311–1320. Jensen, K.B., Dredge, B.K., Toubia, J., Jin, X., Iadevaia, V., Goodall, G.J., and Proud, C.G. (2021). capCLIP: a new tool to probe translational control in human cells through capture and identification of the eIF4E-mRNA interactome. Nucleic Acids Res. 49 , e105. Rhoads, R.E. (2009). eIF4E: new family members, new binding partners, new roles. J. Biol. Chem. 284 , 16711–16715. Ferguson, L., Upton, H.E., Pimentel, S.C., Mok, A., Lareau, L.F., Collins, K., and Ingolia, N.T. (2023). Streamlined and sensitive mono- and di-ribosome profiling in yeast and human cells. Nat. Methods 20 , 1704–1715. Zhang, L., Kasif, S., Cantor, C.R., and Broude, N.E. (2004). GC/AT-content spikes as genomic punctuation marks. Proc Natl Acad Sci USA 101 , 16855–16860. Kharel, P., Becker, G., Tsvetkov, V., and Ivanov, P. (2020). Properties and biological impact of RNA G-quadruplexes: from order to turmoil and back. Nucleic Acids Res. 48 , 12534–12555. Lee, D.S.M., Ghanem, L.R., and Barash, Y. (2020). Integrative analysis reveals RNA G-quadruplexes in UTRs are selectively constrained and enriched for functional associations. Nat. Commun. 11 , 527. Kwok, C.K., Marsico, G., Sahakyan, A.B., Chambers, V.S., and Balasubramanian, S. (2016). rG4-seq reveals widespread formation of G-quadruplex structures in the human transcriptome. Nat. Methods 13 , 841–844. Bedrat, A., Lacroix, L., and Mergny, J.-L. (2016). Re-evaluation of G-quadruplex propensity with G4Hunter. Nucleic Acids Res. 44 , 1746–1759. Van Nostrand, E.L., Freese, P., Pratt, G.A., Wang, X., Wei, X., Xiao, R., Blue, S.M., Chen, J.-Y., Cody, N.A.L., Dominguez, D., et al. (2020). A large-scale binding and functional map of human RNA-binding proteins. Nature 583 , 711–719. Staszewski, J., Lazarewicz, N., Konczak, J., Migdal, I., and Maciaszczyk-Dziubinska, E. (2023). UPF1-From mRNA Degradation to Human Disorders. Cells 12 . Kurosaki, T., Li, W., Hoque, M., Popp, M.W.-L., Ermolenko, D.N., Tian, B., and Maquat, L.E. (2014). A post-translational regulatory switch on UPF1 controls targeted mRNA degradation. Genes Dev. 28 , 1900–1916. Imamachi, N., Salam, K.A., Suzuki, Y., and Akimitsu, N. (2017). A GC-rich sequence feature in the 3’ UTR directs UPF1-dependent mRNA decay in mammalian cells. Genome Res. 27 , 407–418. Gherzi, R., Chen, C.-Y., Ramos, A., and Briata, P. (2014). KSRP controls pleiotropic cellular functions. Semin. Cell Dev. Biol. 34 , 2–8. Cooke, A., Schwarzl, T., Huppertz, I., Kramer, G., Mantas, P., Alleaume, A.-M., Huber, W., Krijgsveld, J., and Hentze, M.W. (2019). The RNA-Binding Protein YBX3 Controls Amino Acid Levels by Regulating SLC mRNA Abundance. Cell Rep. 27 , 3097–3106.e5. Mo, J., Liang, H., Su, C., Li, P., Chen, J., and Zhang, B. (2021). DDX3X: structure, physiologic functions and cancer. Mol. Cancer 20 , 38. Carthew, R.W., and Sontheimer, E.J. (2009). Origins and Mechanisms of miRNAs and siRNAs. Cell 136 , 642–655. Bartel, D.P. (2018). Metazoan MicroRNAs. Cell 173 , 20–51. Lam, J.K.W., Chow, M.Y.T., Zhang, Y., and Leung, S.W.S. (2015). siRNA Versus miRNA as Therapeutics for Gene Silencing. Mol. Ther. Nucleic Acids 4 , e252. Lizio, M., Ishizu, Y., Itoh, M., Lassmann, T., Hasegawa, A., Kubosaki, A., Severin, J., Kawaji, H., Nakamura, Y., FANTOM consortium, et al. (2015). Mapping Mammalian Cell-type-specific Transcriptional Regulatory Networks Using KD-CAGE and ChIP-seq Data in the TC-YIK Cell Line. Front. Genet. 6 , 331. Elbashir, S.M., Lendeckel, W., and Tuschl, T. (2001). RNA interference is mediated by 21- and 22-nucleotide RNAs. Genes Dev. 15 , 188–200. Lin, J., Xu, K., Roth, J.A., and Ji, L. (2016). Detection of siRNA-mediated target mRNA cleavage activities in human cells by a novel stem-loop array RT-PCR analysis. Biochem. Biophys. Rep. 6 , 16–23. Paterson, H.A.B., Yu, S., Artigas, N., Prado, M.A., Haberman, N., Wang, Y.-F., Jobbins, A.M., Pahita, E., Mokochinski, J., Hall, Z., et al. (2022). Liver RBFOX2 regulates cholesterol homeostasis via Scarb1 alternative splicing in mice. Nat. Metab. 4 , 1812–1829. Nishihara, T., Zekri, L., Braun, J.E., and Izaurralde, E. (2013). miRISC recruits decapping factors to miRNA targets to enhance their degradation. Nucleic Acids Res. 41 , 8692–8705. Jung, E., Seong, Y., Jeon, B., Song, H., and Kwon, Y.-S. (2017). Global analysis of AGO2-bound RNAs reveals that miRNAs induce cleavage of target RNAs with limited complementarity. Biochim. Biophys. Acta Gene Regul. Mech. 1860 , 1148–1158. Bracken, C.P., Szubert, J.M., Mercer, T.R., Dinger, M.E., Thomson, D.W., Mattick, J.S., Michael, M.Z., and Goodall, G.J. (2011). Global analysis of the mammalian RNA degradome reveals widespread miRNA-dependent and miRNA-independent endonucleolytic cleavage. Nucleic Acids Res. 39 , 5658–5668. Karginov, F.V., Cheloufi, S., Chong, M.M.W., Stark, A., Smith, A.D., and Hannon, G.J. (2010). Diverse endonucleolytic cleavage sites in the mammalian transcriptome depend upon microRNAs, Drosha, and additional nucleases. Mol. Cell 38 , 781–788. Leung, A.K.L., Young, A.G., Bhutkar, A., Zheng, G.X., Bosson, A.D., Nielsen, C.B., and Sharp, P.A. (2011). Genome-wide identification of Ago2 binding sites from mouse embryonic stem cells with and without mature microRNAs. Nat. Struct. Mol. Biol. 18 , 237–244. Choi, H.M.T., Schwarzkopf, M., Fornace, M.E., Acharya, A., Artavanis, G., Stegmaier, J., Cunha, A., and Pierce, N.A. (2018). Third-generation in situ hybridization chain reaction: multiplexed, quantitative, sensitive, versatile, robust. Development 145 . Gebert, L.F.R., and MacRae, I.J. (2019). Regulation of microRNA function in animals. Nat. Rev. Mol. Cell Biol. 20 , 21–37. Rouleau, S., Glouzon, J.-P.S., Brumwell, A., Bisaillon, M., and Perreault, J.-P. (2017). 3’ UTR G-quadruplexes regulate miRNA binding. RNA 23 , 1172–1179. Andreassi, C., Luisier, R., Crerar, H., Darsinou, M., Blokzijl-Franke, S., Lenn, T., Luscombe, N.M., Cuda, G., Gaspari, M., Saiardi, A., et al. (2021). Cytoplasmic cleavage of IMPA1 3’ UTR is necessary for maintaining axon integrity. Cell Rep. 34 , 108778. Hurt, J.A., Robertson, A.D., and Burge, C.B. (2013). Global analyses of UPF1 binding and function reveal expanded scope of nonsense-mediated mRNA decay. Genome Res. 23 , 1636–1650. - Abstract - Europe PMC Available at: https://europepmc.org/article/pmc/pmc4506499 [Accessed December 11, 2023]. Caterino, M., and Paeschke, K. (2022). Action and function of helicases on RNA G-quadruplexes. Methods 204 , 110–125. Guo, J.U., and Bartel, D.P. (2016). RNA G-quadruplexes are globally unfolded in eukaryotic cells and depleted in bacteria. Science 353 . Kharel, P., Fay, M., Manasova, E.V., Anderson, P.J., Kurkin, A.V., Guo, J.U., and Ivanov, P. (2023). Stress promotes RNA G-quadruplex folding in human cells. Nat. Commun. 14 , 205. Crenshaw, E., Leung, B.P., Kwok, C.K., Sharoni, M., Olson, K., Sebastian, N.P., Ansaloni, S., Schweitzer-Stenner, R., Akins, M.R., Bevilacqua, P.C., et al. (2015). Amyloid precursor protein translation is regulated by a 3’UTR guanine quadruplex. PLoS ONE 10 , e0143160. Hengst, L., and Reed, S.I. (1996). Translational control of p27Kip1 accumulation during the cell cycle. Science 271 , 1861–1864. Cuesta, R., Martínez-Sánchez, A., and Gebauer, F. (2009). miR-181a regulates cap-dependent translation of p27(kip1) mRNA in myeloid cells. Mol. Cell. Biol. 29 , 2841–2851. Kaida, D., and Shida, K. (2022). Spliceostatin A stabilizes CDKN1B mRNA through the 3’ UTR. Biochem. Biophys. Res. Commun. 608 , 39–44. Satoh, T., and Kaida, D. (2016). Upregulation of p27 cyclin-dependent kinase inhibitor and a C-terminus truncated form of p27 contributes to G1 phase arrest. Sci. Rep. 6 , 27829. Noh, J.H., Kim, K.M., McClusky, W.G., Abdelmohsen, K., and Gorospe, M. (2018). Cytoplasmic functions of long noncoding RNAs. Wiley Interdiscip. Rev. RNA 9 , e1471. Ciolli Mattioli, C., Rom, A., Franke, V., Imami, K., Arrey, G., Terne, M., Woehler, A., Akalin, A., Ulitsky, I., and Chekulaeva, M. (2019). Alternative 3’ UTRs direct localization of functionally diverse protein isoforms in neuronal compartments. Nucleic Acids Res. 47 , 2560–2573. Dammes, N., and Peer, D. (2020). Paving the road for RNA therapeutics. Trends Pharmacol. Sci. 41 , 755–775. Chakrabarti, A.M., Haberman, N., Praznik, A., Luscombe, N.M., and Ule, J. (2018). Data Science Issues in Studying Protein–RNA Interactions with CLIP Technologies. Annu. Rev. Biomed. Data Sci. 1 , 235–261. Balwierz, P.J., Carninci, P., Daub, C.O., Kawai, J., Hayashizaki, Y., Van Belle, W., Beisel, C., and van Nimwegen, E. (2009). Methods for analyzing deep sequencing expression data: constructing the human and mouse promoterome with deepCAGE data. Genome Biol. 10 , R79. Pasquier, C., and Robichon, A. (2020). Computational prediction of miRNA/mRNA duplexomes at the whole human genome scale reveals functional subnetworks of interacting genes with embedded miRNA annealing motifs. Comput. Biol. Chem. 88 , 107366. Kuehn, E., Clausen, D.S., Null, R.W., Metzger, B.M., Willis, A.D., and Özpolat, B.D. (2022). Segment number threshold determines juvenile onset of germline cluster expansion in Platynereis dumerilii. J. Exp. Zool. B Mol. Dev. Evol. 338 , 225–240. Stringer, C., Wang, T., Michaelos, M., and Pachitariu, M. (2021). Cellpose: a generalist algorithm for cellular segmentation. Nat. Methods 18 , 100–106. Bahry, E., Breimann, L., Zouinkhi, M., Epstein, L., Kolyvanov, K., Mamrak, N., King, B., Long, X., Harrington, K.I.S., Lionnet, T., et al. (2022). RS-FISH: precise, interactive, fast, and scalable FISH spot detection. Nat. Methods 19 , 1563–1567. Lee, F.C.Y., Chakrabarti, A.M., Hänel, H., Monzón-Casanova, E., Hallegger, M., Militti, C., Capraro, F., Sadée, C., Toolan-Kerr, P., Wilkins, O., et al. (2021). An improved iCLIP protocol. BioRxiv. Sibley, C.R. (2018). Individual Nucleotide Resolution UV Cross-Linking and Immunoprecipitation (iCLIP) to Determine Protein-RNA Interactions. Methods Mol. Biol. 1649 , 427–454. Kurata, J.S., and Lin, R.-J. (2018). MicroRNA-focused CRISPR-Cas9 library screen reveals fitness-associated miRNAs. RNA 24 , 966–981. Haberman, N., Huppertz, I., Attig, J., König, J., Wang, Z., Hauer, C., Hentze, M.W., Kulozik, A.E., Le Hir, H., Curk, T., et al. (2017). Insights into the design and interpretation of iCLIP experiments. Genome Biol. 18 , 7. DeMario, S., Xu, K., He, K., and Chanfreau, G.F. (2023). Nanoblot: an R-package for visualization of RNA isoforms from long-read RNA-sequencing data. RNA 29 , 1099–1107. Additional Declarations No competing interests reported. Supplementary Files FigureS1c.pdf Fig. S1: Related to Fig. 1 (a) Pearson’s correlation of raw CAGE reads counts per TSS or consensus cluster across biological replicates and cell types. (b) Reverse cumulative distribution of CAGE reads after normalisation using CAGEr package [72](CTSS = CAGE Transcription start site). (c) Total number of CAGE reads in each sample. (d) Density of total 5’ CAGE read positions normalised by the length of the correspondent transcript region identified in CAGE-seq libraries of K562 and HeLa samples with two biological replicates each, provided by ENCODE. (e) Percentage of CAGE tags per transcript region using Random primers, Oligod-T primers, and combination of both primers (1:4 oligod(T):Random Primers) in CAGE-seq libraries of THP-1 cells generated by RIKEN. (f) - (i) Pearson’s correlation between CAGE-seq replicates (rep1, rep2) and different cell lines (HeLa, K562) samples in 3’UTRs (F), 5’UTRs (G), CDS (H) and introns (I). (j) Top: Plot of the normalised coverage of the 5’ ends of forward paired-end reads (yellow line) and 3’ ends of reverse paired-end reads (blue line) of RNA-seq relative to 3’UTR CAGE peaks in HeLa cells. Bottom: Schematic representation of paired-end read positioning. Forward and reversed paired-end reads are presented in yellow and blue, respectively. The black box represents the ends of reads that are plotted in the top graph. (k) RT-qPCR data of gene expression using primers designed to amplify sequences located downstream (3’C), upstream (5’C) and overlapping (AC) the 3’UTR CAGE sites of CDKN1B and JPT2. Data represents fold detection using downstream versus upstream/overlapping primers relative to the 3‘UTR CAGE peaks. Each dot represents an independent biological replicate. Primer target sequences relative to the 3’UTR CAGE peak are schematically represented on the top right-hand side and visualised for each gene using IGV genome browser on the bottom. (l) Top gene examples with strongest 3’UTR CAGE peaks present in K562 and HeLa cell lines using IGV-genome browser for visualisation. (m) Visualisation of RNA-seq reads relative to dominant 3’UTR CAGE peaks in CDKN1B and JPT2 gene using IGV-genome browser. (n) Visualisation of 10 gene examples with 3’UTR CAGE peaks (HeLa, K562), rG4-seq clusters (HeLa) and long-read CAGE (Cortical Neuron) reads using IGV-genome browser. FigureS2c.pdf Fig. S2: Related to Fig. 2 (a) RNA-map showing normalised density of CBP20-iCLIP (HeLa) crosslink sites relative to dominant 3’UTR and 5’UTR CAGE peaks. (b) Mean score of GRO-cap seq coverage [26]per CAGE peak for 5’UTR, CDS, intron and 3’UTR regions. The heatmap represents GRO-cap seq scores plotted with deeptools. (c) RNA-map showing normalised density of cap-CLIP (HeLa) crosslink sites relative to dominant 3’UTR and 5’UTR CAGE peaks. (d) Mean coverage of conservation score from UCSC phastCons30way track relative to inner 3’UTR CAGE peaks (≥150 bps downstream from CDS and ≥150 bps upstream from transcript termination) and randomised control positions around the same region of 150 nts window for each peak. (e) Normalised motif enrichment of canonical PolyA motifs relative to 3’UTR ends and to the dominant 3’UTR CAGE peaks. (f) Sequence logos around K562 cells’ CAGE peaks across different transcript regions (g) The 75 nt region centred on K562 cells’ CAGE peaks at different transcript regions was used to calculate pairing probability with the RNAfold program, and the average pairing probability of each nucleotide is shown for the 50 nt region around CAGE peaks. (h) GGG-motif enrichment relative to CAGE (HeLa) peaks. (i) GGG-motif enrichment relative to CAGE (K562) peaks. (j) Summarised score from G4-Hunter prediction tool in the region of 50 nts upstream and downstream relative to CAGE (HeLa) peaks. (k) Summarised score from G4-Hunter prediction tool in the region of 50 nts upstream and downstream relative to CAGE (K562) peaks. (l) Enrichment of RNA-G-quadruplex sequencing (rG4-seq) hits from HeLa cells relative to CAGE (HeLa) peaks. (m) Percentage of G-seq sites per transcript region. (n) Enrichment of eCLIP cross-linking clusters surrounding 5’UTR CAGE peaks from 80 different RBP samples (right panel) in K562 cells from ENCODE database using sum of log ratios. The red line represents the threshold of top 10 RBP targets (left panel). (o) Enrichment of eCLIP cross-linking clusters surrounding intronic CAGE peaks from 80 different RBP samples (right panel) in K562 cells from ENCODE database using sum of log ratios. The red line represents the threshold of top 10 RBP targets (left panel). (p) Enrichment of eCLIP cross-linking clusters surrounding CDS CAGE peaks from 80 different RBP samples (right panel) in K562 cells from ENCODE database using sum of log ratios. The red line represents the threshold of top 10 RBP targets (left panel). (q) Pearson’s correlation between the 3’UTR CAGE (K562) tags and RNA-seq (K562) read coverage per gene (top-left). Pearson’s correlation between the 3’UTR crosslink coverage of UPF1-eCLIP (K562) and 3’UTR CAGE (K562) tags (top-right). Pearson’s correlation between the 3’UTR length and 3’UTR crosslink coverage of UPF1-eCLIP (K562) (bottom-left). Pearson’s correlation between the 3’UTR length and 3’UTR CAGE (K562) tags (bottom-right). (r) UPF1-eCLIP (K562) crosslink enrichment relative to the distance from the 3’UTR CAGE (K562) peaks. (s) Heatmap of UPF1-eCLIP (K562) crosslink site enrichment showing the top 500 3’UTR AGO2 targets in 100 nts flanking region relative to 3’UTR CAGE (K562) peaks. The heatmap represents log2 of crosslink counts, normalised by the mean of all counts within 200 nts of the targeting site. (t) K562 cells were transfected with siRNAs targeting UPF1 or non-targeting controls (C). Left-hand side panel: UPF1 expression was measured with RT-qPCR. Data is normalised by the housekeeping gene RPLP0 and presented as fold change of the control. Right-hand side panel: RT-qPCR data of gene expression using primers designed to amplify sequences located downstream (3’C) and upstream (5’C) the 3’UTR CAGE sites of CDKN1B and JPT2. Data represents fold detection using downstream (3’C) versus upstream (5’C) primers. Each dot represents an independent biological replicate. Primer target sequences relative to the 3’UTR CAGE peaks are schematically represented on the right. FigureS3.pdf Fig. S3: Related to Fig. 3 (a) Visualisation of 5’ CAGE reads relative to dominant transcription start site (TSS) and relative to small interfering RNA of ISL1 target (in red) for CAGE-ISL1-KD and CAGE-control samples with 3 biological replicates using IGV-genome browser. (b) Percentage of AGO2-eiCLIP (HeLa) binding sites per transcript region. (c) Binding enrichment of AGO2-eiCLIP (HeLa) relative to miRNA-regulated transcripts and non-miRNA-regulated transcript in HeLa (data from [73] ). (d) Heatmap of miRNA-seed sequence enrichment in 30 nt flanking region showing the top 500 AGO2 binding sites relative to AGO-eiCLIP (HeLa) crosslink sites. Meta plot visualises the miRNA-seed sequence composition relative to the 5’ of the AGO2 binding site. (e) Heatmap of AGO2-eiCLIP (HeLa) crosslink site enrichment showing the top 500 3’UTR AGO2 targets in 100 nts flanking region relative to 3’UTR CAGE (HeLa) peaks. The heatmap represents log2 of crosslink counts, normalised by the mean of all counts within 200 nts of the targeting site. (f) RNA-map showing normalised density of AGO2 crosslink sites from AGO2 binding sites that contain (mir+) or are absent (mir-) from predicted miRNA binding sites relative to 3’UTR CAGE peaks. (g) AGO2 mRNA expression was measured with RT-qPCR in 3 clonal subpopulations generated by single cell sorting of K562 cells transfected with a plasmid expressing Cas9 and two gRNAs targeting AGO2 and preselected by genomic DNA sequencing. Both KO1 and KO2 contained edited AGO2 sequences and control (C) wild-type sequences. Data is normalised by the housekeeping gene RPLP0 and presented as a fold change of the control. Each dot represents an independent biological replicate. (h) AGO2 protein was detected by Western Blot in 6 clonal subpopulations generated as in (g). Clon 2 and 6 were selected for further experiments and re-named as KO1 and KO2. This experiment was performed once. (i) RT-qPCR data of gene expression using primers designed to amplify sequences located downstream (3’C) and upstream (5’C) the 3’UTR CAGE sites of CDKN1B and JPT2. Data represents fold detection using downstream (3’C) versus upstream (5’C) primers. Each dot represents an independent biological replicate. Primer target sequences relative to the 3’UTR CAGE peaks are schematically represented below. (j) Sequence logos and statistics of top 12 significantly enriched motifs of AGO2-eiCLIP (HeLa) binding sites using Homer for de novo motif discovery. (k) Enrichment of AGO2-eiCLIP (HeLa) cross-linking sites relative to the 3’end of the rG4-seq site (HeLa). (l) Heatmap for AGO2-eiCLIP (HeLa) crosslink site enrichment to show the top 500 3’UTR AGO2 targets in 100 nts flanking region relative to 3’end of rG4-seq (HeLa) site. The heatmap represents log2 of crosslink counts, normalised by the mean of all counts within 200 nts of the targeting site. (m) Enrichment of UPF1-eCLIP (K562) cross-linking sites relative to the 3’end of the rG4-seq site (HeLa). (n) Heatmap for UPF1-eCLIP (K562) crosslink site enrichment to show the top 500 3’UTR UPF1 targets in 100 nts flanking region relative to 3’end of rG4-seq (HeLa) site. The heatmap represents log2 of crosslink counts, normalised by the mean of all counts within 200 nts of the targeting site. (o) Upset plot of intersection of AGO2-eiCLIP (HeLa) and UPF1-eCLIP(K562) binding sites, G4-seq (HeLa) sites relative to 3’UTR CAGE peaks (K562 & HeLa). (p) RNA-map showing normalised density of AGO2 crosslink sites relative to 3’UTR CAGE peaks intersecting G4-seq site (G4+) or not (G4-) from Fig. S3l. (q) RNA-map showing normalised density of UPF1 crosslink sites relative to 3’UTR CAGE peaks intersecting G4-seq site (G4+) or not (G4-) from Fig. S3l. FigureS4.pdf Fig. S4: Related to Fig. 4 (a) Density plots showing the shortest distance per detected signal in pixels to a signal of the opposite colour. The dashed line shows the cutoff used to distinguish colocalising and non-colocalising signals. TableS1.tab.zip Tables Table S1: This table contains genomic locations of 32,065 unique 3’UTR CAGE clusters across all CAGE samples from HeLa and K562 cell lines. Each sample contains a normalised value of 5’ read positions for each cluster. Figure0Graphicalabstract.pdf SupplmentrayFile.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 17 Sep, 2024 Reviews received at journal 17 Sep, 2024 Reviewers agreed at journal 17 Sep, 2024 Reviewers invited by journal 17 Sep, 2024 Editor assigned by journal 30 Jul, 2024 Submission checks completed at journal 29 Jul, 2024 First submitted to journal 26 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-4809688\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":337065041,\"identity\":\"27f54b05-e0b6-4b61-b214-1b3438ab3837\",\"order_by\":0,\"name\":\"Nejc Haberman\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYFACHgZmCIP5wAEIg41oLWwJJGvhMWAgSos5A+/BzwUV96L5Z/d8PPCDwU6eQSItAa8Wywa+ZOkZZ4pzZ9w5u+FgD0OyYYNE2gG8WgwO8BhI87Yl5DbcyN1wGBgGCQwS6Q2EtBj/5v2XkDv/Rs4DoJZ6orSYSfM2JORuuJHDANRyGKiFkMMO85hZzziWkLvxRprBwR6D44ZtPM8S8Gs53mN8u6AmIXfejeTHH35UVMvzs6cZ4NUCixSYCURE5CgYBaNgFIwCwgAAk1lDw0Kl89kAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"Imperial College London\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Nejc\",\"middleName\":\"\",\"lastName\":\"Haberman\",\"suffix\":\"\"},{\"id\":337065045,\"identity\":\"6c4c0b07-31cf-4cfe-b096-bbad6aa24bcc\",\"order_by\":1,\"name\":\"Holly Digby\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Francis Crick Institute\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Holly\",\"middleName\":\"\",\"lastName\":\"Digby\",\"suffix\":\"\"},{\"id\":337065046,\"identity\":\"13ce4dba-691b-4cba-bfa5-d2c1bdfe556e\",\"order_by\":2,\"name\":\"Rupert Faraway\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Francis Crick Institute\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Rupert\",\"middleName\":\"\",\"lastName\":\"Faraway\",\"suffix\":\"\"},{\"id\":337065048,\"identity\":\"3c79e71b-a1f9-442c-8f12-7ebe218bff17\",\"order_by\":3,\"name\":\"Rebecca Cheung\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Imperial College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Rebecca\",\"middleName\":\"\",\"lastName\":\"Cheung\",\"suffix\":\"\"},{\"id\":337065049,\"identity\":\"d9e36b76-0b92-4085-a293-53d09629eb53\",\"order_by\":4,\"name\":\"Anob M. Chakrabarti\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Anob\",\"middleName\":\"M.\",\"lastName\":\"Chakrabarti\",\"suffix\":\"\"},{\"id\":337065051,\"identity\":\"39342bfc-929b-4ecd-b7b0-40e29409dc05\",\"order_by\":5,\"name\":\"Andrew M Jobbins\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Imperial College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Andrew\",\"middleName\":\"M\",\"lastName\":\"Jobbins\",\"suffix\":\"\"},{\"id\":337065052,\"identity\":\"4cc952cb-b231-4082-b8f9-3c310ffa02d3\",\"order_by\":6,\"name\":\"Callum Parr\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"RIKEN Center for Integrative Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Callum\",\"middleName\":\"\",\"lastName\":\"Parr\",\"suffix\":\"\"},{\"id\":337065054,\"identity\":\"ef068ba9-e650-4306-87cb-25eb5792da8c\",\"order_by\":7,\"name\":\"Kayoko Yasuzawa\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"RIKEN Center for Integrative Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kayoko\",\"middleName\":\"\",\"lastName\":\"Yasuzawa\",\"suffix\":\"\"},{\"id\":337065056,\"identity\":\"9488430b-0323-4f55-952a-b941842a685f\",\"order_by\":8,\"name\":\"Takeya Kasukawa\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"RIKEN Center for Integrative Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Takeya\",\"middleName\":\"\",\"lastName\":\"Kasukawa\",\"suffix\":\"\"},{\"id\":337065057,\"identity\":\"ea2ee8c4-9125-4844-99f7-ccce28cc110f\",\"order_by\":9,\"name\":\"Chi Wai Yip\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"RIKEN Center for Integrative Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Chi\",\"middleName\":\"Wai\",\"lastName\":\"Yip\",\"suffix\":\"\"},{\"id\":337065058,\"identity\":\"7854e65f-48e8-4fee-801d-36c55fb6c3e4\",\"order_by\":10,\"name\":\"Masaki Kato\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"RIKEN Center for Integrative Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Masaki\",\"middleName\":\"\",\"lastName\":\"Kato\",\"suffix\":\"\"},{\"id\":337065059,\"identity\":\"a118e019-db08-45b1-904b-0c7d7a325e0a\",\"order_by\":11,\"name\":\"Hazuki Takahashi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"RIKEN Center for Integrative Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Hazuki\",\"middleName\":\"\",\"lastName\":\"Takahashi\",\"suffix\":\"\"},{\"id\":337065060,\"identity\":\"4f7ac248-0707-4dff-a898-232e3b8a8f5c\",\"order_by\":12,\"name\":\"Piero Carninci\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"RIKEN Center for Integrative Medical Sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Piero\",\"middleName\":\"\",\"lastName\":\"Carninci\",\"suffix\":\"\"},{\"id\":337065061,\"identity\":\"f7af7487-5c60-4213-80e6-313f51b85435\",\"order_by\":13,\"name\":\"Santiago Vernia\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Imperial College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Santiago\",\"middleName\":\"\",\"lastName\":\"Vernia\",\"suffix\":\"\"},{\"id\":337065062,\"identity\":\"2f3eee8d-68ad-4c57-921c-094d38c4fa70\",\"order_by\":14,\"name\":\"Jernej Ule\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"UK Dementia Research Institute\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jernej\",\"middleName\":\"\",\"lastName\":\"Ule\",\"suffix\":\"\"},{\"id\":337065063,\"identity\":\"b8a6e64e-3308-4a48-9710-e8698638ad03\",\"order_by\":15,\"name\":\"Christopher R Sibley\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Edinburgh\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Christopher\",\"middleName\":\"R\",\"lastName\":\"Sibley\",\"suffix\":\"\"},{\"id\":337065064,\"identity\":\"b1f8c0a2-7b28-4bf1-b211-cf42e1bc3791\",\"order_by\":16,\"name\":\"Aida Martinez-Sanchez\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Imperial College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Aida\",\"middleName\":\"\",\"lastName\":\"Martinez-Sanchez\",\"suffix\":\"\"},{\"id\":337065065,\"identity\":\"f7581c77-74a1-4bcf-9199-b549437b4e0e\",\"order_by\":17,\"name\":\"Boris Lenhard\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Imperial College London\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Boris\",\"middleName\":\"\",\"lastName\":\"Lenhard\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-07-26 17:44:22\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4809688/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4809688/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":63804968,\"identity\":\"40f8b198-19b2-4ce9-a8f9-b59d8cb200c6\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:32:44\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1949960,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eCAGE-seq identifies non-promoter associated capped 3'UTR-derived RNAs.\\u003c/p\\u003e\\n\\u003cp\\u003e(a) Top: Schematic representation of CAGE signals’ position across different transcript regions. Bottom: Bars indicate the proportion of total 5’ CAGE read positions per transcript region identified in CAGE-seq libraries of K562 and HeLa samples with two biological replicates each (rep1/2), provided by ENCODE.\\u003c/p\\u003e\\n\\u003cp\\u003e(b) Top: Plot of the normalised coverage of the 5’ ends of forward paired-end reads (yellow lines) and 3’ ends of reverse paired-end reads (blue lines) of RNA-seq relative to 3’UTR CAGE peaks in K562 cells. Bottom: Schematic representation of paired-end read positioning. Forward and reversed paired-end reads are presented in yellow and blue, respectively with the intensity of the colour indicating each of two biological replicates. The black box represents the ends of reads that are plotted in the top graph.\\u003c/p\\u003e\\n\\u003cp\\u003e(c) RT-qPCR data of gene expression ratios using primers amplifying regions immediately upstream (5’C) and downstream (3’C) of the 3‘UTR CAGE peak, except for SLC38A2 whose 3’ cleavage site results in uncapped downstream fragment. Data is presented as a fold-change of samples treated with TerminatorTM 5 ́-Phosphate-Dependent Exonuclease (TEX), which degrades 5′ monophosphate RNAs, \\u003cem\\u003eversus \\u003c/em\\u003enon-treated (NT). Each dot represents an independent biological replicate.\\u003c/p\\u003e\\n\\u003cp\\u003e(d) Long-read CAGE data showing 3’ UTR-derived RNAs from CCN1 (above) and CDKN1B (below). Nanoblot plots (left) showing the range of read lengths at these genomic loci from two biological replicates in cortical neurons differentiated from induced pluripotent stem cells (_rep1 and _rep2), with long-read CAGE reads originating near the TSS (purple arrowhead) and those originating near the HeLa and K562 3’UTR CAGE peaks (green arrowhead) indicated. Genome browser visualisation (right) of the reads grouped and coloured in the same manner: 1_TSS (purple) originating near the TSS; 2_UTR (green) originating near the HeLa and K562 3’ UTR CAGE peaks and 3_OTHER (orange) originated at other sites.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/7992e114606d9112401cc1d1.jpg\"},{\"id\":63807009,\"identity\":\"2b074943-b5bf-4b6e-9587-8586e716716a\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:40:44\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1151342,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e5' ends of 3'UTR-derived RNAs are enriched in G-rich motifs and strong secondary structures and flanked by UPF1 binding sites.\\u003c/p\\u003e\\n\\u003cp\\u003e(a) Sequence logos around HeLa cells’ CAGE peaks across different transcript regions.\\u003c/p\\u003e\\n\\u003cp\\u003e(b) The 75 nt region centred on HeLa cells’ CAGE peaks at different transcript regions was used to calculate pairing probability with the RNAfold program, and the average pairing probability of each nucleotide is shown for the 50 nt region around CAGE peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(c) Enrichment of eCLIP cross-linking clusters surrounding 3’UTR CAGE peaks from 80 different RBP samples (right-hand side panel) in K562 cells from the ENCODE database using sum of log2 ratios of crosslink enrichments. The red line represents the threshold of top 10 RBP targets which are presented in detail in the left-hand side panel.\\u003c/p\\u003e\\n\\u003cp\\u003e(d) RNA-map \\u003ca href=\\\"https://sciwheel.com/work/citation?ids=6155972\\u0026amp;pre=\\u0026amp;suf=\\u0026amp;sa=0\\\"\\u003e[71]\\u003c/a\\u003eshowing normalised density of UPF1 crosslink sites relative to 3’UTR CAGE peaks (blue, UPF1) and random positions of the same 3’UTRs as control (grey, UPF1-control) in K562 cells.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure2.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/28f0cec4c4f854224392b7cd.jpg\"},{\"id\":63804969,\"identity\":\"b247275e-9842-461c-997d-5a6eff8497fb\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:32:44\",\"extension\":\"jpg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1487987,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eCapping at small interfering RNAs (siRNAs) target sites.\\u003c/p\\u003e\\n\\u003cp\\u003e(a) Enrichment of 5’ CAGE reads relative to 5’ sites of small interfering RNAs in TC-YIK cells transfected with siRNAs targeting 20 different mRNAs (With IDs indicated on the left-hand side of the bottom graph) and merged control samples (control). The heatmap represents log2 of read counts, normalised by the mean of all counts within 200 nts of the targeting site.\\u003c/p\\u003e\\n\\u003cp\\u003e(b) , (c) Enrichment of 5’ CAGE reads relative to the correspondent dominant transcription start sites (TSS) (left-hand side panels) and to 5’ end of the \\u003cem\\u003eISL1\\u003c/em\\u003e mRNA sequence targeted by the siRNA (right-hand side panels) in samples treated with an siRNA targeting \\u003cem\\u003eISL1 \\u003c/em\\u003e(C, siRNA-ISL1) or with non-targeting siRNA controls (B, control siRNAs). Three biological replicates are shown \\u003cem\\u003eper \\u003c/em\\u003etreatment. Visual representations of the capped, full-length \\u003cem\\u003eISL1 \\u003c/em\\u003emRNA in the absence of \\u003cem\\u003eISL1\\u003c/em\\u003e-targeting siRNAs (B, control siRNAs) \\u003cem\\u003eversus \\u003c/em\\u003eboth the capped, full-lenght and the capped, cleaved fragment in the presence of \\u003cem\\u003eISL1\\u003c/em\\u003e-targeting siRNAs (C, siRNA-ISL1), are shown below the correspondent panels.\\u003c/p\\u003e\\n\\u003cp\\u003e(d) RNA-map \\u003ca href=\\\"https://sciwheel.com/work/citation?ids=6155972\\u0026amp;pre=\\u0026amp;suf=\\u0026amp;sa=0\\\"\\u003e[71]\\u003c/a\\u003eshowing normalised density of eiCLIP-AGO2 crosslink sites relative to 3’UTR CAGE peaks in HeLa cells.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure3.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/b42c83b9ae9df19107b4fe41.jpg\"},{\"id\":63807013,\"identity\":\"aa5884f4-15da-4d9f-afaa-31a1be8d6b25\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:40:44\",\"extension\":\"jpg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":2745307,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eCapped 3’UTR fragments of \\u003cem\\u003eCDKN1B\\u003c/em\\u003e and \\u003cem\\u003eJPT2\\u003c/em\\u003e transcripts do not co-localise with the parental mRNAs\\u003c/p\\u003e\\n\\u003cp\\u003e(a) Schematic representation of probe design for HCR-FISH microscopy to separate regions upstream (green) and downstream (purple) of the 3’UTR CAGE sites as cleaved, independent signals and uncleaved, co-localised signals.\\u003c/p\\u003e\\n\\u003cp\\u003e(b) Representative examples of HCR-FISH images for\\u003cem\\u003e PGAM1 \\u003c/em\\u003e(control),\\u003cem\\u003e JPT2\\u003c/em\\u003eand \\u003cem\\u003eCDKN1B\\u003c/em\\u003e. Independent signal from upstream probes is shown in green and signal from downstream probes is shown in purple, with colocalising signals appearing in white.\\u003c/p\\u003e\\n\\u003cp\\u003e(c) Proportion of independent signals for each upstream or downstream probes. Independent signals are those without a detected colocalising signal from the opposing probset. Error bars represent standard error. Significance was determined using pairwise Welch t-tests. * p (adjusted) \\u0026lt; 0.05, ** p \\u0026lt; 0.005.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure4c.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/e964fd1eef9bb664c52fca5d.jpg\"},{\"id\":63807048,\"identity\":\"89e8bc4d-c1a5-4c3f-b8bd-8e2b034704c1\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:40:53\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":8115441,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/ba9425a5-039c-45de-94e7-59baae616e3e.pdf\"},{\"id\":63804975,\"identity\":\"12d97ff8-de4d-4611-8f9e-837bc3b814b8\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:32:44\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":3192512,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFig. S1: Related to Fig. 1\\u003c/p\\u003e\\n\\u003cp\\u003e(a) Pearson’s correlation of raw CAGE reads counts per TSS or consensus cluster across biological replicates and cell types.\\u003c/p\\u003e\\n\\u003cp\\u003e(b) Reverse cumulative distribution of CAGE reads after normalisation using CAGEr package [72](CTSS = CAGE Transcription start site).\\u003c/p\\u003e\\n\\u003cp\\u003e(c) Total number of CAGE reads in each sample.\\u003c/p\\u003e\\n\\u003cp\\u003e(d) Density of total 5’ CAGE read positions normalised by the length of the correspondent transcript region identified in CAGE-seq libraries of K562 and HeLa samples with two biological replicates each, provided by ENCODE.\\u003c/p\\u003e\\n\\u003cp\\u003e(e) Percentage of CAGE tags per transcript region using Random primers, Oligod-T primers, and combination of both primers (1:4 oligod(T):Random Primers) in CAGE-seq libraries of THP-1 cells generated by RIKEN.\\u003c/p\\u003e\\n\\u003cp\\u003e(f) - (i) Pearson’s correlation between CAGE-seq replicates (rep1, rep2) and different cell lines (HeLa, K562) samples in 3’UTRs (F), 5’UTRs (G), CDS (H) and introns (I).\\u003c/p\\u003e\\n\\u003cp\\u003e(j) Top: Plot of the normalised coverage of the 5’ ends of forward paired-end reads (yellow line) and 3’ ends of reverse paired-end reads (blue line) of RNA-seq relative to 3’UTR CAGE peaks in HeLa cells. Bottom: Schematic representation of paired-end read positioning. Forward and reversed paired-end reads are presented in yellow and blue, respectively. The black box represents the ends of reads that are plotted in the top graph.\\u003c/p\\u003e\\n\\u003cp\\u003e(k) RT-qPCR data of gene expression using primers designed to amplify sequences located downstream (3’C), upstream (5’C) and overlapping (AC) the 3’UTR CAGE sites of CDKN1B and JPT2. Data represents fold detection using downstream versus upstream/overlapping primers relative to the 3‘UTR CAGE peaks. Each dot represents an independent biological replicate. Primer target sequences relative to the 3’UTR CAGE peak are schematically represented on the top right-hand side and visualised for each gene using IGV genome browser on the bottom.\\u003c/p\\u003e\\n\\u003cp\\u003e(l) Top gene examples with strongest 3’UTR CAGE peaks present in K562 and HeLa cell lines using IGV-genome browser for visualisation.\\u003c/p\\u003e\\n\\u003cp\\u003e(m) Visualisation of RNA-seq reads relative to dominant 3’UTR CAGE peaks in CDKN1B and JPT2 gene using IGV-genome browser.\\u003c/p\\u003e\\n\\u003cp\\u003e(n) Visualisation of 10 gene examples with 3’UTR CAGE peaks (HeLa, K562), rG4-seq clusters (HeLa) and long-read CAGE (Cortical Neuron) reads using IGV-genome browser.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"FigureS1c.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/ad5ff8c721d27d56b0225aec.pdf\"},{\"id\":63804970,\"identity\":\"eaed208b-6f34-427c-a6ce-4d2c3c3b440f\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:32:44\",\"extension\":\"pdf\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":1729832,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFig. S2: Related to Fig. 2\\u003c/p\\u003e\\n\\u003cp\\u003e(a) RNA-map showing normalised density of CBP20-iCLIP (HeLa) crosslink sites relative to dominant 3’UTR and 5’UTR CAGE peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(b) Mean score of GRO-cap seq coverage [26]per CAGE peak for 5’UTR, CDS, intron and 3’UTR regions. The heatmap represents GRO-cap seq scores plotted with deeptools.\\u003c/p\\u003e\\n\\u003cp\\u003e(c) RNA-map showing normalised density of cap-CLIP (HeLa) crosslink sites relative to dominant 3’UTR and 5’UTR CAGE peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(d) Mean coverage of conservation score from UCSC phastCons30way track relative to inner 3’UTR CAGE peaks (≥150 bps downstream from CDS and ≥150 bps upstream from transcript termination) and randomised control positions around the same region of 150 nts window for each peak.\\u003c/p\\u003e\\n\\u003cp\\u003e(e) Normalised motif enrichment of canonical PolyA motifs relative to 3’UTR ends and to the dominant 3’UTR CAGE peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(f) Sequence logos around K562 cells’ CAGE peaks across different transcript regions\\u003c/p\\u003e\\n\\u003cp\\u003e(g) The 75 nt region centred on K562 cells’ CAGE peaks at different transcript regions was used to calculate pairing probability with the RNAfold program, and the average pairing probability of each nucleotide is shown for the 50 nt region around CAGE peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(h) GGG-motif enrichment relative to CAGE (HeLa) peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(i) GGG-motif enrichment relative to CAGE (K562) peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(j) Summarised score from G4-Hunter prediction tool in the region of 50 nts upstream and downstream relative to CAGE (HeLa) peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(k) Summarised score from G4-Hunter prediction tool in the region of 50 nts upstream and downstream relative to CAGE (K562) peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(l) Enrichment of RNA-G-quadruplex sequencing (rG4-seq) hits from HeLa cells relative to CAGE (HeLa) peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(m) Percentage of G-seq sites per transcript region.\\u003c/p\\u003e\\n\\u003cp\\u003e(n) Enrichment of eCLIP cross-linking clusters surrounding 5’UTR CAGE peaks from 80 different RBP samples (right panel) in K562 cells from ENCODE database using sum of log ratios. The red line represents the threshold of top 10 RBP targets (left panel).\\u003c/p\\u003e\\n\\u003cp\\u003e(o) Enrichment of eCLIP cross-linking clusters surrounding intronic CAGE peaks from 80 different RBP samples (right panel) in K562 cells from ENCODE database using sum of log ratios. The red line represents the threshold of top 10 RBP targets (left panel).\\u003c/p\\u003e\\n\\u003cp\\u003e(p) Enrichment of eCLIP cross-linking clusters surrounding CDS CAGE peaks from 80 different RBP samples (right panel) in K562 cells from ENCODE database using sum of log ratios. The red line represents the threshold of top 10 RBP targets (left panel).\\u003c/p\\u003e\\n\\u003cp\\u003e(q) Pearson’s correlation between the 3’UTR CAGE (K562) tags and RNA-seq (K562) read coverage per gene (top-left). Pearson’s correlation between the 3’UTR crosslink coverage of UPF1-eCLIP (K562) and 3’UTR CAGE (K562) tags (top-right). Pearson’s correlation between the 3’UTR length and 3’UTR crosslink coverage of UPF1-eCLIP (K562) (bottom-left). Pearson’s correlation between the 3’UTR length and 3’UTR CAGE (K562) tags (bottom-right).\\u003c/p\\u003e\\n\\u003cp\\u003e(r) UPF1-eCLIP (K562) crosslink enrichment relative to the distance from the 3’UTR CAGE (K562) peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(s) Heatmap of UPF1-eCLIP (K562) crosslink site enrichment showing the top 500 3’UTR AGO2 targets in 100 nts flanking region relative to 3’UTR CAGE (K562) peaks. The heatmap represents log2 of crosslink counts, normalised by the mean of all counts within 200 nts of the targeting site.\\u003c/p\\u003e\\n\\u003cp\\u003e(t) K562 cells were transfected with siRNAs targeting UPF1 or non-targeting controls (C). Left-hand side panel: UPF1 expression was measured with RT-qPCR. Data is normalised by the housekeeping gene RPLP0 and presented as fold change of the control. Right-hand side panel: RT-qPCR data of gene expression using primers designed to amplify sequences located downstream (3’C) and upstream (5’C) the 3’UTR CAGE sites of CDKN1B and JPT2. Data represents fold detection using downstream (3’C) versus upstream (5’C) primers. Each dot represents an independent biological replicate. Primer target sequences relative to the 3’UTR CAGE peaks are schematically represented on the right.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"FigureS2c.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/39b0f0b2c06ba887e0e32418.pdf\"},{\"id\":63804978,\"identity\":\"9c278d3f-375d-4d81-96de-8bdaec5e37a3\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:32:44\",\"extension\":\"pdf\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":14154288,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFig. S3: Related to Fig. 3\\u003c/p\\u003e\\n\\u003cp\\u003e(a) Visualisation of 5’ CAGE reads relative to dominant transcription start site (TSS) and relative to small interfering RNA of ISL1 target (in red) for CAGE-ISL1-KD and CAGE-control samples with 3 biological replicates using IGV-genome browser.\\u003c/p\\u003e\\n\\u003cp\\u003e(b) Percentage of AGO2-eiCLIP (HeLa) binding sites per transcript region.\\u003c/p\\u003e\\n\\u003cp\\u003e(c) Binding enrichment of AGO2-eiCLIP (HeLa) relative to miRNA-regulated transcripts and non-miRNA-regulated transcript in HeLa (data from [73] ).\\u003c/p\\u003e\\n\\u003cp\\u003e(d) Heatmap of miRNA-seed sequence enrichment in 30 nt flanking region showing the top 500 AGO2 binding sites relative to AGO-eiCLIP (HeLa) crosslink sites. Meta plot visualises the miRNA-seed sequence composition relative to the 5’ of the AGO2 binding site.\\u003c/p\\u003e\\n\\u003cp\\u003e(e) Heatmap of AGO2-eiCLIP (HeLa) crosslink site enrichment showing the top 500 3’UTR AGO2 targets in 100 nts flanking region relative to 3’UTR CAGE (HeLa) peaks. The heatmap represents log2 of crosslink counts, normalised by the mean of all counts within 200 nts of the targeting site.\\u003c/p\\u003e\\n\\u003cp\\u003e(f) RNA-map showing normalised density of AGO2 crosslink sites from AGO2 binding sites that contain (mir+) or are absent (mir-) from predicted miRNA binding sites relative to 3’UTR CAGE peaks.\\u003c/p\\u003e\\n\\u003cp\\u003e(g) AGO2 mRNA expression was measured with RT-qPCR in 3 clonal subpopulations generated by single cell sorting of K562 cells transfected with a plasmid expressing Cas9 and two gRNAs targeting AGO2 and preselected by genomic DNA sequencing. Both KO1 and KO2 contained edited AGO2 sequences and control (C) wild-type sequences. Data is normalised by the housekeeping gene RPLP0 and presented as a fold change of the control. Each dot represents an independent biological replicate.\\u003c/p\\u003e\\n\\u003cp\\u003e(h) AGO2 protein was detected by Western Blot in 6 clonal subpopulations generated as in (g). Clon 2 and 6 were selected for further experiments and re-named as KO1 and KO2. This experiment was performed once.\\u003c/p\\u003e\\n\\u003cp\\u003e(i) RT-qPCR data of gene expression using primers designed to amplify sequences located downstream (3’C) and upstream (5’C) the 3’UTR CAGE sites of CDKN1B and JPT2. Data represents fold detection using downstream (3’C) versus upstream (5’C) primers. Each dot represents an independent biological replicate. Primer target sequences relative to the 3’UTR CAGE peaks are schematically represented below.\\u003c/p\\u003e\\n\\u003cp\\u003e(j) Sequence logos and statistics of top 12 significantly enriched motifs of AGO2-eiCLIP (HeLa) binding sites using Homer for de novo motif discovery.\\u003c/p\\u003e\\n\\u003cp\\u003e(k) Enrichment of AGO2-eiCLIP (HeLa) cross-linking sites relative to the 3’end of the rG4-seq site (HeLa).\\u003c/p\\u003e\\n\\u003cp\\u003e(l) Heatmap for AGO2-eiCLIP (HeLa) crosslink site enrichment to show the top 500 3’UTR AGO2 targets in 100 nts flanking region relative to 3’end of rG4-seq (HeLa) site. The heatmap represents log2 of crosslink counts, normalised by the mean of all counts within 200 nts of the targeting site.\\u003c/p\\u003e\\n\\u003cp\\u003e(m) Enrichment of UPF1-eCLIP (K562) cross-linking sites relative to the 3’end of the rG4-seq site (HeLa).\\u003c/p\\u003e\\n\\u003cp\\u003e(n) Heatmap for UPF1-eCLIP (K562) crosslink site enrichment to show the top 500 3’UTR UPF1 targets in 100 nts flanking region relative to 3’end of rG4-seq (HeLa) site. The heatmap represents log2 of crosslink counts, normalised by the mean of all counts within 200 nts of the targeting site.\\u003c/p\\u003e\\n\\u003cp\\u003e(o) Upset plot of intersection of AGO2-eiCLIP (HeLa) and UPF1-eCLIP(K562) binding sites, G4-seq (HeLa) sites relative to 3’UTR CAGE peaks (K562 \\u0026amp; HeLa).\\u003c/p\\u003e\\n\\u003cp\\u003e(p) RNA-map showing normalised density of AGO2 crosslink sites relative to 3’UTR CAGE peaks intersecting G4-seq site (G4+) or not (G4-) from Fig. S3l.\\u003c/p\\u003e\\n\\u003cp\\u003e(q) RNA-map showing normalised density of UPF1 crosslink sites relative to 3’UTR CAGE peaks intersecting G4-seq site (G4+) or not (G4-) from Fig. S3l.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"FigureS3.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/4e8c5be573ce9c11e7172b5d.pdf\"},{\"id\":63804972,\"identity\":\"95085946-d970-4044-aa0c-76471099445b\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:32:44\",\"extension\":\"pdf\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":717130,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFig. S4: Related to Fig. 4\\u003c/p\\u003e\\n\\u003cp\\u003e(a) Density plots showing the shortest distance per detected signal in pixels to a signal of the opposite colour. The dashed line shows the cutoff used to distinguish colocalising and non-colocalising signals.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"FigureS4.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/f10275ea84d76be00d7cee72.pdf\"},{\"id\":63804974,\"identity\":\"9621c081-f77d-4333-bf86-8eb03d735636\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:32:44\",\"extension\":\"zip\",\"order_by\":5,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":561231,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eTables\\u003c/p\\u003e\\n\\u003cp\\u003eTable S1: This table contains genomic locations of 32,065 unique 3’UTR CAGE clusters across all CAGE samples from HeLa and K562 cell lines. Each sample contains a normalised value of 5’ read positions for each cluster.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"TableS1.tab.zip\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/e7ddbfe0652e4c7042286a97.zip\"},{\"id\":63804977,\"identity\":\"68576c1b-1fed-4a8c-91fe-acf8baf6496c\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:32:44\",\"extension\":\"pdf\",\"order_by\":6,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":493016,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Figure0Graphicalabstract.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/cf30831a7b94fb0f6bc33980.pdf\"},{\"id\":63807010,\"identity\":\"f9d0c3ae-6b7d-4118-a9fb-bf72f87d330f\",\"added_by\":\"auto\",\"created_at\":\"2024-09-02 13:40:44\",\"extension\":\"docx\",\"order_by\":7,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":32904,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplmentrayFile.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4809688/v1/2dc1850f45c827e14905fbf3.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Widespread 3'UTR capped RNAs derive from G-rich regions in proximity to AGO2 binding sites\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eIn all eukaryotes, mRNA molecules contain an evolutionarily conserved m7G cap (N7-methylated guanosine), which is incorporated at the 5\\u0026rsquo; end of nascent transcripts. Co-transcriptional capping is the first modification made to nascent RNA in the nucleus, which protects it from exonuclease cleavage while promoting cap-related biological functions such as pre-mRNA splicing, polyadenylation and nuclear export [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. In addition to the co-transcriptional capping, there is also evidence for a post-transcriptional capping mechanism, in which an m7G cap is added to newly exposed 5\\u0026rsquo; ends of RNA fragments created upon endonucleolytic cleavage or decapping [\\u003cspan additionalcitationids=\\\"CR3 CR4\\\" citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. However, little is known about the extent and biological role of this post-transcriptional capping, and of its relation to other post-transcriptional RNA processing mechanisms.\\u003c/p\\u003e \\u003cp\\u003eCap analysis of gene expression and deep-sequencing (CAGE-seq) was originally designed to precisely determine transcription start site (TSS) positions by capturing and sequencing 5\\u0026rsquo; ends of capped mRNA transcripts, and it can also be used to measure gene expression [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. However, several studies have detected the unexpected, reproducible, and so-far unexplained presence of CAGE signals (~\\u0026thinsp;10\\u0026ndash;15% of total reads) and/or an enrichment of RNA-seq reads mapping to 3\\u0026rsquo;UTRs, far away from the usual TSS [\\u003cspan additionalcitationids=\\\"CR8 CR9 CR10 CR11 CR12 CR13 CR14\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Previous studies have shown an absence of active promoter marks (i.e. no enrichment histone modifications or RNA polymerase II (RNAPII) occupancy) around these 3\\u0026rsquo;UTR signals [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e], arguing against the possibility that they are unannotated transcription start sites. Moreover, the expression of some of these capped 3\\u0026rsquo; UTRs is tissue-specific and regulated in mouse embryonic development, whilst their subcellular localization can be separated from the associated protein-coding transcript, suggesting that their generation is a regulated process [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. In addition, specific isolated 3'UTRs have been implicated in a growing number of physiological processes, such as cell signalling or oxidative stress [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. Moreover, several capped 3\\u0026rsquo;UTRs have been reported to play important roles in regulating protein expression in \\u003cem\\u003etrans\\u003c/em\\u003e, similar to long non-coding RNAs [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. Truncated mRNAs and RNA decay intermediates can be subject to post-transcriptional, cytosolic capping [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e] and it has been suggested that a similar mechanisms may underlie the generation of some 3\\u0026rsquo;UTR CAGE signals, referred to as 3\\u0026rsquo;UTR-associated RNAs (uaRNAs) [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. To avoid potential misunderstandings we refer to these as 3\\u0026rsquo;UTR-derived RNAs, as these newly generated RNAs are not known to be physically associated with 3\\u0026rsquo; UTRs.\\u003c/p\\u003e \\u003cp\\u003eHere, we thoroughly examine the presence of these 3\\u0026rsquo;UTR-derived RNAs across the transcriptome, and the molecular basis of their generation and characteristics. We perform a genome-wide identification of 3\\u0026rsquo; UTR-derived RNAs based on their capped 5\\u0026rsquo; ends, and proceed to investigate the mechanisms involved in their formation. To this end, we combine CAGE, RNA-seq and cross-linking immunoprecipitation (CLIP)-based techniques from ENCODE and FANTOM consortia. We show that 3\\u0026rsquo;UTR-derived RNAs present biochemical properties similar to their 5\\u0026rsquo; capped counterparts and that they can be as abundant as the protein-coding version of the host transcript, or even more so. We reveal that the 5' ends of 3'UTR-derived RNAs are enriched in G-rich motifs and tend to form strong secondary structures, while the immediately upstream region of these 5' ends is bound by UPF1 and/or AGO2. Moreover, some of these abundant 3\\u0026rsquo; UTR-derived RNAs exhibit a markedly different subcellular localisation profile than their protein-coding counterparts. Finally we show, for the first time, that capped RNAs can also emerge following mRNA cleavage by small interfering RNAs (siRNAs).\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCAGE-seq identifies non-promoter associated capped 3'UTR-derived RNAs\\u003c/h2\\u003e \\u003cp\\u003eWe and others [\\u003cspan additionalcitationids=\\\"CR8 CR9 CR10 CR11\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e] have previously reported the presence of CAGE-seq signals outside of annotated promoter regions in thousands of protein-coding genes. However, their origin or biological relevance has not been thoroughly interrogated. Here we first confirmed the prevalence of these signals in human cell lines using CAGE data provided by the ENCODE consortium. As expected, we detected a similar proportion of CAGE signals per genomic region in two different human cell lines (HeLa and K562) and showed that the CAGE signal is highly reproducible across replicates. This included the library size, number of uniquely mapped CAGE reads and distribution of the 5\\u0026rsquo; CAGE reads mapping to different genomic regions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003ea, \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003ea, b, c, d). A similar genomic distribution has also been detected by other groups before, using the same CAGE-seq protocol [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe relative intensities of CAGE signal detected at different genomic regions depend on the priming method for reverse transcription (oligo-dT, random hexamers, or mixtures thereof in different ratios) [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]. Oligo-dT priming quantitatively favours shorter transcripts, while the reverse is true for random priming. We subsequently verified CAGE signals within 3\\u0026rsquo;UTRs are most detected when a combination of Oligo-dT and random primers is used, with the optimal inclusion ratio of 1 to 4 ratio of Oligo-dT to random primers [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e] (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003ee). Notably, the same ratio was used in ENCODE CAGE samples analysed in this study.\\u003c/p\\u003e \\u003cp\\u003eThe CAGE signal is the strongest at 5'UTRs of known protein-coding genes [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e] (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003ea, ~\\u0026thinsp;65% of total reads). While low-level non-promoter CAGE signal (sometimes referred to as \\u0026ldquo;exon painting\\u0026rdquo; [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e] [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]), can be detected along the entire length of transcripts, the signal at 3\\u0026rsquo;UTRs is consistently present and occurs in localised clusters, similar to CAGE signals at promoters (see Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003el for examples). We focused on the 3\\u0026rsquo;UTR region, which contains a substantial proportion (~\\u0026thinsp;11%) of the total CAGE reads (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003ea), the implications of which are unknown. To identify robust CAGE signals with sufficient sensitivity, we used a 20nt window requiring at least two 5' reads overlapping from two different replicates for each cell line separately. This revealed 32,065 3\\u0026rsquo;UTR CAGE clusters across all samples (Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e). As expected, correlation between technical replicates was high (Pearson correlation (PC)\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.9) for all CAGE signals, independently of genomic location (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003eg-j). Moreover, expression of the 3\\u0026rsquo;UTR CAGE clusters was highly reproducible between HeLa and K562 samples (PC\\u0026thinsp;~\\u0026thinsp;0.98, Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003ef), suggesting biological relevance. Correlation across cell types was much higher for 3\\u0026rsquo;UTR clusters than that for the 5\\u0026rsquo; UTR CAGE (PC\\u0026thinsp;~\\u0026thinsp;0.79, Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003eg) and CDS CAGE (PC of 0.61, Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003eh) signals and comparable to intronic CAGE signal (PC\\u0026thinsp;~\\u0026thinsp;0.93, Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003ei). This may suggest that 3\\u0026rsquo;UTR CAGE signals originate from more stable and/or less tissue specific subset of transcripts. Together these analyses show that the transcripts whose 5\\u0026rsquo; end map to 3\\u0026rsquo;UTR ends of protein-coding genes are highly reproducible across cell types, and that CAGE is a robust method for their quantitative detection.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3'UTR-derived RNAs are confirmed by RNA-seq, qPCR and long-read CAGE\\u003c/h2\\u003e \\u003cp\\u003eNext, we aimed to confirm the existence of these 3\\u0026rsquo;UTR capped RNAs using independent methods. First, we asked if these fragments could be identified in transcriptomic (RNA-seq) data. For this we compared the CAGE signal with the RNA-seq signal of two different cell lines. To categorise CAGE peaks we first used the paraclu [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e] peak caller to identify clusters of 5\\u0026rsquo; ends of capped RNAs, and within each cluster we selected the highest signal as the dominant CAGE peak position. For comparison, we processed paired-end RNA-seq data from the same K562 and HeLa cell lines, then plotted read-starts and read-ends relative to the dominant 3\\u0026rsquo;UTR CAGE peak per transcript (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eb - in blue, and S1J). Both RNA-seq samples showed highly reproducible enrichments of read ends coinciding with dominant 3\\u0026rsquo;UTR CAGE peaks. This reveals that the 3\\u0026rsquo;UTR CAGE peaks are confirmed by the read-ends from reverse-stranded RNA-seq data, which suggests that the signal could be originating from post-transcriptional cleavage sites. Notably, there is also a small enrichment of RNA-seq read-starts downstream from the 3\\u0026rsquo;UTR CAGE peaks, which could represent the same RNA fragments detectable by the CAGE samples (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eb in yellow). More importantly, these findings demonstrate that 3\\u0026rsquo;UTR capped fragments identified by CAGE can also be detected by other, methodologically independent, high-throughput sequencing methods such as RNA-seq.\\u003c/p\\u003e \\u003cp\\u003eWe next aimed to confirm the presence of transcripts initiating at the 3\\u0026rsquo;UTR CAGE peaks by an alternative experimental approach, not dependent on RNA library creation or high-throughput sequencing. We focussed on two genes, \\u003cem\\u003eCDKN1B/\\u003c/em\\u003ep27kip1 (p27) and \\u003cem\\u003eJPT2\\u003c/em\\u003e, which contain a dominant CAGE peak located within the 3\\u0026rsquo;UTR region, demonstrated with highly reproducible read coverage for CAGE and RNA-seq in both K562 and HeLa cells (see Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003em for example). Separate sets of primers were designed to quantitatively PCR-amplify\\u0026thinsp;~\\u0026thinsp;150bp sequences within 300 nucleotides upstream and downstream of the 3\\u0026rsquo;UTR CAGE peaks in \\u003cem\\u003eCDKN1B\\u003c/em\\u003e and \\u003cem\\u003eJPT2\\u003c/em\\u003e (see Methods, Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003ek). In agreement with CAGE and RNA-seq data (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003em), RT-qPCR detected higher levels of these transcripts with the downstream primers (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003eK) than with upstream primers. A similar enrichment in RT-qPCR signal (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003ek) was observed with downstream primers in comparison to primers designed to amplify a\\u0026thinsp;~\\u0026thinsp;150bp region spanning the CAGE peak in CDKN1B, suggesting an accumulation of 3\\u0026rsquo;UTR fragments in comparison to full-length mRNAs.\\u003c/p\\u003e \\u003cp\\u003eTreatment of the samples with TerminatorTM 5\\u0026rsquo;-Phosphate-Dependent Exonuclease (TEX), a 5\\u0026prime;\\u0026rarr;3\\u0026prime; exonuclease that digests RNA with a 5\\u0026prime; monophosphate, but not RNA with 5\\u0026prime;-triphosphate, 5\\u0026prime;-cap or 5\\u0026prime;-hydroxyl group had no or little effect on the amount of \\u003cem\\u003eJPT2\\u003c/em\\u003e and \\u003cem\\u003eCDKN1B\\u003c/em\\u003e transcripts detected with primers amplifying either side of the 3\\u0026rsquo;UTR CAGE peak within these cells. This was in sharp contrast with the known uncapped 3\\u0026rsquo; fragment of \\u003cem\\u003eSLC38A2\\u003c/em\\u003e mRNA, previously described by Malka et al. [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e], which was, as expected, sharply reduced upon TEX treatment (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003ec). These results lend further support that all the quantified transcripts, including the 3\\u0026rsquo;UTR fragments, are capped.\\u003c/p\\u003e \\u003cp\\u003eWe further confirmed that 3\\u0026rsquo;UTR-derived RNAs could be detected by long-read Nanopore-sequencing CAGE (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003ed). We were provided with data in cortical neuron samples by the FANTOM6 consortium for 10 genes that contain HeLa and K562 3\\u0026rsquo;UTR CAGE peaks (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003ed, \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003en). In all of the 10 examples, the full length read sequencing CAGE identified reads spanning from the start of our identified CAGE 3\\u0026rsquo;UTR peaks till the end of the annotated transcripts, whereas for most of these genes, reads spanning between the 5\\u0026rsquo;CAGE and the 3\\u0026rsquo;CAGE signal were absent (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003en). These observations suggest that the capped 3\\u0026rsquo;UTR derived RNAs originate from the full length mRNA whilst fragments upstream of the 3\\u0026rsquo;CAGE may not be stable. Notable exceptions are DDX17 and GHITM but it is unclear whether these 3\\u0026rsquo;CAGE upstream sequences result from alternative polyadenylation or are products from the cytosolic cleavage of the full-lenght.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCapped 3\\u0026rsquo;UTR-derived RNAs are evolutionarily conserved and generated post-transcriptionally\\u003c/h2\\u003e \\u003cp\\u003eWe next wanted to investigate whether the 3\\u0026rsquo;UTR CAGE signals originate from post-transcriptionally capped RNA fragments. First, we explored whether there is evidence of nuclear Cap Binding Complex (CBC) binding to the capped 5\\u0026rsquo; ends of 3'UTR fragments, as this protein is known to bind to 5\\u0026rsquo; ends of nascent protein-coding mRNA transcripts in the nucleus. Individual-nucleotide resolution UV crosslinking and immunoprecipitation (iCLIP) is a method that identifies protein-RNA crosslinking interactions with nucleotide resolution in a transcriptome-wide manner. We examined CBC-iCLIP data from HeLa cells, where the authors targeted nuclear cap-binding subunit CBP20 protein [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. CBP20 is a nuclear component of cap-binding complex (CBC), which binds co-transcriptionally to the 5' cap of pre-mRNAs and interacts directly with the m7-G cap [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. The CBP20 RNA binding data was analysed using a standard iCLIP processing pipeline, where the nucleotide preceding the cDNA-start position after PCR duplicate removal is reported as the crosslinking position (see Methods). The CBP20 crosslinking positions were then screened across all dominant 5\\u0026rsquo;UTR and 3\\u0026rsquo;UTR CAGE peaks per transcript. As expected, CBP20 crosslinks were enriched around the dominant 5\\u0026rsquo;UTR CAGE peaks where the TSS of full-length transcripts is positioned. However, the enrichment was very weak at the non-promoter 3\\u0026rsquo;UTR CAGE peaks (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003ea). This strongly indicates that the 3\\u0026rsquo;UTR capped fragments identified by CAGE are not part of nuclear CBC, further suggesting that they are likely a product of an independent post-transcriptional processing pathway.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eTo further explore whether the 3\\u0026rsquo;UTR capped fragments were generated co-transcriptionally, we investigated the location of cap signals in nascent RNAs identified in global nuclear run-on sequencing experiments of 5\\u0026rsquo; capped RNAs (GRO-cap) [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. As anticipated, strong GRO-cap signals overlapped with CAGE peaks in 5\\u0026rsquo;UTRs and, to a lesser extent, with introns and upstream CDSs but were notably absent around 3\\u0026rsquo;UTR CAGE peaks (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003eb). This also indicates that capping of 3\\u0026rsquo;UTR fragments occurs post-transcriptionally.\\u003c/p\\u003e \\u003cp\\u003eAdditionally, we analysed capCLIP data from HeLa cells. capCLIP is a version of CLIP that targets the translation elongation factor eIF4E, a cytoplasmic protein which binds the 7-methyl-GTP moiety of the 5\\u0026prime;-cap structure of RNAs to facilitate the efficient translation of almost all mRNAs [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. The capCLIP data was analysed following the same methodology as CBP20-iCLIP. The enrichment of capCLIP signal at the non-promoter 3\\u0026rsquo;UTR CAGE peaks was much stronger than in the CBC-iCLIP (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003ea, S2c), which demonstrates that the cap of the 3\\u0026rsquo;UTR-derived RNAs is strongly bound by cytoplasmic eIF4E, but not the nuclear cap binding protein CBP20, suggesting that these RNAs are predominantly cytoplasmic. Furthermore, we investigated ribosome footprinting data [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e] to interrogate whether the 3'UTR-derived RNAs, which are bound by eIF4E, are translated. However, we did not find evidence of ribosomal binding to these RNAs that suggested active translation (data not-shown).\\u003c/p\\u003e \\u003cp\\u003eNext, we investigated the evolutionary conservation of 3\\u0026rsquo;UTR-derived RNAs. Utilising UCSC conservation tracks, we computed conservation scores around 3\\u0026rsquo;UTR CAGE peaks. To exclude the influence of coding regions and transcript termination sites, we specifically selected 21,831 3\\u0026rsquo;UTR CAGE peaks positioned at least 150 bps away from the 3\\u0026rsquo;UTR bordering region (\\u0026ge;\\u0026thinsp;150 bps downstream from CDS and \\u0026ge;\\u0026thinsp;150 bps upstream from transcript termination). Remarkably, our findings reveal that the exact 3\\u0026rsquo;UTR CAGE peaks exhibit lower conservation compared to the surrounding regions. However, the region immediately downstream of the 3\\u0026rsquo;UTR CAGE peaks, corresponding to the \\\"body\\\" of 3\\u0026rsquo;UTR-derived RNAs shows a notable enrichment in conservation scores, suggesting a potential functional contribution (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003ed).\\u003c/p\\u003e \\u003cp\\u003eAltogether, these analyses confirm the presence of abundant, evolutionarily conserved, capped 3\\u0026rsquo;UTR-derived non-coding RNAs that may originate from cytosolic cleavage of full-length mRNAs.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e5' ends of 3'UTR-derived RNAs are enriched for G-rich motifs and strong secondary structures\\u003c/h2\\u003e \\u003cp\\u003eNext, we wanted to understand the sequence features that distinguish the CAGE peaks corresponding to co-transcriptional capping of TSS from those originating from post-transcriptional capping of 3'UTR-derived RNAs. We first explored the possibility that 3\\u0026rsquo;UTR fragments might be a by-product of nuclear polyadenylation and associated endonucleolytic cleavage. If this were the case, the identified 3'UTR CAGE peaks should be preceded by enrichment of the canonical polyA signal (A[A/U]UAAA hexamers), which recruit the nuclear polyadenylation machinery. However, we only found such enrichment at the annotated 3'UTR ends, and not upstream of the 3'UTR CAGE peaks (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003ee). We observed a notable enrichment downstream of the 3\\u0026rsquo;UTR CAGE peaks (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003ee - red line), which most likely corresponds to the canonical polyA site as some of the 3'UTR-derived RNAs are relatively short and their 5\\u0026rsquo; ends are close to the annotated 3'UTR ends.\\u003c/p\\u003e \\u003cp\\u003eNext, we explored whether there were additional distinctive sequence characteristics between the two types of CAGE peaks. Consistent with previous studies [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e], we detected a strong G-enrichment overlapping the 5\\u0026rsquo; end of the CAGE reads present in non-promoter regions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ea, \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003ef), distinct from the YR dinucleotide characteristic of signals at 5\\u0026rsquo; ends of genes. More surprisingly, CAGE peaks within the 3\\u0026rsquo;UTR region showed a strong increase in internal pairing probability (see Methods: Secondary structure) in comparison to CAGE peaks in other regions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eb, \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003eg), suggesting that structural preference may be important for the generation of 3\\u0026rsquo;UTR-derived RNAs. Notably, the surrounding (within 100 bps) region of CAGE peaks in 5\\u0026rsquo;UTRs is more structured (light blue line in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eb, \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003eg), representing the higher GC content that is present around all 5\\u0026rsquo;UTRs in vertebrates [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e], with a distinctive drop at -25 bps coinciding with the canonical TATA box position.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eMotifs with G-rich repeats in the transcriptome can form non-canonical four-stranded structures (G4s) implicated in transcriptional regulation, mRNA processing, the regulation of translation and RNA translocation [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. Similar to web-logo motif analyses of CAGE peaks from different mRNA regions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ea, \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003ef), the nucleotide enrichment plot of GGG sequences showed the highest enrichment overlapping 3'UTR CAGE peaks (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ec, \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003ef). This raises the possibility that the sequence around the 3\\u0026rsquo;UTR CAGE peaks may have an increased propensity to form RNA-G4 structures via the canonical G4 motif (G\\u003csub\\u003e3\\u003c/sub\\u003e-N\\u003csub\\u003e1\\u0026thinsp;\\u0026minus;\\u0026thinsp;7\\u003c/sub\\u003e-G\\u003csub\\u003e3\\u003c/sub\\u003e-N\\u003csub\\u003e1\\u0026thinsp;\\u0026minus;\\u0026thinsp;7\\u003c/sub\\u003e-G\\u003csub\\u003e3\\u003c/sub\\u003e-N\\u003csub\\u003e1\\u0026thinsp;\\u0026minus;\\u0026thinsp;7\\u003c/sub\\u003e-G\\u003csub\\u003e3\\u003c/sub\\u003e) [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. To further explore the RNA G-quadruplexes formation profile, we integrated RNA-G-quadruplex sequencing (rG4-seq) data from HeLa cells [\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e] and ran G4-Hunter predictions [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e] around CAGE peaks. Both the rG4-seq data (HeLa) and G4-Hunter predictions (K562) showed the highest G4s enrichment around CAGE peaks in the 3'UTR region (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003eh-l) with the highest percentage of rG4-seq hits within 3\\u0026rsquo;UTRs (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003em). Nevertheless, it is worth noting that the number of 3\\u0026rsquo;CAGE sites overlapping with rG4-seq sites was relatively small (~\\u0026thinsp;3800 out of ~\\u0026thinsp;133900). In sharp contrast, 8 of the 10 gene examples with 3\\u0026rsquo;UTR CAGE peaks and validated with long-read CAGE explored here (selected due to highest 3\\u0026rsquo;UTR CAGE signal) contained rG4-seq clusters coinciding with 3\\u0026rsquo;UTR CAGE peaks (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003en). It is important to note that the determination of whether these sites are genuinely in the G4-folded state remains uncertain, as the rG4-seq method employs G4 stabilisers to artificially enhance G4 structures.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3\\u0026rsquo;UTR CAGE sites are flanked by enriched UPF1 binding\\u003c/h2\\u003e \\u003cp\\u003eThe evidence outlined so far is consistent with our hypothesis that capped 3\\u0026rsquo;UTR-derived RNAs are formed post-transcriptionally. Next, we aimed to determine whether specific RNA-binding proteins (RBPs) were involved in the mechanism of their generation. To that end, we analysed publicly available enhanced CLIP (eCLIP) data for 80 different RBPs in the K562 cell line, produced by the ENCODE consortium [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. For each RBP, we calculated normalised cross-linking enrichment compared to other RBPs around maximum CAGE peaks per annotated gene region (5\\u0026rsquo;UTR, CDS, intron, 3\\u0026rsquo;UTR). This identified a specific set of RBPs around CAGE peaks, with UPF1 (Up-frameshift protein 1) as the top candidate in 3\\u0026rsquo;UTRs (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ec), DDX3X (DEAD-Box Helicase 3 X-Linked) in 5\\u0026rsquo;UTRs (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003en), KHSRP (KH-type splicing regulatory protein) in introns (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003eo), and less protein specific enrichments in CDS with YBX3 (Y-Box-Binding Protein 3) as the top candidate (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003eo,p). UPF1 is involved in a variety of RNA degradation pathways [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e], including Nonsense-Mediated Decay (NMD) [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e] and the normal mRNA decay where stalled UPF1 at CUG and GC-rich motifs activates decay [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. KHSRP plays a well-characterised role in pre-mRNA splicing, but has also been involved in several other aspects of RNA biology, such as mRNA decay and editing and maturation of miRNA precursors [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. On the other hand, the YBX3 has been implicated in regulation of mRNA translation as well as stability, likely in a transcript-dependent manner [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. As a positive control for our enrichment score approach, we noted DDX3X enrichment around 5\\u0026rsquo;UTR CAGE peaks. This is consistent with known roles for DDX3X in transcription and pre-mRNA splicing through interactions with transcription factors and Spliceosomal B Complexes [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eInterestingly, the crosslinking of UPF1 is enriched within 20 nt upstream of the 3\\u0026rsquo;UTR CAGE peaks, followed by a steep depletion within ~\\u0026thinsp;10 bps downstream (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ed). Additionally, a substantial correlation (R\\u0026thinsp;=\\u0026thinsp;0,654) was observed between the 3\\u0026rsquo;UTR CAGE signal and UPF1 binding, but not associated with gene expression or 3\\u0026rsquo;UTR length (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003eq). More specifically, the degree of UPF1 binding coincides with the intensity of the 3\\u0026rsquo;UTR CAGE peaks and proximity to the peaks (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003er, s). However, transfecting K562 cells with UPF1-targeting small interfering RNAs (siRNAs) for 48 hours did not lead to changes in the enrichment of RT-qPCR signal obtained with primers targeting downstream of the 3\\u0026rsquo;UTR CAGE peak in \\u003cem\\u003eCDKN1B\\u003c/em\\u003e or \\u003cem\\u003eJPT2\\u003c/em\\u003e when compared to upstream-targeting primers (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003et). Thus, it remains unclear if the precise binding position of UPF1 relative to the re-capping position may be important for the generation of the 3\\u0026rsquo;UTR capped fragments, or if accumulation of UPF1 is an indirect result of the presence of other factors that contribute to the cleavage.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003emRNA cleavage by small interfering RNAs generates newly capped RNA fragments\\u003c/h2\\u003e \\u003cp\\u003emRNAs can be cleaved post-transcriptionally through RNA interference (RNAi). Indeed, a common way to artificially accomplish gene silencing is to utilise siRNAs to induce endonucleolytic degradation of the target transcripts [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. SiRNAs are usually 21\\u0026ndash;23 nt long and their sequence is antisense to their mRNA target sequence. Silencing by siRNAs is induced through the endonuclease activity of Argonaute 2 (AGO2), a subunit of the RNA-induced gene-silencing complex (RISC) in the cytoplasm [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eWe hypothesised that siRNA silencing through AGO2 cleavage could lead to cytoplasmic capping of the cleaved RNA fragments instead of degradation. To test this hypothesis, we first investigated if CAGE-seq could detect cleaved RNA fragments guided by siRNA. We analysed CAGE data from siRNA-treated samples from the FANTOM5 dataset [\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e], which included samples from the TC-YIK human cell line transfected with siRNAs targeting mRNAs of 28 different transcription factors (20 siRNAs designed by ThermoFisher and 8 by the study authors) and 5 non-targeting control samples, in triplicates. We detected CAGE signal at the exact position targeted by the siRNA in at least two replicates in 20 out of the 28 samples (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ea). The strongest enrichment in CAGE signal relative to the siRNA target site was detected in the Islet-1 knockdown (\\u003cem\\u003eISL1\\u003c/em\\u003e-KD) samples, with no signal detected in control samples (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eb,c,\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ea). More interestingly, the dominant CAGE 5' end signal was present in the middle of the siRNA target sequence (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ee, \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ea), where the AGO2 cleavage is known to take place [\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e]. As expected, the TSS CAGE signal in the 5'UTR of the corresponding protein-coding gene dropped by ~\\u0026thinsp;75% compared to the control samples in all 3 replicates (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eb,c), confirming that the silencing of the \\u003cem\\u003eISL1\\u003c/em\\u003e transcript was efficient. Together these results indicate that siRNA-mediated recruitment of AGO2 can lead to the generation of post-transcriptionally capped RNA fragments following mRNA cleavage.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3'UTR CAGE peaks coincide with AGO2 and UPF1 binding sites alongside G-rich motifs\\u003c/h2\\u003e \\u003cp\\u003eSince the endonuclease activity of AGO2 facilitates mRNA cleavage guided by siRNAs, we investigated whether AGO2 binding also occurred at the endogenous 3'UTR CAGE peaks. There was no publicly available AGO2 binding data for either HeLa or K562 cells so we produced \\u0026lsquo;enhanced individual nucleotide resolution\\u0026rsquo;-CLIP (eiCLIP) [\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e] data for AGO2 (AGO2-eiCLIP) in HeLa cells. Our analysis revealed that 32.8% of the crosslinking positions mapped to the 3\\u0026rsquo;UTR region (Fig. \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003eb), with a higher binding enrichment in known microRNA (miRNA)-regulated transcripts, and with a clear miRNA-seed matching-sequence enrichment downstream of the crosslinking site (Fig. \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ec,d). Similarly to UPF1, AGO2 crosslinks were enriched immediately upstream from the 3'UTR CAGE peaks but, unlike UPF1, they were not depleted in the downstream region (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ed, \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ee, \\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ed).\\u003c/p\\u003e \\u003cp\\u003eIn animals, endogenous RNAi is mainly mediated by microRNAs (miRNAs). MiRNAs are ~\\u0026thinsp;21\\u0026ndash;23 nucleotide (nt) long RNAs that, in contrast to siRNAs, recruit the miRNA induced silencing complex (miRISC) containing AGO1-4 to mRNAs with partial sequence complementarity. As a result, miRNA action induces translational repression and/or exonucleolytic cleavage of the target mRNAs [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. Thus, miRNA-mediated degradation of target mRNAs in animals usually involves deadenylation, decapping, and degradation by the major cytoplasmic 5\\u0026rsquo;to-3\\u0026rsquo; exonucleases, rather than direct endonucleolytic cleavage by AGO2 [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. Nevertheless, it has been demonstrated that extensive miRNA-mRNA pairing can also trigger AGO2 catalytic activity [\\u003cspan additionalcitationids=\\\"CR51\\\" citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e]. We thus hypothesised that AGO2 miRNA-guided cleavage of mRNA targets might lead to the generation of recapping fragments in a similar manner to that observed for siRNAs. To test this we first identified genomic sequences with extensive complementarity (fewer than 2 mismatches) to human miRNAs. We identified 29 such targets that mapped within 3\\u0026rsquo;UTRs but there was no CAGE signal present around any of them (data not shown). In line with this, AGO2 crosslinking enrichment around 3\\u0026rsquo;UTR CAGE signals was considerably weaker for AGO2 binding sites overlapping with predicted miRNA binding sites (see Methods, Fig. \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ef). Intriguingly, CRISPR/Cas9-mediated elimination of AGO2 in K562 cells did not change the enrichment in RT-qPCR signal detected for \\u003cem\\u003eJPT2\\u003c/em\\u003e and \\u003cem\\u003eCDKN1B\\u003c/em\\u003e with primers downstream the 3\\u0026rsquo;CAGE \\u003cem\\u003eversus\\u003c/em\\u003e upstream primers (Fig \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003eg-i). All together, our observations suggest that AGO2 binds immediately upstream of the site of cleavage that generates 3\\u0026rsquo;UTR-derived RNAs independently of miRNA directed recruitment and that endogenous 3\\u0026rsquo;UTR-derived RNAs are not produced as a result of AGO2 cleavage activity.\\u003c/p\\u003e \\u003cp\\u003eAccordingly, we instead explored the binding specificity of AGO2-eiCLIP data, and performed a motif analysis using HOMER motif finder. When analysing the 15 bp flanking region around AGO2-crosslinking peaks (see Methods), one of the most prominent motifs was highly enriched in Gs (Fig. \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ej \\u0026minus;\\u0026thinsp;2nd and 3rd). Notably, this also agrees with one of the first AGO2-CLIP studies performed on mouse embryonic stem cells, where the authors showed that, without the miRNA present, AGO2 binds preferentially to G-rich motifs [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAs we had previously demonstrated that G-rich motifs, which have the capability to form RNA-G-quadruplexes, are enriched around 3\\u0026rsquo;UTR-derived RNAs, we next investigated whether AGO2 and UPF1 could be attracted to these specific G-rich motif structures independently of their location to CAGE peaks. We first aligned AGO2-eiCLIP and UPF1-eCLIP cross-linking positions relative to the 3' end of rG4-seq sites in different regions of primary transcripts. Both AGO2 and UPF1 crosslink-binding sites are much more highly enriched at rG4-seq sites in the 3\\u0026rsquo;UTRs relative to 5\\u0026rsquo;UTRs, introns and coding sequence although we noted that the binding of UPF1 occurred at the 3\\u0026rsquo;end of the G4-seq sites and AGO2 bound immediately upstream (Fig. \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ek-n). To further explore the relationship between AGO2 and UPF1 binding concerning 3\\u0026rsquo;UTR CAGE peaks and their association with G4-seq signals, we categorised the 3\\u0026rsquo;UTR CAGE peaks into four classes, depending on the presence or absence of these elements. We observed that the majority of 3\\u0026rsquo;UTR CAGE peaks contained both AGO2 and UPF1 binding but not G4-seq signal although, on the other hand, the majority of 3\\u0026rsquo;UTR CAGE sites overlapping with G4-seq also contained AGO2/UPF1 sites (Fig. \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003eo). Then we further explored the binding position of UPF1 and AGO2 relative to the 3'UTR CAGE peaks, in the presence or absence of the G4-seq site. Interestingly, both proteins exhibited a distinct shift in position influenced by the G4 motif enrichment; whilst AGO2 showed a pronounced shift to the upstream region of the 3\\u0026rsquo;UTR CAGE peak in the presence of G4-seq sites, UPF1 displayed a downstream shift (Fig. \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ep-q). An important next direction for future studies will be to experimentally investigate the mechanistic implications of the overlap between sites with the ability to form RNA-G4 structures and AGO2 and UPF1 binding for the generation of the capped 3\\u0026rsquo;UTR-derived RNAs.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCapped 3\\u0026rsquo;UTR fragments of CDKN1B and JPT2 transcripts do not co-localise with the parental mRNAs\\u003c/h2\\u003e \\u003cp\\u003eFinally, we examined the potential implications of 3\\u0026rsquo;UTR-derived RNAs. Specifically, we sought to understand how 3\\u0026rsquo;UTR-derived RNAs might localise either together or independently from the parental mRNAs. To test this, we designed smFISH (single molecule fluorescence in situ hybridization) probes to simultaneously image the RNA upstream and downstream of the proposed post-transcriptional cleavage and capping site in CDKN1B and JPT2 using hybridisation chain reaction RNA-fluorescence in situ hybridization (HCR-FISH 3.0) [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e]. To account for technical biases in detection, we also designed probes against the coding sequence (hereafter upstream) and 3\\u0026rsquo;UTR (hereafter downstream) of a control mRNA, PGAM1, which does not contain CAGE peaks in the 3\\u0026rsquo;UTR and contained a similar 3\\u0026rsquo;UTR length to our targets.\\u003c/p\\u003e \\u003cp\\u003eWe performed HCR-FISH in HeLa cells to determine whether putative 3\\u0026rsquo;UTR-derived RNAs can be found independently of the RNA upstream of the cleavage site (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ea, b). In the control transcript, PGAM1, we observed that 17.3% of upstream signals did not have a colocalising downstream signal and 21.3% of downstream signals did not have a colocalising upstream signal (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ec, \\u003cspan refid=\\\"Fig8\\\" class=\\\"InternalRef\\\"\\u003eS4\\u003c/span\\u003ea). However, the mRNAs that contain a 3\\u0026rsquo;UTR CAGE signature were significantly more likely to show independent signals from the RNA downstream of the proposed cleavage site (CDKN1B: 53.3%, p adj. \\u0026lt; 0.05; JPT2: 52.3%, p adj. \\u0026lt; 0.05; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ec). In the case of JPT2, we also observed significantly more independent signals from the upstream probes (29.3%, p adj. \\u0026lt; 0.05; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ec). These observations are consistent with the existence of cleaved 3\\u0026rsquo;UTR fragments in the cell, and they reveal that these products may localise differently from their host transcripts.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003ePrevious studies had identified 3\\u0026rsquo;UTR-derived RNAs \\u003cem\\u003evia\\u003c/em\\u003e enrichment of RNA-seq reads-starts or CAGE signals mapping at 3\\u0026rsquo;UTRs [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. Nevertheless, most 3\\u0026rsquo;UTR-derived RNAs may have remained undetected until now due to technical limitations inherent to these approaches, including reliance on fragmented-based sequencing methods and potentially biassed library preparations. Here, we provide multiple lines of evidence that complement CAGE and RNA-seq data, including RNA structural features, RBP interactions around 3\\u0026rsquo;UTR CAGE signals and long-read nanopore CAGE to validate the widespread presence of capped 3\\u0026rsquo;UTR-derived RNAs in human cells. We show that capped 3\\u0026rsquo;UTR-derived RNAs are generated post-transcriptionally at positions characterised by the presence of G-rich motifs and specific RBP binding sites. We also demonstrate that, consistent with a functional role, capped 3\\u0026rsquo;UTR-derived RNA sequences are evolutionary conserved and can localise to different subcellular regions than the parental mRNAs.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eThe role of AGO2, UPF1 and G-rich motifs in the generation of 3'UTR-derived capped RNAs\\u003c/h2\\u003e \\u003cp\\u003eOne of the key findings of our work is that siRNA action can result in the generation of capped RNAs downstream of the cleavage site (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ea,c, \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ea). However, with the available data we could not quantify the efficiency of such capping, or identify all the factors that might be involved in the process. It is well established that AGO2 cleaves the double stranded RNA formed by the reverse complementary binding of siRNAs to their target mRNAs in the cytosol, pointing to a model in which AGO2 cleavage products can be recapped. The strong enrichment of AGO2 to a region with a modest increase in sequence conservation (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003ed) immediately upstream of the endogenous 3\\u0026rsquo;UTR CAGE peaks (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ed) suggested that AGO2 also plays a role in the generation of endogenous capped 3\\u0026rsquo;UTR-derived RNAs.\\u003c/p\\u003e \\u003cp\\u003eEndogenous RNA interference in mammalian cells is mainly mediated by miRNAs. MiRNAs drive AGO2 to their targets through partial complementarity only and thus, in contrast to siRNAs, do not trigger AGO2 catalytic activity [\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e]. On the contrary, miRNA action in mammals relies mostly on translational repression and/or exonucleolytic degradation of their targets through the recruitment of other protein partners [\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e]. This raises two interesting possibilities: (1) that the mechanism by which AGO2 is involved in the generation of endogenous 3\\u0026rsquo;UTR-derived capped RNAs is different to its role in the generation of capped fragments following siRNA action. In this scenario, AGO2 role will likely be independent of its catalytic activity and possibly require the recruitment of other nucleases, or (2) that AGO2 endonucleolytic activity is also important for the generation of endogenous 3\\u0026rsquo;UTR-derived capped RNAs and therefore likely independent of its role in miRNA-mediated silencing of gene expression. The latter model is supported by the finding of a stronger enrichment in AGO2 binding in 3\\u0026rsquo;UTR CAGE peaks in the absence of miRNA binding sites (Fig. \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003ef). We also failed to observe CAGE peaks in the vicinity of 29 mRNA targets whose genomics sequences contained miRNA target sites of extensive (\\u0026lt;\\u0026thinsp;2 mismatches) complementarity to known miRNAs. Interestingly, we found that AGO2 binds to potential RNA-G4s in 3\\u0026rsquo;UTR CAGE sites (Fig. \\u003cspan refid=\\\"MOESM3\\\" class=\\\"InternalRef\\\"\\u003eS3\\u003c/span\\u003eh-i). Early AGO2-CLIP experiments had already identified an enrichment of a G-rich motif in sequences cross-linked to AGO2 likely in a miRNA-independent manner [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e]. AGO2 binding sites neighbouring G-rich sequences may be less likely to be guided by miRNAs, as RNA-G4s can prevent miRNA binding from their target sites [\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e]. Thus, our analysis suggests that the role of AGO2 in the generation of capped 3\\u0026rsquo;UTR-derived RNAs is independent of its role in miRNA-mediated gene silencing. This is in agreement with previous findings by Andreassi et al. [\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e]. Moreover, elimination of AGO2 did not affect the enrichment of \\u003cem\\u003eJPT2\\u003c/em\\u003e and \\u003cem\\u003eCDKN1B\\u003c/em\\u003e RT-qPCR signals corresponding to 3\\u0026rsquo;UTR-derived RNAs (S3i) further arguing against a direct role of AGO2 catalytic activity in the generation of these species. In the future, long-read CAGE analysis in models of AGO2 loss of function, possibly in conjunction with the elimination of other AGO proteins (1, 3\\u0026ndash;4) present in the cells, may help clarify the specific role of AGO2 in the global generation of capped 3\\u0026rsquo;UTR-derived RNAs.\\u003c/p\\u003e \\u003cp\\u003eOur work identified UPF1 as the RBP with the strongest binding enrichment around 3\\u0026rsquo;UTR CAGE peaks and uncovered an overlapping of AGO2, UPF1 and G-rich sequences in 3\\u0026rsquo;UTR CAGE sites. Interestingly, a significant overlap between UPF1 and AGO2 binding sites as well as preferential UPF1 binding to structured G-rich regions had been previously reported [\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e]. Whilst it is well-established that UPF1 plays an essential role in mRNA degradation [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e] and binds to GC-rich motifs in 3\\u0026rsquo;UTRs [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e], the main trigger of UPF1-mediated mRNA decay remains unknown. It has been suggested that G-enrichment in 3\\u0026rsquo;UTRs plays a vital role in triggering UPF1-mediated mRNA decay [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. It was therefore tempting to hypothesise a causal role for UPF1 in the generation of 3\\u0026rsquo;UTR-derived RNAs in connection with its role in mRNA decay [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. Nevertheless, arguing against this possibility, siRNA-mediated downregulation of UPF1 did not change the relative amount of \\u003cem\\u003eCDKN1B\\u003c/em\\u003e and \\u003cem\\u003eJPT2\\u003c/em\\u003e mRNA detected with primers targeting downstream \\u003cem\\u003eversus\\u003c/em\\u003e upstream of the 3\\u0026rsquo;CAGE peaks (Fig. \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003et). Additional experimental data will be needed to reach a more definitive conclusion, but it is is also likely that the presence of RNA-G4 sequences (or strong secondary structures) around 3\\u0026rsquo;UTR CAGE causes the stalling of UPF1 as the helicase translocates in a 5\\u0026rsquo;-3\\u0026rsquo; direction [\\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eOur analysis also shows that the G-rich sequences around 3\\u0026rsquo;UTR CAGE peaks have a strong pairing probability and thus have the potential to form G4 structures (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eb, \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003eg-l). Nevertheless, although RNA-G4s are known to form stable structures \\u003cem\\u003ein vitro\\u003c/em\\u003e, recent studies have suggested that they may be less stable \\u003cem\\u003ein vivo\\u003c/em\\u003e due to active unwinding by RNA helicases [\\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e]. However, Kharel et al. (2022) [\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e] demonstrated that 3\\u0026rsquo;UTR-G4s are dynamically regulated under cellular stress conditions and may play a role in mRNA stability for several transcripts, including the 3\\u0026rsquo;UTR-G4 in the amyloid precursor protein (\\u003cem\\u003eAPP\\u003c/em\\u003e) mRNA. The G4 motif in the 3\\u0026rsquo;UTR of \\u003cem\\u003eAPP\\u003c/em\\u003e mRNA was found to suppress overproduction of APP protein, but the underlying mechanism remained unclear [\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e]. Analysis of rG4-seq and CAGE data from HeLa cells showed that the 3\\u0026rsquo; end of this G4 motif in \\u003cem\\u003eAPP\\u003c/em\\u003e 3\\u0026rsquo;UTR precisely coincided with a 3\\u0026rsquo;UTR CAGE signal (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003en - APP, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003el). Moreover, long-read sequencing CAGE from cortical neuron samples, confirmed that abundant 3\\u0026rsquo;UTR-derived capped RNAs are present in these samples that span from the identified 3\\u0026rsquo;UTR CAGE peak to the end of the annotated \\u003cem\\u003eAPP\\u003c/em\\u003e gene (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003en - APP). This raises the possibility that the RNA-G4 regulates APP protein through an unknown mechanism that involves the generation of 3\\u0026rsquo;UTR-derived capped RNAs.\\u003c/p\\u003e \\u003cp\\u003eFuture studies will focus on investigating whether these G-rich sequences form stable G4 structures in other genes and whether they directly contribute to the formation of 3\\u0026rsquo;UTR-derived RNAs. Another important open question that warrants further investigation is whether these G-rich motifs are essential for the recruitment of AGO2 and/or other proteins responsible for the generation of endogenous 3\\u0026rsquo;UTR-derived RNAs.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eIndependent localisation of capped 3\\u0026rsquo;UTR fragments from the parental mRNAs\\u003c/b\\u003e.\\u003c/p\\u003e \\u003cp\\u003eCAGE-seq, RNA-seq, RT-qPCR and long-read CAGE experiments suggested that 3'UTR-derived RNAs in \\u003cem\\u003eCDKN1B\\u003c/em\\u003e and \\u003cem\\u003eJPT2\\u003c/em\\u003e are capped and highly expressed in cells. In line with these experiments, HCR-FISH showed that RNAs derived from \\u003cem\\u003eCDKN1B\\u003c/em\\u003e and \\u003cem\\u003eJPT2\\u003c/em\\u003e 3\\u0026rsquo;UTRs can be detected at separate cytosolic locations than their parental mRNAs. In agreement with the CAGE data, higher ratio of downstream vs. upstream probes is present in \\u003cem\\u003eCDKN1B\\u003c/em\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ea-c, \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003en - CDKN1B).\\u003c/p\\u003e \\u003cp\\u003eInterestingly, some cells exhibited a pronounced perinuclear accumulation of 3\\u0026rsquo;UTR-probes in \\u003cem\\u003eCDKN1B\\u003c/em\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003ea), whereas for the majority of the cells, the signal was dispersed throughout the cytosol. An intriguing possibility is a potential cell cycle-dependence, as observed in other aspects of \\u003cem\\u003eCDKN1B\\u003c/em\\u003e gene expression regulation, such as mRNA translation [\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e]. It has been previously shown that defective \\u003cem\\u003eCDKN1\\u003c/em\\u003e splicing can be rectified to restore CDKN1B/p27\\u003csup\\u003ekip\\u003c/sup\\u003e protein production and induce cell cycle arrest [\\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e]. Likewise, the capped 3\\u0026rsquo;UTR fragments of \\u003cem\\u003eCDKN1B\\u003c/em\\u003e mRNA could regulate p27\\u003csup\\u003ekip\\u003c/sup\\u003e protein in a cell cycle-specific manner, albeit this possibility remains to be investigated. Of note, a separate study proposed a cell-cycle function for 3\\u0026rsquo;UTR fragments of \\u003cem\\u003eNURR1\\u003c/em\\u003e (nuclear receptor related 1 protein) mRNA which were highly expressed in proliferating neuronal cells [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Exploring the dynamic nature of these capped 3\\u0026rsquo;UTR fragments and their potential influence on cellular functions in a manner dependent on the cell cycle remains an important area for further investigation.\\u003c/p\\u003e \\u003cp\\u003eThe different localisation of the 3\\u0026rsquo;UTR-derived fragments to their full-length counterparts raises more questions on the fate and function of these RNAs. It is worth mentioning that analysis of ribosome footprinting data [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e] (not-shown) failed to reveal any substantial ribosomal binding to capped 3\\u0026rsquo;UTR-derived RNAs. This argues against their translation and supports a role similar to other cytosolic lncRNAs [\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e], as previously observed by others for specific 3\\u0026rsquo;UTR-derived RNAs [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e]. Nevertheless, the binding of the translation initiation factor eIF4E to these RNAs seems paradoxical. Moreover, these findings are in sharp contrast with those by Sudmant et al. who found evidence for ribosomal binding and for the existence of peptides encoded by comparable isolated 3\\u0026rsquo;UTR fragments in human brain samples[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e]. It is important to acknowledge that the coverage of ribo-footprinting in 3\\u0026rsquo;UTRs is limited and it therefore can\\u0026rsquo;t fully rule out that some of the capped, eIF4E-bound, 3\\u0026rsquo;UTR-derived RNAs identified in our study are translated. This will require further investigation, possibly in a gene- and tissue-dependent manner.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eMethodological implications\\u003c/h2\\u003e \\u003cp\\u003eDifferent abundance and localisation of 3\\u0026rsquo;UTR derived RNAs relative to their parental transcripts and the 5\\u0026rsquo; cleavage fragment containing protein coding sequence suggests that 3\\u0026rsquo;UTR fragmented-based sequencing methods might be measuring the wrong RNA species in a significant proportion of cases. Even in the case of RNA-seq, quantitating the signal across the entire length of the uncleaved mRNA might measure a combination of protein-coding and non-coding RNA species. To increase the accuracy of quantitation of protein coding transcript levels, as well as those of 3\\u0026rsquo;UTR-derived RNAs themselves, it may be necessary to develop new computational quantitation methods informed by the results of this paper, which will try to estimate the levels of protein-coding and 3\\u0026rsquo;UTR fragments separately. Moreover, many new drugs which are based on siRNA targeting are already in use or under active clinical trials for treating a variety of conditions including neurological diseases [\\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e70\\u003c/span\\u003e]. Side cleavage products of the targeted mRNAs from these therapeutic drugs could be subjected to a cytoplasmic capping mechanism and result in unwanted toxic side effects.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eLimitations\\u003c/h2\\u003e \\u003cp\\u003eAt the moment we do not have the ability to identify the full-length size of 3'UTR-derived RNAs in a high-throughput manner since the main technique that we used (CAGE-seq) is based on 5\\u0026rsquo; end sequencing. Also, CAGE-seq method has a limitation on fragment size similar to other HT-sequencing methods with a minimum fragment size of 200 bps. This can be overcome with the long-read CAGE (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003en), but the whole data is not yet publicly available. Using only experimental datasets has limitations in coverage, organisms, cell lines and can increase the number of false positives as a result of background noise. It is for example important to note that we have limited our study to RBPs with eCLIP available, which may have prevented the identification of other important proteins involved in the cleavage and/or re-capping of 3\\u0026rsquo;UTR mRNA fragments.\\u003c/p\\u003e \\u003cp\\u003eThis study is limited to human samples and, even though the sequence conservation suggests that capped 3'UTR-derived fragments may be conserved, this will need further experimental validation. New computational methods will need to be developed for these studies which are currently limited by the availability of such large datasets.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003e3'UTR-derived RNAs are emerging as novel regulatory molecules, with potential implications in broad cellular processes such as cell cycle or neuronal homeostasis [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e]. However, the molecular mechanisms involved in the generation of these RNA species had been largely unknown. Our study sheds new light into these mechanisms by revealing that capped 3'UTR-derived RNAs originate from sequences rich in G motifs that contain both UPF1 and AGO2 binding sites. These findings suggest a significant role for these elements in the regulatory mechanism. Overall, our findings provide the framework for further investigations where their functions will surely emerge.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was funded in part by The Wellcome Trust grants (106954/Z/15/Z) awarded to B.L., by the Medical Research Council (MRC) (MR/P023223/1 and MR/X009912/1) to A.M-S, MRC (grant number MC_UP_1102/18) to S.V, and by (215593/Z/19/Z) to J.U., Medical Research Council (MRC) Core Funding (MC-A652-5QA10), by the Imperial College Research Fellowship awarded to N.H., and by the Francis Crick Institute which receives its core funding from Cancer Research UK (CC0102), the UK Medical Research Council (CC0102), and the Wellcome Trust (CC0102), and by an institutional budget from RIKEN, MEXT (Ministry of Education, Culture, Sports, Science and Technology) and from institutional budget from the Human Technopole. We thank the Crick Advanced Light Microscopy facility, especially Donald Bell, for their support. We thank Sarvesh Nikumbh for help with the CAGEr tool and other members of Lenhard\\u0026apos;s group for helpful discussions and comments on the manuscript. We thank Ira Iosub for processing the ribosome footprinting data. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eN.H. and B.L. conceived the study. N.H. designed the experiments, analysed the data, and led the project. R.C. and A.M-S. performed and designed qPCR experiments. AGO2-eiCLIP was designed and performed by C.R.S and A.M-S. R.F. and H.D. designed and performed smFISH probe imaging supervised by J.U. Long-read CAGE examples were produced, processed and provided by C.P., K.Y., T.K., C.W.Y., M.K., H.T., P.C., and visualised by A.M.C. N.H. and A.M-S. wrote the manuscript, with contributions from A.M.C., R.F., H.D., A.M.J, S.V., C.R.S., J.U. and B.L.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDeclaration of interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eRamanathan, A., Robb, G.B., and Chan, S.-H. (2016). mRNA capping: biological functions and applications. Nucleic Acids Res. \\u003cem\\u003e44\\u003c/em\\u003e, 7511\\u0026ndash;7526.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eOtsuka, Y., Kedersha, N.L., and Schoenberg, D.R. (2009). Identification of a cytoplasmic complex that adds a cap onto 5\\u0026rsquo;-monophosphate RNA. Mol. Cell. Biol. \\u003cem\\u003e29\\u003c/em\\u003e, 2155\\u0026ndash;2167.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMukherjee, C., Bakthavachalu, B., and Schoenberg, D.R. (2014). The cytoplasmic capping complex assembles on adapter protein nck1 bound to the proline-rich C-terminus of Mammalian capping enzyme. PLoS Biol. \\u003cem\\u003e12\\u003c/em\\u003e, e1001933.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHestand, M.S., Klingenhoff, A., Scherf, M., Ariyurek, Y., Ramos, Y., van Workum, W., Suzuki, M., Werner, T., van Ommen, G.-J.B., den Dunnen, J.T., \\u003cem\\u003eet al.\\u003c/em\\u003e (2010). Tissue-specific transcript annotation and expression profiling with complementary next-generation sequencing technologies. Nucleic Acids Res. \\u003cem\\u003e38\\u003c/em\\u003e, e165.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNaeli, P., Winter, T., Hackett, A.P., Alboushi, L., and Jafarnejad, S.M. (2023). The intricate balance between microRNA-induced mRNA decay and translational repression. FEBS J. \\u003cem\\u003e290\\u003c/em\\u003e, 2508\\u0026ndash;2524.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMurata, M., Nishiyori-Sueki, H., Kojima-Ishiyama, M., Carninci, P., Hayashizaki, Y., and Itoh, M. (2014). Detecting expressed genes using CAGE. Methods Mol. Biol. \\u003cem\\u003e1164\\u003c/em\\u003e, 67\\u0026ndash;85.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKocabas, A., Duarte, T., Kumar, S., and Hynes, M.A. (2015). Widespread differential expression of coding region and 3\\u0026rsquo; UTR sequences in neurons and other tissues. Neuron \\u003cem\\u003e88\\u003c/em\\u003e, 1149\\u0026ndash;1156.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMalka, Y., Steiman-Shimony, A., Rosenthal, E., Argaman, L., Cohen-Daniel, L., Arbib, E., Margalit, H., Kaplan, T., and Berger, M. (2017). Post-transcriptional 3\\u0026acute;-UTR cleavage of mRNA transcripts generates thousands of stable uncapped autonomous RNA fragments. Nat. Commun. \\u003cem\\u003e8\\u003c/em\\u003e, 2029.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMercer, T.R., Dinger, M.E., Bracken, C.P., Kolle, G., Szubert, J.M., Korbie, D.J., Askarian-Amiri, M.E., Gardiner, B.B., Goodall, G.J., Grimmond, S.M., \\u003cem\\u003eet al.\\u003c/em\\u003e (2010). Regulated post-transcriptional RNA cleavage diversifies the eukaryotic transcriptome. Genome Res. \\u003cem\\u003e20\\u003c/em\\u003e, 1639\\u0026ndash;1650.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAffymetrix ENCODE Transcriptome Project, and Cold Spring Harbor Laboratory ENCODE Transcriptome Project (2009). Post-transcriptional processing generates a diversity of 5\\u0026rsquo;-modified long and short RNAs. Nature \\u003cem\\u003e457\\u003c/em\\u003e, 1028\\u0026ndash;1032.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAdiconis, X., Haber, A.L., Simmons, S.K., Levy Moonshine, A., Ji, Z., Busby, M.A., Shi, X., Jacques, J., Lancaster, M.A., Pan, J.Q., \\u003cem\\u003eet al.\\u003c/em\\u003e (2018). Comprehensive comparative analysis of 5\\u0026rsquo;-end RNA-sequencing methods. Nat. Methods \\u003cem\\u003e15\\u003c/em\\u003e, 505\\u0026ndash;511.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCarninci, P., Kasukawa, T., Katayama, S., Gough, J., Frith, M.C., Maeda, N., Oyama, R., Ravasi, T., Lenhard, B., Wells, C., \\u003cem\\u003eet al.\\u003c/em\\u003e (2005). The transcriptional landscape of the mammalian genome. Science \\u003cem\\u003e309\\u003c/em\\u003e, 1559\\u0026ndash;1563.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCarninci, P., Sandelin, A., Lenhard, B., Katayama, S., Shimokawa, K., Ponjavic, J., Semple, C.A.M., Taylor, M.S., Engstr\\u0026ouml;m, P.G., Frith, M.C., \\u003cem\\u003eet al.\\u003c/em\\u003e (2006). Genome-wide analysis of mammalian promoter architecture and evolution. Nat. Genet. \\u003cem\\u003e38\\u003c/em\\u003e, 626\\u0026ndash;635.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKiss, D.L., Oman, K., Bundschuh, R., and Schoenberg, D.R. (2015). Uncapped 5\\u0026rsquo; ends of mRNAs targeted by cytoplasmic capping map to the vicinity of downstream CAGE tags. FEBS Lett. \\u003cem\\u003e589\\u003c/em\\u003e, 279\\u0026ndash;284.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBerger, M.R., Alvarado, R., and Kiss, D.L. (2019). mRNA 5\\u0026rsquo; ends targeted by cytoplasmic recapping cluster at CAGE tags and select transcripts are alternatively spliced. FEBS Lett. \\u003cem\\u003e593\\u003c/em\\u003e, 670\\u0026ndash;679.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMercer, T.R., Wilhelm, D., Dinger, M.E., Sold\\u0026agrave;, G., Korbie, D.J., Glazov, E.A., Truong, V., Schwenke, M., Simons, C., Matthaei, K.I., \\u003cem\\u003eet al.\\u003c/em\\u003e (2011). Expression of distinct RNAs from 3\\u0026rsquo; untranslated regions. Nucleic Acids Res. \\u003cem\\u003e39\\u003c/em\\u003e, 2393\\u0026ndash;2403.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJi, S., Yang, Z., Gozali, L., Kenney, T., Kocabas, A., Jinsook Park, C., and Hynes, M. (2021). Distinct expression of select and transcriptome-wide isolated 3\\u0026rsquo;UTRs suggests critical roles in development and transition states. PLoS ONE \\u003cem\\u003e16\\u003c/em\\u003e, e0250669.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSudmant, P.H., Lee, H., Dominguez, D., Heiman, M., and Burge, C.B. (2018). Widespread Accumulation of Ribosome-Associated Isolated 3\\u0026rsquo; UTRs in Neuronal Cell Populations of the Aging Brain. Cell Rep. \\u003cem\\u003e25\\u003c/em\\u003e, 2447\\u0026ndash;2456.e4.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTakahashi, H., Lassmann, T., Murata, M., and Carninci, P. (2012). 5\\u0026rsquo; end-centered expression profiling using cap-analysis gene expression and next-generation sequencing. Nat. Protoc. \\u003cem\\u003e7\\u003c/em\\u003e, 542\\u0026ndash;561.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDjebali, S., Davis, C.A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., Tanzer, A., Lagarde, J., Lin, W., Schlesinger, F., \\u003cem\\u003eet al.\\u003c/em\\u003e (2012). Landscape of transcription in human cells. Nature \\u003cem\\u003e489\\u003c/em\\u003e, 101\\u0026ndash;108.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKanamori-Katayama, M., Itoh, M., Kawaji, H., Lassmann, T., Katayama, S., Kojima, M., Bertin, N., Kaiho, A., Ninomiya, N., Daub, C.O., \\u003cem\\u003eet al.\\u003c/em\\u003e (2011). Unamplified cap analysis of gene expression on a single-molecule sequencer. Genome Res. \\u003cem\\u003e21\\u003c/em\\u003e, 1150\\u0026ndash;1159.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFrith, M.C., Valen, E., Krogh, A., Hayashizaki, Y., Carninci, P., and Sandelin, A. (2008). A code for transcription initiation in mammalian genomes. Genome Res. \\u003cem\\u003e18\\u003c/em\\u003e, 1\\u0026ndash;12.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGiacometti, S., Benbahouche, N.E.H., Domanski, M., Robert, M.-C., Meola, N., Lubas, M., Bukenborg, J., Andersen, J.S., Schulze, W.M., Verheggen, C., \\u003cem\\u003eet al.\\u003c/em\\u003e (2017). Mutually Exclusive CBC-Containing Complexes Contribute to RNA Fate. Cell Rep. \\u003cem\\u003e18\\u003c/em\\u003e, 2635\\u0026ndash;2650.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eIzaurralde, E., Lewis, J., McGuigan, C., Jankowska, M., Darzynkiewicz, E., and Mattaj, I.W. (1994). A nuclear cap binding protein complex involved in pre-mRNA splicing. Cell \\u003cem\\u003e78\\u003c/em\\u003e, 657\\u0026ndash;668.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSchoenberg, D.R., and Maquat, L.E. (2009). Re-capping the message. Trends Biochem. Sci. \\u003cem\\u003e34\\u003c/em\\u003e, 435\\u0026ndash;442.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCore, L.J., Martins, A.L., Danko, C.G., Waters, C.T., Siepel, A., and Lis, J.T. (2014). Analysis of nascent RNA identifies a unified architecture of initiation regions at mammalian promoters and enhancers. Nat. Genet. \\u003cem\\u003e46\\u003c/em\\u003e, 1311\\u0026ndash;1320.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJensen, K.B., Dredge, B.K., Toubia, J., Jin, X., Iadevaia, V., Goodall, G.J., and Proud, C.G. (2021). capCLIP: a new tool to probe translational control in human cells through capture and identification of the eIF4E-mRNA interactome. Nucleic Acids Res. \\u003cem\\u003e49\\u003c/em\\u003e, e105.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRhoads, R.E. (2009). eIF4E: new family members, new binding partners, new roles. J. Biol. Chem. \\u003cem\\u003e284\\u003c/em\\u003e, 16711\\u0026ndash;16715.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFerguson, L., Upton, H.E., Pimentel, S.C., Mok, A., Lareau, L.F., Collins, K., and Ingolia, N.T. (2023). Streamlined and sensitive mono- and di-ribosome profiling in yeast and human cells. Nat. Methods \\u003cem\\u003e20\\u003c/em\\u003e, 1704\\u0026ndash;1715.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhang, L., Kasif, S., Cantor, C.R., and Broude, N.E. (2004). GC/AT-content spikes as genomic punctuation marks. Proc Natl Acad Sci USA \\u003cem\\u003e101\\u003c/em\\u003e, 16855\\u0026ndash;16860.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKharel, P., Becker, G., Tsvetkov, V., and Ivanov, P. (2020). Properties and biological impact of RNA G-quadruplexes: from order to turmoil and back. Nucleic Acids Res. \\u003cem\\u003e48\\u003c/em\\u003e, 12534\\u0026ndash;12555.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee, D.S.M., Ghanem, L.R., and Barash, Y. (2020). Integrative analysis reveals RNA G-quadruplexes in UTRs are selectively constrained and enriched for functional associations. Nat. Commun. \\u003cem\\u003e11\\u003c/em\\u003e, 527.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKwok, C.K., Marsico, G., Sahakyan, A.B., Chambers, V.S., and Balasubramanian, S. (2016). rG4-seq reveals widespread formation of G-quadruplex structures in the human transcriptome. Nat. Methods \\u003cem\\u003e13\\u003c/em\\u003e, 841\\u0026ndash;844.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBedrat, A., Lacroix, L., and Mergny, J.-L. (2016). Re-evaluation of G-quadruplex propensity with G4Hunter. Nucleic Acids Res. \\u003cem\\u003e44\\u003c/em\\u003e, 1746\\u0026ndash;1759.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVan Nostrand, E.L., Freese, P., Pratt, G.A., Wang, X., Wei, X., Xiao, R., Blue, S.M., Chen, J.-Y., Cody, N.A.L., Dominguez, D., \\u003cem\\u003eet al.\\u003c/em\\u003e (2020). A large-scale binding and functional map of human RNA-binding proteins. Nature \\u003cem\\u003e583\\u003c/em\\u003e, 711\\u0026ndash;719.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eStaszewski, J., Lazarewicz, N., Konczak, J., Migdal, I., and Maciaszczyk-Dziubinska, E. (2023). UPF1-From mRNA Degradation to Human Disorders. Cells \\u003cem\\u003e12\\u003c/em\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKurosaki, T., Li, W., Hoque, M., Popp, M.W.-L., Ermolenko, D.N., Tian, B., and Maquat, L.E. (2014). A post-translational regulatory switch on UPF1 controls targeted mRNA degradation. Genes Dev. \\u003cem\\u003e28\\u003c/em\\u003e, 1900\\u0026ndash;1916.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eImamachi, N., Salam, K.A., Suzuki, Y., and Akimitsu, N. (2017). A GC-rich sequence feature in the 3\\u0026rsquo; UTR directs UPF1-dependent mRNA decay in mammalian cells. Genome Res. \\u003cem\\u003e27\\u003c/em\\u003e, 407\\u0026ndash;418.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGherzi, R., Chen, C.-Y., Ramos, A., and Briata, P. (2014). KSRP controls pleiotropic cellular functions. Semin. Cell Dev. Biol. \\u003cem\\u003e34\\u003c/em\\u003e, 2\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCooke, A., Schwarzl, T., Huppertz, I., Kramer, G., Mantas, P., Alleaume, A.-M., Huber, W., Krijgsveld, J., and Hentze, M.W. (2019). The RNA-Binding Protein YBX3 Controls Amino Acid Levels by Regulating SLC mRNA Abundance. Cell Rep. \\u003cem\\u003e27\\u003c/em\\u003e, 3097\\u0026ndash;3106.e5.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMo, J., Liang, H., Su, C., Li, P., Chen, J., and Zhang, B. (2021). DDX3X: structure, physiologic functions and cancer. Mol. Cancer \\u003cem\\u003e20\\u003c/em\\u003e, 38.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCarthew, R.W., and Sontheimer, E.J. (2009). Origins and Mechanisms of miRNAs and siRNAs. Cell \\u003cem\\u003e136\\u003c/em\\u003e, 642\\u0026ndash;655.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBartel, D.P. (2018). Metazoan MicroRNAs. Cell \\u003cem\\u003e173\\u003c/em\\u003e, 20\\u0026ndash;51.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLam, J.K.W., Chow, M.Y.T., Zhang, Y., and Leung, S.W.S. (2015). siRNA Versus miRNA as Therapeutics for Gene Silencing. Mol. Ther. Nucleic Acids \\u003cem\\u003e4\\u003c/em\\u003e, e252.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLizio, M., Ishizu, Y., Itoh, M., Lassmann, T., Hasegawa, A., Kubosaki, A., Severin, J., Kawaji, H., Nakamura, Y., FANTOM consortium, \\u003cem\\u003eet al.\\u003c/em\\u003e (2015). Mapping Mammalian Cell-type-specific Transcriptional Regulatory Networks Using KD-CAGE and ChIP-seq Data in the TC-YIK Cell Line. Front. Genet. \\u003cem\\u003e6\\u003c/em\\u003e, 331.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eElbashir, S.M., Lendeckel, W., and Tuschl, T. (2001). RNA interference is mediated by 21- and 22-nucleotide RNAs. Genes Dev. \\u003cem\\u003e15\\u003c/em\\u003e, 188\\u0026ndash;200.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLin, J., Xu, K., Roth, J.A., and Ji, L. (2016). Detection of siRNA-mediated target mRNA cleavage activities in human cells by a novel stem-loop array RT-PCR analysis. Biochem. Biophys. Rep. \\u003cem\\u003e6\\u003c/em\\u003e, 16\\u0026ndash;23.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePaterson, H.A.B., Yu, S., Artigas, N., Prado, M.A., Haberman, N., Wang, Y.-F., Jobbins, A.M., Pahita, E., Mokochinski, J., Hall, Z., \\u003cem\\u003eet al.\\u003c/em\\u003e (2022). Liver RBFOX2 regulates cholesterol homeostasis via Scarb1 alternative splicing in mice. Nat. Metab. \\u003cem\\u003e4\\u003c/em\\u003e, 1812\\u0026ndash;1829.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNishihara, T., Zekri, L., Braun, J.E., and Izaurralde, E. (2013). miRISC recruits decapping factors to miRNA targets to enhance their degradation. Nucleic Acids Res. \\u003cem\\u003e41\\u003c/em\\u003e, 8692\\u0026ndash;8705.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJung, E., Seong, Y., Jeon, B., Song, H., and Kwon, Y.-S. (2017). Global analysis of AGO2-bound RNAs reveals that miRNAs induce cleavage of target RNAs with limited complementarity. Biochim. Biophys. Acta Gene Regul. Mech. \\u003cem\\u003e1860\\u003c/em\\u003e, 1148\\u0026ndash;1158.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBracken, C.P., Szubert, J.M., Mercer, T.R., Dinger, M.E., Thomson, D.W., Mattick, J.S., Michael, M.Z., and Goodall, G.J. (2011). Global analysis of the mammalian RNA degradome reveals widespread miRNA-dependent and miRNA-independent endonucleolytic cleavage. Nucleic Acids Res. \\u003cem\\u003e39\\u003c/em\\u003e, 5658\\u0026ndash;5668.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKarginov, F.V., Cheloufi, S., Chong, M.M.W., Stark, A., Smith, A.D., and Hannon, G.J. (2010). Diverse endonucleolytic cleavage sites in the mammalian transcriptome depend upon microRNAs, Drosha, and additional nucleases. Mol. Cell \\u003cem\\u003e38\\u003c/em\\u003e, 781\\u0026ndash;788.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLeung, A.K.L., Young, A.G., Bhutkar, A., Zheng, G.X., Bosson, A.D., Nielsen, C.B., and Sharp, P.A. (2011). Genome-wide identification of Ago2 binding sites from mouse embryonic stem cells with and without mature microRNAs. Nat. Struct. Mol. Biol. \\u003cem\\u003e18\\u003c/em\\u003e, 237\\u0026ndash;244.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChoi, H.M.T., Schwarzkopf, M., Fornace, M.E., Acharya, A., Artavanis, G., Stegmaier, J., Cunha, A., and Pierce, N.A. (2018). Third-generation in situ hybridization chain reaction: multiplexed, quantitative, sensitive, versatile, robust. Development \\u003cem\\u003e145\\u003c/em\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGebert, L.F.R., and MacRae, I.J. (2019). Regulation of microRNA function in animals. Nat. Rev. Mol. Cell Biol. \\u003cem\\u003e20\\u003c/em\\u003e, 21\\u0026ndash;37.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRouleau, S., Glouzon, J.-P.S., Brumwell, A., Bisaillon, M., and Perreault, J.-P. (2017). 3\\u0026rsquo; UTR G-quadruplexes regulate miRNA binding. RNA \\u003cem\\u003e23\\u003c/em\\u003e, 1172\\u0026ndash;1179.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAndreassi, C., Luisier, R., Crerar, H., Darsinou, M., Blokzijl-Franke, S., Lenn, T., Luscombe, N.M., Cuda, G., Gaspari, M., Saiardi, A., \\u003cem\\u003eet al.\\u003c/em\\u003e (2021). Cytoplasmic cleavage of IMPA1 3\\u0026rsquo; UTR is necessary for maintaining axon integrity. Cell Rep. \\u003cem\\u003e34\\u003c/em\\u003e, 108778.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHurt, J.A., Robertson, A.D., and Burge, C.B. (2013). Global analyses of UPF1 binding and function reveal expanded scope of nonsense-mediated mRNA decay. Genome Res. \\u003cem\\u003e23\\u003c/em\\u003e, 1636\\u0026ndash;1650.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003e- Abstract - Europe PMC Available at: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://europepmc.org/article/pmc/pmc4506499\\u003c/span\\u003e\\u003cspan address=\\\"https://europepmc.org/article/pmc/pmc4506499\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e [Accessed December 11, 2023].\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCaterino, M., and Paeschke, K. (2022). Action and function of helicases on RNA G-quadruplexes. Methods \\u003cem\\u003e204\\u003c/em\\u003e, 110\\u0026ndash;125.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGuo, J.U., and Bartel, D.P. (2016). RNA G-quadruplexes are globally unfolded in eukaryotic cells and depleted in bacteria. Science \\u003cem\\u003e353\\u003c/em\\u003e.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKharel, P., Fay, M., Manasova, E.V., Anderson, P.J., Kurkin, A.V., Guo, J.U., and Ivanov, P. (2023). Stress promotes RNA G-quadruplex folding in human cells. Nat. Commun. \\u003cem\\u003e14\\u003c/em\\u003e, 205.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCrenshaw, E., Leung, B.P., Kwok, C.K., Sharoni, M., Olson, K., Sebastian, N.P., Ansaloni, S., Schweitzer-Stenner, R., Akins, M.R., Bevilacqua, P.C., \\u003cem\\u003eet al.\\u003c/em\\u003e (2015). Amyloid precursor protein translation is regulated by a 3\\u0026rsquo;UTR guanine quadruplex. PLoS ONE \\u003cem\\u003e10\\u003c/em\\u003e, e0143160.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHengst, L., and Reed, S.I. (1996). Translational control of p27Kip1 accumulation during the cell cycle. Science \\u003cem\\u003e271\\u003c/em\\u003e, 1861\\u0026ndash;1864.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCuesta, R., Mart\\u0026iacute;nez-S\\u0026aacute;nchez, A., and Gebauer, F. (2009). miR-181a regulates cap-dependent translation of p27(kip1) mRNA in myeloid cells. Mol. Cell. Biol. \\u003cem\\u003e29\\u003c/em\\u003e, 2841\\u0026ndash;2851.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKaida, D., and Shida, K. (2022). Spliceostatin A stabilizes CDKN1B mRNA through the 3\\u0026rsquo; UTR. Biochem. Biophys. Res. Commun. \\u003cem\\u003e608\\u003c/em\\u003e, 39\\u0026ndash;44.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSatoh, T., and Kaida, D. (2016). Upregulation of p27 cyclin-dependent kinase inhibitor and a C-terminus truncated form of p27 contributes to G1 phase arrest. Sci. Rep. \\u003cem\\u003e6\\u003c/em\\u003e, 27829.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNoh, J.H., Kim, K.M., McClusky, W.G., Abdelmohsen, K., and Gorospe, M. (2018). Cytoplasmic functions of long noncoding RNAs. Wiley Interdiscip. Rev. RNA \\u003cem\\u003e9\\u003c/em\\u003e, e1471.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCiolli Mattioli, C., Rom, A., Franke, V., Imami, K., Arrey, G., Terne, M., Woehler, A., Akalin, A., Ulitsky, I., and Chekulaeva, M. (2019). Alternative 3\\u0026rsquo; UTRs direct localization of functionally diverse protein isoforms in neuronal compartments. Nucleic Acids Res. \\u003cem\\u003e47\\u003c/em\\u003e, 2560\\u0026ndash;2573.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDammes, N., and Peer, D. (2020). Paving the road for RNA therapeutics. Trends Pharmacol. Sci. \\u003cem\\u003e41\\u003c/em\\u003e, 755\\u0026ndash;775.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChakrabarti, A.M., Haberman, N., Praznik, A., Luscombe, N.M., and Ule, J. (2018). Data Science Issues in Studying Protein\\u0026ndash;RNA Interactions with CLIP Technologies. Annu. Rev. Biomed. Data Sci. \\u003cem\\u003e1\\u003c/em\\u003e, 235\\u0026ndash;261.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBalwierz, P.J., Carninci, P., Daub, C.O., Kawai, J., Hayashizaki, Y., Van Belle, W., Beisel, C., and van Nimwegen, E. (2009). Methods for analyzing deep sequencing expression data: constructing the human and mouse promoterome with deepCAGE data. Genome Biol. \\u003cem\\u003e10\\u003c/em\\u003e, R79.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePasquier, C., and Robichon, A. (2020). Computational prediction of miRNA/mRNA duplexomes at the whole human genome scale reveals functional subnetworks of interacting genes with embedded miRNA annealing motifs. Comput. Biol. Chem. \\u003cem\\u003e88\\u003c/em\\u003e, 107366.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKuehn, E., Clausen, D.S., Null, R.W., Metzger, B.M., Willis, A.D., and \\u0026Ouml;zpolat, B.D. (2022). Segment number threshold determines juvenile onset of germline cluster expansion in Platynereis dumerilii. J. Exp. Zool. B Mol. Dev. Evol. \\u003cem\\u003e338\\u003c/em\\u003e, 225\\u0026ndash;240.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eStringer, C., Wang, T., Michaelos, M., and Pachitariu, M. (2021). Cellpose: a generalist algorithm for cellular segmentation. Nat. Methods \\u003cem\\u003e18\\u003c/em\\u003e, 100\\u0026ndash;106.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBahry, E., Breimann, L., Zouinkhi, M., Epstein, L., Kolyvanov, K., Mamrak, N., King, B., Long, X., Harrington, K.I.S., Lionnet, T., \\u003cem\\u003eet al.\\u003c/em\\u003e (2022). RS-FISH: precise, interactive, fast, and scalable FISH spot detection. Nat. Methods \\u003cem\\u003e19\\u003c/em\\u003e, 1563\\u0026ndash;1567.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee, F.C.Y., Chakrabarti, A.M., H\\u0026auml;nel, H., Monz\\u0026oacute;n-Casanova, E., Hallegger, M., Militti, C., Capraro, F., Sad\\u0026eacute;e, C., Toolan-Kerr, P., Wilkins, O., \\u003cem\\u003eet al.\\u003c/em\\u003e (2021). An improved iCLIP protocol. BioRxiv.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSibley, C.R. (2018). Individual Nucleotide Resolution UV Cross-Linking and Immunoprecipitation (iCLIP) to Determine Protein-RNA Interactions. Methods Mol. Biol. \\u003cem\\u003e1649\\u003c/em\\u003e, 427\\u0026ndash;454.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKurata, J.S., and Lin, R.-J. (2018). MicroRNA-focused CRISPR-Cas9 library screen reveals fitness-associated miRNAs. RNA \\u003cem\\u003e24\\u003c/em\\u003e, 966\\u0026ndash;981.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHaberman, N., Huppertz, I., Attig, J., K\\u0026ouml;nig, J., Wang, Z., Hauer, C., Hentze, M.W., Kulozik, A.E., Le Hir, H., Curk, T., \\u003cem\\u003eet al.\\u003c/em\\u003e (2017). Insights into the design and interpretation of iCLIP experiments. Genome Biol. \\u003cem\\u003e18\\u003c/em\\u003e, 7.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDeMario, S., Xu, K., He, K., and Chanfreau, G.F. (2023). Nanoblot: an R-package for visualization of RNA isoforms from long-read RNA-sequencing data. RNA \\u003cem\\u003e29\\u003c/em\\u003e, 1099\\u0026ndash;1107.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-biology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"Learn more about [BMC Biology](https://bmcbiol.biomedcentral.com/)\",\"snPcode\":\"12915\",\"submissionUrl\":\"https://submission.springernature.com/new-submission/12915/3\",\"title\":\"BMC Biology\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"3’UTR, CAGE, capping, AGO2, UPF1, 3’UTR-derived RNA, G-rich, subcellular localisation\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4809688/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4809688/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eThe 3\\u0026rsquo; untranslated region (3\\u0026rsquo;UTR) plays a crucial role in determining mRNA stability, localisation, translation and degradation. Cap analysis of gene expression (CAGE), a method for the detection of capped 5\\u0026rsquo; ends of mRNAs, additionally reveals a large number of apparently 5\\u0026rsquo; capped RNAs derived from locations within the body of the transcript, including 3\\u0026rsquo;UTRs. Here we provide direct evidence that these 3\\u0026rsquo;UTR-derived RNAs are indeed capped and widespread in mammalian cells. By using a combination of AGO2 enhanced individual nucleotide resolution UV crosslinking and immunoprecipitation (eiCLIP) and CAGE following siRNA treatment, we find that these 3\\u0026rsquo;UTR-derived RNAs likely originate from AGO2-binding sites, and most often occur at locations with G-rich motifs bound by the RNA-binding protein UPF1. High-resolution imaging and long-read sequencing analysis validate several 3\\u0026rsquo;UTR-derived RNAs, showcase their variable abundance and show that they may not co-localise with the parental mRNAs. Taken together, we provide new insights into the origin and prevalence of 3\\u0026rsquo;UTR-derived RNAs, show the utility of CAGE-seq for their genome-wide detection, and provide a rich dataset for exploring new biology of a poorly understood new class of RNAs.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Widespread 3'UTR capped RNAs derive from G-rich regions in proximity to AGO2 binding sites\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-09-02 13:32:39\",\"doi\":\"10.21203/rs.3.rs-4809688/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2024-09-17T15:47:57+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-09-17T15:40:12+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"121850183731273999210323011765510100218\",\"date\":\"2024-09-17T15:35:28+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2024-09-17T15:32:17+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-07-30T07:54:16+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-07-29T08:44:23+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Biology\",\"date\":\"2024-07-26T17:42:05+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-biology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"Learn more about [BMC Biology](https://bmcbiol.biomedcentral.com/)\",\"snPcode\":\"12915\",\"submissionUrl\":\"https://submission.springernature.com/new-submission/12915/3\",\"title\":\"BMC Biology\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"4ffe34da-aadd-4998-9471-b13821fdebfb\",\"owner\":[],\"postedDate\":\"September 2nd, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-10-02T13:08:42+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-09-02 13:32:39\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4809688\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4809688\",\"identity\":\"rs-4809688\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}