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. 2023 Aug 28;26(10):107723. doi: 10.1016/j.isci.2023.107723

mRNA splicing is modulated by intronic microRNAs

Luba Farberov 1, Daphna Weissglas-Volkov 1,2, Guy Shapira 1,2, Yazeed Zoabi 1,2, Chen Schiff 1, Barbara Kloeckener-Gruissem 3,4, John Neidhardt 5,6, Noam Shomron 1,2,7,8,∗
PMCID: PMC10492213  PMID: 37692287

Summary

Splicing of transcripts is catalyzed by the spliceosome, a mega-complex consisting of hundreds of proteins and five snRNAs, which employs direct interactions. When U1 snRNA forms high-affinity binding, namely more than eight base pairs, with the 5′SS, the result is usually a suppressing effect on the splicing activity. This likely occurs due to the inefficient unwinding of U1/5′SS base-pairing or other regulatory obstructions. Here, we show in vitro and in patient-derived cell lines that pre-microRNAs can modulate the splicing reaction by interacting with U1 snRNA. This leads to reduced binding affinity to the 5′SS, and hence promotes the inclusion of exons containing 5′SS, despite sequence-based high affinity to U1. Application of the mechanism resulted in correction of the splicing defect in the disease-causing VCAN gene from an individual with Wagner syndrome. This pre-miRNA/U1 interaction can regulate the expression of alternatively spliced exons, thus extending the scope of mechanisms regulating splicing.

Subject areas: Molecular biology, Cell biology, Functional aspects of cell biology

Graphical abstract

graphic file with name fx1.jpg

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Highlights

  • •

    Novel pre-miRNA/U1 interaction regulate alternatively spliced exons

  • •

    Corrected VCAN gene splicing was achieved using miR-211

  • •

    Pre-miRNAs can modulate the splicing reaction by interacting with U1 snRNA

Molecular biology; Cell biology; Functional aspects of cell biology

Introduction

Pre-messenger RNA (pre-mRNA) is transcribed by RNA polymerase II and most pre-mRNAs contain both coding (exons) and non-coding (introns) segments. One step in the maturation of mRNA molecules is termed pre-mRNA splicing. In this reaction, introns are removed and exons are ligated to form mature mRNA.1,2,3 The reaction is catalyzed by the spliceosome, a mega-complex consisting of hundreds of proteins and five small nuclear snRNPs, containing the small nuclear RNAs (snRNAs) U1, U2, U4, U5, and U6.1,3,4,5,6,7 As known from yeast and mammalian cells, the interaction of U1 snRNP with pre-mRNA 5′ splice sites is an important early step in spliceosome assembly and pre-mRNA splicing. The 5′-end of U1 snRNA contains a short sequence of 9 nucleotides that is broadly complementary to the 5′-SS of the exon/intron boundary. Base-pairing between these two sequences plays a key role in the initiation of splicing and marks the 5′-end of an intron.8,9,10,11 Splicing requires a minimum of four to six nucleotides of mostly Watson-Crick base pairing (G·C and A·T) but also non-Watson-Crick pairings (G·U and U·U) between U1 snRNA and the 5′SS sequence. Pairing of the last three nucleotides of the donor exon and the first six bases of the proceeding intron (positions −3 to +6) of the pre-mRNA, with the 5′ end of the U1 snRNA, initializes the splicing process and leads to the recruitment of other spliceosomal components.7,12,13 Interestingly, pairing of more than eight bases significantly reduces the efficiency of the splicing reaction. This is likely due to inefficient unwinding of U1/5′SS base-pairing or a variety of other regulation types.7,14,15 The delicate balance at play has an important role in the regulation of 5′SS selection and influences the outcome of alternatively spliced exons, which are under selection for a tightly regulated expression profile.14,15,16

MicroRNAs (miRNAs) are small non-coding single-stranded RNA molecules, 21–24 nucleotides long, which induce posttranscriptional gene silencing of their target genes, thereby functioning as negative gene expression regulators.17 Most human miRNAs are located within intronic regions of either coding or non-coding genes and are transcribed by RNA polymerase II as part of their host transcription units.18,19,20,21 Accordingly, intronic miRNA expression is expected to be correlated with the expression of the spliced mRNA derived from the host transcript,18,22,23,24,25,26,27 yet this is not a general rule.27,28,29,30 In addition to the common miRNA biogenesis by the microprocessor complex, the “mirtron” pathway produces miRNAs using splicing machinery. Intron-derived miRNAs are released from their host transcripts after splicing21,22,31”. The mechanism by which the spliceosome coordinates the processing of both pre-mRNAs and mature miRNAs has been addressed in several studies. Morlando et al. concluded that splicing is enhanced by the microprocessor cleavage of intergenic and intronic miRNA genes.32 Janas et al. demonstrated that microprocessing of miR-211 promotes splicing of the exon 6-7 junction of melastatin and suggested a bidirectional effect. Accordingly, not only does microprocessing promote splicing but also reversely, splicing of the melastatin intron six promotes microprocessing of miR-211.21,33 Yan et al. showed that an alternative splicing event resulted in greater accumulation of miR-400 primary transcripts.34 In contrast, Kim et al. and Kataoka et al. each found mostly independent activities of the microprocessor and the spliceosome, though, to some extent, the microprocessor may interfere with the splicing process.19,35 Agranat-Tamir et al. found an inverse correlation between splicing and microprocessing: inhibition of splicing increased miRNA expression, whereas knock down of Drosha increased splicing.36

Furthermore, contrasting findings were reported regarding the processing of pre-miRNAs that overlap exon-intron splice-site junctions.21 For instance, Melamed et al.37 and Mattioli et al.38 identified a negative spliceosome-microprocessor interaction, while Pianigiani et al. did not find any changes in alternative splicing or miRNA expression following Drosha or splicing factor SF3b1 silencing.39

Despite such extensive studies, many questions remain unanswered, particularly in regard to U1. The goals of the current work were to elucidate how miRNAs can affect and interfere with the splicing reaction by interacting with U1 snRNA. Our results revealed a novel miRNA/U1 interaction that can regulate the expression of alternatively spliced exons. This expands the understanding of mechanisms regulating splicing.

Results

Pre-miRNA base-pairing with U1 snRNA

Most human miRNAs are located within intronic regions of either coding or non-coding genes and are transcribed by RNA polymerase II as part of their host transcription units.18,19,20,21 This raises intriguing questions as to how these intronic miRNAs and spliced genes are co-processed. How do both cellular machineries, namely, the microprocessor and the spliceosome, coordinate the processing of the same transcript to generate both mature miRNA and spliced genes?

To address these questions, we examined the hypothesis that pre-miRNAs mediate U1-binding affinity to the 5′SS and scanned pre-miRNA sequences for potential base-pairing with U1 snRNA. We focused on solitary human pre-miRNAs located in introns shorter than 10kb, in which the U1/pre-miRNA base-pairing is more likely to affect splicing of the host intron. We found that pre-miR-211, located to the TRPM1 (melastatin) intron six,33,40 ranks third in binding affinity to U1 (denoted as a red dot in Figure 1A). This affinity is surpassed only by pre-miR-210, which is located in an intron of a non-coding gene, and pre-miR-593, whose recorded expression is very weak. Both pre-miR-210 and pre-miR-593 are less likely candidates to affect the splicing of coding genes. Therefore, we cloned wild-type TRPM1 intron six between two GFP exons to perform mini-gene splicing assays (Figure S1). As intron 6 (more than 5 kilobases from the start of the transcript), premature termination by cleavage and polyadenylation (PCPA) will not inhibit splicing.43,44 These observations support our notion that intron-located pre-miRNA-211 contains strong base-pairing potential with the U1 snRNA.

Figure 1.

Figure 1

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Pre-miR-211-U1 snRNA binding promotes splicing

(A) Binding of pre-miRNAs to the U1 snRNA. Score distribution (using an EMBL-EBL tool41) of the pre-miRNAs that occur once in an up to 10Kb intron. The higher the score, the stronger the predicted binding between a pre-miRNA and the U1 snRNA. The red dot represents pre-miR-211, the yellow dot represents pre-let-7g, and the orange dot represents pre-miR-7-1.

(B) U1-5′SS score sequence alignment.13,42 Base-pairing miss-matches between the U1 snRNA and the splice sites are denoted in red bold letters.

(C) RT-qPCR analysis of GFP expression following 24 h of overexpression in the HEK 293T cell line. Fold changes of spliced GFP products normalized to the 100 5′SS score. In the absence of primary miR-211, GFP mini-genes showed the most efficient splicing at the 95 5′SS score. The paired Student’s t test was used for the statistical analysis (n = 3, ∗∗p < 0.005). Data are represented as mean ± SEM.

(D) As in C, with miR-211 or control plasmid overexpressed in trans. For miR-211 overexpressed, GFP spliced product expression was directly correlated with the 5′SS score and decreased as the 5′SS score decreased. Overexpression of the control plasmid was like in C. The paired Student’s t test was used for the statistical analysis (n = 3, ∗p < 0.05, ∗∗p < 0.005). Data are represented as mean ± SEM.

(E) As in C, with miR-211 or a control plasmid overexpressed in cis (for both transient and stable transfections). GFP spliced product expression was directly correlated with the 5′SS score and decreased as the 5′SS score decreased. The paired Student’s t test was used for the statistical analysis (n = 3, ∗∗p < 0.005). Data are represented as mean ± SEM.

GFP spliced mRNA product expression in the absence of pre-miR-211

Splicing requires a minimum of four to six nucleotides that base pair between U1 snRNA and the 5′SS sequence. However, pairing of more than eight bases significantly reduces the efficiency of the splicing reaction, due to inefficient unwinding of U1/5′SS base-pairing or a variety of other regulatory obstructions.7,14,15 Therefore, a U1 to 5′SS binding, in which all nine 5′SS base positions are Watson-Crick base paired to the U1 snRNA, is not preferred.

To verify whether this condition is also found in our GFP-TRPM1 mini-gene, we deleted pre-miR-211 and generated four mini-genes with 5′SS of various SS strength (scores of 100, 95, 83, and 78, as predicted by the analyzer splice tool13,42 (Figure 1B). We confirmed that, in the absence of pre-miR-211, expression of the spliced GFP product is preferred at a complementary score of 95 (eight base-pairing U1-5′SS match) (Figures 1B and 1C).

Overexpression (OE) of pre-miR-211 enhances expression of the spliced GFP mRNA product

Next, we measured the splicing efficiency scores of all four 5′SS in the presence of pre-miR-211 that was located either within the intron or delivered externally. We found that miRNA overexpressed either in trans (Figure 1D) or in cis (Figure 1C), as well as using transient or stable transfection (Figures 1E, S2A, and S2B), a score of 100 (nine base U1- 5′SS complementation) showed the highest spliced GFP mRNA product expression, compared with control plasmid OE and/or with other 5′SS scores (Figures 1D and 1E). This result indicates that overexpression of pre-miRNA-211 can assist the splicing mechanism by enhancing the incorporation of the first GFP exon with a 5′SS score of 100.

Subsequently, we tested how replacement of pre-miR-211 in the intron, with different precursor miRNAs, would affect the GFP splicing reaction. To this end, we exchanged the naturally existing pre-miR-211 in melastatin intron six, with two other human precursor miRNAs (let-7g or miR-7-1). These pre-miRNAs were chosen since, as pre-miR-211, they are single pre-miRNAs located in introns shorter than 10kb of coding genes WD repeat-containing protein 82 (WDR82) and heterogeneous nuclear ribonucleoprotein K (HNRNPK), respectively. These pre-miRNAs did not rescue the splicing pattern at the 100 5′SS score, and the spliced GFP mRNA product expression remained the highest, with a score of 95 (Figures 2A and 2B). These results were similar to those obtained in the absence of pre-miR-211. To reverse this effect, we mutated the pre-miR-7-1 sequence to enhance base-pairing with U1 snRNA (Figure S3). This deletion of six bases and insertion of six other nucleotides in the sequence of pre-miR-7-1 resulted in an increase in spliced GFP expression at a 5′SS score of 100 (Figure 2C). Hence, pre-mut-miR-7-1 resembled pre-miR-211 in its promotion of splicing in the presence of the high affinity 5′SS-U1-binding interaction.

Figure 2.

Figure 2

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pre-miR-7-1/pre-let-7g or mut-pre-miR-7-1 overexpression binding affinities to U1 snRNA and the effect on the splicing mechanism

(A) As in Figure 1E, transient transfection when pre-let-7g replaced pre-miR-211 in the intron. GFP spliced product expression does not depend on pre-let-7g overexpression and GFP expression is the highest with the 95 5′SS score. The paired Student’s t test was used for the statistical analysis (n = 3, ∗∗p < 0.005). Data are represented as mean ± SEM.

(B) As in Figure 1E, transient transfection when pre-miR-7 replaced pre-miR-211 in the intron. GFP spliced product expression does not depend on pre-miR-7 overexpression and GFP expression is the highest with the 95 5′SS score. The paired Student’s t test was used for the statistical analysis (n = 3, ∗p < 0.05, ∗∗p < 0.005). Data are represented as mean ± SEM.

(C) As in Figure 1E, transient transfection when mut-pre-miR-7 replaces pre-miR-211 in the intron. GFP spliced product expression is directly correlated with the 5′SS score and decreased as the 5′SS score decreased. The paired Student’s t test was used for the statistical analysis (n = 3, ∗p < 0.05, ∗∗p < 0.005). Data are represented as mean ± SEM.

(D) Streptavidin pull-down of biotinylated-labeled RNA. The fold change of U1 recovery represents the amount of the U1 snRNA recovered by the streptavidin pull-down assay compared to the quantity of the U1 snRNA loaded on the magnetic beads. U1 recovery was significantly higher following hybridization of U1 snRNA with pre-miR-211 or mut-pre-miR-7-1 than with WT pre-miR-7-1. Therefore, U1 snRNA binding to pre-miR-211 and mut-pre-miR-7-1 was stronger than to WT pre-miR-7-1. The paired Student’s t test was used for the statistical analysis (n = 3, ∗∗p < 0.005). Data are represented as mean ± SEM.

pre-miRNAs directly bind the U1 snRNA in a base-complementary manner

To show that the precursor miRNA directly binds to U1 snRNA, we performed a streptavidin pull down of biotinylated-labeled RNA. In this assay, the fold change (FC) of U1 recovery represents the amount of the U1 snRNA recovered by streptavidin. This is compared to the quantity of the U1 snRNA input or the amount loaded into the reaction. We have mixed the biotinylated pre-RNA and U1 snRNA (at 1:1 ratio) and facilitated the formation of the pre-miRNA-U1 dsRNA structure (see the STAR Methods section). Although this 1:1 in vitro ratio might not reflect a direct interaction in vivo, we assumed that this “clean” approach would overcome the masking or reactions that can take place in the cell. As seen in Figure 2D, U1 recovery is significantly higher following hybridization of U1 snRNA with pre-miR-211 or mut-pre-miR-7-1 than with WT pre-miR-7-1. Therefore, U1 snRNA binding to pre-miR-211 and mut-pre-miR-7-1 is stronger than to WT pre-miR-7-1 (Figure 2D). To validate these results, we also excavated an RNase mapping of miRNAs-U1 binding (Figure S4), an Affymetrix analysis of pre-miR-211 or pre-miR-7-1 pull-down (Figure S5), and LIGation of interacting RNA followed by high-throughput sequencing (LIGR-seq analysis45) (Figure S6). Taken together, we can conclude that pre-miRNAs bind to U1 snRNA in a base-to-base complementary manner with gradual affinities, and this affects the splicing reaction. Specifically, pre-miR-211 and mut-pre-miR-7-1 bind to U1 snRNA in a base match manner, and thereby rescue the GFP splicing pattern at the 100 5′SS score.

The global effect of pre-miR-211 overexpression on splicing of different 5′SSs

We were interested in understanding whether the U1-miRNA interaction is not only seen in a mini-gene splicing system but also has a global influence on the genomic gene expression. We analyzed overall HEK-293T RNA expression following 24 h of overexpression of pre-miR-211 or control plasmid (in trans), using next-generation sequencing (NGS) analysis. First, we evaluated the differential expression (DE) of miR-211 targets after miR-211 or control plasmid OE. This was aimed to confirm the canonical downregulation effect of miR-211 on its known targets using gene set enrichment analysis (GSEA).46 We then considered genes with TargetScan scores < −0.25 (“Top 5%”) as likely targets; this resulted in 168 known targets. We obtained significant enrichment of the target genes at the bottom of the ranked DE list (p-value = 0.002, Figure 3A). This supports the notion that miR-211 downregulates its predicted targets and also confirms the results of OE transfection obtained in the cells.

Figure 3.

Figure 3

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miR-211-U1 interaction corrects the VCAN splicing deficiency in fibroblasts derived from patients suffering from Wagner syndrome

(A) Enrichment plot of miR-211 target genes. The top portion of the plot shows where the target gene set appeared in the ranked list of genes. The bottom portion of the plot shows the value of the running enrichment score. The enrichment score is calculated by walking down the ranked list of genes, increasing a running-sum statistic when a gene is in the gene set and decreasing it when it is not. The magnitude of the increment depends on the correlation of the gene with the phenotype. The enrichment score is the maximum deviation from zero encountered in walking the list (designated by the dashed red line). A negative enrichment score indicates gene set enrichment at the bottom of the ranked list.

(B) Histogram of a 5′SS score of 24,860 exons (excluding the first exons and UTRs). The mean 5′SS score is 81, with only 168 (<1%) exons harboring a score of 100 (median score = 81.87, ISQ = 11.04, SD = 8.2).

(C) Boxplots of the mean differences in exon splicing events (SE) between overexpression and control experimental pairs by 5′SS score quantiles, and the 100 score. Means are designated by a red dot. The mean of the 100 5′SS group is significantly greater than the mean of each quantile group and all the other scores combined. The mean of 10,000 random permutations is designated by a blue cross (X).

(D) The VCAN E7-E8:E6-E8 expression ratio was analyzed by RT-qPCR in fibroblasts derived from individuals with Wagner syndrome.47 Exon 7 expression was significantly higher in the mutant cells versus the control cells for miR-211 or miR-182 OE. The paired Student’s t test was used for the statistical analysis (n = 3, ∗p < 0.05, ∗∗p < 0.005). Data are represented as mean ± SEM.

For alternative splicing analysis, the mixture-of-isoforms (MISO)48 model was used to estimate the percentage of exon skipping between two samples.48 We analyzed transcripts that were not downregulated by miR-211 binding to their 3′UTRs. Differential splicing event (SE) was tested in experimental pairs: positive splicing events indicated higher exon inclusion in the overexpression of miR-211 versus control plasmid, and negative splicing events indicated the converse (Figure S8). We assigned to each exon its 5′SS score,13,42 and calculated 5′SS quantiles excluding the 100 score group. This resulted in 5 groups: Q1-Q4 and 100, thresholds: 36, 76, 82, 87, and 100, respectively, with n: 218, 211, 209, 205, and 7, respectively. We observed the highest mean number of splicing events, with statistical significance, in the 100 5′SS score group, when miR-211 versus control plasmid was overexpressed (p-value = 0.03, Figure 3C). Importantly, since a 5′SS score of 100 is quite rare (<1%) (Figure 3B), we calculated an empirical p-value to estimate the likelihood of attaining the observed or a greater mean number of splicing events by random permutations. We obtained a significant empirical p-value of 0.004, suggesting that such a positive mean of splicing events is unlikely to occur by chance.

Hence, in agreement with the in vitro and in vivo studies performed, the RNA-seq splicing analysis supports the notion that OE of miR-211 enhances the inclusion of exons with a 5′SS score of 100 but not of other exons. OE of miR-211 increased the incorporation of alternatively spliced exons of the following genomic genes: protein phosphatase 1 regulatory subunit 12A isoform a (PPP1R12A), acylphosphatase 1 (ACYP1), versican (VCAN), and CCR4-NOT transcription complex subunit 2 (CNOT2) (Table S1). Interestingly, VCAN mis-splicing with exon exclusion leads to the Wagner syndrome (WS).47

Pre-miRNA OE increases the VCAN exon seven inclusion ratio

To apply our gained knowledge to a disease-relevant condition, we attempted to affect the splicing mechanism and to increase the inclusion of alternative spliced exons in fibroblasts derived from individuals with WS.47 WS is a rare vitreoretinal degeneration inherited as an autosomal dominant trait.49 The cause is mutations in the canonical splice sites of the VCAN gene; the consequence is exon exclusion.47 Although the exact molecular pathogenesis of WS is not fully understood, splicing is clearly involved.50,51,52

We overexpressed pre-miRNAs that were predicted to have a strong interaction with the U1 snRNA (pre-miR-211, pre-miR-124a, or pre-miR-182) in fibroblasts derived from persons with WS. Although we cannot be sure how the mutation affects the entire cellular transcriptome and gene expressions, our results showed correction of splicing deficiency, measured by an increase in the incorporation of the disease-related VCAN-lacking exon 7, which possesses a 5′SS score of 100. The ratio of exons 7-8 junction: exons 6-8 junction (E7-E8:E6-E8) expression was significantly higher in cells of patients versus controls for overexpression of pre-miR-211 or pre-miR-182. OE of WT pre-miR-7-1 had the same effect on both fibroblast cell lines, therefore the splicing outcome is specific for pre-miR-211 or pre-miR-182 (Figure 3D).

Discussion

Coordination of spliceosome and microprocessor activity is vital in processing a given pre-mRNA transcript. This is reflected by two observations regarding human miRNAs: (i) they are located within intronic regions of either coding or non-coding genes and (ii) they are transcribed by RNA polymerase II as part of their host transcription units.18,19,20,21

Spliceosome and microprocessor interactions were previously studied only in specific genes that harbored pre-miRNAs in their intron,19,35 or in the context of particular pre-miRNAs that overlap exon-intron junctions.37,39 The results displayed great variability. The possibility of an underlying mechanism based on global miRNA-spliceosome interplay could not be addressed as such. Our approach entailed a comprehensive and unbiased study of the crosstalk between the spliceosome and the microprocessor.

We hypothesized that miRNAs can interfere with the splicing reaction by interacting with U1 snRNA. To address whether miRNAs can modulate the binding affinity of U1 to the 5′SS, we scanned for pre-miRNA candidates that are likely to affect the splicing reaction of coding genes, via potential pre-miRNA/U1 snRNA Watson-Crick base-pairing. Pre-miR-211 binding affinity to U1 was found to rank third among solitary human pre-miRNAs located in introns shorter than 10kb. This prompted the analysis of TRPM1 intron six, which naturally hosts the miR-211 gene.33,40 Thus, the pre-miR-211-flanked GFP construct enabled our use of a native intron-containing miRNA, to study interactions and crosstalk between microprocessing and splicing. Overexpression of pre-miRNA-211 appears to assist splicing machinery by enhancing identification of the first GFP exon with a 5′SS score of 100. The specificity of this reaction was demonstrated by the lack of rescue when other human single precursor miRNAs were located in introns shorter than 10kb (pre-miR-7-1 or pre-let-7g). If the U1-5′SS interaction was based on complete nine base pairs, mut-pre-miR-7-1 would resemble pre-miR-211 in promoting splicing. We were also able to show direct binding of pre-miRNAs to the U1 snRNA by streptavidin pull-down of biotinylated-labeled RNA assays. Specifically, we demonstrated that pre-miR-211-U1 binding is stronger than pre-miR-7-1-U1 binding and that mut-pre-miR-7-1 has a better base-to-base match with U1 snRNA than WT pre-miR-7-1.

Furthermore, we analyzed the effect of overexpression of global pre-miR-211 on genomic gene expression and identified a new class of alternative spliced exons with specific 5′SS levels that are regulated by pre-miR-211 overexpression. Our findings showed that in the context of overexpressed pre-miR-211, significantly increased alternative exon inclusion was only observed in the 100 5′SS score group. Finally, from these differential exons, we were able to correct the splicing of the missing exon seven of the VCAN gene via overexpression of pre-miR-211 in fibroblasts derived from persons with WS. Hence, we showed, in vitro and in vivo, that pre-miR-211 directly binds to U1 snRNA and enhances the incorporation of multiple exons, with high-affinity binding to U1 snRNA.

Taken together, the applicability of our results for therapeutic approaches should be tested, as a means of correcting human diseases that are based on splicing defects. VCAN encodes a large extracellular matrix chondroitin sulfate glycoprotein that can be found in many human tissues. Differential splicing generates four isoforms: containing both exons 7 and 8, or lacking exon 7 or exon 8, or lacking both. Exons 7 and 8 code for protein components that carry glucosamine glycan (GAG) attachments, which appear to be function-related modifications–.53 The proposed functions of VCAN are manifold and affect general cellular processes. Interestingly, all patients diagnosed with WS carry mutations in the splice acceptor or donor site; this causes skipping of exon 7 or exon 8. We had access to fibroblasts of a person with a mutation (c.4004 + 1G>C (splice acceptor)) that leads to skipping exon 7.47 Applying our gained knowledge of interactions between pre-miR-211 and U1 snRNA, we demonstrated a significant increase in transcripts containing exon 7. These are very encouraging results in view of potential therapeutic interference. However, further testing in an animal model system, and eventually in patients is needed.

As non-consensus nucleotides are preferred in DNA-binding sites,54 non-sequential bases are favored in 5′SS.7,14,16 A nine-base U1-5′SS match (a 5′SS score of 100) hinders U1 snRNA release. This results in an inefficient splicing reaction. For alternatively spliced exons and genes, the problem is more prominent.15 The new miRNA splicing regulation that we uncovered modifies splicing interactions and regulates alternative exon inclusion.

Overall, we suggest a new model for pre-miRNA regulation of the splicing mechanism. Accordingly, pre-miRNAs bind to U1 and compete over binding to U1 snRNA with the 5′SS. This rescues the splicing reaction from its regulatory obstructions at the 100 5′SS score (a nine-base U1-5′SS match).

Each miRNA has a distinct binding affinity to U1 snRNA (Figures 4A–4C). A high base match score reflects strong miRNA-U1 binding. Consequently, this miRNA can affect the splicing process in the cell, as we identified by overexpression of pre-miR-211 in a cell line or in fibroblast cells (Figure 4A). Low-miRNA-U1 base complementation, as we showed using overexpressed WT pre-miR-7-1, does not promote the splicing machinery (Figure 4C). We were able to recover high-splicing efficiency by changing the WT pre-miR-7-1 sequence. This resulted in mut-pre-miR-7-1, which resembles pre-miR-211 in its effect on the splicing process (Figure 4D).

Figure 4.

Figure 4

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A suggested miRNA-splicing regulation model based on our results

(A–D) Pre-miRNA-U1 snRNA binding affinity. A high base match score reflects, as indicated previously, a strong miR-U1 interaction. (A) miR-211, (B) let-7g, (C) miR-7, (D) mut-miR-7.

Limitations of the study

Future research at the biological molecular level should elaborate how pre-miRNA competes over the U1 snRNA with the 5′SS. In addition, investigation is required to determine whether pre-miRNA overexpression increases the incorporation of exons with a 5′SS of 100, or reduces the binding affinity of all other 5′SS except those with a score of 100. It would be valuable to repeat these experiments on a lower 5′SS score in order to confirm that this is true for the 100 5′SS scores and not for lower ones.

STAR★Methods

Key resources table

REAGENT or RESOURCE SOURCE IDENTIFIER
Chemicals, peptides, and recombinant proteins
Trizol reagent Thermo Fisher Scientific 15596026
streptavidin magnetic beads Thermo Fisher Scientific 88816
Lipofectamine 2000 Transfection Reagent Thermo Fisher Scientific 11668019
Critical commercial assays
High-Capacity cDNA Reverse Transcription Kit Thermo Fisher Scientific 4368814
TaqMan Universal PCR Master Thermo Fisher Scientific 4304437
SYBR green fast PCR master mix Quantabio 95073-05K
MEGAshortscript T7 kit Thermo Fisher Scientific AM1354
TriFecta Dicer-Substrate RNAi Integrated DNA Technologies
Experimental models: Cell lines
Flp-in 293 cells Thermo Fisher Scientific R75007
HEK 293T cells ATCC CRL-3216™
Other
Zeocin antibiotics Thermo Fisher Scientific R25001
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Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Prof. Noam Shomron (nshomron@tauex.tau.ac.il).

Materials availability

This study did not generate new unique reagents.

Experimental model and study participant details

Cell culture

Monolayer-adherent HEK 293T and fibroblast cells were grown in DMEM medium supplemented with 10% (vol/vol) FCS, 0.3 g/liter L-glutamine, 100 units/ml penicillin, and 100 units/ml streptomycin (Biological Industries, Israel). Monolayer-adherent Flp-in 293 cells were grown in the same medium supplemented with 100 μg/mL Hygromycin and 100 μg/mL Zeocin antibiotics (Thermo Fisher Scientific, USA).

HEK 293T cells were supplied by Prof. Ruth Shalgi, Tel-Aviv University and Flp-in 293 were provided by Prof. Gil Ast, Tel-Aviv University.

Prior to each experiment, the cells were counted using Countess, an automated cell counter (Thermo Fisher Scientific, USA).

Fibroblast VCAN mutant and control cells were established as described in Kloeckener-Gruissem, B. et al.47

Ethics statement

Fibroblast VCAN mutant and control cells were established and propagated with consent of the patient and permission of the physician, Dr. H. Plauchu, as described in Kloeckener-Gruissem, B. et al..47 Experiments respected the principles expressed in the Declaration of Helsinki.

Method details

Determining the 5'SS score

Four 5' splice sites (5'SS) with decreasing scores were chosen (100, 95, 83, and 78), according to "the splice site analyzer tool" (http://ibis.tau.ac.il/ssat/SpliceSiteFrame.htm).13,42

Construct design

WT melastatin gene (TRPM1) intron 6 (minus the first 18bp and last 11bp) was inserted between two GFP exons, using XhoI-ApaI (Thermo Fisher Scientific, USA) restriction enzymes. TRPM1 For primer: GTACACTCGAGCGCAGTCCTCCTGGGCTGAT; TRPM1 Rev primer: GCGGGCCCACCACATTCGCCCATACCACCT.

GFP was designed and split into two exons as described by Wang, Z. et al.55

For deletion of pri-miR-211, the plasmid was doubly digested by ScaI-EcoRV (New England Bio-labs, USA) restriction enzymes and re-ligated by T4 DNA-ligase (New England Bio-labs, USA).

Pre-hsa-let-7g or pre-hsa-miR-7-1was inserted instead of pre-hsa-miR-211 using SacI-PvuI (New England Bio-labs, USA) restriction enzymes.

Pre-let-7g for: TAAGAGCTCGATTCCAGGCTGAGGTAGTAGTTTGTACAGT;

Pre-let-7g rev: GGTTCCGCCGATCGCTGTTCCTGGCAAGGCAGTGG;

Pre-miR-7-1 for: TAAGAGCTCATTCATTGGATGTTGGCCTAGTTCTGT;

Pre-miR-7-1 rev: GCCGATCGGTCCTGTAGAGGCATGGCCTGTG;

pre-miR-7-1 was site-directed mutated by using the QuikChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies, USA) twice. The first PCR deleted six DNA bases, whereas the second PCR inserted six new DNA nucleotides. Primers used for mutagenesis were the ones indicated below (target nucleotides are in italics and bold) and complementary reverse primers:

miR-7 deletion for:

AAGACTAGTGATTTTGTTGTTTTTCTAAATCGACAACAAATCACAGTC; miR-7 deletion rev:

GACTGTGATTTGTTGTCGATTTAGAAAAACAACAAAATCACTAGTCTT;

miR-7 insertion for:

CGACAACAAATCACAGTGGGGGACTGCCATATGGCACAGG;

miR-7 insertion rev:

CCTGTGCCATATGGCAGTCCCCCACTGTGATTTGTTGTCG.

Generating a stable cell line

The Flp-In 293 cell line was designed for rapid generation of stable cell lines. These cells contain a single stably integrated FRT site at a transcriptionally active genomic locus.56,57 Flp-in 293 cells expressing GFP-miRNA constructs were generated according to the manufacturer’s instructions. The plasmids were double digested with HindIII-NotI (New England Bio-labs, USA) and the insert was re-cloned into pOG44 Flp-recombinase expression vector (Thermo Fisher Scientific, USA). Stable for primer: AGCTTGCCAAGCTTGTTTAGTGAACCGTCAGATCCGCTAG;

Stable rev primer: AGCGGCCGCCTCTACAAATGTGGTATGGCTGATTATGATC.

Cells that are resistant to 100 μg/mL Hygromycin and sensitive to 100 μg/mL Zeocin were selected for further research.

miRNA constructs

Pre-miRNAs were cloned into the BamHI–EcoRI restriction site of the miRNA expression vector, miRVec, and were provided by Prof. Reuven Agami.58

Plasmid transfections

HEK 293T or Flp-In 293 cells were seeded in 24-well plates at a concentration of 8×104 cells/well. Fibroblast cells were seeded in 12-well plates at the same concentration of 8×104 cells/well. HEK 293T or Flp-In 293 cells were transfected with 500ng plasmid, whereas the fibroblast cells were transfected with 1μg plasmid, using Lipofectamine 2000 Transfection Reagent (Thermo Fisher Scientific, USA) according to the manufacturer’s instructions. Transfection efficiencies were measured by GFP fluorescence in all the cells, indicating a minimum transfection efficiency of 50% repeatedly. RNA was purified from the cells 24 hours after transfection.

RNA extraction and miRNA profiling

Total RNA was extracted from cell cultures using Trizol reagent (Thermo Fisher Scientific, USA). The final RNA concentration and purity were measured using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Thermo Scientific, USA).

RT-qPCR

Reverse transcription reaction for mRNA was conducted using the random-primer and High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, USA). Reverse transcription reactions for specific mature miRNA were conducted using TaqMan miRNA assays according to the manufacturer’s protocol (Thermo Fisher Scientific, USA). Single miRNA and mRNA expression were tested similarly using the TaqMan Universal PCR Master Mix (Thermo Fisher Scientific, USA) or the SYBR green fast PCR master mix (Quantabio, USA), respectively.

mRNA expression was quantified under the following thermal cycler conditions: 20 seconds at 95°C, 40 amplfication cycles (3 seconds at 95°C and 30 seconds at 60°C), and a melt curve: 15 seconds at 95°C, 1 minute at 60°C, and 15 seconds at 95°C. Expression values were calculated based on the comparative threshold cycle (Ct) method. mRNA expression levels were normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as an endogenous control.

Mature miRNA expression was quantified under the following thermal cycler conditions: 2 minutes at 50°C, 10 minutes at 95°C, and 40 amplification cycles (15 seconds at 95°C and 1 minute at 60°C). miRNA levels were normalized to U6 and are shown as fold changes relative to controls.

PCR was amplified and read using the Step-One Plus Detection Systems (Thermo Fisher Scientific, USA). Specific primers for mRNA expression detection were ordered from Integrated Device Technology, (IDT, USA):

GFP exon1 for: GCTACCCCGACCACATGAAGCA; GFP exon2 rev:

GTCTTGTAGGTGCCGTCGTCCTTG; GAPDH for:

CCACTCCTCCACCTTTGACGCT; GAPDH rev:

ACCCTGTTGCTGTAGCCAAATTCG. VCAN TaqMan specific assays (Thermo Fisher Scientific, USA) were used: Hs01007944_m1 (splice variant exons 7:8) and Hs01007937_m1 (splice variant exons 6:8). GAPDH TaqMan specific assay (Thermo Fisher Scientific, USA) was used as a normalizer- Hs03929097_g1.

Determining the pre-miRNA-U1 snRNA match score

Single miRNA in an up to 10Kb intron and U1snRNA Watson–Crick base paring match score was measured using an EMBL-EBL tool.41

RNase mapping

As described by Lin, C. L. et al.,59 we transcribed the miRNAs and the U1 snRNA using the MEGAshortscript T7 kit (Thermo Fisher Scientific, USA). To remove the 5'phosphate, each RNA probe was treated with 10 units of calf intestinal alkaline phosphatase (New England Bio-labs, USA) in dephosphorylation buffer, supplemented with 20 units of RNasin ribonuclease inhibitor (Promega, USA) at 37°C for 1 hour. The RNA probes were then Trizol extracted and end-labeled with 20 pmol ATP-[γ-32P] (10 Ci/mmol, 2 mCi/mL; PerkinElmer, USA). Next, 3.3μg of each RNA probe were incubated with 10 units of T4 polynucleotide kinase (New England Bio-labs, USA) in PNK buffer supplemented with 20 units of RNasin, at 37°C for 1 hour. The labeled RNA was extracted using the miRNeasy Mini Kit (QIAGEN, Germany). The RNA probes (1:1 ratio, 7 × 105 of total cpm) were heated at 94°C for 3 min and then cooled on the bench top for 10 min to facilitate structure formation (miRNA-U1 dsRNA). For each 10 μL enzymatic reaction, 6.3 × 105 of total cpm, 10 μg yeast RNA, RNA structure buffer, and 0.01 units of RNase T1 (Thermo Fisher Scientific, USA) were mixed, and incubated at room temperature for 15 min. To generate a hydrolysis ladder, the probes were mixed with 3 μg yeast RNA and alkaline hydrolysis buffer and then heated at 94°C for 2 min. The digested products were resolved in an 8.5% urea polyacrylamide gel, exposed to phosphor imager plates, and analyzed by a Typhoon scanner (GE Healthcare, USA).

LIGR-seq

As Described by Sharma et al.,45 in order to identify U1snRNA-pre-miRNA interaction, we have heated each of the in vitro transcribed U1 snRNA, WT or mut pre-miR-7 to 95°C, then incubated the U1 snRNA with the WT or mut pre-miR-7, and finally placed the mixes on the bench till room temperature was reached. These steps resulted in RNA-RNA base pairing and RNA folding. Next, we treated the U1-WT or mut pre-miR-7 mixtures with AMT to cross-link the base pairing sites; digested the non-hybridized RNA (ssRNA) by S1 RNase enzyme for 30 min at room temperature ligated the proximal RNA ends by circRNA ligase for 1 hour in 60°C); digested with RNase R the uncrossed linked RNA for 10 minutes at 37°C. Reversed the cross-links; performed SMARTER stranded RNA-Seq kit for library preparation according to the user manual. The library was run on an Illumina NGS platform, pair-end reads were generated.

Streptavidin pull-down of biotinylated labeled RNA

Pre-miRNA and U1 snRNA were transcribed by the MEGAshortscript T7 kit (Thermo Fisher Scientific, USA), according to the manufacturer’s instructions. Later 50pmol of each precursor miRNA was supplemented with 25% dimethyl sulfoxide (DMSO) and heated for 5 minutes at 85°C in order to relax the significant secondary structure. The RNA biotin labeling reaction was performed by the Pierce RNA 3' End Desthiobiotinylation Kit (Thermo Fisher Scientific, USA), according to the manufacturer’s instructions, and required an overnight incubation at 16°C. The following morning, the labeled pre-miRNAs were extracted using 100ul of chloroform:isoamyl alcohol 24:1 (Merck, Germany), and precipitated overnight at -20°C by adding 10ul of 5M NaCl, 1ul of glycogen and 300ul of ice-cold 100% ethanol.

The biotinylated RNA and U1 snRNA (at 1:1 ratio) were heated at 94°C for 3 minutes and then incubated for 10 minutes at room temperature to facilitate formation of the pre-miRNA-U1 dsRNA structure.

50pmol of biotinylated RNA-hybrid was loaded on 50ul streptavidin magnetic beads (Thermo Fisher Scientific, USA), and incubated with agitation for 30 minutes at room temperature. The RNA complex was eluted using the Pierce Magnetic RNA-Protein Pull-Down Kit (Thermo Fisher Scientific, USA), according to the manufacturer’s instructions.

Supernatant was RNA extracted using TRIzol reagent (Thermo Fisher Scientific, USA), and U1 snRNA expression was assessed by the SYBR Green Fast PCR Master Mix (Quantabio, USA) and specific U1 qPCR amplification primers: U1 snRNA for: CTGGCAGGGGAGATACCATGATC; U1 snRNA rev: GAAAGCGCGAACGCAGTCC.

U1 recovery was calculated as U1 expression output:U1 expression input and the fold change was normalized to the U1 recovery at WT pre-miR-7-1 OE treatment.

Deep sequencing and analysis

The RNA libraries were sequenced using Illumina HiSeq2500 sequencing, 20 million reads designated, paired-end sequencing with a 126nt length. The analysis process included several steps. First, reads were pre-processed (removal of adaptors and poor quality bases (Qpherd <30) at the end of the reads)60 and mapped to the human genome reference sequence GRCh37 (hg19) and transcriptome (GTF transcript annotation retrieved from UCSC).61,62 We assessed the quality of the raw reads using FastQC53 (median # reads = 11.12M, ISQ = 1.86M, paired-end). Gene counts were estimated using the HTSeq tool (25260700). Only genes that had at least 10 reads in at least 2 samples were used in the DE analysis (n=11,794). Samples were classified as overexpressed pre-miR-211 or as a control sequence, with three biological replicates for each group. Next, a PCA was performed and no samples were detected as outliers (Figure S7). Gene set enrichment analysis was applied to determine whether the known targets are over-represented.46 We considered genes with TargetScan63 scores < -0.25 (‘Top 5%’) as likely targets. Subsequently, a mixture-of-isoform model was used to estimate the percentage of exon skipping48 and differential exon skipping, calculated as the difference in exon skipping between two samples.48 A positive splicing event indicates higher exon inclusion in the overexpression samples pre-miR-211 versus the control plasmid, and vice versa for a negative splicing event. For each event, we calculated the average splicing event scores when at least two of the triplicates sufficiently expressed the three consecutive exons (Figure S8). Lastly, to examine the relation between differential exon inclusion and U1 binding, we assigned each event a ‘U1-binding score’ based on the 5’ junction of the middle exon, and calculated 5’SS quantiles excluding the 100-score group. This resulted in 5 groups: Q1-Q4 and 100, thresholds: 36, 76, 82, 87, and 100, respectively, and n: 218, 211, 209, 205, and 7, respectively.

U1 down-regulation

U1 was down-regulated using the TriFecta Dicer-Substrate RNAi according to the manufacturer’s protocol (Integrated DNA Technologies, USA). U1 expression was inhibited by 30% using 1nM of the specific siRNA (sequence: CCACAAATTATGCAGTCGAGTTTCCCA) OE for 24h in the HEK-293T cells (Figure S9A). Analysis of the GFP spliced product mRNA expression transcribed from the mini-gene (Figure S9B) and the global differential SE effect (Figure S9C).

Affymetrix analysis

Pre-miR-211 or pre-miR-7-1 were hybridized with U1 snRNA. The hybrid was then pulled down using U1 snRNP antibody (U1 snRNP 70 Antibody (E-4): sc-390988, Santa cruz, USA), and total RNA was extracted. Pre-miR-211 or pre-miR-7-1 quantity was analyzed using Affymetrix GeneChip miRNA 4.0 Assay (ThermoFisher, USA).

Raw data were normalized using the RMA algorithm from oligo 1.50.0 on R 3.6.3.

Next, batch correction was estimated by sva 3.34.0 and applied using the RemoveBatchEffect function of limma 3.42.2. Finally, normalized intensity values were compared using the Welch unpaired t-test.

Quantification and statistical analysis

Data are presented as mean ± standard error of the mean (SEM). p-values were calculated using a paired t-test, with p < 0.05 considered significant (∗<0.05, ∗∗<0.005).

Acknowledgments

This work was performed in partial fulfillment of the requirements for a Ph.D. degree by Luba Farberov at the Sackler Faculty of Medicine, Tel Aviv University, Israel.

We would like to thank Dodo Chikvashvili from Prof. Ilana Lotan’s lab for helping with the RNase mapping experiment and Prof. Gil Ast and Avital Luba Polsky for commenting on the manuscript.

Funding: The Shomron Laboratory is supported by Horizon 2020 Research and Innovation Framework Program (no. 945151; PSY-PGx); ERA-NET PerMed (no. 3–17928; ArtiPro) from the Israeli Ministry of Health; The Edmond J. Safra Center for Bioinformatics at Tel Aviv University; The Koret-UC Berkeley-Tel Aviv University Initiative in Computational Biology and Bioinformatics; Kodesz Institute for Technologies in Healthcare; Tel Aviv University Healthy Longevity Research Center; Djerassi-Elias Institute of Oncology; Kirschman Dvora Eleonora Fund for Parkinson's Disease; Tel Aviv University Innovation Laboratories (TILabs).

Author contributions

L.F and N.S. conceived the project. N.S. supervised and supported the project. L.F. and N.S. designed and conducted the experiments and wrote the manuscript. D.W.N., G.S., Y.Z., and C.S. performed the NGS data analysis. J.H. and B.K.G. generated and supplied the fibroblasts derived from patients. All the authors discussed the results and commented on the manuscript.

Declaration of interests

The authors declare no competing interests.

Inclusion and diversity

We support inclusive, diverse, and equitable conduct of research.

Published: August 28, 2023

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.isci.2023.107723.

Supplemental information

Document S1. Figures S1–S9 and Table S1
mmc1.pdf (1.2MB, pdf)

Data and code availability

RNA-Seq data used in this study was deposited in the Gene Expression Omnibus (GEO), under accession number: GSE236090. Code will be shared upon request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Figures S1–S9 and Table S1
mmc1.pdf (1.2MB, pdf)

Data Availability Statement

RNA-Seq data used in this study was deposited in the Gene Expression Omnibus (GEO), under accession number: GSE236090. Code will be shared upon request.

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