Intronic small nucleolar RNAs regulate host gene splicing through base pairing with their adjacent intronic sequences.

BACKGROUND: Small nucleolar RNAs (snoRNAs) are abundant noncoding RNAs best known for their involvement in ribosomal RNA maturation. In mammals, most expressed snoRNAs are embedded in introns of longer genes and produced through transcription and splicing of their host. Intronic snoRNAs were long viewed as inert passengers with little effect on host expression. However, a recent study reported a snoRNA influencing the splicing and ultimate output of its host gene. Overall, the general contribution of intronic snoRNAs to host expression remains unclear. RESULTS: Computational analysis of large-scale human RNA-RNA interaction datasets indicates that 30% of detected snoRNAs interact with their host transcripts. Many snoRNA-host duplexes are located near alternatively spliced exons and display high sequence conservation suggesting a possible role in splicing regulation. The study of the model SNORD2-EIF4A2 duplex indicates that the snoRNA interaction with the host intronic sequence conceals the branch point leading to decreased inclusion of the adjacent alternative exon. Extended SNORD2 sequence containing the interacting intronic region accumulates in sequencing datasets in a cell-type-specific manner. Antisense oligonucleotides and mutations that disrupt the formation of the snoRNA-intron structure promote the splicing of the alternative exon, shifting the EIF4A2 transcript ratio away from nonsense-mediated decay. CONCLUSIONS: Many snoRNAs form RNA duplexes near alternative exons of their host transcripts, placing them in optimal positions to control host output as shown for the SNORD2-EIF4A2 model system. Overall, our study supports a more widespread role for intronic snoRNAs in the regulation of their host transcript maturation.

The snoGloBe interaction predictor reveals a broad spectrum of C/D snoRNA RNA targets.

Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2'-O-ribose methylation. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA-RNA interaction datasets detect many snoRNAs binding messenger RNA, but are limited by specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. SnoGloBe is also an excellent tool for discovering viral RNA targets, as shown by its capacity to identify snoRNAs targeting the heavily methylated SARS-CoV-2 RNA. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function.

High-grade ovarian cancer associated H/ACA snoRNAs promote cancer cell proliferation and survival.

Small nucleolar RNAs (snoRNAs) are an omnipresent class of non-coding RNAs involved in the modification and processing of ribosomal RNA (rRNA). As snoRNAs are required for ribosome production, the increase of which is a hallmark of cancer development, their expression would be expected to increase in proliferating cancer cells. However, assessing the nature and extent of snoRNAs' contribution to cancer biology has been largely limited by difficulties in detecting highly structured RNA. In this study, we used a dedicated midsize non-coding RNA (mncRNA) sensitive sequencing technique to accurately survey the snoRNA abundance in independently verified high-grade serous ovarian carcinoma (HGSC) and serous borderline tumour (SBT) tissues. The results identified SNORA81, SNORA19 and SNORA56 as an H/ACA snoRNA signature capable of discriminating between independent sets of HGSC, SBT and normal tissues. The expression of the signature SNORA81 correlates with the level of ribosomal RNA (rRNA) modification and its knockdown inhibits 28S rRNA pseudouridylation and accumulation leading to reduced cell proliferation and migration. Together our data indicate that specific subsets of H/ACA snoRNAs may promote tumour aggressiveness by inducing rRNA modification and synthesis.

RBFOX2 alters splicing outcome in distinct binding modes with multiple protein partners.

RBFOX2 controls the splicing of a large number of transcripts implicated in cell differentiation and development. Parsing RNA-binding protein datasets, we uncover that RBFOX2 can interact with hnRNPC, hnRNPM and SRSF1 to regulate splicing of a broad range of splicing events using different sequence motifs and binding modes. Using immunoprecipitation, specific RBP knockdown, RNA-seq and splice-sensitive PCR, we show that RBFOX2 can target splice sites using three binding configurations: single, multiple or secondary modes. In the single binding mode RBFOX2 is recruited to its target splice sites through a single canonical binding motif, while in the multiple binding mode RBFOX2 binding sites include the adjacent binding of at least one other RNA binding protein partner. Finally, in the secondary binding mode RBFOX2 likely does not bind the RNA directly but is recruited to splice sites lacking its canonical binding motif through the binding of one of its protein partners. These dynamic modes bind distinct sets of transcripts at different positions and distances relative to alternative splice sites explaining the heterogeneity of RBFOX2 targets and splicing outcomes.

Annotation of snoRNA abundance across human tissues reveals complex snoRNA-host gene relationships.

BACKGROUND: Small nucleolar RNAs (snoRNAs) are mid-size non-coding RNAs required for ribosomal RNA modification, implying a ubiquitous tissue distribution linked to ribosome synthesis. However, increasing numbers of studies identify extra-ribosomal roles of snoRNAs in modulating gene expression, suggesting more complex snoRNA abundance patterns. Therefore, there is a great need for mapping the snoRNome in different human tissues as the blueprint for snoRNA functions. RESULTS: We used a low structure bias RNA-Seq approach to accurately quantify snoRNAs and compare them to the entire transcriptome in seven healthy human tissues (breast, ovary, prostate, testis, skeletal muscle, liver, and brain). We identify 475 expressed snoRNAs categorized in two abundance classes that differ significantly in their function, conservation level, and correlation with their host gene: 390 snoRNAs are uniformly expressed and 85 are enriched in the brain or reproductive tissues. Most tissue-enriched snoRNAs are embedded in lncRNAs and display strong correlation of abundance with them, whereas uniformly expressed snoRNAs are mostly embedded in protein-coding host genes and are mainly non- or anticorrelated with them. Fifty-nine percent of the non-correlated or anticorrelated protein-coding host gene/snoRNA pairs feature dual-initiation promoters, compared to only 16% of the correlated non-coding host gene/snoRNA pairs. CONCLUSIONS: Our results demonstrate that snoRNAs are not a single homogeneous group of housekeeping genes but include highly regulated tissue-enriched RNAs. Indeed, our work indicates that the architecture of snoRNA host genes varies to uncouple the host and snoRNA expressions in order to meet the different snoRNA abundance levels and functional needs of human tissues.

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA.

The study of RNA expression is the fastest growing area of genomic research. However, despite the dramatic increase in the number of sequenced transcriptomes, we still do not have accurate estimates of the number and expression levels of non-coding RNA genes. Non-coding transcripts are often overlooked due to incomplete genome annotation. In this study, we use annotation-independent detection of RNA reads generated using a reverse transcriptase with low structure bias to identify non-coding RNA. Transcripts between 20 and 500 nucleotides were filtered and crosschecked with non-coding RNA annotations revealing 111 non-annotated non-coding RNAs expressed in different cell lines and tissues. Inspecting the sequence and structural features of these transcripts indicated that 60% of these transcripts correspond to new snoRNA and tRNA-like genes. The identified genes exhibited features of their respective families in terms of structure, expression, conservation and response to depletion of interacting proteins. Together, our data reveal a new group of RNA that are difficult to detect using standard gene prediction and RNA sequencing techniques, suggesting that reliance on actual gene annotation and sequencing techniques distorts the perceived architecture of the human transcriptome.

Simultaneous sequencing of coding and noncoding RNA reveals a human transcriptome dominated by a small number of highly expressed noncoding genes.

Comparing the abundance of one RNA molecule to another is crucial for understanding cellular functions but most sequencing techniques can target only specific subsets of RNA. In this study, we used a new fragmented ribodepleted TGIRT sequencing method that uses a thermostable group II intron reverse transcriptase (TGIRT) to generate a portrait of the human transcriptome depicting the quantitative relationship of all classes of nonribosomal RNA longer than 60 nt. Comparison between different sequencing methods indicated that FRT is more accurate in ranking both mRNA and noncoding RNA than viral reverse transcriptase-based sequencing methods, even those that specifically target these species. Measurements of RNA abundance in different cell lines using this method correlate with biochemical estimates, confirming tRNA as the most abundant nonribosomal RNA biotype. However, the single most abundant transcript is 7SL RNA, a component of the signal recognition particle. Structured noncoding RNAs (sncRNAs) associated with the same biological process are expressed at similar levels, with the exception of RNAs with multiple functions like U1 snRNA. In general, sncRNAs forming RNPs are hundreds to thousands of times more abundant than their mRNA counterparts. Surprisingly, only 50 sncRNA genes produce half of the non-rRNA transcripts detected in two different cell lines. Together the results indicate that the human transcriptome is dominated by a small number of highly expressed sncRNAs specializing in functions related to translation and splicing.

Identification of discrete classes of small nucleolar RNA featuring different ends and RNA binding protein dependency.

Small nucleolar RNAs (snoRNAs) are among the first discovered and most extensively studied group of small non-coding RNA. However, most studies focused on a small subset of snoRNAs that guide the modification of ribosomal RNA. In this study, we annotated the expression pattern of all box C/D snoRNAs in normal and cancer cell lines independent of their functions. The results indicate that C/D snoRNAs are expressed as two distinct forms differing in their ends with respect to boxes C and D and in their terminal stem length. Both forms are overexpressed in cancer cell lines but display a conserved end distribution. Surprisingly, the long forms are more dependent than the short forms on the expression of the core snoRNP protein NOP58, thought to be essential for C/D snoRNA production. In contrast, a subset of short forms are dependent on the splicing factor RBFOX2. Analysis of the potential secondary structure of both forms indicates that the k-turn motif required for binding of NOP58 is less stable in short forms which are thus less likely to mature into a canonical snoRNP. Taken together the data suggest that C/D snoRNAs are divided into at least two groups with distinct maturation and functional preferences.

Tumor microenvironment-associated modifications of alternative splicing.

Pre-mRNA alternative splicing is modified in cancer, but the origin and specificity of these changes remain unclear. Here, we probed ovarian tumors to identify cancer-associated splicing isoforms and define the mechanism by which splicing is modified in cancer cells. Using high-throughput quantitative PCR, we monitored the expression of splice variants in laser-dissected tissues from ovarian tumors. Surprisingly, changes in alternative splicing were not limited to the tumor tissues but were also found in the tumor microenvironment. Changes in the tumor-associated splicing events were found to be regulated by splicing factors that are differentially expressed in cancer tissues. Overall, ∼20% of the alternative splicing events affected by the down-regulation of the splicing factors QKI and RBFOX2 were altered in the microenvironment of ovarian tumors. Together, our results indicate that the tumor microenvironment undergoes specific changes in alternative splicing orchestrated by a limited number of splicing factors.

Proteins associated with the exon junction complex also control the alternative splicing of apoptotic regulators.

Several apoptotic regulators, including Bcl-x, are alternatively spliced to produce isoforms with opposite functions. We have used an RNA interference strategy to map the regulatory landscape controlling the expression of the Bcl-x splice variants in human cells. Depleting proteins known as core (Y14 and eIF4A3) or auxiliary (RNPS1, Acinus, and SAP18) components of the exon junction complex (EJC) improved the production of the proapoptotic Bcl-x(S) splice variant. This effect was not seen when we depleted EJC proteins that typically participate in mRNA export (UAP56, Aly/Ref, and TAP) or that associate with the EJC to enforce nonsense-mediated RNA decay (MNL51, Upf1, Upf2, and Upf3b). Core and auxiliary EJC components modulated Bcl-x splicing through different cis-acting elements, further suggesting that this activity is distinct from the established EJC function. In support of a direct role in splicing control, recombinant eIF4A3, Y14, and Magoh proteins associated preferentially with the endogenous Bcl-x pre-mRNA, interacted with a model Bcl-x pre-mRNA in early splicing complexes, and specifically shifted Bcl-x alternative splicing in nuclear extracts. Finally, the depletion of Y14, eIF4A3, RNPS1, SAP18, and Acinus also encouraged the production of other proapoptotic splice variants, suggesting that EJC-associated components are important regulators of apoptosis acting at the alternative splicing level.

Alternative splicing of SYK regulates mitosis and cell survival.

Most human genes produce multiple mRNA isoforms through alternative splicing. However, the biological relevance of most splice variants remains unclear. In this study, we evaluated the functional impact of alternative splicing in cancer cells. We modulated the splicing pattern of 41 cancer-associated splicing events and scored the effects on cell growth, viability and apoptosis, identifying three isoforms essential for cell survival. Specifically, changing the splicing pattern of the spleen tyrosine kinase gene (SYK) impaired cell-cycle progression and anchorage-independent growth. Notably, exposure of cancer cells to epithelial growth factor modulated the SYK splicing pattern to promote the pro-survival isoform that is associated with cancer tissues in vivo. The data suggest that splicing of selected genes is specifically modified during tumor development to allow the expression of isoforms that promote cancer cell survival.

Cancer-associated regulation of alternative splicing.

Alternative splicing of pre-mRNA increases the diversity of protein functions. Here we show that about half of all active alternative splicing events in ovarian and breast tissues are changed in tumors, and many seem to be regulated by a single factor; sequence analysis revealed binding sites for the RNA binding protein FOX2 downstream of one-third of the exons skipped in cancer. High-resolution analysis of FOX2 binding sites defined the precise positions relative to alternative exons at which the protein may function as either a silencer or an enhancer. Most of the identified targets were shifted in the same direction by FOX2 depletion in cell lines as they were in breast and ovarian cancer tissues. Notably, we found expression of FOX2 itself is downregulated in ovarian cancer and its splicing is altered in breast cancer samples. These results suggest that the decreased expression of FOX2 in cancer tissues modulates splicing and controls proliferation.

Multiple and specific mRNA processing targets for the major human hnRNP proteins.

Alternative splicing is a key mechanism regulating gene expression, and it is often used to produce antagonistic activities particularly in apoptotic genes. Heterogeneous nuclear ribonucleoparticle (hnRNP) proteins form a family of RNA-binding proteins that coat nascent pre-mRNAs. Many but not all major hnRNP proteins have been shown to participate in splicing control. The range and specificity of hnRNP protein action remain poorly documented, even for those affecting splice site selection. We used RNA interference and a reverse transcription-PCR screening platform to examine the implications of 14 of the major hnRNP proteins in the splicing of 56 alternative splicing events in apoptotic genes. Out of this total of 784 alternative splicing reactions tested in three human cell lines, 31 responded similarly to a knockdown in at least two different cell lines. On the other hand, the impact of other hnRNP knockdowns was cell line specific. The broadest effects were obtained with hnRNP K and C, two proteins whose role in alternative splicing had not previously been firmly established. Different hnRNP proteins affected distinct sets of targets with little overlap even between closely related hnRNP proteins. Overall, our study highlights the potential contribution of all of these major hnRNP proteins in alternative splicing control and shows that the targets for individual hnRNP proteins can vary in different cellular contexts.