The human box C/D snoRNA U3 is a miRNA source and miR-U3 regulates expression of sortin nexin 27

SNORA28 Promotes Proliferation and Radioresistance in Colorectal Cancer Cells through the STAT3 Pathway by Increasing H3K9 Acetylation in the LIFR Promoter

Radiotherapy is essential for treating colorectal cancer (CRC), especially in advanced rectal cancer. However, the low radiosensitivity of CRC cells greatly limits radiotherapy efficacy. Small nucleolar RNAs (snoRNAs) are a class of noncoding RNA that primarily direct post-transcriptional modifications of ribosomal RNAs (rRNAs), small nuclear RNAs (snRNAs), and other cellular RNAs. While snoRNAs are involved in tumor progression and chemoresistance, their association with radiosensitivity remains largely unknown. Herein, SNORA28 is shown highly expressed in CRC and is positively associated with poor prognosis. Furthermore, SNORA28 overexpression enhances the growth and radioresistance of CRC cells in vitro and in vivo. Mechanistically, SNORA28 acts as a molecular decoy that recruits bromodomain-containing protein 4 (BRD4), which increases the level of H3K9 acetylation at the LIFR promoter region. This stimulates LIFR transcription, which in turn triggers the JAK1/STAT3 pathway, enhancing the proliferation and radioresistance of CRC cells. Overall, these results highlight the ability of snoRNAs to regulate radiosensitivity in tumor cells and affect histone acetylation modification in the promoter region of target genes, thus broadening the current knowledge of snoRNA biological functions and the mechanism underlying target gene regulation.

sRNAfrag: a pipeline and suite of tools to analyze fragmentation in small RNA sequencing data

Fragments derived from small RNAs such as small nucleolar RNAs are biologically relevant but remain poorly understood. To address this gap, we developed sRNAfrag, a modular and interoperable tool designed to standardize the quantification and analysis of small RNA fragmentation across various biotypes. The tool outputs a set of tables forming a relational database, allowing for an in-depth exploration of biologically complex events such as multi-mapping and RNA fragment stability across different cell types. In a benchmark test, sRNAfrag was able to identify established loci of mature microRNAs solely based on sequencing data. Furthermore, the 5' seed sequence could be rediscovered by utilizing a visualization approach primarily applied in multi-sequence-alignments. Utilizing the relational database outputs, we detected 1411 snoRNA fragment conservation events between two out of four eukaryotic species, providing an opportunity to explore motifs through evolutionary time and conserved fragmentation patterns. Additionally, the tool's interoperability with other bioinformatics tools like ViennaRNA amplifies its utility for customized analyses. We also introduce a novel loci-level variance-score which provides insights into the noise around peaks and demonstrates biological relevance by distinctly separating breast cancer and neuroblastoma cell lines after dimension reduction when applied to small nucleolar RNAs. Overall, sRNAfrag serves as a versatile foundation for advancing our understanding of small RNA fragments and offers a functional foundation to further small RNA research. Availability: https://github.com/kenminsoo/sRNAfrag.

A prognostic signature based on snoRNA predicts the overall survival of lower-grade glioma patients

Introduction

Small nucleolar RNAs (snoRNAs) are a group of non-coding RNAs enriched in the nucleus which direct post-transcriptional modifications of rRNAs, snRNAs and other molecules. Recent studies have suggested that snoRNAs have a significant role in tumor oncogenesis and can be served as prognostic markers for predicting the overall survival of tumor patients.

Methods

We screened 122 survival-related snoRNAs from public databases and eventually selected 7 snoRNAs that were most relevant to the prognosis of lower-grade glioma (LGG) patients for the establishment of the 7-snoRNA prognostic signature. Further, we combined clinical characteristics related to the prognosis of glioma patients and the 7-snoRNA prognostic signature to construct a nomogram.

Results

The prognostic model displayed greater predictive power in both validation set and stratification analysis. Results of enrichment analysis revealed that these snoRNAs mainly participated in the post-transcriptional process such as RNA splicing, metabolism and modifications. In addition, 7-snoRNA prognostic signature were positively correlated with immune scores and expression levels of multiple immune checkpoint molecules, which can be used as potential biomarkers for immunotherapy prediction. From the results of bioinformatics analysis, we inferred that SNORD88C has a major role in the development of glioma, and then performed in vitro experiments to validate it. The results revealed that SNORD88C could promote the proliferation, invasion and migration of glioma cells.

Discussion

We established a 7-snoRNA prognostic signature and nomogram that can be applied to evaluate the survival of LGG patients with good sensitivity and specificity. In addition, SNORD88C could promote the proliferation, migration and invasion of glioma cells and is involved in a variety of biological processes related to DNA and RNA.

U3 snoRNA-mediated degradation of ZBTB7A regulates aerobic glycolysis in isocitrate dehydrogenase 1 wild-type glioblastoma cells

AIMS

The isocitrate dehydrogenase (IDH) phenotype is associated with reprogrammed energy metabolism in glioblastoma (GBM) cells. Small nucleolar RNAs (snoRNAs) are known to exert an important regulatory role in the energy metabolism of tumor cells. The purpose of this study was to investigate the role of C/D box snoRNA U3 and transcription factor zinc finger and BTB domain-containing 7A (ZBTB7A) in the regulation of aerobic glycolysis and the proliferative capacity of IDH1 wild-type (IDH1WT ) GBM cells.

METHODS

Quantitative reverse transcription PCR and western blot assays were utilized to detect snoRNA U3 and ZBTB7A expression. U3 promoter methylation status was analyzed via bisulfite sequencing and methylation-specific PCR. Seahorse XF glycolysis stress assays, lactate production and glucose consumption measurement assays, and cell viability assays were utilized to detect glycolysis and proliferation of IDH1WT GBM cells.

RESULTS

We found that hypomethylation of the CpG island in the promoter region of U3 led to the upregulation of U3 expression in IDH1WT GBM cells, and the knockdown of U3 suppressed aerobic glycolysis and the proliferation ability of IDH1WT GBM cells. We found that small nucleolar-derived RNA (sdRNA) U3-miR, a small fragment produced by U3, was able to bind to the ZBTB4 3'UTR region and reduce ZBTB7A mRNA stability, thereby downregulating ZBTB7A protein expression. Furthermore, ZBTB7A transcriptionally inhibited the expression of hexokinase 2 (HK2) and lactate dehydrogenase A (LDHA), which are key enzymes of aerobic glycolysis, by directly binding to the HK2 and LDHA promoter regions, thereby forming the U3/ZBTB7A/HK2 LDHA pathway that regulates aerobic glycolysis and proliferation of IDH1WT GBM cells.

CONCLUSION

U3 enhances aerobic glycolysis and proliferation in IDH1WT GBM cells via the U3/ZBTB7A/HK2 LDHA axis.

sRNAfrag: A pipeline and suite of tools to analyze fragmentation in small RNA sequencing data

Fragments derived from small RNAs such as small nucleolar RNAs hold biological relevance. However, they remain poorly understood, calling for more comprehensive methods for analysis. We developed sRNAfrag, a standardized workflow and set of scripts to quantify and analyze sRNA fragmentation of any biotype. In a benchmark, it is able to detect loci of mature microRNAs fragmented from precursors and, utilizing multi-mapping events, the conserved 5' seed sequence of miRNAs which we believe may extraoplate to other small RNA fragments. The tool detected 1411 snoRNA fragment conservation events between 2/4 eukaryotic species, providing the opportunity to explore motifs and fragmentation patterns not only within species, but between. Availability: https://github.com/kenminsoo/sRNAfrag.

Insight on Non-Coding RNAs from Biofluids in Ovarian Tumors

Ovarian tumors are the most frequent adnexal mass, raising diagnostic and therapeutic issues linked to a large spectrum of tumors, with a continuum from benign to malignant. Thus far, none of the available diagnostic tools have proven efficient in deciding strategy, and no consensus exists on the best strategy between "single test", "dual testing", "sequential testing", "multiple testing options" and "no testing". In addition, there is a need for prognostic tools such as biological markers of recurrence and theragnostic tools to detect women not responding to chemotherapy in order to adapt therapies. Non-coding RNAs are classified as small or long based on their nucleotide count. Non-coding RNAs have multiple biological functions such as a role in tumorigenesis, gene regulation and genome protection. These ncRNAs emerge as new potential tools to differentiate benign from malignant tumors and to evaluate prognostic and theragnostic factors. In the specific setting of ovarian tumors, the goal of the present work is to offer an insight into the contribution of biofluid non-coding RNAs (ncRNA) expression.

Sorting nexins: role in the regulation of blood pressure

Sorting nexins (SNXs) are a family of proteins that regulate cellular cargo sorting and trafficking, maintain intracellular protein homeostasis, and participate in intracellular signaling. SNXs are also important in the regulation of blood pressure via several mechanisms. Aberrant expression and dysfunction of SNXs participate in the dysregulation of blood pressure. Genetic studies show a correlation between SNX gene variants and the response to antihypertensive drugs. In this review, we summarize the progress in SNX-mediated regulation of blood pressure, discuss the potential role of SNXs in the pathophysiology and treatment of hypertension, and propose novel strategies for the medical therapy of hypertension.

HITS-CLIP analysis of human ALKBH8 reveals interactions with fully processed substrate tRNAs and with specific noncoding RNAs

Transfer RNAs acquire a large plethora of chemical modifications. Among those, modifications of the anticodon loop play important roles in translational fidelity and tRNA stability. Four human wobble U-containing tRNAs obtain 5-methoxycarbonylmethyluridine (mcm5U34) or 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2U34), which play a role in decoding. This mark involves a cascade of enzymatic activities. The last step is mediated by alkylation repair homolog 8 (ALKBH8). In this study, we performed a transcriptome-wide analysis of the repertoire of ALKBH8 RNA targets. Using a combination of HITS-CLIP and RIP-seq analyses, we uncover ALKBH8-bound RNAs. We show that ALKBH8 targets fully processed and CCA modified tRNAs. Our analyses uncovered the previously known set of wobble U-containing tRNAs. In addition, both our approaches revealed ALKBH8 binding to several other types of noncoding RNAs, in particular C/D box snoRNAs.

Atypical U3 snoRNA Suppresses the Process of Pterygium Through Modulating 18S Ribosomal RNA Synthesis

Background

The progression and recurrence of pterygium mainly occur due to the abnormal proliferation and migration of stromal pterygium fibroblasts. This research explores the aberrant expression of small nucleolar RNA U3 (U3 snoRNA) in pterygium and elucidates the molecular mechanisms of U3 snoRNA in pterygium development.

Methods

Primary human conjunctival fibroblasts (HCFs) and human pterygium fibroblasts (HPFs) were separated and cultured from fresh conjunctiva grafts and pterygium tissues. The PLKO.1 lentiviral system and CRISPR/Cas9 recombinant construct were, respectively, used to overexpress and silence U3 snoRNA in HPFs and HCFs for further specific phenotype analysis. RNA-seq and TMT-labeled quantitative protein mass spectrometry were utilized to evaluate the effect of U3 snoRNA on mRNA transcripts and protein synthesis.

Results

Reduced U3 snoRNA in pterygium promotes HCF or HPF cells’ proliferation, migration, and cell cycle but has no significant effect on apoptosis. U3 snoRNA modulates 18S rRNA synthesis through shearing precursor ribosomal RNA 47S rRNA at the 5′ external transcribed spacer (5′ ETS). Moreover, the altered U3 snoRNA causes mRNA and protein differential expression in HCF or HPF cells.

Conclusions

The atypical U3 snoRNA regulates the translation of specific proteins to exert a suppressive function in pterygium through modulating the 18S rRNA synthesis. Here, we uncover a novel insight into U3 snoRNA biology in the development of pterygium.

Ribosome-Associated ncRNAs (rancRNAs) Adjust Translation and Shape Proteomes

The regulation of protein synthesis is of extreme importance for cell survival in challenging environmental conditions. Modulating gene expression at the level of translation allows a swift and low-energy-cost response to external stimuli. In the last decade, an emerging class of regulatory ncRNAs, namely ribosome-associated non-coding RNAs (rancRNAs), has been discovered. These rancRNAs have proven to be efficient players in the regulation of translation as a first wave of stress adaptation by directly targeting the ribosome, the central enzyme of protein production. This underlying principle appears to be highly conserved, since rancRNAs are present in all three domains of life. Here, we review the major findings and mechanistic peculiarities of rancRNAs, a class of transcripts that is providing new and broader perspectives on the complexity of the ribosome and translation regulation.

Identification of a novel nine-SnoRNA signature with potential prognostic and therapeutic value in ovarian cancer

Background

Increasing evidence has been confirmed that small nucleolar RNAs (SnoRNAs) play critical roles in tumorigenesis and exhibit prognostic value in clinical practice. However, there is short of systematic research on SnoRNAs in ovarian cancer (OV).

Material/Methods

379 OV patients with RNA‐Seq and clinical parameters from TCGA database and 5 paired clinical OV tissues were embedded in our study. Cox regression analysis was used to identify prognostic SnoRNAs and construct prediction model. SNORic database was adopted to examine the copy number variation of SnoRNAs. ROC curves and KM plot curves were applied to validate the prognostic model. Besides, the model was validated in 5 paired clinical tissues by real‐time PCR, H&E staining and immunohistochemistry.

Results

A prognostic model was constructed on the basis of SnoRNAs in OV patients. Patients with higher RiskScore had poor clinicopathological parameters, including higher age, larger tumor size, advanced stage and with tumor status. KM plot analysis confirmed that patients with higher RiskScore had poorer prognosis in subgroup of age, tumor size, and stage. 7 of 9 SnoRNAs in the prognostic model had positive correlation with their host genes. Moreover, 5 of 9 SnoRNAs in the prognostic model correlated with their CNVs, and SNORD105B had the strongest correction with its CNVs. ROC curve showed that the RiskScore had excellent specificity and accuracy. Further, results of H&E staining and immunohistochemistry of Ki67, P53 and P16 confirmed that patients with higher RiskScore are more malignant.

Conclusions

In summary, we identified a nine‐SnoRNAs signature as an independent indicator to predict prognosis of OV, providing a prospective prognostic biomarker and potential therapeutic targets for ovarian cancer.

Protein-RNA Interactome Analysis Reveals Wide Association of Kaposi's Sarcoma-Associated Herpesvirus ORF57 with Host Noncoding RNAs and Polysomes

Kaposi's sarcoma-associated herpesvirus (KSHV) ORF57 is an RNA-binding posttranscriptional regulator. We recently applied an affinity-purified anti-ORF57 antibody to conduct ORF57 cross-linking immunoprecipitation (CLIP) in combination with RNA-sequencing (CLIP-seq) and analyzed the genome-wide host RNA transcripts in association with ORF57 in BCBL-1 cells with lytic KSHV infection. Mapping of the CLIP RNA reads to the human genome (GRCh37) revealed that most of the ORF57-associated RNA reads were from rRNAs. The remaining RNA reads mapped to several classes of host noncoding and protein-coding mRNAs. We found that ORF57 binds and regulates expression of a subset of host long noncoding RNAs (lncRNAs), including LINC00324, LINC00355, and LINC00839, which are involved in cell growth. ORF57 binds small nucleolar RNAs (snoRNAs) responsible for 18S and 28S rRNA modifications but does not interact with fibrillarin or NOP58. We validated ORF57 interactions with 67 snoRNAs by ORF57 RNA immunoprecipitation (RIP)-snoRNA array assays. Most of the identified ORF57 rRNA binding sites (BS) overlap the sites binding snoRNAs. We confirmed ORF57-snoRA71B RNA interaction in BCBL-1 cells by ORF57 RIP and Northern blot analyses using a 32P-labeled oligonucleotide probe from the 18S rRNA region complementary to snoRA71B. Using RNA oligonucleotides from the rRNA regions that ORF57 binds for oligonucleotide pulldown-Western blot assays, we selectively verified ORF57 interactions with 5.8S and 18S rRNAs. Polysome profiling revealed that ORF57 associates with both monosomes and polysomes and that its association with polysomes increases PABPC1 binding to polysomes but prevents Ago2 association with polysomes. Our data indicate a functional correlation with ORF57 binding and suppression of Ago2 activities for ORF57 promotion of gene expression. IMPORTANCE As an RNA-binding protein, KSHV ORF57 regulates RNA splicing, stability, and translation and inhibits host innate immunity by blocking the formation of RNA granules in virus-infected cells. In this study, ORF57 was found to interact with many host noncoding RNAs, including lncRNAs, snoRNAs, and rRNAs, to carry out additional unknown functions. ORF57 binds a group of lncRNAs via the RNA motifs identified by ORF57 CLIP-seq to regulate their expression. ORF57 associates with snoRNAs independently of fibrillarin and NOP58 proteins and with rRNA in the regions that commonly bind snoRNAs. Knockdown of fibrillarin expression decreases the expression of snoRNAs and CDK4 but does not affect viral gene expression. More importantly, we found that ORF57 binds translationally active polysomes and enhances PABPC1 but prevents Ago2 association with polysomes. Data provide compelling evidence on how ORF57 in KSHV-infected cells might regulate protein synthesis by blocking Ago2's hostile activities on translation.

Towards an integrative understanding of cancer mechanobiology: calcium, YAP, and microRNA under biophysical forces

An increasing number of studies have demonstrated the significant roles of the interplay between microenvironmental mechanics in tissues and biochemical-genetic activities in resident tumor cells at different stages of tumor progression. Mediated by molecular mechano-sensors or -transducers, biomechanical cues in tissue microenvironments are transmitted into the tumor cells and regulate biochemical responses and gene expression through mechanotransduction processes. However, the molecular interplay between the mechanotransduction processes and intracellular biochemical signaling pathways remains elusive. This paper reviews the recent advances in understanding the crosstalk between biomechanical cues and three critical biochemical effectors during tumor progression: calcium ions (Ca²⁺), yes-associated protein (YAP), and microRNAs (miRNAs). We address the molecular mechanisms underpinning the interplay between the mechanotransduction pathways and each of the three effectors. Furthermore, we discuss the functional interactions among the three effectors in the context of soft matter and mechanobiology. We conclude by proposing future directions on studying the tumor mechanobiology that can employ Ca²⁺, YAP, and miRNAs as novel strategies for cancer mechanotheraputics. This framework has the potential to bring insights into the development of novel next-generation cancer therapies to suppress and treat tumors.

The RNA methyltransferase METTL8 installs m3C32 in mitochondrial tRNAsThr/Ser(UCN) to optimise tRNA structure and mitochondrial translation

Modified nucleotides in tRNAs are important determinants of folding, structure and function. Here we identify METTL8 as a mitochondrial matrix protein and active RNA methyltransferase responsible for installing m3C32 in the human mitochondrial (mt-)tRNAThr and mt-tRNASer(UCN). METTL8 crosslinks to the anticodon stem loop (ASL) of many mt-tRNAs in cells, raising the question of how methylation target specificity is achieved. Dissection of mt-tRNA recognition elements revealed U34G35 and t6A37/(ms2)i6A37, present concomitantly only in the ASLs of the two substrate mt-tRNAs, as key determinants for METTL8-mediated methylation of C32. Several lines of evidence demonstrate the influence of U34, G35, and the m3C32 and t6A37/(ms2)i6A37 modifications in mt-tRNAThr/Ser(UCN) on the structure of these mt-tRNAs. Although mt-tRNAThr/Ser(UCN) lacking METTL8-mediated m3C32 are efficiently aminoacylated and associate with mitochondrial ribosomes, mitochondrial translation is mildly impaired by lack of METTL8. Together these results define the cellular targets of METTL8 and shed new light on the role of m3C32 within mt-tRNAs.

The role of OncoSnoRNAs and Ribosomal RNA 2'-O-methylation in Cancer

Ribosomes are essential nanomachines responsible for all protein production in cells. Ribosome biogenesis and function are energy costly processes, they are tightly regulated to match cellular needs. In cancer, major pathways that control ribosome biogenesis and function are often deregulated to ensure cell survival and to accommodate the continuous proliferation of tumour cells. Ribosomal RNAs (rRNAs) are abundantly modified with 2'-O-methylation (Nm, ribomethylation) being one of the most common modifications. In eukaryotic ribosomes, ribomethylation is performed by the methyltransferase Fibrillarin guided by box C/D small nucleolar RNAs (snoRNAs). Accumulating evidences indicate that snoRNA expression and ribosome methylation profiles are altered in cancer. Here we review our current knowledge on differential snoRNA expression and rRNA 2ʹ-O methylation in the context of human malignancies, and discuss the consequences and opportunities for cancer diagnostics, prognostics, and therapeutics.

piRNA-IPdb: a PIWI-bound piRNAs database to mining NGS sncRNA data and beyond

Background

PIWI-interacting RNAs (piRNAs) are an abundant single-stranded type of small non-coding RNAs (sncRNAs), which initially were discovered in gonadal cells, with a role as defenders of genomic integrity in the germline, acting against the transposable elements. With a regular size range of 21-35 nt, piRNAs are associated with a PIWI-clade of Argonaute family proteins. The most widely accepted mechanisms of biogenesis for piRNAs involve the transcription of longer precursors of RNAs to be processed, by complexes of proteins, to functional size, preferentially accommodating uridine residues at the 5’ end and 3’ methylation to increase the stability of these molecules. piRNAs have also been detected in somatic cells, with diverse potential functions, indicating their high plasticity and pleiotropic activity. Discovered about two decades ago, piRNAs are a large and versatile type of sncRNA and that remain insufficiently identified and analyzed, through next-generation sequencing (NGS), to evaluate their processing, functions, and biogenesis in different cell types and during development. piRNAs’ distinction from other sncRNAs has led to controversial results and interpretation difficulties when using existing databases because of the heterogeneity of the criteria used in making the distinction.

Description

We present “piRNA-IPdb”, a database based uniquely on datasets obtaining after the defining characteristic of piRNAs: those small RNAs bound to PIWI proteins. We selected and analyzed sequences from piRBase that exclusively cover the binding to PIWI. We pooled a total of 18,821,815 sequences from RNA-seq after immunoprecipitation that included the binding to any of the mouse PIWI proteins (MILI, MIWI, or MIWI2).

Conclusions

In summary, we present the characteristics and potential use of piRNA-IPdb database for the analysis of bona fide piRNAs.

A noncanonical microRNA derived from the snaR-A noncoding RNA targets a metastasis inhibitor

MicroRNAs (miRNAs) are small noncoding RNAs that function as critical posttranscriptional regulators in various biological processes. While most miRNAs are generated from processing of long primary transcripts via sequential Drosha and Dicer cleavage, some miRNAs that bypass Drosha cleavage can be transcribed as part of another small noncoding RNA. Here, we develop the target-oriented miRNA discovery (TOMiD) bioinformatic analysis method to identify Drosha-independent miRNAs from Argonaute crosslinking and sequencing of hybrids (Ago-CLASH) data sets. Using this technique, we discovered a novel miRNA derived from a primate specific noncoding RNA, the small NF90 associated RNA A (snaR-A). The miRNA derived from snaR-A (miR-snaR) arises independently of Drosha processing but requires Exportin-5 and Dicer for biogenesis. We identify that miR-snaR is concurrently up-regulated with the full snaR-A transcript in cancer cells. Functionally, miR-snaR associates with Ago proteins and targets NME1, a key metastasis inhibitor, contributing to snaR-A's role in promoting cancer cell migration. Our findings suggest a functional link between a novel miRNA and its precursor noncoding RNA.

Emerging Data on the Diversity of Molecular Mechanisms Involving C/D snoRNAs

Box C/D small nucleolar RNAs (C/D snoRNAs) represent an ancient family of small non-coding RNAs that are classically viewed as housekeeping guides for the 2′-O-methylation of ribosomal RNA in Archaea and Eukaryotes. However, an extensive set of studies now argues that they are involved in mechanisms that go well beyond this function. Here, we present these pieces of evidence in light of the current comprehension of the molecular mechanisms that control C/D snoRNA expression and function. From this inventory emerges that an accurate description of these activities at a molecular level is required to let the snoRNA field enter in a second age of maturity.