snoDB: an interactive database of human snoRNA sequences, abundance and interactions

Small Non-Coding RNAs and Their Role in Locoregional Metastasis and Outcomes in Early-Stage Breast Cancer Patients

Deregulation of small non-coding RNAs (sncRNAs) has been associated with the onset of metastasis. We evaluated the expression of sncRNAs in patients with early-stage breast cancer, performing RNA sequencing in 60 patients for whom tumor and sentinel lymph node (SLN) samples were available, and conducting differential expression, gene ontology, enrichment and survival analyses. Sequencing annotation classified most of the sncRNAs into small nucleolar RNA (snoRNAs, 70%) and small nuclear RNA (snRNA, 13%). Our results showed no significant differences in sncRNA expression between tumor or SLNs obtained from the same patient. Differential expression analysis showed down-regulation (n = 21) sncRNAs and up-regulation (n = 2) sncRNAs in patients with locoregional metastasis. The expression of SNHG5, SNORD90, SCARNA2 and SNORD78 differentiated luminal A from luminal B tumors, whereas SNORD124 up-regulation was associated with luminal B HER2+ tumors. Discriminating analysis and receiver-operating curve analysis revealed a signature of six snoRNAs (SNORD93, SNORA16A, SNORD113-6, SNORA7A, SNORA57 and SNORA18A) that distinguished patients with locoregional metastasis and predicted patient outcome. Gene ontology and Reactome pathway analysis showed an enrichment of biological processes associated with translation initiation, protein targeting to specific cell locations, and positive regulation of Wnt and NOTCH signaling pathways, commonly involved in the promotion of metastases. Our results point to the potential of several sncRNAs as surrogate markers of lymph node metastases and patient outcome in early-stage breast cancer patients. Further preclinical and clinical studies are required to understand the biological significance of the most significant sncRNAs and to validate our results in a larger cohort of patients.

miR-Blood - a small RNA atlas of human blood components

miR-Blood is a high-quality, small RNA expression atlas for the major components of human peripheral blood (plasma, erythrocytes, thrombocytes, monocytes, neutrophils, eosinophils, basophils, natural killer cells, CD4+ T cells, CD8+ T cells, and B cells). Based on the purified blood components from 52 individuals, the dataset provides a comprehensive repository for the expression of 4971 small RNAs from eight non-coding RNA classes.

RMBase v3.0: decode the landscape, mechanisms and functions of RNA modifications

Although over 170 chemical modifications have been identified, their prevalence, mechanism and function remain largely unknown. To enable integrated analysis of diverse RNA modification profiles, we have developed RMBase v3.0 (http://bioinformaticsscience.cn/rmbase/), a comprehensive platform consisting of eight modules. These modules facilitate the exploration of transcriptome-wide landscape, biogenesis, interactome and functions of RNA modifications. By mining thousands of epitranscriptome datasets with novel pipelines, the 'RNA Modifications' module reveals the map of 73 RNA modifications of 62 species. the 'Genes' module allows to retrieve RNA modification profiles and clusters by gene and transcript. The 'Mechanisms' module explores 23 382 enzyme-catalyzed or snoRNA-guided modified sites to elucidate their biogenesis mechanisms. The 'Co-localization' module systematically formulates potential correlations between 14 histone modifications and 6 RNA modifications in various cell-lines. The 'RMP' module investigates the differential expression profiles of 146 RNA-modifying proteins (RMPs) in 18 types of cancers. The 'Interactome' integrates the interactional relationships between 73 RNA modifications with RBP binding events, miRNA targets and SNPs. The 'Motif' illuminates the enriched motifs for 11 types of RNA modifications identified from epitranscriptome datasets. The 'Tools' introduces a novel web-based 'modGeneTool' for annotating modifications. Overall, RMBase v3.0 provides various resources and tools for studying RNA modifications.

NOCICEPTRA2.0 - A comprehensive ncRNA atlas of human native and iPSC-derived sensory neurons

Non-coding RNAs (ncRNAs) are pivotal in gene regulation during development and disease. MicroRNAs have been extensively studied in neurogenesis. However, limited knowledge exists about the developmental signatures of other ncRNA species in sensory neuron differentiation, and human dorsal root ganglia (DRG) ncRNA expression remains undocumented. To address this gap, we generated a comprehensive atlas of small ncRNA species during iPSC-derived sensory neuron differentiation. Utilizing iPSC-derived sensory neurons and human DRG RNA sequencing, we unveiled signatures describing developmental processes. Our analysis identified ncRNAs associated with various sensory neuron stages. Striking similarities in ncRNA expression signatures between human DRG and iPSC-derived neurons support the latter as a model to bridge the translational gap between preclinical findings and human disorders. In summary, our research sheds light on the role of ncRNA species in human nociceptors, and NOCICEPTRA2.0 offers a comprehensive ncRNA database for sensory neurons that researchers can use to explore ncRNA regulators in nociceptors thoroughly.

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.

Early Detection of Lung Cancer Using Small RNAs

INTRODUCTION

Lung cancer remains the deadliest cancer in the world, and lung cancer survival is heavily dependent on tumor stage at the time of detection. Low-dose computed tomography screening can reduce mortality; however, annual screening is limited by low adherence in the United States of America and still not broadly implemented in Europe. As a result, less than 10% of lung cancers are detected through existing programs. Thus, there is a great need for additional screening tests, such as a blood test, that could be deployed in the primary care setting.

METHODS

We prospectively recruited 1384 individuals meeting the National Lung Screening Trial demographic eligibility criteria for lung cancer and collected stabilized whole blood to enable the pipetting-free collection of material, thus minimizing preanalytical noise. Ultra-deep small RNA sequencing (20 million reads per sample) was performed with the addition of a method to remove highly abundant erythroid RNAs, and thus open bandwidth for the detection of less abundant species originating from the plasma or the immune cellular compartment. We used 100 random data splits to train and evaluate an ensemble of logistic regression classifiers using small RNA expression of 943 individuals, discovered an 18-small RNA feature consensus signature (miLung), and validated this signature in an independent cohort (441 individuals). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin.

RESULTS

We generated diagnostic models and report a median receiver-operating characteristic area under the curve of 0.86 (95% confidence interval [CI]: 0.84-0.86) in the discovery cohort and generalized performance of 0.83 in the validation cohort. Diagnostic performance increased in a stage-dependent manner ranging from 0.73 (95% CI: 0.71-0.76) for stage I to 0.90 (95% CI: 0.89-0.90) for stage IV in the discovery cohort and from 0.76 to 0.86 in the validation cohort. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased after surgery with curative intent. In additional experiments, results of dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted through home sampling.

CONCLUSIONS

These data suggest the potential of a small RNA-based blood test as a viable alternative to low-dose computed tomography screening for early detection of smoking-associated lung cancer.

RNA interaction format: a general data format for RNA interactions

SUMMARY

RNA molecules play crucial roles in various biological processes. They mediate their function mainly by interacting with other RNAs or proteins. At present, information about these interactions is distributed over different resources, often providing the data in simple tab-delimited formats that differ between the databases. There is no standardized data format that can capture the nature of all these different interactions in detail.

AVAILABILITY AND IMPLEMENTATION

Here, we propose the RNA interaction format (RIF) for the detailed representation of RNA-RNA and RNA-Protein interactions and provide reference implementations in C/C++, Python, and JavaScript. RIF is released under licence GNU General Public License version 3 (GNU GPLv3) and is available on https://github.com/RNABioInfo/rna-interaction-format.

A snoRNA-tRNA modification network governs codon-biased cellular states

The dynamic balance between tRNA supply and codon usage demand is a fundamental principle in the cellular translation economy. However, the regulation and functional consequences of this balance remain unclear. Here, we use PARIS2 interactome capture, structure modeling, conservation analysis, RNA-protein interaction analysis, and modification mapping to reveal the targets of hundreds of snoRNAs, many of which were previously considered orphans. We identify a snoRNA-tRNA interaction network that is required for global tRNA modifications, including 2'-O-methylation and others. Loss of Fibrillarin, the snoRNA-guided 2'-O-methyltransferase, induces global upregulation of tRNA fragments, a large group of regulatory RNAs. In particular, the snoRNAs D97/D133 guide the 2'-O-methylation of multiple tRNAs, especially for the amino acid methionine (Met), a protein-intrinsic antioxidant. Loss of D97/D133 snoRNAs in human HEK293 cells reduced target tRNA levels and induced codon adaptation of the transcriptome and translatome. Both single and double knockouts of D97 and D133 in HEK293 cells suppress Met-enriched proliferation-related gene expression programs, including, translation, splicing, and mitochondrial energy metabolism, and promote Met-depleted programs related to development, differentiation, and morphogenesis. In a mouse embryonic stem cell model of development, knockdown and knockout of D97/D133 promote differentiation to mesoderm and endoderm fates, such as cardiomyocytes, without compromising pluripotency, consistent with the enhanced development-related gene expression programs in human cells. This work solves a decades-old mystery about orphan snoRNAs and reveals a function of snoRNAs in controlling the codon-biased dichotomous cellular states of proliferation and development.

SNORD11B-mediated 2'-O-methylation of primary let-7a in colorectal carcinogenesis

Evidence indicates that small nucleolar RNAs (snoRNAs) participate in tumorigenesis and development and could be promising biomarkers for colorectal cancer (CRC). Here, we examine the profile of snoRNAs in CRC and find that expression of SNORD11B is increased in CRC tumor tissues and cell lines, with a significant positive correlation between SNORD11B expression and that of its host gene NOP58. SNORD11B promotes CRC cell proliferation and invasion and inhibits apoptosis. Mechanistically, SNORD11B promotes the processing and maturation of 18 S ribosomal RNA (rRNA) by mediating 2'-O-methylated (Nm) modification on the G509 site of 18 S rRNA. Intriguingly, SNORD11B mediates Nm modification on the G225 site of MIRLET7A1HG (pri-let-7a) with a canonical motif, resulting in degradation of pri-let-7a, inhibition of DGCR8 binding, reduction in mature tumor suppressor gene let-7a-5p expression, and upregulation of downstream oncogene translation. SNORD11B performs comparably to CEA and CA199 in diagnosing CRC. High expression of SNORD11B is significantly correlated with a more advanced TNM stage and lymph node metastasis, which indicates poor prognosis.

iSnoDi-MDRF: Identifying snoRNA-Disease Associations Based on Multiple Biological Data by Ranking Framework

Accumulating evidence indicates that the dysregulation of small nucleolar RNAs (snoRNAs) is relevant with diseases. Identifying snoRNA-disease associations by computational methods is desired for biologists, which can save considerable costs and time compared biological experiments. However, it still faces some challenges as followings: (i) Many snoRNAs are detected in recent years, but only a few snoRNAs have been proved to be associated with diseases; (ii) Computational predictors trained with only a few known snoRNA-disease associations fail to accurately identify the snoRNA-disease associations. In this study, we propose a ranking framework, called iSnoDi-MDRF, to identify potential snoRNA-disease associations based on multiple biological data, which has the following highlights: (i) iSnoDi-MDRF integrates ranking framework, which is not only able to identify potential associations between known snoRNAs and diseases, but also can identify diseases associated with new snoRNAs. (ii) Known gene-disease associations are employed to help train a mature model for predicting snoRNA-disease association. Experimental results illustrate that iSnoDi-MDRF is very suitable for identifying potential snoRNA-disease associations. The web server of iSnoDi-MDRF predictor is freely available at http://bliulab.net/iSnoDi-MDRF/.

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.

Interrogating colorectal cancer metastasis to liver: a search for clinically viable compounds and mechanistic insights in colorectal cancer Patient Derived Organoids

BACKGROUND

Approximately 20-50% of patients presenting with localized colorectal cancer progress to stage IV metastatic disease (mCRC) following initial treatment and this is a major prognostic determinant. Here, we have interrogated a heterogeneous set of primary colorectal cancer (CRC), liver CRC metastases and adjacent liver tissue to identify molecular determinants of the colon to liver spreading. Screening Food and Drug Administration (FDA) approved drugs for their ability to interfere with an identified colon to liver metastasis signature may help filling an unmet therapeutic need.

METHODS

RNA sequencing of primary colorectal cancer specimens vs adjacent liver tissue vs synchronous and asynchronous liver metastases. Pathways enrichment analyses. The Library of Integrated Network-based Cellular Signatures (LINCS)-based and Connectivity Map (CMAP)-mediated identification of FDA-approved compounds capable to interfere with a 22 gene signature from primary CRC and liver metastases. Testing the identified compounds on CRC-Patient Derived Organoid (PDO) cultures. Microscopy and Fluorescence Activated Cell Sorting (FACS) based analysis of the treated PDOs.

RESULTS

We have found that liver metastases acquire features of the adjacent liver tissue while partially losing those of the primary tumors they derived from. We have identified a 22-gene signature differentially expressed among primary tumors and metastases and validated in public databases. A pharmacogenomic screening for FDA-approved compounds capable of interfering with this signature has been performed. We have validated some of the identified representative compounds in CRC-Patient Derived Organoid cultures (PDOs) and found that pentoxyfilline and, to a minor extent, dexketoprofen and desloratadine, can variably interfere with number, size and viability of the CRC -PDOs in a patient-specific way. We explored the pentoxifylline mechanism of action and found that pentoxifylline treatment attenuated the 5-FU elicited increase of ALDHhigh cells by attenuating the IL-6 mediated STAT3 (tyr705) phosphorylation.

CONCLUSIONS

Pentoxifylline synergizes with 5-Fluorouracil (5-FU) in attenuating organoid formation. It does so by interfering with an IL-6-STAT3 axis leading to the emergence of chemoresistant ALDHhigh cell subpopulations in 5-FU treated PDOs. A larger cohort of CRC-PDOs will be required to validate and expand on the findings of this proof-of-concept study.

LINC01137/miR-186-5p/WWOX: a novel axis identified from WWOX-related RNA interactome in bladder cancer

Introduction: The discovery of non-coding RNA (ncRNA) dates back to the pre-genomics era, but the progress in this field is still dynamic and leverages current post-genomics solutions. WWOX is a global gene expression modulator that is scarcely investigated for its role in regulating cancer-related ncRNAs. In bladder cancer (BLCA), the link between WWOX and ncRNA remains unexplored. The description of AP-2α and AP-2γ transcription factors, known as WWOX-interacting proteins, is more commonplace regarding ncRNA but still merits investigation. Therefore, this in vitro and in silico study aimed to construct an ncRNA-containing network with WWOX/AP-2 and to investigate the most relevant observation in the context of BLCA cell lines and patients. Methods: RT-112, HT-1376, and CAL-29 cell lines were subjected to two stable lentiviral transductions. High-throughput sequencing of cellular variants (deposited in the Gene Expression Omnibus database under the GSE193659 record) enabled the investigation of WWOX/AP-2-dependent differences using various bioinformatics tools (e.g., limma-voom, FactoMineR, multiple Support Vector Machine Recursive Feature Elimination (mSVM-RFE), miRDB, Arena-Idb, ncFANs, RNAhybrid, TargetScan, Protein Annotation Through Evolutionary Relationships (PANTHER), Gene Transcription Regulation Database (GTRD), or Evaluate Cutpoints) and repositories such as The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia. The most relevant observations from cap analysis gene expression sequencing (CAGE-seq) were confirmed using real-time PCR, whereas TCGA data were validated using the GSE31684 cohort. Results: The first stage of the whole study justified focusing solely on WWOX rather than on WWOX combined with AP-2α/γ. The most relevant observation of the developed ncRNA-containing network was LINC01137, i.e., long non-coding RNAs (lncRNAs) that unraveled the core network containing UPF1, ZC3H12A, LINC01137, WWOX, and miR-186-5p, the last three being a novel lncRNA/miRNA/mRNA axis. Patients' data confirmed the LINC01137/miR-186-5p/WWOX relationship and provided a set of dependent genes (i.e., KRT18, HES1, VCP, FTH1, IFITM3, RAB34, and CLU). Together with the core network, the gene set was subjected to survival analysis for both TCGA-BLCA and GSE31684 patients, which indicated that the increased expression of WWOX or LINC01137 is favorable, similar to their combination with each other (WWOX↑ and LINC01137↑) or with MIR186 (WWOX↑/LINC01137↑ but MIR186↓). Conclusion: WWOX is implicated in the positive feedback loop with LINC01137 that sponges WWOX-targeting miR-186-5p. This novel WWOX-containing lncRNA/miRNA/mRNA axis should be further investigated to depict its relationships in a broader context, which could contribute to BLCA research and treatment.

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.

Characterization and evaluation of gene fusions as a measure of genetic instability and disease prognosis in prostate cancer

BACKGROUND

Prostate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression.

METHODS

We analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan-Meier estimator, log-rank test, and Cox regression.

RESULTS

Our analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR. These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05).

CONCLUSIONS

Our gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

Analyzing roles of small nucleolar RNA host gene 25 from clinical, molecular target and tumor formation in prostate cancer

BACKGROUND

Prostate cancer (PCa) is one of the most deadly and metastatic cancers of the urinary tract. Latest studies have confirmed that long non-coding RNAs (lncRNAs) play a crucial role in a variety of cancers. Some of these lncRNAs code for small nucleolar RNAs (snoRNAs), called small nucleolar RNA host genes (SNHGs), which exert some value in predicting the prognosis of certain cancer patients, but little is known regarding the function of SNHGs within the PCa.

AIM OF THE STUDY

To explore the expression distribution and differential analysis of SNHGs in different tumors using RNA-seq and survival data from TCGA and GTEx, and to assess the potential impacts of the lncRNA SNHG25 on human PCa. To validate the expression of SNHG25 using experimental data and to investigate in detail its particular molecular biological function on PCa both in vivo and in vitro.

METHODS

LncRNA SNHG25 expression was analyzed by bioinformatic prediction and qPCR. CCK-8, EdU, transwell, wound healing, and western blotting assays were conducted to investigate the main role of lncRNA SNHG25 in PCa. Xenograft tumour growth model in nude mice was surveyed by in vivo imaging and Ki-67 staining. AKT pathway activator (SC79) was used to verify the interaction among SNHG25 and PI3K/AKT signaling pathway.

RESULTS

Bioinformatics analysis and experimental research illuminated that the expression of lncRNA SNHG25 was observably up-regulated in PCa tissues and cells. Moreover, SNHG25 knockdown restrained PCa cell proliferation, invasion and migration, while promoting apoptosis. Xenografts model confirmed that the si-SNHG25 group had a significant inhibitory effect on PCa tumour growth in vivo. Additionally, a series of gain-of-function analyses suggested that SNHG25 could activate the PI3K/AKT pathway to accelerate PCa progression.

CONCLUSIONS

These in vitro and in vivo findings demonstrate that SNHG25 is highly expressed in PCa and facilitates PCa development through regulation of PI3K/AKT signaling pathway. SNHG25 acts as an oncogene to predict tumour malignancy and survival in PCa patients and may therefore become a promising potential molecular target for early detection and therapy of lethal PCa.

The axis of complement C1 and nucleolus in antinuclear autoimmunity

Antinuclear autoantibodies (ANA) are heterogeneous self-reactive antibodies that target the chromatin network, the speckled, the nucleoli, and other nuclear regions. The immunological aberration for ANA production remains partially understood, but ANA are known to be pathogenic, especially, in systemic lupus erythematosus (SLE). Most SLE patients exhibit a highly polygenic disease involving multiple organs, but in rare complement C1q, C1r, or C1s deficiencies, the disease can become largely monogenic. Increasing evidence point to intrinsic autoimmunogenicity of the nuclei. Necrotic cells release fragmented chromatins as nucleosomes and the alarmin HMGB1 is associated with the nucleosomes to activate TLRs and confer anti-chromatin autoimmunogenecity. In speckled regions, the major ANA targets Sm/RNP and SSA/Ro contain snRNAs that confer autoimmunogenecity to Sm/RNP and SSA/Ro antigens. Recently, three GAR/RGG-containing alarmins have been identified in the nucleolus that helps explain its high autoimmunogenicity. Interestingly, C1q binds to the nucleoli exposed by necrotic cells to cause protease C1r and C1s activation. C1s cleaves HMGB1 to inactive its alarmin activity. C1 proteases also degrade many nucleolar autoantigens including nucleolin, a major GAR/RGG-containing autoantigen and alarmin. It appears that the different nuclear regions are intrinsically autoimmunogenic by containing autoantigens and alarmins. However, the extracellular complement C1 complex function to dampen nuclear autoimmunogenecity by degrading these nuclear proteins.

Small Nucleolar (Sno)RNA: Therapy Lays in Translation

The ribosome is one of the largest complexes in the cell. Adding to its complexity are more than 200 RNA modification sites present on ribosomal RNAs (rRNAs) in a single human ribosome. These modifications occur in functionally important regions of the rRNA molecule, and they are vital for ribosome function and proper gene expression. Until recent technological advancements, the study of rRNA modifications and their profiles has been extremely laborious, leaving many questions unanswered. Small nucleolar RNAs (snoRNAs) are non-coding RNAs that facilitate and dictate the specificity of rRNA modification deposition, making them an attractive target for ribosome modulation. Here, we propose that through the mapping of rRNA modification profiles, we can identify cell-specific modifications with high therapeutic potential. We also describe the challenges of achieving the targeting specificity needed to implement snoRNAs as therapeutic targets in cancers.

The emerging diagnostic and therapeutic roles of small nucleolar RNAs in lung diseases

Small nucleolar RNAs (snoRNAs) are non-coding RNA molecules that range from 60 to 300 nucleotides in length and are primarily located in the nucleoli of cells. They play a critical role in modifying ribosomal RNA and can also regulate alternative splicing and posttranscriptional modification of mRNA. Alterations in snoRNA expression can affect numerous cellular processes, including cell proliferation, apoptosis, angiogenesis, fibrosis, and inflammation, making them a promising target for diagnostics and treatment of various human pathologies. Recent evidence suggests that abnormal snoRNA expression is strongly associated with the development and progression of several lung diseases, such as lung cancer, asthma, chronic obstructive pulmonary disease, and pulmonary hypertension, as well as COVID-19. While few studies have shown a causal relationship between snoRNA expression and disease onset, this research field presents exciting opportunities for identifying new biomarkers and therapeutic targets in lung disease. This review discusses the emerging role and molecular mechanisms of snoRNAs in the pathogenesis of lung diseases, focusing on research opportunities, clinical studies, biomarkers, and therapeutic potential.

FUS regulates a subset of snoRNA expression and modulates the level of rRNA modifications

FUS is a multifunctional protein involved in many aspects of RNA metabolism, including transcription, splicing, translation, miRNA processing, and replication-dependent histone gene expression. In this work, we show that FUS depletion results in the differential expression of numerous small nucleolar RNAs (snoRNAs) that guide 2'-O methylation (2'-O-Me) and pseudouridylation of specific positions in ribosomal RNAs (rRNAs) and small nuclear RNAs (snRNAs). Using RiboMeth-seq and HydraPsiSeq for the profiling of 2'-O-Me and pseudouridylation status of rRNA species, we demonstrated considerable hypermodification at several sites in HEK293T and SH-SY5Y cells with FUS knockout (FUS KO) compared to wild-type cells. We observed a similar direction of changes in rRNA modification in differentiated SH-SY5Y cells with the FUS mutation (R495X) related to the severe disease phenotype of amyotrophic lateral sclerosis (ALS). Furthermore, the pattern of modification of some rRNA positions was correlated with the abundance of corresponding guide snoRNAs in FUS KO and FUS R495X cells. Our findings reveal a new role for FUS in modulating the modification pattern of rRNA molecules, that in turn might generate ribosome heterogeneity and constitute a fine-tuning mechanism for translation efficiency/fidelity. Therefore, we suggest that increased levels of 2'-O-Me and pseudouridylation at particular positions in rRNAs from cells with the ALS-linked FUS mutation may represent a possible new translation-related mechanism that underlies disease development and progression.

Evidence for Existence of Multiple Functional Human Small RNAs Derived from Transcripts of Protein-Coding Genes

The human genome encodes a multitude of different noncoding transcripts that have been traditionally separated on the basis of their lengths into long (>200 nt) or small (<200 nt) noncoding RNAs. The functions, mechanisms of action, and biological relevance of the vast majority of both long and short noncoding transcripts remain unknown. However, according to the functional understanding of the known classes of long and small noncoding RNAs (sncRNAs) that have been shown to play crucial roles in multiple biological processes, it is generally assumed that many unannotated long and small transcripts participate in important cellular functions as well. Nevertheless, direct evidence of functionality is lacking for most noncoding transcripts, especially for sncRNAs that are often dismissed as stable degradation products of longer RNAs. Here, we developed a high-throughput assay to test the functionality of sncRNAs by overexpressing them in human cells. Surprisingly, we found that a significant fraction (>40%) of unannotated sncRNAs appear to have biological relevance. Furthermore, contrary to the expectation, the potentially functional transcripts are not highly abundant and can be derived from protein-coding mRNAs. These results strongly suggest that the small noncoding transcriptome can harbor multiple functional transcripts that warrant future studies.

SNORA14A inhibits hepatoblastoma cell proliferation by regulating SDHB-mediated succinate metabolism

Hepatoblastoma (HB) is the most common paediatric liver malignancy. Dysregulation of small nucleolar RNAs (snoRNAs) is a critical inducer of tumour initiation and progression. However, the association between snoRNAs and HB remains unknown. Here, we conducted snoRNA expression profiling in HB by snoRNA sequencing and identified a decreased level of SNORA14A, a box H/ACA snoRNA, in HB tissues. Low expression of SNORA14A was correlated with PRETEXT stage and metastasis in patients. Functionally, overexpression of SNORA14A suppressed HB cell proliferation and triggered cell apoptosis and G2/M phase arrest. Mechanistically, SNORA14A overexpression promoted the processing and maturation of the 18 S ribosomal RNA (rRNA) precursor to increase succinate dehydrogenase subunit B (SDHB) protein levels. In accordance with SNORA14A downregulation, SDHB protein expression was significantly reduced in HB tissues and cells, accompanied by abnormal accumulation of succinate. Overexpression of SDHB showed antiproliferative and proapoptotic effects and the capacity to induce G2/M phase arrest, while succinate dose-dependently stimulated HB cell growth. Furthermore, the inhibition of SNORA14A in HB malignant phenotypes was mediated by SDHB upregulation-induced reduction of cellular succinate levels. Therefore, the SNORA14A/18 S rRNA/SDHB axis suppresses HB progression by preventing cellular accumulation of the oncometabolite succinate and provides promising prognostic biomarkers and novel therapeutic targets for HB.

Maturation of small nucleolar RNAs: from production to function

Small Nucleolar RNAs (snoRNAs) are an abundant group of non-coding RNAs with well-defined roles in ribosomal RNA processing, folding and chemical modification. Besides their classic roles in ribosome biogenesis, snoRNAs are also implicated in several other cellular activities including regulation of splicing, transcription, RNA editing, cellular trafficking, and miRNA-like functions. Mature snoRNAs must undergo a series of processing steps tightly regulated by transiently associating factors and coordinated with other cellular processes including transcription and splicing. In addition to their mature forms, snoRNAs can contribute to gene expression regulation through their derivatives and degradation products. Here, we review the current knowledge on mechanisms of snoRNA maturation, including the different pathways of processing, and the regulatory mechanisms that control snoRNA levels and complex assembly. We also discuss the significance of studying snoRNA maturation, highlight the gaps in the current knowledge and suggest directions for future research in this area.

Non-coding RNAs in immunoregulation and autoimmunity: Technological advances and critical limitations

Immune cell function is critically dependent on precise control over transcriptional output from the genome. In this respect, integration of environmental signals that regulate gene expression, specifically by transcription factors, enhancer DNA elements, genome topography and non-coding RNAs (ncRNAs), are key components. The first three have been extensively investigated. Even though non-coding RNAs represent the vast majority of cellular RNA species, this class of RNA remains historically understudied. This is partly because of a lag in technological and bioinformatic innovations specifically capable of identifying and accurately measuring their expression. Nevertheless, recent progress in this domain has enabled a profusion of publications identifying novel sub-types of ncRNAs and studies directly addressing the function of ncRNAs in human health and disease. Many ncRNAs, including circular and enhancer RNAs, have now been demonstrated to play key functions in the regulation of immune cells and to show associations with immune-mediated diseases. Some ncRNAs may function as biomarkers of disease, aiding in diagnostics and in estimating response to treatment, while others may play a direct role in the pathogenesis of disease. Importantly, some are relatively stable and are amenable to therapeutic targeting, for example through gene therapy. Here, we provide an overview of ncRNAs and review technological advances that enable their study and hold substantial promise for the future. We provide context-specific examples by examining the associations of ncRNAs with four prototypical human autoimmune diseases, specifically rheumatoid arthritis, psoriasis, inflammatory bowel disease and multiple sclerosis. We anticipate that the utility and mechanistic roles of these ncRNAs in autoimmunity will be further elucidated in the near future.

iSnoDi-LSGT: identifying snoRNA-disease associations based on local similarity constraints and global topological constraints

Growing evidence proves that small nucleolar RNAs (snoRNAs) have important functions in various biological processes, the malfunction of which leads to the emergence and development of complex diseases. However, identifying snoRNA-disease associations is an ongoing challenging task due to the considerable time- and money-consuming biological experiments. Therefore, it is urgent to design efficient and economical methods for the identification of snoRNA-disease associations. In this regard, we propose a computational method named iSnoDi-LSGT, which utilizes snoRNA sequence similarity and disease similarity as local similarity constraints. The iSnoDi-LSGT predictor further employs network embedding technology to extract topological features of snoRNAs and diseases, based on which snoRNA topological similarity and disease topological similarity are calculated as global topological constraints. To the best of our knowledge, the iSnoDi-LSGT is the first computational method for snoRNA-disease association identification. The experimental results indicate that the iSnoDi-LSGT predictor can effectively predict unknown snoRNA-disease associations. The web server of the iSnoDi-LSGT predictor is freely available at http://bliulab.net/iSnoDi-LSGT.

Analysis of Expression Pattern of snoRNAs in Human Cells A549 Infected by Influenza A Virus

Small nucleolar RNAs (snoRNAs) are a highly expressed class of non-coding RNAs known for their role in guiding post-transcriptional modifications of ribosomal RNAs and small nuclear RNAs. Emerging studies suggest that snoRNAs are also implicated in regulating other vital cellular processes, such as pre-mRNA splicing and 3'-processing of mRNAs, and in the development of cancer and viral infections. There is an emerging body of evidence for specific snoRNA's involvement in the optimal replication of RNA viruses. In order to investigate the expression pattern of snoRNAs during influenza A viral infection, we performed RNA sequencing analysis of the A549 human cell line infected by influenza virus A/Puerto Rico/8/1934 (H1N1). We identified 66 that were upregulated and 55 that were downregulated in response to influenza A virus infection. The increased expression of most C/D-box snoRNAs was associated with elevated levels of 5'- and 3'-short RNAs derived from this snoRNA. Analysis of the poly(A)+ RNA sequencing data indicated that most of the differentially expressed snoRNAs synthesis was not correlated with the corresponding host genes expression. Furthermore, influenza A viral infection led to an imbalance in the expression of genes responsible for C/D small nucleolar ribonucleoprotein particles' biogenesis. In summary, our results indicate that the expression pattern of snoRNAs in A549 cells is significantly altered during influenza A viral infection.

Single-base resolution mapping of 2′-O-methylation sites by an exoribonuclease-enriched chemical method

2'-O-methylation (Nm) is one of the most abundant RNA epigenetic modifications and plays a vital role in the post-transcriptional regulation of gene expression. Current Nm mapping approaches are normally limited to highly abundant RNAs and have significant technical hurdles in mRNAs or relatively rare non-coding RNAs (ncRNAs). Here, we developed a new method for enriching Nm sites by using RNA exoribonuclease and periodate oxidation reactivity to eliminate 2'-hydroxylated (2'-OH) nucleosides, coupled with sequencing (Nm-REP-seq). We revealed several novel classes of Nm-containing ncRNAs as well as mRNAs in humans, mice, and drosophila. We found that some novel Nm sites are present at fixed positions in different tRNAs and are potential substrates of fibrillarin (FBL) methyltransferase mediated by snoRNAs. Importantly, we discovered, for the first time, that Nm located at the 3'-end of various types of ncRNAs and fragments derived from them. Our approach precisely redefines the genome-wide distribution of Nm and provides new technologies for functional studies of Nm-mediated gene regulation.

Comprehensive characterization of RNA cargo of extracellular vesicles in breast cancer patients undergoing neoadjuvant chemotherapy

Extracellular vesicles (EVs) are g7aining increased attention as carriers of cancer-derived molecules for liquid biopsies. Here, we studied the dynamics of EV levels in the plasma of breast cancer (BC) patients undergoing neoadjuvant chemotherapy (NAC) and explored the relevance of their RNA cargo for the prediction of patients' response to the therapy. EVs were isolated from serial blood samples collected at the time of diagnosis, at the end of NAC, and 7 days, 6, and 12 months after the surgery from 32 patients with locally advanced BC, and 30 cancer-free healthy controls (HCs) and quantified by nanoparticle tracking analysis. The pre-treatment levels of EVs in BC patients were higher than in HCs, significantly increased during the NAC and surgery, and decreased to the levels found in HCs 6 months after surgery, thus showing that a substantial fraction of plasma EVs in BC patients are produced due to the disease processes and treatment. RNA sequencing analysis revealed that the changes in the EV levels were associated with the alterations in the proportions of various RNA biotypes in EVs. To search for RNA biomarkers that predict response to the NAC, patients were dichotomized as responders and non-responders based on Miller-Payne grades and differential expression analyses were carried out between responders and non-responders, and HCs. This resulted in the identification of 6 miRNAs, 4 lncRNAs, and 1 snoRNA that had significantly higher levels in EVs from non-responders than responders at the time of diagnosis and throughout the NAC, and significantly lower levels in HCs, thus representing biomarkers for the prediction of response to NAC at the time of diagnosis. In addition, we found 14 RNAs representing piRNA, miRNA, lncRNA, snoRNA, and snRNA biotypes that were induced by NAC in non-responders and 2 snoRNAs and 1 piRNA that were induced by NAC in patients with early disease progression, thus warranting further functional studies on their role in chemoresistance and metastasis.

Circulating U13 Small Nucleolar RNA as a Potential Biomarker in Huntington's Disease: A Pilot Study

Plasma small RNAs have been recently explored as biomarkers in Huntington’s disease (HD). We performed an exploratory study on nine HD patients, eight healthy subjects (HS), and five psychiatric patients (PP; to control for iatrogenic confounder effects) through an Affymetrix-Gene-Chip-miRNA-Array. We validated the results in an independent population of 23 HD, 15 pre-HD, 24 PP, 28 Alzheimer’s disease (AD) patients (to control the disease-specificity) and 22 HS through real-time PCR. The microarray results showed higher levels of U13 small nucleolar RNA (SNORD13) in HD patients than controls (fold change 1.54, p = 0.003 HD vs. HS, and 1.44, p = 0.0026 HD vs. PP). In the validation population, a significant increase emerged with respect to both pre-HD and the control groups (p < 0.0001). SNORD13 correlated with the status of the mutant huntingtin carrier (r = 0.73; p < 0.001) and the disease duration (r = 0.59; p = 0.003). The receiver operating characteristic (ROC) curve analysis showed the high accuracy of SNORD13 in discriminating HD patients from other groups (AUC = 0.963). An interactome and pathway analysis on SNORD13 revealed enrichments for factors relevant to HD pathogenesis. We report the unprecedented finding of a potential disease-specific role of SNORD13 in HD. It seems to peripherally report a ‘tipping point’ in the pathogenic cascade at the neuronal level.

snoDB 2.0: an enhanced interactive database, specializing in human snoRNAs

snoDB is an interactive database of human small nucleolar RNAs (snoRNAs) that includes up-to-date information on snoRNA features, genomic location, conservation, host gene, snoRNA-RNA targets and snoRNA abundance and provides links to other resources. In the second edition of this database (snoDB 2.0), we added an entirely new section on ribosomal RNA (rRNA) chemical modifications guided by snoRNAs with easy navigation between the different rRNA versions used in the literature and experimentally measured levels of modification. We also included new layers of information, including snoRNA motifs, secondary structure prediction, snoRNA-protein interactions, copy annotations and low structure bias expression data in a wide panel of tissues and cell lines to bolster functional probing of snoRNA biology. Version 2.0 features updated identifiers, more links to external resources and duplicate entry resolution. As a result, snoDB 2.0, which is freely available at https://bioinfo-scottgroup.med.usherbrooke.ca/snoDB/, represents a one-stop shop for snoRNA features, rRNA modification targets, functional impact and potential regulators.

Small Nucleolar RNAs and Their Comprehensive Biological Functions in Hepatocellular Carcinoma

Small nucleolar RNAs (snoRNAs) are a class of highly conserved, stable non-coding RNAs involved in both post-transcriptional modification of RNA and in ribosome biogenesis. Recent research shows that the dysfunction of snoRNAs plays a pivotal role in hepatocellular carcinoma (HCC) and related etiologies, such as hepatitis B virus (HBV), hepatitis C virus (HCV), and non-alcoholic fatty liver disease (NAFLD). Growing evidence suggests that snoRNAs act as oncogenes or tumor suppressors in hepatocellular carcinoma (HCC) through multiple mechanisms. Furthermore, snoRNAs are characterized by their stability in body fluids and their clinical relevance and represent promising tools as diagnostic and prognostic biomarkers. SnoRNAs represent an emerging area of cancer research. In this review, we summarize the classification, biogenesis, activity, and functions of snoRNAs, as well as highlight the mechanism and roles of snoRNAs in HCC and related diseases. Our findings will aid in the understanding of complex processes of tumor occurrence and development, as well as suggest potential diagnostic markers and treatment targets. Furthermore, we discuss several limitations and suggest future research and application directions.

Dysregulation of Small Nucleolar RNAs in B-Cell Malignancies

Small nucleolar RNAs (snoRNAs) are responsible for post-transcriptional modification of ribosomal RNAs, transfer RNAs and small nuclear RNAs, and thereby have important regulatory functions in mRNA splicing and protein translation. Several studies have shown that snoRNAs are dysregulated in human cancer and may play a role in cancer initiation and progression. In this review, we focus on the role of snoRNAs in normal and malignant B-cell development. SnoRNA activity appears to be essential for normal B-cell differentiation and dysregulated expression of sno-RNAs is determined in B-cell acute lymphoblastic leukemia, chronic lymphocytic leukemia, B-cell non-Hodgkin’s lymphoma, and plasma cell neoplasms. SnoRNA expression is associated with cytogenetic/molecular subgroups and clinical outcome in patients with B-cell malignancies. Translocations involving snoRNAs have been described as well. Here, we discuss the different aspects of snoRNAs in B-cell malignancies and report on their role in oncogenic transformation, which may be useful for the development of novel diagnostic biomarkers or therapeutic targets.

Small RNA Sequencing in the Tg4–42 Mouse Model Suggests the Involvement of snoRNAs in the Etiology of Alzheimer’s Disease

Background: The Tg4-42 mouse model for sporadic Alzheimer’s disease (AD) has unique features, as the neuronal expression of wild type N-truncated Aβ4–42 induces an AD-typical neurological phenotype in the absence of plaques. It is one of the few models developing neuron death in the CA1 region of the hippocampus. As such, it could serve as a powerful tool for preclinical drug testing and identification of the underlying molecular pathways that drive the pathology of AD. Objective: The aim of this study was to use a differential co-expression analysis approach for analyzing a small RNA sequencing dataset from a well-established murine model in order to identify potentially new players in the etiology of AD. Methods: To investigate small nucleolar RNAs in the hippocampus of Tg4-42 mice, we used RNA-Seq data from this particular tissue and, instead of analyzing the data at single gene level, employed differential co-expression analysis, which takes the comparison to gene pair level and thus affords a new angle to the interpretation of these data. Results: We identified two clusters of differentially correlated small RNAs, including Snord55, Snord57, Snord49a, Snord12, Snord38a, Snord99, Snord87, Mir1981, Mir106b, Mir30d, Mir598, and Mir99b. Interestingly, some of them have been reported to be functionally relevant in AD pathogenesis, as AD biomarkers, regulating tau phosphorylation, TGF-β receptor function or Aβ metabolism. Conclusion: The majority of snoRNAs for which our results suggest a potential role in the etiology of AD were so far not conspicuously implicated in the context of AD pathogenesis and could thus point towards interesting new avenues of research in this field.

Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease

The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.

Aberrantly Expressed Small Noncoding RNAome in Keloid Skin Tissue

The skin is an organ that protects against injury and infection but can be damaged easily. Wound healing is a subtle balance which, if broken, can lead to keloid formation. Small noncoding (nc) RNAs can be of “housekeeping,” for example, ribosomal RNAs and transfer RNAs, or “regulatory,” for example, microRNAs (miRNAs or miRs), small nucleolar RNAs (snoRNAs), and P-element–induced Wimpy testis (PIWI)-interacting RNA (piRNA) types. We examined five types of small ncRNAs [miR, piRNA, snoRNA, small nuclear (sn) RNA, and repeat-associated small interfering RNA (rasiRNA)] in keloid skin tissue (KST) using sequencing and real-time reverse transcription-quantitative polymerase chain reaction. All comparisons were made in relation to expression in normal skin tissue (obtained by abdominoplasty). The expression of three piRNAs was upregulated, and the expression of six piRNAs was downregulated in KST. The expression of 12 snoRNAs was upregulated, and the expression of two snoRNAs was downregulated in KST. The expression of two snRNAs was downregulated in KST. The expression of 18 miRs was upregulated, and the expression of three miRNAs was downregulated in KST. The expression of one rasiRNA was upregulated, and the expression of one rasiRNA was downregulated in KST. We revealed the differential expression of small ncRNAs in KST, which may aid the development of new treatment for keloids.

The Potential Role of Small Nucleolar RNAs in Cancers – An Evidence Map

Purpose

Cancer seriously endangers human health in every country of the world. New evidence shows that small nucleolar RNAs play important roles in tumorigenesis. Herein, we created this evidence map to systematically assess the impact of dysregulated snoRNAs on cancers.

Methods

We searched four databases to February 2022 using the keywords, “carcinoma”, “neoplasms”, “tumor”, “cancer”, “snoRNA”, and “small nucleolar rna”. The research data were independently screened by two reviewers. Bubble plot, mind map, heatmap were used to depict the relationship between snoRNAs and cancers.

Results

In total, 102 studies met the inclusion criteria and were analyzed in this evidence map. In this study, we found that dysregulated snoRNAs were statistically associated with the clinicopathological characteristics of cancer patients, and affected tumor cell phenotypes. Abnormally expressed snoRNAs were associated with poor survival in cancer patients. Current research confirmed that snoRNAs have good diagnostic efficiency for cancers. snoRNAs could modulate biological processes and signaling pathways of different cancer cells by altering rRNA, regulating mRNA, and recruiting protein factors.

Conclusion

Taken all together, ectopic snoRNAs may serve as new biomarkers for clinical assessment, diagnostic, prognostic prediction of cancer patients, and provide a potential therapeutic strategy for cancer treatment. This article provided a visual analysis of existing evidence on snoRNAs and cancers, which can offer useful information for different researchers interested in snoRNAs.

Epigenetic regulation of human non-coding RNA gene transcription

Recent investigations on the non-protein-coding transcriptome of human cells have revealed previously hidden layers of gene regulation relying on regulatory non-protein-coding (nc) RNAs, including the widespread ncRNA-dependent regulation of epigenetic chromatin states and of mRNA translation and stability. However, despite its centrality, the epigenetic regulation of ncRNA genes has received relatively little attention. In this mini-review, we attempt to provide a synthetic account of recent literature suggesting an unexpected complexity in chromatin-dependent regulation of ncRNA gene transcription by the three human nuclear RNA polymerases. Emerging common features, like the heterogeneity of chromatin states within ncRNA multigene families and their influence on 3D genome organization, point to unexplored issues whose investigation could lead to a better understanding of the whole human epigenomic network.

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.

Protein-RNA interactome analysis reveals wide association of KSHV ORF57 with host non-coding RNAs and polysomes

Kaposi's sarcoma-associated herpesvirus (KSHV) ORF57 is an RNA-binding post-transcriptional regulator. We recently applied an affinity-purified anti-ORF57 antibody to conduct ORF57-CLIP (Cross-linking Immunoprecipitation) 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 CLIPed 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 non-coding and protein-coding mRNAs. We found ORF57 binds and regulates expression of a subset of host lncRNAs, including LINC00324, LINC00355, and LINC00839 which are involved in cell growth. ORF57 binds snoRNAs responsible for 18S and 28S rRNA modifications, but does not interact with fibrillarin and 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 with 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 oligo probe from the 18S rRNA region complementary to snoRA71B. Using RNA oligos from the rRNA regions that ORF57 binds for oligo 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 its association with polysomes increases PABPC1 binding to, but prevent Ago2 from polysomes. Our data indicate a functional correlation with ORF57 binding and suppression of Ago2 activities for ORF57 promotion of gene expression. Significance 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 report, ORF57 was found to interact many host non-coding RNAs, including lncRNAs, snoRNAs and ribosomal RNAs to carry out additional unknown functions. ORF57 binds a group of lncRNAs via the identified RNA motifs by ORF57 CLIP-seq to regulate their expression. ORF57 associates with snoRNAs independently of fibrillarin and NOP58 proteins, and with ribosomal RNA in the regions that commonly bind snoRNAs. Knockdown of fibrillarin expression decreases the expression of snoRNAs and CDK4, but not affect viral gene expression. More importantly, we found that ORF57 binds translationally active polysomes and enhances PABPC-1 but prevents Ago2 association with polysomes. Data provide a compelling evidence on how ORF57 in KSHV infected cells might regulate protein synthesis by blocking Ago2's hostile activities on translation.

Hybridization-proximity labeling reveals spatially ordered interactions of nuclear RNA compartments

The ability of RNAs to form specific contacts with other macromolecules provides an important mechanism for subcellular compartmentalization. Here we describe a suite of hybridization-proximity (HyPro) labeling technologies for unbiased discovery of proteins (HyPro-MS) and transcripts (HyPro-seq) associated with RNAs of interest in genetically unperturbed cells. As a proof of principle, we show that HyPro-MS and HyPro-seq can identify both known and previously unexplored spatial neighbors of the noncoding RNAs 45S, NEAT1, and PNCTR expressed at markedly different levels. Notably, HyPro-seq uncovers an extensive repertoire of incompletely processed, adenosine-to-inosine-edited transcripts accumulating at the interface between their encoding chromosomal regions and the NEAT1-containing paraspeckle compartment. At least some of these targets require NEAT1 for their optimal expression. Overall, this study provides a versatile toolkit for dissecting RNA interactomes in diverse biomedical contexts and expands our understanding of the functional architecture of the mammalian nucleus.

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HyPro labeling uncovers interactors and spatial neighbors of RNAs of interest

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Protein and RNA partners are identified by mass spectrometry and deep sequencing

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No genetic modifications are required, allowing wider biomedical use

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Interactomes of RNA-containing nuclear bodies are mapped as a proof of principle

Small nucleolar RNAs in plasma extracellular vesicles and their discriminatory power as diagnostic biomarkers of Alzheimer's disease

The clinical diagnosis of Alzheimer's disease, at its early stage, remains a difficult task. Advanced imaging technologies and laboratory assays to detect Aβ peptides Aβ42 and Aβ40, total and phosphorylated tau in CSF provide a set of biomarkers of developing AD brain pathology and facilitate the diagnostic process. The search for biofluid biomarkers, other than in CSF, and the development of biomarker assays have accelerated significantly and now represent the fastest-growing field in AD research. The goal of this study was to determine the differential enrichment of noncoding RNAs (ncRNAs) in plasma-derived extracellular vesicles (EV) of AD patients and Cognitively Normal controls (NC). Using RNA-seq, we profiled four significant classes of ncRNAs: miRNAs, snoRNAs, tRNAs, and piRNAs. We report a significant enrichment of SNORDs - a group of snoRNAs, in AD samples compared to NC. To verify the differential enrichment of two clusters of SNORDs - SNORD115 and SNORD116, localized on human chromosome 15q11-q13, we used plasma samples of an independent group of AD patients and NC. We applied ddPCR technique and identified SNORD115 and SNORD116 with a high discriminatory power to differentiate AD samples from NC. The results of our study present evidence that AD is associated with changes in the enrichment of SNORDs, transcribed from imprinted genomic loci, in plasma EV and provide a rationale to further explore the validity of those SNORDs as plasma biomarkers of AD.

Advances in Non-Coding RNA Sequencing

Non-coding RNAs (ncRNAs) comprise a set of abundant and functionally diverse RNA molecules. Since the discovery of the first ncRNA in the 1960s, ncRNAs have been shown to be involved in nearly all steps of the central dogma of molecular biology. In recent years, the pace of discovery of novel ncRNAs and their cellular roles has been greatly accelerated by high-throughput sequencing. Advances in sequencing technology, library preparation protocols as well as computational biology helped to greatly expand our knowledge of which ncRNAs exist throughout the kingdoms of life. Moreover, RNA sequencing revealed crucial roles of many ncRNAs in human health and disease. In this review, we discuss the most recent methodological advancements in the rapidly evolving field of high-throughput sequencing and how it has greatly expanded our understanding of ncRNA biology across a large number of different organisms.

SDE2 is an essential gene required for ribosome biogenesis and the regulation of alternative splicing

RNA provides the framework for the assembly of some of the most intricate macromolecular complexes within the cell, including the spliceosome and the mature ribosome. The assembly of these complexes relies on the coordinated association of RNA with hundreds of trans-acting protein factors. While some of these trans-acting factors are RNA-binding proteins (RBPs), others are adaptor proteins, and others still, function as both. Defects in the assembly of these complexes results in a number of human pathologies including neurodegeneration and cancer. Here, we demonstrate that Silencing Defective 2 (SDE2) is both an RNA binding protein and also a trans-acting adaptor protein that functions to regulate RNA splicing and ribosome biogenesis. SDE2 depletion leads to widespread changes in alternative splicing, defects in ribosome biogenesis and ultimately complete loss of cell viability. Our data highlight SDE2 as a previously uncharacterized essential gene required for the assembly and maturation of the complexes that carry out two of the most fundamental processes in mammalian cells.

Systematic Identification and Functional Validation of New snoRNAs in Human Muscle Progenitors

Small non-coding RNAs (sncRNAs) represent an important class of regulatory RNAs involved in the regulation of transcription, RNA splicing or translation. Among these sncRNAs, small nucleolar RNAs (snoRNAs) mostly originate from intron splicing in humans and are central to posttranscriptional regulation of gene expression. However, the characterization of the complete repertoire of sncRNAs in a given cellular context and the functional annotation of the human transcriptome are far from complete. Here, we report the large-scale identification of sncRNAs in the size range of 50 to 200 nucleotides without a priori on their biogenesis, structure and genomic origin in the context of normal human muscle cells. We provided a complete set of experimental validation of novel candidate snoRNAs by evaluating the prerequisites for their biogenesis and functionality, leading to their validation as genuine snoRNAs. Interestingly, we also found intergenic snoRNAs, which we showed are in fact integrated into candidate introns of unannotated transcripts or degraded by the Nonsense Mediated Decay pathway. Hence, intergenic snoRNAs represent a new type of landmark for the identification of new transcripts that have gone undetected because of low abundance or degradation after the release of the snoRNA.

SnoRNA in Cancer Progression, Metastasis and Immunotherapy Response

Simple Summary

A much larger number of small nucleolar RNA (snoRNA) have been found encoded within our genomes than we ever expected to see. The activities of the snoRNAs were thought restricted to the nucleolus, where they were first discovered. Now, however, their significant number suggests that their functions are more diverse. Studies in cancers have shown snoRNA levels to associate with different stages of disease progression, including with metastasis. In addition, relationships between snoRNA levels and response to immunotherapies, have been reported. Emerging technologies now allow snoRNA to be targeted directly in cancers, and the therapeutic value of this is being explored.

Abstract

Small nucleolar RNA (snoRNA) were one of our earliest recognised classes of non-coding RNA, but were largely ignored by cancer investigators due to an assumption that their activities were confined to the nucleolus. However, as full genome sequences have become available, many new snoRNA genes have been identified, and multiple studies have shown their functions to be diverse. The consensus now is that many snoRNA are dysregulated in cancers, are differentially expressed between cancer types, stages and metastases, and they can actively modify disease progression. In addition, the regulation of the snoRNA class is dominated by the cancer-supporting mTOR signalling pathway, and they may have particular significance to immune cell function and anti-tumour immune responses. Given the recent advent of therapeutics that can target RNA molecules, snoRNA have robust potential as drug targets, either solely or in the context of immunotherapies.

Biomolecule and Bioentity Interaction Databases in Systems Biology: A Comprehensive Review

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology.

EVAtlas: a comprehensive database for ncRNA expression in human extracellular vesicles

Extracellular vesicles (EVs) packing various molecules play vital roles in intercellular communication. Non-coding RNAs (ncRNAs) are important functional molecules and biomarkers in EVs. A comprehensive investigation of ncRNAs expression in EVs under different conditions is a fundamental step for functional discovery and application of EVs. Here, we curated 2030 small RNA-seq datasets for human EVs (1506 sEV and 524 lEV) in 24 conditions and over 40 diseases. We performed a unified reads dynamic assignment algorithm (RDAA) considering mismatch and multi-mapping reads to quantify the expression profiles of seven ncRNA types (miRNA, snoRNA, piRNA, snRNA, rRNA, tRNA and Y RNA). We constructed EVAtlas (http://bioinfo.life.hust.edu.cn/EVAtlas), a comprehensive database for ncRNA expression in EVs with four functional modules: (i) browse and compare the distribution of ncRNAs in EVs from 24 conditions and eight sources (plasma, serum, saliva, urine, sperm, breast milk, primary cell and cell line); (ii) prioritize candidate ncRNAs in condition related tissues based on their expression; (iii) explore the specifically expressed ncRNAs in EVs from 24 conditions; (iv) investigate ncRNA functions, related drugs, target genes and EVs isolation methods. EVAtlas contains the most comprehensive ncRNA expression in EVs and will be a key resource in this field.

RNAnue: efficient data analysis for RNA-RNA interactomics

RNA–RNA inter- and intramolecular interactions are fundamental for numerous biological processes. While there are reasonable approaches to map RNA secondary structures genome-wide, understanding how different RNAs interact to carry out their regulatory functions requires mapping of intermolecular base pairs. Recently, different strategies to detect RNA–RNA duplexes in living cells, so called direct duplex detection (DDD) methods, have been developed. Common to all is the Psoralen-mediated in vivo RNA crosslinking followed by RNA Proximity Ligation to join the two interacting RNA strands. Sequencing of the RNA via classical RNA-seq and subsequent specialised bioinformatic analyses the result in the prediction of inter- and intramolecular RNA–RNA interactions. Existing approaches adapt standard RNA-seq analysis pipelines, but often neglect inherent features of RNA–RNA interactions that are useful for filtering and statistical assessment. Here we present RNAnue, a general pipeline for the inference of RNA–RNA interactions from DDD experiments that takes into account hybridisation potential and statistical significance to improve prediction accuracy. We applied RNAnue to data from different DDD studies and compared our results to those of the original methods. This showed that RNAnue performs better in terms of quantity and quality of predictions.

Evolutionary conservation in noncoding genomic regions

Humans may share more genomic commonalities with other species than previously thought. According to current estimates, ~5% of the human genome is functionally constrained, which is a much larger fraction than the ~1.5% occupied by annotated protein-coding genes. Hence, ~3.5% of the human genome comprises likely functional conserved noncoding elements (CNEs) preserved among organisms, whose common ancestors existed throughout hundreds of millions of years of evolution. As whole-genome sequencing emerges as a standard procedure in genetic analyses, interpretation of variations in CNEs, including the elucidation of mechanistic and functional roles, becomes a necessity. Here, we discuss the phenomenon of noncoding conservation via four dimensions (sequence, regulatory conservation, spatiotemporal expression, and structure) and the potential significance of CNEs in phenotype variation and disease.