Cerina: systematic circRNA functional annotation based on integrative analysis of ceRNA interactions

COL: a pipeline for identifying putatively functional back-splicing

Circular RNAs (circRNAs) are a class of generally non-coding RNAs produced by back- splicing. Although the vast majority of circRNAs are likely to be products of splicing error and thereby confer no benefits to organisms, a small number of circRNAs have been found to be functional. Identifying other functional circRNAs from the sea of mostly non-functional circRNAs is an important but difficult task. Because available experimental methods for this purpose are of low throughput or versality and existing computational methods have limited reliability or applicability, new methods are needed. We hypothesize that functional back- splicing events that generate functional circRNAs (i) exhibit substantially higher back-splicing rates than expected from the total splicing amounts, (ii) have conserved splicing motifs, and (iii) show unusually high back-splicing levels. We confirm these features in back-splicing shared among human, macaque, and mouse, which should enrich functional back-splicing. Integrating the three features, we design a computational pipeline named COL for identifying putatively functional back-splicing. Different from the methods that require multiple samples, COL can predict functional back-splicing using a single sample. Under the same data requirement, COL has a lower false positive rate than that of the commonly used method that is based on the back- splicing level alone. We conclude that COL is an efficient and versatile method for rapid identification of putatively functional back-splicing and circRNAs that can be experimentally validated. COL is available at https://github.com/XuLabSJTU/COL .

Brain-Derived Exosomal CircRNAs in Plasma Serve as Diagnostic Biomarkers for Acute Ischemic Stroke

Acute ischemic stroke (AIS), commonly known as stroke, is a debilitating condition characterized by the interruption of blood flow to the brain, resulting in tissue damage and neurological deficits. Early diagnosis is crucial for effective intervention and management, as timely treatment can significantly improve patient outcomes. Therefore, novel methods for the early diagnosis of AIS are urgently needed. Several studies have shown that bioactive molecules contained in extracellular vesicles, especially circRNAs, could be ideal markers for the diagnosis of many diseases. However, studies on the effects of exosomes and their circRNAs on the development and prognosis of AIS have not been reported extensively. Therefore, we explored the feasibility of using circRNAs in plasma brain-derived exosomes as biomarkers for AIS. By high-throughput sequencing, we first identified 358 dysregulated circRNAs (including 23 significantly upregulated circRNAs and 335 significantly downregulated circRNAs) in the plasma brain-derived exosomes of the brain infarct patient group compared to those of the noninfarct control group. Five upregulated circRNAs (hsa_circ_0007290, hsa_circ_0049637, hsa_circ_0000607, hsa_circ_0004808, and hsa_circ_0000097) were selected for further validation via Real-Time Quantitative Reverse Transcription PCR (qRT‒PCR) in a larger cohort based on the exclusion criteria of log2FC > 1, p < 0.05 and measurable expression. We found that the expression levels of hsa_circ_0007290, hsa_circ_0049637, hsa_circ_0000607, hsa_circ_0004808 and hsa_circ_0000097 were significantly upregulated in AIS patients and could serve as potential biomarkers for AIS with high specificity and sensitivity. Moreover, the expression levels of hsa_circ_0007290, hsa_circ_0049637, hsa_circ_0000607, hsa_circ_0004808 and hsa_circ_0000097 were also found to be positively correlated with National Institutes of Health Stroke Scale (NISS) and modified Rankin scale (mRS) scores, which indicated that the presence of these circRNAs in plasma brain-derived exosomes could also determine the progression of AIS.

Cirscan: a shiny application to identify differentially active sponge mechanisms and visualize circRNA-miRNA-mRNA networks

BACKGROUND

Non-coding RNAs represent a large part of the human transcriptome and have been shown to play an important role in disease such as cancer. However, their biological functions are still incompletely understood. Among non-coding RNAs, circular RNAs (circRNAs) have recently been identified for their microRNA (miRNA) sponge function which allows them to modulate the expression of miRNA target genes by taking on the role of competitive endogenous RNAs (ce-circRNAs). Today, most computational tools are not adapted to the search for ce-circRNAs or have not been developed for the search for ce-circRNAs from user's transcriptomic data.

RESULTS

In this study, we present Cirscan (CIRcular RNA Sponge CANdidates), an interactive Shiny application that automatically infers circRNA-miRNA-mRNA networks from human multi-level transcript expression data from two biological conditions (e.g. tumor versus normal conditions in the case of cancer study) in order to identify on a large scale, potential sponge mechanisms active in a specific condition. Cirscan ranks each circRNA-miRNA-mRNA subnetwork according to a sponge score that integrates multiple criteria based on interaction reliability and expression level. Finally, the top ranked sponge mechanisms can be visualized as networks and an enrichment analysis is performed to help its biological interpretation. We showed on two real case studies that Cirscan is capable of retrieving sponge mechanisms previously described, as well as identifying potential novel circRNA sponge candidates.

CONCLUSIONS

Cirscan can be considered as a companion tool for biologists, facilitating their ability to prioritize sponge mechanisms for experimental validations and identifying potential therapeutic targets. Cirscan is implemented in R, released under the license GPL-3 and accessible on GitLab ( https://gitlab.com/geobioinfo/cirscan_Rshiny ). The scripts used in this paper are also provided on Gitlab ( https://gitlab.com/geobioinfo/cirscan_paper ).

The transcriptomic landscape of neurons carrying PSEN1 mutations reveals changes in extracellular matrix components and non-coding gene expression

Alzheimer's disease (AD) is a progressive and irreversible brain disorder, which can occur either sporadically, due to a complex combination of environmental, genetic, and epigenetic factors, or because of rare genetic variants in specific genes (familial AD, or fAD). A key hallmark of AD is the accumulation of amyloid beta (Aβ) and Tau hyperphosphorylated tangles in the brain, but the underlying pathomechanisms and interdependencies remain poorly understood. Here, we identify and characterise gene expression changes related to two fAD mutations (A79V and L150P) in the Presenilin-1 (PSEN1) gene. We do this by comparing the transcriptomes of glutamatergic forebrain neurons derived from fAD-mutant human induced pluripotent stem cells (hiPSCs) and their individual isogenic controls generated via precision CRISPR/Cas9 genome editing. Our analysis of Poly(A) RNA-seq data detects 1111 differentially expressed coding and non-coding genes significantly altered in fAD. Functional characterisation and pathway analysis of these genes reveal profound expression changes in constituents of the extracellular matrix, important to maintain the morphology, structural integrity, and plasticity of neurons, and in genes involved in calcium homeostasis and mitochondrial oxidative stress. Furthermore, by analysing total RNA-seq data we reveal that 30 out of 31 differentially expressed circular RNA genes are significantly upregulated in the fAD lines, and that these may contribute to the observed protein-coding gene expression changes. The results presented in this study contribute to a better understanding of the cellular mechanisms impacted in AD neurons, ultimately leading to neuronal damage and death.

A Review and In Silico Analysis of Tissue and Exosomal Circular RNAs: Opportunities and Challenges in Thyroid Cancer

Simple Summary

Thyroid cancer is the most common endocrine neoplasm. Recently, knowledge of the molecular genetic changes of thyroid cancer has dramatically improved. Understanding the roles of these molecular changes in thyroid cancer tumorigenesis and progression is essential in developing a successful treatment strategy and improving disease outcomes. As a family of non-coding RNAs, circular RNAs (circRNAs) have been involved in several aspects of the physiological and pathological processes of the cells. The roles of circRNAs in cancer development and progress are evident. In the current review, we aimed to explore the clinical potential of circRNAs as potential diagnostic, prognostic, and therapeutic targets in thyroid cancer. Furthermore, screening the genome-wide circRNAs and performing functional enrichment analyses for all associated dysregulated circRNAs in thyroid cancer have been done. Given the unique advantages circRNAs have, such as superior stability, higher abundance, and presence in different body fluids, this family of non-coding RNAs could be promising diagnostic and prognostic biomarkers and potential therapeutic targets for thyroid cancer.

Abstract

Thyroid cancer (TC) is the most common endocrine tumor. The genetic and epigenetic molecular alterations of TC have become more evident in recent years. However, a deeper understanding of the roles these molecular changes play in TC tumorigenesis and progression is essential in developing a successful treatment strategy and improving patients’ prognoses. Circular RNAs (circRNAs), a family of non-coding RNAs, have been implicated in several aspects of carcinogenesis in multiple cancers, including TC. In the current review, we aimed to explore the clinical potential of circRNAs as putative diagnostic, prognostic, and therapeutic targets in TC. The current analyses, including genome-wide circRNA screening and functional enrichment for all deregulated circRNA expression signatures, show that circRNAs display atypical contributions, such as sponging for microRNAs, regulating transcription and translation processes, and decoying for proteins. Given their exceptional clinical advantages, such as higher stability, wider abundance, and occurrence in several body fluids, circRNAs are promising prognostic and theranostic biomarkers for TC.

circGPA: circRNA functional annotation based on probability-generating functions

Recent research has already shown that circular RNAs (circRNAs) are functional in gene expression regulation and potentially related to diseases. Due to their stability, circRNAs can also be used as biomarkers for diagnosis. However, the function of most circRNAs remains unknown, and it is expensive and time-consuming to discover it through biological experiments. In this paper, we predict circRNA annotations from the knowledge of their interaction with miRNAs and subsequent miRNA-mRNA interactions. First, we construct an interaction network for a target circRNA and secondly spread the information from the network nodes with the known function to the root circRNA node. This idea itself is not new; our main contribution lies in proposing an efficient and exact deterministic procedure based on the principle of probability-generating functions to calculate the p-value of association test between a circRNA and an annotation term. We show that our publicly available algorithm is both more effective and efficient than the commonly used Monte-Carlo sampling approach that may suffer from difficult quantification of sampling convergence and subsequent sampling inefficiency. We experimentally demonstrate that the new approach is two orders of magnitude faster than the Monte-Carlo sampling, which makes summary annotation of large circRNA files feasible; this includes their reannotation after periodical interaction network updates, for example. We provide a summary annotation of a current circRNA database as one of our outputs. The proposed algorithm could be generalized towards other types of RNA in way that is straightforward.

Circ_0058792 regulates osteogenic differentiation through miR-181a-5p/Smad7 axis in steroid-induced osteonecrosis of the femoral head

Osteonecrosis of the femoral head (ONFH) caused by steroids is a severe orthopedic disorder resulting from the use of high-dose steroid drugs, characterized by structural changes in the bone, joint dysfunction, and femoral head collapse. CircRNAs and miRNAs have increasingly been suggested to play pivotal roles in osteogenic differentiation and osteogenesis. Significant upregulation of circ_0058792 was observed in patients with steroid-induced ONFH. Bioinformatic analysis showed that circ_0058792 might act as a sponge for miR-181a-5p. This study further investigated the mechanisms underlying the role of circ_0058792 and miR-181a-5p in osteogenic differentiation in methylprednisolone-induced ONFH rats and MC3T3-E1 cells. The results showed a notable decrease in the serum of miR-181a-5p in methylprednisolone-induced ONFH rats. Silencing of circ_0058792 using siRNAs and overexpression of miR-181a-5p significantly increased alkaline phosphatase activity and matrix mineralization capacity. Additionally, markers for osteogenic differentiation were significantly upregulated in miR-181a-5p-transfected cells. However, overexpression of circ_0058792 and the addition of the miR-181a-5p inhibitor reversed this increase. Smad7 was identified to be miR-181a-5p's direct target and circ_0058792 was confirmed to be miR-181a-5p's competing endogenous RNA (ceRNA). Upregulation of miR-181a-5p promotes phosphorylation of Smad2 and Smad3. Furthermore, circ_0058792 and miR-181a-5p had opposing effects on Smad7 expression. Collectively, these findings indicate that circ_0058792 regulates osteogenic differentiation by sponging miR-181a-5p via the TGF-β/Smad7 pathway. These findings elucidated the functions of circ_0058792 and miR-181a-5p in the regulation of steroid-induced ONFH. Our findings also indicated that circ_0058792 and miR-181a-5p are possible diagnostic markers and therapeutic targets for treating steroid-induced ONFH.

CRAFT: a bioinformatics software for custom prediction of circular RNA functions

Circular RNAs (circRNAs), transcripts generated by backsplicing, are particularly stable and pleiotropic molecules, whose dysregulation drives human diseases and cancer by modulating gene expression and signaling pathways. CircRNAs can regulate cellular processes by different mechanisms, including interaction with microRNAs (miRNAs) and RNA-binding proteins (RBP), and encoding specific peptides. The prediction of circRNA functions is instrumental to interpret their impact in diseases, and to prioritize circRNAs for functional investigation. Currently, circRNA functional predictions are provided by web databases that do not allow custom analyses, while self-standing circRNA prediction tools are mostly limited to predict only one type of function, mainly focusing on the miRNA sponge activity of circRNAs. To solve these issues, we developed CRAFT (CircRNA Function prediction Tool), a freely available computational pipeline that predicts circRNA sequence and molecular interactions with miRNAs and RBP, along with their coding potential. Analysis of a set of circRNAs with known functions has been used to appraise CRAFT predictions and to optimize its setting. CRAFT provides a comprehensive graphical visualization of the results, links to several knowledge databases, and extensive functional enrichment analysis. Moreover, it originally combines the predictions for different circRNAs. CRAFT is a useful tool to help the user explore the potential regulatory networks involving the circRNAs of interest and generate hypotheses about the cooperation of circRNAs into the modulation of biological processes.

CircIMPACT: An R Package to Explore Circular RNA Impact on Gene Expression and Pathways

Circular RNAs (circRNAs) are transcripts generated by back-splicing. CircRNAs might regulate cellular processes by different mechanisms, including interaction with miRNAs and RNA-binding proteins. CircRNAs are pleiotropic molecules whose dysregulation has been linked to human diseases and can drive cancer by impacting gene expression and signaling pathways. The detection of circRNAs aberrantly expressed in disease conditions calls for the investigation of their functions. Here, we propose CircIMPACT, a bioinformatics tool for the integrative analysis of circRNA and gene expression data to facilitate the identification and visualization of the genes whose expression varies according to circRNA expression changes. This tool can highlight regulatory axes potentially governed by circRNAs, which can be prioritized for further experimental study. The usefulness of CircIMPACT is exemplified by a case study analysis of bladder cancer RNA-seq data. The link between circHIPK3 and heparanase (HPSE) expression, due to the circHIPK3-miR558-HPSE regulatory axis previously determined by experimental studies on cell lines, was successfully detected. CircIMPACT is freely available at GitHub.

Roles of ncRNAs as ceRNAs in Gastric Cancer

Although ignored in the past, with the recent deepening of research, significant progress has been made in the field of non-coding RNAs (ncRNAs). Accumulating evidence has revealed that microRNA (miRNA) response elements regulate RNA. Long ncRNAs, circular RNAs, pseudogenes, miRNAs, and messenger RNAs (mRNAs) form a competitive endogenous RNA (ceRNA) network that plays an essential role in cancer and cardiovascular, neurodegenerative, and autoimmune diseases. Gastric cancer (GC) is one of the most common cancers, with a high degree of malignancy. Considerable progress has been made in understanding the molecular mechanism and treatment of GC, but GC’s mortality rate is still high. Studies have shown a complex ceRNA crosstalk mechanism in GC. lncRNAs, circRNAs, and pseudogenes can interact with miRNAs to affect mRNA transcription. The study of the involvement of ceRNA in GC could improve our understanding of GC and lead to the identification of potential effective therapeutic targets. The research strategy for ceRNA is mainly to screen the different miRNAs, lncRNAs, circRNAs, pseudogenes, and mRNAs in each sample through microarray or sequencing technology, predict the ceRNA regulatory network, and, finally, conduct functional research on ceRNA. In this review, we briefly discuss the proposal and development of the ceRNA hypothesis and the biological function and principle of ceRNAs in GC, and briefly introduce the role of ncRNAs in the GC’s ceRNA network.

Aberrant Expression of microRNA Clusters in Head and Neck Cancer Development and Progression: Current and Future Translational Impacts

MicroRNAs are small non-coding RNAs known to negative regulate endogenous genes. Some microRNAs have high sequence conservation and localize as clusters in the genome. Their coordination is regulated by simple genetic and epigenetic events mechanism. In cells, single microRNAs can regulate multiple genes and microRNA clusters contain multiple microRNAs. MicroRNAs can be differentially expressed and act as oncogenic or tumor suppressor microRNAs, which are based on the roles of microRNA-regulated genes. It is vital to understand their effects, regulation, and various biological functions under both normal and disease conditions. Head and neck squamous cell carcinomas are some of the leading causes of cancer-related deaths worldwide and are regulated by many factors, including the dysregulation of microRNAs and their clusters. In disease stages, microRNA clusters can potentially control every field of oncogenic function, including growth, proliferation, apoptosis, migration, and intercellular commutation. Furthermore, microRNA clusters are regulated by genetic mutations or translocations, transcription factors, and epigenetic modifications. Additionally, microRNA clusters harbor the potential to act therapeutically against cancer in the future. Here, we review recent advances in microRNA cluster research, especially relative to head and neck cancers, and discuss their regulation and biological functions under pathological conditions as well as translational applications.