Circular RNA repertoires are associated with evolutionarily young transposable elements

Multi-tissue transcriptome profiling linked the association between tissue-specific circRNAs and the heterosis for feed intake and efficiency in chicken

Heterosis has been widely utilized in chickens. The nonadditive inheritance of genes contributes to this biological phenomenon. However, the role of circRNAs played in the heterosis is poorly determined. In this study, we observed divergent heterosis for residual feed intake (RFI) between 2 crossbreds derived from a reciprocal cross between White Leghorns and Beijing You chickens. Then, circRNA landscape for 120 samples covering the hypothalamus, liver, duodenum mucosa and ovary were profiled to elucidate the regulatory mechanisms of heterosis. We detected that a small proportion of circRNAs (7.83-20.35%) were additively and non-additively expressed, in which non-additivity was a major inheritance of circRNAs in the crossbreds. Tissue-specific expression of circRNAs was prevalent across 4 tissues. Weighted gene co-expression network analysis revealed circRNA-mRNA co-expression modules associated with feed intake and RFI in the hypothalamus and liver, and the co-expressed genes were enriched in oxidative phosphorylation pathway. We further identified 8 nonadditive circRNAs highly correlated with 16 nonadditive genes regulating negative heterosis for RFI in the 2 tissues. Circ-ITSN2 was validated in the liver tissue for its significantly positive correlation with PGPEP1L. Moreover, the bioinformatic analysis indicated that candidate circRNAs might be functioned by binding the microRNAs and interacting with the RNA binding proteins. The integration of multi-tissue transcriptome firstly linked the association between tissue-specific circRNAs and the heterosis for feed intake and efficiency in chicken, which provide novel insights into the molecular mechanism underlying heterosis for feed efficiency. The validated circRNAs can act as potential biomarkers for predicting RFI and its heterosis.

Circular RNA regulatory role in pathological cardiac remodelling

Cardiac remodelling involves structural, cellular and molecular alterations in the heart after injury, resulting in progressive loss of heart function and ultimately leading to heart failure. Circular RNAs (circRNAs) are a recently rediscovered class of non-coding RNAs that play regulatory roles in the pathogenesis of cardiovascular diseases, including heart failure. Thus, a more comprehensive understanding of the role of circRNAs in the processes governing cardiac remodelling may set the ground for the development of circRNA-based diagnostic and therapeutic strategies. In this review, the current knowledge about circRNA origin, conservation, characteristics and function is summarized. Bioinformatics and wet-lab methods used in circRNA research are discussed. The regulatory function of circRNAs in cardiac remodelling mechanisms such as cell death, cardiomyocyte hypertrophy, inflammation, fibrosis and metabolism is highlighted. Finally, key challenges and opportunities in circRNA research are discussed, and orientations for future work to address the pharmacological potential of circRNAs in heart failure are proposed.

Transcriptome- and proteome-wide effects of a circular RNA encompassing four early exons of the spinal muscular atrophy genes

Spinal muscular atrophy (SMA) genes, SMN1 and SMN2 (hereinafter referred to as SMN1/2), produce multiple circular RNAs (circRNAs), including C2A-2B-3-4 that encompasses early exons 2A, 2B, 3 and 4. C2A-2B-3-4 is a universally and abundantly expressed circRNA of SMN1/2. Here we report the transcriptome- and proteome-wide effects of overexpression of C2A-2B-3-4 in inducible HEK293 cells. Our RNA-Seq analysis revealed altered expression of ~ 15% genes (4172 genes) by C2A-2B-3-4. About half of the affected genes by C2A-2B-3-4 remained unaffected by L2A-2B-3-4, a linear transcript encompassing exons 2A, 2B, 3 and 4 of SMN1/2. These findings underscore the unique role of the structural context of C2A-2B-3-4 in gene regulation. A surprisingly high number of upregulated genes by C2A-2B-3-4 were located on chromosomes 4 and 7, whereas many of the downregulated genes were located on chromosomes 10 and X. Supporting a cross-regulation of SMN1/2 transcripts, C2A-2B-3-4 and L2A-2B-3-4 upregulated and downregulated SMN1/2 mRNAs, respectively. Proteome analysis revealed 61 upregulated and 57 downregulated proteins by C2A-2B-3-4 with very limited overlap with those affected by L2A-2B-3-4. Independent validations confirmed the effect of C2A-2B-3-4 on expression of genes associated with chromatin remodeling, transcription, spliceosome function, ribosome biogenesis, lipid metabolism, cytoskeletal formation, cell proliferation and neuromuscular junction formation. Our findings reveal a broad role of C2A-2B-3-4, and expands our understanding of functions of SMN1/2 genes.

Transcriptome- and proteome-wide effects of a circular RNA encompassing four early exons of the spinal muscular atrophy genes

Spinal muscular atrophy (SMA) genes, SMN1 and SMN2, produce multiple circular RNAs (circRNAs), including C2A-2B-3-4 that encompasses early exons 2A, 2B, 3 and 4. Here we report the transcriptome- and proteome-wide effects of overexpression of C2A-2B-3-4 in inducible HEK293 cells. Our RNA-Seq analysis revealed altered expression of ~ 15% genes (4,172 genes) by C2A-2B-3-4. About half of the affected genes by C2A-2B-3-4 remained unaffected by L2A-2B-3-4, a linear transcript encompassing exons 2A, 2B, 3 and 4 of SMN1/SMN2. These fifindings underscore the unique role of the structural context of C2A-2B-3-4 in gene regulation. A surprisingly high number of upregulated genes by C2A-2B-3-4 were located on chromosomes 4 and 7, whereas many of the downregulated genes were located on chromosomes 10 and X. Supporting a cross-regulation of SMN1/SMN2 transcripts, C2A-2B-3-4 and L2A-2B-3-4 upregulated and downregulated SMN1/SMN2 mRNAs, respectively. Proteome analysis revealed 61 upregulated and 57 downregulated proteins by C2A-2B-3-4 with very limited overlap with those affected by L2A-2B-3-4. Independent validations confirmed the effect of C2A-2B-3-4 on expression of genes associated with chromatin remodeling, transcription, spliceosome function, ribosome biogenesis, lipid metabolism, cytoskeletal formation, cell proliferation and neuromuscular junction formation. Our findings reveal a broad role of C2A-2B-3-4, a universally expressed circRNA produced by SMN1/SMN2.

Exploring the interplay between PARP1 and circRNA biogenesis and function

PARP1 (poly-ADP-ribose polymerase 1) is a multidomain protein with a flexible and self-folding structure that allows it to interact with a wide range of biomolecules, including nucleic acids and target proteins. PARP1 interacts with its target molecules either covalently via PARylation or non-covalently through its PAR moieties induced by auto-PARylation. These diverse interactions allow PARP1 to participate in complex regulatory circuits and cellular functions. Although the most studied PARP1-mediated functions are associated with DNA repair and cellular stress response, subsequent discoveries have revealed additional biological functions. Based on these findings, PARP1 is now recognized as a major modulator of gene expression. Several discoveries show that this multifunctional protein has been intimately connected to several steps of mRNA biogenesis, from transcription initiation to mRNA splicing, polyadenylation, export, and translation of mRNA to proteins. Nevertheless, our understanding of PARP1's involvement in the biogenesis of both coding and noncoding RNA, notably circular RNA (circRNA), remains restricted. In this review, we outline the possible roles of PARP1 in circRNA biogenesis. A full examination of the regulatory roles of PARP1 in nuclear processes with an emphasis on circRNA may reveal new avenues to control dysregulation implicated in the pathogenesis of several diseases such as neurodegenerative disorders and cancers. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Processing > Splicing Regulation/Alternative Splicing.

Presenilin-1-Derived Circular RNAs: Neglected Epigenetic Regulators with Various Functions in Alzheimer's Disease

The presenilin-1 (PSEN1) gene is crucial in developing Alzheimer's disease (AD), a progressive neurodegenerative disorder and the most common cause of dementia. Circular RNAs (circRNAs) are non-coding RNA generated through back-splicing, resulting in a covalently closed circular molecule. This study aimed to investigate PSEN1-gene-derived circular RNAs (circPSEN1s) and their potential functions in AD. Our in silico analysis indicated that circPSEN1s (hsa_circ_0008521 and chr14:73614502-73614802) act as sponge molecules for eight specific microRNAs. Surprisingly, two of these miRNAs (has-mir-4668-5p and has-mir-5584-5p) exclusively interact with circPSEN1s rather than mRNA-PSEN1. Furthermore, the analysis of pathways revealed that these two miRNAs predominantly target mRNAs associated with the PI3K-Akt signaling pathway. With sponging these microRNAs, circPSEN1s were found to protect mRNAs commonly targeted by these miRNAs, including QSER1, BACE2, RNF157, PTMA, and GJD3. Furthermore, the miRNAs sequestered by circPSEN1s have a notable preference for targeting the TGF-β and Hippo signaling pathways. We also demonstrated that circPSEN1s potentially interact with FOXA1, ESR1, HNF1B, BRD4, GATA4, EP300, CBX3, PRDM9, and PPARG proteins. These proteins have a prominent preference for targeting the TGF-β and Notch signaling pathways, where EP300 and FOXA1 have the highest number of protein interactions. Molecular docking analysis also confirms the interaction of these hub proteins and Aβ42 with circPSEN1s. Interestingly, circPSEN1s-targeted molecules (miRNAs and proteins) impacted TGF-β, which served as a shared signaling pathway. Finally, the analysis of microarray data unveiled distinct expression patterns of genes influenced by circPSEN1s (WTIP, TGIF, SMAD4, PPP1CB, and BMPR1A) in the brains of AD patients. In summary, our findings suggested that the interaction of circPSEN1s with microRNAs and proteins could affect the fate of specific mRNAs, interrupt the function of unique proteins, and influence cell signaling pathways, generally TGF-β. Further research is necessary to validate these findings and gain a deeper understanding of the precise mechanisms and significance of circPSEN1s in the context of AD.

Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

BACKGROUND

Circular RNA (circRNA) molecules, generated through non-canonical back-splicing of exon-exon junctions, have recently been implicated in diverse biological functions including transcriptional regulation and modulation of protein interactions. CircRNAs are emerging as a key component of the complex neural transcriptome implicated in brain development. However, the specific expression patterns and functions of circRNAs in human neuronal differentiation have not been explored.

RESULTS

Using total RNA sequencing analysis, we identified expressed circRNAs during the differentiation of human neuroepithelial stem (NES) cells into developing neurons and discovered that many circRNAs originated from host genes associated with synaptic function. Interestingly, when assessing population data, exons giving rise to circRNAs in our dataset had a higher frequency of genetic variants. Additionally, screening for RNA-binding protein sites identified enrichment of Splicing Factor Proline and Glutamine Rich (SFPQ) motifs in increased circRNAs, several of which were reduced by SFPQ knockdown and enriched in SFPQ ribonucleoprotein complexes.

CONCLUSIONS

Our study provides an in-depth characterisation of circRNAs in a human neuronal differentiation model and highlights SFPQ as both a regulator and binding partner of circRNAs elevated during neuronal maturation.

Computational approaches for circRNAs prediction and in silico characterization

Circular RNAs (circRNAs) are single-stranded and covalently closed non-coding RNA molecules originated from RNA splicing. Their functions include regulatory potential over other RNA species, such as microRNAs, messenger RNAs and RNA binding proteins. For circRNA identification, several algorithms are available and can be classified in two major types: pseudo-reference-based and split-alignment-based approaches. In general, the data generated from circRNA transcriptome initiatives is deposited on public specific databases, which provide a large amount of information on different species and functional annotations. In this review, we describe the main computational resources for the identification and characterization of circRNAs, covering the algorithms and predictive tools to evaluate its potential role in a particular transcriptomics project, including the public repositories containing relevant data and information for circRNAs, recapitulating their characteristics, reliability and amount of data reported.

Regulation of pre-mRNA splicing: roles in physiology and disease, and therapeutic prospects

The removal of introns from mRNA precursors and its regulation by alternative splicing are key for eukaryotic gene expression and cellular function, as evidenced by the numerous pathologies induced or modified by splicing alterations. Major recent advances have been made in understanding the structures and functions of the splicing machinery, in the description and classification of physiological and pathological isoforms and in the development of the first therapies for genetic diseases based on modulation of splicing. Here, we review this progress and discuss important remaining challenges, including predicting splice sites from genomic sequences, understanding the variety of molecular mechanisms and logic of splicing regulation, and harnessing this knowledge for probing gene function and disease aetiology and for the design of novel therapeutic approaches.

High-throughput analysis of ANRIL circRNA isoforms in human pancreatic islets

The antisense non-coding RNA in the INK locus (ANRIL) is a hotspot for genetic variants associated with cardiometabolic disease. We recently found increased ANRIL abundance in human pancreatic islets from donors with certain Type II Diabetes (T2D) risk-SNPs, including a T2D risk-SNP located within ANRIL exon 2 associated with beta cell proliferation. Recent studies have found that expression of circular species of ANRIL is linked to the regulation of cardiovascular phenotypes. Less is known about how the abundance of circular ANRIL may influence T2D phenotypes. Herein, we sequence circular RNA in pancreatic islets to characterize circular isoforms of ANRIL. We identify several consistently expressed circular ANRIL isoforms whose expression is correlated across dozens of individuals and characterize ANRIL splice sites that are commonly involved in back-splicing. We find that samples with the T2D risk allele in ANRIL exon 2 had higher ratios of circular to linear ANRIL compared to protective-allele carriers, and that higher circular:linear ANRIL was associated with decreased beta cell proliferation. Our study points to a combined involvement of both linear and circular ANRIL species in T2D phenotypes and opens the door for future studies of the molecular mechanisms by which ANRIL impacts cellular function in pancreatic islets.

Context-specific effects of sequence elements on subcellular localization of linear and circular RNAs

Long RNAs vary extensively in their post-transcriptional fates, and this variation is attributed in part to short sequence elements. We used massively parallel RNA assays to study how sequences derived from noncoding RNAs influence the subcellular localization and stability of circular and linear RNAs, including spliced and unspliced forms. We find that the effects of sequence elements strongly depend on the host RNA context, with limited overlap between sequences that drive nuclear enrichment of linear and circular RNAs. Binding of specific RNA binding proteins underpins some of these differences-SRSF1 binding leads to nuclear enrichment of circular RNAs; SAFB binding is associated with nuclear enrichment of predominantly unspliced linear RNAs; and IGF2BP1 promotes export of linear spliced RNA molecules. The post-transcriptional fate of long RNAs is thus dictated by combinatorial contributions of specific sequence elements, of splicing, and of the presence of the terminal features unique to linear RNAs.

Circular RNA Profiles in Viremia and ART Suppression Predict Competing circRNA–miRNA–mRNA Networks Exclusive to HIV-1 Viremic Patients

Since the onset of the HIV-1/AIDS epidemic in 1981, 75 million people have been infected with the virus, and the disease remains a public health crisis worldwide. Circular RNAs (circRNAs) are derived from excised exons and introns during backsplicing, a form of alternative splicing. The relevance of unconventional, non-capped, and non-poly(A) transcripts to transcriptomics studies remains to be routinely investigated. Knowledge gaps to be filled are the interface between host-encoded circRNAs and viral replication in chronically progressed patients and upon treatment with antiviral drugs. We implemented a bioinformatic pipeline and repurpose publicly archived RNA sequence reads from the blood of 19 HIV-1-positive patients that previously compared transcriptomes during viremia and viremia suppression by antiretroviral therapy (ART). The in silico analysis identified viremic patients’ circRNA that became undetectable after ART. The circRNAs originated from a subset of host genes enriched in the HDAC biological pathway. These circRNAs and parental mRNAs held in common a small collection of miRNA response elements (MREs), some of which were present in HIV-1 mRNAs. The function of the MRE-containing target mRNA enriched the RNA polymerase II GO pathway. To visualize the interplay between individual circRNA–miRNA–target mRNA, important for HIV-1 and potentially other diseases, an Interactive Circos tool was developed to efficiently parse the intricately competing endogenous network of circRNA–miRNA–mRNA interactions originating from seven circRNA singled out in viremic versus non-viremic patients. The combined downregulation of the identified circRNAs warrants investigation as a novel antiviral targeting strategy.

Bioinformatics and Machine Learning Approaches to Understand the Regulation of Mobile Genetic Elements

Simple Summary

Transposable elements (TEs) are DNA sequences that are, or were, able to move (transpose) within the genome of a single cell. They were first discovered by Barbara McClintock while working on maize, and they make up a large fraction of the genome. Transpositions can result in mutations and they can alter the genome size. Cells regulate the activity of TEs using a variety of mechanisms, such as chemical modifications of DNA and small RNAs. Machine learning (ML) is an interdisciplinary subject that studies computer algorithms that can improve through experience and by the use of data. ML has been successfully applied to a variety of problems in bioinformatics and has exhibited favorable precision and speed. Here, we provide a systematic and guided review on the ML and bioinformatic methods and tools that are used for the analysis of the regulation of TEs.

Abstract

Transposable elements (TEs, or mobile genetic elements, MGEs) are ubiquitous genetic elements that make up a substantial proportion of the genome of many species. The recent growing interest in understanding the evolution and function of TEs has revealed that TEs play a dual role in genome evolution, development, disease, and drug resistance. Cells regulate TE expression against uncontrolled activity that can lead to developmental defects and disease, using multiple strategies, such as DNA chemical modification, small RNA (sRNA) silencing, chromatin modification, as well as sequence-specific repressors. Advancements in bioinformatics and machine learning approaches are increasingly contributing to the analysis of the regulation mechanisms. A plethora of tools and machine learning approaches have been developed for prediction, annotation, and expression profiling of sRNAs, for methylation analysis of TEs, as well as for genome-wide methylation analysis through bisulfite sequencing data. In this review, we provide a guided overview of the bioinformatic and machine learning state of the art of fields closely associated with TE regulation and function.