DeepEdit: single-molecule detection and phasing of A-to-I RNA editing events using nanopore direct RNA sequencing

Understanding the molecular mechanisms of human diseases: the benefits of fission yeasts

The role of model organisms such as yeasts in life science research is crucial. Although the baker's yeast (Saccharomyces cerevisiae) is the most popular model among yeasts, the contribution of the fission yeasts (Schizosaccharomyces) to life science is also indisputable. Since both types of yeasts share several thousands of common orthologous genes with humans, they provide a simple research platform to investigate many fundamental molecular mechanisms and functions, thereby contributing to the understanding of the background of human diseases. In this review, we would like to highlight the many advantages of fission yeasts over budding yeasts. The usefulness of fission yeasts in virus research is shown as an example, presenting the most important research results related to the Human Immunodeficiency Virus Type 1 (HIV-1) Vpr protein. Besides, the potential role of fission yeasts in the study of prion biology is also discussed. Furthermore, we are keen to promote the uprising model yeast Schizosaccharomyces japonicus, which is a dimorphic species in the fission yeast genus. We propose the hyphal growth of S. japonicus as an unusual opportunity as a model to study the invadopodia of human cancer cells since the two seemingly different cell types can be compared along fundamental features. Here we also collect the latest laboratory protocols and bioinformatics tools for the fission yeasts to highlight the many possibilities available to the research community. In addition, we present several limiting factors that everyone should be aware of when working with yeast models.

Bioinformatics for Inosine: Tools and Approaches to Trace This Elusive RNA Modification

Inosine is a nucleotide resulting from the deamination of adenosine in RNA. This chemical modification process, known as RNA editing, is typically mediated by a family of double-stranded RNA binding proteins named Adenosine Deaminase Acting on dsRNA (ADAR). While the presence of ADAR orthologs has been traced throughout the evolution of metazoans, the existence and extension of RNA editing have been characterized in a more limited number of animals so far. Undoubtedly, ADAR-mediated RNA editing plays a vital role in physiology, organismal development and disease, making the understanding of the evolutionary conservation of this phenomenon pivotal to a deep characterization of relevant biological processes. However, the lack of direct high-throughput methods to reveal RNA modifications at single nucleotide resolution limited an extended investigation of RNA editing. Nowadays, these methods have been developed, and appropriate bioinformatic pipelines are required to fully exploit this data, which can complement existing approaches to detect ADAR editing. Here, we review the current literature on the "bioinformatics for inosine" subject and we discuss future research avenues in the field.

Revealing Differential RNA Editing Specificity of Human ADAR1 and ADAR2 in Schizosaccharomyces pombe

Adenosine-to-inosine (A-to-I) RNA editing is an important post-transcriptional modification mediated by the adenosine deaminases acting on RNA (ADAR) family of enzymes, expanding the transcriptome by altering selected nucleotides A to I in RNA molecules. Recently, A-to-I editing has been explored for correcting disease-causing mutations in RNA using therapeutic guide oligonucleotides to direct ADAR editing at specific sites. Humans have two active ADARs whose preferences and specificities are not well understood. To investigate their substrate specificity, we introduced hADAR1 and hADAR2, respectively, into Schizosaccharomyces pombe (S. pombe), which lacks endogenous ADARs, and evaluated their editing activities in vivo. Using transcriptome sequencing of S. pombe cultured at optimal growth temperature (30 °C), we identified 483 A-to-I high-confident editing sites for hADAR1 and 404 for hADAR2, compared with the non-editing wild-type control strain. However, these sites were mostly divergent between hADAR1 and hADAR2-expressing strains, sharing 33 common sites that are less than 9% for each strain. Their differential specificity for substrates was attributed to their differential preference for neighboring sequences of editing sites. We found that at the -3-position relative to the editing site, hADAR1 exhibits a tendency toward T, whereas hADAR2 leans toward A. Additionally, when varying the growth temperature for hADAR1- and hADAR2-expressing strains, we observed increased editing sites for them at both 20 and 35 °C, compared with them growing at 30 °C. However, we did not observe a significant shift in hADAR1 and hADAR2's preference for neighboring sequences across three temperatures. The vast changes in RNA editing sites at lower and higher temperatures were also observed for hADAR2 previously in budding yeast, which was likely due to the influence of RNA folding at these different temperatures, among many other factors. We noticed examples of longer lengths of dsRNA around the editing sites that induced editing at 20 or 35 °C but were absent at the other two temperature conditions. We found genes' functions can be greatly affected by editing of their transcripts, for which over 50% of RNA editing sites for both hADAR1 and hADAR2 in S. pombe were in coding sequences (CDS), with more than 60% of them resulting in amino acid changes in protein products. This study revealed the extensive differences in substrate selectivity between the two active human ADARS, i.e., ADAR1 and ADAR2, and provided novel insight when utilizing the two different enzymes for in vivo treatment of human genetic diseases using the RNA editing approach.

Detecting haplotype-specific transcript variation in long reads with FLAIR2

BACKGROUND

RNA-seq has brought forth significant discoveries regarding aberrations in RNA processing, implicating these RNA variants in a variety of diseases. Aberrant splicing and single nucleotide variants (SNVs) in RNA have been demonstrated to alter transcript stability, localization, and function. In particular, the upregulation of ADAR, an enzyme that mediates adenosine-to-inosine editing, has been previously linked to an increase in the invasiveness of lung adenocarcinoma cells and associated with splicing regulation. Despite the functional importance of studying splicing and SNVs, the use of short-read RNA-seq has limited the community's ability to interrogate both forms of RNA variation simultaneously.

RESULTS

We employ long-read sequencing technology to obtain full-length transcript sequences, elucidating cis-effects of variants on splicing changes at a single molecule level. We develop a computational workflow that augments FLAIR, a tool that calls isoform models expressed in long-read data, to integrate RNA variant calls with the associated isoforms that bear them. We generate nanopore data with high sequence accuracy from H1975 lung adenocarcinoma cells with and without knockdown of ADAR. We apply our workflow to identify key inosine isoform associations to help clarify the prominence of ADAR in tumorigenesis.

CONCLUSIONS

Ultimately, we find that a long-read approach provides valuable insight toward characterizing the relationship between RNA variants and splicing patterns.

Exploring functional conservation in silico: a new machine learning approach to RNA-editing

Around 50 years ago, molecular biology opened the path to understand changes in forms, adaptations, complexity, or the basis of human diseases through myriads of reports on gene birth, gene duplication, gene expression regulation, and splicing regulation, among other relevant mechanisms behind gene function. Here, with the advent of big data and artificial intelligence (AI), we focus on an elusive and intriguing mechanism of gene function regulation, RNA editing, in which a single nucleotide from an RNA molecule is changed, with a remarkable impact in the increase of the complexity of the transcriptome and proteome. We present a new generation approach to assess the functional conservation of the RNA-editing targeting mechanism using two AI learning algorithms, random forest (RF) and bidirectional long short-term memory (biLSTM) neural networks with an attention layer. These algorithms, combined with RNA-editing data coming from databases and variant calling from same-individual RNA and DNA-seq experiments from different species, allowed us to predict RNA-editing events using both primary sequence and secondary structure. Then, we devised a method for assessing conservation or divergence in the molecular mechanisms of editing completely in silico: the cross-testing analysis. This novel method not only helps to understand the conservation of the editing mechanism through evolution but could set the basis for achieving a better understanding of the adenosine-targeting mechanism in other fields.

Navigating the landscape of epitranscriptomics and host immunity

RNA modifications, also termed epitranscriptomic marks, encompass chemical alterations to individual nucleotides, including processes such as methylation and editing. These marks contribute to a wide range of biological processes, many of which are related to host immune system defense. The functions of immune-related RNA modifications can be categorized into three main groups: regulation of immunogenic RNAs, control of genes involved in innate immune response, and facilitation of adaptive immunity. Here, we provide an overview of recent research findings that elucidate the contributions of RNA modifications to each of these processes. We also discuss relevant methods for genome-wide identification of RNA modifications and their immunogenic substrates. Finally, we highlight recent advances in cancer immunotherapies that aim to reduce cancer cell viability by targeting the enzymes responsible for RNA modifications. Our presentation of these dynamic research avenues sets the stage for future investigations in this field.

Transfer learning enables identification of multiple types of RNA modifications using nanopore direct RNA sequencing

Nanopore direct RNA sequencing (DRS) has emerged as a powerful tool for RNA modification identification. However, concurrently detecting multiple types of modifications in a single DRS sample remains a challenge. Here, we develop TandemMod, a transferable deep learning framework capable of detecting multiple types of RNA modifications in single DRS data. To train high-performance TandemMod models, we generate in vitro epitranscriptome datasets from cDNA libraries, containing thousands of transcripts labeled with various types of RNA modifications. We validate the performance of TandemMod on both in vitro transcripts and in vivo human cell lines, confirming its high accuracy for profiling m6A and m5C modification sites. Furthermore, we perform transfer learning for identifying other modifications such as m7G, Ψ, and inosine, significantly reducing training data size and running time without compromising performance. Finally, we apply TandemMod to identify 3 types of RNA modifications in rice grown in different environments, demonstrating its applicability across species and conditions. In summary, we provide a resource with ground-truth labels that can serve as benchmark datasets for nanopore-based modification identification methods, and TandemMod for identifying diverse RNA modifications using a single DRS sample.

RNA editing enzymes: structure, biological functions and applications

With the advancement of sequencing technologies and bioinformatics, over than 170 different RNA modifications have been identified. However, only a few of these modifications can lead to base pair changes, which are called RNA editing. RNA editing is a ubiquitous modification in mammalian transcriptomes and is an important co/posttranscriptional modification that plays a crucial role in various cellular processes. There are two main types of RNA editing events: adenosine to inosine (A-to-I) editing, catalyzed by ADARs on double-stranded RNA or ADATs on tRNA, and cytosine to uridine (C-to-U) editing catalyzed by APOBECs. This article provides an overview of the structure, function, and applications of RNA editing enzymes. We discuss the structural characteristics of three RNA editing enzyme families and their catalytic mechanisms in RNA editing. We also explain the biological role of RNA editing, particularly in innate immunity, cancer biogenesis, and antiviral activity. Additionally, this article describes RNA editing tools for manipulating RNA to correct disease-causing mutations, as well as the potential applications of RNA editing enzymes in the field of biotechnology and therapy.

Recommendations for detection, validation, and evaluation of RNA editing events in cardiovascular and neurological/neurodegenerative diseases

RNA editing, a common and potentially highly functional form of RNA modification, encompasses two different RNA modifications, namely adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U) editing. As inosines are interpreted as guanosines by the cellular machinery, both A-to-I and C-to-U editing change the nucleotide sequence of the RNA. Editing events in coding sequences have the potential to change the amino acid sequence of proteins, whereas editing events in noncoding RNAs can, for example, affect microRNA target binding. With advancing RNA sequencing technology, more RNA editing events are being discovered, studied, and reported. However, RNA editing events are still often overlooked or discarded as sequence read quality defects. With this position paper, we aim to provide guidelines and recommendations for the detection, validation, and follow-up experiments to study RNA editing, taking examples from the fields of cardiovascular and brain disease. We discuss all steps, from sample collection, storage, and preparation, to different strategies for RNA sequencing and editing-sensitive data analysis strategies, to validation and follow-up experiments, as well as potential pitfalls and gaps in the available technologies. This paper may be used as an experimental guideline for RNA editing studies in any disease context.

The role of ADAR1 through and beyond its editing activity in cancer

Adenosine-to-inosine (A-to-I) editing of RNA, catalyzed by adenosine deaminase acting on RNA (ADAR) enzymes, is a prevalent RNA modification in mammals. It has been shown that A-to-I editing plays a critical role in multiple diseases, such as cardiovascular disease, neurological disorder, and particularly cancer. ADARs are the family of enzymes, including ADAR1, ADAR2, and ADAR3, that catalyze the occurrence of A-to-I editing. Notably, A-to-I editing is mainly catalyzed by ADAR1. Given the significance of A-to-I editing in disease development, it is important to unravel the complex roles of ADAR1 in cancer for the development of novel therapeutic interventions.In this review, we briefly describe the progress of research on A-to-I editing and ADARs in cancer, mainly focusing on the role of ADAR1 in cancer from both editing-dependent and independent perspectives. In addition, we also summarized the factors affecting the expression and editing activity of ADAR1 in cancer.

Harnessing ADAR-Mediated Site-Specific RNA Editing in Immune-Related Disease: Prediction and Therapeutic Implications

ADAR (Adenosine Deaminases Acting on RNA) proteins are a group of enzymes that play a vital role in RNA editing by converting adenosine to inosine in RNAs. This process is a frequent post-transcriptional event observed in metazoan transcripts. Recent studies indicate widespread dysregulation of ADAR-mediated RNA editing across many immune-related diseases, such as human cancer. We comprehensively review ADARs' function as pattern recognizers and their capability to contribute to mediating immune-related pathways. We also highlight the potential role of site-specific RNA editing in maintaining homeostasis and its relationship to various diseases, such as human cancers. More importantly, we summarize the latest cutting-edge computational approaches and data resources for predicting and analyzing RNA editing sites. Lastly, we cover the recent advancement in site-directed ADAR editing tool development. This review presents an up-to-date overview of ADAR-mediated RNA editing, how site-specific RNA editing could potentially impact disease pathology, and how they could be harnessed for therapeutic applications.

Multiomics tools for improved atherosclerotic cardiovascular disease management

Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple 'omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.

Identification of Bona Fide RNA Editing Sites: History, Challenges, and Opportunities

Adenosine-to-inosine (A-to-I) RNA editing, catalyzed by the adenosine deaminase acting on the RNA (ADAR) family of enzymes of which there are three members (ADAR1, ADAR2, and ADAR3), is a major gene regulatory mechanism that diversifies the transcriptome. It is widespread in many metazoans, including humans. As inosine is interpreted by cellular machineries mainly as guanosine, A-to-I editing effectively gives A-to-G nucleotide changes. Depending on its location, an editing event can generate new protein isoforms or influence other RNA processing pathways. Researchers have found that ADAR-mediated editing performs diverse functions. For example, it enables living organisms such as cephalopods to adapt rapidly to fluctuating environmental conditions such as water temperature. In development, the loss of ADAR1 is embryonically lethal partly because endogenous double-stranded RNAs (dsRNAs) are no longer marked by inosines, which signal "self", and thus cause the melanoma differentiation-associated protein 5 (MDA5) sensor to trigger a deleterious interferon response. Hence, ADAR1 plays a key role in preventing aberrant activation of the innate immune system. Furthermore, ADAR enzymes have been implicated in myriad human diseases. Intriguingly, some cancer cells are known to exploit ADAR1 activity to dodge immune responses. However, the exact identities of immunogenic RNAs in different biological contexts have remained elusive. Consequently, there is tremendous interest in identifying inosine-containing RNAs in the cell.The identification of A-to-I RNA editing sites is dependent on the sequencing of nucleic acids. Technological and algorithmic advancements over the past decades have revolutionized the way editing events are detected. At the beginning, the discovery of editing sites relies on Sanger sequencing, a first-generation technology. Both RNA, which is reverse transcribed into complementary DNA (cDNA), and genomic DNA (gDNA) from the same source are analyzed. After sequence alignment, one would require an adenosine to be present in the genome but a guanosine to be detected in the RNA sample for a position to be declared as an editing site. However, an issue with Sanger sequencing is its low throughput. Subsequently, Illumina sequencing, a second-generation technology, was invented. By permitting the simultaneous interrogation of millions of molecules, it enables many editing sites to be identified rapidly. However, a key challenge is that the Illumina platform produces short sequencing reads that can be difficult to map accurately. To tackle the challenge, we and others developed computational workflows with a series of filters to discard sites that are likely to be false positives. When Illumina sequencing data sets are properly analyzed, A-to-G variants should emerge as the most dominant mismatch type. Moreover, the quantitative nature of the data allows us to build a comprehensive atlas of editing-level measurements across different biological contexts, providing deep insights into the spatiotemporal dynamics of RNA editing. However, difficulties remain in identifying true A-to-I editing sites in short protein-coding exons or in organisms and diseases where DNA mutations and genomic polymorphisms are prevalent and mostly unknown. Nanopore sequencing, a third-generation technology, promises to address the difficulties, as it allows native RNAs to be sequenced without conversion to cDNA, preserving base modifications that can be directly detected through machine learning. We recently demonstrated that nanopore sequencing could be used to identify A-to-I editing sites in native RNA directly. Although further work is needed to enhance the detection accuracy in single molecules from fewer cells, the nanopore technology holds the potential to revolutionize epitranscriptomic studies.