Widespread RNA hypoediting in schizophrenia and its relevance to mitochondrial function

Temporal landscape and translational regulation of A-to-I RNA editing in mouse retina development

BACKGROUND

The significance of A-to-I RNA editing in nervous system development is widely recognized; however, its influence on retina development remains to be thoroughly understood.

RESULTS

In this study, we performed RNA sequencing and ribosome profiling experiments on developing mouse retinas to characterize the temporal landscape of A-to-I editing. Our findings revealed temporal changes in A-to-I editing, with distinct editing patterns observed across different developmental stages. Further analysis showed the interplay between A-to-I editing and alternative splicing, with A-to-I editing influencing splicing efficiency and the quantity of splicing events. A-to-I editing held the potential to enhance translation diversity, but this came at the expense of reduced translational efficiency. When coupled with splicing, it could produce a coordinated effect on gene translation.

CONCLUSIONS

Overall, this study presents a temporally resolved atlas of A-to-I editing, connecting its changes with the impact on alternative splicing and gene translation in retina development.

Advances in brain epitranscriptomics research and translational opportunities

Various chemical modifications of all RNA transcripts, or epitranscriptomics, have emerged as crucial regulators of RNA metabolism, attracting significant interest from both basic and clinical researchers due to their diverse functions in biological processes and immense clinical potential as highlighted by the recent profound success of RNA modifications in improving COVID-19 mRNA vaccines. Rapid accumulation of evidence underscores the critical involvement of various RNA modifications in governing normal neural development and brain functions as well as pathogenesis of brain disorders. Here we provide an overview of RNA modifications and recent advancements in epitranscriptomic studies utilizing animal models to elucidate important roles of RNA modifications in regulating mammalian neurogenesis, gliogenesis, synaptic formation, and brain function. Moreover, we emphasize the pivotal involvement of RNA modifications and their regulators in the pathogenesis of various human brain disorders, encompassing neurodevelopmental disorders, brain tumors, psychiatric and neurodegenerative disorders. Furthermore, we discuss potential translational opportunities afforded by RNA modifications in combatting brain disorders, including their use as biomarkers, in the development of drugs or gene therapies targeting epitranscriptomic pathways, and in applications for mRNA-based vaccines and therapies. We also address current limitations and challenges hindering the widespread clinical application of epitranscriptomic research, along with the improvements necessary for future progress.

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.

Alterations in RNA editing in skeletal muscle following exercise training in individuals with Parkinson's disease

Parkinson's Disease (PD) is the second most common neurodegenerative disease behind Alzheimer's Disease, currently affecting more than 10 million people worldwide and 1.5 times more males than females. The progression of PD results in the loss of function due to neurodegeneration and neuroinflammation. The etiology of PD is multifactorial, including both genetic and environmental origins. Here we explored changes in RNA editing, specifically editing through the actions of the Adenosine Deaminases Acting on RNA (ADARs), in the progression of PD. Analysis of ADAR editing of skeletal muscle transcriptomes from PD patients and controls, including those that engaged in a rehabilitative exercise training program revealed significant differences in ADAR editing patterns based on age, disease status, and following rehabilitative exercise. Further, deleterious editing events in protein coding regions were identified in multiple genes with known associations to PD pathogenesis. Our findings of differential ADAR editing complement findings of changes in transcriptional networks identified by a recent study and offer insights into dynamic ADAR editing changes associated with PD pathogenesis.

dsRID: in silico identification of dsRNA regions using long-read RNA-seq data

MOTIVATION

Double-stranded RNAs (dsRNAs) are potent triggers of innate immune responses upon recognition by cytosolic dsRNA sensor proteins. Identification of endogenous dsRNAs helps to better understand the dsRNAome and its relevance to innate immunity related to human diseases.

RESULTS

Here, we report dsRID (double-stranded RNA identifier), a machine-learning-based method to predict dsRNA regions in silico, leveraging the power of long-read RNA-sequencing (RNA-seq) and molecular traits of dsRNAs. Using models trained with PacBio long-read RNA-seq data derived from Alzheimer's disease (AD) brain, we show that our approach is highly accurate in predicting dsRNA regions in multiple datasets. Applied to an AD cohort sequenced by the ENCODE consortium, we characterize the global dsRNA profile with potentially distinct expression patterns between AD and controls. Together, we show that dsRID provides an effective approach to capture global dsRNA profiles using long-read RNA-seq data.

AVAILABILITY AND IMPLEMENTATION

Software implementation of dsRID, and genomic coordinates of regions predicted by dsRID in all samples are available at the GitHub repository: https://github.com/gxiaolab/dsRID.

dsRID: Editing-free in silico identification of dsRNA region using long-read RNA-seq data

Double-stranded RNAs (dsRNAs) are potent triggers of innate immune responses upon recognition by cytosolic dsRNA sensor proteins. Identification of endogenous dsRNAs helps to better understand the dsRNAome and its relevance to innate immunity related to human diseases. Here, we report dsRID (double-stranded RNA identifier), a machine learning-based method to predict dsRNA regions in silico, leveraging the power of long-read RNA-sequencing (RNA-seq) and molecular traits of dsRNAs. Using models trained with PacBio long-read RNA-seq data derived from Alzheimer's disease (AD) brain, we show that our approach is highly accurate in predicting dsRNA regions in multiple datasets. Applied to an AD cohort sequenced by the ENCODE consortium, we characterize the global dsRNA profile with potentially distinct expression patterns between AD and controls. Together, we show that dsRID provides an effective approach to capture global dsRNA profiles using long-read RNA-seq data.