Cardiac splicing as a diagnostic and therapeutic target

Characterised intron retention profiles in muscle tissue of idiopathic inflammatory myopathy subtypes

OBJECTIVES

Idiopathic inflammatory myopathies (IIMs) are a group of heterogeneous autoimmune diseases. Intron retention (IR) serves as an important post-transcriptional and translational regulatory mechanism. This study aims to identify changes in IR profiles in IIM subtypes, investigating their influence on proteins and their correlations with clinical features.

METHODS

RNA sequencing and liquid chromatography-tandem mass spectrometry were performed on muscle tissues obtained from 174 patients with IIM and 19 controls, following QC procedures. GTFtools and iREAD software were used for IR identification. An analysis of differentially expressed IRs (DEIs), exons and proteins was carried out using edgeR or DEP. Functional analysis was performed with clusterProfiler, and SPIRON was used to assess splicing factors.

RESULTS

A total of 6783 IRs located in 3111 unique genes were identified in all IIM subtypes compared with controls. IIM subtype-specific DEIs were associated with the pathogenesis of respective IIM subtypes. Splicing factors YBX1 and HSPA2 exhibited the most changes in dermatomyositis and immune-mediated necrotising myopathy. Increased IR was associated with reduced protein expression. Some of the IIM-specific DEIs were correlated with clinical parameters (skin rash, MMT-8 scores and muscle enzymes) and muscle histopathological features (myofiber necrosis, regeneration and inflammation). IRs in IFIH1 and TRIM21 were strongly correlated with anti-MDA5+ antibody, while IRs in SRP14 were associated with anti-SRP+ antibody.

CONCLUSION

This study revealed distinct IRs and specific splicing factors associated with IIM subtypes, which might be contributing to the pathogenesis of IIM. We also emphasised the potential impact of IR on protein expression in IIM muscles.

RNA-binding proteins in cardiovascular biology and disease: the beat goes on

Cardiac development and function are becoming increasingly well understood from different angles, including signalling, transcriptional and epigenetic mechanisms. By contrast, the importance of the post-transcriptional landscape of cardiac biology largely remains to be uncovered, building on the foundation of a few existing paradigms. The discovery during the past decade of hundreds of additional RNA-binding proteins in mammalian cells and organs, including the heart, is expected to accelerate progress and has raised intriguing possibilities for better understanding the intricacies of cardiac development, metabolism and adaptive alterations. In this Review, we discuss the progress and new concepts on RNA-binding proteins and RNA biology and appraise them in the context of common cardiovascular clinical conditions, from cell and organ-wide perspectives. We also discuss how a better understanding of cardiac RNA-binding proteins can fill crucial knowledge gaps in cardiology and might pave the way to developing better treatments to reduce cardiovascular morbidity and mortality.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.