Intron Retained, Transcript Detained: Intron Retention as a Hallmark of the Quiescent Satellite Cell State

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.

The SpliZ generalizes 'percent spliced in' to reveal regulated splicing at single-cell resolution

Detecting single-cell-regulated splicing from droplet-based technologies is challenging. Here, we introduce the splicing Z score (SpliZ), an annotation-free statistical method to detect regulated splicing in single-cell RNA sequencing. We applied the SpliZ to human lung cells, discovering hundreds of genes with cell-type-specific splicing patterns including ones with potential implications for basic and translational biology.